|
|
Absolute deviation, 绝对离差
7 R0 A7 _- D- w9 j$ x+ x: s# i' hAbsolute number, 绝对数2 y# L( G/ @# T: X# D, ~
Absolute residuals, 绝对残差
. c2 `1 q2 U7 T/ F& Z1 BAcceleration array, 加速度立体阵
: D: T7 F2 H7 `7 Y- h9 Y! S1 hAcceleration in an arbitrary direction, 任意方向上的加速度
# y3 Y t+ ?, H! L4 [' e6 z. SAcceleration normal, 法向加速度
" r1 ?, t. V! B4 L( R0 A5 B9 wAcceleration space dimension, 加速度空间的维数7 C& _" X& i$ @: y5 e6 ]7 R- Q
Acceleration tangential, 切向加速度
. R, L) N2 [& B* c( i5 s- z, U* uAcceleration vector, 加速度向量7 ^5 B' d9 z k. Q0 q7 M! Z; ~" ^
Acceptable hypothesis, 可接受假设
1 E1 g/ G# z& b1 sAccumulation, 累积; u I+ k8 \6 X- N
Accuracy, 准确度- Z4 k4 `" g( r6 H7 d3 Y6 j
Actual frequency, 实际频数
$ M" E: v2 E7 |; _. `$ M" t9 sAdaptive estimator, 自适应估计量
( b0 O0 x; ]: t# Z3 C }Addition, 相加
6 v" [* n0 P! v2 ]. @. J9 MAddition theorem, 加法定理
- P3 o/ O' w7 b3 SAdditivity, 可加性1 r* z# V8 Q1 T
Adjusted rate, 调整率: g& C& `6 Q% @/ A- x+ x7 U
Adjusted value, 校正值
+ r6 U9 z: a5 o: H" z c/ G: R/ SAdmissible error, 容许误差
6 y% V9 N" F# y0 Q) G) d) o9 K% \0 fAggregation, 聚集性
f( C! S. w* U. hAlternative hypothesis, 备择假设
& X# e. ]' J' t, p$ OAmong groups, 组间; n5 ~5 R1 m2 c- p' q7 o6 L$ N
Amounts, 总量
' I# h5 [6 G0 B& iAnalysis of correlation, 相关分析
' |0 F) P3 a# J# a' {Analysis of covariance, 协方差分析. \" g0 H6 s# ]" r7 H$ X4 M A r
Analysis of regression, 回归分析/ g: a$ w" { N- B0 `) k5 \( c
Analysis of time series, 时间序列分析
" ]3 z* w. X9 ~1 O9 g3 r" oAnalysis of variance, 方差分析
" _7 z& o5 n" i2 _Angular transformation, 角转换+ V. l& p0 r/ j$ Y$ A) C5 U8 m
ANOVA （analysis of variance）, 方差分析
8 x4 t2 _0 O3 ~# V6 hANOVA Models, 方差分析模型
6 N+ N- F* I' ^. b6 l, E6 DArcing, 弧/弧旋% ?4 _1 _& G. U) _$ g
Arcsine transformation, 反正弦变换) T+ S7 |( h4 v( k. E" T+ G- `7 l
Area under the curve, 曲线面积9 t0 D0 s* |# z' e6 l9 U
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
$ ?5 B4 L/ b1 W" Z/ B7 x2 oARIMA, 季节和非季节性单变量模型的极大似然估计
. _- X. C! n" [; J# jArithmetic grid paper, 算术格纸
- m3 G/ `" _9 w0 n8 D, i( |7 nArithmetic mean, 算术平均数" v ?8 ]4 u* y
Arrhenius relation, 艾恩尼斯关系
# ^) Q$ b0 V, M, {$ Z5 ]Assessing fit, 拟合的评估' @8 ~( [1 R- b: C. k H2 }
Associative laws, 结合律/ q% ~. c. y+ b$ L0 K, _% m
Asymmetric distribution, 非对称分布
0 e" p; `: F0 D/ S/ N* sAsymptotic bias, 渐近偏倚8 N$ E2 r4 T! A5 @. c; \) [
Asymptotic efficiency, 渐近效率
0 E7 x6 l) r% `2 i3 A- y: wAsymptotic variance, 渐近方差8 i2 E+ n7 b' ~, C0 i! v% a
Attributable risk, 归因危险度
* B2 P8 [3 ]2 y5 n0 bAttribute data, 属性资料
, n- H' E7 X {9 WAttribution, 属性
' ^( h& E$ v! e; E \. I7 ZAutocorrelation, 自相关% R3 ?. y/ C& h2 I4 y
Autocorrelation of residuals, 残差的自相关
( Q: x9 H, T0 Q) F& \Average, 平均数+ N% h( ^8 N9 N
Average confidence interval length, 平均置信区间长度
, D! c# Y' ?) r% nAverage growth rate, 平均增长率
2 p# H" O, Q- e7 f7 R6 N+ D/ k% [Bar chart, 条形图
) `4 v; \& V0 z& o: }! uBar graph, 条形图
3 a$ @* ]$ z5 _* m8 v* A+ pBase period, 基期5 O6 @0 X8 a2 Y s% M0 ]: `* ~
Bayes' theorem , Bayes定理- K& P- @2 N2 e, q
Bell-shaped curve, 钟形曲线
w: s) J" K# SBernoulli distribution, 伯努力分布
, x7 K t9 f; y) i$ h# ?Best-trim estimator, 最好切尾估计量
/ a: C7 c4 G6 M( r! _7 a# GBias, 偏性+ j( X! F- z1 O/ T
Binary logistic regression, 二元逻辑斯蒂回归
8 a" | f2 |. R0 W7 F( L9 _. @: mBinomial distribution, 二项分布) {, f- B" O/ H; p- G, X0 |
Bisquare, 双平方/ y: g, I y" f* E
Bivariate Correlate, 二变量相关
: U) L* Q$ |# H# ~7 W! GBivariate normal distribution, 双变量正态分布* G" R* n: |5 T& e
Bivariate normal population, 双变量正态总体2 a9 z0 D( F0 P
Biweight interval, 双权区间
# N, {' l) s, z$ A8 @: oBiweight M-estimator, 双权M估计量9 E! p* g- \' z/ m1 H# m( D
Block, 区组/配伍组
! E( T/ B: q: WBMDP(Biomedical computer programs), BMDP统计软件包
( d0 k4 |0 I; Z8 \Boxplots, 箱线图/箱尾图5 m8 P7 U C* k* m* r# a
Breakdown bound, 崩溃界/崩溃点
. [; ~5 G5 G2 UCanonical correlation, 典型相关 X. Y( T2 }# o) F2 ]" @
Caption, 纵标目2 w- H8 x" L0 d1 F" P; A6 S' Y
Case-control study, 病例对照研究
, x0 X! G7 @ L% JCategorical variable, 分类变量9 ~/ g* P" i. z0 n. b
Catenary, 悬链线
! d2 ^9 k. n* {$ D- Z; dCauchy distribution, 柯西分布
" o2 b+ f/ X: e( W$ b4 B; E- wCause-and-effect relationship, 因果关系
2 P2 \( E P3 @4 s) l8 L: ^3 ^# d( e SCell, 单元
' S% f/ E# D0 q" H" g3 \0 Q$ _1 K( ~Censoring, 终检, a1 J) P- d6 w0 J0 U# d
Center of symmetry, 对称中心
6 m F4 i3 [) kCentering and scaling, 中心化和定标$ Z/ c% D( a t$ ?
Central tendency, 集中趋势
' u4 d; O( L4 W5 YCentral value, 中心值* V% a; ]1 x8 z K8 |
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
! F t8 R( b) HChance, 机遇
* ] `0 z' v/ K1 _4 BChance error, 随机误差
$ J" U, m ?% T5 a) kChance variable, 随机变量
2 ~0 \8 |: q! v, [: M0 V+ \Characteristic equation, 特征方程8 F5 l- `9 b+ A& k1 y4 o5 ?
Characteristic root, 特征根: d8 z& J5 H4 ]. X
Characteristic vector, 特征向量
3 ?( H5 {* q5 x7 H. X6 e4 f9 ?6 cChebshev criterion of fit, 拟合的切比雪夫准则
$ H. I1 G8 u4 b; A/ |5 q/ rChernoff faces, 切尔诺夫脸谱图
& H: |2 B4 W) m8 vChi-square test, 卡方检验/χ2检验) F5 Y$ u# U" O7 r9 J# g
Choleskey decomposition, 乔洛斯基分解
! l, w% {% T v& N; P3 g; @Circle chart, 圆图
0 ]! B q9 Y4 c" b/ b" h5 iClass interval, 组距
* O. i1 b0 C8 J+ w* [7 a( nClass mid-value, 组中值
$ V. I' O7 U; e) t& y! Q2 D0 KClass upper limit, 组上限
. c+ ]( j) b, lClassified variable, 分类变量
0 ~; q4 ~, y0 w/ Q8 G0 qCluster analysis, 聚类分析
9 y* V! y! g* N6 v7 I9 dCluster sampling, 整群抽样7 l5 R# j0 @* \( E/ P
Code, 代码
9 X$ A4 [+ m+ c- uCoded data, 编码数据9 i9 ~, a; j" ?, Z4 x0 D* P
Coding, 编码
6 q% x ]/ @5 H" f, }Coefficient of contingency, 列联系数
" R; `+ B" w2 L" n* }7 U. T5 }; |& cCoefficient of determination, 决定系数
1 z) d4 @/ M: kCoefficient of multiple correlation, 多重相关系数
" z: B8 g2 m1 W2 R: v. T' _; ACoefficient of partial correlation, 偏相关系数
4 T& ? Z" P: ^$ ]3 v2 CCoefficient of production-moment correlation, 积差相关系数8 l. }& n- ^* w* r1 W. i
Coefficient of rank correlation, 等级相关系数& A5 y: ^9 x3 ?4 x
Coefficient of regression, 回归系数/ z9 f' A% @0 u6 f3 ^; c0 U% f5 {: C
Coefficient of skewness, 偏度系数, U$ a& c1 R; J g/ |5 h5 K% X% {
Coefficient of variation, 变异系数
8 D1 ~( `' M7 U# C) dCohort study, 队列研究' H) A2 O5 d! `+ k$ [- f! U
Column, 列
7 d/ ? Y0 x+ K9 w9 sColumn effect, 列效应- Y/ A& b- j( M) ]5 M" l" s
Column factor, 列因素
3 v( b i' ]1 I2 X) ?: d6 oCombination pool, 合并, G' R6 d; a- W* L( i
Combinative table, 组合表
( ]; ^6 f+ }* g$ F# YCommon factor, 共性因子0 d: F4 W5 e8 u9 T( B4 I
Common regression coefficient, 公共回归系数
; d3 ^8 y, e. c* }" I# ICommon value, 共同值& u: A; N2 d5 s4 Y4 |/ [, H f
Common variance, 公共方差! ~' i5 q% e }/ v% b, M
Common variation, 公共变异& A0 K" d' i! @8 T. R! n: G0 A
Communality variance, 共性方差
$ ^) {. z: M0 V" D, f" j0 w; VComparability, 可比性, z+ D8 h# r7 X' Y) J
Comparison of bathes, 批比较
4 b1 C8 r! h* zComparison value, 比较值
/ k/ s9 k" ^9 mCompartment model, 分部模型
- o+ F6 u: W9 K. QCompassion, 伸缩 g- s7 P7 }% q( D
Complement of an event, 补事件
1 ?6 B% h% L HComplete association, 完全正相关$ H2 g9 t) M& c! w
Complete dissociation, 完全不相关
( [$ e2 q. [6 W1 e+ UComplete statistics, 完备统计量
" ^( I# ]1 _) L" K& G% |& O, F$ wCompletely randomized design, 完全随机化设计9 n) R/ w7 G; Y+ s) G7 ]
Composite event, 联合事件) W: M b% ]5 v' C- Y6 w9 P
Composite events, 复合事件
' E, n5 l3 U7 e9 g5 GConcavity, 凹性
% y4 |' A" m) H. l- y5 fConditional expectation, 条件期望& o8 u4 J w4 R- s
Conditional likelihood, 条件似然
9 Q" M- S, W6 ~# V7 wConditional probability, 条件概率
3 D5 t1 ]' ~% g9 JConditionally linear, 依条件线性7 x( v2 h$ i! Q/ e+ E. W u9 T+ j
Confidence interval, 置信区间
; Z/ _" w6 h$ X9 A7 jConfidence limit, 置信限 [% o/ C. j( _+ ?
Confidence lower limit, 置信下限
! P0 x( ?8 P# v4 e, T2 F8 GConfidence upper limit, 置信上限
. M; C% G) `7 l) p$ w$ z& I. LConfirmatory Factor Analysis , 验证性因子分析
; Q- M* Z0 _2 W: j4 j5 p2 O0 dConfirmatory research, 证实性实验研究
; C* q8 c% r6 v0 l4 TConfounding factor, 混杂因素
4 Z* {6 D5 F Z8 wConjoint, 联合分析
. u1 ~1 x: n, s3 i: c, y8 bConsistency, 相合性) m1 O/ i6 z" t: t* o8 n, R
Consistency check, 一致性检验# f/ y- r$ O) X! z6 }2 \
Consistent asymptotically normal estimate, 相合渐近正态估计
1 V. a, h5 V9 {5 jConsistent estimate, 相合估计3 e! s" \, o$ U1 u% n3 h
Constrained nonlinear regression, 受约束非线性回归
! H: [ h/ D: G1 X% e1 r8 B. E% [- gConstraint, 约束
5 y9 D8 l) D7 hContaminated distribution, 污染分布
+ ~4 W1 p2 Q2 O$ Q2 {/ Q( a5 |Contaminated Gausssian, 污染高斯分布, J. z( s+ W( i# f6 K
Contaminated normal distribution, 污染正态分布: H* x/ E1 z1 B" J. Z
Contamination, 污染
" L: N( k4 C) y4 v7 [# GContamination model, 污染模型
* A; W1 l& X8 r3 c! KContingency table, 列联表
* y7 j1 l9 M6 i) PContour, 边界线. Z; l. `0 k3 M
Contribution rate, 贡献率
1 j# y% M* v8 O, k1 XControl, 对照
* `) g* w+ N" H$ K* k' t+ oControlled experiments, 对照实验
3 F e" r! F. ~' [6 R8 w- ]; UConventional depth, 常规深度
6 ] Q4 f; G5 h% wConvolution, 卷积
7 }* _ [- V3 l. T6 f5 iCorrected factor, 校正因子
9 O( |' b3 B7 K( Q/ Q! i' `Corrected mean, 校正均值
$ h" k8 B" j; Z o5 l6 f F) N$ I+ aCorrection coefficient, 校正系数4 Y. T; [( \' Z9 [1 x
Correctness, 正确性) H! D8 G, d% Q6 `2 P) P
Correlation coefficient, 相关系数( a6 f8 q! J- G9 k" t0 i( |6 w
Correlation index, 相关指数
6 u" O% }. R3 X0 c j0 L2 B' vCorrespondence, 对应5 A4 q2 j+ @: C/ ^( x' U
Counting, 计数
$ Q3 }# _$ R% p7 \7 ZCounts, 计数/频数& L& s. \/ X- L
Covariance, 协方差7 e( M' J9 ~ b8 V) @' \ y
Covariant, 共变
7 A4 h: _( ?. @" ` Q1 s8 WCox Regression, Cox回归: F6 D3 s- T$ E' e
Criteria for fitting, 拟合准则
4 B; M$ m' A2 ^/ JCriteria of least squares, 最小二乘准则
$ u/ F" @' \* g: SCritical ratio, 临界比' A- E- ?3 b$ Q& j
Critical region, 拒绝域
" {' q7 f( I2 g$ m% E: hCritical value, 临界值
; i& P3 d- |" l& N; v2 VCross-over design, 交叉设计
3 w- W9 k' G$ c- YCross-section analysis, 横断面分析$ r8 w' K- A( Z
Cross-section survey, 横断面调查7 b0 [6 Z3 k7 F9 F$ ~6 }, u
Crosstabs , 交叉表
& I( i; y" b, j. H5 ]9 f, sCross-tabulation table, 复合表
) V* @1 @4 R8 R n+ I& Q7 _2 CCube root, 立方根
( c2 v9 j; A7 o4 v! V" }3 FCumulative distribution function, 分布函数) M5 W& T8 x- X W7 }) h, K9 ~7 I
Cumulative probability, 累计概率$ w9 I4 J- w7 t4 P8 z. c
Curvature, 曲率/弯曲- b# L; z! b7 U7 j7 o; h
Curvature, 曲率+ {' x( l' T2 ?$ |
Curve fit , 曲线拟和
& F3 M6 Y/ z* l+ MCurve fitting, 曲线拟合/ `* p6 _3 M& `; n% s% D
Curvilinear regression, 曲线回归
8 ]1 i/ _" H6 g6 ECurvilinear relation, 曲线关系/ o; t* g8 S5 X' j* i! F. j6 u
Cut-and-try method, 尝试法) A$ i1 b+ V: G$ h8 a: Y
Cycle, 周期3 H- l' p2 `& `8 m4 w
Cyclist, 周期性
6 w/ |- n. v$ Y; {0 P% AD test, D检验
1 A# w7 H& ~6 U% l" GData acquisition, 资料收集
{3 a! u, M1 {5 B% v' ^% GData bank, 数据库
) I# e8 ?1 |1 p& H' m' y' a' i, dData capacity, 数据容量+ r( w( a! x, h( C4 n
Data deficiencies, 数据缺乏5 v* g9 k6 c/ }+ C v, @
Data handling, 数据处理
; N" \- S$ N3 t' Q% D, hData manipulation, 数据处理+ I' G: `3 m6 u4 c% F* R& r
Data processing, 数据处理
7 B u: r! y# {# UData reduction, 数据缩减( F# S# L4 o6 m
Data set, 数据集8 m* }1 z& i, J! O5 ?
Data sources, 数据来源! Y% s3 |4 o4 R% A0 ]: d
Data transformation, 数据变换$ v8 o4 @# L9 ?1 \) x: z
Data validity, 数据有效性
5 k7 I! o4 e3 M0 K' _Data-in, 数据输入( V, `. n% n: g; w7 }) A A3 G6 Y
Data-out, 数据输出2 Y' _ s. _, K) O/ }" Y* m3 M( v
Dead time, 停滞期
2 r3 F9 T9 I0 N/ e$ F* k/ r2 j5 ODegree of freedom, 自由度
7 F$ n! l: C. a% JDegree of precision, 精密度
% {! j+ z5 I) h; P+ uDegree of reliability, 可靠性程度6 n. Y" l$ q# `3 w: n$ v' ^
Degression, 递减
6 T! D3 i8 F6 |% D. R9 \Density function, 密度函数: ^. g" ~1 Q( i, q# \. b
Density of data points, 数据点的密度0 m$ l7 `+ x( `) A* H* {+ X
Dependent variable, 应变量/依变量/因变量
/ w* O% I( j8 `0 _Dependent variable, 因变量
" o y5 Y) b% M0 u5 |Depth, 深度
# C; e: {5 k: b9 k" JDerivative matrix, 导数矩阵3 g$ w7 p, [$ O A$ ?
Derivative-free methods, 无导数方法
f# h7 ?4 k/ P, uDesign, 设计9 ^% Z/ ] x8 M S! D0 y/ I2 T6 X
Determinacy, 确定性- J |, r& {5 b; H0 g
Determinant, 行列式
6 u/ I! m& k: t- j5 D6 ~Determinant, 决定因素1 o7 b2 E. ~0 l) W4 b3 t; i& s' `
Deviation, 离差
. x" S- M) t0 @( K) v- W% ?Deviation from average, 离均差
! |3 Y2 J# M6 H( d' rDiagnostic plot, 诊断图' h: b7 ]- ~4 y& n- Y
Dichotomous variable, 二分变量
7 I0 O* x0 D0 Z8 c/ IDifferential equation, 微分方程$ Y: p! t( E2 Z) U- t6 |
Direct standardization, 直接标准化法
' d; s5 }4 s! X* |# r5 O1 DDiscrete variable, 离散型变量
( P9 }* p7 k3 z8 Z- cDISCRIMINANT, 判断 0 p" I5 j8 [. Z
Discriminant analysis, 判别分析
7 \, b8 k: V8 L% g6 Y uDiscriminant coefficient, 判别系数
$ ^) K% Q0 b X& c7 j' ~Discriminant function, 判别值: M) U7 [9 D7 M4 Y& D# k. ^. X6 |
Dispersion, 散布/分散度8 U& E. o8 U {" k
Disproportional, 不成比例的/ O* N+ E0 q3 q5 s
Disproportionate sub-class numbers, 不成比例次级组含量& b- p5 @+ o( N. [5 X
Distribution free, 分布无关性/免分布$ w! g2 u4 a% w6 M
Distribution shape, 分布形状) l5 I2 e0 w9 ^7 ^
Distribution-free method, 任意分布法' ?7 g$ Z3 @# E N/ V8 e
Distributive laws, 分配律* V4 r# q; K* A& J- F
Disturbance, 随机扰动项6 P+ o5 c% h* P$ Z9 x" u
Dose response curve, 剂量反应曲线
- V8 n/ s- z6 A) q; S2 Q+ TDouble blind method, 双盲法
7 e7 h R$ n3 ?& MDouble blind trial, 双盲试验6 `& x+ h) Y1 ^7 i) }! r
Double exponential distribution, 双指数分布: @& x6 H3 c6 X) ~6 e1 A; h
Double logarithmic, 双对数8 V( r$ u5 \/ s9 f# k$ |/ z5 y
Downward rank, 降秩
, {- m6 \& d3 W; {- N+ E2 T6 s; j: @Dual-space plot, 对偶空间图
$ C% M9 W) B" v% O5 ?; yDUD, 无导数方法( H$ Q1 z: \" _0 ?& L
Duncan's new multiple range method, 新复极差法/Duncan新法
6 {* B& J+ {; D+ z9 @4 eEffect, 实验效应# \& C) ~: I# I% U, X6 I
Eigenvalue, 特征值! i7 J+ g( {1 Q% p* p5 U
Eigenvector, 特征向量
- u5 s! E4 t4 V9 c, r4 ~Ellipse, 椭圆4 a% u- A4 L! n! T* n7 x1 n
Empirical distribution, 经验分布
: d- @" h [: I0 I% |/ x" G0 KEmpirical probability, 经验概率单位
% g7 M j+ y5 N& y2 o: ]Enumeration data, 计数资料
) ^. @6 v" c- y8 P( T0 L9 mEqual sun-class number, 相等次级组含量
) V: N" w* f7 b Q4 p) LEqually likely, 等可能
7 e" N; S* \7 e% i& _! y% wEquivariance, 同变性/ [) K* ]9 M, c* F
Error, 误差/错误
" U2 ^5 f5 W9 h" E% F; A; aError of estimate, 估计误差
/ l* V' k! Y S) i) RError type I, 第一类错误
4 w0 R w( Q* c+ Q: Y& x5 GError type II, 第二类错误
" H4 G4 e5 H- p3 K' \& o; |Estimand, 被估量
. }7 w1 ]. ]- |; iEstimated error mean squares, 估计误差均方5 }/ t/ w* t: I% @, Q( V, {
Estimated error sum of squares, 估计误差平方和
& Z3 ^: a0 G. H: G0 S. I# R6 ZEuclidean distance, 欧式距离" I9 m* o3 Y: M3 f: \
Event, 事件+ |9 D' d+ L/ E0 ^( f3 {
Event, 事件2 \ L+ S$ x n" i
Exceptional data point, 异常数据点0 ]! _0 B% L6 _) {7 K r: I
Expectation plane, 期望平面* K9 a8 L8 d: q' l2 X' h1 i% V
Expectation surface, 期望曲面5 i- _; Y% z- Q! Q* I. z9 y6 `5 K6 t+ ]
Expected values, 期望值
+ {" F. q/ |9 IExperiment, 实验
& ~% ]" i9 F2 ?& V2 b, NExperimental sampling, 试验抽样
1 j3 c* R0 L( u4 JExperimental unit, 试验单位 y; X; b2 X" O
Explanatory variable, 说明变量
. [" Z1 w% U- `6 aExploratory data analysis, 探索性数据分析( ~, @0 M! P8 p+ x. b7 W
Explore Summarize, 探索-摘要+ }6 [* U7 W$ J2 Y: q/ R. G5 j
Exponential curve, 指数曲线' k$ z" V! p/ A. a
Exponential growth, 指数式增长
: h% ]8 M* x! V4 |! J; G9 NEXSMOOTH, 指数平滑方法
: M, X8 \/ |- x9 C4 kExtended fit, 扩充拟合3 S3 J0 t* O' N) c6 J6 _; c
Extra parameter, 附加参数3 ^5 U: N7 p' Y$ X
Extrapolation, 外推法* ?; j* r' P- P, Y2 t8 I
Extreme observation, 末端观测值1 @2 O7 S2 S+ j0 C+ T m3 W
Extremes, 极端值/极值& S3 B0 a7 i7 k2 K6 [
F distribution, F分布) |! y9 Q; U/ |4 Z( L
F test, F检验
& ^7 a$ B! x: n3 ~% @6 F& iFactor, 因素/因子
, g6 L* ^: Z2 @" b% E9 ?% H- eFactor analysis, 因子分析" y: Q' \9 B6 R: a/ F
Factor Analysis, 因子分析
3 u" v7 c1 L% M: _Factor score, 因子得分 3 x, f9 }" ~% Z2 A
Factorial, 阶乘
# Z% X- H/ }( t; G5 _- |5 B5 T) JFactorial design, 析因试验设计% K3 ?; N* X" t* i1 l
False negative, 假阴性3 d1 {$ V9 w5 `0 m0 X; d
False negative error, 假阴性错误
4 P9 F* L! ]( p% R I+ RFamily of distributions, 分布族
4 I8 L9 E/ {4 f+ }/ tFamily of estimators, 估计量族: S S, b; o2 P9 I5 d
Fanning, 扇面
3 O% x3 w6 \" [5 CFatality rate, 病死率
, ?: y7 D9 K$ e4 {1 AField investigation, 现场调查5 l. v. B8 e9 F' V3 U* _% ^# a
Field survey, 现场调查8 h. C; Z0 d: F7 H( L+ ~2 D
Finite population, 有限总体! o' S# A3 M0 V$ `# q6 L
Finite-sample, 有限样本
* G' }( {2 S8 L( U3 M5 A2 ZFirst derivative, 一阶导数: n7 c" y% O+ d% C K/ \& l
First principal component, 第一主成分
" y" R) @5 F1 s2 mFirst quartile, 第一四分位数& x2 ^& w9 ]4 {# H
Fisher information, 费雪信息量5 f) R6 |* ~' l: G
Fitted value, 拟合值; k* @) {6 n( B. x! @: v
Fitting a curve, 曲线拟合 N9 i* ]! |$ P* e. @" A+ W
Fixed base, 定基. J, H* H* W2 k; @6 D# \
Fluctuation, 随机起伏
' Z5 L5 l) y2 Q G: BForecast, 预测; l' n) r8 k. {- r9 Z3 u/ d& @
Four fold table, 四格表
4 G: M; b7 @& E' aFourth, 四分点
5 ?- S5 q6 N- aFraction blow, 左侧比率8 S1 \% e/ P$ Q& I
Fractional error, 相对误差$ a! T. O4 z5 I2 Y v7 X% d
Frequency, 频率
# b6 [& {3 z& `( Y @3 e( D2 X+ BFrequency polygon, 频数多边图) ]5 s+ t6 Z7 l8 n7 c: y
Frontier point, 界限点; f7 J9 h1 K+ C7 o; U6 ^
Function relationship, 泛函关系5 F# S; r8 R# Z) j) ]" a1 k
Gamma distribution, 伽玛分布$ F. F/ o5 W. U; P
Gauss increment, 高斯增量$ e$ [1 Z4 x) O: W3 i! B
Gaussian distribution, 高斯分布/正态分布
B5 @. q# z. l2 V T2 v# H5 }! {* {7 ZGauss-Newton increment, 高斯-牛顿增量
4 x4 N; Q1 ]0 I; {7 _* OGeneral census, 全面普查' N- ^7 t/ s% H: ?6 w; ]3 j. \
GENLOG (Generalized liner models), 广义线性模型 ; E7 f6 T& d+ M$ \' E2 O+ E
Geometric mean, 几何平均数
' m0 ~. W! l' x4 J8 LGini's mean difference, 基尼均差
/ S0 O/ N' _1 R& u; S1 dGLM (General liner models), 一般线性模型 + e) y1 m) m' H. d& H9 u
Goodness of fit, 拟和优度/配合度
2 z0 S) n Q4 z" t1 EGradient of determinant, 行列式的梯度1 H" S# S8 H$ f) M% e
Graeco-Latin square, 希腊拉丁方6 e+ U: W/ D6 i% N+ T" f8 k
Grand mean, 总均值
+ q5 i. ] @! u" ? ]Gross errors, 重大错误: ]1 s) Q- t) |5 T9 {( U1 _
Gross-error sensitivity, 大错敏感度
8 R9 {) l* ?$ L- u7 ]0 bGroup averages, 分组平均6 E+ s/ L; v5 j6 |: H2 ?
Grouped data, 分组资料
( K7 B. J, p: e" m/ G; }6 Y2 r- a0 UGuessed mean, 假定平均数! S% V, Y3 B! ^( I6 Q; c
Half-life, 半衰期
2 y( a4 c5 s8 Z! t* Y1 _5 {6 j4 DHampel M-estimators, 汉佩尔M估计量7 [6 q% K# z/ c9 o
Happenstance, 偶然事件
4 I" B- I/ v/ b: J0 e1 CHarmonic mean, 调和均数
3 C% x' i; _* f: NHazard function, 风险均数. L: I! n4 X @1 l, g3 x) Q
Hazard rate, 风险率
/ d: l# b/ o$ ~! zHeading, 标目
# {) e! [7 \8 m/ n' lHeavy-tailed distribution, 重尾分布2 o& C) _ X8 v/ i( {! z0 G3 H
Hessian array, 海森立体阵
0 q0 B# O9 w6 a2 K2 d* ZHeterogeneity, 不同质
+ A+ b+ }- D$ k# u5 B5 sHeterogeneity of variance, 方差不齐 ' H* b& a/ l9 t0 B
Hierarchical classification, 组内分组
/ j/ i' \0 M% @0 ~6 H0 SHierarchical clustering method, 系统聚类法
" i E8 Y% V$ rHigh-leverage point, 高杠杆率点. h9 @7 w! r3 \3 `4 V; Z5 F+ l
HILOGLINEAR, 多维列联表的层次对数线性模型
' T7 Q o, y' yHinge, 折叶点
! |0 \5 J1 Q9 S! o0 g4 n/ A7 BHistogram, 直方图
) H: Y" u# B4 s; {Historical cohort study, 历史性队列研究
& H1 W/ Y, t( h/ ^/ z9 _Holes, 空洞
- z& s5 w# j: L& B9 q/ m: WHOMALS, 多重响应分析
# f& I: K$ t% N* W) z$ ?Homogeneity of variance, 方差齐性4 q( k' y; i) m4 Q8 i- u
Homogeneity test, 齐性检验$ h3 y: a8 Q' C8 o( T: z
Huber M-estimators, 休伯M估计量. u8 f" A! O1 S8 D, y
Hyperbola, 双曲线; X9 H' h! b* R
Hypothesis testing, 假设检验+ ~: W& p7 Y/ Q
Hypothetical universe, 假设总体; M0 o4 B" W4 d! X
Impossible event, 不可能事件+ P1 I/ Q; R; J$ v2 \3 P' g
Independence, 独立性
" v9 ^( }' [4 c5 }Independent variable, 自变量
- [# S5 \6 r0 j% q, X/ v/ rIndex, 指标/指数9 z4 L& p9 @/ ]% c8 O) B1 S8 H
Indirect standardization, 间接标准化法 T: y k6 W! ?9 j, `: I9 f
Individual, 个体, e) z3 e) ~2 R$ x3 z
Inference band, 推断带
8 g9 B: Q8 n8 |" a9 g- VInfinite population, 无限总体4 z7 g% [9 h4 i
Infinitely great, 无穷大2 S' c% G& m( i+ O6 n8 S7 K# n. @% E
Infinitely small, 无穷小: ^3 K! Q, ?' w# N3 h: ^1 z) g
Influence curve, 影响曲线
( M3 Y5 k/ S }! ?$ \6 i8 U/ ~Information capacity, 信息容量5 w, `9 Y" o4 U* j/ z' G. k$ k
Initial condition, 初始条件
& H6 Q8 X! }. N$ K& P! ~$ M8 VInitial estimate, 初始估计值3 z m$ G& P7 a0 b6 Q5 V2 K$ n
Initial level, 最初水平
7 ?1 Y z" `, z2 SInteraction, 交互作用
1 Y! I' s7 B' B# GInteraction terms, 交互作用项; j" y; @# w- o: ]+ ?6 G* t+ N
Intercept, 截距, {! Q$ U% J" G9 y! ?. z8 ^% ~. b
Interpolation, 内插法1 F1 o, U, ^/ B, b- L7 x; y8 f
Interquartile range, 四分位距0 ~$ I3 d0 s1 a5 u& n
Interval estimation, 区间估计
2 z3 x4 q3 F3 lIntervals of equal probability, 等概率区间
& r; O3 P7 ~7 a. i0 y% k6 J% hIntrinsic curvature, 固有曲率
; P$ d( @! B9 z2 o% eInvariance, 不变性' r- V7 [, ?/ d
Inverse matrix, 逆矩阵
" A' C0 U, k' o6 n# w9 `Inverse probability, 逆概率" S* x$ H& _0 {3 j
Inverse sine transformation, 反正弦变换
' J5 M4 y) l2 @6 o0 ?9 QIteration, 迭代 + o' X f" R+ I, e# F4 L% m
Jacobian determinant, 雅可比行列式
U' O9 ]3 U7 x( q: B# mJoint distribution function, 分布函数
# @7 P; I; }/ K1 O/ i. ~Joint probability, 联合概率" m; l( C0 `' a* l. x
Joint probability distribution, 联合概率分布$ x' E5 y9 P+ `5 p+ n5 ~
K means method, 逐步聚类法+ O: \8 w$ U! [" [5 h
Kaplan-Meier, 评估事件的时间长度 " G4 i. G5 j" l2 }: U
Kaplan-Merier chart, Kaplan-Merier图
) V/ G9 s: o6 O* j5 L/ gKendall's rank correlation, Kendall等级相关& ~! W/ B( a* _1 }5 N
Kinetic, 动力学$ n" W ]/ X3 d% B( ^7 d/ j* a7 v
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验; Y; R' B6 r9 q4 u+ ]+ [
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
" p! O& C1 Y6 y. e2 eKurtosis, 峰度7 y7 Q$ ^9 L5 x9 F& \! r8 s
Lack of fit, 失拟
: G: S5 e5 W+ A: wLadder of powers, 幂阶梯
3 c, `: f: Z H7 ~$ a/ NLag, 滞后
5 e+ w7 l$ E0 W7 e# }5 ^& vLarge sample, 大样本
; }( j$ D# ]& h6 VLarge sample test, 大样本检验; m% @8 i9 M. ~6 |/ |" b
Latin square, 拉丁方3 r6 x9 e0 `. X: k# c# ?. J
Latin square design, 拉丁方设计
. q% s5 p5 D6 t9 JLeakage, 泄漏
' C! A8 j( ?5 j- yLeast favorable configuration, 最不利构形- v8 e# g: j$ h0 A
Least favorable distribution, 最不利分布
$ X8 m; i! ~; m/ b7 ]Least significant difference, 最小显著差法. H9 t( k5 Y% i" f2 T# ^
Least square method, 最小二乘法" Q. K% Z2 A% X% O; K
Least-absolute-residuals estimates, 最小绝对残差估计
2 X+ p. F0 y/ X1 b( c6 Z. K- QLeast-absolute-residuals fit, 最小绝对残差拟合
, U* k. a0 T, vLeast-absolute-residuals line, 最小绝对残差线$ | ^# T& Y) e6 g: I( f3 G
Legend, 图例0 H4 A X* M( l7 s- M
L-estimator, L估计量
! T3 e+ t6 `5 Q& I; r! XL-estimator of location, 位置L估计量
" N }, A* J) l" N4 VL-estimator of scale, 尺度L估计量
8 G* \. {* v& A0 d. C0 aLevel, 水平
* E4 m. d/ b, P! rLife expectance, 预期期望寿命
: U7 T, ~ m0 vLife table, 寿命表
2 Y/ J* V* E7 Z+ t5 ^0 v* X! jLife table method, 生命表法+ ~+ f2 I3 |6 k; }0 M2 A* A
Light-tailed distribution, 轻尾分布
5 a$ u, d- D# YLikelihood function, 似然函数
/ x: }& U# O: B. [Likelihood ratio, 似然比
6 H i; p7 R. X: T# M# Gline graph, 线图 d$ d& ^8 X% V# I5 x8 b
Linear correlation, 直线相关
, P3 r4 J) N( ` t" @% z% }/ ZLinear equation, 线性方程
8 f. i* ^5 {" k! @/ z5 s) yLinear programming, 线性规划0 Z; N+ l+ x) P$ f, E3 S: D
Linear regression, 直线回归
6 @; h% n* N- ^) jLinear Regression, 线性回归
9 U3 y/ r1 H/ I) o/ e, rLinear trend, 线性趋势 H$ G \5 v8 P; f6 d7 h- H9 l
Loading, 载荷 , y. C, q8 [# o- _5 h" {$ ?, E
Location and scale equivariance, 位置尺度同变性) Y8 V/ b4 K) v. z G, @- }
Location equivariance, 位置同变性
1 R& a: g+ P3 l! {, Y1 c5 tLocation invariance, 位置不变性& \* Z6 A9 q4 E% P* L( q2 y
Location scale family, 位置尺度族
9 U; L3 B& c; Y0 _5 S( V, ~5 RLog rank test, 时序检验
9 S6 F/ e. {- P& D5 g$ K# ]* \Logarithmic curve, 对数曲线% l2 q, ?: P$ x8 H
Logarithmic normal distribution, 对数正态分布: i* @: s1 ?: s8 \; r; g* G) `
Logarithmic scale, 对数尺度
2 q& I$ V7 ?% [! BLogarithmic transformation, 对数变换
. g( G/ t0 ~+ H; f+ s2 {Logic check, 逻辑检查
5 t/ ?) F7 Z. M2 MLogistic distribution, 逻辑斯特分布
( _& U7 y3 U+ P' q8 ?Logit transformation, Logit转换6 p& O4 R) g$ l4 u! }* G. `% A
LOGLINEAR, 多维列联表通用模型 2 y& h( P$ u* M2 T( O% p' v
Lognormal distribution, 对数正态分布
L* F4 y: q) K1 D# vLost function, 损失函数3 Z7 V$ Z8 m5 f0 [1 C2 ]7 a6 V
Low correlation, 低度相关 x& v! `; X' s' x6 K
Lower limit, 下限
6 c ~% W/ i _5 r; @Lowest-attained variance, 最小可达方差
& B& I+ Q" H7 g* ]LSD, 最小显著差法的简称
( j/ L8 q$ V0 ?0 n5 K/ p5 @Lurking variable, 潜在变量/ A1 u- |8 q* ]+ D* k- s
Main effect, 主效应
3 f% Y: y4 z) P; w" i9 G9 lMajor heading, 主辞标目( X# Z9 Z9 c0 a+ `- W: U. g8 w$ `0 [
Marginal density function, 边缘密度函数
2 }" z8 u5 K+ x+ _: N# A& aMarginal probability, 边缘概率
9 Q1 Y; \( H/ c+ CMarginal probability distribution, 边缘概率分布7 [ M+ K) F/ w4 b0 q
Matched data, 配对资料
) `4 m' t3 F/ ^+ UMatched distribution, 匹配过分布" q! Q b& R/ G+ S4 P* j h
Matching of distribution, 分布的匹配
* [7 P+ M3 a/ ]Matching of transformation, 变换的匹配$ w$ [2 Z, X# u4 O) h
Mathematical expectation, 数学期望) ~' f# d* r" x! ~( S3 v' v
Mathematical model, 数学模型# ?3 P, u3 a$ R; A( M. r
Maximum L-estimator, 极大极小L 估计量
Z1 S5 }/ o6 F& ?9 uMaximum likelihood method, 最大似然法
" K: B ~1 a& N+ s. jMean, 均数
6 x8 T4 z+ S! t9 CMean squares between groups, 组间均方1 J7 @" n! F' U1 r; s% K! S
Mean squares within group, 组内均方
$ Z: H: \/ @1 N) jMeans (Compare means), 均值-均值比较
, E4 v7 y3 w. `7 J9 Q' ~4 m* [Median, 中位数
6 U4 K( V$ J' m' I* |) NMedian effective dose, 半数效量; L) e, o1 b' F: j/ [
Median lethal dose, 半数致死量
7 e2 ^5 u# ?9 a4 K- O5 c+ `Median polish, 中位数平滑" h* V/ |. c4 [" a" u, W5 \
Median test, 中位数检验
1 G$ A# [" s# R, lMinimal sufficient statistic, 最小充分统计量. Q1 [% H, }2 k* L9 M% O
Minimum distance estimation, 最小距离估计
+ s* {0 H) E% o9 z) M# W% ^Minimum effective dose, 最小有效量
# W+ ]- B1 ]. `) jMinimum lethal dose, 最小致死量
* ~. k8 R G6 i) T: jMinimum variance estimator, 最小方差估计量
L( o; r: F8 \. L3 AMINITAB, 统计软件包( j: k7 u! J' x! _
Minor heading, 宾词标目
* F- y3 w1 j4 _& OMissing data, 缺失值! \5 z% _+ e, ?2 X, x. Y& \
Model specification, 模型的确定+ A# L" J* b9 b3 ]& O' F* a
Modeling Statistics , 模型统计4 r3 X5 \" V+ {7 R7 _1 Y' a$ Y( J
Models for outliers, 离群值模型
" q% b% J4 C- b4 `1 O. c+ |% ]. i qModifying the model, 模型的修正
M3 c$ N3 |3 FModulus of continuity, 连续性模" Y0 i" q3 J; b/ A
Morbidity, 发病率 4 k# F+ W& J) A' `" z
Most favorable configuration, 最有利构形. @) D; j* k2 `8 ~; i
Multidimensional Scaling (ASCAL), 多维尺度/多维标度 o( h/ X. B! @( x5 ?0 @' V" T
Multinomial Logistic Regression , 多项逻辑斯蒂回归) }: S2 s& \' [1 H/ A8 }' g, ?
Multiple comparison, 多重比较7 S8 y; r. _7 p" n9 z( |
Multiple correlation , 复相关
7 K2 ~! ^ m2 \/ z% OMultiple covariance, 多元协方差' c3 S# \: i/ c! F
Multiple linear regression, 多元线性回归
, F: F+ l7 \5 I5 x# K# a2 d; q& VMultiple response , 多重选项
( {* y4 F% ~9 X+ ^/ U( TMultiple solutions, 多解# `- o1 J* e$ [2 l7 G( h
Multiplication theorem, 乘法定理
/ ~" i5 F7 y: j; HMultiresponse, 多元响应
$ t% _5 N, V5 \* Q0 `3 {Multi-stage sampling, 多阶段抽样
) e( ^3 H7 c3 b/ d! sMultivariate T distribution, 多元T分布
6 [4 u# c# }& DMutual exclusive, 互不相容
% L- n# s+ z2 u h6 N6 IMutual independence, 互相独立8 {9 x, l! s9 F
Natural boundary, 自然边界# D0 n f1 B; _) T, c
Natural dead, 自然死亡9 G! |! L! L) i4 z! U" i# a
Natural zero, 自然零
. b5 b. O+ K, CNegative correlation, 负相关0 \8 _7 \/ q% F1 A. o
Negative linear correlation, 负线性相关4 X4 O! t( ^( I9 G/ x. c/ g
Negatively skewed, 负偏3 n6 ~* H# p& Z/ e7 C
Newman-Keuls method, q检验& Z* }3 |0 q+ { s$ _
NK method, q检验/ y1 _6 }8 U$ b
No statistical significance, 无统计意义
E% C- {$ ^0 V' k+ g% UNominal variable, 名义变量
& w, h6 Y- ~/ K* X1 nNonconstancy of variability, 变异的非定常性 B4 K- p* K. Y0 x+ b: w/ ~+ I
Nonlinear regression, 非线性相关; B4 o- G5 x, k1 F. G
Nonparametric statistics, 非参数统计
( d% ?% K8 j% C1 Q+ C, Y) fNonparametric test, 非参数检验7 [5 ^. S% g0 F+ e4 g/ j5 d
Nonparametric tests, 非参数检验5 K: m* r" m' X- b- ~
Normal deviate, 正态离差5 q; _8 _$ G1 f" W0 f5 t, }
Normal distribution, 正态分布
- J5 Y3 G- ]8 NNormal equation, 正规方程组
8 U8 L, a# W# q1 G( r) d$ Y. }2 r0 `Normal ranges, 正常范围
- q- j) s5 I( c3 \) _& ?Normal value, 正常值6 u" H Y N5 _2 `- J: F3 M
Nuisance parameter, 多余参数/讨厌参数2 Y4 R9 D+ z* r* Y
Null hypothesis, 无效假设 0 a9 G0 X# u8 X2 n
Numerical variable, 数值变量1 I, O2 U$ f1 V% v
Objective function, 目标函数4 x! ]4 I6 E6 v3 m
Observation unit, 观察单位
& q- i' o$ b) RObserved value, 观察值/ M& s3 y* Z5 E$ a3 N
One sided test, 单侧检验* b, Q; B5 K8 x# e; P4 `
One-way analysis of variance, 单因素方差分析
5 O( u! P2 c! H, d1 AOneway ANOVA , 单因素方差分析 r& V3 T- h$ b9 `2 I
Open sequential trial, 开放型序贯设计& C! M9 u# L2 f
Optrim, 优切尾
0 i& ]2 W7 r7 \' F. s/ [, X2 DOptrim efficiency, 优切尾效率# R5 W: l* N% q% Z5 c2 U
Order statistics, 顺序统计量
3 k# x5 S/ l- i1 ~9 {! Y1 u5 QOrdered categories, 有序分类
! y8 M5 M( N# H' _; DOrdinal logistic regression , 序数逻辑斯蒂回归
5 R. Z d% M) i- s o2 POrdinal variable, 有序变量8 I$ i1 \, A' e. j; _' P6 p5 Z
Orthogonal basis, 正交基* K9 C' I1 \* h% R2 Z
Orthogonal design, 正交试验设计. L" C9 T# h( ~2 e# j
Orthogonality conditions, 正交条件- n: d3 {, ~, H& i
ORTHOPLAN, 正交设计
' x% N% L8 u# N6 ?$ {Outlier cutoffs, 离群值截断点
, c% U i2 n8 p4 }. GOutliers, 极端值
* F3 w2 D9 \( r0 P: l, _OVERALS , 多组变量的非线性正规相关 9 ^9 z8 F1 V# Y, |
Overshoot, 迭代过度
! w2 v% E7 v9 x0 v$ E; oPaired design, 配对设计3 p- L8 Y, J0 A5 {6 f' s7 a" E
Paired sample, 配对样本1 Y) s# ~+ R, S" u' a$ ]7 ^, S
Pairwise slopes, 成对斜率
% ?, G. B7 ]9 B* H2 X1 @Parabola, 抛物线+ |4 t2 r A5 e+ l$ l5 _* i7 z9 f) d
Parallel tests, 平行试验
! B6 T; \ R6 A& FParameter, 参数& u) r$ t2 J9 U4 A
Parametric statistics, 参数统计& m G4 O% Y! d1 P7 B
Parametric test, 参数检验# Q1 e U/ U3 R& a3 X2 Q: q
Partial correlation, 偏相关2 a6 s0 C: i) R! v. U% n6 ]
Partial regression, 偏回归7 A( Y4 ?' ~- z& Q: g% h, s
Partial sorting, 偏排序- u* j5 F$ n# W9 |) n
Partials residuals, 偏残差/ `$ _4 Y9 b4 f
Pattern, 模式
9 |7 l6 U3 j" R$ _5 sPearson curves, 皮尔逊曲线 }) w, E0 }; [- l" G
Peeling, 退层
I9 }3 M" c) X, D' U( MPercent bar graph, 百分条形图
5 e! z% [1 G( |: D$ m/ j1 Y8 HPercentage, 百分比
* t5 q/ h# P7 a& PPercentile, 百分位数8 F/ C9 K* Y8 p5 A5 L* u
Percentile curves, 百分位曲线2 }- O0 G( u1 ~. S* j! m
Periodicity, 周期性3 W6 v, x$ f: j! w% e% F& o
Permutation, 排列
1 ~" T' Y& z! E+ y/ E9 R5 E5 {/ ~P-estimator, P估计量
% v0 T& }: F7 M3 KPie graph, 饼图7 l+ N; r6 R& [5 x
Pitman estimator, 皮特曼估计量# u" |; L* O& \1 T
Pivot, 枢轴量
8 @9 y- \! G! B* LPlanar, 平坦
. `6 w) y- I" p$ Q( o& p" A, J# zPlanar assumption, 平面的假设
1 \9 v, V- Z" C* xPLANCARDS, 生成试验的计划卡( P R+ [9 g1 Y. J' P4 V
Point estimation, 点估计
! J6 Y' V% p, g- WPoisson distribution, 泊松分布
' K0 h- V/ r( OPolishing, 平滑
8 L/ U" ?4 n) c0 g+ M6 n3 dPolled standard deviation, 合并标准差
0 `( y* E- W1 [3 w3 ^ @) UPolled variance, 合并方差! _" y# t: u+ M
Polygon, 多边图; J/ ^: `- Y* V& g; b
Polynomial, 多项式. L/ ?. s" M+ h( k7 g' r+ g
Polynomial curve, 多项式曲线; \( C l) P# E- b* W/ K0 Y5 }
Population, 总体5 B7 O0 v2 W- @# {5 q. |! o
Population attributable risk, 人群归因危险度: M2 }! g w6 E$ t
Positive correlation, 正相关
9 T( w) `) I+ v9 @ j# Q1 @- f2 cPositively skewed, 正偏$ u* I: F5 E* Y" E
Posterior distribution, 后验分布
9 |( Q: j6 B+ U( t6 E- n7 zPower of a test, 检验效能
5 K: N) n, F. E4 |1 ?Precision, 精密度
& t. p4 H# ~, O: i- T0 {! |( ^Predicted value, 预测值 [0 D% H* G# ^$ | d& l
Preliminary analysis, 预备性分析' n8 ?& N) {# e* D) _
Principal component analysis, 主成分分析
4 t8 ~0 M' b3 ]/ uPrior distribution, 先验分布
$ U+ K$ y& s! Z/ X8 `Prior probability, 先验概率 h3 y# r& f+ e6 B4 k
Probabilistic model, 概率模型2 ^5 }. s4 e0 A H4 C# L
probability, 概率# `, Z1 H' [6 y: U, ~& a
Probability density, 概率密度
( c2 ^3 f% i! R( G' m6 k7 _: ?Product moment, 乘积矩/协方差: M! S3 x C! v. t9 m0 z" f8 K' H
Profile trace, 截面迹图2 `) n. n3 \) s, J! X
Proportion, 比/构成比
5 K1 n4 x2 T* G$ \* p9 @Proportion allocation in stratified random sampling, 按比例分层随机抽样1 f4 J! d; I8 j! W1 Z
Proportionate, 成比例& F' l/ z9 j$ C7 S
Proportionate sub-class numbers, 成比例次级组含量7 Q7 x9 a3 \& ]# Q {
Prospective study, 前瞻性调查2 \" f T4 k6 X: L
Proximities, 亲近性 : e' R! J, C4 B0 d
Pseudo F test, 近似F检验
2 V4 B9 I/ {$ F% z jPseudo model, 近似模型& p# }* d, J4 I# v3 G
Pseudosigma, 伪标准差8 b3 |) S% N% v3 L
Purposive sampling, 有目的抽样- n3 n# V5 |) B; [% N9 S, W9 P
QR decomposition, QR分解' D9 R8 | p. X3 K$ X. s
Quadratic approximation, 二次近似7 H/ J9 c& P4 ~; A8 c: U1 e
Qualitative classification, 属性分类
+ I# v0 J/ ]8 b- Y: `- N ~9 { eQualitative method, 定性方法/ N* z2 e5 f, H0 b
Quantile-quantile plot, 分位数-分位数图/Q-Q图
8 h W' m$ W( yQuantitative analysis, 定量分析
! z/ ~( n& x K+ iQuartile, 四分位数
5 k' c b+ D2 ^1 ]& {0 X1 IQuick Cluster, 快速聚类: l6 c9 G/ j! d
Radix sort, 基数排序3 ?, j7 c8 z( i( e$ R8 }3 S
Random allocation, 随机化分组
& B# ^1 \: @* d/ hRandom blocks design, 随机区组设计
7 w/ d( x# m3 Q" x6 Z! kRandom event, 随机事件/ P* y: o* d2 | F/ m2 y& m
Randomization, 随机化 { I# j Z( m: k" L! @
Range, 极差/全距
s" \ O( f+ q; Y* n7 bRank correlation, 等级相关
* V# O& k e5 H7 DRank sum test, 秩和检验
! p1 A3 ~: F9 W. pRank test, 秩检验/ B0 @6 V! \2 W% X+ ], ?
Ranked data, 等级资料
/ r! X& K6 \: F. _+ M- eRate, 比率+ e0 @+ B5 q* ]% U% {8 v
Ratio, 比例1 f) x& l, O! c# E5 X% I
Raw data, 原始资料
. b, S0 ~2 ^0 g; k& f2 ERaw residual, 原始残差
) R6 U& g/ Z. ^7 X7 A& W* nRayleigh's test, 雷氏检验( y5 Q- a7 U# f3 _! l. A1 Z, R
Rayleigh's Z, 雷氏Z值 0 B4 S8 I i1 C1 W+ T& z
Reciprocal, 倒数: _ A, v1 g* X0 F
Reciprocal transformation, 倒数变换; a" y. t- P# n* u
Recording, 记录; o" [# }" l) e% W, ?3 ^
Redescending estimators, 回降估计量& j9 @ G, O9 R) B& _
Reducing dimensions, 降维, Q9 O; f7 z1 ?( E
Re-expression, 重新表达
- O; a1 x. |/ qReference set, 标准组
1 `9 g8 H* K, O! QRegion of acceptance, 接受域
4 k' O+ {* {' J5 Q1 Z6 rRegression coefficient, 回归系数
* {" N W: C4 G3 rRegression sum of square, 回归平方和. I6 Q- m6 y; R& D) B
Rejection point, 拒绝点& @- I5 y, U1 b: m1 X
Relative dispersion, 相对离散度3 {+ Q0 N2 y5 h) u
Relative number, 相对数 e r. C9 x# O% X( u
Reliability, 可靠性4 c5 O5 E- ?6 T! r
Reparametrization, 重新设置参数- H/ \% q \+ f
Replication, 重复2 ?. v/ G. ?# j, [
Report Summaries, 报告摘要8 l2 O8 A1 R, N! _$ H" F
Residual sum of square, 剩余平方和: g; e( @6 `! u( q" z
Resistance, 耐抗性
1 A% _* J/ J- p! J- QResistant line, 耐抗线& P, K: |6 @1 d6 {4 q& Z
Resistant technique, 耐抗技术/ C; d8 f4 X. t. V
R-estimator of location, 位置R估计量
+ N* F$ x& F( G5 h: \1 eR-estimator of scale, 尺度R估计量
0 M& Q2 X* L, j* K2 w1 r- N0 ?Retrospective study, 回顾性调查
2 I2 F& D$ R8 k1 U! E& oRidge trace, 岭迹; r& v6 y7 Y# E- t. f! ~4 F
Ridit analysis, Ridit分析
7 @7 g) r8 b4 k& R7 {* I8 {# m$ [Rotation, 旋转
A. o: ~5 O, b+ C- QRounding, 舍入
! C' a$ }; p t U3 W( W3 n* B: LRow, 行
& {4 ]8 O, N' vRow effects, 行效应
. i0 I- E ~6 T% e; {Row factor, 行因素/ Z; t' l( Q7 u
RXC table, RXC表- t% D: a1 d* U& J. ~
Sample, 样本
1 y6 h- s( k' N. aSample regression coefficient, 样本回归系数
& x7 s& w2 X! xSample size, 样本量
9 A( N: ]/ Z) uSample standard deviation, 样本标准差
6 D* R6 V1 s1 k; ]2 o$ }Sampling error, 抽样误差
: H! D6 a1 B0 v5 C3 z# s7 vSAS(Statistical analysis system ), SAS统计软件包
( L6 g: D3 \% B; |4 [9 u/ qScale, 尺度/量表
; z! x R; y8 R3 O' E/ |- _# cScatter diagram, 散点图
% Z. K. N1 c1 }$ M6 H( U% T3 qSchematic plot, 示意图/简图+ Y' h# A9 Q9 V& _+ m2 E
Score test, 计分检验
$ M# n9 e/ u! W5 u% Z: ZScreening, 筛检0 G1 a6 v4 W4 ]" b3 n
SEASON, 季节分析 5 \, y9 B3 r/ ?# p" G3 t/ P5 o
Second derivative, 二阶导数
; F0 }0 \8 m$ OSecond principal component, 第二主成分
* K* i L7 S- I- W$ c QSEM (Structural equation modeling), 结构化方程模型
7 F$ Q+ w) w0 s) ~" u, S9 }; P# M4 WSemi-logarithmic graph, 半对数图; H, L* L _6 }) l
Semi-logarithmic paper, 半对数格纸
, }% B* P9 R, S5 b4 aSensitivity curve, 敏感度曲线
: d# }8 L: f4 S. K1 [ v/ J2 p" `Sequential analysis, 贯序分析
6 U+ H- ^" x WSequential data set, 顺序数据集
9 x4 Z( L {4 USequential design, 贯序设计
; H6 I. \# H, A. e$ \ v- i1 mSequential method, 贯序法
9 i' Z7 H; Z! ?1 V2 @Sequential test, 贯序检验法
7 L& L5 V. y5 Q" u @Serial tests, 系列试验
- Y0 p( e9 ?' D6 x# r8 vShort-cut method, 简捷法 8 N9 o# k, y9 {" R6 }' R, O
Sigmoid curve, S形曲线) k$ w' K' D X) u, `
Sign function, 正负号函数, u! Z; W6 @1 P1 D# b- P
Sign test, 符号检验
8 D& q, H$ O1 U1 D3 ASigned rank, 符号秩' |9 M/ e! `& \; Y0 y& h
Significance test, 显著性检验+ s& V3 I! s. ]& l
Significant figure, 有效数字3 B/ Q+ Q! l3 z5 H( \& `/ L( ]
Simple cluster sampling, 简单整群抽样/ M' n1 R1 N V4 x8 s1 @; u. M! k
Simple correlation, 简单相关3 ^+ o% o5 ]3 |* n3 L' D
Simple random sampling, 简单随机抽样
0 o/ L4 z/ r4 H3 ^) ISimple regression, 简单回归 i9 z3 w; r8 ?7 p8 D. {
simple table, 简单表5 r" z, b' M S' T8 R+ k0 @
Sine estimator, 正弦估计量+ D6 F. P" V S. z
Single-valued estimate, 单值估计' j$ E3 f- _. b
Singular matrix, 奇异矩阵
8 j3 F- s, o; g# ~% cSkewed distribution, 偏斜分布1 J) c" E. t, Q) t% o0 @) w0 ?2 e# A
Skewness, 偏度
1 J N# d; N8 a' y8 J; fSlash distribution, 斜线分布5 [- t4 w% [( e; W. L* Q
Slope, 斜率
7 o' U$ k5 Y* V4 h$ n {. f# ISmirnov test, 斯米尔诺夫检验0 z6 D' ?0 i' x
Source of variation, 变异来源
% O# a2 p7 E: H1 r. M9 ]! RSpearman rank correlation, 斯皮尔曼等级相关( U2 O0 }. ~, d, o+ I
Specific factor, 特殊因子
; E$ l% U; \7 s$ S9 ASpecific factor variance, 特殊因子方差
+ r: E& f2 c2 RSpectra , 频谱) Z( H9 S( O9 `
Spherical distribution, 球型正态分布& M8 E3 t, x$ h% [! I
Spread, 展布
1 c2 u8 E7 z. b7 |$ n) ]SPSS(Statistical package for the social science), SPSS统计软件包
' T" M% W" [% x0 X( a+ y2 c7 QSpurious correlation, 假性相关: Q( D% ^& B. h5 `. p5 j) m
Square root transformation, 平方根变换
6 @' t) J6 S8 ^& { I T- JStabilizing variance, 稳定方差
, ^, ^; D7 J- M7 e( B/ `Standard deviation, 标准差
/ b4 v" U- N. Y; uStandard error, 标准误/ y1 J- ?* y; B! x4 E& o/ {& t( ?- y
Standard error of difference, 差别的标准误
3 |( P8 G$ X0 A7 S/ [) WStandard error of estimate, 标准估计误差
e6 f, \) |& B7 \Standard error of rate, 率的标准误
3 B; d: E( t. n* ~9 h0 E5 KStandard normal distribution, 标准正态分布
( U3 S% N6 M fStandardization, 标准化! m+ T4 J" y4 L: ^1 j# p0 a) V5 k* ~
Starting value, 起始值
( x9 j% j% S. ~/ P9 B7 b. cStatistic, 统计量! ~, e/ ~9 h. V- g/ t7 [/ ?6 r, W
Statistical control, 统计控制
0 Q, z6 K/ _7 O3 A3 BStatistical graph, 统计图1 N. k- p& ?2 C* e, q
Statistical inference, 统计推断
, }+ c5 o; j( `# DStatistical table, 统计表+ ^0 e) D" g! o: V( e
Steepest descent, 最速下降法
# h+ z- z: O$ ~- k. L" rStem and leaf display, 茎叶图% |3 E7 m, b4 J3 A. J
Step factor, 步长因子
$ E4 p4 A- }4 {4 JStepwise regression, 逐步回归
* Z- l" { @! b* C: s. Q& f7 G/ tStorage, 存
f9 R3 ]& {4 B, ^5 i5 l/ hStrata, 层（复数）
' E4 w' R1 v2 l/ zStratified sampling, 分层抽样$ v3 n" z, N- X- j7 W' r" J! _ `
Stratified sampling, 分层抽样% {9 h8 Q( y4 @4 w
Strength, 强度- p- D' W- ~. i$ F; l
Stringency, 严密性
# V! {# X- u2 m# W9 _+ iStructural relationship, 结构关系3 T) Y$ B6 N5 ?5 l7 a
Studentized residual, 学生化残差/t化残差 C- P1 r5 L D# U3 J, U3 f
Sub-class numbers, 次级组含量$ \' C/ u# R# V R5 ~
Subdividing, 分割
6 q1 f4 d/ A2 T% C$ `* vSufficient statistic, 充分统计量
2 @' X& \& Q5 d5 TSum of products, 积和9 y6 W. _) n# ]4 M
Sum of squares, 离差平方和6 O8 }" ^4 w) Q
Sum of squares about regression, 回归平方和
. _7 N& v+ X5 C( sSum of squares between groups, 组间平方和6 {) _3 C# s# }4 L+ @3 G
Sum of squares of partial regression, 偏回归平方和
9 y+ I. g; J/ W4 \Sure event, 必然事件: a T n' X+ m6 Y
Survey, 调查7 Q! L# A' m0 z8 D
Survival, 生存分析
" E2 o' w7 e4 ?: C8 P9 OSurvival rate, 生存率. P% i$ `6 x* Z- c. s5 E2 `
Suspended root gram, 悬吊根图4 w- P& _* B; e& n+ j+ s
Symmetry, 对称
6 u6 T& S ^9 @, e9 BSystematic error, 系统误差; Q1 [: @$ _: r ~" j' h6 j/ _6 U- l
Systematic sampling, 系统抽样
! q8 |& b- L# K3 D1 ATags, 标签
9 V0 f& h7 I n; ETail area, 尾部面积
$ n+ T! ?& W kTail length, 尾长+ f* h% E: M |& f: n: a
Tail weight, 尾重2 I- }" J z: V. O; J9 n0 I
Tangent line, 切线
( O# q1 F1 z2 T1 S# dTarget distribution, 目标分布 R b2 z* S B4 D ]4 K. r3 B7 I
Taylor series, 泰勒级数! m) v T; T0 i) S6 c% q, H" o# ~: h
Tendency of dispersion, 离散趋势
9 y# g. Y2 O2 N- r0 j& }Testing of hypotheses, 假设检验+ x% P! F! u5 W: C. G3 p0 j
Theoretical frequency, 理论频数
, H9 o% a) a2 M/ [- ?5 X7 zTime series, 时间序列
6 q4 B0 W0 ]6 f0 eTolerance interval, 容忍区间
; N7 M" \- J. O9 y% V( X. J' ?Tolerance lower limit, 容忍下限
D6 c% Q6 D( y2 x$ PTolerance upper limit, 容忍上限$ |5 M# ?' o# I& K6 X5 w, b
Torsion, 扰率
# i: L# d2 w" ~Total sum of square, 总平方和8 l: G; H4 Z. V" f9 k7 V$ m8 Y5 Y
Total variation, 总变异/ C/ }* U! D' Q. y' a
Transformation, 转换
( O. e- }! |, H; H+ YTreatment, 处理
! `4 J9 t8 O7 `7 i& t9 J; _Trend, 趋势
; Z4 ~$ M1 x( `: k1 ~, rTrend of percentage, 百分比趋势' Z: y! _% I/ Z u. G# D
Trial, 试验: @' t1 [6 \# q& i2 e, x9 l
Trial and error method, 试错法9 f& L0 }7 o, I* @
Tuning constant, 细调常数
. N* y) O+ b2 O; z2 e% f8 R! eTwo sided test, 双向检验0 z$ e& w3 w. D& `$ `2 ]6 e
Two-stage least squares, 二阶最小平方, `: F, v7 \1 m2 W$ g5 o7 M+ A& z
Two-stage sampling, 二阶段抽样
9 U) S! V$ J8 zTwo-tailed test, 双侧检验
8 V" R! m5 l4 L( ?4 T: bTwo-way analysis of variance, 双因素方差分析
% ^0 c8 q% O2 p k) R4 nTwo-way table, 双向表4 R+ u3 x, U7 _+ ^4 R+ x/ n
Type I error, 一类错误/α错误
1 ~8 K, x( d! y5 XType II error, 二类错误/β错误- L2 t ^3 Z& `( `+ d
UMVU, 方差一致最小无偏估计简称4 O$ {% b3 }: u) L
Unbiased estimate, 无偏估计
# u4 U2 c( Q, K% L) }/ }Unconstrained nonlinear regression , 无约束非线性回归7 Q, P2 h/ w4 _1 i
Unequal subclass number, 不等次级组含量
0 ^# ~% h! {& F8 [2 c" r2 M/ @6 CUngrouped data, 不分组资料1 }: O" u- e. I2 S5 c! ^1 ~
Uniform coordinate, 均匀坐标
8 B( @+ ^$ k# Z: B0 tUniform distribution, 均匀分布
8 F+ H* q9 l! [" sUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
& Z S' i. y5 `) R; vUnit, 单元# Q6 J- u4 p- `0 G* C- }
Unordered categories, 无序分类9 P3 x4 Z( \; ^0 Z
Upper limit, 上限
' F. {+ j& e% @/ X2 c7 U- C% QUpward rank, 升秩4 d8 b$ I# m7 c2 d% Z( G+ N
Vague concept, 模糊概念
- z2 {' s& x" B1 v% ?6 s& H6 @Validity, 有效性0 @4 F7 p0 r$ B7 p$ a7 L# X$ T
VARCOMP (Variance component estimation), 方差元素估计
* q. N& b- K" h1 K; D7 b2 dVariability, 变异性# _2 P$ d- X- s9 w- S4 ~
Variable, 变量+ d ]) I* r' I1 F% S
Variance, 方差
! F$ Q0 Q5 ^5 G% VVariation, 变异' i5 d# ^; h8 A1 j, U
Varimax orthogonal rotation, 方差最大正交旋转5 U4 s% ^$ ?( K8 M# J1 E2 _* _( T
Volume of distribution, 容积
2 F; U$ x% v: H, j; l6 }W test, W检验
/ R+ [. M" e3 E$ t( hWeibull distribution, 威布尔分布
3 I$ T9 p8 _% n! e( t* e6 eWeight, 权数3 ]: q# \- {0 o2 }' l
Weighted Chi-square test, 加权卡方检验/Cochran检验+ c8 W% v, Q# J$ D0 l, K& v
Weighted linear regression method, 加权直线回归) A1 d* v; c7 \4 Z
Weighted mean, 加权平均数
v4 H5 S0 B! ]4 QWeighted mean square, 加权平均方差, z) y! N3 ^/ Y* H c$ v! Y
Weighted sum of square, 加权平方和0 u( }. A3 N$ ?6 r
Weighting coefficient, 权重系数7 R# W! |$ W& Z4 g! X* D
Weighting method, 加权法 2 B+ m! j) e$ Y# z) S( W* k5 c
W-estimation, W估计量 Z: K+ |# k) H4 |% r4 A
W-estimation of location, 位置W估计量
; Z2 }# I: t+ }Width, 宽度
) ~3 {5 Z4 U0 _5 O! k; eWilcoxon paired test, 威斯康星配对法/配对符号秩和检验; ?0 ]8 }: H, J- p2 R
Wild point, 野点/狂点6 s1 h: `0 E. D& \3 z
Wild value, 野值/狂值2 `( \9 |3 S) j4 b5 Y
Winsorized mean, 缩尾均值
' b1 m8 H6 m! [) f( |Withdraw, 失访
8 U& b5 g" t1 P) S% k- gYouden's index, 尤登指数
7 D/ K( l* L" P5 }$ pZ test, Z检验
! C9 q* _0 O7 |9 N! `3 b6 L) s/ VZero correlation, 零相关" @$ z$ Q6 y$ h' k, j4 Z
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
