What We’re Learning About
Statistics is about collecting and understanding data to answer questions, like “How tall are students?” We’re focusing on one-variable data, which looks at just one thing about people or things. Numbers need context - like who they’re from or what they mean - to make sense. For example, “5” could be 5 apples or 5 miles without context, which can lead to mistakes.

Variables are things that can change, like height or favorite color. There are two types:
•    Categorical Variables: Group data into labels (e.g., dominant hand: left or right; favorite sport: soccer, basketball). Differences show up as more or fewer in each group.
•    Quantitative Variables: Numbers that measure amounts.
These can be: 
o    Discrete: Whole numbers you can count (e.g., number of pets: 0, 1, 2). Differences are in steps.
o    Continuous: Any number in a range (e.g., height in cm: 160.5, 170.2). Differences can be tiny.

Variation is how much data points differ - it's why we study statistics! If everyone were the same height, we wouldn’t need averages. For example, heights vary more than hand dominance.

--Assignment 
Part 1: Warm-Up Activity 
Here’s a small set of student heights (in cm) from 5 students:
•    160, 165, 170, 175, 180
Wrong Statement: "The average height is 170 cm for all students."
Tasks:
•    Point out what’s wrong with this statement. (Hint: Think about how many students are included and if it fits everyone.)
•    Write 1–2 sentences explaining why context (like who these students are) matters. 


Part 2: Guided Practice Activity 
Work with a partner. Use the data below from 10 students (from Census at School, a real student project). One partner figures out the variable types and explains variation, while the other makes a simple picture (like a tally or list). Switch roles after 10 minutes, then talk as a group.
Data:
•    Dominant Hand: Left, Right, Right, Left, Right, Right, Left, Right, Right, Left
•    Age (years): 15.2, 15.5, 14.9, 15.1, 15.3, 15.6, 14.8, 15.4, 15.0, 15.7
•    Number of Siblings: 1, 2, 0, 1, 3, 2, 1, 0, 2, 1
Tasks:
1.    Classification and Variation (Partner 1): 
o    Say if each variable is categorical or quantitative. For quantitative ones, note if it’s discrete or continuous.
o    Write 1–2 sentences about variation for each (e.g., “Age changes a little with decimals like ……, showing small …. differences among teens.”).
o    Extra Practice: Pick two things from your life (e.g., “Favorite Movie: Action, Comedy…” and “Time Spent Reading (hours): 1.5, 2.0…”). Classify them and explain their variation.

2.    Representation (Partner 2): 
o    For Dominant Hand, make a tally or bar graph (show heights for Left/Right, e.g., sketch bars - Left: 4, Right: 6).
   
o    For Age, list in order or sketch a dotplot (mark where dots go on a line from 14 to 16 - graph not provided, draw by hand to show spread).
 
o    For Number of Siblings, tally the numbers (e.g., 0: __, 1: __, 2: __, 3: __).
 
o    Extra Practice: Draw a tally for “Favorite Movie” from your extra classification (e.g., Action: 3, Comedy: 2).

3.    Group Discussion: 
o    Compare your work on types, variation, and pictures.
o    Talk about: “How does variation differ across these, and why does context (like student ages) matter?” Write 2–3 sentences about what you found. (Example: “Age varies with decimals, showing small changes, while Siblings jumps in whole numbers. Context helps because it tells us these are teens, explaining why age differences are small.”)

Part 3: Independent Practice
Look at this data from a survey of 5 students:
•    Eye Color: Blue, Brown, Green, Brown, Blue
•    Test Score: 85, 92, 78, 88, 95
Tasks:
•    Classify each variable as categorical or quantitative, and say if quantitative is discrete or continuous. Explain variation for each (e.g., “Test scores change a lot, from 78 to 95, showing different skills.”).
•    Write 2–3 sentences describing the data, including how variation might look as numbers or a picture, and why context matters (e.g., “Eye color has 3 groups, which a bar graph could show. Test scores vary from 78 to 95, suggesting different student efforts in class.”).

•    Extra Activity: Make up a real-life example. Create data for 5 people (e.g., “Pet: Dog, Cat…” and “Backpack Weight (kg): 4.5, 5.2…”). Classify them, explain variation, and sketch a tally (e.g., for pets—graph not provided, draw by hand).
Write why it could answer a question like “Do heavier backpacks link to pet types?”

Homework Assignment
•    Gather a small dataset from home (e.g., ages of 5 family members and their favorite foods). Figure out the variable types, explain variation with context, and make a simple picture (e.g., tally or list) to share next class. (This helps you practice and prepares you for more data work.)

Last modified: Monday, 8 September 2025, 5:56 AM