1. Simple Random Sampling
Lecture 7
Section 2.5
Mon, Jan 28, 2008

2. Simple Random Sample
Simple Random Sample of size n.

3. Simple Random Sample
A consequence of this is that all individuals in the population have the same chance of being selected for the sample.

4. Simple Random Sample
However, just because a sampling method guarantees that all individuals in the population have the same chance of being in the sample, it does not mean that the sample is a simple random sample.

5. Selecting a Simple Random Sample
Given a population of size N,
Number the members from 1 to N.
Use a random number generator (such as on a calculator) to generate n random integers from 1 to N.

6. Selecting a Simple Random Sample
The sampling may be done with or without replacement.
If the sampling is done without replacement, then repetitions should be discarded.

7. TI-83 – Selecting a Sample
Suppose that the population size is N = 100.
Press MATH.
Use arrow keys to highlight PRB menu.
Press 5 to select randInt (item #5).
Enter randInt(1, 100) and press ENTER.
A random number appears.
Press ENTER repeatedly for more random numbers.

8. Example
Let the population be the students in this class, numbered 1 – 7 in alphabetical order.
So N = 7.
Choose a random sample of size n = 3.
What is each person’s chance of being selected for the sample?

9. Getting a Set of Random Numbers
To get several random integers at once, possibly with repetitions, use randInt with a third parameter.
For example, to get 3 random integers from 1 to 7, enter
randInt(1, 7, 3)

10. TI-83 – Setting the Seed Enter the desired seed, say, 48. Press STO.
Press MATH, highlight PRB, select rand (item #1).
Press ENTER. The seed is set to 48.

11. Example
Set the seed to 48.
Then select a random sample of size 3 from the population of the previous example.

12.
The web site will provide truly random numbers!
The numbers are integers ranging over any specified interval.
They can be generated with repetitions or without repetitions.
You can also do random coin flips.