This document summarizes quantitative data analysis methods for hypothesis testing including measures of central tendency, variability, relative standing, and linear relationships. It also discusses data warehousing, data mining, and operations research techniques. Finally, it covers ethics and security considerations for handling information technology including protecting individual privacy and ensuring data accuracy.

1. Chapter – 12 Notes Research Methods (KJAN) Summer Quarter 2014
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Quantitative Data Analysis: Hypothesis Testing: Based on Data
All analytical tests will be performed in the class when students will bring the data for their projects.
1. Measures of Central Location
 Mean, Median, Mode
2. Measures of Variability
 Range, Standard Deviation, Variance, Coefficient of Variation
3. Measures of Relative Standing
 Percentiles, Quartiles
4. Measures of Linear Relationship
 Covariance, Correlation, Least Squares Line
Notation
When referring to the number of observations in a population, we use uppercase letter N When
referring to the number of observations in a sample, we use lower case letter n The arithmetic mean for
a population is denoted with Greek letter “mu”: The arithmetic mean for a sample is denoted with an
“x-bar”:
Information Needs of Business: To run a business, useful, timely, accurate, reliable, and valid
data are needed. When data in their raw from are evaluated, analyzed, and synthesized, useful
information becomes available to managers that helps them make good business decisions.
Information gathering, communicating, and decision making go hand in hand.
The methods used to gather, analyze, and synthesize information from the external and internal
environments are becoming more and more sophisticated owing to the immense scope of technology,
which makes possible timely and efficient research vital to the survival of companies.
Data Warehousing, Data Mining and Operations Research:
Data Warehousing: A data warehouse that serves as the central repository of all data collected
from different sources including those pertaining to the company’s finance, manufacturing, sales, and
the like. The data warehouse is usually built from data collected through the different departments of
the enterprise and can be accessed through various on-line analytical processing (OLAP) tools to
support decision making. Data warehousing can be described as the process of extracting, transferring,
and integrating data spread across multiple external databases and even operating systems.
Data Mining: Data mining is a strategic tool for reaching new levels of business intelligence. Using
algorithms to analyze data in a meaningful way, data mining more effectively leverages the data
warehouse by identifying hidden relations and patterns in the data stored in it. Such “mined” data
pertaining to the vital areas of the organization can be easily accessed and used for different purposes.

2. Chapter – 12 Notes Research Methods (KJAN) Summer Quarter 2014
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Operations Research: Operation research (OR) or management sciences (MS) is another
sophisticated tool used to simplify and thus clarify certain types of complex problems that lend
themselves to quantification. OR uses higher mathematics and statistics to identify, analyze, and
ultimately solve intricate problems of great complexity faced by the manager. Areas of problem
solving that easily lend to OR include those relating to inventory, queuing, sequencing, routing, and
search and replacement.
Management Information Systems (MIS), Decision Support System, the Executive Information
System, and the Expert System, are good decision making aids. A good information system collects,
mines, and provides a wide range of pertinent information relating to aspects of both the external and
internal environments of the organization.
International Dimensions of Cyberspace: Cyberspace is not free of geographical boundaries
or cultural issues. Foreign governments can use the firewall and filtering technology to deter computer
hackers. Unregulated cyberspace is a mythical notion. Local laws do indeed govern what can and
cannot appear in cyberspace. Copyright laws can also be deemed to be broken.
Data Storage and Surveillance:
Storage of Databases: Data is the lifeblood of companies and should be mirrored live in at least
two other locations, or at least backed up on tape and stored in other remote locations.
Data Security: Increasingly, organizations and their information systems are faced with security
threats that include computer hacking, Internet fraud, and sabotage, from a wide range of sources.
Computer viruses, and computer hacking are the incessant threats and ever-present danger. To protect
information from a variety of threats, digital IDs and firewalls are a few of the security measures used
to prevent fraud and unauthorized use. Authentication, authorization, and encryption are some basic
security methodologies employed to prevent unauthorized people from having access.
Managerial Advantage of Technological Advancements: Information technology and the
development of software to gather, store, and analyze information—are registering advances at an
exponential rate. It is important for managers to take full advantage of information technology and
keep current on the latest innovations. Software technology can be put to effective use in the research
process for problem identification, theory building, and collecting data from respondents, analyzing it,
and presenting the results. Technology is not, however, without its drawbacks.

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Ethics in Handling Information Technology: Although technology offers unbounded
opportunities for organizations and facilitates decision making at various levels, it also imposes certain
obligations on the part of its users.
1. It is important that the privacy of all individuals is protected. Businesses have to
balance their information needs against the individual rights.
2. Companies also need to ensure that confidential information relating to individuals is
protected.
3. Care should be taken to ensure that incorrect information is not distributed across the
many different files of the company.
4. Those that collect data for the company should be honest, trustworthy, and careful in
obtaining and recording the data in a timely fashion.