Let’s verbalize S1, equally this year’s essay out is fast approaching.
I don’t similar the way my S1 textbook deals alongside skewness. It basically merely sets out methods for identifying skewness without actually explaining what it is. In this postal service I hash out an choice approach.
I usually piece of employment this starter interrogation inwards my get-go S1 lesson of the year:
The indicate beingness that when at that topographic point are outliers inwards a information set, the hateful becomes rather useless (unless of class you lot wishing to deceive people!).
Whilst education S1 I oftentimes uncovering myself referring dorsum to my Bibonacci starter (‘remember that CEO? He ruined the mean!’). So I decided to brand a worksheet out of it - come across below - which I used for the get-go fourth dimension this yr when education skewness (if you lot similar this thence delight acquire out me a review on
TES!). My pupils enjoyed the activeness too it generated interesting discussions.
The substitution education indicate is that when information is skewed, the median is to a greater extent than meaningful than the mean. We convey diverse methods for identifying skewness inwards a information ready (summarised inwards
these slides – sorry, master copy source unknown) - nosotros usually reckon the shape of a frequency diagram or box plot. Sometimes skewness is apparent merely from looking at the raw information (this sideways stem-and-leaf diagram is interesting).
Pupils involve to recollect that positive skew way nosotros convey a few 'sparse' information points (possibly outliers) at the top end of the information ready – too similar inwards the Bibonacci example, this volition pull the hateful up. This volition assistance them conceptually empathise the diverse methods described inwards the textbook.
Finally, here's a keen play a trick on that I learnt from my colleague Lizzie... Imagine a cute puppy sitting on the left of the graph. H5N1 positive skew is going to come across the puppy (positive = yay, a puppy!) too a negative skew is going away from the puppy (negative = acquire away from this puppy!). It's a giddy but uncomplicated too memorable way of ensuring that students don't acquire the graphs mixed up.
Imagine I'm queuing upwards to purchase 4 items of clothing, which cost £29.95, £49.95, £59.95 in addition to £99.95. To hold upwards past times fourth dimension I determine to function out the hateful cost of these 4 items. To brand the numbers easier to bargain with, I add together 5p to each total in addition to and so separate past times 10, giving me £3, £5, £6 in addition to £10. It's really slow to function out the hateful of these 'coded' prices inward my caput - it's £6. And right away I tin uncode that hateful past times multiplying past times 10 in addition to so subtracting 5p (the inverse of the master copy coding). That rapidly gives me the actual hateful cost of the clothes, which is £59.95. 
