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Firstly, I picked up three variables (X1: average temperature in January, X2: average temperature in February, and X3: average temperature in March) and set dependant variable Y as number of days after end of February. So, if the blooming day is 03/25, Y equals to 25; and if the day is 04/08, Y becomes 31+8=39. I arranged monthly average air temperature data in 1961 – 2004, ran MS-Excel regression data analysis function and gets the multiple linear regression equation as follows': Y=0.886X1 – 1.910X2– 3.213X3 + 63.069 (R²= 0.81)

Firstly, I picked up three variables (X1: average temperature in January, X2: average temperature in February, and X3: average temperature in March) and set dependant variable Y as number of days after end of February. So, if the blooming day is 03/25, Y equals to 25; and if the day is 04/08, Y becomes 31+8=39. I arranged monthly average air temperature data in 1961 – 2004, ran MS-Excel regression data analysis function and gets the multiple linear regression equation as follows': Y=0.886X1 – 1.910X2– 3.213X3 + 63.069 (R²= 0.81)

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 94E
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Can someone explain to me how this person set up the his multiple linear regression equation in excel when he ran a regression? I assume his X range would be the monthly average air temperature  (X1 - jan X2-feb X3-march) but what about his input range for y?

Firstly, I picked up three variables (X1: average temperature in January, X2: average temperature in February, and X3: average temperature in March) and set dependant variable Y as number of days after end of February. So, if the blooming day is 03/25, Y equals to 25; and if the day is 04/08, Y becomes 31+8=39. I arranged monthly average air temperature data in 1961 – 2004, ran MS-Excel regression data analysis function and gets the multiple linear regression equation as follows': Y=0.886X1 – 1.910X2 – 3.213X3 + 63.069 (R²=0.81)
Transcribed Image Text:Firstly, I picked up three variables (X1: average temperature in January, X2: average temperature in February, and X3: average temperature in March) and set dependant variable Y as number of days after end of February. So, if the blooming day is 03/25, Y equals to 25; and if the day is 04/08, Y becomes 31+8=39. I arranged monthly average air temperature data in 1961 – 2004, ran MS-Excel regression data analysis function and gets the multiple linear regression equation as follows': Y=0.886X1 – 1.910X2 – 3.213X3 + 63.069 (R²=0.81)
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