|
|
Absolute deviation, 绝对离差
# z3 i5 ]8 x* wAbsolute number, 绝对数: q: G' A1 k% d9 y4 d# a: \' I- M
Absolute residuals, 绝对残差
% T- X- R+ O. G2 F, u" ]1 HAcceleration array, 加速度立体阵
. D4 o& S3 j2 R- L h( z5 {Acceleration in an arbitrary direction, 任意方向上的加速度5 G1 j% Y% ^& F! c
Acceleration normal, 法向加速度
. p# Z' V8 k% S: K2 N+ ZAcceleration space dimension, 加速度空间的维数
* D+ r6 j7 e6 Q4 F; {+ ?Acceleration tangential, 切向加速度: X+ D" [6 @/ i: F
Acceleration vector, 加速度向量: K% M8 c) Y- C$ n% |- ~
Acceptable hypothesis, 可接受假设
w0 Z( I! z: {* G% Z; D& F, D& \! DAccumulation, 累积! C7 p& D4 o; Q4 b6 O
Accuracy, 准确度$ E( T( k' Z( u I; E2 N, Z2 D+ O
Actual frequency, 实际频数$ N( a- L; S6 c h7 U
Adaptive estimator, 自适应估计量! u& x; m5 T* P% n& x& O
Addition, 相加
1 ]/ N1 v* N0 ^Addition theorem, 加法定理
# q, N. c' A) @7 f1 UAdditivity, 可加性
, w' C- W: s! @' w+ yAdjusted rate, 调整率. p) N* Q! a; I
Adjusted value, 校正值
% c" @6 q1 u; Y) DAdmissible error, 容许误差
, |5 W4 d1 d8 _Aggregation, 聚集性5 f1 E/ R9 u) p
Alternative hypothesis, 备择假设
' U5 O$ y8 m! s" ^- rAmong groups, 组间
6 T* H9 O; p* o% ZAmounts, 总量
9 N# f Q2 }3 ]" G+ U$ rAnalysis of correlation, 相关分析
1 A c, J' R) c% tAnalysis of covariance, 协方差分析; A! l" ]" a }( }) }* Q5 f7 s3 s
Analysis of regression, 回归分析
0 W( c6 J# B( X* HAnalysis of time series, 时间序列分析
& `6 M7 x: V- W! \Analysis of variance, 方差分析5 F* f/ }" d# e: w0 _2 B
Angular transformation, 角转换
; J% r8 v6 f9 t" ?4 j9 |! DANOVA （analysis of variance）, 方差分析
0 ~) X& k+ ?9 p: g/ j9 n8 uANOVA Models, 方差分析模型
3 T; q H4 I6 S/ }, ^ dArcing, 弧/弧旋
. L; C2 e1 t+ w RArcsine transformation, 反正弦变换1 G2 u: }- l3 Q, h* N. A" g
Area under the curve, 曲线面积$ n2 Z8 s1 X b' D+ V
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 , N% G: K5 A4 X' ^, R
ARIMA, 季节和非季节性单变量模型的极大似然估计 . V( ~: b+ e! c' ~+ K9 z
Arithmetic grid paper, 算术格纸! _( _. d4 \, O" l/ _2 V+ |( x
Arithmetic mean, 算术平均数
) b' @& q# q( I3 N2 o4 JArrhenius relation, 艾恩尼斯关系/ @; L" a9 j! X! K
Assessing fit, 拟合的评估
% [, i6 ~* J7 O" Q- p' RAssociative laws, 结合律0 E: W O) H8 b1 G& m
Asymmetric distribution, 非对称分布
. `9 [: L% H7 c0 O. E7 iAsymptotic bias, 渐近偏倚
/ i! P' v1 d" A0 u$ [% q, FAsymptotic efficiency, 渐近效率$ S3 Y% J* F5 s6 k7 i
Asymptotic variance, 渐近方差: m3 D7 Z, m$ s6 H5 ^! u
Attributable risk, 归因危险度% r& k% Z7 L: C0 H
Attribute data, 属性资料9 B- Z- s7 ~/ P. b2 S& M5 g
Attribution, 属性' J* R3 ^' j! S& L
Autocorrelation, 自相关
' Z& K. @8 l3 B, s; KAutocorrelation of residuals, 残差的自相关3 |9 }5 u( P* V- M# o, I' C. [2 @
Average, 平均数& f2 q0 k( u$ c; x
Average confidence interval length, 平均置信区间长度
" h" {) |+ f0 h C2 j% z7 K& W: c) K2 ?Average growth rate, 平均增长率
$ c: e0 x7 ^$ V8 o1 W- }. Q9 |* eBar chart, 条形图5 p' P, {& L* R3 s% g6 E. J
Bar graph, 条形图
2 t) [ a$ l6 P% {5 W; J+ zBase period, 基期. C7 A* A. p* Y8 {+ U
Bayes' theorem , Bayes定理
/ L2 k% W8 ]' r- dBell-shaped curve, 钟形曲线/ ^" S% {, z9 u2 t
Bernoulli distribution, 伯努力分布
1 f1 F: O$ }. x( ~" ?, gBest-trim estimator, 最好切尾估计量
+ ~8 ]5 X% k5 J; G, ?" yBias, 偏性
) C. i" t" A4 V4 `Binary logistic regression, 二元逻辑斯蒂回归
6 H$ x- L6 w& P% XBinomial distribution, 二项分布
+ ?) v) |( Y8 vBisquare, 双平方
! y9 \. R, h) p b9 I) S& LBivariate Correlate, 二变量相关- v# E% X5 S, b! h0 v. i
Bivariate normal distribution, 双变量正态分布
: n$ I* m" e2 C$ T% l% ?; H3 k, `Bivariate normal population, 双变量正态总体
3 Z9 f L( V5 y; u, D! B/ ^% cBiweight interval, 双权区间; Z" |1 Q* e6 m2 O4 m
Biweight M-estimator, 双权M估计量; p% J+ Q6 C8 u, |( E: O9 s7 y
Block, 区组/配伍组
a& D( x3 K4 }- {BMDP(Biomedical computer programs), BMDP统计软件包
/ U p* g3 E4 Y2 ZBoxplots, 箱线图/箱尾图
! ^& Z L, V1 {( U% _Breakdown bound, 崩溃界/崩溃点
6 {" [. H. n9 j0 N! ~6 h& ?( g+ \8 UCanonical correlation, 典型相关
$ Z8 q: {7 m) W1 p, E# JCaption, 纵标目
% D2 e; K1 |! ?, }( f( `& ]9 ?9 xCase-control study, 病例对照研究0 Y' o* \9 o$ N1 E4 Y! S
Categorical variable, 分类变量
0 O2 O( x8 a |Catenary, 悬链线 j0 s) R) b2 w9 d8 z' N
Cauchy distribution, 柯西分布6 m# k$ x+ x I) f* D
Cause-and-effect relationship, 因果关系
8 O6 Y8 b q9 x9 NCell, 单元
- b- i5 ~& e3 _* d5 HCensoring, 终检4 z+ d3 l$ I- @. z0 c5 ^1 X$ `: e
Center of symmetry, 对称中心$ [ F# q, D6 o' G& f
Centering and scaling, 中心化和定标. a/ h- a2 a2 i l5 ?
Central tendency, 集中趋势1 {1 @9 R( O" w5 ]9 o' c8 d {
Central value, 中心值
) S9 `) Q( o* a4 ?CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 h* P4 @3 Z6 U i
Chance, 机遇3 V1 v6 h; L+ ?; C; y3 d& h
Chance error, 随机误差
/ F3 e: Q7 m* b' ~1 d' N0 UChance variable, 随机变量
; \% @; `: X. O! S9 w# oCharacteristic equation, 特征方程
2 p4 j, G6 q7 R& E$ `Characteristic root, 特征根
9 S& Q8 `6 c' @" T ]Characteristic vector, 特征向量
" ~3 h- Q7 c/ v5 Z4 YChebshev criterion of fit, 拟合的切比雪夫准则
# Z% f1 [, |1 q4 L, {Chernoff faces, 切尔诺夫脸谱图
7 D M+ C# s8 h' cChi-square test, 卡方检验/χ2检验4 m4 a7 `* V6 r) W9 b9 E K
Choleskey decomposition, 乔洛斯基分解
/ M( F7 k8 C- X2 k) ACircle chart, 圆图
' p& R9 X3 ?- F8 \2 A% G0 |Class interval, 组距5 [* s' S# i% F* p3 h, X; _ R, m
Class mid-value, 组中值
$ r5 n: F. q( p$ D2 \/ M6 mClass upper limit, 组上限$ \4 x- A# }+ o7 ?
Classified variable, 分类变量3 B/ E6 k1 A0 |1 \
Cluster analysis, 聚类分析; U: H) u, N9 r
Cluster sampling, 整群抽样
3 ^- p1 o M7 oCode, 代码
6 W' i' u' ~! J: b6 kCoded data, 编码数据6 |/ A# k! n7 X- e! b# y, Q$ l% G
Coding, 编码
, Q2 x$ l/ V7 ^3 L, [5 KCoefficient of contingency, 列联系数
t( O0 V, K1 O1 TCoefficient of determination, 决定系数$ ~' V/ k# P* \- A5 F3 e
Coefficient of multiple correlation, 多重相关系数
" M' l' J! Q% Y7 z' l3 M. C; jCoefficient of partial correlation, 偏相关系数
" X& c) d2 r/ L' q5 P* `Coefficient of production-moment correlation, 积差相关系数+ i, q7 h& y l1 L- o. F$ }: i* u
Coefficient of rank correlation, 等级相关系数
, C7 t: q; s/ gCoefficient of regression, 回归系数3 S) O! x8 t5 s
Coefficient of skewness, 偏度系数( {% r" ?, r6 K* g I/ k" Z5 C+ l
Coefficient of variation, 变异系数- `8 c( V- t" q7 ~0 ~
Cohort study, 队列研究" P! {- j6 D0 E: G
Column, 列
% F) N1 h& Y8 R# }! v/ }Column effect, 列效应
- V2 [! d& t# ]. H# B, lColumn factor, 列因素6 Y7 j$ C- q, l7 u. [! p& z- U
Combination pool, 合并
' v9 t7 [; G* H7 PCombinative table, 组合表6 m( l) A2 A( J! u4 L9 \' B, C
Common factor, 共性因子( H# R4 F$ H0 P* `$ E8 w* _
Common regression coefficient, 公共回归系数6 Z' d$ p3 s6 f
Common value, 共同值
5 }0 V2 v2 H& W" A7 a1 }/ PCommon variance, 公共方差$ o0 @0 c7 O1 j7 z
Common variation, 公共变异( P* O0 y3 T$ L- U$ z
Communality variance, 共性方差7 p7 e1 C' Z# I" Q) {
Comparability, 可比性
( ^- h3 S2 ?' D+ o' WComparison of bathes, 批比较, B& H3 d* o) z% w% S" o- V
Comparison value, 比较值
' Y9 U" n0 Z9 m1 i3 ?* dCompartment model, 分部模型
2 D2 g/ V( H; m' t: d! gCompassion, 伸缩( j8 L0 S4 `5 P( i. l4 f5 [/ Y+ h
Complement of an event, 补事件
/ h, T5 j1 _ D% zComplete association, 完全正相关
9 r. b$ w) q: _8 T3 T: {Complete dissociation, 完全不相关- u' D: ^+ M h1 S- v4 {
Complete statistics, 完备统计量
' N+ P+ r7 l+ eCompletely randomized design, 完全随机化设计
. w/ J7 Q( m9 V g$ `Composite event, 联合事件
; b1 p/ l; D% `+ v% M/ `% cComposite events, 复合事件
. W ?0 E- _$ X: N' E4 I' D) PConcavity, 凹性
- o: L0 M! A# gConditional expectation, 条件期望' g+ ^/ O; P v }% o* g( R& r
Conditional likelihood, 条件似然! I! K9 d' I8 x9 z1 e
Conditional probability, 条件概率
a7 Z+ Z: O; m) g( RConditionally linear, 依条件线性& c4 q0 \0 K% A3 `1 M0 F9 C( |
Confidence interval, 置信区间
: m; V2 F! h8 z7 ]2 d$ ^* {Confidence limit, 置信限; Z8 ^3 W$ n6 s9 `
Confidence lower limit, 置信下限" [+ d8 R# T2 E) S) M2 D
Confidence upper limit, 置信上限
1 z I9 l! ~' L+ K' W. iConfirmatory Factor Analysis , 验证性因子分析
8 G! n$ Q' V) \! z: @7 V; DConfirmatory research, 证实性实验研究
5 ]0 z9 e, ]4 \% y. Z( C2 RConfounding factor, 混杂因素8 \: ]$ G. v0 c) z
Conjoint, 联合分析1 }# P% B1 ?1 H* Y6 C7 l, J
Consistency, 相合性
1 U9 T" y) Q3 KConsistency check, 一致性检验$ b2 b- c9 B/ X/ j
Consistent asymptotically normal estimate, 相合渐近正态估计* j8 b9 @: K. f& S$ C
Consistent estimate, 相合估计
5 S8 [1 y1 A* n" ?& u2 V$ ?. [Constrained nonlinear regression, 受约束非线性回归- s% `0 H$ A% K4 u
Constraint, 约束; P9 P: L9 o1 j' h: j6 F; \! n' B
Contaminated distribution, 污染分布
) v$ L6 [+ B# }+ ]Contaminated Gausssian, 污染高斯分布
C/ h* F$ }, X5 i( s; z2 J- e/ h4 MContaminated normal distribution, 污染正态分布+ @1 Y$ `+ r4 q6 t1 l
Contamination, 污染
1 _; X) y* h3 D p: v" E$ z4 BContamination model, 污染模型 Z9 J3 u& C" H
Contingency table, 列联表
: c5 _/ U0 V Z/ s# gContour, 边界线$ U. f8 @9 Q' @6 r; G& B r( t
Contribution rate, 贡献率* U$ N1 c$ g+ G9 ]) H. [
Control, 对照
3 q7 j: n1 S7 A9 a! |) E9 g9 Q% _4 eControlled experiments, 对照实验
4 K, C! }7 m8 o5 b& \ L% s' `Conventional depth, 常规深度
( k# z+ h& ^) [$ }$ gConvolution, 卷积8 O( d/ }0 J; {$ n! c
Corrected factor, 校正因子
. b& y* Z0 ?. n& h3 J2 K3 ~& tCorrected mean, 校正均值; ^/ H/ ~. Z1 O1 U( D' Y+ X
Correction coefficient, 校正系数+ _* B' X! |# ^. X0 Z
Correctness, 正确性
# g7 l2 O o5 I3 p. G; ACorrelation coefficient, 相关系数
" P& t6 R" w$ D+ N# K9 S6 n+ nCorrelation index, 相关指数5 f/ D6 [# X1 j2 i$ }, |+ l
Correspondence, 对应1 P1 T. l8 X9 Q: v& P
Counting, 计数
& b8 W4 M* n6 l$ h/ sCounts, 计数/频数* T+ H/ W- o8 I0 }* D3 b
Covariance, 协方差
5 X O# D/ e; ?Covariant, 共变
/ S; |' V, A x$ N0 v* R( v1 mCox Regression, Cox回归, y9 Q r% T n# V' s& ?" ?; A
Criteria for fitting, 拟合准则# H- B L* T0 _% _5 c2 p- R
Criteria of least squares, 最小二乘准则
. l# Z7 t; `# R2 G5 s: X/ |Critical ratio, 临界比- j# v* ?5 S* O. E' I* k
Critical region, 拒绝域% X: I g# ?( F# x
Critical value, 临界值0 N4 {, d; Y, h7 `: R4 c$ Q
Cross-over design, 交叉设计' w2 [, N6 @! l9 x/ c
Cross-section analysis, 横断面分析. n- Y& l; e0 V# U+ F% A
Cross-section survey, 横断面调查
3 ?2 P* G$ F7 l2 A/ I/ Z- k" ?7 E+ gCrosstabs , 交叉表
" @( M' ]; w) g6 wCross-tabulation table, 复合表; e% X7 O, A; t! w o( P7 \, L
Cube root, 立方根
% ~& p( r: X" T0 rCumulative distribution function, 分布函数
3 D/ U# d8 H! t; y, L( uCumulative probability, 累计概率* O7 p+ d6 m5 c- |
Curvature, 曲率/弯曲
( W' X6 H7 u- u9 X2 `2 I' }Curvature, 曲率
- D! w% {. w/ I" WCurve fit , 曲线拟和
+ ]' P: w/ |; w' m/ ?. nCurve fitting, 曲线拟合$ c5 ^) c- w$ z( w" M
Curvilinear regression, 曲线回归
/ B2 C8 D+ F- X8 E2 {Curvilinear relation, 曲线关系/ Z' y' H# i/ i) u1 _
Cut-and-try method, 尝试法0 d1 ]1 s1 n/ o& Q$ U# U
Cycle, 周期 C2 r/ X, t4 v# E
Cyclist, 周期性3 {1 ~4 l3 y' G5 r! S* k) {+ g! V2 e
D test, D检验
. V+ a X& L2 [5 C% W8 [Data acquisition, 资料收集% q7 W, }/ X. q1 a; I: C
Data bank, 数据库# `. E3 R6 _" q
Data capacity, 数据容量
- M/ T* [4 B3 vData deficiencies, 数据缺乏9 ]. y- t5 S, ^5 u3 F8 f
Data handling, 数据处理
5 r3 B% {* O# `5 W. d1 Y0 f2 ]0 S2 GData manipulation, 数据处理8 Q3 x& F* G1 ?: B( L8 M7 B
Data processing, 数据处理4 a& B& G: s3 J! e; H' \- y0 M
Data reduction, 数据缩减7 l" O1 B5 f& @* q! ]% n
Data set, 数据集* x: {* ~3 i5 X8 ]# k7 X9 J7 ^1 ~
Data sources, 数据来源5 V) D1 o! G# M( n$ x$ W6 m" \& g
Data transformation, 数据变换: k& J! |* a0 ?, A0 \- V/ Q: _$ K
Data validity, 数据有效性8 j' o2 c, J% _
Data-in, 数据输入
1 w8 R7 k7 x+ ]& i5 FData-out, 数据输出
3 s* Q( A6 E& YDead time, 停滞期
q2 T, J' o: I& N0 kDegree of freedom, 自由度
+ @2 u+ E; [; w( F5 L sDegree of precision, 精密度# \$ C6 R/ n8 g% v
Degree of reliability, 可靠性程度( v& C% H6 S! b g# a
Degression, 递减
9 J1 i( r+ z8 QDensity function, 密度函数) U# J: I4 R6 O" r
Density of data points, 数据点的密度
, W" t! _( }# Z' `Dependent variable, 应变量/依变量/因变量- t; ?% o2 {: L) p6 A
Dependent variable, 因变量
! E* ?0 _& _( b6 C8 i2 eDepth, 深度
+ f0 K$ z; ]- DDerivative matrix, 导数矩阵
# q9 J! \, y/ e7 d ODerivative-free methods, 无导数方法
5 Z' K3 w$ v" t$ xDesign, 设计
1 {, U' B$ z- q* PDeterminacy, 确定性. k8 g& E4 Y- a
Determinant, 行列式# \: u3 S1 H* e- ^
Determinant, 决定因素! j9 G' n- {5 S, I& w
Deviation, 离差
, N* B7 k& b8 W3 V1 D, k3 TDeviation from average, 离均差) v( D; ]1 S0 R: l# f$ Y# m
Diagnostic plot, 诊断图
% ? H) U& D6 x! x5 P' V3 h. qDichotomous variable, 二分变量3 U* k: D2 w/ i. G# t; u
Differential equation, 微分方程7 O# E( A6 f4 q3 E+ S# Z* `
Direct standardization, 直接标准化法+ ]+ \5 ]. J9 K% U" K8 W
Discrete variable, 离散型变量! h% s9 Z% j5 _- s# a$ s
DISCRIMINANT, 判断 , I9 P% u2 J4 o8 w& f
Discriminant analysis, 判别分析4 [( C# f. Z a9 H% z d
Discriminant coefficient, 判别系数 o$ p) X+ i2 Z& E. {" {+ Q; m
Discriminant function, 判别值" I0 _- ]$ z' B
Dispersion, 散布/分散度
" X" O4 ^* _5 c* B' RDisproportional, 不成比例的. j6 A, ?3 S( B8 B0 ~
Disproportionate sub-class numbers, 不成比例次级组含量% |- A x q3 m! n. K8 |7 z
Distribution free, 分布无关性/免分布
- [) N' a: ]7 G; {& VDistribution shape, 分布形状
0 I9 H2 j+ i" n+ K' Q rDistribution-free method, 任意分布法* ?0 Q# [$ Z1 V* G
Distributive laws, 分配律
/ L! D6 Q: l- q4 i: p4 B: {Disturbance, 随机扰动项% \1 C$ w" z+ e9 [! [; I/ x3 \
Dose response curve, 剂量反应曲线
2 J9 Q7 R1 L5 ]/ P- _) ?Double blind method, 双盲法
: ^" A: a+ y0 d6 a* I$ EDouble blind trial, 双盲试验 A; k- O" c: @% e* \- w
Double exponential distribution, 双指数分布 {6 \' v+ S! L9 h; p& y# _
Double logarithmic, 双对数
2 k8 y6 x; G" @$ XDownward rank, 降秩
! _, a) T9 s. W1 JDual-space plot, 对偶空间图+ k9 }! N7 g4 z, m
DUD, 无导数方法2 Y" ]5 D$ }. K2 \4 @" k$ ?
Duncan's new multiple range method, 新复极差法/Duncan新法
+ ^( a8 h0 R1 }Effect, 实验效应# }' i8 h7 P/ ?: e
Eigenvalue, 特征值2 ^& O& N/ R& b& C
Eigenvector, 特征向量; f' M# N a0 e- p" O1 g
Ellipse, 椭圆
* g1 M" c( i5 E1 _5 p( j' a/ O4 ?Empirical distribution, 经验分布
3 t9 t1 w% X* VEmpirical probability, 经验概率单位
# n8 ]7 n; _8 l" ~' s) bEnumeration data, 计数资料
2 ]7 f+ \( y1 M* H6 U/ W1 kEqual sun-class number, 相等次级组含量
! L% O& b# l: S, \) I6 UEqually likely, 等可能! a4 r! B8 g1 T) ~
Equivariance, 同变性
' `) T: x8 H$ h9 T( u, W! NError, 误差/错误9 l5 z. v3 Y/ ]$ U' ~0 l5 X* s! I
Error of estimate, 估计误差
: }8 x4 o) P8 qError type I, 第一类错误
. i/ D4 A: C3 kError type II, 第二类错误! k( b" U6 c# D/ K$ A% _
Estimand, 被估量
/ P4 k) m& d; y# `Estimated error mean squares, 估计误差均方' L' h7 Y, S3 w
Estimated error sum of squares, 估计误差平方和
) b& |5 t0 D( Q; K3 X% nEuclidean distance, 欧式距离
- u) S* g: \6 _4 g! d* a, BEvent, 事件+ V2 {; ]9 s/ R2 U
Event, 事件
" h: p9 Q) K( d( p+ ?+ AExceptional data point, 异常数据点
0 ?2 ~8 ~3 _3 A. [6 y9 b/ v) TExpectation plane, 期望平面
& s- r5 W/ m: o% gExpectation surface, 期望曲面
9 K* x' B4 ]9 E7 ]Expected values, 期望值# Q" u$ m' _, ]; {4 F1 G/ H# _
Experiment, 实验9 G4 U1 ~2 X9 d7 W
Experimental sampling, 试验抽样
3 n! F- c! t% R! rExperimental unit, 试验单位. m+ s. L! J9 N4 a7 ?" k+ y' F
Explanatory variable, 说明变量
; e0 S6 \4 b7 h: N2 }) y5 }Exploratory data analysis, 探索性数据分析 p4 I* ~% N5 ?1 F# t3 D
Explore Summarize, 探索-摘要0 m: _! t$ o3 B' L( Q$ O
Exponential curve, 指数曲线7 l1 k: V N; E+ z1 x" @7 I
Exponential growth, 指数式增长
& u2 p9 e8 E0 X4 V, b7 f, bEXSMOOTH, 指数平滑方法
% s' J2 A. a$ ?( zExtended fit, 扩充拟合
' T) y) X8 }& N& p4 d/ `9 x XExtra parameter, 附加参数
" S/ @" v: H& m& aExtrapolation, 外推法2 o7 j5 I" `! I5 H& i/ S6 x% p" c6 V
Extreme observation, 末端观测值* n+ P) V$ F$ O/ \
Extremes, 极端值/极值' i8 T c$ j" J* p' t3 G$ Q# y6 a
F distribution, F分布. V; {' b( b& v, I( d2 \+ ^" I* s, v
F test, F检验
# g- t; T* M9 T4 {: IFactor, 因素/因子
$ j) [5 x. M0 t }( aFactor analysis, 因子分析
. [8 _7 ^* A$ a- E' k1 _; TFactor Analysis, 因子分析
6 K" ]) U& {' u) z {- F' dFactor score, 因子得分
: G+ G1 l4 `8 SFactorial, 阶乘
5 h) {1 Z8 s9 f. C# m8 h/ uFactorial design, 析因试验设计; ~* Z9 ^% A W- `& e3 A
False negative, 假阴性
! v4 {+ y5 S; m3 E) M' p7 o' DFalse negative error, 假阴性错误
2 A7 K' ^% y6 Z0 a" `Family of distributions, 分布族3 m, z& p, O- o: r
Family of estimators, 估计量族
5 s$ {7 }% S" L) aFanning, 扇面) D# [" T. A3 S+ y
Fatality rate, 病死率9 P" k8 N2 [+ D/ ?% E$ ~
Field investigation, 现场调查- W0 ] q1 t. I- G3 W5 i
Field survey, 现场调查! B% {3 _6 Y8 o. U# ^/ e2 I2 p
Finite population, 有限总体% R d% F$ M, V0 Q% @
Finite-sample, 有限样本8 c7 K& m0 N% ^! |$ |* w
First derivative, 一阶导数3 [, Y3 M" g( {- a! O
First principal component, 第一主成分
/ W" z: K- v) T; GFirst quartile, 第一四分位数
/ \4 x' E+ V( i1 k3 _7 fFisher information, 费雪信息量
0 X* n b, B; u `! q8 kFitted value, 拟合值. b+ i8 ]% @) T/ t0 P9 U2 g
Fitting a curve, 曲线拟合! r4 h/ L$ M, [3 N7 N: k# V8 l" R
Fixed base, 定基
" m2 i0 J2 {0 @! FFluctuation, 随机起伏
9 _1 O, _, [9 _ J$ V2 j; \Forecast, 预测, m4 X) b! |! j1 D; l! x, |1 S
Four fold table, 四格表
( I# I6 L& E3 G2 VFourth, 四分点
6 M5 q3 f8 v. W) uFraction blow, 左侧比率
5 c4 u0 C% v+ x4 zFractional error, 相对误差* [+ O: {6 n3 M$ t
Frequency, 频率8 z) q' K5 c5 n8 o2 o2 ~* B
Frequency polygon, 频数多边图
^+ o- a0 y) G' W- [5 ~Frontier point, 界限点
: l" w- A( I; MFunction relationship, 泛函关系) Y. B$ e6 D( D
Gamma distribution, 伽玛分布8 \: e. p! d( _5 ?9 k7 D$ B' j
Gauss increment, 高斯增量+ v/ A, \8 d& U" F
Gaussian distribution, 高斯分布/正态分布& e: \% e) \" E x G# M6 ?$ ^
Gauss-Newton increment, 高斯-牛顿增量/ R- J5 b B% X" y
General census, 全面普查
* e9 N% Q( y8 v# T+ `+ F# GGENLOG (Generalized liner models), 广义线性模型
9 D! X- c8 c0 _7 C6 j. q0 O, n* [+ EGeometric mean, 几何平均数
8 K( p$ e4 O/ i- [1 @0 s9 @6 d+ q) ^Gini's mean difference, 基尼均差
( a9 j" {" i! l! BGLM (General liner models), 一般线性模型
( q4 q8 g' L4 B0 |0 C" K* _3 nGoodness of fit, 拟和优度/配合度1 p% m$ q4 N5 m* ~5 T0 W
Gradient of determinant, 行列式的梯度0 q8 B( c9 o, J
Graeco-Latin square, 希腊拉丁方9 S. Y6 Z! {0 t1 F3 s
Grand mean, 总均值2 N( ]% `* U5 w. a! {0 T; c: B, j+ \
Gross errors, 重大错误
7 K. o( h, A4 q- @; p* H# i0 |Gross-error sensitivity, 大错敏感度
* u6 l" K3 A+ J0 r. wGroup averages, 分组平均
6 e1 {8 t$ b# Q, uGrouped data, 分组资料* |5 Q) {8 g: C4 s8 @2 C/ P
Guessed mean, 假定平均数
5 y4 t* E3 k* i* q; E8 q6 f+ d t& ZHalf-life, 半衰期
; s* M' R. g8 l: C( Z" @ u' }Hampel M-estimators, 汉佩尔M估计量9 u# I% K9 x% G+ D" L" E% M
Happenstance, 偶然事件. j4 C* Z; A+ R/ Y& g
Harmonic mean, 调和均数6 l, M4 v) ]) s: [& Y |4 H+ H
Hazard function, 风险均数
; e. W$ b9 u3 C* f3 n5 _$ UHazard rate, 风险率: z/ _. f i8 `, n8 ?+ A; a" _
Heading, 标目
$ Z& D+ Q$ \- d( q, U+ c5 _2 }Heavy-tailed distribution, 重尾分布* h% Q4 t+ o7 b5 n
Hessian array, 海森立体阵; P F# y* A6 G, t: {9 f- \3 {
Heterogeneity, 不同质9 N! z, E0 z7 { g
Heterogeneity of variance, 方差不齐
! V3 a8 {7 ^/ P' j, XHierarchical classification, 组内分组
$ R0 F- @0 ^8 o' t4 T3 HHierarchical clustering method, 系统聚类法
7 R q b) n! ?5 e2 {2 ?High-leverage point, 高杠杆率点1 w4 \# u- H* i3 n5 ~
HILOGLINEAR, 多维列联表的层次对数线性模型
. i( _( O/ F9 L- N$ B8 {: `8 aHinge, 折叶点
0 C+ q- h7 O/ GHistogram, 直方图/ Q( s( K7 V. t+ I; { d' }
Historical cohort study, 历史性队列研究
2 U& j* E& ?4 [& V# ~6 k7 q, yHoles, 空洞5 f2 h+ T7 {* K4 F6 B3 @0 \3 ]3 v' {
HOMALS, 多重响应分析 p4 X) Z' z, D* Q
Homogeneity of variance, 方差齐性3 S1 u. a# b! l3 |0 ^
Homogeneity test, 齐性检验
) X* W' ?9 \" A. L+ OHuber M-estimators, 休伯M估计量
6 [8 L0 P/ P0 uHyperbola, 双曲线7 V# i1 L6 O2 V( V2 P) v) t
Hypothesis testing, 假设检验
+ A8 a1 Z" \6 X. E3 wHypothetical universe, 假设总体
" ?' \: E5 b7 d- NImpossible event, 不可能事件! E; a4 Y# O5 j8 m! Y: W% ^; O
Independence, 独立性9 B# N. I6 i7 n6 ~
Independent variable, 自变量
# t% E, r+ F, e3 oIndex, 指标/指数
; M0 W- O+ J3 E; I; o }* L5 T% n& xIndirect standardization, 间接标准化法
' C" p% _* M6 I- B0 D: p* f$ j2 FIndividual, 个体
8 I5 H! o' C! I/ ]$ J/ U- L3 A4 rInference band, 推断带9 E9 d% I, z. N7 g; O. l
Infinite population, 无限总体
3 {, R& g+ v& u. E' W6 O: g3 b% [Infinitely great, 无穷大
% h. O! \. o1 MInfinitely small, 无穷小: Z5 k3 q. `* l* |
Influence curve, 影响曲线6 V: D9 z: N+ G! C, z# [5 K) J2 I5 w4 a
Information capacity, 信息容量
, |/ L1 z* b0 d; gInitial condition, 初始条件4 l& B% t, h9 }% g+ R: n
Initial estimate, 初始估计值
- H& q3 v/ ?( Z/ }/ v6 O% cInitial level, 最初水平# c! p- B$ F- A; ^0 K6 l
Interaction, 交互作用
, T: {# k; g6 R9 E; `/ F& u. ~' ^Interaction terms, 交互作用项
$ x! _, ?" `# F$ b0 KIntercept, 截距+ ^6 s z; P( {8 S4 L8 s/ V8 P
Interpolation, 内插法
& d/ b3 W" |' w1 wInterquartile range, 四分位距
' K" D1 b6 G, q/ r; |Interval estimation, 区间估计
+ |5 {! f5 m# PIntervals of equal probability, 等概率区间
4 ?, w- ?0 |3 d0 g2 bIntrinsic curvature, 固有曲率& P# z. Z- l- c5 E, T. P" H6 n
Invariance, 不变性8 k. H7 R" \8 Y/ z. m
Inverse matrix, 逆矩阵
% X( E8 m9 K6 a$ BInverse probability, 逆概率
& v8 j% z0 G1 g, v( `. Z; s% _Inverse sine transformation, 反正弦变换; l! ?2 ~1 L- j% s9 ^" g2 b5 G. H
Iteration, 迭代 7 K- m' Y8 h, F; A# T
Jacobian determinant, 雅可比行列式1 U1 d7 N3 g: U6 q" \
Joint distribution function, 分布函数
6 r/ X4 }: q0 B: s$ F7 KJoint probability, 联合概率) S; p$ D( r, H6 A x
Joint probability distribution, 联合概率分布
: G* k0 E* p( a w4 `: u8 ?1 Q5 VK means method, 逐步聚类法
0 f5 c* O; w m5 s3 P2 W! I5 f" HKaplan-Meier, 评估事件的时间长度 4 N3 Y) v* {1 m' `1 q7 M. C- I$ X
Kaplan-Merier chart, Kaplan-Merier图4 H5 b8 B; W2 u* `& y& l
Kendall's rank correlation, Kendall等级相关! v. h) m6 t. i' w& w$ d
Kinetic, 动力学
. F" ?$ N9 [7 E5 F' g* A! x+ aKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
% ?+ N& K+ m/ R% }6 g7 _Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 a( x- v( H0 A8 `$ R
Kurtosis, 峰度
+ U7 _/ T9 ?: a6 R8 uLack of fit, 失拟
T2 v$ f% o5 ? n! iLadder of powers, 幂阶梯
! U8 U% Y6 K7 ^+ `% R r2 XLag, 滞后3 \2 Z" U9 j1 M- i6 ~: j
Large sample, 大样本, b8 s2 ]5 U# @# W7 E& j6 ~
Large sample test, 大样本检验# r; e6 q* s6 L. }
Latin square, 拉丁方
+ N. c, i8 v+ ]$ g+ x P2 l4 yLatin square design, 拉丁方设计( R' d; c3 u5 N+ E, g
Leakage, 泄漏
1 d' |* P8 j+ y( c. s- zLeast favorable configuration, 最不利构形7 F& I' ^8 V+ w
Least favorable distribution, 最不利分布: I: C K" q# S, |
Least significant difference, 最小显著差法
: k! U& k. _% CLeast square method, 最小二乘法0 H/ Q0 T& | J& Z& }
Least-absolute-residuals estimates, 最小绝对残差估计% Q `" O4 t- x! V
Least-absolute-residuals fit, 最小绝对残差拟合
+ z5 \/ i& ? o1 v3 U% H ULeast-absolute-residuals line, 最小绝对残差线% B; o8 r/ o: `# t" }
Legend, 图例
! n. z4 }8 {; m3 U. M, RL-estimator, L估计量
' D, U+ R- u9 u0 A4 q2 nL-estimator of location, 位置L估计量
7 D+ y& x5 X& ?6 g) m6 sL-estimator of scale, 尺度L估计量
; k& n8 x r/ K1 s* v/ H( eLevel, 水平0 b" g) h' I, \
Life expectance, 预期期望寿命1 P" f _3 B5 ?' x# v# S
Life table, 寿命表
0 d I8 r' Q7 Y+ \Life table method, 生命表法
/ ~+ s$ T* H' c; g* }Light-tailed distribution, 轻尾分布5 e4 N2 H$ L% O& m. T9 a
Likelihood function, 似然函数/ B( o4 |+ u' Q. l+ i Y; |- ]. P
Likelihood ratio, 似然比* W& v) [9 F* q0 f" @8 N
line graph, 线图; d- `# P* L: N
Linear correlation, 直线相关
7 x- j1 K2 y* V) c; O0 q! TLinear equation, 线性方程3 q" H s) k4 c7 y
Linear programming, 线性规划
+ Z, K/ i( p* J% W0 N* G: YLinear regression, 直线回归0 B; ^0 h4 _9 N6 o' a- W) }3 [
Linear Regression, 线性回归1 M; z) q. n( J- @; s
Linear trend, 线性趋势" ?# {$ s1 k& q- \& S; M0 _
Loading, 载荷 2 }* n/ X. m% _
Location and scale equivariance, 位置尺度同变性
6 e) i2 C0 @2 Z* s, h8 C& ~Location equivariance, 位置同变性" o4 ~: y2 |1 f$ W
Location invariance, 位置不变性
. O/ @0 q& j8 cLocation scale family, 位置尺度族
0 P2 w: O, N1 q: o9 Q# GLog rank test, 时序检验
% `& y! P9 \4 S- S& pLogarithmic curve, 对数曲线
4 @' _/ Z& q7 `& Q9 LLogarithmic normal distribution, 对数正态分布% q X9 @8 g" u _
Logarithmic scale, 对数尺度* F+ q* x" R# a! z2 H) b- V
Logarithmic transformation, 对数变换# |( x: \) X5 m2 Z6 H
Logic check, 逻辑检查9 Y3 [! N* F5 h6 ]' |4 B7 c: `" X
Logistic distribution, 逻辑斯特分布
# ]2 o- z* V3 [- z" k5 JLogit transformation, Logit转换
1 D3 h+ i' g0 vLOGLINEAR, 多维列联表通用模型
/ i6 R. w- F j" g6 lLognormal distribution, 对数正态分布
+ ?( z. a9 C- R8 A, f4 MLost function, 损失函数, m' \# y$ g7 _7 Q, s
Low correlation, 低度相关
; N1 u( Y$ \* V6 @Lower limit, 下限
2 \6 u. C$ X& D/ i. c& E+ LLowest-attained variance, 最小可达方差
# w2 N6 G {; G& b' R3 kLSD, 最小显著差法的简称
. a+ h3 I: Z: b* ~" o8 bLurking variable, 潜在变量: f6 I: l- D3 q [* g5 q% [* q
Main effect, 主效应/ l4 O3 \: f/ l
Major heading, 主辞标目
' J3 v+ a- C5 @, v4 SMarginal density function, 边缘密度函数" Y3 A' E% R. M" Q
Marginal probability, 边缘概率8 O" M6 q/ s W [1 |) W' g' Q
Marginal probability distribution, 边缘概率分布! L; d, x$ ?! k# v' S$ ^0 M: T
Matched data, 配对资料
: k& q |0 g6 o5 dMatched distribution, 匹配过分布 V9 q }/ |: x' b& G4 u5 k
Matching of distribution, 分布的匹配
: X6 N/ K' m, ~2 ?% c4 d4 M/ d% [Matching of transformation, 变换的匹配
& i& q5 F+ V+ n: V$ ]; c0 w+ T# k3 d, PMathematical expectation, 数学期望
3 [$ O, l' x3 P" Z( h, nMathematical model, 数学模型
% d# u' k: H( N! zMaximum L-estimator, 极大极小L 估计量8 { C7 [9 T+ P8 R9 f
Maximum likelihood method, 最大似然法
! j& l+ Y& y/ @Mean, 均数( o! n" t5 ^! n2 r
Mean squares between groups, 组间均方7 U8 n6 I# u+ B6 c
Mean squares within group, 组内均方8 O1 S7 `7 Y' o3 r6 i
Means (Compare means), 均值-均值比较( N' L* i+ `: n0 D
Median, 中位数2 ~4 \* y7 y: @
Median effective dose, 半数效量
% o9 y& k1 J1 o* p& ZMedian lethal dose, 半数致死量
0 N! j' b' k7 FMedian polish, 中位数平滑
9 Q) q* F1 R* E: ~( ?Median test, 中位数检验
9 {% |* y# a4 _% p- u) m' OMinimal sufficient statistic, 最小充分统计量
4 T% P1 P" o$ @9 C5 P$ O- L YMinimum distance estimation, 最小距离估计' r8 r( X; K( S. [0 W' Q
Minimum effective dose, 最小有效量: \9 M7 c4 l" C4 h
Minimum lethal dose, 最小致死量- _: p6 I! g& D8 t" f
Minimum variance estimator, 最小方差估计量
! s- ~: k# t+ X, i; nMINITAB, 统计软件包' @* ~5 [/ i& r6 ]
Minor heading, 宾词标目
9 v! k$ d O! O6 }1 J5 J" Q$ e- lMissing data, 缺失值
! F8 D. B! v8 cModel specification, 模型的确定. s" a+ W t7 A
Modeling Statistics , 模型统计, ^0 [, \! a% S1 x+ u# p' r7 N. X
Models for outliers, 离群值模型
) M; E- k$ B* F1 j* t' n. l1 FModifying the model, 模型的修正6 o' I1 P9 s" S# P( G& V
Modulus of continuity, 连续性模- l1 Z4 l+ Y, {4 O. m+ ]; _
Morbidity, 发病率 7 @- M. P" a6 ]; v4 l& x
Most favorable configuration, 最有利构形( L3 g$ ~3 M/ z, E
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
8 s1 T/ k: M5 I& Z; ZMultinomial Logistic Regression , 多项逻辑斯蒂回归6 m' y% D2 O$ ]% `6 @
Multiple comparison, 多重比较4 D5 i# f J" u
Multiple correlation , 复相关' ?$ h4 z- A8 l6 b6 S
Multiple covariance, 多元协方差" e9 I$ M O0 L! S T$ l
Multiple linear regression, 多元线性回归
: |7 G, Q% c+ V( t0 WMultiple response , 多重选项
) |! |. L* c3 D7 tMultiple solutions, 多解* o/ n% x1 _8 ?7 [9 Z
Multiplication theorem, 乘法定理
/ }# P* u+ ^' {0 e$ }0 d8 r! qMultiresponse, 多元响应+ r" i F, x' @# d/ U- d
Multi-stage sampling, 多阶段抽样
4 h. ~- T' }8 o% B. _Multivariate T distribution, 多元T分布
$ R! D9 i- P0 Y) g, x- FMutual exclusive, 互不相容, ^$ X- e# E9 p5 |$ u
Mutual independence, 互相独立* C7 [+ C; x W0 Y- W
Natural boundary, 自然边界
3 k3 X$ f' d2 X/ yNatural dead, 自然死亡1 Z* C L' F* q# E s3 @5 {: E
Natural zero, 自然零: ?6 L5 y R0 o' p
Negative correlation, 负相关
7 o7 M5 K G8 s3 MNegative linear correlation, 负线性相关
, V3 \; W9 `% Y' d: t, \Negatively skewed, 负偏9 O7 T7 O+ X3 {$ `7 v* K. P
Newman-Keuls method, q检验* B W+ T: b; `# w& Q6 x
NK method, q检验* G- @/ w6 R4 i& @# ?2 H6 i
No statistical significance, 无统计意义. ~, M B9 n2 }: ^* M
Nominal variable, 名义变量
" W3 c: c" V4 ]5 D$ x' I0 Y4 ^$ o5 RNonconstancy of variability, 变异的非定常性; c1 I* d/ F5 S7 w% G# Q' ?6 N
Nonlinear regression, 非线性相关 M j4 G* a3 l" C$ R0 U
Nonparametric statistics, 非参数统计4 s) ^: y' v& J' q! [( ]% T) o
Nonparametric test, 非参数检验
5 k# c5 e1 G5 {" ^( ]3 y% X0 i7 [Nonparametric tests, 非参数检验' U3 e; L$ w- D$ F0 z) w6 q- {5 q$ J
Normal deviate, 正态离差
; J, k ]# j2 P& Y; h9 @% o8 H( WNormal distribution, 正态分布3 t5 A: l1 f8 M' X/ s9 b
Normal equation, 正规方程组
( f3 _' i9 i" b1 b5 e# d7 l/ ^Normal ranges, 正常范围/ P% G+ Z3 h7 x; u) l- x
Normal value, 正常值9 z3 @' p2 z) I# I* a j+ m( C+ {
Nuisance parameter, 多余参数/讨厌参数
, C+ J9 d3 E! l6 C1 v/ ANull hypothesis, 无效假设 % @1 p8 C" q }' q
Numerical variable, 数值变量
7 T; |# _- T5 h4 N4 yObjective function, 目标函数
4 p$ b- R! B3 K% d2 e0 {- d" DObservation unit, 观察单位3 A0 w3 ]' M# D: u, D
Observed value, 观察值 N1 T& P3 B E* t2 b1 U Y# Q
One sided test, 单侧检验
' r& k! h% C$ O" {& b8 s4 l, TOne-way analysis of variance, 单因素方差分析
# `! y+ y1 q$ k* oOneway ANOVA , 单因素方差分析
' J/ ]: f9 D, w! c; g+ a3 GOpen sequential trial, 开放型序贯设计
# C; Z+ D* l% j" [$ v4 U$ o' C6 MOptrim, 优切尾
4 z, o( r% \9 bOptrim efficiency, 优切尾效率
4 U( U* f0 Z1 N! j6 w# B1 L: \. z" KOrder statistics, 顺序统计量
; I( ]1 W) q. O6 Z& LOrdered categories, 有序分类
0 ]9 G: z3 Y1 _9 SOrdinal logistic regression , 序数逻辑斯蒂回归 _! Z+ e2 g2 o8 t9 ?: r
Ordinal variable, 有序变量
$ t. `# z k% ^9 R' T' hOrthogonal basis, 正交基, q, ?5 v( q7 A: M, V
Orthogonal design, 正交试验设计; O$ [3 A( z" J
Orthogonality conditions, 正交条件 t1 [! Q; N8 v9 p8 @* F6 B5 u {
ORTHOPLAN, 正交设计
% g3 M* T) q7 C3 LOutlier cutoffs, 离群值截断点5 `" X) K% m6 u6 j {1 w/ v+ g" [
Outliers, 极端值
5 U9 _$ e* v% u5 I; aOVERALS , 多组变量的非线性正规相关
" R$ n: _" j. k. x& S& ~Overshoot, 迭代过度" s* b9 d, D4 `6 x6 O; i+ Y
Paired design, 配对设计
p7 b- y' t/ O1 J8 xPaired sample, 配对样本1 j# n0 z, J! K) ]
Pairwise slopes, 成对斜率! Q# e1 M* \9 s. f2 x* [
Parabola, 抛物线
, |- i( k' |2 j: s( N; q3 ]! |3 SParallel tests, 平行试验
5 f1 [9 J8 S, U3 X) Y* V% YParameter, 参数& r) K2 t2 p; }8 D7 H
Parametric statistics, 参数统计% f1 c% A. K0 X6 E
Parametric test, 参数检验, K7 _3 `! _$ Z$ M1 E4 h/ \' c7 D
Partial correlation, 偏相关
( Y% F$ a, ^- IPartial regression, 偏回归6 }* X1 c4 _- v# D
Partial sorting, 偏排序7 U. c& e4 i. w$ i" N2 F! p; L
Partials residuals, 偏残差. {$ d/ ^* D1 q8 ^2 i8 J
Pattern, 模式
2 ]7 Y) m7 N* Y7 v) r. g- |Pearson curves, 皮尔逊曲线/ w. M: h- m% s, y. Q4 c3 H: m
Peeling, 退层
( e' u, j4 j( |$ g' A3 Z$ V0 yPercent bar graph, 百分条形图
7 `; B. j/ x! w, v3 b- V$ C9 U2 bPercentage, 百分比* D1 r/ ?* N* |" k; E* \. b( w
Percentile, 百分位数
; u# x% d/ g5 B# y, R1 I# q, {Percentile curves, 百分位曲线4 h4 X0 \" n1 L4 K8 a
Periodicity, 周期性* p$ R4 c3 l4 ^- i4 _
Permutation, 排列
0 N2 {. d! b2 D. |4 m+ n1 d4 xP-estimator, P估计量( _5 V% r3 n; t7 O1 @) }
Pie graph, 饼图
5 c, z2 P; X4 q& S$ L, L; ~Pitman estimator, 皮特曼估计量7 l: _& ^2 I& ?0 ^- D$ t2 c6 T7 l
Pivot, 枢轴量
. i" b) c& o: ~, ?/ z* q9 W3 mPlanar, 平坦 a7 |( v# X' C$ }. Q- Q
Planar assumption, 平面的假设5 y1 z3 |9 d# g1 i: e, h6 X
PLANCARDS, 生成试验的计划卡5 i9 y6 O j$ O2 ]8 i8 j
Point estimation, 点估计
1 @) e& y. A) @& X4 T; M5 oPoisson distribution, 泊松分布
& Z4 E* U/ e7 Z7 F: L8 _, jPolishing, 平滑2 g' D+ K8 ]+ d6 G$ |. j4 g; ~
Polled standard deviation, 合并标准差
) o, [1 u. g# jPolled variance, 合并方差9 l! M6 o Y' ~/ Y1 T/ k; V0 H% v
Polygon, 多边图! X, E6 I9 |& v. K- q; U. K+ `
Polynomial, 多项式
; h9 X+ ~2 r. e% w/ JPolynomial curve, 多项式曲线# ^5 f/ |3 X, L4 w d& o* m$ d
Population, 总体
" w& G+ p! h! f) c& oPopulation attributable risk, 人群归因危险度4 a0 w9 V+ D' G$ k
Positive correlation, 正相关$ m3 S5 T! _: i0 g5 c# m
Positively skewed, 正偏* m3 i4 S4 b; t, x& K
Posterior distribution, 后验分布. A( y3 I- s. A5 }( z
Power of a test, 检验效能
+ K: X+ b7 w o t% V7 A' tPrecision, 精密度
+ ^$ _. _5 X, B) ~1 V. LPredicted value, 预测值. m" k* T5 m, h5 }
Preliminary analysis, 预备性分析
; b& l& {% f! {8 R2 d: {8 NPrincipal component analysis, 主成分分析
/ ~' [% |* a' a, J/ o( O+ xPrior distribution, 先验分布% P# u5 @/ r! ?- M/ F, C, K
Prior probability, 先验概率
; L, ]" B a0 rProbabilistic model, 概率模型
- ~0 h S+ x2 q7 b! W @probability, 概率 I6 B2 q) W8 K* G0 ?
Probability density, 概率密度
. D1 {. w. E4 a6 b# YProduct moment, 乘积矩/协方差
+ v* m3 U- @, G8 IProfile trace, 截面迹图
: \( |' t! o9 O2 o0 P/ F0 ~) jProportion, 比/构成比 |! y- b. U0 V; a, j0 h: R! I+ w
Proportion allocation in stratified random sampling, 按比例分层随机抽样6 b E5 w1 A, z
Proportionate, 成比例
8 i+ _) D) e, f7 g2 dProportionate sub-class numbers, 成比例次级组含量, _+ W1 L' g# r* g
Prospective study, 前瞻性调查% g# q5 d) B0 x6 M
Proximities, 亲近性
`6 J: {- S+ v- T: Y5 YPseudo F test, 近似F检验# o0 {+ c2 {( M. N
Pseudo model, 近似模型- T6 h9 X+ b$ L2 u3 A
Pseudosigma, 伪标准差* F- J% ]$ N# H! l
Purposive sampling, 有目的抽样
+ [5 I9 D8 x4 ~- i/ c" e. GQR decomposition, QR分解
* ?. n, b. `# p$ r9 h( tQuadratic approximation, 二次近似
; Z4 r/ v5 q& ^5 R) k" HQualitative classification, 属性分类) U. D$ X& b7 C- s) K
Qualitative method, 定性方法$ @% Z6 q: S O( }5 j+ E- Z
Quantile-quantile plot, 分位数-分位数图/Q-Q图( s, n' y% M' \, U/ p
Quantitative analysis, 定量分析0 Y; F6 Z( F6 I; L2 d5 }) a
Quartile, 四分位数
$ q1 L6 h ?; V1 w# Q5 yQuick Cluster, 快速聚类
9 i1 S' ~5 R% i% i% i. z4 fRadix sort, 基数排序
! S4 J4 Q4 C, ~* S6 l* o; o- Y- r( WRandom allocation, 随机化分组
6 D9 e$ n& |. e1 HRandom blocks design, 随机区组设计: J4 _- k8 [. n
Random event, 随机事件$ t9 I: h D" e K/ D% W: {; \
Randomization, 随机化- x! m4 U2 I$ {
Range, 极差/全距
, N+ L/ ^1 C% ^# n6 VRank correlation, 等级相关# o' i) |# O& ~% V7 G) E4 h
Rank sum test, 秩和检验. H4 H/ A2 b+ c0 Q4 m, Q+ t. e
Rank test, 秩检验. S2 K3 v. ~# k/ n5 Q) n
Ranked data, 等级资料
4 U0 t, p* Y' }+ z& t& aRate, 比率
* i3 A- L& K" S8 A& a" MRatio, 比例9 J2 s4 _6 J5 H8 Z; g& N. \
Raw data, 原始资料; y8 ^8 M. t2 X* a# ^- T* r5 c
Raw residual, 原始残差6 B6 V' S# Q) S
Rayleigh's test, 雷氏检验
% H. g4 v% f# k! W. ^: tRayleigh's Z, 雷氏Z值 ; X- h) j; S* c' ]- V
Reciprocal, 倒数! p9 o- ~+ K# W0 Q d- i3 v0 n8 h" o% r o# d
Reciprocal transformation, 倒数变换6 d( i' m# `' w9 s' P* s
Recording, 记录
/ ~( e3 ~# ?/ y, P5 ERedescending estimators, 回降估计量( Y1 Z* l! n7 R( d, w/ e+ _
Reducing dimensions, 降维5 @4 a: ^1 e7 K0 b
Re-expression, 重新表达
* B- Y' a2 y/ k) i4 H: {Reference set, 标准组
9 h% g$ s! i% z; J \Region of acceptance, 接受域
+ v. l1 ^( B! x+ r4 wRegression coefficient, 回归系数
H" U; W% ^% j6 {" J: TRegression sum of square, 回归平方和
) N: W& g7 n( \Rejection point, 拒绝点7 z9 n+ X6 `2 B) D2 C3 l
Relative dispersion, 相对离散度8 A4 ]- g, s6 Z3 l8 u5 p( M9 m# h
Relative number, 相对数( R0 ], T7 U$ f
Reliability, 可靠性
/ R& H0 s- q" hReparametrization, 重新设置参数7 s0 A9 s: |; B! S- `: W
Replication, 重复
) h- N9 F# Q d9 G' A/ UReport Summaries, 报告摘要2 [7 n% r+ \& T. m+ K
Residual sum of square, 剩余平方和) j7 F$ k4 G. B0 X
Resistance, 耐抗性
4 T& ]' n$ b! q" g1 DResistant line, 耐抗线; c8 ?) E# G+ ~) s# r9 z
Resistant technique, 耐抗技术; x% _; m2 S9 U! v' Z h# ^% }
R-estimator of location, 位置R估计量
1 N- ^; j& d9 v/ y9 ~- {6 p' iR-estimator of scale, 尺度R估计量3 H* _+ k( R: z& S& J7 Y9 [7 f% a
Retrospective study, 回顾性调查) J4 j; s* c7 F/ p/ D
Ridge trace, 岭迹$ s7 E0 ?4 \+ f) z3 ^6 }, I
Ridit analysis, Ridit分析# s1 [3 a2 i. q2 K
Rotation, 旋转
0 `" m( `0 P/ _2 T& XRounding, 舍入7 n# n( B4 i9 m0 q
Row, 行# {. T& _# K# v. K
Row effects, 行效应
' _$ B7 |2 m& Z6 l4 H9 _Row factor, 行因素, r+ ^* o9 X* V. n* s( @3 U' E
RXC table, RXC表# K- ?' k6 T: a. H
Sample, 样本
5 h* a) t2 K' P, t% pSample regression coefficient, 样本回归系数2 \& y8 Y% G/ \ F8 u; u% R
Sample size, 样本量# ~" Y- H; u8 V1 D2 k4 A; e
Sample standard deviation, 样本标准差
2 {) `8 Q% W) C& c5 DSampling error, 抽样误差
: y' K( ]* C2 E4 r6 F+ L- `SAS(Statistical analysis system ), SAS统计软件包
. B6 u6 W7 N8 { C& w' h9 a' L. i+ a$ WScale, 尺度/量表7 J) B- y4 ~6 }( o" W
Scatter diagram, 散点图
4 ]+ R* ?0 x, Z! |8 _Schematic plot, 示意图/简图0 x' M1 `* e' y: c1 ?3 u
Score test, 计分检验0 C% _ ]* |3 Q4 y" p
Screening, 筛检+ ~- O0 c. M/ G# a m1 C
SEASON, 季节分析 : z* ~ G U3 p# w8 ~, g6 a2 X
Second derivative, 二阶导数
5 i# D/ u$ P0 c$ l/ N' q; _# PSecond principal component, 第二主成分& u3 k, `4 m+ v8 l' b4 ~9 F
SEM (Structural equation modeling), 结构化方程模型
; O2 D* v. \0 s; p LSemi-logarithmic graph, 半对数图
: M& u$ m& n Q) YSemi-logarithmic paper, 半对数格纸! u* i* f5 m" K3 Q5 `
Sensitivity curve, 敏感度曲线4 l( V0 q" d4 }, D/ }" D7 V5 x
Sequential analysis, 贯序分析: H _" \3 Q2 W2 n/ Y- n% l
Sequential data set, 顺序数据集
/ z- {# S7 l) o( FSequential design, 贯序设计
) f4 s! q0 o9 q% |) k0 h+ vSequential method, 贯序法
. L1 n" q; T* k* \0 B5 f* TSequential test, 贯序检验法
8 [4 g# ^1 g1 B4 ]& XSerial tests, 系列试验1 J3 d. A1 S3 @2 I
Short-cut method, 简捷法 8 c; Y2 y: r8 {0 c& R) d! G+ C
Sigmoid curve, S形曲线
3 L$ d# `+ B. sSign function, 正负号函数
) H% z7 e/ t( @Sign test, 符号检验5 l$ N* c2 j9 t" R! B' A9 E @
Signed rank, 符号秩
; ~1 U0 p+ ^: qSignificance test, 显著性检验7 t% [; b3 X2 [4 {' _9 C4 L. Y
Significant figure, 有效数字) T& E& B& d" W8 y# q
Simple cluster sampling, 简单整群抽样1 w7 J2 t+ c, a$ x2 w% P
Simple correlation, 简单相关
! C8 J' Q6 Z4 c( lSimple random sampling, 简单随机抽样
- o( R: V8 V$ I! E6 ]Simple regression, 简单回归
0 M3 Z0 t H7 L5 K: n; s6 p% _6 D8 osimple table, 简单表
9 i* O% M$ d; _3 R1 N, l! TSine estimator, 正弦估计量8 t) ?3 m/ @/ x$ @
Single-valued estimate, 单值估计
. ^' c- X% x8 v- x. |& NSingular matrix, 奇异矩阵0 M1 Q) Q' R( G8 }
Skewed distribution, 偏斜分布3 H& H9 g5 B- X2 ?
Skewness, 偏度
2 w) Z" l. X2 r& m0 jSlash distribution, 斜线分布) m9 U( Q7 E* y# d7 z( ?
Slope, 斜率
' }9 ? l( j' n+ r( Z) s/ ], d* GSmirnov test, 斯米尔诺夫检验* L6 K! R' Y3 f( h
Source of variation, 变异来源. b. u! }( z, Z* A! S$ P4 E" D: J
Spearman rank correlation, 斯皮尔曼等级相关
9 i3 w8 X% ^; W& |# l' k+ P9 I9 XSpecific factor, 特殊因子
& d' Y9 R* u* i# z$ RSpecific factor variance, 特殊因子方差
% |) Y, n6 i$ B$ `+ i& A: fSpectra , 频谱9 c/ g8 x! Y* {
Spherical distribution, 球型正态分布# T0 I) s: `( d) I2 \2 U. [) T
Spread, 展布 S R; _, }3 [1 [
SPSS(Statistical package for the social science), SPSS统计软件包
9 H/ _8 Q5 A* f% _' R% XSpurious correlation, 假性相关 o4 b4 F7 m) L# G* V$ t3 F+ _
Square root transformation, 平方根变换
6 E/ {- t! S w8 \" cStabilizing variance, 稳定方差
9 N V/ N: a2 dStandard deviation, 标准差7 ~1 z! v6 l& m) ~% m# `1 I
Standard error, 标准误, E# ^1 g& I3 ?' b! S
Standard error of difference, 差别的标准误
6 o1 X3 I2 l* c7 v. nStandard error of estimate, 标准估计误差+ ?$ _- Q" K% ^, L2 e8 q4 y
Standard error of rate, 率的标准误
- k$ J2 g l/ E+ D. U' `& N! N: ?/ CStandard normal distribution, 标准正态分布, r+ r1 d, O6 P# {
Standardization, 标准化
5 h0 D- I* J3 E. K$ ^$ l5 RStarting value, 起始值7 l2 o4 }- o; |
Statistic, 统计量
& j$ q2 f- N9 }' O/ LStatistical control, 统计控制1 b% O& M$ q6 y2 H# @ t/ _
Statistical graph, 统计图
% k; l$ ^8 ^' h$ |2 Q0 f: LStatistical inference, 统计推断. d9 ?) o. ]+ ~( s
Statistical table, 统计表* G4 ^* P! z. ^4 n4 r% r
Steepest descent, 最速下降法5 j% p n9 \0 M; B! c- J4 G
Stem and leaf display, 茎叶图2 f1 N- f+ @+ |5 ^/ s) `/ B7 l
Step factor, 步长因子
* D; F) i7 o5 L! b6 ~Stepwise regression, 逐步回归
. z% _" n3 g7 U9 n6 ]4 mStorage, 存
% f1 Z8 ]7 a, S6 c4 FStrata, 层（复数）( W# \" n U# \/ B1 N5 V
Stratified sampling, 分层抽样- g: t9 g4 m+ O# ?5 S
Stratified sampling, 分层抽样7 I9 p' \" f5 Z/ H
Strength, 强度9 q& J2 c8 R& h
Stringency, 严密性
2 M2 j# m0 C: oStructural relationship, 结构关系5 L$ @5 y8 A- \3 X1 `
Studentized residual, 学生化残差/t化残差
3 u0 k2 m: @6 h) qSub-class numbers, 次级组含量& B f2 v1 e% }. d: N
Subdividing, 分割; E9 B( e( O! ], o
Sufficient statistic, 充分统计量# T% @* c( O ?7 k5 K1 ^
Sum of products, 积和
# v9 l/ e( }2 y8 V, {Sum of squares, 离差平方和+ I7 Q! B) j, ?+ L- Z
Sum of squares about regression, 回归平方和
5 D, V# B( `; n, c+ |Sum of squares between groups, 组间平方和6 S/ n: T: F! i4 K
Sum of squares of partial regression, 偏回归平方和% I, m8 c4 y9 _
Sure event, 必然事件
( y) O) v0 O v* J$ @! x$ T0 jSurvey, 调查4 E# n/ X# }4 w/ e6 q; ?& c; m
Survival, 生存分析1 _; M! u9 P. S$ H' j4 Y" t. J! I
Survival rate, 生存率! y a) F, K, E" C* {8 V
Suspended root gram, 悬吊根图
5 D# ^2 ^2 }8 t# }6 XSymmetry, 对称4 b) e+ U ~5 o# i
Systematic error, 系统误差" h8 Y5 o& S! e1 b* N" D# H9 E9 s
Systematic sampling, 系统抽样
% z4 O0 p3 W' B& l+ g0 iTags, 标签
& d) G, B3 G4 W# |" W& fTail area, 尾部面积' d; x3 d: |1 z$ ^. ?; _9 F4 h5 z
Tail length, 尾长) O6 {& z8 {; z8 L
Tail weight, 尾重0 V A/ B/ k' c! m4 f& W. j
Tangent line, 切线0 W q6 | h' ]8 I5 Q/ o+ ]& }3 E
Target distribution, 目标分布
- x3 ?2 ~) e* \. ITaylor series, 泰勒级数
% N# E( }4 R( I- dTendency of dispersion, 离散趋势: S! w4 U) @# c; R
Testing of hypotheses, 假设检验7 F# C( c' V% M; j7 }
Theoretical frequency, 理论频数
# t) {1 Q* E! v- STime series, 时间序列
- ~( K, N6 Q3 CTolerance interval, 容忍区间/ L1 D! |3 V% n7 z; }
Tolerance lower limit, 容忍下限, x1 f: g8 y& I& n4 \
Tolerance upper limit, 容忍上限
& _! d; v5 ^# o# H; ATorsion, 扰率/ }* O5 H$ J/ ]: e/ D- H
Total sum of square, 总平方和, ^ X! y2 E/ A( @
Total variation, 总变异" s' D o& N: }& v/ U
Transformation, 转换- h4 H3 _- B+ b1 F+ @9 O6 U: _! S
Treatment, 处理2 {. S' G4 ~3 r3 l# Q! }
Trend, 趋势
! g) W' R6 r0 d4 ?4 F' i8 VTrend of percentage, 百分比趋势" {' J1 T5 E0 X; p
Trial, 试验
d. c4 _5 e% ?* O( V. G4 @( |Trial and error method, 试错法
7 J" g9 {5 T2 g. _( l* LTuning constant, 细调常数
6 {# ~: e, E. A5 sTwo sided test, 双向检验
$ {' o" r1 } A) ~; `Two-stage least squares, 二阶最小平方" a* G3 ?; e6 R7 `2 `, N
Two-stage sampling, 二阶段抽样
& ~3 a) k* Z5 g- zTwo-tailed test, 双侧检验" I$ ?3 V4 i# K
Two-way analysis of variance, 双因素方差分析4 m$ h( F, O* B+ D2 H
Two-way table, 双向表+ j4 A; @ N3 y* w
Type I error, 一类错误/α错误- `& I0 V' K. d; P) u( q
Type II error, 二类错误/β错误: }0 T1 L* k% o; `
UMVU, 方差一致最小无偏估计简称5 y' \3 G6 v4 ~7 Q
Unbiased estimate, 无偏估计; }/ ~+ v- t' o
Unconstrained nonlinear regression , 无约束非线性回归
1 e2 {$ _6 C' mUnequal subclass number, 不等次级组含量9 |5 a$ d j6 r0 M& b! l) p" u
Ungrouped data, 不分组资料$ ^. x1 ~' A, A5 [( ^
Uniform coordinate, 均匀坐标1 A% D1 j8 ?0 ?3 ]- c
Uniform distribution, 均匀分布
5 s/ G0 {0 j' p4 vUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
2 ~5 G2 W! E9 k; f. VUnit, 单元
" [% _* d- c) N( T& lUnordered categories, 无序分类- ^& M6 u; G/ Z9 ~
Upper limit, 上限
6 t x. b6 o" a1 ^1 N2 }4 y- |, J( RUpward rank, 升秩, G( i9 u% t- M9 f% y
Vague concept, 模糊概念7 O8 I5 ]! O# a, I9 U; E( q! A
Validity, 有效性
+ u$ a" Z: }1 D7 }9 ~% q, B. w% RVARCOMP (Variance component estimation), 方差元素估计' K5 t3 v, m0 }$ N" |: [
Variability, 变异性& a4 w1 u! o% [& F$ l
Variable, 变量, i# Y0 q# p& f7 g1 H" F# c
Variance, 方差% ?: y4 |& |1 J/ I, U
Variation, 变异+ [3 j! Z5 x6 }: Y+ g' ^9 w& |% ?
Varimax orthogonal rotation, 方差最大正交旋转& ?8 j( I# B+ N* v) c# }) H
Volume of distribution, 容积4 J2 Y: K0 ?& U" }5 T2 K$ [ }& b
W test, W检验- F6 l0 H: { S2 e( ~7 Y1 c
Weibull distribution, 威布尔分布( j3 e% p7 c% O8 n% a* e
Weight, 权数% i# q4 c- ^! X: k1 Q( ^5 _2 t% z
Weighted Chi-square test, 加权卡方检验/Cochran检验
. \# }5 D3 x3 p1 o, c% nWeighted linear regression method, 加权直线回归
7 C+ D x+ H4 ]8 d& kWeighted mean, 加权平均数
7 b- N F+ s- a5 O7 Z# } G9 u TWeighted mean square, 加权平均方差# r0 \; X7 [- @$ }& v+ S
Weighted sum of square, 加权平方和9 _2 ]0 x# w% C; i# r& Y8 k
Weighting coefficient, 权重系数% t& C x) i; f( ]
Weighting method, 加权法 * ^$ M1 N- X2 e
W-estimation, W估计量! f$ W0 |0 Y( J+ B
W-estimation of location, 位置W估计量
& t" F$ {! ]6 \" I/ VWidth, 宽度
3 ?9 x4 D9 f0 Z2 C9 }# ?5 lWilcoxon paired test, 威斯康星配对法/配对符号秩和检验6 ~/ ]9 K4 [" l2 {1 ^6 q
Wild point, 野点/狂点
- U% L3 u- J% \; E: |) uWild value, 野值/狂值! o6 D( V7 ~4 @# b; }1 R( X
Winsorized mean, 缩尾均值" Q' V! p+ T2 |9 \* i3 U5 i8 b
Withdraw, 失访 9 C; n+ s7 f1 p7 Y3 Q; W
Youden's index, 尤登指数$ D5 ~' e5 L6 [, {8 b: I: C
Z test, Z检验 B- z/ N" P7 I- Z. H: U V
Zero correlation, 零相关9 E3 d s- w5 _: V5 z$ N% b+ x6 }5 u P
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
