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Comm 87 Midterm 2
Terms in this set (28)
tests whether two sample means are significantly different from one another
Formula (t-ratio): t=xbar1-xbar2/Sdiff
degrees of freedom
number of scores free to vary
sampling distribution obtained using an estimated standard error of the difference, not a single t-distribution for all sample sizes
single-factor ANOVA "oneway"
to test whether more than two sample means differ significantly from one another in the population, use when you have one IV (divided into more than two levels) and one DV measured at interval/ratio level
F-test (F ratio)
ratio of two different kinds of variance.
F= between groups variance/within groups variance
the mean of all means of all groups in an ANOVA
the mean of a specific group, used to compare to other group means
between groups variance
variability between groups' means that represents variability in the dependent variable due to the independent variable
within groups variance (error variance)
the difference between each individual score and its own group mean, variability within groups
post hoc tests
identifies exactly which groups differ significantly from which other groups, conducted after a primary statistical test such as the F-test is found to be significant
independent variables that might change the outcome of the dependent variable
theoretical distributions created from the ratio of two variances for different degrees of freedom, in order to reject null, the calculated F-value must fall in the outermost 5% of the distribution
sum of squares between
represents how much of the total variability in the dependent variable (how scores differ from grand mean) is explained by the independent variable (which group a person is in)
sum of squares within (sum of squares error)
variability within groups' scores (ideally a small value)
sum of squares total
sum of squared differences between each individual score and the grand mean of all scores
mean squares between
mathematical measure of amount of variance there is between groups (calculated by taking sum of squares between groups and dividing by the associated degrees of freedom)
mean squares within (mean squares error)
mathematical measure of amount of variance there is within the groups, computed by taking sum of squares within groups and diving by the corresponding degrees of freedom
multiple factor ANOVA
involves more than one independent variable, groups means are still compared, but now the groups are defined as a function of two or more independent variables
type of experimental design in which subjects are randomly assigned to groups defined by two or more independent variable factors
an effect or difference across levels of a single independent variable
an effect or difference across levels of two or more independent variables
rules for identifying main and interaction effects
main effect: test the marginal means (average the cell means for each level of the independent variable), on a graph: if the lines inside the graph are not parallel to the x-axis, there is a main effect, if the lines inside do not coincide or overlap, there is a main effect.
interaction effect: on a graph, if the two lines are not parallel, there is an interaction effect
statistical techniques involving nominal or ordinal level data which do not deal with estimates of population parameters
chi square goodness of fit test (one way)
seeks to see how subjects from a single sample are distributed across categories of a variable, involves determining whether there is a significant difference in the number of observations in each category compared with theoretical values
chi square test of association (two-way)
examines whether the distribution of observations across categories differs between two or more samples, two dimensions of variables are of interest: categories and samples
frequency observed for each category
frequency one would theoretically expect to observe if there was no difference among groups
log linear analysis
extension of the chi-square test, used when more than two categorical variables are involved
Salkind Ch 5: If X and Y have a negative correlation, what happened to X as Y increases? (pg 83)
What measurement of central tendency is appropriate for an ordinal variable?
What are the purposes of inferential statistics?
What are the two types of frequency distributions?
Recommended textbook explanations
Myers' Psychology for the AP Course
David G Myers
Psychology: Principles in Practice
Spencer A. Rathus
Understanding Psychology, Student Edition
Richard A. Kasschau
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