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Simple Random Sampling Lecture 7 Section 2.5 Robb T. Koether Hampden-Sydney College Mon, Jan 30, 2012 Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 1 / 28

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Page 1: Simple Random Sampling -

Simple Random SamplingLecture 7

Section 2.5

Robb T. Koether

Hampden-Sydney College

Mon, Jan 30, 2012

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 1 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 2 / 28

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Review Quiz

Example (Review Quiz)1 Researchers select all the patients that are suffering from

depression at a large hospital for their study.This could be an example of(a) Selection bias.(b) Non-response bias.(c) Response bias.(d) Experimenter bias.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 3 / 28

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Review Quiz

Example (Review Quiz)2 Patients agree (or disagree) to be a part of a study to test the

effectiveness of a new treatment.This could be an example of(a) Selection bias.(b) Non-response bias.(c) Response bias.(d) Experimenter bias.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 4 / 28

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Review Quiz

Example (Review Quiz)3 Patients join either a treatment group that receives the new

treatment and a control group that does not receive the treatment.This could be an example of(a) Selection bias.(b) Non-response bias.(c) Response bias.(d) Experimenter bias.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 5 / 28

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Review Quiz

Example (Review Quiz)4 After two weeks, the researchers check each patient to see how

well they are doing.This could be an example of(a) Selection bias.(b) Non-response bias.(c) Response bias.(d) Experimenter bias.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 6 / 28

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Review Quiz Answers

Example (Review Quiz Answers)1. (a) Selection bias.2. (b) Non-response bias.3. (c) Response bias.4. (d) Experimenter bias.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 7 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 8 / 28

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Introduction

Suppose I wanted to select a random sample of 4 students fromthis class.

I start in the front left corner and toss a coin.Heads, that student is selected.Tails, he is not selected.

I move on to the next student behind him and use the same rule.I continue in this manner, row by row, until I have 4 students.Is the sample a random sample?Is this a good method?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 9 / 28

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Introduction

Suppose I wanted to select a random sample of 4 students fromthis class.I start in the front left corner and toss a coin.

Heads, that student is selected.Tails, he is not selected.

I move on to the next student behind him and use the same rule.I continue in this manner, row by row, until I have 4 students.Is the sample a random sample?Is this a good method?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 9 / 28

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Introduction

Suppose I wanted to select a random sample of 4 students fromthis class.I start in the front left corner and toss a coin.

Heads, that student is selected.Tails, he is not selected.

I move on to the next student behind him and use the same rule.

I continue in this manner, row by row, until I have 4 students.Is the sample a random sample?Is this a good method?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 9 / 28

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Introduction

Suppose I wanted to select a random sample of 4 students fromthis class.I start in the front left corner and toss a coin.

Heads, that student is selected.Tails, he is not selected.

I move on to the next student behind him and use the same rule.I continue in this manner, row by row, until I have 4 students.

Is the sample a random sample?Is this a good method?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 9 / 28

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Introduction

Suppose I wanted to select a random sample of 4 students fromthis class.I start in the front left corner and toss a coin.

Heads, that student is selected.Tails, he is not selected.

I move on to the next student behind him and use the same rule.I continue in this manner, row by row, until I have 4 students.Is the sample a random sample?

Is this a good method?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 9 / 28

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Introduction

Suppose I wanted to select a random sample of 4 students fromthis class.I start in the front left corner and toss a coin.

Heads, that student is selected.Tails, he is not selected.

I move on to the next student behind him and use the same rule.I continue in this manner, row by row, until I have 4 students.Is the sample a random sample?Is this a good method?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 9 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 10 / 28

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Simple Random Sample

Definition (Simple random sample)A simple random sample of size n is a random sample that is selectedin such a way that all samples of size n have the same chance of beingselected.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 11 / 28

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Simple Random Sample

A consequence of this is that all individuals in the population havethe same chance of being selected for the sample.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 12 / 28

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Simple Random Sample

Example (Simple Random Sample)For example, let the population be {Armstrong, Bean, Craycroft,Davis, Freston, Garner}.The possible samples of size 3 are

{A, B, C} {A, C, D} {A, D, G} {B, C, G} {C, D, F}{A, B, D} {A, C, F} {A, F, G} {B, D, F} {C, D, G}{A, B, F} {A, C, G} {B, C, D} {B, D, G} {C, F, G}{A, B, G} {A, D, F} {B, C, F} {B, F, G} {D, F, G}

Choose one of the above samples at random.What is each person’s chance of being in the sample?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 13 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 14 / 28

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Simple Random Sample

For larger populations, the previous method is not practical.For example, if N = 100 and n = 6, then there are 1,192,052,400different possible samples.However, it turns out that if we select individuals one at a time,with all individuals equally likely at each step, then all samples areequally likely.Thus, our sample will be a simple random sample.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 15 / 28

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Selecting a Simple Random Sample

Select a Sample of Size nGiven a population of size N,

Number the members of the population from 1 to N.Use a random number generator (such as on a calculator) togenerate n random integers from 1 to N.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 16 / 28

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Sampling With or Without Replacement

Definition (Sampling with replacement)When we sample with replacement, a selected item may be selectedagain. That is, repetitions are allowed.

Definition (Sampling without replacement)When we sample without replacement, a selected item may not beselected again. That is, repetitions are not allowed.

Sampling may be done with or without replacement.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 17 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 18 / 28

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TI-83: Selecting a Sample

TI-83: Selecting a Sample1 Press MATH.2 Use the arrow keys to highlight the PRB menu title.3 Press 5 to select randInt (item #5).4 Enter randInt(1,100). (E.g., if N = 100.)5 Press ENTER. A random number appears.6 Press ENTER repeatedly for more random numbers.

If the sampling is done without replacement, then repetitionsshould be discarded.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 19 / 28

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Example

Let the population be the students in this class.Then N = 18.Number the members 1 - 18 in alphabetical order.We will choose a sample of size n = 6.What is each individual’s chance of being in the sample?

PracticeUse randInt(1,18) to select 6 students.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 20 / 28

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TI-83: Getting a Set of Random Numbers

To get several random integers at once, possibly with repetitions,use randInt with a third parameter, representing the samplesize.For example, to get 6 random integers from 1 to 18, enterrandInt(1,18,6).However, this may include repetitions.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 21 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 22 / 28

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TI-83: Setting the Seed

TI-83: Setting the Seed1 Enter a seed (choose any number whatsoever).2 Press STO. An arrow appears in the display.3 Press MATH, highlight PRB, select rand (item #1).4 Press ENTER. The seed is now set.

In general practice, this is not done.We do it only to “synchronize” our calculators so that we will all getthe same answer.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 23 / 28

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Practice

PracticeSet the seed to 157 (an arbitrary choice).Then select a random sample of size 6 from the population of thestudents in this class.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 24 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 25 / 28

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Simple Random Sample

Example (Simple Random Sample)Just because a sampling method guarantees that all individuals inthe population have the same chance of being in the sample, itdoes not mean that the sample is a simple random sample.For example, suppose we toss a coin to choose one of thefollowing samples.

{A, B, C} {D, F, G}

What is each person’s chance of being in the sample?What is the probability of getting the sample {A,B,C}?What is the probability of getting the sample {A,B,D}?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 26 / 28

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Simple Random Sample

Example (Simple Random Sample)Just because a sampling method guarantees that all individuals inthe population have the same chance of being in the sample, itdoes not mean that the sample is a simple random sample.For example, suppose we toss a coin to choose one of thefollowing samples.

{A, B, C} {D, F, G}What is each person’s chance of being in the sample?

What is the probability of getting the sample {A,B,C}?What is the probability of getting the sample {A,B,D}?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 26 / 28

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Simple Random Sample

Example (Simple Random Sample)Just because a sampling method guarantees that all individuals inthe population have the same chance of being in the sample, itdoes not mean that the sample is a simple random sample.For example, suppose we toss a coin to choose one of thefollowing samples.

{A, B, C} {D, F, G}What is each person’s chance of being in the sample?What is the probability of getting the sample {A,B,C}?

What is the probability of getting the sample {A,B,D}?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 26 / 28

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Simple Random Sample

Example (Simple Random Sample)Just because a sampling method guarantees that all individuals inthe population have the same chance of being in the sample, itdoes not mean that the sample is a simple random sample.For example, suppose we toss a coin to choose one of thefollowing samples.

{A, B, C} {D, F, G}What is each person’s chance of being in the sample?What is the probability of getting the sample {A,B,C}?What is the probability of getting the sample {A,B,D}?

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 26 / 28

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Outline

1 Introduction

2 Simple Random Samples

3 Selecting Simple Random SamplesOn the TI-83Setting the Seed

4 Non-Simple Random Samples

5 Assignment

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 27 / 28

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Assignment

HomeworkRead Section 2.5, pages 98 - 106.Let’s Do It! 2.4.Page 107, exercises 13, 15 - 18.

Robb T. Koether (Hampden-Sydney College) Simple Random Sampling Mon, Jan 30, 2012 28 / 28