This introductory course provides a foundation in statistical concepts, methods, and their applications in biology and agriculture. It covers essential techniques for data exploration, analysis, and interpretation, enabling individuals to make data-driven decisions in these fields. The course focuses on developing the skills and knowledge needed to effectively use statistical tools and methods, including the statistical software R.

Topics will include descriptive statistics, basic probability, discrete and continuous distribution, sampling distribution, point estimation, confidence intervals, hypothesis testing, one-way analysis of variance, correlation, linear regression analysis, and chi-square test.

Lab Description:
Lab sessions include hands-on experience with the statistical software R. Students will learn how to perform statistical analysis and interpret its outputs.

 

• Summarize and visualize data using descriptive statistics and graphs.
• Understand and apply probability theory and probability distributions.
• Understand sampling techniques and the Central Limit Theorem.
• Conduct hypothesis testing and construct confidence intervals for inferential statistics.
• Compare means using ANOVA and assess relationships with correlation and regression.
• Analyze categorical data using chi-square tests.
• Communicate statistical results effectively and apply them to real-world problems.
• Use statistical software (e.g., R) to perform data analysis and interpret results.

• This course will be conducted entirely in English, including all lectures, course materials, and assignments.
• Cheating and plagiarism in any form of assessment are considered serious academic misconduct and will be handled according to university policy.
• Absence from the mid-term or final exam without obtaining official leave through the university procedure will result in a grade of 0% with no opportunity for a re-sit.
• Assignments submitted after the deadline will receive a grade of 0%.

• 📖 Introduction to statistics and data analysis: with exercises, solutions and applications in R (2022) by Christian Heumann, Michael Schomaker, Shalabh
  
  
• 📖 Biostatistics with R an introduction to statistics through biological data (2012) by Babak Shahbaba
  
  
• 📖 Introductory Statistics (2023) by OpenStax