On the probability of frog croaks.

Posted on 02/01/2017 by dougaj4

A recent logical puzzle from TED discussed the probability of one of two frogs being female, if we know that at least one of them is male:

This puzzle is discussed (arriving at different conclusions) here:

and puzzles of this type even have their own Wikipedia article:

Boy or Girl paradox

People discussing this problem tend to fall into one of two camps, and are convinced that the other camp is completely wrong, but the correct answer depends not just on what information is given in a particular version of the puzzle, but also on the factors that control what information is given.

To summarise the TED puzzle, a man has to decide if he is more likely to find a female frog in a group of two, one of which croaks like a male, or a single  frog that is not croaking.  The problem is that we do not know if female frogs croak, the frequency of croaking, or if being in a group of two affects the rate of croaking, but all these things affect the answer.

The explanation in the TED video appears to assume that only male frogs croak, and that when in a group of two, only one will croak, although this is not stated explicitly.  Based on this they calculate a probability of 2/3 for one of the two frogs being female, but only 1/2 for the single frog being female.

The discussion at the second video on the other hand states that:

frogriddle1

… so which (if either) is right?

One way to find out is to carefully tabulate all the possibilities, and calculate the probabilities of each, which is the approach used in the video links, arriving at different answers.

A simpler approach is to set up a computer simulation of the problem, and see what numbers come out, which is what:
Frog Croaks.xlsb
does.

The spreadsheet setup is shown below:
frogriddle2

The spreadsheet is set up to model any situation where it is required to find a female, either from a group of 2 (assumed to be on the left), or a single specimen on the right.  Obviously it could also be applied to any other situation with a binary choice and a 50/50 frequency.  For each sample the spreadsheet generates 1000 random numbers between 0 and 1, and assumes a male for numbers below 0.5, or female for above.  The following options are provided:

  • Cell C1 is the “cut-off score”.  The spreadsheet generates a second random number.  If this is below the cut-off score the sex of the sample  is treated as being known, otherwise it remains unknown.  In the frog context this is equivalent to the frog croaking or not croaking.
  • Cell E1 controls whether the cut-off score is applied to males only (only males croak), or both male and female (both croak, but with different croaks).
  • The spreadsheet includes a macro to do multiple repeats of the analysis, for  a range of different cut-off scores.  Enter the number of repeats in cell P2, press Alt-F8, and select the “Repeats” macro.
  • Results for a single run are displayed in cells K2 and L2, showing the probability of a female in the group of 2, on the left, and from the single sample on the right.
  • The same results from the repeat analyses are in columns S and T, and in the graph below.

The screen shot above shows results if only male frogs croak, with a cut off score (equivalent to the probability of any individual male frog being heard to croak) in the range 0.1 to 0.8.  It can be seen that the probability of a female increases from just over 50% to over 83%, but it is the same for the group of two (with a single croaking frog) and the single un-croaking frog.

If we assume that females croak at the same rate as males (with a different distinctive croak) then the probability of a female frog reduces to 50% for both the pair of frogs and the single frog, as shown below.  The rate of croaking now makes no difference to the probability of a female, which makes sense because it is now assumed that females croak at the same rate as males:frogriddle3

So are there any circumstances where the conclusion reached in the original video (that the pair of frogs with at least one male is more likely to have a female) is correct?  This would require that only males croaked, they only croaked when in a pair, and there was a 50% chance of a male frog in a pair being heard to croak.  Under those conditions the probability of a female in the pair of frogs would be 2/3 (as stated in the TED video), and the probability of the single frog being female would be 1/2.

None of these details are stated or implied in the puzzle statement however, so the correct answer is that the man should go for the single frog on the right, since it is easier to catch and lick one frog than two.

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Chris Hadfield reviews 2016

Posted on 01/01/2017 by dougaj4

Canadian Astronaut, Commander Chris Hadfield, reminds us of all the great many positives that happened in 2016. :

It’s easy to forget that this year saw a great many positives

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Transferring and converting strings in Excel and Python

Posted on 26/12/2016 by dougaj4

The load table for the 3D Frame spreadsheet has a column listing the global axis for each load as text (X, Y, or Z).  In the VBA version the table is converted to a variant array, and the axes are handled with a Select Case statement.  This will not work in Python, because the load data is copied to a Numpy array, which will not handle data of different types.  If the data type is not specified then all the data is converted to strings, or if a numeric data type is specified Numpy returns an error.

Converting text to a number based on the ASCII code value can be done easily on the spreadsheet using the CODE() or UNICODE() functions.  In this case X, Y, and Z (or x,y,z) are to be converted to 1, 2, or 3 respectively.  The ASCII code for W is 87, so the function required is:

  • =CODE(UPPER(A1))-87, or =UNICODE(UPPER(A1))-87

In VBA the equivalent function is Asc():

Function TextToNum(Txt As String, Optional Offset As Long = 0)
    TextToNum = Asc(Txt) - Offset
End Function

Doing the conversion in Python (using xlwings to transfer the data from Excel) requires a little more work.  The column with the text data must be converted to values before converting the data to a Numpy array, but the Excel range, which is converted to a Variant array in VBA, is transferred to Python as a Tuple, which is an immutable object.  A single row of data could be converted to a list with:

DistLoads = list(DistLoads)

But a multi-row range will be passed as a tuple of tuples, which the code above will convert to a list of tuples, leaving the data still in immutable form.  The map function will convert all the data to list form:

DistLoads = map(list, DistLoads)

The text in the Axis column (Column 2) can then be converted to integers with:

for row in DistLoads:
        if type(row[1]) == unicode:
            row[1] = ord(row[1].upper())-87

The resulting list of lists can be converted to a Numpy array with:

if type(LoadA) != np.ndarray:  LoadA = np.array(LoadA, dtype=np.float64)

Note that:

  • Text is passed from Excel as Unicode data, which is different to the str data type, so:
    if type(row[1]) == str:
    would always be false.
  • The ord function converts the text to an integer, but the load data needs to be passed as Numpy float64 values, so the Axis integer values are also converted into doubles
  • If data contains mixed integers and doubles (or float64), it will all be converted to doubles.  The statement “dtype=np.float64” is therefore optional, but serves as useful documentation.
Posted in Excel, Link to Python, Newton, NumPy and SciPy, VBA | Tagged , , , , , , , , | Leave a comment

Brent’s Method and a daft engineer’s blog

Posted on 23/12/2016 by dougaj4

Browsing links on Brent’s Method I found:

Daft Engineer – Numerical Methods and Excel*

which is well worth a look (plenty of stuff on statistics and Python, with the odd dash of Excel).  The link has VBA code for a class based Excel user defined function implementing Brent’s Method to find the roots of non-linear equations.  Time permitting, I’ll have a look and compare with my effort

* From a quick survey of the blog, I ‘m not convinced of the daftness of the author, but he should know I suppose.

Posted in Excel, Maths, Newton, UDFs, VBA | Tagged , , | 3 Comments

The Lime in the Coconut …

Posted on 14/12/2016 by dougaj4

… is a song by Harry Nilsson, released in 1972:

but somehow, the BBC managed to record three gorillas singing the same song in 1971:

Thereafter, the song was recorded by a wide variety of creatures, including Muppets:

and Dannii Minogue:

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