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 0.86
C 0.92
D 0.63
Question #3
A Both
B its size
C Its sign (+ or – )
D Neither
Question #4
A X is NOT a good predictor of Y
B low scores on X are associated with low scores on Y
C High scores on X are associated with high scores on Y
D X is 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 ordinal level data
D both nominal and interval
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 amount of change in Y for each unit change in X
D the point where the regression line crosses the Y axis when X = 0
Question #8
A neither its sign (+ or -) or size
B its sign (+ or -)
C both its size and sign (+ or -)
D its size
Question #9
A Cramer’s V
B Spearman’s rank order correlation coefficient
C Pearson’s r
D contingency coefficient
Question #10
A Spearman’s r
B Phi coefficient
C Pearson’s r
D Contingency Coefficient
Question #11
A Cramer’s V
B Goodman’s and Kruskal’s Gamma
C Pearson’s r
D Spearman’s r
Question #12
A the given table does not have the same number of row and columns
B the table is 2 x 2
C the table has the same number of rows and columns
D there is a large sample
Question #13
A the independent variable is influenced by the dependent variable
B the independent variable must be categorical in nature
C one variable is believed to be influenced by the other
D the variables being investigated must be correlated
Question #14
A the proporion of variance in Y that is attributed to error
B the proportion of the variance in Y that is explained by X
C the proportion of variance in X that is attributed to error
D the proportion of variance in Y that is NOT explained by X
Question #15
A the worse the obtained data fit the regression line
B the less variance has been accounted for by the independent variable
C the better the obtained data fit the regression line (AKA line of best fit)
D the ore the independent variable predicts the independent variable
Question #16
A the amount of change in X for each change in Y
B the point where the regression line crosses the Y-axis when X=0
C the point where the regresssion line corsses the X-axis when Y=0
D the amount of change in Y for each unit change in X
Question #17
A a negative relationship
B curvilienear relationship
C a positive relationship
D not enough information to answer question
Question #18
A varies from -1.0 to +1.0
B presents the direction of the relationship
C presents the strength of the relationship
D all of the above
Question #19
A (+0.58)
B (+0.12)
C -0.28
D -0.31
Question #20
A correlations provide statements of causation
B correlations can never exceed 1.0
C correlations can be negative
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 positive
B inverse
C there is not enough information to estimate the nature of the correlation
D negative