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Learn t-tests, earn certificates with paid and free online courses from The Open University, Peking University, Vanderbilt University, CU Boulder and other top universities around the world. Read reviews to decide if a class is right for you.
Intro to Inferential Statistics will teach you how to test your hypotheses and begin to make predictions based on statistical results drawn from data!
Learn the statistical concepts and techniques you need to conduct rigorous inferential analysis and draw accurate conclusions from data sets.
Master statistical decision-making in R through hands-on practice with t-tests, ANOVA, chi-square, and non-parametric tests. Apply these methods to real-world data analysis scenarios.
Master statistical analysis through hands-on Python implementation of t-tests, Mann-Whitney U tests, ANOVA, and Chi-Square tests to make data-driven decisions and validate hypotheses.
Discover how to leverage AI tools for creating data visualizations, conducting statistical analyses, and generating clear explanations of patterns and relationships in your data.
Learn hypothesis testing for data science applications, covering theory, implementation, and ethical considerations. Develop skills to make informed decisions from data using statistical inference techniques.
Handling statistical data is an essential part of psychological research. However, many people find the idea of using statistics, and especially statistical software packages, extremely daunting. ...
Learn the key terms and analysis methods in statistics
Increase Your Data Analytic Skills – Highly Valued And Sought After By Employers
In this course you'll learn about basic experimental design, a crucial part of any data analysis.
In this course you'll learn techniques for performing statistical inference on numerical data.
Dive deep into advanced Six Sigma Analyze phase techniques, including hypothesis testing and design of experiments, to enhance process improvement skills and business performance.
Learn about experimental design, and how to explore your data to ask and answer meaningful questions.
Learn advanced statistical analyses in R: correlations, t-tests, ANOVA, regression, and reliability indicators. Step-by-step guidance for parametric and non-parametric tests, with assumption checks and result interpretation.
Develop statistical skills for hypothesis testing in econometrics, covering OLS properties, t-tests, F-tests, and diagnostic techniques to address violations of classical linear regression assumptions.
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