Data Mining and Data Analysis Quiz

Study Notes

Data Types

Respondents: samples who are actual participants in the research
Data: facts or set of information gathered or under studies
Nominal data: labels or classes with an implied ordering in these labels
Ratio data: has all the properties of the interval scale and can be multiplied and divided, has a true zero point, and is the highest level of measurement
Geometric shapes belong to the nominal level of measurement

Statistics

Descriptive statistics: summarizes data from the entire population or a sample with numerical descriptors such as Mean, Standard Deviation for Continuous Data, Frequency, Percentage for Categorical Data
Inferential statistics: uses patterns in the sample data to draw inferences about the represented population or accounting for randomness
Predictive analytics: uses statistical models to analyze current and historical data for forecasting (predictions)
Text analytics: process of deriving high-quality information from text

Data Classification

Numerical information: Age, Height, Grade
Non-numerical information: Level Of awareness, Emotions, Grade in letter

Data Sources

Primary data: information collected from sources such as personal interviews, questionnaires or survey with a specific intention on a specific subject
Secondary data: information that already available somewhere, like journals, the internet, a company’s records or, on a larger scale, in corporate or governmental archives

Data Analysis

Qualitative data: attributes which cannot be subjected to meaningful arithmetic, involves or may be influenced by subjectivity (bias), examples: attitudes, feelings, willingness, likeliness
Data mining: analysis of large quantities of data to extract previously unknown, interesting patterns of data, unusual data and the dependencies
Data analysis: process of inspecting, cleaning, transforming and modeling data with the goal of discovering useful information, suggesting conclusions and supporting decision-making
Business intelligence: acquisition and transformation of large amounts of unstructured business data to help identify, develop and create new strategic business opportunities

Statistics Terms

Conclusion: an opinion based on the findings, a generalization on population based on the result of the investigation on samples
Population: a group or aggregates of people, animals, objects, materials, happenings or things of any form
Sample: a portion of a population to represent their characteristics or property whereby the members of the group or set vary or differ from one another
Statistics: science which deals with methods in the collection, gathering, presentation, analysis and interpretation of data

Description

Test your knowledge on data mining, data analysis, and business intelligence. Learn about extracting patterns from large quantities of data, cleaning and modeling data, and transforming unstructured business data for strategic opportunities.