Category:Displayr - Anything Menu
List of scripts that appear in the Anything menu in Displayr.
Pages in category ‘Displayr - Anything Menu’
The following 200 pages are in this category, out of 364 total.
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C
- Calculation - Any of - Any of
- Calculation - Any of - Any of Each Column
- Calculation - Any of - Any of Each Row
- Calculation - Average - Average
- Calculation - Average - Average Each Column
- Calculation - Average - Average Each Row
- Calculation - Count - Count
- Calculation - Count - Count Each Column
- Calculation - Count - Count Each Row
- Calculation - Divide
- Calculation - First
- Calculation - Last
- Calculation - Maximum - Maximum
- Calculation - Maximum - Maximum Each Column
- Calculation - Maximum - Maximum Each Row
- Calculation - Minimum - Minimum
- Calculation - Minimum - Minimum Each Column
- Calculation - Minimum - Minimum Each Row
- Calculation - Multiply
- Calculation - None of - None of
- Calculation - None of - None of Each Column
- Calculation - None of - None of Each Row
- Calculation - Standard Deviation - Standard Deviation
- Calculation - Standard Deviation - Standard Deviation Each Column
- Calculation - Standard Deviation - Standard Deviation Each Row
- Calculation - Subtract
- Calculation - Sum - Sum
- Calculation - Sum - Sum Each Column
- Calculation - Sum - Sum Each Row
- Calculation - Variance - Variance
- Calculation - Variance - Variance Each Column
- Calculation - Variance - Variance Each Row
- Choice Modeling - Compare Models
- Choice Modeling - Convert Alchemer (Survey Gizmo) Conjoint Data for Analysis
- Choice Modeling - Diagnostic - Class Parameters Table
- Choice Modeling - Diagnostic - Experimental Design - Balances and Overlaps of Design
- Choice Modeling - Diagnostic - Experimental Design - Numeric Design
- Choice Modeling - Diagnostic - Experimental Design - Parameter Standard Errors of Design
- Choice Modeling - Diagnostic - Parameter Statistics Table
- Choice Modeling - Diagnostic - Posterior Intervals Plot
- Choice Modeling - Diagnostic - Trace Plots
- Choice Modeling - Ensemble of Models
- Choice Modeling - Experimental Design
- Choice Modeling - Export Design To Qualtrics
- Choice Modeling - Hierarchical Bayes
- Choice Modeling - Latent Class Analysis
- Choice Modeling - Multinomial Logit
- Choice Modeling - Optimizer
- Choice Modeling - Preview Choice Questionnaire
- Choice Modeling - Save Variable(s) - Class Membership
- Choice Modeling - Save Variable(s) - Class Membership Probabilities
- Choice Modeling - Save Variable(s) - Individual-Level Coefficients
- Choice Modeling - Save Variable(s) - Proportion of Correct Predictions
- Choice Modeling - Save Variable(s) - RLH (Root Likelihood)
- Choice Modeling - Save Variable(s) - Utilities (Mean 0)
- Choice Modeling - Save Variable(s) - Utilities (Mean 0, Max Range 100)
- Choice Modeling - Save Variable(s) - Utilities (Mean 0, Mean Range 100)
- Choice Modeling - Save Variable(s) - Utilities (Min 0)
- Choice Modeling - Save Variable(s) - Utilities (Min 0, Max Range 100)
- Choice Modeling - Save Variable(s) - Utilities (Min 0, Mean Range 100)
- Choice Modeling - Simulator
- Choice Modeling - Utilities Plot
- Combo Box (Drop-Down) Filters on an Output
- Correlation - Correlation Matrix
- Correlation - Distance Matrix
- Correlation - Scatterplot Matrix
- Create New Variables - Binary Variable(s)
- Create New Variables - Bottom 2 Category Variable(s) (Bottom 2 Boxes)
- Create New Variables - Bottom 3 Category Variable(s) (Bottom 3 Boxes)
- Create New Variables - Bottom K Category Variable(s) (Bottom K Boxes)
- Create New Variables - Case-Level Shares
- Create New Variables - Combine Questions as a Grid
- Create New Variables - Flatten Question(s)
- Create New Variables - Log Transform Variable(s)
- Create New Variables - Numeric Variable(s) from Code/Category Midpoints
- Create New Variables - Rebase Multiple Response Data in Variable(s) to NET
- Create New Variables - Recode Net Promoter Score (NPS) Variable(s)
- Create New Variables - Scale Variable(s) - Center Within Case
- Create New Variables - Scale Variable(s) - Center Within Variable
- Create New Variables - Scale Variable(s) - Ranks Within Case
- Create New Variables - Scale Variable(s) - Ranks Within Variable
- Create New Variables - Scale Variable(s) - Standardize Within Case
- Create New Variables - Scale Variable(s) - Standardize Within Variable
- Create New Variables - Scale Variable(s) - Unit Interval Within Case
- Create New Variables - Scale Variable(s) - Unit Interval Within Variable
- Create New Variables - Square-Root Variable(s)
- Create New Variables - Top 2 Category Variable(s) (Top 2 Boxes)
- Create New Variables - Top 3 Category Variable(s) (Top 3 Boxes)
- Create New Variables - Top K Category Variable(s) (Top K Boxes)
- Create New Variables - Translate Text
- Create New Variables - Variable(s) with Outliers Removed
D
- Data - Countries from IP Address(es) (Geocoding)
- Data - Data Set - Combine - By Case
- Data - Data Set - Combine - By Variable
- Data - Data Set - Stack
- Data - Dynamic Text Box
- Data - Google Trends
- Data - Sample Size Description
- Data - Stock Prices
- Delete Tables and Plots - Delete If Broken
- Delete Tables and Plots - Delete If Not Significant at Specified Level
- Delete Tables and Plots - Delete If Not Significant at the 0.001 Level (99.9%)
- Delete Tables and Plots - Delete If Not Significant at the 0.01 Level (99%)
- Delete Tables and Plots - Delete If Not Significant at the 0.05 Level (95%)
- Delete Tables and Plots - Delete If Sample Size Lower Than Specified Value
- Dimension Reduction - Correspondence Analysis of a Square Table
- Dimension Reduction - Correspondence Analysis of a Table
- Dimension Reduction - Diagnostic - Component Plot
- Dimension Reduction - Diagnostic - Goodness of Fit Plot
- Dimension Reduction - Diagnostic - Moonplot
- Dimension Reduction - Diagnostic - Quality Table
- Dimension Reduction - Diagnostic - Scree Plot
- Dimension Reduction - Dimension Reduction Scatterplot
- Dimension Reduction - Multidimensional Scaling (MDS)
- Dimension Reduction - Multiple Correspondence Analysis
- Dimension Reduction - Principal Components Analysis
- Dimension Reduction - Principal Components Analysis Biplot
- Dimension Reduction - Save Variable(s) - Components/Dimensions
- Dimension Reduction - t-SNE
F
M
- Machine Learning - Classification And Regression Trees (CART)
- Machine Learning - Compare Models
- Machine Learning - Deep Learning
- Machine Learning - Diagnostic - Analysis Report
- Machine Learning - Diagnostic - Model Simulator
- Machine Learning - Diagnostic - Prediction-Accuracy Table
- Machine Learning - Diagnostic - Table of Discriminant Function Coefficients
- Machine Learning - Ensemble of Models
- Machine Learning - Gradient Boosting
- Machine Learning - Linear Discriminant Analysis
- Machine Learning - Random Forest
- Machine Learning - Save Variable(s) - Discriminant Variables
- Machine Learning - Save Variable(s) - Predicted Values
- Machine Learning - Save Variable(s) - Probabilities of Each Response
- Machine Learning - Support Vector Machine
- Marketing - Brand Health Table
- Marketing - MaxDiff - Compare Models
- Marketing - MaxDiff - Convert Alchemer (Survey Gizmo) MaxDiff Data for Analysis
- Marketing - MaxDiff - Diagnostic - Class Parameters Table
- Marketing - MaxDiff - Diagnostic - Class Preference Shares Table
- Marketing - MaxDiff - Diagnostic - Parameter Statistics Table
- Marketing - MaxDiff - Diagnostic - Posterior Intervals Plot
- Marketing - MaxDiff - Diagnostic - Trace Plots
- Marketing - MaxDiff - Ensemble of Models
- Marketing - MaxDiff - Experimental Design
- Marketing - MaxDiff - Hierarchical Bayes
- Marketing - MaxDiff - Latent Class Analysis
- Marketing - MaxDiff - Multinomial Logit
- Marketing - MaxDiff - Save Variable(s) - Class Membership
- Marketing - MaxDiff - Save Variable(s) - Class Membership Probabilities
- Marketing - MaxDiff - Save Variable(s) - Individual-Level Coefficients
- Marketing - MaxDiff - Save Variable(s) - Preference Shares
- Marketing - MaxDiff - Save Variable(s) - Proportion of Correct Predictions
- Marketing - MaxDiff - Save Variable(s) - RLH (Root Likelihood)
- Marketing - MaxDiff - Save Variable(s) - Sawtooth-Style Preference Shares (K Alternatives)
- Marketing - MaxDiff - Save Variable(s) - Zero-Centered Utilities
- Marketing - MaxDiff - Varying Coefficients
- Marketing - Price Sensitivity Meter
- Missing Data - Little's MCAR Test
- Missing Data - Plot by Case
- Missing Data - Plot of Patterns
- Missing Data - Save Variable(s) - Filter for Complete Cases
- Modify Data - Add Bottom K Category NETs (Bottom K Boxes)
- Modify Data - Add Top K Category NETs (Top K Boxes)
- Modify Data - Merge Categories of Size 0.5% or Less
- Modify Data - Merge Categories of Size 1% or Less
- Modify Data - Merge Categories of Size 2% or Less
- Modify Data - Merge Categories of Size 3% or Less
- Modify Data - Merge Categories of Size 4% or Less
- Modify Data - Merge Categories of Size 5% or Less
- Modify Data - Remove Don't Know Categories
- Modify Labels - Modify Text in Selected Items
- Modify Labels - Relabel Other/Specify Categories as Other
- Move Data - Move All Filters to the Top
- Move Data - Move All Hidden Questions to the Bottom
- Move Data - Move All Weights to the Top
- Move Data - Move Variable Set(s) Down One Row
- Move Data - Move Variable Set(s) to Bottom
- Move Data - Move Variable Set(s) to Top
- Move Data - Move Variable Set(s) Up One Row
P
- Preliminary Project Setup - Check for Errors in Data File Construction
- Preliminary Project Setup - Hide Uninteresting Data
- Preliminary Project Setup - Identify Questions with Straight-Lining/Flat-Lining
- Preliminary Project Setup - Remove Truncated Text from Variable Labels
- Preliminary Project Setup - Reverse Scales in Question(s)
- Preliminary Project Setup - Suggest Better Question Names from Source Labels
- Preliminary Project Setup - Summary Plots
- Preliminary Project Setup - Summary Tables
- Preliminary Project Setup - Tables for Data Checking
