1DataPredictionresidualSquared error Outliers? Sigificance Level0.05Linear Regression and ScattE^2-0.31147541 0.097016931-3.31147541 10.965869392.691256831 7.2428633282 XYYhatRegression LineY-InterceptSlope385.31147541a=14.9071038316425.31147541b=-1.1994535521431411.30874317Correlation Coefficientr=-0.836787256121112.50819672-1.5081967212.27465735Correlation of Determination0.70021291110Sample SizeTest statisticP-value of rSum of Squared ErrorStandard deviation0.691256831 0.4778360061.890710383 3.57478575171211.30874317In=118841210.10928962t=D-4.58489980861112.50819672-1.5081967212.27465735P-value0.00131857541011213.70765027-1.707650273 2.916069456SSE40.98907104111414.90710383-0.9071038250.82283735s=2.134090257212128.9098360663.090163934 9.54911314213451341110.109289620.890710383 0.79336498614Explanatory Variable >1516171819202122232425.Linear Regressionresponse variable y 5. Best fit line, Regression Line, Least Square Line: We would like to be able to make prediction fromthe scatterplot data. One way to do this is create a "best fit line". Then use the line to predict values thathave not been measured yet. Let's label our variables;a is the erplanatory variable.y is the response variable.ŷ is the predicted response variable that we get by using our best fit line.In general the formula we use in statistics for the best fit line isŷ = a + bxwhere a and b found from the bivariant data and are constants. In this case b is the rate of change, or slopeof the line and a is the initial value or y-intercept of the line.Below we have data from 21 college students. Forearm length in inches is the explanatory variable. Height ininches is the response variable. The line is a good summary of the linear pattern in the data.747270686664626058569.5 10.0 10.5 11.0 11.5 12.O 12.5Forearm (inches)8.0 8.59.0The equation of the line is given by the following regression equation.Predicted height = 39 + 2.7 · forearm length(a) Based on the graph of this line, which is the best prediction of the height of a woman with a forearm of11 inches?A. 64.5 inches B. 68 inchesC. 68.75 inchesD. just under 72 inches(b) What is the most precise and accurate interpretation of the slope?(c) Use the equation of the line to predict the height of a woman with a 10-inch forearm. Show your work.

We have a regression line, where , Forearm length : independent variable. Predicted height :…

RO RS 20 2s 10.0 10s 11.0 11s 120 12s Ferearm (inches) The equation of the line is given by the following regression equation. Predicted height = 39 + 2.7 - forearm length (a) Based on the graph of this line, which is the best prediction of the height of a woman with a forearm of 11 inches? A. 61.5 inches B. 68 inches C. 68.75 inches D. just under 72 inches (b) What is the most precise and accurate interpretation of the slope?

RO RS 20 2s 10.0 10s 11.0 11s 120 12s Ferearm (inches) The equation of the line is given by the following regression equation. Predicted height = 39 + 2.7 - forearm length (a) Based on the graph of this line, which is the best prediction of the height of a woman with a forearm of 11 inches? A. 61.5 inches B. 68 inches C. 68.75 inches D. just under 72 inches (b) What is the most precise and accurate interpretation of the slope?

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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1.
A set of X and Y scores has SSX = 15, SSY = 24, and SP = 60. The regression equation for these scores will have a slope constant of ______. a. 6 b. 5 c. 3 d. 4
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