The post is about MCQs Linear Regression and correlation Quiz. There are 20 multiple-choice questions covering topics related to the basics of correlation and regression analysis, best-fitting trend, least square regression line, interpretation of correlation and regression coefficients, and regression plot. Let us start with the MCQs about Linear Regression and Correlation Quiz now.
Online Linear Regression and Correlation Quiz with Answers
Linear Regression and Correlation Quiz with Answers
- A regression analysis is run between two continuous variables “amount of food eaten” vs “the amount of calories burnt”. The coefficient value is $-0.33$ for “the amount of food eaten” and an R-square value of 0.81. What is the correlation coefficient?
- In the simple linear regression equation, the term $B_0$ represents the
- In model development, one can develop more accurate models when one has which of the following?
- How should one interpret an R-squared if it is 0.89?
- When comparing linear regression models, when will the mean squared error (MSE) be smaller?
- Which of the following is NOT true about a model?
- Which of the following is NOT a method for evaluating a regression model?
- Which of the following is NOT true about a model?
- What type of model would you use if you wanted to find the relationship between a set of variables?
- Pearson correlation are concerned with
- Which of the following statements describes a positive correlation between two variables?
- When using the Pearson method to evaluate the correlation between two variables, which set of numbers indicates a strong positive correlation?
- What are the key reasons to develop a model for your data analysis?
- There are four assumptions associated with a linear regression model. What is the definition of the assumption of homoscedasticity?
- Which performance metric for regression is the mean of the square of the residuals (error)?
- When comparing the MSE of different models, do you want the highest or lowest value of MSE?
- Which is NOT true for comparing multiple linear regression (MLR) and simple linear regression (SLR)?
- One can visualize the correlation between two variables by plotting them on a scatter plot and then doing which of the following?
- When using the Pearson method to evaluate the correlation between two variables, how can one know that there is a strong certainty in the result?
- The method of least squares finds the best-fit line that ————– the error between observed and estimated points on the line.
