早稲田大学大学院経済学研究科・政治学研究科2015年度)西郷担当講義

 

(作成:西郷浩;掲示開始:201541日;最終更新:20151117日)

 

講義の記録を目的としたページです。見栄えはよくありませんので、悪しからず。

 

 

経済データ分析[経研]

l  開講時期・曜日時限・教室:春学期・月1(貞廣先生と共同担当)@3-902

l  教科書:プリント

l  参考書:

1.      廣松毅・高木新太郎・佐藤朋彦・木村正一『経済統計』新世社 2006

l  評価:assignments

l  講義記録:

1.      46日:本講義の目的、本講義の構成、R事始、時系列データの分解

2.      413日:CSVファイルの読み込み、ヒストグラムの見方、階級の構成

3.      420日:ヒストグラムの見方、階級の構成(続き)、代表値(算術平均、中央値、最頻値)、代表値と歪みとの関係、散らばりの尺度(四分位偏差、分散、標準偏差)

4.      427日:箱ヒゲ図、散布図、相関、相関係数、回帰直線、決定係数

5.      511:有意性、変数変換、複数の説明変数(導入)

6.      518日:複数の説明変数(続き)、需要分析(時系列グラフ)

7.      527日:需要分析(散布図、全期間の推定、観測値と予測値の時系列グラフの描画、期間の分割、ダミー変数の利用)、レポート課題

Ø  レポート課題:プリントの最後のレポート課題について、PDFファイルを作成・提出しなさい。
期日:201568日(月)23:59
提出方法:PDFファイルをCourse N@viに。

8.      以降は、貞廣先生がご担当。

 

 

Statistics [Graduate School of Economics]

l  Lectures: Tuesday 9:00-10:30@3-709, Friday 9:00-10:30@3-709 (Fall Semester)

l  Textbook: Lavine, M. (2013), Introduction to Statistical Thought
http://people.math.umass.edu/~lavine/Book/book.html

l  Language: English

l  Grading: Assignments (50%) + the final exam (50%)

l  Course Schedule:

1.      September 25, 2015: Basic rules, contents covered by this course, sample points, the sample space, events, disjoint sets, the addition rule, conditional probabilities, independence, the multiplication rule, the Bayes theorem

2.      September 29, 2015: The Bayes theorem (continued), random variables, discrete random variables and continuous random variables, E(X) and E(g(X)) for discrete random variables, the moments of X, the variance of X, the standard deviation of X.

3.      October 2, 2015: The Bernoulli distribution, the binomial distribution, and the Poisson distribution.

4.      October 6, 2015: The Poisson distribution (continued), the normal distribution

5.      October 9, 2015: The normal distribution (P(|Z|<1, etc. ), V(a+bX), multivariate r.v.s, the joint probability, the marginal probability, the conditional probability, independence, X=sum X_i, where X_i ~ Bernoulli(p).

6.      October 13, 2015: The binomial disribution, conditional expectation, conditional variance, E(X+Y)=E(X)+E(Y), V(X+Y)=V(X)+V(Y)+ 2Cov(X, Y),

7.      October 16, 2015: What is Cov(X, Y)?, Independence of r.v.’s, V(X+Y) under independence

Ø  Assignment 1, Due date: October 23, 2015

8.      October 20, 2015: Populations and samples, the sample mean, Chebysev’s inequality, the WLLN.

9.      October 23, 2015: The CLT, the normal approximation to the binomial distribution.

10.   October 27, 2015: The likelihood function, the maximum likelihood estimator

11.   October 30, 2015: The MLE for a normal population, the MLE for the Bernoulli population, unbiasedness, consistency.

12.   November 3, 2015: The score function, the Cramer-Rao bound, properties of the MLE’s (approximate unbiasedness, consistency, asymptotic normality)

Ø  Assignment 2, Due date: November 10, 2015.

13.   November 10, 2015: The likelihood ratio test, the null hypothesis, the alternative hypothesis, the rejection region.

14.   November 13, 2015: Comments on Assignment 2, the likelihood ratio test for a simple null hypothesis vs a composite alternative hypothesis.

15.   November 17, 2015: t-test, the LRT and the t-test under normality, two samples problem.

16.   November 20, 2015: The final exam, teaching evaluation

 

 

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