1. GREAT Day!!!

2. Sampling
Population – Entire group of individuals or objects that we want information about. Defined in terms of what we want to know.
Sample – The part of the population that we actually use to gather information and draw
Census – data from every individual in a population
Bias – a systematic slant toward one outcome over another. Overestimates or underestimates the value you want to know

3. The Idea of a Sample Survey
Population
Sample
Collect data from a representative sample
Make an inference about the population.
We often draw conclusions about a whole population on the basis of a sample. Choosing a sample from a large, varied population is not that easy.

4. Planning a Sample Survey
The Idea of a Sample Survey
A sample survey is a study that collects data from a sample that is chosen to represent a specific population.
Planning a Sample Survey
Decide what population we want to describe.
Decide what we want to measure.
Decide how to choose a sample from the population.

5. Good Sampling Designs SRS Stratified Random Sample
– simple random sample
Every individual unit or set of units has an equal chance of being selected
A sample chosen by chance rules out both favoritism by the sampler and self-selection by respondents. .
Stratified Random Sample
– First divides population into similar groups called strata.
Then does a simple random sample in each stratum.
Then combines to form a full sample.
- When strata are “similar within but different between,” these samples
give more precise estimates of unknown population values than do
simple random samples.

6. How to Choose an SRS How to Choose an SRS with Technology
Label. Give each individual in the population a distinct numerical label from 1 to N, where N is the number of individuals in the population.
Randomize. Use a random number generator to obtain n different integers from 1 to N, where n is the sample size.
Select. Choose the individuals that correspond to the randomly selected integers.
How to Choose an SRS with Table D
Label. Give each member of the population a distinct numerical label with the same number of digits. Use as few digits as possible.
Randomize. Read consecutive groups of digits of the appropriate length from left to right across a line in Table D. Ignore any group of digits that wasn’t used as a label or that duplicates a label already in the sample. Stop when you have chosen n different labels.
Select. Choose the individuals that correspond to the randomly selected integers.

7. How to Choose an SRS
Use line 130 of Table D to choose an SRS of 4 hotels.
01 Aloha Kai 08 Captiva 15 Palm Tree 22 Sea Shell
02 Anchor Down 09 Casa del Mar 16 Radisson 23 Silver Beach
03 Banana Bay 10 Coconuts 17 Ramada 24 Sunset Beach
04 Banyan Tree 11 Diplomat 18 Sandpiper 25 Tradewinds
05 Beach Castle 12 Holiday Inn 19 Sea Castle 26 Tropical Breeze
06 Best Western 13 Lime Tree 20 Sea Club 27 Tropical Shores
07 Cabana 14 Outrigger 21 Sea Grape 28 Veranda

8. Multistage Sampling
– When you take an SRS of a large category, then take another SRS from a smaller category within those chosen from the larger category and so on and so on.
Example:
Pick counties by SRS
Then pick city by SRS
Then pick townships by SRS .
Then pick block by SRS

9. Systematic Sampling -
In this type of sampling the Population is divided up into equal
size groups then an SRS is done in the first group and then
the subjects are selected systematically from each of the other
groups.
Divide sample by the number of units you want, this makes equal groups
Number each unit in the sub groups consecutively
Randomly pick one from the first sub group
Add the total number in each group to the randomly picked number in each sub group to pick the next number.
Do example in class

10. Cluster Sampling
When populations are large and spread out over a wide area, we’d prefer a method that selects groups (clusters) of individuals that are “near” one another. That’s the idea of cluster sampling.
– selects a sample by randomly choosing Clusters and including each
member of the selected cluster In the sample.
a cluster is a group of individuals in the population that
are located near each other.
Each cluster should mirror the population
Used for practical reasons like to save time and money.

11. Poor Sampling Designs Convenience Sampling
- Chooses the people that are easiest to reach.
Often these subjects are likely to give a response you are hoping for
Ex. Study habits of students – you survey student in the library
Voluntary Response Sampling –
- allows people to choose to be in the sample by responding to a general invitation.
- Ex. Phone in responses to radio, T.V. or newspaper articles
-Generally these people are not representative of the larger population

12. Problems with Sampling
Undercoverage
– When certain groups in a population are left out of the process of choosing a sample.
- Ex. Telephone poll of Dewey vs. Truman
Homeless people, prisoners, people in hospitals
Non-Response
– when an individual chosen for a survey cannot be contacted or refuses to participate.
Wording of Question
– poor wording can elicit certain responses.

13. Problems with Sampling
Response Bias
- Occurs when there is a systematic pattern of inaccurate answers to a survey question
When the person being surveyed lies. There may be a number of reasons:
Sensitive topic or about illegal behavior
Question about prejudice when asked by a minority interviewer
Make joke of survey

14. Homework: p
# 1, 3, 11, 13, 15,17, 19, 21, 22, 23