Preparing Data for Quantitative Analysis Copyright © 2010 by the McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin.

Preparing Data for

Quantitative Analysis

Copyright © 2010 by the McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin

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Learning Objectives

Describe the process for data preparation and analysis

Discuss validation, editing, and coding of survey data

Explain data entry procedures as well as how to detect errors

Describe data tabulation and analysis approaches

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Wal-Mart and Scanner Technology

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Data Preparation Process

Data validation

Editing and coding

Data entry

Data tabulation

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Exhibit 10.1 Overview

Errordetection

Validation

Editing and coding

Data entry

Data tabulation

Data analysis

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Exhibit 10.1 Overview_2

Data analysis

Interpretation

Univariate and bivariate

analysis

Descriptiveanalysis

Multivariate analysis

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Data Validation

Data validation is the process of determining to the extent possible whether the interviews or observations were correctly conducted and free of fraud or bias

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Primary Areas of Validation

Fraud

Screening

Procedure

Completeness

Courtesy

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Areas of Editing Concern

Asking the proper questions Recording answers accurately Screening questions correctly Recording open-ended answers completely

and accurately

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Coding

Coding involves grouping and assigning value to various responses from the survey instrument

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Developing Response Codes

Generate list of potential responses and assign values

Consolidate responses

Assign numerical value as a code

Assign a coded value to each response

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Data Entry

Data entry includes tasks involved with the direct input of the coded data into some specified software package that will ultimately allow the research analyst to manipulate and transform the raw data into useful information

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Methods of Error Detection

Determine if the software used will allow the user to perform “error edit routines”

Scan the actual data that was entered Produce a data/column list procedure for the

entered data

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Exhibit 10.5 SPSS Data View of Coded Values

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One-Way Tabulation

Categorization of single variables in study Illustrate one-way tabulation by constructing

a one-way frequency table Used to calculate summary statistics on

questions Averages Standard deviations Percentages

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Exhibit 10.6 One-Way Frequency Distribution

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Exhibit 10.6 One-Way Frequency Table with Missing Data

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Cross-Tabulation

Simultaneously treat two or more variables in the study

Purpose is to determine if certain variables differ when compared among various subgroups of the total sample

Main form of data analysis in most research projects

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Marketing Research in Action: Deli Depot

How could Deli Depot’s survey and questionnaire be improved?

What are the competitive advantages and disadvantages of Deli Depot over Subway?