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Elementary Statistics
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Individuals
objects described by a set of data
people, animals, things
Variable
any characteristic of an individual
can take different values for different individuals
Categorical Variable
places an individual into one of several groups or categories
Quantitative Variable
takes numerical values for which artihmetic operations like adding and averaging make sense
usually recorded in a unit of measurement
Distribution of a Variable
what values it takes and how often it takes these values
Distribution of a categorical Variable
lists categories and gives count or % of individuals who fall in each category
Roundoff error
don't point to mistakes but to effects of rounding off results
Pie Charts
show distribution of a categorical variable as pie slices
must include all the categories that make up the whole
use pie chart only when you want to emphasize each categories relation to whole
Bar graphs
represent each category as a bar
bar height shows category counts or %'s
can compare any set quantities measured in the same units
Histogram
Most common graph of the distribution of one quantitative variable
Shape of a distribuition
symmetric-right and left side are roughly mirror images
Skewed to the right-right side of histogram extends much farther than the left
Skewed to the left- left side of histogram extends much farther than the right
Center of a distribuition
midpoint of distribuition
Spread of a distribuition
The range of a distribuition between the smallest value to the largest
Stemplot
like a histogram turned on end using #'s
cannot chose classes they are given to you
preserves actual value of each observation
do not work well with large data sets
stems and leaves
Parts of a stemplot
stems-all but the final (rightmost) digit
leaf- the final digit
Split stems
double the # of stems when all the leaves would fall on just a few stems
each stem appears twice
0 to 4 go on upper stem, 5 to 9 go on lower stem
Timeplot
plots each observation of a variable against the time at which it was measured
Always put time on horizontal
always put variable you are measuring on vertical
Cycles
regular up and down movements in a timeplot
Trend
long term up or down movement over time
Time series data
change in one variable at a specific location over time
timeplot
Cross sectional data
displays a variable at many locations at the same time
Exploratory data analysis
using graphs and and numerical summaries to describe the variables in a data set and the relations among them
mean is not a resistant measure of center
mean is sensitive to a few extreme observations
also sensitive to skewed distribution without outliers pulled towards tail
Median M
midpoint of distribution
such that half the observations are smaller and half larger
five number summary
gives the smallest and largest as well the median and 1st and 3rd Q
Minimum Q1 M Q3 Maximum
Boxplot
central box spans Q1 andQ3
line in box marks median M
lines extend from box out to smallest and largest observations
best used for side by side comparison of more than one distribution
IQR
Interquartile range
distance between Q1 and Q3
IQR = Q3 - Q1
1.5 x IQR rule for outliers
call an observation an outlier if it is more than 1.5 x IQR above Q3 or below Q1
Author
ametzga
ID
230736
Card Set
Elementary Statistics
Description
Elementary Statistics
Updated
2013-09-04T03:29:07Z
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