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Ryerson University
MKT 500
Tina West

Survey ResearchData Analysis Overview Once survey data are collected from respondents the next step is to input the data on the computer do appropriate statistical analyses interpret the data and make recommendations pertaining to your research objectives Steps in data analysis include i editing and coding survey data ii inputting them in the computer in a softwarereadable format iii doing basic analysis such as frequency distribution means analysis and crosstabulation to generate insights iv testing hypotheses where pertinent and if needed v resorting to higher order analyses such as correlation and regressionThis module will emphasize the practical applications of the statistical techniques and interpretation rather than on the technical aspects or statistical detailsIn addition students will learn how to perform data analysis using Excel Learning Objectives Upon successful completion of this module you will be able to Write a code sheet and enter the data in an Excel spreadsheetConstruct and interpret frequency distributionsCompute means and proportions using Excel Perform statistical testsAnalyze and interpret crosstabulation data Perform correlation and regression analysesReadings Complete the readings for this module in the order suggested below handout in class 1 Data Editing and Coding2 Data AnalysisBasics handout in class 3 Data AnalysisFrequency Distribution handout in class 4 Optional read Chapter 14 Data Processing and Fundamental Data Analysis in Marketing Research The Impact of the Internet texthandout in class 5 Data AnalysisMeans and Standard Deviations6 Data AnalysisProportions handout in class 7 Optional read Chapter 15 Statistical Testing of Differences in Marketing Research The Impact of the Internet texthandout in class 8 Data AnalysisCross Tabulation9 Data AnalysisCorrelation handout in class 10 Data AnalysisRegression handout in classhandout in class 11 Writing a Research Report12 Summary handout in class1 Data Editing and Coding First the completed questionnaires must be edited potentially invalid or inaccurate questionnaires should be eliminatedInvalid and therefore unusable responses can be identified in different waysIf respondents take relatively very little time to complete the questionnaire or they mark the same point say 7 on a 7point scale for all questions they are indicators of invalid answersUnusable questionnaires would be those in which respondents have failed to complete a significant portion of the questionnaireIn paperandpencil surveys respondents sometimes fail to turn the page over and so fail to complete an entire page of the surveyFor this reason it is always best to point out explicitly if questions are on both sides of the sheet In online surveys respondents may skip screens intentionally or inadvertentlyDesign of an online questionnaire should try to control for this possibility Coding is the process of assigning numeral or character codes to all responses for each and every question in the surveyThis enables us to enter data into Excel for analysisWe will illustrate coding by using the shoe purchase survey on the class websiteQuestion A1First you must know what type of scale it isnominal ordinal etc refresh your memory from Module 4Theme 2This question has a nominal scaleused simply for classification So any numbering system with Yes and No getting different numbers is a valid codeExamples Yes1 No2 Yes1 No0 Yes5 No8 etcAs a convention we use the code Yes1 and No0Why might a researcher want to use this coding systemYes1 and No2 is also commonly usedQuestion A2Recognize that this is an interval scaleSo any numbering system in which the uniform interval is maintained is acceptableA simple coding would be to keep the numbers as is 11 2277Another permissible and commonly used coding systems is the following 13 22 31 40 51 62 73Note that uniform interval property is maintainedWhy might a researcher want to use this coding systemQuestion A3Note that this is an openended question respondents can write in their own wordsThere are two ways to handle this One is to put what is said verbatim in a separate Excel columnThe other is to put all openended statements in a separate word documentThen analyze the openended statements for content and compile some general insightsQuestion A4This is an ordinal scaleThere is an ordering in the range of prices that consumers would pay for dress shoesAny numbering system that maintains the ordering is fineExample 1 11999 2203999916017999 10180 or aboveYou might find it useful to employ a more informative and legitimate coding system 1 11999 2020399916016017999 180180 and aboveWhy is it a legitimate coding for this question and why might this coding be more informative 2
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