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1.what is an adequate and reliable sample size. Obviously, for some populations 30 is enough. But what about if you are not sure? Also, if you total population is only let’s say 1500, you would use it. Right? Yes – no?
2.Reading a newspaper article, you learn that the national unemployment rate is 5.1%. The next month you read another article that states that a recent survey in your area, based on a random sample of the labor force, estimates that the local unemployment rate is 4.7% with a margin of error of .5%. Thus, you conclude that the unemployment rate in your area is somewhere between 4.2% and 5.2%.
So, what does this say about the local unemployment picture in your area versus the national unemployment situation? Since a major portion of the interval for the local unemployment rate is below 5.1%, is it reasonable to conclude that the local unemployment rate is below the national unemployment rate? Not really. When looking at the confidence interval, you have some degree of confidence, usually between 90% and 99%. If we use
z=1.96
z
When making conclusions based on the types of confidence intervals you have learned and will learn in this course, you will only be able to conclude that either there is a difference or there is not a difference. However, the methods you will learn in Chapter 9 will also allow you to determine the validity of a conclusion that states that the local rate is lower (or higher) than the national rate.
3.What to do , and how to look at the null hypothesis
4.Try finding a confidence interval yourself. A commonly used degree of confidence is 95%, corresponding to an interval extending about 2 standard deviations either side of the mean as the 68-95-99.7 rule says. In this case, the low-bound is about 15.7% and the high-bound is about 20.9%, thus a confidence interval for the proportion of times the dissolved oxygen levels failed to meet minimum standards says that although we can never know the true proportion, we can be 95% confident that it is no less than 15.7%, nor more than 20.9% of the time.
5.Watch the “p-value Approach” video in Ch. 9.
Consider the following as you watch:
- Set up and design a scenario in which a hypothesis test is warranted. Identify all main terms above in this context.
Discuss your perceptions in class/online forum.
6. Carefully define the following terms: Null hypothesis, alternative hypothesis, Type I error, Type II error, one-tailed test, two-tailed test
- Carefully define the following terms: Null hypothesis, alternative hypothesis, Type I error, Type II error, one-tailed test, two-tailed test
