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78 Cards in this Set
 Front
 Back
statistics

science of collecting, summarizing, analyzing, and interpreting data.


descriptive statistics

summarizing data


inferential statistics

analyzing and interpreting


probablility

determining relative frequency of events


deductive thought process

known facts imply new facts


inductive thought process

observations infer properties


frequency distribitution

2 column table including values of the variable and its frequency


stem and leaf plot

displays distribution of values of quantitative variables.


skewness

direction of longest tail


histogram

graphs values of quantitative variables on xaxis and frequency on Yaxis


Sample mean (formula)

X/=Exi/n


variance (symbol)

s^2, distance from mean


sample Standard deviation (symbol)

s, square root of variance


scatterplot

plot elements as a point on 2d axis


linear correlation coefficient

stregnth of relationship between x and y (r)


probability experiment

random process, distinct outcomes


outcome

result of probability experiment


sample space

S, set of all possible outcomes of probability experiment


event

collection of outcomes from S


null event

no outcomes


simple event

one outcome


union event (U)

or


Intersection event ()

and


mutually exclusive

no outcomes in common


formula for equally likely outcomes

P(A)=# of outcomes in A/# of outcomes in S


Independent events

knowing whether one event occurs doesn't change the probability that the other event occurs


complement rule (formula)

P(A)=1P(A')


addition rule (formula)

P(AUB)=P(A)+P(B)


multiplication rule (formula)

P(AB)=P(A)P(B)


condtional probability rule (formula)

P(BlA)=P(AB)/P(A)


random variable

assign numbers to each outcome of a probability experiment.


discrete random variable

random variable that takes finite number of values


probability distribution of a discrete random variable

assigns probabilities to each value of a drv


mean of a discrete random variable (formula)

E(all y)yp(y)


continuous random variable

random variable whose value can be any number in 1 or more intervals


probability density funtion of a continuous random variable

f(y) likelihood


standard normal random variable (symbol)

Z, tablezx


standardizing random variable (formula)

z=Yu/e


population

large set of elements of interest


parameter

characteristic of a population


sample

draw random with replacement from a population


statistic

characteristic of a sample


point estimator

random process used to obtain guess for a parameter


estimate

number obtained from point estimator


unbiased estimator

statistic used to estimate a parameter if the mean of its sampling distribution is equal to its parameter


sampling distribution X/(formula)

N(u,e/SRn)


interval estimator

point estimator + MoE


MoE

table value x standard error


hypothesis testing

decision making process between two alternative statements about a population


type 1 error

rejecting true null hypothesis


type 2 error

failing to reject false null hypothesis


level of significance

compares severity of errors


test statistic

describes Ho


rejection region

values of the test statistic that reject Ho and support Ha


S.v. of T.s.

computed value of the test statistic using data collected


pvalue

probablity of test statistic being more supportive of Ha


critical value

cut off between rejection region and acceptance region


independent random samples

random samples taken from each popuation with none of the elements in either sample related to any element in other samples


pooled estimator

weighted average of 2 sample variances


sampling distribution X/(formula)

N(u,e/SRn)


interval estimator

point estimator + MoE


MoE

table value x standard error


hypothesis testing

decision making process between two alternative statements about a population


type 1 error

rejecting true null hypothesis


type 2 error

failing to reject false null hypothesis


level of significance

compares severity of errors


test statistic

describes Ho


rejection region

values of the test statistic that reject Ho and support Ha


S.v. of T.s.

computed value of the test statistic using data collected


pvalue

probablity of test statistic being more supportive of Ha


critical value

cut off between rejection region and acceptance region


independent random samples

random samples taken from each popuation with none of the elements in either sample related to any element in other samples


pooled estimator

weighted average of 2 sample variances


response variable

random variable whose value is determined by a random process


explanatory variable

variable controlled by experimenter


goals of regression analysis

determine relationship between the explanatory variable and response variable and find the best fit line


outlier (formula)

Q11.5 x IQR, Q3+1.5 x IQR


sample proportion (formula)

p^, x1+x2+x3.../n
