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Statistics
a science dealing with the collection, analysis, interpretation, and presentation of numerical data.

Accounting
auditing and cost estimation

Economics
Regional, national and international economics performance

Finance
investments and portfolio management

Management
 human resources, compensation, and quality management

Management Information Systems
performance of systems which gather, summarize, disseminate information to various managerial levels.

Marketing
market analysis and consumer research

International Business
market and demographic analysis.

Descriptive statistics
using data gathered on a group to describe about the group

Inferential statistics
data gathered from a sample and used to reach conclusions about population from which data was gathered.

Population
The whole collection of persons, objects, or items under study.

Census
Gathering data from the entire population

Parameter:
Descriptive measure of the population. Usually represented by Greek letters.

Statistic
Descriptive measure of a sample. Usually represented by Roman letters.

Nominal Level Data:
can be used only to classify or categorize. The categorize can be numbered, but no ordering of the cases is implied. e.g. gender, religion, ethnicity, political affiliation, geographic location, place of birth, job, SSN, telephone numbers, area code, ZIP codes.

Ordinal Level Data:
Can be used to rank or order objects. Like first place, second place, third place, etc. Or: Instructor displayed interest in student’s learning, rank interest on 1 to 10 with 10 as the highest and 1 as the lowest.

Interval Level Data:
If the data always numerical and the distances between consecutive numbers are equal, and location of origin (zero) is arbitrary. e.g. Fahrenheit Temperature and Celsius Temperature (note: zero degree is just another point on the scale and does not mean the absence of the temperature), percentage change in employment, percentage return on a stock, dollar change in stock price.

Ratio Level Data:
Ratio level data have the same properties as interval level data, but reatio level data have an absolute zero, and the ratio of two numbers is meaningful. e.g. height, weight, time, volume, distance, number of people, age, profit and loss, revenue, expenses, financial ratios (P/E Ratio, Inventory Turnover, Quick Ratio).

