Welcome to your first lesson in Statistics for Actuarial Science! During this course, you will get to know how actuaries use data to make strategic decisions, primarily in fields such as risk management and insurance. If you are new to statistics, there is no need to worry, we will develop all of that in a simple and practical manner. Let's start with the most basic question: What is data?
Data is the raw form of information, as it consists of unstructured facts, figures, or observations that must be processed to provide details about a certain event. We can make data useful by processing, organizing or presenting data in a particular way. At that stage, it is known as information.
| Data (raw) | Information (processed) |
|---|---|
| Age: 25, 55, 87 | Average age = 55.67 |
| Claim: $300, $5000, $300 | Most frequent claim = $300 |
An insurance company keeps data records for all policyholders such as, age, gender, policy type, whether the claim was made or not and annual premium. All of them represent a unique piece of data that behaves differently in statistical analysis.
Data is typically categorized into two main types:
Categorical data consists of values that are grouped into categories based on names or labels. These categories describe qualities or characteristics rather than numerical quantities. While the frequency of each category can be counted, the categories themselves cannot be meaningfully added, subtracted, multiplied, or divided.
Examples:Numerical data is a type of statistical data which can be measured, counted or expressed in the form of numbers. The numerical or quantitative data is most common form of data and can be used for calculations, such as averages, mean, median, and others.
Examples:Numerical Data can be of two types:
A variable whose possible values can be listed or counted. Values occur with a jump or break. Quantitative data that measure "how many" are discrete.
Examples:This type of data can take any value within a specified range, which includes decimals and fractions.
Examples:Actuaries rely mainly on data to do their job. They apply it in estimating the future risks, charging fair and accurate insurance premiums and in knowing how customers will behave when they are buying insurance products.
Example: The insurance company will charge a higher life insurance premium from person who has unhealthy habits like smoking as compared to the person maintaining a healthy lifestyle.
Fantastic beginning! You learned the definition of data and its many forms, such as numerical and categorical data, in this session. Additionally, you saw how data appears in real actuarial and insurance contexts. Large datasets will be much simpler to comprehend when we learn how to arrange data using frequency tables and grouped data in the upcoming lesson. Now, attempt the questions. They will help you judge if you understand the content.