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1. a. Houston Chronicle, Des Moines Register, Chicago There are no scores in the high 70's.
Tribune, Washington Post
b. Capital One, Campbell Soup, Merrill Lynch, 13: a 2 23 Stem units: 1.0
Prudential 3 2344567789 Leaf units: .10
c. Bill Jasper, Kay Reinke, Helen Ford, David Menendez. 4 01356889
d. 1.78, 2.44, 3.50, 3.04 5 00001 114455666789
4. a Inatampe of 100DVD plage, wha wet chances 6 | ooorz2zzza444seooresse9
that more than 20 need service while under warranty? B45555
What are the chances that none need service while still § 02255488
under warranty? 9 012233335666788
b. What proportion of all DVD players of this brand and lo | 2344455688
model will need service within the warranty period? 11 | 2335999
5. a, No, the relevant conceptual population is all scores of B 7
all students who participate in the SI in conjunction ;
with this particular statistics course. 14 | 36
b. The advantage of randomly allocating students to the 15 0035
two groups is that the two groups should then be fairly 16
comparable before the study. If the two groups perform 17
differently in the class, we might attribute this to the 1s | 9
treatments (SI and control). If it were left to students to
choose, stronger or more dedicated students might b. A representative value could be the median, 7.0.
gravitate toward SI, confounding the results. ¢. The data appear to be highly concentrated, except for
c. If all students were put in the treatment group there a few values on the positive side
would be no results with which to compare the d. No, there is skewness to the right, or positive
treatments skewness.
7. One could generate a simple random sample of all single The vals, 1B sppeane'tn be an outlier; being mate
: than two stem units from the previous value.
family homes in the city, or a stratified random sample
by taking a simple random sample from each of the ten 15, a, ———H—-——_
district neighborhoods. From each of the homes in the Relative
sample the necessary data would be collected. This Naaabar frequency
would be an enumerative study because there exists a -
finite, identifiable population of objects from which to nonconforming Frequency (Freq/60)
sample. 0 7 0.117
9. a. There could be several explanations for the variability 1 12 0.200
of the measurements. Among them could be measuring 2 13 0.217
error, (due to mechanical or technical changes across 3 14 0.233
measurements), recording error, differences in 4 6 0.100
weather conditions at time of measurements, etc. 3 3 0.050
b. This study involves a conceptual population. There is é 3 0.050
no sampling frame a ( ai
1. 61 034 8 1 0.017
6h 667899 1.001
71 00122244 Doesn't add exactly to | because relative
Th Stem = tens frequencies have been rounded
81 001111122344 Leaf = ones
8h 5557899
91 03
oh 58
814
--- Trang 828 ---
Chapter! 815
b. .917, 867, | ~.867 = .133 ——
¢. The center of the histogram is somewhere around bd. Class Freq Rel freq Density
2 or 3 and it shows that there is some positive —
skewness in the data. 0 < 50 8 0.08 0016
50-< 10013 0.13 0026
AEs Pes 100-< 1501 0.11 0022
© 242 150- < 200 21 0.21 0042
d. The histogram is very positively skewed. 200-< 300 26 0.26 0026
300-< 40012 0.12 0012
19. a. The number of subdivisions having no cul-de-sacs is, 400- < 500 4 0.04 “0004
17/47 = .362, or 36.2%. The proportion having at 500:
g - < 600 3 0.03 0003,
least one cul-de-sac is 30/47 = .638, or 63.8% 600. < 9002 ne “S000
i00 1.00
yr Count Percent
ie) EF 36.17 coe
1 22 46.81
2 6 12.77
. pe Class Freq Class Freq
5 1 2.13 10- < 20 8 Lie < 12 2
N=47 20- < 30 14 12 < 13 6
2362, .638 30- < 40 8 13-<14 7
40- < 50 4 14<15 9
OS 50- < 60 3 15-< 16 6
b. cad Count Percent 60- < 70 2 1.6-< 1.7 4
TT 70- < 80 a 17 < 18 5
° 13 27.66 40 18-< 1.9 1
1 ts 23.40 40
2 3 6.38 a
3 7 14.89
4 5 10.64
The original distribution is positively skewed
5 3 6.38
The transformation creates a much more symmetric,
6 3 6.38
mound-shaped histogram.
8 2 4.26 a
N=47 :
25. a. Class interval Freq Rel. Freq.
-894, .830
0-< 50 9 0.18
2 a —§ A 50-< 100 19 0.38
Class Freq Rel freq 100-< 150 ul 0.22
i 150-< 200 4 0.08
O=5 100 at O71 200-< 250 2 0.04
100- < 200 32 0.32 b50-< 400 5 004