1. Section 7.3 – Simple Random Samples
Special Topics

2. Probability Sampling
The way we use to avoid bias in sampling is to use probability sampling.
Probability Sampling is any sampling method which gives every member of the population the same chance of being selected.

3. Simple Random Sampling
Simple Random Sampling is a probability sampling method.
Definition: A Simple Random Sample (SRS) consists of n individuals from the population chosen in such a way that every set of n individuals has the same chance to be selected.
It can be conducted as easily as drawing name from a hat.
It is a better sampling technique than Convenience or Voluntary Response because it doesn’t favor any part of the population.

4. Conducting a Simple Random Sample
Step 1: Label. Give each member of the population a numerical label of the same length. Up to 10 items can be labeled with single digits (0-9). Up to 100 items can be labeled with two digits (00-99). Up to 1000 items can be labeled with three digits ( ).
Step 2. Table (or technology). Use a Random Digit Table to make selections for your sample.

5. Random Digit Table
A Table of Random Digits is a list of the digits from 0-9, with these two properties:
Each entry in the table is equally likely to be any of the 10 digits from 0 to 9.
The entries are independent of each other.
Independent means knowing that something has happened doesn’t give you any clue as to what might happen next.
In the random digit table, if you read 0000, that doesn’t tell you if the next number will be a zero or not. This is an example of independence.

6. Random Digit Table
Each line in the random digit table starts with 3 digits. Those three digits are Line Numbers and are not part of the line they label. Do not use them to pick your sample.
Skip any number which has already been chosen.
Continue until you have reached your sample size.

7. SRS Activity
Use the list of students provided and a random digit table to select a sample of size n = 7.

8. Justification for Using an SRS
Simple random sampling can produce a sample which represents the population well.
A sample which represents the population well, helps to avoid bias, and gives trustworthy results.

9. *Note: There is always error in sampling.
Sampling errors cannot be avoided.
Three categories of sampling errors:
Random Sampling Error – chance variation.
Sampling Method Error – error that occurs because of the choice of a sampling method.
Non-sampling Error – error occurs in the responses by individuals in the sample.

10. Homework
Worksheet