Outliers and data cleaningAQA A-Level Maths: Flashcards

What these 13 flashcards ask

What is an outlier?
State the quartile rule for outliers.
State the standard deviation rule for outliers.
Upper boundary when Q1=24 and Q3=36?
How are outliers shown on a box plot?
How do you deal with missing data?
How do you deal with an obvious error such as -1 for a spend?
What do you do with a genuine outlier?
Which average is least affected by an outlier?
Which measure of spread is least affected by an outlier?
Why is a value exactly on the boundary not an outlier?
What should you check first about a suspected outlier?
A wrong value a should be b. How does the total change?

Exam questions on Outliers and data cleaning

The daily numbers of visitors to a museum over a period have lower quartile 24 and upper quartile 36. A value is treated as an outlier if it is more than $1.5\times$ the interquartile range above the upper quartile or more than $1.5\times$ the interquartile range below the lower quartile.
The value 63 is found to be a typing error caused by swapping two digits. State the corrected value and explain whether it is still an outlier.2 marks
Ten temperature readings, in $^\circ$ C, from a sensor have mean 50 and standard deviation 6. One of the readings is 70. A reading is treated as an outlier if it lies more than 2 standard deviations from the mean.
The reading of 70 is confirmed as a sensor fault and removed. Find the mean of the remaining 9 readings.2 marks
A supermarket stores the weekly grocery spend, in pounds, of 200 households in a spreadsheet. Six entries are blank, three entries are $-1$ (the till uses this to mean 'card declined') and one entry is 4500. All the other values are between 15 and 310.
For each of the three kinds of problem entry (blank, $-1$ , 4500), state how it should be dealt with before the mean spend is calculated, giving a reason.3 marks

Written by the Exaim team, led by Shaun Daswani (Head of Upper Secondary, Improve ME Institute; MSc Financial Mathematics, Imperial College London; BSc, UCL) and Jason Daswani (operational lead, Improve ME Institute; LSE).