Type of Credit: Partially Required
Credit(s)
Number of Students
This course is designed for students who want to apply the knowledge of modern econometrics to practical research questions. We will learn key statistical concepts and research methods that are essential for conducting valid quantitative analysis in the social sciences. In addition to studying the fundamental principles of statistical inference, students will also gain hands-on experience in modern statistical packages and programming tools that are necessary for researchers to comprehend and implement these research designs.
能力項目說明
The objective of the course is to assist students in developing a functional understanding of key econometrics topics and gaining confidence in applying this knowledge to their own research. We will utilize both mathematical methods and empirical datasets to illustrate the empirical strategies employed by researchers. Students will have the opportunity to gain experience in employing these strategies through in-class exercises and take-home assignments.
The course will cover various topics, including but not limited to:
If time allows, we will also delve into recent advancements in big data analysis and its application in economics. This will include an overview of high-dimensional data analysis and classification methods.
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
|
Week |
Date |
Topic |
Readings |
|
1 |
9/11/2024 |
Introduction |
Anderson et al. (2020) Ch. 1-3 |
|
2 |
9/18/2024 |
Probability |
Anderson et al. (2020) Ch. 4 |
|
3 |
9/25/2024 |
Probability Distribution I |
Anderson et al. (2020) Ch. 5 |
|
4 |
10/2/2024 |
Probability Distribution II |
Anderson et al. (2020) Ch. 6 |
|
5 |
10/9/2024 |
Hypothesis Tests |
Anderson et al. (2020) Ch. 7 |
|
6 |
10/16/2024 |
Inference about Means and Proportions |
Anderson et al. (2020) Ch. 8 |
|
7 |
10/23/2024 |
Population comparison |
Anderson et al. (2020) Ch. 9 |
|
8 |
10/30/2024 |
Midterm |
|
|
9 |
11/6/2024 |
ANOVA |
Anderson et al. (2020) Ch. 12-13 |
|
10 |
11/13/2024 |
Simple Linear Regression |
Anderson et al. (2020) Ch. 14 |
|
11 |
11/20/2024 |
Simple Linear Regression |
Anderson et al. (2020) Ch. 14 |
|
12 |
11/27/2024 |
Multiple Regression 1 |
Anderson et al. (2020) Ch. 15 |
|
13 |
12/4/2024 |
Multiple Regression 2 |
Anderson et al. (2020) Ch. 16 |
|
14 |
12/11/2024 |
Model Building |
Anderson et al. (2020) Ch. 16 |
|
15 |
12/18/2024 |
Time Series Analysis |
Anderson et al. (2020) Ch. 17 |
|
16 |
12/25/2024 |
Final Exam |
|
|
17 |
1/1/2025 |
Flexible Learning Week |
TBD |
|
18 |
1/8/2025 |
Flexible Learning Week |
TBD |
The teaching schedule may be subject to change. The dates for midterm and final exams are not fixed and could be moved earlier or later depending on the teaching progress. If there are any changes to the dates of the midterm or final exams, they will be announced in class and on the class website. Additional information regarding week 17 and 18 will be provided during class discussions.
AI assistance is permitted for completing assignments, but students must fully understand the content of their answers and are responsible for their accuracy.
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