Engineering reasearch methodology
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Transcript of 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