-
Notifications
You must be signed in to change notification settings - Fork 10
/
schedule.qmd
91 lines (65 loc) · 5.51 KB
/
schedule.qmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
---
title: "Schedule"
format:
html:
code-fold: true
code-tools: true
editor: source
---
You can find the **official course schedule** provided by University of Oslo [here](https://www.uio.no/studier/emner/medisin/med/MF9130E/v24/timeplan/index.html).
If there is an error in the time and place on this page, please refer to the official schedule.
::: callout-note
## Time and place
Sessions are roughly divided by AM (morning) and PM (afternoon).
- AM: 8:30 - 11:45
- PM: 12:45 - 16:00
Locations
- **Aud13**: Auditorium 13 in Domus Medica ([map](https://use.mazemap.com/#v=1&config=uio&campusid=799&zlevel=2¢er=10.715371,59.946743&zoom=18&sharepoitype=poi&sharepoi=1000983201))
- **Runde**: Runde auditorium R105 ([map](https://use.mazemap.com/#v=1&config=uio&campusid=799&zlevel=1¢er=10.715886,59.946189&zoom=18&sharepoitype=poi&sharepoi=1001022929))
:::
# Week 1
| Day | Session | Place | Topic | Course material |
|:-------:|:---:|:------:|:---------------:|:-------------:|
| Day 1 - Apr 8 |PM | Aud 13 | **Course introduction** | [Lecture](v24/day1-1-Course_introduction.pdf)|
| | | | **Data and descriptive statistics** |[Lecture](v24/day1-2-Data_and_descriptive_statistics.pdf) |
| Day 2 - Apr 9 |AM | Aud 13 | Lab 1 | [Lecture](v24/lab_20240409_intro_to_r.pdf), [Lab notes](lab/lab_intro_r.qmd), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/1_intro_r.R) |
| | | | Lab 2 |[Lecture](v24/lab_20240409_descriptive.pdf), [Lab notes](lab/lab_eda_part1.qmd), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/2_eda_part1.R) |
| |PM | | **Intro to probability** |[Lecture](v24/lecture_20240409_probability.pdf) |
| | | | **Diagnostic test** | [Lecture](v24/lecture_20240409_diagtest.pdf)|
| | | | Lab 3 |[Lab notes](lab/lab_diagtest.qmd), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/2_diagtest.R) |
| Day 3 - Apr 10 |AM | Aud 13 | **Binomial distribution** | [Lecture](v24/lecture_20240410_binom.pdf)|
| | | | **Normal distribution** | [Lecture](v24/lecture_20240410_normaldist.pdf)|
| | | | Lab 4 |[Lab notes](lab/lab_distribution.qmd), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/2_distributions.R)|
| |PM | | **Statistical inference I** | [Lecture](v24/day3_Introductory_Lecture.pdf)|
| | | | **Sample mean** | [Lecture](v24/day3_key_concept_1.pdf)|
| | | | **Confidence interval** | [Lecture](v24/day3_key_concept_2.pdf) |
| | | | **t-test** | [Lecture](v24/day3_key_concept_3.pdf)|
| Day 4 - Apr 11 |AM | Aud 13 | Lab 5 |[Lecture](v24/lab_20240411_ttest.pdf), [Lab notes](lab/lab_ttest.qmd), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/3_ttest.R) |
| |PM | | **Statistical inference II** | [Lecture](v24/day4_Introductory_Lecture.pdf) |
| | | | **One proportion** |[Lecture](v24/day4_key_concept_1.pdf)|
| | | | **Two proportions** | [Lecture](v24/day4_key_concept_2.pdf) |
| | | | **Table analysis** | [Lecture](v24/day4_key_concept_3.pdf)|
| Day 5 - Apr 12 |AM | Aud 13 | Lab 6 |[Lecture](v24/lab_20240412_categorical.pdf), [Lab notes](lab/lab_categorical.qmd), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/4_categorical.R) |
# Week 2
| Day | Session | Place | Topic | Course material |
|:-------:|:---:|:------:|:---------------:|:---------------:|
| Apr 22 |AM | Runde | **Exploratory analysis** (Part II) |[Lecture](v24/nonparametric_lecture_eda2.pdf) |
| | | | **Transformation, non-parametric** | [Lecture](v24/nonparametric_lecture.pdf) |
| | | | **Randomness and probability** | [Lecture](v24/week_2_day_1_1.pdf) |
| | | | Lab 7 |[Lab notes](lab/lab_nonpara.qmd) |
| |PM | | **Sample size and statistical power** | [Lecture](v24/sample_size_lecture.pdf), [Exercise](v24/sample_size_exercise.pdf), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/day5_lab_sample_size.R)|
| Apr 23 |AM | Runde | **Study designs** | [Lecture](v24/2024-04-23_Epidemiological-clinical-design_Stenehjem_UPLOAD.pdf)|
| |PM | | **Linear regression I** |[Lecture](v24/linear_regression_part_1.pdf) |
| | | | Lab 8 |[Lab notes](lab/lab_linearreg-I.qmd) |
| Apr 24 |AM | Aud 13 | **Linear regression II** | [Lecture](v24/regression_analysis_part_2.pdf)|
| | | | Lab 9| [Lab notes](lab/lab_linearreg-II.qmd)|
| |PM | | **Linear regression III** | [Lecture](v24/regression_analysis_part_3.pdf)|
| | | |Lab 10 | [Lab notes](lab/lab_linearreg-III.qmd)|
| | | |Additional | [Breiman_2001](v24/Breiman_2001.pdf), [Shmueli_2019_slides](v24/Shmueli_2019_slides.pdf), [Shmueli_2019](v24/Shmueli_2019_StatScience.pdf)|
| | | | Course summary | [Lecture](v24/Course_summary.pdf)|
| Apr 25 |AM | Runde | **Logistic regression** | [Lecture](v24/Module7-Logistic-Regression.pdf)|
| | | |Demo: ppn | [Lecture](v24/MF9130E - Introductory course in Statistics LR examples.pdf), [Code](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/code/height_demo.R), [ppnLR.csv](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/ppnLR.csv), [classroom.csv](https://github.com/ocbe-uio/teaching_mf9130e/blob/main/lab/classroom.csv)|
| | | | Lab 11| [Lab notes](lab/lab_logistic_reg.qmd)|
| |PM | | **Survival analysis** | [Lecture](v24/Module8-Survival.pdf)|
| | | || [Tutorial](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1065034/pdf/cc2955.pdf)|
| | | |Lab 12 | [Lab notes](lab/lab_survival.qmd)|