8 Consider the following data.9123055y10.220.030.737.975.1117.8(a) Find a linear model. (Round all values to two decimal places.)y =Plot the data along with the linear modelyy1201201001008080606040402020102030405060102030405060yy120120-1001008080606040402020102030405060102030405060(b) Find a power model. (Round all values to two decimal places.)y =

Name: 8 Consider the following data.9123055y10.220.030.737.975.1117.8(a) Fin
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Description: 8 Consider the following data.9123055y10.220.030.737.975.1117.8(a) Find a linear model. (Round all values to two decimal places.)y =Plot the data along with the linear modelyy1201201001008080606040402020102030405060102030405060yy120120-10010080806060

Given information: Given data represents the values of the variables x and y.

Answered: Consider the following data. x 2|5 | 9…

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Consider the following data. x 2|5 | 9 | 12 y 10.2 20.0 | 30.7 | 37.9 75.1 117.8 30 55 (a) Find a linear model. (Round all values to two decimal places.) y =

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

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...

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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?
Consider the following regression equation representing the linear relationship between the Canada Child Benefit provided for a married couple with 3 children under the age of 6, based on their annual family net income: ŷ =121.09−0.57246xR2=0.894 where y = annual Canada Child Benefit paid (in $100s) x = net annual family income (in $1000s) Source: Canada Revenue Agency a. As the net annual family income increases, does the Canada Child Benefit paid increase or decrease? Based on this, is the correlation between the two variables positive or negative?The Canada Child Benefit paid .The correlation between the two variables is .b. Calculate the correlation coefficient and determine if the relationship between the two variables is strong, moderate or weak.r= , the relationship is . Round to 3 decimal places c. Interpret the value of the slope as it relates to this relationship. For every $1 increase in annual family net income, there is a $0.57246 decrease in…
Consider the following regression equation representing the linear relationship between the Canada Child Benefit provided for a married couple with 3 children under the age of 6, based on their annual family net income: ŷ =121.09−0.57246xR2=0.894 where y= annual Canada Child Benefit paid (in $100s) x = net annual family income (in $1000s) Source: Canada Revenue Agency a. As the net annual family income increases, does the Canada Child Benefit paid increase or decrease? Based on this, is the correlation between the two variables positive or negative?The Canada Child Benefit paid ? .The correlation between the two variables is ? .b. Calculate the correlation coefficient and determine if the relationship between the two variables is strong, moderate or weak.r= , the relationship is ? . Round to 3 decimal places c. Interpret the value of the slope as it relates to this relationship. For every $1 increase in annual family net income, there is a $0.57246 decrease in…
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 following table shows the annual expenditures, in dollars, per customer unit for residential landline phone services and cellular phone services in the United States in the given year.† Year Landline Cell 2004 592 378 2006 542 524 2008 467 643 2010 401 760 Calculate the regression line for each type of service. (Let t be the time in years since 2004, L be the operating revenue of landline phone services and C be the expenditure of cellular services. Round your regression parameters to two decimal places.) L(t) = C(t) = Determine the expenditure level at which the two lines cross. Round your answer for the expenditure level to one decimal place. million dollars
The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female).ŷ = 30 + 0.7x1 + 3x2Also provided are SST = 1200 and SSE = 384.The yearly income of a 24-year-old female individual is _____.
Which of the following does not need to be computed to determine a simple regression line? SSx SP "Y-hat" SSy
A particular professor has noticed that the number of people, y, who complain about his attitude is dependent on the number of cups of coffee, x, he drinks. From eight days of tracking he compiled the following data: People (y) 10 10 9 11 7 6 5 5 Cups of coffee (x) 1 1 2 2 3 4 5 5 Unless otherwise stated, you can round values to two decimal places.a) Using regression to find a linear equation for ˆyy^ . Round to three decimal places.ˆyy^ = b) Find the correlation coefficient. Round to three or four decimals.rr = c) Does the correlation coefficient indicate a strong linear trend, a weak linear trend, or no linear trend? strong linear trend weak linear trend no linear trend d) Use your model to predict the number of people that will complain about his attitude if he drinks 10 cups of coffee.
Shown below is a portion of a computer output for a linear regression analysis relating an individual's income (y in thousands of dollars) to age (x1 in years), level of education (x2 ranging from 1 to 5), and the individual's gender (x3 where 0 = female and 1 = male). Coefficient Standard Error t-statistic p-value Intercept 15.934 1.389 11.47 0.000 x1 0.625 0.094 6.65 0.000 x2 0.921 0.190 4.85 0.000 x3 –0.510 0.920 –0.55 0.590 Source of Variation Sum of squares Degrees of freedom Mean square F-statistic p-value Regression 84 3 28 4 0.027 Error 112 16 7 Total 196 19 a. Is there a significant relationship between an individual's income and the set of variables, age, level of education, and gender (based on a significance level α =05 )? Explain why using one of the p-values in the output tables. b.Which of the three predictor variables are…
The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 7171 6262 7878 9494 8383 8181 8080 9494 8585 6262 Grades on Final 8888 7979 8888 9191 8080 7070 7171 9393 6565 7777
The mean height of Americanwomen in their twenties is about 64.3 inches, and the standard deviation is about 3.9 inches. The mean height of menthe same age is about 69.9 inches, with standard deviationabout 3.1 inches. Suppose that the correlation between theheights of husbands and wives is about r 0.5.(a) What are the slope and intercept of the regressionline of the husband’s height on the wife’s height in youngcouples?(b) Draw a graph of this regression line for heights of wivesbetween 56 and 72 inches. Predict the height of the husbandof a woman who is 67 inches tall, and plot the wife’s heightand predicted husband’s height on your graph.(c) You don’t expect this prediction for a single couple to bevery accurate. Why not?