Assessing Happiness and Competitiveness of World Major Metropolises, 2006 empirically examines happiness and community/city conditions assessed by residents living in ten major cities of the world: Beijing, Berlin, London, Milan, New York City, Paris, Seoul, Stockholm, Tokyo, and Toronto. Respondents were asked questions about themselves and their city of residence. Questions focused on a range of topics including the economy, culture and education, welfare, safety, environment, living conditions, city administration, community life, health, and happiness. Demographic questions included city of residence, gender, age, education level, income level, occupation, marital status, and religion.
Crime in Boomburb Cities: 1970-2004 focused on the effect of economic resources and racial/ethnic composition on the change in crime rates from 1970-2004 in United States cities in metropolitan areas that experienced a large growth in population after World War II. A total of 352 cities in the following United States metropolitan areas were selected for this study: Atlanta, Dallas, Denver, Houston, Las Vegas, Miami, Orange County, Orlando, Phoenix, Riverside, San Bernardino, San Diego, Silicon Valley (Santa Clara), and Tampa/St. Petersburg. Selection was based on the fact that these areas developed during a similar time period and followed comparable development trajectories. In particular, these 14 areas, known as the “boomburbs” for their dramatic, post-World War II population growth, all faced issues relating to the rapid growth of tract-style housing and the subsequent development of low density, urban sprawls. The study combined place-level data obtained from the United States Census with crime data from the Uniform Crime Reports for five categories of Type I crimes: aggravated assaults, robberies, murders, burglaries, and motor vehicle thefts. The dataset contains a total of 247 variables pertaining to crime, economic resources, and race/ethnic composition.
R is freely available, open source statistical software that has been widely adopted in the research community. Due to its open nature, thousands of add-ons (“packages” in R parlance) are available that handle many specialized functions and implement the latest statistical techniques. Ryan Womack, the Data Librarian, is presenting a three-part workshop series, “An Introduction to R” covering
Statistical Techniques: Descriptive Statistics, Regression, Significance, Finding Additional Packages
Graphics: comparison of graphing techniques of basic R, lattice, and ggplot2 packages
Data Manipulation: Data Import and Transformation
This is the schedule for Fall 2011:
Workshops will run for three consecutive weeks at the following times; choose the time that is most convenient for you.
Tuesdays 10-11:30 (Sept 6, Sept 13, Sept 20)
Wednesdays 1-2:30 (Sept 7, Sept 14, Sept 21)
Fridays 12-1:30 (Sept 9, Sept 16, Sept 23)
Put another way,
Statistical Techniques will be covered in the 1st week: Sept 6-9
Graphics will be covered in the 2nd week: Sept 13-16
Data Manipulation will be covered in the 3rd week: Sept 20-23
All workshops will be held in Alexander Library, Room 413 (4th floor of the new wing).
Each workshop is self-contained and will be hands-on with the software. A beginner would want to attend all three, but if there is one aspect
you want to brush up on, it is fine to attend that single session as well. All sessions are first come, first served (the lab has 23 PCs). If you have R on your laptop, feel free to bring it too. There is no need to register.
More R stuff at http://libguides.rutgers.edu/content.php?pid=115296&sid=1208422