Biological Data Analysis: Exam 1 answers

Here are the answers to exam 1. For some of the questions, I have provided explanatory material in regular type, and the answer in bold; all you need to write down is the answer. If you don't understand why your answer was wrong, you may e-mail me, talk to me before or after class, or set up a time to talk to me in my office. The exam was worth 15 points, so each question was worth 0.75 points.

1. Two nominal variables, Lignextra vs. control, snoring vs. not snoring; total sample size is 90; Fisher's exact test of independence.

2. Because the null hypothesis is true, the probability of getting a significant result is equal to the significance level, or alpha. Because we're using a significance level of 0.05 in this class, all you needed to write for full credit was 0.05 or 5%.

3. Two nominal variables, kind of cat, adopted vs. not adopted; total sample size is more than 1000; chi-square test of independence or G-test of independence.

4. An exact test is better when the sample size is small, because the P-value is more accurate than for a chi-square or G-test. We use the chi-square or G-test when the sample size is large, because the calculations for an exact test are difficult even for a computer, and because all three tests give about the same P-value when sample sizes are large. .

5. Because 42.3% of the area is cars, The null hypothesis is that 42.3% of the poops will be on cars.. There is one nominal variable, car vs. asphalt, and the total sample size is less than 1000, so the test is exact test of goodness-of-fit.

6. Hematocrit: measurement (because there are more than 5 values);
Time to ride 100 miles: measurement.

7. Two nominal variables, dimly lit vs. dark, noon vs. midnight; total sample size is greater than 1000 (750+800); chi-square test of independence or G-test of independence.

8. alpha: 0.05 (also known as significance level)
beta: 0.20 or power: 0.80 . You got points off for putting down both beta and power, because power equals one minus beta, you only need to pick one.
Effect size: 15 percent fewer deaths

9. Make alpha larger; make beta larger (or power smaller); make effect size larger..

10. Species of slug: nominal
Water content: nominal
(because just two values, 15 and 30%.

11. Three nominal variables, kind of corn (sweet vs. yellow dent), strain of borer (E or Z), location; Cochran-Mantel-Haenszel test.

12. 0.003 is the probability of getting a difference in mean milk production between grass-fed and hay-fed goats of 0.7 liters per day, or more, by chance if the null is true.

13. Three nominal variables, near vs. far from cedar tree, rust spot vs. no rust spot, orchard; Cochran-Mantel-Haenszel test.

14. Time that turtle pokes its head up: measurement
walking speed: measurement
eaten vs. safe: nominal

15. Total number of salamanders: measurement
soil pH: measurement
number of dead logs: measurement
white oak vs. non-white oak leaf: nominal
human activity scale: measurement
amount of light: ranked
. Whether you consider the quadrats to be a nominal variable is a gray area that we'll talk about later in the semester; you didn't get points off for omitting or including it. You did get points off if you considered the quadrats to be a measurement variable.

16. Two nominal variables, Mpi genotype, young vs. adult; total sample size greater than 1000: chi-square test of independence or G-test of independence. These are the actual numbers from a study I did for my Ph.D. dissertation; the results were so boring that their only use is for exam questions.

17. One nominal variable, raccoon vs. feces vs. cheese; total sample size less than 1000: exact test of goodness-of-fit .

18. Number of fireflies, measurement
sand particle size: measurement
percent of area that is bare sand: measurement
(because it's the percentage of the area, you're not counting individual grains and sorting them into sand vs. something else).
streetlight present or absent: nominal. Again, whether you consider the locations to be a nominal variable is optional.

19. Two nominal variables, HTPAP genotype, cancer vs. no cancer; total sample size less than 1000: Fisher's exact test of independence.

20. Behavior: measurement
Sugar amount: ranked
Age: measurement
If you explicitly said you measured the age in years, I accepted "nominal," since second graders might all be either 7 or 8. But any sensible biologist would measure the age of such young children in months or days, which would be a measurement variable.
Sex: nominal
Teacher: nominal. It would be important to treat the teacher as a nominal variable, just like you treat each location in question 11 and 13 as a nominal variable; because the teachers are rating the behavior, each teacher may have different results.

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