Grade 4
Arithmetic Mean
This test develops calculation of the arithmetic mean by adding all values and dividing by the number of values. Tasks also involve finding a missing data value and interpreting an average in a practical context.
Tests by topic
Statistics
These tests help build a secure understanding of each topic and its solution methods. Choose a test for your school level and work at your own pace.
Tests by topic
Tests for this topic
Grade 6
Mean, mode and median
This test develops the ability to calculate and interpret the arithmetic mean, mode, median and range. Tasks require students to order data, read frequency tables and choose the most appropriate measure of centre for a situation.
Grade 7
Pie charts and samples
Dynamic tasks on sectors, percentages and data represented by pie charts. The test also checks understanding of representative samples and sampling methods.
Grade 8
Histograms and grouped data
Dynamic tasks on reading histograms, interval frequencies, relative and cumulative frequencies, and estimated means.
Grade 8
Quartiles and box plots
Dynamic tasks on medians, quartiles, interquartile range, outliers and reading box-and-whisker plots.
Grade 9
Scatter plots and correlation
Dynamic correlation direction, trend-line prediction, sample reliability and causation interpretation.
Grade 10
Variance and standard deviation
This test develops calculation and interpretation of the mean, variance and standard deviation. Tasks compare data spread, examine the effect of outliers and assess whether a sample reliably represents a population.
Grade 12
Statistical study and data interpretation
This test develops planning of a statistical investigation and justified interpretation of data. Tasks cover populations, samples, variable types, the mean, standard deviation, outliers and the reliability of conclusions.
Grade 12
Correlation and linear model
This test evaluates relationships between two variables using correlation and a linear model. Students interpret the correlation coefficient and R², calculate predictions and residuals and assess model suitability and the limits of causal conclusions.