Lecture Unit 1Distinguish between Statistics and statistics
Identify different types of data variables
Objectives: be able to –
Common Situations that Require Statistics
An opinion poll wants to know what fraction of the public approves of the president’s performance in office.
Will a new package design increase sales enough to pay the cost of implementing the new design Tropicana Disaster
Gov’t economists release monthly reports about the nation’s economic activity
Baseball salary arbitration (one or the other)
The Flood of Data
90% of all data created by humankind has been created in the last 2 years
The Flood of Data
Data Flow Now
1.Sunday Night Football NBC 20.7
2. American Idol (Wed.) Fox 20.1
3. NCIS CBS 19.7
5. Dancing With the Stars ABC 18.3
6. NCIS: Los Angeles CBS 16.3
7. Dancing With the
Stars Results ABC 16.2
* The Voice NBC 15.9
Nielsen Ratings
1.Sunday Night Football NBC 10.2
2. American Idol (Wed.) Fox 8
3. The Voice NBC 7.9
4. Modern Family ABC 7.4
5. The Big Bang Theory CBS 7.1
* American Idol (Thu.)Fox 7.1
8. 2 Broke Girls CBS 5.6
* The X Factor (Wed.) Fox 5.6
10. Grey’s Anatomy ABC 5.5
Statistics and data determine which shows survive and which are canceled
Beginning of lecture unit 2 in coursepack
Data Determines Ratings. Ratings Are IMPORTANT!
Broad Definition
Psychology: Why we think what we think
Biology: Life
Anthropology: Who?
Philosophy: Why?
Engineering: How?
Statistics is about … Variation
The discipline of Statistics deals with the efficient collection and the analysis of data to solve real-world problems in the presence of variability.
More Specifically …
Q. What is Statistics?
Q. What are statistics?
A. Statistics is a way of reasoning, along with a set of tools and methods, designed to help us understand the world.
A. statistics are quantities calculated from data.
Statistics Overview: 2 Primary Methods of Analyzing Data
Descriptive statistics
utilizes numerical and graphical methods to summarize data, look for patterns and trends, present information
Descriptive statistics
Statistics Overview: 2 Primary Methods of Analyzing Data-2
Inferential statistics
Uses data to make estimates, decisions, predictions or other generalizations about a larger data set or population
Population versus sample
Population: The entire group of individuals in which we are interested but can’t usually assess directly.
Examples: All humans, all working-age people in California, all crickets
Sample: The part of the population we actually examine and for which we do have data. How well the sample represents the population depends on the sample design.
Population
Sample
A parameter is a number describing a characteristic of the population.
A statistic is a number describing a characteristic of a sample.
Some populations are conceptual, they do not actually exist, they are hypothetical.
Example of conceptual population: the times it would take all eligible financial aid applicants to complete the FAFSA form.
Sample Statistics Estimate Parameters
Values of population parameters are unknown; in addition, they are unknowable.
Example: The distribution of heights of all adult females (at least 18 yrs of age) in the United States has average (or mean) value µ. µ is a population parameter whose value is unknown and unknowable
The heights of 1500 females are obtained from a sample of government records. The sample average of the 1500 heights is calculated to be 64.5 inches.
The sample average is a sample statistic that we use to estimate the unknown population parameter µ.
End of Chapter 1