
Department of Statistics
California State University,
Hayward
Winter 2003


Stat 3601: Introductory Statistics for Scientists and Engineers
Week 9:
 This Thursday there will be a takehome midterm give in class. The
will cover the normal distribution and the basics of confidence intervals and
hypotheses tests.
 There will be a quiz given in class next week on Tuesday.
 This week we will continue talking about Statistics, confidence intervals
and hypothesis tests.
 Computer Lab Examples:
 Minitab: Control Charts. Is a "process in control" or "out
of control?" Using the appropriate statistical methods we can get a
good idea about how well a production process is going. See the
following link to a webpage on
control charts.
 Midterm 2 will be a takehome exam.
TakeHomeMidterm.doc
sleep.txt
sleep.xls
 The final homework assignment has been posted.
Week 8:
 Homework 5 will be posted this week.
Week 7:
 Homework 4 has been posted.
Week 6:
 The midterm will be given this week on Tuesday.
Week 5:
 Continuation of Week 3 material. Discrete probability models.
Continuous probability models.
 Midterm 1 next week on Tuesday.
Week 4:
 Continuation of Week 3 material. Introduction to discrete random
variables.
 Quiz 1 next week on Tuesday.
Week 3:
 Homework 3 has been posted.
 See the Handout link for simulation program of Bayes' Theorem.
 The dates have been posted for Quiz I and Midterm II.
 For a good examples of Bayesian Analysis in Computer Science see
Linux Journal,
March 2003.
 Math vs. Spam: beyond Bayesian Filtering
 Power filtering with SpamBayes
Week 2:
 Computer issues:
 Make sure you can log into Blackboard (Bb). The HOWTO above gives
a description of how to log in. The link to Blackboard takes you to
the login window. From your first page in Bb you should have Stat.
3601, click on that and see if you get in. I will be using Bb for some
Announcements, online Discussion, maybe to turn in come homework through the
Digital Dropbox, and for the Gradebook. I have posted a Homework 1
grade for everyone to test if you can view your grades online. See if
you can view your grades. Let me know if you can't by sending me an
email.
 Make sure you can log into you Horizon email. The link is posted
above.
 The three new PseudoRandom Number handouts have been posted. Please
print the three Random Number handout for class on Thursday.
 Also, I have posted a handout on getting started with S called
Introduction to S (R). See the bottom of the Handouts page from the link
above.
 Computer lab examples:
handout2.doc
 Minitab: California Lottery.
CA lottery website Example of
histograms. Make a histogram for each number drawn, smallest to largest.
Describe the shape of each distribution. Compute the mean of the lottery
numbers for each drawing and plot a histogram. data file:
SUPER.mtw
 Question: What is the shape of the distribution of the sample mean?
 Minitab: Six Sigma. Example of sidebyside boxplots. data file:
SIXSIGMA.MTW
 Question: Do the samples the samples seem to have the same center
and spread over time?
Week 1:
 Homework 1 has been posted.
 Print out the 3 Handouts on Random Number Generation for next week.
 Computer lab examples: handout:
handout1.doc
 Minitab: Air Pollution. Example of Descriptive Statistics.
Mean and Median. Standard Deviation. 5number summary.
Boxplots. See Ch. 1, Section 1.4, page 13. data file:
pollution.MTW
 Question: Which cities had the worse pollution during the 1990's?
Give the relevant graphical and numerical evidence for you answer.
 Minitab: Gas Prices versus Oil Prices. Example of the
relationship between two quantitative variables. Scatterplots,
correlation, linear regression, and prediction. Do problem 9.6, page
485. data file: EX96.MTP
 Question: Does the price of gas depend on the price of oil per
barrel? If so, is it linear? What is the equation of the linear
regression? What is the prediction of gas price for oil price of
$20 per barrel?
 R: Flipping a fair coin. program:
coin.R
 Question: What happens to the relative frequency of heads as the
number of trails of the experiment increases?
 R: Rolling fair dice. program:
dice.R
 Question: What happens to accuracy of the simulated probability as
the number of the experiment increases?
Week 0:
 I have decided on the book for the course, it is Probability and Statistics for Engineers, by Scheaffer and
McClave. I chose this book because I think it has very good examples and
problems, also because it discusses the use of simulation.
