1 / 15
Session 2 of 8
Types of Data
Not all data is the same. Today we learn to tell the difference — and why it matters for choosing the right graph.
📊 Data Science for Young Minds · Grade 4
2 / 15
Opening Hook
Which One Is Different?
Which one is different? Why?
3 / 15
Today's Plan
What We're Doing Today
- 🏷️ Categorical data — names, labels, groups
- 🔢 Numerical data — counts and measurements
- 📌 Discrete vs. continuous — can it be a fraction?
- 📊 Which graph fits which type of data
- 🃏 Data Sorting Challenge — 20 cards to classify
4 / 15
Lesson 1
Categorical Data
Data that names a group or label. You can't do math on it — you can only count how many are in each group.
🏷️ Examples of Categorical Data
Favorite color · Eye color · Type of pet · Country of birth
Preferred sport · Hair color · Season born · Shoe brand
Quick test: Can you calculate the average? If no → it's probably categorical.
What's the average eye color? 🤷 Meaningless! That confirms it's categorical.
5 / 15
Lesson 2
Numerical Data
Data that is a number you can calculate with — add, subtract, find the average, compare sizes.
🔢 Examples of Numerical Data
Height (cm) · Age · Test score · Hours of sleep · Temperature
Number of pets · Distance to school · Pulse rate · Weight
Quick test: Can you find the average? If yes → it's numerical.
Average height of the class? ✅ That makes sense!
6 / 15
Lesson 3
Discrete vs. Continuous
Numerical data has two sub-types. The key question: can it be a fraction?
📌 Discrete
- Whole numbers only
- You count them
- Can't be a fraction
- 2 siblings, not 2.5
- 3 pets, 7 books, 4 goals
📏 Continuous
- Any value on a number line
- You measure them
- Can be a decimal
- 1.73 m tall, 36.8°C
- Height, weight, time, temp
7 / 15
Lesson 4
Data Type → Graph Type
The type of data you have determines which graph to use. Wrong type = misleading graph!
Categorical
Bar Chart
Compare group counts
Categorical
Pie Chart
Show parts of a whole
Categorical
Pictograph
Visual count by symbol
Numerical (Discrete)
Line Plot
Show frequency on a number line
Numerical (Discrete)
Stem-and-Leaf
Show distribution of values
Numerical (Continuous)
Line Graph
Show change over time
8 / 15
Activity Time!
Data Sorting Challenge
Your group has 20 data cards. Sort each one into:
🏷️ Categorical
Names a group or label.
Can't calculate average.
🔢 Numerical
A number you can calculate with.
Can find average.
⚠️ Some cards might be "Either" — that's OK! Be ready to explain your choice. ⏱ You have 15 minutes.
9 / 15
Tricky Cases!
Edge Cases — What Would You Do?
- 🏠 Zip Code — looks like a number. Is it numerical? (Think: does it make sense to average zip codes?)
- ⭐ Star rating (1–5) — number, but is it really measuring something continuous?
- 👟 Shoe size — numbers, but only certain values exist (4, 4.5, 5…)
- 📅 Year of birth — number, but often used as a category (decade)
Data scientists debate these edge cases all the time. What matters is explaining your reasoning.
10 / 15
🧠
Brain Break — Data Type Bingo!
Your teacher will call out a variable. Stand up if it's categorical, stay seated if it's numerical!
Favorite food · Height · Eye color · Temperature · Number of siblings · Country · Test score · Hair color
11 / 15
Debrief
Sort Debrief — Let's Compare!
"Did any card cause a debate in your group? Which one? How did you decide?"
- Which cards were easiest to sort? Which were hardest?
- Did any group put a card in a different pile than yours?
- Is "zip code" categorical or numerical? Defend your answer.
- For each card: which graph type would you use to display it?
12 / 15
Graph Matching
Match the Data to the Graph
For each scenario below, which graph type would you choose?
- 📊 Students' favorite school subjects (15 choices)
- 📈 Daily temperature in your city for 30 days
- 🔵 Heights of 25 students in centimeters
- 🥧 How students get to school (walk/bus/car/bike)
- 📉 Books read each month for a year
No single right answer for every case — but some choices are clearly better. Be ready to explain why.
13 / 15
Connecting to Real Life
Where You See Data Types Every Day
🏷️ Categorical Around You
- Sports teams (names)
- Menu items at lunch
- Countries on a map
- Genres of books
🔢 Numerical Around You
- Sports scores (discrete)
- Weather temperature (continuous)
- Price of lunch (continuous)
- Steps walked today (discrete)
Data scientists ask "what type is this?" before doing anything else with data.
14 / 15
Vocabulary Review
Words to Know
Categorical
Data that names groups or labels; can't be averaged
Numerical
Data that is a number you can calculate with
Discrete
Countable whole numbers only — no fractions
Continuous
Can be any value including decimals; measured not counted
Variable
Any characteristic being measured or observed
Graph type
The visualization chosen based on the data type
15 / 15
Wrap Up
Session 2 Complete!
- ✅ Categorical data names groups — can't calculate averages on it
- ✅ Numerical data is a number you can calculate with
- ✅ Discrete = whole numbers only · Continuous = any value
- ✅ Your data type determines your graph type
- ✅ Edge cases exist — reasoning matters more than memorizing
🔮 Coming up — Session 3: Now that we know what types of data exist, how do we collect it well? Better surveys — without the bias.