Exam 4

A  Ranked scores

B  Ordinal data

C  The chi-square value

D  All of the above

A  0.92

B  0.63

C  0.86

D  0.14

A  Both

B  Neither

C  Its sign (+ or – )

D  its size

A  X is a good predictor of Y

B  X is NOT a good predictor of Y

C  low scores on X are associated with low scores on Y

D  High scores on X are associated with high scores on Y

A  for tables that are 2 x 2

B  when random sampling has been used

C  for nominal data

D  all of the above

A  both nominal and interval

B  nominal level data

C  interval level data

D  ordinal level data

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 amount of change in X for each unit change in Y

D  the points where the regression line crosses the X axis when Y = 0

A  its sign (+ or -)

B  its size

C  neither its sign (+ or -) or size

D  both its size and sign (+ or -)

A  contingency coefficient

B  Pearson’s r

C  Cramer’s V

D  Spearman’s rank order correlation coefficient

A  Phi coefficient

B  Contingency Coefficient

C  Pearson’s r

D  Spearman’s r

A  Goodman’s and Kruskal’s Gamma

B  Pearson’s r

C  Cramer’s V

D  Spearman’s r

A  the table has the same number of rows and columns

B  the table is 2 x 2

C  the given table does not have the same number of row and columns

D  there is a large sample

A  the independent variable must be categorical in nature

B  the independent variable is influenced by the dependent variable

C  one variable is believed to be influenced by the other

D  the variables being investigated must be correlated

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

A  the ore the independent variable predicts the independent variable

B  the less variance has been accounted for by the independent variable

C  the better the obtained data fit the regression line (AKA line of best fit)

D  the worse the obtained data fit the regression line

A  the amount of change in X for each change in Y

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 point where the regression line crosses the Y-axis when X=0

A  a positive relationship

B  a negative relationship

C  curvilienear relationship

D  not enough information to answer question

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

A  (+0.58)

B  (+0.12)

C  -0.28

D  -0.31

A  correlations closer to 0.0 are considered to be weak, while correlations closer to 1.0 are considered to be strong.

B  correlations provide statements of causation

C  correlations can never exceed 1.0

D  correlations can be negative

A  there is not enough information to estimate the nature of the correlation

B  positive

C  negative

D  inverse