. The Department of Transportation (DOT) is responsible for replacing road signs that are no longer adequately reflective. The DOT has replacement signs in a warehouse but wants to know whether their inventory differs from the types of signs found in a certain area. The DOT takes a random sample of 100 signs and observes the type of each. The sample data are tabulated below along with the known percentage of each type currently in inventory. Sign Type Route Stop Yield Other Sample Count Inventory% 37 36% 45 9 9 44% 9% 11% Of the following, which is the best procedure to investigate whether there is convincing statistical evidence that the distribution of sign types in this area differs from the distribution in the DOT's inventory? (A) A chi-square goodness-of-fit test (B) A chi-square test of independence (C) A chi-square test of homogeneity (D) A matched-pairs 1-test for a mean difference (E) A two-sample t-test for the difference between two means
. The Department of Transportation (DOT) is responsible for replacing road signs that are no longer adequately reflective. The DOT has replacement signs in a warehouse but wants to know whether their inventory differs from the types of signs found in a certain area. The DOT takes a random sample of 100 signs and observes the type of each. The sample data are tabulated below along with the known percentage of each type currently in inventory. Sign Type Route Stop Yield Other Sample Count Inventory% 37 36% 45 9 9 44% 9% 11% Of the following, which is the best procedure to investigate whether there is convincing statistical evidence that the distribution of sign types in this area differs from the distribution in the DOT's inventory? (A) A chi-square goodness-of-fit test (B) A chi-square test of independence (C) A chi-square test of homogeneity (D) A matched-pairs 1-test for a mean difference (E) A two-sample t-test for the difference between two means
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question

Transcribed Image Text:. The Department of Transportation (DOT) is responsible for replacing road signs that are no longer
adequately reflective. The DOT has replacement signs in a warehouse but wants to know whether
their inventory differs from the types of signs found in a certain area. The DOT takes a random
sample of 100 signs and observes the type of each. The sample data are tabulated below along with
the known percentage of each type currently in inventory.
Sign Type
Route
Stop
Yield
Other
Sample Count
Inventory%
37
36%
45
9
9
44%
9%
11%
Of the following, which is the best procedure to investigate whether there is convincing statistical
evidence that the distribution of sign types in this area differs from the distribution in the DOT's
inventory?
(A) A chi-square goodness-of-fit test
(B) A chi-square test of independence
(C) A chi-square test of homogeneity
(D) A matched-pairs 1-test for a mean difference
(E) A two-sample t-test for the difference between two means
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