Statistics 001 - Elementary Statistics I for the Social Sciences » Spring 2020 » Exam 4
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Question #1
If we correlated people’s height and their shoe size, the correlation would probably be:
A.
there is not enough information to estimate the nature of the correlation
B.
positive
C.
negative
D.
inverse
Question #2
which statement is NOT true of Pearson’s Correlation Coefficient (r)?
A.
correlations can never exceed 1.0
B.
correlations provide statements of causation
C.
correlations closer to 0.0 are considered to be weak, while correlations closer to 1.0 are considered to be strong.
D.
correlations can be negative
Question #3
Choose the weakest correlation:
A.
-0.28
B.
(+0.58)
C.
(+0.12)
D.
-0.31
Question #4
Pearson’s Correlation Coefficient (r):
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 #5
As years of educaiton increase, the likelihood of domestic violence decreases. This is an example of :
A.
curvilienear relationship
B.
a positive relationship
C.
not enough information to answer question
D.
a negative relationship
Question #6
In a regresion equation a refers to:
A.
the point where the regression line crosses the Y-axis when X=0
B.
the point where the regresssion line corsses the X-axis when Y=0
C.
the amount of change in X for each change in Y
D.
the amount of change in Y for each unit change in X
Question #7
The stronger the correlation:
A.
the better the obtained data fit the regression line (AKA line of best fit)
B.
the less variance has been accounted for by the independent variable
C.
the ore the independent variable predicts the independent variable
D.
the worse the obtained data fit the regression line
Question #8
The coefficient of determination explains:
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 #9
In regression analysis:
A.
the variables being investigated must be correlated
B.
one variable is believed to be influenced by the other
C.
the independent variable must be categorical in nature
D.
the independent variable is influenced by the dependent variable
Question #10
Cramer’s V is preferable to the Contingency Coefficient when:
A.
there is a large sample
B.
the table is 2 x 2
C.
the given table does not have the same number of row and columns
D.
the table has the same number of rows and columns
Question #11
When ordinal data measurement produces a large number of tied ranks, we should use:
A.
Cramer’s V
B.
Goodman’s and Kruskal’s Gamma
C.
Pearson’s r
D.
Spearman’s r
Question #12
When nominal data are presented in a 3 x 3 cross -tabulation, the correlation is computed usig the:
A.
Pearson’s r
B.
Spearman’s r
C.
Contingency Coefficient
D.
Phi coefficient
Question #13
To determine the relationshiop between rank-ordered or ordinal data, we compute:
A.
Pearson’s r
B.
contingency coefficient
C.
Cramer’s V
D.
Spearman’s rank order correlation coefficient
Question #14
The direction of the correlation is indicated by:
A.
its size
B.
its sign (+ or -)
C.
both its size and sign (+ or -)
D.
neither its sign (+ or -) or size
Question #15
In a regression equation, the slope accounts for:
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 #16
Which of the following is a requirement when computing Spearman’s Correlation Coefficient?
A.
nominal level data
B.
interval level data
C.
ordinal level data
D.
both nominal and interval
Question #17
As measure association, the Phi coefficient can only be used
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 #18
A strong correlation between variable X and Y implies:
A.
X is a good predictor of Y
B.
X is NOT 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 #19
The strengh of the correlation is indicated by:
A.
Its sign (+ or - )
B.
its size
C.
Both
D.
Neither
Question #20
Its r2 = .37, the coefficient of non-determination is equal to:
A.
0.63
B.
0.86
C.
0.14
D.
0.92
Question #21
To calculate the Phi coefficient we require:
A.
The chi-square value
B.
Ordinal data
C.
Ranked scores
D.
All of the above
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