Math 103 Spring 2012

Exam 3 review

The third hour exam will be on Friday, April  20, in class, and will cover Chapters 6 through 8 of the textbook (but please remember that you are still responsible for the tools and definitions given in Chapter 5.

Some preliminary notes:

• I have attempted to be comprehensive in the following, but you are responsible for the material covered, even if I do forget to list something here.  If you do find an omission, please do let me know.

• You may find a calculator useful on this exam, but only for the usual operations of addition, subtraction, multiplication, division, and the calculation of square roots.  The use of statistical functions on your calculator is not permitted.

In your review, look at definitions, textbook examples, and homework problems assigned.  In particular:

• Be able to give a definition of terms encountered so far (a list of definitions appear at the end of each chapter).  We have had quite a lot of them in the chapters covered for this exam (including chapter 5, whose definitions you should know).

• Be able to explain the difference between explanatory and response variables.

• Be able to draw a scatter-plot and to describe it (form, strength, etc.).

• Be able to calculate Pearson's correlation coefficient from data provided..

• Be able to calculate the equation of a linear regression line from the correlation coefficient and averages and standard deviations of the variables involved.  Be able to use the linear regression line to make predictions.  Be able to say what a residual is, and why the linear regression line is a "least squares" linear regression line.
• Be able to describe the difference between a population and a sample, and the difference between a parameter and a statistic.
• Be able to describe kinds of samples (i.e., voluntary response sample, convenience sample, etc..  Be able to say what it means for a sample to be biased.
• Be able to say what a simple random sample is and be able to produce one using a table of random numbers (to be provided with the exam).
• Be able to describe what an experiment is.
• Be able to say what it means for a result to be statistically significant.
• Be able to say what a 95% confidence interval and be able to compute one both as an interval and as a margin of error.
• Be able to say what a random phenomenon is, what a sample space is, what an event is, and what the probability of an outcome means.
• Be able to say what a probability model is, and to give (and use!) the rules for probability models, along with attendant definitions (complementary events, disjoint events, independent events, etc.).
• Know and be able to use the rules for counting given in chapter 8.  Know which rule to use when.
• Know what density curves are and how they may be used.
• Be able to describe and use the Law of Large Numbers.
• Be able to describe and use the Central Limit Theorem.

• We have discussed several mathematicians during the past few weeks.  Please be prepared to give brief descriptions of each and be able to say how they are relevant to this course.  Links provided point to articles about the mathematicians.

• Jakob Bernoulli
• Girolamo Cardano
• Pierre de Fermat
• Pierre-Simon Laplace
• Abraham de Moivre
• Blaise Pascal
• Simeon Poisson

Notes: 

1.         Show your work.  Answers given without indication of how you got the answer may not receive credit

2.         Calculators will be permitted on this exam.  In problems involving calculating a number, however, it is sufficient to leave the calculation in a form in which it can be entered into a calculator.  If you do use a calculator, you should include this “pre-calculator” expression as part of your answer.

Any questions?  Please ask!