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</p> Signup and view all the answers

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

    <p>Dispersion</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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