(By-Hand) A dietetics student wants to look at the relationship between calcium intake (g/week) and knowledge score about calcium in sports science students (knowledgescore out of 50). Further she wants to know if knowledge about calcium can be used to predict calcium intake of the students. The table below shows the data she collected.Knowledge Score38Total:DENFES254828224118263043319Calcium Intake9.407.339.857.635.838.107.987.748.0510.8582.76xy357.20183.25472.80213.64128.26332.10143.64201.24241.50466.552740.2x²144462523047844841681324676900184911071y²88.360053.728997.022558.216933.988965.610063.680459.907664.8025117.7225703.0402 Part d:Compute the least squares regression equation. Show your work.Parte:If appropriate, use a 99% interval for the average calcium intake of people who have a knowledge score of 3 (show your work). If not appropriate, explain why. Eitherway, clearly present your answer in a sentence. [Hint: Use the key words to determine if this should be a confidence interval or a prediction interval.]Part f:If appropriate, use a 99% interval for the specific calcium intake of Darby Alexander who have a knowledge score of 41 (show your work). If not appropriate, explain why.Either way, clearly present your answer in a sentence. [Hint: Use the key words to determine if this should be a confidence interval or a prediction interval.]

The given data is Knowledge Score Calcium Intake xy x2 y2 38 9.4 357.2 1444 88.36 25…

Answered: Part d: Compute the least squares…

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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Report the equation of the regression line and interpret it in the context of the problem
Interpret the regression results.
Part and b. Thank you!
a. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 x
How does R treat those observations with missing values? In other words, what role do the observations with missing values play in the regression? No command is needed for this question. You must need to provide an answer or take a guess.
1. School administrators believe their freshman applications are influenced by two variables: tuition and the size of the applicant pool of eligible high school seniors in the state. The following data for an 8-year period show the tuition rates (per semester) and the sizes of the applicant pool for each year: Tuition in pesos Applicants Pool Applicants 27000 76,200 11,060 37500 78,050 10,900 41250 67,420 8,670 42000 70,390 9.050 46500 62,550 7,400 48750 59,230 7,100 52500 57,900 6,300 57900 60,080 6,100
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
In order to explain the U.S. defense budget, the following variables are considered. Data from 1962-1981 is collected. Variable Definition Y Defense budget-outlay for year t, $ billions X2 GNP for year t, $ billions X3 U.S. military sales/assistance in year t, $ billions X4 Aerospace industry sales, $ billions Dependent Variable: Y Method: Least Squares Date: 11/22/21 Time: 11:20 Sample: 1962 1981 Included observations: 20 Variable Coefficient Std. Error t-Statistic Prob. X2 0.016703 0.007017 2.380261 0.0301 X3 -0.696174 0.453978 -1.533497 0.1447 X4 1.467729 0.277608 5.287047 0.0001 22.77514 3.311695 6.877186 0.0000 R-squared 0.971088 Mean dependent var 83.86000 Adjusted R-squared 0.965667 S.D. dependent var 28.97771 S.E. of regression Sum squared resid 5.369339 Akaike info criterion 6.376143 461.2769 Schwarz criterion 6.575290 Log likelihood -59.76143 Hannan-Quinn criter. 6.415019 F-statistic 179.1337 Durbin-Watson stat 0.676777 Prob(F-statistic) 0.000000
Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 658.
Please answer A,B, D, F, & G pls and thank you!
Use the p-value criterion to find the best model for predicting the number of points scored per game by football teams using the accompanying National Football League Data. Does the model make logical sense? E Click the icon to view the National Football League Data. Determine the best multiple regression model. Let X, represent Rushing Yards, let X, represent Passing Yards, let X3 represent Penalties, let X4 represent Interceptions, and let Xg represent Fumbles. Enter the terms of the equation so that the Xy-values are in ascending numeral order by base. Select the correct choice below and fill in the answer boxes within your choice. (Type an integer or decimal rounded to three decimal places as needed.) Points/Game =+ OX 01+Og+O1 A. OB Points/Game = O C. Points/Game = OD. Points/Game = + Dx O E. Points/Game = Data table for the national football league Points/ Game Rushing Yards/ Game Passing Yards/ Penalties Interceptions Fumbles O Game 25.2 90.1 259.2 140 18 4 16.2 95.2 208.5 108…
Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 602.

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