📊 Part 1: Identifying Data Features

WALT: Identify and describe features and trends in data visualisations

1. Look at the temperature data graph for Auckland (January-December 2023). What type of trend do you observe?

Increasing trend

Decreasing trend

Seasonal pattern

No clear pattern

2. Which features might you look for when analysing data? (Select all that apply)

Outliers

Clusters

Gaps in data

Central tendency

Spread of data

3. In a scatter plot showing study hours vs exam scores, you notice most points cluster around a diagonal line going upward. This suggests:

No relationship

Positive relationship

Negative relationship

Random pattern

4. Describe what an "outlier" is in your own words:

📈 Part 2: Analysing Trends and Making Inferences

5. A time series graph shows New Zealand's population growth from 1990-2023. The line shows steady upward movement. What informal inference could you make about population in 2025?

6. When drawing a "line of best fit" on a scatter plot, you should try to:

Connect all the dots

Draw a line that passes through most points

Draw a line with roughly equal points above and below

Only connect the highest points

7. Complete this sentence: "When making informal inferences from data trends, it's important to consider _____________ and _____________ because..."

8. A box plot shows that 75% of Year 11 students scored between 65-85% on a maths test, but there are three dots below 40%. What do these dots represent and what might cause them?

🎯 Part 3: Extension Challenge

9. For Advanced Learners: You notice that your line of best fit doesn't pass through several data points. These deviations are called "residuals". Suggest two possible reasons why data points might not fit perfectly on the trend line:

10. Real-world Application: Choose a current issue in New Zealand (e.g., housing prices, climate data, sports performance). Describe what type of data visualisation would be most useful for analysing trends and explain why:

Success Criteria Check: Can you tick off what you've achieved today?

I can read and interpret different types of data visualisations

I can describe trends, clusters, and outliers using statistical vocabulary

I can explain what a line of best fit shows

I can make informal inferences from data trends

I can communicate my findings with evidence