PluralSight – Interpreting Data Using Statistical Models With Python-JGTiSO
English | Size: 359.00 MB
Category: Tutorial
Data science and data modeling are fast emerging as crucial capabilities that every enterprise and every technologist must possess these days. Increasingly, different organizations are using the same models and modeling tools so what differs is how those models are applied to the data. Today, more than ever, it is really important that you know your data well
In this course, Interpreting Data using Statistical Models with Python you will gain the ability to go one step beyond visualizations and basic descriptive statistics, by harnessing the power of inferential statistics
First, you will learn how hypothesis testing, which is the foundation of inferential statistics, helps posit and test assumptions about data Next, you will discover how the classic t-test can be usedin a variety of common scenarios around estimating means You will also learn about related tests such as the Z-test Pearson s Chi-squared test, Levene s test and Welch s t test for dealing with populations that have unequal variances
Finally, you will round out your knowledge by using ANOVA, a powerful statistical technique used to measure statistical properties across different categories of data. When you re finished with this course, you will have the skills and knowledge to use powerful techniques from hypothesis testing, including t-tests, ANOVA and regression tests in order to measure the strength of statistical relationships within your data
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