STAT 101- Exam One (Ch. 1-8) Iowa
State Questions and Answers
Statistics - ANSWER-Understanding data and making informed decisions in the face of
uncertainty; examine and understand variability to make decisions
Data - ANSWER-Pieces of information collected about cases (people, place, thing) and
is only meaningful in context
Five W's of data - ANSWER-Who, What, When, Where, Why, How
Who - ANSWER-people, places and things information was gathered on
What - ANSWER-The info/characteristics gathered
When - ANSWER-The time period in which data was collected
Where - ANSWER-Source of the data
Why - ANSWER-Goals/purpose of gathering the data
How - ANSWER-Methods used to collect this data
Categorical Variables - ANSWER-Recorded as labels, take on different categories and
must choose from an option
Quantitative Variables - ANSWER-Recorded and used as numbers, take on numeric
values, measurement units (years, lbs, number)
Cases - ANSWER-Who, rows
Variables - ANSWER-What, columns
Summarize the distribution of the categorical variable with: - ANSWER-Frequency table,
pie chart, and bar chart
Frequency table - ANSWER-Allows us to see various answers from a survey and how
it's distributed
Pie Chart - ANSWER-Comparing sizes of pie slices, add up to 100%
, Bar Chart - ANSWER-Order does not matter, measure height for differences
Contingency Table - ANSWER-Look at various distributions for our variables
Count - ANSWER-The number of observations belonging to a particular category, If you
divide this count by the total number, it's called a proportion
Frequency/ Relative frequency table - ANSWER-Summary of the distribution of one
categorical variable containing the number and proportion of observations belonging to
each category. Contains counts and proportions
Contingency Table - ANSWER-A cross-classification of observations according to the
categories of two categorical variables. This examines the relationship, explanatory is
used to explain differences in the distribution of the response
Rows - ANSWER-Categories of the explanatory variable
Columns - ANSWER-Categories of the response variable
Mosaic Plot - ANSWER-Graphical summary of conditional distributions in contingency
table, similar to bar charts
Association - ANSWER-The lines do not line up and conditional distributions are
different; closer the lines line up, less association
No association - ANSWER-Lines do line up and conditional distributions are same; lines
do not have to match up perfectly for it to be no association
Conditional distribution - ANSWER-Summarize distribution of one variable contingent
upon a particular category for other variables
Marginal distribution - ANSWER-Summarize the distribution of each variable separately,
ignoring categories of other variables
Histogram - ANSWER-A graphical summary of the distribution of the quantitative
variable
Stem-and-Leaf Plot - ANSWER-Shows every observation while a histogram only shows
a summary
Distribution of a quantitative variable can be summarized by: - ANSWER-Shape, center,
and variability
Mode - ANSWER-A peak in the histogram
Unimodal - ANSWER-One peak in histogram
State Questions and Answers
Statistics - ANSWER-Understanding data and making informed decisions in the face of
uncertainty; examine and understand variability to make decisions
Data - ANSWER-Pieces of information collected about cases (people, place, thing) and
is only meaningful in context
Five W's of data - ANSWER-Who, What, When, Where, Why, How
Who - ANSWER-people, places and things information was gathered on
What - ANSWER-The info/characteristics gathered
When - ANSWER-The time period in which data was collected
Where - ANSWER-Source of the data
Why - ANSWER-Goals/purpose of gathering the data
How - ANSWER-Methods used to collect this data
Categorical Variables - ANSWER-Recorded as labels, take on different categories and
must choose from an option
Quantitative Variables - ANSWER-Recorded and used as numbers, take on numeric
values, measurement units (years, lbs, number)
Cases - ANSWER-Who, rows
Variables - ANSWER-What, columns
Summarize the distribution of the categorical variable with: - ANSWER-Frequency table,
pie chart, and bar chart
Frequency table - ANSWER-Allows us to see various answers from a survey and how
it's distributed
Pie Chart - ANSWER-Comparing sizes of pie slices, add up to 100%
, Bar Chart - ANSWER-Order does not matter, measure height for differences
Contingency Table - ANSWER-Look at various distributions for our variables
Count - ANSWER-The number of observations belonging to a particular category, If you
divide this count by the total number, it's called a proportion
Frequency/ Relative frequency table - ANSWER-Summary of the distribution of one
categorical variable containing the number and proportion of observations belonging to
each category. Contains counts and proportions
Contingency Table - ANSWER-A cross-classification of observations according to the
categories of two categorical variables. This examines the relationship, explanatory is
used to explain differences in the distribution of the response
Rows - ANSWER-Categories of the explanatory variable
Columns - ANSWER-Categories of the response variable
Mosaic Plot - ANSWER-Graphical summary of conditional distributions in contingency
table, similar to bar charts
Association - ANSWER-The lines do not line up and conditional distributions are
different; closer the lines line up, less association
No association - ANSWER-Lines do line up and conditional distributions are same; lines
do not have to match up perfectly for it to be no association
Conditional distribution - ANSWER-Summarize distribution of one variable contingent
upon a particular category for other variables
Marginal distribution - ANSWER-Summarize the distribution of each variable separately,
ignoring categories of other variables
Histogram - ANSWER-A graphical summary of the distribution of the quantitative
variable
Stem-and-Leaf Plot - ANSWER-Shows every observation while a histogram only shows
a summary
Distribution of a quantitative variable can be summarized by: - ANSWER-Shape, center,
and variability
Mode - ANSWER-A peak in the histogram
Unimodal - ANSWER-One peak in histogram
