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According to Towards Data Science, a data science business blog, descriptive statistics include normal distribution (bell curve), central tendency (mean, median, and mode), variability (25 percent, 50 percent, 75 percent quartiles), variance, standard deviation, modality, skewness, and kurtosis.

The procedure of completing numerous statistical operations is known as statistical data analysis. It is a type of quantitative research in which the goal is to quantify the data using some form of statistical analysis. Descriptive data, such as survey data and observational data, are examples of quantitative data.

The most common method for examining quantitative research data is statistical analysis. It use probability and models to assess population predictions based on sample data. What makes descriptive statistics different from inferential statistics? The properties of a data set are summarised using descriptive statistics.

The process of analysing, cleansing, manipulating, and modelling data with the objective of identifying usable information, informing conclusions, and assisting decision-making is known as data analysis.

Statistics literally means "numerical data," and it is a branch of mathematics that deals with data gathering, tabulation, and interpretation. It's a type of mathematical analysis that use several quantitative models to generate a set of experimental data or real-world research.

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