This project dedicates to completing the final project in the probability course by Paccman. In this project, we will tell about the probabilities that may appear in insurance data. This project contains descriptive statistics, categorical variable analysis (PMF), continuous variable analysis (CDF), variable correlation analysis, and hypothesis testing. This analysis will answer several research questions.
Descriptive statistics are brief informational coefficients that summarise a given data set, representing the entire population or a population sample. Descriptive statistics consist of measures of central tendency and variability (spread). Categorical variable analysis (PMF) Categorical data analysis is the data analysis where the response variable has grouped into a set of mutually exclusive ordered (such as age group) or unordered categories.
A random variable X is continuous if possible values comprise either a single interval on the number line or a union of disjoint intervals.
The statistical method measures the strength of the linear relationship between two variables and computes their association. Simply put - correlation analysis calculates the level of change in one variable due to the change in the other.
Hypothesis testing is a statistical act whereby an analyst tests an assumption regarding a population parameter. The methodology employed by the analyst depends on the data used and the reason for the analysis. Hypothesis testing uses to assess the plausibility of a hypothesis by using sample data.
For a more comprehensive understanding of the results and methodology, we suggest referring to the medium article. The article provides an in-depth analysis and explanation of the findings and provides a comprehensive overview of the research process.