|
|
Absolute deviation, 绝对离差 w. w' p: z& F* T! s% {
Absolute number, 绝对数, M' ~0 a8 v* z9 r0 E7 Z7 {( |
Absolute residuals, 绝对残差3 O U- p5 @- ?$ I" e3 E5 }
Acceleration array, 加速度立体阵' h: T [1 m+ P1 q- s8 t, t5 w6 e
Acceleration in an arbitrary direction, 任意方向上的加速度, P8 x, g+ C0 F" X* b9 t8 I* u' x
Acceleration normal, 法向加速度
/ O. r V1 U2 _3 w" NAcceleration space dimension, 加速度空间的维数
: D. V& P5 g) L; j: lAcceleration tangential, 切向加速度0 q8 B/ x! o) B9 p+ \
Acceleration vector, 加速度向量% T& ^4 K5 v1 B: q: a9 L# B# c
Acceptable hypothesis, 可接受假设& H# j1 v |$ o* y) o- J
Accumulation, 累积
( W `( Y8 Y. u8 \$ LAccuracy, 准确度. _8 q' ?. M9 U# g8 I1 G. g
Actual frequency, 实际频数7 j" c1 q8 R5 I) Q7 }4 l' v, v
Adaptive estimator, 自适应估计量$ D7 {0 g- v( g) Q& a- p
Addition, 相加
- P. C$ z9 N( |3 z! pAddition theorem, 加法定理
* J0 D5 O2 e7 U7 T& E& JAdditivity, 可加性
" Z- K6 F3 F! X8 P0 N/ o, \Adjusted rate, 调整率# U0 V7 b- _# q" R0 d' i) F" r
Adjusted value, 校正值
$ K& V" e$ s( W: MAdmissible error, 容许误差' n+ l( v1 [: B8 g3 k% v
Aggregation, 聚集性
/ \0 T* I: t) W1 {) V( c JAlternative hypothesis, 备择假设
8 }0 m& d+ `) ]" K! N" U: |Among groups, 组间" A* n% `+ L. M6 z: G4 M# E/ J1 _
Amounts, 总量
$ r' ^" O! N% q" i8 T& U" rAnalysis of correlation, 相关分析% t+ p0 \- J% G8 u8 f
Analysis of covariance, 协方差分析$ R9 O1 {2 T# t( j9 E! J2 s
Analysis of regression, 回归分析+ W5 R; s2 \' n- q% B
Analysis of time series, 时间序列分析# E' S0 ?4 b- s% `- D1 s# V
Analysis of variance, 方差分析
, D, p2 N' \ j# IAngular transformation, 角转换4 M3 G; \% O5 y. u+ g$ n b- |
ANOVA （analysis of variance）, 方差分析
- l1 v) v' W, r. sANOVA Models, 方差分析模型8 o& b/ `9 k$ U, R( I2 p" h! I8 H
Arcing, 弧/弧旋$ ~4 N- Z% ^3 T
Arcsine transformation, 反正弦变换
0 E% S k. T8 B: VArea under the curve, 曲线面积
3 [6 T5 {- A4 LAREG , 评估从一个时间点到下一个时间点回归相关时的误差
# ~5 A" ]! e' cARIMA, 季节和非季节性单变量模型的极大似然估计 0 ^ A T( x6 w4 N/ s
Arithmetic grid paper, 算术格纸
4 _# a6 @- d5 ~# FArithmetic mean, 算术平均数- u* }$ x% X5 \& g+ o. `2 [
Arrhenius relation, 艾恩尼斯关系6 A" B7 b1 n- ~1 [: z' ?' M
Assessing fit, 拟合的评估 Z" T. g; G6 P, P
Associative laws, 结合律
- ?/ D, A" Y8 `Asymmetric distribution, 非对称分布8 x# M3 V6 C" f
Asymptotic bias, 渐近偏倚
4 D$ e% W2 w* SAsymptotic efficiency, 渐近效率 F4 S" w( f: y: U
Asymptotic variance, 渐近方差
+ R- @& q! L5 A$ ^Attributable risk, 归因危险度8 p( N- |: y1 q/ g
Attribute data, 属性资料' L# l* m0 P6 W* ]
Attribution, 属性
( O" I! Y3 l; c( g6 M0 S0 pAutocorrelation, 自相关: v5 O9 {6 A# _6 Z' \ g. i
Autocorrelation of residuals, 残差的自相关
6 M, q) |% s7 ^; _Average, 平均数8 r3 }$ e$ [% S9 p# e8 T
Average confidence interval length, 平均置信区间长度/ v J3 @: I# Y2 z
Average growth rate, 平均增长率0 B& I* o7 F. b# K+ r
Bar chart, 条形图
/ O( Z- A9 z3 d+ r/ U* NBar graph, 条形图
( {9 ?5 b# v. | t1 [Base period, 基期
% X0 M7 X$ ?, qBayes' theorem , Bayes定理! }* e3 _; T/ a
Bell-shaped curve, 钟形曲线. S" g2 N! V) M" i8 R) m. [
Bernoulli distribution, 伯努力分布
8 c& w: v3 ?+ c0 f+ mBest-trim estimator, 最好切尾估计量! O# W) v/ {; q, t1 o0 f# }9 X
Bias, 偏性 |" O7 J% E( F1 y" A1 h4 w* t
Binary logistic regression, 二元逻辑斯蒂回归& U9 q9 T2 ]1 T
Binomial distribution, 二项分布
7 c+ ?2 m+ v. R6 D+ n& EBisquare, 双平方
4 Z9 Z: _6 d/ a& \' kBivariate Correlate, 二变量相关5 {- M, {0 `6 o& ]
Bivariate normal distribution, 双变量正态分布
. P8 l$ k2 v" y* @6 LBivariate normal population, 双变量正态总体9 o; ?/ t7 r! M9 @* j& ^4 m
Biweight interval, 双权区间2 d6 o q1 _1 c) T( b9 v
Biweight M-estimator, 双权M估计量4 i% _3 w8 X! M: \1 c0 t# D# R
Block, 区组/配伍组& y2 F w( h/ Y( V# Z
BMDP(Biomedical computer programs), BMDP统计软件包! s _6 X( q& T8 Y0 m
Boxplots, 箱线图/箱尾图$ h. j9 l+ T0 r! o; b6 \
Breakdown bound, 崩溃界/崩溃点 f1 e/ n; ?( d, E6 x
Canonical correlation, 典型相关
( L0 X1 t8 D) Z4 m W) h* \Caption, 纵标目
. n* f' |: L" @0 r+ @) F) U( uCase-control study, 病例对照研究) |1 V4 [7 l1 }, ^- P3 K: Y
Categorical variable, 分类变量6 B4 ?+ J. w' b8 h
Catenary, 悬链线
! Q; W$ f6 P4 H+ I$ A G5 u: |Cauchy distribution, 柯西分布
5 y' w/ k7 L3 Q9 B# `, [: pCause-and-effect relationship, 因果关系
6 g: ]. l. z5 m) X' D( @; tCell, 单元" L% i8 T: v+ b$ h& x1 g1 L
Censoring, 终检* Z; q! e: q: T2 q5 H
Center of symmetry, 对称中心% x; k0 N# Z/ k1 }7 w# S; J( E
Centering and scaling, 中心化和定标$ { N- ?3 r; m, j8 }, [$ R
Central tendency, 集中趋势
" D2 g. q0 r+ ~- N$ }5 CCentral value, 中心值
9 _- R# C1 z5 Z" H" I H% XCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
/ Q8 L' A$ H( k5 ^+ X1 B" s; RChance, 机遇
2 h: A6 K, }6 T. B' |) ]) b8 K8 FChance error, 随机误差
# p1 t8 e( r6 z0 f' b; YChance variable, 随机变量
3 G- k/ S, m6 RCharacteristic equation, 特征方程' C. D$ j3 \8 X+ }5 p, W
Characteristic root, 特征根# ]& q3 F* c A, C
Characteristic vector, 特征向量
' V. B0 o. _1 X. S& _, [2 U9 zChebshev criterion of fit, 拟合的切比雪夫准则
$ \6 ~* x9 D) i* O+ k+ PChernoff faces, 切尔诺夫脸谱图
9 U& z( ^$ W; k# wChi-square test, 卡方检验/χ2检验 l; p/ m* r1 _* g/ F" P8 c3 `5 ]5 t
Choleskey decomposition, 乔洛斯基分解
! I, S) f( K- W: LCircle chart, 圆图 1 ~6 _0 ^# V2 M3 j# H! r5 W
Class interval, 组距
7 s/ R# B% ^/ G$ X( \1 L2 bClass mid-value, 组中值) d3 a! ?+ \; M1 }
Class upper limit, 组上限* q* D& T7 F+ H
Classified variable, 分类变量
9 [) O- u0 s9 z" F0 ~Cluster analysis, 聚类分析
1 U0 Z% | n$ t GCluster sampling, 整群抽样2 ~6 T: x" l1 v
Code, 代码
5 c4 S; y, Z5 X: `8 r0 f: {0 ^Coded data, 编码数据
h) _2 X5 L v* [Coding, 编码1 E' s$ v. E. V: _4 \+ \
Coefficient of contingency, 列联系数+ P* o" n* f0 s, J; A8 S' M
Coefficient of determination, 决定系数
$ D) ?; T9 e/ C: |. VCoefficient of multiple correlation, 多重相关系数
8 X5 k% i" \1 p7 ECoefficient of partial correlation, 偏相关系数
4 X- I$ }- h* Y1 ?Coefficient of production-moment correlation, 积差相关系数# Z5 S" N; H: E3 e" i+ [, C5 U
Coefficient of rank correlation, 等级相关系数! K7 _. X! W8 j8 U) p
Coefficient of regression, 回归系数
" U" G4 } n. ?: F5 ~Coefficient of skewness, 偏度系数2 ?9 X8 w1 Y: Z7 l
Coefficient of variation, 变异系数, p( Y/ @! M$ g- V* Z
Cohort study, 队列研究- `* J, L0 I0 ~9 f/ G# `( {
Column, 列) e4 T$ K, @ K. J+ n: g$ {
Column effect, 列效应; s5 J/ Y7 K& ?4 ?6 X( u: B9 S9 J
Column factor, 列因素1 J) `+ G: j* _5 s" X1 f# x8 Y
Combination pool, 合并
2 O. r% {8 w& ^6 L0 K+ yCombinative table, 组合表# S; m: T+ u: B7 p5 g* W
Common factor, 共性因子' z2 q. r3 D5 c$ M0 [* { d8 S- H
Common regression coefficient, 公共回归系数+ B" q% i+ W* k8 r& i
Common value, 共同值
) {! T y1 F4 ]/ aCommon variance, 公共方差: U! B1 w( H4 }8 g0 D
Common variation, 公共变异
8 B" P0 V1 O. l& Z. o; ]' {Communality variance, 共性方差: N2 E, I7 `7 E6 u. k) [% D
Comparability, 可比性! Z6 N2 O H/ v7 g
Comparison of bathes, 批比较
1 u- ~ y# {7 z$ x* f+ nComparison value, 比较值
/ H( D/ m2 C9 U' }Compartment model, 分部模型* z: L) w9 z( U: D* r
Compassion, 伸缩 z5 v1 V# G# a4 G; {, u. y2 N
Complement of an event, 补事件9 @0 \8 h# J) t, G/ W4 @* i
Complete association, 完全正相关
. l, C- r( w5 n6 {1 Q$ P5 tComplete dissociation, 完全不相关
/ G& h# b& Y" gComplete statistics, 完备统计量* p8 L$ {8 j# e: ]: N+ E
Completely randomized design, 完全随机化设计
. s7 U8 j }; }! w6 [& fComposite event, 联合事件
% u7 H2 \- q: }$ `" c2 M) V4 U! C( i" pComposite events, 复合事件$ Q* P: e* X$ g# R
Concavity, 凹性6 p! q5 G* M- {& s* b/ U
Conditional expectation, 条件期望
: H# ^. S8 L, Q! Q& y$ nConditional likelihood, 条件似然
/ I$ K8 [! }# S$ \" g5 sConditional probability, 条件概率- e+ m! i. Y- |! x' ~: }
Conditionally linear, 依条件线性: {# p1 l% N1 I: w S8 Z
Confidence interval, 置信区间
$ \3 `! I2 f8 ^% n7 ?* l. O* gConfidence limit, 置信限
V) n7 }" R" I7 r! e S& U1 OConfidence lower limit, 置信下限( X& J7 t" @* k# D" {: Y4 W% a
Confidence upper limit, 置信上限
! {9 c _9 i4 F6 r& t8 F/ OConfirmatory Factor Analysis , 验证性因子分析
/ Z/ a- f6 I( l6 ~1 p iConfirmatory research, 证实性实验研究
7 Q$ T( n' \% pConfounding factor, 混杂因素; R* b W& `8 U5 M2 R& m7 ?
Conjoint, 联合分析
4 O% D; w7 c3 ]5 xConsistency, 相合性& [7 c/ h" K8 t' W5 u% x
Consistency check, 一致性检验
+ ?3 y# b9 x% }. T1 {Consistent asymptotically normal estimate, 相合渐近正态估计7 [: c" w/ z# w- v
Consistent estimate, 相合估计2 {* ` K ^! U
Constrained nonlinear regression, 受约束非线性回归
A% f5 f8 c; LConstraint, 约束5 o( r% |$ t; s( w
Contaminated distribution, 污染分布
! C M* e% x% {Contaminated Gausssian, 污染高斯分布
2 w6 s; |9 |& b6 P1 PContaminated normal distribution, 污染正态分布8 R8 \5 n; {) |1 H/ _
Contamination, 污染
9 q& X' x/ I8 v, }/ CContamination model, 污染模型; I% w: J+ C* O; r9 p6 O9 @
Contingency table, 列联表% \ x2 I# o; J
Contour, 边界线
/ k1 L; b# Z# Z* H1 PContribution rate, 贡献率6 h1 A2 I% \4 A
Control, 对照
6 |) ~5 B+ D' u' Y# J" dControlled experiments, 对照实验
. _! s! k. o. \9 q& V9 T* mConventional depth, 常规深度
8 L6 J2 g5 ~2 L1 k8 NConvolution, 卷积
, y+ Z/ P1 x! R uCorrected factor, 校正因子
4 g$ d- }: w- ~Corrected mean, 校正均值
! R( a, P" m: Z, K6 DCorrection coefficient, 校正系数; ?& H6 h1 H2 P8 |
Correctness, 正确性
' B9 d; _, o% S" T) JCorrelation coefficient, 相关系数$ S# f1 Y' P$ _; ?! F" d! Y8 M- l+ n
Correlation index, 相关指数+ D# c$ k5 c9 G. ]1 N- e
Correspondence, 对应2 l# E. f s' ?, h& O
Counting, 计数+ z, ~. T7 K) K) {
Counts, 计数/频数4 D* A/ a1 K8 P4 X* t+ a
Covariance, 协方差
2 L5 `4 v. V- V2 q+ U" pCovariant, 共变 3 V! B% ?$ m$ Y3 F
Cox Regression, Cox回归) ~7 h5 U7 I( \
Criteria for fitting, 拟合准则* V1 ^" x9 [7 o
Criteria of least squares, 最小二乘准则
; X: M9 `+ W- A! t9 tCritical ratio, 临界比 t& } W/ N o' \1 R# Q+ W
Critical region, 拒绝域
: F( }" e+ }# l/ xCritical value, 临界值5 u9 p. t6 K' J$ k
Cross-over design, 交叉设计# E6 Y! J) }/ G, ^( z1 ^0 J: A
Cross-section analysis, 横断面分析+ _" A: l" D# _' C& b
Cross-section survey, 横断面调查
, y& p. {9 I% g0 [Crosstabs , 交叉表 5 T! M- F, ]! ]' E. N& |! Q
Cross-tabulation table, 复合表: Q3 a3 k3 k% O" t2 n7 w* ~
Cube root, 立方根/ d) R! U3 d* q* z! N7 `9 A
Cumulative distribution function, 分布函数) s% |7 r/ I" {
Cumulative probability, 累计概率
2 m; S: g. A8 W5 Z( h$ D+ {6 f! dCurvature, 曲率/弯曲
& K6 k! U2 d8 n0 w2 ] t6 {Curvature, 曲率
k* D4 C0 X5 [% jCurve fit , 曲线拟和
* k, q' y$ a) q" A ` P2 pCurve fitting, 曲线拟合
; o& b( t8 c4 p: L8 \4 K6 iCurvilinear regression, 曲线回归
. P. a- G1 l7 `/ _' P) JCurvilinear relation, 曲线关系; A$ i2 j6 g, L2 M
Cut-and-try method, 尝试法
$ ~: z$ k) Y; M3 P2 t @, j& lCycle, 周期
1 m5 F7 m) m+ n/ O2 {+ RCyclist, 周期性# C' @( C, i6 w. N
D test, D检验7 q. E3 R5 H+ H% n
Data acquisition, 资料收集
5 N3 x1 \( {2 ?! r- LData bank, 数据库; W" v- b' m& [9 O8 r% r
Data capacity, 数据容量
4 E7 P+ Y" d. r- o7 D& ZData deficiencies, 数据缺乏- s+ j5 T4 j/ [" b- S
Data handling, 数据处理
* t( C% H/ }' c. O( {3 Q4 lData manipulation, 数据处理
: B) N3 Z& K( r* {$ L9 p8 G2 SData processing, 数据处理 g$ a7 T8 W$ a6 c
Data reduction, 数据缩减. _8 [2 W. R' [7 H( c3 t; D
Data set, 数据集/ i# Q1 x+ |9 U) C
Data sources, 数据来源5 P5 N8 R2 x4 }, e* j& O
Data transformation, 数据变换9 K! M. f; a/ U9 q
Data validity, 数据有效性
" H* }; s8 S" ^; h# C2 C, YData-in, 数据输入# ^4 f, r( a# V1 v( g
Data-out, 数据输出# q5 d4 c( k) o/ a. b: ^9 E
Dead time, 停滞期
( v c; k b c( F q0 qDegree of freedom, 自由度
: {2 s' D% S9 F& }9 tDegree of precision, 精密度
J, t" X y- i& JDegree of reliability, 可靠性程度
: g8 r) Z% i5 a! \2 J$ Y+ u: ?1 X% dDegression, 递减
" X' t3 ?( j( S$ J$ q* w& nDensity function, 密度函数5 c7 B/ t( y3 k5 `* i
Density of data points, 数据点的密度; V7 e5 _9 `/ L+ D0 X( I2 E6 L4 l
Dependent variable, 应变量/依变量/因变量5 `/ \, X! L; f# a! B
Dependent variable, 因变量2 o1 n/ M6 Q+ R0 w8 e
Depth, 深度, v; H5 r$ v; [) V
Derivative matrix, 导数矩阵
! o0 w2 I( j" G2 u% W5 W) n( `; mDerivative-free methods, 无导数方法
& c/ {: O% W) I" u; o- r" a" z8 DDesign, 设计0 ^6 X5 g& j! x( D# _$ Z5 c1 A
Determinacy, 确定性
8 J3 i& p* W& o% g1 ^Determinant, 行列式3 \' W) y+ v1 L) Q w
Determinant, 决定因素
) ~/ A: n* g3 n4 H/ ~$ \2 eDeviation, 离差3 Y" h1 c p$ f$ I6 `' F
Deviation from average, 离均差
1 [5 j) Z: X$ g9 d! L* P+ bDiagnostic plot, 诊断图( `6 a/ S' v, E5 l- y, R
Dichotomous variable, 二分变量5 Q, H1 T3 b( A2 b2 L5 x4 o+ V, y
Differential equation, 微分方程
6 P: ~. ]( v* x; H( ?0 F9 pDirect standardization, 直接标准化法0 w9 i+ E, n- v# |8 S3 B4 s$ u- w
Discrete variable, 离散型变量# g3 ], A7 ]: I/ R* T/ O
DISCRIMINANT, 判断
( S" m4 f- }- MDiscriminant analysis, 判别分析
# X' u J: q. Z/ dDiscriminant coefficient, 判别系数( J t8 p) I+ F5 P
Discriminant function, 判别值
5 W& e- Q9 u6 b3 G2 { Q' A4 X' ^+ }Dispersion, 散布/分散度
9 s2 R$ ` C- s( [" K a3 K0 e% I! x# @Disproportional, 不成比例的, w* q4 F F% q5 \% Q4 j# s3 g: W, e
Disproportionate sub-class numbers, 不成比例次级组含量# B: R7 q$ Y/ ?. O2 z( |1 A7 ]
Distribution free, 分布无关性/免分布) I& r. _ x: M5 V- y
Distribution shape, 分布形状0 z9 k6 v" W, I) i: [: Y
Distribution-free method, 任意分布法
H7 |0 n4 S& I9 \) yDistributive laws, 分配律) `* P$ A4 j5 n1 d+ u8 a
Disturbance, 随机扰动项
0 o+ w. ~4 H4 M& K& cDose response curve, 剂量反应曲线
! Q8 ?1 Y1 o7 P9 a) _. C, O' sDouble blind method, 双盲法
: v: z; d' C) MDouble blind trial, 双盲试验
& W+ j6 Y( O/ L4 M; KDouble exponential distribution, 双指数分布
$ R+ d% j3 K, y; S$ ADouble logarithmic, 双对数0 A! c- K; C+ U, _" D
Downward rank, 降秩; K! Z0 M# @1 U8 Z! l0 F+ D0 A
Dual-space plot, 对偶空间图1 |3 H. f( M3 q! B1 S6 g3 l$ X
DUD, 无导数方法/ |* [7 @6 [8 e% D) j, v& \. r& o
Duncan's new multiple range method, 新复极差法/Duncan新法
M/ {& B1 C: e1 y7 a- { BEffect, 实验效应$ } Q# W5 s9 e, A
Eigenvalue, 特征值
3 O. W3 n- Z- u9 c; VEigenvector, 特征向量
% W; h7 ^$ k( qEllipse, 椭圆
$ H# Y+ n" i* `5 X+ l, C$ [6 tEmpirical distribution, 经验分布6 F; z; B. u- l. f6 ?: x
Empirical probability, 经验概率单位
$ q2 \5 Y" ~, z& a K, I1 E; GEnumeration data, 计数资料
' Y( ~9 c4 R# r' P$ d" B7 }/ ?Equal sun-class number, 相等次级组含量
+ [3 g& a+ B5 _5 B. iEqually likely, 等可能
3 v" w5 x& P% C2 FEquivariance, 同变性+ n ?) e9 ?( p2 W# C+ G0 e
Error, 误差/错误) J+ v8 h5 Q1 r3 M; K+ ^
Error of estimate, 估计误差
& m" ?& O, G$ ?* y. gError type I, 第一类错误
) h* |' w2 Z# pError type II, 第二类错误
. ?) k+ A! Z9 Y3 @! |3 Q5 W) kEstimand, 被估量0 {! j, k% f% C& \' H! k" ]2 F/ j" Q
Estimated error mean squares, 估计误差均方% O) e8 w0 D) I" L& p6 g8 V+ t
Estimated error sum of squares, 估计误差平方和
% ?+ Q) s O) D/ B$ bEuclidean distance, 欧式距离
3 W* r: a, V9 D- ?# N. s3 z, OEvent, 事件+ W' i% q0 G, N! @9 ?" C5 K
Event, 事件' d5 l T/ K9 a5 ^2 O/ Q# S5 K c
Exceptional data point, 异常数据点/ e( s: }/ w/ d: H% s: ^6 p* i
Expectation plane, 期望平面
$ Q0 N: w2 m" e: T4 LExpectation surface, 期望曲面! i1 [) F0 h" Z6 C l
Expected values, 期望值
0 i. u' r, p$ d8 y$ p9 E% qExperiment, 实验. c" P( H d9 e D2 s
Experimental sampling, 试验抽样4 a+ I9 G2 c( B% d4 q
Experimental unit, 试验单位. J( _ B; Z: I: o% [0 E5 Q7 z: v
Explanatory variable, 说明变量
9 p: |! T! `0 O6 e& P c% X9 _5 WExploratory data analysis, 探索性数据分析& n. i6 K% v$ m( n& k, |0 l
Explore Summarize, 探索-摘要9 w5 v5 x+ f3 w$ v
Exponential curve, 指数曲线" [* {6 K- X$ ~, ^8 D
Exponential growth, 指数式增长' ?/ A3 I2 J& A
EXSMOOTH, 指数平滑方法
4 k4 u+ h4 R9 C2 [# h yExtended fit, 扩充拟合
) R( s6 {8 b4 H& Z8 }& s% DExtra parameter, 附加参数4 l& j" d8 I# {' I
Extrapolation, 外推法6 L o8 ~9 v y' _
Extreme observation, 末端观测值
; J) A( f9 z, f7 D2 @ `" iExtremes, 极端值/极值7 ]: O% ]2 R# j0 ~6 @$ {0 o( V
F distribution, F分布3 D9 t4 ^, i! H6 s5 N# t$ E+ B
F test, F检验! Z( b7 C) t- J4 @0 l- L8 K$ X
Factor, 因素/因子
" J8 z7 ^6 L8 N; O) `Factor analysis, 因子分析
; i2 d2 q3 I$ D! ~, }2 yFactor Analysis, 因子分析8 f' s8 x7 j( b! G
Factor score, 因子得分 4 G0 Y- W5 ~% d; q4 M G
Factorial, 阶乘# V4 O- ~! U/ @* u
Factorial design, 析因试验设计
, d5 S6 `6 { A0 \False negative, 假阴性+ V/ _: H7 \6 g* y
False negative error, 假阴性错误$ e8 w% z5 v4 O7 M$ j
Family of distributions, 分布族0 L d8 ]. Z( h* t3 A
Family of estimators, 估计量族
/ a7 M9 r; E- F8 d: ]Fanning, 扇面$ ?: ]0 R) m. A7 H+ `. I1 z- N
Fatality rate, 病死率& C5 V! |+ p- r; u9 Z
Field investigation, 现场调查
1 f3 g9 v& T9 F2 x; B; ^" dField survey, 现场调查
0 @2 V1 C4 Y% I* N- LFinite population, 有限总体
( f6 e. u5 b1 R t8 Z2 U: e2 s3 iFinite-sample, 有限样本1 ?" ~5 }2 z+ n) D9 m; i
First derivative, 一阶导数, l8 q7 x7 G' ^1 h
First principal component, 第一主成分( J4 n" S- `8 `- @
First quartile, 第一四分位数
) i* |* ] E1 X. H# QFisher information, 费雪信息量2 U% e5 G) q" s5 C+ i
Fitted value, 拟合值
! g9 e. B4 H& OFitting a curve, 曲线拟合+ K8 G/ Z0 j& j$ @2 Z
Fixed base, 定基/ r L" K) ^' {% p8 T! s; s. I
Fluctuation, 随机起伏
8 z. C8 R% B; f8 I7 |- _6 {- B+ sForecast, 预测
: d5 a) T# G/ j6 v- XFour fold table, 四格表
' D0 N) v* T% L# y8 e+ GFourth, 四分点, p' [. p4 O5 @4 s" u" @
Fraction blow, 左侧比率* r8 D* H6 w0 {
Fractional error, 相对误差
* g" A5 Z9 ?1 h7 hFrequency, 频率4 B2 x+ Y7 b1 o& b# X0 K, W4 N
Frequency polygon, 频数多边图
" E4 _: F" T7 Q$ O; j2 _Frontier point, 界限点
2 u- d8 k: _- G" F/ @" F$ g$ u+ MFunction relationship, 泛函关系
% c( J0 Y2 D, WGamma distribution, 伽玛分布. \9 E2 R8 r5 N$ ~: S6 y
Gauss increment, 高斯增量# @1 x4 f* p5 e/ w3 Y
Gaussian distribution, 高斯分布/正态分布( ~* h& L& `9 H
Gauss-Newton increment, 高斯-牛顿增量
1 M" n0 e4 n- ~8 vGeneral census, 全面普查8 `3 B$ n( [: E4 E& v% W
GENLOG (Generalized liner models), 广义线性模型
, n! M5 K5 r% A" CGeometric mean, 几何平均数0 R! ?$ y( w% [) W+ ?- n, P: r
Gini's mean difference, 基尼均差" }3 e, X3 Z& r, e& x
GLM (General liner models), 一般线性模型
+ ~9 J/ g- J# u5 `Goodness of fit, 拟和优度/配合度 _8 [/ I8 z# H6 B" U) A9 p4 J
Gradient of determinant, 行列式的梯度
- {1 {, X q L- D) N) AGraeco-Latin square, 希腊拉丁方
: \6 `4 Q9 |2 e, @2 u) x u8 P1 n$ cGrand mean, 总均值" ]5 f. B! J r
Gross errors, 重大错误
- [& D& ~. `2 IGross-error sensitivity, 大错敏感度
3 ~ D; d/ d( [, F+ _) p; w* WGroup averages, 分组平均1 r7 v! s- I$ S! h: _6 W
Grouped data, 分组资料
3 R# x8 G8 l- H) O8 ^( k; ^# T# F {Guessed mean, 假定平均数
% W, M4 Q4 ~1 B* \2 r8 FHalf-life, 半衰期
$ ?7 Q$ U6 A+ p2 X+ N8 @ HHampel M-estimators, 汉佩尔M估计量 ^$ A$ G G9 Y- h% W' E( k5 d
Happenstance, 偶然事件
" C, M0 s, S% w+ V. ?! lHarmonic mean, 调和均数
7 p5 z+ P( u2 U2 h2 j3 W$ d9 dHazard function, 风险均数
9 u0 c1 R& _2 b( N: qHazard rate, 风险率# d! ^4 v) [$ D+ v
Heading, 标目 1 n( m( T/ H/ H. z8 {% M4 a
Heavy-tailed distribution, 重尾分布
* T* | `! u( `. [Hessian array, 海森立体阵
5 D7 \/ h& M( `' F% SHeterogeneity, 不同质7 b" @$ ^& n/ w5 Q* O
Heterogeneity of variance, 方差不齐
& Q5 i. y5 Y6 pHierarchical classification, 组内分组
' W: O8 L2 B! a- q& ZHierarchical clustering method, 系统聚类法8 p% E; w6 r% O
High-leverage point, 高杠杆率点
0 u- F) m$ n& t+ j2 f" q/ g: wHILOGLINEAR, 多维列联表的层次对数线性模型
0 {0 C& G$ e0 @Hinge, 折叶点2 R; f1 b( L& I o
Histogram, 直方图( o5 D; Q6 @1 k* S3 C0 Z" H9 v
Historical cohort study, 历史性队列研究 ) O; ?0 X$ w8 f" D8 _4 C2 w
Holes, 空洞% t. R c$ N, r- e
HOMALS, 多重响应分析* n2 g& p. \: P$ X' X/ s. T
Homogeneity of variance, 方差齐性
, W7 Z" ]; d8 s2 y. m" N% XHomogeneity test, 齐性检验" j1 b, h* u( `% y4 O$ d4 G( h( x) ?
Huber M-estimators, 休伯M估计量
$ I; @2 i- {1 bHyperbola, 双曲线9 f$ d, i9 q9 Z- }
Hypothesis testing, 假设检验7 W6 \2 {: f" y# v5 {$ [- ]
Hypothetical universe, 假设总体
% R. J& }+ z9 S: B2 V5 hImpossible event, 不可能事件1 a, u) f0 u/ R# A) Y' D. i2 h
Independence, 独立性
- ~" ^- h/ b8 [0 L3 b% r8 FIndependent variable, 自变量
& }" g7 |9 Q5 ~+ R- e& CIndex, 指标/指数/ A) |+ y0 b) Z- h: Z" l
Indirect standardization, 间接标准化法. N6 z9 }# z( a* U( F, B: C
Individual, 个体
V, t. O; g" l6 W3 F9 T0 ]Inference band, 推断带
4 i* {# q% ^2 xInfinite population, 无限总体5 f! s& K" s2 u
Infinitely great, 无穷大
: P; Z- ~1 U# A4 k8 X" J# o* f9 NInfinitely small, 无穷小. e# q) ?* d* H# O' x
Influence curve, 影响曲线
) g! n' a. ?. PInformation capacity, 信息容量2 Y( R# f: {+ I$ k# r) {
Initial condition, 初始条件
: ?; Q$ X* J( J, E) _, E# D( W" gInitial estimate, 初始估计值
- d8 _- D- V% z0 c7 @* TInitial level, 最初水平
% {: u& ^6 ]4 K( M6 `' _6 iInteraction, 交互作用; T1 Y. }) v; w& `
Interaction terms, 交互作用项
3 @( K2 ?0 Z+ i) Q: dIntercept, 截距! J0 O( x% P4 S: D
Interpolation, 内插法
" J1 `# ^; c0 E# [- c) l* RInterquartile range, 四分位距' U( W& V, B7 D6 N. Q! R% X
Interval estimation, 区间估计" v6 w* L" Y e' d. ]
Intervals of equal probability, 等概率区间0 ]( @2 U$ q( t4 R
Intrinsic curvature, 固有曲率, w7 E6 B7 v! B! J. ~/ ]! ?
Invariance, 不变性
: G+ Y4 Z. n$ \5 @Inverse matrix, 逆矩阵
; Z$ a7 t7 C2 I& {% |Inverse probability, 逆概率5 }$ F1 G7 k* W. r8 h5 W
Inverse sine transformation, 反正弦变换 z7 i: C% q! d v0 W
Iteration, 迭代
) Z( ?7 t/ T# x1 C# oJacobian determinant, 雅可比行列式3 a- |5 |. i/ b2 R# z8 N
Joint distribution function, 分布函数/ C T7 p% r, e; J+ k
Joint probability, 联合概率: R; S4 O( M9 T; h- k
Joint probability distribution, 联合概率分布
% L! l; {$ f% f0 _3 h5 E4 ^K means method, 逐步聚类法
8 g- ~$ A1 n& Q) g) XKaplan-Meier, 评估事件的时间长度
1 S* A# v# ^! FKaplan-Merier chart, Kaplan-Merier图
/ `% {1 Q1 \/ v' J, n! [ IKendall's rank correlation, Kendall等级相关
1 D6 n2 q$ f" ? N4 L9 W& Q7 dKinetic, 动力学: `8 V. E- ` _1 b5 W4 a+ V
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
/ |0 b2 a6 k: L$ q7 RKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验1 m& P0 E- E- H% H) j* k- E3 W
Kurtosis, 峰度
0 H3 F, s& b; e; z' K6 BLack of fit, 失拟& w5 S) U c4 o& A1 o. E
Ladder of powers, 幂阶梯% u% P" M! C; b# q7 g4 P4 D/ z. \' F
Lag, 滞后! Z' g3 a0 j* X2 B! }3 x
Large sample, 大样本! r! M# J, `8 r) t, @* c% ?& c0 x
Large sample test, 大样本检验
& i( w9 g8 L. n& J) k- {8 }* }Latin square, 拉丁方! o4 e/ Q! j" m, H, x
Latin square design, 拉丁方设计
3 _3 B! N- _7 ]" F3 G @' rLeakage, 泄漏$ h2 P. a m5 C2 x, t
Least favorable configuration, 最不利构形/ d& }4 b8 {7 B ~1 p' U( e
Least favorable distribution, 最不利分布3 X) C4 J4 c5 N ]+ g# e
Least significant difference, 最小显著差法. D3 P3 |5 ]- ?7 k5 @- n7 @
Least square method, 最小二乘法
; W# h, k( N% F' H7 y; K' [Least-absolute-residuals estimates, 最小绝对残差估计
U6 A# j% o5 r4 zLeast-absolute-residuals fit, 最小绝对残差拟合
+ ~9 J8 X' v( A' R7 [9 gLeast-absolute-residuals line, 最小绝对残差线
! z/ x$ S/ _( b$ d. ^Legend, 图例+ K0 [, D" e- h) Z) [6 g
L-estimator, L估计量
6 ?8 y, S" b; `2 ?9 dL-estimator of location, 位置L估计量; R& v& u; ^5 v! c3 h% \7 P
L-estimator of scale, 尺度L估计量
7 Y g6 M& O H! W t2 r/ V% ]Level, 水平- i5 i( ^/ n" A/ t; p+ c% U
Life expectance, 预期期望寿命) R: Y; V+ b9 s( b: N5 M
Life table, 寿命表& s* f1 H: O V: p+ O
Life table method, 生命表法
1 p3 `7 G7 x7 {Light-tailed distribution, 轻尾分布
! [0 h9 q7 c5 }1 jLikelihood function, 似然函数
' r; `( G! [! j3 WLikelihood ratio, 似然比$ F) i# ]) d9 \0 w, u) M
line graph, 线图
# f" c( u2 m- v eLinear correlation, 直线相关1 R/ A( c9 R# }& ~# G/ e
Linear equation, 线性方程
) V8 a7 e7 w, Q3 E* p6 r; a$ OLinear programming, 线性规划+ j# {/ `# z# `5 J
Linear regression, 直线回归
5 |; g1 }; ]$ l9 ~9 j" H/ ~Linear Regression, 线性回归
' i1 b- |5 n) }" MLinear trend, 线性趋势
* d0 `7 |" I+ O/ d- YLoading, 载荷
- C k k& {- W3 i! J" F$ CLocation and scale equivariance, 位置尺度同变性
5 w* e5 B! y. t# v9 ^Location equivariance, 位置同变性' r3 q1 g! f7 R# Y9 _: K
Location invariance, 位置不变性" q2 w& I: g* `4 Z3 d
Location scale family, 位置尺度族6 u' q+ x) R* r$ G
Log rank test, 时序检验
/ H; a) ]- O4 Y! _Logarithmic curve, 对数曲线
" Y. z. \' |4 `/ r+ \3 z/ `' iLogarithmic normal distribution, 对数正态分布( P. Y7 u$ w) a
Logarithmic scale, 对数尺度
" r) v% q/ Z) U3 Y! U. D1 Z3 M, ELogarithmic transformation, 对数变换% t. R0 l G& J: ^& |
Logic check, 逻辑检查$ [2 Y) U% n* P: |1 ]8 K+ B5 b- q
Logistic distribution, 逻辑斯特分布( x0 F) H* k# ]! n( Z% n8 g/ Z
Logit transformation, Logit转换; K- |5 W$ L: T
LOGLINEAR, 多维列联表通用模型 3 ^1 G. S* E8 V4 ?
Lognormal distribution, 对数正态分布1 ^9 z" W/ j' x4 ~0 R+ Y. a
Lost function, 损失函数
8 a8 K6 z% B' K" Y/ u; sLow correlation, 低度相关) n. ^8 ?: P% h8 j
Lower limit, 下限
4 T8 i( p' m k3 w8 w7 M( V1 S: dLowest-attained variance, 最小可达方差
1 A0 {9 Q# A2 H8 M, O1 g: uLSD, 最小显著差法的简称' H+ j3 O0 w1 l2 F
Lurking variable, 潜在变量& m5 {- f* x3 u4 l3 D
Main effect, 主效应( ?* P2 R+ v: H) c" ^% U
Major heading, 主辞标目
0 z! P' S# ?! B* o3 lMarginal density function, 边缘密度函数1 m' K" K% u% O7 ?
Marginal probability, 边缘概率
P' B+ K- `8 @Marginal probability distribution, 边缘概率分布# N1 h/ C7 R, v8 \
Matched data, 配对资料, X$ p% r7 W/ W! a( r- `3 e
Matched distribution, 匹配过分布% m) ^6 D& t+ s* Y( g
Matching of distribution, 分布的匹配. V$ C7 b0 c3 `7 N
Matching of transformation, 变换的匹配
( @2 I+ B) h& W, tMathematical expectation, 数学期望
; S* R% M/ P; BMathematical model, 数学模型
/ C& y4 v6 z1 J4 sMaximum L-estimator, 极大极小L 估计量2 z& D3 M4 Q1 Q& N4 O, m
Maximum likelihood method, 最大似然法
. b3 K' p( \' k+ }Mean, 均数
# s- I5 x: U* ]8 \& K. ^2 zMean squares between groups, 组间均方
0 B, m# M; o! }/ c7 u7 M5 pMean squares within group, 组内均方" F3 W2 ^( v& K
Means (Compare means), 均值-均值比较
$ I% _: b1 ~4 s9 j7 K* S7 vMedian, 中位数
5 ~8 V1 R b7 WMedian effective dose, 半数效量" C- q. ]; ~8 h" M
Median lethal dose, 半数致死量
: h' D9 a2 y s" \6 cMedian polish, 中位数平滑
- H$ m" b- U+ _$ o1 _0 h# P7 j$ vMedian test, 中位数检验% h$ M4 _& d- L1 v/ y
Minimal sufficient statistic, 最小充分统计量6 u' Y, V; B2 `2 P/ z
Minimum distance estimation, 最小距离估计( s9 [# j( d1 G: Z( K" P
Minimum effective dose, 最小有效量, @( c3 q( n6 C
Minimum lethal dose, 最小致死量
- e @8 W8 K" S1 xMinimum variance estimator, 最小方差估计量
3 \+ o( z$ D; WMINITAB, 统计软件包
0 d- e' K& ?& ~7 \3 V( PMinor heading, 宾词标目
) I2 {5 o- r: z( K1 N' _Missing data, 缺失值
- V6 W2 x; A" B; e& f. q4 F9 BModel specification, 模型的确定6 g# A2 I9 ~1 Y6 k& D2 i- O! Y# W( I
Modeling Statistics , 模型统计
' Q% C' N6 n% OModels for outliers, 离群值模型
; B( y; ?' e9 Y$ e3 h5 |Modifying the model, 模型的修正
2 X3 g% _- ~; e& CModulus of continuity, 连续性模
% t Z7 X: `4 g& o. z7 z5 w# fMorbidity, 发病率
: b5 K/ n& k) t/ m1 HMost favorable configuration, 最有利构形
+ m4 l% |) ?$ aMultidimensional Scaling (ASCAL), 多维尺度/多维标度
. \! h! \1 [) Q# z7 Z- e0 ZMultinomial Logistic Regression , 多项逻辑斯蒂回归. H7 P6 r8 x1 ~7 |' E: @8 {
Multiple comparison, 多重比较
7 s" B% W1 `- wMultiple correlation , 复相关
+ W; A$ v# K @0 PMultiple covariance, 多元协方差
$ Q0 J- K. w# B, P7 L8 g$ ]: PMultiple linear regression, 多元线性回归
3 k7 r& h' v6 y& t' {Multiple response , 多重选项
6 \% S# X$ g% g& A+ j: NMultiple solutions, 多解& f+ p; c0 n( E2 ^
Multiplication theorem, 乘法定理
8 z3 `0 i' h; QMultiresponse, 多元响应. f: b1 G4 B5 P; ~) W0 B; ^- r
Multi-stage sampling, 多阶段抽样
! r; J. o V. ?$ n( a1 Y4 MMultivariate T distribution, 多元T分布3 N. k7 z* b4 v1 U9 Z6 ~7 H
Mutual exclusive, 互不相容% X3 N! T( g3 J1 v7 n$ V/ ~
Mutual independence, 互相独立
. z6 b- U! k8 vNatural boundary, 自然边界3 D% n! r% W- c; a* C B
Natural dead, 自然死亡" |* f3 R& q! O( K, m
Natural zero, 自然零* T" I b/ N; `8 K/ C, o' J# w
Negative correlation, 负相关+ n: Q9 O% }2 z. [3 U9 T- O, d
Negative linear correlation, 负线性相关
. D( h4 Q" V1 r$ M# b: |8 {Negatively skewed, 负偏8 T6 ]2 v+ \$ i% h" }
Newman-Keuls method, q检验7 t& g' k0 _. Z7 D$ s5 \5 ^4 C* p
NK method, q检验
+ T4 u+ o% N4 H" e- a& }No statistical significance, 无统计意义
# ~6 y1 h5 Q- I& r& a& tNominal variable, 名义变量
# l, @& k+ ^( p/ Q. V+ @Nonconstancy of variability, 变异的非定常性
; t4 t" {# f- tNonlinear regression, 非线性相关6 y. D% ~$ [9 C7 x+ b! V
Nonparametric statistics, 非参数统计
/ m, _, |9 m! i' |( O) K, jNonparametric test, 非参数检验
# ~) R2 ^6 c: d c3 M* B" X4 XNonparametric tests, 非参数检验
- {- I* O# b, ]Normal deviate, 正态离差
- z. a0 \0 d( j% |7 F$ V( wNormal distribution, 正态分布
* {9 e5 a' q K$ C; A3 G; d+ aNormal equation, 正规方程组
" |+ j, h5 O$ @Normal ranges, 正常范围
$ [7 W5 Z7 a* J( U* ~7 }2 m' @Normal value, 正常值- e4 a: f9 U$ X* F# F
Nuisance parameter, 多余参数/讨厌参数0 W; A3 U H' Z3 u1 o
Null hypothesis, 无效假设
# ^9 H/ }( l1 `/ G# SNumerical variable, 数值变量
- c* Z$ b7 e m( {Objective function, 目标函数# V4 ?3 A9 u% C8 d3 F$ `
Observation unit, 观察单位
/ M5 i- o9 m+ T. VObserved value, 观察值7 _% Q7 ~+ l* k5 F" f! _* Q
One sided test, 单侧检验0 W7 X9 Z C# O. N& O
One-way analysis of variance, 单因素方差分析6 v W% A Q. }
Oneway ANOVA , 单因素方差分析
/ F! q. G0 Y' y+ C& e) e3 Q2 dOpen sequential trial, 开放型序贯设计
: `7 H j9 T4 E6 I9 cOptrim, 优切尾
" E6 D% c1 @/ U; \- W& qOptrim efficiency, 优切尾效率% a) ?' b+ }4 v5 e/ ^
Order statistics, 顺序统计量
+ x: W+ u0 H3 m/ COrdered categories, 有序分类
$ y/ k3 E0 d# Y3 qOrdinal logistic regression , 序数逻辑斯蒂回归: T8 r* V6 o1 ?
Ordinal variable, 有序变量
4 s2 e. U# e$ a3 ^Orthogonal basis, 正交基
9 p7 n! }+ I. ?+ r4 H( n" |& iOrthogonal design, 正交试验设计, v/ U @: A; d, l' k8 r# C
Orthogonality conditions, 正交条件, p0 R3 _+ x. Q& A; a0 o% W, k
ORTHOPLAN, 正交设计 ) L2 z D: ?8 s0 u7 i8 E
Outlier cutoffs, 离群值截断点# o( U+ A, M9 c, P a
Outliers, 极端值
9 e2 j- l% X: x: wOVERALS , 多组变量的非线性正规相关
0 h- K* k$ M! v' }& }! z4 n) ZOvershoot, 迭代过度
' w; ^: o9 O* }, jPaired design, 配对设计
4 A9 f! [2 M. B9 zPaired sample, 配对样本
2 L" B. C: I7 l3 LPairwise slopes, 成对斜率9 z9 b( _/ T( X$ U
Parabola, 抛物线
, u% r( l* n1 E1 H3 i% t; ~Parallel tests, 平行试验, D: ~2 c' J! G9 `' X+ B' ^/ h
Parameter, 参数! M- u; `3 b( H3 a8 p; U8 {1 @
Parametric statistics, 参数统计
# d9 Z# X! {, S( H- [5 J: h {Parametric test, 参数检验
7 S) I+ ~8 e, _ N0 _3 h9 aPartial correlation, 偏相关
: C1 {) Z! f; ?1 j4 l8 x. yPartial regression, 偏回归& z# o0 A$ O- f
Partial sorting, 偏排序1 m& E: g7 M: C/ [0 I
Partials residuals, 偏残差
: \, o" I$ @. \, e& d; H: e0 bPattern, 模式
, j& a g# T+ `/ d/ i( {Pearson curves, 皮尔逊曲线
; n8 T4 P$ h. I4 K5 [Peeling, 退层
" |3 E! v& r9 A6 j! o- f7 APercent bar graph, 百分条形图1 `( G) @7 ]/ F3 @1 C$ D
Percentage, 百分比
' v- n9 E" p; z$ m& ?Percentile, 百分位数# c( V4 Y2 O+ k5 V
Percentile curves, 百分位曲线5 w' u: w+ N$ U/ ^1 L2 B
Periodicity, 周期性9 M( M- C% g* g& V6 q; }1 \3 r
Permutation, 排列
5 Q, T" y3 _+ e+ [% FP-estimator, P估计量. T+ I, ~: N7 p
Pie graph, 饼图: \1 ?. F; R* t
Pitman estimator, 皮特曼估计量5 F5 S, J. I' }# E0 F1 O$ z
Pivot, 枢轴量$ C' n7 K3 J$ F2 I8 r
Planar, 平坦
9 _( q5 O& O" ~0 @Planar assumption, 平面的假设
9 \+ j- m9 C' LPLANCARDS, 生成试验的计划卡1 e7 A& w# e7 T. b
Point estimation, 点估计
% b2 `& P8 E/ v8 g; XPoisson distribution, 泊松分布
$ p* h7 O# |6 _/ D0 r. UPolishing, 平滑
3 U; u( G3 l SPolled standard deviation, 合并标准差
: P9 w/ w2 M# h* u; A" p- }Polled variance, 合并方差
# S+ ^3 l2 }- b. _/ wPolygon, 多边图- a: R5 a# t" ^) }* H4 Y3 g4 S/ G
Polynomial, 多项式
& h$ f9 ~' f8 h( ^& TPolynomial curve, 多项式曲线6 R9 R3 C9 Y7 _. n; d
Population, 总体
$ T1 v$ j& q6 O$ U. R4 s$ K( }Population attributable risk, 人群归因危险度/ h$ i1 ^2 O, Y/ t3 b# f0 f2 _
Positive correlation, 正相关0 \: K, a3 p- V0 ^5 y& o
Positively skewed, 正偏
0 e c" {& @4 H$ D" kPosterior distribution, 后验分布8 K+ H3 |$ M' O3 A }
Power of a test, 检验效能
0 V! H2 d/ O2 A4 u* D8 GPrecision, 精密度% X! X) l4 ~2 a/ `5 Y" y
Predicted value, 预测值! w l1 X& F0 L7 W
Preliminary analysis, 预备性分析% j7 x6 w+ w5 P' g) R0 J
Principal component analysis, 主成分分析
7 `! g t4 N& D0 TPrior distribution, 先验分布: u2 U9 k9 z% X# F
Prior probability, 先验概率
J0 h- [$ W3 U0 d M: w U7 \' |Probabilistic model, 概率模型8 c* F& d9 c# ]9 R6 q5 ?: ?
probability, 概率
6 n3 w5 d) n* x' r% ZProbability density, 概率密度
3 p6 f- Y, w) h& Y. YProduct moment, 乘积矩/协方差
$ ?7 W: |5 {, \& Z9 Z5 }Profile trace, 截面迹图
$ ]# m# F- z, wProportion, 比/构成比5 L5 s9 q' O1 Y
Proportion allocation in stratified random sampling, 按比例分层随机抽样- p2 H- T' ]5 o2 S% z
Proportionate, 成比例/ T' Y: ?+ L i# q2 Y
Proportionate sub-class numbers, 成比例次级组含量
# e) w' P) X: J% L( \1 [& B$ YProspective study, 前瞻性调查
5 E5 J$ w/ r# @8 @2 e+ E# l# pProximities, 亲近性
, q* I4 a! {0 {! \( GPseudo F test, 近似F检验
) `: e* `2 z0 a8 H1 oPseudo model, 近似模型8 Z1 Y0 g. w5 [7 O
Pseudosigma, 伪标准差
- }6 y. G) M1 |: ZPurposive sampling, 有目的抽样
5 o& J) |5 s0 M6 P- |$ ]) N( ZQR decomposition, QR分解
/ q2 v1 ~7 P: t6 E8 R1 j) AQuadratic approximation, 二次近似
9 M2 U3 m* \. J% T8 e! B- r. C! NQualitative classification, 属性分类/ v: I$ I& t2 p% k( i X) J2 u U
Qualitative method, 定性方法* [- }, A0 n/ ^( n1 _ h
Quantile-quantile plot, 分位数-分位数图/Q-Q图0 K3 W5 t, r( Y& i2 t
Quantitative analysis, 定量分析$ V" \' m$ ]2 y- t" Z: W% y8 W
Quartile, 四分位数
1 q1 V* `( q6 V+ d, V }3 F8 }Quick Cluster, 快速聚类
$ i: J; G7 O' V5 U# }& nRadix sort, 基数排序: I3 K8 p2 L2 L) N: r$ J
Random allocation, 随机化分组6 m8 v8 e: ?% o$ B. b% X
Random blocks design, 随机区组设计; `# L8 Y) [. v/ w5 L& _0 g+ ~1 i
Random event, 随机事件, s1 L' X( Q! q6 X
Randomization, 随机化! [2 v6 O9 S: F( U" j
Range, 极差/全距
* O1 w. Q3 w% U3 p5 KRank correlation, 等级相关
( e$ U0 D, C) e/ V9 kRank sum test, 秩和检验
" q, [( q$ A& F3 N) WRank test, 秩检验
+ k# `% l- ^( t( W0 ]2 M; uRanked data, 等级资料3 \0 M# s6 o7 u6 V
Rate, 比率
R' _8 n, n3 G) a3 e$ tRatio, 比例1 @9 K4 `! T8 p! M8 e
Raw data, 原始资料! B) D. o4 T, n, {8 a) B2 w" H
Raw residual, 原始残差( w3 o/ S. @, b. z9 i0 z
Rayleigh's test, 雷氏检验: Z- E1 P0 a: _1 e$ D& R
Rayleigh's Z, 雷氏Z值 ) ^, m, ]3 _/ O$ P1 c$ V ?% d
Reciprocal, 倒数
# E; a, S% o9 fReciprocal transformation, 倒数变换
4 p+ V# ~" D" W) Z dRecording, 记录/ y; P l u% G: |# v: M- x
Redescending estimators, 回降估计量; }! q, v# c# f! W
Reducing dimensions, 降维
; j! M- s& I" }: f e2 k, i# y. PRe-expression, 重新表达
" @, T y! j6 C! dReference set, 标准组' D1 b+ P2 b. P4 S6 g( t% E
Region of acceptance, 接受域4 X1 w5 c2 q1 i
Regression coefficient, 回归系数
/ P- P* w) h7 u0 G! u/ TRegression sum of square, 回归平方和
( E+ {0 W: b9 r0 A2 d1 s; PRejection point, 拒绝点1 T$ L3 e, k' l
Relative dispersion, 相对离散度, o4 P' W$ T8 v3 R6 }: Z
Relative number, 相对数# m" \* f! G( W& ?! ~1 R
Reliability, 可靠性; }3 F1 C) W; z* }2 I
Reparametrization, 重新设置参数
2 _7 i$ D( `, M4 S6 ~: {7 {Replication, 重复
+ C( U3 P- A* {0 |( ~Report Summaries, 报告摘要
2 i2 x# j K; e1 G2 iResidual sum of square, 剩余平方和
, y! O. `' }* J7 _Resistance, 耐抗性
5 C8 _% j: W, F. ?3 xResistant line, 耐抗线
4 O3 V4 b' `( s( w8 S( _/ K' {; h& wResistant technique, 耐抗技术
7 Y* d+ R1 F4 Y- F! f0 b$ yR-estimator of location, 位置R估计量, d/ n8 }' P R9 d. s
R-estimator of scale, 尺度R估计量
$ T3 R/ Z- G' \5 K9 y) m; jRetrospective study, 回顾性调查
- Q3 ?; A2 e/ a2 {: \$ S1 ~Ridge trace, 岭迹# N' A- e. T. W9 V
Ridit analysis, Ridit分析
" f& v2 }* Y! ~8 `Rotation, 旋转
5 t, N# V2 L' v( Q/ C7 _Rounding, 舍入4 }6 ^% v& w1 T
Row, 行4 ]: m6 m, X- {
Row effects, 行效应
" g. a! y" p" V6 MRow factor, 行因素. l `" R8 i; Z' ^
RXC table, RXC表
" I$ q, ]! M9 V! {0 G) iSample, 样本
* y' i/ j. J. B& e# g- T5 GSample regression coefficient, 样本回归系数
: U4 g# V1 N2 R* h& }2 V; uSample size, 样本量
+ ~2 h& U7 ?( rSample standard deviation, 样本标准差0 r6 b; x) H" b4 [
Sampling error, 抽样误差
6 L9 `- C. ^! W4 t6 U- H! bSAS(Statistical analysis system ), SAS统计软件包3 ~8 T# ~5 o- v: P& q* _
Scale, 尺度/量表
7 X2 ^( B) T1 W7 b. [' AScatter diagram, 散点图
6 V9 j& S C7 V& {. ]8 u6 hSchematic plot, 示意图/简图3 }0 q" V6 _3 S) b* |
Score test, 计分检验
; I1 f" ~9 j& X$ `6 s3 KScreening, 筛检- Q2 ?% }, m" b7 M. i1 i2 x* a* z
SEASON, 季节分析 ) c% j: f# F# q0 r$ t6 u0 H5 G4 Z
Second derivative, 二阶导数) F% {3 l( o; S" b" X. T
Second principal component, 第二主成分. ], F" {" N& t1 `
SEM (Structural equation modeling), 结构化方程模型 " d2 Y% u9 Z3 n0 Y l, w: j' |: |
Semi-logarithmic graph, 半对数图
1 _; O7 p0 |" r* T# a6 eSemi-logarithmic paper, 半对数格纸. a& J0 V( ?8 R, \
Sensitivity curve, 敏感度曲线
* C+ n5 Q# d' h. q$ g" YSequential analysis, 贯序分析7 W( L5 [9 e1 y2 C0 [9 c5 R
Sequential data set, 顺序数据集
% e1 s0 g2 y) K# VSequential design, 贯序设计
+ V0 P" [* |7 L6 F2 X6 N1 |5 c LSequential method, 贯序法, m( B, k% U, Q) D8 o
Sequential test, 贯序检验法
" t; }: p* ~4 V' g+ [" ~Serial tests, 系列试验
1 s# S+ y( K' @, j7 @7 d. RShort-cut method, 简捷法 " Y# l8 X/ V3 ^+ v
Sigmoid curve, S形曲线7 g5 N( [" T* s& c. j$ X# B7 z5 K, R6 I
Sign function, 正负号函数
3 h8 F) m0 S/ R: B8 C2 RSign test, 符号检验6 H' I0 F4 f& a9 o6 N/ i
Signed rank, 符号秩
, Y1 g7 q1 V$ Q. ^5 V9 h, uSignificance test, 显著性检验
) ?3 S) t7 y- c3 b" f$ HSignificant figure, 有效数字7 E4 `8 u* ?( o7 `8 m6 n9 i0 _: h
Simple cluster sampling, 简单整群抽样8 d" [4 r, g$ q
Simple correlation, 简单相关
/ H5 {8 }) d. Q/ w1 @6 I8 M ^Simple random sampling, 简单随机抽样
# N E+ d3 n$ U5 TSimple regression, 简单回归: z7 _ H8 L- Q
simple table, 简单表( ?3 q4 U7 J% Q
Sine estimator, 正弦估计量) X' ?+ @( n6 w! s( v
Single-valued estimate, 单值估计: `+ ?& H3 A3 `
Singular matrix, 奇异矩阵' Y$ x$ c5 u* _! V0 @
Skewed distribution, 偏斜分布6 @6 m6 X7 Q. e" m
Skewness, 偏度; t6 X( k5 V2 `
Slash distribution, 斜线分布2 Q- H7 ~; ^, a1 O) Y$ D3 D
Slope, 斜率! _# M3 C5 Y% b( k l% j% k
Smirnov test, 斯米尔诺夫检验) C3 o& U V* m _$ `
Source of variation, 变异来源/ P) F& t7 @% ]: \/ O
Spearman rank correlation, 斯皮尔曼等级相关
' o T9 R5 q% y/ j2 f# L: y9 N% HSpecific factor, 特殊因子3 o( E: z' R- i' K# z6 T
Specific factor variance, 特殊因子方差' X: Q' g# j. x2 ?; ~. e
Spectra , 频谱
5 B0 ]8 R) U$ j2 O- G4 wSpherical distribution, 球型正态分布- E, }; Y$ m- }" w7 _3 }* K
Spread, 展布" n! L0 O! w$ w+ y7 E' [; ^6 q3 [! m
SPSS(Statistical package for the social science), SPSS统计软件包
! A; B! N4 ^4 I! T S# aSpurious correlation, 假性相关
/ w- \& T0 f1 K2 I+ Z4 JSquare root transformation, 平方根变换+ R+ [7 T1 e1 Z0 V% B4 J4 N+ U
Stabilizing variance, 稳定方差3 |2 i6 X2 x7 O& r6 D- g
Standard deviation, 标准差: g4 M; b: Y) v8 o W! ]
Standard error, 标准误
1 ?4 D% O, x' f5 P8 H$ i: o, XStandard error of difference, 差别的标准误
( ` b: {1 B7 ? f0 mStandard error of estimate, 标准估计误差7 u( r3 W7 i: e1 v# x
Standard error of rate, 率的标准误
1 s" U$ }- J' M% ^' ?3 zStandard normal distribution, 标准正态分布$ {$ W* `! I; t+ l0 Z- J& ]0 i8 o7 S
Standardization, 标准化- h2 v" c& o& j$ C
Starting value, 起始值
) [4 h2 J2 s" G' Q% K0 B8 ?3 [Statistic, 统计量5 o+ k/ P5 u# P0 i
Statistical control, 统计控制
9 [1 y. }0 m# k4 L1 I4 H) LStatistical graph, 统计图
$ A/ y3 s' u0 Z7 H7 ]Statistical inference, 统计推断: P6 r5 x" V9 l8 W+ b% a1 x
Statistical table, 统计表
" u8 O/ F' Q# [( T9 L. \+ z9 `# xSteepest descent, 最速下降法
b. j( h6 ?8 UStem and leaf display, 茎叶图
+ z- L2 K' q/ l0 ?! u; Q# qStep factor, 步长因子; `- J. m# I( Z6 m9 G
Stepwise regression, 逐步回归
) O, A j$ ?& e" A$ ~+ R" uStorage, 存
% H: _4 T |, KStrata, 层（复数）
! f/ @, C; `. I" {; u7 a1 s/ J; mStratified sampling, 分层抽样5 z- f: ]; w9 R/ b9 H5 h3 @
Stratified sampling, 分层抽样& R( @/ W9 Q: g$ T. @' v" [" F
Strength, 强度; b8 i, [. W8 o( v& J
Stringency, 严密性: l6 q9 v- O4 [5 J8 q3 a( q. \ n
Structural relationship, 结构关系
7 y- B4 q" R$ G0 k9 R, tStudentized residual, 学生化残差/t化残差% Y# X: V) i9 w4 R4 M3 e
Sub-class numbers, 次级组含量
8 _! {8 b' d/ e% i. sSubdividing, 分割* t; H' N5 o" `/ d2 o
Sufficient statistic, 充分统计量
& s4 w/ h. L6 }# l2 u+ a$ YSum of products, 积和( i: {" J6 o, G$ ?% \
Sum of squares, 离差平方和. D9 O: n5 k6 }6 J4 }
Sum of squares about regression, 回归平方和
& `) @; F; h. o5 e9 wSum of squares between groups, 组间平方和
5 y6 }* C# Y" ` H1 H' C e/ Z1 r- YSum of squares of partial regression, 偏回归平方和
$ a8 w W2 b: ?- ^5 [) C8 rSure event, 必然事件
8 R6 x y4 [! R# c) n9 xSurvey, 调查
4 ~9 c6 c! k9 y# y% Q- \5 A5 E6 VSurvival, 生存分析. |6 W: g, N8 j8 V- Q
Survival rate, 生存率, X3 C u' O5 l2 o) }; `( L& q
Suspended root gram, 悬吊根图
% v* ]% h3 v7 v6 M% P3 Q$ RSymmetry, 对称7 W- J1 @. V) Y& Y! u8 U( I
Systematic error, 系统误差
+ ]0 x" A- K p7 G# k5 r+ RSystematic sampling, 系统抽样
* ]- w* F3 U7 Q3 dTags, 标签; W! W% }: t* y( O4 K6 X
Tail area, 尾部面积
& h1 L# O. R0 V4 T& o1 O6 z' ZTail length, 尾长1 {& \. p9 D5 _- |' T4 v
Tail weight, 尾重% A# f! }' ], L& D" D
Tangent line, 切线
; Y3 H1 L i- |Target distribution, 目标分布; `! b1 [& j& x! G; G. `3 A3 }
Taylor series, 泰勒级数# v' w% F/ l' O$ Q4 ?: I' R
Tendency of dispersion, 离散趋势* A8 A2 e% d; H7 h
Testing of hypotheses, 假设检验) ^9 J6 q5 V8 x9 T3 D% `& e
Theoretical frequency, 理论频数
/ n: x. B5 z0 F; ?, P% ~Time series, 时间序列. y+ M+ O# k+ f$ j5 ~$ C( ^& j) ^
Tolerance interval, 容忍区间
T1 P$ T2 l7 b* FTolerance lower limit, 容忍下限
; i8 a- q) e( j6 Y+ xTolerance upper limit, 容忍上限
3 P7 ^8 T5 y8 p+ ~Torsion, 扰率
* F) I8 m+ r0 A" a" s& mTotal sum of square, 总平方和3 Z# ~% z* N* D2 d
Total variation, 总变异3 X" D$ w h# x% m
Transformation, 转换
3 @* \! K8 x7 P2 o6 uTreatment, 处理
& d* n- O' l- i- n' ~9 n$ l! ?Trend, 趋势1 v* P* _6 m0 Y4 e/ Y( {5 I
Trend of percentage, 百分比趋势
" d4 l' A: t V$ \8 aTrial, 试验5 p' y! p6 n. z* U' ~$ w
Trial and error method, 试错法2 {# C. \8 Q8 Q
Tuning constant, 细调常数7 i9 J2 e: O, m1 P0 ~
Two sided test, 双向检验
s( P. e9 p5 ^# o8 Q+ k0 |Two-stage least squares, 二阶最小平方/ s8 B x" t9 z6 P, N
Two-stage sampling, 二阶段抽样8 ]. P: A( _! d
Two-tailed test, 双侧检验
! j/ A* @/ ^3 S/ q2 o J& z# dTwo-way analysis of variance, 双因素方差分析
: A+ k6 R( P0 h# R ^9 x& Z8 dTwo-way table, 双向表
2 v W, G2 C* N) [) E, BType I error, 一类错误/α错误; |- c* K5 P7 O
Type II error, 二类错误/β错误
! D* C; m5 M9 M" l+ Z* x4 j9 MUMVU, 方差一致最小无偏估计简称6 {1 `! g% a- ?7 V# ]1 p# L
Unbiased estimate, 无偏估计# l& D( a) U6 y0 q3 Y
Unconstrained nonlinear regression , 无约束非线性回归. J9 \0 j4 l0 x7 }
Unequal subclass number, 不等次级组含量9 n# p( g2 ]: Y) v
Ungrouped data, 不分组资料
8 Y2 G. l, z& y; jUniform coordinate, 均匀坐标) K( I$ d8 c3 s( P! l1 B T" c
Uniform distribution, 均匀分布
! Q* j+ P9 S/ }' h' g$ [; F YUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
: C0 j9 J2 C% t7 `$ mUnit, 单元0 _2 Y; B" x6 U
Unordered categories, 无序分类6 r" O, T$ l2 E. w" }
Upper limit, 上限
D' A0 Y1 s% W* t1 FUpward rank, 升秩
2 [" ]6 g6 G1 I# bVague concept, 模糊概念' Z% J0 M8 ^, n! `0 C. x
Validity, 有效性0 v! Z. G3 v: e" ]! `! ^
VARCOMP (Variance component estimation), 方差元素估计
5 p% d: h( H8 C% H' @4 ]4 [# [Variability, 变异性 {2 L) f5 g4 w3 [" ~! \
Variable, 变量
% b. {8 J4 | K& y4 Q7 D& zVariance, 方差
' H* q. W3 Y+ r7 @$ G& f W. FVariation, 变异
" F) {6 c, ~* L E# f }" rVarimax orthogonal rotation, 方差最大正交旋转
4 B. N/ y. c: M j: uVolume of distribution, 容积% U6 S! t4 g# f
W test, W检验
E% \, L6 ]" f) l6 U( H" q9 IWeibull distribution, 威布尔分布, Z* y J* ]7 M- x3 j; Z7 p
Weight, 权数. d! u0 z* e ^' N0 M6 P7 D
Weighted Chi-square test, 加权卡方检验/Cochran检验- L" u: x2 P, f4 m
Weighted linear regression method, 加权直线回归
0 m$ q! q: B4 \3 b: v G7 DWeighted mean, 加权平均数
0 J8 I+ N# a2 T6 K9 k9 m5 hWeighted mean square, 加权平均方差$ d- L1 E7 u6 G; F- _
Weighted sum of square, 加权平方和% y* {' E" W/ y4 ?# {$ `
Weighting coefficient, 权重系数9 t* `4 q x' _, r0 @; m
Weighting method, 加权法
6 U: M; X6 } }1 o7 OW-estimation, W估计量
L3 z5 q# ^) s- R/ _W-estimation of location, 位置W估计量$ c9 k- p/ _7 y4 s, [+ i" L( }' B2 V
Width, 宽度
- u: I# f+ l2 q- |Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验8 m* p' F. W5 _0 \* {& z
Wild point, 野点/狂点+ C8 b9 E+ l( d* ]- K" Q: r* J
Wild value, 野值/狂值: b r [( h( W! D1 J
Winsorized mean, 缩尾均值
" n7 o9 c k2 ^7 v7 dWithdraw, 失访 ' B+ ~' Z+ e- b7 c# T- q+ y
Youden's index, 尤登指数
% g, K! U: z$ {Z test, Z检验
- J6 c: I" z- S1 q) pZero correlation, 零相关4 a3 J6 W1 o& y% F; C- Z- j
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
