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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
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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.
Distinguishing Characteristics • Case Study • Experimental Design • Descriptive Design • Quasi-Experimental Design • Correlational Design • Causal Comparative Design • Qualitative Design
Validity • Validity • Does it measure what it is supposed to measure? • Study • Quantitative • Qualitative • Instrument • Score
Reliability • Measurement Error • (inverse relationship) • Causes • Wording • Administration • Grading • Coefficients – 0 - 1 • Test retest, split half, alternate forms etc.
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.
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)
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.
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
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
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.
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
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
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).
Correlation • Descriptive stat. • Strength of the relationship between two variables • Inferential stat. • Test the hypothesis, “there is no relationship between variables”
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
Secondary Analysis – must have criteria for selection • Meta-analysis • Difference in means/ s of control • Effect size • (.33-.5 for “practical significance) • Vote Counting