|
|
Absolute deviation, 绝对离差
n; }8 C9 D! VAbsolute number, 绝对数' O4 }+ ?& w* \
Absolute residuals, 绝对残差
7 i, \5 l8 K% V- f, ^Acceleration array, 加速度立体阵
5 q7 i* I( i8 `+ ~ dAcceleration in an arbitrary direction, 任意方向上的加速度
$ G$ c# t- n* u0 [Acceleration normal, 法向加速度
3 ~* ^* |: s* i. r& O+ EAcceleration space dimension, 加速度空间的维数
$ k$ A3 M$ T5 c+ \% w0 g9 S* XAcceleration tangential, 切向加速度
2 u. H. m5 \3 q. N; W/ ? |9 H' MAcceleration vector, 加速度向量8 h/ X" B3 h( j
Acceptable hypothesis, 可接受假设
- K$ ^+ P- j# t" G7 l. _Accumulation, 累积
* j# o* r+ @! F' \) }7 SAccuracy, 准确度* s% K' k; j& C) c! v
Actual frequency, 实际频数
$ [& d* ?5 \$ z8 W& R! PAdaptive estimator, 自适应估计量8 L" j: ]) f/ @ k* I( f
Addition, 相加
# B% P$ k& n: A- N. TAddition theorem, 加法定理. w- y2 A; ]; X' J2 V
Additivity, 可加性
& g6 S& g* H4 g. ?0 D! HAdjusted rate, 调整率' P( i% t; B$ S8 i# s
Adjusted value, 校正值
, y/ x7 t/ ] u2 N+ N( AAdmissible error, 容许误差
C, z* w( V5 l+ IAggregation, 聚集性
! h% {1 l3 I1 m, J3 ?3 [Alternative hypothesis, 备择假设 L) l# {8 j$ B; B8 e$ ` |
Among groups, 组间
. k4 b; @! m7 Z8 a) tAmounts, 总量7 r# W" Y: @: z6 [, n3 g
Analysis of correlation, 相关分析. |6 U; ]+ `; q; ?: f4 g" p
Analysis of covariance, 协方差分析! T; ?* r% O2 s
Analysis of regression, 回归分析
0 p- `5 C) Y* ^' W: ~% X) i1 K1 _- FAnalysis of time series, 时间序列分析1 M( J! }# T9 c, w5 U! P
Analysis of variance, 方差分析
* D" a: Q4 t0 I+ ]3 v, R4 IAngular transformation, 角转换2 ]. D% e7 A2 _* s+ O
ANOVA （analysis of variance）, 方差分析
. \/ Y3 i. N0 _! c7 D0 uANOVA Models, 方差分析模型5 k, ?: D+ p( D5 U* T
Arcing, 弧/弧旋! _- {0 K6 O( `; C, C4 n( k( T3 X
Arcsine transformation, 反正弦变换2 M( y& }$ `* q% d" A
Area under the curve, 曲线面积+ T( D, X6 `0 W) }5 f6 w
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
! K" G& u a M5 \ARIMA, 季节和非季节性单变量模型的极大似然估计 n3 \: f4 y3 r, t/ z5 {) I0 D
Arithmetic grid paper, 算术格纸
) u8 O$ _% b$ N/ |Arithmetic mean, 算术平均数# M' D( x7 I, S
Arrhenius relation, 艾恩尼斯关系' M( d+ C# [3 A S" ^9 _
Assessing fit, 拟合的评估& U1 ]% u" z# M4 I( l
Associative laws, 结合律
$ u; ^% B) y& O( L+ {1 Y4 ^7 j6 z* B5 ZAsymmetric distribution, 非对称分布! s0 r6 K( s9 g# W4 H2 a
Asymptotic bias, 渐近偏倚
3 M* Z5 \( ~1 N: _ _' i: K% z: L2 ^Asymptotic efficiency, 渐近效率3 b3 h: Z a- Z& W, g' Z
Asymptotic variance, 渐近方差
9 J1 n( f8 P( Z1 ^/ {Attributable risk, 归因危险度
; d+ k) A! X6 b: M! VAttribute data, 属性资料, B- ^) r3 Q0 w& G
Attribution, 属性
s! L* ?% ?" _! d+ Z+ I7 q6 XAutocorrelation, 自相关3 u$ e9 q/ A1 A. m: _: z2 j
Autocorrelation of residuals, 残差的自相关
% V. I& B1 I1 _" G$ c; ~0 {+ R: TAverage, 平均数
3 o7 m$ h+ T! Y# s2 hAverage confidence interval length, 平均置信区间长度/ K7 z+ V4 m! T
Average growth rate, 平均增长率
* ]) q3 X! y* w L; _8 R( hBar chart, 条形图 i+ j$ K/ v/ ?2 u6 i7 ]& W
Bar graph, 条形图
: M4 o/ b& U9 k, ^Base period, 基期
1 h1 n" f( l% a; vBayes' theorem , Bayes定理3 _) z" L1 ^8 k1 q6 R* x4 N8 X
Bell-shaped curve, 钟形曲线' E" g" M3 w/ {1 c
Bernoulli distribution, 伯努力分布; w3 r5 O/ _9 ~8 b- p. G* G- P
Best-trim estimator, 最好切尾估计量( H* z; a5 N5 g4 t4 i0 |1 n& I2 l
Bias, 偏性" D* I. |* u$ C( N* z+ }+ E/ [
Binary logistic regression, 二元逻辑斯蒂回归! u! S9 d+ T+ a. |8 Z3 _/ D" H$ Q7 s
Binomial distribution, 二项分布& h% E6 y" k5 [/ V0 O& z5 J
Bisquare, 双平方+ F% w8 `- T( G3 i, _
Bivariate Correlate, 二变量相关' d; i4 g6 Q- V- E. E( R
Bivariate normal distribution, 双变量正态分布9 P9 c" H+ [0 g& D: Z
Bivariate normal population, 双变量正态总体+ c3 `; f) z9 y/ D3 z6 J
Biweight interval, 双权区间
5 a l! r) R- ?9 n* C# dBiweight M-estimator, 双权M估计量) b1 G+ W% q2 e& Q: a* Q
Block, 区组/配伍组* E$ z! ^4 Q1 J, c- g) I
BMDP(Biomedical computer programs), BMDP统计软件包
8 X2 @" `2 c- Y; j* tBoxplots, 箱线图/箱尾图! Q' ^3 ]+ d8 v' s' V* _( m: m+ t0 C/ f
Breakdown bound, 崩溃界/崩溃点, O2 ^( N# C0 N7 b# n$ t" @
Canonical correlation, 典型相关1 X4 F- O# ^- c2 Y
Caption, 纵标目) t! \5 e* L9 B- Y9 e: u5 r E6 Z
Case-control study, 病例对照研究+ T1 o- S, M/ U9 \% @
Categorical variable, 分类变量
; ]3 ^0 v/ p4 P( f5 Q' CCatenary, 悬链线
* w! w) W7 i! UCauchy distribution, 柯西分布
) v+ _4 H# L O) F& A- h% b* i' CCause-and-effect relationship, 因果关系, h- s% Q; A1 N/ [8 ^6 u: e6 _
Cell, 单元
~& R0 h. U1 k' fCensoring, 终检
E! n9 w( _" h4 z# bCenter of symmetry, 对称中心 z* e# d' x0 j! D" k7 H) r
Centering and scaling, 中心化和定标0 ?- r# W7 Q! F) W- c" Y
Central tendency, 集中趋势
! k/ V+ j; N8 yCentral value, 中心值8 P# ]" K) S" w- t8 |
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
# d, a* b0 y! x) N, @/ @% k/ ]Chance, 机遇8 W8 i7 O9 z) q# ?& ]5 F3 j
Chance error, 随机误差# z. w( y+ u$ A7 s5 P* S; N9 I+ N
Chance variable, 随机变量0 G0 B0 F6 o3 q
Characteristic equation, 特征方程
: s3 ^# T7 |9 d6 HCharacteristic root, 特征根
9 Z* I. o: N8 s6 QCharacteristic vector, 特征向量
% q( L& u' S: e6 O0 pChebshev criterion of fit, 拟合的切比雪夫准则# k0 j; w( h% [, y# y: N# t# h
Chernoff faces, 切尔诺夫脸谱图
4 `9 h- V p9 M) N+ u8 FChi-square test, 卡方检验/χ2检验
) A$ U4 R) ~) |" {+ {' f4 @Choleskey decomposition, 乔洛斯基分解
1 R" @: B0 r9 {Circle chart, 圆图
' l) y2 V q7 J% Q& g$ ^Class interval, 组距
( A. m7 E# Y# x! nClass mid-value, 组中值
' z) K. a; r! Y3 |; V! q' g" |2 bClass upper limit, 组上限( h2 z1 p& i" @8 _
Classified variable, 分类变量0 ]( H+ B- \9 f2 ^
Cluster analysis, 聚类分析
* K" u+ e2 F; H) g2 KCluster sampling, 整群抽样3 \; ]3 r- s2 x; ^, E% E
Code, 代码6 O; s) z! L* W+ z3 V. b! I
Coded data, 编码数据8 [$ O! A* c) y \# ^
Coding, 编码8 r; G# x% t, g1 t$ ~
Coefficient of contingency, 列联系数
$ d+ [6 Y9 A* XCoefficient of determination, 决定系数! b: ?6 t, f' H7 P( P
Coefficient of multiple correlation, 多重相关系数
/ M& J5 U5 O( V( Y$ e* d) N0 VCoefficient of partial correlation, 偏相关系数
( a( w) h5 L( dCoefficient of production-moment correlation, 积差相关系数2 `+ V) F% m; C2 t* w( f: Y
Coefficient of rank correlation, 等级相关系数9 X" `, {& S8 A" {8 O$ E
Coefficient of regression, 回归系数
4 S7 q0 l" w3 ~1 n6 CCoefficient of skewness, 偏度系数
5 Y& U0 g9 M( `, q' Z# \. X( zCoefficient of variation, 变异系数. w |; D' w- y
Cohort study, 队列研究% h! n& [ n( D# F& R* B1 p
Column, 列
2 f( E- v5 E, d. B7 D# PColumn effect, 列效应; R! v1 v8 ~& }. c5 Z
Column factor, 列因素
* a# h1 F& p# F' Z* f- W2 `8 A& i8 ICombination pool, 合并
3 G& f f% K4 r6 @Combinative table, 组合表& u, z, Y+ F) d- J- F& `, B
Common factor, 共性因子
" K; }+ U' V8 x* m' ICommon regression coefficient, 公共回归系数& m# A, `( T$ W3 Q0 R
Common value, 共同值
5 A! k, {5 U' l( s9 F& lCommon variance, 公共方差
8 b' V- o+ U/ v; uCommon variation, 公共变异
/ l9 S4 g6 y) pCommunality variance, 共性方差- Z+ t9 A0 W- k7 o" l
Comparability, 可比性" b( f. ]) s! m1 V9 U4 Y7 Q
Comparison of bathes, 批比较
+ m. y; h# D3 i1 u' P7 YComparison value, 比较值
, {0 L+ ^4 x3 C/ M3 o! D& RCompartment model, 分部模型
7 U# [" d: A3 RCompassion, 伸缩
9 U& z6 k' H" {# b! q5 E# xComplement of an event, 补事件% O) q4 h, H3 i4 b( P1 d
Complete association, 完全正相关
' J# {" l8 \( a! }Complete dissociation, 完全不相关
/ t. O3 z7 d" w5 G5 mComplete statistics, 完备统计量
/ i1 K2 |( R$ U: bCompletely randomized design, 完全随机化设计) p- r) Z6 a. V, X3 u4 c; _$ F
Composite event, 联合事件
' D* ~3 ]; R+ A9 a. kComposite events, 复合事件( I: K% }7 j. ?
Concavity, 凹性
: k: ]: {4 g, Q" H9 c7 SConditional expectation, 条件期望
; d) G" Q. P: P e9 c: a5 N" Y2 K [Conditional likelihood, 条件似然6 z) B# ~) [7 I. G
Conditional probability, 条件概率
6 A9 j8 d* {8 s: y6 T4 E8 nConditionally linear, 依条件线性
" i/ p% i4 [) H/ t" @Confidence interval, 置信区间 P3 b& V* I$ {: k- E' s
Confidence limit, 置信限6 {+ k r+ r. S' a7 v+ w
Confidence lower limit, 置信下限
+ P! F+ V1 C/ H1 B0 iConfidence upper limit, 置信上限8 g& D8 A) O- @5 ?! M- S
Confirmatory Factor Analysis , 验证性因子分析* j* P3 R0 k1 o" u" v5 b5 C0 @
Confirmatory research, 证实性实验研究/ P! N& t# Z: v+ B
Confounding factor, 混杂因素8 e' ~3 x+ E: l7 Z1 z
Conjoint, 联合分析
0 C; y0 S- {) A uConsistency, 相合性
0 o+ D3 j) _0 n. ]# } ]6 T) r7 rConsistency check, 一致性检验
' o, Y k7 B9 c/ U+ QConsistent asymptotically normal estimate, 相合渐近正态估计5 ^' \% O4 d2 l6 d/ w! v" N x
Consistent estimate, 相合估计 y! J' x4 _, k2 ~
Constrained nonlinear regression, 受约束非线性回归" I# \5 K+ C' I) ~4 [. [
Constraint, 约束
2 \6 ]& v+ c; l% o+ F# JContaminated distribution, 污染分布/ U$ U2 j' A- @; M
Contaminated Gausssian, 污染高斯分布
$ I! J1 a( v$ L2 Q6 tContaminated normal distribution, 污染正态分布
' s2 d7 g1 H& V7 \( _Contamination, 污染
4 r% I: l- w8 j6 n" m- ?) EContamination model, 污染模型- a0 b$ Z3 Y5 _) a( I4 B2 |- o' I/ f9 S
Contingency table, 列联表
( b' w" F9 P- T3 v5 [$ |Contour, 边界线
/ v0 | Y% X2 `) k2 L; ?/ R5 w+ ]4 lContribution rate, 贡献率
8 m4 s% d# ~: _8 c/ y1 j% q7 PControl, 对照6 o1 B5 h- h3 A; D
Controlled experiments, 对照实验
: R+ N$ {, _8 ]' _6 I2 XConventional depth, 常规深度
6 b# _% e. \2 c. m% V# e- \Convolution, 卷积1 G b& u& v- F; i3 V
Corrected factor, 校正因子5 P8 B2 |* _' h% j, t
Corrected mean, 校正均值
" E0 P$ E9 y: Z& F7 y iCorrection coefficient, 校正系数
/ ^$ D' {6 H. r) m$ xCorrectness, 正确性
; ~8 A/ m0 p% u, cCorrelation coefficient, 相关系数; q2 `7 `. }: o } {4 [/ T% @! ]
Correlation index, 相关指数& z, T3 }" a+ M" s4 J3 M* F2 q# j2 I9 A
Correspondence, 对应 J, ]& n+ H2 u" H( f6 ^
Counting, 计数
# }' E7 D+ |; UCounts, 计数/频数
- \+ \( I3 r% Y6 K/ C+ oCovariance, 协方差6 P5 T. s6 y! V( o. s) e# h
Covariant, 共变 % z5 e0 {8 N2 `
Cox Regression, Cox回归
& k% W# y, ^8 e8 R0 e0 HCriteria for fitting, 拟合准则2 i& R+ z2 y* \/ O
Criteria of least squares, 最小二乘准则/ Y U+ @* N9 u% U5 r% U
Critical ratio, 临界比# l/ J$ H' ~3 x! O3 n9 _9 d! c
Critical region, 拒绝域
6 L: F" Y* {3 {* ZCritical value, 临界值
9 ^' Q# o: m5 g# e4 OCross-over design, 交叉设计
9 Q: c; r/ g7 ZCross-section analysis, 横断面分析# u' l, G% k: J6 {4 M
Cross-section survey, 横断面调查3 s$ o; r5 m3 l$ e7 R) m
Crosstabs , 交叉表 $ ~5 b# _1 U5 [ P. b
Cross-tabulation table, 复合表& j# _0 u( r8 Y) P
Cube root, 立方根' d' C9 _! B) g# N
Cumulative distribution function, 分布函数
7 O7 R8 N( `7 `5 F6 p0 oCumulative probability, 累计概率
1 B' j/ M, D* q+ {' jCurvature, 曲率/弯曲
) E$ k# a9 \6 ]7 R+ q0 w& t0 pCurvature, 曲率
# H8 Z2 d/ N: \% eCurve fit , 曲线拟和 # A1 Y* }$ V7 x' @
Curve fitting, 曲线拟合/ q: d8 V4 o4 g' u, [
Curvilinear regression, 曲线回归
' F/ A7 Y8 J# {1 P! x1 @Curvilinear relation, 曲线关系& a8 Y. C9 ]! T' c7 e; o8 Z) h
Cut-and-try method, 尝试法
, M, F) ] l5 h u) HCycle, 周期+ d9 ~6 y1 b" B' e+ x I! w
Cyclist, 周期性
, Y- b6 g' d- Z3 F( d' s- r3 H8 vD test, D检验
6 Z. G) _" c# fData acquisition, 资料收集
) e8 G) F" H% K% c3 \6 N/ F6 z7 _Data bank, 数据库- ]( I! r) I$ `' |5 U0 r* O
Data capacity, 数据容量
) g# e ^8 r. N7 G6 l- iData deficiencies, 数据缺乏
* w7 y1 G+ I |1 C! kData handling, 数据处理
6 x ]0 d, t6 \& B6 H; GData manipulation, 数据处理
% ~) |4 k7 t, x# {: J- _" @5 kData processing, 数据处理
; f6 L$ }7 q8 ?/ V8 C7 LData reduction, 数据缩减* T: i( n# y3 z4 \4 C
Data set, 数据集! `% W* m7 Q7 a# K6 @ b
Data sources, 数据来源
! f1 M' p* L- K! IData transformation, 数据变换' [" i+ n/ ?, O8 e* f0 t3 h8 `0 e
Data validity, 数据有效性( g; @* `; D9 u2 p& @; S/ U
Data-in, 数据输入$ ~# S; o+ K. @! d( Z
Data-out, 数据输出
' w P! t+ }5 F: {- j8 yDead time, 停滞期# ]8 Z! A+ T4 I! x4 P0 m
Degree of freedom, 自由度
3 A5 Y& S% w, I9 `4 X( s" _Degree of precision, 精密度4 I/ U6 b8 V V8 P+ _
Degree of reliability, 可靠性程度
2 K7 k5 G% W K1 u2 f& {1 `Degression, 递减9 U5 }; ]3 r, U1 o& ^$ G2 y
Density function, 密度函数
' _2 ?: x: ` l) _/ s% X6 pDensity of data points, 数据点的密度
6 ?# O' b, `, H3 X, ]Dependent variable, 应变量/依变量/因变量
: M4 I E& ^% t( F3 w6 NDependent variable, 因变量
# H; F3 N6 ]. h- H7 J# @Depth, 深度
- {) |$ ~ [, a+ c' _7 C0 p" [Derivative matrix, 导数矩阵6 X! l& n" G: r8 n
Derivative-free methods, 无导数方法1 t- w% _" L* b2 k8 @ Q3 M
Design, 设计
+ n8 B( ` u( e! |7 y7 q0 oDeterminacy, 确定性 U/ K7 n; V( F* m
Determinant, 行列式; _1 k* v) e$ G9 K% f
Determinant, 决定因素
! C. B' d2 j* W+ i# mDeviation, 离差
K# K, ^0 e% o; J% JDeviation from average, 离均差
; ?9 v2 Z3 S% k/ W+ ^9 TDiagnostic plot, 诊断图/ B1 s F, H6 K9 F! u8 Q. ^9 ]
Dichotomous variable, 二分变量# z" K9 U" T6 Y& S$ L! J9 l1 O/ M3 h
Differential equation, 微分方程
$ {/ x' C8 V& i _$ BDirect standardization, 直接标准化法
" S* y7 G: G- s# A& U1 [( dDiscrete variable, 离散型变量
' `7 @, o8 e8 ^* m: p; HDISCRIMINANT, 判断
?3 D, T9 @6 x' G# ~) sDiscriminant analysis, 判别分析
3 {# F& S4 q7 _* Z0 X( eDiscriminant coefficient, 判别系数
/ b) [2 L$ d, i- EDiscriminant function, 判别值5 j: H9 x# ~. b; s( ?
Dispersion, 散布/分散度8 K' f6 ], a5 O& ~5 K
Disproportional, 不成比例的
2 T- I& G2 g' n8 y3 eDisproportionate sub-class numbers, 不成比例次级组含量
6 L/ i3 d7 ~) LDistribution free, 分布无关性/免分布! ^1 F; L7 {! q s3 d
Distribution shape, 分布形状- `9 ]3 a7 T: x* o
Distribution-free method, 任意分布法
2 |* z+ H9 t2 `, i( W _0 c+ {Distributive laws, 分配律7 H/ R1 e: Y9 X& }4 C+ M6 Q
Disturbance, 随机扰动项
& n4 z5 M1 ?7 ?+ xDose response curve, 剂量反应曲线# n$ B, o" u' g9 n% J! f1 M5 n
Double blind method, 双盲法5 k, H# Z& P2 w4 a7 K1 K: ~( R
Double blind trial, 双盲试验
' f* X. Z- ~0 Q+ @7 O/ T3 ODouble exponential distribution, 双指数分布; j. g; p7 p9 ], i8 v
Double logarithmic, 双对数0 @/ y& d% d f" A" `/ H
Downward rank, 降秩
' Y; V: S$ @. q5 I2 N* G' L8 v/ _Dual-space plot, 对偶空间图
7 a, g& C; c. v P" zDUD, 无导数方法
/ q1 T6 v; s% I2 K' S2 ~, fDuncan's new multiple range method, 新复极差法/Duncan新法
1 ~1 B2 n2 U: r* Q7 y( x! mEffect, 实验效应
6 R4 j1 |, p0 v1 {* j+ ^Eigenvalue, 特征值0 j3 c- d& }) R4 T6 V
Eigenvector, 特征向量
5 m! ^3 H+ D2 N! JEllipse, 椭圆/ b# a4 O/ m0 b. h: N# W
Empirical distribution, 经验分布, B* p3 H( @( S/ m
Empirical probability, 经验概率单位
5 O6 s3 m' Y; k3 J( Y/ gEnumeration data, 计数资料
* ~% x6 E; d* P8 n& o% J/ V" ?7 EEqual sun-class number, 相等次级组含量
! L& O" e4 x4 k8 MEqually likely, 等可能* j# D+ Z6 c& n9 X& I
Equivariance, 同变性
# \- r" l+ ^! ]3 ~5 oError, 误差/错误/ L% @& G( c6 ] ]" I" @, e
Error of estimate, 估计误差* {8 G* \2 J+ D' k) I
Error type I, 第一类错误4 o2 R4 `, k" d, \
Error type II, 第二类错误# o8 a* p) a- x- R
Estimand, 被估量5 u# n2 d# l, `. U8 [$ k
Estimated error mean squares, 估计误差均方5 m* {% D, _% [3 D7 K7 _7 N! z8 S
Estimated error sum of squares, 估计误差平方和
& v$ U# ]$ u8 F! X# Z# WEuclidean distance, 欧式距离
' j- Z0 K3 B OEvent, 事件
; q& N5 q$ [# T: \Event, 事件
) E4 K+ A3 U0 E/ kExceptional data point, 异常数据点6 Z, C6 n6 W, W! W
Expectation plane, 期望平面8 Y6 U4 r! J. g
Expectation surface, 期望曲面6 n8 e- s' b7 u7 ]3 E4 @
Expected values, 期望值8 W, c4 U6 c$ ^; l: g# p6 T) l
Experiment, 实验0 ^! h7 u* C) F2 B- { M
Experimental sampling, 试验抽样
3 N( @1 U2 s' X8 Z4 p7 R1 G# bExperimental unit, 试验单位$ q, x2 u6 Y4 P2 E" B( n4 A- f6 y
Explanatory variable, 说明变量
: }6 r8 d( n5 _Exploratory data analysis, 探索性数据分析
; r+ D6 d! i3 P2 ~! T4 ^- E$ L% WExplore Summarize, 探索-摘要
) p7 @5 k7 ^9 D8 F4 g& W0 \( p; CExponential curve, 指数曲线
, m0 A: X# X* X+ S7 p" b6 K4 ?* tExponential growth, 指数式增长
* Q- \5 I( \. M! p( R9 l" d3 LEXSMOOTH, 指数平滑方法
4 ~2 T% H2 L) J3 w/ z. TExtended fit, 扩充拟合& s1 C6 ~, r0 o/ U
Extra parameter, 附加参数; P) d0 y" J, ]$ L4 P
Extrapolation, 外推法
; m C3 d9 _5 o2 r% k2 L/ eExtreme observation, 末端观测值
- r6 U0 @0 n" l+ }3 TExtremes, 极端值/极值
6 T6 T& y# O; C& b# c+ d. y% JF distribution, F分布
8 m8 R* ^: v0 I6 h! rF test, F检验
$ v8 K/ x# Q( u( q: ?, h& xFactor, 因素/因子2 f$ ]! ]- Z2 \' X2 ^0 f/ L- Z
Factor analysis, 因子分析
( ], S% S, Q1 i8 v5 K+ ^Factor Analysis, 因子分析
) ~7 T. ~' D* ?9 D9 p, `* {Factor score, 因子得分 1 W8 K9 n7 X H1 [
Factorial, 阶乘
) \- Y/ Z( A S8 W/ m' XFactorial design, 析因试验设计/ v7 p# u6 T8 k9 j2 }; G
False negative, 假阴性
$ l0 H7 g+ S3 O8 N6 ] v3 CFalse negative error, 假阴性错误
. E. n+ b! ^2 ~9 GFamily of distributions, 分布族$ z' ?) { k1 U. @2 l
Family of estimators, 估计量族
- w# w1 p9 O( m! ?5 }6 d6 pFanning, 扇面5 n. l) B% c. u4 l
Fatality rate, 病死率: Q0 R6 z/ Q8 |* b) z" h- h1 d7 T
Field investigation, 现场调查/ ]8 F; X' m1 m) s R6 U
Field survey, 现场调查
' [( @' Y" P; NFinite population, 有限总体9 _5 K( e5 q. p' Z f
Finite-sample, 有限样本
M3 e9 [; H# t. Q% X1 hFirst derivative, 一阶导数
& ?; P4 F9 w- hFirst principal component, 第一主成分
' |9 [/ q8 B8 O) z# Y* ~( bFirst quartile, 第一四分位数
1 v1 w4 f! l" @- W" i0 v9 gFisher information, 费雪信息量$ } ^2 R+ `% \, i% R- \
Fitted value, 拟合值0 {! T. J. s+ v" ?$ e; v! g# \" b
Fitting a curve, 曲线拟合
6 T4 k: K" R( i4 L8 ?" oFixed base, 定基; Z5 |, q/ U) W4 c1 H
Fluctuation, 随机起伏
6 _, \1 ]7 E6 I4 {, GForecast, 预测5 b, q8 V3 y! L
Four fold table, 四格表
$ c* m. H( A, h8 D% g( p& I) }1 P1 R; ~Fourth, 四分点" Y& z! {' x: n. D1 m9 s8 o% H
Fraction blow, 左侧比率' H% R5 o. l5 l. {' }3 H3 w# ~
Fractional error, 相对误差
$ x: g" K: y) t* E( hFrequency, 频率
" b$ w: N# y2 }& DFrequency polygon, 频数多边图& g+ E, S& N$ S# P
Frontier point, 界限点
0 j& S# j7 C- y+ ?6 mFunction relationship, 泛函关系% {! P+ U1 P5 q Q t) e( H
Gamma distribution, 伽玛分布9 ]) ] A0 a' J% [0 X# j8 r
Gauss increment, 高斯增量
; _% {1 M) D5 q- RGaussian distribution, 高斯分布/正态分布: r, c1 b5 ^' e* E% y
Gauss-Newton increment, 高斯-牛顿增量, a2 ^6 x& i# U* z
General census, 全面普查7 N+ U; n% |* R- e
GENLOG (Generalized liner models), 广义线性模型 * T. h b" q9 Y; V' K
Geometric mean, 几何平均数# z: u6 H3 {# Z( d( Z: t: b6 Q
Gini's mean difference, 基尼均差
2 @5 V8 \' o+ X! _) I' TGLM (General liner models), 一般线性模型 , q& m- M( R& ]/ S
Goodness of fit, 拟和优度/配合度3 i4 y( t5 `4 F* [
Gradient of determinant, 行列式的梯度: b. @! y& B+ F$ U- B
Graeco-Latin square, 希腊拉丁方7 [) H. V( T, H' [. w4 Y5 U3 [
Grand mean, 总均值
0 _$ P) {, U# }Gross errors, 重大错误
2 n' C0 A( d2 m5 A: ^" p$ K" V) EGross-error sensitivity, 大错敏感度
1 V& G/ t; f+ l' `" IGroup averages, 分组平均4 O! d0 c8 \# m- o) X/ |
Grouped data, 分组资料
* d8 G' T* J2 l Z& ^Guessed mean, 假定平均数; ^- {- F/ v2 R' b/ k- r! a
Half-life, 半衰期
6 e. P: u7 X+ w+ k) h r$ o3 X% v* ]Hampel M-estimators, 汉佩尔M估计量
8 H' m* B9 F0 `% |Happenstance, 偶然事件! C" h+ s/ H8 q7 C4 h
Harmonic mean, 调和均数% s" i$ O2 @* M" u
Hazard function, 风险均数
, h% d* B8 |( c, }Hazard rate, 风险率0 D' h; c* c, P/ @* x" h* I f) j
Heading, 标目
4 o) Q7 f$ b( PHeavy-tailed distribution, 重尾分布+ b4 O+ @# o* t9 p; L8 u
Hessian array, 海森立体阵
4 A9 _* L% x/ LHeterogeneity, 不同质1 y. D% s( Y. z
Heterogeneity of variance, 方差不齐 ; s6 @5 g/ J+ x3 q; g$ {
Hierarchical classification, 组内分组) e! D$ e0 {. K# C& W) X
Hierarchical clustering method, 系统聚类法
! u" n" A0 m- o/ g; f8 [. \5 e# }High-leverage point, 高杠杆率点% ], b. V9 f( l2 Q/ M4 S
HILOGLINEAR, 多维列联表的层次对数线性模型; P& T3 _# |& Z5 H, k) Z ~; j
Hinge, 折叶点- W; ]4 k3 ^, j
Histogram, 直方图, h. s5 A& |- D' C! o' \$ y
Historical cohort study, 历史性队列研究 7 C6 O8 c# o: F8 `( z# _0 q3 w9 P9 u
Holes, 空洞
* H J) s9 M v. P/ zHOMALS, 多重响应分析' N& [) H# x& d
Homogeneity of variance, 方差齐性
6 F, l. S+ y2 ~( E5 @Homogeneity test, 齐性检验7 Z4 a/ ~1 N5 O0 h
Huber M-estimators, 休伯M估计量- [( y1 t% ~6 q& T
Hyperbola, 双曲线
1 Z$ g9 C8 D w! j( x1 x7 F5 }: Y' hHypothesis testing, 假设检验, y2 j+ D/ ^2 N$ x: E* {
Hypothetical universe, 假设总体1 ^$ R w2 n7 l% U4 H& T
Impossible event, 不可能事件
' Y$ Y5 v, n0 ?" x5 l/ m: dIndependence, 独立性3 u$ c! u. Q7 F- V' L" O4 ]" q
Independent variable, 自变量
7 a! ^4 |: ^, `8 j, {8 }. XIndex, 指标/指数
7 ~! v- L7 o0 t: {/ e bIndirect standardization, 间接标准化法# n2 E( z4 K7 N7 T
Individual, 个体( ^0 p1 Z9 b. ~0 h
Inference band, 推断带7 \! M Z* i' A) E7 i) y r1 c
Infinite population, 无限总体/ }8 E1 L V6 S) I5 d
Infinitely great, 无穷大
$ r- q( \6 w8 l) z8 O# p2 J5 ^Infinitely small, 无穷小& r+ S* |* I7 r& \
Influence curve, 影响曲线( `- L/ y1 E, [& {' r5 Q: L
Information capacity, 信息容量
8 F' p" Y9 w1 `+ K# t% Q: a7 @; EInitial condition, 初始条件
: o# m d- O. ]# A& KInitial estimate, 初始估计值$ U- _, {) M6 Q. t$ ^7 O
Initial level, 最初水平
' s+ |" e( f- m wInteraction, 交互作用$ r b1 `4 V' T8 w
Interaction terms, 交互作用项
; A; e# B8 w6 Y+ y4 kIntercept, 截距* u' E2 |' `! Q! e& @0 u9 `
Interpolation, 内插法
8 i0 n. L6 y. w! p/ L' i# NInterquartile range, 四分位距
* ?7 S9 ]1 h! z5 r. n* Q8 i0 dInterval estimation, 区间估计" `" l* M. j7 Y N: c* ^, k" I
Intervals of equal probability, 等概率区间
) H8 A H5 i* A- L* n1 kIntrinsic curvature, 固有曲率
% n1 y `( r% U9 VInvariance, 不变性, F; e: r! Y. L7 \! A* p# e8 E
Inverse matrix, 逆矩阵, j2 ^) Y0 n- m- M
Inverse probability, 逆概率
& U) R4 M; S' y+ eInverse sine transformation, 反正弦变换$ V6 h4 Q$ G7 b" W
Iteration, 迭代
% c. @+ V. ^2 X, ]Jacobian determinant, 雅可比行列式! j6 E$ P1 a; I6 o: c( H( X
Joint distribution function, 分布函数
. [. e" Q3 W# l+ g* rJoint probability, 联合概率
% r1 R% M8 w9 w/ cJoint probability distribution, 联合概率分布
% Y, j5 o; b: U5 w" }K means method, 逐步聚类法
( _9 h- Q1 h |# Q7 bKaplan-Meier, 评估事件的时间长度
; p/ u( K$ w6 V: D: j% I: V- fKaplan-Merier chart, Kaplan-Merier图* \! q6 ^5 E) V; D+ p
Kendall's rank correlation, Kendall等级相关' R( {0 d4 b0 L0 M/ @6 G' r
Kinetic, 动力学# J. |0 q* ?. P3 ^, _ p
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
3 A5 I9 U! \3 _& yKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
7 b2 v H$ {4 J; HKurtosis, 峰度
: E, j1 s8 Z, Q) z7 l' QLack of fit, 失拟7 C6 y4 F9 ^# J: v9 }
Ladder of powers, 幂阶梯
\ f2 t2 s) ~: j# NLag, 滞后8 {+ |2 ?; ^9 J8 f& ^+ E- ^( H
Large sample, 大样本
" Y. S0 o+ N* @; R6 q+ \' vLarge sample test, 大样本检验! T- \7 {9 p7 G# ?6 S' D
Latin square, 拉丁方
8 f- f% T) [* E+ f) }Latin square design, 拉丁方设计8 U% J$ F3 r* f1 {7 d
Leakage, 泄漏( c% i* D8 v: l$ h. ~
Least favorable configuration, 最不利构形& G4 J) K9 s# ?: t
Least favorable distribution, 最不利分布) G! c. H. ~% M
Least significant difference, 最小显著差法8 Q- y' ?" f2 A U$ g6 q# h6 H
Least square method, 最小二乘法
N* v: Q6 {" S8 C4 Z3 NLeast-absolute-residuals estimates, 最小绝对残差估计3 U- B: f! O/ z) Y
Least-absolute-residuals fit, 最小绝对残差拟合: }# o- z4 \$ q& M
Least-absolute-residuals line, 最小绝对残差线
! n- k5 N. V) gLegend, 图例
r& X) H6 N8 L' V* k: KL-estimator, L估计量. m# H# B$ f m! j$ e3 E. \
L-estimator of location, 位置L估计量2 Z2 b+ M- m y9 T" i6 \0 x
L-estimator of scale, 尺度L估计量: ^" N% m$ C, p; E g# l8 g
Level, 水平5 {0 ` x2 {8 o4 i( Q: e5 @
Life expectance, 预期期望寿命; x0 Y7 ~8 f) {. |- l6 j2 W7 u
Life table, 寿命表
, Z7 U2 R, K. I% {& dLife table method, 生命表法
) }' g1 D# \5 [# A# h% @Light-tailed distribution, 轻尾分布( R* K E( p; b' n! X5 u- r# f
Likelihood function, 似然函数
( a3 |0 C! q% |! J) u- L6 YLikelihood ratio, 似然比
1 p& P5 t- C6 U, g1 ~" ]1 |) Iline graph, 线图& A. ~4 ?3 S9 E8 g2 P" L3 b! O) i* Z
Linear correlation, 直线相关
# M4 m* \, T" Z4 n* O3 SLinear equation, 线性方程
6 X$ i; a& q2 M3 qLinear programming, 线性规划3 g& ?5 _: p% n5 k7 B0 i( r. o6 G
Linear regression, 直线回归
8 w4 S/ U# D# t8 VLinear Regression, 线性回归
9 B: v& f5 f) rLinear trend, 线性趋势: W- [# F7 ]2 Y" g/ u- M
Loading, 载荷
5 E3 n" Q7 ^1 d, G2 P4 u; o2 XLocation and scale equivariance, 位置尺度同变性- d/ T3 g; r# T: X
Location equivariance, 位置同变性, i K( P( M' E5 U; M/ c
Location invariance, 位置不变性
( }2 S7 U: [4 P7 u* w7 ELocation scale family, 位置尺度族
1 u/ D) c- V# @& ]3 ]: w, n2 OLog rank test, 时序检验 8 c6 T9 t7 c7 E2 @% G5 I( ~/ B
Logarithmic curve, 对数曲线
' A2 ]# E! X4 Q. k0 O2 p: I4 O8 wLogarithmic normal distribution, 对数正态分布. n3 @- b& N3 x- M$ K" C+ d7 M
Logarithmic scale, 对数尺度8 p8 |# F+ c" d- ?/ C8 Z# F0 e
Logarithmic transformation, 对数变换
1 H/ w5 n) w- ~" Z' i1 WLogic check, 逻辑检查 i4 v' j6 \7 o( ~2 s
Logistic distribution, 逻辑斯特分布
0 z+ }- U7 ]1 j3 A2 f8 HLogit transformation, Logit转换
+ n4 R: u2 \' n" N! x% Q2 G8 pLOGLINEAR, 多维列联表通用模型
! @% l+ ^1 o0 @- ?- K( \3 X7 BLognormal distribution, 对数正态分布+ Y4 Z2 B" ], G
Lost function, 损失函数
! i: z5 Q/ F6 BLow correlation, 低度相关* ]' w* W3 ^) B6 d8 e: ?
Lower limit, 下限
- F& ]4 I L# q/ ALowest-attained variance, 最小可达方差# V% c% o* P. ~- t0 W2 H( y
LSD, 最小显著差法的简称
7 u, p3 r9 n" c/ aLurking variable, 潜在变量
. l3 K2 v' B2 ~0 T1 E3 {+ M* EMain effect, 主效应$ {* w0 c# J D% W
Major heading, 主辞标目/ J" i7 b; ?6 `5 E6 t5 ` K
Marginal density function, 边缘密度函数' O" C% B+ Q, y8 |5 K
Marginal probability, 边缘概率
3 J' N/ a) L% A/ f1 oMarginal probability distribution, 边缘概率分布5 R0 c3 J( {) \2 K
Matched data, 配对资料& l1 j' K/ f6 H2 Y% X! `
Matched distribution, 匹配过分布
) C, ?. E/ m3 dMatching of distribution, 分布的匹配9 M! d; t1 V8 L* T( n: e0 I
Matching of transformation, 变换的匹配6 A1 r" \: d4 V
Mathematical expectation, 数学期望
1 b8 J3 r3 @ J7 I' G/ XMathematical model, 数学模型
0 b* q( q9 m; ^$ h5 t- {- f& gMaximum L-estimator, 极大极小L 估计量' W- Z, p, y1 I1 M; T
Maximum likelihood method, 最大似然法
9 K) P* Z. b% [4 [* F( s, Y, bMean, 均数# n- t$ x# I! C+ C0 I
Mean squares between groups, 组间均方0 w) e. z# \$ E$ z
Mean squares within group, 组内均方8 O7 D( I% Z1 J# d- I9 t
Means (Compare means), 均值-均值比较4 o- j# r' M" r* M* \: a2 {
Median, 中位数8 k8 L+ k: M1 p1 N6 j" ?! L; ~- r
Median effective dose, 半数效量2 k" g- ?7 R' h3 t4 M% c$ u7 S& H
Median lethal dose, 半数致死量8 a3 J/ h1 L6 M' ]6 M( o! p
Median polish, 中位数平滑/ _: f6 U0 j2 r' s1 @3 K( _' w. m
Median test, 中位数检验
+ Q2 o8 S( h; [Minimal sufficient statistic, 最小充分统计量. b( o( [) @/ P+ z p2 h4 ~) `
Minimum distance estimation, 最小距离估计: R" G. p" q0 s- {
Minimum effective dose, 最小有效量
9 { }+ d: k: @Minimum lethal dose, 最小致死量
- ^7 u5 O, G0 P0 G' _Minimum variance estimator, 最小方差估计量
4 j% g9 c0 Z, u$ F: |$ RMINITAB, 统计软件包
- R! n9 G. [6 f9 Z1 D" \7 OMinor heading, 宾词标目* {7 K% @1 s8 I( Y" h* S
Missing data, 缺失值- P, ^" B+ k- j9 Q2 o/ s9 V
Model specification, 模型的确定8 F) c4 s4 Q4 I
Modeling Statistics , 模型统计
7 j7 s: s" \# C' S; dModels for outliers, 离群值模型* ], A4 z) A+ V: a
Modifying the model, 模型的修正1 q: f2 d. r2 X' @% a5 h ]
Modulus of continuity, 连续性模1 Q Z. ~* H1 e* S+ a
Morbidity, 发病率 ! R, r( L7 V/ f! Q, n
Most favorable configuration, 最有利构形
, u- X& F- @5 |Multidimensional Scaling (ASCAL), 多维尺度/多维标度
, O6 q% L! t! B1 p6 ~Multinomial Logistic Regression , 多项逻辑斯蒂回归% m, [, V( @' S t6 h5 t3 T
Multiple comparison, 多重比较 c% l0 j% F# L% {% h3 }. r* N: x
Multiple correlation , 复相关 A; @: W" ]+ z
Multiple covariance, 多元协方差2 S- p7 g; v+ o w5 Y" Z2 O2 y
Multiple linear regression, 多元线性回归
& z' G& k, E' EMultiple response , 多重选项1 l ^) L. V; D S3 H
Multiple solutions, 多解8 {% N ~; v8 X. V7 P* o7 L* d
Multiplication theorem, 乘法定理
' _% b% \# ^3 _3 N5 X7 k, RMultiresponse, 多元响应' Y6 S6 R, R# D+ u
Multi-stage sampling, 多阶段抽样
( ]7 e0 c% R& f0 @Multivariate T distribution, 多元T分布& L1 q/ d: G }' |
Mutual exclusive, 互不相容2 q6 p1 o& `; ^6 u
Mutual independence, 互相独立
& c+ k1 Q# g, V! A1 |7 fNatural boundary, 自然边界
" ?$ f3 O0 {$ |2 CNatural dead, 自然死亡
) }( R& C! ~7 BNatural zero, 自然零% h- X z5 S% Y* ]9 g5 E" S- }
Negative correlation, 负相关
' E+ O5 b- {- l) k8 Y2 b! oNegative linear correlation, 负线性相关) g' x# ^" X* c. \' Z; H8 k
Negatively skewed, 负偏
6 E# V1 T4 g: R: G" k5 [! }! t7 \1 pNewman-Keuls method, q检验
9 Q2 _( w* R: w( z9 P" S1 W2 f! rNK method, q检验( w) Q. B1 `. l* K# O- C
No statistical significance, 无统计意义3 b- P8 G% \/ O$ R" b0 r
Nominal variable, 名义变量
9 Q2 K, D; L! f/ i$ WNonconstancy of variability, 变异的非定常性- Q3 [3 @' d' z+ \6 ]/ n0 m
Nonlinear regression, 非线性相关% c% f" ? `' |2 t
Nonparametric statistics, 非参数统计3 ~/ H+ @1 J; k+ N3 r8 U+ Y+ v
Nonparametric test, 非参数检验9 c0 c; c9 |: e2 y
Nonparametric tests, 非参数检验# w% M# ]& z' ?% Z, t
Normal deviate, 正态离差
6 n1 k. z+ H+ y$ f6 MNormal distribution, 正态分布
9 x5 o2 I# p% [- XNormal equation, 正规方程组
) \* ~: T' Z$ n# ENormal ranges, 正常范围
" X+ t4 ~/ X2 [7 UNormal value, 正常值
/ @- H, E, l+ W( o. {6 TNuisance parameter, 多余参数/讨厌参数
! I0 C" N6 B4 x6 QNull hypothesis, 无效假设 ! X0 {2 _; g' K/ m5 c
Numerical variable, 数值变量, V8 i' @2 }# u
Objective function, 目标函数
S; ?9 S; h6 X3 Y& m6 k9 C- v! QObservation unit, 观察单位
" Y9 l. Y" X& c }( Y5 h" t# _Observed value, 观察值4 Y9 ]4 y$ \2 j! Q6 A: T
One sided test, 单侧检验" }. r) R9 L$ _% l$ k, X
One-way analysis of variance, 单因素方差分析
, F. v7 V5 A8 R, D( ? yOneway ANOVA , 单因素方差分析
" V) v" L1 w0 g( [2 |0 tOpen sequential trial, 开放型序贯设计% W' }9 D9 S) |
Optrim, 优切尾3 \* k+ M5 o% U9 n+ s, `
Optrim efficiency, 优切尾效率+ [9 r% r2 d+ r0 a
Order statistics, 顺序统计量! H2 J3 p" c8 W* H
Ordered categories, 有序分类8 @5 t+ @4 ]/ y+ [" v/ {9 i& A
Ordinal logistic regression , 序数逻辑斯蒂回归
+ i$ Q* v$ }- S# Q3 d- q) X8 M1 dOrdinal variable, 有序变量
: M+ B1 m' ~; g8 R3 iOrthogonal basis, 正交基8 V3 H# T8 y. k! F
Orthogonal design, 正交试验设计
0 h& D/ [! X1 D0 HOrthogonality conditions, 正交条件
0 h+ i5 v, E/ a: w) t9 ]ORTHOPLAN, 正交设计
: p) a9 z. z5 a# B0 ?$ MOutlier cutoffs, 离群值截断点
+ P9 ^" i3 e8 V- Y8 S. r% KOutliers, 极端值
8 h% f6 l% g+ i2 DOVERALS , 多组变量的非线性正规相关 6 `% s5 X1 m- X$ J; t
Overshoot, 迭代过度
1 w; G" e8 k, ?3 s! A2 jPaired design, 配对设计
; q! [+ c7 Y D! qPaired sample, 配对样本
^9 K, J7 V4 ^0 Q R4 f6 QPairwise slopes, 成对斜率- Q+ Q2 c' e* k/ c( \9 P4 R, P
Parabola, 抛物线* ]7 L$ ~6 E9 V u7 N; E
Parallel tests, 平行试验
# P1 T8 q) e: V( ^. J$ |2 r$ [Parameter, 参数
8 U2 [; Z! P4 N/ x$ m# ?0 I5 M5 BParametric statistics, 参数统计
1 \+ ^% _$ C* C+ T$ W; kParametric test, 参数检验" _2 q9 K3 g- |. T6 L, a% e( s7 n
Partial correlation, 偏相关. T: H( i) ?) _( F# H) g5 V6 T
Partial regression, 偏回归2 w. w5 C. y$ k3 j: a) j2 t
Partial sorting, 偏排序
- _( @7 t9 i/ ]+ ePartials residuals, 偏残差
. h2 P* j" }" A$ o& s( _9 KPattern, 模式
' A# M' [# i$ k$ t' SPearson curves, 皮尔逊曲线1 e0 i8 e! V) p8 f5 ]3 S( N; |5 `- p
Peeling, 退层" |4 I, d2 P: L3 i+ `, j; b
Percent bar graph, 百分条形图/ X+ C! K8 q- `$ {, k# d: T
Percentage, 百分比7 Q$ ~3 p( G, [) R# z3 X6 t
Percentile, 百分位数
4 w9 V1 j2 M i- @5 oPercentile curves, 百分位曲线
' c( C# Q+ j9 U' p8 r: QPeriodicity, 周期性
) Q8 J, h3 \6 k [- kPermutation, 排列
3 a( L! F: b3 D' l: O9 [! q9 ^! P6 C% |P-estimator, P估计量
3 D. k! A" \3 f( |$ ~, G, H! D/ T# w8 APie graph, 饼图2 |+ Q1 W" o. `9 Y h: G- q$ M
Pitman estimator, 皮特曼估计量# S3 a9 x: d$ T3 B) T) Y, {' a% @- q
Pivot, 枢轴量
2 D% L. L& T1 U* P- |9 iPlanar, 平坦6 V" n+ Z+ p! G6 z, v9 O
Planar assumption, 平面的假设0 ^/ B& N( l _ \2 i
PLANCARDS, 生成试验的计划卡. p# E: g/ H5 |! _) k+ L( R
Point estimation, 点估计
+ U0 a( C& P4 Z; h/ b* b PPoisson distribution, 泊松分布2 u4 f4 \. ~( d) Q
Polishing, 平滑
L9 r5 q) O7 @! B3 W0 ~* c& UPolled standard deviation, 合并标准差9 G L# v C8 }4 o
Polled variance, 合并方差
4 n: R Y. B" l, Z6 w- g- UPolygon, 多边图
8 U k) `6 `4 T1 f; qPolynomial, 多项式
- b: L& T& W N9 ZPolynomial curve, 多项式曲线
1 G; m2 E; Q( r1 E! }Population, 总体$ a# j/ u) C0 O* l0 o. q) e
Population attributable risk, 人群归因危险度
8 L/ d. b5 G9 q. C- h1 d cPositive correlation, 正相关
% r3 k+ L% a! O% IPositively skewed, 正偏" ] q3 m/ k: h5 v
Posterior distribution, 后验分布
$ [7 p8 h- m3 \Power of a test, 检验效能: H4 p& _$ ]8 e9 `& d! k
Precision, 精密度+ Y3 H' d8 b2 T& M
Predicted value, 预测值
7 J" [* R& D9 t% w4 \Preliminary analysis, 预备性分析
4 r/ t( P5 p0 `( ?Principal component analysis, 主成分分析 J( n- h( {8 H! D2 |* C
Prior distribution, 先验分布
. b( Z# [9 L% n5 n( k* q0 BPrior probability, 先验概率, o. |0 G; H* G7 g" M8 B9 u* c
Probabilistic model, 概率模型% e/ S- E R1 R+ j( [% z
probability, 概率# }; N0 U* m) h p
Probability density, 概率密度) | J0 G# G$ D) w& s2 @/ G; x
Product moment, 乘积矩/协方差
) z2 W& Z! b; v, X9 LProfile trace, 截面迹图' M$ Q5 u* ?9 t D' ^
Proportion, 比/构成比
t5 d& [8 D2 e7 V; F- i3 S9 ZProportion allocation in stratified random sampling, 按比例分层随机抽样- ^- j- ~' x: n( n5 ?9 J
Proportionate, 成比例
; }. ]1 {# D( rProportionate sub-class numbers, 成比例次级组含量
! ^- P7 e% y0 ~. t8 ?Prospective study, 前瞻性调查
9 N6 O) ~6 d& a aProximities, 亲近性 5 M+ E/ `* _* r1 v+ w' C
Pseudo F test, 近似F检验8 J; V9 r% R- u- @% U+ Y# `/ J
Pseudo model, 近似模型
8 }! v b" }" b, K6 b% G. H8 nPseudosigma, 伪标准差' A6 V6 k. N8 W+ O% `
Purposive sampling, 有目的抽样
* W' V. K! v- R2 H0 }QR decomposition, QR分解9 N% O: [! M8 a* q5 F
Quadratic approximation, 二次近似
) P# s m9 ?1 M3 fQualitative classification, 属性分类
! C2 {& [: B m4 f, f9 b0 YQualitative method, 定性方法
+ u& g, d* m n% ]. bQuantile-quantile plot, 分位数-分位数图/Q-Q图1 z+ e+ M' |& ]. H
Quantitative analysis, 定量分析" s# n, ~1 ^( ^3 k
Quartile, 四分位数 a( ~/ m# E. c* j
Quick Cluster, 快速聚类
. i: P1 ~2 Q7 f9 {) J$ _Radix sort, 基数排序
" N7 \! w& C* Q- S" O. r/ ~& _Random allocation, 随机化分组, F! k0 Y+ t2 ^$ b; l* }9 ~. g
Random blocks design, 随机区组设计
1 O. r3 @" g2 X5 wRandom event, 随机事件
3 t7 a6 n! m3 J8 B% b g# k, rRandomization, 随机化
/ E' F _( O$ t D- t5 U0 fRange, 极差/全距2 E* t2 s% r" g6 J: O+ `3 h4 l
Rank correlation, 等级相关
9 V' H( A6 ~8 \$ aRank sum test, 秩和检验
7 V; I9 p9 x& XRank test, 秩检验
. ~- z) g( {, ^8 D( S5 e2 yRanked data, 等级资料) d2 J4 d8 e/ w p) Z
Rate, 比率- \, T* }9 r t( c; q$ e
Ratio, 比例/ a4 e8 k! f$ J
Raw data, 原始资料# s2 L5 ?3 C) v; J
Raw residual, 原始残差0 Z0 l; {4 g0 e) Z7 H( c
Rayleigh's test, 雷氏检验
4 E7 f0 k9 K1 u% f) ~/ H N: LRayleigh's Z, 雷氏Z值 4 N) C( Q+ R9 e* b! ^6 A+ m
Reciprocal, 倒数6 q# g( I8 k6 {* V' g
Reciprocal transformation, 倒数变换
% y' N) O* y- nRecording, 记录) `/ d5 ^8 J5 R9 {) T, j# R! U9 t
Redescending estimators, 回降估计量
2 L2 Q* w% ^! D. OReducing dimensions, 降维# ?' I. @: l8 x- {
Re-expression, 重新表达
4 s" X$ \7 k! Y' }0 SReference set, 标准组
' a% x" d7 U4 |, P. NRegion of acceptance, 接受域
- m+ i" m/ ?1 G9 CRegression coefficient, 回归系数# e* D. W( _1 p0 T2 i1 q
Regression sum of square, 回归平方和
" q' D+ s( c3 _. eRejection point, 拒绝点
1 T8 A2 g C( f4 \6 K1 @Relative dispersion, 相对离散度0 _9 \2 W4 B$ D) ]8 g0 @2 v
Relative number, 相对数9 T* {- p1 {9 s, m( H
Reliability, 可靠性
7 q% l; q( _, s6 n" q* y2 nReparametrization, 重新设置参数% ?3 g: P) m# y! ~6 C/ {5 O; A: e% H
Replication, 重复& ?2 t. j% @ _5 r# g4 }
Report Summaries, 报告摘要
; ? a: A# e3 S/ n+ kResidual sum of square, 剩余平方和* } |" C1 n( E5 J
Resistance, 耐抗性
, ]* W$ B: _# sResistant line, 耐抗线5 F; L3 `6 d, V
Resistant technique, 耐抗技术
( j) L3 b8 v: P) A# b+ mR-estimator of location, 位置R估计量: b% N& V+ v* z
R-estimator of scale, 尺度R估计量2 F$ g) O8 G5 X! H3 a. ?; @
Retrospective study, 回顾性调查! [9 R& v9 n* E! k, x5 y
Ridge trace, 岭迹
* N; J1 t+ a* E# C3 X4 w" aRidit analysis, Ridit分析
8 | i3 G% i% xRotation, 旋转% C& W; `! `' [5 |# K/ P- N# x
Rounding, 舍入6 m r* }' h( J# H4 c/ \) i" V
Row, 行, s9 ?$ z% a/ f
Row effects, 行效应2 v" c% x6 d2 \' B# P# d
Row factor, 行因素
' O& |( ~* u: gRXC table, RXC表# f8 h. Q+ f0 K) U4 E% }4 [$ t5 i
Sample, 样本: C: D9 T3 x5 `( D7 l
Sample regression coefficient, 样本回归系数3 T/ T6 y) d' w( X
Sample size, 样本量
( K, m( n7 Y" b, j" R+ w8 v. ?Sample standard deviation, 样本标准差
9 Y4 k& S) t8 H/ w/ Q. VSampling error, 抽样误差
N D; P! D2 b8 G+ ^SAS(Statistical analysis system ), SAS统计软件包
7 f: b4 \* c: B! w5 t% pScale, 尺度/量表& }1 Y2 T9 I. r7 M: N
Scatter diagram, 散点图+ l) [ @) _% F9 Q& m
Schematic plot, 示意图/简图' p. p/ R2 P* w0 {% s
Score test, 计分检验 I$ W# E; _0 H0 z( }8 @' o
Screening, 筛检
2 C2 s/ s) o# x' l+ MSEASON, 季节分析
1 t' b$ o* _9 q3 mSecond derivative, 二阶导数
6 f4 u+ S, ]$ d- \% ]Second principal component, 第二主成分
3 _) p& ~5 P P. Z6 p8 x/ w; a+ QSEM (Structural equation modeling), 结构化方程模型
9 b6 p( p: m7 G5 Q! ASemi-logarithmic graph, 半对数图
* ^ M u- Q0 ~ k e, RSemi-logarithmic paper, 半对数格纸3 w4 P( C3 \8 m: A: N5 w
Sensitivity curve, 敏感度曲线& w! h& X9 d4 e8 T+ \1 l/ H( ~
Sequential analysis, 贯序分析4 [$ C7 Q2 Y# @) ?# l- D& ~
Sequential data set, 顺序数据集
0 R7 s% m/ g) \- r. t5 GSequential design, 贯序设计9 [- o8 ~( w- e7 B+ T | u3 I
Sequential method, 贯序法' V* J- A. {6 F+ h! M& j0 l/ _
Sequential test, 贯序检验法& v# G& b( ]: g. `
Serial tests, 系列试验' }& W% U( p# K
Short-cut method, 简捷法 : X, e! ~2 l2 z
Sigmoid curve, S形曲线
# e( d" b6 U4 c" \Sign function, 正负号函数( ^! V. r9 x: v2 V3 G
Sign test, 符号检验
I, v. p9 a2 v5 {7 b5 l. |Signed rank, 符号秩
3 Y+ C+ l" p$ p, E& dSignificance test, 显著性检验
3 ] ?4 D0 T* k1 E9 HSignificant figure, 有效数字
+ @) D1 j* B8 q) w# S9 R% pSimple cluster sampling, 简单整群抽样9 Q* P% I- r6 c G6 }" r0 h# _
Simple correlation, 简单相关
: c3 S, h3 W0 j( X' _Simple random sampling, 简单随机抽样
, m: E5 C- ` d7 a/ C6 z) [Simple regression, 简单回归
: r: d; V, c0 h/ H' S. h: I9 m# Dsimple table, 简单表% A( z3 \/ G- C/ K
Sine estimator, 正弦估计量% V) w" s* X& C8 Y1 \ c
Single-valued estimate, 单值估计
, @7 N% _* }# m& @* ]7 k4 M7 \Singular matrix, 奇异矩阵2 k+ ~ B% O Z
Skewed distribution, 偏斜分布
, i6 Q1 S7 O) ^6 LSkewness, 偏度
; `. Q) \/ D' d+ f; D; J& ?, ESlash distribution, 斜线分布9 J# L- a! Y+ M7 Y. }
Slope, 斜率% t v, j" s6 [# X, P& s
Smirnov test, 斯米尔诺夫检验
& p2 A# T8 s2 L) _( F6 gSource of variation, 变异来源0 W8 i: |" \2 S+ @7 Y8 d; V
Spearman rank correlation, 斯皮尔曼等级相关
2 J6 z: I/ y3 `& ~7 U/ V# @Specific factor, 特殊因子& h' f! C& n3 y& L/ C; O
Specific factor variance, 特殊因子方差( X% L8 b. q+ B( k+ `2 }
Spectra , 频谱
# I0 p" W& J+ O1 p& y1 u! cSpherical distribution, 球型正态分布
1 ?2 B' w' z" D/ L: ?: @# r/ nSpread, 展布
4 ?( Z- F0 w! E0 k& ~$ {2 T1 \7 eSPSS(Statistical package for the social science), SPSS统计软件包# I8 e6 e6 S+ L) v
Spurious correlation, 假性相关) U1 c8 I; V6 n0 f; ?
Square root transformation, 平方根变换$ L. c8 i/ D n: B/ {- [4 n4 Z
Stabilizing variance, 稳定方差% u; ?' c" A& }* e5 C
Standard deviation, 标准差
/ g$ B5 Z+ |2 T# P. _Standard error, 标准误( B8 z% y6 y& U2 F" D
Standard error of difference, 差别的标准误# i- g- R; O `5 ^
Standard error of estimate, 标准估计误差0 Z# o1 w$ G% {) ]7 ~
Standard error of rate, 率的标准误
+ N* ?4 q+ @8 C' TStandard normal distribution, 标准正态分布: c# _ g. y" ^
Standardization, 标准化9 I, v6 N3 |+ N$ C0 {
Starting value, 起始值5 B6 d% l2 S+ k" k+ {9 d3 x# \, ]% S
Statistic, 统计量' N4 L% Q- D; e6 j% G) G# b
Statistical control, 统计控制& w a9 F; T' q: v
Statistical graph, 统计图% a" F& A2 _4 D
Statistical inference, 统计推断4 |+ ^2 j- r9 V, R6 A6 ^0 b
Statistical table, 统计表) j+ P& D$ G; P+ k
Steepest descent, 最速下降法
7 y+ N) k% g# UStem and leaf display, 茎叶图
$ i- m+ Y' g; J( I% V: V" RStep factor, 步长因子9 P* ]. u* K3 W: | b7 F
Stepwise regression, 逐步回归
' R8 F. h% a! h$ o8 {Storage, 存* l1 l% j, y# Q! z R
Strata, 层（复数）* h! i% n7 b0 G" I8 _
Stratified sampling, 分层抽样7 P8 d5 ]' u' r0 g! h8 ]
Stratified sampling, 分层抽样+ m3 E! n( Y( H' n; K* X/ x
Strength, 强度
+ H/ t& h9 B9 g8 G/ x1 |1 } Q1 X. ]7 @Stringency, 严密性 F4 E: U! T* \! B
Structural relationship, 结构关系" {) x6 }# L, Q" {( o* c
Studentized residual, 学生化残差/t化残差
" k& @4 }" Q9 X4 e+ gSub-class numbers, 次级组含量' V0 f9 w$ Q6 |- w% ]
Subdividing, 分割. D) K, R2 V4 I8 y4 C, L: b. z0 w
Sufficient statistic, 充分统计量$ P9 X: k( a. y
Sum of products, 积和
* e' [7 n; X) hSum of squares, 离差平方和 E1 W2 b% ^9 |4 r7 ?- V$ [
Sum of squares about regression, 回归平方和1 h. u3 {* E8 Y
Sum of squares between groups, 组间平方和* A/ c3 }6 d6 ^* y# Z$ l; t
Sum of squares of partial regression, 偏回归平方和
/ [4 _! s3 }7 ]2 jSure event, 必然事件2 ^) b8 w5 b. c0 _( d3 A
Survey, 调查
- S; m) ?. m f1 V7 _: J: oSurvival, 生存分析
4 g6 `% v. a) ?" ~9 Y, ~Survival rate, 生存率0 @2 O- N7 a' @1 z& |' U. @: |# {0 {
Suspended root gram, 悬吊根图
# r" p( R1 r" u& c q+ }Symmetry, 对称
4 C& p7 ^2 S! u& D( w2 @0 n4 @Systematic error, 系统误差
$ z1 x) y5 r2 c _- YSystematic sampling, 系统抽样
6 B; S7 l" {% _1 LTags, 标签* k- a4 r, |: S4 j0 c. E$ e+ i
Tail area, 尾部面积9 Z, s' Z+ g$ m/ Q* W
Tail length, 尾长6 U" |" @3 J; K, C
Tail weight, 尾重, C& `8 s) p# B8 t1 f; _
Tangent line, 切线 ~7 j% M6 r+ G; ?! C. |2 V) d
Target distribution, 目标分布
: m7 w& U4 G; E; KTaylor series, 泰勒级数
1 D1 S9 P# W+ X; o2 |Tendency of dispersion, 离散趋势
9 o ]2 U1 A! L) A$ C% K+ jTesting of hypotheses, 假设检验
' Y9 w* T; W P4 Y( H2 ZTheoretical frequency, 理论频数
9 F3 C; d+ q, o( I! z4 p: b4 ^Time series, 时间序列
3 d A3 y! ^! FTolerance interval, 容忍区间
3 x3 W; h+ F) j* _Tolerance lower limit, 容忍下限
7 A/ w- ^6 A, n {9 kTolerance upper limit, 容忍上限. R( f+ u( J b$ `- K7 i
Torsion, 扰率
6 [6 z; R, Q; p/ `' ?" yTotal sum of square, 总平方和
9 G/ v+ l; _0 K J! A( `9 hTotal variation, 总变异& L( p; ~4 e8 o" _8 B) K
Transformation, 转换
' k; Y8 J7 G) R, L: w) {Treatment, 处理
+ n. X7 d# n- t" d% G0 ?& n7 {Trend, 趋势
: L1 `# X. h2 n2 }2 P- a. HTrend of percentage, 百分比趋势$ T. u. i" s. {- ?. \
Trial, 试验
4 S2 y/ W+ r& M* Z0 v; l- g. GTrial and error method, 试错法, D9 q+ [7 N/ m) L$ v
Tuning constant, 细调常数+ z6 u+ a f7 _# \* v+ B
Two sided test, 双向检验6 l+ Q: F3 z; a6 v5 e# }. V4 F V1 n7 T8 j
Two-stage least squares, 二阶最小平方3 T& T- z; V' @' V U1 a/ D
Two-stage sampling, 二阶段抽样
- ~; Z8 L- o$ kTwo-tailed test, 双侧检验$ j4 N& |" P$ ]
Two-way analysis of variance, 双因素方差分析
4 _6 J9 {8 C7 k" V: u! ]Two-way table, 双向表& W) B: c% W7 ~
Type I error, 一类错误/α错误2 m0 o# ^' u: M+ B* {
Type II error, 二类错误/β错误
( @0 Y8 O% c- v0 [; \& _UMVU, 方差一致最小无偏估计简称
* x" i8 S: X9 }% E( L4 Q5 p: g4 m7 D5 GUnbiased estimate, 无偏估计; V( K' l% O1 r, N6 I3 _2 l
Unconstrained nonlinear regression , 无约束非线性回归; }9 ]2 i" G3 _& e" Q2 o. A) k9 {
Unequal subclass number, 不等次级组含量
7 J; u6 Y M [" B: `" O4 j( O. aUngrouped data, 不分组资料
6 _; |! g0 g- n/ CUniform coordinate, 均匀坐标
0 A7 a3 H2 i4 @ |/ [1 wUniform distribution, 均匀分布' n) r' ?1 {: e( \1 t& S
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计& \5 r! C. r9 E! ?" Z; f) W9 e4 \+ M
Unit, 单元0 R. n. R* b" D
Unordered categories, 无序分类
8 P$ o, t+ J5 d- d8 F- Z" jUpper limit, 上限
: |6 f6 K5 Q: O! X; BUpward rank, 升秩
# U. z; W9 ^2 G- |Vague concept, 模糊概念
. x4 n6 w- {5 C z/ ^Validity, 有效性; d* T1 ] N- f( H7 M; D. y6 Z/ h
VARCOMP (Variance component estimation), 方差元素估计
/ A% N( y$ ]) p- ^2 fVariability, 变异性, g, F, a3 W) t: V, W
Variable, 变量/ a: w) O, e3 g* K
Variance, 方差1 r: C* r, G; T6 ?0 s
Variation, 变异! P1 w& r% i+ i( r+ K
Varimax orthogonal rotation, 方差最大正交旋转
. q0 ?2 V+ \4 n7 f) y* MVolume of distribution, 容积
# G- l( V2 K( p: C0 nW test, W检验
( W# N# o1 W; ] V& AWeibull distribution, 威布尔分布
+ X/ ^- s9 o. q# I( H7 ^7 sWeight, 权数
2 N' v: L8 @4 t' E3 K2 y. tWeighted Chi-square test, 加权卡方检验/Cochran检验
0 M W5 M: P$ j. ~Weighted linear regression method, 加权直线回归/ F1 m2 T2 U0 u) ?9 b
Weighted mean, 加权平均数
1 u. n9 C2 K0 j% ^" A- b% P! AWeighted mean square, 加权平均方差
7 M; ^/ l& q$ RWeighted sum of square, 加权平方和
+ o" c* M( y# T6 mWeighting coefficient, 权重系数- g+ S0 [+ {/ X/ D( k- j9 T
Weighting method, 加权法 % Z! S/ W8 X! q R4 N
W-estimation, W估计量4 S: u1 J/ i: [4 T/ ? x
W-estimation of location, 位置W估计量8 g5 o+ Z4 k: O# T% K- e
Width, 宽度
* V# o" v, o0 Z8 _Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验& v) j& d+ V+ [$ @8 T
Wild point, 野点/狂点
' a& V9 Y) O3 Y2 X8 QWild value, 野值/狂值
5 D& @( \' ?! k3 Z7 t1 a, ?# ^8 WWinsorized mean, 缩尾均值
3 H8 _# ]3 r; Y) N1 H3 o0 K0 f) rWithdraw, 失访
& }' b. F0 m+ V4 DYouden's index, 尤登指数& N; a* N3 h. i* h& u- e
Z test, Z检验' A$ g* x t* j4 E
Zero correlation, 零相关
1 J6 L3 |0 c0 A$ B3 s& D% |& V$ ?& nZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
