Delve into modern statistical analysis with R. Gain insights into data description, linear modeling, advanced techniques, and GLMs. Discover how to effectively interpret and analyze real-world models.

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R is a widely used programming language for statistical computing. It features robust libraries that cover everything from basic data analytics to visualization functions for presentation. R is used by professional data scientists, researchers, and marketers.

This course is a comprehensive introduction to modern statistical analysis using R, particularly for researchers in life and environmental sciences. You’ll review R and cover its functionality with its various packages. You'll review essential statistical functions including data description, linear modeling, regression analysis, and more. You’ll also cover advanced analytical techniques looking at analysis of variance, factorial designs, and non-normal data distributions. You’ll also discuss generalized linear models, including binomial GLMs and GLMs for binary data. 

By the end of this course, you’ll be prepared to apply statistical methods to real-world problems and interpret and analyze various models in an effective contemporary manner.

Performing Modern Statistical Analysis with R

The statistical analysis technique will capture the true parameter 95% of the time.

We can be 95% confident that our interval will include the population parameter.

We can be 5% confident that our interval won't include the population parameter.

What does a confidence interval of 95% indicate?

What does a confidence interval of 95% indicate?

If $p < 0.10$, it's statistically significant.

If $p > 0.10$, it's marginally significant.

Which statement best describes the general rule of interpretation of the level of significance of a statistical test?

Which statement best describes the general rule of interpretation of the level of significance of a statistical test?

(**Fill in the blanks**) A **two-way** analysis of variance will use _______ *F-tests*.

(Fill in the blanks) A two-way analysis of variance will use _______ F-tests.

It indicates the probability that we’re correct if we accept the null hypothesis.

It indicates how the significance of the difference between means.

It indicates the probability that we’re wrong if we reject the null hypothesis.

It indicates if we should accept or reject our null hypothesis.

What does the level of significance of a statistical test indicate?

What does the level of significance of a statistical test indicate?

Introduction

Description

Estimation

Linear Models

Regression

Prediction

Testing

Intervals

Analysis of Variance

Factorial Designs

Analysis of Covariance

Linear Model Complexities

Generalized Linear Models

GLMs for Count Data

Binomial GLMs

GLMs for Binary Data

Conclusion

Appendix

Quiz: Intervals