4.A statistician ran a regression of Y on X, X, X, X4, Xs, X6, using 27 observations.He tells you thatSSR( X1, X2, Xa, Xa, Xs, X6)=101.Fill out all the blanks in the following ANOVA Table.No need to look up any F-values or test any hypotheses.ANOVA TableMeanTestDegrees ofFreedomSource of VariationSum ofSquaresSquaresStatistic7.5X122X2, X3 | X1X4, Xs, X6 | X1, X2, X3Error88Total

Consider, the degrees of freedom: There are 27 observations. The number of variables in the given…

Answered: A statistician ran a regression of Y on…

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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After performing a statistical regression on a set of data the value of the correlation coefficient r was -0.2041. What does that imply about the data?
A person wishes to predict a woman's shoe size from her height. he has gathered this information from your female classmates. The mean height of women in your class is 64 inches, and the standard deviation is 2 inches. The mean shoe size is 8, and the standard deviation is 1. The correlation between these two variables is .5. What is the slope of the regression line?
If the regression line is not a "good fit" what would be better to use to approximate a response variable?
Answer it correctly and explain well.Typed answer only. Do it fast.
It is known that the slope coefficient for regression line Y on X is 0.942 The standard deviation of X and Y are 5 and 9 respectively. Find the value of the correlation coefficient for using given information.
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of fifteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation y = 40.86-0.45x. This line is shown in the scatter plot below. Mileage, x (in thousands) 29.7 27.8 26.8 24.2 21.1 23.0 24.3 15.4 37.7 23.6 34.4 27.8 23.5 20.9 259 Used selling price, y (in thousands of dollars) 27.4 29.4 31.2 30.1 31.7 31.7 27.2 34.2 23.4 28.2 26.3 26.5 33.7 30.6 267 Used selling price (in thousands of dollars) 40- 35+ 30- 25- 20 THIS 15 X 20 X X X 30 Mileagex (in thousands) X 35 40
There exists a moderate relationship between the variables x and y.if we draw samples of increasing sample size,what can we expect from the sample r value,the regression slope and the p value of the regression or correlation be affected by increasing sample size
The following sample contains the scores of 6 students selected at random in Mathematics and English. Use the scores in English as the dependent variable Y. Mathematics score (X) 70 92 80 74 65 83 English score (Y) 74 84 63 87 78 90 ∑x=464, ∑y=476,∑x^2=36354,∑y^2=38254, ∑xy=36926. Estimate the regression parameters and also write the prediction equation.
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation Ŷ=42.80-0.53x. This line is shown in the scatter plot below. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)
Find the simple regression line y=α+βx for the pairs of points belonging to the independent and dependent variables (xi,yi) , respectively. Also, interpret the result by calculating the Pearson correlation coefficient. Please dont use excel.
please do this urgently
Consider a certain data set on shoulder girth and height of a group of individuals. The mean shoulder girth is 107.20 cm with a standard deviation of 10.37 cm. The mean height is 171.14 cm with a standard deviation of 9.41 cm. The correlation between height and shoulder girth is 0.67. Calculate R2 of the regression line for predicting height from shoulder girth, and interpret it in the context of the application.

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A statistician ran a regression of Y on X, X, X, X4, Xs, X6, using 27 observations. He tells you that SSR( X1, X2, X, Xa, Xs, X6)= 101. Fill out all the blanks in the following ANOVA Table. No need to look up any F-values or test any hypotheses.