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HTH 320 Final Exam Study Guide: Statistical Analysis Questions and Answers, Exams of Statistics

This comprehensive study guide provides a valuable resource for students preparing for their hth 320 final exam. it offers a range of questions and answers covering key statistical concepts, including hypothesis testing, anova, t-tests, chi-squared tests, effect sizes, and scales of measurement. The guide is particularly useful for reinforcing understanding of statistical procedures and their applications.

Typology: Exams

2024/2025

Available from 05/05/2025

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HTH 320: FINAL EXAM STUDY GUIDE QUESTIONS WITH
COMPLETE SOLUTIONS
what must you do when finding significance in ANOVA? -- Answer ✔✔ conduct post
hoc tests (Tukey’s)
what are the steps of hypothesis testing -- Answer ✔✔ 1. state the null and alternative
hypothesis
2. set criteria for decision
3. compute the test statistic
4. make a decision
degrees of freedom between groups for ANOVA -- Answer k (number of groups) -
1
degrees of freedom within groups for ANOVA -- Answer N (number of total
participants - k (number of groups)
effects size for one-sample ttest -- Answer ✔✔ cohen's D (number of standard
deviations an effect shifted above/below the population mean stated by null hypothesis)
=(M - mu)/population standard deviations
effect size for two-sample independent ttest -- Answer ✔✔ estimated cohen's D
(number of standard deviations an effect shifted above/below the population mean
stated by null hypothesis)
eta-squared (proportion variance)= (t^2)/(t^2 +df)
Omega-squared (more accurate proportion variance)= (t^2 -1)/(t^2 +df)
effect size for ANOVA -- Answer ✔✔ eta squared (proportion variance) (t^2)/(t^2 +df)
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HTH 320: FINAL EXAM STUDY GUIDE QUESTIONS WITH

COMPLETE SOLUTIONS

what must you do when finding significance in ANOVA? -- Answer ✔✔ conduct post hoc tests (Tukey’s) what are the steps of hypothesis testing -- Answer ✔✔ 1. state the null and alternative hypothesis

  1. set criteria for decision
  2. compute the test statistic
  3. make a decision degrees of freedom between groups for ANOVA -- Answer ✔✔ k (number of groups) - 1 degrees of freedom within groups for ANOVA -- Answer ✔✔ N (number of total participants - k (number of groups) effects size for one-sample ttest -- Answer ✔✔ cohen's D (number of standard deviations an effect shifted above/below the population mean stated by null hypothesis) =(M - mu)/population standard deviations effect size for two-sample independent ttest -- Answer ✔✔ estimated cohen's D (number of standard deviations an effect shifted above/below the population mean stated by null hypothesis) eta-squared (proportion variance)= (t^2)/(t^2 +df) Omega-squared (more accurate proportion variance)= (t^2 - 1)/(t^2 +df) effect size for ANOVA -- Answer ✔✔ eta squared (proportion variance) (t^2)/(t^2 +df)

2 - sample-independent ttest degrees of freedom -- Answer ✔✔ n- 2 f formula (regression) -- Answer ✔✔ f = (variance of Y related to changes of X)/(variance of Y not related to X) what happens when the Fobt is past the critical value? -- Answer ✔✔ reject null, determine that y is related to the changes in x standard error estimate -- Answer ✔✔ provides a measure of the typical distance between regression line and the actual data points (similar to standard deviation) (as it gets closer to - 1.00 or +1.00 the stronger the better the prediction is) what does r^2 mean? -- Answer ✔✔ the percent of variance of y that is explained by x (correlation coefficient) parametric tests -- Answer ✔✔ made assumptions about the shape and functioning of a given parameter (only with ratio/interval variables) nonparametric tests -- Answer ✔✔ a family of statistical procedures that do not rely on the restrictive assumptions of parametric tests. In particular, they do not assume that the sampling distribution is normally distributed. chi-squared test -- Answer ✔✔ a statistical procedure used to test hypotheses about the discrepancy between the expected values and observed values fe formula -- Answer ✔✔ fe = Np (sample size * proportion of expected) or (row total *column total)/ N chi-squared formula -- Answer ✔✔ sum of (observed-expected)^2/expected chi-squared degrees of freedom -- Answer ✔✔ number of categories (k) - 1 what is special about chi-squared? -- Answer ✔✔ it can be used to confirm null hypothesis is correct (goal is to retain null)

nominal -- Answer ✔✔ categorical in nature, does not imply order among responses (ex: how many siblings) ordinal -- Answer ✔✔ measurements that convey order and rank alone (ex: 1st, 2nd, and 3rd place) doesn't tell us about distance between levels interval -- Answer ✔✔ numerical scales in which the intervals have the same interpretation, no true zeros (ex: temperature; at 0 degrees there isn't a lack of temperature its just cold) ratio -- Answer ✔✔ (most informative) all the same properties as interval but there is a true zero (ex: money; you can have zero money)