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Statistics for PT
NPTE Research & EBP
|Measures of central tendency
|mean, median, mode
|average of all scores
|midpoint of all scores
|most frequently occurring score
|mean is appropriate for what data types?
|median is appropriate for what data types?
|mode is appropriate for what data types?
|Measures of variability
|range, standard deviation, normal distribution, percentiles & quartiles
|difference between highest and lowest score
|variability of scores from the mean. most frequently used
|How to calculate SD
|subtract each score from mean, square each difference, add up all squares, divide by number of scores
|symmetrical bell shaped curve indiecating distribution of scores. Mean/median/mode all similar.
|allow determination of how likely results can be generalized to a population
|Standard error of measurement
|an estimate of expected errors in a score, measure of response stability or reliability
|Tests of significance
|estimation of true differences not due to chance, rejection of null hypothesis
|probability level - reselected level of statistical significance. Most commonly .05 or .01 (.05= only 5x out of 100 is the difference due to chance)
|Degrees of freedom
|based on # of subjects and groups, allows determination of level of significance
|result of sampling error, expected chance variation among the means
|Type 1 error
|Null hypothesis rejected when it is true.
|Type 2 error
|Null hypothesis is not rejected when it is false. means concluded to be due to chance when truly different
|How to decrease type 1/2 errors
|increase sample size, random selection, valid measures
|Interval or Ratio data
|Assumptions for parametric statistics
|normal distribution (usu large representative samples this is met), random sampling performed, variance in groups is equal
|parametric test of significance used to compare 2 independent groups created by random assignment and ID difference at a selected probability level
|T-test for independent samples
|compares 2 independent groups
|T-test for paired samples
|compares 2 matched samples (does therapy incr fxn in siblings with autism)
|based on directional hypothesis. Evaluates differences in data on only one end of distribution (neg or pos)
|based on a nondirectional hypothesis. Evaluates differences in data on both ends of a distribution. Tests of signif are almost always two-tailed
|Inappropriate use of T-test
|use to compare more than 2 means within a single sample.
|parametric test used to compare 3 or more independent tx groups at a selected probability level.
|Simple (one-way) ANOVA
|compares multiple groups on a single IND variable. Ex: Balance Master score for 3 different age groups
|compares multiple groups on two or more IND variables. Ex: 3 levels of ankle injury compared for balance and sensory
|Parametric test used to compare 2 or more treatment groups or conditions while also controlling for the effectss of intervening variables.
|ORDINAL or NOMINAL data, testing not based on population parameters
|When to use nonparametric
|parametric assumptions cannot be met. used with small sample, ordinal or nominal level data. Less powerful than parametric
|Chi square test
|nonparametric test of significance. Used to compare data in the form of frequency counts in 2 or more mutually exclusive categories (rate treatment preferences)
|used to determine the relative strength of a relationship between 2 variables
|Pearson product-moment coefficient (r)
|used to correlate CONTINUOUS data wi
|used to establish relationship between two variables as a basis of prediction
|NONPARAMETRIC test to correlate ORDINAL data.