Jacques turns into a squirrel on certain days and he needed to keep track of his activity to help me better understand which activity or activities triggers his squirrel transformation.
To better understand this guide, you need to read it along with the eloquent javascript textbook. You can find it here

1. The dynamic data entry
To start off, Jacques needs to state all the activities he does in a day and record them for some time (say a month or two)

NOTE: if you declare an object property name without a value, it takes its value from the parameter that shares the same name. (ie. The squirrel object property will be matched with the value of the function parameter “squirrel”)

// console.log(journal) will give us something like this which is an array of objects
 [ 
    {
      squirrel: false,
      events: ["pizza","brushed teeth","work"]
    },
    {
      squirrel: true,
      events: ["pizza","peanuts","candy","work"]
    }
]

2. The Correlation

To get the events correlation, we need to follow the steps below.

• the Phi coefficient

  Basically, we are using the phi coefficient where (you can find the formula from eloquent javascript chapter 4)
  For the numerator

  n00 = no squirrel, no event

  n01 = no squirrel, yes event

  n10 = yes squirrel, no event

  n11 = yes squirrel, yes event

  We will be using an array index for this and here’s how we do it

  [0, 1, 2, 3] ⇒ convert to binary, and if the number is not up to two values we will add 0 to the left of it.

  [00, 01, 10, 11] ⇒ this gives us a replica of what we have from n00,n11,n01,n00 etc.

  For the denominator

  n1. = sum of all places where the squirrel is true

  n0. = sum of all places where the squirrel is false

  n.1 = sum of all places where the event occurred

  n.0 = sum of all places where the event did not occur

• So let’s say we have the correlation table for work is ⇒[76, 9, 4, 1 ]
  Analyzing it:

  n00 = 76

  n01 = 9

  n10 = 4

  n11 = 1
  n1. = 5 ⇒ (4 + 1)

  n0. = 85 ⇒(76 + 9)

  n.1 = 10 ⇒ (9 + 1)

  n.0 = 80 ⇒(76 + 4)

• the dynamic correlation table

  Now we have a clue of what each array index denotes, we can now go ahead to find the number of occurrences for a particular event (say “work” will look like).
  Basically, I want to loop through the journal array and search for the number of times a particular event happened and if the squirrel happened or not alongside the event.

  

    console.log(tableFor("work", journal)) ⇒ [4, 3, 1, 2]
    // which means:-
    // The event “work” has no squirrel and no work occurrence ⇒ 4
    // has  no squirrel and a work occurrence ⇒ 3
    // has  a squirrel and no work occurrence ⇒ 1
    // has  a squirrel and a work occurrence ⇒ 2
  

• The phi function

  Using the correlation array we got in the previous step, we can now write a function using the phi formula to help us get the phi coefficient.

  

    console.log(phi([4, 3, 1, 2]))
    =>  0.2182178902359924
    // this means the chance of turning to a werewolf on "work" activity is low.
  

• Get all the activities done

  To get the correlation table for all the activities done, we need to know all the different activities in the journal.

  

    // logging to the console we will get a list of all the activities done
    console.log(eventsInJournal(journal))
    [
        'work', 'touched tree', 'pizza', 'running','television', 
        'ice cream', 'cauliflower', 'lasagna','weekend'......
    ]
  

• dynamic correlation table for all events.
  Now that we have a list of all activities/events in the journal, we can now go ahead to get a correlation table for each event.

  

    bread :  -0.21821789023599236
    pudding :  -0.21821789023599236
    brushed teeth :  -0.8017837257372732
    weekend :  -0.2182178902359924
     touched tree :  -0.42857142857142855
     lasagna :  0.2182178902359924
     peanuts :  1
     work :  0.2182178902359924
     carrot :  -0.42857142857142855
     nachos :  -0.21821789023599236
     cycling :  -0.3273268353539886
     pizza :  0.2182178902359924
     candy :  0.5091750772173156
     brussel sprouts :  -0.21821789023599236
     ice cream :  -0.42857142857142855
    ......... and others.
  

  From here we can see the particular activity that actually turns him into a squirrel.

• filtering the result to get the least and the highest correlation value

  

    brushed teeth :  -0.8017837257372732
    peanuts :  1
    candy :  0.5091750772173156
    spaghetti :  0.5091750772173156
  

  This shows that eating peanuts causes him to transform into a squirrel while brushing his teeth has the least chance of turning him into a squirrel.

I hope this guide helps you in understanding the lycanthrope's exercise, for more questions, do use the comment session.