Statistical Analysis

Statistical analysis is an integral part of analyzing survey data. Without using true statistical tests to analyze the data, many important findings could remain hidden. Whether you prefer running basic stat tests to help you understand your data, or advanced scripts to dig deeper, MarketSight can cater to your analysis requirements. The platform provides a variety of options to ensure thorough statistical analyses are applied to your data, via automatic stat testing in crosstabs, customizable stat tests, and a native R integration.


Automatic Statistical Significance

When analyzing data in MarketSight, the first step is to create a crosstab that displays significant relationships between variables. The platform automatically runs statistical significance tests based on the data in each crosstab cell. MarketSight reads the data and runs the appropriate test, highlighting the cells that are significant to help you focus on the essential insights.

statistical analysis

Statistics Settings

Additionally, MarketSight lets users personalize statistical analysis settings to match their level of expertise. You can change the type of test being run, adjust confidence level, correct for Type I errors, add weights, or even stat test using letters to denote which cells are significant against another. Users can also run multiple tests at once and apply labels that designate which test is which. The flexible interface lets you use your preferred settings across all analyses, or change them on a case-by-case basis.

R Integration

MarketSight allows you to take your analysis a step further with a native R integration, the open source scripting language for statistical analysis. Users can upload or write their own R script, allowing their research team to perform additional tests in the survey data analysis process, such as Max Diff, Conjoint Analysis, or Discriminant Analysis. Users can also run independent T-tests or create their own custom variables and import them back into MarketSight.

When looking for patterns and trends in survey data, running these types of scripts can help the analyst pinpoint positive and negative trends, relative importance, or areas of significance. MarketSight’s allowance of custom R scripts provides users unlimited options for completing analysis, and creates an output for each analysis that can be used to describe your insights.

Advanced Analytics

For quicker analyses, choose from one of several pre-built modules in the MarketSight application, such as:

  • Correlation
  • Linear, Logistic, and Ordered Regression
  • K-means Clustering
  • Factor Analysis

To run one of these tests, drag and drop your variables into the Advanced Analytics selection pane, and the results will be calculated instantly.


statistical analysis