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Introduction to Statistics

Introduction to Statistics. BUSA 2100, Sect. 1.0, 1.2 - 1.5 Dr. Moore. Definition of Statistics. Many people think of statistics as large amounts of numerical data, e.g. stock prices, sports statistics.

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Introduction to Statistics

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

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

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

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

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

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

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

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

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

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

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