Psychology 200
Psychology 201
Instructor:
Measurement and Data Analysis in Psychology
Measurement and Data Analysis Lab
Julie Neiworth [email: jneiwort@carleton.edu]
Office of Instructor: Olin 113, x4372
Office Hours: Mondays, 11-12:30 pm; Thursdays, 3:00 – 4:30 pm
Also, last 30 minutes of every lab meeting! (T-TH)
Text
We will use Aron, Aron & Coups (2009) Statistics for Psychology, Fifth Edition .
Course meets
2a, MW 9:50 – 11:00; F: 9:40 – 10:40 am. in Olin 102-104
Lab (Psy 201) meets: 2,3c T-TH and 4,5c T-TH in Olin 102-104
PLEASE ATTEND YOUR REGISTERED LAB PERIOD ONLY.
WE DON’T HAVE ENOUGH COMPUTERS TO TREAT THIS FLEXIBLY.
Background and Purpose of Course
The course considers the role of measurement and data analysis focused on psychology. To understand data, you need to understand its distribution, and the implications of its distribution on any questions you want to ask. To test an idea using data, you have to select wisely. The tests also make some assumptions about the distribution of the data and what is appropriate to do.
Thus, various forms of measurement and standards for the evaluation of measures are explored in this course. You will learn how to summarize, organize, and evaluate data using a variety of techniques that are applicable to research in psychology. Among the analyses are tests of means, various forms of analysis of variance, correlation and regression, planned and post-hoc comparisons, as well as various non-parametric tests. Research design is also explored.
Why learn statistics, other than to fulfill a requirement?
Here are good reasons for doing so.
1) Understanding statistics is crucial to being able to read psychology research articles.
2) Understanding statistics is crucial to doing research yourself.
3) Understanding statistics helps to develop your analytic and critical thinking.
Of course, experimental design issues are vastly important to understanding which statistical test to use. Thus, we will start the course reviewing these concepts, including simple ideas such as independent and dependent variables, and more complex ideas such as random selection, matched group designs, repeated measures designs, and so forth. It is important to have a common terminology to discuss the story problems you will use for practicing stats tests, and to select the appropriate statistical tests to conduct in exams, homeworks, and in your future experimentation.
Statistical Packages Used
Excel, and Excel with StatPlus
SPSS 19, 20, or 21, whichever you can access!
We will also calculate a lot of stuff by hand. Calculators are essential, but nothing fancy. You need to square stuff, and find the square root, and do normal algebraic functions.
Flexibility in Using Formulas, Stats Packages, Calculators, Software for Math
I am sometimes asked by students if they can use a different mathematical package because it is something they are used to. I think it is important to be flexible in doing calculations and using software – you don’t want to absolutely need any particular package to get something done.

However, it will be important to you in psychology (in psychology classes, in reading articles, in comps, etc) to be able to use SPSS as a statistical package, so I will ask you to use it consistently in your homework. If you also want to run the stats on another package, that’s fine, but I need to see you demonstrate competence on SPSS. So don’t fight the need for that.
My teaching focuses on definitional formulas for you to use to calculate statistics. These types of formulas emphasize the meaning of the statistics you are doing, and they remind you of how you are manipulating data or what you are constructing as you use them.
Definitional formulas are typically not the easiest formulas to put into a calculator, to mathematica, etc. though. There are formulas called computational formulas, which were invented mostly about 40 years ago when people used calculators pretty exclusively to run statistics. They are mathematical shortcuts to getting an answer, but conceptually they are empty.
For example, there is a definitional formula I will have you use to calculate variance wherein you take each data point and subtract it from the mean of the data, square the difference, sum those all up, and divide by N, the number of data points. This goes a little slow (unless you use EXCEL, which I will show you how to do), and requires subtracting each data point from the mean individually. The formula reminds you of what you are measuring, the differences between the mean and the individual data, and you get a real sense of what the variance is by doing this.
Alternatively, there is a computational formula that involves you squaring all the data, summing those squares, and subtracting that total from the sum of all the data that is then squared (and then dividing by N). You get the same answer but it does not emphasize the differences you are collecting and the squaring of those. Not since L B Johnson was president have these formulas been necessary (back when researchers calculated by hand stats from large data sets), and even then, they were poor teaching tools. So you’ll run into a computational formula periodically but we won’t focus on those in class.
Assignments
There will be weekly homework assignments, a midterm exam and a final exam. In addition, there is one short paper assignment, in which you design an experiment with the express purpose of picking appropriate statistical analyses to use with the data you would collect. Each exam covers only the material just before it, so there will be no cumulative exam over the entire term.
Grading
Lecture Grade (Psy 200):
• Two exams : each worth 30% of your lecture grade. (Wed Oct 15 and Wed Nov 19)
• Paper , including preliminary construction, on experimental design and stats analysis:
30% of your lecture grade. (due Saturday, Nov 22)
• Participation makes up an additional 10% of your lecture grade.
Laboratory Grade (Psy 201):
• Homeworks : approximately 9 assignments, worth 10% each, make up your lab grade.
• Participation also makes up 10% of that grade.
Penalties
The course and lab go rather quickly, and it is important to stay current with homeworks. The grading of the homeworks is also a very onerous task, especially if I want to give you feedback about what you are dong wrong, or how you are doing generally. Thus, I need you to hand in homeworks on time. The homeworks will be penalized for lateness, and after 2 weeks of the deadline for each, they will no longer be accepted.

Academic Honesty
I don’t want to prohibit you from working in groups to work out the homework problems. Working in groups can be a good learning experience, and can make the work fun. However, you should not copy someone else’s homework, or their answers. To assure me that you are not doing that, I will be asking you to show your work on various homework problems. This means that you need to write down all steps that brought you to the answer. Having the correct answer, but no steps to show me how you got there will lead to LESS POINTS for the answer than showing both.

DATE DAY READING ASSIGNMENT
9/15 Monday Numbers, Tables, Graphs
AAC: Ch. 1, Displaying the Order in a Group of Numbers Using Tables and Graphs
Homework # 1 assigned, due Monday, Sept 22 (see Psy 201 assignments for all homeworks).
9/17 Wednesday Experimental Design in Psychology
Web chapter 1: design issues. Get this from MOODLE or from my website if you are not yet registered.
Overview of the logic and language of psychological research.
9/19 Friday
AAC: Ch 2, Central Tendency & Variability
Central Tendency
9/22 Monday Z-Scores, the Normal Curve,
Sample vs Population, and
Probability
AAC: Ch. 3, Some Key Ingredients for Inferential Statistics
9/24 Wednesday Continuation of Z-scores, and other ingredients
9/26 Friday Intro to Hypothesis Testing
AAC: Ch. 4, Introduction to Hypothesis Testing
Experimental Design Worksheet given today.
9/29 Monday Hypothesis Testing: Z-scores
AAC: Ch. 5, Hypothesis Testing with Means of Samples
10/01 Wednesday Hypothesis Testing Wrap-Up
10/03 Friday
AAC: Ch 11, Correlation
Correlations and Z-scores: a Connection
10/06 Monday
AAC: Ch. 12, Prediction
10/08
10/10
Wednesday
Friday
Regression
Correlation and Regression: Wrap-up
Revisit Design Issues and
Working Group – Paper ideas
Possible review of sampling and survey construction, if we have time!
10/13 Monday
Exam 1 Study Guide in pdf form.
Review for first EXAM I: all topics above
10/15 Wednesday EXAM 1: tables & graphs, experimental design, central tendencies, Z-scores, hypothesis testing, correlation, regression

DATE DAY READING ASSIGNMENT
10/17 Friday Class Canceled. Relax!
10/20 Monday MIDTERM BREAK – TAKE A BREAK!
10/22 Wednesday t-Tests: They’re fun!
AAC: Ch. 7, Introduction to t Tests: Single sample and dependent means.
10/24 Friday t Test for independent means
AAC: Ch. 8, the t-Test for Independent Means
10/27 Monday Planning for group discussions; papers.
Demonstration of ANOVA and t test similarity
Web chapter 2: Applying Stats to Your Own Project (see MOODLE to get this)
10/29 Wednesday Basics: ANOVA.
AAC: Ch. 9, Introduction to ANOVA, focus on the Structural Model
Formula Handout Given: t-tests and simple ANOVA’s.
10/31 Friday
Scary statistics on Halloween!
Paper work: Groups – Open meeting.
FACTORIAL ANOVA 11/03 Monday
AAC: Ch. 10, Factorial ANOVA
11/05
11/07
Finish up Ch. 9-10.
Wednesday
Friday
Interpretation of Interaction effects.
Factorial ANOVA continued. in class working session. (instructor absent)
11/10 Monday Repeated Measures ANOVA and Mixed Models
Web chapter 3: repeated measures ANOVA (see MOODLE to get this).
11/12 Wednesday
AAC: Ch. 13, Chi-Square Tests
AAC: Ch. 14, Nonparametric Tests.
Begin Nonparametrics.
Formula Sheet: and HELP sheet: ANOVA and nonparametrics
11/14 Friday Review of Nonparametrics.
Exam 2 Study Guide given here.
11/17 Monday General Review for Exam 2.
11/19 Wednesday EXAM 2: t Tests, ANOVA (fixed, repeated measures, mixed), posthoc tests, nonparametric tests.
Note that the exams will contain problems for which you will need to use the computers in the
Mac Lab. Therefore, there will be no other options for self-scheduling. Extended times may be offered for people who have demonstrated through the student support services such a need, but a special exam time may need to be planned. I will provide extra time by starting people early on the same day (1a) and letting them continue through 2a.

Paper due: Saturday, Nov 22nd, by 5:00 pm. A box will be made available outside the psych dept office for you to drop it off or you can email it directly to her before the deadline. Julie will pick paper copies up around 6:00 pm on Saturday.