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