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14 Cards in this Set
 Front
 Back
descriptive stats

gathering of data; often expressed through polls, surveys, charts


statistical inference/generalizations

this involves drawing conclusions about the larger picture; predicting the future


population

the entire group that is being studied;


sample

a subgroup of teh population that is being studied; conclusions are drawn about the data from this sample as it is supposed to be rep. of the population


random sample

 a sampling technique to held make samples unbaised; yet, it is not always rep. of the populatoin


summation notation

look at notes


parameter

any numerical value describing a population;
 often described using greek lettes 

statistic

any numerical value describing a sample;
 often denoted by english letters; often these are used to estimate for the parametere as the ral parameter is often too large to work with  note: if several samples are taken, they will not all be the same yet they should be close to each other 

measures of central tendency

 what are they? any measure used to locate teh center of a collection of data
1. mean  avg. used most often 2. median  number in the middle (line up the numbers and find the middle one; even= find avg bt 2 middle ones; in large samples: teh middle value is the number of values plus one divided by 2 3. mode  most often; can be bimodial or na 

measures of variation

 this is testing how spread out the data is; and how it compares to the mean
 3 types: 1. range: biggest value  smallest 2. variance: involves finding the deviation from the mean; where the deviation of an observation from teh mean is gotten by subtracting the mean from the observation; denoted by sigma sq. ; thiis number is almost always postive, but it can be zero if all the data is the same as mean; this number is sq of the std 3. standard deviation (std)  used for a measure of variability in some units of data, we take the sq. root of the variance to get this number ; always use the postiivve sq roott 

note:

 use the same unit throughout problem


chebshev's theorem

 for any collection of values, at least the fraction 11/k2 of the observations; know three 3 numbers: 2, 3, 4; for 2: (either at least 3/4 or at most 1/4); for 3: (at least 8/9 , at most 1/9); for 4: (at least 15/16, at most 1/16)
 note: the more spread out the data, the larger the length of the inverval and the sigma; 

z scores

 used to do a comparision for ranking purposes from 2 groups
 formula: z = x'u'/ sigma  it is an observation (x) from a population with a mean and std that has a zscore or a zvalue  this gives the number of std away from teh mean  z is just a number, does not use units 

frequency distribution

 a table, which is the result of grouping data into classes or intervals and finding out the number of observations in eac. class
 steps: 1. decide number of class intervals req. (usually given) 2. determine the range 3. divide the range by number of intervals to = class width  always whole number so round up 4/5. get class limits and class boundaries 6. tally and record frequencies for each class voc: * class limits: the upper and lower  usally the same iterval, and they don't over lap, whole numbers * class boundaries: overlap, and go out .5 from teh class limits * class width: the upper class boundary minus the lower class boundary; it stays constant through a problem; should be one more than the class limit differnce; always a whole number 