Colleagues, #4 on our Top 10 countdown is Interpreting Data Using Statistical Models with Python. 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, discover how the classic t-test can be used in a variety of common scenarios around estimating means. 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. Upon completion 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. {Pluralsight}
Enroll today (teams & execs welcome): https://tinyurl.com/22xntxa2
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