(a) The table below shows the age of children and the number of words recalled in a memory game. Age Number of Words Recalled 3 5 4 5 6 4 6 (1) Based on the data above, find the linear regression...


q2  can you show every step on how to do the question do that I can understand the steps clearly. Also attached the regression . please use this formula ya


(a) The table below shows the age of children and the number of words recalled in a memory game.<br>Age<br>Number of Words Recalled<br>3<br>5<br>4<br>5<br>6<br>4<br>6<br>(1) Based on the data above, find the linear regression equation to predict the number of words<br>recalled from their age.<br>(1) Calculate the predicted Y value for each of the X value<br>

Extracted text: (a) The table below shows the age of children and the number of words recalled in a memory game. Age Number of Words Recalled 3 5 4 5 6 4 6 (1) Based on the data above, find the linear regression equation to predict the number of words recalled from their age. (1) Calculate the predicted Y value for each of the X value
Regression Steps<br>STEP 1 PEARSON CORRELATION FIND r VALUE<br>STEP 2 REGRESSION<br>Regression function<br>Σx ΣΥ = Σxy -<br>ỹ = a + bx<br>Σχ2ΣΥ2 :<br>N =<br>ExEy<br>SP -Σxy -<br>Slope b regression of line<br>SP<br>n<br>(Ey)?<br>b<br>SSx<br>SSy = Ey2<br>n<br>(Σx)2<br>Y intercept a of regression line<br>SSy Σχ2<br>а — Му — ьмх<br>– bMx<br>à =<br>SP<br>r =<br>(SSx)(SSy)<br>STEP 3<br>F RATIO HYPOTHESIS TESTING REGRESSIION STANDARD ERROR OF ESTIMATE<br>STEP4<br>но-<br>SS resi dual<br>п — 2<br>SS regression =r2 SSy<br>SS residual = (1-r^2 XSSY )<br>Df regression<br>Df residual =n – 2<br>(Numerator)<br>(denominator)<br>MS regression = (SS regression)/df regression)<br>MS residual = (SS residual)/(df residual)<br>F= (MS regression)/(MS residual)<br>a 0.05, df = Numerator, Denominator, F Critical (from<br>the table) =<br>If F calculated >F Critical , H0 Rejected<br>

Extracted text: Regression Steps STEP 1 PEARSON CORRELATION FIND r VALUE STEP 2 REGRESSION Regression function Σx ΣΥ = Σxy - ỹ = a + bx Σχ2ΣΥ2 : N = ExEy SP -Σxy - Slope b regression of line SP n (Ey)? b SSx SSy = Ey2 n (Σx)2 Y intercept a of regression line SSy Σχ2 а — Му — ьмх – bMx à = SP r = (SSx)(SSy) STEP 3 F RATIO HYPOTHESIS TESTING REGRESSIION STANDARD ERROR OF ESTIMATE STEP4 но- SS resi dual п — 2 SS regression =r2 SSy SS residual = (1-r^2 XSSY ) Df regression Df residual =n – 2 (Numerator) (denominator) MS regression = (SS regression)/df regression) MS residual = (SS residual)/(df residual) F= (MS regression)/(MS residual) a 0.05, df = Numerator, Denominator, F Critical (from the table) = If F calculated >F Critical , H0 Rejected

Jun 06, 2022
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