Data
Writing
Marketing
Examples of Data in the following topics:

Data and Information
 Data consists of nothing but facts, which can be manipulated to make it useful; the analytical process turns the data into information.
 Binary files (readable by a computer but not a human) are sometimes called "data" and are distinguishable from humanreadable data, referred to as "text" .
 Once data is in digital format, various procedures can be applied on the data to get useful information.
 Data processing may involve various processes, including:
 Data processing may or may not be distinguishable from data conversion, which involves changing data into another format, and does not involve any data manipulation.

Data Snooping: Testing Hypotheses Once You've Seen the Data
 Testing hypothesis once you've seen the data may result in inaccurate conclusions.
 The error is particularly prevalent in data mining and machine learning.
 Sometimes, people deliberately test hypotheses once they've seen the data.
 Data snooping (also called data fishing or data dredging) is the inappropriate (sometimes deliberately so) use of data mining to uncover misleading relationships in data.
 Although datasnooping bias can occur in any field that uses data mining, it is of particular concern in finance and medical research, which both heavily use data mining.

Analyzing Data
 Data Analysis is an important step in the Marketing Research process where data is organized, reviewed, verified, and interpreted.
 Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes.
 In statistical applications, some people divide data analysis into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA).
 All are varieties of data analysis.
 Summarize the characteristics of data preparation and methodology of data analysis

MLA: Reporting Data

APA: Reporting Data

Chicago/Turabian: Reporting Data

MLA: Reporting Data

Chicago/Turabian: Reporting Data

Observations, variables, and data matrices
 These observations will be referred to as the email50 data set, and they are a random sample from a larger data set that we will see in Section 1.7
 The data in Table 1.3 represent a data matrix, which is a common way to organize data.
 Data matrices are a convenient way to record and store data.
 How might these data be organized in a data matrix?
 These data were collected from the US Census website.

Analyzing Data and Drawing Conclusions
 In statistical applications, some people divide data analysis into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA).
 In an exploratory analysis, no clear hypothesis is stated before analyzing the data, and the data is searched for models that describe the data well.
 Coding is the process of categorizing qualitative data so that the data becomes quantifiable and thus measurable.
 How data is coded depends entirely on what the researcher hopes to discover in the data; the same qualitative data can be coded in many different ways, calling attention to different aspects of the data.
 Coded data is quantifiable.