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Syllabus In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment, discuss generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, creating informative data graphics, accessing R packages, creating R packages with documentation, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples. Objectives After taking this course you should be able to Read formatted data into R Subset, remove missing values from, and clean tabular data Write custom functions in R to implement new functionality and making use of control structures such as loops and conditonals Use the R code debugger to identify problems in R functions Make a scatterplot/boxplot/histogram/image plot and modify a plot with custom annotations Define a new data class in R and write methods for that class Lecture Materials Lecture videos will be released weekly and will be available for the week and thereafter. You are welcome to view them at your convenience. Accompanying each video lecture will be a PDF copy of the slides, unless the lecture is a demo, in which case there will be no lecture slides. Quizzes There will be four weekly quizzes that will test your comprehension of the material covered in the lecture material provided that week. The quizzes will consist of multiple choice, true/false, or short answer questions. Each quiz is worth 10 points. You will be allowed 3 attempts to submit each quiz and your maximum score will be taken as the final score. Quiz Opening/Closing Dates Quiz 1: 2012-09-24 12:00:00 AM PDT to 2012-09-30 11:59:00 PM PDT Quiz 2: 2012-10-01 12:00:00 AM PDT to 2012-10-07 11:59:00 PM PDT Quiz 3: 2012-10-08 12:00:00 AM PDT to 2012-10-14 11:59:00 PM PDT Quiz 4: 2012-10-15 12:00:00 AM PDT to 2012-10-21 11:59:00 PM PDT Programming Assignments There will be two programming assignments that will involve writing R code and R functions. These assignments will allow you to work on your R programming skills and practice writing and debugging code. For each programming assignment you will be asked to write R code or functions that produce output given a certain input. Your grade on the assignment will be based on whether the output your function produces matches the correct output. Details can be found in the descriptions of each programming assignment. Each programming assignment is worth 30 points and is broken down into sub-parts. For each sub-part you will be allowed an unlimited number of submissions and your latest score will be taken as the final score. Programming Assignment Due Dates Programming Assignment 1: 2012-10-07 11:59:00 PM PDT Programming Assignment 2: 2012-10-21 11:59:00 PM PDT Technical Information Regardless of your platform (Windows or Mac) you will need a high-speed Internet connection in order to watch the videos on the Coursera web site. It is possible to download the video files and watch them on your computer rather than stream them from Coursera and this may be preferable for some of you. Here is some platform-specific information: Windows The Coursera web site seems to work best with either the Chrome or the Firefox web browsers. In particular, you may run into trouble if you use Internet Explorer. The Chrome and Firefox browsers can be downloaded from Chrome: http://www.google.com/chrome Firefox: http://www.mozilla.org Mac The Coursera site appears to work well with Safari, Chrome, or Firefox, so any of these browsers should be fine. Grading Your grade in this course will consist of performance on four weekly quizzes and two programming assignments. The breakdown of the weighting for these elements is Week 1 Quiz: 10 points Week 2 Quiz: 10 points Week 3 Quiz: 10 points Week 4 Quiz: 10 points Programming assignment 1: 30 points Programming assignment 2: 30 points There is a maximum of 100 points to obtain in this course through the four quizzes and the two programming assignments. Performance in this course will be evaluated on a pass/fail basis. The final grade for the course will be based on the total number of points earned across the four quizzes and two programming assignments. In order to receive a passing grade, you must have a earned a total number of points of 70 or more. Weekly Schedule Week 1 Introduction and overview Installing R Data types, subsetting Reading/writing data Week 2 Control structures Functions Loop functions Debugging Week 3 Simulation Plotting, visualizing data Priniciples of data graphics Week 4 Objected oriented programming Data abstraction Regular expressions
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