3.3 z-scores and boxplot Flashcards
z-score equation
(x-“mu” or population mean)/sigma or standard deviation
z-score can be negative or positive
negative means below mean and positive means above mean
use the empirical rule to interpret z-scores with bell-shaped populations
because z-score is the number of standard deviations from the mean
z-score and the empirical rule
z= -1/1 is 68% z=-2/2 is 95% z=-3/3 is almost all
find the value x with a given z-score (answer is n 3 decimal places)
x=”mu”+zsigma (use GEMS so zsigma goes first)
outliers
the value that is considerably larger or considerably smaller than most of the values in a data set
interquartile range
a measuring method to detect outliers. Is Q3-Q1
interquartile range equation
IQR=Q3-Q1 (subtracting the first quartile from the third quartile)
IQR method
most frequent method used to detect outliers.
Steps for IQR method
- find the first quartile Q1 and third quartile Q3. 2. Compute the interquartile range: IQR-Q3-Q1. 3. Compute the outlier boundaries. These boundaries are the cutoff point for determining outliers
Lower Outlier Boundary
Q1-1.5(IQR)
Upper Outlier Boundary
Q3+1.5(IQR)
Finding Interquartile Range from the calculator
Using the 1-Vars States menu you can find Q3 and Q1, then subtract to find what the range is. Then put them in the lower and upper outlier boundary. Any number above or below is an outlier.
boxplots
can determine skewness in a data set. outliers are plotted seperately using x’s.
The boxes are the Q1, median and Q3
The whiskers are the smallest and largest data set within the lower and upper and lower outlier boundaries