• What is Big Data?

• What is Data Science?

• Why are you taking this course?

• Big Data is the latest ‘information explosion.’

• The printing press was probably the first major one.

• Took 300 years for the world to 'settle down' after its invention.

• We're still settling down with big data…

• It's a matter of opinion…..

• polio vaccine

• smoking causes lung cancer

• fertilizing crops increases yield

• All are data oriented

• the average person needs to know about data to get along

• there are jobs working with data

• creative people needed in data field:

• http://www.forbes.com/sites/georgeanders/2015/07/29/liberal-arts-degree-tech/

• The Father of Microbiology (1632 - 1723)

• Improved the microscope in order to bring small things into focus.

• The goal of Data Science is to bring large things into focus.

"The greatest value of a picture is when it forces us to notice what we never expected to see."

• Web page: https://bb.uvm.edu

• Software: R and RStudio

• Topics (not in this exact order)….

• I. Data Wrangling (Organizing, ‘tidying’, ‘munging’ data)

• II. Data Visualization

• III. Data Analysis

• IV. Using Statistical Thinking to interpret everything

• Basic ideas

• Computing skills!!

• Managing data

• What constitutes a good Graphic? (Tufte text)

• Basic plots (base R and ggplot2)

• Fancy plots (Shinyapps, etc.?)

• Market Basket Analysis – Association Rules

• Correlation, Regression and Predictive Modeling

• Classification and Clustering methods

• http://www.fastcodesign.com/1671172/how-a-story-from-world-war-ii-shapes-facebook-today

• How was data collected? Random sampling & selection bias

• How was study designed? Random assignment & cause-effect

• Separate signal from noise: Modeling & visualizations

• Could results be due to chance? Bootstrap confidence intervals

• Presenting the results (we'll use RMarkdown)

We'll use R Studio as our "driver's seat" and we'll use R for data analysis,

summary(mtcars$wt)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   1.513   2.581   3.325   3.217   3.610   5.424

summary(mtcars$mpg)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   10.40   15.42   19.20   20.09   22.80   33.90

…and for plotting:

ggplot(data = mtcars,
       mapping = aes(wt,mpg,color=factor(cyl))) +
  geom_point()