Mean:

The mean is the sum of scores divided by the number of scores.

 where is the number of scores.

Mode:

Mode of a set of data is the value in the set that occurs most often.

Range:

The range of a set of data is the difference between the highest and lowest values in the set.

Variance:

The variance of a sample measures how the conservations are spread around the mean.

Standard Deviation:

The standard deviation is the square root of the average of the squared deviations from the mean (variance).

Categorical frequency distributions:

Categorical frequency distributions can be used for data that can be placed in specific categories, such as nominal- or ordinal-level data.

Central Limit Theorem:

As the sample size increases the sampling distribution of the sample mean approaches the normal distribution with mean and variance .

 The exponential, binomial, and normal density functions:

The exponential, binomial and normal density functions are used to approximate statistical models and values.

Flash Movie	Flash Game	Flash Card
Core Concept Tutorial	Problem Solving Drill	Review Cheat Sheet

This tutorial mentions statistics and its different applications. Problem solving methods for statistics are mentioned in the examples. Knowing the data and its different aspects are important to the understanding of histograms and bar charts in statistics. The measures of central tendency are exhibited with the use of graphical representation.

The measures of variability, range, deviation and standard deviation are important principles that are used in statistical problems. Hypothesis testing and the different types of error are presented in this tutorial. The Central Limit Theorem is defined and how it is applied to the different types of probability distributions.

Specific Tutorial Features:

• Examples showing the calculation of the mean, mode and variance are presented.
• Hypothesis testing is presented with different alternatives and the use of examples.

Series Features:

• Concept map showing inter-connections of new concepts in this tutorial and those previously introduced.
• Definition slides introduce terms as they are needed.
• Visual representation of concepts
• Animated examples—worked out step by step
• A concise summary is given at the conclusion of the tutorial.

Basic concepts of statistics
           Problem solving methods
           Measures of central tendency
           Mean
           Mode
           Midrange
           Range
           Variance 
           Standard Deviation
           Random Variable
           Frequency Distribution and its graph
Stem-and-Leaf Plot
Probability Distribution Graph
Testing Hypothesis
Alternative and Null Hypothesis
Central Limit Theorem