Question

You must provided printed R codes and Any work done in R must be printed. 1. Snow geese feeding trial. Refer to the Journal of Applied Ecology (Vol. 32, 1995) study of the feeding habits of baby snow geese. The data on gosling weight change, digestion efficiency, acid-detergent fiber (all measured as percentages) and diet (plants or duck chow) for 42 feeding trials are saved in the SNOWGEESE file. The botanists were interested in predicting weight change (y) as a function of the other variables. a) Assume x1 = digestion efficiency and X2 = acid-detergent fiber and give the least squares prediction equation for the weight change, y. b) Interpret the B - estimates in the equation in part (a). c) Conduct the F-test for overall model adequacy using a = 0.01. d) Find and interpret the value of Radj. e) Conduct a test to determine if digestion efficiency, X1, is a useful linear predictor of weight change. Use a = 0.01. f) Form a 95% confidence interval for B2. Interpret the result.

SnowGeese File:

Trial   Diet   WtChange   DigEff   ADFiber
1   Plants   -6.0   0.0   28.5
2   Plants   -5.0   2.5   27.5
3   Plants   -4.5   5.0   27.5
4   Plants   0.0   0.0   32.5
5   Plants   2.0   0.0   32.0
6   Plants   3.5   1.0   30.0
7   Plants   -2.0   2.5   34.0
8   Plants   -2.5   10.0   36.5
9   Plants   -3.5   20.0   28.5
10   Plants   -2.5   12.5   29.0
11   Plants   -3.0   28.0   28.0
12   Plants   -8.5   30.0   28.0
13   Plants   -3.5   18.0   30.0
14   Plants   -3.0   15.0   31.0
15   Plants   -2.5   17.5   30.0
16   Plants   -0.5   18.0   22.0
17   Plants   0.0   23.0   22.5
18   Plants   1.0   20.0   24.0
19   Plants   2.0   15.0   23.0
20   Plants   6.0   31.0   21.0
21   Plants   2.0   15.0   24.0
22   Plants   2.0   21.0   23.0
23   Plants   2.5   30.0   22.5
24   Plants   2.5   33.0   23.0
25   Plants   0.0   27.5   30.5
26   Plants   0.5   29.0   31.0
27   Plants   -1.0   32.5   30.0
28   Plants   -3.0   42.0   24.0
29   Plants   -2.5   39.0   25.0
30   Plants   -2.0   35.5   25.0
31   Plants   0.5   39.0   20.0
32   Plants   5.5   39.0   18.5
33   Plants   7.5   50.0   15.0
34   Chow   0.0   62.5   8.0
35   Chow   0.0   63.0   8.0
36   Chow   2.0   69.0   7.0
37   Chow   8.0   42.5   7.5
38   Chow   9.0   59.0   8.5
39   Chow   12.0   52.5   8.0
40   Chow   8.5   75.0   6.0
41   Chow   10.5   72.5   6.5
42   Chow   14.0   69.0   7.0

Please use R-Studio and Provide code neatly

Answer 1

library(dplyr)
library(tidyr)

setwd=("D:/Baswanth)
data=read.csv("D:/Baswanth/goose.csv")

fit<-lm(data$DigEff~data$ADFiber)

summary(fit)

Call: Im(formula = data$Digeff - datasADFiber) Residuals: Min 10 Median -19.238 -8.143 2.067 3Q 8.040 Max 18.250 Coefficients : Estimate std. Error t value Pr(t) (Intercept) 77.5673 4.3520 17.82 < 2e-16 *** data $ADFiber -2.1106 0 .1801 -11.72 1.64e-14 *** Signif. codes: ****' 0.001 ***' 0.01 *' 0.05 ' 0.1''1 Residual standard error: 10.4 on 40 degrees of freedom Multiple R-squared: 0.7745, Adjusted R-squared: 0.7689 F-statistic: 137.4 on 1 and 40 DF, P-value: 1.636e-14

(b) interpret :=77.5673

(c)F-test=137.4

(d) adjusted R-squared=0.7689

(e) p-value=1.6 so statistically not significance

(f) compute alpha=1(confidence/100)=1-95/100=0.05

critical probability p=1-0.05/2=1-0.05/2=0.975

degree of freedom=40-2=38

Me=critical value*standard error

1.0*10.4=10.4