1. Analyzing One-Variable Data
Lesson 1.1
Statistics: The Science and Art of Data
Statistics and Probability with Applications, 3rd Edition
Starnes & Tabor
Bedford Freeman Worth Publishers

2. Statistics: The Science and Art of Data
Learning Targets
After this lesson, you should be able to:
Identify the individuals and variables in a data set, then classify the variables as categorical or quantitative.
Summarize the distribution of a variable with a frequency table or a relative frequency table.

3. Statistics: The Science and Art of Data
We live in a world of data. Every day, we encounter data from scientific studies to poll results to test scores to analyses about sports. To understand what the data are saying, you need to learn more about statistics. An understanding of statistics will help you make good decisions based on data.
Statistics
Statistics is the science and art of collecting, analyzing, and drawing conclusions from data.

4. Statistics: The Science and Art of Data
Statistical Problem-Solving Process
  Ask Questions: Clarify the research problem and ask one or more valid statistics questions.
  Collect Data: Design and carry out an appropriate plan to collect the data.
  Analyze Data: Use appropriate graphical and numerical methods to analyze the data.
  Interpret Results: Draw conclusions based on the data analysis. Be sure to answer the research question(s)!

5. Statistics: The Science and Art of Data
Individual, Variable
An individual is a person, animal, or thing described in a set of data.
A variable is any attribute that can take different values for different individuals.

6. Statistics: The Science and Art of Data
Variable
A variable is any attribute that can take different values for different individuals.
Categorical Variable
Quantitative Variable
A categorical variable assigns labels that place individuals into particular groups.
A quantitative variable takes number values for which it makes sense to find an average.

7. Qualitative or Categorical Variables
Types of Variables
Qualitative or Categorical Variables
Consists of attributes, labels, or non-numerical entries.
Major
Place of birth
Eye color
Common statistic calculated: percentages
Larson/Farber 4th ed. 7

8. Quantitative Variables
Measured with units and answers questions about the quantity of what is measured.
Age
Weight of a letter
Temperature
Common statistic calculated: averages
Larson/Farber 4th ed. 8

9. BEWARE!! Not all numerical variables can be
classified as quantitative variables.
For example, consider the following list of zip codes:
These data values of the variable zip codes are certainly
Numerical, however, they are labeling locations and do
Not have units of measure. Therefore zip code is a
Categorical variable!!

10. Statistics: The Science and Art of Data

11. Statistics: The Science and Art of Data
A variable generally takes values that vary from one individual to another.
The distribution of a variable describes the pattern of variation of these values.
Distribution
The distribution of a variable tells us what values the variable takes and how often it takes these values.

12. Statistics: The Science and Art of Data
We can summarize a variable’s distribution with a frequency table or a relative frequency table.
Frequency Table
A frequency table shows the count of individuals having each data value.
Relative Frequency Table
A relative frequency table shows the proportion or percent of individuals having each data value.

13. Homework Last Night (min)
LESSON APP 1.1
What are my classmates like?
On the first day of a statistics course, the instructor gave all 40 students in the class a survey. The table below shows data from the first 10 students on the class roster.
Gender
Class
GPA
Pulse Rate
Dominant Hand
Children in Family
Homework Last Night (min)
Sleep (hours)
Have a Smartphone? F Fr
3.22 72 R 3
0-14 10 Y
2.3
110 L 8 N M Ju
3.8 60 6
15-29 7 So
3.1 2
7.5 4 51 1
45-59
3.4 68
8.5 80
30-44
3.5 59
3.9 65 Sr
144 …

14. Statistics: The Science and Art of Data
Learning Targets
After this lesson, you should be able to:
Identify the individuals and variables in a data set, then classify the variables as categorical or quantitative.
Summarize the distribution of a variable with a frequency table or a relative frequency table.