Data collection & data presentation

DATA COLLECTION &

DATA PRESENTATION

Ms. Nurazrin Jupri

Sources of Data

• Primary data

• Specific information collected by the person

who is doing the research

• Secondary data

• Any material that has been collected from

published records

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Types of Data and Variables

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Data/

Variables

Quantitative

(Numerical)

Discrete

Qualitative

(Categorical)

Continuous

Examples:

• Colour

• Flavour

• Gender

(Defined categories)

Examples:

• Profits

• Weight

• Speed

(Measured characteristics)

Examples:

• Number of cars

• Defects per hour

• Accidents

(Counted items)

Scale of Data Measurement

• Data can be divided into numerical and categorical data.

• Numerical data contains numbers that we can manipulate

using ordinary arithmetical operations.

• Categorical data can be sorted into categories.

• Data is classified as nominal, ordinal, interval or ratio.

Ms. Nurazrin Jupri

Sampling

is the process of selecting a small number of

elements from a larger defined target group

(Population) of elements such that the information

gathered from the small group will allow judgments

to be made about the larger groups.

Ms. Nurazrin Jupri

Sampling

is the act, process, or technique of selecting a

suitable sample, or a representative part of a

population for the purpose of determining

parameters or characteristics of the whole

population

Ms. Nurazrin Jupri

Purpose Of Sampling

To draw conclusions about populations from samples,

which enables us to determine a population`s

characteristics by directly observing only a portion (or

sample) of the population.

We obtain a sample rather than a complete enumeration (a

census ) of the population for many reasons.

Ms. Nurazrin Jupri

Main Reasons for Sampling

● Economy

● Timeliness

● The large size of many populations

● Inaccessibility of some of the population

● Accuracy

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●Economy - taking a sample requires fewer resources than a census.

●Time factor -a sample may provide you with needed information quickly.

●The very large populations -many populations about which inferences must

be made are quite large

●The partly accessible populations- There are some populations that are

so difficult to get access to that only a sample can be used.

●Accuracy and sampling- A sample may be more accurate than a census. A

sloppily conducted census can provide less reliable information than a carefully obtained

sample.

Ms. Nurazrin Jupri

Important terminologies

●. Population

●. Element

●. Sample

●. Sampling Unit

●. Subject

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Population

The population refers to the entire group of people,

events or things of interest that the researcher wishes

to investigate.

Example: ● If an organizational consultant is interested in studying the effects of

a four-day work week on the white-coller workers in a telephone

company in Ireland. Then all white-coller workers in that company will

make up the population.

● If regulators wants to know how patients in nursing homes run by a

company in France?

● If however, the regulators are interested only in one particular nursing

home run by that company ?

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Population: All the patients in all the nursing

homes run by them.

then only the patients in that particular

nursing home will make the population.

Element

An element is the

single member of the population.

Example:

●If 1000 blue-coller workers in a particular organization are working and

an researcher is interested to know the satisfaction level of these

workers then each member (blue-coller) of the particular organization

will be considered as element.

●Census is a count of all elements in the human population.

Ms. Nurazrin Jupri

Sample

A sample is a subset of the population. It comprises some

members from it.

Example:

●. If 200 members are drawn/selected from a population of 1000 blue-coller workers to

study the desire outcome, then 200 members form the sample for the study.

●. If there are 145 patients in a hospital and 40 of them are to be surveyed by the hospital

administrator to assess there level of satisfaction with the treatment received. Number

of sample?

●A sample is thus a subgroup or subset of the population. By studying the sample, the

researcher should be able to draw conclusions that are generalizable to the population of

interest.

Ms. Nurazrin Jupri

40 members will be called the sample

Sampling Unit

The sample unit is the element or the set of elements

that is available for selection in some stage of the

sampling process.

Example of sampling units in a multi stage sample are city blocks,

house hold, and individuals with in the households.

Ms. Nurazrin Jupri

Subject

A subject is a single member of the sample just as

an element is a single member of the population.

Example:

●. If 200 members from the total population of 1000 blue-coller workers form the

sample for the study. Then each blue-coller worker in the sample is a subject.

●. If there are 145 patients in a hospital and 40 of them are to be surveyed by

the hospital administrator to assess there level of satisfaction with the

treatment received, then each member from sample of 40 will be called the

subject.

Ms. Nurazrin Jupri

Representative of Sampling

● Choosing the right sample cannot be overemphasized.

● If we choose the sample in a scientific way, we can be reasonably

sure that sample statistics (Mean, Standard Deviation, (S) Variation in the sample ) and

population parameters (Mean (u), Standard Deviation, Variation in the sample ) are close to

each others.

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What is a Good Sample?

● Accurate: absence of bias

● Precise estimate: sampling error

Sampling error is any type of bias that is attributable to mistakes in either drawing a sample or determining the sample size.

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Sampling Process

Define the Population

Determine the Sampling Frame

Select Sampling Technique(s)

Determine the Sample Size

Execute the Sampling Process

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Defining Population of Interest

Population of interest is entirely dependent on

Management Problem, Research Problems, and

Research Design.

Some Bases for Defining Population:

● Geographic Area (Pakistan, Punjab, Banking sector, Our Institute etc.)

● Demographics (Gender, Age, Color, Height etc.)

● Usage/Lifestyle

● Awareness

Ms. Nurazrin Jupri

Sampling Frame

A list of population elements (people, companies, houses,

cities, etc.) from which units to be sampled can be selected.

●Difficult to get an accurate list.

●Sample frame error occurs when certain elements of the

population are accidentally omitted or not included on the

list.

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Sampling Methods/Techniques

Probability

Sampling

Nonprobability

Sampling

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Sampling Methods/Techniques/Types

Sampling Techniques

Nonprobability

Sampling Techniques

Probability

Sampling Techniques

Convenience

Sampling

Judgmental

Sampling

Quota

Sampling

Snowball

Sampling

Systematic

Sampling

Stratified

Sampling

Cluster

Sampling

Other

Sampling

Techniques

Simple

Random

Sampling

Ms. Nurazrin Jupri

Probability Sampling Designs

A probability sample is one that gives every member of the population a known chance of being selected.

All are selected randomly.

● Simple random sampling - anyone

● Systematic sampling

● Stratified sampling - different groups (ages)

● Cluster sampling - different areas (cities)

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Nonprobability Sampling

Nonprobability sample is an arbitrary grouping

that limits the use of some statistical tests. It is not

selected randomly.

Classifications of Nonprobability Sampling

● Convenience Sampling

● Judgment Sampling

● Quota Sampling

● Snowball Sampling

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Factors to Consider in Sample Design

Research objectives Degree of accuracy

Resources Time frame

Knowledge of

target population Research scope

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Determining Sample Size

●How many completed questionnaires do we need to have

a representative sample?

●Generally the larger the better, but that takes more time

and money.

●Answer depends on:

●How different or dispersed the population is.

●Desired level of confidence.

●Desired degree of accuracy.

Ms. Nurazrin Jupri

Acknowledgments to Uma Sekaran

Ms. Nurazrin Jupri

Data Collection Methods

How to reach respondents in order to obtain the required

data?

Ms. Nurazrin Jupri

1. Observation

2. Experimentation

3. Simulation

4. Interviewing

5. Panel Method

6. Mail Survey

Example

Data Collection Methods

• Types of Tools

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Observation schedule

Interview guide and schedule

Questionnaires

Checklists

Data sheet

Example

Data Presentation

• An essential step before further statistical analysis is

carried out

• Data are summarized and displayed enabling

researchers, managers and decision-makers to observe

important features of the data and provide insight into the

type of model and analysis that should be used.

Ms. Nurazrin Jupri

Data Presentation

• Frequency table

• Bar chart

• Pie chart

• Histogram

• Frequency curve

• Line graph

• Pictograph

• Stem-and-leaf display

• Box plot

• Ogive

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