A student was performed on a type of bearing to find the relationship of amount of wear y to x, oil viscosity and x2 = load. The accompanying data were obtained. Complete parts (a) and (b) below. Click here to view the bearing data. Click here to view page 1 of the table of critical values of the t-distribution. Click here to view page 2 of the table of critical values of the I-distribution. (a) Estimate o2 using multiple regression of y on x, and x2. (Round to one decimal place as needed.) Bearing Data y X1 X2 194 1.7 844 173 22.2 1052 114 32.9 1362 230 15.7 809 95 42.9 1205 128 40.3 1106 - X
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- Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.Use the table of values you made in part 4 of the example to find the limiting value of the average rate of change in velocity.Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below. ANOVA table Source SS df MS F Regression 1,865.5782 1 1,865.5782 39.56 Residual 1,320.4934 28 47.1605 Total 3,186.0716 29 Regression output Variables Coefficients Std. Error t(df=28) Intercept 13.7523 3.0957 3.672 Distance–X 6.3449 1.0088 6.29 a-1. Write out the regression equation. (Round your answers to 3 decimal places.) a-2. Is there a direct or indirect relationship between the distance from the fire station and the amount of fire damage? How much damage would…
- Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below. ANOVA table Source SS df MS F Regression 1,850.5782 1 1,850.5782 39.69 Residual 1,305.4934 28 46.6248 Total 3,156.0716 29 Regression output Variables Coefficients Std. Error t(df=28) Intercept 12.6882 3.1699 2.82 Distance–X 5.121 8.504 6.3 c-1. Determine the coefficient of determination. (Round your answer to 3 decimal places.) c-2. Fill in the blank below. (Round your answer to one decimal place.) d-1. Determine the correlation coefficient. (Round…Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below. ANOVA table Source SS df MS F Regression 1,815.5782 1 1,815.5782 40.82 Residual 1,245.4934 28 44.4819 Total 3,061.0716 29 Regression output Variables Coefficients Std. Error t(df=28) Intercept 13.3334 3.0617 3.556 Distance–X 4.7711 0.7468 6.39 Click here for the Excel Data File a-1. Write out the regression equation. (Round your answers to 3 decimal places.) a-2. Is there a direct or indirect relationship between the distance from the fire station and…Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below. ANOVA table Source SS df MS F Regression 1,850.5782 1 1,850.5782 39.69 Residual 1,305.4934 28 46.6248 Total 3,156.0716 29 Regression output Variables Coefficients Std. Error t(df=28) Intercept 12.6882 3.1699 2.82 Distance–X 5.121 8.504 6.3 Click here for the Excel Data File a-1. Write out the regression equation. (Round your answers to 3 decimal places.) a-2. Is there a direct or indirect relationship between the distance from the fire station and…
- Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below. ANOVA table Source SS df MS F Regression 1,850.5782 1 1,850.5782 39.69 Residual 1,305.4934 28 46.6248 Total 3,156.0716 29 Regression output Variables Coefficients Std. Error t(df=28) Intercept 12.6882 3.1699 2.82 Distance–X 5.121 8.504 6.3 Click here for the Excel Data File d-1. Determine the correlation coefficient. (Round your answer to 3 decimal places.) d-2. Choose the right option. d-3. How did you determine the sign of the correlation…Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below. ANOVA table Source SS df MS F Regression 1,850.5782 1 1,850.5782 39.69 Residual 1,305.4934 28 46.6248 Total 3,156.0716 29 Regression output Variables Coefficients Std. Error t(df=28) Intercept 12.6882 3.1699 2.82 Distance–X 5.121 8.504 6.3 e-1. State the decision rule for 0.01 significance level: H0 : ρ = 0; H1 : ρ ≠ 0. (Negative value should be indicated by a minus sign. Round your answers to 3 decimal places.) e-2. Compute the value of the test…I want to examine the relationship between gas mileage of cars and the engine size (displacement in cubic inches). Which explanatory variable is Engine size Gas mileage Relationship between the two Both engine size and gas mileage Neither engine size nor gas mileage
- Z= P value =Water is poured into a large, cone-shaped cistern. The volume of water, measured in cm, is reported at Which of the following would linearize the data for volume and time? different time intervals, measured in seconds. The scatterplot of volume versus time showed a curved Seconds, cm3 O In(Seconds), cm3 Seconds, In(cm') pattern. O In(Seconds), In(cm³)Residuals are the: 1.horizontal deviations from the line of best fit to each data point 2.perpendicular distances from the line of best fit to each data point 3.vertical deviations from the line of best fit to each data point 4.areas of the squares between the line of best fit and each data point