1. Regression analysis was applied to return rates of sparrow hawk colonies. Regression analysis was used to study the relationship between return rate (x: % of birds that return to the colony in a given year) and immigration rate (y: % of new adults that join the colony per year). The following regression equation was obtained. ! = 31.9 – 0.34x Based on the above estimated regression equation, if the return rate were to decrease by 10% the rate of immigration to the colony would: a. increase by 34% b. increase by 3.4% c. decrease by 0.34% d. decrease by 3.4%ood alcohol by exactly 0.018/
1.
a. increase by 34%
b. increase by 3.4%
c. decrease by 0.34%
d. decrease by 3.4%ood alcohol by exactly 0.018/
2. In regression analysis, the variable that is being predicted is the
a. response, or dependent, variable
b. independent variable
c. intervening variable
d. is usually x
3. The
a. A specific value of the y-variable given a specific value of the x-variable
b. A specific value of the x-variable given a specific value of the y-variable
c. The strength of the relationship between the x and y variables
d. None of these
4. If there is a very strong correlation between two variables then the correlation coefficient must be
a. any value larger than 1
b. much smaller than 0, if the correlation is negative
c. much larger than 0, regardless of whether the correlation is negative or positive
d. None of these alternatives is correct.
5. The relationship between number of beers consumed (x) and blood alcohol content (y) was studied in 16 male college students by using least squares regression. The following regression equation was obtained from this study: != -0.0127 + 0.0180x The above equation implies that:
a. each beer consumed increases blood alcohol by 1.27%
b. on average it takes 1.8 beers to increase blood alcohol content by 1%
c. each beer consumed increases blood alcohol by an average of amount of 1.8%
d. each beer consumed increases bl
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