Psychological Statistics || Module 7 & 8

Analysis of Variance

Method to identify variability sources in data sets

Variability

Spread of scores around the mean

ANOVA Table

Displays sources of variability, degrees of freedom, and F-statistic

Between-Groups Sum of Squares

Variability between groups in ANOVA

Within-Groups Sum of Squares

Variability within each group in ANOVA

Total Sum of Squares

Sum of between-groups and within-groups sums of squares

Hypothesis in ANOVA

Testing differences in group means using ANOVA

Grouping Variable

Predictor or independent variable in ANOVA

Outcome Variable

Variable based on group differences in ANOVA

Individual Group Means

Means of each group in ANOVA

Grand Mean

Overall mean across all groups in ANOVA

Degrees of Freedom

Number of values in the final calculation of a statistic

F-Statistic

Ratio of two variances in ANOVA hypothesis testing

Critical Values

Values from F distribution table for hypothesis testing

Mean Square

Sum of squares divided by degrees of freedom

Test Statistic

Statistic used to make decisions in hypothesis testing

Correlation

Statistical measure of relationship size and direction

Covariance

Tool to determine relationship between random variables

Variability and Covariance

Significance in statistical analysis and understanding data patterns

Pearson's Correlation Coefficient

Formula to calculate and interpret correlation between variables

Visualizing Relationships

Importance of graphical representation in understanding variables

Form, Direction, Magnitude

Concepts in interpreting relationships between variables

Correlation vs. Causation

Distinguishing between relationship and cause-effect in statistics

Variance

Measure of how spread out a set of values are from the mean

Sum of Products

Result of multiplying deviations of paired values and summing them

Scatterplot

Visual representation of relationship between two variables

Positive Correlation

Relationship where both variables increase/decrease together

Negative Correlation

Relationship where one variable increases as the other decreases

Form

Shape of a relation in a scatterplot

Linear Relation

Relation best represented by a straight line in a scatterplot

Curvilinear Relation

Relation represented by a curved line in a scatterplot

No Relation

Points in a plot show no consistent relationship

Direction

Indicates how variables change together (positively or negatively)

Magnitude

Strength or consistency of the relationship between variables

Pearson's r

Popular correlation coefficient for linear relationships

Assumptions for Pearson Correlation

Conditions to check before performing a Pearson correlation test

Critical Value

Value used to determine statistical significance in hypothesis testing

Test Statistics

Calculations used to assess the relationship between variables

Standard Deviation

Measure of the amount of variation or dispersion of a set of values

Causation

Relationship where one action causes another