BUS304 – Data Collection 1

Chapter 1 Data Collection

Descriptive Statistics

Tools that collect, present and describe data

Collecting Data

Collecting Data

Characterizing Data

Characterizing Data

Presenting Data

Presenting Data

survey

observation

experiments

etc

Mathematical

description of data: e.g.

average housing price;

stock price volativity.

BUS304 – Data Collection 2

Population and Samples

A statistic research always starts with a question: What is the average starting

salary for a business major?

How is the housing price in San Diego area?

Are the college textbooks too expensive?

Who is a more valuable player? Reggie Bush or Vince Young?

What else?

Population:

-- All the items that are of interest

Sample:

-- A subset of the population

(or say, part of the population)

a b c d

ef gh i jk l m n

o p q rs t u v w

x y z

PopulationSample

b c

g i n

o r u

y

How to determine? -- Check whether it covers all the items of interest

Exercise: Determine the population for each question on the leftHow to determine? -- Check whether it covers all the items of interest

Exercise: Determine the population for each question on the left

BUS304 – Data Collection 3

Sampling:

Techniques to select only part of the population to conduct the

study

The result will be less reliable than that from studying the

population

But sometimes it is more reasonable to use sample than use

population

Less time consuming

Less costs

Sometimes, study is destructive. e.g. matches

Think of some examples of sampling.

BUS304 – Data Collection 4

Sampling Techniques

Non-Statistical Sampling

Samples are selected at

convenience

Results will be subject to

bias

Examples:

• Ask a friend, a neighbor, etc.

• A survey on the Internet;

• Judges.

Statistical Sampling

Use probability theory to

guide the selection

Sampling bias can be

estimated (we will learn how

to estimate later the

semester)

We will learn four

techniques in this category.

BUS304 – Data Collection 5

Four Statistical Sampling Techniques

Simple random Sampling The most basic statistical sampling

method. Select at random Dice, Card, Random number

generator (calculator, Excel)

Exercise: Use random number generator in

Excel to select a sample of ten NBA players and find out the average heights.

Simple Random

Systematic

Stratified

Cluster

BUS304 – Data Collection 6

Four Statistical Sampling Techniques

Systematic Sampling A simplified version of simple random

sampling

Select a random start, and then go by equal space

Question: how to determine the interval so that everyone has a chance to be selected?

Formula:

Interval = Population size / sample size

Simple Random

Systematic

Stratified

Cluster

BUS304 – Data Collection 7

Systematic sampling exercise

Use systematic sampling technique to select 10 NBA players

and find out the average height.

Think? How many random numbers you need to generate?

BUS304 – Data Collection 8

Four Statistical Sampling Techniques

Stratified Sampling Divide the population into subgroups

Use simple random sampling method (or systematic sampling) to select from each group

Combine to form one big sample

Think: what is the benefit of using stratified sampling?

• More representative

Simple Random

Systematic

Stratified

Cluster

BUS304 – Data Collection 9

Stratified sampling exercise

Use stratified sampling technique to select a sample of 10 NBA

players, including 2PFs, 2SFs, 2SGs, 2PGs, and 2Cs.

Find out the average weight.

BUS304 – Data Collection 10

Four Statistical Sampling Techniques

Cluster Sampling Divide the population into subgroups

-- called “clusters”.

Randomly select some subgroups (not

all!)

In each selected subgroup, use random

sampling technique to select sub-

samples

Combine the sub-samples to form one

aggregate sample

Think: when we use cluster sampling?

(e.g. market research, select towns first)

Simple Random

Systematic

Stratified

Cluster

BUS304 – Data Collection 11

Clustered Sampling Technique

Use each NBA team as a cluster

Randomly select 5 teams to conduct the study

In each of the selected teams, select 2 players

Combine them into an aggregate sample of ten.

Think, how many times do you need to use the Random

Number Generator?

Discuss the difference between cluster sampling technique and

stratified sampling technique.

BUS304 – Data Collection 12

Compare different techniques Simple random sampling and systematic sampling:

Need to know the population size

Doesn’t care about the composition of the population

Stratified sampling: Use the information about the population composition to control sample

The sample can be more representative to the population

Cluster sampling: Generally used when you have a geographically distributed population

Divide the population into several geographical areas

Randomly select some areas (not all) to study – cost saving.

Sometimes, a combination of techniques can be used.

BUS304 – Data Collection 13

Discussion Which sampling techniques should be used for (or are used in)

the following studies? – discuss the potential bias of the

techniques.

1. NBC wants to conduct an opinion poll to understand people’s opinion

on Hillary Clinton’s chance of being selected as president in 2008.

2. CSUSM wants to collect opinions about how the junior faculty

members teach their classes

3. Policemen want to detect drunk drivers to prevent potential accidents.

4. Oscar judges determine the best pictures of the year.

5. Fans vote for the NBA all-star team.

6. American Citizens vote for president.

BUS304 – Data Collection 14

Summary

In today’s lecture:

Two important concepts: Population and Sample

Four Sampling Techniques:

• Simple Random Sampling

• Systematic Sampling

• Stratified Sampling

• Cluster Sampling