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Questions and Answers
What is the primary goal of Inferential Statistical Analysis?
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?
Which of the following is NOT a type of Statistical Analysis?
- Inferential
- Data Mining
- Descriptive
- Predictive (correct)
What is the purpose of Data Mining?
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?
Which of the following software is NOT commonly used for analyzing and mining data?
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What is the term for the amount of variation in a dataset?
What is the term for the amount of variation in a dataset?
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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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