Analisi di regressione

Performs linear, logarithmic, or power regression analysis of a data set comprising one dependent variable and multiple independent variables.

For example, a crop yield (dependent variable) may be related to rainfall, temperature conditions, sunshine, humidity, soil quality and more, all of them independent variables.

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Scegliete Dati - Statistiche - Regressione


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Per maggiori informazioni sull'analisi di regressione, consultate l'articolo wikipedia relativo (in inglese).


Dati

Intervallo delle variabili indipendenti (X):

Enter a single range that contains multiple independent variable observations (along columns or rows). All X variable observations need to be entered adjacent to each other in the same table.

Intervallo delle variabili dipendenti (Y):

Enter the range that contains the dependent variable whose regression is to be calculated.

Gli intervalli X e Y hanno entrambi etichette

Check to use the first line (or column) of the data sets as variable names in the output range.

Risultato in:

Il riferimento della cella alla estrema sinistra dell'area in cui i risultati verranno visualizzati.

Raggruppamento per

Selezionate se visualizzare i dati in colonne o righe.

Tipi di output della regressione

Impostate il tipo di regressione. Sono disponibili tre tipi:

Opzioni

Livello di confidenza

A numeric value between 0 and 1 (exclusive), default is 0.95. Calc uses this percentage to compute the corresponding confidence intervals for each of the estimates (namely the slopes and intercept).

Calcola residui

Select whether to opt in or out of computing the residuals, which may be beneficial in cases where you are interested only in the slopes and intercept estimates and their statistics. The residuals give information on how far the actual data points deviate from the predicted data points, based on the regression model.

Forza intercetta come zero

Calculates the regression model using zero as the intercept, thus forcing the model to pass through the origin.