📊 Part 1: Understanding Categorical Data

1. Circle the examples that are categorical data:

Hair colour (brown, blonde, black)

Height in centimetres

Favourite sport (rugby, netball, cricket)

Number of siblings

Eye colour (blue, green, brown)

2. Explain the difference between categorical and numerical data:

3. Give three examples of categorical data you might collect about your classmates:

🔍 Part 2: Ethics in Data Collection

4. Which of these survey questions are ethical and appropriate? Check all that apply:

"What is your favourite subject at school?"

"How much money does your family earn?"

"What type of transport do you use to get to school?"

"What is your parents' relationship status?"

"What is your favourite hobby?"

5. Fill in the blanks about ethical data collection:

Before collecting data from people, we should always get their ____________. We should only ask questions that are ____________ and not too ____________. The data we collect should be kept ____________ and only used for the stated purpose.

6. Write one ethical survey question you could ask your classmates about their preferences:

📈 Part 3: Data Collection and Organisation

7. Complete this tally table for "Favourite Season" data:

Data collected: Summer, Winter, Spring, Summer, Autumn, Summer, Winter, Spring, Summer, Winter, Summer, Autumn, Spring

8. Create a frequency table from your tally table above:

9. Draw a bar graph for the "Favourite Season" data in the space below:

🔎 Part 4: Analysing Data Visualisations

10. Look at your bar graph from Question 9. Complete these "I notice" statements:

I notice that ____________ is the most popular season with _____ votes.

I notice that ____________ is the least popular season with _____ votes.

I notice that Summer has _____ more votes than Winter.

11. What is the difference between "reading the data" and "reading between the data"?

12. Based on your data analysis, what conclusion can you draw about seasonal preferences?

⚠️ Part 5: Critical Evaluation of Data Claims

13. A graph shows that 90% of people prefer Brand X chocolate. What questions should you ask before believing this claim? List three:

14. Circle the potential problems with data visualisations:

Misleading scale on axes

Too small sample size

Biased survey questions

Missing data labels

All of the above

15. How can you tell if a data visualisation is trustworthy and accurate?

🎯 Part 6: Planning Your Own Investigation

16. Design your own categorical data investigation. Complete the planning template:

Research Question: ________________________________

Variable to investigate: ____________________________

Target group: ____________________________________

Data collection method: ____________________________

Ethical considerations: ______________________________

17. Write three survey questions you would ask for your investigation:

18. Reflection: What did you learn about categorical data analysis today?

Categorical Data Analysis Worksheet

Categorical Data Analysis Worksheet

📊 Part 1: Understanding Categorical Data

🔍 Part 2: Ethics in Data Collection

📈 Part 3: Data Collection and Organisation

🔎 Part 4: Analysing Data Visualisations

⚠️ Part 5: Critical Evaluation of Data Claims

🎯 Part 6: Planning Your Own Investigation

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