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Course title |
Statistics |
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Semester |
110-2 |
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Designated for |
DEPARTMENT OF AGRONOMY |
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Instructor |
STEVEN HUNG-HSI WU |
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Curriculum Number |
Agron2002 |
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Curriculum Identity Number |
601E20020 |
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Class |
03 |
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Credits |
3.0 |
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Full/Half
Yr. |
Half |
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Required/
Elective |
Required |
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Time |
Monday 7,8,9(14:20~17:20) |
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Remarks |
The upper limit of the number of students: 40.
The upper limit of the number of non-majors: 10. |
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Course introduction video |
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Table of Core Capabilities and Curriculum Planning |
Table of Core Capabilities and Curriculum Planning |
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Course Syllabus
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Please respect the intellectual property rights of others and do not copy any of the course information without permission
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Course Description |
This course will introduce some of the fundamental statistical concepts, methods and their applications to biology and agriculture.
There are lab sessions associated with this course. Lab sessions include hands-on experience using statistical software R, and students will be working on lab exercises and assignments in the lab.
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Course Objective |
This course will cover descriptive statistics, discrete and continuous random variables, normal distribution, sampling distribution, point estimation, confidence intervals, hypothesis testing, t-test, chi-square test, one-way analysis of variance, correlation and regression, non-parametric statistics.
By the end of the course, students should be able to apply correct statistical analysis, using statistical software R to perform correct analysis and interpretation of the results.
The mid-term and final exam will include the usage of statistical language R and interpret its output.
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Course Requirement |
- This is an English Medium Instruction (EMI) course. All materials are available in English only.
- Absent from the mid-term and final exam without applying for leave through the university procedure will receive 0% and will not be able to re-sit the test.
- Late assignments will receive 0%.
- Each time you missed a roll call, 1% of the total mark will be deducted.
- Cheating and plagiarism in assignments, exams or any other assessments are serious academic misconduct. All instances will be handled according to the university policy.
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Student Workload (expected study time outside of class per week) |
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Office Hours |
Appointment required. |
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Designated reading |
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References |
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Grading |
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No. |
Item |
% |
Explanations for the conditions |
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1. |
Assignments and labs |
30% |
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2. |
Mid-term exam |
35% |
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3. |
Final exam |
35% |
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Week |
Date |
Topic |
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Week 01 |
02/14 |
Introduction |
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Week 02 |
02/21 |
Descriptive statistics |
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Week 03 |
02/28 |
Holiday |
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Week 04 |
03/07 |
Basic probability |
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Week 05 |
03/14 |
Discrete Random Variables |
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Week 06 |
03/21 |
Continuous Random Variables and normal distribution
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Week 07 |
03/28 |
Sampling distribution and point estimation
Interval estimation
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Week 08 |
04/04 |
Holiday |
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Week 09 |
04/11 |
Midterm exam |
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Week 10 |
04/18 |
Hypothesis testing (I) |
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Week 11 |
04/25 |
Hypothesis testing (II) |
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Week 12 |
05/02 |
Hypothesis testing (III) |
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Week 13 |
05/09 |
Chi-square test for categorical data
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Week 14 |
05/16 |
Analysis of Variance |
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Week 15 |
05/23 |
Correlation and simple linear regression |
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Week 16 |
05/30 |
Final Exam |