Tables, averages, range and bar-chart conclusions
Read a data table, select and interpret central tendency and range, inspect bar-chart format and draw a conclusion linked to an aim.
Section Paper 1 · Paper 1 · Topics 1–3 and experimental method
Original teaching mapped to Cambridge IGCSE Psychology 0266 Version 3 for 2027–2029. The course is independent study support, not Cambridge material, an official mark scheme or an awarded grade. Named-study notes summarise the required findings; candidates are not expected to evaluate named studies. Self-check practice is not official grading, a timed Paper 1/2 simulator or teacher review.
Before you begin
- Use the Version 3 syllabus and confirm availability in your administrative zone with Cambridge and your school. Both papers are compulsory. The updated named-study summaries are required context; full original research articles are not required.
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
Before tables, averages, range and bar-chart conclusions, which approach is most useful?
What you will learn
- Read and structure tables with headings and units
- Select and interpret mean, median or mode and range
- Recognise correct bar-chart axes, labels, spacing and units
- Draw a cautious conclusion from a table or bar chart
Good tables make comparisons readable
Use rows and columns with clear row and column headings and units where appropriate. Information may be presented in prose, tables or bar charts. A reader should be able to identify what each value represents without guessing.
Choose a typical value and describe spread
The mean is the arithmetic average, the median is the middle score after ordering, and the mode is the most frequent score. A measure of spread shows how similar or different values are; range is highest minus lowest. Cambridge states that candidates are not expected to calculate central-tendency measures or range, so practice here focuses on selecting and interpreting supplied values.
Bar charts show category comparisons
A bar chart has labelled axes, suitable bar placement and units where appropriate. The scale should be clear and bars should be separated to show categories. A conclusion describes the pattern and states whether it supports the research aim; it should not claim more than the data show.
Pause and explain
Which response best shows understanding of tables, averages, range and bar-chart conclusions?
Worked example
A table gives mean recall scores: quiet room 8, noisy room 5. The aim was to test whether noise affects recall. State a cautious conclusion.
Show the worked solution
- Compare the supplied means.
- Recall was higher in the quiet condition.
- Relate the pattern to the aim without claiming universal proof.
Answer In this sample, recall was higher in the quiet condition, which is consistent with noise reducing recall; the result does not establish that it happens for everyone.
Try a topic test
Choose Easy, Normal or Difficult. Save your answers and open worked review after finishing.
Test this topic →From guided practice to a new situation
Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.
A chart compares mean accuracy for two conditions: A = 12 correct, B = 9 correct. Which condition is higher and what should the conclusion say?
Give me a hint
Read the values, then relate them to the measured outcome.
Compare my reasoning
- Condition A has the higher supplied mean.
- The difference is three correct responses in this sample.
- Conclude that A performed higher here, without claiming the difference is universal.
Condition A was higher by three responses in this sample; avoid a claim beyond the data.
Look for these in your work
- Reads the chart
- States the comparison
- Keeps the conclusion cautious
A data table has numbers but no units or column headings. What two changes make it interpretable?
Give me a hint
Tell the reader what each column and score means.
Compare my reasoning
- Add a descriptive heading to each column.
- Add units for values where they apply.
- Keep row labels clear so each result can be located.
Add clear row/column headings and units where appropriate.
Look for these in your work
- Names headings
- Includes units
- Recognises row labels
A bar chart shows higher reported helping in one group, but the groups were not randomly assigned. What conclusion is justified?
Give me a hint
Describe the association and avoid a causal leap.
Compare my reasoning
- The chart shows a difference in reported helping.
- The design does not isolate the group factor from all other influences.
- State the pattern, but do not claim group membership caused it.
Reported helping was higher in that group in this sample; the chart alone does not show group membership caused the difference.
Look for these in your work
- Describes observed pattern
- Considers design
- Avoids causal overreach
Common mistakes
- Ignoring row labels or units.
- Calculating averages or range when the paper expects selection/interpretation.
- Claiming a bar-chart pattern proves causation without a suitable design.
What can you explain now?
What does the range describe?
Compare with the explanation
The difference between the highest and lowest values
Range is a simple measure of spread.
After trying it yourself, choose your next review. This is your self-assessment.
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Make it stick
How do clear tables and charts help you select a measure, describe spread and draw a conclusion linked to the aim?
If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.