Information Technology

Statistical and Machine-Learning Data Mining

---

The personal computer (PC) has changed everything—for both better and worse—in the world of statistics. The PC can effortlessly produce precise cal- culations and eliminate the computational burden associated with statistics. One need only provide the right questions. With the minimal knowledge required to program (instruct) statistical software, which entails telling it where the input data reside, which statistical procedures and calculations are desired, and where the output should go, tasks such as testing and ana- lyzing, the tabulation of raw data into summary measures, as well as many other statistical criteria are fairly rote. The PC has advanced statistical think- ing in the decision-making process, as evidenced by visual displays, such as bar charts and line graphs, animated three-dimensional rotating plots, and interactive marketing models found in management presentations. The PC also facilitates support documentation, which includes the calculations for measures such as the current mean profit across market segments from a marketing database; statistical output is copied from the statistical software and then pasted into the presentation application. Interpreting the output and drawing conclusions still requires human intervention.
Unfortunately, the confluence of the PC and the world of statistics has turned generalists with minimal statistical backgrounds into quasi statisti- cians and affords them a false sense of confidence because they can now produce statistical output. For instance, calculating the mean profit is stan- dard fare in business. However, the mean provides a “typical value”—only when the distribution of the data is symmetric. In marketing databases, the distribution of profit is commonly right-skewed data.* Thus, the mean profit is not a reliable summary measure.†

---

Availability

No copy data

Detail Information

Series Title

Statistical and Machine-Learning Data Mining

Call Number

-

Publisher

USA : Taylor & Francis Group, LLC., 2011

Collation

1-524

Language

English

ISBN/ISSN

13: 978-1-4398-6092-

Classification

NONE

Content Type

-

Media Type

-

Carrier Type

-

Edition

1st Edtion

Subject(s)

Information Technology

Specific Detail Info

-

Statement of Responsibility

-

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment