Central tendency

Question 1

Central tendency

Answer 1

A generic term describing the centre of a frequency distribution of observations, measured by mean, mode, and median.

Question 2

Confounding variable

Answer 2

A variable (that may or may not have been measured), other than the independent variable/s, which influences the outcome of the dependent variable.

Question 3

Content validity

Answer 3

Evidence that the content of a test corresponds to the content of the construct it was designed to cover.

Question 4

Correlation coefficient

Answer 4

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.

Question 5

Raw data

Answer 5

A set of data which is yet to be screened for analysis.

Question 6

Repeated measures/within subjects t-test

Answer 6

A test using the t-statistic that establishes whether two means collected from the same sample differ significantly.

Question 7

Independent samples/between subjects t-test

Answer 7

A test using the t-statistic that establishes whether two means collected from independent samples differ significantly.

Question 8

Ecological validity

Answer 8

Evidence that the results of a study, experiment, or test can be applied, and allow inferences, to real-world conditions.

Question 9

Experimental hypothesis

Answer 9

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).

Question 10

Null hypothesis

Answer 10

The reverse of the experimental hypothesis- that there will be no effect from your experimental manipulation, or that certain variables are not related.

Question 11

Fit

Answer 11

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).

Question 12

Frequency distribution

Answer 12

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.

Question 13

Homogeneity of variance

Answer 13

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.

Question 14

Hypothesis

Answer 14

A prediction about the state of the world.

Question 15

Independent design

Answer 15

An experimental design in which different treatment conditions use different participants, resulting in independent data.

Question 16

Repeated design

Answer 16

An experimental design in which different treatment conditions use the same participants, resulting in related or repeated data.

Question 17

Interval data

Answer 17

Data measures on a scale along which all intervals are equal, for example pain ratings on a scale of 1 to 10.

Question 18

Ratio data

Answer 18

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.

Question 19

Nominal data

Answer 19

Data where numbers represent categories or names.

Question 20

Ordinal data

Answer 20

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.