Statistical work on environmental studies (plastic bag pollution in Palm Beach County, FL)<\/p>\n
will be sent by email, this is a complicated assignment and needs to be done by the best you have. I will pay extra, just let me know<\/p>\n
ENV 340<\/p>\n
Computer Assignment #2<\/p>\n
Introduction<\/p>\n
For this assignment you work for the Nature Conservancy. Your group is considering lobbying for plastic bags to be banned at grocery stores in southeastern Florida to reduce the occurrence of plastic pollution on southeast Florida beaches. You are assigned to create a feasibility study of implementing such a ban. Your task is to determine which county (Broward, Palm Beach, Miami-Dade, Martin, St. Lucie, and Indian River) you should lobby for the plastic bag ban to occur in. You need to consider how easy it will be to implement a ban in each county and which county needs the ban the most. Based on your understanding of the area you form a hypothesis.<\/p>\n
Hypothesis: The Nature Conservancy should lobby for a plastic bag ban in Palm Beach County, Florida as residents of that county will comply with a plastic bag ban and Palm Beach County has the beaches most polluted with plastic.<\/p>\n
To test your hypothesis you design two experiments. The first experiment tests how likely it is that the residents of each county will accept a bag ban. The second experiment determines how polluted each of the county\u2019s\u2019 beaches are.<\/p>\n
Experiment 1<\/p>\n
For the first experiment you and a team conduct a survey of people who live in the counties that would be subject to the proposed plastic bag ban. You call people randomly who live all over each county. You only ask them \u201cWould you support a plastic bag ban in your county?\u201d You mark their answers as \u201cyes\u201d, \u201cno\u201d, or \u201cundecided\u201d. Now it is time to plot your data.<\/p>\n
Open \u201cBag Ban Data.xlsx\u201d<\/p>\n
Make sure you are on the sheet \u201cProb1\u201d<\/p>\n
Here is a table of your results organized by county. You want to plot this data two ways, first as a clustered bar chart, and second as a 100% stacked bar chart. The data in the table is already organized in a way that will work for plotting the clustered bar chart, but you must convert the data to percent for the stacked bar chart.<\/p>\n
To build your % stacked bar chart you need to calculate the percent. To do this follow these steps:<\/p>\n
(1) Calculate the total number of respondents in each county by summing the Yeses, Nos, and Undecideds. Be sure to label the column you put this new data in.<\/p>\n
(2) Create a new table below the original table that has the same column and row labels, but leave the cells in the tables blank.<\/p>\n
(3) In each cell in the new table divide the associated number of respondents from table above by the total number of people surveyed in that county and multiply by 100. Note that if you build your formula well, you can copy and paste the formula to fill much of the table without retyping the formula every time.<\/p>\n
Once you have created your second data table you can make your plots. DO NOT SELECT THE DATA BEFORE SELECTING THE CHART! To make your clustered bar plot select a cell to the right of the top table. Go to charts->column->cluster column. A white plot should appear on your excel sheet. Right click on the plot and click on \u201cselect data\u201d.<\/p>\n
Under the \u201cseries\u201d box click \u201cadd\u201d.<\/p>\n
In the \u201cname\u201d box enter \u201cyes\u201d<\/p>\n
Click the \u201cY values\u201d box and select the values in the table in the yes column. Click the \u201cCategory (X) axis labels\u201d and select the name of the counties. Repeat adding series for \u201cNo\u201d and \u201cUndecided\u201d.<\/p>\n
Ensure this figure follows the \u201cRules for Good Figures and Tables\u201d Handout. Ask if you need help. You can edit most of the figure properties by clicking on the figure and then clicking on the \u201cChart Layout\u201d tab that appears.<\/p>\n
To make your stacked bar plot select a cell to the right of the bottom table. Go to charts->column->stacked column. A white plot should appear on your excel sheet. Right click on the plot and click on \u201cselect data\u201d. Repeat the previous process using the bottom table.<\/p>\n
Decide which of these tables better represents the results of your survey and will be more useful when evaluating your hypothesis. Paste it into a word document. This will be Figure 1. Add a descriptive figure caption below the figure.<\/p>\n
Experiment 2<\/p>\n
For your second experiment you and your team collect data from annual countywide beach clean ups conducted in the spring of 2016, 2015, 2014, and 2013. The data is organized into tables by county on the second sheet of your spreadsheet (Prob2). At each clean up, the volunteers counted the number of total pieces of trash and the umber of non-plastics pieces. You also have the area in square kilometers of each beach. Since you want to calculate the average number of plastic pieces per square meter of beach, you will need to do some calculations. Follow the steps below:<\/p>\n
1)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 First you need to determine the average and standard error of the total pieces of trash and non-plastic pieces of trash for each beach. Using a series of formulas calculated the average, standard deviation, and standard error for each row.<\/p>\n
A \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 B \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 C<\/p>\n
D<\/p>\n
E<\/p>\n
F<\/p>\n
G<\/p>\n
H<\/p>\n
I<\/p>\n
1 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Broward County \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Beach Area (square km): \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 60 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Average \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Standard Deviation \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Err<\/p>\n
2 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Clean Up: \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 2013<\/p>\n
2014<\/p>\n
2015<\/p>\n
2016<\/p>\n
3 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Total Pieces \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 200300000 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 300200000<\/p>\n
234500000<\/p>\n
298700000<\/p>\n
4 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Non- Plastic Pieces: \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 30500000 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 65400000<\/p>\n
20300000<\/p>\n
40500000<\/p>\n
2) To find the number of plastic pieces, subtract the non-plastic pieces from the plastic pieces.<\/p>\n
3) Propagate the error associated with the non-plastic pieces and the total pieces to find the error of the plastic pieces. Reference the rules for error propagation<\/p>\n
4) Then to determine the concentration of plastic pieces divide the number of plastic pieces total by the area of each beach. You should now have the number of plastic pieces per square kilometer.<\/p>\n
5) Be sure to propagate the error through this calculation according to the rules for error propagation in your text book.<\/p>\n
6) Now you need to convert the concentration from plastic pieces per square kilometer of beach to number of plastic pieces per square meter of beach. To do this multiply the number of pieces per square kilometer by 10002, because there are 1000 m in 1 km.<\/p>\n
7) Propagate the error through this calculation according to the rules for error propagation in your text book.<\/p>\n
After you have calculated the values for average pieces of plastic per square meter and the error plot a bar graph. You need to reorganize your table into a new more compact table first. Create a table that looks like the table below and fill in the correct values you calculated:<\/p>\n
County Plastic Pieces per m2 \u00a0\u00a0\u00a0\u00a0 Error<\/p>\n
Broward<\/p>\n
Palm Beach<\/p>\n
Miami-Dade<\/p>\n
Martin<\/p>\n
St. Lucie<\/p>\n
Indian River<\/p>\n
To make your clustered bar plot select a cell to the right of the top table. Go to charts->column->cluster column. A white plot should appear on your excel sheet. Right click on the plot and click on \u201cselect data\u201d.<\/p>\n
Under the \u201cseries\u201d box click \u201cadd\u201d.<\/p>\n
In the \u201cname\u201d box enter \u201cPlastics\u201d<\/p>\n
Click the \u201cY values\u201d box and select the values in the table in the \u201cPlastics Pieces Per Square m\u201d column.<\/p>\n
Click the \u201cCategory (X) axis labels\u201d and select the name of the counties.<\/p>\n
Now add the error bars. Right click on one of the columns and select \u201cFormat Data Series\u201d.<\/p>\n
Select the \u201cError Bar\u201d tab.<\/p>\n
Select \u201cboth\u201d under \u201cdisplay\u201d and \u201ccustom\u201d under \u201cerror amount\u201d.<\/p>\n
Click \u201cspecify value\u201d.<\/p>\n
A pop up window will come up. Click the box next to \u201cpositive error value\u201d and highlight the row\/column with the error values on your sheet. Repeat for the \u201cnegative error value.<\/p>\n
Ensure this figure follows the \u201cRules for Good Figures and Tables\u201d Handout. Ask if you need help. You can edit most of the figure properties by clicking on the figure and then clicking on the \u201cChart Layout\u201d tab that appears. Note you will not need a legend (since there is only one data series) or a title, so delete these.<\/p>\n
Copy and paste this document into your word document this will be Figure 2. Be sure to write a descriptive caption under the figure.<\/p>\n
Writing Your Report<\/p>\n
Below both of the figures write a header for your results section in bold. Below the header describe the results. You should explicitly call out the figures in order when you introduce the data, and call out the statistics when you describe them. Here you only list results. Do not interpret the data here. This should be 1-2 paragraphs in length.<\/p>\n
Below the results section make a header for your discussion section in bold. Below the header you will write your discussion. In your discussion section you should identify whether your hypothesis was supported or disproven by the statistics of the data. Do not say you \u201cproved\u201d anything. Experiments cannot \u201cprove\u201d hypotheses only disprove or support. If your hypothesis was disproven you should identify which county you should try to implement a plastic bag ban instead. This would be a county that has a lot of plastic pollution, but also would be accepting of a bag ban.<\/p>\n
Call out the data as relevant in the discussion. You should to end the discussion with a proposed future experiment to test new questions you have, or indicate areas of further study. Your discussion should be 2-3 paragraphs in length.<\/p>\n
Turning in Your Assignment<\/p>\n
When you are finished with your assignment turn it into Canvas. The word document must be submitted to the assignment \u201cAssignment 2 (Word)\u201d, and the excel document must be submitted to the assignment \u201cAssignment 2 (Excel).<\/p>\n
Computer Assignment Rubric<\/p>\n
Computer Assignment Rubric<\/p>\n
Criteria Ratings Pts<\/p>\n
This criterion is linked to a Learning OutcomeRules for Figures and Tables\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.0 pts<\/p>\n
This criterion is linked to a Learning OutcomeFigures and Tables in text\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.0 pts<\/p>\n
This criterion is linked to a Learning OutcomeTitles\/Captions\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.0 pts<\/p>\n
This criterion is linked to a Learning OutcomeFigures and Tables Accuracy\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.0 pts<\/p>\n
This criterion is linked to a Learning OutcomeFormatting and Grammar\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.0 pts<\/p>\n
This criterion is linked to a Learning OutcomeDescription of criterion\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.0 pts<\/p>\n
This criterion is linked to a Learning OutcomeExcel Spreadsheet\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.0 pts<\/p>\n
Total Points: 35.0<\/p>\n","protected":false},"excerpt":{"rendered":"
Statistical work on environmental studies (plastic bag pollution in Palm Beach County, FL) will be sent by email, this is a complicated assignment and needs to be done by the best you have. I will pay extra, just let me Read More …<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-428082","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/428082","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=428082"}],"version-history":[{"count":0,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/428082\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/media?parent=428082"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/categories?post=428082"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/tags?post=428082"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}