流水號
81008
課號
PPM5084
課程識別碼
633 U1500
無分班
- 3 學分
選修
植物病理與微生物學系
植物病理與微生物學系
選修- 張皓巽
- 搜尋教師開設的課程
生物資源暨農學院 植物病理與微生物學系
- 五 6, 7, 8
學新820
2 類加選
修課總人數 8 人
本校 8 人
無領域專長
- 中文授課
- NTU COOL
- 備註本課程中文授課,使用英文教科書。教室:學新館820
本校選課狀況
載入中- 課程概述Statistics is once named as “The Grammar of Science” by Karl Pearson in 1891. This is not only a compliment, but more an emphasis to show the importance of statistics in knowing the probability and difference for research in all fields of science. In other words, any claim from observational difference to experimental significance relies on a solid and robust statistical analysis. As the field of statistics contains a broad spectrum from theoretical statistics to applied statistics, and from frequentist’s statistics to Bayesian’s statistics, this course “Applied Biostatistics” would focus on the classic and applied statistics, with an aim to equip students with the ability of using R language to perform statistical analyses, programing, and plotting.
- 課程目標The goals of “Applied Biostatistics” includes the instructions of the concepts and principles of classic statistics, with expectation that students who completed this course to have the ability of using standard statistical terminologies in scientific discussion, and the ability of applying the skills of R programing and plotting in personal research.
- 課程要求1. 本課程將學習以R程式進行統計分析。學生將以手算結果與R分析結果相互驗證。本課程將學習基礎R語言,歡迎沒有使用過R語言的同學。 2. 每位學生需自備筆電與科學計算機以利作業與考試進行。 1. This is a statistic course based on R programming. Students will need to hand-calculate and learn how to use R to match the results. No R background is needed. 2. Students need to prepare a personal scientific calculator/laptop for exams
- 預期每週課後學習時數
- Office Hour
星期二 13:30 - 14:00 - 指定閱讀
- 參考書目#For each midterm and final, you are allowed to bring a single A4 page cheat-sheet. You may write down any formula, note, and even draw tables and figures to assist you pass the exam. You are not allowed to write down any exact examples in the cheat-sheet. If you bring a cheat-sheet to the exam, you will need to turn in the cheat-sheet together with your exam papers.
- 評量方式
20% Midterm I
20% Midterm II
20% Midterm III
13% Final
27% Homeworks
9 HWs. Each accounts for 3%
- 針對學生困難提供學生調整方式
- 課程進度
2/23第 1 週 2/23 Preface. Syllabus Chapter 1. What is Statistics? 1. Statistics is the grammar of science 2. Milk tea and Ronald Fisher Chapter 2. Descriptive Statistics 1. Parameters and statistics 2. Data visualization 3. The philosophy of statistics 4. Pearson’s and Spearman’s correlation 3/1第 2 週 3/1 Chapter 3. Normal distribution 1. Normal distribution (Gaussian distribution) 2. Z-distribution (standardized normal distribution) 3. Bivariate normal distribution Chapter 4. Inference Statistics, Z test and Z distribution 1. Inference statistics 2. Estimation of confidence interval 3. Z test 4. Type I error and Type II error (#HW1) 3/8第 3 週 3/8 Chapter 5. Student’s t-test and t distribution 1. Central limit theorem 2. Unbiased variance 3. Student’s t-test and t distribution 4. Degree of freedom 5. Unpaired t-test, Welch’s t-test and paired t-test (#HW2) 3/15第 4 週 3/15 Chapter 6. Chi-square test and F test for Variance Inference 1. One sample chi-square test 2. Two sample F test 3. Multi-sample F test (#HW3) 3/22第 5 週 3/22 Midterm I. (Chapter 1-5) 3/29第 6 週 3/29 Chapter 7. Analysis of Variance (ANOVA) 1. One-way ANOVA 2. Multiple comparisons 3. Bonferroni correction and false discovery rate (FDR) 4. Fisher least significant difference (LSD) 5. Tukey’s honest significant test (TukeyHSD) 6. Dunnett’s test 7. Scheffe’s test (#HW4) 4/5第 7 週 4/5 No Class 4/12第 8 週 4/12 Chapter 8. Linear Regression 1. Simple linear regression 2. Coefficient of determination (R2) 3. Multiple linear regression 4. Analysis of covariate (ANCOVA) 5. Polynomial regression (#HW5) 4/19第 9 週 4/19 Chapter 8. Linear Regression 1. Multicollinearity 2. Variance inflation factor (VIF) 3. Model selection – likelihood, Akaike information criterion (AIC), Bayesian information criterion (BIC) Chapter 9. Assumption Diagnosis and Data transformation 1. Normality 2. Equal variance (homoscedasticity) 3. Data transformation 4. Leverage, outlier and influential points (#HW6) 4/26第 10 週 4/26 Midterm II. (Chapter 6-7) 5/3第 11 週 5/3 Chapter 10. Experimental Design 1. Fisher’s basic principles of experimental design 2. The meaning of replicate and repeat 3. Complete randomized design (CRD) 4. Complete randomized block design (RCBD) 5. Latin square (#HW7) 5/10第 12 週 5/10 Chapter 11. Mixed Model and Variance Partition 1. Variance partition 2. Fixed effect 3. Random effect (#HW8) 5/17第 13 週 5/17 Midterm III (Chapter 8-10) 5/24第 14 週 5/24 Chapter 12. Nonparametric Statistics 1. Contingency table – Pearson’s chi square test and Fisher’s exact test 2. Nonparametric t test – Wilcoxon rank sum test (Mann-Whitney U test) 3. Nonparametric paired t test – Wilcoxon signed rank test 4. Nonparametric one-way ANOVA– Kruskal-Wallis test 5. Nonparametric two-way ANOVA – Friedman test (#HW9) 5/31第 15 週 5/31 Closing Remarks 6/7第 16 週 6/7 Final (All Chapters)