• Previous literature • Conduct exploratory research • Wording needs to be precise and self-explanatory • The norm is to have 5 to 7 values on your scale A couple of things to remember when using metric questions for your questionnaire Answer coding – Gender: Male = 1; Female = 2 – Marital status: Single = 1; Married no children = 2; Married with children = 3; divorced = 4; Separated = 5; windowed =6; Partner=7 – Likelihood to repeat purchase: “Definitely will not” = 1; “Definitely will” = 5 Data view For both categorical and metric questions, the answers are typically coded in numbers Customer ID Gender Marital Status Likelihood to repeat 0001 1 5 3 0002 1 4 4 0003 2 2 2 0004 1 7 2 0005 1 3 5 0006 2 3 1 0007 1 2 2
9 • Metric – data that you can add, subtract, and compute averages for • Categorical – cannot add, subtract, or compute averages for (even if it is coded as numbers, such as in marital status on the previous page) This is an important distinction because comparative research questions entails comparing these averages. The difference between metric and categorical can be traced back to the scales they use Main difference between metric vs. categorical data (for this unit) Scaling • Goal - to precisely quantify what is to be measured. • Definition - the process of assigning a set of descriptors to represent the range of possible responses to a question about a particular construct. • Examples – Temperature – Rate the car on a scale of 1 to 10 – Male, Female (value ≠ numbers) 8/22/2016 26 Every fixed ‐ alternative question uses a scale There are 4 types of primary scales 27 Primary Scales Nominal Ordinal Interval Ratio Categorical Metric
10 • Nominal scale – no rank-ordering between values – Example: Which one of the following media influences your purchasing decisions the most? 1. TV 2. Radio 3. Newspaper • Ordinal scale – rank ordering between values – Example: Which of the following describes your level of education (please circle the number on the left) 1. Did not complete high school 2. High school graduate 3. Some College 4. College graduate 5. Postgraduate degree Difference between nominal vs. ordinal scale Cannot compute averages – e.g., there is no sense of talking about “average media” or “average level of education” for data obtained from such categorical questions Examples of categorical questions and scales used Nominal Scale Ordinal Scale Nominal Scale Ordinal Scale • This includes all the examples of metric questions we used earlier in this week’s lecture • Interval scale is a type of metric scale – You can talk about “average customer satisfaction”, or “average importance rating”, and etc Interval scale - most measures of the strength of feelings, emotions, attitude and beliefs are based on an interval scale
11 There is one scale that we have left out in our lecture so far: ratio Scale • You use ratio scale to provide exact quantity measures of tangible things • Example: What is your annual income before taxes? ___ What makes a ratio scale and how does it differentiate from interval scale?
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- rating scale, Semantic differential