Applying Advanced Analytics

Econometrics is used to analyze quantitative and qualitative economic relations by means of mathematical and statistical methods and models. Econometrics is used to forecast economic processes.

Econometrics methods can be applied to workbook data using the Foresight Analytics Platform tool that is Modeling and Forecasting.

To apply econometrics methods:

1. Select the data range on the workbook sheet.

2. Open the Advanced Analytics ribbon tab.

3. Click the Modeling and Forecasting button in the Econometrics group.

A modeling problem opens, which calculates the chain of models based on the selected data.

Perform econometric analysis of data.

Validation is used to check time series data for correspondence with the set conditions and constraints.

To validate data:

1. Create a validation rule or make sure that the required rule already exists in the time series database, which is used as a data source located on the workbook sheet.

2. Select the data range on the workbook sheet.

3. Open the Advanced Analytics ribbon tab.

4. Click the Validation button in the Data Validation group.

5. The list opens, in which select the required validation rule.

As a result, validation is executed for the selected data range and detected exceptions are displayed.

The following operations are available when working with exceptions:

• Navigate by exceptions.

• Explain exceptions.

• Hide explained exceptions.

• Show or hide validation legend.

• Clear validation results.

For detailed description of working with data validation, see the Working with Validation Results section.

Data mining is used to reveal hidden facts and relations in large data arrays. Obtained data may be used to make decisions in various life spheres.

To perform data mining:

1. Select the data range on the workbook sheet.

2. Open the Advanced Analytics ribbon tab.

3. Click the button corresponding to the data mining method in the Data Mining group:

• Clustering. Divides data into the set number of groups by means of the selected method.

• Exception Search. Determines the degree of probability to be excluded for each criterion of each object by judging the general collection of data. The obtained characteristics can be used to rank objects by the degree of their probability to be excluded.

• Pattern Substitution. Uses the current classification to fill in missing values of the explained attribute depending on the values of explanatory attributes.

• Key Factors. Estimates the degree of influencing of each factor on the dependent variable and reveals most relevant factors.

• Association Analysis. Determines most frequent joint sets of elements by means of the analysis of the set of repeated transactions.

The data mining wizard opens to perform the analysis.