The table below lists measured amounts of redshift and the distances (billions of light-years) to randomlyselected astronomical objects. Find the (a) explained variation, (b) unexplained variation, and (c) indicatedprediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable touse the regression equation when making predictions. For the prediction interval, use a 90% confidence levelwith a redshift of 0.0126.RedshiftDistance0.02380.31a. Find the explained variation.0.05430.74(Round to six decimal places as needed.)b. Find the unexplained variation.(Round to six decimal places as needed.)c. Find the indicated prediction interval.0.07221.02billion light-years

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Answered: The table below lists measured amounts…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude 4 10 14 19 29 31 33 D Temperature 55 31 27 - 1 - 27 - 41 - 54 a. Find the explained variation. (Round to two decimal places as needed.) b. Find the unexplained variation. (Round to five decimal places as needed.) c. Find the indicated prediction interval. °F
The following estimated regression equation based on 10 observations was presented. ŷ = 27.1270 +0.5104x₁ + 0.4980x₂ 1 Here, SST = 6,736.125, SSR = 6,222.375, 5b₁ = 0.0813, and = 0.0567. 562
The following estimated regression equation based on 10 observations was presented. ŷ = 27.1270 +0.5104x₁ + 0.4980x₂ 1 Here, SST = 6,736.125, SSR = 6,222.375, 5b₁ = 0.0813, and = 0.0567. 562
A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies, X3 = 2004 federal expenditures per capita (a leading predictor), and X4 = 2005 high school graduation percentage. (a) Fill in the values in the table given here for a two-tailed test at α = 0.01 with 33 d.f. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p-values to 4 decimal places.) Predictor Coefficient SE tcalc p-value Intercept 4,579.5465 791.5050 AgeMed -27.292 12.1893 Bankrupt 19.5612 12.0754 FedSpend -0.0132 0.0116 HSGrad% -27.5839 7.1731 (b-1) What is the critical value of Student's t in Appendix D for a two-tailed test at α = .01 with 33 d.f? (Round your answer to 3 decimal places.) t-value = (b-2) Choose the correct option.…
A professor obtains SAT scores and freshman grade point averages (GPA) for a group of n=15 college students. The SAT scores have a mean of M=580 with SS=22,400, and GPA has a mean of 3.10 with SS=1.26, and SP=84.c. Does the regression equation account for a significant portion of the variance in GPA? Use ?=.05α=.05 to evaluate the F-ratio.
The table below lists measured amounts of redshift and the distances (billions of light-years) to randomly selected astronomical objects. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 90% confidence level with a redshift of 0.0126. Redshift Distance a. Find the explained variation. 0.0237 0.34 (Round to six decimal places as needed.) 0.0541 0.75 0.0723 0.98 C 0.0397 0.57 0.0444 0.62 0.0103 0.13
The data shown below are the initial weights and gains in weight (in grams) of female rats on a high protein diet from 24 to 84 days of age. The point of interest in these data is whether the gain in weight is related to (dependent on) the initial weight. If so, then feeding experiments on female rats can be made more precise by adjusting for differences in initial weights of the rats. Statistically test this with a regression analysis. Rat Number Initial Weight (gms) Weight Gain (gms) 1 50 128 2 64 159 3 76 158 4 64 119 5 74 133 6 60 112 7 69 96 8 68 126 9 56 132 10 48 118 11 57 107 12 59 106 13 46 82 14 45 103 15 65 104 I used excel's regression took pak and got the following: SUMMARY OUTPUT Regression Statistics Multiple R 0.489416452 R Square 0.239528464 Adjusted R Square 0.181030653 Standard Error 8.869929833 Observations 15…
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 120 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. Click the icon to view the blood pressure data. Blood Pressures a. The explained variation is 650 (Round to two decimal places as needed.) b. The unexplained variation is (Round to two decimal places as needed.) Systolic Diastolic 126 69 102 67 128 75 107 63 c. The 99% prediction interval for a systolic bloo (Round to one decimal place as needed.) 156 74 95 52 154 89 110 71 120 69 116 75 103 60 126 69 Print Done X
The table below lists measured amounts of redshift and the distances (billions of light-years) to randomly selected astronomical objects. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 90% confidence level with a redshift of 0.0126. D Redshift Distance 0.0237 0.32 0.0545 0.75 0.0724 1.02 0.0397 0.56 0.0442 0.61 0.0103 0.16 a. Find the explained variation. (Round to six decimal places as needed.) b. Find the unexplained variation. (Round to six decimal places as needed.) c. Find the indicated prediction interval. billion light-years
Section 10.3 Question #6 Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude 4 11 14 20 28 31 34 Temperature 55 39 26 −2 −34 −41 −59 a. Find the explained variation. ______________ (Round to two decimal places as needed.) b. Find the unexplained variation. _______________ (Round to five decimal places as needed.) c. Find the indicated prediction interval. _____________°F < y < ____________ °F (Round to four decimal places as needed.)
The table below lists measured amounts of redshift and the distances (billions of light-years) to randomly selected astronomical objects. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 90% confidence leve with a redshift of 0.0126. Redshift Distance 0.0231 0.31 a. Find the explained variation. 0.0536 0.77 (Round to six decimal places as needed.) b. Find the unexplained variation. (Round to six decimal places as needed.) c. Find the indicated prediction interval. 0.0716 0.0395 1.01 0.53 billion light-years

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