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The probability density function (PDF) is a statistical expression that defines the probability that some outcome will occur. In this function, the probability is the percentage of a dataset's distribution that falls between two criteria.

Statistics is the science deals with collection, classification, summarizing, organizing and interpretation of data to make inference and draw conclusions based on data. While statistic (as a singular) is a single measure of some attribute of a sample.

What are the types of statistical analysis? There are two main types of statistical analysis: descriptive and inferential, also known as modeling.

Probability Density Function (PDF) vs Cumulative Distribution Function (CDF) The CDF is the probability that random variable values less than or equal to x whereas the PDF is a probability that a random variable, say X, will take a value exactly equal to x.

We begin by introducing two general types of statistics: Descriptive statistics: statistics that summarize observations. Inferential statistics: statistics used to interpret the meaning of descriptive statistics.

Descriptive statistics is used to summarize and describe data, while inferential statistics is used to make inferences and predictions about a population based on a sample of data.

Descriptive and Inferential Statistics The two major areas of statistics are known as descriptive statistics, which describes the properties of sample and population data, and inferential statistics, which uses those properties to test hypotheses and draw conclusions.