Open style Q&A (Because personal writing is hard to read. Just type the words, don't take pictures.)

Regarding the topic of hypothesis testing in chapter 7 of the textbook, what is one example in your life in which you'd like to conduct a hypothesis test? How would you do it? How would you gather data to prove your hypothesis true or not true? What obstacles would you encounter?

This is a difficult question because you are trying to come up with something you know is true and then prove it still true or prove it not true. And, it is an individual question. So our responses to each other could be of the nature of "did you think to gather the data this way or prove the hypothesis that way".

T Inferenees Based on a Single Sample TissIs onypotheses :- T.1 The Elements of a Test of Hypothesis STATISTICS in ACTION CONTINUED STATISTICS in ACTION REUISTTED - Key Elements of a Hypothesis Test [m - Testing a Population tulean [m - Testing a Population Proportion {p. 391} 0 Data Set: TISSUE Suppose you wanted to detennine whether the mean waiting time in the drive-through line of a fast-food restaurant is less than 5 minutes, or whether the majolity of consumers are optimistic about the economy. In both cases you are interested in making an inference about how the value of a parameter relates to a specic numerical 'II'EIUE. Is it less than, equal to, or greater than the specied number? This type of inference, called a test of hypothesis. is the subject of this chapter. We introduce the elements of a test of hypothesis in Sections 1113. We then show how to conduct a large-sample test of hypothesis about a population mean in Section T4. In Section TE we use small samples to conduct tests about means. Largesample tests about binomial probabilities are the subject of Section To, and a test about a population variance is covered in Section TT. Finally, so me advanced methods for determining the reliability of a test are covered in Section 18. T.1 The Elements of a Test of Hypothesis Suppose building specications in a certain city require that the average breaking strength of residential sewer pipe he more than 2,400 pounds per foot of length (is, per linear foot). Each manufacturer who wants to sell pipe in this city must demonstrate that its product meets the specication. Note that we are interested in matting an inference about the mean 3.: of a population. Howeyen in this example we are less interested in estimating the 'II'EIUE of p: than we are in testing a hypothesis about its valuethat is, we want to decide whether the mean breaking strength of the pipe exceeds 2,4ti pounds per iinear foot. A statistical hypothesis is a statement about the numerical 'II'EIIJE of a population parameter. The method used to reach a decision is based on the rare-event concept explained in eadier chapters. We dene two hypotheses: {1] The null hypothesis is that which represents the status quo to the party performing the sampling experimentthe hypothesis that will be accepted unless the data provide convincing evidence that it is false. {2} The altern ative, or research, hypothesis is that which will be accepted only if the data provide convincing evidence of its truth. From the point of view ofthe city conducting the tests, the null hypothesis is that the manufacturers pipe does not meet specications unless the tests provide convincing evidence othenrvise. The null and altern atiye hypotheses are therefore Nut! hypothesis (Hg) : p E 21.4\"\" [i.e., the manufacturer's pipe does not meet specications) Alternative (research) hypothesis {Ha} : p 3: 2,4011] [i.e., the manufacturer's pip-e meets specications}