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  • Sample size and statistical significance in Google Analytics

    - by colmcq
    I have been asked to compile a report into dropout rates during checkout for a global webstore I have used a sample size over one month as my sample because: google analytics slows to a crawl over larger sample sizes and makes much of the analysis agonisingly small I believe it to be statistically significant and a representative sample My client has asked me why I didn't use yearly figures and wants proof that one month of data is 'statistically significant'. Am I right in thinking that I need to compare the standard deviation of my monthly sample to the yearly sample and ensure that the deviation is under a certain %age? Question: how do I prove one month of Google Analytics data is representative to one year worth of data? Stats: 90k unique views/month ~1.1m per year.

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  • over reporting in google analytics - social media stats

    - by colmcq
    I have a client and their traffic from social media reads thus: 80% from facebook 1% from Twitter This suggestsd they are not exploiting twitter at all and this was in my presentation but my boss took it out claiming twitter stats are under reported in google analytics. I can't substantiate this claim and wonder where she got this idea from. Can anyone shed light on this? Are my stats wrong and should I disregard these figures? but 80-1 seems like one hell of an under report! thanks c

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  • google analytics statistics

    - by colmcq
    I am compiling a report for a client using google analytics. I have observed that the client has unusually good page view times (5 mins) and excellent bounce rates (<25%). I need to reference research data that validates my assertion that these figures are excellent compared to an industry standard (the industry is ecommerce and gaming). Can you direct me to any published research data that specifies normal bounce rates and page view times for this industry?

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