Education is not preparation...

 

Getting Along

Getting Along

{A refreshing look at how to get along with others....}

 

Money

Money

{The things in life that money can't buy}

 

A Rainy Night in New Orleans

It was a rainy night in New Orleans;

At a bus station in the town,

I watched a young girl weeping

As her baggage was taken down.

 

It seems she'd lost her ticket

Changing buses in the night.

She begged them not to leave her there

With no sign of help in sight.

 

The bus driver had a face of stone

And his heart was surely the same.

"Losing your ticket's like losing cash money,"

He said, and left her in the rain.

 

Then an old Indian man stood up

And blocked the driver's way

And would not let him pass before

He said what he had to say.

"How can you leave that girl out there?

Have you no God to fear?

You know she had a ticket.

You can't just leave her here.

You can't put her out in a city

Where she doesn't have a friend.

You will meet your schedule,

But she might meet her end."

 

The driver showed no sign

That he'd heard or even cared

About the young girl's problem

Or how her travels fared.

 

So the old gentleman said,

"For her fare I'll pay.

I'll give her a little money

To help her on her way."

He went and bought the ticket

And helped her to her place

And helped her put her baggage

In the overhead luggage space.

 

"How can I repay," she said,

"the kindness you've shown tonight?

We're strangers who won't meet again

A mere 'thank you' doesn't seem right."

 

He said, "What goes around comes around.

This I've learned with time -

What you give, you always get back;

What you sow, you reap in kind.

Always be helpful to others

And give what you can spare;

For by being kind to strangers,

We help angels unaware."

 

Author Unknown

 

Being Ignorant...

 

You Dont get to choose..

 

Shadow Dancers

Absolutely amazing, brilliantly conceived and even more brilliantly executed! Dont miss this...

Mandatory skills for an IT professional

A career in the field of information technology (IT) is one of the most sought these days. Most engineering college graduates land up in the IT industry. While, a job as a software engineer looks very lucrative at first glance, once you get into the industry, you realise that it is not just your technical skills that will keep you in the race.

You need something more to ensure that you are able to do a good job. In other words, you need some extra skills to ensure that you are able to keep the job after you land it. These extra skills are called 'soft skills'.

 What are the advantages of soft skills?
Your soft skills or people skills decide how fast and well you climb the ladder of success. Here are some of the advantages that your soft skills can reap for you:

~ They help you grow in your career
~ They give you an eye to identify and create opportunities
~ They help develop relationships with your colleagues and clients
~ They develop good communication and leadership qualities in you
~ They help you think beyond dollars.

After reading the advantages your soft skills can get you, you would want to know what is it that you need as a technical person to grow as a professional and climb the ladder of success.  

Here are some soft skills which will help you grow not just as a professional but also as a person: 

~ A never-say-die attitude
Any task that comes to you or your team, undertake with a can-do attitude. Slowly you will observe that you and your team have become the favorite of the management. Every accomplished task boosts your self confidence and pushes you one step closer to success.

~ Communication
This includes verbal, non-verbal and written communication. Be sure that you are able to put across your point clearly and confidently. As an IT professional you will need to work with colleagues and clients of various nationalities and backgrounds. Ensure that you are able communicate clearly with them. This applies to teleconferencing as well.

~ Learn to listen
Listening is an essential part of communication. Ensure that you listen attentively. This will help make the other party feel comfortable while interacting with you and improve your communications.

~ Be a team player
Help your team members help themselves. Be friendly and approachable. If your team is stuck somewhere look out for ideas to overcome the obstacle together.

~ Learn to delegate
Chances are you will have junior members on the team. Recognise their strengths and delegate them the right work.  

~ Give credit to those who deserve it
Do not all the credit for a job well done. Pass on praise or recognition from superiors to team members who deserve it. Doing it publicly or in front of your boss will further instill a feeling of confidence among your team.

 ~ Motivate yourself and others
As you look ahead to grow in your career you will need to deal with various people under you. You can not expect quality results from a team whose motivational level is too low. So, stay motivated and keep others motivated.

~ Develop leadership qualities
A leader is a person whom people are ready to follow. Develop qualities that will make people follow you not because they are required to but because they want to. Even while operating in a team, take a role to lead and facilitate the work for other members.

~ Control your sense of humour
When you are working with people from various cultures you need to be extra careful with your sense of humour and gestures. Behaviour that is acceptable among Indian colleagues might be considered obscene or disrespectful by people from other cultures. Stay away from controversial topics or ideas in the office.

~ Mentoring
This is a quality one needs to develop in order to grow. If you want to grow in the hierarchy, you need to help sub-ordinates grow. Be a good mentor. Help them understand things better. This not only improves the work environment but also improves your work relationships.

~ Handling criticism
When you are working with people, at times you will be criticised while at others you will be required to criticise your colleagues or sub-ordinates. Ensure that you take the criticism constructively and look at it as an opportunity to grow. Similarly, while criticising others shoose your words carefully and keep it professional. Destructive criticism will lead to loss of respect and trust. Let your criticism help the other person grow.

~ IT-preneur- Like an entrepreneur, have a risk-taking attitude. Learn to take responsibility for failures and pride in a job well done.

~ Managing spoil sports
While working in a team there will always be one or two people with a negative attitude. This attitude can be contagious. Employ tactics to deal with such people and improve motivation.

~E-tiquette
Keep an eye on your e-mails for proper language. Open up the e-mail with a suitable address and end with a thanking note. Your words should convey the correct meaning and invoke the desired action.

~ Multitasking
As you climb the ladder of success, you will need to handle work from various fields. For example, you will have to interact with your technical team on project success, with the HR department for team appraisal and recruitment, with clients on project requirements or problems etc. Organise and plan to fit in all the required activities into your schedule.

Once you have developed these soft skills along with your technical skills you will find that you are a lot more confident about your capabilities.

 

Probability Theory

Probability has gained a lot of importance and the mathematical theory of probability has become the basis for statistical applications in the areas of management, space technology and the like.  Various business decisions in real life are made under situations when a decision maker is very uncertain as to what will happen after the decisions are made.  The theory of probability is helpful in all such areas.  In particular it enables a person to make 'educated guesses' on matters where either full facts are not known or there is uncertainty about the outcome. 

 

The probability formulae and techniques were developed by Jacob Bernoulli, De Moiure, Thomas Bayes and Joseph Lagrange.  Later on, Pierre Simon and Laplace unified all these early ideas and compiled the first general 'theory of probability'.

 

Probability Concepts

 

Þ      Experiment - Any operation / process that results in two or more outcomes.

Þ      Random experiment – Any well-defined process of observing a given chance phenomena through a series of trials that are finite or infinite and each of which leads to a single outcome is known as a random experiment.

Þ      Possible outcome – The result of a random experiment.

Þ      Event – One or more possible outcomes of an experiment or a result of a trial or an observation.

Þ      Elementary Event – a single possible outcome of an experiment.

Þ      Compound Event – When two or more events occur in connect with each other.

Þ      Favourable event – the number of outcomes that result in the happening of a particular event.

Þ      Mutually exclusive events – Two events are said to be mutually exclusive or incompatible if the happening of any one of them precludes the happening of all others.

Þ      Dependent events or independent events – Two are more events are said to be independent if the happening of an event is not affected by the supplementary knowledge concerning the occurrence of any number of the remaining events.  The question of dependence or independence of events is relevant when experiments are consecutive and not simultaneous.

Þ      Exhaustive events – the total number of possible outcomes in any trial.

Þ      Equally likely events – Events are said to be equally likely, if taking into consideration all the relevant evidence, there is no reason to expect one in preference to the others.

Þ      Complementary events  - the number of unfavourable cases in an experiment.

 

 

 

THEORIES (OR TYPES) OF PROBABILITY

 

There are four basic ways of classifying probability based on the conceptual approaches to the study of probability theory.  They are:

 

1. Classical approach
2. Relative frequency of occurrence approach
3. Axiomatic approach
4. Subjective approach

 

Classical approach

 

The classical approach is based on the assumption that each event is equally likely to occur.  This is an apriori assumption (the term apriori refers to something that is known by reason alone) and the probability based on this assumption is known as apriori probability.  This approach employs abstract mathematical logic and hence is also called the 'abstract' or 'mathematical' probability.  This is the reason for considerable use of familiar objects like cards, coins, dice, etc., where the answer can be stated in advance before picking a card, tossing a coin or throwing a die respectively. 

 

If a random experiment results in 'N' exhaustive, mutually exclusive, and equally likely outcomes, out of which 'f' are favourable to the happening of an event 'E', then the probability of occurrence of 'E', usually denoted by P(E) and is given by

 

          P = P(E) = f/N =       Number of favourable outcomes

                                      ----------------------------------

                                         Total number of outcomes

 

The classical approach is highly hypothetical in its assumptions.  It assumes situations that are very unlikely but could conceivably happen. The limitation is that it is applicable only when the trials are equally likely or equally probable.  For instance, the probability that a candidate, attending an interview, will succeed is not 50% since the two possible outcomes, viz. success and failure are not equally likely.  Another limitation is that it is applicable only when the exhaustive number of cases in a trial is finite and only when the events are mutually exclusive.  Thus it is useful in card games, dice games, tossing coins, etc., but has serious problems when it is applied to less orderly decision problems that are encountered in the area of management. 

 

Relative Frequency of Occurrence Approach

 

The relative frequency of occurrence approach defines the probabilities as either:

 

v      The proportion of times that an event occurs in the long run when the conditions are stable, or

v      The observed relative frequency of an event in a very large number of trials.

 

In this approach, the probability of happening of an event is calculated knowing how often the event has happened in the past.  In other words, this method uses the relative frequencies of past occurrences as probabilities.  Hence, it is also called an 'empirical' approach to probability theory. 

 

For example, if an organization knows from past data that around 25 out of 300 employees entering each year leave the organization due to better opportunities elsewhere, then the organization can predict the probability of employee turnover as 25/300, i.e. 0.083 or 8.3%.

 

Another characteristic of probabilities established by the relative frequency of occurrence approach can be illustrated by tossing a fair coin 1000 times.  In this case, it is found that the proportion of getting either a head or tail is more initially but as the number of tosses increase, both a head or tail become equally likely and the probability of the event showing a head is 0.5 or the event showing a tail is 0.5.  Thus, accuracy is gained as the experiment is repeated and the number of observations is more.  But the limitation of this approach is the consumption of time and cost for such large repetitions and additional observations.  Moreover, predicting probability using this approach becomes a blunder if the prediction is not based on sufficient data.

 

Axiomatic Approach

 

There is no precise definition available for this approach, but this concept is considered as a set of functions based on the following axioms:-

 

v      The probability of an event ranges from 0 to 1.  That is, an event surely not to happen has probability 0 and another event sure to happen has probability 1.

v      The probability of an entire sample space is 1.  Mathematically P(S)=1.

v      If A and B are mutually exclusive events, then the probability of occurrence of either A or B denoted by P(AUB) is given by P(AUB) = P(A) + P(B).

 

Subjective Approach

 

Subjective probabilities are those assigned to events by the researcher based on past experiences or occurrences or on the basis of evidences available.  It may be an educated guess or intuition.  At higher levels of managerial decision making, where it becomes extremely important, specific and is demanded to be unique, subjective probability would be used.  It is therefore based on the personal beliefs of the person making the decision based on his past information, experiences, observed trends and estimation of futuristic situations.

 

 

 

Set Theory

Set theory is the mathematical theory of sets, which represent collections of abstract objects. It has a central role in modern mathematical theory, providing the basic language in which most of mathematics is expressed. In mathematics, a set can be thought of as any collection of distinct things considered as a whole. Although a simple idea, it is, nevertheless, one of the most important and fundamental concepts in modern mathematics.

 

A set is described as a well-defined collection of objects. These objects are called the elements or members of the set. Objects can be anything: numbers, people, other sets, etc. For instance, 4 is a member of the set of all even integers. As can be seen from this example, sets are allowed to have an infinite number of elements.

 

If x is a member of A, then it is also said that x belongs to A, or that x is in A. In this case, we write x ∈ A. (The symbol "∈" is a derivation from the Greek letter epsilon, "ε"). The symbol  is sometimes used to write x ∉ A, or "x is not in A".

 

Two sets A and B are defined to be equal when they have precisely the same elements, that is, if every element of A is an element of B and every element of B is an element of A. Thus a set is completely determined by its elements; the description is immaterial. For example, the set with elements 2, 3, and 5 is equal to the set of all prime numbers less than 6. If A and B are equal, then this is denoted symbolically as A = B (as usual).

 

An empty set, often denoted by "{}" is a set without any members at all. Since a set is determined completely by its elements, there can only be one empty set. A Universal Set is a set consisting of all objects or elements of a type or of a given interest and is normally depicted by the alphabets X, U or S.  A Finite Set is one in which the number of elements can be counted.  An Infinite Set is one in which the number of elements cannot be counted. 

 

Given two sets A and B we say that A is a subset of B if every element of A is also an element of B. Notice that in particular, B is a subset of itself; a subset of B that isn't equal to B is called a proper subset. If A is a subset of B, then one can also say that B is a superset of A, that A is contained in B, or that B contains A. In symbols, A ⊆ B means that A is a subset of B, and B ⊇ A means that B is a superset of A. A is called a subset if every element of A is an element of B.  B is a superset of A if every element in A is an element of B.

 

Unions, intersections, and relative complements

Given two sets A and B, we may construct their union. This is the set consisting of all objects which are elements of A or of B or of both (see axiom of union). It is denoted by A ∪ B. The intersection of A and B is the set of all objects which are both in A and in B. It is denoted by A ∩ B. Finally, the relative complement of B relative to A, also known as the set theoretic difference of A and B, is the set of all objects that belong to A but not to B. It is written as A \ B. Symbolically, these are respectively

 

A ∪ B := {x : (x ∈ A) or (x ∈ B)};

A ∩ B := {x : (x ∈ A) and (x ∈ B)} = {x ∈ A : x ∈ B} = {x ∈ B : x ∈ A};

A \ B := {x : (x ∈ A) and not (x ∈ B) } = {x ∈ A : not (x ∈ B)}.

 

A set can also have zero members. Such a set is called the empty set (or the null set) and is denoted by the symbol ø. For example, the set A of all living dragons has zero members, and thus A = ø. Like the number zero, though seemingly trivial, the empty set turns out to be quite important in mathematics.

 

Set Theory does have its place in a Business Organization.  Any organization essentially comprises of various types of resources such as men, machines, money, materials, etc.  The inter-relationship between these resources, often limited if not scarce, as also the inter-relationship between the subsets of each set of resources is used to equate assets of one kind with assets of another kind.  A subset of skilled workers within the set of all workers is a critical subset that has an impact on the overall productivity of the organization.  A subset of skilled salesmen within the set of all staff in the Marketing and Sales department of an organization is another critical subset, especially in a marketing driven organization which has an impact on the topline of the organization.  Similarly there could be subsets of products, materials, etc. which when inquired into analytically could pave the way for effective decision making and sound organizational plans, policies and procedures.