11) Ch11: Data Analysis Flashcards
Descriptive Stats
Used to summarize patterns/characteristics in the data to describe the distribution of data points
- Include sum, mean, mode, standard deviation, and frequency of nominal variables
- Typically performed on all measured/recorded variables in a study
Correlative Statistics
Used to calculate how variables are similar or relate to each other/ Strength of relationships btwn variables
- Includes Pearson Product Moment Correlation Coefficient, ICC, Spearman Rank Correlation Coefficient
Pearson Product Moment Correlation Coefficient
Used to determine if the scores of 2 variables vary together
ICC
Used to determine if the scores of 2 variables vary together and how closely those scores are matched
Spearman Rank Correlation Coefficient
Used to determine if the scores of 2 variables of ordinal data vary together
- Same as Pearson except used w/ordinal data
Comparative Stats
Used to compare 2+ sample groups on 1+ measured attributes; Describe how variables are different; Determine whether 2+ groups of data are different and suggest cause-and-effect relationships between an intervention and an outcome
- Includes t-tests, ANOVA, ANCOVA, MANOVA (Parametric), Mann-Whitney U Test, and Wilcoxen Signed-Ranks Test(Nonparametric)
Independent T-Test
Compares the means of 2 groups in which there aren’t any repeated measures
- Assumes a normal distribution of the sample and random selection & assignment
Paired T-Test
Compares the means of 2 repeated measures from the same sample group or from matched pairs of subjects
ANOVA
Compares the means of 3+ groups on a single measure or 3+ repeated measures on the same group
ANCOVA
Compares the means of 2+ groups on 2 measures or repeated measures on 2+ groups
MANOVA
Compares 3+ independent variables
Mann-Whitney U Test
Compares the rank order of scores from 2 groups on an independent variable
Wilcoxen Rank Sum Test
Compares the rank order of scores from 2 groups on an independent variable w/sample sizes <30 subjects
- Same as Mann-Whitney but used for sample sizes <30 subjects
Kruskal-Wallis ANOVA
Compares rank or ordinal data from 3+ groups
Clinical Significance
Differences in the measured variable that result in useful changes