Topic 3.6

Data Analysis, Interpretation & Statistics

Analysing patterns, calculating statistics, and explaining results using geographical theory

Analysis = WHAT

Describing patterns in data - what the numbers/graphs show

"River width increased from 2m to 12m"

Interpretation = WHY

Explaining WHY patterns occur - link to geographical theory/processes

"...due to tributary inputs increasing discharge, as Bradshaw model predicts"

Statistical Techniques

Mean (Average)

Sum of all values ÷ Number of values

Use: Compare typical values between sites

Limitation: Affected by outliers (extreme values)

Median

Middle value when data is ordered

Use: When data has outliers (less affected than mean)

Advantage: Not skewed by extreme values

Mode

Most common/frequent value

Use: Categorical data, identifying typical value

Limitation: May be no mode or multiple modes

Range

Maximum value - Minimum value

Use: Compare variation/spread between sites

Large range = high variability, small range = consistent

Interquartile Range (IQR)

Q3 - Q1 (range of middle 50%)

Use: Better than range if outliers present

Advantage: Removes extreme outliers from calculation

Percentage Change

((New - Old) ÷ Old) × 100

Use: Comparing change over time or distance

Shows proportional change, not just absolute difference

Statistics Calculator Practice

Practice calculating mean, median, mode, range, and percentage change

Question 1 of 5Score: 0/0

Mean

Sum of all values ÷ Number of values

Pebble sizes (cm): 5, 8, 6, 7, 9

cm

Describing Data from Graphs

Line Graphs - Describing Trends

  • Overall trend: "Generally increasing/decreasing/stable"
  • Specific changes: Quantify with numbers ("increased from 2m to 12m")
  • Rate of change: Where is change fastest/slowest?
  • Anomalies: Any values that don't fit the pattern?

Bar Charts - Describing Patterns

  • Comparisons: Use multipliers ("3.75× higher")
  • Similarities/differences: Group similar values
  • Categories: Rank from highest to lowest

Scatter Graphs - Describing Relationships

  • Correlation type: Positive, negative, or none
  • Strength: Strong (close to line), weak (scattered), moderate
  • Anomalies: Points far from line of best fit
  • r value: Quote if given (±0.7-1.0 = strong)
Graph Description Practice

Learn to write strong analytical descriptions of graphs and data

Question 1 of 3Score: 0/0
Line Graph - Trend

River width increases from 2m at Site 1 (source) to 12m at Site 6 (mouth) over 10km distance.

Which description best analyses this trend?

Interpreting Data (Linking to Theory)

Interpretation means explaining WHY patterns occur by linking to geographical theory:

Quote specific data: "15m movement", "decreased from 12cm to 3cm"

Reference theory: "Bradshaw model predicts...", "Urban decline cycle suggests..."

Link cause and effect: "BECAUSE attrition erodes particles, THEREFORE size decreases"

Consider alternatives: "However, human management may also affect..."

Interpretation Builder

Build interpretations by linking analysis to theory and processes

Scenario 1 of 3
TheoryProcessFull Answer
River Fieldwork

Analysis (WHAT):

Bedload size decreased from 12cm mean at Site 1 to 3cm at Site 6

Step 1: Which geographical theory does this relate to?

Weak vs Strong Answer Comparison

Question: "Analyse the data shown in Figure X (graph showing river width increasing from 2m to 12m over 10km distance)." (4 marks)

Weak Answer

1-2/4 marks

"The river gets wider as you go downstream. It starts at 2m and ends at 12m. This is what happens to rivers."

Why weak:

Basic description only
Doesn't quantify change
No explanation WHY
Doesn't reference theory
Generic statement

Strong Answer

4/4 marks

"River width increases progressively from 2m at the source to 12m at 10km downstream, a 500% increase. The rate of widening is greatest in the first 4km (2m to 8m = 6m increase), then slows in the lower course (8m to 12m = only 4m increase over remaining 6km). This supports Bradshaw model which predicts channel width increases downstream as discharge rises due to tributary inputs adding water. The faster widening in upper/middle course corresponds to where the OS map shows major tributary confluences at 2km and 5km, explaining the steepest increases at those points."

Why strong:

Quantifies change (500%)
Describes rate of change variation
Links to Bradshaw theory explicitly
Explains cause (tributary inputs)
Uses additional evidence (OS map)
Chain of reasoning clear
Key takeaway: Analysis = WHAT you see (describe patterns with specific data). Interpretation = WHY it happens (explain causes using geographical theory).

Limitations & Evaluation

Reliability Issues

Sample size: Too small to be representative

Timing: Only one time of day/year

Location bias: Only sampled certain areas

Weather: Conditions affected results

Subjectivity: Personal opinion varies

Accuracy Issues

Equipment precision: Limited accuracy

Human error: Inconsistent measurements

External factors: Uncontrolled variables

Method limitations: Technique doesn't capture true value

Limitations & Evaluation Practice

Identify limitations and suggest improvements for fieldwork methods

Scenario 1 of 3

Questionnaire Survey

20 questionnaires completed at shopping center, 2pm on a Tuesday

Click to reveal limitations (try to think of them first!):

Grade 8/9 Analysis Approach

Quantify: Use specific numbers, not vague terms

Calculate: Mean, %, range shows data processing

Identify anomalies: Note + explain outliers

Link sources: Primary data + secondary evidence

Name theories: Bradshaw, bid-rent, etc.

Evaluate critically: Acknowledge limitations

Data Analysis Quiz

Question 1 of 5 | Score: 0

What is the difference between analysis and interpretation?

Worked Example4 marks

Analyse the data shown in Figure X (graph showing pebble size decreasing from 12cm to 3cm mean over 6 sites downstream). (4 marks)

Key Terms

Analysis

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Describing patterns in data - WHAT the results show (e.g., 'pebble size decreased from 12cm to 3cm')

Interpretation

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Explaining WHY patterns occur by linking to geographical theory and processes

Correlation

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Statistical relationship between two variables - positive (both increase), negative (one increases as other decreases), or none

Anomaly

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A data point or result that doesn't fit the expected pattern - requires explanation

Reliability

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Whether results are consistent and repeatable if the study was conducted again

Accuracy

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How close measurements are to the true value - affected by equipment and human error