## INTRODUCTION AND DATA COLLECTION

a. Why a manager needs to know about statistics

b. The growth and development of modern statistics

c. Statistical thinking and modern statistics

d. Descriptive versus inferential statistics

e. The need for data

f. Data source

g. Types of data and measurement scales

a. Why a manager needs to know about statistics

Managers need to know :

How to properly present and describe information

How to draw conclusion about large population based on information from sample

How to improve processes

How to obtain reliable forecasts of variable of interest.

b. The growth and development of modern statistics

It can be traced to three separate phenomena :

The needs of the Government to collect data on its citizenry

The development of the mathematics of probability theory

The advent of the computer

Profoundly changed in the last 30 years

c. Statistical thinking and modern statistics

Statistical thinking can be defined as thought processes

that focus on ways to understand, manage, and reduce

variation

d. Descriptive versus inferential statistics

Descriptive statistics can be defined as those methods involving the collection, presentation, and characterization of a set of data in order to describe the various features of that set of data properly.

Inferential statistics can be defined as those methods that make possible the estimation of the characteristic of a population or the making of a decision concerning a population based on sample results.

A population is the totality of items or things under consideration

A sample is the portion of the population that is selected for analysis

A parameter is a summary measure that is computed to describe a characteristic of an entire population

A statistic is a summary measure that is computed to describe a characteristic from only a sample of the population

e. The need for data

Data are needed to :

Provide the necessary input to a survey

Measure performance in an ongoing service or Production processes

Assist in formulating alternative courses of action in a decision-making process

Satisfy our curiosity

f. Data source

The data collector is the primary source

The data compiler is the secondary source

Four main reasons for collecting data :

to provide input to a research study

To measure performance

To enhance decision making

To satisfy our curiosity

g. Type of data and Measurement scales

Types of data

Two types of characteristics of random variable :

Categorical random variables yield categorical responses

Numerical random variables yield numerical responses

Types of measurement scales :

Nominal scale

Ordinal scale

Interval scale

Ratio scale

The need for operational definitions

An operational definition provides a meaning to a concept or variable that can be communicated to other individuals.

It is something that has the same meaning yesterday, today and tomorrow to all individuals

Types of samples

Non-probability sample and probability sample

Non-probability sample such as judgment sample, quota sampling and chunk sampling.

A probability sample is one in which the subjects of the sample

are chosen on the basis of known probabilities.

Simple random sample

Systematic sample

Stratified sample

Cluster sample

There are four types of survey error :

Coverage error or specification bias

Non-response error

Sampling error

Measurement error

A man with one watch always knows what time it is

A man with 2 watches always searches to identify the correct one

A man with 10 watches is always reminded of the difficulty in measuring time

**Baca Juga :**