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40 Cards in this Set

  • Front
  • Back
statistics
the art and science of collection, analysing, presenting, and interpreting the data.
data
the facts and figures collected. analyzed, and summarized for presentation and interpretation
elements
entities of which data is collected. ex. AB stock`
variables
charecteristics of interest for the elements. ex. NYSE, OTC
observations
measurments of each variable for every element
qualitative
names and labels
quantitative
numbers, numeric
existing source for obtaining data
internet, census, employers, etc.
experimental study for obtaining data
test and control
observational study for obtaining data
survey, observations
statistical inferance
using a sample to generalize about a population
frequency table
table showing the number for frequency of items in each of several non overlapping classes
n=
sample size
relative frequency
proportion of occurance. freq/n. sum of relative frequencies should equal 1
percent frequency
percent of occurance. rel. freq x 100
bar graph
qualitative data. bars do not touch
histogram
quantitative data. bars touch eachother.
pie chart degrees for a sector=
rel. freq. x 360
how many classes in quantitative data?
5-20
width of each class in quantitative data?
high value - low value / # of classes
sum.
-
x
sample mean. ∑x/n
µ
population mean. ∑x/N
n
sample size
N
population size
mean
average
median
middle number
mode
most frequently occuring number. bimodal, multimodal
i
index for percentile. (p/100)n.

if i has a deciamal, bump it up.

if i is whole, average of i and i+1.
range
highest # - Lowest #
interquartile range (IQR)
Q3-Q1
variance
a # that describes how much the data varries from the mean
2
s
sample varience.
- 2
∑(x-x) / n-1
2
σ
population variance.
2
∑(x-µ) /N
standard deviation
amount an observation varries from the mean
s
sample standard deviation.

2
s=✓s
σ
population Standard Deviation.

2
σ=✓σ
z
z score.
_
x-x/s

x minus mean divided by standard deviation
chebyshev's therom
2
at least (1-(1/z )) of the data values must be within z standard deviations of the mean, where z is any value greater than 1.

at least 75% within z=2
89% within z=3
94% within z=4
emperical rule
symetrical distribution of data in the shape of a bell.

68% within 1 sd
95% within 2 sd
almost all within 3 sd