Statistics: Descriptive and Inferential Analysis
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Questions and Answers

What is the primary goal of Inferential Statistical Analysis?

  • To provide a summary of what the data represents
  • To make inferences, or generalizations, about data (correct)
  • To extract knowledge from data using pattern recognition technologies
  • To develop an understanding of Central Tendency and Dispersion

Which of the following is NOT a type of Statistical Analysis?

  • Inferential
  • Data Mining
  • Descriptive
  • Predictive (correct)

What is the purpose of Data Mining?

  • To summarize data using Central Tendency and Dispersion
  • To develop an understanding of what the data represents
  • To make inferences, or generalizations, about data
  • To extract knowledge from data (correct)

Which of the following software is NOT commonly used for analyzing and mining data?

<p>Java (B)</p> Signup and view all the answers

What is the term for the amount of variation in a dataset?

<p>Dispersion (D)</p> Signup and view all the answers

Study Notes

Statistics and Statistical Analysis

  • Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of numerical or quantitative data.
  • Statistical Analysis is the process of developing an understanding of what the data represents through the use of statistical methods.

Types of Statistical Analysis

  • Descriptive Analysis: provides a summary of what the data represents, involving measures such as:
    • Central Tendency
    • Dispersion
    • Skewness
  • Inferential Analysis: involves making inferences, or generalizations, about data, involving measures such as:
    • Hypothesis Testing
    • Confidence Intervals
    • Regression Analysis

Data Mining

  • Data Mining is the process of extracting knowledge from data, involving:
    • Pattern recognition technologies
    • Statistical analysis
    • Mathematical techniques
  • Goals of Data Mining include:
    • Identifying correlations
    • Identifying patterns
    • Identifying variations
    • Identifying trends

Data Mining Techniques

  • Classifying attributes of data
  • Clustering data into groups
  • Establishing relationships between:
    • Events
    • Variables
    • Input and output

Data Analysis Tools and Software

  • Spreadsheets
  • R-Language
  • Python
  • IBM SPSS Statistics
  • IBM Watson Studio
  • SAS
  • Each tool has its own:
    • Characteristics
    • Strengths
    • Limitations
    • Applications

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Description

This quiz covers the basics of statistical analysis, including descriptive and inferential statistics, and their applications in data analysis.

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