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Introduction to Correlation and Regression MCQ

1. Just because there is a correlation between a and b __________.

Is the same as the correlation between B and A.

At least one output and one input, but the output obviously is insufficient to generate the input shown

At least one input and one output, but the input obviously is insufficient to generate the output shown

Answer

Correct Answer: Is the same as the correlation between B and A.

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2. Based on the regression equation, we can _______________.

Predict the value of the dependent variable given a value of the independent variable

Predict the value of the independent variable given a value of the dependent variable

Predict the value slope of the line

Measure the association between two variables

Answer

Correct Answer: Predict the value of the dependent variable given a value of the independent variable

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3. A ______ shows two variables combined as individual points on a graph.

Positive correlation

A positive correlation between amount of sunlight and plant growth.

A positive correlation between studying and grades

Negative correlation

Answer

Correct Answer: Positive correlation

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4. A relationship in which one factor can be said to be the cause of another is called as “chance is lumpy”

True

False

Answer

Correct Answer: True

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5. The correlation in which variable x may be related to y or the variable y may be related to x is known as_____

Pearson’s product–moment correlation

Zero-order correlation

Point-biserial correlation

Spearman’s Correlation

Answer

Correct Answer: Zero-order correlation

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6. T distribution is a table of critical values that can be used to test the significance of_____

Correlation coefficient

Independent t test

Dependent t test

All of these

Answer

Correct Answer: All of these

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7. A relationship in which a low score on variable x will be associated with a low score on variable y is known as Strong Positive Relationship.

True

False

Answer

Correct Answer: True

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8. A relationship in which a high score on variable x will be associated with a high score on variable y is known as Strong Negative Relationship.

True

False

Answer

Correct Answer: False

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9. Spearman’s Correlation is represented by the coefficient _____

Rpb

Answer

Correct Answer: Rs

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10. A measure of the relationship between two ordinal rankings of the same set of data is known as_____

Pearson’s product–moment correlation

Phi correlation

Point-biserial correlation

Spearman’s Correlation

Answer

Correct Answer: Spearman’s Correlation

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11. A statistical procedure where the focus is on the way one variable (y) varies based on how one other variable (x) varies is known as simple regression.

True

False

Answer

Correct Answer: True

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12. Scatterplot is a graphic representation of the relationship of two _____ in correlational designs.

Dependent Variables

Confounding Variables

Continuous Variables

Independent Variables

Answer

Correct Answer: Continuous Variables

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13. Regression analysis is a statistical procedure that measures the strength of a relationship between _____

An independent variable and a dependent variable

Two dependent variables

Two independent variables

Two continuous variables

Answer

Correct Answer: An independent variable and a dependent variable

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14. Point-Biserial Correlation is a measure of the strength of a relationship between_____

A continuous and a dichotomous variable

Two continuous variables

Two dichotomous variables

None of these

Answer

Correct Answer: A continuous and a dichotomous variable

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15. Phi Correlation is a measure of the strength of a relationship between_____

A continuous and a dichotomous variable

Two continuous variables

Two dichotomous variables

None of these

Answer

Correct Answer: Two dichotomous variables

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16. A measure of the strength of a relationship between two continuous variables is known as_____

Pearson’s product–moment correlation

Phi correlation

Point-biserial correlation

None of these

Answer

Correct Answer: Pearson’s product–moment correlation

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17. Multiple regression analysis is a statistical procedure that measures the strength of a relationship between multiple independent variables and _____

Single dependent variable

Single independent variable

Multiple dependent variables

Multiple independent variables

Answer

Correct Answer: Single dependent variable

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18. Linear relationship is a relationship in which a straight line best fits the bivariate distribution of two _____

Confounding variables

Dependent variables

Discrete variables

All of these

Answer

Correct Answer: Confounding variables

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19. Least squares method is a method in regression that produces the single best-fitting line that predicts a _____

Y score given an X score

X score given a Y score

Both X and Y scores

None of these

Answer

Correct Answer: Y score given an X score

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20. Heteroscedasticity is a violation of homoscedasticity.

True

False

Answer

Correct Answer: True

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21. All are true about heteroscedasticity except_____

Violation of the homoscedasticity assumption

The bivariate distribution has greater variance for some values of the y scores

Linear regression distributions have similar variances

Linear regression distributions have different variances

Answer

Correct Answer: Linear regression distributions have different variances

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22. Degrees of freedom is a parameter that is equal to the _____ of observations or groups in a study minus some value(s) that limits the observations’ or groups’ freedom to vary.

Number

Sum of numbers

Square of numbers

Sum of square of numbers

Answer

Correct Answer: Number

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23. An assumption that a curved line best fits the graphic representation between two variables is known as _____

Linear relationship

Curved relationship

Curvilinear relationship

None of these

Answer

Correct Answer: Curvilinear relationship

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24. Correlation is the _____ between two variables.

Degree of freedom

Strength of a relationship

Dependance

None of these

Answer

Correct Answer: Strength of a relationship

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25. A constant is a _____ value in a statistical formula.

Common

Fixed

Nonspecified

All of these

Answer

Correct Answer: Fixed

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26. Coefficient of determination is obtained by squaring the _____ coefficient.

Phi

Pearson’s

Spearman

None of these

Answer

Correct Answer: Pearson’s

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27. Chi-square distribution is a theoretical sampling distribution that can be used to_____

Test the significance of a phi correlation

Test nonparametric frequency data

Test difference of variance

Both a and b

Answer

Correct Answer: Both a and b

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28. Causal relationships should never be inferred from a correlational design or a correlational test statistic, although correlational relationships may suggest causal relationships.

True

False

Answer

Correct Answer: True

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29. All are true about archival data except_____

Data that have already been collected

Experimenter only has statistical power

Experimenter has both statistical and experimental power

Experimenter can no longer change the original experimental design

Answer

Correct Answer: Experimenter has both statistical and experimental power

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MCQ on Analysis of Factorial ANOVA	MCQ on Basic Statistics
MCQ on Chi-Square and Nonparametric Tests in Statistics	MCQ on Computing Correlation Coefficients
MCQ on Computing and Understanding Averages in Statistics	MCQ on Creating Graphs in Statistics
MCQ on Factorial ANOVA Statistics	MCQ on Factorial ANOVA in Statistics
MCQ on Factorial Analysis of Variance in Statistics	MCQ on Gentle and Statistical Introduction
MCQ on Inferential Statistics	MCQ on Introduction to Correlation and Regression
MCQ on Introduction to Getting Most Out of Your BIG Data	MCQ on Introduction to Understanding statistical Reliability and Validity
MCQ on Measures of Central Tendency in Statistics	MCQ on Multiple Comparison Tests in Statistics
MCQ on Nonparametric Statistics	MCQ on One-Factor Completely Randomized Design
MCQ on One-Factor Repeated-Measures Design	MCQ on One-Sample Z Test
MCQ on Other (Important) Statistical Procedures	MCQ on Predicting the Future Statistics
MCQ on Significantly Significant in Statistics	MCQ on Standard Statistics Hypothesis Testing
MCQ on Statistical Probability	MCQ on Statistical Tests Between the Means of Different Groups
MCQ on Statistical Tests Between the Means of Related Groups	MCQ on Statistical Topics, Parameters, and Tests in Statistics
MCQ on Statistics or Sadistics	MCQ on T Test for Dependent Groups
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MCQ on Testing Your statistical Questions	MCQ on Try Analysis of Variance in Statistics
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