Posts tagged with online statistics help

Almost all smart devices (phones, tablets, and computers) are made with touch screens. A concern of many consumers is the shelf life of the “touch” component of the screens. A consumer advocacy group wanted to inform its members of a range that they can expect their touch screens to last. The group took a sample of 26 screens and measured the life of the “touch” function of the screens. That is, they used digital devices to simulate billions of touches to determine the life of the screens. Of the 26 screens sampled, the average “touch” life was 90 months with a standard deviation of seven months. Construct a 98% confidence interval for the standard deviation of the life of the touch screens. Assume that the life of the touch screens has an approximately normal distribution. Round any intermediate calculations to no less than six decimal places and round the endpoints of the interval to four decimal places.

A technician working for the Chase-National Food Additive Company would like to estimate the preserving ability of a new additive. This additive will be used for Auntie’s brand preserves. Based on past tests, it is believed that the time to spoilage for this additive has a standard deviation of 8 days. To be 95% confident of the true mean time to spoilage, what sample size will be needed to estimate the mean time to spoilage with an accuracy of one day?

The electric cooperative needs to know the mean household usage of electricity by its non-commercial customers in kWh per day. They would like the estimate to have a maximum error of 0.13 kWh. A previous study found that for an average family the standard deviation is 2.1 kWh and the mean is 15.8 kWh per day. If they are using a 99% level of confidence, how large of a sample is required to estimate the mean usage of electricity? Round your answer up to the next integer.