Answers in the internet mostly say that a = 3.0490, b = 0.2796, and c = 0.1673, but my quiz said I'm incorrect.
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Answers in the internet mostly say that a = 3.0490, b = 0.2796, and c = 0.1673, but my quiz said I'm incorrect.
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?Given a generic data set (x,y) with a linear regression. How do you determine if the y(dependent) will be less than a certain value?Given a generic data set (x,y) with a linear regression. How do you determine if the y(dependent) will be less/greater than a certain value at a decided value of x?
- The estimated regression equation for a model involving two independent variables and 10 observations follows.A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x1 – 2.5 x2, to predict y = the market price of a home (in $1,000s), using two independent variables, x1 = the total number of square feet of living space, and x2 = the age of the house in years. With this regression model, the predicted price of a 10-year old home with 2,500 square feet of living area is __________. $205.00 $200,000.00 $205,000.00 $255,000.00Create the regression equations based on the research model below!
- Plot the linear regression line y = 3 + 0.5x without using excel with proper labellingCalculate the estimated R2 and state why we should consider using adjusted R2 instead of R2 in the setting of multiple linear regression?Would I use the regression line to predict Y from X ? And what is the pattern of the scatterplot?
- The predictions made using multiple regression are often more ______ than the predictions made using linear regression with one predictor variable.In a simple linear regression, show that the OLS regression line always passes through the mean (average) of both x and y.Discuss the relationship of the negative sign or positive sign in the value ofcorrelation coefficient or “r” to the direction of the linear regressionequation or “y hut.”
