Data Inference and Prediction

Name:

Date:

📊 Part 1: Understanding Data Concepts

1. What is an inference in statistics?

A fact that is definitely true

A conclusion drawn from data with some uncertainty

A type of graph

A mathematical formula

2. A prediction in statistics is:

Always 100% accurate

An estimate of future values based on data trends

Only used in weather forecasting

The same as an inference

3. Which of these are examples of statistical predictions? (Check all that apply)

Weather forecast for next week

Sports team performance predictions

Sales trends for a business

Your favourite colour

4. A line of best fit on a scatter plot helps us to:

Make the graph look prettier

Predict possible values and identify trends

Count the number of data points

Remove outliers from the data

📈 Part 2: Interpreting Data

5. Look at this scenario: A scatter plot shows the relationship between hours of study per week and test scores for Year 9 students. The line of best fit shows an upward trend. What inference can you make?

6. Using the same scenario from Question 5, if a student studies for 8 hours per week and the line of best fit suggests they might score around 75%, what factors might affect the accuracy of this prediction?

7. Complete this sentence: When making predictions from data, it's important to consider _____________ because predictions are not always _____________ .

8. A graph shows that ice cream sales increase as temperature increases in Auckland. If the temperature tomorrow is predicted to be 28°C, and the pattern continues, ice cream sales will likely be _____________ compared to a day when it's 15°C.

🔍 Part 3: Critical Thinking

9. You see a news headline: "Study shows 90% of teenagers prefer social media over reading books." What questions should you ask before accepting this as reliable? List at least two:

10. Explain why outliers (unusual data points) might affect the accuracy of predictions. Give an example:

11. Think of a real-life situation where you or your family might use data to make a decision or prediction. Describe the situation and explain how data would help: