|
|
Absolute deviation, 绝对离差1 {$ w* X1 F( b3 @& X: ~
Absolute number, 绝对数
% J" ~# q$ V1 S; a" zAbsolute residuals, 绝对残差6 j |; h7 z. O2 U0 d# u
Acceleration array, 加速度立体阵
% u/ j& U' P* H: `- Z7 _! Q- kAcceleration in an arbitrary direction, 任意方向上的加速度7 T! N: w% m* E- ?: y$ e
Acceleration normal, 法向加速度
3 ?+ b* ?; G/ zAcceleration space dimension, 加速度空间的维数 B1 J: R- J+ D0 l
Acceleration tangential, 切向加速度
; c, c( _0 X% ~' oAcceleration vector, 加速度向量* \/ S8 Z5 G' z' F, Y
Acceptable hypothesis, 可接受假设. E/ a- v. R& [* n3 Q* u$ Y& N- g* L
Accumulation, 累积
' r3 f& w P! |7 S I1 J6 b' JAccuracy, 准确度
1 m3 J; W# A8 {, {4 j. O% iActual frequency, 实际频数% E( Z" v! ^% h
Adaptive estimator, 自适应估计量% z7 d" l2 A9 Z" L+ K) |
Addition, 相加, @& n+ {: x8 \7 F3 y
Addition theorem, 加法定理4 s$ n; v! E: t" v8 h: M! J1 D/ ^
Additivity, 可加性: P6 n2 [: b& N! x, b8 t
Adjusted rate, 调整率; k# a& A0 D: z
Adjusted value, 校正值
$ |2 G3 L/ v( F( e- ZAdmissible error, 容许误差
2 w+ }6 f9 U" A" FAggregation, 聚集性
. n! B- A3 s: ?2 ~2 j0 m6 HAlternative hypothesis, 备择假设
, x, l( W) `- I2 _4 ~Among groups, 组间
8 k/ W+ Y6 c& A( sAmounts, 总量
- ^, [0 s) i" @& _Analysis of correlation, 相关分析* V% D% n7 h' \7 { v7 M
Analysis of covariance, 协方差分析
, O. m. W8 B7 Z# v! u& t- \2 @! GAnalysis of regression, 回归分析& r" c! Y4 V( U; z+ ~% q4 K- w
Analysis of time series, 时间序列分析: i! X6 X W2 j; [+ N0 q& m, j L
Analysis of variance, 方差分析
2 m3 j, t* o) T. B, [Angular transformation, 角转换( w1 ]" Q4 S5 L5 s& g' T; F
ANOVA （analysis of variance）, 方差分析
: E% P+ E% O; o% w, g8 _" ^- |$ ?ANOVA Models, 方差分析模型- l6 U( s% J' _
Arcing, 弧/弧旋2 W# A/ W! F& _; }/ _
Arcsine transformation, 反正弦变换) y: u: g; v+ r0 Y
Area under the curve, 曲线面积9 l" S, o( [) R' w/ m- b
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 " h. ~, H/ ^' i7 W3 g
ARIMA, 季节和非季节性单变量模型的极大似然估计
4 M. j# A8 x ^+ f8 ~% \9 e/ @7 r* m% E$ JArithmetic grid paper, 算术格纸
8 V( R8 G4 h. U9 AArithmetic mean, 算术平均数
% F+ b+ ?7 j) F5 ZArrhenius relation, 艾恩尼斯关系
5 m2 j) ?3 ~/ j7 w$ r# cAssessing fit, 拟合的评估
3 t1 ?( _9 h# f4 G2 Z5 Q, B! wAssociative laws, 结合律
0 W" ~. C- r7 I' U/ |& c0 aAsymmetric distribution, 非对称分布
) D" W: ?, G" t" S; GAsymptotic bias, 渐近偏倚
- P% v/ x4 P" H n( K" O( tAsymptotic efficiency, 渐近效率1 r. f4 ]( L5 n8 ^" _
Asymptotic variance, 渐近方差
5 K2 g+ Q& q6 T/ QAttributable risk, 归因危险度
; o$ @9 U* h3 c' P; Q) D! VAttribute data, 属性资料2 N! S" `; l# D P8 c
Attribution, 属性. [$ C6 {6 }6 ~: i1 l6 @
Autocorrelation, 自相关
' B O4 y- k7 c! y5 F! d: Z3 S- hAutocorrelation of residuals, 残差的自相关: b+ \# }" T4 D0 P% h
Average, 平均数
% U6 F$ W3 S9 SAverage confidence interval length, 平均置信区间长度9 ` P. N0 X1 A7 {
Average growth rate, 平均增长率" Q5 I% v, |* A! x3 N
Bar chart, 条形图+ v& n: J% M1 b* Y' f7 k) z4 m' }
Bar graph, 条形图
' Q$ k, ]" H# J- J9 {- j4 k, RBase period, 基期7 {9 H5 `0 Z9 O$ x; Q0 j5 i+ I6 ~
Bayes' theorem , Bayes定理
e( Q/ j/ D2 r2 m3 _Bell-shaped curve, 钟形曲线
% K8 z! A9 u8 }3 A# [2 B9 _3 _0 S! wBernoulli distribution, 伯努力分布+ e' {' b- R. S
Best-trim estimator, 最好切尾估计量
( d# N" D2 i/ T. d* j, V" U& Z* g, J/ bBias, 偏性
3 a' a, F" n8 [+ r( GBinary logistic regression, 二元逻辑斯蒂回归
- X$ T7 _, D2 W" YBinomial distribution, 二项分布2 l1 w1 w( @' D- S- P3 P4 m- p
Bisquare, 双平方; { M6 R# C) B8 X W
Bivariate Correlate, 二变量相关+ n- F6 N* [$ a. q V) R
Bivariate normal distribution, 双变量正态分布6 d+ X# y9 Q( B. p
Bivariate normal population, 双变量正态总体0 A1 q) `; F3 x# g$ l' M [
Biweight interval, 双权区间1 ~/ X4 b! h: ?: w' i
Biweight M-estimator, 双权M估计量
( f- h0 i6 S* { p) L# u" x& e R& yBlock, 区组/配伍组
# h" O9 }2 E) d4 N) e( p: Q" b& yBMDP(Biomedical computer programs), BMDP统计软件包
9 ?: p4 n7 Y1 Y- \. T M# _1 A( m9 iBoxplots, 箱线图/箱尾图
/ h8 S q: T6 R1 i7 U% XBreakdown bound, 崩溃界/崩溃点. x5 J1 V8 f) M+ z! ]
Canonical correlation, 典型相关
9 ]) @. B# J2 G7 e; O oCaption, 纵标目
+ d$ b: u- F9 f# L. A+ L& hCase-control study, 病例对照研究1 B/ `9 D2 p2 e8 }
Categorical variable, 分类变量
# _- D( ~5 |! l0 a; VCatenary, 悬链线
! x8 C' \& C0 i' XCauchy distribution, 柯西分布
% q' {" r! M k0 j3 s$ a- X# {7 fCause-and-effect relationship, 因果关系
# F- Y5 g8 P" ]& j; \Cell, 单元. {. S8 m3 b/ S. O; r1 a$ R$ x% B
Censoring, 终检( j1 S5 B+ J h% g/ E; c
Center of symmetry, 对称中心5 W; H5 n) R- C4 ?
Centering and scaling, 中心化和定标
! c% Q" f _* y( J/ M, xCentral tendency, 集中趋势
% M& ?$ D- D. }/ _3 L3 LCentral value, 中心值
: h% X2 f5 _, X4 f* }, qCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测) N: n3 r9 g0 |( }
Chance, 机遇" j: K) L. c O
Chance error, 随机误差
# `5 h6 e9 B! Y# EChance variable, 随机变量# ]6 v4 S$ f! T) z. U, s* z* n
Characteristic equation, 特征方程
% A. U' K5 l$ P6 rCharacteristic root, 特征根
2 H8 h! o0 C+ `8 r6 s4 pCharacteristic vector, 特征向量8 A: h& J5 M4 ~/ Q
Chebshev criterion of fit, 拟合的切比雪夫准则3 v) p1 Q& T8 Q% }6 C2 i
Chernoff faces, 切尔诺夫脸谱图1 h6 L* l9 L3 t- }
Chi-square test, 卡方检验/χ2检验
" I+ a( i7 k! ~/ ?0 ~Choleskey decomposition, 乔洛斯基分解2 C4 B( m3 r+ @, r d
Circle chart, 圆图 ( i: t: e1 v3 u
Class interval, 组距
( ?* B, K6 p6 P/ S2 hClass mid-value, 组中值& [' k: Z/ X$ o$ b% v5 u E* V
Class upper limit, 组上限
+ e4 o/ k& x2 `: K( K7 t/ E. t, hClassified variable, 分类变量, T, ~( @( g: @5 I" }4 Q
Cluster analysis, 聚类分析
0 F) r5 g% V0 _. ?8 [0 fCluster sampling, 整群抽样6 `+ {) ]* z% _& k) j9 W: y
Code, 代码
# y# {) ^" G% K- s7 fCoded data, 编码数据8 @! u1 \; \4 w
Coding, 编码9 t( m/ y5 d/ Y0 \. T- j C
Coefficient of contingency, 列联系数$ p. _( ?5 T# S% l# k/ B; P
Coefficient of determination, 决定系数
; L0 s( x6 h" w2 w8 z4 z+ A- g- `Coefficient of multiple correlation, 多重相关系数: ~2 l. l; H& g8 t
Coefficient of partial correlation, 偏相关系数
3 ^0 Q9 |0 M8 t; N! p: nCoefficient of production-moment correlation, 积差相关系数
A+ H8 }/ t' hCoefficient of rank correlation, 等级相关系数
8 I4 S7 B0 B. @- k' xCoefficient of regression, 回归系数+ r& i3 M3 `$ V) b9 w4 ?* `: j6 k
Coefficient of skewness, 偏度系数
6 s$ A0 ~9 t& N2 P9 tCoefficient of variation, 变异系数
- z1 V4 H, B2 A1 aCohort study, 队列研究
/ b/ o1 w3 U v* h6 V) N% [Column, 列+ j/ s" |. ^$ {& a
Column effect, 列效应+ C0 y/ p- P8 H8 U+ m0 v# ?1 T7 S
Column factor, 列因素
4 w3 v& J w: m3 qCombination pool, 合并
: t% K1 J7 L; `$ k+ S7 s8 YCombinative table, 组合表$ o+ o* Q# d0 |2 {
Common factor, 共性因子
2 U# `0 I* T" h4 ?0 [Common regression coefficient, 公共回归系数' \% {* w7 v" Q- F7 @9 R
Common value, 共同值
2 C1 B; S! t' s1 p, ~0 _/ fCommon variance, 公共方差
- m0 l' B( {+ g) ^* B/ ^, fCommon variation, 公共变异
" P& J9 Z* N& [( UCommunality variance, 共性方差5 } m& s! Z/ r. V! f) Y
Comparability, 可比性
0 D1 n& Z! M$ H8 M8 n& u% gComparison of bathes, 批比较: u$ R" r0 R4 I
Comparison value, 比较值
; Y7 O5 \ n2 U# p, f; l7 u9 FCompartment model, 分部模型, |* j4 \% F9 h
Compassion, 伸缩* b2 A6 f, k$ x5 }. ]. O; t
Complement of an event, 补事件1 _ y7 Y( A9 O, O
Complete association, 完全正相关
7 F' }, u6 m4 G) e" }Complete dissociation, 完全不相关$ W& m) s( @* L$ p2 {6 d
Complete statistics, 完备统计量. H- D3 P* u Z o3 y C
Completely randomized design, 完全随机化设计1 j/ Q6 E! E% r N
Composite event, 联合事件+ V- _! G7 e! a/ R' z/ X3 b: S8 [* ~
Composite events, 复合事件8 Z9 Y0 ^$ \' @4 t: z& k0 _! A
Concavity, 凹性6 D% Y8 J, U3 H$ ~* I. N
Conditional expectation, 条件期望
& s: ?8 Y; q' n5 m. k' ~0 FConditional likelihood, 条件似然! U& }* T) N8 N- d! h
Conditional probability, 条件概率
% z$ @. k* ^6 t+ A& CConditionally linear, 依条件线性% Z+ t' s- `5 U& K& L: W1 n( R, b: g& H
Confidence interval, 置信区间
I+ A* z, _4 q' o) B# k# g5 V' QConfidence limit, 置信限3 ~. p. S$ i! H/ K2 u
Confidence lower limit, 置信下限0 H2 }) x; i* `2 c
Confidence upper limit, 置信上限 u. M; F0 m( G8 x8 C5 h+ T: f
Confirmatory Factor Analysis , 验证性因子分析
+ B- w6 h! n* U+ |# v4 v% ~- VConfirmatory research, 证实性实验研究# v, V& l" ~- ^9 A9 h, s( n- a
Confounding factor, 混杂因素
- ]1 x" g- \; T2 ]Conjoint, 联合分析
; {2 i! B( H8 F2 l: \8 E; zConsistency, 相合性
! _) J9 z8 u& }Consistency check, 一致性检验' R" }/ J* b) v
Consistent asymptotically normal estimate, 相合渐近正态估计
! f1 F% r! d7 o1 k1 `Consistent estimate, 相合估计2 O6 i) ]3 H4 v/ v/ h" l3 B% @/ ~/ X* Z Y
Constrained nonlinear regression, 受约束非线性回归$ q% u# }4 U R& ]% S
Constraint, 约束
/ g& M7 K+ d' B; }$ J; hContaminated distribution, 污染分布
$ }2 N1 p& A8 Q4 i( c6 uContaminated Gausssian, 污染高斯分布, @& p, d1 g1 L0 k3 G, b2 w3 I% X
Contaminated normal distribution, 污染正态分布1 a+ u+ c- u/ Z3 F6 |
Contamination, 污染! C+ ~ z( K. T- C6 l
Contamination model, 污染模型- U8 ~& O& m0 F6 R, m3 j; L4 t
Contingency table, 列联表 r) W+ c5 Q% C7 X& c$ y: Q
Contour, 边界线
2 R5 b# `( W6 o: T- oContribution rate, 贡献率 U" E0 f0 j& U7 o$ U
Control, 对照
+ c% j4 U* i: T) h* x; [Controlled experiments, 对照实验* X i' y: i' Q& [, c" G
Conventional depth, 常规深度
4 H( S! b3 R; e3 h, q0 ]# CConvolution, 卷积( R/ \; f2 o' l( \3 u O {
Corrected factor, 校正因子
# [. L( M) C% ~# [* l5 S; {, GCorrected mean, 校正均值1 E+ H' K; l3 S+ P
Correction coefficient, 校正系数
% Z; j# v: f" l e9 Y# U3 eCorrectness, 正确性& F! d. P+ t! L. ^% i$ j7 h
Correlation coefficient, 相关系数
- Z; c0 m! P9 r8 i* E/ O' wCorrelation index, 相关指数
7 g3 y0 F6 B% f) T, `" a7 sCorrespondence, 对应
/ C) N! M" w: w) O( O0 A* f# fCounting, 计数
( X2 e% ?2 I) o% x* ~1 }Counts, 计数/频数 l7 Z! d1 d3 v. z9 T$ O
Covariance, 协方差
! s) x( w. ?. j5 G2 Q1 f7 A: wCovariant, 共变 5 s \: p! n7 g. m& ` K: A/ e
Cox Regression, Cox回归
7 E6 _, H4 X$ J- R) c& a' D9 YCriteria for fitting, 拟合准则
- P% b# e5 [; f$ Y1 ?. j" tCriteria of least squares, 最小二乘准则
. |9 o" d% C4 a Y u$ rCritical ratio, 临界比
o; x, Y7 q0 ?5 V& SCritical region, 拒绝域- t% ^- c2 A$ V1 M9 e) d
Critical value, 临界值! ?9 S- M0 i& u) C3 L" i
Cross-over design, 交叉设计9 w8 y: ~) i. z. [1 {
Cross-section analysis, 横断面分析% c/ C) g1 M3 K2 }+ c3 }6 F) F
Cross-section survey, 横断面调查$ C# f7 ?7 S+ H( G2 g# u0 n# u
Crosstabs , 交叉表
# {! f- w: l L% c3 ZCross-tabulation table, 复合表! L- W7 u* }. c+ J. g. m
Cube root, 立方根
5 |+ A$ P/ u: t) |; QCumulative distribution function, 分布函数
+ L9 b' Y. F1 b% {3 _. HCumulative probability, 累计概率0 J/ v- d Y/ |5 B; ?6 A/ s
Curvature, 曲率/弯曲
$ |) a" a+ M2 E3 W! W. m9 \5 G, [Curvature, 曲率
, P& {6 b! |0 bCurve fit , 曲线拟和
$ r3 R9 l2 U. R+ M0 KCurve fitting, 曲线拟合
) v4 O; J! D/ G Y$ [! F/ sCurvilinear regression, 曲线回归
4 g }5 F& x* yCurvilinear relation, 曲线关系( t: \8 ~0 k5 ]1 s4 N7 B$ O- n
Cut-and-try method, 尝试法
* h; |2 p! ]# ^" o* K* E7 pCycle, 周期
( j: s5 q* c P0 ]/ M8 n; GCyclist, 周期性
7 Y2 U/ L; C. O! H1 DD test, D检验
0 w4 D, q8 t: Z9 |# BData acquisition, 资料收集
7 ]* @/ D* W1 P* F& m; N/ p" d% jData bank, 数据库
& K! j5 d% i) P3 rData capacity, 数据容量$ n# `5 [- x* z6 C% T4 e) a
Data deficiencies, 数据缺乏+ V& z# \9 ^0 }" c2 G% d) B
Data handling, 数据处理
# G' n9 x8 r8 U& S: ~Data manipulation, 数据处理
( U; j$ A7 V+ K4 [ K9 dData processing, 数据处理) d) |' ]9 q) l! |* A0 T
Data reduction, 数据缩减- W0 T9 h$ z! f1 j6 b
Data set, 数据集 a* a( [7 l. r' y# ^9 d
Data sources, 数据来源
6 ^; S6 s; }0 {% Z" M3 [Data transformation, 数据变换, p) y5 J( c) |
Data validity, 数据有效性
/ F# g B( g, u. ^! I$ c& bData-in, 数据输入 O! z* |/ D/ U8 Y+ ?
Data-out, 数据输出
' _3 H6 ~& S; nDead time, 停滞期0 R, r5 M! ?0 [; i8 j
Degree of freedom, 自由度
! n5 a4 l+ M) T8 P! i, V0 B6 kDegree of precision, 精密度- o7 V" h. ~5 E4 y
Degree of reliability, 可靠性程度
6 j; a/ B! o4 h. n ~: Q& X- {Degression, 递减8 O. v8 X$ x; x$ v. n+ K: I7 `9 O
Density function, 密度函数
' R9 N% o! u( P: J2 s& ADensity of data points, 数据点的密度1 j7 G6 w4 o9 e: @, N$ q- K
Dependent variable, 应变量/依变量/因变量, I3 }6 S: w# I' e) W' j: \
Dependent variable, 因变量
$ a( R7 C% I/ v1 F( yDepth, 深度3 l) H0 b7 X9 @9 z) E
Derivative matrix, 导数矩阵+ j% u/ [( L, ?+ l3 ~/ `
Derivative-free methods, 无导数方法; n: y( e G# S1 O) p3 r6 K
Design, 设计
3 {& Y, N6 j i# eDeterminacy, 确定性
& T m m# w1 S: c; t$ qDeterminant, 行列式8 e" j/ V& N+ N7 H
Determinant, 决定因素! i, u) d6 W' Z* d7 o) W2 U: d' L! y
Deviation, 离差
: C$ U( e5 Q+ D7 ~- bDeviation from average, 离均差
; M5 ]: m. O6 t$ S3 u! IDiagnostic plot, 诊断图
! [2 z9 c& H: gDichotomous variable, 二分变量
) B; ]8 m/ a8 ~, |$ ?3 T5 k8 u1 `Differential equation, 微分方程
h- W! C8 r3 r5 A# M# O. m$ _4 _Direct standardization, 直接标准化法( U' B/ ^4 D7 c# g* _* r$ S
Discrete variable, 离散型变量
, o3 _8 [5 o% N; q' k$ K; oDISCRIMINANT, 判断
4 l; T2 `# H# H2 N1 h4 j, NDiscriminant analysis, 判别分析
3 i% J8 c. u1 q/ WDiscriminant coefficient, 判别系数1 y7 _; Z. ~- N1 F" b F
Discriminant function, 判别值
- Z% K( Z9 q% v4 eDispersion, 散布/分散度* P; u: N; A# I3 `# Y6 X' t
Disproportional, 不成比例的- G' U0 D; d0 v: D1 A3 Z* ]
Disproportionate sub-class numbers, 不成比例次级组含量# n. L1 z* A, w5 P
Distribution free, 分布无关性/免分布/ |! r& n% B' K, H/ W7 h' s
Distribution shape, 分布形状
! D0 Y, W k/ F; IDistribution-free method, 任意分布法( }0 x, K8 A! f+ c
Distributive laws, 分配律" r" s! f* Q' u" u# q
Disturbance, 随机扰动项2 ]$ @; f/ ^4 Q
Dose response curve, 剂量反应曲线
( ~! X9 x" H- Y. p. xDouble blind method, 双盲法5 ?# g9 o- x5 ], ?/ R! W8 ]
Double blind trial, 双盲试验
5 D1 E& s! A ?5 ^6 w* x9 g( ?2 p- o, q1 xDouble exponential distribution, 双指数分布5 u7 d4 |4 M @5 O1 h. b* ]& O
Double logarithmic, 双对数# o6 D/ D% Z" D# ^2 W& A
Downward rank, 降秩
0 y( O0 v$ }- h8 S1 ~/ iDual-space plot, 对偶空间图
2 {% y3 S6 [- W5 E; W6 X6 q& ^DUD, 无导数方法% D' l0 G" p2 K$ I, d7 o8 ~
Duncan's new multiple range method, 新复极差法/Duncan新法
# W' K7 X" i9 B; t: B& HEffect, 实验效应
! t5 p+ k. }& F2 M# Y6 U; v9 E$ ]) k! FEigenvalue, 特征值9 ]7 ]+ S( V1 H; g6 `' b9 Y
Eigenvector, 特征向量
$ s& |4 X% Z+ H$ V+ U* SEllipse, 椭圆0 W9 ?: f. G. p& K9 J( y X* S
Empirical distribution, 经验分布' p- V) e! L1 T
Empirical probability, 经验概率单位
, M6 X5 x8 r7 J* z6 p) K1 kEnumeration data, 计数资料0 `- u' k8 n! x
Equal sun-class number, 相等次级组含量
/ v5 ? N1 V4 C5 M5 @8 g; {: iEqually likely, 等可能5 l& D7 L" @* n. K; i8 w2 o
Equivariance, 同变性* P/ n8 V; |- l' B% @5 A
Error, 误差/错误
0 w7 t' u% G4 @, ]9 S( R. gError of estimate, 估计误差
o L/ I& R" ?5 n# ? EError type I, 第一类错误* T% e# ]3 P6 Q5 f/ t& F5 F2 e3 F
Error type II, 第二类错误! y( b5 ~0 x" |- D4 L9 ^9 P
Estimand, 被估量, l: f% e7 o& Z
Estimated error mean squares, 估计误差均方1 X; l% \* ^6 z
Estimated error sum of squares, 估计误差平方和
) @' Z+ i z" [& l9 y) REuclidean distance, 欧式距离& T1 B9 {- c, |6 c, ~
Event, 事件" T! F/ E T8 j' D5 e
Event, 事件6 {& i9 _$ T& \8 @/ w4 d6 I
Exceptional data point, 异常数据点
& O' u) i' n# a* sExpectation plane, 期望平面* K+ I6 ?; |: D6 r0 U' }) W
Expectation surface, 期望曲面
! j% }. J# o/ l' ~Expected values, 期望值- ?2 c% W# q- i: o! i0 _" S8 }
Experiment, 实验
+ X% |" G2 I! |, @% A* w* U6 ^Experimental sampling, 试验抽样
$ N2 m9 S6 h/ o" {1 \2 z2 w- EExperimental unit, 试验单位4 {% `- W0 a- p0 k$ | |
Explanatory variable, 说明变量4 g# L3 t; d( A0 ?
Exploratory data analysis, 探索性数据分析
" ^% Z; @9 ~# }1 @ tExplore Summarize, 探索-摘要
" H: ^, k! q3 a% m" b3 |- gExponential curve, 指数曲线
, o/ x) l8 D' v0 c& rExponential growth, 指数式增长
# k$ y* U, f0 K' REXSMOOTH, 指数平滑方法
. x9 \4 p' s/ c$ U3 |Extended fit, 扩充拟合
- J) q, S& b( X8 f' d, eExtra parameter, 附加参数
z: n+ k9 e. \" E- }' mExtrapolation, 外推法$ H- |7 X) f8 Y
Extreme observation, 末端观测值
+ j" n/ i6 [3 X* z0 X/ q3 Q! j4 C& AExtremes, 极端值/极值
: M; l j' Z; \! Y RF distribution, F分布
8 S8 F6 s; Q" ]- Y* m9 wF test, F检验4 n; N1 t7 M- S# b3 Z
Factor, 因素/因子# @' R/ u, Y! ^: W5 N
Factor analysis, 因子分析! Z! o6 x7 J/ m3 ~. P6 m" O
Factor Analysis, 因子分析
- G5 h7 }' s+ v6 B! m# k" lFactor score, 因子得分 : i( w1 `# D7 |% U1 S; b' i
Factorial, 阶乘
# I+ A9 @/ J) I5 M+ k6 O$ p' w- vFactorial design, 析因试验设计; t' J5 \, x2 t: S2 ~+ L8 P
False negative, 假阴性
2 K' F' [) P. ` X* GFalse negative error, 假阴性错误
$ P8 k$ R. \3 L+ \5 `4 N! BFamily of distributions, 分布族
* _' k) I, N- y8 BFamily of estimators, 估计量族
. K# f0 S/ H! m, MFanning, 扇面0 n+ y+ ?$ t3 d0 b7 q
Fatality rate, 病死率
1 B" g* c9 x& DField investigation, 现场调查
4 R; ?/ M- l) L5 x, lField survey, 现场调查4 y* |" y4 A9 v9 M: x
Finite population, 有限总体. z1 |% ]- }5 h4 u4 O
Finite-sample, 有限样本( c- H9 [" {" a( L1 w) @# Y# H( p+ {
First derivative, 一阶导数
6 y T. F1 \0 I5 dFirst principal component, 第一主成分5 t1 e# y/ N8 V A3 x6 M. y" K r9 X
First quartile, 第一四分位数7 j; r& O$ L* t( a0 E
Fisher information, 费雪信息量! L# G; X9 k3 M, U6 D' x
Fitted value, 拟合值& d# ?3 ~# C: }6 J( G- G- Y
Fitting a curve, 曲线拟合
4 H' ~0 T% Z7 ^8 BFixed base, 定基
$ o( I3 i' V6 \8 ]Fluctuation, 随机起伏* y, Q: a, W% C2 { B8 }6 X, S
Forecast, 预测
; }8 t( b( ] P" C, s5 zFour fold table, 四格表) c) V5 V; ~* _' l" U! ]: t# e6 ?9 M
Fourth, 四分点
4 }7 l0 e& y1 p: m5 {4 E& ~3 GFraction blow, 左侧比率" t, b5 l+ l3 |. m+ C
Fractional error, 相对误差7 P0 K7 _# N* t8 A$ @0 v. u0 h! c
Frequency, 频率
) [( G2 |7 @* F, E# Q7 e, B+ ZFrequency polygon, 频数多边图
9 b, T7 w3 q9 R5 ?& f6 h! C4 {3 H1 sFrontier point, 界限点% |. c* { w. v; N. k
Function relationship, 泛函关系. B+ v" _/ Y6 O3 F: a/ j
Gamma distribution, 伽玛分布
1 P. f1 Z" _/ m: o. pGauss increment, 高斯增量$ D7 X7 E9 [9 f& E q+ ^
Gaussian distribution, 高斯分布/正态分布7 S. J0 r' p0 V: i( C5 d
Gauss-Newton increment, 高斯-牛顿增量
1 V" X N7 l1 g4 X3 k$ C! B3 MGeneral census, 全面普查
2 r) N9 u0 z: K8 i" B+ t* hGENLOG (Generalized liner models), 广义线性模型
8 H6 H* `4 z, O7 s* k3 t5 AGeometric mean, 几何平均数9 }# |( q0 T' n8 d. k
Gini's mean difference, 基尼均差, F g! i; b- m0 |3 x
GLM (General liner models), 一般线性模型
7 _3 J( a5 p3 x9 EGoodness of fit, 拟和优度/配合度# K7 _( u5 \5 R6 R- M" g$ j" Z
Gradient of determinant, 行列式的梯度
& J& V) ~+ W% Z% _- O+ r5 m7 k5 XGraeco-Latin square, 希腊拉丁方7 G' U b0 z* S% Y0 _
Grand mean, 总均值: y0 V; v& |( g# e1 ]5 C
Gross errors, 重大错误, v. ?% ^, J' `$ s/ ^/ \. }5 Z
Gross-error sensitivity, 大错敏感度6 [9 e- M' n- [+ |: z% @
Group averages, 分组平均
/ @; c8 A) k7 t8 |- SGrouped data, 分组资料
" K) w6 ?1 ^& [5 b& O% y- l, KGuessed mean, 假定平均数! w) z+ Y% ^( T# l$ |. Y9 l
Half-life, 半衰期
$ n% t* |$ ~/ y2 EHampel M-estimators, 汉佩尔M估计量
, e( m" N& K; d' `Happenstance, 偶然事件
( U4 R: ?* U# K& G8 \1 |Harmonic mean, 调和均数2 Q* {* r- d/ ]6 P- q
Hazard function, 风险均数
: }. c7 m# B% N7 P) u" h$ LHazard rate, 风险率
; ]% B1 ^, j# V8 t) g& [4 `! ZHeading, 标目
) C0 P8 i$ y. T+ \8 b0 oHeavy-tailed distribution, 重尾分布
( e- K: `/ t5 C* r# ~+ PHessian array, 海森立体阵
3 h+ C9 I) k) [! k5 |4 pHeterogeneity, 不同质2 ?, u$ k5 N% S
Heterogeneity of variance, 方差不齐 H: z3 m) N) ~# J& v# a+ p& M' M
Hierarchical classification, 组内分组5 q( n$ s; r2 R4 [) D' G; K) V9 w
Hierarchical clustering method, 系统聚类法* |: o4 j; j2 G) J: M* L1 F7 _
High-leverage point, 高杠杆率点$ r9 k3 p" l! |4 Q; w
HILOGLINEAR, 多维列联表的层次对数线性模型" w3 m5 @" I: B8 s" F; E* x
Hinge, 折叶点" K7 L" z2 C: Q6 E
Histogram, 直方图5 m9 V+ f; h/ w+ v# \4 v) M
Historical cohort study, 历史性队列研究
; u5 H/ q% g5 Q% @$ bHoles, 空洞; u, A1 C2 s. z
HOMALS, 多重响应分析& q! v: i( a3 y% S9 x
Homogeneity of variance, 方差齐性
4 {: D9 e. C L- X3 e u* dHomogeneity test, 齐性检验
4 A D" c6 K _$ e8 _+ MHuber M-estimators, 休伯M估计量1 \! l( O g4 z7 D; e+ r; e
Hyperbola, 双曲线' _( i$ l3 y0 R! s, o! B
Hypothesis testing, 假设检验
, A& `+ ^1 {: o" p9 O. t1 iHypothetical universe, 假设总体
1 {" J; U: R1 G2 bImpossible event, 不可能事件
5 W/ w, u- E; I/ W% ~9 }5 k: iIndependence, 独立性
+ @1 [2 e* a$ w. B" I, [Independent variable, 自变量
1 p; T/ a3 A0 y/ L* B4 }, K' ~Index, 指标/指数8 u; m! f% g3 w. b! ]
Indirect standardization, 间接标准化法
E8 i! C. W$ dIndividual, 个体1 I8 ]; F8 S7 m" o1 L
Inference band, 推断带: T5 C( {) M1 W7 `3 [" [3 `/ k
Infinite population, 无限总体
9 R u# \1 R2 X9 v2 d5 ~Infinitely great, 无穷大& o1 m9 ]" d3 p( a/ ^; I5 w
Infinitely small, 无穷小
& T" s4 X5 k f/ W, R8 k' EInfluence curve, 影响曲线: }% N! w& ~% e) g
Information capacity, 信息容量
0 m' \/ J1 ]$ l0 F+ pInitial condition, 初始条件$ H5 ~; [/ D& z9 R
Initial estimate, 初始估计值
: {7 p8 w f# Z& F+ a1 b( _Initial level, 最初水平
/ y. ]' D8 ]& l1 f9 S7 FInteraction, 交互作用. ^, O2 i; y9 H: C
Interaction terms, 交互作用项
* _7 U* c$ |! Z6 w3 ?Intercept, 截距
W8 v/ i) O9 UInterpolation, 内插法; u7 G' `( x/ Y: `
Interquartile range, 四分位距
: S4 p9 W% x$ v* ?; K; D0 U! {- DInterval estimation, 区间估计* l9 l2 L' s! }
Intervals of equal probability, 等概率区间
; Y% ]0 n" q: xIntrinsic curvature, 固有曲率; P" X4 t0 e( _8 h# T
Invariance, 不变性
' j2 J5 x. Y& XInverse matrix, 逆矩阵
4 d8 R1 z" y' B* {3 yInverse probability, 逆概率
8 L, S( }: D7 ~) J- {( K' DInverse sine transformation, 反正弦变换
. M( L3 S5 U |) EIteration, 迭代 5 G' g( F# ]% {
Jacobian determinant, 雅可比行列式
+ y. ^3 W9 h7 vJoint distribution function, 分布函数4 o3 y* ?. @. L: X
Joint probability, 联合概率
' w) p s5 m4 l g, O' f, dJoint probability distribution, 联合概率分布
" L, e) Q1 @0 F; tK means method, 逐步聚类法" l8 E3 B* K. p$ n7 ^" x
Kaplan-Meier, 评估事件的时间长度 * N _8 ^' ?7 K* L
Kaplan-Merier chart, Kaplan-Merier图
" S) j9 \! v! r, | U, z) V4 m3 _Kendall's rank correlation, Kendall等级相关; d" o4 s; P# \1 f g: v
Kinetic, 动力学
! H* O9 `7 e2 s( E1 R# nKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
$ e4 L; F" t* D3 t8 FKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
/ o7 j7 R4 b+ ^+ Y# p; `! IKurtosis, 峰度
$ M8 e6 n2 Q- B M' s1 ^; QLack of fit, 失拟' a, O3 V8 {" q$ s. a% r
Ladder of powers, 幂阶梯
" c# p- d7 ~* U$ k/ L$ f+ V, H" ]Lag, 滞后$ W4 @: W" A \+ ~: M! U8 g; R' a
Large sample, 大样本
. [) h0 L& h1 l3 [# G, d) G- u7 \Large sample test, 大样本检验' u q9 H& u5 C0 K: b
Latin square, 拉丁方3 G, W* ^& ]% f: W
Latin square design, 拉丁方设计
# a6 B- {* b" X! q! \" y; SLeakage, 泄漏
; A0 i* B3 r8 {6 J2 I2 sLeast favorable configuration, 最不利构形4 z* z; B7 X/ b) a) s
Least favorable distribution, 最不利分布1 B v% `) ^' h" m1 a. }- c
Least significant difference, 最小显著差法" E* [1 ~$ }) D( I+ c: w
Least square method, 最小二乘法4 l5 c' V0 K1 e. C8 B
Least-absolute-residuals estimates, 最小绝对残差估计. E6 G# B( C& L
Least-absolute-residuals fit, 最小绝对残差拟合4 y1 R9 r& u: W# {5 h
Least-absolute-residuals line, 最小绝对残差线
q! L! d, O- \& e7 e: Y# yLegend, 图例# \7 Q( [/ _' m' y9 X
L-estimator, L估计量
4 U7 z6 ^& y+ I$ Q2 {L-estimator of location, 位置L估计量
8 L& H" Q) j0 D# q( E3 cL-estimator of scale, 尺度L估计量- ]& A' d/ l8 u4 {
Level, 水平! E2 H/ I4 Q9 }' f, S0 y5 z
Life expectance, 预期期望寿命" P6 s+ W. a, Q) n8 N
Life table, 寿命表
+ x t; k$ j7 U& xLife table method, 生命表法
8 M: r' I- g9 p& m! hLight-tailed distribution, 轻尾分布
5 @ @+ H$ f) ~9 ~ z4 m* xLikelihood function, 似然函数
6 ~: a! D6 J7 v% U- `Likelihood ratio, 似然比
) S( B; f; R. i( ~line graph, 线图. o: g0 e. u, i) Z
Linear correlation, 直线相关
7 `/ W% |+ t Z$ N2 x* Y5 s. {Linear equation, 线性方程7 B- X [1 i* N
Linear programming, 线性规划
: e; E0 }1 p: a" V8 a" G% X5 M3 BLinear regression, 直线回归/ u) {( B5 }* ~. ]
Linear Regression, 线性回归
( a" q! |- D9 ?0 s1 N$ W) T6 LLinear trend, 线性趋势
: n$ Y5 ], s: q9 s: E( J8 ]Loading, 载荷
$ Q) q; [) D" F; l% A# O0 }8 C6 d( jLocation and scale equivariance, 位置尺度同变性! I. X( J$ r& Y) l* `# k* d
Location equivariance, 位置同变性4 E' A+ \- J- B. d# g9 c
Location invariance, 位置不变性
V# Z. K/ k7 S" w% H& vLocation scale family, 位置尺度族
8 T) \9 I5 R3 U- K, @% f) HLog rank test, 时序检验
" {0 |( E* ]6 @9 V% S6 dLogarithmic curve, 对数曲线7 ^" b. s, `+ d$ g
Logarithmic normal distribution, 对数正态分布* N$ M7 F( ?. k& k! |; A- T! I
Logarithmic scale, 对数尺度5 H+ ~7 L9 ?7 V3 `6 R0 x6 k
Logarithmic transformation, 对数变换
4 r7 s/ r! R! M7 x4 K/ s( aLogic check, 逻辑检查
. W1 T4 o- [3 f3 t- iLogistic distribution, 逻辑斯特分布 u9 C9 R4 ~0 ]" n
Logit transformation, Logit转换5 e3 N+ J1 J' A
LOGLINEAR, 多维列联表通用模型 $ y( N( _$ J; r" x1 m
Lognormal distribution, 对数正态分布
" k) y0 O6 S! P; M; w; mLost function, 损失函数4 S& f/ {" X* e- }
Low correlation, 低度相关
# |# z2 A, a: s3 J) J! A4 z* d, |Lower limit, 下限( E7 z" k5 g" p- ?7 G+ N4 p' p; g) s
Lowest-attained variance, 最小可达方差
+ e+ {. E% z" J0 fLSD, 最小显著差法的简称5 y7 p8 @% d7 L2 X0 P
Lurking variable, 潜在变量1 g$ U# u' L& ~4 X$ X1 h1 ?5 ~5 W7 S/ q
Main effect, 主效应
& c# b( t# f1 c% ~3 y6 j" l8 @Major heading, 主辞标目7 K+ o& \! Z0 z* V; L
Marginal density function, 边缘密度函数
1 X3 h W0 `, D; L! L4 s) w& tMarginal probability, 边缘概率/ M) D) ]- t5 q% p# Z' M
Marginal probability distribution, 边缘概率分布( r9 q0 e# z' v' e3 O0 C' |; ~
Matched data, 配对资料
9 y; m5 o5 F7 \5 ]9 wMatched distribution, 匹配过分布/ O* o/ O* w: N) u c; Q
Matching of distribution, 分布的匹配8 Y9 e- B# I* |. V/ J
Matching of transformation, 变换的匹配& D6 \! O# a! [3 I0 g) Q$ W' v
Mathematical expectation, 数学期望
! H7 L6 g! d( j# f: T3 u6 XMathematical model, 数学模型8 B/ M$ ] K' u3 r* g# G- [
Maximum L-estimator, 极大极小L 估计量& s' j: p' t9 d) A
Maximum likelihood method, 最大似然法' S' J4 y' L" c! u2 ?8 C( E$ z: M5 e
Mean, 均数9 F) |% s2 W5 z
Mean squares between groups, 组间均方
: X: A d: ^3 r( c3 t+ f3 I3 C/ UMean squares within group, 组内均方# K- T8 D) Z" E( \) W! c; x. I
Means (Compare means), 均值-均值比较
+ F1 P* o, t# }Median, 中位数
& Q6 M3 N' j- |. k* m: _Median effective dose, 半数效量0 T* \4 ^1 x7 k, c% B7 u' W! u
Median lethal dose, 半数致死量
- D1 Y4 j" Q; Q' SMedian polish, 中位数平滑5 Y/ _( L% s5 m% P5 D
Median test, 中位数检验
" o. F% v. @1 V$ ]. E* PMinimal sufficient statistic, 最小充分统计量" k! I+ r) d* l G
Minimum distance estimation, 最小距离估计1 i: S. A" Q8 Y
Minimum effective dose, 最小有效量
& B' W3 q/ K4 s8 x! AMinimum lethal dose, 最小致死量
" \1 D+ A7 R: T: |: K. {Minimum variance estimator, 最小方差估计量
( X X) @4 v2 t# [7 D/ ~MINITAB, 统计软件包, x' h- M! K! z
Minor heading, 宾词标目$ k/ q; k4 s* _2 ~" u! }& Q
Missing data, 缺失值# S8 G5 E8 H2 |+ p7 j- C( u* l
Model specification, 模型的确定
/ ?5 b9 [0 S# S: v- o& C* ~# @, NModeling Statistics , 模型统计8 g6 Z/ v7 r! \3 i
Models for outliers, 离群值模型# a7 p" c6 M# Z: s- Q' |/ ]7 c
Modifying the model, 模型的修正
3 {4 C9 `7 j+ p" b# ^, ~, \Modulus of continuity, 连续性模$ o% D! h2 f8 D1 P
Morbidity, 发病率
2 n& G& p K' kMost favorable configuration, 最有利构形
: B7 Y1 b/ }% b' w/ G$ uMultidimensional Scaling (ASCAL), 多维尺度/多维标度
* i+ I; _( Z2 W8 F6 O1 JMultinomial Logistic Regression , 多项逻辑斯蒂回归% D8 P! A. i k6 q
Multiple comparison, 多重比较
; w* U4 l/ C+ aMultiple correlation , 复相关7 V6 a, `9 |/ N7 i7 N
Multiple covariance, 多元协方差
! A( }% C: V- e, d" x- NMultiple linear regression, 多元线性回归, o5 B ?& ~) r; e
Multiple response , 多重选项, ?) O. X- `& ~& J" _
Multiple solutions, 多解+ L" |$ d' ]' q) c1 K) j
Multiplication theorem, 乘法定理
' N5 l+ ]: j- M$ ?' z7 nMultiresponse, 多元响应
$ W3 W3 ~& c8 J* \Multi-stage sampling, 多阶段抽样
; C& a# q5 U* } pMultivariate T distribution, 多元T分布
8 u% t5 D |" F" M% Z4 l* IMutual exclusive, 互不相容
% ^! F- |4 {2 g' t; k; V4 G2 KMutual independence, 互相独立
. x% p' }3 T6 q3 p! g% S4 tNatural boundary, 自然边界
% g9 K4 D! U( f: xNatural dead, 自然死亡* \+ w% q% _# {1 h1 {
Natural zero, 自然零7 }4 f4 S- k0 d9 q- [! z
Negative correlation, 负相关- S4 ?* J7 S" ^, k
Negative linear correlation, 负线性相关
4 H+ M7 U) B" f& ?& z) f) oNegatively skewed, 负偏
, o1 X( H, R W+ uNewman-Keuls method, q检验
: j# Y+ z6 B( n% m1 \% T- I u! zNK method, q检验- Q9 _6 [/ E) b( `( P
No statistical significance, 无统计意义( ^$ i4 f Y! D: O" T" o6 S9 {- }
Nominal variable, 名义变量
, _ e3 R$ c7 Y$ v9 f7 M& aNonconstancy of variability, 变异的非定常性
, r @ I6 M7 A1 W) h6 l- VNonlinear regression, 非线性相关! U% q& n4 ^9 J) q
Nonparametric statistics, 非参数统计
: j0 K' S% |1 Q2 U3 _) j6 YNonparametric test, 非参数检验
' y2 [# E. O7 ~9 P3 `) Z' tNonparametric tests, 非参数检验! N- W# o- ]) U% K9 Z6 m9 ?
Normal deviate, 正态离差; W* f1 `" m8 x
Normal distribution, 正态分布 f' G1 B& ]0 P# O
Normal equation, 正规方程组6 y }8 t8 \3 F9 f/ o, N1 M
Normal ranges, 正常范围# K5 |! }- \3 k" w5 r4 ~/ e+ q
Normal value, 正常值
5 `3 R$ ^5 r* v$ [: r c) J& _ bNuisance parameter, 多余参数/讨厌参数; o5 i1 B6 t: L2 l
Null hypothesis, 无效假设 5 t4 }, d, {' j
Numerical variable, 数值变量, G$ V2 J* R" g5 D- U
Objective function, 目标函数
Q6 z( w/ f4 O$ l2 o" j+ ]/ u# }Observation unit, 观察单位/ m! [( o3 u4 {
Observed value, 观察值
* j- ^1 Y7 M3 x- JOne sided test, 单侧检验4 P& R) m/ h8 a
One-way analysis of variance, 单因素方差分析! o& Z- O; m) a$ T5 g
Oneway ANOVA , 单因素方差分析: r' I& f$ ^" W
Open sequential trial, 开放型序贯设计
/ M; o- o6 g- a+ ~+ G2 Y) {4 k9 fOptrim, 优切尾0 E! m; g0 p2 Q2 p: i2 A
Optrim efficiency, 优切尾效率) J9 n, \) ]8 O5 y+ N' }* A
Order statistics, 顺序统计量
1 \9 K' g# F+ L. [% EOrdered categories, 有序分类
9 W5 k2 W2 x2 i4 B/ \; QOrdinal logistic regression , 序数逻辑斯蒂回归
0 ~& z$ [1 Z4 l+ d) p6 H2 ZOrdinal variable, 有序变量: g) [, r5 G% n8 k" f
Orthogonal basis, 正交基
, \2 P% J+ }; j6 d) S. n7 Y, DOrthogonal design, 正交试验设计2 c: L- u( Y% A+ B0 }9 x# W9 w* M
Orthogonality conditions, 正交条件$ [7 D) h5 [$ ^
ORTHOPLAN, 正交设计 7 G" O g* ~: x5 E5 W+ e2 a
Outlier cutoffs, 离群值截断点% g( h! M7 T4 b6 }6 X) Q- E* d
Outliers, 极端值. o% ^: N+ B9 b2 ^
OVERALS , 多组变量的非线性正规相关 L' T1 |5 G/ H) V
Overshoot, 迭代过度- h. f& |& c! \
Paired design, 配对设计4 e# w) ?! R. ^9 U0 s+ ^' X
Paired sample, 配对样本
B- n" P9 o/ d- SPairwise slopes, 成对斜率) `$ u3 U* h2 @6 z& t
Parabola, 抛物线3 `( Y6 z0 P6 G B& Z
Parallel tests, 平行试验5 f! m K H& s# w) H" C) d
Parameter, 参数- K+ p I! O6 N9 I% Z$ I
Parametric statistics, 参数统计' p1 ^& o( F5 q1 c
Parametric test, 参数检验
6 x/ w0 T2 s- G) ? Q+ Q4 YPartial correlation, 偏相关
; J, L! U% n" M7 I, YPartial regression, 偏回归& [1 [1 C# I$ m* o/ }% T
Partial sorting, 偏排序
( ]' g" D9 Y7 j3 D' PPartials residuals, 偏残差% N+ D9 X6 @( N; [
Pattern, 模式
* U* |# y( e; k$ Z# bPearson curves, 皮尔逊曲线
8 |0 O! H8 D T b4 ?% ~$ yPeeling, 退层5 a, P" O' u4 h$ p, G- x
Percent bar graph, 百分条形图
2 {2 T' s3 S! y; x# QPercentage, 百分比3 Q4 [( ~' g! i. m
Percentile, 百分位数
. s6 p9 \: M* [3 aPercentile curves, 百分位曲线( g0 w9 q9 Y1 R0 M% V; G2 w
Periodicity, 周期性 e; S" F+ g) d1 e
Permutation, 排列. v1 d8 U0 Z" `; P% j
P-estimator, P估计量6 ^0 p* |" h, }$ C3 A( {
Pie graph, 饼图
! J" F- p& g6 u9 E' qPitman estimator, 皮特曼估计量, I% x& Q0 q* s; F
Pivot, 枢轴量0 ^) Q; D& j; E& h# R8 {
Planar, 平坦9 k% \( @( Z9 F" t
Planar assumption, 平面的假设
$ _! \- b6 J E8 ?& z1 ]9 d, pPLANCARDS, 生成试验的计划卡
! R/ x. C% ~* r) R. nPoint estimation, 点估计
+ g5 S; K) ^, q& G( PPoisson distribution, 泊松分布" Q# F0 {& A- x, t9 C
Polishing, 平滑
- |# h; Y# p0 N: VPolled standard deviation, 合并标准差1 L8 u1 X' T2 m% T$ ~
Polled variance, 合并方差
) L7 y: |9 s: o- u$ IPolygon, 多边图9 H4 Z% c1 J. N N8 j% }
Polynomial, 多项式9 q* f6 M% H! W9 K, N
Polynomial curve, 多项式曲线3 X. O: a, Q4 l$ q" D; Y, c7 W
Population, 总体
- e5 t- X1 o; q- h1 k D7 YPopulation attributable risk, 人群归因危险度" l$ Q0 E2 u% o7 {( A
Positive correlation, 正相关8 j6 h, H0 _# r4 _4 u1 l
Positively skewed, 正偏. |, u) p% ]$ f+ T d z
Posterior distribution, 后验分布
2 k. q' j5 @# s+ J( P/ kPower of a test, 检验效能$ l; Y+ z+ N8 ?6 w/ [: q
Precision, 精密度
7 e# J) j: O& vPredicted value, 预测值
4 _8 l! f9 R& H1 y2 lPreliminary analysis, 预备性分析' z! k* v! B7 v7 @1 g4 W) M* c
Principal component analysis, 主成分分析
2 o/ [ T5 P7 z. [6 L. `* mPrior distribution, 先验分布# u' I2 V$ F) Q! E& U7 I
Prior probability, 先验概率; N& | @ s; t' R h& g% a9 z/ k5 f
Probabilistic model, 概率模型8 K$ L& E1 N; m8 f( g: ]
probability, 概率
( K# N+ D/ S; P0 b" g4 g$ XProbability density, 概率密度* c' ?% [, }# ^) _5 G
Product moment, 乘积矩/协方差
4 X4 X/ [) u& BProfile trace, 截面迹图
6 k9 y8 D, V6 nProportion, 比/构成比; l' f6 d0 S9 V4 V0 Y
Proportion allocation in stratified random sampling, 按比例分层随机抽样1 o0 v# a9 F. \3 C8 o
Proportionate, 成比例
! Y8 E3 c/ n% o6 d' M( m9 _7 F$ oProportionate sub-class numbers, 成比例次级组含量6 r6 B# ?. e9 S1 I9 E. r
Prospective study, 前瞻性调查: p# q$ N5 D* ?
Proximities, 亲近性
' {7 O( h& X+ P2 i- r9 KPseudo F test, 近似F检验
- c$ `3 a1 {6 W8 T$ ~Pseudo model, 近似模型
+ ?; _( [7 Y" P/ t; L" xPseudosigma, 伪标准差4 O: V5 v0 q$ m o+ F( I
Purposive sampling, 有目的抽样
9 x# M1 a4 y' Z4 FQR decomposition, QR分解
0 t7 @" j! ~% `Quadratic approximation, 二次近似
- w5 ?* A8 v1 p2 X" @Qualitative classification, 属性分类
; |/ S* [ _! [6 N3 D- J6 @" m- z: l+ H8 cQualitative method, 定性方法5 \+ L' @' x2 K$ e* r: M9 l* `
Quantile-quantile plot, 分位数-分位数图/Q-Q图+ \& r( O, S/ @1 h& v$ \/ O) v. O
Quantitative analysis, 定量分析
1 {+ ]" N m- W/ `, y! M/ P. T9 X% @Quartile, 四分位数
" C$ s$ g( @6 u cQuick Cluster, 快速聚类
9 h. x C8 }3 f; FRadix sort, 基数排序
5 A6 b' Z% Z0 DRandom allocation, 随机化分组
2 K8 u1 h5 ^# R$ `( R) mRandom blocks design, 随机区组设计6 m j) o: y& z D4 n- J- ?& F1 e
Random event, 随机事件9 t0 u0 l# d8 ]6 x
Randomization, 随机化
( B: L; @+ N: t; u; O9 ~. E# A) [5 kRange, 极差/全距
2 {/ I9 O. |; f# k' ZRank correlation, 等级相关& O2 c2 r) o! {% ]( R& L8 x
Rank sum test, 秩和检验! E9 W' f1 j: z/ p! H
Rank test, 秩检验3 _0 W2 l1 s. I3 \( S$ K! g* K% X: C
Ranked data, 等级资料/ ?0 f" a; l* f/ }! ]+ S; Q
Rate, 比率+ i8 T4 |2 l+ j# J7 ], a/ v
Ratio, 比例! P( _' Q" V% r
Raw data, 原始资料
- m ^ {% ?2 L. T& iRaw residual, 原始残差
& B1 `! c/ T, Y7 mRayleigh's test, 雷氏检验
3 W0 a* `# _ y3 h0 W2 rRayleigh's Z, 雷氏Z值 % N& X2 W$ Q3 u5 S
Reciprocal, 倒数
7 _3 a. M3 ^6 r. yReciprocal transformation, 倒数变换
: e) i- R# ~5 ^2 K+ jRecording, 记录
+ @5 N/ j1 y$ V- NRedescending estimators, 回降估计量5 e F3 K c$ a" k, j, W3 z
Reducing dimensions, 降维
9 l* d, R% t. ~; SRe-expression, 重新表达
+ h1 A4 R! [% ^5 }2 o/ K0 X$ `Reference set, 标准组, _0 o% _" l. _+ t; f, E; u
Region of acceptance, 接受域0 B+ @0 w0 i% {" Q; }1 p
Regression coefficient, 回归系数
* C& I* ~# z" WRegression sum of square, 回归平方和
) ^+ t: I* \5 {9 Q7 NRejection point, 拒绝点
6 ~( ?0 P4 o$ MRelative dispersion, 相对离散度
* y7 a* Q ?2 i; ^% j' J8 G4 \/ mRelative number, 相对数
6 p3 {7 P; r8 K# p5 h* [' T" ^. |Reliability, 可靠性
3 M1 b4 ~! `8 n7 ]: R. lReparametrization, 重新设置参数; h" R0 E- Q! x" ?! O8 ^9 r
Replication, 重复
: ]4 G1 W9 d g1 BReport Summaries, 报告摘要
% v% U$ o( X! z2 Y0 B0 ~Residual sum of square, 剩余平方和* r; N8 p5 s$ E/ T5 K3 f
Resistance, 耐抗性
6 ~5 R1 I# u# u8 R/ xResistant line, 耐抗线1 H$ ~) ?# J) A
Resistant technique, 耐抗技术
$ E; z& U4 W/ R. A) `R-estimator of location, 位置R估计量& a% |) F. @/ B4 @
R-estimator of scale, 尺度R估计量
1 [9 M7 p6 w8 G5 e' b& l; f% SRetrospective study, 回顾性调查. q( j! f% _5 a! P* k# R, T! P. n9 W
Ridge trace, 岭迹
% C- K( K8 T! URidit analysis, Ridit分析$ j6 `# i. z9 V+ W( ?
Rotation, 旋转
! ~( ` A9 S7 F" |& o3 \7 {Rounding, 舍入
' H$ b" y& l" c4 oRow, 行' x5 x/ N r6 e
Row effects, 行效应4 } f0 v% \/ s. H+ j9 f# z* l6 K
Row factor, 行因素
) [* S% y; t7 F5 KRXC table, RXC表
: ^% h" r3 h# l# X9 t- L" |( s2 w, RSample, 样本
9 R) M8 y1 e+ [* nSample regression coefficient, 样本回归系数1 U' ?. @7 S7 X4 B3 p3 X
Sample size, 样本量
0 Z! f- n# z, F1 b; ^; M' h& L# BSample standard deviation, 样本标准差; L4 s8 g( t. g R( x
Sampling error, 抽样误差
# \2 W, R& T- F: _% H ?SAS(Statistical analysis system ), SAS统计软件包3 A, E1 I% o/ C; }1 @7 |8 G
Scale, 尺度/量表
/ v$ A. c- W% U/ u$ O6 I& hScatter diagram, 散点图
! S. A( g6 t( `, C: H) pSchematic plot, 示意图/简图2 A% h/ s6 A7 D3 l& b
Score test, 计分检验5 p2 S6 I: S/ P* J& m5 K* F; e
Screening, 筛检, A9 v& N; J8 b- ?% S5 c
SEASON, 季节分析
9 S/ a; P# F0 Y0 mSecond derivative, 二阶导数% l5 o% ^) X" W2 u1 L/ i9 y' E
Second principal component, 第二主成分
. A' p6 w6 E3 q/ [5 VSEM (Structural equation modeling), 结构化方程模型 & u6 U- i5 A$ P7 T) x! A4 @+ l
Semi-logarithmic graph, 半对数图
p" k7 p' a3 z: mSemi-logarithmic paper, 半对数格纸
$ h4 w$ B" r5 [9 d. C! c% FSensitivity curve, 敏感度曲线: t0 G8 a% l" ^3 s' @: g$ W
Sequential analysis, 贯序分析
0 _3 e2 p, K8 x p! L/ P3 E! gSequential data set, 顺序数据集/ T6 k. B# w& g
Sequential design, 贯序设计' N, w/ U$ T" O" s6 d' c
Sequential method, 贯序法7 `$ _: ?) N& i+ ]4 [( j& X4 J* b
Sequential test, 贯序检验法
5 G/ Z( j; g6 T* Y4 @7 u' v, RSerial tests, 系列试验
# k0 o2 ]" i' C+ rShort-cut method, 简捷法
2 u' T" v# s/ |1 ?9 {8 Q7 [Sigmoid curve, S形曲线
% \) @) P$ U) B/ y, e- CSign function, 正负号函数
4 f+ q* D% d8 ^( B' k0 X2 z; LSign test, 符号检验
/ {! i* A4 `' @. J: n3 t' dSigned rank, 符号秩/ [! i$ [- @7 H
Significance test, 显著性检验
, x4 N' F6 H& T* j4 |! oSignificant figure, 有效数字+ r. L& E& o3 h3 c
Simple cluster sampling, 简单整群抽样5 r! n: k0 v* j l' G
Simple correlation, 简单相关
5 B9 C9 `; r& y0 cSimple random sampling, 简单随机抽样, N: Q& J0 p" F+ |8 X; E! i" i
Simple regression, 简单回归
% ^( S" W) [* e* ]! Ksimple table, 简单表1 }( w4 \9 P4 k; x3 w# ~" S% p
Sine estimator, 正弦估计量
5 n# a! H, }* d6 NSingle-valued estimate, 单值估计
$ Z% s2 j) g& m. w; ISingular matrix, 奇异矩阵' C+ B" q' x% g4 C9 q
Skewed distribution, 偏斜分布" Q2 H$ d0 }$ `
Skewness, 偏度. ~! b# H2 ^2 i
Slash distribution, 斜线分布+ }* v! W$ W- r, r8 u6 U% l
Slope, 斜率
) ?& {) V, M, Q9 e( ^Smirnov test, 斯米尔诺夫检验: W) |2 z* y' W
Source of variation, 变异来源: ]% ^' f$ o( ~5 e1 U( f7 P& p- b& b
Spearman rank correlation, 斯皮尔曼等级相关+ ?$ Q8 |7 h2 ]7 Q( b) F# _+ g
Specific factor, 特殊因子
8 a' D" r* m b+ V4 _ d% WSpecific factor variance, 特殊因子方差) [6 r. ~! s7 B9 C& b" ]5 i, r
Spectra , 频谱
( `5 Y$ c; ?! |! S& q8 o: o$ `Spherical distribution, 球型正态分布
9 j/ R, [6 R( ^7 c' ~! K' {, TSpread, 展布- U' i7 [# h0 R0 M
SPSS(Statistical package for the social science), SPSS统计软件包
7 _: o- H0 p8 [8 Q& T2 t& K5 k) |Spurious correlation, 假性相关
% y4 v( O* c$ \. N4 dSquare root transformation, 平方根变换 k8 w: X/ p v4 ^+ x$ r) h
Stabilizing variance, 稳定方差3 i! s! {2 t0 ~( k5 @$ {" a) y
Standard deviation, 标准差
! W$ H5 y2 a& K) bStandard error, 标准误( j# {8 Q* ?0 [8 v1 ~# l- m3 Z
Standard error of difference, 差别的标准误2 n+ N$ H* A! o, s
Standard error of estimate, 标准估计误差) p. _9 h0 V: g1 A& }% D( a
Standard error of rate, 率的标准误
. O. e, J& F/ {- d& H3 iStandard normal distribution, 标准正态分布; B: H$ ~' P0 a+ o
Standardization, 标准化; \$ j! E- m; T! q
Starting value, 起始值! a( N( c$ Q m- s% a: n* J
Statistic, 统计量
* O7 O6 n) d5 ?; [9 I* R! M4 LStatistical control, 统计控制! j5 y0 _; _ l, I7 M, d! P
Statistical graph, 统计图8 j) J* w7 B" f1 s+ }, K1 k
Statistical inference, 统计推断+ x7 Q( P- U2 V6 P# f( `
Statistical table, 统计表
2 f, `* v: f( A: D( b& }Steepest descent, 最速下降法
$ B2 n- `: E( d% Z# |+ \Stem and leaf display, 茎叶图
( v( h, Z( W- [* w! CStep factor, 步长因子
* o+ [* K! A! lStepwise regression, 逐步回归0 u7 [1 ^# G5 ?/ Z, d
Storage, 存& G( u* ~5 R. x' ]4 f
Strata, 层（复数）
5 q+ r: S! U I2 W) HStratified sampling, 分层抽样
" G3 r, ~' R e4 ]$ L1 Q: g, \Stratified sampling, 分层抽样( M% p1 Y& q5 f& V; A3 {
Strength, 强度
5 M& F9 k* w9 b/ b& R: i {1 |8 `/ ~Stringency, 严密性8 U9 z4 K# m/ ?5 d/ o
Structural relationship, 结构关系) J) h. a7 r( S. O
Studentized residual, 学生化残差/t化残差8 j. T( j8 O/ i; C# ?9 i2 n- r
Sub-class numbers, 次级组含量
2 _* J- p7 v% l0 C+ ^Subdividing, 分割
5 r/ l# I& j( j) [' c3 |Sufficient statistic, 充分统计量
' U2 G5 p& b* i* r1 N. o9 `+ q8 aSum of products, 积和& }# G4 y/ o/ f, q/ c% b
Sum of squares, 离差平方和
$ P/ ?1 T5 n. I( M: n; [! FSum of squares about regression, 回归平方和
4 w% {- _% b, a7 A) f- TSum of squares between groups, 组间平方和; Z! [* n. _( n! _% r
Sum of squares of partial regression, 偏回归平方和" k1 g( J; F1 k+ E
Sure event, 必然事件0 P2 H: G' A. K f, `
Survey, 调查
6 Y" }# m, N/ A" u9 YSurvival, 生存分析2 y I, Z0 S& R e9 Z
Survival rate, 生存率" ~: @2 [7 V7 R& _
Suspended root gram, 悬吊根图' Z$ x7 M+ Y2 j3 Y' G1 K' K
Symmetry, 对称
6 ]( a" G" z- o$ [8 g$ ZSystematic error, 系统误差# B- W/ a) {5 I1 |, I5 j
Systematic sampling, 系统抽样2 c/ ?' k' o/ e' x
Tags, 标签2 Q, \2 a8 ^8 H% l
Tail area, 尾部面积
* U. u# F$ E5 W) P0 TTail length, 尾长& h& h& _" a6 |$ ~
Tail weight, 尾重/ q/ f8 k% s$ R: ^! c
Tangent line, 切线
( O$ h( R( j; S: s% w3 nTarget distribution, 目标分布* p/ M ]3 H( e1 n& v1 h, m9 {
Taylor series, 泰勒级数, k4 v& @7 q1 r) I& r8 t( d( u" n
Tendency of dispersion, 离散趋势
* v% i# [2 Y* `0 Q+ g2 v9 ZTesting of hypotheses, 假设检验
8 L" I$ z y j4 @7 E/ y' VTheoretical frequency, 理论频数
% K+ ^7 A. `+ Q- }, A" }Time series, 时间序列' h& c7 n' P' i4 I4 U0 j+ g
Tolerance interval, 容忍区间7 z/ B: a2 H1 `' Z, P- e
Tolerance lower limit, 容忍下限
8 y' s9 i! @3 f, TTolerance upper limit, 容忍上限- o& U: \8 K9 ]6 C5 i& E3 G
Torsion, 扰率6 D& v4 m' r& w# B6 |+ G1 g- t
Total sum of square, 总平方和
2 t& w4 h1 J# }1 p, `& L0 f$ N: u8 ?Total variation, 总变异7 b6 q, ~: G+ d3 r; G
Transformation, 转换2 q0 A! h% Q+ _1 p
Treatment, 处理4 i' {) y( s* _& T0 x
Trend, 趋势' F8 C6 Q4 v% g! ~: S& P$ q: `
Trend of percentage, 百分比趋势
0 k- j& @: e5 r/ QTrial, 试验
5 a6 A: V; l5 E; C+ l* HTrial and error method, 试错法
6 V, y7 ?; ], F0 G" t% g8 S0 ?! uTuning constant, 细调常数
; j9 e; V0 {# ~7 a8 CTwo sided test, 双向检验0 o% f5 J: c1 \* |% [
Two-stage least squares, 二阶最小平方3 n% R5 X2 p! J. e; W V, H/ n
Two-stage sampling, 二阶段抽样, R1 P3 e# _# E( D* `! X" Q9 b
Two-tailed test, 双侧检验+ O8 v) N6 M0 D& _& r
Two-way analysis of variance, 双因素方差分析
$ ~/ |& _. I- @8 vTwo-way table, 双向表8 U! J0 J' J& `4 Q$ ~9 O/ F4 q
Type I error, 一类错误/α错误
1 S7 B7 D2 s4 Y0 n1 v' N, nType II error, 二类错误/β错误
; s5 D) E& n; x. N8 MUMVU, 方差一致最小无偏估计简称
. j: P* A4 i! C% ?1 gUnbiased estimate, 无偏估计, q8 e2 K/ L7 I8 B3 U: x
Unconstrained nonlinear regression , 无约束非线性回归
; v# H6 k* h% Z) e! e2 x) nUnequal subclass number, 不等次级组含量
- J- j# {7 c' h# l* O5 d' YUngrouped data, 不分组资料; z: U1 b% s, X6 s1 ?
Uniform coordinate, 均匀坐标0 B% u3 D( T( X0 @; h' d
Uniform distribution, 均匀分布, J8 a# q2 s8 c N
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计, y% d! e8 m- z# ?* \ d3 g4 V
Unit, 单元
" z2 ^/ z. O2 t, `/ m3 P" M6 gUnordered categories, 无序分类: D6 l7 r% q! J# ]: R* o$ \1 R
Upper limit, 上限$ }# {3 c* o$ W* M5 A, Y
Upward rank, 升秩
4 z7 M7 ~6 l0 g0 f( F l% F( w F OVague concept, 模糊概念! n" z% E4 P2 X% b
Validity, 有效性& L1 g7 G% H; J- d& t
VARCOMP (Variance component estimation), 方差元素估计$ R2 m' A5 |& i K+ p
Variability, 变异性7 U% I7 H% X6 P5 }/ R/ a- ]! z/ g$ w
Variable, 变量) i6 j; V( R5 o. r' t; z( e
Variance, 方差4 @" F' [9 P3 L8 `
Variation, 变异/ x2 l; ?% z* f' b+ o% ?
Varimax orthogonal rotation, 方差最大正交旋转
( d( u. F/ W }' |" r/ w& XVolume of distribution, 容积6 r' a/ f( M4 I6 M, @& ]# Q
W test, W检验% g* V+ v/ Z8 {7 ?
Weibull distribution, 威布尔分布
4 F4 e. |6 q! h0 iWeight, 权数
' I2 h* P$ ?$ g6 o4 n( oWeighted Chi-square test, 加权卡方检验/Cochran检验
1 u; W3 _8 g1 t: T3 y8 mWeighted linear regression method, 加权直线回归
- C1 s: P; y& d: SWeighted mean, 加权平均数
/ a* ]+ i4 Y% V3 K7 B& H# a0 n- {Weighted mean square, 加权平均方差; H/ q" l8 e9 u* u% U3 h
Weighted sum of square, 加权平方和
% ]) Z* }; T) u" J( XWeighting coefficient, 权重系数
) ^: _$ L" ?7 f: VWeighting method, 加权法 % a6 Z$ @/ b$ I$ y: K4 r: S ~
W-estimation, W估计量
) L1 J# J2 ]) P3 b" X# QW-estimation of location, 位置W估计量0 J* }! O1 c3 ^) H: o3 r: @3 Z
Width, 宽度/ O2 m1 \. k0 C5 P4 Q( i5 W
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验% H/ X6 J5 H! T1 S3 {) J* r1 f
Wild point, 野点/狂点7 ^* x [2 p6 \
Wild value, 野值/狂值% o3 o. U" y) `% [5 y7 [
Winsorized mean, 缩尾均值
5 P3 P; Q/ F9 |1 @# E+ @, AWithdraw, 失访
7 _( k' [9 U; L' iYouden's index, 尤登指数4 A; r: o/ {" ]; s# M# ~) x
Z test, Z检验
4 A+ a# T+ {0 B) v7 _Zero correlation, 零相关. h; ^% t! X3 F2 s. |; o9 Q3 P
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
