1 / 13

PSYC512: Research Methods Lecture 9

PSYC512: Research Methods Lecture 9. Brian P. Dyre University of Idaho. Lecture 8 Outline. Exam Next Week Will cover all lecture material, all material in Howell Chapters 1-5, broad concepts assumptions from Howell Chapters 6-11 What do I mean by “broad concepts?”

leo-gentry
Download Presentation

PSYC512: Research Methods Lecture 9

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. PSYC512: Research MethodsLecture 9 Brian P. Dyre University of Idaho PSYC512: Research Methods

  2. Lecture 8 Outline • Exam Next Week • Will cover all lecture material, all material in Howell Chapters 1-5, broad concepts assumptions from Howell Chapters 6-11 • What do I mean by “broad concepts?” • which tests are associated with which types of scaling properties of variables? • What variants of the tests exist and why? • What assumptions underlie the test? • Questions about material covered in Lecture 8 • Describing Data • The Normal Distribution • Testing Hypotheses • Inferential Statistics PSYC512: Research Methods

  3. Review: The Normal Distribution • What is the difference between a normal distribution and a standard normal distribution? • What is the difference between a raw score and a standardized score? • What are confidence intervals? PSYC512: Research Methods

  4. Testing Hypotheses • Hypothesis testing is the process by which hypothetical relationships between intervening variables are assessed • Hypotheses are always tested relative to one-another or to a “null” hypothesis • Examples • Comparing groups • Assessing performance interventions • Assessing relationships between variables PSYC512: Research Methods

  5. Null-Hypothesis Testing and Inferential Statistics • 2 possible realities • Relationship between your variables does not exist—a null relationship (Ho, the null hypothesis) • Relationship between the two variables in question actually exists (H1, the experimental or alternative hypothesis) • 2 possible decisions when looking at the data • Conclude that a relationship exists (reject the null hypothesis, Ho  DISCONFIRMATION!) • Conclude that no relationship exists (do not reject the null hypothesis  CONFIRMATION? NO!) PSYC512: Research Methods

  6. Null-Hypothesis Testing and Inferential Statistics True State of the World 2 realities by 2 decisions form a 2 x 2 matrix of 4 possibilites Decision PSYC512: Research Methods

  7. Null-Hypothesis Testing and Inferential Statistics 1 Population • Why might we observe a difference between two groups if no difference actually exists (null is true; samples are drawn from the same population)? • Each sample may have a unique mean due to sampling error Frequency m 2 samples Frequency PSYC512: Research Methods

  8. Null-Hypothesis Testing and Inferential Statistics 2 Populations • How does this change if a difference actually exists between my groups? • Each sample has a unique mean that represents both sampling error and the differences between the 2 populations Frequency m1 m2 Frequency PSYC512: Research Methods

  9. Hypothesis Testing: Probability and Statistics • Problem: How do we distinguish real differences or relationships from measurement noise? • Probability and statistics may be used to assess (descriptive statistics) or compare (inferential statistics) the relative magnitude of different types of variability • Effect (treatment) Variance • Variability due to relationship between variables or effect of different levels of independent variable (treatments) • “Good” variance that we want to maximize • Error Variance • Variability in measure due to factors other than the treatment • “Bad” variance that we want to minimize PSYC512: Research Methods

  10. Hypothesis Testing: Inferential Statistics • All inferential statistics are evaluating this ratio: Effect (good) Variance Test statistic = -------------------------------------- Error (bad) Variance • Example test statistics: Chi-square, t, F • These test statistics have known distributions that then allow us to estimate p, the probability of a Type I error (inappropriately rejecting the null hypothesis) • Decision to reject null is made by comparing p to some generally accepted criterion for Type I error probability, a = .05 PSYC512: Research Methods

  11. How is the probability of a Type I error, p, calculated? It depends on… • Scaling properties of your dependent variable (DV) • DV is interval or ratio parametric tests • DV is nominal or ordinal non-parametric tests • Research design • Experimental – test differences on measure between conditions or groups  t-test, ANOVA, sign test, Mann-Whitney • Correlational – test relations between different measures  Pearson product-moment correlation, point-biserial correlation, etc. • Manner in which you phrase your hypotheses • One tailed vs. two-tailed tests PSYC512: Research Methods

  12. Examples? PSYC512: Research Methods

  13. Next Time… • Topic: Review of broad concepts related to power, Chi-square, t-tests, and correlation • Be sure to: • Review Howell chapters 6-10 • Bring questions! • Continue searching and reading the scientific literature for your proposal PSYC512: Research Methods

More Related