STA115 CH 4 - Sampling Errors

sampling errors

errors that are caused by the act of taking a sample and cause the results to be different from the results of a census

sampling errors examples

under coverage and/or biased sampling methods

non-sampling errors

errors that are not related to the act of selecting a sample

non-sampling errors examples

processing errors and/or non-response

under-coverage

occurs when some groups of the population are left out of the process of choosing the sample

non—response

failure to obtain data from a selected individual for a sample

sampling error covered by margin of error

random sampling error

wording bias

happens in a survey when the wording of a question systematically influences the responses

Which of the following is not a requirement for a simple random sample (SRS)?
a. Every member of the sample is representative of the population
b. Every possible sample from the population has the same chance of being selected
c. Every member of the population has the same chance of being selected for a sample

a. Every member of the sample is representative of the population

Charlie wants to interview people at TCNJ about their opinion on campus dining. He decides to randomly select 20 freshmen, 20 sophomores, 20 juniors, 20 seniors, and 20 faculty members.

Is this a simple random sample (SRS)?

no!

Dee, VP of Human Resources for Target, would like to study the effects of a recent healthcare benefit program for cashiers. She obtains a list of all cashiers employed by Target from corporate, alphabetizes the names, and randomly selects a group of 250. She then administers a survey to this sample.

Is this a sample random sample (SRS)?

yes

Dennis wants to select a group of 5 brothers from his fraternity to sing karaoke. He decides to select every other brother in line for the bathroom at Friday night's party, until he has a sample of 5 brothers.

Is this a simple random sample (SRS)?

no

The average height of a man is 177 cm. Suppose you select a random sample of 50 men from TCNJ. You calculate their average height to be 183 cm.

Match the terms to their values. (parameter, sample, statistic)

a. 177
b. 50
c. 183

a. 177 parameter

b. 50 sample

c. 183 statistic

Fill in the blanks:

In an attempt to eliminate variability, statisticians will _____________ the ______________ .

increase; sample size

What is the biggest influence on bias in a sample?
a. Margin of error
b. Random selection
c. Sample size
d. The treatment

b. random selection

The margin of error for a poll is 4%. This means that:
a. the confidence we have in the statistic is 4%.
b. 4% of those sampled gave the wrong answer to the question asked.
c. 4% of those sampled did not answer the question asked.
d. 4% of the population was in the sample.
e. we have 95% confidence that the sample statistic is within 4% of the population parameter.

e. we have 95% confidence that the sample statistic is within 4% of the population parameter.

A recent survey asked a sample of 1010 people if they were soccer fans; 454 people in the sample said "Yes." Assuming there is no bias, we can be 95% confident that the percent of all adults who are soccer fans is approximately between:

a. 40% and 50%.

b. 37% and 53%.

c. 42% and 48%.

d. 34% and 56%.

e. 41% and 49%.

c. 42% and 48%.

If a Gallup Poll surveys a national sample of 3000 people rather than 1500 people, the margin of error of the sample result would be:
a. either less or greater than it would be for 1500 because it depends on the chance outcome of the sample.
b. the same as for 1500 because the population is the same.
c. either less or greater than it would be for 1500. We can't say because sample size 3000 is not in the table.
d. less than it would be for 1500 because the sample is now larger.
e. greater than it would be for 1500 because the sample is now larger.

d. less than it would be for 1500 because the sample is now larger.

__________ in a sampling method means that the sample results will systematically misrepresent the population in the same way when we take repeated samples.

bias

What is one of the distinctions between a population parameter and a sample statistic?

a. A population parameter is only based on conceptual measurements, but a sample statistic is based on a combination of real and conceptual measurements.

b. A sample statistic typically changes each time you try to measure it, but a population parameter remains fixed.

c. A population parameter changes each time you try to measure it, but a sample statistic remains fixed across samples.

d. The true value of a sample statistic can never be known but the true value of a population parameter can be known.

e. A sample statistic typically changes each time you try to measure it, but a population parameter remains fixed.

b. A sample statistic typically changes each time you try to measure it, but a population parameter remains fixed.

__________ in a sampling method describes how spread out the values of the sample statistic are when we take repeated samples.

variability

Does using a cell phone while driving make an accident more likely? Researchers compared telephone company and police records to find 699 people who had cell phones and were also involved in an auto accident. Using phone billing records, they compared cell phone use in the period of the accident with cell phone use the same period on a previous day. Result: The risk of an accident was four times higher when using a cell phone.

The explanatory variable in this study is _______________ .

a. whether the subject had an auto accident.

b. whether the subject was using a cell phone.

c. the risk of an accident.

d. whether the subject owned a cell phone.

b. whether the subject was using a cell phone.

Does using a cell phone while driving make an accident more likely? Researchers compared telephone company and police records to find 699 people who had cell phones and were also involved in an auto accident. Using phone billing records, they compared cell phone use in the period of the accident with cell phone use the same period on a previous day. Result: The risk of an accident was four times higher when using a cell phone.

An example of a lurking variable that might affect the results of this study is _______________ .

a. whether the subject had an auto accident.
b. whether the subject was using a cell phone.
c. whether the subject was talking to a passenger in the car.
d. whether the subject owned a cell phone.

c. whether the subject was talking to a passenger in the car.