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DATA COLLECTION & ANALYSIS APPLICATION PRINCIPLES OF MARKETING WEEK 09

DATA COLLECTION & ANALYSIS APPLICATION

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DATA COLLECTION & ANALYSIS APPLICATION. Principles of Marketing Week 09. Learning Objectives. Data Preparation • Process of data preparation for analysis • Validation , editing, and coding of survey data • Data entry procedures • How to detect errors • Data tabulation approaches. - PowerPoint PPT Presentation

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Page 1: DATA COLLECTION & ANALYSIS APPLICATION

DATA COLLECTION& ANALYSIS APPLICATIONPRINCIPLES OF MARKETING WEEK 09

Page 2: DATA COLLECTION & ANALYSIS APPLICATION

LEARNING OBJECTIVES

Data Preparation• Process of data preparation for analysis• Validation, editing, and coding of survey data• Data entry procedures• How to detect errors• Data tabulation approaches

Page 3: DATA COLLECTION & ANALYSIS APPLICATION

OVERVIEW OF DATA PREPARATION & ANALYSIS

Page 4: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONProcess of converting information from a questionnaire so it can be utilized

Four Steps:• Data Validation• Editing and Coding• Data Entry• Data Tabulation

Page 5: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Validation

• Determine if the survey’s interview or observations were conducted correctly and free of interviewer fraud or bias.

• Need to check for factors such as• Courtesy• Screening• Procedure• Completeness

Page 6: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Editing and Coding

• Editing• The process that checks the data for mistakes made by

either the interviewer or respondent• Areas to check:

• Asking proper questions• Accurate recording of answers• Correct screening questions• Reponses to open ended questions

Page 7: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Editing and Coding

• Editing

Page 8: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Editing and Coding

• Coding• Grouping and assigning values to various responses

from the survey instrument• Coding should be:

• Numerical (from 0-9)• Well planned and constructed questionnaires

reduce time spent on coding• Numeric codes should be designed into the

questionnaire from the beginning.• If questionnaires do not use coded responses a

master coding system must be established

Page 9: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Editing and Coding

• Example of a Master Code Sheet

Page 10: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Editing and Coding

• Coding• Coding open ended questions is a four-step process

• Generate a master list of potential responses• Assign values to the responses

• Specify a numerical value as a code• Assign a coded value to each response

Page 11: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Entry

• 4 Major Ways• Computer (Most popular)• Scanner• Touch Scanner• Light Pen

Page 12: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Entry

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DATA PREPARATIONFour Steps:• Data Entry

• Error Detection : First Step• Determine if the software used for data entry and

tabulation includes error editing routines• Identify the wrong type of data• Prepare a printed representation of the data

entered• To produce a data/column list of the data• To find individual questionnaires and verify the

proper response (code)

Page 14: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Tabulation

• Process of counting the numbers of observations classified into certain categories• One way tabulation• Cross tabulation

Page 15: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Tabulation

• One Way Tabulation Purposes• Determine the frequency of non response to individual

questions• Locate errors or blunder in data entry• Calculate summary statistics such as means, standard

deviations, range, etc.• Communicate results of research project

Page 16: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Tabulation

• Cross Tabulation• Determine whether variables differ when compared

across sample subgroups. • Results show frequencies and percentages for both

rows and columns.

Page 17: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Tabulation

• Issues to be considered• Judgment of the analyst—selection of variables

(questions) to use examining relationships• Demographic variables or lifestyle / psychographic

characteristics are the starting point in developing cross-tabulations.

• Technique is simple but findings may be difficult to interpret• Keep research objectives in mind when constructing

and using tables• Spreadsheets help

Page 18: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Tabulation

• Descriptive Statistics• Summarize and describe data obtained from a sample

of respondents

Page 19: DATA COLLECTION & ANALYSIS APPLICATION

DATA PREPARATIONFour Steps:• Data Tabulation

• Descriptive Statistics• Summarize and describe data obtained from a sample

of respondents

Page 20: DATA COLLECTION & ANALYSIS APPLICATION

HOMEWORKIn this week’s homework you will be expected to complete the following:

Questionnaire DesignRedesign the questionnaire from last week’s

homework and give it out to a minimum of 75 people.

Review answers and began the data analysis portion of your final project. Bring to class for review week 10.

Page 21: DATA COLLECTION & ANALYSIS APPLICATION

FINAL PROJECT SPECSThe final project is the culminating academic endeavor of the class’s research over the quarter.

It will provide you with the opportunity to explore a problem or issue of particular personal or professional interest and to address it in a thorough focused study and applied research.

This project should demonstrate your ability to synthesize and apply the knowledge and skills acquired through the class, and it should not only exemplify your ability to think critically, but should utilize the variety of research methods introduced to come to a cohesive and logical conclusion.

Page 22: DATA COLLECTION & ANALYSIS APPLICATION

FINAL PROJECT SPECS» Sections

Executive Summary Industry AnalysisMarketing ResearchHypothesis/Problem Statement/PurposeResearch ObjectivesLimitationsMethodologySample QuestionnaireData AnalysisConclusions