1 / 18

ECON 3790 Statistics for Business and Economics

ECON 3790 Statistics for Business and Economics. Instructor: Ou Hu, Ph.D., CFA Youngstown State University Summer 2014. Chapter 1 Data and Statistics. Outline – Statistics in the world of business - examples What does business statistics entail? Data set as the object of statistics

erica-summers
Download Presentation

ECON 3790 Statistics for Business and Economics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ECON 3790 Statistics for Business and Economics Instructor: Ou Hu, Ph.D., CFA Youngstown State University Summer 2014

  2. Chapter 1 Data and Statistics Outline – • Statistics in the world of business - examples • What does business statistics entail? • Data set as the object of statistics • Scales of measurement • Classifications of data and statistics • Data sources

  3. Statistics in the Business and Economy • Examples • The U.S. real GDP has grown about 1.8% in the past decade; • The sales of iPhone accounts for about 25% in the global smartphone market; • In the U.S., a person with 4-year college education earns averagely twice as much as the one with a high school degree does; • By the time the lecture was prepared, the Dow Jones Industrial Average reached its historical highest point of 16167.97 on December 18, 2013.

  4. What does business statistics entail? • Statistics is the art and science of collecting, presenting, analyzing, and interpretingdata. • In business, statistics is not just about numbers and mathematics, but a tool that analyzes the available data and helps make informed and better business decisions.

  5. Data Set as the Object of Statistics • The structure of a data set: • Elements – the entities on which data are collected; • Variables – characteristics of the elements; • Observations – the set of measurements for an element.

  6. Data Set – An Example Variables An Observation Data Set Names of Elements

  7. Scales of Measurement • Data of different scales of measurement require different statistical analyses. • There are four scales of measurement: • Nominal • Ordinal • Interval • Ratio

  8. Nominal Scale • Names or labels that show the attributes of elements, variables such as • Names of companies; • Gender of employees; • Data of nominal scale can be numeric. ( For instance, ‘0’ denotes female and ‘1’ denotes male.)

  9. Ordinal Scale • It has the properties of nominal scale and the order or rank matters. For example, • Customer service rating ( poor, average, good, outstanding); • Variables of ordinal scale can assume numeric data values.

  10. Interval Scale • It has the properties of ordinal scale and the interval/difference between values is measured in the same unit. For example, • Temperatures – oF or oC • SAT scores • Data of interval scale are always numeric. • For interval data, zeros do not mean nothing. For instance, a temperature of 0 degree does not mean there is no temperature.

  11. Ratio Scale • It has the properties of interval scale and the ratio of of two values are meaningful. For example, • Weight, height, distance, time, income, etc. • Data of ratio scale are always numeric. • For ratio data, zeros do mean nothing. For instance, a profit of zero $ means there is no profit.

  12. Q1.1 – Which of the following variables uses the ordinal scale of measurement? • Paint colors • Social Security Numbers • Letter grades (A,B,C,…) • Monthly return of S&P 500 Index

  13. Q1.1 – Which of the following variables uses the ordinal scale of measurement? • Paint colors • Social Security Numbers • Letter grades (A,B,C,…) • Monthly return of S&P 500 Index Answer:c

  14. Classifications of Data • Qualitative vs. Quantitative data • Nominal and ordinal data are qualitative, while interval and ratio data are quantitative. • Mathematical operations don’t apply to qualitative data even if they are numeric. • Cross-Sectional vs. Time Series data

  15. Classifications of Statistics • Descriptive Statistics • To summarize data in an informative way; • Demonstrate patterns; • Use tables, graphs, and numerical measures.

  16. Classifications of Statistics • Inferential Statistics • A population is the entire set of data in a particular study. • Its characteristics are called population parameters. • The study of a population is probably very daunting, time-consuming, and costly. • A sample is a subset of a population. • Its characteristics are called sample statistics. • The study of a sample is much more manageable.

  17. Inferential Statistics To estimate population parameters based on sample statistics Population Parameters Sample Statistics • Sample mean: • Sample variance: • Sample proportion: • Population mean: • Population variance: • Population proportion:

  18. Data Sources • Nowadays, the public can get easy access to business and economics data online. For instance: • Yahoo! Finance • Federal Reserve Economic Data • Census Bureau

More Related