| Course title | |||||
| 農学実験計画法および統計解析演習Ⅰ [Exercise for Methods of Agricultural Experimental design and Statistical Analysis I] | |||||
| Course category | Requirement | Credit | 1 | ||
| Department | Year | 1～ | Semester | 1st | |
| Course type | 1st | Course code | 05ce0001d | ||
| Instructor(s) | |||||
| 川森 愛, 渡辺 誠 [KAWAMORI Ai, WATANABE Makoto] | |||||
| Facility affiliation | Graduate School of Agriculture | Office | Email address | ||
| Course description |
| This course provides students with basic knowledge of statistical processing necessary for reading research papers on experiments and field surveys in agriculture and related fields. In this course, we focus especially on the analysis used in the fields of agriculture, life science, and ecology. In this course, students will learn how to take comparison targets in experiments and field surveys, how to calculate the necessary number of samples, and so on, through exercises using statistical software R, with the aim of acquiring the ability to perform a series of processes from planning experiments and observations to the minimum necessary statistical analysis on their own. |
| Expected Learning |
|
To understand the basics of statistics as a basic subject necessary for conducting research in agriculture and related fields, and to understand how to process data and interpret the results using statistical analysis methods. The following three points are the achievement criteria. 1. Understand the basics of statistics 2. To acquire statistical methods for processing phenomena related to agriculture and related fields. 3. To be able to judge and evaluate the validity of the results obtained from the analysis. Corresponding criteria in the Diploma policy: See the curriculum maps on the university website (Three Policies). https://www.tuat.ac.jp/campuslife_career/campuslife/policy/ |
| Course schedule |
|
Lesson 1, Guidance of the course and basic knowledge of statistics Lesson 2, Data handling ? Does every roll of the dice has equal chance of coming up? - Lesson 3, Various probability density and random sampling Lesson 4, The importance of random sampling in the past election case and statistical inference Lesson 5, Statistical tests and p-values from a statistical philosophy perspective Lesson 6, Properties of p-values, typical statistical tests, and experimental design Lesson 7, Regression and GLM Lesson 8, Likelihood, statistical modeling, and the way to evaluate the model After each lecture, a small assignment will be given to improve the understanding (deadline is until next lecture). Students are required to submit all assignment, but the content of these will not be reflected in the grade. Most of the grade will be based on the content of the final report given after all lectures. |
| Prerequisites |
|
In addition to the school hours (16 hours), prepare and review the lecture referring to the distributed lecture materials and reference books. Understanding mathematics provided at Japanese high school and basic knowledge about statistical software R. In completing this course, students will spend the standard amount of time as specified by the University. |
| Required Text(s) and Materials |
| Handout will be arbitrarily provided before each coursework |
| References |
| Assessment/Grading |
| Assignment of each lesson: 30%, report: 70% |
| Message from instructor(s) |
| The final goal of this lecture is getting skills to generate sample data based on their own models, select appropriate statistical methods, and analyze them. The progress and the goal may be adjusted according to the students' understanding. |
| Course keywords |
| statistical analysis, data handling, interpretation of the data, interpretation of the result of the analysis, statistical modeling, statistical software R |
| Office hours |
|
Before and after of each coursework. Open for any questions by e-mail |
| Remarks 1 |
| Remarks 2 |
| Related URL |
| Lecture Language |
| Japanese |
| Language Subject |
| Last update |
| 2/16/2022 1:28:36 PM |