During the quarter, a series of emails will be sent to all students who are enrolled in the class. Each of these messages is also posted to this page for later reference.
All course email is automatically sent to each student's UW email account. Thus, students who use a private commercial email account or a departmental email account are responsible for having their UW Dante email forwarded to their other account. Also, for access to some course web pages you must use your UW NetID and UW password.
Date: Fri, 25 Sep 2009 19:56:48 -0700
Subject: Welcome to Q SCI 381 Section C
We wish to welcome you to the start of autumn quarter and to Q SCI 381C. We hope you have an enjoyable experience this term.
To access information about the course on the web go to the following web site:
http://faculty.washington.edu/bare/qs381/qs381.html
All course information is posted on this web site. Please familiarize yourself with all of this information. Also, please note that additional study materials are available on the CourseCompass web site which is accessible from the above course web site. Please register on the CourseCompass web site so you can access the additional course materials. Free access to CourseCompass via an access code comes with a purchase of the new textbook package purchased from the U Bookstore.
The first hourly exam is on Wednesday, October 14. As with all exams, it is closed book. Please bring a hand held calculator and your formula card (sheets) to all exams (see next email for more information about the formula sheets which come with the purchase of a new textbook). When needed, we will provide statistical tables that are not included with your formula sheets.
If you wish to take the exams at an off-campus location such as UWB, UWT, a regional university, a community college or a city/county library you must let me know the name and email address of the exam proctor at your preferred location by the end of week one of the term.
All homeworks are self-evaluated and not turned in for a grade. Exam dates are shown on the course web site. All exams MUST be taken on the dates shown. Our web site shows the times for all hourly exams. The room location for the Exams will be posted as soon as it known.
Please use your UW email account and UW Net ID when communicating with us. If you use an alternate email system please set your UW email account to automatically forward your email. You will not be able to use the class email list or the online discussion group unless logged into the UW system. Also, be careful when using the class email list as your response might be sent to the entire list instead of only me or the person you intended.
If you need assistance please plan on coming to the TA sessions in MGH 291 during office hours.
If you have any questions please email me or Stanislav (our TA).
Thanks and welcome aboard!
Access to CourseCompass
The course id for access to CourseCompass is bare93379. The web site is www.coursecompass.com.
On-line Quizzes and Tests
The quizzes and tests that you may access on-line through the CourseCompass web site are for YOUR USE only. The same holds for the quizzes and chapter tests found in your text book. Do NOT send to me or our TA as they are not graded by us and they are not counted in computing your grade for the course.
Reserve Materials
The reserve copy of the Larson/Farber text (4th Edition) and a copy of the student's solution manual are available in closed stacks reserve in the OGUL. Online study aids, including an online version of the text, are also accessible from the CourseCompass web site. No other edition of the text will suffice.
Formula Card (Sheets)
If you bought a used text, you may be missing the detachable Formula Card (sheets) that you are allowed to use during all of our closed book exams. If so, you may print a copy from the CourseCompass web site. Go to Chapter Contents (Tools for Success) on the CourseCompass web site.
You may bring your hand held calculator and all pages of the formula card (sheets) -- including those pages that contain the statistical tables -- to the exams.
You may write any notes that you may need on the formula sheets, but only on the side of the paper that contains printed material. You can not use your text or any old exams during the tests and you can not share your formula card or any thing else with anyone during any exam.
Study Groups
We encourage you to utilize the online discussion group if you have questions. It is accessible from our class web page.
Purchasing MyMathLab Access Separately from the Text
If you purchased a used copy of the text, you probably do not have an access code to use the CourseCompass web resources for our course. If this is the case the following instructions will allow you to purchase this access code online
1. Go to the CourseCompass web site and click the Register button in the Students dialog box on the right.
2. Locate the credit card option you wish to use and proceed to purchase your access code online.
3. The course id is bare93379
These instructions are also available online from our class web site. Look under Class Email Archive. Thanks.
I hope you have found our course web page and are completing the self-evaluated homework assignment one. Homework One is a short assignment that covers some elementary introductory concepts in Chapter One and the first section of Chapter Two.
Our course web site is: http:/faculty.washington.edu/bare/qs381.
The CourseCompass web site is: www.coursecompass.com.
To register for CourseCompass the course id is bare93379.
All information about the course is available online. You are responsible for reading this information.
A word about the course--
Although this is a relatively easy course, you must spend time with the material and you must keep up. Expect to spend at least ten hours per week studying the material. Once you fall behind it is very difficult to catch up. We cover one chapter per week and we have five hourly examinations spaced about every two weeks. Plan on spending a good amount of time reading and working problems each week. If you have questions contact either your TA or me and come to our office hours for extra help. We are here to help you succeed, but you are ultimately responsible for learning the course material and showing your proficiency on the exams.
An online discussion group is also available for you to exchange questions and answers. I will also be monitoring this site and will participate as needed. I also answer email inquiries frequently during the day. Note you must be logged into the UW computer system to access the online discussion group.
Hourly Examination One is on Wednesday, October 14 and covers Chapters 1-2. A practice examination (with answers) is available on our course web site. In addition, the CourseCompass web site contains chapter quizzes and tests that you may use to test your understanding of material presented in the text.
I suggest that if you need extra help you use the video lectures available from the CourseCompass web site -- Chapter Contents.
Best wishes.
Homework Two (self-graded) should be worked this week. Hourly Examination One is scheduled for Wednesday, October 14. It covers Chapters 1-2 and is closed book.
Bring all pages of your formula card (sheets), including those pages that contain the statistical tables, with any additional notes you wish to inscribed thereon and a hand held calculator to the exams. You can not use your text, nor any other materials other than the formula card, during the exams, and you can't share your formula card with others.
You may arrange to take the exams at a remote location such as UWT, UWB or a county/city library. If you live away from the Seattle campus and wish to do this, I need the email address and name of the exam proctor by the close of business October 9 so I can make proper arrangements with the remote site.
A practice exam similar to Exam One with answers is available on our class web site. You should also use the review exercises located at the end of each text chapter as a study guide. Additional review quizzes and tests are available on our CourseCompass web site.
In Chapter Two we continue our study of graphical ways to summarize and present data; investigate numerical ways to measure central tendency; measure variation in a data set; and measure the position of a data point in a data set.
If you have questions or concerns about the class send me or our TA a cheerful email.
This week we study the elementary rules of probability in preparation for the rest of the course. Some of these rules are very simple while others may perplex you for a while. While the math is simple -- the logic may be confusing. In Chapters Four and Five we will apply many of these rules to more applied situations as we move on to study inferential statistics.
Probability is an essential aspect of inferential statistics because when we sample a population and make an inference about the larger population, we can never be absolutely sure that our inference is correct. Thus, there is always a chance that an error is made. Probability theory allows us to quantify the magnitude of this error. Thus, it is a very important aspect of statistics.
If you have questions or concerns about the class send me an email. Also, please work as many problems as you have time for and utilize the Course Compass web materials.
Class:
Next week, both Stanislav (our TA) and I will be out of the country attending a symposium. However, I will be in email contact should any questions arise and I will also monitor our online discussion board.
Our exam on Wednesday, October 28 will be proctored by Mr. Daisuke Sasatani. Exam times/location are as posted on our class web site: http://faculty.washington.edu/bare/qs381/hexam.html.
If you have a class conflict on Wednesdays and need to take the exam on a different date you have two options: -- go to MGH 291 at Noon on Tuesday, October 27 or Noon on Thursday, October 29 to take Exam Two. Daisuke will be in Room 291, MGH from Noon-1:20 on both of these days.
In week four, our attention turns to Chapter Four and an investigation of discrete probability distributions. We first learn how to define a probability distribution and then how to calculate the mean (expected value), variance and standard deviation of same. Some distributions are so common we have attached names to them. Specifically, we study the binomial, geometric and Poisson distributions. For each, we can easily determine the mean and standard deviation using formulas shown in our text. Each of these distributions is defined in terms of one or two parameters.
As usual, work plenty of problems to ensure that you have grasped the basics being described. Please visit our CourseCompass web site for additional study suggestions.
Hourly Examination Two takes place on Wednesday, October 28. It covers Chapters Three and Four of our text. Please bring your formula sheets (with any additional notes inscribed on the printed side of the page only) and a hand held calculator. No other materials may be used during the exam. You can't share formula cards during the exam.
We will hold the exam at the times and location shown on the class web site.
A practice exam (with answers) is available on our class web site. You should also use the review exercises located at the end of each text chapter as a study guide. Review quizzes and exams are also available on our CourseCompass web site.
If you need assistance please contact our TA. Thanks and good luck.
In week five our attention turns to Chapter Five and an investigation of continuous probability distributions -- notably the normal distribution. This two parameter distribution is the most used of all distributions we encounter in our studies this quarter.
As usual, work plenty of problems to ensure that you have grasped the basics being described. You can also view videos available from our CourseCompass web site if you need extra help.
The reason the normal is so widely used is due to the Central Limit Theorem. In many practical applications of statistics we must draw a sample from a population. Based upon this sample, we intend to draw an inference about the larger - unsampled - population. Usually we only draw one sample of some given size. The Central Limit Theorem states that if the sample size is about 30 or larger, the distribution of sample means is approximately normal and becomes more normal as the sample size increases. See our class web site for some additional information on the normal distribution and the Central Limit Theorem.
Thus, even if we sample from a population where the characteristic we are measuring is not normally distributed, if the sample size is 30 or more, the distribution of the sample means is approximately normal and we can use the normal distribution to determine the needed probabilities to place confidence bounds around our estimate of the sample mean.
And, if the sample we draw is random, we also know that the mean of the distribution of sample means is equal to the population mean. Of course, for any one sample, it is very unlikely (i.e., probability = 0) that the mean of our single sample exactly equals the population mean. But, using the techniques from the next chapter (Six) we are able to establish confidence intervals around our sample mean and these tell us how much confidence to place in our sample results.
The idea to remember at this point is that the normal distribution is very important in our future study of inferential statistics -- largely because of the Central Limit Theorem.
With these inspiring words I turn you over to Chapter Five. Best wishes.
This week we study Chapter 6. It is a long chapter wherein several new ideas are introduced. You learn how to construct confidence intervals about population means, proportions and standard deviations based upon sample evidence drawn from random samples. In developing confidence intervals about population means, two procedures are introduced depending upon sample size. If the sample size is < 30 a new continuous probability distribution is used -- the t-distribution. You also are shown how to determine the appropriate sample size required given the level of confidence and accuracy desired. The maximum error of estimate is also defined and is equal to 1/2 of the confidence interval. When setting a confidence interval for the standard deviation or variance, another continuous distribution is introduced -- the chi-square distribution. Unlike the z and t-distributions, the chi-square is not symmetrical. You also learn how to determine the confidence interval for a population proportion.
As usual, work plenty of problems to ensure that you have grasped the basics being described. CourseCompass is available to provide additional problems and study materials.
Examination Three is scheduled for Thursday, November 12. It covers Chapters Five and Six of our text. Please bring your formula sheets (with any notes you care to add on the printed side of the page only) and a hand held calculator to the exam. No other materials are allowed to be used during the exam. You cannot share your formula card (sheets) with others.
We will hold the exam at the times and location shown on the class web page.
A practice exam (with answers) is available on our class web site. You should also use the review exercises located at the end of each text chapter as a study guide.
If you need assistance please contact our TA. Thanks and good luck.
This week we study Chapter 7. It is a fairly long chapter wherein several new ideas are introduced. In section 7.1 you are exposed to the concepts that underlie hypothesis testing. This is a very important discussion that involves logic much more than statistics. In the remaining sections of the chapter you apply this logic to hypothesis tests involving population means, proportions and standard deviations based upon sample evidence drawn from random samples.
In testing a hypothesis for population means, two procedures are introduced depending upon sample size. If the sample size is < 30 the t-distribution is used. If n >= 30, we use the standard normal distribution. You also are shown how to calculate and interpret the P-value. When testing a hypothesis for the standard deviation or variance, we use the chi-square distribution. We also learn how to test a hypothesis for a population proportion for a large sample.
As usual, work plenty of problems to ensure that you have grasped the basics being described.
Thanks and best wishes.
Some additional information related to hypothesis testing can be reviewed at this link.