Past exam Qus.pdf

2 Question 1. Answer all parts 1A to 1E. Prompted by the devastating fire season this year in Australia, a climate scientist decided to analyse if climate change played a significant role in this particular event. The scientist first plotted the annual average of monthly maximum temperature anomalies in southern Australia since 1910: The scientist then performed a statistical analysis on her computer to analyse the data above and sees the following on her screen: 1A) What kind of analysis did she perform? Write the equation, explain the information you can gather from this output in your own words, and conclude.

3 Dangerous fire conditions do not only depend on maximum temperatures but also on fuel load (vegetation biomass) and if the fuel load is dry enough to burn. She therefore performed a similar analysis for annual mean precipitation (in mm per month) over time and gets the following result: 1B) Write the equation, explain the information you can gather from this output in your own words, and conclude. The scientist then divided her data into three groups, years with large fires (>1M acres burnt), years with medium fires (between 0.5M and 1M acres burnt) and years with small fires (< 0.5 M burnt), and produced the following box plot:

4 She then ran a statistical analysis and sees the following on her screen: Source SS df MS F Prob>F Groups 4.7245 2 2.36225 5.38 0.0059 Error 46.9945 107 0.4392 Total 51.719 109 1C) What kind of analysis did she perform? Explain the information you can gather from this output in your own words, and conclude. Here is a similar plot for precipitation and the result of a similar analysis for precipitation: Source SS df MS F Prob>F Groups 317.33 2 158.666 4.72 0.0109 Error 3596.84 107 33.615 Total 3914.18 109

5 1D) Explain the information you can gather from this output in your own words and conclude. Below is a different way to visualize the data with the black diamonds marking the years with large fires (exceeding 1M acres of burnt land). 1E) Most of the fires are sitting in the upper left quadrant. What does this mean? Would there have been a smarter way to analyse the data? How?

6 Question 2 . Answer all parts 2A to 2D. A team of conservation biologists was monitoring the reproduction of an endangered plant in a national park south of Sydney. They set up 15 plots in the heathland in Spring 2019 and measured the number of seedlings that had recently emerged. Over summer 2019/2020, the group actively removed weeds from all the plots. In Spring 2020, they revisited the plots and again measured the number of seedlings that had recently emerged. They collected the following data plotted the differences between seedling recruitment in the two years. Plot Number of seedlings in 2019 Number of seedlings in 2020 1 5 18 2 3 24 3 7 45 4 9 23 5 10 76 6 23 30 7 2 15 8 8 8 9 12 26 10 15 34 11 31 41 12 10 32 13 8 19 14 2 15 15 9 24 A paired-t test was run to formally test whether the two years were different. Paired t-test data: Seedlings$Seedlings by Seedlings$Year t = -4.5718, df = 14, p-value = 0.0004352 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -27.032092 -9.767908 sample estimates: mean of the differences -18.4

7 2A) Why did the scientists decide to use a paired t -test? 2B) Write a paragraph that could be given the national park managers to explain the result. 2C) Can you see any problems with the analysis that they ran? 2D) How confident are you that the results can be explained by the weed removal work conducted between the two sampling events? Describe a sampling design that would allow a more effective test of whether removing weeds could help the regeneration of the endangered plant.

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help