Bivariate Correlation and Regression MCQs
Bivariate Correlation and Regression MCQs
Welcome to MCQss.com's collection of multiple-choice questions (MCQs) focusing on bivariate correlation and regression in the field of statistics. This page aims to deepen your knowledge and comprehension of the concepts, calculations, interpretation, and applications of bivariate correlation and regression.
By engaging with these MCQs, you will gain a comprehensive understanding of bivariate correlation and regression techniques and their practical applications in various fields, such as social sciences, business, healthcare, and more. You will also learn about the assumptions and limitations associated with these methods, as well as strategies for addressing common challenges in bivariate analysis.
These MCQs are designed to support students, researchers, and professionals in the field of statistics, data analysis, social sciences, or any discipline where bivariate analysis is relevant. Whether you are learning about correlation and regression for the first time or seeking to reinforce your existing knowledge, these MCQs provide a valuable resource for self-assessment and learning.
Expand your proficiency in bivariate correlation and regression by exploring and answering these MCQs. Strengthen your understanding of their concepts, calculations, interpretation, and practical applications in data analysis and research.
1: _____ is the name for the population parameter of the slope, but also a name given to the standardized slope regression coefficient in multiple regression.
A. Alpha Coefficient
B. Beta Coefficient
C. Slope
D. None of these
2: Bivariate Correlation measures the _____ relationship between two variables.
A. Linear
B. Skewed
C. Both
D. None
3: Coefficient Of Determination is the percentage of the variation in the dependent variable (y) that is explained by the _____ variable.
A. Dependent
B. Independent
C. Continous
D. Confound
4: Means of y calculated for every value of x is known as conditional Mean of y.
A. True
B. False
5: Assumption in ordinary least-squares (OLS) regression that the error terms are varied across all values of x is known as Homoscedasticity.
A. True
B. False
6: Least Squares Regression Line is a regression line based on the least-squares function to calculate an equation that characterizes the best-fitting line between two _____ variables.
A. Interval
B. Ratio
C. Nominal
D. Both a and b
7: The effect of x on y is generally _____ at all values of x.
A. Different
B. Same
C. Both
D. None
8: As the independent variable increases, the _____ variable decreases, it is called Negative Correlation.
A. Dependent
B. Independent
C. Both
D. None
9: Nonlinear relationships can take several forms but generally indicate a relationship that changes direction as the values of the independent variable______.
A. Increase
B. Decrease
C. Remains same
D. Both a and b
10: Pearson’s Correlation Coefficient is a statistic that quantifies the direction and strength of the relationship between two _____ -level variables.
A. Interval
B. Ratio
C. Nominal
D. Both a and b
11: According to positive Correlation,as the independent variable increases, the dependent variable_____.
A. Increases
B. Decreases
C. Remains same
D. Both a and c
12: Value of the dependent variable predicted by a regression equation is known as _____
A. Predicted Value of x
B. Predicted Value of y
C. Both
D. None
13: Regression Line depicts the relationship between independent and _____ variables determined by an ordinary least-squares regression equation.
A. Dependent
B. Continuous
C. Confound
D. All of these
14: Difference between the predicted value of y from the regression equation and the observed value at a given x score is known as Residual.
A. True
B. False
15: _____ is a graphical display of the linear relationship between two interval/ratio-level variables.
A. Scatterplot
B. Scattergram
C. Boxplot
D. Both a and b
16: Slope is a term in an ordinary least-squares (OLS) regression equation that indicates the change in y associated with a one-unit change in _____
A. X
B. Y
C. Both
D. None
17: Y Intercept is a value of y in an ordinary least-squares (OLS) regression equation when x is equal to _____
A. Zero
B. 1
C. 10
D. 0.1
List of Bivariate Correlation ...
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Bivariate Correlation and Regression MCQs
