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 September 28th, 2012, 12:37 PM #1 Newbie   Joined: Sep 2012 Posts: 1 Thanks: 0 How would you figure out the confidence interval given... Lets say you want to test an email version for a marketing campaign, assuming a 5% click through ratio with 20,000 email addresses sample size. What would be the lower and upper bounds at 90% confidence interval if you were only willing to accept What would be the lower and upper bounds @ 90% confidence interval you would accept as �equal to the baseline� response rate? What about at 95%? Please explain how you would do something like this? September 28th, 2012, 07:09 PM #2 Senior Member   Joined: Aug 2012 Posts: 229 Thanks: 3 Re: How would you figure out the confidence interval given.. Hey fstep. If you are testing a proportion (i.e. estimating this from some data), then if you have a huge sample size: your distribution would correspond to an asymptotic distribution where [p - p_hat]/SE(p_hat) ~ N(0,1) where p_hat = X/n and SE(p_hat) = SQRT(p_hat*(1 - p_hat)/n) where n is the sample size and X is the number of successes. Since this is a normal distribution, you need to use a computer to find a value where P(-a < Z < a) = 0.9 for some a. For a 95% interval, the a is roughly 1.96 so it means for a 90% interval it will be slightly lower (but not a great deal). Now if you figure out this a (search for a Normal probability calculator on google) then your interval will be [p_hat - a*SE(p_hat), p_hat + a*SE(p_hat)] for some given a where this a corresponds to P(-a < Z < a) = 0.9 where a > 0 [It has to be]. Tags confidence, figure, interval Thread Tools Show Printable Version Email this Page Display Modes Linear Mode Switch to Hybrid Mode Switch to Threaded Mode Similar Threads Thread Thread Starter Forum Replies Last Post tay101 Advanced Statistics 1 January 7th, 2014 09:37 AM Jessicasamide Algebra 1 November 24th, 2012 08:57 AM Kat-M Advanced Statistics 0 May 12th, 2009 10:21 AM shalomhk Advanced Statistics 1 August 1st, 2008 12:50 PM symmetry Advanced Statistics 1 June 18th, 2007 08:17 PM

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