|
|
Absolute deviation, 绝对离差
! l9 N! t. N: i* L- CAbsolute number, 绝对数7 L e8 m8 E# f& K6 `
Absolute residuals, 绝对残差% p" F; p* u( i8 Q5 c. I
Acceleration array, 加速度立体阵
. S2 ~, |- n8 c7 Y) R) i9 xAcceleration in an arbitrary direction, 任意方向上的加速度
1 G0 h5 Q+ n; |9 ^Acceleration normal, 法向加速度& |5 \7 w1 J2 p! L3 f
Acceleration space dimension, 加速度空间的维数3 s# C+ ~; S' @0 D1 Y" p
Acceleration tangential, 切向加速度! }6 O9 v, n3 @, \% O, N
Acceleration vector, 加速度向量0 h* m; r) c3 {6 ]6 X- ~$ I' z
Acceptable hypothesis, 可接受假设
) Z* T% h/ b ?( m% I0 M# C! FAccumulation, 累积
, a) ]1 j' Q' F$ F8 d3 IAccuracy, 准确度" C+ @" } }: g$ q# g5 {
Actual frequency, 实际频数# p: d: N q% t+ Y
Adaptive estimator, 自适应估计量2 u/ A% `3 I9 X5 d; R
Addition, 相加
% @% M+ V9 @1 mAddition theorem, 加法定理
0 n4 y2 v6 b3 ~* a4 WAdditivity, 可加性
: M3 v* R, w, y$ mAdjusted rate, 调整率
" k5 M: e. e0 B0 p8 r z% {! d7 jAdjusted value, 校正值
( t, a( y# ]% z8 I) N* _# U9 PAdmissible error, 容许误差
4 ]( v! T0 T" s& RAggregation, 聚集性
* E1 x" @/ k& ]( [Alternative hypothesis, 备择假设7 s- t+ D% Y: Q) F
Among groups, 组间) u: O& Y4 l! I; t8 v
Amounts, 总量8 x2 r- ^0 u7 w/ b
Analysis of correlation, 相关分析 f% a2 p; |+ d1 c4 p
Analysis of covariance, 协方差分析
& A; j, v; n0 X3 d4 f3 rAnalysis of regression, 回归分析
' k( i& F& F* IAnalysis of time series, 时间序列分析" @" x: u) s4 K# ?. A: P
Analysis of variance, 方差分析/ @2 K' o7 B2 M
Angular transformation, 角转换
( W3 J- n; \6 g: G% nANOVA （analysis of variance）, 方差分析
6 [$ {& U- Y! u" aANOVA Models, 方差分析模型1 i) P1 P" F3 a+ Y
Arcing, 弧/弧旋
# G& w4 ~) J5 V* h! Z/ o& ~) W" OArcsine transformation, 反正弦变换3 j5 u7 u4 m6 v) j
Area under the curve, 曲线面积7 o8 e8 e8 L; W: |0 T% r& ?
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 - S8 m! \& ^4 \* P9 Q3 U
ARIMA, 季节和非季节性单变量模型的极大似然估计 1 p+ {. _& a9 N" E. t' {/ ?
Arithmetic grid paper, 算术格纸9 G! Z6 j3 W4 c: b4 d, [
Arithmetic mean, 算术平均数
% E& x: {7 `" U- ?1 ?. e: |3 d. o+ DArrhenius relation, 艾恩尼斯关系
% g; ^2 h8 S3 GAssessing fit, 拟合的评估
! y" k( h5 y" x6 l: jAssociative laws, 结合律
& k: c! {) Y! ]0 Y! v2 n; H1 X. KAsymmetric distribution, 非对称分布4 M0 e! o$ T4 N/ L2 e
Asymptotic bias, 渐近偏倚
( Y6 D; L. }$ ~. B2 bAsymptotic efficiency, 渐近效率
+ }6 Z. ` J( V: |4 d/ |& iAsymptotic variance, 渐近方差& A* Q$ c: H- Y; V
Attributable risk, 归因危险度
( f' j! A4 T$ SAttribute data, 属性资料
( @ C) m/ i/ {7 }) z% C; }Attribution, 属性6 o/ e2 R2 |; d/ A6 S ~
Autocorrelation, 自相关
8 R" W2 f' l5 J- e8 ~( S( F( D3 RAutocorrelation of residuals, 残差的自相关
. M! L* c- E: P0 q2 a. S7 uAverage, 平均数
3 F0 M5 m* ]+ V3 H3 j6 BAverage confidence interval length, 平均置信区间长度
8 B+ C% b+ g/ x1 o8 \/ u) h7 `Average growth rate, 平均增长率9 c, h* Z$ G/ k+ d1 C/ g! A, b3 i' B
Bar chart, 条形图2 u) G# G6 }/ z8 ]0 a9 m7 \- }0 j
Bar graph, 条形图$ c. j& B$ O4 c! Y2 i) `8 B
Base period, 基期* U- C! l* u0 t [
Bayes' theorem , Bayes定理
' `' f/ u8 e: G0 sBell-shaped curve, 钟形曲线
0 c. I0 t3 ^: X6 m$ {9 UBernoulli distribution, 伯努力分布 U9 l6 ~5 f0 n( ~( |
Best-trim estimator, 最好切尾估计量
9 O3 ?" K6 [. F- @Bias, 偏性
% y9 K0 N6 M& H4 WBinary logistic regression, 二元逻辑斯蒂回归8 T- s2 B5 X& O5 X3 e* h3 H
Binomial distribution, 二项分布
/ B: M0 I6 j* a! p& @# vBisquare, 双平方! O+ B' }! Z' K2 \0 ]
Bivariate Correlate, 二变量相关
$ B7 O, B+ d, ~6 O1 o0 L4 DBivariate normal distribution, 双变量正态分布
) h& G* K% ?% J5 v, h, tBivariate normal population, 双变量正态总体
; q* A! W8 X% I) T5 vBiweight interval, 双权区间
, S4 U6 d$ c: L3 w3 O% fBiweight M-estimator, 双权M估计量% @/ x. l, L& ~& w
Block, 区组/配伍组3 d: n6 v4 R$ j! C1 f
BMDP(Biomedical computer programs), BMDP统计软件包
9 d2 I0 _ q% B6 Y8 Y0 Y3 X# uBoxplots, 箱线图/箱尾图
. R/ p) d" K! }0 r" e& r4 hBreakdown bound, 崩溃界/崩溃点
9 W8 k+ u9 g$ C/ C- F: |7 Y/ fCanonical correlation, 典型相关
1 I4 y- |0 }3 \, s& d9 yCaption, 纵标目
, u) K; [5 T- E! gCase-control study, 病例对照研究
9 J3 z% Z ~( RCategorical variable, 分类变量8 n6 h. |# E: S+ p& b
Catenary, 悬链线1 I9 B( l+ `% k3 a7 f
Cauchy distribution, 柯西分布
( m. c( E8 L. M0 R8 jCause-and-effect relationship, 因果关系
$ Q3 i4 B3 S+ E$ ^. ^+ b' W3 R2 uCell, 单元7 U7 b) W# g2 L( I6 x" w$ u& B
Censoring, 终检0 [# K$ C1 {! _. Q
Center of symmetry, 对称中心, R5 p, s- j6 z3 B3 K* H5 s
Centering and scaling, 中心化和定标
* {( r8 o; E" ]& W. l* CCentral tendency, 集中趋势
8 r* ~0 v2 A8 a3 W6 M \Central value, 中心值
0 F: g0 M) u$ |9 ^) G+ I$ y- _5 FCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测; c3 j; z# k: F" K0 u
Chance, 机遇
& m' |) N# x; I; m I4 A- CChance error, 随机误差 v% X3 _2 i$ {7 f' l( w6 I* m
Chance variable, 随机变量
3 R' D4 g ^7 s- k1 dCharacteristic equation, 特征方程( L+ m- L8 g6 z# F8 u
Characteristic root, 特征根
, r. }6 o9 }# D; f/ _Characteristic vector, 特征向量
; U( K4 C6 X6 K! |9 jChebshev criterion of fit, 拟合的切比雪夫准则6 w" L# a* ^$ N) s& A
Chernoff faces, 切尔诺夫脸谱图0 h5 Q. H% p- s) v% E
Chi-square test, 卡方检验/χ2检验3 A) H' l5 b' ?/ o. t
Choleskey decomposition, 乔洛斯基分解4 e. D5 ]$ `, u. `) [( I4 o! [ ]
Circle chart, 圆图
, B3 x9 E3 m. m+ _8 CClass interval, 组距
$ `( E/ ?. A* e9 \: d. hClass mid-value, 组中值% q i$ t" E( Z: H( R. ?+ m# w
Class upper limit, 组上限4 y Y& V- w/ s$ _ k
Classified variable, 分类变量1 q* _) d+ e& q/ C. I7 x* O
Cluster analysis, 聚类分析' G+ j5 ?$ Y0 a- K" K0 M+ _( C
Cluster sampling, 整群抽样+ e8 B" c0 H& K7 O+ ?
Code, 代码6 T/ }: {) E7 A
Coded data, 编码数据
' |" M3 U% o1 [+ ACoding, 编码
9 B1 A- s6 t9 T( |6 ~3 a, X- ECoefficient of contingency, 列联系数
$ N/ r2 z+ r1 k) C! tCoefficient of determination, 决定系数* M0 O2 E! `; T
Coefficient of multiple correlation, 多重相关系数, }5 T, n4 {0 N$ J2 t# V+ w0 g
Coefficient of partial correlation, 偏相关系数
: t8 }; b, |, d: J6 M: PCoefficient of production-moment correlation, 积差相关系数
% c* u% f( Z/ J# E2 u: KCoefficient of rank correlation, 等级相关系数
! ]2 k0 s$ s4 P* {) _3 g9 Q6 vCoefficient of regression, 回归系数# `( n! w* n4 C7 a. D% J
Coefficient of skewness, 偏度系数
- K# Y& @* X1 ]Coefficient of variation, 变异系数
8 z! U0 q$ _! JCohort study, 队列研究, f) Y |0 O0 _: a" h# {
Column, 列: p/ I; j+ L# V% N' [5 |' ]# `1 S6 {
Column effect, 列效应 a1 J2 u/ o$ ]8 |& J, g
Column factor, 列因素
% O, s2 J2 l# v. O6 `+ I: hCombination pool, 合并
) A; e2 j/ ~$ yCombinative table, 组合表6 S3 D$ u- n! I
Common factor, 共性因子
- Q7 [; L K: tCommon regression coefficient, 公共回归系数
" t: c+ }2 m) r$ Z% X$ }$ qCommon value, 共同值
* D0 ?& a$ E' H4 {; gCommon variance, 公共方差- `% m1 `8 \( q" o. @" i
Common variation, 公共变异" C m3 p; m. i) x7 |1 k0 ?
Communality variance, 共性方差
2 h* h" g2 W- H4 ` qComparability, 可比性# k% U4 a- d/ }$ H
Comparison of bathes, 批比较0 q: e8 X' q) g1 Y1 B t
Comparison value, 比较值
4 J+ T+ e/ O N! XCompartment model, 分部模型
2 @" ~' J* L+ ?0 A1 cCompassion, 伸缩
! K8 L- A9 N7 k$ iComplement of an event, 补事件
2 H: v6 ]. B6 X% `Complete association, 完全正相关4 g7 f1 K3 i5 }: h! D: B3 v
Complete dissociation, 完全不相关
0 y# J8 M, l- K; M+ vComplete statistics, 完备统计量5 u8 P% _: q% ^$ y( _+ [, E
Completely randomized design, 完全随机化设计
4 H0 H S2 ]& b( @3 {7 @Composite event, 联合事件+ a* m6 J+ c0 ? \) I% z7 D
Composite events, 复合事件% u0 t4 B9 z. |+ U/ s# I9 H7 m
Concavity, 凹性
/ @. W F) n' j% {7 f9 wConditional expectation, 条件期望3 w" w, P. r" R% A& R+ k! q
Conditional likelihood, 条件似然
0 Z$ f2 [$ N' J9 DConditional probability, 条件概率
1 W+ j" ^6 q4 C ~ ^3 F4 i/ k' T* Q7 lConditionally linear, 依条件线性9 o5 G" F" S1 A( u3 K5 h
Confidence interval, 置信区间
" G- q+ v' c0 V" @' H0 XConfidence limit, 置信限! J$ z4 o8 z# b1 P3 h! M u
Confidence lower limit, 置信下限
! V9 g& N: d" h# ~5 j$ }% O' s! TConfidence upper limit, 置信上限
0 l; P$ @3 `) P# m' q! ^5 eConfirmatory Factor Analysis , 验证性因子分析
) D/ Z& L W9 m6 XConfirmatory research, 证实性实验研究
( b5 i% G8 ~7 j- ~& B1 g' ^Confounding factor, 混杂因素0 g9 r* H( t# g
Conjoint, 联合分析
: w" y0 c* r3 u* \! eConsistency, 相合性0 x( k3 `) p/ y1 A T% P" V
Consistency check, 一致性检验" n$ o" a8 w( N% y0 Q `
Consistent asymptotically normal estimate, 相合渐近正态估计8 U8 F5 U, o( U/ L
Consistent estimate, 相合估计
1 X7 f: [/ c( M7 i; k7 j* UConstrained nonlinear regression, 受约束非线性回归3 ^9 h2 L$ [- ]! W
Constraint, 约束
7 Q- O- c( C8 |. IContaminated distribution, 污染分布, Z: j# m1 y* `
Contaminated Gausssian, 污染高斯分布
Q8 n7 u; Q6 _, r1 fContaminated normal distribution, 污染正态分布
6 {1 ]4 {$ ]2 n+ L0 J( S K6 EContamination, 污染
$ G6 }: B6 A" N9 [ {Contamination model, 污染模型+ d) Q* E" W7 }
Contingency table, 列联表, x5 O* ~2 {- I, _
Contour, 边界线
6 l, i! Q8 J0 OContribution rate, 贡献率
+ t3 r+ _( S3 |* L) j5 xControl, 对照
6 l+ |# ^% P( d3 nControlled experiments, 对照实验
" M! s& p; z6 B ~* L5 C; n; H5 VConventional depth, 常规深度( p1 \% g$ N# N+ Y3 e$ I- O
Convolution, 卷积2 h6 U/ S; k7 e( {' D" f: U9 R
Corrected factor, 校正因子. d X2 p8 Y9 y, ~+ r2 W
Corrected mean, 校正均值% c Z( ^( W1 I7 k: j
Correction coefficient, 校正系数
& N0 e* Y; L0 D* e# v; d6 {& E3 }* vCorrectness, 正确性9 A% T9 k: Q- E6 `( R% n7 p' `% N g
Correlation coefficient, 相关系数
5 j' E r7 m$ n4 h, i) ]Correlation index, 相关指数+ F4 J% U9 }+ k5 K1 F$ }
Correspondence, 对应
+ G- A( U; P' U* wCounting, 计数. n9 u: \8 z( R3 H. ]& x2 D
Counts, 计数/频数5 f3 X' `3 i* e+ d5 N
Covariance, 协方差% G5 e, S2 j4 I0 X# i: H* o4 {& Q
Covariant, 共变
' j2 ]: G$ w# P# o0 l4 kCox Regression, Cox回归7 @' _- T6 O* |3 E3 [$ P8 l
Criteria for fitting, 拟合准则
; N6 X- z/ F8 k9 c" e( u5 nCriteria of least squares, 最小二乘准则
$ T) o9 b8 q4 j2 d$ Z( i$ QCritical ratio, 临界比) I! ~, m( k& O% |2 R2 g) j( `
Critical region, 拒绝域6 `+ R( L6 g8 b) \/ t
Critical value, 临界值
% ^8 j2 M* `' ?' s, o6 n! @Cross-over design, 交叉设计: _- K' {' a& s" _: y
Cross-section analysis, 横断面分析
5 U* w8 t- q ECross-section survey, 横断面调查- w1 L3 O& h3 r! M0 S2 m: x) ?( v& t
Crosstabs , 交叉表 4 v, z8 V2 `/ h$ I9 S" i
Cross-tabulation table, 复合表2 T% Y! l& [1 b4 t% k8 `
Cube root, 立方根7 d4 V8 `, a w5 u! e) P X4 }& L
Cumulative distribution function, 分布函数3 |% b. J/ Y5 |0 n. h# F" B& K
Cumulative probability, 累计概率* s$ ]" O) l( X0 A
Curvature, 曲率/弯曲7 k4 I7 l, @- S) [" `0 n; I8 [
Curvature, 曲率* H- K0 Q7 `& |- ]6 p) p
Curve fit , 曲线拟和 - J+ N9 N2 q# w0 k) y8 Z6 L1 Z
Curve fitting, 曲线拟合0 m% f( I0 i8 v1 n6 B0 |/ j6 z6 @
Curvilinear regression, 曲线回归& I! ^6 u* Y, a7 k v
Curvilinear relation, 曲线关系9 l R( n3 Z6 _6 i5 p4 u
Cut-and-try method, 尝试法) a! S. _5 i. y' y' {
Cycle, 周期
a; \4 z+ }3 a mCyclist, 周期性7 K' ~3 h }- r1 ?+ _
D test, D检验
/ I3 |" G+ }2 K. QData acquisition, 资料收集4 }3 t# k6 Y" c; P) a" }
Data bank, 数据库
?9 N8 z ?. [9 R8 y" {3 c1 d2 A" v- u" vData capacity, 数据容量
$ K! F: p' O( n r3 lData deficiencies, 数据缺乏
& i1 Q( v4 G$ R3 rData handling, 数据处理
. G9 V' [: ]& R) x# ZData manipulation, 数据处理
( ?; p* W; O1 b8 ^, [2 kData processing, 数据处理
% R: ^9 h+ j, W9 S `! BData reduction, 数据缩减. q2 F$ c3 q, D$ f% b
Data set, 数据集$ D2 u, L* a+ {
Data sources, 数据来源
4 _$ M$ ]: Y& _" f0 C/ u, FData transformation, 数据变换7 n; J4 X: a6 q- r& a; p; u
Data validity, 数据有效性
2 Z* Z/ f! c5 yData-in, 数据输入! J$ J# m9 D) T: N* Q$ x ~
Data-out, 数据输出
3 @- H; U$ x9 W G( LDead time, 停滞期
5 c v) y. w8 |$ t8 u, k0 ?7 B' I9 LDegree of freedom, 自由度( T# z% {( H' T" P. j
Degree of precision, 精密度3 v, K& G6 _( b0 m6 F9 P# n
Degree of reliability, 可靠性程度0 t; { H3 a; s
Degression, 递减) F8 N* p3 {8 [) q/ T1 O& ?$ r( E
Density function, 密度函数2 j( x' O0 t5 n4 E
Density of data points, 数据点的密度
* E4 I& t5 I+ c* C# k8 d1 Y/ KDependent variable, 应变量/依变量/因变量% k7 O& Y7 A( z2 C9 S$ p
Dependent variable, 因变量
6 I/ r3 n/ ]/ W3 q/ B2 D& j9 `Depth, 深度& E3 B# E; u* @! t: y+ f$ R
Derivative matrix, 导数矩阵) ?+ @9 D4 [( P* `, I& g
Derivative-free methods, 无导数方法! K" {+ f+ }7 h' W( w4 I8 u0 E1 P
Design, 设计3 q* R, N- `% S* \, {- l) v0 E) \
Determinacy, 确定性
# f% v9 x5 R8 ]2 S! X$ o# HDeterminant, 行列式% V1 j* z1 G" C8 F3 S2 j
Determinant, 决定因素
5 j- I8 m9 h& A5 L1 W" P% i9 KDeviation, 离差( w/ X8 h# l3 S6 X m# i
Deviation from average, 离均差 ?$ T* ~/ C- k" B. I
Diagnostic plot, 诊断图. p4 ]! `" \7 a5 v3 w1 i5 E
Dichotomous variable, 二分变量
( R5 M9 N6 }. f! |! n B! ~Differential equation, 微分方程
* n M) d% U9 m0 EDirect standardization, 直接标准化法
, W9 m" k" n. g1 J* QDiscrete variable, 离散型变量
7 u, ~) d( i, O/ x# q2 h$ C( x gDISCRIMINANT, 判断 8 O9 C$ W: n8 x9 O% q
Discriminant analysis, 判别分析( y8 }0 W" l2 C( K
Discriminant coefficient, 判别系数' h) Q1 U% D* r3 O3 O' h. u
Discriminant function, 判别值( a: \! U, K6 z. N) L
Dispersion, 散布/分散度
6 V" h4 @* g, I6 aDisproportional, 不成比例的
& Z6 ]( A8 R) N% V1 HDisproportionate sub-class numbers, 不成比例次级组含量
* d- }5 {7 `) R5 p" ^1 E: w4 tDistribution free, 分布无关性/免分布
# f* i) s1 z; X3 R: L# FDistribution shape, 分布形状
/ ^4 R+ J3 K: R/ a8 h; sDistribution-free method, 任意分布法
. p9 d. N' P9 _2 N# W7 X* M% i8 L. Y* ^Distributive laws, 分配律+ H" v7 u I8 r$ C. ~
Disturbance, 随机扰动项: o, e0 i) t7 C ^# {
Dose response curve, 剂量反应曲线
2 ]6 M: ~4 }, o# k: B5 vDouble blind method, 双盲法
/ \, O7 w Z; dDouble blind trial, 双盲试验
4 S) S+ _- |! c6 P7 }- f) ]% `: J- HDouble exponential distribution, 双指数分布% X2 r. n4 y0 j! N, G
Double logarithmic, 双对数0 r/ W. p1 ^! l H* X( w
Downward rank, 降秩
. E5 U1 v3 V$ f& p5 L" }' `Dual-space plot, 对偶空间图) y- I0 f5 Z3 R! Y
DUD, 无导数方法
* q6 p$ Y0 Q/ ]. s nDuncan's new multiple range method, 新复极差法/Duncan新法; k3 w0 M/ C, J% R1 {" c9 ?
Effect, 实验效应( h. D, ?* }* L
Eigenvalue, 特征值% t7 q) z6 t& O& M: T, G" E. O, b
Eigenvector, 特征向量
~* f+ p& Q5 J1 f) ^) p) h4 EEllipse, 椭圆
3 P! F6 I F3 A' W7 d+ lEmpirical distribution, 经验分布3 B, W2 [2 l, `- u5 Q
Empirical probability, 经验概率单位
/ r( Y" [' A/ @% QEnumeration data, 计数资料
4 c5 C, _8 V9 S: k' ?Equal sun-class number, 相等次级组含量, x" _' m6 q2 q: Y
Equally likely, 等可能
w/ U V9 w! z C) HEquivariance, 同变性
$ W+ d ^* k* k* H6 g. \Error, 误差/错误7 G) y; b2 t1 I& X- v4 @
Error of estimate, 估计误差* a- }0 M( G" n: Q( M
Error type I, 第一类错误! x- |0 j4 t+ i
Error type II, 第二类错误/ o1 \" x2 n s
Estimand, 被估量' c! Z! M5 r1 T, Y$ D& B& O9 |
Estimated error mean squares, 估计误差均方) l; Q( ]7 [0 w+ j+ J! N8 N( q+ P
Estimated error sum of squares, 估计误差平方和
. W0 u! O9 q7 C. T9 \* w' ?Euclidean distance, 欧式距离: W( r& O. S9 g9 ?
Event, 事件; {0 R8 [, H0 M
Event, 事件
9 a3 [2 V! D+ U M5 K1 K5 ?1 DExceptional data point, 异常数据点
* b J# x4 {8 P- [* X$ P; fExpectation plane, 期望平面0 o$ |/ w N* G+ c3 Q8 z1 g% \
Expectation surface, 期望曲面* c& p4 n2 {8 o- |2 {1 o( @. _6 `$ c
Expected values, 期望值
0 ]) P- o, j, DExperiment, 实验 N- }4 C8 L, [' `1 V& P7 u5 F) m
Experimental sampling, 试验抽样
7 U4 ~- I" I8 c1 M5 O. I9 Q$ [1 NExperimental unit, 试验单位; r4 k; A ^, D u
Explanatory variable, 说明变量6 y. \5 `/ A7 k0 t. m8 |
Exploratory data analysis, 探索性数据分析
" d; K! }) `' O4 i4 ]Explore Summarize, 探索-摘要& |0 r+ ]" [4 @! A; O
Exponential curve, 指数曲线8 o2 P3 `, Y0 W. N
Exponential growth, 指数式增长0 G% f7 P5 u5 ?! d
EXSMOOTH, 指数平滑方法 ' x, S* Z8 ~8 P- p: C
Extended fit, 扩充拟合4 q( X' B- ?' W% R, E
Extra parameter, 附加参数% G5 H/ D9 O* D8 q
Extrapolation, 外推法% R4 ^* k- c5 j
Extreme observation, 末端观测值) Y! T- s, ^& k
Extremes, 极端值/极值5 q3 S8 S0 ?7 ]3 N5 w$ B; X
F distribution, F分布
) `8 I7 C! i* ]. y" D$ H5 ^4 ~F test, F检验/ y. ?( Y, s, j& ~0 b
Factor, 因素/因子& N; n3 V+ s; s8 l
Factor analysis, 因子分析% q/ e+ v$ u3 g) h
Factor Analysis, 因子分析
& i- e$ z. T9 M2 RFactor score, 因子得分
* W% m% }, n- _$ xFactorial, 阶乘
4 L1 B" ^1 s; A" LFactorial design, 析因试验设计( I' J; W: h n) ^) @' z4 u( L% N
False negative, 假阴性- f: f8 B4 J, M; w' C, m
False negative error, 假阴性错误
# Q0 c1 B5 T5 v8 z4 DFamily of distributions, 分布族 H$ w" F5 f* h4 k
Family of estimators, 估计量族& c: k; `0 k4 W* }" S" E
Fanning, 扇面
& b/ U o. }/ f- Z1 I5 ?Fatality rate, 病死率
3 }# s6 v: l" }* C( f* xField investigation, 现场调查# q: ?+ v( \2 H0 _+ M( [$ B0 ?5 I
Field survey, 现场调查( D5 H2 }1 {3 x* e6 B
Finite population, 有限总体
4 D9 ~% {0 |1 n, k+ CFinite-sample, 有限样本' I3 S' l M6 R8 e: q% |
First derivative, 一阶导数" [, F7 d: C9 x$ \) w. t) I
First principal component, 第一主成分4 t4 n+ P- w" ~7 I- E
First quartile, 第一四分位数
% p: @3 F. r+ {Fisher information, 费雪信息量
) V. }% r& x( @* i! JFitted value, 拟合值3 E3 o! v, Q* }8 M5 ]; v7 d
Fitting a curve, 曲线拟合
' ]. o& [5 \$ r/ ]4 hFixed base, 定基
; ~' @& R8 m1 c/ `! X. _6 v6 ~Fluctuation, 随机起伏. F+ O/ @, S: D; p* l2 q
Forecast, 预测
7 T1 z3 N' t! mFour fold table, 四格表
6 F: s' D" i% {8 o3 w- KFourth, 四分点
( {: E6 f9 ^0 _: q! YFraction blow, 左侧比率- J1 o3 A5 [! _0 m
Fractional error, 相对误差
9 s6 ~8 t. p% a" [) L3 S& dFrequency, 频率
# v7 L# k$ R; G% eFrequency polygon, 频数多边图4 T6 T: |* @$ r. Q x6 T& D1 l" t
Frontier point, 界限点
: ~6 _( V& @ k9 V7 X/ D; ]4 r- b4 JFunction relationship, 泛函关系/ J( \6 p( }# u9 c% u
Gamma distribution, 伽玛分布+ N% ?% j* c$ Y& n
Gauss increment, 高斯增量
: j$ w$ ~9 G- z. B4 SGaussian distribution, 高斯分布/正态分布# s* W1 X' a1 P" |# a9 F
Gauss-Newton increment, 高斯-牛顿增量
5 z* H3 z) y9 ?5 b! `: Y Y* t, jGeneral census, 全面普查
3 }6 D2 u, P4 A6 D5 dGENLOG (Generalized liner models), 广义线性模型 ! U+ }! \( X: ]7 ~) w! { l
Geometric mean, 几何平均数$ T7 g5 M- m0 F6 d* k. T; w
Gini's mean difference, 基尼均差
6 @/ f/ ]8 a4 J- k, \GLM (General liner models), 一般线性模型 1 R* z6 N/ t& b b9 e( S8 y' `
Goodness of fit, 拟和优度/配合度5 [% `- H; V& E( ~! s, Y
Gradient of determinant, 行列式的梯度
+ |2 g9 N! H j e& ?! m2 |( sGraeco-Latin square, 希腊拉丁方
: \; F% ^+ G# l! r7 kGrand mean, 总均值
6 x9 m5 x/ Q1 u6 ]Gross errors, 重大错误4 ~1 f: n6 V3 n# B
Gross-error sensitivity, 大错敏感度
+ G) A) {% q/ @: aGroup averages, 分组平均( I- i3 s$ u L- c5 c' [
Grouped data, 分组资料
1 ^0 Y1 D# {* yGuessed mean, 假定平均数
: f/ I! ~& Y0 G) J" y6 G7 J5 C5 dHalf-life, 半衰期
3 k: Q& r9 X% c B; yHampel M-estimators, 汉佩尔M估计量* }5 W. n* q7 s$ }7 c+ o2 F
Happenstance, 偶然事件
, N3 ]% I! }/ {7 H5 hHarmonic mean, 调和均数% q# w: {) I5 x
Hazard function, 风险均数, E% w8 h) H# U& g! K m" ~
Hazard rate, 风险率
8 x4 G! |/ n! cHeading, 标目
8 ]: ~# r4 J, I/ ~7 w+ C9 \Heavy-tailed distribution, 重尾分布- \5 X/ I/ _- [- u
Hessian array, 海森立体阵
& x, R$ R- E3 ^6 C5 N# mHeterogeneity, 不同质, Q o( T3 _% V5 \% w
Heterogeneity of variance, 方差不齐 5 b9 X9 v% p' e& @" Q3 h M
Hierarchical classification, 组内分组
1 W! z5 z3 R! \% x a8 pHierarchical clustering method, 系统聚类法1 i7 G; ~" Y. g9 ?2 @/ X
High-leverage point, 高杠杆率点
# V2 D. O! ]* z! H" [0 A' Z3 UHILOGLINEAR, 多维列联表的层次对数线性模型 B1 B8 w/ x. v" H7 P
Hinge, 折叶点9 U2 B r" r1 @2 T
Histogram, 直方图* Y/ g2 p6 j: u0 R0 x0 h
Historical cohort study, 历史性队列研究
# {" |1 Y% l; Q8 k3 L, CHoles, 空洞 h: g" u. z% V t9 J* ]" I9 i
HOMALS, 多重响应分析8 l- R* h& r5 C, {: b0 `
Homogeneity of variance, 方差齐性
0 v$ l5 q' R: e) Z0 h& f5 k5 q2 EHomogeneity test, 齐性检验
6 ?7 o7 }0 {0 e3 x) l4 ~Huber M-estimators, 休伯M估计量
9 j# q( P6 x6 @1 E- ^' Q2 mHyperbola, 双曲线8 H8 _4 K a6 u' `
Hypothesis testing, 假设检验 D0 c7 w6 N {/ e7 ?" R4 m3 ?3 H
Hypothetical universe, 假设总体
( W9 l2 F) G0 N% g5 [* S/ xImpossible event, 不可能事件4 C3 D8 y" `0 Y6 j6 V. O1 a$ Q" S; h. w
Independence, 独立性
" I4 R0 ~ ?2 @2 l/ B; iIndependent variable, 自变量
& z# v$ {9 H% D% iIndex, 指标/指数
$ k; m4 D, P8 E) ~2 ` T/ H8 i( wIndirect standardization, 间接标准化法; {6 L, ? I/ L/ ?1 ^6 a, p
Individual, 个体2 i" q# ?5 L( A) T
Inference band, 推断带
4 ]+ |; {: w- T% ^6 a( ^Infinite population, 无限总体
/ H( _4 T( m! p1 @* HInfinitely great, 无穷大
) i8 E' ~1 U1 K2 u7 L1 AInfinitely small, 无穷小* o; A/ |) G" t p9 d
Influence curve, 影响曲线
2 m4 c% @/ G V F0 P! KInformation capacity, 信息容量8 r9 Y) v! n" S/ r' E! f7 p
Initial condition, 初始条件
) m; ?1 R6 w; j3 d" X) oInitial estimate, 初始估计值2 u% S# V# `2 B% C1 U" D
Initial level, 最初水平
U0 L* s$ o- L8 `$ TInteraction, 交互作用
, {# c8 x: X0 Z) a$ U" u" ^8 eInteraction terms, 交互作用项5 X: z# _5 H5 F& a' V
Intercept, 截距
; [# x( E2 Y6 l5 I0 [Interpolation, 内插法
- e" _* ^, J8 o, X' NInterquartile range, 四分位距
| ^$ u6 E$ _! x* xInterval estimation, 区间估计
- S4 B+ V$ g+ `8 A6 [Intervals of equal probability, 等概率区间
, ?' C# u; `6 [7 q/ f% FIntrinsic curvature, 固有曲率
4 z6 P/ s' |# z+ G6 \Invariance, 不变性
+ A3 y* q9 r. D7 d/ q) PInverse matrix, 逆矩阵0 P# f+ P, S1 b; j" d; K( K9 g
Inverse probability, 逆概率( G; C% e. H$ Y$ O
Inverse sine transformation, 反正弦变换4 Y! g! Z! u R# O3 p
Iteration, 迭代
( I& i1 ]; B& Q; `Jacobian determinant, 雅可比行列式
6 t. N& F5 j+ s) O( RJoint distribution function, 分布函数
5 u$ e8 m3 z3 |# m9 i# [3 IJoint probability, 联合概率
$ o5 @ i6 k( XJoint probability distribution, 联合概率分布5 }, U. K& A8 u5 \
K means method, 逐步聚类法
9 |4 _+ }' }+ u/ |4 VKaplan-Meier, 评估事件的时间长度 5 ]3 `8 N) Y8 G$ p5 c7 w: J- k/ z1 e* ]
Kaplan-Merier chart, Kaplan-Merier图
/ v# r+ w; U& m% ^' ~1 ^" |: nKendall's rank correlation, Kendall等级相关3 C0 y8 }' H! n) ^' D( }* x
Kinetic, 动力学7 U& G! ^* T! ?" y% a
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
' n0 b" z5 ?* v0 eKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验! C* e- E# H3 ? V
Kurtosis, 峰度
% @/ q( X8 T) y& c- E+ {7 H% ^Lack of fit, 失拟& `1 j) k4 H: r& L. Q9 p
Ladder of powers, 幂阶梯
O9 F6 g/ l5 p LLag, 滞后
9 H; X6 C/ T ~ f) yLarge sample, 大样本
4 f7 i' a7 q; B8 N; j1 C9 z$ N9 `Large sample test, 大样本检验
; b, L( X* t) iLatin square, 拉丁方+ t0 {3 S# S' F! ^0 r( N, s
Latin square design, 拉丁方设计4 K: G" t- t# `/ K8 H
Leakage, 泄漏
( y1 c/ Y- ?9 HLeast favorable configuration, 最不利构形6 v8 p5 d9 F( @% u0 Y7 n' {2 E
Least favorable distribution, 最不利分布
% {9 q2 T" D% u$ F1 K7 j8 |Least significant difference, 最小显著差法
' q" F# u2 t9 i( y! FLeast square method, 最小二乘法
0 m+ Q, ` w: I, q8 ~: rLeast-absolute-residuals estimates, 最小绝对残差估计
- D9 S/ _- \# f/ F8 N/ f BLeast-absolute-residuals fit, 最小绝对残差拟合
' T6 p" X0 h( s5 ~Least-absolute-residuals line, 最小绝对残差线
2 K1 h3 ` g; Y0 h+ lLegend, 图例! {- d- l0 e- t4 p, n" ^: j
L-estimator, L估计量
( X- ?: q$ c6 q4 N, o) v4 h4 PL-estimator of location, 位置L估计量
# _5 L4 x8 d! \: ZL-estimator of scale, 尺度L估计量9 [- K, D V, u
Level, 水平
5 F9 S+ Z9 O$ I+ ?Life expectance, 预期期望寿命6 z% A3 j" B% E. Z# D2 m2 ?( N
Life table, 寿命表
$ n' i+ Q6 u! X6 \2 R- ZLife table method, 生命表法, C0 A4 q. {6 F4 ~ e2 h1 L2 x J
Light-tailed distribution, 轻尾分布
1 ]: \: A" G$ ^" r4 ~0 bLikelihood function, 似然函数( y$ ~+ R9 V7 j
Likelihood ratio, 似然比) V. b' w/ N& m3 l
line graph, 线图7 D, S' s" _" q3 N
Linear correlation, 直线相关; T8 y, K# q) v/ L
Linear equation, 线性方程
% D3 O9 I9 b. I& iLinear programming, 线性规划
) d0 j: a+ ^: x7 K/ NLinear regression, 直线回归
& Q, z% o/ j) yLinear Regression, 线性回归, L" N; z L3 R" z+ [
Linear trend, 线性趋势' b& Z& ~1 P0 u" \
Loading, 载荷
: H3 _9 V1 Z* I$ K) L0 c5 xLocation and scale equivariance, 位置尺度同变性
6 l# \0 p H$ F& y; ILocation equivariance, 位置同变性4 M9 i& r' Y4 m! B/ F
Location invariance, 位置不变性! Z; z8 W$ s L* _# i% \9 @
Location scale family, 位置尺度族
8 j! I2 {& }, V; r; YLog rank test, 时序检验
1 I' k! y! P, s& U% SLogarithmic curve, 对数曲线
6 U( K+ z3 s; c# x1 u- V' b7 TLogarithmic normal distribution, 对数正态分布
! x) U( M# v. ?5 V% @Logarithmic scale, 对数尺度
1 ?/ \0 j2 u) f) a# c6 o$ V1 wLogarithmic transformation, 对数变换$ P [6 L! N [: z, F
Logic check, 逻辑检查
) \) b" v2 H9 W: U9 V dLogistic distribution, 逻辑斯特分布
8 G8 x; P" i( z6 F! P/ b8 C4 `$ oLogit transformation, Logit转换5 w* y( y6 D3 G3 T& K$ b3 b$ [
LOGLINEAR, 多维列联表通用模型
' H- o+ e/ t+ z+ j7 r2 E- dLognormal distribution, 对数正态分布
% v! G" _8 P- G% [Lost function, 损失函数
% v H0 Y8 y; g3 T6 ?Low correlation, 低度相关
! P$ K+ z' r' d1 h* u$ rLower limit, 下限1 [. H. m: ^( ?4 L& ]0 x) x' }; t* f
Lowest-attained variance, 最小可达方差+ Q( d2 i% |+ A, ~* A* Q
LSD, 最小显著差法的简称" B) b7 ?) `. Q4 `
Lurking variable, 潜在变量
* U# r. Y5 I" Y* X. y& l5 V, TMain effect, 主效应' b2 Z" t% X8 r Z- n9 I
Major heading, 主辞标目' _ Z; n D$ s9 v' t. O
Marginal density function, 边缘密度函数
* {5 L( y$ q# |2 @7 o( ?' qMarginal probability, 边缘概率& f; ~$ M" o8 b8 x7 j' Z2 ^1 ^
Marginal probability distribution, 边缘概率分布5 Q* X U% D6 B+ q& j
Matched data, 配对资料 F1 o" c) X+ ~% R2 d" M! N
Matched distribution, 匹配过分布
- U% B7 J2 D$ K8 m1 yMatching of distribution, 分布的匹配
! e8 Z: W% x. E gMatching of transformation, 变换的匹配" { s: p# @$ j. W" G+ Z# X
Mathematical expectation, 数学期望4 P" t1 n& E9 e, g& c; B
Mathematical model, 数学模型* S; ~# |& w: b$ m) I3 Z
Maximum L-estimator, 极大极小L 估计量$ i5 W. O+ w/ c7 M
Maximum likelihood method, 最大似然法
# o" Q5 ~/ N+ N3 V2 k1 F7 rMean, 均数& {* \9 g' G, o% j# |
Mean squares between groups, 组间均方
/ j% l* C8 x) F/ sMean squares within group, 组内均方; D$ [/ I! W2 E/ A, R6 ^) D- |
Means (Compare means), 均值-均值比较
/ u" Z; r) }) L% g& [, cMedian, 中位数5 v, i+ k. Z7 n
Median effective dose, 半数效量
: c# a5 `1 k& d4 C2 SMedian lethal dose, 半数致死量* `" L! W9 r$ w" _# }; z
Median polish, 中位数平滑
4 J6 b! \) x: D" ]5 ]/ @Median test, 中位数检验) R- r, u& O- B9 W L) U# Z
Minimal sufficient statistic, 最小充分统计量" Q* N1 @' Y7 g( c5 {# g* Z
Minimum distance estimation, 最小距离估计# J% q: I: N% s4 y7 w: O
Minimum effective dose, 最小有效量
3 z5 H; e; _9 C: u8 s" g qMinimum lethal dose, 最小致死量
: d- d0 W. U. ?+ Q8 dMinimum variance estimator, 最小方差估计量
$ U1 G; O: w& H( x$ FMINITAB, 统计软件包6 ^4 ]2 L; c2 n- I+ d0 \( ]& d4 j: e0 g
Minor heading, 宾词标目( a [* T5 h x
Missing data, 缺失值
# {" K1 | W2 Q5 N) c, l. YModel specification, 模型的确定
* J9 E: [0 U, i0 yModeling Statistics , 模型统计
3 R% t5 Z K8 |+ ~- {( E3 AModels for outliers, 离群值模型
$ Z$ n4 V: |7 o4 L+ ?8 ~Modifying the model, 模型的修正
- n) ?+ X- q0 Z |! [Modulus of continuity, 连续性模1 j% c8 Q. ]6 e
Morbidity, 发病率
" [# \# H' o. t7 _Most favorable configuration, 最有利构形6 ~+ M% c& q( M1 k6 Y `
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
- M7 L% n# ]* ]& ~+ [% LMultinomial Logistic Regression , 多项逻辑斯蒂回归5 \ F* B- o& I; I8 m' `+ Z- q
Multiple comparison, 多重比较
$ h3 ]" p+ W) \; I- U+ TMultiple correlation , 复相关1 D$ p( k2 E" t
Multiple covariance, 多元协方差
+ L8 B( D* P( y" q3 EMultiple linear regression, 多元线性回归$ F% _1 k3 }, I C0 k1 l/ W
Multiple response , 多重选项
- r- y+ f: C# _% T: ~' B( R" f: ~Multiple solutions, 多解9 F$ }: z, Q' U) `
Multiplication theorem, 乘法定理( o8 p* e, w8 F6 V0 D
Multiresponse, 多元响应
* }) }+ a' Q& Q8 R+ @. wMulti-stage sampling, 多阶段抽样3 @0 T& Q, Q3 ?$ D* ]) `6 u% s
Multivariate T distribution, 多元T分布
/ `1 d, L/ a( w ?$ _5 F$ E6 z6 R5 cMutual exclusive, 互不相容6 w+ ^; R/ A( F6 `* K) z
Mutual independence, 互相独立
' c* I6 g' c! s4 F, h! pNatural boundary, 自然边界
) U, W3 K& r l$ [3 \+ T2 VNatural dead, 自然死亡+ {- ~" _% S k& v; O, Q
Natural zero, 自然零) [4 r8 J4 ^7 @2 j7 q! i5 @
Negative correlation, 负相关
9 U" M6 a) C% \: A9 o# @6 x" A. xNegative linear correlation, 负线性相关5 f/ j+ v6 D4 o+ p+ V/ z0 l, m2 S8 S
Negatively skewed, 负偏
& P6 R3 }- ?( P$ M4 ^9 RNewman-Keuls method, q检验
) H6 [' E6 `/ y7 A% D) Z* Y/ nNK method, q检验
0 a8 d( |/ s8 \% f9 P" \7 Z6 iNo statistical significance, 无统计意义8 ?1 S9 n1 ?0 e# }
Nominal variable, 名义变量# c9 N2 ~9 t* W0 P0 p9 R9 ^2 P
Nonconstancy of variability, 变异的非定常性9 F" b9 t/ K9 E: X" D: C: X9 \% E
Nonlinear regression, 非线性相关% ~* p0 X7 X- d/ s6 a b4 K
Nonparametric statistics, 非参数统计
7 j n6 T9 f# A: n2 W& hNonparametric test, 非参数检验2 e/ T. o% Z+ @
Nonparametric tests, 非参数检验
4 k, D, K; `& ^8 e' qNormal deviate, 正态离差. Y- H5 C- Q" p8 t& s
Normal distribution, 正态分布' U H# i& q( G; [9 \& ~
Normal equation, 正规方程组
7 m% P. K. K/ S2 kNormal ranges, 正常范围
; ^: m1 N& Y' TNormal value, 正常值
' V* K" K; R. A) K' N* TNuisance parameter, 多余参数/讨厌参数
# t! q$ E! r. o+ a8 ANull hypothesis, 无效假设 ) v0 }5 { R6 W3 i! x* Z1 _: N
Numerical variable, 数值变量8 _" s5 {# h. ?' G+ n2 N
Objective function, 目标函数
9 ]8 }7 n% y$ q. mObservation unit, 观察单位
4 H0 B0 C* z0 |' J, _Observed value, 观察值: r% w( ~) Z* K; i
One sided test, 单侧检验
u! ?7 g7 C+ q: {) wOne-way analysis of variance, 单因素方差分析
$ O1 q: W! j w, BOneway ANOVA , 单因素方差分析
- n4 s( W' G, u6 p! P- N/ S5 }Open sequential trial, 开放型序贯设计
8 j3 R) t, T" X/ r' ~3 VOptrim, 优切尾) ]+ m4 Y9 U4 w7 l9 F" }
Optrim efficiency, 优切尾效率% T6 o/ _ g R
Order statistics, 顺序统计量, v* Z6 M. E! F
Ordered categories, 有序分类
- i& m, v+ Q, h" SOrdinal logistic regression , 序数逻辑斯蒂回归6 T: \$ A4 l! H4 M5 s) Y
Ordinal variable, 有序变量7 Z Y4 N' A, ]& g! I" V
Orthogonal basis, 正交基
% q* s( G7 u; O4 R0 K9 g. `Orthogonal design, 正交试验设计
3 J9 N0 T" V- \. M) ?Orthogonality conditions, 正交条件; t$ p3 f3 E+ }4 }+ _" f) _0 c
ORTHOPLAN, 正交设计
8 K) y% R! ^% i* l$ y2 |Outlier cutoffs, 离群值截断点
; J0 l0 T6 k2 n1 X6 p* t* z; P. rOutliers, 极端值! i* }+ U: A8 {4 g2 Q& {/ k" b
OVERALS , 多组变量的非线性正规相关 1 E3 o; U# N. _# V2 W7 n% E
Overshoot, 迭代过度
9 V" v+ n0 z6 y! W% M9 O% D8 oPaired design, 配对设计
/ M) r0 M. Z9 ~( @Paired sample, 配对样本) o& G9 S2 ]% u
Pairwise slopes, 成对斜率( y: m0 _( x. l8 F' K
Parabola, 抛物线
( J- `( T# b7 p, eParallel tests, 平行试验
7 S. M- g) w9 P- R* u% \Parameter, 参数
# I- Z7 w3 c+ h8 z" s$ q/ p& UParametric statistics, 参数统计
6 f: V/ N3 |, U; H) ^6 ~6 zParametric test, 参数检验% _; X: R) N7 b" y2 R
Partial correlation, 偏相关
: L" h$ @8 a! |. R+ k4 ]Partial regression, 偏回归( u: z3 e. e1 m( z# P0 g
Partial sorting, 偏排序
( m. e2 m, R9 J' q' f8 DPartials residuals, 偏残差: ^1 E7 B; q6 l5 T( ^
Pattern, 模式/ G8 w# D; R( C( p9 V0 R
Pearson curves, 皮尔逊曲线
7 G4 V: U0 k. iPeeling, 退层5 E) L+ Y4 J, ?9 E
Percent bar graph, 百分条形图& a5 c1 t4 e- e% v& H0 ~( u1 p
Percentage, 百分比
3 v& s. S! N, `( e5 `; C6 F4 @Percentile, 百分位数6 O" {6 u% h1 _( }* x$ u l
Percentile curves, 百分位曲线! d! D; Y1 A. t- Q% q% v
Periodicity, 周期性
. U, g' _7 Q3 l" V8 @$ ]Permutation, 排列- l3 U+ o+ l7 U; J/ z
P-estimator, P估计量. H1 R* z- L3 |7 u- t9 J* z
Pie graph, 饼图5 P+ m8 H' f2 {) u" M, K
Pitman estimator, 皮特曼估计量4 _( b. Y! k. U, |5 U
Pivot, 枢轴量
3 _+ o2 ]% n" Y2 F0 E) w) |9 BPlanar, 平坦5 C2 ]0 i- E; d9 k5 @) z) T, c3 O
Planar assumption, 平面的假设0 O% t/ a3 n2 Y8 `" M/ l/ g+ J8 i
PLANCARDS, 生成试验的计划卡$ `- M. t8 |6 ]- a7 y2 w
Point estimation, 点估计( N& q: C5 T! W3 J7 `" z
Poisson distribution, 泊松分布
7 p: }6 F! n8 iPolishing, 平滑
, b$ L5 Q; y) k: @8 yPolled standard deviation, 合并标准差
+ Z0 a% T- f# q4 B. tPolled variance, 合并方差2 a& H' j' p7 c
Polygon, 多边图0 j' B) b4 h, Q! u" k" r
Polynomial, 多项式+ t; x8 A2 q& L7 P4 I. y
Polynomial curve, 多项式曲线+ c; Z3 N* c" n- h( _0 O5 ?# \
Population, 总体" P2 T& m" ]7 b
Population attributable risk, 人群归因危险度
0 E8 }0 t# }* k, e% [Positive correlation, 正相关+ q7 S0 a7 U: ~. K, u7 s
Positively skewed, 正偏
8 g- J7 C. B: N# YPosterior distribution, 后验分布0 e# S+ n n2 R: a) r7 Z9 O
Power of a test, 检验效能. f/ p: _+ R D$ |3 ?
Precision, 精密度
( ^. e+ e( q6 p4 |% RPredicted value, 预测值' d1 l$ w+ P8 Q) w2 a2 {" m* ?
Preliminary analysis, 预备性分析
" o3 a" k, @$ m, NPrincipal component analysis, 主成分分析
H6 a7 w! P" i0 q& J, wPrior distribution, 先验分布
6 M. Y; ^8 |3 w- t& u, PPrior probability, 先验概率
9 G0 F4 s0 |) a. [% i, C1 e' _Probabilistic model, 概率模型4 r# z6 B& B: A4 q. ]
probability, 概率
2 v8 U( A: R5 s! CProbability density, 概率密度
h! s A* t! |- ~8 GProduct moment, 乘积矩/协方差
3 \6 R0 b% I0 J5 ?+ n, KProfile trace, 截面迹图3 ~9 p" L2 H' R; ~3 Q! i+ t
Proportion, 比/构成比
3 e7 f/ u6 @" T s; C: X4 |8 p1 P. LProportion allocation in stratified random sampling, 按比例分层随机抽样2 z4 J/ g$ T) F2 y
Proportionate, 成比例
* J9 Y1 K$ m( ~Proportionate sub-class numbers, 成比例次级组含量0 K+ @% K* C; ?9 E
Prospective study, 前瞻性调查
! g6 V! q0 c( s0 c# O* i+ }: _7 NProximities, 亲近性
8 B8 O8 Z; L5 ?. [2 |; _2 wPseudo F test, 近似F检验 Z( ?7 ], d/ X4 L
Pseudo model, 近似模型0 A8 I$ j% B! R) A7 \3 v2 l0 \3 G
Pseudosigma, 伪标准差
' t, s( @/ P$ l, ` EPurposive sampling, 有目的抽样" q" {% ^7 L4 x+ W8 Z5 t2 \" I
QR decomposition, QR分解. G/ d6 l! \8 F/ M
Quadratic approximation, 二次近似
4 H6 H+ p! j' K: z5 XQualitative classification, 属性分类
% E- @! H9 q. {& s1 A" G/ A( ]Qualitative method, 定性方法( a& ^; `* ]( y% i
Quantile-quantile plot, 分位数-分位数图/Q-Q图2 ^6 t4 E2 s+ {
Quantitative analysis, 定量分析% ~. q6 z, |2 h. h8 ]$ o
Quartile, 四分位数3 r, N$ M8 A3 p# ~% E& `
Quick Cluster, 快速聚类
3 F G+ v3 \ ^3 [& tRadix sort, 基数排序
3 L8 M6 w$ U" ^" f4 ]) r: [, fRandom allocation, 随机化分组
$ [) M7 ?' j) f/ o! ^Random blocks design, 随机区组设计7 r0 ^, U- D# n5 V! c. L
Random event, 随机事件
' x2 Q2 y* w+ B; F% ]5 QRandomization, 随机化
) g1 v9 R& `3 u* P: ~/ `Range, 极差/全距
l. T4 V8 q# e2 ]1 B& ~% ]Rank correlation, 等级相关" K/ {$ d& W3 e1 ?& n
Rank sum test, 秩和检验' W7 Q- L- I& l: y% g- D2 ~
Rank test, 秩检验
! |, a1 ]2 O1 l2 s: f3 W( B! YRanked data, 等级资料
% @1 x+ p2 L; b6 |# y) M% \$ P' q# \Rate, 比率# a' ~8 N; ^ R! F) n
Ratio, 比例
* w. e) s( D" r* aRaw data, 原始资料" ?/ O% @9 M( C( ] x3 P- i
Raw residual, 原始残差 ~2 R) N/ F- `0 w$ q- P" L
Rayleigh's test, 雷氏检验 i; j8 }. q2 `. W% y: s& N
Rayleigh's Z, 雷氏Z值
4 `5 _4 u5 x# x8 iReciprocal, 倒数
% E) D( E0 S4 R' }Reciprocal transformation, 倒数变换
5 H4 y6 V$ y- G. }Recording, 记录6 w0 q0 M9 U: M$ q+ {
Redescending estimators, 回降估计量/ [0 x* W) Q2 ?% G
Reducing dimensions, 降维' m" n1 H( ^' _7 N4 n6 x- R, u
Re-expression, 重新表达$ {+ ], ?, R$ l) V2 N/ w- T2 E. j
Reference set, 标准组4 y& r8 X6 F% D+ a! {
Region of acceptance, 接受域
) D# s4 T/ }* \8 Z- I6 D MRegression coefficient, 回归系数
5 P' g2 v" |: Y/ t- Z3 `7 b" VRegression sum of square, 回归平方和; t' U! n5 @* w0 l* L* h" d
Rejection point, 拒绝点( _4 |. l1 P# [% I
Relative dispersion, 相对离散度
& I6 ^5 m; t8 gRelative number, 相对数
, i, b4 Y% x F3 dReliability, 可靠性
* r5 G: m9 |/ J% U7 ~2 }Reparametrization, 重新设置参数
4 F7 o8 w5 x/ t b: I% ZReplication, 重复5 |% j }! Y6 I5 x
Report Summaries, 报告摘要
7 g/ n4 M4 `, C# ]% ~" xResidual sum of square, 剩余平方和
! m R( }3 H4 g! L; | xResistance, 耐抗性
- O; w# j- J* `2 B; HResistant line, 耐抗线
1 r# P! Y, p4 J" p7 T2 AResistant technique, 耐抗技术
+ E8 r8 J7 v* B* g. h B8 Q3 L! @R-estimator of location, 位置R估计量4 R3 @$ f1 [% K% T
R-estimator of scale, 尺度R估计量
% Q0 F2 f5 B6 Z \0 ?( q' BRetrospective study, 回顾性调查7 f, P6 A1 C4 ~1 O2 h; L+ S' Q
Ridge trace, 岭迹' l; l: T9 X& D: t
Ridit analysis, Ridit分析3 B4 N9 y: ^9 t: y A+ B
Rotation, 旋转1 k1 b8 W# w! j) S
Rounding, 舍入3 H0 R' @3 `/ j- r0 m
Row, 行
0 y0 ~* ~5 Y, |. R, M ]" T$ u; SRow effects, 行效应
6 j/ {3 g8 f j( n' ^; ARow factor, 行因素
+ G% {7 E2 ~0 q9 Y) fRXC table, RXC表
0 U4 ]2 P, t6 j' nSample, 样本, _4 z& I) l4 f3 ~
Sample regression coefficient, 样本回归系数
+ o$ Z. _( O# M2 cSample size, 样本量 \ w6 j! }* s/ T, B7 ]
Sample standard deviation, 样本标准差( N3 Z& @3 U9 u2 A' w9 V( d
Sampling error, 抽样误差; w+ T' J: Y# ?: W" Q) G0 O4 x, w
SAS(Statistical analysis system ), SAS统计软件包4 s* L, u# ?( B |
Scale, 尺度/量表/ A2 Q$ A( d y; [
Scatter diagram, 散点图9 e' }. v# G; G! O3 b) @
Schematic plot, 示意图/简图7 l) @( G! s1 C- G0 k+ G" r
Score test, 计分检验
, p8 F% d! H3 M I7 n' m7 QScreening, 筛检; {% v9 R4 n1 T' A0 f
SEASON, 季节分析 3 a2 Y* \9 Z Y0 t* [
Second derivative, 二阶导数+ l% L! h; X# q2 M+ Y" A2 E
Second principal component, 第二主成分* ~/ J1 `9 `- \' h0 T2 x9 ?. E0 \
SEM (Structural equation modeling), 结构化方程模型 2 c7 O. A% Y q/ C
Semi-logarithmic graph, 半对数图8 R; m* i9 @! o+ A( @0 M
Semi-logarithmic paper, 半对数格纸; q c* T4 h3 I- T! F
Sensitivity curve, 敏感度曲线6 F l7 ^) y# Q: z
Sequential analysis, 贯序分析
% v9 ]; | \2 K$ d4 l" l, |Sequential data set, 顺序数据集
" q3 L [; A6 ?Sequential design, 贯序设计9 F" ?$ d+ t+ \9 U3 Q# k
Sequential method, 贯序法
, i- b# R) g3 _* g( `; RSequential test, 贯序检验法* y# f K+ a5 X/ B, h1 u, m
Serial tests, 系列试验
. o# d B" O3 ]Short-cut method, 简捷法
' Q. @ m3 d7 c) I: cSigmoid curve, S形曲线
6 L; n& j) o9 I n6 Y, OSign function, 正负号函数' y& z$ ]( C( K' u k( R% m& Z
Sign test, 符号检验
7 S- K) ?$ A3 @. r. i9 o( P, |! pSigned rank, 符号秩
: {; H5 u. k5 i" z+ b" VSignificance test, 显著性检验, u3 [5 t' f; p% u8 v
Significant figure, 有效数字
" I: a. X( S! X. L9 U4 iSimple cluster sampling, 简单整群抽样# C+ M G; A/ q5 p$ W) U8 h$ Y
Simple correlation, 简单相关
/ X& B2 g) @" C9 X0 fSimple random sampling, 简单随机抽样
- }' V1 Z6 w/ p; |Simple regression, 简单回归
0 [3 V% w/ r @2 X+ jsimple table, 简单表, `: c* v, }0 L6 Z7 J
Sine estimator, 正弦估计量
0 \6 H Q& B+ {+ n. _1 T9 {5 {Single-valued estimate, 单值估计
+ C/ ~8 j" p2 t8 Z7 W; YSingular matrix, 奇异矩阵5 \* o2 s1 A6 }4 I
Skewed distribution, 偏斜分布! |0 k' d4 c4 |5 {
Skewness, 偏度$ L/ t3 C* @ d. {4 l- S# @( \
Slash distribution, 斜线分布/ I. ~+ S% O$ `1 o9 T
Slope, 斜率
5 M l( X0 X0 `- [Smirnov test, 斯米尔诺夫检验
, O, q6 L% ^8 m, G! C; NSource of variation, 变异来源
2 d6 p/ s* R# ?+ LSpearman rank correlation, 斯皮尔曼等级相关
7 y4 ^5 ?" o7 g: v( dSpecific factor, 特殊因子
/ y2 {# R& r6 u# H9 J4 vSpecific factor variance, 特殊因子方差! L8 V9 u& w) I8 i4 E
Spectra , 频谱
6 w; T7 U h* `# y" KSpherical distribution, 球型正态分布
0 x* q3 z3 e5 c) e% N) CSpread, 展布
: P* U/ J* e v% ?) oSPSS(Statistical package for the social science), SPSS统计软件包8 p0 h( I" D' c7 z& y0 `
Spurious correlation, 假性相关
; p6 T ?5 T- v |# ?Square root transformation, 平方根变换
5 S8 y9 X, c x1 ?Stabilizing variance, 稳定方差
B/ Y7 b; W, J" I7 L1 W1 NStandard deviation, 标准差
2 i) d \1 P/ j' t2 w8 z0 @6 sStandard error, 标准误# i9 h) ^6 m' D( R
Standard error of difference, 差别的标准误5 @+ u( N0 t% X( E4 m
Standard error of estimate, 标准估计误差8 g* u" @3 z& v7 e- D
Standard error of rate, 率的标准误. r4 `/ g7 o ?* W2 G3 I! O" h( H& b
Standard normal distribution, 标准正态分布2 D( C# i# N6 O" l
Standardization, 标准化
( L/ Z7 P, P) V, {6 c# |( ]; YStarting value, 起始值2 Y0 s5 d" Y3 j* L1 E' E
Statistic, 统计量
9 q8 W V9 L: pStatistical control, 统计控制
8 f9 T+ B+ R- P P. g. W- n' JStatistical graph, 统计图
% ~3 l: E" W3 \, Z9 }5 \Statistical inference, 统计推断5 b: n, P0 s; I- x1 F2 P( P
Statistical table, 统计表: O; Y" V9 G' t! U
Steepest descent, 最速下降法
' d% J2 N4 r, v$ @ q2 f# XStem and leaf display, 茎叶图
5 O! L6 N5 B! ^( f- ?. \ ]Step factor, 步长因子
3 w9 R+ s& ?2 m1 z# }( rStepwise regression, 逐步回归 d# @$ a7 l* V( o: Z5 o7 e
Storage, 存9 _0 c9 {/ A4 X3 [4 a
Strata, 层（复数）
+ ]( `2 @. f! d0 u0 s; sStratified sampling, 分层抽样2 ~8 Y C7 Y1 Y3 p8 \' y( F6 i
Stratified sampling, 分层抽样
3 P/ `0 d, C# R- D ?Strength, 强度
* d- J$ W6 a+ s# i# V. \Stringency, 严密性) Y( g4 c0 M$ N( B9 ?4 w& V3 d0 m
Structural relationship, 结构关系
! N# B" x- A5 tStudentized residual, 学生化残差/t化残差- B4 Y% O l" G* L
Sub-class numbers, 次级组含量
8 H+ b8 w8 l$ L/ K9 RSubdividing, 分割
% X; s/ B( F, I# f" S* iSufficient statistic, 充分统计量
! p f4 ?# N7 |* Q% K. USum of products, 积和
& n7 |! y8 H2 V4 PSum of squares, 离差平方和
; X6 ^9 G5 B& u/ ^1 [' [Sum of squares about regression, 回归平方和
; G; o/ i) {3 ?- q* ~1 s LSum of squares between groups, 组间平方和
- q- L, B8 l) G) |0 YSum of squares of partial regression, 偏回归平方和. h1 \ g6 E& Z1 V+ S* c! v2 }4 r
Sure event, 必然事件0 \1 R8 J* n5 s1 g* U
Survey, 调查- h+ c0 M Y6 e
Survival, 生存分析
7 n, Y4 w: A% g7 Z# LSurvival rate, 生存率
1 s* a. a s% Y ySuspended root gram, 悬吊根图
; I) H9 r1 g% D& ?Symmetry, 对称
! O+ @& s. n5 X8 T4 fSystematic error, 系统误差
4 J! t7 u* u: f, l3 M( hSystematic sampling, 系统抽样
8 P2 i! g! W# J) m7 l GTags, 标签
" M1 I) ^; K0 \$ yTail area, 尾部面积
4 ]; ?; Q# k/ G _: ` E) FTail length, 尾长9 v7 _% A4 Z- y9 |# z$ w2 b
Tail weight, 尾重
& `; A; {& \0 W) qTangent line, 切线
% M% w: a+ c7 R. `+ X5 e* @, [Target distribution, 目标分布2 x2 v" n# e% ^0 h# r+ S I" I) Q$ k
Taylor series, 泰勒级数5 H; Q7 y9 J4 |% l) d( F; I. n
Tendency of dispersion, 离散趋势
9 W4 y9 E5 |: b9 W3 b0 H) y( OTesting of hypotheses, 假设检验& T, X' S; F( f, W
Theoretical frequency, 理论频数; Q0 @ C8 n8 k( Z* R+ n
Time series, 时间序列
& [+ A/ l1 v' g% `1 a0 q4 _Tolerance interval, 容忍区间 E% ]0 L' m; b5 |
Tolerance lower limit, 容忍下限
l6 r* w6 G+ H% j* {Tolerance upper limit, 容忍上限
6 a$ ` {: i5 U- ^Torsion, 扰率
* {6 \9 C, X7 v" k6 j' eTotal sum of square, 总平方和
7 R% U5 E5 B% h! ? z& x1 W% z2 }" gTotal variation, 总变异: b$ Y1 s+ F1 |8 C
Transformation, 转换) _: S" X6 D. \5 g6 d# C
Treatment, 处理
' g" {. L2 b. U* |2 E& CTrend, 趋势
0 t! j& E& O+ l m/ |: Q, E- xTrend of percentage, 百分比趋势% y" E. f3 |, V4 Q
Trial, 试验
! ^% m' i2 L* }5 }- E0 iTrial and error method, 试错法
# i2 L5 p; p: U6 O- Z! Y* v' NTuning constant, 细调常数" B, S' g6 A1 w4 ]3 N( d
Two sided test, 双向检验
# q2 j) p! {7 g7 w( i2 {1 JTwo-stage least squares, 二阶最小平方& u; I) X+ d% Q5 W# t$ P9 m, G
Two-stage sampling, 二阶段抽样
( ?# U" g9 D% ]3 cTwo-tailed test, 双侧检验/ q% Q9 ^' h' ~. ]; ^! U- U+ ?
Two-way analysis of variance, 双因素方差分析6 d- D& C2 l5 z9 T; _ B, `! s" _
Two-way table, 双向表
* m4 S4 y$ E: y7 L+ C( w" e% KType I error, 一类错误/α错误6 m8 w0 I" x v( D
Type II error, 二类错误/β错误
* D; m E, U/ s& S& \! FUMVU, 方差一致最小无偏估计简称
! B, G* g. g, E6 p. E0 N$ X6 U9 HUnbiased estimate, 无偏估计
" H/ k% X4 B$ V$ X1 g( Y7 TUnconstrained nonlinear regression , 无约束非线性回归& D7 b: X3 r# I+ q& ]' r0 {0 h
Unequal subclass number, 不等次级组含量( f L" W9 E) n
Ungrouped data, 不分组资料
! I8 f- b- u1 N7 b% g# DUniform coordinate, 均匀坐标
L& n7 _: u& `7 h. P- yUniform distribution, 均匀分布. y6 W' |3 l) y# v8 C
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
/ A( n6 H2 Q* k" QUnit, 单元
0 }$ R) R M& _: f& b4 hUnordered categories, 无序分类9 Q p: g# h! s+ @8 @1 E3 F
Upper limit, 上限
% e% ]1 ^# b% q0 q+ Y- hUpward rank, 升秩$ H. ~# P6 ~" N' P. |0 x" {
Vague concept, 模糊概念" |1 u \% }* Q9 k- c/ W1 X0 q3 y9 x
Validity, 有效性
# ~( J, D7 ]$ b" W; o ~VARCOMP (Variance component estimation), 方差元素估计& \+ f- G F5 C8 M
Variability, 变异性4 o% v4 D+ v2 d+ @3 V
Variable, 变量' h7 W1 S, W' q. P# ~
Variance, 方差
9 D5 |* b% M1 _* XVariation, 变异! e& d0 `, m2 r
Varimax orthogonal rotation, 方差最大正交旋转
) Z7 _7 ?2 q9 M# ZVolume of distribution, 容积0 q6 q9 s6 Y9 g N5 P
W test, W检验% n: w- k6 Z- {4 O. J4 e% U1 s2 c
Weibull distribution, 威布尔分布+ a, I& C1 @0 u9 p% i& A
Weight, 权数" K% \# B6 K8 U$ |! H. \+ `
Weighted Chi-square test, 加权卡方检验/Cochran检验! j% b! x2 N" l: e/ K* r; D. }
Weighted linear regression method, 加权直线回归( ^% S1 x6 A1 `" T6 U8 N
Weighted mean, 加权平均数! Z/ b) r; @1 a- C" a* x' P! h
Weighted mean square, 加权平均方差) J) k! e" _. D9 H- x
Weighted sum of square, 加权平方和# s" T& H h4 Y
Weighting coefficient, 权重系数
- k! w, }4 S/ e4 `& E: sWeighting method, 加权法 7 S5 t x$ h( m; {9 K2 P
W-estimation, W估计量% y# }7 [9 y. E; X) [
W-estimation of location, 位置W估计量
! R' j9 E* \9 V& X6 ]Width, 宽度) I4 `1 K- U1 i L- i+ u- L/ x4 R; v
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
' R0 w! B. _5 B: [6 ~Wild point, 野点/狂点
( k4 Y3 x6 V% \6 W9 S! SWild value, 野值/狂值
+ J% w0 @. u! w; u" U, }+ |Winsorized mean, 缩尾均值# I1 ?+ f% s) \+ i! f. z
Withdraw, 失访 ) k2 a: M' `9 Y0 t+ ~0 u; _5 F5 s
Youden's index, 尤登指数
* }# G! H% j# v' A: S8 U+ W$ JZ test, Z检验* G+ U' D$ B& |3 b2 y
Zero correlation, 零相关$ _; j6 P( ~5 W2 x( \/ l
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
