Understanding probability and statistics is indispensable in the contemporary world where print and electronic media are full of statistical information and interpretation. This course aims to explain the fundamental concepts of probability and statistics with a wide range of applications. It illustrates the significance of statistics to make decisions using models involving data. You will discover the science concerned with developing and studying methods for collecting, analysing, interpreting and presenting empirical data. Next, we explain the various types of data measurement scales in statistics. You will explore the importance of recognising different data types for performing various kinds of statistical analysis. In addition to this, we outline the methods of categorising and classifying multiple data types. Following this, you will study the concept of cases and variables in statistics. This includes measuring a characteristic that can take on different values. Finally, we will describe the procedure for collecting data at single and successive data points using cross-sectional and time-series methods.

The course explains the methods of presenting various types of data in charts. You will discover how the bar chart conveniently illustrates a categorical variable and summarises categorical data using ‘median’ and ‘mode’. You will study the core principles in describing numerical data in statistics before exploring the process of defining categorical variables based on tabulating their frequencies or probabilities and the importance of contingency analysis in quantifying their association. Next, we discuss the strategies of ascertaining the relationship between two or more numerical variables. This will include the significance of the dependent variable in manipulating the independent variable. Subsequently, we explore the various fundamental aspects of probability studies. You will learn to apply the rules of probability to determine the measure of the likelihood of an event occurring. This will include predicting the certainty of an event through various illustrative examples.

Finally, we will teach you about deriving conditional probability equations from the multiplication rule. We also explain the role of a tree diagram in calculating the probabilities during dependent and independent events. You will comprehend the significance of random variables in mapping the outcomes of a random process to a numeric value. In addition, we will illustrate the process of determining the various measures of association and correlation between two or more random variables. Lastly, the course explains modelling count data using multiple probability distributions. You will ascertain the need for a rich class of probability distributions in modelling flexible and generalised count data distributions. ‘Diploma in the Foundations of Probability and Statistics’ is an informative course that provides essential knowledge on statistical reasoning to quantify the uncertainties’ concerned with a random event. The course lays the foundation to make the learners sensible, critical users of probability and statistics, applying processes and principles to real-world problems. Enrol in this course and learn to judge whether the statistics and probability are meaningful and used appropriately.