Chapter 5 Section 1:

SAMPLES

Read p. 201

Sample #1:

American Idol wants to decide their next winner. They do this through a call-in poll. They get a sample of 540,000 callers. 65% of them vote for Jimmy, so they declare that the American public has chosen Jimmy as the winner. Is it true that 65% of Americans like Jimmy the best?

What’s wrong with this sample???

Sample #2:

A company wants to know about people’s TV habits. They decide to send employees to the mall to walk around and stop people and interview them about their TV usage and habits.

What’s wrong with this sample???

Sample #3:

A newspaper columnist asks his readers to write in about whether or not they want universal health care in this country. He gets 12,000 responses and 72% of them do not favor universal health care. Is it true that 72% of Americans don’t want universal health care?

What’s wrong with this sample???

Sample #4:

To determine whether a shipment of potatoes is good, a grocery store owner takes 10 potatoes off of the top of each crate and looks them over. If they are ok, then he accepts the lot.

What’s wrong with this sample???

Sample #5:

To try and gain info about HS students sleep habits, a researcher goes into a high school in the area and samples the first 100 students who walk in the door. He records info about their sleep habits. From this, he determines that on average high school students only sleep 5-6 hours per night.

What’s wrong with this sample???

GOOD SAMPLES

Sample #6:

To try and gain info about students sleep habits, a researcher goes to one high school in every school district in the nation. Once in that high school he gets a list of all students and randomly selects 30 students to interview.

Why is this a GOOD sample?

Sample #7:

To determine whether Americans want universal health care, the Gallup Poll phones 8 randomly selected households in each city/town in the country to ask their opinions about the subject.

Why is this a better sample than before? What is still wrong with it?

5.1- SAMPLING METHODS

GOOD & BAD

BIAS (in sampling):

•Systematically favoring one outcome over another

•Be able to identify sources of bias in a sample.

•Better to list more than less

BIASED SAMPLING METHODS:Voluntary Response Samples

•Chooses itself by responding to a general appeal.

•Very biased in that many reply with extreme or strong opinions on the subject matter.

•Not a representative sample since not all people would choose to respond.

•EX: Call-in, write-in, stopping in the mall, etc.

Convenience Samples

•Selecting individuals that are the easiest to reach/contact

•Not representative

Turn to page 205 and do #2 & 3

5.2 An online poll(a) Voluntary Response Sample(b) The sample is limited to those that read Parade, those that have access to online services, and were willing to go to the website to vote.

The 85% is probably higher than the true percent of all adults who believe that cell phone use while driving should be banned. People that are for the ban on cell phones would probably have stronger feelings on the subject and be more likely to go online to complete the survey.

5.3 Sleepless nights

(a) Convenience Sample

(b) Since the student chose the first 100 to arrive these students had probably had a good night sleep, awoken refreshed, and made it to school early.

The average is probably higher than the true average since those that did not sleep well or went to bed late probably hadn’t made it to school yet.

 

Also, look at #4

UNBIASED SAMPLING METHODS:

Simple Random Sample (SRS):

Sample of size n from a population chosen in such a way that:1.Every individual of the population has the same chance of being selected2.Every possible sample of size n has the same chance of being selected.

How to take a SRS:

Table of Random Digits (table A)-

•A long string of digits (0-9) with the following properties:

•Each digit in the table is equally likely to be any of the 10 digits

•The entries are independent of each other. So knowing one digit doesn’t affect what the next one is.

HOW TO USE THE TABLE (p.T2):

* Label each individual in your population with a number

* Each number given must have the same number of digits

2) TABLE

* Go to the table and read across in groups that are the same size as the numbers you assigned your individuals

1) LABEL

EXAMPLE:

Take a sample 5 from the following list. Start at line 131 in the table.

Smith Jones Holloway

DeNizzo David Adams

Schaefer Gray Capito

Meyers Gingrich Card

Dietrich Moreland Hall

Walsh Whitter Jordan

EXAMPLE:

Take a sample 4 from the following list. Start at line 118 in the table.

McGlone McCuen Wilson

Szarko Bellavance Woodring

Stotler Kelly Wheeles

Timmins Arden McNelis

Gemgnani O’Brien Robinson

Lorenz Lake Bainbridge

Turn to page 209, and do #7 & 8

7) Labels: 01 – 33

Line 117: 16, 32, 18

Fairington, Waterford Court, Fowler

8) (a) False

(b) True

(c) False

CALCULATOR: randInt( )

- MATH

- PRB

- #5

- randInt(Lowest #in sample, highest #)

- hit ENTER (as many times as you need)

- repeats? IGNORE!

EXAMPLE:

Take a sample 5 from the following list. Use the calculator!

Johnson Hitchens McCarthy

Salimbene Hopkins Rolin

Fielder Hoffman Washington

Scott Robinson Clark

Lane Vazquez Loria

Sanchez Hamilton Chen

Schulze Steinberg Suzano

Turn to page 210 and do #11 using your calculator.

How to write instructions for SRS:

• Label each _______ with #’s (list the #’s)

• Use TRD, read across, every ____ digits represent a person.

• Ignore #’s ________, and repeats

• The first _____ numbers are our sample