Houston Community College Confidence Interval and Hypothesis Testing Discussion

Discussion Board # 5 Last DB

DISCUSSION BOARD DUE: NOVEMBER 9, 2020 AT 2PM CENTRAL TIME.

Overview: In module 2 we focused on using statistics to make assumptions about the entire population. What allowed us to make that connection was the:

Central Limit Theorem – if you can’t explain it in under 10 words you probably don’t get it! So in this DB be sure you have it down before you move on.

Submit: You may choose however you would like to submit your analysis- only request is that the work be converted to PDF, and you show your work. Failure to do so will result in loss of points. You are more than welcome to work all problems out by hand & feel free to add a catchy title for fun, also as a signal (data) to me that you know what you are doing.

Data you will need: Class Survey Data (Can be found in Files link to left or Modules tab)

1. Create a table – with column headers population, sample, & concepts. Then for each row put one important fact that you ‘predict’ will be on the exam & underneath each column heading (sample & population) give examples/symbols/etc. In the concepts column briefly explain ‘why’ you think it will be on the exam. Be sure to only include relevant examples, (Links to an external site.) therefore, there is no max or min on how many you need to include. As long as they are relevant (Links to an external site.)you are fine! This will “feel’ strange because I’m ask you to use your critical thinking skills, which isn’t hard but it is different. Do your best, I trust you but of course I’ll be sure to give you copious amounts of feedback until you get it right. You can compare & contrast, analyze, etc. Only thing to avoid is copy & pasting definitions.
2. Using class data create a 95% Confidence Interval on the average number of hours a student is taking at HCC
3. Draw a normal distribution curve & mark the mean, upper limit & lower limit
4. Is it possible to find someone on campus who is not w/in the upper & lower limits, if so, why would this happen & how often would it occur?
5. Looking at your answer above in #4 is that a fact?
6. Review the class data file – given an example when this would be the population, given an example when this would be a sample.
7. Perform a statistical test -Do Men & Women take the same # of Hours? Include all 6 steps outlined by book
   1. State Hypothesis Statements
   2. Significance Level – lets use 5%
   3. Determine test statistic – (depends on independence, are they normally distributed, etc-go back to your earlier analysis)
   4. Decision Rule -lets use 2 tail (this is much easier to learn at first)
   5. State your decision (did you use critical value & t statistic or P?
   6. Interpret the results – Is gender significant, why or why not (include diagram)

Feedback post: 100% of your grade will be based on this. You must peer review 2 posts and provide constructive feedback on their work to receive full credit.)

Word of caution: Most students will not link the concept of sampling to earlier chapters on bivariate data. Students will also confuse samples, with populations – best way to keep these straight is to understand that the terms are not permanent. It depends on context. Was survey we used a good sample? Are they independent, normally distributed, is standard deviation known (this will help you determine ‘which’ tests you can use).