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dot plots, stem-leaf plot, box-whiskers plot, outliers, cumulative frequency plot
Bilibili youtube
Bilibili
youtube
what other ways of representing data how other visualizations differentiate themselves in different angles and uses (brilliant and intuitive effort!)
what other ways of representing data
how other visualizations differentiate themselves in different angles and uses (brilliant and intuitive effort!)
replace histogram's bars with dots, a dot stands for an individual data point) frequency = height of a bar = number of dots in the bar's position see visualization of dot plots but still missing details of individual data values
replace histogram's bars with dots, a dot stands for an individual data point)
frequency = height of a bar = number of dots in the bar's position
see visualization of dot plots
but still missing details of individual data values
replace bar positions with stems 0s, 10s, 20s... 80s replace dots with numbers, ranging from 0 lower to 9 higher both overall frequency and individual data values are portrayed on the graph
replace bar positions with stems 0s, 10s, 20s... 80s
replace dots with numbers, ranging from 0 lower to 9 higher
both overall frequency and individual data values are portrayed on the graph
use median and spread based on median IQR to represent all the dataset central tendency median as middle point Q1 = first half's median Q3 = second half's median IQR = Q3 - Q1 = middle half lower fence from middle median extend 1.5 IQR to the left upper fence from middle median extend 1.5 IQR to the right minimum the actual smallest data point inside left fence maximum the actual largest data point within upper fence outliers the actual data points smaller than lower fence the actual data points larger than upper fence how densely distributed from Q1 to median, same amount of data points widely spreaded from median to Q3, same amount of data points narrowly spreaded compared with left outliers are much less frequent, but do occur
use median and spread based on median IQR to represent all the dataset
central tendency
lower fence
upper fence
minimum
maximum
outliers
how densely distributed
outliers are much less frequent, but do occur
keep the interested a few very high rents in the neighborhood you are interested in throw away the non-interested a football star sneak into your local neighborhood team or a typo (making 5 into 500) in the dataset when collected if not sure, use pre-existing rules to decide data points, beyond lower and upper fence, are outliers, should be removed
keep the interested
throw away the non-interested
if not sure, use pre-existing rules to decide
this one does not tell you anything useful or meaningful
imagine it yourself :)
stats visualizations are everywhere visualizations are only as good as the data behind many of them could be mistaken or misleading always ask questions about them
stats visualizations are everywhere
visualizations are only as good as the data behind
many of them could be mistaken or misleading
always ask questions about them
The text was updated successfully, but these errors were encountered:
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Plots, Outliers, and Justin Timberlake - Data visualization part 2
key words
Video links
Key Questions
Interesting points
dot plots
Stem-Leaf Plot
Box-Whisckers plot
when to or not throw away an outlier
When not to use box-whiskers plot
cumulative frequency plot
Be critical on the charts
The text was updated successfully, but these errors were encountered: