Exercise 7.15 introduces data on shoulder girth and height of a group of individuals. In the data set, the minimum shoulder girth is 87 cm and the maximum shoulder girth is 134 cm. The mean shoulder girth is 105.87 cm with a standard deviation of 10.13 cm. The mean height is 173.14 cm with a standard deviation of 9.01 cm. The correlation between height and shoulder girth is 0.695. a) Write the equation of the regression line for predicting height. Slope (round 3 decimal places): c) Calculate R2R2 of the regression line for predicting height from shoulder girth. Round to three decimal places Interpret R2R2 in the context of the application. A. About 100*(R2R2)% of the variability in height is accounted for by the model, i.e. explained by the shoulder girth B. About 100*(R2R2)% of the variability in shoulder girth is accounted for by the model, i.e. explained by the height C. About 100*(R2R2)% of the data in height is accounted for by the model, i.e. explained by the shoulder girth D. About 100*(R2R2)% of data in shoulder girth is accounted for by the model, i.e. explained by height
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
Exercise 7.15 introduces data on shoulder girth and height of a group of individuals. In the data set, the minimum shoulder girth is 87 cm and the maximum shoulder girth is 134 cm. The mean shoulder girth is 105.87 cm with a standard deviation of 10.13 cm. The mean height is 173.14 cm with a standard deviation of 9.01 cm. The
a) Write the equation of the regression line for predicting height.
Slope (round 3 decimal places):
c) Calculate R2R2 of the regression line for predicting height from shoulder girth. Round to three decimal places
Interpret R2R2 in the context of the application.
A. About 100*(R2R2)% of the variability in height is accounted for by the model, i.e. explained by the shoulder girth
B. About 100*(R2R2)% of the variability in shoulder girth is accounted for by the model, i.e. explained by the height
C. About 100*(R2R2)% of the data in height is accounted for by the model, i.e. explained by the shoulder girth
D. About 100*(R2R2)% of data in shoulder girth is accounted for by the model, i.e. explained by height
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