|
|
Absolute deviation, 绝对离差
$ q) O% p' U/ L6 l% ^' YAbsolute number, 绝对数8 m/ l' K& X* k6 J1 a: o
Absolute residuals, 绝对残差
. J! c2 u, d5 T, OAcceleration array, 加速度立体阵: I9 }0 g" P- r- T
Acceleration in an arbitrary direction, 任意方向上的加速度
6 f- c. S# g0 b6 l- {$ b- aAcceleration normal, 法向加速度9 s* M8 Z7 b$ Y$ v3 O
Acceleration space dimension, 加速度空间的维数
; y( h. }% Y0 ]Acceleration tangential, 切向加速度
4 f7 y' X' p* O, K' A: L( H, JAcceleration vector, 加速度向量
& r @- s+ Q; \7 d1 v% UAcceptable hypothesis, 可接受假设" Y' ?) Z! M7 B/ R5 U! X% m! i
Accumulation, 累积3 g4 B1 x9 d% b; M9 P
Accuracy, 准确度, x6 W4 a5 |; H0 M: q- Y% U5 Z' C
Actual frequency, 实际频数
3 N! Y; j; `" ^Adaptive estimator, 自适应估计量
! F# D& m3 X7 f) v9 F* [Addition, 相加
' r* v' p' p7 b" _8 ZAddition theorem, 加法定理2 n9 Z+ C8 M. m% g& p$ O; `1 q1 `; X
Additivity, 可加性4 y" \% R1 {6 [& k! @% p* A
Adjusted rate, 调整率) A- @+ I( d! v$ t; w5 F* h3 B
Adjusted value, 校正值
- c4 Y! L# o% x, j+ jAdmissible error, 容许误差
; y5 T* {: }' k: | {% LAggregation, 聚集性
8 t" [' X& c* e% Z/ @) A& }1 M" |Alternative hypothesis, 备择假设% q6 s4 [; {, p. c; D2 G
Among groups, 组间
, ?8 z a6 Y- P" FAmounts, 总量! q. W# j* ^; b ^' c2 w7 ?4 I
Analysis of correlation, 相关分析
+ I0 S( T" B. CAnalysis of covariance, 协方差分析
- V0 z" I! g0 G- oAnalysis of regression, 回归分析0 u; {1 I' j% a- w: W
Analysis of time series, 时间序列分析
& p8 l2 z# K9 T8 e1 T8 w0 r- G' nAnalysis of variance, 方差分析0 x) ~ g# T8 y3 a/ b
Angular transformation, 角转换
6 R# ]8 U( Y1 B. q# [) [# u# }ANOVA （analysis of variance）, 方差分析
# S% v2 X( p- Z# H/ jANOVA Models, 方差分析模型, z1 \4 P$ J! z
Arcing, 弧/弧旋: s3 v G' t' J3 w; X
Arcsine transformation, 反正弦变换
5 ~' I) |( f% U p( ~, u$ @Area under the curve, 曲线面积2 V& K' J0 f5 o S5 e5 t& D
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 " D) b4 h ]4 T
ARIMA, 季节和非季节性单变量模型的极大似然估计 * n6 Y3 j+ F3 ]% C6 C2 M6 ?! S
Arithmetic grid paper, 算术格纸7 A) [# T4 M5 \
Arithmetic mean, 算术平均数) Q4 w0 ?$ R" o3 u$ @
Arrhenius relation, 艾恩尼斯关系
. U) V8 I) _6 \4 y# ~5 y5 aAssessing fit, 拟合的评估
# h6 T# D0 b' b9 h0 B+ nAssociative laws, 结合律
6 v5 [$ j9 b) b6 A4 Z6 E! c) G. M( JAsymmetric distribution, 非对称分布7 Y% r8 q5 }0 E2 D& F
Asymptotic bias, 渐近偏倚
& B1 M0 R7 e6 l' CAsymptotic efficiency, 渐近效率6 s2 b6 a6 F, j2 Z" I* K
Asymptotic variance, 渐近方差+ b4 N) V) \# q; g0 [
Attributable risk, 归因危险度
4 ]1 X/ h$ L) |5 A; i# KAttribute data, 属性资料
8 s2 C% J* C4 I3 }9 sAttribution, 属性
5 t. }5 ^$ q2 q+ j* z5 \, u& ]: G: ^Autocorrelation, 自相关( j6 N5 w9 W( A3 S- G% j0 X
Autocorrelation of residuals, 残差的自相关, P' e$ F+ t# @% n. P/ v' O9 M
Average, 平均数4 y, V4 f& D3 \; p( ?2 K
Average confidence interval length, 平均置信区间长度
7 Q5 D7 z' r: _6 e$ dAverage growth rate, 平均增长率$ `5 V2 |9 X! u; u9 |
Bar chart, 条形图6 u0 y5 g; P# r5 H. n4 Q
Bar graph, 条形图
7 y0 ]3 C8 Q7 P- _- KBase period, 基期- Z/ F+ o6 q. d2 S* |
Bayes' theorem , Bayes定理
s8 s$ j: q( V# t7 {/ X" zBell-shaped curve, 钟形曲线
8 E2 }1 R" C' X7 ]7 FBernoulli distribution, 伯努力分布
' d8 ^8 [. @2 H, n/ \0 pBest-trim estimator, 最好切尾估计量7 b7 N( l. ^ G- }; a0 Y
Bias, 偏性
3 o0 F0 @- ?) Z% v3 C+ ~) H9 x# gBinary logistic regression, 二元逻辑斯蒂回归
+ L3 j2 _# v! }8 a& GBinomial distribution, 二项分布
4 a8 [. f7 ?% P3 o8 L( u ZBisquare, 双平方$ T+ H s. o9 a0 T" X+ {
Bivariate Correlate, 二变量相关- ^% f6 R7 U( r. J7 j ^7 s
Bivariate normal distribution, 双变量正态分布0 Q" h; y' p8 a) R4 T3 I
Bivariate normal population, 双变量正态总体
& _7 Q9 ^$ c1 `; mBiweight interval, 双权区间
. F6 R% @" M5 ?3 k0 ZBiweight M-estimator, 双权M估计量
. Q( R2 {4 @1 m/ k! X7 UBlock, 区组/配伍组! I/ r- Z. A. d8 b: U; \5 X
BMDP(Biomedical computer programs), BMDP统计软件包
% R& p9 c+ t+ }9 v. ^; `Boxplots, 箱线图/箱尾图3 ^; r% p" h% I p+ `. A
Breakdown bound, 崩溃界/崩溃点
$ |. r: v* t, k n$ _* Q( ]& wCanonical correlation, 典型相关2 S& ?6 z3 f. [4 N5 T
Caption, 纵标目 @2 k/ E3 m0 c2 {3 s+ ]
Case-control study, 病例对照研究; O; o% `, r- p2 {. y) b
Categorical variable, 分类变量2 _5 K3 V i! ?4 e4 o
Catenary, 悬链线
4 W% R4 u. y7 dCauchy distribution, 柯西分布" Y. {6 u0 Q3 A% ^
Cause-and-effect relationship, 因果关系) q3 _6 m) L5 E" V: `
Cell, 单元
9 f; ~9 ~ b" d+ Q( L. TCensoring, 终检 o. B0 c: D% l+ _: V S! B3 \
Center of symmetry, 对称中心
: T. @* X: } @) e, cCentering and scaling, 中心化和定标) u4 c$ B4 Q- _' H' [
Central tendency, 集中趋势, J& I3 s) T2 f, w& \4 x+ o+ L* R
Central value, 中心值
2 n0 t: b5 _5 f" e5 P$ qCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测' e9 m* M" U R1 p
Chance, 机遇
: d3 E. }8 V" P- CChance error, 随机误差
! Z' L3 X! J9 z8 \: A: C4 C( m6 ZChance variable, 随机变量
8 Y; f0 j+ J. J9 q+ @) }Characteristic equation, 特征方程& W7 w$ t+ Z1 `* |4 m8 u
Characteristic root, 特征根
( ]9 v# k _: s% f) B8 @! S+ gCharacteristic vector, 特征向量
! y# L' ?% s9 D2 G* G5 i8 LChebshev criterion of fit, 拟合的切比雪夫准则' I# Y& f, U) E
Chernoff faces, 切尔诺夫脸谱图
6 m& B% `1 ]+ P- V- K4 i sChi-square test, 卡方检验/χ2检验/ ^6 l- t1 P9 P9 z$ R
Choleskey decomposition, 乔洛斯基分解 h# j2 t L6 [7 p1 Q7 f
Circle chart, 圆图 / E. L5 m3 g6 |3 p4 E2 F v
Class interval, 组距
, S- ^5 ~+ q) R9 F7 T1 H) P! }8 nClass mid-value, 组中值% y$ c4 l: Q% j, B2 c( h
Class upper limit, 组上限
( k4 w0 G+ u0 L1 U+ oClassified variable, 分类变量
1 D2 _ e6 F, h2 _$ e: D2 ICluster analysis, 聚类分析
! Y5 P* I" b: u# i" ?Cluster sampling, 整群抽样9 d: ]5 z1 ]6 }: J# `
Code, 代码: K6 ]1 X4 `' Z4 F% y# h
Coded data, 编码数据+ S+ ^5 l( T7 Q( z/ @
Coding, 编码, a) q' v) V+ z
Coefficient of contingency, 列联系数9 G; C2 _# X% X7 A/ S6 F
Coefficient of determination, 决定系数
& g, E4 P& Y) R* {* G7 ACoefficient of multiple correlation, 多重相关系数/ h8 E/ A1 H& @* G2 \
Coefficient of partial correlation, 偏相关系数
. e) V8 {% a( D& OCoefficient of production-moment correlation, 积差相关系数
6 E" O& M8 F% f! q* iCoefficient of rank correlation, 等级相关系数
4 R! n. n! M7 X: I, t q( p aCoefficient of regression, 回归系数" x q# R: t: q2 } X; R# P3 q
Coefficient of skewness, 偏度系数) n# h1 k3 ^; Y+ X+ H) m
Coefficient of variation, 变异系数2 J4 t$ f1 L9 H% X8 F+ p
Cohort study, 队列研究. e' g) ^5 T& c2 b# O6 O) ~$ F
Column, 列
. e# J3 S5 ^# k4 N! CColumn effect, 列效应8 ^6 _4 H# [- } ?: j
Column factor, 列因素
: ~8 X! l# u: c7 M) a. I' C# wCombination pool, 合并; T3 z* U1 z+ t9 X# f' F. b; n
Combinative table, 组合表- x& G4 y7 r& X3 s5 H3 ?; R, K
Common factor, 共性因子
$ r8 ?& i$ U# }2 b( z4 A/ HCommon regression coefficient, 公共回归系数
) M# b3 _ w* T9 W9 L$ n1 J) fCommon value, 共同值
7 X& `8 W' ~/ BCommon variance, 公共方差* _. u0 K/ O4 K* i/ l
Common variation, 公共变异+ U" \" m6 S+ k& K/ h
Communality variance, 共性方差3 n5 c2 W$ x2 R/ j8 V; W; M
Comparability, 可比性: b7 x$ c Z" z) j
Comparison of bathes, 批比较$ F/ `0 r' X! A- x% z' z
Comparison value, 比较值
# B8 `& ?0 m2 u) x+ V! rCompartment model, 分部模型
* j; P! }5 Y* C6 _Compassion, 伸缩. e( }4 L1 D& F
Complement of an event, 补事件
1 \, [2 D% H: C' LComplete association, 完全正相关4 x. B3 B8 d* F# `) t- c
Complete dissociation, 完全不相关# M* B1 K6 a$ i; q
Complete statistics, 完备统计量
$ P4 {0 ]! g RCompletely randomized design, 完全随机化设计
( t1 }3 M* E# l! d+ \Composite event, 联合事件
7 V( h c1 E7 `. S5 qComposite events, 复合事件& L7 J7 }9 [! g+ r. ~0 F% p1 o' M; P
Concavity, 凹性) _8 c' t p8 g
Conditional expectation, 条件期望
/ K7 }: `1 w+ e% x: ZConditional likelihood, 条件似然1 J0 C0 }; w; q' ]! L9 _2 h
Conditional probability, 条件概率" P) `. t' Q& m2 B# q/ U
Conditionally linear, 依条件线性
9 u" z9 {: }7 dConfidence interval, 置信区间
9 T7 f$ Q. }$ C$ h7 h9 l) ^" D, AConfidence limit, 置信限
" q0 F% ?, s+ BConfidence lower limit, 置信下限/ q( X) E0 C5 K5 T; ^6 }
Confidence upper limit, 置信上限
- v c' e U& {6 H1 rConfirmatory Factor Analysis , 验证性因子分析% X% @9 h; `0 n: Z+ S% v2 e
Confirmatory research, 证实性实验研究
7 ^' E g; I, u9 p" \* OConfounding factor, 混杂因素
1 N( u6 j1 M5 E2 ?+ p [1 s" g# \Conjoint, 联合分析
- o, z+ a$ M8 ^* ]5 g( lConsistency, 相合性7 c, F* v5 [3 O: z
Consistency check, 一致性检验' p" {+ U2 D: \/ m
Consistent asymptotically normal estimate, 相合渐近正态估计
( w& r4 z8 ~. a, r# ~8 I: DConsistent estimate, 相合估计
* z1 F" M6 n6 yConstrained nonlinear regression, 受约束非线性回归
8 ~; R5 K9 L1 G8 GConstraint, 约束# }$ ?9 S" Y4 B/ l& e
Contaminated distribution, 污染分布# A+ E6 L( ^% G# z* ?3 \ C- E
Contaminated Gausssian, 污染高斯分布, b) i# O3 q5 O x5 v Z
Contaminated normal distribution, 污染正态分布
7 y2 k) N, S; V% Z0 P% OContamination, 污染% S# _; B2 e7 G) k3 f& @4 L
Contamination model, 污染模型
& n# k, O8 _9 n8 jContingency table, 列联表' D9 {, m; s* `3 Q
Contour, 边界线
7 I) j4 o4 Z5 hContribution rate, 贡献率- A. l) S' r8 Z
Control, 对照
- R% K S! w3 w$ z8 n0 vControlled experiments, 对照实验, l$ Q8 p9 b) ~1 ~% z! }# U5 o, E' z
Conventional depth, 常规深度& S& \* r; `# d2 E g& t% I( a9 p
Convolution, 卷积 w2 M8 `5 |5 ? ? z5 X" v
Corrected factor, 校正因子
% t' `) r4 K! L5 B# p' u* ] ^0 \Corrected mean, 校正均值
E7 }- M, o' A5 L% JCorrection coefficient, 校正系数9 `) O) m; A9 ~. {. e
Correctness, 正确性
8 w0 o+ P' s# r7 ECorrelation coefficient, 相关系数
2 ?1 F% d N5 F+ |9 z, C) WCorrelation index, 相关指数$ _/ |( E, F+ I" f
Correspondence, 对应, r) u- C) c/ P G+ j+ g, u* g) O
Counting, 计数. n/ r% x' u! `! u8 S$ q
Counts, 计数/频数$ Q7 `) R% y: W/ M4 \, E
Covariance, 协方差) w0 e/ q6 Y: u
Covariant, 共变 # J% J' x! n" r. \+ ?* t
Cox Regression, Cox回归
( p4 O( K% ~- @$ jCriteria for fitting, 拟合准则: b, @, I$ S X- T% S3 K' Y
Criteria of least squares, 最小二乘准则
6 ^; `# w2 |/ B W: MCritical ratio, 临界比& @% f8 m) Q3 j8 o' l& M7 I
Critical region, 拒绝域- w; g% r; k7 u" Z% ~ B% {
Critical value, 临界值) T' N8 B& `: ]/ K Y) j* ?7 \& W
Cross-over design, 交叉设计
" I$ k. c+ [4 z$ gCross-section analysis, 横断面分析
8 k/ G$ E0 t" i3 v& jCross-section survey, 横断面调查
# u) \; {2 ~! S; i" ]: M, ZCrosstabs , 交叉表
8 c1 n1 C' c; G0 fCross-tabulation table, 复合表
. A2 h4 \2 O- V' I& {6 Z1 v$ WCube root, 立方根' z! v# V. t, ~9 c4 F
Cumulative distribution function, 分布函数2 n( Z9 c6 ~4 Q: l& \* G5 Q
Cumulative probability, 累计概率* o; q+ M7 Q# Z3 e
Curvature, 曲率/弯曲, M$ t$ D" }/ I+ a1 w$ B j0 k
Curvature, 曲率
9 i. W' x" r# @ }+ Y3 pCurve fit , 曲线拟和
0 ]- X, @9 J0 _- p. HCurve fitting, 曲线拟合$ J$ v7 j# n: h& o& ^
Curvilinear regression, 曲线回归* [- o! g" ~% w& D) Z- v. ~
Curvilinear relation, 曲线关系5 v$ P- l$ m1 v
Cut-and-try method, 尝试法
- @7 m9 [0 z# G. n- X, ?Cycle, 周期
$ \# O8 H1 y y" y' ~ mCyclist, 周期性' R( }* l( `* e% X2 z
D test, D检验
1 A# q2 F3 Q( N& VData acquisition, 资料收集9 f# ~' `& w' y, X1 o5 E' a
Data bank, 数据库. M& o4 G) h4 o
Data capacity, 数据容量
U# C8 o% V# ~- ~: PData deficiencies, 数据缺乏
5 \% P$ v' ^4 t. f, }2 KData handling, 数据处理+ M0 a8 a0 {& r
Data manipulation, 数据处理2 w( ^0 y+ X! W5 T: ]5 f
Data processing, 数据处理2 G0 C5 `: G' H' B9 b J
Data reduction, 数据缩减
+ C* F! n8 e# FData set, 数据集
: _7 O% W$ I: S9 \( q7 CData sources, 数据来源/ d7 S9 x; p9 } A Q
Data transformation, 数据变换
# X- @8 O6 T/ h, RData validity, 数据有效性% I, T! q; D, a: U: K
Data-in, 数据输入
5 h! }7 Y8 l! f! Y, P/ X3 ^- \& m! |Data-out, 数据输出
7 k! R8 s4 q) ^1 o1 UDead time, 停滞期# ^4 m2 s: P& C3 h$ A
Degree of freedom, 自由度
$ x1 N ^" b' {5 K7 Y. W. L! t6 KDegree of precision, 精密度
( ^/ N' K" D1 E5 d' Z7 ]+ O; yDegree of reliability, 可靠性程度
, o' j% d! N8 S5 o9 eDegression, 递减* ^, }8 H/ V% O ^0 V* W3 y0 A! k
Density function, 密度函数
+ D) f3 t1 j8 c6 hDensity of data points, 数据点的密度
/ ?& T: o* ]2 B3 f( IDependent variable, 应变量/依变量/因变量
7 \3 L0 O9 V4 S. o8 o4 j$ U2 _- fDependent variable, 因变量
9 U$ R8 v S2 c Q" [Depth, 深度2 _: r$ N% c6 b: C
Derivative matrix, 导数矩阵! }8 \. e2 ?' n* m+ }8 y
Derivative-free methods, 无导数方法7 `) Z% o6 @5 M% x
Design, 设计
K; j, v$ M; f) x0 ^Determinacy, 确定性& p4 G8 y- I# K d3 Q
Determinant, 行列式
* T; `. f( V6 x( J% o2 NDeterminant, 决定因素; [/ p! H6 E, r# C! V# P; ?9 _. R; F2 h( o
Deviation, 离差( k" L. \8 h3 ^* W$ ~
Deviation from average, 离均差
; f* V: N, ^% ~Diagnostic plot, 诊断图$ P& T C+ A. z3 g! ~9 q/ z2 P! y
Dichotomous variable, 二分变量; K# `5 C- {$ g- g/ U+ a7 D( Z
Differential equation, 微分方程$ ?, A$ s" i) U8 z! E
Direct standardization, 直接标准化法4 G& q. H' z7 s7 B! s% O
Discrete variable, 离散型变量) Z4 _8 U! |. G5 L; _# L5 a
DISCRIMINANT, 判断 + X3 s* ~& t3 n, {1 `; t
Discriminant analysis, 判别分析1 c1 ~* p1 {2 d( _; X) M( y
Discriminant coefficient, 判别系数
! S' ^ Z9 f4 O2 b' ~3 _Discriminant function, 判别值' V+ Z' g/ T1 q3 W r
Dispersion, 散布/分散度# Q, g0 \' }, _. C M' e
Disproportional, 不成比例的9 p8 T; S$ V, ~, ]" z5 d
Disproportionate sub-class numbers, 不成比例次级组含量! R: L3 P' C c0 {
Distribution free, 分布无关性/免分布# ]& b$ A$ C0 u% l1 W
Distribution shape, 分布形状
* X3 Y6 k6 t, x+ w7 Z! ~3 r' k4 i# N JDistribution-free method, 任意分布法
6 N r/ s9 c; KDistributive laws, 分配律# J9 }- K. U* p
Disturbance, 随机扰动项
3 F+ A8 R" j2 R( F# Y2 u7 {( m; R+ ZDose response curve, 剂量反应曲线
# g3 X: e" W$ {Double blind method, 双盲法/ J! i$ l+ P. ^$ l# B5 ~ H
Double blind trial, 双盲试验
. g: s( W' r+ z' l9 f7 WDouble exponential distribution, 双指数分布
- {% m0 U5 R$ }Double logarithmic, 双对数
5 _1 m( z* @8 c+ U0 o9 _# [/ uDownward rank, 降秩2 x; s& G. }# L. p9 z8 n9 [
Dual-space plot, 对偶空间图
) P/ W1 P" v$ }$ u9 wDUD, 无导数方法
. {; U, A, M. \2 G) D( {Duncan's new multiple range method, 新复极差法/Duncan新法
' h0 d4 i2 @( B9 hEffect, 实验效应/ J. ^" T# r3 T4 _
Eigenvalue, 特征值; \& ~: c$ n' V* I! e5 M
Eigenvector, 特征向量
/ l/ [+ |# y2 m# c% [Ellipse, 椭圆
, p! u$ B W+ T4 O" PEmpirical distribution, 经验分布/ v7 P ]4 B1 I
Empirical probability, 经验概率单位
+ W5 l, _% S# m+ J2 J# [Enumeration data, 计数资料' O% j ^( |% C* ]
Equal sun-class number, 相等次级组含量
2 H- d; G, x5 ^' n. l* e/ fEqually likely, 等可能
$ p7 O& P! Z8 @0 x qEquivariance, 同变性
! c7 z6 \) P6 A- B9 QError, 误差/错误- J# O9 r, \# k$ V' M
Error of estimate, 估计误差
/ f4 c+ N6 d0 VError type I, 第一类错误" i, C' h1 [. T# Y) Q0 ^+ d
Error type II, 第二类错误
9 r0 J! {# H" ^6 l- {2 r7 ZEstimand, 被估量5 _$ [1 G/ i- I! m F5 i" F
Estimated error mean squares, 估计误差均方
2 A, ^( Y! G, o' P3 k: Y @' m( m5 |) lEstimated error sum of squares, 估计误差平方和
! w' {% }/ q; G9 G A b1 o h% yEuclidean distance, 欧式距离! o+ Y. X8 t/ n/ t% }; [8 e
Event, 事件" j$ f' r) K5 {. H9 _' e8 x
Event, 事件 @4 J) l( l: T$ j. a
Exceptional data point, 异常数据点/ G* h# ]/ Y$ k' l$ ]* D+ C
Expectation plane, 期望平面
: S- J$ F B+ h/ U& \) c- lExpectation surface, 期望曲面
6 @; i3 S3 G% N1 iExpected values, 期望值" v5 }. v2 [0 p; U4 G: V
Experiment, 实验* b& N, Z+ @, F9 M- z. d3 d
Experimental sampling, 试验抽样
0 v- D: ]# Z- G5 {Experimental unit, 试验单位5 q% [- F. k, x6 T y1 P1 w: ~# U
Explanatory variable, 说明变量
y+ i, T. s' w% V7 v1 oExploratory data analysis, 探索性数据分析
! C) G3 \' j6 H+ uExplore Summarize, 探索-摘要/ x* G% q) _6 ?3 U8 q
Exponential curve, 指数曲线
9 j6 w% x3 i- X% N6 O; g5 u1 SExponential growth, 指数式增长
. p, b$ |' V1 ~$ Y7 k4 N7 ?EXSMOOTH, 指数平滑方法 ) `; S- ~$ q+ V$ x5 F3 i. w) t
Extended fit, 扩充拟合
/ t6 o/ ]3 B0 X! {% _. ]2 RExtra parameter, 附加参数1 B( v3 @) H, O6 S$ M8 E
Extrapolation, 外推法& p/ v$ W* x$ s/ ~) L& B. Y
Extreme observation, 末端观测值; a+ E6 P8 A3 A- I3 r. f& K( m- V
Extremes, 极端值/极值% [0 x6 M9 E8 N; j3 F! d+ V% Q2 J
F distribution, F分布- _# ?; B" T; ~3 X, k
F test, F检验% C% K3 Y) D# ^: I
Factor, 因素/因子7 d1 H% _0 \1 e
Factor analysis, 因子分析
5 i, a: L( u1 h* HFactor Analysis, 因子分析9 Q* k# f* P, r/ }0 [# D$ f2 j
Factor score, 因子得分 N0 `, G% n$ d% F* h& R x1 L2 L
Factorial, 阶乘% ?1 p( Z9 Q8 B Z7 F
Factorial design, 析因试验设计
- J/ \- w$ C% D9 H4 j) Y" j! LFalse negative, 假阴性4 a# I* |& t1 T8 b4 v6 d
False negative error, 假阴性错误
) u- {) n( ~' D& i/ ZFamily of distributions, 分布族; q: h' `! c/ S
Family of estimators, 估计量族
" \) X. t, m$ A: FFanning, 扇面7 I, C( Z3 ]' b6 u2 y
Fatality rate, 病死率! [1 \: j, z; H" c
Field investigation, 现场调查/ l& a+ Z: m( M
Field survey, 现场调查
& K! n! n3 F/ yFinite population, 有限总体1 Y2 A0 l% l' ]$ b8 M+ ]3 P
Finite-sample, 有限样本
4 Q7 {' f2 r$ j% v( d" xFirst derivative, 一阶导数
! R' o# ~# x, v4 q& FFirst principal component, 第一主成分
9 f0 }) |. Q- q0 ~1 e% @First quartile, 第一四分位数
^' L9 a, D7 s; [) Z9 S3 ^! TFisher information, 费雪信息量
! H) \( o c3 ?5 s6 J. VFitted value, 拟合值
; C3 }+ i J+ n# mFitting a curve, 曲线拟合
* F2 a& ?, S# e/ u; o3 A9 @' WFixed base, 定基2 {$ [0 F/ V4 m/ N# e7 n
Fluctuation, 随机起伏
3 W: g& ]4 t- r$ J! UForecast, 预测
/ r: o: e/ t, TFour fold table, 四格表$ A8 z3 D$ L% o" R" }
Fourth, 四分点5 O6 X. l5 K9 O2 V) r6 k: P* O" F9 R
Fraction blow, 左侧比率1 j; b1 b$ N: L7 H0 X& Y2 x
Fractional error, 相对误差' S+ m: f5 @, O9 I+ e0 J" W
Frequency, 频率
) i# z$ S: X: o- ?* ~! t* e5 f2 dFrequency polygon, 频数多边图9 F; X* ?' b8 [; U, @: A
Frontier point, 界限点
1 U ?& m9 v6 ?: p: ^ q1 D0 nFunction relationship, 泛函关系3 f0 T+ E2 D3 F# S
Gamma distribution, 伽玛分布, n9 t, j! Q. {# p
Gauss increment, 高斯增量/ r8 m! @) A5 T- u, ~
Gaussian distribution, 高斯分布/正态分布
/ Z, V* \' i H: k9 |4 GGauss-Newton increment, 高斯-牛顿增量& n! W0 X: v! {
General census, 全面普查
9 k9 M* @: X/ I$ i- H5 L! e; h7 uGENLOG (Generalized liner models), 广义线性模型 ) j9 g1 R3 g, } {/ y) Q1 b& D
Geometric mean, 几何平均数( k/ ^2 \" y" S3 z* m# `
Gini's mean difference, 基尼均差# c0 F( P& X. q6 ?
GLM (General liner models), 一般线性模型 0 Z9 j" k$ U1 L3 |
Goodness of fit, 拟和优度/配合度! F# J& ]6 a/ K3 g
Gradient of determinant, 行列式的梯度' d9 r2 s Q, C, ]7 p
Graeco-Latin square, 希腊拉丁方
' m7 A5 o0 A2 K" y) iGrand mean, 总均值4 G. P9 C; N. v( j
Gross errors, 重大错误* i5 g5 V/ R. O7 F% K$ K
Gross-error sensitivity, 大错敏感度% E6 s* P% b; `) Z, \
Group averages, 分组平均8 x6 t/ z0 k1 {* Q. }
Grouped data, 分组资料4 X" k: H# f& Z; c9 F( r+ k
Guessed mean, 假定平均数
1 n. j0 s3 Q2 K( l2 JHalf-life, 半衰期
% b! W1 k* e6 JHampel M-estimators, 汉佩尔M估计量6 I* m: {7 v, [ p) u& u, d @
Happenstance, 偶然事件
3 w: V6 S; n* W4 DHarmonic mean, 调和均数
. q. t$ Y- x" pHazard function, 风险均数3 v' |" q" t4 H$ B5 @
Hazard rate, 风险率! D5 b% m/ r% V1 ~
Heading, 标目 # X0 [5 g6 |; S! E* m! P+ B, B
Heavy-tailed distribution, 重尾分布( [5 r& l6 ?( G7 O' [% w' ~
Hessian array, 海森立体阵( a5 v1 [0 `3 \ Y0 P$ j6 A
Heterogeneity, 不同质* f, i. l8 K' |5 F( x' F
Heterogeneity of variance, 方差不齐 P) M9 t n. n- ^8 |4 U& A
Hierarchical classification, 组内分组5 x9 h8 R1 B# h: I
Hierarchical clustering method, 系统聚类法
6 k: b9 B. k/ C2 p) C. [High-leverage point, 高杠杆率点$ \0 j2 s5 U, k5 j( d, m( W
HILOGLINEAR, 多维列联表的层次对数线性模型' n2 h2 E* L9 p# x
Hinge, 折叶点
9 v$ b0 i$ V6 j7 I- E5 b% W8 yHistogram, 直方图; a4 J! m2 n: C0 n [3 Z
Historical cohort study, 历史性队列研究
2 ]+ I) d- O) N6 F# YHoles, 空洞
0 j) a0 G6 X& r# XHOMALS, 多重响应分析
/ B9 v' h4 E/ _2 p" D: R" qHomogeneity of variance, 方差齐性. T4 z% k' w6 x3 c8 T
Homogeneity test, 齐性检验( y: H) p! T+ C: p
Huber M-estimators, 休伯M估计量: s2 O) T( ^: }
Hyperbola, 双曲线! y$ x2 c0 W& {( |+ h; d
Hypothesis testing, 假设检验
0 M( o7 b3 C: hHypothetical universe, 假设总体
; K# W. s; {5 QImpossible event, 不可能事件! i" H( Z/ Q: D3 d
Independence, 独立性
5 K7 f8 U3 K& `Independent variable, 自变量2 D8 E! X0 ]. I9 s0 q$ t; _
Index, 指标/指数
( a( @% E" W% w4 y. pIndirect standardization, 间接标准化法
( @% Z% u# m0 R) b' S, S. O4 AIndividual, 个体
: i! a2 m$ Z# f+ l$ H/ c" B8 U3 Y" sInference band, 推断带
2 e$ f @5 A3 A. Q# Q$ z0 x1 E4 K$ [5 p3 uInfinite population, 无限总体, O# Z% d5 _9 G g* Y: I/ U
Infinitely great, 无穷大
& B5 _/ x. Y/ A3 }" ?+ h2 kInfinitely small, 无穷小" F1 V/ N9 J% b2 t9 @
Influence curve, 影响曲线1 P5 L' ]8 j* q' F6 p
Information capacity, 信息容量' N9 B2 c0 N, Y( S* Y' Q/ I
Initial condition, 初始条件- k1 P7 `8 d5 s) K9 ?8 v; y
Initial estimate, 初始估计值: w8 V4 X2 B0 O: P1 A
Initial level, 最初水平, M, u' ?2 u! \9 [) } g
Interaction, 交互作用
. d4 D& E. v# Q5 ?. m* U8 ?Interaction terms, 交互作用项! w) F8 x( R3 }4 G' B% s2 F" a, ^
Intercept, 截距, V. V) y5 i: |+ W/ e
Interpolation, 内插法
$ R. n/ z3 U6 a7 _6 R9 |' b. mInterquartile range, 四分位距2 M+ r( O) d' ?3 Q+ q7 b* T& Z! s- S4 A
Interval estimation, 区间估计7 o) h9 ?- ?/ y+ w
Intervals of equal probability, 等概率区间
2 M# ~) _5 v8 X3 i7 UIntrinsic curvature, 固有曲率
9 M- X9 K5 r, h0 H3 U2 `- UInvariance, 不变性
7 Y' Q, R% R$ a5 ~2 zInverse matrix, 逆矩阵* n! _' G, C" x$ |4 z
Inverse probability, 逆概率
1 g- \2 u7 h5 K" {Inverse sine transformation, 反正弦变换
5 V" z8 q7 }0 b: N1 ~, [3 jIteration, 迭代 ( z4 c+ l/ a0 i4 d* s
Jacobian determinant, 雅可比行列式4 z/ R# P4 x! ~( U2 I
Joint distribution function, 分布函数
2 r# y0 m. d3 {! I+ |8 dJoint probability, 联合概率
/ \ L9 f% P; O* f# l9 UJoint probability distribution, 联合概率分布# K0 H! F" C; q% ]# u& h) Z$ B
K means method, 逐步聚类法
A: x6 v1 \: f, j" `# R; \6 E8 fKaplan-Meier, 评估事件的时间长度 " R: \8 `! ?" a/ s, w9 L0 m! H0 q) ]
Kaplan-Merier chart, Kaplan-Merier图
' @3 ^, |& S1 r1 pKendall's rank correlation, Kendall等级相关
% x b y7 O: p* h# gKinetic, 动力学
( v& q) r( _! x; U. W: Z" bKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验! K) r1 B" ^% ?; O/ {6 U
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
/ Y& G0 N4 S' [4 YKurtosis, 峰度
* p3 ?% J# I6 x; j9 Y' GLack of fit, 失拟4 f( x9 X- }9 e2 S0 {
Ladder of powers, 幂阶梯3 X3 H# C; m/ p
Lag, 滞后5 O: g4 v. ?% X, O* W
Large sample, 大样本1 a, @" S* [. k2 }4 z5 w
Large sample test, 大样本检验
' {% l9 [# l/ CLatin square, 拉丁方 n; I5 D. E) P5 ^, k$ _
Latin square design, 拉丁方设计
, j8 q0 d \+ [6 rLeakage, 泄漏
2 U% q- R3 X+ VLeast favorable configuration, 最不利构形
- I0 |" K# \% O$ j) h7 o0 kLeast favorable distribution, 最不利分布: E, y; v# Q: p* E! {
Least significant difference, 最小显著差法+ a$ o0 j6 g8 p9 i& J1 ^( D
Least square method, 最小二乘法+ R! x5 w" v5 e1 B, \9 A, g: B
Least-absolute-residuals estimates, 最小绝对残差估计5 {) s3 k* J5 J6 b2 ]6 p0 h% i4 B
Least-absolute-residuals fit, 最小绝对残差拟合: X& {+ D9 ~2 e0 w/ b/ M
Least-absolute-residuals line, 最小绝对残差线
% w+ f. Q( Q$ b& M8 [Legend, 图例- I/ F! o) v- M' e+ L1 x
L-estimator, L估计量9 y6 u2 g; ?) u
L-estimator of location, 位置L估计量
% ^% ]. z {: t4 j8 o, jL-estimator of scale, 尺度L估计量
+ w* p: H) C0 R5 f6 _+ @( A' VLevel, 水平
. Y9 K' }. q% E" A G: n4 t1 ^* TLife expectance, 预期期望寿命 |% V$ q4 ?) P! l/ y/ e
Life table, 寿命表! q0 J7 c6 T* D8 q* Q V: d. _
Life table method, 生命表法$ ?2 y. [! M4 I& o, G
Light-tailed distribution, 轻尾分布: ^3 i/ c1 \) E0 P
Likelihood function, 似然函数
& }; j, z: m0 G: e/ H, ~% iLikelihood ratio, 似然比" c$ K/ i7 e8 S! U
line graph, 线图
) O% y# W7 N# m. KLinear correlation, 直线相关
1 }: W: Y! r1 D4 B, Q0 E% LLinear equation, 线性方程. Y; `7 i# U' E& g
Linear programming, 线性规划' x0 R# j8 f3 u B
Linear regression, 直线回归
+ f, D7 L: T. V, ]% r* ILinear Regression, 线性回归8 n- U; o; s5 Q9 U7 Y3 B; _+ B( [
Linear trend, 线性趋势
: C7 o- C3 l9 d9 E* M+ N7 u( ]Loading, 载荷 ; N6 h3 y* V# G2 D/ g- ]( k1 ~: H9 F6 ~
Location and scale equivariance, 位置尺度同变性: J$ I3 S) V, O. ?% X6 x
Location equivariance, 位置同变性
- o: t" i1 W; w" ~Location invariance, 位置不变性
5 o+ O# J6 d1 [; F) s6 ^( ELocation scale family, 位置尺度族
/ M: q5 g |! J4 E9 m! jLog rank test, 时序检验 1 h9 T: I- |* R4 M* k9 R. Q+ s. M6 V
Logarithmic curve, 对数曲线
1 Q" I1 J- Z' r D/ T I# ]- ]Logarithmic normal distribution, 对数正态分布
. o1 M3 u9 r: s5 J1 dLogarithmic scale, 对数尺度
. u, ]0 L/ L; {$ M4 u$ `/ ILogarithmic transformation, 对数变换
3 D& R- u5 u. J- HLogic check, 逻辑检查: |" Y. K9 n- x* x/ I3 x. ]. g' l
Logistic distribution, 逻辑斯特分布. a5 M4 Q( [3 |
Logit transformation, Logit转换; J0 A$ @4 `7 e* ^
LOGLINEAR, 多维列联表通用模型
5 \8 Z: g9 ~9 \8 S+ O8 f2 I+ mLognormal distribution, 对数正态分布
# D! Y: H9 S* J) T8 s" GLost function, 损失函数' m. P/ ~" w6 V6 L+ \, j
Low correlation, 低度相关$ B ^4 l0 O& o3 v/ B
Lower limit, 下限4 ?" T6 R7 X9 ^: o) I
Lowest-attained variance, 最小可达方差
- `0 W6 u; S' F+ _LSD, 最小显著差法的简称+ Z5 W- n; G+ g5 f# A
Lurking variable, 潜在变量! N, I8 N7 i' v# T
Main effect, 主效应# V8 a+ ?* Q1 c# r7 i: D3 c
Major heading, 主辞标目1 L; a7 U! B* j
Marginal density function, 边缘密度函数8 v& }8 o" \" f7 q
Marginal probability, 边缘概率
8 o- D2 c/ ]. c/ k$ ]Marginal probability distribution, 边缘概率分布
& h$ a& y$ h* }: QMatched data, 配对资料
_# w, t" `% UMatched distribution, 匹配过分布4 {) w" q: j6 [( p( [
Matching of distribution, 分布的匹配2 |% \" Q, {5 ]7 g& Q
Matching of transformation, 变换的匹配( V" \$ N+ u8 S
Mathematical expectation, 数学期望) {2 v) ?) j# [' ^( x# b
Mathematical model, 数学模型- w# w0 l: J/ x1 U/ B' S
Maximum L-estimator, 极大极小L 估计量7 C0 r: m& A$ v7 R) c+ D
Maximum likelihood method, 最大似然法- M6 _, L( y2 ?0 E ^+ a
Mean, 均数
% }" Y, S. K5 N3 bMean squares between groups, 组间均方6 [0 S7 W+ ?; J# X% e% ]
Mean squares within group, 组内均方
* I7 h% C; O- v* Y# l, w6 p: f+ HMeans (Compare means), 均值-均值比较7 A% z# L9 V5 k$ @4 W D# P7 u
Median, 中位数0 V% Y0 Z) h6 G( K( u
Median effective dose, 半数效量% F' u6 Y# G3 Q; t3 u G
Median lethal dose, 半数致死量
7 b% _5 L7 ~% N* mMedian polish, 中位数平滑) s; ?6 b7 W+ g7 ?6 f/ X
Median test, 中位数检验2 f; H+ K1 I' v8 a( c# F
Minimal sufficient statistic, 最小充分统计量! h: Q; k& M' b( D+ A7 ]
Minimum distance estimation, 最小距离估计
' C" s2 R' s. c# m6 VMinimum effective dose, 最小有效量' L T, j8 \ P" _! {
Minimum lethal dose, 最小致死量
5 L9 k6 l% e8 Y6 RMinimum variance estimator, 最小方差估计量8 [9 o8 ]/ {$ q6 x" T# w
MINITAB, 统计软件包3 l1 u' `/ c4 D
Minor heading, 宾词标目
; X4 h! T6 v9 ~+ SMissing data, 缺失值
1 m. v; b/ [' pModel specification, 模型的确定1 D( C/ P1 Y) j$ j% V/ X1 l
Modeling Statistics , 模型统计
& E" t+ G. |" B1 s. E- t: iModels for outliers, 离群值模型+ t5 V) }9 T* A3 N6 A
Modifying the model, 模型的修正
# C& {5 t# H) eModulus of continuity, 连续性模
& z7 H% ?. L9 y! u/ mMorbidity, 发病率
5 i/ L0 r' A& g) n3 b( p+ CMost favorable configuration, 最有利构形
+ Y" I% ?1 n" i0 |+ `$ o* A5 |6 |Multidimensional Scaling (ASCAL), 多维尺度/多维标度3 ~4 Q3 _8 R# c
Multinomial Logistic Regression , 多项逻辑斯蒂回归
K1 M/ U/ ^. L9 hMultiple comparison, 多重比较" B% G0 X8 _& I. I& {
Multiple correlation , 复相关
5 j) T" p1 R' _6 ZMultiple covariance, 多元协方差
& J* z. ]6 a1 e' c! ~9 c, bMultiple linear regression, 多元线性回归1 a K! k9 r4 T$ o" p
Multiple response , 多重选项- D) K( D$ f) {4 a
Multiple solutions, 多解5 d2 P) M; {2 J/ r& s
Multiplication theorem, 乘法定理
+ x+ P! D+ ?: U5 b, p: G/ Q" [9 oMultiresponse, 多元响应# n' o/ F/ O7 ]: W( L' U
Multi-stage sampling, 多阶段抽样( | U1 C/ ?$ a& o
Multivariate T distribution, 多元T分布. ]. I6 X9 O, t3 Y6 x; l5 L' ]$ w: C
Mutual exclusive, 互不相容
- R7 n+ E% l3 H# t4 k" S# PMutual independence, 互相独立# { k) F( a& i& _5 M
Natural boundary, 自然边界% H$ b( z9 m2 j$ W& ]
Natural dead, 自然死亡
& |8 q: G& M0 i3 X$ ~! `5 i. O A+ aNatural zero, 自然零
# Z3 \8 m+ q" j# |Negative correlation, 负相关
) Y: c: i" M; a. g, f( d7 q9 P2 YNegative linear correlation, 负线性相关5 J) \1 k8 j6 z6 S2 y
Negatively skewed, 负偏
3 R' y2 g+ S) c$ _& j! ~: ?Newman-Keuls method, q检验
) i& _+ v/ A5 d; pNK method, q检验
: R6 V7 D' d4 bNo statistical significance, 无统计意义
5 n' k0 T; g) I1 t$ j ^8 ANominal variable, 名义变量/ N( n9 f7 N3 q' d
Nonconstancy of variability, 变异的非定常性
' d! t1 A5 n& [2 d& O, ^& K$ NNonlinear regression, 非线性相关
! k d4 _" m, \6 y& V5 I$ ?, gNonparametric statistics, 非参数统计7 Z/ `- M" i8 C( d" y8 d, i
Nonparametric test, 非参数检验+ J2 \7 `9 _5 J. ^# D: P
Nonparametric tests, 非参数检验( Y4 n, c+ `; r" ^ i: P
Normal deviate, 正态离差
1 j9 t1 `- Q, d, D9 iNormal distribution, 正态分布4 r& v7 y7 |, ?1 K) l, ^! J
Normal equation, 正规方程组
% t6 r2 g! ^1 dNormal ranges, 正常范围
3 x6 N8 X& p$ R+ dNormal value, 正常值
( ]! w, L# j- D6 _( JNuisance parameter, 多余参数/讨厌参数/ \ j" M$ _! U! h! z6 u
Null hypothesis, 无效假设
, n, r( l* _. tNumerical variable, 数值变量
" F- C0 D1 r# e6 R6 l) kObjective function, 目标函数: M/ E+ V& o' r8 I% T; Y1 y# `
Observation unit, 观察单位. k% `, _2 n2 Y4 K# |
Observed value, 观察值
4 U8 i. l* Y8 w1 Y, T' NOne sided test, 单侧检验) z, A3 {& M, U
One-way analysis of variance, 单因素方差分析2 e, X* v% Z3 O: H$ B
Oneway ANOVA , 单因素方差分析
' ^) S2 c0 Z0 I) F" P! q- jOpen sequential trial, 开放型序贯设计
, n0 s! l# O9 c3 ^+ b7 ~Optrim, 优切尾0 L" x- H# n) B' O l& J, Y+ W
Optrim efficiency, 优切尾效率
3 U9 @/ U# h3 D/ L9 n* H+ POrder statistics, 顺序统计量
; N6 W y2 [: |2 i/ JOrdered categories, 有序分类
- N S$ j, R: v$ i. p& SOrdinal logistic regression , 序数逻辑斯蒂回归
2 N; D& a# c& J2 p1 i, xOrdinal variable, 有序变量, _' l5 W, u3 F
Orthogonal basis, 正交基0 ^7 d1 q d9 k' i
Orthogonal design, 正交试验设计
1 R" ?; j/ g) P9 C5 r( SOrthogonality conditions, 正交条件
1 [ M& u* r; P x9 FORTHOPLAN, 正交设计
& r+ s' {; g; T8 ?Outlier cutoffs, 离群值截断点$ B' N3 F5 E6 h0 D5 V- J- h
Outliers, 极端值; J2 r2 {$ K5 C- m
OVERALS , 多组变量的非线性正规相关 / P* R$ s/ C$ ?1 _; z" R
Overshoot, 迭代过度. V: i; V5 |# O6 H; E
Paired design, 配对设计
. A6 q3 }+ Z: D0 V7 {* NPaired sample, 配对样本! \( D: A: X/ D1 J% O
Pairwise slopes, 成对斜率' Y2 ^6 n7 Y1 V# @, G' ?
Parabola, 抛物线
8 m" }1 }7 h; C( p1 Q! @% lParallel tests, 平行试验3 w F E! {2 T+ G$ ?
Parameter, 参数, M7 B4 u/ |! E: A' H: F' ^5 m1 @
Parametric statistics, 参数统计) G: v& s. }4 Y! _3 b
Parametric test, 参数检验
) V" C/ y8 x! T! @4 ?7 ]0 Z# WPartial correlation, 偏相关5 G0 B$ R2 l6 ^/ [) N. M
Partial regression, 偏回归
' Q2 R2 B U$ Z+ n5 N3 ]Partial sorting, 偏排序7 q6 r5 @1 I$ A5 X4 f1 D
Partials residuals, 偏残差
. H* z- o8 G& T. H( WPattern, 模式
9 c; t5 `% ~3 n! C% ^Pearson curves, 皮尔逊曲线! j8 K! u6 Y+ _) }# b$ N- a
Peeling, 退层& O m: n2 H( S
Percent bar graph, 百分条形图
4 T8 j% x+ F* ~5 P# CPercentage, 百分比! q7 ~4 o5 p- B# i8 H+ ]! B
Percentile, 百分位数& K0 |8 Q! n8 h
Percentile curves, 百分位曲线) y# J) m7 ?+ m& c; K; {' ~
Periodicity, 周期性3 @7 F& ?/ t- ?* u: A
Permutation, 排列
! @& }1 n) E5 D4 u# r8 R- |P-estimator, P估计量" P; y/ D7 U* M0 s
Pie graph, 饼图5 ~' N3 K* x* f0 h3 {
Pitman estimator, 皮特曼估计量
, @6 n! R( V8 J5 J: OPivot, 枢轴量' v' d: }, _ p9 B
Planar, 平坦
( Z. Q, m, u/ C9 [+ J. ^Planar assumption, 平面的假设
: D: w. F3 S3 p" O3 L4 BPLANCARDS, 生成试验的计划卡6 P7 _' ]2 F2 |0 t5 b L0 \! Y- d
Point estimation, 点估计
& ^3 ~+ A. |1 [- y: H& a6 [, ?' _Poisson distribution, 泊松分布. _' x0 |+ u8 Y0 t: y9 O+ |
Polishing, 平滑
, [- q8 W; n6 a2 uPolled standard deviation, 合并标准差
, c; Q& l! E5 m e+ HPolled variance, 合并方差) v# j0 Y) E4 J$ w q# r' w
Polygon, 多边图
+ z+ K ]7 i' UPolynomial, 多项式+ b: z) \5 q' C/ n b! g/ c7 V
Polynomial curve, 多项式曲线, {/ Y' U9 s! r$ D8 b: ^$ M
Population, 总体
0 g! y, `$ p( M) f! a; H iPopulation attributable risk, 人群归因危险度
3 H" U& v$ | g! y5 F8 S' H( rPositive correlation, 正相关! {) R2 Z! v2 \% B* i$ ]4 b" n7 D
Positively skewed, 正偏4 B: [% |/ B% {) b6 ~) S- e
Posterior distribution, 后验分布
2 U `% ?) O/ ^; H- K) APower of a test, 检验效能+ X0 ^% q# q% z+ v
Precision, 精密度' B8 A! |, M) v7 O2 ~) o$ z
Predicted value, 预测值
/ w2 b( K! T) h) YPreliminary analysis, 预备性分析
. ^7 V9 I+ @* h; R; D8 R. pPrincipal component analysis, 主成分分析8 a& h* K& K$ t; ?
Prior distribution, 先验分布) o2 p6 s k& m. G. T% }1 j/ ?
Prior probability, 先验概率 W6 a' ~5 {7 n8 P5 q2 B: L
Probabilistic model, 概率模型
7 X+ D5 ]7 u/ K3 \ a9 ^, Hprobability, 概率
% C& f# d* |; V d; ?# ?Probability density, 概率密度
/ d. ~1 d; l5 `8 L. v3 yProduct moment, 乘积矩/协方差
) p* H/ F, b7 J- y$ _. IProfile trace, 截面迹图5 G& ] t A9 u2 u8 y: x1 M6 P
Proportion, 比/构成比
7 Q- F h, [& @4 p2 }Proportion allocation in stratified random sampling, 按比例分层随机抽样
/ m! [4 \; n/ t6 k1 \$ uProportionate, 成比例
, A: {/ t( |3 V' i+ L# ~* m5 I$ xProportionate sub-class numbers, 成比例次级组含量4 e% N' u4 Q1 W; A9 Z
Prospective study, 前瞻性调查
6 m4 Z4 f) I2 p nProximities, 亲近性 5 h W8 H: ]% |5 q
Pseudo F test, 近似F检验
4 @5 e' J3 s3 `6 {2 ^' uPseudo model, 近似模型
( ^; G! u# `6 I1 Z+ a! r6 TPseudosigma, 伪标准差
& ?; I! { }0 u4 G3 aPurposive sampling, 有目的抽样
0 h2 _3 Q9 r$ D: J7 C. H: `QR decomposition, QR分解4 a8 V% o) a( B0 I/ o1 I, y
Quadratic approximation, 二次近似1 J$ p) z2 D. B
Qualitative classification, 属性分类" s5 X3 D, h0 r0 U
Qualitative method, 定性方法2 J& }6 I5 y3 h( q
Quantile-quantile plot, 分位数-分位数图/Q-Q图
6 [5 y0 y1 S+ ?6 a) z7 CQuantitative analysis, 定量分析
5 ^* {4 G7 g5 y" _$ [Quartile, 四分位数
0 g; c! t% x2 ^. l, g, BQuick Cluster, 快速聚类( {; d" E& S* V6 n7 n2 x1 ^4 D7 F
Radix sort, 基数排序+ U _* v" N0 f( o1 k- `
Random allocation, 随机化分组
* g2 c- s! f! `; D: d/ |Random blocks design, 随机区组设计5 g* f5 \1 v1 I" u5 T+ I6 t' {& m
Random event, 随机事件# l4 B4 o6 z3 J; e3 z5 R% y! ~( I
Randomization, 随机化8 [' I/ a* b! X
Range, 极差/全距6 {1 c. v5 n6 B9 H
Rank correlation, 等级相关
0 {2 U# w% I. f9 wRank sum test, 秩和检验
- { n5 a+ g2 `9 Z; j- B* fRank test, 秩检验
" J+ H8 W4 w$ D2 ?6 X; ^Ranked data, 等级资料 b3 b8 K; W7 {6 B7 A& J7 |+ E0 s
Rate, 比率
& S+ z) F9 m: i6 Z2 iRatio, 比例4 w; C6 |6 f1 Y( O' L
Raw data, 原始资料! {; [) ?) n5 G$ V, W$ c
Raw residual, 原始残差
& v+ O$ q" x+ a8 FRayleigh's test, 雷氏检验
1 A) P' }4 e0 f, L- ^Rayleigh's Z, 雷氏Z值 & T0 o/ X: i& v2 Q" m! B3 i9 o
Reciprocal, 倒数
, Y6 I# z/ ^& RReciprocal transformation, 倒数变换
% }1 v2 Q1 M" v* t5 r8 [ ERecording, 记录; X2 ?% O) b1 p' T9 y
Redescending estimators, 回降估计量
0 m, x9 x( u2 ?+ m: UReducing dimensions, 降维
% ~" o' S$ D* VRe-expression, 重新表达
# Q" P, v, b( J1 |( rReference set, 标准组
) d5 ~+ m6 \7 d5 QRegion of acceptance, 接受域
4 i" ~# o5 ^7 x/ i, s8 e' iRegression coefficient, 回归系数
' |! ^2 b7 \3 L. URegression sum of square, 回归平方和
: Y) k# o3 S: E yRejection point, 拒绝点$ m+ m- S- v0 Z5 B% z. f' }
Relative dispersion, 相对离散度
?0 x& \, _- J+ w! XRelative number, 相对数
; [, V! P! I: X' G4 w4 I oReliability, 可靠性
; b5 E! }; D/ ~; Q" RReparametrization, 重新设置参数( f7 k: u3 O. J9 D
Replication, 重复2 h5 l; I! j, q; o1 ]
Report Summaries, 报告摘要, {5 @3 I+ q- |
Residual sum of square, 剩余平方和
4 N/ p) r3 L: ZResistance, 耐抗性9 ], n" V( s" I* c' P+ g7 W2 r
Resistant line, 耐抗线
2 a; c8 r9 t# U/ H v2 IResistant technique, 耐抗技术
( I( R' h5 t) l: p/ l( T* n1 `R-estimator of location, 位置R估计量; @- p' L% v2 B1 @
R-estimator of scale, 尺度R估计量
6 R/ M4 I1 f$ {3 t& _* ARetrospective study, 回顾性调查/ U2 g7 q3 v5 l( `* p; V8 j' {
Ridge trace, 岭迹
4 ]. y. `, v+ NRidit analysis, Ridit分析
4 {& F7 ~* I' d# oRotation, 旋转
! B2 p& {8 ]/ ?' l. L0 ^% E" t8 L: ~Rounding, 舍入6 }! }8 G+ w& g2 t
Row, 行5 w! r& p( H# Q* l6 I' N/ `. N$ @
Row effects, 行效应
+ c, O M g9 tRow factor, 行因素
" O0 _* R, [5 F2 \RXC table, RXC表
- E x; q+ p9 K3 @: Y: N& V2 oSample, 样本) e6 p5 G6 B y
Sample regression coefficient, 样本回归系数9 J: ]2 R& O3 Y2 [/ v% r: _7 k9 ~
Sample size, 样本量- T- r; V; d# t$ V
Sample standard deviation, 样本标准差* F5 U5 B' i0 C; r& l1 I
Sampling error, 抽样误差
6 G6 w A: x# N. B+ WSAS(Statistical analysis system ), SAS统计软件包$ {5 S" x z5 }# {) w3 a
Scale, 尺度/量表1 y q1 z' \& Y
Scatter diagram, 散点图, O1 L$ f$ a, f5 I K& \) O7 O
Schematic plot, 示意图/简图& N0 }) D! q" y s7 p D& U
Score test, 计分检验
% p- p! t1 _' A: ^+ s4 uScreening, 筛检
4 l1 {" M( p% [" g0 p1 FSEASON, 季节分析
5 Y% K0 g3 R# U2 y# [Second derivative, 二阶导数4 ~4 S* ~, J# Z7 D' ]2 t+ j
Second principal component, 第二主成分
( N5 [0 S0 X8 L* u% X' u1 {SEM (Structural equation modeling), 结构化方程模型 ; i. q; L/ K) O+ ]4 ~# E, n
Semi-logarithmic graph, 半对数图+ T* v5 }/ ~3 U4 a/ {
Semi-logarithmic paper, 半对数格纸# K' b8 G" ~8 D4 b
Sensitivity curve, 敏感度曲线
& s V1 f* q7 h( Q/ D4 [0 X8 Y# ?Sequential analysis, 贯序分析
- A1 T! z5 |$ E. J4 S7 ^Sequential data set, 顺序数据集
5 Q: a1 q2 R T5 K; x( BSequential design, 贯序设计! ` X. Q$ V, y0 l0 S' K
Sequential method, 贯序法% V8 x+ @3 t/ _$ L! p) y/ t
Sequential test, 贯序检验法
N' P! t- O+ ?! X. OSerial tests, 系列试验
# o( }0 p) X8 N" sShort-cut method, 简捷法 2 f% L0 F# ?% }
Sigmoid curve, S形曲线- i- B! b. \& d; H/ v4 H
Sign function, 正负号函数4 X2 v1 V, F8 u& f5 K4 N- @
Sign test, 符号检验! B6 s( T3 s+ R% w5 W" J
Signed rank, 符号秩
0 g) I+ J- P' z; LSignificance test, 显著性检验7 R( Q/ p" Z6 L9 p- z, ]+ m4 |
Significant figure, 有效数字4 `" d4 f9 A; b3 U6 H
Simple cluster sampling, 简单整群抽样0 ?$ E" j! [& D Q/ y( E
Simple correlation, 简单相关
1 B3 C6 S' `) ^2 RSimple random sampling, 简单随机抽样5 v# g3 ?% a9 b: O& o3 `
Simple regression, 简单回归
3 F: O: [2 X+ g4 esimple table, 简单表
$ i- i' Q ~. p4 hSine estimator, 正弦估计量* a% O5 X% N7 n$ _. S
Single-valued estimate, 单值估计
) S+ L; W$ r. D$ X* m) oSingular matrix, 奇异矩阵
7 P& _) F' N, JSkewed distribution, 偏斜分布, A# d" J9 w2 O; O
Skewness, 偏度! x9 f& _; B1 f. X" O
Slash distribution, 斜线分布* y: T( C) h* Q$ E
Slope, 斜率
) X! C' W6 }" DSmirnov test, 斯米尔诺夫检验
1 b9 m; h a ^+ Q4 l! a3 d/ b- k$ H( Q- zSource of variation, 变异来源. b% O4 Z- Q1 \
Spearman rank correlation, 斯皮尔曼等级相关
- e2 \9 }3 T" [" ~5 tSpecific factor, 特殊因子
# R! f% Z* b4 c% `8 oSpecific factor variance, 特殊因子方差 _) K5 F2 S( X4 b% v0 F2 _
Spectra , 频谱 b9 Y9 \) ^4 M* L/ }1 R* T
Spherical distribution, 球型正态分布8 A1 I* w+ C4 I- b* Q# J$ L
Spread, 展布. _( E7 {( Y- z* ~3 ~
SPSS(Statistical package for the social science), SPSS统计软件包& ^2 H- |" U3 h2 E& i* ^# B
Spurious correlation, 假性相关
; A' O. Q6 X0 u) VSquare root transformation, 平方根变换
( _: w+ S( m$ D( h6 p6 c3 tStabilizing variance, 稳定方差
# M# m, m) n3 t) d4 ~3 T6 P6 ^& zStandard deviation, 标准差
5 J: ^7 t' Y( M6 H6 P- A. kStandard error, 标准误# I, y) c0 d X/ N6 F4 F5 {9 D
Standard error of difference, 差别的标准误7 B" w2 E- c6 m+ ]% P+ O$ H. O
Standard error of estimate, 标准估计误差1 ]& y \* J, i1 Q" T
Standard error of rate, 率的标准误. m( h5 ~( i( @
Standard normal distribution, 标准正态分布
2 a$ f6 J: `) Z0 Z* v/ ?, nStandardization, 标准化 R, d2 ? w- f7 R- L
Starting value, 起始值" G. B& h# d% {4 J) P0 P
Statistic, 统计量
9 L% { s3 L! H% |( J2 yStatistical control, 统计控制
, ^! [- i/ }6 c! \' p: f9 IStatistical graph, 统计图$ i. M/ g& N6 f
Statistical inference, 统计推断
/ H# X- d- t1 X" c fStatistical table, 统计表
+ Z/ ^! p% S5 H! |Steepest descent, 最速下降法. E) L( r2 V4 p8 h0 o
Stem and leaf display, 茎叶图. T% B9 ]5 u# R( n$ J) q
Step factor, 步长因子
7 T3 T) @( Z" G! x9 U, X6 ?+ g2 vStepwise regression, 逐步回归9 z* p& C* A2 @( F% d8 L( ?
Storage, 存 |& C9 }7 f7 n
Strata, 层（复数）
' e5 d0 J0 Q, DStratified sampling, 分层抽样
6 J( S1 U! i3 B4 m5 v) \$ s" n: Y$ N1 {Stratified sampling, 分层抽样" J2 k# w9 o) ]! p
Strength, 强度+ b' c* F: f9 @5 ~: G* @ \
Stringency, 严密性5 h- ^" U3 q, s
Structural relationship, 结构关系
% M7 m+ ]9 J& E, U, gStudentized residual, 学生化残差/t化残差4 A3 k4 m. i0 |: L
Sub-class numbers, 次级组含量' o" m( k, T7 L$ q% G% T
Subdividing, 分割8 S' Z4 q) ^' {0 N5 q1 r
Sufficient statistic, 充分统计量6 k4 n6 f7 V8 H6 l
Sum of products, 积和) c( C( x t8 B5 f; o( j3 I2 ]+ ], Q
Sum of squares, 离差平方和
* v+ F, o- G g$ _. G" kSum of squares about regression, 回归平方和
, p4 V8 X$ P9 Y- i$ KSum of squares between groups, 组间平方和& w5 i# v% S y6 P
Sum of squares of partial regression, 偏回归平方和
. S* `0 N, H' D. W. B$ e5 W3 C+ ySure event, 必然事件$ {. D& Z' F( R& v+ | f5 }
Survey, 调查
: Z M% e+ x6 d% V! dSurvival, 生存分析
9 W+ O# D9 y6 G1 zSurvival rate, 生存率
) E9 X/ r. Q" Q6 ~8 v WSuspended root gram, 悬吊根图
8 U: a, b8 } ZSymmetry, 对称1 P" e6 a5 s) R, S# P! v
Systematic error, 系统误差
" h* Z9 E+ [* K% kSystematic sampling, 系统抽样
0 ?6 N9 `6 y' RTags, 标签
9 a# R$ _/ }! B4 s! n+ p1 k; dTail area, 尾部面积
; n4 l9 j% v3 y2 ]8 ~+ t' q! |Tail length, 尾长
8 B: G; o7 C% z Y0 pTail weight, 尾重: f6 K' G( `( ^& m& x+ u
Tangent line, 切线! T' K7 y, M: w% A t
Target distribution, 目标分布
# R$ J+ g- t+ O% RTaylor series, 泰勒级数" v1 ~" m7 |$ D. L8 a* r4 n( [9 ]
Tendency of dispersion, 离散趋势: s! X, ~( ~+ v, V# t$ R- q
Testing of hypotheses, 假设检验
$ n, f, Z& `% @& a( d1 zTheoretical frequency, 理论频数) s/ d$ A; X1 V) e6 T' ]. `
Time series, 时间序列
. z: z- Q9 }2 U4 F vTolerance interval, 容忍区间1 f3 p, U7 y. J5 Q! l. b/ E) c' { L& C- r
Tolerance lower limit, 容忍下限
- t1 q4 x& q1 _: C. |) eTolerance upper limit, 容忍上限5 H- k- g; S. Y& Z9 Y& `, ~ S
Torsion, 扰率# r0 Q4 g! O& L- Z6 T- F1 v" Z
Total sum of square, 总平方和% C: Y% o/ S% E; ?
Total variation, 总变异
6 @3 R7 @3 D2 }8 m4 rTransformation, 转换8 L, y# e$ ] M" m" A) a3 {
Treatment, 处理3 f: @) q3 n) [, [) p3 o! L5 `
Trend, 趋势
0 w% f% q' H" S4 t7 e! Z* ^Trend of percentage, 百分比趋势
! b( o; `! O$ S& w7 qTrial, 试验
* I5 B( o: f4 D$ CTrial and error method, 试错法5 b4 p7 p/ `. m9 @* Y% S6 h
Tuning constant, 细调常数
; ]( E: Q! o! U8 X9 ?Two sided test, 双向检验
- Z5 x1 E9 m" ~4 n( OTwo-stage least squares, 二阶最小平方
0 o. Q9 w. F) p5 t( O2 q8 b0 PTwo-stage sampling, 二阶段抽样3 D5 x, d* J: j& C
Two-tailed test, 双侧检验
- h) K9 G' i! Y# p0 x6 g0 nTwo-way analysis of variance, 双因素方差分析4 h6 O, B3 }; T' y0 s
Two-way table, 双向表
0 p% `3 ~1 H6 E9 L, Y. |8 I0 pType I error, 一类错误/α错误
' ?+ E% ]; f3 Q) k) J- ~: rType II error, 二类错误/β错误1 o; G! X3 \9 d) J2 a7 _/ \
UMVU, 方差一致最小无偏估计简称! ] O5 g8 }) d9 k: N7 s" k' w' z
Unbiased estimate, 无偏估计
# Z$ a7 `5 [% VUnconstrained nonlinear regression , 无约束非线性回归; A! j0 g5 x7 M/ a- s
Unequal subclass number, 不等次级组含量4 A( }4 m+ c) c; e k
Ungrouped data, 不分组资料) I% V/ _: b' P5 \# L
Uniform coordinate, 均匀坐标
6 W, O% u- Y0 [9 l5 DUniform distribution, 均匀分布
! I! \2 P/ B1 d) D' L jUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
* w4 K' q) L( o5 k4 N X. pUnit, 单元
- z$ L" R; b7 [+ iUnordered categories, 无序分类2 Y8 u, |- F% V6 y
Upper limit, 上限' u, E# ~* N6 r' P# m6 L
Upward rank, 升秩
9 ]' Z1 j% ^& y5 pVague concept, 模糊概念. O( J$ C$ C) _8 b3 S1 L' B
Validity, 有效性
& f% n, r# l# DVARCOMP (Variance component estimation), 方差元素估计
8 m8 N/ k/ k& g, uVariability, 变异性
4 F$ K8 ^7 D; }% \/ A; [Variable, 变量8 l1 z+ I, `0 d% r( l! a* J& n
Variance, 方差
0 W2 v5 @- b, N7 N+ F3 D6 @Variation, 变异
, { t& |* [2 u) l( wVarimax orthogonal rotation, 方差最大正交旋转
8 t$ V7 k/ U4 A, d8 dVolume of distribution, 容积
$ P; Z: P8 h; G$ [; v- p" t# O/ nW test, W检验7 E, Y! h+ I2 g4 c2 q) M
Weibull distribution, 威布尔分布4 v: n! }& ^( i/ `$ U" M% f
Weight, 权数
1 _9 {- ^- ^0 m0 s W, tWeighted Chi-square test, 加权卡方检验/Cochran检验
! ^, s$ K, w- k+ q, G: zWeighted linear regression method, 加权直线回归
3 P: S+ K9 c6 r3 C$ a5 \. eWeighted mean, 加权平均数: {! I- M6 h' `& @
Weighted mean square, 加权平均方差
1 }% }' U. D, yWeighted sum of square, 加权平方和
. c f" G5 I( y8 HWeighting coefficient, 权重系数+ S Q7 C5 u. A( I) W
Weighting method, 加权法 ! U% W( e: V) \
W-estimation, W估计量$ Q% l, O9 Y" a
W-estimation of location, 位置W估计量
/ P) A# i B P5 nWidth, 宽度8 _+ Y" }" f, E
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
7 N1 ^8 K3 o, W" o; @+ I9 SWild point, 野点/狂点& r+ l, n; u6 M' X
Wild value, 野值/狂值
3 |; O/ {7 w2 _8 L, ]Winsorized mean, 缩尾均值; G) Q! j' n. u( M$ r! D
Withdraw, 失访 * [' R0 g8 A& f, p% Z
Youden's index, 尤登指数
& C. @% [% z8 @2 f+ }9 O5 CZ test, Z检验( z8 y: [9 ?3 I5 G( {
Zero correlation, 零相关' k& q$ k! M2 A2 `( x! j; t! }
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
