Glossary

Hypothesis

A statement about the value of a population parameter developed for the purpose of testing.

Null Hypothesis (H0)

The hypothesis tentatively assumed true in the hypothesis testing procedure.

Statistical Test

A procedure that uses sample data to make inferences about populations.

Level of Significance (α)

The probability of rejecting the null hypothesis when it is actually true.

p-value

The probability of obtaining the observed effect if the null hypothesis is true; lower p-values indicate greater evidence against the null hypothesis.

One-way ANOVA

A hypothesis test that allows comparison of means for more than two groups.

F Test

A statistical test used to determine if two samples are from populations with equal variances.

Variances

A measure of the dispersal of data points around the mean.

Type I Error

The error of rejecting H0 when it is true.

Type II Error

The error of accepting H0 when it is false.

Test Statistic

A statistic whose value helps determine whether a null hypothesis should be rejected.

Critical Value

A value compared with the test statistic to determine whether H0 should be rejected.

Correlation Coefficient (r)

A measure of the strength and direction of the linear relationship between two variables.

Coefficient of Determination (R2)

The square of the correlation coefficient, representing the proportion of variance in the dependent variable explained by an independent variable.

Regression Analysis

A statistical process for estimating relationships among variables.

Simple Linear Regression

A regression analysis method to model the relationship between two variables by fitting a linear equation.

Chi-Square Test

A statistical test used for testing relationships between categorical variables.

Goodness-Of-Fit Test

A test used to determine if the observed frequency distribution of a categorical variable matches an expected distribution.

Contingency Table

A table used to display the frequency distribution of categorical variables.

Dummy Variable

A variable that takes on only two possible outcomes, often used in regression for qualitative data.

Total variation (SST)

The sum of the squared differences between each observation and the overall mean.

Between-group variation (SSB)

The sum of squared differences between each treatment mean and the overall mean. In the textbook, it is called treatment variation that is the variation due to the treatments.

Within-group variation (SSW)

The sum of the squared differences between each observation and its treatment mean. In the textbook, it is called random variation that is the variation due to the random errors.

Alternative hypothesis

The hypothesis concluded to be true if the null hypothesis is rejected.

Type I error

The error of rejecting 𝑯𝟎 when it is true.

Type II error

The error of accepting 𝑯𝟎 when it is false.

Correlation matrix

Shows all possible correlation coefficients (r) between pairs of variables.

Dummy variable

A variable by which there are only 2 possible outcomes.

Chi-square statistic

Used for testing relationship between categorical variables.