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