The table below gives the age and bone density for 5 women. Use the equation of the regression line, y= b0 + b1x, for predicting a women's bone density based on her age. The correlation coefficient may or may not be statically significant for the data given. Remember it wouldn't be appropiate to use regression line to make a prediction if the correlation coefficient isn;t statically significant. (y has a "hat" on the top) age 39 51 54 56 67 bone density 355 349 347 315 313 Find the estimated slope. Rund your answer to three decimal places. Find the estimated y-intercept. Round your answer to three decimal places. Determine the value of the dependent variable y at x+ 0 (y has a "hat" onthe top) Find the estimated value of y when x = 51. Round your answer to three decimal places. Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the valueof the independent variable is increased by one unit, then find the change in the deoendent variable y. (y has a "hat" at the top) Find the value of the coefficient of dteremination. Round your answer to three decimal places.
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.
The table below gives the age and bone density for 5 women. Use the equation of the regression line, y= b0 + b1x, for predicting a women's bone density based on her age. The
| age | 39 | 51 | 54 | 56 | 67 |
| bone density | 355 | 349 | 347 | 315 | 313 |
Find the estimated slope. Rund your answer to three decimal places.
Find the estimated y-intercept. Round your answer to three decimal places.
Determine the value of the dependent variable y at x+ 0 (y has a "hat" onthe top)
Find the estimated value of y when x = 51. Round your answer to three decimal places.
Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the valueof the independent variable is increased by one unit, then find the change in the deoendent variable y. (y has a "hat" at the top)
Find the value of the coefficient of dteremination. Round your answer to three decimal places.
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