Given are the set of Y (price) and X (demand) of a certain commodity. X- {9,7,8,9,3,2} and Y- {6,5,7,6,9,8} respectively. a. The equation of the regression line is y=3.6712+4.2318x y=3.6712-4.2318x y=9.1972-0.3732x none of these b. What will be the price of a commodity if the demand is 12? 3.9724 4.1788 5.7689 none of these

Given are the set of Y (price) and X (demand) of a certain commodity. X- {9,7,8,9,3,2} and Y- {6,5,7,6,9,8} respectively. a. The equation of the regression line is y=3.6712+4.2318x y=3.6712-4.2318x y=9.1972-0.3732x none of these b. What will be the price of a commodity if the demand is 12? 3.9724 4.1788 5.7689 none of these

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.4: Linear Regression

Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
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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?
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Given are the set of Y (price) and X (demand) of a certain commodity. X- {9,7,8,9,3,2} and Y- {6,5,7,6,9,8} respectively.a. The equation of the regression line isy=3.6712+4.2318xy=3.6712-4.2318xy=9.1972-0.3732xy=9.1972+0.3732xb. What will be the price of a commodity if the demand is 12?3.97244.17885.76898.1234c. What will be the demand of a commodity if the price is 6?5.43567.23158.56709.1254d. The coefficient of correlation is equal to0.850.78-0.85-0.78
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