A forester reported the following distribution of tree types to a local logging company. Tree Type Percent Spruce 52% Pine 22% Fir Deciduous Other 8% 10% 8% The logging company generated a random sample of 100 trees and observed the following distribution of trees in each of the categories. Spruce Pine Fir Deciduous Other Tree Type Observed Count 51 21 10 9 9 The logging company would like to use its sample to provide convincing statistical evidence that over 50 percent of the trees in the forest are spruce trees. The logging company has decided to use a chi-square goodness-of-fit test to justify its claim. Why is the chi-square goodness-of-fit test not an appropriate procedure for the logging company to use? A chi-square goodness-of-fit test would be used to show that the entire distribution of trees in the forest is (A) different than what the forester reported, not necessarily the individual proportion representing the spruce trees. The logging company should find the average number of spruce trees using several samples and then (B) construct a confidence interval for a difference in population means to show that there are more spruce trees in the forest than reported. (C) The logging company does not need to complete an inference procedure; there are more than 50 percent spruce trees in the sample. In order to perform a chi-square test, the logging company needs expected counts, not percentages. The (D) logging company should declare its current sample as expected values and then generate a new sample of observed values to compute the test statistic. (E) The sample does not meet the minimum requirements needed for a chi-square goodness-of-fit test.
A forester reported the following distribution of tree types to a local logging company. Tree Type Percent Spruce 52% Pine 22% Fir Deciduous Other 8% 10% 8% The logging company generated a random sample of 100 trees and observed the following distribution of trees in each of the categories. Spruce Pine Fir Deciduous Other Tree Type Observed Count 51 21 10 9 9 The logging company would like to use its sample to provide convincing statistical evidence that over 50 percent of the trees in the forest are spruce trees. The logging company has decided to use a chi-square goodness-of-fit test to justify its claim. Why is the chi-square goodness-of-fit test not an appropriate procedure for the logging company to use? A chi-square goodness-of-fit test would be used to show that the entire distribution of trees in the forest is (A) different than what the forester reported, not necessarily the individual proportion representing the spruce trees. The logging company should find the average number of spruce trees using several samples and then (B) construct a confidence interval for a difference in population means to show that there are more spruce trees in the forest than reported. (C) The logging company does not need to complete an inference procedure; there are more than 50 percent spruce trees in the sample. In order to perform a chi-square test, the logging company needs expected counts, not percentages. The (D) logging company should declare its current sample as expected values and then generate a new sample of observed values to compute the test statistic. (E) The sample does not meet the minimum requirements needed for a chi-square goodness-of-fit test.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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what is the correct answer and solutions to the given problem?
Transcribed Image Text:A forester reported the following distribution of tree types to a local logging company.
Tree Type
Percent
Spruce
52%
Pine
22%
Fir
Deciduous
Other
8%
10%
8%
The logging company generated a random sample of 100 trees and observed the following distribution of trees in
each of the categories.
Spruce Pine Fir Deciduous Other
Tree Type
Observed Count 51 21 10 9
9
The logging company would like to use its sample to provide convincing statistical evidence that over 50 percent of
the trees in the forest are spruce trees. The logging company has decided to use a chi-square goodness-of-fit test to
justify its claim. Why is the chi-square goodness-of-fit test not an appropriate procedure for the logging company to
use?
Transcribed Image Text:A chi-square goodness-of-fit test would be used to show that the entire distribution of trees in the forest is
(A) different than what the forester reported, not necessarily the individual proportion representing the spruce
trees.
The logging company should find the average number of spruce trees using several samples and then
(B) construct a confidence interval for a difference in population means to show that there are more spruce trees
in the forest than reported.
(C)
The logging company does not need to complete an inference procedure; there are more than 50 percent
spruce trees in the sample.
In order to perform a chi-square test, the logging company needs expected counts, not percentages. The
(D) logging company should declare its current sample as expected values and then generate a new sample of
observed values to compute the test statistic.
(E) The sample does not meet the minimum requirements needed for a chi-square goodness-of-fit test.
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