Department of Statistics

California State University, Hayward 

Winter 2003

Stat 3601: Introductory Statistics for Scientists and Engineers

Course Description Homework Important Dates Statistics Software
Syllabus Handouts Stat Lab Times Open Statistics Online Texts
Blackboard HOWTO csuhbb.csuhayward.edu Horizon email Statistics Links

Week 9:

  • This Thursday there will be a take-home 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 take-home 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 Pseudo-Random 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 side-by-side 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.  5-number 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: EX9-6.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.