Sampling Methods
Random Sampling
Systematic Sampling
Quota Sampling
Cluster Sampling
Convenience Sampling
Stratified Sampling
Systematic Sampling
Quota Sampling
Cluster Sampling
Convenience Sampling
Stratified Sampling
Statistical Charts
Drawing and interpreting bar charts (include comparative and component bar charts), pie charts (including comparative pie charts) line graphs and histograms.
Using a spreadsheet to draw charts and graphs.
Describe the shape of distributions using terms such as symmetrical, skewed, multi-modal.
Interpreting complex charts eg line graph superimposed on bar chart and any charts or graphs related to students’ other studies.
Extension Opportunities – other appropriate diagrams eg stem & leaf.
Revision Task- What do I know? Make up your own questions for a grouped frequency table
Using a spreadsheet to draw charts and graphs.
Describe the shape of distributions using terms such as symmetrical, skewed, multi-modal.
Interpreting complex charts eg line graph superimposed on bar chart and any charts or graphs related to students’ other studies.
Extension Opportunities – other appropriate diagrams eg stem & leaf.
Revision Task- What do I know? Make up your own questions for a grouped frequency table
Statistical Measures
Find mean, mode, median, range, quartiles and standard deviation of data from a list and from a frequency table. Consider outliers and include using both a calculator and spreadsheet.
Use of a cumulative frequency graph to find the median, quartiles and percentiles.
Compare and contrast data sets using statistical charts and measures.
Extension Opportunity – box & whisker.
Handling Data Revision Cards
Handling Data Revision
Use of a cumulative frequency graph to find the median, quartiles and percentiles.
Compare and contrast data sets using statistical charts and measures.
Extension Opportunity – box & whisker.
Handling Data Revision Cards
Handling Data Revision
Finding Information from Complex tables: Percentages and Reverse Percentage
Include calculation of percentages and ‘reverse’ percentages
Correlation and Regression
Definition of independent and dependent (controlled and response) variables.
Plot scatter diagrams of bivariate data, including the mean point and draw a line of best fit by eye. Understand positive, negative, strong, weak and no correlation.
Calculation and interpretation of the product-moment correlation coefficient (using both a calculator and spreadsheet).
Include the fact that correlation does not necessarily imply cause and effect, that a third variable may underlie correlation and that not all relationships are linear.
Discuss the principle of least squares. Find the equation of a regression line using both a calculator and spreadsheet. Draw the regression line (by hand and spreadsheet) and interpret regression coefficients in context.
Extension Opportunity – rank correlation coefficients, non-linear models.
Plot scatter diagrams of bivariate data, including the mean point and draw a line of best fit by eye. Understand positive, negative, strong, weak and no correlation.
Calculation and interpretation of the product-moment correlation coefficient (using both a calculator and spreadsheet).
Include the fact that correlation does not necessarily imply cause and effect, that a third variable may underlie correlation and that not all relationships are linear.
Discuss the principle of least squares. Find the equation of a regression line using both a calculator and spreadsheet. Draw the regression line (by hand and spreadsheet) and interpret regression coefficients in context.
Extension Opportunity – rank correlation coefficients, non-linear models.
The Normal Distribution
The use of theoretical probability distributions to model populations.
Features of normal distributions:
• continuous variable
• unimodal
• symmetrical
• mean = mode = median
• approximately two-thirds of the distribution lies within one standard deviation of the mean
• approximately 95% of the distribution lies within two standard deviations of the mean
The standard normal distribution with mean 0 and variance 1.
Use of the standard normal table to find probabilities and expected frequencies.
Use of the standard normal table in reverse calculations.
Extension Opportunities – other probability distributions eg uniform, binomial, Poisson.
Significance tests – t, z, Mann Whitney, Wilcoxin signed rank, chi-squared.
Hypothesis Testing Tutorial
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