Activity You will now determine whether penguins respond the presence of DMS. We

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Activity
You will now determine whether penguins respond the presence of DMS. We will evaluate chicks and adults separately (Note: if you’ve take another statistics course, you may recognize another approach could be used to assess this data).
First, complete the following steps for the adult data.
1. Given the biological information above, create a null hypothesis about the relationship between king penguins and DMS that you expect to be able to observe and test using the experimental data. Your hypothesis should focus on what you expect to see when comparing the responses of the two groups (the one exposed to DMS and the one exposed to the control) and consider the average response to DMS in the two groups.
2. Then create corresponding alternative hypotheses.
Now open the dataset below (titled “Sleeping”) in either Excel or Google Sheets. Note is has two tabs, one with adult and with chick data.
4. First, visualize the data for each treatment group. What type of graph would you use to visualize this data (examples include scatterplots, bar graphs, etc.)? Explain your choice and make the chart(s) (hint: ask your instructor about having multiple histograms on one chart or check out the Data Summaries in Google Sheets page. ) You can make one chart for the adult data and one for the chick data.
5. Calculate the summary statistics for each treatment group (mean, sample size, standard deviation, and standard error). These are useful numerical summaries of the data.
Use MSExcel/Google Sheets formulas to do this. Use =AVERAGE() and=STDEV() for computing the mean and standard deviation respectively. To calculate your sample size (n), you can either count up your data points or use =COUNT().
MSExcel and Google Sheets do not have formulas for standard error (SE), so you will need to create your own. SE = SD√n, in MSExcel you can use =()^0.5 or =SQRT() to calculate square root, your formula then becomes SE = SD/(n^0.5) or SE=SD/SQRT(n). Enter your formula in the SE cell =SD/(n^0.5).
6. Compile a table in your lab report of the summary statistics of your data like so:
7. What do each of these summary statistics tell us about our data?
8. Next, you will graph the average of the DMS and Control treatments (hint: ask your instructor about creating bar charts or check out the Data Summaries in Google Sheets page. )
9. Look at your descriiptive statistics and the figure you created. Do you think there is a significant difference visually between the Control and DMS treatments?
Dataset- “Sleeping”
 Now you will see if there is a numerically significant difference between the treatments by doing a statistical test.
Because the data above is comprised of ranking the extent of the response of each individual from 0-2, it does not meet the usual assumptions of normality required for tests that you may have encountered before (a t-test). Therefore, you will be using a special kind of test designed for this type of data known as a Mann-Whitney U-test to compare the means between groups.
The steps to do this are as follows:
 You will be using a free online calculator of sorts for t-tests and other statistical analyses found here: http://vassarstats.net
 When you get to the main page, click on the tab in the menu box on the right labeled “Ordinal Data”. Then choose the option for “Mann-Whitney Test”
 A pop-up window will appear for you to enter your sample size for each treatment. The Control treatment is Sample A and the DMS treatment is Sample B. Use the sample size (n) you calculated above.
 You will copy and paste each column of data for the Control treatments in the box for Sample A and the data from the DMS treatments in the box for Sample B (the numbers pictured below are fake data to show you how the entry will look–do not use them! Only use the data in the Sleeping spreadsheet).
 Once you have your data in the boxes, click “Import data into data cells”. This will autofill the “Raw Data for…” in the “Data Entry” heading.
 Then, click the “Calculate from Raw Data” button at the bottom of your autofilled Data. It will give you a series of different outputs. The output we will be using in this exercise is the p(2) value; this corresponds a null hypothesis that states the two groups are equal to each other.
10. What is the p-value for the test? Is there a significant difference between the groups exposed to DMS and those exposed to the Control?
Now complete steps 1 – 10 for the chick data before you answer the following questions!
11. Based on your statistics, are adult King penguins able to detect DMS? What makes you think this?
12. Are baby King penguins able to detect DMS? How do you know?
13. Does your analysis suggest there is a difference between the responses of adults versus chicks to DMS? Why or why not?
14. Are there differences between adults and young penguins in how they respond to a scent indicating prey? Why do you think this might be?

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