Key Idea: At Higher Level, Topic 6.7 demands more sophisticated statistical analysis, including the application of standard deviation to business contexts, the interpretation of data distributions, and the use of statistical evidence to support business decisions.
Core measures (memorise)
- Mean = total ÷ number of values
- Median = middle value when ordered
- Mode = most frequent value
- Range = highest − lowest
- Standard deviation = average distance from the mean
📊 What each measure helps show: Mean uses all data. Median resists distortion from outliers. Mode is useful for popularity or category frequency. Low standard deviation suggests consistency.
⚠️ What students must notice: Mean can be distorted by outliers. Range only uses two values. High standard deviation suggests volatility. Statistics show patterns, not full explanations.
What HL students should do
- Choose the right measure for the data
- Comment on the effect of outliers
- Interpret what low or high dispersion means for the business
- Use statistics to compare performance, consistency and risk
- Support judgement with context, not numbers alone
Chart construction essentials
- Bar charts must have labelled axes, equal width bars, scale and key if needed
- Stacked bar charts show subcategories within totals
- Pie charts require degree calculations: value ÷ total × 360
- Draw to scale using a ruler or protractor where required
- Presentation marks depend on labels and accuracy
HL answers should not just calculate or identify a measure. The key is interpreting what the result means for decision-making, reliability, consistency or risk.
Evaluation tip: statistics are useful, but they do not explain why something happened and they should be combined with qualitative evidence before making business decisions.
Important: Common trap: students identify the mean or standard deviation correctly but fail to explain whether the data is reliable, representative or useful for the business decision.
- Choose the correct measure or chart
- Show working where required
- Interpret the result in business terms
- Comment on outliers, spread or consistency where relevant
- Explain how the data helps decision-making
- Add a limitation or qualitative counterpoint for HL evaluation