Rosalinda Rataczak AP Statistics terms for Chapters 1-7

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(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
(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
(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)
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