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.**

- One measurement variable, years of football; one nominal variable, encephelopathy or not; if there's a cause-and-effect relationship, football causes encephalopathy:
**simple logistic regression** - One measurement variable, number of mosquitoes; two nominal variables, copper vs. no copper, identity of yard (because two observations of mosquito number in each yard):
**paired t-test or two-way anova without replication** - One measurement variable, number of calls; two nominal variables, color of stuffed bird, identity of live bird (live bird is a nominal variable because multiple measurements per bird); each live bird found in combination with each color of stuffed bird; one measurement per combination:
**two-way anova without replication** - One measurement variable, light amount; one nominal variable, interphase or not; if there's a relationship, light amount affects probability of being in interphase:
**simple logistic regression** **Decide on the rules that will determine which studies you will include in your meta-analysis.**- One measurement variable, distance from fluorescent corn field; one nominal variable, fluorescent or non-fluorescent pollen grain; if there's a cause-and-effect relationship, it's that distance affects percentage of pollen that are fluorescent:
**simple logistic regression** - One measurement variable, stoma size; two nominal variables, carbon dioxide concentration (nominal because just two values), individual stoma (because two measurements per stoma):
**paired t-test or two-way anova without replication** **Cancer cells could have a larger standard deviation, or you could have a smaller number of cancer cells.****Check the normality and homoscedasticity of C-reactive protein level.**- One nominal variable, right vs. left; theoretical expectation of 1:1 ratio if null is true; sample size is less than 1000:
**exact test of goodness-of-fit** - Two nominal variables, pupa on surface or side, mutation type; total sample greater than 1000:
**chi-square or G-test of independence** - Two measurement variables, warmup distance, speed in 100 meters; relationship is curved (question says fastest speeds at intermediate warmup distances):
**curvilinear regression** - One nominal variable (food type) and one measurement variable (appendix size), so the appropriate statistical test is a one-way anova; to compare one pair of categories in a one-way anova:
**Tukey-Kramer test** - One measurement variable, lens clarity; two nominal variables, identity of mouse, eyepatch vs. no eyepatch; multiple measurements per eye:
**two-way anova with replication** - One measurement variable, number of chloroplasts; one ranked variable, size of cell:
**Spearman's rank correlation** - One measurement variable, length of fish; one nominal variable, each scoop of the net:
**Fisher's one-way anova or Welch's one-way anova** - One nominal variable, type of cell; one measurement variable, fluorescence intensity:
**Fisher's one-way anova, Welch's one-way anova, Student's two-sample t-test or Welch's two-sample t-test** - Three measurement variables, miles run, age, and weight; one nominal variable, osteoarthritis or not:
**multiple logistic regression** - One measurement variable, blood pressure; two nominal variables, before and after Frogger, identity of person; each person in combination with before and after; multiple measurements for each combination:
**two-way anova with replication** - Two nominal variables, spot that is stared at, identity of person; each person stares at each spot; only one measurement for each combination of person with spot:
**two-way anova without replication** **Culture medium has a significant effect on cell growth, cell line does not have a significant effect, and the effect of culture medium is not different for different cell lines.**- Two nominal variables, moisture amount (nominal because just two values), alive or dead; total sample size less than 1000:
**Fisher's exact test.**Note that even though you only count the number of live flies, you started with 50 eggs, so you know how many flies died. - One measurement variable, leaf length; one nominal variable, identity of tree:
**Fisher's one-way anova or Welch's one-way anova** - One measurement variable, uvula length; one nominal variable, professional vs. church vs. non-singers:
**Fisher's one-way anova or Welch's one-way anova** - Two nominal variables, magnet on or off, quadrant; total sample size over 1000:
**chi-square or G-test of independence** - One measurement variable, jump length; one nominal variable, baby or not:
**Fisher's one-way anova, Welch's one-way anova, Student's two-sample t-test or Welch's two-sample t-test** - One measurement variable, income; one ranked variable, dental condition:
**Spearman's rank correlation** - One measurment variable, number of oranges; one nominal variable, tree type:
**Fisher's one-way anova or Welch's one-way anova** **Beta (or power, which is 1-beta; don't say beta AND power); standard deviation of polar bear weight**- One nominal variable, dead or alive; four measurement variables, age, height, weight, time; if there's a cause-and-effect relationship, the meaasurements affect survival:
**multiple logistic regression**