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Module 5 · L02 of 12 ~30 min MS12-7 ⚡ +70 XP available

Describing Correlation

Cricket Australia analysts use correlation to find which batting statistics best predict match wins — not always the obvious ones. To use correlation like this, you need to describe both direction (positive/negative) and strength (strong/moderate/weak) precisely.

Think first — A scatterplot shows that taller people tend to earn more. Is this a strong or weak relationship? Is it positive or negative?
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Worksheets

Practise this lesson

Three printable worksheets that build from foundations to mastery — or build your own from any module’s questions.

01
Think First — recall from memory
+5 XP warm-up

A scatterplot shows that taller people tend to earn more. Before reading on, decide: is this relationship strong or weak? Is it positive or negative? How would you describe it in a complete sentence?

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02
The big idea — direction and strength together
+5 XP to read

Correlation describes the relationship between two variables in a scatterplot. It has two components you must always state together.

Direction: positive (both variables increase together), negative (as one increases the other decreases), or no correlation.

Strength: strong (points close to a line), moderate, or weak (widely scattered).

Full description = direction + strength + "linear correlation"
e.g. "strong positive linear correlation"
Direction first
Is the overall pattern going up (positive) or down (negative)? Or is there no clear direction?
Strength second
How close are the points to a straight line? Tight = strong; a broad band = moderate; random scatter = weak or none.
Use both words
Always state both direction AND strength. "Positive correlation" alone is incomplete — add "strong," "moderate," or "weak."
03
What you will learn
Know

Key facts

  • The three possible directions: positive, negative, none
  • The three possible strengths: strong, moderate, weak
  • The correct language for a full correlation description
Understand

Concepts

  • What "direction" means visually on a scatterplot
  • What "strength" means in terms of how close points are to a line
  • Why both components are needed to describe correlation
Can do

Skills

  • Identify direction and strength from a scatterplot description
  • Write a complete correlation description using correct vocabulary
  • Match a description to one of several scatterplot patterns
04
Key terms — correlation
CorrelationA measure of the relationship between two variables — described by direction and strength.
Positive correlationAs the x variable increases, the y variable tends to increase — points rise from lower-left to upper-right.
Negative correlationAs the x variable increases, the y variable tends to decrease — points fall from upper-left to lower-right.
No correlationNo consistent pattern between the two variables — points appear randomly scattered with no clear direction.
Strong correlationPoints are clustered closely around a straight line — the relationship is clear and consistent.
LinearDescribes a relationship that follows an approximately straight-line pattern (as opposed to curved).
05
Direction — positive, negative, or none
MS-S4 core

The direction of correlation describes whether the two variables move in the same direction or opposite directions as you move along the x-axis.

  • Positive: Higher x tends to pair with higher y. The points slope upward from left to right. Example: hours studied and exam score — more study tends to give higher scores.
  • Negative: Higher x tends to pair with lower y. The points slope downward from left to right. Example: temperature and hot coffee sales — hotter days mean fewer hot drinks sold.
  • No correlation: No consistent pattern. Example: shoe size and IQ score — no systematic relationship.
Visual check: Imagine a line through the cloud of points. Does it slope up? Down? Or is there no line that fits? That tells you the direction.
What to write in your book
  • Positive: points slope up (both increase together).
  • Negative: points slope down (as x increases, y decreases).
  • No correlation: random scatter — no consistent trend.

Quick check: A scatterplot shows that as daily temperature increases, the number of umbrellas sold decreases. What direction is this correlation?

06
Strength — strong, moderate, or weak
MS-S4 core

The strength of correlation describes how closely the points follow a straight line.

  • Strong: Points are tightly clustered along a line — you can predict y from x with high accuracy. The trend is obvious at a glance.
  • Moderate: Points follow a general trend but with noticeable scatter — you can predict the direction of y but not its exact value.
  • Weak: Points are widely scattered — there is barely a pattern, and x is a poor predictor of y.

Think of strength as "how close together are the dots?" — the tighter the band of points around a straight line, the stronger the correlation.

Remember: Even a weak correlation has a direction (unless there is truly no correlation). Always state both — e.g. "weak positive" or "strong negative."
What to write in your book
  • Strong: points very close to a line — tight band.
  • Moderate: points follow the trend but with clear scatter around it.
  • Weak: points widely scattered — barely a pattern visible.

Which does NOT belong? Descriptions used when classifying correlation:

07
Describing correlation using both components together
MS-S4 core

A complete correlation description uses both direction AND strength. The standard HSC format is:

[strength] + [direction] + "linear correlation"

Examples:

  • "There is a strong positive linear correlation between hours of study and exam score."
  • "There is a moderate negative linear correlation between temperature and hot coffee sales."
  • "There is a weak positive linear correlation between age and income." (Note: weak, not strong, because the scatter is large.)
  • "There is no linear correlation between shoe size and reading ability."
Common error
Saying only "positive correlation"
Stating just "positive" or just "negative" without a strength word is incomplete. Full marks require both: "strong positive," "moderate negative," etc.
Common error
Confusing direction with strength
"Strong" and "weak" describe how close the points are to a line, NOT how steep the line is. A steep line can still have weak correlation if the scatter is large.
What to write in your book
  • Full description format: [strength] [direction] linear correlation.
  • Options: strong/moderate/weak + positive/negative/no + linear correlation.
  • Never say "positive correlation" alone — always include the strength word.

Complete: A scatterplot showing points tightly grouped along a downward-sloping line would be described as a linear correlation.

PROBLEM 1 · DESCRIBE FROM A DESCRIPTION

A scatterplot of study hours vs exam score shows points rising from lower-left to upper-right, closely grouped around a straight line. Describe the correlation.

1
Direction: points rise from lower-left to upper-right → positive.
As study hours increase, exam scores tend to increase — same direction.
PROBLEM 2 · IDENTIFY THE MATCHING DESCRIPTION

Four scatterplot descriptions: (A) points slope down, tightly grouped. (B) points slope up, widely scattered. (C) random scatter. (D) points slope up, closely grouped. Which matches "weak positive linear correlation"?

1
"Positive" → points slope up. This eliminates (A) and (C).
Positive correlation means both variables increase together — points rise from left to right.
PROBLEM 3 · DESCRIBE A REAL-WORLD PATTERN

A researcher plots the number of cigarettes smoked per day (x) against resting heart rate (y). The points show a general upward trend but with noticeable scatter. Describe the correlation.

1
Direction: upward trend → positive. As smoking increases, heart rate tends to increase.
Both variables go in the same direction.
What to write in your book
  • Step 1: identify direction (slope up/down/none). Step 2: identify strength (tight/scattered). Step 3: write full description.
  • Template: "There is a [strength] [direction] linear correlation between [x variable] and [y variable]."
09
Activity — classify and describe

For each situation below, write a full correlation description (strength + direction + "linear correlation"):

  1. Daily temperature (°C) vs hot coffee sales: points slope steeply down, tightly clustered.
  2. Number of absences vs final grade: general downward trend, wide scatter.
  3. Birth month vs favourite colour: no pattern visible.
  4. Height vs weight for adults: clear upward trend, moderate scatter.
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10
Revisit your thinking

At the start you described the relationship between height and earnings. This relationship, if it exists, would likely be described as a weak positive linear correlation — there is an upward trend (taller tends to earn more in some datasets), but the scatter is large because many other factors (education, occupation, experience) affect earnings much more than height does.

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01
Multiple choice
+5 XP per correct · +25 XP all-correct

Pick your answer, then rate your confidence. Each retry pulls a fresh mix from the bank.

02
Short answer
ApplyBand 33 marks

Q1. A scatterplot shows the relationship between hours of TV watched per day and academic grade (%). The points cluster loosely around a downward-sloping line. (a) What is the direction of this correlation? (b) What is the strength? (c) Write a complete description of the correlation. (3 marks)

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AnalyseBand 42 marks

Q2. A student says: "The scatterplot shows positive correlation." Explain why this description is incomplete and rewrite it in full. (2 marks)

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Answers (click to reveal)

Activity answers: (1) Strong negative linear correlation. (2) Weak negative linear correlation. (3) No linear correlation. (4) Moderate positive linear correlation.

Q1 (3 marks): (a) Negative — as TV hours increase, grades decrease [1]. (b) Moderate — points cluster loosely (not tightly) around the line [1]. (c) "There is a moderate negative linear correlation between hours of TV watched per day and academic grade" [1].

Q2 (2 marks): The description is incomplete because it states only the direction (positive) but not the strength [1]. A complete description requires both: e.g. "There is a strong positive linear correlation between the two variables" [1].

01
Boss battle · Correlation Classifier
earn bronze · silver · gold

Classify direction and strength, write full descriptions, and match patterns. Beat the boss to bank a tier. Replays welcome.

⚔ Enter the arena
02
Science Jump · platform challenge

Climb platforms answering correlation questions. Pool: lesson 02.

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