1. Statistics Data

2. Other Variables Alaska Airlines 501/3775 = 13.3%
On Time
Delayed
Alaska Airlines
3274
501
America West
6438
787
Alaska Airlines 501/3775 = 13.3%
America West 787/7225 = 10.9%
Alaska Airline
America West
On Time
Delayed
Los Angeles
497 62
694
117
Phoenix
221 12
4840
415
San Diego
212 20
383 65
San Francisco
503
102
320
129
Seattle
1841
305
201 61
Total
3274
501
6438
787
Los Angeles: Alaska Airline 62/559 = 11.1%
America West 117/811 = 14.4%
Phoenix: Alaska Airline 12/233 = 5.2%
America West 415/5255 = 7.9%

3. “70% OF PARENTS SAY KIDS NOT WORTH IT”
Quote from Ann Landers article
A statistically designed poll where all parents get an equal chance to answer shows 91% of parents would have children again.
A new advertisement for Ben and Jerry’s ice cream introduced in late May of last year resulted in a 30% increase in ice cream sales for the following three months. Thus, the advertisement was effective.
The more churches in a city, the more crime there is. Thus, churches lead to crime.

4. Statistics
Has become more popular over the past 4 decades or so. Why?? Computers and computer software! Used for research in nearly every possible profession. A lot of college programs require some type of statistics class.

5. True or False
“There are three kind of lies: lies, damned lies, and statistics.”
However, statistics are numerical facts such as:
Family income
Age of a student
Percentage of passes completed
Starting salary of a college graduate

6. Definition
Statistics – a group of methods used to collect, analyze, present, and interpret data and to make decisions Make an educated guess (statistics) vs a pure guess (a shot in the dark). Think about multiple choice questions.

7. Theoretical vs applied
Theoretical (or mathematical) statistics – development, derivation, and proof of statistical theorems, formulas, rules, and laws Applied – application of those theorems, formulas, rules, and laws We will focus on applied so we can think statistically and make educated guesses.

8. More Definitions
Using data collected on student test scores as an example
Data set
elements
observation
Test scores
Test 1
Test 2
Test 3
Test 4
Allen 79 83 70 81
Betty 98 90 92 85
Carl 91 93
Diane 61 75
Variable

9. Data set – collection of observations or measurements - the whole set of numbers that represents the scores of the students Element (or Member) – a specific subject or object included in a sample or population - name of each student Observation (or Measurement) – the value of a variable for an element - score for each student Variable – a characteristic under study that assumes different values for different elements - each test

10. Practice 1. 2. Season Average attendance at Interleague Games 1999
33352
2000
33212
2001
33692
2002
31921
2003
30894
2004
32976
Company
2004 Profits (millions of $)
Wal-Mart Stores
10267
Exxon
25330
General Electric
16593
Citigroup
17046
Home Depot
5001
Pfizer
11361
Target
3198
Give examples of a variable, an observation or measurement, an element or member, and data set

11. Descriptive Statistics
Data sets are usually too large, so we use
Graphs
Tables
Summary measures
Descriptive Statistics – consists of methods for organizing, displaying, and describing data by using tables, graphs, and summary measures

12. Inferential Statistics
Since it is not easy to get data on entire populations (collection of all elements of interest) we use a sample (selection of a few elements from the population).
Inferential Statistics – consists of methods that use sample results to help make decisions or predictions about a population

13. Population vs. Sample Suppose we are interested in
The percentage of all voters in a city who will vote for a particular candidate in an election
The 2005 gross sales of all companies in New York City
The price of all houses in California
In these examples notice ALL voters, ALL companies, and ALL houses

14. Population vs. Sample
Population - consists of all elements – individuals, items, or objects – whose characteristics are being studied Sample – a portion of the population selected for study

15. Practice
Explain whether each of the following constitutes a population or a sample
Pounds of bass caught by all participants in a bass fishing derby.
Credit card debts of 100 families selected from a city.
Number of home runs hit by all Major League baseball players in the 2009 season.
Number of parole violations by all 2147 parolees in a city.
Amount spent on prescription drugs by 200 senior citizens in a large city.
Yearly expenditures on clothes for 50 persons.
Total items produced on a machine for each year from 1995 to 2005.

16. Survey and Census
Survey – collection of information from the elements of a population or sample
Census – survey that includes every element of the target population
Since census is expensive and time consuming we usually use a sample of elements from the whole population
A sample survey is a technique of collecting information from a portion of the population

17. Other samples
Representative Sample – sample that represents the characteristics of the population as closely as possible
Average income of New York City families
Random Sample – a sample draw in such a way that each element of the population has an equally likely chance of being selected.

18. To replace or not to replace…
With replacement – each time we select an element from the population, we put it back in the population before we select the next element. (we can select the same element more than once)
Without replacement – the selected element is not replaced back into the population, therefore reducing the population by one element for the next selection. (we cannot select the same element more than once)

19. Quantitative vs. Qualitative
Quantitative variable – A variable that can be measured numerically
Discrete variable – a variable whose values are countable, or can only assume certain values with no intermediate values
Continuous variable – A variable that can assume any numerical value over a certain interval or intervals
Qualitative (or Categorical) variable – A variable that cannot assume a numerical value but can be classified into two or more nonnumeric categories

20. Quantitative (numerical)
Variable
Quantitative (numerical)
Discrete
(number of houses, students, cows in a field)
Continuous
(height, weight, time)
Qualitative
(make of car, hair color, gender)

21. Practice
Indicate which of the following variables are quantitative and which are qualitative.
Number of persons in a family
Color of cars
Marital status of people
Length of a frogs jump
Number of errors in a person’s credit report
Number of typographical errors in newspapers
Monthly TV cable bills
Spring break locations favored by college students
Number of cars owned by families
Lottery revenues of states

22. Practice discrete vs. continuous
Indicate which of the following quantitative variables are discrete and which are continuous.
Number of persons in a family
Length of a frogs jump
Number of errors in a person’s credit report
Number of typographical errors in newspapers
Monthly TV cable bills
Number of cars owned by families
Lottery revenues of states