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AP Statistics
Test 1 Syllabus
Chap. 1
qualitative/quantitative
population/sample
AP Statistics: Test 1 Syllabus1
1.11 ( After working this exercise, suppose that the categories
A, B, C, and D represent grades. Would it make sense to regard these as quantitive variables?) 1.12, 1.13, 1.15, 1.19–1.20,
1.25.
(2.1)
graphical displays
2.2, 2.4, 2.6, 2.10, 2.12.
qualitative vars.
(2.2)
graphical displays
2.18 , 2.20, 2.23 (for parts (a), (b) just make estimates; for part
(d) see page 49 for an understanding of “skewness”); 2.26
2.30 (use your TI-83 calculator), 2.31.
quantitative vars.
Introduction to M INITAB.
(2.4)
central tendency
2.44, 2.48, 2.50, 2.51, 2.52 , 2.53.
mean, median, mode
(2.5)
variance and
2.56, 2.62 , 2.63.
standard deviation
(2.6)
Interpreting variance:
Impirical Rule
2.70, 2.72 (also use your TI-83 calculator to create a
histogram—use sensible window settings!) Use M INITAB to
create a histogram.
1 All exercises in this batch are from our textbook, S TATISTICS , by James T. McClave and Terry Sincich, Eighth Edition, Prentice
Hall, 2000, ISBN 0-13-022329-8.
AP Statistics: Test 1 Syllabus, continued
1.11 ( 2.85 (do you really need the z-scores to do this one?),
2.89, 2.93 ,
(2.7)
relative standing
the “z-score”
P ROBLEM A: Refer to the graph on page 73 of the “normal
distribution” with mean µ and standard deviation σ. As we
have seen, a z-score of 1 approximately marks the upper 68
percentile, and a z-score of 0 marks the upper 50 percentile.
Would you say, therefore, that a x-score of 0.5 would mark
the upper 59 percentile? What about the score z = 1.5?
Roughly where (that is what z-score) would mark the upper
75 percentile?
P ROBLEM B: Assume that the variable x is sampled from a
normally distributed population. Find the (approximate) zscores which correspond to QL and QU . (Remember: in a normal population, the mean and median agree.)
2.97, 2.100 , 2.101
(2.8)
outliers;
box plots
P ROBLEM A: The authors say that a potential outlier is
a data value x such that either x < QL − (1.5)IQR or
x > QU + (1.5)IQR If we assume that the underlying population is normal, what are the z-scores corresponding to the
above?
P ROBLEM B: The authors say that an outlier is a data value x
such that either x < QL − (3.0)IQR or x > QU + (3.0)IQR. If
we assume that the underlying population is normal, what
are the corresponding z-scores?
P ROBLEM C: Input the EPA milage data (Table 2.3, page 30)
as a list variable on your TI-83.
(i) Give a picture of the box plot.
(ii) Give a picture of the histogram (Use the window values
Xmin=28, Xmax=48, Xscl=1, Ymin=-5, Ymax=35, Yscl=5.
(iii) Sketch the two graphs, superimposed on the same picture. (This can all be done very nicely on the TI-83 and
even more nicely on M INITAB)
(2.9)
bivariate data;
2.110, 2.111, 2.114.
scatterplots
(2.10)
bivariate data;
telling lies
‘EYECUE,” page 95. Don’t just follow the text’s instructions,
use your own judgement and imagination!