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Chapter 2
Data
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2.1 Data Tables
Some Basic Ideas
Data are a collection of numbers, labels, or symbols with context
A data table is a rectangular arrangement of data with rows and columns
Observations or cases form the rows; common attributes or variables form the columns
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2.1 Data Tables
Disorganized Data
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2.1 Data Tables
Same Data in a Data Table
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2.1 Data Tables
Organize data to yield meaningful information
Provide context (e.g., who, what, when)
Improve interpretability with meaningful names, formatting and units
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7. 2.2 Categorical and Numerical Data
Categorical Data
Also called qualitative or nominal variables
Identify group membership
Type of purchase made and Brand of bike are examples
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8. 2.2 Categorical and Numerical Data
Also called quantitative or continuous variables
Describe numerical properties of cases
Have measurement units
Size of bike (cm) and Amount spent ($) are examples
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9. 2.2 Categorical and Numerical Data
Measurement Scales
Nominal – name categories without implying order (categorical)
Ordinal – name categories that can be ordered (categorical)
Interval – numerical values that can be added or subtracted (no absolute zero)
Ratio – numerical values that can be added, subtracted, multiplied or divided (makes ratio comparisons possible)
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10. 2.2 Categorical and Numerical Data
Likert Scale (Ordinal – 5 to 7 Categories)
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11. 2.3 Recoding and Aggregation
Recode: building a new variable from another (recoding price into expensive or inexpensive)
Aggregate: reduce rows in a data table by counting or summing values within categories
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12. 2.3 Recoding and Aggregation
An Example of Aggregation
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13. 4M Example 2.1: MEDICAL ADVICE
Motivation
Are patients from one HMO more likely to visit the doctor than those from another HMO?
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14. 4M Example 2.1: MEDICAL ADVICE
Method
Gather data and organize in a data table. Cases that make up the rows are office visits. The following variables make up three columns: Patient ID; HMO Plan; and Duration of patient’s office visit.
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15. 4M Example 2.1: MEDICAL ADVICE
Mechanics
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16. 4M Example 2.1: MEDICAL ADVICE
Message
Aggregate the duration of office visits to learn whether patients from one plan are consuming most of the doctor’s office time.
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2.4 Time Series
Some Definitions
Time series – data recorded over time
Timeplot – graph of a time series showing values in chronological order
Frequency – regular time spacing of data in a time series (e.g., daily, monthly, etc.)
Cross-sectional – data observed at the same time
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2.4 Time Series
Timeplot of Monthly Unemployment Rate
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19. 2.5 Further Attributes of Data
Useful to Know
When and where the data were collected
Source of the data (available online?)
How the data were collected
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20. 4M Example 2.2: CUSTOMER FOCUS
Motivation
How do customers in a focus group react to a new product design?
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21. 4M Example 2.2: CUSTOMER FOCUS
Method
Gather data and organize in a data table. The cases that make up the rows are participants in the focus group. One of the variables that make up the columns is participants’ ratings of the product.
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22. 4M Example 2.2: CUSTOMER FOCUS
Mechanics
In addition to product ratings, the columns should include characteristics of the participants such as name, age (in years), sex, and income.
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23. 4M Example 2.2: CUSTOMER FOCUS
Message
Determine who likes the design (younger or more affluent members of the focus group, for example) and choose advertising that appeals to this group.
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Best Practices
Provide a context for your data.
Use clear names for your variables.
Distinguish numerical data from categorical data.
Track down the details when you get the data.
Keep track of the source of data.
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Pitfalls
Do not assume that a list of numbers provides numerical data.
Don’t trust all of the data that you get from the Internet.
Don’t believe every claim based on survey data.
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