A student was performed on a type of bearing to find the relationship of amount of wear y to x₁ = 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 t-distribution.(a) Estimate 2 using multiple regression of y on x and x2.(Round to one decimal place as needed.)Bearing Datayx1X21941.7844173 22.2 105211432.9136223015.780995 42.9120512840.31106- X

The formula of S2 is,where,MSE denotes the Mean sum of squares of errorSSE denotes the sum of…

Answered: A student was performed on a type of…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter7: Analytic Trigonometry

Section7.6: The Inverse Trigonometric Functions

Problem 94E

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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)
A researcher tested two new exercise routines, PowerHour, and MightyFifty on reducing heart rate. For Power Hour, each participant performs a routine consisting of 50 each of jumping jacks, push-ups, and sit ups in two 30-minute sessions every week for 6 weeks. With the MightyFIfty, the participants perform the same routine but only for a total of 50 minutes each week. At the end of the six week period, he measured the heart rate of the participants. At the beginning, the mean of participants' heart rate was 71.5.A the end of the study, the mean heart rate of 6 participants in the PowerHour program was 69.5 with variance of 2.1, while that of 5 participants in th Mighty-Fifty program was 68.9 with standard deviation of 1.5. The researcher concluded that the MightyFifty Program is significantly better in lowering the heart rate than the PowerHour Program. Is his claim true? Answer by first completing the calculation of each of the following and then explaining the t-value obtained! Copy…

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