|
|
Absolute deviation, 绝对离差
: j0 a: t6 a8 jAbsolute number, 绝对数
2 _2 r! b( G- o/ D5 g5 ~& sAbsolute residuals, 绝对残差* S5 K& P8 E. j; f
Acceleration array, 加速度立体阵% w) U7 Z( M% k' a6 S0 n
Acceleration in an arbitrary direction, 任意方向上的加速度
* u0 n/ C- F0 pAcceleration normal, 法向加速度
8 V4 B5 q4 B% J$ B6 ~: YAcceleration space dimension, 加速度空间的维数
s- U- T1 B5 G; O& J% xAcceleration tangential, 切向加速度
" L. ^, }2 M* S" DAcceleration vector, 加速度向量
- V( ]. V3 S$ r& E QAcceptable hypothesis, 可接受假设+ b1 c4 S4 u8 H
Accumulation, 累积% T. d4 i1 L E, D# K+ f
Accuracy, 准确度
: N# q6 p s! A, D ZActual frequency, 实际频数
7 T9 g* w H# k* T P9 W* cAdaptive estimator, 自适应估计量5 i( f1 _ N0 C4 b) s; H8 p% A
Addition, 相加0 c4 G. }- Z) Q
Addition theorem, 加法定理* Y* m5 A3 e! D
Additivity, 可加性
7 a. H: j: ?6 k8 y" \Adjusted rate, 调整率
5 ~9 l& H; N: i% C2 ?Adjusted value, 校正值( W2 F8 n, j, s
Admissible error, 容许误差
5 w: B/ @( f) L wAggregation, 聚集性
, h6 Q+ V* X: H' HAlternative hypothesis, 备择假设$ U- w$ B% B2 V$ |6 q8 D1 B
Among groups, 组间- Q+ z, L! e. N
Amounts, 总量! y s# b7 x' L; L# [
Analysis of correlation, 相关分析! C3 v2 V M( ^" O6 g# K3 O% E
Analysis of covariance, 协方差分析3 \& J$ i ]" x, m/ E/ U
Analysis of regression, 回归分析3 {; f; V& a* V$ S' ~* j% @2 S
Analysis of time series, 时间序列分析9 I9 |+ X: H: d0 |
Analysis of variance, 方差分析
4 S& K8 v4 v7 D3 {, W* h) }& mAngular transformation, 角转换
- G9 O. ^# m& C( Z1 I# f1 Z6 Q. N4 TANOVA （analysis of variance）, 方差分析
. G4 T) m7 c2 a! V" o5 iANOVA Models, 方差分析模型
: ~7 }) w) f: h6 b y# z. A& {Arcing, 弧/弧旋
/ R+ Z. u; D1 m8 c1 }Arcsine transformation, 反正弦变换0 g v4 z1 u5 i1 y% Z
Area under the curve, 曲线面积
6 {) y* ~- y% p5 `7 AAREG , 评估从一个时间点到下一个时间点回归相关时的误差 * p4 M1 E2 S6 v' t
ARIMA, 季节和非季节性单变量模型的极大似然估计
: h) e+ e. O' Y8 c. u3 UArithmetic grid paper, 算术格纸 M: O0 D% N4 W) k- |
Arithmetic mean, 算术平均数3 A! H4 H7 }" V( `
Arrhenius relation, 艾恩尼斯关系
; ]; |5 `+ H( n$ [! ]2 {( sAssessing fit, 拟合的评估
A! @. h' T- F* B: T% L# o+ p5 J& @Associative laws, 结合律9 I7 r* z/ Q, U7 b" u, _
Asymmetric distribution, 非对称分布
1 Z3 m9 D3 d1 P9 H, o) UAsymptotic bias, 渐近偏倚
7 K L& k$ |, j" D0 HAsymptotic efficiency, 渐近效率$ i( z# o( |) Q4 B
Asymptotic variance, 渐近方差
0 ?" O% ~8 p7 c) t" P; FAttributable risk, 归因危险度
- c- u# X: p- d% M! dAttribute data, 属性资料& W0 M% d0 J0 G, W) q8 z* m
Attribution, 属性9 X# |9 t, E2 [
Autocorrelation, 自相关' C8 X O# I- q4 S- T
Autocorrelation of residuals, 残差的自相关( {5 b8 ?2 o! ?
Average, 平均数
: u7 X9 [- w+ FAverage confidence interval length, 平均置信区间长度. v3 n- C$ Q) R5 {0 J0 j& k
Average growth rate, 平均增长率2 k( j# ]! K) I2 j5 J4 i
Bar chart, 条形图
! z4 b7 S% d% t& `( l% mBar graph, 条形图+ P8 m* d( [4 d/ f
Base period, 基期* Y) g/ B9 m0 o0 O
Bayes' theorem , Bayes定理
2 @, I" N/ j! Q/ \; l+ i; dBell-shaped curve, 钟形曲线" n" H: t/ H# m/ m- c$ i- x. _1 H
Bernoulli distribution, 伯努力分布
- w T9 v& F% }* m5 ^Best-trim estimator, 最好切尾估计量& ` p6 W) G) z' T
Bias, 偏性2 B* a* I% e+ w8 d1 e
Binary logistic regression, 二元逻辑斯蒂回归
1 e' a) i8 i& g; e" g* o ^* `4 C% `Binomial distribution, 二项分布
9 x' j& s% ^6 f7 wBisquare, 双平方
; C1 r$ y8 o) l- [; \Bivariate Correlate, 二变量相关; ]: `2 W# ^7 A
Bivariate normal distribution, 双变量正态分布* g. P% |8 m# h7 [' G _7 r% }
Bivariate normal population, 双变量正态总体
7 m; o. b( }1 g: `Biweight interval, 双权区间7 ?0 S( G# o& _" C; r! V
Biweight M-estimator, 双权M估计量
) ^1 O$ |9 r1 G! b( X6 d. j- QBlock, 区组/配伍组
; F" a7 q4 u: Z5 o+ Z6 H- F7 eBMDP(Biomedical computer programs), BMDP统计软件包0 V& X8 {( S" x+ C0 d8 w! x
Boxplots, 箱线图/箱尾图
- z e9 S/ V4 Q8 S/ cBreakdown bound, 崩溃界/崩溃点
2 h( m/ R. \. L0 m3 Y. NCanonical correlation, 典型相关6 f* ^# l) p! s& H" f( T4 [& K# ]
Caption, 纵标目
2 c, _7 I. Q$ z6 t) T- ?' cCase-control study, 病例对照研究, ]) Q, l2 R$ N$ Z
Categorical variable, 分类变量5 \6 h" P2 I; L- m3 U @
Catenary, 悬链线
/ g, Q9 d3 E! I+ x$ O3 xCauchy distribution, 柯西分布
. g& P' }/ d& D: r# @+ {Cause-and-effect relationship, 因果关系+ a+ u: _$ K( _! e2 d
Cell, 单元% H, h( x, P! @0 F! \
Censoring, 终检& K& ]& a3 h6 S! c
Center of symmetry, 对称中心! h d# O+ e7 p; j/ J, @- ~' S
Centering and scaling, 中心化和定标
3 e1 @% p4 \$ W& j6 x. J7 D7 Q- jCentral tendency, 集中趋势% c" B' X4 {, k# \; Q
Central value, 中心值) k) T# S ?0 M
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
5 m6 ^; a( O& \! P! ~& I+ z$ OChance, 机遇
9 Z0 J% _3 c- i1 L" LChance error, 随机误差( o6 d7 i- G3 E- X y7 a
Chance variable, 随机变量
# F6 _$ d& D" y" T9 T0 _' ]' x5 \' \4 zCharacteristic equation, 特征方程
* Z9 G* p7 B' I. b( E4 Q1 vCharacteristic root, 特征根( a( f9 |, I, S$ S1 F
Characteristic vector, 特征向量& e1 ]7 Z2 m' c3 V+ i. b( d4 v. c
Chebshev criterion of fit, 拟合的切比雪夫准则
( x0 _2 I5 W, h% l$ L! q/ z/ m" G" o! HChernoff faces, 切尔诺夫脸谱图) K4 G" }. y( L
Chi-square test, 卡方检验/χ2检验, h l- _$ n W3 X. [% \7 _
Choleskey decomposition, 乔洛斯基分解
! K7 M( {6 G3 FCircle chart, 圆图
& _0 V; r4 H" H. u# M" YClass interval, 组距
& \' }, S9 ~, Y* |Class mid-value, 组中值- S6 T0 M% U# s( p9 V
Class upper limit, 组上限
) x5 b# v2 R% NClassified variable, 分类变量
2 q7 R! h/ J. T" I( m pCluster analysis, 聚类分析" n$ [* S3 P1 j, ?% A
Cluster sampling, 整群抽样3 E1 j: \$ H( k# t" f3 E
Code, 代码. N9 z( O$ H: r" J
Coded data, 编码数据6 ] N$ |+ R% c6 ]
Coding, 编码
" J# d' }' ?- E% D1 H; qCoefficient of contingency, 列联系数
; [% G* Q2 K, U: N8 H4 _1 sCoefficient of determination, 决定系数
, u8 g/ w+ _0 J4 r! WCoefficient of multiple correlation, 多重相关系数
4 e2 T1 u; h0 `* T! ~8 }% r/ lCoefficient of partial correlation, 偏相关系数
. G% x) X/ R" V& n n$ oCoefficient of production-moment correlation, 积差相关系数
4 w" Q( E( f. r# T, p; xCoefficient of rank correlation, 等级相关系数
* i; D' b% _4 |6 ]8 }% e' T: l3 f' ICoefficient of regression, 回归系数
; m) n0 b! X2 e& j* K1 A5 X) pCoefficient of skewness, 偏度系数
/ B# T+ Z5 p8 E0 A& xCoefficient of variation, 变异系数/ h% ~1 k" V9 M1 V5 Y6 c- H5 \
Cohort study, 队列研究
- H7 y3 }" _8 |% G ZColumn, 列
. t: n% t9 o* C; q) f m! D0 pColumn effect, 列效应8 g! n5 ?% a) j I4 Z1 G, N
Column factor, 列因素 ^$ s( C3 d8 l+ g7 P1 C
Combination pool, 合并' L& w- P& v. ~8 W8 P
Combinative table, 组合表
. ?7 Q' i( V& U' J" JCommon factor, 共性因子- ^0 k B( N/ {% P9 N# X
Common regression coefficient, 公共回归系数' D) ]! W4 Z! Z' e, r
Common value, 共同值
$ l1 p" w3 G$ X7 R9 NCommon variance, 公共方差
! k2 H: g6 V3 x! d. n; hCommon variation, 公共变异4 s. S8 s! F: q1 r
Communality variance, 共性方差
r5 h# q' f I7 x; QComparability, 可比性 }' N9 Q5 i5 u# Z$ v" E" d' L
Comparison of bathes, 批比较0 p5 i4 g" h) m6 u8 y8 u2 ?
Comparison value, 比较值( _# q* C7 ~7 Z) C8 V
Compartment model, 分部模型% v$ e. N3 R0 y' s
Compassion, 伸缩; W9 E8 p' l B" W* H, p- B
Complement of an event, 补事件
8 X& ]- A$ g5 V+ BComplete association, 完全正相关
8 x. z9 f p& AComplete dissociation, 完全不相关
6 J; L1 I5 P4 HComplete statistics, 完备统计量- ~- h, H( S3 g# u+ S! j( \
Completely randomized design, 完全随机化设计, \( P4 R; p9 M5 U- p
Composite event, 联合事件
# L- i% S" z6 Q1 x3 ?Composite events, 复合事件' D8 ]. M$ `* O: b! r
Concavity, 凹性
8 l9 s2 s% D4 s2 n5 ]6 ~! w6 sConditional expectation, 条件期望, A8 {$ N- c% A5 x2 k2 s) ]
Conditional likelihood, 条件似然
2 x4 ^: i6 g+ J6 V& l8 mConditional probability, 条件概率/ Q" u8 L" b/ a$ K% ~' P
Conditionally linear, 依条件线性+ D3 ]! |$ f5 q, I7 o4 }; z
Confidence interval, 置信区间" d5 i/ s0 J+ J
Confidence limit, 置信限( E# s! l4 D" L# w1 g% |
Confidence lower limit, 置信下限
" S2 \- d5 K$ ^# g" l" v \Confidence upper limit, 置信上限
, r! y! @/ c% JConfirmatory Factor Analysis , 验证性因子分析
! t- F$ S( C5 T- ^( hConfirmatory research, 证实性实验研究5 _4 z; Q( _3 b/ k5 i& L' z
Confounding factor, 混杂因素
! {2 i7 L+ v2 X8 ]. K6 wConjoint, 联合分析4 `! D6 r7 z* |& e: f+ ^
Consistency, 相合性7 \- a3 d- L5 Q* n, }
Consistency check, 一致性检验
) A4 Y G: H+ e3 R1 [4 A" dConsistent asymptotically normal estimate, 相合渐近正态估计
" m. M3 L A* V: L' a3 S: PConsistent estimate, 相合估计
3 K0 j7 Q' n VConstrained nonlinear regression, 受约束非线性回归
9 d4 C7 }0 b/ ~Constraint, 约束0 E2 n4 U- X0 p t" S8 W
Contaminated distribution, 污染分布
+ z/ {8 A7 I; |: i; }8 a; c5 LContaminated Gausssian, 污染高斯分布
$ j+ U1 |) X: y U0 M/ Q" u# F' }Contaminated normal distribution, 污染正态分布& w% k1 u* k9 l6 H3 i1 U
Contamination, 污染
! a5 N; J4 Y0 K: QContamination model, 污染模型( P. { w. W" Y/ K- A) k
Contingency table, 列联表
" P8 B9 J7 {+ a' xContour, 边界线; F5 X, k1 T) U" d
Contribution rate, 贡献率8 S+ v r8 C. t L. P
Control, 对照
# e; v" x3 f# J$ r, J$ GControlled experiments, 对照实验
! r6 r8 Z5 S" q% n3 KConventional depth, 常规深度1 ^8 k. e6 _, I% J9 R/ T3 A
Convolution, 卷积; N: i5 U5 Y& B5 G6 v
Corrected factor, 校正因子
2 g4 H! n2 Q( g+ L! y& aCorrected mean, 校正均值
7 z2 Y" Y& }) b1 L1 n ^5 _- uCorrection coefficient, 校正系数
, C* `' \# n% `5 kCorrectness, 正确性% U- a2 A& l& i3 G3 C$ X
Correlation coefficient, 相关系数
4 E3 g+ _$ h' a& Z+ xCorrelation index, 相关指数( n% A& M$ ^" }$ ]+ G0 A0 e5 ]
Correspondence, 对应
2 Z% T: U; W0 MCounting, 计数: F/ q. v% r! d/ ^8 {
Counts, 计数/频数
? T2 |. \" I5 Y) rCovariance, 协方差
- W" K/ _ ?% ]8 c) U$ T1 _Covariant, 共变
$ m6 J; v u8 D1 f2 b8 ECox Regression, Cox回归+ }/ a8 ` \" g3 P
Criteria for fitting, 拟合准则 y+ T0 C+ m* Q" I D! H
Criteria of least squares, 最小二乘准则9 n3 K- G* T" G' ~4 y6 F, m
Critical ratio, 临界比
. u( l5 z. q$ p/ C+ T3 C8 z4 @Critical region, 拒绝域0 V. m3 J3 ~! n( F8 g
Critical value, 临界值( I( Q% u J$ q2 E& G) P
Cross-over design, 交叉设计/ i$ V; o% ]0 C D1 |
Cross-section analysis, 横断面分析
4 ~4 I; ^; W$ a" v% R q: M- m, j7 jCross-section survey, 横断面调查
' _: a- y) }; S5 }Crosstabs , 交叉表
# ^' D/ ?, p" Q ?+ ?Cross-tabulation table, 复合表 l' k, J& }) k4 _. a
Cube root, 立方根/ u. p6 A/ ]9 I5 y$ \+ L
Cumulative distribution function, 分布函数
, j& Q ^& _/ d: ?- iCumulative probability, 累计概率
p z0 }# H8 F5 @! pCurvature, 曲率/弯曲
/ ^, s" ?( [4 C/ z4 r3 GCurvature, 曲率" Y6 P7 `8 w7 U9 g) [& g9 j& M$ ?5 J# C
Curve fit , 曲线拟和 2 A/ {/ m8 t4 {: O8 _. Z
Curve fitting, 曲线拟合( C2 }4 w" H! c1 h+ A W
Curvilinear regression, 曲线回归, ~' Y4 M9 }' H9 B' _
Curvilinear relation, 曲线关系% V3 f( ]/ E& O$ ~1 _8 ^! |
Cut-and-try method, 尝试法% {0 X* p0 a/ S6 e m& Z) E% f! q
Cycle, 周期
& n' c% \5 i% c: R3 WCyclist, 周期性
; l9 W' |8 R1 R4 L1 H$ A6 q) YD test, D检验
8 f: S( U" P. ^% l6 ]- ~1 GData acquisition, 资料收集+ `7 @5 _7 e& P0 [% ^
Data bank, 数据库1 T6 V, v2 D9 Z+ f* z+ N/ e7 k
Data capacity, 数据容量3 K3 c( w3 e9 r4 u
Data deficiencies, 数据缺乏
) x7 T: }6 ^' N+ @& \Data handling, 数据处理
5 w+ Q5 r( @5 d1 I/ H* t, O6 rData manipulation, 数据处理9 N0 `6 K8 b* s2 q) f! ?5 ~
Data processing, 数据处理
+ `- ]$ ^) P, C5 R4 SData reduction, 数据缩减/ z* E4 }- V- }% j$ J
Data set, 数据集, R( N8 E7 |3 Y# P8 z$ V! R
Data sources, 数据来源
* Z4 n X6 U" G3 z+ Z; UData transformation, 数据变换& p2 H) W. @) V- } v5 y+ E% L
Data validity, 数据有效性
4 o/ F8 Z, a9 xData-in, 数据输入0 F, ?1 H% ?6 d
Data-out, 数据输出
8 E) ]) D" m) J$ D3 V! iDead time, 停滞期0 t9 d+ R: I1 f1 c4 I
Degree of freedom, 自由度* F) x8 V/ |( u2 d# y: T' A
Degree of precision, 精密度" A z9 ^, u+ Q( S% ~" h
Degree of reliability, 可靠性程度
2 E$ K# {- A0 Q: X6 tDegression, 递减* j) i$ F% O9 s
Density function, 密度函数- h/ _) `# b" V6 R8 z, o
Density of data points, 数据点的密度
% o# C/ s) k" |Dependent variable, 应变量/依变量/因变量4 _- ~* n9 S7 c. H- Z# u5 o/ `' D
Dependent variable, 因变量5 f; d+ z% N: L$ J k; Q% c9 [; b
Depth, 深度4 E- P0 i( c6 f5 M2 T
Derivative matrix, 导数矩阵
/ K# X6 L* K! A# V" q Y* g" ZDerivative-free methods, 无导数方法6 k' v+ O) O+ R: [+ y' m
Design, 设计. p' W1 M5 z9 Z" j
Determinacy, 确定性
1 S1 w1 d) E7 V7 }9 `Determinant, 行列式
# k. U+ M- ~* y! h% |Determinant, 决定因素: W" b5 O* V% ~: i! ]: U p
Deviation, 离差7 q0 t* }1 _. G
Deviation from average, 离均差
( o. C: X& q8 M3 p' E0 X" |# T: ZDiagnostic plot, 诊断图
& j7 G6 f% n1 n; mDichotomous variable, 二分变量
0 |7 I# x+ d7 y' m9 |: x6 XDifferential equation, 微分方程
0 s2 Q. G0 }* X# B, b6 q, lDirect standardization, 直接标准化法
! f2 a9 t! E+ |% wDiscrete variable, 离散型变量
' r6 I/ d# Q+ GDISCRIMINANT, 判断 : R; w" h" h' v2 J# o9 d' b# l
Discriminant analysis, 判别分析
9 t& d4 M+ e% v0 {3 DDiscriminant coefficient, 判别系数
& \- ^ L6 Z4 y ?# WDiscriminant function, 判别值
, ]! e" ]* w/ w* B% oDispersion, 散布/分散度
( B1 b# F5 Y/ f, VDisproportional, 不成比例的
8 s4 K s- c! S$ r5 M0 LDisproportionate sub-class numbers, 不成比例次级组含量0 e3 A; r, R# f) X
Distribution free, 分布无关性/免分布
0 g5 L8 u- u, u1 @0 _Distribution shape, 分布形状+ [& r& g' z" w/ f7 v- W" {7 `; ?' v
Distribution-free method, 任意分布法, K& z* u2 h; s
Distributive laws, 分配律: y7 R( t, c, ^6 D% r& U
Disturbance, 随机扰动项
% d# }0 r8 y) j/ UDose response curve, 剂量反应曲线
) \4 M4 C! y5 Y2 D8 K# WDouble blind method, 双盲法
P6 u) r% Q# [. ~. SDouble blind trial, 双盲试验
; b J% F1 R2 s/ I! n) k# k' y+ [Double exponential distribution, 双指数分布 a' ]1 q- w7 I0 O6 `
Double logarithmic, 双对数
% s' L5 W- T3 I( \; `Downward rank, 降秩 k+ U1 r, V+ H" n; F5 B A8 S
Dual-space plot, 对偶空间图
5 T5 u- Y3 L( v- N/ c# rDUD, 无导数方法# ]5 D7 V/ J/ E/ ~, j3 N
Duncan's new multiple range method, 新复极差法/Duncan新法
' I5 F. t2 z N- ~2 `& m) e' P8 }Effect, 实验效应# V- R$ K1 G8 I3 E9 j6 x; O D
Eigenvalue, 特征值7 N7 Q% L1 x7 h$ N; y( v% {7 ^
Eigenvector, 特征向量
- C( h8 f* s: D9 n8 LEllipse, 椭圆
" E" U; z1 U" p3 v+ k& e# QEmpirical distribution, 经验分布
. ?- {6 h1 c- ?0 W! TEmpirical probability, 经验概率单位& k: `+ a7 h& o# f F3 w0 ?
Enumeration data, 计数资料
1 K$ W" S3 r$ D: LEqual sun-class number, 相等次级组含量
+ z6 ^5 R$ W e) f9 v0 T, UEqually likely, 等可能1 [7 X8 r! G: b4 x x0 v$ L
Equivariance, 同变性
" \" D" B0 g& L* g* v# `& nError, 误差/错误
6 E" i7 ` N. H0 ?8 J1 m' _8 |" EError of estimate, 估计误差
- i4 D; l7 { D& x! A$ |9 E; RError type I, 第一类错误& E! N) [" ^, M, C
Error type II, 第二类错误
: B( _" F5 Z* R3 @, H6 L, R: I& d' d2 XEstimand, 被估量
1 F& M/ s) `! N6 S& rEstimated error mean squares, 估计误差均方/ J/ z6 @' I9 q3 ?5 D% k' v
Estimated error sum of squares, 估计误差平方和
+ T X; ]8 D- V3 [. o: a+ iEuclidean distance, 欧式距离0 G1 g6 h" D. u- u5 P
Event, 事件
$ U: [/ w& v; _0 H( MEvent, 事件
; @) ?/ q5 d: E! X+ @0 Z# V% B8 @Exceptional data point, 异常数据点9 r' o/ n' P# `( }4 Z$ r/ o
Expectation plane, 期望平面+ b- e% e7 Z: V4 [* \( q
Expectation surface, 期望曲面
- f. {* T. c5 V, hExpected values, 期望值* {. \# g' I4 a4 R, @' _) K
Experiment, 实验
" C X) |: b3 f% A1 h$ d pExperimental sampling, 试验抽样
0 f5 f; }) f1 m4 i8 k: M+ tExperimental unit, 试验单位- g) g% G$ @" Q$ b2 W
Explanatory variable, 说明变量; B' O; k% s) c' d# D. Q
Exploratory data analysis, 探索性数据分析
* w/ s6 {8 f/ q( {Explore Summarize, 探索-摘要4 e% I- L9 e; ]" S+ d! y3 W. U8 ^
Exponential curve, 指数曲线5 V3 |5 m2 k. X! q- H% y
Exponential growth, 指数式增长4 J, \* j3 @& v P- z
EXSMOOTH, 指数平滑方法 $ H: b# F* h) E2 ]) E9 d
Extended fit, 扩充拟合
# c7 W* \: A. x, y& ^* RExtra parameter, 附加参数
' s9 W' r4 a: T0 g7 \) R2 JExtrapolation, 外推法- f% D, _, @; O$ l* M
Extreme observation, 末端观测值
0 u( K+ G/ E" h' hExtremes, 极端值/极值
: U! x. r+ I. I3 X7 zF distribution, F分布; G7 c# n( @- ]$ U
F test, F检验5 ~/ M9 y2 G% j' m8 N
Factor, 因素/因子7 w8 t1 T+ T4 s8 I U7 F
Factor analysis, 因子分析4 T6 ]7 l/ t/ O% }" {+ u* b
Factor Analysis, 因子分析0 t) r3 N. `* F7 f# c: k
Factor score, 因子得分
: Z4 v) n: f1 q* {+ N1 ~5 j1 _Factorial, 阶乘) `7 I+ P% ^) F$ y
Factorial design, 析因试验设计3 A3 M/ z Y$ Z9 L( J. \/ `# @
False negative, 假阴性 U" P0 r9 N% M' b/ E/ F) M
False negative error, 假阴性错误
. }+ {/ M5 J* {8 T# B$ ~" sFamily of distributions, 分布族
' G+ }- B1 O/ l9 h( r* F3 U4 RFamily of estimators, 估计量族' {, X4 M1 m7 |- q: N+ U& W2 [
Fanning, 扇面
, J3 ~+ q \/ jFatality rate, 病死率- h e' V' y- S9 m! ~% S
Field investigation, 现场调查
j; n3 j. d' T* p& H5 U2 _Field survey, 现场调查
, m9 \& @/ g, y3 W# \8 sFinite population, 有限总体5 F- x' \4 m$ P' [
Finite-sample, 有限样本
. q5 `. I8 v T8 uFirst derivative, 一阶导数& ]8 N: A4 R1 B5 R
First principal component, 第一主成分
+ t- J" N3 v1 T t! m1 Z1 oFirst quartile, 第一四分位数0 k( z! I; x f# ]4 ]- ~+ S/ `- k9 Q
Fisher information, 费雪信息量
5 [! j& I; K8 i: B& q$ A$ ?Fitted value, 拟合值0 {, x& {* W5 i+ m2 p t) E8 c
Fitting a curve, 曲线拟合4 t2 Q! r2 \+ ?- S% Y0 Y9 _3 Y
Fixed base, 定基, m" t/ ?% r5 d) P& _- p2 \
Fluctuation, 随机起伏! |4 o2 w& J% G$ F. ?
Forecast, 预测
: w+ V9 k) m$ vFour fold table, 四格表
2 Q! }/ i! t1 z$ T8 \; yFourth, 四分点
: J! I( m5 [# g1 |Fraction blow, 左侧比率: w% o. Y4 e5 m/ r% Q7 Z H" \9 g' F
Fractional error, 相对误差
( l0 p0 A1 J N4 f% u* n. g) VFrequency, 频率/ U. E% o; k$ [% a, }
Frequency polygon, 频数多边图# i3 M6 U* w9 @: ]1 Q9 _7 j% b% K
Frontier point, 界限点
# Y( q! }# q/ O0 VFunction relationship, 泛函关系0 F& I0 K0 B( |2 u% Z5 @- ^$ e
Gamma distribution, 伽玛分布
- x3 L$ S$ h( U, t- d+ c, P) `Gauss increment, 高斯增量
1 E( y" i$ M- i$ p# s" v8 iGaussian distribution, 高斯分布/正态分布
1 X% d) M7 [0 rGauss-Newton increment, 高斯-牛顿增量
+ _% Q* t8 r* _% bGeneral census, 全面普查0 Y8 U# W: z9 m2 U% e# _
GENLOG (Generalized liner models), 广义线性模型
% I: R) m) l! W1 z1 pGeometric mean, 几何平均数
1 |( d$ r q3 @& bGini's mean difference, 基尼均差+ z/ K5 A; |$ d& r8 { F. k& i
GLM (General liner models), 一般线性模型
3 D' m. D: a& BGoodness of fit, 拟和优度/配合度1 f# J4 ~5 G- V% q: O
Gradient of determinant, 行列式的梯度; y: |& I' }; }& {
Graeco-Latin square, 希腊拉丁方
0 P* T1 y' x8 l+ f& |" mGrand mean, 总均值
M' J( g% g' M E) r$ PGross errors, 重大错误
3 I+ @2 Z) j5 ?, ]! j X! _5 n" b6 NGross-error sensitivity, 大错敏感度) V1 { s9 p$ y+ b6 E/ |. @
Group averages, 分组平均
k4 e( k$ e$ ?+ yGrouped data, 分组资料
# }, Z1 i4 c" b& w8 wGuessed mean, 假定平均数: s; O7 p% B! G& g! a9 A
Half-life, 半衰期
% w0 x: o @+ \8 Q8 I Q E' oHampel M-estimators, 汉佩尔M估计量 o c! O' C( V9 @$ H8 J
Happenstance, 偶然事件7 m$ h& V, P& P9 t, d
Harmonic mean, 调和均数
! O7 V- L. c1 s8 LHazard function, 风险均数: Y4 k: f- w, C% w j# S
Hazard rate, 风险率
. L9 T! B0 ~, [+ m& O* X XHeading, 标目
+ u* B: g ]* bHeavy-tailed distribution, 重尾分布/ ]* ]2 U8 T& j0 z9 Z5 [2 w% m9 l
Hessian array, 海森立体阵2 M* |( y* w K$ M9 w; S' S& y* B
Heterogeneity, 不同质# ]4 z- w Q5 L
Heterogeneity of variance, 方差不齐 # D& l8 b, X& n, z
Hierarchical classification, 组内分组, N! e7 K8 R) [- i+ `4 J9 K, S; T
Hierarchical clustering method, 系统聚类法8 ?# A% c# u, f: R1 A
High-leverage point, 高杠杆率点8 u N& ^- ?* q' M
HILOGLINEAR, 多维列联表的层次对数线性模型: I& L& ?1 F) Y/ e
Hinge, 折叶点1 y9 s; t4 E6 o* @% U& w: b$ |
Histogram, 直方图8 X; f1 ^* g# o$ Z3 w6 F) ^. L i2 f
Historical cohort study, 历史性队列研究
* c) \8 A" P' m& r% w/ P2 K2 A" Z+ iHoles, 空洞
3 M" N; Z, S0 r/ WHOMALS, 多重响应分析
1 X7 ]; e3 B* m# V! V4 f! }) ~Homogeneity of variance, 方差齐性
+ c7 j7 d9 Q7 ~5 e) p* e: a" l3 uHomogeneity test, 齐性检验
7 Z, Z8 ?& r0 Z5 xHuber M-estimators, 休伯M估计量
& ^; k( y2 i: B* [& ]7 V. V# ~3 uHyperbola, 双曲线
9 g8 N" w9 M8 I) v$ |" J" CHypothesis testing, 假设检验) b$ `4 z) L- w" C* }
Hypothetical universe, 假设总体
! x5 J) D& K; P, J. QImpossible event, 不可能事件
2 ` }0 \8 n* K* \2 R2 D) u" oIndependence, 独立性/ E. n. X7 v, C6 W: @/ M3 q
Independent variable, 自变量
/ s( {6 n* Y6 X+ f" y ]8 _+ EIndex, 指标/指数
+ n7 t% H. O6 p3 J. l: N$ oIndirect standardization, 间接标准化法
# K! a" j9 W5 h1 k+ \" a$ rIndividual, 个体
' F; t: X% m6 j) J5 g& B; {' j( v" {Inference band, 推断带 O1 Q! B$ E0 V
Infinite population, 无限总体$ q0 o; Z ^9 }
Infinitely great, 无穷大
8 i& [# T& e3 L! X3 _Infinitely small, 无穷小
" V: l. j% f* T U. s8 @6 P6 {. YInfluence curve, 影响曲线: i. [5 r$ E1 k: ?. R
Information capacity, 信息容量
3 k7 d0 G, }% s/ U8 yInitial condition, 初始条件
$ O( O& ~/ ~3 f/ zInitial estimate, 初始估计值; @. y$ S' }; K: Y, h- i( \- M. ^
Initial level, 最初水平
. e& X v, V* t7 R' m5 D; H6 jInteraction, 交互作用% y, }) A6 }7 M/ a
Interaction terms, 交互作用项- N& m* L) u* }* v7 x& J9 ]
Intercept, 截距
: n1 c1 v3 a: d0 e1 q- s$ ]Interpolation, 内插法- B5 r* d& d$ k ]# r& T; x
Interquartile range, 四分位距9 D) u! N2 E* T/ B# E0 _/ p
Interval estimation, 区间估计. d2 N% ~6 u6 v' y
Intervals of equal probability, 等概率区间3 S$ j) ]8 O9 {( F* H) }# ]
Intrinsic curvature, 固有曲率
% |8 ^: a8 C4 _& `" C2 i; fInvariance, 不变性
9 D) S6 s; v$ k; Y/ `, Y0 HInverse matrix, 逆矩阵
0 O" o4 G( m: }+ LInverse probability, 逆概率
8 t3 c3 a! ^- X% V3 bInverse sine transformation, 反正弦变换
2 I5 C: f0 a' AIteration, 迭代 8 \ J9 G8 u( q# S* ?0 e$ ?7 ?
Jacobian determinant, 雅可比行列式
( r; c# e; W2 q% O1 _0 s8 hJoint distribution function, 分布函数8 @/ g# v; T/ y& r4 [9 c! o
Joint probability, 联合概率2 W/ v# D* [% ]- I
Joint probability distribution, 联合概率分布
" z- n2 u: j. B; N8 q5 L$ ]K means method, 逐步聚类法" t% g) s5 @- U- H
Kaplan-Meier, 评估事件的时间长度
5 T# Q/ a& x; o4 J6 y# _" I. ~Kaplan-Merier chart, Kaplan-Merier图
( D6 @, K& j2 a% d2 P2 I9 W6 YKendall's rank correlation, Kendall等级相关6 X" V( q. }; b7 a$ Z9 {) t
Kinetic, 动力学
, K1 @: [# l c o" G; WKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
% G! L- _ O4 g4 m, uKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验1 P" X- W& A* {% n+ @: K- @' Q3 V9 [
Kurtosis, 峰度! z/ |& |% U7 B& F/ T$ o
Lack of fit, 失拟, m+ V9 z$ w+ U4 E) }# h; A
Ladder of powers, 幂阶梯 G, J. v; E% p' R
Lag, 滞后' f: k K+ I) i/ [8 l/ b2 e% o
Large sample, 大样本
! r2 O- `& s H' s1 x' _- MLarge sample test, 大样本检验
" Y# n$ R; ?1 y$ E2 T5 F: eLatin square, 拉丁方
$ y+ N1 {% }0 ^1 w9 ZLatin square design, 拉丁方设计
0 G( e6 R' _3 K5 g; JLeakage, 泄漏
6 Z" A7 U# O! ^! @7 B# Q8 oLeast favorable configuration, 最不利构形& B+ B# ?$ v) _: M2 A
Least favorable distribution, 最不利分布
. Z3 g7 K) c8 R) I0 N9 Y1 X. uLeast significant difference, 最小显著差法
/ U9 G+ H9 f8 D3 `Least square method, 最小二乘法& M, @6 o/ N4 R2 B' B
Least-absolute-residuals estimates, 最小绝对残差估计
6 N# {0 a) B W9 \Least-absolute-residuals fit, 最小绝对残差拟合! H' y! K* t5 A ~* g1 @# B" o" ?
Least-absolute-residuals line, 最小绝对残差线1 J3 t8 i* R' M5 D
Legend, 图例' A4 z) O2 B% \$ {
L-estimator, L估计量
! \, l: W: L* M3 p, K F) EL-estimator of location, 位置L估计量- l% l9 |6 B7 h* V; Q! m
L-estimator of scale, 尺度L估计量! v" }- _6 V0 k' f* D
Level, 水平& `+ j. e/ [! @& T
Life expectance, 预期期望寿命5 M2 z! a# r2 z% b' v
Life table, 寿命表
* K# F( \7 s6 Z% d3 I. q( [# GLife table method, 生命表法) j9 W- f, B/ K
Light-tailed distribution, 轻尾分布; i. y3 p- {. s5 d# z
Likelihood function, 似然函数
6 y1 b% U" \" p) |+ G* ]Likelihood ratio, 似然比2 R! y( f/ `7 n, g% s! E1 G8 r
line graph, 线图
/ _; `* u8 i4 F O2 V* m! s L0 ELinear correlation, 直线相关& l2 T4 ]5 Q& \6 F
Linear equation, 线性方程
2 K5 G; d3 x7 P2 s. jLinear programming, 线性规划
) ]" {7 G! p& h$ n" WLinear regression, 直线回归
" h- m9 G5 k# q" z+ d+ bLinear Regression, 线性回归
' O! b) T; R$ G3 dLinear trend, 线性趋势% J7 d3 ~7 Z+ i- K% P) p5 X
Loading, 载荷 4 M W- r3 F; W, F( ]2 g, H
Location and scale equivariance, 位置尺度同变性
; X1 G4 P3 L! D7 G) X8 _7 ]Location equivariance, 位置同变性
$ S9 }. e# b- H1 {& E' FLocation invariance, 位置不变性
1 q1 w1 V5 Z2 J: @ N0 _Location scale family, 位置尺度族6 t# L- w" d0 K) Y% \
Log rank test, 时序检验
1 b4 H: s3 P6 xLogarithmic curve, 对数曲线4 d% O) A2 G7 I, N
Logarithmic normal distribution, 对数正态分布2 N' f# A; M! f7 y0 t
Logarithmic scale, 对数尺度. F. q5 f, d& @$ b
Logarithmic transformation, 对数变换& H' u/ R% D& ]" C* V) D; I5 Y7 Y
Logic check, 逻辑检查
* G0 s- T$ d' A& W% XLogistic distribution, 逻辑斯特分布( ~8 n P1 r1 d. q" L
Logit transformation, Logit转换
0 S: h& V: }" J8 b8 }LOGLINEAR, 多维列联表通用模型 , m) A5 ?; J0 [; I- W4 {) G
Lognormal distribution, 对数正态分布
6 H: B0 q& Y6 f5 ALost function, 损失函数
% }9 B$ e7 d. _9 C1 SLow correlation, 低度相关
! m) W: G/ P3 n/ oLower limit, 下限
( Y1 @1 X( E' V6 a; z1 E1 mLowest-attained variance, 最小可达方差
* R/ K' `9 B- q, zLSD, 最小显著差法的简称& g6 o+ r& C, ~+ `
Lurking variable, 潜在变量
; z; n# A) g0 }9 t+ [Main effect, 主效应7 |% [+ {0 W& X8 S2 x
Major heading, 主辞标目% Y$ y i* T; A4 h7 v+ C
Marginal density function, 边缘密度函数
5 E1 `6 q) N! c' e0 \Marginal probability, 边缘概率
( A5 a) O% q1 ~* k5 _: o# R" CMarginal probability distribution, 边缘概率分布
! w! A( A( d J# tMatched data, 配对资料
3 c$ L8 P% H9 B( ]5 A* qMatched distribution, 匹配过分布
}* Q; A$ M; W# V$ v' OMatching of distribution, 分布的匹配
+ X: m7 p s7 r( L) uMatching of transformation, 变换的匹配# J* H* o0 u( U8 z7 |$ W4 x* t. B
Mathematical expectation, 数学期望 T& ~$ | I0 E
Mathematical model, 数学模型& _& g, {% U4 u' {
Maximum L-estimator, 极大极小L 估计量3 k" q2 C( [/ o' V
Maximum likelihood method, 最大似然法
. C8 ?% b6 x+ Z( _ N7 d+ n4 ZMean, 均数( p3 V' S: }# Z ~' g" r
Mean squares between groups, 组间均方0 D4 v+ C5 C# }" J" ]- z5 y
Mean squares within group, 组内均方# b# u6 Q2 l" d* B3 Y- `0 o
Means (Compare means), 均值-均值比较0 o" Y, V; j& y# C7 ]; C: R/ H
Median, 中位数
0 [7 i, }+ o; ?% a4 `- O: A* mMedian effective dose, 半数效量
! \" L% }9 T E# yMedian lethal dose, 半数致死量
4 e5 `$ B- E9 V4 n2 yMedian polish, 中位数平滑
$ K/ U2 V3 L- C- c; z. h( k# I' JMedian test, 中位数检验3 c) M9 }- m/ S, D* S; l
Minimal sufficient statistic, 最小充分统计量3 q* h2 t2 }) x, I) L! t
Minimum distance estimation, 最小距离估计& c' K. Y/ N( v: c: _9 h
Minimum effective dose, 最小有效量
5 @8 S8 Q+ {6 [: T- bMinimum lethal dose, 最小致死量
# k. c5 i. m, S2 JMinimum variance estimator, 最小方差估计量6 E9 N2 w! ~7 ~* F2 x) {
MINITAB, 统计软件包
$ c0 @; z3 d5 m9 b& lMinor heading, 宾词标目# a- j! K* m+ J0 g
Missing data, 缺失值
4 J4 Y3 r5 a, U6 J( A% q6 pModel specification, 模型的确定
% }- x% B" m' N. m( [* LModeling Statistics , 模型统计
9 ~: D- R7 E3 ?' [7 c/ KModels for outliers, 离群值模型
, p) W) ], J4 `Modifying the model, 模型的修正6 E, p% o# t+ i) G
Modulus of continuity, 连续性模) y7 C) j8 Q/ E* i* q5 T
Morbidity, 发病率 " @( `0 V& k0 `: G8 d$ P- G
Most favorable configuration, 最有利构形
. [ z/ y0 Q) Q+ [Multidimensional Scaling (ASCAL), 多维尺度/多维标度
D, X- i" y2 w M' V% K- O5 TMultinomial Logistic Regression , 多项逻辑斯蒂回归5 \" D! q) I1 U r, n0 O4 ~
Multiple comparison, 多重比较& A# _$ M% {' q0 [7 T0 _
Multiple correlation , 复相关; i7 N# ~. h- D2 f
Multiple covariance, 多元协方差- o! A% P7 d$ B# ?* E
Multiple linear regression, 多元线性回归
. O P0 q7 d% X$ B! VMultiple response , 多重选项2 M! y) o/ ^8 _' ~$ W7 A$ ^
Multiple solutions, 多解/ ^ K, J! o8 z/ }
Multiplication theorem, 乘法定理
( D9 F. o2 p' I/ CMultiresponse, 多元响应5 H9 E; |! y" W
Multi-stage sampling, 多阶段抽样
& R" J i x1 v p# ?4 \6 z3 z7 j6 @Multivariate T distribution, 多元T分布
$ G* V6 a. z! c5 G& ?. BMutual exclusive, 互不相容4 }& X/ R( y% J# R; H9 f
Mutual independence, 互相独立
, Z+ a! l* d; kNatural boundary, 自然边界8 [* d. J$ c' A* E8 Z/ G& J
Natural dead, 自然死亡 ]1 `9 \9 Y& m9 @ Y! p! B0 F; s
Natural zero, 自然零
1 P' K: w# H5 x ]. e! C( k4 W7 tNegative correlation, 负相关. f. H) ~1 W( j& k
Negative linear correlation, 负线性相关
4 i! |0 H5 c) R3 C: U8 ?* V QNegatively skewed, 负偏0 o0 i3 n; g$ h" D$ V
Newman-Keuls method, q检验 X" ?1 k7 G, p4 w4 | j' d
NK method, q检验
' V% t) h: a" ^; L/ tNo statistical significance, 无统计意义- M. N1 K0 e6 E- @2 V- y+ e
Nominal variable, 名义变量
% G& t% S6 s8 P$ \Nonconstancy of variability, 变异的非定常性) N' P( o3 ?% R4 X$ a
Nonlinear regression, 非线性相关3 [/ Y1 a l3 {# O$ |: U
Nonparametric statistics, 非参数统计* ]* t* a8 c& M; k, H% D% \( J% {
Nonparametric test, 非参数检验
; [+ n; _+ k7 Q) z; tNonparametric tests, 非参数检验
" C/ ^! G7 U* J# R; {7 A" u# z( oNormal deviate, 正态离差
4 m* _6 \4 R* p/ M7 _9 U9 {; `, J) `Normal distribution, 正态分布5 Q. E S! [7 @; \7 h7 l7 {
Normal equation, 正规方程组
% P9 a2 g) ?, ~. U. @0 b$ o& JNormal ranges, 正常范围. g. u' R+ ^+ [( I# F3 y" M0 c
Normal value, 正常值6 b/ D3 d9 y/ g" F" `
Nuisance parameter, 多余参数/讨厌参数
- }+ \8 d0 [* f9 x, f9 d, KNull hypothesis, 无效假设 , S/ n( o/ M( n! A
Numerical variable, 数值变量( H f2 O: t) w
Objective function, 目标函数$ P0 I) D( h" S/ a) Z) X8 r
Observation unit, 观察单位0 S( X7 A4 n% J' ~
Observed value, 观察值
, b" J0 w: v' g# hOne sided test, 单侧检验) X, [+ t; O$ {
One-way analysis of variance, 单因素方差分析
/ @% v: x, G1 M% J$ a: GOneway ANOVA , 单因素方差分析
x; K5 `& M1 x/ b' G- rOpen sequential trial, 开放型序贯设计! q- j, n4 r: S$ `6 s! Q) l
Optrim, 优切尾% R, ]4 K5 i* ?* n& k$ ~0 H
Optrim efficiency, 优切尾效率
1 _1 s9 j7 a" d* @Order statistics, 顺序统计量# T, C* F/ [# |% A* ~1 O
Ordered categories, 有序分类
- ^! d6 g6 Q8 }) I; NOrdinal logistic regression , 序数逻辑斯蒂回归+ g3 m" M+ U) i. E# j, y
Ordinal variable, 有序变量; D8 \' Z) j" u) U3 |+ [
Orthogonal basis, 正交基. e+ U6 S/ R) S q+ w* O
Orthogonal design, 正交试验设计
0 g9 ~. J% a) j- d5 U. e6 ~Orthogonality conditions, 正交条件" L, f9 }, s; d2 o2 Q$ b6 A
ORTHOPLAN, 正交设计
2 R0 D6 @3 H& |5 o: G6 KOutlier cutoffs, 离群值截断点" A A P% e5 H, R
Outliers, 极端值
2 S" {2 W4 g4 J. c' ~1 g) W9 yOVERALS , 多组变量的非线性正规相关
+ L y4 N4 _3 G j8 g a- MOvershoot, 迭代过度
0 e+ H: s$ T. i7 M0 nPaired design, 配对设计
( ?& G" t* m1 t% }' `/ x: e3 b p) KPaired sample, 配对样本
2 w& {: E/ ]; J5 E* M$ |+ PPairwise slopes, 成对斜率% r9 ~$ ~7 v% w P
Parabola, 抛物线$ ?. i1 g8 y. M* j
Parallel tests, 平行试验
' K. y8 q9 `/ v9 A4 U4 fParameter, 参数
9 e: w2 O! X+ K0 Z! W) g+ KParametric statistics, 参数统计! h9 W4 b1 Y; P) s' D. J. L1 z7 q" T
Parametric test, 参数检验
- N! i$ i, Y4 D8 n+ |) IPartial correlation, 偏相关
& b, G! `1 I( BPartial regression, 偏回归
! t4 C" K% ~0 U5 t. D8 UPartial sorting, 偏排序
3 N# p! H. l! N! YPartials residuals, 偏残差
. I. z) @& Z+ U b3 L0 N: m! m6 {Pattern, 模式
: `6 h W% L% \Pearson curves, 皮尔逊曲线% Y7 o% c: i& K
Peeling, 退层
1 f; ?/ r2 o I) q+ Q! h& Y6 dPercent bar graph, 百分条形图
( j9 |. j8 D; i, ]. r1 sPercentage, 百分比$ `/ I. Q) H5 a" U; r) v0 s
Percentile, 百分位数
6 e3 u/ w6 C" S( e6 c2 j* hPercentile curves, 百分位曲线
) ~( o6 U; u( v' ?Periodicity, 周期性
, H) H0 P( M5 @' {Permutation, 排列. |' m9 a/ s- V- f! L) X& c
P-estimator, P估计量! K) J, v H# V! [0 s! S- L6 g
Pie graph, 饼图
* h8 T: y2 @) FPitman estimator, 皮特曼估计量
0 T0 Z. R5 x3 r S5 U3 ?Pivot, 枢轴量8 M# d# G) r. o% ]
Planar, 平坦
2 N( F8 x8 \( v9 C! G+ s7 S) JPlanar assumption, 平面的假设
6 ^6 F0 Q7 p9 ]4 S+ d) z# |PLANCARDS, 生成试验的计划卡
) V" b* H, C# j5 EPoint estimation, 点估计% c: P L* E( j
Poisson distribution, 泊松分布
* a6 e' N5 j$ G6 M) TPolishing, 平滑
# y u! O; S0 z. I8 L* t9 s; jPolled standard deviation, 合并标准差 _+ R2 W G) O( f
Polled variance, 合并方差: z. j# L3 Z8 | \: U6 U" w/ }9 @9 [$ E
Polygon, 多边图
: m0 a, C% R8 D" t jPolynomial, 多项式
9 M5 ^: ]' }/ y4 iPolynomial curve, 多项式曲线) g9 _9 Q4 D$ v- S$ P& L
Population, 总体
4 ~' t( v$ H8 k3 M( j8 r$ u0 M1 lPopulation attributable risk, 人群归因危险度" G5 ^ u/ W1 Z1 f& O2 n- x- I0 V
Positive correlation, 正相关
- R8 `: U& V" l5 I: ZPositively skewed, 正偏
! e' X( J9 p3 ^1 H" z: L7 SPosterior distribution, 后验分布& p3 a; y' W% {
Power of a test, 检验效能
) b$ j4 L" K. t& G- Z# o; f8 tPrecision, 精密度
- ^$ I, q3 ?9 ZPredicted value, 预测值
# m9 _% K/ S' ]% SPreliminary analysis, 预备性分析
) W' g+ X, G$ mPrincipal component analysis, 主成分分析
3 m( U4 I9 ~7 P6 o8 WPrior distribution, 先验分布' U. n6 b. X3 u" Y5 l
Prior probability, 先验概率
" @% J# E, T7 {2 M( }3 x' AProbabilistic model, 概率模型3 R) W. G6 P, M9 ]* g$ H0 y
probability, 概率
6 y+ T5 R* k$ R& }: J4 TProbability density, 概率密度
6 O8 L$ K8 J2 E8 UProduct moment, 乘积矩/协方差* d6 K; L$ d8 O* S- I& Q9 w
Profile trace, 截面迹图/ G1 L' u# [7 j; [4 ?' h' B& R, Q
Proportion, 比/构成比
" ^( y: y: ]6 ^3 [Proportion allocation in stratified random sampling, 按比例分层随机抽样: U% }3 g( x9 P! L. s
Proportionate, 成比例
5 ]! x y, U3 L8 S7 L# fProportionate sub-class numbers, 成比例次级组含量, e1 F, m5 s% w4 k, e; J
Prospective study, 前瞻性调查
4 S8 f1 X) x, m0 a& A/ h% `& r- ?Proximities, 亲近性 : R% m+ [/ {8 Q* V# k- o, q1 k
Pseudo F test, 近似F检验
9 c" X$ I+ U* c9 K0 WPseudo model, 近似模型$ C2 O* u ]4 S9 [, m7 `
Pseudosigma, 伪标准差$ R6 f. l' s$ c" f' ~+ L$ V) a
Purposive sampling, 有目的抽样
/ |) M/ j9 Z: m( v0 n* E; K4 WQR decomposition, QR分解
. t# |( e; K/ K3 ?Quadratic approximation, 二次近似, h' v7 I9 p4 Z9 r3 {
Qualitative classification, 属性分类
. I8 f2 l' n& h; S# r0 J+ JQualitative method, 定性方法% ~$ X }0 h$ [
Quantile-quantile plot, 分位数-分位数图/Q-Q图
4 ^' P8 m6 c2 W7 WQuantitative analysis, 定量分析
$ A7 Q' k% i; dQuartile, 四分位数- W0 c9 `+ q: q. C0 J
Quick Cluster, 快速聚类
( j9 W' A" e3 x1 QRadix sort, 基数排序
( {' C2 @7 U* S. o9 URandom allocation, 随机化分组
, ^( P6 i6 `4 I+ vRandom blocks design, 随机区组设计
+ F$ |% T& i4 q8 ~9 H$ H# ZRandom event, 随机事件 U7 R+ X% [. \9 o( p
Randomization, 随机化1 m/ n! I% I1 N, t" g2 ]
Range, 极差/全距! S4 L2 v5 ~7 I
Rank correlation, 等级相关
, O. C3 K2 \+ a) ]1 d4 e7 y. DRank sum test, 秩和检验% E8 w. ?( h7 Y A7 E& v0 q
Rank test, 秩检验
, v. q9 @( y9 g7 z7 X: y; i. `Ranked data, 等级资料
( f4 |) Q4 _2 E' o; n% o" s+ U7 _Rate, 比率! B. E4 ]0 d" F
Ratio, 比例+ S! D6 e2 R% X$ D
Raw data, 原始资料
3 v9 f2 x7 t# M1 }+ N, T2 cRaw residual, 原始残差$ \. {% z! ?+ v' I; F
Rayleigh's test, 雷氏检验) g+ z I7 a, ~+ s+ h0 _% l, u
Rayleigh's Z, 雷氏Z值 & F1 u) P* _& P) s. j
Reciprocal, 倒数: v' u2 m' r% F- a& Z7 {& B6 l
Reciprocal transformation, 倒数变换) }6 H- V; |4 Y/ q7 |
Recording, 记录7 \! b1 z/ c4 ~1 P: c7 n7 J& P
Redescending estimators, 回降估计量# G: Z2 Q/ a5 t# L# Y4 i8 i! O
Reducing dimensions, 降维
1 P) F, b9 [7 O5 U) YRe-expression, 重新表达
; \$ o! m' q% p' x8 X, \ bReference set, 标准组- |7 {8 L3 V7 N+ e- [5 z" g
Region of acceptance, 接受域) @' }: x/ W7 U; }4 Y3 @# _
Regression coefficient, 回归系数
. }9 s' [$ C8 h; `0 sRegression sum of square, 回归平方和
# Y( q. z$ \, H/ xRejection point, 拒绝点7 Q+ W- q! C3 [+ m5 {9 h+ m! b9 @8 ?
Relative dispersion, 相对离散度
" q6 Y( ]5 L8 F+ V3 b5 `Relative number, 相对数
, J. p+ B, \( P8 S9 OReliability, 可靠性! Y! o; A2 N, U$ I3 a0 D! o
Reparametrization, 重新设置参数+ y+ J% ?% I& a
Replication, 重复0 {: m7 ]+ N5 g0 c; v( q
Report Summaries, 报告摘要
/ A6 o' m8 h' i1 ^' AResidual sum of square, 剩余平方和' W3 b) H" g: s4 z0 G
Resistance, 耐抗性, @9 o# m) {' `; k& z# T
Resistant line, 耐抗线
9 I2 j" c$ |! }) O/ V: y3 g9 KResistant technique, 耐抗技术
8 P5 ~" G8 j% U! z; s- cR-estimator of location, 位置R估计量
W. U' D* l/ [7 j* FR-estimator of scale, 尺度R估计量
+ @3 ^7 q5 a( w( m- I) ARetrospective study, 回顾性调查& t7 r' |' x) ]8 Z# b- {- w" a
Ridge trace, 岭迹
/ N* _5 ~+ u) \2 @Ridit analysis, Ridit分析
+ S, n% u/ H1 U# |+ Q( z2 ARotation, 旋转
1 } ]* ?1 c; g9 w6 i6 XRounding, 舍入
- \3 V% u. q+ ^7 iRow, 行* e- C2 n) ~* ~3 ]; b
Row effects, 行效应0 j4 `# x2 D8 O3 D; r" z
Row factor, 行因素0 L3 _( k3 y. G3 f3 v+ M" a
RXC table, RXC表0 X- l- ~* S; Z ^9 d5 H' w; `+ ?
Sample, 样本' @: d% e8 M" @' w6 x% {
Sample regression coefficient, 样本回归系数' p% O4 o& x1 w+ X9 }* P. r7 X
Sample size, 样本量
, p$ l& e6 e- g3 p2 F/ @Sample standard deviation, 样本标准差3 s4 G# W7 Y: K, j Y* { J$ [) k
Sampling error, 抽样误差
" K6 a; \2 \( Q' HSAS(Statistical analysis system ), SAS统计软件包
) z" o3 P6 r, H% GScale, 尺度/量表$ ?7 ~4 q1 x+ G
Scatter diagram, 散点图: }! M* t8 U! w3 N' m3 C. N+ K# n, F
Schematic plot, 示意图/简图
8 |4 y0 E: f. q" yScore test, 计分检验
/ n3 e% p. N/ \) O: ?) f o3 K! FScreening, 筛检9 \$ }' X3 I+ T1 `* y5 e: ?. I
SEASON, 季节分析
" Q, J4 R. `/ e6 k1 V2 _Second derivative, 二阶导数; v% n% l7 A. l) u. C* P' p7 m1 ~
Second principal component, 第二主成分& W& f; @3 Q7 |2 X7 s
SEM (Structural equation modeling), 结构化方程模型
. f( ^! t7 Z ~* t; gSemi-logarithmic graph, 半对数图: i4 t- ?& |6 ` l* R
Semi-logarithmic paper, 半对数格纸: o$ S8 j; p3 B" ^
Sensitivity curve, 敏感度曲线! t+ y2 Z$ c8 G9 X$ X
Sequential analysis, 贯序分析
) e( {$ h h* S: {2 C1 QSequential data set, 顺序数据集
2 Y- h( M& @$ A7 ^9 w' n1 H) HSequential design, 贯序设计5 J8 j6 ?1 P" C& l' Q3 S% L7 f
Sequential method, 贯序法
, @2 O# v% s! l% zSequential test, 贯序检验法' t& Q: D- B6 _4 R( n( E
Serial tests, 系列试验3 u, u. I+ e- ^0 @8 C; F5 {/ j
Short-cut method, 简捷法 5 `9 F# F% S- b+ J, ]
Sigmoid curve, S形曲线
0 u' g! `, t4 B9 o$ USign function, 正负号函数8 O. u; a5 q2 }; z1 m; u. _
Sign test, 符号检验
/ s* }* ]5 z- G9 c3 c' \4 pSigned rank, 符号秩 J3 e8 ^- U- ?
Significance test, 显著性检验; s# C" h- r. c2 j! t: Z
Significant figure, 有效数字
/ I) a! I5 L% Z$ J7 MSimple cluster sampling, 简单整群抽样
& `7 z+ |4 T# f1 L' T. ?Simple correlation, 简单相关 O8 u/ ?; A4 c- W, M4 a/ k2 c
Simple random sampling, 简单随机抽样
1 t4 o, j1 T0 N% R1 ]Simple regression, 简单回归
. x ?( Z, }( D6 t. Q- @2 ]simple table, 简单表/ m x- w" p* ~0 I" x5 u# O
Sine estimator, 正弦估计量# g7 g2 X8 m! z, K) Y' t1 I0 g( j
Single-valued estimate, 单值估计1 i; Z7 w1 C1 Y4 R6 O
Singular matrix, 奇异矩阵: ^; L$ O, q; U9 c5 C
Skewed distribution, 偏斜分布5 q, C: {" x" J* h9 Y9 V, Y6 W
Skewness, 偏度3 B- ~4 r& a- W
Slash distribution, 斜线分布" J K5 K* x$ T/ R
Slope, 斜率
3 k) ?6 v7 s, K- u3 o" ]Smirnov test, 斯米尔诺夫检验
9 C; |8 H5 e5 s$ B& OSource of variation, 变异来源; U* g' P* E7 K% }
Spearman rank correlation, 斯皮尔曼等级相关; I% _, S/ }: X. z2 |* G4 B' `0 A) h
Specific factor, 特殊因子
, A1 f5 p# B5 p& b& A) vSpecific factor variance, 特殊因子方差" h4 T- V3 E3 d& m
Spectra , 频谱
/ z/ L3 k4 W) T8 sSpherical distribution, 球型正态分布* U. t2 s6 ^6 A$ b* t
Spread, 展布: h( ~; ]1 d6 D+ C
SPSS(Statistical package for the social science), SPSS统计软件包
: U# h t$ l& ], Z! m6 I' kSpurious correlation, 假性相关
8 q% X# y4 A4 O3 C! jSquare root transformation, 平方根变换; ]; T7 x1 }% j
Stabilizing variance, 稳定方差
# S4 ^: `3 j1 Z7 L7 Y# D3 i, vStandard deviation, 标准差
+ P7 Z( X( B0 Y, e% BStandard error, 标准误* ]6 g7 P8 ]$ o, d9 w' T9 Q
Standard error of difference, 差别的标准误1 v2 z. z0 t2 j9 q( [& x
Standard error of estimate, 标准估计误差
: [, m0 [% ^" \* f- h% {# A F0 eStandard error of rate, 率的标准误
: N& r. Z% \& M L* I* y# AStandard normal distribution, 标准正态分布0 |9 E0 s) w l6 A, u% j
Standardization, 标准化
/ l6 W8 _* M& N- N4 rStarting value, 起始值6 T' Z/ I5 p6 O2 i9 N
Statistic, 统计量2 A/ i( h+ D) \! R6 x
Statistical control, 统计控制
, |+ ?9 K0 |1 U' c( M: xStatistical graph, 统计图
6 c. d" f7 k7 O" K: C6 TStatistical inference, 统计推断, E `2 b8 N$ ^
Statistical table, 统计表
2 E" `, H& G: R- cSteepest descent, 最速下降法5 }# s5 Y. f9 g, o; H9 F
Stem and leaf display, 茎叶图
/ _6 @$ }( l( t& e9 g r& l9 q- HStep factor, 步长因子
8 L, h/ m% ?- T6 FStepwise regression, 逐步回归
$ Z# N# t3 E) g4 P: ~1 CStorage, 存# s0 f, H9 Q, Q2 C# J
Strata, 层（复数）5 j6 Y+ }$ B& ~) P3 g! ~2 U! E
Stratified sampling, 分层抽样4 ]) v( B, a3 D& e- m( U* d0 G
Stratified sampling, 分层抽样) n$ s& y, w q
Strength, 强度2 x* F- u0 c2 \: l9 J* [7 C/ A
Stringency, 严密性; @4 i2 t) h) a* o0 @
Structural relationship, 结构关系( S9 J) a9 y# E% E3 U& m$ k
Studentized residual, 学生化残差/t化残差
6 ]3 ~% I2 ~. U9 p) _/ x% h$ gSub-class numbers, 次级组含量
- y3 W7 R5 U5 {& g# X2 {Subdividing, 分割3 Z& m8 g4 A7 V v6 N
Sufficient statistic, 充分统计量4 c0 l0 T4 I* i" j# a6 I8 X) @
Sum of products, 积和$ B% G, @; K- f j
Sum of squares, 离差平方和. M: |$ y! e0 `7 ?4 h
Sum of squares about regression, 回归平方和
, N! F- E/ a: C4 a) CSum of squares between groups, 组间平方和
/ a& O: g8 A" _- w5 ]Sum of squares of partial regression, 偏回归平方和* F. a! V0 z \: d1 T; o; g
Sure event, 必然事件3 ~9 M5 L5 c# m. z) L; ~
Survey, 调查8 a, w4 Y3 {, G* a. G( C1 \6 o* j
Survival, 生存分析$ u& ?5 l* y' L6 k. j
Survival rate, 生存率5 q0 L* E- B0 t2 a5 f4 Y2 p
Suspended root gram, 悬吊根图) Y1 Q! N; @% a/ {: N" D6 J
Symmetry, 对称
0 u; M6 n8 E& y! Q* a, pSystematic error, 系统误差 r/ O) x; Y2 g, Z
Systematic sampling, 系统抽样- k& s& D' x, X$ e* c m. v
Tags, 标签3 `7 b2 b8 e& F
Tail area, 尾部面积- a# J+ _% a5 s3 s+ R% {' n1 Y
Tail length, 尾长8 G D* `0 P0 l" ^; [
Tail weight, 尾重
, Q" I6 }' o2 Z3 ~Tangent line, 切线
9 I q3 e% q# O* G) `" @" ?Target distribution, 目标分布
) F. j# f. r0 H7 Z/ lTaylor series, 泰勒级数
1 ?3 |: S" f6 F( `5 V/ P' BTendency of dispersion, 离散趋势
U# }9 L8 Z3 y# D* e! DTesting of hypotheses, 假设检验
' { g/ S+ C7 MTheoretical frequency, 理论频数
% ~1 P+ c9 {2 t+ u- GTime series, 时间序列
8 h/ j, y! b) k3 M0 u2 Y& K. eTolerance interval, 容忍区间3 c' A8 H! j& }/ u+ k$ N/ {
Tolerance lower limit, 容忍下限
|1 `7 G% x1 z5 }$ \Tolerance upper limit, 容忍上限0 P- c2 F. H7 `# S
Torsion, 扰率 n* d: i& l# y& L
Total sum of square, 总平方和( E% s" _9 t' T7 M
Total variation, 总变异
# d0 l6 Y0 W% B. WTransformation, 转换 y$ y4 {! P7 m
Treatment, 处理
8 |; P9 X! S+ k8 H2 @Trend, 趋势
% x' W% R* R4 g K2 C, XTrend of percentage, 百分比趋势 W: w) N+ ~" J$ M
Trial, 试验0 T O! z% u% z! n- s" Y" n6 F
Trial and error method, 试错法4 B' ]4 L0 n6 _+ T# a( z0 c
Tuning constant, 细调常数9 e$ ~8 c. K0 I' F2 h: c: w
Two sided test, 双向检验
1 o. m4 i: s- H n6 B$ G4 nTwo-stage least squares, 二阶最小平方
5 T8 W. b: }3 rTwo-stage sampling, 二阶段抽样/ S' d; ]. C9 [* K, C, p' g
Two-tailed test, 双侧检验; E) \- a. w. }+ w( L, d
Two-way analysis of variance, 双因素方差分析
0 o3 f: M m: _( d1 aTwo-way table, 双向表" X5 V% Q$ j0 `' ^1 d+ x" \' h5 M5 u$ z
Type I error, 一类错误/α错误% W6 @1 u0 D( u
Type II error, 二类错误/β错误: ^2 B. [+ ~) H! a8 `0 T
UMVU, 方差一致最小无偏估计简称 I4 v. \: u. [1 T4 l
Unbiased estimate, 无偏估计1 _$ @1 ~6 e7 W9 r- W* c3 c7 I3 s
Unconstrained nonlinear regression , 无约束非线性回归
- c1 p: I+ ~% z, O: `; eUnequal subclass number, 不等次级组含量
2 \( v, J/ r! L3 O6 A/ J( TUngrouped data, 不分组资料7 D& b$ X# {( v) G1 S; V; |7 X
Uniform coordinate, 均匀坐标1 ^: ~' O+ o: e' v) d! u
Uniform distribution, 均匀分布
, G p$ `" G( K) O1 S# p* K( NUniformly minimum variance unbiased estimate, 方差一致最小无偏估计, W) R! v! T2 i7 l0 I
Unit, 单元: P0 _1 N2 O) V9 a/ Q
Unordered categories, 无序分类$ a5 ?+ P2 N i7 k% s9 q
Upper limit, 上限& R9 O3 p1 }3 Z2 S
Upward rank, 升秩" r; V0 r% K$ b4 G, g C( X
Vague concept, 模糊概念8 F6 c4 R) x, t3 M
Validity, 有效性
8 I; Q. C* B* X% K* {VARCOMP (Variance component estimation), 方差元素估计
2 I* \4 j& @9 bVariability, 变异性! ^8 [& |1 H" \7 {3 n( @
Variable, 变量5 |8 _" G) m( R H$ c9 u9 v5 I
Variance, 方差
% }7 p# i# w' z& g7 S( m1 rVariation, 变异" ?. _4 _+ U% i
Varimax orthogonal rotation, 方差最大正交旋转
- J M( E6 m2 p$ m4 XVolume of distribution, 容积6 H' I, k& Y: Y( p: u, M3 V5 p
W test, W检验% i- E: q2 }" L; ?+ _3 b- K
Weibull distribution, 威布尔分布
; g( F2 k; d) F2 c( V$ G' iWeight, 权数
( i/ t4 x5 y* _- r) b u. @, WWeighted Chi-square test, 加权卡方检验/Cochran检验
4 n- ], J9 T/ w9 i4 i" u" xWeighted linear regression method, 加权直线回归
4 O: h! c( U3 ]2 e- hWeighted mean, 加权平均数
+ Q N' ^, q3 t' w( j/ A3 uWeighted mean square, 加权平均方差
% W# @$ n+ _0 V7 Q q* X& CWeighted sum of square, 加权平方和
! Z# l2 X+ W7 h2 q7 e' [0 EWeighting coefficient, 权重系数: n% e4 s/ |4 B% p3 }/ p
Weighting method, 加权法
+ S& p# n) B- z, rW-estimation, W估计量
6 R& C+ v; _' ~) B% C7 BW-estimation of location, 位置W估计量
) g& U1 x$ k9 t5 E4 t' h. ^( nWidth, 宽度
+ z1 K0 x) `; r* H7 V3 k" v" T$ s$ uWilcoxon paired test, 威斯康星配对法/配对符号秩和检验/ s2 p# G+ f$ l- S/ p
Wild point, 野点/狂点
6 g* O5 Q& O* b. aWild value, 野值/狂值
0 W0 c; s! S- a! W- fWinsorized mean, 缩尾均值: i4 u- _9 g; v, m# F) A
Withdraw, 失访 4 d7 T/ h* v0 |+ P4 i$ `
Youden's index, 尤登指数
- v; U3 u$ |, b; rZ test, Z检验8 r! y5 S c. q. D" U
Zero correlation, 零相关5 K! U# u2 n: S# R z+ U% K
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
