# AP Stats: Chapter 2

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1. percentile implication
if someone scored at the 93rd percentile, that means that in the distribution, 93% of the people earned that score or less
2. how to calculate percentile from data
(number of scores below the score) / (total number of scores)
3. cumulative relative frequency graph
used to examine a location within a distribution. Groups the observations into equal-width classes, shows accumulating percent of observations as you move through the classes in increasing order
4. how to calculate relative frequency
(frequency)/(total frequencies) x100
5. how to calculate cumulative frequency
(frequency) + (frequencies below this frequency)
6. how to calculate cumulative relative frequency
(cumulative frequency)/(total frequencies)
7. cumulative relative frequency graph aka ogive
8. interpretation of cumulative relative frequency
percentage represents the amount of people at that class or lower
9. ogive
aka cumulative relative frequency graph
10. how to calculate z-scores
11. effect of adding or subtracting a constant
• adds a to the center and location (mean, median, quartiles, percentiles)
• does not affect shape or measures of spread (range, IQR, standard deviation)
12. effect of multiplying or dividing by a constant
• multiplies/divides measures of center and location by b (mean, median, quartiles, percentiles)
• multiplies/divides measures of spread by |b| (range, IQR, standard deviation)
• multiplies/divides the variance by b2
• does not change shape
13. density curve
• a curve that is always on or above the horizontal axis and has exactly 1 area underneath it
• describes the overall pattern of a distribution
14. median of a density curve
point with half the area under the curve to its left and  the remaining half of the area to its right, divides the area of the density curve in half
15. mean of a density curve
the point at which the curve would balance if made of solid material
16. normal distribution
• described by the normal density curve, specified by the mean and standard deviation N (μ, σ)
• mean is at the center of the symmetric normal curve, standard deviation is the distance from the center to the change-of-curvature points on each side
17. inflection point
point where the curve changes shape; where the curve changes from a right-side up U to an upside down U
18. common examples of normal distributions
• scores on tests taken by many people
• repeated careful measurement of same quantity
• characteristics of biological populations
19. 68-95-99.7 Rule
20. Chebyshev's inequality
in any distribution, the proportion of observations falling within k standard deviations of the mean is at least
21. standard normal distribution
normal distribution with a mean 0 and standard deviation 1
22. standard normal distribution
23. standard normal table
table of areas under the standard normal curve; table entry for each value z is the area to the left of z; shown in Table A
24. normal probability plot
25. normal probability plot
used to assess whether a data set follows a normal distribution
26. how to use a normal probability plot to tell if something is a normal distribution
• normal if points lie close to a straight line
• clear departures from normality indicate that the data is not normal
27. normal cdf
calculator function used to find the area of a normal distribution when you have the cutoff points
28. invnorm
calculator function used to find the associated cutoff points when you have the area
 Author: Gymnastxoxo17 ID: 240910 Card Set: AP Stats: Chapter 2 Updated: 2013-10-16 02:26:47 Tags: Modeling Data Distributions Folders: Description: s Show Answers: