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本頁翻譯進度

燈號說明

審定:無
翻譯:翁于棻(簡介並寄信)
編輯:侯嘉玨(簡介並寄信)

以下為Sorensen教授對作業的要求

The assignments are described below, in Professor Sorensen's own words.

這些作業都沒有特定答案。我不會指定你該用什麼相依變數、該解釋什麼…等等。這樣的部份目的是要讓你練習如何使用數據、估計模型和使答案合理化。利用課程15.347所學,你要規劃出數據的概念性模型和統計模型。這門課較大的限制是你只能使用當週課堂中討論的方法(例如:計算模型)。我都已經將適當的數據資料設定好,不過你也可以使用自己取得的數據。

The assignments are deliberately open-ended. It is not specified what the dependent variable should be, what you are trying to explain, etc. Part of the goal of these exercises is to give you practice with working with data, estimating models and making sense of the results. In the language of 15.347, I want you to formulate a conceptual model of the data as well as a statistical model. The major constraint is that you apply the method discussed during that week's class (e.g., count models). I will make appropriate datasets available for this purpose, but you are also allowed to use your own data sources.

每次「應用」課的開始都要交一份分析結果概要,本文最多兩頁,加上圖表,並根據推衍出的概念性模型討論其結果。這些作業最多可由兩人一組完成。我每週會請兩或三組提出他們的工作結果,並在課堂中討論。

At the beginning of class in each "Application" week, I ask that you hand in a brief summary of the results of your analysis. This summary should be a maximum of two pages of text, plus any tables and figures, and should discuss the results in light of the conceptual model you have developed. These assignments may be done in groups of up to two people. I will ask two or three groups each week to present the results of their work, so that we may discuss them as a class.


課程單元 作業
1 導讀:課程目標與運算
Introduction: Course Goals and Logistics
2 理論:普通最小平方迴歸
Principles: Ordinary Least Squares Regression
3 應用:普通最小平方迴歸 口頭報告
Presentations of worked data
4 理論:二元結果模型
Principles: Models for Binary Outcomes
5 應用:二元結果模型
Applications: Models for Binary Outcomes
口頭報告
Presentations of worked data
6 理論:計算模型
Principles: Models for Counts
7 應用:計算模型
Applications: Models for Counts
口頭報告
Presentations of worked data
8 理論:跨區域整合/時間序列分析
Principles: Pooled Cross-Section/Time Series Analysis
9 應用:跨區域整合/時間序列分析
Applications: Pooled Cross-Section/Time Series Analysis
口頭報告
Presentations of worked data
10 理論:事件歷史分析與數據架構之基礎概念
Principles: Basic Concepts of Event History Analysis and Data Structures
11 理論:事件歷史數據之敘述統計
Principles: Descriptive Statistics for Event History Data
12 理論:事件歷史數據之模型
Principles: Models for Event History Data
13 應用:事件歷史分析
Applications: Event History Analysis
口頭報告
Presentations of worked data
14 回顧與整合
Review and Wrap-up

 
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