|
|
Absolute deviation, 绝对离差
! E. i7 K# J0 i( }( ?6 cAbsolute number, 绝对数
- L" N- G& M4 }: Z/ AAbsolute residuals, 绝对残差, k+ ]3 q$ M1 U o4 N+ r8 C# @
Acceleration array, 加速度立体阵
& n) \1 _7 o* N- V+ XAcceleration in an arbitrary direction, 任意方向上的加速度
5 l* z [0 \( k) ]) D( r$ @( {Acceleration normal, 法向加速度4 P/ X' p2 X# h! Z% h
Acceleration space dimension, 加速度空间的维数
2 T2 m, b4 X3 z4 ?; x" ]+ sAcceleration tangential, 切向加速度
, `% W: P8 z& l, K$ Q a9 LAcceleration vector, 加速度向量
. w& Q4 U* ?; j) j/ IAcceptable hypothesis, 可接受假设8 N- K0 A2 w) L/ N" D/ q6 f
Accumulation, 累积
; n) U. K1 |$ G$ N9 eAccuracy, 准确度, V$ |2 y# b4 L; Y
Actual frequency, 实际频数
) x* h& K. g) f: t& A6 {! Z: J* N2 J0 uAdaptive estimator, 自适应估计量
`; d! J2 n9 h) v' NAddition, 相加) l" J' s) N1 G7 [8 {! Z
Addition theorem, 加法定理; V X4 M9 N2 f4 U% ^2 K9 G
Additivity, 可加性4 p3 G8 [( ^& L$ j
Adjusted rate, 调整率
/ @1 G! P% A6 S/ tAdjusted value, 校正值- o9 q9 h: L6 F. u9 Y
Admissible error, 容许误差
+ m' b h; g9 ]+ QAggregation, 聚集性7 z# E0 m- D5 s+ T4 @
Alternative hypothesis, 备择假设( n3 U4 [/ u( g2 h3 x( a/ k; k' O
Among groups, 组间1 Y: I) \: L/ z/ o$ N( B- [8 D
Amounts, 总量4 b7 [# l8 Y1 _: B6 Z% F
Analysis of correlation, 相关分析
3 L5 Y! W7 N4 \. f+ wAnalysis of covariance, 协方差分析
2 E0 v/ ?2 O$ w- u+ TAnalysis of regression, 回归分析5 m, f# [7 z! @* w1 K9 A; W
Analysis of time series, 时间序列分析6 S- C$ C0 p1 j0 t+ Q
Analysis of variance, 方差分析
( i% p. I, T+ R YAngular transformation, 角转换9 `# x3 Y3 U! s- a! b4 j
ANOVA （analysis of variance）, 方差分析- ^6 N9 |7 K# K
ANOVA Models, 方差分析模型- k) m. G; g! t' t0 ]
Arcing, 弧/弧旋
% D! j o: \$ I" P8 c# qArcsine transformation, 反正弦变换5 ]+ A: M$ i& A- k1 y% `
Area under the curve, 曲线面积. T, W1 z4 X1 W
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
1 @% ^' \0 P/ RARIMA, 季节和非季节性单变量模型的极大似然估计
8 t: h2 ]; _9 WArithmetic grid paper, 算术格纸
. x3 k& c x: W$ [+ z+ hArithmetic mean, 算术平均数
2 b& H5 k- |5 n- g- q" j" x. {4 vArrhenius relation, 艾恩尼斯关系
; S2 @: h1 t3 F7 y# z7 E0 |- `Assessing fit, 拟合的评估' Q; r2 D$ ^; L& l1 m' a
Associative laws, 结合律
+ ~/ z r1 |& O8 Q& OAsymmetric distribution, 非对称分布6 o9 h! M6 n+ P1 W4 D6 y
Asymptotic bias, 渐近偏倚- v! G* E8 v9 y% b/ O& g* Q$ T
Asymptotic efficiency, 渐近效率
( u3 F# o# N! p5 X/ vAsymptotic variance, 渐近方差- I; U5 |4 y8 d4 Y" d k# A
Attributable risk, 归因危险度
& C k# w; W }: k7 hAttribute data, 属性资料' S- X" {3 k/ S& S0 T& ~& w
Attribution, 属性
0 f' b1 E U, N0 @# s8 d: xAutocorrelation, 自相关
" ^5 x" T" J1 t( E; HAutocorrelation of residuals, 残差的自相关
1 n: U2 ~* ~. ? fAverage, 平均数2 h/ X: d. V( z% W$ F H5 j1 p
Average confidence interval length, 平均置信区间长度
7 r0 \& h0 U) p8 ^Average growth rate, 平均增长率' r- V$ D" T7 s4 s! e0 T' w }9 W
Bar chart, 条形图6 h' N# c" w2 f7 O1 X
Bar graph, 条形图
( A, v _0 s) gBase period, 基期) s$ I q9 m( f% q9 o/ r0 j
Bayes' theorem , Bayes定理
, ]3 P' ?. H4 L- yBell-shaped curve, 钟形曲线
8 |, l1 r% x' N* IBernoulli distribution, 伯努力分布
. v4 C7 L3 ^% pBest-trim estimator, 最好切尾估计量$ u- @. n' u+ @. L7 ^
Bias, 偏性) o. W' W6 j; j" t S) g
Binary logistic regression, 二元逻辑斯蒂回归$ E, c1 [- ^0 R2 h' [6 O
Binomial distribution, 二项分布$ P: F4 K% e, g+ Z4 b! M2 C" k, G
Bisquare, 双平方
' @4 T( |0 ?: b# [$ y' [' T3 HBivariate Correlate, 二变量相关
3 i: l& J0 d+ Q; k2 G) K; aBivariate normal distribution, 双变量正态分布3 S/ o6 f5 u" }8 {- l) v
Bivariate normal population, 双变量正态总体4 M1 ~) V+ A- x! \
Biweight interval, 双权区间
+ f! s- ?5 z4 ~Biweight M-estimator, 双权M估计量
0 O$ i) G$ y' z7 eBlock, 区组/配伍组
d/ t! V* L3 M% R) KBMDP(Biomedical computer programs), BMDP统计软件包+ h/ F& \' g5 A9 s
Boxplots, 箱线图/箱尾图
. O7 L$ G% N, P) sBreakdown bound, 崩溃界/崩溃点4 Z& N* H8 z# s) u( N0 X
Canonical correlation, 典型相关
5 o, m; Y3 ?& f. JCaption, 纵标目) u8 }7 E3 X8 s' v' Y. h- K
Case-control study, 病例对照研究
# T, ~- U6 z: p1 I) W4 B7 c* d* YCategorical variable, 分类变量7 s. u& Z) d4 Q6 x: s, V% k
Catenary, 悬链线) w' f" E* i0 ^1 u
Cauchy distribution, 柯西分布
' a. E/ | p1 U5 Y5 oCause-and-effect relationship, 因果关系% M ]2 Z7 x: n$ M2 L( l
Cell, 单元6 J* t* ]6 @ Y
Censoring, 终检
( I9 q" N$ Q2 A+ \3 N' `& L1 XCenter of symmetry, 对称中心; ] z5 P# K$ \9 Y" F$ k4 R
Centering and scaling, 中心化和定标& y8 T- s1 I; O7 z/ S5 p0 \& u
Central tendency, 集中趋势8 l6 y$ x. _! v+ n: x% M1 X' R
Central value, 中心值
- w1 w; N# [* U% jCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测; q* w1 W( o3 g, g8 L
Chance, 机遇
* ^1 X' {% b; ^2 n" v( qChance error, 随机误差
5 H- ]' b+ X5 u$ e, P/ a g5 a( yChance variable, 随机变量4 m7 i8 w3 c2 M& H
Characteristic equation, 特征方程
2 ^1 |: G; Q0 Z( {# B) H) }' cCharacteristic root, 特征根
4 L1 M7 k$ t2 {% DCharacteristic vector, 特征向量
# Y- s/ h ?. UChebshev criterion of fit, 拟合的切比雪夫准则
3 J8 l+ v4 Y5 dChernoff faces, 切尔诺夫脸谱图 {# r3 f D) a" N, |4 |# f
Chi-square test, 卡方检验/χ2检验
3 {# S% o- t: G% G8 }* H, c3 D* dCholeskey decomposition, 乔洛斯基分解
( x1 X2 H) }2 k2 QCircle chart, 圆图
& U5 x2 V8 f3 y2 e) p' f3 tClass interval, 组距
4 Q. `# ?2 `4 e4 `' a Y! yClass mid-value, 组中值
8 B2 p# X4 ^2 o2 F- T; xClass upper limit, 组上限
6 `$ f& W' g' m0 o5 CClassified variable, 分类变量
- _2 c7 \1 l7 g1 b; GCluster analysis, 聚类分析( G3 b- f; z/ `) Z
Cluster sampling, 整群抽样2 L+ v2 L8 X. l( f$ g
Code, 代码& ?8 Y( I) C# K/ G) b
Coded data, 编码数据- q1 ~* b- T ?. J) c2 O
Coding, 编码" m+ R: O: a5 D, |, O4 \
Coefficient of contingency, 列联系数
; D1 E5 M3 A( M& aCoefficient of determination, 决定系数
0 X9 v3 n# g9 Z; M) b9 kCoefficient of multiple correlation, 多重相关系数' L* O5 `! y, V# a2 Z$ C( b/ [; t
Coefficient of partial correlation, 偏相关系数& q# W/ d% t0 z: {6 I
Coefficient of production-moment correlation, 积差相关系数# o- r" n( E8 P
Coefficient of rank correlation, 等级相关系数+ r, N0 Y0 y! l2 l+ V
Coefficient of regression, 回归系数
/ S$ R( p- G$ xCoefficient of skewness, 偏度系数
- g( N/ D3 V# `9 vCoefficient of variation, 变异系数! l4 A8 l& ?' P/ ^; c/ y3 W6 o4 t- E
Cohort study, 队列研究 q+ e7 [3 r* G' X' }: v
Column, 列, u, L" y1 U! [% M. L/ r. ?$ y
Column effect, 列效应; g1 Y5 y3 |0 K( J. r
Column factor, 列因素1 |* T. o4 R) w4 d% ]/ }
Combination pool, 合并7 R6 \, T4 }* ^
Combinative table, 组合表, ]- ?4 Q5 f- y# L. @" f7 J
Common factor, 共性因子
9 g9 W. D" q* o7 vCommon regression coefficient, 公共回归系数+ T% e9 s: S% u. U2 i
Common value, 共同值
; e8 D2 ^- R0 p( `$ t* |Common variance, 公共方差
% x: [4 {! F' H3 W! k1 p, FCommon variation, 公共变异+ b; z8 t+ ]! ^7 x
Communality variance, 共性方差
8 y7 t7 Q9 D1 [/ O: PComparability, 可比性+ y) M) x5 j; N9 \ E4 X
Comparison of bathes, 批比较
+ m% P3 Q* z0 t4 T3 K8 M8 ?2 A* @: ^Comparison value, 比较值0 I/ m( a2 J8 Q( P7 R
Compartment model, 分部模型" a0 K& O- |1 f& t# L
Compassion, 伸缩
1 `4 R# T" O6 @; i/ x* n! H( gComplement of an event, 补事件 H: ?7 C2 j: f2 H
Complete association, 完全正相关 ]) b. v5 L( v5 j3 W. d
Complete dissociation, 完全不相关
7 P7 K) c+ D6 SComplete statistics, 完备统计量
3 Y5 {5 h9 K* ?1 BCompletely randomized design, 完全随机化设计
0 ?# i+ _" }: BComposite event, 联合事件. C$ E: m, Q1 n2 s$ n& Q; Z% t
Composite events, 复合事件: Z# k f( ]1 P9 m; e" c
Concavity, 凹性
3 r/ b9 ~* K, k5 l8 v# [ j/ HConditional expectation, 条件期望
5 l# p$ p, j( _: Q ]Conditional likelihood, 条件似然0 x6 Q( Z$ Q4 ~( X8 l( k
Conditional probability, 条件概率
, S3 i9 J2 X8 ]: {. O; O; n- {* WConditionally linear, 依条件线性
8 l' S: L' {* [, n8 z7 WConfidence interval, 置信区间; q, J4 d( W2 d2 M8 G+ U3 C' m
Confidence limit, 置信限( F& ?& `. S; M( ?4 V* F ]/ o. L& C
Confidence lower limit, 置信下限8 D* w/ Y5 }+ v
Confidence upper limit, 置信上限
* `- F9 t, Q6 ?* {Confirmatory Factor Analysis , 验证性因子分析4 @+ C; a0 Y" [" V3 J
Confirmatory research, 证实性实验研究+ W! } X/ z8 ~/ Y; t* a
Confounding factor, 混杂因素0 M! W! G" ^; c, _) {: O, o
Conjoint, 联合分析
! i3 _2 b9 P! R; q. TConsistency, 相合性$ y* \6 t$ m- T- G! S
Consistency check, 一致性检验
6 w6 L% n% D. {2 B$ jConsistent asymptotically normal estimate, 相合渐近正态估计6 a7 G. f! N" ]0 m
Consistent estimate, 相合估计; `' ^, t3 _9 C* J
Constrained nonlinear regression, 受约束非线性回归
" f% c& c) h; [: ]Constraint, 约束
( P. Y3 C6 e4 X v" d% |) p' P3 M" QContaminated distribution, 污染分布7 Z6 x, |! Y; O2 h4 [/ Q1 U
Contaminated Gausssian, 污染高斯分布$ S" M0 B0 @& G0 J
Contaminated normal distribution, 污染正态分布
6 `$ n, b8 L( C# a$ b9 _Contamination, 污染
$ [& {5 k* i9 ^! K O2 _' ]2 G( GContamination model, 污染模型
4 ^6 Y- I: b' ZContingency table, 列联表+ ^* L! r/ b1 p7 D5 ?* e
Contour, 边界线7 \& U: j, n+ X( }
Contribution rate, 贡献率
6 R5 ]5 I3 _8 BControl, 对照$ J% ]" {( r C' K6 R& H; e+ x
Controlled experiments, 对照实验
6 \9 q2 t) a- S F9 C7 zConventional depth, 常规深度# D" Y s% b3 W0 B1 a
Convolution, 卷积2 n; {! e. G& r6 }; U+ n b
Corrected factor, 校正因子
$ e' j2 @, A; c* \& k7 b% D mCorrected mean, 校正均值
8 J7 l5 k- A3 P; E+ UCorrection coefficient, 校正系数2 w$ v& O, s, c* W) z
Correctness, 正确性
+ [! ]8 S4 l/ S wCorrelation coefficient, 相关系数/ @1 ]) y: A# Z R
Correlation index, 相关指数
( `# r5 D8 k# RCorrespondence, 对应
7 X. u' G& Z' Y; R* i- a5 mCounting, 计数+ w+ g9 d' b V/ g
Counts, 计数/频数
( t& C+ q) e oCovariance, 协方差/ a5 |8 _5 T; c% h: m5 D3 p! ~3 W) v
Covariant, 共变 Y3 `+ Z0 ?7 ]0 E( o) v% S- x
Cox Regression, Cox回归 L8 I2 @1 \+ g1 K4 ^
Criteria for fitting, 拟合准则1 N. T2 Z7 b3 b8 n9 H
Criteria of least squares, 最小二乘准则
: g3 E: T# ~- j5 R7 }) W' qCritical ratio, 临界比& I9 E0 h! ^$ u+ A" i9 n
Critical region, 拒绝域
: w* {2 @# X8 j; e4 Z: z% _Critical value, 临界值3 Q0 i: D5 }5 v+ Q
Cross-over design, 交叉设计
! u# m8 r& `; L6 M- T! k3 KCross-section analysis, 横断面分析
7 U: H- d, [9 J+ V# D5 ACross-section survey, 横断面调查
. Q# c/ Z- g7 W$ l1 k( K% y- _Crosstabs , 交叉表
. Z+ Z- O- [: n% O; t0 NCross-tabulation table, 复合表
4 l8 s) c; V1 H$ vCube root, 立方根. N J' O, Y! f" \
Cumulative distribution function, 分布函数
- p2 J! I: Y" ?3 ]; j$ C3 h y% \; SCumulative probability, 累计概率
& Q8 H, I" H" c2 TCurvature, 曲率/弯曲0 p: |' Y8 ?6 S' U C' v+ e9 ?
Curvature, 曲率4 @3 m% o1 {& E1 h0 l0 e
Curve fit , 曲线拟和 ) s4 r) U; z/ E9 a: H8 d; E( i% P' y9 r
Curve fitting, 曲线拟合
& t: B" `. \+ ?: a9 M U3 I+ _Curvilinear regression, 曲线回归& \8 `! p0 x2 O5 |* g7 h; ]
Curvilinear relation, 曲线关系1 {) J& N: c* B
Cut-and-try method, 尝试法
_6 {% T. z! |: U( c1 M, \1 N* pCycle, 周期
+ y1 z" R% q4 j) f, w: q% BCyclist, 周期性
( x4 w8 ]$ }3 T' KD test, D检验
& {8 Y7 o( U7 n1 d! b' m" DData acquisition, 资料收集. O' d/ K( `4 f8 x
Data bank, 数据库
6 M4 f2 u+ c7 ?2 u YData capacity, 数据容量
* i- A: X+ M- n$ ^Data deficiencies, 数据缺乏/ }0 C5 T# m7 H# t0 g
Data handling, 数据处理
h; K- g: w5 Y! x2 _* W$ TData manipulation, 数据处理1 @4 \: \4 d, S" `4 W. Q0 y) u
Data processing, 数据处理
% J4 m, M& M+ DData reduction, 数据缩减+ J* l1 m) y5 H+ f) C. `3 G
Data set, 数据集 T% T; p' N; |# u! b+ L
Data sources, 数据来源' q: j. t' ?3 g
Data transformation, 数据变换
- V U5 ~/ Z1 Z! l! W1 [5 H% HData validity, 数据有效性7 B0 L0 x. H6 v/ ]/ s
Data-in, 数据输入, k9 W8 h4 O$ @8 k7 t* K! G+ U. q
Data-out, 数据输出
- @2 d' ?- h) a1 gDead time, 停滞期, Z; t5 `4 f9 E6 n1 w6 a7 u* ~4 w) A" B- T
Degree of freedom, 自由度# ]' W b& c4 c" U8 ^& {8 ~
Degree of precision, 精密度
1 N8 ^1 } e/ jDegree of reliability, 可靠性程度8 _# g5 w! I3 l/ K5 s0 {# U
Degression, 递减
0 Z* Z- q2 b N! G; WDensity function, 密度函数8 K2 D$ r5 h. s0 N. Z( ^# u6 h
Density of data points, 数据点的密度
5 m, L$ Z% R QDependent variable, 应变量/依变量/因变量
8 H% }* Y( K, M5 P. A. C) fDependent variable, 因变量7 n* j. y& _+ _4 }% Z
Depth, 深度
: P2 H! U( x6 i6 q1 v6 c% lDerivative matrix, 导数矩阵5 `, T W4 V, H! O' E! h
Derivative-free methods, 无导数方法8 q& I( I. m/ }% m2 n: c7 W
Design, 设计; k4 D6 \" G# D
Determinacy, 确定性1 j, }5 Q% G, P6 i+ P9 |$ ~
Determinant, 行列式
E8 s& q- M5 T5 I2 |Determinant, 决定因素# l g, }6 I& W9 s
Deviation, 离差
! i! w0 e- I5 \0 T2 F( `4 IDeviation from average, 离均差
# V! v. J/ q* k1 f6 b& T* p) dDiagnostic plot, 诊断图' G) z4 |5 L! J7 K3 ]- \( Y
Dichotomous variable, 二分变量
5 ` \% j7 l8 W3 a: ^) J1 S+ S2 FDifferential equation, 微分方程
8 O O% ^& V7 DDirect standardization, 直接标准化法
' k# E& B9 ?$ A8 bDiscrete variable, 离散型变量3 |: N0 e) Z/ n
DISCRIMINANT, 判断
/ `; Z0 F; q4 i( n' ]Discriminant analysis, 判别分析 x" h( f+ I4 ]% G" w
Discriminant coefficient, 判别系数
! j) [# k) u9 a1 N' e( P# KDiscriminant function, 判别值
5 |- o& ?4 n# [1 c! S+ xDispersion, 散布/分散度/ J% Z2 ]8 l* p
Disproportional, 不成比例的* m( _ c, Y. z. ~2 ~8 S3 x8 H
Disproportionate sub-class numbers, 不成比例次级组含量" s/ b% d9 l$ v3 A# m2 n8 d: c
Distribution free, 分布无关性/免分布. X% \0 q& f" m! x9 o
Distribution shape, 分布形状
- {- v( [* L: C- F8 K% ^( HDistribution-free method, 任意分布法
; d# Y) Y5 @9 {! i# X4 X9 a: U/ j7 TDistributive laws, 分配律
7 q0 a4 p4 t3 \7 u4 rDisturbance, 随机扰动项
+ V. v7 L6 o. uDose response curve, 剂量反应曲线
) S+ }6 b: i2 U$ @! s0 m! tDouble blind method, 双盲法& B6 ?+ ^$ u5 [& T
Double blind trial, 双盲试验
/ @4 i7 G+ w! X9 I# MDouble exponential distribution, 双指数分布
' R: b; ^: a; v$ jDouble logarithmic, 双对数! w+ k. a2 u% I5 [" ?* S$ [
Downward rank, 降秩" x0 H" {3 A4 \+ [# b5 s& `6 P
Dual-space plot, 对偶空间图
V' H! C5 M0 V# A% Z0 |: q) T6 ~" j8 vDUD, 无导数方法
1 r3 ^4 a, T. y0 i! Y# ^Duncan's new multiple range method, 新复极差法/Duncan新法
3 D( a8 |+ ]; u0 n% z, AEffect, 实验效应2 s/ K0 k) p' Y6 D
Eigenvalue, 特征值6 K6 R% I6 @% `7 e: h
Eigenvector, 特征向量
9 h4 k( W5 u( s0 b* _% pEllipse, 椭圆; x# M% ]9 B: B4 C5 K
Empirical distribution, 经验分布
' j# @0 v! Z/ w. t6 C7 g! `Empirical probability, 经验概率单位, r" K6 u/ c& X- h
Enumeration data, 计数资料
; T. Y7 G- S4 Y& p/ eEqual sun-class number, 相等次级组含量) W! ^! F" W2 z+ f; _
Equally likely, 等可能- D5 W( T; R) L
Equivariance, 同变性4 ]) ^ x& Z& a" m6 T
Error, 误差/错误, B X- n; M* x! @4 y
Error of estimate, 估计误差# j: F$ G( s* K7 L
Error type I, 第一类错误, h6 j* t7 j t, v0 E8 Z. W- P
Error type II, 第二类错误
H- J6 X7 W2 i2 A' N& Z AEstimand, 被估量
! _+ S7 {; J! DEstimated error mean squares, 估计误差均方; `* g0 u& w6 b4 D6 G3 `
Estimated error sum of squares, 估计误差平方和7 `; G4 Y1 ]5 j! G7 S) l
Euclidean distance, 欧式距离
, u' Z: M$ _1 ?$ |6 W+ V6 JEvent, 事件% c7 X% z6 r* u& V) k( X
Event, 事件
5 W7 d# H6 m3 D8 `" OExceptional data point, 异常数据点2 l1 Z Q m# \1 T/ Y6 w9 }5 x1 Y
Expectation plane, 期望平面
4 Y, P2 q! w6 ^7 bExpectation surface, 期望曲面/ i, A4 u- ^, i2 u/ n( X
Expected values, 期望值
5 R8 M$ g, q! S3 h) ^( V& BExperiment, 实验
7 e Y6 W# q& }3 GExperimental sampling, 试验抽样9 h. f/ |9 V& V1 \8 _
Experimental unit, 试验单位
( u- Z( F8 |8 m! y# |Explanatory variable, 说明变量; m0 t: w3 }& \( u* Y- h2 @# w
Exploratory data analysis, 探索性数据分析
# X0 `" m$ E; SExplore Summarize, 探索-摘要
z& \) l' X- h/ o7 ^/ `& J% BExponential curve, 指数曲线) X! U7 k4 L* i- j' t l6 z
Exponential growth, 指数式增长2 A' B' h7 u! z6 i
EXSMOOTH, 指数平滑方法 , g- G) `/ @2 T. E
Extended fit, 扩充拟合( G/ C/ [* f+ c. P( f" S @9 A
Extra parameter, 附加参数1 o0 L- P- }( I% c9 I
Extrapolation, 外推法
. w& n" {) c, r$ O( UExtreme observation, 末端观测值
7 h* T3 U4 I" M' E/ D# nExtremes, 极端值/极值
3 t- s& ?) E l4 DF distribution, F分布2 e8 P9 v/ d/ R, Q" U4 N9 [
F test, F检验 J/ e) i+ \5 F; g; a2 m- ]; v
Factor, 因素/因子
/ ?! b0 }5 G* q7 p" xFactor analysis, 因子分析$ U% o J9 l# K5 M8 M( I3 I
Factor Analysis, 因子分析! g5 B+ ?4 a) G) j
Factor score, 因子得分
. |( }- i, J8 I: Z) nFactorial, 阶乘
3 x8 d% b4 X8 }" k: oFactorial design, 析因试验设计
$ a d. |, ^* v0 t* D7 I5 [False negative, 假阴性. N8 d) i8 e+ A# K- M
False negative error, 假阴性错误8 v) v4 d1 r1 t8 ^
Family of distributions, 分布族
- ~4 x: x. ~% v: ZFamily of estimators, 估计量族
) u" ~: X: y, V kFanning, 扇面$ `1 L: K+ p. |" A3 q' l* l+ O
Fatality rate, 病死率
3 a) m7 a3 ~- W- l1 W) D0 jField investigation, 现场调查
& M- i7 E0 ]4 dField survey, 现场调查4 ^/ S, V" a5 r: E$ N1 h+ V
Finite population, 有限总体9 C6 T G! b4 O6 r' a2 M. K d
Finite-sample, 有限样本
+ O+ R3 ^# S: i s1 F$ eFirst derivative, 一阶导数& f+ N' E4 ] c2 ?1 m* {
First principal component, 第一主成分
6 G* n8 Z$ @. |) rFirst quartile, 第一四分位数
7 ?2 Y4 B" K" e i+ gFisher information, 费雪信息量 J6 k# W W" f
Fitted value, 拟合值7 i( N7 T8 u- Z! D
Fitting a curve, 曲线拟合( ]- v$ K2 j; g# ^' q
Fixed base, 定基6 Y( {8 j2 ]1 G
Fluctuation, 随机起伏, L8 Y! t- U& F; D4 @. ]0 `/ G w
Forecast, 预测0 ^( v, j6 ^( z1 @6 Q
Four fold table, 四格表. b( a Q% T! X- u* A# L: H
Fourth, 四分点6 }1 m+ h) W, u8 n" T4 _
Fraction blow, 左侧比率
8 e/ R; I0 S% J; y( [- cFractional error, 相对误差
) {1 E; S9 r5 ~" p2 J4 P6 A* R; xFrequency, 频率) e1 h3 [4 }$ E5 K5 S( x; M
Frequency polygon, 频数多边图
, h4 O5 ^6 B: p% d. K, M( KFrontier point, 界限点2 w6 A4 u e) e! B' K
Function relationship, 泛函关系
0 f( W+ ^7 C8 BGamma distribution, 伽玛分布. W# C: s" ^9 Z$ {
Gauss increment, 高斯增量
5 u6 D, D) P/ S) i& p4 R3 G1 YGaussian distribution, 高斯分布/正态分布
8 d' a) X5 M( M2 I: IGauss-Newton increment, 高斯-牛顿增量) L- Y0 R$ y* r: M8 i
General census, 全面普查
, k+ A$ }- ^; @GENLOG (Generalized liner models), 广义线性模型 & u2 b, y1 E: l0 g/ v7 i
Geometric mean, 几何平均数
% ^* ~6 e f( K1 c8 f# a# P: q9 CGini's mean difference, 基尼均差( a8 C- V% z, e" C) e
GLM (General liner models), 一般线性模型
9 C: V! F* K) I) e6 v+ XGoodness of fit, 拟和优度/配合度
* G3 r! y) R% ]! XGradient of determinant, 行列式的梯度
4 h% [! E! ~) Y- [2 o+ R+ B6 fGraeco-Latin square, 希腊拉丁方! A$ T% U2 b- g: }0 A
Grand mean, 总均值' G& C' \$ j. }$ Z' M) c+ P8 ~" `
Gross errors, 重大错误
! ~% B6 E7 S9 X( A) `) XGross-error sensitivity, 大错敏感度
+ n. S0 Q9 R* T0 _( z0 |0 m' KGroup averages, 分组平均
. d) P6 h+ G! ?6 K3 Q `, Q" S" BGrouped data, 分组资料
* \: K7 [" ^+ a% M/ e# q# d. ?. VGuessed mean, 假定平均数
! f- {4 k0 [ S1 c j# \) h8 SHalf-life, 半衰期
2 D! _# l B3 i. n3 q& LHampel M-estimators, 汉佩尔M估计量
4 k+ m+ y7 j* G- V' n7 BHappenstance, 偶然事件
8 Z& k+ ~' V! d! r' X gHarmonic mean, 调和均数% S( {% z1 r7 Q# B3 t; L
Hazard function, 风险均数
A" q$ T: I; U: @Hazard rate, 风险率) v. G. i) {3 P9 x
Heading, 标目 ; e1 M% e6 J. k& T, e; ~6 H" {
Heavy-tailed distribution, 重尾分布) [! v0 d2 `; U& {6 ~
Hessian array, 海森立体阵8 @7 S. }; [) U# B
Heterogeneity, 不同质/ J' }8 ^6 t8 W' x
Heterogeneity of variance, 方差不齐 " o G$ l( A0 f9 v1 S9 ?
Hierarchical classification, 组内分组 \4 p! u9 {( e- L, q f- N( j
Hierarchical clustering method, 系统聚类法/ F, G. p8 R& G: N5 M+ [
High-leverage point, 高杠杆率点9 C/ G+ D3 A+ I" z$ i
HILOGLINEAR, 多维列联表的层次对数线性模型
- ^* F& A" T- M: _Hinge, 折叶点1 t, M: c$ y }) k# p2 `
Histogram, 直方图+ O3 x, [- u, w$ G& x' x8 T
Historical cohort study, 历史性队列研究
) x: X; p, b" \9 x4 G1 ~7 AHoles, 空洞
; x8 _: T1 s. j% o$ ^* kHOMALS, 多重响应分析% O( K' A. m4 k' j. G8 e. F
Homogeneity of variance, 方差齐性6 e$ L3 g0 s; @
Homogeneity test, 齐性检验
* F0 c" W' ^: L$ ?0 y# y, ?0 PHuber M-estimators, 休伯M估计量# G) F% A6 V# n5 ]
Hyperbola, 双曲线
" l5 K8 y2 [, a: q3 t1 ZHypothesis testing, 假设检验
2 V# W6 \% z8 {. C4 @! H% g, p! |7 bHypothetical universe, 假设总体
- ~. Q9 |% r* _! o/ U4 m; GImpossible event, 不可能事件
; b' L6 @2 A1 k# x7 c' PIndependence, 独立性9 {2 t7 N$ s) A3 [3 w$ c
Independent variable, 自变量
$ D' j# b! W5 }7 CIndex, 指标/指数
, j% @8 z9 O: t9 CIndirect standardization, 间接标准化法+ g! K0 n/ a$ C( u1 {; r9 R
Individual, 个体$ e/ e. a" o0 J9 r% [
Inference band, 推断带+ H n" W7 |4 v& J( @" u. Q1 L% Q" A2 Q6 G
Infinite population, 无限总体
% H/ v/ D- Y0 r/ p* n0 z) E& ?Infinitely great, 无穷大
: Q; g. t7 G) T5 mInfinitely small, 无穷小
% P% P: I, G8 a9 B5 eInfluence curve, 影响曲线' I, A- M2 F3 ^: x
Information capacity, 信息容量! g/ ~3 G1 C! R6 N) \! m$ [9 K
Initial condition, 初始条件% | J, g% n4 s* G
Initial estimate, 初始估计值
6 [) L I% p# M/ m0 }Initial level, 最初水平1 F7 d+ |, F, L' @ [" Q3 \
Interaction, 交互作用0 i' m; }5 d) V5 @1 _; l
Interaction terms, 交互作用项. @8 {. b/ i( ^0 H
Intercept, 截距/ P3 s5 G% [+ W( k4 n
Interpolation, 内插法
. n& p( p g2 o) A# KInterquartile range, 四分位距! H1 A2 f6 h8 |$ H
Interval estimation, 区间估计; r: S! m* |# l' p+ A3 ~1 \0 D8 ]
Intervals of equal probability, 等概率区间
1 w3 C% a3 O ?$ c, E( K( EIntrinsic curvature, 固有曲率
( R; H, h( D X' ]Invariance, 不变性3 H/ ~0 `+ N( h5 y$ W* C6 l1 b) y, j
Inverse matrix, 逆矩阵; `% a3 \- R1 E; m! k" [
Inverse probability, 逆概率
0 G% F: O, d& v8 ~$ kInverse sine transformation, 反正弦变换; o' {( T9 V: [( E ?# V1 U
Iteration, 迭代 s! S4 P- [: {) g3 u7 c% Y; ~9 X
Jacobian determinant, 雅可比行列式( x. r. \& _2 {7 z9 c2 z5 G' u
Joint distribution function, 分布函数! t* o1 k$ v' R6 \0 q9 y& m
Joint probability, 联合概率$ o+ {/ Y1 ?- f- J% ?5 ^4 |4 E; u
Joint probability distribution, 联合概率分布3 h( W) c( T4 M2 n/ B* u
K means method, 逐步聚类法: r4 \6 v; u5 |6 V. g {
Kaplan-Meier, 评估事件的时间长度
1 o; k1 w9 H2 @* g; `0 dKaplan-Merier chart, Kaplan-Merier图! ^7 `/ e. ^ G( V7 T
Kendall's rank correlation, Kendall等级相关
! V0 f( q5 v }9 O) O8 OKinetic, 动力学9 v" \# d6 w/ w; o' H
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
& ^, O7 \9 k* m% J4 [# i% H+ _Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
+ a3 |1 |$ }$ j4 fKurtosis, 峰度3 T6 b9 s2 ~" |# g, O
Lack of fit, 失拟
c% M! j' _+ B& `Ladder of powers, 幂阶梯) a, D! u- n7 ^2 N
Lag, 滞后2 m; }% E' T* Y( Y6 S
Large sample, 大样本% u0 k5 D: [7 \$ G9 T# {- }/ I# l
Large sample test, 大样本检验
! Q* I3 p: f- q5 I& D% r1 i. oLatin square, 拉丁方. K- N8 Z7 u' W5 |4 b- d) F- k* M; i, B
Latin square design, 拉丁方设计
, T) W6 ~8 F+ f/ |) y3 kLeakage, 泄漏
% q4 `- C% s5 S9 m+ t* v( zLeast favorable configuration, 最不利构形
4 S. M: s5 e1 c0 x, P% s- ALeast favorable distribution, 最不利分布
4 ^. V# @4 ]' H+ G9 g1 T" sLeast significant difference, 最小显著差法' F+ {1 G1 |# `5 C! h8 u$ ^- l
Least square method, 最小二乘法
. g w: Q$ B q1 F4 mLeast-absolute-residuals estimates, 最小绝对残差估计, k2 E( \5 l' ^/ O1 c9 O9 l
Least-absolute-residuals fit, 最小绝对残差拟合. a. S7 z* D' N( U2 {8 |) U% o8 l
Least-absolute-residuals line, 最小绝对残差线9 N0 A, F0 Y: V/ J9 P7 `5 M
Legend, 图例
* K1 z: \! e7 G" B1 k: U, i1 f% GL-estimator, L估计量3 v; n8 R+ z% [
L-estimator of location, 位置L估计量 [& H9 ]4 \+ C {
L-estimator of scale, 尺度L估计量+ g! B9 @$ a* t
Level, 水平4 f/ V% n/ _% j: F; _, P
Life expectance, 预期期望寿命2 I7 {$ f4 l8 _5 p( z: o
Life table, 寿命表
7 M8 i/ M+ h1 W) A5 w9 Q; `Life table method, 生命表法6 r$ q6 ^5 Y+ i4 D/ {
Light-tailed distribution, 轻尾分布
" H H$ h( @% K5 u% O- xLikelihood function, 似然函数
" @' C0 A9 E# i. q/ U5 P0 Q+ {' @Likelihood ratio, 似然比; m0 e5 b4 u6 F& G% r p
line graph, 线图
. x, B! h8 _$ i/ A/ m) }Linear correlation, 直线相关
. K+ L% z1 D: L0 Q) W: q$ V; l! SLinear equation, 线性方程0 ^5 l4 K2 |+ ?
Linear programming, 线性规划' p1 Z( P& z& i1 |) e0 o
Linear regression, 直线回归 r( m' L$ X6 `+ r4 D# P8 v
Linear Regression, 线性回归
( O3 i0 A" p; ?7 O/ u. r* yLinear trend, 线性趋势! U( K/ W' M# F- H
Loading, 载荷
* i, }8 |/ X' F5 i- KLocation and scale equivariance, 位置尺度同变性
! e. ?) b S. X& n0 n2 O$ VLocation equivariance, 位置同变性/ I1 Q" o, H( v: o0 C
Location invariance, 位置不变性0 Z/ N3 v2 d; f& D! k
Location scale family, 位置尺度族9 P7 a A3 a6 U5 k7 a Y3 {0 V
Log rank test, 时序检验
& B9 H/ U7 W; ]6 H5 V& BLogarithmic curve, 对数曲线! ~. z% \# u0 }0 _. e
Logarithmic normal distribution, 对数正态分布
1 n4 j" l( A+ ^: R. ]3 \Logarithmic scale, 对数尺度; M; W% r. D9 J! G% w% G0 r8 }
Logarithmic transformation, 对数变换$ c: \) u) |$ R
Logic check, 逻辑检查
6 }$ d8 J. Y8 v6 tLogistic distribution, 逻辑斯特分布* b4 j6 O# [. X, k2 r
Logit transformation, Logit转换
, A3 s6 g0 F8 ?1 s" K4 PLOGLINEAR, 多维列联表通用模型 ( a& E3 H! {" |+ p' o" F! C3 V
Lognormal distribution, 对数正态分布
9 u A* Y3 \! p" O/ fLost function, 损失函数2 E3 J( |& Q, Z2 d$ e- b( G0 `
Low correlation, 低度相关
( q# W' S, w# a. ZLower limit, 下限
5 `; S( k( `2 F, G4 ~2 \Lowest-attained variance, 最小可达方差
) n% r# i0 \- ?/ j! t: ~* w' m5 CLSD, 最小显著差法的简称2 A+ e7 c0 V7 X1 f" r$ ?
Lurking variable, 潜在变量
( d5 i) ?7 X9 T& Q) X5 ^Main effect, 主效应
+ I/ f' O8 F1 e6 f5 gMajor heading, 主辞标目
2 a6 `. `' j- Y. xMarginal density function, 边缘密度函数
( }6 w, _: t1 ]Marginal probability, 边缘概率6 ]! y2 X4 t6 ?/ n
Marginal probability distribution, 边缘概率分布' H" d) D2 H: Y$ X0 X0 S/ q
Matched data, 配对资料
. o9 d4 K* p5 N0 kMatched distribution, 匹配过分布1 Q* D- |+ }/ |: r! I+ p F
Matching of distribution, 分布的匹配* ^0 g6 v$ m0 U+ y# x" {" v
Matching of transformation, 变换的匹配 s# e I7 v3 V( _; n
Mathematical expectation, 数学期望, ], D- m! q! e7 ]2 i, j' c
Mathematical model, 数学模型' G$ w3 Q, d% a. r
Maximum L-estimator, 极大极小L 估计量4 l' D9 _2 `2 \# ~
Maximum likelihood method, 最大似然法) f' z& X( e6 f, O' ], X
Mean, 均数
8 s2 W& Y) J0 B5 m. zMean squares between groups, 组间均方
" q7 z1 V8 [& ~5 {9 {/ qMean squares within group, 组内均方
$ ^! }8 \5 n4 y# l" VMeans (Compare means), 均值-均值比较
! E7 y6 N1 l' _- T1 b6 BMedian, 中位数* ] C& u2 l# B
Median effective dose, 半数效量 n/ |3 a* O2 A" z- }0 J- [5 y
Median lethal dose, 半数致死量
. h3 t N$ N% AMedian polish, 中位数平滑
; j' x; Q5 m. M4 g7 ?6 }Median test, 中位数检验
( @* x% D4 n8 o: ?7 f8 k% UMinimal sufficient statistic, 最小充分统计量
, Z- e. G$ z! d( dMinimum distance estimation, 最小距离估计
2 i$ f2 b+ N, hMinimum effective dose, 最小有效量
+ F1 s) K* _" t6 ]! U+ UMinimum lethal dose, 最小致死量
2 A" i N- a( Q/ kMinimum variance estimator, 最小方差估计量; d6 ?' M. S: n+ V/ b
MINITAB, 统计软件包
/ L0 g. m, y/ ^$ l; sMinor heading, 宾词标目
~9 S$ W$ L" t, ^ ?Missing data, 缺失值" `. t1 D* D: O3 L1 l+ `" _
Model specification, 模型的确定. d0 v! v- l, @, X
Modeling Statistics , 模型统计
$ ?# \% E7 K0 F Z s+ tModels for outliers, 离群值模型& H$ \+ e# }' g$ c) q
Modifying the model, 模型的修正
% B/ n4 F) u% b* P% ]# [Modulus of continuity, 连续性模; s6 w, U i; a
Morbidity, 发病率 $ D6 q$ n( g. P; K! o- a
Most favorable configuration, 最有利构形5 a2 C0 }1 n' L# m. ?5 a
Multidimensional Scaling (ASCAL), 多维尺度/多维标度% b; c A' s" H) D
Multinomial Logistic Regression , 多项逻辑斯蒂回归- x" w' V3 Q" k2 r8 s3 E
Multiple comparison, 多重比较 U! \& J8 B# }8 f) [+ n1 D# c
Multiple correlation , 复相关6 S8 ]" \4 a; \, m! g$ D
Multiple covariance, 多元协方差
& Z/ p( J8 T' O( g& F ~4 KMultiple linear regression, 多元线性回归
; b9 V0 X+ U3 \* O: Q) t# B& UMultiple response , 多重选项
& [3 o* [# J/ ?7 g- e) O/ Q; UMultiple solutions, 多解" K; u: ~* D8 y" D) V- s
Multiplication theorem, 乘法定理
8 F, ]. l6 h0 F* ^3 a' A d" EMultiresponse, 多元响应
+ \% p0 @ c. L2 xMulti-stage sampling, 多阶段抽样
6 q' P7 R7 k( v- ^! V& TMultivariate T distribution, 多元T分布8 a- v" ?. ~5 D! h
Mutual exclusive, 互不相容+ X1 B% n* x4 s; A
Mutual independence, 互相独立
6 e: b1 m) s" oNatural boundary, 自然边界
: [, O, a; [/ A+ E7 B4 W% L( ^/ R4 CNatural dead, 自然死亡
. l# q# @8 q8 CNatural zero, 自然零: Q) j& r# V8 z# p
Negative correlation, 负相关: f h. y) { v8 Y, @
Negative linear correlation, 负线性相关
0 L, g$ U$ t% U# [& s& tNegatively skewed, 负偏
' }5 k5 S7 D! h0 U( U9 r% u, RNewman-Keuls method, q检验% k5 Z. y3 l+ m# ^
NK method, q检验
0 S0 ~' N5 {+ x3 `4 R- b! _No statistical significance, 无统计意义* o( x6 H) l( C* m
Nominal variable, 名义变量
! `% A5 @$ K o# A/ eNonconstancy of variability, 变异的非定常性9 _! M) Q8 X" T% f' W! C
Nonlinear regression, 非线性相关
8 t: F, }* n7 a! V7 s+ F1 p4 h! uNonparametric statistics, 非参数统计. l" g8 N8 l6 Y1 Z" C- v5 l6 P
Nonparametric test, 非参数检验4 v) V$ {1 X- x3 `5 C( O3 G4 D- t
Nonparametric tests, 非参数检验
9 L3 z/ n# ~8 x6 u7 H! `: bNormal deviate, 正态离差
, L+ Q5 j" `7 i4 i. O. x% tNormal distribution, 正态分布5 G$ A9 r7 r7 T/ L; k4 m% J, E
Normal equation, 正规方程组- j& D* q9 a/ A8 g; K m$ L
Normal ranges, 正常范围
, @7 ~5 ?) v0 P0 _/ }9 E$ CNormal value, 正常值6 c! i. t+ Y. b, m8 N
Nuisance parameter, 多余参数/讨厌参数# Z( ]: z3 A7 R/ f; c$ c: @0 l
Null hypothesis, 无效假设
9 w) ?. ]1 [3 ^9 C" Z7 Z7 eNumerical variable, 数值变量7 l6 |) I6 V# F) d
Objective function, 目标函数' U7 [3 e8 @8 K( Q1 _
Observation unit, 观察单位- X# m& [0 o3 A
Observed value, 观察值
" g3 W( J9 c9 oOne sided test, 单侧检验; |: n) t6 e ]) _4 P2 L; u' E
One-way analysis of variance, 单因素方差分析2 t6 m: q( `" O' c
Oneway ANOVA , 单因素方差分析# L2 c0 g5 ]2 l0 I5 x, o, U, w
Open sequential trial, 开放型序贯设计8 _( ~) ]: j. l& j3 r r
Optrim, 优切尾1 A: O9 q+ d6 ^9 |
Optrim efficiency, 优切尾效率
, H5 K+ v4 Z6 v/ h2 ^Order statistics, 顺序统计量1 r4 j: l" L* Q- f! S8 Z2 V4 U
Ordered categories, 有序分类4 o: W& }* n6 P3 U$ B1 ~
Ordinal logistic regression , 序数逻辑斯蒂回归
. D4 K+ [8 h- [Ordinal variable, 有序变量5 g7 K2 R# d/ t3 s4 T/ W d1 I
Orthogonal basis, 正交基
: p3 L2 r( G0 W* K+ N, @0 i3 ?. kOrthogonal design, 正交试验设计
* d7 x, G6 w% _( a' HOrthogonality conditions, 正交条件
. \- b" i5 }( u) w! h% [7 pORTHOPLAN, 正交设计
: u; Y- v; y, G, L9 b l; BOutlier cutoffs, 离群值截断点
0 P5 {* T6 ?! D( s3 vOutliers, 极端值) c! D* Z2 t, J d: S7 ]$ @6 @
OVERALS , 多组变量的非线性正规相关
& U5 v% v; C% H i+ lOvershoot, 迭代过度
% b+ Q, ?3 K* h6 e. XPaired design, 配对设计
* S9 |+ U i: P! T/ {- dPaired sample, 配对样本
4 k4 k1 G) X+ J7 `: ?) V+ kPairwise slopes, 成对斜率; @& t) E9 E# }
Parabola, 抛物线
+ k5 X7 @- r- N! ~' qParallel tests, 平行试验
% g6 i' x1 F# ^ j6 f$ bParameter, 参数
$ | {, A7 N# ~) }Parametric statistics, 参数统计5 S t4 h E# R- W7 q
Parametric test, 参数检验6 j! n3 I# Y% `9 N# {4 p: O" Y
Partial correlation, 偏相关
; L! F3 C! g6 Z" NPartial regression, 偏回归
' w3 _$ ?9 e1 z8 {1 W: N2 {Partial sorting, 偏排序
, ]( h0 s$ Y- YPartials residuals, 偏残差
" E+ r- z8 q0 D% ~Pattern, 模式8 b7 c: c9 l+ }9 t7 B; \- b U
Pearson curves, 皮尔逊曲线7 x* H9 }& H# l2 I8 U; x
Peeling, 退层* T D6 z1 e8 T5 I! H. ?9 `' ]
Percent bar graph, 百分条形图( T9 S, p0 G9 z# l( P+ y
Percentage, 百分比
6 W) Z7 C* K# Y! d9 b/ s4 {Percentile, 百分位数6 Y, V( C5 C- }6 G4 ?: W' A
Percentile curves, 百分位曲线
I0 R2 Q; b$ ~' v3 i' k: Z% s' ?) }Periodicity, 周期性. L' d8 l$ y4 C o; C
Permutation, 排列
( `& l8 s- D J, W7 y SP-estimator, P估计量+ L. D' C; I: M9 i' d) ]0 a
Pie graph, 饼图' U3 P# E9 k- M( }$ Z# z1 c! W
Pitman estimator, 皮特曼估计量
. H/ Q4 A) F+ h F1 B R$ x1 FPivot, 枢轴量
" _/ S8 Y) H* k- F7 g/ VPlanar, 平坦( q: t% C- \% r; e- s
Planar assumption, 平面的假设% O$ e1 Y, }/ d' F! }' v# h
PLANCARDS, 生成试验的计划卡
4 L( m( j; K, K" d, HPoint estimation, 点估计" L* a" E- e: k# ^% E1 P# p( G
Poisson distribution, 泊松分布. v2 c( b+ f+ [2 x6 F( a
Polishing, 平滑9 ?& L# @- I6 c0 ]5 |% A( X" v
Polled standard deviation, 合并标准差$ O D z+ e0 ]7 F: Z
Polled variance, 合并方差: Y" F2 S- d- P$ m
Polygon, 多边图
* x% K$ D) x% t6 v' KPolynomial, 多项式
7 c) k: F6 H. f5 P. K% O7 GPolynomial curve, 多项式曲线
. ?6 e$ o5 ?& v# K# ]' iPopulation, 总体
8 m# N' p( X' S- sPopulation attributable risk, 人群归因危险度
1 B Q4 i7 h5 F; M# v5 EPositive correlation, 正相关. i/ w: h" s @) C
Positively skewed, 正偏
7 U& `/ ?$ D& ~ RPosterior distribution, 后验分布
) ?0 r y1 P3 R2 c! b" sPower of a test, 检验效能( x/ {; Q- g& U4 V
Precision, 精密度, }5 g; O: j+ D* r
Predicted value, 预测值8 b0 @6 h) i; w" ]( l4 X- j/ R
Preliminary analysis, 预备性分析7 ?; O7 l5 H' f2 ]5 P! G! v
Principal component analysis, 主成分分析+ o( M& [- V) A# `
Prior distribution, 先验分布
/ C! S$ i( t" \& }0 O/ SPrior probability, 先验概率5 b9 @7 f/ [3 x$ a
Probabilistic model, 概率模型/ O" [7 H1 Q' Q9 |1 v" l# F
probability, 概率. J) G, x5 O6 K* H
Probability density, 概率密度
8 o( D, j' @6 [3 q& S# b# PProduct moment, 乘积矩/协方差
7 u* m2 V0 ^2 _8 I' \: _, {8 {0 bProfile trace, 截面迹图* _/ }+ D# s8 E3 U
Proportion, 比/构成比% a' M$ ^* Z6 R: M7 p% i
Proportion allocation in stratified random sampling, 按比例分层随机抽样; D) }* {, I8 w
Proportionate, 成比例
$ d& l1 T( {0 Z: {+ CProportionate sub-class numbers, 成比例次级组含量+ A' @! V% }8 O2 v% `
Prospective study, 前瞻性调查
/ Z5 D) A& S+ b! H1 y" {$ ~6 a( _Proximities, 亲近性 5 [* u, |. f- _! A1 a
Pseudo F test, 近似F检验
( r" ^. p9 N% H/ NPseudo model, 近似模型
/ n0 ? q j. e) |% E# @Pseudosigma, 伪标准差
, v$ m; Y/ s1 N% E8 u! ZPurposive sampling, 有目的抽样
* R+ u) |4 x# F, VQR decomposition, QR分解$ E8 I7 d: |, ?: u6 F
Quadratic approximation, 二次近似
: ?- T" V% Y2 [& rQualitative classification, 属性分类7 E' I9 i& h5 M- ~2 i
Qualitative method, 定性方法
: B, _$ W/ z3 t( M& oQuantile-quantile plot, 分位数-分位数图/Q-Q图. F8 e* ]' }6 T |1 a. ~6 g
Quantitative analysis, 定量分析 w( M2 Z( l) E: v
Quartile, 四分位数6 T2 u: f1 e% q5 A. @4 P
Quick Cluster, 快速聚类
1 [* C# @: t1 U. i5 URadix sort, 基数排序
1 d# `; r6 h5 E7 FRandom allocation, 随机化分组
' y/ a# |1 l; g) ~. j* gRandom blocks design, 随机区组设计; l _! n7 h& Y$ X
Random event, 随机事件
) m" B* C0 Z, v3 W* O6 J8 |Randomization, 随机化5 Z- C0 w; _/ i c% J
Range, 极差/全距3 J; }' f, ^7 |% Q/ i
Rank correlation, 等级相关
2 e, R7 v( V; iRank sum test, 秩和检验
6 h( p4 a) Z0 @) ^8 i% BRank test, 秩检验
4 f5 t* y7 m0 H E' V2 BRanked data, 等级资料
' a9 C4 i" p. FRate, 比率
% b& F% M; l3 Y% F' Q4 I+ Q6 |( @Ratio, 比例0 V" T) y+ [' ?4 v1 m! K2 V! N% g
Raw data, 原始资料
( _0 u9 H9 E3 {1 IRaw residual, 原始残差
2 b% N4 }' @8 \8 a3 D1 b- F7 A) RRayleigh's test, 雷氏检验( J' u8 ~/ V4 y$ f8 W
Rayleigh's Z, 雷氏Z值 1 ?9 `! b) O7 K, p+ i
Reciprocal, 倒数% j4 e- e# O1 f9 Z& |
Reciprocal transformation, 倒数变换
( f: j' R; G* L) @$ T. [4 MRecording, 记录- P( r8 M1 G/ ~; x5 H! F( F, g
Redescending estimators, 回降估计量
6 v$ K/ X: l' k# W0 g8 HReducing dimensions, 降维0 A. W1 F- m3 U
Re-expression, 重新表达' a1 {. [: F+ w( B. X% K
Reference set, 标准组$ w. L6 L3 P$ I7 ~7 q
Region of acceptance, 接受域- U! h5 R s' a' O: B
Regression coefficient, 回归系数
V4 D- e. y& `. d1 dRegression sum of square, 回归平方和
# ~; r3 R2 r# z3 B+ }# HRejection point, 拒绝点+ W8 b* t8 F0 U
Relative dispersion, 相对离散度
. `( _, N+ A/ N: I) @9 ^Relative number, 相对数7 O0 l/ f1 Q+ K# r
Reliability, 可靠性
9 I% k G: ]' _9 n6 SReparametrization, 重新设置参数! l% M( r- P- l+ K3 V+ k6 H' `8 m
Replication, 重复8 p- |8 a$ P- d' _6 N) f; s
Report Summaries, 报告摘要
6 I6 l1 C7 H l+ T3 l! A. K6 O& VResidual sum of square, 剩余平方和
; e+ r5 `4 x$ Y9 rResistance, 耐抗性( ?1 u$ _( Z9 O* O0 W# q
Resistant line, 耐抗线7 z4 D7 J" j Q
Resistant technique, 耐抗技术
: u: y; _* I0 @( t" G) h; oR-estimator of location, 位置R估计量6 l# Y' ?4 d) u# }- ~- U m
R-estimator of scale, 尺度R估计量
( ~5 {9 m8 g0 F* n8 D% D) T* cRetrospective study, 回顾性调查
7 ]1 W" I' k' e' D) O, `Ridge trace, 岭迹
$ P' R+ P- P- {" d4 `Ridit analysis, Ridit分析
& e/ |9 B. I GRotation, 旋转0 u* Q0 U5 Z5 }
Rounding, 舍入/ l. Q/ |; x5 i2 q/ R
Row, 行
/ { d0 G8 ~4 t- S$ N, s# S0 uRow effects, 行效应
2 R2 T! q: t8 G; ]Row factor, 行因素
. Q' H$ L- @( f: N% aRXC table, RXC表6 i q- a5 h- Z( X, y- x. B; h
Sample, 样本+ `; {1 f7 @. L
Sample regression coefficient, 样本回归系数
% Y" O" l+ N2 C2 c8 G9 gSample size, 样本量
) m1 p* B& x4 D F* z: j$ N1 ySample standard deviation, 样本标准差4 w6 c& y1 Y X( a# K7 z7 J
Sampling error, 抽样误差# X/ k* J1 X" ?: T6 J) f5 D5 f) Q, Z
SAS(Statistical analysis system ), SAS统计软件包
9 G `2 I2 K) ?; x( a, b' |Scale, 尺度/量表& ?8 a5 \ h1 e3 x# e! P) ~0 t! F
Scatter diagram, 散点图
& Q% f/ o6 s) u4 z* E. k' a8 U, Y2 xSchematic plot, 示意图/简图7 _# ]& y z1 S3 I: A* }7 T
Score test, 计分检验
) }, m) e/ I. v: o" vScreening, 筛检
( S+ k4 U, R1 F0 l, [9 b! }1 |/ JSEASON, 季节分析
2 L& K M7 [5 w4 B- D* a( TSecond derivative, 二阶导数
/ A/ f# R1 m% r0 @7 Q5 s6 ~Second principal component, 第二主成分4 y6 @9 X5 |% n% F% T; T
SEM (Structural equation modeling), 结构化方程模型 / x: l: I1 D {0 H
Semi-logarithmic graph, 半对数图2 N5 s' L' i: B, Q S- d
Semi-logarithmic paper, 半对数格纸
+ z( X) S2 m9 Q9 c; B2 ~Sensitivity curve, 敏感度曲线& d9 R* L$ F" @1 i
Sequential analysis, 贯序分析7 Y% F9 f0 _4 v9 t+ N0 ~
Sequential data set, 顺序数据集. j5 c' ^3 s9 f# H4 e6 p2 C4 ^
Sequential design, 贯序设计
+ x# C& h8 h r0 s% g% X1 ]2 SSequential method, 贯序法; W) ]% L* u7 n8 N7 e# c$ O; U7 u) }
Sequential test, 贯序检验法3 `5 b/ ^; c8 l* n
Serial tests, 系列试验1 |/ i" I! a% g
Short-cut method, 简捷法
. { Y6 |, {9 i' C1 }Sigmoid curve, S形曲线
: i& l$ Q X' ] [6 j8 _Sign function, 正负号函数
8 v$ Y8 K) h0 J6 w2 f( l6 G) wSign test, 符号检验1 Y3 B2 _/ a4 x4 ?7 ^6 Q$ O/ f
Signed rank, 符号秩& H {6 e7 b7 B
Significance test, 显著性检验/ f8 y+ x2 }: I& C; |$ Z. @
Significant figure, 有效数字1 ~3 t6 r9 R! Z/ j
Simple cluster sampling, 简单整群抽样# F' v. I5 [" \* i5 L
Simple correlation, 简单相关
$ e3 R2 n" a. L2 A/ y/ T, CSimple random sampling, 简单随机抽样6 X5 \" Q0 `' g/ s2 w
Simple regression, 简单回归
; {1 W! R! k# b5 B2 Z3 y. csimple table, 简单表0 f5 x8 ^+ G: w* H. B( ^- A
Sine estimator, 正弦估计量
. ], K2 m' ^ v2 I( \- XSingle-valued estimate, 单值估计5 R0 y: P' w0 i; a Q8 f
Singular matrix, 奇异矩阵5 ^" M) P' T( x' [& ?. l' {
Skewed distribution, 偏斜分布
$ {( x/ F4 h3 _8 a4 O+ k7 TSkewness, 偏度: v* c; o: {$ Z% J) D. n
Slash distribution, 斜线分布" T( O# S/ r" p2 B5 e8 |
Slope, 斜率
1 a4 h, |& c1 ^7 W+ r5 i8 sSmirnov test, 斯米尔诺夫检验
, m: \1 u; s/ A2 j* VSource of variation, 变异来源
9 j9 @. U" `1 M* fSpearman rank correlation, 斯皮尔曼等级相关
- }! Q* Q% k8 C. RSpecific factor, 特殊因子
* D7 o4 _1 t* a& @3 USpecific factor variance, 特殊因子方差
& R, ~4 s9 V2 T9 lSpectra , 频谱
) _" ~8 ?& f, i! _) F1 e4 ASpherical distribution, 球型正态分布
4 s2 [0 c, V# y b2 @# @/ QSpread, 展布& A! n o/ I0 R, L5 L6 F
SPSS(Statistical package for the social science), SPSS统计软件包
$ b* W9 Z* h% `# I. _Spurious correlation, 假性相关
d5 ^8 _6 A* Q1 d) L# u" @Square root transformation, 平方根变换
0 ^# x" \; k uStabilizing variance, 稳定方差
8 A/ F2 V: E7 @. `! d/ B5 AStandard deviation, 标准差
/ o; J9 J v9 PStandard error, 标准误9 J% |+ Y. ^* @+ W) p2 i. H( S
Standard error of difference, 差别的标准误2 }1 V2 u( S5 n2 J7 \
Standard error of estimate, 标准估计误差& f6 J& E$ l' y9 i: c* y1 v S
Standard error of rate, 率的标准误
' k ]" ?, U' Q: I pStandard normal distribution, 标准正态分布
8 A: e. D: `9 t+ y8 }7 c* dStandardization, 标准化# r6 B# s- y: I: v
Starting value, 起始值
; h$ y/ x* [# J/ w6 R) iStatistic, 统计量
+ J/ j8 s9 ^ y/ I: lStatistical control, 统计控制
3 N! J1 b9 }" }2 S/ v$ s7 xStatistical graph, 统计图) o# A' _8 b* L; K! _5 B
Statistical inference, 统计推断) c7 G' K, o4 q3 D
Statistical table, 统计表9 L8 q5 Y+ B8 _. g! `
Steepest descent, 最速下降法
. R8 Y" C- `4 g9 \* BStem and leaf display, 茎叶图
9 g8 @, P U% k% {% `9 _9 rStep factor, 步长因子! ~' W2 l! o8 U& I
Stepwise regression, 逐步回归
" s* ^2 t# p# U0 X6 z9 x9 R4 x: ~$ T) BStorage, 存; j2 r! p; j0 K) L
Strata, 层（复数）% D/ p0 X: h/ r- w8 o4 Z
Stratified sampling, 分层抽样
- q, W$ z" c) ~Stratified sampling, 分层抽样8 W3 e9 r0 O W1 u, n. n
Strength, 强度
2 S- S M6 Q8 Q1 G; } V: bStringency, 严密性
) `- o" @5 Q; ?/ P; tStructural relationship, 结构关系9 x6 B6 P: w# @; X) {
Studentized residual, 学生化残差/t化残差
, H& v5 t8 v8 _# d* W% X+ }5 YSub-class numbers, 次级组含量, T. X1 y- r0 a! s3 K7 S
Subdividing, 分割
# { ^" K I) E# e0 i$ eSufficient statistic, 充分统计量
1 T7 h" z7 o4 g, bSum of products, 积和
2 S4 G' U$ S. u9 |( X1 _Sum of squares, 离差平方和
6 p8 k1 G8 j" Q) PSum of squares about regression, 回归平方和
5 U2 i @" C" T: n/ TSum of squares between groups, 组间平方和
5 n% q1 K6 a+ rSum of squares of partial regression, 偏回归平方和& ?+ _" R/ [; }
Sure event, 必然事件
. y+ _. O& O3 QSurvey, 调查
4 F9 x) Z5 S* rSurvival, 生存分析
' t' j/ V9 Q! [& G7 {# dSurvival rate, 生存率
- A3 _9 K {( k' `Suspended root gram, 悬吊根图5 L8 T! T' V' ~' E% t8 }$ |
Symmetry, 对称
4 L5 R Z0 L. t$ NSystematic error, 系统误差; ?6 w! ]3 Y6 ^
Systematic sampling, 系统抽样
: G# k0 q9 g- p6 }4 i/ PTags, 标签/ S7 [- y& i+ ^' i0 n) `
Tail area, 尾部面积
# o! U% H$ j( s7 U8 V! jTail length, 尾长, R- G6 Y' w7 ?
Tail weight, 尾重: T6 _; z/ y0 C% C2 h! z% d c
Tangent line, 切线 |1 P1 T5 v/ Y3 E2 P( s2 E/ \
Target distribution, 目标分布
9 N l1 c2 l( o" v3 L" VTaylor series, 泰勒级数
. R4 t+ a1 l& `1 D$ ~- r3 hTendency of dispersion, 离散趋势8 y4 W- L2 {- M. Z, U! K
Testing of hypotheses, 假设检验
0 O3 Y" T3 z5 B) H2 W# n5 KTheoretical frequency, 理论频数" Q: `1 X* H U1 n! {( t
Time series, 时间序列
! y; D6 Y C: `+ {; G- U( lTolerance interval, 容忍区间
2 P1 u/ j* V- O8 STolerance lower limit, 容忍下限
% _) f5 }. t8 {# W5 D2 j0 K+ c) ITolerance upper limit, 容忍上限+ S6 @5 C) ~ h5 @- ~
Torsion, 扰率7 c+ R6 o/ O; I7 m& ~* r9 Z2 C
Total sum of square, 总平方和5 K2 K1 x3 k% j) |: `
Total variation, 总变异
5 l' j9 H3 N- ^6 O' TTransformation, 转换/ J6 z* G& s- o$ k4 Y* A
Treatment, 处理
" ?& t6 g7 N T* O7 L( l* mTrend, 趋势
6 H+ ^5 I; K( k. ZTrend of percentage, 百分比趋势
. z8 J: J3 Q8 A; D8 {0 k. nTrial, 试验# ~6 g! u3 _# ]& S# U7 D
Trial and error method, 试错法: [* C2 m8 w1 ~% s5 x
Tuning constant, 细调常数
{# b( {# }& TTwo sided test, 双向检验
Z8 [5 Y8 e4 ?' t0 D/ TTwo-stage least squares, 二阶最小平方
c8 U5 b* v: {; w1 W( L$ @Two-stage sampling, 二阶段抽样: E, P3 M3 o4 V% w
Two-tailed test, 双侧检验8 W4 |8 c) W0 G$ r7 ?6 t
Two-way analysis of variance, 双因素方差分析
- |( W0 Z$ o7 ?* w2 j( WTwo-way table, 双向表
: Y$ k: j7 R+ F6 _Type I error, 一类错误/α错误& @! t' N7 s8 x. \3 h4 G
Type II error, 二类错误/β错误
; c# B' c% Z7 f {( ~! R1 ]. u9 ^UMVU, 方差一致最小无偏估计简称7 g) c! a; s0 E! E- D+ J& n' B1 \
Unbiased estimate, 无偏估计- F% y% D" D% m7 e$ }% g" a, k
Unconstrained nonlinear regression , 无约束非线性回归
$ L; z: j' I( w+ BUnequal subclass number, 不等次级组含量6 |( B" r5 r- _! N( a) E
Ungrouped data, 不分组资料
0 E" i# S$ s+ i5 bUniform coordinate, 均匀坐标
4 P: b8 j6 p) z& I. ~+ J- h2 yUniform distribution, 均匀分布
) h, P! |; |2 q# H& p( M0 P+ NUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
0 L% \: n. y' Q6 Z: o& o( n! h$ PUnit, 单元
) c) Y6 { S3 U4 a2 j+ |" PUnordered categories, 无序分类
0 V5 P9 |8 \2 g( UUpper limit, 上限
3 n6 q; t( U% p: pUpward rank, 升秩9 ^ w# d6 {! u% V
Vague concept, 模糊概念
m1 V8 O% V+ O. CValidity, 有效性
- i9 Q1 y2 {# \8 L$ }. ?) f' IVARCOMP (Variance component estimation), 方差元素估计7 d8 k" T2 q* d4 G# [- R: h
Variability, 变异性$ t! z2 U% _; @# B
Variable, 变量& u2 p, N0 G. C3 v8 n X( ~2 J
Variance, 方差
: S1 E! N. @; C5 BVariation, 变异 ^4 a/ Z7 D& y/ @# I( s
Varimax orthogonal rotation, 方差最大正交旋转
- m9 @9 {* e$ p% cVolume of distribution, 容积
' T( R/ V& M, d8 vW test, W检验
5 |+ a( p& |7 wWeibull distribution, 威布尔分布
" `0 n6 J% E" Q0 nWeight, 权数
8 y. ~4 q% _* y! U0 n/ f! j @' CWeighted Chi-square test, 加权卡方检验/Cochran检验
! g* x, L. u. o8 m! i- |; bWeighted linear regression method, 加权直线回归- ^5 H8 a' f4 U( f1 m9 r3 k$ ~; ]
Weighted mean, 加权平均数, L2 h3 v& L$ _- b) P& X
Weighted mean square, 加权平均方差+ v0 `1 e6 [" i& @* ~
Weighted sum of square, 加权平方和& X* ^3 I5 x! y# K6 M
Weighting coefficient, 权重系数' R" V9 g2 F4 E1 N$ q* }% b1 e
Weighting method, 加权法
/ V. w3 y0 F \4 d5 d: N/ M- gW-estimation, W估计量* t* E6 H7 \, k3 w
W-estimation of location, 位置W估计量
. ]+ `+ {$ n, a7 n8 sWidth, 宽度
, h4 H1 z4 q" J/ i; t" JWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
" @7 V& f# \4 D# HWild point, 野点/狂点: J8 n& x& K7 a. u% u; W5 B) Z
Wild value, 野值/狂值. w0 K* g: n7 l' u( v+ V
Winsorized mean, 缩尾均值
& e9 ]; \6 t0 p+ YWithdraw, 失访
5 O1 ]4 m; D4 @ ]Youden's index, 尤登指数% H, U% R0 X6 `. X9 O
Z test, Z检验
; b! a9 a7 m1 q6 z6 j& t1 o1 m- {Zero correlation, 零相关- f# E, Z: G4 H4 Y$ M
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
