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Sampling Methods Sampling Methods

Sampling Methods - PowerPoint Presentation

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Uploaded On 2016-02-29

Sampling Methods - PPT Presentation

and Cautions What is Random Random Drawing from a hat Rolling a die Using a number generator Not Random Picking randomly First one toraise their hand do a task etc Why Random ID: 235526

bias random selection types random bias types selection number selected randomly sample generator population response person sampling strata interest

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Presentation Transcript

Slide1

Sampling Methodsand CautionsSlide2

What is Random?

Random:

Drawing from a hat

Rolling a die

Using a number generator

Not Random:

“Picking” randomly

First one to…(raise their hand, do a task, etc.)Slide3

Why Random?

Everyone has an equal chance of being selected

Helps to reduce bias by eliminating the human factor of selection

Helps to account for the variability between people (even when we don’t know it’s there)Slide4

Types of Random Selection

Simple Random Sample: Everyone gets a number and is selected via a random number generatorSlide5

Types of Random Selection

Stratified Random Sample: The population is broken up into strata (Male/Female, Freshmen/Sophomore/Junior/Senior) and a certain number of people are randomly selected from each strata.Slide6

Types of Random Selection

Systematic Random Sample: A random number generator is selected to pick a person from 1-X. Each

X

th

person is then selected after that.

For example, a die is used to select a number 1-6. Let’s say it comes up a 2. The second person would be selected for the experiment, and then the 8

th

, and then the 14

th

, continuing by 6.Slide7

Types of Random Selection

Cluster Sampling: Choosing random clusters of subjects.

Pickings pairs of Husband/Wife, Father/

Dauther

, entire families, neighborhoods, etc.Slide8

Types of Random Selection

Convenience Sampling: “randomly,” or randomly choosing those conveniently close to survey.

Surveyors at the mall, how we’ve surveyed so far (in the classroom), asking friends or neighborsSlide9

Population of Interest

We always want to ask ourselves: Who is this generalizing to?

If we take the heights of our class, are we trying to generalize to AP Stats students? To Juniors and Seniors at HSHS? To the school? To the county, the state, the country…? What is the population of interest?Slide10

BiasBias is bad, yet unavoidable. We seek to reduce bias.Slide11

Types of Bias

Selection Bias: When the researcher actively creates a bias in the way they select their subjects.

Undercoverage

Non-randomSlide12

Types of Bias

Response Bias

Non-response

Voluntary ResponseSlide13

Types of Bias

Anything else that might throw off the data

Using a placebo unnecessarily

Not using a placebo when one should

Not utilizing blind or double-blind methods when appropriate

Etc.Slide14

Random Digit Table