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Review for Final Exam

Review for Final Exam. 2011, 12, 8. Important Dates. Today: All late HWK Due 5.12 (TR): Submit your project paper to Hauser 105 between 3:45-4:45. Final Exam 5.17 , 1:30 – 3:30, Hauser 28 & 30 Review sheet Formula sheet. Lecture Outline. When to use One-sample z -test

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Review for Final Exam

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  1. Review for Final Exam 2011, 12, 8

  2. Important Dates • Today: All late HWK Due • 5.12 (TR): Submit your project paper to Hauser 105 between 3:45-4:45. • Final Exam • 5.17, 1:30 – 3:30, Hauser 28 & 30 • Review sheet • Formula sheet

  3. Lecture Outline • When to use • One-sample z-test • One-sample t-test • Related-samples t-test, or • Independent-samples t-test? • One-way ANOVA • When to use • Pearson Correlation Analysis • Regression Analysis, or • Chi-square test?

  4. One-Sample z-Test • When the population mean () and Std. Dev. () are KNOWN, we use one-sample z-test to compare a single sample mean to the known population mean (). • Key: Look for Population Std. Dev. ()

  5. One-Sample t-Test • When the population Std. Dev. () is UNKNOWN, we use one-sample t-test to compare a single sample mean to the known population mean (). We use the sample standard deviation (S) to estimate the Std. Err. • Key: Look for Population Std. Dev. ()

  6. Related-Samples t-Test • Situation 1: When we want to compare two samples that representing two populations (e.g., women vs. men), and the two samples are related, we use related-samples t-test to exam if one population mean is greater/less/equal to the other population mean. • Situation 2: When we want to compare two set of scores collected from one sample, we use related-samples t-test to exam if posttest mean is greater/less/equal to pretest mean. • Key terms: • You must have two set of scores (two columns). • The two set of scores must relate to each other.

  7. Independent-Samples t-Test • When we want to compare two samples that representing two populations (e.g., women vs. men), and the two samples are independent, we use independent-samples t-test to exam if one population mean is greater/less/equal to the other population mean. • Key terms: • You must have two set of scores (two columns) • The two set of scores must from two independent samples

  8. One-Way ANOVA • When we want to compare three or more samples that representing correspondent populations (e.g., freshmen, sophomore, junior, and senior), we use one-way ANOVA to exam if at least one population mean is different from others. • Key terms: • You must have three or more sets of scores

  9. Pearson Correlation Analysis • When we want to examine the relationship between two CONTINUOUS variables, we conduct Pearson Correlation Analysis. • Key term: • You are examining a relationship. • You have “continuous” variables

  10. Regression Analysis • When we want to use one variable to predict the value of another variable, we compute the regression equation for the best-fitting line. • Key terms: • Predict • Predictor (X) • Criterion (Y)

  11. Lecture Summary • When to use • One-sample z-test • One-sample t-test • Related-samples t-test, or • Independent-samples t-test? • One-way ANOVA • When to use • Pearson Correlation Analysis • Regression Analysis

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