The post is about the MCQs correlation and regression Quiz. There are 20 multiple-choice questions covering topics related to the basics of correlation and regression analysis, best-fitting trends, least square regression lines, interpretation of correlation and regression coefficients, and regression plots. Let us start with the MCQs correlation and regression Quiz now.
Online MCQs correlation and Regression Analysis with Answers
MCQs Correlation and Regression
- Which of the following statement(s) about correlations is/are right? I. When dealing with a positive Pearson’s r, the line goes up. II. When the observations cluster around a straight line, we deal with a linear relation between the variables. III. The steeper the line, the smaller the correlation.
- Suppose you have collected the following data about how much chocolate people eat and how happy these people are. Amount of chocolate bars a week: 2, 4, 1.5, 2, 3. Grades for happiness: 7, 3, 8, 8, 6. (Note that the data follows paired observations) The Pearson Correlation between these two variables will be
- Suppose, you have investigated how eating chocolate bars influences the grades of students. For this purpose, you keep track of their chocolate intake (in bars per week) and assess their exam results one day later. Which statement(s) about the regression line $\hat{y} = 0.66x + 1.99$ is/are true?
- A professor uses the following formula to grade a statistics exam: $\hat{y} = 0.5 + 0.53x$. After obtaining the results the professor realizes that the grades are very low, so he might have been too strict. He decides to level up all results by one point. What will be the new grading equation?
- What is the explained variance? And how can you measure it?
- A teacher asks his students to fill in a form about how many cigarettes they smoke every week and how much they weigh. After obtaining the data/results, he makes a scatterplot and analyses the data points. Pearson’s r is computed to assess the correlation and found to of 0.80. From the correlation results, it is concluded that smoking more cigarettes causes high body weight. What is wrong with this analysis?
- What can you conclude about a Pearson’s r that is bigger than 1?
- Why do we use squared residuals when computing the regression line?
- What technique is used to help identify the nature of the relationship between two variables?
- Regression is a form of this?
- The correlation coefficient is used to determine
- If there is a very strong correlation between two variables then the correlation coefficient must be
- Regression modeling is a statistical framework for developing a mathematical equation that describes how
- In the least squares regression, which of the following is not a required assumption about the error term $\varepsilon$?
- In a regression analysis if $R^2=1$ then
- In a regression analysis, the variable that is used to explain the change in the outcome of an experiment, or some natural process, is called
- For a mathematical model related to a straight line, if a value for the x variable is specified, then
- When a regression line passes through the origin then
- The range of the multiple correlation coefficient is
- In regression analysis, the variable that is being predicted is
