PROFESSOR: Ms. Sally Sievers.     Email: sievers@wells.edu   Website: aurora.wells.edu/~srs
         Office: Macmillan 102. Phone: 364-3210 (office), 607-257-7641 (home).

I am on campus MWF from about 9:15 to 4:00. Find me, I'm yours, usually. I teach at 9:30 and 11:30.  If not in my office, I am usually in one of the computer labs or math prof’s offices, or will leave a note on my door. After class is a great time to meet if you're free. Best is to let me know you want to see me and when (i.e. make an appointment, by phone, email, or at class time).

OBJECTIVE: To learn many of the ways in which information can be derived from data, and some models for chance phenomena.
The focus will be on

• the techniques of data analysis, summarizing and interpreting collections of data;
• ideas important in the collection of data, as in designing experiments and sampling;
• and the ideas and techniques of statistical inference, drawing conclusions from a set of data about the world from which it came.
• All but the first topic require some concepts from probability, to create mechanisms that produce data that can produce good inferences about the mechanisms.

TESTS: Quizzes will be given at intervals as needed (closed book). Exams may be in-class, closed book, take-home open book, or a combination.  There may be a project component as part of Exam 1.)
Exam 1 Somewhere in Sept. 30-Oct. 12
Exam 2 Somewhere in Nov. 4-18
Final Exam , take-home open book, due Thursday, Dec. 19

TEXT: David S. Moore and George P. McCabe, Introduction to the Practice of Statistics, 5^th ed. I think this is a great book, chuck full of important stuff, and the spearhead of the latest philosophy of teaching and understanding statistics. Though it is an "introductory" text, it assumes a fairly high level of reading and reasoning sophistication. The amount of formal math in the text is not great: I will "add" some in class.
I expect to cover a good portion of chapters 1 through 8; more if time allows. We will not have time in class to go over all the material in the text—I will be concentrating on areas that need the most extra input. You however are independently responsible for all the assigned material—happily, the book uses lots of section heads, boxed items, words in the margin, summaries to guide you. Annotate and mark, take notes.
The problems are one of the strongest parts of this strong book. Almost all of them are taken from real life.
Try to imagine yourself as the data collector—how would you acquire such values—and the user—what information do you want out of this data?

COMPUTATIONAL AIDS
We will be learning to use SPSS, a very powerful statistical computer package.  I'll provide handouts.

Everyone should have a calculator with at least a square root button to do simple computations. If you have a scientific calculator with statistical capabilities, fine, but don’t buy one for me.

OTHER RESOURCES
I will use handouts and material in lecture which will supplement the text, and may have some reserved readings. (here is where we will use a small amount of differentiation and integration.)
    Solutions to Exercises--for all problems.  One copy is in the Math Clinic; Mac 101 computers: Class Material/Math251 folder .
   CD in book mirrors most of website stuff (www.whfreeman.com/ips).  We'll use some...

HOMEWORK: Homework will be assigned every class day and collected the following class. The website will give the assignment for each day, with updates and corrections.  Please label it with the class day it was assigned. I encourage you strongly to get a "homework buddy" or buddies to work with: you are each other’s best teachers and supporters--the best way to learn is by teaching!

Odd-numbered problems have solutions in the back of the book. Solutions to ALL the problems in the text are in the Math Library, Mac 121,& on Mac 101 computers.  Our able grader and assistant is LaReina Bates.

If you don’t "get" a problem, don’t try to fake it--set down as clearly as you can how and where you went wrong. It is better to know that (and what) you don’t know than to not know that you don’t know. Bring remaining questions to class. Homework and class participation will be marked more on conscientiousness, effort and engagement with the process than with "correctness."

CLASS WORK: Again, you are each other’s best teachers and supporters; the best way to learn is by teaching.

--To this end, in the first several minutes of each class you will check over your homework with a neighbor in the class, (not your "buddy") and try to resolve any difficulties or questions. When you as a pair have resolved what you can, take your further questions to another pair--or if you have no more questions, take your expertise to people in the class who need it.  Write the number of any remaining problem on the board!

--The next part of the class will be devoted to a brief discussion of any remaining questions or ideas that were prompted by the homework assignment, of interest to much or most of the class.

--The third part will be the introduction of new material.

Study skills:
In 1995 American college freshmen reported that they spent an average of 3 hours a week studying in high school (I doubt it's gone up.). This is less than the amount spent PER DAY in any other industrialized country.
The classic rule of thumb for college courses is two-three  hours of study for every hour of class time, but for some courses this is more than enough and for some it is not nearly enough. (A recent survey of an elementary (!) statistics class at another college found the average time was 11 hours per week.) Also time put in may or may not be effective or productive. New studies show that it takes several hours for skill learning (e.g. playing a piano piece) to sink into long term memory, and the process can be disrupted if too much is crammed in at once. If, as I suspect (no proof), a similar thing happens with conceptual learning, many shorter sessions will be more effective than one long exhausting session. Experiment, keep notes on what works and what doesn’t!