The figure shown to the right contains a scatter plot of 10 data points for trees, where the diameter of a tree at breast height (Dbh) is given in inches and the height is given in feet. The regression model is shown below, where x is the Dbh in inches and y is the height in feet. Q 40- y= 1.16x +0.82 Dbh (in) ATICI iNCiease in Don prouuces a 1.10 100l inciease in neigrit. (C) Estimate the height of a tree with a Dbh of 15 inches. yz 18 feet (Round to the nearest foot as needed.) (D) Estimate the Dbh of a tree that is 25 feet tall. x inches (Round to the nearest inch as needed.) 25 to Height (f)

The figure shown to the right contains a scatter plot of 10 data points for trees, where the diameter of a tree at breast height (Dbh) is given in inches and the height is given in feet. The regression model is shown below, where x is the Dbh in inches and y is the height in feet. Q 40- y= 1.16x +0.82 Dbh (in) ATICI iNCiease in Don prouuces a 1.10 100l inciease in neigrit. (C) Estimate the height of a tree with a Dbh of 15 inches. yz 18 feet (Round to the nearest foot as needed.) (D) Estimate the Dbh of a tree that is 25 feet tall. x inches (Round to the nearest inch as needed.) 25 to Height (f)

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 40RE: For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina...

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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.
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 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.
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.
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.
The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. a. Fit the regression line y = a+bx to the data and interpret the results. b. Use the regression equation to determine the SY16C grade for a college student who scored60 on their achievement test. What would their SY16C grade be?
In the space below (or on a separate sheet of paper), plot all observations of the table above and draw the OLS regression line. You can estimate the slope and constant of the OLS regression line by hand,
A surgery intern has conducted a study of the sleeping habits of her colleagues and has developed a following regression equation: y-hat = 6 + 0.1X, where X is the number of hours working on one shift, and Y is the number of hours sleeping at night after that shift. Yvette worked 10 hours and slept 8 hours. What is Yvette’s residual? 0.1 1 6 7
The following table represents the survey result from the seven online stores. Use linear regression to find the linear equation that is best fit for the data, width x equal to the online advertising. Round your coefficient to three decimal places. Online Store Online Advertising (in thousand dollars) Monthly e-commerce Sales (in thousand dollars) 1 1.5 368 2 1.7 340 3 2.8 665 4 5 954 5 1.3 331 6 2.2 556 7 1.3 376
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.9 8.1 6.8 3.9 2.6 2.7 2.1 0.6 yy 14.4 10.7 10.1 7.6 6.2 6.5 5.7 4.4 xx = thousands of automatic weaponsyy = murders per 100,000 residentsDetermine the regression equation in y = a + bx form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 6.2 thousand automatic weapons? Answer = Round to 4 decimal places. B) How many murders per 100,000 residents can be expected in a state with 8.7 thousand automatic weapons? Answer = Round to 4 decimal places.
A set of n=10 pairs of X and Y scores has SSx=10, SSy=60, and SP=20. What is the slope of the regression equation for these scores?
A set of n=20 pairs of x and y scores had SSx=10,SSy=40,and SP=30.What is the slope for the regression equation for predicting y from x?