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