PLS 120: Applied Statistics in Agriculture
Statistical methods and data analysis for agricultural and plant sciences
Course Overview
This course provides an introduction to basic statistical concepts and techniques. It aims to equip undergraduate students with the necessary skills to understand and analyze data, make informed decisions, and interpret statistical results. The course will cover fundamental topics such as descriptive statistics, probability, hypothesis testing, and inferential statistics.
Main Objectives:
- Acquire Fundamental Competencies: Students will gain essential skills in data collection, organization, analysis, visualization, and interpretation to form a strong foundation in statistical methods.
- Develop Statistical Reasoning: The course aims to cultivate a comprehensive understanding of statistical thinking and reasoning, enabling students to critically evaluate and analyze data in various contexts.
Course Information
📍 Location
Lectures: Teaching and Learning Complex 1010
Lab Discussions:
- Session 1: Wednesdays — Teaching and Learning Complex 2212
- Sessions 2, 3, and 4: Thursdays & Fridays — Teaching and Learning Complex 2216
📹 Lecture Records
Instructors
Mohsen B. Mesgaran
Instructor
276 Robbins Hall
mbmesgaran@ucdavis.edu
Office Hours: By appointment (send email to schedule)
Mohammadreza Narimani
Teaching Assistant
Lab Section: A01
mnarimani@ucdavis.edu
Office Hours: Thursdays 10 AM - 12 PM (Zoom)
Weekly Schedule
Week 1: Applied Statistics in Agriculture
Overview of statistics, data types, and introduction to R programming with Binder.
View Week →Week 2: Descriptive Statistics
Measures of central tendency, variability, and data distribution analysis.
View Week →Week 3: Data Manipulation with dplyr
Data filtering, transformation, and visualization using dplyr and ggplot2.
View Week →Week 4: Probability and Sampling
Probability theory, random sampling, and normal distribution functions.
View Week →