Stats: Modeling the World - Bock, Velleman, & DeVeaux
Key Vocabulary:
 Statistics
 context
 data, datum
 cases
 respondent
 subject
Calculator Skills:
 participant
 experimental unit
 observation
 representative
 sample
 population
 variable
 units
 individual
 variable
 categorical
 quantitative
 enter data in a list
 change a datum
 delete a datum
 name a new list
 clear a list
 delete a list
1.
Name three things you learned about Statistics in Chapter 1.
 recreate a list
 copy a list
2.
The authors claim that this book is very different from a typical mathematics textbook.
Would you agree or disagree, based on what you read in Chapter 1? Explain.
3.
According to the authors, what are the “three simple steps to doing Statistics right?”
4.
What do the authors refer to as the “W’s of data?”
5.
Why must data be in context (the W’s)?
Chapter 1: Stats Starts Here
Chapter 2: Data

Stats: Modeling the World - Bock, Velleman, & DeVeaux
Key Vocabulary:
 frequency table
 relative frequency table
 distribution
 area principle
 bar chart
 pie chart
 categorical data condition
 contingency table
 marginal distribution
 conditional distribution
 independence
 segmented bar chart
 Simpson’s Paradox
1.
According to the authors, what are the three rules of data analysis?
2.
Explain the difference between a frequency table and a relative frequency table.
3.
What is the area principle?
4.
When is it appropriate to use a bar chart?
5.
When is it appropriate to use a pie chart?
6.
When is it appropriate to use a contingency table?
7.
What does a marginal distribution show?
8.
When is it appropriate to look at a conditional distribution?
9.
What does it mean for two variables to be independent?
Chapter 4: Displaying and Summarizing Quantitative Data

Stats: Modeling the World - Bock, Velleman, & DeVeaux
10.
How does a segmented bar chart compare to a pie chart?
11.
Explain what is meant by Simpson’s Paradox.
Key Vocabulary:
 distribution
 histogram
 relative frequency histogram
 gap
 stem-and-leaf display
 dotplot
 shape
 center
 spread
 mode
Calculator Skills:
 unimodal
 bimodal
 multimodal
 uniform
 symmetric
 tail
 skewed
 outliers
 median
 range
 quartile
 interquartile range (IQR)
 percentile
 5-number summary
 mean
 resistant
 variance
 standard deviation
 display a histogram  Display 1-Var Stats
1.
What is meant by a distribution ?
2.
Explain the difference between a histogram and a relative frequency histogram .
3.
In what ways are histograms similar to stem-and-leaf displays ?
4.
Name some advantages of stem-and-leaf displays.
Chapter 4: Displaying and Summarizing Quantitative Data

Stats: Modeling the World - Bock, Velleman, & DeVeaux
5.
When is it more appropriate to use a histogram rather than a stem-and-leaf display ?
6.
Name some advantages of dotplots.
7.
When describing a distribution , what three things should you always mention?
8.
What should you look for when describing the shape of a distribution (try to find five things)?
9.
In general, what is meant by the center of a distribution ?
10.
In general, what is meant by the spread of a distribution ?
11.
What is a better way to describe the spread of a distribution ?
12.
What is meant by the 5-number summary ?
13.
When is it more appropriate to use the mean as a measure of center rather than the median ?
14.
What does referring to the median as a resistant measure indicate?
15.
When is it more appropriate to use the median as a measure of center rather than the mean ?
Chapter 5: Understanding and Comparing Distribtions

Stats: Modeling the World - Bock, Velleman, & DeVeaux
16.
Why is the standard deviation considered a more powerful approach to summarizing the spread?
17.
What is the relationship between the variance and the standard deviation ?
18.
When many data values are far from the center of a distribution, how will this be reflected in the standard deviation and the IQR ?
19.
What is the danger in summarizing a variable with the mean and the standard deviation ?
Key Vocabulary:
 boxplot
 outlier
Calculator Skills:
 far outlier
 comparing distributions
 modified boxplots  ZoomStat
19.
What is meant by an upper fence and lower fence ?
20.
How are outliers determined?
21.
What should you look for when comparing two histograms ?
 comparing boxplots
 timeplot
Chapter 5: Understanding and Comparing Distribtions

Stats: Modeling the World - Bock, Velleman, & DeVeaux
22.
What should you look for when comparing two or more boxplots ?
23.
What does the text recommend we “do” with outliers ?
24.
What should we never do with outliers?
25.
What is a timeplot ?
26.
Why is skewed data sometimes re-expressed using a mathematical function such as logarithms?
27.
How is re-expressing data helpful with regard to the spread across different groups?
Chapter 5: Understanding and Comparing Distribtions