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A fitness trainer teaches an exercise class that is adjacent to an ice cream shop. The ice cream shop wants to attract more customers so they provide coupons for a free milkshake. The trainer randomly selects students as they enter the class and asks them if they would like a coupon for a free milkshake. Only 5% of the students take her up on her offer. Based on the random sample, a 90% confidence interval for the true proportion of her students that would want a free milkshake is between 1% and 9%. What is one potential source of bias in the study that is not accounted for by the margin of error? Nonresponse. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Nonresponse. The students may turn down the free milk shake (even those who truly want it) because they are being offered it from their trainer and want to appear dedicated to their fitness goals. Undercoverage. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Response bias. The students may turn down the free milkshake (even those who truly want it) because they are being offered the milkshake coupon from their trainer and want to appear dedicated to their fitness goals. There is no bias in this study.

A fitness trainer teaches an exercise class that is adjacent to an ice cream shop. The ice cream shop wants to attract more customers so they provide coupons for a free milkshake. The trainer randomly selects students as they enter the class and asks them if they would like a coupon for a free milkshake. Only 5% of the students take her up on her offer. Based on the random sample, a 90% confidence interval for the true proportion of her students that would want a free milkshake is between 1% and 9%. What is one potential source of bias in the study that is not accounted for by the margin of error? Nonresponse. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Nonresponse. The students may turn down the free milk shake (even those who truly want it) because they are being offered it from their trainer and want to appear dedicated to their fitness goals. Undercoverage. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Response bias. The students may turn down the free milkshake (even those who truly want it) because they are being offered the milkshake coupon from their trainer and want to appear dedicated to their fitness goals. There is no bias in this study.

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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A fitness trainer teaches an exercise class that is adjacent to an ice cream shop. The ice cream shop wants to attract more customers so they provide coupons for a free milkshake. The trainer randomly selects students as they enter the class and asks them if they would like a coupon for a free milkshake. Only 5% of the students take her up on her offer. Based on the random sample, a 90% confidence interval for the true proportion of her students that would want a free milkshake is between 1% and 9%. What is one potential source of bias in the study that is not accounted for by the margin of error? Nonresponse. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Nonresponse. The students may turn down the free milk shake (even those who truly want it) because they are being offered it from their trainer and want to appear dedicated to their fitness goals. Undercoverage. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Response bias. The students may turn down the free milkshake (even those who truly want it) because they are being offered the milkshake coupon from their trainer and want to appear dedicated to their fitness goals. There is no bias in this study.
Transcribed Image Text:A fitness trainer teaches an exercise class that is adjacent to an ice cream shop. The ice cream shop wants to attract more customers so they provide coupons for a free milkshake. The trainer randomly selects students as they enter the class and asks them if they would like a coupon for a free milkshake. Only 5% of the students take her up on her offer. Based on the random sample, a 90% confidence interval for the true proportion of her students that would want a free milkshake is between 1% and 9%. What is one potential source of bias in the study that is not accounted for by the margin of error? Nonresponse. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Nonresponse. The students may turn down the free milk shake (even those who truly want it) because they are being offered it from their trainer and want to appear dedicated to their fitness goals. Undercoverage. The true proportion of students that would want the free milkshake would be greater if she didn't leave out all of the people who do not attend her exercise class. Response bias. The students may turn down the free milkshake (even those who truly want it) because they are being offered the milkshake coupon from their trainer and want to appear dedicated to their fitness goals. There is no bias in this study.
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In statistical inference an investigator wants to know about the population parameters. But for practical purposes one may not observe the whole population and collect data. A part of the population that represents it, is called a sample. In estimating a parameter on basis of sample observations some errors may occur. One such is a bias that is the systematic deviation from the parameter.

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