Transcript 1.2 Simple Random Sampling

Copyright © 2008 Pearson Education, Inc.
Chapter 1
The Nature of Statistics
Section 1.2
Simple Random Sampling
Slide 1-2
Three Methods for Obtaining Information


Census – obtaining information for the entire population of
interest
This method can be time consuming, costly, impractical , or
even impossible.
Slide 1-3
Three Methods for Obtaining Information


Sampling – obtaining a sample from the population to draw
conclusion about the entire population.
Two sampling procedures:
 Representative sample – should reflect as closely as
possible the relevant characteristics of the population under
consideration.
 Examples of samples that would not be representative of
the population.
 Surveying people regarding political candidates as
they enter or leave an upscale business location
 Surveying the readers of a particular publication to
get information about the population in general
 Polling college students who live in dormitories to
obtain information of interest to all students
Slide 1-4
Three Methods for Obtaining Information

Probability sampling – a random device (tossing a coin,
table of random numbers, number generator) is used to
decide which members of the population will constitute the
sample.
Slide 1-5
Three Methods for Obtaining Information


Experimentation – there are three basic principles of
experimental design.
 Control
 Randomization
 Replication
This method will be introduced throughout the book.
Slide 1-6
Simple Random Sampling
Simple Random Sample
Simple random sampling: A sampling procedure for which
each possible sample of a given size is equally likely to be
the one obtained.
Simple random sample: A sample obtained by simple
random sampling.
There are two types of simple random sampling. One is
simple random sampling with replacement, whereby a member
of the population can be selected more than once; the other is
simple random sampling without replacement, whereby a
member of the population can be selected at most once.
The Inferential techniques considered in this book are intended
for use with Simple Random Sampling.
Slide 1-7
Simple Random Sampling (without replacement)

Oklahoma State Officials: The top five Oklahoma state officials
are: Governor (G), Lieutenant Governor (L), Secretary of State
(S), Attorney General (A), and Treasurer (T)
List 10 possible samples (without replacement) of size three that
can be obtained from the population of five officials.
GLS, GLA, GLT, GSA, GST, GAT, LSA, LST, LAT, SAT
What are the chances of GLS procedure being used?
1/10
What are the chances of GLA procedure being used?
1/10 … This would be true for all the options on the list.
Slide 1-8
Sampling Methods

Random samples – is a sample selected in such a way that every
member of the population has an equal chance of being selected.
i.e., the process of selecting the sample does not favor any
member of the population, either intentionally or inadvertently.

If a sample is not random, then it is said to be biased. Random
Samples are selected using chance methods or random methods.

Obtaining a simple random sample by picking slips of paper out
of a box is usually impractical, especially when the population is
large, and could be a bias sample.
Slide 1-9
Random-Number Tables
Fortunately, we can use several practical procedures
to get simple random samples.
We can now use computers or calculators to
generate random samples.
One common method involves a table of random
numbers – a table of randomly chosen digits, as
illustrated in Table 1.5.
Slide 1-10
Random
numbers
Table 1.5
Slide 1-11
Random-Number Generators
Nowadays, statisticians prefer statistical software
packages or graphing calculators, rather than
random-number tables, to obtain simple random
samples.
The built-in programs for doing so are called
random-number generators.
When using random-number generators, be aware
of whether they provide samples with replacement
or samples without replacement.
Slide 1-12
HOMEWORK – CHAPTER 1.2
Page 17
27, 31, 33, 35, and 41
Slide 1-13