Welcome to "Statistics for Data Analysts and Scientists" - the ultimate course to help you master the practical and business applications of essential statistical tests and concepts!

Are you struggling to make sense of statistical tests like the Chi Square test of independence, t-tests, correlation, and Analysis of Variance (ANOVA)? Are you looking to understand how these tests can be applied in real-world situations, and how they can be used to drive critical business decisions?

This comprehensive course is designed to equip you with the knowledge and skills to excel as a data analyst or scientist. You will learn how to conduct and interpret key statistical tests such as the one-sample t-test, independent sample t-test, dependent sample t-test, correlation, simple and multiple linear regression, and one-way ANOVA. You will also gain a deep understanding of key statistical concepts like homoscedasticity of variance, multicollinearity, and homogeneity of variance.

With an exciting and engaging teaching style, this course will take you on a journey of discovery that will transform your understanding of statistics. You will learn through a combination of theory, practical examples, and case studies that will help you understand how statistical tests can be applied in real-world situations.

By the end of this course, you will have the confidence and expertise to apply statistical tests and concepts to drive critical business decisions. You will be able to use statistical tools to gain insights into complex data sets, and you will be equipped with the skills to communicate these insights to key stakeholders.

So, what are you waiting for? Sign up for "Statistics for Data Analysts and Scientists" today, and take the first step towards becoming a master of statistical analysis!

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Chapters
00:00 Intro
01:08 Intro to Statistics
05:20 Statistical Scale of Measurement
11:20 Common Statistical Terms
17:23 Downloading IBM SPSS
18:32 Course Resources
19:06 Understanding Inferential Statistics
26:56 Chi Square Test of Independence
38:39 One Sample t-test
50:20 Independent Sample t-test
01:02:06 Paired Sample t-test
01:11:16 Pearson Correlation Analysis
01:22:16 Course Outro

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