Statistical Control MCQs

Statistical Control MCQs

Welcome to MCQss.com, your source for multiple-choice questions (MCQs) on statistical control. This page contains a collection of MCQs designed to help you improve your understanding of this important statistical concept.

Statistical control refers to the process of accounting for and eliminating the influence of extraneous variables in an analysis. It is used to ensure that the relationship between the independent and dependent variables is accurately estimated without the interference of confounding factors. Statistical control is commonly employed in experimental design, regression analysis, and other statistical modeling techniques.

To excel in this topic, it is essential to grasp the concepts of confounding variables, randomization, blocking, and covariate adjustment. Understanding the principles and methods of statistical control allows researchers to draw valid conclusions and make meaningful inferences from their data.

At MCQss.com, we offer free interactive MCQs on statistical control to help you assess your knowledge and practice applying concepts. These MCQs cover various aspects of statistical control, including experimental design, analysis of covariance (ANCOVA), and the use of control variables in regression analysis.

By utilizing our MCQs, you can evaluate your proficiency, identify areas for improvement, and reinforce your understanding of statistical control in a practical and engaging manner. Whether you are preparing for exams, interviews, quizzes, or simply seeking to enhance your knowledge, our MCQs provide a valuable resource for self-assessment and learning.

The benefits of using MCQs for statistical control include gaining a deeper understanding of the topic, improving analytical skills, and enhancing problem-solving abilities. MCQs allow you to test your knowledge, apply theoretical concepts to real-world scenarios, and build confidence in your ability to implement statistical control techniques.

1: When information is available about at least one additional variable (Z) is known as:

A.   Covariate

B.   Control Variable

C.   Experimental Control

D.   Statistical Control

2: ___________________ means researchers may use a variety of strategies to “control” variables other than the manipulated independent variable.

A.   Covariate

B.   Control Variable

C.   Experimental Control

D.   Statistical Control

3: A covariate is a variable that is included so that its association with the Y outcome and its confound with other predictors can be statistically controlled when assessing the predictive importance of other variables that are of greater interest is called ___________ .

A.   Covariate

B.   Control Variable

C.   Experimental Control

D.   Statistical Control

4: A correlation between X1 and Y is said to be spurious if the correlation drops to 0 when you control for an appropriate X2 variable is known as:

A.   Suppressor Variable

B.   Spurious Correlation

C.   Suppression

D.   None of these

5: In a first-order partial correlation, just one other variable is statistically controlled when the relation between X1 and Y is assessed is called __________ .

A.   Second-Order Partial Correlation

B.   First-Order Partial Correlation

C.   Both

D.   None of these

6: _______________ is a second-order partial correlation between X1 and Y involves statistically controlling for two variables (such as X2 and X3) while assessing the relationship between X1 and Y.

A.   Second-Order Partial Correlation

B.   First-Order Partial Correlation

C.   Both

D.   None of these

7: Suppression is a X2 is said to suppress the X1, Y relationship if the relationship between X1 and Y either gets stronger or reverses sign when X2 is statistically controlled.

A.   True

B.   False

8: An X2 variable is called a suppressor variable relative to X1 and Y if the partial correlation between X1 and Y controlling for X2 (r1Y.2) is larger in absolute magnitude than r1Y is known as:

A.   Error Variance

B.   Suppressor Variable

C.   Both

D.   None of these

9: The proportion of variance in scores for a dependent variable that is not predictable from independent variables included in the analysis is called __________ .

A.   Error Variance

B.   Suppressor Variable

C.   Both

D.   None of these