Who is Thomas Bayes?

Ever since the Malaysian Air flight has been missing, Statisticians went back to Bayes theory,

I like to put a special event for this day as to remind us who Thomas Bayes was!

The English theologian and mathematician Thomas Bayes has greatly contributed to the field of probability and statistics. His ideas have created much controversy and debate among statisticians over the years.
Thomas Bayes was born in 1702 in London, England. Bayes's father was one of the first six Nonconformist ministers to be ordained in England. (4) Bayes's parents had their son privately educated. There is no information about the tutors Bayes worked with. However, there has been speculation that he was taught by de Moivre.

Still to put it, he was one who revolutionized Statistics with conditional probability and this algorithm is being used by advance software tools in the industry today from B.I. tools to Predictive Analytics.

Dr. Siegel and Predictive Analytics 2014

Predictive Analytics by Dr. Siegel
Cross-Industry, Cross-Vendor Sessions

The only conference of its kind, Predictive Analytics World delivers vendor-neutral sessions across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, high technology, insurance, non-profits, publishing, and retail.

And PAW covers the gamut of commercial applications of predictive analytics, includingresponse modeling, customer retention with churn modeling, product recommendations, online marketing optimization, behavior-based advertising, fraud detection, insurance pricing and credit scoring.

Why bring together such a wide range of endeavors? No matter how you use predictive analytics, the story is the same: Predictively scoring customers and other organizational elements optimizes business performance. Predictive analytics initiatives across industries leverage the same core predictive modeling technology, share similar project overhead and data requirements, and face common process challenges and analytical hurdles.

The Cross-Vendor Summit:

• Meet the vendors and learn about their solutions, software and services
• Discover the best predictive analytics vendors available to serve your needs
• Learn what they do and see how they compare.

Valuable Colleagues:

• Mingle, network and hang out with your best and brightest colleagues
• Exchange experiences over lunch, breaks and the conference reception, connecting with those professionals who face the same challenges as you.

Creating GEO Maps using Google Fusion Tables

by Albert Anthony D. Gavino

January 28, 2014

I just started teaching a class Fundamentals to Business Analytics every Mondays and Wednesdays from 04:20 to 05:50 pm. I guess there are a lot of topics to cover and yet so little time to teach the students given only 14 Weeks. Anyhow I was able to introduce them to Google Analytics, IBM-Cognos Insight for Dashboards, Google APIs for making pie charts, bar graphs and Motion Charts and just recently Geographical maps using Google Fusion Tables.

Have you Ever tried making a GEO MAP? its quite easy, you just need additional variables such as Latitude and Longitude and this will be mapped to a tab under your google spreadsheet.

Google GEO maps

to use the spreadsheet, I made it available to public consumption and access it here:
https://www.google.com/fusiontables/DataSource?docid=1FKYKWJdCuzHnnjFXkBOapt2aoL-a0e5Q4xpRlho

You may also link it to other tables by joining them and come up with awesome GEO maps.

Google fusion tables may be accessed at www.google.com/fusiontables/

Big Data vs Small Data (why our Stat traditional teachers are against it)

by Albert Anthony D. Gavino

Parametric vs Non-Parametric, Small Data vs Big Data,
Who is the more superior race?

The traditional "parametric" tests, such as t-tests and the analysis of variance, assume the population(s) to be normally distributed; they generally assume that one's measures derive from an equal-interval scale. 

Non-parametric tests involve non-normal distributions, some of which are the following: 

• multi forms of chi-square tests

• Fisher Exact Probability test

• Mann-Whitney Test

• Wilcoxon Signed-Rank Test

•  Kruskal-Wallis Test

• and the Friedman Test

In the field of Big Data, Non-parametric is the higher science and the more powerful one, as noted by one of the UP professors.

We no longer assume that distributions are normal and we can’t use t-tests or ANOVA for that matter.

The book has arrived!

Predictive Analytics Book by Eric Siegel

Finally the book I requested from Prediction Impact has arrived! this package was sent by my good friend Bobbe Cook from the Marketing Dept of Predictive Analytics World through UPS shipping at $20.15 and the book price at $28.00. (a thumbs up to these guys!)

Fortunately I got it all for free for being a Predictive Analytics World

Blog Partner, a partnership program by the Prediction Impact Inc.
to reach through the Asian Countries.

Package delivered on Sept 26, 2013

The book is a hard bound type with glossy pages

Front Cover

"What Nate Silver did for poker and politics, this does for everything else, A broad, well-written book easily accessible to non-nerd readers"-DAVID LEINWEBER, author of Nerds on Wall Street: Math, Machines and Wired Markets

"This is Moneyball for business, government, and healthcare"
-JIM STERNE, founder, eMetrics Summit; chairman, Digital Analytics Association

Back Cover of the Book

Some of its pages are in colored print and glossy paper material,

I can't wait to read all the chapters from Mortgage Risks, to the Ensemble Effect, Crowd-sourcing and Persuasion by the Numbers: How Telenor, U.S. Bank and the Obama Campaign engineered Influence (that's an Uplift!) Geeky as it sounds this book is for beginners and is friendly to 

starters for Predictive Analytics.

Inside Pages of the book

If you want to buy the book, its available through the ff:

    

    

6716 Cascade Rd., D10

Grand Rapids, MI 49546

12th National Convention on Statistics

The Philippine Statistical System (PSS) through the National Statistical Coordination Board (NSCB) invites you to participate in the 12th National Convention on Statistics (NCS) which will be held on 1-2 October 2013 at EDSA Shangri-La Hotel, Mandaluyong City.

Day 1 – October 1, 2013 (Tuesday)

7:00 – 8:45	Registration
8:45 – 9:00	Ribbon Cutting of the Statistical Information Management Exhibit (SIMEX) 2013
9:00 – 10:00	JOINT OPENING CEREMONIES of the 24th National Statistics Month and 12th National Convention on Statistics (Isla Ballroom) Welcome Remarks: Jose Ramon G. Albert NSCB Secretary General Keynote Address:  Senate President Franklin Drillon
10:10 – 10:30	Coffee Break
10:30 – 12:15	Plenary Session 1 (Isla Ballroom)1   Accelerating Inclusive Growth and Competitiveness through Statistics Session Organizer: Prof. Solita Collas-Monsod    Presenters: Mr. Guillermo Luz Dr. Josef T. Yap Discussant: Dr. Johannes Jutting
12:15 – 1:15	Lunch Break
1:15 – 2:45	Simultaneous Scientific Sessions (10 sessions)
2:50 – 4:20	Simultaneous Scientific Sessions (10 sessions)
4:25 – 4:40	Coffee Break
4:40 – 6:10	Simultaneous Sessions (10 sessions)

Day 2 – October 2, 2013 (Wednesday)

8:30 – 10:00	Simultaneous Scientific Sessions  (10 sessions)
10:00 – 10:15	Coffee Break
10:15 – 12:00	Plenary Session 2 (Isla Ballroom)2 Social media and statistics (big data, organic data and privacy) Session Organizer: Dr. Corinne Grace Burgos Presenters: Mr. Johannes Jutting Dr. Jose Ramon G. Albert Ms. Jeanette Beltran
12:00 – 1:00	Lunch Break
1:00 – 2:30	Simultaneous Scientific Sessions (10 sessions)
2:35 – 4:20	Plenary Session 3 (Isla Ballroom) Managing risks to development (disaster and financial risk management, social protection, food security) Session Organizer: Asst. Secretary Lila Shahani Presenters: Asst. Secretary Romeo Recide Gov. Jose Clemente "Joey" Salceda
4:20 – 4:35	Coffee Break
4:35 – 5:00	CLOSING CEREMONY of the 12th NCS (Isla Ballroom)

Root Mean Square Error Approximation (RMSEA) and WARP PLS

by Albert Anthony D. Gavino, MBA

Model fit is one important aspect in the field of SEM, otherwise known as Structural Equation Modeling, RMSEA or Root Mean Square Error Approximation is a test if our data is a good fit to the model, with experts saying an acceptable value is less than 0.05.

There are two software programs used by my colleagues in this certain field, one of them is IBM-SPSS AMOS and another is WARP PLS using Partial Least Squares Method, these are deemed popular among Moderation and Mediation experts, the WARP PLS is recommended for users who would want a deeper insight into their moderation variables, while the IBM-SPSS AMOS software is good for researchers looking into mediation variables, Nevertheless both software are powerful for the Researcher and provides them a good tool into coming with the best model.

I guess this is what happens when your colleagues are statistical nerds, Psychometricians and highly cognitive people who just have fun with RMSEA values and Structural Equation Modeling.