|
|
Absolute deviation, 绝对离差& X9 b. j4 r, \5 [' P+ V& ^
Absolute number, 绝对数* Q. y' [1 o' f. k! A" N
Absolute residuals, 绝对残差
7 ]. Z3 I/ c0 \0 Y: ^0 ^- X. X" N. ZAcceleration array, 加速度立体阵
9 ?" J; s8 ]' |7 AAcceleration in an arbitrary direction, 任意方向上的加速度
7 R: Z; L7 k$ S1 W7 T) HAcceleration normal, 法向加速度9 e( [ V8 h- N; @6 j
Acceleration space dimension, 加速度空间的维数
1 e( ]* X% E7 ~% W! c! u0 GAcceleration tangential, 切向加速度* z" Y, a' U# ~% z( I
Acceleration vector, 加速度向量" Q2 ~. B; V4 I
Acceptable hypothesis, 可接受假设
: ^5 J5 I$ [' C" n( X- b7 tAccumulation, 累积
8 z' z, ^( h$ f# _Accuracy, 准确度
: o+ i8 r4 k; g# V' q7 Y6 u; MActual frequency, 实际频数+ `. |, M5 _0 K' q/ b
Adaptive estimator, 自适应估计量6 |* c( Q- q# W9 M
Addition, 相加# V0 }8 O- ?. W1 E
Addition theorem, 加法定理6 c# q) n7 T/ j: k% H
Additivity, 可加性
, e( W0 c: z% G6 W; I8 ?$ y* XAdjusted rate, 调整率8 b: z* }) @- v
Adjusted value, 校正值$ G2 `3 `% l$ |4 b4 \( Z! ?& x
Admissible error, 容许误差
$ H7 O @" l+ A b4 P/ `Aggregation, 聚集性
. d, B4 b- C' QAlternative hypothesis, 备择假设8 s7 `. T: {) H) [8 d, ~
Among groups, 组间; ?1 l2 R# ~- e
Amounts, 总量! y7 A* }: \: m( E; b0 }: m
Analysis of correlation, 相关分析9 ]1 d4 u* l: U b( L3 h
Analysis of covariance, 协方差分析
) b6 W2 E: C$ A" J$ g8 sAnalysis of regression, 回归分析
1 N; E5 F' p) |$ q7 h- ?% V7 gAnalysis of time series, 时间序列分析5 q* A0 I3 v% P
Analysis of variance, 方差分析- y* V9 O$ u; e$ M
Angular transformation, 角转换; }% D% v) F! a( P) `* T& U
ANOVA （analysis of variance）, 方差分析; C3 x0 s6 Q7 N& ?
ANOVA Models, 方差分析模型
( F& M- a3 c5 ^$ E) b4 _8 r& W( WArcing, 弧/弧旋0 c4 R4 Z+ W; `1 ?3 L6 v1 Q9 J/ |
Arcsine transformation, 反正弦变换: o' t# O. b i: \: O8 C. h; J
Area under the curve, 曲线面积; d. }, x: U6 e5 l) m6 n
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 5 E+ X/ \0 T+ y" f& c
ARIMA, 季节和非季节性单变量模型的极大似然估计
2 o$ P6 Q/ K1 C9 M9 ^' Y2 O/ f% H/ y( bArithmetic grid paper, 算术格纸
9 n* Q S0 n/ ]. ]0 G6 zArithmetic mean, 算术平均数: @; j+ W i$ k7 y7 K0 Y. w
Arrhenius relation, 艾恩尼斯关系 o# a) I6 p8 }/ i: U8 u% s
Assessing fit, 拟合的评估
% q6 R/ B. ]1 Q+ ^2 WAssociative laws, 结合律
& ?# ^: {! w2 b/ D' A' }+ nAsymmetric distribution, 非对称分布" @- |+ } `* @) O) q7 F; A% W
Asymptotic bias, 渐近偏倚2 ~) V D% P# O
Asymptotic efficiency, 渐近效率
0 s- a+ r7 O: s5 ?Asymptotic variance, 渐近方差
( Y. l" U( R8 K0 }% q" S# o: ?; ]Attributable risk, 归因危险度7 @5 S4 v" D4 { A6 V) f
Attribute data, 属性资料1 j6 G6 g* u7 n% W1 b: }
Attribution, 属性
& F* @' c& t& hAutocorrelation, 自相关
& |) r/ W& v; r" hAutocorrelation of residuals, 残差的自相关
1 L4 I6 p. w4 y; o0 J, p# YAverage, 平均数# {( v n. ]$ P% ?5 w+ W
Average confidence interval length, 平均置信区间长度5 c8 u4 i; F+ M8 T% o
Average growth rate, 平均增长率
, {( \" {4 T4 @" rBar chart, 条形图
) F/ R7 `% F& M1 E4 G- W1 _* D- ]Bar graph, 条形图
1 B' N5 ]: Q$ u& M9 L! {, DBase period, 基期% u( x' y9 ^* z) }5 Z$ e5 X( ]: }$ m
Bayes' theorem , Bayes定理+ x+ L0 n& n @% h
Bell-shaped curve, 钟形曲线
) S) X) D: Z$ ]! d- YBernoulli distribution, 伯努力分布
, z6 T& p6 K; W; cBest-trim estimator, 最好切尾估计量
0 G: Z0 }9 X1 a- XBias, 偏性
+ K' B X; V& w- OBinary logistic regression, 二元逻辑斯蒂回归
- ~9 r7 d1 g! ?6 Z1 eBinomial distribution, 二项分布6 `4 `4 ?7 |% F
Bisquare, 双平方/ }/ b. x& o9 K( Z1 ~
Bivariate Correlate, 二变量相关
% [( C& `9 S( M6 [Bivariate normal distribution, 双变量正态分布! r; D" `6 p! S+ w* e( c# m
Bivariate normal population, 双变量正态总体2 I2 H% o/ U, j9 t% g; Q
Biweight interval, 双权区间
3 E/ n! a; w2 I# ABiweight M-estimator, 双权M估计量
- Y& w) L, k7 j; R6 iBlock, 区组/配伍组
8 e) C; J# [% \7 z1 DBMDP(Biomedical computer programs), BMDP统计软件包" M- u- v H& d5 a+ p( `- I+ d
Boxplots, 箱线图/箱尾图
. A2 E( j% }- ^( |3 MBreakdown bound, 崩溃界/崩溃点9 E! {- B( K8 K% E. Z
Canonical correlation, 典型相关
% r0 G$ c: Z6 kCaption, 纵标目
+ j, _9 ]7 b: Z6 q4 p( xCase-control study, 病例对照研究3 h1 |) Y2 [8 ?% D! w( V$ u
Categorical variable, 分类变量- T- K! ^1 `7 u5 W7 A
Catenary, 悬链线
/ o0 g4 z d& l8 QCauchy distribution, 柯西分布
6 u9 p) `1 e/ J4 ^, A5 \2 {" ~Cause-and-effect relationship, 因果关系
' f1 T$ E0 l, _4 q ~9 J( XCell, 单元
9 Z( g( E% _$ [; z6 Z" L+ ~& w# |Censoring, 终检
- A M, t: ?7 g& X) L3 [' ^Center of symmetry, 对称中心+ n$ k0 j0 n! N1 V2 f* |2 q
Centering and scaling, 中心化和定标, A7 A% q T; E* M, E' k, s4 F! p
Central tendency, 集中趋势. O; J& O% H/ q- {3 v
Central value, 中心值
" S# S$ _( v( w2 t7 D" b7 _CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测7 z* H$ b$ k- {9 |8 @
Chance, 机遇
" R6 S2 Z0 n0 o: ~' R3 b; Z+ H# nChance error, 随机误差7 ]) ? g. a( |( y! e- r
Chance variable, 随机变量
' W' {( A0 W# t( K/ p3 S+ mCharacteristic equation, 特征方程" ?5 w0 ~; w& D( g0 Y4 |" ~
Characteristic root, 特征根
4 c$ C! Q9 t( K# \! Q$ YCharacteristic vector, 特征向量2 I2 Z, F/ ^% k% H ]2 r
Chebshev criterion of fit, 拟合的切比雪夫准则
2 n/ V0 Y4 y* D% t1 S/ l* EChernoff faces, 切尔诺夫脸谱图; K. t8 T1 R- r8 t M
Chi-square test, 卡方检验/χ2检验
' G U. n# B$ G; vCholeskey decomposition, 乔洛斯基分解
1 g* y0 k$ k# K' xCircle chart, 圆图
# }& o7 \. P1 _3 ^. G+ }. }Class interval, 组距' N* v6 P# u* Y( |8 U
Class mid-value, 组中值, z8 t3 J5 l1 A) }: q5 Y
Class upper limit, 组上限
+ o' E3 t2 [- i* i7 g8 ~Classified variable, 分类变量4 A7 Z3 G2 ]$ y Z5 Y
Cluster analysis, 聚类分析% m/ k3 v* x$ u
Cluster sampling, 整群抽样: V. m# v) O8 @$ S; _/ z) _7 F
Code, 代码# E, X) V, c' |: o2 r/ P
Coded data, 编码数据
0 h0 I. J( J& fCoding, 编码# X, W) B6 S, {- ~- F8 p: B* T2 D% ~
Coefficient of contingency, 列联系数
) a3 U2 b0 p. OCoefficient of determination, 决定系数- j% v- y9 S! `- \; I
Coefficient of multiple correlation, 多重相关系数
8 n; U: u1 {/ pCoefficient of partial correlation, 偏相关系数
- Y$ ?1 y+ ]$ i1 ACoefficient of production-moment correlation, 积差相关系数
/ B1 `- i: E: \8 J* _" ~, kCoefficient of rank correlation, 等级相关系数
$ E& G2 `( D9 p9 p9 X, PCoefficient of regression, 回归系数
' W4 X6 t' I7 @, T/ OCoefficient of skewness, 偏度系数& `& z7 a3 L6 Y. }
Coefficient of variation, 变异系数# V" S) b) r9 q& x; y
Cohort study, 队列研究
0 @6 R$ H- Y( [8 v" M' wColumn, 列
2 W8 G& p! ?+ ~7 vColumn effect, 列效应
5 H( U( G# A4 w( XColumn factor, 列因素 Z6 N; |" T5 P
Combination pool, 合并
9 B( E/ O! ?: K6 aCombinative table, 组合表
6 y& t# B+ A# pCommon factor, 共性因子0 h! L, }% M. g8 N
Common regression coefficient, 公共回归系数
S+ W O2 E( r$ W3 X; s* ECommon value, 共同值
& G0 V( E+ }: K9 Y3 \Common variance, 公共方差
! M- [0 O+ B% E, p4 b9 Z) p0 F; oCommon variation, 公共变异
$ V, q. r: x* e. h ICommunality variance, 共性方差2 |; D z+ M: {
Comparability, 可比性1 B3 G/ ]5 n) M9 A
Comparison of bathes, 批比较
! j9 Q3 y( c* _; JComparison value, 比较值
' ^9 r. @6 c6 C4 `! _Compartment model, 分部模型9 {% ?( A6 g/ c3 ]/ ]7 E F
Compassion, 伸缩. f% n$ g1 {# k a* {
Complement of an event, 补事件
* A) J- a8 |, j0 ?& b8 hComplete association, 完全正相关' t& X" x, X- q7 t
Complete dissociation, 完全不相关+ o2 Q* @7 v+ s) T' P
Complete statistics, 完备统计量& D) b) D" _. u0 W
Completely randomized design, 完全随机化设计4 G( W' `2 }8 T) X0 T* }6 M, f
Composite event, 联合事件% w+ Y( m! R# m+ l0 L/ |( X
Composite events, 复合事件: D2 V: z& Y2 B( {. }4 H. t
Concavity, 凹性
, @) s. j+ T2 EConditional expectation, 条件期望7 `; K+ ^" x8 A( K
Conditional likelihood, 条件似然4 C* \3 b8 W- ]( `
Conditional probability, 条件概率: [- A q. E/ D2 N
Conditionally linear, 依条件线性
/ w1 h$ Q) ^/ M `6 s" mConfidence interval, 置信区间
' D% Z; M3 f; N, j/ S' X3 U( ^Confidence limit, 置信限2 F* C$ z5 }" S/ d5 s0 G2 e
Confidence lower limit, 置信下限) D' T& B! {1 H: u( H7 |
Confidence upper limit, 置信上限4 z" l1 O: n# E* U: J
Confirmatory Factor Analysis , 验证性因子分析7 U4 d- Q0 I6 [8 k% m0 j
Confirmatory research, 证实性实验研究. L* O+ g- m: i
Confounding factor, 混杂因素
8 u' S+ K6 [: v$ Y: ]0 s sConjoint, 联合分析
* b9 x7 m1 M7 JConsistency, 相合性8 [1 a0 T" R7 v
Consistency check, 一致性检验
" X$ d6 T# M% J9 ], F' eConsistent asymptotically normal estimate, 相合渐近正态估计( M2 M# z6 z# _7 {9 U1 P
Consistent estimate, 相合估计% m3 b* K2 s2 ~3 [" b
Constrained nonlinear regression, 受约束非线性回归& I% p- w& e @7 k3 w+ U$ L8 {
Constraint, 约束
3 a1 v0 \- n4 n, e2 UContaminated distribution, 污染分布, R! z7 E# b: i. f7 @
Contaminated Gausssian, 污染高斯分布
7 | d" Y- s- ^$ oContaminated normal distribution, 污染正态分布
# I% v# }4 B2 qContamination, 污染, {1 |- L; o" j- n: d( `* M( k- j
Contamination model, 污染模型5 v+ S+ i! H+ J% o% B" R( `3 x$ I
Contingency table, 列联表1 q& K- ?2 r+ b- H O
Contour, 边界线2 d9 t @" u* v& T* y
Contribution rate, 贡献率0 ] t2 n8 I( H5 r
Control, 对照" `; b" t' Q/ L9 q" `7 D
Controlled experiments, 对照实验
8 K" H# U4 `. y7 a# Q9 n9 EConventional depth, 常规深度: Y/ E3 I9 [+ m9 E9 ]" D
Convolution, 卷积, o4 R" P4 k$ ?1 N6 g0 f
Corrected factor, 校正因子1 w5 n, b( t( Q4 W. Q& @3 R' I
Corrected mean, 校正均值
1 z! h) \. h1 SCorrection coefficient, 校正系数
8 }5 V" p r5 @2 RCorrectness, 正确性4 ^8 d& R/ S2 _# H, x N
Correlation coefficient, 相关系数& P2 |4 A- r1 t# v
Correlation index, 相关指数
z3 x" I9 C& B% FCorrespondence, 对应* M* e8 q r; m8 D6 u( z1 i. q) J
Counting, 计数
/ R" ~, _; U' e( M6 Z2 Y3 ACounts, 计数/频数& i! o9 A% g) t4 y
Covariance, 协方差4 K# U- s% w3 j; L: e& U2 o
Covariant, 共变 ! D- W( }/ D N5 @
Cox Regression, Cox回归
4 a7 r3 V3 J0 L- ^8 ]' @5 r E9 OCriteria for fitting, 拟合准则5 O6 s0 b* K) C
Criteria of least squares, 最小二乘准则, w& A# W" w: R5 K& Z+ r' M
Critical ratio, 临界比
7 i$ I1 K b4 t7 J9 _Critical region, 拒绝域# D8 r, z3 ^9 N7 |$ Z! Q2 M
Critical value, 临界值" L" H: q! p# L5 m
Cross-over design, 交叉设计- X3 j' ]& k3 f
Cross-section analysis, 横断面分析
+ H. i9 i p" C" h6 B5 L6 BCross-section survey, 横断面调查
5 u& a& L1 h& d6 YCrosstabs , 交叉表
: E. @4 |4 ~$ g/ L- m9 @Cross-tabulation table, 复合表
1 _3 P0 D8 T/ ZCube root, 立方根7 C' y1 y5 y1 ]+ J' I9 I. M: p+ `
Cumulative distribution function, 分布函数
! t8 ]5 @ O0 \- u4 q# q& hCumulative probability, 累计概率5 J9 Y# h9 g* x$ N9 w
Curvature, 曲率/弯曲
" D& I% y6 e' bCurvature, 曲率
' o+ ]% }% j% p, |Curve fit , 曲线拟和
. x7 Z5 G% ^( GCurve fitting, 曲线拟合
. t: R9 d6 ]: M$ qCurvilinear regression, 曲线回归. ~: ~) i" d' D" w2 |1 K
Curvilinear relation, 曲线关系
8 S+ h! {: h5 F' _Cut-and-try method, 尝试法
( T- J" @5 B, pCycle, 周期9 P; R* ^5 u% o% q: p# B
Cyclist, 周期性
! }- r( @9 z+ A1 f5 MD test, D检验
( h. [/ D a; Q8 G8 Z: dData acquisition, 资料收集
( Q1 Y2 x+ J, M1 RData bank, 数据库
' H6 u# M$ ^1 F% f6 S1 rData capacity, 数据容量: ?: f# a7 E8 J' C& u7 U3 t @
Data deficiencies, 数据缺乏
! v4 h6 s" b) Z" c2 B) nData handling, 数据处理( l, F0 w! C5 E
Data manipulation, 数据处理
8 m, S, Z* X5 D: j, kData processing, 数据处理
. f/ o# ]8 F$ mData reduction, 数据缩减4 B1 A! g% ?. t. E+ ^
Data set, 数据集
4 {: M* a+ `- L- w4 nData sources, 数据来源, [- x8 m# Q% K4 r& x2 S* a! x: j
Data transformation, 数据变换, A" g0 S0 b z5 ]8 t2 g$ g
Data validity, 数据有效性
9 a4 }7 M) ], q1 {$ HData-in, 数据输入/ v$ l# N% E+ j2 k7 _% b% u6 P# O* N" _
Data-out, 数据输出4 c. O, B2 H9 k4 ?. t# S
Dead time, 停滞期7 ^3 a, s, U: N, T2 T6 X4 B
Degree of freedom, 自由度
7 A1 F7 V( i `" A! A$ Z( N7 t* x/ SDegree of precision, 精密度
/ Y( z; G p- O, O# A( DDegree of reliability, 可靠性程度9 p I! L" _6 I
Degression, 递减8 m; O# x" r2 u, ^" S4 `
Density function, 密度函数7 q2 s/ v( n0 Y' r+ |$ D
Density of data points, 数据点的密度
" t: J" ^) w3 y6 |; TDependent variable, 应变量/依变量/因变量# \+ a B$ q& `- w. z3 }! L* a
Dependent variable, 因变量
+ W) ^( E5 W* N+ \/ l0 p# x" [5 ~7 aDepth, 深度" C% C# w1 n$ G' m$ K& Y! ^
Derivative matrix, 导数矩阵7 u; T( z9 B2 S
Derivative-free methods, 无导数方法
- L! Q4 M8 f# R9 B" vDesign, 设计: ?9 Y: C# X" B" d u
Determinacy, 确定性 l" v' Y9 ^% L$ _1 t/ P8 L
Determinant, 行列式9 }$ b S. h& A5 q* }( N; x
Determinant, 决定因素" `: s: _8 U" X! O/ G$ }
Deviation, 离差/ S5 A9 ^) q8 W6 W& P6 B# l- n
Deviation from average, 离均差: i5 ]3 y- ~! i
Diagnostic plot, 诊断图
8 z/ I3 W6 c; g$ SDichotomous variable, 二分变量
; d2 K9 _6 V, \! Z2 YDifferential equation, 微分方程
# n0 A; r7 l% Y( |: q, K1 nDirect standardization, 直接标准化法
$ t& Q+ P9 d2 x! Z8 W$ zDiscrete variable, 离散型变量/ M p4 a) o: @" c& ^: x
DISCRIMINANT, 判断
' t3 h! @9 W% dDiscriminant analysis, 判别分析
, H; J! L5 I; b H8 ^Discriminant coefficient, 判别系数
4 E0 c9 H: J8 \' y9 c! A* U/ A0 fDiscriminant function, 判别值
1 u, |3 n) M- j$ O0 ]( ]% ZDispersion, 散布/分散度
' W5 A2 ?6 B1 Q) ?. v3 L0 @Disproportional, 不成比例的
1 P1 |" d1 N2 j$ S& CDisproportionate sub-class numbers, 不成比例次级组含量. ~ d% d% ]- E) O1 R: }
Distribution free, 分布无关性/免分布
" [4 o* Y5 N+ P# WDistribution shape, 分布形状
# d, R! r- J, a3 GDistribution-free method, 任意分布法9 A1 R# F+ O. f' L$ W. D1 S
Distributive laws, 分配律* M f7 q2 T' S; ?9 w, L
Disturbance, 随机扰动项
1 y8 u0 \1 x" |, P2 H/ F8 aDose response curve, 剂量反应曲线6 z7 ?9 I; \) m4 Y2 v9 g3 p
Double blind method, 双盲法, b4 Z4 T: p3 H8 e0 o
Double blind trial, 双盲试验
6 _, x# ]* w! _, K) {/ LDouble exponential distribution, 双指数分布
a* t% u( c; [ `( l. [/ gDouble logarithmic, 双对数$ @- X/ q( P" ]9 l2 {! J( s9 n& M" ^
Downward rank, 降秩1 w5 R% P; D+ I+ O8 d
Dual-space plot, 对偶空间图+ [# d+ L I, O. j& g
DUD, 无导数方法/ c( x6 A3 t, q& ]/ A) V
Duncan's new multiple range method, 新复极差法/Duncan新法6 Z# k8 v7 s" W& H3 [+ @
Effect, 实验效应
. ^ o" u" A! `: R& p! MEigenvalue, 特征值
a3 |) B2 G- T1 W! tEigenvector, 特征向量
1 G5 y: i& h2 M5 v) |: ] |Ellipse, 椭圆3 Z f. \) m( b. j
Empirical distribution, 经验分布
* p: R7 [3 k6 V: vEmpirical probability, 经验概率单位' v* v4 x, c) d4 v
Enumeration data, 计数资料: o7 ~) j; ~) I
Equal sun-class number, 相等次级组含量
$ v! O9 L' P( I- SEqually likely, 等可能
: O9 H6 n+ D; w' t8 U0 e9 e/ `4 ?! cEquivariance, 同变性
5 L* ?. L+ X1 K3 y. NError, 误差/错误
9 f: {* K8 d4 }! R. MError of estimate, 估计误差
! t5 d- J1 J0 w3 a P# h) s7 `- \Error type I, 第一类错误
2 ^4 ?! i1 u3 {7 `! `" i* AError type II, 第二类错误
( {: S+ n" d5 m; G5 G6 [! O6 j3 GEstimand, 被估量
4 |- x- \! ^6 b8 x) ?) j. M3 r$ yEstimated error mean squares, 估计误差均方' Q1 q. O( M4 {4 I7 r
Estimated error sum of squares, 估计误差平方和0 b1 R R d/ K! a* n
Euclidean distance, 欧式距离
, D* r/ G. ~5 a4 v0 `% BEvent, 事件, U* {1 g$ O/ C, h- @ q
Event, 事件" s2 i7 F( t4 g$ F3 V5 c" S. o
Exceptional data point, 异常数据点
8 v6 `- f. F, u2 D0 PExpectation plane, 期望平面
) [& B- r9 U- P% E# p3 xExpectation surface, 期望曲面
! c/ o: p9 w& }9 wExpected values, 期望值
/ F1 X7 Z M% z! AExperiment, 实验( Q* @. y+ u0 t( r3 C! a8 O1 X" T
Experimental sampling, 试验抽样2 i6 r s, l1 s
Experimental unit, 试验单位) J# w. h+ i7 M% C5 a/ ] H! J1 _/ y
Explanatory variable, 说明变量
" ]& G. e0 p8 @9 Z6 i6 dExploratory data analysis, 探索性数据分析( p( t- ?7 e* K/ ?
Explore Summarize, 探索-摘要2 j+ t: n7 ^9 P5 y' ^7 x; `$ S
Exponential curve, 指数曲线
9 S3 L, {$ R* @( z& [$ ] d; a: ^; HExponential growth, 指数式增长
4 o, _1 i6 h8 }$ b0 a E0 r* h. PEXSMOOTH, 指数平滑方法 2 y* ~% I; v; Q' y' x
Extended fit, 扩充拟合: J0 [8 \4 T6 m
Extra parameter, 附加参数6 }$ J: e2 R6 K& N. s
Extrapolation, 外推法
; N8 W& W1 D! ]8 BExtreme observation, 末端观测值
# U' I5 m4 b% W8 P! `+ Y( ^Extremes, 极端值/极值
) ^8 e# U( e1 G+ i" w( j3 g3 jF distribution, F分布
$ m7 u. y, o' @* C. IF test, F检验
w% C4 M: i W2 V5 K, s% iFactor, 因素/因子# ~5 d* _4 [' J9 {! f$ R, p- ]
Factor analysis, 因子分析8 b8 l$ U2 [6 }* ~
Factor Analysis, 因子分析$ V7 D/ R% e: {( V# V! z
Factor score, 因子得分 9 j+ j6 [: {) T7 d* D# _
Factorial, 阶乘
. r. m- ]* ?" s3 k/ GFactorial design, 析因试验设计
$ o( ^4 K- x- @& x7 lFalse negative, 假阴性$ n0 ]4 a: j% e/ W8 Z! h
False negative error, 假阴性错误
! ^/ |$ h, _4 _' }: }/ K4 }/ j& @Family of distributions, 分布族
0 K/ K. {& U: Y& {% P* iFamily of estimators, 估计量族
( r; {. M7 ~* v" \Fanning, 扇面
K7 F0 {3 r1 B) N; h3 D" oFatality rate, 病死率8 x0 A8 v; \7 i i) L0 K
Field investigation, 现场调查
1 `1 L6 H5 } P5 {0 g* t; h% y# q( F1 GField survey, 现场调查6 s; E% t$ q4 C
Finite population, 有限总体
9 ? V% v ?# J& iFinite-sample, 有限样本
: z( h4 Z' O7 x; Z/ m% W, h9 p8 QFirst derivative, 一阶导数
6 C5 U- Q# M9 y- ZFirst principal component, 第一主成分
' o4 d" b2 Q( j( v! ^) @+ FFirst quartile, 第一四分位数2 M5 z# b7 x* v6 C& g4 m
Fisher information, 费雪信息量
) J7 K' w. t I2 i, ^Fitted value, 拟合值- e5 Y+ p/ u* t V
Fitting a curve, 曲线拟合
+ O6 h8 E% \) f# d* w1 D. cFixed base, 定基4 s0 b u$ q* V6 ]$ V
Fluctuation, 随机起伏 s1 u- R* o t0 \ P# w7 R& t' H
Forecast, 预测
+ D5 ?1 ?0 s3 {Four fold table, 四格表
' u( h4 }; Z6 U$ y$ tFourth, 四分点
0 n0 e7 d. l. E% N! vFraction blow, 左侧比率
. o0 z4 v+ ^9 NFractional error, 相对误差
7 h5 r k9 c8 q5 |Frequency, 频率 t; t% \ q/ s& s
Frequency polygon, 频数多边图: {1 E' J. A4 H
Frontier point, 界限点
1 q+ N4 l) t) }- ]# cFunction relationship, 泛函关系
3 ~) P Y2 X7 u5 S2 A4 {) cGamma distribution, 伽玛分布
* ~5 h1 ~. h+ @% O4 S3 PGauss increment, 高斯增量. w# U- W. T4 O, m' }1 A
Gaussian distribution, 高斯分布/正态分布
, p: U8 }+ x9 `( ^) H3 cGauss-Newton increment, 高斯-牛顿增量, c1 o, P o' V( z2 u; z
General census, 全面普查
/ U" Z3 d+ V1 o2 FGENLOG (Generalized liner models), 广义线性模型 & w% T/ R3 ]% Q4 _
Geometric mean, 几何平均数/ H! q5 d6 S: O0 K' ^/ ^# e
Gini's mean difference, 基尼均差- s5 B A8 S# q+ W
GLM (General liner models), 一般线性模型 5 x, Q! f h) Q, h% O
Goodness of fit, 拟和优度/配合度
1 K4 O% P# F- e* KGradient of determinant, 行列式的梯度$ _6 u, ~/ F, r" w7 j
Graeco-Latin square, 希腊拉丁方
5 r5 f Y( W% [! x/ kGrand mean, 总均值
. K9 x, s/ T d# gGross errors, 重大错误
/ [( K+ O' o u+ IGross-error sensitivity, 大错敏感度
0 j' k8 C& P2 s) A8 ~Group averages, 分组平均/ k# `% a: n9 a6 P' m
Grouped data, 分组资料 { _7 m; I6 I/ f1 o- _
Guessed mean, 假定平均数
6 H4 H) W( b; Z' NHalf-life, 半衰期
, P! L" R1 y" b! }Hampel M-estimators, 汉佩尔M估计量" E, B' [ \0 \
Happenstance, 偶然事件
; O. y, Z9 s3 Y4 n: l$ P+ [0 {Harmonic mean, 调和均数- q( Q v, c3 i2 F# ~
Hazard function, 风险均数
+ R! t w/ Y: K: jHazard rate, 风险率; J0 K/ C% d+ A3 z
Heading, 标目 4 G9 v/ y" B4 A8 k* N+ R
Heavy-tailed distribution, 重尾分布( s' ~! Z8 ]& O$ R D) F6 u
Hessian array, 海森立体阵
7 d9 J: G9 @# D, }) g$ \% B" X0 i3 gHeterogeneity, 不同质; p- u/ }5 \' `2 h. x
Heterogeneity of variance, 方差不齐
6 _* T; g3 U4 j8 p3 K+ IHierarchical classification, 组内分组
7 S+ d$ m5 o# j7 a3 @Hierarchical clustering method, 系统聚类法
( [9 M+ v" t7 |" h: YHigh-leverage point, 高杠杆率点7 X2 \( [( {' F1 k
HILOGLINEAR, 多维列联表的层次对数线性模型( M9 i( ~) |0 B! a
Hinge, 折叶点
, k+ q% L" w# o$ U) pHistogram, 直方图3 Q7 Y9 @% m% [( T' `6 @' @
Historical cohort study, 历史性队列研究 ! o/ R6 `0 r' H. G& Q' o
Holes, 空洞" s9 d5 r* o6 J! F; Z, L* P, g3 d" t
HOMALS, 多重响应分析" y q! i( @2 b- S* N, o
Homogeneity of variance, 方差齐性 {$ y( d, l5 S* G8 R
Homogeneity test, 齐性检验
) Z$ {7 }; @- H1 ^Huber M-estimators, 休伯M估计量. F$ w, Q& o& R8 A; [
Hyperbola, 双曲线 t) z3 h3 T0 `" r/ A
Hypothesis testing, 假设检验
) m2 f. M. p9 A+ m8 b3 lHypothetical universe, 假设总体$ c) S" S6 Y* Q. z
Impossible event, 不可能事件
" J) o) L: G8 e! P- iIndependence, 独立性
# S# `( d1 m$ CIndependent variable, 自变量
9 w; U8 H% W% i5 K8 s: ?7 }Index, 指标/指数, H) e$ d# G7 o$ P
Indirect standardization, 间接标准化法. a4 B# J: o l7 z+ z4 H# c, H
Individual, 个体: q5 z% b# k9 [$ k0 V) ^' M
Inference band, 推断带1 a' P/ v- R$ H- H% E6 {
Infinite population, 无限总体
/ U' x$ ?& B- D$ M, ZInfinitely great, 无穷大
/ T. C% j% M' ]% eInfinitely small, 无穷小
$ {0 O, W& W$ @5 ]# M* Q1 eInfluence curve, 影响曲线# b6 c* V, d& \/ b3 l# `" N( n
Information capacity, 信息容量
$ I B- ]3 f+ I. f: y2 e* R$ uInitial condition, 初始条件; k( C5 A2 t) a# Q/ c# E) ^ e
Initial estimate, 初始估计值) U) _& Q7 _1 Y8 z
Initial level, 最初水平' u' L( a, y6 E
Interaction, 交互作用5 l* _+ d; V% |8 s
Interaction terms, 交互作用项
- r' o( B* {$ w/ V: C, l6 OIntercept, 截距* N8 r* X, n" N8 @, t K9 ^2 f
Interpolation, 内插法
1 _( B! Y3 t* F* y3 D9 TInterquartile range, 四分位距5 q, \: g( A2 w5 ~, P
Interval estimation, 区间估计) k2 [3 p Y3 p3 s, z
Intervals of equal probability, 等概率区间$ A/ W4 M/ q: K2 z
Intrinsic curvature, 固有曲率
9 g2 E1 S3 X' Y' A; D6 b4 [6 vInvariance, 不变性 Y w3 A, {" Q# t) t: S
Inverse matrix, 逆矩阵1 E" k r3 i/ e+ K* B
Inverse probability, 逆概率
" u+ M4 A" }; n h. fInverse sine transformation, 反正弦变换0 P9 B9 N2 e4 S% R; U
Iteration, 迭代 0 v- \5 Q6 |$ I8 J
Jacobian determinant, 雅可比行列式
0 b/ O9 D" c0 c8 e) u* H( KJoint distribution function, 分布函数
; J5 \$ f8 @* l! e8 X4 s" D/ T7 _Joint probability, 联合概率
, v/ }. I+ H# _Joint probability distribution, 联合概率分布
( d% ~9 T. g* \4 {) w$ mK means method, 逐步聚类法5 O3 m$ j2 K0 Z/ v& r+ Q
Kaplan-Meier, 评估事件的时间长度 % G6 D* U) C# Z
Kaplan-Merier chart, Kaplan-Merier图
, O) ^5 r3 t; `! BKendall's rank correlation, Kendall等级相关# n8 r( i; V& S" C, g" r6 s) E
Kinetic, 动力学 a9 M" R- w; L5 v/ m) e
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验# n+ P& [/ N( q9 E
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
, }' w5 X0 @$ f! vKurtosis, 峰度
9 O9 O: a7 n1 h4 e9 j( U$ u% E! T; M9 xLack of fit, 失拟- j7 d# | {, K, D \5 c, l
Ladder of powers, 幂阶梯
1 D7 J0 {/ q5 }4 [) D7 m& aLag, 滞后2 h( p6 ^8 [, X& p' S3 H# x8 g2 I j
Large sample, 大样本
& F: o% |5 ?+ a5 N2 |% e" T' ?Large sample test, 大样本检验4 R& [; s! X x+ \7 c
Latin square, 拉丁方5 w# P- t9 _ X
Latin square design, 拉丁方设计8 K! N) a% R+ y7 c
Leakage, 泄漏: g$ P7 _4 q0 V8 {/ o. \1 g
Least favorable configuration, 最不利构形5 w2 o* e% T% L1 Z% [
Least favorable distribution, 最不利分布
1 P ~# V, ~5 u# v2 LLeast significant difference, 最小显著差法
# A& ]# G- O4 S1 ^Least square method, 最小二乘法
( N. A& w* E, @ oLeast-absolute-residuals estimates, 最小绝对残差估计1 N: Z: u/ s7 C* x/ f
Least-absolute-residuals fit, 最小绝对残差拟合0 Z/ L1 K: g4 p6 }0 P: N8 f: [
Least-absolute-residuals line, 最小绝对残差线
]9 n$ X; y) t4 G/ h4 P k: gLegend, 图例% j3 b4 L5 q5 }- F# `
L-estimator, L估计量+ `4 B: ]0 ?: [. A
L-estimator of location, 位置L估计量
7 p1 M" I# z. U+ N5 LL-estimator of scale, 尺度L估计量
' C `- A2 F9 {- s5 p+ F- h5 VLevel, 水平4 y* h' O; l. W0 D! i' o8 S$ K
Life expectance, 预期期望寿命
+ u; n: n9 s: z7 M- j( lLife table, 寿命表
. T. ]! ?: c! O& xLife table method, 生命表法
1 t7 o: a2 X* h: Q1 @ I" [) MLight-tailed distribution, 轻尾分布' ]( B% }4 B! Y0 S4 p/ `. H6 ^+ A( u
Likelihood function, 似然函数
2 D6 ]/ d! P% D# X7 S. rLikelihood ratio, 似然比
- h$ v: @" ]% r. T; yline graph, 线图
4 F6 k! l r5 E& `* U. r: j t3 U4 ?0 pLinear correlation, 直线相关
" p3 e3 }# ?) _Linear equation, 线性方程
0 {; o$ u: N! `# X7 w8 g( |Linear programming, 线性规划2 q7 ?% t8 d# B ?1 N2 h
Linear regression, 直线回归0 \* v; p9 C, @/ k3 Y& t, n9 D
Linear Regression, 线性回归7 ?& z; v2 X( ]
Linear trend, 线性趋势- L* R+ X7 {0 C. b2 k
Loading, 载荷
* S) O4 ?5 C! w5 c& wLocation and scale equivariance, 位置尺度同变性+ S' X$ k- }' E" @/ q
Location equivariance, 位置同变性
q1 Q5 d1 a* NLocation invariance, 位置不变性+ C5 M5 \/ M$ i5 s( G, k
Location scale family, 位置尺度族
! @# r+ ]: J5 w& A6 _5 qLog rank test, 时序检验
% n, N9 `" {3 p. d( q. u* m# a8 RLogarithmic curve, 对数曲线! _- v9 ^: F+ L# N# F
Logarithmic normal distribution, 对数正态分布
' ?4 e+ T0 g# \3 ^" _6 `) ]Logarithmic scale, 对数尺度0 t0 A( P+ ~$ D+ V+ {) m6 `: D
Logarithmic transformation, 对数变换" X) |6 h3 g$ s/ r
Logic check, 逻辑检查5 d \. U. P, ?! T% S$ I
Logistic distribution, 逻辑斯特分布8 A$ \( f( d u' T' s' R" Z: S, e
Logit transformation, Logit转换) m$ g' X6 s8 d1 {
LOGLINEAR, 多维列联表通用模型 K6 ~6 f6 ~5 D& a
Lognormal distribution, 对数正态分布( c. r0 k# A B" `
Lost function, 损失函数
7 e' H% x" b5 O2 GLow correlation, 低度相关2 v! u) h& H4 ^, ?' k
Lower limit, 下限0 `9 z$ e; r4 Y$ u% S j J
Lowest-attained variance, 最小可达方差
4 c, ?6 o/ O4 D2 `; dLSD, 最小显著差法的简称
! E- n% r; Z1 f. W; [Lurking variable, 潜在变量
/ {$ |" Z3 T. V2 s3 AMain effect, 主效应+ T/ i0 f2 D; |4 ]5 [4 {
Major heading, 主辞标目
, T' ]0 R0 v+ O" mMarginal density function, 边缘密度函数
1 w5 g% f, w$ [1 c' YMarginal probability, 边缘概率
6 w) s9 n6 o- a" q: X; Q$ }Marginal probability distribution, 边缘概率分布$ a2 g0 N- h. D) x t% W
Matched data, 配对资料
; R( W% Q9 N6 v( q7 y" P6 P" D' dMatched distribution, 匹配过分布
! |: R! c/ j( F1 V- U) J+ OMatching of distribution, 分布的匹配
2 `$ U5 o3 N. E2 s" C! @+ NMatching of transformation, 变换的匹配 o& \1 C# @; T1 z J. Z
Mathematical expectation, 数学期望! p1 {/ a9 }/ E, p' y, A) s
Mathematical model, 数学模型' _* v4 C4 u7 t; J0 w
Maximum L-estimator, 极大极小L 估计量8 L! U% }/ y4 \! @5 l1 ^7 [
Maximum likelihood method, 最大似然法$ M- x/ i, p0 |# M& X
Mean, 均数
5 ^4 f# f- e/ e8 l ]Mean squares between groups, 组间均方5 h% i9 ]0 k4 @1 z7 T
Mean squares within group, 组内均方
. T8 S2 m( k7 H1 }Means (Compare means), 均值-均值比较$ d9 V. t# j% ?$ W9 x5 t
Median, 中位数. E( Q5 Q5 T' y9 v# X Y# Z7 ]
Median effective dose, 半数效量
5 C3 h, C+ ]% @Median lethal dose, 半数致死量
# x% l7 k g$ e$ GMedian polish, 中位数平滑# [( H$ `$ v6 K' h/ A8 W1 `- m5 ~
Median test, 中位数检验) L; v6 P4 A1 |4 b1 e
Minimal sufficient statistic, 最小充分统计量
?% V; b* O+ rMinimum distance estimation, 最小距离估计
- g1 c2 c4 x1 j) F! B# A* _/ DMinimum effective dose, 最小有效量2 i+ L0 X& `) y' T7 }* T @
Minimum lethal dose, 最小致死量9 x) M; [: G) ?, J: j4 p4 }% m
Minimum variance estimator, 最小方差估计量
; t8 y; \" n) Y/ h! b7 v& s" y' ~MINITAB, 统计软件包# J) g/ p7 U& m3 R; M6 d8 v
Minor heading, 宾词标目$ U4 z, _8 g. \4 m; [$ h* S
Missing data, 缺失值4 q/ {/ x. k; e' g% y5 J: x
Model specification, 模型的确定2 c; ?; k. u* h" {4 A7 @
Modeling Statistics , 模型统计
& b& m) K4 G1 ^- }# N+ b: iModels for outliers, 离群值模型: n6 [7 ]( O1 }! y6 e0 W
Modifying the model, 模型的修正
4 v& W% ]" o+ H' E; @2 @4 EModulus of continuity, 连续性模! y( J& P& W5 t" {* Y) d
Morbidity, 发病率 2 [$ t) o5 @; W6 ~* I! ]% G* D0 Q- g
Most favorable configuration, 最有利构形
* v7 X" ?% z: Z" n+ `* @- eMultidimensional Scaling (ASCAL), 多维尺度/多维标度
0 W5 n# k! ]2 t% {Multinomial Logistic Regression , 多项逻辑斯蒂回归
) \8 P% Q) U1 L% p! h% _7 b. V0 gMultiple comparison, 多重比较; t1 v, @4 n; g; M- @
Multiple correlation , 复相关! B1 z% W' F7 r
Multiple covariance, 多元协方差8 a2 D7 }& T: A! ~' i' R. f* m
Multiple linear regression, 多元线性回归# y* f8 |$ b" R6 s5 \: `
Multiple response , 多重选项
, G: Z; N; W! @% w" }5 {Multiple solutions, 多解
# g& Z3 P9 \ aMultiplication theorem, 乘法定理
1 q: Y5 w; I! e7 R6 v8 }Multiresponse, 多元响应; P+ N( d- O! F" @( p+ B0 ~1 o' [
Multi-stage sampling, 多阶段抽样
, l! B. ]: o1 d4 V* L$ \: }Multivariate T distribution, 多元T分布
h- p8 @4 t% nMutual exclusive, 互不相容
3 x3 f& Q+ ]: i2 pMutual independence, 互相独立6 N, P: f# ^0 i! T: y; v
Natural boundary, 自然边界
. b: I- K8 o$ sNatural dead, 自然死亡" J$ b* G" y5 V
Natural zero, 自然零- ]. k, s9 o# P3 b- ^, x( G+ N
Negative correlation, 负相关& M \" o: B+ v$ X2 @ v, q8 n
Negative linear correlation, 负线性相关
B, R- J8 c: O2 vNegatively skewed, 负偏
; _' Z( ?& Y! y9 j6 z: h8 XNewman-Keuls method, q检验
2 e# D) V0 ^7 K+ XNK method, q检验! A( u; b5 Z/ A, ?' ?. T( C
No statistical significance, 无统计意义6 H6 w# G+ e- H- `9 U. h% W- ?
Nominal variable, 名义变量2 p6 e: ^: N* R; q% j
Nonconstancy of variability, 变异的非定常性& y4 `1 i. a% E
Nonlinear regression, 非线性相关
K5 I9 Q/ p3 Y B2 j* eNonparametric statistics, 非参数统计. p# u/ D! C1 F* \! R0 b% \( D# [
Nonparametric test, 非参数检验4 o8 M' M4 `- ?. x# A
Nonparametric tests, 非参数检验1 q$ q1 @9 i, i% X: ]8 u* M( r
Normal deviate, 正态离差
3 J# U9 G( f" h6 z9 I# kNormal distribution, 正态分布( ]8 J, U9 m$ t; K# ]' y3 ?/ y
Normal equation, 正规方程组
1 @% b# j8 ?1 z: U f* g- fNormal ranges, 正常范围
2 E* h# `/ _# y; D0 E1 KNormal value, 正常值. V$ ]: z# y6 `* _' x; J
Nuisance parameter, 多余参数/讨厌参数4 ~% c' P: p, t2 i- a8 D
Null hypothesis, 无效假设
& q( [: R. @1 VNumerical variable, 数值变量
& N2 j+ S0 f; f( `6 a% s: o9 QObjective function, 目标函数
/ {" d' @4 _$ L3 {$ i; \Observation unit, 观察单位
3 ]9 I2 E5 s+ s. L& H' q1 S& _Observed value, 观察值- g9 b5 b6 ?9 h& _3 z2 B
One sided test, 单侧检验
! i2 [7 a4 d3 z: M- `One-way analysis of variance, 单因素方差分析: C" y k: R% r9 i
Oneway ANOVA , 单因素方差分析" E M3 f% C% C- Z2 T
Open sequential trial, 开放型序贯设计
. r+ ]7 _# T/ K, j0 @: FOptrim, 优切尾, s* a( l3 T+ Q, E: S
Optrim efficiency, 优切尾效率
+ [$ }0 T% _- R, E) ^6 IOrder statistics, 顺序统计量
! V" E- l! }9 k3 j# zOrdered categories, 有序分类
9 N' \7 M/ |# X; V# U8 N2 _, @Ordinal logistic regression , 序数逻辑斯蒂回归 f/ Q) g9 G6 L# ^+ }, B
Ordinal variable, 有序变量& t5 n. [- T- @
Orthogonal basis, 正交基
# {0 D* B, C1 |3 [# POrthogonal design, 正交试验设计6 o4 C6 G Q; D; t; E8 b6 a
Orthogonality conditions, 正交条件
& h! K4 B1 m' Y, D8 iORTHOPLAN, 正交设计
) g, q9 y5 g- x& H+ d$ C. VOutlier cutoffs, 离群值截断点& O6 T7 L e: z! `" M
Outliers, 极端值
- h: U/ \) t# a2 P( h% P* o7 iOVERALS , 多组变量的非线性正规相关 ) ]3 ?7 K* }( Q% e. {/ y
Overshoot, 迭代过度( {# L/ B. E/ \' N9 y3 x( T) z
Paired design, 配对设计
4 n2 v: Z# E' g6 NPaired sample, 配对样本
# F, q' L5 s7 K1 g0 [7 iPairwise slopes, 成对斜率$ P b- s3 K2 Q1 c3 ^/ l
Parabola, 抛物线
" B$ ~3 M" x' g1 g, s$ rParallel tests, 平行试验0 I! e% y/ }9 O% ^: |
Parameter, 参数
0 q/ Y/ q1 F+ F% o9 PParametric statistics, 参数统计
9 r, D% T0 R" x# c6 H4 d2 y j6 LParametric test, 参数检验
3 N/ c9 X2 G' p& K; ^Partial correlation, 偏相关5 F" E7 _5 u; r* V
Partial regression, 偏回归
8 b% W$ a8 m$ f' ~Partial sorting, 偏排序
% S- J A# t. ]% z6 _( PPartials residuals, 偏残差, [+ M A" l& _2 N8 L
Pattern, 模式8 f' w* V6 R& H9 L5 {+ r4 w" f
Pearson curves, 皮尔逊曲线
, U: ?9 K3 X1 _Peeling, 退层% j5 ?, d O& ^' o: T" i3 \
Percent bar graph, 百分条形图3 o3 H1 P6 [: X: d/ q
Percentage, 百分比$ w& H+ v9 j& @7 S
Percentile, 百分位数
$ m2 B! n5 |( N; w. D! ePercentile curves, 百分位曲线
9 u2 C$ X/ ^5 D/ {% z9 i3 X0 q* vPeriodicity, 周期性. }) z; F5 a+ l6 v4 t1 e, }
Permutation, 排列
6 S2 N1 Z; Q# K$ K9 hP-estimator, P估计量+ w6 r0 t6 d5 {3 P* J2 y
Pie graph, 饼图% D. j0 ]- H0 u- Z% v4 H
Pitman estimator, 皮特曼估计量/ k* g% x9 D: y+ d; I
Pivot, 枢轴量
* O' \7 m3 E @% C# \Planar, 平坦% t2 p- v6 o& k, W8 m& U% K
Planar assumption, 平面的假设
2 d$ w+ @) w- E# q/ YPLANCARDS, 生成试验的计划卡7 \) b* c$ l& Y3 N
Point estimation, 点估计7 X7 c0 P. |: T" G9 f4 ^+ w, g
Poisson distribution, 泊松分布% t1 l2 p! d. [
Polishing, 平滑
! {/ D% @# Z# T* i/ k4 x. c, PPolled standard deviation, 合并标准差
! l5 t% G% A- z6 F5 l5 VPolled variance, 合并方差
D v. N- Q$ _5 ?3 q" J! CPolygon, 多边图
4 ^4 ^/ U% V! l. y. t# APolynomial, 多项式
9 R/ i0 m* i0 {' S! t8 P" ^Polynomial curve, 多项式曲线9 Z. j$ e9 A; Q7 @ `8 y
Population, 总体/ }* [. I8 J5 h S% I
Population attributable risk, 人群归因危险度) v6 O) A4 b+ p1 W& `2 `( |
Positive correlation, 正相关
) [. N$ k D" `6 @) T( OPositively skewed, 正偏. C1 J1 K8 P% [, U- o/ Z; A/ I& y6 E
Posterior distribution, 后验分布9 g. m2 f$ D* \( A# H7 Q
Power of a test, 检验效能
8 K. @' k( ]/ i; v H. F2 sPrecision, 精密度
' N7 ?- q* ], Z8 B% lPredicted value, 预测值
! A$ o6 P, `0 B& d' n2 U! [Preliminary analysis, 预备性分析
I% I, Z9 a0 ~Principal component analysis, 主成分分析0 |; [) s+ ^7 X' ?! ~% e% t5 s7 h* q
Prior distribution, 先验分布
$ h8 S7 z) I: m) ]2 E# N/ `' S, ?Prior probability, 先验概率
2 I4 |% R$ L( r- Y K* LProbabilistic model, 概率模型/ B2 m- e+ B' w) p: I. q2 G! v( P1 |
probability, 概率3 w2 G6 ^ Q9 `4 w
Probability density, 概率密度
6 o+ n+ L# V$ t: T2 u" { QProduct moment, 乘积矩/协方差
# i4 N4 O7 M q' ^6 m$ EProfile trace, 截面迹图
0 t; x7 R d& C# b" j( i! wProportion, 比/构成比9 Z, |* x! r9 ?# l" l4 A- G
Proportion allocation in stratified random sampling, 按比例分层随机抽样
, t4 m% K. X! r. T- ?; R- RProportionate, 成比例1 z& ~7 ?/ N: R
Proportionate sub-class numbers, 成比例次级组含量
8 A' J4 K# o( @5 G9 x5 aProspective study, 前瞻性调查
7 s6 C. c! a k+ _ \Proximities, 亲近性
- l T3 H$ M. Z. w* ~; gPseudo F test, 近似F检验
% ?1 I. \4 g) pPseudo model, 近似模型* | Z8 Q h4 R! [
Pseudosigma, 伪标准差
; U# T+ N) z% TPurposive sampling, 有目的抽样
@+ |- n) o9 `/ S/ VQR decomposition, QR分解
) P% R2 o+ _4 _5 |% d* sQuadratic approximation, 二次近似/ W ^2 p% M- R- V( `# O. V9 {
Qualitative classification, 属性分类
9 a5 L8 |: I- a T7 o( Q: AQualitative method, 定性方法
- Z; ]( \! F) w' C! g, mQuantile-quantile plot, 分位数-分位数图/Q-Q图
% m6 B( H8 G% q% U) G8 T$ z4 p: gQuantitative analysis, 定量分析
2 s, g- j' C. y q1 k" yQuartile, 四分位数! [ J3 o5 _. v
Quick Cluster, 快速聚类
/ \- L0 I+ Q+ v& [Radix sort, 基数排序0 T' W. ]! i; p8 K2 h4 K% B
Random allocation, 随机化分组7 x( o, V- g* i. q' R( ]' v! G) D
Random blocks design, 随机区组设计
; {* I8 u r4 IRandom event, 随机事件2 g- L) ~* i3 F' n8 [3 x
Randomization, 随机化
9 L, y: m: h! zRange, 极差/全距
/ S ?! \; \. n6 y6 q! y9 _' R! vRank correlation, 等级相关 @/ q$ G7 W+ @+ a( S- Z- }
Rank sum test, 秩和检验4 J, v. Z8 i9 i
Rank test, 秩检验
; n# |: N. a, `) Z+ f2 c" g; ARanked data, 等级资料( W0 |. l2 t7 C: @
Rate, 比率
2 w3 {, \! I2 I0 z' ^+ [% U+ c( xRatio, 比例8 X" l1 p9 I& e6 s3 r P7 _. P
Raw data, 原始资料
2 K. u' ~- X8 ^5 H; YRaw residual, 原始残差6 K- V6 F2 Z% ]/ a. A1 q, }
Rayleigh's test, 雷氏检验: A) n, i) y0 I* B; a, @
Rayleigh's Z, 雷氏Z值
: t9 k4 `" E0 H5 p" X4 uReciprocal, 倒数
2 G% k8 @' O* t9 r" HReciprocal transformation, 倒数变换
$ I8 ?; p9 R) i/ Q, P$ HRecording, 记录* v' o0 V% j5 a0 {! R+ V5 }1 i
Redescending estimators, 回降估计量
5 ?7 M; c# c* L4 \Reducing dimensions, 降维
3 X2 D) h4 p8 g& s) x# TRe-expression, 重新表达
1 f" X: _- H+ r. s IReference set, 标准组- m$ M9 `# D3 m% Z+ [ A, L5 s+ Q
Region of acceptance, 接受域5 j' U! L: Q1 {. x3 ~
Regression coefficient, 回归系数* {7 H1 P; H" S$ I* ^9 n
Regression sum of square, 回归平方和; E7 _5 |( X% y% T: @# j& f
Rejection point, 拒绝点
* P" C; k8 L5 e3 n( |9 b9 H2 YRelative dispersion, 相对离散度* M W$ h0 x' R
Relative number, 相对数. y9 @) V5 V4 ^, @7 L
Reliability, 可靠性
1 Z2 r* |9 ? L: ]8 nReparametrization, 重新设置参数) R& K0 F) ?9 ^% j
Replication, 重复
8 t5 Y5 U0 F% ]1 hReport Summaries, 报告摘要
3 ^2 G3 ~0 t3 s" h$ j5 F6 h* iResidual sum of square, 剩余平方和
7 a) s/ }$ v" L. `4 KResistance, 耐抗性9 V/ R; O- j+ j: h5 M
Resistant line, 耐抗线
, o% J8 ?# A) Z. F$ b }) GResistant technique, 耐抗技术
# X/ C" Z7 e% QR-estimator of location, 位置R估计量& i* n2 T) |0 x* J3 o
R-estimator of scale, 尺度R估计量
" V! J& i' I1 E% Y6 bRetrospective study, 回顾性调查; _; \1 ~" k# u: e, Z0 F3 w
Ridge trace, 岭迹
, g' |3 _0 A/ nRidit analysis, Ridit分析
4 O4 j; h6 x# p; H" r t; WRotation, 旋转2 {$ h- \5 A. y: ~
Rounding, 舍入
) f& Z! L5 F+ {: TRow, 行
8 m, i; l$ ~6 y+ d6 RRow effects, 行效应
: H! U# `0 U- N; S S! M5 QRow factor, 行因素
1 Y" F0 R p% |& W8 J2 R$ @' k4 `RXC table, RXC表
* s$ {) M9 O6 c) h. TSample, 样本% H# r! ?( g1 J2 M3 l$ m
Sample regression coefficient, 样本回归系数1 M4 }. l# V% l6 F9 p
Sample size, 样本量: E) P1 q+ F% Z
Sample standard deviation, 样本标准差
1 k( M& |) m( i! F% S. ^Sampling error, 抽样误差" _6 d( [& {$ n3 R( |; s( f& j
SAS(Statistical analysis system ), SAS统计软件包
/ d4 n9 F+ a2 OScale, 尺度/量表
2 G: f" J7 V; \" W; Y2 N yScatter diagram, 散点图
. K+ ^$ f' a' g3 W0 jSchematic plot, 示意图/简图8 ^7 r* u2 s1 T: `* i$ r
Score test, 计分检验
2 e( R$ |! [- w5 w5 w+ ^0 C$ z: XScreening, 筛检& m! F x k Z2 ]# w
SEASON, 季节分析
- Y6 l/ B N* f, V, W7 PSecond derivative, 二阶导数1 T3 G/ W/ |0 S: b. b& f
Second principal component, 第二主成分: Y4 t J9 C/ ?( C7 F5 X8 }
SEM (Structural equation modeling), 结构化方程模型
" ~+ `' c7 Y, I: J- FSemi-logarithmic graph, 半对数图9 a* H8 e! `' E0 Y% e$ c/ ] Z) t
Semi-logarithmic paper, 半对数格纸8 o( ^" m, ?( r$ e
Sensitivity curve, 敏感度曲线
0 B; n5 ~7 r7 Q3 D' m: c7 |: OSequential analysis, 贯序分析
6 q4 T2 Z2 z* I& o* J: L# kSequential data set, 顺序数据集
6 P" L2 q. H( k! n' \- XSequential design, 贯序设计+ S' U3 p0 ~' k" y
Sequential method, 贯序法! ]* S/ M3 ^9 N3 u% r1 d6 N/ E
Sequential test, 贯序检验法
0 _2 R0 |3 ~9 ~. Q2 ?1 D0 [; eSerial tests, 系列试验# L8 G0 K' {6 z
Short-cut method, 简捷法 7 |3 S3 U) S1 p8 ]9 g) S1 i
Sigmoid curve, S形曲线
4 _/ a- `/ }. N: n8 A) TSign function, 正负号函数' x' S9 R' x6 V- \* ?, s3 f4 k
Sign test, 符号检验
G O" s* K$ V5 ]8 Z+ C7 Y4 pSigned rank, 符号秩
8 }" b3 b5 |! t* ]8 X7 ?Significance test, 显著性检验
! Q7 n6 ~' M/ s! ?Significant figure, 有效数字
( x# B# S& \5 |. J4 q" ~( XSimple cluster sampling, 简单整群抽样
% O; p% L0 Z+ CSimple correlation, 简单相关
" V7 l$ V) D/ r4 b# t6 Z" }5 A) aSimple random sampling, 简单随机抽样
! E( @# w% U8 v1 z" t0 JSimple regression, 简单回归
4 [0 W8 {" v6 ^3 ^/ l6 l4 |simple table, 简单表
$ z0 l8 C# D0 z0 R! mSine estimator, 正弦估计量! z) k+ F% R6 H1 k' P2 m, P( Q/ E
Single-valued estimate, 单值估计
# ^; I# C: `$ C& r( v T1 ?Singular matrix, 奇异矩阵
& B1 |, E8 h, ?' s2 cSkewed distribution, 偏斜分布% w, f J4 e5 h! L
Skewness, 偏度3 d5 ?0 k: ^! m. P, ]2 a
Slash distribution, 斜线分布( L" I2 }* Y9 o j3 o
Slope, 斜率
1 K4 h( y( v0 x* |, O& aSmirnov test, 斯米尔诺夫检验0 b. s6 `7 j. M3 P: d3 `: q+ E6 |
Source of variation, 变异来源+ R% p F9 v" x9 n/ f0 F
Spearman rank correlation, 斯皮尔曼等级相关
4 N8 {9 F1 D3 [Specific factor, 特殊因子& ^3 A; [7 R2 D# S5 n, p
Specific factor variance, 特殊因子方差
: a1 B+ n+ K9 hSpectra , 频谱- ?" o7 c* U% u( y; Q* d# m6 V
Spherical distribution, 球型正态分布
0 _& t6 L/ W4 E2 H! ]% [Spread, 展布& a/ x& `1 d- R, d6 L- }1 N* @
SPSS(Statistical package for the social science), SPSS统计软件包
. l6 J; o3 G: lSpurious correlation, 假性相关$ J9 ]$ Y9 Y) A& Z
Square root transformation, 平方根变换, j# b/ {: [% f. ^# Z- m( C( g
Stabilizing variance, 稳定方差: S/ |' a! V/ x
Standard deviation, 标准差$ b3 }' H) |3 }. E& x4 I
Standard error, 标准误3 j( q' Z- s# H$ A
Standard error of difference, 差别的标准误' L. Y( a% ?0 |; ], L
Standard error of estimate, 标准估计误差* }' H! |1 u4 N9 Y3 J5 n
Standard error of rate, 率的标准误; ~' V" `0 H+ \
Standard normal distribution, 标准正态分布
. v# V6 R* d# S. |7 I' PStandardization, 标准化: g( v4 `8 v [6 p* L
Starting value, 起始值
( V8 _0 S( F2 c# M# \Statistic, 统计量1 d; ?, Z0 J+ K9 K/ m7 S) M
Statistical control, 统计控制) R0 h0 U% q# M
Statistical graph, 统计图- a9 k' }$ I5 v, A8 G( G& T
Statistical inference, 统计推断( c$ {# I* F# \/ x
Statistical table, 统计表* E1 G9 C7 U4 K( s% B, i% O# a" h
Steepest descent, 最速下降法$ L. ^- y( K; q# o: T7 X
Stem and leaf display, 茎叶图1 ], l" Y: J& C: j
Step factor, 步长因子
4 {% M* [+ s T% S* gStepwise regression, 逐步回归) g* o3 Y* j$ k! r4 h/ n( e8 X5 p0 u
Storage, 存
; {, j# x2 F* pStrata, 层（复数）
2 F1 V) t, B* G9 t; S* gStratified sampling, 分层抽样2 F' b5 ^9 T/ x- Z) q# H
Stratified sampling, 分层抽样
9 i; H2 x# Y7 H8 k( IStrength, 强度
2 w( \3 m6 ?# Z! a% N; v* e3 \0 M) eStringency, 严密性; u! t* ^6 {" w. B
Structural relationship, 结构关系
2 H& Q3 B/ e- J8 @1 R7 h: M3 I1 PStudentized residual, 学生化残差/t化残差
+ L2 s0 U4 q% w# E! d" nSub-class numbers, 次级组含量
. W6 G. l6 W: ]5 NSubdividing, 分割
* N3 v) o8 x8 E9 m1 G; jSufficient statistic, 充分统计量- x6 F1 Y: Z; S6 n0 j; {
Sum of products, 积和& q& I4 R# Y5 h+ D
Sum of squares, 离差平方和
7 m% e# {) Z, [Sum of squares about regression, 回归平方和% }" `$ H& m3 K& w
Sum of squares between groups, 组间平方和
) G m( b$ [( \" p$ ?( `Sum of squares of partial regression, 偏回归平方和
: O6 `; H4 }# {7 B/ V. V# ], hSure event, 必然事件) i- {4 ], f5 A* w2 e7 Z2 B" i
Survey, 调查
8 n2 j1 m+ o5 j/ ^( ?+ NSurvival, 生存分析
% l, h* C/ K" R; _2 pSurvival rate, 生存率
: F2 S8 q: ?2 YSuspended root gram, 悬吊根图
# t- S4 u, w- Z3 ISymmetry, 对称
, z$ t, g0 e0 H, C- z% iSystematic error, 系统误差: ?% Z d; |% D" Z/ ?9 f
Systematic sampling, 系统抽样
, d/ X9 J+ L9 o9 u9 O1 BTags, 标签: A+ h1 \" a8 Y; a2 M
Tail area, 尾部面积
- l2 J, {- ]4 N$ }- a R8 l5 g VTail length, 尾长
* C# h1 d/ o0 Q. u" vTail weight, 尾重- V! J( ]9 X1 e4 b; e4 A
Tangent line, 切线
# i) Q( N! S# B+ S& N. mTarget distribution, 目标分布
+ R' Z, x1 i3 b8 E4 BTaylor series, 泰勒级数5 K9 F! e6 f- j
Tendency of dispersion, 离散趋势
6 K3 i+ d* V7 X2 n f9 QTesting of hypotheses, 假设检验2 x- ?$ O( a; a) C, d: C; P
Theoretical frequency, 理论频数
0 |8 d F j2 f& A' w9 `Time series, 时间序列
' `( @1 V! s# r5 ^( }6 U/ STolerance interval, 容忍区间8 f) ]. [5 ^( u# f, A8 E
Tolerance lower limit, 容忍下限; t* O6 ]8 H+ \5 D$ k' y4 V
Tolerance upper limit, 容忍上限. y' ^& v( L0 z: T/ C
Torsion, 扰率
8 j- S% n. J" W4 B$ e. u5 sTotal sum of square, 总平方和
0 ]0 g! O9 {/ x4 q2 K/ k# K eTotal variation, 总变异" T1 y, ~5 a4 @- D3 X! U9 ?, E
Transformation, 转换) n5 K' v! \& F4 w' C
Treatment, 处理
/ ~, r# V* z* B7 |Trend, 趋势1 L. S6 t3 _ E4 {
Trend of percentage, 百分比趋势3 a* X0 i8 V% n. m9 h Q2 b+ |
Trial, 试验4 ?- R+ Z) N$ {) v: Q0 N
Trial and error method, 试错法
( Y9 C1 T- E/ ?) |5 S7 {6 g" HTuning constant, 细调常数" w/ r+ i) P; i( C v2 g( W
Two sided test, 双向检验
0 n* B! Z: V6 z; ?+ Y3 V( s: {) K- {Two-stage least squares, 二阶最小平方! { R7 X8 N: P! D; ]/ P% i; F3 W% d
Two-stage sampling, 二阶段抽样2 X7 a7 |& r2 S5 ^; h. E# _
Two-tailed test, 双侧检验- P: B8 g; ]7 J- |" D
Two-way analysis of variance, 双因素方差分析( {' d* E; \8 K5 b% d" h) ]
Two-way table, 双向表
% T) ~2 ^+ Q9 qType I error, 一类错误/α错误! R1 t% e) k7 m0 y% E8 N
Type II error, 二类错误/β错误2 ]6 A& j! D' a9 ^! G! j* e. s
UMVU, 方差一致最小无偏估计简称7 J- ^# r" P6 X, V$ d, N, \+ L3 o/ R+ H
Unbiased estimate, 无偏估计% Q9 k& U7 [* ?
Unconstrained nonlinear regression , 无约束非线性回归2 b1 @$ E, J, A/ \* ]+ W
Unequal subclass number, 不等次级组含量% t8 }$ ~ j* j$ f1 s
Ungrouped data, 不分组资料
/ Z/ f/ v+ {8 X/ JUniform coordinate, 均匀坐标- f. H, [! x! g6 \$ V
Uniform distribution, 均匀分布7 K1 F9 N% R: {% Z' v9 _0 l e
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
& G x& p5 b0 GUnit, 单元
; t6 P0 V9 h- f( lUnordered categories, 无序分类
9 `" G- J* W C# f( o6 u8 p( SUpper limit, 上限
- F: ^/ C3 }* m/ k: `/ q* DUpward rank, 升秩; x1 V7 o0 M+ Q. g2 |/ I( u4 r* L
Vague concept, 模糊概念# ~' t! T# E" d3 @! S0 h% L- L
Validity, 有效性8 C- u; I" b3 S+ L- ~, y
VARCOMP (Variance component estimation), 方差元素估计
) S2 \: }; I! X5 M0 x& f, L( y4 [2 hVariability, 变异性# {1 p' n9 j. R6 s5 ~
Variable, 变量+ J9 _6 u% i3 [1 K# v' k2 \
Variance, 方差; i! B: x! p [: h
Variation, 变异! F+ B6 d" a$ |5 { A
Varimax orthogonal rotation, 方差最大正交旋转( f$ R/ m" w5 n( A" m+ ? V
Volume of distribution, 容积6 f# [+ E5 j1 ~1 m2 P9 _
W test, W检验. Y$ j5 J/ n+ g" D. n
Weibull distribution, 威布尔分布
$ u3 v3 s- H$ W5 xWeight, 权数
8 n! w, d" L+ [+ Z- _+ tWeighted Chi-square test, 加权卡方检验/Cochran检验
; h: y) a7 i/ iWeighted linear regression method, 加权直线回归
. G5 K# j9 `, }6 {& uWeighted mean, 加权平均数. L" j& z s& a; p, | w
Weighted mean square, 加权平均方差. a4 H* K3 @; r7 P# D2 z+ @
Weighted sum of square, 加权平方和5 V4 {8 E: l; t& B/ V/ g
Weighting coefficient, 权重系数: Z$ s2 l {2 K
Weighting method, 加权法
% ~8 w6 u. z( X5 ~W-estimation, W估计量2 b% x( g* ~3 v( p
W-estimation of location, 位置W估计量
& [# j/ ]1 ?3 ]' t& O' wWidth, 宽度6 L7 C; T2 I/ J% l' j& x
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验% T7 M2 _) {5 d
Wild point, 野点/狂点
0 k: h- ^( S/ F |: Y& _Wild value, 野值/狂值
9 `8 B: \# B- |# QWinsorized mean, 缩尾均值7 l" H7 c1 t$ D' |$ i/ l7 ?* o
Withdraw, 失访
4 y3 t7 o( [" n" i6 tYouden's index, 尤登指数1 s* b& s8 J, v0 N2 ?% V$ G# a, T$ B
Z test, Z检验
% r0 P' \+ Y$ ~Zero correlation, 零相关
- _) c" m" ]0 C2 [! IZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
