Illustration 37. Calculate the (i) two regression co-efficients, (ii). Co-efficient of correlation, and(iii). the two regression equations from the following information:N= 10, ΣΧ= 350, ΣΥ= 310, Σ(Χ- 35)? 162,E(Y- 31)? = 222, E(X – 35) (Y – 31) = 92

Answered: Image /qna-images/answer/29519da5-4f7c-4fca-ba61-01672c709b67.jpg

Answered: Illustration 37. Calculate the (i) two…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 41RE: For the following exercises, consider the data in Table 5, which shows the percent of unemployed in...

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For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.
For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
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?
For the following exercises, consider this scenario: The population of a city increased steadily overa ten-year span. The following ordered pairs show the population and the year over the ten-year span (population, year) for specific recorded years: (3,600,2000);(4,000,2001);(4,700,2003);(6,000,2006) 44. What is the correlation coefficient for this model tothree decimal places of accuracy?
For the following exercises, draw a scatter plot for the data provided. Does the data appear to be linearly related?
For the following exercises, refer to Table 12. Use a graphing calculator to create a scatter diagram of the data.
For the following exercises, consider this scenario: The profit of a company decreased steadily overa ten-year spam.The following ordered pairs shows dollars and the number of units sold in hundreds and the profit in thousands ofover the ten-year span, (number of units sold, profit) for specific recorded years: (46,600),(48,550),(50,505),(52,540),(54,495). Use linear regression to determine a function Pwhere the profit in thousands of dollars depends onthe number of units sold in hundreds.

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Illustration 37. Calculate the (i) two regression co-efficients, (ii). Co-efficient of correlation, and (iii). the two regression equations from the following information: N=10, ΣΧ= 350, ΣΥ= 310, Σ(Χ- 35)? 162, E(Y-31)? = 222, E(X– 35) (Y – 31) = 92