1. Chapter 1 Introduction to Statistics
Larson/Farber 4th ed.
Larson/Farber 4th ed

2. Chapter Outline 1.1 What is Statistics? 1.2 Random Samples
1.3 Experimental Design
Larson/Farber 4th ed.

3. Section 1.1
What is Statistics?
Larson/Farber 4th ed.

4. Section 1.1 Objectives Define statistics
Define individual/observational unit
Distinguish between a population and a sample
Distinguish between a parameter and a statistic
Distinguish between descriptive statistics and inferential statistics
Distinguish between levels of measurement
Larson/Farber 4th ed.

5. What is Data? Rows: Who? Columns: What? Data needs to have context.
Chapter 1
What is Data?
Analyze.
Rows: Who? Columns: What?
Data needs to have context.
Larson/Farber 4th ed.
Larson/Farber 4th ed

6. Statements Based on Data
Data Consist of information coming from observations, counts, measurements, or responses. Statements are often based on data:
“People who eat three daily servings of whole grains have been shown to reduce their risk of…stroke by 37%.” (Source: Whole Grains Council)
“Seventy percent of the 1500 U.S. spinal cord injuries to minors result from vehicle accidents, and 68 percent were not wearing a seatbelt.” (Source: UPI)
Larson/Farber 4th ed.

7. What is Statistics? Chapter 1 Analyze. Larson/Farber 4th ed.

8. What is Statistics?
Statistics The science of collecting, organizing, analyzing, and interpreting data in order to make decisions.
Larson/Farber 4th ed.

9. What is Statistics?
Larson/Farber 4th ed.

10. What are Individuals and Variables?
Observational Unit
Variables
Weight: 1.5 pounds
Sugars: 16 grams
Age: 6 months
Weight: pounds
Analyze.
Individuals (or observational units) are people or objects included in the study
Variables are characteristics about each individual

11. Exercise 1: Individuals and Variables
We want to do a study about the people who have climbed Mt. Everest. Identify the individuals and possible variables of interest:
Variables
Individuals
Age
Sex
Weight
Tom Jones 46 M
144
Susan Anthony 23 F
137
Harry Potter 62
175
Identify.

12. Types of Data
What are Qualitative Data? Consists of attributes, labels, or non-numerical entries.
Major
Place of birth
Eye color
Larson/Farber 4th ed.

13. Types of Data
What are quantitative data? Numerical measurements or counts. Must include units.
Age
Weight of a letter
Temperature
Larson/Farber 4th ed.

14. Types of Variables
Larson/Farber 4th ed.

15. Compare: Population vs. Sample
Chapter 1
Compare: Population vs. Sample
Population
Sample
The collection of all outcomes, responses, measurements, or counts that are of interest.
A subset of the population.
Compare.
Larson/Farber 4th ed.
Larson/Farber 4th ed

16. Exercise 2: Identifying Data Sets
Chapter 1
Exercise 2: Identifying Data Sets
In a recent survey, 1708 adults in the United States were asked if they think global warming is a problem that requires immediate government action. Nine hundred thirty-nine of the adults said yes. 1. Identify the population and the sample. 2. Describe the data set. (Adapted from: Pew Research Center)
Identify.
Larson/Farber 4th ed.
Larson/Farber 4th ed

17. Solution: Identifying Data Sets
The population consists of the responses of all adults in the U.S.
The sample consists of the responses of the 1708 adults in the U.S. in the survey.
The sample is a subset of the responses of all adults in the U.S.
The data set consists of 939 yes’s and 769 no’s.
Responses of adults in the U.S. (population)
Responses of adults in survey (sample)
Larson/Farber 4th ed.

18. Solution: Identifying Data Sets
Survey: Is Global Warming a Problem?
Individuals NO
YES
TOTAL
Adult #1 X
Adult #2
. . .
Adult # 1708
939
769
1708
NOTE: The data set is the collection of responses. It is not the summary totals!
Larson/Farber 4th ed.

19. Compare: Parameter vs. Statistic
Chapter 1
Compare: Parameter vs. Statistic
Population of All Course Grades
Chem 1 A
Algebra 2 B- B+
GPA
3.27
Parameter
[Based on Population]
Geometry B
Vocab Quiz 1
>>>>>>>>>>> 88
Quiz 2
Vocab Quiz 3 80
Sample Average
88.67
Statistic
Quiz 4
[Based on Sample]
Vocab Quiz 5 98
Quiz 6
Compare.
Larson/Farber 4th ed

20. Parameter and Statistic
A number that describes a population characteristic.
Average age of all people in the United States
Statistic
A number that describes a sample characteristic.
Average age of people from a sample of three states
Larson/Farber 4th ed.

21. Distinguish: Parameter vs. Statistic
Decide whether the numerical value describes a population parameter or a sample statistic:
A recent survey of a sample of MBAs reported that the average salary for an MBA is more than $82,000. (Source: The Wall Street Journal)
Solution:
Sample statistic (the average of $82,000 is based on a subset of the population)
Larson/Farber 4th ed.

22. Distinguish: Parameter vs. Statistic
Decide whether the numerical value describes a population parameter or a sample statistic:
Starting salaries for the 667 MBA graduates from the University of Chicago Graduate School of Business increased 8.5% from the previous year.
Solution:
Population parameter (the percent increase of 8.5% is based on all 667 graduates’ starting salaries)
Larson/Farber 4th ed.

23. What is the Difference? Inferential Statistics. Descriptive Statistics
Chapter 1
What is the Difference?
Inferential Statistics.
Descriptive Statistics
Analyze.
Larson/Farber 4th ed.
Larson/Farber 4th ed

24. Branches of Statistics
Descriptive Statistics Involves organizing, summarizing, and displaying data.
e.g. Tables, charts, averages
Inferential Statistics Involves using sample data to draw conclusions about a population.
Larson/Farber 4th ed.

25. Example: Descriptive and Inferential Statistics
Chapter 1
Example: Descriptive and Inferential Statistics
Decide which part of the study represents the descriptive branch of statistics. What conclusions might be drawn from the study using inferential statistics?
A large sample of men, aged 48, was studied for 18 years. For unmarried men, approximately 70% were alive at age 65. For married men, 90% were alive at age 65. (Source: The Journal of Family Issues)
Analyze.
Larson/Farber 4th ed.
Larson/Farber 4th ed

26. Solution: Descriptive and Inferential Statistics
Chapter 1
Solution: Descriptive and Inferential Statistics
Descriptive Statistics
Possible Inference
“… being married is associated with a longer life for men.”
Status
Percentage Alive at Age 65
Unmarried
70%
Married
90%
Larson/Farber 4th ed.
Larson/Farber 4th ed

27. What is Nominal Level Data?
Chapter 1
What is Nominal Level Data?
Cases are order of preference. Variable is pesticide brand.
Larson/Farber 4th ed.
Larson/Farber 4th ed

28. What is Nominal Level Data?
Chapter 1
What is Nominal Level Data?
Characterized by data consisting of names, labels or categories
Cannot be ordered
Example: Survey Responses: Yes, No, Undecided
Example: Hair Color: Brown, Black, Red
Cases are order of preference. Variable is pesticide brand.
Larson/Farber 4th ed.
Larson/Farber 4th ed

29. What is Ordinal Level Data?
Chapter 1
What is Ordinal Level Data?
Data can be arranged in order
Differences between data entries is not meaningful
Larson/Farber 4th ed.
Larson/Farber 4th ed

30. Example: Classifying Data by Level
Chapter 1
Example: Classifying Data by Level
Two data sets are shown. Which data set consists of data at the nominal level? Which data set consists of data at the ordinal level? (Source: Nielsen Media Research)
Network Affiliates: Cases are station names. Variables are network affiliations.
Larson/Farber 4th ed.
Larson/Farber 4th ed

31. Solution: Classifying Data by Level
Ordinal level (lists the rank of five TV programs. Data can be ordered. Difference between ranks is not meaningful.)
Nominal level (lists the call letters of each network affiliate.)
Larson/Farber 4th ed.

32. What is Interval Level Data?
Quantitative data
Differences between data points makes up an interval
Differences between data points is meaningful
Zero represents a position on a scale
Zero does not imply “none”
No inherent zero
Larson/Farber 4th ed.

33. What is Ratio Level Data?
Chapter 1
What is Ratio Level Data?
Analyze.
Larson/Farber 4th ed.
Larson/Farber 4th ed

34. Levels of Measurement Ratio level of measurement
Zero entry is an inherent zero (implies “none”)
A ratio of two data values can be formed
One data value can be expressed as a multiple of another
Examples: 
Ruler (inches or centimeters )
Years of work experience
Annual income
Larson/Farber 4th ed.

35. Example: Classifying Data by Level
Two data sets are shown. Which data set consists of data at the interval level? Which data set consists of data at the ratio level? (Source: Major League Baseball)
Larson/Farber 4th ed.

36. Solution: Classifying Data by Level
Interval level (Quantitative data. Can find a difference between two dates, but a ratio does not make sense.)
Ratio level (Can find differences and write ratios.)
Larson/Farber 4th ed.

37. Data by Level: Why Does it Matter?
The level of the data determines which operations make sense for the data set
We may compute the average of data at the interval or ratio level
Larson/Farber 4th ed.

38. Summary: Levels of Measurement

39. Summary: Levels of Measurement
Level of
Measurement
Put data in
categories
Arrange
data in
order
Subtract
data
values
Determine if one data value is a multiple of another
Nominal
Yes No
Ordinal
Interval
Ratio
Larson/Farber 4th ed.