|
|
Absolute deviation, 绝对离差
5 `- u; m5 w6 [. z' _2 dAbsolute number, 绝对数
3 M# q% }5 s. F8 Y$ w) Q4 |Absolute residuals, 绝对残差. V1 C' S3 ^$ S( b' c: ~
Acceleration array, 加速度立体阵4 {6 H8 k3 ^. w2 V& |1 Z' G
Acceleration in an arbitrary direction, 任意方向上的加速度6 m. S# }. e* w/ S/ K w
Acceleration normal, 法向加速度& T2 O; X0 @9 G B
Acceleration space dimension, 加速度空间的维数' J' c- L" A, J. A& K" K
Acceleration tangential, 切向加速度
$ l1 ^. C7 S( f8 Z- @1 {/ W8 MAcceleration vector, 加速度向量
3 `: c) M7 J0 @Acceptable hypothesis, 可接受假设 c! f' t; D4 N
Accumulation, 累积% a# M4 E& V8 u8 C1 |
Accuracy, 准确度
9 ^: e) g/ m" y/ P6 {' _Actual frequency, 实际频数
6 d8 h- y, B7 c8 w# E4 i. rAdaptive estimator, 自适应估计量( A1 u* X9 W* q3 i
Addition, 相加4 D# q0 v0 {: t3 f8 B
Addition theorem, 加法定理
6 A! G7 c2 x; E, V4 H+ P$ o& aAdditivity, 可加性
1 |6 T" m( S* G1 w% {Adjusted rate, 调整率
3 s% c' q' G+ GAdjusted value, 校正值% \+ ~& t3 n# {3 J% W u5 A; h; Z
Admissible error, 容许误差
2 q3 \# ~; z5 n _Aggregation, 聚集性* N7 B0 c. f; Q0 L
Alternative hypothesis, 备择假设
/ C- R$ e# E; M/ k0 B& i: cAmong groups, 组间* h3 l- _0 v6 i4 }+ M; O/ b
Amounts, 总量
8 S. p+ K4 i. w; g$ aAnalysis of correlation, 相关分析
7 h: }7 w, l& U5 e( k: z: CAnalysis of covariance, 协方差分析& s; J3 g- D4 N
Analysis of regression, 回归分析
+ x2 @! E! a. C xAnalysis of time series, 时间序列分析
# B, w* _& F+ D! aAnalysis of variance, 方差分析2 M9 j9 z- ?6 V
Angular transformation, 角转换
' h7 k/ @8 t# N" _" |1 XANOVA （analysis of variance）, 方差分析
4 Y3 t, v Q* N* x. yANOVA Models, 方差分析模型( U8 V6 V2 E7 k4 j& F
Arcing, 弧/弧旋" [. R* h6 w" Z: P5 m" `2 Z( j
Arcsine transformation, 反正弦变换9 ^" m5 Y a0 k% _" k
Area under the curve, 曲线面积* x3 X* Y6 N% A& X
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
+ G6 |: Y7 C. ^5 q1 hARIMA, 季节和非季节性单变量模型的极大似然估计 6 O- V* g( g" o) m
Arithmetic grid paper, 算术格纸4 M `) A( b0 G; |
Arithmetic mean, 算术平均数
: ?8 Q0 @, q7 M1 w; | `- ^) HArrhenius relation, 艾恩尼斯关系
" ~7 }/ y' w8 P) m: a1 ~Assessing fit, 拟合的评估
* }$ d" I* R5 d p) Y# H$ k( qAssociative laws, 结合律
: Y6 T8 V- s7 g& r% s0 ^1 N( L1 rAsymmetric distribution, 非对称分布3 L, F! p% {$ m: |9 d7 V; [, j n
Asymptotic bias, 渐近偏倚0 S8 o" Q+ d* O
Asymptotic efficiency, 渐近效率
. |1 J5 I, f/ L& t3 w4 `, W, W; SAsymptotic variance, 渐近方差
: }4 ~. z# K2 dAttributable risk, 归因危险度
* V0 b# m* T9 r; o9 tAttribute data, 属性资料
% H+ t: Z& L# s9 ^% eAttribution, 属性: n- J" J. _5 q9 ^
Autocorrelation, 自相关
8 q" s/ b) `* ^2 h4 d2 ~9 NAutocorrelation of residuals, 残差的自相关% q5 u: ~ W5 L3 d
Average, 平均数
& _) ?$ C! P1 B) B/ Y1 Z8 U% AAverage confidence interval length, 平均置信区间长度
6 Z% X$ p* o( R5 T, NAverage growth rate, 平均增长率7 ~! W4 _3 d7 Q, _8 ]9 t
Bar chart, 条形图8 x1 T" n' G4 {8 _
Bar graph, 条形图
( R/ T5 M" ?7 n* _! ZBase period, 基期
. u: u' _4 y- W; [0 N2 `Bayes' theorem , Bayes定理$ V- A: a- v! D$ b; ^& u
Bell-shaped curve, 钟形曲线
0 K( m) r0 ]$ Y @4 E" C c! w2 kBernoulli distribution, 伯努力分布1 b2 g: u5 i9 _* C
Best-trim estimator, 最好切尾估计量9 c% B. K4 x" _7 |, @
Bias, 偏性
9 M4 G, O9 X9 e" a+ m& E) ?Binary logistic regression, 二元逻辑斯蒂回归& r) T$ M/ ]$ L$ ~! O
Binomial distribution, 二项分布( P: g6 P9 C- J( l. _; C
Bisquare, 双平方0 I: M: X7 p. G% a/ {' u
Bivariate Correlate, 二变量相关
0 E& _" o$ j3 J4 ^" ~Bivariate normal distribution, 双变量正态分布: R( u2 Y" a+ H
Bivariate normal population, 双变量正态总体
% W$ f ^! _7 B6 R+ hBiweight interval, 双权区间
$ J+ I+ A, p2 v6 M+ |8 ^, K0 ?Biweight M-estimator, 双权M估计量- `$ f# Z* V! l% v! P: M |
Block, 区组/配伍组
! s( c: u* K2 q/ J: E: PBMDP(Biomedical computer programs), BMDP统计软件包
$ g! d. z4 X% x; O5 Z6 JBoxplots, 箱线图/箱尾图- v$ S7 W1 W( E- m. e
Breakdown bound, 崩溃界/崩溃点
8 s2 C" v5 O4 N/ X" eCanonical correlation, 典型相关, u" F% h5 c) I N
Caption, 纵标目5 I9 M P: N' E5 n1 c4 y5 w7 u. C
Case-control study, 病例对照研究
( J2 K9 @0 b6 {" A" `( |5 t- C' tCategorical variable, 分类变量
. R3 Q; G+ B, v' c: S6 BCatenary, 悬链线$ }! A, U+ W7 t# b. K! F% v
Cauchy distribution, 柯西分布
! S( k* o. X. \4 {* {Cause-and-effect relationship, 因果关系0 E6 S$ P. X3 C1 c
Cell, 单元
, W G' F* Q0 c/ N3 o# XCensoring, 终检
. E; @' b6 S0 i* UCenter of symmetry, 对称中心. N/ Q; I+ ` q/ ~7 Q
Centering and scaling, 中心化和定标 v9 c2 D, w6 g6 e' q# A: r6 P6 y
Central tendency, 集中趋势
, H' x2 {/ h" V1 e% uCentral value, 中心值1 Y2 ^( a5 i/ k. Q
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
w# M) e L7 a+ ^3 {/ KChance, 机遇
2 R' u% }) ~/ ~Chance error, 随机误差
0 b+ a6 w6 ^8 Z7 U! A% ]( QChance variable, 随机变量. k" K; g/ ^' D, c7 f
Characteristic equation, 特征方程
9 y5 e o0 n* i+ a, h# d9 Z, ICharacteristic root, 特征根
0 n' @! T7 V9 l' p- C2 [+ N; X4 hCharacteristic vector, 特征向量
( i+ m& G3 D( G- |% G+ LChebshev criterion of fit, 拟合的切比雪夫准则7 O1 O$ E, k- X& I' w! M
Chernoff faces, 切尔诺夫脸谱图0 K# v% O! c P' Z, c2 d
Chi-square test, 卡方检验/χ2检验
: E! @6 _; V" M \) WCholeskey decomposition, 乔洛斯基分解
! `( x M: D+ _# S3 v" wCircle chart, 圆图
' C! o( C0 b9 zClass interval, 组距7 ]' r H& a0 y! e4 e: p
Class mid-value, 组中值
3 Y9 O; |/ _( c5 f% I5 U" y- j& KClass upper limit, 组上限
- b; A, l" g8 B8 q( S+ a( `Classified variable, 分类变量
! E9 u' ]1 t8 o! Y& U0 aCluster analysis, 聚类分析
0 t; l: J6 b5 R: v5 k! Z0 \Cluster sampling, 整群抽样
. g7 {1 W& f; @+ Q' f& b8 b4 S6 SCode, 代码8 @, e _' D o7 C
Coded data, 编码数据$ d0 ^: A+ e( k9 R: ?, {
Coding, 编码
! c5 D: F3 ^; s8 G2 i: o; [' ECoefficient of contingency, 列联系数
) x- N! A1 @" ^4 @. }3 tCoefficient of determination, 决定系数
* ]& h, n( X9 g4 m# ~ I, cCoefficient of multiple correlation, 多重相关系数+ s3 t# |$ W# O, y3 ~- R, \- F8 J
Coefficient of partial correlation, 偏相关系数$ A! Y/ A' b( `: u; \$ o9 l4 v' i
Coefficient of production-moment correlation, 积差相关系数1 K# ?# B Z) m8 O; W
Coefficient of rank correlation, 等级相关系数
2 S- p; C. } E ^Coefficient of regression, 回归系数% d; ~# g4 [# v4 l
Coefficient of skewness, 偏度系数3 `5 ?5 x s, ~1 X! s5 o8 d- \
Coefficient of variation, 变异系数, F: T$ s9 J2 L
Cohort study, 队列研究: d, _7 I( _' z- v3 P, ~" x
Column, 列8 R$ j& n$ H! B J
Column effect, 列效应
4 M5 M2 q- }0 k: QColumn factor, 列因素, e& q( [8 R7 Y* Q* l
Combination pool, 合并
" p3 ?7 E, P- M4 \5 [' OCombinative table, 组合表' s. m0 ~- y$ ^" c0 b
Common factor, 共性因子
4 Y/ @+ M ]0 N% |: D, A" d: M( MCommon regression coefficient, 公共回归系数
3 Z# M* e, m* F: n+ s! a# ]Common value, 共同值6 c) b0 U: M9 t, q
Common variance, 公共方差
( R# Z3 N( {5 w: ?! n0 JCommon variation, 公共变异5 @! l" w! s, z/ p
Communality variance, 共性方差
! G0 J1 W( S( D/ R! yComparability, 可比性
! Y1 I0 e3 d' Q: e# l$ RComparison of bathes, 批比较/ d& C6 Q* a1 Z* ~1 m1 {( S
Comparison value, 比较值
0 S' D: @; N; f3 m& T7 K% z5 o$ ^Compartment model, 分部模型( ~5 |4 N# y4 m& |
Compassion, 伸缩; d2 ~2 }- G7 M
Complement of an event, 补事件6 ^1 P9 I' @0 u3 Q
Complete association, 完全正相关
+ w; h* h* |& k1 P+ mComplete dissociation, 完全不相关( A) q' q Y0 h8 d
Complete statistics, 完备统计量
1 j: K' N* s& k4 }+ b- uCompletely randomized design, 完全随机化设计7 e1 m( T C( N5 s5 r5 X! U
Composite event, 联合事件
0 q1 D' a) C% ^, I- u% v" AComposite events, 复合事件
/ _& o' X; ~) e: T/ GConcavity, 凹性
- ]* _ V& t. x6 H: e" G6 T( U- @* oConditional expectation, 条件期望6 l) B0 | g4 A E
Conditional likelihood, 条件似然
: w. M2 n' a- V& P. MConditional probability, 条件概率
8 a; S; Q% p+ X. p8 G" UConditionally linear, 依条件线性9 \" j9 W8 L7 h" E7 | M* P5 R. W4 m
Confidence interval, 置信区间5 [ `- R2 f$ s! u6 F( Q
Confidence limit, 置信限
+ E$ g( V7 T `Confidence lower limit, 置信下限1 M1 i9 s" T, e2 h2 R x5 g
Confidence upper limit, 置信上限
T4 q. m; I- g5 O9 F0 PConfirmatory Factor Analysis , 验证性因子分析. ^' U+ W3 ]( J+ F, j
Confirmatory research, 证实性实验研究' Z# ^: K: L |
Confounding factor, 混杂因素: Z* l5 O$ Y$ l2 l. f9 g8 o: x) `% I; P
Conjoint, 联合分析
5 ?# M" \4 Z! y# J/ g/ o, v7 ^1 ?2 AConsistency, 相合性+ r/ k5 p4 G5 `$ K4 r9 \7 {
Consistency check, 一致性检验& ~8 j u- Z" `
Consistent asymptotically normal estimate, 相合渐近正态估计- ^' c, |9 P V. a9 k4 J H
Consistent estimate, 相合估计 s+ G5 g: Z: x1 s G8 t- L6 |
Constrained nonlinear regression, 受约束非线性回归
3 `; n5 h1 l: |6 D. j- W5 ]Constraint, 约束
' u+ m- @; D, q4 }( d4 ?Contaminated distribution, 污染分布. _; q2 C o+ C1 x$ R9 Q6 U% k4 e- S
Contaminated Gausssian, 污染高斯分布 j$ w- G/ b U
Contaminated normal distribution, 污染正态分布! w/ C7 M4 l0 H2 n6 K" q; A
Contamination, 污染* C' S0 m& y5 \; D1 x) Z5 A
Contamination model, 污染模型
8 d4 m% X9 @5 D) P" CContingency table, 列联表0 a1 a6 C) I( K1 M f
Contour, 边界线' o" ? p% @7 \ @4 b( ]
Contribution rate, 贡献率 M6 B+ b, w) `6 j/ F
Control, 对照
: W" a! X$ Q5 RControlled experiments, 对照实验
7 ]' C2 N/ U. k& L' v; I; f2 cConventional depth, 常规深度6 w# K5 {4 _( v. ]
Convolution, 卷积
. U3 ]! c8 t7 Z' v2 n1 B2 iCorrected factor, 校正因子: L& A" E' ]/ [5 b; Q6 Y
Corrected mean, 校正均值
: P! q. P$ a- m* p. H. c, d6 hCorrection coefficient, 校正系数1 n% e5 p( h- a* o3 _) y, T9 X, n
Correctness, 正确性
' W' ^' @, P" B6 E" ]! pCorrelation coefficient, 相关系数
9 K& [0 z# J& i, jCorrelation index, 相关指数4 G, `. L# s" h- N
Correspondence, 对应$ i7 j& S6 M; ]4 F* V" h
Counting, 计数
( N! u8 O9 }4 D4 K; QCounts, 计数/频数5 {: n5 O4 K' w
Covariance, 协方差- L9 ~5 M: U9 B! O
Covariant, 共变 0 g* X' |" H# j1 ?7 c# ?
Cox Regression, Cox回归+ S# T' E, S! N
Criteria for fitting, 拟合准则
# h) T; G" P3 T# HCriteria of least squares, 最小二乘准则9 d4 d8 T4 o! z6 Y. S, }9 M9 j
Critical ratio, 临界比. A5 k4 T1 q( ]1 b
Critical region, 拒绝域
% G, |6 q' k C' p0 }Critical value, 临界值% n8 |7 g+ a+ u6 O O2 \
Cross-over design, 交叉设计
% g0 O/ k7 O& P1 u( `! c1 |Cross-section analysis, 横断面分析: o8 ?' \( I: e7 S1 F% w5 H0 p) G; \
Cross-section survey, 横断面调查. }; d: H- B, R; a0 c
Crosstabs , 交叉表 ; X+ q, E" ^/ `; t3 c$ Y: o
Cross-tabulation table, 复合表
: V" d7 J5 W; \* QCube root, 立方根+ U7 B2 V7 w3 X( ]3 y# I6 [1 O0 A, ~
Cumulative distribution function, 分布函数
" E5 D+ p5 D9 N. \! C. aCumulative probability, 累计概率
' m! G0 c% S2 c0 Q1 oCurvature, 曲率/弯曲
( Y. D3 z- t- h3 h' \Curvature, 曲率 F3 v- D- [- ]! {
Curve fit , 曲线拟和
4 R% ~7 d3 E8 R- u5 MCurve fitting, 曲线拟合6 A# f6 T6 p- G/ u- i a( S4 f$ ~
Curvilinear regression, 曲线回归8 o0 Y# r5 D' f8 k( V2 V3 U
Curvilinear relation, 曲线关系) c7 S. O1 h- c- W% ^! h
Cut-and-try method, 尝试法; G7 ]: E6 e$ u M) ?
Cycle, 周期
1 |. A9 r4 K7 c- E; a- JCyclist, 周期性8 o8 [3 s# w, s: i6 O
D test, D检验
2 L" R6 [. P: b3 Y6 D) ?Data acquisition, 资料收集! I7 f/ N/ H0 d& ~: J+ b# `
Data bank, 数据库) ]0 x6 e) j2 X, u0 L
Data capacity, 数据容量8 D2 e5 q, N4 ]4 q3 C y$ O
Data deficiencies, 数据缺乏5 Y$ a" t/ Y) B- x8 \
Data handling, 数据处理
* \% j8 [0 Y$ c# o. R' ]% {Data manipulation, 数据处理
2 n. s7 u1 r3 `2 n0 L4 a5 y) iData processing, 数据处理' T) J! ]: S' s1 P' v6 [
Data reduction, 数据缩减& [% O* |3 A* J& W! m: z
Data set, 数据集* W9 @3 F+ T$ T( t" u
Data sources, 数据来源" r! U8 S+ q( _! y0 s% M# T0 |
Data transformation, 数据变换8 H. V7 E5 Q" _4 }& @
Data validity, 数据有效性
7 ^2 D( L) o) p( HData-in, 数据输入
1 \. A+ v# `$ G# ?Data-out, 数据输出
- [* G; u7 B9 e& @+ b- FDead time, 停滞期# L& c0 s, I1 m/ Y. p: M
Degree of freedom, 自由度
1 q6 |% H o3 P- f# r E$ nDegree of precision, 精密度4 r3 i* L; W2 I$ v v
Degree of reliability, 可靠性程度- h& ~3 [& Q1 k6 C/ g# l
Degression, 递减
9 Z+ S5 n }: ]3 ?" A4 pDensity function, 密度函数$ ]4 U! Y I9 ]; o
Density of data points, 数据点的密度
9 k" Q5 G3 k( l# ]Dependent variable, 应变量/依变量/因变量
1 Y2 O8 _8 S. ~) E- D: K, D" IDependent variable, 因变量
7 H5 p/ a! ?: s) B- Z: B; ODepth, 深度
! Z# p/ J$ B0 f) N# \8 F- E5 aDerivative matrix, 导数矩阵0 D; D. N/ a7 }; Q; u4 f
Derivative-free methods, 无导数方法9 l6 b+ P1 S5 N5 f' {$ \
Design, 设计/ h8 S4 T9 O7 M# ]7 A1 t; N
Determinacy, 确定性1 `' z& c& q$ f3 i6 B6 j, D
Determinant, 行列式1 L; b( h, I- A
Determinant, 决定因素' u# O" U5 p: O0 O4 ~) p; t- Y
Deviation, 离差& Q( g; K1 O' q$ \, }. s# K
Deviation from average, 离均差9 v6 z8 t* S1 |
Diagnostic plot, 诊断图
! c& t" }2 K9 M* K& E& h' C ADichotomous variable, 二分变量; c. a w- ]" C0 H# ]7 d/ E1 @
Differential equation, 微分方程4 K" [" a9 ]4 N5 ^
Direct standardization, 直接标准化法
. v$ C9 V0 e2 d* Q3 bDiscrete variable, 离散型变量3 \7 L3 A2 K7 k2 z/ F- c4 t. I
DISCRIMINANT, 判断 0 `- B5 `6 n/ J2 f1 r% X
Discriminant analysis, 判别分析/ f* f1 J. K- R3 Z2 U: k
Discriminant coefficient, 判别系数. d3 s7 r0 S' t" x; x3 O0 `0 _2 L
Discriminant function, 判别值& h5 ~/ @, d7 u1 l2 v: |
Dispersion, 散布/分散度
c. v6 ~6 i: VDisproportional, 不成比例的
4 C+ S; Q2 o% U" a3 [5 fDisproportionate sub-class numbers, 不成比例次级组含量. s$ C1 p; [) v7 v# j
Distribution free, 分布无关性/免分布! |7 K& o7 D# X: q( d& |: ]3 K; t
Distribution shape, 分布形状
5 k4 B% D! G: X# S8 {" g- |Distribution-free method, 任意分布法( p% I& f i3 N( ^: A
Distributive laws, 分配律
; v9 u! a {. A+ \/ T. xDisturbance, 随机扰动项
7 s3 z2 e N& dDose response curve, 剂量反应曲线6 o. v0 X" O0 y! D
Double blind method, 双盲法
+ F; S& L& c) c& s9 hDouble blind trial, 双盲试验' U2 r& U& t X/ K
Double exponential distribution, 双指数分布' I& g+ d. T: [! f; I/ r
Double logarithmic, 双对数1 Y6 W3 ]% R! @$ D* G
Downward rank, 降秩
6 c5 N# y! l, vDual-space plot, 对偶空间图/ t# w2 @: V- Y ]1 \) E
DUD, 无导数方法
# n- Q+ ?: T. H* kDuncan's new multiple range method, 新复极差法/Duncan新法8 V* `) r. g3 S5 M1 g: y6 p
Effect, 实验效应
2 y# L6 G* ~1 Z8 m7 U+ S. Y* nEigenvalue, 特征值
0 ^% f9 h1 }. m, C* o/ eEigenvector, 特征向量
6 z6 [: t8 V4 R% |' \Ellipse, 椭圆
6 \0 R1 c- U5 Q# h6 E/ Y( |Empirical distribution, 经验分布
$ \: d2 C0 I2 w0 {% @Empirical probability, 经验概率单位4 l0 }2 A8 T5 u# y, L
Enumeration data, 计数资料
) _6 [: h9 d1 Y; k0 N5 REqual sun-class number, 相等次级组含量
' t- |6 @% V4 y! m. v5 D; r# hEqually likely, 等可能
- b& B- p. B" M/ |$ ZEquivariance, 同变性
0 x$ t0 u& H% MError, 误差/错误5 o) |0 G) \! }0 v5 o
Error of estimate, 估计误差( X9 U2 J8 y* U9 `" ^
Error type I, 第一类错误! Q* Q. z( m0 y1 R0 q# {' e
Error type II, 第二类错误7 [/ u1 D9 G2 ?. \
Estimand, 被估量
8 p7 X. [% {8 u( h: nEstimated error mean squares, 估计误差均方
6 ^6 v+ i4 [& o( w8 y/ IEstimated error sum of squares, 估计误差平方和
% ]& }' [1 J3 i5 t8 @- aEuclidean distance, 欧式距离1 K0 i$ l( q! A, E9 F$ a% h
Event, 事件7 G( m- k3 A( \' O* v! R
Event, 事件
3 R5 k7 r6 E9 z- v' aExceptional data point, 异常数据点/ b2 E/ T. v, [" @; R5 M; P. p# q
Expectation plane, 期望平面9 K/ o' p. X8 U' U w% g q
Expectation surface, 期望曲面6 ?) Y$ w6 \" G, K1 p- f
Expected values, 期望值: [5 Z! P0 e; H1 j# |2 \
Experiment, 实验: Z2 \. \' J( }7 `+ z
Experimental sampling, 试验抽样1 h% \4 X* ?- e* q9 {
Experimental unit, 试验单位
3 I9 f! w! I4 q" q* S _Explanatory variable, 说明变量
* b9 Y/ w, i4 S. [4 xExploratory data analysis, 探索性数据分析* y: N }# V. o
Explore Summarize, 探索-摘要
+ c* o( }/ \( vExponential curve, 指数曲线* d% E1 v( v; l* _( p3 o
Exponential growth, 指数式增长( p% H8 m9 c7 S1 m" F1 M( b- T
EXSMOOTH, 指数平滑方法
4 O# a) k+ Y: w8 A3 E! `! l/ GExtended fit, 扩充拟合
, ?1 y; K0 p$ ]! H; r2 q# s* ]Extra parameter, 附加参数/ ]8 {' k% J9 _3 i# |
Extrapolation, 外推法! M. B0 Z) L: P2 [+ o6 [! r- V
Extreme observation, 末端观测值: h* M1 T1 X; {2 V9 b
Extremes, 极端值/极值! ^$ X; G7 _9 `9 F+ m9 G
F distribution, F分布
; R2 {, q' n* m- UF test, F检验- p' B- S; ~$ B. Y6 W+ v/ S7 R! _
Factor, 因素/因子
" W% f/ R- S4 b6 U/ \4 OFactor analysis, 因子分析; `4 @' R+ Y8 [6 ]+ r6 G9 \
Factor Analysis, 因子分析
$ n* V6 k) h0 v/ l- d5 ^Factor score, 因子得分 $ z7 T) n9 ^. X- i$ [6 p
Factorial, 阶乘, `, A' {2 r( P9 j" X
Factorial design, 析因试验设计
2 w! N, G* l8 mFalse negative, 假阴性
( _2 \ K* t; QFalse negative error, 假阴性错误
2 \! e9 F7 s1 X+ ~' i6 TFamily of distributions, 分布族
; _4 _% B& [. L( C; @/ ]4 UFamily of estimators, 估计量族
8 r7 }& d; I: B+ R |8 b% r: j) lFanning, 扇面! M& W6 ]' k: M: v3 {. @& A
Fatality rate, 病死率
% I& \. }& H8 W: q/ m- G0 sField investigation, 现场调查
" s: C3 ^4 F4 [% u: E# AField survey, 现场调查9 Z% \+ h9 a7 o
Finite population, 有限总体5 X: {. Y- u( I m% N7 X4 @
Finite-sample, 有限样本
) P3 `! g, h$ u( `8 V' I7 | @1 t2 u% dFirst derivative, 一阶导数
0 S6 w; a- m) L! j! O9 aFirst principal component, 第一主成分& P" o- ]/ o' i# @; z v
First quartile, 第一四分位数9 ^, k' g: Z$ c: |' l
Fisher information, 费雪信息量
7 ^0 U( [6 B6 hFitted value, 拟合值
* Y# F- q$ h. k# D1 K x3 ]( HFitting a curve, 曲线拟合
7 @" u7 b u2 S9 t, HFixed base, 定基" P |5 k+ a& t; S' V9 Z/ N
Fluctuation, 随机起伏8 V! X: F6 m) c i3 l# p
Forecast, 预测
) z& H" o; E* z, d" m A( g* G- }Four fold table, 四格表, V# l$ E Y4 }: B
Fourth, 四分点' \$ k# s; W+ {& S/ p5 t4 _: q
Fraction blow, 左侧比率
! D8 M7 b$ Z* i+ I x4 [7 gFractional error, 相对误差; d& `* Y4 T/ p0 z3 C
Frequency, 频率
- M [3 ]9 U6 d8 @8 T( ^Frequency polygon, 频数多边图
7 i+ `" S) h& O' N8 Q, jFrontier point, 界限点" [; p( Y0 {4 ^8 E0 A
Function relationship, 泛函关系5 _3 x" K: s' I
Gamma distribution, 伽玛分布
6 f' J! h9 f+ Y/ iGauss increment, 高斯增量$ Q! d$ _: Z$ h' L. p
Gaussian distribution, 高斯分布/正态分布) n1 ]0 ?9 V+ Q4 E# k& k
Gauss-Newton increment, 高斯-牛顿增量
" h y/ w' N' H2 I, x+ GGeneral census, 全面普查/ e, y( a% q7 e, Z
GENLOG (Generalized liner models), 广义线性模型 8 Y( G5 q3 K- y- }7 ]- p8 n4 W
Geometric mean, 几何平均数0 S# q$ \. F, c3 g
Gini's mean difference, 基尼均差2 W& o! F! E7 _. ^' Z3 g
GLM (General liner models), 一般线性模型
, Y% w; D; {. ?2 R' v) fGoodness of fit, 拟和优度/配合度
# Y* R9 [$ Q [7 f$ P" S8 iGradient of determinant, 行列式的梯度
4 b3 Y& E9 I# u+ u( ^- @# t* qGraeco-Latin square, 希腊拉丁方" G9 X4 U3 }+ Z6 `, u
Grand mean, 总均值
1 p8 a# `2 |( `) A: P& K5 PGross errors, 重大错误
' h0 K: B n" k* Y% D! GGross-error sensitivity, 大错敏感度
: m" x' B. B5 h$ M9 z. `Group averages, 分组平均
+ |* a h: ^& V0 d, @" E: A" C" oGrouped data, 分组资料
! J& i" t" y! TGuessed mean, 假定平均数6 X% V+ V- V6 z
Half-life, 半衰期9 M8 |. g) a8 T
Hampel M-estimators, 汉佩尔M估计量- `) P8 R& r. `) D- C+ j6 Y
Happenstance, 偶然事件4 t% N1 v( C1 h! d' N+ y3 z- h- H4 q
Harmonic mean, 调和均数0 Y, ~6 I% T; k3 W) D' J
Hazard function, 风险均数1 Z3 L' z0 {# _- |9 r! Q
Hazard rate, 风险率
) X0 j9 u1 y, ~0 `6 _/ F) V* h- i% u0 R- QHeading, 标目
( r7 u) H; M: H% n8 r# T4 AHeavy-tailed distribution, 重尾分布' I- g! `3 q5 h( h" D- }6 q
Hessian array, 海森立体阵+ }% W( e6 Y! d8 [, \5 N; _5 x
Heterogeneity, 不同质
: G# e' C/ ~7 C2 E' D9 K" `6 wHeterogeneity of variance, 方差不齐 4 k2 y% Y+ u' N; V- j, C* ~
Hierarchical classification, 组内分组" ~. e" P) n7 i+ i8 d
Hierarchical clustering method, 系统聚类法& V, S" C. ]8 p2 E% O$ \7 W
High-leverage point, 高杠杆率点! F7 M/ |$ m5 Z) j+ o
HILOGLINEAR, 多维列联表的层次对数线性模型; A: @( |+ Z; e- {1 K
Hinge, 折叶点! L& B; [& \2 s4 Y
Histogram, 直方图, t4 \5 Z8 ]# ], S% Z/ R& S
Historical cohort study, 历史性队列研究 * r) p7 ?# M0 u4 ?5 @# k
Holes, 空洞9 l8 L2 K% ^) I
HOMALS, 多重响应分析
- l" a7 Q* v+ m8 h4 Z# L$ |Homogeneity of variance, 方差齐性2 m- O# U8 t: Q/ R
Homogeneity test, 齐性检验
c0 u1 S* [! v, ~/ n/ Q$ s1 I" bHuber M-estimators, 休伯M估计量
8 N+ ~6 R' d2 H+ ^* l$ L( yHyperbola, 双曲线
) H n+ i* V* o- Q# N) z* `' t4 _Hypothesis testing, 假设检验* d7 R! y. L8 {. ?0 ?3 Z0 y+ U
Hypothetical universe, 假设总体& Q- ^" c; n7 @0 E$ n4 C9 n$ F7 ]6 _
Impossible event, 不可能事件4 v3 r9 }# Y2 f, P- O, X
Independence, 独立性
, y# L7 K9 X$ b8 s0 lIndependent variable, 自变量
9 j1 N% F% Z4 M+ p. j) c2 |1 FIndex, 指标/指数8 i8 P: N1 W. B( n) V
Indirect standardization, 间接标准化法$ \; ^ w% u$ Z- Z% t1 X7 \' _% A
Individual, 个体
7 j- E1 J, L. ?6 PInference band, 推断带
7 e0 }- q2 [: M1 e; {, P" M6 UInfinite population, 无限总体
. U5 A9 R; l2 j2 n9 o2 SInfinitely great, 无穷大- l: n6 ~( s2 O3 I
Infinitely small, 无穷小
4 c/ m- s, ]! B2 u, KInfluence curve, 影响曲线
, k$ i+ M a3 d7 @/ Z1 mInformation capacity, 信息容量
8 ~" x3 g8 }8 [. `Initial condition, 初始条件/ i) U* r& f% k
Initial estimate, 初始估计值
; B& c6 h' F& S2 J4 zInitial level, 最初水平
% `: c% p7 C: Q3 r; \Interaction, 交互作用
: y$ Q3 K, W% p8 H# d& w, e+ uInteraction terms, 交互作用项
; u+ f) C( M+ `% I. o& P, C, xIntercept, 截距
+ q7 {- b( |3 pInterpolation, 内插法
5 K5 P7 w: b: x& B$ k) FInterquartile range, 四分位距
1 d2 e$ ^# V$ I, G& `$ kInterval estimation, 区间估计2 q6 I$ w0 j% E5 v
Intervals of equal probability, 等概率区间) P4 ^- E! s4 P$ s; F
Intrinsic curvature, 固有曲率' m3 p x4 N2 T0 m: e& T4 w- d9 ?
Invariance, 不变性5 [& o5 ^, T9 r) p
Inverse matrix, 逆矩阵& y* _; X6 C3 A6 g/ f5 v
Inverse probability, 逆概率
; E5 }/ ?1 S/ [; GInverse sine transformation, 反正弦变换
& J0 G2 V3 ]4 Q4 w* x0 @ NIteration, 迭代
+ b5 J0 U; L' l# J/ K" LJacobian determinant, 雅可比行列式
3 e6 z! G7 F7 jJoint distribution function, 分布函数 i$ s4 T7 p0 D2 i c
Joint probability, 联合概率1 X+ j- M" S- N
Joint probability distribution, 联合概率分布5 V" c! T5 ~ _3 G6 s
K means method, 逐步聚类法
' W* O+ Z l2 `$ _Kaplan-Meier, 评估事件的时间长度
2 [( l, w0 m- T, o/ FKaplan-Merier chart, Kaplan-Merier图: ]7 h9 o# Q4 Q' ?
Kendall's rank correlation, Kendall等级相关 v: ~# N* n* a. y
Kinetic, 动力学
) g; X; v9 S, X2 ]/ B1 _Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
# Z! S6 u% y9 }! m9 ^Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验, @) u% ?7 W2 ^
Kurtosis, 峰度
$ t R. L, f5 p- }: ?0 d- j% HLack of fit, 失拟
/ f7 v2 i3 F! mLadder of powers, 幂阶梯
# ^ c5 T( L5 Q, A `$ ILag, 滞后* t5 w4 j3 _& U( @
Large sample, 大样本$ y/ `/ q j! x
Large sample test, 大样本检验( y' t! Y7 x1 ~8 y% _3 \1 _
Latin square, 拉丁方8 Q0 B' [- N' d- O0 l V* [
Latin square design, 拉丁方设计
+ ` G5 E* j. H x$ T, l5 b. DLeakage, 泄漏
* \7 l. z' |, y: qLeast favorable configuration, 最不利构形
+ F8 N% S7 G" v2 U3 g9 d# aLeast favorable distribution, 最不利分布% T% |& g& u$ E/ i! `, Y$ k
Least significant difference, 最小显著差法; u4 ~9 d& F! D, D7 B
Least square method, 最小二乘法
: X! s) u7 g! n5 v6 n' J7 fLeast-absolute-residuals estimates, 最小绝对残差估计7 K- {1 V8 f2 `
Least-absolute-residuals fit, 最小绝对残差拟合
% t% Z' S% b. d& c& Z' \Least-absolute-residuals line, 最小绝对残差线
% Z; U# ?6 Z d/ k. TLegend, 图例
+ T. b7 `* F% r9 y l8 w$ `L-estimator, L估计量7 x2 L) H7 ]1 c
L-estimator of location, 位置L估计量3 \* z5 @$ S8 Q! j- h! M- e
L-estimator of scale, 尺度L估计量$ A6 `9 ^" u2 b) L+ \
Level, 水平 w P, \, d& V; x$ Q
Life expectance, 预期期望寿命, T( [; f: y/ v6 _" i
Life table, 寿命表
: Y, }3 J; c, O1 F: Y" d5 eLife table method, 生命表法
, s/ @/ n* ^3 c& SLight-tailed distribution, 轻尾分布
& p3 s- V) e# wLikelihood function, 似然函数
; l( X6 l' B" O- ~Likelihood ratio, 似然比
: K; Z F1 B; zline graph, 线图
& U6 l8 `; `( M3 CLinear correlation, 直线相关 V* [8 v& f6 H* h, d2 X
Linear equation, 线性方程
* J/ o6 P8 E+ Q: V# SLinear programming, 线性规划7 S+ E# {6 h5 c
Linear regression, 直线回归
8 C0 F' d3 B6 y/ a xLinear Regression, 线性回归: \6 C6 Q# o) R- ?6 j
Linear trend, 线性趋势0 i1 G; W( n! y! T5 J
Loading, 载荷 . i( j' y. h; D' O
Location and scale equivariance, 位置尺度同变性3 C; e3 S3 J- [8 L T
Location equivariance, 位置同变性' y- ]0 q/ n# U: B* Z* {6 V; B
Location invariance, 位置不变性
* b2 o/ G, ^: m; C M+ BLocation scale family, 位置尺度族
i. x/ w O. S1 d; Y- O# gLog rank test, 时序检验 ' }2 ~' X8 Z. y! k W
Logarithmic curve, 对数曲线
7 q5 _- \" D+ \2 b1 T' vLogarithmic normal distribution, 对数正态分布
: U" |: Q4 x+ T0 o4 V2 m$ aLogarithmic scale, 对数尺度$ p! D4 z( N: \6 y7 A# r) ]
Logarithmic transformation, 对数变换
6 H1 y- g- F5 ]. {1 \Logic check, 逻辑检查
8 Y& I' g# K) L9 }/ sLogistic distribution, 逻辑斯特分布6 @3 u( w7 H+ Z
Logit transformation, Logit转换
5 {& k5 U7 N8 uLOGLINEAR, 多维列联表通用模型
4 `. h. a. H. g7 W" d" _Lognormal distribution, 对数正态分布" W: V3 ?9 h' T' s- ?; ~
Lost function, 损失函数( O5 C% N& T4 c1 d8 W- n
Low correlation, 低度相关
- h ?5 P9 T/ m' D; d5 L, o- HLower limit, 下限3 J: G1 E5 S0 ], G c# Q' f
Lowest-attained variance, 最小可达方差
: _& ~, M1 y6 `! e yLSD, 最小显著差法的简称- v! P. q/ N8 f
Lurking variable, 潜在变量
/ ?8 P4 }) Z0 _Main effect, 主效应
' \0 [3 I# C* u1 V: l! J; `! WMajor heading, 主辞标目; q* {) J% q# Y
Marginal density function, 边缘密度函数. G" R. r! l8 D( v+ F
Marginal probability, 边缘概率
0 P0 @6 z( {! I& {# J. L9 Q3 w+ K3 s$ _6 LMarginal probability distribution, 边缘概率分布/ q B, {$ l, Y- i: h
Matched data, 配对资料
& Y# c, Q+ t- T Q- yMatched distribution, 匹配过分布; ?! v/ I+ e- v" F* R/ o
Matching of distribution, 分布的匹配. j1 M: [2 ?! d G' N
Matching of transformation, 变换的匹配
1 _: d6 @! I! [$ ~2 W5 bMathematical expectation, 数学期望
% W# e' I& m& A9 i& ]$ N K" |Mathematical model, 数学模型) I& W9 F4 ~3 R# u
Maximum L-estimator, 极大极小L 估计量
; ^- r$ \# u+ W9 Y' eMaximum likelihood method, 最大似然法! K* |) |1 N( Z' H4 b2 F W
Mean, 均数* y3 Z' o" W% w: Q
Mean squares between groups, 组间均方2 n6 w9 Q( l0 T8 Z! w0 n. p
Mean squares within group, 组内均方+ J+ Y: K5 V: W% l! H- I1 ^( ?
Means (Compare means), 均值-均值比较% _ Y z8 X. x* \8 M1 S0 e
Median, 中位数3 x! H5 y- H$ a n
Median effective dose, 半数效量
3 X& j/ R+ C7 h" q5 B) P: K, H' e% _Median lethal dose, 半数致死量
( _0 G; J( z8 D% x T d+ p: d- AMedian polish, 中位数平滑
. A2 k: V' d9 y- Q$ AMedian test, 中位数检验( o A4 H- `/ F7 k6 B
Minimal sufficient statistic, 最小充分统计量
/ r( c7 t' |5 j- n% l( T) v% }+ SMinimum distance estimation, 最小距离估计
1 L/ o6 X: W3 L4 d9 NMinimum effective dose, 最小有效量( a1 Y6 S' N4 f9 M
Minimum lethal dose, 最小致死量
7 m P! B- g$ N- b$ ~( W; t$ MMinimum variance estimator, 最小方差估计量0 n V& ?% h7 |$ c
MINITAB, 统计软件包. i% a+ l- n) k- h- a
Minor heading, 宾词标目0 {& [ [5 V( d
Missing data, 缺失值0 h! m N g/ @: F. m- g6 V0 @
Model specification, 模型的确定
+ f; m+ R1 w: G; CModeling Statistics , 模型统计
8 |$ w' w: ]( `; U, l! {8 E* iModels for outliers, 离群值模型) f9 C! |6 T0 p" q7 Q% m! M5 x0 Q
Modifying the model, 模型的修正6 p( T5 {. B8 b: S
Modulus of continuity, 连续性模
/ d; ~& u) C$ E' M+ FMorbidity, 发病率 7 {- j* e8 R! @- y
Most favorable configuration, 最有利构形& ?1 s3 R/ o# k
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
+ ]: x* E0 b9 Y* |3 G4 lMultinomial Logistic Regression , 多项逻辑斯蒂回归
3 e0 p; F' O9 HMultiple comparison, 多重比较
8 u2 ^& K( u1 m' D7 T3 kMultiple correlation , 复相关
. O; |4 U9 C- t0 t. q3 s2 \9 @Multiple covariance, 多元协方差3 ~, _5 {4 d# `# t3 ^) k3 U
Multiple linear regression, 多元线性回归
* h. [) W8 y4 T* m0 N( ^; w kMultiple response , 多重选项' ?1 J. o& C( F, ` Q
Multiple solutions, 多解
( { \* Z% G) |9 LMultiplication theorem, 乘法定理9 X, w& Q# G( m4 c
Multiresponse, 多元响应8 ?2 a+ K% j$ x& A7 ~
Multi-stage sampling, 多阶段抽样3 _$ J( }3 V3 c4 o! c2 B" `4 ?
Multivariate T distribution, 多元T分布
% x' t% d L' X! O' V) h3 j+ `Mutual exclusive, 互不相容
7 s% V% F$ E, @# O2 x+ A/ BMutual independence, 互相独立* t; A9 |6 I8 s3 s
Natural boundary, 自然边界
3 K/ {, R" w' U0 p, M5 N& I9 ENatural dead, 自然死亡" L& Z8 I; }( Z- v2 N
Natural zero, 自然零
$ C+ A6 \( i. ?! N/ m5 Z) `Negative correlation, 负相关
1 A! n( n& P }4 T0 M) L7 GNegative linear correlation, 负线性相关
: o0 C# J4 @7 D& x1 L+ \Negatively skewed, 负偏
+ x1 i% l7 f+ E9 g% t- }Newman-Keuls method, q检验
1 C. i0 e4 w( N8 Q; N0 L4 k2 ANK method, q检验
5 [& H0 g x$ A( w' l) ?* \/ oNo statistical significance, 无统计意义- k) L9 }2 W* D9 J: J+ [
Nominal variable, 名义变量
, t6 z. G) L5 U$ H3 h4 S& j/ UNonconstancy of variability, 变异的非定常性
" S+ I" _, r) nNonlinear regression, 非线性相关* y/ F8 d/ b. U" _. S6 j; e! R
Nonparametric statistics, 非参数统计' M8 _( U/ [ o: Y1 }
Nonparametric test, 非参数检验
0 X# m% T& C9 }8 VNonparametric tests, 非参数检验
) l8 R- M1 _" Q0 m# B& JNormal deviate, 正态离差
7 b- O8 h0 z5 {- J4 Q. ANormal distribution, 正态分布# w. c4 S( W1 n# p3 i
Normal equation, 正规方程组
" h* _$ p% G' P- @% ?Normal ranges, 正常范围
# D! L- l) _! R5 l+ a6 `! u5 ^Normal value, 正常值8 H: H, |/ l; X/ _1 i
Nuisance parameter, 多余参数/讨厌参数
3 \4 J/ `& C# h1 T3 U+ ^Null hypothesis, 无效假设
8 z, Q- U+ k" ^6 U8 j0 o8 fNumerical variable, 数值变量
- I& K i2 F" U1 ]- V. AObjective function, 目标函数: `, R8 `( c/ W1 Q, {" ?, E
Observation unit, 观察单位
% `* Z) _: U0 l$ B6 gObserved value, 观察值. _+ X- S, h5 M' Z3 m; h. }7 |
One sided test, 单侧检验5 x7 w& G, t2 o. s
One-way analysis of variance, 单因素方差分析5 L; e p- E8 j& I- I9 _( k
Oneway ANOVA , 单因素方差分析
- n3 q# B2 e s6 P; G* ZOpen sequential trial, 开放型序贯设计& D+ H+ G0 W% M3 n G2 ]
Optrim, 优切尾
+ G: F% B; H8 R; F/ z* B8 I" T3 wOptrim efficiency, 优切尾效率
$ G/ A- h6 j% }' O, \ oOrder statistics, 顺序统计量* E8 f, N8 _$ j$ c6 v
Ordered categories, 有序分类
+ v/ [- T/ r' F: S1 `1 |8 YOrdinal logistic regression , 序数逻辑斯蒂回归* X# b' ]3 s2 [( u! f! Z/ ~4 P6 ]
Ordinal variable, 有序变量1 ?/ H8 t/ ?9 ^1 H
Orthogonal basis, 正交基
4 f$ T( ?5 `. V A- }' R6 uOrthogonal design, 正交试验设计
" ?7 L) D- h1 |Orthogonality conditions, 正交条件
) i$ O0 a7 F& M7 h( g; V$ R" rORTHOPLAN, 正交设计 " s' y7 B3 p) Z2 q7 j0 N
Outlier cutoffs, 离群值截断点
5 }8 \! @) g5 `$ x3 f* T6 a- |Outliers, 极端值
) v: e" f4 R% Q; M( O0 ~, tOVERALS , 多组变量的非线性正规相关 p9 @5 q+ f& H
Overshoot, 迭代过度; Q5 }* s$ Z* F( c+ y( B$ h5 w& k
Paired design, 配对设计
6 C5 f2 G m/ H, ~* m" X+ EPaired sample, 配对样本
" z% {+ u/ ~& \Pairwise slopes, 成对斜率
& e) L( K# L$ k2 IParabola, 抛物线
3 ?6 c. G* w3 _6 ]Parallel tests, 平行试验: [3 x1 K d: ~
Parameter, 参数/ h/ @+ p$ `% ?4 C& {
Parametric statistics, 参数统计0 ]3 y) o8 }4 r9 O
Parametric test, 参数检验
" P2 J( W. a3 c% v0 EPartial correlation, 偏相关
! l$ l) Z+ d' e) v3 h! b( Q1 uPartial regression, 偏回归
. p4 @) o& ^7 `: OPartial sorting, 偏排序. e$ f* @$ v" C J
Partials residuals, 偏残差
6 K" F. f; P4 y$ [7 p$ }Pattern, 模式4 r% Y0 \' q. X1 C
Pearson curves, 皮尔逊曲线4 b/ k1 V$ W. s1 `" }
Peeling, 退层
* ?5 Y8 D* I4 APercent bar graph, 百分条形图. {; }- D' d- Z) M) s
Percentage, 百分比
% L5 @0 l5 g7 ~" t1 u# X9 nPercentile, 百分位数) h" n T$ ?0 }0 G
Percentile curves, 百分位曲线! ?0 k( F1 }3 Z# z: E2 F7 c' W
Periodicity, 周期性
0 j, N1 b( G& q, D" ^: U5 o- OPermutation, 排列
2 K- [: x* V9 `; ^. EP-estimator, P估计量
, \% Z M2 \8 G- h E$ lPie graph, 饼图
- I- ^1 K' c& V. [Pitman estimator, 皮特曼估计量% J" L" e, A3 l! M; N, X" m) D4 f
Pivot, 枢轴量
5 D! Z+ I! z$ l# o1 p5 W2 u+ rPlanar, 平坦3 q% I1 `/ k+ c) z
Planar assumption, 平面的假设6 D& M; J+ e$ K8 Q4 T
PLANCARDS, 生成试验的计划卡
+ A. }2 O6 y fPoint estimation, 点估计0 r+ K t* c# E9 c, C. U( G2 R4 c
Poisson distribution, 泊松分布
. A% ^ V8 s$ X, l+ o# z3 wPolishing, 平滑9 O8 z' u) w. O1 R x; L' E' b) J
Polled standard deviation, 合并标准差
9 u% Z2 F8 r+ ?1 z$ c0 I9 u5 B1 K cPolled variance, 合并方差
+ T. b- O4 h) T6 `; `% H0 m3 rPolygon, 多边图' V( c6 C# ^) J1 x* S( j- J* o
Polynomial, 多项式9 @" B1 c) n' W9 C K3 B% \ e
Polynomial curve, 多项式曲线, B+ n/ N0 r j5 e
Population, 总体
9 p8 ?; n7 C* L) M5 U8 iPopulation attributable risk, 人群归因危险度" ~: k0 @$ C: }% T! Q6 ` u3 F
Positive correlation, 正相关: W8 A. `% K7 G6 s7 `" S0 L
Positively skewed, 正偏& B" R/ D0 d" S D3 C
Posterior distribution, 后验分布) X$ K3 j5 g2 y1 H% r6 v. [
Power of a test, 检验效能5 @" c+ Y2 a3 O) r, _9 ~
Precision, 精密度! u; n! E2 M. d3 i
Predicted value, 预测值
; C5 B/ Q) [" [Preliminary analysis, 预备性分析
% m. d0 ]. l+ l* NPrincipal component analysis, 主成分分析
+ Y3 }- u& B1 ?; q2 mPrior distribution, 先验分布8 o7 T; I4 S$ g; R
Prior probability, 先验概率; d% H* v4 c- E
Probabilistic model, 概率模型
2 L0 V; _( j$ y& fprobability, 概率9 f$ q3 y; j. |' O( o% L0 U9 \
Probability density, 概率密度) ~& O n! \5 ^, ~8 p+ u
Product moment, 乘积矩/协方差2 w1 P4 c. p# \# \0 X- S
Profile trace, 截面迹图
: U/ n: {4 u/ y8 p+ _$ K" l- wProportion, 比/构成比( O; W: u& R: ^- i. z1 x
Proportion allocation in stratified random sampling, 按比例分层随机抽样8 F8 u {$ d. b' z
Proportionate, 成比例% S, L0 o/ y" \) J" Z/ Q
Proportionate sub-class numbers, 成比例次级组含量) N1 M5 Z- U. z q$ R- m
Prospective study, 前瞻性调查
{$ i' f$ `% W" b( kProximities, 亲近性
4 ]* {6 q: W& R3 O6 g+ N3 z9 kPseudo F test, 近似F检验1 g: q5 d) x. a$ S* M
Pseudo model, 近似模型
; g2 K1 l0 W6 k; G! QPseudosigma, 伪标准差
; N3 t6 F# C5 l* f; APurposive sampling, 有目的抽样
+ P+ X4 c8 b. a/ N8 F: @QR decomposition, QR分解
- Y, i. P7 S' k. b- j- O5 u. NQuadratic approximation, 二次近似
% S% u5 g8 M0 t6 O- j9 } J9 v% YQualitative classification, 属性分类: J, R" ?8 P2 E' U
Qualitative method, 定性方法
7 z8 S7 v6 a/ o1 AQuantile-quantile plot, 分位数-分位数图/Q-Q图/ {1 N' y/ C( M5 v6 C9 k
Quantitative analysis, 定量分析& @5 T% q1 v# q
Quartile, 四分位数& V" l% u. h6 N! `; u
Quick Cluster, 快速聚类. X. P i# W9 U7 {# B
Radix sort, 基数排序
' m M8 g! }7 |) z! y/ P q/ qRandom allocation, 随机化分组8 g$ N/ ]0 c' z j' g: Y, h
Random blocks design, 随机区组设计8 F* q. R: b9 a- C5 v3 T; A
Random event, 随机事件
$ C2 q# g- z3 g( r( xRandomization, 随机化6 Z, c( e4 R# S, { n2 a
Range, 极差/全距
( j! L4 o! \# Z5 M5 nRank correlation, 等级相关
& d! `7 M9 s9 A- i; E" B' ^Rank sum test, 秩和检验
b$ a' d( c: |$ b9 CRank test, 秩检验
0 }0 z( G: _# N9 NRanked data, 等级资料
4 U- Z' V) U, w+ M' {Rate, 比率
4 m9 T- P0 H0 m- tRatio, 比例% L6 S+ [' Z1 S
Raw data, 原始资料7 E; R. j9 s4 [: G. O
Raw residual, 原始残差
$ j8 U6 T5 o! l. ]$ ZRayleigh's test, 雷氏检验
1 d3 p& h% Z- ^# r9 v* E, q) QRayleigh's Z, 雷氏Z值 2 P+ J) Z( d1 l' v4 r# ]( t% i2 v
Reciprocal, 倒数
3 z) f) b. G- DReciprocal transformation, 倒数变换
( S) b1 @4 A+ s& wRecording, 记录
7 E3 Q. R! A. K0 R. URedescending estimators, 回降估计量3 P% K1 h0 ?1 ~0 P# u, [' g
Reducing dimensions, 降维6 h% ~1 Q; n' ^7 V# x
Re-expression, 重新表达' |2 P' u1 t- h1 M8 ^; U
Reference set, 标准组
* F; z' `. ^/ S8 _0 w8 URegion of acceptance, 接受域; X' o8 G( x: c- o8 E( c# e
Regression coefficient, 回归系数& J3 c0 y! F p" w/ {0 P S
Regression sum of square, 回归平方和
% I z$ D2 T6 T6 GRejection point, 拒绝点0 |% E: V9 T! h; c+ v+ V5 Y
Relative dispersion, 相对离散度
& V* j& H1 J' k2 ^% V, @( W/ pRelative number, 相对数
2 T+ `/ ?. d+ k8 l) Z" m% {; kReliability, 可靠性! e0 F' i" X3 v4 X
Reparametrization, 重新设置参数1 }/ \/ G3 d/ n' M C) A
Replication, 重复
; E. i/ d! `& A& y XReport Summaries, 报告摘要; D' v3 y7 p2 s( P% m
Residual sum of square, 剩余平方和
; T, m+ |% q: m- R- bResistance, 耐抗性2 @. Q$ H; q3 m! m6 q& t
Resistant line, 耐抗线) K, B O: n/ z7 a0 M6 @
Resistant technique, 耐抗技术/ |5 O8 ]8 s/ V9 F% @+ K
R-estimator of location, 位置R估计量
! E# _+ i6 [4 v$ C9 r6 E$ gR-estimator of scale, 尺度R估计量! G l7 o4 c2 j5 l7 b# e- p# g
Retrospective study, 回顾性调查1 }. o4 Y; p9 y6 J
Ridge trace, 岭迹) S& {9 T7 |4 C8 i
Ridit analysis, Ridit分析
0 l& M* e! h! r1 [- W' vRotation, 旋转# V5 [" J3 |# L( I
Rounding, 舍入( B2 b1 J$ V! ]' B3 W! L' p1 N( `
Row, 行) M' t& ? G3 u3 [, L: I7 r* i
Row effects, 行效应
. {, B2 K# L6 |2 f) V3 v/ r% SRow factor, 行因素
9 U% s7 k) J$ @9 u, ORXC table, RXC表
, I D: k* D/ \* P% k; USample, 样本, k ?3 q; C" s7 O
Sample regression coefficient, 样本回归系数
- w8 K8 |5 ?% ~Sample size, 样本量
, M2 C" n# ]9 g( wSample standard deviation, 样本标准差& M9 q, \, o+ C* M( \
Sampling error, 抽样误差
+ _" q' D* Z5 \9 d+ Q$ WSAS(Statistical analysis system ), SAS统计软件包" n T1 e b8 h
Scale, 尺度/量表
2 I5 g. z O1 oScatter diagram, 散点图
9 k* e0 O+ k' [Schematic plot, 示意图/简图2 \2 o2 Z5 x" {5 R
Score test, 计分检验
3 y- _; e( O1 C& ]' JScreening, 筛检
8 \8 W- e6 N+ x$ Q* V; D& o0 k: j- Y% _SEASON, 季节分析
6 i2 p7 Z7 q2 m6 DSecond derivative, 二阶导数
% i9 {6 q0 ?8 l$ b. HSecond principal component, 第二主成分# u) `$ @: p1 [" Z! D4 @
SEM (Structural equation modeling), 结构化方程模型
3 A! L2 F+ S" U9 b3 U4 \Semi-logarithmic graph, 半对数图" F/ k% P V" I* f# O8 l
Semi-logarithmic paper, 半对数格纸0 D, b1 [& w2 v* ^6 V7 j9 f' H8 k
Sensitivity curve, 敏感度曲线
' T) v5 L A, w3 m: e V6 ^Sequential analysis, 贯序分析
3 H' S5 k& h6 O1 ]1 [Sequential data set, 顺序数据集- |7 R2 O( m( ?. B! E' `) x9 [- f
Sequential design, 贯序设计
8 P K9 p- b) m2 z# xSequential method, 贯序法
Q( G6 b4 I. `# ~% ySequential test, 贯序检验法
z: J4 y" W. c: u- n6 USerial tests, 系列试验* C, Q* z1 b; e% f$ q2 V( _9 E4 h
Short-cut method, 简捷法
0 G- X' Z; x* [9 W5 XSigmoid curve, S形曲线
0 x2 K; Y7 {" RSign function, 正负号函数
6 D" D, p' v# r! r; }Sign test, 符号检验
) o5 I, f$ H$ q( vSigned rank, 符号秩0 X7 A: h: H5 d4 J
Significance test, 显著性检验7 n/ g& c4 S w/ X* q a6 X4 y( g
Significant figure, 有效数字1 }& Z; w4 T& V/ b3 p% M3 f
Simple cluster sampling, 简单整群抽样
" T8 i7 }0 H7 E3 ]9 O# G# MSimple correlation, 简单相关; \) ^7 Q3 k: S+ ?
Simple random sampling, 简单随机抽样* [7 d1 ?+ N! ?& s+ c/ U: G& D
Simple regression, 简单回归6 J- ^, ]. Q; m
simple table, 简单表* E! q) O( C5 U) o3 B# F
Sine estimator, 正弦估计量
, I& q+ q- u" L7 i1 P+ I, T7 K% ?Single-valued estimate, 单值估计# ?* z0 o v; I( a
Singular matrix, 奇异矩阵
R8 f" I, i2 kSkewed distribution, 偏斜分布
* W: ]8 [; X R+ I9 A+ J& o8 cSkewness, 偏度
) m5 s: e3 Y( M* u$ b gSlash distribution, 斜线分布) l$ t5 H. X( R( _
Slope, 斜率1 ~3 k) j% {6 |! A+ e
Smirnov test, 斯米尔诺夫检验
4 x* d- A( D7 _Source of variation, 变异来源
- D" q: ^$ W2 mSpearman rank correlation, 斯皮尔曼等级相关) ?7 `4 n$ X& R# D: R
Specific factor, 特殊因子
6 e3 s1 q9 L6 u& c4 `+ @Specific factor variance, 特殊因子方差 ? S$ k% |! B1 S+ `' a! ^
Spectra , 频谱: U; o3 o' e; ?6 ^7 z' v
Spherical distribution, 球型正态分布7 N, j; n' }4 {8 k9 r7 |
Spread, 展布- p" L7 q! k+ G2 c+ S; [( I
SPSS(Statistical package for the social science), SPSS统计软件包& c' w1 x- e" f4 T0 y$ |/ k
Spurious correlation, 假性相关8 ?9 a& q& i" l3 X
Square root transformation, 平方根变换+ [+ o7 }" ^5 M4 j) d
Stabilizing variance, 稳定方差
& s* e. c) h+ O0 CStandard deviation, 标准差
& }- q3 F" n0 @% B8 oStandard error, 标准误# T9 ?! v, r( ^3 M: @) O6 l* ?
Standard error of difference, 差别的标准误
/ L, B* w/ {6 c: OStandard error of estimate, 标准估计误差
, F4 I1 ]# Q- w+ Z* o' kStandard error of rate, 率的标准误
! u* `% N4 p" ~ {( xStandard normal distribution, 标准正态分布
' e$ i$ c* d/ }+ eStandardization, 标准化5 P* o y/ Q+ h, F8 `
Starting value, 起始值* e' Z1 j6 q# B1 D, d
Statistic, 统计量0 w7 o7 N- C* G9 A9 i
Statistical control, 统计控制$ ]4 q: @1 c9 X% P! Z- Z
Statistical graph, 统计图
' A4 p$ k! Y( B9 B7 l( }Statistical inference, 统计推断
$ K6 } H- v+ p* w5 Z9 IStatistical table, 统计表
1 M) Q6 \4 j, Q9 b! N& ySteepest descent, 最速下降法) }" L3 r0 V& m: o( O& b
Stem and leaf display, 茎叶图
, u# t) m2 ^/ R+ W. \' ^2 [- OStep factor, 步长因子
- g4 j, }4 |& q. D1 T1 wStepwise regression, 逐步回归! @5 Q/ R& C* A
Storage, 存' A* }0 s8 Q2 j7 n5 _7 T0 O" d' D i
Strata, 层（复数）- ^ H$ K9 D: ?% W
Stratified sampling, 分层抽样
: c" `, @) W$ b! u7 P6 R, AStratified sampling, 分层抽样! \5 z. E5 m! B. M! K# J/ [3 s
Strength, 强度# t' X U8 ^& j9 U& l$ `
Stringency, 严密性
6 t) Z3 i6 Z+ O b% j o" sStructural relationship, 结构关系$ N" G7 x4 Q3 y6 s) E2 o. L
Studentized residual, 学生化残差/t化残差
& Y; r2 ?6 D0 u- ~7 K) _; `Sub-class numbers, 次级组含量2 H" x$ T1 ]& C5 C* |& E2 g2 ?
Subdividing, 分割% V' U- q7 P1 u L- W3 w
Sufficient statistic, 充分统计量
7 @) d- z- O9 ZSum of products, 积和; I( e/ V" u1 H$ U
Sum of squares, 离差平方和
0 t, P, j6 r+ K( X: k5 F: ISum of squares about regression, 回归平方和5 N; p/ G- [6 d% ]. _8 ^
Sum of squares between groups, 组间平方和
2 \8 G& b4 U/ ]4 ]$ XSum of squares of partial regression, 偏回归平方和
( L2 ~! z- s( E: i' n8 nSure event, 必然事件% u+ \! U3 g3 I8 t& i1 Q @
Survey, 调查
- }- j4 N' v" o0 e8 [8 B8 |; {4 Y% iSurvival, 生存分析& Z) W% y$ o& ?8 t: ^- [( r( c) S
Survival rate, 生存率, s0 E& K3 @4 A5 E( }3 s! i
Suspended root gram, 悬吊根图' h1 L _3 E. b8 Q
Symmetry, 对称. |8 e; Y; _" f! q
Systematic error, 系统误差
4 b z. J0 s' V4 c S7 V. n+ E# ySystematic sampling, 系统抽样
2 z5 ~+ A, D8 I. L6 Q9 UTags, 标签4 ~& U" M/ u1 |+ d
Tail area, 尾部面积3 p8 O( O# w2 t
Tail length, 尾长+ F% f/ S9 N* M9 i# o
Tail weight, 尾重. G5 n C( j# O: H c+ V% U
Tangent line, 切线
5 f" t! z- w: U5 Q6 [+ w! {" x) k! Y7 BTarget distribution, 目标分布
+ r; ? j% b( s, s* v! XTaylor series, 泰勒级数
( f; r/ ]% o: DTendency of dispersion, 离散趋势
- b; N% y1 N Z8 k. uTesting of hypotheses, 假设检验
6 f% c: U- I) r+ n# zTheoretical frequency, 理论频数
* Q% Y4 ^6 i" ~) G4 q* RTime series, 时间序列
5 Y' v4 o" @: hTolerance interval, 容忍区间; ~4 a3 w1 ^! i% t$ L
Tolerance lower limit, 容忍下限
. c7 J& M' A7 v" q$ t& ^Tolerance upper limit, 容忍上限
4 Q; h9 k& ]6 |! E* ^' hTorsion, 扰率+ j7 ?" }' w& V. @- \+ l0 S
Total sum of square, 总平方和
7 i |3 n9 ` E. N$ wTotal variation, 总变异4 L! l3 j5 }4 F0 Y
Transformation, 转换$ ]7 A1 E' H. g+ w/ M- n. z7 K
Treatment, 处理
% n4 {( w7 V0 t* N1 n8 K% @; G- MTrend, 趋势
" a- S8 p; K) |2 j9 KTrend of percentage, 百分比趋势7 S5 b8 Q/ Y) ~1 b
Trial, 试验
; L0 n- S0 Z5 v1 F ^: ]* k+ YTrial and error method, 试错法
' x+ F- S. n( i4 x' m3 D' v9 eTuning constant, 细调常数
& \& Y) { U P; GTwo sided test, 双向检验! D2 G# h9 A" ^ ^3 Q! t4 V
Two-stage least squares, 二阶最小平方2 m5 `9 Y/ M+ A" z, X" w$ a
Two-stage sampling, 二阶段抽样& P' h, E( Z. E
Two-tailed test, 双侧检验
5 _7 r! I( g8 A; QTwo-way analysis of variance, 双因素方差分析
v& O$ h2 `. C, J4 \% nTwo-way table, 双向表9 O& b1 D1 h! T7 u( \1 T
Type I error, 一类错误/α错误
5 ]" l& b8 q; A8 ]Type II error, 二类错误/β错误
0 ~9 o6 V/ X; M7 j' C* e9 R/ CUMVU, 方差一致最小无偏估计简称
( y% H7 _! y* Q- Y5 |Unbiased estimate, 无偏估计
, d( {4 m% Q, U5 H2 ^9 {Unconstrained nonlinear regression , 无约束非线性回归# L6 `# P& t8 n3 I8 _0 J1 x/ [
Unequal subclass number, 不等次级组含量
& W7 ?3 c7 j2 E( \* N+ JUngrouped data, 不分组资料* m3 W/ a" N. I7 J: M! i& e" Z6 e
Uniform coordinate, 均匀坐标+ t% n2 ]- B. \7 f$ d4 k: e
Uniform distribution, 均匀分布3 ?2 I, z7 X7 Y( {3 C
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计* @ y2 T# w u/ }( D8 Q$ ~2 y
Unit, 单元( H+ |! Y! \- Q* H+ }8 Y
Unordered categories, 无序分类
& m( J f* H1 H2 FUpper limit, 上限9 V; M+ G" U- r. J7 j: C
Upward rank, 升秩+ Q8 Z& W$ ~5 A% g4 @0 a. G- d
Vague concept, 模糊概念: s( T6 Z+ H' J& i, W, T( x
Validity, 有效性" }$ L+ |4 B- g- D
VARCOMP (Variance component estimation), 方差元素估计
- Y6 N; [7 @6 a( t8 }# C1 fVariability, 变异性 E2 e s2 v9 I. ^( h
Variable, 变量
$ j( B2 V7 H5 `; F$ |+ \Variance, 方差% H4 |5 c" w" U6 [' A( D1 n9 `6 B
Variation, 变异' c) c) P0 f9 g" B7 [3 z- F
Varimax orthogonal rotation, 方差最大正交旋转
8 J9 {& v2 k, O* A0 q/ l5 yVolume of distribution, 容积% t# p/ q8 d' u4 f; E/ v
W test, W检验/ `! y% ^) G$ E" m$ z1 Y
Weibull distribution, 威布尔分布; b/ W$ I7 u( z3 y, j2 @
Weight, 权数: I4 P7 n4 {( ]% m! u2 {6 {
Weighted Chi-square test, 加权卡方检验/Cochran检验4 y; {0 P( e1 K
Weighted linear regression method, 加权直线回归
1 ?1 H6 ^. F* I7 NWeighted mean, 加权平均数# Y$ }. `& @; X" `4 b
Weighted mean square, 加权平均方差
" H @! F7 H; Y! UWeighted sum of square, 加权平方和* f3 F( F2 E. h' E" b
Weighting coefficient, 权重系数 d9 i3 ?7 h U8 W0 u
Weighting method, 加权法
3 n: _5 q, L6 ~5 A n( @$ N. gW-estimation, W估计量7 Y+ Y7 P8 C6 N% n# Y# F5 E
W-estimation of location, 位置W估计量4 y0 e+ K+ e; k) w
Width, 宽度2 Q- o# s1 L/ u3 V. v. W
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
% J S5 N% U6 }2 w) OWild point, 野点/狂点, ^. S! B5 h& ?8 C5 W! \7 a
Wild value, 野值/狂值2 ]) g! A) I: c. K7 t2 O3 C" I+ l
Winsorized mean, 缩尾均值( N3 A9 {( I. X: a, \5 J
Withdraw, 失访 ( Z& p3 i5 M r7 I6 O- F5 g8 @
Youden's index, 尤登指数
/ V; R9 c1 P& J6 U3 u5 \* _+ rZ test, Z检验
2 S! e" c: k* C' Q6 |Zero correlation, 零相关$ x: D: K7 w7 t! W# |. y
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
