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Week 5 ETEC 668 Quantitative Research in Educational Technology

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##### Week 5 ETEC 668 Quantitative Research in Educational Technology

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**Week 5 ETEC 668 Quantitative Research in Educational**Technology Dr. Seungoh Paek February 12, 2014**Tonight’s Agenda**• Continuing SPSS • Introduction to PSPP • Introduction to RStudio • Introduction to Probability • Group Discussion for Research Paper**Sigma Freud & Descriptive Statistics**A Picture is Really Worth a Thousand Words**Histograms with Polygon**Hand Drawn Histogram**Cool Ways to Chart Data**• Line Chart**Cool Ways to Chart Data**• Pie Chart**Using the Computer to Illustrate Data**• Creating Histogram Graphs**Using the Computer to Illustrate Data**• Creating Bar Graphs**Using the Computer to Illustrate Data**• Creating Line Graphs**Using the Computer to Illustrate Data**• Creating Pie Graphs**PSPP**Download PSPP - For Mac, click here. For Window, click here.**R**• R is a free software environment for statistical computing and graphics.**RStudio**• RStudio is a free and open source integrated development environment (IDE) for R, a programming language for statistical computing and graphics.**Probability, Samples, Bell Curve, zScores, Hypotheses,**Hypothesis Testing, & significance Chapter 7 & Chapter 8**Why Probability?**• Describe and predict what we don’t know from current data • Basis for the Degree of confidence a Hypothesis is “true” • statistical significance**Examples**• Flip a coin • 2 possible outcomes • Heads or Tails • 50% chance each • Role a Die • 6 possible outcomes • 1 – 2 – 3 – 4 – 5 – 6 • 16.6% chance each • Flip 2 coins • How many possible outcomes? • What % chance for each?**Examples**• Flip 2 coins • 4 possible outcomes • 25% chance each**Definitions**• Population • The large group to which you would like to generalize your findings • Sample • The smaller, representative group of the population used for research.**Characteristics of a sample**• Needs to be representative • Truly random = representative = unbiased • Sampling error – • how well the sample represents the population • Size matters – • larger sample = more representative**Mathematical Symbols**• Mean • Population = μ • Sample = X • Standard Deviation • Population = σ • Sample = SD • Variance • Population = σ2 • Sample = SD2 • Number of Cases • Population = N • Sample = n**About Normal Curve**• Almost all scores fall between -3 and +3 SD from mean • 99.74% • Specific percentages between points on x-axis • 2 or more normal curves can be compared**The z Score**• The number of standard deviations from the mean • Negative scores are below (left of) the mean • Positive scores are above (right of) the mean**The z Score**• Standard Score • Allows you to compare apples and oranges • The probability of a score occurring =**What is a Hypothesis?**• An “educated guess” • Direct extension of the question • Translates problem or research question into a testable form • Two types • Null Hypothesis • Research Hypothesis**A Good Hypothesis**• Declarative statement • Expected relationship between variables • Reflection of theory/literature • Brief, to the point • Testable**Why a Null Hypothesis?**No amount of experimentation can ever prove me right; a single experiment can prove me wrong. ~Albert Einstein**The Null Hypothesis**• Statement of no relationship • Two things are equal H0 : μA = μB • Refers to Population • Indirectly tested**The Research Hypothesis**• Definite Statement • Relationship exists between variables • Two types • Nondirectional - H1 : XA ≠ XB • Directional - H1 : X1 > X2 • Refers to sample • Directly tested**Hypothesis Testing**• All events have a probability associated with them • p = your guess of chance p < .05 • .05 or 5% in Education and Psychology • 5% likelihood of results occurring by chance alone**Error types**• Type I • Reject H0 when you should not • Type II • Fail to reject H0 when you should**Statistical**• Based on probability • Research was technically successful • H0 was rejected • P value • Education p < .05 = 5% chance • Medical p < .01 or .001 = 1% or .1% chance**Practical**• Does it mean anything to the population? • Is that new treatment worth the cost? • Are my students really doing that much better?**Stating the Research Question**February 12, 2014