The White Man's Burden-Poem

Rudyard Kipling, The White Man’s Burden

Take up the White Man’s burden–Send forth the best ye breed–

Go bind your sons to exile To serve your captives’ need;

To wait in heavy harness, On fluttered folk and wild–

Your new-caught, sullen peoples, Half-devil and half-child.

Take up the White Man’s burden–In patience to abide,

To veil the threat of terror And check the show of pride;

By open speech and simple, An hundred times made plain

To seek another’s profit, And work another’s gain.

Take up the White Man’s burden– The savage wars of peace–

Fill full the mouth of Famine And bid the sickness cease;

And when your goal is nearest The end for others sought,

Watch sloth and heathen Folly Bring all your hopes to nought.

Take up the White Man’s burden–No tawdry rule of kings,

But toil of serf and sweeper–The tale of common things.

The ports ye shall not enter,The roads ye shall not tread,

Go mark them with your living,And mark them with your dead.

Take up the White Man’s burden–And reap his old reward:

The blame of those ye better,The hate of those ye guard–

The cry of hosts ye humour (Ah, slowly!) toward the light:–

“Why brought he us from bondage, Our loved Egyptian night?”

Take up the White Man’s burden–Ye dare not stoop to less–

Nor call too loud on Freedom To cloke your weariness;

By all ye cry or whisper, By all ye leave or do,

The silent, sullen peoples Shall weigh your gods and you.

Take up the White Man’s burden– Have done with childish days–

The lightly proferred laurel, The easy, ungrudged praise.

Comes now, to search your manhood Through all the thankless years

Cold, edged with dear-bought wisdom, The judgment of your peers!

This famous poem, written by Britain‘s imperial poet, was a response to the American take over of the Phillipines after the Spanish-American War.(published in 1899)

source

http://www.fordham.edu/halsall/mod/kipling.html

The White Man’s Burden-Poem

Rudyard Kipling, The White Man’s Burden

Take up the White Man’s burden–Send forth the best ye breed–

Go bind your sons to exile To serve your captives’ need;

To wait in heavy harness, On fluttered folk and wild–

Your new-caught, sullen peoples, Half-devil and half-child.

Take up the White Man’s burden–In patience to abide,

To veil the threat of terror And check the show of pride;

By open speech and simple, An hundred times made plain

To seek another’s profit, And work another’s gain.

Take up the White Man’s burden– The savage wars of peace–

Fill full the mouth of Famine And bid the sickness cease;

And when your goal is nearest The end for others sought,

Watch sloth and heathen Folly Bring all your hopes to nought.

Take up the White Man’s burden–No tawdry rule of kings,

But toil of serf and sweeper–The tale of common things.

The ports ye shall not enter,The roads ye shall not tread,

Go mark them with your living,And mark them with your dead.

Take up the White Man’s burden–And reap his old reward:

The blame of those ye better,The hate of those ye guard–

The cry of hosts ye humour (Ah, slowly!) toward the light:–

“Why brought he us from bondage, Our loved Egyptian night?”

Take up the White Man’s burden–Ye dare not stoop to less–

Nor call too loud on Freedom To cloke your weariness;

By all ye cry or whisper, By all ye leave or do,

The silent, sullen peoples Shall weigh your gods and you.

Take up the White Man’s burden– Have done with childish days–

The lightly proferred laurel, The easy, ungrudged praise.

Comes now, to search your manhood Through all the thankless years

Cold, edged with dear-bought wisdom, The judgment of your peers!

This famous poem, written by Britain‘s imperial poet, was a response to the American take over of the Phillipines after the Spanish-American War.(published in 1899)

source

http://www.fordham.edu/halsall/mod/kipling.html

Clustering Business Analysts and Industry Analysts

In my interactions with the world at large (mostly online) in the ways of data, statistics and analytics- I come across people who like to call themselves analysts.

As per me, there are 4 kinds of analysts principally,

1) Corporate Analysts- They work for a particular software company. As per them their product is great and infallible, their code has no bugs, and last zillion customer case studies all got a big benefit by buying their software.

They are very good at writing software code themselves, unfortunately this expertise is restricted to Microsoft Outlook (emails) and MS Powerpoint ( presentations). No they are more like salesmen than analysts, but as Arthur Miller said ” All salesmen (person) are dreamers. When the dream dies, the salesman (person) dies (read transfers to bigger job at a rival company)

2) Third -Party Independent Analsyst- The main reason they are third party is they can not be tolerated in a normal corporate culture, their spouse can barely stand them for more than 2 hours a day, and their Intelligence is not matched by their emotional maturity. Alas, after turning independent analysts, they realize they are actually more dependent to people than before, and they quickly polish their behaviour to praise who ever is sponsoring their webinar,  white paper , newsletter, or flying them to junkets. They are more of boutique consultants, but they used to be quite nifty at writing code, when younger, so they call themselves independent and “Noted Industry Analyst”

3) Researcher Analysts- They mostly scrape info from press releases which are mostly written by a hapless overworked communications team thrown at a task at last moment. They get into one hour call with who ever is the press or industry/analyst  relations honcho is- turn the press release into bullet points, and publish on the blog. They call this as research Analysts and give it away for free (but actually couldnt get anyone to pay for it for last 4 years). Couldnt write code if their life depended on it, but usually will find transformation and expert somehwere in their resume/about me web page. May have co -authored a book, which would have gotten them a F for plagiarism had they submitted it as a thesis.

4) Analytical Analysts- They are mostly buried deep within organizational bureaucracies if corporate, or within partnerships if they are independent. Understand coding, innovation (or creativity). Not very aggressive at networking unless provoked by an absolute idiot belonging to first three classes of industry analyst. Prefer to read Atlas Shrugged than argue on business semantics.

Next time you see an industry expert- you know which cluster to classify them 😉

Image Citation-

http://gapingvoidgallery.com/

New Deal in Statistical Training

The United States Government is planning a new initiative at providing employable skills to people, to cope with unemployment.
One skill perpetually in shortage is analytics training along with skills in statistics.

It is time that corporates like IBM SPSS, SAS Institute and Revolution Analytics as well as offshore companies in India or Asia can ramp up their on demand trainings, certification as well as academic partnership bundles. Indeed offshroing companies can earn revenue as well as goodwill if they help in with trainers available via video- conferencing. The new Deal initiative would require creative thinking as well as direct top management support to focus their best internal brains at developing this new revenue stream. Again the company that trains the most users (be it Revolution for R, IBM for SPSS-Cognos, SAS Institute for Base SAS-JMP, WPS for SAS language) is going to get a bigger chunk of new users and analysts.

Analytics skills are hot. There is big new demand for hot new skills by millions of unemployed Americans and Asians. How do you think this services market will play out?

If the US government could pump 800 Billion for bailouts, how much is your opinion it should spend on training programs to help citizens compete globally?

From http://www.nytimes.com/2010/10/03/business/economy/03skills.html?hpw

The national program is a response to frustrations from both workers and employers who complain that public retraining programs frequently do not provide students with employable skills. This new initiative is intended to help better align community college curriculums with the demands of local companies.

SAS recognizes the market –

see http://www.sas.com/news/preleases/aba-tech-engage.html

In tough economic times, it is more important than ever that companies be able to make better decisions using analytics. SAS is involved in two programs this summer that offer MBAs and unemployed technology workers the opportunity to learn and enhance analytics skills, and increase their marketability.

SAS is a partner in TechEngage, a week-long program of training classes that offer unemployed technology professionals new skills at a low cost to help them compete effectively in the marketplace.”

So does IBM-

http://www-03.ibm.com/press/us/en/pressrelease/28994.wss

. “Fordham has a long history of collaboration with IBM that has brought innovative new skills to our curriculum to prepare students for future jobs. With this effort, Fordham is preparing students with marketable skills for a coming wave of jobs in healthcare, sustainability, and social services where analytics can be applied to everyday challenges.”

and R

Well TIBCO and Revolution ….hmmm…mmmm

I am not sure there is even a R Analytics Certification program at the least.

Wealth = function (numeracy, memory recall)

As per a recent paper by the National Bureau of Economic Research

It has been postulated that wealth is simply a function of your ability to handle numbers as well as recall memory.

That is – answering just three numerical questions for Retirement/ people with age above 50 years. This alone should serve as a wake up call for greater investment in Education (than just banks and corporations).

Citation- NBER

Cognition and Economic Outcomes

Household wealth is strongly associated with numeracy and memory recall.

In Cognition and Economic Outcomes in the Health and Retirement Survey, (NBER Working Paper No. 15266), co-authors John McArdle, James Smith, and Robert Willis show that the ability to answer three simple mathematical questions is a significant predictor of wealth, wealth growth, and wealth composition for people over 50 years of age.

Using data from the Health and Retirement Survey (HRS) — a nationally representative longitudinal survey for the United States, which combines comprehensive information on household wealth with “cognition variables” designed to measure memory, intactness of mental status, numerical reasoning, broad numeracy, and vocabulary — these authors find that household wealth is strongly associated with numeracy and memory recall.

To test memory recall, respondents listened to a list of ten simple nouns, answered other questions for five minutes, and then were asked to recall as many of the nouns as possible. Two-thirds of the HRS survey respondents were able to recall between three and seven of the words. Most respondents answered just one of the three numeric questions correctly.

Answering a numeric question correctly in the three-question sequence was associated with a $20,000 increase in total household wealth and about a $7,000 increase in total financial wealth. Wealth also tended to increase with a higher numeracy score for either spouse in a married couple—when neither spouse answered any numeric questions correctly, which was about 10 percent of the cases, household wealth was about $200,000. When both spouses answered all questions correctly, household wealth was about $1,700,000.

In households where one spouse, the financial respondent, was in charge of finances, household financial wealth was larger if the financial respondent had the higher numeracy score. Answering a question correctly was associated with a $30,000 increase in household wealth if the financial respondent answered correctly and only a $10,000 increase if the non-financial respondent answered correctly. Households with higher numeracy scores were also more likely to have higher fractions of their portfolios in stock.

In this sample, wealth was higher for couples than for single-person households, and lower for minorities than non-minorities. Wealth increased with age and family income, and rose steeply with education. In the HRS, median household wealth was $198,000, and 9 percent of that was held in stocks. Median total income was $37,000, and the typical sample member was a high school graduate.

The authors point out that their exploratory analysis has only established that specific cognitive measures are useful predictors of accumulated wealth and that they have not established causal pathways. It is possible, for example, that a lifetime interest in investments and the stock market can improve numerical ability. However, they note that the fact that numeracy seems to predict total and financial wealth at lower wealth quartiles where people are less likely to be active investors does seem to weigh against a purely reverse pathway from investments to cognitive ability.

— Linda Gorman

Speaking of Educational Programs I came across a good example on education in numeracy –

SAS Institute has been working in the field in the following  manner- directly as provider of SAS® Curriculum Pathways®

Fully funded by SAS and offered at no cost to US educators and students, SAS Curriculum Pathways is designed to enhance student achievement and teacher effectiveness by providing Web-based curriculum resources in all the core disciplines: English, math, science, social studies/history and Spanish, to educators and students in grades 8-14 in virtual schools, home schools, high schools and community colleges.

I believe other statistical softwares (like RE Computing, IBM SPSS , etc ) can also donate a small part of their product portfolio to K12 education (not just college education) as well. Education is an area where software companies especially in the field of statistics and analytics, co-operation and co-mpetition can co-exist to enhance the pool of potential developers , users and enhance life skills in numeracy as well .

Born in the USA?

Here is some econometric search-ing I did

Using Google Public Data-and Wolfram Alpha and The Bureau of Labour Statistics

United States

United States – Monthly Data
Data Series Back
Data
May
2009
June
2009
July
2009
Aug
2009
Sept
2009
Oct
2009
Unemployment Rate (1)
Jump to page with historical data
9.4 9.5 9.4 9.7 9.8 10.2
Change in Payroll Employment (2)
Jump to page with historical data
-303 -463 -304 -154 (P) -219 (P) -190
Average Hourly Earnings (3)
Jump to page with historical data
18.53 18.54 18.59 18.66 (P) 18.67 (P) 18.72
Consumer Price Index (4)
Jump to page with historical data
0.1 0.7 0.0 0.4 0.2 0.3
Producer Price Index (5)
Jump to page with historical data
0.2 1.7 (P) -1.0 (P) 1.7 (P) -0.6 (P) 0.3
U.S. Import Price Index (6)
Jump to page with historical data
1.7 2.7 (R) -0.6 (R) 1.5 (R) 0.2 (R) 0.7
Footnotes
(1) In percent, seasonally adjusted. Annual averages are available for Not Seasonally Adjusted data.
(2) Number of jobs, in thousands, seasonally adjusted.
(3) For production and nonsupervisory workers on private nonfarm payrolls, seasonally adjusted.
(4) All items, U.S. city average, all urban consumers, 1982-84=100, 1-month percent change, seasonally adjusted.
(5) Finished goods, 1982=100, 1-month percent change, seasonally adjusted.
(6) All imports, 1-month percent change, not seasonally adjusted.
(R) Revised
(P) Preliminary
United States – Quarterly Data
Data Series Back
Data
3rd Qtr
2008
4th Qtr
2008
1st Qtr
2009
2nd Qtr
2009
3rd Qtr
2009
Employment Cost Index (1)
Jump to page with historical data
0.6 0.6 0.3 0.4 0.4
Productivity (2)
Jump to page with historical data
-0.1 0.8 0.3 6.9 9.5
Footnotes
(1) Compensation, all civilian workers, quarterly data, 3-month percent change, seasonally adjusted.
(2) Output per hour, nonfarm business, quarterly data, percent change from previous quarter at annual rate, seasonally adjusted.

And also included are the average wages for salary of teachers and average salary per hour of some offshore  prone industries

http://www.bls.gov/oes/2008/may/oes_nat.htm#b25-0000

http://www.bls.gov/oes/2008/may/oes_nat.htm#b11-0000

and

http://www.google.com/publicdata?ds=usunemployment&met=unemployment_rate&idim=state:ST370000:ST540000:ST510000&tdim=true

WHAT THEY PAY TEACHERS (MAY 2008)

Education, Training, and Library Occupations top
Wage Estimates
Occupation Code Occupation Title (click on the occupation title to view an occupational profile) Employment (1) Median Hourly Mean Hourly Mean Annual (2) Mean RSE (3)
25-0000 Education, Training, and Library Occupations 8,451,250 $21.26 $23.30 $48,460 0.5 %
25-1011 Business Teachers, Postsecondary 69,690 (4) (4) $77,340 1.0 %
25-1021 Computer Science Teachers, Postsecondary 32,520 (4) (4) $74,050 1.0 %
25-1022 Mathematical Science Teachers, Postsecondary 45,710 (4) (4) $68,130 0.9 %
25-1031 Architecture Teachers, Postsecondary 6,430 (4) (4) $75,450 1.9 %
25-1032 Engineering Teachers, Postsecondary 32,070 (4) (4) $90,070 1.1 %
25-1041 Agricultural Sciences Teachers, Postsecondary 10,000 (4) (4) $77,770 1.6 %
25-1042 Biological Science Teachers, Postsecondary 51,930 (4) (4) $83,270 2.7 %

WHAT THEY PAY THEMSELVES

Management Occupations top
Wage Estimates
Occupation Code Occupation Title (click on the occupation title to view an occupational profile) Employment (1) Median Hourly Mean Hourly Mean Annual (2) Mean RSE (3)
11-0000 Management Occupations 6,152,650 $42.15 $48.23 $100,310 0.2 %
11-1011 Chief Executives 301,930 $76.23 $77.13 $160,440 0.5 %
11-1021 General and Operations Managers 1,697,690 $44.02 $51.91 $107,970 0.2 %
11-1031 Legislators 64,650 (4) (4) $37,980 1.1 %

and JOBS PRONE TO SHORTAGE /OFFSHORING

Computer and Mathematical Science Occupations top
Wage Estimates
Occupation Code Occupation Title (click on the occupation title to view an occupational profile) Employment (1) Median Hourly Mean Hourly Mean Annual (2) Mean RSE (3)
15-0000 Computer and Mathematical Science Occupations 3,308,260 $34.26 $35.82 $74,500 0.3 %
15-1011 Computer and Information Scientists, Research 26,610 $47.10 $48.51 $100,900 1.1 %
15-1021 Computer Programmers 394,230 $33.47 $35.32 $73,470 0.6 %
15-1031 Computer Software Engineers, Applications 494,160 $41.07 $42.26 $87,900 0.4 %
15-1032 Computer Software Engineers, Systems Software 381,830 $44.44 $45.44 $94,520 0.5 %
15-1041 Computer Support Specialists 545,520 $20.89 $22.29 $46,370 0.3 %
15-1051 Computer Systems Analysts 489,890 $36.30 $37.90 $78,830 0.4 %
15-1061 Database Administrators 115,770 $33.53 $35.05 $72,900 0.8 %
15-1071 Network and Computer Systems Administrators 327,850 $31.88 $33.45 $69,570 0.3 %
15-1081 Network Systems and Data Communications Analysts 230,410 $34.18 $35.50 $73,830 0.4 %
15-1099 Computer Specialists, All Other 191,780 $36.13 $36.54 $76,000 0.5 %
15-2011 Actuaries 18,220 $40.77 $46.14 $95,980 1.4 %
15-2021 Mathematicians 2,770 $45.75 $45.65 $94,960 1.7 %
15-2031 Operations Research Analysts 60,860 $33.17 $35.68 $74,220 0.8 %
15-2041 Statisticians 20,680 $34.91 $35.96 $74,790 1.5 %
15-2091 Mathematical Technicians 1,100 $18.46 $20.24 $42,100 2.7 %
15-2099 Mathematical Science Occupations, All Other 6,600 $26.44 $31.55 $65,630 4.3 %

 

UNEMPLOYED IN THE USA (above)

BY STATE (below)

16 million people out of work. Give or take a million.

How can America pay 5.6 million people UNEMPLOYMENT BENEFITS

Keep another 10 million unemployed,

another 10 million only partially employed.

[tweetmeme source=”decisionstats”]

and still claim aggregate cost savings from offshoring jobs.

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