CRX id
jdijbhedpeoddlmcbooapojknnfkengj
jdijbhedpeoddlmcbooapojknnfkengj
Description from extension meta
This extension enhances Google Analytics by providing implicit statistical evaluation of data.
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Description from store
One very useful feature of Google Analytics is the comparison of timeframes for metrics. You can compare number of sessions, bounce rate, E-commerce transactions, AdWords cost, etc. between adjacent weeks, months, or years.
One shortcoming in this comparison feature is that the percentage change calculated by Google for these metrics is not qualified. This extension addresses this shortcoming by evaluating the change between time periods for statistical significance.
Currently, for 5 < points < 40 the Wilcoxon Signed-Rank test is used. For points > 40, the paired Student's t-test is used.
Release Notes:
Version 3.1
* Separate tab for each metric; support multiple metrics on graph
* Should support metrics from line graphs on any page
* Reload button for when extension misses capturing data
* Also show date range and percentage change for metric
Version 2.3
* Update calculation of Wilcoxon statistic (used when n<40) with port of SciPy implementation
* Styling changes
* Warnings added and other fixes
Version 2.1
* Versions 1.* were broken due to changes in Google Analytics. Updated data extraction to pull directly from Google's web requests, rather than calculating from the DOM. More accurate and robust
* When you change the dates or metric on a chart, it will automatically recalculate
Limitations:
1. Time frames to be compared should begin on the same weekday (Monday and Monday or Friday and Friday), to minimize confounding factors in the comparison. They should be the same length of time. Be careful to ensure this, especially for year-over-year monthly comparisons. This script derives its statistical power by treating metrics as paired data points (based on the day of the week).
2. Must compare at least 5 data points (days, weeks, or months). Beyond the lower limit, the statistical test lacks sufficient power.
For further documentation and description of the statistical tests, visit https://noahonnumbers.com/blog/entry/statistics-google-analytics
Latest reviews
- (2020-04-02) Eric Richard: The extension only says that "data is loading". Seems not to work. Sorry for the rating but chrom web store wants us to rate first before we write the review.
- (2014-05-30) Sean Clark: I am used to using "statistical significance" in our conversion rate optimisation, but to have it easily available directly in Google Analytics for any data is just awesome.