If you are looking to learn about statistics, but are reluctant to do so, this is the course for you. This module provides a gentle introduction to key concepts in statistics. Statistical methods are used in various fields, from scientific research to business decision-making.
You will learn what types of data are, how they condition the choice of statistical methods. In addition, you will discover data visualization tools, tools for detecting outliers and you will know how to demystify statistical tests and decision making in the presence of uncertainty.
This applied training provides a solid basis for all other training courses.
Course Outline
Session 1: Introduction to Statistics
- Separating signal from noise
- Population(s), sample(s), sampling variation
- Descriptive vs. inferential statistics
- Type & role of variables
- Characterising distributions
Session 2: Descriptive Statistics or Exploratory Data Analysis
- Summary statistics – What they mean, when to use them
- How to best summarise & depict data
- Outlier detection & handling
- Bivariate statistics
- Pitfalls & good practices
Session 3: Hypothesis Testing Principle
- Controlling the risk of making wrong decisions
- Null & alternative hypotheses, p-values, power, confidence level, effect size, one- vs, two-sided tests
- Confidence intervals
Session 4: Sample Size Estimation
- Principle underlying sample size
- Calculation of sample size & power
- Input parameter needed: Effect size, variation/noise, risk levels
- Statistical significance vs. practical significance
Course Duration
The recommended duration for this course is 4 online sessions.
Target Audience
This course is aimed at engineers, researchers, biologists. Depending on the target audience, the course is adapted by the use of specific examples and case studies, on the one hand by using examples specific to the field of application and on the other hand by presenting specific tools or applications.
Excellent overview of statistics. I feel like I was able to obtain a strong understanding of the basics and will now be able to build on that. Highly recommended!
Excellent overview of the most important concepts in statistics. The box-plot graphical tool was excellent in helping to determine if data can be considered independent, normally distributed samples so that standard statistical analysis can be conducted. The scope of statistical tests, use of the p-value, and how to minimize risks were all clearly explained. Finally, how to interpret confidence intervals and the equivalence between confidence intervals and hypothesis testing helped me to gain more confidence in my analyses.
I started with a minimal knowledge of statistics and statistical methods and tests. This course brought me right up to speed with my colleagues. The concepts were clearly explained and there were several examples of each concept. Overall, an enjoyable and informative course.
Over-all the course was great. The teacher was very thorough in all aspects of the class. The class was well taught, the teacher asked questions to make sure we all understood, got class participation and incorporated in real examples from each participant.
I strongly recommend Natalie Rodrigue because of her extensive knowledge of statistical principles, a great understanding of application of statistics to biological data and her excellent and engaging teaching skills.