States is 2.24. Assume the population standard deviation number of television sets in the United St is 1.38 a) Describe the sampling distribution for all sample sizes of n = 40. The distribution will be normal because the sample size is greater than 30 b) A random sample of 40 households results in a sample mean of 2.55 tv sets per household. Wh. the probability of obtaining a sample mean of at least 2.55 if the population mean is 2.24? Does contradict the results reported by A.C. Nielsen? 2.55-2.24 - 0.046 Since the probability is larger than 0.05 it is not unusual 1.38 V40 1-P(Z>0.05) = 0.52 c) construct a 95% confidence interval for the sample mean. How does this support your conclus on part b? (2.55+1.96() 1.38 V40- (2.55-0.428),(2.55+0.428) (2.12, 2.98) It supports b because mean 2.55 lies between 2.12and 2.98 d) Which would be more likely to happen...one household to have 3 televisions or a sample o households to have a mean of 3 televisions? Explain.

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Inverse Normal Distribution

The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.

Mean, Median, Mode

It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.

Z-Scores

A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.