Presentation is loading. Please wait.

Presentation is loading. Please wait.

Chapter Twelve Quality Control and Initial Analysis of Data.

Similar presentations


Presentation on theme: "Chapter Twelve Quality Control and Initial Analysis of Data."— Presentation transcript:

1 Chapter Twelve Quality Control and Initial Analysis of Data

2 Copyright © Houghton Mifflin Company. All rights reserved.12 | 2 Chapter Objectives Define editing and distinguish between a field edit and an office edit Define coding and outline the steps it involves Compute measures of central tendency and dispersion of the data for each variable in a data set State the potential uses of frequency distribution or one- way tables

3 Copyright © Houghton Mifflin Company. All rights reserved.12 | 3 Data Analysis at Rockbridge Associates: Data Integrity Data integrity is the foundation for successful marketing research Rockbridge ensures integrity in the collection and processing of the data by a number of quality control checks for –mail surveys –telephone surveys –web surveys Rockbridge ensures data integrity in how the results are interpreted and explained to management

4 Copyright © Houghton Mifflin Company. All rights reserved.12 | 4 Editing Editing is the process of examining completed data collection forms and taking whatever corrective action is needed to ensure the data are of high quality –Preliminary or field edit –Final or office edit

5 Copyright © Houghton Mifflin Company. All rights reserved.12 | 5 Field Edit A field edit, or preliminary edit, is a quick examination of completed data collection forms, usually on the same day they are filled out Objectives –Ensure that proper procedures are being followed in selecting respondents, interviewing them, and recording their responses –Fix fieldwork deficiencies before they turn into major problems

6 Copyright © Houghton Mifflin Company. All rights reserved.12 | 6 Office Edit A final, or office edit, verifies response consistency and accuracy –Makes necessary corrections –Determines whether some or all parts of a data collection form should be discarded

7 Copyright © Houghton Mifflin Company. All rights reserved.12 | 7 What Is Wrong With this Response… A respondent said he was 18 years old but indicated that he had a Ph.D. when asked for his highest level of education.

8 Copyright © Houghton Mifflin Company. All rights reserved.12 | 8 Editing Can Help Uncover Improper field procedures Incomplete interviews Improperly conducted interviews Technical problems with the questionnaire or interview Respondent rapport problems Consistency problems that can be isolated and reconciled

9 Copyright © Houghton Mifflin Company. All rights reserved.12 | 9 Improper Field Procedures Wrong questionnaire form used Interview inadvertently not taken

10 Copyright © Houghton Mifflin Company. All rights reserved.12 | 10 Incomplete Interviews Questions not asked Directions not followed (proper segments of the questionnaire were not administered)

11 Copyright © Houghton Mifflin Company. All rights reserved.12 | 11 Improperly Conducted Interviews The wrong respondent interviewed (e.g., son instead of father) Questions misinterpreted by interviewer or respondent Evidence of bias or influencing of answers. Failure to probe for adequate answers or the use of poor probes Interviewer's illegible writing and/or style. Interviewer recorded information which identified a respondent whose anonymity should have been protected

12 Copyright © Houghton Mifflin Company. All rights reserved.12 | 12 Improperly Conducted Interviews (Cont’d) Interviewer apparently does not understand what type of responses constitute an answer to the actual question asked Interviewer does not understand what the objective of the question is and thus accepts an improper frame of reference for the respondent's answer Other evidence of need for training or instructions to be given to interviewer –failure to write down probes, wrong abbreviations, failure to follow directions

13 Copyright © Houghton Mifflin Company. All rights reserved.12 | 13 Technical Problems With the Questionnaire or Interview Space was not provided for needed information The presence of unanticipated or unusually frequent extreme responses to questions, indicating a possible need for rewording of certain questions Inappropriate or unworkable interviewer instructions not detected in the pretest The order in which questions were asked introduces confusion, resentment, or bias into the respondent's answers

14 Copyright © Houghton Mifflin Company. All rights reserved.12 | 14 Respondent Rapport Problems Frequent refusal to answer certain questions. Reports of abnormal termination of the interview (or presence of hostility) due to sensitive questions Evidence that respondent and interviewer are playing the "game" of "What answer do you want me to give?" Evidence that the presence of other people in the interview situation is causing problems

15 Copyright © Houghton Mifflin Company. All rights reserved.12 | 15 Consistency Problems That Can Be Isolated and Reconciled Contradictory answers –Reports no savings in one section of the interview but reports interest from bank accounts in another section Misclassification –Mortgage debt improperly reported as installment debt Impossible answers –Reports paying $600 for a new Edsel in the car should have been recorded as a "used" car; or weekly income reported on the income-per-month line

16 Copyright © Houghton Mifflin Company. All rights reserved.12 | 16 Consistency Problems That Can Be Isolated and Reconciled (Cont’d) Unreasonable (and probably erroneous) responses –Respondent reports borrowing $2,000 for two years to buy a car but reported monthly payments multiplied by 24 months are less than $2,000 –Respondent reports that the house value is $90,000 while income is $2,000 per year and the respondent claims less than a high school education

17 Copyright © Houghton Mifflin Company. All rights reserved.12 | 17 Preventing Errors Careful planning before fieldwork begins Automating data entry

18 Copyright © Houghton Mifflin Company. All rights reserved.12 | 18 Coding Coding broadly refers to the set of all tasks associated with transforming edited responses into a form that is ready for analysis Steps –Transforming responses to each question into a set of meaningful categories –Assigning numerical codes to the categories –Creating a data set suitable for computer analysis

19 Copyright © Houghton Mifflin Company. All rights reserved.12 | 19 Transforming Responses into Meaningful Categories A structured question is pre-categorized Responses to a nonstructured or open-ended question to be grouped into a meaningful and manageable set of categories

20 Copyright © Houghton Mifflin Company. All rights reserved.12 | 20 The Best Way to Treat "Don't Know" Responses Infer an actual response – dubious validity Classify the "don't know's" as a separate response category for each question

21 Copyright © Houghton Mifflin Company. All rights reserved.12 | 21 Missing-Value Category A missing value can stem from –A respondent's refusal to answer a question –An interviewer's failure to ask a question or record an answer or a "don't know" that does not seem legitimate Best way to treat missing value responses –Sound questionnaire design –Tight control over fieldwork

22 Copyright © Houghton Mifflin Company. All rights reserved.12 | 22 Assigning Numerical Codes Assign appropriate numerical codes to responses that are not already in quantified form To assign numerical codes, the researcher should facilitate computer manipulation and analysis of the responses

23 Copyright © Houghton Mifflin Company. All rights reserved.12 | 23 Coding Multiple Response Which of the following countries have you visited during the past 12 months? ________Canada ________England ________France ________Germany ________Japan ________Mexico Need six variables, each relating to a specific country and having two possible values. For example, 1= “No” and 2 = “Yes” Six columns must be set aside in the data spreadsheet to record responses to this question

24 Copyright © Houghton Mifflin Company. All rights reserved.12 | 24 Multiple Response Question – Rank Order Question Please rank the following fast-food restaurants by placing a 1 beside the restaurant you think is best overall, a 2 beside the restaurant you think is second best, and so on. __________Burger King __________McDonald's __________Wendy's __________Whataburger This question requires as many variables (and columns) as there are objects to be ranked 4 separate variables are needed

25 Copyright © Houghton Mifflin Company. All rights reserved.12 | 25 Creating a Data Set Organized collection of data records Each sample unit within the data set is called a case or observation Structure of a Data Set –The number of observations = n –The total number of variables embedded in the questionnaire is m, then Data set = n x m matrix of numbers

26 Copyright © Houghton Mifflin Company. All rights reserved.12 | 26 Table 12.3 Structure of a Data Sheet

27 Copyright © Houghton Mifflin Company. All rights reserved.12 | 27 Preliminary Data Analysis: Basic Descriptive Statistics Preliminary data analysis examines the central tendency and the dispersion of the data on each variable in the data set

28 Copyright © Houghton Mifflin Company. All rights reserved.12 | 28 Table 12.4 Measures of Central Tendency and Dispersion for Different Types of Variables

29 Copyright © Houghton Mifflin Company. All rights reserved.12 | 29 Measurement Level of Data Pertaining to Variable – Nominal Measures of Central Tendency –Mode: Most frequently occurring response Measures of Dispersion –Strictly speaking, the concept of dispersion is not meaningful for nominal data –An idea about the distribution of responses can be obtained by examining their relative frequencies of occurrence

30 Copyright © Houghton Mifflin Company. All rights reserved.12 | 30 Measurement Level of Data Pertaining to Variable – Ordinal Measures of Central Tendency –Median: 50th percentile response Measures of Dispersion –Range: Defined by the highest and lowest response values –Interquartile range: Difference between the 75th and 25th percentile responses

31 Copyright © Houghton Mifflin Company. All rights reserved.12 | 31 Measurement Level of Data Pertaining to Variable – Interval Measures of Central Tendency –Mean: Arithmetic average of response values Measures of Dispersion –Standard deviation: As defined in Chapter 9

32 Copyright © Houghton Mifflin Company. All rights reserved.12 | 32 Measurement Level of Data Pertaining to Variable – Ratio Measures of Central Tendency –Mean: Arithmetic average of response values Measures of Dispersion –Standard deviation: As defined in Chapter 9

33 Copyright © Houghton Mifflin Company. All rights reserved.12 | 33 Mode The value that occurs most frequently

34 Copyright © Houghton Mifflin Company. All rights reserved.12 | 34 Table 12.5 How Long Have You Been Using the Services of National? – Computing Mode

35 Copyright © Houghton Mifflin Company. All rights reserved.12 | 35 Median The observation below which 50 percent of the observations fall

36 Copyright © Houghton Mifflin Company. All rights reserved.12 | 36 Table 12.6 Length of Time Service Used – Responses from 20 Customers

37 Copyright © Houghton Mifflin Company. All rights reserved.12 | 37 Table 12.7 Computing Median for Length of Time Service Used

38 Copyright © Houghton Mifflin Company. All rights reserved.12 | 38 Mean n = Number of units in the sample x i = data obtained from each sample unit I = sample mean value, given by

39 Copyright © Houghton Mifflin Company. All rights reserved.12 | 39 Table 12.8 Overall Quality of Services Provided by National– Computing Mean

40 Copyright © Houghton Mifflin Company. All rights reserved.12 | 40 Measures of Dispersion Range Variance Standard Deviation

41 Copyright © Houghton Mifflin Company. All rights reserved.12 | 41 Range Range is the difference between the largest and smallest value The simplest measure of dispersion

42 Copyright © Houghton Mifflin Company. All rights reserved.12 | 42 (x i –x ) 2 S 2 = n-1 Variance Variance of a set of data is a measure of deviation of the data around the arithmetic mean

43 Copyright © Houghton Mifflin Company. All rights reserved.12 | 43 n  (x i –x ) 2 i= n-1 Standard Deviation Standard deviation is the square root of the variance

44 Copyright © Houghton Mifflin Company. All rights reserved.12 | 44 Table 12.9 Overall Quality of Services Provided by National: Computing Range, Variance, and Standard Deviation

45 Copyright © Houghton Mifflin Company. All rights reserved.12 | 45 Frequency Distribution: One-Way Tabulation One-way tabulation is a table showing the distribution of data pertaining to categories of a single variable

46 Copyright © Houghton Mifflin Company. All rights reserved.12 | 46 Table Age and Length of Time Service Used

47 Copyright © Houghton Mifflin Company. All rights reserved.12 | 47 Table Age and Length of Time Service Used (Cont’d)

48 Copyright © Houghton Mifflin Company. All rights reserved.12 | 48 Why Averages May be Misleading Researchers tested a new sauce product and found –Mean rating of the taste test was close to the middle of the scale, which had "very mild" and "very hot" as its bipolar adjectives Researcher’s conclusion –Consumers need really neither really hot nor really mild sauce

49 Copyright © Houghton Mifflin Company. All rights reserved.12 | 49 Why Averages May be Misleading (Cont’d) Deeper examination revealed –The existence of a large proportion of consumers who wanted the sauce to be mild and an equally large proportion who wanted it to be hot nor really mild sauce Moral of the story –A clear understanding of the distribution of responses can help a researcher avoid erroneous inferences


Download ppt "Chapter Twelve Quality Control and Initial Analysis of Data."

Similar presentations


Ads by Google