Coding the Data: Creating Codebooks Chapter 19

Stages in the Research Process Formulate Problem Determine Data Collection Method Determine Research Design Design Data Collection Forms Analyze and Interpret the Data Prepare the Research Report Design Sample and Collect Data

Coding The process of transforming raw data into symbols (usually numbers) that can be utilized for analysis.

Example of Likert Scale Strongly Disagree Agree Neither Agree nor Disagree Strongly Agree The celebrity endorser is trustworthy. The celebrity endorser is unattractive. The celebrity endorser is an expert on the product. The celebrity endorser is not knowledgeable about the product.

Coding Likert Scales 1. Give each statement a name: Trustworthy Unattractive Expert Knowledge 2. Assign numbers to each response: 1 = Strongly disagree 2 = Disagree 3 = Neither Agree nor Disagree 4 = Agree 5 = Strongly Agree

Example of Semantic-Differential Scale SALESPERSON Knowledgeable Not Knowledgeable :::::: Did Not Pester me Pestered me :::::: Not FriendlyFriendly :::::: Helpful Not Helpful ::::::

Coding Semantic Differential Scales 1. Name each set of bipolar adjectives Helpful Friendly Pester Knowledge 2. Assign numbers to each blank Example for “Helpful” 1 = not helpful 2 = 3 = 4 =Do this for each set. 5 =Beware of Reverse Coded Items 6 = 7 = helpful

Coding Closed-ended Items What is your overall opinion of SEARS department stores? unfavorablefavorable Typical coding: 1=unfavorable 2= 3= 4= 5= 6= 7 =favorable

Coding Closed-ended Items: Check All That Apply How did you learn about Brown Furniture Company? (check all that apply) newspaper advertising radio advertising billboard advertising recommended by others drove by store other: _______________ Typical coding: 6 different variables (1 if checked; 0 if not)

Coding Open-ended Items Open-ended items seeking concrete, or factual, responses are relatively easy to code: numeric answers are typically recorded as given by the respondent, while other types of responses are given a specific code number. (1)In what year were you born? (code year) (2)How many times have you eaten at Streeter’s Grill in the last month? (code number) (3) Name the first 3 coffee shops located in Jackson that come to mind. (code as 3 separate variables; assign numbers to represent each coffee shop mentioned)

Coding Open-ended Items Open-ended items seeking less structured responses are much more difficult to code. In your own words, give us two or three reasons why you prefer to leave Mississippi after graduation.

Process for Coding (Abstract) Open-ended Questions 1.Develop initial response categories (before reading responses) 2.Identify usable responses 3.Review responses; add, delete, revise categories 4.Sort responses into categories, using multiple coders; compare results 5.Repeat #3 and #4 if one or more categories are too broad 6.Assign code numbers for each category; use these codes to represent responses in the data file 7.Assess interrater reliability (the degree of agreement between coders); low interrater reliability suggests that the categories are not well-defined, and #3-6 should be repeated

Developing a Codebook SPORTING GOODS SURVEY Please answer the following questions about buying sporting goods over the internet: 1.During the past year, what percentage of the sporting goods you purchased were ordered through the internet? ________ percent 2.How willing are you to purchase merchandise offered through the Avery Sporting Goods web site? Not at all willing Somewhat willing Very willing 3.Please provide some reasons why someone might not want to purchase sporting goods over the internet:

Developing a Codebook Avery Sporting Goods – CODEBOOK (partial) Var. Name Description IDquestionnaire identification number PERCENT% products purchased through internet (record response) WILLINGwillingness to purchase through web site1=not at all willing 2=somewhat willing 3=very willing REASON1first reason for not purchasing over internet1=security issues (open ended) 2=no internet access 3=can’t examine goods 4=difficult to return 5=don’t want to wait 6=prior bad exper. w/internet 7=other REASON2second reasonSAME REASON3third reasonSAME

What do the data look like? IDPERCENTWILLINGREASON1REASON2REASON