Introduction to Educational Statistics EDPSY 511-001: Introduction to Educational Statistics

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 Other sections W 1 - 3:30 T 12:30 - 3:00 The textbook and I might differ on some things, but it should be helpful. Practice Problems : Fluency Distributed Practice Fluency Compensates for once per week contact

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)

Syllabus Assessment (cont.) A comment on grades 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

Syllabus Professionalism Behavior Pathfinder Class starts at 4:00 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

Syllabus Work Habits Other course policies 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

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

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 ;-)

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 Other sections W 1 - 3:30 T 12:30 - 3:00 The textbook and I might differ on some things, but it should be helpful. Practice Problems : Fluency Distributed Practice Fluency Compensates for once per week contact

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.

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:

Notice where stats fits into this ONE process What stats can and cannot do to address a research question.

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

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

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

Populations vs. Samples 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

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

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

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?

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?

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

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.

Values Exhaustive Mutually Exclusive 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.

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

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

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