Friday, July 08, 2011

Introduction

The blogging technology gives us chance to share our thoughts and ideas to the world without the hassle. Many blogs provide commentary or news on a particular subject; others function as more personal online diaries. A typical blog combines text, images, and links to other blogs, Web pages, and other media related to its topic. The ability of readers to leave comments in an interactive format is an important part of many blogs. Most blogs are primarily textual, although some focus on art (art blog), photographs (photoblog), videos (video blogging), music (MP3 blog), and audio (podcasting). Microblogging is another type of blogging, featuring very short posts.

     This E-Portfolio is another way of using the technology in education. It gives us the way to communicate with the class after class hours. It is an innovation of written assignments that can be checked right away. Everybody can make the blog for a great purpose. Let’s enjoy the comfort of the blogging technology now!
I.  Objectives:
  • Records ongoing learning in Statistics and facilitates reflection and evaluation.
  • Creates enthusiasm for responsible public writing and communication.
  • Shares important statistical knowledge and ideas to other bloggers.
II. Scope of the blog
        The List of Content in Educ 213
    Chapter 1 Introduction to Statistics 
    Chapter 3 Measures of Central Location 
    Chapter 4 Measures of Variation 
    Chapter 5 Simple Correlation
    Chapter 6 Simple Regression 
    Chapter 9 Statistical Inference             
    Chapter11 T-Test of Significance
    Chapter12 ANOVA

    Chapter13 Factorial ANOVA
    Chapter14 The Chi-Square Test 

  III. My Blog OUTPUTS
            1. Powerpoint Presentation
            2. Variance and Coefficient of Variation
  IV. Multimedia 
       1. Videos Teaching Statistics
         a. Statistics: The Average
         f. Excel Statistics 34: MEAN, MEDIAN, MODE (Averages) 
       2. Games
          a. Mean, Median, Mode and Range
          b. Train Race
          c. Data Grapher
          d. Linear Regression 

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