Correlation and Regression Quiz 2

This Post contains a Correlation and Regression Quiz that covers topics on Correlation Analysis, Simple Regression Analysis, Multiple Regression Analysis, Coefficient of Determination (Explained Variation), Unexplained Variation, Model Selection Criteria, Model Assumptions, Interpretation of results, Intercept, Slope, Partial Correlation, Significance tests, Multicollinearity, Heteroscedasticity, Autocorrelation, etc. Let us start with MCQs on the Correlation and Regression Quiz.

Correlation is a statistical measure used to determine the strength and direction of the mutual relationship between two quantitative variables. The value of correlation lies between $-1$ and $1$. The regression describes how an explanatory variable is numerically related to the dependent variables.

Both of the tools are used to represent the linear relationship between the two quantitative variables. The relationship between variables can be observed either using a graphical representation between the variables or numerical computation using an appropriate computational formula.

Online Correlation and Regression Quiz with Answers

Online Correlation and Regression Quiz with Answers

• The strength (degree) of the correlation between a set of independent variables $X$ and a dependent variable $Y$ is measured by
• The percent of the total variation of the dependent variable $Y$ explained by the set of independent variables $X$ is measured by
• A coefficient of correlation is computed to be -0.95 means that
• Let the coefficient of determination be computed to be 0.39 in a problem involving one independent variable and one dependent variable. This result means that
• The relationship between the correlation coefficient and the coefficient of determination is that
• Multicollinearity exists when
• If “time” is used as the independent variable in a simple linear regression analysis, then which of the following assumptions could be violated
• In multiple regression, when the global test of significance is rejected, we can conclude that
• A residual is defined as
• What test statistic is used for a global test of significance?
• If the value of any regression coefficient is zero, then two variables are said to be
• In the straight line graph of the linear equation $Y=a+bX$, the slope will be upward if
• In the straight line graph of the linear equation $Y=a+bX$, the slope will be downward if
• In the straight line graph of the linear equation $Y=a+BX$, the slope is horizontal if
• For the regression $\hat{Y}=5$, the value of regression coefficient of $Y$ on $X$ will be
• If $\beta_{yx} = -1.36$ and $\beta_{xy} = -0.34$ then $r_{xy} =$
• If one regression coefficient is greater than one then the other will be
• To determine the height of a person when his weight is given is
• The dependent variable is also called
• The dependent variable is also called

Note that neither regression nor correlation analyses can be interpreted as establishing some cause-and-effect relationships. Both of these can be used to indicate only how or to what extent the variables under study are associated (or mutually related) with each other. The correlation coefficient measures only the degree (strength) and direction of linear association between the two variables. Any conclusions about a cause-and-effect relationship must be based on the judgment of the analyst.

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