1. 6-6 Classifying Data Objective
Classify data as either categorical or quantitative
Understand the difference between discrete and continuous

2. Lesson Quiz: 6-5 Answers
1. The data set gives the times of Tara’s one-way ride to school (in minutes) for one week. Find the mean, median, mode, and range of the data set.
{8, 3, 5, 4, 5}
mean: 5; median: 5; mode: 5; range: 5
2. Which value describes the time that occurred most often?
mode, 13
3. Which value best describes Tara’s ride time? Explain.
Mean, 13; It’s the average time

3. Categorical vs Quantitative Data
Categorical Data
Deals with descriptions.
Data can be observed but
not measured.
Colors, textures, smells,
tastes, appearance, beauty,
etc.
Categorical → Description
Quantitative Data
Deals with numbers.
Data which can be
measured.
Length, height, area,
volume, weight, speed, time,
cost, age, etc.
Quantitative → Quantity

4. Example 1: Oil Painting Categorical data: red/green color, gold frame
smells old and musty
texture shows brush strokes of oil paint
peaceful scene of the country
masterful brush strokes
Quantitative data:
picture is 10" by 14”
with frame 14" by 18”
weighs 8.5 pounds
surface area of painting is 140 sq. in.
cost $300

5. Example 2: :Latte Categorical data: robust aroma frothy appearance
strong taste
glass cup
Quantitative data:
12 ounces of latte
serving temperature 1500 F
serving cup 7 inches in height
cost $4.95

6. Example 3: Freshman Class
Categorical data:
friendly demeanors
civic minded
Environmentalists
positive school spirit
Quantitative data:
672 students
394 girls, 278 boys
68% on honor roll
150 students accelerated in mathematics

7. Make one categorical observation about the picture above.
Explain why this is a qualitative observation.
Make one quantitative observation about the picture above.
Explain why this is a quantitative observation.

8. Make one categorical observation about the picture above.
Explain why this is a qualitative observation.
Make one quantitative observation about the picture above.
Explain why this is a quantitative observation.

9. Discrete Data 0 1 2 3 4 5 6 7 Only certain values are possible
(there are gaps between the possible values)

10. Examples: Discrete Data
Number of children in a family
Number of students passing a stats exam
Number of crimes reported to the police
Number of bicycles sold in a day.
Discrete data
We would not find:
2.2 children in a family
88.5 students passing an exam
127.2 crimes being reported
half a bicycle being sold in one day

11. Continuous Data Theoretically, with a fine enough measuring device.
(no gaps between possible values)

12. Examples: Continuous data
Size of bicycle frame
Height
Time
Age
Temperature
Any value within an interval is possible with a fine enough measuring device

13. Points are NOT connected
Discrete Data
Points are NOT connected

14. Continuous Data
Points ARE connected

15. Classwork/Homework
6-6 Worksheet