Chapter 14 Defintions

Bayesian Statistics: A type of statistics that updates the probability of a hypothesis based on new data.

Central Tendency: A measure of the "center" of a data set (mean, median, or mode).

Cohen's d: A measure of effect size that shows the difference between two groups in terms of standard deviation units.

Correlation Coefficient: A number showing the strength and direction of the relationship between two variables.

Criterion Variable: The outcome variable in a study, predicted by the predictor variable.

Descriptive Statistics: Statistics that summarize data (like mean, median, mode, range).

Effect Size: The size of a relationship or difference in a study, indicating its practical significance.

Frequency Distribution: A table or graph showing how often each value in a data set occurs.

Frequency Polygons: A graph made by connecting the midpoints of bars in a histogram with lines.

Histogram: A bar graph showing the frequency of data within intervals.

Inferential Statistics: Statistics that allow us to make conclusions or inferences about a population based on sample data.

Mean: The average of a data set, calculated by adding up all values and dividing by the number of values.

Median: The middle value in an ordered data set.

Mode: The most frequently occurring value in a data set.

Multiple Correlation: The combined relationship between multiple predictor variables and one criterion variable.

Multiple Regression: A statistical method that predicts a criterion variable based on multiple predictor variables.

Normal Distribution: A bell-shaped curve where most data points are near the mean.

Null Hypothesis Significance Testing (NHST): A test to decide if an effect in data is likely due to chance or if it’s statistically significant.

Outliers: Data points that are much higher or lower than the rest of the data.

P-value: A measure showing the likelihood that results happened by chance, with lower values indicating stronger evidence.

Partial Correlation: The relationship between two variables while controlling for the effect of another variable.

Pie Chart: A circular chart divided into segments representing parts of a whole.

Predictor Variable: The variable used to predict the outcome (criterion) variable.

Regression Equation: A formula used to predict the criterion variable from predictor variables.

Restriction of Range: When the range of data in a study is limited, which can affect results.

Scatterplot: A graph of data points showing the relationship between two variables.

Squared Correlation Coefficient: The proportion of variance shared between two variables.

Squared Multiple Correlation Coefficient: The proportion of variance in a criterion variable explained by all predictor variables together.

Standard Deviation: A measure of how spread out data points are from the mean.

Variability: How much data points differ from each other in a data set.

Variance: The average squared difference from the mean, showing data spread.

Outliers: Extreme values in a data set that differ significantly from others.

P-value: Indicates the probability that the observed result occurred by chance. A smaller value suggests stronger evidence against the null hypothesis.

Partial Correlation: The correlation between two variables after removing the influence of one or more additional variables.

Pie Chart: A circular chart divided into slices to represent the proportions of different categories in a whole.

Predictor Variable: A variable used to forecast or predict the criterion (outcome) variable.

Regression Equation: A formula that describes the relationship between predictor variables and a criterion variable to make predictions.

Restriction of Range: A limitation in the data range that can affect the strength of correlations and results.

Scatterplot: A graph that displays data points for two variables to show their relationship.

Squared Correlation Coefficient (r²): A value that shows the proportion of variation in one variable that is explained by its relationship with another variable.

Squared Multiple Correlation Coefficient (R²): The proportion of variance in a criterion variable explained by multiple predictor variables.

Standard Deviation: A measure that shows how much values in a data set deviate from the mean, indicating spread.

Variability: The degree to which data points in a set differ from one another.

Variance: The average of the squared deviations from the mean, showing the data's spread or dispersion