The following table lists the monthly incomes (in hundreds of dollars) and the monthly rents paid (in hundreds of dollars) by a sample of six families. Let x be monthly income and y be monthly rent. Monthly Income Monthly Rent 24 7.0 16 4.5 19 6.5 31 9.5 12 4.5 27 8.5 Using the regression of monthly rent paid on monthly income. the predicted value of monthly rent paid by a family with a monthly income of $2700. rounded to the nearest dollar, is:

The following table lists the monthly incomes (in hundreds of dollars) and the monthly rents paid (in hundreds of dollars) by a sample of six families. Let x be monthly income and y be monthly rent. Monthly Income Monthly Rent 24 7.0 16 4.5 19 6.5 31 9.5 12 4.5 27 8.5 Using the regression of monthly rent paid on monthly income. the predicted value of monthly rent paid by a family with a monthly income of $2700. rounded to the nearest dollar, is:

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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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?
The following data shows the percent of females 18 years old or older who were overweight in the number of years indicated, judging on the basis of BMI. Year, Percent Obese 3 , 23.3 4, 23.7 5, 24.3 6, 25.6 7, 25.2 8, 27.6 9, 26.8 Using regression equation, predict the percent of overweight females in year 15.
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $841. The equation of the regression line is ModifyingAbove .y=1.403x+9.259. Wages (state), x 724 747 800 803 839 897 901 939 951 956 Wages (federal), y 1,035 1,060 1,111 1,144 1,190 1,245 1,276 1,306 1,332 1,396 Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $841. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) A. There is a 95% chance that the predicted average weekly wages of federal government…
The following table gives information on the amount of sugar (in grams) and the calorie count in one serving of a sample of varieties of Kellogg's cereal. Find the predictive regression equation of the number of calories on the amount of sugar. Sugar (grams) 6 15 12 11 8 6 7 4 9 14 20 13 3 Calories 120 200 150 110 120 80 190 120 120 190 190 120 120
Below is a sample of men’s shoe size and height. At 5% level of significance, is there a relationship between men’s shoe size and their height? Shoe size (x) Men's Heights (in inches), y 10 70 10.5 71 9.5 70 11 72 12 74 8.5 66 9 68.5 13 76 10.5 71.5 10.5 70.5 10 72 9.5 70 10 71 10.5 69.5 11 71.5 12 73.5 Leave your answer in 3 decimal places The regression equation: y = + ()x
A specialist in hospital administration stated that no. of employees in a hospital can be estimated by counting the no. of beds in the hospital .A health care researcher decided to develop a regression model in an attempt to predict the number of employees of a hospital by the no. of beds . 12 hospitals were surveyed and obtained following data. No of Beds. Employees 23 69 29 95 29 102 35 118 42 126 46 125 50 138 54 178 64 156 66 184 76 176 78 225 After obtaining the regression model and interpret it accordingly based on your understanding. Explain the…
The following table displays the mathematics test scores for a random sample ofcollege 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 whoscored 60 on their achievement test. What would their SY16C gradebe? Mathematics test(x) SY16C grades(y)1 39 652 43 783 21 524 64 825 57 926 47 897 28 738 75…
Using the regression line attached. Based on only the above plot, one can conclude: a) height causes an increase in weight b) weight causes an increase in height c) taller people are more likely to weigh more than shorter people, at least in the sample on which this data is based d) a statistically significant predictive relationship between height and weight e) c and d
The following data shows the dexterity test scores of five assembly-line employees of Dimples Company Limited and their respective hourly productivity.Employee Score on dexterity test (?) Ali 12Kofi 14Kwesi 17Abudu 16Nana 11Units produced in an hour (?) 55636770 51You are required to(i) Write the regression equation(ii) Interpret the regression equation(iii) Calculate the Pearson’s Product Moment Correlation Coefficient.(iv) Interpret the correlation coefficient (v) Suppose the dexterity test score is 13, what would be the units produced in an hour? (vi) Clearly explain (in detail) the difference between regression analysis and correlation analysis.
The following data on x=soil depth and y=percentage of montmorillonite in the soil were analyzed from samples taken in Belize X 40 50 60 70 80 90 100 Y 58 34 32 30 28 27 22 Draw the scatterplot Compute and draw the least square regression line. Compute the residual and construct a residual plot. Are there any unusual features of this plot?
The following table lists the monthly incomes (in hundreds of dollars) and the monthly rents paid (in hundreds of dollars) by a sample of six families. Monthly Income Monthly Rent 24 7.0 16 4.5 19 6.5 31 11.6 10 4.5 27 8.5 4. The null hypothesis is that the slope of the population regression line of monthly rent on monthly income is zero and the alternative hypothesis is that the slope of this population regression line is greater than zero. The significance level is 1%. By hand, test whether the slope of the monthly income is greater than zero using the CV approach, including identifying the reject/non reject regions, etc
The following data is a regression model where the U.S. Department of Transportation has tried to relate the rate of fatal traffic accidents (per 1000 licenses) to the percentage of motorists under the age of 21. Data has been collected for 42 major cities in the United States. SUMMARY OUTPUT Regression Statistics Multiple R 0.83938748 R Square 0.70457134 Adjusted R Square 0.69718562 Standard Error 0.58935028 Observations 42 ANOVA df SS MS F Regression 1 33.13441764 33.1344 95.3964 Residual 40 13.89335048 0.34733 Total 41 47.02776812 Coefficients Standard Error t Stat P-value Intercept -1.5974138 0.371671454 -4.2979 0.00010 Percent Under 21 0.28705317 0.029389769 9.76711 3.79E-9…