intro to numerical measures Flashcards
3 numerical measures
-measure of location
-measure of variability
-measure of dist shape
measures of location
-mean media mode
-percentiles (quartiles, quantiles, tertiles, median
measure of variability
-range
-IQR
-variance
-standard deviation
measure of dust shape
skewness
do sample mean and population mean have same formulas
yes
n is
size of sample
N is the size of
population
problem with only using mean
influenced by extreme values
problems of mode
-poor measure if dist is flat (all have same frequency)
-not a great measure if data is continuous
when is mode helpful
if not discretet and few alternatives
percentile tells us
about how the data is spread over the interval from smallets to largest value
review of percentile
ook
quantiles
cut points that divide set of data into equal intervals
purpose of quantiles
summarize distribution and help understand the spread
quantiles is useful for
descending dist and comparing dist
descending distribution
allow you to see how data is spread and identify outliers + trends
comparing distribution
used to compare diff dataset dist
common types of quantiles
percentiles, quartiles, deciles, and tertiles
percentiles divide date into
100 equal parts
quartiles divide date into
4 equal parts (each is 25%)
deciles divide data into
10 equal parts (each 10%)
tertiles divide data into
Three equal parts (cut points are 33rd and 67th percentile)
IQR
diff between 3rd and 1st quartile (Q3-Q1)
IQR overcomes
dependency on ectreme values
IQR is the range
for the middle 50% of the data
problem with IQR
problem is it only takes 50% of voices where the other half may have important data
variance utilizes all
data
variance is based on
diff between value of each obersvation and mean
diff between each Xi and the mean is called
deivaiton about the mean
standard deviation
positive square root of variance
S denotes what for standard deviation
sample
omega denotes what for standard deviation
population
