Philosophy, business: the “single source of truth” concept

In the tutoring realm, awareness of new insights and definitions is important. The tutor mentions single source of truth.

In my March 5 post I mention the idea of a data silo. Put simply, it’s knowledge kept secret by some members of an organization, even though they’re meant to be cooperating with the others.

Single Source of Truth
The single source of truth model conceives one source of information to which everyone has access and everyone trusts as “best”. It eliminates the possibility of data silos – why would you use your own private information when the others have access to better?

In business, many believe that the reason one enterprise is more successful than the next is that its internal cooperation is superior. Hence, the single source of truth paradigm appeals to many business leaders.


Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Computer science, business: what is a data silo?

Keeping current with technical language can mean continual self-tutoring. The tutor shares a great term: data silo.

data silo:

data or knowledge known by only one department (or some subset of a an organization).

The existence of a data silo means some – possibly most – members of a company are making decisions without the maximum possible awareness.

Obviously, the data silo concept is fascinating. I look forward to producing more posts about it:)


Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Economics, business: the US trade deficit: good or bad? (Part 0)

Reading about economics means self-tutoring. The tutor discusses the disadvantage – or advantage, of the US trade deficit.

The US has run a trade deficit since the late 70s. Simply put, a trade deficit means that the country’s imports are worth more than its exports. The US trade deficit is famous; for 2016 it was 502.3 billion.

Old-time wisdom suggests that a trade deficit, long-term, is bad, since it means wealth is leaving the country. The departing wealth is either savings being spent, or else household debt increasing.

Yet Senator Lankford, of Oklahoma, argues the US trade deficit is likely helpful to America. He makes the following arguments:

  1. Americans import goods to save money (because the same goods, if made in America, would cost more). The money Americans save by buying imports, they can re-invest in their businesses. Therefore, importing goods indeed can lead to increased investment in America with the savings from those cheaper goods.
  2. Take Mexico, for example. If the US runs a trade deficit with Mexico, the Mexicans become more prosperous. The US will enjoy at least two benefits of Mexican prosperity:
    • Fewer Mexicans will want to illegally migrate to the US.
    • Mexicans will have more money to spend on goods, some of which they will import from America.
  3. The US trade deficit includes foreign investment in US companies. Since investment in US businesses increases American productivity, the part of the US trade deficit due to it should be welcomed, not criticized.

Lankford seems to believe that as long as trade is open and fair, where its balance sits is not for the government to influence. The reason Americans run a trade deficit now is because they perceive it benefits them. They are following the laws of economics and should be allowed to do so.


Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Business: what do Carly Fiorina and Martha Stewart have in common?

Tutoring, you’re interested in education. The tutor brings up two business titans from the late ’90s/2000s: What were their first degrees?

In their time, I followed both Carly Fiorina (CEO, Hewlett-Packard, 1999-2005) and Martha Stewart through the headlines. Both were tremendous achievers – that’s an understatement.

Interestingly, both have arts degrees (among others). Carly has a BA in philosophy and medieval history from Stanford; Martha has a double major in history and architectural history from Barnard College.

Some people say it’s hard to succeed in business with an arts degree….:)




Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Statistics: an assumption of the linear regression model

Tutoring statistics, linear regression is perennial. The tutor mentions an assumption it includes.

When appropriate, linear regression models data by the equation

y = a + bx + e,

e being an error term due to variability.

An inherent assumption of linear regression modelling is that the error term, e, does not depend on the actual data value, x.

In many lab environments, the assumption that error magnitude does not depend on the measurement’s magnitude makes sense. For instance, measuring with a ruler, the error is often set to ± 0.5mm, regardless of the length measured.

For some types of data, however, the measurement’s magnitude seems to impact its error magnitude. An example might be inventory counting. One imagines that, counting only three items, the error would likely be 0. Counting a thousand, however, would more likely yield an observation a few off from the real number present, and so on.

Perhaps the point is that the data has to be measured or observed, which itself brings error, perhaps dependent on the size of the measurement itself.


Harnett, Donald L. and James L. Murphy. Statistical Analysis for Business and Economics. Don Mills: Addison-Wesley, 1986.

Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Calculator usage: finding final price after discount and tax with the HP-10B

Tutoring financial math, you might often use the HP-10B. The tutor shows how easily it can apply a discount then add tax to get the final price.

Example: Imagine a handbag is regular price $85 but is discounted by 20%. Assuming 12% sales tax, find final price using the HP-10B.


  1. Key in 85
  2. Key in – 20 % =
  3. Key in + 12 % =



Hewlett-Packard HP-10B Business Calculator Owner’s Manual. Corvallis: Hewlett-Packard, 1994.

Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Calculator usage: memory on the HP-10B

Tutoring financial math, you’ll likely encounter the capable HP-10B. The tutor tells how to use its user-accessible memory.

The HP-10B seems to have 11 dedicated places to store your own numbers. The locations are at 0 to 9, plus there is the M register.

Example: On the HP-10B, store the number 65.21 in register 5.

  1. Key in 65.21
  2. Press the orange key
  3. Press RCL
  4. Press 5

To retrieve the number,

  1. Press RCL
  2. Press 5



Hewlett-Packard Business Calculator HP-10B Owners Manual. Corvallis: Hewlett-Packard, 1994.

Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Microsoft Word 2007: changing date format

Tutoring Business English, word processing formats inevitably arise. The tutor suggests how to change the date format in Microsoft Word 2007.

I prefer the date format April 14, 2017. There’s no chance of misunderstanding it, since the month is a proper noun and the year is four digits.

On my computer, anyway, Microsoft Office Word 2007 prefers the format 2017-04-14. What can a user do to change the date format?

  1. Click Insert at the top (next to Home).
  2. Locate, in the Text area of the toolbar (probably right side), the option Date and Time. Click it.
  3. You will be offered a menu of date formats.
  4. On mine, among the English (Canada) choices, the closest to April 14, 2017 is 14 April 2017.

Of course, the user can type any date format they want. However, Word will try to autocorrect it to the chosen (or else default) format. To stop the autocorrect, simply left-click when it’s offered. (Make sure the mouse pointer is on the cursor when you do so, or else your cursor might be sent wherever the mouse pointer is.)


Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Statistics, spreadsheets: confidence interval for population mean: CONFIDENCE() function on Excel and LibreOffice Calc

Tutoring statistics, you realize how convenient using a spreadsheet can be.

In yesterday’s post I mentioned some theoretical points about two-sided confidence intervals for the population mean.

On the practical side, if you simply need a confidence interval for the population mean, you can use Excel’s CONFIDENCE() function, which works the same on LibreOffice Calc. It has the following format:

=confidence(1-confidence_level, pop_standard_deviation, sample_size)

The formula assumes the population standard deviation is known. If not, you can just use a sample_size ≥31, calculate the sample standard deviation, and use it. This gives a pretty good approximation (see yesterday’s post).

The CONFIDENCE() formula gives the margin of error for the confidence interval. To get the actual lower and upper bounds, you both subtract and add its output to the sample mean.


Imagine an exam written by 706 students. A sample of 42 papers reveals a mean grade of 67.3 and standard deviation 12.4. Give a 95% confidence interval for the mean exam mark.


The confidence level is 95% = 0.95, so the first parameter is 1-0.95=0.05.

In a cell, key

=confidence(0.05, 12.4, 42)

Hopefully, you obtain the output 3.75, which means the confidence interval for the mean is given by



63.55 to 71.05

Apparently the mean, with 95% confidence, is between 63.55 and 71.05.


Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.

Statistics: confidence interval for the mean (two sided)

Tutoring statistics, confidence intervals are important.

A two-sided confidence interval for the population mean is given by

sample_mean – (standard_dev/n1/2)*sig_factor, sample_mean + (standard_dev/n1/2)*sig_factor

The sig_factor (significance factor) depends on the certainty (confidence level) with which we want the confidence interval to include the population mean; typically it’s around 2 (aka, 1.96) for 95% confidence.

The standard deviation might be known or might be calculated from the sample itself. If it’s known, the normal distribution is used; if calculated, then technically the t-distribution should be used (see point 3 below).

There are a few points that make the two-sided confidence interval for the population mean an elegant construct:

  1. Its lower and upper boundaries depend on the sample size, but not the population size.
  2. For sample size n≥31, the parent population needn’t be normal for the sample mean to be normally distriubted. This validates the confidence interval even for a non-normal population for n≥31. It’s a consequence of the Central Limit Theorem. (Actually, the rule of thumb is n≥30, but for the purpose of the next point, I like 31.)
  3. For n≥31, the t-distribution approximates the normal to around 4%, so the normal approximation can probably be used even for unknown population standard deviation.


Harnett, Donald L. and James L. Murphy. Statistical Analysis for Business and Economics, first Can. ed. Don Mills: Addison-Wesley, 1993.

Jack of Oracle Tutoring by Jack and Diane, Campbell River, BC.