The document provides a comprehensive overview of data types and categories, explaining qualitative and quantitative data, including discrete and continuous data. It describes sources of data, various representations, and how to organize and summarize data through distributions and frequency tables. Additionally, it highlights the importance of class intervals in data analysis.

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4.  Data is a collection of facts, such as values or
measurements.
 It can be
numbers, words, measurements, observation
s or even just descriptions of things.
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6. Data can be qualitative or quantitative.
 Qualitative data is descriptive information
(it describes something)
 Quantitative data, is numerical information
(numbers).
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7.  Discrete data can only take certain values
(like whole numbers)
 Continuous data can take any value (within
a range)
Discrete data is counted,
Continuous data is measured
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8. Qualitative:
 He is brown and black
 He has long hair
 He has lots of energy
Quantitative:
 Discrete:
 He has 4 legs
 He has 2 brothers
 Continuous:
 He weighs 400 pounds
 He is 3.5foot tall
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9. QUALITATIVE
NOMINAL ORDINAL
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10. A type of categorical data in which objects
fall into unordered categories.
 Type of Bicycle
 Mountain bike, road bike,BMX.
 Smoking status
 smoker, non-smoker
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11. A type of categorical data in which order is
important.
 Class of degree-1st class, 2:1, 2:2, 3rd
class, fail
 Opinion of students about stats classes-
Very unhappy, unhappy, neutral, happy
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12.  The different sources of data are published and
unpublished documents, govt
magazines, personal diaries, memories, letters
etc
 Data may be obtained from
 Internal sources
 External sources
 Surveys and experiments
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13. Organized representations of data that help to
summarize and simplify
Many types:
 Ranked frequency distributions
 Simple frequency distributions
 Grouped frequency distributions
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14. A distribution of numbers in which scores are
arranged in order (ranked), with the highest
number at the top and the lowest number at
the bottom of a list . 9
Raw Data 8
3 8 6 9 5 2 7 7
6
5
3
2
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15.  Created by listing all possible score values in
any distribution and then indicating the
frequency (f).
 Frequency ( f ) is the number of times a
score occurs.
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16. Raw Data Score f
2 5 8 7 2 2 8 3
7 2
6 8 5 2 5 7
6 3
4 5 6 2 8 6 5 4
4 1
2 5
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17.  Rawdata are combined into equal-sized
groups called class intervals.
 Class intervals
 Often data has natural classes
 E.g., grades in a course
 Intervals must not be too large or too small
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18. Class interval f
90-100 1
80-89 5
70-79 2
60-69 7
<59 7
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