|
|
Absolute deviation, 绝对离差
/ e* _# { M6 I: DAbsolute number, 绝对数
6 }6 { T; s7 o; xAbsolute residuals, 绝对残差
0 M( V7 C2 i& u7 w& D& fAcceleration array, 加速度立体阵
2 r( N! j4 y! `4 ?Acceleration in an arbitrary direction, 任意方向上的加速度5 d' i3 h/ s4 o0 S# G3 z2 ?# r8 i
Acceleration normal, 法向加速度' N5 H# m9 S0 [" [, I$ S
Acceleration space dimension, 加速度空间的维数
/ Y" ?1 e+ g. p& p9 b" {! a2 \$ O2 JAcceleration tangential, 切向加速度) C% E6 m+ V6 |# }
Acceleration vector, 加速度向量
4 `+ p" l5 p# nAcceptable hypothesis, 可接受假设* a X* K6 Q) m, t1 p
Accumulation, 累积
4 R) Q ?- S+ ?1 U, a" ^% P& qAccuracy, 准确度
7 h. ?) q1 K* x( P+ QActual frequency, 实际频数$ u- u) o. [% i
Adaptive estimator, 自适应估计量
3 V' E+ E3 f2 ?$ E; G$ KAddition, 相加- ]. C8 y8 Z' h& O/ Y4 `, q2 _
Addition theorem, 加法定理
" b$ v5 }% n" H* ?+ U8 cAdditivity, 可加性! F! o9 @3 i1 p" @
Adjusted rate, 调整率
) ~6 q P p- @( v' a* TAdjusted value, 校正值- f$ H: q2 I0 ?+ a4 j/ H5 V
Admissible error, 容许误差4 t2 t5 V, p, H- P% A8 K
Aggregation, 聚集性 I1 F# S7 ~- {
Alternative hypothesis, 备择假设* B% o+ @0 B- s
Among groups, 组间: Z5 x# b# N h- B* C' H% q
Amounts, 总量
$ n9 ~4 G$ [0 a& n0 D4 h& @: s& t5 W9 ?Analysis of correlation, 相关分析2 c* g. N+ S4 K; v
Analysis of covariance, 协方差分析" e# A( o4 k/ G( W* ]& m3 F
Analysis of regression, 回归分析
8 B4 f7 m; J) q' _. P# u$ a2 rAnalysis of time series, 时间序列分析% r2 E- T1 m7 A' M# r0 v( X' O
Analysis of variance, 方差分析
' o3 K8 R0 @6 k- p0 }" k6 ^1 `Angular transformation, 角转换; e5 u; [8 `0 s/ s
ANOVA （analysis of variance）, 方差分析 K1 @: u9 O4 B3 s& R
ANOVA Models, 方差分析模型
6 v! C! I; s3 \ h: m/ C5 @* v! qArcing, 弧/弧旋+ _9 [# y. b- R2 H; L/ `$ Z3 v. ~
Arcsine transformation, 反正弦变换
; M2 z8 d$ n/ v/ o' DArea under the curve, 曲线面积
. N% d6 |( a5 |( H- P HAREG , 评估从一个时间点到下一个时间点回归相关时的误差 # M+ i% [. L* ]# r
ARIMA, 季节和非季节性单变量模型的极大似然估计 / M" L* H. H: i
Arithmetic grid paper, 算术格纸; O$ v* ^1 s- ^: ?
Arithmetic mean, 算术平均数/ N# v& b H" M) H4 w: }* b# E
Arrhenius relation, 艾恩尼斯关系1 T \) E' Z* A5 s+ X* q$ e
Assessing fit, 拟合的评估
C3 j5 D7 p1 K9 VAssociative laws, 结合律$ |) N2 S/ b% i. v4 C) U% U
Asymmetric distribution, 非对称分布
5 k- G J8 d Y% PAsymptotic bias, 渐近偏倚+ Z& f) |5 I. ^( A
Asymptotic efficiency, 渐近效率3 r) z1 q2 Y5 v/ | ?, H- l. ~3 q
Asymptotic variance, 渐近方差# G2 `# z/ o! X; _ [4 y& w
Attributable risk, 归因危险度. x* X6 ~9 f1 a
Attribute data, 属性资料
* ^ z$ E) K3 }9 QAttribution, 属性- c0 D% B. m: A# P$ q; v
Autocorrelation, 自相关
! |! a$ m( U2 H7 x3 A; A, ~4 i+ KAutocorrelation of residuals, 残差的自相关% o& d) e. c/ s' ?5 e+ `
Average, 平均数3 K6 I& T# T0 I4 O
Average confidence interval length, 平均置信区间长度: X6 [0 k. U5 S! C Y1 N
Average growth rate, 平均增长率, @% ` _5 a z
Bar chart, 条形图
" x5 C9 ^) l% ]; v1 `! I; NBar graph, 条形图+ B- {5 O$ x. O+ W
Base period, 基期2 x! S+ z) a& x0 c
Bayes' theorem , Bayes定理
: U. j7 H E$ t& U. zBell-shaped curve, 钟形曲线
8 C# @3 q% a3 i, t9 zBernoulli distribution, 伯努力分布- m$ V! w& s' u( f0 o2 r* i* K
Best-trim estimator, 最好切尾估计量/ w) @; b2 G- _7 V+ }: ]! e
Bias, 偏性* T- c0 P( P! H" ?4 Y4 W$ }7 q0 j
Binary logistic regression, 二元逻辑斯蒂回归
+ x7 n6 M' i @/ i' W& q" nBinomial distribution, 二项分布
4 U! \ n E( v9 u0 @) u/ ]Bisquare, 双平方
- C( [* y0 W, k2 K8 x( }Bivariate Correlate, 二变量相关% G% C7 c7 r. `- P; R
Bivariate normal distribution, 双变量正态分布
' F9 j- W& j& L8 d/ x! R7 cBivariate normal population, 双变量正态总体0 t7 u r6 N! T* R# |1 `3 v: C
Biweight interval, 双权区间) r" Y& s! Z( w. ~
Biweight M-estimator, 双权M估计量+ [3 j6 y% o/ z' ~5 L
Block, 区组/配伍组
4 g" B& w4 H3 JBMDP(Biomedical computer programs), BMDP统计软件包# X. K' |6 Q3 M' C% o7 v" Z
Boxplots, 箱线图/箱尾图
y% Q; a9 }8 M1 W, S+ {$ K0 Z! WBreakdown bound, 崩溃界/崩溃点2 p: y2 }7 ?$ z# t9 j
Canonical correlation, 典型相关& t# r/ m5 x$ Y0 Z2 _$ A% S
Caption, 纵标目( ^! E9 C& [9 ` M" N, ` f& w
Case-control study, 病例对照研究
5 @* ~. K6 n3 C0 @3 a- \2 k9 kCategorical variable, 分类变量5 {5 l, ]! |/ q
Catenary, 悬链线
5 v9 ~' A% L8 z8 A0 O4 x0 y+ d. b5 R# q# rCauchy distribution, 柯西分布
) e1 O0 K7 k, p8 cCause-and-effect relationship, 因果关系
L8 C+ k8 W! NCell, 单元
, \6 I9 h: ^* X$ A+ SCensoring, 终检
9 q! [6 X$ d4 a( F: M/ wCenter of symmetry, 对称中心# T6 g% ?6 t- b$ n" k
Centering and scaling, 中心化和定标! |' ~- T# f( ^# Q u# B; F& t. A
Central tendency, 集中趋势
8 _! |& s: h! W5 q+ f+ C4 N$ ^Central value, 中心值# R! Z8 A; |. z
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测6 s3 ^0 z: R. g3 T5 w
Chance, 机遇
/ h% N z. ]8 c, c: z% a' TChance error, 随机误差
% P( T" v0 a$ C9 v BChance variable, 随机变量0 x* R2 s3 C& ^: V
Characteristic equation, 特征方程4 ]" t8 W0 R7 v/ C
Characteristic root, 特征根6 z5 Y( Z8 l" n; s' a
Characteristic vector, 特征向量
+ k* V) Z- D/ R, K1 D4 @" v* iChebshev criterion of fit, 拟合的切比雪夫准则 G! u# e) @* _ a% Q
Chernoff faces, 切尔诺夫脸谱图
% G; a2 V3 E- L. b- K* l( W, `4 n5 ]# zChi-square test, 卡方检验/χ2检验5 i! }2 }" M* F9 R6 R: K q3 M/ N' x+ T
Choleskey decomposition, 乔洛斯基分解
) Q$ f2 F. i( O3 ?% m% t7 |( y. LCircle chart, 圆图
6 b( v' q; l" t, |. ]9 p: XClass interval, 组距
9 A8 X; q3 K9 z V: HClass mid-value, 组中值
- S+ X: s$ ^2 Y6 A' cClass upper limit, 组上限
5 K3 n* {) p& ], g+ h' N* O% @Classified variable, 分类变量% k9 w: V! h9 z: S
Cluster analysis, 聚类分析
; ?: |& }1 z. d# `Cluster sampling, 整群抽样
- h a( K4 @ a' i* }( y+ gCode, 代码9 c8 g8 [8 P- j* M4 Y5 o( t/ E5 a% z
Coded data, 编码数据
. M f: Q5 N' C8 w' K) N% a: WCoding, 编码: g# A$ F7 f4 r* g
Coefficient of contingency, 列联系数$ w/ T% j$ s3 x/ \8 b( ^
Coefficient of determination, 决定系数
& m7 I7 }7 J2 G! t6 X+ N5 X1 xCoefficient of multiple correlation, 多重相关系数8 ?6 Q+ _6 U. V% f' B
Coefficient of partial correlation, 偏相关系数/ c8 S* P7 u" D1 P7 z( _9 L# x
Coefficient of production-moment correlation, 积差相关系数1 G* d) ^2 s" W0 a( A: P4 a3 ~" M
Coefficient of rank correlation, 等级相关系数
: V+ U) n# D ]8 f5 zCoefficient of regression, 回归系数
9 u6 u1 L2 i% Q: F- e1 m, ?Coefficient of skewness, 偏度系数 d1 i( o& u! r# _" u* R y/ s5 \
Coefficient of variation, 变异系数: K4 r9 v2 h9 }; _* I/ H
Cohort study, 队列研究- J: W9 `) m3 y: |! S7 S. {
Column, 列
. z3 q( o& @1 C; vColumn effect, 列效应
r0 E9 b7 \( v, d7 r* k0 g2 X1 C% o8 yColumn factor, 列因素2 X3 W9 f6 j1 m' T0 s2 o
Combination pool, 合并/ j$ m+ i: @/ e6 q2 t* z
Combinative table, 组合表
1 a; ?1 ?! {9 ZCommon factor, 共性因子
0 p" E* `* a2 m h7 T I. @Common regression coefficient, 公共回归系数3 ]- C/ r2 Y. V$ @! R, x0 s
Common value, 共同值8 ~) c# ]+ e0 J2 F% J: q
Common variance, 公共方差
1 p! g5 ?7 T, E4 P, p1 ]$ t+ @# }Common variation, 公共变异% S4 u) E# d0 W* E7 v
Communality variance, 共性方差
: P3 D3 O8 O$ o. `4 n: sComparability, 可比性/ k8 x% _8 T( m+ |
Comparison of bathes, 批比较
5 h0 ]1 \5 {- P; \, s2 Z* |8 z8 SComparison value, 比较值
& M+ ]- c" j9 `& V; s+ z& Q3 yCompartment model, 分部模型9 x9 B9 w5 ^+ j, Q+ T
Compassion, 伸缩
& s) k8 D/ d3 \7 q5 QComplement of an event, 补事件
) O3 ^( J; M& {Complete association, 完全正相关
; C+ \; @4 p2 {& P- p3 f: v$ `Complete dissociation, 完全不相关
y* t6 [7 a& L) f! i* DComplete statistics, 完备统计量" P* z' o, r1 f; U4 J, q
Completely randomized design, 完全随机化设计
4 d8 c' e( b5 j/ PComposite event, 联合事件0 F: w8 j' p) l; |; W
Composite events, 复合事件# y/ r. ?: b2 c' ^/ O
Concavity, 凹性
# T' f/ Q/ B: y7 Q7 s3 |3 nConditional expectation, 条件期望1 A; Q' l8 X. ^ s& p$ o# X
Conditional likelihood, 条件似然
2 }* f3 M$ X4 i1 g5 ^: UConditional probability, 条件概率& Q7 C9 J" y* `1 W5 F% R& y4 n" }* ~
Conditionally linear, 依条件线性/ g+ J( Z: k; |4 V
Confidence interval, 置信区间
# ?9 J# a" k+ S/ \& [Confidence limit, 置信限( p" D4 ^5 z H7 u6 P
Confidence lower limit, 置信下限/ Z5 o% ?) d h$ Q6 ^2 s
Confidence upper limit, 置信上限
) @. r- ~8 X# d- _- M$ l: _Confirmatory Factor Analysis , 验证性因子分析
- i2 C$ [& J$ bConfirmatory research, 证实性实验研究
1 g7 {, R6 X! U, ^Confounding factor, 混杂因素" Q% d( V! M% R
Conjoint, 联合分析
: q- C, |2 m. I$ D# y/ f$ QConsistency, 相合性
( p- u$ z- C7 }1 g5 a$ K& ^9 |Consistency check, 一致性检验
) I; ?) n! D: q. q3 tConsistent asymptotically normal estimate, 相合渐近正态估计
: _, O/ m: I7 H3 C! n0 eConsistent estimate, 相合估计% c) t' ^& {9 z) }6 Z
Constrained nonlinear regression, 受约束非线性回归! [9 D& y: o/ D2 t5 D0 X
Constraint, 约束' ?, n6 H9 G+ f* k) f, z: F9 [
Contaminated distribution, 污染分布9 v8 X# y. G, z0 `) ]# q, t% k; g
Contaminated Gausssian, 污染高斯分布
) ]" a6 n [" Y5 X+ N4 {Contaminated normal distribution, 污染正态分布
1 ]/ h9 E* u( O0 X0 H" eContamination, 污染
: b: J6 l j& q5 G9 B. s0 tContamination model, 污染模型
3 t7 x; s9 _0 v0 q8 U/ AContingency table, 列联表9 m6 J6 @& J3 A$ \3 y& o
Contour, 边界线/ z% `( A) F; w0 q( L# [2 c
Contribution rate, 贡献率8 C& T# J- T# ~
Control, 对照% `& ]. s3 q9 X# I- a8 G1 o
Controlled experiments, 对照实验
$ p" ~4 t& E% l+ e7 zConventional depth, 常规深度- i [: L: R6 w) g9 w( l$ F# o9 X
Convolution, 卷积
+ u# W* [8 }& Y1 t/ Q2 _& C5 T) yCorrected factor, 校正因子' r" z: B( @8 T' k; r0 B) A
Corrected mean, 校正均值
7 C; f+ j0 D6 r- S2 x, iCorrection coefficient, 校正系数: u) k# J* Y, {! C' ^& Z+ p: b
Correctness, 正确性
( l/ h! [+ B3 lCorrelation coefficient, 相关系数
5 [) V' l A( z* nCorrelation index, 相关指数4 X+ k. t9 D/ O: d3 S7 t
Correspondence, 对应
. [. p: B8 a; s/ p6 B- | _Counting, 计数5 g$ l9 v) X( d @% g
Counts, 计数/频数$ c8 u# q( {; ~: d- {* G0 ^
Covariance, 协方差
8 J+ d3 T3 n' N0 K& KCovariant, 共变 ; |4 i! \ c; h% L2 e8 \
Cox Regression, Cox回归6 [' I l$ ~+ m9 y( s" W1 Z* m0 I' K
Criteria for fitting, 拟合准则4 \6 p# g+ m* |# Z2 X" Q
Criteria of least squares, 最小二乘准则
) E: N7 o4 H. |1 KCritical ratio, 临界比
6 H$ T5 F( t9 V/ P9 kCritical region, 拒绝域
. G% {( g2 p4 {$ p' O0 rCritical value, 临界值% I- l( E7 Q/ O0 M8 E6 b# E
Cross-over design, 交叉设计( v/ u5 v4 d0 C8 ~
Cross-section analysis, 横断面分析
- R$ e2 W9 F0 V, `& iCross-section survey, 横断面调查
4 ]7 h+ a( H( m& c+ bCrosstabs , 交叉表
' A. p, w5 i. I4 x4 ~$ f7 H$ x" uCross-tabulation table, 复合表
1 I" B9 L" d2 pCube root, 立方根( z/ l! _0 i: {! }5 K& m) y
Cumulative distribution function, 分布函数4 T3 E1 l6 A. m& |+ I, ~, y
Cumulative probability, 累计概率7 N$ a2 K6 `, `1 }9 H/ f
Curvature, 曲率/弯曲
7 ~" Y4 V5 S& p7 V+ BCurvature, 曲率5 v' P7 v; \/ U2 A) E' A
Curve fit , 曲线拟和 % o( \* B6 }" a- f& Y
Curve fitting, 曲线拟合( u! }3 p- f8 Z$ ]* i" Q9 V
Curvilinear regression, 曲线回归1 I( }9 |5 O0 d) p1 z
Curvilinear relation, 曲线关系
/ T& q, ]1 W3 p! M6 }Cut-and-try method, 尝试法6 D( v$ a9 ?; i) L
Cycle, 周期
( H2 |3 | t) u$ N' [/ HCyclist, 周期性, [& N" ~6 B' G/ v" k
D test, D检验
! Z g4 G2 N3 r. k8 S0 ]) Z% ^Data acquisition, 资料收集
7 S r! Q: q* G+ U; m" M7 x! ]Data bank, 数据库1 t4 k( m# o9 G8 h1 C, j0 ?3 X8 [
Data capacity, 数据容量9 r0 B- i8 s$ o, H3 J
Data deficiencies, 数据缺乏
" d- H& X) u" k' BData handling, 数据处理& \) E9 Q* {# Z; h
Data manipulation, 数据处理$ ?, v. F4 q5 X! o1 O
Data processing, 数据处理, }8 |' }% O3 N# M" U0 W
Data reduction, 数据缩减
* v. m: s0 p4 |/ F+ y; XData set, 数据集1 {0 V, y9 X" o
Data sources, 数据来源
7 `+ z' y1 e/ ]- j+ TData transformation, 数据变换
! e+ t4 z' p- A- ]9 K# ?) QData validity, 数据有效性( M# K" P( }: A0 C9 m. [& h
Data-in, 数据输入/ q7 f4 n: Y9 G4 K1 W- C
Data-out, 数据输出/ W. `# j5 a) f5 K1 _/ N9 g
Dead time, 停滞期# M; p0 _) g/ x2 ] T
Degree of freedom, 自由度/ ]8 j! s" z5 J8 x
Degree of precision, 精密度' e6 |( N5 \. v, r+ Z+ m# ]
Degree of reliability, 可靠性程度% p6 R7 E0 g6 [, j+ A4 |9 K( L0 H
Degression, 递减
! U3 p3 @5 w7 yDensity function, 密度函数9 A. y. U, D2 Q' I" X$ m; F" l
Density of data points, 数据点的密度
% g9 n6 I2 g- o6 g S4 B4 ] QDependent variable, 应变量/依变量/因变量
* S% D: X3 c ~, s* D! rDependent variable, 因变量
+ i, j1 m! V1 b, ^Depth, 深度
7 }9 C& N( ^+ G7 s2 DDerivative matrix, 导数矩阵
1 r5 M% T, t: N- \. o4 x5 rDerivative-free methods, 无导数方法9 a* k5 B2 }* c+ @$ ^& E: i$ S. e
Design, 设计
5 c. z8 I7 ^) G) Z8 M9 a$ FDeterminacy, 确定性
$ }& p/ ~5 h$ K1 P) gDeterminant, 行列式
% j; X& d# j: I4 B4 v; c8 CDeterminant, 决定因素
. S+ f0 |5 K& ~" bDeviation, 离差
+ v1 h6 I! M ^ A$ f7 oDeviation from average, 离均差0 i( T. G+ b5 u# A7 l3 Y
Diagnostic plot, 诊断图: }3 }# b% J) X6 z- M3 `
Dichotomous variable, 二分变量
6 Q+ o0 W- Z; T) rDifferential equation, 微分方程
4 c+ q' U2 Y5 e2 G4 Q* h$ x8 f8 J6 CDirect standardization, 直接标准化法
0 O) u, E( c f' I6 {1 E% q3 Y6 N QDiscrete variable, 离散型变量; M# e0 y% l6 D; z
DISCRIMINANT, 判断
# ^3 O( s2 W. R1 X: d5 k5 v( pDiscriminant analysis, 判别分析
' V$ d/ _+ p$ ^) b, E$ dDiscriminant coefficient, 判别系数" v* X2 p7 w; X8 L3 ~* C* u
Discriminant function, 判别值* S: S8 ]. M7 d3 g
Dispersion, 散布/分散度
. J( A, M K+ M6 ?7 d3 W- vDisproportional, 不成比例的
* v7 L; ?7 X& J9 N8 O' cDisproportionate sub-class numbers, 不成比例次级组含量9 f1 F& M3 C; K6 w/ o5 \
Distribution free, 分布无关性/免分布
' {: Q! z7 V1 c& M/ }3 M- |Distribution shape, 分布形状
: e1 l% r+ }, ~* l/ kDistribution-free method, 任意分布法, t% t8 `- c7 Y, i
Distributive laws, 分配律
# o3 P" p. z; a' v9 E0 W9 aDisturbance, 随机扰动项% @0 [3 y% K! w( {3 u
Dose response curve, 剂量反应曲线; t. B' e# N3 T! n; T8 D4 Z1 p
Double blind method, 双盲法! Z& b/ D R- n B {
Double blind trial, 双盲试验- i; W: Q, z8 l8 l
Double exponential distribution, 双指数分布
+ z6 `: P- {5 i( c. ~, d0 uDouble logarithmic, 双对数
: j- o, S0 @( Z+ w, sDownward rank, 降秩1 O4 [5 b: Q+ m$ C
Dual-space plot, 对偶空间图
; \2 P- P# g' Z% W. [DUD, 无导数方法
) ]- ^/ A" h7 V7 a1 _4 `Duncan's new multiple range method, 新复极差法/Duncan新法! _$ f8 T6 t! O& n* m4 h
Effect, 实验效应
) u8 j* q; y( O& j: S; UEigenvalue, 特征值# B' J/ C$ j2 F b& U
Eigenvector, 特征向量
+ Q; l0 @, H8 w, G6 n, q& rEllipse, 椭圆, q% \4 r( o- ?; w7 u6 A
Empirical distribution, 经验分布0 G/ J- |* x, C5 l3 P B( B$ t
Empirical probability, 经验概率单位
& t' B1 J3 B/ G# ]+ @7 [Enumeration data, 计数资料
1 I5 {+ s |: g UEqual sun-class number, 相等次级组含量" a& C5 V6 x+ _% n, P
Equally likely, 等可能
; i' t2 U& Q. _6 wEquivariance, 同变性/ ?0 G) W- ~7 P7 l. D/ D' J3 } {, w
Error, 误差/错误' G2 D" ^7 q% j8 e ^; `
Error of estimate, 估计误差% v1 x: `0 }" }) M+ c7 \
Error type I, 第一类错误
* C' ?& `1 B, S2 J4 FError type II, 第二类错误
4 P" d! p X" PEstimand, 被估量
( X/ A% E H* q7 G, LEstimated error mean squares, 估计误差均方6 p# { J" M* H. c+ {% W
Estimated error sum of squares, 估计误差平方和
# ~; S$ ~# X, w& D6 U5 Z) G7 ^" nEuclidean distance, 欧式距离. T+ U/ N+ m7 S
Event, 事件9 b% _0 R9 F" h- F3 f7 }
Event, 事件; o( w M8 O) x$ m4 J# V
Exceptional data point, 异常数据点
/ v1 C1 |% A& O8 {! QExpectation plane, 期望平面5 P; }& W# x7 [6 z) S. t
Expectation surface, 期望曲面
* @8 m( p$ W* J# F5 a" QExpected values, 期望值# V3 |5 j+ A. I, L1 v/ `, K4 s
Experiment, 实验- n" n3 j/ m; w$ a6 _, j
Experimental sampling, 试验抽样# s& d( _+ l z- s2 p
Experimental unit, 试验单位
V$ ^0 M& u8 U5 f" v+ t0 TExplanatory variable, 说明变量
/ l* I9 p& e! ^1 L9 SExploratory data analysis, 探索性数据分析1 G- b; k8 D' g: X/ E
Explore Summarize, 探索-摘要
/ E7 |- m \- b4 EExponential curve, 指数曲线/ r- _2 I6 l/ Q! c# x/ [5 T6 }& a
Exponential growth, 指数式增长
7 Z1 Q1 I% p) I! i4 q. e3 v/ nEXSMOOTH, 指数平滑方法
. A0 V0 N3 i: TExtended fit, 扩充拟合
1 y5 j" V: q1 ~6 QExtra parameter, 附加参数# U( r5 q" ~9 h1 I; A$ P
Extrapolation, 外推法- T3 W, \6 R( m* v- q6 U, L6 }* L
Extreme observation, 末端观测值
0 ^5 c1 i. Y9 x2 QExtremes, 极端值/极值
% d; M, }& a; j2 f1 }+ YF distribution, F分布
- J5 R' k/ n$ t0 G2 M! E! _F test, F检验
& l. g' v- A# B& R/ }Factor, 因素/因子 ~1 k- X) k P5 d O
Factor analysis, 因子分析
7 C8 e+ i, A+ r, w! m: F& ]9 [Factor Analysis, 因子分析
6 K- b) E! f/ L9 A5 r( O0 W9 W2 nFactor score, 因子得分 3 M. Z% J( N0 L
Factorial, 阶乘4 y7 Z+ O" N W/ W3 V7 g5 w& J
Factorial design, 析因试验设计
1 v2 ^) R$ D4 rFalse negative, 假阴性3 Z/ _$ v2 S5 ^ [% X9 P
False negative error, 假阴性错误
7 |6 ~6 Q2 T6 G3 |7 }Family of distributions, 分布族
1 s# W/ M; l3 I- ]3 r# }8 MFamily of estimators, 估计量族
- k/ P. _6 z! [8 X9 @Fanning, 扇面2 G0 m) y" ?+ t$ V1 M9 T5 X
Fatality rate, 病死率/ J; I5 W- s4 c+ S# i v
Field investigation, 现场调查' }. g% H( c, M/ Q5 E& r
Field survey, 现场调查
# K o/ c1 |* C2 Y) O9 U3 |Finite population, 有限总体+ ?; a" G( f/ g% t% T; [) ~" h
Finite-sample, 有限样本
3 ^- r' F" O" A( AFirst derivative, 一阶导数5 c- s4 D( p" q/ K
First principal component, 第一主成分. ^6 ]6 B1 b( b4 @" j7 l$ h' ?
First quartile, 第一四分位数
- Q. l* L' ^% N0 m: sFisher information, 费雪信息量8 ^$ w2 W7 k8 i& |. i: {2 K. ]( X+ o
Fitted value, 拟合值
1 k3 w7 r& b# iFitting a curve, 曲线拟合
, s- T9 J' J' mFixed base, 定基
0 u! I$ |* ^2 t+ l4 {* A" |. i+ UFluctuation, 随机起伏
) o1 C X' k) ^( KForecast, 预测+ h0 r; |& Z6 m* ^5 K
Four fold table, 四格表/ {) p; T& D9 }& A( O
Fourth, 四分点# K& m+ x2 r" d: ]2 [' }, O7 g
Fraction blow, 左侧比率: E5 r6 h5 w* L I7 A
Fractional error, 相对误差" e& S5 G1 k0 e7 O
Frequency, 频率
" l/ [$ C) N9 k3 kFrequency polygon, 频数多边图
0 `: Q- ?# Z$ P4 H! y' B4 n+ j6 }) wFrontier point, 界限点
/ x; @- b3 e. ?% W% RFunction relationship, 泛函关系4 M* J( P. b+ u! _" a3 V
Gamma distribution, 伽玛分布( @# A; Q2 G( Q3 o
Gauss increment, 高斯增量( C. Z3 C8 q; L( E# V% {$ w( U# s
Gaussian distribution, 高斯分布/正态分布
7 T5 T7 @" x" C% ~. L) A2 c# pGauss-Newton increment, 高斯-牛顿增量
0 K3 j! U' W; r5 [General census, 全面普查
" N& [$ N8 Y' r+ S6 oGENLOG (Generalized liner models), 广义线性模型
4 {0 z" S: R6 ^+ YGeometric mean, 几何平均数/ j& I, v# ]5 M+ O& o
Gini's mean difference, 基尼均差: G" ~9 ]5 F3 X! Y3 t
GLM (General liner models), 一般线性模型 - s) I4 X; w9 V% I" B
Goodness of fit, 拟和优度/配合度& W: T5 Y& w; c( x6 _
Gradient of determinant, 行列式的梯度7 {! h& ?: i4 P, e) A, p
Graeco-Latin square, 希腊拉丁方
/ T9 ?0 J1 E% ~7 I& B5 mGrand mean, 总均值
; _ _9 ?2 D0 u# D4 M2 w- KGross errors, 重大错误+ R' v* d) B0 @
Gross-error sensitivity, 大错敏感度
" ]8 v% m- w! HGroup averages, 分组平均
7 D& @. y7 m- u8 c+ w1 B8 HGrouped data, 分组资料4 z+ Z# v' _1 H/ v' Q: {1 T! J
Guessed mean, 假定平均数
3 {# Y7 z* W% hHalf-life, 半衰期4 k4 |1 g a$ E* [- b P
Hampel M-estimators, 汉佩尔M估计量* x' q* V1 Y2 I
Happenstance, 偶然事件" Z: n" O G2 o! i
Harmonic mean, 调和均数) B& S, R& l [6 I. Z! @9 Z
Hazard function, 风险均数2 j( k# Q4 l ~7 x2 ]2 C$ M9 g5 Q/ |% g
Hazard rate, 风险率% J) [, |) I) c: j3 \: @
Heading, 标目 3 t* |3 |- m W. J6 |
Heavy-tailed distribution, 重尾分布
# s/ w2 b! p0 D: RHessian array, 海森立体阵
3 J, w; K* ^# y- W+ q. R' h) n: UHeterogeneity, 不同质
/ y. D% _, l5 g, [) C' w. yHeterogeneity of variance, 方差不齐
6 r6 L( B$ t T4 e' d3 MHierarchical classification, 组内分组5 x. x% B, ~7 d0 w3 |3 J) Z! U5 Z
Hierarchical clustering method, 系统聚类法( z- l1 I- Y. a7 {; D1 H3 B, A
High-leverage point, 高杠杆率点
; H. a% c# K2 E4 } k5 l7 ~HILOGLINEAR, 多维列联表的层次对数线性模型9 q8 g, H, Q1 D0 L
Hinge, 折叶点
# M6 I3 w/ o$ g' E: s5 OHistogram, 直方图
+ _, R; s3 h! z5 t, L: G/ D. aHistorical cohort study, 历史性队列研究 / \9 O, t8 Q$ w, a' A0 V6 q
Holes, 空洞/ ^/ ?0 }5 X" N$ @( w. \3 P
HOMALS, 多重响应分析
* C0 K' g9 t8 f& z2 k5 N# v# v( CHomogeneity of variance, 方差齐性
0 g/ M' w( Y$ J5 i o4 {Homogeneity test, 齐性检验
; a& H+ K& k, V, ?Huber M-estimators, 休伯M估计量
6 o8 E& E: U3 }- e; r1 E2 \Hyperbola, 双曲线
4 V1 J/ ?( ~4 ?: ?5 a0 t5 \Hypothesis testing, 假设检验
# a; @: |6 ^/ {1 z6 X4 ZHypothetical universe, 假设总体
, h% m* R5 X$ o+ A+ mImpossible event, 不可能事件2 i, e5 j$ p/ l
Independence, 独立性
6 {6 \- ~" a- d/ @! @ p2 f% JIndependent variable, 自变量% u( l9 l( g4 n' W
Index, 指标/指数
2 C- Z/ ], S/ w' KIndirect standardization, 间接标准化法
* M$ `# i1 D# r3 O5 @/ yIndividual, 个体1 K- k+ Z8 C$ F5 s
Inference band, 推断带, O/ ^, p( g' |% L/ _
Infinite population, 无限总体, p1 j' t; {: O; c e2 r
Infinitely great, 无穷大$ e9 q2 F4 `; [# S; D
Infinitely small, 无穷小% a- D2 H: R" E$ r5 b& M& [3 G
Influence curve, 影响曲线3 q, K" f( k- e ~
Information capacity, 信息容量
( x: C) \6 x/ Z! DInitial condition, 初始条件
7 _6 @6 i! s7 Y( cInitial estimate, 初始估计值
, H0 f a7 P9 e- k" lInitial level, 最初水平
# E' r. X* f3 K: b$ PInteraction, 交互作用* G! z$ F5 R# g3 k; {( W; T
Interaction terms, 交互作用项
) @) H. T1 L; FIntercept, 截距
9 [7 u$ G! G1 P& a3 E5 NInterpolation, 内插法. I/ l4 p! a* _7 o2 V/ B$ z( X( q# Q
Interquartile range, 四分位距% k. X, ^+ ~& J1 u+ k
Interval estimation, 区间估计, `7 P& d$ Q" T0 [; D0 E: e
Intervals of equal probability, 等概率区间
( O3 L& \: F3 H+ f: dIntrinsic curvature, 固有曲率. |4 s" g3 }4 L8 R& j3 H3 k& A
Invariance, 不变性4 Y( g) c! f( M2 X9 \
Inverse matrix, 逆矩阵
! L0 Q! ^8 q0 ~, s. _7 LInverse probability, 逆概率
* p+ p1 J8 G- x5 k, @. J1 ZInverse sine transformation, 反正弦变换+ }0 r/ u4 g. F5 c
Iteration, 迭代
, r6 B6 P* S! P! C& ]2 V) ^Jacobian determinant, 雅可比行列式
, a$ Y1 B4 G, m$ MJoint distribution function, 分布函数/ `" p1 |3 ~. z
Joint probability, 联合概率( W. {( U$ I1 ~' c8 y6 x. Q2 t2 w
Joint probability distribution, 联合概率分布
7 j1 e0 C C3 Y0 \ BK means method, 逐步聚类法
+ y2 A( P5 M! j: e I7 gKaplan-Meier, 评估事件的时间长度
) I- M4 V& u3 {6 z% t, _" ^Kaplan-Merier chart, Kaplan-Merier图+ n1 c6 P3 k8 {
Kendall's rank correlation, Kendall等级相关; e/ Q* v' v% s& ]0 D
Kinetic, 动力学% o$ j9 R; Q4 e5 B
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
; z, C6 O* O# a' P4 eKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验( }3 p2 v5 @9 r. x$ }* [) ]
Kurtosis, 峰度( K0 {# I+ U) `
Lack of fit, 失拟
7 u( I0 d/ U2 L2 f8 DLadder of powers, 幂阶梯: R( J* s- Y& \# X) E+ F
Lag, 滞后
; F: t1 x+ g- m2 M! x! A3 k9 NLarge sample, 大样本
* b, C2 y8 n9 c x: u6 c2 w% I( y+ fLarge sample test, 大样本检验
e) [+ `" ?1 t1 u* A. {Latin square, 拉丁方# O5 h/ c$ i& @2 T
Latin square design, 拉丁方设计- n, ~1 \% \7 a8 w5 G9 e" y/ e
Leakage, 泄漏
" ]# W& X4 [9 n" E; lLeast favorable configuration, 最不利构形. n2 }+ ?5 k8 y& ?, e
Least favorable distribution, 最不利分布
/ T) a9 {4 I% c# Y2 Q$ V' CLeast significant difference, 最小显著差法9 O8 w% h5 m# m8 I& R7 S& n
Least square method, 最小二乘法
( b+ G( D1 B! CLeast-absolute-residuals estimates, 最小绝对残差估计/ ]7 @3 b8 f3 L. W% p0 {% r
Least-absolute-residuals fit, 最小绝对残差拟合
9 `3 W' k) }) b2 L1 Q1 XLeast-absolute-residuals line, 最小绝对残差线
3 q% O( a( N% S+ ~Legend, 图例
3 t" J! T$ U& e0 g: xL-estimator, L估计量$ w0 Q9 \* {9 b; }/ k
L-estimator of location, 位置L估计量
9 ^# K- L& i1 `L-estimator of scale, 尺度L估计量
( a* D1 l7 k+ \Level, 水平
8 B" f3 U) k; XLife expectance, 预期期望寿命
2 G0 C. O' G6 ]. Q* {" R* O TLife table, 寿命表
7 o( H$ @' k$ q- X) }Life table method, 生命表法
# i. E1 X# ~% U6 R* vLight-tailed distribution, 轻尾分布
' ^8 c3 K* b; r5 L. E |; ]1 wLikelihood function, 似然函数
& A& n% h7 E ` o3 @Likelihood ratio, 似然比
3 u- [1 B. d' f# fline graph, 线图4 c9 [7 Z0 x4 O) `
Linear correlation, 直线相关
, c0 @, l4 p, c. d$ o5 F. m( FLinear equation, 线性方程
2 ~0 N# @5 T/ WLinear programming, 线性规划 P1 W; G. f8 s: j% x
Linear regression, 直线回归$ H+ H4 `) ~6 Q- q9 ]6 X- F; i
Linear Regression, 线性回归; X. R( \* W0 r% X5 _) P
Linear trend, 线性趋势
1 P& y7 u$ \- j) _" rLoading, 载荷 8 d. p- w6 e) n/ F6 w* y: [
Location and scale equivariance, 位置尺度同变性
7 p' C( S) q _! Q8 w: j$ B3 lLocation equivariance, 位置同变性9 h" P6 l7 w9 j$ e7 l. g1 t; {% r
Location invariance, 位置不变性0 x/ o+ I5 `* D1 i
Location scale family, 位置尺度族
/ Z5 T8 Z A# X0 k2 fLog rank test, 时序检验
: N0 T. g/ `( O( I% nLogarithmic curve, 对数曲线- ]' v9 r7 d6 t6 [
Logarithmic normal distribution, 对数正态分布7 }5 Y/ y) V0 N+ P% k, a
Logarithmic scale, 对数尺度
# \( V; S9 J: _# _$ Y. k8 Q7 O: ?' kLogarithmic transformation, 对数变换
) q/ J/ n) d* P* X9 ^8 }/ x: w6 xLogic check, 逻辑检查
& p2 z5 o+ [( D4 }( l4 t' K2 cLogistic distribution, 逻辑斯特分布
, J$ t5 L4 Q7 t! kLogit transformation, Logit转换6 H0 w5 W/ I* H7 k
LOGLINEAR, 多维列联表通用模型 6 e5 p D9 Z7 Z/ r# F
Lognormal distribution, 对数正态分布, Q" d! S+ ^. a
Lost function, 损失函数: X$ O- p/ C& M% }% A. F/ s( I
Low correlation, 低度相关
) i+ S3 K# m+ u b* TLower limit, 下限
# _- M8 H' C8 g, }! M" G: ILowest-attained variance, 最小可达方差
* O: f: q7 [7 V2 mLSD, 最小显著差法的简称1 p) C' a0 k2 O6 b0 u
Lurking variable, 潜在变量
7 r& E5 d; O; g. `$ D8 |- zMain effect, 主效应. l5 F; n1 X' V* m: }
Major heading, 主辞标目
$ l8 B5 g5 X0 s" O3 O$ e' Y# ^Marginal density function, 边缘密度函数
0 h' z8 \7 ~. Z9 ?9 _4 K, M7 }Marginal probability, 边缘概率
$ j; J- q- l+ Y! R' tMarginal probability distribution, 边缘概率分布
) E% b8 i8 n. b# rMatched data, 配对资料) j* H9 {0 v, Y% C/ w; t
Matched distribution, 匹配过分布& C5 v! I9 _ G8 f
Matching of distribution, 分布的匹配! _' H, B! ^2 |, K- R9 c
Matching of transformation, 变换的匹配" W8 }# b' L3 {
Mathematical expectation, 数学期望
7 N. N0 {: f% W" w4 ?4 _& jMathematical model, 数学模型6 O* d: W0 k5 {1 K% A& i
Maximum L-estimator, 极大极小L 估计量
( L3 J: i- q) ^+ f6 x; YMaximum likelihood method, 最大似然法
" t( ?# r0 T6 A& b. YMean, 均数
& V) M( U1 g- j" k: w$ a9 mMean squares between groups, 组间均方
0 Y0 i. o) _* C: r8 g/ C/ |Mean squares within group, 组内均方
' q- z$ _+ l6 _- K; m" RMeans (Compare means), 均值-均值比较
/ @# t" z5 c3 u c$ C- M/ {Median, 中位数
$ G6 L/ r1 i$ S6 LMedian effective dose, 半数效量5 Y* {" z! d- K ?2 [
Median lethal dose, 半数致死量; L7 e: Y' a4 m, Q; u6 S( D6 v i; p
Median polish, 中位数平滑
3 b3 `0 z0 v, @* z" Q2 OMedian test, 中位数检验/ J6 _" Z/ y' j9 T* L
Minimal sufficient statistic, 最小充分统计量
8 L }9 T9 f, D4 qMinimum distance estimation, 最小距离估计
( K# ]+ M8 u8 {8 g, b1 AMinimum effective dose, 最小有效量: o0 A7 m8 I: g: ~: \
Minimum lethal dose, 最小致死量
6 r4 q) I3 R: E- @" n9 HMinimum variance estimator, 最小方差估计量" P3 i* f2 m- w" T* {' G
MINITAB, 统计软件包+ ?9 K! R0 T/ @4 f: x8 G+ L
Minor heading, 宾词标目1 H+ U7 D' E! }* B- W) [2 |
Missing data, 缺失值
7 x- X) j2 i& c% YModel specification, 模型的确定
4 r+ R/ X' v. V% x( NModeling Statistics , 模型统计9 W4 W' O8 u2 T) }! A$ b
Models for outliers, 离群值模型! _& D. Z; n! E( f
Modifying the model, 模型的修正% C! [" V+ M" x
Modulus of continuity, 连续性模 [; u) e6 U1 q9 K9 d: d: {( _
Morbidity, 发病率 6 V1 R Q2 s- k" ^
Most favorable configuration, 最有利构形3 K q9 ^, J4 v: ]
Multidimensional Scaling (ASCAL), 多维尺度/多维标度8 h1 b0 w ~" s% J
Multinomial Logistic Regression , 多项逻辑斯蒂回归0 }9 m" ^% \, M4 Y' {/ @( @% o
Multiple comparison, 多重比较; Q0 n/ G8 A f* k
Multiple correlation , 复相关) { X) D- @7 X5 }# r: c7 i+ C
Multiple covariance, 多元协方差
9 `/ l. o4 I6 ^# wMultiple linear regression, 多元线性回归
7 N9 A# T4 Z1 ~) z7 U' sMultiple response , 多重选项
2 Y3 t# l; J/ w" P& e1 R2 h+ _; c1 ZMultiple solutions, 多解
7 q6 r) G: z- \ vMultiplication theorem, 乘法定理7 k4 l& v: |3 z6 C( y
Multiresponse, 多元响应
) V* J9 U- ]5 D) S* {Multi-stage sampling, 多阶段抽样' t8 U& _: Y5 z8 q) D
Multivariate T distribution, 多元T分布5 a; T* Z; O4 b% w1 t
Mutual exclusive, 互不相容" ^& V+ T7 f% `$ O) k
Mutual independence, 互相独立. a# s( C0 R& {" X" [& N" M
Natural boundary, 自然边界
$ x* S, j [* R4 b) FNatural dead, 自然死亡7 [5 L7 M7 _: o$ P' f& a
Natural zero, 自然零3 h/ v8 g, x+ N9 r5 ?0 P* c
Negative correlation, 负相关
; {" J; V" [. |# oNegative linear correlation, 负线性相关4 M: m- B8 K: W L
Negatively skewed, 负偏
8 y( ~/ Y8 L( x7 e: r9 f# i! j8 iNewman-Keuls method, q检验6 S, U O! Z+ s2 i% {8 d
NK method, q检验
! ~7 s3 s: c; h& O2 K, fNo statistical significance, 无统计意义
* a; P# u' Q2 j( _0 S: ~0 K7 UNominal variable, 名义变量' r1 e0 ~' V" Q* D& r4 N
Nonconstancy of variability, 变异的非定常性1 B: U' u2 N6 G" F5 F! _3 A/ Z% Q
Nonlinear regression, 非线性相关& _, g, _( k S8 Q
Nonparametric statistics, 非参数统计
! E1 U+ T2 Z5 H$ O. f j ~0 h- |Nonparametric test, 非参数检验
6 F; B, Z* M/ ^3 H. t& mNonparametric tests, 非参数检验9 \7 | Z+ E1 ^/ J( E$ X9 M2 d
Normal deviate, 正态离差; C) R/ s9 S# b
Normal distribution, 正态分布# c/ \7 i. n; P+ b* y9 _8 q
Normal equation, 正规方程组: J( o" v) S% _3 `+ D+ j' g3 A/ L
Normal ranges, 正常范围" C7 t- S; y8 G' X- G
Normal value, 正常值% i5 ?9 u0 }, n' X& D+ x) h0 r2 {3 ]
Nuisance parameter, 多余参数/讨厌参数
* u% }- m5 K1 H9 R+ ]Null hypothesis, 无效假设
' @) j3 N8 {6 [) _3 eNumerical variable, 数值变量
) s5 ]3 [4 k* Z" v7 c5 x- ]Objective function, 目标函数, O$ i' m2 }" t8 m
Observation unit, 观察单位
; p2 M+ r% Z6 Q3 XObserved value, 观察值3 L3 s1 I7 ^' [
One sided test, 单侧检验
( n5 @8 k9 z& x% q; F3 B8 S6 s; DOne-way analysis of variance, 单因素方差分析
6 x5 C" S" f6 rOneway ANOVA , 单因素方差分析
$ Y' H1 ~ }! R" F( c( Y* M& bOpen sequential trial, 开放型序贯设计$ V) P% B h g# D' o3 m
Optrim, 优切尾
; K) E! Y! K9 A; KOptrim efficiency, 优切尾效率. E+ d) d- `# d5 f f: h9 w
Order statistics, 顺序统计量
+ f$ s1 ?' T! y6 p4 \Ordered categories, 有序分类
E1 Y& a# c# Q8 v3 h% {- f9 m/ g' SOrdinal logistic regression , 序数逻辑斯蒂回归
' I6 h" u7 ]$ f S7 E- X7 L6 d( eOrdinal variable, 有序变量6 x) D7 h, i! b0 D7 S7 B( y
Orthogonal basis, 正交基
3 M$ ?5 I# u5 s0 yOrthogonal design, 正交试验设计
, g& F! H0 w# v3 pOrthogonality conditions, 正交条件! i/ ^, \3 M; D4 s3 v6 a
ORTHOPLAN, 正交设计
2 y( q) w, F, H) R8 Z+ f) Z6 aOutlier cutoffs, 离群值截断点6 _& h1 D. b. k+ R9 E5 C
Outliers, 极端值
0 ^6 M k, U& l7 w+ E$ l5 yOVERALS , 多组变量的非线性正规相关
+ z2 {9 {0 V4 G* \Overshoot, 迭代过度! x* s" l( h8 d. @" {! K
Paired design, 配对设计
3 Q; I2 R, I5 A5 ]# {' [2 [4 b! ZPaired sample, 配对样本
! n$ _; e2 g6 _/ r1 g! U }+ zPairwise slopes, 成对斜率6 m7 ~. x) a0 f1 T- P
Parabola, 抛物线
) a$ b2 a5 f: |9 y$ `Parallel tests, 平行试验* H. J8 T" N# u6 `1 z, k* M( M" `
Parameter, 参数
7 T7 X6 }, a5 H) Z5 O% V# oParametric statistics, 参数统计
, o, z7 K& `# t: K5 BParametric test, 参数检验8 v) L2 y6 P8 L" a2 V! i: I5 J
Partial correlation, 偏相关2 a+ P3 d( n; E/ s
Partial regression, 偏回归
' E5 x! p2 m0 l' Y9 v) b6 M. TPartial sorting, 偏排序$ e+ V+ q3 b' T. z: @% O
Partials residuals, 偏残差* b$ \. m l& g
Pattern, 模式! n2 b1 s7 k4 \9 h3 L; f* ?" Q) Z
Pearson curves, 皮尔逊曲线5 X W% i6 b7 Z1 H# p4 ^4 w
Peeling, 退层
+ \( ~6 n2 H: _7 w. V! @Percent bar graph, 百分条形图
' s/ \( W$ Z& Y5 D" ?% _9 B8 u+ \Percentage, 百分比1 Q" z3 M; D4 m& W8 |/ Q
Percentile, 百分位数7 \8 E$ `& M+ g5 p$ d& \
Percentile curves, 百分位曲线: Z, ` S4 r4 j- G% R
Periodicity, 周期性
' M5 Q$ `# w) d- G: O0 I) XPermutation, 排列
7 z7 z1 f. f1 V* {P-estimator, P估计量
) q) b6 }$ t0 F8 s) r) n% T: JPie graph, 饼图
' C: E% L8 H8 K, r% V QPitman estimator, 皮特曼估计量1 R, g' f) `9 _
Pivot, 枢轴量
# f- z9 P* I3 n8 Z1 l" hPlanar, 平坦1 E. A0 \& B5 m$ d; G/ N# P: F* x
Planar assumption, 平面的假设* I9 D5 J4 {: X; y6 Z
PLANCARDS, 生成试验的计划卡4 b" O. J0 j! K/ |' o8 m) x9 X
Point estimation, 点估计% J/ {# h5 H3 Q
Poisson distribution, 泊松分布0 s3 w) A0 `# z+ H# o
Polishing, 平滑; }! c; K4 x& m7 A( j0 }
Polled standard deviation, 合并标准差3 p9 i1 U! i0 l
Polled variance, 合并方差
$ C! d2 ?" R/ C+ [. [7 |# uPolygon, 多边图
6 r; z* A# g( i" m( b4 {, w! Y) V# h: lPolynomial, 多项式
' O' x) b- r: d3 ~; U8 a, c0 _6 nPolynomial curve, 多项式曲线# t# e. p: E$ L. t9 m
Population, 总体0 e/ ?+ d) m! p
Population attributable risk, 人群归因危险度
4 l; H8 {: k8 O/ U0 pPositive correlation, 正相关
. f: \8 E X! o H' f9 dPositively skewed, 正偏
. {" X% J6 B1 K4 kPosterior distribution, 后验分布3 |% ]& I0 Q2 A0 U
Power of a test, 检验效能
, m2 p# E: r: A T+ l' O) P1 IPrecision, 精密度
6 k' J" N& u; u! UPredicted value, 预测值
0 ]. y* v* w5 Q( zPreliminary analysis, 预备性分析
" k1 X* B8 N s NPrincipal component analysis, 主成分分析4 J: j" k) \3 O6 v) _' q8 a
Prior distribution, 先验分布: W! s1 {# b* n" |0 j
Prior probability, 先验概率4 y. S U: `( U+ S
Probabilistic model, 概率模型% q7 B( g0 k7 _
probability, 概率* e8 }6 h3 Z+ J" f
Probability density, 概率密度
2 v1 |3 o. J5 X* B% J* p7 Z5 YProduct moment, 乘积矩/协方差
: W- \& n: ^# ], }Profile trace, 截面迹图
, o/ X7 s1 K0 G" X1 P8 dProportion, 比/构成比 W$ I" \+ c2 A5 l3 u9 y
Proportion allocation in stratified random sampling, 按比例分层随机抽样0 `& w+ ?! N, P. K& q. G
Proportionate, 成比例6 o- y) P) B0 X
Proportionate sub-class numbers, 成比例次级组含量: k' l# @9 x. E2 [8 p
Prospective study, 前瞻性调查, W; P& n r- `6 `, ~9 L9 Q; F* u
Proximities, 亲近性
: I0 {% b+ X7 s8 {( rPseudo F test, 近似F检验' ^) `* V( l' @7 b$ J
Pseudo model, 近似模型
7 I, d7 h3 y4 X! k; SPseudosigma, 伪标准差
$ a" f8 p' ?; mPurposive sampling, 有目的抽样
: p! s6 z. P, {6 CQR decomposition, QR分解
5 Q# X2 Q( E& ?- H+ aQuadratic approximation, 二次近似0 S2 C+ F9 s% y( M" E% x
Qualitative classification, 属性分类
3 I& o! y( v2 s0 i) M1 y. y+ B/ YQualitative method, 定性方法8 f0 |* F0 ]1 d( W7 C. d0 r: o, e
Quantile-quantile plot, 分位数-分位数图/Q-Q图, S. L& U8 u8 e
Quantitative analysis, 定量分析
# n9 e" g( v$ ~: eQuartile, 四分位数0 _! N5 I! x3 `; a
Quick Cluster, 快速聚类
3 Z* g$ h; \, q1 E# ORadix sort, 基数排序
+ \* e; o$ U# I+ O( M9 ]' h& ]Random allocation, 随机化分组- C( Y& @7 c B+ \
Random blocks design, 随机区组设计
8 n% `) A0 }. j/ ~7 CRandom event, 随机事件6 C5 U. w/ \) ~) T) w8 A3 n6 F
Randomization, 随机化
* b# n' D( s4 c2 f3 P( f" nRange, 极差/全距
i1 X" h& M$ f G) c+ ?Rank correlation, 等级相关
7 s! a; @6 U4 T( _7 M$ pRank sum test, 秩和检验
( s2 L( [1 K' i$ VRank test, 秩检验. q( x- p" g/ _
Ranked data, 等级资料% ] Z7 ?1 n. W: C* y! r
Rate, 比率 y3 Z0 R/ J9 m+ ^1 ?3 e* {& k
Ratio, 比例
6 \, n) \4 x6 i! A% Q1 s3 IRaw data, 原始资料- a( J# S4 a% z7 Q
Raw residual, 原始残差
6 M( ^7 h6 ~* @- E% {1 fRayleigh's test, 雷氏检验
: }! s* m' q6 o5 I8 K9 ?' ERayleigh's Z, 雷氏Z值
( F0 ?! ^: m3 T- y7 K8 c+ B7 l0 hReciprocal, 倒数+ y! }5 T+ a# A1 a; Y
Reciprocal transformation, 倒数变换5 _6 b3 U. U& B2 a
Recording, 记录
0 [0 s/ f" C9 I3 S0 X8 N+ a7 [Redescending estimators, 回降估计量
+ K2 }# ~; m1 {3 K; H& H& ZReducing dimensions, 降维% ~+ _% F) v/ a, Q( k
Re-expression, 重新表达# c" X# g z( |+ ]$ \/ [+ S
Reference set, 标准组( E- A' J1 U; _8 Z
Region of acceptance, 接受域
7 W4 K1 l1 ^6 ?+ qRegression coefficient, 回归系数
2 b( s! A( p2 N* E) h, s. iRegression sum of square, 回归平方和
; J; j$ S: ~+ n& E8 ^Rejection point, 拒绝点0 r3 B% ?$ m( |
Relative dispersion, 相对离散度
5 O9 z: J' N( j2 q1 T! ]& _3 j- m6 SRelative number, 相对数3 B' D6 Q$ k, S
Reliability, 可靠性
; E! V$ ^/ Q0 k" P* F+ l& bReparametrization, 重新设置参数, k" Q: x* _/ l. U Q
Replication, 重复5 F8 M2 `- o- k/ c* V a/ B
Report Summaries, 报告摘要9 I n. E+ z5 z/ i9 r _
Residual sum of square, 剩余平方和" R$ N' J; y: ? A* l! N1 c+ w8 m
Resistance, 耐抗性
/ v8 F6 i# G' t7 K2 q2 dResistant line, 耐抗线4 |0 W: e) @( i m
Resistant technique, 耐抗技术& P. z, Y1 c' E4 e
R-estimator of location, 位置R估计量; {1 ]6 y2 R% ]
R-estimator of scale, 尺度R估计量
; N- k, s* x- y; j9 l' U! o6 NRetrospective study, 回顾性调查
3 L9 ~/ ]8 n- f0 T1 H+ PRidge trace, 岭迹
z" {. p' e3 U7 nRidit analysis, Ridit分析
% g8 N7 ]2 v( rRotation, 旋转
) ^+ x4 i0 w$ O) L: C6 R7 d* {Rounding, 舍入
, v T0 Q; Z( C+ @7 CRow, 行) g9 y: \+ M3 Z1 b3 e
Row effects, 行效应) r4 C2 [5 F& f* [
Row factor, 行因素
' `* @3 o8 \ H5 I$ MRXC table, RXC表
( D$ j+ T6 {, a" A* A7 [Sample, 样本' g- V& r) a' V8 l
Sample regression coefficient, 样本回归系数( s1 Q n8 Z v$ l" C1 @) E8 z. ]
Sample size, 样本量) b0 `3 y& L5 h: m
Sample standard deviation, 样本标准差
+ x2 |' U8 L& Y; A5 USampling error, 抽样误差5 U( B! H8 J3 y( n' q- n
SAS(Statistical analysis system ), SAS统计软件包
6 V! L& W9 u* t$ f7 X. XScale, 尺度/量表
" D( t# t3 q( G ~1 h2 e! Z% mScatter diagram, 散点图
7 c& ]) w8 G! D. i/ Z% m' HSchematic plot, 示意图/简图
! n' i1 N6 r0 `1 e U) bScore test, 计分检验
5 K( W5 G: [6 R8 c8 L% NScreening, 筛检6 Y8 n" |% i5 O5 Q I; O
SEASON, 季节分析
7 \9 W, \5 j3 q5 N( ^2 GSecond derivative, 二阶导数! h' c( Y, E) @) j# m
Second principal component, 第二主成分
1 e% H$ d0 A' ~# n( V# }2 s9 t+ D: R7 OSEM (Structural equation modeling), 结构化方程模型
7 ?+ x! O% D% w# L* k1 qSemi-logarithmic graph, 半对数图
% c X1 t. W. o4 k' o5 wSemi-logarithmic paper, 半对数格纸
8 g, y5 N4 L4 |$ ESensitivity curve, 敏感度曲线6 h! D4 B/ K+ W- I A- w# w6 Z8 Z
Sequential analysis, 贯序分析7 ?8 }5 v7 e. V
Sequential data set, 顺序数据集
) \3 l K: S% H" ^Sequential design, 贯序设计, _2 d! @/ i; _$ |2 }
Sequential method, 贯序法
" T% ^1 R4 S! KSequential test, 贯序检验法
7 c' d, a$ R, [Serial tests, 系列试验
8 o7 |1 `! l6 E2 D3 uShort-cut method, 简捷法
* |3 t+ m4 q+ ^7 F0 F! X$ rSigmoid curve, S形曲线6 @, ~ Z. ]" e0 @4 j/ R
Sign function, 正负号函数
8 ?4 C+ @3 M \9 p% M6 zSign test, 符号检验) T' a8 G* x3 o0 e
Signed rank, 符号秩; w/ h! z5 a6 ]( U9 U
Significance test, 显著性检验8 D6 {# A( Z1 R V: T1 A% N( Q
Significant figure, 有效数字
4 S+ |( U f, z# h+ u2 z# U& H Y+ [Simple cluster sampling, 简单整群抽样% M! K- \$ ?, L; T* ~
Simple correlation, 简单相关
' O; U- V! W* B4 [. [Simple random sampling, 简单随机抽样5 t5 Z$ m f4 g4 O
Simple regression, 简单回归
- t% {5 N, z5 P2 X, ?simple table, 简单表
% l9 v: i# r- Z" qSine estimator, 正弦估计量 W. h- F; Y* J2 R% ?' [8 {
Single-valued estimate, 单值估计
! K1 M% J8 N3 ]2 H' r: w+ hSingular matrix, 奇异矩阵8 N9 @; y9 ~+ h: Q5 E+ a
Skewed distribution, 偏斜分布: R1 l9 N/ T' W, V
Skewness, 偏度
; m6 Z' o/ y/ Y2 U) Z% C: a0 N4 ^Slash distribution, 斜线分布$ P m. Y4 i# R; J4 u6 s
Slope, 斜率( A9 _$ `6 U& v' X1 I
Smirnov test, 斯米尔诺夫检验
+ H" ~8 F. J" |0 n, A% q3 XSource of variation, 变异来源
1 B# S3 G% m5 H' oSpearman rank correlation, 斯皮尔曼等级相关+ k9 S( q! u2 l& o
Specific factor, 特殊因子& U( N- }5 y2 ^# b! e
Specific factor variance, 特殊因子方差
* h' U# m2 t4 \% u. bSpectra , 频谱' \: P- t+ G& E7 [
Spherical distribution, 球型正态分布0 D* ?' r9 E8 R) P6 W' i
Spread, 展布
}3 U8 ?( k5 {' HSPSS(Statistical package for the social science), SPSS统计软件包
3 Q) Z; p" C2 F& lSpurious correlation, 假性相关
4 y- x! p* {) D3 k: a |) m8 mSquare root transformation, 平方根变换
/ o& |* r' e/ {7 S' zStabilizing variance, 稳定方差. K# G* x5 Z( [: A4 y0 r" H" Y
Standard deviation, 标准差
5 ?3 [+ H) c1 w0 yStandard error, 标准误
1 [ g$ q* H6 c( ? L% Y6 aStandard error of difference, 差别的标准误7 S& L. t \, \* R; V- b% c4 {
Standard error of estimate, 标准估计误差
' j l' i" C. {) M3 v2 BStandard error of rate, 率的标准误
4 V; B& v7 y9 i) {$ LStandard normal distribution, 标准正态分布1 C$ B5 \) {4 ~6 E2 q$ {8 J
Standardization, 标准化) S' r' O5 C: U4 \% S' l8 r1 I% U
Starting value, 起始值
]% b1 Z' V/ c9 h, MStatistic, 统计量$ |# x% R! a4 V5 u
Statistical control, 统计控制0 ^; P* l- ?5 ?/ [5 O+ _% A
Statistical graph, 统计图0 Y8 t; R% F9 p
Statistical inference, 统计推断3 O' M$ D0 [7 f$ K0 {3 l5 |
Statistical table, 统计表/ F; h; J- @7 J& G
Steepest descent, 最速下降法9 }. j8 u+ K% A' \4 U; g( G
Stem and leaf display, 茎叶图 z& M# | d, [3 j7 M* |
Step factor, 步长因子
. K: @' t3 i* B) N, X) T, TStepwise regression, 逐步回归 Z+ y' o. \* M) e
Storage, 存' [( N; L# D% N6 s2 M* x
Strata, 层（复数）, r% R: x0 D- g* }# B& y
Stratified sampling, 分层抽样
9 q- r! A3 b1 A2 rStratified sampling, 分层抽样9 @4 @$ B5 I) b! Z$ \( p
Strength, 强度
! D6 a# X8 I) p3 `Stringency, 严密性
6 C9 v" S1 g. P/ v6 E& u" E. pStructural relationship, 结构关系4 N m7 {( B* q2 m! R' P
Studentized residual, 学生化残差/t化残差
4 o) m6 D* l# F! e8 BSub-class numbers, 次级组含量+ P$ g* R# y# B. r/ T2 R! F
Subdividing, 分割
( S9 S, k' o5 ZSufficient statistic, 充分统计量; p* D2 ~$ x& p8 W+ ]
Sum of products, 积和9 @, ~9 ]9 B/ ^9 \# K6 K1 O: a
Sum of squares, 离差平方和2 i/ \# ^, d! c: A6 ` I5 }+ T+ P! u
Sum of squares about regression, 回归平方和: v5 N: @* a! n
Sum of squares between groups, 组间平方和
' v- u& p+ Q# u( ^5 ^7 f# P" S( zSum of squares of partial regression, 偏回归平方和
8 L* g1 P" F, ASure event, 必然事件
$ _! e& b# k* e, K6 ASurvey, 调查: g( C# m# X, O' o: z: X
Survival, 生存分析
" j9 p* _: z7 g9 K& fSurvival rate, 生存率5 z3 s4 [; r% ]
Suspended root gram, 悬吊根图6 k4 m! o* R. `% l* y9 T
Symmetry, 对称 Z+ H. L4 j7 w! e0 V+ q6 w
Systematic error, 系统误差
2 v% }; {# @$ [Systematic sampling, 系统抽样
! y4 E& t0 b/ ]9 ~5 w( gTags, 标签6 r l" S, @/ l @
Tail area, 尾部面积. i# g8 y% ~4 \
Tail length, 尾长8 I# o: V# E4 ~
Tail weight, 尾重0 z) p1 m* H( |7 i. Y" ~$ s
Tangent line, 切线4 B, U( W/ ^! f. y
Target distribution, 目标分布# g9 ~5 i1 |8 F; V2 x8 W& g
Taylor series, 泰勒级数
$ |4 u- F$ f5 c! Q. Y$ YTendency of dispersion, 离散趋势
+ P. M- x2 X1 M% a! lTesting of hypotheses, 假设检验- f0 F8 h8 L. m: B" r. n% K
Theoretical frequency, 理论频数4 _ D4 i) R$ F @' g
Time series, 时间序列
6 w" T2 L' i0 A$ p# c; J6 pTolerance interval, 容忍区间, q4 d7 s; v, ?/ {! L2 U
Tolerance lower limit, 容忍下限
' ?$ T) a0 A# S) PTolerance upper limit, 容忍上限
, s5 E! |: a$ |- `Torsion, 扰率0 l& J% V9 D7 t3 I4 U9 }) Z' u
Total sum of square, 总平方和4 \ T$ ~& @7 ^4 `2 ^, e
Total variation, 总变异! M% H8 a& Q- D W
Transformation, 转换
v# f: K- I4 J0 m6 @' x" WTreatment, 处理
" d% X/ o( ?8 S( cTrend, 趋势
' h; O& D1 ^/ _% Q5 QTrend of percentage, 百分比趋势
: F( r" `# ]) A% p; @. E1 fTrial, 试验8 L4 l" _$ A# n# h' O' |, J
Trial and error method, 试错法2 A# c" Y# @' @
Tuning constant, 细调常数
" I, |" {* s; z" E4 T( WTwo sided test, 双向检验/ o7 F$ S. J9 q% r
Two-stage least squares, 二阶最小平方
; z5 r" J5 o" X( r$ |+ T0 e, i e) F6 wTwo-stage sampling, 二阶段抽样
2 Z, z' b+ k# k, M( J- ~Two-tailed test, 双侧检验
& F) d2 v4 o/ TTwo-way analysis of variance, 双因素方差分析# w5 ~0 t/ |: y, w
Two-way table, 双向表/ k( i) k' x+ ~8 X" J2 c+ n( r- V
Type I error, 一类错误/α错误
- F) U9 ^( a( v- V$ P( QType II error, 二类错误/β错误
0 C) J. M8 R9 O+ z) lUMVU, 方差一致最小无偏估计简称5 B7 ^( s: A% j( Y' r+ A, Y6 C
Unbiased estimate, 无偏估计
; a6 o. [+ u9 X. j+ w% F* d. UUnconstrained nonlinear regression , 无约束非线性回归5 @4 m& @* e* a5 M
Unequal subclass number, 不等次级组含量
/ _" g |! N1 z R- B: hUngrouped data, 不分组资料
0 z2 U, s8 f3 dUniform coordinate, 均匀坐标
5 Z- V0 I4 ]! f9 mUniform distribution, 均匀分布6 u* k' a1 s" [6 }% `8 {; y, p9 z: Q7 ]
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
! w' p% s9 g: ^8 E! mUnit, 单元0 V2 F: Y. E1 D, Q, ^# j- h
Unordered categories, 无序分类
: Q$ T5 j. ]$ h: kUpper limit, 上限
, u& T& M3 z; ]) a( b& g! gUpward rank, 升秩
/ }6 _( q0 p; H4 l. l: X" hVague concept, 模糊概念- N3 S' V+ i5 J
Validity, 有效性2 S: i0 w4 c: P! X$ w4 c$ D P2 N
VARCOMP (Variance component estimation), 方差元素估计
& _8 {9 c3 B" ^Variability, 变异性
. E" _' M# ^) K3 }Variable, 变量) P) p( N+ H" |( e
Variance, 方差
- p- h( Z3 F* J9 K1 x" aVariation, 变异* e+ i+ \* I; S4 {
Varimax orthogonal rotation, 方差最大正交旋转- S1 N6 |6 o+ \# K# d! J D4 Y
Volume of distribution, 容积
! d B. Q9 Q2 |1 M/ L* j8 BW test, W检验
9 j) w' V5 U( E' GWeibull distribution, 威布尔分布4 q$ K1 s* b0 N) q
Weight, 权数
" M; X5 m) d- A8 p5 j0 ~) OWeighted Chi-square test, 加权卡方检验/Cochran检验+ c: u4 `+ V2 i% @6 M
Weighted linear regression method, 加权直线回归
5 V: U( A4 D& f% h5 kWeighted mean, 加权平均数& t+ b% p. g% U }* \
Weighted mean square, 加权平均方差6 Z, C/ s$ V; F9 _
Weighted sum of square, 加权平方和
, z& w: p: y0 _5 {6 q- o' M9 ]& Q0 mWeighting coefficient, 权重系数
6 x* P# y! m" hWeighting method, 加权法 - I) H0 ?) {( }$ _1 S" [6 d
W-estimation, W估计量
- N n# r1 k! |) SW-estimation of location, 位置W估计量
+ m9 \0 I% u/ t1 {. D" ]% ^Width, 宽度& S9 Y+ j3 D& w0 |0 G
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
) T& a! h4 S9 q) M0 d" bWild point, 野点/狂点* A( n& N8 X) M' U
Wild value, 野值/狂值
' \$ s0 s, g& r# D1 \1 tWinsorized mean, 缩尾均值8 Z! D5 r! Z( ?5 j
Withdraw, 失访 $ s; v3 Z' |0 J& O% ^ X
Youden's index, 尤登指数+ f/ C; y6 n* U2 {$ f2 |# a6 S
Z test, Z检验
( X q; F3 V& O3 ^8 v4 R# pZero correlation, 零相关
L9 [( J* `8 O mZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
