Engineering reasearch methodology

7/26/2019 Engineering reasearch methodology

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UNIT-IV

DATA COLLECTION

K NAVEEN KUMA

1005-15-74531


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What is DATA?

Facts and statisticscollected together forreference or analysis

Statistics is the studyof the collection,analysis,interpretation,

presentation, andorganization of data


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Why a Manager Needs to Know About

Statistics

To Know How to Properly Present Information

To Know How to Draw Conclusions about

Populations Based on Sample Information

To Know How to Improve Processes

To Know How to Obtain Reliable Forecasts


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Why We Need Data

To Provide Input to SurveyTo Provide Input to Study

To Measure Performance of Ongoing Service

or Production ProcessTo Evaluate Conformance to Standards

To Assist in Formulating Alternative Courses

of ActionTo Satisfy Curiosity


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Exploring the Data

The task of data collection begins after a research

problem has been defined.

The researcher has to decide which type of data and

the data collection methods


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Source of Data:

The Researcher should keep in mind two types of data:

1. Primary

2. Secondary

The Primary Data : Those which are collected as afresh and for the first time, and thus happen to beoriginal in character.

The secondary data : Those which have already beencollected by someone else and which have already been

passed through the statistical process.

The distinction between Primary and Secondary data

can be made more clear on the basis of documents:1. Primary data :Documented as record

2. Secondary data :Documented as report


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COLLECTION OF PRIMARY DATA

Primariy Data obtained by Experiments,Perform surveys(If it is Descriptive type of Research)

Methods of collecting primary data

(i)Observation method,

(ii)Interview method,

(iii)Through questionnaires,

(iv)Through schedules, and

Other methods


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Other Methods:(a)Warranty cards;

(b)Distributor audits;

(c)Pantry audits;(d)Consumer panels;

(e)Using mechanical devices;

(f)Through projective techniques;

(g)Depth interviews, and

(h)Content analysis.


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Observation Method

Components of Observation: Observation involvesThree Processes:

1. Sensation: It is gained through the sense of organs

which depends upon the physical alertness of the

observer. It is reports the facts as observed.2. Attention : Which is largely a matter of habit.

3. Perception:Which involves the interpretation of

sensory reports.It enables the mind to recognize the facts.


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Interview Method

It is oral-verbal questions and correspondingoral verbal response to the queries made.

Personal interviews

Direct personal investigation Indirect oral examination

Telephone interviews


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THROUGH QUESTIONNAIRES

Rating scale


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SOME OTHER METHODS

1. Warranty cards: Warranty cards are usually postal sized cards

which are used by dealers of consumer durables to collect

information regarding their products. The consumer to fill in the

card and post it back to the dealer.

2. Distributor or store audits: Performed by distributors as well as

manufactures through their salesmen at regular intervals. To

estimate market size, market share, seasonal purchasing pattern

and so on. The data are obtained in such audits not by

questioning but by observation.

3. Pantry audit technique: It is used to estimate consumption of thebasket of goods at the consumer level. It is to find out what types

of consumers buy certain products and certain brands, the

assumption being that the contents of the pantry accurately

portray consumers preferences.


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4.Consumer panel:An extension of the pantry audit approach on

a regular basis is known as consumer panel , where a set of

consumers are arranged to come to an understanding to maintain

detailed daily records of their consumption and the same is made

available to investigator on demands.

5.Use of mechanical devices : The use of mechanical devices hasbeen widely made to collect information by way of indirect

means. Eye camera, Pupilometric camera, Psychogalvanometer,

Motion picture camera and Audiometer are the principal devices

so far developed and commonlyused by modern big businesshouses, mostly in the developed world for the purpose of

collecting the required information.


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5.Projective techniques: Projective techniques (or what are

sometimes called as indirect interviewing techniques) for the

collection of data, it play an important role in motivational

researches or in attitude surveys.

6.Depth interviews : Depth interviews are held to explore needs,

desires and feelings of respondents Unless the researcher hasspecialized training, depth interviewing should not be attempted

7.Content-analysis : Content-analysis consists of analysing the

contents of documentary materials such as books, magazines,

newspapers and the contents of all other verbal materials.


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COLLECTION OF SECONDARY DATA

Usually published data are available in:

a. Various publications of the central, state are local

governments;

b. Various publications of foreign governments or of

international bodies and their subsidiary organizations;

c. Technical and trade journals;

d. Books, magazines and newspapers;

e. Reports and publications of various associations connected

with business and industry, banks, stock exchanges, etc.;f. Reports prepared by research scholars, Universities,

Economists, etc. In different fields;

g. Public records and statistics, historical documents, and other

sources of published information.


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The sources of unpublished data

Diaries, letters, unpublished biographies and

autobiographies and also may be available with

scholars and research workers

Considerations

1. Reliability of data

2. Suitability of data

3. Adequacy of data


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Description Operations

Field Editing How long have you at your current

address? Ans:48 years

What is your age? Ans:32What is the mistke in above data?

Central editing:It should take place when all

forms or schedules have been completed andreturned to the office.


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Coding:

Coding refers to the process of assigning numerals or othersymbols to answers so that responses can be put into a limited

number of categories or classes.

Coding is necessary for efficient analysis and through it the

several replies may be reduced to a small number of classeswhich contain the critical information required for analysis.


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Classification:

Most research studies result in a large volume of raw data which

must be reduced into homogeneous groups if we are to getmeaningful relationships.

1. Classification according to attributes: Data are classified on

the basis of common characteristics which can either bedescriptive (such as literacy, sex, honesty, etc.) or numerical

(such as weight, height, income, etc.).

2. Classification according to class-intervals : The numericalcharacteristics refer to quantitative phenomenon which can be

measured through some statistical units. Data relating to income,

production, age, weight, etc.


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Tabulation: When a mass of data has been assembled, it

becomes necessary for the researcher to arrange the same insome kind of concise and logical order. This procedure isreferred to as tabulation.

Tabulation is essential because of the following reasons:

1. It conserves space and reduces explanatory and descriptivestatement to a minimum.

2. It facilitates the process of comparison.3. It facilitates the summation of items and the detection of errors

and omissions.

4. It provides a basis for various statistical computations.


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Sample Design

The following are to considered for a sample design:

i. Nature of universe: Universe may be either homogenous or heterogenous in nature.

If the items of the universe are homogenous, a small sample can serve the purpose.

But if the items are heteogenous, a large sample would be required. Technically,

this can be termed as the dispersion factor.

ii. Number of classes proposed:If many class-groups (groups and sub-groups) are to

be formed, a large sample would be required because a small sample might not be

able to give a reasonable number of items in each class-group.

iii. Nature of study: If items are to be intensively and continuously studied, the sample

should be small. For a general survey the size of the sample should be large, but a

small sample is considered appropriate in technical surveys.iv. Type of sampling: Sampling technique plays an important part in determining the

size of the sample. A small random sample is apt to be much superior to a larger but

badly selected sample.


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v. Standard of accuracy and acceptable confidence level:If the standard of

accuracy or the level of precision is to be kept high, we shall requirerelatively larger sample. For doubling the accuracy for a fixed significance

level, the sample size has to be increased fourfold.

vi. Availability of finance: In practice, size of the sample depends upon the

amount of money available for the study purposes. This factor should be

kept in view while determining the size of sample for large samples result

in increasing the cost of sampling estimates.

vii.Other considerations: Nature of units, size of the population, size of

questionnaire, availability of trained investigators, the conditions under

which the sample is being conducted, the time available for completion of

the study are a few other considerations to which a researcher must pay

attention while selecting the size of the sample.


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Role of Statistics for Data Analysis


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The important statistical measures that areused to summarise the survey/research data

are:

1.Measures of central tendency or statisticalaverages

2.Measures of dispersion

3.Measures of asymmetry (skewness)4.Measures of relationship


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A Population (Universe) is the whole collection of things

under consideration

A Sampleis a Portion of the population selected for analysis

A Parameteris a Summary measure computed to describe thecharacteristic of a population

A Statistic is a Summary measure computed to describe the

characteristic of a sample


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Population and Sample

Population Sample

Use parameters tosummarize features

Use statistics to

summarize features

Inference on the population from the sample


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Types of Data

Categorical

(Qualitative)

Discrete Continuous

Numerical

(Quantitative)

Data


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IMPORTANT STATISTICAL MEASURES

Measures of Central Tendency(Statistical averages)

Mean, Median, Mode, Geometric Mean, Harmonic Mean

Quartiles

Measure of Variation

Range, Semi Inter-quartile Range, Mean Deviation, Variance,Standard Deviation and Coefficient of Variation

Measures of Skewness / Shape (Measure Asymmetry)

Symmetric, Skewed

Measures of Kurtosis/Peakedness Lepto kurtic / Platy Kurtic / Meso kurtic


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Summary Measures

Summary Measures

Central Tendency

MeanMedian

Mode

Quartile

Geometric Mean

Variation

Variance

Standard Deviation

Coefficient

of VariationRange

Documents

Engineering reasearch methodology