Navigation » List of Schools » Los Angeles Harbor College » Statistics » Statistics 001 – Elementary Statistics I for the Social Sciences » Spring 2020 » Exam 4
Below are the questions for the exam with the choices of answers:
Question #1
A Ordinal data
B The chi-square value
C Ranked scores
D All of the above
Question #2
A 0.14
B 0.63
C 0.86
D 0.92
Question #3
A Neither
B Its sign (+ or – )
C its size
D Both
Question #4
A High scores on X are associated with high scores on Y
B X is a good predictor of Y
C low scores on X are associated with low scores on Y
D X is NOT a good predictor of Y
Question #5
A for tables that are 2 x 2
B for nominal data
C when random sampling has been used
D all of the above
Question #6
A nominal level data
B interval level data
C both nominal and interval
D ordinal level data
Question #7
A the points where the regression line crosses the X axis when Y = 0
B the amount of change in X for each unit change in Y
C the point where the regression line crosses the Y axis when X = 0
D the amount of change in Y for each unit change in X
Question #8
A neither its sign (+ or -) or size
B both its size and sign (+ or -)
C its sign (+ or -)
D its size
Question #9
A Spearman’s rank order correlation coefficient
B Pearson’s r
C contingency coefficient
D Cramer’s V
Question #10
A Spearman’s r
B Contingency Coefficient
C Pearson’s r
D Phi coefficient
Question #11
A Goodman’s and Kruskal’s Gamma
B Spearman’s r
C Pearson’s r
D Cramer’s V
Question #12
A the table has the same number of rows and columns
B there is a large sample
C the given table does not have the same number of row and columns
D the table is 2 x 2
Question #13
A the variables being investigated must be correlated
B one variable is believed to be influenced by the other
C the independent variable is influenced by the dependent variable
D the independent variable must be categorical in nature
Question #14
A the proporion of variance in Y that is attributed to error
B the proportion of variance in Y that is NOT explained by X
C the proportion of variance in X that is attributed to error
D the proportion of the variance in Y that is explained by X
Question #15
A the ore the independent variable predicts the independent variable
B the better the obtained data fit the regression line (AKA line of best fit)
C the worse the obtained data fit the regression line
D the less variance has been accounted for by the independent variable
Question #16
A the amount of change in X for each change in Y
B the amount of change in Y for each unit change in X
C the point where the regression line crosses the Y-axis when X=0
D the point where the regresssion line corsses the X-axis when Y=0
Question #17
A a positive relationship
B not enough information to answer question
C curvilienear relationship
D a negative relationship
Question #18
A presents the strength of the relationship
B presents the direction of the relationship
C varies from -1.0 to +1.0
D all of the above
Question #19
A -0.31
B -0.28
C (+0.12)
D (+0.58)
Question #20
A correlations provide statements of causation
B correlations can be negative
C correlations can never exceed 1.0
D correlations closer to 0.0 are considered to be weak, while correlations closer to 1.0 are considered to be strong.
Question #21
A there is not enough information to estimate the nature of the correlation
B positive
C inverse
D negative