M8. Let's Talk About Accuracy vs Precision | Ask Lex PH Academy | YouTubeToText
YouTube Transcript: M8. Let's Talk About Accuracy vs Precision
Skip watching entire videos - get the full transcript, search for keywords, and copy with one click.
Share:
Video Transcript
hi welcome back in this section we will continue
continue
studying important characteristics of data
data
using statistical concepts such as accuracy
accuracy
and precision and why is it important
for us to know these concepts
as we the lean six sigma before we go to
the details
let's focus first on a recap of what are
measures of central tendency
in statistics central tendency measures
are measures that are used to compare
the center of a data set
as against to a reference point measures
of central tendency include
mean median and mode min talks about the
arithmetic average
of all the data values as we know it the average
average
however median this talks about the
midpoint of the data values
while mode it talks about the most
frequently according data value
now let's take an example to put context
say we have a data set
with data values 1 1
1 3 5 and 9. let's take the average
so let's take the sum of all the data
values and divide it to the number of
values that we have summed
that gives us a value of 3.33
the mean of this data set is 3.33
now let's go to the median for us to
calculate median
we have to arrange the data set from
lowest to highest
and take the midpoint because the total
number of data
in our set is even which is 6
therefore the midpoint is located in the
two middle values
now we have to take the average of the
two values which is 1
plus 3 all over 2 which give us a median
of 2.0 in data sets where the total
number of data values
is add the midpoint is certain now let's
take the mode
because the value one is the most
frequently occurring value
therefore mode is one now these are the
three central tendency measures that we
are using
in statistics most of the time we use
the average
but in cases that there are outliers we
rather use the median
this is because median is not
susceptible to bias
due to outliers or unusual observations
if you're using continuous data most of
the time
you will be using mean and regen and if
you're using discrete data
mode is more appropriate so this is the
central tendency measure
now let's talk about measures of
dispersion in statistics
this person describes the
characteristics of data and how far they
are from each other
common measures are range standard division
division
and variance range is the difference
between the maximum value and the
minimum value
standard deviation is the distance of
the values from the mean
or the average distance of each values
from the mean
and variance is the squared value of the
standard deviation
now let's put context by giving an example
example
let's use the same data set from the
measures of central tendency
range maximum minus minimum therefore
9 minus 1 which is 8. standard deviation
using our formula or using excel it will
give us
3.2 while variance as the square of the
standard deviation
we can get 10.24 now this will give us
an idea
of how disperse our data values are from
each other
now let's talk about accuracy and precision
precision
accuracy is based on the measures of
central tendency
it gives us an idea of how far is the center
center
of the data set from the target while precision
precision
it is guided by the concepts of measures
of dispersion
how dispersed are the data values from
each other
in linsix sigma what we want to see is a
process that can give us an output that
is accurate
and precise take note that we use
and not or the picture on the upper left
of this slide gives us the ideal state
where there is high accuracy
and high precision while on the upper right
right
we can see that there is high precision
but there is low accuracy
the data values are not dispersed they
are close to each other
but they are far away from the target
the lower part of the picture
on the left side it gives us the idea of
high accuracy but low precision
data values are around the target but
they are
a bit dispersed compared from the
previous exercises or examples
therefore there is low precision and the
last picture on the lower right side
gives us the worst case scenario wherein
there is low accuracy
and there is low precision in lean six
sigma what we want to achieve
is a process that can give us an
accurate and precise output
remember as accuracy increases
the more conforming products we can
produce but not only accuracy is important
important
as well as precision as we may know quality
quality
is inversely proportional to variability
and dispersion and precision is the same
with variability
so as we have more variability in the process
process
the lower the potential quality level
will be these are the important concepts
of accuracy and precision
as we take them into our lean six sigma journey
Click on any text or timestamp to jump to that moment in the video
Share:
Most transcripts ready in under 5 seconds
One-Click Copy125+ LanguagesSearch ContentJump to Timestamps
Paste YouTube URL
Enter any YouTube video link to get the full transcript
Transcript Extraction Form
Most transcripts ready in under 5 seconds
Get Our Chrome Extension
Get transcripts instantly without leaving YouTube. Install our Chrome extension for one-click access to any video's transcript directly on the watch page.
