In no more than 3-4 sentences, respond to the following: Provide a null hypothesis and an alternative hypothesis for a research experiment that utilizes the one-tailed test or the two-tailed test. Be

In no more than 3-4 sentences, respond to the following: Provide a null hypothesis and an alternative hypothesis for a research experiment that utilizes the one-tailed test or the two-tailed test. Be sure to clearly specify which one you selected.

This week's information addresses the problem of whether or not it is reasonable to conclude that a sample with a mean of M occurred by chance from a population having a given mean . The general hypothesis-testing procedure is employed.  First, you assume that the sample comes from the given population with a mean of some known quantity. Then set alpha and calculate the probability of randomly getting a sample mean as extreme as the one obtained. If this probability is less than alpha, reject Ho and conclude that the sample mean did not come from the given population. You can calculate the probability of getting a sample mean by chance with the aid of the central limit theorem. The central limit theorem states that if you make a distribution of a very large number of sufficiently large random sample means from a population, then the distribution of sample means will be approximately normal, the distribution will have a mean equal to the population mean, and the distribution will have a standard deviation equal to σ/√N. The distribution of sample means is called the sampling distribution of the mean, or simply the sampling distribution. A sample mean can be transformed to a z score in the sampling distribution. The probability of getting the sample mean by chance can be calculated from the z score. A hypothesis test conducted in this way is called a z test. If the population standard deviation, σ , is not known, you cannot conduct a z test. You can, however, estimate σ from your sample and use a one-sample t test to determine the probability of getting the sample mean by chance. Since estimating σ introduces additional variability, the one-sample t test compensates by using a more stringent decision criterion.