Stat 1040, Sections 007 & 009, Study Guide for Midterm 2 (Fall 2007)
Your second midterm exam is scheduled for Friday, November 9, 2007.
The exam is worth 200 points, i.e., 20% of your final grade.
A review session for Sections 007 & 009 will be held
at the following place and time:
- Thursday 11/8/2007, 4.45pm-6.15pm, BUS 313.
Note that quizzes, midterms, and final exams from the most recent
semester can be found in the Stat 1040 workbook. Solutions for these quizzes
and exams and additional quizzes and exams from earlier semesters
can be found on the course Web site at
http://www.math.usu.edu/~symanzik/teaching/2007_stat1040_fall/stat1040.html.
The second midterm will cover material from Chapters 11 through 20
(except Chapter 15)
of the Freedman, Pisani, and Purves book. To better prepare you
for the joint final, the second midterm will contain at least
one question from previous midterms or joint finals (as featured
in the Stat 1040 workbook or Web page), a review exercise question,
a question from a past quiz, and a new
question. However, just memorizing the answers from the Stat 1040
workbook (for the old exams or for the review questions)
is not sufficient since numbers in the questions will
be changed (while the principle of the question remains unchanged).
Overall, there will be 4 to 6 questions in this exam.
You will be given about 50 minutes to complete the exam. The exam
will be a closed-book exam, which means that you are not allowed to
use the textbook or the lecture notes. All required tables (such
as for the normal curve) will be provided and required
formulas will be listed on the exam. You should bring your
calculator!
To prepare for the exam, you should solve old exam questions,
review exercise questions, questions from old quizzes,
and regular exercises from the textbook.
During the review session, it is
planned to discuss selected exercises from old exams.
Make sure that you are familiar with the keywords and concepts
listed below.
- Chapter 11 (omit Sections 11.4 and 11.5) -
The R.M.S. Error for Regression:
error (residual), r.m.s. error (meaning and computation),
residual plots (construction and interpretation)
- Chapter 12 - The Regression Line:
slope and intercept for regression line
(interpretation and computation),
equation of the regression line,
prediction using this equation,
method of least squares (idea)
- Chapter 13 - What are the Chances?:
chance, probability, Opposites Rule,
conditional probabilities (conditional
and unconditional chance),
Multiplication Rule, independence and dependence,
drawing with/without replacement from a box,
Multiplication Rule for independent events
- Chapter 14 - More About Chance:
listing the ways (dice, coins, cards, etc.),
mutually exclusive events,
Addition Rule for mutually exclusive events,
general Addition Rule (see Possibility 1 and
Possibility 2)
- Chapter 16 - The Law of Averages:
the law of averages (interpretation),
box models (construction: what numbers,
how many of each number, how many draws),
sum of draws
- Chapter 17 - The Expected Value and Standard Error:
box average and box SD,
expected value (EV) and standard error (SE) of the sum,
square root law,
using the normal curve for box models,
classifying and counting,
shortcut formulas for the SD for boxes with only
two different tickets and for boxes with only
0 and 1 tickets
- Chapter 18 - The Normal Approximation for Probability Histograms:
empirical histogram, probability histogram,
similarity between empirical and probability histogram
after a large number of draws,
central limit theorem,
normal approximation for sum of draws (related to "large",
symmetric/asymmetric box)
- Chapter 19 - Sample Surveys:
population, sample, parameter, statistic, inferences,
polls, bias, non-response bias,
problems due to wording of questions,
probability methods, simple random sample (SRS),
voluntary responses
- Chapter 20 - Chance Error in Sampling:
expected value (EV) and standard error (SE) for the sample percentage,
square root law,
shortcut formula for calculating the SE percentage when multiplying
the size of a sample by a factor,
using the normal curve for 0-1 boxes
Note that even if a keyword is only listed once, it may be related
to more than one chapter (e.g., confounding or SD).