Math 533 Part B

The critical value for for this two-tailed test is. The rejection region is given by

So, we should reject the null hypothesis H0. At a 0.05 level of significance level, we conclude that there is a significant difference between the average height for females and the average height for the males.

Under Ho, the average proportion is: p= x/n = 48/450 = 0.10666. If H0 is true then we would expect the expected frequencies for each type of residences to be: fei = 0.10666*column total. Using PHStat, the expected frequencies are computed and used to evaluate the test statistic.

|A random group of apartments was selected from a city to analyze the number of bedrooms they have. Is there evidence to reject |

Select one (1) project from your working or educational environment that you would use the hypothesis test technique. Next, propose the hypothesis structure (e.g., the null hypothesis, data collection process, confidence interval, test statistics, reject or not reject the decision, etc.) for the business process of the selected project. Provide a rationale for your response.

When you perform a test of hypothesis, you must always use the 4-step approach: i. S1:the “Null” and “Alternate” hypotheses, ii. S2: calculate value of the test statistic, iii. S3: the level of significance and the critical value of the statistic, iv. S4: your decision rule and the conclusion reached in not rejecting or rejecting the null hypothesis. When asked to calculate p–value, S5, relate the p-value to the level of significance in reaching your conclusion.

To test the null hypothesis, if the P-Value of the test is less than 0.05 I will reject the null hypothesis.

Since P value is 0.049 which less than o.o5, the null hypothesis is rejected. The sample supports the alternative hypothesis that the mixing rate of the machine is less than 5 gallons per minute.

Solution: since the sample size 81>30 therefore we use Z test and the test statistics will be

Reject H0 if z cal is >than the z critical (1.96) or if the z cal is < z critical (-1.96)

“Hypothesis testing is a decision-making process for evaluating claims about a population” (Bluman, 2013, p. 398). This process is used to determine if you will accept or reject the hypothesis. The claim is that the bottles contain less than 16 ounces. The null hypothesis is the soda bottles contain 16 ounces. The alternative hypothesis is the bottles contain less than 16 ounces. The significance level will be 0.05. The test method to be used is a t-score. The test statistic is calculated to be -11.24666539 and the P-value is 1.0.  The P-value is the probability of observing a sample statistic as extreme as the test statistic, assuming the null hypothesis is true. The T Crit value is 1.69912702. The calculations show there is enough evidence to support the claim that the soda bottles do

Fry Brothers heating and Air Conditioning, Inc. employs Larry Clark and George Murnen to make service calls to repair furnaces and air conditioning units in homes. Tom Fry, the owner, would like to know whether there is a difference in the mean number of service calls they make per day. Assume the population standard deviation for Larry Clark is 1.05 calls per day and 1.23 calls per day for George Murnen. A random sample of 40 days last year showed that Larry Clark made an average of

H0: µ0 =3.2 GPA H1: µ0 ≥ 3.2 GPA The significance level is α = .05

a) A recent article in Bangladesh Observer indicated that the mean selling price of the homes in the city of Dhaka is more than Tk. 2200. Can we conclude that the mean selling price in the Gulshan area is more than Tk. 2200? Use the 0.01 significance level. What is the P-value?

The distribution of the test statistic under the null-hypothesis is derived from the assumptions identified previously. Common test statistics may follow the following distributions: Normal, Student T, and Chi-Square. This distribution separates the possible values of the estimator into two categories: values for which the null-hypothesis is accepted or rejected. The region for which we accept the null-hypothesis is called the critical region and the area underneath the curve that corresponds to the critical region is known as the level of confidence. Hence, we can develop a confidence interval for which we can see the lowest and highest point of the critical region. Any observed sample mean that lies outside of this confidence interval (outside the critical region) would cause us to reject the null-hypothesis in favor of the alternative hypothesis. The area of the rejection region is known as the level of significance and represents type I error (alpha) corresponding to the probability that a true null-hypothesis is rejected (as opposed to type II error- beta; the probability of accepting a false null-hypothesis). Essentially, hypothesis testing calls for comparing a test statistic to the critical value of the test statistic. If this test statistic is greater than the critical value of the test statistic, we will reject the null hypothesis in favor of the alternative hypothesis. If