A new way to make a Lecture List! 2015-02-08

Everything pointed to should be somewhere under http://pj.freefaculty.org/guides

1.1 Welcome stat/Regression/Welcome/ PDF R
1.2 Overview stat/Regression/Overview/ PDF R
2 Describe & Plot 1 stat/Descriptive/CentralTendencyAndDispersion/ PDF R
3 Describe & Plot 2 stat/Descriptive/ScatterBoxBarPlots/ PDF R ogv
4.1 Stat. Distributions stat/Distributions/DistributionOverview/ PDF R ogv
4.2 R-Random Rcourse/rRandomVariables/ PDF R
5 Stat. Distributions stat/Distributions/DistributionOverview/ PDF R ogv
6 CLT & Sampling Dist stat/Inferential/CentralLimitTheorem/ PDF R
7 Confidence Intervals stat/Inferential/ConfIntervals/ PDF R ogv
8 Hypo Testing stat/Inferential/HypoTesting/ PDF R
9 Regression 1 stat/Regression/ElementaryOLS/ PDF R ogv
10 Regression 2 stat/Regression/ElementaryOLS/ PDF R
11.1 Regression 3 stat/Regression/ElementaryOLS/ PDF R ogv
11.2 Regression 3 stat/Regression/ElementaryOLS/ PDF R ogv
11.3 Regression 3 stat/Regression/ElementaryOLS/ PDF R ogv
12 Multiple Regression 1 stat/Regression/MultipleRegression/ PDF R
13 Multiple Regression 2 stat/Regression/MultipleRegression/ PDF R ogv
15 Regression Assumptions and Plots stat/Regression/MultipleRegression/ PDF R ogv
16 Multicollinearity stat/Regression/Multicollinearity/ PDF R
17 Standardized Regression stat/Regression/StandardizedBeta/ PDF R ogv
18 Nonlinear 1 stat/Regression-Nonlinear/Nonlinear-Overview/ PDF R
19 Nonlinear 2 stat/Regression-Nonlinear/Nonparametric-Loess-Splines/ PDF R ogv
20 Diagnostics, Outliers, and the Hat Matrix stat/Regression/RegressionDiagnostics/ PDF R
21 Interactions and Mean Centering stat/Regression-Nonlinear/Interaction-Continuous/ PDF R ogv
22 Categorical Predictors stat/Regression/CategoricalPredictors/ PDF R
23 Interactions and Categorical Variables stat/Regression-Nonlinear/Interaction-Categorical/ PDF R ogv
24 Heteroskedasticity stat/Regression/Heteroskedasticity-WLS/ PDF R
25 Missing Data stat/MissingData/ PDF R ogv
27 Logit 1 Regression-Categorical/LogitProbit/ PDF R ogv
28 Logit 2 Regression-Categorical/LogitProbit-WorkedExample/ PDF R

Do you want to download everything to your system?

I don't mean to say it is inconvenient to look up lectures twice per week but if you think it is boring... Today I've written an R program that should grab the files for you and create a more or less coherent file structure on your computer.

I did that mostly because I was bored and needed something to entertain myself with today. This new R program is called getEverything.R. To try that, download the R file getEverything.R. Its just R code, save. Then open it in Emacs or RStudio, and run bit by bit. But be alert: Save that in a folder where you want do download lectures. If you don't supply the argument for dest, this will plop a lot of stuff into the current directory.

has a function at the top, which you just need to read into R as if it were code you wrote. If you step through that, you'll find some example usage commands at the bottom.

This will be a relatively small download if you only ask for the PDF files for the lectures, or if you include the R files. If you set the argument ogv = TRUE, then recordings will be downloaded, and they average about 100MB per file.

Caution. This will create directories, one for each lecture topic, and it will download files.

The only Warning I know of so far: This will not download selectively. It grabs everything, old and new. If I revise a lecture here or there, running this again will download everything again. Currently, there is no way to download the new things selectively. I've got to do some hard thinking on that one. There is a program on Linux and Mac that is smart enough to notice those differences, no Windows solutions has presented itself.

I think we could customize this to get particular lectures, say lectures between 10-12. If you think that's a good idea, let me know and I'll think of how it can be done. Maybe your best idea is to run this once, since it creates a nice directory structure for you. In the future, you can download \& drop new things in where they fit.