Lab Assignments

Lab assignments are due as specified in the assignment. Labs due at the beginning of a class period will not be accepted 5 minutes after the class has started.

Lab 8: ANOVA (Nov 29)

In this lab we will be using everything we have learned in our text and applying that information to understanding the t-statistic.

File needed:
goggles.sav

Submit Lab8.doc via the "Drop Box" on Blackboard.
Print out your Lab8.doc, sign your honor code and give it to me by the end of class.
* Make sure you sign the honor code on your printed lab work for your work to be graded.

Lab 7: T-tests (Nov 8)

In this lab we will be using everything we have learned in our text and applying that information to understanding the t-statistic.

Files needed:
SpiderBG.SAV and SpiderRM.SAV

Submit Lab7.doc via the "Drop Box" on Blackboard.
Print out your Lab7.doc and updated lab7.SAV and give it to me by the end of class.
* Make sure you sign the honor code on your printed lab work for your work to be graded.

Lab 6: Repeated Measures Data (Oct 25)

In this lab we will be using everything we have learned in our text and applying that information to understanding the t-statistic.

Files needed:
SpiderBG.SAV and SpiderRM.SAV

Submit Lab6.doc via the "Drop Box" on Blackboard.
Print out your Lab6.doc and updated SpiderRM.SAV and give it to me by the end of class.
* Make sure you sign the honor code on your printed lab work for your work to be graded.

Lab 5: Midterm (Oct 11)

This lab will only take place during our scheduled exam time. You may bring one sheet of notes with you to use during the lab.

Pick up a sheet of instructions from me and download SPSSExam.sav to get started.
Please let me know if you have any questions. * Make sure you sign the honor code on your submitted work for your work to be graded.

Lab 4: Correlation & Scatterplots (Sept 27)

In this lab we will be using everything we have learned in our text and applying that information to understanding correlations and scatterplots.

File needed:
ExamAnxiety.sav

Submit Lab4.doc via the "Drop Box" on Blackboard.
Print out your Lab4.doc and give it to me by the end of class.
* Make sure you sign the honor code in our lab book for your work to be graded.

Lab 3: Glastonbury Revisited (Sept 27)

In this lab we will be using everything we have learned from chapters 4 and 5 in the text and applying that information to understand a large dataset from a Glastonbury Festival.

File needed:
GlastonburyFestival.sav

Submit Lab3.doc via the "Drop Box" on Blackboard.
Print out your Lab3.doc and give it to me by the end of class.
* Make sure you sign the honor code in our lab book for your work to be graded.

Lab 2: Exploring Glastonbury (Sept 13)

In this lab we will be using everything we have learned from chapters 1-3 in the text and applying that information to understand a large dataset from a Glastonbury Festival.

File needed:
GlastonburyFestival.sav

Submit Lab2.doc via the "Drop Box" on Blackboard.
* Make sure you sign the honor code in our lab book for your work to be graded.

Lab 1: Introduction to SPSS (Sept 6)

You have already completed a class survey to obtain data for use in our course. We are now going to use that data to learn about SPSS.

The following assignment will get you familiar with some of the basic properties of SPSS.

Files needed:
Data for section 3.
Additional_survey_data_07.sav for section 4.

Submit the following 2 files via the "Drop Box" on Blackboard: by the start of next class

You will also need to complete Part 2 of the Lab Assignment by the start of next class.

* Make sure you sign the honor code in our lab book for your work to be graded.

Lab 0: Review of Mathematics (Aug 30)

This lab will concentrate on reviewing algebraic properties that you will be using for this course. We will start with a review of concepts and then you will break into pairs to work on the following assignments.

Due by the end of class:

Due by the start of the next Lab on Sept 6, #1-39 on page 696, "Basic Mathematics Review."

Note: for both assignments, make sure you show your work to receive full credit.