Variables and Statistical Investigation Questions
Understanding data types and research design Year 11 Mathematics New Zealand Curriculum
What Are Variables?
Variables are characteristics that can change or vary They are the building blocks of statistical investigations We collect data about variables to answer questions Examples: height, eye colour, number of pets, favourite subject
Types of Variables
{"left":"Categorical Variables: Data that can be grouped into categories (qualitative)\nNumerical Variables: Data that can be measured or counted (quantitative)","right":"Eye colour, gender, favourite sport\nHeight, age, test scores"}
Variable Classification Challenge
Classify each variable as Categorical or Numerical: 1. Brand of smartphone 2. Number of text messages sent per day 3. Favourite Netflix series 4. Hours spent studying per week 5. Type of transport to school
Numerical Variables: Discrete vs Continuous
Discrete: Counted in whole numbers only Examples: Number of siblings, goals scored, books read Continuous: Can take any value within a range Examples: Height, weight, time, temperature
Think and Discuss
Is 'number of cars in a parking lot' discrete or continuous? What about 'distance travelled to school'? Can you think of a variable that might be tricky to classify?
Response vs Explanatory Variables
Response Variable (Dependent): What you're trying to explain or predict Explanatory Variable (Independent): What might influence the response Example: Does study time affect test scores? Response = test scores, Explanatory = study time
Design Your Investigation
Choose a topic that interests you Write a statistical question that includes: - Clear variables (response and explanatory) - Target population - Purpose of investigation Example: 'Does the amount of sleep affect academic performance in Year 11 students at our school?'
Next Steps: Data Collection and Analysis
Retrieve your dataset from Google Classroom Enter data into NZGrapher software Use Display Explorer to investigate variables Look for patterns and relationships Prepare to draw evidence-based conclusions
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