Week 5 Project – STAT 3001 .<\/p>\n
Part I. Chi-Square Goodness of Fit Test (equal frequencies)<\/p>\n
Four different brands of a pain medication used for chronic back ailments were tested to see if the number of side effects for each brand were the same. The table<\/p>\n
below lists the results of the reported number of side effects for each brand of pain medication.<\/p>\n
Brand A\tBrand B\tBrand C\tBrand D
\n23\t17\t33\t11<\/p>\n
[Hint: Be sure to watch the video at Week 5 Resources on the \ufffd\ufffd\ufffdChi-Square Goodness-of-Fit test (equal frequencies)\ufffd\ufffd\ufffd before attempting this problem. Instructions for<\/p>\n
performing this test in STATDISK can be found in the Statdisk User Manual.]<\/p>\n
Instructions\tAnswers
\n1.\tUse the Chi-Square Goodness-of-Fit test to see if there is a difference between the number of side effects from the different brands of medication. Use a<\/p>\n
significance level of .01.
\nPaste results here.
\n2.\tWhat are we trying to show here?
\n3.\tWhat is the p-value and what does it represent in the context of this problem?
\n4.\t State in your own words what the results of this Goodness-of-fit test tells us.
\n5.\tRepeat the above procedure using only Brands A, B, and D. Paste results here.
\n6.\tDo you get a different result?<\/p>\n
\ufffd\ufffd\ufffd
\nPart II. Chi-Square Goodness of Fit Test (unequal frequencies)<\/p>\n
An opinion poll was taken to see how people felt about Health Care reform. Previous poll results indicate that within a particular population 34% were for reform,<\/p>\n
41% were against reform, and 25% were uncertain.<\/p>\n
This year, the following results were observed:<\/p>\n
FOR: 317 people\t\tAGAINST: 223 people\t\tUNCERTAIN: 211 people<\/p>\n
[Hint: Be sure to watch the video at Week 5 Resources on the \ufffd\ufffd\ufffdChi-Square Goodness-of-Fit test (unequal frequencies)\ufffd\ufffd\ufffd before attempting this problem. Instructions for<\/p>\n
performing this test in STATDISK can be found in the Statdisk User Manual.]<\/p>\n
Instructions\tAnswers
\n7.\tComplete the table as necessary.<\/p>\n
[Hint: You will need to compute the expected frequencies based on the previous poll results. Round to the nearest integer.]
\n\tOBSERVED
\n\tEXPECTED
\n8.\tUse the Chi-Square Goodness-of-Fit test for Unequal frequencies to see if there is a difference between the observed frequencies (this year) and the expected<\/p>\n
frequencies (based on the previous poll results). Use a significance level of .01.
\nPaste results here.
\n9.\tState the null and alternative hypothesis.
\n10.\tWhat conclusion would you reach, given the result of your Goodness-of-Fit test? [State in your own words.]<\/p>\n
\ufffd\ufffd\ufffd
\nPart III. Chi-Square Test of Independence<\/p>\n
A study was done to test the claim that discharging a newborn infant discharged early (less than 30 hours after birth) is related to re-hospitalization of that infant<\/p>\n
within a week of discharge.<\/p>\n
The following data was collected related to early discharge and re-hospitalization:<\/p>\n
\tRe-hospitalized within 1 week \tNot
\nre-hospitalized\tTotal
\nEarly Discharge (less than 30 hours)\t 622\t3997\t4619
\nLate Discharge (30 \ufffd\ufffd\ufffd 78 hours)\t 631\t4660\t5291<\/p>\n
Hint: Instructions for performing this test in STATDISK can be found in the Stat Disk User\ufffd\ufffd\ufffds Manual under the heading Chi Square Test of Independence (Contingency<\/p>\n
Tables).<\/p>\n
Instructions\tAnswers
\n11.\tJust looking at the numbers in the table, what is your best guess about whether early discharge is related to re-hospitalization? [Hint: you might compute the<\/p>\n
difference in percentages between those that were discharged early and those that were not.]
\n12.\tCompute a Chi-Square Test of Independence on this data using a 0.05 level of significance. Paste your results here.
\n13.\tWhat is the null and alternative hypothesis for this result?
\n14.\tWhat is the p-value for this result? What does this represent?
\n15.\tState your conclusion related to the context of this problem.<\/p>\n
\ufffd\ufffd\ufffd
\nPart IV. Apply this to your own situation<\/p>\n
Using one of the above statistical tests, compose and SOLVE an actual problem from the context of your own personal or professional life. You will need to make up<\/p>\n
some data and describe which test you will use to analyze the situation. Here\ufffd\ufffd\ufffds an example:<\/p>\n
\tExample
\nState the problem that you are analyzing. \tLast year, I asked the kids in my neighborhood what kind of cookies they preferred. 50% said chocolate-chip, 20% said<\/p>\n
oatmeal-raisin, and 30% said sugar cookie. I want to see if this has changed.
\nMake up some data for the new situation. \tI asked 50 neighborhood kids what kind of cookie they preferred now and here\ufffd\ufffd\ufffds what they said:<\/p>\n
\ufffd\ufffd\ufffd\t35 said chocolate-chip
\n\ufffd\ufffd\ufffd\t5 said oatmeal-raisin
\n\ufffd\ufffd\ufffd\t10 said sugar-cookie
\nDetermine which type of Chi-Square test you will perform.\tSince these are unequal frequencies, I will perform a Chi-Square Goodness-of-Fit Test (Unequal<\/p>\n
Frequencies).
\nSpecify your null and alternative hypotheses.\tH0: There is no difference this year in the preferences of cookies within the neighborhood kids.
\nH1: Things have changed.
\nSetup the test\t\tChocolate-Chip\tOatmeal-Raisin\tSugar-Cookie
\n\tOBSERVED\t35\t5\t10
\n\tEXPECTED\t25\t10\t15
\nPerform the test\tPaste your STATDISK results here
\nState your conclusion\tWe have evidence to believe \ufffd\ufffd\ufffd.<\/p>\n
Submit your final draft of your Word file by going to Week 5, Project, and follow the directions under Week 5 Assignment 2. Please use the naming convention<\/p>\n
“WK5Assgn2+first initial+last name” as the Submission Title.<\/p>\n","protected":false},"excerpt":{"rendered":"
Week 5 Project – STAT 3001 . Part I. Chi-Square Goodness of Fit Test (equal frequencies) Four different brands of a pain medication used for chronic back ailments were tested to see if the number of side effects for each Read More …<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-5442","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/5442","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=5442"}],"version-history":[{"count":0,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/5442\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/media?parent=5442"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/categories?post=5442"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/tags?post=5442"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}