Using statistical models to predict future sales

Building Models of Customer Behavior using Statistics and Multiple Regression

We also offer online tools for data analysis

Use nonlinear multiple regression to build a predictive sales model.


Online Tools: Multiple Regression, Graphing, and Summary Statistics
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Weather, Sales Trend demand forecasting
We offer three primary online tools. The graphing tool can be used for quickly visualizing sales data. The time-trend and summary tool generates summary statistics, calculates Pearson's r, partial, and semipartial correlations in order to generate a simple regression equation. This tool can be used to spot general time-related trends, and calculates to what extent sales vary predictably based on whether it is a weekday or weekend. Finally, the multiple regression tool analyzes patterns in daily sales figures related to changing local weather conditions, the season and holidays, and general sales trends to create models that describe both customer behavior and demand trends.
Step 1. Select a dataset from the following list
Step 2. Using the icons below, select the tool you want to use on the data.
Note: When you log in or register, you can create, manage, and store your own datasets online. Once stored, you can analyze your datasets using our free online tools (including the multiple regression analysis tool). As a guest, you can experiment with sample datasets, but any changes you make to the data will not be applied.
To proceed, select a dataset from the list above, or select a different online tool using the list below:
= Regression Analysis = Sales Trend Analysis with Summary Stats
= Bar Graph of Data = Manage or Edit Datasets
= Explore data/weather relationships and build your own model

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