{"id":434538,"date":"2018-04-24T22:07:11","date_gmt":"2018-04-24T22:07:11","guid":{"rendered":"https:\/\/essaypaper.org\/assignment-paper-12\/"},"modified":"2018-10-24T09:15:12","modified_gmt":"2018-10-24T09:15:12","slug":"assignment-paper-12","status":"publish","type":"post","link":"https:\/\/www.benedictsol.com\/blogs\/assignment-paper-12\/","title":{"rendered":"Assignment Paper"},"content":{"rendered":"\n

Assessment 1 (Autumn 2018)<\/span><\/strong><\/p>\n

Assessment 1 provides you with six research scenarios, each with associated data and two tasks to complete.  For each scenario you are assuming the role of a researcher employed by an organisation with the purpose of helping them answer a question about their business.<\/span><\/p>\n

Your role is to gather data related to the question, analyse this data, and write a “results section” providing an answer to the question (hence this assessment is a partial<\/em> research report because it only requires an APA-style results section).<\/span><\/p>\n

Each scenario consists of three tasks;<\/span><\/p>\n

TASK 1: Analyse the data provided using the relevant statistical analysis in SPSS, and write a results section using these findings. <\/span><\/strong><\/p>\n

In the results you are expected to;<\/span><\/em><\/p>\n

(a) Provide the hypothesis (include the units of measure for the dependent variable).<\/span><\/p>\n

(b) Describe the overall number of participants, and the means and standard deviations of the age of these participants, grouped by sex.<\/span><\/p>\n

(c) Test parametric assumptions<\/span><\/p>\n

(d) Present the appropriate statistical finding<\/span><\/p>\n

(e) Interpret the statistical findings and include post hoc analyses if necessary <\/span><\/p>\n

(f) Calculate effect sizes where appropriate<\/span><\/p>\n

(g) Include all relevant SPSS outputs in an appendix<\/em> following your results write-up, e.g., a table of means, a table of normality tests, the statistical output table etc.<\/span><\/p>\n

TASK 2: Describe your research findings using a single sentence.<\/span><\/strong><\/p>\n

Based on the statistical analysis you’ve performed, write a clear statement explaining whether the company’s hypothesis was supported or not supported.  If the hypothesis does not involve a specific prediction, d<\/span>escribe the research findings and the conclusion you would provide the company.<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 3:  Identify a design flaw in the scenario.<\/span><\/strong><\/p>\n

Each scenario has a hidden experimental design flaw.  Identify this design flaw and explain how it might affect your statistical finding, leading to an inaccurate<\/u> or invalid<\/u> conclusion.<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

Submission of Assessment 1 is through Turnitin.<\/u>  See vUWS and the Learning Guide for further information. The Turnitin Link will be in your Assessment Folder.<\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TYPE YOUR ANSWERS INTO THIS WORD DOCUMENT (Note: you might need to use more<\/u> space than that which is currently provided under each task e.g., your results section might take up a full page if you include a table).<\/span><\/strong>
<\/span><\/strong><\/p>\n

Scenario 1<\/span><\/strong><\/p>\n

A health-food company is planning to market a new one-month weight-loss “diet-shake” program to the public.  The company executives believe the program will be effective in helping people lose weight, however they require scientific evidence of its success to use in a future advertising campaign.<\/span><\/p>\n

To help them gather this evidence, you randomly recruit a group of 40 volunteer participants from the public who have been identified by medical professionals as clinically “obese” and measure their weight.  You then immediately administer the diet program, which consists of a three “diet-shakes” and three very small meals a day,  and a specialised exercise regime.  Every participant starts on the same day, Monday of Week 1, and ends the program on the same day, Friday of Week 4.  Throughout the month you monitor your participants and are please to find they are all taking the program seriously.<\/span><\/p>\n

At the end of the one-month program you organise for your participants to take a second weight measurement, however many of the participants are taking summer holidays and are not available for you to weigh.  Consequently, you decide to postpone the second weight measurement and wait an additional two months before re-weighing them (so that all 40 can participate).<\/span><\/p>\n

Finally, three months after the beginning of the program you finally get your chance and collect new weight measurements from the 40 participants.   You use the data from these participants to answer the company’s question – did the program result in a significant drop in weight?<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

TASK 1<\/span><\/strong><\/p>\n

Analyse the data and write a results section using APA format.<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 2<\/span><\/strong><\/p>\n

Describe the research findings using a single sentence (i.e., write a clear statement explaining whether the company’s hypothesis was supported or not supported.). <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 3<\/span><\/strong><\/p>\n

There is a hidden design flaw in this scenario.  Identify this flaw and explain how it might affect your statistical finding, hence lead to an inaccurate conclusion.<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/u><\/p>\n

 <\/span><\/span><\/u><\/p>\n

Table 1<\/span><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/p>\n

<\/span><\/strong><\/p>\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Start Weight<\/span><\/p>\n<\/td>\n

\n

End Weight<\/span><\/p>\n<\/td>\n

\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Start Weight<\/span><\/p>\n<\/td>\n

\n

End Weight<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

128<\/span><\/p>\n<\/td>\n

\n

131<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

117<\/span><\/p>\n<\/td>\n

\n

90<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

128<\/span><\/p>\n<\/td>\n

\n

136<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

48<\/span><\/p>\n<\/td>\n

\n

121<\/span><\/p>\n<\/td>\n

\n

112<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

107<\/span><\/p>\n<\/td>\n

\n

130<\/span><\/p>\n<\/td>\n

\n

23<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

138<\/span><\/p>\n<\/td>\n

\n

139<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

101<\/span><\/p>\n<\/td>\n

\n

90<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

48<\/span><\/p>\n<\/td>\n

\n

117<\/span><\/p>\n<\/td>\n

\n

112<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

5<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

23<\/span><\/p>\n<\/td>\n

\n

140<\/span><\/p>\n<\/td>\n

\n

147<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

50<\/span><\/p>\n<\/td>\n

\n

107<\/span><\/p>\n<\/td>\n

\n

92<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

6<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

129<\/span><\/p>\n<\/td>\n

\n

125<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

120<\/span><\/p>\n<\/td>\n

\n

120<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

7<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

132<\/span><\/p>\n<\/td>\n

\n

134<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

120<\/span><\/p>\n<\/td>\n

\n

108<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

56<\/span><\/p>\n<\/td>\n

\n

119<\/span><\/p>\n<\/td>\n

\n

121<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

150<\/span><\/p>\n<\/td>\n

\n

141<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

115<\/span><\/p>\n<\/td>\n

\n

105<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

128<\/span><\/p>\n<\/td>\n

\n

138<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

41<\/span><\/p>\n<\/td>\n

\n

146<\/span><\/p>\n<\/td>\n

\n

139<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

\n

124<\/span><\/p>\n<\/td>\n

\n

120<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

113<\/span><\/p>\n<\/td>\n

\n

114<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

135<\/span><\/p>\n<\/td>\n

\n

125<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

125<\/span><\/p>\n<\/td>\n

\n

104<\/span><\/p>\n<\/td>\n

\n

32<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

139<\/span><\/p>\n<\/td>\n

\n

132<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

13<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

138<\/span><\/p>\n<\/td>\n

\n

137<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

60<\/span><\/p>\n<\/td>\n

\n

143<\/span><\/p>\n<\/td>\n

\n

135<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

125<\/span><\/p>\n<\/td>\n

\n

127<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

127<\/span><\/p>\n<\/td>\n

\n

136<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

123<\/span><\/p>\n<\/td>\n

\n

136<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

54<\/span><\/p>\n<\/td>\n

\n

124<\/span><\/p>\n<\/td>\n

\n

137<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

56<\/span><\/p>\n<\/td>\n

\n

127<\/span><\/p>\n<\/td>\n

\n

133<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

52<\/span><\/p>\n<\/td>\n

\n

129<\/span><\/p>\n<\/td>\n

\n

123<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

128<\/span><\/p>\n<\/td>\n

\n

119<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

141<\/span><\/p>\n<\/td>\n

\n

132<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

118<\/span><\/p>\n<\/td>\n

\n

126<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

110<\/span><\/p>\n<\/td>\n

\n

120<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

19<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

114<\/span><\/p>\n<\/td>\n

\n

119<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

123<\/span><\/p>\n<\/td>\n

\n

119<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

44<\/span><\/p>\n<\/td>\n

\n

133<\/span><\/p>\n<\/td>\n

\n

136<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

117<\/span><\/p>\n<\/td>\n

\n

115<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

“Start weight” = weight of participants immediately before<\/u> the one-month weight-loss program (kg).  “End weight” = weight of participants two months after<\/u> the termination<\/em> of the program (kg). <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Scenario 2<\/span><\/strong><\/p>\n

A large private IT organisation is interesting in determining the intelligence of their 1000 employees, and asks you to compare the IQ (intelligence quotient) of a sample of employees with the population IQ score of 100.  <\/span><\/p>\n

 <\/span><\/p>\n

The company’s management team assumes their employees will be more<\/u> intelligent than the population. <\/span><\/p>\n

 <\/span><\/p>\n

Using the organisation’s email system, you email everyone in the company requesting volunteers to take part in an intelligence study.  In reply you receive expressions of interest from 20 enthusiastic employees.  These 20 employees agree to complete a validated IQ test at the organisation’s head office on a Friday morning.  The data you collect from them is shown in Table 1. <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 1<\/span><\/strong><\/p>\n

Analyse the data and write a results section using APA format.<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 2<\/span><\/strong><\/p>\n

Describe the research findings using a single sentence (i.e., write a clear statement explaining whether the company’s hypothesis was supported or not supported.). <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 3<\/span><\/strong><\/p>\n

There is a hidden design flaw in this scenario.  Identify this flaw and explain how it might affect your statistical finding, hence lead to an inaccurate conclusion.<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

Table 2<\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

IQ<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

\n

120<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

112<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

104<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

109<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

5<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

121<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

6<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

101<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

7<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

112<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

98<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

100<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

92<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

112<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

104<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

13<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

103<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

32<\/span><\/p>\n<\/td>\n

\n

124<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

108<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

118<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

111<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

102<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

19<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

99<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

101<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

“IQ” = validated intelligence quotient score (Unit of measure “Validated test score”)<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Scenario 3<\/span><\/strong><\/p>\n

A large accounting firm wants to know if their proposed “Be Happy at Work” campaign will improve employees’ work satisfaction.  Specifically, at the completion of the campaign, will those employees who were originally the least<\/u> happy show an improved work satisfaction that is now equivalent to the happiest<\/u> employees?<\/span><\/p>\n

Before<\/span><\/em> the firm implements their campaign, you administer a validated survey to measure the “work satisfaction” of each of the 120 employees in the company.  The survey measures employee’s attitudes about their current employment status, and their future in the firm, on a scale from 0-20 where a low score signifies low satisfaction, and a high score signifies high satisfaction. <\/span><\/p>\n

From 120 scores you collect, you select the bottom-scoring 20 employees (indicating very low work satisfaction) and the top-scoring 20 employees (indicating very high work satisfaction).  The bottom-scoring employees provide a mean score of approximately 10 out of 20.  The top-scoring employees provide a mean score of approximately 18 out of 20. <\/span><\/p>\n

The firm then implements the fortnight-long “Be Happy at Work” campaign, and when it concludes you re-call the 40 employees (20 low satisfaction, 20 high satisfaction) and ask them to complete a second, equivalent work satisfaction survey which also uses a 0-20 scale, where the higher the score, the more positive the participant’s work satisfaction.  You assume that the campaign will not necessarily affect scores for the high satisfaction employees (as they might have reached a score “ceiling” of around 18 out of 20, and the campaign does not significantly increase their personal work satisfaction) but will improve scores for the low satisfaction group.<\/span><\/p>\n

Assuming the “Be Happy at Work” campaign is valid and improves employee work satisfaction, you predict that the mean score of the low satisfaction group following the campaign<\/em> will rise and be equivalent to the mean score of the high satisfaction group.<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

TASK 1<\/span><\/strong><\/p>\n

Analyse the data and write a results section using APA format (Note: test assumptions separately<\/u> for each group)<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 2<\/span><\/strong><\/p>\n

Describe the research findings using a single sentence (i.e., write a clear statement explaining whether the company’s hypothesis was supported or not supported.). <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 3<\/span><\/strong><\/p>\n

There is a hidden design flaw in this scenario.  Identify this flaw and explain how it might affect your statistical finding, hence lead to an inaccurate conclusion.<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Table 3<\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/p>\n

<\/span><\/strong><\/p>\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Group<\/span><\/p>\n<\/td>\n

\n

Score<\/span><\/p>\n<\/td>\n

\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Group<\/span><\/p>\n<\/td>\n

\n

Score<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

13<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

59<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

48<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

23<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

59<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

48<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

13<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

5<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

23<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

5<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

50<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

13<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

6<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

7<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

56<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

7<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

57<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

12<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

41<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

53<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

13<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

32<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

13<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

60<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

54<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

51<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

52<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

17<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

52<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

19<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

47<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

12<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

19<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

60<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

“Group” = Participation in either the low work or high work satisfaction groups, where 1 = Low satisfaction and 2 = high satisfaction.  “Score” is score on the work satisfaction scale (0 – 20) (Unit of measure “Work satisfaction scale score”).<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Scenario 4<\/span><\/strong><\/p>\n

A company manufacturing electronic automotive-parts wants to determine the highest temperature their factory-employees can work in without detrimentally affecting productivity (to save electricity costs!).  To answer this question you recruit a random sample of 80 workers from the same factory location and erect three dividing walls between them.  This creates four identical workspaces, such that 20 are working in each location.  In each workspace you install an air conditioning unit and in the first location set the temperature at 220<\/sup> C, which is the current workplace temperature.  In the second location you set the temperature at 260<\/sup> C, in the third location you set the temperature at 300<\/sup> C and in the fourth location you set the temperature at 350<\/sup> C. <\/span><\/p>\n

The employees are required to work in these conditions for a full 5-day week, starting Monday morning. On Friday afternoon (at the close of business) you measure each worker’s performance as number of products they manufactured during the thirty eight-hour work week (Note:  you made sure that each of the 80 workers were operating at an equivalent production level before you recruited them, i.e. they were all manufacturing roughly the same amount of product weekly before you began your experiment). <\/span><\/p>\n

Assuming “normal” work performance is mean (average) product output at 220<\/sup> C, you are interested in determining at what (increased) temperature the mean product output of employees significantly declines<\/em> from this 220<\/sup> C mean.  That is, is a significant decline at 260<\/sup> C, 300<\/sup> C or 350<\/sup> C?  Or is there a decline at all?<\/span><\/p>\n

When collating the data you notice that 5 of the 20 workers in the 300<\/sup> C condition, and 8 of the 20 workers in the 350<\/sup> C condition, resigned from the company during the week.  You cannot use their incomplete data, so you remove them from the study.  Nevertheless you feel you still have collected enough data to run an analysis and answer the company’s question – which is the highest workplace temperature above 220<\/sup> C that exhibits normal product output?<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

TASK 1<\/span><\/strong><\/p>\n

Analyse the data and write a results section using APA format.<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

TASK 2<\/span><\/strong><\/p>\n

Describe the research findings using a single sentence and the conclusion you would provide the company. <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 3<\/span><\/strong><\/p>\n

There is a hidden design flaw in this scenario.  Identify this flaw and explain how it might affect your statistical finding, hence lead to an inaccurate conclusion.<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Table 4<\/span><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/p>\n

<\/span><\/strong><\/p>\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Temp.<\/span><\/p>\n<\/td>\n

\n

Output<\/span><\/p>\n<\/td>\n

\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Temp.<\/span><\/p>\n<\/td>\n

\n

Output<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

72<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

69<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

72<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

82<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

32<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

82<\/span><\/p>\n<\/td>\n

\n

23<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

73<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

92<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

5<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

76<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

54<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

75<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

6<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

97<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

74<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

7<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

56<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

62<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

77<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

56<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

83<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

80<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

96<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

83<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

77<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

76<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

78<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

54<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

104<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

98<\/span><\/p>\n<\/td>\n

\n

32<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

81<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

13<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

19<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

84<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

84<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

60<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

101<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

103<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

87<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

88<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

90<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

63<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

92<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

78<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

95<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

83<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

19<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

90<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

102<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

85<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

82<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Table 4 (cont.)<\/span><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/p>\n

<\/span><\/strong><\/p>\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Temp.<\/span><\/p>\n<\/td>\n

\n

Output<\/span><\/p>\n<\/td>\n

\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

Temp.<\/span><\/p>\n<\/td>\n

\n

Output<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

41<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

105<\/span><\/p>\n<\/td>\n

\n

61<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

99<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

62<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

45<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

63<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

101<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

44<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

69<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

32<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

93<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

45<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

58<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

94<\/span><\/p>\n<\/td>\n

\n

65<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

103<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

90<\/span><\/p>\n<\/td>\n

\n

66<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

100<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

47<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

92<\/span><\/p>\n<\/td>\n

\n

67<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

87<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

48<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

83<\/span><\/p>\n<\/td>\n

\n

68<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

95<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

94<\/span><\/p>\n<\/td>\n

\n

69<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

59<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

50<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

70<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

51<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

72<\/span><\/p>\n<\/td>\n

\n

71<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

51<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

99<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

52<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

65<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

105<\/span><\/p>\n<\/td>\n

\n

72<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

53<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

86<\/span><\/p>\n<\/td>\n

\n

73<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

71<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

54<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

75<\/span><\/p>\n<\/td>\n

\n

74<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

75<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

57<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

56<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

50<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

76<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

90<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

57<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

73<\/span><\/p>\n<\/td>\n

\n

77<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

45<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

58<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

82<\/span><\/p>\n<\/td>\n

\n

78<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

81<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

59<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

91<\/span><\/p>\n<\/td>\n

\n

79<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

60<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

73<\/span><\/p>\n<\/td>\n

\n

80<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

81<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

“Temp.” = Temperature of the four workspaces, 1 = 220<\/sup> C, 2 = 260<\/sup> C, 3 = 300<\/sup> C and 4 = 350<\/sup> C.  Unit of measure is “Weekly product output”.  Empty cells indicate missing data, meaning participant did not complete a week of work in their location, and their data cannot be used for the analysis<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Scenario 5<\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

A clothing company using a business website for retail purposes, and is seeking to determine which background colour scheme is most effective in retaining customers’ attention when viewing this website to make online purchases. The management team has been provided with four potential colour schemes from their IT department; blue\/grey, red\/yellow, black\/white and green\/orange.<\/span><\/p>\n

You recruit 30 participants (from the public) and take them individually to a room with a computer displaying the company’s website.  You ask them to sit down and interact with this website.  For all participants the blue\/grey background colour scheme is the first one shown.  You record the amount of time they spend on the site (in seconds) until they say they are “bored” and no longer wish to continue viewing the site.<\/span><\/p>\n

Following a 5 minute break, you then show the same participants the company website, however this time it is presented with a red\/yellow background colour scheme.  You record the time they spend on the site before they request to stop.<\/span><\/p>\n

After another 5 minute break, you show the same participants the company website however this time it is presented with a black\/white background colour scheme.  Again you record the time they spend on the site before requesting to stop.<\/span><\/p>\n

Finally, after another 5 minute break, you show participants the company website however now it is presented with a green\/orange background colour scheme.  Once more you record the time they spend on the site before requesting to stop.<\/span><\/p>\n

You collate the time-spent data (in seconds) for each participant and each colour condition.  Your task is to determine which website colour condition participants spend most<\/u> time interacting with, and assume this indicates the optimal background colour scheme for the company’s website.<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 1<\/span><\/strong><\/p>\n

Analyse the data and write a results section using APA format (Hint: If the overall ANOVA is significant and you calculate post hoc comparisons, only include those pairs that describe the most important “time spent watching” differences – that is, you don’t need to include every single comparison).<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 2<\/span><\/strong><\/p>\n

Describe the research findings and the conclusion you would provide the company. <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 3<\/span><\/strong><\/p>\n

There is a hidden design flaw in this scenario.  Identify this flaw and explain how it might affect your statistical finding, hence lead to an inaccurate conclusion.<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Table 5<\/span><\/strong><\/p>\n

 <\/span><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/p>\n

<\/span><\/strong><\/p>\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

37<\/span><\/p>\n<\/td>\n

\n

106<\/span><\/p>\n<\/td>\n

\n

78<\/span><\/p>\n<\/td>\n

\n

79<\/span><\/p>\n<\/td>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

131<\/span><\/p>\n<\/td>\n

\n

92<\/span><\/p>\n<\/td>\n

\n

91<\/span><\/p>\n<\/td>\n

\n

19<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

152<\/span><\/p>\n<\/td>\n

\n

75<\/span><\/p>\n<\/td>\n

\n

97<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

155<\/span><\/p>\n<\/td>\n

\n

97<\/span><\/p>\n<\/td>\n

\n

91<\/span><\/p>\n<\/td>\n

\n

13<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

99<\/span><\/p>\n<\/td>\n

\n

134<\/span><\/p>\n<\/td>\n

\n

86<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

23<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

\n

164<\/span><\/p>\n<\/td>\n

\n

81<\/span><\/p>\n<\/td>\n

\n

88<\/span><\/p>\n<\/td>\n

\n

22<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

131<\/span><\/p>\n<\/td>\n

\n

77<\/span><\/p>\n<\/td>\n

\n

97<\/span><\/p>\n<\/td>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

132<\/span><\/p>\n<\/td>\n

\n

93<\/span><\/p>\n<\/td>\n

\n

97<\/span><\/p>\n<\/td>\n

\n

23<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

5<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

132<\/span><\/p>\n<\/td>\n

\n

121<\/span><\/p>\n<\/td>\n

\n

86<\/span><\/p>\n<\/td>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

165<\/span><\/p>\n<\/td>\n

\n

105<\/span><\/p>\n<\/td>\n

\n

82<\/span><\/p>\n<\/td>\n

\n

16<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

6<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

160<\/span><\/p>\n<\/td>\n

\n

122<\/span><\/p>\n<\/td>\n

\n

41<\/span><\/p>\n<\/td>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

92<\/span><\/p>\n<\/td>\n

\n

84<\/span><\/p>\n<\/td>\n

\n

50<\/span><\/p>\n<\/td>\n

\n

9<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

7<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

97<\/span><\/p>\n<\/td>\n

\n

66<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

131<\/span><\/p>\n<\/td>\n

\n

136<\/span><\/p>\n<\/td>\n

\n

61<\/span><\/p>\n<\/td>\n

\n

18<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

8<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

45<\/span><\/p>\n<\/td>\n

\n

139<\/span><\/p>\n<\/td>\n

\n

114<\/span><\/p>\n<\/td>\n

\n

54<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

28<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

36<\/span><\/p>\n<\/td>\n

\n

138<\/span><\/p>\n<\/td>\n

\n

110<\/span><\/p>\n<\/td>\n

\n

70<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

178<\/span><\/p>\n<\/td>\n

\n

67<\/span><\/p>\n<\/td>\n

\n

60<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

44<\/span><\/p>\n<\/td>\n

\n

152<\/span><\/p>\n<\/td>\n

\n

88<\/span><\/p>\n<\/td>\n

\n

59<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

99<\/span><\/p>\n<\/td>\n

\n

82<\/span><\/p>\n<\/td>\n

\n

68<\/span><\/p>\n<\/td>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

26<\/span><\/p>\n<\/td>\n

\n

94<\/span><\/p>\n<\/td>\n

\n

128<\/span><\/p>\n<\/td>\n

\n

65<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

60<\/span><\/p>\n<\/td>\n

\n

130<\/span><\/p>\n<\/td>\n

\n

120<\/span><\/p>\n<\/td>\n

\n

56<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

85<\/span><\/p>\n<\/td>\n

\n

116<\/span><\/p>\n<\/td>\n

\n

77<\/span><\/p>\n<\/td>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

13<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

43<\/span><\/p>\n<\/td>\n

\n

156<\/span><\/p>\n<\/td>\n

\n

67<\/span><\/p>\n<\/td>\n

\n

61<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

54<\/span><\/p>\n<\/td>\n

\n

107<\/span><\/p>\n<\/td>\n

\n

106<\/span><\/p>\n<\/td>\n

\n

87<\/span><\/p>\n<\/td>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

44<\/span><\/p>\n<\/td>\n

\n

124<\/span><\/p>\n<\/td>\n

\n

85<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

96<\/span><\/p>\n<\/td>\n

\n

96<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

30<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

17<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

109<\/span><\/p>\n<\/td>\n

\n

109<\/span><\/p>\n<\/td>\n

\n

97<\/span><\/p>\n<\/td>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

18<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

164<\/span><\/p>\n<\/td>\n

\n

126<\/span><\/p>\n<\/td>\n

\n

71<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

19<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

55<\/span><\/p>\n<\/td>\n

\n

127<\/span><\/p>\n<\/td>\n

\n

134<\/span><\/p>\n<\/td>\n

\n

49<\/span><\/p>\n<\/td>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n

\n

20<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

112<\/span><\/p>\n<\/td>\n

\n

64<\/span><\/p>\n<\/td>\n

\n

58<\/span><\/p>\n<\/td>\n

\n

25<\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n

\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

“1” = Time spent (seconds) viewing the website with a blue\/grey background colour scheme.  “2” = Time spent (seconds) viewing the website with a red\/yellow background colour scheme.  “3” = Time spent (seconds) viewing the website with a black\/white background colour scheme.  “4” = Time spent (seconds) viewing the website with a green\/orange background colour scheme. <\/span><\/p>\n

Scenario 6<\/span><\/strong><\/p>\n

A financial company is shifting to a smaller office building in the same city, which will save money but means there will be no space for employees to be assigned individual private offices.  The leadership team is interested in determining the best alternative style of workspace – other than a separate office in a city building – to maintain productivity<\/em> (i.e., achievement goals for each employee set by the company).  The CEO picks three different new surroundings;<\/span><\/p>\n

(1) A fully-open office design (i.e., employees are stationed in a large room on an office floor and are able to see each other from their desks).<\/span><\/p>\n

(2) A partitioned office environment (i.e., employees are stationed in a large room on an office floor but they are separated by low partitions and are unable to view each other directly).<\/span><\/p>\n

(3) A home office (i.e., employees work remotely from home)<\/span><\/p>\n

You recruit 45 employees from the company and randomly assign them to work in one of the three environmental conditions for a 5-day week starting on Monday (either open office, partitioned office or home office).  On Friday evening (after 5 work days have been completed) you provide an online questionnaire for each participant to complete, which measures the liking<\/em> for the week’s work environment as a score from 0 – 100, where the higher the score, the more liked<\/u> the work environment.  You compare these mean liking scores amongst the three groups of participants to reach a conclusion on which workspace is preferred<\/em>.<\/span><\/p>\n

 <\/span><\/p>\n

TASK 1<\/span><\/strong><\/p>\n

Analyse the data and write a results section using APA format.<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 2<\/span><\/strong><\/p>\n

Describe the research findings using a single sentence, and the conclusion you would provide the company. <\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

TASK 3<\/span><\/strong><\/p>\n

There is a hidden design flaw in this scenario.  Identify this flaw and explain how it might affect your statistical finding, hence lead to an inaccurate conclusion.<\/span><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

Table 6<\/span><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/p>\n

<\/span><\/strong><\/p>\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

E<\/span><\/p>\n<\/td>\n

\n

S<\/span><\/p>\n<\/td>\n

\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

E<\/span><\/p>\n<\/td>\n

\n

S<\/span><\/p>\n<\/td>\n

\n

ID<\/span><\/p>\n<\/td>\n

\n

Sex<\/span><\/p>\n<\/td>\n

\n

Age<\/span><\/p>\n<\/td>\n

\n

E<\/span><\/p>\n<\/td>\n

\n

S<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

42<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

10<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

41<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

27<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

76<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

11<\/span><\/p>\n<\/td>\n

\n

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45<\/span><\/p>\n<\/td>\n

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2<\/span><\/p>\n<\/td>\n

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39<\/span><\/p>\n<\/td>\n

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42<\/span><\/p>\n<\/td>\n

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33<\/span><\/p>\n<\/td>\n

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98<\/span><\/p>\n<\/td>\n

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26<\/span><\/p>\n<\/td>\n

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27<\/span><\/p>\n<\/td>\n

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38<\/span><\/p>\n<\/td>\n

\n

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\n

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\n

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\n

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\n

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9<\/span><\/p>\n<\/td>\n

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M<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

14<\/span><\/p>\n<\/td>\n

\n

29<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

59<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

41<\/span><\/p>\n<\/td>\n

\n

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\n

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\n

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\n

10<\/span><\/p>\n<\/td>\n

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25<\/span><\/p>\n<\/td>\n

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\n

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11<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

34<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

12<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

51<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

69<\/span><\/p>\n<\/td>\n

\n

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12<\/span><\/p>\n<\/td>\n

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F<\/span><\/p>\n<\/td>\n

\n

20<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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16<\/span><\/p>\n<\/td>\n

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32<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

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64<\/span><\/p>\n<\/td>\n

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25<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

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13<\/span><\/p>\n<\/td>\n

\n

33<\/span><\/p>\n<\/td>\n

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27<\/span><\/p>\n<\/td>\n

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15<\/span><\/p>\n<\/td>\n

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12<\/span><\/p>\n<\/td>\n

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17<\/span><\/p>\n<\/td>\n

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27<\/span><\/p>\n<\/td>\n

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37<\/span><\/p>\n<\/td>\n

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37<\/span><\/p>\n<\/td>\n

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42<\/span><\/p>\n<\/td>\n

\n

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30<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

24<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

74<\/span><\/p>\n<\/td>\n

\n

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\n

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\n

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\n

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\n

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\n

19<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

48<\/span><\/p>\n<\/td>\n

\n

39<\/span><\/p>\n<\/td>\n

\n

F<\/span><\/p>\n<\/td>\n

\n

38<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

81<\/span><\/p>\n<\/td>\n

\n

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\n

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20<\/span><\/p>\n<\/td>\n

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M<\/span><\/p>\n<\/td>\n

\n

21<\/span><\/p>\n<\/td>\n

\n

2<\/span><\/p>\n<\/td>\n

\n

35<\/span><\/p>\n<\/td>\n

\n

40<\/span><\/p>\n<\/td>\n

\n

M<\/span><\/p>\n<\/td>\n

\n

31<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

88<\/span><\/p>\n<\/td>\n

\n

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\n

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\n

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\n

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\n

 <\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

“E” = Environmental condition where 1 = Open office, 2 = Partitioned office and 3 = Home office.  S = Score on the “liking” survey (Unit of measure “Liking score”).<\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

END OF ASSESSMENT 1<\/span><\/strong><\/p>\n

 <\/span><\/strong><\/p>\n

The post Assignment Paper appeared first on Custom Essay Papers.<\/p>\n","protected":false},"excerpt":{"rendered":"

Assessment 1 (Autumn 2018) Assessment 1 provides you with six research scenarios, each with associated data and two tasks to complete.  For each scenario you are assuming the role of a researcher employed by an organisation with the purpose of helping Read More …<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[15,1],"tags":[],"class_list":["post-434538","post","type-post","status-publish","format-standard","hentry","category-essay-paper-writing","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/434538","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/comments?post=434538"}],"version-history":[{"count":0,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/434538\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/media?parent=434538"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/categories?post=434538"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/tags?post=434538"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}