Consider a regression model in which the response variable Y, is linked to the explanatory variable X, by the following equation: Y, = a + bX,+ e;, i = 1, .., n assuming that the error terms e; are independent and Normally distributed with expectation 0 and variance o. In a sample of size n = 10, the following statistics have been observed: x; = 141, > Ex,= 127, =1 > = 2,014, = 1,629, xy= 1,810. (i) Calculate values for Ser, Syy, and Sy. (ii) Write down, using your answers to part (i), the value of Pearson's correlation coefficient between the variables X, and Y. (ii) Calculate estimates of the parameters a and b in the regression model.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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ISBN:9780079039897
Author:Carter
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Chapter10: Statistics
Section10.1: Measures Of Center
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Consider a regression model in which the response variable Y, is linked to the
explanatory variable X, by the following equation:
Y;= a + bX;+ e;, i = 1, ., n
assuming that the error terms e are independent and Normally distributed with
expectation 0 and variance o?. In a sample of size n = 10, the following statistics have
been observed:
x, = 141,
= 127,
i=1
> x = 2,014, v = 1,629,
xyi= 1,810.
i=1
i=1
(i)
Calculate values for Sy, Sy, and Sy.
Write down, using your answers to part (i), the value of Pearson's correlation
coefficient between the variables X, and Y,.
(ii)
(iii)
Calculate estimates of the parameters a and b in the regression model.
Transcribed Image Text:Consider a regression model in which the response variable Y, is linked to the explanatory variable X, by the following equation: Y;= a + bX;+ e;, i = 1, ., n assuming that the error terms e are independent and Normally distributed with expectation 0 and variance o?. In a sample of size n = 10, the following statistics have been observed: x, = 141, = 127, i=1 > x = 2,014, v = 1,629, xyi= 1,810. i=1 i=1 (i) Calculate values for Sy, Sy, and Sy. Write down, using your answers to part (i), the value of Pearson's correlation coefficient between the variables X, and Y,. (ii) (iii) Calculate estimates of the parameters a and b in the regression model.
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