|
|
Absolute deviation, 绝对离差+ L' |5 k* V, F0 W" {; ?1 s
Absolute number, 绝对数6 t* g2 Y! Y& @4 B4 H, @
Absolute residuals, 绝对残差
0 H: [5 V/ D1 |9 o$ w4 VAcceleration array, 加速度立体阵
0 U' N! v. q, I8 T5 |% tAcceleration in an arbitrary direction, 任意方向上的加速度
/ L: s5 U4 o$ T$ J% vAcceleration normal, 法向加速度( }: M# _6 c& `" C2 F: J& ~) H
Acceleration space dimension, 加速度空间的维数
. N$ W3 q. T( n2 v. b: {9 Q1 BAcceleration tangential, 切向加速度
2 z) D: }8 ]" W9 sAcceleration vector, 加速度向量/ E6 |3 R9 V t+ o* |& Y
Acceptable hypothesis, 可接受假设
) [* G3 s5 Z& E- @$ {/ AAccumulation, 累积6 c7 N. o0 ?% A* z+ v, r& |
Accuracy, 准确度$ F* {$ K! c0 ?& m
Actual frequency, 实际频数" s) h3 _) o9 E" K% Y8 b
Adaptive estimator, 自适应估计量
1 r6 T8 n) W$ `" C/ x) VAddition, 相加
% u- n8 p( `& h; \Addition theorem, 加法定理
$ R3 I4 H1 X/ b& S( @Additivity, 可加性4 H: _! u# U/ M$ {
Adjusted rate, 调整率2 p# q+ V2 H0 W8 O! {/ R
Adjusted value, 校正值2 a" Z. G- X/ P$ P g1 K
Admissible error, 容许误差6 G2 u0 T6 I i, O* h( n# O
Aggregation, 聚集性( Q5 P8 J) K+ \) }
Alternative hypothesis, 备择假设
j4 o* o0 w0 pAmong groups, 组间
) `/ v. ^3 s5 R/ j& ^8 qAmounts, 总量! s x1 @% S+ @
Analysis of correlation, 相关分析+ k' H5 S) s9 O1 P
Analysis of covariance, 协方差分析4 H& }( T7 j7 x) `+ l6 v0 I
Analysis of regression, 回归分析
' F* k7 I8 p- H" c9 G$ D3 R2 cAnalysis of time series, 时间序列分析4 z3 `) ?2 x U) u6 v. \
Analysis of variance, 方差分析 p% c! a. {0 t9 U8 T, W' E
Angular transformation, 角转换+ O% S9 l0 J% \7 F; ~1 S( G
ANOVA (analysis of variance), 方差分析
8 Y% }4 K) A& PANOVA Models, 方差分析模型0 T2 L/ ] m# B: L. e
Arcing, 弧/弧旋. B9 g* i9 L- T) S( \
Arcsine transformation, 反正弦变换
0 \5 l: D0 M/ ~- j# cArea under the curve, 曲线面积$ M& g+ D. r6 V, T" u; c- 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 & D! x- [4 B6 H' r
ARIMA, 季节和非季节性单变量模型的极大似然估计
4 O+ p4 W+ J4 w. XArithmetic grid paper, 算术格纸
+ ]$ E* f" K/ I* J2 P) @- uArithmetic mean, 算术平均数
; \; l2 A0 q! k! L2 \Arrhenius relation, 艾恩尼斯关系. X% O9 N2 Y7 } _
Assessing fit, 拟合的评估
. R4 j% x# R5 RAssociative laws, 结合律. _( d5 @7 [4 G, e
Asymmetric distribution, 非对称分布4 N5 d" O0 C+ D7 N
Asymptotic bias, 渐近偏倚( @: d3 w9 E* y
Asymptotic efficiency, 渐近效率: Z; C" B2 u% X
Asymptotic variance, 渐近方差1 x- H4 [, R* f7 `4 ^% \
Attributable risk, 归因危险度
& O2 `! }2 m5 c4 FAttribute data, 属性资料
/ R, v& T: m- S, D/ bAttribution, 属性# w& X) i$ Q5 ]* x6 n. K5 W
Autocorrelation, 自相关) f1 O4 [6 k7 k: s+ U9 y6 A
Autocorrelation of residuals, 残差的自相关. f! l7 o& @0 N$ B, `
Average, 平均数2 y. r+ M! k% o
Average confidence interval length, 平均置信区间长度
4 T* L3 d9 z/ T: t% F$ U% mAverage growth rate, 平均增长率
4 h: g6 k4 f6 m& p3 \' YBar chart, 条形图0 s1 D3 V# A) Z$ w& a& x+ l
Bar graph, 条形图
$ b+ i4 t! O( ?& {7 ABase period, 基期6 O8 R" k' n) V, k; I7 L: F
Bayes' theorem , Bayes定理- d9 p* {" L- g: e$ y
Bell-shaped curve, 钟形曲线5 [* r' Y* B) I0 c
Bernoulli distribution, 伯努力分布
$ i; a& ^/ i2 s* }Best-trim estimator, 最好切尾估计量* b5 ]; h6 B& `
Bias, 偏性
3 z: t! T8 I7 Y0 z9 TBinary logistic regression, 二元逻辑斯蒂回归1 O z9 d& D: ~5 T% R: @: u7 p
Binomial distribution, 二项分布
* f+ o& \ Z7 @Bisquare, 双平方& ?7 m, w" x/ j# ~0 b. A2 O
Bivariate Correlate, 二变量相关- n1 P; D$ e7 P" z3 W
Bivariate normal distribution, 双变量正态分布
Q, {3 u, c4 U- ZBivariate normal population, 双变量正态总体
* [) X. I* c5 o: Y1 @Biweight interval, 双权区间" w, D4 H4 ~8 C# K
Biweight M-estimator, 双权M估计量
8 J+ q5 M1 I" IBlock, 区组/配伍组
7 n5 j1 Y2 N% h* N7 c% v: a. zBMDP(Biomedical computer programs), BMDP统计软件包2 T2 ?# L7 [1 b# X; v( o* P1 Y
Boxplots, 箱线图/箱尾图- E; _+ X% y7 Y6 T6 J
Breakdown bound, 崩溃界/崩溃点
! k& w! z0 y# ?: A) V8 X, w* VCanonical correlation, 典型相关
) b" {. l; g. A6 r8 HCaption, 纵标目5 b2 t4 Z2 Y% V' K0 _, x. R( o
Case-control study, 病例对照研究/ _, J0 c( \ J" f. ]& v" a
Categorical variable, 分类变量+ B* h" [9 K7 ^+ S6 ?
Catenary, 悬链线
; X" G. x+ V, T! jCauchy distribution, 柯西分布5 I. Y. z% B6 V: n
Cause-and-effect relationship, 因果关系
( ]9 ^# X3 l9 Y/ f5 |4 ECell, 单元
/ @% k+ ~0 F, B5 C C5 w7 t. @Censoring, 终检. R7 K$ B+ e, _: I- l5 D& k* i e
Center of symmetry, 对称中心% y! S2 ]2 O3 p$ z
Centering and scaling, 中心化和定标) U9 a. ?9 f4 x+ `2 x4 D# k
Central tendency, 集中趋势% I' T+ \' y6 F% t. m. u. P0 O
Central value, 中心值* ?7 P* H( e" @/ X! b( b; ~
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测1 e5 y8 q4 ^5 M i! v
Chance, 机遇3 w0 L6 \9 n, j5 C
Chance error, 随机误差
$ |7 C e6 k! c7 F4 d" NChance variable, 随机变量
" [, v V9 z' T& ?, t* x6 bCharacteristic equation, 特征方程! U8 U$ \1 L& @- H6 V1 B
Characteristic root, 特征根! y, j! n1 A: u- R& ^
Characteristic vector, 特征向量
4 {6 j2 T1 v' P) \8 X+ h5 k7 nChebshev criterion of fit, 拟合的切比雪夫准则' g9 e) Y# ^3 {2 e1 r9 V+ K$ H
Chernoff faces, 切尔诺夫脸谱图
& S$ z: e' P2 X HChi-square test, 卡方检验/χ2检验
: X5 K* K! N1 Y" B) Z* k4 bCholeskey decomposition, 乔洛斯基分解
- c' L0 { B1 L. F/ O& h0 W* |Circle chart, 圆图 5 u3 q# L7 N3 \4 @. i! S
Class interval, 组距6 a! l, \' T9 T3 c' {
Class mid-value, 组中值$ r; Q- D7 r1 B0 g9 \
Class upper limit, 组上限
: i2 a1 \& K* mClassified variable, 分类变量
$ Z' B6 |& O% o3 I9 PCluster analysis, 聚类分析
& B3 O, a6 X0 ~2 I, BCluster sampling, 整群抽样
( x& t, F4 k2 B; hCode, 代码1 R* m( J) N4 X
Coded data, 编码数据8 q1 b9 N) i& I2 u& G
Coding, 编码5 h' u8 B5 s! x; F
Coefficient of contingency, 列联系数
, o+ p# N h: a, o/ l4 mCoefficient of determination, 决定系数
6 h* B* J7 y+ V5 J u- x' wCoefficient of multiple correlation, 多重相关系数8 n5 I4 a7 U9 H% ~, Z4 T
Coefficient of partial correlation, 偏相关系数
8 Q, T7 W5 b" z; l3 M( {Coefficient of production-moment correlation, 积差相关系数
3 [$ k7 Z0 N/ ^- j2 @9 U# ^Coefficient of rank correlation, 等级相关系数0 s" [! D% n, C3 ^/ }* Y
Coefficient of regression, 回归系数$ @: J7 J9 D# N" c- ?5 h U' M
Coefficient of skewness, 偏度系数5 s! D, c0 |4 K) n t4 \
Coefficient of variation, 变异系数 q& w% s1 O! |
Cohort study, 队列研究 i9 u% k: w- ~) c
Column, 列$ n! G8 ~6 \- N
Column effect, 列效应& @4 J" e4 w+ N- m. {
Column factor, 列因素
& ]' q8 Q1 e. ^Combination pool, 合并% s5 R; [/ h& d
Combinative table, 组合表# e% m( X( c, a
Common factor, 共性因子- ^: |* T1 D# ?2 A. X3 m( H$ @
Common regression coefficient, 公共回归系数
3 V$ o1 K- s- U4 ~7 ~ pCommon value, 共同值
6 X6 |: P/ L1 M! T! [Common variance, 公共方差. m7 t o$ G& ^/ W! N9 T9 L
Common variation, 公共变异
( G6 ^" A% o9 p* g$ yCommunality variance, 共性方差# N- b+ }( G4 c% r7 p
Comparability, 可比性
" @/ L9 [$ l' f5 NComparison of bathes, 批比较
' G+ m6 r, I' h0 ?7 qComparison value, 比较值+ {4 X. W9 _- ]$ X
Compartment model, 分部模型: J/ g/ ^- j' _3 u0 C, t( Y1 L
Compassion, 伸缩
/ o* E$ {8 O7 V4 D: t+ IComplement of an event, 补事件
. x0 H( `, @* M7 T/ h" dComplete association, 完全正相关% n6 |/ L" d& ?5 }" K# r
Complete dissociation, 完全不相关
5 x( V W2 m! Z% ]# wComplete statistics, 完备统计量
* A) X# g" Q0 y. @% NCompletely randomized design, 完全随机化设计1 @$ F0 \4 M, ~# P
Composite event, 联合事件" G) B- Z& s# n0 K
Composite events, 复合事件
2 d1 ?5 O& E& i' ~! JConcavity, 凹性, X! w/ t }) `$ P
Conditional expectation, 条件期望
3 w, N1 W4 e9 nConditional likelihood, 条件似然
7 n; V" _% r! D' p( t, v' MConditional probability, 条件概率
1 q' |/ i/ ~& ^5 sConditionally linear, 依条件线性
+ g% Y! a. S- K7 N) I/ {Confidence interval, 置信区间
0 _6 T8 M, X. P2 z; W/ jConfidence limit, 置信限
0 V$ P6 S9 H) C5 m( ]Confidence lower limit, 置信下限% q$ j) x V7 [% | _8 }( m. I
Confidence upper limit, 置信上限
2 ^0 {9 f7 y2 [1 v9 P5 T, kConfirmatory Factor Analysis , 验证性因子分析' R& s! _3 `" n$ W- P/ X' |! ^
Confirmatory research, 证实性实验研究
5 ]# H H' [1 s# @Confounding factor, 混杂因素- q+ h7 T. p( V' R2 H/ l( t
Conjoint, 联合分析3 h% I: R. ] l6 l3 \4 e
Consistency, 相合性; x. Z' B" O2 F' i. F/ e
Consistency check, 一致性检验
, O# ~5 }1 U! H2 WConsistent asymptotically normal estimate, 相合渐近正态估计; B$ T6 m4 {' x9 x1 q; v! [* a
Consistent estimate, 相合估计
. K% A- A8 M+ Z: n4 XConstrained nonlinear regression, 受约束非线性回归
7 l9 D' N, }! B8 G+ c3 `) w4 LConstraint, 约束
9 h# T* g& Q3 S) A$ U1 c# nContaminated distribution, 污染分布6 X" h# s/ e( f4 H5 F& h" e3 V7 h
Contaminated Gausssian, 污染高斯分布, d" @4 |& U! s& W' _
Contaminated normal distribution, 污染正态分布8 k5 J5 I5 F/ l& y s- u
Contamination, 污染
# _3 z0 ~1 a$ Z; fContamination model, 污染模型
f$ ^% Z+ h0 a/ iContingency table, 列联表0 K+ _/ f2 [, c* |+ i& {
Contour, 边界线" l- R6 g: C- ^, H' H) `, }
Contribution rate, 贡献率7 [4 L; z5 V) ?" n* ^* ]- j n7 ?, P
Control, 对照" a3 @4 g* |& I: D! E8 |
Controlled experiments, 对照实验
$ Q d8 W" J- W( r. W: {$ d( PConventional depth, 常规深度
3 I& W% l* [7 x& E0 G2 JConvolution, 卷积
3 F/ e1 c- n* |( N" GCorrected factor, 校正因子2 {; N; f- h4 r# w9 c
Corrected mean, 校正均值% U5 F" x% ~/ Z0 F/ R
Correction coefficient, 校正系数
/ M8 ~$ h1 T$ x% H2 \8 GCorrectness, 正确性
2 T6 y0 c9 ?: j9 V2 O* ]0 E; G; {Correlation coefficient, 相关系数
. d# T$ q; ~2 C+ G% a" xCorrelation index, 相关指数
c# K* i. ]; `$ VCorrespondence, 对应
- S' f4 A' V5 a* }$ ]% @Counting, 计数
. ~/ Q4 L$ ^) g3 Z+ M5 f" g2 VCounts, 计数/频数
@) m0 j% g& J( @$ ACovariance, 协方差( A' M4 [- f0 L( e
Covariant, 共变
1 ^7 W3 a+ a% i9 |Cox Regression, Cox回归0 q' D- z C/ B4 a
Criteria for fitting, 拟合准则
: }6 q( P% ~) s `- wCriteria of least squares, 最小二乘准则! x# Y( [$ ~2 p4 W
Critical ratio, 临界比
1 H Q' G. l7 t* w. UCritical region, 拒绝域1 U" i' o# M h
Critical value, 临界值; J3 K( I, D$ M3 n- n8 \# w
Cross-over design, 交叉设计
$ U ]+ G& E8 g9 }$ |/ mCross-section analysis, 横断面分析7 {7 w; Q/ }# H1 n
Cross-section survey, 横断面调查1 W$ F7 S( a' o+ @
Crosstabs , 交叉表 % x' y+ @$ B' t
Cross-tabulation table, 复合表' e" G; C# O- U1 M. u/ y' n
Cube root, 立方根2 \# z( w$ `( ~. g2 \3 C
Cumulative distribution function, 分布函数4 u' a3 t9 n+ B- ^& {2 a: E
Cumulative probability, 累计概率" S* |- M+ c/ g! @' ~
Curvature, 曲率/弯曲7 [6 l B" r8 F/ B
Curvature, 曲率. t8 B) A5 ^$ S/ I2 T0 P
Curve fit , 曲线拟和
; n5 a* F5 C; z5 R+ ]+ c2 L0 B3 Q% {! DCurve fitting, 曲线拟合* m3 @- w) p( t% l% ]" p+ p& t* [5 A
Curvilinear regression, 曲线回归
4 V8 y; X* w; Q3 z) o! xCurvilinear relation, 曲线关系
{2 }, s% G4 f% ^Cut-and-try method, 尝试法
( Z" d+ b: t; SCycle, 周期) \% I' D/ S& F' O. W! ^% l
Cyclist, 周期性& E# _4 x" \* s$ ?) G$ z* G" s
D test, D检验* K+ j% ?( ?" D( H" G
Data acquisition, 资料收集
, O* e/ R6 ^) T8 WData bank, 数据库' l# r5 G$ G$ c/ G) y
Data capacity, 数据容量
/ t& F9 ]$ v' Y# k: K& d0 z7 ^Data deficiencies, 数据缺乏) [* N, I& L# W4 q1 B5 Y( ^: A
Data handling, 数据处理+ V0 R5 o1 O, [; o0 P j' c* B! J% d
Data manipulation, 数据处理' m L$ N$ m6 l
Data processing, 数据处理
2 ?8 }$ ?3 g0 T4 WData reduction, 数据缩减: O, g' A$ j' X- d
Data set, 数据集6 a5 m: i; j* }% W
Data sources, 数据来源
! X! ~8 d1 J' V; p5 D2 VData transformation, 数据变换
. e1 A9 A( Z; B3 HData validity, 数据有效性, _( [; Z2 n3 c1 {
Data-in, 数据输入 G" K7 W* Q ?
Data-out, 数据输出
0 U7 K9 ]+ ]9 y) M6 lDead time, 停滞期2 B; p+ r1 ^% v, u
Degree of freedom, 自由度
( ^8 O8 Y2 k; @- W9 s YDegree of precision, 精密度! |# f: K5 d5 L" o& D; G
Degree of reliability, 可靠性程度
- E1 e3 K! C! F4 A! K V+ t CDegression, 递减$ D. |& U4 A8 k+ d& V
Density function, 密度函数& d+ l7 D8 K# z2 e
Density of data points, 数据点的密度
2 `4 ?' t/ ^4 y# hDependent variable, 应变量/依变量/因变量
- G9 T# |: M* {* A3 pDependent variable, 因变量 N g6 q; A4 v6 V2 t2 z
Depth, 深度
# {$ d6 \* e1 j/ uDerivative matrix, 导数矩阵' a9 G- m% O: D" A' U! e4 K1 o
Derivative-free methods, 无导数方法
g8 M* ^: Z( GDesign, 设计
; K+ F3 _) A3 ~Determinacy, 确定性
7 M7 O7 f5 h6 E. SDeterminant, 行列式2 c2 i Q H9 n* U
Determinant, 决定因素. {& P) S; Q+ s' G) H
Deviation, 离差9 f3 |" k9 R& B/ e0 I; z( f
Deviation from average, 离均差
" B2 @+ Z' [% T% i4 N, E2 xDiagnostic plot, 诊断图
/ j; b; G- Z E( b1 s- b- N* IDichotomous variable, 二分变量4 B2 v0 d ~* L! w3 ^4 c! |5 s
Differential equation, 微分方程
: m* g; P8 N$ N4 bDirect standardization, 直接标准化法4 Z7 s1 B- L7 w4 M% i7 D
Discrete variable, 离散型变量
E8 f! J5 n; O& oDISCRIMINANT, 判断
6 n. l/ H& u0 M/ SDiscriminant analysis, 判别分析
. u' `2 E3 I- J. cDiscriminant coefficient, 判别系数
- T+ g3 Z, d5 ?Discriminant function, 判别值; m( c; g* Q0 F7 f0 H: p
Dispersion, 散布/分散度% L8 e2 n% Y; f0 u8 K0 f3 ?* [
Disproportional, 不成比例的
6 ^! m( K; T1 J, ZDisproportionate sub-class numbers, 不成比例次级组含量
4 }8 K' }0 T4 t- l1 CDistribution free, 分布无关性/免分布7 F$ O# I, R( h; m3 x
Distribution shape, 分布形状
* n1 b2 e4 i5 cDistribution-free method, 任意分布法
; X8 p! F3 h- h8 _' a+ c: @5 B3 YDistributive laws, 分配律
$ {+ B9 E& z6 @0 DDisturbance, 随机扰动项2 u! N/ R, j9 ?9 E
Dose response curve, 剂量反应曲线
9 b4 m0 n7 Y% e( DDouble blind method, 双盲法
' K; V0 c2 o5 ~ ~Double blind trial, 双盲试验& s2 M6 @0 b+ E
Double exponential distribution, 双指数分布$ \8 O) @5 H, h, j* X2 f
Double logarithmic, 双对数* F' m' i1 f0 ~7 e4 l( b& U
Downward rank, 降秩5 N5 f" n! X1 O3 G* I" a
Dual-space plot, 对偶空间图
! d/ o2 |1 W/ h2 Q0 j1 ZDUD, 无导数方法& y( k X$ v6 s: v: K0 N8 k
Duncan's new multiple range method, 新复极差法/Duncan新法9 V; L' T8 G0 C/ j( P$ k8 {& }4 [
Effect, 实验效应
# G* W& e/ l( K4 ~ M. fEigenvalue, 特征值
K: b& a" v9 ~0 oEigenvector, 特征向量
* _7 {8 g8 [: sEllipse, 椭圆
5 A" p$ d9 j2 N6 T ]Empirical distribution, 经验分布
: t7 U+ b2 ^0 k; U: lEmpirical probability, 经验概率单位
: f7 M$ Y0 e& c% O& Z' ?Enumeration data, 计数资料& i2 b& ]. x, C2 o# ?5 b& C+ r
Equal sun-class number, 相等次级组含量; u: Q( x1 A0 i: P$ g V/ L
Equally likely, 等可能1 l _7 s+ J7 {
Equivariance, 同变性, S) _- D6 W" _6 n( t) W6 q
Error, 误差/错误( F; G) j" ]6 t: j3 h
Error of estimate, 估计误差2 p/ J* N' ]7 T: ^. ~! c5 w+ v
Error type I, 第一类错误/ L, R- ]1 D7 _; K; c: [
Error type II, 第二类错误
$ I4 s# a. y& ZEstimand, 被估量" S4 ]9 l2 t8 s7 \, l3 h: N% G2 D5 n
Estimated error mean squares, 估计误差均方, _ M; }2 ^! I
Estimated error sum of squares, 估计误差平方和
5 x% c5 Y. i: \- V, a* H" y2 eEuclidean distance, 欧式距离, b& o$ a, f7 N% d! t
Event, 事件4 z/ x7 X# b" Z# p0 M" Z
Event, 事件: \, ^1 p6 s$ k5 m: L* d
Exceptional data point, 异常数据点, M7 V5 {% I0 C& j
Expectation plane, 期望平面
. V) o5 R* q! _$ T$ CExpectation surface, 期望曲面
3 G/ O9 M0 g" _Expected values, 期望值% O. V' f8 I& z
Experiment, 实验
4 [0 ]1 E. s8 z9 B) b" d# @. cExperimental sampling, 试验抽样
4 P6 D) D% T: D7 W+ Q' u% `8 K6 d- dExperimental unit, 试验单位
! H$ j+ U4 r+ G7 QExplanatory variable, 说明变量
6 R/ D W3 f, g" OExploratory data analysis, 探索性数据分析
) I- d ~1 |8 x, k# [Explore Summarize, 探索-摘要
7 b& N, D C/ Y( O* Z. h b/ Z7 m9 bExponential curve, 指数曲线6 c( i2 P7 g0 @
Exponential growth, 指数式增长. P: B4 o2 S$ l6 j1 F9 { x& ]7 s
EXSMOOTH, 指数平滑方法
! @4 `& b( l# GExtended fit, 扩充拟合
7 p- }) ?2 R( k8 S5 \: g! L' t( nExtra parameter, 附加参数8 J: N3 n+ x' y4 h) \
Extrapolation, 外推法9 P: F8 M( b8 D$ g7 |
Extreme observation, 末端观测值& D8 w _8 U$ C2 ]. e+ d2 v
Extremes, 极端值/极值
* e9 A6 m$ I2 e$ b. f$ WF distribution, F分布
$ Y$ A9 q; d2 s8 `2 p6 QF test, F检验/ D, Q0 W7 q$ \! [) Y
Factor, 因素/因子& D. q; W, D# |1 h+ O
Factor analysis, 因子分析
" B$ m' |; n/ _ mFactor Analysis, 因子分析/ ^! k' j: V Z0 ~; D+ e
Factor score, 因子得分
/ l9 @2 m4 [0 F% J; ^Factorial, 阶乘+ x+ k; ^* E- f, ]+ j
Factorial design, 析因试验设计
; Z' A. h" [0 A4 Y g5 S8 rFalse negative, 假阴性0 J) M6 d* \2 A( p1 L5 R+ U* G
False negative error, 假阴性错误
) F2 D- f5 |# S3 u xFamily of distributions, 分布族
+ j2 l; m! u6 q7 P' W" AFamily of estimators, 估计量族
) ?/ b" t' \' z. yFanning, 扇面
0 C, B7 f) j5 p' lFatality rate, 病死率
: Q6 ]+ q$ T" i4 f- ^Field investigation, 现场调查1 a. ~& u. y3 \; a; \# q
Field survey, 现场调查: x: n6 D4 h3 s
Finite population, 有限总体9 K& O: L2 G& a6 o$ n/ S
Finite-sample, 有限样本& s9 M* @9 Q/ l: x2 b( _
First derivative, 一阶导数 j. B# t" @; T0 @! m
First principal component, 第一主成分, m; K) q) j- Q
First quartile, 第一四分位数
3 H2 Q( l* j) e. t; ~Fisher information, 费雪信息量6 R3 p c2 l! C
Fitted value, 拟合值3 O6 B& o& ]" M
Fitting a curve, 曲线拟合8 _ u6 k$ ^0 W7 D
Fixed base, 定基9 b1 _+ ]4 ^+ M- Q" [4 x2 S
Fluctuation, 随机起伏" G' C. D ]4 Y+ f! X3 |/ N
Forecast, 预测# K+ i3 f) \" S$ C, ]* |
Four fold table, 四格表
3 v1 }( d+ ^6 |. WFourth, 四分点
+ t$ ^3 ^3 |# S- c. q" R; ?Fraction blow, 左侧比率3 D$ l# R4 J8 [+ `) [' e6 c6 j
Fractional error, 相对误差
9 w0 H$ n% D7 y# B' t! q( i7 pFrequency, 频率
2 i, @& c1 {& M) R9 j; CFrequency polygon, 频数多边图1 r% w1 Z) b+ J1 W7 a- a8 H3 V2 t
Frontier point, 界限点
' E s$ j `; O p* EFunction relationship, 泛函关系! C( \( H1 e N
Gamma distribution, 伽玛分布: `0 l! Q% }: R& V F
Gauss increment, 高斯增量" u3 c" j/ b8 p; U0 D. Z
Gaussian distribution, 高斯分布/正态分布! M, B4 q% }3 Q8 Y" F
Gauss-Newton increment, 高斯-牛顿增量) k( c, X& p- h$ G$ t( o
General census, 全面普查
; n9 ~- q& q8 [8 QGENLOG (Generalized liner models), 广义线性模型
8 z _8 m# z' w0 zGeometric mean, 几何平均数
/ ^6 {4 g' ?% _" ]% F4 KGini's mean difference, 基尼均差& W0 N/ I# A. D1 Z: k" E; W! I
GLM (General liner models), 一般线性模型
) a2 c, N5 ~2 M8 P _) Y4 LGoodness of fit, 拟和优度/配合度5 j; K" M5 Z( e) y
Gradient of determinant, 行列式的梯度: {6 y! _0 m: s1 G
Graeco-Latin square, 希腊拉丁方$ M4 s1 I, j3 s( S( N; q3 O
Grand mean, 总均值
) o- w4 l" ]( L" J8 o4 c2 `4 A# QGross errors, 重大错误
/ l# z0 w) h' c) YGross-error sensitivity, 大错敏感度
2 L& }0 R2 e( j: ZGroup averages, 分组平均, n$ t: S1 W. v
Grouped data, 分组资料
% q$ X3 w, K9 h3 r+ @Guessed mean, 假定平均数
( f- i2 }: q+ T5 e8 a( KHalf-life, 半衰期
) f, i* o, u5 J6 e0 q* MHampel M-estimators, 汉佩尔M估计量/ G2 M- L& t: D, f! X$ P
Happenstance, 偶然事件
/ L. T3 V0 e' _' r1 S9 d# t4 K LHarmonic mean, 调和均数1 \! Y( _6 m0 M0 O7 `" ^
Hazard function, 风险均数
- E6 G2 L5 j8 Z8 w1 u% [2 [Hazard rate, 风险率$ c+ P( G! Z' A
Heading, 标目
2 n( i2 w' W5 `Heavy-tailed distribution, 重尾分布' g0 ?4 J5 `6 k' b( h# ]6 u
Hessian array, 海森立体阵9 g- l; i( ?- N" r8 h* I
Heterogeneity, 不同质) j; C4 H( g& L6 a, \8 X$ [
Heterogeneity of variance, 方差不齐
1 s3 q/ E8 U$ y* R7 bHierarchical classification, 组内分组" k+ \# \) V" S
Hierarchical clustering method, 系统聚类法
% k. x- P5 z5 Z+ z. ]& L8 JHigh-leverage point, 高杠杆率点% v [7 a" h- d, V# A8 J
HILOGLINEAR, 多维列联表的层次对数线性模型
( z: i. {( v; `Hinge, 折叶点
7 d( q' D9 {" I8 E2 L. XHistogram, 直方图4 H+ }2 v x' p% a
Historical cohort study, 历史性队列研究 2 ^! [+ h+ C: n
Holes, 空洞' @( l) t# g2 M( V; N
HOMALS, 多重响应分析
8 ^9 A$ T* g! i) e! r# m" gHomogeneity of variance, 方差齐性
$ g9 K' w8 |* M; t0 p6 P* eHomogeneity test, 齐性检验
2 E) K* f$ o `) S% I" ]Huber M-estimators, 休伯M估计量& n$ H% @8 L% _
Hyperbola, 双曲线. y$ Q' r0 T Z4 L9 @, u! v
Hypothesis testing, 假设检验4 i! s3 |* n) c0 x( X; w
Hypothetical universe, 假设总体
0 _# P; {! T" F9 v; y o+ zImpossible event, 不可能事件
* A+ X( T0 M% I- `4 F; e5 S# ]Independence, 独立性
5 q) c# Y4 \! i% W6 u7 V1 NIndependent variable, 自变量
- v% w( |) q0 x1 u/ y. jIndex, 指标/指数7 j& [& ^' J& v
Indirect standardization, 间接标准化法4 N; A3 N% i7 h' o6 s
Individual, 个体+ r) M' Y$ {9 s
Inference band, 推断带2 q) b6 ?& K% k7 r- i5 ~
Infinite population, 无限总体* _) J3 w. c p& p) U% w, p
Infinitely great, 无穷大5 _! S8 ?2 Z( J+ z
Infinitely small, 无穷小7 q" C! q# W! I0 s' o
Influence curve, 影响曲线8 b6 h! I" j* o2 |1 b
Information capacity, 信息容量7 Y, ~5 i" L7 A
Initial condition, 初始条件0 [' A* t$ U/ O b
Initial estimate, 初始估计值
. \% O4 u! {# G! R& kInitial level, 最初水平
/ L, C5 {, S5 W. J/ W' fInteraction, 交互作用5 A2 N Z$ ~. b% ~5 @" t
Interaction terms, 交互作用项1 E% X. I3 D+ Y4 h8 p
Intercept, 截距
/ \* K1 S/ t! I y n% OInterpolation, 内插法( ^! u, ]& ^) Y2 f) {
Interquartile range, 四分位距, a! o7 a+ [* H' A9 |2 {
Interval estimation, 区间估计1 r% A, ?0 P; l% r8 f
Intervals of equal probability, 等概率区间
1 w: ~0 Y# k+ n( _0 FIntrinsic curvature, 固有曲率
) O8 T3 H7 B* `4 zInvariance, 不变性
) q7 j- Q# d! b1 F' m% n1 fInverse matrix, 逆矩阵
) m5 D& M+ j) x5 b; SInverse probability, 逆概率
$ c U: W: {; e F4 K8 Y5 JInverse sine transformation, 反正弦变换" ~( i3 t. G+ }4 E+ A
Iteration, 迭代
5 |( T" t' t$ }/ ]& EJacobian determinant, 雅可比行列式, J3 G" J$ t- _9 N! D
Joint distribution function, 分布函数2 q. o0 {) m7 s( B! _+ M) z7 P
Joint probability, 联合概率
3 W5 K/ P) b" \8 A( l7 ^Joint probability distribution, 联合概率分布" V" P, U+ h( `9 O( n/ B+ t
K means method, 逐步聚类法
8 g5 g& R7 \" Y; b; |8 ?/ E$ v$ {Kaplan-Meier, 评估事件的时间长度 : g3 F3 S1 \/ @3 b' V6 X) G
Kaplan-Merier chart, Kaplan-Merier图
# ^6 E2 l5 B) w* m1 ~' h AKendall's rank correlation, Kendall等级相关/ a( B6 Y7 Q: x- p5 c
Kinetic, 动力学/ ?) b$ k" F/ m+ e6 A# ]
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
* T* ]* i( |$ XKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验( F, g1 |( Y" j0 r; o
Kurtosis, 峰度
6 u$ O0 j' H gLack of fit, 失拟5 S0 N- T6 y' X( q, Q% J9 @
Ladder of powers, 幂阶梯4 d/ b# H; O* B3 ]4 e3 c. }( Z
Lag, 滞后' R" o' e& V( a3 _1 R! v: b
Large sample, 大样本. X0 C e# i8 X8 u0 b
Large sample test, 大样本检验# M0 o, l6 n3 o2 \& ]( g$ k5 M
Latin square, 拉丁方
- P( w# t2 D) j$ ^" NLatin square design, 拉丁方设计 u% D5 K0 ~! O
Leakage, 泄漏$ C. X6 i; G" V& Z; }6 l8 ]
Least favorable configuration, 最不利构形6 y5 U: ~; h7 \, m, Z: E8 ~! q
Least favorable distribution, 最不利分布
8 ]3 d/ M! [# c( T$ T% M- {% E4 RLeast significant difference, 最小显著差法
* }1 O! e! m- w4 P7 p4 q; f" ?/ RLeast square method, 最小二乘法1 J' R: p8 Z' P* U/ D1 [
Least-absolute-residuals estimates, 最小绝对残差估计
, @9 W# G4 I0 |5 O% O; hLeast-absolute-residuals fit, 最小绝对残差拟合
5 \5 y% ^+ h: n; F; BLeast-absolute-residuals line, 最小绝对残差线
: R- [& D) o6 L5 P0 o" B; ^ h( uLegend, 图例
: `6 k _# {7 \; ^9 M Y3 NL-estimator, L估计量
! F0 m7 d$ A1 `3 h6 TL-estimator of location, 位置L估计量5 b; w6 K0 @ L+ [
L-estimator of scale, 尺度L估计量! K5 s: x( ? t) b9 f
Level, 水平
- J6 O$ R/ _. a( T' Z; ^( aLife expectance, 预期期望寿命! U+ x$ Q' g% b) K( v% ~3 q
Life table, 寿命表# d' V/ \6 I) |4 H' v* K
Life table method, 生命表法
- C2 _3 {9 h: Y1 f/ F/ u1 eLight-tailed distribution, 轻尾分布
6 D' p m! |- e1 L+ ]& JLikelihood function, 似然函数 d: b8 Y0 x. \ a
Likelihood ratio, 似然比
9 V- \3 L" b' b+ T' _line graph, 线图
) ]4 `- i0 x" M; W6 gLinear correlation, 直线相关, @) K8 ]6 c" s$ Y* q6 n
Linear equation, 线性方程; c7 |' u/ `$ V3 N! Y ~
Linear programming, 线性规划
\6 S' x& N7 J z- l0 w1 NLinear regression, 直线回归6 D" q [6 F6 y; |* c8 i" y
Linear Regression, 线性回归
) f9 S3 _2 p7 p+ s3 h' l F0 R0 _0 Q5 YLinear trend, 线性趋势( `0 W+ |! D% f1 d6 W' }, l( x7 O
Loading, 载荷 % L! f. P* ~& |# S3 b e& Q' a) V2 i
Location and scale equivariance, 位置尺度同变性
; R& U, |7 `2 Z# I2 a2 VLocation equivariance, 位置同变性
9 \" V- ]$ F5 uLocation invariance, 位置不变性* l, d5 {0 `! j% m2 ~9 I) n8 k! J
Location scale family, 位置尺度族
. o; r- b4 |+ kLog rank test, 时序检验 ( S7 B* I. ?$ R' I8 K$ x. @
Logarithmic curve, 对数曲线# e+ z: b* I& g9 @
Logarithmic normal distribution, 对数正态分布
1 l [. t4 o+ [ K" RLogarithmic scale, 对数尺度" M( O7 l& j4 a& g
Logarithmic transformation, 对数变换
0 r) j; m# E q1 l1 y5 _/ E* T jLogic check, 逻辑检查1 @: U; B4 Y9 E* ?2 ]* t- E" Q
Logistic distribution, 逻辑斯特分布; N8 m* L. E- |0 e3 u& P' F( m
Logit transformation, Logit转换1 Q* U& H; _# Z) R
LOGLINEAR, 多维列联表通用模型 . U8 c0 |; Z4 y" N& {8 J$ T8 @
Lognormal distribution, 对数正态分布
. V- H& z, Z: x- W4 ~Lost function, 损失函数5 ~2 m$ e |+ E( A
Low correlation, 低度相关
0 s& A) {% A* ]0 }/ a' o7 FLower limit, 下限3 R) |+ r& K! z# q6 Z
Lowest-attained variance, 最小可达方差
1 A& b" N0 |( l2 o/ hLSD, 最小显著差法的简称& H9 ]4 n! T# [- Z$ u/ l" I
Lurking variable, 潜在变量
2 Q( ~4 K. Z; z/ i- {7 @2 s- iMain effect, 主效应
* N$ u d* X3 ^. h5 i5 y" cMajor heading, 主辞标目$ A4 C( |% i+ {
Marginal density function, 边缘密度函数
|: J! ?8 ^2 r; o8 |Marginal probability, 边缘概率
- Y1 X) d! a' A7 Z4 g0 ~Marginal probability distribution, 边缘概率分布% p" B0 V0 h6 Y
Matched data, 配对资料# e6 m) g7 Z2 @3 ^: ?
Matched distribution, 匹配过分布3 u% e+ V! I: Q6 w
Matching of distribution, 分布的匹配( ?- X7 d1 ^8 L- o4 M# _, j5 ~# R
Matching of transformation, 变换的匹配% }+ A8 Y8 j9 ~ w
Mathematical expectation, 数学期望" c" W1 [# }# ~& m) B$ A {* C
Mathematical model, 数学模型/ h% i; s. h1 l3 d! H# h7 w& j; W
Maximum L-estimator, 极大极小L 估计量& b5 I3 }: _8 R: P* h3 G9 t
Maximum likelihood method, 最大似然法0 K: g- t; I! K4 l6 t2 ~, @, ]* c
Mean, 均数0 I3 k; l( d" f4 o
Mean squares between groups, 组间均方
. G3 \* }' @4 l2 H. [$ `- xMean squares within group, 组内均方
, @9 H X1 Z7 f- z5 d; g6 BMeans (Compare means), 均值-均值比较
- R. T& I9 N/ A/ d6 gMedian, 中位数, B; k' K0 L; X( S5 O* o ~; X
Median effective dose, 半数效量2 l c3 Z- ~' r C1 {: j' N! [
Median lethal dose, 半数致死量
( ~; E' F( O' bMedian polish, 中位数平滑6 w5 _. j+ A+ y2 y9 ~5 y# R
Median test, 中位数检验
+ _+ Y2 ]; g( f+ pMinimal sufficient statistic, 最小充分统计量
& }3 T4 W' Y0 `$ }5 b& tMinimum distance estimation, 最小距离估计3 H1 l+ k7 Q$ i9 R1 K [
Minimum effective dose, 最小有效量
, T' R6 [9 J. B! Y7 x8 {/ bMinimum lethal dose, 最小致死量1 i. I: G% e q( z( C
Minimum variance estimator, 最小方差估计量+ n5 e% Z- ?. ~, n. {: O1 l( ~
MINITAB, 统计软件包
% t" U* ]5 X6 k7 L2 u4 k( cMinor heading, 宾词标目/ k/ T. X5 o1 Y( y5 p
Missing data, 缺失值
5 \3 P+ ^$ v0 LModel specification, 模型的确定
; w; u) R2 m r: E7 N; GModeling Statistics , 模型统计$ C! G# S' l1 t0 n
Models for outliers, 离群值模型
" y7 M5 f4 z1 G+ KModifying the model, 模型的修正
- E0 u! m. K' gModulus of continuity, 连续性模
, Y. }$ m8 T6 b* c. uMorbidity, 发病率
& ]% O7 b% e: g2 c( V: H' m+ UMost favorable configuration, 最有利构形* ?. q& D* i1 y. v
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
. V* \( Z, ?: `& K) F% \Multinomial Logistic Regression , 多项逻辑斯蒂回归0 D$ v, G4 z1 i5 \0 X. E8 e8 G
Multiple comparison, 多重比较6 j1 s2 `3 |7 T* G$ \( G0 F9 E2 o
Multiple correlation , 复相关
0 N8 H7 |2 B: w. y7 p; I! _Multiple covariance, 多元协方差' Z. ?2 I# i& F
Multiple linear regression, 多元线性回归8 l& a" W* N( G. d
Multiple response , 多重选项
( P- }, S5 Q' a% eMultiple solutions, 多解
! \1 M% f. A9 i6 J9 KMultiplication theorem, 乘法定理1 C4 C8 f. X* T0 i! w* T
Multiresponse, 多元响应' I! u& s) A7 |8 k
Multi-stage sampling, 多阶段抽样
. l1 |$ h8 |+ M# w) @7 EMultivariate T distribution, 多元T分布
. p0 \" [& ~4 [Mutual exclusive, 互不相容' _9 G( Y: ]6 u
Mutual independence, 互相独立3 W$ f) q. ^- @5 _ Z9 m0 S4 ]" s
Natural boundary, 自然边界
2 a; S! L! ]- X2 s3 u. `5 V# `Natural dead, 自然死亡
8 I9 h$ t- n% @) Z5 x8 FNatural zero, 自然零
/ E3 {7 D3 i9 m9 ONegative correlation, 负相关
' ~6 B2 e4 w! B7 l! UNegative linear correlation, 负线性相关0 }) W0 a1 z0 O$ C# X
Negatively skewed, 负偏
4 L, P/ ?. ?$ E9 ~% yNewman-Keuls method, q检验
6 \0 _* M) e. A- o, V5 W3 M) t0 nNK method, q检验+ B# y- i- J. A' Y% H& z
No statistical significance, 无统计意义% u9 m. _4 T' b ?3 ?0 s* L4 B
Nominal variable, 名义变量
0 `( M0 |) ~; S9 X$ C6 G! K8 [Nonconstancy of variability, 变异的非定常性
5 t/ G% Y6 |) p( `- n$ O7 S+ KNonlinear regression, 非线性相关( {( n% g/ ?9 P# c1 v
Nonparametric statistics, 非参数统计$ l. E& J6 W: P" l9 E2 {+ F
Nonparametric test, 非参数检验
' ^! _% P- s: v ~! Y0 PNonparametric tests, 非参数检验- K( @9 f& b U, @% m
Normal deviate, 正态离差5 A% U) V- }/ K$ D; j
Normal distribution, 正态分布
) N( ]. Q: {) |. s3 o4 MNormal equation, 正规方程组9 q/ P3 J. J* M9 W: h2 i
Normal ranges, 正常范围
- s* M) W- r( p& K; P9 n! |: yNormal value, 正常值
( S0 \$ _ N+ M6 m* xNuisance parameter, 多余参数/讨厌参数
& M- E1 M+ s' i' G5 {' Q9 L, TNull hypothesis, 无效假设 8 d! @) v5 t( v7 R6 D
Numerical variable, 数值变量
" I2 L6 r$ }# x+ }+ VObjective function, 目标函数) q, a( W5 \% U Z& i' ]6 H! ~
Observation unit, 观察单位
4 J( J0 J9 R# e7 k; q F) _; X$ j& CObserved value, 观察值& f b) `" G8 U# v/ Y3 o# i
One sided test, 单侧检验. z) X- S+ w; L" H. T' `
One-way analysis of variance, 单因素方差分析3 f' B' p: r. M
Oneway ANOVA , 单因素方差分析. e6 X7 s! I1 p k R: H' i& v& }
Open sequential trial, 开放型序贯设计; n# x9 O& G* S% n8 r% }1 o
Optrim, 优切尾4 }& Y; L; p/ m1 R5 t
Optrim efficiency, 优切尾效率) X7 [5 }% ]* b% \
Order statistics, 顺序统计量* E, j; @+ @7 M1 o! v. ?- n2 I
Ordered categories, 有序分类6 V" S6 y) h: o w$ J: l2 Y9 q6 T
Ordinal logistic regression , 序数逻辑斯蒂回归
1 q; e1 m% J* o- iOrdinal variable, 有序变量
* I7 @9 G* @* q: rOrthogonal basis, 正交基
9 ?5 u* h, B9 u: B) x( U3 a: j; G. iOrthogonal design, 正交试验设计2 K$ V+ Z" {0 c0 J) P6 S! n
Orthogonality conditions, 正交条件
3 T8 B! z) B9 _4 A7 UORTHOPLAN, 正交设计
( T# c' a, R4 q, kOutlier cutoffs, 离群值截断点
+ L4 E" n; g5 m$ UOutliers, 极端值
) R. C$ I8 u7 q( H2 u3 ^OVERALS , 多组变量的非线性正规相关 + u% a- K& D' t' y7 q2 K+ `
Overshoot, 迭代过度/ f$ t9 Y9 P1 U" h* o9 N
Paired design, 配对设计: D6 `) L d+ v8 i7 Y9 \8 J
Paired sample, 配对样本+ y6 j. b* u+ N4 X5 ?1 G4 i
Pairwise slopes, 成对斜率
- m1 g0 ?* Z- |5 {Parabola, 抛物线
/ }( v" E2 Z6 ~6 V1 ^1 P( g& t2 O& rParallel tests, 平行试验
, J& [- I( B9 k R, d& g, jParameter, 参数
: E# i$ ]8 y# a& k F7 dParametric statistics, 参数统计) ~2 o/ K4 C' E2 _5 x |
Parametric test, 参数检验
4 o/ s* Q1 l+ qPartial correlation, 偏相关& Y6 @8 e& ?& I
Partial regression, 偏回归9 R$ T+ ~1 v2 Z. P& g4 N2 j
Partial sorting, 偏排序
5 v: m7 t: H9 RPartials residuals, 偏残差
& R0 g+ _+ v6 s3 J2 iPattern, 模式' l* G) m& C2 e) R' ]/ H
Pearson curves, 皮尔逊曲线' T! t/ [& ]: q6 g- W5 i
Peeling, 退层% }" l1 G4 V: v3 G: q3 `
Percent bar graph, 百分条形图- k# F' B) u4 w
Percentage, 百分比$ W2 e5 @9 q4 f3 n; \: @3 ~
Percentile, 百分位数3 M n) g3 W! L& y- X. R/ G L L
Percentile curves, 百分位曲线
, S' b! w/ ^( {; p) d( y/ [Periodicity, 周期性1 p% ?0 H8 C1 y9 |( p
Permutation, 排列) z7 e* x2 R% c/ Q Y3 E
P-estimator, P估计量
. O; T# r- t* cPie graph, 饼图
/ ?1 e7 l- n5 c- K7 `. WPitman estimator, 皮特曼估计量3 l- R8 s6 D9 O& b/ s
Pivot, 枢轴量
% M5 p) @1 M6 D+ rPlanar, 平坦
( L6 o6 M& n7 G6 NPlanar assumption, 平面的假设* ^" ^, K9 E4 @5 P( ^; y
PLANCARDS, 生成试验的计划卡& V- X' \& d9 q O! b- S' H; N
Point estimation, 点估计
4 J" N, b. k- x: L) s; j1 O' wPoisson distribution, 泊松分布
+ A% V7 g/ P5 J2 b% R3 hPolishing, 平滑4 N' l5 @0 Y; a6 n' g. r& e
Polled standard deviation, 合并标准差
2 y E+ [' r Y7 X+ h5 KPolled variance, 合并方差
" e" E% E$ A+ O) \8 [Polygon, 多边图* k* R% T& S* r& T1 m1 i9 L
Polynomial, 多项式
3 N, q/ s9 b l" H8 fPolynomial curve, 多项式曲线
3 A; X( |2 Y4 C9 I7 o) E8 UPopulation, 总体
4 o! \) @' T0 n) h, P( NPopulation attributable risk, 人群归因危险度
( o/ r# ~; ]: Q% `. {: ^: [" j GPositive correlation, 正相关
) g+ Z7 x, `5 ?4 r* ]) a$ UPositively skewed, 正偏) w& X3 {# t! L& x7 V/ ^
Posterior distribution, 后验分布, f/ j* T. g: P' i: F: E5 o
Power of a test, 检验效能
: L% X+ e; n3 }5 o( h/ nPrecision, 精密度4 T- W5 ?, N/ ]3 b4 _
Predicted value, 预测值; e A/ i/ ?4 X! n* u6 D
Preliminary analysis, 预备性分析2 ]' ~) u$ `) h
Principal component analysis, 主成分分析
* r0 n9 p% _9 A RPrior distribution, 先验分布
! k4 H# l3 J* {! y' x9 w( }0 ~2 bPrior probability, 先验概率
, s0 R% `4 D8 y0 @! ~. C0 PProbabilistic model, 概率模型
4 u& W' u, d. `' C# Wprobability, 概率
# O5 x2 q7 O8 s* |Probability density, 概率密度
6 Q! V) b0 K1 L6 b" Y4 ^9 vProduct moment, 乘积矩/协方差
6 T) c$ Y4 Z% s/ C2 CProfile trace, 截面迹图- }' E" i9 V3 T& J; a
Proportion, 比/构成比3 @# X8 Q u/ T9 ~
Proportion allocation in stratified random sampling, 按比例分层随机抽样$ g; T2 Y6 b F% A5 c& b3 e
Proportionate, 成比例
& n4 O4 y9 M7 |" ]5 S7 QProportionate sub-class numbers, 成比例次级组含量/ p- z/ m0 A4 B5 E) Z
Prospective study, 前瞻性调查, e6 a( G: z' \' U- K
Proximities, 亲近性
! J/ _2 T9 i% j I5 _$ z8 FPseudo F test, 近似F检验
' r9 s' l2 r' h$ u, t ^) WPseudo model, 近似模型5 U+ m( A4 v$ {9 L# `% m* M( f
Pseudosigma, 伪标准差
& u9 r$ B1 E0 ]$ _Purposive sampling, 有目的抽样
; n3 J5 w. ~8 ~# o# PQR decomposition, QR分解$ v9 |9 v' _; Q
Quadratic approximation, 二次近似
8 t$ q3 |: V6 y& QQualitative classification, 属性分类6 f, m5 f; }; Q( K
Qualitative method, 定性方法% j: K9 W% O# N3 W
Quantile-quantile plot, 分位数-分位数图/Q-Q图% |# x! Z7 C9 Z$ T! w& \
Quantitative analysis, 定量分析5 Q: K3 \" \4 S/ B: w2 L; a
Quartile, 四分位数) P3 e( s7 O2 r5 [4 ]& C
Quick Cluster, 快速聚类; N$ [7 m8 k$ m# R- R, E
Radix sort, 基数排序
. `# }* W5 V# V; eRandom allocation, 随机化分组
7 L& P# ?. W2 E1 n+ n2 z; ]Random blocks design, 随机区组设计6 b* t2 P: \) W7 @8 R8 \( V
Random event, 随机事件
/ a& d8 w" l/ E. ^' U1 j/ f& DRandomization, 随机化
( |$ W# D8 Y( c. ERange, 极差/全距
2 k3 X( @+ s! P/ M- k+ QRank correlation, 等级相关
, K4 N. n# e- v; p+ ORank sum test, 秩和检验
* Z9 \: O; f6 N1 H3 YRank test, 秩检验# Z* J! g7 N) i# e; [
Ranked data, 等级资料4 U1 Y7 |7 _; Q; d. V
Rate, 比率
0 u8 n6 s! S4 f' u- ~1 t. R6 s" kRatio, 比例1 y) ?* X( @5 P
Raw data, 原始资料
0 `5 o# h% X9 r! d( g' s; HRaw residual, 原始残差
y( O; T [$ i) ARayleigh's test, 雷氏检验$ o- e- S- p' B+ W1 i2 ^+ e
Rayleigh's Z, 雷氏Z值 ; F% E3 o N& K4 W
Reciprocal, 倒数) H2 z% Q4 P0 }: i! l' L
Reciprocal transformation, 倒数变换; a4 K% ?) Q& c5 Q* `! z3 Z
Recording, 记录
/ p: R9 ~$ R2 d7 }+ KRedescending estimators, 回降估计量
1 K" r! q$ g; n* |8 WReducing dimensions, 降维
! G* F- _% r; [! M' ZRe-expression, 重新表达$ r) ]* j$ _2 W8 ^6 h4 V, G
Reference set, 标准组
9 Q' Z+ K/ \. h: [9 @. ^9 c m, Q8 HRegion of acceptance, 接受域
' r+ V9 Y% S! a+ w0 [Regression coefficient, 回归系数5 z; X* h8 w4 q% h4 N4 f
Regression sum of square, 回归平方和, Y1 `" i: G1 G$ T. V" {# X3 |* H
Rejection point, 拒绝点
9 [) `6 Q x9 E }& mRelative dispersion, 相对离散度* S+ s3 v) V4 ?
Relative number, 相对数+ U$ |/ y. h$ c7 Q8 W
Reliability, 可靠性
7 P$ X: P: n' E4 W- {6 dReparametrization, 重新设置参数7 c% q3 y0 e9 E0 D! N/ v# X
Replication, 重复
" O) K$ D7 D T/ X( _- ~' pReport Summaries, 报告摘要
; _- C7 C) K2 j: J# b, wResidual sum of square, 剩余平方和
0 u, U: j( a# s; ?5 fResistance, 耐抗性$ B/ D+ D2 n8 ]: L( s: d
Resistant line, 耐抗线
1 J! Z \( x3 b3 o1 p. r; N% i. X) @Resistant technique, 耐抗技术8 ] g' w1 f" w5 k9 n1 e: T
R-estimator of location, 位置R估计量) r) X l! m& x* V4 {6 y
R-estimator of scale, 尺度R估计量
, U) ^* E) @- S) }Retrospective study, 回顾性调查
& b P8 C2 s& ~/ zRidge trace, 岭迹
9 B: E, _% t/ {: n5 Y, N$ E. t/ \* | K8 SRidit analysis, Ridit分析5 v4 R0 ?4 M8 O B# h H+ H
Rotation, 旋转. A; d# d. a2 K3 L. Q8 X
Rounding, 舍入
( U1 N/ [1 a6 Z8 fRow, 行
: J8 ?1 ^4 Q# E" M/ b6 L% DRow effects, 行效应
" t! g% n& E, G- O! q, URow factor, 行因素2 z* P& T; n: [ @9 e
RXC table, RXC表0 H' Q: a) b- F6 \ D7 o
Sample, 样本
& r# u2 Y: a, U6 a& x+ ~& O. }: iSample regression coefficient, 样本回归系数
/ ~4 W0 i0 H4 W/ v# eSample size, 样本量
& M+ V2 w8 t! a/ c: h6 X4 dSample standard deviation, 样本标准差 V* M6 ^& j8 j0 P
Sampling error, 抽样误差+ N, v/ H% {1 k! f2 ]+ k" N
SAS(Statistical analysis system ), SAS统计软件包
; y, N& u t/ e9 f0 H7 HScale, 尺度/量表+ Z2 }6 a' F: }' `* s/ f3 v/ e' |
Scatter diagram, 散点图/ c, |. f: m4 R2 r+ d+ N
Schematic plot, 示意图/简图0 q- f6 G- j! E7 l
Score test, 计分检验
! W' h' j0 x5 ZScreening, 筛检9 o' D2 ?- p' J9 L Q0 ?) ^
SEASON, 季节分析 0 X; Q6 Q1 f; D% N8 E h
Second derivative, 二阶导数
! f2 C/ X/ f R! R" I2 J; aSecond principal component, 第二主成分
1 C S! F" `# H7 ~9 t- Z7 mSEM (Structural equation modeling), 结构化方程模型 / a0 h# \" y1 R9 g. V2 v, g
Semi-logarithmic graph, 半对数图
( G! |2 J6 y$ N+ RSemi-logarithmic paper, 半对数格纸1 R9 ]' S" S* E+ g
Sensitivity curve, 敏感度曲线
3 |( Q# n9 i" M& RSequential analysis, 贯序分析; P8 H) Q9 |% z1 a! L2 {" E) `
Sequential data set, 顺序数据集
* d( N- `& F5 Z9 {) jSequential design, 贯序设计/ C W/ f6 v2 F, L" K! R/ h
Sequential method, 贯序法! X" }. r; \& Z) I, j3 }& Q; v
Sequential test, 贯序检验法8 q% k$ a- s' K' f7 C2 g4 j. J: P
Serial tests, 系列试验: x; l1 K: F6 h& c( N
Short-cut method, 简捷法 ; z# ]& q/ z/ n: {: o
Sigmoid curve, S形曲线6 K' o" z- W, p/ w7 i* x4 U/ O
Sign function, 正负号函数
. j( [/ h, E% c4 L' n, ^Sign test, 符号检验
0 U- m( W. g& R6 y. ~* i1 R3 x; `Signed rank, 符号秩
, l# C! Z& M# l' m6 a/ _Significance test, 显著性检验
1 Z8 A" t! \- W7 }8 X# ASignificant figure, 有效数字' [# o9 D- O+ y* F7 S4 M- L
Simple cluster sampling, 简单整群抽样/ ~$ j% n/ U/ B1 J; I8 @7 e* Y
Simple correlation, 简单相关
: p; ^6 G6 d, R! {6 [* t8 dSimple random sampling, 简单随机抽样" c4 p! [/ h/ I Z: A
Simple regression, 简单回归- S+ s, J% a x% @7 _
simple table, 简单表
7 e @2 V$ s8 I* U: F" B0 ySine estimator, 正弦估计量
7 G; e9 ~) J6 s- X+ W# U& mSingle-valued estimate, 单值估计
6 T* d4 ^( {# b* x8 D$ u' ^Singular matrix, 奇异矩阵
% N. U7 s7 N: b5 c/ |Skewed distribution, 偏斜分布1 @( J; p6 k' X
Skewness, 偏度* S/ o2 A9 L6 ?7 d
Slash distribution, 斜线分布0 I" h# B* d' K4 X- t1 W/ j
Slope, 斜率% k% P" E5 K7 _( ]. m9 ^
Smirnov test, 斯米尔诺夫检验
7 _ _% `0 M5 o% s" TSource of variation, 变异来源
4 x) Y1 [& b U/ {Spearman rank correlation, 斯皮尔曼等级相关
. _/ w2 G. A, |5 {- `3 S. {Specific factor, 特殊因子# H( O/ c* O& U. {
Specific factor variance, 特殊因子方差0 U( L' D( _8 E% M7 S, s$ T5 ]
Spectra , 频谱6 `$ G/ H) a+ W) L
Spherical distribution, 球型正态分布
2 i$ e8 F* j& r [' Q- {Spread, 展布
4 Q: t1 \& W5 U9 m$ o DSPSS(Statistical package for the social science), SPSS统计软件包. l0 I3 P2 V( p$ q7 Y% G/ `" s: \
Spurious correlation, 假性相关
$ }; X. ^" N. L2 PSquare root transformation, 平方根变换) e2 ]: I- t* s6 o! F
Stabilizing variance, 稳定方差
+ E8 ] K7 T7 V5 hStandard deviation, 标准差( I' |0 c" @( B: L
Standard error, 标准误
; C2 j. J! q3 t3 p) D0 e0 R9 mStandard error of difference, 差别的标准误2 m0 z( q7 z) L8 @2 {
Standard error of estimate, 标准估计误差5 r# c J$ a. S' [8 i
Standard error of rate, 率的标准误
* t" ?; d7 B9 O. o' d9 ]. u5 c. wStandard normal distribution, 标准正态分布
1 `6 U% q$ `/ \Standardization, 标准化" k2 @! I4 f( `! Z
Starting value, 起始值1 z" _9 g* \, j& B8 p
Statistic, 统计量
7 R: C4 C8 i) R/ |4 {Statistical control, 统计控制" d, K' w6 V; M9 J
Statistical graph, 统计图* W' x# t) K: M3 r' y
Statistical inference, 统计推断' C6 z! m* }( ~+ Y2 E, n2 I2 ~ J1 w
Statistical table, 统计表0 l8 i6 M) A/ k. l/ J9 t- D2 z% L
Steepest descent, 最速下降法
. I( Z' b0 z2 B) LStem and leaf display, 茎叶图1 h# J W, I9 {( |5 f' r g9 A5 ~
Step factor, 步长因子
8 g. m0 C7 U* C. u4 j DStepwise regression, 逐步回归
" U7 G) y2 I5 E5 s4 l& u) zStorage, 存0 c% l) M$ U5 E% H. e
Strata, 层(复数)( w0 a" W' z* ^- c+ C, ]+ j2 r
Stratified sampling, 分层抽样
o7 K' D4 t& a0 CStratified sampling, 分层抽样
4 A# t% E4 w, M& c* Z, `Strength, 强度
( B" z# H3 r. j3 E/ [' [1 SStringency, 严密性
9 A9 H' x: E; M" D) MStructural relationship, 结构关系
3 @7 f2 r4 Y" E }Studentized residual, 学生化残差/t化残差2 j9 }3 {6 W" M1 Y/ T
Sub-class numbers, 次级组含量 @, c y4 j1 o% r$ j! I3 L0 ^* J
Subdividing, 分割
7 D) H1 u2 k/ ^, @+ GSufficient statistic, 充分统计量/ ~8 i! ^& X# Q+ ]) W3 k
Sum of products, 积和9 n ~$ U* {1 b# T! F
Sum of squares, 离差平方和; }( o$ J. U7 P' Y1 B% h
Sum of squares about regression, 回归平方和* F: [" V+ z! {7 j. x8 _
Sum of squares between groups, 组间平方和
1 F# J' b8 f0 K" c- M M! G* T& WSum of squares of partial regression, 偏回归平方和
2 X1 m% u* ]' e! BSure event, 必然事件
$ _5 L: P7 m6 L; JSurvey, 调查+ {+ n* a% P, |3 l; z$ r" j
Survival, 生存分析* t) o! I0 j+ O/ A7 P/ ?
Survival rate, 生存率
( _# `; `' Z5 S* [- j+ K& LSuspended root gram, 悬吊根图
- w3 T# E3 \) v7 m& C `Symmetry, 对称8 J: b5 q3 ?+ o. `8 s
Systematic error, 系统误差0 }: I5 y% Q. @
Systematic sampling, 系统抽样
5 `; y9 n1 Y x$ Z5 c L4 H/ |Tags, 标签' s; X1 l3 a6 ^( v/ [9 y. p- V9 V0 P
Tail area, 尾部面积
- s( \# p' A& G% |+ a+ GTail length, 尾长( x0 q; p! V5 I' X9 E
Tail weight, 尾重
7 V4 `& a# C' y3 a* E+ WTangent line, 切线; t6 D! b# _4 b/ g- t
Target distribution, 目标分布
9 t0 [6 y, y, H, ?4 K& n; [Taylor series, 泰勒级数% J' K& D" ?1 f. N
Tendency of dispersion, 离散趋势
' |5 o" Z5 q. l7 f9 aTesting of hypotheses, 假设检验( M' N3 a/ F5 v5 j5 v
Theoretical frequency, 理论频数7 X% _, N/ C6 W
Time series, 时间序列
( t5 f( c! s7 Y: M/ u5 S$ O8 u/ {% ZTolerance interval, 容忍区间, f- C2 O! }5 e* T
Tolerance lower limit, 容忍下限. Z; G1 j/ L. L7 h
Tolerance upper limit, 容忍上限( ]# S' u7 e' U; _+ o
Torsion, 扰率
/ T6 K6 E2 D* h# k+ c; rTotal sum of square, 总平方和
- b4 U# L: R: BTotal variation, 总变异0 C$ W3 a+ P) `/ z/ A3 d
Transformation, 转换
; b! u. X M. ?4 H4 ETreatment, 处理! u& d& v) |, t; F
Trend, 趋势
; P# J. l8 l$ [( R- w& UTrend of percentage, 百分比趋势8 c* L9 M# g; C9 ?+ {8 i! J% E
Trial, 试验
# ~1 p* K. p# C. |% [. p9 ~Trial and error method, 试错法
$ D+ E& i6 N( H. R3 K) tTuning constant, 细调常数
9 ?# ~, ~ F! Q" ~3 STwo sided test, 双向检验" l2 H7 z% W% Z" I; ~* \9 ~7 V0 z" |
Two-stage least squares, 二阶最小平方9 e& e( f& `5 v1 ?
Two-stage sampling, 二阶段抽样% @2 a% e* a& d% u& y; _4 V* b
Two-tailed test, 双侧检验
, u3 C' j9 R8 r8 A2 s2 a8 b3 Z; WTwo-way analysis of variance, 双因素方差分析
" H [& t5 q; r1 _( fTwo-way table, 双向表
; V$ x1 E* |1 j* a& _Type I error, 一类错误/α错误1 K$ y' R9 Z: f& Z' W
Type II error, 二类错误/β错误
. h w4 I6 P7 h7 i L* `7 }UMVU, 方差一致最小无偏估计简称
- [/ e' u; Q( C$ C$ aUnbiased estimate, 无偏估计
5 l, e+ r0 q3 a7 |2 H8 QUnconstrained nonlinear regression , 无约束非线性回归& ^$ U5 ?& l$ K- i2 ?% k; M" K
Unequal subclass number, 不等次级组含量
0 f+ O, w( Q0 l9 P* m( l; QUngrouped data, 不分组资料9 F; d0 q( Q* g
Uniform coordinate, 均匀坐标
: b! o9 {2 H3 M+ `- ?0 S8 D; ^Uniform distribution, 均匀分布! D7 }$ H$ N2 Y8 Z, t. c6 m
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
5 x% I/ S& |. oUnit, 单元
( Y& u$ t. f3 [* r! a- U" X+ S. y+ DUnordered categories, 无序分类
1 W& `1 l3 X0 l8 F" P" ~! WUpper limit, 上限8 N5 T0 \3 N( [- l0 U! k
Upward rank, 升秩2 |) j1 \) |$ R/ T
Vague concept, 模糊概念, }2 @* V, g" z
Validity, 有效性* S3 h7 L4 D8 d& K7 Y1 J
VARCOMP (Variance component estimation), 方差元素估计" _: S. g% U% f9 P! V, t
Variability, 变异性+ E- F) F7 `: \' h% F8 C) v4 v
Variable, 变量
; \9 o9 N* P- Q- _Variance, 方差
# U( _' X" i* R2 _% PVariation, 变异
. l) h: J$ A4 [" KVarimax orthogonal rotation, 方差最大正交旋转. {3 R4 V3 D4 s2 e5 W$ g& h
Volume of distribution, 容积
7 p- y, a8 b* _+ _, eW test, W检验
/ p) }' r8 u1 C6 W' W; f- k/ A2 u& Y- [Weibull distribution, 威布尔分布
1 d# \/ f. n. G) U: r2 n9 jWeight, 权数
' c6 x! T. u1 R, NWeighted Chi-square test, 加权卡方检验/Cochran检验
4 o: ]; }* c- y* ~Weighted linear regression method, 加权直线回归, q2 ~8 r+ a* y8 w) ]- n$ T: }6 M
Weighted mean, 加权平均数 w) q( b/ W# t2 r7 l
Weighted mean square, 加权平均方差- I$ A$ u' [) Y) F6 U
Weighted sum of square, 加权平方和* z5 w3 G C: H7 U, ^ `& g
Weighting coefficient, 权重系数8 r8 q( s8 H+ t, V
Weighting method, 加权法 , C% I) P$ C* z. i' f
W-estimation, W估计量
4 B0 l; e& Q1 ZW-estimation of location, 位置W估计量* ~9 R% i! Y \" R
Width, 宽度
& S9 h! n3 g5 |+ g8 o/ cWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
; y+ D5 ^* U# I2 M0 MWild point, 野点/狂点
3 h. S4 G' Q) r8 T1 GWild value, 野值/狂值6 A9 R- z8 R" `% e7 k
Winsorized mean, 缩尾均值
7 p& x5 g$ k& [2 _Withdraw, 失访 0 q( d+ Y) y- H4 m* |5 h7 c1 q
Youden's index, 尤登指数& K1 r" Y' Q1 D( V
Z test, Z检验9 F# `7 Y, I8 {; t) N0 d
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