Discovering Statistics Using IBM
SPSS Statistics, 5e Question and
answers 100% correct 2025/2026
−2LL - correct answer ✔the log-likelihood multiplied by minus 2.
*used in logistic regression*
Biserial correlation coefficient - correct answer ✔Coefficient used when one variable is a continuous
dichotomy (e.g., has an underlying continuum between the categories).
α-level - correct answer ✔the probability of making a Type I error (usually this value is 0.05).
Adjusted mean - correct answer ✔in the context of analysis of covariance this is the value of the group
mean adjusted for the effect of the covariate.
Adjusted predicted value - correct answer ✔The predicted value of a case from a model estimated
without that case included in the data, calculated by re-estimating the model without the case in
question, then using this new model to predict the value of the excluded case.
*A measure of the influence of a particular case of data*
How to interpret adjusted predicted value - correct answer ✔If a case does not exert a large influence
over the model then its predicted value should be similar regardless of whether the model was
estimated including or excluding that case.
Adjusted R² - correct answer ✔This tells us how much variance in the outcome would be accounted for
if the model had been derived from the population from which the sample was taken.
*measure of the loss of predictive power/shrinkage in regression*
,AIC (Akaike's information criterion) - correct answer ✔a goodness-of-fit measure that is corrected for
model complexity (takes account of how many parameters have been estimated).
It is not intrinsically interpretable, but can be compared in different models to see how changing the
model affects the fit. A small value represents a better fit to the data.
AICC (Hurvich and Tsai's criterion) - correct answer ✔a goodness-of-fit measure that is similar to AIC
but is designed for small samples. It is not intrinsically interpretable, but can be compared in different
models to see how changing the model affects the fit.
Small value=better fit
Alpha factoring - correct answer ✔a method of factor analysis.
Alternative hypothesis - correct answer ✔the prediction that there will be an effect (i.e., that your
experimental manipulation will have some effect or that certain variables will relate to each other).
Analysis of covariance (ANCOVA) - correct answer ✔a statistical procedure that uses the F-statistic to
test the overall fit of a linear model, adjusting for the effect that one or more covariates have on the
outcome variable. In experimental research this linear model tends to be defined in terms of group
means and the resulting ANOVA is therefore an overall test of whether group means differ after the
variance in the outcome variable explained by any covariates has been removed.
Analysis of variance (ANOVA) - correct answer ✔a statistical procedure that uses the F-statistic to test
the overall fit of a linear model.
In experimental research this linear model tends to be defined in terms of group means, and the result is
therefore an overall test of whether group means differ.
Anderson-Rubin method - correct answer ✔a way of calculating factor scores which produces scores
that are uncorrelated and standardized with a mean of 0 and a standard deviation of 1.
AR(1) - correct answer ✔this stands for first-order autoregressive structure. It is a covariance structure
used in multilevel linear models in which the relationship between scores changes in a systematic way. It
,is assumed that the correlation between scores gets smaller over time and that variances are assumed
to be homogeneous. This structure is often used for repeated-measures data (especially when
measurements are taken over time such as in growth models).
Autocorrelation - correct answer ✔when the residuals of two observations in a regression model are
correlated.
bi - correct answer ✔unstandardized regression coefficient. Indicates the strength of relationship
between a given predictor, i, of many and an outcome in the units of measurement of the predictor. It is
the change in the outcome associated with a unit change in the predictor.
βi - correct answer ✔standardized regression coefficient. Indicates the strength of relationship
between a given predictor, i, of many and an outcome in a standardized form. It is the change in the
outcome (in standard deviations) associated with a one standard deviation change in the predictor.
β-level - correct answer ✔the probability of making a Type II error (Cohen, 1992, suggests a maximum
value of 0.2).
Bar chart - correct answer ✔a graph in which a summary statistic (usually the mean) is plotted on the y-
axis against a categorical variable on the x-axis (this categorical variable could represent, for example,
groups of people, different times or different experimental conditions). The value of the mean for each
category is shown by a bar. Different-coloured bars may be used to represent levels of a second
categorical variable.
Bartlett's test of sphericity - correct answer ✔A test of the assumption of sphericity that examines
whether a variance-covariance matrix is proportional to an identity matrix
Therefore, it effectively tests whether the diagonal elements of the variance-covariance matrix are equal
(i.e., group variances are the same), and whether the off-diagonal elements are approximately zero (i.e.,
the dependent variables are not correlated).
Questionable practical utility because it's often significant
, Bimodal - correct answer ✔a description of a distribution of observations that has two values that
appear most often
Binary logistic regression - correct answer ✔logistic regression in which the outcome variable has
exactly two categories.
Binary variable - correct answer ✔a categorical variable that has only two mutually exclusive categories
(e.g., being dead or alive).
Biserial correlation - correct answer ✔a standardized measure of the strength of relationship between
two variables when one of the two variables is dichotomous.
Bivariate correlation - correct answer ✔a correlation between two variables.
Blockwise regression - correct answer ✔another name for hierarchical regression.
Bonferroni correction - correct answer ✔a correction applied to the α-level to control the overall Type I
error rate when multiple significance tests are carried out. Each test conducted should use a criterion of
significance of the α-level (normally 0.05) divided by the number of tests conducted. *Tends to be too
strict when lots of tests are performed*
Bootstrap - correct answer ✔a technique from which the sampling distribution of a statistic is
estimated by taking repeated samples (with replacement) from the data set (in effect, treating the data
as a population from which smaller samples are taken). The statistic of interest (e.g., the mean, or b
coefficient) is calculated for each sample, from which the sampling distribution of the statistic is
estimated. The standard error of the statistic is estimated as the standard deviation of the sampling
distribution created from the <___> samples. From this, confidence intervals and significance tests can
be computed.
SPSS Statistics, 5e Question and
answers 100% correct 2025/2026
−2LL - correct answer ✔the log-likelihood multiplied by minus 2.
*used in logistic regression*
Biserial correlation coefficient - correct answer ✔Coefficient used when one variable is a continuous
dichotomy (e.g., has an underlying continuum between the categories).
α-level - correct answer ✔the probability of making a Type I error (usually this value is 0.05).
Adjusted mean - correct answer ✔in the context of analysis of covariance this is the value of the group
mean adjusted for the effect of the covariate.
Adjusted predicted value - correct answer ✔The predicted value of a case from a model estimated
without that case included in the data, calculated by re-estimating the model without the case in
question, then using this new model to predict the value of the excluded case.
*A measure of the influence of a particular case of data*
How to interpret adjusted predicted value - correct answer ✔If a case does not exert a large influence
over the model then its predicted value should be similar regardless of whether the model was
estimated including or excluding that case.
Adjusted R² - correct answer ✔This tells us how much variance in the outcome would be accounted for
if the model had been derived from the population from which the sample was taken.
*measure of the loss of predictive power/shrinkage in regression*
,AIC (Akaike's information criterion) - correct answer ✔a goodness-of-fit measure that is corrected for
model complexity (takes account of how many parameters have been estimated).
It is not intrinsically interpretable, but can be compared in different models to see how changing the
model affects the fit. A small value represents a better fit to the data.
AICC (Hurvich and Tsai's criterion) - correct answer ✔a goodness-of-fit measure that is similar to AIC
but is designed for small samples. It is not intrinsically interpretable, but can be compared in different
models to see how changing the model affects the fit.
Small value=better fit
Alpha factoring - correct answer ✔a method of factor analysis.
Alternative hypothesis - correct answer ✔the prediction that there will be an effect (i.e., that your
experimental manipulation will have some effect or that certain variables will relate to each other).
Analysis of covariance (ANCOVA) - correct answer ✔a statistical procedure that uses the F-statistic to
test the overall fit of a linear model, adjusting for the effect that one or more covariates have on the
outcome variable. In experimental research this linear model tends to be defined in terms of group
means and the resulting ANOVA is therefore an overall test of whether group means differ after the
variance in the outcome variable explained by any covariates has been removed.
Analysis of variance (ANOVA) - correct answer ✔a statistical procedure that uses the F-statistic to test
the overall fit of a linear model.
In experimental research this linear model tends to be defined in terms of group means, and the result is
therefore an overall test of whether group means differ.
Anderson-Rubin method - correct answer ✔a way of calculating factor scores which produces scores
that are uncorrelated and standardized with a mean of 0 and a standard deviation of 1.
AR(1) - correct answer ✔this stands for first-order autoregressive structure. It is a covariance structure
used in multilevel linear models in which the relationship between scores changes in a systematic way. It
,is assumed that the correlation between scores gets smaller over time and that variances are assumed
to be homogeneous. This structure is often used for repeated-measures data (especially when
measurements are taken over time such as in growth models).
Autocorrelation - correct answer ✔when the residuals of two observations in a regression model are
correlated.
bi - correct answer ✔unstandardized regression coefficient. Indicates the strength of relationship
between a given predictor, i, of many and an outcome in the units of measurement of the predictor. It is
the change in the outcome associated with a unit change in the predictor.
βi - correct answer ✔standardized regression coefficient. Indicates the strength of relationship
between a given predictor, i, of many and an outcome in a standardized form. It is the change in the
outcome (in standard deviations) associated with a one standard deviation change in the predictor.
β-level - correct answer ✔the probability of making a Type II error (Cohen, 1992, suggests a maximum
value of 0.2).
Bar chart - correct answer ✔a graph in which a summary statistic (usually the mean) is plotted on the y-
axis against a categorical variable on the x-axis (this categorical variable could represent, for example,
groups of people, different times or different experimental conditions). The value of the mean for each
category is shown by a bar. Different-coloured bars may be used to represent levels of a second
categorical variable.
Bartlett's test of sphericity - correct answer ✔A test of the assumption of sphericity that examines
whether a variance-covariance matrix is proportional to an identity matrix
Therefore, it effectively tests whether the diagonal elements of the variance-covariance matrix are equal
(i.e., group variances are the same), and whether the off-diagonal elements are approximately zero (i.e.,
the dependent variables are not correlated).
Questionable practical utility because it's often significant
, Bimodal - correct answer ✔a description of a distribution of observations that has two values that
appear most often
Binary logistic regression - correct answer ✔logistic regression in which the outcome variable has
exactly two categories.
Binary variable - correct answer ✔a categorical variable that has only two mutually exclusive categories
(e.g., being dead or alive).
Biserial correlation - correct answer ✔a standardized measure of the strength of relationship between
two variables when one of the two variables is dichotomous.
Bivariate correlation - correct answer ✔a correlation between two variables.
Blockwise regression - correct answer ✔another name for hierarchical regression.
Bonferroni correction - correct answer ✔a correction applied to the α-level to control the overall Type I
error rate when multiple significance tests are carried out. Each test conducted should use a criterion of
significance of the α-level (normally 0.05) divided by the number of tests conducted. *Tends to be too
strict when lots of tests are performed*
Bootstrap - correct answer ✔a technique from which the sampling distribution of a statistic is
estimated by taking repeated samples (with replacement) from the data set (in effect, treating the data
as a population from which smaller samples are taken). The statistic of interest (e.g., the mean, or b
coefficient) is calculated for each sample, from which the sampling distribution of the statistic is
estimated. The standard error of the statistic is estimated as the standard deviation of the sampling
distribution created from the <___> samples. From this, confidence intervals and significance tests can
be computed.
