Understanding Data Types and Variables in Statistics

This course introduces you to the world of data collection and analysis and teaches you how to measure associations between variables. Have you wondered what exactly statistics can do or the purpose of analysing data? Firstly, we will explain the role of statistics in answering questions using data or information pertaining to a particular situation. By studying the actual definition of statistics and the primary difference between the terms ‘statistics’ and ‘statistic’, you will discover how statistics is a crucial process behind the discoveries presented in science by making decisions and predictions based on data. Next, you will be taught about a statistical procedure concerned with selecting the individual observations to draw inferences about the population. For example, you will determine how samples are used in statistical testing when population sizes are too large for the test to include all possible members or observations. Following this, we explain the procedure for summarising the data from a sample of the entire population. This method consists of using graphical and numerical techniques to transform data into information.

The course illustrates the methods of recognising different types of data used in statistics. You will learn how understanding data types are a crucial prerequisite for applying appropriate statistical measurements from the data at hand. Following this, you will study the data type grouped according to the variables present in the dataset. You will explore the need for organising observations into groups that share a common trait to understand and extract valuable information from the data. Subsequently, you will study the methods of displaying categorical data using graphical and numerical summaries. We delve into the common forms of describing categorical data, namely frequencies, proportions, marginal and visualisation techniques. Next, you will investigate a data type that expresses the information in numbers for performing arithmetic operations. You will notice how numerical data provides an organisation with accurate inferences for critical decision-making without emotional or inaccurate bias.

The course outlines the significance of incorporating information about shape, centre, spread and unique features commonly used in describing numerical data. You will examine how to represent numerical data using graphs and the importance of expressing numerical data in words. Following this, you will study the various factors used to quantify a relationship between two or more variables. You will uncover how to use correlation, regression and coefficients to determine the association among variables. We also explain the appropriate methods for investigating the relationships between two categorical variables. You will realise how the chi-square measures the association between two categorical variables and how contingency analysis quantifies their association. Finally, you will be taught about the process of finding the relationship among numerical variables. You will research how linear, quadratic and exponential functions are standard models used to describe the relationship among numerical variables. Statistics are the sets of mathematical equations used to analyse various data. In today’s world, most day-to-day information is determined by statistical analysis. Statistical knowledge thus helps you use the proper methods to collect data, employ the correct calculations and effectively present the results. Why wait? Sign up today and become proficient in descriptive and inferential statistics while you discover what data science can do for you!