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 Ranked scores
B The chi-square value
C Ordinal data
D All of the above
Question #2
A 0.63
B 0.14
C 0.86
D 0.92
Question #3
A Neither
B Its sign (+ or – )
C Both
D its size
Question #4
A low scores on X are associated with low scores on Y
B High scores on X are associated with high scores on Y
C X is NOT a good predictor of Y
D X is a good predictor of Y
Question #5
A when random sampling has been used
B for tables that are 2 x 2
C for nominal data
D all of the above
Question #6
A both nominal and interval
B interval level data
C ordinal level data
D nominal level data
Question #7
A the point where the regression line crosses the Y axis when X = 0
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 amount of change in Y for each unit change in X
Question #8
A its size
B neither its sign (+ or -) or size
C both its size and sign (+ or -)
D its sign (+ or -)
Question #9
A Pearson’s r
B contingency coefficient
C Cramer’s V
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 Goodman’s and Kruskal’s Gamma
C Cramer’s V
D Pearson’s r
Question #12
A the table has the same number of rows and columns
B there is a large sample
C the table is 2 x 2
D the given table does not have the same number of row and columns
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 proportion of the variance in Y that is explained by X
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 proporion of variance in Y that is attributed to error
Question #15
A the worse the obtained data fit the regression line
B the better the obtained data fit the regression line (AKA line of best fit)
C the ore the independent variable predicts the independent variable
D the less variance has been accounted for by the independent variable
Question #16
A the amount of change in Y for each unit change in X
B the amount of change in X for each change in Y
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 negative relationship
B curvilienear relationship
C a positive relationship
D not enough information to answer question
Question #18
A presents the strength of the relationship
B varies from -1.0 to +1.0
C presents the direction of the relationship
D all of the above
Question #19
A -0.28
B (+0.12)
C (+0.58)
D -0.31
Question #20
A correlations can never exceed 1.0
B correlations can be negative
C correlations provide statements of causation
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