📊 Part 1: Identifying Data Features
WALT: Identify and describe features and trends in data visualisations
1. Look at the scatter plot showing rainfall (mm) vs temperature (°C) in Auckland. Which statement best describes the relationship?
Strong positive correlation - as temperature increases, rainfall increases
Weak negative correlation - as temperature increases, rainfall decreases slightly
No correlation - temperature and rainfall are unrelated
Perfect positive correlation - rainfall always increases with temperature
2. In a box plot showing student test scores, which features indicate the spread of the data? (Select all that apply)
The length of the box (interquartile range)
The position of the median line
The length of the whiskers
Any outliers beyond the whiskers
3. A time series graph shows New Zealand's population from 1990-2020. The trend line shows steady growth with a steeper increase after 2010. What might explain this pattern?
Increased immigration policies after 2010
Higher birth rates throughout the period
Data collection errors before 2010
Population decrease in other countries
4. Describe what you would look for when identifying an outlier in a data set:
📈 Part 2: Analysing Trends and Making Inferences
5. You are given a scatter plot showing hours of study vs exam scores for Year 11 students. Describe how you would draw a line of best fit and what it would tell you:
6. A bar graph shows that ice cream sales in Christchurch peak in January and are lowest in July. Based on this trend, predict sales for March and explain your reasoning:
7. Complete this statement about making informal inferences from data:
When the data shows a clear trend, we can predict that _________________ will likely continue, but we must consider _________________ and _________________ that might affect future results.
8. A time series shows Wellington's average monthly temperature over 10 years. You notice the data points cluster around two distinct ranges. What statistical features would you investigate to better understand this pattern?
🎯 Part 3: Extension Challenge
9. Advanced Task: You have data showing the relationship between house prices ($) and distance from Auckland CBD (km). The scatter plot shows some points far from the general trend. Explain how you would investigate whether these are true outliers or represent different housing types:
10. Critical Thinking: Describe one limitation of using informal inferences from data trends to make predictions about real-world situations:
Success Criteria Check: Can you describe trends using statistical vocabulary? ☐ Can you make reasonable predictions from data? ☐ Can you explain your reasoning with evidence? ☐
