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EDPSY 511-001:

This syllabus provides an overview of the Introduction to Educational Statistics course. It includes information on key points, assessment methods, course policies, professionalism expectations, and homework assignments.

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EDPSY 511-001:

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  1. EDPSY 511-001: Introduction to Educational Statistics

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

  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 • Four 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 • Rule of thumb • Three hours of outside work for every credit hour

  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. Homework • The assignments require hand calculations and SPSS practice • The first assignment and tutorial are available online • 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

  8. 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. • Study groups • New friends • Misery loves company ;-)

  9. 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

  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 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:

  12. 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

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

  14. Variables • 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

  15. 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

  16. 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

  17. 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

  18. 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?

  19. 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

  20. Measurement • Is the assignment of numerals to objects. • Nominal • Examples: Gender, party affiliation, and place of birth • Ordinal • Examples: SES, Student rank, and Place in race • Interval • Examples: Test scores, personality and attitude scales. • Ratio • Examples: Weight, length, reaction time, and number of responses

  21. Categorical, Continuous and Discontinuous • Categorical (nominal) • Gender, party affiliation, etc. • Discontinuous • No intermediate values • Children, deaths, accidents, etc. • Continuous • Variable may assume an value • Age, weight, blood sugar, etc.

  22. Values • Exhaustive • Must be able to assign a value to all objects. • Mutually Exclusive • Each object can only be assigned one of a set of values. • A variable with only one value is not a variable. • It is a constant.

  23. Chapter 2: Statistical Notation • Nouns, Adjectives, Verbs and Adverbs. • Say what? • Here’s what you need to know • X • Xi = a specific observation • N • # of observations • ∑ • Sigma • Means to sum • Work from left to right • Perform operations in parentheses first • Exponentiation and square roots • Perform summing operations • Simplify numerator and divisor • Multiplication and division • Addition and subtraction

  24. Pop Quiz (non graded) • In groups of three or four • Perform the indicated operations. • What was that?

  25. Rounding Numbers • Textbook describes a somewhat complex rounding rule. • For this class, truncate at the thousandths place. • e.g. 3.45678  3.456

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