Correlation and Regression Analysis: A Comprehensive Guide for Psychology Students

Question 1

In a regression line, a regression coefficient of -0.5 indicates that:

Accepted Answer

The dependent variable decreases by 0.5 units for every 1-unit increase in the independent variable.

Answer

The dependent variable increases by 0.5 units for every 1-unit increase in the independent variable.

Answer

The dependent variable is unrelated to the independent variable.

Answer

The independent variable increases by 0.5 units for every 1-unit increase in the dependent variable.

Question 2

A Pearson correlation coefficient of **0.60** indicates a relationship that is:

Accepted Answer

Moderate and positive

Answer

Weak and positive

Answer

Weak and negative

Answer

Strong and negative

Question 3

In a multiple regression model, the adjusted R-squared value is:

Accepted Answer

Adjusted for the number of independent variables in the model

Answer

Always higher than the R-squared value

Answer

An indicator of the predictive power of the model

Answer

A measure of the strength of the relationship between the variables

Question 4

Which of the following statistical tests can be used to determine the significance of a correlation coefficient?

Accepted Answer

Z-test

Answer

T-test

Answer

F-test

Answer

Chi-square test

Question 5

When interpreting a Pearson correlation coefficient, a value نزدیک to 1 indicates:

Accepted Answer

A strong positive linear relationship

Answer

A strong negative linear relationship

Answer

A weak positive linear relationship

Answer

No linear relationship

Question 6

When the relationship between two variables is nonlinear, which correlation coefficient should be used?

Accepted Answer

Spearman rank correlation coefficient

Answer

Pearson correlation coefficient

Answer

Regression coefficient

Answer

Coefficient of determination

Question 7

Which of the following measures the proportion of variance in the dependent variable that is explained by the independent variable in a linear regression model?

Accepted Answer

Coefficient of determination

Answer

Pearson correlation coefficient

Answer

Spearman rank correlation coefficient

Answer

Regression coefficient

Question 8

When the regression line perfectly fits the data points, the coefficient of determination will be:

Accepted Answer

1

Answer

0

Answer

0.5

Answer

-1

Question 9

Which of the following is NOT a type of correlation?

Accepted Answer

Curvilinear correlation

Answer

Positive correlation

Answer

Negative correlation

Answer

Zero correlation

Question 10

What is the range of possible values for the Pearson correlation coefficient?

Accepted Answer

-1 to 1

Answer

0 to 1

Answer

-1 to 0

Answer

0 to 100

Question 11

What does the slope coefficient in a linear regression equation represent?

Accepted Answer

The average change in the dependent variable for a one-unit change in the independent variable

Answer

The average value of the dependent variable

Answer

The amount of variance in the dependent variable accounted for by the independent variable

Answer

The correlation coefficient between the variables

Question 12

Which of the following characteristics is associated with a strong positive correlation?

Accepted Answer

Data points are clustered around a line of best fit with a positive slope.

Answer

Data points are scattered randomly with no clear pattern.

Answer

Data points are dispersed evenly along a horizontal line.

Answer

Data points are scattered above and below the line of best fit.

Question 13

What is the range of potential values for the Pearson correlation coefficient?

Accepted Answer

-1 to 1

Answer

0 to 1

Answer

-100 to 100

Answer

-∞ to ∞

Question 14

Which type of regression line is NOT commonly used?

Accepted Answer

Exponential

Answer

Linear

Answer

Quadratic

Answer

Cubic

Question 15

What does the slope of a regression line represent?

Accepted Answer

The amount the dependent variable changes for a one-unit change in the independent variable

Answer

The mean of the dependent variable

Answer

The correlation between the two variables

Answer

The intercept of the line

Question 16

Which of the following measures the goodness of fit of a regression line to the data?

Accepted Answer

Coefficient of determination

Answer

Root mean squared error

Answer

Correlation coefficient

Answer

P-value

Question 17

What is the purpose of hypothesis testing in regression analysis?

Accepted Answer

To determine if the regression line is statistically significant

Answer

To calculate the correlation coefficient

Answer

To estimate the slope of the regression line

Answer

To predict the dependent variable

Question 18

Which statistical test is used to determine the significance of a regression line?

Accepted Answer

F-test

Answer

t-test

Answer

χ² test

Answer

ANOVA

Question 19

Which measure quantifies the strength and direction of the linear relationship between two variables?

Accepted Answer

Pearson correlation coefficient

Answer

Spearman rank correlation coefficient

Answer

Linear regression coefficient

Answer

R-squared

Question 20

What is the primary purpose of linear regression analysis?

Accepted Answer

Predicting the value of one variable based on another

Answer

Measuring the strength of the relationship between two variables

Answer

Determining significant differences between groups

Answer

Identifying outliers in data

Question 21

Which of the following is NOT an assumption of linear regression analysis?

Accepted Answer

Error-free measurement of the independent variable

Answer

Linear relationship between variables

Answer

Normally distributed residuals

Answer

Constant variance of residuals

Question 22

What does the R-squared value represent in linear regression analysis?

Accepted Answer

Proportion of variance in the dependent variable explained by the independent variable

Answer

Strength of the relationship between variables

Answer

Significance of the regression model

Answer

Slope of the regression line

Question 23

Which option describes a limitation of correlation analysis?

Accepted Answer

Cannot establish causality

Answer

Only applicable to linear relationships

Answer

Sensitive to outliers

Answer

Cannot be used for prediction

Question 24

What is the key difference between simple and multiple linear regression?

Accepted Answer

Simple linear regression uses one independent variable, while multiple linear regression uses two or more.

Answer

Multiple linear regression uses one dependent variable, while simple linear regression uses two or more.

Answer

Simple linear regression is used for prediction, while multiple linear regression is used for explanation.

Answer

Multiple linear regression is more sensitive to outliers than simple linear regression.

Question 25

In linear regression analysis, what does the intercept represent?

Accepted Answer

Value of the dependent variable when the independent variable is zero

Answer

Slope of the regression line

Answer

Standard error of the regression

Answer

R-squared value

Question 26

What does a correlation coefficient of -0.75 between variables X and Y indicate?

Accepted Answer

A strong negative relationship

Answer

A moderate positive relationship

Answer

A weak negative relationship

Question 27

What is the range of possible values for the Pearson correlation coefficient?

Accepted Answer

-1 to 1

Answer

0 to 1

Answer

-0.5 to 0.5

Answer

-100 to 100

Question 28

What does the slope coefficient in a linear regression equation represent?

Accepted Answer

The average change in the dependent variable for a one-unit increase in the independent variable, assuming a linear relationship

Answer

The intercept of the regression line

Answer

The correlation between the variables

Answer

The standard deviation of the dependent variable

Question 29

What is the main purpose of a scatterplot in statistical analysis?

Accepted Answer

To visualize the relationship between two variables

Answer

To predict the value of one variable based on another

Answer

To test the significance of a correlation coefficient

Answer

To determine the slope of a regression line

Question 30

Which of the following is NOT a step typically involved in conducting a correlation analysis?

Accepted Answer

Designing the experiment or study

Answer

Calculating the correlation coefficient

Answer

Testing the significance of the correlation coefficient

Answer

Interpreting the results

Question 31

What is the key difference between a positive correlation and a negative correlation?

Accepted Answer

A positive correlation indicates a positive relationship, while a negative correlation indicates a negative relationship

Answer

A positive correlation indicates a negative relationship, while a negative correlation indicates a positive relationship

Answer

There is no difference between a positive and negative correlation

Answer

A positive correlation indicates a strong relationship, while a negative correlation indicates a weak relationship

Question 32

In a significance test for a correlation coefficient, what is the null hypothesis?

Accepted Answer

The correlation coefficient is equal to 0

Answer

The correlation coefficient is not equal to 0

Answer

The correlation coefficient is positive

Answer

The correlation coefficient is negative

Question 33

What does the slope of a regression line indicate?

Accepted Answer

Average change in the dependent variable for a one-unit change in the independent variable.

Answer

Correlation between the dependent and independent variables.

Answer

Regression line intercept.

Answer

Regression analysis p-value.

Question 34

What is the null hypothesis in correlation analysis?

Accepted Answer

There is no statistically significant correlation between variables.

Answer

There is a statistically significant correlation between variables.

Answer

The correlation between variables is positive.

Answer

The correlation between variables is negative.

Question 35

Which potential problem arises when using correlation to infer causation?

Accepted Answer

Lurking variables may exist.

Answer

Relationship direction cannot be determined.

Answer

Relationship strength cannot be quantified.

Answer

Relationship is not statistically significant.

Question 36

Which of the following is NOT a type of correlation coefficient used to assess the strength of a linear relationship between two variables?

Accepted Answer

Linear regression coefficient

Answer

Pearson correlation coefficient

Answer

Spearman rank correlation coefficient

Answer

Kendall's tau coefficient

Question 37

What does the slope of the regression line represent?

Accepted Answer

The average change in the dependent variable for each unit change in the independent variable

Answer

The intercept of the regression line

Answer

The correlation coefficient between the variables

Answer

The coefficient of determination

Question 38

What does the coefficient of determination indicate?

Accepted Answer

The proportion of variance in the dependent variable that is explained by the independent variable

Answer

The square root of the correlation coefficient

Answer

The slope of the regression line

Answer

The intercept of the regression line

Question 39

What is the primary purpose of a scatterplot in correlation and regression analysis?

Accepted Answer

To visualize the relationship between the variables

Answer

To calculate the correlation coefficient

Answer

To estimate the slope of the regression line

Answer

To test for normality of the residuals

Question 40

Which of the following is NOT a benefit of using correlation and regression analysis?

Accepted Answer

Drawing causal conclusions

Answer

Predicting the value of one variable based on another

Answer

Understanding the relationship between variables

Answer

Controlling for confounding variables

Question 41

How do correlation and regression differ?

Accepted Answer

Correlation measures the strength of the relationship between two variables, while regression predicts the value of one variable based on the other

Answer

Regression measures the strength of the relationship between two variables, while correlation predicts the value of one variable based on the other

Answer

Correlation and regression are the same thing

Answer

Correlation measures the direction of the relationship between two variables, while regression predicts the strength of the relationship