In: Statistics and Probability
1. Which of the following symbols is used to reflect Goodman and Kruskal's gamma?
a. r2
b. Y
c. β
d. Ø
e. λ
2. Briefly explain how an analyst should interpret the r2 value in a regression analysis.
3. Explain how a researcher should interpret a correlation coefficient.
4. When the number of discordant pairs and concordant pairs in a P-Q relationship is equal, the interpretation is that the variables _____.
a. are perfectly correlated
b. have a weak but significant relationship
c. are normally distributed
d. have no relationship
e. have a negative association
5. Which of the following is true of relationships among nominal measures?
a. when there is no relationship at all, the coefficient should be 1.
b. when there is no relationship at all, the coefficient should be 0.
c. When there is complete dependency, the coefficient should be negative.
d. When there is complete dependency, the coefficient should be positive
e. none are correct
Ans1;- (b) Y
Ans2:- The r2 is the coefficient of determination and it refers to the amount of common variance in two variables in a regression equation. Consequently, it allows the analyst to assess how much of a variable (the dependent variable) can be explained by the variables in the equation (the independent variables.
Ans3:-To interpret a correlation coefficient, one will address three pieces of information. First, is the relationship significant? If the significance level (p value) is less than the alpha level (typically .05), then the relationship is significant and the researcher will reject the null hypothesis. This means that the relationship is real and is not occurring simply by chance. Second, the researcher will assess the magnitude of the correlation coefficient. A correlation coefficient can range from -1 to +1. The closer to 1 (either positive or negative), the stronger the relationship is. Third, the researcher will evaluate the direction of the relationship by observing the sign of the correlation coefficient. If the sign is positive, then the relationship is positive. A positive relationship means that the variables covary together. If the sign is negative, then the relationship is inverse. This means that the variables covary in opposite directions.
Ans4:- (d) have no relanationship
Ans5:- (e) none are correct