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A simple random sample of size n = 200 drivers with a valid driver's license is asked if they drive an American-made automobile. Of the 200 drivers surveyed, 104 responded that they drive an American-made automobile. Determine if a majority of those with a valid driver's license drive an American-made automobile at the a = 0.05 level of significance. What type of variable is "drive an American-made automobile, or not"? O A. Qualitative with more than two possible outcomes O B. Discrete OC. Continuous O D. Qualitative with two possible outcomes

A simple random sample of size n = 200 drivers with a valid driver's license is asked if they drive an American-made automobile. Of the 200 drivers surveyed, 104 responded that they drive an American-made automobile. Determine if a majority of those with a valid driver's license drive an American-made automobile at the a = 0.05 level of significance. What type of variable is "drive an American-made automobile, or not"? O A. Qualitative with more than two possible outcomes O B. Discrete OC. Continuous O D. Qualitative with two possible outcomes

MATLAB: An Introduction with Applications
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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**Survey Analysis: Determining Majority Using Sample Data** In a study involving a simple random sample of 200 drivers with valid driver's licenses, each participant was asked whether they drive an American-made automobile. Of these 200 individuals surveyed, 104 responded affirmatively, indicating they drive an American-made vehicle. The objective is to determine whether a majority of drivers with valid licenses operate an American-made automobile at a 0.05 level of significance. **Question: Type of Variable** The variable of interest is whether the driver operates an American-made automobile or not. Which of the following best describes this type of variable? - **A.** Qualitative with more than two possible outcomes - **B.** Discrete - **C.** Continuous - **D.** Qualitative with two possible outcomes **Explanation of Options:** - **Option A:** This choice is incorrect as the variable has only two possible outcomes. - **Option B:** Discrete variables are numerical, often counting in nature, which does not apply here. - **Option C:** Continuous variables are numerical and can take on any value within a range, unsuitable for this scenario. - **Option D:** Correct. The variable "drive an American-made automobile, or not" is qualitative with two possible outcomes: "Yes" or "No." This setup is typical for hypothesis testing, where significant levels like 0.05 are used to ascertain the statistical majority in a population.
Transcribed Image Text:**Survey Analysis: Determining Majority Using Sample Data** In a study involving a simple random sample of 200 drivers with valid driver's licenses, each participant was asked whether they drive an American-made automobile. Of these 200 individuals surveyed, 104 responded affirmatively, indicating they drive an American-made vehicle. The objective is to determine whether a majority of drivers with valid licenses operate an American-made automobile at a 0.05 level of significance. **Question: Type of Variable** The variable of interest is whether the driver operates an American-made automobile or not. Which of the following best describes this type of variable? - **A.** Qualitative with more than two possible outcomes - **B.** Discrete - **C.** Continuous - **D.** Qualitative with two possible outcomes **Explanation of Options:** - **Option A:** This choice is incorrect as the variable has only two possible outcomes. - **Option B:** Discrete variables are numerical, often counting in nature, which does not apply here. - **Option C:** Continuous variables are numerical and can take on any value within a range, unsuitable for this scenario. - **Option D:** Correct. The variable "drive an American-made automobile, or not" is qualitative with two possible outcomes: "Yes" or "No." This setup is typical for hypothesis testing, where significant levels like 0.05 are used to ascertain the statistical majority in a population.
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