Find the linear regression equation for an approximate linear model for Gary's recent mountain bike rides.Use the data below. Let d be the ride distance in miles and t be the ride time in hours.20time (hours)distance (miles)181.18.9161.1410.21141.1811.11121.2111.55101.3911.961.4312.11.512.980.250,50.751.251.51.75a. State the linear equation: y = 1.47 + 7.66x x syntax error. Check your variables - you might beusing an incorrect one.Round to the nearest hundredth.b. Interpret the slope:For each additional 1 hourGary rides, he will travel about 7.66 milesmilesfurther on average.c. Use your linear equation to estimate the distance of a 1.5-hour ride, to the nearest tenth of a mile.13.0miles

From the given information, d represents ride distance and t represent ride time in hours.

Answered: Find the linear regression equation for…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 38RE: 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 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.
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 over a 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) 42. Use linear regression to determine a function y,where the year depends on the population, to threedecimal places of accuracy.
According to the summary result of linear regression model between A and B obtained from R given below, we can fit a regression line. Assume thatA has any value. If we decrease the value of A by 3, how would Y be affected?a) 58.8945 decreaseb) 58.8945 increasec) 29.8827 increased) 49.5142 decreasee) 29.8827 decrease
When a linear regression for the growth of the number of employees in the health care and social assistance fields in Quebec from 2010 to 2014 is performed, the following values are determined: r=0.9948 r2=0.9897 These values indicate that a linear model is a good fit for the data. True False

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