Statistical Calculators

Make sure your data is Real Data! Setting up experiments? A/B tests? Doing data analysis? Perform the necessary stasticial calculations on your Google Analytics or AdWords data with our tools: statistical significance calculator, sample size calculator and more. To use this tool, you need to sign in to Analytics-ToolKit.com. Sign In or Register For Free.

Why use this tool?

If you are making data-driven decisions you need statistical calculators in order to mimize the possibility of wasted budgets or, to the contrary - missed opportunities. Without a significance calculator you can't differentiate between noise and data, chance and real results! With this tool you can make sure that the experiments you set up are good and that your decisions are based on statistically sound data.

The statistical significance calculator is one of the most advanced out there and excels where many others fail. It handles multiple variants properly by adjusting for the increased False Discovery Rate. It also checks the power of the tests in order to prevent you from acting on an underpowered test, and more.

  • Advanced Statistical Significance Calculator
  • Sample Size Calculator
  • Input data in bulk
  • Unrivaled ease of use

Statistical Significance Calculator

Close [X]



Statistical Significance Calculator - Video Transcript

In this video we present the Statistical Calculators in Analytics-Toolkit.com.

We’ll begin with our statistical significance calculator. Calculating statistical significance is a fundamental part of any internet marketing analysis. Without it you could easily fall prey to the noise in your data and mistake a false positive for a real result and vice versa.

Stopping a successful campaign or ad copy could be just as destructive to your business as continuing to run an underperforming one. If you are not calculating the statistical significance of your data you have no valid way of telling which is which.

Our calculator is here to help. First, input the sample size – that is in most cases the number of ad impressions, website visits or pageviews. Then enter the conversion rate for the metric of interest, be it CTR, goal conversion rate, e-commerce transaction rate or others. Select the required level of confidence. A level of 90% would mean that there is a 1 in 10 chance that the results you are seeing are due to pure chance.

Let the calculator do its job and tell you if you have a winner or if your data is inconclusive. You can add and remove rolls as you want. You can also do a bulk input, as we shall now demonstrate with data from Google AdWords. Export the data from AdWords into Excel, then copy-paste it into our bulk input field. Voila!

What differentiates our calculator from most other calculators is that it supports multiple comparisons and corrects intelligently for the error that is introduced when doing so. It uses the False Discovery Rate correction method developed by Benjamini, Hochberg and Yekutieli.

Our other calculator is the sample size calculator. It lets you estimate how much traffic you’ll need to send to a test in order to be able to detect a given amount of change with a selected amount of certainty.

Stop chasing the statistical ghosts: use a good statistical significance calculator.

Close [X]

Tool Characteristics

Automation N/A

Time-Saving N/A

Unique Tool Yes / No

API Only N/A

Expertise Level Novice / Experienced / Expert

How to use this tool?

There are actually several tools under the hood here. The first one allows you to compute how much traffic you would need in order to have a statistically significant result from a given experiment. The other let's you calculate whether the observed differences your data comparisons (A/B testing of any kind) are real or are due to chance alone.