A) Analysis of continuous variables only
B) Analysis of a single variable
C) Analysis of two variables
D) Analysis of multiple variables simultaneously

A) T-test
B) Chi-square test
C) Principal component analysis
D) ANOVA

A) ANOVA
B) Regression analysis
C) Correlation analysis
D) Cluster analysis

A) To determine correlation coefficients
B) To determine outliers
C) To determine which variables discriminate between two or more group
D) To determine descriptive statistics

A) To determine the number of factors to retain in factor analysis
B) To identify outliers
C) To plot data points
D) To show correlation coefficients

A) To test hypotheses
B) To perform regression analysis
C) To find correlation between a variable and itself
D) To examine the relationships between two sets of variables

A) The number of factors to retain
B) The correlation between variables
C) The significance of variables
D) The standard deviation of variables

A) Testing for differences between groups
B) Plotting bivariate data
C) Grouping similar observations into clusters
D) Conducting factor analysis

A) To test for outliers
B) To determine sample size
C) To perform factor analysis
D) To understand the relationships and variances between multiple variables

A) To find outliers
B) To perform cluster analysis
C) To determine correlations
D) To predict group membership based on predictor variables

A) When outliers are present
B) When variables are highly correlated
C) When dealing with categorical data only
D) When variables are independent

A) MANOVA is used for categorical data analysis, while ANOVA is used for continuous data analysis
B) ANOVA is appropriate for small sample sizes, while MANOVA is for large sample sizes
C) ANOVA uses mixed-effect models, while MANOVA uses fixed-effect models
D) MANOVA considers multiple dependent variables simultaneously, while ANOVA focuses on a single dependent variable

A) To determine the relationship between two sets of variables
B) To determine outliers
C) To perform hypothesis testing
D) To determine factor loadings

A) Test for correlations
B) Identify outliers in the data
C) Conduct factor analysis
D) Determine which variables best predict group membership