EDUC 216 E-portfolio of BaronClare: 2011

Wednesday, May 18, 2011

Introduction

E-Portfolio is a collection of electronic evidence assembled and managed by a user and it is very valuable to us, students of masteral.
It include inputted text, output or reports, images, powerpoint and it can be used for multiple purposes.
Students in Masteral will be using this innovative menu to increased activity in the creation of E-portfolio for a variety of activity in EDUC 216( Statistics as Applied in Education).

II. Table of Contents of My E-Portfolio

Chapter 1 Introduction to Statistics
     Chapter 2 Variables : The Subject Matter for Statistics & Research
   Chapter 3 Measures of Central Location
   Chapter 4 Measures of Variation
     Chapter 5 Simple Correlation
     Chapter 6 Simple Regression
     Chapter 7 The Normal Probability Distribution
     Chapter 8 Statistical Estimation & Sampling Theory
   Chapter 9 Statistical Inference

Chapter10 Z-Test of One Sample Means

Chapter11 T-Test of Significance

Chapter12 ANOVA

Chapter13 Factorial ANOVA

Chapter14 The Chi-Square Test

Chapter15 Computer Statistical Applications using MS Excel

III. E-Portfolio Research Sample

1. Powerpoint Presentations
   2. Video for Demo Teaching
   3. Resources / Links
   4. Multimedia
   5. Games

IV. A. Higher Order Thinking Skills (HOTS) B. Multiple Intelligences (MI)

1. Innertoob 1.Grazr

2. Classblogmeister 2. Widget Finding

3. Twitter 3. Animoto

4. Classtool.net 4. LibriVox

5. Wikis 5. Evoca

6. Flickr 6. Elluminate

7. Meebo Me 7. Forums

V. Related Statistical Videos

1. Correlation: PASW (SPSS) Statistics v.17 video

2. Normal Probability

3. Standard Error in Linear Regression

4. ANOVA in EXCEL

5. Calculating Z-Scores

VI. Achievements in this Subject
1. My presentation
2. Output (handout)

Data Analysis and Interpretation

The Last reporter was Renante Cerna.His topic focus the over all interpretation of data.He presented lots of examples and data to be analyzed and interpreted.
He felt nervous at first but as he go on to his report he started to become energetic and very enthusiastic in explaining the lesson.I congratulate him that he delivered his lesson in a very good way and keep it up sir!

Data Analysis and Interpretation

One Way Analysis of Variance

Just like me, Sheila Ancino is not good also in making powerpoint, but in amazement she made it very well.She discussed about ANOVA-Analysis of Variance, its characteristics, advantages, and the process of Solving One-Factor Anova. This topic is a little bit hard to explain but sheila managed to deliver it and explain it well to her classmates.

ANOVA

Tuesday, May 17, 2011

Estimation of Population Means

Lesson No. 9:

The next presenter was Marites B. Agustin, her report is about on the Estimation of Population Means ,its confidence Level and Interval ,and hypothesis testing. On this lesson, she taught us how to make hypothesis and test it with the given confidence interval and levels. Her lesson is more on describing and understanding about the statistical Inference, but it helps us to understand better as we go along to our lesson in Statistics. I appreciated Ma’am Marites for doing her presentation in a brief and clearer way that we able to relate ourselves in the lesson.

Statistical Estimation and Sampling Theory

Lesson No. 8:

Marmaee C. Pilapilwas the fifth presenter. Her Lesson focus on Statistical Estimation and Sampling Theory. This lesson are useful especially in starting our research study. She presented her topic very well, her presentation is very nice and deliberate the lesson with all her knowledge. And I think her lesson has a big part in our research study soon by getting the right procedure or sampling theory for our research. She made her lesson in a simple way but easy to understand though her topic involved much description of samples, population and sampling theory with their example data.

Statistical Estimation and Sampling Theory

Normal Probability Distribution

Lesson 7. I was assigned also to report and my topic was the Normal Probability Distribution.

With the help of PowerPoint, I showed to my classmate the examples of Normal Distribution, its characteristics, the areas under normal distribution and the application of the normal curve.

I included also the Divergence from normality includes the Kurtosis and Skewness

Normal Probability Distribution

Simple Linear Regression

Lesson 6. In statistics, we have different ways on how to solve the problem. Just like to our third reporter, Mrs. Rosemarie F. Delos Reyes, she used two types of teaching method: the traditional and the modern teaching method. Fortunately, she really captured our attention by doing the activities manually and because of that we really understand her lesson. Even though she is not really good in computer using the PowerPoint but the effort was there and she discussed the Simple Linear Regression successfully.

We learned also from this topic on how to construct Scatter Diagram, to solve the linear regression equation and determining the standard error of estimate.

She showed to us the formula of getting the Linear Regression through manually, the distance of the Y from Y the corresponding ordinate of the regression line. This can be well understood by the standard error of estimation formula given.

Simple Regression

The Measures of Variability

Lesson 4. As we continue to our lesson, the topic becomes harder and more formula to be memorized. The Measures of Variability was reported by Mr.Melvin Calixton with all his knowledge he delivered it very well. He has a 95% confidence that he will deliberate the lesson successfully and he did it.

Measures of Variability are a single value that is used to describe the spread out of the scores in a distribution that is above or below the measures of Central Tendency. There are commonly used measure of variability, the range, the quartile deviation and the standard deviation.

The measures of variability are two kinds: 1.) Absolute Variability 2.) Relative Variability.

Absolute Variability are Range, Quartile Deviation, Average Deviation, Variance and Standard deviation. Under the Relative Variability are coefficient of variation, Coefficient of Quartile Deviation and Coefficient of Mean Deviation.

Different ways to measure variable was introduced to us by using the different formula. All of these topics can be easily solved by using and with the help of the Microsoft Excel. We are also taught on how to get its answer by dragging the mouse, by choosing the option and by clicking it then the answer were there automatically.

Although the topic was so hard because there were so many formulas to be memorized but it’s a big help to us, especially in our field work like solving the problem data whether it is grouped data or ungrouped data by getting its midpoint, frequency, its standard deviation through formula and with the help of Microsoft Excel.

Partly, multimedia contributed a big part of this subject matter.

Measures of Variability: https://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BxdEwwm0X26CYTk0Mjk0MDUtMWNiMi00NGE1LTkyZTAtNTU5MWVkMzUzZGMy&hl=en

“Measures of Central Location"

Lesson No. 3. Our first reporter was Mr. Richard Agapay, he discussed about “Measures of Central Location and the subtitle are: Mean, Median, Mode, Weighted Mean, Grand Mean. Point Measures: Measures of Central Tendency for Nominal and Ordinal Data, Percentile as a Measure of Location (group and Ungroup), Comparison of three Measure of Central Tendency.

The reporter delivered his topic very well. He has a lot of examples wherein we can easily understand his lesson. His presentation was very artistic and entertaining to view with.

I really don’t love mathematics specially statistics because it makes my brain drain but in this subject I need and I should learn to love mathematics because it played a big part in our daily life specially in our field of education like by doing our grades and getting their average, mean ,median, and mode.

According to Fruchter (1973)- average , whether it be a mean, median or mode, serves two important purposes.

FIRST- It is a shorthand description of a mass of quantitative data obtained from a sample.

- It is more meaningful and economical to let one number stand for a group than to try to note and remember all the particulars.

- An average is, therefore, description of a sample obtained at a particular time in a particular way.

SECOND- Describes indirectly, but with some accuracy, the population from which the sample was drawn.

Sunday, May 1, 2011

I. Introduction