--- title: AddMaple Glossary category: FAQs and Trust slug: glossary blurb: Comprehensive glossary of key terms and concepts used throughout the AddMaple platform and documentation. order: 2 --- # AddMaple Glossary This glossary defines key terms and concepts used throughout the AddMaple platform and documentation. --- ## Core Platform Terms ### **AddMaple** A browser-based data analysis platform that processes data locally without uploading to the cloud. Uses modern web APIs (File API, Worker API) to read and analyze files directly in your browser. ### **Project** A workspace containing your dataset and all associated analyses, charts, dashboards, and reports. ### **Dataset** The raw data file you upload and analyze within AddMaple. Can be CSV, XLSX, SAV, JSON, Parquet, or AddMaple file formats. ### **Column Store** AddMaple's proprietary data structure designed for fast pivoting, binning, and filtering of data within the browser. --- ## Data Types & Detection ### **Multiple Choice (MC)** Categorical columns with a limited set of text results. Appears with turquoise bars on the chart dashboard. Used for single-answer survey questions or categorical data. ### **Multiple Choice Plus (MC+)** Columns where there are multiple results per row. Appears with blue bars. Used for multi-select survey questions, tags, or any data where multiple values can be assigned to one record. ### **Numeric** Automatically detected numeric data (numbers, currency, percentages). Appears with green bars. AddMaple automatically creates bins/buckets for visualization in histograms. ### **Opinion Scale** Special detection for opinion scales including both numeric scales (1-10) and text-based answers (Very Important, Somewhat Important, etc.). Allows display of Likert charts. ### **Date/Datetime** Automatically detected date and time columns. Enables time-based analysis and special date binning features. ### **Text** Free text answers or responses. Future improvements will include full text search and automated tagging. ### **Unique** Columns with different values for each row, typically identifiers. Cannot be filtered or pivoted but can be viewed in table or raw data view. ### **Currency** Automatically detected currency columns with currency symbols. Can be filtered and viewed like numeric columns. ### **Percent** Automatically detected percentage columns containing numbers followed by "%" signs. --- ## Data Processing & Preparation ### **Binning** The process of grouping numeric or date values into ranges for easier analysis and visualization. #### **Number Binning** - **Auto (Freedman-Diaconis rule)**: Statistically optimal bin width - **Equal Frequency**: Bins with similar counts - **Fixed Width**: Consistent interval bins - **Custom**: Manually defined ranges and labels #### **Date Binning** - **Auto**: Optimal time-based bins - **Calendar Periods**: Year, Quarter, Month, Week, Day, Hour - **Fixed Intervals**: Every X minutes/hours/days/weeks - **Custom Breakpoints**: User-defined date boundaries ### **Weighting** Applying respondent weights to survey data for more accurate analysis. Adjusts results to better represent target populations when certain groups are over- or under-represented. ### **Column Grouping** Combining similar columns with overlapping categories to analyze their totals together. Useful for aligning data across similar questions. ### **Data Cleaning** Process of preparing data for analysis, including merging categories, renaming columns, and handling missing values. --- ## Analysis & Visualization ### **Pivot/Pivoting** The process of cross-tabulating data by selecting two columns to analyze their relationship. Creates pivot charts and tables showing how one variable relates to another. ### **Filter/Filtering** Narrowing down your dataset to focus on specific segments or values. Can be applied by clicking bars in charts, using the sentence builder, or from table views. ### **Aggregation** Summarizing data using statistical measures: - **Total/Sum**: Adding up values - **Average/Mean**: Calculating the mean - **Median**: Finding the middle value - **Count Unique**: Counting distinct values ### **Chart Dashboard** The main interface showing all your data as interactive charts. Each column type appears with color-coded tiles (turquoise for MC, blue for MC+, green for numeric, etc.). ### **Pivot Chart** Interactive charts created when you pivot two columns together. Show relationships between variables with statistical summaries. ### **Likert Chart** Special chart type for opinion scale data, showing responses in a scale format. Created by pivoting opinion scale columns or grouping similar columns. ### **Histogram** Chart type for numeric data showing the distribution of values across bins or ranges. ### **Horizontal Bar Chart** Default chart type for categorical data, showing categories as horizontal bars with values. ### **Box Plot** Statistical visualization showing quartiles, median, and outliers for numeric data. ### **Scatter Plot** Chart showing relationship between two numeric variables, often with regression lines. --- ## Statistical Analysis ### **Chi-Square Test** Statistical test determining significant relationships between two categorical columns. Provides p-value, Cramér's V (relationship strength), and chi-square statistic. ### **T-Test** Statistical test comparing means between two groups. Automatically performed when pivoting a numeric column with a categorical column having exactly 2 categories. ### **Correlation** Measures relationship strength between two numeric variables: - **Pearson Correlation**: For normally distributed data - **Spearman Correlation**: For non-normally distributed data ### **Regression Analysis** - **Linear Regression**: Relationship between numeric variables - **Logistic Regression**: Relationship between numeric and binary variables - **Multivariate Regression**: Planned future feature ### **ANOVA (Analysis of Variance)** Statistical test comparing means across multiple groups. ### **Kruskal-Wallis Test** Non-parametric alternative to ANOVA for non-normally distributed data. ### **P-Value** Statistical measure indicating the probability that observed relationships are due to chance. Lower values indicate stronger evidence of real relationships. ### **Effect Size** Measures the practical significance of statistical relationships: - **Cramér's V**: For categorical relationships (0-1 scale) - **Cohen's d**: For mean differences --- ## Dashboard & Reporting ### **Dashboard** A collection of pages containing charts, text, images, and KPIs arranged for storytelling and sharing findings. ### **Page** Individual canvas within a dashboard containing various items. Tabs can be reordered by dragging. ### **Item Types** Components that can be added to dashboard pages: - **Text**: Written content - **Section**: Content dividers - **Call Out**: Highlighted information - **Image**: Visual content - **Video**: Video content - **Charts**: Saved analyses from My Collection ### **My Collection/Insights** Storage area for saved charts and notes. Items can be organized into Collections and added to dashboards. ### **Collections** Folders for organizing Insights by theme (e.g., "Q3 Feedback", "Launch Readout"). ### **Report** Document containing selected charts and analyses for presentation or sharing. ### **Publishing** Making dashboards publicly accessible via shareable links. Can include password protection and explorable data options. ### **Explorable Data** Feature allowing dashboard viewers to interact with underlying data by exploring selected columns. ### **Public Link** Shareable URL for published dashboards that can be accessed without AddMaple accounts. --- ## Text Analysis & AI Features ### **AI Summary** Automated analysis of text columns using AI to generate summaries of responses. Processing time varies by dataset size. ### **Thematic Coding** Process of categorizing text responses into themes or codes for analysis. Can be done manually or with AI assistance. ### **AI Chart Explanation** AI-powered summaries explaining what current charts show and their key insights. ### **Clean with AI** Automated feature for cleaning, renaming, ordering, and merging categories in legends. ### **Text Search** Feature for filtering text responses by specific words or phrases. --- ## User Interface Elements ### **Sentence Builder** The top black menu bar that displays applied filters and pivots in plain English. Interactive interface for adding filters, pivots, and aggregations. ### **Legend** Interface for managing how categories appear in charts: - Rename categories - Reorder categories - Merge categories - Assign colors - Hide/show categories - Toggle between Ordered vs Independent categories ### **More Menu** Context menu providing additional options for charts, columns, and analyses. ### **Column Settings** Interface for configuring individual column properties including binning, types, and display options. ### **Manage Columns** Central interface for configuring all columns in a project, including types, binning, and other settings. ### **Project Settings** Configuration area for project-wide settings including color presets, weighting, and data management. --- ## Data Views ### **Graph View** Default view showing all columns as interactive charts on the chart dashboard. ### **Table View** Tabular display of data with options to add/remove columns, sort, filter, and explore individual rows. ### **Row-by-Row View** Individual record view showing complete responses with comparison to overall dataset. Useful for reading free-text responses and understanding context. ### **Raw Data View** Direct display of original data without processing or formatting. --- ## Export & Sharing ### **Export Formats** - **CSV**: Comma-separated values - **XLSX**: Excel format - **JSON**: JavaScript Object Notation - **Parquet**: Columnar storage format - **AddMaple Fast**: Optimized for fast loading - **AddMaple Compressed**: Smallest file size ### **PowerPoint Export** Export charts and analyses to PowerPoint presentations. ### **Excel Crosstabs** Export pivot tables to Excel format with proper formatting. ### **Public Sharing** Sharing dashboards and reports via public links with optional password protection. --- ## Technical Terms ### **Browser-Based Processing** All data analysis happens locally in your browser without uploading to cloud servers. ### **File API** Modern web API allowing browsers to read files directly from your computer. ### **Worker API** Web API enabling background processing for large datasets without blocking the user interface. ### **Columnar Storage** Data storage format optimized for analytical queries and fast aggregation. ### **Effective Sample Size** Adjusted sample size accounting for weighting schemes in statistical calculations. ### **Degrees of Freedom** Number of values free to vary in statistical calculations. ### **Expected Values** Theoretical counts expected if no relationship existed between variables (used in chi-square tests). ### **Outlier Handling** Statistical methods for identifying and managing extreme values that might distort analysis. ### **Welch-Satterthwaite Degrees of Freedom** Method for calculating degrees of freedom in weighted t-tests. ### **Kish Effective Sample Size** Method for adjusting sample size calculations when using survey weights. --- ## Workflow Terms ### **Save/Add to Dashboard** Process of saving charts or analyses to My Collection for later use in dashboards. ### **Swap Columns** Feature allowing you to switch which column is being pivoted vs. which is doing the pivoting. ### **Related Columns** Columns that AddMaple suggests as potentially related based on data patterns. ### **Cross-tabulation** Statistical table showing relationships between two categorical variables. ### **Segmentation** Process of dividing data into meaningful groups for analysis and comparison. ### **Demographic Analysis** Analysis focusing on population characteristics like age, gender, income, education, etc. ### **Response Rate** Percentage of contacted individuals who completed a survey or provided data. ### **Sample Size** Number of observations or responses in your dataset. ### **Confidence Level** Statistical measure of certainty in results (typically 95% or 99%). --- *This glossary covers the main terms and concepts used throughout AddMaple. For detailed explanations and step-by-step instructions, refer to the specific user guide sections.*