8/30/2021

Introduce Milo Levine (MSSC Tutor)

Sampling Activity - see agenda for our first day of class

• Put sticky notes on the white boards for the statistics we decide to compare
• Which statistic is best? Why?

Types of Variables

• A quantitative variable is a variable that takes on numerical values for which arithmetic makes sense.
• A categorical or qualitative variable is a variable that records which category a person place or thing falls into.

Questions about data

• What variables are being measured?
• Are these variables appropriate for answering the question(s) of interest?
• What are the units of measurement?
• How are the data recorded?

Graphical Displays

• Why are graphing techniques useful?
  • Examine the overall shape of a distribution - (symmetric or skewed?)
  • Look for deviations from the overall shape - (unusual observations, gaps, etc.)
  • Locate the center of the distribution

Stem and Leaf Plots

• Separate each observation into a stem and a leaf.
• List the stems vertically in increasing order from top to bottom.
• Add the leaves (typically the last digit) to the right of the stems.

Histograms

• Divide the range of the data into classes of equal width.
• Count the number of observations in each class.
• Compute the relative frequency or percent for each class.
• Erect bars over each class interval.

Getting started with R

• Lauch RStudio (you can download R and RStudio on your personal computer/laptop for free)
• Load our data from the class survey (ClassDataF21.csv)
  • Method 1 - mydata=read.csv(file=file.choose())
  • Method 2 - ClassDataF21<-read.csv("P:/data/MATH/STATS/Datasets/ClassDataF21.csv")
• Some basic R
  • mydata
• str(mydata)
• head(mydata)
• tail(mydata)
• names(mydata)
• libarary(mosaic) -- a package that we will be using throughout the semester.

Graphical Displays with R (Use ClassDataF21.csv)

• Bar Charts - barchart(Year, data=mydata)
• Dotplots - dotplot(Height, data=mydata)
• Stemplots - stem(mydata$Height)
• Histograms - histogram(Height, data=mydata)
• Boxplots - boxplot(mydata$HometownSize), boxplot(mydata$HometownSize~mydata$Year)
• Scatterplots - plot(Height~FootLength, data=ClassDataF21)

Please read Section 1.3 for class on Wednesday