stat512.cwick.co.nz

Methods of data analysis.stat512

Methods of data analysis. Winter 2015. Oregon State University. MWF 1000-1050, WNGR 153. Wednesdays noon, 1pm, 2pm and 5pm Milne Computing Center 201. Charlotte Wickham, 76 Kidder. Charlotte.wickham@stat.oregonstate.edu. Tuesday 3-5pm Cordley 3003. Friday 11am-noon Kidder 76. Ben Brintz brintzb@science.oregonstate.edu. Katie Eng engka@science.oregonstate.edu. Joe Maurer maurerjo@science.oregonstate.edu. Joe Mon 3-4pm, Thu 9-10am. Sleuth: 7&8, 9.1 and 9.3.2. Multiple explanatories and indicator variables.

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Methods of data analysis.stat512 | stat512.cwick.co.nz Reviews

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Methods of data analysis. Winter 2015. Oregon State University. MWF 1000-1050, WNGR 153. Wednesdays noon, 1pm, 2pm and 5pm Milne Computing Center 201. Charlotte Wickham, 76 Kidder. Charlotte.wickham@stat.oregonstate.edu. Tuesday 3-5pm Cordley 3003. Friday 11am-noon Kidder 76. Ben Brintz brintzb@science.oregonstate.edu. Katie Eng engka@science.oregonstate.edu. Joe Maurer maurerjo@science.oregonstate.edu. Joe Mon 3-4pm, Thu 9-10am. Sleuth: 7&8, 9.1 and 9.3.2. Multiple explanatories and indicator variables.

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1 lectures

2 labs

3 instructor

4 homework help sessions

5 ta's

6 ta office hours

7 katie tue 2 3pm

8 ben thu noon 1pm

9 week 1

10 intro and review

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lectures,labs,instructor,homework help sessions,ta's,ta office hours,katie tue 2 3pm,ben thu noon 1pm,week 1,intro and review,reading,welcome,review of slr,week 2,sleuth 9,multiple linear regression,another example,inference,week 3,mlk no lecture,week 4

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Methods of data analysis.stat512 | stat512.cwick.co.nz Reviews

https://stat512.cwick.co.nz

Methods of data analysis. Winter 2015. Oregon State University. MWF 1000-1050, WNGR 153. Wednesdays noon, 1pm, 2pm and 5pm Milne Computing Center 201. Charlotte Wickham, 76 Kidder. Charlotte.wickham@stat.oregonstate.edu. Tuesday 3-5pm Cordley 3003. Friday 11am-noon Kidder 76. Ben Brintz brintzb@science.oregonstate.edu. Katie Eng engka@science.oregonstate.edu. Joe Maurer maurerjo@science.oregonstate.edu. Joe Mon 3-4pm, Thu 9-10am. Sleuth: 7&8, 9.1 and 9.3.2. Multiple explanatories and indicator variables.

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stat512.cwick.co.nz

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Homework 2.stat512

http://stat512.cwick.co.nz/homeworks/homework-2.html

Due Jan 21 on Canvas. The only question that requires R this week is 1.3. Consequently, this homework does not have to be in the form of an R notebook. You should hand in a .pdf (either from Word, or a scan of handwritten answers). Recall the parallel lines model from the meadowfoam case study [ mu { text{Flowers} , , text{light}, text{ early} } = beta 0 beta 1 textit{light} beta 2 textit{early} ] where. An alternative approach would be to use the days before PFI as a continuous. Variable. I.e. Fit both ...

2

Getting set up on your own computer.stat512

http://stat512.cwick.co.nz/installingRlocally.html

Getting set up on your own computer. For ST411/511 we will RStudio as our integrated development environment (IDE) for R. It provides an uniform experience over all operating systems and has a nice built-in editor. RStudio and R are also available in your lab computer room and in the main computer lab in the basement of Milne. Follow these instructions to get R and RStudio. There are three. Steps, complete them all. Step One: Install R for your operating system. Visit http:/ cran.r-project.org/. You shou...

3

Syllabus.stat512

http://stat512.cwick.co.nz/syllabus.html

Stat 412/512 is an introduction to multiple regression, including inference and model checking in multiple regression, two-way analysis of variance, adjustment for serial correlation, repeated measures and strategies for variable selection. From the catalog: ST 411/511. We will be closely following chapters 9 16 in The Statistical Sleuth by F. Ramsey and D. Shafer, 3rd Ed. Course materials (lecture notes, homeworks and labs) will be posted at stat512.cwick.co.nz. You need to have an ONID account. Are lon...

4

FAQ.stat512

http://stat512.cwick.co.nz/faq.html

How can I do well in this class? I need a (insert grade here) to (maintain my visa status) (maintain my fellowship/funding) (satisfy program requirements). How can I ensure I get it? I cannot make special accommodations for you. Read the suggestions for doing well above. Can you tell me if I have the right answer for this homework problem? May I submit my homework assignment electronically? Can I get an incomplete? The Department of Statistics requires a student requesting a grade of Incomplete in a Stat...

5

Homework 4.stat512

http://stat512.cwick.co.nz/homeworks/homework-4.html

Due Feb 11 on canvas. Chap 11, p. 338) 1, 2, 5, 6, 7, 8,. Do the above conceptual exercises from the Sleuth but do not hand them in. As part of your homework. The answers can be found at the end of the chapter, but make an honest effort to answer them before looking. They are a useful way to gauge how much you understood and can show up on exams. This homework asks you to reproduce the analysis of the second case study in Chapter 11. You can read more about this case study here. Fit the tentative model: ...

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Methods of data analysis. Fall 2014. Oregon State University. MWF 1000-1050 Cordley 1109. Milne Computing Center 201. Charlotte Wickham, 76 Kidder. Charlotte.wickham@stat.oregonstate.edu. Weds 1500-1650 Cordley 3003. Fri 1100-1150 Kidder 76. Ben Brintz brintzb@science.oregonstate.edu. Tue 11am and 1pm. Katie Eng engka@science.oregonstate.edu. Mon 5pm, Tue 4pm. Kalbi Zongo zongok@stat.oregonstate.edu. Mon noon and 2pm. Katie, Monday 9-9:50am, Thursday 3-3:50pm. Ben, Tuesday 2-2:50pm, Wednesday 11-11:50am.

stat512.cwick.co.nz

Methods of data analysis.stat512

Methods of data analysis. Winter 2015. Oregon State University. MWF 1000-1050, WNGR 153. Wednesdays noon, 1pm, 2pm and 5pm Milne Computing Center 201. Charlotte Wickham, 76 Kidder. Charlotte.wickham@stat.oregonstate.edu. Tuesday 3-5pm Cordley 3003. Friday 11am-noon Kidder 76. Ben Brintz brintzb@science.oregonstate.edu. Katie Eng engka@science.oregonstate.edu. Joe Maurer maurerjo@science.oregonstate.edu. Joe Mon 3-4pm, Thu 9-10am. Sleuth: 7&8, 9.1 and 9.3.2. Multiple explanatories and indicator variables.

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