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 0.14
B 0.86
C 0.92
D 0.63
Question #3
A Neither
B Its sign (+ or – )
C its size
D Both
Question #4
A X is 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 NOT a good predictor of Y
Question #5
A for nominal data
B when random sampling has been used
C for tables that are 2 x 2
D all of the above
Question #6
A ordinal level data
B both nominal and interval
C interval level data
D nominal 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 its sign (+ or -)
C both its size and sign (+ or -)
D its size
Question #9
A contingency coefficient
B Pearson’s r
C Cramer’s V
D Spearman’s rank order correlation coefficient
Question #10
A Phi coefficient
B Spearman’s r
C Pearson’s r
D Contingency Coefficient
Question #11
A Pearson’s r
B Goodman’s and Kruskal’s Gamma
C Spearman’s r
D Cramer’s V
Question #12
A the table has the same number of rows and columns
B the given table does not have the same number of row and columns
C the table is 2 x 2
D there is a large sample
Question #13
A one variable is believed to be influenced by the other
B the independent variable is influenced by the dependent variable
C the independent variable must be categorical in nature
D the variables being investigated must be correlated
Question #14
A the proportion of variance in Y that is NOT explained by X
B the proporion of variance in Y that is attributed to error
C the proportion of the variance in Y that is explained by X
D the proportion of variance in X 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 less variance has been accounted for by the independent variable
D the better the obtained data fit the regression line (AKA line of best fit)
Question #16
A the point where the regression line crosses the Y-axis when X=0
B the amount of change in Y for each unit change in X
C the point where the regresssion line corsses the X-axis when Y=0
D the amount of change in X for each change in Y
Question #17
A not enough information to answer question
B a positive relationship
C a negative relationship
D curvilienear relationship
Question #18
A varies from -1.0 to +1.0
B presents the strength of the relationship
C presents the direction of the relationship
D all of the above
Question #19
A -0.31
B (+0.58)
C -0.28
D (+0.12)
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 be negative
C correlations provide statements of causation
D correlations can never exceed 1.0
Question #21
A negative
B positive
C inverse
D there is not enough information to estimate the nature of the correlation