EBK BUSINESS STATISTICS
8th Edition
ISBN: 9780135179833
Author: STEPHAN
Publisher: VST
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardWhat does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forward
- 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?arrow_forwardwhen a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?arrow_forwardExplain in your own words how simple regression can be helpful in identifying relationships between variables.arrow_forward
- Why the regression line is a straight line rather than a curved line?arrow_forwardIn linear regression, how can you minimise the error between predicted and actual observed values?arrow_forwardSuppose you a manager for a local car dealership, and you want to use a linear regression model to predict the price of a used car. You decide to use four predictor variables - "Age' (how long the car has been in use since it was produced), "Dents" (the number of visible dents on the outside of the car), "Accidents" (the number of accidents the car has been in), and "mpg" (the fuel efficiency of the car, measured in miles per gallon). Your dataset contains this information for the past 120 cars sold at your dealership. Using this model, your analysis finds an R² of 37%. What is the F statistic of your analysis? Note: 1- Only round your final answer. Round your final answer to two decimal places.arrow_forward
- Professional basketball has truly become a sport that generates interest among fans around the world. More and more players come from outside the United States to play in the National Basketball Association (NBA). You want to develop a regression model to predict the number of wins achieved by each NBA team, based on field goal (shots made) percentage and three-point field goal percentage. The data are stored in NBA.xlsx . TEAM Wins Field Goal % Three-Point Field Goal % Points Per Game Rebound Freedraw Turnover Houston Rockets 65 46 36.2 112.4 43.5 19.6 13.8 Toronto Raptors 59 47.2 35.8 111.7 44 17.3 13.4 Golden State Warriors 58 50.3 39.1 113.5 43.5 16.6 15.4 Boston Celtics 55 45 37.7 104 44.5 16 14 Philadelphia 76ers 52 47.2 36.9 109.8 47.4 17.1 16.5 Cleveland Cavaliers 50 47.6 37.2 110.9 42.1 18.1 13.7 Portland Trail Blazers 49 45.2 36.6 105.6 45.5 16.7 13.5 Indiana Pacers 48 47.2 36.9 105.6 42.3 14.9 13.3 New Orleans Pelicans 48 48.3 36.2 111.7 44.3 16.1 14.9…arrow_forwardProfessional basketball has truly become a sport that generates interest among fans around the world. More and more players come from outside the United States to play in the National Basketball Association (NBA). You want to develop a regression model to predict the number of wins achieved by each NBA team, based on field goal (shots made) percentage and three-point field goal percentage. The data are stored in NBA.xlsx . TEAM Wins Field Goal % Three-Point Field Goal % Points Per Game Rebound Freedraw Turnover Houston Rockets 65 46 36.2 112.4 43.5 19.6 13.8 Toronto Raptors 59 47.2 35.8 111.7 44 17.3 13.4 Golden State Warriors 58 50.3 39.1 113.5 43.5 16.6 15.4 Boston Celtics 55 45 37.7 104 44.5 16 14 Philadelphia 76ers 52 47.2 36.9 109.8 47.4 17.1 16.5 Cleveland Cavaliers 50 47.6 37.2 110.9 42.1 18.1 13.7 Portland Trail Blazers 49 45.2 36.6 105.6 45.5 16.7 13.5 Indiana Pacers 48 47.2 36.9 105.6 42.3 14.9 13.3 New Orleans Pelicans 48 48.3 36.2 111.7 44.3 16.1 14.9…arrow_forwardIdentify six problems that can arise in data collection for a regression analysis.arrow_forward
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