# 308. Zombie stats

I’ve used word length analysis for years as a source of comparative statistics. The concept is easy – you take a children’s book and a grown up book and compare the word lengths of the first 20, 40, 80 words. After you collect the information in a table, you can use this data to compare averages and the range.

Image credit: www.comingsoon.net
But what texts to use? Well – you can’t beat a bit of Dr Seuss, but what grown up text could you use. I can highly recommend this extract from ‘Pride and Prejudice and Zombies’:

Pride and Prejudice and Zombies by Seth Grahame Smith

Not only will you be investigating mathematical concepts, but you might just be inspiring a student to pick up a book and read.
Update: If you use the first chapter (say thirty words) of ‘Pride & Prejudice & Zombies’ you get some interesting data. The range is wide, but the highest frequency word length is just two. It’s a great conversation piece – why does this happen? The language is a very precise parody of 19th prose with all the correct connectives and no contractions eg ‘it is’ not ‘it’s’.

# 243. Messy Means

I have recently been teaching lower ability Year 9 students how to calculate the mean from grouped and ungrouped data tables. I didn’t want to teach them a method to learn by rote, so I used a more investigative approach.

Image Credit: http://www.thisismykea.com/designs/mr-messy

Grouped Frequency tables discussion

I started with a table with all the working shown, but some information blacked out. Each group had an A3 version and they filled in what was missing.

The second table had more information covered up. After a discussion the groups decided there wasn’t enough information and they would have to guess what the missing numbers were.

The third table had minimal information. Each group used their own method to find the missing values. Some chose the largest value in the range, some guessed what the results could have been in each group and one group decided to calculate two means – one using the largest value and one using the smallest.

We collected our results together on the board and discussed their accuracy. The class decided to use the middle of each range to calculate the estimated mean. They had gone from no understanding of estimated mean to formulating their own method.

We followed this up a Splitting the Steps estimated mean worksheet that I wrote after seeing Bruno Reddy’s presentation after #MathsConf2014 (Mr Reddy’s blog).