|
|
Absolute deviation, 绝对离差
& T' k; k$ b$ ~% h$ ?9 QAbsolute number, 绝对数" I) n$ h2 e/ v3 U& W
Absolute residuals, 绝对残差& K. x' z, m+ H# r
Acceleration array, 加速度立体阵
7 u& p- \" X* UAcceleration in an arbitrary direction, 任意方向上的加速度2 _6 M9 h8 Z" Z- ]/ l) d; o1 g
Acceleration normal, 法向加速度8 Q8 _% S9 q {2 w0 r2 g
Acceleration space dimension, 加速度空间的维数
( l/ \* n4 x- x$ a+ k: oAcceleration tangential, 切向加速度
! p. G' x5 C G7 V" NAcceleration vector, 加速度向量" X b' @. x! N. F! L
Acceptable hypothesis, 可接受假设
; a3 v! h# H3 H# w9 aAccumulation, 累积1 v G: X$ C) x, Y
Accuracy, 准确度
- `: X+ T- r7 i# e# V, GActual frequency, 实际频数
, M1 |! }/ R6 X3 D& R3 iAdaptive estimator, 自适应估计量3 j! X2 S9 q( m4 j
Addition, 相加* j) N& U. }) y9 A( c
Addition theorem, 加法定理
) A d- v; O) p4 yAdditivity, 可加性
1 D( o/ N/ [# w1 ^" I( {% `Adjusted rate, 调整率! @' d& T: S5 j" D4 I0 S! g
Adjusted value, 校正值
3 a0 B1 q, I% v b& A B: JAdmissible error, 容许误差
3 I6 A% a# B7 lAggregation, 聚集性6 @' S( u5 S2 [
Alternative hypothesis, 备择假设% Q. K( ~1 V1 K0 `( N
Among groups, 组间
+ s& B! b, i/ `( MAmounts, 总量
: T8 k/ W" W; @, s t/ Q6 {Analysis of correlation, 相关分析- M, G; _: i5 h9 r
Analysis of covariance, 协方差分析1 N" X: N" i1 ]& }+ z
Analysis of regression, 回归分析+ Z& e. ~) g; ~ }6 F
Analysis of time series, 时间序列分析
4 z( g; d# w2 W- x' @3 q7 eAnalysis of variance, 方差分析
- n8 |- c7 b" w: X) \# L$ A4 aAngular transformation, 角转换+ P3 T: p5 b: A+ V4 Y9 I
ANOVA (analysis of variance), 方差分析
' O7 k& U! ]4 F8 sANOVA Models, 方差分析模型- O0 s5 f0 W @: |% ]6 u# p
Arcing, 弧/弧旋
% s7 ~. o% M M* X# g' a2 @0 QArcsine transformation, 反正弦变换( r, A! a; o3 `/ O- j# p
Area under the curve, 曲线面积
0 c9 U# L$ N2 E* g1 WAREG , 评估从一个时间点到下一个时间点回归相关时的误差
: H! [" o+ x- U0 DARIMA, 季节和非季节性单变量模型的极大似然估计 & h1 d ^8 d& `8 ^
Arithmetic grid paper, 算术格纸8 t) i. M j" a# |
Arithmetic mean, 算术平均数
7 t/ _4 }+ h7 r+ L( x9 h2 j! [Arrhenius relation, 艾恩尼斯关系
# v" z& m9 W7 j2 ? JAssessing fit, 拟合的评估
' w+ y. V9 A! r, WAssociative laws, 结合律2 A N% L) b0 q& C5 \
Asymmetric distribution, 非对称分布
. Y5 N( P1 P/ d, L/ G ]Asymptotic bias, 渐近偏倚
) Q2 e; b' n1 c6 q* dAsymptotic efficiency, 渐近效率: O+ C5 x! D' ]. q
Asymptotic variance, 渐近方差
% F8 g, V. E: k4 GAttributable risk, 归因危险度8 k0 l' X7 r9 n; p. X" `9 ]
Attribute data, 属性资料5 u7 N) d0 @4 r
Attribution, 属性/ A ?& n; ` Y* ?$ H& n
Autocorrelation, 自相关4 H" G& k! o' p; B: l; T! T
Autocorrelation of residuals, 残差的自相关
& O( b9 _7 o( Q+ SAverage, 平均数6 B- d' H% Y1 m5 |4 D6 T
Average confidence interval length, 平均置信区间长度
2 u" {* X4 w M7 KAverage growth rate, 平均增长率
1 p7 S* f3 }7 mBar chart, 条形图/ p8 h4 V, ^ ~9 r
Bar graph, 条形图4 o; ]6 ?( @: ? }3 {1 O" v
Base period, 基期* {: d) E" _9 O2 N$ ^ j% B+ A; h
Bayes' theorem , Bayes定理" f9 q0 v2 w) R. `; Z# x) _: G) F
Bell-shaped curve, 钟形曲线9 t4 R/ ]( H s9 }
Bernoulli distribution, 伯努力分布% M' p- F! W" X/ |. n
Best-trim estimator, 最好切尾估计量: J; B. S) J- H( K/ P' K$ Y
Bias, 偏性" ^, k) E: l' c) D" ]/ k2 x
Binary logistic regression, 二元逻辑斯蒂回归
8 k3 X& {- K# S2 ~4 uBinomial distribution, 二项分布
; T( V( s! J# w4 H+ y: JBisquare, 双平方) g! N2 O H2 }& G
Bivariate Correlate, 二变量相关
5 @: E6 \/ J, V u1 I2 IBivariate normal distribution, 双变量正态分布
( U% e% @" U8 H9 N+ [; v/ rBivariate normal population, 双变量正态总体
- B* ~, w+ ]0 ]5 k* d. ~Biweight interval, 双权区间( R- L9 R: M; V. Z
Biweight M-estimator, 双权M估计量$ P5 s5 Z" C! \4 c& D: O
Block, 区组/配伍组6 W5 a! T; Z* s4 ~4 R5 ~) r
BMDP(Biomedical computer programs), BMDP统计软件包; v) z7 e* M8 @
Boxplots, 箱线图/箱尾图
% X- d% q# p c. S R5 g- C) s& vBreakdown bound, 崩溃界/崩溃点
5 u3 V6 @6 M- G* n% u( h1 _% cCanonical correlation, 典型相关
- H" A4 R. o. q+ cCaption, 纵标目( v$ V* z5 x1 t# W9 Y: J2 M
Case-control study, 病例对照研究
& G! ?3 z* B+ x, o2 _4 `Categorical variable, 分类变量
0 D" c* `6 s0 Z6 [' F2 QCatenary, 悬链线6 ~1 b2 F2 ?' m! m- q" u: T. s
Cauchy distribution, 柯西分布
1 I8 |" H% }6 U) @Cause-and-effect relationship, 因果关系6 i- E# b, F# P0 j( z" s
Cell, 单元
) ^# j. b& F* A- D9 bCensoring, 终检
7 b3 s8 H$ _3 c/ E, x2 UCenter of symmetry, 对称中心0 e- @ \( l* J0 C8 h1 D
Centering and scaling, 中心化和定标
/ Z! i7 L. O+ S2 s; w' BCentral tendency, 集中趋势
/ E+ B: A5 E+ F0 P3 Z" |Central value, 中心值
3 K: s9 S5 B3 _, l' z5 dCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测5 Q6 p& e+ b2 g3 T
Chance, 机遇$ h) u, T9 C: u$ b1 ?5 T0 ~2 Y- I
Chance error, 随机误差5 m |: Q3 @1 D1 s
Chance variable, 随机变量, Q8 p: C8 ~4 T( O
Characteristic equation, 特征方程
* d; M* G, Y ?. E3 PCharacteristic root, 特征根) [$ b2 @! l6 b1 \
Characteristic vector, 特征向量% c; S3 M/ {% I$ v4 m
Chebshev criterion of fit, 拟合的切比雪夫准则
P% M/ k% X6 W2 D$ B9 [" E3 [Chernoff faces, 切尔诺夫脸谱图
; d2 n' W. _9 M1 E4 t1 RChi-square test, 卡方检验/χ2检验: k6 R- _( t7 G) \
Choleskey decomposition, 乔洛斯基分解6 R' s0 W2 t- a+ p# D
Circle chart, 圆图
0 o. K: V& t8 H% N( I" v5 ^Class interval, 组距6 H) H6 T- t, \7 f
Class mid-value, 组中值
8 e: q6 z9 z. e8 T" ?Class upper limit, 组上限# D8 K7 x# f9 O
Classified variable, 分类变量
, Q# d7 a2 ~0 `/ q- ]Cluster analysis, 聚类分析
7 _6 |0 T* h& @$ V1 a+ u& v# PCluster sampling, 整群抽样, ^7 N6 ~! ~1 ]$ L ]- Z5 k4 p
Code, 代码: {- O! T4 {7 G8 _1 @. c
Coded data, 编码数据
% b6 V1 E$ \) z4 R$ R( @Coding, 编码
+ ?! ^4 D7 ?3 ], F' xCoefficient of contingency, 列联系数
& L6 ~( _/ x5 r; eCoefficient of determination, 决定系数
4 P0 l' y& O' S" u0 B! h; x: LCoefficient of multiple correlation, 多重相关系数
, O, A, i# P0 G& A: k; w+ pCoefficient of partial correlation, 偏相关系数( I) ?# ~8 m7 w$ ?7 P6 M# c
Coefficient of production-moment correlation, 积差相关系数+ `, \5 n ?3 |+ y
Coefficient of rank correlation, 等级相关系数$ n0 W+ K; s6 k. q- E, s2 B. y4 }! C
Coefficient of regression, 回归系数+ ?# l3 f" {, U& n" l
Coefficient of skewness, 偏度系数
# D0 h' U/ ~/ k" Q/ |! D, pCoefficient of variation, 变异系数+ \% \$ `6 i, }8 c. F
Cohort study, 队列研究. J- B1 p' L9 C* L. b& Z
Column, 列
2 a( R9 W6 f5 E- b' `Column effect, 列效应# k L) V8 B' f: D
Column factor, 列因素) g. |4 N# c( U u
Combination pool, 合并
" s: h: }# k3 c9 g: K& xCombinative table, 组合表
" K" R+ y1 {" v1 w. o/ i9 YCommon factor, 共性因子
. V( J( `% U i: \/ Y1 \Common regression coefficient, 公共回归系数. q, U9 [/ T) h7 G2 ~3 Y( ?
Common value, 共同值2 M; t% a7 s" e* _0 e a
Common variance, 公共方差6 n; w" Q5 P' I8 x& o- o
Common variation, 公共变异
1 y# i9 ?% o T/ nCommunality variance, 共性方差
# ^, c) C5 P# o1 W8 l) iComparability, 可比性
' X! Z2 c. ^4 Y1 w% ~1 RComparison of bathes, 批比较9 Q9 Z. n9 G6 M! F1 M
Comparison value, 比较值( d- }; |9 Z' s6 ? }0 K
Compartment model, 分部模型
5 L& a2 z* T3 O; ]Compassion, 伸缩) M4 \$ l* c5 w8 G0 K
Complement of an event, 补事件# Y0 w+ e) C9 k+ t; d( K2 V
Complete association, 完全正相关7 O! J2 o+ v U' m9 f, F$ j
Complete dissociation, 完全不相关
+ o! `7 {* T$ }2 S! t& u; qComplete statistics, 完备统计量
5 A( j7 c4 x! }5 w8 f eCompletely randomized design, 完全随机化设计5 z3 Q$ q3 B0 p j8 D# ^
Composite event, 联合事件* t: x0 P. |2 G, J8 Z3 }/ V7 E
Composite events, 复合事件
) K2 w1 i* |( n- k5 Q5 {# BConcavity, 凹性
/ n7 _! }$ |6 l! r2 p; d/ {) N% cConditional expectation, 条件期望
' i* `$ b$ Z% jConditional likelihood, 条件似然
2 [ C; n0 i! U" i- }6 y( DConditional probability, 条件概率7 @% T1 u# I# V* m! C* Z" |
Conditionally linear, 依条件线性
+ t2 L$ o( s# z, z: G+ a8 DConfidence interval, 置信区间
: y- O* s/ T# ?# L( g- x$ S3 \Confidence limit, 置信限
' |& }7 I9 g. L. pConfidence lower limit, 置信下限1 d! s2 P; c. X
Confidence upper limit, 置信上限) S6 z( I! X; Z/ a4 v
Confirmatory Factor Analysis , 验证性因子分析, }' F( ?8 \! o+ E" [9 h
Confirmatory research, 证实性实验研究" H) b6 {+ |- i" e2 ]
Confounding factor, 混杂因素
- C2 d$ o2 ?# b1 x( @5 w/ VConjoint, 联合分析
! s- `: P' I) PConsistency, 相合性
7 j; X+ i/ p9 J1 W. a" N$ ^Consistency check, 一致性检验
/ u$ V+ F$ Y+ _& s; BConsistent asymptotically normal estimate, 相合渐近正态估计! y4 h! t$ t* r! h- b2 Q
Consistent estimate, 相合估计2 |' a5 J O/ L" }. F) C
Constrained nonlinear regression, 受约束非线性回归
2 M5 q. W4 U2 v; b( ^2 n3 vConstraint, 约束
. [( z6 w; Z9 r n/ Z2 w. y2 ^7 A5 d1 _Contaminated distribution, 污染分布
! ]3 B4 E7 m8 Q6 y& ]3 `Contaminated Gausssian, 污染高斯分布2 E6 r8 j6 t+ r% Y% A
Contaminated normal distribution, 污染正态分布 X8 r8 O/ [* w' I! P# L
Contamination, 污染; b1 H6 `, `. t6 [+ V! O
Contamination model, 污染模型
7 [; l6 O4 R* N% l# ZContingency table, 列联表
$ s5 K l# [, i. tContour, 边界线
: g$ T0 S( x! S! {! @Contribution rate, 贡献率
5 Z. L& p# i6 p$ y8 Y7 C* Q5 U1 ~Control, 对照
: j) G. Z$ Y3 Q7 T W" _Controlled experiments, 对照实验
. a+ N3 u x' O1 ZConventional depth, 常规深度
: G: y" e6 s& w) V! VConvolution, 卷积( y$ L' T% a8 F4 w+ n: Z! R! X$ v
Corrected factor, 校正因子
5 x Q) y+ b8 D* E% rCorrected mean, 校正均值6 _3 E" T8 l4 e4 j- H
Correction coefficient, 校正系数
" O4 c/ Y% G9 J# s. o) s- P" {% GCorrectness, 正确性
$ Y+ V* m' m, p1 _2 L* |Correlation coefficient, 相关系数
/ p2 c! L9 H: j- [) ^) _3 k" ^% tCorrelation index, 相关指数! |, c, c# T5 o4 ^$ _
Correspondence, 对应7 c6 R, v6 S9 I7 _; L2 y
Counting, 计数
- j" ^5 n o/ j. | e& z3 c0 D! yCounts, 计数/频数
- w" E D6 s S% zCovariance, 协方差
8 q8 i" z" P6 u" L$ T& Z9 P7 d7 B% eCovariant, 共变
& T1 v" d" V$ _( u* k9 m! h$ cCox Regression, Cox回归
3 ?5 U' e7 J% c* c) x' T* x5 |$ BCriteria for fitting, 拟合准则- s0 ~3 _. }) z# n( d& u# I
Criteria of least squares, 最小二乘准则/ t1 A: X( {" v# ? S
Critical ratio, 临界比3 A$ n. F' B$ y/ x/ x9 a
Critical region, 拒绝域
6 w/ E6 D7 J0 q$ x# A$ mCritical value, 临界值
( A# ]% ~/ ~1 B$ [ bCross-over design, 交叉设计! \! P4 @1 V* {/ l* R
Cross-section analysis, 横断面分析% ^& \7 F, z' D$ n, n
Cross-section survey, 横断面调查. W( ~9 \) C( I
Crosstabs , 交叉表
6 a- F$ _( s7 e5 n# ~, W" y' }Cross-tabulation table, 复合表
8 ~0 \! e$ c. T- O; HCube root, 立方根. g* x: N6 e" q5 }, D
Cumulative distribution function, 分布函数
/ }. d0 ]& S% K. R# P5 DCumulative probability, 累计概率
0 z" h+ v R" ?& U- n( [! }4 XCurvature, 曲率/弯曲3 U4 s1 l+ B# Z4 X1 o
Curvature, 曲率1 _' Y) a3 x' v* O p+ p: E
Curve fit , 曲线拟和
( O* ]! u' D, Q; `. B$ n- ~# OCurve fitting, 曲线拟合* z* `& F$ |* ]* l/ ^, q
Curvilinear regression, 曲线回归. ^( |2 D* b; s/ e: h
Curvilinear relation, 曲线关系
. U( x( n, O1 B1 F! dCut-and-try method, 尝试法
5 y$ o2 F: n& E6 X4 ICycle, 周期$ o n$ g0 ?8 |- {+ C% ?
Cyclist, 周期性. t! p7 A" y* M& u0 I
D test, D检验1 l% Z* z2 W# }& ?! a& U7 ?
Data acquisition, 资料收集" V$ p* `1 b" H
Data bank, 数据库
- t% u5 R# A# `7 jData capacity, 数据容量; V, ]6 g7 s2 Y! i: |/ y
Data deficiencies, 数据缺乏 c9 G: z% t. r2 a# R. ]
Data handling, 数据处理" c3 P9 o2 f* w2 r* j9 F) h
Data manipulation, 数据处理
) V+ ^0 g; @* cData processing, 数据处理
0 J" k& C5 a3 f% WData reduction, 数据缩减, y# f ?' n* m" N+ g& v. `
Data set, 数据集
/ c' p- | C9 {# U# c& R5 {Data sources, 数据来源
/ P$ @! `( i/ U5 l! b% nData transformation, 数据变换
* ~% m$ i" e$ VData validity, 数据有效性. a- o! k) ? p6 p
Data-in, 数据输入) a# I7 [, g( o1 g% V! C) q
Data-out, 数据输出
) Z8 Q9 N' l" W2 D8 Z8 B# h, V# UDead time, 停滞期
( a8 |0 a& r2 e6 h$ R5 pDegree of freedom, 自由度
1 ^0 U# O \$ p6 l6 c# W% iDegree of precision, 精密度* a9 r l* f i; P
Degree of reliability, 可靠性程度
0 b% E7 f& s$ m* C( K9 M, S* GDegression, 递减 V0 Z. w+ n& j9 e2 W9 g
Density function, 密度函数
- |6 h( |( Q+ ^6 p ^Density of data points, 数据点的密度+ J# V5 Z# {. h. _. a/ B5 }
Dependent variable, 应变量/依变量/因变量/ M, w' T) r9 |. A! _/ w w: Y
Dependent variable, 因变量
3 x0 h+ }) D3 {+ gDepth, 深度& }% L8 @2 u0 A. X" `
Derivative matrix, 导数矩阵6 Q+ K7 q. p+ `3 d/ s8 i
Derivative-free methods, 无导数方法
+ Y1 }/ V9 ?' VDesign, 设计
4 M0 p) I! e* z% _Determinacy, 确定性9 f+ t6 @3 i9 j V5 A- R0 H! t3 i5 P
Determinant, 行列式- y D" g' E% J" a
Determinant, 决定因素5 Q( o0 }. Y o" a C
Deviation, 离差
2 L: b) D' Q! V- `% B+ o% ^Deviation from average, 离均差
; `* Q+ s) A5 O! T- \6 r$ y7 RDiagnostic plot, 诊断图
, H5 i# J2 j9 O3 N$ EDichotomous variable, 二分变量
5 p8 L. ?% @ j5 A8 nDifferential equation, 微分方程
Q, _; M9 e2 GDirect standardization, 直接标准化法7 d. p7 @% g6 b- D+ H
Discrete variable, 离散型变量; {( ?- R/ ~' _
DISCRIMINANT, 判断
; {- w5 T* }4 F' i8 t! aDiscriminant analysis, 判别分析8 h# I; l' x% M n
Discriminant coefficient, 判别系数
( x) R4 {. K/ x- Y% H! c" b3 ^Discriminant function, 判别值
$ F$ P4 `! A/ r! O( ^Dispersion, 散布/分散度
' j* o8 V8 x9 T' uDisproportional, 不成比例的4 y& y) |, Z; F8 E
Disproportionate sub-class numbers, 不成比例次级组含量
2 ]& P2 y* C( xDistribution free, 分布无关性/免分布$ l( B! h F8 Q
Distribution shape, 分布形状9 N/ g8 f( A6 h: u
Distribution-free method, 任意分布法$ `( I4 }, y% [2 Y$ R3 j4 P3 I# H' Y/ W% F
Distributive laws, 分配律
$ d+ K4 i& j" t1 k4 s/ @) yDisturbance, 随机扰动项: w0 P( x1 q M w+ b0 P
Dose response curve, 剂量反应曲线& A5 P/ t7 @1 C4 q$ d
Double blind method, 双盲法6 @3 x) ~" o+ _; D& {4 n2 d
Double blind trial, 双盲试验% I, L4 b( N0 g8 j
Double exponential distribution, 双指数分布$ i7 {, c' W" \- J1 w8 S
Double logarithmic, 双对数7 ` y- }0 ?5 `! h) v
Downward rank, 降秩5 L# ~/ c k A8 b \. x' P+ r' r% _. k
Dual-space plot, 对偶空间图
/ ?' H# _" ]6 s8 k2 nDUD, 无导数方法
9 N9 H P! U% n9 U4 ~0 F& dDuncan's new multiple range method, 新复极差法/Duncan新法/ N0 W0 _) A# g; z5 |
Effect, 实验效应
: w; K3 S# T+ k" ~" BEigenvalue, 特征值
7 W% Z' I" D; u% k! [) kEigenvector, 特征向量8 D# c# [6 q" i% ?
Ellipse, 椭圆- C- i4 E0 r9 ]: q
Empirical distribution, 经验分布9 `$ p5 [4 v% R$ Y Q, \- d
Empirical probability, 经验概率单位7 x: F/ D, O4 L/ A3 P3 p4 D
Enumeration data, 计数资料
" R& _7 i, ^ _& {Equal sun-class number, 相等次级组含量- i8 n( i* N7 e' V1 t
Equally likely, 等可能
: ]4 J2 b9 @) R3 w' ~Equivariance, 同变性
5 o$ u7 }; k0 m4 g) LError, 误差/错误' E' S" i1 w- k( o8 ~- N
Error of estimate, 估计误差
! {8 Z6 c' ~0 ]2 F2 A& X' x! @/ X- GError type I, 第一类错误 q0 q4 Y! T- @9 |7 p& B
Error type II, 第二类错误
% S3 P) e. |4 d4 fEstimand, 被估量3 [9 k( V6 A/ N
Estimated error mean squares, 估计误差均方& g6 X1 b: `/ n: t6 m! i
Estimated error sum of squares, 估计误差平方和
4 J# w6 \8 N+ t+ _& ~" c3 ~Euclidean distance, 欧式距离
* a4 N6 p( z4 J8 ]2 S0 [- W% uEvent, 事件
! |: G" r1 ^6 fEvent, 事件
) d% f% w7 R7 q+ S1 pExceptional data point, 异常数据点
9 ?, c" h0 D5 r1 t% VExpectation plane, 期望平面7 F1 P( _% z/ B7 W
Expectation surface, 期望曲面
2 M% ^$ L& M0 h9 P! t- eExpected values, 期望值9 {8 o" ]( r: [/ j2 O! p7 Q
Experiment, 实验
: \4 k7 q' l' r B# ~5 IExperimental sampling, 试验抽样% c; Q( u/ w4 B) I5 @0 n( X
Experimental unit, 试验单位* a, j" g# O& C1 w4 A( }
Explanatory variable, 说明变量
# q4 C7 {! Y, \% F% G P6 J0 |Exploratory data analysis, 探索性数据分析, g3 Q, o& N3 k J: [2 }
Explore Summarize, 探索-摘要. N# W! @0 `9 i( h' l7 m
Exponential curve, 指数曲线 I6 U4 _& U3 A) T7 {5 Z9 ^
Exponential growth, 指数式增长
1 a4 ]% x. |2 BEXSMOOTH, 指数平滑方法
* f$ q8 C# g1 y0 g6 W+ UExtended fit, 扩充拟合$ z, h, Q, F! d# l) R
Extra parameter, 附加参数 {7 K& K8 W7 X. P- B! w* u) a
Extrapolation, 外推法
, r9 [. Z7 C" c" i2 }8 I2 L, `3 gExtreme observation, 末端观测值
' S4 O) Z$ i8 @" y+ g8 W+ W- @# WExtremes, 极端值/极值
% T3 k# u* I; h8 z+ A. uF distribution, F分布
# z# N( q! z: h1 {. E g* g( Z2 uF test, F检验
" q8 t6 t, y: X I% {( X+ sFactor, 因素/因子
v! J v$ i- L# V+ X- uFactor analysis, 因子分析7 e7 ]( ]" K& f" ^& f
Factor Analysis, 因子分析" V: S* X. ?1 u, z! }% q
Factor score, 因子得分
6 J( l y M2 D; M0 u9 X2 [ Z dFactorial, 阶乘
. }" [( D" }. t# m2 MFactorial design, 析因试验设计# p c) H/ \9 D: f1 d$ j
False negative, 假阴性
: \) u9 D8 `7 S1 b- xFalse negative error, 假阴性错误4 @* n0 q8 e t& J$ g1 _; E
Family of distributions, 分布族% u' J0 s& n/ g+ l$ T" w' O ]
Family of estimators, 估计量族# v1 f4 S. Q% X/ E* r/ `) o
Fanning, 扇面4 I. v1 M0 B: T
Fatality rate, 病死率
7 L+ g8 _/ j, _- U0 \: e# m) {Field investigation, 现场调查1 t! p$ L* p* W& g' R; ]) j# b
Field survey, 现场调查. s) e9 z4 Y# y c
Finite population, 有限总体: Z* a3 T, w. p9 X3 p
Finite-sample, 有限样本. \; o/ U( \" }2 V- Y9 a q, R, h! r
First derivative, 一阶导数8 v; p# O T: U J: L5 ]
First principal component, 第一主成分
- ^, S9 `2 ^& R5 u" J1 iFirst quartile, 第一四分位数
( t# I# \% u) j! D( S& |/ l4 j2 DFisher information, 费雪信息量4 s: J" R& j" P$ H0 U
Fitted value, 拟合值
# v8 A8 v; r9 j Z8 s6 ?Fitting a curve, 曲线拟合
) j) j0 a/ s2 J& e% O. J$ fFixed base, 定基% y$ w+ A' ?( b% _2 T- N6 `
Fluctuation, 随机起伏
+ x9 r: N6 C8 p+ l$ EForecast, 预测
. b1 ?% g3 H# l+ x4 T/ z3 NFour fold table, 四格表( D8 s: L( _$ R" w% V, q
Fourth, 四分点 z& Z! C) Y; W. l. _
Fraction blow, 左侧比率" \! _5 G: ?0 T/ F" K% f9 H: _4 V
Fractional error, 相对误差
0 ^3 L, G3 j9 kFrequency, 频率% f7 h/ @8 B; Y! q$ f
Frequency polygon, 频数多边图1 v! P ], |0 h8 |) b$ z. A
Frontier point, 界限点
. s% j3 E6 D: QFunction relationship, 泛函关系3 j4 i" Q6 }, a, o2 b
Gamma distribution, 伽玛分布
7 _. l- K. @9 ?Gauss increment, 高斯增量5 K. @$ l- U/ s# d
Gaussian distribution, 高斯分布/正态分布
+ t) h( |6 F% f; E! G' e& nGauss-Newton increment, 高斯-牛顿增量0 d- A* C( d5 o( V' A5 D
General census, 全面普查
1 G* h) ?# {. q9 iGENLOG (Generalized liner models), 广义线性模型 8 c0 c" {) q/ u; Q: x0 G& I0 X1 R
Geometric mean, 几何平均数: _: H$ ` [0 H7 c& D
Gini's mean difference, 基尼均差& Y3 g' F" z2 Z v( }2 l
GLM (General liner models), 一般线性模型 ' g D. t: Z4 ^, K; d
Goodness of fit, 拟和优度/配合度
( D5 y! h n0 t; p9 |Gradient of determinant, 行列式的梯度
9 T8 n# o' D0 C6 o0 B* XGraeco-Latin square, 希腊拉丁方0 U' `6 Z7 T1 {9 P% J& R
Grand mean, 总均值
5 E7 |; F0 d* H- ]' tGross errors, 重大错误1 I6 [( N2 L, M6 _, v
Gross-error sensitivity, 大错敏感度
+ |' E; H! O+ g; `Group averages, 分组平均
9 @! a2 i5 e4 F* f+ @Grouped data, 分组资料9 B4 `5 D# D. e: X8 C! d5 u
Guessed mean, 假定平均数
; |2 f! v; d( T2 E+ J5 Y8 o5 X0 ZHalf-life, 半衰期
, T c( D9 o1 M3 R/ \+ F5 OHampel M-estimators, 汉佩尔M估计量
! {6 c. I5 ^( b6 IHappenstance, 偶然事件
0 Z# s6 g1 M' D2 G6 sHarmonic mean, 调和均数+ Q2 G7 s: v) f2 e4 V; b* B& ?- ^
Hazard function, 风险均数
8 w5 g7 W# M& b* }0 k7 u+ |Hazard rate, 风险率
7 [+ Z6 C: |2 x7 m" [! `Heading, 标目 . d3 p L' T$ q
Heavy-tailed distribution, 重尾分布9 e; W. l% ?: _! {
Hessian array, 海森立体阵
% h4 R9 x5 i, d. B: n% O2 WHeterogeneity, 不同质+ p5 ]1 B3 b3 ^5 l& F
Heterogeneity of variance, 方差不齐 $ e6 u1 O5 j7 l7 B. K8 \# B" a
Hierarchical classification, 组内分组
( x' k) O W( Z' dHierarchical clustering method, 系统聚类法 A$ S% a* C4 [
High-leverage point, 高杠杆率点
6 W: \& }+ K* e( g4 EHILOGLINEAR, 多维列联表的层次对数线性模型) `# P# [0 g5 }5 D
Hinge, 折叶点
% `5 \7 z1 B: q! r# ]& S- J" FHistogram, 直方图
3 g Q( A: Z/ j s$ I- w/ THistorical cohort study, 历史性队列研究 + l% ^7 B9 f6 I
Holes, 空洞
" t) q3 @# m1 j! I2 `# f1 \3 S* dHOMALS, 多重响应分析9 L; i; F+ r( j+ u- Y8 x/ z
Homogeneity of variance, 方差齐性
1 p4 W O/ q7 }/ \2 e8 ?Homogeneity test, 齐性检验
v6 G/ z0 }4 UHuber M-estimators, 休伯M估计量
0 G( S( n3 I. w0 @9 t% i! Q1 D ]Hyperbola, 双曲线4 P/ i x: ?7 ^6 o' m
Hypothesis testing, 假设检验
{% u8 D8 {1 XHypothetical universe, 假设总体) H1 y/ O5 p! P9 p% L9 g
Impossible event, 不可能事件
% A0 e, ~! H2 `: {3 _3 \Independence, 独立性
+ Y7 U( f3 m7 x3 { i3 w, E0 i: TIndependent variable, 自变量4 X" Q% z; F y7 M9 I7 Y# d+ z. R* a
Index, 指标/指数
! {3 O" V% E& [3 N, K d/ bIndirect standardization, 间接标准化法, C. T( ]9 a0 c- f
Individual, 个体
& E- P, D/ L( O# N' A& L2 H; w6 ~Inference band, 推断带, x6 G9 L" l8 s# c/ e. V
Infinite population, 无限总体
0 Y4 s# H N: C+ l* b; BInfinitely great, 无穷大2 d. k9 o& b! E! [' p. b9 [
Infinitely small, 无穷小/ {4 X K. j0 _2 }$ n0 v
Influence curve, 影响曲线
* s/ a: i' |/ g( O" Y0 u# X' wInformation capacity, 信息容量$ T! {2 J7 y" ]5 b( Z, y( d
Initial condition, 初始条件4 l: g- V5 `" o/ o( C2 Y7 r" I b
Initial estimate, 初始估计值
5 x& g+ u! b$ R. M3 yInitial level, 最初水平! S# l+ @0 r; U( u: n5 N+ a e/ _
Interaction, 交互作用9 T% W% D4 D' n. k4 j; I1 V
Interaction terms, 交互作用项
0 n# q0 W! T/ J; U- ^Intercept, 截距7 z3 g7 j6 @' k6 e- ?, m& W& U# ~% Y
Interpolation, 内插法
; F- T: P. h$ |" P) yInterquartile range, 四分位距+ H" F% v2 \4 Q% s" ~ \$ {0 ^
Interval estimation, 区间估计7 k% k. X H& L0 R
Intervals of equal probability, 等概率区间. ^( } a$ v! q" N7 Z4 y* H) q0 U
Intrinsic curvature, 固有曲率
% g! r6 g$ [- JInvariance, 不变性
. T( e3 u7 H, \. P$ f& h6 tInverse matrix, 逆矩阵
" a r8 e" P+ z. a' x. KInverse probability, 逆概率0 G, `- v' G& O! f
Inverse sine transformation, 反正弦变换
; d6 [( C2 ^! M8 ?Iteration, 迭代 ' V7 g( S$ K* E+ i$ X
Jacobian determinant, 雅可比行列式2 v# w, R/ h8 c$ r; B
Joint distribution function, 分布函数
( Q! b* e3 D( Z+ D" RJoint probability, 联合概率/ ]( A- C; t- ]( }5 _' Q
Joint probability distribution, 联合概率分布
0 M* f* o- F% k/ T+ V. OK means method, 逐步聚类法
$ O) M3 K. O. w7 I7 |Kaplan-Meier, 评估事件的时间长度
+ H9 N: }3 x# Z1 y L6 f- w8 CKaplan-Merier chart, Kaplan-Merier图
7 d z/ [' m# t# F% ^# DKendall's rank correlation, Kendall等级相关
7 V0 e& {! O( lKinetic, 动力学
3 @5 t1 y" c% v2 G4 bKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
0 D6 J! q* P. F! NKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
Y. S7 ^) ?/ FKurtosis, 峰度
8 |/ Z( [( D! L x' w) H* F- YLack of fit, 失拟" i5 ?2 F8 Q& |
Ladder of powers, 幂阶梯
^" i! t5 F1 S7 B9 ?) I; MLag, 滞后, t5 G+ o+ L( L9 t; L* }4 \" V% g
Large sample, 大样本
0 R; b0 R k; c/ O8 ~5 Z6 D" _$ h% zLarge sample test, 大样本检验
; M- \ Y3 P. ]4 |* i; R) wLatin square, 拉丁方
7 g1 z* a& c r; v! B1 s2 cLatin square design, 拉丁方设计. }7 D1 D" }/ ]& j$ V4 a
Leakage, 泄漏9 p: V! C: @, ^6 r% E. H
Least favorable configuration, 最不利构形
1 b( I9 T+ \8 D. o. L, BLeast favorable distribution, 最不利分布7 `# f! d2 h4 m" B; O
Least significant difference, 最小显著差法
# ]6 t5 s2 P! b: m' f9 GLeast square method, 最小二乘法
7 q3 o+ h6 Y6 }, |$ q' w; i; XLeast-absolute-residuals estimates, 最小绝对残差估计
/ W& K- T( B- G P8 t rLeast-absolute-residuals fit, 最小绝对残差拟合) P9 F8 \ s3 {0 l' b6 u( O, s
Least-absolute-residuals line, 最小绝对残差线; X% o& t' X/ c% f8 E% N' N) \, f
Legend, 图例9 Q. q7 R: W6 I3 S/ v1 j: c
L-estimator, L估计量
# Q6 o5 R- Y5 r2 e" W2 C2 rL-estimator of location, 位置L估计量
, z+ ?, i7 I9 v! K' _: BL-estimator of scale, 尺度L估计量
' s' n8 Q+ S$ `0 y; C6 b% vLevel, 水平
7 g3 o" y! x6 P9 |, A dLife expectance, 预期期望寿命$ ~- f6 s5 t8 ]* [7 i
Life table, 寿命表1 H9 R# a5 |6 ]8 ?0 O
Life table method, 生命表法) l% \& L1 f1 F* I
Light-tailed distribution, 轻尾分布
1 j$ f G0 d! u1 v$ wLikelihood function, 似然函数
, R, B5 x" M* u3 ?9 mLikelihood ratio, 似然比) X& K7 r+ I! y: ?. w
line graph, 线图3 Y7 D" ~8 }2 T Q$ K. s- }
Linear correlation, 直线相关
1 o' K: C$ t6 S8 J3 z3 JLinear equation, 线性方程
/ c# @5 y6 N; }Linear programming, 线性规划0 o+ e* m. ~" H9 c
Linear regression, 直线回归3 C* _7 H( u% R- H8 Q2 i
Linear Regression, 线性回归
9 `$ i/ \8 V: X# s6 F, yLinear trend, 线性趋势
& ^$ T, f* o9 }: m, G( L5 m- kLoading, 载荷
2 P6 C6 U5 w: R" sLocation and scale equivariance, 位置尺度同变性
7 F* R& M# E4 K$ wLocation equivariance, 位置同变性2 v5 m' Y$ n# A$ J
Location invariance, 位置不变性2 E! r% x6 D U* I* f* h1 G
Location scale family, 位置尺度族
I1 X# }. ]+ [: s& ~Log rank test, 时序检验 1 C, E+ F! H( t
Logarithmic curve, 对数曲线: j& {* i) ~: @+ B; w- x: S9 s
Logarithmic normal distribution, 对数正态分布5 F' q2 \4 Z% i4 d5 R6 T# |
Logarithmic scale, 对数尺度: E' d) F& ?( d% l
Logarithmic transformation, 对数变换
; t/ D' e: f2 j4 r; x* nLogic check, 逻辑检查% J/ \ t7 }& A( ]* j
Logistic distribution, 逻辑斯特分布% I6 s# B8 _1 D A/ V
Logit transformation, Logit转换
! N* n- Q" j" m+ p( W- CLOGLINEAR, 多维列联表通用模型 : a& f+ q. R3 `8 I* a
Lognormal distribution, 对数正态分布7 O6 J) s9 H# ?& a& f, `
Lost function, 损失函数- r+ e( o- [, C) x5 {8 h- i; U
Low correlation, 低度相关
/ x4 r: T7 P0 ]5 j* n3 ^4 L3 N" S1 nLower limit, 下限( ^0 t* Z2 t! L$ I$ N& c, a
Lowest-attained variance, 最小可达方差
: `, I% r8 J, LLSD, 最小显著差法的简称+ v: W9 A! R7 c' N7 n4 j" j- N4 D; \1 c
Lurking variable, 潜在变量; M, h; f( w) S( Q; _
Main effect, 主效应( X) e6 y& z3 }
Major heading, 主辞标目
4 j1 I% D! _7 aMarginal density function, 边缘密度函数
# K! m9 d7 B7 `+ O: E. z. |Marginal probability, 边缘概率" G% R& ]3 A _$ `. K( G# @! q
Marginal probability distribution, 边缘概率分布
j$ @. W( Y* \; a5 VMatched data, 配对资料
0 ?, n5 D1 i5 A+ ?3 r7 ?3 K! h; JMatched distribution, 匹配过分布6 i7 f8 U5 I* X' o' l$ l
Matching of distribution, 分布的匹配( U: y2 Y+ l, X: i/ W: Z$ D3 ?
Matching of transformation, 变换的匹配8 E& T5 }; Y# i
Mathematical expectation, 数学期望
! h+ a5 D/ X/ B* s" K. A& x- I# T5 HMathematical model, 数学模型' r& I8 \2 U+ [- f2 m. l
Maximum L-estimator, 极大极小L 估计量5 J" k' s4 O( v, o6 y
Maximum likelihood method, 最大似然法
2 G/ m+ I ]" |6 HMean, 均数
. W1 v% s: a8 J# m( o, L8 XMean squares between groups, 组间均方 @* n# ]3 n* E
Mean squares within group, 组内均方
; b D h9 [# A. jMeans (Compare means), 均值-均值比较
$ m/ }" O7 v* JMedian, 中位数
- _2 l, [( ^+ g, ~8 KMedian effective dose, 半数效量 b! _. G& S) e# r' T9 L
Median lethal dose, 半数致死量
, d% [8 V7 X7 W) l# QMedian polish, 中位数平滑# A4 a' E. C i& g
Median test, 中位数检验
* a, m" a$ _- p$ R' s9 K7 B4 |Minimal sufficient statistic, 最小充分统计量
g1 {5 D+ U. s$ m8 n, fMinimum distance estimation, 最小距离估计+ w6 F1 v9 H; x$ n6 m k9 O
Minimum effective dose, 最小有效量, k; \* T7 m! s) n7 \
Minimum lethal dose, 最小致死量
. J1 C$ W2 b3 a6 b6 RMinimum variance estimator, 最小方差估计量9 y2 k T7 {: C! ~
MINITAB, 统计软件包: k$ b( [7 A& G) A4 o/ q2 V9 `. M, m
Minor heading, 宾词标目
4 F" n8 a0 [9 jMissing data, 缺失值7 ?1 P& S" z7 c' |: }2 S, S
Model specification, 模型的确定
3 R1 `# f. C0 X/ T/ e5 p UModeling Statistics , 模型统计
' T. |8 i) T; F: z$ W* H( XModels for outliers, 离群值模型! \( |9 J9 k5 n& X7 {
Modifying the model, 模型的修正
H+ {' ~# s% {Modulus of continuity, 连续性模- U6 F6 Y. w z+ r" F
Morbidity, 发病率 ! u h) _& g b$ r5 s8 h
Most favorable configuration, 最有利构形
. b9 Y* q% a4 s/ N- F: B9 oMultidimensional Scaling (ASCAL), 多维尺度/多维标度! P+ v0 X/ A+ V0 q) {2 i1 c
Multinomial Logistic Regression , 多项逻辑斯蒂回归
$ @. N& ^. L4 e. |, hMultiple comparison, 多重比较
% {8 X9 ~; ?0 M4 ~Multiple correlation , 复相关
6 r9 [/ `( k# `2 y6 u) aMultiple covariance, 多元协方差
' i# b" K" e BMultiple linear regression, 多元线性回归
* c& ^. K6 |9 v6 U* WMultiple response , 多重选项
. I) K& Z9 N" X3 ?+ D( I) q/ w4 ?2 \- QMultiple solutions, 多解$ w5 G# {* L! ]+ ]7 B1 ]( `, Z
Multiplication theorem, 乘法定理
8 a4 {5 B6 f+ _8 g% a! gMultiresponse, 多元响应* n( E! Q9 j4 v) _0 [
Multi-stage sampling, 多阶段抽样( G" X- i+ r' C9 y- m' s) l( y$ O- ~# ~8 H
Multivariate T distribution, 多元T分布
0 P6 _1 W2 L0 K& qMutual exclusive, 互不相容
. T' w& X* m1 uMutual independence, 互相独立
% M% c7 k& C: ], c% @/ xNatural boundary, 自然边界7 z7 W6 Q, g U( R8 \0 h' h+ ]% `% m$ {
Natural dead, 自然死亡
( l6 s, {1 R& U Z( YNatural zero, 自然零/ x* r8 n! n. L
Negative correlation, 负相关* {2 Z6 c2 }& o# v4 Q1 T( |
Negative linear correlation, 负线性相关" x3 h& b4 [( }) l( s
Negatively skewed, 负偏0 W5 p$ D- h! y6 d7 ~( K9 _
Newman-Keuls method, q检验- d! B: W$ u2 `# Q
NK method, q检验 [+ C" b8 e: K7 P* d! @) N) p
No statistical significance, 无统计意义5 c! B2 M! _, e6 m% y* c: q
Nominal variable, 名义变量
2 K, F+ R9 R2 J- S3 TNonconstancy of variability, 变异的非定常性
; j6 h1 b G' ~% @# RNonlinear regression, 非线性相关3 { \: K2 U- N3 H. e6 X
Nonparametric statistics, 非参数统计- b t j" A+ n$ d
Nonparametric test, 非参数检验
# {2 q! T% D! Q8 F5 i( `Nonparametric tests, 非参数检验
+ ?1 N+ h8 x$ N; F7 { Y4 m1 y: MNormal deviate, 正态离差# |; z4 `' S( u; u. V8 w- N
Normal distribution, 正态分布
' J1 a5 T/ {3 D" ~- {Normal equation, 正规方程组
3 [% Y3 m0 C" j- lNormal ranges, 正常范围
0 p a& F$ z5 l0 U/ F) \1 aNormal value, 正常值
" x" M# H% I9 s# [4 h. u! C9 XNuisance parameter, 多余参数/讨厌参数
, B8 l9 [$ y9 x6 z. KNull hypothesis, 无效假设 * }* ^/ G& Q ]3 l6 f
Numerical variable, 数值变量
" U$ d" \8 K# R! \. S% QObjective function, 目标函数9 g6 q8 e# q$ L3 y7 f
Observation unit, 观察单位
( }1 d6 k) C. hObserved value, 观察值7 l% v3 h" V/ c: \
One sided test, 单侧检验% v1 U. Z/ ]$ h9 H! ]( C0 |
One-way analysis of variance, 单因素方差分析
+ s: k# @2 @/ k) i/ k* G" QOneway ANOVA , 单因素方差分析8 m: P( \4 F% v9 H: ~7 O
Open sequential trial, 开放型序贯设计
7 ~# Y% K S1 ^Optrim, 优切尾
: Y/ v# I8 p+ \9 `, {/ ]1 {Optrim efficiency, 优切尾效率
. D' I# g# y: O0 T: T) MOrder statistics, 顺序统计量9 K0 B8 m: p) B6 B2 p) ~
Ordered categories, 有序分类
; V+ K: w. u6 o/ W \8 zOrdinal logistic regression , 序数逻辑斯蒂回归- g+ p! i. ?: p
Ordinal variable, 有序变量" E" t/ l; G3 f( q" S
Orthogonal basis, 正交基1 e: s+ }# m# Y6 O* T i1 c
Orthogonal design, 正交试验设计6 F4 P6 o! E! y7 Q# b7 t4 L1 Y4 i+ e
Orthogonality conditions, 正交条件' r: E, W2 ?: t: p1 `2 {) ?
ORTHOPLAN, 正交设计
" E0 o( Y2 w- w* G6 oOutlier cutoffs, 离群值截断点
) D& W, [ X8 n3 |2 k: W0 G- YOutliers, 极端值
3 b% m& O: m! T7 K+ mOVERALS , 多组变量的非线性正规相关
- e, h% `( W" e& u. POvershoot, 迭代过度: O/ U" h) Q4 ^' G5 F7 r ~
Paired design, 配对设计
0 k, [+ v( A6 ~+ V5 f) K) W/ yPaired sample, 配对样本4 ~% E1 V6 j0 Y
Pairwise slopes, 成对斜率
9 ^ B) B0 z2 e: ^/ h4 k% ^$ t, NParabola, 抛物线
- \$ e# v( R; H( ^! [Parallel tests, 平行试验
1 _' U+ ]1 P2 EParameter, 参数8 t6 d3 d+ a# O8 B" b0 o7 g
Parametric statistics, 参数统计
$ L6 X$ ^3 c1 @" ^Parametric test, 参数检验; U* w2 H, [4 e# `0 s, @; z
Partial correlation, 偏相关4 G/ O5 Y5 J0 L
Partial regression, 偏回归" w. }, M$ V5 p8 M. u1 s( O
Partial sorting, 偏排序. K0 C, y* v6 U P
Partials residuals, 偏残差
2 Z: i- R2 a" D( pPattern, 模式+ }( p+ w' H/ k4 Q
Pearson curves, 皮尔逊曲线
1 Y8 y* i) X$ F4 jPeeling, 退层0 T% B. o$ r8 f9 O3 i1 N
Percent bar graph, 百分条形图
+ O5 ~$ w4 V8 m( E' @0 zPercentage, 百分比
4 J5 |. V- b7 G8 q) h' } rPercentile, 百分位数! X2 K& j5 b" |" J e
Percentile curves, 百分位曲线
- |% G; {5 M; J/ S4 @+ LPeriodicity, 周期性1 G. }" r. _5 l
Permutation, 排列
# [/ |/ k# Q3 z) J8 X# H% |P-estimator, P估计量
" G7 U& A! }3 Z! i# ]/ B6 z( F' ?+ fPie graph, 饼图, ]3 f7 s) s. E W( D' G8 d$ }
Pitman estimator, 皮特曼估计量6 L- v1 `2 @9 B
Pivot, 枢轴量! [6 F+ l5 K% p. ~& Y
Planar, 平坦. p; {8 K; q( g6 t3 D' _' n
Planar assumption, 平面的假设
8 _- f4 R; }8 j! ]5 @3 lPLANCARDS, 生成试验的计划卡
& o* h2 H1 @7 [5 B) x6 ]3 [% cPoint estimation, 点估计5 H5 T1 s5 u c; z. E9 c3 l9 f* r' U* K
Poisson distribution, 泊松分布! |/ Y+ W$ I5 r
Polishing, 平滑2 ~7 H- o3 M4 N% a# i* l
Polled standard deviation, 合并标准差
4 ^7 w3 {$ W4 A: `8 ~. FPolled variance, 合并方差
" h/ u1 ^& R6 M8 @# R4 D+ V/ Q; XPolygon, 多边图8 U* U; Z( N8 F4 S) B4 Z
Polynomial, 多项式
2 }( e/ d# }& Y1 ~Polynomial curve, 多项式曲线) \ b+ R* t4 t" K6 Z+ b, z2 n7 J
Population, 总体; ^& k' i( |3 l4 N- W3 P) L) X9 r
Population attributable risk, 人群归因危险度
+ s* u8 g7 e& p9 t9 Y" t7 cPositive correlation, 正相关: G& L+ s9 n7 b6 U8 ^" @8 z
Positively skewed, 正偏/ H5 d, \7 h4 [* H/ l, C
Posterior distribution, 后验分布
" P! Q. Q4 l1 ]- v$ xPower of a test, 检验效能/ x/ {4 X+ ^$ F0 i- W/ H
Precision, 精密度
; h! e1 U2 r) L9 \; `Predicted value, 预测值
$ n& a( r7 ^' A' i+ R6 n" g! \Preliminary analysis, 预备性分析: x1 |) O7 ^+ x% y4 U/ R2 Z& V
Principal component analysis, 主成分分析: e! m9 E) H2 V1 B/ e- @
Prior distribution, 先验分布
% E( i1 c+ c! Z/ [, m" qPrior probability, 先验概率
5 R$ T! M+ H3 }& N) H1 A: }- WProbabilistic model, 概率模型& o- d/ d! E& L% I6 P4 [3 s
probability, 概率
8 @, Y* A1 r* d5 s1 R4 {) |Probability density, 概率密度$ h- I4 R6 P1 V9 d
Product moment, 乘积矩/协方差
8 D$ ]6 }7 s# _8 P; W6 {# G9 M7 E% O2 DProfile trace, 截面迹图 m' n! r+ o' Z; |9 N9 v
Proportion, 比/构成比1 R9 ~4 G- N4 \
Proportion allocation in stratified random sampling, 按比例分层随机抽样
* W7 C y/ R- ?% |, L$ B) iProportionate, 成比例% O8 q$ H/ n1 k1 I: N8 ]
Proportionate sub-class numbers, 成比例次级组含量9 i+ b0 [2 J2 D3 h3 D0 G
Prospective study, 前瞻性调查
1 {5 B4 ]+ J& Y: O6 OProximities, 亲近性 8 @' r o* h* l+ s3 f* L) r
Pseudo F test, 近似F检验
2 x. A; X1 v9 `2 ?8 T# F6 H/ c2 NPseudo model, 近似模型
7 |" H, x3 X* y) V) dPseudosigma, 伪标准差0 p4 U! Z3 P2 G
Purposive sampling, 有目的抽样
* e* b+ n% G5 ^' r/ i' s0 _QR decomposition, QR分解
0 [3 i( o! a* R1 p; ~7 i! rQuadratic approximation, 二次近似4 Q6 d; i/ T9 A. u8 Y, d; R# `
Qualitative classification, 属性分类
( V% H2 g- c0 @3 I- j; `8 w. H4 PQualitative method, 定性方法3 t1 Q1 S& x& `$ ~( R4 p! X* S8 p
Quantile-quantile plot, 分位数-分位数图/Q-Q图 X5 h, W. J$ j5 r, e, m
Quantitative analysis, 定量分析
7 O/ `9 O3 |- x; e$ w6 e+ `Quartile, 四分位数
: F$ r. ^$ ~1 k" T2 k- `- GQuick Cluster, 快速聚类' I# t% _& G; o+ j0 }/ w$ x
Radix sort, 基数排序7 Q$ h7 ]8 `. y! E6 u% }3 X
Random allocation, 随机化分组) _" S7 [0 A3 J- n' _
Random blocks design, 随机区组设计
) S. S) ]" Y( T" y, aRandom event, 随机事件1 V: `0 T2 c* b6 }( G& O1 S) N
Randomization, 随机化2 o3 l) L/ f; p$ t7 K$ [
Range, 极差/全距
2 E: I, P- Z* HRank correlation, 等级相关. p, Y4 y0 `& v# I
Rank sum test, 秩和检验9 a1 C6 ~7 t7 W- \( C8 w* V
Rank test, 秩检验9 d6 N9 C0 l2 U; L# y
Ranked data, 等级资料
R$ m; Q, ~1 B3 S: B1 G/ r6 aRate, 比率5 D) C+ z1 |' C5 q( e" L
Ratio, 比例
8 W9 N' Y0 N8 yRaw data, 原始资料
4 j4 K6 E! O. k# E8 S; T+ |8 b( ORaw residual, 原始残差* ^$ }+ u$ z4 o1 `# E9 O% Z
Rayleigh's test, 雷氏检验5 j1 V$ I, z3 J
Rayleigh's Z, 雷氏Z值
6 i! T4 x+ C8 H7 c+ P) Q0 E& P8 |Reciprocal, 倒数
, C: [0 O- [# _ {2 c7 u5 O% AReciprocal transformation, 倒数变换5 A0 d/ `3 N2 d) K/ D7 Y8 q
Recording, 记录
D9 Z- e: O% |1 O O; dRedescending estimators, 回降估计量
: F0 b& p3 v: q: M) \Reducing dimensions, 降维! F% C+ O4 s+ O5 L8 O
Re-expression, 重新表达
. _$ e/ s5 h0 Q3 b: _8 v$ ?Reference set, 标准组
6 b0 w) M# p2 G1 B; W2 _Region of acceptance, 接受域/ j: D/ d6 i6 D) w9 B. {
Regression coefficient, 回归系数7 \, B8 o1 B- H4 @
Regression sum of square, 回归平方和
- s" O. `, }/ w4 e6 h% `# aRejection point, 拒绝点
4 q2 T+ }- P K; y# MRelative dispersion, 相对离散度
9 ?* N. q. m5 ^, q7 d DRelative number, 相对数
; d- c+ F. @, T8 NReliability, 可靠性
) [) X' `4 p: \" d& ~6 |Reparametrization, 重新设置参数5 N B! C u6 T7 J; U: U# m
Replication, 重复
* u4 Z0 B0 r' G4 n! T7 mReport Summaries, 报告摘要8 @: {) J `$ K0 t; p
Residual sum of square, 剩余平方和
3 o" \' X5 a. o1 TResistance, 耐抗性
& B3 w; c) Y6 [% kResistant line, 耐抗线
8 v9 e0 O) y4 RResistant technique, 耐抗技术
$ B( q1 v8 k& |; f; Z# _4 WR-estimator of location, 位置R估计量
f# X" Z, Q* HR-estimator of scale, 尺度R估计量
8 b$ x5 l/ Z2 E1 G) J' H* e$ @0 [Retrospective study, 回顾性调查8 @3 p. K" ^. | l8 A; Q" o% A
Ridge trace, 岭迹
9 M5 p' C4 }; z: gRidit analysis, Ridit分析
* y9 m% |4 \% kRotation, 旋转' L5 g- o$ U) B3 C$ y% i- c4 T
Rounding, 舍入" U5 G9 ^1 g" b! A& S
Row, 行
( v- D4 s3 H( q" Z" K+ Y0 FRow effects, 行效应* b" F/ G* \0 k8 z! B! x
Row factor, 行因素
9 y7 x, R3 `. }! e2 R0 ?- J! I4 uRXC table, RXC表 z) y/ V. P: K) f
Sample, 样本6 c, K, @& }+ }7 U/ M7 Z; t1 s3 ^! t7 d
Sample regression coefficient, 样本回归系数9 Q. A2 ]$ U3 \0 e% A& Q
Sample size, 样本量& T9 r) u, A7 Y, ~
Sample standard deviation, 样本标准差; Q- |3 u/ L3 G5 s
Sampling error, 抽样误差9 w) S9 T4 @3 S! q. {; \$ A$ @0 r
SAS(Statistical analysis system ), SAS统计软件包
( D k o2 o) v, x2 @( _Scale, 尺度/量表! e. l# y6 w3 @4 z
Scatter diagram, 散点图
. w7 A$ g8 n; xSchematic plot, 示意图/简图
- s8 ~9 Y9 V. `3 n) GScore test, 计分检验
: |! L. ]2 X8 K, Q0 k2 vScreening, 筛检 D) C G, p+ V/ i2 [
SEASON, 季节分析 % \3 D' w9 [' f5 `9 u
Second derivative, 二阶导数" [: E N1 h$ p0 p1 m
Second principal component, 第二主成分
: [1 w1 y" W+ P. pSEM (Structural equation modeling), 结构化方程模型
7 l- ]* i* F' v/ BSemi-logarithmic graph, 半对数图
3 F! R# [: e# Q$ @. TSemi-logarithmic paper, 半对数格纸; d0 t% q5 `. @/ P2 l5 |" p! _! J
Sensitivity curve, 敏感度曲线
% A2 m% D+ _! o8 E: F2 e9 J- @; aSequential analysis, 贯序分析
3 o- N" x0 y. |5 Y; d% t& b$ tSequential data set, 顺序数据集
' v5 g1 g* ~9 @+ kSequential design, 贯序设计( ^* l/ w8 A' c; Z
Sequential method, 贯序法
4 }! H# U+ F% k6 b( }4 HSequential test, 贯序检验法
$ F$ f1 q, u5 [$ u! R; M: b: aSerial tests, 系列试验
% X1 r% }) d- x% ~Short-cut method, 简捷法
% I3 o& Q. k! Q. ], w4 \/ k( W4 WSigmoid curve, S形曲线
" U% i6 `8 r0 V% LSign function, 正负号函数# p4 R7 z8 H# w0 P9 K. V: F
Sign test, 符号检验 Y& t. H$ h" h* q
Signed rank, 符号秩2 ^" J, [3 {1 N% ~$ b: M
Significance test, 显著性检验7 K7 f/ n6 \/ ]6 D1 ?6 F1 D
Significant figure, 有效数字
6 X2 \" E/ M: @Simple cluster sampling, 简单整群抽样6 I6 u4 b8 }0 A6 I
Simple correlation, 简单相关: b8 H; D4 o, Q6 [2 o( H5 Y
Simple random sampling, 简单随机抽样
7 J$ S3 L9 m" wSimple regression, 简单回归" Q. D. q' l5 a: P6 P0 ~ V7 b
simple table, 简单表/ T" U* ?( f# t* U
Sine estimator, 正弦估计量
+ Q1 U/ m" r! D- ^# S/ PSingle-valued estimate, 单值估计
% T2 T% a5 S, J3 ^$ L- g/ `Singular matrix, 奇异矩阵
$ c% d8 {/ A+ z/ {' J7 Q: r! N- SSkewed distribution, 偏斜分布
& C5 K6 S$ z1 ~, q- y) \! }Skewness, 偏度, d: z x1 _2 Z+ E
Slash distribution, 斜线分布
& v4 R6 Y* B' l2 X# M- ^8 ]( JSlope, 斜率2 w7 X5 ^# {5 }. X" R( E, F
Smirnov test, 斯米尔诺夫检验
3 V* f* n$ u+ O7 o6 S5 ~) C- cSource of variation, 变异来源
6 i3 ?7 X. J9 S, F9 a, qSpearman rank correlation, 斯皮尔曼等级相关
* a( T& W" v0 h9 `* R% z$ C. @Specific factor, 特殊因子6 W1 g# J6 a3 C [7 A4 {8 v2 m
Specific factor variance, 特殊因子方差! L9 I1 N# i7 u* Q0 P
Spectra , 频谱
T) _) R# k( ?6 BSpherical distribution, 球型正态分布
, N5 } v1 u3 |7 ISpread, 展布5 Z4 |, |1 z2 o
SPSS(Statistical package for the social science), SPSS统计软件包
$ P) f4 z0 E. X' A# H/ x5 [Spurious correlation, 假性相关
7 \6 ]/ S8 z; q& T6 Z3 g* lSquare root transformation, 平方根变换, I% D7 q! V7 ^5 m' q3 N
Stabilizing variance, 稳定方差& L6 Y2 V; ?; g* B7 d# E
Standard deviation, 标准差7 o# ~: D! _; T: M6 L3 t/ v
Standard error, 标准误
/ ~3 J: i; z1 H+ R( [; U1 K8 q& aStandard error of difference, 差别的标准误( x0 c/ ?2 n" ~( a9 v8 P
Standard error of estimate, 标准估计误差
( ^$ Y2 r' s) E, f# d% m8 PStandard error of rate, 率的标准误. p. E* @3 R' c: n. E. P( d# s! U
Standard normal distribution, 标准正态分布5 \6 A7 ]6 B, z; \3 S
Standardization, 标准化3 B! s6 s0 T- @/ U5 H4 z- A5 [
Starting value, 起始值
7 V+ E6 u9 w q2 M( zStatistic, 统计量
% W$ Y0 m/ _6 Y: nStatistical control, 统计控制
! y4 Y" A2 x" M0 ^! MStatistical graph, 统计图
- R# v9 B) _( e. R/ u. A! `7 H5 |Statistical inference, 统计推断+ @' w4 @1 M1 Q$ s& w e
Statistical table, 统计表
. G5 p" H! o% ]Steepest descent, 最速下降法. g# J: _2 s4 c" _$ p4 ^7 r. N
Stem and leaf display, 茎叶图7 l2 h$ `8 t: p( ~& S
Step factor, 步长因子
; u) @$ ^: |+ J( X) h- M! ~Stepwise regression, 逐步回归( A9 @0 l, L' q1 w2 y" D) M- j8 G
Storage, 存
! }$ P& _0 I# D$ F2 ?0 mStrata, 层(复数)! ?) ^8 t0 h& e. J1 e* \ R/ z
Stratified sampling, 分层抽样9 l9 ?0 p# k- A
Stratified sampling, 分层抽样
& x4 `" ]- O6 iStrength, 强度
& s, F l& A8 a4 _Stringency, 严密性
' J0 A+ C. F7 JStructural relationship, 结构关系
- R. d$ y# R1 S0 RStudentized residual, 学生化残差/t化残差
& U7 {/ E5 C+ |& Y$ v3 JSub-class numbers, 次级组含量
) b4 M4 `3 a" c. pSubdividing, 分割
5 f7 B( Y8 X. A9 I( e; [5 |Sufficient statistic, 充分统计量) T1 _8 D7 B3 L1 X2 h- {. K8 h* N2 H
Sum of products, 积和' S3 o# T/ I$ [* v' e! X
Sum of squares, 离差平方和
- q l0 D6 o4 w$ p# b3 P& ISum of squares about regression, 回归平方和
( O9 _$ U! I( g3 [& d4 m) VSum of squares between groups, 组间平方和* o4 t L) K# U9 \4 q$ M1 L( V
Sum of squares of partial regression, 偏回归平方和
0 b& w9 l2 q& A& s5 |) eSure event, 必然事件) C( A9 }1 q3 F# d( ?# S
Survey, 调查' ~7 ~+ r: m5 r
Survival, 生存分析
7 c: s4 s4 e( N0 O3 `. m) jSurvival rate, 生存率
# U V) A/ E' C+ GSuspended root gram, 悬吊根图
0 u0 T0 f- j0 U3 |: rSymmetry, 对称7 j# m# {( ?* H6 }
Systematic error, 系统误差
" o j, R& s& ]Systematic sampling, 系统抽样
8 ?8 d6 K# x1 N2 a! i. j9 tTags, 标签
; [2 a8 |- Q2 t4 xTail area, 尾部面积
% j4 W; [6 \! ]' X q6 wTail length, 尾长$ E: a# | y S, i6 @
Tail weight, 尾重8 \$ n h6 k( ~, E" h
Tangent line, 切线
Y0 i+ u1 n& lTarget distribution, 目标分布
- K. ]3 @& _0 ^# j O3 Y1 ]Taylor series, 泰勒级数: g* G8 ~& ?" G6 E5 j
Tendency of dispersion, 离散趋势
9 J6 r5 i0 E4 e; E6 I1 Y% k4 [) bTesting of hypotheses, 假设检验
& [1 H& ?+ o) b! W; L PTheoretical frequency, 理论频数
9 v. h$ n* G' r6 m. D+ sTime series, 时间序列" I) d; A( S' S. P1 d+ |4 o
Tolerance interval, 容忍区间 A3 f! m" h6 ]5 E7 T4 S @
Tolerance lower limit, 容忍下限+ n0 y" }9 B8 K
Tolerance upper limit, 容忍上限
. N( c, k! h+ ^6 M; [Torsion, 扰率/ O1 @& ?1 h0 N* g0 R
Total sum of square, 总平方和0 q/ C. b& i- z6 D A
Total variation, 总变异
/ ^4 M; ^: R0 C% g6 P4 T( dTransformation, 转换; N0 E( ~/ C. G; ~! O4 g
Treatment, 处理
# v1 Z1 j; w$ X# jTrend, 趋势
2 W& t+ M8 M1 \6 z2 n2 ITrend of percentage, 百分比趋势& ^* B$ O. q* W
Trial, 试验
+ p8 l2 J& Y3 w2 iTrial and error method, 试错法 p3 m& p6 y' P5 j5 W( n
Tuning constant, 细调常数4 N* M a7 q$ h, P, r
Two sided test, 双向检验
0 B, r* H' d; a0 K! f3 ~Two-stage least squares, 二阶最小平方
7 a& p4 a+ n3 \, {3 tTwo-stage sampling, 二阶段抽样
% n3 K) p" @3 ]$ Z' qTwo-tailed test, 双侧检验
2 ~7 C+ x4 i3 ^# k- kTwo-way analysis of variance, 双因素方差分析5 d; {# F/ E2 p
Two-way table, 双向表2 \3 E5 |5 g8 T; L
Type I error, 一类错误/α错误
2 c# F: U R6 E' ^! ~% Z8 i. W* CType II error, 二类错误/β错误# ]9 {3 v/ y+ w" E! @0 C; x! h
UMVU, 方差一致最小无偏估计简称
) C; d6 K1 z; q- a2 v: L% {+ iUnbiased estimate, 无偏估计
u" O! S) y3 ]& e4 VUnconstrained nonlinear regression , 无约束非线性回归
) W: h( U9 S4 q& P* U* u; \, tUnequal subclass number, 不等次级组含量4 @* z1 r3 Z2 I
Ungrouped data, 不分组资料
' V, R& U4 ]% M! e% g4 v! dUniform coordinate, 均匀坐标* N" `) ?7 `, \ z8 h$ E
Uniform distribution, 均匀分布. K1 Y% K4 m: Z
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计) A9 T7 q, w8 R: H7 t
Unit, 单元
/ B+ f7 @( D( r4 E6 i, u6 ~Unordered categories, 无序分类1 C3 M* L- c9 }8 p R
Upper limit, 上限
6 c9 Z4 c* ^+ V9 t; E" A% jUpward rank, 升秩
8 _0 N" g: e# u8 u9 a$ vVague concept, 模糊概念" D o; y) I3 [9 ]
Validity, 有效性
; a! V/ K9 g) f3 F/ N0 a' MVARCOMP (Variance component estimation), 方差元素估计& M% ?8 G: e7 ^$ [8 A! X0 I
Variability, 变异性
; C3 z1 O5 |! D$ S; L0 `) N3 m# F# `1 `Variable, 变量( t+ ~8 {5 ?, \# L" {1 M
Variance, 方差
8 ^' P4 P9 w' x- p8 M' ~( NVariation, 变异
% _% `9 ~8 S( M$ C: oVarimax orthogonal rotation, 方差最大正交旋转3 r' ^$ R) ~) a
Volume of distribution, 容积
8 a2 E1 L" d' uW test, W检验
$ J1 S ^( m* e: lWeibull distribution, 威布尔分布6 c4 \' Q/ Q# ~0 R) X& m
Weight, 权数
) \! d+ y0 O" E8 SWeighted Chi-square test, 加权卡方检验/Cochran检验
, s7 `/ g& D9 ZWeighted linear regression method, 加权直线回归6 M5 t2 f9 H5 S8 x" p3 B
Weighted mean, 加权平均数
, h' Q6 n( S, NWeighted mean square, 加权平均方差, U* C6 M, x7 u7 D6 a( _: b0 T+ I
Weighted sum of square, 加权平方和: F$ ]5 d$ \# F9 ]4 c" N
Weighting coefficient, 权重系数
( W$ T7 e/ J. g! W: Y( o# _Weighting method, 加权法
; V$ K! ^- E6 |7 TW-estimation, W估计量
# i" |! b8 _% ^W-estimation of location, 位置W估计量
$ u) c+ E5 b2 X9 tWidth, 宽度
1 Y4 s& L/ G9 TWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
/ ?. _' p/ {! V* qWild point, 野点/狂点
% ~$ H P7 C* x. V3 uWild value, 野值/狂值
7 S8 F' y* W- C3 g6 Y9 q2 ?Winsorized mean, 缩尾均值
8 ?' G0 b i: ^Withdraw, 失访
0 n, M1 o5 j/ `6 I7 q0 Y) V4 F2 f( {0 PYouden's index, 尤登指数" P7 k0 b7 n+ Z `8 F+ @; P
Z test, Z检验3 W1 n7 ?& i" ^- h) K
Zero correlation, 零相关
) E) X. E4 a! b, h% l6 k5 n: UZ-transformation, Z变换 |
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