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ECON 3790 Statistics for Business and Economics

Instructor: Ou Hu, Ph.D., CFA

Youngstown State University

Summer 2014

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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

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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.

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What does business statistics entail?

Statistics is the art and science of collecting, presenting, analyzing, and interpreting data.

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.

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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.

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Data Set – An Example

Names of Elements

Company ExchangeMarket Capitalization

($Billion)Market Risk (Beta)

Apple Inc. Nasdaq 496 0.63Boeing NYSE 102 0.94Netflix Nasdaq 23 1.79Starbucks Nasdaq 59 0.75Wal-Mart NYSE 252 0.3

Data Set

An Observation

Variables

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Scales of Measurement

Data of different scales of measurement require different statistical analyses.

There are four scales of measurement:• Nominal • Ordinal • Interval • Ratio

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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.)

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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.

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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.

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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.

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Q1.1 – Which of the following variables uses the ordinal scale of measurement?

a. Paint colors

b. Social Security Numbers

c. Letter grades (A,B,C,…)

d. Monthly return of S&P 500 Index

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Q1.1 – Which of the following variables uses the ordinal scale of measurement?

a. Paint colors

b. Social Security Numbers

c. Letter grades (A,B,C,…)

d. Monthly return of S&P 500 Index

Answer: c

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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

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Classifications of Statistics

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

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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.

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Inferential Statistics

Sample Statistics

Population Parameters

Sample mean:

Sample variance:

Sample proportion:

Population mean:

Population variance:

Population proportion:

X

2S 2

P P

To estimate population parameters based on sample statistics

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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