Data Preparation and Analysis Final

8/2/2019 Data Preparation and Analysis Final

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Data Preparation and Analysis


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Data Preparation andAnalysis

Data Preparation

The steps necessary to convert data from a rawform to a form which allows for analysis

Steps in the ProcessCheck Questionnaires

Edit data

Code Data

Transcribe data

Clean data

Adjust data


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Checking Questionnaires

Insure you have all the questionnaires

What makes a questionnaire unsusable?

Incomplete questionnairesQuestionable patterns of response

Unusual patterns

Were skip patterns followed?

No variance in responseQuestionnaires physically incomplete


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Questionnaire received after the cut-off date

Questionnaire answered by someone who did not qualifyto be sample member

Calculation of response rateRate = (Contact (termination+rejection))/Contact


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Editing Unsatisfactory Responses

Unsatisfactory responses

Poor recording

InconsistenciesDifficult interpretation

Words

Marks for scale

Dealing with unsatisfactory responsesRecontact respondent

Assign a missing value

Discard record


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Development of Data CodingCoding

The process of assigning a number to eachpossible response to a question

Coding questions

A codebook

SPSS vs EXCEL

Missing data

Coding of open ended responses

Review all responses

Develop structure

Assign codes

Enter data into datafile


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Transcribing Data

Data Transcription

The process of transferring coded data topermanent storage

Options

Manual data entry

Optical scanning


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Data Cleaning

Data Cleaning

The process of ensuring that all responses fall

within allowable rangesExample - gender

Out-of-range checks

Frequency tables

Consistency checksSkip patterns


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Missing Data

Ignore

Estimation

Substitute a neutral responseImputation (remove)


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Data Adjustment

Data adjustment is often necessary to ensure that thesample data can be generalized to the population ofinterest

Check for sample representativenessOptions

Data weighting

Variable re-specification

Data recodingCreating dummy variables

Scale transformation

Standardizing variables


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Getting Ready to Answer the Management Question

The Translation Process

From Observation to Management QuestionFrom Management Question to Marketing Management

Question

From Marketing Management Question to Research

QuestionFrom Research Question to Hypothesis

From Research Question to Data Analysis

Depends on the type of question


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Planning for Data Analysis

What has gone on before?

Model

Research question

Research design

The key questions

What kind of question have you asked?

Descriptive versus inferential?

Causal or non-causal?

Differences or relationships


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What kind of data do you have

Primary scales of measurement?

Independent variable, Dependent variable?

Causal versus non-causal


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Documents

Data Preparation and Analysis Final