A statistical program is recommended. Is the number of square feet of living space a good predictor of a house's selling price? The following data show the square footage and selling price for fifteen houses in Winston-Salem, North Carolina.† Size (1,000s sq. ft) Selling Price ($1,000s) 1.26 117.5 3.02 299.9 1.99 139.0 0.91 45.6 1.87 129.9 2.63 274.9 2.60 259.9 2.27 177.0 2.30 175.0 2.08 189.9 1.12 95.0 1.38 82.1 1.80 169.0 1.57 96.5 1.45 114.9 #1) Find the value of the test statistic (round to two decimal places). Find the p-Value (round to three decimal places) #2) Use the estimated regression equation to predict the selling price (in $1,000s) of a 2,100 square foot house in Winston-Salem, North Carolina. (Round your answer to one decimal place.) = $______ Thousand #3)Do you believe the estimated regression equation developed in part (b) will provide a good prediction of selling price of a particular house in Winston-Salem, North Carolina? Explain. (Round your answer to three decimal places.) Since r2 =______ is (at least OR less than .55) , the estimated regression equation will (provide OR not provide) a good prediction of selling price of a particular house in Winston-Salem.
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.
| Size (1,000s sq. ft) |
Selling Price ($1,000s) |
|---|---|
| 1.26 | 117.5 |
| 3.02 | 299.9 |
| 1.99 | 139.0 |
| 0.91 | 45.6 |
| 1.87 | 129.9 |
| 2.63 | 274.9 |
| 2.60 | 259.9 |
| 2.27 | 177.0 |
| 2.30 | 175.0 |
| 2.08 | 189.9 |
| 1.12 | 95.0 |
| 1.38 | 82.1 |
| 1.80 | 169.0 |
| 1.57 | 96.5 |
| 1.45 | 114.9 |
#1) Find the value of the test statistic (round to two decimal places). Find the p-Value (round to three decimal places)
#2) Use the estimated regression equation to predict the selling price (in $1,000s) of a 2,100 square foot house in Winston-Salem, North Carolina. (Round your answer to one decimal place.) = $______ Thousand
#3)Do you believe the estimated regression equation developed in part (b) will provide a good prediction of selling price of a particular house in Winston-Salem, North Carolina? Explain. (Round your answer to three decimal places.) Since r2 =______ is (at least OR less than .55) , the estimated regression equation will (provide OR not provide) a good prediction of selling price of a particular house in Winston-Salem.
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