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Picture

Assessment & Evaluation

 Inferential Statistics Basic Concepts, and
​Evaluation Models

​0   1   2   3   4   5   6   7   8 
IST:622 Term 4

Week 3 Objectives

  1. Identify different samples and determining which statistical procedure to use for data analysis
  2. Interpret meaning of scores, measurement and scientific inquiry
  3. Develop an appropriate evaluation plan for a given project
  4. Videos-
    1. Independent sample t-test
    2. MAC t-test 2 sample for means unequal
    3. MAC t-test sample paired difference
  5. Reading Assignments
    1. ​Russ-Eft & Preskill:  Chap 5
    2. Pedhazur & Schmelkin Article
    3. Paired Sample t-test example
    4. Independent sample t-test example
    5. Lecture- Inferential Statistics (Week 3) (See accordion below)
​
Assignment 
Follow instructions from Data File and Lab Instruction
Practice Questions-
  1. SAT scores of 100 girls compared to SAT scores of 100 boys in a private school in California. Are these dependent or independent samples? What is the degree of freedom? (Answer: These are independent samples because there is no indication of matching, pairing, or repeated measure. Therefore, the df=100+100-2=198)
  2. Twenty-five first graders' mid-term and end-of-term math exam scores are compared. Dependent or independent sample? What is the degree of freedom? (Answer: These are dependent samples because each student's mid-term score is compared to his/her end-of-term score. This is an example of repeated measure. Therefore, the df=25-1=24)
note:  To run a t-test, it is important to know whether the samples are dependent or independent from each other since there are multiple different test options for running a t-test based on what kind of samples you have.
Lecture Notes
Inferential Statistics (Week 3)
Four Ways to Obtain Samples
  1. Simple random sampling
    1. Each member of the population has an equal and independent chance of being chosen
    2. The sample should be very representative of the population
  2. Systematic sampling
    1. The term nth stands for a number between 0 and the size of the sample that you want to select
  3. Stratified Sampling
    1. Select a sample that is representative of the population
    2. Use this method when the individuals in the population are not equal to...
  4. Convenience Sampling
    1. Captive or easily sampled population
    2. Not random
    3. Weak representativeness

t-Test- To be able to run a t-test you will need to obtain the following data first
  1. value of the means of each sample
  2. value of the standard deviations
  3. number of cases in each group

Independent vs. dependent sample-
  1. Example of independent samples: randomly choose from two populations, use random selection procedure to assign elements from one population to two samples, cases in the two groups are not related or matched, etc. Basically, obtained scores in one group are independent or not related to the scores in the other group.
  2. Example of dependent samples: repeated measures using the same subjects, subject matching, selecting pairs of business partners, etc. Comparing pre-test and post-test scores after an instructional intervention to a group of students would need dependent sample t-test since it meets the definition of repeated measure

How Inference Works
t-test for dependent samples-
Is a process for determining if there is a statistically significant difference between the means of two dependent samples. (slide 19)  For additional information review examples at: http://www.uwsp.edu/PSYCH/stat/11/hyptest2s.htm

Summary-  Inferential statistics tell us how much confidence we can have when we generalize from a sample to a population. In choosing the proper inferential statistic, an analyst must consider the size and number of samples drawn and the nature of the measures taken. 
Picture
Su, B. (2016).
Picture
Su, B. (2016).

IST:622  Assessment & Evaluation
Professor Bude Su, Ph.D.

Payne e-Portfolio
Dana Payne

Testing the chat box widget from chatango.com
Titled ​Q&A
.

​​E-mail dpayne@csumb.edu

  • Home
    • Annotated Bibliography
    • Applications
    • Professional Organizations
  • Term 1A & 1B
    • T1. A. 501 Technology Workshop >
      • Set Up, ePortfolio
      • Audio / Video
      • Instructional Video
      • Interactive Video and Multimedia
      • Learning Management Systems
      • Tools- Research/ Searching
      • Webology
      • 501 Assignments
    • T1. A. 524 Instructional Technology >
      • Intro, ISD, Controversies
      • Behaviorism / Cognitivism
      • Constructivism
      • Performance/ Change Management
      • Views, Issues, Lecternnosaurus
      • Trends, Issues, Ethics
      • Current Issues/ New Directions
      • Wrap Up
      • 524 Assignments
    • T1. B. 522 Instructional Design >
      • Introduction, ISD Model
      • Needs Analysis 1
      • Task Analysis 2
      • Analysis / Design 1
      • Design 2
      • Asynchronous Seminar
      • Implementation / Evaluation 2
      • 522 Assignments
    • T1. B. 511 Writing Workshop >
      • APA / In-Text Citations
      • Evaluation APA/ Reference
      • Conjunction
      • Apostrophe
      • Annoted Bibliography
      • Implementation / Evaluation 2
      • Guides
      • Workshop Reflection
      • 511 Assignments
  • Term 2
    • T2. 520 Learning Theories >
      • Learning Theory
      • The Brain, Skinner
      • Robert Gagné - Information
      • Social Constructivism/ Metacognition
      • Inuit Holistic Lifelong L.M.
      • Albert Bandura
      • Motivation in Learning
      • Putting It All Together
      • 520 Assignments
    • T2. 531 Multimedia Tools >
      • Basics
      • Audio
      • Scripting, Editing, Titles
      • Framing, shots, and Movements
      • Preparation, Lighting, and Interviews
      • Theory and Copyright
      • Final Instructional Video
      • 531 Assignments
  • Term 3
    • T3. 526 Interactive Multimedia Instruction >
      • Authoring Software
      • Try it/ Guide me
      • Test me
      • Drag and Drop
      • Final Projects
      • Tin Can
      • Project Simulation
      • Audio / Images
  • Term 4
    • T4. 622 Assessment/ Evaluation >
      • Evaluation
      • Inferential Statistics and Evaluation Models
      • T-Test / Meaning of Scores
      • Data Collection Methods
      • Usability Test / Performance Assessment
      • Evaluation Data
      • Ethics, Bias, and Effective Evaluation
      • Data Analytics and Wrapping Up
  • Term 5
    • T5. 541 Multimedia Tools II: Interactive Media >
      • HTML5 / Common Tags
      • CSS
      • jQuery UI Lab 2
      • jQuery UI Lab 3
      • Storyboard/ lab 4
      • Local Storage Lab 5
      • Image Map/ Hot Spot
      • Final Project Description
      • 541 Assignments
      • checking_fluid_levels
    • T4. 626 Advanced Instructional Design >
      • 1 ISD Models, Team Projects
      • 2 Analysis 1, Needs Assessment
      • 3 Task Analysis, Content Types
      • 4 Assessments/ Testing
      • 5 Course Design, Lesson Design
      • 6 Development, Adding Activites
      • 7 Formative Evaluation
      • 8 Final Product
      • 626 Assignments
  • chat room