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Final Exam Prep Seminar Scheduled
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I am not ready to take registrations yet, but I want to let you know that the Final Exam Seminar will be Friday, December 5 from 9:00 am to 6:00 pm, and will be held on the UM campus (room 100 St. Paul's College). I will send you an email
when I am ready to take registrations.
Did you read my tips on how to study and learn Stat 1000? If not, here is a link to those important suggestions: Did you read my Calculator Tips? If not, here is a link to those important suggestions: You will have to study both Lesson 6: The Binomial Distribution and Lesson 7: The Distribution of the Sample Mean in my Basic Stats 1 book to prepare for this assignment. NOTE: You need only
study up to the end of question 7 (end of page 392) in Lesson 6 at this time (the rest of Lesson 6 will be covered after the second midterm). You also need only study to the end of question 7 in Lesson 7 (end of page 447). The section on control charts has been removed from the course.
Exception: Always do any JMP stuff open-book. Have my tips in front of you, and let me guide you step-by-step through any JMP stuff. JMP
is just "busy" work. The sooner you get it done and can move on to productive things like understanding the concepts and interpreting the JMP outputs, the better off you will be.
Don't have my book? You can download a free sample of my book and audio lectures
containing Lesson 1:
A Warning about StatsPortal
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Make sure that you are using Firefox for your browser. Don't even use Internet Explorer. It actually also has some glitches in the HTML editor boxes.
Do note that every time you exit a question in StatsPortal, the next time you return to it, the data may very
well change. Do not press the "back-up" button on your browser in a question. That, too, will change the data. When you are prepared to actually do a question, open the link, keep it open, and do not close it until you have submitted your answers. Be sure to press "Save Answers" once you have done any calculations and entered any information to ensure the data does not change and force you to start over again.
After you submit the answer to a question, if
you have been marked wrong on any parts, be sure that you write down the correct answers before you exit the screen (or grab a screen shot). To try a second attempt at the question do not click the link to the question again, that will change the data and you will have to start all over again. Also, DO NOT click "try again" or make a "second attempt." That will also reset the data.
Instead, exit back to the home screen where they show the links
for all the different questions on the assignment. Where it shows the tries for a question on the right side of your screen, you should see the "1" grayed out, showing that you have had 1 attempt. Click the number "2" to get your second attempt with the same data. That way you can enter the answers you already know are correct and focus on correcting your mistakes.
You should also have already downloaded the JMP statistical software which was provided
with either one of the course options for StatsPortal as mentioned in your course outline.
Make sure you have gone through Assignment 0 completely to learn how to use the interface. I also suggest you print out a copy of question 8 in Assignment 0 (Long Answer Questions - Part 3) so that you have the steps for saving and uploading files into the HTML editor in front of you.
Lesson 6. If you are ever asked to decide if a particular situation is binomial or not, remember, to be binomial, four conditions must be satisfied: - There must be a fixed number of trials, n.
- Each trial can have only two possible outcomes, success or failure, and the probability of success on each trial must have a constant value, p.
- Each trial must be independent.
- X, the number of successes, is a discrete random variable
where X = 0, 1, 2, ... n.
Hints:
- If you are reading off numbers from a randomly selected row in the random number table, note that every row has 40 digits. That is like 40 trials looking for whatever digit you may be looking for. What is the probability that, at any moment on the table, the next digit is a 0, or a 1, or a 2, etc..
- If you are selecting objects, are you sampling with replacement
(independent trials) or without replacement (dependent trials)?
- If you are given a Normal population, but are selecting a sample of size n, and want to see how many of them are greater than 62 (for example), THAT IS A BINOMIAL DISTRIBUTION! You can use Table A to find what proportion are greater than 62. That is your p. Each trial, the person/thing either is greater than 62, or they are
not. And the chance they are greater than 62 is p.
- If you are ever conducting trials until you get a desired result, that will never be binomial because you do not have a fixed number of trials, n.
Lesson 6. I introduce the formula for mean and standard deviation of a binomial distribution in my question 7. Note that they are asking for the variance, not the standard deviation. That is a little neater
since the variance is np(1-p).
Be careful that you are using the correct n and p for each question since they keep switching which colour light, and how many days they are talking about. Note that n is the TOTAL number of intersections the student has encountered during the time period.
I tell you the definitions of parameters and statistics at the start of Lesson 4 of my book and I repeat them again in Lesson 7 and illustrate with my question 1.
Note that although n is a sample size, n is a parameter. This is not a contradiction from what I tell you at the start of Lesson 4 and 7. It is still true that, when you are given n, you are being alerted that a sample has been selected, and any values they compute from that sample, by definition, will be statistics. However, the n,
itself, is considered a parameter.
This is Lesson 7 stuff. You have to always be asking yourself, "Is the problem talking about one individual score X? Or, is it talking about the mean of n scores, x-bar?" If it is talking
about just one score X, is X normally distributed? If it is talking about the mean of n scores, x-bar, can we assume x-bar is normally distributed? Why or why not? If we can assume these are normally distributed, then be careful to use the proper standardizing formula. Either the X-Bell Curve formula or the x-Bar Bell Curve formula.
Look at my questions 4
through 7 in Lesson 7 for examples. Especially take note of my questions 6 and 7 if they give you a total amount in a question.
Be careful in part (d). They are talking about the mean of a sample of some size n (the value of n varies for different students). Thus, you must compute the mean of x-bar and the standard deviation of x-bar, which are mu and sigma/ square root n
first, then use those values for your 68-95-99.7 rule. Make sure you put the smaller answer first. Approach this just like the previous question. Ask yourself the same questions.
Your probabilities are exact if you know for sure that the distribution is normal. However, if you were only able to say the distribution is approximately normal, then your probabilities are only approximate. This question boils down to,
"Were you told the population is normal?" If you know for a fact that the population is normal, you can compute exact probabilities. If you do not, the best you can do is compute approximate probabilities.
You are on your own for this question.
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