This module is aimed at students who are taking their first course in statistics but have background knowledge of probability. This module introduces students to fundamental statistical concepts and elementary statistical analysis.
The following is a list of the specific topics this module covers.
 Data Presentation:

Histograms, ungrouped data, grouped data, ogives, frequency table, frquency histogram, relative frequency histogram.
 Measures of Central Tendency:

Sample mean, sample mode, sample median, expected value, weighted mean, properties of the mean.
 Measures of Dispersion:

Range, mean deviation, mean squared deviation, expected squared deviation, variance, standard deviation, weighted variance, skewness, kurtosis,
properties of the variance.
 Samples:

Populations, samples, random samples, random sampling, stratified samples, Central Limit Theorem, small versus large samples, Student's t distribution, degrees of freedom.
 Estimation:

The mean as a random variable, the variance as a random variable, the mean and variance of one sample, the means and variances of two samples,
the proportion and variance of one sample, the proportions and variances of two samples.
 Confidence Intervals:

Confidence intervals of one mean, one proportion, one variance, two means; confidence intervals of the difference in two means, two proportions,
two variances; minimum sample size determination, level of significance, level of confidence.
 Questions: 850 practice questions with explained solutions.
Prerequisites for this Module
This module requires prior knowledge of probability such as that in the Introduction to Probability module. Prior probability knowledge must include an emphasis on the normal probability distribution.
This module is a prerequisite for the Statistics I module on hypothesis testing.