Edexcel Statistics S1 Tuition
Mathematical models in probability and statistics
The basic ideas of mathematical modelling as applied in probability and statistics.
Representation and summary of data
Histograms, stem and leaf diagrams, box plots.
Measures of location — mean, median, mode.
Measures of dispersion — variance, standard deviation, range and interpercentile ranges.
Skewness.
Concepts of outliers.
Probability
Elementary probability.
Sample space.
Exclusive and complementary events.
Conditional probability.
Independence of two events.
Sum and product laws.
Correlation and regression
Scatter diagrams.
Linear regression.
Explanatory (independent) and response (dependent) variables.
Applications and interpretations.
The product moment correlation coefficient, its use, interpretation and limitations.
Discrete random variables
The concept of a discrete random variable.
The probability function and the cumulative distribution function for a discrete random variable.
Mean and variance of a discrete random variable.
The discrete uniform distribution.
The Normal distribution
The Normal distribution including the mean, variance and use of tables of the cumulative distribution
function.
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