The accompanying table lists overhead widths (cm) of seals measured from photographs and the weights (kg) of the seals. Find the (a) explained variation, (b) unexplained variation, and (c)prediction interval for an overhead width of 9.2 cm using a 99% confidence level. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regressionequation when making predictions.Click the icon to view the seal data.a. The explained variation is(Round to the nearest integer as needed.)b. The unexplained variation is(Round to the nearest integer as needed.)c. The 99% prediction interval for an overhead width of 9.2 cm is ☐ kg

Answered: Image /qna-images/answer/3e11f069-25f2-43d3-a2d6-7fd359c2ec2d.jpg

Answered: The accompanying table lists overhead…

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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TAMU admissions board believes the score you get on the SAT in high school can help predict your college GPA. Below is a regression model using the SAT scores and GPA for 83 college graduates. Calculate a 70% Confidence Interval for the slope of the regression line. Use 4 decimal places.(Note: The SAT scores have been divided by 100 just to make the numbers nicer) Simple linear regression results:Dependent Variable: GPAIndependent Variable: SAT/100GPA = 1.318967 + 0.174653 [SAT/100]Sample size: 83R (correlation coefficient) = 0.1487R-sq = 0.0221Estimate of error standard deviation: 0.118302Parameter estimates: Parameter Estimate Std. Err. DF T-Stat P-Value Intercept 1.318967 0.3631 81 3.633 0.00049 Slope 0.174653 0.129086 81 1.353 0.1798 Use 4 decimal places
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05 Right Arm 101 100 94 75 Left Arm 174 167 146 144 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is (Round to one decimal place as needed.) 76 144 CRITS
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 103 102 95 79 80 Left Arm 174 168 143 143 144 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y=____?+____?x.
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 11 13 24 28 31 32 Temperature 57 32 24 1 - 31 - 41 - 52 a. Find the explained variation. (Round to two decimal places as needed.)
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 Temperature 2 55 a. Find the explained variation. 8 40 10370.30 (Round to two decimal places as needed.) b. Find the unexplained variation. (Round to five decimal places as needed.) 13 25 20 - 3 28 - 26 31 41 34 - 53
A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n = 15 college students. The SAT scores have a mean of M = 580 with SS = 22,400, and the GPAs have a mean of 3.10 with SS = 1.26, and SP = 84. Find the regression equation for predicting GPA from SAT scores. What percentage of the variance in GPAs is accounted for by the regression equation? (Compute the correlation r, then find r^2.) Does the regression equation account for a significant portion of the variance in GPA? Use α = .05 to evaluate the F-ratio.
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 9090 mm Hg. Use a significance level of 0.05 Right Arm 100 99 91 79 79 Left Arm 176 171 141 145 143 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is ModifyingAbove y with caretyequals=31.931.9plus+1.41.4x. (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 90mm Hg, the best predicted systolic blood pressure in the left arm is ???? mm Hg. (Round to one decimal place as needed.)
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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
As a marketing manager for TriFood, you want to determine whether store Sales (# sold in one month) of TriPower bars are related to price (in cents) of TriPower bars and in-store promotional expenditures (in dollars) for TriPower bars. You conduct a multiple regression analysis with store Sales (Y) as the response variable, and Price (X1) and Promotion (X2) as explanatory variables. Use the pictured Excel regression output below to answer the questions. a) Interpret the value for R square. Interpret the estimated coefficient for price. b) State the hypotheses for assessing the statistical significance of the overall regression equation. Does the model overall fit the data (yes or no?) f) An external consultant to TriFoods believes that for every $1 increase in promotional expenditures, sales will increase by 4.7 units. Test the consultant's hypothesis at a 5% significance level using both approaches (tcalc vs tcrit and p-value vs a).
Pls help ASAP. Pls show all work.
Consider the following data: - 4 - 3 - 1 P(X = x) 0.2 0.1 0.2 0.1 0.4 Step 4 of 5: Find the value of P(X > -2). Round your answer to one decimal place.

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