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updates for lab 4.

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nickreich committed Oct 6, 2018
1 parent f8495dc commit e42307507a0e89c045da0bf4bf60d9a46c211947
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Create a short reproducible report answering the questions below. The report should be less than 3 pages, including all figures. You do not need to show your code in the PDF report.
This lab is due at 5pm on Friday, October 13th. You should submit your assignment, in the form of both a knitted RMarkdown PDF as well as the .Rmd file that created the PDF, by uploading them to your personal Google Drive folder that is shared with the TA and the instructor. While you may collaborate with other students on this assignment, you must write up your own code and answers to the questions. Absolutely no cutting and pasting of any portion of the answers. This assignment, like the others, will be worth 50 points.
This lab is due at 5pm on Friday, October 12th. You should submit your assignment, in the form of both a knitted RMarkdown PDF as well as the .Rmd file that created the PDF, by uploading them to your personal Google Drive folder that is shared with the TA and the instructor. While you may collaborate with other students on this assignment, you must write up your own code and answers to the questions. Absolutely no cutting and pasting of any portion of the answers. This assignment, like the others, will be worth 50 points.
\subsection*{Data exploration}
This lab will cover model selection and checking for multiple linear regression using the FEV dataset (found in the \href{http://biostat.mc.vanderbilt.edu/wiki/Main/DataSets}{Vanderbilt Datasets repository}). This dataset contains 654 observations on 6 variables, including a continuous outcome variable, forced expiratory volume (FEV) which is a measure of lung health and strength, age, height, sex, and smoking status. To begin, load (install if necessary) the Hmisc package to load the dataset from the Vanderbilt website. The brief FEV dataset codebook can be found on \href{http://biostat.mc.vanderbilt.edu/wiki/pub/Main/DataSets/FEV.html}{this webpage}.
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@@ -140,7 +140,8 @@ _Thurs, week 5_
- looking for TAs for next semester
- UGrid?
- QUIZ! https://nickreich.github.io/data-stories/pages/quiz1-doc.html
- Lecture 6: model validation vs. model diagnostics
- went over quiz on whiteboard, with diagrams/explanations of slopes of models with and without interaction
- Lecture 6: model validation vs. model diagnostics (left model selection to later)
_Tues, week 6_
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@@ -29,7 +29,7 @@ Month   | Day | | Topic | Notes   | HW Due   | Reading
| Fri, 5| | | | [Lab 3](../assets/labs/lab3-regress/lab3-regress.pdf) |
| Tu, 9| | _No Class_ | | |
| Th, 11| | Logistic regression | <!-- [Lec 7](../assets/lectures/lecture7-logistic/lecture7-logistic.pdf)--> || Kaplan 16, OI 8, [OI Video](https://www.youtube.com/watch?v=uYC2eLVSpI8&list=PLkIselvEzpM5f1HYzIjFt52SD4izsJ2_I&index=4)
| Fri, 12| | | | Lab 4|
| Fri, 12| | | | [Lab 4](../assets/labs/lab4-interact/lab4-interact.pdf)|
| Tu, 16| | Understanding Uncertainty | <!--[Lec 8](../assets/lectures/lecture8-confidence/lecture8-inference.pdf), [Suppl](../assets/lectures/lecture8-confidence/lecture8-activity.html) -->| | Kaplan 11-13
| Th, 18| | Understanding Uncertainty | <!--[Lec 9](../assets/lectures/lecture9-intervals/lecture9-intervals.pdf), [Suppl](../assets/lectures/lecture9-intervals/lecture9-activity.Rmd)--> | ||
| Fri, 19| | | | Lab 5|

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