Regression Analysis: Growth versus Water, Fertilizer The regression equation is Growth = B + 0 Water + aFertilizer Predictor Сoef SE Coef T Constant 42.085 ** 3.118 0.009 Water 0.178 0.386 0.460 0.654 Fertilizer 5.790 0.952 6.083 * 6.159 R-Sq 77.1%% R-Sq (adj) = 73.3% S = Analysis of Variance Source DF SS MS F Regression 1532.603 766.301 *** **** Residual Error 12 455.130 37.928 Total 14 1987.733

College Algebra
1st Edition
ISBN:9781938168383
Author:Jay Abramson
Publisher:Jay Abramson
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3SE: What is regression analysis? Describe the process of performing regression analysis on a graphing...
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The Mayor of texas whom is partners with a local agriculturalist wants to know how the amount of fertilizer and the amount of water given to plants affect their growth. The results were inputted into MINITAB so as to fit the model

a) Write out the regression equation 

b) What is the sample size used in this investigation? 

c) Determine the values of *, ** and ***, **** 

d) Conduct a hypothesis test, at the 5% level of significance, to determine whether ? is significant.

e) What would be the growth of the plant if 4g of fertilizer and 7g of ater was given to it daily? 

f)  Carry out an F -test at the 1% significance level to determine whether the model is significant

 

Regression Analysis: Growth versus Water, Fertilizer
The regression equation is
Growth
B + Ø Water + aFertilizer
Predictor
Соef
SE Coef
T
Constant
42.085
**
3.118
0.009
Water
0.178
0.386
0.460
0.654
Fertilizer
5.790
0.952
6.083
S
6.159
R-Sq
77.1%%
R-Sq (adj)
73.3%
Analysis of Variance
Source
DF
SS
MS
F
P
Regression
Residual Error
1532.603
766.301
***
****
12
455.130
37.928
Total
14
1987.733
Transcribed Image Text:Regression Analysis: Growth versus Water, Fertilizer The regression equation is Growth B + Ø Water + aFertilizer Predictor Соef SE Coef T Constant 42.085 ** 3.118 0.009 Water 0.178 0.386 0.460 0.654 Fertilizer 5.790 0.952 6.083 S 6.159 R-Sq 77.1%% R-Sq (adj) 73.3% Analysis of Variance Source DF SS MS F P Regression Residual Error 1532.603 766.301 *** **** 12 455.130 37.928 Total 14 1987.733
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