Statistics Chapter 1 complete test
with 100% correct answers
Individuals - ANSWER-Objects described by a set of data; may be people, animals or things.
Variable - ANSWER-Characteristic of an individual; can take different values for different
individuals.
When you first meet a new data set, ask yourself the following questions: - ANSWER-Who
are the individuals described by the data? How many individuals are there? What are the
variables? In what units is each variable recorded?
Categorical variable - ANSWER-Places an individual into one of several groups or categories
Quantitative variable - ANSWER-Takes numerical values for which it makes sense to find an
average
Do numbers guarantee a quantitative variable? - ANSWER--Not every variable that takes
number values is quantitative.
-Other categorical variables are created by grouping values of a quantitative variable into
classes
How do we determine how to analyze variables? - ANSWER-The proper method of analysis
for a variable depends on whether it is categorical or quantitative.
Case - ANSWER-Another name used for individual
Common setup of data tables - ANSWER-Each row is an individual; each column is a variable.
Distribution - ANSWER-What values the variable takes and how often it takes these values.
How do we explore data? - ANSWER--Begin by examining each variable by itself. Then move
on to study relationships among the variables.
-Start with a graph or graphs. Then add numerical summaries.
Inference - ANSWER-Draw conclusions beyond the data
- Depends on probability; study of chance behavior
- What are the chances?
Values of a categorical variable - ANSWER-Labels for the categories
Distribution of a categorical variable - ANSWER-Lists the categories and gives either the
count or the percent of individuals who fall into each category
Frequency table - ANSWER-Displays the counts (frequencies) of individuals in a category
, Relative frequency table - ANSWER-Shows the percents (relative frequencies) of individuals
in a category
Roundoff error - ANSWER-Don't point to mistakes in our work, just to the effect of rounding
off results
- Ex: percents don't add to 100
Two types of charts/graphs for categorical variables - ANSWER-1.) Pie Chart
2.) Bar Graph/Chart
What is important to consider when reading data? - ANSWER-Whether the data you have
help answer your questions.
Pie Chart - ANSWER-Pie charts show the distribution of a categorical variable as a "pie"
whose slices are sized by the counts or percents for the categories. A pie chart must include
all the categories that make up a whole.
Use a pie chart only when you want to emphasize each category's relation to the whole.
Bar graph/chart - ANSWER-Bar graphs represent each category as a bar. The bar heights
show the category counts or percents. Bar graphs are easier to make than pie charts and are
also easier to read.
Advantages of bar graph when compared to a pie chart - ANSWER-Both graphs can display
the distribution of a categorical variable, but a bar graph can also compare any set of
quantities that are measured in the same units.
Comparison w/ bar graphs - ANSWER-Compare several quantities by comparing the heights
of bars that represent the quantities
Good bar graphs; area and height - ANSWER-Our eyes react to the area of the bars as well as
to their height. When all bars have the same width, the area (width × height) varies in
proportion to the height, and our eyes receive the right impression. Make the bars equally
wide for a bar graph.
What should we beware of when looking at graphs? - ANSWER-1.) Pictography
2.) Scales
Misleading/may get distorted impression of relative frequencies or percentages of
categories
Two-way table - ANSWER-Organized two categorical variables; often used to summarize
large amounts of information by grouping outcomes into categories.
Row variable - ANSWER-Described by each row in a two-way table
Column variable - ANSWER-Described by each column in a two-way table
What should you do if there are no totals and why? - ANSWER-Calculate them b/c it helps
with marginal distribution
with 100% correct answers
Individuals - ANSWER-Objects described by a set of data; may be people, animals or things.
Variable - ANSWER-Characteristic of an individual; can take different values for different
individuals.
When you first meet a new data set, ask yourself the following questions: - ANSWER-Who
are the individuals described by the data? How many individuals are there? What are the
variables? In what units is each variable recorded?
Categorical variable - ANSWER-Places an individual into one of several groups or categories
Quantitative variable - ANSWER-Takes numerical values for which it makes sense to find an
average
Do numbers guarantee a quantitative variable? - ANSWER--Not every variable that takes
number values is quantitative.
-Other categorical variables are created by grouping values of a quantitative variable into
classes
How do we determine how to analyze variables? - ANSWER-The proper method of analysis
for a variable depends on whether it is categorical or quantitative.
Case - ANSWER-Another name used for individual
Common setup of data tables - ANSWER-Each row is an individual; each column is a variable.
Distribution - ANSWER-What values the variable takes and how often it takes these values.
How do we explore data? - ANSWER--Begin by examining each variable by itself. Then move
on to study relationships among the variables.
-Start with a graph or graphs. Then add numerical summaries.
Inference - ANSWER-Draw conclusions beyond the data
- Depends on probability; study of chance behavior
- What are the chances?
Values of a categorical variable - ANSWER-Labels for the categories
Distribution of a categorical variable - ANSWER-Lists the categories and gives either the
count or the percent of individuals who fall into each category
Frequency table - ANSWER-Displays the counts (frequencies) of individuals in a category
, Relative frequency table - ANSWER-Shows the percents (relative frequencies) of individuals
in a category
Roundoff error - ANSWER-Don't point to mistakes in our work, just to the effect of rounding
off results
- Ex: percents don't add to 100
Two types of charts/graphs for categorical variables - ANSWER-1.) Pie Chart
2.) Bar Graph/Chart
What is important to consider when reading data? - ANSWER-Whether the data you have
help answer your questions.
Pie Chart - ANSWER-Pie charts show the distribution of a categorical variable as a "pie"
whose slices are sized by the counts or percents for the categories. A pie chart must include
all the categories that make up a whole.
Use a pie chart only when you want to emphasize each category's relation to the whole.
Bar graph/chart - ANSWER-Bar graphs represent each category as a bar. The bar heights
show the category counts or percents. Bar graphs are easier to make than pie charts and are
also easier to read.
Advantages of bar graph when compared to a pie chart - ANSWER-Both graphs can display
the distribution of a categorical variable, but a bar graph can also compare any set of
quantities that are measured in the same units.
Comparison w/ bar graphs - ANSWER-Compare several quantities by comparing the heights
of bars that represent the quantities
Good bar graphs; area and height - ANSWER-Our eyes react to the area of the bars as well as
to their height. When all bars have the same width, the area (width × height) varies in
proportion to the height, and our eyes receive the right impression. Make the bars equally
wide for a bar graph.
What should we beware of when looking at graphs? - ANSWER-1.) Pictography
2.) Scales
Misleading/may get distorted impression of relative frequencies or percentages of
categories
Two-way table - ANSWER-Organized two categorical variables; often used to summarize
large amounts of information by grouping outcomes into categories.
Row variable - ANSWER-Described by each row in a two-way table
Column variable - ANSWER-Described by each column in a two-way table
What should you do if there are no totals and why? - ANSWER-Calculate them b/c it helps
with marginal distribution
