deviation.
Standard Error of the Mean
The standard deviation of the distribution of the sample means, σ
√ .
n
Standard Normal Distribution
A continuous random variable (RV) X~N (0, 1) .. When X follows the standard normal
distribution, it is often noted as Z~N (0, 1).
Statistic
A numerical characteristic of the sample. A statistic estimates the corresponding population
parameter. For example, the average number of full-time students in a 7:30 a.m. class for this
term (statistic) is an estimate for the average number of full-time students in any class this term
(parameter).
Student’s-t Distribution
Investigated and reported by William S. Gossett in 1908 and published under the pseudonym
Student. The major characteristics of the random variable (RV) are:
• It is continuous and assumes any real values.
• The pdf is symmetrical about its mean of zero. However, it is more spread out and flatter at
the apex than the normal distribution.
• It approaches the standard normal distribution as n gets larger.
• There is a "family" of t distributions: every representative of the family is completely
defined by the number of degrees of freedom which is one less than the number of data.
Student-t Distribution
T Tree Diagram
The useful visual representation of a sample space and events in the form of a “tree” with
branches marked by possible outcomes simultaneously with associated probabilities
(frequencies, relative frequencies).
Type 1 Error
The decision is to reject the Null hypothesis when, in fact, the Null hypothesis is true.
Type 2 Error
The decision is to not reject the Null hypothesis when, in fact, the Null hypothesis is false.
U Uniform Distribution
A continuous random variable (RV) that has equally likely outcomes over the domain,
a < x < b. Often referred as the Rectangular distribution because the graph of the pdf has the
form of a rectangle. Notation: X~U (a, b). The mean is µ = a+b and the standard deviation is
2
σ =
(b−a)2 The probability density function is f (X) = 1 for a < x < b or a ≤ x ≤ b. The
12
b−a
cumulative distribution is P (X ≤ x) = x−a .
b−a
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GLOSSARY
679
V Variable (Random Variable)
A characteristic of interest in a population being studied. Common notation for variables are
upper case Latin letters X, Y, Z,...; common notation for a specific value from the domain (set of
all possible values of a variable) are lower case Latin letters x, y, z,.... For example, if X is the
number of children in a family, then x represents a specific integer 0, 1, 2, 3, .... Variables in
statistics differ from variables in intermediate algebra in two following ways.
• The domain of the random variable (RV) is not necessarily a numerical set; the domain may
be expressed in words; for example, if X = hair color then the domain is {black, blond, gray,
green, orange}.
• We can tell what specific value x of the Random Variable X takes only after performing the
experiment.
Variance
Mean of the squared deviations from the mean. Square of the standard deviation. For a set of
data, a deviation can be represented as x − x where x is a value of the data and x is the sample
mean. The sample variance is equal to the sum of the squares of the deviations divided by the
difference of the sample size and 1.
Venn Diagram
The visual representation of a sample space and events in the form of circles or ovals showing
their intersections.
Z z-score
The linear transformation of the form z = x− µ . If this transformation is applied to any normal
σ
distribution X~N ( µ, σ) , the result is the standard normal distribution Z~N (0, 1). If this
transformation is applied to any specific value x of the RV with mean µ and standard deviation
σ , the result is called the z-score of x. Z-scores allow us to compare data that are normally
distributed but scaled differently.
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680
INDEX
Index of Keywords and Terms
Keywords are listed by the section with that keyword (page numbers are in parentheses). Keywords
do not necessarily appear in the text of the page. They are merely associated with that section. Ex.
apples, § 1.1 (1) Terms are referenced by the page they appear on. Ex. apples, 1
"
"hypothesis testing.", 377
condition, § 3.3(124)
conditional, § 3.2(122), § 3.11(144), 230
A A AND B, § 3.2(122)
conditional probability, 123
A OR B, § 3.2(122)
confidence interval, 328, 336
accessibility, § (5)
confidence intervals, 339, 377
addition, § 3.4(127)
confidence level, 329, 339
additional, § (5)
contingency, § 3.5(131), § 3.9(141)
adoption, § (5)
contingency table, 131, 481
alternate hypothesis, § 13.2(584), § 13.3(585)
continuity correction factor, 299
ANOVA, § 13.1(583), § 13.2(584), § 13.3(585),
Continuous, § 1.5(18), 18, § 1.10(38), § 1.12(42),
§ 13.4(589), § 13.5(593), § 14.5.4(649)
§ 5.1(221), § 5.2(223), § 5.3(226), § 5.4(233),
answer, § 1.8(33)
§ 5.5(239), § 5.6(240), § 5.7(243), § 5.8(245),
appendix, § 14.3(632)
§ 5.9(251), § 5.10(254), § 14.4.2(637)
area, § 5.2(223)
continuous random variable, 233
article, § 14.4.3(640)
convenience, § 1.10(38)
average, § 1.4(16), § 4.3(169)
Convenience sampling, § 1.6(24)
B
Counting, § 1.5(18)
bar, § 2.4(63)
critical value, 267
Bernoulli, § 4.5(172), § 4.15(192)
cumulative, § 1.9(33), § 1.10(38), § 1.12(42),
Bernoulli Trial, 173
§ 1.13(50)
binomial, § 4.4(172), § 4.5(172), § 4.9(183),
cumulative distribution function (CDF), 234
§ 4.15(192)
Cumulative relative frequency, 34
binomial distribution, 381
curve, § 13.4(589)
binomial probability distribution, 173
bivariate, § 14.4.5(643)
D Data, § 1.1(13), § 1.2(13), 13, § 1.4(16), 17,
box, § 2.5(68), § 2.11(90), § 2.13(95), § 5.10(254)
§ 1.5(18), § 1.7(31), § 1.10(38), § 1.11(39),
boxes, § 2.4(63)
§ 1.12(42), § 1.13(50), § 2.1(59), § 2.2(59),
C
§ 2.4(63), § 14.3(632), § 14.4.1(635),
cards, § 4.17(205)
§ 14.4.5(643), § 14.5.2(647)
categorical, § 1.4(16)
degrees of freedom, 336, § 13.3(585),
center, § 2.6(71)
§ 13.4(589), § 13.5(593)
central, § 14.4.2(637)
degrees of freedom (df), 431
Central Limit Theorem, § 7.2(290), § 7.3(293),
descriptive, § 1.2(13), § 2.2(59), § 2.3(60),
§ 7.10(318), 387
§ 2.6(71), § 2.11(90), § 2.13(95)
chance, § 3.2(122), § 3.3(124)
deviation, § 2.11(90), § 2.13(95)
chi, § 11.4(474), § 11.5(481)
diagram, § 3.6(134), § 3.7(135)
Chi-Square, § 11.7(488), § 14.5.3(648), § 15(671)
dice, § 4.18(209)
CLT, 294
Discrete, § 1.5(18), 18, § 1.10(38), § 1.12(42),
cluster, § 1.10(38), § 1.14(52)
§ 4.1(167), § 4.2(168), § 4.3(169), § 4.4(172),
cluster sample, § 1.6(24)
§ 4.5(172), § 4.6(175), § 4.7(178), § 4.8(180),
collaborative, § (1), § (5)
§ 4.9(183), § 4.10(185), § 4.15(192), § 4.16(202),
collection, 1
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INDEX
681
§ 4.17(205), § 4.18(209)
§ 14.4.1(635), § 14.4.2(637), § 14.4.3(640),
display, § 2.2(59)
§ 14.4.4(642), § 14.4.5(643), § 14.5.1(646),
distribution, § 4.1(167), § 4.2(168), § 4.5(172),
§ 14.5.2(647), § 14.5.3(648), § 14.5.4(649),
§ 4.6(175), § 4.7(178), § 4.8(180), § 4.10(185),
§ 14.6(650), § 14.7(651), § 14.8(656)
§ 4.16(202), § 4.17(205), § 4.18(209), § 5.1(221),
elementary statistics, § (11), § 2.13(95)
§ 5.2(223), § 5.3(226), § 5.4(233), § 5.5(239),
empirical, § 5.10(254)
§ 5.6(240), § 5.7(243), § 5.8(245), § 5.9(251),
equally likely, § 3.2(122), 122
§ 5.10(254), § 11.5(481), § 14.4.2(637),
error bound for a population mean, 329, 337
§ 14.5.3(648)
error bound„ 339
distribution is binomial, 339
event, § 3.2(122), 122, § 3.11(144)
dot plot, § 1.2(13)
exclusive, § 3.3(124), § 3.10(143), § 3.11(144)
exercise, § 1.14(52), § 2.13(95), § 3.9(141),
E elementary, § (1), § (5), § (9), § 2.1(59),
§ 3.13(157), § 4.15(192), § 4.16(202), § 4.17(205),
§ 2.2(59), § 2.3(60), § 2.6(71), § 2.7(76),
§ 4.18(209), § 5.6(240), § 5.7(243), § 5.9(251),
§ 2.8(79), § 2.9(81), § 2.10(89), § 2.11(90),
§ 5.10(254)
§ 2.12(93), § 2.14(112), § 3.4(127), § 3.5(131),
exercises, § 3.12(155)
§ 3.6(134), § 3.7(135), § 3.8(140), § 3.9(141),
expected, § 4.3(169)
§ 3.10(143), § 3.11(144), § 3.12(155), § 3.13(157),
expected value, 169
§ 4.1(167), § 4.2(168), § 4.3(169), § 4.4(172),
experiment, § 3.2(122), 122, § 4.1(167),
§ 4.5(172), § 4.6(175), § 4.7(178), § 4.8(180),
§ 4.5(172), § 4.7(178), § 4.8(180), § 4.17(205),
§ 4.9(183), § 4.10(185), § 4.12(188), § 4.13(189),
§ 4.18(209)
§ 4.14(191), § 4.15(192), § 4.16(202), § 4.17(205),
exponential, § 5.1(221), § 5.4(233), 233,
§ 4.18(209), § 5.1(221), § 5.2(223), § 5.3(226),
§ 5.5(239), § 5.7(243)
§ 5.4(233), § 5.5(239), § 5.6(240), § 5.7(243),
exponential distribution, 297
§ 5.8(245), § 5.9(251), § 5.10(254), § 6.1(261),
§ 6.2(262), § 6.3(263), § 6.4(265), § 6.5(265),
F f, § 15(671)
§ 6.6(269), § 6.7(270), § 6.8(272), § 6.9(278),
F Distribution, § 13.1(583), § 13.2(584),
§ 6.10(280), § 6.11(283), § 7.1(289), § 7.4(294),
§ 13.3(585), § 13.4(589), § 13.5(593),
§ 7.5(301), § 7.6(302), § 7.7(305), § 7.8(312),
§ 14.5.4(649)
§ 7.9(314), § 8.1(327), § 8.2(329), § 8.3(336),
F Ratio, § 13.3(585)
§ 8.4(339), § 8.5(344), § 8.6(345), § 8.7(347),
fit, § 11.4(474)
§ 8.8(349), § 8.9(351), § 8.10(361), § 8.11(364),
formula, § 3.8(140), § 4.9(183), § 5.5(239)
§ 8.12(367), § 8.13(369), § 9.1(377), § 9.2(378),
frequency, § 1.9(33), 34, § 1.10(38), § 1.11(39),
§ 9.3(379), § 9.4(380), § 9.5(381), § 9.6(381),
§ 1.12(42), § 1.13(50), § 1.14(52), 63, § 2.11(90),
§ 9.7(382), § 9.8(383), § 9.9(383), § 9.10(385),
§ 2.13(95), § 3.2(122)
§ 9.11(385), § 9.12(396), § 9.13(397), § 9.14(399),
function, § 4.2(168), § 4.4(172), § 4.5(172),
§ 9.15(401), § 9.16(403), § 9.17(416), § 9.18(419),
§ 4.6(175), § 4.7(178), § 4.9(183), § 4.16(202),
§ 10.1(429), § 10.2(430), § 10.3(433), § 10.4(435),
§ 5.1(221), § 5.3(226), § 5.4(233), § 5.6(240),
§ 10.5(437), § 10.6(442), § 10.7(443), § 10.8(445),
§ 5.7(243), § 5.8(245), § 5.9(251)
§ 10.9(447), § 10.10(459), § 10.11(461),
functions, § 5.2(223)
§ 11.1(471), § 11.2(472), § 11.3(472), § 11.4(474),
§ 11.5(481), § 11.8(488), § 11.9(491),
G geometric, § 4.4(172), § 4.6(175), § 4.9(183),
§ 11.10(492), § 11.11(494), § 11.12(496),
§ 4.15(192)
§ 11.13(498), § 11.14(507), § 11.15(511),
good, § 11.4(474)
§ 11.16(516), § 12.1(523), § 12.2(523),
Goodness-of-Fit, § 11.7(488)
§ 12.3(525), § 12.4(526), § 12.5(528), § 12.6(534),
graph, § 2.2(59), § 2.3(60), § 5.1(221), § 5.6(240),
§ 12.7(536), § 12.8(541), § 12.9(541),
§ 5.7(243), § 5.8(245), § 14.4.1(635)
§ 12.10(548), § 12.11(551), § 12.12(552),
guide, § (5)
§ 12.13(555), § 12.14(571), § 12.15(574),
H histogram, § 2.4(63), § 2.11(90), § 2.13(95),
§ 12.16(576), § 13.6(596), § 13.7(597),
§ 5.10(254)
§ 13.8(599), § 13.9(604), § 13.10(608),
Homework, § 1.12(42), § 2.11(90), § 2.13(95),
§ 14.1(613), § 14.2(622), § 14.3(632),
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682
INDEX
§ 3.9(141), § 3.12(155), § 3.13(157), § 4.15(192),
Normal, § 15(671)
§ 4.16(202), § 4.17(205), § 4.18(209), § 5.6(240),
Normal Approximation to the Binomial, 299
§ 5.7(243), § 5.8(245), § 5.9(251), § 5.10(254)
normal distribution, 336, 339, 380, § 13.5(593)
homogeneity, § 11.6(485), § 11.7(488)
normally distributed, 290, 293, 381
hypergeometric, § 4.4(172), § 4.7(178),
null hypothesis, 381, 382, 383, § 13.2(584),
§ 4.15(192)
§ 13.3(585)
hypergeometric probability, 178
numbers, § 4.3(169)
hypergeometrical, § 4.9(183)
numerical, § 1.4(16)
hypotheses, 378
hypothesis, § 14.4.3(640), § 14.4.4(642),
O One-Way Analysis of Variance, § 13.1(583),
§ 14.5.1(646), § 14.5.2(647)
§ 13.2(584), § 13.3(585)
hypothesis test, 381, 383, 385, § 13.2(584),
One-Way ANOVA, 584, § 14.5.4(649)
§ 13.3(585)
outcome, § 3.2(122), 122, § 3.3(124)
outlier, 60, 72
I
independence, § 11.5(481), § 11.7(488)
outliers, 71, 541
independent, § 3.3(124), 124, 128, § 3.10(143),
§ 3.11(144)
P p-value, 382, 383, 383, 383, 385
inferential, § 1.2(13)
pair, § 14.5.2(647)
inferential statistics, 327
parameter, § 1.4(16), 17, § 1.10(38), 327
interquartile range, 71
PDF, § 4.2(168)
Introduction, § 1.1(13), § 3.1(121), § 4.1(167)
percentile, § 2.6(71), § 2.11(90), § 2.13(95)
IQR, § 2.6(71)
percentiles, 71
plot, § 2.11(90), § 2.13(95), § 5.10(254)
K key terms, § 3.2(122)
point estimate, 327
Poisson, § 4.4(172), § 4.8(180), § 4.9(183),
L lab, § 1.14(52), § 3.13(157), § 4.17(205),
§ 4.15(192)
§ 4.18(209), § 5.10(254), § 7.10(318),
Poisson probability distribution, 180
§ 14.4.1(635), § 14.4.2(637), § 14.4.5(643)
population, § 1.4(16), 16, 31, § 1.10(38),
large, § 4.3(169)
§ 2.13(95), § 5.9(251), § 13.2(584), § 13.3(585)
law, § 4.3(169)
populations, § 13.5(593)
Law of Large Numbers, 294
practice, § 1.11(39), § 2.11(90), § 3.9(141),
leaf, § 2.3(60)
§ 3.10(143), § 3.12(155), § 4.16(202), § 5.6(240),
likelihood, § 1.3(16)
§ 5.7(243), § 5.9(251)
limit, § 14.4.2(637)
probability, § 1.3(16), 16, § 1.10(38), § 3.1(121),
location, § 2.6(71)
§ 3.2(122), 122, § 3.3(124), § 3.4(127), § 3.5(131),
long term, § 3.2(122)
§ 3.6(134), § 3.7(135), § 3.8(140), § 3.9(141),
long-term, § 3.13(157), § 4.3(169)
§ 3.10(143), § 3.11(144), § 3.12(155), § 3.13(157),
M
§ 4.2(168), § 4.3(169), § 4.4(172), § 4.5(172),
mean, 17, § 2.6(71), 76, § 2.11(90), § 2.13(95),
§ 4.6(175), § 4.7(178), § 4.8(180), § 4.9(183),
§ 4.3(169), 169, 290, 292, 295, § 14.5.1(646)
§ 4.10(185), § 4.16(202), § 4.17(205), § 4.18(209),
means, § 14.5.2(647)
§ 5.1(221), § 5.2(223), § 5.3(226), § 5.5(239),
means square, § 13.3(585)
§ 5.6(240), § 5.7(243), § 5.9(251)
measurement, § 1.7(31)
probability distribution function, 168
Measuring, § 1.5(18)
problem, § 2.13(95), § 4.15(192), § 14.4.4(642)
median, § 2.1(59), § 2.5(68), 68, § 2.6(71), 76,
project, § 14.4.1(635), § 14.4.2(637),
§ 2.11(90), § 2.13(95)
§ 14.4.5(643)
mode, § 2.6(71), 77, § 2.11(90), § 2.13(95)
proportion, § 1.4(16), 17, § 14.5.1(646),
modules, 1
§ 14.5.2(647)
multiplication, § 3.4(127)
mutually, § 3.3(124), § 3.10(143), § 3.11(144)
Q Qualitative, § 1.5(18), § 1.10(38), § 1.12(42)
mutually exclusive, 125, 128
Qualitative data, 18
N
Quantitative, § 1.5(18), § 1.10(38), § 1.12(42)
nonsampling errors, § 1.6(24)
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INDEX
683
Quantitative data, 18
standard error, 430
quartile, § 2.6(71), § 2.11(90), § 2.13(95)
standard error of the mean., 291
quartiles, § 2.5(68), 68, 71
standard normal distribution, 262
statistic, § 1.4(16), 17, § 1.10(38), 79
R random, § 1.3(16), § 1.10(38), § 1.12(42),
statistics, § (1), § (5), § (9), § 1.1(13), § 1.2(13),
§ 1.14(52), § 4.1(167), § 4.2(168), § 4.3(169),
13, § 1.3(16), § 1.5(18), § 1.6(24), § 1.7(31),
§ 4.4(172), § 4.5(172), § 4.6(175), § 4.7(178),
§ 1.8(33), § 1.9(33), § 1.10(38), § 1.11(39),
§ 4.8(180), § 4.9(183), § 4.10(185), § 4.15(192),
§ 1.12(42), § 1.13(50), § 1.14(52), § 2.1(59),
§ 4.16(202), § 4.17(205), § 4.18(209), § 5.1(221),
§ 2.2(59), § 2.3(60), § 2.6(71), § 2.7(76),
§ 5.2(223), § 5.3(226), § 5.4(233), § 5.5(239),
§ 2.8(79), § 2.9(81), § 2.10(89), § 2.11(90),
§ 5.6(240), § 5.7(243), § 5.8(245), § 5.9(251)
§ 2.12(93), § 2.13(95), § 2.14(112), § 3.1(121),
random sampling, § 1.6(24)
§ 3.2(122), § 3.3(124), § 3.4(127), § 3.5(131),
random variable, 167, 431, 434
§ 3.6(134), § 3.7(135), § 3.8(140), § 3.9(141),
randomness, § 1.3(16)
§ 3.10(143), § 3.11(144), § 3.12(155), § 3.13(157),
relative, § 1.9(33), § 1.10(38), § 1.12(42),
§ 4.1(167), § 4.2(168), § 4.3(169), § 4.4(172),
§ 1.13(50), § 2.13(95), § 3.2(122)
§ 4.5(172), § 4.6(175), § 4.7(178), § 4.8(180),
relative frequency, 34, 63
§ 4.9(183), § 4.10(185), § 4.12(188), § 4.13(189),
replacement, § 1.10(38), § 3.13(157)
§ 4.14(191), § 4.15(192), § 4.16(202), § 4.17(205),
representative, § 1.4(16)
§ 4.18(209), § 5.1(221), § 5.2(223), § 5.3(226),
resources, § (5)
§ 5.4(233), § 5.5(239), § 5.6(240), § 5.7(243),
review, § 3.12(155), § 4.16(202), § 5.9(251)
§ 5.8(245), § 5.9(251), § 5.10(254), § 6.1(261),
round, § 1.8(33)
§ 6.2(262), § 6.3(263), § 6.4(265), § 6.5(265),
rounding, § 1.8(33)
§ 6.6(269), § 6.7(270), § 6.8(272), § 6.9(278),
rule, § 3.4(127)
§ 6.10(280), § 6.11(283), § 7.1(289), § 7.2(290),
S
§ 7.3(293), § 7.4(294), § 7.5(301), § 7.6(302),
sample, § 1.4(16), 16, § 1.6(24), § 1.7(31),
§ 7.7(305), § 7.8(312), § 7.9(314), § 7.10(318),
§ 1.10(38), § 1.12(42), § 1.14(52), § 2.13(95),
§ 8.1(327), § 8.2(329), § 8.3(336), § 8.4(339),
§ 13.2(584), § 13.3(585), § 13.5(593),
§ 8.5(344), § 8.6(345), § 8.7(347), § 8.8(349),
§ 14.4.5(643)
§ 8.9(351), § 8.10(361), § 8.11(364), § 8.12(367),
Sample Means, § 7.2(290)
§ 8.13(369), § 9.1(377), § 9.2(378), § 9.3(379),
sample space, § 3.2(122), 122, 127, 136
§ 9.4(380), § 9.5(381), § 9.6(381), § 9.7(382),
samples, 31
§ 9.8(383), § 9.9(383), § 9.10(385), § 9.11(385),
Sampling, § 1.1(13), § 1.4(16), 16, § 1.6(24),
§ 9.12(396), § 9.13(397), § 9.14(399), § 9.15(401),
§ 1.7(31), § 1.10(38), § 1.11(39), § 1.12(42),
§ 9.16(403), § 9.17(416), § 9.18(419), § 10.1(429),
§ 1.13(50), § 1.14(52)
§ 10.2(430), § 10.3(433), § 10.4(435), § 10.5(437),
sampling distribution, 78
§ 10.6(442), § 10.7(443), § 10.8(445), § 10.9(447),
sampling errors, § 1.6(24)
§ 10.10(459), § 10.11(461), § 11.1(471),
sampling variability of a statistic, 83
§ 11.2(472), § 11.3(472), § 11.4(474), § 11.5(481),
set, § 14.3(632)
§ 11.8(488), § 11.9(491), § 11.10(492),
sheet, § 14.5.1(646), § 14.5.2(647), § 14.5.3(648)
§ 11.11(494), § 11.12(496), § 11.13(498),
simple, § 1.10(38)
§ 11.14(507), § 11.15(511), § 11.16(516),
simple random sampling, § 1.6(24)
§ 12.1(523), § 12.2(523), § 12.3(525), § 12.4(526),
single, § 14.5.1(646)
§ 12.5(528), § 12.6(534), § 12.7(536), § 12.8(541),
Sir Ronald Fisher, § 13.3(585)
§ 12.9(541), § 12.10(548), § 12.11(551),
size, § 1.7(31)
§ 12.12(552), § 12.13(555), § 12.14(571),
skew, § 2.6(71), § 13.4(589)
§ 12.15(574), § 12.16(576), § 13.1(583),
solution, § 14.5.1(646), § 14.5.2(647),
§ 13.2(584), § 13.3(585), § 13.4(589), § 13.5(593),
§ 14.5.3(648), § 14.5.4(649)
§ 13.6(596), § 13.7(597), § 13.8(599), § 13.9(604),
spread, § 2.6(71)
§ 13.10(608), § 14.1(613), § 14.2(622),
square, § 11.4(474), § 11.5(481)
§ 14.3(632), § 14.4.1(635), § 14.4.2(637),
standard, § 2.11(90), § 2.13(95)
§ 14.4.3(640), § 14.4.4(642), § 14.4.5(643),
standard deviation, 81, 336, 380, 381, 382, 385
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684
INDEX
§ 14.5.1(646), § 14.5.2(647), § 14.5.3(648),
Type I error, 379, 383
§ 14.5.4(649), § 14.6(650), § 14.7(651),
Type II error, 379
§ 14.8(656)
stem, § 2.3(60)
U uniform, § 5.1(221), § 5.3(226), § 5.5(239),
stemplot, § 2.3(60)
§ 5.6(240), § 5.10(254)
stratified, § 1.10(38), § 1.14(52)
uniform distribution, 226
stratified sample, § 1.6(24)
univariate, § 14.4.1(635), § 14.4.5(643)
Student’s-t distribution, 336, 381
usage, § (5)
student’s-t distribution., 380