Syllabus Lectures: T. 1310-1500, R. 1610-1700 @ SE A211 Instructor: Yu-Ling Tseng. Office Hours: T. 1200~1300 R. 1500~1600@SE A409 TA: 黃煜霖 Office Hour F. 1100~1200 @ SE 408 ～ 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
我們 就
星期 二 都 13 點 整
開始上課 ～～大家一起加油喔～
Data sets in txt form
| (date discussed in class)
Programs |
Description | Code with Output in HTML |
| (20260305) 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 |
SetUp1html |
| (20260326/31
) 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. construct 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 |
SetUp2html SetUp2pdf |
(by Robert
I. Kabacoff, Ph.D.
)Very informative web site on R| Date |
Problems 『作 業成績10％由各組派一代表和 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 （ 助教office hour:TBA 時 間若不行請另行和助 教email約時間）』 |
Due date |
| 0326 |
Ch.1 : 19 , 28 , 45 Ch.2 : 4, 8 (a, c), 10, 13 , 23 (a, c) |
0409 |
| 0310 |
Ch.1 : 7, 8, 33, 34, 39 (a) , 41 Ch.2 : 3, 17 |
0326 |
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.
