39 terms

(6.1) Mean of a discrete random variable

∑xipi

(6.1) Standard deviation of a discrete random variable

√(∑(xi-µx)²/n)

or, put the values in L1 and the probabilities in L2 and do Stat, Calc, 1-Var Stats, L1, L2

or, put the values in L1 and the probabilities in L2 and do Stat, Calc, 1-Var Stats, L1, L2

(6.1) Variance of a discrete random variable

∑pi(xi-µx)²

(1.3) Outlier in a distribution

an observation that falls more than 1.5xIQR above Q₃ or below Q₁

(5.3) Independent events (in probability)

two events for which the occurrence of one event has no effect on the chance that the other event will happen - P(A|B)=P(A) and P(B|A)=P(B)

(3.1) Correlation coefficient = r

measures the strength and direction of the linear relationship between two quantitative variables

(3.2) Outlier in a regression

an observation that lies outside the overall pattern of the other observations. Points that are outliers in the y direction but not the x direction of a scatterplot have large residuals. Points that are outliers in the x direction but not the y direction may not have large residuals, but may be influential observations.

(6.1) Random variable

a numerical outcome of a random phenomenon

(7.1) Parameter

a number that describes some characteristic of the population

(6.3) Requirements for a binomial setting

Binary - two possible outcomes for each trial, "success" or "failure"

Independent - each trial is independent from the previous one

Number - the number of trials executed must be fixed in advance

Same - the probability of success is the same for each trial

Independent - each trial is independent from the previous one

Number - the number of trials executed must be fixed in advance

Same - the probability of success is the same for each trial

(7.1) Sampling distribution of a statistic

the distribution of values taken by the statistic in all possible samples of the same size from the same population

(7.2) Requirements for inference

SRS, n≤1/10N

(7.3) Mean of the sampling distribution of xbar

µ

(7.3) Standard deviation of the sampling distribution of xbar

σ/√n

(7.3) Requirements for Normality of the sampling distribution of xbar

Normal population or n≥30

(7.2) Mean of the sampling distribution of phat

p

(7.2) Standard deviation of the sampling distribution of phat

√(pq/n)

(7.2) Requirements for Normality of the sampling distribution of phat

np≥10, nq≥10

(7.?) Mean of the sampling distribution of khat

np

(7.?) Standard deviation of the sampling distribution of khat

√(npq)

(7.?) Requirements for Normality of the sampling distribution of khat

np≥10, nq≥10

(2.1) Density curve

a curve describing a distribution that is always on or above the x-axis, has an area of 1 below it, and for which the area under the curve from x=a to x=b is the proportion of all observations on the interval a to b

(6.2) Independent random variables

If knowing whether any even involving X alone has occurred tells us nothing about the occurrence of any event involving Y alone, then X and Y are __________

(3.2) Coefficient of determination = r²

measures the percent of variation in the values of y that is accounted for by the least-squares regression line of y on x

(3.2) r²=

1-SSE/SST (where SSE=∑(residuals)² and SST=∑(yi-ybar)²)

(3.2) Influential observation in a regression

an observation in a regression whose removal would markedly change the result of the calculation. Points that are outliers in the x direction of a scatterplot are often influential for the least-squares regression line.

(4.1) Simple random sample (SRS)

a sample consisting of n individuals from the population chosen in such a way that every set of n individuals has an equal chance of being the sample selected

(7.1) Statistic

a number that describes some characteristic of a sample

(2.1) z-score with z isolated

z=(x-µ)/σ

(2.1) z-score with x isolated

x=zσ+μ

(3.1) formula for finding the correlation coefficient without using the regression on your calculator

r=1/(n-1)Σzxzy

(?) Cumulative relative frequency

The probability (as a percent) that the outcome is a certain value or less; percentile.

(?) Simpson's paradox

A situation in which there is a lurking variable such that the conclusion of the whole is contradicted when broken down to account for the lurking variable.

(6.3) formula for the binomial probability

n!/(k!(n-k)!)*p∧k*q^(n-k)

(?) General rule for probability of a union

P(AUB)=P(A)+P(B)-P(A∩B)

(?) Special rule for the probability of a union if mutually exclusive

If P(A∩B)=0, then P(AUB)=P(A)+P(B)

(?) General rule for the probability of an intersection

P(A∩B)=P(A)xP(B|A) or =P(B)xP(A|B)

(?) Special rule for the probability of an intersection if independent

P(A∩B)=P(A)xP(B)

(?) Conditional probability

P(A|B)=P(A∩B)/P(B) or P(B|A)=P(A∩B)/P(A)