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
2
Q
Axes
A
The horizontal and vertical scales of a graph (see x-axis and y-axis)
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
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%
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
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
7
Q
Association
A
Neutral word to describe a relationship
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
9
Q
Extraneous variable
A
An unwanted variable that may be influencing a DV
10
Q
Model effect size
A
Effect size of the whole model on the DV
11
Q
Confirmatory research
A
Research designed to test a specific hypothesis
12
Q
ANOVA
A
Analysis of Variance, type of statistical test that splits variance of DV into its various sources
13
Q
Covariance
A
A measure of the joint variability between two variables
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
15
Q
Nominal variable
A
Another term used for Categorical variables
16
Q
Outlier
A
- Authors of new, alternative statistics textbooks
- Also used to describe data points that appear not to belong to the population being studied, either randomly occurring or due to research error
17
Q
Categorical variable
A
Variable where data is divided into labelled groups (categories); there is no order to the groups
18
Q
Likert scale
A
Ordinal self-report scale used for responses to questions, often with agree – neutral – disagree options
19
Q
Linear
A
- Used to describe relationships where both variables plotted together form a straight line
- Also used to describe combinations of variables by addition
20
Q
Mediation
A
The possibility that the effect of an IV on a DV occurs through an intermediary (mediating) variable
21
Q
Variable
A
Any way in which people/animals/situations differ
22
Q
2-Tailed Test
A
Statistical test with no predicted effect size direction
23
Q
Experimental study
A
Study which deliberately creates an independent variable, such as dividing participants into active and control groups
24
Q
Variance
A
Measure of variability: spread of values, the square of the standard deviation
25
Order effects
Within-participants design issue where participants are influenced by experiencing one condition before another: can influence the IV and the DV
26
Idea
Any proposed relationship between variables, specific or otherwise
27
Uncertainty
In psychological research, uncertainty is how well (or not well) a sample parameter matches a population parameter
28
Discrete
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”
29
Contingency table
A table comparing expected and observed frequencies for a chi-square test
30
Type II error
False negative outcome; when the null hypothesis is not rejected, despite the population having an effect
31
Null hypothesis
The hypothesis that there is no effect in the population
32
Correlation coefficient
Effect size that measures the strength of a linear relationship on a normalized scale
33
Median
Measure of central tendency for Ordinal data, the middle value of a data set or halfway point between two central values
34
Non-parametric test
Statistical tests conducted on Ordinal or atypical data sets which don’t meet the requirements of parametric tests
35
Standard error
The standard deviation of the Sampling Distribution
36
Null hypothesis testing
Test used when looking for evidence to reject the null hypothesis
37
Likelihood
The relative chance that an event (like a sample) was caused by another event (like a specific population)
38
Variability
A term to describe the mount of differences between different people/animals/situations
39
Scatter plot
Type of graph with two continuous numeric variables plotted. Each data point is a single unconnected point in the graph
40
Opportunity sampling
Sampling strategy that uses any available group; no attempts to match a population or collect a random set of participants
41
Categories
The values of a categorical variable; also referred to as groups. Traits (e.g. blue eyes/brown eyes) or situations (before/after)
42
Path model
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
43
Mixed measures
Term used to describe an ANOVA where 1 or more variables are between-participants and 1 or more are within-participants
44
Likelihood function
A graph that shows the relative likelihood that a particular sample effect size came from a range of different population effect sizes
45
Residual
The difference between the expected value for an Interval DV and the actual value for one participant
46
AIC
Akaike Information Criterion. Value used to assess the fit of a model, typically by comparing models. Smaller is better
47
Natural effect size
An effect size measured in the same units as the DV
48
Type I error
False positive; the incorrect rejection of the null hypothesis
49
X-axis
Horizontal scale of a graph
50
Deviation
The difference between the value of a data point and the mean for that data set
51
Local mean
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
52
Logarithmic scale
A transformation that expands the amount of space given to small values and contracts the amount of space given to large values
53
Value
A specific description of a variable for one person or situation: e.g. ‘green’ for the variable eye colour, or ‘112’ for IQ score
54
Endogenous variable
A response variable, or dependent variable in a model
55
Interaction
A mechanism by which the effect of one IV on a DV depends on the value of another IV
56
Ordinal variable
A variable with ordered values, but no meaningful difference between values
57
Bar chart
Chart typically used to present frequencies of categorical data. Data illustrated using separated columns
58
Standard deviation
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
59
Parametric test
Standard null hypothesis statistical testing, typically between Interval and Categorical variables
60
Dispersion
The spread of a set of a values, often defined using the standard deviation or inter-quartile range
61
Patchy coverage
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
Hypothesis
A specific and testable prediction including a description of expected effect
63
Sample size
Number of participants recruited, commonly denoted with ‘n=’
64
Observational study
Study that makes use of variables that already exist, as distinct from an experimental study where an experimental variable is created
65
Marginal distribution
The distribution of values for a single variable – usually used in the context of a scatter plot of two variables
66
Exogenous variable
A predictor or independent variable in a model that is not proposed to have any causes amongst the other variables
67
Sum of squared deviations
A useful intermediate step in calculating means, standard deviations, regression and ANOVA
68
Standardized effect size
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
Estimate
Logical guess based on known information
70
Repeated measures
Term used to describe an ANOVA where both IVs use a within-participants design
71
r-statistic
Normalised effect size ranging from -1 to +1, where 0 is no effect
72
Mean
Measure of central tendency for Interval data, the value where the sum of squared deviations is smallest
73
Statistically significant
Term given to results typically where p<0.05 (or other alpha)
74
Contrast test
A modified version of a 1-tailed test where categorical data is converted to numeric data to allow a correlation
75
Distribution
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
Inferential statistics
Statistics which use sample data to produce knowledge about a population and determine the uncertainty of that knowledge
77
Confidence limits
The end values of the range of a confidence interval
78
Between-participants
Design choice for categorical data, where participants each only experience one group of a categorical variable
79
Replication
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
1-way ANOVA
Statistical test for Categorical IV and Interval DV
81
Central tendency
The typical value used to summarise a set of values
82
1-Tailed Test
Statistical test with a predicted effect size direction
83
Count
See frequency
84
General linear model
A statistical model where there is a set of predictors (IVs) whose added effects are thought to relate to the response variable (DV)
85
Bivariate
Meaning two-variable
86
Regression line
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
Counterbalancing
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
Measurement error
The difference between the real value of some variable in a participant and the measured value
89
Dependent variable (DV)
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
Publication bias
The tendency for journals and other publications to only report research which delivers statistically significant findings
91
Sampling distribution
The distribution of expected sample effect sizes given a particular population and sampling design
92
BESD
Binomial effect size display. Effect size that measures effects as comparison between expected and observed values
93
Population
Everyone of interest in a piece of research: as big as everyone in the whole world, as small as any limited group chosen
94
Skew
Asymmetric distribution with one long tail, either positive or negative
95
Placebo
The non-specific effect of a treatment that arises purely because of participant expectations (e.g. sugar pills which cure headaches)
96
Line graph
A graph where a sequence of values are shown as (usually but not necessarily) connected points
97
Significance testing
See null hypothesis testing
98
APA format
American Psychological Association format for presenting statistical results
99
Sample effect size
Measured effect size of a sample: always certain, if the calculations are done correctly. But an uncertain estimate of the population effect size
100
Sample
Set of participants recruited for a piece of research
101
Stratified sampling
Recruitment strategy that attempts to match the frequency distribution of the population to create a representative sample
102
Sampling error
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
Y-axis
Vertical scale of a graph
104
Data analysis
Typically used to refer to the inferential stage of statistics
105
Exploratory research
Research intended to investigate phenomena without prior expectations that might be confirmed or not
106
Correlation
The strength of any linear relationship between two variables
107
Dummy variable
Extra variables created to replace categorical variables. Dummy variables can be treated as numerical with values 0 and 1
108
Omnibus test
A test that there is some effect in a set of data, without being more specific about where
109
Logistic regression
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
Moderator
Another term for interaction. One IV is said to moderate (change) the effect of another IV on a DV
111
Regression
A process of measuring the quantitative effect of one or more Interval IVs on a DV
112
Data
Information deliberately collected together to answer a question: quantitative, in the context of this book
113
Effect size
A value used to quantify the strength of a relationship between variables
114
Bias
A systematic (i.e. not random) difference between a sample and the population
115
Pearson correlation
Test used to assess linear relationships between numeric variables
116
Average
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
Non independence
Used to describe participants who are related in some way
118
Mode
The most common value. A measure of central tendency useful especially for Categorical data (typically the biggest group)
119
Constant
Any number that doesn’t change
120
Square root
Any number to the power of ½. The square root of 9 is 3
121
Statistical test
General term typically used to describe null hypothesis statistical testing
122
Causation
The assumption that one variable affects another
123
Alternative hypothesis
The hypothesis that makes the prediction that researchers are interested in. Not statistically tested
124
Power analysis
Calculation based on predicted effect size to determine sample size that has 80% chance of producing a significant result (referred to as power)
125
Normal distribution
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
Post-hoc
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
Inference
Using statistics to produce knowledge about a population based on data from a sample; a conclusion that is always uncertain
128
Alpha
Accepted criterion value of p for statistical significance, also chance of a Type I error. Most commonly used value is 0.05
129
P-value
Probability value: the probability of the null hypothesis producing the same or a more extreme result. Used to determine statistical significance
130
Descriptive statistics
Statistics used to describe a sample, to summarise and indicate patterns
131
Research design
Decisions about sample, measurement, and data collection for research
132
Random sampling
Sampling strategy where all members of a population have equal chance of being selected for a sample
133
Covariation
Possible relationship between two different IVs
134
t-statistic
Test statistic for the t-test. The t statistic is found by dividing an estimated value by its standard error
135
Degrees of freedom
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
Model
A description of a pattern in some data. The model is then thought to capture important variability in the data
137
Test statistic
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
Normalized effect size
An effect size measured on a scale from -1 to +1 (see r-statistic)
139
Main effect
The independent effect of one IV on one DV
140
Independent variable (IV)
Variable that is predicted to influence the DV. The IV is treated as independent of the DV
141
Frequency
Relative commonness of a value of a variable: e.g. proportion of participants in one group
142
Pooled standard deviation
Typical standard deviation of multiple groups, weighted by group size
143
Probability
The chance that an event in the future will happen
144
Within-participants
Research design for a Categorical IV where participants experience all groups of the IV
145
Total effect size
The effect of one IV on a DV, disregarding any other variables
146
Cronbach’s alpha
A measure of the consistency of responses to a set of questions about a common state or trait
147
Coefficient
A ratio: how much change in a DV for a given change in an IV
148
Latent variable
Any unmeasured variable: internal state or otherwise
