What does an R-squared value of 0.80 indicate?
The slope of the regression line is 0.80.
The correlation between the variables is 0.80.
20% of the variation in the dependent variable is explained by the independent variable.
80% of the variation in the dependent variable is explained by the independent variable.
A bag contains 3 red balls and 2 blue balls. You draw two balls from the bag without replacement. What is the probability that the second ball is red, given that the first ball was blue?
3/4
3/5
2/5
1/4
A Chi-square test is most appropriate for analyzing which type of data?
Continuous data
Time series data
Categorical data
Normally distributed data
What does a p-value less than the significance level (alpha) indicate?
The alternative hypothesis is proven true.
The null hypothesis should be accepted.
There is insufficient evidence to reject the null hypothesis.
There is strong evidence to reject the null hypothesis.
An autoregressive model (AR) uses ______ values of the time series to predict future values.
Random
Past
Average
Future
What is the purpose of using a correlation matrix in multivariate statistics?
To visualize the distribution of residuals in regression
To determine the optimal number of factors in factor analysis
To identify outliers in a dataset
To assess the strength and direction of linear relationships between pairs of variables
Which of the following statements is TRUE about multivariate analysis of variance (MANOVA)?
It analyzes the differences between groups on multiple dependent variables simultaneously.
It is used for dimensionality reduction of categorical variables.
It examines the relationship between two continuous variables.
It tests the difference in means between two groups on a single dependent variable.
In multiple regression, what does a high variance inflation factor (VIF) indicate?
Heteroscedasticity in the residuals
A good fit of the regression model
High multicollinearity among predictor variables
Low multicollinearity among predictor variables
When is Spearman's rank correlation a more appropriate measure of association than Pearson's correlation?
When the variables are measured on an interval or ratio scale and normally distributed
When the relationship between variables is perfectly linear
When the relationship between variables is non-linear but monotonic
When outliers are not present in the data
A moving average model is best suited for forecasting time series data with which characteristic?
Strong seasonality
High volatility
A constant mean
Significant outliers