Lesson 1-Lesson 1-11

Statistics

for Management

Lesson 1

Introduction

and Data Collection

Lesson. 1- 2

Lesson Topics

•Statistical Thinking and Management

•Descriptive versus Inferential Statistics

•Types of Data and their Sources

•Types of Sampling Methods

•Survay methods

•Types of Survey Errors

Lesson. 1- 3

1. Statistical Thinking and Management

Three Aspects of Quality Improvement

Management Philosophy

Behavioral Tools

Statistical Methods

Lesson. 1- 4

2. Statistical Methods

•Descriptive Statistics

•Inferential Statistics

Collecting and describing data.

Making decisions based on sample data.

Lesson. 1- 5

Descriptive Statistics

•Collect Data e.g. Survey

•Present Data e.g. Tables and Graphs

•Characterize Data e.g. Mean

nx i

A Characteristic of a: Population is a Parameter

Sample is a Statistic.

Lesson. 1- 6

Inferential Statistics

•Estimation•Hypothesis

Testing

Making decisions concerning a population based on sample results.

Lesson. 1- 7

3. Types of Data

Categorical

Discrete Continuous

Numerical

Data

Lesson. 1- 8

3. Data Sources

PrimaryData Collection

SecondaryData Compilation

Observation

Experimentation

Survey

Print or Electronic

Lesson. 1- 9

Quota

4.Types of Sampling Methods

Samples

Non-Probability Samples

Judgement Chunk

Probability Samples

Simple Random

Systematic

Stratified

Cluster

Lesson. 1- 10

Probability Samples

Probability Samples

Simple Random

Systematic Stratified Cluster

Subjects of the sample are chosen based on known probabilities.

Lesson. 1- 11

Simple Random Samples•Every individual or item from the

target frame has an equal chance of

being selected.

•Selection may be with replacement or

without replacement.

• One may use table of random numbers

for obtaining samples.

Lesson. 1- 12

Systematic Samples• Decide on sample size: n

• Divide population of N individuals into groups of k individuals: k = N/n

• Randomly select one individual from the 1st group.

• Select every k-th individual thereafter.

N = 64

n = 8

k = 8

First Group

Lesson. 1- 13

Stratified Samples• Population divided into 2 or more groups according to some common characteristic.

• Simple random sample selected from each.• The two or more samples are combined into one.

Lesson. 1- 14

Cluster Samples• Population divided into several “clusters”,

each representative of the population. • Simple random sample selected from each.• The samples are combined into one.

Population divided into 4 clusters.

Lesson. 1- 15

5. Survey methods

• Interview (Anket, Face to face, Telephon, Letter)

• Observation

• Experimentation

• Data compilation

Lesson. 1- 16

6. Types of Survey Errors

•Coverage Error

•Non Response Error

•Sampling Error

•Measurement Error

Excluded from selection.

Follow up on non responses.

Chance differences from sample to sample.

Bad Question!

Lesson. 1- 17

Lesson Summary•Described the use of Statistical Thinking to improve

quality.

•Addressed the notion of Descriptive versus Inferential

Statistics.

•Defined and described different Types of Data and

Sources

•Listed Types of Sampling Methods.

•Described different Types of Survey Errors.