TCP-SP Exam Dumps and Practice Questions

TERR functions are a subset of the built-in expression functions in Spotfire that invoke the TERR engine for advanced statistical analysis. You can find them in the Function list of the Custom Expressions or Insert Calculated Column dialog box, under the category Statistical functions. TERR functions have the prefix TERR_ or TERRAggregation_ followed by the Spotfire data type of the output. For example, TERR_Real, TERRAggregation_String, etc. You can also register your own TERR scripts as expression functions and assign them to a custom category.Reference:Built-In TERR Expression Functions in Spotfire,Registering the TERR Script as an Expression Function

Correlation similarity is a distance measure option of the line similarity tool that calculates the similarity value by comparing the shape of a line to the master line selected. Correlation similarity measures how well the values of two lines are linearly related, regardless of their absolute values or offsets. A high correlation similarity means that the lines have similar shapes, while a low correlation similarity means that the lines have different shapes or opposite directions. Correlation similarity is useful when the absolute values or scales of the lines are not important, but the relative trends or patterns are.Reference:Details on Line Similarity,How to Perform a Line Similarity Comparison

The Linear Regression method in Predictive Modelling is used when the response column is numeric and continuous, and the relationship between the response and the predictors is assumed to be linear. The Linear Regression method models the numeric response column as a weighted sum of the predictor columns, plus an intercept term.The weights, or coefficients, are estimated by minimizing the sum of squared errors between the observed and predicted values1.The Linear Regression method can be used to assess the significance and effect of each predictor, as well as to make predictions for new data2.Reference:Building a Regression Model in Spotfire,TIBCO Spotfire - Use Regression Modeling to Predict Numerical Values

Comparison circles are a way to display whether or not the mean values for various categories (boxes in the box plot) are significantly different from each other. The circles are drawn with their centers at the mean value for the box to which they correspond. If the circles for different groups do not overlap, the means of the two groups are generally significantly different. If the circles have a large overlap, the means are not significantly different.Reference:What are Comparison Circles? - TIBCO Software

A data function is a reusable calculation that can be applied to data in a Spotfire analysis. A data function can have input and output parameters that define how the data function interacts with the data and the analysis. The input parameters specify what data or values are required for the data function to run, and the output parameters specify what data or values are returned by the data function.The types of input or output parameters for a data function are1:

Column: A column parameter represents a single column of data from a data table. A column parameter can be used as input to provide a vector of values to the data function, or as output to create a new column in the data table or overwrite an existing column. A column parameter can have a data type such as real, integer, string, or boolean.

Document property: A document property parameter represents a value that is stored in the analysis document and can be used to control various aspects of the analysis, such as filters, markings, colors, etc. A document property parameter can be used as input to provide a scalar value to the data function, or as output to create a new document property or overwrite an existing document property. A document property parameter can have a data type such as real, integer, string, boolean, date, or time.

Value: A value parameter represents a scalar value that is entered by the user or calculated by the data function. A value parameter can be used as input to provide a constant or variable value to the data function, or as output to return a single value from the data function. A value parameter can have a data type such as real, integer, string, boolean, date, or time.

The other options, column property, table, and visualization, are not valid types of input or output parameters for a data function.Reference:

Details on Data Functions -- Parameters

Configuring Data Function Parameters

How to select/deselect inputs/outputs/parameters in Statistica Data Function for Spotfire

How to pass input from Spotfire to Statistica Data Function?