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| a genetic term describing the centre of a frequency disribution of observations measured by mean, median and mode |
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| A variable that may or may not have been measured, other than the independent variable which influences the outcome of the dependent variable |
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| Evidence that the content of a test corresponds to the content of the construct it was designed to cover |
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| A measure of strength and direction of the association between two variables. |
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| A set of data that is yet to be screened for analysis |
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| Repeated measure/within a subject t-test |
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| A test using the t-statistic that establishes whether two means collected from the same sample differ significantly |
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| Independent sample between subjects t test |
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| A test using the t statistic that establishes whether two means cllected from independent samples differ significantly |
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| refers to how the results produced from a study can be applied and generalised to real-life conditions |
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| the prediction that there will be an effect. The experiment manipulation of one variable will have some effect on the dependent variable or that certain varibles will relate to each other |
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| The reverse of the experimental hypothesis- that there will be no effect from your experimental manipulation, or that certain variables are not related. |
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| The degree to which a statistical model is an accurate representation of the observed data.Basic models- mean median mode. Complex models- correlation, t-test. |
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| 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. |
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| An assumption of parametric testing in between-group designs, where the variance of one variable is stable at all levels of another variable. |
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| A prediction about the state of the world |
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| An experimental design in which different treatment conditions use different participants, resulting in independent data. |
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| An experimental design in which different treatment conditions use the same participants, resulting in related or repeated data. |
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| Data measures on a scale along which all intervals are equal, for example, pain ratings on a scale of 1 to 10. |
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| 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. |
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| Data where numbers represent categories or names |
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| 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. |
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measure the degree to which scores cluster at the tails of a frequency distribution. Positive kurtosis- too many scores in the tail, resulting in a peaked curve.
Negative Kurtosis- too few scores in the tail, resulting in a flattened curve |
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| the probability of obtaining a set of observations given the parameters of a model fitted to those observations |
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| a non-parametric test that examines the difference between two independent samples. The non-parametric version of a t-test |
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| A simple statistical model on the center 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). |
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| The middle score of a test of ordered observations |
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| The most frequently occurring score |
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| A family of statistical tests that do not rely on the restrictive assumptions for parametric tests. In particular, they do not assume sampling disribution is normal. Normally considered less powerful. |
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| A family of statistical tests that require data to meet most assumptions. In particular around the distribution of data and the inter-relation between variable levels. The basic assumptions are: data normally disributed, homogenecity of variance, interval or ratio data, independence of scores. |
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| In statistical terms, this refers to the group from which we draw a sample, and to which we want to generalise results. |
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| Extrapolating evidence for a theory from what people say and write (in contrast to quantitative methods). |
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| Inferring evidence for a theory through measurement of variables that produce numeric outcomes (in contrast to qualitative methods). |
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| A generic term for the three values that cut an ordered data set into four equal parts. The three sections are known as the lower, middle, and upper quartiles. The space between the lower and upper quartiles is known as the inter-quartile range. |
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| a smaller collection of units from a population, used to determine truths about population. (how a certain population behaves under certain conditions) |
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| An estimate of the average spread and variability in set of data, measures in the same unit as original data. It is the square root of the variance |
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| A measure of the symmetry of a distribution, with a skew of 0 representing perfect symmetry. When scores are clustered at the lower end of the distribution, the skew is positive. When scores are clustered at the higher end of the higher end of the distribution, the skew is negative. |
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| A statistic for which we know how frequently different values occur in random samples. The observed value of such a statistic is usually used to test a hypothesis. |
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| Evidence that a study allows correct inferences about the question it was designed to answer, or that a test measures what is set out to measure. |
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| An estimate of the average variability of a set of dT. It is the sum of the squares divided by the number of values on which the sum of the square is based, minus 1. |
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| Wilcox's signed-rank test. |
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| A non-parametric test that looks for the differences between a related t-test. |
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| The value of an observation expressed in standard deviation units, calculated by taking the observed score and subtracting the sample mean, then dividing the result by the standard deviation of all observations. Z-scores can be used to assess the likelihood of obtaining certain scores on a measure. |
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