1.
Prepare of list of all the players and number them
1 through 750
2.
Randomly pick a starting place in the random
number table
3.
Select 10 three-digit numbers between 1 and 750

Using a Table of Random
Numbers
Example:
1.
Choose a starting point randomly. Let’s say it’s 3:04pm, so we
choose row 3, column 4
2.
The number is 03759, so the first player is player number 37.
3.
Move in any direction you want. Let’s say to the right. So the
next player is player 447.
4.
The next two column on the right has number > 750. So the
next available column is 18910, so player 189 is selected.

If you do not have a list of the entire population to
begin with, you can use the systematic random
sample
SYSTEMATIC RANDOM SAMPLE
A random starting point is selected, and then
every
𝑘
th member of the population is
selected
Systematic Sample

Example:
Stood’s Grocery Store wants to study the length of
time customers spend in their store. They decide
to select 100 customers over 4 days (25/day),
Mon-Thurs.
Randomly select the days of the week, the times,
and the starting point of the study, then
systematically select the customers and measure
the time each spends in the store
Time
Day
Random
Number
Begin selection process
Measure length of time for selected customer

▪
When the population can be divided into groups
based on some characteristic, use stratified random
sampling
▪
Guarantees that each group, called strata, is
represented in the sample
STRATIFIED RANDOM SAMPLE
A population is divided into subgroups,
called strata, and a sample is randomly
selected from each stratum
Stratified Sample

Example
▪
A study of 50 of the 352 largest US firms’ ad
spending. The objective is to determine whether
firms with high returns on equity spend more on
advertising than firms with low returns on equity
▪
Begin by identifying the strata, then use random
sampling within each group based on relative
frequencies to collect the sample

Cluster sampling is a common type of sampling, used
to reduce the cost of sampling over large geographic
areas
CLUSTER SAMPLING
A population is divided into clusters using
naturally occurring geographic or other
boundaries. Then clusters are randomly selected
and a sample is collected by randomly selecting
from each cluster
Clustered Sampling