1. Introduction to Statistics BUSA 2100, Sect. 1.0, 1.2 - 1.5 Dr. Moore

2. Definition of Statistics l Many people think of statistics as large amounts of numerical data, e.g. stock prices, sports statistics. l Definition: The academic discipline of statistics is the study of how data are collected, analyzed, summarized, presented, and interpreted.

3. Why Study Statistics? l 1.Statistics are widely used in bus- iness. Usage continues to increase as the business world becomes larger, more complex, and more quantitative. l 2.Statistics provide data and tools for better quality decision making.

4. Why Study Stat? / Definitions l 3. Decisions made using quantitative data tend to be more accurate, more objective, and more easily defended. l Definition: Data are facts and figures. l Qualitative or categorical data: labels, names, non-numeric descriptions, and numeric codes. (State examples.)

5. More About Data l Quantitative data: always numeric; indicate how much or how many. l Where do data come from? We will consider 5 source categories. l 1. Internal business records: personnel records, sales records, inventory records, financial statements

6. Sources of Data l 2. Internet: company web sites l 3. Experimental studies: prescription drug comparisons, agricultural plots l 4. Governmental agencies: Dept. of Labor (wages, employment rates); Census Bureau (populations, data about households). l 5. Surveys: Questionnaires or interviews to obtain information about topics of interest.

7. Branches of Statistics l The academic discipline of statistics can be divided into two major branches: descriptive and inferential statistics. l Descriptive statistics: Deals with summarizing and presenting data in a readable, easily understood form. l Ex.: Graphs, tables, charts, averages

8. Descriptive Stat. Example l Example: Daily high temperatures in Atlanta for the past 10 years; N = 3,650.

9. Inferential Statistics l The amount of data has been greatly reduced and is much easier to under- stand. l Inferential statistics: Drawing conclusions about a population based on information from a sample.

10. Populations and Samples l Population: Set of all items of interest in a particular study. l Sample: A subset (portion) of the population. l Examples of inferential statistics: Nielsen TV ratings surveys, political preference polls.