final exam Flashcards
Interquartile range formula
Q3-Q1
outliers equations
Q1-1.5(IQR)=lower bound
Q3+1.5(IQR)=higher bound
When are dot plots best?
For small sets of data with values that are close together
Measure of center and variation for data with no outliers
Mean and standard deviation
z-score formula
x-x bar/s
how to find frequency distribution
Highest value-lowest value/class number
how to find percentiles
number/100 x number of data values
how to find percentile corresponding to a number
number of values below number+0.5/number of data values x 100
how to determine a probability distribution
sum of values=1, values are all between 0 and 1
p(x=a)
binompdf(n,p,a)
p(x< or equal to a)
binomcdf(n,p,a)
p(x<a)
binomcdf(n,p,a-1)
p(x>a)
1-binomcdf(n,p,a)
p(x> or equal to a)
1-binomcdf(n,p,a-1)
mean for binomials
n x p
standard deviation for binomials
square root of n x p x q
uniform distribtion
x-axis: a and b, y-axis: 1/b-a
p(x<c>c) or p(c<x<d)</c>
number in between x times 1/b-a
p(a<x<b) in-between
normalcdf(a,b, mean, standard deviation)
p(x<b>b) small tail</b>
0.5-normalcdf(a,b, mean, sd)
p(x<b>b) big tail</b>
0.5+normalcdf(a,b,mean,sd)
area of normal distribution
x=invnorm(alpha, mean, standard deviation)
two small tails
1-normalcdf(a,b,mean,sd)
distribution for z scores
mean=0, standard deviation=1
Empirical rule
percentage of values that lie within an interval estimate in a normal distribution: 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively
Chebyshev’s theorem
if the mean (μ) and standard deviation (σ) of a data set are known, then at least 75% of the data points should lie within two standard deviations of the mean (μ ± 2σ)
Sample size is larger or smaller if you increase the confidence level or decrease the margin of error
Larger
Level of confidence increases as…
the size of the interval increases
Relative frequency
sum of all values=1
Cumulative frequency
how much has accumulated up to that class
Cumulative relative frequency
Cf/total
