Learners will be introduced to the processes involved in the collection and preliminary scrutiny of the data. The goal of this unit is to help learners effectively summarize large data sets by the application of appropriate graphical or numerical techniques.

Probability distributions are mathematical functions that associate an outcome of a statistical experiment with its likelihood of occurrence. There are two types of probability distributions – Discrete probability distribution and Continuous probability distribution.

In this unit, learners will be introduced to the topics of probability and discrete probability distribution. The goal of this unit is to enable learners to make informed decisions by reducing the risk of uncertainty through the application of theory of probability.

Statistics as a subject deals with variables which vary over time, space and units of study. These variables have a definite pattern which is unique to them. Without a knowledge of this pattern, evaluation of probabilities of events associated with the variable is not feasible. These patterns are known as distributions in statistical parlance. In this unit, learners will study the concepts of Continuous and Sampling distributions.

Statistics deals with variables. Variables exhibit patterns and these patterns are known as distributions. Distributions are functions of the variable and they also involve parameters. Parameters are population characteristics and hence most often are unknown due to the size of the population. Hence, the best method to estimate these unknown parameters is from a small sample data. However, a single value as estimate or a point estimate may not always provide the desired result therefore a small interval of possible values or an interval estimate is considered.

In addition to Point and Interval estimation techniques, learners will be introduced to the concept of Testing of Hypothesis in this unit.

A hypothesis test is a statistical test that is used to determine whether there is sufficient evidence in a sample of data to conclude that a certain hypothesis is true for the entire population. This test examines two opposing hypotheses about a population: the null hypothesis and the alternative hypothesis. This test can also be extended to two populations or samples. These different possibilities are discussed in detail in this unit.

Additionally, learners will also study about Chi-Square test which is a statistical method to evaluate the goodness of fit between a set of observed values and those expected theoretically.

Regression analysis is a statistical analysis technique which can be used to ascertain the relationship between a dependent variable and one or more independent variables. Correlation analysis helps in estimating the strength of a relationship between two variables. Both these techniques aid in understanding and quantifying the relationship between two or more variables.