|
|
Absolute deviation, 绝对离差2 p/ C1 a3 ]' @0 I) Y0 }
Absolute number, 绝对数" @3 o5 K6 A% o1 h5 M
Absolute residuals, 绝对残差
3 F/ W* p3 [6 z' ]7 ^Acceleration array, 加速度立体阵! i" f. M. o3 i' g h
Acceleration in an arbitrary direction, 任意方向上的加速度0 v' S8 L. ^ g+ E) _0 U7 @ T; r( @
Acceleration normal, 法向加速度" F M- y7 D1 o1 ?5 Q
Acceleration space dimension, 加速度空间的维数
3 u9 f$ T- }6 z) M% J, T! Z# pAcceleration tangential, 切向加速度- p2 I9 a8 p/ o8 G
Acceleration vector, 加速度向量
% x: I7 |1 f* E' m/ p4 u% T1 o6 sAcceptable hypothesis, 可接受假设' m" {# q- k: \' M0 r: h1 x
Accumulation, 累积2 @* ~% Q! M- n: S# t4 i- T% D A
Accuracy, 准确度, I; D' U w" c+ {7 z; d% \
Actual frequency, 实际频数
8 f7 Z% J& k! F9 `- iAdaptive estimator, 自适应估计量' r1 C# c+ O8 M+ g, N
Addition, 相加
2 b$ p9 b% P( D" J6 X7 X6 P. u/ t+ {( ~/ \Addition theorem, 加法定理9 a! S L9 C& B! v
Additivity, 可加性
, q2 q, M! e2 ?+ L0 O f3 \Adjusted rate, 调整率7 U0 g& w/ C# O" m y9 i+ ~/ H# m& Y
Adjusted value, 校正值
: `: M& X' w4 U8 e+ ]Admissible error, 容许误差
9 F' j7 H! j) u4 LAggregation, 聚集性( G" n) X% D+ r( }& Y3 |3 e: _3 M
Alternative hypothesis, 备择假设; n7 O) z" D' X( ~- {/ ?8 E& F9 |
Among groups, 组间
2 l: {# D2 T, \) _5 q" ^Amounts, 总量& J. \( s4 r0 g2 p
Analysis of correlation, 相关分析2 v4 x5 f' v$ L% z2 z% L
Analysis of covariance, 协方差分析9 n' l% `: s$ d) I
Analysis of regression, 回归分析/ X. w1 y2 W# V$ ~0 L7 N# L. f
Analysis of time series, 时间序列分析
4 q3 ?; k0 J2 R% _; nAnalysis of variance, 方差分析
9 L3 f' @0 M6 D+ |9 g' lAngular transformation, 角转换6 s6 _% V2 C: m( r2 i
ANOVA （analysis of variance）, 方差分析
1 `3 C! C4 d% hANOVA Models, 方差分析模型
* M" z5 s6 ]) O' k3 x" `4 R# yArcing, 弧/弧旋 D/ \0 S. [* l5 _% e% E/ w$ m
Arcsine transformation, 反正弦变换
- [" `/ i, g, \Area under the curve, 曲线面积* O4 v, ^" O; n2 w. Z( t- c0 M
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 0 D3 m4 \) J* i
ARIMA, 季节和非季节性单变量模型的极大似然估计
1 S2 ~8 a# d: p8 Z7 A* ]; uArithmetic grid paper, 算术格纸5 s4 f' `/ _. X& k4 }% ^; F
Arithmetic mean, 算术平均数- s5 q# s/ i- Z3 y# V. g
Arrhenius relation, 艾恩尼斯关系
$ S* g8 n2 Y) `+ a. D V/ r9 \Assessing fit, 拟合的评估, n4 @/ l% ?) \- v7 i
Associative laws, 结合律
5 F* L( Y3 j: ?6 e8 c! Y0 AAsymmetric distribution, 非对称分布% T9 T4 J& _; a$ P6 e3 b* k& m
Asymptotic bias, 渐近偏倚
3 H& R. k1 P4 p; L8 G( @! VAsymptotic efficiency, 渐近效率; K/ c0 Y! @3 Q) `* x. F
Asymptotic variance, 渐近方差
( m, R: U' W& W( t, e' I3 Y$ ]! z, nAttributable risk, 归因危险度
' W# X4 F8 G$ `3 B6 ]) N' P7 RAttribute data, 属性资料
( V) V5 m* {( B1 Y" o4 Y0 RAttribution, 属性
- O& ]( j. C+ N4 Q/ N5 s" RAutocorrelation, 自相关
: P; U4 G* ~/ C& R3 V4 fAutocorrelation of residuals, 残差的自相关
, b& ~4 E3 L4 o4 M5 v1 P; n& RAverage, 平均数
% j6 v* t& I0 w3 t4 f" F/ mAverage confidence interval length, 平均置信区间长度" f7 d# U( V, H
Average growth rate, 平均增长率# b; _/ j6 x8 |0 F3 f! d: M
Bar chart, 条形图6 C3 [! L1 q( d1 ]. h
Bar graph, 条形图
- \5 e6 j2 \1 j/ J- \- @3 \Base period, 基期$ n# C1 A& o, y% C. E/ n( t/ [) b0 P* Z
Bayes' theorem , Bayes定理3 C' C# P( a( ~. }1 d3 k8 I) a7 d
Bell-shaped curve, 钟形曲线- G2 i6 J; V3 ~: Q& W7 p% s" O! B
Bernoulli distribution, 伯努力分布" A* m) Q3 ~4 v, t; D& @9 e
Best-trim estimator, 最好切尾估计量5 ]* W* u; @) m! e0 U
Bias, 偏性 g3 e' `* } n# ]7 Y
Binary logistic regression, 二元逻辑斯蒂回归, M8 n& u ^& m. ?# H0 {
Binomial distribution, 二项分布$ ~4 p l. V9 L" M
Bisquare, 双平方
2 W3 l( \8 T; UBivariate Correlate, 二变量相关 b5 D' m5 N& C* J- a
Bivariate normal distribution, 双变量正态分布
6 f3 `4 Z1 A: c1 c! IBivariate normal population, 双变量正态总体' j- }7 V7 _% P" p
Biweight interval, 双权区间
6 H( w3 n! l6 c$ e+ IBiweight M-estimator, 双权M估计量. H. E/ f8 h2 ^- S7 G& K1 _* b5 x
Block, 区组/配伍组4 G, w3 o7 s, z- x1 Q+ y
BMDP(Biomedical computer programs), BMDP统计软件包6 O% ~) \0 }8 a
Boxplots, 箱线图/箱尾图/ j# L2 G* m6 y% y9 o
Breakdown bound, 崩溃界/崩溃点( d1 R% R/ ~* i: M% M$ {
Canonical correlation, 典型相关
4 g' R9 L S$ W& T' D( jCaption, 纵标目/ D/ i& u- b8 n0 x+ `8 M& }( A; H0 ]
Case-control study, 病例对照研究0 U4 n, J" F, p. V3 C' Y
Categorical variable, 分类变量; {! X6 u- s: M" t6 X" m5 Y
Catenary, 悬链线5 w: k( D0 J- D
Cauchy distribution, 柯西分布; R) C$ r$ G( K/ }3 Q7 p
Cause-and-effect relationship, 因果关系
, M3 U- z' C j9 `/ n9 V- CCell, 单元
/ H6 u- |3 F, \5 h& M. t- U/ DCensoring, 终检: R" T! W; T$ C
Center of symmetry, 对称中心, _ \( l8 z' u$ W: a$ j" @$ w
Centering and scaling, 中心化和定标% o3 Z7 t4 O2 c1 @
Central tendency, 集中趋势% c0 X7 R9 v, I4 |1 s% |6 h
Central value, 中心值
% u4 G& V" ^5 w) ?CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
: @2 \/ ^# [8 U: ZChance, 机遇
o9 b- s$ Z) L1 p) N, hChance error, 随机误差5 J5 `* y Z; S! P! p
Chance variable, 随机变量% Z6 Z7 y3 {8 z5 f
Characteristic equation, 特征方程
! z$ y I. i; d0 ~Characteristic root, 特征根
0 j2 I9 ~" V4 b w! BCharacteristic vector, 特征向量. l# L" a8 D" H- q! N* }( t
Chebshev criterion of fit, 拟合的切比雪夫准则
- c8 `% `) ?; S5 VChernoff faces, 切尔诺夫脸谱图1 n7 v+ W, |. o( E
Chi-square test, 卡方检验/χ2检验2 {4 a* @) p j9 f$ v }4 u/ t+ K
Choleskey decomposition, 乔洛斯基分解
' U/ @$ F8 ~8 R A, c9 |: F; XCircle chart, 圆图 9 ^6 g1 |- `' k% [0 S
Class interval, 组距. Z+ m$ S4 j P! C4 f
Class mid-value, 组中值# n% _# d4 `/ ]# J
Class upper limit, 组上限
& ~+ {6 t Q- h/ j5 g; LClassified variable, 分类变量+ \ D. V; k5 e. J: g, P# h
Cluster analysis, 聚类分析
4 C. V5 Z; r/ M& QCluster sampling, 整群抽样) U2 W( M3 a6 I$ x8 N9 `( \9 c
Code, 代码. j$ k& _4 b+ |5 s, Y
Coded data, 编码数据5 w: Q) e# r3 F9 i( q6 l2 V
Coding, 编码
8 |3 m) P5 H, p) OCoefficient of contingency, 列联系数; _6 Y- Z* i. W& n4 t' ~
Coefficient of determination, 决定系数
3 D; {! U# y( m8 J) l: h- q! ICoefficient of multiple correlation, 多重相关系数: ?- W3 M6 ~8 O+ \# s2 @9 @; Q7 f: e
Coefficient of partial correlation, 偏相关系数
2 k0 ^$ c* \, {* s8 ^4 Q% wCoefficient of production-moment correlation, 积差相关系数% n6 D- p/ H( l9 b9 F
Coefficient of rank correlation, 等级相关系数
- E% d5 O. v/ A; P! \! NCoefficient of regression, 回归系数
8 f# h* S& c# X* KCoefficient of skewness, 偏度系数; N: {0 ^& q* X0 V& s' O
Coefficient of variation, 变异系数
( g9 `" p/ y/ ~: v8 D3 CCohort study, 队列研究
" R+ \( V; n" ]Column, 列
6 ^7 ^ v: C! F# d+ [1 B. }Column effect, 列效应
( s+ g3 Z7 I7 p7 A9 Q9 |Column factor, 列因素 b% Y" ~0 ~( |3 S2 @5 P/ l
Combination pool, 合并8 T z! D- b" A
Combinative table, 组合表 C4 ]% n$ H* J4 D- J/ L% `
Common factor, 共性因子
2 r) ], a3 `) S nCommon regression coefficient, 公共回归系数; Q" u$ I/ V; z% m; N4 W3 @, g
Common value, 共同值1 V# K4 k0 W$ P8 _' s
Common variance, 公共方差
5 v' o: J; C6 t' b6 RCommon variation, 公共变异
# y+ }) p" o1 ]. mCommunality variance, 共性方差9 z* U( i+ Z* ?, e7 U. i
Comparability, 可比性% O b4 s8 f" U& n
Comparison of bathes, 批比较
- u) s( J7 x& zComparison value, 比较值7 v' x' I, g0 j: E- N' T1 @
Compartment model, 分部模型
- r4 U$ ~3 f* FCompassion, 伸缩
% W0 g4 Q" h( h3 CComplement of an event, 补事件1 q- P) x M% g: u) i& r/ F% h
Complete association, 完全正相关% F: g! h6 S7 \. P
Complete dissociation, 完全不相关
4 m. C8 A. k' @+ \; x6 t7 m) i$ f) dComplete statistics, 完备统计量
( x$ `8 Q) t( @1 f+ ~( Y( dCompletely randomized design, 完全随机化设计
+ c7 ~: i) S( T, e& {1 KComposite event, 联合事件
( ^6 }* }7 M: ^( xComposite events, 复合事件
1 n1 C# P* Z& _% m( m3 C6 vConcavity, 凹性
) z, m7 l; z9 X1 C; KConditional expectation, 条件期望7 }0 Q8 F' {+ y, s1 W, ^8 o" z
Conditional likelihood, 条件似然
# J6 Z+ M$ i+ ]1 i; NConditional probability, 条件概率
5 E- u3 }2 [ d; Z& Z- V' FConditionally linear, 依条件线性7 h3 z, {: T. Z8 k/ a8 J! Y; y* c. }4 ]5 O
Confidence interval, 置信区间
: ~$ h6 y9 Y) |3 M0 Q5 NConfidence limit, 置信限
$ i" N& ^+ |7 F% k( OConfidence lower limit, 置信下限
/ ?9 a1 z% M2 }9 \3 ?/ |Confidence upper limit, 置信上限$ B& S+ ]/ z) ?7 `+ @
Confirmatory Factor Analysis , 验证性因子分析
' Z% H+ G- Q, e/ X+ L- I$ OConfirmatory research, 证实性实验研究6 t( B! T2 q- P5 H4 ], }
Confounding factor, 混杂因素9 O+ X: F0 P: J$ [; }1 z
Conjoint, 联合分析% @% E7 E7 n: d# ?
Consistency, 相合性0 g* b" E5 s% w! K, v3 o
Consistency check, 一致性检验
$ j7 M4 t* }% v' EConsistent asymptotically normal estimate, 相合渐近正态估计
# a' i* l! Y# A5 k% M# QConsistent estimate, 相合估计: m- z6 E! _6 [4 Q; X1 s b2 ^: B
Constrained nonlinear regression, 受约束非线性回归/ [7 M5 b9 V5 O7 h
Constraint, 约束2 u% e9 l3 T7 L1 z5 ^& ], _
Contaminated distribution, 污染分布1 p7 x' H9 b! V4 M" E
Contaminated Gausssian, 污染高斯分布) L* M1 A% O+ d2 \7 H
Contaminated normal distribution, 污染正态分布
+ B/ g' D' N. j3 O5 z0 ^3 hContamination, 污染
4 k& i7 Y I9 S: v# P `Contamination model, 污染模型: A& F' v2 m# ^* r) I: [
Contingency table, 列联表% |- ]3 S% h8 K5 }
Contour, 边界线3 {3 U- ^& _, x" E1 R
Contribution rate, 贡献率( M2 f& V' I3 Y8 O
Control, 对照
+ g, U4 u" F3 k: t& t: RControlled experiments, 对照实验
; U- p/ ]3 ?" X* |Conventional depth, 常规深度
4 Q: S; f _( gConvolution, 卷积
3 _. w0 b/ m' ^$ ~% I+ v: I. NCorrected factor, 校正因子2 n/ U3 B+ Y7 ?$ Y0 h
Corrected mean, 校正均值
5 ]( ?4 }4 n+ L! H* D9 _9 vCorrection coefficient, 校正系数
* _% ^' o( z _' Q+ \. @Correctness, 正确性: O6 ^% R' f) G l- V. E
Correlation coefficient, 相关系数
+ w1 w+ h! _+ I, \* f* FCorrelation index, 相关指数% t8 d1 }1 K8 ?2 b& U8 H' Q% a
Correspondence, 对应5 o0 t! T7 i1 u+ t1 q+ I# S2 v9 r
Counting, 计数
4 m3 K. e' ^6 e+ m9 ~2 K* s+ m; jCounts, 计数/频数
: y2 H: ~# N% |6 m& ~7 C( Q# m. aCovariance, 协方差
! x# |" H5 G; ]) w2 \Covariant, 共变 1 l# H$ I; N6 d) ~( @" a
Cox Regression, Cox回归
! C& w1 ~, E% L8 O: _/ WCriteria for fitting, 拟合准则* ^2 z$ D: u. J5 v, d
Criteria of least squares, 最小二乘准则( x7 z0 T, k# n/ x( M9 b; J* M
Critical ratio, 临界比+ k9 z& B3 r$ |2 | Q
Critical region, 拒绝域$ l+ ^2 I3 k2 d) X* \: f) y2 _: g4 l
Critical value, 临界值: k1 J. r9 O1 s% k7 E/ y+ E
Cross-over design, 交叉设计- C! s& E/ ^8 K& c) ~& D9 m& l
Cross-section analysis, 横断面分析) e- ]; I/ o1 ?+ I% B7 N1 E3 I
Cross-section survey, 横断面调查
" l2 R; Q. p6 p5 `5 PCrosstabs , 交叉表
; b/ _$ \7 U7 ]$ z6 L2 pCross-tabulation table, 复合表
" ?7 z* b9 S2 n7 J0 O, ]Cube root, 立方根! a6 h5 K+ @5 U' a8 {( p
Cumulative distribution function, 分布函数1 o# Q+ F( F, t" f. i/ x
Cumulative probability, 累计概率
& f. c# ]2 z @Curvature, 曲率/弯曲
7 n, t& S K" E) rCurvature, 曲率
9 H, k6 O+ s. D' b9 V0 ]Curve fit , 曲线拟和 0 Y T" C- e) E% w# R" \
Curve fitting, 曲线拟合% }/ m- t) \3 Q
Curvilinear regression, 曲线回归2 h+ j8 m f' ^1 G
Curvilinear relation, 曲线关系
8 @' ]$ n+ `* d$ z$ Q! iCut-and-try method, 尝试法
0 n* J) s( a+ v5 d; ~7 K$ MCycle, 周期% Y1 U2 g; L2 @9 L9 v+ ]: j
Cyclist, 周期性
. z& q8 ^9 m( F; ~- [2 N: l& {D test, D检验, v# V6 |: n" O* a
Data acquisition, 资料收集1 r/ N! z i0 Y0 C7 E
Data bank, 数据库
7 z L+ ?; g4 g* b/ M( Q p$ G% ]Data capacity, 数据容量 V' k7 Y% }! ~. M
Data deficiencies, 数据缺乏6 \% F( |0 L% i9 X% M
Data handling, 数据处理* b9 j1 x6 b, N% X: l& X/ P
Data manipulation, 数据处理: j0 w) o% W) m! p( d0 u( \3 [
Data processing, 数据处理6 |! W4 D! ~7 \& d$ i8 m
Data reduction, 数据缩减4 ^' t( c* P( r$ f( c6 l2 _
Data set, 数据集* ^/ f) ?0 o8 J+ L
Data sources, 数据来源% j2 `# c) f# A& x9 r$ B
Data transformation, 数据变换& U: y( W5 E5 `" \" G4 ?9 U5 Q8 K0 L9 {
Data validity, 数据有效性
! g# d- b1 I( V: TData-in, 数据输入
" u+ `" W" L/ \5 \9 x& vData-out, 数据输出
3 T5 n- |5 ]) pDead time, 停滞期
6 R1 p, L) m, V9 k# JDegree of freedom, 自由度" ]$ ]) d( k6 [6 ], G# ?/ ~
Degree of precision, 精密度
9 Z9 E( m. t; ]3 c' @Degree of reliability, 可靠性程度9 r6 u4 R$ K7 S0 i9 t
Degression, 递减
9 F% L$ j, Q& f9 \* g1 RDensity function, 密度函数
: a; |" n2 u' [Density of data points, 数据点的密度
/ w, |3 g& E5 D# W f, Y, Z5 WDependent variable, 应变量/依变量/因变量- m3 i# B6 a7 x& @ n% }+ q
Dependent variable, 因变量
\/ l: _5 g% |8 F: {Depth, 深度
( n' N0 e: s1 LDerivative matrix, 导数矩阵
2 x% h+ z( S# e0 l WDerivative-free methods, 无导数方法
' W" R* v/ w6 I. f" F! rDesign, 设计
: q7 k1 f1 z" |! H: {# k+ `Determinacy, 确定性+ c+ y1 x$ s% _, @$ C
Determinant, 行列式
! N% A4 [0 D. ]3 a: @Determinant, 决定因素
) K7 t* \6 t1 w9 C8 E, M# VDeviation, 离差: g- H9 A, D% ?( l9 E4 y5 D- [
Deviation from average, 离均差
3 b. z z7 J, k ]Diagnostic plot, 诊断图
# [: n1 u* C# K8 P' j2 B0 Y: LDichotomous variable, 二分变量
* F" E3 u8 {2 _6 g9 }4 hDifferential equation, 微分方程
0 I( D0 ~6 j: i" tDirect standardization, 直接标准化法7 M$ Y1 m8 a1 k( F+ x
Discrete variable, 离散型变量
2 m' r$ \1 L9 {5 pDISCRIMINANT, 判断
7 }# `, O& s/ z; q) yDiscriminant analysis, 判别分析. n3 d9 @8 A! ?6 ?9 [; c t
Discriminant coefficient, 判别系数$ P- h; {# ~3 E. Q
Discriminant function, 判别值% i0 G+ q- C4 L. _
Dispersion, 散布/分散度1 X% f w$ ~6 o9 N8 B" ~( v5 G
Disproportional, 不成比例的
/ V1 q/ W3 p, j9 BDisproportionate sub-class numbers, 不成比例次级组含量/ M9 @# D3 g, S1 n1 h
Distribution free, 分布无关性/免分布
& d( ^, @! n1 v$ U1 N- L8 eDistribution shape, 分布形状
K7 K8 Y1 `9 z7 GDistribution-free method, 任意分布法7 Y7 j+ b F9 a2 u# G. c! ~
Distributive laws, 分配律
$ ~- ^8 c( ^- k3 |% v9 HDisturbance, 随机扰动项
% D+ h1 j! `6 D. pDose response curve, 剂量反应曲线
9 k! C, W X* D; X' ]5 S+ oDouble blind method, 双盲法
- l' c2 B( v3 [) ~+ R/ vDouble blind trial, 双盲试验; r( e: [1 S, Q+ h3 G
Double exponential distribution, 双指数分布
, h0 H$ f7 q/ K/ [5 ?Double logarithmic, 双对数1 j$ a I2 @( w/ C) |! W
Downward rank, 降秩
) n8 h6 [9 h( D B! S% hDual-space plot, 对偶空间图
& A3 O; l/ E% |8 ]/ K" z- R2 \6 U# UDUD, 无导数方法- c' Q4 x2 m2 \4 _, k0 i
Duncan's new multiple range method, 新复极差法/Duncan新法. R$ Y6 t, Z) @7 b; z- P; Q5 s3 J( V, r
Effect, 实验效应
, U5 }2 X' ^$ oEigenvalue, 特征值
+ b) G& }" {! E0 W7 fEigenvector, 特征向量
* y- l' [2 l- b( q0 oEllipse, 椭圆
1 b" L& S8 E5 B! c% n, ^* cEmpirical distribution, 经验分布
0 a, N* i" _: DEmpirical probability, 经验概率单位# T5 V7 `* {( }9 O2 E6 `
Enumeration data, 计数资料" Y& J% w6 z) I$ P
Equal sun-class number, 相等次级组含量" L( o( a8 _2 c; A' i
Equally likely, 等可能# m' ?$ [: {) E' ^# ]0 K
Equivariance, 同变性* D. L$ W6 u+ Y" o/ D/ J# [
Error, 误差/错误5 C) M% D$ V3 H: X$ L9 U; m: w" B
Error of estimate, 估计误差
# G R. x- H6 t4 ?! xError type I, 第一类错误0 q0 Y. }( k! m
Error type II, 第二类错误' e, ~9 b/ m% x
Estimand, 被估量: ^! _0 X+ _+ b
Estimated error mean squares, 估计误差均方
6 `9 {2 y! w& z$ P0 WEstimated error sum of squares, 估计误差平方和
2 f9 ~- Z, p+ s0 m* n" n% a# I5 R. xEuclidean distance, 欧式距离
6 ~! h9 @) A9 |& K# ~! HEvent, 事件: Z. o6 G7 ]+ S8 q: t% B7 e
Event, 事件
1 ^! c- r/ A8 v) ?( PExceptional data point, 异常数据点+ a' G. w, D& R! l7 I
Expectation plane, 期望平面
$ H) Z" x7 j% d# q8 B3 A: d# b6 ]8 F# rExpectation surface, 期望曲面% h2 n/ e5 Z* p0 Y; z( J7 @
Expected values, 期望值; B/ W$ O! Q4 h2 Y
Experiment, 实验
- _8 D$ D! q, V+ n6 L' t- CExperimental sampling, 试验抽样1 z$ C; `( w* v) [; m
Experimental unit, 试验单位
+ k/ _) _7 n% O f R5 wExplanatory variable, 说明变量
5 P8 c: B" h- K3 a( XExploratory data analysis, 探索性数据分析
- s# X; c7 [& k% W- _% dExplore Summarize, 探索-摘要
4 @. D! z V: C4 P9 ~! |: E9 Y- aExponential curve, 指数曲线) c! H5 {8 p% {8 W
Exponential growth, 指数式增长
9 X% c# U: q4 qEXSMOOTH, 指数平滑方法 ' Y1 P$ {, Q5 b# F( y6 P3 R5 [
Extended fit, 扩充拟合+ M( W. P2 I+ M8 I5 Y4 a% |- @/ s
Extra parameter, 附加参数& Z) |$ v9 o/ T
Extrapolation, 外推法
2 k9 ?4 J8 o' Q, ?3 O. _Extreme observation, 末端观测值" |3 Q v; i" q& _; b v9 b* R
Extremes, 极端值/极值
/ E. r2 T/ } f! b9 Q9 UF distribution, F分布
. A4 ?" {; ^9 ^; j6 x* F& K' M3 YF test, F检验
$ H( l; y* `$ [$ l8 I, g( _: kFactor, 因素/因子
9 q: C* k) S( v( D' X; IFactor analysis, 因子分析
& B7 w4 q7 \$ |* S- |% [Factor Analysis, 因子分析
; Z% s+ Q! B3 `9 I- X j1 f$ HFactor score, 因子得分
( O' n$ d' X/ B( @0 RFactorial, 阶乘
E. x6 L. |- o. OFactorial design, 析因试验设计
) l t, B3 L* ]. DFalse negative, 假阴性% |& Z! l' \0 Q
False negative error, 假阴性错误
3 E) x6 A& k7 U% I- |. o7 Y# mFamily of distributions, 分布族1 w6 {# e+ N% B7 j
Family of estimators, 估计量族
+ [) R! `, ?' J1 d g0 WFanning, 扇面" \- {* J' x" W
Fatality rate, 病死率$ A, A; G S5 m- e% V$ Q
Field investigation, 现场调查
+ o! F4 u; x) l" `( t; iField survey, 现场调查
+ @! S6 X. W5 wFinite population, 有限总体4 H# _, s; Z: Y1 _, S3 X& s
Finite-sample, 有限样本. q8 O ^/ H1 d, W N
First derivative, 一阶导数9 h, i% a- [2 X( L; q3 ]
First principal component, 第一主成分
- A4 T) g' e6 A g2 rFirst quartile, 第一四分位数+ G9 O4 Y) ~. ]
Fisher information, 费雪信息量% z+ x$ \6 w, E2 I# X
Fitted value, 拟合值
- _( U9 |3 x6 _2 ?Fitting a curve, 曲线拟合
+ \3 K6 W" N2 [7 W' d- K/ MFixed base, 定基
7 X0 X8 Y! R/ b" k- r9 G4 EFluctuation, 随机起伏
: \4 G* Z# Y& U) HForecast, 预测
, B2 |- R/ s# [8 aFour fold table, 四格表
6 }% \" d6 A& }! {Fourth, 四分点
9 c6 [$ K! } ?3 Y/ ]Fraction blow, 左侧比率
1 z2 l' S {' L# rFractional error, 相对误差
3 ?4 G! K: t9 AFrequency, 频率
f/ Z: u D; x z! S/ hFrequency polygon, 频数多边图( u" j; K/ z% n4 j& H- P
Frontier point, 界限点
4 f. @% V; Y2 D u0 I, MFunction relationship, 泛函关系
4 `, g' {+ ?: f6 K8 }Gamma distribution, 伽玛分布4 ^7 F# O1 G& s
Gauss increment, 高斯增量
, A" U+ W# J2 K3 c+ P* _* X- j5 WGaussian distribution, 高斯分布/正态分布
2 r! W' D4 d# C7 D8 WGauss-Newton increment, 高斯-牛顿增量
- @ [$ Z7 z% kGeneral census, 全面普查
Y: y8 I- e. V7 v% ZGENLOG (Generalized liner models), 广义线性模型 + W6 i6 {1 [0 E. T R* R' j; Z
Geometric mean, 几何平均数
$ N" m2 o n, b3 w% [0 |. jGini's mean difference, 基尼均差1 w) S9 L: P6 _6 U
GLM (General liner models), 一般线性模型
1 t9 N0 n) v0 O/ n! qGoodness of fit, 拟和优度/配合度
0 [; x6 y- Z$ g8 C; NGradient of determinant, 行列式的梯度
4 Z0 V3 C$ a2 |9 v& j5 _- SGraeco-Latin square, 希腊拉丁方( s" U: @, N. S" e
Grand mean, 总均值
N' B5 w' o+ {Gross errors, 重大错误
% |) k8 H/ u3 }Gross-error sensitivity, 大错敏感度3 |2 u5 C5 \* w
Group averages, 分组平均
( b" J- _% [# }9 F; ]8 S$ `Grouped data, 分组资料7 o% M$ {, l$ ]9 F
Guessed mean, 假定平均数( {7 w0 d, o% d5 {' b3 X7 @0 o [+ U
Half-life, 半衰期; u$ I: U% Q2 s
Hampel M-estimators, 汉佩尔M估计量
& T0 _0 ]: W+ l0 o Y2 SHappenstance, 偶然事件, ~5 D& N6 ], V
Harmonic mean, 调和均数/ D% |( c, {$ R& }* N+ c
Hazard function, 风险均数; i6 Y- M. ?/ X6 ]9 h! W
Hazard rate, 风险率
3 {7 }# X: l# T$ OHeading, 标目 / O. d9 O+ n# I* y
Heavy-tailed distribution, 重尾分布# z/ f9 Q" g$ n: P1 g' L. T- M9 g
Hessian array, 海森立体阵
2 U2 [2 U# |- f( KHeterogeneity, 不同质$ A5 V( C3 j1 m: g
Heterogeneity of variance, 方差不齐
) u5 v5 B |+ r5 a. ^8 zHierarchical classification, 组内分组
/ ~4 H$ h, B pHierarchical clustering method, 系统聚类法. W2 [: W% B6 U% O
High-leverage point, 高杠杆率点- d# L- [, o8 E4 ^) E+ a7 y+ [
HILOGLINEAR, 多维列联表的层次对数线性模型
4 O; I3 @$ n$ O9 T2 d& @. n7 `Hinge, 折叶点. M$ ]) Z% N# i
Histogram, 直方图
) S( _' r( [ [Historical cohort study, 历史性队列研究 * ?6 J% t+ I5 ~! b4 Y2 e8 T8 u
Holes, 空洞
l& s! Y; v: T! I7 c; b$ s0 dHOMALS, 多重响应分析/ M+ X$ [+ l/ o9 V9 H* I" y9 U+ k
Homogeneity of variance, 方差齐性 a# d) x8 H! |3 {4 j/ R4 g0 }
Homogeneity test, 齐性检验8 R3 `6 J$ B) _ o
Huber M-estimators, 休伯M估计量
& a7 \8 V) |$ y) gHyperbola, 双曲线
9 @3 q# P1 z& f6 MHypothesis testing, 假设检验
4 V- z5 f8 D0 W9 _Hypothetical universe, 假设总体
6 J) r) A2 h4 @) N9 f& JImpossible event, 不可能事件
( }) j4 S l1 m- BIndependence, 独立性
+ R4 F' M9 ?( p8 k% ?Independent variable, 自变量
7 B `. B8 e8 m, C' EIndex, 指标/指数* r$ H0 v7 T* m$ P, r
Indirect standardization, 间接标准化法/ M' j# u. N; g
Individual, 个体) f: x! H% G. g
Inference band, 推断带; n/ ?' E& n- H( Q; h5 h
Infinite population, 无限总体
% T# @0 O/ {0 m" X: d4 U0 D8 xInfinitely great, 无穷大
t+ h: k# E: _4 }Infinitely small, 无穷小0 d" [ t3 Z. o0 n/ x5 F
Influence curve, 影响曲线
. b" C% r& v8 kInformation capacity, 信息容量; [! f' r, g1 K, P7 m1 m
Initial condition, 初始条件1 Z. S* K; I1 L" \+ Z' a6 D; j
Initial estimate, 初始估计值. o: K' N* g4 w; x
Initial level, 最初水平1 j5 T- v- ^4 G+ V
Interaction, 交互作用/ y) D! P: ]4 J! s
Interaction terms, 交互作用项
( k! }. o) n5 j- `Intercept, 截距/ C" i$ B7 v m
Interpolation, 内插法
3 q0 g3 j& d- E" b+ K) B/ lInterquartile range, 四分位距
7 R' P7 b3 ~ b5 X/ |. YInterval estimation, 区间估计3 [' z4 w" a. i \ p$ L
Intervals of equal probability, 等概率区间4 `: n' x2 w9 V/ _
Intrinsic curvature, 固有曲率
/ {7 t" r( E* [# [Invariance, 不变性5 d# W# [9 g, c1 _ u& x* j
Inverse matrix, 逆矩阵
) Z9 X. k, [/ s7 ^% o, mInverse probability, 逆概率; p4 h5 M8 {1 l
Inverse sine transformation, 反正弦变换 G& a. f1 \, [' [
Iteration, 迭代 7 k. F" U4 q9 e7 R# y4 C. W3 H# l
Jacobian determinant, 雅可比行列式) m0 t5 _1 k$ D1 L" D+ n) E% M6 m
Joint distribution function, 分布函数
) s3 j" \3 N2 t* H% s1 a3 g IJoint probability, 联合概率6 }3 o6 `" g; m3 I: ^ F" }0 f6 U
Joint probability distribution, 联合概率分布2 a6 l+ y! ~3 Z; L: K
K means method, 逐步聚类法
& W* W. Q- }1 `8 C* i5 pKaplan-Meier, 评估事件的时间长度 ' f6 `; k$ B! S4 S; P0 ]
Kaplan-Merier chart, Kaplan-Merier图, ]; n! l+ k$ i
Kendall's rank correlation, Kendall等级相关
l- v- D( s6 D; AKinetic, 动力学
F% F4 L7 _0 M1 o( m# yKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
8 _" |# }; J/ L$ R, IKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
6 t5 ]& s( N- H% UKurtosis, 峰度
! G6 E2 m2 I+ e4 {) a& ULack of fit, 失拟
' N: t" v, h: @3 u9 Q7 ?Ladder of powers, 幂阶梯
' t5 o! e' o, ~Lag, 滞后
' T# j, u7 v; E+ D2 p, KLarge sample, 大样本* G5 J" j( J6 ~$ {
Large sample test, 大样本检验& u2 _( C) u; x; j
Latin square, 拉丁方! e' c! y. w, c u( \
Latin square design, 拉丁方设计
9 W. d$ W4 @, c, r5 J& TLeakage, 泄漏- w0 T8 X) I8 U( B7 T
Least favorable configuration, 最不利构形
8 `6 n1 } E$ q7 f3 Y3 Y& kLeast favorable distribution, 最不利分布
( _: I/ F% c- K. v6 W; T7 u& A4 hLeast significant difference, 最小显著差法
# }9 ]8 ~! D# K q0 sLeast square method, 最小二乘法9 n# T1 @% }' I
Least-absolute-residuals estimates, 最小绝对残差估计
# r$ w6 v( c& k9 J0 u$ {Least-absolute-residuals fit, 最小绝对残差拟合
! B! ~/ P; t, f. N4 ]Least-absolute-residuals line, 最小绝对残差线
" ~* }, S8 B Y. Z) C$ kLegend, 图例% e; `8 T% E6 P/ k+ K
L-estimator, L估计量
/ d. R2 Z& F0 V) Q% Z1 U- X l* `# ?L-estimator of location, 位置L估计量6 y8 }4 m/ F5 Y! O0 F* S
L-estimator of scale, 尺度L估计量
) F- p& c1 |- }8 f9 b, TLevel, 水平
8 p( E1 D2 X0 O$ |/ g5 P2 R/ C0 ULife expectance, 预期期望寿命
- i: T! Q0 W7 N, g4 z7 m! b. P5 lLife table, 寿命表3 V9 B. B. W. a* Z' S! E% Z% d7 H6 c
Life table method, 生命表法
/ A$ ?5 W7 E" E1 l7 p) u! y/ ?Light-tailed distribution, 轻尾分布) J6 a1 l) [ Y& h! d7 x
Likelihood function, 似然函数3 J& s& B$ J3 ~
Likelihood ratio, 似然比5 A" e" i0 p( {& U& V- w
line graph, 线图
9 ?5 j1 f3 g' ]Linear correlation, 直线相关0 g9 ?# u1 y! e; V }
Linear equation, 线性方程
# v' t3 Q4 G7 z/ g8 BLinear programming, 线性规划
3 |( d3 V, C# h# ^) hLinear regression, 直线回归, a: n' a! u& X. Z/ ?) f# Q% ?
Linear Regression, 线性回归: z" n: B, ]" @; V2 W
Linear trend, 线性趋势' x* _+ {+ R* T$ L0 w
Loading, 载荷 ; j# {3 O3 _2 k! z5 [
Location and scale equivariance, 位置尺度同变性
5 q! p6 u! [ B! g/ b2 t w3 tLocation equivariance, 位置同变性# n$ F2 z* [$ L; o- F
Location invariance, 位置不变性1 l. g* b5 K0 M' i3 u
Location scale family, 位置尺度族) H; X5 L, k/ U
Log rank test, 时序检验
5 ]% B x. g. @3 z: X$ ^0 \2 p& U' pLogarithmic curve, 对数曲线
! B B; h1 l f9 i; F4 A1 a& ELogarithmic normal distribution, 对数正态分布
6 C3 T# @ E- WLogarithmic scale, 对数尺度
1 Y) `/ C* ?# R; jLogarithmic transformation, 对数变换" J! |8 A# v& }$ q4 x+ K! I `' n
Logic check, 逻辑检查0 v: J" }8 R) \* V0 y
Logistic distribution, 逻辑斯特分布
# U+ h1 Q3 A$ F( Z6 H5 a. U4 g( ULogit transformation, Logit转换
8 F+ D3 I' ^7 `1 u' CLOGLINEAR, 多维列联表通用模型 % X/ E1 g- z2 U- v
Lognormal distribution, 对数正态分布
. f! \2 x M# N! R9 VLost function, 损失函数
4 M$ {) ]# X& HLow correlation, 低度相关4 P; `, E3 _0 v- z6 l' Y x
Lower limit, 下限8 b3 J2 b! M) c- |2 Y# l4 e
Lowest-attained variance, 最小可达方差' G; g# ]1 p. ]0 q; \
LSD, 最小显著差法的简称% X6 x' o- u. [& v- I
Lurking variable, 潜在变量5 p' R/ q1 o/ y4 f, _& W2 v
Main effect, 主效应
- M- f. P; y" X; T. f$ }5 H# m" VMajor heading, 主辞标目& J4 _. Q# N7 r5 e7 a5 X
Marginal density function, 边缘密度函数. X+ l5 ?* g% Y) }9 b
Marginal probability, 边缘概率
5 L) P; O0 o7 a) ^9 t! C: z: mMarginal probability distribution, 边缘概率分布
( ?8 m: R4 B) Z) L! O7 _) ^Matched data, 配对资料
" h* E+ o+ {* p, p( b3 SMatched distribution, 匹配过分布" N+ D7 H8 [3 a3 H: u1 [
Matching of distribution, 分布的匹配
) v! Z2 i3 f$ O" Q& rMatching of transformation, 变换的匹配- D* I( a9 Y( f8 I- B
Mathematical expectation, 数学期望4 L' Q' L) E$ B r7 V0 V4 {( j
Mathematical model, 数学模型
- { F h" }; n6 c, W6 b* Y0 F0 `Maximum L-estimator, 极大极小L 估计量+ r4 c4 c# ~7 A: J; [' J; r
Maximum likelihood method, 最大似然法
+ l8 B' S% g* z: z+ O: RMean, 均数
' Y9 W& g" t+ \8 w0 _7 h/ m+ [Mean squares between groups, 组间均方# P: d; @' N0 O& G/ T
Mean squares within group, 组内均方% I! [8 I7 b* d
Means (Compare means), 均值-均值比较
. J% f: E1 e1 n8 d2 QMedian, 中位数7 L# ^( |3 h! M# \7 d! O, [
Median effective dose, 半数效量
- |/ N. C. u9 Y0 e6 V) x9 uMedian lethal dose, 半数致死量- X" v( O9 {' V" L" o# T/ y0 d
Median polish, 中位数平滑; ]* E6 a: L( M# a3 R, L
Median test, 中位数检验, M/ V/ d) ~& p. y1 g2 W
Minimal sufficient statistic, 最小充分统计量
& O$ t$ y: \! e! r' EMinimum distance estimation, 最小距离估计
8 e) \+ h0 C. `) S- x' PMinimum effective dose, 最小有效量
6 \$ D% t, f5 \; I7 g. q/ HMinimum lethal dose, 最小致死量, f3 |0 v# v* T
Minimum variance estimator, 最小方差估计量. p* x$ e$ Z# V8 z6 v
MINITAB, 统计软件包/ _# Y* ^( a7 O: h1 ]- j
Minor heading, 宾词标目9 j% I9 V; t& D3 q& g5 a
Missing data, 缺失值
5 g0 p' z9 d: \6 |Model specification, 模型的确定
& t0 T3 R! T% G* \: k. ~Modeling Statistics , 模型统计
0 ~" k9 w Z5 CModels for outliers, 离群值模型
1 n! a1 }9 B7 W+ ?1 ?( PModifying the model, 模型的修正# E0 g. t2 K+ F! I
Modulus of continuity, 连续性模
2 m; Q& a {; m- u0 z, OMorbidity, 发病率
! L. b4 h- j- b# [Most favorable configuration, 最有利构形. T8 M4 }$ G( P) [
Multidimensional Scaling (ASCAL), 多维尺度/多维标度* c: f. J) o+ h/ ]1 [
Multinomial Logistic Regression , 多项逻辑斯蒂回归
. u: U2 x/ q8 K$ Y& a) hMultiple comparison, 多重比较. E. d2 u; `+ I/ K
Multiple correlation , 复相关
& B9 D) c- @; k3 S$ OMultiple covariance, 多元协方差
, o6 | d! l, JMultiple linear regression, 多元线性回归
$ {+ @. Z; {# A' gMultiple response , 多重选项3 ~# }2 t$ ~) K6 }2 s2 m! X4 U
Multiple solutions, 多解0 H8 _8 v" z* e+ X
Multiplication theorem, 乘法定理
% f8 S- r" r; C3 E) eMultiresponse, 多元响应* T& a3 n+ g' d$ K/ j* Z
Multi-stage sampling, 多阶段抽样
/ b7 z7 ]! w# D4 L. XMultivariate T distribution, 多元T分布4 r5 N) t2 S! m, X3 K
Mutual exclusive, 互不相容
1 Y& m" y2 [) O" M# \8 w' V. IMutual independence, 互相独立: Y( B# b3 b# Q3 [
Natural boundary, 自然边界
+ S( Y$ d, q8 @* bNatural dead, 自然死亡
# p( Q4 i1 y2 q+ `Natural zero, 自然零
3 ~# J! D5 }! c; T4 S* Q A6 G' hNegative correlation, 负相关
' \+ x8 A! Z. Q* m- }Negative linear correlation, 负线性相关 U: T) Q$ J) C; o, R1 D
Negatively skewed, 负偏* ]& e6 V$ V5 J+ @2 Y' U% e- T
Newman-Keuls method, q检验
; a6 |4 ~1 m3 E* ~NK method, q检验. M7 d& ~" K* U2 I- d ]
No statistical significance, 无统计意义
0 s5 B& Q4 E7 K# SNominal variable, 名义变量# D* r$ |' [3 i+ q0 ?
Nonconstancy of variability, 变异的非定常性
: n( ]" i7 u0 k+ l0 r" NNonlinear regression, 非线性相关; Q* o) A* V" {/ ~" M7 @
Nonparametric statistics, 非参数统计
9 R) {, E! w) A- K$ h/ ]2 Y: ]Nonparametric test, 非参数检验7 Q4 g& K% v2 o6 e: P; T
Nonparametric tests, 非参数检验
5 J* x I: f: Y, YNormal deviate, 正态离差( ` {0 g u, e, T) ? f* Z
Normal distribution, 正态分布
5 ?- M- _ r' q* s) D( Y Y+ INormal equation, 正规方程组
9 ~0 E0 x) V6 oNormal ranges, 正常范围% L9 N0 C+ H, \4 \
Normal value, 正常值/ w8 p R4 O+ L! s5 S
Nuisance parameter, 多余参数/讨厌参数
- W% O" C" D8 Z% \) KNull hypothesis, 无效假设
' J' I e9 L, H) CNumerical variable, 数值变量
/ I0 i1 U, P7 u8 I: Q5 @2 bObjective function, 目标函数
- e) ]& X7 F3 yObservation unit, 观察单位
: g* I/ T. V$ l1 bObserved value, 观察值
( n( L- v' `; \5 p+ _One sided test, 单侧检验0 g8 L3 }4 {2 t" P
One-way analysis of variance, 单因素方差分析! x' {2 W3 z) L- V9 s4 P
Oneway ANOVA , 单因素方差分析
' L5 _& r$ N4 l% J4 LOpen sequential trial, 开放型序贯设计8 j- d# l; P9 l ?1 B$ o& L
Optrim, 优切尾
P7 g. |5 Z+ r" v3 UOptrim efficiency, 优切尾效率" w3 L" t$ o7 H! m; Q6 P* R' r9 G8 H
Order statistics, 顺序统计量
- m4 Y9 B4 ~! W" }. c" g. \4 ~ GOrdered categories, 有序分类 M- w N! H3 H0 [
Ordinal logistic regression , 序数逻辑斯蒂回归
. q7 G3 L- r1 q. }3 W1 k3 uOrdinal variable, 有序变量; f+ k) A, u2 F1 F
Orthogonal basis, 正交基
# W% G( n! O5 h# }2 Y% q7 mOrthogonal design, 正交试验设计
7 p' C/ n/ w% uOrthogonality conditions, 正交条件
2 d! E2 C( t* i( Q Y5 iORTHOPLAN, 正交设计
. I0 f# K6 h5 B( c- B* a/ n/ I. dOutlier cutoffs, 离群值截断点
& r6 O; V" C) D# @5 [: s0 EOutliers, 极端值
K, @& _; P. f5 r9 [7 rOVERALS , 多组变量的非线性正规相关
. H: k/ C; J" E1 T. ]Overshoot, 迭代过度
0 \& ^, V4 J* V% w& VPaired design, 配对设计7 l' i6 j, r f% Q+ U+ m+ z- ~
Paired sample, 配对样本
" F! e' I* U2 J/ FPairwise slopes, 成对斜率! _! ] q) e6 j: c
Parabola, 抛物线6 P$ b' T" Y% Q( M' F* m- x
Parallel tests, 平行试验
; T2 L1 Y5 h8 @Parameter, 参数
/ [2 h2 q4 C) q+ I, g! fParametric statistics, 参数统计- w9 K" H a- g: [9 i% N
Parametric test, 参数检验2 d$ d; U% \( U7 U D: P
Partial correlation, 偏相关2 u& `/ h1 V9 t/ t- [% I1 x6 R
Partial regression, 偏回归
% @) V5 `9 b3 L2 M; uPartial sorting, 偏排序
. k/ q; |4 H( y4 T6 O6 Z8 MPartials residuals, 偏残差
4 ~9 f3 y5 X) E' rPattern, 模式9 a3 t- Y& Z7 Y7 w+ A
Pearson curves, 皮尔逊曲线- O, t( M, A3 F- v/ U |+ Z
Peeling, 退层2 B& l* O$ _7 @9 e% U2 p
Percent bar graph, 百分条形图% Q( Y! c3 n) ]6 x' v
Percentage, 百分比
& u5 d2 r. P" }Percentile, 百分位数
: l$ p8 i+ |) I6 ~3 YPercentile curves, 百分位曲线( C; ~$ H! z, g/ i
Periodicity, 周期性
; N$ C0 G4 l5 ^. j* xPermutation, 排列
) x1 d# i5 t2 v% D, LP-estimator, P估计量0 f* f }4 [5 U% N2 K% B
Pie graph, 饼图
4 W* Y/ _, @( \% E5 J% E" FPitman estimator, 皮特曼估计量
: G1 }7 l- K, v9 E" YPivot, 枢轴量; v: s* r3 I$ z# f |
Planar, 平坦. X* A0 I9 b# A; O+ j
Planar assumption, 平面的假设0 N/ w- S$ L6 e1 B$ [
PLANCARDS, 生成试验的计划卡
- k0 c1 C# n3 VPoint estimation, 点估计5 v2 T! p$ `8 L9 e/ q9 y6 ^
Poisson distribution, 泊松分布
+ m( Y- L& e z4 ]Polishing, 平滑+ |( E3 n( c% Z6 r/ E8 |8 B
Polled standard deviation, 合并标准差
4 s. w2 Z1 P# s2 X s2 p; gPolled variance, 合并方差
: R$ H; I/ ~. V1 }$ `9 D$ aPolygon, 多边图% }( i% a6 ^5 N+ J6 l
Polynomial, 多项式
$ S2 i9 e- g5 e0 @! ` DPolynomial curve, 多项式曲线
, y! k9 X, X: K/ x! Q) i$ wPopulation, 总体; z B- E) s- d) K5 p' o# p9 K
Population attributable risk, 人群归因危险度
5 ^0 F' M* T5 {4 B2 }1 q6 ]# ^Positive correlation, 正相关8 m B( Z1 w* Q+ n6 I( m
Positively skewed, 正偏
7 Y- r3 y; }4 V0 ^Posterior distribution, 后验分布, E* z$ u0 Q7 Z% L3 ?& R
Power of a test, 检验效能. m# z; W7 N% u. E# e4 f
Precision, 精密度/ J8 n4 l7 M0 W# O$ ~
Predicted value, 预测值) ?* I" s' s. t7 O8 c# c! t% x
Preliminary analysis, 预备性分析
/ y4 c" | t; ?- n8 mPrincipal component analysis, 主成分分析& Y# F( t( R, \2 b
Prior distribution, 先验分布
8 _6 j8 X+ Q: I0 S' YPrior probability, 先验概率* k/ ~8 y# f: O% @& |1 K* V0 m1 P
Probabilistic model, 概率模型/ E$ P4 x5 o j# X
probability, 概率/ k0 P5 a; j! V
Probability density, 概率密度
! z( r2 u3 U9 G' l7 { dProduct moment, 乘积矩/协方差
& X$ _! i0 K' j' C1 K7 AProfile trace, 截面迹图
7 I7 Z( k$ b0 k5 S+ q5 y/ xProportion, 比/构成比
0 ?" }9 p* F; S! B; ^3 \; {5 aProportion allocation in stratified random sampling, 按比例分层随机抽样- T7 H* z! ^" X; U; M) ~
Proportionate, 成比例 u. h! y) p. O s. V( n
Proportionate sub-class numbers, 成比例次级组含量
8 B( n) X2 {( e( C- A1 [Prospective study, 前瞻性调查- b$ s/ x$ Z. @8 J+ r
Proximities, 亲近性 ( \ }0 ~, h3 B: O
Pseudo F test, 近似F检验
( q: @( @6 m* H& v! {: y, |Pseudo model, 近似模型
/ L0 i9 f: p, P' q6 {4 ]& k% `Pseudosigma, 伪标准差
& U/ s7 I; X' k9 j) \Purposive sampling, 有目的抽样
3 o0 j! i# S, t- K0 ?# Q. kQR decomposition, QR分解
+ | p' h( m0 S/ W, eQuadratic approximation, 二次近似3 \9 e5 ^' [! G! a4 d/ F
Qualitative classification, 属性分类
: f4 K- v) b1 P" a) FQualitative method, 定性方法, J0 c7 M n$ M, G8 L I+ ^
Quantile-quantile plot, 分位数-分位数图/Q-Q图
" D' ^; X6 y! g C- ` e! mQuantitative analysis, 定量分析( {1 i8 X* J* ?, t
Quartile, 四分位数* b' ^/ b N1 m( \$ _
Quick Cluster, 快速聚类0 a9 g' y5 J7 v! @
Radix sort, 基数排序/ ~5 [$ t( n q2 M" Z: C
Random allocation, 随机化分组
( \2 `% J' \) pRandom blocks design, 随机区组设计 o: R% [" A* C( t! k
Random event, 随机事件
# L0 m1 e- J8 ]6 e6 CRandomization, 随机化
& T$ I! ?4 x" d6 S3 l( _Range, 极差/全距
4 B( A+ Z7 I Q" ^, {2 i. eRank correlation, 等级相关" j2 e( r, ?( y+ ~3 p( q
Rank sum test, 秩和检验
. i$ D! J# r9 zRank test, 秩检验$ @7 q. c: O1 l: D) o8 V' ^. |" d
Ranked data, 等级资料8 J9 q u: W1 a" h1 X- k8 R
Rate, 比率. v# t+ \5 u1 Q
Ratio, 比例 m0 `) X. e* g5 G5 i# Q& p
Raw data, 原始资料9 x7 V! |3 i8 E. ~7 O
Raw residual, 原始残差
- ^! J9 x5 G5 |5 wRayleigh's test, 雷氏检验! J8 P o s6 }. `8 c2 P
Rayleigh's Z, 雷氏Z值
& G. t) b- A6 ?5 F: hReciprocal, 倒数7 j, V& G% U# A8 w- A; C
Reciprocal transformation, 倒数变换* I! D0 A1 v4 L1 W
Recording, 记录2 n) [7 A4 W4 J& x
Redescending estimators, 回降估计量
* ^" n7 G( ~6 w3 ^$ w2 U& |Reducing dimensions, 降维5 S {# V* |: m- `+ g
Re-expression, 重新表达
1 i' K7 @( ~; O8 Z! l# l2 vReference set, 标准组$ a3 g$ V6 I; ^$ \, ~( {
Region of acceptance, 接受域
& g5 w6 X7 _9 |: r1 bRegression coefficient, 回归系数! t/ d9 {, @; ]+ b, l. T
Regression sum of square, 回归平方和
$ r' n: D5 r/ E( C6 Q- r2 R! CRejection point, 拒绝点: Z$ b( E* ?1 |( D
Relative dispersion, 相对离散度
- h5 g' f1 ^7 G) L( VRelative number, 相对数& f* z- Z, T; K2 @) k+ B2 ^: k3 `
Reliability, 可靠性4 H; G" `8 A4 z! }8 _' Q3 q
Reparametrization, 重新设置参数
) j0 l6 Q$ N/ d% i @' T! O3 W1 R# SReplication, 重复
# N+ ?( J+ W; z& N; vReport Summaries, 报告摘要9 u, Q& q) E0 \& X
Residual sum of square, 剩余平方和
/ n0 a! i$ [/ T) S k Q8 BResistance, 耐抗性
; H0 g9 @( z# ^8 ?: `7 BResistant line, 耐抗线
# y! c8 f! K- r+ UResistant technique, 耐抗技术+ A5 Q& S! N% K
R-estimator of location, 位置R估计量6 h0 U. V* g! t3 }! B
R-estimator of scale, 尺度R估计量$ e0 |$ l! X3 C. ]- q$ V# r
Retrospective study, 回顾性调查2 Y' Y- b l. L* g1 d' K! D: x
Ridge trace, 岭迹" I% C5 N5 y* g# w; z9 m, D* }
Ridit analysis, Ridit分析
3 X$ y) Z; O5 L1 O" u' wRotation, 旋转& w0 l6 Q: q7 Z
Rounding, 舍入
( t1 `0 |) ^; K5 E- K6 [5 [8 ~5 ORow, 行( B* l" ]0 F( f# f1 q% G3 _0 D
Row effects, 行效应
8 Y4 d8 G$ j+ ~/ z$ H5 fRow factor, 行因素# l3 n; J. C- Y+ {- T2 D
RXC table, RXC表
8 E+ L; K% ` ?2 ESample, 样本
9 h- ?3 g# u! |, Y1 _0 iSample regression coefficient, 样本回归系数
! [0 G/ }. c6 ]Sample size, 样本量
4 \! o% M6 T6 _# dSample standard deviation, 样本标准差
# B! f0 W. ~, FSampling error, 抽样误差+ z+ g( |% ?! T8 g. V8 b: B2 Y
SAS(Statistical analysis system ), SAS统计软件包
8 n5 }% \. m3 b2 f5 e3 [Scale, 尺度/量表
0 L! z8 L, C% Q1 RScatter diagram, 散点图
+ R; i- o8 f0 P. v# N) BSchematic plot, 示意图/简图
7 V! X, X. U0 ?& y# QScore test, 计分检验5 E3 ]' b8 N& }, G5 n
Screening, 筛检
. ~$ T1 D; Q& ^; Q9 E9 X. ZSEASON, 季节分析 D- k @; r) y0 ~$ P' T
Second derivative, 二阶导数
p* s0 A4 [& t- F% B4 b% ^Second principal component, 第二主成分
3 A+ a+ E; n- h. u: k! r: q) F3 @SEM (Structural equation modeling), 结构化方程模型 6 H/ L% _2 G! @5 y
Semi-logarithmic graph, 半对数图+ J* g, l4 w9 d7 v3 R+ c- |
Semi-logarithmic paper, 半对数格纸$ K5 R8 B9 {: E- m; D9 s8 u7 b% I
Sensitivity curve, 敏感度曲线
& G4 P3 t' k$ Y$ \1 bSequential analysis, 贯序分析
F2 k7 ?' x7 { i: u/ kSequential data set, 顺序数据集
/ ]) U# F" q \8 W+ I' `% A& G2 o5 ~Sequential design, 贯序设计, X- d) C8 e, S- Z8 Q/ M
Sequential method, 贯序法
7 [, l! D- y: D! JSequential test, 贯序检验法; `% s$ [' n L$ ~( u# g( M7 L- G
Serial tests, 系列试验
, N& j. @# N8 y. {Short-cut method, 简捷法
5 [# v1 R4 j5 E0 i' N2 J8 LSigmoid curve, S形曲线7 p! W) S5 ]. l5 K& y$ S* T
Sign function, 正负号函数
) n) a+ {2 D8 n0 ^3 NSign test, 符号检验6 n$ t1 x% W6 ?: t5 n8 L
Signed rank, 符号秩
7 I- S, H+ H# M2 D$ J( [Significance test, 显著性检验
7 c: f T# O* }7 [' wSignificant figure, 有效数字, j1 _6 | ]5 ^; l& \) a
Simple cluster sampling, 简单整群抽样" y& x8 g: h) Y' z! _
Simple correlation, 简单相关 B( v: X: C/ D) U) V- ^
Simple random sampling, 简单随机抽样6 z4 w" R5 ]5 U, G [ b% U
Simple regression, 简单回归* A: w3 M- F4 \6 B7 a: E
simple table, 简单表
- |8 E+ Z, }+ O5 h2 A5 R% gSine estimator, 正弦估计量6 N8 e$ V6 N* `, M, p( q& C; P7 D
Single-valued estimate, 单值估计- y: |! i; A& Z, G5 }5 o2 q
Singular matrix, 奇异矩阵
% }" E1 a# B5 N. BSkewed distribution, 偏斜分布" F7 T2 n* D9 i5 W5 z# r$ f9 g
Skewness, 偏度
|- `# X9 I9 U- ]2 q0 dSlash distribution, 斜线分布
0 W; k/ X' _# b+ p$ ~, H; DSlope, 斜率6 H) |0 }1 Q' `' u
Smirnov test, 斯米尔诺夫检验2 Z# p, P1 `3 p5 r) E3 I$ A% n
Source of variation, 变异来源
' T6 R7 [2 ?- F. }( wSpearman rank correlation, 斯皮尔曼等级相关
% k ?8 m C0 ^; P T4 x7 kSpecific factor, 特殊因子
/ h" O5 d8 m0 |! Z/ Y1 TSpecific factor variance, 特殊因子方差
4 Y& v d+ G4 N7 Q# ^, Z. a3 M7 vSpectra , 频谱
; K& j: a0 q' I5 g+ ?. _Spherical distribution, 球型正态分布0 k' h# ^% D# a/ q' E$ X
Spread, 展布
" N7 \7 q. W1 M2 U/ I' ~" W) n. cSPSS(Statistical package for the social science), SPSS统计软件包
5 y5 ]) _4 r' u, N7 NSpurious correlation, 假性相关
1 q) S/ ? d% W3 wSquare root transformation, 平方根变换
. v. }7 s# x8 }& UStabilizing variance, 稳定方差! Y: X0 F1 e: r6 o# Y! P) O
Standard deviation, 标准差
! R4 h7 A( Q' r- {0 d- x: fStandard error, 标准误
9 a; M) `; T+ ~8 p9 M2 }3 oStandard error of difference, 差别的标准误- M- u: _4 q. u" [5 E* p' n
Standard error of estimate, 标准估计误差4 j D0 W2 w# X/ e& k8 ]3 r
Standard error of rate, 率的标准误
3 Z: Q3 J' l: t: U+ gStandard normal distribution, 标准正态分布
* i+ Z0 _2 v, z6 l% CStandardization, 标准化
" N! B9 u: O% T! ~Starting value, 起始值
# Y* @3 J7 \: _9 j9 BStatistic, 统计量/ B2 N4 V. ^* Z5 ~/ f
Statistical control, 统计控制. _% S2 V( R( I2 H
Statistical graph, 统计图
# j* l" g- V7 }2 kStatistical inference, 统计推断, I9 M) b7 @3 W! Y3 Z, m
Statistical table, 统计表$ _# n* e0 K5 E% A% ]. C
Steepest descent, 最速下降法: x! K+ Z/ }0 E+ p
Stem and leaf display, 茎叶图6 t- i, H: l8 G) d7 I
Step factor, 步长因子
# g0 n0 l# u5 m# q$ v" HStepwise regression, 逐步回归
4 P% h# D# C' t: iStorage, 存
) M1 c7 j, ^) I2 i% o3 M3 Y, h7 oStrata, 层（复数）
# [8 I+ k" D, m3 Q AStratified sampling, 分层抽样
% Q' N. P4 C4 E. V. n1 L0 SStratified sampling, 分层抽样* E0 R2 F2 K" r4 r( m
Strength, 强度$ Q% V. o' {( D9 m. T0 J
Stringency, 严密性- V% E3 k3 a& @0 k8 |
Structural relationship, 结构关系) J$ i$ l* K( G, s8 l5 W
Studentized residual, 学生化残差/t化残差* l' _3 Z+ R# T$ W& f/ O' X
Sub-class numbers, 次级组含量
/ W! \' n& L- m! u6 ]# t' b P) i& dSubdividing, 分割% p7 Z! o6 V+ c
Sufficient statistic, 充分统计量
* f: t: p: U, r" q* e/ z1 GSum of products, 积和7 p C$ P: d" _( I: n+ l
Sum of squares, 离差平方和
: X! o1 l9 t# ~6 bSum of squares about regression, 回归平方和
% w+ a$ O2 x- B4 t* g6 g$ \! I% XSum of squares between groups, 组间平方和
: K' }& i, h0 @( [# aSum of squares of partial regression, 偏回归平方和0 ]* }* h' N G# ~! T3 n, }
Sure event, 必然事件4 R, X' y6 T. W) y s
Survey, 调查
, {. f$ r, ]& P; sSurvival, 生存分析
2 { R! d, f2 U9 ZSurvival rate, 生存率
( z1 _$ H" J8 V/ P5 S$ ESuspended root gram, 悬吊根图5 X2 Q, }$ \9 s/ s
Symmetry, 对称 P5 J2 F, p4 m* P" x' O, p. `
Systematic error, 系统误差& ~7 K7 k' o- k4 ~' r4 R c# V
Systematic sampling, 系统抽样% d+ e- e3 n$ Q6 [% Q4 U4 o9 ]& B
Tags, 标签. o! d. }" Q* z! h6 Q) n0 r3 R
Tail area, 尾部面积
5 ]& M: R* q. ]2 ^1 h" VTail length, 尾长5 O$ u% b5 j A2 y3 V
Tail weight, 尾重
% T. k& l! f$ q0 w4 \- g+ h; H8 T9 yTangent line, 切线 I; a1 r$ J" l3 H1 U
Target distribution, 目标分布% m4 R% K3 c) ]9 ^! ^4 j
Taylor series, 泰勒级数8 F; g6 H+ W% d( }# d1 \
Tendency of dispersion, 离散趋势
" V4 Q2 v1 v# q0 n4 B8 HTesting of hypotheses, 假设检验2 _! m: k% P0 L8 w. j: C1 d1 | {
Theoretical frequency, 理论频数0 o1 ]) N! M5 K! i
Time series, 时间序列% Q$ g' v- m6 {+ ?1 r6 ?
Tolerance interval, 容忍区间
2 n, m9 G: U- Q* Y) R) D n" R/ f% DTolerance lower limit, 容忍下限
2 _4 x* Y7 w8 l; s5 @% Y; x6 hTolerance upper limit, 容忍上限! h- d( n' M9 s- `
Torsion, 扰率
( k8 n8 N5 S6 e5 d& o0 v6 ]Total sum of square, 总平方和5 A- ~) t( ^+ M* l. l3 d: ^
Total variation, 总变异
0 }% E. j8 z5 ITransformation, 转换
+ n1 u: U N* L1 u+ _2 {; |# ]Treatment, 处理
+ J7 ?' z- i) D T( d; I1 TTrend, 趋势* N$ c. w3 D3 [( C
Trend of percentage, 百分比趋势6 c8 [, ~+ `9 H9 B: |5 x, A4 R
Trial, 试验) D. Q2 E3 ? |+ |# u
Trial and error method, 试错法
0 V$ d. J( K7 d9 L4 @7 b! MTuning constant, 细调常数4 q2 c. R( d1 A0 _/ h- @
Two sided test, 双向检验8 Q# E5 O' F' H% Y7 }; q# p
Two-stage least squares, 二阶最小平方
8 |6 Q6 z! h' {Two-stage sampling, 二阶段抽样
4 ?7 M# t7 X( E. z: Y( JTwo-tailed test, 双侧检验' W2 ]# C: [7 F. t6 L' q
Two-way analysis of variance, 双因素方差分析
& b9 E7 h! P9 ?3 ]0 o+ ITwo-way table, 双向表& W2 P" s9 g. Y: X$ B# p3 j4 e A
Type I error, 一类错误/α错误+ `4 d4 F. Y. v7 R3 F2 c6 P# N2 t+ g
Type II error, 二类错误/β错误
, J9 C6 s P1 a, }, \1 gUMVU, 方差一致最小无偏估计简称
4 X+ ?: |. z+ l: S. d: o# g0 i2 C- cUnbiased estimate, 无偏估计. }" ]& X. c3 a% M( v8 X
Unconstrained nonlinear regression , 无约束非线性回归! U6 J8 ^4 ]! o
Unequal subclass number, 不等次级组含量8 }7 g4 ?/ Y: [: S; h2 u7 P9 E z: H
Ungrouped data, 不分组资料
( D( b8 v$ K2 q& r+ o# G6 D ^$ BUniform coordinate, 均匀坐标
- l! l1 w/ H0 o5 {0 BUniform distribution, 均匀分布$ I- P! n' n# |
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计! ]$ V! ~! F9 V: R
Unit, 单元8 L: |& W& E& x I$ e- |
Unordered categories, 无序分类; ]4 g) ^8 c& Y$ `( c8 v
Upper limit, 上限5 E5 G8 k/ g* r& m8 w" D3 n
Upward rank, 升秩
7 E/ h' U# b5 y- hVague concept, 模糊概念$ O& k: Y# ~- d0 N+ k4 q
Validity, 有效性
6 e$ Z5 u# O, O# w0 XVARCOMP (Variance component estimation), 方差元素估计: h% n/ D$ m, V0 b; }4 F0 n
Variability, 变异性/ D/ t- \8 t7 K) w9 F& a9 c, ^
Variable, 变量0 c- r& t0 G1 H \+ H
Variance, 方差
/ |/ o$ t$ Q0 K5 G; D& h LVariation, 变异% g; o7 J# Y5 j4 f
Varimax orthogonal rotation, 方差最大正交旋转# [, } ?( Q3 ~/ b. ^7 ^* n! g
Volume of distribution, 容积! b5 ?( @( V0 Z6 |
W test, W检验- g% ?1 `) C) Z/ n5 F
Weibull distribution, 威布尔分布* U2 n& [. `/ b1 J1 |0 b
Weight, 权数
( t3 @" R4 `7 C/ h4 Q; j9 h) h: h" rWeighted Chi-square test, 加权卡方检验/Cochran检验
z, `+ |9 g7 |4 r7 F' cWeighted linear regression method, 加权直线回归
3 z3 j: L" O4 }/ ]# G# _3 T2 u7 eWeighted mean, 加权平均数( O# r. f2 E$ d& H* o3 `# H' O' N
Weighted mean square, 加权平均方差 P: s% b2 f& M2 L* H
Weighted sum of square, 加权平方和
# d, r/ I) y% E* ^5 M7 J/ tWeighting coefficient, 权重系数$ M; [' f3 I- C: e. F; n
Weighting method, 加权法
0 w7 z5 c3 n6 l4 cW-estimation, W估计量
. E1 `' h, l3 T3 WW-estimation of location, 位置W估计量
: K( L* q) @: }Width, 宽度& C6 T( |$ F6 |# P7 [/ t) d
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
" o% L0 J+ R4 tWild point, 野点/狂点
1 t1 p. i# y5 d% S3 B4 c UWild value, 野值/狂值2 Z; g5 I5 X: {& H X
Winsorized mean, 缩尾均值
: {, A( }% M9 y4 k9 o `Withdraw, 失访 4 C/ X C3 X% { w) W; J, C
Youden's index, 尤登指数3 F) v- r d6 _' y$ |3 t5 Y4 ?
Z test, Z检验 f) m& S7 e; T& F: b& G) \4 O
Zero correlation, 零相关
6 R! g" _" |3 c, ?; E& A9 MZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
