pros and cons of measures

pros and cons of IQR

• +Less affected by outliers cuz it only considers middle 50% of data

• -= doesn’t consider entire dataset

• - shouldn’t use IQR on its own, should consider range and IQR

pros and cons of mean

• + considers entire data set

• - affected by outliers

• - not a good measure if data is skewed as it might not reflect central location

pros and cons of median

• + less affected by outliers

• + better measure of central location when data is skewed

• - only considers middle value leaves out rest of data

pros and cons of variance

• + shows how observations differ from sample mean

• - harder to interpret because it is in squared units (hence used standard deviation)

pros and cons of SD

• + gives you how far data deviates from mean in the same unit

• - is affected by outliers

coefficeint of variation

• how big is SD comparative to sample mean

• + can be used as a relative measure and can be used to compare between data sets. shows variability.

• - affected by outliers

Covariance

• - only tells you direction of association either positive or negative

• + gives you an idea how data is related/ the trend between data

unit of covariance is the units of each variable multipled

Correlation

• + tells you direction and strength

• - doesn’t prove casusation, can overlook other variables

pros and cons of pie charts

• + each slice represents the categories proportion of the whole and is good for categorical data

• - can be confusing if there’s too many categories as it can be hard to discern the relative size of each slice in comparison to the whole

Pros and cons of bar charts

• + where the height of bar is proportional to value it represents

• + effective for emphasising differences between groups

• - can become cluttered if too many categories are included

pros and cons of histograms

• + good for finding information about how data is skewed or symmetric

• used for quantitative continuous data over a continuous interval

• - it is very sensitive to the bin size chosen and it can be hard to compare between data sets.

pros and cons of scatterplots

• + shows the relationship between 2 variables

• - they don’t prove causation

• - it can get visually confusing if two many data points are clustered in one region, covering each other.

pros and cons of box and whisker plot

• + good for large data sets

• + good for comparison

• - can’t identify mode

• - doesn’t show shape of data