Du
Du hast
Du hast mich
Du
Du hast
Du hast mich
Du
Du hast
Du hast mich
Du
Du hast
Du hast mich
Du
Du hast
Du hast mich
Du hast mich
Du hast mich gefragt
Du hast mich gefragt
Du hast mich gefragt und ich hab nichts gesagt
Willst du bis der Tod euch scheidet
treu ihr sein fur alle Tage…
nein nein
Willst du bis zum Tod der Scheide
sie lieben auch in schlechten Tagen….
nein nein
Du
Du hast
Du hast mich
Du
Du hast
Du hast mich
Du
Du hast
Du hast mich
Du hast mich
Du hast mich gefragt
Du hast mich gefragt
Du hast mich gefragt und ich hab nichts gesagt
Willst du bis der Tod euch scheidet
treu ihr sein fur alle Tage…
nein nein
Willst du bis zum Tod der Scheide
sie lieben auch in schlechten Tagen….
nein nein
Willst du bis der Tod euch scheidet
treu ihr sein fur alle
nein nein

[English Translation:]

You
You hate
You hate me
You
You hate
You hate me
You
You hate
You hate me
You
You hate
You hate me
You
You hate
You hate me
You hate me
You hate me to say
You hate me to say
And I did not obey
Will you until death does sever
Be upright to her forever
Never never
Will you ’til death be her rider
Her lover too, to stay inside her
Never never
You
You hate
You hate me
You
You hate
You hate me
You
You hate
You hate me
You hate me
You hate me to say
You hate me to say
And I did not obey
Will you until death does sever
Be upright to her forever
Never never
Will you ’til death be her rider
Her lover too, to stay inside her
Never never
Will you until death does sever
Be upright to her

An article on central tendency.

Central Tendency

The term central tendency refers to the “middle” value or perhaps a typical value of the data, and is measured using the mean, median, or mode. Each of these measures is calculated differently, and the one that is best to use depends upon the situation.

Mean

The mean is the most commonly-used measure of central tendency. When we talk about an “average”, we usually are referring to the mean. The mean is simply the sum of the values divided by the total number of items in the set. The result is referred to as the arithmetic mean. Sometimes it is useful to give more weighting to certain data points, in which case the result is called the weighted arithmetic mean.

The notation used to express the mean depends on whether we are talking about the population mean or the sample mean:

=  population mean

=  sample mean

The population mean then is defined as:

=

where

=  number of data points in the population

=  value of each data point i.

The mean is valid only for interval data or ratio data. Since it uses the values of all of the data points in the population or sample, the mean is influenced by outliers that may be at the extremes of the data set.

Median

The median is determined by sorting the data set from lowest to highest values and taking the data point in the middle of the sequence. There is an equal number of points above and below the median. For example, in the data set {1,2,3,4,5} the median is 3; there are two data points greater than this value and two data points less than this value. In this case, the median is equal to the mean. But consider the data set {1,2,3,4,10}. In this dataset, the median still is three, but the mean is equal to 4. If there is an even number of data points in the set, then there is no single point at the middle and the median is calculated by taking the mean of the two middle points.

The median can be determined for ordinal data as well as interval and ratio data. Unlike the mean, the median is not influenced by outliers at the extremes of the data set. For this reason, the median often is used when there are a few extreme values that could greatly influence the mean and distort what might be considered typical. This often is the case with home prices and with income data for a group of people, which often is very skewed. For such data, the median often is reported instead of the mean. For example, in a group of people, if the salary of one person is 10 times the mean, the mean salary of the group will be higher because of the unusually large salary. In this case, the median may better represent the typical salary level of the group.

Mode

The mode is the most frequently occurring value in the data set. For example, in the data set {1,2,3,4,4}, the mode is equal to 4. A data set can have more than a single mode, in which case it is multimodal. In the data set {1,1,2,3,3} there are two modes: 1 and 3.

The mode can be very useful for dealing with categorical data. For example, if a sandwich shop sells 10 different types of sandwiches, the mode would represent the most popular sandwich. The mode also can be used with ordinal, interval, and ratio data. However, in interval and ratio scales, the data may be spread thinly with no data points having the same value. In such cases, the mode may not exist or may not be very meaningful.

The article has been sourced from

http://www.quickmba.com/stats/centralten/

On 2nd July, 2008. 1838 IST

All credits go to the authors.

When to use Mean, Median, and Mode

The following table summarizes the appropriate methods of determining the middle or typical value of a data set based on the measurement scale of the data.

The Map of IIM Bangalore. Please find the Jogging track parallel to the main gate boundary wall. Someone please find it for me.

There are only 2 contenders.

1.The Panasonic Toughbook

2. SIEMENS Simatic Field PG M2

Something interesting related to the Field PG M2

Having been a thinkpad user for the past 5 years have worked on the whole range of thinkpads starting from the R-Series & the T-series. But one which has always carried an aspirational value to it has been the Thinkpad Z-series. To get a better understanding about the perception & performance of the Z-series one could look at the discussion which happened when the Z-series was launched.

To determine whether the R-Series, T-series or the Z-series is better is something that would depend on many factors th most important being price. However on an absolute scale there’s no taking away from the fact that the Z-series packs in the most and has been the best to come from the IBM stable.

Just day before yesterday got introduced to the Case Study Method of Learning. The case discussed was about the Dabbawallahs of Mumbai. A BBC Documentary on various aspects about the life of Dabbawallahs as also the way they conduct their business was discussed.

The Objective of learning i believe is aggregation of data, processing it, identifying problems, approaching those problems based on processed data, coming up with valid, uptodate, implementable solutions.

I believe the case study method of learning does that in a very comprehensive manner.

On a different line alogether, i am expecting that the Ranbaxy sell off will very soon be studied as a case at most of the IIM’s, since it is a landmark deal in the sense, a family owned business which separated ownership and management and did what was best for the company. CAPITAL INFUSION. On the other hand a cyncial approach to the deal also makes one feel that the promoters cashed out sensing tougher times ahead, especially 2011. Well what happens is for all of us to see, but what has happened is what we must try and learn from.

Q: What entices an individual to sell off his family owned company?

Is it greed, business, for the company’s good or else are there other reasons which when taken together make a sell off proposition too good to say no to.

I read this article by “P.T. Jyothi Datta” (Sify Business, Friday, 27 June , 2008, 08:54) which tries to look at this very issue. Is sell-out the cure?