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iNZight Documentation

website·Indexed 33 days ago

https://inzight.nz

Documentation for iNZight, a data analysis and visualization tool. Includes guides on data wrangling, model fitting, and graphics, as well as reference materials for iNZight Lite and associated R packages such as iNZightTools 2.0.2, iNZightRegression 1.3.5, iNZightPlots 2.16, iNZightModules 2.6.0, iNZightTS 2.0.3, and iNZightMR 2.3.1.

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What's inside iNZight

  1. Overview of iNZightTS Time Series Analysis Module

    iNZightTS is a time series analysis module. As of version 2.0.0, the package has been rebuilt to incorporate features from the tidyverts ecosystem. It provides tools for time series visualization, including sub-series plots, decomposition plots, and seasonal plots.

  2. Overview of iNZight data analysis capabilities

    iNZight is a data analysis and visualization tool designed for users of all skill levels. It allows users to select variables and automatically determines the appropriate graph, summary, and statistical test. The tool features interactive controls for slicing data and generating publication-ready visualizations without requiring the user to write code.

  3. Overview of iNZight data visualisation tool

    iNZight is a free data visualisation and analysis tool designed for both beginners and experts to generate statistical graphs and summaries without requiring coding or complex specialist software. It is available in two versions: Desktop and Lite.

  4. Overview of the Model Fitting module

    The Model Fitting module provides a graphical interface for fitting and diagnosing regression models. It supports multiple model families, diagnostic plotting with bootstrap overlays, and model comparison. Access the module via Advanced > Model Fitting.

  5. Distinguish between descriptive and analytic survey studies

    Survey research generally falls into two categories with different goals:

    • Descriptive Studies: Focused on "What was it like?" These aim to summarize a real, finite population at a specific time. They produce estimates of population means, totals, counts, proportions, and ratios. Uncertainty in these studies is caused specifically by the randomness of selection from the finite population.
    • Analytic Studies: Focused on "How does it work?", "Why is it like that?", or predicting future outcomes.

  6. Understand Get Summary behavior for survey data

    The behavior of the Get Summary feature in iNZight changes depending on whether a survey design is specified:

    • Without a survey design: Provides summary information about the dataset itself.
    • With a survey design: Provides estimates of population quantities.

    This distinction is critical because raw summaries of survey data are often meaningless due to unequal probabilities of selection.

  8. Access the Design of Experiment module in iNZight Lite

    The Design of Experiment module provides tools for analyzing data from designed experiments, including support for mixed effects models. This module is exclusively available in iNZight Lite and can be accessed via the module dropdown menu.

  9. Access educational statistics resources by Professor Chris Wild

    Several educational resources are available for statistical learning:

    • Wild About Statistics Channel: A collection of educational videos about statistics.
    • StatThink: Resources for teaching statistical thinking.
    • WPRH (Wild's Probability and Random Happenings): Resources for understanding probability concepts.

    Wild About Statistics: https://www.stat.auckland.ac.nz/~wild/wildaboutstatistics/index.html StatThink: https://www.stat.auckland.ac.nz/~wild/StatThink/index.html WPRH: https://www.stat.auckland.ac.nz/~wild/WPRH/index.html

  10. Access multivariate analysis tools in iNZight Lite

    The multivariate analysis module provides tools for Principal Components Analysis (PCA) and various clustering methods. This module is exclusively available in iNZight Lite and can be accessed via the module dropdown menu.

  11. Use the iNZightModules model fitting module

    The model fitting module, rewritten in gWidgets2, allows users to perform the following tasks: specify general linear models, apply survey designs for the analysis of survey data, toggle data types between numeric and categorical, and specify confounding variables separately.

  12. Generate automated 1-variable summaries

    To get a comprehensive numeric overview of the entire dataset, navigate to Advanced > Quick Explore > All 1-Variable Summaries. This produces a single window containing:

    • Numeric variables: Mean, standard deviation, min, quartiles, max, and count of missing values.
    • Categorical variables: A frequency table of levels.