Chapter 1 Introduction: Stats Starts Here, Data  Distinguish between Statistics and statistics  Identify different types of data variables Objectives: be able to –

Statistics: An Overview  Everyday experiences: Gallup polls, newspaper articles, lotteries, CPI, unemployment data, your admittance to NCSU (predicted GPA) Basic stock dataCollege data Increasing in importance; used in more and more ways in many disciplines NY Times: StatisticsNY Times: Statistics Sports AnalyticsSports Analytics NCSU Sports Analytics

Common Situations that Require Statistics 1. An opinion poll wants to know what fraction of the public approves of the president’s performance in office. 2. Will a new package design increase sales enough to pay the cost of implementing the new design Tropicana DisasterTropicana Disaster 3. Gov’t economists release monthly reports about the nation’s economic activity 4. 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 a Decade AgoData Flow Now Marketing Survey

Examples-1 Many election year polls s/general_election_romney_vs_obama-1171.html

Examples-2  Surveys about the US:  American Community Survey  Consumer Price Index  Unemployment Rate (political hot potato!)  Billion Prices Project MIT (sampling?)  Nielsen TV Ratings How does Nielsen work?

Top shows of a recent season 1.Sunday Night Football NBC American Idol (Wed.) Fox NCIS CBS American Idol (Thu.)Fox Dancing With the Stars ABC NCIS: Los Angeles CBS Dancing With the Stars Results ABC The Big Bang Theory CBS 15.9 * The Voice NBC The Mentalist CBS 14.8 Nielsen Ratings (name, network, avg. weekly viewers) Top shows of a recent season (18-49) 1.Sunday Night Football NBC American Idol (Wed.) Fox 8 3. The Voice NBC Modern Family ABC The Big Bang Theory CBS 7.1 * American Idol (Thu.)Fox Two and a Half Men CBS Broke Girls CBS 5.6 * The X Factor (Wed.) Fox Grey’s Anatomy ABC 5.5 Statistics and data determine which shows survive and which are canceled

Data Determines Ratings. Ratings Are IMPORTANT! million-on-cbs

Broad Definition Many disciplines can be summarized in a few words:  Economics is about … Money (and why it is good)  Psychology: Why we think what we think  Biology: Life  Anthropology: Who?  History: What, where, and when?  Philosophy: Why?  Engineering: How?  Accounting: How much?  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 1. Descriptive statistics utilizes numerical and graphical methods to summarize data, look for patterns and trends, present information Descriptive statistics lack a measure of reliability

Statistics Overview: 2 Primary Methods of Analyzing Data-2 2. Inferential statistics Uses data to make estimates, decisions, predictions or other generalizations about a larger data set or population Opinion Polling Inferential statistics have a measure of reliability

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