Final exam study guide: Practice exam 4 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. One measurement variable, insulin sensitivity index; one nominal variable, genotype (individual is not a nominal variable because only one measurement per individual); one-way anova
  2. Because the slopes are different, whether there's a difference in fat content between males and females depends on their weight
  3. Two nominal variables, position of treat, caught or not; total sample size less than 1000: Fisher's exact test
  4. One nominal variable, cell type; one measurement variable, fluorescence: two-sample t-test or one-way anova
  5. One measurement variable, length; two nominal variables: temperature (nominal because just two values), tank (because multiple snail eggs per tank); each tank found in only one temperature: nested anova
  6. One nominal variable, fertilized vs. unfertilized; two measurement variables, number of walnuts, diameter of tree: ancova
  7. Two measurement variables, number of apples eaten, number of doctor visits:a correlation/linear regression
  8. One measurement variable, amount of mRNA for MPI; one nominal variable, normal vs. cancer: two-sample t-test or one-way anova
  9. One measurement variable, distance from black walnut tree; one nominal variable, damaged vs. undamaged leaf; if there's a cause-and-effect relationship, distance affects leaf damage: simple logistic regression
  10. Two measurement variables, length of ulna and size of flexion/extension moment arm: correlation/linear regression/correlation
  11. One nominal variable, red vs. green; theoretical expectation of 1:1 ratio if null is true; sample size less than 1000: exact test of goodness-of-fit
  12. One measurement variable, arsenic concentration; one nominal variable, Halomodadaceae or not; if there's a relationship, arsenic concentration affects the proportion of Halomondadaceae: simple logistic regression
  13. One measurement variable, corn borers per quadrat; one nominal variable, crop type: one-way anova
  14. One measurement variable, time until first gull arrives; one nominal variable, food type: one-way anova or two-sample t-test
  15. One measurement variable, sodium level; two nominal variables, cell line, gramicidin or no gramicidin; each cell line in combination with gramicidin or no gramicidin; multiple measurements per combination: two-way anova with replication
  16. One measurement variable, projection length; three nominal variables, challenged vs. unexposed, embryo, pigment cell: nested anova..
  17. One nominal variable, right vs. left, theoretical expectation of 50:50 ratio, total sample size greater than 1000: chi-square test of goodness-of-fit or G-test of goodness-of-fit.
  18. Two nominal variables, genotype and cancer type, total sample size greater than 1000: chi-square test of independence or G-test of independence.
  19. Three measurement variables, vigilant vs. not vigilant, edge vs. interior, 11 different flocks: Cochran-Mantel-Haenszel test
  20. Two measurement variables, shear modulus and range-of-motion; one nominal variable, injury type; goal is to compare different regression lines of shear modulus vs. range of motion: ancova
  21. One measurement variable, running speed; two nominal variables, food type and mouse identity (since there are multiple measurements per mouse); each mouse has only one food type: nested anova
  22. One measurement variable, maze time; two nominal variables, mouse identity and blindfold/noseplug/normal; each mouse in combination with each condition, run 5 times: two-way anova with replication
  23. One measurement variable, time (since you sample from 11 months); one ranked variable, taste: Spearman rank correlation
  24. One measurement variable, latitude; one nominal variable, right vs. left-handed; if there's a relationship, latitude affects handedness, handedness doesn't affect latitude: simple logistic regression
  25. One measurement variable, weight of pollen; two nominal variables, orchard type, hive identity (since you have multiple measurements per hive): nested anova
  26. Three measurement variables, age, weight, and height; one nominal variable, defective vs. normal sperm: multiple logistic regression..
  27. Two nominal variables, embryonic vs. adult stem cells, cartilage vs. undifferentiated; total sample size greater than 1000: chi-square test of independence or G-test of independence. Note that because you start with 750 undifferentiated cells and count how many cells differentiated into cartilage cells, you know (by subtraction) how many cells didn't differentiate into cartilage.
  28. One measurement variable, foot length; one ranked variable, penis length: Spearman rank correlation
  29. One measurement variable, speed; two nominal variables, time of testing and identity of snail (since there are multiple measurements per snail); one measurement per snail/time combination:Two-way anova without replication.
  30. Three measurement variables, salinity, temperature, and taste: multiple linear regression.

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