Suppose that a random sample of 200 twenty-year-old men is selected from a population and that these men's height and weight are recorded. A regression of weight on height yields Woight= (- 101.3982) + 4.0188 x Height, R = 0.83, SER = 10.4, where Weight is measured in pounds and Height is measured in inches. What is the regression's weight prediction for someone who is 71 inches tall? The regression's weight prediction for someone who is 71 inches tall is pounds. (Round your response to two decimal places.) A man has a late growth spurt and grows 1.2 inches over the course of a year. What is the regression's prediction for the increase in this man's weight? The regression's prediction for the increase in this man's weight ispounds. (Round your response to two decimal places.) Suppose that instead of measuring weight and height in pounds and inches these variables are measured in centimeters and kilograms (1 in = 2.54 cm and 1 b = 0.4536 kg). Suppose the regression equation in centimeter-kilogram units is: Weight = 70 +7, Height.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
 alt="Suppose that a random sample of 200 twenty-year-old men is selected from a population and that these men's height and weight are
recorded. A regression of weight on height yields
Weight= (-101.3982)+ 4.0188 x Height, R = 0.83, SER = 10.4,
where Weight is measured in pounds and Height is measured in inches.
What is the regression's weight prediction for someone who is 71 inches tall?
The regression's weight prediction for someone who is 71 inches tall is pounds. (Round your response to two decimal places.)
A man has a late growth spurt and grows 1.2 inches over the course of a year. What is the regression's prediction for the increase in
this man's weight?
The regression's prediction for the increase in this man's weight is I pounds. (Round your response to two decimal places.)
Suppose that instead of measuring weight and height in pounds and inches these variables are measured in centimeters and
kilograms (1 in = 2.54 cm and 1 lb = 0.4536 kg).
Suppose the regression equation in centimeter-kilogram units is:
Weight = 70 + 7,Height.
The regression estimates from this new centimeter-kilogram regression are:
70 =O kg. (Round your response to four decimal places.)
71 = kg per cm. (Round your response to four decimal places.)
%3D
R2 =D (Round your response to two decimal places.)
SER =O kg. (Round your response to four decimal places.)
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