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## AP STATS EXAM REVIEW

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**Chapter 2**Chapter 1 Chapter 3 and Chapter 4 Chapter 5 Chapter 6 100 100 100 100 100 200 200 200 200 200 300 300 300 300 300 400 400 400 400 400 500 500 500 500 500**These are the three terms you should always discuss when**describing a set of data Categories**Shape, center, spread**Categories**These four graphs may only be used for quantitative data**Categories**Stemplot, boxplot, histogram, and dotplot**Categories**This distribution shape has the mean greater than the median**Categories**Skewed right**Categories**Chapter 1 400 Points**This is the formula for finding outliers in a set of data Categories**Chapter 1 400 Points**Q1 -1.5IQR and Q3 + 1.5IQR Categories**Chapter 1 500 Points**the formula for this measurement that is used to describe a set of data is to subtract the mean from each of the numbers in the data set, square that difference, find the sum of the differences, and then take the square root of the sums Categories**Chapter 1 500 Points**Standard deviation Categories**Chapter 2 100 Points**This is what the 95 means in the 68-95-99.7 rule Categories**Chapter 2 100 Points**95% of the data is within 2 standard deviations Categories**Chapter 2 200 Points**this is the formula for the z score of a mean Categories**Chapter 2 200 Points**(x-bar – mean)/standard devation Categories**Chapter 2 300 Points**This is the area to the left of a z-score of 2.34 Categories**Chapter 2 300 Points**Categories**Chapter 2 400 Points**Probability for a two sided Z-score is 13.1%, this is the z-score Categories**Chapter 2 400 Points**1.52 Categories**Chapter 2 500 Points**In 2000, the scores of men on the math SAT followed a normal distribution with mean 533 and standard deviation 115. This is the percentage of men who scored 750 or better Categories**Chapter 2 500 Points**2.94% Categories**Chapter 3/4 100 Points**This is the equation for the LSRL Categories**Chapter ¾ 100 Points**Yhat = a + bx Categories**Chapter 3/4 200 Points**This point is on all LSRL Categories**Chapter 3/4 200 Points**(xbar, ybar) Categories**Chapter 3/4 300 Points**This is the formula for slope Categories**Chapter 3/4 300 Points**B = r(sy/sx) Categories**Chapter 3/4 400 Points**Formula for a residual Categories**Chapter 3/4 400 Points**Observed – predicated (y – yhat) Categories**Chapter 3/4500 Points**This transformation uses the log of the y’s Categories**Chapter 3/4 500 Points**exponential Categories**Chapter 5 100 Points**A deliberate grouping of subjects in an experiment based on a characteristic that you suspect will affect responses to treatments in a systematic way Categories**Chapter 5 100 Points**blocking Categories**Chapter 5 200 Points**Term that refers to the fact that neither the subjects nor experimenters know who is receiving what treatment Categories**Chapter 5 200 Points**double blind Categories**Chapter 5 300 Points**A variable that is not able to be separated from the two variables being studied Categories**Chapter 5 300 Points**confounding Categories**Chapter 5 400 Points**Term that has same meaning as blocking, but is used in a survey, not an experiment Categories**Chapter 5 400 Points**Stratifying Categories**Chapter 5 500 Points**Well-designed experiments have these three principles Categories**Chapter 5 500 Points**Control, randomization, replication Categories**Chapter 6 100 Points**P(A intersection B) = 0 is this property Categories**Chapter 6 100 Points**Mutually exclusive Categories**Chapter 6 200 Points**This means that the occurrence or non-occurrence of one event does not effect the probability that the other event occurs Categories**Chapter 6 200 Points**Independent Categories**Chapter 6 300 Points**Formula for the union of two events Categories**Chapter 6 300 Points**p(A B) = P(A) + P(B) – P(AB) Categories**Chapter 6 400 Points**Two alternate approaches to finding probability Categories**Chapter 6 400 Points**Tree Diagrams or Venn Diagrams Categories