Outline of Material for Exam 1
This outline is intended to help you in studying for the first exam. However, you are
responsible for all material covered in class and in chapters 1-8 of the book (except for
time series in chapter 1, Simpson’s Paradox in chapter 5 and blocking in chapter 8).
Chapter 1: Picturing Distributions with Graphs
Individuals
Categorical vs. Quantitative Variables: Know the difference between categorical and
quantitative variables. Given a data set be able to tell whether the data is quantitative or
categorical.
Graphs: Stemplots, dotplots, histogram, bar chart and pie chart. Know which graphs
should be used for categorical data and which should be used for quantitative data. Know
when it is appropriate to use each kind of graph. Be able to make stemplots and dotplots.
Be able to interpret all five graphs.
Histograms: Be able to discuss the shape(symmetry, modality), center, spread and
outliers .
Chapter 2: Describing Distributions with Numbers
Mean & Standard Deviation vs. Five Number Summary: Know when to use the mean &
standard deviation as a measure of center and spread versus when to use the five number
summary as a measure of center and spread.
Be able to find the mean and standard deviation of a data set (you can use built in
calculator functions).
Be able to find the five number summary by hand.
Be able to determine which observations are outliers using the 1.5*IQR rule.
Boxplot: Be able to make a boxplot, by hand, using the method shown in class (denote
outliers with *, know rules for how far to extend the whiskers). By examining a boxplot
be able to discuss shape, center, spread and outliers.
Chapter 3: Scatterplots and Correlation
Scatterplot: Given a scatterplot be able to discuss its direction, form and strength. Be able
to identify any outliers.
Positive and Negative Association
Explanatory and response variables
Know the properties and interpretation of r.
Chapter 4: Regression
Be able to interpret Minitab output for regression.
Given the Minitab regression output, be able to write the regression line in the form
bxay
ˆ
.
Given
x
,
y
, Sx, Sy and r be able to find the equation of the least squares regression
line.
Be able to interpret the slope and y-intercept.
Be able to predict/estimate y given a value of x.
Be able to interpret r2.
