Transcript Topic 01 - Producing Data 2013 part 2

Producing Data: Samples and
Experiments
Chapter 5
Warm up
 A sociologist wants to know the opinions of
employed adult women about government funding
for day care. She obtains a list of the 520
members of a local business and professional
women’s club and mails a questionnaire to 100 of
these women selected at random. Only 48
questionnaires are returned. What is the
population in this study? What is the sample?
Role of Sampling Design
 An important goal of statistics is to answer
questions using data with some guarantee
that the answers are good ones.
 An conclusion will be unreliable if the
method of collecting data is flawed.
 A poor design systematically favors certain
outcomes or results and thus provides
biased results.
Voluntary Response Design
 Suppose the principal is interested in
finding out if McCallum students think
more trees should be planted. He makes an
announcement and instructs students to
come by his office to let him know if tree
planting is an issue they support.
 Discuss the following:


Will your results provide reliable information?
Define “voluntary response design” on white
board.
Voluntary Response continued
 A voluntary response sample consists of
people who choose themselves by
responding to a general appeal.
 Voluntary response samples over represent
people with strong opinions.
Convenience Sample Design
 The principal is surprised to find most of
the students coming in his office are in
favor of the tree planting. Feeling that
maybe his design may not have worked, he
ventures into the hallways and starts asking
students randomly.
 Discuss the following:


Will your results provide reliable information?
Define “convenience sample design” on white
board.
Random-random sample practice
1. simple random
sample
2. convenience sample
3. cluster sample
4. voluntary response
5. systematic sample
6. stratefied sample
1. McCallum seniors
2. UT alumni
3. Time magazine
subscribers
4. Texans
5. national pet stores
6. Austin middle school
students
Cautions about sample surveys
 The following are terms that describe
potential problems while taking a sample.
 undercoverage
 nonresponse
 response bias
 wording of questions
 Discuss and define each term in your group.
Cautions about sample surveys
 Remember: sample results sometimes simply
do not necessarily match the population.
 undercoverage

the issue occurs when a sampling design misses a
part of the population
 nonresponse

the issue occurs when a significant part of the
population refuses to participate in the survey
Cautions about sample surveys
 response bias

the issue occurs when the person asking the
question makes the respondent uncomfortable and
possibly influence their answer
 wording of questions

the issue occurs when a question is leading and
attempts to persuade a respondent toward a
particular answer
Identify potential problems
 To obtain a sample of households, a
television rating service dials numbers taken
at random from telephone-directories.
 Teen magazine sent a mail-in questionnaire
to 500 randomly selected subscribers. One
of the questions was the following:
“Knowing that the cover price would likely
increase, would you prefer the number of
advertisements in the magazine to be
limited.?”
Identify potential problems
 For a survey of student opinions about high
school athletic programs, a member of the
school board obtains a random sample of
students by listing all high school students
and using a random number table to select
30 of them. After making phone calls last
weekend, she notes six of the students said
that they didn’t have time to participate in
the survey.
Role of mathematics in sampling
 Results will differ from sample to
sample. This phenomenon is called
sampling variability.
 Since we deliberately use ranomization,
the results obey the laws of probability
allowing fairly consistent results.
 The degree of accuracy can be improved
by increasing the size of the sample.