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Full book glossary Flashcards

1
Q

Interval variable

A

A variable where the values are numerical and where differences between values are consistent across the range of values

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2
Q

Axes

A

The horizontal and vertical scales of a graph (see x-axis and y-axis)

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3
Q

Unique effect size

A

The result of ANOVA analysis. A measure of the effect of each IV on the DV which discards all overlapping covariation. The unique effect size is the contribution made by an IV to a DV that is not made by any other measured IV

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4
Q

Confidence interval

A

A range of values that a particular statistical value is believed to fall within at a specified level of confidence e.g. 95%

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5
Q

Inter-quartile range

A

Measure of dispersion used typically for ordinal data; the range of values in the middle two quadrants of a data set

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6
Q

Maximum likelihood

A

A value of an estimated parameter (mean, coefficient etc.) that has the highest likelihood making it the most likely value

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7
Q

Association

A

Neutral word to describe a relationship

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8
Q

Direct effect size

A

The effect size in a linear model between an IV and a DV. It shows how much the DV is changed by a change in the IV

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9
Q

Extraneous variable

A

An unwanted variable that may be influencing a DV

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10
Q

Model effect size

A

Effect size of the whole model on the DV

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11
Q

Confirmatory research

A

Research designed to test a specific hypothesis

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12
Q

ANOVA

A

Analysis of Variance, type of statistical test that splits variance of DV into its various sources

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13
Q

Covariance

A

A measure of the joint variability between two variables

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14
Q

Scale

A

A common way of using numbers to describe quantities. The use of cm to describe the length of things is an example. Other scales can be used for the same purpose (inches, cubits). Scales specify how much the quantity involved must be changed to increase its value by a certain amount

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15
Q

Nominal variable

A

Another term used for Categorical variables

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16
Q

Outlier

A
  1. Authors of new, alternative statistics textbooks
  2. Also used to describe data points that appear not to belong to the population being studied, either randomly occurring or due to research error
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17
Q

Categorical variable

A

Variable where data is divided into labelled groups (categories); there is no order to the groups

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18
Q

Likert scale

A

Ordinal self-report scale used for responses to questions, often with agree – neutral – disagree options

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19
Q

Linear

A
  1. Used to describe relationships where both variables plotted together form a straight line
  2. Also used to describe combinations of variables by addition
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20
Q

Mediation

A

The possibility that the effect of an IV on a DV occurs through an intermediary (mediating) variable

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21
Q

Variable

A

Any way in which people/animals/situations differ

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22
Q

2-Tailed Test

A

Statistical test with no predicted effect size direction

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23
Q

Experimental study

A

Study which deliberately creates an independent variable, such as dividing participants into active and control groups

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24
Q

Variance

A

Measure of variability: spread of values, the square of the standard deviation

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25
Q

Order effects

A

Within-participants design issue where participants are influenced by experiencing one condition before another: can influence the IV and the DV

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26
Q

Idea

A

Any proposed relationship between variables, specific or otherwise

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27
Q

Uncertainty

A

In psychological research, uncertainty is how well (or not well) a sample parameter matches a population parameter

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28
Q

Discrete

A

A scale or a set of values are discrete if there are breaks or jumps in between them. Having group members labelled “person 1” and “person 2” uses discrete values as there is no “person 1½”

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29
Q

Contingency table

A

A table comparing expected and observed frequencies for a chi-square test

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30
Q

Type II error

A

False negative outcome; when the null hypothesis is not rejected, despite the population having an effect

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31
Q

Null hypothesis

A

The hypothesis that there is no effect in the population

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32
Q

Correlation coefficient

A

Effect size that measures the strength of a linear relationship on a normalized scale

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33
Q

Median

A

Measure of central tendency for Ordinal data, the middle value of a data set or halfway point between two central values

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34
Q

Non-parametric test

A

Statistical tests conducted on Ordinal or atypical data sets which don’t meet the requirements of parametric tests

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35
Q

Standard error

A

The standard deviation of the Sampling Distribution

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36
Q

Null hypothesis testing

A

Test used when looking for evidence to reject the null hypothesis

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37
Q

Likelihood

A

The relative chance that an event (like a sample) was caused by another event (like a specific population)

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38
Q

Variability

A

A term to describe the mount of differences between different people/animals/situations

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39
Q

Scatter plot

A

Type of graph with two continuous numeric variables plotted. Each data point is a single unconnected point in the graph

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40
Q

Opportunity sampling

A

Sampling strategy that uses any available group; no attempts to match a population or collect a random set of participants

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41
Q

Categories

A

The values of a categorical variable; also referred to as groups. Traits (e.g. blue eyes/brown eyes) or situations (before/after)

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42
Q

Path model

A

A model where variables are not as a simple split into predictors (IVs) and a response (DV) but are instead allowed to connect more freely

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43
Q

Mixed measures

A

Term used to describe an ANOVA where 1 or more variables are between-participants and 1 or more are within-participants

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44
Q

Likelihood function

A

A graph that shows the relative likelihood that a particular sample effect size came from a range of different population effect sizes

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45
Q

Residual

A

The difference between the expected value for an Interval DV and the actual value for one participant

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46
Q

AIC

A

Akaike Information Criterion. Value used to assess the fit of a model, typically by comparing models. Smaller is better

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47
Q

Natural effect size

A

An effect size measured in the same units as the DV

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48
Q

Type I error

A

False positive; the incorrect rejection of the null hypothesis

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49
Q

X-axis

A

Horizontal scale of a graph

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50
Q

Deviation

A

The difference between the value of a data point and the mean for that data set

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51
Q

Local mean

A

A theoretical concept where a set of values are divided into infinite small groups, and each group has its own mean, to generate a line of best fit

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52
Q

Logarithmic scale

A

A transformation that expands the amount of space given to small values and contracts the amount of space given to large values

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53
Q

Value

A

A specific description of a variable for one person or situation: e.g. ‘green’ for the variable eye colour, or ‘112’ for IQ score

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54
Q

Endogenous variable

A

A response variable, or dependent variable in a model

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55
Q

Interaction

A

A mechanism by which the effect of one IV on a DV depends on the value of another IV

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56
Q

Ordinal variable

A

A variable with ordered values, but no meaningful difference between values

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57
Q

Bar chart

A

Chart typically used to present frequencies of categorical data. Data illustrated using separated columns

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58
Q

Standard deviation

A

Measure of dispersion: based on the range of squared deviations from the mean. A small standard deviation indicates a small spread of values in a group

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59
Q

Parametric test

A

Standard null hypothesis statistical testing, typically between Interval and Categorical variables

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60
Q

Dispersion

A

The spread of a set of a values, often defined using the standard deviation or inter-quartile range

61
Q

Patchy coverage

A

A situation where the range of values obtained for a variable (usually an IV) does not cover the full possible range but instead has gaps

62
Q

Hypothesis

A

A specific and testable prediction including a description of expected effect

63
Q

Sample size

A

Number of participants recruited, commonly denoted with ‘n=’

64
Q

Observational study

A

Study that makes use of variables that already exist, as distinct from an experimental study where an experimental variable is created

65
Q

Marginal distribution

A

The distribution of values for a single variable – usually used in the context of a scatter plot of two variables

66
Q

Exogenous variable

A

A predictor or independent variable in a model that is not proposed to have any causes amongst the other variables

67
Q

Sum of squared deviations

A

A useful intermediate step in calculating means, standard deviations, regression and ANOVA

68
Q

Standardized effect size

A

An effect size system that uses the range zero to infinity. Standardized effect sizes do not depend on the scales used to measure variables: they use a standard scale

69
Q

Estimate

A

Logical guess based on known information

70
Q

Repeated measures

A

Term used to describe an ANOVA where both IVs use a within-participants design

71
Q

r-statistic

A

Normalised effect size ranging from -1 to +1, where 0 is no effect

72
Q

Mean

A

Measure of central tendency for Interval data, the value where the sum of squared deviations is smallest

73
Q

Statistically significant

A

Term given to results typically where p<0.05 (or other alpha)

74
Q

Contrast test

A

A modified version of a 1-tailed test where categorical data is converted to numeric data to allow a correlation

75
Q

Distribution

A

The whole set of values for a variable in a population or sample. Distributions are usually illustrated by showing the frequency of different values

76
Q

Inferential statistics

A

Statistics which use sample data to produce knowledge about a population and determine the uncertainty of that knowledge

77
Q

Confidence limits

A

The end values of the range of a confidence interval

78
Q

Between-participants

A

Design choice for categorical data, where participants each only experience one group of a categorical variable

79
Q

Replication

A

The process of repeating a piece of research, copying the original design as accurately as is possible. It is normal to increase the sample size to have more statistical power

80
Q

1-way ANOVA

A

Statistical test for Categorical IV and Interval DV

81
Q

Central tendency

A

The typical value used to summarise a set of values

82
Q

1-Tailed Test

A

Statistical test with a predicted effect size direction

83
Q

Count

A

See frequency

84
Q

General linear model

A

A statistical model where there is a set of predictors (IVs) whose added effects are thought to relate to the response variable (DV)

85
Q

Bivariate

A

Meaning two-variable

86
Q

Regression line

A

The straight line of best fit between two Interval variables. Best fit is usually assessed by minimizing the sum of squared deviations, and the regression line is then sometimes called the Least Squares fit

87
Q

Counterbalancing

A

A within-participants design measure which allows some participants to experience one situation first then the other, and the other participants to experience the situations in the opposite order. Controls for order effects

88
Q

Measurement error

A

The difference between the real value of some variable in a participant and the measured value

89
Q

Dependent variable (DV)

A

A variable that is treated as if its value may have been affected by the values of any other variables in a hypothesis. It is usually the variable we are trying to explain

90
Q

Publication bias

A

The tendency for journals and other publications to only report research which delivers statistically significant findings

91
Q

Sampling distribution

A

The distribution of expected sample effect sizes given a particular population and sampling design

92
Q

BESD

A

Binomial effect size display. Effect size that measures effects as comparison between expected and observed values

93
Q

Population

A

Everyone of interest in a piece of research: as big as everyone in the whole world, as small as any limited group chosen

94
Q

Skew

A

Asymmetric distribution with one long tail, either positive or negative

95
Q

Placebo

A

The non-specific effect of a treatment that arises purely because of participant expectations (e.g. sugar pills which cure headaches)

96
Q

Line graph

A

A graph where a sequence of values are shown as (usually but not necessarily) connected points

97
Q

Significance testing

A

See null hypothesis testing

98
Q

APA format

A

American Psychological Association format for presenting statistical results

99
Q

Sample effect size

A

Measured effect size of a sample: always certain, if the calculations are done correctly. But an uncertain estimate of the population effect size

100
Q

Sample

A

Set of participants recruited for a piece of research

101
Q

Stratified sampling

A

Recruitment strategy that attempts to match the frequency distribution of the population to create a representative sample

102
Q

Sampling error

A

The (usually unknown) difference between a sample estimate and the population value. It is usually unknown because we don’t usually have the population value

103
Q

Y-axis

A

Vertical scale of a graph

104
Q

Data analysis

A

Typically used to refer to the inferential stage of statistics

105
Q

Exploratory research

A

Research intended to investigate phenomena without prior expectations that might be confirmed or not

106
Q

Correlation

A

The strength of any linear relationship between two variables

107
Q

Dummy variable

A

Extra variables created to replace categorical variables. Dummy variables can be treated as numerical with values 0 and 1

108
Q

Omnibus test

A

A test that there is some effect in a set of data, without being more specific about where

109
Q

Logistic regression

A

A form of regression where the DV is Categorical and the regression line (which is usually S-shaped) gives the probability of the DV being one or other category as a function of the IV

110
Q

Moderator

A

Another term for interaction. One IV is said to moderate (change) the effect of another IV on a DV

111
Q

Regression

A

A process of measuring the quantitative effect of one or more Interval IVs on a DV

112
Q

Data

A

Information deliberately collected together to answer a question: quantitative, in the context of this book

113
Q

Effect size

A

A value used to quantify the strength of a relationship between variables

114
Q

Bias

A

A systematic (i.e. not random) difference between a sample and the population

115
Q

Pearson correlation

A

Test used to assess linear relationships between numeric variables

116
Q

Average

A

Also called a ‘typical value’; measure of central tendency. Single value which is used to summarise a set of values. Usually refers to the mean

117
Q

Non independence

A

Used to describe participants who are related in some way

118
Q

Mode

A

The most common value. A measure of central tendency useful especially for Categorical data (typically the biggest group)

119
Q

Constant

A

Any number that doesn’t change

120
Q

Square root

A

Any number to the power of ½. The square root of 9 is 3

121
Q

Statistical test

A

General term typically used to describe null hypothesis statistical testing

122
Q

Causation

A

The assumption that one variable affects another

123
Q

Alternative hypothesis

A

The hypothesis that makes the prediction that researchers are interested in. Not statistically tested

124
Q

Power analysis

A

Calculation based on predicted effect size to determine sample size that has 80% chance of producing a significant result (referred to as power)

125
Q

Normal distribution

A

Typically described as a ‘bell shaped curve’; a symmetrical smooth distribution where the mean, mode, and median are equal and at the peak of the curve

126
Q

Post-hoc

A

A specific test that is applied after an initial omnibus analysis has shown that there is an effect within the data. The post-hoc test is designed to establish where the effect lies

127
Q

Inference

A

Using statistics to produce knowledge about a population based on data from a sample; a conclusion that is always uncertain

128
Q

Alpha

A

Accepted criterion value of p for statistical significance, also chance of a Type I error. Most commonly used value is 0.05

129
Q

P-value

A

Probability value: the probability of the null hypothesis producing the same or a more extreme result. Used to determine statistical significance

130
Q

Descriptive statistics

A

Statistics used to describe a sample, to summarise and indicate patterns

131
Q

Research design

A

Decisions about sample, measurement, and data collection for research

132
Q

Random sampling

A

Sampling strategy where all members of a population have equal chance of being selected for a sample

133
Q

Covariation

A

Possible relationship between two different IVs

134
Q

t-statistic

A

Test statistic for the t-test. The t statistic is found by dividing an estimated value by its standard error

135
Q

Degrees of freedom

A

A measure of how much raw information remains in a sample after statistical calculations. Initially, the degrees of freedom equals the number of data points. When a mean is calculated, the degrees of freedom is reduced by one because the mean replaces that much raw information

136
Q

Model

A

A description of a pattern in some data. The model is then thought to capture important variability in the data

137
Q

Test statistic

A

Output of any statistical test: used traditionally as a halfway step for calculations of p and then significance when tests are done by hand

138
Q

Normalized effect size

A

An effect size measured on a scale from -1 to +1 (see r-statistic)

139
Q

Main effect

A

The independent effect of one IV on one DV

140
Q

Independent variable (IV)

A

Variable that is predicted to influence the DV. The IV is treated as independent of the DV

141
Q

Frequency

A

Relative commonness of a value of a variable: e.g. proportion of participants in one group

142
Q

Pooled standard deviation

A

Typical standard deviation of multiple groups, weighted by group size

143
Q

Probability

A

The chance that an event in the future will happen

144
Q

Within-participants

A

Research design for a Categorical IV where participants experience all groups of the IV

145
Q

Total effect size

A

The effect of one IV on a DV, disregarding any other variables

146
Q

Cronbach’s alpha

A

A measure of the consistency of responses to a set of questions about a common state or trait

147
Q

Coefficient

A

A ratio: how much change in a DV for a given change in an IV

148
Q

Latent variable

A

Any unmeasured variable: internal state or otherwise

Stats (3 decks)

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