Question 26 of 50

In a simple linear regression model, the variable that serves as the predictor is best described as the:

Which of the following best describes the method of Ordinary Least Squares (OLS)?

If the covariance between variables X and Y is 20 and the variance of X is 10, what is the estimated slope coefficient for the regression of Y on X?

Given a regression equation Y = 0.5 + 1.2X, how is the slope coefficient interpreted?

Calculate the intercept of a regression line where the mean of Y is 15, the mean of X is 5, and the estimated slope coefficient is 2.

Which of the following is NOT a necessary assumption of simple linear regression?

The condition where the variance of the error term is not constant across all observations is known as:

In the context of regression analysis, the term 'residuals' refers to:

If the Regression Sum of Squares (RSS) is 60 and the Sum of Squared Errors (SSE) is 40, what is the Total Sum of Squares (SST)?

The coefficient of determination (R-squared) measures:

If a regression model has an RSS of 45 and an SST of 100, what is the value of R-squared?

The Standard Error of Estimate (SEE) is calculated as the square root of which value?

In a simple linear regression with 32 observations, what are the degrees of freedom for the error term?

Calculate the F-statistic if the Mean Regression Sum of Squares (MSR) is 100 and the Mean Squared Error (MSE) is 20.

In a simple linear regression, the F-test is equivalent to determining the statistical significance of:

The appropriate degrees of freedom for the numerator in the F-test for a simple linear regression is:

If the calculated t-statistic for a slope coefficient is 2.5 and the critical t-value is 2.0, what is the appropriate conclusion?

For a simple linear regression, the null hypothesis used to test the statistical significance of the slope coefficient is:

If the standard error of the slope coefficient is 0.5 and the estimated slope is 1.5, what is the calculated t-statistic for testing if the slope is zero?

Given a regression equation Y = 2 + 3X, what is the predicted value of Y when X is 4?

In a log-lin model where ln(Y) = b0 + b1*X, how is the slope coefficient (b1) interpreted?

In a lin-log model where Y = b0 + b1*ln(X), the slope coefficient indicates:

Which functional form involves taking the natural logarithm of both the dependent and independent variables?

If a stock's return is explained by the market return, the stock's return is the:

If the correlation coefficient between two variables is 0.7, what is the coefficient of determination (R-squared)?

In an ANOVA table, the Mean Squared Error (MSE) is calculated by dividing:

A residual plot that shows residuals increasing in magnitude as the independent variable increases indicates:

If the confidence interval for a slope coefficient includes zero, we can conclude that:

Which of the following values can the coefficient of determination (R-squared) NOT take?

Standard Error of Estimate (SEE) measures:

If a regression has an SSE of 200 and n = 22, what is the MSE?

In simple linear regression, the F-statistic is always a:

The intercept term in a regression is best interpreted as:

Using a 5 percent significance level with 34 degrees of freedom, the critical t-value is approximately 2.03. If the calculated t-statistic is 2.46, you should:

Which of the following indicates a stronger linear relationship?

If a regression has R-squared of 0.64, what is the correlation coefficient?

The Sum of Squared Errors (SSE) measures:

A confidence interval for a predicted Y-value relies on:

In a regression model Y = b0 + b1*X + error, the term 'error' represents:

If a slope coefficient is 0.64, it implies that:

In the context of the F-test, Mean Regression Sum of Squares (MSR) is calculated as:

If the correlation between X and Y is negative, the slope coefficient of the regression of Y on X must be:

A confidence interval for the predicted value of Y becomes wider when:

Which assumption is violated if the variance of the residuals increases as the predicted values increase?

Calculate the t-statistic for a slope of 1.2 with a standard error of 0.4.

In the ANOVA table for simple regression, the Total Sum of Squares (SST) degrees of freedom is:

If RSS = 80 and SSE = 20, what is the value of R-squared?

Prediction intervals are generally wider than confidence intervals because:

If a company uses a regression model to predict sales based on advertising spend, 'Sales' is the: