### Final exam study guide: Practice exam 1 answers

Here are the answers to practice exam 1. The answer is in bold; my explanation, which you don't need to write on the exam, is in regular type.

Where two correct answers are shown for these practice questions (such as chi-squared or G-test of independence), you must only write down one on the actual exam.

1. With a larger sample size, the standard deviation may be smaller or larger; standard error will be much smaller.
2. Two nominal variables, age (nominal because just two categories, first-grade and about 80) and handedness; sample size greater than 1000: chi-squared or G-test of independence.
3. Two nominal variables, sex of dog, sex of owner; sample size less than 1000: Fisher's exact test
4. One nominal variable, birthplace; one ranked variable, dominance: Kruskal-Wallis test
5. One measurement variable, heart rate; two nominal variables, before and after training, person (person is a nominal variable because you take two measurements from each person): Paired t-test or two-way anova without replication
6. See if the data are normal and homoscedastic
7. One nominal variable, mounting from right or left; theoretical expectation of 50:50 ratio; sample size less than 1000: exact test of goodness-of-fit
8. The significant interaction term tells you that the effect of food on speed is different in males than in females
9. One measurement variable, quadriceps strength; two nominal variables, sex and torn vs. untorn ACL: two-way anova with replication
10. One measurement variable, HDL; two nominal variables, before vs. after, person (person is a nominal variable because you take two measurements from each person): paired t-test or two-way anova without replication
11. Two nominal variables, Montana vs. Alberta, black vs. grizzly; sample size less than 1000: Fisher's exact test
12. Two measurement variables, weight and alcohol intake; nothing in the question suggests a curved relationship: correlation/linear regression
13. Two measurement variables, weight and alcohol intake; one nominal variable, extracurricular activity: ancova
14. Two measurement variables, tryptophan (measurement because more than 5 values), time awake: correlation/linear regression
15. Two measurement variables, prostate size, age; one nominal variable, steroid vs. no steroid: ancova
16. One measurement variable, barkiness; one nominal variable, litter (individual is not a nominal variable, because only one measurment of barkiness per dog): Fisher's one-way anova or Welch's one-way anova
17. One nominal variable, genotype; theoretical expectation of 1:3:3:9 ratio; total sample size greater than 1000: chi-squared or G-test of goodness-of-fit
18. One nominal variable, presence or absence of both parasites; theoretical expectation of 1/6 present, 5/6 absent; total sample size greater than 1000: chi-squared or G-test of goodness-of-fit
19. One measurement variable, melanopore index; three nominal variables: predator; tank (because more than one fish per tank); individual killifish (because more than one measurement per fish); each tank found with only one predator, each fish found with only one tank: nested anova
20. One measurement variable, nitrogen fixation rate; one nominal variable, site (flask is not a nominal variable because only one mesurement per flask): Fisher's one-way anova or Welch's one-way anova
21. One measurement variable, number of colonies; two nominal variables, bacterial species, detergent type; each species found with each detergent type; more than one measurement for each combination of species and detergent: two-way anova with replication
22. One dependent measuremnt variable, lifespan; two independent measurement variables, exercise time and food consumption: multiple linear regression
23. One measurement variable, light reflectance; two nominal variables, background, and individual crab (because two measurements per crab: paired t-test or two-way anova without replication
24. One measurement variable, catabolic activity; two nominal variables, clonal strain, and line (line is a nominal variable because three measurements per line); each line found in only one strain: nested anova
25. One measurement variable, tryptophan amount (measurement because more than 5 values); one nominal variable, asleep or awake; if there's a relationship, tryptophan affects the probability of falling asleep: : simple logistic regression
26. Two measurment variables, age and running speed; question implies that relationship is curved (fastest at intermediate ages, slower at younger and older ages): curvilinear regression
27. One nominal variable, vegetarian vs. carnivore; one ranked variable, order falling asleep: Kruskal-Wallis test
28. Two measurement variables, fertilizer amount, number of tomatoes; question implies the relationship is curved (most tomatoes at intermediate fertilizer): curvilinear regression
29. One dependent measurement variable, speed; two independent measurement variables, length and weight: multiple linear regression
30. One nominal variable, back or feet; theoretical expectation of 1:1 ratio; sample size less than 1000: exact test of goodness-of-fit

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