Examining Relationships among Statistics and Applications MCQs
Examining Relationships among Statistics and Applications MCQs
Answer these 30 Examining Relationships among Statistics and Applications MCQs and assess your grip on the subject of Examining Relationships among Statistics and Applications.
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1: Restricting the upper limit of a measure so that higher levels of a measure are not assessed accurately is called
A. Ceiling effect
B. Correlation effect
C. Main effect
D. Multiple effect
2: Coefficient of determination is proportion of vari-ability accounted for by knowing the relationship (correla-tion) between ___ variables.
A. One
B. Two
C. Three
D. Fourth
3: A relationship between variables is called
A. Correlation
B. Coefficient
C. Frequency
D. All of these
4: A correlational research design investigates relationships between variables without the researcher controlling or manipulating any of them
A. True
B. False
5: Criterion variable is predicted variable in a regression equation.
A. True
B. False
6: Dichotomous variable is a nominal variable that has ___ levels or groups.
A. One
B. Two
C. Three
D. Zero
7: Restricting the lower limit of a measure so that lower scores are not assessed accurately is called
A. Main effect
B. Floor effect
C. Constant effect
D. Single effect
8: A relationship between two variables, defined by their moving in a single direction together is ____ relationship
A. Linear
B. Nonlinear
C. Constant
D. Zero
9: ____ regression is a statistical technique that computes both the individual and combined contribu-tion of two or more variables to the prediction of another variable.
A. Single
B. Multiple
C. Zero
D. Constant
10: A relationship where scores on two variables move in opposite directions (one increases while the other decreases).
A. Positive correlation
B. Negative correlation
C. Zero correlation
D. Constant correlation
11: Perasons's r coefficient in statistics used to describe a linear rela-tionship between ___interval/ratio measures describes the direction (positive or negative) and strength (between +/− 1.0) of the relationship.
A. One
B. Two
C. Zero
D. Three
12: Point biserial correlation coefficient describes the relationship between a dichotomous variable and an interval/ratio variable; interpreted similarly to a Pearson correlation coefficient.
A. True
B. False
13: A relationship where scores on two variables move in the same direction is called
A. Positive correlation
B. Negative correlation
C. Zero correlation
D. Constant correlation
14: The variable that is used to predict the value of another variable, and a term used instead of IV in a correlational design.
A. Scatterplot
B. Slope
C. Regression
D. Predictor
15: Equation that describes the rela-tionship between ___variables and allows us to predict Y from X.
A. One
B. Two
C. Three
D. Fourth
16: A graph of the data points created by participant scores on two measures is called
A. Scatterplot
B. Slope
C. Regression
D. Predictor
17: Describes the rate of change in Y with each unit of change in X (or the incline of the line of best fit), desig-nated by “___” in the regression equation is called slope
A. A
B. B
C. X
D. Y
18: Standard error of the estimate is formula for a ___ regression equation.
A. Linear
B. Nonlinear
C. Constant
D. Zero
19: The point at which a line of best fit crosses the y-axis, designated as “___” in the regression equation is Y intercept
A. A
B. B
C. X
D. Y
20: The value that results from entering a particular X value in a regression equation is ___ predicted
A. X
B. Y
C. Z
D. S
21: After the first test, your professor found a correlation of r = –.23 between students’ self-reported anxiety and test scores. This means that ______.
A. Students’ level of anxiety is not related to their test scores
B. There is a moderate positive relationship between anxiety and test scores
C. There is a weak negative relationship between anxiety and test scores
D. Anxiety causes lower test scores
22: When two variables move in the same direction together (both increase or both decrease), they will be ______.
A. Positively correlated
B. Negatively
C. Not correlated
D. Perfectly correlated
23: The statistic used to assess relationships between two interval/ratio variables is a ______.
A. Pearson’s correlation coefficient
B. Point-biserial correlation coefficient
C. Regression equation
D. Multiple R
24: You are studying the relationship between pet ownership (yes–no) and life satisfaction. You should compute a ______.
A. Pearson’s correlation coefficient
B. Point-biserial correlation coefficient
C. Regression equation
D. Multiple R
25: The regression equation is the formula ______.
A. For the line of best fit
B. Used to determine whether we have a strong correlation between variables
C. Used to determine whether X caused changes in Y
D. Used to graph all of the X and Y values
26: The standard error of the estimate represents the ______.
A. Error in our dependent variable due to the independent variable
B. Difference between the X and Y values
C. Average difference between the predicted Y values (Y′) and their actual values
D. Estimated error in X values once Y values have been predicted
27: The scatterplot above depicts a ______.
A. No relationship
B. Positive relationship
C. Negative relationship
D. Perfect relationship
28: Correlational studies are used ______.
A. As a pilot study to examine trends before an experiment is conducted
B. To assess reliability and validity of measures
C. To supplement other studies
D. All of these
29: By substituting an X value in the regression equation, we compute the ______.
A. Predicted Y (Y′) value that falls on the line of best fit
B. Actual Y value in our sample that also falls on the line of best fit
C. Actual Y value in our sample that does not fall on the line of best fit
D. Error between the predicted and actual Y values
30: After the first quiz to assess student knowledge of the reading material, a professor reports that student scores ranged from 0 to 2 on the 10-point quiz. If the students really read the material, what could explain the scores?
A. Floor effect
B. Ceiling effect
C. The quiz may be unreliable.
D. The quiz did not engage the students.
31: The straight line that best fits a correla-tion and consists of each X value in the relationship and its predicted Y value is line of best fit
A. True
B. False
Examining Relationships among Statistics and Applications MCQs
