1. EDPSY 511-001: Introduction to Educational Statistics

2. Syllabus Key points –Introductory course –Office hours Tuesdays 3:30 to 5:00 Thursdays 2:00 to 3:30 Or by appointment –Pre-requires or co-requires Edpsy 505

3. Syllabus Key points (cont.) –Assessment plan Three Exams (100 points each) –Tend to select items from end of the chapter »Multiple choice »Short answer »Calculations –One page of notes –Can redo missed items for half credit Five Homework Assignments (75 points each)

4. Syllabus Assessment (cont.) –No extra credit –No incompletes Except for extreme circumstances (e.g., illness, death of family member) A comment on grades –You earn them

5. Syllabus Professionalism –Pathfinder Honesty Integrity –Cheating, plagiarism, etc. will not be tolerated and will result in a referral to whoever is in charge of this place. Behavior –Class starts at 4:00 –Turn off cell phones –If you must leave early let me know –Be respectful of others

6. Syllabus Work Habits –Read –Due dates are non-negotiable –Attempt practice items at end of chapters If you struggle with the items see tutors ASAP. –Bring a calculator Follow class examples –Passive learning does not work Other course policies –Religious accommodations –Disabilities Inform and provide documentation

7. Who is here? In groups of three or four –Identify yourself and get to know one another Ask the following questions –What are your professional experiences? –What is your program of study? –What topics within your program interest you? –What is your favorite recreational activity? Be prepared to introduce one member of your group. Exchange email addresses and/or phone numbers –Contact if you miss class. –Bounce ideas –New friends –Misery loves company ;-)

8. How to study & learn statistics: Statistics is a Language Read the textbook Do the practice problems with each chapter (odd problems) Distributed Practice –Studying once a week does not work Use the tutors and my office hours Don’t get behind & don’t wait to say you don’t understand

9. How to study & learn statistics: This is not a Cookbook Course -- I want you to know why we do what we do even more than how we do what we do. You can always look up how; but errors in research are made at the "why" level, not the "how" level.

10. Working with your feelings & attitudes HIGH ANXIETY! –Try to put your math fears aside. –You have the basic math skills. Some people think the whole process is hogwash (Suspend your Disbelief!) I cannot promise scintillation or excitement; this will be intellectually taxing. Some people like my methods and some don't.

11. The Big Picture: Statistics in Context There are many different research processes Each has its own: –Philosophies of Inquiry –Methods of Inquiry –Purposes for doing research –Processes and “Rules” Statistics does not fit them all. Here is one process:

13. EDPSY 511: The Big Lessons Statistics is a language Statistics is a tool Statistics is reasoned argument Statistics and facts are not the same things

14. Chp. 1 Key points –Statistics is a process of collecting data in a scientific manner and making decisions based on these data. Personal experience vs. systematic empiricism –Personal experience if useful BUT »Subject to bias »Can be haphazard –Systematic empiricism »Systematic observation »Control of bias »Replicable

15. Fundamentals of Research Answering empirical questions –Observable by the senses. Publicly verifiable knowledge –Operational definitions –Direct replication Identical conditions –Systematic replication Similar conditions

16. Variables –Characteristics that takes on different values Achievement Age Condition –Independent variable (IV) Manipulated or Experimental –Condition Subject –Personality –Gender –Dependent variable (DV) The outcome of interest –Achievement –Drop-out status

17. Populations vs. Samples Population –The complete set of individuals Characteristics are called parameters Sample –A subset of the population Characteristics are called statistics. –In most cases we cannot study all the members of a population

19. Descriptive vs. Inferential Descriptive statistics –Summarize/organize a group of numbers from a research study Inferential statistics –Draw conclusions/make inferences that go beyond the numbers from a research study –Determine if a causal relationship exists between the IV and DV

20. Random Sampling vs. Random Assignment Simple random sampling –Each member of the population has an equal likelihood of being selected. Helps ensure that our sample will represent the population of interest. Random assignment –Assigning subjects to different conditions in a way that they have equal chance of being placed in either condition. Controls for confounding

21. Goals of Scientific Research Exploratory –What is out there? Descriptive –What does this group look like? Explanatory –Why and how are these constructs related? Evaluation –Does this program work? Prediction –Who will become depressed?

22. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and ex post facto designs. Quasi-experiments –Researcher manipulates IV True experiments –Must have random assignment. Why? –Researcher manipulates IV

23. A little on SPSS The assignments require hand calculations and SPSS practice –Typically I have you check your answers using SPSS –Do not buy SPSS –Do not leave the SPSS work for night before the due date. –You will need a TEC center account Do that after class today