SAFMEDS Flashcards
A generic term describing the centre of a frequency distribution of observations, measured by mean, mode, and median.
Central tendency
A variable (that may or may not have been measured), other than the independent variable/s, which influences the outcome of the dependent variable
Confounding variable
Evidence that the content of a test corresponds to the content of the construct it was designed to cover.
Content validity
A measure of the strength and direction of the association between two variables. There are two common variants- Pearson’s for parametric data, and Spearman’s for non-parametric data. In both cases, coefficients range between -1 and 1.
Correlation coefficient
A set of data which is yet to be screened for analysis.
Raw data
A test using the t-statistic that establishes whether two means collected from the same sample differ significantly.
Repeated measures/within subjects t-test
A test using the t-statistic that establishes whether two means collected from independent samples differ significantly.
Independent samples/between subjects t-test
Evidence that the results of a study, experiment, or test can be applied, and allow inferences, to real-world conditions.
Ecological validity
The prediction that there will be an effect (ie, that an experimental manipulation will have some effect on the dependent variables, or that certain variables will relate to each other).
Experimental hypothesis
The reverse of the experimental hypothesis- that there will be no effect from your experimental manipulation, or that certain variables are not related.
Null hypothesis
The degree to which a statistical model is an accurate representation of the observed data. These range from basic models (eg, the mean) to more complex models (eg, t-test and correlations).
Fit
A graph plotting values of observations on the Y axis, and the frequency with which those values occur on the X axis, commonly called a histogram. Used to assess the distribution of data.
Frequency distribution
An assumption for parametric testing in between-groups designs, where the variance of one variable is stable (roughly equal) at all levels of another variable.
Homogeneity of variance
A prediction about the state of the world.
Hypothesis
An experimental design in which different treatment conditions use different participants, resulting in independent data.
Independent design
An experimental design in which different treatment conditions use the same participants, resulting in related or repeated data.
Repeated design
Data measures on a scale along which all intervals are equal, for example pain ratings on a scale of 1 to 10.
Interval data
Interval data, with the additional property that ratios are meaningful. For example, when assessing pain on a scale of 1 to 10, for the data to be considered ratio level, a score of 4 should genuinely represent twice as much pain as a score of 2.
Ratio data
Data where numbers represent categories or names.
Nominal data
Data that tell us not only that something occurred, but the order in which it occurred. Examples include data presented as ranks, for example placements on participants in a race.
Ordinal data
Measures the degree to which scores cluster at the tails of a frequency distribution; positive kurtosis indicates too many scores in the tails, resulting in a peaked curve. Negative kurtosis indicates too few scores in the tails, resulting in a flattened curve.
Kurtosis
The probability of obtaining a set of observations given the parameters of a model fitted to those observations.
Likelihood
A non-parametric test which examines differences between two independent samples. The non-parametric equivalent of an independent t-test
Mann-Whitney test
A simple statistical model on the centre of a distribution of scores; a hypothetical estimate of a ‘typical’ score, calculated by summing the observed scores and dividing by the number of observations (n).
Mean