Imagine that you are an expert in Website Analytics, and you have been hired to

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Imagine that you are an expert in Website Analytics, and you have been hired to

Imagine that you are an expert in Website Analytics, and you have been hired to manage a company’s websites. A successful website is one where visitors come and spend time on the site. More time spent on the site is desirable because you can then convince advertisers to pay you to place their ads on your sites. You have been asked to analyze performance of the following websites:
WGG.com – “Watching Grass Grow”, a website showing real-time live video of a field of grass growing on the lawn. Some data collection analysis of WGG visitors showed that out of 100 unique visitors, the average duration was equal to 2 minutes, with a standard deviation equal to 20 minutes.
Confidence Intervals
With 99% confidence, calculate the confidence interval that estimates the true duration of time a visitor would spend on the WGG site.
What would the Confidence Interval be, if you changed the confidence level to 90%? (Notice how the interval width has changed)
Based on your analysis, would you recommend that advertisers buy time and space to display their ads on the WGG site? Explain.
Is it better to have a higher confidence level and a wider range? Or is it better to have a smaller and more precise interval but lower confidence? Explain
Hypothesis Testing
Using a traditional hypothesis testing approach at a p-level or alpha of .01, test the same question/hypothesis about whether visitors spend a statistically significant amount of time different than 0 minutes on the WGG site. Be sure you specify your Null Hypothesis, and your Alternative Hypothesis.
Based on your hypothesis test analyses, would you recommend that advertisers buy time and space to display their ads on the WGG site? Explain.
Is you conclusion from a hypothesis test analysis to be consistent, or different from the conclusion from using Confidence Intervals? Explain
At the end of a hypothesis test, you must either reject or retain the null hypothesis based on the data, and make a decision. In the scenario here, what is a Type 1 error? What is a Type 2 error?

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