MS-S1
Data Analysis
Represent, interpret and analyse data using tables, graphs and summary statistics including mean, median and standard deviation.
Sample questions
- 1.The following data shows exam scores: {45, 52, 63, 71, 71, 82, 94}. Find the mean, median, and IQR.
Exam weighting
5–8 marks — data interpretation is consistently tested.
Common student mistakes
- ·Confusing mean, median and mode when data is skewed
- ·Using a population formula instead of sample standard deviation
- ·Misreading box-and-whisker plots
MS-S2
Relative Frequency and Probability
Use relative frequency and theoretical probability to solve practical problems and model random experiments.
Sample questions
- 1.A spinner has 3 red, 5 blue, and 2 green sections. Find P(not red).
Exam weighting
2–4 marks.
Common student mistakes
- ·Confusing 'at least' with 'exactly' in probability problems
- ·Not listing all outcomes in a sample space
MS-S4
Bivariate Data Analysis
Investigate relationships between two variables using scatterplots, correlation coefficients and lines of best fit.
Sample questions
- 1.A scatterplot shows study hours vs exam scores. Describe the correlation and use the line of best fit to predict the score for 4 hours of study.
Exam weighting
3–5 marks — interpreting a given scatterplot is typical.
Common student mistakes
- ·Confusing correlation with causation
- ·Incorrectly reading/interpolating from a line of best fit
MS-S5
The Normal Distribution
Apply the properties of the normal distribution and z-scores to interpret and compare data sets.
Sample questions
- 1.Test scores are normally distributed with mean 65 and SD 10. What percentage of students scored between 55 and 85?
Exam weighting
3–5 marks — z-score calculations and interpretation.
Common student mistakes
- ·Forgetting to include both tails when using the 68-95-99.7 rule
- ·Using wrong mean or SD when standardising
Other Standard 2 topics
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