Installing Rcmdr in R and boxplots

After last night's class, it seemed to me that I was being a bit too ambitious. We were trying to learn coding as well as statistics  in a completely new software environment. The key thing is to be able to use statistics to solve business problems. That is the goal. So I want us to use the  Rcmdr graphical user interface. Then you can just point and click and we can get the work done more quickly. The Rcmdr will produce code which you can as you wish. For sure, being able to write code yourself is much more flexible and more efficient. But it takes some time. So we can start with Rcmdr and then you can start writing code as you wish.

I'd like you to either work in the library, using the R software installed there, or install R on your computer at home. The instructions for doing this are in the chapter 1 notes which I passed around last night, and which are also on the course Moodle site.

I have just prepared a YouTube on installing Rcmdr and doing the car mileage box plot we did last night. I will prepare more YouTubes in the next few days.

The link to the YouTube is here.

I am going to send you some homework in the next few days. You email it to me and I will send it back to you with comments and also a solutions file.

You can contact me by email at any time and I will do my best to help you.

Best wishes
Stephen

Correlation and regression

When you have a bunch of independent variables to pick from, a good start is to check their correlation with the dependent variable. Youtube here. Look for an 'r' value (Pearson Product Moment) of greater than + 0.7 or smaller than - 0.7. Look at this example, where the dependent variable is Duration.





Length looks hopeful, so try that to start with. You can add others are you go, taking out those that don't work. Watch for multicollinearity, where two or more independent variables are explaining the same thing. Speed and height seem to be collinear (see their high 'r' values) so probably they wouldn't work. Thought experiment: wouldn't you expect that being dropped from a great height would add to your speed?
Youtube on multiple regression here.

Youtubes

Here are some Youtubes....I'll be adding more in the next few days


Simple linear regression

Creating a dummy variable

Moving averages, exponential smoothing and MSE

Solver for the Eqyptian farmer problem (Q9) in-class work Part 5

Solver Minimisation for the Marketing Professor Problem (Q10)

Data Sources

You can either collect your own data or find external sources, such as the Internet. Here are some sources to get you started. If you find more that you'd like to share, please let me know and I'll add them.

Vancouver

http://data.vancouver.ca/datacatalogue/index.htm

World Bank

http://data.worldbank.org/

 BC Data

http://www.data.gov.bc.ca/

Kwantlen Library…business stats

http://www.kwantlen.ca/library/subjects/busi_stats.html

World Health Organisation
http://www.who.int/research/en/

Weather -- including historical weather data for any city. Might be useful if you were doing the bike-riding example!
www.wunderground.com