|
|
Absolute deviation, 绝对离差1 B- |. b8 ^; J' t. s2 }& g e& C
Absolute number, 绝对数) F. Y9 ?8 q5 A5 ]: ]9 M; c
Absolute residuals, 绝对残差
* r1 \, @( I& L4 Y4 R$ fAcceleration array, 加速度立体阵( R# g! [- K1 @" A2 Y
Acceleration in an arbitrary direction, 任意方向上的加速度4 O6 }% A! k1 [4 E. A
Acceleration normal, 法向加速度
8 G H2 x; b+ w/ p+ _" A; f# E8 zAcceleration space dimension, 加速度空间的维数
) Q# J. k; i. a9 r+ `) aAcceleration tangential, 切向加速度+ \! E( j8 X) q$ [6 ]" s" \
Acceleration vector, 加速度向量
+ a. R# R' b% B3 Y& pAcceptable hypothesis, 可接受假设
6 f3 F) i% c% F" x) U) T( \/ QAccumulation, 累积
! z( K* S! t% ]+ \! xAccuracy, 准确度
- Q3 B8 T# @# i' b" o% ^; ?Actual frequency, 实际频数
/ I, Y9 k0 R0 e/ \. p& |% rAdaptive estimator, 自适应估计量
1 i$ G# n7 f2 P" y3 H' d8 ~* aAddition, 相加) w- g9 z. A, f% t& N
Addition theorem, 加法定理7 e4 E2 b) N* [. M$ p) U+ m5 ]
Additivity, 可加性) g; l& O& Q- h
Adjusted rate, 调整率
' j, W" H# a& [/ b: @+ w5 PAdjusted value, 校正值
- y5 `- {+ ~% DAdmissible error, 容许误差
) z) ]0 ]2 _/ SAggregation, 聚集性 G3 \3 g# i- P
Alternative hypothesis, 备择假设
6 O- h3 J- {1 p& Y2 r' vAmong groups, 组间
' h5 t i- ?/ t$ K" _* h9 BAmounts, 总量
: l$ z, U, t3 ^2 o5 ^% YAnalysis of correlation, 相关分析
) f0 H( t4 F6 W9 KAnalysis of covariance, 协方差分析
2 {$ c: y; f# X. t/ r% F! }7 bAnalysis of regression, 回归分析
I4 o. Y* ]- @. pAnalysis of time series, 时间序列分析! y3 ]& |5 R' K0 |1 k8 p9 ^
Analysis of variance, 方差分析
/ @# ^; u0 Q6 v3 T' S! T' w- EAngular transformation, 角转换
/ V9 m3 M6 l$ BANOVA （analysis of variance）, 方差分析8 D2 b: }5 D; V' A( m5 }
ANOVA Models, 方差分析模型
7 i* j; z O7 I9 S* xArcing, 弧/弧旋
0 X# N r; w$ k1 C8 p5 w. yArcsine transformation, 反正弦变换6 u+ f$ g! _6 P$ N
Area under the curve, 曲线面积
. l! i/ z* k3 ~1 f" _2 ~1 o/ iAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ! l% V) H8 s7 a9 S3 s
ARIMA, 季节和非季节性单变量模型的极大似然估计 1 d3 w7 g" z# N
Arithmetic grid paper, 算术格纸, s# [' ?9 ^. d3 @7 @
Arithmetic mean, 算术平均数% S9 n L" [2 b- W, H; F
Arrhenius relation, 艾恩尼斯关系- h W! `' o2 B# `0 H: M
Assessing fit, 拟合的评估
# U$ [. z1 a. J! ?Associative laws, 结合律
0 D" G c; F9 N# ]0 C3 u6 A6 Z8 q: QAsymmetric distribution, 非对称分布
/ @ {$ N t2 Y/ Y, F c" LAsymptotic bias, 渐近偏倚3 v+ R7 e# s% m- T! G2 X
Asymptotic efficiency, 渐近效率
" E% d0 y& P% |$ p: {3 uAsymptotic variance, 渐近方差% X' c& p2 h2 u8 H+ R
Attributable risk, 归因危险度
; L3 k1 d6 d: A* F) TAttribute data, 属性资料0 }( T) n6 ]% e9 q K% G* b6 W
Attribution, 属性. C A7 j2 K W* m2 ?# V
Autocorrelation, 自相关4 e4 Z/ Z4 K. }7 P
Autocorrelation of residuals, 残差的自相关
7 E7 b! K+ f3 W% xAverage, 平均数 ~# O6 ^$ m1 D4 ^
Average confidence interval length, 平均置信区间长度, r# {" @! A+ O5 e2 F( G+ k( E
Average growth rate, 平均增长率% F4 l# M4 A9 g2 E/ h J
Bar chart, 条形图: A8 }' @2 o/ n* U! K
Bar graph, 条形图6 M% R8 Z% T$ E6 D' J4 j2 Q0 Q
Base period, 基期, p! [0 r* s; b3 ]. \8 n
Bayes' theorem , Bayes定理! [ [! j9 ~- @4 C: S
Bell-shaped curve, 钟形曲线! s! L% M# ]6 {; h
Bernoulli distribution, 伯努力分布7 `/ f" E; c' U6 z, H2 T) Y a
Best-trim estimator, 最好切尾估计量) r4 ~; K# ?( `4 e N+ m% V r. W
Bias, 偏性* {$ }6 D* W+ b+ |0 f
Binary logistic regression, 二元逻辑斯蒂回归
+ y Q+ u" `; T0 [1 eBinomial distribution, 二项分布
9 w* H2 |& h+ DBisquare, 双平方( X6 D7 @5 R! f4 U- m$ q
Bivariate Correlate, 二变量相关0 O$ B& d; r- B
Bivariate normal distribution, 双变量正态分布; l- n6 w" q) Z3 n: K9 y, B
Bivariate normal population, 双变量正态总体
$ z* y. R% a# n/ Z9 p: C% c' nBiweight interval, 双权区间
' A9 [8 e+ f2 O6 @7 gBiweight M-estimator, 双权M估计量
/ K0 Y- `0 W2 ]5 g0 K; R/ \( x6 ~* OBlock, 区组/配伍组* h* [- e% I b
BMDP(Biomedical computer programs), BMDP统计软件包* v' ^1 d% m5 J
Boxplots, 箱线图/箱尾图
; C' s2 \: y$ s& @! V) a* ZBreakdown bound, 崩溃界/崩溃点6 }* I% N; |$ _3 U$ F' ~
Canonical correlation, 典型相关
) a7 O( X: `5 n% vCaption, 纵标目 v9 l6 z+ _3 K* u0 e' `
Case-control study, 病例对照研究% S7 |6 ?1 \% u/ V; A$ {
Categorical variable, 分类变量2 c# _$ N C% {
Catenary, 悬链线
8 ~4 V, y' w2 BCauchy distribution, 柯西分布& h7 a9 o5 ?* {2 q, R
Cause-and-effect relationship, 因果关系
0 ^1 J5 z0 ?4 A: p& h8 t# W. ]# H5 kCell, 单元
1 {( b# x3 N% G( ` n/ Q& ZCensoring, 终检
M& W( d8 r, ]/ b! }Center of symmetry, 对称中心
- J3 p( \0 {/ n# k( r9 W% tCentering and scaling, 中心化和定标
# P4 m% }: R$ R: zCentral tendency, 集中趋势$ B6 r& V: `# p
Central value, 中心值
: W- w0 x3 O+ R& `0 \3 rCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测. e2 L9 ?: _5 n, O
Chance, 机遇
* g; k9 `" R' {. jChance error, 随机误差
$ i/ n6 T' @ l+ i& ^- a6 b; IChance variable, 随机变量% _, B2 }7 d' P7 p F4 W
Characteristic equation, 特征方程5 m( D* \" _5 O" Z
Characteristic root, 特征根6 x! g7 U; r# S% `# w' z' w
Characteristic vector, 特征向量
* y8 A; y9 j: {: x1 l0 J, \* MChebshev criterion of fit, 拟合的切比雪夫准则
7 }: _3 D; F* BChernoff faces, 切尔诺夫脸谱图
# A3 F @; p6 w# h) j, z; aChi-square test, 卡方检验/χ2检验* \9 J, C1 q% |% b4 j7 D6 U
Choleskey decomposition, 乔洛斯基分解% l( a: r% E0 I! r3 ~& u9 i
Circle chart, 圆图
. w5 v6 x& J2 T9 P6 }5 GClass interval, 组距
* }; a* V2 m# y7 r/ Q! MClass mid-value, 组中值
- k) \) `* y2 P% G5 }$ JClass upper limit, 组上限- |; [" ?1 `: g4 w3 X/ S& p
Classified variable, 分类变量
& Y1 b& p7 r$ _7 g, i* uCluster analysis, 聚类分析/ y# t% r$ I: _/ C
Cluster sampling, 整群抽样
) U" p% p; O. G6 Y0 L p4 k& ~Code, 代码7 }' y( B4 ~& Q% a1 J5 S8 r
Coded data, 编码数据
9 Y6 T: ~, r1 o3 w' Z7 D( _Coding, 编码
6 o3 e7 E5 O2 U! v7 D% c+ ~5 @" OCoefficient of contingency, 列联系数
% M' E, K. r. t" Q# oCoefficient of determination, 决定系数
: P. F8 z5 o. ^/ s* OCoefficient of multiple correlation, 多重相关系数" \: a5 i. Y* S0 L& E
Coefficient of partial correlation, 偏相关系数 P0 G+ S: {: W: V
Coefficient of production-moment correlation, 积差相关系数% z) }" Z. N! c' x7 I- ~# |8 z+ O
Coefficient of rank correlation, 等级相关系数# J1 Q4 Z# D& P. o( T2 f2 j7 m$ a
Coefficient of regression, 回归系数5 Y7 D( Z7 o* o6 T5 f4 f
Coefficient of skewness, 偏度系数( t1 L! }$ f. a" ^# R
Coefficient of variation, 变异系数. N9 @+ \# W* v" P$ Q* {
Cohort study, 队列研究
a& Y! N8 m: r4 Q0 V1 y9 A3 S, ZColumn, 列2 F; N1 y; V& }' {) C- _" f( h
Column effect, 列效应0 `! B7 E& e, a: P J8 i: B
Column factor, 列因素
& Y }/ Y! F) ~/ j( q! ?Combination pool, 合并1 ~/ C5 f0 y' ~: o( H
Combinative table, 组合表* S- z7 {2 E: J) }9 J
Common factor, 共性因子3 U# p& O. D: A3 C
Common regression coefficient, 公共回归系数: l) _; g8 V2 \. J
Common value, 共同值
- M3 g5 @1 i! e$ X2 QCommon variance, 公共方差; {+ n _/ K0 T# T# f
Common variation, 公共变异
, k5 e9 }+ B$ ^! D/ BCommunality variance, 共性方差
% C! h V8 K$ S& H7 eComparability, 可比性! s( Z _0 V0 i* K8 a( V- r- s
Comparison of bathes, 批比较
0 ~* H, K6 h* E1 S) T% V& RComparison value, 比较值7 r. y$ n$ Z6 w9 k# L
Compartment model, 分部模型5 A6 a6 l* o' [+ j* Y
Compassion, 伸缩
' @* x9 L- g1 PComplement of an event, 补事件
7 h0 x2 a: z- m9 K9 XComplete association, 完全正相关
, [# z Y0 h3 j* p6 ?# `1 X: vComplete dissociation, 完全不相关. { a' h/ W5 i9 m) S
Complete statistics, 完备统计量
9 U* E, G- N2 Y3 a2 B: ECompletely randomized design, 完全随机化设计
4 E: a6 `+ ]& C) F" uComposite event, 联合事件8 O" j6 }9 _; \7 p5 t8 ]' y
Composite events, 复合事件; m* K! S/ F5 z( n
Concavity, 凹性3 C L/ L9 u1 z; t8 L+ w
Conditional expectation, 条件期望
i6 [ P* J6 {8 r3 jConditional likelihood, 条件似然
2 J: Q6 s8 G+ m' A% }* h5 ]Conditional probability, 条件概率
8 j, X# \8 s# ^7 V* zConditionally linear, 依条件线性7 a9 e) x2 j6 k8 ]3 H
Confidence interval, 置信区间
; [# Q, c/ `( g1 }! W; D+ WConfidence limit, 置信限* N- O& {2 S7 t0 d& ^
Confidence lower limit, 置信下限! Q* P" v) z9 H" S
Confidence upper limit, 置信上限! T& p" ?8 H( _" Q3 ]+ J
Confirmatory Factor Analysis , 验证性因子分析/ H0 i, g+ [; J5 ^* W2 x
Confirmatory research, 证实性实验研究
2 `! ^6 G( ^; K6 d' }% GConfounding factor, 混杂因素
3 p) X+ N/ @" H8 X: W. OConjoint, 联合分析. H7 D6 D5 H6 M- m5 k. D
Consistency, 相合性
S4 Z+ I3 p) H+ ^. w! ]Consistency check, 一致性检验
6 R/ G6 u0 ^" Y1 `% o7 a4 [$ }Consistent asymptotically normal estimate, 相合渐近正态估计1 F% [7 x& u- r( ^0 c
Consistent estimate, 相合估计
) p& z2 `& Y Y R4 C* t2 cConstrained nonlinear regression, 受约束非线性回归5 x" w3 G' I% M2 ?7 D$ A
Constraint, 约束
: I% ~5 D" C ]4 n* KContaminated distribution, 污染分布
4 V/ H# O' `5 s7 u4 L1 g' k2 i8 nContaminated Gausssian, 污染高斯分布; [5 D3 ^/ [% i( E+ X- y
Contaminated normal distribution, 污染正态分布$ D" O% G+ N9 P
Contamination, 污染
0 L- I* L% O; I. dContamination model, 污染模型
3 W! i% x5 x$ }& iContingency table, 列联表
! r2 q+ @, R; \% ?* q6 EContour, 边界线$ B' e: E2 C" B
Contribution rate, 贡献率* c6 ~3 M% o5 B4 o/ P, _4 `: P4 e2 c
Control, 对照9 S8 w- T5 D$ S K" ]6 @4 `
Controlled experiments, 对照实验! Z# t: h* e) [
Conventional depth, 常规深度
* [: `6 K, U& Y; u* t( O* \, \Convolution, 卷积
7 u: y; O3 Y" k' _2 J$ zCorrected factor, 校正因子
+ S, u1 h, m6 V4 r/ v( O/ oCorrected mean, 校正均值: V& d8 |4 |; p' s: d* L5 |
Correction coefficient, 校正系数2 j: I# t# `5 v9 M
Correctness, 正确性
4 r: ^! z9 _6 ?( iCorrelation coefficient, 相关系数
; t+ v/ x3 j# Q5 N" _Correlation index, 相关指数
0 g( ^- w& y+ u% DCorrespondence, 对应+ r& f% S7 z9 Q& S3 x7 \6 E- R" J
Counting, 计数
! Z' _0 N! \9 l8 |6 h6 KCounts, 计数/频数 w! c) L1 T M, k
Covariance, 协方差' k8 N. T0 x/ O& m: B# s+ [4 T/ s
Covariant, 共变 , K2 ?" F) e' F- n
Cox Regression, Cox回归0 j5 k' p' ?3 [: m/ K8 X" `- Q
Criteria for fitting, 拟合准则
g# ~5 u6 N+ y9 F% i/ ICriteria of least squares, 最小二乘准则3 m' J' |% Q5 T$ i
Critical ratio, 临界比* Z+ Z( `4 `4 }, {
Critical region, 拒绝域% F' @( C3 ?9 i0 k, j9 E" E
Critical value, 临界值5 C% @- m( y6 ~3 ~5 w
Cross-over design, 交叉设计/ }$ c5 I2 v8 v- C+ ]5 D X
Cross-section analysis, 横断面分析
7 M& Z! v# N% @. G( BCross-section survey, 横断面调查
/ ]0 Z1 R. `" T6 r2 ^5 f" \Crosstabs , 交叉表 # j7 z$ E. ~; T1 T4 @
Cross-tabulation table, 复合表
* ]( K3 R! V: |1 C* \/ o; fCube root, 立方根5 [& e0 u2 w, e- X) X
Cumulative distribution function, 分布函数: a- u1 Z' Y' C0 F: _1 ]
Cumulative probability, 累计概率
: `: Q; V) M; \8 h' ~Curvature, 曲率/弯曲5 ~6 A: r8 r! w2 Q3 @2 M
Curvature, 曲率) Q+ f+ x/ X) c* n; _
Curve fit , 曲线拟和
! g5 B) f- _$ o! p/ Z4 n( @# eCurve fitting, 曲线拟合
6 m* g* Q6 |- ~Curvilinear regression, 曲线回归
+ Q! I, x& n/ G& e/ gCurvilinear relation, 曲线关系" W' D* [ T! H) B, F! J* ?0 V4 X
Cut-and-try method, 尝试法
, g% Y6 B6 j gCycle, 周期
$ R! H$ v u* _, o: u8 xCyclist, 周期性' j5 {( Z& s( s4 D5 E) [
D test, D检验
: @% X0 P' \. c- x. HData acquisition, 资料收集3 e! H0 q8 T$ v1 m. ]/ U$ @
Data bank, 数据库7 y9 F1 X/ i- f0 s6 a5 C/ _* x6 O
Data capacity, 数据容量
' z6 X% q. G/ f5 M+ K' QData deficiencies, 数据缺乏
# E2 _ m0 g3 gData handling, 数据处理
( s/ J; V E6 D; H4 |+ z6 @ sData manipulation, 数据处理: ~, A8 t2 Z, y
Data processing, 数据处理
/ }: D; |! u* \: j I7 kData reduction, 数据缩减
$ q, P, u6 W0 ~. B1 sData set, 数据集
) o0 { p6 j9 b% y9 J8 @Data sources, 数据来源) v J; Y, W; w) m+ W0 {$ |; s0 j
Data transformation, 数据变换
@4 f' K9 T. N+ C; k! vData validity, 数据有效性% Q) R; T& Q% R
Data-in, 数据输入1 j& s% A# c( D* H* {) R4 k
Data-out, 数据输出
/ @0 G8 s5 B; e) h8 K& [Dead time, 停滞期1 M( q2 Z+ m) t/ u3 O
Degree of freedom, 自由度
( v- W# o5 j& nDegree of precision, 精密度3 b7 {+ J, _9 [! ~$ ^
Degree of reliability, 可靠性程度
5 l9 m' Q8 L e& o& PDegression, 递减; b& t* }8 S) D% [: |- \: d- R
Density function, 密度函数
: u' s* B/ d# m; `Density of data points, 数据点的密度) `) \3 r, @0 h) H, C
Dependent variable, 应变量/依变量/因变量) H# x, q) |5 \. w
Dependent variable, 因变量
& ?1 N: {4 g1 C( d3 L' J0 v/ fDepth, 深度 J4 ^1 N) p+ @; e. T
Derivative matrix, 导数矩阵$ q2 ?2 F* |5 b% E" A
Derivative-free methods, 无导数方法
3 \ I/ k! ~/ m {5 }Design, 设计
5 x. W/ e/ F( j, L0 F9 ^Determinacy, 确定性: f! f0 d" e) w
Determinant, 行列式1 d8 M z: _* F- V+ c" g
Determinant, 决定因素
5 x2 y* W2 j* p$ ^, M' zDeviation, 离差# E4 ? S" Z8 N
Deviation from average, 离均差4 ]9 v3 a* Y8 |# _9 [* |0 D
Diagnostic plot, 诊断图% _/ Z/ ?& v3 W' \; ~
Dichotomous variable, 二分变量7 N$ U% y. D+ H: C# ^: c
Differential equation, 微分方程
, Z' k$ Z$ z: _1 \" D- M9 PDirect standardization, 直接标准化法
/ h+ T0 w" d4 E9 v/ H1 P9 @8 BDiscrete variable, 离散型变量6 r& s9 |, |. \/ b- x7 C
DISCRIMINANT, 判断 ( ~8 Q/ V3 _! I3 d# P
Discriminant analysis, 判别分析
1 F d: E( c4 pDiscriminant coefficient, 判别系数+ s2 ?- z9 g! K3 A
Discriminant function, 判别值
. Q) h. W% U5 y6 @" WDispersion, 散布/分散度
+ d& z% z | N' _( B, c5 }Disproportional, 不成比例的: R( R) {1 W! s' @
Disproportionate sub-class numbers, 不成比例次级组含量
* [: Q5 n8 ?' A& `- W& M3 C+ U9 |Distribution free, 分布无关性/免分布
* _7 S2 y y" }7 u- ^/ \* F- ]Distribution shape, 分布形状8 ~9 B9 g8 d" ~0 N; f% b
Distribution-free method, 任意分布法: J7 ~0 [! ?/ ^! L
Distributive laws, 分配律
2 H4 A( n# e* u \4 aDisturbance, 随机扰动项
' g6 |1 J1 P. EDose response curve, 剂量反应曲线, n" j5 x* P4 c" U7 v3 M- g
Double blind method, 双盲法
9 d6 V' A6 h" v& KDouble blind trial, 双盲试验
# r! k4 c8 K$ o X7 |& z6 mDouble exponential distribution, 双指数分布
$ i3 C, X' } B0 GDouble logarithmic, 双对数
& @! L8 A! P O, ?: yDownward rank, 降秩) j5 Z1 b4 o; I t+ W7 y
Dual-space plot, 对偶空间图
9 `+ P, p3 z7 i( y yDUD, 无导数方法" u# q' ^4 W% O9 W3 w
Duncan's new multiple range method, 新复极差法/Duncan新法
M4 _( S9 F, L& W% XEffect, 实验效应' P5 t1 i2 A: H
Eigenvalue, 特征值7 O; t, r$ }; n s7 D. u
Eigenvector, 特征向量
7 J8 q- g5 n8 Y$ W ]7 KEllipse, 椭圆6 C" X* l' e& r9 Z$ `: b1 `
Empirical distribution, 经验分布- H- R. p2 J1 A. A! E( O; s( J
Empirical probability, 经验概率单位
; u4 L( v$ F: V0 HEnumeration data, 计数资料0 l! D( ?( c! h }. T# Q
Equal sun-class number, 相等次级组含量3 H% W+ y9 s/ T0 t! n# q
Equally likely, 等可能
" K8 ~/ ^# ^2 l6 V; [Equivariance, 同变性
) m- T7 i) e1 @5 `: ]" G6 M, IError, 误差/错误5 s, q; r) a; \1 A& M) d9 j n8 l
Error of estimate, 估计误差
+ y6 H& z7 W; c2 P- I; F) `. ]Error type I, 第一类错误
: d* o1 K) @1 J. xError type II, 第二类错误! r7 e. y9 _+ E; G8 f4 F
Estimand, 被估量: j' U0 j0 W; P; M/ L
Estimated error mean squares, 估计误差均方
! P8 _# j' A! b" oEstimated error sum of squares, 估计误差平方和7 R$ y' m8 j; Z' S. t
Euclidean distance, 欧式距离7 h' V9 ^7 K! |+ y8 f+ i( {* L6 @
Event, 事件1 ?' R$ |( g8 m( J
Event, 事件 q! x2 _1 o! C2 n" n7 ^3 |
Exceptional data point, 异常数据点
" p) A& Y: H2 nExpectation plane, 期望平面
2 Q& l) W- J1 i& k0 }Expectation surface, 期望曲面
4 n6 e8 ~; a' z3 m9 D$ qExpected values, 期望值. Q: |4 x- x( t. w3 | {
Experiment, 实验
3 @6 ~+ d1 A% [) z9 HExperimental sampling, 试验抽样
# B Z/ `1 p/ N+ xExperimental unit, 试验单位- N. m$ J- ^0 q5 _
Explanatory variable, 说明变量
: X7 J( n, G! ?2 ~Exploratory data analysis, 探索性数据分析8 a1 p2 C K- C8 t
Explore Summarize, 探索-摘要( Q" ~. |& V: R Y$ O/ F
Exponential curve, 指数曲线
$ J/ z+ L6 E; j$ Z- \0 D/ ~Exponential growth, 指数式增长
+ i& Y* T2 l4 C8 A* hEXSMOOTH, 指数平滑方法
' D- K5 f6 V/ h* b- |; d6 nExtended fit, 扩充拟合
! \8 k7 Q4 Q5 k. z' m g+ OExtra parameter, 附加参数+ T v L. R. p
Extrapolation, 外推法6 o p$ B& B$ C
Extreme observation, 末端观测值
8 e1 f& Z% X, K; j! e5 |2 gExtremes, 极端值/极值
, B% b# b1 L( O0 Y ?3 fF distribution, F分布
/ U7 m! h; N( I# W) j/ B/ G' zF test, F检验
& R+ v4 S# X |! D( V z) U# N% I2 M4 ]4 XFactor, 因素/因子# y' W0 \+ |3 u
Factor analysis, 因子分析
. i7 e- s8 K- j1 y% @Factor Analysis, 因子分析* h0 a' ?9 r& M/ \ ~* ]8 S
Factor score, 因子得分
, R8 q2 |; n- GFactorial, 阶乘
5 J, q9 ~' \$ `& Q5 e2 QFactorial design, 析因试验设计
7 B; q# T" {$ A( gFalse negative, 假阴性
3 s/ }$ I& j) fFalse negative error, 假阴性错误
% o2 Z8 o; R# @: hFamily of distributions, 分布族" y; C! f) j( C) Z
Family of estimators, 估计量族; R6 c/ V1 |* t6 P, D; K8 u
Fanning, 扇面
' l9 w8 k" z% n$ Z8 v+ I7 i( [! ]Fatality rate, 病死率
5 {5 ~4 m' Z+ Z" d; h* xField investigation, 现场调查
1 w' `. t) R# b. g8 @Field survey, 现场调查
8 S( u+ L M. I* uFinite population, 有限总体
" Q, q. |' W3 b0 [% o9 L, AFinite-sample, 有限样本
r7 n0 w+ y3 e2 D. k; \! tFirst derivative, 一阶导数4 K. a2 v& e- h3 X
First principal component, 第一主成分1 A# O6 w4 H( U( i( @
First quartile, 第一四分位数/ u% \4 g0 d8 n: z* H9 C
Fisher information, 费雪信息量& s0 c6 v# F9 f# A1 ^
Fitted value, 拟合值. N; p$ |8 t+ v1 d2 n0 V- F
Fitting a curve, 曲线拟合
^5 x5 B2 F! B) Z/ l, D5 m1 BFixed base, 定基
" I. Q5 A9 ]# O( D% Q Y8 aFluctuation, 随机起伏
+ c1 |1 s7 r' S4 o9 n$ TForecast, 预测% A/ u+ H% O; x1 b& r7 Z
Four fold table, 四格表
% P2 l E- F2 r4 l8 @' xFourth, 四分点% a: j& `. Y1 r, S! [1 t
Fraction blow, 左侧比率2 C" b! R; s, P* c3 t6 L
Fractional error, 相对误差0 u: V. n: C2 Z1 l" W$ H
Frequency, 频率
9 K' j" `) g! z" k; Q) NFrequency polygon, 频数多边图; H9 y8 E t* g: y4 w6 W2 \& t4 N) @
Frontier point, 界限点, V1 t/ e1 A# Z5 c6 ] R G$ k, h
Function relationship, 泛函关系% j1 }$ w" I2 l7 y; D
Gamma distribution, 伽玛分布
0 G& X( v9 h/ SGauss increment, 高斯增量1 t5 ^1 ^8 r' S0 E
Gaussian distribution, 高斯分布/正态分布9 {6 ?3 O! v- g; v/ k& T- ^2 d
Gauss-Newton increment, 高斯-牛顿增量
4 |) W4 n! ?. O, |: X, O# q( N" VGeneral census, 全面普查: c/ B4 y9 T! E( W5 v
GENLOG (Generalized liner models), 广义线性模型 & e5 u: q/ _( Y1 M
Geometric mean, 几何平均数8 Y8 F4 B/ x2 E. |
Gini's mean difference, 基尼均差
! M. e2 E4 L$ e' a7 _7 ZGLM (General liner models), 一般线性模型
, ?* @, O; x& m8 sGoodness of fit, 拟和优度/配合度3 N6 d0 M2 J# M5 A ^4 n. T! B* x
Gradient of determinant, 行列式的梯度4 g J$ M9 z& z7 u5 H* b5 ^
Graeco-Latin square, 希腊拉丁方
( ]+ i- e: y3 @+ D. Q$ w8 L! AGrand mean, 总均值
; {- M3 K2 O4 M( {! K* Z& XGross errors, 重大错误) F0 k. ~' g' H+ z. ]5 X" }( c
Gross-error sensitivity, 大错敏感度
5 }4 q% J% J/ E- ~Group averages, 分组平均: t' _2 @5 H" q* i
Grouped data, 分组资料
& j S; r+ v& k% r! jGuessed mean, 假定平均数( Z3 f# Q( j1 `/ o% K( i
Half-life, 半衰期
! w7 S! s3 d- THampel M-estimators, 汉佩尔M估计量+ V5 e8 c+ D- ]
Happenstance, 偶然事件
; N9 q: p2 x' e" X$ n7 jHarmonic mean, 调和均数
; E: j9 N2 ]- W0 w# q, h) C1 wHazard function, 风险均数
9 t7 F9 B/ d G" l8 K+ `Hazard rate, 风险率
7 ]2 d# d1 b# u* Z& E* y/ cHeading, 标目 ; Z6 f: r6 N# z$ H, b. f# Y7 Y+ ^
Heavy-tailed distribution, 重尾分布
$ N0 P+ d( b( @+ {, q" BHessian array, 海森立体阵
! i: \8 h' X/ m% r. JHeterogeneity, 不同质% B* d0 T1 l& r6 ] I
Heterogeneity of variance, 方差不齐
/ L8 ?" Z1 o C. b9 Y! \7 y. lHierarchical classification, 组内分组
9 }% l' g# @" w" aHierarchical clustering method, 系统聚类法
: ]8 a1 W+ c# ?2 QHigh-leverage point, 高杠杆率点
4 J7 `3 ]) x( I- F# ]HILOGLINEAR, 多维列联表的层次对数线性模型
, C" I% Z7 r8 fHinge, 折叶点! y0 L k1 L5 d9 ^' y' |0 O0 Q8 n
Histogram, 直方图
& ~& D. N1 A0 h; O# @Historical cohort study, 历史性队列研究
* Y% [* k+ ^9 [- ], BHoles, 空洞
1 R+ E) w' i3 L9 I' `HOMALS, 多重响应分析
$ ~% k) ?) `3 x0 a, fHomogeneity of variance, 方差齐性
$ F9 i3 F4 o* v* h) v$ V/ WHomogeneity test, 齐性检验3 ] F/ ]5 U& f" a) J! R. \
Huber M-estimators, 休伯M估计量1 o4 P4 V" h0 f: [* [5 @
Hyperbola, 双曲线
4 Q7 o9 U% i& qHypothesis testing, 假设检验
3 r. R/ h' ?7 {Hypothetical universe, 假设总体$ \- o a( ^" `
Impossible event, 不可能事件
5 W9 s/ }- J/ A: s8 l% t3 MIndependence, 独立性
% }) R5 U; F* X0 f: S% F7 dIndependent variable, 自变量
. ?" o* ~! g J, N$ i, VIndex, 指标/指数
) \) k7 u3 i0 V/ R! O# X- DIndirect standardization, 间接标准化法3 Y4 R/ H! O5 @% g: U* N7 v! |( u$ {
Individual, 个体6 h# u4 s8 O5 H6 V6 D
Inference band, 推断带. N% h; j) h: P7 x! }0 j
Infinite population, 无限总体9 H" w- ^; y/ v
Infinitely great, 无穷大
) V D4 O1 P$ y0 ` [. x/ x# tInfinitely small, 无穷小
3 s+ q* g' `) Y1 MInfluence curve, 影响曲线4 R/ e1 j2 N2 P( J/ Q
Information capacity, 信息容量
) o$ D! W2 Z8 @- Z7 TInitial condition, 初始条件; Z4 {5 Y& s- U/ i! Q
Initial estimate, 初始估计值. F+ ~$ N' e$ @) m" x
Initial level, 最初水平
; R. x8 N4 z5 i7 M" R( cInteraction, 交互作用$ s) b B5 l3 b- i
Interaction terms, 交互作用项
: I! a& F5 W7 AIntercept, 截距
9 t1 L( O% r9 v1 F/ g' ZInterpolation, 内插法
; s# y" P7 f8 R: m) AInterquartile range, 四分位距
8 H9 o8 v C0 M4 n% \Interval estimation, 区间估计
4 P' r$ V! U7 u$ q$ gIntervals of equal probability, 等概率区间1 _+ }9 K* j8 q
Intrinsic curvature, 固有曲率% F; }5 b& k8 Y/ c4 y
Invariance, 不变性. X) u0 e. ~$ y3 D N
Inverse matrix, 逆矩阵
$ S( S$ ]2 R5 P+ y- h KInverse probability, 逆概率
- @4 x. {5 P3 `2 k( ]Inverse sine transformation, 反正弦变换8 e, a$ H6 T* w' `( Z
Iteration, 迭代
+ h% l8 B, ]5 M/ }" T; @' j) YJacobian determinant, 雅可比行列式
7 H! B6 b1 b5 Z, K, Z9 `Joint distribution function, 分布函数( o. |! m; @3 @, g. |" w
Joint probability, 联合概率
$ p. i% o0 |4 {" o. N: r0 tJoint probability distribution, 联合概率分布4 T+ f, N5 t" f) Z
K means method, 逐步聚类法
/ C% d% q& R! v% rKaplan-Meier, 评估事件的时间长度
o/ s' F0 c# i# ?5 u9 TKaplan-Merier chart, Kaplan-Merier图, ?. G; J) w4 `$ i4 p
Kendall's rank correlation, Kendall等级相关& u# e2 ?3 E. N) _ r1 J
Kinetic, 动力学6 \) W6 }# t( Z6 ^
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
" @, X5 i. d, |+ OKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验8 m$ l+ S8 y% K5 G( d2 T. I) V
Kurtosis, 峰度
9 b& a0 A) I6 u) |# W# ?Lack of fit, 失拟
& }$ @5 s7 n( i0 ?4 dLadder of powers, 幂阶梯8 Z* L5 B: r4 ]0 L( y6 Q
Lag, 滞后
& R9 [$ B# {* CLarge sample, 大样本
5 O. j# Z/ z1 w, }Large sample test, 大样本检验. j- Q6 w% z |+ |6 |
Latin square, 拉丁方
; F# u( w) M; u5 SLatin square design, 拉丁方设计# ]* L+ A$ }$ {' [/ ~
Leakage, 泄漏
. U/ n S! h" z: d0 G7 a, YLeast favorable configuration, 最不利构形
4 c- y# B8 C) `4 h) Z4 f7 N) ELeast favorable distribution, 最不利分布
. ^! K- S; _+ ^3 y% R4 ?( _( T5 [ {Least significant difference, 最小显著差法0 R9 R6 I1 k' f, J) F
Least square method, 最小二乘法! _) f7 ?6 P' Z3 p
Least-absolute-residuals estimates, 最小绝对残差估计
2 ^9 ~; b- P# q. ]Least-absolute-residuals fit, 最小绝对残差拟合- _3 ~1 }+ G3 ]+ G7 z j& h, r- M
Least-absolute-residuals line, 最小绝对残差线
" ?$ R7 e+ m6 p7 Z9 ^% v5 I kLegend, 图例
! D; t9 _' n FL-estimator, L估计量 p* b' e, b% a) v
L-estimator of location, 位置L估计量
v/ z6 `" E% j' X/ sL-estimator of scale, 尺度L估计量
% u1 |* ], D- b' ~' GLevel, 水平
8 \+ n; G3 Y" v q( L" o5 GLife expectance, 预期期望寿命 ^' Y4 i; n0 D5 [* ^, P8 P' H: k0 L
Life table, 寿命表7 \: I: `' E: m, V# G
Life table method, 生命表法
K1 x, g1 P' CLight-tailed distribution, 轻尾分布
3 Q& f# w! V9 g' }Likelihood function, 似然函数
/ M! R+ s# Q4 B+ ULikelihood ratio, 似然比
" f6 W, V9 a: l/ r4 N4 Oline graph, 线图" {( P2 b' E# ]
Linear correlation, 直线相关4 e: o' E% M$ {6 }2 e% H: I
Linear equation, 线性方程& B" V# V, l( ]+ I% R( d
Linear programming, 线性规划) Z: E: y3 D5 A1 O- Z1 G3 Y
Linear regression, 直线回归
3 {/ ?: u8 h* G4 a o9 \Linear Regression, 线性回归
" x% S, ^# E3 X- ?& R+ V- t- W( @; OLinear trend, 线性趋势
9 e& z+ F8 ]9 q9 ^- u, n* P! hLoading, 载荷 $ G8 |& H& }" v- V' D3 a
Location and scale equivariance, 位置尺度同变性
* Q/ ~; l) P- z6 OLocation equivariance, 位置同变性
; r0 u; D Z5 w* d, f) ~* e/ p+ gLocation invariance, 位置不变性4 V, B% P3 u+ P; a0 t
Location scale family, 位置尺度族2 c1 z4 |8 c6 A- M
Log rank test, 时序检验 ) t: @) `' q; i( V6 E( t9 p& Q: _
Logarithmic curve, 对数曲线, `; T/ t& z7 V3 b# W7 V1 S; T2 g& K
Logarithmic normal distribution, 对数正态分布
) {0 M( Z- w. z& n8 g [; vLogarithmic scale, 对数尺度
( V7 {6 w+ @" n w$ z: |Logarithmic transformation, 对数变换0 o4 q) B3 H* j, c @# _
Logic check, 逻辑检查0 q" I3 L7 p' V% u
Logistic distribution, 逻辑斯特分布
/ q" |1 I' L5 {Logit transformation, Logit转换
. f4 o9 N' D. GLOGLINEAR, 多维列联表通用模型
; b/ l; v' E+ ~$ {Lognormal distribution, 对数正态分布. o1 u- ]' C; m+ P
Lost function, 损失函数
, c3 s: P- o# G8 H0 \( GLow correlation, 低度相关
6 j4 |) x' A* s# Y: nLower limit, 下限
- r3 W/ R) e6 \& NLowest-attained variance, 最小可达方差9 C) _3 v2 _0 R3 L3 U' U
LSD, 最小显著差法的简称& Q) @, G- ?# d9 a/ J+ u
Lurking variable, 潜在变量
1 t: `6 l+ n# G- p9 w3 _& {Main effect, 主效应
$ r' H J+ d( N& i) k0 lMajor heading, 主辞标目
, C* A1 j. k% N: h v8 [Marginal density function, 边缘密度函数: I# p& f: Y* w7 V: |9 W
Marginal probability, 边缘概率" N8 T- H2 n: `9 Y& z9 k
Marginal probability distribution, 边缘概率分布
2 B7 g+ n" I, U- mMatched data, 配对资料 B2 O- I. }$ q2 U4 I
Matched distribution, 匹配过分布6 b) K) K+ s2 m
Matching of distribution, 分布的匹配' i+ T* R1 B$ M# t/ _8 l6 x
Matching of transformation, 变换的匹配
, R* L/ G/ K4 h6 v2 m! {+ `Mathematical expectation, 数学期望! l4 o; \, Y- T% v0 f6 I
Mathematical model, 数学模型
- \) V1 L# a0 W% z2 p0 VMaximum L-estimator, 极大极小L 估计量
0 @ r7 t6 Q% o7 G7 c J4 A6 MMaximum likelihood method, 最大似然法
/ Z; ^ p+ h! ]; x* @; [0 C2 g8 Z) dMean, 均数1 w7 j4 a. q( y3 n4 e% L" Z$ \
Mean squares between groups, 组间均方) A8 n/ F- t9 Z, Z
Mean squares within group, 组内均方
9 _7 E8 M0 [9 u9 ?$ j: t/ GMeans (Compare means), 均值-均值比较% C# d& U9 o3 O6 ]( X, z
Median, 中位数: J W! a$ L7 B9 _; W, t" ?
Median effective dose, 半数效量$ E0 X9 l$ S& v) u# ^
Median lethal dose, 半数致死量, @/ P8 j- }/ e2 n* o; p' g/ l0 v
Median polish, 中位数平滑
# e0 y; j% h WMedian test, 中位数检验( N2 d$ {$ F D. b/ ?3 y
Minimal sufficient statistic, 最小充分统计量% E/ B' t! _- X& l
Minimum distance estimation, 最小距离估计
; F+ ?" E4 L) h) V$ XMinimum effective dose, 最小有效量
- u6 ]" ]- E4 r/ E, W4 ?/ hMinimum lethal dose, 最小致死量+ [+ R$ f2 [8 o/ U" m* O
Minimum variance estimator, 最小方差估计量5 O0 _& o; s! b2 i3 \. v+ t' q
MINITAB, 统计软件包6 B( [. k7 e' S
Minor heading, 宾词标目
5 A( A4 h' P; v9 B1 g2 tMissing data, 缺失值3 x$ a2 x9 h! H3 H0 R+ V) N
Model specification, 模型的确定
" ]% t4 o( K6 d }" L' M$ _Modeling Statistics , 模型统计1 @/ {2 q9 R- Z: l% R
Models for outliers, 离群值模型
X/ _( R& f3 `5 k& M5 MModifying the model, 模型的修正
" T- I, v; |! _; JModulus of continuity, 连续性模# j% w# ^9 d ~# N: `( C( C* R
Morbidity, 发病率
$ r% x8 ^$ W; ZMost favorable configuration, 最有利构形
* d$ A( H k" C4 KMultidimensional Scaling (ASCAL), 多维尺度/多维标度; j8 f2 U9 J' P1 l# a; r
Multinomial Logistic Regression , 多项逻辑斯蒂回归( s# l5 Q2 V3 k# J$ L5 `# n
Multiple comparison, 多重比较
9 Y6 C- l E/ x$ ?Multiple correlation , 复相关2 d( i7 }( _ |, e
Multiple covariance, 多元协方差
2 g, c" O$ ]6 f8 z: u0 N: _Multiple linear regression, 多元线性回归
( e2 \$ O7 g5 T: l& JMultiple response , 多重选项
0 T7 n+ B) q& iMultiple solutions, 多解! q: G7 j3 e) E0 k" X k
Multiplication theorem, 乘法定理4 a% w* k3 X* t, u& s. _
Multiresponse, 多元响应7 I+ t6 M4 \) o; ]
Multi-stage sampling, 多阶段抽样
+ j: m/ z* S$ _# w c8 GMultivariate T distribution, 多元T分布1 E6 h3 A5 T0 o- f8 x6 `7 L* y) q! G
Mutual exclusive, 互不相容
& I/ m- J# G$ w8 f- w! c2 m8 j* [Mutual independence, 互相独立$ i5 i& A J7 { F: j: s
Natural boundary, 自然边界
- } g# p6 k/ P- h4 cNatural dead, 自然死亡0 ?# D+ p/ h3 |5 }
Natural zero, 自然零
8 C6 m9 s; f+ I* _Negative correlation, 负相关4 [6 p7 A. X$ C' ~
Negative linear correlation, 负线性相关
9 y' ~+ W! u4 Q, W' w6 sNegatively skewed, 负偏+ _$ i S% e I! R5 @
Newman-Keuls method, q检验
' a, B7 z; ~7 [+ |NK method, q检验
4 v& ~- f5 r2 T4 h# x% \No statistical significance, 无统计意义
% C$ c7 _9 Q1 h/ o* `Nominal variable, 名义变量
# j; U8 D- B5 I4 QNonconstancy of variability, 变异的非定常性
. v: B3 M: m4 B z6 z# s8 ONonlinear regression, 非线性相关
) G9 ~/ M' n5 ?! U6 Z) A- n7 ENonparametric statistics, 非参数统计
4 T% e) ?/ D2 G3 ]Nonparametric test, 非参数检验4 _- q2 M+ l5 [( u
Nonparametric tests, 非参数检验" O. ~) x! Z+ M7 h3 G
Normal deviate, 正态离差
! v! s3 }4 `* qNormal distribution, 正态分布' E( G( Q/ T* Q! n6 x( E
Normal equation, 正规方程组) E# a/ c% @$ ?1 F
Normal ranges, 正常范围
; `/ U& @) n: ^Normal value, 正常值: Q5 h; t# @1 l W
Nuisance parameter, 多余参数/讨厌参数& ?( o: h+ P i4 H7 ^! \9 B# q
Null hypothesis, 无效假设
9 @2 A2 m% y/ ~% V; v4 oNumerical variable, 数值变量' m+ \3 a% l( H* E2 P3 u. \7 Y
Objective function, 目标函数
; Z& q( v0 Y& J7 x* ?Observation unit, 观察单位* m0 b! O0 l# t. S M
Observed value, 观察值: }# o- a: b4 s2 R2 l2 m4 t
One sided test, 单侧检验) {- b% [. N6 l x- V6 F
One-way analysis of variance, 单因素方差分析
9 E7 E2 [1 o; k3 t6 e7 XOneway ANOVA , 单因素方差分析
& g: g8 w5 c$ EOpen sequential trial, 开放型序贯设计
1 o1 k2 M a$ G) oOptrim, 优切尾
$ o- t7 z% e' DOptrim efficiency, 优切尾效率
7 G1 { {- x6 ^# p" l# oOrder statistics, 顺序统计量
- `3 ^; A6 e0 }5 wOrdered categories, 有序分类
+ }& d4 i( Z6 @! @$ F4 NOrdinal logistic regression , 序数逻辑斯蒂回归5 t, U7 p. \; r+ l- l6 X
Ordinal variable, 有序变量 z8 r8 x0 s5 I2 E1 i
Orthogonal basis, 正交基
' M$ q c3 D6 B Y1 }: G+ tOrthogonal design, 正交试验设计' u7 @) m" V% d- p( Z
Orthogonality conditions, 正交条件
# x, W" ^) V4 Y# [# VORTHOPLAN, 正交设计
, b' A: ?9 e1 ~1 q! _Outlier cutoffs, 离群值截断点
* d( [! u' w' ^( ?6 H# K: h* xOutliers, 极端值
/ v6 ^5 K- p/ B& MOVERALS , 多组变量的非线性正规相关 ' \( g7 A4 H2 _" A2 f
Overshoot, 迭代过度. {! a2 v2 X9 M
Paired design, 配对设计
! v( R* T1 G5 m$ p( u# `Paired sample, 配对样本3 Q. f3 X: a% h2 M2 l
Pairwise slopes, 成对斜率" G* a: f' [; @/ ^$ d) f3 b# n8 Q* s
Parabola, 抛物线, b+ K# d, `6 M+ g5 u
Parallel tests, 平行试验
. y- q8 _; w& F' |% B$ q3 N0 DParameter, 参数
8 H \' G! S% Q* \; r8 kParametric statistics, 参数统计
9 Y2 k% y+ f: i& hParametric test, 参数检验
) g' b( `' a/ q1 LPartial correlation, 偏相关
2 @2 `% I9 P& ]; A# J& X7 BPartial regression, 偏回归0 M0 c# n9 b- G1 M& f2 V9 _
Partial sorting, 偏排序, Y& l. E& M% X% F
Partials residuals, 偏残差. Q1 P1 ?' U8 {$ Q- z" `5 z
Pattern, 模式; K( e( C. K" S
Pearson curves, 皮尔逊曲线. B) R. C) t8 @7 v* Y6 d# h
Peeling, 退层
, E6 o0 ~; k8 VPercent bar graph, 百分条形图
' g8 k* y5 }3 Z/ P# b( d+ QPercentage, 百分比# M+ U: N+ w/ _1 `) z
Percentile, 百分位数% a# d2 d- ~3 k3 f' ~' Z' s
Percentile curves, 百分位曲线
" H# z! f9 R, s: T" `Periodicity, 周期性, J e `3 W. ?9 `- G2 I$ U$ d& n
Permutation, 排列
% {2 W; v4 a4 j, b7 x0 f8 IP-estimator, P估计量
) S6 Q0 v; i }! W" c" sPie graph, 饼图
8 w8 ^, D$ K+ b a4 x3 TPitman estimator, 皮特曼估计量. M2 C, u$ w6 p+ C
Pivot, 枢轴量
1 H) i( R: O( K2 O: PPlanar, 平坦+ I) G9 `2 e; \
Planar assumption, 平面的假设
" y8 c# [5 U! F7 s: V9 D1 HPLANCARDS, 生成试验的计划卡; P) C% g+ p8 j8 K( }
Point estimation, 点估计
0 y2 Q, l3 n' LPoisson distribution, 泊松分布
* ~3 x, v$ h8 }Polishing, 平滑
8 z. C$ m4 X+ @4 n2 b" l8 `1 @Polled standard deviation, 合并标准差( T: f9 z) R) J1 }3 X5 y
Polled variance, 合并方差4 e7 d5 a+ J. p0 |& z/ o' ]
Polygon, 多边图
+ y v# c& k) x2 D& |1 l6 B3 ]) Y+ kPolynomial, 多项式
; | G5 k7 z1 t1 M6 Q. XPolynomial curve, 多项式曲线* h4 U: J0 z/ [
Population, 总体
% g7 u0 l3 K# A5 L7 [# R! a( U" KPopulation attributable risk, 人群归因危险度
% c9 _% R% p. _8 |3 x' T4 PPositive correlation, 正相关
I$ Q8 N3 \; x' ]* pPositively skewed, 正偏
6 }0 U( d( H. t! g# ~4 _: ~3 _& iPosterior distribution, 后验分布7 d$ m$ E# A7 W' s, p9 w
Power of a test, 检验效能
; R9 t8 M+ s, \# x& Q) T# F/ y( VPrecision, 精密度, I, A$ ]5 C' G
Predicted value, 预测值, W7 q7 R# [! r# b) B
Preliminary analysis, 预备性分析
6 \! S \# w" l& FPrincipal component analysis, 主成分分析4 e( v8 o, t2 s1 b$ z5 H; J; F
Prior distribution, 先验分布& H+ j4 D! U9 U1 b2 E9 e" G; H
Prior probability, 先验概率
. y& b6 p: b3 X7 k; D9 `% mProbabilistic model, 概率模型6 @5 d$ j3 d2 q% r2 a# s" q7 E2 d; A, p/ s8 A
probability, 概率# T$ v: J) ?9 T4 `3 K. `8 R: O
Probability density, 概率密度
( N+ d! ~$ S( Y. K$ e2 OProduct moment, 乘积矩/协方差
; y$ n2 I# A" W" n- [Profile trace, 截面迹图
3 F0 ], U t+ U* s1 mProportion, 比/构成比
% C! C6 y5 D1 Q* w1 a0 qProportion allocation in stratified random sampling, 按比例分层随机抽样
5 |, @4 c! N. X- H7 @Proportionate, 成比例- ^1 W( B6 f- t) A7 f
Proportionate sub-class numbers, 成比例次级组含量6 x3 k. E: e0 L; s; O, d6 @
Prospective study, 前瞻性调查
; N1 ~; e" m. Y) t$ D' {7 {Proximities, 亲近性 + t ]9 k+ q, w" k5 Y: q- }( K
Pseudo F test, 近似F检验
( r% j) v' U. O9 yPseudo model, 近似模型1 y# @, d' Q) E$ O3 I- {5 i( }' d
Pseudosigma, 伪标准差6 H$ U+ w- p) F* h6 _$ @
Purposive sampling, 有目的抽样
9 H7 a1 k: C- `. a1 B" ~1 t5 ]QR decomposition, QR分解* c2 p1 {1 ~, \ I+ b/ M; C& P
Quadratic approximation, 二次近似
# w& ~- O/ S: N1 u4 l, ~Qualitative classification, 属性分类
% @" b& ]: {3 h# Z) f: R6 m: aQualitative method, 定性方法) S* p3 L* ^6 O/ t; R& h; Q% H. Z+ L
Quantile-quantile plot, 分位数-分位数图/Q-Q图( g. Y4 U) w5 u2 ]( d' q' m
Quantitative analysis, 定量分析4 c- A( Q6 P7 t
Quartile, 四分位数
9 g2 K& {. M- g, PQuick Cluster, 快速聚类
; z+ n! y0 s7 }( B$ ]& cRadix sort, 基数排序/ v! x0 h; {5 @& L9 G
Random allocation, 随机化分组: j# O7 ]4 w. ]
Random blocks design, 随机区组设计/ M) `0 u: c% E7 L6 O1 S1 f, j
Random event, 随机事件/ B4 M3 e2 a. N' o. o. K+ W3 _
Randomization, 随机化
" I( z b5 L7 ^ ?! i" r. bRange, 极差/全距
4 q3 ^% m' J& e$ \Rank correlation, 等级相关1 K5 n1 u8 R% G# K( @# @
Rank sum test, 秩和检验
3 J9 h) V/ m' M: c( hRank test, 秩检验
8 k1 d/ ~6 F5 c. J5 rRanked data, 等级资料
+ K3 h6 a# S5 r6 O9 QRate, 比率3 M+ B2 M ~( T9 d! o7 p F/ u) F
Ratio, 比例) X' N7 V6 y3 `, m
Raw data, 原始资料
* o9 c) y/ x3 pRaw residual, 原始残差0 Z+ X3 I9 l8 `( m
Rayleigh's test, 雷氏检验$ V& \$ _, _$ P! X( v4 N
Rayleigh's Z, 雷氏Z值 4 D% K% `% Q" S0 ?& G) u
Reciprocal, 倒数( H' ^& k- }$ r9 i; K! n
Reciprocal transformation, 倒数变换- G* F" {& [1 L% t
Recording, 记录6 H6 a+ |1 m8 A/ D# e* ]
Redescending estimators, 回降估计量
! @" I6 B( T5 J0 G' qReducing dimensions, 降维
9 p9 o' T6 T; q: CRe-expression, 重新表达
I! @0 l, N% j, r1 r8 \9 ?) ?Reference set, 标准组
. M' `8 ? r+ O. P5 S% v' P2 sRegion of acceptance, 接受域
3 z+ }& A8 I' bRegression coefficient, 回归系数+ r2 P* t2 C. e L
Regression sum of square, 回归平方和) V8 O/ P; i- m. v8 H9 Q
Rejection point, 拒绝点2 ?7 b' i* O; z9 _- k
Relative dispersion, 相对离散度% _ g9 d4 r9 G
Relative number, 相对数+ W7 S' q( Q4 m) O; [
Reliability, 可靠性& D( k8 a* F! e7 f' S' K5 Z1 n
Reparametrization, 重新设置参数
6 z. R' A/ p! \Replication, 重复
$ X( m* R2 a& r, y; LReport Summaries, 报告摘要
# w; h. j0 g c, k; x# B0 BResidual sum of square, 剩余平方和. V5 ~$ X/ Z/ d
Resistance, 耐抗性0 S" x& i) [4 T- e6 r
Resistant line, 耐抗线$ N% i; {9 T) X0 X( i P$ \
Resistant technique, 耐抗技术
+ [! V$ f" [ `/ t) C2 m- aR-estimator of location, 位置R估计量
6 O5 k$ R2 y/ h7 zR-estimator of scale, 尺度R估计量4 T* o9 d2 m2 ~8 F$ q# f% S) l% d
Retrospective study, 回顾性调查
8 ?4 l) F8 J" {5 ]Ridge trace, 岭迹! m) ?$ h7 p: h- I
Ridit analysis, Ridit分析' C$ m! Z9 e/ I t+ E
Rotation, 旋转+ P0 T3 M& L, P. G4 A
Rounding, 舍入" r+ ?4 F7 _/ \( d1 L0 a" e# y% d- [. S
Row, 行) k. t3 _: R5 O4 g; o
Row effects, 行效应) q7 v) n k: N3 Q3 f3 _8 {& l& q
Row factor, 行因素- c' S- @+ ~& g: b
RXC table, RXC表
& \9 o$ {2 h) ^Sample, 样本. R6 I4 f1 w) p5 L4 x$ f* X4 s
Sample regression coefficient, 样本回归系数7 e+ z1 r2 x$ q
Sample size, 样本量 [5 c4 l* L5 N z
Sample standard deviation, 样本标准差4 V/ p- E6 L! [
Sampling error, 抽样误差 {+ Q& z; p7 b% E3 t
SAS(Statistical analysis system ), SAS统计软件包6 L$ `6 S; d/ w. f4 [
Scale, 尺度/量表
5 B0 @+ h5 R8 o" c, iScatter diagram, 散点图2 g/ e: u7 \. x- A' L" C7 D
Schematic plot, 示意图/简图
* _* o3 w4 g8 t4 I$ N, G! {Score test, 计分检验
7 c+ S- q" d+ v/ L( A1 RScreening, 筛检
0 i8 E* q# r; @+ D* oSEASON, 季节分析 N1 {3 d8 q( h- S
Second derivative, 二阶导数3 H9 o5 H8 _3 s% I9 o+ {/ g) C
Second principal component, 第二主成分
: W" L9 J* o) ^1 o* P- y& |SEM (Structural equation modeling), 结构化方程模型 # j4 D" q- I0 w h$ `7 f
Semi-logarithmic graph, 半对数图
7 I0 @- T$ k1 c: \/ E& VSemi-logarithmic paper, 半对数格纸
5 O: U0 B6 a7 m! D6 E& A- w- MSensitivity curve, 敏感度曲线8 `( ]* I/ A W- ]2 N- D
Sequential analysis, 贯序分析4 C2 @! D1 X' Q+ @& c C* O
Sequential data set, 顺序数据集5 f+ m0 k) a" H: \) F
Sequential design, 贯序设计
+ A$ q+ X. w5 P8 b6 f4 _+ ASequential method, 贯序法
3 O6 B9 x3 E- y! NSequential test, 贯序检验法
3 Y8 h& S5 e' J" Q1 C1 VSerial tests, 系列试验+ Y% X8 |8 f- ?* }1 {) W
Short-cut method, 简捷法
+ \+ A) {) N7 C2 k. i' l) G8 ASigmoid curve, S形曲线8 V# I2 r: r( ~1 f
Sign function, 正负号函数7 Z# d/ [- f4 Y' r/ g8 W5 c
Sign test, 符号检验
! ]# ]! M+ }, s) D9 n/ \, W5 [, B; ISigned rank, 符号秩* }$ j. e# Q# o5 P7 _4 i( a! |
Significance test, 显著性检验
9 c% e% |# m2 v. w) \; ZSignificant figure, 有效数字
S( t3 [" ?0 e: W( L' OSimple cluster sampling, 简单整群抽样
6 P; j% Z/ D# b; Y: D$ `Simple correlation, 简单相关
) `& U. B# V& p( v$ N! y; g3 bSimple random sampling, 简单随机抽样 a: X9 S: u( o/ F# D: ~# A: T
Simple regression, 简单回归8 K/ y$ f! S9 W
simple table, 简单表
L# \8 M0 o1 M0 }$ E: nSine estimator, 正弦估计量; Z% ]6 ~! T1 q$ m/ K7 T4 A. Q. A
Single-valued estimate, 单值估计
0 A( Z( E+ }& y1 E7 nSingular matrix, 奇异矩阵/ U& }; U6 a7 @
Skewed distribution, 偏斜分布
9 C+ S3 t2 g0 z3 e% DSkewness, 偏度
3 r" [5 I: `8 ISlash distribution, 斜线分布
; v9 H, n+ J' U! BSlope, 斜率! D8 x i2 O! F$ H. b5 [
Smirnov test, 斯米尔诺夫检验
@$ Y8 e# {* |; F& a2 J1 A2 ]( CSource of variation, 变异来源
; W2 D4 z0 e' p) kSpearman rank correlation, 斯皮尔曼等级相关: N) h2 Z6 o7 D- `, w" I
Specific factor, 特殊因子5 s1 u: G* k: \" x& K* S2 K; c
Specific factor variance, 特殊因子方差
; b# ^. n+ ? xSpectra , 频谱2 ]' Y. w9 M4 W/ ~
Spherical distribution, 球型正态分布5 I9 i2 y5 d% d5 b7 v$ A
Spread, 展布
. V0 f5 W5 h B1 W& \+ l GSPSS(Statistical package for the social science), SPSS统计软件包
2 I+ Q$ E# M0 qSpurious correlation, 假性相关1 k5 q: a7 O4 g/ q& H
Square root transformation, 平方根变换 \4 h4 m$ k( m: X
Stabilizing variance, 稳定方差( {' q$ a. a0 r* d
Standard deviation, 标准差8 [5 P$ b H7 A+ U7 F
Standard error, 标准误
$ b8 y9 t7 P' U$ P1 s9 R e! `Standard error of difference, 差别的标准误# A* U* A- E8 |+ d0 \) N
Standard error of estimate, 标准估计误差
0 X" n: ~# g7 h( p! w0 D8 ]Standard error of rate, 率的标准误) p2 h) i( V4 Q7 k1 Q% E
Standard normal distribution, 标准正态分布4 r. V0 [+ `0 y, t z$ H' s/ {
Standardization, 标准化) w# c% u& v: K- p
Starting value, 起始值+ Y' b7 K* `, M$ [# O
Statistic, 统计量
3 l( J/ a2 k4 I6 ]Statistical control, 统计控制
# X6 C8 @: w$ m- HStatistical graph, 统计图" d) Z" {% g( V# \9 S) O
Statistical inference, 统计推断
) k- n: J7 J g/ eStatistical table, 统计表
" ]0 Z) n& G$ [9 m3 OSteepest descent, 最速下降法- D" u$ ^$ y9 A3 }
Stem and leaf display, 茎叶图
7 c$ ]% o/ P; }3 ^# |Step factor, 步长因子
$ [4 C0 x' N. V5 a1 I _; b9 }. w- oStepwise regression, 逐步回归
7 X$ `( S& E) e& l& q& {2 q8 G2 u4 ^Storage, 存4 _) `% E5 g/ y; M5 _% k. ]+ I i
Strata, 层（复数）
/ A! g; O/ z* U4 m9 T3 NStratified sampling, 分层抽样% l9 m3 l, [& Y t5 _. ?
Stratified sampling, 分层抽样) r$ V1 _* t3 p1 l3 Z( n
Strength, 强度- _4 E# z$ t( y4 L/ O5 |6 _
Stringency, 严密性0 @; i* ~; `5 i3 `1 g. T7 T6 Y6 F& L
Structural relationship, 结构关系5 M- Z2 U- H& ?' q
Studentized residual, 学生化残差/t化残差
/ f8 w/ G* Z3 a/ H w; ?$ CSub-class numbers, 次级组含量
/ q( ?5 A/ M+ V; v, CSubdividing, 分割
2 U4 ^3 T& k; a$ ]( G5 i9 }& k2 `Sufficient statistic, 充分统计量+ K: P/ v1 C8 v- _3 ]
Sum of products, 积和
9 T; m6 w/ P, A8 t9 PSum of squares, 离差平方和% {4 `$ k; ?* \
Sum of squares about regression, 回归平方和8 Z- V0 j* J. y0 Y( A
Sum of squares between groups, 组间平方和3 X; o8 N$ T0 x( n
Sum of squares of partial regression, 偏回归平方和
6 }) X3 i8 s$ A; e5 U iSure event, 必然事件/ D1 \, K- o& o! J" j+ u
Survey, 调查
& t8 W# S& F6 I3 d; MSurvival, 生存分析
1 N) O! [# _3 R2 B# s1 r; LSurvival rate, 生存率
* h) \# R% I/ q2 g. H5 }Suspended root gram, 悬吊根图% F0 |' i; l) L/ u2 P; \1 v) n
Symmetry, 对称
; Z- O; j0 R) Z. @Systematic error, 系统误差
+ W. P! T# y; G- ~ {Systematic sampling, 系统抽样- K$ z# I, ?( z) m; R' W9 [2 I9 M
Tags, 标签8 {' E6 T& {) ^4 x: |* ~: c9 c) |* K
Tail area, 尾部面积
: i8 A$ W& T9 q( j+ Z5 ~' STail length, 尾长
8 t, P* W* I2 p' m zTail weight, 尾重0 U6 B; B' ^& h" d7 y4 y. v7 M
Tangent line, 切线
8 \& @, P5 P7 W' L* W% y) |/ s/ G- WTarget distribution, 目标分布8 x4 p$ I* j1 k% ^" b/ I
Taylor series, 泰勒级数# j$ u$ y* R: U6 n# h4 n
Tendency of dispersion, 离散趋势
7 n& [/ A/ `. q7 Q. I- O5 MTesting of hypotheses, 假设检验$ R& j8 C/ z7 Q4 |- y$ w3 l' r
Theoretical frequency, 理论频数3 l3 A' H! X+ y* D% P u, _ l
Time series, 时间序列& g3 L' F0 F5 j# {' m
Tolerance interval, 容忍区间% v1 _! X# z; b2 i! a
Tolerance lower limit, 容忍下限
% s) h( v% Q" _Tolerance upper limit, 容忍上限: ` q0 X' L2 M
Torsion, 扰率1 @7 J0 y. g2 m, Z- b' ~
Total sum of square, 总平方和/ ^! l$ U; ]" Q9 t. }# J4 R
Total variation, 总变异
3 k5 q) q. x* w! k9 STransformation, 转换6 }' U) N6 D/ [& r% T/ w+ l! A% l
Treatment, 处理* p- \ {& K3 p% D
Trend, 趋势
6 X+ j) r! N" v" N" e7 @7 ]1 BTrend of percentage, 百分比趋势
x6 Z4 K+ n& P; OTrial, 试验5 f- P8 o$ H' ?! R
Trial and error method, 试错法8 t6 _( t$ X4 W+ \* K/ d2 v' G& a
Tuning constant, 细调常数
2 ]/ S. { _1 c( q4 b, c1 H0 t! rTwo sided test, 双向检验& I! @+ \+ F# ^0 U9 a, Q
Two-stage least squares, 二阶最小平方# q6 N4 ]0 A9 d O% d: S5 S* {
Two-stage sampling, 二阶段抽样* ~$ N1 n5 Y5 v% E6 q
Two-tailed test, 双侧检验
& N4 v: l5 }+ ~2 @) c5 J K- M! yTwo-way analysis of variance, 双因素方差分析
2 d! e f- T; W V% y8 Z# MTwo-way table, 双向表7 \4 q: U& Z4 V# S: a
Type I error, 一类错误/α错误
# ~5 J7 J5 i: \4 E# LType II error, 二类错误/β错误
+ h9 [5 Q. Q7 w7 q. R& M2 A8 kUMVU, 方差一致最小无偏估计简称
* G( ]7 N" c3 W. Y" ]' l4 fUnbiased estimate, 无偏估计
. P3 |# G4 O I7 OUnconstrained nonlinear regression , 无约束非线性回归
8 w; J' Y, Y4 k9 ?) s; xUnequal subclass number, 不等次级组含量( o! s# A5 \5 ]# C/ N$ `
Ungrouped data, 不分组资料
( F' c2 A4 e7 O8 ~: kUniform coordinate, 均匀坐标) s! x& Y9 t% p5 ? u. V/ L
Uniform distribution, 均匀分布+ Y6 w. C0 d% F. x7 ]3 Q& a
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
6 T$ V6 A1 L) s$ Y" A2 U' ~/ hUnit, 单元: E7 D3 j, C5 j5 k+ c' q
Unordered categories, 无序分类9 B. d! k! r/ [0 t1 X; ^1 m
Upper limit, 上限
/ Z9 i' q, t% U6 @Upward rank, 升秩
' W4 V4 j1 [/ p n1 ^Vague concept, 模糊概念
% l- `) w9 M/ i( J; Y7 i* P4 TValidity, 有效性
- p- b& J! x f j! K6 KVARCOMP (Variance component estimation), 方差元素估计" Y7 `2 L: Y! U2 s9 e) u4 p1 C
Variability, 变异性9 l3 ]2 |" E) k5 {& e% m9 J
Variable, 变量
9 ]) j t( l/ d- F% S4 ]/ b' JVariance, 方差. }& J6 A' s- ?: v% N# F; ~& S
Variation, 变异& B1 j' t m U0 y* a! b
Varimax orthogonal rotation, 方差最大正交旋转
5 g& W, y3 u. @' C8 c5 cVolume of distribution, 容积( I% F- P" [$ K( C! r/ `
W test, W检验
0 C7 q* p& v1 p1 e- a& zWeibull distribution, 威布尔分布0 t4 i# n2 D) c/ {1 I. \* r
Weight, 权数
" X6 Y* X& r! `! _6 GWeighted Chi-square test, 加权卡方检验/Cochran检验8 o A. r, d F, v8 R( V
Weighted linear regression method, 加权直线回归- R: s( c( R' E# M3 i- ]# @
Weighted mean, 加权平均数
0 l1 K' g4 M4 ~+ zWeighted mean square, 加权平均方差$ r! E( P7 m, z) Y, u a- n
Weighted sum of square, 加权平方和# W. W# ?! |6 w1 i: I
Weighting coefficient, 权重系数
5 G c2 x7 c$ O; v6 gWeighting method, 加权法
- J2 T2 }1 J. i- g% |) x" t( CW-estimation, W估计量4 t: t! s6 Q+ }& A V1 l
W-estimation of location, 位置W估计量% t1 `% y; i% P7 ]; a; S& w, X+ }
Width, 宽度
+ d4 H( p* _" b3 ]2 t2 KWilcoxon paired test, 威斯康星配对法/配对符号秩和检验. c6 P# d: [/ h. L I, P4 G/ C) A8 G
Wild point, 野点/狂点
) Z& D& [) R! O# H# [2 _Wild value, 野值/狂值
1 i7 L, a- m0 B% ?* AWinsorized mean, 缩尾均值, H) H! y8 @/ A1 _8 M
Withdraw, 失访 . H* z; G& k ^' C
Youden's index, 尤登指数: {8 M' }' R7 w7 w$ Z
Z test, Z检验* b% D, T) V# E
Zero correlation, 零相关9 A H6 V1 E E: \: Q% _
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
