The following data on r = the line speed (feet per minute) and y = the number of defective parts found for a production process at Brawdy Plastics provided the estimated regression equation ŷ = 27.5 – 0.3x. Excel File: data14-37.xlsx Number of Defective Line Speed Parts Found 20 23 20 21 30 19 30 16 40 15 40 17 50 14 50 11 For these data SSE = 16 Develop a 95% confidence interval for the mean number of defective parts for a line speed of 25 feet per minute (to 4 decimals). Use Table 1 of Appendix B. 29.895 to 29.895
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4The data on y = annual sales ($1,000s) for new customer accounts and x = number of years of experience for a sample of 10 salespersons provided the estimated regression equation ŷ = 80 + 4x. For these data, x = 7, Σ(xi − x)2 = 142, and s = 4.6098. (a)Develop a 95% confidence interval for the mean annual sales (in thousands of dollars) for all salespersons with seven years of experience. (Round your answers to two decimal places.) $______ thousand to $_____thousand (b)The company is considering hiring Tom Smart, a salesperson with seven years of experience. Develop a 95% prediction interval of annual sales (in thousands of dollars) for Tom Smart. (Round your answers to two decimal places.) $_______ thousand to $_______ thousandThe data on y = annual sales ($1,000s) for new customer accounts and x = number of years of experience for a sample of 10 salespersons provided the estimated regression equation ŷ = 80 + 4x. For these data, x = 7, Σ(xi − x)2 = 142, and s = 4.6098. (a) Develop a 95% confidence interval for the mean annual sales (in thousands of dollars) for all salespersons with twelve years of experience. (Round your answers to two decimal places.) $ thousand to $ thousand (b) The company is considering hiring Tom Smart, a salesperson with twelve years of experience. Develop a 95% prediction interval of annual sales (in thousands of dollars) for Tom Smart. (Round your answers to two decimal places.) $ thousand to $ thousand
- The accompanying data resulted from an experiment in which weld diameter and shear strength (in pounds) were determined for five different spot welds on steel. Below are the data collected and the regression equation. Diameter Strength 200.1 813.7 210.1 785.3 220.1 960.4 230.1 1118.0 240.0 1076.2 Strength = -941.6992 + 8.5988*Diameter The predicted y-hat value for a diameter of 201 is 864. if we observed a weld that had a diameter of 235 that had a strength 1000, what would be its residual?The accompanying table lists systolic blood pressures (mm Hg) and diastolic blood pressures (mm Hg) of adult females. Find the prediction interval for a systolic blood pressure of 121mm Hg using a 99% confidence level. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. Systolic Diastolic 125 69 104 65 129 75 108 65 157 74 95 53 155 89 110 69 120 69 115 73 101 59 127 67 The 99% prediction interval for a systolic blood pressure of 121mm Hg is ____mm Hg<y<___mm Hg.A sociologist was hired by a large city hospital to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (miles) between home and work for the employee. A sample of 10 employees was chosen, and the following data were collected. A. Is the estimated regression equation appropriate and adequate
- The attached results are for a multiple regression study of smartphone addiction (SSA-SV) proneness in relation to 1) Gender 2)Age 3) Anxiety (GAD-7). I just want to clarify what the F-statistic means and the effects of AGE on the F-statistic; given that AGE is statistically significant compared to the other predictor variables.The accompanying table lists systolic blood pressures (mm Hg) and diastolic blood pressures (mm Hg) of adult females. Find the (a) explained variation, (b) unexplained variation, and (c) prediction interval for a systolic blood pressure of 118 mm Hg using a 99% confidence level. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. Systolic Diastolic 127 69 103 65 130 73 104 64 157 74 97 51 155 90 111 69 124 68 112 75 103 60 128 67The following data are the monthly salaries and the grade point averages for students who obtained a bachelor's degree in business administration. GPA Monthly Salary ($) 2.6 3,600 3.4 3,900 3.6 4,300 3.2 3,800 3.5 4,200 2.9 3,900 The estimated regression equation for these data is and . Use Table 1 of Appendix B. a. Develop a point estimate of the starting salary for a student with a GPA of (to 1 decimal). b. Develop a confidence interval for the mean starting salary for all students with a GPA (to 2 decimals). ( , ) c. Develop a prediction interval for Ryan Dailey, a student with a GPA of (to 2 decimals). ( , ) d. Discuss the differences in your answers to parts (b) and (c).
- Mr. James, president of Daniel-James Financial Services, believes that there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, he gathered the following information from a sample of clients for the last month. Let X represent the number of times that the client was contacted and Y represent the valye of sales ($1000) for each client sampled. Number of Contacts (X) Sales ($1000) 14 24 12 14 20 28 16 30 23 30 a) Compute the regression equation for client contacts and sales. Interpret the slope and intercept parameters.The following output comes from regression using the actual HW9 scores and the Final test scores from intro stats one semester. Sample size: 50R (correlation coefficient) = 0.3658R-sq = 0.1338Estimate of error standard deviation: 10.36256Parameter estimates: Parameter Estimate Std. Err. DF T-Stat P-Value Intercept 43.558118 11.1716 48 3.899 0.0003 Slope 0.360048 0.132225 48 2.723 0.009 Assume no assumptions are violated. Form a 87% Confidence interval for how much your final is supposed to increase for each problem done on homework 9.Use 5 decimal placesSuppose the following data were collected from a sample of 15 houses relating selling price to square footage and the architectural style of the house. Use statistical software to find the following regression equation: PRICEi=b0+b1SQFTi+b2COLONIALi+b3RANCHi+ei . Is there enough evidence to support the claim that on average, houses that are ranch style have lower selling prices than houses that are Victorian style at the 0.05 level of significance? If yes, write the regression equation in the spaces provided with answers rounded to two decimal places. Else, select "There is not enough evidence."Selling Price Square Footage Colonial (1 if house is Colonial style, 0 otherwise) Ranch (1 if house is Ranch style, 0 otherwise) Victorian (1 if house is Victorian style, 0 otherwise) 377640 1941 1 0 0 460996 3397 0 1 0 405781 2764 0 0 1 407216 2906 0 0 1 435139 3401 1 0 0 405275 2600 0 0 1 381141 2203 0 1 0 370490 2046 1 0 0 404070 2210 0 0 1 460196 3692 0 1 0 382780 2172 1 0 0 406466 2606 0 1…