Regression

Spring 2024

MandH

Course Info

  • Syllabus
  • Lectures: T. 1310-1500, R. 1610-1700 @ SE A316
  • Instructor: Yu-Ling Tseng.      Office Hours: T. 1200~1300  R. 1500~1600@SE A409
  • TA: 張 秝穎  (負責聽用R講解習題)W. 1600~1700 @ SE 412  吳雨瑾    (負責打作業分數)W. 1500~1600 @ SE 434 ~  有問題要多多請教助教喔   
  • 數學小天地   ~~ 討 論 各類 數學相關問題 的好地方 ~~
  • Prerequisites: Probability Theory, Statistics, Linear Algebra 
  • YesKno時間   有點迷路時聽聽第一堂課的也許有幫助,請直接收聽第29集: https://play.kkbox.com/podcast/episode/9XiNiBkrgcwXNDx5MA


  •   0514 期中考成績枝葉圖
    人 數: 37 (不計缺考人數)總分:110

      0 | 069
      1 | 568
      2 | 001134489

      3 | 0012469
      4 | 0003349

      5 | 9
      6 | 02799
      7 | 3

      8 |1 


    Q1= 21,   Q2= 32,   Q3= 44
    平均:36.35      標準差: 20.02

    註:成績顏色帶代表:紅色 警告 區,黃色 小心後通行 區, 綠色 安全通行


    每組一個同學代表去講給助教聽,目前(截至0511)已經有7組完成,
    其他 5組代表請進快 email 助教 張 秝穎 約定要講的題目,請在0524前完成這部份。 

    ==> 除去到助教處講解習題者外,我們 預計 0528 由各組其他組員中 隨機 選出各組 期末 上機考試 (預計在第18周的星期二, 線上舉行)代表。



    20240514期中考考題        <<  0514 12:30 上傳。。。。。。。。。>>



     403地震影響,0410~0426全校 改 線上上課。。。。。。。

    兩件事:

    1  原本0411要交的作業,請 將 白紙黑字 寫的作業作業 掃描成pdf檔,寄給助教吳雨瑾  

       線上上課期間,課程網頁上還是會依照進度勾習題,但 批改困難,所以 作業 就 不 用 繳 交囉,請每位同學按部就班依進度將習題做做。

      待恢復教室上課(希望盡早!)紙本作業的繳交就照舊。   

      每組一個同學代表去講給助教聽,目前(截至0511)已經有7組完成,其他5組代表請進快 email 助教 張 秝穎 約定要講的題目,請在0524前完成這部份。 


    2 迴歸分析 線上上課 訊息


    時間   星期二 下午1:00 - 3:00      星期四 下午4:00 - 5:00

    課程代碼/迴 歸分析: https://classroom.google.com/c/NjcyOTI2MDcyNzQ4
    視訊通話連結/GoogleMeet: https://meet.google.com/iuf-moqs-mhm
    課程邀 請連結:https://classroom.google.com/c/NjcyOTI2MDcyNzQ4?cjc=uduy5ph


    Office hour

     T  12:00 - 13:00  R 15 :00 - 16:00
    if on line

    https://meet.google.com/pab-rggx-han

    有其他問題,數學小天地也有線上值班喔

    https://meet.google.com/ygg-jfrm-rog


    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    學 期只有17周上課時間,學校行事曆18周的彈性補課我們就安排如下。。。。

    星期二都 13 點 整 開始上課  ~~~

    Data sets in txt form

    https://drive.google.com/open?id=1Q8krL5S0FC2sk1OmvV2wpEycxOR70BKx

    https://drive.google.com/drive/folders/1rcQeNvDQ2d8OzBcYPBy9ydeB874ss6p-?usp=sharing


    (date discussed in class)  Programs
    Description 
    (20240314)  SetUp(1) SetUp(1)shows you how to:
    1. devide graphical windows (not necessary if using R studio where you use the left program with extension .r)
    2. assign variables/sequences
    3. plot and make titles for the graph
    4. generate normally distributed observations/make histograms
    5. do simple regressions and related plots  (you should see the effect of sample size and s.d.  on the fitted reg. lines)
    6. quit R
    (20240314/21 )   SetUp(2)

      ch01ta01 data
    SetUp(2)shows you how to:
    1. scan a data set in your working directory into R
    2. get figures and tables in the textbook with the Toluca Company examples
    3. construct confidence intervals for reg. coeff.'s, confidence/prediction  intervals for the mean response at given predictor x's values
    4. construt conf. band for the entire reg line,
    5. overlay three type of intervals in one plot for better comparison
    6. save the output to a file for preparing your homework, or save the R commands for later use
    (20240425)  MLR

    ch06fi05 data
      MLR shows you how to
    1. some basic matrix operations in R,
    2. how to obtain the design matrix after fitting a simple linear regression model,

    With the Dwaine Studios examples
    3. do multiple linear regression
    4. get figures and tables in the textbook
    5. make basic scatter plots for M-L-R data analysis
    6. obtain the design matrix
    7. get (simultaneous) conf. intervals for reg. coefficients,  confidence/prediction  intervals for the mean response at given predictors's values
    (20240507)GLT

    ch6pr18 data
    GLTshows you how to
    1. obtain SSEs from the full model and the reduced model
    2. obtain F(1-alpha; m, k) in R
    3. use the general linear test approach  for testing certain hypotheses (by giving 3 examples)

    (20240516)
    ResidPlot
    This program ResidPlot
    1.  let you get a feeling as how a random sample of size n from N(0, 1) would look like in time sequence plots, and in histograms;
    and
    2. with simulated regression data.....  shows you some basic residual-plots for diagnostic in a regression analysis
    Please note that how a violation of certain assumptions made in reg model affect the display........


      You may find useful R programs  here:
                   
    Assignments (NO LATE HOMEWORK IS ALLOWED!)                                                                                                           
    Date
    Problems  『作 業成績10%由各組派一代表和張 秝穎  助教面試講解一題要用R程式回 答的問題;題目採先選先贏制,講過題目其他組不得再選擇喔
    張 秝穎  助教 office hour W. 1600~1700 @ SE 412  時間若不行請另行和助教email約時間)
    Due date
    0502
    Ch.6 : 6 (c),  11 (b), 16 (b, c), 17, 19
    0418/25
    These Problems  and
    Ch.2 : 27 , 28
    Ch.6 : 2, ,4, 5 (a, b), 6 (a, b), 7, 15 (c), 16 (a), 22, 23, 24, 25, 26

    0328
    Ch.1 : 19(已被選) , 28 (已被選), 45 (已被選)
     Ch.2 :
    4
    , (已被選)8 (a, c)(已被選), 10, 13 (已被選), 23 (a, c)
    (已被 選)  Ch.5 : 17, 18. 19
    0411
    0312
    Ch.1 : 7, 8, 33, 34, 39 (a) , 41
    Ch.2 : 3, 17.
    0328

    20240220 First day of class

    課本:Applied Linear Statistical Models, Applied Linear Regression Models, 5th ed, Kutner, Nachtsheim, Neter and Li, 2019, McGRAW-HILL International. 洽華泰書局 周益彰 先生(0910-275877)

    參考書目:
    1. Applied Regression Analysis, 2nd ed, Draper, N. R. and Smith, H., 1981, Wiley.
    2. Introduction to Linear Regression Analysis, 2nd ed, Montgomery, D. C. and Peck,     E., 1991, Wiley.

    Course Grade

    Homework (20%=10%+10%)  Midterm (30%)  Final (50%= 30%+20%)



    Computing                                                                                               

    1. R website (original, mirror @ NTU)  
    2.     R ClassRoom 
    3. Document Reader: Acrobat Reader

    Murray_0408

    Last modified: 20200908
    yltseng@mail.ndhu.edu.tw