Interesting facts about Michael Phelps

Interesting facts about Michael Phelps

Michael Phelps  is an American competition swimmer and the most decorated Olympian of all time. He holds 39 world records (29 individual, 10 relay), surpassing Mark Spitz’s previous record of 33 world records (26 individual, 7 relay). The male swimmers with the next-highest career medal totals have exactly half of Phelps’ total. Mark Spitz, Matt Biondi and Ryan Lochte all have 11.

When Michael Phelps was in the sixth grade, he was diagnosed with attention deficit hyperactivity disorder (ADHD).  The more interesting fact about him is he placed his bedroom environment at a high altitude to decreases the amount of oxygen available, which forces his body to work harder to produce more red blood cells and deliver oxygen to his muscles. It also helps Phelps increase his performance endurance and prepare himself for competitions at high elevations.

“Once I'm already in my room I still have to open a door to get into my bed," Phelps said on the CBS News program "60 Minutes" in 2012. "It's just like a giant box. It's like 'boy and the bubble.'”

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How Sensex and Nifty are Calculated? Free-Float Methodology

Sensex and Nifty two major stock indices of Indian share markets are trading in its all time time as of June 2017.  BSE SENSEX - 31,273.27 - 2 Jun, 11:26 AM IST and NIFTY 50 - 9,648.50 - 11:27 AM IST.

Understanding Sensex and Nifty

Understanding Sensex and Nifty - www.iamsulthan.in

Both Sensex and Nifty are Calculated using Free-float methodology.

Free float methodology – Explained

Free-float methodology is a method to calculate market capitalization index for particular market. It is calculated by taking the equity's price and multiplying it by the number of shares readily available in the market i.e excluding the following categories 

  1. Shares held by founders/directors/acquirers which has control element
  2. Shares held by persons/ bodies with “Controlling Interest”
  3. Shares held by Government as promoter/acquirer
  4. Holdings through the FDI Route
  5. Strategic stakes by private corporate bodies/ individuals
  6. Equity held by associate/group companies (cross-holdings)
  7. Equity held by Employee Welfare Trusts
  8. Locked-in shares and shares which would not be sold in the open market in normal course.

The free-float methodology has been adopted by most of the world's major indexes.

Step by Step process

Step - 1 Determining the market capitalization for each company

Market Capitalization = Shares outstanding * Price

Step - 2 Weights of company is determined by NSE (for nifty). Weights is a multiple by which company’s Market capitalization is multiplied to arrive at Free-float market capitalization. The weights for each company in the index are determined based on the public shareholding of the companies as disclosed in the shareholding pattern submitted to the stock exchanges on quarterly basis. Weights are between 0.05 to 1.

Step – 3 Calculation of Free Float Market Capitalization

FFMC= Shares outstanding * Price * IWF

IWF - Investible weight factors (weights used in Nifty)

Step –4 Calculating the Index Value

Index value = Current Market Value / Base Market Capital * Base Index Value 

Base Date and Value

Base market capital of the Index is the aggregate market capitalisation of each scrip in the Index during the base period. The market cap during the base period is equated to an Index value of 1000 known as the base Index value.  The base period selected for NIFTY 50 index is the close of prices on November 3, 1995, which marks the completion of one year of operations of NSE's Capital Market Segment. The base value of the index has been set at 1000 and a base capital of Rs.2.06 trillion.


The method also takes into account constituent changes in the index and importantly corporate actions such as stock splits, rights, etc without affecting the index value. The index is reviewed every six months (on half-yearly basis) and a four weeks’ notice is given to the market before making changes to the index set. The Index Maintenance Sub-committee takes all decisions on addition/ deletion of companies in any Index.

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Measurement Scales–Nominal, Ordinal, Interval and Ratio

Measurement scales are classified popularly under four categories:

  1. Nominal,
  2. Ordinal,
  3. Interval,
  4. Ratio.

Let’s discuss in brief about these measurement scales before going on for some technical details. If you want to test Network of 50 smart phone users. Let’s begins by evaluating each on 4G – Non 4G data; this is a nominal measurement. Then the users ranks the Quality from best to worst; this is an ordinal measurement. Next, the mobile users uses a 5 or 7 point scale that has equal distance between points to rate the 4G network with regard to some criterion (e.g., data speed, Coverage, cost and etc.., ); this is an interval measurement. Finally, the user considers another network dimensions (eg.3G) and assigns 100 points among the 50 smart phone users; this is a ratio measurement. The characteristics of these measurement scales are summarized in below table.

Measurement Scales - Sulthan Academy

Note: Likert scale variables falls under Ordinal and/or Interval scale depends on the nature of the measurement.

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Measures of Location–Mean and Median

Measures of location are used in order to determine where the data distribution is concentrated. The most usual measures of location are Mean and Median

Mean

The mean of a set of numerical observations is just the familiar arithmetic average. The sum of the observations divided by the number of observations gives you Arithmetic Mean. It is helpful to have concise notation for the variable on which observations were made.

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were

x = the variable for which we have sample data

n = the number of observations in the sample (the sample size)

x1 = the first observation in the sample

x2 = the second observation in the sample

xn = the nth (last) observation in the sample

The Greek letter Ʃ is traditionally used in mathematics to denote summation. It denotes the sum of all the x values in the data set.

Median

Like a median strip of a highway divides the highway in half, the median of a numerical data set does the same thing for a data set. Once the data values have been listed in order from smallest to largest, the median is the middle value in the list, and it divides the list into two equal parts. Depending on whether the sample size n is even or odd, the process of determining the median is slightly different. When n is an odd number (say, 7), the sample median is the single middle value. But when n is even (say, 8), there are two middle values in the ordered list, and we average these two middle values to obtain the sample median.

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