1/19/2022

Casey Flueckiger (MSSC Tutor)

Questions on our Sampling Activity - see agenda for our first day of class

• How would you decide which rule or statistic is best?

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

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 (I will demo the commands below, which you can find in the file ClassDataS22.R)

• Lauch RStudio
• Load our data from the class survey (ClassDataS22.csv)
  • Method 1 - ClassDataS22=read.csv(file=file.choose())
  • Method 2 (need the path) - ClassDataS22<-read.csv("G:/My Drive/Stat206-DataAnalysis-S2022/!Class Material/Day1-S2022.csv")
• Some basic R
  • ClassDataS22
• str(ClassDataS22)
• head(ClassDataS22)
• tail(ClassDataS22)
• names(ClassDataS22)
• libarary(mosaic) -- a package that we will be using throughout the semester.

Graphical Displays with R (Use ClassDataS22.csv)

• Histograms - histogram(~Height, data=ClassDataS22)
• Boxplots - boxplot(ClassDataS22$Age), boxplot(Age~Year, data=ClassDataS22)
• Scatterplots - plot(Height~FootLength, data=ClassDataS22)

Please read Section 1.3 for class on Friday and complete the handout R_Introduction.pdf in our !Class-Notes folder on Google Drive.