Question

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The types of browse favored by deer are shown in the following table. Using binoculars, volunteers...

The types of browse favored by deer are shown in the following table. Using binoculars, volunteers observed the feeding habits of a random sample of 320 deer.

Type of Browse Plant Composition
in Study Area
Observed Number of Deer
Feeding on This Plant
Sage brush           32% 105                
Rabbit brush           38.7% 125                
Salt brush           12% 46                
Service berry             9.3% 22                
Other             8% 22                

Use a 5% level of significance to test the claim that the natural distribution of browse fits the deer feeding pattern.

(a) What is the level of significance?


State the null and alternate hypotheses.

H0: The distributions are different.
H1: The distributions are the same.

H0: The distributions are the same.
H1: The distributions are the same.    

H0: The distributions are the same.
H1: The distributions are different.

H0: The distributions are different.
H1: The distributions are different.


(b) Find the value of the chi-square statistic for the sample. (Round the expected frequencies to at least three decimal places. Round the test statistic to three decimal places.)


Are all the expected frequencies greater than 5?

Yes

No    


What sampling distribution will you use?

binomial

Student's t    

uniform

normal

chi-square


What are the degrees of freedom?


(c) Estimate the P-value of the sample test statistic.

P-value > 0.100

0.050 < P-value < 0.100    

0.025 < P-value < 0.050

0.010 < P-value < 0.025

0.005 < P-value < 0.010

P-value < 0.005


(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis that the population fits the specified distribution of categories?

Since the P-value > α, we fail to reject the null hypothesis.

Since the P-value > α, we reject the null hypothesis.    

Since the P-value ≤ α, we reject the null hypothesis.

Since the P-value ≤ α, we fail to reject the null hypothesis.


(e) Interpret your conclusion in the context of the application.

At the 5% level of significance, the evidence is sufficient to conclude that the natural distribution of browse does not fit the feeding pattern.

At the 5% level of significance, the evidence is insufficient to conclude that the natural distribution of browse does not fit the feeding pattern.

Solutions

Expert Solution

Use a 5% level of significance to test the claim that the natural distribution of browse fits the deer feeding pattern.

(a) What is the level of significance?
0.05

State the null and alternate hypotheses.

H0: The distributions are the same.
H1: The distributions are different.


(b) Find the value of the chi-square statistic for the sample. (Round the expected frequencies to at least three decimal places. Round the test statistic to three decimal places.)


Are all the expected frequencies greater than 5?

Answer: Yes

No    


What sampling distribution will you use?

Answer: chi-square


What are the degrees of freedom?
5-1 = 4

(c) Estimate the P-value of the sample test statistic.

Answer: P-value > 0.100

0.050 < P-value < 0.100    

0.025 < P-value < 0.050

0.010 < P-value < 0.025

0.005 < P-value < 0.010

P-value < 0.005


(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis that the population fits the specified distribution of categories?

Answer: Since the P-value > α, we fail to reject the null hypothesis.

Since the P-value > α, we reject the null hypothesis.    

Since the P-value ≤ α, we reject the null hypothesis.

Since the P-value ≤ α, we fail to reject the null hypothesis.


(e) Interpret your conclusion in the context of the application.

At the 5% level of significance, the evidence is sufficient to conclude that the natural distribution of browse does not fit the feeding pattern.

Answer: At the 5% level of significance, the evidence is insufficient to conclude that the natural distribution of browse does not fit the feeding pattern.

Goodness of Fit Test

observed

expected

O - E

(O - E)² / E

105

102.400

2.600

0.066

125

123.840

1.160

0.011

46

38.400

7.600

1.504

22

29.760

-7.760

2.023

22

25.600

-3.600

0.506

320

320.000

0.000

4.111

4.111

chi-square

4

df

0.3912

p-value


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