|
|
Absolute deviation, 绝对离差* ]0 \5 l5 r8 ~( T6 y% g) m) \
Absolute number, 绝对数( z3 c" y* n$ m0 h' R6 E
Absolute residuals, 绝对残差# S. a3 C% {9 {1 Q8 x- O! h
Acceleration array, 加速度立体阵) z1 a+ j& e0 n4 I, |, B+ |; J6 A
Acceleration in an arbitrary direction, 任意方向上的加速度
* E j* O) B0 V \Acceleration normal, 法向加速度' m- W# O. U# v, g: _. ^, }
Acceleration space dimension, 加速度空间的维数0 d3 O$ d$ L1 I. D7 |5 m" z
Acceleration tangential, 切向加速度
6 @6 }/ {- i% g# n+ h6 @1 u. oAcceleration vector, 加速度向量
0 i" h" o( \, nAcceptable hypothesis, 可接受假设
! S1 q- p: \, z* z3 k8 GAccumulation, 累积' ~7 u7 W8 Z# X7 y$ P0 y8 t7 c
Accuracy, 准确度0 o ?4 d+ M& {6 z
Actual frequency, 实际频数! N9 \+ ?4 E) m" c- H
Adaptive estimator, 自适应估计量5 t% W9 [/ m- v9 M. _, v
Addition, 相加
+ I" c. F, i- N- }Addition theorem, 加法定理
$ `' S' f) [% T) L4 R) G0 \0 |Additivity, 可加性
8 i! T0 ]0 L; D7 rAdjusted rate, 调整率
& ^1 C+ m# W- {8 [, i. _Adjusted value, 校正值5 Z. z# i; N J0 Q" c) [& Z. l
Admissible error, 容许误差' u5 X4 S6 Q9 A: N$ F6 [
Aggregation, 聚集性0 @, i5 o8 e5 j, n5 {' a a4 n
Alternative hypothesis, 备择假设
) a. v' J! S0 P, M2 a& PAmong groups, 组间
4 q" i* H$ d1 C- z$ r+ yAmounts, 总量0 f' C/ ?$ a6 `. \ w) Z
Analysis of correlation, 相关分析
% }3 ~/ V( O' L5 `Analysis of covariance, 协方差分析
6 F! F' W ]6 K0 xAnalysis of regression, 回归分析/ f& n8 g1 \: C/ {9 V8 Z" D
Analysis of time series, 时间序列分析- O0 b k! }: O
Analysis of variance, 方差分析0 q0 A, `) Q) k' K8 _ W7 J
Angular transformation, 角转换! o! C# E- A1 w) k
ANOVA （analysis of variance）, 方差分析7 h. @: O2 z/ i
ANOVA Models, 方差分析模型5 p3 u7 L& |! a; @% J0 j1 Q
Arcing, 弧/弧旋
% `$ a; \2 R: S, D) S" ]- ?, MArcsine transformation, 反正弦变换9 K K) }7 @+ D
Area under the curve, 曲线面积
" r n5 l- l. t$ S) ~4 XAREG , 评估从一个时间点到下一个时间点回归相关时的误差 # D5 O# C* f5 k
ARIMA, 季节和非季节性单变量模型的极大似然估计 ' ^3 U; ~; c3 o5 ?4 [3 r
Arithmetic grid paper, 算术格纸
H$ R- j! c; {Arithmetic mean, 算术平均数5 x3 G! S3 p6 k$ [7 T" w
Arrhenius relation, 艾恩尼斯关系
2 F% k8 [4 S3 V+ Q5 m% D$ [Assessing fit, 拟合的评估
# g1 X8 c9 q! H) {4 t8 E/ OAssociative laws, 结合律) [ m9 V; l; N9 ^ Q2 ~$ i# k H
Asymmetric distribution, 非对称分布6 a# t `8 h- x ]; a, |
Asymptotic bias, 渐近偏倚
8 H4 u8 {4 b3 A$ x0 H) W8 bAsymptotic efficiency, 渐近效率
9 Y( d9 S; J# x1 ]+ d" p( u8 lAsymptotic variance, 渐近方差
7 _: s n7 _3 X; E9 Z8 g1 g; {; JAttributable risk, 归因危险度
5 P, N! L8 Q1 J3 K! A( u- K2 b, IAttribute data, 属性资料. u; |" p' x, |; y; O5 ]6 B% b ]/ c7 {
Attribution, 属性
# j; o; _5 z6 G0 I: r" Y% L7 ^' fAutocorrelation, 自相关; [" }2 [" S7 R' W& I# X
Autocorrelation of residuals, 残差的自相关
9 ]+ I5 U- n3 l7 f: rAverage, 平均数
4 W* H3 z" G( Z& u4 z3 \/ @" P. vAverage confidence interval length, 平均置信区间长度" H! `9 j7 m4 g: d: \: ]
Average growth rate, 平均增长率
2 _6 ^! ~$ W C4 B, n" yBar chart, 条形图$ ?5 g1 p# m) u* q1 [* C6 }
Bar graph, 条形图
) e7 r3 V3 U7 R" x$ g5 j7 LBase period, 基期
' `/ T7 b: |/ X: J+ H, IBayes' theorem , Bayes定理* J9 P! Z8 H+ o7 H2 L9 E
Bell-shaped curve, 钟形曲线9 e' m1 @7 h( U# Y0 {
Bernoulli distribution, 伯努力分布1 X7 d- ?8 O1 D* v- ^7 ]; k; i
Best-trim estimator, 最好切尾估计量
1 s" a. b2 v9 J/ w# EBias, 偏性
0 K0 ^% @, _) y7 r8 oBinary logistic regression, 二元逻辑斯蒂回归2 u/ [4 n* j* R" d- o% v
Binomial distribution, 二项分布; G# y* v" L& ~. h$ d
Bisquare, 双平方( q+ [- i8 B# T4 x
Bivariate Correlate, 二变量相关/ ~0 y; F4 y+ n1 T: t2 U
Bivariate normal distribution, 双变量正态分布5 ~/ v3 M, I' J6 ~9 G
Bivariate normal population, 双变量正态总体- `# M W K; p3 A, l
Biweight interval, 双权区间
. T& K" I1 D( @' O( rBiweight M-estimator, 双权M估计量: h4 H. B1 Z' ]' v6 c l
Block, 区组/配伍组0 c( \0 l# k2 T8 s. h
BMDP(Biomedical computer programs), BMDP统计软件包
# z3 n& ^* Q! G! K% I9 xBoxplots, 箱线图/箱尾图( c& V: c2 |& L# I
Breakdown bound, 崩溃界/崩溃点' Y4 X+ B$ g- m/ W$ N6 N
Canonical correlation, 典型相关
* g1 j; \- _% r& \2 N* u& Q( I, d; UCaption, 纵标目
+ O f9 ~ W- [+ ~1 H: _Case-control study, 病例对照研究& z* A5 I3 Y ~. ^, C7 z$ D! n
Categorical variable, 分类变量8 J9 |* m) r( y( F9 i
Catenary, 悬链线3 Y9 _6 }- w+ T9 I: k$ X& u
Cauchy distribution, 柯西分布
& t" \4 c; n/ nCause-and-effect relationship, 因果关系- e5 z+ l: @4 \$ U
Cell, 单元
# D+ e- k3 a0 p" FCensoring, 终检
0 ~! i( m3 N) g2 TCenter of symmetry, 对称中心
6 \& s8 L' h. g- E; ECentering and scaling, 中心化和定标
! O# `% w3 A- C. D/ j9 \! m6 [: \1 U ]) mCentral tendency, 集中趋势: x7 O( Z) Z% ~* [: G* E
Central value, 中心值& @% d' ~; p. e
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测6 Z% C0 ]0 h* D0 A; C8 i: r
Chance, 机遇; J' m+ Z: M! [+ Z; L: c
Chance error, 随机误差
& l: q3 }+ p9 x/ @9 |4 sChance variable, 随机变量) V& N( Z* j: b8 r
Characteristic equation, 特征方程
+ u7 A p# R3 C* u0 QCharacteristic root, 特征根" @; p- ]& Q3 {
Characteristic vector, 特征向量6 W5 K/ o- W* p( ]& _( j
Chebshev criterion of fit, 拟合的切比雪夫准则1 V% Y4 k2 t( F m
Chernoff faces, 切尔诺夫脸谱图4 u9 t# Y' e, @* h& X1 X
Chi-square test, 卡方检验/χ2检验& m7 X8 D" P3 b& E
Choleskey decomposition, 乔洛斯基分解
5 K7 \# P5 L0 ~1 m% {Circle chart, 圆图
$ S/ X" a+ T0 x5 ?1 k' _) k7 u9 CClass interval, 组距
1 q/ c+ l5 e. G3 I% N; }9 uClass mid-value, 组中值
% T! {- n) A# J8 H& E# ^% hClass upper limit, 组上限
9 T9 p" w' E& y* OClassified variable, 分类变量8 P9 a$ r' U% Q/ r% z0 w4 U2 f0 w" N
Cluster analysis, 聚类分析
6 O4 q& P8 i5 {/ T: _: D$ }Cluster sampling, 整群抽样4 O) Y% {7 i0 L% Q
Code, 代码" e+ d j; b7 V$ T4 A2 ?1 W
Coded data, 编码数据
1 c6 f r8 ?* ^& a7 j3 oCoding, 编码
4 s" C% q+ p* `) M* CCoefficient of contingency, 列联系数; |6 c' t- P2 `! r% G7 b
Coefficient of determination, 决定系数2 c! u- w5 m& x1 }* ?/ ^, I6 A
Coefficient of multiple correlation, 多重相关系数
6 o6 ?8 V; g+ b% s" \Coefficient of partial correlation, 偏相关系数+ a" R' T& N$ E v; y* l$ e" f
Coefficient of production-moment correlation, 积差相关系数: j5 M0 ?# \; c4 J7 g z o& Q
Coefficient of rank correlation, 等级相关系数
) T+ r; T$ q; K- u; i$ t5 N* nCoefficient of regression, 回归系数
% l+ N( f! _8 A$ [3 M. DCoefficient of skewness, 偏度系数# ^7 C8 y, N8 u
Coefficient of variation, 变异系数
% r, ]/ l- O$ ?( L. C% OCohort study, 队列研究
4 U, y; h1 ]+ l- V( h* jColumn, 列
F. n v0 ?5 PColumn effect, 列效应
V" M7 K2 Z! R3 y0 B7 |! sColumn factor, 列因素
; Z) \0 C3 e; x/ R7 D4 C9 n. C6 \Combination pool, 合并
. a3 l$ ?% J8 V- PCombinative table, 组合表! N% N6 M3 u" h7 J/ u
Common factor, 共性因子
* k7 M! _% ~+ c3 i1 x) MCommon regression coefficient, 公共回归系数9 J4 b H+ T, A' W' p: m2 T, p
Common value, 共同值5 E1 s& p* \! G
Common variance, 公共方差- R N, d. Z! b( Q5 a. v% a' b
Common variation, 公共变异8 J* O* q9 E4 ]: r% p9 |
Communality variance, 共性方差
0 Y7 i; c7 q8 r& ~; J4 ?* l @Comparability, 可比性! T5 U0 I+ R7 y" ~3 b/ ~
Comparison of bathes, 批比较
& \ H% w& `/ ?4 G& wComparison value, 比较值
% n/ x7 o/ i; p$ jCompartment model, 分部模型
7 J( [7 _' G6 D- n; {( p& QCompassion, 伸缩) m3 E5 H8 v6 \- C: c
Complement of an event, 补事件
0 k0 H" r8 O% A, y) }Complete association, 完全正相关7 w2 ?5 {; w0 x+ W
Complete dissociation, 完全不相关8 Z/ K! U8 Z& {) a& `
Complete statistics, 完备统计量
8 t: v1 j. x) J2 [' vCompletely randomized design, 完全随机化设计
9 ]: J, F: P' I, Q9 x* W7 [3 HComposite event, 联合事件! H4 ^6 U; s6 O' t; i* L. V
Composite events, 复合事件
0 r7 I4 o) ^# D6 F% f% ZConcavity, 凹性
" _2 S" }0 k" X1 QConditional expectation, 条件期望+ U; s1 {5 Q/ P
Conditional likelihood, 条件似然& f: r7 ?+ h2 @3 M; x& ^4 ]* E) y
Conditional probability, 条件概率
# j1 ~8 a, [- ~/ F9 W. A3 yConditionally linear, 依条件线性
3 @$ J1 B: E3 A; @/ C- `- ?Confidence interval, 置信区间
( H% e- [) s; L6 p/ fConfidence limit, 置信限' b4 V3 |( d4 ~( d& n/ m8 ~9 r; Y
Confidence lower limit, 置信下限+ d8 M8 d4 }9 d* f2 z5 Y9 M
Confidence upper limit, 置信上限# o4 g* Z* p- s, _: l
Confirmatory Factor Analysis , 验证性因子分析
! X3 o" i6 Z( q( o2 g' \1 k" WConfirmatory research, 证实性实验研究2 Q+ }0 ~, W& A. H% S
Confounding factor, 混杂因素
M5 T6 Z( _3 D2 }Conjoint, 联合分析" j8 D U& q1 i
Consistency, 相合性
5 U/ P2 }& e) Q# V N3 w) N Y Q# IConsistency check, 一致性检验
* W+ n1 k( b3 f" @; t3 `: rConsistent asymptotically normal estimate, 相合渐近正态估计) V4 w: u& X4 i1 M x5 b |
Consistent estimate, 相合估计
% D) I# R& r' Y1 s/ P) m5 Z, ZConstrained nonlinear regression, 受约束非线性回归/ i" ~$ D _; \ Z
Constraint, 约束
/ T. b/ C$ q* F* M7 S4 G% cContaminated distribution, 污染分布. _+ N5 r; `6 A# a7 S4 Q
Contaminated Gausssian, 污染高斯分布
2 G- y( ^' N5 @; tContaminated normal distribution, 污染正态分布& ~! a1 i7 t) r, l p0 k
Contamination, 污染
M3 c0 c: i1 S) i" a1 k- X" HContamination model, 污染模型5 R& ^: x: W' \/ |
Contingency table, 列联表
( f$ P9 y. y. G4 }, b7 V' xContour, 边界线7 a6 u, ~; I u% N9 [- d6 \) Z
Contribution rate, 贡献率
z0 p* v& I" W# `( o% \6 DControl, 对照! _7 F& Q) Q P9 G) h- r2 n
Controlled experiments, 对照实验
4 D9 u) m) V9 k6 s. P4 jConventional depth, 常规深度
6 M' \" k: m2 W$ |, _: @Convolution, 卷积- P' ]' d Z% m3 V9 l6 ?9 T
Corrected factor, 校正因子& @& ^/ O0 F6 f& l
Corrected mean, 校正均值) [+ n* g& s/ y! `2 W9 C$ q1 q# R
Correction coefficient, 校正系数
9 o& D8 l- o4 m, V" r; J* h4 i: ?8 uCorrectness, 正确性9 m9 _& {% x8 K0 D' j: o
Correlation coefficient, 相关系数
9 \9 |+ P" O" p8 F% `1 n9 }0 c) UCorrelation index, 相关指数( y: f+ A0 x, v0 v0 }
Correspondence, 对应, [2 D! [0 I8 h& t& }, x( j
Counting, 计数
1 v, t7 k$ U- wCounts, 计数/频数
9 d7 Z3 H" i% S) s6 |3 ECovariance, 协方差
( G6 H: }% H: K& s* F- mCovariant, 共变
& v; ~8 B6 k# B J% x4 x) gCox Regression, Cox回归
, C" c4 D7 n1 _, W* H& i/ y9 s3 y# D' jCriteria for fitting, 拟合准则7 r! {$ h0 Z' D8 w$ d
Criteria of least squares, 最小二乘准则# L. ]- N6 L( {
Critical ratio, 临界比
4 M3 b6 C4 X- ?7 M0 gCritical region, 拒绝域# J. k! c2 \# K9 L. w% y1 p5 u
Critical value, 临界值
2 g0 \' V' |9 ], y) V4 ]Cross-over design, 交叉设计
' `) X, ~) K' v( E" {$ d/ J RCross-section analysis, 横断面分析
5 i0 ?% V" T) @, u# J8 k& }) |Cross-section survey, 横断面调查2 y, k/ V3 U& r( o6 T* K) `
Crosstabs , 交叉表
" n2 O [4 r: L3 D, q5 [Cross-tabulation table, 复合表# Y0 i. U2 J' a4 Z5 H+ Z
Cube root, 立方根. g9 K2 F- y. x" D" N0 s4 M" z
Cumulative distribution function, 分布函数+ H/ [/ D- x7 x& X; a) L$ b2 W
Cumulative probability, 累计概率8 _5 J3 m, ]) o R
Curvature, 曲率/弯曲
; o0 V0 \9 @; j8 |. f, RCurvature, 曲率' j5 ]5 _+ H5 k7 u$ H
Curve fit , 曲线拟和 ! K+ g' E$ J% \6 k4 ?# d; a" P
Curve fitting, 曲线拟合/ C: u0 V; o H+ P# d/ N
Curvilinear regression, 曲线回归2 `- {: y! R4 G, ~$ [& [9 q b
Curvilinear relation, 曲线关系9 n, E- g" a) c" n' P6 R
Cut-and-try method, 尝试法+ f$ H% k6 D! \. w W
Cycle, 周期
; n { p' R; gCyclist, 周期性
( O* l# ?) P3 T* a3 ]; ED test, D检验
! J+ E; n+ \1 `$ JData acquisition, 资料收集
& r1 A+ Y9 ~' k$ h0 s' }% cData bank, 数据库- }" Z* P# R# j, i
Data capacity, 数据容量
' G) ]+ Y/ f9 z6 C) H7 w% j1 eData deficiencies, 数据缺乏8 @3 y k8 r; C" p/ Z1 ?, Z7 w
Data handling, 数据处理# x# b+ |! r! d7 y* ~7 ~. j
Data manipulation, 数据处理
" J4 c* ?3 y5 u$ F9 M$ r, AData processing, 数据处理* ~; x5 }$ k! m& ^4 T& e* a7 d
Data reduction, 数据缩减
$ t7 p' ^- I& A* B( u# e; wData set, 数据集
( x6 P$ k' L6 u k; h% {0 PData sources, 数据来源1 A6 u7 w( ?- Y0 K+ J2 c
Data transformation, 数据变换( ~& x* o* A" W, k# c( x
Data validity, 数据有效性
: \1 l$ O- d ^. \Data-in, 数据输入! g9 O: d }( y' _5 A" a
Data-out, 数据输出7 s: u# _$ A. Z2 t
Dead time, 停滞期
5 p* v, I. r+ `/ CDegree of freedom, 自由度# a/ l1 d' p, S
Degree of precision, 精密度- [- {- Y6 ^ R5 f
Degree of reliability, 可靠性程度
6 k6 R$ T2 T9 a6 ]9 [# |2 QDegression, 递减
3 ]" |( X& c5 B; F5 ^9 d, a+ jDensity function, 密度函数, D2 e. {* A7 k5 W
Density of data points, 数据点的密度
2 D/ L. D0 l5 B, I& q" }3 wDependent variable, 应变量/依变量/因变量- Y3 E6 r+ G3 l3 X1 D
Dependent variable, 因变量 c5 w6 ^. \ X
Depth, 深度$ a: l( i g1 ~8 b) a
Derivative matrix, 导数矩阵
7 a2 @+ C, F V' `0 v: LDerivative-free methods, 无导数方法) K/ l- k4 n2 U2 d8 c2 @
Design, 设计
! ~# W; R% J: a2 dDeterminacy, 确定性
6 ^* r2 `! C1 ]% T% pDeterminant, 行列式
' L# T+ K! X5 Q; Z& e, i6 p& HDeterminant, 决定因素
$ q/ {+ _' G- cDeviation, 离差/ \% m/ v: d T' m/ @" |8 X
Deviation from average, 离均差( T( T( Q7 T1 b* J" i% q
Diagnostic plot, 诊断图, e8 {) Z, a$ Z# u# f8 x
Dichotomous variable, 二分变量" ~) K) n) q, `$ W: c9 g
Differential equation, 微分方程
2 T8 O! X2 Q. n9 TDirect standardization, 直接标准化法
8 Y$ o5 ~2 B9 Q5 ~3 `: _( FDiscrete variable, 离散型变量
' l9 r7 v' ^- PDISCRIMINANT, 判断 " A) [" {; f$ b; l3 t
Discriminant analysis, 判别分析0 z, d/ _9 j; O
Discriminant coefficient, 判别系数6 s) K* _ v6 B
Discriminant function, 判别值
" |! d8 ]& U% H% e4 S4 g8 M, ]& r FDispersion, 散布/分散度/ T8 [# O; K4 d1 i# m$ _
Disproportional, 不成比例的
' l2 w+ A$ f% H) B2 J$ S$ pDisproportionate sub-class numbers, 不成比例次级组含量6 _# d' @2 v) `
Distribution free, 分布无关性/免分布
* K- \ u- f, ?. p6 q- _& bDistribution shape, 分布形状
) L+ v W& V' Y P" {Distribution-free method, 任意分布法
& W& [4 R9 j* r3 K: ]) ODistributive laws, 分配律
" P j; U1 J- v( s* H1 f# _Disturbance, 随机扰动项7 q; D) \" ~' b0 y$ V
Dose response curve, 剂量反应曲线* r& W. B# _5 P6 x
Double blind method, 双盲法
4 J h3 m" H! z- ADouble blind trial, 双盲试验
" ` M/ O" A s; L' u; N1 ^1 }Double exponential distribution, 双指数分布5 T% Y% Q3 v2 t
Double logarithmic, 双对数4 p& A: D5 H0 S8 Q. s. ^# k
Downward rank, 降秩2 }+ j0 {2 S) e$ r# S
Dual-space plot, 对偶空间图2 k( ?8 b. g$ ~9 U( Z
DUD, 无导数方法
& m3 i3 R/ l* p/ pDuncan's new multiple range method, 新复极差法/Duncan新法
& |( D: Y# P) D2 [- ?Effect, 实验效应
& w4 B& f$ Y- z+ S) E) t8 eEigenvalue, 特征值
9 L1 E- U( k0 N' vEigenvector, 特征向量. _" A- W4 m5 F- W' b" |; C& ^% p
Ellipse, 椭圆: X/ u: m2 a9 s) } G" [
Empirical distribution, 经验分布
+ B' F* _# W9 J3 zEmpirical probability, 经验概率单位
8 j" f& N$ C' A. T- mEnumeration data, 计数资料
1 A+ j; H3 h6 n( e5 K2 o/ _Equal sun-class number, 相等次级组含量 [% P: h5 e8 c
Equally likely, 等可能5 g! Y: w5 X0 W9 `1 Q' ?. Z# ~# L( |
Equivariance, 同变性
& D0 `/ N5 @7 ^Error, 误差/错误
' t) u: D4 R! b c" O8 _7 d- ~7 iError of estimate, 估计误差1 c+ |: u# T: c5 a* v) y
Error type I, 第一类错误( l4 a7 n8 \$ S) E, e" N* q
Error type II, 第二类错误6 ?: s) h1 K: Z7 R
Estimand, 被估量! I0 X0 z1 \$ n0 T
Estimated error mean squares, 估计误差均方
8 |9 L3 S# z/ x* G6 l$ IEstimated error sum of squares, 估计误差平方和
1 [5 T1 }/ R, U, `Euclidean distance, 欧式距离
8 {4 v* K. i0 D* s, R% ^Event, 事件 }" `1 `. z6 h" u \$ g4 M
Event, 事件
: b6 y9 t; C1 P" b7 v" f3 n t5 `Exceptional data point, 异常数据点4 p5 v% k' \( C
Expectation plane, 期望平面
$ S+ l% S% B$ C7 W* ^: GExpectation surface, 期望曲面* E7 v3 ^" K4 h s1 K
Expected values, 期望值+ q4 l3 U% _, p& m
Experiment, 实验1 N; s9 F: Y: f$ a, J
Experimental sampling, 试验抽样; H0 s% O' m" y( \
Experimental unit, 试验单位* f. j5 h$ O9 U& p
Explanatory variable, 说明变量
, @/ j( o+ U4 m) u4 HExploratory data analysis, 探索性数据分析% P* Z/ x7 W! M. r' M! N
Explore Summarize, 探索-摘要3 e0 N- v% V+ o$ W- g5 e& t0 p
Exponential curve, 指数曲线
; n( K' o+ [; g8 i0 Y! U- @Exponential growth, 指数式增长$ g" j" H6 D7 T2 }8 I8 c4 W
EXSMOOTH, 指数平滑方法 + m1 i% ~. w$ R4 A% H* F* `- ^
Extended fit, 扩充拟合3 P. n& P( f& m1 k' b; B5 O& y
Extra parameter, 附加参数! n6 @9 p# G+ z9 C$ _+ V- c1 x! W
Extrapolation, 外推法! T: J7 ~+ K( v- S3 Z% b1 S
Extreme observation, 末端观测值+ u! {: W) D/ e4 z! m5 B' y- a4 N
Extremes, 极端值/极值 D: T- ^0 s; ]# U5 A: U5 J
F distribution, F分布 O& ~$ j3 H& S# p2 k: d8 [' X5 [
F test, F检验
! q+ [0 r3 `1 mFactor, 因素/因子
* \: A W7 k8 l. n/ @1 u2 g$ [ t8 ZFactor analysis, 因子分析/ r: s3 ?, k. y% s& v
Factor Analysis, 因子分析7 a6 K6 {1 @$ `+ u# T: x
Factor score, 因子得分
4 k% b. R' o9 O( CFactorial, 阶乘
7 ?% m9 M" i3 j7 d- _+ G" }Factorial design, 析因试验设计
; @4 ?0 w/ Y" F0 b2 R0 zFalse negative, 假阴性
& } z8 |, L4 @; O3 NFalse negative error, 假阴性错误
8 ? Y' [( V4 s# [! `9 V- {Family of distributions, 分布族# y- R" c/ u7 m! f0 G; o
Family of estimators, 估计量族
/ [6 c3 i C, q! K- V9 hFanning, 扇面
# \0 T6 g: [& Q4 c7 L. _Fatality rate, 病死率
1 P* H0 r9 q5 p& x3 a5 y/ b* C: o% xField investigation, 现场调查
; L$ P# u: Q7 P2 {Field survey, 现场调查
# t: J1 t# Z. oFinite population, 有限总体2 j' u* s0 L$ o$ ^5 A
Finite-sample, 有限样本5 q8 I$ w0 P) Y b- u+ j3 `5 Q+ t
First derivative, 一阶导数
e9 b O, _ {First principal component, 第一主成分" k* O# J7 b3 R' E1 ~( Y
First quartile, 第一四分位数
3 }% m* \; `2 x/ {Fisher information, 费雪信息量
$ B' C2 I H3 bFitted value, 拟合值, K; {! L; ?5 Q9 _- M( Z( I
Fitting a curve, 曲线拟合
5 P0 ?- @3 Q9 {+ J+ Q' FFixed base, 定基
' A" f8 V, ]% b) T. _* oFluctuation, 随机起伏* K. E) N/ w0 b% C0 T; t0 g: b0 E
Forecast, 预测
+ r3 F& t! h/ G/ ~4 w: S0 W& ?Four fold table, 四格表
& R( j6 t! w2 P6 UFourth, 四分点2 ^' s5 L+ x" o( u" ~# {
Fraction blow, 左侧比率
: e7 E- g, P! ~) m7 L5 n9 |% VFractional error, 相对误差% g1 |2 X% |. X) a$ }
Frequency, 频率* z/ \' N- M: h! W8 A7 a& _8 V$ ]
Frequency polygon, 频数多边图5 {/ }3 x( C9 V1 q9 B
Frontier point, 界限点7 [- O- L3 l! G" Y" g& [
Function relationship, 泛函关系
. o$ m$ ]" n J5 M- `, N( V2 iGamma distribution, 伽玛分布$ A4 i1 L3 T. Q6 ]9 e
Gauss increment, 高斯增量
+ e @9 R, `1 d6 z$ ]Gaussian distribution, 高斯分布/正态分布
' B$ W9 d6 O- G. KGauss-Newton increment, 高斯-牛顿增量& l0 |- a6 t5 f# M# s$ G+ i& q
General census, 全面普查
; @ O6 U% T7 w; D9 [GENLOG (Generalized liner models), 广义线性模型 , ?* A# V) N# w# e
Geometric mean, 几何平均数9 b# E. _- C2 `/ L6 u# U
Gini's mean difference, 基尼均差$ r- S) ^/ f% q) i) D
GLM (General liner models), 一般线性模型 ( y; Q/ v+ A& {1 o" N$ h
Goodness of fit, 拟和优度/配合度
- F5 X+ S0 f8 u( a& h6 ]5 R! s2 BGradient of determinant, 行列式的梯度' h$ M; I: _1 O) Y2 \
Graeco-Latin square, 希腊拉丁方. f, |" \2 Q, m( T# G, K
Grand mean, 总均值$ j6 Q5 W: l+ A/ L) ^
Gross errors, 重大错误0 ?- h% }) l$ T+ ?
Gross-error sensitivity, 大错敏感度
. V" e) r6 L7 }2 B% _/ z5 TGroup averages, 分组平均
6 S- n8 m/ V' rGrouped data, 分组资料' E( S# O$ U' X F6 B
Guessed mean, 假定平均数
- L `! N& Z' G# k( bHalf-life, 半衰期
2 f& O4 W& T* B/ \ X, {! f+ tHampel M-estimators, 汉佩尔M估计量
" P% _7 t* q1 g+ f: o d; h' B. F* {% uHappenstance, 偶然事件6 Y* o. W3 K$ j4 C/ v/ W# t
Harmonic mean, 调和均数 ?. ]) w1 S2 ?0 Q6 q9 C
Hazard function, 风险均数( w4 k. S3 O5 {6 C. j, w8 C% i' N; L
Hazard rate, 风险率. G* y' e1 \' I9 }/ f/ ^. I' m
Heading, 标目 4 h- L7 X4 g- S
Heavy-tailed distribution, 重尾分布
. p) r! y; e }% s5 o% @6 @$ w2 z5 ~Hessian array, 海森立体阵
( b& ?- z* h9 U. H+ gHeterogeneity, 不同质
9 R- r6 y5 T5 u- c7 YHeterogeneity of variance, 方差不齐 ! e# H8 N3 _8 C- q, f# `& R
Hierarchical classification, 组内分组
! i4 f7 C% i6 c d/ H8 _' dHierarchical clustering method, 系统聚类法* M( q! B1 D# X4 ^
High-leverage point, 高杠杆率点& L& D6 g& {( I6 A9 Z& I0 }7 g G
HILOGLINEAR, 多维列联表的层次对数线性模型
% \6 `/ D% c1 R/ m/ C$ XHinge, 折叶点" m7 H- A" b; }! n [
Histogram, 直方图
; s% ?2 n- p9 aHistorical cohort study, 历史性队列研究
7 }& [5 n) h+ p8 j5 h9 _Holes, 空洞
& k# _% Y+ \+ b$ ^, S3 JHOMALS, 多重响应分析
, c" F/ w, I5 ^+ l" M1 `7 lHomogeneity of variance, 方差齐性
7 V# V9 w5 \& L3 _. S# QHomogeneity test, 齐性检验
! w1 I" K5 t% K- q w% fHuber M-estimators, 休伯M估计量
0 U- }% m6 H+ L! P9 T0 m: }Hyperbola, 双曲线
7 q. j% J y" O' GHypothesis testing, 假设检验
, t" ]9 R- i6 a% Y3 \Hypothetical universe, 假设总体: H1 R6 T) q( [
Impossible event, 不可能事件( ]+ v+ q- c4 p
Independence, 独立性
/ I& I& `7 \9 y% S7 {1 h% YIndependent variable, 自变量
& o9 Z1 a. u( q, rIndex, 指标/指数5 Q9 c* | l, u
Indirect standardization, 间接标准化法
/ J% E' y6 ?4 X4 hIndividual, 个体$ f q& F; L: r0 e. j
Inference band, 推断带7 }( S9 ~: j) E6 k2 b
Infinite population, 无限总体
7 J% a/ f, ]: N9 dInfinitely great, 无穷大/ t/ g" a( Q' \$ Q9 l
Infinitely small, 无穷小
% w3 Z3 C- f% Z) X' \: G/ nInfluence curve, 影响曲线
0 Y$ e1 w% B; d6 [ v% |Information capacity, 信息容量) b5 V. f) Z. I, }
Initial condition, 初始条件8 O0 U4 P: A" G" b
Initial estimate, 初始估计值5 x; d8 c2 `% o6 n- ^( |' i2 e$ s
Initial level, 最初水平4 {4 `; t9 \) M, _( g" R
Interaction, 交互作用" g# p; J: y7 u/ y3 m
Interaction terms, 交互作用项( m% F$ n: S& C- c* g
Intercept, 截距* A. V5 R8 M5 Q/ F9 f! {9 y% T
Interpolation, 内插法5 X: L6 D8 B* ?& w9 E% E S: N
Interquartile range, 四分位距2 E- S5 F8 A5 s3 E4 o
Interval estimation, 区间估计2 G5 e" P8 y) m7 e$ ~
Intervals of equal probability, 等概率区间' a" U! g1 B5 ~+ B
Intrinsic curvature, 固有曲率
6 G* C$ W2 ^) P* bInvariance, 不变性
+ `) D/ p9 `/ k1 {" yInverse matrix, 逆矩阵! h& b( a) V& h# _3 e
Inverse probability, 逆概率6 {( r0 P2 i) h- K7 o2 S& D/ \
Inverse sine transformation, 反正弦变换: L6 i- ~6 Q: Q' _' k: `6 O, x
Iteration, 迭代
* c% ]2 |# z; R! m8 u2 cJacobian determinant, 雅可比行列式! s7 W+ n9 `- k. M
Joint distribution function, 分布函数" q2 w5 ?( F- Y. j. Q# I
Joint probability, 联合概率
; A5 g9 [) l* j! n# R, IJoint probability distribution, 联合概率分布5 `" e0 R7 o: E# \
K means method, 逐步聚类法
% \1 m+ ~/ r' h, a0 N' r3 U7 n5 ZKaplan-Meier, 评估事件的时间长度 0 @" K5 }, b1 |1 |: D# Q
Kaplan-Merier chart, Kaplan-Merier图, t6 }- w- z$ V4 t3 L# L' M- o
Kendall's rank correlation, Kendall等级相关
* `3 j+ a: x0 r! \, B& X8 P' L7 h# ?Kinetic, 动力学9 N+ B, m% _% {* a' K
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
$ m: K) k/ U, J+ m& h2 ~Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
) `, q. \, y" Q* P, f; xKurtosis, 峰度6 M; r/ Q& x1 D* y, d' G) c
Lack of fit, 失拟
/ @) n2 D' w7 E7 d% QLadder of powers, 幂阶梯/ Z* l5 U+ S8 r. e
Lag, 滞后1 f( J+ r$ h6 l' `0 {
Large sample, 大样本
& K7 L& L! f% O% w0 |$ y* z) w' GLarge sample test, 大样本检验
' w4 [* E S# G$ X9 u% vLatin square, 拉丁方! s& P5 F: U2 a5 ?8 I3 t
Latin square design, 拉丁方设计
$ [. d, L% N: i4 y `3 OLeakage, 泄漏# n3 k9 B( I: y% f
Least favorable configuration, 最不利构形3 w3 w3 W/ ^* Y4 g
Least favorable distribution, 最不利分布5 [" r2 N) s/ ?! l4 c7 q
Least significant difference, 最小显著差法
4 w5 X( h* u' C' |1 I- ULeast square method, 最小二乘法
; s; J$ e8 M% H+ D* E- \; c' DLeast-absolute-residuals estimates, 最小绝对残差估计
7 `. Q+ ~" w( S) FLeast-absolute-residuals fit, 最小绝对残差拟合
$ F4 | X) q# f. R7 }% T* Y2 SLeast-absolute-residuals line, 最小绝对残差线
* F( T( v6 l3 r: nLegend, 图例; t1 G0 }6 M' S. j9 }7 K, c
L-estimator, L估计量
' b7 ^$ Z& T( d: _L-estimator of location, 位置L估计量
$ g( D! U+ D* G4 Y; d: r" hL-estimator of scale, 尺度L估计量5 ~# f9 \% w4 F2 F
Level, 水平4 ?1 u0 r4 Q5 @6 q% N7 N& \
Life expectance, 预期期望寿命
0 v A: _4 `8 RLife table, 寿命表
% V K; C) j* @) @0 c4 yLife table method, 生命表法+ c& P6 \0 c# z" r% E6 K: Y
Light-tailed distribution, 轻尾分布
% N! P& m; r3 zLikelihood function, 似然函数
" P9 t6 G- G& U8 l yLikelihood ratio, 似然比
- b8 p, O9 A8 E! {" ^7 Yline graph, 线图8 e2 F$ `) J. f( f5 U
Linear correlation, 直线相关
0 Q2 n" L+ P- C$ i ~3 B' [Linear equation, 线性方程
5 j% U# z' u1 }7 GLinear programming, 线性规划
; e# z M. ?7 ?* o t7 ~Linear regression, 直线回归/ i3 C- @7 \% R7 m! t+ q
Linear Regression, 线性回归
7 _1 q- d- n9 X! d7 K- `: WLinear trend, 线性趋势 Y |5 V6 s# t1 _: \. Z1 z
Loading, 载荷 j$ u- N+ A4 q' O# n1 C
Location and scale equivariance, 位置尺度同变性 V1 [" z; g2 W. A/ P9 @
Location equivariance, 位置同变性: z* {' n& L1 L/ F5 n) t
Location invariance, 位置不变性
9 P+ A4 I- Y& M) A% x7 W' hLocation scale family, 位置尺度族/ ^! \7 [ s$ g) i
Log rank test, 时序检验 " _! ?# J# _ ^" Q) ~
Logarithmic curve, 对数曲线
( L9 `2 @" Q. X* n/ o% qLogarithmic normal distribution, 对数正态分布
2 x( t3 H% j" RLogarithmic scale, 对数尺度
6 Y! b6 I) \0 e& z6 SLogarithmic transformation, 对数变换
" J4 T$ H5 a' ?7 HLogic check, 逻辑检查# t k! a* D; m
Logistic distribution, 逻辑斯特分布
& `5 a' M: ?8 M: [8 q m- GLogit transformation, Logit转换
* }. Y- Y2 }, ]$ J4 K. T4 vLOGLINEAR, 多维列联表通用模型 9 G4 Y. i6 K' R6 i; X
Lognormal distribution, 对数正态分布7 T$ j, U" w$ i# T- E
Lost function, 损失函数: R: ~1 r7 f$ @0 k* u- r c( m
Low correlation, 低度相关
' T* l, Q. T: ` YLower limit, 下限3 h# ?& X" H, m( o' Y2 J0 H
Lowest-attained variance, 最小可达方差/ i& O1 C8 [% }) w% M+ z1 r. k
LSD, 最小显著差法的简称
+ Z a; m5 I5 y* _# |( V0 a2 J7 YLurking variable, 潜在变量
& Z0 `8 s3 U" U% E! c' BMain effect, 主效应2 H& J+ B; `' L4 ^
Major heading, 主辞标目
0 [4 O& h( H4 F8 c& gMarginal density function, 边缘密度函数/ ^, e% ^, h- I
Marginal probability, 边缘概率
7 d2 r8 V2 I& m* e! x: v# _2 K9 }Marginal probability distribution, 边缘概率分布/ p0 F3 m) @1 C: X+ B
Matched data, 配对资料
- Z" X/ ~2 I1 c" y) XMatched distribution, 匹配过分布
7 i! t; W; z6 J: i7 i4 n: x; NMatching of distribution, 分布的匹配
7 e0 J% r; R2 j0 ?Matching of transformation, 变换的匹配% U1 _' n! _9 ~ O' Y9 z. G5 u2 l0 z
Mathematical expectation, 数学期望
|! I9 F, J/ j0 I/ z1 S: wMathematical model, 数学模型3 [. c, o9 t7 s9 W& m) w
Maximum L-estimator, 极大极小L 估计量
; W$ E# ?& o& U; P4 H# v; x9 W, eMaximum likelihood method, 最大似然法
y( C5 l) A* n9 JMean, 均数
7 l$ O" L: Y/ _8 vMean squares between groups, 组间均方$ p* h" h# i+ O. M
Mean squares within group, 组内均方
- B s& h, S. G% {Means (Compare means), 均值-均值比较 L% ^4 P2 s8 H& Q! l5 C$ `
Median, 中位数
# H( W% O0 V+ [5 s* \/ l# A/ EMedian effective dose, 半数效量! |7 b4 q3 Y3 F' j! Z
Median lethal dose, 半数致死量
' ]& |4 v5 i; i" \' o5 \6 T! mMedian polish, 中位数平滑! E2 t( x# L+ c
Median test, 中位数检验3 P4 r6 C9 u' L7 \# C% t
Minimal sufficient statistic, 最小充分统计量
1 E6 J) @& f9 U' O- f$ } i% hMinimum distance estimation, 最小距离估计) q; H1 \5 d$ N& O* W
Minimum effective dose, 最小有效量! k1 A' V% ]3 K) v
Minimum lethal dose, 最小致死量
/ ]6 b5 h$ z3 c" iMinimum variance estimator, 最小方差估计量$ J+ H1 M8 c5 F6 E& [9 T
MINITAB, 统计软件包
8 V, f! L# M/ i) N9 z2 [7 [) QMinor heading, 宾词标目
( ]# x& E! h' P, w! ]% \- F! wMissing data, 缺失值
/ P6 v9 J( j' S5 `% S; ]Model specification, 模型的确定# ?( H# I) W( F& I- U. b h( w
Modeling Statistics , 模型统计4 ^9 u/ q2 ]. m" ^/ i; t; A0 Q* N
Models for outliers, 离群值模型. T% d4 Q. ~. o# ]$ Y0 b
Modifying the model, 模型的修正
3 [" K7 z: I4 ~0 W4 ?Modulus of continuity, 连续性模' u/ F4 H M+ S. A+ h4 |$ K
Morbidity, 发病率
# C$ c. o) }8 N' h5 f9 N% F% jMost favorable configuration, 最有利构形
% J+ y8 Q' l6 C3 MMultidimensional Scaling (ASCAL), 多维尺度/多维标度- G3 R _3 h+ y$ ?5 J/ A! i0 j0 U c
Multinomial Logistic Regression , 多项逻辑斯蒂回归
' }+ [7 U& ~+ c+ m8 @Multiple comparison, 多重比较& q' a9 c+ ]5 E4 ]1 l# [. u8 n
Multiple correlation , 复相关
& C8 i7 w4 T/ `4 b: zMultiple covariance, 多元协方差
2 E) s; _ ~2 H5 K0 xMultiple linear regression, 多元线性回归! i/ Z0 l) u9 r8 N* M! i8 D
Multiple response , 多重选项
) X$ O9 Z |$ z9 M. M6 ~Multiple solutions, 多解
; }+ s2 I' g8 eMultiplication theorem, 乘法定理6 k# E! |& K/ _) \/ P/ ]! {
Multiresponse, 多元响应& F- {$ V1 \. R. Y6 W
Multi-stage sampling, 多阶段抽样6 E$ C& m7 s, \
Multivariate T distribution, 多元T分布
4 p/ E; Z1 ]. J: D/ I& b* r1 rMutual exclusive, 互不相容
2 _; {3 k/ s8 R BMutual independence, 互相独立3 `! G1 _/ k3 i( E8 @5 H x3 U
Natural boundary, 自然边界
5 O" o4 a* ~" S2 y% \- E# WNatural dead, 自然死亡- g8 ?7 m2 t5 f2 T. R. W
Natural zero, 自然零
0 M5 ?8 O) \& {) `Negative correlation, 负相关1 h! t, d- F) x3 C- K6 @0 b: L% l
Negative linear correlation, 负线性相关; B7 R5 r4 q. s6 o
Negatively skewed, 负偏
- h) t1 e' `$ w1 C0 RNewman-Keuls method, q检验
" _1 V: y" k& {* }9 [6 eNK method, q检验) P( ?/ \, j4 n; `& |+ X" B( J! n
No statistical significance, 无统计意义4 g' Y; c) p: Y5 Z; ^0 y. {( _; e3 c7 w4 n
Nominal variable, 名义变量
( I% P' [- M- w2 G& cNonconstancy of variability, 变异的非定常性0 K' q' c+ N# Z8 |( d
Nonlinear regression, 非线性相关# e7 J. P3 K6 ^5 m* }% M- }4 Y
Nonparametric statistics, 非参数统计
4 Z3 D& w* }( LNonparametric test, 非参数检验
0 B: C7 o" m6 ]* z9 [Nonparametric tests, 非参数检验
9 J2 a8 n( F, X1 @; n% K, XNormal deviate, 正态离差, A- Z0 d3 O& H
Normal distribution, 正态分布# b0 j7 t- G; e" Q( N
Normal equation, 正规方程组
3 p: m( D) H0 j3 |+ U7 [Normal ranges, 正常范围! U& ~: }: G: } D) o
Normal value, 正常值
) l0 I* c4 {7 ]Nuisance parameter, 多余参数/讨厌参数
" B9 S% ?% `9 G# k8 P* h9 G+ R+ N1 SNull hypothesis, 无效假设 0 a! z# v* f: [: r4 F
Numerical variable, 数值变量8 j- f$ Z1 Q. o9 i1 `
Objective function, 目标函数
5 r0 r! R5 E& I3 h6 NObservation unit, 观察单位
I3 K/ N0 O! ?! h% AObserved value, 观察值7 Y. W3 b) I' |, t( m* U1 d
One sided test, 单侧检验
( l% b% }$ b6 e" M7 [One-way analysis of variance, 单因素方差分析
; [; c' i( V' a' tOneway ANOVA , 单因素方差分析2 x5 T2 n( d3 x1 X- F
Open sequential trial, 开放型序贯设计6 U' P0 u' n1 H2 ~
Optrim, 优切尾0 ~% y) D K$ K A. c# @$ K! x
Optrim efficiency, 优切尾效率
' m" P, Z# g4 N+ G+ C" f: gOrder statistics, 顺序统计量! u# z: U' f$ k9 R5 _! M
Ordered categories, 有序分类
( P. x. k- t- I% XOrdinal logistic regression , 序数逻辑斯蒂回归1 n0 I8 i3 ]# {5 s" H" Y
Ordinal variable, 有序变量! c9 f1 T2 P3 Z/ |' v' Y
Orthogonal basis, 正交基
2 s+ d5 ~- y4 U2 @1 nOrthogonal design, 正交试验设计
" w# @+ X: a$ b7 H; o h& eOrthogonality conditions, 正交条件
* l, ~$ \+ o7 f: p8 i. m& SORTHOPLAN, 正交设计
; P. E7 q4 F& d GOutlier cutoffs, 离群值截断点
/ i4 y, ~* h9 p( aOutliers, 极端值; B" W/ c) { v5 M! M7 \/ ]1 r7 e, d
OVERALS , 多组变量的非线性正规相关 + h5 q: A4 N. X" \1 z; s! G
Overshoot, 迭代过度1 r4 o7 O X l3 u/ B! I- |
Paired design, 配对设计. v+ D5 z) ?/ O! |
Paired sample, 配对样本
5 O* W, e; D! L; H% s" z+ BPairwise slopes, 成对斜率$ D' o/ L6 j+ s, q" x- b
Parabola, 抛物线
+ p+ B1 [2 h' H# v# Y+ J. z$ SParallel tests, 平行试验
6 w% |' g" k5 W" T8 l* w7 Z. XParameter, 参数
5 c0 S4 k4 v% D6 X' h& o: zParametric statistics, 参数统计
5 V6 X& z L) W3 d Q, t- k! a* iParametric test, 参数检验; |/ o# B3 D2 Q+ \4 k5 s1 R
Partial correlation, 偏相关
5 C" q2 }( ]6 U/ t `- k7 `# APartial regression, 偏回归
3 Y" c. o' J. |& _Partial sorting, 偏排序2 o% q- l( K& A; C4 q- M: W
Partials residuals, 偏残差
) y% Z) v/ y- j& x" q1 W; y* LPattern, 模式, n' _% Q! G' p& R% p$ A9 c3 ^
Pearson curves, 皮尔逊曲线
% y7 s! s' @9 a) ZPeeling, 退层: T2 t7 u' Q& x2 g& a9 x; k B
Percent bar graph, 百分条形图
1 n' n! l8 M: ]; pPercentage, 百分比
4 P$ g$ A: F& T; ?4 A" o0 yPercentile, 百分位数
& X8 @0 z+ C6 ]2 uPercentile curves, 百分位曲线
4 G7 p) P8 {1 ^3 c8 Z5 N' v7 a5 gPeriodicity, 周期性/ C! b* [: j6 V' [/ |$ E# a) d1 h
Permutation, 排列" Y0 w, y! v6 D' M4 m" t) d5 z
P-estimator, P估计量# A: e4 m% `( N6 q; S1 ?! [
Pie graph, 饼图' K y8 t" ^( A& u- ]5 j& z
Pitman estimator, 皮特曼估计量$ F% r+ A- O. }: d- Y8 a$ \! X8 }
Pivot, 枢轴量# w/ Q+ \: g9 A! i
Planar, 平坦
2 D+ t z8 o9 G2 e& s% y5 zPlanar assumption, 平面的假设- b/ y; q# u/ H) ^( X
PLANCARDS, 生成试验的计划卡( [: p4 }1 E/ \0 h; O2 H
Point estimation, 点估计/ t- U% F7 P, D
Poisson distribution, 泊松分布% l3 T8 `1 C1 s# D
Polishing, 平滑
5 E' j a3 a- u4 o( p1 \" gPolled standard deviation, 合并标准差
/ c! `: v/ r. T( CPolled variance, 合并方差
7 \( D4 M+ U" [% p" P9 Y* {Polygon, 多边图
& m; `3 U3 F! y5 T) T* QPolynomial, 多项式) I! P: S/ A# G4 V' c/ d! I9 J
Polynomial curve, 多项式曲线
. ~# j9 |. k& }: [- D* DPopulation, 总体# h3 L# i) U8 i
Population attributable risk, 人群归因危险度
L/ @) w! f7 J) u0 ?7 x# D: n6 \Positive correlation, 正相关! |8 u L$ O* O/ F, ]
Positively skewed, 正偏: `& Q" J3 k$ O8 R
Posterior distribution, 后验分布
0 L U4 F9 @, F# R' s- r/ nPower of a test, 检验效能8 }$ l% f! c; X2 G
Precision, 精密度
3 e3 ^6 G+ o, t* XPredicted value, 预测值4 b+ d! F+ E) H, j& r8 l5 u0 Q
Preliminary analysis, 预备性分析) W p7 ^2 b/ j0 ?
Principal component analysis, 主成分分析5 }7 ~: G% y' ~1 i! ~9 {8 d$ J
Prior distribution, 先验分布
]$ p h5 N6 ~9 T* i$ \& i! JPrior probability, 先验概率
0 S4 T: F) u. \) a% ~8 ]Probabilistic model, 概率模型
O/ j9 S1 j$ J. a8 }" Wprobability, 概率9 b3 V; {4 D6 M; F( w& w
Probability density, 概率密度 D: B/ I p" z. o; Q
Product moment, 乘积矩/协方差
( n9 N9 J8 u ~: @ ?Profile trace, 截面迹图9 P# j# {% f# J
Proportion, 比/构成比) z5 r5 C$ W( c4 O& U# s
Proportion allocation in stratified random sampling, 按比例分层随机抽样! C; f" e; X* T+ u7 L# I9 P( a( a
Proportionate, 成比例
; G$ J1 a1 m, }+ K: eProportionate sub-class numbers, 成比例次级组含量
7 p* M6 {7 a' T% H, E$ R( l9 FProspective study, 前瞻性调查; M: o% C5 S6 F5 }7 A* L
Proximities, 亲近性
- s+ |+ a1 O* _% J, XPseudo F test, 近似F检验/ J) ^* Y: `# \' {
Pseudo model, 近似模型
+ ]" B1 `7 t* n& B' ?Pseudosigma, 伪标准差
" l6 m; |; t" s+ y2 `1 w* kPurposive sampling, 有目的抽样% X5 I! |4 L6 x" ?/ O5 \' {
QR decomposition, QR分解9 G8 R# @1 i9 P
Quadratic approximation, 二次近似
& t+ P4 e( @% l e' Y9 wQualitative classification, 属性分类$ M7 j( H3 L8 f; I7 p4 A
Qualitative method, 定性方法% c8 `, W3 [6 Z
Quantile-quantile plot, 分位数-分位数图/Q-Q图- F' |/ G) U4 z
Quantitative analysis, 定量分析
7 ]' B U0 E7 K, }' f. L" W3 fQuartile, 四分位数! K+ r9 P9 {$ a8 w- W _
Quick Cluster, 快速聚类
, F, Z. S1 B: BRadix sort, 基数排序
1 H6 I1 o+ d7 fRandom allocation, 随机化分组
2 ?7 Z2 k' C {. P. x+ W7 q* O' U8 q; rRandom blocks design, 随机区组设计
; }4 D* g$ B3 l! p+ W8 yRandom event, 随机事件
- o4 H8 p& t1 l t- s: x/ J1 }8 zRandomization, 随机化. p' @+ I* g5 }
Range, 极差/全距5 R5 d, S+ H- @# r- { C; {
Rank correlation, 等级相关/ y- `" N8 C& B7 u# c3 S0 X
Rank sum test, 秩和检验
$ [# h' m6 g* S0 ], a. ^, O* rRank test, 秩检验0 ?% t- B* f/ P2 @# w7 \& i% i. S
Ranked data, 等级资料. h2 [ @6 R2 I
Rate, 比率
/ R9 u" x9 \6 ]3 uRatio, 比例
# ]+ L' n2 c) GRaw data, 原始资料
9 O% a( i6 j, F* Z! VRaw residual, 原始残差
E6 Z' U& @1 K! k/ h7 s3 f( n& _$ IRayleigh's test, 雷氏检验
1 ^/ R q1 A4 R) U& `9 jRayleigh's Z, 雷氏Z值
. Z5 A- ?/ c6 d+ S9 y- r$ _Reciprocal, 倒数
( S# G! D* L, v) PReciprocal transformation, 倒数变换3 M: [1 O" o' V% d# L
Recording, 记录
- i3 ^1 L3 Y* A6 P4 N1 t9 r- C9 g1 PRedescending estimators, 回降估计量
- f1 f- [/ g f) cReducing dimensions, 降维% n1 M: P$ t$ P0 w4 X
Re-expression, 重新表达
; F; h: m$ `# x6 S7 [Reference set, 标准组0 g4 e/ X# z" h* b8 u0 K: O
Region of acceptance, 接受域4 W; C. @" Y; I; k
Regression coefficient, 回归系数1 t0 e0 c# m2 h* \! g) H1 [4 u" v& n
Regression sum of square, 回归平方和
6 w$ }/ M% @- ^' V) XRejection point, 拒绝点
# t/ g5 q" u: h- | w' B8 g& i8 aRelative dispersion, 相对离散度
4 u/ T& c- b4 t mRelative number, 相对数& J+ g2 W4 J: g% Y$ h" _/ ^
Reliability, 可靠性7 N3 d8 z9 @0 J6 ]" [9 C/ l; U, E @) M
Reparametrization, 重新设置参数 x8 Y4 z' l; o' t! ^
Replication, 重复
/ `. O. }, O) L8 g/ C) t7 NReport Summaries, 报告摘要
( a- l+ F- j& p4 l2 N6 {Residual sum of square, 剩余平方和
2 z' y& r) \) {+ v8 g8 b* HResistance, 耐抗性
, c6 {+ ?# q% F3 sResistant line, 耐抗线
3 v" F- {7 y3 @9 A! \5 H. tResistant technique, 耐抗技术! Y6 r* ^- }0 t* J
R-estimator of location, 位置R估计量, B1 W9 Q, i& e$ R8 U
R-estimator of scale, 尺度R估计量0 F! G/ i* ~$ k9 A( t; {9 s. K
Retrospective study, 回顾性调查0 O7 A# I, z1 c! b* {# h
Ridge trace, 岭迹
% f4 t/ S0 ~. m+ }- y& BRidit analysis, Ridit分析
" F/ I7 F2 [4 G) U' J8 kRotation, 旋转) y; o% Y; s/ |: Z) h
Rounding, 舍入
0 R4 E$ H% d6 F9 Q+ ^# rRow, 行
8 u/ }7 r7 }8 f; IRow effects, 行效应; [/ g+ l& C0 W- |
Row factor, 行因素% q" T) I( ` Z3 w! i
RXC table, RXC表
- I6 W s6 Z1 u! l+ `) c2 ISample, 样本
% Q7 J5 @( G, m" ~# VSample regression coefficient, 样本回归系数
4 K: G! ?- o; ~0 s' B4 Z4 bSample size, 样本量
$ ^5 n, x+ [) A4 c# YSample standard deviation, 样本标准差& k# V6 f) i; ]8 p/ h, r
Sampling error, 抽样误差8 W+ C: [0 z: X4 E- [5 P
SAS(Statistical analysis system ), SAS统计软件包" v6 Y* O! @3 ^7 s6 p
Scale, 尺度/量表
: n' q6 }# ?- G/ T, x$ N1 M0 HScatter diagram, 散点图
1 f9 k8 E' d/ `% Z' ^Schematic plot, 示意图/简图
# \/ {1 |$ P7 oScore test, 计分检验, o ]2 t1 c2 u* @; |+ i' y+ m4 a
Screening, 筛检
0 j, C% s2 {1 @( z# wSEASON, 季节分析
! K: R# J' U. ?6 X! i3 oSecond derivative, 二阶导数
9 ~0 A$ A* o- j1 N4 O' F2 qSecond principal component, 第二主成分9 T+ V _+ [& k) }# Y! \# B
SEM (Structural equation modeling), 结构化方程模型 a ^) ~6 w( q( J) N' s6 N! Y/ L
Semi-logarithmic graph, 半对数图
0 B$ }! \3 O1 }( D% HSemi-logarithmic paper, 半对数格纸1 `! a( Y3 K( g1 h S4 |. h) z
Sensitivity curve, 敏感度曲线
}3 {* Q* _" Q' Z+ U8 _; uSequential analysis, 贯序分析
9 F+ L3 ]/ a/ b. i* w! @: ISequential data set, 顺序数据集& l M+ g$ a9 P2 z" p- j
Sequential design, 贯序设计2 Q- @& \" Y( H- X2 W# ^& N. a0 s" M
Sequential method, 贯序法6 w' `0 `- R0 Z& m) I! c9 z
Sequential test, 贯序检验法
# L5 o9 Y' ], d, t3 mSerial tests, 系列试验
, e7 ^3 _- ^" u6 n' A8 A* V$ ?Short-cut method, 简捷法 ' L8 V2 D) J8 W* X! @1 B
Sigmoid curve, S形曲线# ~2 N" x- F( b) P5 {8 P
Sign function, 正负号函数
* s0 Z9 Q# ^5 g. r* l$ ZSign test, 符号检验1 `+ n" T& S- j+ V! U. A5 u
Signed rank, 符号秩, Z8 a6 i: K! c7 W# N/ ~" |) R
Significance test, 显著性检验
7 T: U2 u/ J) q; ISignificant figure, 有效数字5 Q" G' |- F, o/ K+ j
Simple cluster sampling, 简单整群抽样
8 X+ T& N7 L/ J: H4 c( o# M jSimple correlation, 简单相关
$ t6 {) e* l- X, }- X0 lSimple random sampling, 简单随机抽样
6 v* Y/ O+ v0 XSimple regression, 简单回归5 N; R# H2 T2 }; g( L& u
simple table, 简单表
: u. U* g7 ?1 I' A7 z( k- w- _" lSine estimator, 正弦估计量: q' b& a' }' J) k
Single-valued estimate, 单值估计) P6 L& a |) G/ b+ t
Singular matrix, 奇异矩阵
- h3 e8 W7 I( H3 ~; N# ^, WSkewed distribution, 偏斜分布
4 i$ O- e9 ^+ x: CSkewness, 偏度
- m! G2 g8 K3 R+ ~Slash distribution, 斜线分布
: G' G4 I- Z6 F6 tSlope, 斜率
* q) d0 u7 N9 ]Smirnov test, 斯米尔诺夫检验6 P. M; K- o* _% T
Source of variation, 变异来源7 B: d& \* B3 x& c" w
Spearman rank correlation, 斯皮尔曼等级相关! Z4 m5 w1 H9 G) p; E' H
Specific factor, 特殊因子; h& V% `- h" a, I
Specific factor variance, 特殊因子方差. X- A% A& F: G( m2 i! d
Spectra , 频谱9 z* {# q, z W3 r8 I2 t
Spherical distribution, 球型正态分布' I$ y9 u2 b8 V
Spread, 展布, v" R [; J& J
SPSS(Statistical package for the social science), SPSS统计软件包
( E8 x; O7 D. e4 ]' n6 Q* |! SSpurious correlation, 假性相关
; p2 }# t# a3 y& [) O+ K* pSquare root transformation, 平方根变换7 n) b* k+ {: i( ^1 m# N
Stabilizing variance, 稳定方差) b" G, M1 w% v# w+ p7 v4 j! N4 o
Standard deviation, 标准差
8 L p0 A3 g, x! QStandard error, 标准误
$ b- T0 p! F& ZStandard error of difference, 差别的标准误
4 }! D; I5 R+ |2 T+ E6 H6 zStandard error of estimate, 标准估计误差% z0 H _2 p0 P
Standard error of rate, 率的标准误
# x2 H* w" ]3 w9 ^Standard normal distribution, 标准正态分布
" {& P# J+ |' m# TStandardization, 标准化" G. c/ `( _* S( Y
Starting value, 起始值8 V3 q0 p" t5 {2 w# K
Statistic, 统计量. ~9 J. S" L; E' L
Statistical control, 统计控制
4 @! V4 q& x, aStatistical graph, 统计图
, O+ A& H) z0 @8 l, p! {& IStatistical inference, 统计推断$ U8 @* q9 g* a) R( h
Statistical table, 统计表+ r8 u! b4 w5 ]4 E
Steepest descent, 最速下降法
3 C8 n8 S0 N& `9 ^Stem and leaf display, 茎叶图
/ S4 n- d/ D8 B, F [' YStep factor, 步长因子
0 s% s6 G& V o# a8 w. eStepwise regression, 逐步回归+ J) D* \: R$ M8 n
Storage, 存$ { n: ~& c4 a2 k0 Y( @
Strata, 层（复数）# D% R* |& z' j5 y
Stratified sampling, 分层抽样, v) c/ C2 I6 B6 D9 L3 F
Stratified sampling, 分层抽样
1 _4 v( K" g: B$ U% aStrength, 强度) H3 N( i, G8 k9 \* {
Stringency, 严密性" B* i5 x* a6 d$ ]
Structural relationship, 结构关系+ n4 `7 t& X3 P/ x; a. d
Studentized residual, 学生化残差/t化残差; D. }/ K5 _* T9 K8 Q, E* m+ \
Sub-class numbers, 次级组含量9 O. t5 M: t0 L5 l' `2 `+ o1 C
Subdividing, 分割, v8 J6 y! r; F; @$ x9 c
Sufficient statistic, 充分统计量
$ W3 B6 X$ y# E5 q$ c! ~2 o* t) O3 T1 }Sum of products, 积和
# P7 F* J2 B' u: p9 F% z2 uSum of squares, 离差平方和; k; ^6 l. S8 C
Sum of squares about regression, 回归平方和
k0 \. W t0 m! P1 @; }Sum of squares between groups, 组间平方和
. J8 m4 [1 S% J! j. { G& lSum of squares of partial regression, 偏回归平方和
`9 J/ N( o# Y3 W% |Sure event, 必然事件
; a2 Q' \; X5 j s9 X+ QSurvey, 调查
3 P+ q$ N" J. }/ _' x3 d/ O; u- v, XSurvival, 生存分析
% E" C) b; u+ m7 ~Survival rate, 生存率+ E* O9 o* z1 x/ F) w) b* ~( Y* [9 r
Suspended root gram, 悬吊根图7 D$ p" l& R+ l' P. K
Symmetry, 对称
- S) E) `+ V0 \$ t# ]0 PSystematic error, 系统误差* w. s+ ?, D& }# N* h! o
Systematic sampling, 系统抽样
! L, j* a3 S) i% ?$ t' A+ ^5 ]Tags, 标签
& A1 Y. l8 P P/ x- I; bTail area, 尾部面积
1 s0 @: s0 f2 `Tail length, 尾长" J* }4 _1 B: I9 O" n
Tail weight, 尾重" J/ c B m* u1 q; ~# F. `6 Q
Tangent line, 切线
% l# K/ _* p1 w9 {& GTarget distribution, 目标分布
: x! M4 U2 v: g4 Z" [7 A0 jTaylor series, 泰勒级数" Z9 c. y5 ~, n
Tendency of dispersion, 离散趋势9 g j6 O1 U3 X" Z1 q; b
Testing of hypotheses, 假设检验) [' W+ v9 X1 w6 i; `1 r
Theoretical frequency, 理论频数! Z- n$ h/ ?& h4 H
Time series, 时间序列
* q/ U1 ~1 C0 l- ]Tolerance interval, 容忍区间& V( A1 I9 P4 l2 X( V0 |8 m
Tolerance lower limit, 容忍下限& k8 k5 r7 k- p4 {" g
Tolerance upper limit, 容忍上限8 m3 A) K! p+ ?4 c0 M: k
Torsion, 扰率
' V8 s6 q. `" ETotal sum of square, 总平方和
5 ^" w) p2 L0 Y; I) o. jTotal variation, 总变异: _. n$ f0 \; C* ~3 s
Transformation, 转换$ r7 U! c0 d$ C# V7 T- k0 d
Treatment, 处理
U* V( H6 c, t2 ?% Q+ D" k0 OTrend, 趋势8 V0 k/ w9 L8 v1 Z& U9 X) g
Trend of percentage, 百分比趋势! l; [, `8 v/ T3 \8 d9 M
Trial, 试验+ c+ i( V5 h% g4 m$ N
Trial and error method, 试错法6 e* a; M5 E( W5 d1 s _% s% ?
Tuning constant, 细调常数. ~3 c1 m8 ~- l K0 f; J! S5 ^
Two sided test, 双向检验- D2 R' h0 Q; J; N- O' }9 w9 E# \
Two-stage least squares, 二阶最小平方
4 J7 h) z# A9 C( Z$ hTwo-stage sampling, 二阶段抽样
- Y' K: c. { H9 ^* F% ATwo-tailed test, 双侧检验
2 ]5 M6 {3 I9 s: r: HTwo-way analysis of variance, 双因素方差分析
/ K4 [! |/ k$ Y) G8 H3 L, g. TTwo-way table, 双向表
, z" }3 O! a" E! uType I error, 一类错误/α错误
+ r1 k- x; U. J. R. }Type II error, 二类错误/β错误0 _0 c$ G- a7 x- p# g
UMVU, 方差一致最小无偏估计简称* b1 g2 I$ L2 T/ X+ r T( T
Unbiased estimate, 无偏估计# ~; d# {* U$ W
Unconstrained nonlinear regression , 无约束非线性回归5 y$ E6 R) Y% {5 @+ P
Unequal subclass number, 不等次级组含量2 ]0 p& L+ `4 w* Y
Ungrouped data, 不分组资料; ~* y4 C7 B3 w
Uniform coordinate, 均匀坐标1 f1 t' U! @) R ^+ g: h
Uniform distribution, 均匀分布
$ G# H7 S W g) f$ d9 i( VUniformly minimum variance unbiased estimate, 方差一致最小无偏估计/ _; N5 f" u2 s. I' H7 g' I
Unit, 单元7 I2 @' l9 z {$ [+ I
Unordered categories, 无序分类
4 ]: K7 ]2 c5 H, C d- S9 p& ?* [Upper limit, 上限5 z) E- f& m: K- r8 X5 `7 d
Upward rank, 升秩- E% K/ @ [$ u' N
Vague concept, 模糊概念
! w9 l8 {$ f# M0 c7 mValidity, 有效性; w8 _% Y) k }
VARCOMP (Variance component estimation), 方差元素估计2 e6 b7 x. N7 [: L) K
Variability, 变异性
* B0 l% ^) Y5 e% {Variable, 变量
- }# B V W+ J$ DVariance, 方差# [2 D! m& U3 x7 W0 R4 i" }
Variation, 变异
: m4 g' M) w% y) [. wVarimax orthogonal rotation, 方差最大正交旋转
- M4 J8 h- [, ~" U# sVolume of distribution, 容积- \8 A$ i7 C1 D
W test, W检验
" s9 k N _* i; B% |/ Q3 t- mWeibull distribution, 威布尔分布
. Y" ]3 G$ G' W4 h6 g3 t$ pWeight, 权数/ Z1 J& w5 T K0 @
Weighted Chi-square test, 加权卡方检验/Cochran检验
$ k" v3 c1 D3 Y: Y, `7 P. oWeighted linear regression method, 加权直线回归
( n) k: J% r% i3 j6 N# H( xWeighted mean, 加权平均数6 u, N9 c+ v9 g$ z# b O8 o# H' o
Weighted mean square, 加权平均方差( x: t, h* y1 i$ A
Weighted sum of square, 加权平方和5 H% J- P- H& D9 Q+ W
Weighting coefficient, 权重系数8 T3 @1 f- P) y9 J1 |
Weighting method, 加权法 ; x& q8 Q% @5 O- a5 S
W-estimation, W估计量
! B/ d2 Z9 u# F' oW-estimation of location, 位置W估计量
* i0 \4 S* B$ v. y8 V# EWidth, 宽度
0 s$ ?+ q* ]8 oWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
: P9 v1 g7 ^) z! M, o6 PWild point, 野点/狂点& C0 F. K- F" q7 x5 m
Wild value, 野值/狂值
" j1 n9 w9 j: O& r& uWinsorized mean, 缩尾均值2 [8 c; Y: E, y! r! r% K; C9 e
Withdraw, 失访
& A: A6 g. Q$ {. R& j- c0 `* ]9 qYouden's index, 尤登指数
; M; L' ]4 e, I( ~Z test, Z检验
5 p$ d: C: Y* I6 x+ bZero correlation, 零相关5 g0 m% }! x( E# G
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
