235_ch.10 - ppt

DATA PROCESSING

CHAPTER-10

RESEARCH METHODOLOGY

CONCEPTS AND CASES

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CONCEPTS AND CASES

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The data preparation process

DATA EDITING

DATA TABULATION

DATA CLASSIFICATION

DATA CODING

EXPLORATORY DATA ANALYSIS

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CONCEPTS AND CASES

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HIField work validation

Pre-survey In case the form has been translated into another languageThe questionnaire survey has to be done at multiple locations and

if one has outsourced to outside research investigators , thus there might have been discrepancy in conduction or recording

Post-surveyThe qualifying instructions like-“in case answer is ----- please

answer the next set of questions else go to question-------.” were overlooked.

The respondent seems to have used the same response category for all the questions.

The form that is received back is incomplete.The form has been filled in by someone who is not representative

of the population to be studied.The forms are not in proportion to the sampling plan.

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CONCEPTS AND CASES

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HIBenefits of data editing

The data obtained is complete in all respects.

It is accurate in terms of information recorded and

responses sought.

Questionnaires are legible and are correctly deciphered,

especially the open ended questions.

The response format is in the form that was instructed.

The data is structured in a manner that entering the

information will not be a problem.

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CONCEPTS AND CASES

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HIData editing

Field editing: usually done by the field investigators at the end of every field day the investigator(s) who must review the filled forms for any inconsistencies, non-response, illegible responses or incomplete questionnaires.

Centralized in-house editing: usually done at the researcher’s end.

BacktrackingAllocating missing valuesPlug valueDiscarding unsatisfactory responses

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CONCEPTS AND CASES

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HIData coding

The process of identifying and denoting a numeral to the responses given by the respondent is called coding

Field

Record

File

Data matrix

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CONCEPTS AND CASES

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HIData coding

Sample record: Excel sheet for two-wheeler owners

Unit Column 1

occupation Column 2

Vehicle Column 3

Km/day Column 4

Marital status

Column 5

Family size Column 6

1 4 1 20 1 3 2 3 2 25 2 1 3 5 1 25 1 4 4 2 1 15 2 2 5 4 2 20 2 4 6 5 2 35 2 6 7 1 1 40 1 3 8 5 2 20 2 4

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CONCEPTS AND CASES

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Code book formulation

Appropriate to the research objective

Comprehensive

Mutually exclusive

Single variable entry

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CONCEPTS AND CASES

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HIPre-Coding

closed-ended questionsDichotomous questions:Do you eat ready-to-eat food? Yes=1; no=0 (X-1)Ranking questions

Q.NO. Variable name Coding instructions Variable name 1. Balika Badhu Number from 1-10 X 10a 2. Sathiya Number from 1-10 X 10b 3. Sasural Genda Phool Number from 1-10 X 10c 4. Bidai Number from 1-10 X 10d 5. Pathshala Number from 1-10 X 10e 6. Bandini Number from 1-10 X 10f 7. Laptaganj Number from 1-10 X 10g 8. Sajan Ghar Jaaana Hai Number from 1-10 X 10h 9. Tere Liye Number from 1-10 X 10i 10. Uttaran Number from 1-10 X 10j

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CONCEPTS AND CASES

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HIPre-Coding

Closed-ended questionsChecklists/multiple responsesHow many columns will you make for the following

question?Which of the following newspapers do you read (tick all that you read)

Times of India --------------------

Hindustan Times ---------------------

Mail Today ----------------------

Indian Express ---------------------

Deccan Chronicle ---------------------

Asian Age ----------------------

Mint ----------------------.

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CONCEPTS AND CASES

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HIPre-Coding

Closed-ended questionsScaled questions

Col.no. Variable name Coding instructions Variable name 1. Individual shops more A number from 1 to 5

SA = 5, A = 4, N = 3, D = 2, SD = 1

X 1a

2. Well informed - do - X 1b 3. Knows what to buy - do - X 1c 4. More spending money - do - X 1d 5. More shopping options - do - X 1e

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CONCEPTS AND CASES

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HISample code book extract

Question No. Variable Name Coding Instruction

Symbol used for variable

name

1. Buy ready to eat food products Yes = 1 No = 0

X1

2. Use ready to eat food products Yes = 1 No = 0

X2

22. Age

Less than 20 yrs = 1, 21 to 26 years = 2, 27 to 35 years = 3, 36 to 45 years = 4,

More than 45 years = 5

X22

23. Gender Male = 1

Female = 2 X23

24. Marital status Single = 1

Married = 2 Divorced/widow = 3

X24

25. No. of children Exact no. to be written X25

26. Family size One to two = 1,

Three to five = 2, Six & more = 3

X26

27. Monthly household income

Rs.20000 to Rs.34999 = 1, Rs.35000 to Rs.50000 = 2, Rs.50001 to Rs.74999 = 3

Rs.75000 & above = 4

X27

28. Education Less than graduation = 1

Graduation = 2 Post graduation & above = 3

X28

29. Occupation

Student = 1 Businessman = 2 Professional = 3

Service = 4 Housewife = 5

Others = 6

X29

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CONCEPTS AND CASES

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HIPost-Coding

Open-ended questionsIf you think Lean was a success so far, please specify

three most significant reasons that have contributed to its success in your opinion?

Col.no. Variable name Coding instructions Variable name

63. Improvement at work place by eliminating waste. Yes = 1No = 0

X 63a

64 To meet increasing demands of customers Yes = 1No = 0

X 63b

65 To improve quality Yes = 1No = 0

X 63c

66 To achieve corporate goal Yes = 1No = 0

X 63d

67 It reduces cycle time of the manufacturing & production. Yes = 1No = 0

X 63e

68 Reduced response time Yes = 1No = 0

X 63f

69 Enhanced innovation and creativity Yes = 1

No = 0

X 63g

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CONCEPTS AND CASES

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HIClassification and tabulation of data

Classification by attributes: mostly categorical

Classification by class intervals: this could be exclusive or inclusive

Tabulation: arrangement of data into an orderly arrangement of rows and columns in order to subject it to statistical analysis

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CONCEPTS AND CASES

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HIExploratory data analysis

Sample characteristics: age group of the sample

Age groups frequency percent

20-25 27 27.0

26-30 37 37.0

31-35 9 9.0

36-40 22 22.0

41-45 3 3.0

46 & above 2 2.0

Total 100 100.0

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CONCEPTS AND CASES

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pie charts

46 & Above41-4536-4031-3526-3020-25

Age Group

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CONCEPTS AND CASES

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bar charts

46 & Above41-4536-4031-3526-3020-25

Age Group

40

30

20

10

0

Freq

uenc

yAge Group

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CONCEPTS AND CASES

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histograms

40.0035.0030.0025.0020.0015.0010.00

purchase in gms

6

4

2

0

Freq

uenc

y

Mean =18.3553Std. Dev. =6.55777

N =15

Histogram

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CONCEPTS AND CASES

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HIExploratory data analysisstem and leaf diagrams

Purchase distribution of customers purchase of gold jewellery

13 1 3 3 9

15 6 6 8

16 3 6

17 3 7

18 2

22 2

31 0

35 6

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CONCEPTS AND CASES

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Statistical software packagesMS EXCEL

MINITAB

System for Statistical Analysis(SAS)

Statistical Software for Social Sciences(SPSS)

END OF CHAPTER


CONCEPTS AND CASES

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235_ch.10 - ppt

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