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An information technology analyst believes that they are losing customers on their website who find the checkout and purchase system too complicated. she adds a​ one-click feature to the website to make it​ easier, but finds that only about 99​% of the customers are using it. she decides to launch an ad awareness campaign to tell customers about the new feature in the hope of increasing the percentage. she​ doesn't see much of a​ difference, so she hires a consultant to help her. the consultant selects a random sample of recent​ purchases, tests the hypothesis that the ads produced no change against the alternative that the percent who use the​ one-click feature is now greater than 99​%, and finds a​ p-value of 0.240.24. what conclusion is​ appropriate?

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MrCreighton

Two questions:

what is the confidence level we are looking at?

also the p-value of .240.24? Is that a mistake in typing or is it .240 to the 24 decimal?

Generally, if the p-value is less than the confidence level (alpha) you reject the null hypothesis. The null hypothesis here is that the ads didn't nothing to help.

For instance, if the p-value were .240 and the alpha was .05 you would reject the null hypothesis and say that the ads may have had an effect on the outcome.

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