About

Course overview

Welcome to the captivating world of statistical thinking! This course will provide you with a solid foundation in statistical theory while taking you on a journey through the practical aspects of the subject. Along the way, you’ll gain experience with statistical software, learn to interpret and effectively communicate statistical findings, and explore a range of topics in descriptive and inferential data analysis and both parametric and non-parametric statistical inference. Some of the areas we’ll delve into include probability, normal distribution, sampling distributions, confidence intervals, hypothesis testing and simple linear regression.

At the heart of this course is the ability to interpret results and grasp underlying concepts, rather than merely obtaining numerical outcomes. By engaging with a diverse set of problems, you’ll become well-versed in statistical methodologies. However, it’s crucial to remember that a deep understanding of the concepts is the key to drawing meaningful conclusions.

Learning Objectives

• Master the basic principles of data analysis, including the production and application of data in studies and experiments.
• Apply principles of inference to construct confidence intervals and conduct hypothesis tests effectively.
• Critically evaluate statistical arguments and methodologies in published research.
• Compare and differentiate between parametric and non-parametric methods in statistical analysis.
• Utilize software R to conduct data analysis, create graphs, and perform basic statistical tests.