|
|
Absolute deviation, 绝对离差
) r5 f8 F( H/ w1 c. k4 i3 OAbsolute number, 绝对数5 r$ q! O6 S& j/ U7 y3 i, b
Absolute residuals, 绝对残差) {' p0 k1 [3 _. l0 f# q, i2 v
Acceleration array, 加速度立体阵
4 ~! W! ?$ X/ O' d" H5 n. YAcceleration in an arbitrary direction, 任意方向上的加速度
/ s% C# {' S8 f) B+ ZAcceleration normal, 法向加速度
; y# |% \5 A! i. TAcceleration space dimension, 加速度空间的维数
$ l& v7 m$ D9 y) e# ?+ mAcceleration tangential, 切向加速度
) j8 B; i, z4 M# D. WAcceleration vector, 加速度向量( W% g3 W6 `2 S3 X+ l8 X
Acceptable hypothesis, 可接受假设
9 p! |! H/ s8 G6 m& q1 W5 iAccumulation, 累积4 k- d e9 }$ z# J' p" \
Accuracy, 准确度4 M5 I6 F; `% I3 @0 E5 g$ V3 |
Actual frequency, 实际频数
( w" b# G" g+ F3 g6 r( GAdaptive estimator, 自适应估计量 C5 p2 n9 E6 H9 d3 H6 J( W8 }
Addition, 相加& ?+ ~1 e2 F6 }7 t4 q7 V. C: Y
Addition theorem, 加法定理7 d T, L# U5 v9 o' I, a; x9 j
Additivity, 可加性
9 z5 F: Q/ A. z* w+ b9 X# wAdjusted rate, 调整率" V" o. T$ L5 R/ s E
Adjusted value, 校正值6 w: y9 m, B x* W8 T( \
Admissible error, 容许误差
$ f$ r4 |' B$ _6 x6 Z7 `/ }Aggregation, 聚集性* _3 y: r% U9 O3 Z
Alternative hypothesis, 备择假设
& k4 z( V# P6 E3 ]+ }3 z1 y1 _Among groups, 组间
& n, v: O+ W7 o0 dAmounts, 总量
" ?" f! c: F$ d' ~+ C" hAnalysis of correlation, 相关分析
+ y/ B8 g' v2 x* K1 Q0 ]1 G- p- S2 IAnalysis of covariance, 协方差分析
% H6 F" ~+ I4 F6 X% i& lAnalysis of regression, 回归分析6 u9 ]# O, Z8 [# j6 \5 s" m
Analysis of time series, 时间序列分析
( A- M9 \: m8 f, X# wAnalysis of variance, 方差分析- [0 e9 b+ Y: B: V5 B/ Q5 a% ^' f, L
Angular transformation, 角转换
+ k& D# M0 W" G0 U1 W! UANOVA （analysis of variance）, 方差分析
! Q( n$ V5 \2 ]2 M0 z2 wANOVA Models, 方差分析模型7 u; E- r& [! n
Arcing, 弧/弧旋& y4 q8 h) s: z ^/ a, t
Arcsine transformation, 反正弦变换
2 E q1 Y G9 @Area under the curve, 曲线面积
% k0 c8 w: x2 D9 W" K! A6 p. B# mAREG , 评估从一个时间点到下一个时间点回归相关时的误差 - ^ P4 c! C" s
ARIMA, 季节和非季节性单变量模型的极大似然估计
/ d8 p$ m$ R OArithmetic grid paper, 算术格纸( s/ D* ^, G! H' `, E8 D4 l
Arithmetic mean, 算术平均数
9 a! c1 M9 P! d. iArrhenius relation, 艾恩尼斯关系
% K# v. X, R d s. m( HAssessing fit, 拟合的评估
9 T0 R0 S: p8 J) C" L5 R: hAssociative laws, 结合律3 c& k* w2 [0 L9 f4 w
Asymmetric distribution, 非对称分布
/ ~3 i6 l1 y9 c" y% i5 v% pAsymptotic bias, 渐近偏倚
8 h: o$ |. D& U' e) t) G5 i YAsymptotic efficiency, 渐近效率
! F0 D$ s& Z E1 Q/ I( O- M$ zAsymptotic variance, 渐近方差
/ J* ^: ^6 d: e0 _( xAttributable risk, 归因危险度
+ U# V$ [8 o, gAttribute data, 属性资料7 A6 X! j) a5 R5 T* V r/ t, p
Attribution, 属性
6 z7 w8 ~6 r& f2 _/ {Autocorrelation, 自相关
5 v1 z) k% l: H3 n2 k# EAutocorrelation of residuals, 残差的自相关/ P" f+ ^1 ^' _- [$ y2 H/ q
Average, 平均数- [ t, T$ Z( b, V- |% j& {- j$ w
Average confidence interval length, 平均置信区间长度+ Q8 \. P$ N' K N* M9 K6 _; @
Average growth rate, 平均增长率
; B- f% [6 E# w& LBar chart, 条形图
a. X i7 i) _! v) ^+ k( VBar graph, 条形图
6 C* _* d" G+ G8 @Base period, 基期
$ Y( `" t! _& n6 D x3 N: ZBayes' theorem , Bayes定理+ w q3 F' b' w% J
Bell-shaped curve, 钟形曲线
+ x# x9 Y" ?! f2 k) o O9 {Bernoulli distribution, 伯努力分布
) M$ N- r% i+ U: ZBest-trim estimator, 最好切尾估计量
# G6 o- W1 s7 T( }3 v$ `, yBias, 偏性7 |4 {! U* |' M" H5 ?6 c
Binary logistic regression, 二元逻辑斯蒂回归
: ] z1 _/ o5 L# S% h$ H9 jBinomial distribution, 二项分布
4 Z c, ~8 i3 s! KBisquare, 双平方
5 a$ j4 G# q: i6 aBivariate Correlate, 二变量相关
: p1 Q* I0 C, Q+ \$ Q) O2 lBivariate normal distribution, 双变量正态分布" l* z- _5 F9 h" h+ A
Bivariate normal population, 双变量正态总体* U$ [. d! X( F2 G
Biweight interval, 双权区间
; e, `- a0 R" p& l% {2 OBiweight M-estimator, 双权M估计量
q" T t0 K$ Z% W0 y& K* dBlock, 区组/配伍组+ \) Q# ]/ g4 l
BMDP(Biomedical computer programs), BMDP统计软件包
6 T, k) [/ w+ h& U8 J ~: qBoxplots, 箱线图/箱尾图
5 |2 ] f( o6 a8 g( HBreakdown bound, 崩溃界/崩溃点
# e, M6 t! {& lCanonical correlation, 典型相关
6 k0 T. L7 M, H. r/ C; P0 _* \Caption, 纵标目. a7 d) T, v6 X- l1 _# e
Case-control study, 病例对照研究
3 V; ?% T) h& f9 d% n6 q/ e$ FCategorical variable, 分类变量' L' L" T# x( Z6 [* r
Catenary, 悬链线
5 q: U5 P; o/ iCauchy distribution, 柯西分布- A" t, t' a4 e3 ~
Cause-and-effect relationship, 因果关系
h" C0 H$ f9 W- y' u: l4 YCell, 单元' [8 c. }; J8 H# b) z
Censoring, 终检
, y, Z+ _2 C4 Z9 SCenter of symmetry, 对称中心
5 H# Z3 y+ W& r7 x PCentering and scaling, 中心化和定标
) r( W2 N0 R6 A' g; x- T" cCentral tendency, 集中趋势& I; I( H! B i$ u
Central value, 中心值- C& M) K6 [' B3 D
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测 f3 B" w) W. ?1 X1 A- j
Chance, 机遇3 u7 K2 s8 e5 a9 }
Chance error, 随机误差" R) B9 _0 n- ?/ q' L. e# ^
Chance variable, 随机变量5 \( {9 d% |4 N# N4 k
Characteristic equation, 特征方程
, s0 E$ P/ r2 S+ y. C" e/ lCharacteristic root, 特征根
/ E/ N% g# Y% a- dCharacteristic vector, 特征向量
7 _+ M% J; f* g: p- ]" H, B$ y) C# vChebshev criterion of fit, 拟合的切比雪夫准则% G$ Y( I3 G$ s
Chernoff faces, 切尔诺夫脸谱图
% i% T3 M7 b, F2 cChi-square test, 卡方检验/χ2检验" e$ u) w2 y7 a- L! G8 ^) T/ N
Choleskey decomposition, 乔洛斯基分解
2 t1 h. x* y7 }; V3 d0 g8 U: dCircle chart, 圆图 + R$ M% J( L# p8 \
Class interval, 组距
3 Q) c0 X* ~2 f2 YClass mid-value, 组中值: ^7 v! E4 f A& t! V7 v4 `! d
Class upper limit, 组上限3 x) z* C; Y8 M" P
Classified variable, 分类变量; E" N6 i3 `& R* l- d F" n+ f$ @2 `
Cluster analysis, 聚类分析
m( M0 v% P, A$ `7 C+ g1 MCluster sampling, 整群抽样. l- f# J5 b8 J' t( N5 } c$ p
Code, 代码
! Z1 `5 V; u' \. o+ D/ lCoded data, 编码数据+ H( n& \- g- d" s
Coding, 编码+ M8 L1 J7 i1 C
Coefficient of contingency, 列联系数1 O% R! _5 Q& h Q0 X0 v" {& Q% o
Coefficient of determination, 决定系数/ w4 W" O6 r" c1 C: z
Coefficient of multiple correlation, 多重相关系数6 A4 d( @3 ^9 v/ ? d6 w6 v8 W- c4 ]
Coefficient of partial correlation, 偏相关系数* j; e( ~8 F) I4 N$ `2 x0 b9 w
Coefficient of production-moment correlation, 积差相关系数2 n2 J; }+ M# n: k& e: b
Coefficient of rank correlation, 等级相关系数& ]2 Z; i" Z l2 M4 |9 ^& N
Coefficient of regression, 回归系数
0 O# {' m+ o7 n# J% yCoefficient of skewness, 偏度系数
$ V* q, x+ ~9 H ~( i6 MCoefficient of variation, 变异系数& O( Z- Y( a8 S' X
Cohort study, 队列研究
! O K1 N* C: A+ G; FColumn, 列
4 F8 s8 J" @; y7 n2 `' p$ CColumn effect, 列效应
0 v* ~ K. m0 A; ?Column factor, 列因素
Y e. M; S3 y4 F" yCombination pool, 合并& Z7 b' m% E; Z# z! b% m. U- F2 \
Combinative table, 组合表
1 W! s+ X+ Y" f3 h$ rCommon factor, 共性因子2 U; u B: I9 s/ M6 C/ Y! r/ T/ @
Common regression coefficient, 公共回归系数
5 A" g- l( |8 P. @Common value, 共同值% p0 U$ J1 h8 B# M. G
Common variance, 公共方差
9 t7 A/ Z x0 B5 K# l- ?4 W0 BCommon variation, 公共变异. q: ^- }, Z* `: R. U
Communality variance, 共性方差
i: P3 n9 |1 m' ^) lComparability, 可比性% i" K8 l7 \5 i2 Q/ w" v
Comparison of bathes, 批比较5 o3 ~% \2 h1 a' x. a2 y% q$ c1 h
Comparison value, 比较值! m( o% z- e! W9 v& _/ l4 L+ K
Compartment model, 分部模型, ]6 R2 ?$ H7 R
Compassion, 伸缩
9 h+ u1 s" B( L( HComplement of an event, 补事件
& R) j/ j% {5 b- f% m; DComplete association, 完全正相关! `5 H; n! n- |/ ? E: z; s
Complete dissociation, 完全不相关: r1 Y' w" y: @. V
Complete statistics, 完备统计量
4 g* R2 ?, q8 e/ ICompletely randomized design, 完全随机化设计7 J0 X4 e( S; r/ D# w) i
Composite event, 联合事件
, @3 M' W9 |6 y G: QComposite events, 复合事件
) j; |. }- p# S/ k, p( w; ]Concavity, 凹性
* B& d! Q* [7 k yConditional expectation, 条件期望
! m* c( Q8 D( G7 a$ O$ jConditional likelihood, 条件似然9 b& F; S0 o9 d) H7 B7 n/ ^
Conditional probability, 条件概率
5 e- @0 F8 ^, V- WConditionally linear, 依条件线性! w& n6 g# x9 u* u3 `
Confidence interval, 置信区间
: }* G: y( W, e, J$ _ Q% g' J( wConfidence limit, 置信限
) p+ ~* j7 c: v6 FConfidence lower limit, 置信下限" B- W) w( c( z& {# o3 Q7 T7 }
Confidence upper limit, 置信上限! s! m, _' t$ [" r7 m
Confirmatory Factor Analysis , 验证性因子分析
0 y" Z q/ H! p5 W3 [Confirmatory research, 证实性实验研究: G6 B3 y) q; A w" w" k8 L
Confounding factor, 混杂因素+ b, N0 H: X; s: f3 [0 _- i
Conjoint, 联合分析6 _- F+ U3 h$ N6 D3 Q
Consistency, 相合性2 x6 x4 O& v/ }( }, ^
Consistency check, 一致性检验
# c0 v5 b' y# q- ]# ~Consistent asymptotically normal estimate, 相合渐近正态估计: Y( {* O: l5 w' s) k
Consistent estimate, 相合估计
/ L& h# \% q/ O7 D. qConstrained nonlinear regression, 受约束非线性回归# v4 \7 g& ]0 v6 \( [
Constraint, 约束0 }0 M$ C' K& o( S1 |; x# Y
Contaminated distribution, 污染分布! y! P) | ?# o
Contaminated Gausssian, 污染高斯分布
4 C! v2 |& `& W9 p& Y. mContaminated normal distribution, 污染正态分布
/ t' J' G9 x0 u, q' I( t1 o p$ AContamination, 污染
0 X0 B' S& Y0 O4 {) hContamination model, 污染模型
\4 n9 c F# j7 hContingency table, 列联表
7 b4 R. c; N. Q" o7 Z- H) b$ |9 ]Contour, 边界线6 k0 x2 H$ K7 z* l- h
Contribution rate, 贡献率! O' Q; ?) Y6 X/ h- x
Control, 对照( q6 u1 J& J/ G
Controlled experiments, 对照实验
- s- v# v% ^# U2 L8 k! R: IConventional depth, 常规深度/ V1 l; O4 p% W# O( L
Convolution, 卷积
z9 S' V8 G/ U( iCorrected factor, 校正因子8 @' B8 E( Z6 }
Corrected mean, 校正均值: [: T0 a) U% ~8 \ z
Correction coefficient, 校正系数8 O1 I/ T3 \# h# n- ^2 l5 y) ~
Correctness, 正确性. e. \. @) U, O. d: Z3 w* l
Correlation coefficient, 相关系数( n( _. ^" ]2 T$ u4 K- p4 \# L+ T- d
Correlation index, 相关指数
8 N8 Q8 S) }- w# ]6 q( PCorrespondence, 对应# n0 i* `4 Z2 x+ u
Counting, 计数
2 \5 o) Y7 A% z; ]Counts, 计数/频数
! s0 d4 @# L. m/ x6 @% A, O/ k |Covariance, 协方差
- M2 u& h7 l0 z- ZCovariant, 共变
' `% \* P w; MCox Regression, Cox回归" R [1 }+ ]7 h4 j' V& T
Criteria for fitting, 拟合准则
, v: U" ?" |" d) ?9 dCriteria of least squares, 最小二乘准则
* l1 `" ? b# w/ `2 rCritical ratio, 临界比7 q) R- S7 I5 S! i! }
Critical region, 拒绝域
- j, c: e1 \+ r' l$ {% c) U) wCritical value, 临界值
/ }$ a# O8 l# x$ d6 A$ gCross-over design, 交叉设计; J; Z/ }: N( ]# w3 I" n: A6 V6 j
Cross-section analysis, 横断面分析2 r! _" S3 x+ e( x% S2 X7 k
Cross-section survey, 横断面调查" p4 _1 _2 j) S3 D
Crosstabs , 交叉表 * I% [; A/ v N4 L2 G
Cross-tabulation table, 复合表
( @8 h3 W ]4 M' O, G: C% _9 SCube root, 立方根
' k; [& X( ~5 h; w& H! a8 C( i9 `: kCumulative distribution function, 分布函数
# N! k) Y# f, x8 n3 e( aCumulative probability, 累计概率4 _- I9 K* n( B: ^
Curvature, 曲率/弯曲
0 p. |& v- F4 f) w" v3 f! T: X$ n. xCurvature, 曲率: Q6 U5 k3 Z! J' X8 A5 ~. |
Curve fit , 曲线拟和 5 X, ?( Y' s. B# b! C; w
Curve fitting, 曲线拟合9 ^) E" ]3 k2 @. o4 P
Curvilinear regression, 曲线回归
/ w+ ?' B- t z$ x5 b; uCurvilinear relation, 曲线关系/ o: b; f* K5 Q6 u9 i q
Cut-and-try method, 尝试法
/ Y) S3 J; Y6 V+ q9 xCycle, 周期
; w+ `+ h! @6 O& TCyclist, 周期性
. [" C; G S5 L2 r* ~" T5 D5 K* @* j8 yD test, D检验
3 N( t( e, D2 U& e; b1 i+ {- JData acquisition, 资料收集
* S) R+ C! k/ \+ ]6 w z9 p7 j( JData bank, 数据库
9 H3 \4 Y( Q$ M0 H- d0 EData capacity, 数据容量3 _) |/ y; ?7 j+ y: f9 I
Data deficiencies, 数据缺乏) Q# X- e: w6 Y2 d& ~( l( U
Data handling, 数据处理
* _& ] Z% C2 ?+ R) w2 ^Data manipulation, 数据处理7 f/ e; \+ p9 e! d9 M$ X
Data processing, 数据处理
/ |( J& A% b. d8 n$ mData reduction, 数据缩减) m9 a u& M0 [& I! P
Data set, 数据集% H, I; h0 ?3 E& \ b7 z
Data sources, 数据来源& I1 }/ ~8 q4 {" }7 E4 | |) f
Data transformation, 数据变换
( k" w; E+ _7 e1 @; U/ HData validity, 数据有效性
( E! t7 @1 A) p r" e$ {% H% v2 CData-in, 数据输入$ }* `$ ]) q8 E. `( J) z
Data-out, 数据输出
1 b( b; A0 {; P! m5 b& |% jDead time, 停滞期
$ N4 {( o- b8 Q" e+ p7 a9 P! KDegree of freedom, 自由度 {' a0 g! ?+ ?& w* b
Degree of precision, 精密度- Y/ N4 l- Y9 n1 Z! T
Degree of reliability, 可靠性程度& O; b3 H9 v& b. ?9 W4 _
Degression, 递减1 ^0 D: A6 }& _: N0 H+ l; h& T% g! p
Density function, 密度函数
. C$ i# Q7 [' O* P1 Y, T6 L; BDensity of data points, 数据点的密度
1 l" r3 z6 A, MDependent variable, 应变量/依变量/因变量
M5 b$ o8 B' t( a3 RDependent variable, 因变量
8 H( m9 H8 F- p( o& S* jDepth, 深度- k5 g* ^9 \ E- V! _# C" I6 L
Derivative matrix, 导数矩阵
( j- F Y. Y- m) U( `0 bDerivative-free methods, 无导数方法
2 u1 f( V* I0 ]1 J0 j" f2 ADesign, 设计
+ P$ v8 m" b4 M" KDeterminacy, 确定性
% T7 S' y- N$ o! l9 z0 k3 lDeterminant, 行列式$ b$ F& x% A% B2 V
Determinant, 决定因素
J) a3 k# v6 d' b# Q2 M! u! WDeviation, 离差9 {9 q; r6 S- F" p9 {
Deviation from average, 离均差
0 p2 ^5 K E7 M6 i- ?Diagnostic plot, 诊断图+ y6 C9 v( W# w
Dichotomous variable, 二分变量
1 S2 z2 z8 L) j- F1 w0 D0 pDifferential equation, 微分方程5 q* {& w4 o8 R6 | w8 Q ^# G
Direct standardization, 直接标准化法
6 |- u2 f) T; }0 n! p) i% X/ U3 `- l' VDiscrete variable, 离散型变量7 i1 ~2 o8 q7 G0 Z
DISCRIMINANT, 判断
* i9 D$ e* |9 G9 `1 A6 pDiscriminant analysis, 判别分析
) g8 x% p5 W% d, i* @Discriminant coefficient, 判别系数
5 `( Q/ U; R/ i5 R8 U4 _Discriminant function, 判别值! I: u9 c# q4 u3 Q! t6 f
Dispersion, 散布/分散度
6 Q* d; N3 g8 ADisproportional, 不成比例的
' ^3 M, Q% d+ ]# w# FDisproportionate sub-class numbers, 不成比例次级组含量5 X5 K' e, K% y3 H5 ^2 k( H, @
Distribution free, 分布无关性/免分布
, {/ ~7 @/ n! n( `4 nDistribution shape, 分布形状
. ` ~6 D( Y7 cDistribution-free method, 任意分布法
* g, e+ z. B% GDistributive laws, 分配律
5 R6 V) k( N% Y; B2 @9 c C( FDisturbance, 随机扰动项
* k. S% f9 ?: |- y: n1 m& YDose response curve, 剂量反应曲线. V6 N! @, \! N5 H* k. j& W. F
Double blind method, 双盲法
& Q8 C* J# ]: j Z' p: o. iDouble blind trial, 双盲试验
V, Q( O t" N/ M+ r% w0 M# DDouble exponential distribution, 双指数分布
0 `9 ]( _3 c1 z; C3 W8 ~% rDouble logarithmic, 双对数7 r+ `4 |' ^ ^
Downward rank, 降秩' s8 m g% Q9 q5 B- M
Dual-space plot, 对偶空间图) E' p& D/ }: X+ }
DUD, 无导数方法" S. C S; D" o$ f
Duncan's new multiple range method, 新复极差法/Duncan新法
, r, S9 y8 }& W G3 R# D- @Effect, 实验效应
! `6 c; b* i. NEigenvalue, 特征值' m, m7 S4 l6 s! d& ]; I* Q2 j4 B
Eigenvector, 特征向量/ Q" R* [9 b U7 D- j# u- {" f
Ellipse, 椭圆( I6 ^. k' m" O- L
Empirical distribution, 经验分布8 M% e+ j: I' X; P2 H, [
Empirical probability, 经验概率单位
* o$ m9 _' j. `' o; U0 \3 fEnumeration data, 计数资料
R) @5 |6 p7 R% xEqual sun-class number, 相等次级组含量
) R' P6 w7 a# g. wEqually likely, 等可能
* [/ h1 u7 l( l' H0 EEquivariance, 同变性: j: M# d. ]2 u8 B1 r
Error, 误差/错误
6 R2 z) w/ x# A1 fError of estimate, 估计误差2 ^) t. U: K- ]' x) {; Z: B2 n
Error type I, 第一类错误2 y ?) n- o4 a3 O, r
Error type II, 第二类错误
! t! v% `2 w2 V% M$ {Estimand, 被估量* L, j, M1 E; L7 N8 {
Estimated error mean squares, 估计误差均方, e& A3 C3 M% l4 W$ c6 V" p
Estimated error sum of squares, 估计误差平方和
h" c" E% w t5 o, _( C6 DEuclidean distance, 欧式距离
& c5 Y% ^- ]7 j# ?% tEvent, 事件/ V- K, _2 H! A( H( P$ Q8 G q
Event, 事件
$ }' M" H& l" \: D+ xExceptional data point, 异常数据点2 X% e7 A0 b9 d- D6 k8 o2 h) u- H
Expectation plane, 期望平面
: M8 F( H% u5 u0 RExpectation surface, 期望曲面
+ ]6 H: f8 Y [9 {3 n& @% ~Expected values, 期望值+ z4 |! b1 V/ I6 [1 c
Experiment, 实验
1 J& C% N+ q! `+ I0 tExperimental sampling, 试验抽样) R+ b w$ Z. B; _/ _
Experimental unit, 试验单位+ g* E8 T% F) [3 l, @& n
Explanatory variable, 说明变量
3 q# i* U; W" }+ E5 t$ YExploratory data analysis, 探索性数据分析" {) g8 S: c6 a! z {
Explore Summarize, 探索-摘要
* y) ~4 l6 H% P7 I' qExponential curve, 指数曲线
: R' o5 r4 C g/ z2 {4 @Exponential growth, 指数式增长2 k6 \9 j5 `+ \: a4 o! `, w+ W
EXSMOOTH, 指数平滑方法 ! v2 P5 U9 x* q9 g3 x
Extended fit, 扩充拟合4 T K. j; ~/ A4 a: l* v, M8 l
Extra parameter, 附加参数
2 x& N% q0 o/ O- E$ y+ h% P" ?Extrapolation, 外推法8 ^8 K: U+ y3 i
Extreme observation, 末端观测值6 ?, S$ ]0 |" ?7 G: u3 I
Extremes, 极端值/极值, V# F0 g- s' s7 c# b7 s3 l
F distribution, F分布+ I- ~$ F, n) ?1 Y) U
F test, F检验: h3 n o8 p0 n* X) F% s
Factor, 因素/因子
- B1 D: _6 }% p- QFactor analysis, 因子分析
+ r. z+ d3 H; t& T' kFactor Analysis, 因子分析6 |# [7 F0 `- ]8 G
Factor score, 因子得分 ! ]9 ^0 n+ k9 o! A8 `- p
Factorial, 阶乘8 J# U8 @- F5 d8 {3 l+ i! }
Factorial design, 析因试验设计& j) {+ v+ |, _, U$ J9 @& E
False negative, 假阴性$ i5 ]5 @9 X7 P3 I8 }
False negative error, 假阴性错误
+ o# { y8 o1 l4 K" p! r3 xFamily of distributions, 分布族! M _. Y" k, u
Family of estimators, 估计量族5 U4 G0 @+ e# P1 H. f8 n
Fanning, 扇面
, B% l- O- L1 k+ b: g* aFatality rate, 病死率
8 _: Z# w1 k+ h4 fField investigation, 现场调查$ r0 R( k, l( e& y# h
Field survey, 现场调查
: Q( S1 h0 j8 T0 vFinite population, 有限总体2 O, @7 J8 H( @
Finite-sample, 有限样本) ~; r6 l6 c; g) X! T( R
First derivative, 一阶导数
2 P# c; t! h w; @$ A [1 X6 c- wFirst principal component, 第一主成分. W6 Z! L. F7 i0 p
First quartile, 第一四分位数
2 \( h$ \9 `8 t0 X/ y. l' V0 d& EFisher information, 费雪信息量7 y% L v0 ~( X) u3 k1 w
Fitted value, 拟合值' k ~/ i5 H- c
Fitting a curve, 曲线拟合
$ R- V9 }7 E7 L( E! l& AFixed base, 定基
; B3 P# X6 U: V9 W( @ lFluctuation, 随机起伏3 G" z; Q6 A, D5 n$ ?
Forecast, 预测7 g9 P* _8 P3 G$ e0 H2 q
Four fold table, 四格表
5 `; e6 ~" O" jFourth, 四分点" Y. _1 W9 ~- e, B1 M" {. `
Fraction blow, 左侧比率4 Y0 ]2 s Z |/ u* F$ ]3 \
Fractional error, 相对误差4 A* l& d5 d3 m
Frequency, 频率% S" Q2 w/ [& m3 a
Frequency polygon, 频数多边图! G9 x& D, w# \( N
Frontier point, 界限点
$ _; W" O# \7 A) ^5 T) KFunction relationship, 泛函关系
4 N5 l' _! c k' `6 p8 R/ S; v8 M7 kGamma distribution, 伽玛分布
# M1 ~& M Z3 |( L, r) JGauss increment, 高斯增量
3 F1 e1 h z) x3 ? f7 Q% P1 g, GGaussian distribution, 高斯分布/正态分布2 N4 E3 |: N$ @4 x e' U
Gauss-Newton increment, 高斯-牛顿增量" K% t4 U+ l& t1 X) x# W2 V
General census, 全面普查1 A6 d( y" D/ b- i0 m. o
GENLOG (Generalized liner models), 广义线性模型
' L- y( I8 |1 H; E' ZGeometric mean, 几何平均数$ ^$ m" s1 s% @4 Y4 P* q/ _
Gini's mean difference, 基尼均差
; k2 ^ u0 `0 J6 wGLM (General liner models), 一般线性模型 ! k& ~9 s$ g* v: h, A
Goodness of fit, 拟和优度/配合度( G5 ]5 \% v; D1 r
Gradient of determinant, 行列式的梯度" | C1 E6 `; @6 x
Graeco-Latin square, 希腊拉丁方8 u5 D+ N5 r) o* w/ e. d
Grand mean, 总均值& p- _# @( ]' a# J( k
Gross errors, 重大错误* L7 p4 n: I7 u7 e' M! b
Gross-error sensitivity, 大错敏感度
7 ?4 }' D& A# Z/ w6 p5 L: {Group averages, 分组平均/ M/ k& x% L/ c: u0 M( r2 s
Grouped data, 分组资料: a+ c) m0 @. ^! ?5 `# a! e
Guessed mean, 假定平均数
3 [$ S! k& T5 N6 I! L- O7 |& U5 AHalf-life, 半衰期3 z; x i2 b3 z, W4 I6 h; }7 ^: n" ]
Hampel M-estimators, 汉佩尔M估计量
9 N4 m: D. o; f7 OHappenstance, 偶然事件+ k7 U" x8 N6 w# M9 c* J
Harmonic mean, 调和均数
5 T- s$ Y [. a1 j) W! R QHazard function, 风险均数
) r0 L W* ]& ]0 {Hazard rate, 风险率
2 v: x# u+ `) w/ d2 J4 yHeading, 标目 - w/ Q! |3 s- E9 P" k
Heavy-tailed distribution, 重尾分布
- r+ m5 \' P: H% T0 H+ `; ~2 x. B" qHessian array, 海森立体阵* \1 W& ^* ~7 m2 ?7 S
Heterogeneity, 不同质& T0 g# V6 O! J3 ^* @& q7 S& y: ?
Heterogeneity of variance, 方差不齐
$ u. n! k3 W! m2 ~2 M2 Z6 \/ IHierarchical classification, 组内分组
/ J: a3 M% \' a: `0 RHierarchical clustering method, 系统聚类法/ F d( f/ q5 ]2 M
High-leverage point, 高杠杆率点
1 I- K9 {& e$ x! t/ C1 ~* k% z. xHILOGLINEAR, 多维列联表的层次对数线性模型" f# t6 k: v3 K, L# m7 F. N, e
Hinge, 折叶点
- P4 K8 m: ]1 sHistogram, 直方图' Q. H$ q! o3 f M
Historical cohort study, 历史性队列研究 4 d* U& F9 }3 Q" I/ d( O
Holes, 空洞+ P6 r& U, ]0 l$ A, D
HOMALS, 多重响应分析
# v8 V3 o5 y+ ~. ~. s1 rHomogeneity of variance, 方差齐性
+ c0 e- o- F( w. t( B9 K: g1 L5 RHomogeneity test, 齐性检验
* z% r8 {1 k- X- v+ N. S$ u! c0 |Huber M-estimators, 休伯M估计量$ U" U0 _' d ^0 h, j {( D
Hyperbola, 双曲线
2 ^; @9 F2 Q) b7 IHypothesis testing, 假设检验2 ?8 Y$ c/ ^- N* D( u$ k
Hypothetical universe, 假设总体( }) H, G1 s6 O5 Q: N3 {
Impossible event, 不可能事件- W/ F+ T$ G" s
Independence, 独立性
6 ?+ _) B' G* M$ ?$ v+ @6 qIndependent variable, 自变量
8 T: Q2 V- i% G) x/ ~Index, 指标/指数" o# f! e8 o6 i; z4 ^9 o
Indirect standardization, 间接标准化法6 t. j( V" X- u2 L. o: E F: ?1 h
Individual, 个体
/ T" O; E/ l# Y- ~0 t+ \Inference band, 推断带6 c- P' n2 I1 T/ L* |
Infinite population, 无限总体# k' e5 X8 f. T% I- W
Infinitely great, 无穷大' o2 Q/ f. a7 b" k( m
Infinitely small, 无穷小
2 x1 z. ?0 E$ y. @7 a9 H1 MInfluence curve, 影响曲线; k, M- E4 w) v! [
Information capacity, 信息容量
# H. k, w% t3 ]# P9 n0 r5 v) Y- WInitial condition, 初始条件0 B. V$ ]8 k. H. k, e5 ~
Initial estimate, 初始估计值
% c+ z- {7 Z" ?1 ]Initial level, 最初水平* N3 _( _' N9 s! i. O( {! N
Interaction, 交互作用
5 h/ x5 E' N, J3 f+ | HInteraction terms, 交互作用项
7 `2 O: o, p. I4 ]Intercept, 截距
3 I- I# }- R! K) f: r3 u1 A' Z; k8 q- qInterpolation, 内插法+ K) Z3 O9 R0 [, ~
Interquartile range, 四分位距6 y/ q$ L( P4 V
Interval estimation, 区间估计
) h2 ]1 H% h' KIntervals of equal probability, 等概率区间
: J+ Q5 c; o' VIntrinsic curvature, 固有曲率
6 m1 {+ ?8 E2 N2 H/ ]Invariance, 不变性
8 S' S i# l7 a* Q2 _. D9 eInverse matrix, 逆矩阵
, c8 j3 _# j9 {) r5 G, NInverse probability, 逆概率
, S1 ^, Y# D8 l. GInverse sine transformation, 反正弦变换
, l$ i- t+ Q$ h- D" tIteration, 迭代
5 g" R ]: A! l, ~- u' N& tJacobian determinant, 雅可比行列式' M, u8 g0 n. h0 Q7 A
Joint distribution function, 分布函数
1 |- k7 x2 C+ `* [0 hJoint probability, 联合概率& _* f7 h: G" b6 z2 u9 J0 i! T
Joint probability distribution, 联合概率分布7 L& ^# [& J5 L1 p! \
K means method, 逐步聚类法
$ e y- u" ]) o0 p a0 \) }1 IKaplan-Meier, 评估事件的时间长度 " a# x1 Z: A( C) ~, e; ^) ]; |* R" h
Kaplan-Merier chart, Kaplan-Merier图
- P+ |5 e% R: Q3 _7 pKendall's rank correlation, Kendall等级相关
. J" F. M3 q; f' y0 c+ @Kinetic, 动力学/ s# J7 D6 k9 m# f8 j& B
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
- I, U- ]; a; W3 p( P, sKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验) @) n4 o# f7 j7 Y# d2 n
Kurtosis, 峰度
* z. w: \% N% u3 mLack of fit, 失拟
! j& m4 X% E9 F. ELadder of powers, 幂阶梯- e: W' v) Z3 T# c6 Z- W; @
Lag, 滞后6 ~% ?2 N9 ?+ g
Large sample, 大样本1 ^) z ~8 Y3 C5 J5 c9 I) d
Large sample test, 大样本检验
: v2 z# O; n+ A7 w7 f) g& oLatin square, 拉丁方
# a o9 S4 w0 Z0 E* ]: E) A9 ?Latin square design, 拉丁方设计
( ?8 ~; T, c3 y. D0 V) DLeakage, 泄漏) t3 E( W+ u! d6 a
Least favorable configuration, 最不利构形+ f; h( a, d5 c3 @
Least favorable distribution, 最不利分布
2 z4 e& l% j8 i% N( b5 cLeast significant difference, 最小显著差法
( z( h$ G% H0 X! H1 KLeast square method, 最小二乘法; q" {( C! D) d
Least-absolute-residuals estimates, 最小绝对残差估计
. T- R. d2 z& P" a8 c& NLeast-absolute-residuals fit, 最小绝对残差拟合
5 |1 D3 B$ Z) D* QLeast-absolute-residuals line, 最小绝对残差线: k+ t& {( \0 {
Legend, 图例! M% [6 |6 U. l' n' ^5 p; O
L-estimator, L估计量
- C5 `1 ]2 N" M2 @0 L/ c7 k! D$ X" mL-estimator of location, 位置L估计量5 U$ Z5 J* O# \
L-estimator of scale, 尺度L估计量5 C+ Z( x! V" X+ g4 w$ f$ L' l
Level, 水平8 k* U" }2 A' s. v B
Life expectance, 预期期望寿命* r/ z) s- W2 K3 k' D6 F( M9 Q
Life table, 寿命表
) Q: k+ N4 [. Q- f" GLife table method, 生命表法
2 ~1 F- d* v$ [/ K Q9 ^9 R( j1 BLight-tailed distribution, 轻尾分布
- s2 O, ], G' k2 j4 N% P( y9 ULikelihood function, 似然函数; J1 M' b% ?4 Z4 M2 \# z" n, ?
Likelihood ratio, 似然比# A) X' [0 {$ u$ x1 j9 B9 J
line graph, 线图
+ X& g, _# x7 m6 l0 s% hLinear correlation, 直线相关
4 w z @. f: e1 w5 D! G* HLinear equation, 线性方程# }8 b3 i# I7 ^8 Q5 G/ t3 X
Linear programming, 线性规划
/ e3 f1 H2 w6 Q. F: T' l, @/ e& tLinear regression, 直线回归% F3 [6 g* s7 f& c- R/ ?. Y) c6 E
Linear Regression, 线性回归
: q0 d4 H' ], t) ILinear trend, 线性趋势/ j1 C1 b2 ?: C, t$ [# X
Loading, 载荷
; p1 }, n& M. e8 P: n$ n8 DLocation and scale equivariance, 位置尺度同变性
# p9 d& y3 d9 CLocation equivariance, 位置同变性* d- @) A4 I& x' W, ` L9 i' v9 w
Location invariance, 位置不变性
" ]; H' M, l! G" D0 W2 lLocation scale family, 位置尺度族
" N5 [. w9 ^7 O) l. K( ELog rank test, 时序检验
! ~) b9 W, o3 u2 g3 G, CLogarithmic curve, 对数曲线
$ @4 G$ u# D% K, C. TLogarithmic normal distribution, 对数正态分布6 G3 W6 ~4 \& i F. j# M
Logarithmic scale, 对数尺度, d5 f$ `( n. Y1 k1 q
Logarithmic transformation, 对数变换6 j3 }2 P1 G( ~, d5 b
Logic check, 逻辑检查
( o# z; ]3 l( i( S. d8 CLogistic distribution, 逻辑斯特分布# Z6 o1 G: u! E+ L
Logit transformation, Logit转换
) R( O' [) j5 fLOGLINEAR, 多维列联表通用模型 ; r( ^, h: c, r$ Z8 X
Lognormal distribution, 对数正态分布4 M% g9 p$ I: H
Lost function, 损失函数+ K8 @" ~. d8 ?2 S3 c8 z8 `
Low correlation, 低度相关; K% U5 @0 g, f. y
Lower limit, 下限
9 M w4 w r9 u3 Q% U1 r7 kLowest-attained variance, 最小可达方差
1 X9 n$ J" M: r* z P- x% \2 BLSD, 最小显著差法的简称
. ]2 ~# ]! r3 X( m4 B9 [4 ~2 vLurking variable, 潜在变量8 B8 |, L2 n) ]# O6 v ]. z
Main effect, 主效应* V' [8 A8 E6 j5 H$ ^1 _& _
Major heading, 主辞标目: K8 S1 F; ^* _& w! d4 @
Marginal density function, 边缘密度函数
* N4 W+ \- _* [' lMarginal probability, 边缘概率8 I. E5 t* L, ]: D, V0 z
Marginal probability distribution, 边缘概率分布# h$ W- l8 S9 b* I! u7 F- L
Matched data, 配对资料7 e/ G! p2 M8 h0 Z2 q5 E9 V
Matched distribution, 匹配过分布/ q4 ^, T4 ?0 |, o* g& z' x
Matching of distribution, 分布的匹配
# J7 k$ Q) F* d# a4 {Matching of transformation, 变换的匹配
: j6 M+ B, {5 p2 n! X p/ E) mMathematical expectation, 数学期望9 _. ^1 b2 i: X2 g) ^
Mathematical model, 数学模型
5 g( g9 ^6 W: s! H) M" h: GMaximum L-estimator, 极大极小L 估计量7 J( E& Q: ?( F7 w R1 b
Maximum likelihood method, 最大似然法
/ @* o" |, Y5 A8 M: CMean, 均数- }3 @! w5 b) [/ T# @% {% N
Mean squares between groups, 组间均方% `" z. b& E' I1 T4 o; o
Mean squares within group, 组内均方
! k' e3 Z( q) V) f2 g1 n& `Means (Compare means), 均值-均值比较
" j* @5 f( Y0 p. a; DMedian, 中位数
r. z C1 t1 e, h8 CMedian effective dose, 半数效量
* F; o8 w8 S! K7 B5 NMedian lethal dose, 半数致死量
0 C' ?# C4 l8 N1 o' DMedian polish, 中位数平滑3 k3 a, i: `8 S
Median test, 中位数检验5 @; \5 |( R! Q6 T; r. A
Minimal sufficient statistic, 最小充分统计量
, s% B% t8 ]3 s$ Z/ K5 n+ wMinimum distance estimation, 最小距离估计) z$ z' h9 s; ~9 |6 l! v9 f/ A
Minimum effective dose, 最小有效量/ U) j* H9 `" M% J, w3 c- q9 M: n
Minimum lethal dose, 最小致死量
2 m) [% s, j' N4 m2 v& gMinimum variance estimator, 最小方差估计量. D2 h7 D8 w( `
MINITAB, 统计软件包
$ S5 c: t8 F/ ~) lMinor heading, 宾词标目2 @! U& B2 F! B1 Z/ i6 ^
Missing data, 缺失值
5 U5 y- m$ o$ y0 \* w0 R; ^Model specification, 模型的确定7 k4 [. `. q1 X6 @ c
Modeling Statistics , 模型统计' c- L& U/ M) _( a) g1 a" w; L& {/ K
Models for outliers, 离群值模型
+ L4 s- e8 z5 C* D+ O3 g# X; R* XModifying the model, 模型的修正
5 O+ L0 s1 N `" C# @2 ^Modulus of continuity, 连续性模
; T4 X! {( F* ^Morbidity, 发病率 2 Y2 ]/ c+ n$ P6 ~
Most favorable configuration, 最有利构形0 Y& |% L* O( \2 W0 A% c
Multidimensional Scaling (ASCAL), 多维尺度/多维标度, l# @- G$ n) P$ |1 ^5 c
Multinomial Logistic Regression , 多项逻辑斯蒂回归
: N% u# e0 t# N3 EMultiple comparison, 多重比较" o% M9 y4 Y, m m, `* U
Multiple correlation , 复相关; E* ]1 }4 _$ c1 w! c0 g
Multiple covariance, 多元协方差
; X6 V3 G3 g, K4 _$ i/ c. EMultiple linear regression, 多元线性回归6 y+ V' I% M4 W' D7 }/ F0 e( m# B0 Q
Multiple response , 多重选项& e$ P/ D& ^1 X' c0 W6 Z; @
Multiple solutions, 多解/ R, G( A1 o* a8 V$ i& `8 C
Multiplication theorem, 乘法定理
3 K# m9 G% p' M' ^Multiresponse, 多元响应/ V# w0 f' \/ ^. _( M4 s) F+ D b: U
Multi-stage sampling, 多阶段抽样
4 w! A8 k4 q9 [; z ~; f/ }Multivariate T distribution, 多元T分布+ t9 g+ s4 h# x
Mutual exclusive, 互不相容
! [7 D/ C5 V! T6 U& IMutual independence, 互相独立. o# }( J8 ^8 K
Natural boundary, 自然边界8 q1 R$ k2 L' j2 p6 s# Z9 |
Natural dead, 自然死亡& a* w2 X+ v& x
Natural zero, 自然零7 X: v- O6 H5 `' p7 V
Negative correlation, 负相关
) K" K* K; f) |( x( R- }Negative linear correlation, 负线性相关: `# t* ?4 o7 u* x) F3 Q
Negatively skewed, 负偏6 T% i# M+ [8 z% ^7 L5 ^7 F
Newman-Keuls method, q检验% T8 q0 I0 U2 J& _5 p: D: G
NK method, q检验
. [. z2 ~5 d) E$ KNo statistical significance, 无统计意义
- _/ n- R% K* zNominal variable, 名义变量" Y" k# o( X. ^$ W
Nonconstancy of variability, 变异的非定常性2 t0 v K% l& S8 \: x9 p
Nonlinear regression, 非线性相关5 X6 f3 d T# e; G
Nonparametric statistics, 非参数统计# j$ X4 [! E8 o& q0 e1 k0 k
Nonparametric test, 非参数检验
$ c" @6 C4 C" r R7 \. r. b" nNonparametric tests, 非参数检验
. H$ r3 _8 ^, u: gNormal deviate, 正态离差6 q( A4 j% |* l) C( [* _
Normal distribution, 正态分布
$ T) i2 f4 D( v$ X8 Q5 b; e8 TNormal equation, 正规方程组
; B+ V: j3 d8 l/ O8 z3 ~Normal ranges, 正常范围
' B4 l' Y5 d: F( ?$ l. qNormal value, 正常值; {! K& g* k# P7 z+ q
Nuisance parameter, 多余参数/讨厌参数9 G9 r6 L' }. T( N6 O
Null hypothesis, 无效假设
! f6 w* z9 k- {Numerical variable, 数值变量
" y. n& y; A; f; `Objective function, 目标函数) k3 N% d# N) j: U. m4 W9 \
Observation unit, 观察单位9 c6 d; F9 O7 Z( N. z2 r- ~
Observed value, 观察值
( b0 ~2 d4 H! U2 a8 _1 B; HOne sided test, 单侧检验: W: J$ e7 X9 e: }( B
One-way analysis of variance, 单因素方差分析
6 G4 l9 A5 u9 L- B7 G. K+ D2 C: {Oneway ANOVA , 单因素方差分析$ W( Q6 M- G4 |1 Q5 O9 g: ^6 e
Open sequential trial, 开放型序贯设计/ n% x }9 P4 x# c' t, G T
Optrim, 优切尾
: H/ l9 c& [$ c& x5 \Optrim efficiency, 优切尾效率1 Y' v+ v2 C+ Z S* x& ?) d
Order statistics, 顺序统计量* q5 P( }1 t7 v0 j3 z& W& D, h5 w
Ordered categories, 有序分类
0 |, |7 g- ^6 W8 I ~Ordinal logistic regression , 序数逻辑斯蒂回归: D( y9 d( [: _5 _0 ?+ N) I$ J0 @
Ordinal variable, 有序变量: i. v% O6 b* F; y/ B
Orthogonal basis, 正交基
8 c3 @4 u% |. ZOrthogonal design, 正交试验设计5 U, M1 D* T8 y
Orthogonality conditions, 正交条件
) ]. \: y5 v/ r1 c* zORTHOPLAN, 正交设计 3 H; D6 L" q& _0 `5 ?& S
Outlier cutoffs, 离群值截断点
7 J) x; _- n5 ~) V) y7 u( lOutliers, 极端值
}) m j U' C$ y2 l5 D7 s6 U, fOVERALS , 多组变量的非线性正规相关 : X9 D) o/ s8 |! c
Overshoot, 迭代过度
) Z) f; u& u! fPaired design, 配对设计
8 P3 I3 j( n, P) \, @( H7 ePaired sample, 配对样本 _: ~3 r5 O: r" k
Pairwise slopes, 成对斜率
- Z8 I1 |3 K! ^! C* l5 AParabola, 抛物线
. i/ z8 e6 X% o& K9 XParallel tests, 平行试验 L! P$ Z3 n! X
Parameter, 参数
; |* b' ~; d% a1 z: o3 tParametric statistics, 参数统计. B3 X9 o+ M A2 f, h% n8 b: L
Parametric test, 参数检验; E T+ |( l6 c1 ~
Partial correlation, 偏相关! g' F! H* \" z
Partial regression, 偏回归
" u: ~8 A) z! r3 E* I' S# cPartial sorting, 偏排序- k$ `& U4 [1 X3 k
Partials residuals, 偏残差
% c! e: q1 n2 l, z5 n7 g. `Pattern, 模式
5 c$ U$ D( R1 Q$ r& l* G7 _& mPearson curves, 皮尔逊曲线& [3 [/ f4 i' p( O& Z$ Q; w
Peeling, 退层
) f" x3 K0 V0 s$ EPercent bar graph, 百分条形图
, @4 @6 F( S" I0 k) UPercentage, 百分比
- t0 O& W P4 l: e& G+ F; ]1 ~Percentile, 百分位数) q2 C: ]" R6 y7 A1 h
Percentile curves, 百分位曲线
! m/ H0 Z2 y9 M+ V6 I3 O' ~* dPeriodicity, 周期性; A: F; C( e$ U
Permutation, 排列
6 v) J' X" Y+ j. n2 T3 `6 sP-estimator, P估计量
5 V9 m' ~+ @4 Z: R. M% OPie graph, 饼图' U2 f3 z. L" Z
Pitman estimator, 皮特曼估计量- d& I& c( O; b+ C; Z" v- I- o
Pivot, 枢轴量
! p r) Q1 E+ W4 S& GPlanar, 平坦 }/ d, v7 n2 g- `
Planar assumption, 平面的假设
% u! ?$ w+ R" @PLANCARDS, 生成试验的计划卡
3 h3 y, q0 M# r6 S I& WPoint estimation, 点估计
5 C1 E& ^& R% X: \: |Poisson distribution, 泊松分布
* f4 H( x) v( f" F* o" ~Polishing, 平滑
# r" r( m8 r2 O) E+ }+ L2 wPolled standard deviation, 合并标准差
- g' R# q9 h( h( u! ~Polled variance, 合并方差- j4 g8 n8 C. h% F
Polygon, 多边图
4 T) |- b8 @- a9 e/ jPolynomial, 多项式+ M+ E& q% A* E" @/ l1 d' s8 g
Polynomial curve, 多项式曲线
3 H1 g4 o v4 ~( t6 b" X/ g% L; c* kPopulation, 总体
! |- P- Z. w; |Population attributable risk, 人群归因危险度2 H9 Y, n& S& p& L; b
Positive correlation, 正相关
! l( a9 q! G% jPositively skewed, 正偏
0 H6 Y9 A4 f( V1 C7 hPosterior distribution, 后验分布
% d; p! _0 o( b2 b XPower of a test, 检验效能0 j% i4 R& c% l8 n- H. p# o
Precision, 精密度, u. a0 ?' p# {) c- S) f% R
Predicted value, 预测值
: s# w7 D5 }7 E9 g0 Q$ jPreliminary analysis, 预备性分析6 x4 i" {" X' b2 }8 K
Principal component analysis, 主成分分析$ C! v! I6 m6 S; l! C
Prior distribution, 先验分布
. Q& S4 V" |. P5 `4 l# r# f' m4 KPrior probability, 先验概率* ~# J" u) j: I" H7 O' L9 P
Probabilistic model, 概率模型
: c- x0 n, R2 t1 A4 s: Q2 ?probability, 概率2 G1 a$ W: F- b% u1 x. ?
Probability density, 概率密度0 s' K6 f/ @ `+ O
Product moment, 乘积矩/协方差
: `) ]1 V% n8 K' QProfile trace, 截面迹图
. Y9 Q* P- T! Y6 [Proportion, 比/构成比
, D/ J& G6 n( U6 p$ F5 xProportion allocation in stratified random sampling, 按比例分层随机抽样0 _/ Q& c) z& U S- v
Proportionate, 成比例4 N! B8 o$ L" `
Proportionate sub-class numbers, 成比例次级组含量/ s- {' z* U' E- Z* a7 H& `
Prospective study, 前瞻性调查, f( i& S) L. |" ~
Proximities, 亲近性 ' F) j5 f- [- Q8 E1 ?
Pseudo F test, 近似F检验- F+ F5 Y2 |* @& f: {! t5 w6 b+ B z
Pseudo model, 近似模型, y* C5 m, p; H+ r
Pseudosigma, 伪标准差
" [6 B- m( k3 D$ v$ n; E. X* p1 ]Purposive sampling, 有目的抽样
% X. v0 D1 v/ ~# `2 m* `5 @7 FQR decomposition, QR分解8 m7 I' X) n8 W. }; n' }! P* ]
Quadratic approximation, 二次近似! o" _+ h5 x+ p# c6 Q7 U% K
Qualitative classification, 属性分类
/ t( v# Q9 V6 |* C7 oQualitative method, 定性方法* F5 N# y" v7 x/ |3 G
Quantile-quantile plot, 分位数-分位数图/Q-Q图
: y8 k5 J( M# _6 L2 N0 ~3 LQuantitative analysis, 定量分析
9 i! z8 I/ e! N/ zQuartile, 四分位数8 ~, X4 v# V4 r& q+ j6 c4 F
Quick Cluster, 快速聚类8 u9 R( L9 `, w* E
Radix sort, 基数排序
( e2 p- s* n2 Y* K+ _Random allocation, 随机化分组
) i2 A: E9 i0 ~9 Z* _ eRandom blocks design, 随机区组设计# o6 Z% a3 j) T J
Random event, 随机事件
* L( I2 W# t. q5 XRandomization, 随机化5 e1 N' F& X; g
Range, 极差/全距
. V8 E8 [6 ^. T/ Q i) b. zRank correlation, 等级相关
' x. V# Y: v6 e( \% O+ T% O2 Y l6 L- mRank sum test, 秩和检验' g- b* V- `8 @1 z! n$ G
Rank test, 秩检验
& h- {* N- U: V8 \: l8 c" kRanked data, 等级资料
7 C" ^2 o) H& z M' u# t PRate, 比率
' d* J/ L7 @+ | E! m+ M1 r7 gRatio, 比例9 x7 D. N2 ^( u* Z4 d
Raw data, 原始资料
" H: j5 [" ?3 c Z7 q9 q9 q) _Raw residual, 原始残差
7 _) _8 r; q$ T* F& mRayleigh's test, 雷氏检验6 D1 {- O% X0 ^% i
Rayleigh's Z, 雷氏Z值 5 J1 ], S( |' E4 \& |
Reciprocal, 倒数
6 E. f8 d% P2 w; U! o* EReciprocal transformation, 倒数变换
0 u% m# ?2 n: n9 ~ R1 xRecording, 记录. ~, H+ }# N7 k
Redescending estimators, 回降估计量
: `3 R' |, y9 g0 g. CReducing dimensions, 降维4 s# h9 x7 m6 h* o( s
Re-expression, 重新表达" ^" O, @7 N- z! M: `- ?9 b" F) h
Reference set, 标准组
! R" [! n0 h. Y6 _' h/ e( E* dRegion of acceptance, 接受域
7 A9 ^ p9 J: {6 H; t! s& hRegression coefficient, 回归系数- \) C0 I) X" K0 T
Regression sum of square, 回归平方和# Z- d4 @2 q' i {! T/ Z
Rejection point, 拒绝点- e$ ~/ l& i" v4 ^, R. {( \7 ]3 m
Relative dispersion, 相对离散度2 j+ N+ v" G: o1 S% S: Y
Relative number, 相对数
/ r9 _1 u$ \& a4 ?Reliability, 可靠性: G3 c! I6 [/ k- ?
Reparametrization, 重新设置参数
: X2 X6 J& X1 }Replication, 重复" R- s3 f1 `3 K
Report Summaries, 报告摘要* I+ ~4 b: f' R- k1 q! f
Residual sum of square, 剩余平方和
6 A4 S2 M5 |3 n' ]5 g2 t8 UResistance, 耐抗性
: T+ b/ E2 S s; _Resistant line, 耐抗线% j0 ?! k* Y8 b3 R+ ?9 B& m
Resistant technique, 耐抗技术$ \9 I+ T% E6 D2 l( `" I
R-estimator of location, 位置R估计量
, b/ I" {1 J8 n MR-estimator of scale, 尺度R估计量% H6 ^, o" H O
Retrospective study, 回顾性调查* E' T( v. p; ~! l3 c2 p& d: a
Ridge trace, 岭迹
B( C( `: G. URidit analysis, Ridit分析
1 x% {/ u7 }& r! K' |Rotation, 旋转
2 L' }* y' u/ g2 y2 rRounding, 舍入
4 d3 @7 @7 ~: nRow, 行
8 e8 T/ a- L3 ^. d, q6 R4 z0 bRow effects, 行效应
: q( c: A* }5 l! }5 R. @: w' P! ]5 D& @Row factor, 行因素* z* C! V, u$ m+ L# f
RXC table, RXC表
% _* m* E9 [% BSample, 样本
( Z$ q1 l \7 {Sample regression coefficient, 样本回归系数
& Q3 }/ V6 q$ q/ u% x' W+ XSample size, 样本量+ k$ L1 n/ \. O
Sample standard deviation, 样本标准差! m' I! E& Z- k6 R: {
Sampling error, 抽样误差# S1 q5 @& E. _% F) E2 c
SAS(Statistical analysis system ), SAS统计软件包
, A" t& `7 m) x4 o, FScale, 尺度/量表$ X+ G1 k& U: c2 T/ f4 b' O' i
Scatter diagram, 散点图. Z% {$ x4 U8 m6 b
Schematic plot, 示意图/简图8 }$ \6 m; w/ O2 @; V
Score test, 计分检验- G! N2 h$ t; a' Y- w% E Q
Screening, 筛检
. d3 J' `8 @' R, c, c: OSEASON, 季节分析 , \$ |/ {- d" R5 A# a i# \1 \
Second derivative, 二阶导数
" \& {* {5 w- BSecond principal component, 第二主成分( s4 M+ N) {6 `$ o# N
SEM (Structural equation modeling), 结构化方程模型
( r9 d% {# z: F# BSemi-logarithmic graph, 半对数图# ^1 I6 d; f) m: h9 B
Semi-logarithmic paper, 半对数格纸& x+ O' g" S+ P; H
Sensitivity curve, 敏感度曲线7 c8 P4 F9 {. W* a
Sequential analysis, 贯序分析/ Y+ {) ~" o [, x, x
Sequential data set, 顺序数据集0 c. i) {# B1 B/ ^) d! k
Sequential design, 贯序设计) }! A: z7 |- M( o$ ]! `
Sequential method, 贯序法
8 @. b" @- G4 ~9 o& w$ a8 VSequential test, 贯序检验法
3 e& M; N, N8 |* {0 B' `. ~Serial tests, 系列试验: ?8 P! Y( R. i; }' s0 i
Short-cut method, 简捷法 ' e' V4 S$ ?% r8 [
Sigmoid curve, S形曲线8 `+ S! Q% x( Z, d+ @
Sign function, 正负号函数3 p! o' G# f/ F! Z5 N, |
Sign test, 符号检验# f# m! F, T6 C. ~
Signed rank, 符号秩/ H2 G: s+ j2 r1 D& p0 M
Significance test, 显著性检验. ]3 c& X( Y. A9 s! j2 N
Significant figure, 有效数字# ?# m; p; L8 A) \& Y3 G
Simple cluster sampling, 简单整群抽样" U, |3 {$ ~. |; I
Simple correlation, 简单相关
0 ~) [0 V s. ]% r! E) N: SSimple random sampling, 简单随机抽样
1 ?6 D) i- f3 `' j- ?0 x9 L$ a7 YSimple regression, 简单回归
' \. O6 c1 U# Nsimple table, 简单表7 \% Y: f( z9 r& T* J: x9 F
Sine estimator, 正弦估计量0 Z, T* k4 M$ _
Single-valued estimate, 单值估计
+ c, M" d+ c4 J) U6 B% x4 gSingular matrix, 奇异矩阵
$ I' O% ]# J; WSkewed distribution, 偏斜分布. Q$ y, G" w' M7 H' R3 H) I
Skewness, 偏度, ~; F. j4 V& w+ A {, h
Slash distribution, 斜线分布0 z* l G0 E- a% @
Slope, 斜率- m3 @6 n2 B# p) x) W7 u$ o* r7 Q; Z f* _
Smirnov test, 斯米尔诺夫检验
: n& X! Y: W4 e. {6 n8 SSource of variation, 变异来源
`, K! S$ [ }- cSpearman rank correlation, 斯皮尔曼等级相关
' c+ t3 m# e- z: c! n0 A: f% ISpecific factor, 特殊因子
- Q1 v/ l. b T9 T9 WSpecific factor variance, 特殊因子方差) m# H8 F7 t3 J3 T3 _
Spectra , 频谱4 Y0 I- G+ i D; B( a
Spherical distribution, 球型正态分布7 M; O& P# w7 h- D
Spread, 展布& b0 [: `1 ]0 s; G0 Q; U- j) D
SPSS(Statistical package for the social science), SPSS统计软件包' M$ O+ z+ J3 O
Spurious correlation, 假性相关
* _$ X$ q) a- D# kSquare root transformation, 平方根变换
3 |/ d8 ~& A- S6 XStabilizing variance, 稳定方差
4 K9 M: ]6 v0 H! b: ]Standard deviation, 标准差
* M$ `7 C. i( m. p7 `6 tStandard error, 标准误) y- b* H7 i1 D8 @
Standard error of difference, 差别的标准误5 Y1 O% V y9 s+ j& W/ V
Standard error of estimate, 标准估计误差
5 V0 q- Z5 A$ h8 t. [& S8 |Standard error of rate, 率的标准误8 i" Q, f* N+ F8 H
Standard normal distribution, 标准正态分布
7 X( X3 I* H/ O/ e$ ]; c( ~& `Standardization, 标准化% l+ A: Y* |; k$ J
Starting value, 起始值
: @1 V8 m% \+ pStatistic, 统计量
2 G& I, L- ~* b: xStatistical control, 统计控制
6 i& X% N$ U0 d/ S( B/ P9 EStatistical graph, 统计图
' ^* P/ L. x$ f: _: j7 S2 [Statistical inference, 统计推断: y' ~+ W8 k6 J5 J3 t
Statistical table, 统计表5 M/ H" [7 s' Q$ w& ~1 l% _
Steepest descent, 最速下降法9 [8 D% J$ y" }7 D& e1 o7 o
Stem and leaf display, 茎叶图% W1 |" u( A$ `9 a
Step factor, 步长因子
2 h6 p. W4 d- _Stepwise regression, 逐步回归
9 y5 m& F( y7 ]: \( E IStorage, 存
# X- k6 l0 x0 DStrata, 层（复数）
' Z! m( ^; Z7 M8 z+ TStratified sampling, 分层抽样
- K0 `: b6 z l6 |( r/ i5 JStratified sampling, 分层抽样
6 F) j( U1 `3 q7 vStrength, 强度
( J3 |! y9 Y4 {9 }1 ZStringency, 严密性
! }6 E3 C) W5 x2 j1 ]9 O2 p1 `2 TStructural relationship, 结构关系! h4 k: n0 [, \ V2 U7 n
Studentized residual, 学生化残差/t化残差
; Q! j m# w% Q) i! g. E5 ISub-class numbers, 次级组含量
$ V" e$ i/ C% M, [' A! rSubdividing, 分割2 `1 r- Y) J: W. D
Sufficient statistic, 充分统计量
; A& J) P- Q% e# [9 h( a CSum of products, 积和2 t* ?: }5 k. P0 l
Sum of squares, 离差平方和
2 p, I* p' X$ t' ^2 MSum of squares about regression, 回归平方和, D: E( [4 y m7 y' f- m
Sum of squares between groups, 组间平方和
) c& N' O* z( c+ B" Z4 c: QSum of squares of partial regression, 偏回归平方和
% `4 g2 |" `# @' w+ `Sure event, 必然事件
1 G' o- |4 X: L y/ _& ASurvey, 调查
6 l: `/ [) J4 O0 }2 m! cSurvival, 生存分析' q4 S. e+ E7 g3 ~+ B! b
Survival rate, 生存率
+ h7 v: Z4 F: P8 p8 b+ F0 HSuspended root gram, 悬吊根图: M, c+ ^+ j9 F9 Q0 a' O
Symmetry, 对称: Q3 J2 N8 [ Y& U0 A+ f
Systematic error, 系统误差
" ?) m9 Y9 m7 ? A8 C- B' r2 uSystematic sampling, 系统抽样/ v" F4 M F# l/ _
Tags, 标签
3 ?& |0 W4 l& } M: C9 |2 FTail area, 尾部面积
% [$ t5 H7 X2 m' iTail length, 尾长9 h7 W# c4 @3 d) G- h( H7 l
Tail weight, 尾重- ^2 d J) h/ Y7 {, t( f
Tangent line, 切线- i, s2 `5 [/ m) @% U V: [' T2 S
Target distribution, 目标分布
+ v: q5 j( q% u4 p4 STaylor series, 泰勒级数
! V( `: J4 F6 @/ j% i) Z2 BTendency of dispersion, 离散趋势
7 u( f7 b6 u% ~! O. e7 STesting of hypotheses, 假设检验
5 r7 V( t& D: P3 sTheoretical frequency, 理论频数
% r: \4 `5 i! E2 x8 hTime series, 时间序列& U' f# \; }7 P3 K, r, R; N
Tolerance interval, 容忍区间
: n' G. F) W% h- B eTolerance lower limit, 容忍下限
0 q8 i6 r8 s* A) q" p) u7 STolerance upper limit, 容忍上限. a# c% P/ R1 x
Torsion, 扰率
- g4 f% C6 r2 D' @2 A4 rTotal sum of square, 总平方和
4 d1 X8 ]% L$ o$ JTotal variation, 总变异" n, i. c! ?1 [
Transformation, 转换
& m) k3 M; O% x1 v% L+ m4 ?Treatment, 处理/ S9 U, M2 \ T# a @
Trend, 趋势
9 d2 s7 G% n( Z5 i' uTrend of percentage, 百分比趋势6 O' f+ e$ m' R: i5 M9 Z- N
Trial, 试验8 Z8 z( y" \/ s) I
Trial and error method, 试错法) q P3 [1 R; x6 N
Tuning constant, 细调常数2 F/ |+ C9 @6 i- \ W
Two sided test, 双向检验
3 N; }. k' C) p; |Two-stage least squares, 二阶最小平方; a9 n) `! J8 S& r$ r: O9 ~6 r9 k: C
Two-stage sampling, 二阶段抽样
) f6 ^- m9 G' wTwo-tailed test, 双侧检验
, y+ Z- l+ ?+ pTwo-way analysis of variance, 双因素方差分析' a( k0 d8 S" d$ x& I& v. q) Z
Two-way table, 双向表
! L1 D# j( l$ M' c' e$ y+ CType I error, 一类错误/α错误
: {6 M: l4 M' G4 W) f2 W% g7 TType II error, 二类错误/β错误
/ q8 `/ Y- p2 w8 G5 B" W) H; y% \/ u! aUMVU, 方差一致最小无偏估计简称8 y- t3 L- j/ g; G3 b
Unbiased estimate, 无偏估计0 k( j! j; O# w+ `. p
Unconstrained nonlinear regression , 无约束非线性回归; U' @+ t7 f" D" Z' X
Unequal subclass number, 不等次级组含量
2 Y) n% |& e7 W& PUngrouped data, 不分组资料
& g4 }% l! C" U: m D. Q+ QUniform coordinate, 均匀坐标
/ Z# y8 t( ~% EUniform distribution, 均匀分布: k: a3 ]( o# U% ^5 ?4 R
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
$ `+ s/ S: d+ S9 uUnit, 单元; n" R1 u3 k' U% U: ]0 f' s! `
Unordered categories, 无序分类4 Y# q' F; }% I/ r: S6 f/ V# W
Upper limit, 上限
3 c3 K2 r9 g: @* g' w0 x j1 OUpward rank, 升秩
/ v3 w& b- l- WVague concept, 模糊概念2 }# B( V2 {; p: r) z
Validity, 有效性
' A f5 C ^7 @7 X. R( ]7 }VARCOMP (Variance component estimation), 方差元素估计
) v4 c X! J' Q- QVariability, 变异性
# X! ?0 s. B4 Q9 I3 CVariable, 变量
$ S% \$ I% q# [* f; [7 K4 q& vVariance, 方差( A+ _- b5 o0 S W
Variation, 变异
6 T7 g2 C/ L9 r j7 HVarimax orthogonal rotation, 方差最大正交旋转
3 C% Z: E( P* A0 X5 FVolume of distribution, 容积3 j, i* N, X. D4 E1 i. I3 ^
W test, W检验2 r. H5 D, [( G& X' e' m
Weibull distribution, 威布尔分布; J4 z0 i7 Z. B5 ?( u% K6 r
Weight, 权数/ h2 F; g( n( V8 _5 X" Z9 ]
Weighted Chi-square test, 加权卡方检验/Cochran检验. {4 x7 _, P) K5 Y
Weighted linear regression method, 加权直线回归
; Q R" \# E0 o6 Y6 EWeighted mean, 加权平均数
, Q+ E3 p/ O& V5 P- {Weighted mean square, 加权平均方差
8 j, K8 z, y, m# ^) ?, |+ EWeighted sum of square, 加权平方和
; f* ?4 ?, N7 m: T, z0 EWeighting coefficient, 权重系数9 `3 t; W% y+ m
Weighting method, 加权法 , _$ v; J9 l7 }' h0 B: j k9 C
W-estimation, W估计量, u" [1 X+ E* o
W-estimation of location, 位置W估计量' E; a2 }. _" z) z
Width, 宽度
1 V* m+ y( l) U' K+ }# F! U! ~3 E0 ~Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
* Z) ?! A" d, _5 I0 CWild point, 野点/狂点
. t& l/ o* _* fWild value, 野值/狂值
6 T$ O8 n- _2 I5 L8 U3 ]Winsorized mean, 缩尾均值& M% y5 J0 w" B8 a Q( [9 g( `
Withdraw, 失访 , k5 j/ u% ` ]2 `7 d9 g. U% U
Youden's index, 尤登指数
) ?* d5 v) v: Q" JZ test, Z检验1 y) K4 q+ T% b8 U( {# O* F. ?
Zero correlation, 零相关
' l- ~, v# r" B; B9 qZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
