|
|
Absolute deviation, 绝对离差
* p! m% _# F4 L; ~1 zAbsolute number, 绝对数' r. z0 [; z' ?' _( S
Absolute residuals, 绝对残差/ r3 i% t! R3 e2 D
Acceleration array, 加速度立体阵
$ A2 A. y" r2 M' v7 M! mAcceleration in an arbitrary direction, 任意方向上的加速度
- x; i: O" ^9 k" U) a6 W( R+ EAcceleration normal, 法向加速度1 U3 W3 c! {3 B+ ?
Acceleration space dimension, 加速度空间的维数0 R8 \1 F5 u9 t3 @7 Y4 ~1 x/ O
Acceleration tangential, 切向加速度
5 ?* \7 T7 x; q" A- a/ W/ M6 L. VAcceleration vector, 加速度向量% b0 G7 A. {3 e0 m
Acceptable hypothesis, 可接受假设
3 t4 p# }5 g5 C; T- |Accumulation, 累积9 {6 p& l% }: T- p5 w2 h
Accuracy, 准确度
0 j7 @: R ?/ U0 h7 m# FActual frequency, 实际频数. R( i( f* W7 H6 @
Adaptive estimator, 自适应估计量8 H- w- d7 E$ W& b
Addition, 相加 D _/ O) |. |& n
Addition theorem, 加法定理7 m/ r& n& R/ s" M
Additivity, 可加性
$ { O: T7 t* A6 LAdjusted rate, 调整率5 g/ ?7 W! F2 u; K
Adjusted value, 校正值
9 T* P( M4 B! O* a- f4 b/ eAdmissible error, 容许误差! v# [2 F$ k8 b% L# F3 p
Aggregation, 聚集性
9 v' w% t) A1 @7 l4 ?$ lAlternative hypothesis, 备择假设9 o2 `/ ?& _% h1 Y. Q- m; J: v
Among groups, 组间. r0 q$ h, H, ^) V: f' u
Amounts, 总量
* A3 d8 S: [" fAnalysis of correlation, 相关分析
( S8 X; h0 W u _% K% `* tAnalysis of covariance, 协方差分析
! M7 f+ k9 g" T- `% vAnalysis of regression, 回归分析
2 j! r Z% f8 Q3 cAnalysis of time series, 时间序列分析
$ s% ?) l$ v1 ?" [; }Analysis of variance, 方差分析" u; x# J5 D$ X6 a2 G" t
Angular transformation, 角转换3 _' W+ I& g8 Q, j4 D9 I7 d
ANOVA （analysis of variance）, 方差分析
2 `+ u. U4 {/ BANOVA Models, 方差分析模型, D; ?8 o4 t$ e7 q4 Y
Arcing, 弧/弧旋
3 _, k( ^% O: G2 pArcsine transformation, 反正弦变换( G# A0 }, G$ z+ K; H
Area under the curve, 曲线面积
4 q1 T* a5 V* T) Z$ r V' AAREG , 评估从一个时间点到下一个时间点回归相关时的误差 * t8 |* n5 Q. V+ D0 c8 {$ B
ARIMA, 季节和非季节性单变量模型的极大似然估计
$ m- x$ n8 j4 z+ R% M0 n5 ?; W- yArithmetic grid paper, 算术格纸
( p" |/ |/ [. J8 d8 P& `Arithmetic mean, 算术平均数/ b" y/ R# F3 D8 R+ p6 e
Arrhenius relation, 艾恩尼斯关系
, f8 U( K4 a% }Assessing fit, 拟合的评估* Y1 |$ q+ K& W2 K9 a }
Associative laws, 结合律
/ t# N$ w; J+ w5 d4 _( R( cAsymmetric distribution, 非对称分布
7 W- ?! z* s% E5 |+ X3 d% yAsymptotic bias, 渐近偏倚; g1 F1 M" |+ E
Asymptotic efficiency, 渐近效率; W$ W1 L d/ O8 p, j) A7 p# }7 M8 i, Q
Asymptotic variance, 渐近方差
. n; P% y) p0 ^Attributable risk, 归因危险度. L% A4 S& W5 h% \1 t
Attribute data, 属性资料
& L( g j- T3 j- @- LAttribution, 属性
I$ \* s/ R0 [$ b& _7 |. u, C7 KAutocorrelation, 自相关
; \2 V `' X/ {# h/ L9 [8 v8 RAutocorrelation of residuals, 残差的自相关4 f- t# C2 C7 w5 ?7 ~$ y
Average, 平均数4 ?# L, W4 i! [8 y' @
Average confidence interval length, 平均置信区间长度
* \* C% N) F: f; JAverage growth rate, 平均增长率, _2 F b! C4 U( X* G4 G8 O/ h/ i
Bar chart, 条形图
- r1 G7 _' Y, E7 R5 YBar graph, 条形图
. q5 Z1 K9 o% G" [9 b/ XBase period, 基期. K# [2 O r# x+ a8 M/ g
Bayes' theorem , Bayes定理
5 R, i# k3 q* S3 jBell-shaped curve, 钟形曲线+ n. t0 U7 m, d+ x! [8 T1 G
Bernoulli distribution, 伯努力分布
1 l- {- Y+ A9 g/ wBest-trim estimator, 最好切尾估计量% f8 M! C/ P8 C: P- q; p
Bias, 偏性7 v& t& Y i+ c$ g
Binary logistic regression, 二元逻辑斯蒂回归) t2 D/ Y1 o" K& j' U! y# _2 {4 F
Binomial distribution, 二项分布0 K+ @" J( d9 ?$ N4 g4 C& k c+ E
Bisquare, 双平方5 A( R7 W9 T5 o) X
Bivariate Correlate, 二变量相关; C# v& s6 Y3 P/ a1 y
Bivariate normal distribution, 双变量正态分布( {3 U7 x0 `% U
Bivariate normal population, 双变量正态总体% j( D2 |! F2 K. S7 E* V
Biweight interval, 双权区间/ C ~' W* p" D+ S# A$ i1 `
Biweight M-estimator, 双权M估计量
1 D2 N* j6 E+ F! D/ Y; ]3 hBlock, 区组/配伍组
5 s; ~" K" v/ C" {( Q* ]0 dBMDP(Biomedical computer programs), BMDP统计软件包
; E5 i& x% ?. O! {Boxplots, 箱线图/箱尾图/ D( \6 O0 N$ D. T; r
Breakdown bound, 崩溃界/崩溃点1 [ o/ O# d+ N7 ^+ h
Canonical correlation, 典型相关' W% A' v# s$ D9 z3 R/ r
Caption, 纵标目
# y3 G2 e$ D. U6 O% }Case-control study, 病例对照研究, u" T* U1 F2 w( m# T' `" x5 d
Categorical variable, 分类变量; B# U1 S9 L* p" n
Catenary, 悬链线
- C: j4 D0 Z, n* n" J2 W/ VCauchy distribution, 柯西分布2 s; r4 k1 Z8 m7 G, M; X* H
Cause-and-effect relationship, 因果关系 E6 I N5 k' g' x! }0 [
Cell, 单元, p- E5 e1 j& }( x" J* q5 V! q0 o. e, O
Censoring, 终检( b0 x1 R: ?1 F1 F0 @& ]5 P, ?
Center of symmetry, 对称中心$ G# q3 P: l% o3 O+ m0 O/ G4 @
Centering and scaling, 中心化和定标/ j4 ~3 `; X% j5 D2 G n" Q
Central tendency, 集中趋势+ f5 E+ X1 e. G* R) |
Central value, 中心值3 n p/ u, b y
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测0 h) T6 a' g" K0 o& M9 \" r
Chance, 机遇* c7 e0 ?; _9 K
Chance error, 随机误差
+ Z$ ]2 ^+ c& f! t+ r aChance variable, 随机变量) r6 H1 ^2 v% p9 i, t& C; [, h+ [
Characteristic equation, 特征方程
2 N0 b+ \5 A$ @+ m& x2 f% R2 l# B$ ?Characteristic root, 特征根
9 Q; q3 y" E- B( Y6 vCharacteristic vector, 特征向量5 ]+ w( I, ?$ r! [
Chebshev criterion of fit, 拟合的切比雪夫准则
0 Z1 D9 J o' w) n$ m9 g3 u" y$ ]Chernoff faces, 切尔诺夫脸谱图 i3 M1 Z6 W, `1 t) e, L
Chi-square test, 卡方检验/χ2检验# u# ]( b# m9 z% S7 @9 X7 F9 }
Choleskey decomposition, 乔洛斯基分解
% l3 ~( u1 @9 [' o& |3 dCircle chart, 圆图 ) L5 [- U/ t8 o% U0 I
Class interval, 组距
; N4 i* a2 X* V2 EClass mid-value, 组中值. E# c% g& W3 k- E0 ~$ n
Class upper limit, 组上限
M: e5 W2 P% J; JClassified variable, 分类变量, b, k( ~) U& A& b# G' f/ C
Cluster analysis, 聚类分析( B+ m0 ^& N5 D; v
Cluster sampling, 整群抽样0 E& v2 w9 U) c' H" I& B8 r% W
Code, 代码
, H) \0 C, O" V! d7 W' MCoded data, 编码数据* ^: n+ r' u2 j; z" @* d4 r
Coding, 编码
# d2 f# k: G: o# ]6 kCoefficient of contingency, 列联系数
, h4 k% S" E' O4 WCoefficient of determination, 决定系数
. V! ?2 O: A% g! RCoefficient of multiple correlation, 多重相关系数* k2 P8 D$ ^ g0 ]% B
Coefficient of partial correlation, 偏相关系数
) m v! F, P- G0 I6 {) K" jCoefficient of production-moment correlation, 积差相关系数
" x: H2 o8 X' b6 E2 NCoefficient of rank correlation, 等级相关系数
/ }: T* [. g- N; n& m9 dCoefficient of regression, 回归系数0 e, q0 A2 A! H5 c1 Y8 h2 _
Coefficient of skewness, 偏度系数
. r) h2 t- ]; w7 W6 @Coefficient of variation, 变异系数
! W7 e1 z, c6 eCohort study, 队列研究# n9 o1 T7 b8 Y8 t1 B
Column, 列5 D9 f. g4 P1 }+ J/ A
Column effect, 列效应9 V6 }+ I( P: ?/ G6 Q9 m
Column factor, 列因素
% y) B$ A$ A, x- B! NCombination pool, 合并$ N. e, u0 U: [+ X$ g$ V
Combinative table, 组合表6 k' L0 j$ m& t' A
Common factor, 共性因子
1 B3 c) Q5 c S9 a9 Q0 K" E2 @Common regression coefficient, 公共回归系数; \7 ~9 f6 R. [" P; W
Common value, 共同值' o+ g4 T+ _, U' Y5 h
Common variance, 公共方差5 y( |$ Y- G3 U; C( i
Common variation, 公共变异4 y1 \0 A3 d: r7 e0 W- D2 d
Communality variance, 共性方差
" o6 v- |3 P: ~: q$ P3 {Comparability, 可比性5 {+ d( p+ b; \
Comparison of bathes, 批比较% O8 b& q9 n/ g& y: `% _
Comparison value, 比较值% c9 T$ O" c! g0 w' J$ x! a
Compartment model, 分部模型
0 p, b' C; W6 i0 Y2 dCompassion, 伸缩
- \, i' ]7 v5 I) N. J5 uComplement of an event, 补事件
- b% u" Y9 Z, g' a( @) h6 RComplete association, 完全正相关" z9 {6 ] b! a+ F6 T/ v* |
Complete dissociation, 完全不相关
2 y H |2 n1 _7 x0 eComplete statistics, 完备统计量
8 M/ c. z& `4 M" e+ t8 zCompletely randomized design, 完全随机化设计
' b4 j! U: k1 P* y: k7 e3 g* M% mComposite event, 联合事件
- x: s/ V" I5 s+ ~ A. CComposite events, 复合事件# r* ~+ K& K" _) w- p
Concavity, 凹性
& ]+ u& |$ J) l3 \7 H2 ~! {3 JConditional expectation, 条件期望
4 v# _" R6 {7 R( Z; B0 hConditional likelihood, 条件似然
# k6 J, {* G4 t. N( |9 a1 jConditional probability, 条件概率6 N8 {8 l. K0 y8 O( g. i
Conditionally linear, 依条件线性
3 ^. B' T2 B, R/ Q& y( GConfidence interval, 置信区间
1 ~7 ]5 O V# YConfidence limit, 置信限9 ~* g* w2 }8 X/ P- B; x; [
Confidence lower limit, 置信下限
0 ?( n. w( u3 W: g& RConfidence upper limit, 置信上限: s3 E+ ]3 O: n, d, I7 _. Q
Confirmatory Factor Analysis , 验证性因子分析7 B6 F- L1 x2 i- d& j; V$ [
Confirmatory research, 证实性实验研究0 H4 X+ }3 g! s2 C+ y
Confounding factor, 混杂因素, Q" x& G: A6 H. u/ a9 h2 V
Conjoint, 联合分析. D& @4 X/ N% a, N
Consistency, 相合性 k! g8 a% S$ Z$ _* L
Consistency check, 一致性检验 m7 B, l( X0 [* j9 z
Consistent asymptotically normal estimate, 相合渐近正态估计
9 q* v6 N; M0 i/ F8 k/ _# V n' tConsistent estimate, 相合估计
# s9 R0 v7 b& N PConstrained nonlinear regression, 受约束非线性回归# D- \, O0 d$ ~1 X$ x4 V6 j+ R* l
Constraint, 约束
; t( ?) R6 Y# z/ w: ]Contaminated distribution, 污染分布
/ F2 {0 f/ |1 M* p; q; LContaminated Gausssian, 污染高斯分布( }, v5 `: M9 v0 e9 g
Contaminated normal distribution, 污染正态分布
& N$ ^# T7 L( U3 p# WContamination, 污染
* x. k/ V3 B( d1 S, B7 sContamination model, 污染模型
2 i% x, V E+ f' F0 H! D g5 wContingency table, 列联表
" y; X$ }( L1 P' ^5 A+ M H4 kContour, 边界线" `$ c$ T0 i. s, M, z* e
Contribution rate, 贡献率+ p3 V* ~- |) d# U2 w
Control, 对照
! a' V, d% ?9 d8 E* b5 pControlled experiments, 对照实验
2 n2 s U! [/ K+ N- R9 yConventional depth, 常规深度* t" g/ |3 ]3 z8 p5 g( U! Q' z" v
Convolution, 卷积
6 x0 @9 Y* @5 J w! F% c2 fCorrected factor, 校正因子
1 i4 g! a( Y6 v/ I J0 kCorrected mean, 校正均值
5 U/ V# H8 d S- ?9 ^3 L$ f5 PCorrection coefficient, 校正系数. e! Q6 p- \0 Y8 I0 Z
Correctness, 正确性) g6 | u0 n3 e4 d( f6 K
Correlation coefficient, 相关系数
! Z6 C) a5 y$ l; b \9 L) \- @Correlation index, 相关指数
, c3 T' g0 c, V6 {Correspondence, 对应
7 N8 x( C# a8 RCounting, 计数5 c1 E1 B/ i0 m7 g0 U2 V
Counts, 计数/频数
# ` G5 l3 d( G, R/ lCovariance, 协方差
& J9 c; `/ x; s+ X8 ^+ b! E. pCovariant, 共变
' i1 }; N4 b% T7 C2 aCox Regression, Cox回归
) T1 k/ v2 ?8 p( P: O. |: P" [! s" NCriteria for fitting, 拟合准则# @, F" S& M3 S0 U; H! C
Criteria of least squares, 最小二乘准则9 l% M2 C9 A, b
Critical ratio, 临界比
5 X9 L% u: I# b2 x+ Q% q/ lCritical region, 拒绝域4 |& d/ r- Q5 C% }8 B
Critical value, 临界值& J3 X1 d5 T S7 l$ w9 H
Cross-over design, 交叉设计
% G/ D0 p8 K! }3 L$ u1 Q& KCross-section analysis, 横断面分析
& r) c& X- k& \, I" R E: o% BCross-section survey, 横断面调查! A* G( l8 N9 K: j4 H: M
Crosstabs , 交叉表 6 M2 E6 V$ W) m$ t' H' L
Cross-tabulation table, 复合表
3 N3 k, o- K$ V0 O5 z0 @8 w" xCube root, 立方根: C" \/ Z( i2 t! e- x
Cumulative distribution function, 分布函数0 n |( P# Z: {& U p! w/ R
Cumulative probability, 累计概率1 d: o3 _1 V0 r9 j, k9 F
Curvature, 曲率/弯曲: e# X3 t2 z+ P! k' h' |
Curvature, 曲率
* t; R& V8 D ~' i0 G( |: rCurve fit , 曲线拟和
; g0 G6 r' \; z9 WCurve fitting, 曲线拟合/ B* j. o. u2 [' ?1 n
Curvilinear regression, 曲线回归
( f. f9 ~0 m0 xCurvilinear relation, 曲线关系 P' b$ q; b$ p! L7 c) F0 r
Cut-and-try method, 尝试法
* w% E5 n& i b& vCycle, 周期
2 d. e6 {/ E2 P! s9 G' \' C) LCyclist, 周期性$ L- u4 l& |' R |7 w1 W. G
D test, D检验
; {* I7 J" C" q$ ^# O5 t1 CData acquisition, 资料收集7 H5 v* A5 T) t, G( s+ G& {3 R
Data bank, 数据库
* }8 c8 W; c/ u+ tData capacity, 数据容量
& o( R; @" V. H* H4 vData deficiencies, 数据缺乏/ O2 X: ?5 s6 j+ I
Data handling, 数据处理
/ ~' u4 V/ f# u% V7 iData manipulation, 数据处理
* H+ y" Q! k! O4 q( B! F8 R6 P1 p( rData processing, 数据处理( v$ s, Y2 j% v0 `! z8 `+ q& p
Data reduction, 数据缩减
# Y- P# h/ |, q; z8 l- l* CData set, 数据集& T4 F: O" X8 e& Q% i% w
Data sources, 数据来源
6 f* I) A- u# d. l/ v& q0 lData transformation, 数据变换4 T% I+ y4 m" B( T
Data validity, 数据有效性
' x5 p, d$ w' FData-in, 数据输入
0 g Z1 @* ?) I( Q' dData-out, 数据输出& i! z* G* |. w8 }0 e
Dead time, 停滞期6 d# ~3 G# q5 [+ i% [+ _ v2 q
Degree of freedom, 自由度" M' Z( i4 q) N/ ~4 a) `, @
Degree of precision, 精密度
* U+ V A6 y% C( ^# ~: G( w& t7 mDegree of reliability, 可靠性程度1 g6 o* ?+ O& E& k. i
Degression, 递减
. s& p2 ^3 p3 f+ oDensity function, 密度函数
# f+ N1 n+ `: O$ c# U4 eDensity of data points, 数据点的密度
1 f2 h1 V0 D& z/ B o4 @Dependent variable, 应变量/依变量/因变量" ]( N+ ^, U2 f' F2 F: X
Dependent variable, 因变量
( c6 F9 w. P% t7 |0 i* e( c" ]4 uDepth, 深度$ U0 V2 r' y! s2 b# @
Derivative matrix, 导数矩阵; I& O# L% E2 n5 i
Derivative-free methods, 无导数方法8 @! T9 b0 |$ i; x3 v
Design, 设计
4 @! p8 f9 B+ `- b6 c, YDeterminacy, 确定性/ U3 l- P+ P7 |- M2 E' R7 m( t+ O( X3 ?! K
Determinant, 行列式
4 _* q0 y( J% U" ]3 XDeterminant, 决定因素/ j$ h" y4 H$ s7 \- `3 Z
Deviation, 离差
( y0 `( p& e: u+ iDeviation from average, 离均差
8 B9 S4 U7 q$ yDiagnostic plot, 诊断图( Q7 {: h9 W- Z6 R' K
Dichotomous variable, 二分变量
3 x9 H$ s1 ]8 l% LDifferential equation, 微分方程
4 d/ d8 y1 N" }% T* _/ kDirect standardization, 直接标准化法
6 u' f. m3 l3 ? A3 z0 j! G" k9 KDiscrete variable, 离散型变量
* e- F/ b8 v4 w3 ^( Z; dDISCRIMINANT, 判断
# @/ w% J$ Z5 P4 ]" x) aDiscriminant analysis, 判别分析3 e% h( B" ?. }3 E' `* e8 t" K
Discriminant coefficient, 判别系数& P8 A! d$ @! a3 X/ i& a( V7 }
Discriminant function, 判别值9 D! \8 ?& U4 k6 ] l. |
Dispersion, 散布/分散度( i, T7 z3 j1 r; Y( Z( T
Disproportional, 不成比例的4 S6 M+ V2 \+ T) B
Disproportionate sub-class numbers, 不成比例次级组含量9 G4 B2 O/ S. c" Y
Distribution free, 分布无关性/免分布& x- v5 K# f Y9 y
Distribution shape, 分布形状4 p! e& u# S3 u' Z' {# Q; q
Distribution-free method, 任意分布法
/ x# j8 D4 C7 l6 X; BDistributive laws, 分配律5 I7 N$ [/ m+ o) R) u% _
Disturbance, 随机扰动项( w/ I1 k2 H5 C# M6 l. b( R
Dose response curve, 剂量反应曲线% z( B2 _1 {6 C& f. q Z, c) }
Double blind method, 双盲法
" s5 ~! `7 \+ C) [4 JDouble blind trial, 双盲试验
" ?& w, n& K& K* G$ KDouble exponential distribution, 双指数分布: r/ a! i& f/ ?8 c
Double logarithmic, 双对数' G H6 r, h+ f
Downward rank, 降秩
/ J/ w# o4 s( N$ `Dual-space plot, 对偶空间图
4 ?" l7 J8 R }" ^3 W: f K* v8 w, lDUD, 无导数方法# R7 p2 ?7 B+ C# W- M" X4 T
Duncan's new multiple range method, 新复极差法/Duncan新法
. b9 h) }5 T3 n5 @, TEffect, 实验效应
6 N& P( d4 e- l; g! p& oEigenvalue, 特征值
* j+ {/ `- [/ V& pEigenvector, 特征向量' V/ s% F/ G5 g, M% k P
Ellipse, 椭圆& x$ V$ `' z4 @' o* } K6 D, F' v
Empirical distribution, 经验分布
8 z& ]: A! N3 s( x0 B6 eEmpirical probability, 经验概率单位7 c1 s6 c ^2 ]5 ^0 a
Enumeration data, 计数资料8 f* U$ t4 h% p' k
Equal sun-class number, 相等次级组含量
$ l# g/ ?$ {. k$ OEqually likely, 等可能
& w# ]! |! @, ?- a7 w! zEquivariance, 同变性! z. V0 r$ r: | E4 j; Q0 K
Error, 误差/错误
' B# |% f9 ^2 f; X7 {2 jError of estimate, 估计误差
7 o3 T. f/ T3 O! XError type I, 第一类错误
) K+ B* ]/ P% @. H4 i2 iError type II, 第二类错误5 ^, q5 {/ U3 E* r' v
Estimand, 被估量
6 l( D( Q; @+ ]8 A, ?+ KEstimated error mean squares, 估计误差均方
+ r9 `7 w6 E& @* wEstimated error sum of squares, 估计误差平方和
& h+ c% \0 o t* g, @6 gEuclidean distance, 欧式距离
5 }7 d2 L8 V" q) SEvent, 事件
1 q4 c8 y, q/ xEvent, 事件
2 p9 c9 W& E% o/ ^8 w: M) YExceptional data point, 异常数据点$ ?( m: W# P _( A3 @* P+ Z) ^. s
Expectation plane, 期望平面
$ d7 _6 h* r7 x! N2 P* ^8 AExpectation surface, 期望曲面! j( g/ l: {0 c# _3 s
Expected values, 期望值
( S' Y7 l6 p7 G. q; k8 p5 E6 ~Experiment, 实验2 q2 T5 o2 X/ B r- G8 D/ `5 h# o
Experimental sampling, 试验抽样
# @" b! r8 F2 k9 @% iExperimental unit, 试验单位
5 C% x+ c% s, ?! _Explanatory variable, 说明变量- s/ \. f0 `/ {" I5 }: x
Exploratory data analysis, 探索性数据分析
7 h; k5 g* p8 j: E) v8 w0 ?, UExplore Summarize, 探索-摘要- ]) G4 U; \' r" r$ ~, O, S; h$ b
Exponential curve, 指数曲线7 h V$ \/ m; n
Exponential growth, 指数式增长1 }5 b' L1 e7 N/ N. n# g
EXSMOOTH, 指数平滑方法
R* T6 I0 q: y( E! t1 r. ZExtended fit, 扩充拟合+ ?% ]4 w; b+ A6 i) t+ @: a
Extra parameter, 附加参数6 j' o6 g7 x& V# f. t
Extrapolation, 外推法
8 m% p; c( K6 c w3 aExtreme observation, 末端观测值; S' n& P: O0 w% v2 n+ t* ]
Extremes, 极端值/极值$ c9 L4 `& q5 n8 f
F distribution, F分布
; R: E4 T7 U" T( W$ m9 ]1 N3 `F test, F检验9 M8 ]) R3 D8 `# Y# t* J6 [& T
Factor, 因素/因子! t8 h, x& I8 I8 p' _
Factor analysis, 因子分析$ q5 g6 n7 W; F4 R: l' J! ^
Factor Analysis, 因子分析
5 G$ F U+ c/ r, ^+ {* g8 {, JFactor score, 因子得分
- P- C ~2 T8 h; x2 Q. qFactorial, 阶乘
4 N! b1 W- G" P% C5 Z2 N& ~Factorial design, 析因试验设计) G* X( L: K$ D4 Q, R0 v
False negative, 假阴性
0 p8 F: M) C9 @/ g) j0 ZFalse negative error, 假阴性错误
4 t" z7 [5 u; y0 H" dFamily of distributions, 分布族# X& Y, p$ v z x8 x2 g/ {% L
Family of estimators, 估计量族
0 V4 O/ d4 w- ^1 ~3 ^4 IFanning, 扇面
) Q4 v% q2 f) }$ F7 _9 Z+ g/ vFatality rate, 病死率: V" S+ u. L, H9 ~- V# g& m+ |7 C
Field investigation, 现场调查5 k _! X& u. s2 C& ^% g' T
Field survey, 现场调查, @9 I1 R- I, k4 Q
Finite population, 有限总体
" d7 L4 s7 i( @) C3 W* z8 _Finite-sample, 有限样本2 e* T$ T1 Y4 ?: _3 S F) N) V' i( H
First derivative, 一阶导数# T4 U: K& E9 r
First principal component, 第一主成分 H: s+ P6 [& _! B
First quartile, 第一四分位数8 Q! t- r4 Y+ B; e
Fisher information, 费雪信息量
# |- c, b9 L d& ]! F: S1 S/ D5 ?Fitted value, 拟合值
: I/ z& B! _0 m' [4 x' ^* IFitting a curve, 曲线拟合$ p; M# K; l v- l0 Q! n8 U7 C( g
Fixed base, 定基0 x0 i+ C2 [5 X
Fluctuation, 随机起伏
5 g* M7 {4 T, [8 G) c4 Y* \Forecast, 预测
! p, \ ~' P7 R3 ^+ s7 P$ S8 LFour fold table, 四格表
4 ^' ?& Y/ `( w1 DFourth, 四分点( h* Z" z) j2 |
Fraction blow, 左侧比率
1 |1 I' `' T, B; k; JFractional error, 相对误差
- [4 J5 R" s ^* v" j; yFrequency, 频率9 c5 E# t4 `* }: V
Frequency polygon, 频数多边图
6 ]& I, ]" x+ V% ~$ U O- X2 a0 hFrontier point, 界限点% I" X2 b; O" E% v) t+ M
Function relationship, 泛函关系
( p8 p+ X- v$ V) A. }9 i6 W& \Gamma distribution, 伽玛分布0 Z$ E0 X5 `: N6 X/ N: g$ H
Gauss increment, 高斯增量
6 |( O; X. ~+ gGaussian distribution, 高斯分布/正态分布
' n! Q4 ^) f( b6 DGauss-Newton increment, 高斯-牛顿增量
9 v3 a% i4 R9 l* d" ZGeneral census, 全面普查
8 A9 |2 R; X9 h8 j. L- uGENLOG (Generalized liner models), 广义线性模型
$ d2 z- S5 C8 k4 ?& x6 C lGeometric mean, 几何平均数9 T) J2 e8 s3 G' }, c* B( X
Gini's mean difference, 基尼均差
, u" a* ^& d1 ]( o3 `GLM (General liner models), 一般线性模型 2 P- f5 E" X' \8 Z6 N- u
Goodness of fit, 拟和优度/配合度2 Q( U( n4 T3 j6 Y* t
Gradient of determinant, 行列式的梯度8 u% K+ ?- W% A$ g7 U; H
Graeco-Latin square, 希腊拉丁方" j4 q; Q; x/ R3 h; ~$ q
Grand mean, 总均值! d( y3 G. a% B9 R* a1 Q
Gross errors, 重大错误
% o3 K" K9 I! n2 V8 OGross-error sensitivity, 大错敏感度5 ?& C4 [4 n) k$ H! h
Group averages, 分组平均3 C, A9 N: m& p( D
Grouped data, 分组资料( N# x& H; s. K5 a" ]9 C
Guessed mean, 假定平均数1 g# o8 @) D: w
Half-life, 半衰期
/ f% U( M, x5 @9 iHampel M-estimators, 汉佩尔M估计量
% U1 \: f1 f' r& U, ^: JHappenstance, 偶然事件- B" k" f6 _& W, [
Harmonic mean, 调和均数
- ?) p* K7 e5 o) W3 ^/ UHazard function, 风险均数
- X3 {6 L! n1 ^; ]) U4 \8 ^Hazard rate, 风险率0 w" z7 ?& M6 m
Heading, 标目 6 O2 x! ? G$ O
Heavy-tailed distribution, 重尾分布
4 x! Z* l$ B: eHessian array, 海森立体阵3 x' S4 {, K) d1 ^2 h! T l% d, D
Heterogeneity, 不同质& g- v7 a* H2 }) [, T, g- O" r
Heterogeneity of variance, 方差不齐
r8 |1 ?, \# i' W5 O( BHierarchical classification, 组内分组% p5 [% Q0 i2 e
Hierarchical clustering method, 系统聚类法% d1 U/ E+ l# L9 F& @* |
High-leverage point, 高杠杆率点
3 Q# m( d1 y* y9 \/ r. d, V* {& QHILOGLINEAR, 多维列联表的层次对数线性模型
# A6 i6 Y' p4 _5 }% NHinge, 折叶点+ U9 N# Z5 t' O" k; v! J4 \
Histogram, 直方图 Z2 Z$ q/ }2 o2 v3 b8 v/ H
Historical cohort study, 历史性队列研究
7 q3 C7 ?% G! zHoles, 空洞
9 s. X& |% Q) K ]( q" JHOMALS, 多重响应分析4 ]+ c% C1 a/ [+ O W
Homogeneity of variance, 方差齐性6 x) V2 ?/ H/ J5 b5 w9 y% z
Homogeneity test, 齐性检验. x! q% Z. q1 d+ T
Huber M-estimators, 休伯M估计量
0 r& u! [' t0 f7 B# y3 Z/ @Hyperbola, 双曲线7 Q1 R2 }: D! `
Hypothesis testing, 假设检验
) @0 s# i9 q5 O; n# s, |Hypothetical universe, 假设总体
% m9 M, Z+ [# U* H; x! }% V0 oImpossible event, 不可能事件, R- @5 N9 c% }
Independence, 独立性
V6 g m& s, ]8 i. w& xIndependent variable, 自变量
$ P/ K* i0 @" u" _' pIndex, 指标/指数4 c1 Z3 |4 K* |* W' Z% M9 @$ z
Indirect standardization, 间接标准化法: F% A: P& @& ^# s" f9 m
Individual, 个体
6 W& A, `* N' C g UInference band, 推断带
" i/ r9 V# [5 H: W: yInfinite population, 无限总体8 {- d# \" k4 o! z3 z. h+ \
Infinitely great, 无穷大1 Q1 l$ T1 n. N- N7 W
Infinitely small, 无穷小; k: @$ t) V7 N8 n
Influence curve, 影响曲线
7 g" `( |1 Q7 X: F& ^. ?Information capacity, 信息容量" U4 O; H7 l8 P2 b
Initial condition, 初始条件
" c) I8 M, r. U! PInitial estimate, 初始估计值 q# S$ Q, [, ~: e* J1 T. A, a
Initial level, 最初水平. |/ H8 H/ d: p6 z* T5 o* X
Interaction, 交互作用
4 ?4 [2 Y" A5 P9 A$ k MInteraction terms, 交互作用项- ]; h" D a, H7 [1 V
Intercept, 截距5 Y8 \4 {0 e- L% t2 F N
Interpolation, 内插法
% U k6 ]5 v2 A4 F# p3 w2 o3 DInterquartile range, 四分位距$ X1 V" h0 ], D0 n/ P) u
Interval estimation, 区间估计
# [$ W+ q2 N9 v2 D, @3 ]Intervals of equal probability, 等概率区间
- Y6 p$ u2 }( F& g6 D9 Z" bIntrinsic curvature, 固有曲率2 A8 j4 l/ L3 _& W& b
Invariance, 不变性
* R+ h. R; _" o; P& G7 E1 }% c+ XInverse matrix, 逆矩阵. _9 ^/ g- h3 q' s. ^. m+ I
Inverse probability, 逆概率
* ]1 o) J% [' N. D3 OInverse sine transformation, 反正弦变换
: ^+ p) N7 h1 Y, k% [; QIteration, 迭代
: l5 e% }' t) G( R( Q; j# `Jacobian determinant, 雅可比行列式
3 u+ }) v0 K3 J' f# k2 l5 oJoint distribution function, 分布函数
" l; @9 V' j9 f2 y2 A; n' HJoint probability, 联合概率
, X2 M# S& `& J2 A7 SJoint probability distribution, 联合概率分布# a+ q1 `& U# d
K means method, 逐步聚类法$ b3 J4 }# ]5 _4 R& m2 @9 A
Kaplan-Meier, 评估事件的时间长度
# n Q# n( ~0 \/ o) yKaplan-Merier chart, Kaplan-Merier图( x9 m2 C4 V" F" }
Kendall's rank correlation, Kendall等级相关: O3 v* w( |( D* V
Kinetic, 动力学
4 C6 m3 p! H& zKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
: p# `/ P' d1 | R5 H+ ?+ o, EKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
2 z/ g; t: h* GKurtosis, 峰度 e5 C6 S: } |" r( N& P- Q8 M
Lack of fit, 失拟
8 r& @! ^' n. i5 U+ KLadder of powers, 幂阶梯
2 ?; W) i6 y% ? y/ |4 CLag, 滞后
; C* ]- y6 Q3 d5 n& J4 b+ K& xLarge sample, 大样本0 O2 Y& X& o0 X0 t
Large sample test, 大样本检验
. ^1 ^1 _' P9 F h: Y! cLatin square, 拉丁方
% o" ^) I* D$ \7 B( D: H$ _Latin square design, 拉丁方设计& f2 X+ S5 M R2 E( Y9 J' d* @
Leakage, 泄漏6 y, P3 w2 L. \3 U. }
Least favorable configuration, 最不利构形
?) ^7 q& K( d2 e0 O% d" B0 XLeast favorable distribution, 最不利分布
/ _! \1 j$ [/ sLeast significant difference, 最小显著差法
" e5 e3 H4 U c7 RLeast square method, 最小二乘法
' E+ I9 o; C+ D3 I0 uLeast-absolute-residuals estimates, 最小绝对残差估计) y7 n: {% K! m' h
Least-absolute-residuals fit, 最小绝对残差拟合- @9 D" \- {" @2 y8 Y4 D+ |4 ^
Least-absolute-residuals line, 最小绝对残差线4 G" @1 T, D3 K. q: L$ U
Legend, 图例
) R$ q* F/ @9 M+ U6 I2 l0 L) ^; jL-estimator, L估计量
. V) \" Z& a& y7 UL-estimator of location, 位置L估计量6 g3 H/ f1 h7 [2 V, e
L-estimator of scale, 尺度L估计量0 Q" X% G& w* C
Level, 水平; i" l, ]& w% I" U
Life expectance, 预期期望寿命: k% m- X+ o0 J
Life table, 寿命表
7 l' L3 ~: A0 \" iLife table method, 生命表法& f9 C) M# A' a# E" V& I
Light-tailed distribution, 轻尾分布! n! f5 J4 I: G8 q4 @0 V1 }7 x3 |
Likelihood function, 似然函数
8 D c7 V& Y, d; ?% y: S/ QLikelihood ratio, 似然比
. o& v1 C5 G6 Wline graph, 线图# \- q# P! ]( C2 @
Linear correlation, 直线相关
. K7 ~* j8 S; x* a5 J2 D" I% s# n# yLinear equation, 线性方程: t' I$ J1 F( U+ u+ y, I/ w
Linear programming, 线性规划- }3 r8 {; q! J, U7 D
Linear regression, 直线回归
" u) g9 z+ ?: r( T- S) u' j$ [Linear Regression, 线性回归/ ]/ e3 m* i) P" a# \* n! m
Linear trend, 线性趋势8 v5 g( j& k. c4 b z |; P+ [
Loading, 载荷 % x) e) }/ F3 r. o. l
Location and scale equivariance, 位置尺度同变性
* f* ?$ N& y0 G: W% H; wLocation equivariance, 位置同变性$ N. x0 O5 N* ]. }/ F; W: W/ C
Location invariance, 位置不变性
$ k; ]" Q2 a/ ~3 `) E1 y* @4 FLocation scale family, 位置尺度族# Z5 `( E+ h" X6 f0 f) z
Log rank test, 时序检验 . m, r& |; G. m. E' G
Logarithmic curve, 对数曲线
. F( ]8 ]! x8 ~9 L, M( zLogarithmic normal distribution, 对数正态分布% \6 ~3 Z- W7 K: i8 q P
Logarithmic scale, 对数尺度* ?( S$ ~6 X- l9 q+ K, s6 {
Logarithmic transformation, 对数变换5 j/ v7 N" {% w$ L
Logic check, 逻辑检查) a" a4 G" D2 h% w8 f/ [7 ^
Logistic distribution, 逻辑斯特分布
& o& C& h1 G8 [ B( nLogit transformation, Logit转换
! r; k* J% |8 m: `# A. mLOGLINEAR, 多维列联表通用模型
; r8 U/ a- B2 x& I% ~- I: WLognormal distribution, 对数正态分布
0 E! d! z' H) J) qLost function, 损失函数" G3 o; Y ~% e( i/ @; A: Z
Low correlation, 低度相关
8 S8 W, R+ Z/ f7 b% K7 r, LLower limit, 下限
6 X" i% [- C- z3 {# C: L* P# lLowest-attained variance, 最小可达方差
9 X) A, d6 a3 B, Q) Q1 P7 G" jLSD, 最小显著差法的简称
l: K0 m2 o; Y' y& m% R1 Y7 R9 aLurking variable, 潜在变量
9 k1 u; `$ f" Y# XMain effect, 主效应
$ t5 d, u; `3 k& O3 z9 W: oMajor heading, 主辞标目$ @6 G q% g4 u+ H1 W! K: A
Marginal density function, 边缘密度函数8 O& |. y5 ^& j1 Q. [, m
Marginal probability, 边缘概率4 z5 ~/ \6 F% `( W3 Z
Marginal probability distribution, 边缘概率分布
, U$ V/ g& F1 |Matched data, 配对资料
+ V. A+ |2 s2 w# B: ]8 H1 fMatched distribution, 匹配过分布- {9 C* w% ^6 Y3 h% f% r1 I
Matching of distribution, 分布的匹配
* `7 s1 Q3 y! f% [# `3 LMatching of transformation, 变换的匹配
5 \! i8 Q/ W7 F* T8 j3 a8 O9 v; EMathematical expectation, 数学期望
. I" u! J8 i9 i2 F7 l, A' e1 _( iMathematical model, 数学模型7 a/ {0 k$ @& Z0 N
Maximum L-estimator, 极大极小L 估计量% L0 }, ?: m3 y; C" Z2 N, n. p
Maximum likelihood method, 最大似然法
- |. U0 s: _2 @1 @Mean, 均数
' V9 A1 @/ {# z* x% Y. p: PMean squares between groups, 组间均方) c8 q' V! V9 a Y
Mean squares within group, 组内均方4 H0 I/ p6 E. Z$ ^" Y5 t
Means (Compare means), 均值-均值比较
) B' z( g: y% J5 g" q* XMedian, 中位数) k" s0 X5 p3 ^- Z+ \' a
Median effective dose, 半数效量6 F) f9 T& J0 r6 Y0 D( e3 Y1 k
Median lethal dose, 半数致死量- L- `! I z- s# Q
Median polish, 中位数平滑
; R' B9 {# X) T* kMedian test, 中位数检验
w. ]( d9 C9 }2 {! kMinimal sufficient statistic, 最小充分统计量
; [2 ^% b! E/ ]Minimum distance estimation, 最小距离估计
" Q; h7 w/ _2 W3 S- e! m- BMinimum effective dose, 最小有效量$ P6 q0 M8 G7 T+ k. _
Minimum lethal dose, 最小致死量
7 T4 P' c3 u) y/ eMinimum variance estimator, 最小方差估计量 [0 [+ ^2 ^; Y9 m' E' o, D: x
MINITAB, 统计软件包1 f2 g9 Q: x9 Y6 A
Minor heading, 宾词标目
0 j X9 ~. z/ i2 d) _0 `Missing data, 缺失值7 ~2 e0 j* l; r+ d5 u
Model specification, 模型的确定
7 C. z4 d; P- O7 W* zModeling Statistics , 模型统计
) G: o. x' J# g4 iModels for outliers, 离群值模型3 W9 p6 a/ M6 B$ S
Modifying the model, 模型的修正0 M# [' r) E* y, o* d" t
Modulus of continuity, 连续性模# j3 c, _* P( Q" M+ q. L% h! ^ l
Morbidity, 发病率 % ]7 N- L( T* q; o. p
Most favorable configuration, 最有利构形9 k$ N1 p- X4 I9 Q0 u. T
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
3 K+ f4 i! |' ~. PMultinomial Logistic Regression , 多项逻辑斯蒂回归- f% e0 T4 W6 Y2 {; c" M
Multiple comparison, 多重比较
+ y# o( U) `) H: H* X3 a& SMultiple correlation , 复相关5 o3 k# A- d1 p3 `2 A- f" l
Multiple covariance, 多元协方差
9 ]6 C$ M# a7 h! P1 @Multiple linear regression, 多元线性回归
' n, ^+ {4 ~: Y4 W3 `6 }Multiple response , 多重选项) g3 l; {! |0 s# i; E* i9 F4 s
Multiple solutions, 多解
[) t) B9 ~9 N; S( jMultiplication theorem, 乘法定理; t$ w6 P( Q1 J9 m9 {9 {! p1 r
Multiresponse, 多元响应
, T- Y) v1 X! i( p7 NMulti-stage sampling, 多阶段抽样% M) ? j6 @$ h( {# M( l2 |1 m. R
Multivariate T distribution, 多元T分布; ~5 C' r+ S! X. e
Mutual exclusive, 互不相容; o7 y% v0 o; t" B* |
Mutual independence, 互相独立
! ^/ A; {1 p( oNatural boundary, 自然边界
0 \- V8 R8 w/ A& WNatural dead, 自然死亡6 P0 H2 L, A) w. e p2 k* v
Natural zero, 自然零
6 F+ y& Z5 s) x2 d+ X/ uNegative correlation, 负相关
7 p5 k+ R; o0 ^0 NNegative linear correlation, 负线性相关0 q" O8 P: p; E- w: Y
Negatively skewed, 负偏4 J# o3 U. a5 }; k
Newman-Keuls method, q检验& z( m" A o; A
NK method, q检验# Y, g6 A! g$ l7 {5 l; h1 q& U( j2 V- F) G
No statistical significance, 无统计意义& l) o2 z. u B& f5 A
Nominal variable, 名义变量7 o# Q- U6 u$ D6 Q
Nonconstancy of variability, 变异的非定常性
+ A7 C: P& {2 K3 V. I6 z) sNonlinear regression, 非线性相关
% U; ]3 }' D: M8 x5 r. gNonparametric statistics, 非参数统计: [5 A" y& r) {0 E/ t& V
Nonparametric test, 非参数检验
4 f) E" s* u9 I3 qNonparametric tests, 非参数检验
/ Y/ E8 k$ I$ QNormal deviate, 正态离差
" r2 p T+ L4 o0 h( jNormal distribution, 正态分布9 A$ H; A0 o7 e" _! N
Normal equation, 正规方程组4 C, f( p4 }! X; |' \7 t
Normal ranges, 正常范围$ y" N- s$ v9 d0 O
Normal value, 正常值
5 m- a! F' W0 @/ J" N7 c1 LNuisance parameter, 多余参数/讨厌参数
% C, A/ L# Q9 i( H3 [Null hypothesis, 无效假设 5 b$ |& W; y2 s. a& S* h
Numerical variable, 数值变量) w! c/ l3 g5 I, M" m. c) h
Objective function, 目标函数# J& Z% ]1 a8 G2 z$ R" a/ [
Observation unit, 观察单位
$ \% o5 b# G( ]7 QObserved value, 观察值
8 @1 S1 l6 L3 c- J5 `# ^One sided test, 单侧检验# w% k4 O) b# i8 {4 o6 O' }
One-way analysis of variance, 单因素方差分析3 I: o5 S( i$ r7 {' \) ?0 o4 Z: _5 {1 q3 o
Oneway ANOVA , 单因素方差分析
# e) w# T& w) h4 K2 G6 nOpen sequential trial, 开放型序贯设计
) Y. n( n! z7 H- k6 HOptrim, 优切尾" i, D, b4 [- A: u9 I6 u6 b( f4 j
Optrim efficiency, 优切尾效率+ U3 Z; H( M9 V1 q8 b5 w
Order statistics, 顺序统计量
6 q; U- G- f( p0 S* c* J& C/ yOrdered categories, 有序分类' E# g8 t! J" W0 Q$ H/ R
Ordinal logistic regression , 序数逻辑斯蒂回归
% N+ _8 W2 `, g" l- ]: i* cOrdinal variable, 有序变量
5 K/ W$ M5 k4 gOrthogonal basis, 正交基) L4 B% d0 z2 u9 X- o* \
Orthogonal design, 正交试验设计* }$ }$ |( {0 e' A
Orthogonality conditions, 正交条件
/ i7 N* i. b7 K$ \ORTHOPLAN, 正交设计
I" F% Z3 g8 g# Q' H9 H' POutlier cutoffs, 离群值截断点 ? O% V3 R9 |
Outliers, 极端值0 Y0 e' f9 Z, r( u+ Y( L
OVERALS , 多组变量的非线性正规相关
% ~+ {- U1 X( M& t# MOvershoot, 迭代过度# U/ m0 `' v1 j% R/ t, a1 I
Paired design, 配对设计
7 s6 Q0 N, I0 Q) x; ~6 Y: }* m( [Paired sample, 配对样本
0 n' s3 X/ m( `0 E4 O1 D! r9 z- JPairwise slopes, 成对斜率
4 Q: U/ q" K3 ZParabola, 抛物线# @, R$ a8 I! }3 X
Parallel tests, 平行试验
/ b- A5 j- k w! x+ F3 M+ `; qParameter, 参数
$ n8 _# ]5 [! A) Q& ~+ a+ @8 KParametric statistics, 参数统计
8 F6 f( W. f0 A1 p% k. I5 TParametric test, 参数检验5 z6 l* p: y3 f& q* r3 h
Partial correlation, 偏相关
) H* |' }8 g5 R. S4 p4 aPartial regression, 偏回归) M1 N4 R3 r2 O7 M% g( G& Z
Partial sorting, 偏排序' U8 ^, ~1 Z; B7 r# H& l! j
Partials residuals, 偏残差; v6 r# ?5 x: \9 H- O$ Q- G9 U% E
Pattern, 模式& y2 |# l3 E% g' O8 @* ~% w- l
Pearson curves, 皮尔逊曲线- u5 H6 S/ I' [. R; Q9 P: L
Peeling, 退层
; D/ f' V$ A0 Q. z3 Z) ^7 w6 gPercent bar graph, 百分条形图$ \2 K( F3 Z" u3 F ^8 z( f5 a2 P
Percentage, 百分比- \+ i& \; I8 X
Percentile, 百分位数
S3 P. z' f1 @5 FPercentile curves, 百分位曲线! C6 Y4 i8 H0 X: k& h. J9 M% u6 @0 Q/ |
Periodicity, 周期性
4 R; B( m# h, }+ I; V% \Permutation, 排列
" c! @& p) ~4 t7 y# \: rP-estimator, P估计量3 A2 z$ G3 D; q. \2 V2 x
Pie graph, 饼图; r$ z7 I- u) g; N- @/ S
Pitman estimator, 皮特曼估计量
9 |& N+ W, }; o* M; R9 QPivot, 枢轴量8 V5 d( a! z5 v5 y4 J
Planar, 平坦1 k' [) G5 n2 t$ `3 I
Planar assumption, 平面的假设
+ X4 b. n, L' K" W& ^. ePLANCARDS, 生成试验的计划卡
: X/ A; @4 l/ w1 U/ i# IPoint estimation, 点估计7 ^% R& {- J+ L0 C' D: [9 B% x. o, Q* A
Poisson distribution, 泊松分布4 F; a# P( i" |2 G2 T" H
Polishing, 平滑
$ m a( O; k4 Z- B; p! x9 a) KPolled standard deviation, 合并标准差
0 Z# c5 k( X6 k! yPolled variance, 合并方差# r6 u& t8 y* X5 }" R5 t6 n( W9 X
Polygon, 多边图
9 Q6 Y' U2 G% B& W$ NPolynomial, 多项式9 x, _! X& _- L: ]! ^
Polynomial curve, 多项式曲线
. m- \( `' g+ K1 O4 D* UPopulation, 总体/ z$ d1 _: O- `" j; w9 ^ H
Population attributable risk, 人群归因危险度
# C' t/ u" j) J3 a8 HPositive correlation, 正相关
! f. y3 p r& H- K6 |% {Positively skewed, 正偏
+ z! c1 t2 o. {- S! VPosterior distribution, 后验分布
6 D0 K8 e3 u/ _8 u' m6 uPower of a test, 检验效能& L5 g: `: I# H; S# p% B/ Z8 d! q6 _
Precision, 精密度
% [# m( ^( C/ v- EPredicted value, 预测值
n. @) p1 _- SPreliminary analysis, 预备性分析1 g5 r0 ?' I2 W' h; K' ?& r
Principal component analysis, 主成分分析+ G6 P5 _* t* j$ l4 l1 P+ g2 `
Prior distribution, 先验分布9 S* p+ }2 K6 J7 n/ @. W
Prior probability, 先验概率/ l& R' L* ^& e+ G3 h
Probabilistic model, 概率模型
7 ~# _4 C) P# f9 H' Iprobability, 概率1 r, d) B, Y9 ^# n# e# u8 w# l
Probability density, 概率密度
# U% r; V. z2 m/ D0 J/ [, [Product moment, 乘积矩/协方差" b1 V3 a/ H% S5 w8 e% \0 I- ~, x
Profile trace, 截面迹图4 @# P1 h9 {* b1 k4 T
Proportion, 比/构成比/ x, q) s! L( @
Proportion allocation in stratified random sampling, 按比例分层随机抽样
; o2 w8 [0 `3 R9 u' m' tProportionate, 成比例& [7 ~3 Z' E! V" K$ S/ D- G
Proportionate sub-class numbers, 成比例次级组含量, E( @1 B+ y- X
Prospective study, 前瞻性调查: f& V- m$ e) g2 E3 l- K
Proximities, 亲近性
4 d G+ h5 q" C* @0 zPseudo F test, 近似F检验
- c- {0 o" E: J% K4 R! kPseudo model, 近似模型
$ J% P8 v% j7 n+ yPseudosigma, 伪标准差 j: U5 |0 ~# H1 v2 A# b
Purposive sampling, 有目的抽样
^* N! Z% T( P/ x$ o5 H% DQR decomposition, QR分解
# T7 K8 Q& ^$ `# MQuadratic approximation, 二次近似
& e, e: J1 Z0 I8 UQualitative classification, 属性分类
$ m {( u# \3 f7 }9 b+ \Qualitative method, 定性方法
! k: l7 Y$ q9 c3 r! w! B tQuantile-quantile plot, 分位数-分位数图/Q-Q图
9 \ j) H. ]" h5 G iQuantitative analysis, 定量分析
5 D3 T+ Q4 E/ a# h4 r4 w$ ?2 zQuartile, 四分位数
' g' r. S1 d) \1 _: g, gQuick Cluster, 快速聚类
, M/ A0 y! }$ C1 }5 l( oRadix sort, 基数排序8 }8 o x) ]2 g+ B" w/ C
Random allocation, 随机化分组6 B% ^! _: D; P$ h& s
Random blocks design, 随机区组设计0 Q& J7 [6 m9 r. W6 j
Random event, 随机事件; a7 n' y' O% ^0 K: m3 p- v; ?
Randomization, 随机化
. Z# }5 }/ _; d, PRange, 极差/全距
# Y- q( ?6 V. g) X$ h, X) h9 ~: @Rank correlation, 等级相关5 e5 p, r2 I/ G2 s! G
Rank sum test, 秩和检验* V6 c0 K8 A- j* F7 z+ |5 ~' L
Rank test, 秩检验
7 [8 ]" t9 @6 mRanked data, 等级资料
% O% d% t; J+ i- cRate, 比率
5 g$ j3 P, S4 ^2 s) ]6 H. aRatio, 比例
; ~. R, U8 G/ d9 V4 NRaw data, 原始资料" G# b, [ e/ }0 I( o
Raw residual, 原始残差0 t: ]% G. V" g1 f
Rayleigh's test, 雷氏检验1 `: }2 F. c3 u7 L8 ]( o
Rayleigh's Z, 雷氏Z值
4 I! _( S. P* ?Reciprocal, 倒数/ e; B! m; P6 W4 s8 R7 S5 T% W
Reciprocal transformation, 倒数变换
3 G9 {, m0 f% w; d/ x0 |7 x! hRecording, 记录& n1 ]3 b) V. ^% Z* d
Redescending estimators, 回降估计量
' `* h4 R# \1 j% y! y# xReducing dimensions, 降维( Y) Y8 x! ]$ ]6 N3 ^
Re-expression, 重新表达
& o5 U' l; `- n WReference set, 标准组6 v4 z5 k" u; ?+ E
Region of acceptance, 接受域
( I" V2 i# {3 l. Y) d( DRegression coefficient, 回归系数
8 p5 c6 `8 c( e, V- Z/ YRegression sum of square, 回归平方和" }: G. C4 E& M/ R# o( F
Rejection point, 拒绝点
% f7 [) S+ W: Y& K' RRelative dispersion, 相对离散度
' r* p' D5 w/ {2 {Relative number, 相对数9 t2 S# J% w3 s6 U: G1 S
Reliability, 可靠性: m+ s8 u7 {9 X; r+ _5 e, v
Reparametrization, 重新设置参数
9 _$ K# S! a/ |Replication, 重复
" b) y E g7 E! d4 L+ q9 |Report Summaries, 报告摘要
9 u+ [. l0 _2 j1 p! x" WResidual sum of square, 剩余平方和/ I% f* }: J& w) R& t5 v
Resistance, 耐抗性% o6 U5 c4 K, l6 \1 o6 U
Resistant line, 耐抗线- S( G$ V, d8 l- S/ g2 r
Resistant technique, 耐抗技术* i! ]# F3 ?, N, ]& b
R-estimator of location, 位置R估计量; X5 T3 Z- l* C* n: v2 E( o! d
R-estimator of scale, 尺度R估计量, ^0 J- p+ D( W9 H
Retrospective study, 回顾性调查
4 K- z5 ~( y0 K Z" s. D* e( jRidge trace, 岭迹
! v* {6 R5 J- ]6 t) @& [Ridit analysis, Ridit分析
5 E2 [+ {2 ~; _# e) TRotation, 旋转
% ^2 F6 T W$ U* t" FRounding, 舍入
/ W( j+ Z! a0 l( j1 LRow, 行
+ a1 E/ s7 X+ QRow effects, 行效应; q: j q9 Q, T
Row factor, 行因素2 ]) b+ }/ W) Z W" b8 _/ F
RXC table, RXC表) C: Z# q* C- g2 n' N
Sample, 样本
$ p g T* s& I# XSample regression coefficient, 样本回归系数
3 e! [! ], x" O; f, G8 vSample size, 样本量. ?; O& l, D* ~5 v
Sample standard deviation, 样本标准差
1 y8 t+ X& t. P2 ~Sampling error, 抽样误差- C: o/ \# L, i: \2 l( l
SAS(Statistical analysis system ), SAS统计软件包2 p! |& q! T/ U5 h
Scale, 尺度/量表# O* d( }6 e8 q
Scatter diagram, 散点图
1 u- `8 u$ f9 x5 R7 |0 L* l0 R2 CSchematic plot, 示意图/简图. d1 N$ h5 j6 R
Score test, 计分检验0 Q+ |. g1 n& `2 z+ G3 w+ a
Screening, 筛检
4 n) x" L: G) C" t( S1 ySEASON, 季节分析 $ b/ {/ n R; e% W1 y
Second derivative, 二阶导数
, H3 u! h1 F, i: A; l8 v9 uSecond principal component, 第二主成分
# r4 f e/ q/ x/ D& Y i; gSEM (Structural equation modeling), 结构化方程模型
0 H! I. |$ c9 @; V# VSemi-logarithmic graph, 半对数图
( J9 \- j* I: D# w& ]Semi-logarithmic paper, 半对数格纸
. w# t7 s" {: i. q hSensitivity curve, 敏感度曲线/ C& i1 h+ [# j; n% X3 { p
Sequential analysis, 贯序分析
* F0 J: r' W T* Z$ ]4 MSequential data set, 顺序数据集
; F& i! w5 o D7 F8 ]Sequential design, 贯序设计
1 f0 A6 p, Z2 LSequential method, 贯序法
' w7 ]2 T6 X1 L, g. z) cSequential test, 贯序检验法* s( S" m) ?) W; K/ A. X
Serial tests, 系列试验
* _& c, O5 A& V: \Short-cut method, 简捷法 " j. o, @4 H! u/ C! _- \) t
Sigmoid curve, S形曲线
& B4 `' k2 I: a3 e6 \Sign function, 正负号函数" f1 t( N8 D$ I; g- x( n2 g
Sign test, 符号检验7 p: ~1 X: S( Y
Signed rank, 符号秩
) U" Z$ V5 H8 XSignificance test, 显著性检验
: e7 l! ^0 v# k7 USignificant figure, 有效数字
6 l E1 I- |2 pSimple cluster sampling, 简单整群抽样1 I5 }6 ?1 m6 k( p C
Simple correlation, 简单相关# b# ~- l% U6 V. T% E7 {$ I
Simple random sampling, 简单随机抽样1 e# }7 w: ^# l5 ?+ _
Simple regression, 简单回归
, `$ v; B2 y& V2 k) Y$ Lsimple table, 简单表& `" \3 `, g' [& V* Y( F
Sine estimator, 正弦估计量* F' u% M* b" Y3 A; }6 `& K1 X% i& E
Single-valued estimate, 单值估计4 f+ D l8 ?( }4 P7 M! c
Singular matrix, 奇异矩阵
{- @& ]" _3 m1 p+ y9 v6 @8 ?8 z8 [Skewed distribution, 偏斜分布
' k* ~' P( k, t9 bSkewness, 偏度& a. Z) v, n( l. Q
Slash distribution, 斜线分布+ K! U, C' e; S- W' S& e+ j9 p
Slope, 斜率
0 z3 o5 [! E# R/ _! ^) tSmirnov test, 斯米尔诺夫检验
: ^1 K$ M# q5 Y/ k& y* ]Source of variation, 变异来源- U' h, R" z1 p. T, Z% B/ k: }
Spearman rank correlation, 斯皮尔曼等级相关
$ k; i( x3 J; y( ESpecific factor, 特殊因子' \( Z4 ]& w5 y, _2 _/ U
Specific factor variance, 特殊因子方差
0 j- W0 _: ]% {8 V+ h- B+ d* ^/ |- USpectra , 频谱
) U& f4 w4 q( @$ V* ^$ J! J2 |Spherical distribution, 球型正态分布8 v: u! E+ y' l/ C
Spread, 展布+ y4 _& m( i2 C* w9 }/ V
SPSS(Statistical package for the social science), SPSS统计软件包2 u' |2 r; j8 F7 P5 A* s
Spurious correlation, 假性相关
$ v+ H- s/ G& TSquare root transformation, 平方根变换
. C0 W9 {& D! w2 Y( N% F' yStabilizing variance, 稳定方差4 e. c/ c0 g) L' M
Standard deviation, 标准差
+ H: {; `9 w- SStandard error, 标准误
7 o; [) {: z) r _2 x* W, v; q, g8 Z8 X1 zStandard error of difference, 差别的标准误1 h0 ^8 B. a- o* l4 f1 E
Standard error of estimate, 标准估计误差
4 e, t! n1 O5 H4 GStandard error of rate, 率的标准误3 `+ ?( o7 _( ]: m; d- B
Standard normal distribution, 标准正态分布
2 |0 d: x! |& e4 D3 CStandardization, 标准化
0 r5 K% O x' u- G# X8 o5 v+ VStarting value, 起始值+ }+ l' P s/ c, f" u
Statistic, 统计量
* H' a% \3 a, QStatistical control, 统计控制
" ~* K2 h; J8 }8 D( K' oStatistical graph, 统计图
* q9 F6 \8 x9 X4 GStatistical inference, 统计推断
% `1 E7 m: R: }9 qStatistical table, 统计表
( ^' b" N$ W* y3 ]) @5 SSteepest descent, 最速下降法
3 w& h. \# |2 \+ @. JStem and leaf display, 茎叶图* H( D( V* y5 }/ g1 T5 r# M
Step factor, 步长因子3 [- b, s8 B8 n" ~ o8 x" ]4 M( f
Stepwise regression, 逐步回归
_8 r, Z( g9 q3 r; j8 `- zStorage, 存" a1 q3 m2 j0 I
Strata, 层（复数）. s+ y/ H2 ~: n
Stratified sampling, 分层抽样# W7 s: W8 K6 b' K
Stratified sampling, 分层抽样% k7 i7 c( }3 u5 e/ R
Strength, 强度
8 {1 z- r) `* A( V; a$ s1 H+ cStringency, 严密性( t$ h' |3 [' j0 ?7 M3 q
Structural relationship, 结构关系
; M# K( S0 q: s8 g8 mStudentized residual, 学生化残差/t化残差$ K9 u; F/ A$ l! y( ~
Sub-class numbers, 次级组含量8 y7 j6 k6 q, ~. H/ [& B
Subdividing, 分割' n1 L( z0 B% x+ T# N
Sufficient statistic, 充分统计量3 C1 i) ^! ?% B2 ?$ A5 K7 i
Sum of products, 积和1 ~1 I2 B( z7 O: j
Sum of squares, 离差平方和
% P8 |3 Q2 b/ E" z7 RSum of squares about regression, 回归平方和
' u* G9 D% x% w7 ^Sum of squares between groups, 组间平方和
3 F$ M# }3 ?7 ^/ PSum of squares of partial regression, 偏回归平方和* w0 G& @; d, d6 T$ @( F) I% l8 M
Sure event, 必然事件
5 K* k g) P$ z- i0 [. Z* nSurvey, 调查
0 o8 o! Q8 f3 ?$ z5 N: l9 P( wSurvival, 生存分析
8 C. v! [0 `, L% E6 sSurvival rate, 生存率
# m0 |' p1 E+ z% ZSuspended root gram, 悬吊根图
( u* E' u! h0 f3 a* r3 h) D bSymmetry, 对称5 z1 M+ W4 X& k& {$ T+ X
Systematic error, 系统误差1 F# H- \6 M7 B+ Z3 x( ^, ^* Y
Systematic sampling, 系统抽样( @3 G, K5 h( }# U* M, J4 g4 H' c
Tags, 标签4 c, e& d+ f& O3 m, g9 M
Tail area, 尾部面积
) W! H0 D5 I: d8 o' Y1 V5 _ H6 B3 L, tTail length, 尾长5 O2 V, q& b& Q% P! G
Tail weight, 尾重
" D' \6 a4 W# b( MTangent line, 切线 H* w+ v% \: i$ C& v" S G3 T
Target distribution, 目标分布" P% ~- w) D8 ^( `) w7 R
Taylor series, 泰勒级数, [- W0 ^" K; K' c
Tendency of dispersion, 离散趋势
6 [5 b& B& ^9 c8 d4 _Testing of hypotheses, 假设检验
8 W+ Q" R5 [4 {- x- Y- NTheoretical frequency, 理论频数2 u' C* \ L5 o
Time series, 时间序列
$ s9 U, i, i( b5 h' u3 H6 ~2 nTolerance interval, 容忍区间' d% E: l. u+ d
Tolerance lower limit, 容忍下限0 @0 Q5 D$ c- N( W3 M. t4 u% b# t0 m: G& r
Tolerance upper limit, 容忍上限
' r5 y$ X& G$ W @Torsion, 扰率
: `- `+ X- J* z; VTotal sum of square, 总平方和4 K* t* u2 [* b
Total variation, 总变异3 u$ R) r5 r& z# p4 G) {
Transformation, 转换
9 i9 W4 T" n) ?5 U( ^Treatment, 处理# D5 X! y, k0 K, @/ X
Trend, 趋势& H! n ~$ O. M; O$ [ \+ u1 S' ^
Trend of percentage, 百分比趋势) ~9 D8 v5 r9 U4 N4 R
Trial, 试验
4 [. D# j0 z: N3 e, r, H1 LTrial and error method, 试错法8 Q2 r. A; l, N% q8 Q
Tuning constant, 细调常数# R* a8 |/ z0 e( R9 g; x1 o3 U k
Two sided test, 双向检验% Z1 d7 F* y: v4 S8 F# ?8 O+ v8 O
Two-stage least squares, 二阶最小平方
, @& }' B7 W; ~Two-stage sampling, 二阶段抽样
7 x1 e; O8 e. ?: K! G0 ?Two-tailed test, 双侧检验
& _ f: G; Z3 g( C; R& W) |) VTwo-way analysis of variance, 双因素方差分析1 d' U0 {1 \8 X% }( j& P
Two-way table, 双向表, _1 t7 |3 r3 k- G5 C6 ]
Type I error, 一类错误/α错误 b9 k7 u6 r0 ]; p! @
Type II error, 二类错误/β错误6 H& E0 s& [7 [
UMVU, 方差一致最小无偏估计简称
; [. M9 }% l+ z4 z. SUnbiased estimate, 无偏估计9 `# N+ [/ z' B# u
Unconstrained nonlinear regression , 无约束非线性回归
: M2 l9 _6 G, E- zUnequal subclass number, 不等次级组含量
4 U& t- N5 ?) i& ZUngrouped data, 不分组资料
# S# M9 k/ ^$ x6 @Uniform coordinate, 均匀坐标
8 V! n& ]( n: h! ?" [Uniform distribution, 均匀分布. R* V2 |# z3 G% M* i
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
% T. j$ g9 s6 ~! }- K+ W! B, qUnit, 单元
3 h" A9 F; g( I1 J; bUnordered categories, 无序分类
% U, y0 @7 V8 i, {, J3 K$ x' lUpper limit, 上限
2 {1 i I7 t2 a. Y: v7 |Upward rank, 升秩 \2 a+ j) A% E5 C
Vague concept, 模糊概念8 W: ~1 A4 U9 M0 t0 j2 Q
Validity, 有效性
/ O+ Z# d7 s+ y0 h- o0 M7 t$ fVARCOMP (Variance component estimation), 方差元素估计/ l. C& q y9 W! l
Variability, 变异性
6 d7 q1 i' R! J6 z0 U9 E4 ~5 I" w2 ^$ eVariable, 变量
$ Q6 m5 N/ ? |. x5 M* cVariance, 方差8 j- f5 f' D" G1 j0 o: ^
Variation, 变异- ^# X2 @0 ]3 E# A$ T+ O
Varimax orthogonal rotation, 方差最大正交旋转
. ]8 w, Z! I1 J4 e* \. s' XVolume of distribution, 容积
% o7 c* b7 {0 Y4 G5 aW test, W检验+ c# M* q" N% B2 h: l+ {* p( s
Weibull distribution, 威布尔分布
, K2 j& ?: m# h. P' SWeight, 权数
1 r1 l5 U' J& s, c1 IWeighted Chi-square test, 加权卡方检验/Cochran检验
6 ]0 Z) V/ K$ y7 x& \: tWeighted linear regression method, 加权直线回归
8 }6 Y( H) h) @& Z, l" G. i( NWeighted mean, 加权平均数# [. N6 J# r1 B+ v; ^; \; J8 i
Weighted mean square, 加权平均方差
. k2 v! t: c, s$ R4 O l7 A9 wWeighted sum of square, 加权平方和
6 |9 _: W% c4 }( ]! j) VWeighting coefficient, 权重系数
- S7 ` x5 M( {* IWeighting method, 加权法 9 R1 S+ g& R6 Q
W-estimation, W估计量/ R% k1 t. ]5 Z) ~ Z. R1 c
W-estimation of location, 位置W估计量
' n: f' P& T$ y& c7 k. \$ wWidth, 宽度
: I# w4 i2 \( g; K" l% _Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验7 I9 \! a% h# K8 R+ V% q# ?& ~+ `
Wild point, 野点/狂点
" N; J) U% h$ ~, S9 {) k" \Wild value, 野值/狂值
" e* o1 t& Y9 ^ i- K+ aWinsorized mean, 缩尾均值1 `( H. A0 E' u c! A' G) p
Withdraw, 失访
* A! ^ }4 w! GYouden's index, 尤登指数
2 p# R: E0 ?8 K% S! iZ test, Z检验/ e; T5 b: v# _5 K5 J1 A/ A9 L- B
Zero correlation, 零相关4 F: i* z* f3 D: u! t
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
