Skewness
Friday, September 6, 2019
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Let’s beak S1, equally this year’s examine is fast approaching.
I don’t similar the way my S1 textbook deals alongside skewness. It basically only sets out methods for identifying skewness without actually explaining what it is. In this post service I hash out an choice approach.
I unremarkably operate this starter inquiry inwards my commencement S1 lesson of the year:
I don’t similar the way my S1 textbook deals alongside skewness. It basically only sets out methods for identifying skewness without actually explaining what it is. In this post service I hash out an choice approach.
I unremarkably operate this starter inquiry inwards my commencement S1 lesson of the year:
The quest existence that when in that place are outliers inwards a information set, the hateful becomes rather useless (unless of course of report you lot want to deceive people!).
Whilst instruction S1 I oft detect myself referring dorsum to my Bibonacci starter (‘remember that CEO? He ruined the mean!’). So I decided to brand a worksheet out of it - run across below - which I used for the commencement fourth dimension this twelvemonth when instruction skewness (if you lot similar this thence delight endure out me a review on TES!). My pupils enjoyed the action in addition to it generated interesting discussions.
The fundamental instruction quest is that when information is skewed, the median is to a greater extent than meaningful than the mean. We bring diverse methods for identifying skewness inwards a information laid upwardly (summarised inwards these slides – sorry, master copy source unknown) - nosotros unremarkably reckon the shape of a frequency diagram or box plot. Sometimes skewness is apparent only from looking at the raw information (this sideways stem-and-leaf diagram is interesting).
Whilst instruction S1 I oft detect myself referring dorsum to my Bibonacci starter (‘remember that CEO? He ruined the mean!’). So I decided to brand a worksheet out of it - run across below - which I used for the commencement fourth dimension this twelvemonth when instruction skewness (if you lot similar this thence delight endure out me a review on TES!). My pupils enjoyed the action in addition to it generated interesting discussions.
The fundamental instruction quest is that when information is skewed, the median is to a greater extent than meaningful than the mean. We bring diverse methods for identifying skewness inwards a information laid upwardly (summarised inwards these slides – sorry, master copy source unknown) - nosotros unremarkably reckon the shape of a frequency diagram or box plot. Sometimes skewness is apparent only from looking at the raw information (this sideways stem-and-leaf diagram is interesting).
Pupils necessitate to retrieve that positive skew agency nosotros bring a few 'sparse' information points (possibly outliers) at the top end of the information laid upwardly – in addition to similar inwards the Bibonacci example, this volition pull the hateful up. This volition help them conceptually sympathise the diverse methods described inwards the textbook.
Finally, here's a keen fob that I learnt from my colleague Lizzie... Imagine a cute puppy sitting on the left of the graph. Influenza A virus subtype H5N1 positive skew is going to run across the puppy (positive = yay, a puppy!) in addition to a negative skew is going away from the puppy (negative = acquire away from this puppy!). It's a giddy but uncomplicated in addition to memorable way of ensuring that students don't acquire the graphs mixed up.
Finally, here's a keen fob that I learnt from my colleague Lizzie... Imagine a cute puppy sitting on the left of the graph. Influenza A virus subtype H5N1 positive skew is going to run across the puppy (positive = yay, a puppy!) in addition to a negative skew is going away from the puppy (negative = acquire away from this puppy!). It's a giddy but uncomplicated in addition to memorable way of ensuring that students don't acquire the graphs mixed up.