Chapter 10

Dependent variable

the outcome being measred; which must be on a continuous scalel to allow calculation and comparison of means

Independent Variable

define the groups, conditins, or categories being compared

One sample z-test

 used when the population standard deviation (σ) is known; When you want to compare the mean on a single variable in your data to a specified population mean (μ) to determine whether they are statistically significantly different

one sample t-test

used when the population standard deviation (σ) is unknown.

In between subjects

when two samples consist of separate and distinct groups of people with no overlap in membership

Within Subjects

When two samples are connected—either because the same individuals are measured under different conditions or because participants are matched into pairs 

 independent groups t test 

used to compare the means of two independent groups

related samples t-test

used to compare two means that are connected in some way

When should you use indepent group t-tests?

when the groups are distinct and there is no overlap in participants.

What does ANOVA stand for?

ANalysis Of VAriance

Independent groups ANOVA (one-way ANOVA)

compare means across three or more independent groups; between subjects design.

related samples ANOVA (repeated measures ANOVA)

used to compare means across three or more conditions or time points within the same group of participants.

factorial ANOVA

used in experiments involving two or more independent variables (factors). This method allows researchers to test for main effects (differences across levels of each factor) and interactions (whether the effect of one factor depends on the levels of another factor)

Correlation

 used when you have two variables and want to determine the strength and direction of their association, as well as whether this relationship is statistically significant.

simple regression

used when you want to predict scores on an outcome variable using scores on a predictor variable

multiple regression

allows researchers to predict an outcome variable using two or more predictor variables. 

Multiple regression is versatile use for the following:

1. explaining more variance

2. testing the incremental value of a predictor

3. statistically controlling for variables

4. testing for nonlinear relationships

5. testing for interactions

chi-square

are used to analyze categorical data by comparing observed frequencies to expected frequencies

chi-square goodness-of-fit test

evaluates whether the observed frequencies in a single categorical variable differ significantly from the expected frequencies

chi-square test for associaton (chi-square test of independence)

examines the relationship between two categorical variables by analyzing how the observed frequencies in a contingency table differ from the frequencies we would expect to be unrelated

contingency table

is a grid that displays the counts of observations for each combination of categories for two variables