State-of-the-art Regression In Minutes

Harness the power of regression analysis with Displayr. Our intuitive tools make it easy to uncover key data relationships, empowering confident, data-driven decisions and insightful trend analysis.

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Illustration of Regression
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Unlock insights with advanced regression tools

Illustration of Regression - Easy to use

Easy to use

Drag and drop data to run a regression (no need to write code). The outputs automatically show the key results in an easy-to-digest format, so you don’t need to spend time working out which output to read and why.

Expert systems that make you an expert

Displayr’s expert systems guide you through choosing the appropriate type of regression – linear, logistic, ordered logit, NBD, etc. – and automatically solving many of the uglies of regression analysis, such as outliers, multicollinearity, heteroscedasticity, and categorical outcome variables.

Illustration of Regression - Designed for survey data
Illustration of Regression - Expert systems that make you an expert

Designed for survey data

If you have ever read their manuals, you will know that most regression software is not designed for survey data, and will calculate statistical significance incorrect if you use weights. Displayr uses Taylor Series Linearization to appropriately perform the regression with weighted data.

Best-in-class for missing data

One of the great innovations in regression in the past few years has been the use of multiple imputation for missing data. Displayr automates this entirely. And, you can still use the older methods if you prefer them as well.

Illustration of Regression - Best-in-class for missing data
Illustration of Regression - Automated updating

Automated updating

Analysis will automatically update when you revise the data, whether filtering, data cleaning, or adding in a new wave of data.

Life without Displayr would be like going back to the dark ages. I don’t even want to imagine it.
Michael Alborough
Michael Alborough

Founder, MAC Research

10x faster regression

Displayr works with all types of data

All types of data

SQL, databases, Excel, CSV, text, SPSS, survey platforms, APIs, integrations, & more.

Displayr support all types of analysis

All types of analysis

Summary tables, crosstabs, pivot tables, regression,
text analysis, segmentation, machine learning, & more.

Illustration for displayr all types of reporting

All types of reporting

Data visualization, interactive data apps, dashboards, presentations, PowerPoint, Excel, PDF, web pages, & more.

Integrated AI

Integrated AI

Displayr’s Research Agents integrate AI across your full workflow, from data cleaning to analysis to reporting.

Case Study - CYGNAL

Global Survey Research Company ​

Displayr helps Cygnal cut report creation time in half

Challenges

  • Time-consuming manual processes
  • A need to offer dynamic data presentations to stay competitive—and no time to create them

Solutions

  • An all-in-one statistical package built for survey data with presentation and dashboarding tools

Results

  • 50% time saved on data presentations and reports
  • More deals closed

“Displayr is at least 50% faster than just creating a PowerPoint presentation. In some cases, I think it’s even higher than 50%.”
Matt Hubbard
VP Data & Analytics, Cygnal

See why people love Displayr

Regression FAQs

What is regression, and how does it work?
Regression quantifies the relationship between an outcome variable and one or more predictor variable. This might be looking at a company’s how sales would be impacted by a pricing change. There are several different types of regression – each serving a different purpose – including linear, logistic, ordered logit, NBD, and more. Linear regression is the most commonly used model.
Estimating regression is relatively simple. The tricky part can often be selecting the correct regression model for your data. The right regression model depends on your data type, variable relationships, and analysis goals, whether for prediction, explanation, or pattern detection.
Businesses use regression analysis to forecast sales by identifying relationships between sales data and influencing factors such as pricing, marketing spend, seasonality, and customer behavior. This insights helps optimize strategies and improve revenue projections.

Displayr allows users to create regression models with just a few clicks. Various models are available via Anything > Advanced Analysis > Regression. You can also check out this guide on how to run linear regression in Displayr.

To perform regression analysis in Excel:

  1. Go to Data > Data Analysis (enable the Analysis ToolPak if needed).
  2. Select Regression and choose your input data range.
  3. Define the dependent (Y) and independent (X) variables.
  4. Click OK to generate regression output, including coefficients, R-squared values, and significance tests.

Several software tools support regression analysis, including:

  • Displayr (no-code workflows for quick analysis)
  • R (advanced statistical computing)
  • Python (Statsmodels, scikit-learn)
  • Excel (basic regression tools)
  • SPSS, SAS, and Stata (industry-standard statistical software)

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