Introduction to Statistical Software - Flashcards

60 practice flashcards in the QUESTION_AND_ANSWER format based on lecture notes on statistical software, PBSE, data visualization, BI, SNCES, specialized software, and freeware.

What is statistical software?

Specialized computer programs and environments designed for statistical analysis, data management, and data visualization.

What does PBSE stand for?

Programming-Based Statistical Environments.

What is the core purpose of statistical software?

To transform raw data into meaningful insights for informed decision-making.

What is the core philosophy of Programming-Based Statistical Environments (PBSEs)?

Analysis is performed through a programming language; scripts enable flexible, reproducible data analysis.

Name two key features of PBSEs.

Integrated suite of tools; reproducibility and automation via scripts.

What does 'reproducibility' mean in PBSEs?

The ability to reproduce results by re-running the same code.

What is data management in statistical software?

Features for cleaning, transformation, and manipulation of data to prepare for analysis.

Name two advantages of using statistical software.

Increased accuracy and efficiency.

Name two disadvantages of using statistical software.

Steep learning curve and cost.

Name three commercial statistical software packages.

IBM SPSS Statistics, SAS, Stata.

What is IBM SPSS Statistics known for?

An intuitive GUI with modules and a syntax language for reproducible analysis.

What does SPSS offer besides the GUI?

A command syntax language for reproducible analysis and automation.

What is SAS known for?

A powerful programming language, scalability, and validated procedures for enterprise analytics.

What is Stata known for?

Fast, accurate, comprehensive statistics with a broad set of commands and reproducibility.

What is a major reason researchers use statistical software?

To automate complex calculations and analyze large datasets efficiently.

What is data visualization?

Graphical representation of information using charts, graphs, and maps.

Why are data visualizations important in data analysis?

They help with quick information processing, identify trends, and communicate findings to a broad audience.

Name three common types of data visualizations.

Bar charts, line charts, pie charts.

What is a Bar Chart used for?

Comparing quantities across different categories.

What is a Line Chart used for?

Showing trends over time.

What is a Pie Chart used for?

Showing proportions of a whole.

What is a Scatter Plot used for?

Display the relationship between two numerical variables.

What is a Heat Map used for?

Represent data values with color in a matrix, often geographic data or correlations.

What is a Histogram used for?

Showing the distribution of a single numerical variable.

What is a Treemap used for?

Display hierarchical data as nested rectangles.

What does BI stand for?

Business Intelligence.

What are the core components of a BI environment?

Data preparation, data warehousing, reporting, dashboards, ad-hoc analysis.

Name three leading BI tools.

Microsoft Power BI, Tableau, Qlik Sense.

Name a key feature of Microsoft Power BI.

Power Query and DAX (data modeling/ calculations) and integration with Excel.

What is Tableau known for?

Exceptional visuals, interactive dashboards, and data storytelling.

What is Qlik Sense known for?

Associative engine, self-service analytics, and scalability.

Name two advantages of data visualization and BI tools.

Enhanced data comprehension and faster, data-driven decision-making.

Name two disadvantages of data visualization and BI tools.

Potential for misinterpretation and data quality dependence.

What does ETL stand for?

Extract, Transform, Load.

What is Data Warehousing?

A centralized repository for storing large volumes of historical and operational data, optimized for reporting and analysis.

What is a Dashboard in BI?

A single-screen visual display of the most important metrics and KPIs.

What is Ad-Hoc Analysis?

The ability for users to ask questions and explore data on the fly without needing IT.

What does SNCES stand for?

Scientific and Numerical Computing Environments.

What are the key characteristics of SNCES?

Optimized for numerical operations; rich mathematical libraries; high-level programming; IDE; powerful visualization; extensibility; interoperability.

Name two examples of SNCES.

MATLAB and Julia.

What are specialized statistical software?

Software designed for a very specific type of analysis or domain with optimized algorithms and domain-specific interfaces.

Name SEM-related software.

LISREL, AMOS, Mplus, WarpPLS, SmartPLS.

What is WarpPLS?

SEM software using PLS that can model non-linear relationships (e.g., U-curve, S-curve).

What is SmartPLS?

A tool for variance-based SEM using PLS path modeling.

What is Winsteps?

Software for Rasch measurement and IRT analysis.

What is IRTPRO?

Software for IRT model calibration, scaling, and scoring.

What is G*Power?

Free software for calculating statistical power.

What are the advantages of specialized statistical software?

Methodological precision; efficiency for niche tasks; tailored outputs; handles complexities; adheres to standards.

What are the disadvantages of specialized statistical software?

High cost; steep learning curve; limited versatility; smaller expert community; interoperability challenges.

What is freeware statistical software?

Open-source software with no licensing cost, community-driven, often programming-based, extensible, cross-platform.

Name examples of leading freeware software.

JASP, Jamovi, GNU PSPP, KNIME, Orange Data Mining, Gretl, SOFA Statistics.

What is KNIME Analytics Platform?

Free and open-source software for data science with a low-code/no-code workflow interface.

What is Orange Data Mining?

Open-source data visualization and analysis tool with a drag-and-drop interface.

What is Gretl?

Gnu Regression, Econometrics and Time-series Library; cross-platform free/open-source econometric analysis.

What is SOFA Statistics?

Open-source statistics package focused on basic tests and attractive outputs.

What are the advantages of freeware (open-source) software?

Zero licensing costs; transparency; community-supported; rapid innovation; cross-platform; reproducibility.

What are the disadvantages of freeware (open-source) software?

Steep learning curve; less intuitive GUIs; lack of dedicated support; varying package quality.

What is vendor lock-in in software?

Dependency on a vendor's format/platform, making migration difficult.

What is data storytelling in BI?

Creating engaging presentations that communicate insights to non-technical stakeholders.

What is Minitab used for?

Quality improvement and Six Sigma, with DOE, SPC charts, and reliability analysis.

What is statistical software?

Specialized computer programs and environments designed for statistical analysis, data management, and data visualization.

What does PBSE stand for?

Programming-Based Statistical Environments.

What is the core purpose of statistical software?

To transform raw data into meaningful insights for informed decision-making.

What is the core philosophy of Programming-Based Statistical Environments (PBSEs)?

Analysis is performed through a programming language; scripts enable flexible, reproducible data analysis.

Name two key features of PBSEs.

Integrated suite of tools; reproducibility and automation via scripts.

What does 'reproducibility' mean in PBSEs?

The ability to reproduce results by re-running the same code.

What is data management in statistical software?

Features for cleaning, transformation, and manipulation of data to prepare for analysis.

Name two advantages of using statistical software.

Increased accuracy and efficiency.

Name two disadvantages of using statistical software.

Steep learning curve and cost.

Name three commercial statistical software packages.

IBM SPSS Statistics, SAS, Stata.

What is IBM SPSS Statistics known for?

An intuitive GUI with modules and a syntax language for reproducible analysis.

What does SPSS offer besides the GUI?

A command syntax language for reproducible analysis and automation.

What is SAS known for?

A powerful programming language, scalability, and validated procedures for enterprise analytics.

What is Stata known for?

Fast, accurate, comprehensive statistics with a broad set of commands and reproducibility.

A major reason researchers use statistical software?

To automate complex calculations and analyze large datasets efficiently.

What is data visualization?

Graphical representation of information using charts, graphs, and maps.

Why are data visualizations important in data analysis?

They help with quick information processing, identify trends, and communicate findings to a broad audience.

Name three common types of data visualizations.

Bar charts, line charts, pie charts.

What is a Bar Chart used for?

Comparing quantities across different categories.

What is a Line Chart used for?

Showing trends over time.

What is a Pie Chart used for?

Showing proportions of a whole.

What is a Scatter Plot used for?

Display the relationship between two numerical variables.

What is a Heat Map used for?

Represent data values with color in a matrix, often geographic data or correlations.

What is a Histogram used for?

Showing the distribution of a single numerical variable.

What is a Treemap used for?

Display hierarchical data as nested rectangles.

What does BI stand for?

Business Intelligence.

What are the core components of a BI environment?

Data preparation, data warehousing, reporting, dashboards, ad-hoc analysis.

Name three leading BI tools.

Microsoft Power BI, Tableau, Qlik Sense.

Name a key feature of Microsoft Power BI.

Power Query and DAX (data modeling/ calculations) and integration with Excel.

What is Tableau known for?

Exceptional visuals, interactive dashboards, and data storytelling.

What is Qlik Sense known for?

Associative engine, self-service analytics, and scalability.

Name two advantages of data visualization and BI tools.

Enhanced data comprehension and faster, data-driven decision-making.

Name two disadvantages of data visualization and BI tools.

Potential for misinterpretation and data quality dependence.

What does ETL stand for?

Extract, Transform, Load.

What is Data Warehousing?

A centralized repository for storing large volumes of historical and operational data, optimized for reporting and analysis.

What is a Dashboard in BI?

A single-screen visual display of the most important metrics and KPIs.

What is Ad-Hoc Analysis?

The ability for users to ask questions and explore data on the fly without needing IT.

What does SNCES stand for?

Scientific and Numerical Computing Environments.