Merlins breeding gives data on the number of breeding pairs of merlins in an iso
ID: 3172498 • Letter: M
Question
Merlins breeding gives data on the number of breeding pairs of merlins in an isolated area in each of nine years and the percent of males who returned the next year. The data show that the percent returning is lower after successful breeding seasons and that the relationship is roughly linear. Figure 5.11 shows software regression output for these data. What is the equation of the least-squares regression lion for predicting the percent of males that return from the number of breeding pairs? Use the equation to predict the percent of returning males after a season with 30 breeding pairs. What percent of the year-to year variation in percent of returning males is explained by the straight -line relationship with number of breeding pairs the previous year? Husbands and wives. The mean height of American women in their twenties is about 64 inches, and the standard deviation is about 2.7 inches. The mean height of men the same age is about 69.3 inches, With standard deviation about 2.8 inches. if the correlation between the heights of husbands and Wives is about r = 0.5, what is the slope of the regression line of the husband's height on the wife's height in young couples? Draw a graph of this regression line. Predict the height of the husband of a woman who is 67 inches tall What's my grade? In professor Friedman's economics course the correlation between the students' total scores prior to the final examination and their final-examination scores is r = 0.6.The pre-exam totals for all students in the course have mean 280 and standard deviation 30.The final-exam scores have mean 75 and standard deviation 8.professor Friedman has lost Julie's final exam.Explanation / Answer
5.29
a) From given regression results,
Equation of least square regression line:
pct = 157.68216 - 2.9934945* pairs
For pairs = 30,
pct = 157.68216 - 2.9934945* 30 = 67.877 (Rounded off to three decimal places)
So,
For 30 breeding pairs, the percentage of returning males after a season is approx 67.88%.
b) From regression output,
R - sq = 0.6308588
Hence,
Approx 63.09% of the variation in percentage of returning males can be explained by the linear relationship with number of breeding pairs the previous year.