Department of Statistics

California State University, East Bay

Fall 2007

MGMT 6110: Business and Economic Forecasting

Course Description Homework Important Dates Software
Syllabus Handouts   Links
Blackboard     

Week 10:

  • The solution to Homework 5, 7 and Homework 8 have been posted on Blackboard.
  • This week we will go over how to use ForecastX to identify an ARIMA model and forecast using the model.
  • We will also discuss some of the ideas in Ch. 8 and Ch. 9.  betterforecasting.doc
  • For the final you should review all of the material presented in the class, but the questions on the final will focus on the second half of the class.

Week 9:

  • This week we will discuss the topic of ARIMA modeling. arimna.doc arima1.doc
  • This week we will introduce the use of SPSS.
  • Homework 8 has been posted.
  • Next week we will review for the final.  Please do a review of the material since the midterm and bring questions to class next week. 
  • There will be a short in class quiz today for preparation for the final.

Week 8:

  • This week we will discuss the Time Series Decomposition.
  • This week we will introduce the use of Minitab.
  • Homework 7 has been posted.
  • Homework 5 and 6 are due this week.  If you have not submitted it please do this week.
  • See the Links link above for a few suggested website with time series data.  If anyone has an suggested links to find data please forward the links to me.  Thanks.

Week 7:

  • This week we will cover the topic of Multiple Linear Regression.  In the use of multiple linear regression a correlation matrix should be computed to check for multicollinearity.  The DW test should be checked to see if there is serial correlation in the residuals.  And the adj-R square should be used as the criteria for model selection, or AIC, or BIC.
  • The class project has been assigned.
  • An interesting article was written a few years ago about the problems with the "art" of using Multiple Linear Regression.
  • Many of the examples in the book relate to home values.  Some current companies that collect and analyze data are HouseValues.com, Zillow.com, and Zaio.com  What are the main differences between these companies in their approaches to the appraisal of homes?  What other companies are there that do this type of valuation?
  • Homework 6 has been posted.  Since we have only talked about Multiple Linear Regression, I have postponed the hw for the next chapter until next week.  You should complete the Multiple Linear Regression homework and we will discuss it next week.

Week 6:

  • This week the midterm will be given, the exam will last about 2 hours.
  • The class Project will be assigned next week.
  • Homework 5 has been posted and will be discussed in class next week.

Week 5:

  • This week we reviewed the ideas of hypotheses testing and the ideas of linear regression. 
  • Today we will be discussing correlation and multiple linear regression.
  • Quiz 1 will be given and gone over as preparation for the midterm next week.
  • I have posted the solutions for hw3 and hw4.

Week 4:

  • This week we will cover the topic of Simple Linear Regression.  The most important thing to do is to plot the data before you try to fit a line to data.
  • During the Week 5 class we will review for the Midterm which will be given Week 6.  Next week we will review the material that has been covered in class, go over homework questions, and we will discuss the topics to be covered on the in class midterm exam.
  • During the Week 5 class we will discuss the class project.
  • Please turn in Homework 3 this week in Blackboard in the Digital Dropbox.
  • Homework 4 has been posted.
  • The solution to Homework 1 and 2 are available on Blackboard under the Course Materials.  And the solution to Homework 3 will be posted this weekend.

Week 3:

  • This week we will cover various smoothing methods including the Moving Average, Simple Exponential Smoothing, Holt's Exponential Smoothing, Winter's Exponential Smoothing, ADRES Exponential Smoothing, and Growth Curve Fitting.
  • Please turn in Homework 2 this week in Blackboard in the Digital Dropbox.
  • Homework 3 has been posted.
  • Check out this forecasting competition from Netflix.  Netflix Prize  Note the accuracy calculation used on the leaderboard.

 

  • How to name your homework files to turn in.  When preparing your homework file for the class make sure that you save you file with an acceptable file name.  The convention is, for example for hw1,   lastname_firstname_hw1.doc
  • If you did not receive credit in Blackboard in the Gradebook please resubmit your hw using the acceptable file name.

Week 2:

  • This week we will finish going over the Naive Forecasting methods from Chapter 1.  We will cover the ideas of the Forecasting Process, the concepts of Trend, Seasonality, and Cyclical data patterns from Chapter 2.  We will also introduce the idea of Autocorrelation.  Autocorrelation is the concept of correlation within a time series.
  • Please turn in Blackboard in the Digital Dropbox by Friday.
  • Homework 2 has been posted.

Week 1:

  • This week we will introduce the ideas of Forecasting.
  • Homework 1 has been posted.
  • Please turn in Homework 1 using Blackboard in the digital dropbox.
  • How to name your homework files to turn in.  When preparing your homework file for the class make sure that you save you file with an acceptable file name.  The convention is, for example for hw1,   lastname_firstname_hw1.doc

Week 0: