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Statistics and Analysis - Lesson Summary

Qualitative data refers to a variable that cannot assume a numerical value, but that can be classified into two or more non-numeric categories whilst quantitative data refers to a variable that can be measured numerically.
Descriptive statistics refers to the methods that are used to organize, display, describe data through the use of tables, summary measures and graphs.
Inferential statistics consists of methods that use sample results to help make decisions or predictions about a population.
The frequency distribution of qualitative data lists all categories and the number of elements that belong to each of the categories.
The frequency distribution of quantitative data lists all the classes and the number of values that belong to each class.
If a continuous random variable has a distribution with a graph that is symmetric and bell-shaped, it is classified as having a normal distribution.
Machine Learning refers to computers' programming to optimize a certain performance criterion using example data or past experience. It can automatically detect patterns in data and use them to predict future outcomes of interest.
The most important aspect to consider when creating a model is having sound knowledge of the problem you intend to solve. This is critical since the quality of the output depends upon the quality of the inputs.
Univariate data analysis refers to the data that has only one variable, and its major purpose is to describe, summarize and find patterns in the data.