1 / 20

Discuss the three points from your response to the first slide with your neighbor.

Write down the three most interesting/important points/concepts/construct from today’s reading assignment. Discuss the three points from your response to the first slide with your neighbor. Review. Distinguishing Characteristics. Case Study Experimental Design Descriptive Design

diane
Download Presentation

Discuss the three points from your response to the first slide with your neighbor.

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. Write down the three most interesting/important points/concepts/construct from today’s reading assignment.

  2. Discuss the three points from your response to the first slide with your neighbor.

  3. Review

  4. Distinguishing Characteristics • Case Study • Experimental Design • Descriptive Design • Quasi-Experimental Design • Correlational Design • Causal Comparative Design • Qualitative Design

  5. Validity • Validity • Does it measure what it is supposed to measure? • Study • Quantitative • Qualitative • Instrument • Score

  6. Reliability • Measurement Error • (inverse relationship) • Causes • Wording • Administration • Grading • Coefficients – 0 - 1 • Test retest, split half, alternate forms etc.

  7. Hypothesis • Directional – Method A is better than method B. • Can show A is better • Can show A is not better • Null – there is no significant difference between ….. • Can show control condition is better • Can show experimental treatment is better • Can show there is no significant difference.

  8. p value • The percentage of occasions that a chance difference between mean scores of a certain magnitude will occur when the population means are identical • (Gall, Gall, & Borg, 1999, p 159)

  9. Two-tailed t tests • Use a two tailed t test for null hypothesis • Use a one tailed t test for directional hypothesis • If you select P< .05 for two tailed you would compare calculated value with the chart at .025 because the result could show the independent variable to be better or worse.

  10. Directional Research HypothesisHypothesis – A will be significantly greater than B (P < .05) 95% Reject Region 5% Accept Region B bigger __________________ Difference ________________ A BiggerA smaller B smaller Null HypothesisHypothesis – There will be no significant difference between the means of A & B (P < .05) 95% Accept Region(no significant difference) 2.5% Rejection Region 2.5% Rejection Region B bigger __________________ Difference ________________ A BiggerA smaller B smaller

  11. Control 27 27 29 26 28 31 27 27 27 32 32 28 34 31 29 31 29 28 28 26 29 31 29 2 2 2 2 2 3 2 2 2 3 3 2 3 3 2 3 2 2 2 2 2 3 2 Experimental 28 25 29 26 26 30 31 25 29 32 29 30 31 30 29 30 28 30 31 29 27 30 29 2 2 2 2 2 3 3 2 2 3 2 3 3 3 2 3 2 3 3 2 2 3 2 Quality of Data Fall Reading Scores

  12. Parametric • The t test – compare two means • df = n-1 • Larger df (sample size) more normal the distribution (assumed) • P 446 Table B • Analysis of Variance (ANOVA) • One Way comparing more than two means • Two Way – Comparing more than one set of variables – looking for interactions • Uses F value • Uses a Tukey’s or Scheffe’s to determine which are significantly different.

  13. When using cluster sampling if groups are not equivalent - • Gain scores • Ceiling effect is can be a problem • ANCOVA • Uses F value • Must have a pre-test or other measure to use as a covariate • Matched Pair Study

  14. Non-Parametric Non-parametric normal distribution and equal interval cannot be assumed. not interval data (categorical/nominal, rank/ordinal??, sample size is small) • Tests • Chi Square Mann-Whitney U Wilcoxon sign-rank

  15. Errors we can make in research • Type I error • We reject the null hypothesis when the null hypothesis is true. • We said method “a” was better (or worse) when it was not • Type II error • We accept the null hypothesis when the null hypothesis is false. • We said that method “a” was not better (or worse) when it really was better (or worse).

  16. Correlation • Descriptive stat. • Strength of the relationship between two variables • Inferential stat. • Test the hypothesis, “there is no relationship between variables”

  17. Correlation • Bivariate • r range from +1 to -1 • Strength of relationship between two variables. • Multivariate • Determine which multiple variables predict another variable (criterion). • ACT scores, SAT scores, high school class rank, high school GPA as predictors of success in college

  18. Secondary Analysis – must have criteria for selection • Meta-analysis • Difference in means/ s of control • Effect size • (.33-.5 for “practical significance) • Vote Counting

More Related