This will be my first ever post and first set of solutions for the Guardian’s weekly “Pyrgic Puzzles”! Let’s dive in with the first puzzle:
1. “When Mrs May lost one of her Brexit votes by 230 the presenter of the BBC lunchtime News remarked that Mrs May “needs to persuade 230 MPs to change their minds.” What made Pendanticus almost choke on his panino?”
I think what Pedanticus is turning his nose up at here is the use of the phrase “change their minds.” The government was defeated by 432 votes to 202, so let us imagine what would happen if MPs started to change their minds:
- 432 to 202 (starting point – 230 margin)
- 431 to 203 (one mind changed – 228 margin)
- 430 to 204 (two minds changed – 226 margin)
For every “mind changed” the margin of the win drops by 2! In fact we only need 115 MPs to change their minds for the margin to be 0, and therefore 116 need only change their mind for May to win. Let’s crack on with puzzle number 2!
2. “Garabaggios latest effort – The Source Of Circles shows a corner (a right angle) and a large circle (of radius 1 unit, according to the catalogue) and a sequence of smaller and smaller circles, each tangent to each of the two walls and each touching the next biggest circle. According to the catalogue the circles continue ad infinitum into the corner. By what (linear) factor (f) is each circle smaller than the next largest one? Hence work out the total area of the infinite set of circles.”
We can see the first two of these circles in the diagram below:

Now let’s put in a few helpful lines:

The green line joins the centres of the two circles. Now if we consider the right-angled triangle created by the red, purple and green lines we can start to deduce some useful relationships.
If we call the radius of the the little circle r, then the base of our right-angled triangle is length 1-r and similarly for the height. The hypotenuse is length 1+r – it is the sum of the radii of the two circles. Now we can involve Pythagoras:

The radius of the large circle is 1, so the linear factor by which each circle is smaller than the last is simply equal to the radius of the first smaller circle, r, which we found above. Now we can use the formula for the sum of a geometric series to find the sum of the areas of all the infinitely many circles. Here R is the ratio between successive areas which will be our length ratio squared:

The use of this formula is made possible by the fact that our length ratio is less than 1, and so our area ratio is also less than 1.
3. “Andy was flummoxed by the last question of this week’s homework:

“Clearly 2 is one answer,” remarked Candy, “but it’s a cubic so there must be two other roots.” “But I can’t solve a cubic!” replied Andy. But Candy thought it wasn’t necessary to solve a cubic. How did she go about it?”
Unless I’m missing some subtlety of this puzzle, I think it is just hinting at a good method for solving cubics which is taught at A-level. The method is to try to find one obvious root (2 in this case) and then to divide by the linear factor that produces the root ( (x-2) in this case ) :

You are then left with a quadratic factor which hopefully Candy knows how to solve. In this case we want to know if there are any other roots than 2, so we should investigate whether the quadratic even has real roots before we try to find them! Let’s check out the discriminant:

The discriminant is negative! Now we know the final two roots are a pair of imaginary conjugates so 2 is our only real root.
4. “Down at the Last Chance Saloon Gullible Gus was explaining the die-rolling game to a visitor from Chipolata County. “You expect to need on average 6 rolls to get 2 consecutive odd scores and 14 to get 3,” he said. “It seems to me,” drawled the newcomer, “that if you roll the die over and over again and you know the expected number of successive rolls to get n successive odd scores – let’s call it u(n), it should be a doddle to deduce the expected number of rolls you need to get n+1 succesive odd scores – let’s call it u(n+1).” How?”
This is the most interesting problem of the lot. This answer is far more detailed than required and if anyone has a nice, simple and intuitive way of explaining it please get in touch! Before I even thought about the actual question at hand, I wanted to satisfy myself that I understood where those 6 and 14 figures came from.
Usually if you want to find out how long you would have to wait to see an event occur, you would work out the probability of it occurring and use that to work out your waiting time. For example the probability of rolling a 6 is 1/6 so we know intuitively that we would expect to have to roll the dice 6 times before seeing a 6, on average (although it is no guarantee!). But in this scenario we cannot simply work out the probability of our event occurring. Sure, if you were given a fixed number of rolls you could work out the probability of you seeing two or more consecutive odds, but that’s not really the problem a hand. We’re going to have to work in the language of expectation.
We’re going to work out what our expected waiting time will be before we see two consecutive odds. Expectation is a weighted average of the possible values our waiting time could take, each weighted to the probability of that waiting time occurring. For example, the expected score when rolling a dice is the sum of each score multiplied by the probability it occurs: (1/6)*1 + (1/6)*2 + (1/6)*3 + (1/6)*4 + (1/6)*5 + (1/6)*6 =3.5 . Essentially what you would expect the average score of a dice roll to be!
Let’s set up an equation with our waiting time to see two consecutive odds:

Now we can put in one situation we know lots about: rolling two odds straight away. Our “waiting time” was two rolls of the dice and the probability of this happening is 1/4 so we can put this weighted event into our expectation formula:

Now what about if we roll an even on our first roll? The probability of this happening is 1/2. Let’s think about our waiting time now. We are still going to have to wait however long we would expect to wait to see two consecutive odds but now we have wasted one roll on getting an even. Our waiting time for the event of rolling an even first will be how long we have to wait to see two consecutive odds + 1 (for the wasted roll of the dice):

Finally lets think about what happens if we roll odd then even straight out of the gate. In the same way as before we will still have to wait as long as we would expect from the start to see two consecutive odds except this time we’ve wasted two rolls:

We’ve now covered all our bases and have set up a nice (and solvable!) equation for our expected waiting time. We can now set about solving it:
Just what we wanted to show! We can set up a similar equation thinking about wasted rolls for waiting to see three odds in a row:

Now again we got the answer we wanted! Now I feel satisfied I know where these figures are coming from. Now lets try to set up a shortcut to finding u(n+1). It seems to me that u(n+1) = 2( u(n) + 1). Let’s make sure and generalise our expression for u(n):

This checks out for the two we know: 2*(4-1)=6 and 2*(8-1)=14. Now we can test our claim about the relationship between u(n) and u(n+1):

Our speculation was right! 2(u(n)+1) = u(n+1). I’ll repeat what I said at the start – this is not, as the puzzle wants our solution to be, a doddle. I’m sure there is a nice intuitive explanation out there, I just wanted to do this one in depth.
This is an equivalent question to how many flips of a coin until we can expect to see n consecutive heads. Both problems are related to a concept called a Markov chain. If you want to read something even more in depth about this type of problem here are some notes that do it justice: https://courses.cit.cornell.edu/info2950_2012sp/mh.pdf