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LCCC Statistics

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Term
Definition
Statistics   The science or study of data  
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Data   Info gained from counting, measurements, surveys/response, or experiments  
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Population   everyone or everything you wish to study  
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Census   a study of the entire population  
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Sample   a part, portion, or subset of population  
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Parameter   any number that describes a population  
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N   population size ( number of data in a population)  
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Statistic   any number that describes a sample  
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n   sample size ( number of data in sample)  
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Descriptive Statistics   organizing, displaying, and analyzing (calculations)  
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Inferential Statistics   make a decision/conclusion based on a sample  
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Qualitative data   describes, labels, categories, ranking  
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Nominal   No meaningful order to categories  
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Ordinal   meaningful order to categories  
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Quantitative data   numerical data (except description)  
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Discrete   any countable data  
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Continuous   any form of measurement, any value on the number line, interval data  
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Interval level of measurement   meaningful differences between values, 0 is a placeholder  
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Ratio level of measurement   meaningful ratio/ ("twice as many"), 0 is nothing or none  
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Statistical Study Goal   make a decision about the population based on a sample  
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Steps to Design a Study   1) decide the population 2) best method for data collection 3) Collect Data 4) Summarize and analyze data 5) Make a conclusion 6) Consider any possible errors  
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Observational Study   watch and record, do not interact/implement change  
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Perform an experiment   part of the sample is changed and then you compare  
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Simulation   a physical/ computer imitation of real life  
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Survey   interview and record responses ( in person, mail, paper, telephone, email)  
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Center   value that indicates where the MIDDLE of data set is  
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Variation   a measure of the amount the data values VARY  
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Distribution   shape/spread of data over a range  
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Frequency Distribution Table   table that lists all categories/ classes/ intervals and the COUNT of data values in each class  
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Class   interval used to split up/organize data values into a frequency distribution  
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frequency of class   number of data values in that class  
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n=sample size   total number of data values in study  
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range   highest data value - lowest data value  
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lower class limit   smallest possible number that belongs to each class  
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upper class limit   largest possible number that belongs to each class  
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class width   difference between 2 consecutive lower class limits  
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Frequency Histogram   touching bar graph, x=class midpoints, y=frequency  
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Frequency Polygon   line graph that represents continuous change, x=class midpoints, y=frequency, need a midpoint less and higher than table midpoints for frequency of 0  
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Relative Frequency Histogram   touching bar graph, x= class midpoints, y= relative frequency  
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Ogive   line graph with no closure, x= class boundaries, y= cumulative frequency  
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Class Midpoint   (lower class limit + its upper class limit)/2  
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relative frequency   (class frequency/ total frequency)x100%  
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cumulative frequency   class frequency + all previous frequencies  
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class boundary   the average between a upper limit and the next lower limit  
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Dot Plot   each data value represented as a point (dot) above a horizontal axis, multiple data values are represented by stacked dots  
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Pareto Chart   bar graph ( not touching) with decreasing frequencies from left to right  
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Range   R=max value - mininum value  
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Deviation   difference of value and mean of data set ( dev= x- mean)  
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Variance   average of the squared deviations from the mean ( take each deviation and square it)  
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Standard Deviation   square root of the variance ((E(x-m)^2)/N) sample=same but n-1  
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Empirical Rule   68% of data= 1 stdev., 95% of data= 2 stdev, 99.7% of data= 3 stdev  
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Empirical Rule Unusual   more than 2 standard deviations away from the mean ( outlier??)  
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Empirical Rule Very Unusual   more than 3 standard deviations away from the mean (outlier***)  
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First Quartile (Q1)   25% of the data is at or below ( median of lower half)  
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Second Quartile (Q2)   50% of the data is at or below (median)  
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Third Quartile (Q3)   75% of the data is at or below ( median of lower half)  
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Interquartile Range (IQR)   Q3-Q1  
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Finding Outlier fences   step= IGR(1.5), Q1- step, Q3 + step  
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Five number summary   min, Q1, Q2, Q3, max  
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Percentile   breaks a data set up into 100 equal parts (Pk=Kth percentile)  
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Standard Score (z-score)   z=(x-mean/st.dev.)  
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Quartile   splits the data into 4 equal parts  
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probability experiment   action/trial through which specific results are obtained  
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outcome   result of a single trial  
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sample space (S)   set of all possible outcomes  
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event(E)   subset(part) of a sample space  
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simple event   event with single outcome  
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compound event   more than one outcome  
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fundamental counting principle   if one event can occur in "m" ways and a second event can occur in "n" ways, the # of ways both events occur in sequence is:  
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subjective probability   result from intuition, educated guess, estimates  
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empirical/statistical probability   based on observations P(E)=freq. of E./total freq.  
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classical/theoretical probability   # of outcome in E(# favorable)/total # of possible outcomes(# in S)  
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law of large numbers   as an experiment is repeated over and over, empirical probability of an event approaches the theoretical(actual) probability of the event  
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properties of probability   1) 0<=P(E)<=1 prob. is never negative prob. is never bigger than 1 2)P(E)=1=certain event 3)P(E)=0=impossible event EP(S)=1  
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complement of event E   P(not E)=P(E^1) P(not E)=1-P(E)  
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conditional probability   probability of B given that A has already occurred P(B|A)=P(B and A)/P(A)  
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independent events   one event does NOT affect the probability of the occurrence of the other event P(B|A)=P(B)  
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dependent events   the first affects the second conditional  
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multiplication rule   probability that 2 events occur in sequence P(A and B)=P(A and then B) independent=P(A and B)=P(A)*P(B) dependent=P(A and B)=P(A)*P(B|A)  
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mutually exclusive   A and B can't occur at the same time  
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addition rule   not mutually exclusive=P(A)+P(B)-P(A and B) mutually exclusive=P(A)+P(B)  
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n factorial   n!=n(n-1)(n-2)...3*2*1 3!=3*2*1=6  
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permutation   an arrangement of "n" objects, taking "n" objects and putting them in order n!  
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permutations of n objects taken r at a time   "n" objects=group of "r" objects, order matters!!! nPr=n!/(n-r)!  
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distinguishable permutations   ordered arrangement, repeats!, n!/(n1!n2!...nk!)  
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Combinations   a part of the whole group, order does not matter, nCr=n!/(r!(n-r)!)  
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