|
|
Absolute deviation, 绝对离差
" F5 f- t# R+ A) g' K" B3 u. eAbsolute number, 绝对数( ^+ `4 Q. ^- d! F
Absolute residuals, 绝对残差
# T( {3 ~9 _7 n: C) DAcceleration array, 加速度立体阵) e: C: |( y6 W$ B6 R# i4 o E
Acceleration in an arbitrary direction, 任意方向上的加速度
$ @( U2 L7 Z5 A+ M3 fAcceleration normal, 法向加速度$ v3 M* \; x/ Q9 h: o+ M' y
Acceleration space dimension, 加速度空间的维数
+ {3 B8 d q) ^0 x( pAcceleration tangential, 切向加速度
$ r" w6 i6 Y- |# kAcceleration vector, 加速度向量8 C% t* E1 N3 g* E+ ?- W- Q7 G0 o/ W
Acceptable hypothesis, 可接受假设/ R2 Z/ u0 I+ y. P9 z$ v$ o
Accumulation, 累积0 v5 n# ^$ z% [. f( v' g* D& x
Accuracy, 准确度$ |2 e2 f' w) z. }' J
Actual frequency, 实际频数
: I: W5 r% j5 r# a. HAdaptive estimator, 自适应估计量6 s6 M; u% J1 r* x
Addition, 相加9 q( x9 L' W" G. s q1 S
Addition theorem, 加法定理3 [5 a9 ?( Y- N0 j: ^
Additivity, 可加性
2 O# A' i8 e' PAdjusted rate, 调整率' R+ A0 A4 w; j2 u: a" t
Adjusted value, 校正值
- i' p! z0 K- f4 ~& P* rAdmissible error, 容许误差5 N f3 l6 B6 L: M( d1 |8 j8 q, X
Aggregation, 聚集性
1 P4 v5 y- t; xAlternative hypothesis, 备择假设
0 K- F3 b$ ?6 U& U7 WAmong groups, 组间
* R2 X+ W/ n" [3 `& ]- ^# D( t# VAmounts, 总量( n8 U1 c$ e% t( N2 r: K" t! w
Analysis of correlation, 相关分析- w! L* H& h8 h) g( w b$ {7 W; T
Analysis of covariance, 协方差分析( `8 `1 Q# w6 q. U4 }9 V# h' M
Analysis of regression, 回归分析
4 G8 v% B6 v# M i" BAnalysis of time series, 时间序列分析, H5 A" k) R+ V+ X* g/ X
Analysis of variance, 方差分析
, E( S. P. g- c8 rAngular transformation, 角转换
, f* y& A0 G5 C) F% \+ qANOVA （analysis of variance）, 方差分析7 x( t7 ~+ {. h1 U* A9 K! v
ANOVA Models, 方差分析模型! l1 F `0 k7 E8 w! {; B
Arcing, 弧/弧旋
5 |' V3 z) A( qArcsine transformation, 反正弦变换
* `3 M" ^$ e& I+ L9 E9 e/ VArea under the curve, 曲线面积
/ h# t5 t- U' o: X( W. mAREG , 评估从一个时间点到下一个时间点回归相关时的误差 " h) f' p4 o7 U
ARIMA, 季节和非季节性单变量模型的极大似然估计
: ]; U0 z* N$ W9 s$ _5 _Arithmetic grid paper, 算术格纸. D' b) o5 ^0 q, g- i2 T
Arithmetic mean, 算术平均数! [' j) J7 l4 @" ~
Arrhenius relation, 艾恩尼斯关系# B- c1 h$ R2 g, w6 k+ I' D9 ?- o5 l
Assessing fit, 拟合的评估5 [' u9 j% g0 _) \/ v
Associative laws, 结合律, _; p- g$ @! ]
Asymmetric distribution, 非对称分布* f r) E3 g. b6 U1 y3 h+ K. r: L
Asymptotic bias, 渐近偏倚/ N4 C e! ?& n l9 u
Asymptotic efficiency, 渐近效率
8 T! g0 M; \9 W6 s0 O* m' A' |9 z6 eAsymptotic variance, 渐近方差
A( w) L v0 P. K5 fAttributable risk, 归因危险度
) D+ c, h: N* o. k+ p4 @Attribute data, 属性资料/ U% ^# W1 G% x o( z( ?% z: x- I
Attribution, 属性, o: z7 w$ w+ x! l" I1 T
Autocorrelation, 自相关
2 W* v- Q' z6 M+ KAutocorrelation of residuals, 残差的自相关3 S( [: w: v1 _; j
Average, 平均数! J: Q& i# h2 W2 T6 S
Average confidence interval length, 平均置信区间长度+ s. g. D3 k W( z% f6 ^' F; C
Average growth rate, 平均增长率2 _/ b C s: \2 ]2 J' t
Bar chart, 条形图
* a) \- x( ~9 _% @5 i, {4 zBar graph, 条形图
! o4 ?- D: j$ C+ k" eBase period, 基期+ [8 d5 M" }3 m
Bayes' theorem , Bayes定理
( k$ Q. P" B( W5 A; u Y5 z& DBell-shaped curve, 钟形曲线
& e5 X) p: _7 Q' l- A) lBernoulli distribution, 伯努力分布 d' U+ e$ ]7 X
Best-trim estimator, 最好切尾估计量2 l: a$ Q4 Y: n# q0 |7 t
Bias, 偏性2 M: X5 s9 w$ k" i* i% n
Binary logistic regression, 二元逻辑斯蒂回归
& D/ n. m/ A3 e7 q& C/ q0 FBinomial distribution, 二项分布
) H4 e+ f1 r4 M. O. ZBisquare, 双平方
% Z# g8 J/ | j7 {1 J' ?4 }8 gBivariate Correlate, 二变量相关
h2 h) F0 R# ?! F5 UBivariate normal distribution, 双变量正态分布 C. k" @7 {! G* R2 r
Bivariate normal population, 双变量正态总体
# T, a- m' q0 r+ m# @Biweight interval, 双权区间
" X0 y5 z3 k; O& ^' ?6 YBiweight M-estimator, 双权M估计量1 v2 k( D3 F$ k" k
Block, 区组/配伍组
. z3 a+ W, j. h( C' QBMDP(Biomedical computer programs), BMDP统计软件包; C8 C' k: T% Y( L1 b0 ^
Boxplots, 箱线图/箱尾图1 C) z& x3 I* T! a$ I' @
Breakdown bound, 崩溃界/崩溃点
, ?" [8 z8 e6 X; d0 vCanonical correlation, 典型相关. e' e$ X* C1 H0 }1 @" Z0 L
Caption, 纵标目
. g" x) M# i3 XCase-control study, 病例对照研究
4 `) b% p9 O+ c6 N+ T5 J5 J3 rCategorical variable, 分类变量
( P0 S; V M; B5 kCatenary, 悬链线
" ~0 |- X0 N p# V- Y# q; D* VCauchy distribution, 柯西分布
. f0 C; N6 X" ]4 c5 NCause-and-effect relationship, 因果关系6 @5 g' }; A' Z2 `
Cell, 单元: F2 W+ h }; s% [5 p1 G
Censoring, 终检
! M+ M6 z/ W3 m% i4 D! ] {Center of symmetry, 对称中心
' Y1 [4 E* {. w/ O' `" lCentering and scaling, 中心化和定标
6 I0 Z6 F& q; }7 W* vCentral tendency, 集中趋势
, b* B+ W3 }+ J* }Central value, 中心值5 Q& ?( S, [- Q
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测5 ]! ]' g. ?& P5 z# e0 s; F
Chance, 机遇* E9 S7 J( h; h
Chance error, 随机误差
* R! z& F7 B" U( H# w7 p4 e/ DChance variable, 随机变量
- ]6 a# O' G" J6 }6 Z- W) ?Characteristic equation, 特征方程
" ?, C, J3 r8 y2 l' bCharacteristic root, 特征根
- |9 B" X; s5 F. t& JCharacteristic vector, 特征向量- O* R- M; h( U, j, }7 N
Chebshev criterion of fit, 拟合的切比雪夫准则
; t+ x, z. r! \& }; yChernoff faces, 切尔诺夫脸谱图
4 P v+ k' ]/ N. e# V& s' QChi-square test, 卡方检验/χ2检验# a: r- |& q h. F0 E1 z, k \& [1 v
Choleskey decomposition, 乔洛斯基分解" }4 x7 x9 G5 ~, `1 r4 ~( Z9 c
Circle chart, 圆图
' q/ q) L& U( W! E4 G6 JClass interval, 组距
, @* C7 c6 [3 ?6 O7 W3 e* |Class mid-value, 组中值
, C- U1 G: E! X2 Z; W# rClass upper limit, 组上限& W- e6 C& @4 b* P% I
Classified variable, 分类变量5 _: o. I- }4 |" `
Cluster analysis, 聚类分析% L7 n1 |' \& J( H# S I* m& `
Cluster sampling, 整群抽样
$ i9 {% x+ ~8 Q9 ZCode, 代码
; j1 \& X5 d: Z$ c! ECoded data, 编码数据 i j9 J* o7 w/ T! ~
Coding, 编码# `5 w5 P5 Z0 z- A
Coefficient of contingency, 列联系数6 T* g- z# n& V7 N4 Z# c
Coefficient of determination, 决定系数% l, g, X; S) y, G# v9 ]
Coefficient of multiple correlation, 多重相关系数5 e+ R7 x. D- _2 F0 t& u) `; c
Coefficient of partial correlation, 偏相关系数4 z! |1 v& d7 M* n& U+ T/ {0 Y2 P
Coefficient of production-moment correlation, 积差相关系数
" {5 l! L2 k/ @3 q/ F- `! eCoefficient of rank correlation, 等级相关系数
! |# e' K3 W6 M' _Coefficient of regression, 回归系数
# d! `& s1 G) h6 }% SCoefficient of skewness, 偏度系数( G/ m7 u+ C k4 k
Coefficient of variation, 变异系数
8 m" ~/ I3 ~, U; W+ n* TCohort study, 队列研究( ^3 u" a1 C* X$ R9 O! D# |
Column, 列# u) Q$ \& I( n& G! g; x) B
Column effect, 列效应
" S+ S" ]" C4 R( _Column factor, 列因素8 e8 N! V/ h4 H4 r2 c/ X
Combination pool, 合并
; Z; S `3 w; q# rCombinative table, 组合表& G4 |8 q4 A3 X0 }6 }$ }, A% d
Common factor, 共性因子: d5 i1 S* m) K0 X0 @( O
Common regression coefficient, 公共回归系数' E& Z8 i" @/ [8 [2 F' \5 F
Common value, 共同值$ J- m u1 S3 d/ p- Y! s! w7 V
Common variance, 公共方差
$ ]- k1 q8 a7 F; P" [! BCommon variation, 公共变异
+ }* d$ a7 ]3 `7 s. q2 w: lCommunality variance, 共性方差- b& \, n, K! b; y) ~; ]
Comparability, 可比性
S6 i! g7 \5 ^. t: P3 R) ~8 xComparison of bathes, 批比较
$ s) c4 K, J$ ]# HComparison value, 比较值
- X" b/ u0 B/ A3 ECompartment model, 分部模型
, w- H4 ~% E) g" \( uCompassion, 伸缩
3 L7 }$ g! J5 CComplement of an event, 补事件* v% M3 w, w* W2 Y4 }; }
Complete association, 完全正相关4 J" ?: F; D0 E/ K( {) \- C
Complete dissociation, 完全不相关
r9 B. M$ u/ z' F" BComplete statistics, 完备统计量& A; B1 ]1 }6 f' N6 s! I
Completely randomized design, 完全随机化设计
& E2 E; p) E3 \+ LComposite event, 联合事件- h) } o/ B7 d" h* U) ]
Composite events, 复合事件
; n# r- l8 s2 c7 v, h0 y5 VConcavity, 凹性
! A+ v$ Y5 Y' e; l! F1 z; QConditional expectation, 条件期望
% s' o2 m3 {/ z- oConditional likelihood, 条件似然
3 \/ i: f. {1 N$ I5 w9 gConditional probability, 条件概率
5 ]: j8 K9 P; ~1 b- i3 vConditionally linear, 依条件线性! F i9 B, {) r4 a
Confidence interval, 置信区间. h0 g# U0 {7 R4 S
Confidence limit, 置信限6 y3 X0 V+ s5 P% v0 }9 R
Confidence lower limit, 置信下限6 j, k) V, T& i2 l$ f/ [; j+ P; ?
Confidence upper limit, 置信上限
2 r8 {& _/ W$ Z( `3 ^! CConfirmatory Factor Analysis , 验证性因子分析( Y% @: o8 b( r& d% Y& ?+ M
Confirmatory research, 证实性实验研究6 [( Z3 J' s) h# |
Confounding factor, 混杂因素
) g+ ]! c+ Z; M. ZConjoint, 联合分析7 O$ p% ^! i6 R) ~7 I* f4 Y
Consistency, 相合性
, z" i; Z3 Q7 d- V+ [( Y. M' `Consistency check, 一致性检验
: m" K- y3 c, t' I( n. mConsistent asymptotically normal estimate, 相合渐近正态估计
# M& o6 z4 d+ GConsistent estimate, 相合估计
. z/ \2 {. k9 d5 s9 H% k# T \Constrained nonlinear regression, 受约束非线性回归: p, F' a9 f. j" Y4 [& \% C9 k' n) D
Constraint, 约束$ P* X$ p/ z7 C3 ?( X
Contaminated distribution, 污染分布: m- v. d3 I' f6 ~5 s
Contaminated Gausssian, 污染高斯分布
, b: P! W! t: p$ j( X+ O& fContaminated normal distribution, 污染正态分布
9 C1 L; ]' J, @ g+ hContamination, 污染. \2 |+ ^5 `0 @! e3 k5 L
Contamination model, 污染模型
6 H/ Y& Y6 O' e% n- qContingency table, 列联表
! I9 f: U @$ [/ I' WContour, 边界线
) U. Q* C1 _( y7 lContribution rate, 贡献率
/ C( ]- {& m0 f3 y4 M1 ?8 {; \* eControl, 对照
: H) u, }$ v R' U$ eControlled experiments, 对照实验
7 M# t% F' v/ z% z2 e* H% a+ c4 BConventional depth, 常规深度! f# T; j0 h0 n3 N/ V
Convolution, 卷积
* x$ ~: D. ~2 Z9 tCorrected factor, 校正因子2 J4 _+ B) f" T. e) o! p* q* O
Corrected mean, 校正均值
7 D; L3 Y- ^4 F) j& U4 HCorrection coefficient, 校正系数7 i# C4 N- E I, _& S+ A) A
Correctness, 正确性
/ I, O# K. z o8 l( ^1 W4 t: n4 HCorrelation coefficient, 相关系数
1 w3 k7 v; l7 L" w" {7 ?Correlation index, 相关指数
, Q8 f6 O d, |4 m* }& i6 ZCorrespondence, 对应1 Q( V" T4 f" H) [' L! s4 S: \ b
Counting, 计数
% z; J. ?. z: ]9 D" O* _4 U- pCounts, 计数/频数
' _; t5 B1 y0 [Covariance, 协方差
9 _; g e) W/ Z5 NCovariant, 共变 / z6 B6 n& M+ m% B; K; @
Cox Regression, Cox回归6 Z! t q# ~6 v( g2 Q$ m
Criteria for fitting, 拟合准则5 _9 d( j( S5 { |" v% |
Criteria of least squares, 最小二乘准则/ ~ G6 k8 Y) q* r4 k6 m5 r) d
Critical ratio, 临界比7 {2 W# v5 [. P$ i6 N5 _
Critical region, 拒绝域
; T p/ S) p M& s) Z5 ~7 p. JCritical value, 临界值
5 p' O5 R, S( D* }& p, H" ]- kCross-over design, 交叉设计
( c$ v/ ?( t* ?$ f0 Q% G" _Cross-section analysis, 横断面分析8 U# |7 v4 n$ F
Cross-section survey, 横断面调查& T7 n/ J% w- L! u ~5 I, l
Crosstabs , 交叉表
5 U/ m K8 \1 q2 _" g6 pCross-tabulation table, 复合表
/ P; o' z9 c. H! g7 }Cube root, 立方根1 _1 }; k t- p% f1 L
Cumulative distribution function, 分布函数
$ h! `, L4 X/ o0 v0 W5 i3 _Cumulative probability, 累计概率
: ~. B8 x( F5 S/ H+ S. {Curvature, 曲率/弯曲
2 \ Q/ L9 d1 z3 u0 ACurvature, 曲率# S; c W2 h" U3 k. m
Curve fit , 曲线拟和 9 g. D/ }1 z3 R5 u5 Z6 r% G
Curve fitting, 曲线拟合
: x: O4 L3 U) mCurvilinear regression, 曲线回归1 E" A* J) ]) @$ O6 H
Curvilinear relation, 曲线关系- ? K) ~( ^/ R( g' L& T3 [
Cut-and-try method, 尝试法/ ]# l+ C" O3 w8 h' J3 P
Cycle, 周期
9 v" L, E X2 D8 h0 ]" CCyclist, 周期性4 n% p4 M- u# v% {
D test, D检验" E$ D+ ] c F) O- X
Data acquisition, 资料收集. r; L0 C0 `+ I; }
Data bank, 数据库7 q3 \9 D, g$ ~% x& `
Data capacity, 数据容量1 R% W) Z% W' D5 I
Data deficiencies, 数据缺乏: {+ f# o+ Q; Y* N# u$ U
Data handling, 数据处理$ k; j2 l! X0 @4 B
Data manipulation, 数据处理% C% }/ N+ E) A
Data processing, 数据处理( L# s( V2 P3 U1 h' j
Data reduction, 数据缩减& E7 o+ Y }$ L0 h; Z4 q2 B
Data set, 数据集8 z4 h- M9 C, W' t
Data sources, 数据来源 g, m/ k; h, m
Data transformation, 数据变换
& l+ k/ H. L, L Z1 o' a! a# zData validity, 数据有效性
- z& r5 c7 b* g5 ~/ v$ N6 O5 UData-in, 数据输入3 P, ?/ n$ c1 R) g+ f- _- q& L, ^
Data-out, 数据输出
' m% w# E% d7 S! N: yDead time, 停滞期
e, p& b; p# Q( TDegree of freedom, 自由度# Q8 W& l2 y$ l& E) E( D
Degree of precision, 精密度
C+ r) b6 A, Q# S8 eDegree of reliability, 可靠性程度# v# H, r U: _+ J1 j- X
Degression, 递减% z! c5 g8 \8 n0 j# V7 s
Density function, 密度函数( p/ a6 b6 g" T/ ?! B0 t3 ?- e
Density of data points, 数据点的密度
. D( |( I, Z5 ~4 ^* V; C+ {Dependent variable, 应变量/依变量/因变量
0 \ W3 H, d5 s1 `5 cDependent variable, 因变量
+ i6 Z. v4 b( h8 zDepth, 深度
; k1 n( F1 ^+ q; eDerivative matrix, 导数矩阵
) H' v2 Y1 C0 p& K6 P/ i% fDerivative-free methods, 无导数方法
3 {4 N; e4 b# N* i2 KDesign, 设计
' z8 C1 [4 D2 L6 j8 @; w: R6 SDeterminacy, 确定性
6 u; p, ~4 t/ J+ d+ r7 W1 qDeterminant, 行列式$ Z+ ^. w1 [( v k: o2 S$ P6 ]
Determinant, 决定因素
( R% M3 {- B) L+ a3 J1 SDeviation, 离差
6 _ N$ z! m" M& ?9 QDeviation from average, 离均差
; B; P3 M2 b" Q/ EDiagnostic plot, 诊断图. p+ y" S9 e& ~0 T, R8 J8 k
Dichotomous variable, 二分变量1 G0 v7 X' h* p
Differential equation, 微分方程
" X* ]4 j3 p' b4 eDirect standardization, 直接标准化法
' j& l4 a+ X5 w, [; TDiscrete variable, 离散型变量
+ e0 e9 c/ ` ^, L0 |/ c' oDISCRIMINANT, 判断
9 y# l' M( s4 G% oDiscriminant analysis, 判别分析
1 ^8 J, f5 O W) L& y& Z4 ]Discriminant coefficient, 判别系数9 Y0 b1 [" I0 c% G3 W4 r
Discriminant function, 判别值' o6 ]% K- W f0 k$ V7 z9 Z
Dispersion, 散布/分散度
8 w5 M) ^$ e$ {8 i* KDisproportional, 不成比例的, K% q' ^3 u5 t Q! }1 X7 }6 d
Disproportionate sub-class numbers, 不成比例次级组含量
6 o2 D0 {# c+ _Distribution free, 分布无关性/免分布- }1 M: j% h, {" F$ ^' e
Distribution shape, 分布形状
5 d) b0 R2 g, w4 }Distribution-free method, 任意分布法8 \1 f, R6 D* b/ N" v) Y n
Distributive laws, 分配律/ o: v. x4 k- T$ r) p; d
Disturbance, 随机扰动项
- X+ z' _' H% J" KDose response curve, 剂量反应曲线/ F& \! \) v; l4 S4 U# x
Double blind method, 双盲法
, b% R) f0 w6 K6 R& sDouble blind trial, 双盲试验- i$ h( P" z0 K$ } C4 {8 T* }0 z4 x
Double exponential distribution, 双指数分布
9 K8 X, K$ j. F$ TDouble logarithmic, 双对数
; q5 z% h! g8 G7 m4 S! HDownward rank, 降秩
. ?/ A1 N3 [: v) r# O, n9 ]Dual-space plot, 对偶空间图4 K& x! `3 v7 g1 l" m2 A7 w& K7 t
DUD, 无导数方法4 x. q- D5 k- q- [! T5 F
Duncan's new multiple range method, 新复极差法/Duncan新法
/ N5 t8 p) M4 J2 \' WEffect, 实验效应5 t" q6 e' w# N, X _0 ^; P& `6 v5 Z
Eigenvalue, 特征值3 t' s( G: A1 k" } |* J: ^- i
Eigenvector, 特征向量' k8 T+ j' O% Q3 a( G
Ellipse, 椭圆- P4 S3 p6 m& \5 v2 U8 x
Empirical distribution, 经验分布
$ Q2 U5 c7 p. CEmpirical probability, 经验概率单位
- V) u" u; X& e/ d" MEnumeration data, 计数资料
4 B( W" Z) F! B1 _& ?5 Z- |+ xEqual sun-class number, 相等次级组含量2 u) U8 X8 P$ E" l, {4 N! N* V' \
Equally likely, 等可能
3 n) R% K' K0 r$ J! [2 qEquivariance, 同变性! x" m% f% M: h( A! k' i
Error, 误差/错误
& D" N6 p+ a. e' @& v3 BError of estimate, 估计误差
( |# \9 g+ F4 C' P: P# RError type I, 第一类错误
2 l$ c( H5 o: gError type II, 第二类错误
" z! B8 a+ d1 p' A) jEstimand, 被估量
v8 T8 R( x' d# w# G) h5 Z. aEstimated error mean squares, 估计误差均方2 _& x8 {" g" X _! \
Estimated error sum of squares, 估计误差平方和, ^9 U% G& q' |0 g; w- _; C; ]1 b
Euclidean distance, 欧式距离, ?+ ]" X+ [ L3 t. l0 N; T
Event, 事件: |3 {4 r3 l3 o$ X( K' o+ K6 I( M. [3 {
Event, 事件4 x" D! r1 Z0 {
Exceptional data point, 异常数据点
/ a& n- U% D& H( b' p! gExpectation plane, 期望平面$ U/ z4 D! L/ l3 B
Expectation surface, 期望曲面
( w- ]& T) O1 ^2 BExpected values, 期望值% `/ i! u% V4 {/ L# M6 l& f# ^# s
Experiment, 实验
$ }9 P7 P. l! v, c g7 nExperimental sampling, 试验抽样
0 U" v+ C: x) L. b+ K+ q7 gExperimental unit, 试验单位& z: L# F# C1 P- Q% v
Explanatory variable, 说明变量- A0 k& g7 y+ v$ M7 {
Exploratory data analysis, 探索性数据分析( G% P5 y& V `1 Y" D
Explore Summarize, 探索-摘要2 m1 t8 a! p) z4 f6 ]! F
Exponential curve, 指数曲线- B$ C+ R9 {8 i- G }2 X
Exponential growth, 指数式增长
% _+ y! O$ Y3 D( t) C; Y$ VEXSMOOTH, 指数平滑方法 C: d9 `, l5 v9 h) `/ P3 j
Extended fit, 扩充拟合" S+ m$ {5 C- ?8 X
Extra parameter, 附加参数
6 R- r. {: \7 u1 u r, DExtrapolation, 外推法9 {) L1 Q7 d6 Q
Extreme observation, 末端观测值
# h$ H0 r0 f( LExtremes, 极端值/极值
0 |5 @4 @8 Y! D2 y m' gF distribution, F分布
( x0 L5 C7 t! E1 c- cF test, F检验; I- l8 O3 F! z! l4 u5 s0 v6 Y0 V2 g; ]
Factor, 因素/因子( p: @* d: \- v; o( ?
Factor analysis, 因子分析
: A& F+ A; [5 F2 y7 A3 LFactor Analysis, 因子分析
* P* F# p* J2 G# Z- fFactor score, 因子得分 ( ^2 r( Z5 r" I) o1 g( I |! P @
Factorial, 阶乘7 P# ^: R* i' t8 {# b
Factorial design, 析因试验设计5 i7 S) x; P2 F; ~/ |7 \4 N+ U* l
False negative, 假阴性
! u. @" t# c4 Z0 s: J/ ?False negative error, 假阴性错误5 m; A! X7 p5 H8 k6 c! B& c7 l& ?
Family of distributions, 分布族
3 \" f+ r/ U O; _$ ], F, J9 BFamily of estimators, 估计量族
+ g' g6 f4 a( Y' N; e! g" rFanning, 扇面
+ y7 c5 M0 c) J6 B9 o/ kFatality rate, 病死率
- p5 {' [+ E" d( n' @: EField investigation, 现场调查
8 `0 l& D7 _8 wField survey, 现场调查# _8 F8 g- ]9 `1 d4 M
Finite population, 有限总体
/ c) B7 U9 a0 n: FFinite-sample, 有限样本! v3 Y: J0 z0 Q% ]- c
First derivative, 一阶导数
- u L; U, D i# U7 ]First principal component, 第一主成分
3 P0 P1 E. v. T v& NFirst quartile, 第一四分位数$ l1 x* L; [! B7 d
Fisher information, 费雪信息量
; P; K' i9 U- L2 B, n& g1 n8 A1 [Fitted value, 拟合值4 \0 B! R9 i5 W1 C$ ?+ N
Fitting a curve, 曲线拟合
% S; a3 [6 a( K4 c' q) FFixed base, 定基: y$ L+ W- v* O' A3 n! h9 O- n
Fluctuation, 随机起伏
x4 m# V' s& R# c" M; g( ]/ ?Forecast, 预测* S* ^( H- a# n C, {0 K6 g, h
Four fold table, 四格表3 t4 |1 `/ W8 Y
Fourth, 四分点 f( b8 Q* y7 z
Fraction blow, 左侧比率' J7 ~9 B* n5 n; N# T! @
Fractional error, 相对误差
9 m, e! J. T5 t F: |Frequency, 频率1 o: A+ I7 E' Y% I& e6 q0 l# p! g
Frequency polygon, 频数多边图& d* {7 T) I6 q
Frontier point, 界限点( V/ h Y) F8 M) q) A' l \
Function relationship, 泛函关系1 k0 z0 {( Y. N+ k; A8 x
Gamma distribution, 伽玛分布
, ~6 p! y) d2 B$ V7 U5 h1 Y( L$ yGauss increment, 高斯增量
$ r$ n. F/ m3 O% m9 n z! `4 JGaussian distribution, 高斯分布/正态分布
) }) R8 F$ A- G+ RGauss-Newton increment, 高斯-牛顿增量, w; f& @: ]: k) B$ w6 b7 r
General census, 全面普查
2 _: p( h3 b# i3 K$ n8 xGENLOG (Generalized liner models), 广义线性模型 ( K! k A9 W$ `: v& q0 I
Geometric mean, 几何平均数
; d) N9 Q6 f* r( x. hGini's mean difference, 基尼均差. w. C5 I& I: q# [# ?
GLM (General liner models), 一般线性模型
3 s0 [% \' O. K8 JGoodness of fit, 拟和优度/配合度2 @0 J# c# [' M5 a' s8 r
Gradient of determinant, 行列式的梯度; t' R0 o/ o {" X, t
Graeco-Latin square, 希腊拉丁方
" W$ [% \2 C0 l1 |& w. eGrand mean, 总均值* U- q( B' E/ z% B% e9 w8 C1 P
Gross errors, 重大错误$ `5 a% W @& @# v. B2 |5 E
Gross-error sensitivity, 大错敏感度
0 [7 v. r! o4 j( y1 `! I) QGroup averages, 分组平均) M6 j9 U6 v/ u! x! D$ e) P+ h
Grouped data, 分组资料2 B/ b9 S3 a. F1 V' l
Guessed mean, 假定平均数
* ~1 Y- m4 F4 d' B0 w, m" f2 [' Z& ~Half-life, 半衰期" F! y" D: p0 m8 } l% O
Hampel M-estimators, 汉佩尔M估计量, _$ D5 M& X1 g& C/ W% P" i' t
Happenstance, 偶然事件
4 `. n8 K. v2 P, r4 I8 n' _# ?Harmonic mean, 调和均数8 C" E! i- B# Z- v- ]3 D
Hazard function, 风险均数
& F" f5 T2 B/ H( Z* KHazard rate, 风险率
+ \4 L' H! A" U" s1 O }Heading, 标目
$ T5 y2 n7 U2 Q- b1 WHeavy-tailed distribution, 重尾分布) z# w4 c" t% N7 E7 D8 O
Hessian array, 海森立体阵
( o. f; t: x9 M2 B* `Heterogeneity, 不同质
# O& S& w! @2 f0 L# uHeterogeneity of variance, 方差不齐 3 U$ v3 }* c6 F1 o. l( V/ M
Hierarchical classification, 组内分组
1 Q: M4 Q9 G1 b( X! D& f$ ^/ ^, iHierarchical clustering method, 系统聚类法
/ I: r% b. w& W" X# jHigh-leverage point, 高杠杆率点9 ]. b* K& c" \6 X
HILOGLINEAR, 多维列联表的层次对数线性模型
8 v. a( i4 d2 v/ w3 jHinge, 折叶点
3 t& T$ K T6 F1 YHistogram, 直方图+ g4 M% ^! ]8 i7 N8 S% b. \
Historical cohort study, 历史性队列研究
, @& Z' R7 K8 b0 _8 x5 J- D; yHoles, 空洞8 e! L7 o% g1 h3 k# s4 { R3 F' ~
HOMALS, 多重响应分析
3 T' O+ H/ _. WHomogeneity of variance, 方差齐性
( b2 O1 w- y4 ]5 p) Y( d5 jHomogeneity test, 齐性检验
, m+ y/ n1 |9 q6 u9 v- A5 v) N9 A3 aHuber M-estimators, 休伯M估计量4 u E+ M. C' p" h+ X
Hyperbola, 双曲线
% Y. Y+ b. q: H/ F2 J4 eHypothesis testing, 假设检验$ v9 d% u' ^& C6 ~. q. f
Hypothetical universe, 假设总体7 R `% y% R% ?9 }$ @( W
Impossible event, 不可能事件+ K! r/ `! u6 H; t
Independence, 独立性
% u6 d& k3 l- p5 ]# x! K5 ?Independent variable, 自变量
+ t7 q% m. n7 F7 m! `Index, 指标/指数
" x, w# |7 t. m4 w; vIndirect standardization, 间接标准化法
* x! C# k8 m( B& Q# xIndividual, 个体
) ]8 F* m0 {& S2 CInference band, 推断带& ^- o7 }( }# o8 P. h" o7 N
Infinite population, 无限总体
$ F, i8 v8 l* rInfinitely great, 无穷大! {# t- V9 _. N _0 m8 ]$ P
Infinitely small, 无穷小. N: |6 J( |, {- q8 w
Influence curve, 影响曲线) ^/ j, C& N; n8 K0 I% q# B$ d6 {
Information capacity, 信息容量% R n e8 V0 i2 a+ }, q! Q W+ H
Initial condition, 初始条件7 R, q$ Q7 |1 c6 Y% o) n
Initial estimate, 初始估计值1 X6 D2 z9 s1 ]1 w" F
Initial level, 最初水平% l6 H9 V2 {, a- p) \" O. F
Interaction, 交互作用( y/ o0 _% b: {, x. h' Q
Interaction terms, 交互作用项# J' E9 K3 |7 q& p
Intercept, 截距
- A" F. v3 \% q) Y- o' g FInterpolation, 内插法
, \8 F ~( r4 T/ L4 Q( K! v% xInterquartile range, 四分位距
9 g. O: C, f0 x/ \& EInterval estimation, 区间估计6 s$ R3 p+ c' _. I! u6 o A
Intervals of equal probability, 等概率区间
8 o9 y+ g9 z3 S: I' H, G' LIntrinsic curvature, 固有曲率/ A; M( _6 f9 C# D, w$ ]$ h
Invariance, 不变性
. r! Z0 i& S* {3 `Inverse matrix, 逆矩阵. n* t4 ?% c9 }- C! @1 E
Inverse probability, 逆概率
0 ]" J. z7 J* G1 G- U2 w4 C7 R tInverse sine transformation, 反正弦变换
, R# F4 K4 ]% L- gIteration, 迭代 : z9 e& R4 C. j
Jacobian determinant, 雅可比行列式
- [' ?6 k4 i) \, G" L- _% UJoint distribution function, 分布函数3 c: X0 k8 v& y5 R; v5 p
Joint probability, 联合概率
! H/ w( Y [) a: j6 }Joint probability distribution, 联合概率分布
0 D$ e3 x3 A7 y' P/ j$ t! [$ h& EK means method, 逐步聚类法
: T6 X B0 Z* b: A) t' ?% B2 UKaplan-Meier, 评估事件的时间长度 0 A2 L8 V6 S( N) k" { Q6 O
Kaplan-Merier chart, Kaplan-Merier图% @6 k4 @/ R8 o6 p" L$ z
Kendall's rank correlation, Kendall等级相关
% u' Z: C$ \9 z1 i0 m5 N; p6 yKinetic, 动力学
4 j9 S* W1 v! @Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验- n. P/ @7 g6 X( Q" P, S
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
) s/ n' j; x* G& ~9 `0 NKurtosis, 峰度
7 ~9 X( j3 c. i1 x9 ]% {Lack of fit, 失拟
" r9 ^' J$ i% t) Z4 Y, BLadder of powers, 幂阶梯$ w- w' `; j2 d( t4 N( P) Z4 x
Lag, 滞后6 o) R/ ^& J' [# |& ]6 A8 U
Large sample, 大样本% q+ B! l0 c0 Z4 N( y" Z
Large sample test, 大样本检验' s4 v6 V p1 u: `' I* Z
Latin square, 拉丁方/ f) j, w: g5 F6 \
Latin square design, 拉丁方设计1 ~8 `2 T2 L" }, O
Leakage, 泄漏' K4 C6 F, b! c5 \% B
Least favorable configuration, 最不利构形
" ^. O4 I. n5 j. T7 CLeast favorable distribution, 最不利分布
# J% r- A. `! d- S+ CLeast significant difference, 最小显著差法1 n7 r" W) q9 L" _
Least square method, 最小二乘法
7 ?4 g6 B. y3 I; P2 y3 |# ?7 h0 N1 bLeast-absolute-residuals estimates, 最小绝对残差估计9 E: m5 y* s. s7 K
Least-absolute-residuals fit, 最小绝对残差拟合
k, r; S$ H6 U/ g6 k4 A0 ELeast-absolute-residuals line, 最小绝对残差线( `# V* C* w; k
Legend, 图例
5 w! H- L( I9 I# B4 _% ?# AL-estimator, L估计量* u% `- w+ \, \5 Q
L-estimator of location, 位置L估计量, ~! ]8 c" I" j
L-estimator of scale, 尺度L估计量' |$ }3 I9 b* g. S1 H! `' P0 U% u
Level, 水平
" b; z. A4 S( U- J" NLife expectance, 预期期望寿命) M3 l( ^% P# C. R7 Y* D
Life table, 寿命表
+ L2 O, R% L2 Z8 P d; dLife table method, 生命表法& ^" R: _; X! q) P# B
Light-tailed distribution, 轻尾分布
: G) C* L/ U3 PLikelihood function, 似然函数0 h; X# }/ R+ W; s6 K
Likelihood ratio, 似然比
$ n {$ `. f8 aline graph, 线图, m0 H7 d, Q6 G& ]& ]
Linear correlation, 直线相关, k9 K8 I* K3 P( r) l y' E; G @2 n
Linear equation, 线性方程
8 S# R" j7 V" RLinear programming, 线性规划
4 y2 P4 v, r4 A" w* \4 lLinear regression, 直线回归4 b8 z' p( J- b
Linear Regression, 线性回归0 Z4 g3 Z+ J. C
Linear trend, 线性趋势7 B" O/ a6 X: l2 u y; M1 r( ^
Loading, 载荷
' ? H$ ^7 j% U. YLocation and scale equivariance, 位置尺度同变性
, I8 ~0 ?; c$ q6 z4 m" K0 T. oLocation equivariance, 位置同变性
- c( K/ B9 F$ [. T, _( oLocation invariance, 位置不变性
: K/ w, c) V4 w3 u KLocation scale family, 位置尺度族0 d5 m# T" ?) i" F' `& `, f
Log rank test, 时序检验 * i# J7 V; w8 ^7 Y& Z( G/ \' b
Logarithmic curve, 对数曲线
) D/ b+ D* r5 g. p* Y: }/ KLogarithmic normal distribution, 对数正态分布3 C$ z% v2 p" s
Logarithmic scale, 对数尺度: a6 A. f# s" [$ Q' K* b* q2 }* B
Logarithmic transformation, 对数变换6 I+ f/ a+ m, r; T: h& P8 d/ ?
Logic check, 逻辑检查3 l- O, z7 B1 b" h( e7 t- w
Logistic distribution, 逻辑斯特分布/ A9 m: |/ y( F- T
Logit transformation, Logit转换+ G" ]# x% Q# y, w, u5 F
LOGLINEAR, 多维列联表通用模型
/ P+ j3 y8 F QLognormal distribution, 对数正态分布
4 c: _7 y% y' qLost function, 损失函数
) O* y( v% {/ j- JLow correlation, 低度相关& H; i* Y T" }8 z4 H" W4 L' |8 X6 J. t
Lower limit, 下限
+ f) w( c+ k: r9 u0 E. I3 zLowest-attained variance, 最小可达方差
: p4 s) h& r0 P$ h# d/ p. _9 QLSD, 最小显著差法的简称
: l5 T+ o$ {2 \, W7 J& YLurking variable, 潜在变量 O1 i! e0 r1 ~# u* p0 T# H* V
Main effect, 主效应
y! Z% q$ K- _" E9 U* @5 X/ UMajor heading, 主辞标目. z, o7 s) j+ d" y6 i! v1 [
Marginal density function, 边缘密度函数- E0 \' F7 X8 J* m
Marginal probability, 边缘概率, Y/ E3 w) M/ z. O. C( n
Marginal probability distribution, 边缘概率分布! P8 Z4 N/ J3 J: M, d1 G
Matched data, 配对资料
0 Q4 c2 l+ s/ i0 P/ qMatched distribution, 匹配过分布
* { n" M t$ N$ [0 QMatching of distribution, 分布的匹配" Y M: u: U# {* s
Matching of transformation, 变换的匹配
9 x e R# ~( S0 Z% D6 hMathematical expectation, 数学期望
$ f" O% _1 ]9 g7 X* ~, j9 [% ^Mathematical model, 数学模型
- X, \2 S6 i, c6 j. hMaximum L-estimator, 极大极小L 估计量" c6 J# v# a+ x% g
Maximum likelihood method, 最大似然法
# L. t; x2 g" {Mean, 均数
# B/ S( n. b4 {8 aMean squares between groups, 组间均方
5 _$ d: W7 s1 }0 i, x* _5 q4 IMean squares within group, 组内均方2 h" M+ Z7 H' |8 N! r
Means (Compare means), 均值-均值比较3 a* J0 z4 L1 `$ e3 ^5 h
Median, 中位数
1 K2 t H8 d, p2 Q' i( Q7 bMedian effective dose, 半数效量
; j' _8 `% `* Z$ ~Median lethal dose, 半数致死量
8 K- h% h$ X5 `# H% gMedian polish, 中位数平滑0 S. m% z7 J4 i
Median test, 中位数检验
8 y1 }& M" d \' h4 D$ sMinimal sufficient statistic, 最小充分统计量" k& U' Y4 r4 q4 K8 R) ~- R2 n: F: m
Minimum distance estimation, 最小距离估计, _0 d/ w- M( F3 W" r+ `: e4 w9 E
Minimum effective dose, 最小有效量3 v' e$ {+ g8 x7 _9 j9 J
Minimum lethal dose, 最小致死量. `% x X1 P; X& \% b1 s: g
Minimum variance estimator, 最小方差估计量
4 N% G% o0 R; c u! \7 F* D8 i! L% pMINITAB, 统计软件包/ s7 j+ |/ Q' ]% F
Minor heading, 宾词标目- G* T \" ?; z9 w/ D, ]' d
Missing data, 缺失值. R" C; S- m0 S$ h/ o
Model specification, 模型的确定
3 f; h* t' g4 W! S* J% q0 S% vModeling Statistics , 模型统计
: I4 x2 h( G6 I. Q, jModels for outliers, 离群值模型. Z c0 o( C& `2 L4 c, w
Modifying the model, 模型的修正
/ ^: m: u7 P3 y7 P# _6 P- TModulus of continuity, 连续性模5 p# ~+ v' j, f6 l! K+ E
Morbidity, 发病率 - ~; c8 w2 B+ `$ ?, J) O
Most favorable configuration, 最有利构形+ H9 p% ?& z3 w1 B/ L7 m% E& E$ E
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
L# ]: s$ l# c9 \Multinomial Logistic Regression , 多项逻辑斯蒂回归4 A& [( N7 s; c
Multiple comparison, 多重比较) C8 j) G; ~$ F4 D9 m# ~- ]
Multiple correlation , 复相关2 y3 \3 D( m/ w3 e1 E5 ~2 H! s
Multiple covariance, 多元协方差
0 T2 V: ?7 ^8 i) yMultiple linear regression, 多元线性回归
6 E4 @. b0 ^; p3 ]3 l; f, VMultiple response , 多重选项4 C: K- L3 b( A W! I
Multiple solutions, 多解$ |; ]/ j2 t% ?: }! z" o1 l) \6 j' c
Multiplication theorem, 乘法定理2 O2 f' P" \9 ]9 x4 `, z6 l& {
Multiresponse, 多元响应; v! U% ^* T, H2 W4 x4 T* z6 x
Multi-stage sampling, 多阶段抽样2 g# O x9 n* b9 r
Multivariate T distribution, 多元T分布. ?; Z3 l) [4 o0 X9 t
Mutual exclusive, 互不相容* r, @, [/ a, c# r ~6 A! W$ i
Mutual independence, 互相独立% P) {* P) @* z
Natural boundary, 自然边界: q1 {2 G! C. G/ C9 j
Natural dead, 自然死亡+ f5 t* e* o: z
Natural zero, 自然零
" f3 P% w+ S8 q% y+ Z/ A/ D ?( R) n) ANegative correlation, 负相关: X! N6 L! \# k! q- y2 X; R0 O
Negative linear correlation, 负线性相关" h$ @ ~! i+ a, c) L0 \
Negatively skewed, 负偏) t2 G7 k1 o5 c! s5 L6 T8 ~3 `6 f
Newman-Keuls method, q检验4 Q# K. Z1 y- J/ l% V) B" x6 |
NK method, q检验
: N: a+ P+ X8 ?% rNo statistical significance, 无统计意义
# P( r* c% J2 { _$ r" E7 u% Z# JNominal variable, 名义变量
" ^* d3 `/ _) }8 Q! i( {( PNonconstancy of variability, 变异的非定常性
- ?1 f: y$ c+ u, d2 P9 ONonlinear regression, 非线性相关
- U8 \6 \6 x6 D8 i7 aNonparametric statistics, 非参数统计" f) A% ^; z* K* _( N; r
Nonparametric test, 非参数检验1 K! ^2 g: G1 U: R
Nonparametric tests, 非参数检验# @+ ?% a2 [7 E- I) E7 d
Normal deviate, 正态离差: `# K7 A" Q* j; `5 S& U, W1 t
Normal distribution, 正态分布8 i* q9 Y9 G$ ~2 i# y9 `' M2 A
Normal equation, 正规方程组) y& [. G1 L; l1 r# L1 a& E: w6 @
Normal ranges, 正常范围9 z& [. z1 O( J0 t7 d
Normal value, 正常值
+ \, r; ?% J+ [* e8 T9 {6 SNuisance parameter, 多余参数/讨厌参数
1 r0 `; Y* O" }! H2 BNull hypothesis, 无效假设 # p; x' k- Z! w5 R6 U8 \8 i e
Numerical variable, 数值变量7 n) s' ?, r% Q
Objective function, 目标函数
% Z1 d" y/ H) ]: g9 T/ XObservation unit, 观察单位
3 ?# @& h0 a! RObserved value, 观察值7 m k, r. J$ M0 h7 s( b
One sided test, 单侧检验& |% l# W4 _/ u1 @1 O6 e, k6 [
One-way analysis of variance, 单因素方差分析9 e! [2 l! q6 b
Oneway ANOVA , 单因素方差分析1 Y6 [" e( @8 {9 X4 q
Open sequential trial, 开放型序贯设计' X. m3 F; z2 l+ \6 o* V
Optrim, 优切尾
0 e8 T! @3 c0 u8 JOptrim efficiency, 优切尾效率
# |5 V! P3 S5 a, jOrder statistics, 顺序统计量
, F, u( k; z# L6 N; T2 d& Y8 ^Ordered categories, 有序分类
1 H5 I9 |; [& l* q) S& M. gOrdinal logistic regression , 序数逻辑斯蒂回归
5 [8 e* M4 @: L5 C! D/ M2 `$ z0 iOrdinal variable, 有序变量
; Y& Z! P" y+ h; GOrthogonal basis, 正交基+ N4 _. d7 q1 z) w' h z6 ]) {, D: H
Orthogonal design, 正交试验设计
8 C* B; s" U0 [- [: j' t2 iOrthogonality conditions, 正交条件
0 V4 \8 e1 ~6 }% `1 c0 kORTHOPLAN, 正交设计 8 {$ D* B- x ?* s7 g$ U: s
Outlier cutoffs, 离群值截断点
: {4 U3 i, q7 H6 I( {Outliers, 极端值
, [% i' M% K+ R$ \7 `0 }$ }- SOVERALS , 多组变量的非线性正规相关 ( Z, K; d- Z9 c1 Z: N. R
Overshoot, 迭代过度! ~+ j0 M5 | U# Y6 v
Paired design, 配对设计
" s* Y" k# J0 t/ a, L' G3 iPaired sample, 配对样本
5 B- J) U; {0 O* R6 y5 H+ }; JPairwise slopes, 成对斜率
# V s" B# f+ T' |! @* q" ZParabola, 抛物线; I4 Y' Z, @6 u* G. H" t
Parallel tests, 平行试验; a% t, U- a% e, z" J) [6 {
Parameter, 参数4 [/ Z9 u; d: @7 b0 h1 Y
Parametric statistics, 参数统计3 f) H c+ n, o& k; w! _4 w' @' `4 E
Parametric test, 参数检验- O0 {: U" D- R$ b [$ x: l5 v
Partial correlation, 偏相关
& G% t& }. l6 s# G4 oPartial regression, 偏回归$ X! n) k+ c" x' G- O! e8 a0 R
Partial sorting, 偏排序
% E1 |: H+ a" `) SPartials residuals, 偏残差4 S- I8 @0 k4 h, u( h4 E8 c5 E' `
Pattern, 模式
/ ]" \/ x1 L! I) P/ r2 BPearson curves, 皮尔逊曲线3 D& b6 G% D' n2 k) }1 |; g4 Z: u
Peeling, 退层6 N2 o# t3 _- K: ~; q# G" e
Percent bar graph, 百分条形图8 e. Y! P: F8 d
Percentage, 百分比" U& P) F$ {% k; D; [/ s3 L$ d, j
Percentile, 百分位数
; G4 {/ L; U$ ], V5 f) kPercentile curves, 百分位曲线' Y5 f, P5 l1 f8 x. J/ N* Y: G
Periodicity, 周期性
0 S$ W' P7 Z: F/ T* m2 zPermutation, 排列
: B9 C6 n. O, g8 x" ?P-estimator, P估计量1 u( _5 L* x! A; r& i5 b
Pie graph, 饼图
/ V2 X7 v3 Q# x; xPitman estimator, 皮特曼估计量
7 ?! Q) R) }; H1 RPivot, 枢轴量
) R8 N8 e! ?# ^( uPlanar, 平坦( l. i9 J$ a# a0 }* c1 b3 d
Planar assumption, 平面的假设% b; r& Q* L' N4 ]$ u. U
PLANCARDS, 生成试验的计划卡7 W1 H6 D, j9 r4 k
Point estimation, 点估计
. _+ H" v+ @! A/ Q/ @! x) XPoisson distribution, 泊松分布
" H; {; Z6 N! APolishing, 平滑
4 y% E$ K1 T6 f% P" DPolled standard deviation, 合并标准差
" y, e6 @: I4 i0 n2 `& IPolled variance, 合并方差' k0 W7 h1 W2 Y8 L& U- U$ I' ~
Polygon, 多边图
0 x+ r6 b: G+ V. r8 ]9 e8 B2 z- |Polynomial, 多项式
9 @7 ^3 D7 `# xPolynomial curve, 多项式曲线: o; b: D7 \) g
Population, 总体
: f! ?' Y7 j' f# D5 M& }1 a' ZPopulation attributable risk, 人群归因危险度! I% x& w; z; I, b2 ^6 Z
Positive correlation, 正相关
7 X+ C1 Y& y0 d' b0 H4 r0 xPositively skewed, 正偏- [' O! [4 H$ p
Posterior distribution, 后验分布6 D0 B- b# _1 ~; m
Power of a test, 检验效能9 ?6 g$ G! j3 w+ `7 ~2 v$ {; `4 z
Precision, 精密度9 T- u6 P. I: j; T9 o. a
Predicted value, 预测值( S: c3 w9 v0 f! L
Preliminary analysis, 预备性分析
* ^: Z( |# F+ O# y+ X* qPrincipal component analysis, 主成分分析
5 C& B0 n. R- \5 d# hPrior distribution, 先验分布
' q6 }; o+ E; G( C! SPrior probability, 先验概率2 ^6 l! V, j1 v# C
Probabilistic model, 概率模型/ V* e" ^- |: ], x3 ~* ?
probability, 概率
* V1 `( ?5 [# p5 g9 rProbability density, 概率密度
8 M- Q& b2 [; P XProduct moment, 乘积矩/协方差* Q, \) Q! b# ^+ _2 T
Profile trace, 截面迹图
7 d: {9 e# Z3 u* dProportion, 比/构成比
8 o- t Y1 i/ F8 v2 t- s0 X; DProportion allocation in stratified random sampling, 按比例分层随机抽样
3 @; x7 r" R- Y" U5 c/ o2 V7 y! ^Proportionate, 成比例
2 [: K6 U/ w0 X3 @% ~1 c, vProportionate sub-class numbers, 成比例次级组含量8 Y- L" O8 f z
Prospective study, 前瞻性调查, S8 x; w& E+ z+ u1 k
Proximities, 亲近性
7 ^% F" I+ x0 u& _/ }# }8 WPseudo F test, 近似F检验 a6 [, v3 K6 W+ L$ i& z( P+ \
Pseudo model, 近似模型9 R/ a: B( G5 U. q- s
Pseudosigma, 伪标准差9 _3 w9 f* ]/ C6 R6 |6 o) _
Purposive sampling, 有目的抽样9 q% w+ Z0 P9 F2 q1 C% G
QR decomposition, QR分解
$ z7 |7 C- g: m3 n: PQuadratic approximation, 二次近似
! i/ u) R2 A2 CQualitative classification, 属性分类( y1 f6 l; O9 ^9 r: b# W
Qualitative method, 定性方法
: p5 L% t, U" ]) z |. m3 ~6 p+ lQuantile-quantile plot, 分位数-分位数图/Q-Q图$ p' ?9 g6 b+ V8 z% k, k2 Z c2 B9 e. j
Quantitative analysis, 定量分析
" C) Q" g! z# Y6 ^( j' ^Quartile, 四分位数
8 X8 u5 f! _7 R, }+ R- NQuick Cluster, 快速聚类 r0 i5 t, e* O" k/ x9 B
Radix sort, 基数排序
. @0 L+ m4 E. a7 m: S. k& hRandom allocation, 随机化分组
6 r% J* \" D: u- a9 k" g( |Random blocks design, 随机区组设计
) M$ C! l i5 F9 oRandom event, 随机事件! @ ? s3 J& b8 K" y; _8 U
Randomization, 随机化
3 O8 a2 ~# ]4 tRange, 极差/全距
4 e3 @6 Z/ ~- S3 l9 m. v5 BRank correlation, 等级相关
# g- c# n7 }& r, GRank sum test, 秩和检验0 c/ R H! b& c- f; n
Rank test, 秩检验
/ y$ v6 Z2 e4 j% ]Ranked data, 等级资料
- T4 [- |$ @1 o ]Rate, 比率3 g! d1 ?% E m: T( |' t% I5 g3 J
Ratio, 比例) J# U( t) i' S" d
Raw data, 原始资料
W1 u$ _$ y8 kRaw residual, 原始残差$ u$ H% t ?/ | @+ U A. {
Rayleigh's test, 雷氏检验7 K) O4 K: w6 ]
Rayleigh's Z, 雷氏Z值 ) h2 a3 Q' Y0 o% \
Reciprocal, 倒数+ ]* e/ K K" r$ l$ z+ J6 ~
Reciprocal transformation, 倒数变换
, A. K3 c" w* v: @# |5 k# d+ xRecording, 记录. }" X q" B' p! R
Redescending estimators, 回降估计量4 | l& C; h0 ~2 ]0 [" V
Reducing dimensions, 降维# D2 H) A5 _+ e
Re-expression, 重新表达
) z1 L6 c: q9 i5 [- i( TReference set, 标准组
$ R) `7 m) F. U: f) BRegion of acceptance, 接受域
- E1 ]0 B* g) k! R4 ~* k& ORegression coefficient, 回归系数
, N4 K3 {# a% [# D% Z" p, |) A; HRegression sum of square, 回归平方和( Z2 p5 ~2 C& t! F
Rejection point, 拒绝点
7 J1 j- r+ |+ i* d, k: o3 {3 CRelative dispersion, 相对离散度0 _+ R2 r6 y$ p
Relative number, 相对数
4 B M* K6 N8 S( OReliability, 可靠性
& ?& E' d$ S4 n: h1 j yReparametrization, 重新设置参数& ~2 M8 }: w5 k& g0 X( H) ^# S
Replication, 重复! \3 y1 ^% D( w2 \# }3 b
Report Summaries, 报告摘要
- i2 B) _2 ?; t5 v: W/ VResidual sum of square, 剩余平方和& J) n/ t; \! b; T) Q! x5 F o% o7 f8 X
Resistance, 耐抗性8 M$ ^' ~' _( e
Resistant line, 耐抗线
Y Z5 G1 _9 SResistant technique, 耐抗技术% `8 _1 q& D' |4 a$ q& z( Q- u5 P
R-estimator of location, 位置R估计量
8 d. o2 V/ ^0 K G" C7 UR-estimator of scale, 尺度R估计量
# o+ ]5 {. M' R- S4 @6 MRetrospective study, 回顾性调查
9 J5 D9 {4 t+ F2 A# _- \) M' n" _6 ?Ridge trace, 岭迹: z0 D6 h7 l/ e: D0 ^5 C
Ridit analysis, Ridit分析
1 C1 F4 E9 g: p& D4 kRotation, 旋转4 i/ ~- _2 e4 n
Rounding, 舍入+ `# X* U' o; ^/ e4 P$ l! F. ?
Row, 行6 |3 d, l# `6 f+ ~. z4 ^. w
Row effects, 行效应+ K m3 \) t4 l9 _) ]
Row factor, 行因素
: k/ g. M/ b9 N) g. B+ R L; ~ dRXC table, RXC表
: I# W* |, o! ^; m$ jSample, 样本
+ y$ D& }0 o: i* i/ c; qSample regression coefficient, 样本回归系数
% H- c+ o+ n6 ~, t4 uSample size, 样本量; F4 q7 ?- J( \- f
Sample standard deviation, 样本标准差
" n" L1 d, p+ c+ P! d. XSampling error, 抽样误差! }- O( e, a \ ~* @& g/ I
SAS(Statistical analysis system ), SAS统计软件包
* ~" s, }1 ^; t" V$ a! ?3 S7 HScale, 尺度/量表
* z& G/ [* ^! V0 |; {5 ZScatter diagram, 散点图
/ {9 i+ q o5 x5 c$ Y- GSchematic plot, 示意图/简图
6 {. q* |6 R+ U! }$ \* eScore test, 计分检验* x+ ?3 Z8 e! m+ g( c
Screening, 筛检
' I1 G* k- S4 I$ {' {/ FSEASON, 季节分析
* p3 G- L& `- PSecond derivative, 二阶导数
0 ]* W* h1 ]$ S* d5 j# e/ nSecond principal component, 第二主成分
7 g& I1 e* w& jSEM (Structural equation modeling), 结构化方程模型
& B2 A8 H, X* \7 I" d9 v" V9 bSemi-logarithmic graph, 半对数图
- t" U5 n1 t" [1 ]. O) w, N/ \Semi-logarithmic paper, 半对数格纸
$ }; d- {8 Q3 O" c4 K# d2 lSensitivity curve, 敏感度曲线' m7 x7 s$ A9 {% U- X
Sequential analysis, 贯序分析
: g7 n. T" g2 _9 s7 nSequential data set, 顺序数据集 ]: Z# C8 b; Q$ I
Sequential design, 贯序设计
$ ^ k; G! @) K6 |! ySequential method, 贯序法
3 F6 Y; `$ j" cSequential test, 贯序检验法' ]" s" q/ r3 Y- r
Serial tests, 系列试验
. I0 d& Q8 V! X$ S3 g3 `Short-cut method, 简捷法 / I- |4 m3 @1 b1 V8 G% m- P8 y- e
Sigmoid curve, S形曲线5 I. e' v$ G2 S4 Z3 l+ s
Sign function, 正负号函数. P" j$ Q8 u) K1 L }" I+ r
Sign test, 符号检验; D- Y% a, Y7 |: _& W* t" }
Signed rank, 符号秩8 u* q3 J) h* A9 M! `/ p4 R z
Significance test, 显著性检验
4 p1 R( n# \, W) Q- d# B- Q% xSignificant figure, 有效数字1 E1 ]' ?5 X% K/ ~
Simple cluster sampling, 简单整群抽样
% ]4 m+ }6 `. ^* N& lSimple correlation, 简单相关
) U% ^5 S# l* ~2 P# `Simple random sampling, 简单随机抽样
5 ~& @- ]3 o8 C3 y ASimple regression, 简单回归
9 c* ^8 N& ]6 e3 fsimple table, 简单表
$ A t) x R$ {$ c) iSine estimator, 正弦估计量# \3 P/ C, {) s# V8 u& E! O$ R
Single-valued estimate, 单值估计
8 A9 I S0 I- |$ T' sSingular matrix, 奇异矩阵$ n) A# j g2 |" M. M0 x
Skewed distribution, 偏斜分布* x6 b! K1 c$ A1 u( i
Skewness, 偏度$ X; o3 V+ `2 s
Slash distribution, 斜线分布
' a& `8 n5 f/ ^. q2 i( \# VSlope, 斜率) J7 U$ P# x9 `. O5 c; r" n( T
Smirnov test, 斯米尔诺夫检验
+ l: ]! X+ L9 \2 Y N/ ~Source of variation, 变异来源
) I+ I# u9 }+ _' XSpearman rank correlation, 斯皮尔曼等级相关$ W, J; t! A6 f
Specific factor, 特殊因子
+ v" O& I; {' s6 g/ l+ mSpecific factor variance, 特殊因子方差
w" @9 p4 X lSpectra , 频谱
& l5 t6 I7 T, F0 c: CSpherical distribution, 球型正态分布 G! E& k' f" F0 j7 T
Spread, 展布
) ?6 i/ g) B9 vSPSS(Statistical package for the social science), SPSS统计软件包% Z0 f7 D* o/ k: O
Spurious correlation, 假性相关. h! u& r% N! j2 d a* U" k
Square root transformation, 平方根变换
) u) w6 B0 b" w9 \; LStabilizing variance, 稳定方差. a! t2 }5 m _( v
Standard deviation, 标准差6 A! l3 m) K; W: ]
Standard error, 标准误
, {- {* s; L+ v* w6 L) c6 S4 l5 P9 w, tStandard error of difference, 差别的标准误 Q2 ?- v) {' f( R
Standard error of estimate, 标准估计误差. e' w! k- |! B9 c( h
Standard error of rate, 率的标准误
( g5 S, G) u9 N% oStandard normal distribution, 标准正态分布9 s- l9 ]6 ]! F5 ], N
Standardization, 标准化& I. B* A$ _+ m! |
Starting value, 起始值 ~2 {" ?: L" x |
Statistic, 统计量
8 u6 C. h- J1 F6 r, W) d/ J; sStatistical control, 统计控制0 [0 u, [' ?0 L8 R# h
Statistical graph, 统计图
8 x3 Y! f/ V& jStatistical inference, 统计推断
! ?: Z: e" c6 Y" e$ I% lStatistical table, 统计表5 E2 H/ { \: e( t' t e
Steepest descent, 最速下降法6 m! \- z5 X+ b& d& {3 Q! V4 M
Stem and leaf display, 茎叶图
$ n/ G6 }/ S2 qStep factor, 步长因子( d( h9 M! H0 K( J
Stepwise regression, 逐步回归! C' L7 |- D' b1 Q8 e
Storage, 存
4 S, T0 S0 n: G* F9 o5 {9 [Strata, 层（复数）2 V9 w. E2 G3 r0 @
Stratified sampling, 分层抽样7 T1 k7 v: W' o4 B$ z, [
Stratified sampling, 分层抽样* ]$ \; W# w# [% J- O
Strength, 强度
, [( L- d. L: M5 B( a% t2 y+ dStringency, 严密性
( A* [9 [0 i' |& RStructural relationship, 结构关系
! ^9 r& ~+ X% b/ d0 X5 B& VStudentized residual, 学生化残差/t化残差
; }6 y5 }) u. m& o" ~" GSub-class numbers, 次级组含量8 \+ Q& G! q `1 W
Subdividing, 分割
* e7 q. P- p3 c- k1 tSufficient statistic, 充分统计量* ]. @) q$ ?# o; x. _& v4 X! x
Sum of products, 积和: j( Y+ y- `8 F4 ^
Sum of squares, 离差平方和7 p& i: V& ~* z( D
Sum of squares about regression, 回归平方和3 N: M' e; {8 v' b/ \+ K
Sum of squares between groups, 组间平方和
6 s1 e7 {- P/ V- a6 {Sum of squares of partial regression, 偏回归平方和+ X* v9 t0 R6 ?' N, f
Sure event, 必然事件
# g" o, ~3 n' o3 OSurvey, 调查
% [% i, {! P! K/ G+ USurvival, 生存分析
) p8 B& B& ~4 ]4 _5 RSurvival rate, 生存率) E+ U( n( H% n3 }; z: z; T& ]
Suspended root gram, 悬吊根图0 S& W" E) [ G' w
Symmetry, 对称) T2 |& O/ s4 s" ^5 S
Systematic error, 系统误差 @4 m/ r+ j" c
Systematic sampling, 系统抽样" E) p8 p3 ?4 u l
Tags, 标签9 O5 Q- z; g+ i' O
Tail area, 尾部面积8 [- V9 P3 S% K
Tail length, 尾长( l* ?; s5 B* D% r3 A
Tail weight, 尾重* V9 m; {' U* u# \- e$ o0 }: r
Tangent line, 切线
+ @9 `% ^3 j- S/ O6 F0 ZTarget distribution, 目标分布
' z' ]: @2 C6 _1 H7 p2 BTaylor series, 泰勒级数: N, E4 G5 [' ~# ?+ y
Tendency of dispersion, 离散趋势
( Z7 l5 F4 r8 m4 ZTesting of hypotheses, 假设检验
9 A3 F& l# A4 K S7 a: J' y6 UTheoretical frequency, 理论频数
4 G6 u$ \( T9 V' f; f7 mTime series, 时间序列2 J. I% S% y6 x" _6 c
Tolerance interval, 容忍区间+ _8 j- q7 K. j
Tolerance lower limit, 容忍下限3 v9 p; U* Y* D" l
Tolerance upper limit, 容忍上限2 T$ s3 H: n, P: s$ q8 j
Torsion, 扰率
V% _! k v; V4 n6 y5 y8 RTotal sum of square, 总平方和0 R6 p7 o& A6 h/ j2 w s# W) R
Total variation, 总变异! W- R5 I. @9 O$ L7 c' i, p6 m. S
Transformation, 转换
2 L; _& T& k* xTreatment, 处理
J6 O3 [) X0 i5 r) K, O2 MTrend, 趋势3 |& t1 {3 d% s- k, A% J
Trend of percentage, 百分比趋势7 R6 T& v) y0 _9 `8 [1 W
Trial, 试验
, D. A2 i) u& I# u3 gTrial and error method, 试错法$ \$ s, N2 q* C0 z7 k# \
Tuning constant, 细调常数) v/ j8 K) x7 o# c" ^- a* u. x
Two sided test, 双向检验
- o& X3 L: c0 ?4 e* H* b! G# c" \* \Two-stage least squares, 二阶最小平方2 b# L5 i: G. A p
Two-stage sampling, 二阶段抽样
2 e6 e* W- c6 F/ A" V# MTwo-tailed test, 双侧检验
6 ]5 w+ ^0 `# V. o8 U% f: O4 CTwo-way analysis of variance, 双因素方差分析
6 e2 r8 K9 `# i/ K9 l# n! _; BTwo-way table, 双向表
, G; i/ z. ]) o1 QType I error, 一类错误/α错误- Z' ^5 X, k; b3 w( _* B; {4 N
Type II error, 二类错误/β错误
0 M! z Z/ E" o* E9 G+ R! F" UUMVU, 方差一致最小无偏估计简称& c9 X J8 A. V: \+ ]3 q
Unbiased estimate, 无偏估计+ A* ?" j6 m w$ L8 Q
Unconstrained nonlinear regression , 无约束非线性回归! M( G, r2 u. x2 e
Unequal subclass number, 不等次级组含量1 p* @' k J' F! K7 r; U1 J( \
Ungrouped data, 不分组资料
6 e4 Q( Y, }: N" d6 [! FUniform coordinate, 均匀坐标
& M3 G* h: ]! [Uniform distribution, 均匀分布9 R9 d- q8 g' h/ Y4 d
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计# E2 e; e; x+ z, r
Unit, 单元
" D5 _ E# S, h4 B3 X# \Unordered categories, 无序分类
) l: N, w1 q* B$ T6 NUpper limit, 上限8 i8 m1 F& y ?2 ~1 y! W/ h
Upward rank, 升秩
; Q' e0 L- i, x# bVague concept, 模糊概念3 |! W! }$ L( ~' Z( u; v- U
Validity, 有效性
, E6 U; Q- o5 G% kVARCOMP (Variance component estimation), 方差元素估计2 Z5 H+ ? l5 U" @9 Q; D6 v5 w$ g
Variability, 变异性+ Q' x- d% f4 e# Y! @
Variable, 变量
, ?9 a$ D1 ~ F3 sVariance, 方差
: Z0 v, J# G, G/ N& U; u2 v+ WVariation, 变异
- Q( L- V4 b) s& DVarimax orthogonal rotation, 方差最大正交旋转
7 Z. @* B- m; Q4 b: DVolume of distribution, 容积& a" Y3 _/ m( l0 R# B
W test, W检验
. o! Z0 Y; C- ]- {1 M" ~Weibull distribution, 威布尔分布
4 ]! @* f8 L7 ]) u* B# B3 M$ mWeight, 权数6 M: K7 d/ Y" c6 D
Weighted Chi-square test, 加权卡方检验/Cochran检验
: [, B+ W# ^. S" r4 z/ O0 m* V, `Weighted linear regression method, 加权直线回归) {6 l5 P5 w9 Q H; }* k* f, n1 e
Weighted mean, 加权平均数
2 Q* g7 |4 E4 U0 PWeighted mean square, 加权平均方差7 f* b; A' g6 k R" m0 D! v
Weighted sum of square, 加权平方和
2 b! }6 ^ y! [$ I% GWeighting coefficient, 权重系数' v8 V e6 u t; q
Weighting method, 加权法
`( ~( j. G, [# N* O8 L0 o8 a, }W-estimation, W估计量5 m, r/ {& E; @# x: {
W-estimation of location, 位置W估计量; _, F% m: }. e* m" M
Width, 宽度8 \: P& ]# k7 g- x. j0 r. [
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验3 O) a9 t! F. a1 A- Y9 b
Wild point, 野点/狂点1 l0 i1 a$ n6 N7 ]9 s, y
Wild value, 野值/狂值; g1 A# v. |9 g5 ^4 u+ t
Winsorized mean, 缩尾均值9 Q+ i* d3 Q3 H% w* t
Withdraw, 失访 + X0 o' G* \3 u9 k& y! G1 h
Youden's index, 尤登指数
% y& _% p; X6 e+ O, y6 q. OZ test, Z检验
0 v% F) e( Y- d+ ~& T. l. I+ JZero correlation, 零相关
$ R: M6 U, @3 ^% A, Y, _' JZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
