|
|
Absolute deviation, 绝对离差# ]1 I5 L7 J, y" y
Absolute number, 绝对数" m$ t- G i2 g9 J$ {. ^
Absolute residuals, 绝对残差, f, T, h0 k. R+ \9 l3 ~4 I: D# X
Acceleration array, 加速度立体阵
- `+ z# N# D: y T3 A1 GAcceleration in an arbitrary direction, 任意方向上的加速度
! v3 @- r; P3 @Acceleration normal, 法向加速度8 T/ N( F+ a* `. ^, A5 \' V, c
Acceleration space dimension, 加速度空间的维数
; q" x1 i" k0 e" V1 x; H, y. S9 F/ eAcceleration tangential, 切向加速度1 [9 c# J, _9 l, a A; P+ s8 c
Acceleration vector, 加速度向量8 O" A0 s7 v x1 a z# V, g, a/ l
Acceptable hypothesis, 可接受假设/ ?) \9 l$ R; Y6 {' G
Accumulation, 累积
: e2 N* O8 G2 p d% I2 K, kAccuracy, 准确度
! O5 w& M c$ n% g& h5 m. v6 i ^Actual frequency, 实际频数; {* w) g. f' U; S/ d( v8 T
Adaptive estimator, 自适应估计量; }! R* `; _5 N' F- M. D
Addition, 相加
! T% D9 ~/ K, Q6 f4 u) S4 aAddition theorem, 加法定理
7 k3 j8 _' ]# l4 d d& k7 uAdditivity, 可加性
/ ^: j3 g2 a9 n7 }Adjusted rate, 调整率
$ u5 ]$ y" R; O" b$ w. B2 B# ?) DAdjusted value, 校正值: z/ S1 m& I% T( x) o
Admissible error, 容许误差
7 b8 u; v- L5 s! g$ hAggregation, 聚集性+ f4 d X2 C H. B0 J
Alternative hypothesis, 备择假设! |& O6 C: z: _! \& [
Among groups, 组间6 z" Q/ _$ n. @
Amounts, 总量
- }& k2 g, M& _2 z4 sAnalysis of correlation, 相关分析, j4 ^" B" d/ m1 O% ^
Analysis of covariance, 协方差分析) d4 c0 R7 _ C8 f: _, [& v' A
Analysis of regression, 回归分析7 J& j8 v; H- t, U7 `2 }3 t& ?
Analysis of time series, 时间序列分析
) g9 i0 U# c$ C- U) |Analysis of variance, 方差分析& c2 U* X- T+ c6 G
Angular transformation, 角转换% _( u6 g; } c1 ~' ]9 p& S
ANOVA （analysis of variance）, 方差分析! i& K+ B' O9 Y, @
ANOVA Models, 方差分析模型% e: c3 p- \9 e& m: {0 C) f; k
Arcing, 弧/弧旋% U b4 s& k3 U0 Y z% V
Arcsine transformation, 反正弦变换! F9 J8 @7 v5 ? S& i
Area under the curve, 曲线面积
; P) n% k8 s; P- F+ n0 w) LAREG , 评估从一个时间点到下一个时间点回归相关时的误差 8 b% D; s7 O; D$ l" f$ m9 g' e; h
ARIMA, 季节和非季节性单变量模型的极大似然估计 / \4 M; h' R; {
Arithmetic grid paper, 算术格纸9 u3 h' E& _6 N N
Arithmetic mean, 算术平均数
$ \3 x! C$ i; }. VArrhenius relation, 艾恩尼斯关系
; U7 I- K: _. l" i7 A4 M+ RAssessing fit, 拟合的评估
- v& E% W! G; j. HAssociative laws, 结合律% L1 _/ T8 S j3 }# ?
Asymmetric distribution, 非对称分布
. |% q- Q$ Y' ^6 @Asymptotic bias, 渐近偏倚: Q2 K. x* F M, }, m! P7 z; M
Asymptotic efficiency, 渐近效率
0 {: B# W2 X: g: O' i# R( nAsymptotic variance, 渐近方差4 n% L+ \6 @8 }
Attributable risk, 归因危险度
, V9 R4 c# g2 j' @& i8 n! oAttribute data, 属性资料
$ q/ j% m$ f! R2 c& _Attribution, 属性' {6 N/ f& a. v1 C6 Q
Autocorrelation, 自相关' B4 R- p& N0 K5 m
Autocorrelation of residuals, 残差的自相关$ x6 e& h, g; ]) a/ @" A9 f
Average, 平均数
$ a2 a" j, @% p: r0 g2 dAverage confidence interval length, 平均置信区间长度# O; n" s9 ~1 M* x. T; \. I j
Average growth rate, 平均增长率
7 i- g+ g1 w& D* f7 k+ q( u tBar chart, 条形图
* K/ t' \& W% z: b) n# ?' ~Bar graph, 条形图" H" t, z1 }& b7 ]
Base period, 基期- h0 V4 c% [& ~2 n' W1 c
Bayes' theorem , Bayes定理
2 z& ~8 \7 W" Q. J$ e8 l* G9 Y$ cBell-shaped curve, 钟形曲线
# I0 C y* }, I+ j1 z- @0 C9 Z8 j: eBernoulli distribution, 伯努力分布% y6 K3 s7 f7 @2 r
Best-trim estimator, 最好切尾估计量
6 e. P! w8 B5 z: g' iBias, 偏性 N0 ^2 Z' _& |- f6 ^
Binary logistic regression, 二元逻辑斯蒂回归
_6 ?4 b* y7 J Q& CBinomial distribution, 二项分布
7 r! Z2 i* G* G* v3 EBisquare, 双平方) }2 M4 O5 G7 [% C+ z* a9 y- W! F
Bivariate Correlate, 二变量相关
/ B1 F3 E" E1 D9 s* T: v8 ?Bivariate normal distribution, 双变量正态分布
: o" e& a/ C1 \8 ?+ r. T* mBivariate normal population, 双变量正态总体
, E8 n! v i6 l& q- |/ v yBiweight interval, 双权区间2 s% S) B! X8 G# \" \4 R" S
Biweight M-estimator, 双权M估计量
7 ] k+ n: Q0 o- {) U7 e7 O) Q2 fBlock, 区组/配伍组
+ l( e( N a; lBMDP(Biomedical computer programs), BMDP统计软件包, o+ t% N/ M" ]( w
Boxplots, 箱线图/箱尾图0 m, x& r7 x) M' U/ s
Breakdown bound, 崩溃界/崩溃点
! |- v0 V& ~& o! F6 a9 vCanonical correlation, 典型相关
3 Q# U1 _4 R% G8 o& Y7 ~) f4 R* YCaption, 纵标目+ R7 f$ }8 Q: Z6 Q
Case-control study, 病例对照研究
( I4 h0 Q& j. dCategorical variable, 分类变量/ z1 p% [1 l9 j& e
Catenary, 悬链线
* z- M8 r* M8 B; V3 C0 k. ^Cauchy distribution, 柯西分布
K0 y$ N9 }* q, Q9 t& B3 ACause-and-effect relationship, 因果关系
7 O( I& e3 d1 ?7 g* L o2 A# tCell, 单元
) Q) k, `9 Z J1 c3 zCensoring, 终检; n6 d+ d; c0 e
Center of symmetry, 对称中心
+ E9 R: ^7 S9 Q/ s- K3 j7 ICentering and scaling, 中心化和定标
i5 B8 p0 E+ p, D% K* dCentral tendency, 集中趋势" M6 U: e0 Z" Q* D
Central value, 中心值) ~7 O& e! l3 q) b
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
. c1 a) y% D6 ~, u. A+ XChance, 机遇$ v$ c# I3 Z( i' b' k2 e/ s
Chance error, 随机误差4 I8 G, [! ?0 L7 d# k0 S! O
Chance variable, 随机变量$ F" I8 V8 N3 U" R( E
Characteristic equation, 特征方程- I7 L: K9 y- i
Characteristic root, 特征根# K: o, p$ Y/ _. }6 F x3 J) z
Characteristic vector, 特征向量
3 r) l3 A2 o6 V ^4 A. B; H$ _ pChebshev criterion of fit, 拟合的切比雪夫准则$ G* U# o8 @& m, n$ C9 l0 _
Chernoff faces, 切尔诺夫脸谱图
4 @* Q0 J/ g0 GChi-square test, 卡方检验/χ2检验, E3 i: ]1 n8 I9 Q! k- ?9 ]
Choleskey decomposition, 乔洛斯基分解, c; \4 @8 q: N0 c- J
Circle chart, 圆图 7 |' R* ~$ W! z4 R3 ]% x g* n
Class interval, 组距- r/ |! F3 s# p7 O* N$ c
Class mid-value, 组中值
! r; }! z$ r! q5 }. X" ~5 BClass upper limit, 组上限
) v; o& z5 ] K, S( z& mClassified variable, 分类变量
, ?. o: f: r: O3 H HCluster analysis, 聚类分析; {2 l6 M+ T. F& I! _: `* ~# g7 P
Cluster sampling, 整群抽样3 X1 s( ?# O0 A; j
Code, 代码( t' O! W9 }# e, S" `
Coded data, 编码数据
( N6 x. F+ f' h# O0 z1 Z% V. gCoding, 编码/ I3 W" G5 X0 B7 W6 k$ a
Coefficient of contingency, 列联系数. f4 ^* |- v% ?% R& R; F" {: b3 g
Coefficient of determination, 决定系数' Q7 J4 H8 r- d' `4 h; h% G- h
Coefficient of multiple correlation, 多重相关系数
- i4 p0 p6 D9 K% j: K' b Y: }Coefficient of partial correlation, 偏相关系数
( B; J5 G& P/ ^Coefficient of production-moment correlation, 积差相关系数
! ]5 x& Y. a. S( q2 x6 D- ECoefficient of rank correlation, 等级相关系数/ l3 Z1 ?2 a( g7 O
Coefficient of regression, 回归系数7 ]) o% Z8 S8 d& p6 X+ \5 H
Coefficient of skewness, 偏度系数
5 J. S0 O0 C6 gCoefficient of variation, 变异系数2 c# @+ U- \& s' q/ j: z
Cohort study, 队列研究
# C- k# O2 y, i9 U) dColumn, 列) d$ D1 E2 A2 p
Column effect, 列效应! q( @% {% N. f& A7 c
Column factor, 列因素2 ]1 d5 _. c) m% c0 O* T
Combination pool, 合并) ]& K$ j5 E2 k
Combinative table, 组合表
3 P( a# r9 X* d5 q" ?$ I1 |- sCommon factor, 共性因子
% F, u3 R8 L/ M& h2 K7 aCommon regression coefficient, 公共回归系数% s \+ H' X0 O% H2 @
Common value, 共同值
( w' a* F) }- X3 r% X8 \3 P7 i! TCommon variance, 公共方差
$ e1 M0 M! g* X. f$ ~4 I; V) |Common variation, 公共变异
# P9 @1 J# L2 R9 z4 `' o4 JCommunality variance, 共性方差4 o o6 U: h3 N) M7 {9 l# V
Comparability, 可比性
& ^% \) B- N+ d( v" _5 RComparison of bathes, 批比较, h, B( {: V" o/ l! o/ a! K4 D
Comparison value, 比较值- i$ l# j( P& O4 U
Compartment model, 分部模型
( W+ w, M2 E% ~3 [Compassion, 伸缩
. f. t6 E" \7 ~0 ]: C- ~7 \5 _2 tComplement of an event, 补事件
' `- f, D% ? m( ^) M/ J& F0 @: oComplete association, 完全正相关: i) ^9 f# }$ b( g
Complete dissociation, 完全不相关% ?( s+ I6 l* @4 q$ v) ?8 J% A
Complete statistics, 完备统计量
# m8 e+ }& B+ J) _4 B( W9 i+ ]1 kCompletely randomized design, 完全随机化设计
) l0 r( X' ?$ ]) w( L- j9 l3 _Composite event, 联合事件
' ]9 v; z1 S' O' E! B! ^; kComposite events, 复合事件
9 q9 ?- I2 V+ @( \Concavity, 凹性1 {5 b3 {$ \2 G3 m7 r( f' S0 _! y
Conditional expectation, 条件期望
1 C# v7 r! {/ B# }Conditional likelihood, 条件似然: \, ?! _- w; ^1 ~& S8 E
Conditional probability, 条件概率
! ?" d% P' }: h2 v4 A! t* HConditionally linear, 依条件线性# h/ K& C9 w- d9 m! k# x/ U
Confidence interval, 置信区间% L/ r9 |2 W" u$ {/ O" N" b! T
Confidence limit, 置信限
; y1 G, M) U& N. p$ d/ F% E% FConfidence lower limit, 置信下限! p* C& N5 k0 \) c
Confidence upper limit, 置信上限" L- o5 p5 K5 c. C4 A
Confirmatory Factor Analysis , 验证性因子分析
; j! E) n' R! K) b% }3 VConfirmatory research, 证实性实验研究8 ~% d+ u# R: a9 L* G" ~, U
Confounding factor, 混杂因素
\- h0 M* O @0 a4 L: lConjoint, 联合分析
4 X% r% n4 B3 s9 P% tConsistency, 相合性
+ r! r9 |" F5 R' A7 oConsistency check, 一致性检验
. w- i. F, V, K$ n% i2 ^( UConsistent asymptotically normal estimate, 相合渐近正态估计 P1 |/ \! q. o% H6 K4 ~4 o
Consistent estimate, 相合估计# c% K$ z% h# D. D
Constrained nonlinear regression, 受约束非线性回归% B9 E8 j! n' K* N, B( y8 ?
Constraint, 约束
& m0 z2 r3 M( o6 u# |Contaminated distribution, 污染分布9 @3 K3 F7 Y/ d. N5 ~ X9 J/ C
Contaminated Gausssian, 污染高斯分布7 f ?5 x/ t6 k* L/ x* V
Contaminated normal distribution, 污染正态分布2 O; v7 }7 b* \* ^5 m( e2 F
Contamination, 污染
& k# X- o$ J& @3 @/ S3 U2 M8 hContamination model, 污染模型
: w# F2 t3 E- aContingency table, 列联表" E& `9 i" M( p( x7 r! l0 o' F
Contour, 边界线- ?6 V& I8 O0 \- T7 ]2 x
Contribution rate, 贡献率, G4 }. u% V9 M
Control, 对照, J0 Z8 N K3 C! B# Y. |0 A
Controlled experiments, 对照实验
+ G3 A ]& S$ L! E5 `& ^Conventional depth, 常规深度
; y$ m3 ~; N2 t! sConvolution, 卷积# g8 ~: [6 k& D# d8 n) b X
Corrected factor, 校正因子9 j) x* U+ Y" y0 B
Corrected mean, 校正均值
/ t0 P7 e. E( D" b& b JCorrection coefficient, 校正系数
+ |: E5 D' p3 E: q: q# }2 VCorrectness, 正确性
7 ], j! @3 u: _% |# e( jCorrelation coefficient, 相关系数) M0 ]6 O( q) Z3 V7 f1 A2 `
Correlation index, 相关指数" Q4 _4 A' r9 Q# H! a5 W
Correspondence, 对应
, r# T0 N b; @; X$ f. _Counting, 计数7 z8 g+ f$ e$ D3 E
Counts, 计数/频数
2 b, r! ~. `9 O8 F( N) |# L4 f8 B8 d! gCovariance, 协方差
0 N! Q2 p6 w. I$ k7 WCovariant, 共变 ' `' k6 N- M' a/ \" X- C- S. h
Cox Regression, Cox回归
# p6 M9 j' _- T2 [Criteria for fitting, 拟合准则
+ \9 P7 ]& V" v' t, KCriteria of least squares, 最小二乘准则
* |. C8 v2 H% L' t/ OCritical ratio, 临界比
# N; v; Q4 w* q4 q8 a' R, B1 TCritical region, 拒绝域" F2 b3 w A3 @$ c
Critical value, 临界值+ U9 m& [" o# z# C) S l3 v% X
Cross-over design, 交叉设计" w$ z: G w% }8 a- _4 L& v
Cross-section analysis, 横断面分析
1 l/ A& ?' t. f/ s9 [Cross-section survey, 横断面调查8 j$ J7 e* N4 \2 |
Crosstabs , 交叉表
6 N+ s- Z1 u p& D5 ^) |- n6 QCross-tabulation table, 复合表
4 _0 u; v- y0 \+ f2 Q! X- I* aCube root, 立方根4 y( F, z# O5 z
Cumulative distribution function, 分布函数+ L+ j$ @$ h: C3 o! O" K$ [
Cumulative probability, 累计概率+ E ]1 |; h2 i6 y9 f/ a
Curvature, 曲率/弯曲2 G/ S0 L- k0 N& z) }
Curvature, 曲率) N6 A% X3 @' e# `
Curve fit , 曲线拟和 * E$ q1 [& O1 x# `0 Y& ^+ k7 m) y
Curve fitting, 曲线拟合
% q3 N3 T- o2 O, u# ^) u& H' |9 Q, X cCurvilinear regression, 曲线回归
7 r3 T6 m* a% r7 g% CCurvilinear relation, 曲线关系; K3 [; a- I \! {& U! A3 I
Cut-and-try method, 尝试法
$ q( t7 M3 U: Q7 m4 X! \+ hCycle, 周期
+ Q$ M) m; [ q2 b* j/ \4 lCyclist, 周期性
# G }$ }: L: n& `! l# m8 |D test, D检验
! A& S8 j- G; ~Data acquisition, 资料收集
) B$ x7 {$ B( X3 a9 W5 V8 FData bank, 数据库, a$ G' J' Z% `+ U. d4 G* A4 z$ r
Data capacity, 数据容量% r% |) S+ a; {( f$ D, z
Data deficiencies, 数据缺乏/ w* I( j7 B: C4 F, j1 ]
Data handling, 数据处理
5 S" b9 s! E. ?Data manipulation, 数据处理! S* W$ ~+ r3 ^' {' G& T, x; W
Data processing, 数据处理
4 j5 _4 y; F8 ]) l3 l$ JData reduction, 数据缩减5 c+ w5 O$ n2 X
Data set, 数据集" F, R; w+ ?5 O. }! [/ Z
Data sources, 数据来源
( p$ W' v; e$ Q$ T0 [1 O. Q! bData transformation, 数据变换
* d* q- v' k6 a3 }) r% c& M1 s; hData validity, 数据有效性
2 n$ K. U" Y, R! gData-in, 数据输入) E5 i! M C% [; v+ S0 g5 z9 O7 W
Data-out, 数据输出; c/ |: g% a; ~$ F4 t: k
Dead time, 停滞期
0 s) b5 R4 X- h' w6 sDegree of freedom, 自由度
/ l2 N. F% Q5 [% V3 d9 N SDegree of precision, 精密度! g5 y \0 f/ R' R6 X# }" }
Degree of reliability, 可靠性程度
6 [ J$ l8 a* K7 s. VDegression, 递减
9 P& D6 R* l0 V% {2 B- \" g* ]Density function, 密度函数
: L% T; U! y9 J" h* F( u5 B/ JDensity of data points, 数据点的密度/ `, ?, p" v) w K
Dependent variable, 应变量/依变量/因变量
- u6 A: |% Z- O# X6 XDependent variable, 因变量
& w( g1 V% Q2 w% h6 x ]2 K* VDepth, 深度
' }0 A% D3 e: FDerivative matrix, 导数矩阵
1 ?0 k0 O6 ~+ ^$ pDerivative-free methods, 无导数方法
/ H/ I" P# M) P8 U# I. e R% yDesign, 设计
! M& {& Y2 F u- j$ d; i$ B$ |Determinacy, 确定性
) C q) j3 a# d' r( _- sDeterminant, 行列式
; `8 M- f! z9 b6 C4 T$ x. HDeterminant, 决定因素+ [8 x: k9 |$ {5 A" @9 b
Deviation, 离差* w. y: N; D* u8 N" B) F: F
Deviation from average, 离均差0 i+ Z: }, v+ H* |& i$ M
Diagnostic plot, 诊断图: C' z8 |. F8 J6 k! e4 b0 d
Dichotomous variable, 二分变量
3 z8 V4 V7 R) W. ADifferential equation, 微分方程( R; O* o1 `* G, p2 Y
Direct standardization, 直接标准化法
: D) d9 l' t. C+ R' H- H8 m% }) ?" O+ LDiscrete variable, 离散型变量" y! ?, W! g# L+ l: _( S: j
DISCRIMINANT, 判断 * D- ^$ D7 O8 j& i) A6 ^& [3 H; k7 y
Discriminant analysis, 判别分析0 t- @7 u8 M0 l" C) \3 f( p
Discriminant coefficient, 判别系数, ~2 b' O5 V& K0 |6 x7 A' S
Discriminant function, 判别值
3 \8 w2 y& Z5 p- H/ p* aDispersion, 散布/分散度
0 |; O+ t% A' L; J kDisproportional, 不成比例的# x/ g" |; l+ M+ ]
Disproportionate sub-class numbers, 不成比例次级组含量
. w. y# G& s3 c V% V" MDistribution free, 分布无关性/免分布- S) n* E; S i) G4 q# X$ n
Distribution shape, 分布形状
) A3 g* r# r1 u% R3 D3 eDistribution-free method, 任意分布法 A8 W3 V3 F& o/ c; u
Distributive laws, 分配律
, ~# N% ~2 [ o. SDisturbance, 随机扰动项
0 n& q' ?5 ~4 Q: u9 h3 L, QDose response curve, 剂量反应曲线4 N6 @/ c% j0 o, V
Double blind method, 双盲法' u+ W4 T: L/ P+ X8 l
Double blind trial, 双盲试验
( M7 d+ a: |8 h# K/ ODouble exponential distribution, 双指数分布
9 n' { d( t6 h$ L. h0 vDouble logarithmic, 双对数
/ [: i: ]. I& c5 pDownward rank, 降秩
- F/ w- X0 r7 L xDual-space plot, 对偶空间图 ^( U' h& j' z9 Q
DUD, 无导数方法1 B. \% n% F8 t& G9 ?. K4 T5 k5 t
Duncan's new multiple range method, 新复极差法/Duncan新法
+ R2 e9 z& m0 R( iEffect, 实验效应6 f1 g6 Y- z) B- t
Eigenvalue, 特征值, Q, V- T9 Y5 X" v7 k: G' S1 d4 d
Eigenvector, 特征向量4 ?6 R# \) `; p
Ellipse, 椭圆
! p/ Z8 x r7 F( u3 ^4 ]Empirical distribution, 经验分布
; }; G( M# n7 d4 [Empirical probability, 经验概率单位
. U% t' m1 W' h# DEnumeration data, 计数资料. `/ j9 j& U$ {; G* ]5 v
Equal sun-class number, 相等次级组含量7 T# y+ o4 l M% M3 x2 v
Equally likely, 等可能8 a) A; C+ r, n$ ^0 O/ D$ o
Equivariance, 同变性* i( z1 Q3 d5 N& X
Error, 误差/错误3 S$ d; C/ S( C" [
Error of estimate, 估计误差& z+ t% r/ j/ h, W. V
Error type I, 第一类错误- ^7 T' m8 ^+ f
Error type II, 第二类错误
) ^1 b: ~* ^; D1 @, T+ NEstimand, 被估量 E8 R3 ~9 w$ X8 ^
Estimated error mean squares, 估计误差均方
( W/ n+ u2 W2 l& n* M, KEstimated error sum of squares, 估计误差平方和% b7 B; E4 r ]( X" W7 f/ s
Euclidean distance, 欧式距离
0 k9 H. H" |0 [0 K: x* m" fEvent, 事件0 b; j" Y8 k& \
Event, 事件
' R8 I8 y& |0 q1 e% hExceptional data point, 异常数据点% Q0 S/ c: H( _& G
Expectation plane, 期望平面# U9 S" f) G; d" `* ?
Expectation surface, 期望曲面
2 }5 Y+ U9 y3 \: C! A1 `/ jExpected values, 期望值' Q% U# d) }: \8 _
Experiment, 实验9 a$ x2 Z$ S8 U- [% f8 R, _% z
Experimental sampling, 试验抽样
" V+ Z& L% O9 L7 kExperimental unit, 试验单位
+ B4 e8 R) [8 X$ i& j6 _5 gExplanatory variable, 说明变量
# W J. T F, h9 rExploratory data analysis, 探索性数据分析
* {( M# n# ?( b( j% d1 @' Z$ M A, tExplore Summarize, 探索-摘要
3 {4 Y0 H3 W$ R& x& ~8 @' IExponential curve, 指数曲线) C& s+ D; E) G
Exponential growth, 指数式增长
7 \8 M5 G, x p( N5 q; ?& pEXSMOOTH, 指数平滑方法
. }) O- X$ N2 j. \# L ]$ jExtended fit, 扩充拟合
+ I4 M4 Z* d# CExtra parameter, 附加参数
( W$ {& J4 X) ]8 | V5 TExtrapolation, 外推法0 `& }+ f \" D' [" o
Extreme observation, 末端观测值
6 j& @5 f" f1 L8 x: H A6 HExtremes, 极端值/极值
3 D: D; t) x7 O& EF distribution, F分布
; u" J5 B$ b4 L% A$ B4 PF test, F检验7 ~8 {8 V8 C3 w6 K
Factor, 因素/因子* | g: Q; l% n! y# T. C
Factor analysis, 因子分析" ]# j; I/ s; H: I- P( _
Factor Analysis, 因子分析. l0 P" F5 }" y5 X' o
Factor score, 因子得分 6 V+ b3 Z4 z3 h8 H
Factorial, 阶乘 g6 ~* ]: s1 Z/ l% y) @
Factorial design, 析因试验设计5 Q( q: S7 f6 A( q
False negative, 假阴性* k6 O y, a3 e- X ~. a0 K# L
False negative error, 假阴性错误
$ o2 a p2 f& \; F! NFamily of distributions, 分布族
. b5 z _. b& S/ UFamily of estimators, 估计量族
: a* [8 }+ \0 \; C4 e Q8 ?1 QFanning, 扇面
$ h( z' B8 l6 w7 K2 t' T3 SFatality rate, 病死率
- W9 l& o: L/ d: wField investigation, 现场调查( C2 e* f- @$ x# b b9 K
Field survey, 现场调查
3 Q* b3 V2 R) l9 k' ?2 [+ XFinite population, 有限总体1 V, w, g: e" W3 Q' ^
Finite-sample, 有限样本
/ O- t' [7 D2 [/ T [- s5 y" S& }3 fFirst derivative, 一阶导数# V' t2 d" @1 c% R
First principal component, 第一主成分- k) o6 {2 O$ d* b# T5 x- j
First quartile, 第一四分位数5 f( q& g5 y! l6 g) y' A' |
Fisher information, 费雪信息量
# T4 f$ B, \1 f; i! zFitted value, 拟合值0 x& t) u# c, K1 u
Fitting a curve, 曲线拟合& B8 h) s4 W' [
Fixed base, 定基
$ N" c4 D! t2 o0 C: T" MFluctuation, 随机起伏
0 F/ f" ~* u4 N: Y( cForecast, 预测$ X- I9 h T$ x9 C* h/ G
Four fold table, 四格表1 _0 B4 [% y) T9 x. U) O6 Q+ D
Fourth, 四分点% X! {+ g4 [; \
Fraction blow, 左侧比率, Y% P l3 d4 b+ A* `
Fractional error, 相对误差
' O9 U* ?! E5 H1 \5 s4 ~Frequency, 频率& G/ I' F" t! l+ [
Frequency polygon, 频数多边图
- L S" e+ ?1 }! U! |Frontier point, 界限点/ V9 L; S+ C( J8 n3 F3 A
Function relationship, 泛函关系
5 ^$ Z: K) x) g' L" OGamma distribution, 伽玛分布. Y8 d. Q0 u+ L# Z% \3 ^( v
Gauss increment, 高斯增量
3 ~; {! X" e# N/ L: _) I1 {& |Gaussian distribution, 高斯分布/正态分布4 q3 t& C6 P5 x* Y# I, a# a
Gauss-Newton increment, 高斯-牛顿增量
- B% n. i3 D& M8 L5 ?6 v, OGeneral census, 全面普查. i& V- f; W2 w* L8 m, l. U
GENLOG (Generalized liner models), 广义线性模型
1 n6 o3 `$ z( p( L# f1 aGeometric mean, 几何平均数
; i4 B* S4 J) k+ ^1 b& V* |* A& P6 YGini's mean difference, 基尼均差
& @6 O: V9 E: D4 ^; ~; UGLM (General liner models), 一般线性模型 . \3 t7 g3 h$ C; x4 v$ q
Goodness of fit, 拟和优度/配合度
& _) y3 \( M5 x4 i% ^Gradient of determinant, 行列式的梯度# K ^* h8 K* N3 O- o
Graeco-Latin square, 希腊拉丁方3 q" |3 w5 W3 `6 K
Grand mean, 总均值
2 E5 k8 U% @! m( j$ [Gross errors, 重大错误
& T8 Q9 C: e$ M' Z- t9 s1 b% Q" k; gGross-error sensitivity, 大错敏感度
& J+ l+ G0 E/ r, BGroup averages, 分组平均! ^$ h4 ], G6 [9 Z0 S
Grouped data, 分组资料
1 x# N e8 F5 c9 o `5 LGuessed mean, 假定平均数* L4 Z- [. w4 y9 N" K
Half-life, 半衰期- b2 r& `: v7 k+ e
Hampel M-estimators, 汉佩尔M估计量! {$ e. s: t/ N, \
Happenstance, 偶然事件
( i; m6 Y3 t EHarmonic mean, 调和均数. U; P, ?$ V" B, R* D- |/ ]
Hazard function, 风险均数1 Z2 b$ r/ M7 M2 V8 ]7 G4 f) j" c+ S/ ~
Hazard rate, 风险率
) J2 m# V: M$ q6 d' @Heading, 标目
6 @8 E/ o% S) @ lHeavy-tailed distribution, 重尾分布
+ k X# \8 |7 {& ^6 X8 y5 f2 dHessian array, 海森立体阵+ e3 @* o8 r1 }
Heterogeneity, 不同质
" M& E% a: e" I9 UHeterogeneity of variance, 方差不齐 ' B# K8 [ P- }( q9 w( S* `
Hierarchical classification, 组内分组
8 n# c4 o7 s( Z( fHierarchical clustering method, 系统聚类法
$ |& r5 V; h& h- s& xHigh-leverage point, 高杠杆率点2 w K, t! H G* _8 X& }
HILOGLINEAR, 多维列联表的层次对数线性模型2 k: x( U' N7 h5 @. b/ \
Hinge, 折叶点6 y& p- y" a G
Histogram, 直方图+ S/ S* r& D1 L' b8 c' T H
Historical cohort study, 历史性队列研究
5 m0 A' r) A9 T* `. d \- aHoles, 空洞# y- ~% p& M J0 A( F8 |
HOMALS, 多重响应分析
9 y% E- ~ F; r, u+ UHomogeneity of variance, 方差齐性
8 h, [ D, m* EHomogeneity test, 齐性检验
0 h2 {) h6 ?) [& p; u- cHuber M-estimators, 休伯M估计量9 j- Y& E& A2 r; E
Hyperbola, 双曲线
7 _/ k$ F! s0 T% p5 JHypothesis testing, 假设检验" P/ R( I9 w, [: M
Hypothetical universe, 假设总体
( V4 k, F3 `" D: y7 h8 P8 b/ h( OImpossible event, 不可能事件& W, N1 d9 E8 q8 ]% \, w7 E
Independence, 独立性
* z3 F" K1 |7 x# ~ X C1 UIndependent variable, 自变量. r, y% I- d' @5 u0 L2 m& x2 t1 d
Index, 指标/指数) Q( p! ~$ Y% g1 b- y
Indirect standardization, 间接标准化法 ?+ J w7 ~& v" b0 }( r
Individual, 个体6 E9 I0 { w' m9 P
Inference band, 推断带! y* m$ T$ ?! G9 r5 B& i
Infinite population, 无限总体, \! I, z$ q2 c' k; a; i, {6 W
Infinitely great, 无穷大- X y7 h3 O. q5 ~- C
Infinitely small, 无穷小
l6 U9 f2 D n' f8 RInfluence curve, 影响曲线
4 K! S0 o. l3 a/ a, wInformation capacity, 信息容量" D9 Y ~9 o$ H+ |6 Z$ a) r& v! ]
Initial condition, 初始条件
& z9 |! V3 K9 Z+ r: Q# L4 iInitial estimate, 初始估计值
8 b3 h4 r1 U, A$ e9 iInitial level, 最初水平% h2 b' b7 v' p- p
Interaction, 交互作用/ ` {# d$ @' I' h% }
Interaction terms, 交互作用项
6 Y o9 U8 I7 K% KIntercept, 截距 l8 o6 O6 m* _( f+ C! ]
Interpolation, 内插法8 [3 ^) j3 a5 x
Interquartile range, 四分位距
; R: O2 a6 l( l* h" n0 q, qInterval estimation, 区间估计
0 e5 \5 ~2 A* W. YIntervals of equal probability, 等概率区间
2 T1 Q' F1 {. `; UIntrinsic curvature, 固有曲率$ b; s# ~$ d/ |/ ^0 k# s' w
Invariance, 不变性/ U4 n6 E9 q9 m" a! _: r& h
Inverse matrix, 逆矩阵
2 O1 q% W4 S! q/ o4 @7 ?0 |' }Inverse probability, 逆概率/ b D# q3 B$ S' m0 `% J( ]% e3 B1 ^
Inverse sine transformation, 反正弦变换. y2 w8 l3 c0 S6 y) P
Iteration, 迭代
" S9 b' m' a1 a; J0 q9 ~& LJacobian determinant, 雅可比行列式. P1 b0 l' v" [7 Q @; K
Joint distribution function, 分布函数1 q! y0 ^+ E; E5 S+ X
Joint probability, 联合概率! H, |% H: {1 T
Joint probability distribution, 联合概率分布% [( g( r1 R* a- r' Q
K means method, 逐步聚类法
7 J8 i1 `# n& s. Q5 E3 FKaplan-Meier, 评估事件的时间长度 & [; C+ w9 v) k% B
Kaplan-Merier chart, Kaplan-Merier图 g' _5 q4 p. J. ^7 a# Q; |
Kendall's rank correlation, Kendall等级相关
9 N" P6 ^' n4 B- L7 ^7 YKinetic, 动力学
6 b" h4 g" ]+ Y5 H9 a1 wKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验7 C9 W1 K% P. l. o
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
+ X: Y) B |% H9 dKurtosis, 峰度
; Y1 W$ u( P% {& q5 t- RLack of fit, 失拟# M! Z; F. }& r# z( O6 Q& S" _
Ladder of powers, 幂阶梯& O \& ?) u' D" i# B& Q5 A1 \4 |
Lag, 滞后" T. Y8 u( [# z0 h$ ?9 ~8 F/ g5 d
Large sample, 大样本8 o! T; o( k+ A* n
Large sample test, 大样本检验( b* a: o2 _1 Q% K
Latin square, 拉丁方8 F! {3 r5 {0 W- Y
Latin square design, 拉丁方设计
7 i6 h; E- n% ~1 PLeakage, 泄漏1 j- A( G( }$ S% a" |9 _
Least favorable configuration, 最不利构形
7 E) p- G! G, w m, FLeast favorable distribution, 最不利分布! E) q% Z, q2 q( g
Least significant difference, 最小显著差法
! C0 A$ F- }+ ]1 g4 rLeast square method, 最小二乘法6 c' W" ^* J: O& S: X5 u+ `
Least-absolute-residuals estimates, 最小绝对残差估计8 Y- i7 Y1 I- W5 G$ B. E
Least-absolute-residuals fit, 最小绝对残差拟合6 y9 j% `- c+ m. x2 x# V4 a8 }
Least-absolute-residuals line, 最小绝对残差线
, f. [5 \ j, K- i5 r" c3 z; ]Legend, 图例
- t4 G) y( a! ?! T1 \1 x" a7 C+ r/ B1 xL-estimator, L估计量
# b* A$ k# j0 S/ X8 h7 m% ^L-estimator of location, 位置L估计量1 W/ j h% O* J) F9 V9 J
L-estimator of scale, 尺度L估计量3 i; t6 r( _. @3 d
Level, 水平
: F5 L0 X2 o- w, |6 }% bLife expectance, 预期期望寿命# }8 q. |: `/ \7 o1 Q) J% [1 P2 G) a0 T
Life table, 寿命表; \/ ^6 ?0 V1 T/ |
Life table method, 生命表法
. f, Z5 }+ v) B/ L+ y# q% a$ i: JLight-tailed distribution, 轻尾分布
0 Z& N( @7 B7 ?6 lLikelihood function, 似然函数
, @, K6 {6 N( _; c( w9 Y$ ?Likelihood ratio, 似然比1 q* f3 ]2 t. K, K6 e
line graph, 线图) C4 I: b; R, Y- v# s
Linear correlation, 直线相关
" P* x4 M$ ^/ A% l V, ILinear equation, 线性方程# x$ W' r" _. I$ k
Linear programming, 线性规划6 x( w! f, U& y, X4 u6 m
Linear regression, 直线回归$ W. Z: d! }% i) R) C+ ^8 D
Linear Regression, 线性回归
. ]' w- B0 } w1 O! W8 ILinear trend, 线性趋势
, t2 z8 I( q! O% u3 O8 b% _Loading, 载荷 ! ?" a$ k: u" i! M# H7 M
Location and scale equivariance, 位置尺度同变性
3 ?; Z, f& D+ _3 d+ q' x$ }Location equivariance, 位置同变性
! r6 z; Z3 j+ V4 S! F k8 \$ L0 \4 pLocation invariance, 位置不变性
2 m2 ?- U+ J* U$ Y9 o8 }( ZLocation scale family, 位置尺度族, t4 o9 V+ Y: o, n0 d
Log rank test, 时序检验
; L$ L5 Z; a* {& P: r/ nLogarithmic curve, 对数曲线4 j" J0 Q; j: n' |. {8 Z% a
Logarithmic normal distribution, 对数正态分布) E, x, g$ F$ t% s' [! m
Logarithmic scale, 对数尺度9 |' y; C, g5 g: |
Logarithmic transformation, 对数变换! T1 p: i* C8 e4 ^: [
Logic check, 逻辑检查
: I3 E q3 ^, dLogistic distribution, 逻辑斯特分布0 f% {/ D# a4 ]/ e% p
Logit transformation, Logit转换
4 c1 I7 p5 @! A5 i) H5 G& [+ o+ fLOGLINEAR, 多维列联表通用模型
6 ]. t3 U" L. [: zLognormal distribution, 对数正态分布% Q! S- l A* F
Lost function, 损失函数
4 L5 L- \8 O. P, ?1 oLow correlation, 低度相关
" \% t+ N9 `6 z# G8 Z8 \Lower limit, 下限
# e3 c& ?8 k' A; c) g2 [: k pLowest-attained variance, 最小可达方差
; [3 K' p1 L4 `; T4 x. Y2 VLSD, 最小显著差法的简称% K$ l" O' a$ z. p: J' H
Lurking variable, 潜在变量) H" f; r, `6 Q6 q# e; H: {) T: K C
Main effect, 主效应) b) }7 J6 R* P6 g. h# p/ A7 n
Major heading, 主辞标目
. {5 x, t, q. MMarginal density function, 边缘密度函数
6 p; t- [- P/ ]9 i+ n& D9 tMarginal probability, 边缘概率4 X% u6 q2 g2 {7 N ]
Marginal probability distribution, 边缘概率分布1 o* M- f: c; J. `8 } f7 R4 |
Matched data, 配对资料
2 k+ S- \- |! v, r2 P! KMatched distribution, 匹配过分布
* w! Z7 q8 A" o5 fMatching of distribution, 分布的匹配& w. P# g6 ^( D6 E$ l
Matching of transformation, 变换的匹配
1 [8 W7 R% K3 M, FMathematical expectation, 数学期望6 _$ Z! c! d( g: B6 \7 I
Mathematical model, 数学模型; J( H3 Y$ l& G1 y B+ l/ h7 U
Maximum L-estimator, 极大极小L 估计量
+ F; t/ Z( L- M: K. NMaximum likelihood method, 最大似然法" U" `: ^) v- R6 M* X; I0 S5 B" k
Mean, 均数
: Y5 t0 p8 d9 F8 `Mean squares between groups, 组间均方
b4 V# N3 x5 D+ BMean squares within group, 组内均方
; B/ w+ n3 C& W! ~6 M/ BMeans (Compare means), 均值-均值比较0 h7 E1 e1 B: G9 l1 L
Median, 中位数$ }4 B0 C$ U- g: M" W& C+ |7 b8 o
Median effective dose, 半数效量! a1 C2 U y( N- h2 K6 e5 ]
Median lethal dose, 半数致死量
- H* R% v) j; x/ o! e2 V+ bMedian polish, 中位数平滑
$ L' v" y T1 SMedian test, 中位数检验6 g8 q# g' [: S; r* w- D- @- H
Minimal sufficient statistic, 最小充分统计量# K: X0 _% f% N2 I
Minimum distance estimation, 最小距离估计
2 G# S6 k" k, w# Z& W- ?2 {4 {$ SMinimum effective dose, 最小有效量
2 z% L8 c9 J; d/ g6 x$ x) u3 iMinimum lethal dose, 最小致死量
6 u" X5 |5 r4 P4 m6 |% r. AMinimum variance estimator, 最小方差估计量; J2 f/ q8 }! B0 r9 c$ L
MINITAB, 统计软件包
J* H3 x1 f* w. _6 ^* VMinor heading, 宾词标目
" s8 F! |! |; ?, x6 {0 TMissing data, 缺失值. F0 v* F4 s6 o3 w j- D
Model specification, 模型的确定
% c0 j( h) v4 I2 O" IModeling Statistics , 模型统计
! w0 T- \7 ?; n5 h' F! f8 bModels for outliers, 离群值模型; a; H) g5 \9 x# h
Modifying the model, 模型的修正
* i. d9 E; C4 e! g2 Q1 lModulus of continuity, 连续性模
4 a: H3 [" Y( N+ y/ w3 bMorbidity, 发病率
! E5 N% Z' b/ K1 v3 f2 eMost favorable configuration, 最有利构形$ D8 J3 S- l/ M, ~& A3 H
Multidimensional Scaling (ASCAL), 多维尺度/多维标度2 Q$ P1 _5 @ ]0 Z6 U: V5 N# T: N w
Multinomial Logistic Regression , 多项逻辑斯蒂回归9 D' o- d5 \: V
Multiple comparison, 多重比较
: v @, B9 v; O4 M% w7 H7 M/ \# L6 LMultiple correlation , 复相关, Y% `$ { m4 Y4 [3 ]# c) ]# P
Multiple covariance, 多元协方差, ?9 z8 I" {$ S/ ~
Multiple linear regression, 多元线性回归
) A9 [: @% [, x, ~# NMultiple response , 多重选项 z. d/ ?. y7 u5 \; `& w
Multiple solutions, 多解* c W# A/ Z2 k3 I [' o. f
Multiplication theorem, 乘法定理
/ o2 R7 K( s6 e. C. F) xMultiresponse, 多元响应+ Y' s0 j" T+ z6 I( l1 X( z
Multi-stage sampling, 多阶段抽样
. P1 _- p+ K& j, R% L/ B5 UMultivariate T distribution, 多元T分布8 s! p5 K# _4 D8 l& ~
Mutual exclusive, 互不相容
; ]" Q$ g) p% G! `9 ~) q" q* |- [- r `Mutual independence, 互相独立
* ?7 y3 H- n* A* N& HNatural boundary, 自然边界 C$ ?* K1 P0 j9 Y6 O9 t
Natural dead, 自然死亡
5 P8 L, k+ J/ M* i. \9 g/ YNatural zero, 自然零
& z$ J! L4 Y7 ]" r& ? PNegative correlation, 负相关# U" @4 }, F1 B( ^* ^6 c$ o
Negative linear correlation, 负线性相关
|" _& N# ?5 p* `+ XNegatively skewed, 负偏
# q* e! L5 [$ y1 p1 |$ PNewman-Keuls method, q检验6 s$ O. n/ N4 p! D: _- F
NK method, q检验
, Y. G& }* T: X& [; X2 B7 l) U: i0 ENo statistical significance, 无统计意义
+ l7 N% C- c9 HNominal variable, 名义变量- o/ q c4 a2 O
Nonconstancy of variability, 变异的非定常性3 \6 {5 i3 V m0 J7 |( q
Nonlinear regression, 非线性相关. j) ]1 \0 b+ B y4 i6 k# o; v
Nonparametric statistics, 非参数统计8 _. _' g* x( |6 I
Nonparametric test, 非参数检验
8 q7 D( l% o1 A+ l: E0 ]" kNonparametric tests, 非参数检验+ n+ U" ]4 d7 r5 V; d* _
Normal deviate, 正态离差
1 A& Y A9 i* R' i: S% PNormal distribution, 正态分布9 z& H* v4 }0 A, S/ L
Normal equation, 正规方程组
3 e. Q! `& Y+ J: C. O* z e4 }Normal ranges, 正常范围
9 [) L3 Q' B( Y/ z" eNormal value, 正常值) d5 \* J" d w9 h2 X0 _/ s
Nuisance parameter, 多余参数/讨厌参数' X$ J1 n$ f; t9 u
Null hypothesis, 无效假设 0 S/ C D+ ?7 G; p* z
Numerical variable, 数值变量( N% o) A: C5 i: Z5 V: y: s
Objective function, 目标函数
3 _. r6 \: _& [6 D1 x( }* p/ WObservation unit, 观察单位
, i) c# d0 t/ S3 N$ h IObserved value, 观察值
n" {7 r" y8 r- b/ F, V; i) C, vOne sided test, 单侧检验$ p4 Q; C* E4 ^9 Q
One-way analysis of variance, 单因素方差分析* C9 ^9 n% }! A7 r- {5 ]4 N
Oneway ANOVA , 单因素方差分析- z( s8 A% q- I, X% w
Open sequential trial, 开放型序贯设计
# }' h' y! o, r; v! R0 D; n7 }Optrim, 优切尾6 |+ \( S) J9 J3 e) w
Optrim efficiency, 优切尾效率$ X* u5 a# B: {( u5 f, s, Y
Order statistics, 顺序统计量# i" j* K" d8 A1 D
Ordered categories, 有序分类 z0 S7 x2 R0 m5 \( H0 r) s% b/ ?
Ordinal logistic regression , 序数逻辑斯蒂回归
0 P2 b: j) K+ s- v o2 vOrdinal variable, 有序变量& r" H3 h( g. X# O/ T- i
Orthogonal basis, 正交基2 A7 @) h: h2 I. g+ h' w( S
Orthogonal design, 正交试验设计) k6 }0 k. Q- W, c5 i
Orthogonality conditions, 正交条件
3 D7 b, v5 A: A: X2 e" Q/ hORTHOPLAN, 正交设计 / R( N& F0 |2 P g* L" y, F$ m' w
Outlier cutoffs, 离群值截断点
) J$ b: \) ]8 O+ AOutliers, 极端值
. }$ h- g% F V4 ^$ x$ KOVERALS , 多组变量的非线性正规相关
. |3 z3 a' @# U" @8 a, ?* P, @5 R nOvershoot, 迭代过度3 t) l% d* C0 f/ R! S
Paired design, 配对设计: _! a2 A- r+ P* X6 R% S
Paired sample, 配对样本 @0 P+ T" [) X5 o! u" i1 C
Pairwise slopes, 成对斜率
. o* C; x% X$ ` E! T ~9 {Parabola, 抛物线& x, ^7 {8 E$ ?6 G9 G" r
Parallel tests, 平行试验
& L; _9 @/ s+ V" v5 vParameter, 参数0 l% V0 ^/ [0 f7 s3 H1 f
Parametric statistics, 参数统计
6 r9 x3 j& q H; L8 [( M7 zParametric test, 参数检验
; s2 p* i/ B2 `$ V5 m/ K* EPartial correlation, 偏相关
# ?! Z1 ~/ P; }, [, m3 z: ^/ w5 OPartial regression, 偏回归
) d" y6 K, I& l7 `7 N6 u g$ {Partial sorting, 偏排序- i* p5 W ^& Q, O' {) a+ i% |
Partials residuals, 偏残差( q! z" F8 \% d, k2 t/ d
Pattern, 模式
7 W1 \: D$ a9 E. q6 i( }, P! uPearson curves, 皮尔逊曲线$ D% g$ W0 w' u8 _: ^$ l
Peeling, 退层* |* w/ }. s7 W. I: g
Percent bar graph, 百分条形图1 N; k4 J' g# S* w" G2 I0 F
Percentage, 百分比
& ^! g2 i' O+ P5 ?6 APercentile, 百分位数
; P, M9 w; d* T+ X$ IPercentile curves, 百分位曲线
. G' [2 J4 @2 E, n) sPeriodicity, 周期性
1 g0 p d# c/ e; k) _0 [. ~Permutation, 排列8 O0 p/ e. d! c- e( B( o( O! |3 u
P-estimator, P估计量2 ~% e" X7 A5 Y F" N: W0 W
Pie graph, 饼图7 } R* e% r$ {
Pitman estimator, 皮特曼估计量: A) I8 `2 X9 b# n- N
Pivot, 枢轴量, P" v8 ?% m) }! @4 ~% B
Planar, 平坦
; H3 m" E. U. M+ `/ ?Planar assumption, 平面的假设/ {5 v" `! U# [ c$ b( \
PLANCARDS, 生成试验的计划卡 i) Z8 B) A2 r7 E* @
Point estimation, 点估计
9 p0 |6 L( y, s" }9 @Poisson distribution, 泊松分布
4 s( r3 i( m7 K: A i; Y9 Q/ m" K+ Z- VPolishing, 平滑
8 f5 \3 y# ], d3 l0 V6 mPolled standard deviation, 合并标准差& I) x0 N. p5 y
Polled variance, 合并方差- d, d9 z. e9 Y! \3 y( n
Polygon, 多边图
" @% @+ ~3 D# D& kPolynomial, 多项式$ ^7 v9 ^5 T, n! n
Polynomial curve, 多项式曲线
" G" O1 T' C( c# ]$ S$ VPopulation, 总体& m0 Y4 u. o% `9 l- a' i" d
Population attributable risk, 人群归因危险度( |% W$ H' _. L9 t! j/ d O
Positive correlation, 正相关
% Q: B1 {5 Y; |7 Q6 `4 gPositively skewed, 正偏
2 ~1 e2 G6 F( g7 `' ?Posterior distribution, 后验分布
* ]$ c7 g: ?# F: i TPower of a test, 检验效能/ z* D7 Z2 l0 D% j {
Precision, 精密度
7 A: n9 F% H. E5 F" h. B l2 BPredicted value, 预测值7 Y8 T7 Q5 b+ M
Preliminary analysis, 预备性分析' f* d$ l) C6 _, W, l6 }5 s) h0 ^
Principal component analysis, 主成分分析# V6 |, X( E, ]0 H: x' R
Prior distribution, 先验分布
. v5 b, |: s# a$ EPrior probability, 先验概率
2 |% P! q7 b& |4 D0 G2 C. |; g) o h6 UProbabilistic model, 概率模型% X: z; A9 W# M" I ^5 v" E
probability, 概率
% w# \6 }" u" x9 {. i- M; w; AProbability density, 概率密度8 k/ j# {6 G7 d: q& ~0 e% j" e
Product moment, 乘积矩/协方差
4 x: r( Y. @5 c- fProfile trace, 截面迹图
1 i" c! F1 \* d: w+ m% oProportion, 比/构成比& q5 ^: A, ~# f
Proportion allocation in stratified random sampling, 按比例分层随机抽样
# N( `4 D: J/ ?: iProportionate, 成比例
' X2 i; C5 V% JProportionate sub-class numbers, 成比例次级组含量; Q1 y0 f& o2 \5 e- ~7 j& i
Prospective study, 前瞻性调查
6 c% D) x( z, `Proximities, 亲近性 " y" c. I, ]3 d
Pseudo F test, 近似F检验
& O4 x: Z( I' p% r3 [; `Pseudo model, 近似模型
: @$ A* g0 v* N) b6 K6 I# d1 u1 _Pseudosigma, 伪标准差& t |- [6 b7 Q l+ L) [' Y
Purposive sampling, 有目的抽样! ?# _1 B6 t/ A' X7 I# [
QR decomposition, QR分解
* o# V9 k% o9 \$ kQuadratic approximation, 二次近似3 h0 T0 [' c5 H5 s6 a
Qualitative classification, 属性分类- |* j! V- o/ ], c: z! |3 F
Qualitative method, 定性方法' C M# E/ B" m) [
Quantile-quantile plot, 分位数-分位数图/Q-Q图7 Y+ E, B+ P' K$ S) J
Quantitative analysis, 定量分析$ e4 o- m2 X1 L2 H! d% ?: j2 F
Quartile, 四分位数
, A: U1 R. g3 u" u0 t9 @, b# f* qQuick Cluster, 快速聚类 ?+ h$ m2 a$ l" R# z7 H) Y" _- s
Radix sort, 基数排序
& o" _) X5 L2 g7 `Random allocation, 随机化分组+ R# u F' `1 e: a
Random blocks design, 随机区组设计1 d& t9 W( Z$ P. N
Random event, 随机事件
) j/ c* w; [1 R. yRandomization, 随机化. `5 l3 ?3 p' Q+ J
Range, 极差/全距
8 g' u) S: r) t; z; pRank correlation, 等级相关& U6 [ M' l" t+ J3 |3 J6 [$ j; J
Rank sum test, 秩和检验1 ^5 X9 K% C3 O3 ^; O% S! w
Rank test, 秩检验
. `" v0 P9 r- M; k' FRanked data, 等级资料
. u# F, Q8 V- R C9 b2 PRate, 比率
# M' n4 k3 W5 V' |+ C* T3 ?' e+ HRatio, 比例2 e+ w% M$ l! R
Raw data, 原始资料
5 Z! B) O1 V3 N- ~Raw residual, 原始残差4 q& y& c. i: F; `
Rayleigh's test, 雷氏检验4 C. a. s3 a: n/ {7 F
Rayleigh's Z, 雷氏Z值
6 z. b2 M+ M( V* dReciprocal, 倒数; W* x* h2 `1 G, t$ }
Reciprocal transformation, 倒数变换
9 z# L2 s: Z5 D# I# n$ D& URecording, 记录1 w/ \3 S$ {+ M6 b
Redescending estimators, 回降估计量
1 n% C( L* M) A* t9 \Reducing dimensions, 降维) O' y8 o9 | P6 B
Re-expression, 重新表达( t' a( M* |+ e/ j8 s
Reference set, 标准组2 ]+ _. S4 D: K4 i+ g5 i
Region of acceptance, 接受域
# l% e+ L4 ]& i) Q0 b+ FRegression coefficient, 回归系数
- }. k9 _* g' w. F( ZRegression sum of square, 回归平方和 S6 M" I( Q+ u$ N0 ]2 x
Rejection point, 拒绝点* W. k' |5 k- Q2 ~% x- \0 s9 x
Relative dispersion, 相对离散度& ~# N* p& c& \5 S! ~3 z
Relative number, 相对数" ^. ~3 Y" L& W/ T" q
Reliability, 可靠性2 g. K- k2 n7 g/ l J; `2 e
Reparametrization, 重新设置参数
( ?) z' l5 R- q% n7 o) @& Y- eReplication, 重复
) g! j; q& Y! s1 s& v& J- @Report Summaries, 报告摘要 u! u: P1 g- n& h, s% \
Residual sum of square, 剩余平方和: R5 d4 Z% l1 t* r/ p* j5 w3 g& j3 X
Resistance, 耐抗性6 @2 A0 g4 U S( A% n
Resistant line, 耐抗线- g; V2 c- v7 g" `5 W& L
Resistant technique, 耐抗技术. Q: i0 y( K5 R" Y9 @
R-estimator of location, 位置R估计量
7 n/ f+ Z# S' \6 |R-estimator of scale, 尺度R估计量, n2 ]! j" J9 j9 x) |, p
Retrospective study, 回顾性调查( Y% W3 ?$ j6 W
Ridge trace, 岭迹
: J4 c+ V0 s* B% J0 l0 IRidit analysis, Ridit分析+ A+ s. m3 j! @
Rotation, 旋转
! G. T3 g. M5 Z+ M% D- X: H5 W. DRounding, 舍入
& G7 M4 K* v% o3 DRow, 行' N, b/ y* Q) a. G7 @# X
Row effects, 行效应( A% s5 ?. N* @( P$ ]( g- Q
Row factor, 行因素
" a6 M9 m/ n" RRXC table, RXC表* B: j" }1 P& e4 q. m: S
Sample, 样本
( Q- I6 B7 C( |; W% s# aSample regression coefficient, 样本回归系数5 n9 Q: q& i/ n( c( d& X
Sample size, 样本量
0 z) g% Y* p5 t V) DSample standard deviation, 样本标准差, a4 g) w& u5 G% h$ N1 S2 V( L2 l
Sampling error, 抽样误差
' w& I2 M3 x: y! q! z4 BSAS(Statistical analysis system ), SAS统计软件包, x1 E2 P/ W& U+ n7 N, o
Scale, 尺度/量表
5 F/ v6 ]. ^ f) ~# S! X# \Scatter diagram, 散点图5 G9 M" j% `0 Y8 O( W. T" o
Schematic plot, 示意图/简图
- A. j6 e4 G: r$ GScore test, 计分检验& |% e* R/ t# R7 }* P& J4 n
Screening, 筛检9 G$ c9 I, J) f8 Y$ x
SEASON, 季节分析 3 s" D- b8 }2 ]& H5 x- Q6 F" E
Second derivative, 二阶导数
. B; X( k) X1 \; Z% z0 [" G i1 kSecond principal component, 第二主成分. `% U. Q- `) t5 i# o9 v4 ~* t, o8 t
SEM (Structural equation modeling), 结构化方程模型
& X" Z* t* m6 m: S) U7 e% M" _9 H1 wSemi-logarithmic graph, 半对数图
7 w6 I; I8 [: M% b3 m# ]7 S, QSemi-logarithmic paper, 半对数格纸
, Y& c5 w4 b( R" P( p6 g7 KSensitivity curve, 敏感度曲线
9 E) t6 X* ?" B9 P( jSequential analysis, 贯序分析
: v' n# X6 h' f' RSequential data set, 顺序数据集 F8 S% Z& \6 ^& H
Sequential design, 贯序设计$ l# S/ e9 _" A5 `3 z! ]7 A
Sequential method, 贯序法
: T+ C7 A" d" K3 U+ X sSequential test, 贯序检验法
2 \7 m* T2 b8 uSerial tests, 系列试验
, G7 T _) y9 u1 S$ i" {Short-cut method, 简捷法
2 ?" [; t+ ?1 a& J8 ISigmoid curve, S形曲线% \! e; D# ~$ T% t: Z+ z9 U2 Z
Sign function, 正负号函数
8 B# A) g) E. b* g KSign test, 符号检验
& {, ~' w+ |' V% [' i. v: @' \Signed rank, 符号秩
2 t0 c" X X ]' T+ mSignificance test, 显著性检验% w+ T- d: x& Y; D
Significant figure, 有效数字8 G0 ^8 c4 n$ V
Simple cluster sampling, 简单整群抽样+ }4 f. M K- q0 N" h& i5 t
Simple correlation, 简单相关
' C; s( U% i" O0 aSimple random sampling, 简单随机抽样$ E" P5 e. |8 \' o' z$ O7 c8 L
Simple regression, 简单回归3 e! j' ~+ _6 A, d) O
simple table, 简单表
- J% q( ~( r& f" `Sine estimator, 正弦估计量
$ S' L7 R; X2 I: b ISingle-valued estimate, 单值估计
+ a% C) F) p+ U9 oSingular matrix, 奇异矩阵
8 C3 j# I+ X7 _7 D* ~8 h0 zSkewed distribution, 偏斜分布
7 v! ? a5 K- b& x7 FSkewness, 偏度
" k9 Q4 Y' }& v% bSlash distribution, 斜线分布( s0 U6 i4 j& B5 [8 @' H, e7 O' X! i
Slope, 斜率
" Y( \- N" y$ ~2 w9 H# `0 H5 x8 SSmirnov test, 斯米尔诺夫检验" r% x: D) ^' \# _
Source of variation, 变异来源+ V8 T& U# E k Z# U
Spearman rank correlation, 斯皮尔曼等级相关
0 z. ` ~% |# i+ I( Z: ISpecific factor, 特殊因子
! m" D' p9 K0 O: PSpecific factor variance, 特殊因子方差0 Q, y- I9 e# p7 T
Spectra , 频谱
8 O! j; Y! \0 t5 I/ V8 e4 N2 i6 E. S/ TSpherical distribution, 球型正态分布, L) y7 D; g9 R p4 v
Spread, 展布
( |- w3 @4 I. T9 MSPSS(Statistical package for the social science), SPSS统计软件包
! `5 \& F: n4 n+ RSpurious correlation, 假性相关
6 I+ _: W' ]0 s1 s& j' o0 ZSquare root transformation, 平方根变换9 a; |/ `' Y9 \0 s; g
Stabilizing variance, 稳定方差
5 I( w5 N4 h* n: N! E: TStandard deviation, 标准差
: v, r6 h5 h+ \& W* I* zStandard error, 标准误3 V+ F4 c5 h: I
Standard error of difference, 差别的标准误0 h- C9 w; ?3 _
Standard error of estimate, 标准估计误差
; j8 w% z: G8 r/ L( A/ {0 M2 @9 QStandard error of rate, 率的标准误: ?, O7 P o( R5 n- ^- l4 K; f( s
Standard normal distribution, 标准正态分布( W% f" U" m, ~7 V8 n6 c! S4 y
Standardization, 标准化
+ j. u. F# I7 A+ i3 p1 KStarting value, 起始值8 o3 g! `* \4 A5 d" T5 y/ H8 ^" i
Statistic, 统计量
- a" d+ D3 d3 _6 m8 C1 ]. D8 wStatistical control, 统计控制; j1 t' I9 D# x2 F
Statistical graph, 统计图
- ~# X* r, D, ^% f3 t/ aStatistical inference, 统计推断( b6 R8 p3 ] [" \
Statistical table, 统计表% l( a) z! Z b; }$ y# C. R
Steepest descent, 最速下降法
# d0 A. ~ [' F: O wStem and leaf display, 茎叶图8 b& M$ H3 v8 o4 k
Step factor, 步长因子
& p$ [- e- w8 x5 F6 h xStepwise regression, 逐步回归3 M' |4 ]$ t5 h B/ O: @
Storage, 存
3 H1 f9 b' G3 s# N1 zStrata, 层（复数）0 |5 ]' M4 V8 T% K, E7 m
Stratified sampling, 分层抽样
3 d4 X, X0 \/ I: z9 X6 EStratified sampling, 分层抽样2 |9 K( C D8 ^& o1 J
Strength, 强度+ |9 s$ D8 o9 N& K+ O0 @' f
Stringency, 严密性
7 M; T6 {; Q7 v1 Z% ^, eStructural relationship, 结构关系
! T1 F4 {$ \9 q8 ^* dStudentized residual, 学生化残差/t化残差
& s. F. k+ x/ j' L2 MSub-class numbers, 次级组含量
' Y3 \" i7 h8 Q# ~" {0 f gSubdividing, 分割
3 P, y- Y0 H7 \Sufficient statistic, 充分统计量6 v5 b9 F E6 h
Sum of products, 积和
& ]/ k5 U, Q8 ASum of squares, 离差平方和
; |% {7 ]. H" v1 [Sum of squares about regression, 回归平方和5 e7 I/ E4 t, B1 H
Sum of squares between groups, 组间平方和0 s" i8 p1 W3 b: g) X
Sum of squares of partial regression, 偏回归平方和
; e" b0 ]3 J6 N/ n7 K& e& f' ?& NSure event, 必然事件
" j5 f+ h' V( p6 y6 vSurvey, 调查
8 \) k- d9 }4 C3 d; }+ J( qSurvival, 生存分析
$ P* e- s( x$ g d: LSurvival rate, 生存率
$ |4 M' L! b% l# v w5 MSuspended root gram, 悬吊根图1 ?9 P+ t; C: Y$ d$ E
Symmetry, 对称
8 n* K) K: Y0 L3 e% g1 R1 QSystematic error, 系统误差
; W$ w9 M9 m6 ?# TSystematic sampling, 系统抽样
6 F* m7 r9 T# h) F. j( v' Z. KTags, 标签
- n$ x u; H$ u7 \. }4 eTail area, 尾部面积
& [' D, V* c/ [. pTail length, 尾长
s( w1 ~- q- a* P: m4 S ~+ fTail weight, 尾重# v3 K! y6 g3 n# p
Tangent line, 切线
0 G ^/ k! o# F" N: mTarget distribution, 目标分布; d, ]; V2 ?8 i. S
Taylor series, 泰勒级数
, L! f/ t) |: e# R7 j7 O$ `" B6 F. eTendency of dispersion, 离散趋势- L- }6 W: L7 K* Q/ B
Testing of hypotheses, 假设检验
9 Z4 ?# W5 e. c# dTheoretical frequency, 理论频数& t: a6 o9 t2 z1 {: E$ l
Time series, 时间序列' i" @( {. @6 G# H2 n% u* n
Tolerance interval, 容忍区间
- S# [( y. v6 _: O; i: M" RTolerance lower limit, 容忍下限+ v# W6 R( l/ c: [5 U: A5 U# }
Tolerance upper limit, 容忍上限1 p- P. B$ X* W- m* d6 }7 \, o
Torsion, 扰率4 c& K$ V. Z5 K0 u9 W7 b+ A% l
Total sum of square, 总平方和) ?6 u9 b& Y8 X
Total variation, 总变异
. N7 G* M" E) e% R; u2 |1 bTransformation, 转换
4 U5 f: R n# Q1 b1 ~Treatment, 处理
! l. h, \9 G! r, x* qTrend, 趋势
" L0 b8 x8 V. j2 r/ w, t6 PTrend of percentage, 百分比趋势
' W1 d% X4 j$ }; `Trial, 试验1 H" z$ u" I# a/ d
Trial and error method, 试错法7 x* x2 L/ s1 s9 @! x4 R- [, ^# Z
Tuning constant, 细调常数& r, K. w0 J% a1 \" ?+ _7 [% M
Two sided test, 双向检验
8 Z6 S# z# L6 A0 ]Two-stage least squares, 二阶最小平方
" y* \, f! A( W. Q9 ?Two-stage sampling, 二阶段抽样
: K, P9 n6 `8 B* U* F& aTwo-tailed test, 双侧检验; X5 y& r4 o& M; C8 p
Two-way analysis of variance, 双因素方差分析2 R$ }7 ~- P( q4 h, l. P
Two-way table, 双向表
9 ~0 x1 ] a4 J2 h! o' nType I error, 一类错误/α错误
3 z$ x# ^* b2 gType II error, 二类错误/β错误7 {0 P6 ~4 b% j P
UMVU, 方差一致最小无偏估计简称
s1 k1 v1 Z. w( JUnbiased estimate, 无偏估计) x* B, e8 `' R% _! J/ |
Unconstrained nonlinear regression , 无约束非线性回归, d6 f9 q) G7 R; J a a0 c
Unequal subclass number, 不等次级组含量
' z3 e/ Y8 {# c; ]9 o, CUngrouped data, 不分组资料
& t; [0 Z3 \4 q; O) ]6 XUniform coordinate, 均匀坐标) i0 y. h1 F# ~8 b
Uniform distribution, 均匀分布
. e: P4 o) W: {: x3 N/ a& D; EUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
, |" r' E" M; A% a" c: f9 {Unit, 单元
4 M& i" X: w* |5 ] E' `3 K. hUnordered categories, 无序分类$ V! [- |, N* ~, m0 v% Z
Upper limit, 上限
' u2 m9 ]" p8 R/ m/ ~Upward rank, 升秩
: @2 B {' c l( h3 sVague concept, 模糊概念
* C) h9 H p* p# s" n) M9 j; i0 g3 nValidity, 有效性0 t* g# E/ J% }# F& x
VARCOMP (Variance component estimation), 方差元素估计
7 }3 w2 W5 a5 T; Z% x; b3 B; EVariability, 变异性
4 g; Y8 W. F" |5 r: _4 U7 oVariable, 变量+ @- M& ^& L6 e, ~ o# ~0 g- c4 w' B
Variance, 方差. R' O# _6 e, |$ F- n2 @% x$ A
Variation, 变异 e8 m, e7 M/ m
Varimax orthogonal rotation, 方差最大正交旋转. J0 G; ~4 ?; V9 W) \$ B d
Volume of distribution, 容积: q" `" w, @) X0 C9 d7 s! L/ O
W test, W检验* R% a+ I- \ X6 |7 p1 e
Weibull distribution, 威布尔分布
& B$ t+ b% ]# w @ @, HWeight, 权数
$ P: \# U& _ c W" d3 JWeighted Chi-square test, 加权卡方检验/Cochran检验
1 _# G& A0 r ~* sWeighted linear regression method, 加权直线回归3 a& k" [" J$ B$ z$ u
Weighted mean, 加权平均数; ]0 G$ u: D7 q- Y4 |
Weighted mean square, 加权平均方差1 J% b, d* c& L# Z* D$ Y. K' H
Weighted sum of square, 加权平方和5 h" d% V6 k( ` F3 `
Weighting coefficient, 权重系数
d! Y; Q9 i$ KWeighting method, 加权法 % \! l0 q+ n# \, T P. ^( t
W-estimation, W估计量
/ u$ k7 Y( C/ `+ b0 Y" r; k# jW-estimation of location, 位置W估计量+ J t" v5 Y9 N$ z3 F5 Y
Width, 宽度& D4 m9 N8 o$ V# O3 p: f& \, I
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验7 K8 o q( Y7 S* Q" D
Wild point, 野点/狂点6 [% F, Y- Z* o% a; E0 E; L
Wild value, 野值/狂值
$ J# n! K* F' U; [Winsorized mean, 缩尾均值6 G# ~$ B& h5 k6 @' W% U. c3 J
Withdraw, 失访
8 r, B" G* D0 r9 X; O6 `! kYouden's index, 尤登指数
) X; Y; K; x% y b+ B% xZ test, Z检验
# c7 B. d% o/ b( n3 ^7 O j: O8 v" E: }Zero correlation, 零相关
n- J! _- A& ~- vZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
