|
|
Absolute deviation, 绝对离差
7 v* H( f# i9 S5 t( E, lAbsolute number, 绝对数
/ o$ ]! m$ }) [" L, x3 ]( `Absolute residuals, 绝对残差
/ a; @3 u" z/ F. B+ Q* @Acceleration array, 加速度立体阵
, V) f! }& h; e/ e& h0 ?Acceleration in an arbitrary direction, 任意方向上的加速度
) n4 E( v* Q3 I1 kAcceleration normal, 法向加速度
. i* {0 t+ f8 ^3 K: bAcceleration space dimension, 加速度空间的维数
6 N; x# g, ]' i! dAcceleration tangential, 切向加速度3 I# _4 T6 E& P( c: _ [
Acceleration vector, 加速度向量
6 @, J4 I1 M' }Acceptable hypothesis, 可接受假设: b- {7 ?/ [- h' B0 m7 [
Accumulation, 累积
$ N/ y& Z! y$ U/ xAccuracy, 准确度
. d4 t4 t$ D& SActual frequency, 实际频数( u0 N5 v3 ]! I4 j
Adaptive estimator, 自适应估计量1 V* c9 k0 f$ o3 p0 p) T' q' i
Addition, 相加1 E# B% X' t0 Y
Addition theorem, 加法定理
; Y$ b2 D7 m; X+ E; V! J2 B& v- JAdditivity, 可加性
& W) Y) r9 E+ \; p6 f8 v* oAdjusted rate, 调整率1 Z1 L2 v/ o; O9 e
Adjusted value, 校正值
3 o; K [- [; ]( B r* J gAdmissible error, 容许误差5 {7 } j- c W( _# ^
Aggregation, 聚集性 f, O# _! h: `7 h
Alternative hypothesis, 备择假设8 V. d/ w; |$ X6 [
Among groups, 组间- S4 r4 s; A- X1 k, G" ]) a
Amounts, 总量
' P7 y6 _ h. ?. @; V0 u! dAnalysis of correlation, 相关分析$ r! l! a8 ~) u0 I
Analysis of covariance, 协方差分析- `9 {9 O- b9 l: t9 [4 I
Analysis of regression, 回归分析 Z, @7 T; b8 B# p
Analysis of time series, 时间序列分析
& [" {4 a0 _+ n; d5 _3 d3 e; JAnalysis of variance, 方差分析! I* W; A: Q/ _/ n: n2 ~0 W
Angular transformation, 角转换
5 {4 p: Y2 `% t9 a. n4 K1 D+ @ANOVA (analysis of variance), 方差分析, i& X6 _& E' ^6 q" \& {6 c0 b7 G) S
ANOVA Models, 方差分析模型
/ u2 H3 h: U+ o' Y& P; D2 IArcing, 弧/弧旋
1 ]$ X' n5 w! k; [Arcsine transformation, 反正弦变换
+ Z6 Q5 e6 d f/ m pArea under the curve, 曲线面积
Y4 f6 Z4 J1 i% _& XAREG , 评估从一个时间点到下一个时间点回归相关时的误差
. O6 H5 I ?" f# X; D0 ZARIMA, 季节和非季节性单变量模型的极大似然估计
' R8 d R6 K- v3 I: C) E7 e' @Arithmetic grid paper, 算术格纸
9 p# M5 C0 t2 c& Z$ \3 b: q" QArithmetic mean, 算术平均数
?: j+ O6 A; R$ g- ^6 wArrhenius relation, 艾恩尼斯关系
4 m# I! I1 b( m8 |! sAssessing fit, 拟合的评估
5 N' J0 l f, Q. ?) I, ]0 r. tAssociative laws, 结合律 c) I( j* R. G/ y* {3 b- Q T' Q
Asymmetric distribution, 非对称分布
" M" ~( T7 z6 T0 |) h$ I% IAsymptotic bias, 渐近偏倚: F3 X$ s8 a# O, H/ z5 u9 \
Asymptotic efficiency, 渐近效率5 ]; m) H+ L6 p4 q. q7 Y
Asymptotic variance, 渐近方差
; I! S( H, v' n: G: m# G2 OAttributable risk, 归因危险度
% a, o2 {( g5 d- @Attribute data, 属性资料3 W' u' n$ s+ I! `
Attribution, 属性
# F% B7 _! Z* Q. p/ TAutocorrelation, 自相关% b- q1 |- S, v1 w
Autocorrelation of residuals, 残差的自相关
* q- Y% u; j) J4 ^# b- ]Average, 平均数3 J. v; l9 v5 N4 N
Average confidence interval length, 平均置信区间长度3 K8 g6 j1 G3 v8 r" z; s$ k$ {
Average growth rate, 平均增长率
- n6 w3 P% m4 \/ m& u8 W" PBar chart, 条形图# ^* T* s5 ]8 S9 Y2 i; [
Bar graph, 条形图3 u( j7 G" h* q" ?
Base period, 基期) c/ w- Q1 m5 @6 Q; L1 g. e' D6 z
Bayes' theorem , Bayes定理
) @4 y0 B0 C2 g4 L9 {Bell-shaped curve, 钟形曲线- r/ ]' o6 @/ Y6 X7 Q( @. c% c
Bernoulli distribution, 伯努力分布' j8 A: d K* R4 P& } I
Best-trim estimator, 最好切尾估计量4 P. G3 r9 \& v" c' R' r; l
Bias, 偏性" X7 z3 G2 I' z% ~: h, u
Binary logistic regression, 二元逻辑斯蒂回归% a! |" ], z& \( f4 L. L0 I1 ]5 w
Binomial distribution, 二项分布' d5 W4 e5 h0 G; l7 U* g
Bisquare, 双平方$ U$ h6 c% e: L* X" ]9 B
Bivariate Correlate, 二变量相关
& y0 s3 @4 f+ J7 Y5 ?# ^( VBivariate normal distribution, 双变量正态分布$ x* G4 O# Y! z- p6 i
Bivariate normal population, 双变量正态总体
! I7 S. R3 A$ _! Q4 C6 }Biweight interval, 双权区间% Y3 _* l. \3 Q6 q! O" @
Biweight M-estimator, 双权M估计量
. c3 i! S2 a) n4 [. rBlock, 区组/配伍组
% o% ^4 a* u# }! w) aBMDP(Biomedical computer programs), BMDP统计软件包
5 q( j6 v' L5 h" ^5 h) G% |& JBoxplots, 箱线图/箱尾图
# b( Z" H' ^$ T! EBreakdown bound, 崩溃界/崩溃点9 o) g6 j& C( z2 ?
Canonical correlation, 典型相关
) y' T7 n+ ]8 Q* Y" Z: nCaption, 纵标目# J1 ~& E2 b S" C' M- @
Case-control study, 病例对照研究
2 n" D8 F& g7 @4 u) iCategorical variable, 分类变量
2 [" x2 x$ E4 V. t% }7 C2 {Catenary, 悬链线4 Y7 h" }! V1 J0 L! ]
Cauchy distribution, 柯西分布, B; V& s& ^& r) P" _+ K' x
Cause-and-effect relationship, 因果关系
$ A+ }2 u2 w0 H) P3 ~ p. qCell, 单元7 L' u4 J+ b, |0 K- l( Z0 q
Censoring, 终检
2 S0 C7 l+ Z$ o) p7 UCenter of symmetry, 对称中心+ j; Y! l. w7 K% u# S+ F0 t
Centering and scaling, 中心化和定标7 f' q3 J2 M0 B3 l
Central tendency, 集中趋势* t& D$ y' T+ }
Central value, 中心值' t3 j' _3 V/ o8 j
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
- H. `! l+ m/ |( d) SChance, 机遇# s, F/ L X% i3 K, x
Chance error, 随机误差" O7 W" }, r( C8 m' Q5 U9 Y
Chance variable, 随机变量
) H0 c( f1 n8 {2 V5 V. aCharacteristic equation, 特征方程% Z" O _2 E0 h y: \
Characteristic root, 特征根$ f2 a' [3 i& i1 r8 G( F
Characteristic vector, 特征向量
( I; T3 R! ]+ i. ~0 kChebshev criterion of fit, 拟合的切比雪夫准则& D! b, I5 Y5 P) d# @7 T
Chernoff faces, 切尔诺夫脸谱图
/ b6 f5 ?" m" P# c$ R. T$ tChi-square test, 卡方检验/χ2检验) t5 t! ~% h! @& r( `- l9 w3 v
Choleskey decomposition, 乔洛斯基分解" p$ T1 v, M; |( q9 A) r2 I
Circle chart, 圆图 8 C: k3 e# T1 N [% W$ z% S
Class interval, 组距( Y6 \: C; ~/ `: r
Class mid-value, 组中值
/ x% ^$ V6 s! ZClass upper limit, 组上限" e) B ]0 K; }7 z2 Q' @
Classified variable, 分类变量$ q3 N' k& H' ^: P4 S+ x( X/ U
Cluster analysis, 聚类分析
2 G3 @& t& U# F# Z4 O& DCluster sampling, 整群抽样
, m. ` \* }' J# T: mCode, 代码8 c# C: y6 J! \/ l3 t0 O+ k
Coded data, 编码数据( y, v# @: N5 q9 C
Coding, 编码$ l0 b7 H9 Y1 z
Coefficient of contingency, 列联系数
% W2 Z2 X/ t+ k" v7 l* o2 f9 v: NCoefficient of determination, 决定系数" ]$ }" I1 W6 v
Coefficient of multiple correlation, 多重相关系数
9 I% n, b$ C; p: BCoefficient of partial correlation, 偏相关系数5 ?7 g, D1 M' i# C- p) J, r
Coefficient of production-moment correlation, 积差相关系数
- L$ X1 }' ?0 f" [* P7 e9 QCoefficient of rank correlation, 等级相关系数" g- S7 O5 M4 I! f+ B
Coefficient of regression, 回归系数
: n& _* c. v% }Coefficient of skewness, 偏度系数
5 n7 {( X1 u) N! Z" [Coefficient of variation, 变异系数9 l9 x4 }' y# i- h( _+ D0 f- d& f
Cohort study, 队列研究
) F( `# E9 P7 M% I; O. _$ AColumn, 列) u+ U7 }. b3 @$ y/ W, F
Column effect, 列效应, a. W( Y) z+ X6 E! f5 T
Column factor, 列因素
( }8 q# G* u$ o2 o+ DCombination pool, 合并& O. l- }; x0 S
Combinative table, 组合表
- d; G! {; G: d( S3 H2 `Common factor, 共性因子7 h- T4 E. y$ ]4 b
Common regression coefficient, 公共回归系数3 F3 N4 H5 L9 O
Common value, 共同值3 j0 e! W4 i2 ^9 |
Common variance, 公共方差
- h7 f; m: @ }7 ^, w% F6 JCommon variation, 公共变异( X* \% K. c4 w* D2 @! @6 L
Communality variance, 共性方差
6 I; {0 J Z. q f: y9 p- L) C, }Comparability, 可比性
" |4 G9 m- R/ |4 T! i( ~, {Comparison of bathes, 批比较5 E' B s6 S/ F. y$ W
Comparison value, 比较值9 |3 _) r3 r" c+ f2 y$ D
Compartment model, 分部模型5 L: E2 l( E+ h! x# v
Compassion, 伸缩$ [4 d f7 E% y' R; y6 ^4 ]
Complement of an event, 补事件& S" |+ d! @" h8 z& j) Y
Complete association, 完全正相关1 i, ~& w) |; t7 N
Complete dissociation, 完全不相关
2 e2 F; |# s# G. {2 w: CComplete statistics, 完备统计量* Y8 v L3 ^+ A# D- J1 k" f
Completely randomized design, 完全随机化设计6 M6 D7 [% K( r( _8 U5 [
Composite event, 联合事件
1 P* p- [8 h: S2 }; r9 cComposite events, 复合事件
' |" e7 @3 l1 g( W3 \Concavity, 凹性
' K. n1 Y+ h# c! J9 iConditional expectation, 条件期望
' x6 q& H! n8 A# @8 |- iConditional likelihood, 条件似然* n1 n+ C. Z* X+ b7 u
Conditional probability, 条件概率5 u; Q7 k: j4 C+ d) [1 }. c
Conditionally linear, 依条件线性
# Y6 D6 O2 M* k, H. s6 ^Confidence interval, 置信区间
! F$ k x! ^+ T6 ^& J" PConfidence limit, 置信限
# V. a9 D- l+ }Confidence lower limit, 置信下限0 e7 ^" T2 M2 I- p2 P
Confidence upper limit, 置信上限0 D6 N" T# b& A8 J. q
Confirmatory Factor Analysis , 验证性因子分析/ _, l2 X, p# k5 n
Confirmatory research, 证实性实验研究: F1 C9 H# J. P/ ^% {% `5 m+ `
Confounding factor, 混杂因素
4 R: E. q2 h' `8 FConjoint, 联合分析
% E( ?& k9 l+ q$ aConsistency, 相合性3 v% g/ u$ ^! W2 r( d2 Z, ?! }) C; j
Consistency check, 一致性检验
" y! X" a% d5 A6 ?6 YConsistent asymptotically normal estimate, 相合渐近正态估计
% ^5 P9 S9 a0 [* yConsistent estimate, 相合估计
1 a1 L# d2 |2 f t, P4 `0 X) QConstrained nonlinear regression, 受约束非线性回归
0 x4 x1 L+ {: `% {! U5 R" P/ tConstraint, 约束
+ k6 G; R8 J3 `2 s$ R6 Z# D2 rContaminated distribution, 污染分布+ g; d/ F0 A2 m8 D% Z" n
Contaminated Gausssian, 污染高斯分布 X: v& J4 t: O& M, y6 \8 C& {
Contaminated normal distribution, 污染正态分布9 y$ X7 `3 l, y8 T. g4 Q
Contamination, 污染
5 w* @$ G, D* u* a# C9 o1 QContamination model, 污染模型
O7 v$ z' {; h; Z2 BContingency table, 列联表
/ \' m- k7 l" H, V+ h n$ ]Contour, 边界线
0 @- }- f3 v+ i9 x. x' wContribution rate, 贡献率9 a! e' A. Y2 t7 [/ G
Control, 对照
+ ~1 p% Y. G1 q4 R e. KControlled experiments, 对照实验% c0 H' x6 o) q6 H$ K4 Y. l
Conventional depth, 常规深度
" F, K7 b( H! ~4 _4 [Convolution, 卷积
2 O& L2 Y6 o6 E1 H, L5 |Corrected factor, 校正因子 Y4 W% A6 W7 @0 @# n; j
Corrected mean, 校正均值 G+ J1 A9 M) p2 g; `
Correction coefficient, 校正系数' Q% E2 f' r% B ]
Correctness, 正确性2 e8 V+ [, ^. R6 C3 x/ X$ Q
Correlation coefficient, 相关系数
) u( E& N1 j1 ]$ g9 I# [% K3 y4 {8 rCorrelation index, 相关指数# f B, [" v. p% m- U
Correspondence, 对应
@" F5 U, v2 VCounting, 计数
/ \0 V, S+ x+ `* Z- gCounts, 计数/频数
9 }, b9 O& T2 z& h8 P" B6 j; r2 O4 PCovariance, 协方差' L6 h+ v0 L- m: K
Covariant, 共变 : B7 L( g7 ?0 C' s( o& v
Cox Regression, Cox回归+ Z, r3 Y. Z. `! R2 e) z8 ^
Criteria for fitting, 拟合准则
. W& }' Y& t( e2 ^# U8 \7 f3 q |7 {Criteria of least squares, 最小二乘准则
, o' L& O9 ]* X( y! N% _Critical ratio, 临界比- ^; j ^( x' D( G M7 n2 q
Critical region, 拒绝域 Y# O% A# ]) l+ T
Critical value, 临界值
& l+ G! M n( g5 uCross-over design, 交叉设计
. h [6 `8 A2 @+ |3 WCross-section analysis, 横断面分析
4 z7 W; W* q9 b* w) R% vCross-section survey, 横断面调查, g+ f3 j- G5 x; H6 ?6 ?* f
Crosstabs , 交叉表
1 d% L6 X+ \& p, J9 C5 ]3 wCross-tabulation table, 复合表# C# k, ?: d( a- t8 P( Y! }1 B/ V3 ~$ U
Cube root, 立方根
# t$ L4 z4 Q) L) MCumulative distribution function, 分布函数0 o7 B6 D+ f8 O$ m/ ?( C
Cumulative probability, 累计概率. B& r, w2 M: A
Curvature, 曲率/弯曲6 n7 {& d& I. e6 n
Curvature, 曲率5 o. g. ^- ?. K# J
Curve fit , 曲线拟和
/ I5 C3 ?$ w+ T1 }Curve fitting, 曲线拟合- ] V+ T: H M8 ?9 G( C' D
Curvilinear regression, 曲线回归# M, D L: y/ b" y' J& b/ ~) p
Curvilinear relation, 曲线关系* v! J \& v6 p# g5 T5 d
Cut-and-try method, 尝试法
9 p" s- M: x: F+ G% ]Cycle, 周期, L1 f" u1 N D: y: F; {6 v
Cyclist, 周期性
! d1 p4 t6 l4 kD test, D检验6 F, |: ]6 W2 G1 t4 C3 b1 Z
Data acquisition, 资料收集
7 v+ e5 I7 F" W3 nData bank, 数据库, g, i/ n# E" F1 l
Data capacity, 数据容量
( j/ V. o3 Q# G; ~; hData deficiencies, 数据缺乏
% K" t8 a! Q- z, C; G4 HData handling, 数据处理
; f8 U p2 F: K) N# Y7 G2 x# T$ ZData manipulation, 数据处理
y( \: y4 Z' ?. W, f7 IData processing, 数据处理
, t4 ^5 m; {0 G/ W: HData reduction, 数据缩减9 @5 b9 j! S$ _9 `. T
Data set, 数据集% O, h4 l$ m% i
Data sources, 数据来源+ w+ K4 e l0 @* s
Data transformation, 数据变换
7 i( O- b- }% gData validity, 数据有效性) q9 l9 T) Z! j7 ~0 k+ z/ |
Data-in, 数据输入
- ^/ x7 o2 |7 ]2 v& U5 Y' JData-out, 数据输出6 {/ n3 y' K( K6 N0 v8 ]/ b
Dead time, 停滞期4 N, C3 z) s/ ]! y$ L. \; z
Degree of freedom, 自由度
3 t, n) n) w: p4 ]Degree of precision, 精密度
% K9 I" F: N/ @Degree of reliability, 可靠性程度9 E* q7 i A" ^8 z* \" L! n
Degression, 递减
' W, ?% _( _9 L" W' Y$ JDensity function, 密度函数
* f# e' y5 V4 J8 P* ^Density of data points, 数据点的密度. {9 F, h6 b* `& M; i0 y- A
Dependent variable, 应变量/依变量/因变量- p/ ~ ]5 B$ a5 p
Dependent variable, 因变量
z' k+ r! k; ?/ O3 j& S# _; i+ ADepth, 深度/ d" [9 n# w; \+ l& e
Derivative matrix, 导数矩阵
5 q) u$ Y& o+ g, ^( zDerivative-free methods, 无导数方法
2 R% r2 H3 e) k* z. {6 @( B2 CDesign, 设计; S* S# |! F7 U8 P1 o3 `# g, M
Determinacy, 确定性) V, B' x7 ]0 i* ]/ ]! }# G
Determinant, 行列式
3 i3 J* L! Q7 l2 ADeterminant, 决定因素# @( Z2 Y! i; y/ ?: p4 M" N T
Deviation, 离差( R4 D+ p: t+ L6 l0 |6 ~
Deviation from average, 离均差
" \9 N# R6 n; w7 Y( F" QDiagnostic plot, 诊断图
S7 s& d: E) X! S g9 IDichotomous variable, 二分变量; w) O2 @# q' u8 Q' K8 q
Differential equation, 微分方程
3 `( z7 y. o; O1 x# V* oDirect standardization, 直接标准化法8 F- U) `6 `' b& e. Y! p
Discrete variable, 离散型变量
3 x3 T1 M. K% O4 [. ?6 ~# v' TDISCRIMINANT, 判断
: V9 T3 q e% YDiscriminant analysis, 判别分析; x7 z, R! E: C5 M; a5 z. E, B
Discriminant coefficient, 判别系数
5 d: y/ a( F. P$ v) ?( VDiscriminant function, 判别值
* J+ Z+ Z6 q9 l* I0 W9 o# W( WDispersion, 散布/分散度
. x5 c. E( w5 R: HDisproportional, 不成比例的* E$ f; a% U: E, v4 {+ D T
Disproportionate sub-class numbers, 不成比例次级组含量7 P5 Y; b- ^6 o; y, H! P5 ~, E
Distribution free, 分布无关性/免分布4 S0 F1 y3 N" ~% J x" {0 A
Distribution shape, 分布形状2 j* V9 ~0 P K. P! z2 e( O8 O! ~
Distribution-free method, 任意分布法7 K4 o- V2 h: M3 m' Y' ]1 I
Distributive laws, 分配律
: H5 y! p/ a# x5 f5 G: }) SDisturbance, 随机扰动项( F, K4 H1 M4 m$ L
Dose response curve, 剂量反应曲线% e4 f7 r9 b0 N8 t
Double blind method, 双盲法
; f- j5 I( ^8 A7 i! A$ m9 C1 MDouble blind trial, 双盲试验
. M$ }9 t: O5 G8 t5 l+ YDouble exponential distribution, 双指数分布
" f _1 l3 x& C! M5 yDouble logarithmic, 双对数
' L' P" [, S; G' |Downward rank, 降秩2 p. B6 z1 K# H5 D( s
Dual-space plot, 对偶空间图
3 z0 o: A7 U4 P1 ^7 s E9 s& nDUD, 无导数方法
0 ]2 _2 O: j3 z* m% Z9 |! U' RDuncan's new multiple range method, 新复极差法/Duncan新法8 f3 m3 K) U$ J
Effect, 实验效应
* e! g. |4 V }! p, ]$ mEigenvalue, 特征值2 \/ j# ?! p1 l/ v9 N
Eigenvector, 特征向量 C, L7 D0 @1 Z* [
Ellipse, 椭圆
2 m- G C7 n. p w4 T) ^Empirical distribution, 经验分布- }/ B0 M9 M9 `4 z4 t* X
Empirical probability, 经验概率单位+ S: S$ O) x' T' a; F7 Y
Enumeration data, 计数资料9 W, \/ n& |+ N5 i1 `
Equal sun-class number, 相等次级组含量! }/ M+ E* O1 V# j$ {
Equally likely, 等可能. D) |- z9 O" P- e. \7 X
Equivariance, 同变性& U1 h) Z9 C1 t7 h) H- O- X z9 ~! C
Error, 误差/错误
4 S" {9 f7 d' ~6 } \9 U& W3 [* n! LError of estimate, 估计误差, ~* |3 Q( l+ I0 _. k+ ?
Error type I, 第一类错误6 S- w( n8 H) d7 l
Error type II, 第二类错误) j: W$ y. R2 e" w0 R
Estimand, 被估量$ k* W0 p4 K7 C1 d+ R2 Q* _
Estimated error mean squares, 估计误差均方
' C- |2 ^, c/ c0 T/ SEstimated error sum of squares, 估计误差平方和9 J4 Z3 J3 `1 t7 R
Euclidean distance, 欧式距离2 w( m3 \1 r- U5 L, ^0 d2 K
Event, 事件
( L6 o& V: ]! F7 YEvent, 事件6 s2 q/ i0 u6 r+ R+ o, u
Exceptional data point, 异常数据点
: S" B5 A1 f9 M" n& i- _Expectation plane, 期望平面
: N( L/ c% P! C. `4 |" w5 WExpectation surface, 期望曲面: f& c3 H; R g$ K" h% s) m
Expected values, 期望值& W6 d" q) x9 V. ^3 `
Experiment, 实验! \9 n( T0 k2 T
Experimental sampling, 试验抽样* e2 p$ d: r; c2 K* `& Y
Experimental unit, 试验单位 T" i7 A" R9 B
Explanatory variable, 说明变量
" W$ x" N% e4 i& b) L2 @# p RExploratory data analysis, 探索性数据分析
$ q5 g9 T- y4 n, \3 IExplore Summarize, 探索-摘要+ F0 \/ s! t9 F, T/ ]
Exponential curve, 指数曲线
$ Z$ u+ y5 Q# t1 Q& Q- k1 W0 c' p- WExponential growth, 指数式增长* R: |/ O- R# e( g% j% D/ b
EXSMOOTH, 指数平滑方法 " z3 f" [$ d' d$ f" n
Extended fit, 扩充拟合8 e# Z6 f5 L+ Y7 ], {* T- U8 I, O% E8 A
Extra parameter, 附加参数
5 E$ | d9 p$ d, J, t- |7 mExtrapolation, 外推法" x7 Y: }2 u0 Y# H8 A! G/ G
Extreme observation, 末端观测值) {. r- N- {, O3 f, G
Extremes, 极端值/极值
& ], S. ?0 |# v8 K1 P" S* d, e2 {: UF distribution, F分布
, f5 f! g6 T8 l" j, H$ ]0 _0 M7 TF test, F检验
" F. p7 m. B8 d- E0 W; zFactor, 因素/因子2 F% Z6 M( P+ A2 y1 w" o& H% Q# s
Factor analysis, 因子分析2 L: o8 M; W% B8 ^& l8 Z) t
Factor Analysis, 因子分析# u4 \% ]4 k4 _* m* y' K
Factor score, 因子得分 6 n- X3 n( p$ O$ d* H
Factorial, 阶乘
8 }; J3 N' m7 d4 N7 j& lFactorial design, 析因试验设计+ p" p9 M7 y5 [! _7 {; t
False negative, 假阴性+ x* q0 z' o* s3 E5 U
False negative error, 假阴性错误: Z( F, g# _0 o! K# Q1 l% ~
Family of distributions, 分布族
( g8 @5 O: a4 M8 x& pFamily of estimators, 估计量族
5 A# O. O6 a4 q: G' J. _Fanning, 扇面3 |% F6 R1 x6 @( t( Y
Fatality rate, 病死率
( ]. E+ P& a" n6 W" {4 r* kField investigation, 现场调查
- r# n% S* \- Z1 v1 Y. zField survey, 现场调查# k8 E% r N4 Y- I4 G
Finite population, 有限总体. F# J& z& g5 | y- [1 x4 W9 X
Finite-sample, 有限样本% \3 T, b- ?, I. q
First derivative, 一阶导数
) U! i5 |6 y2 L' ]) T9 h+ ~First principal component, 第一主成分* j/ [5 @, U" O7 V2 R- n7 O3 u
First quartile, 第一四分位数
T/ d8 H/ g/ h4 l. LFisher information, 费雪信息量2 b# Z# I6 W/ F
Fitted value, 拟合值
0 g% o7 ^$ w4 k' N( |' x y. W' QFitting a curve, 曲线拟合( o/ }3 l1 t, ~ w5 I7 G
Fixed base, 定基
, L9 I4 |: I( nFluctuation, 随机起伏1 r8 U7 b4 ^1 @+ p, V
Forecast, 预测9 m2 v; T' K. k& f
Four fold table, 四格表5 i5 ~: X- S/ C4 K( T
Fourth, 四分点
1 ~ D% T3 ?; X* g8 C: dFraction blow, 左侧比率
! }- _! o+ B: Z6 Q. r: RFractional error, 相对误差
1 |! k1 ~: Z7 B5 W Z% FFrequency, 频率
$ Q3 }* I# w# M3 ZFrequency polygon, 频数多边图
! s6 r5 H* M+ B. L6 j6 e8 ZFrontier point, 界限点; d( ]3 ~1 e. D8 I% `
Function relationship, 泛函关系
. ^( w1 Z. c, m# |Gamma distribution, 伽玛分布
% \7 I. a1 J; QGauss increment, 高斯增量
' X( P& q' i5 v" D. z7 GGaussian distribution, 高斯分布/正态分布: \) |2 p! {" O5 m3 V7 ^8 O1 K ?
Gauss-Newton increment, 高斯-牛顿增量5 d5 g2 {% |* W" o& w) Y+ I3 y D
General census, 全面普查
& s: w( P7 A+ B) B9 T2 a0 Y( AGENLOG (Generalized liner models), 广义线性模型 6 e4 ]2 X3 I6 y% C/ y3 ^* \
Geometric mean, 几何平均数
3 W5 m( k0 j2 p$ YGini's mean difference, 基尼均差
* L+ s: V* l& }, \GLM (General liner models), 一般线性模型
# X5 S1 p# E. A: P6 TGoodness of fit, 拟和优度/配合度
$ u. K$ `; k5 ~) @: `2 GGradient of determinant, 行列式的梯度
5 \- Z' ~) k, r" b8 dGraeco-Latin square, 希腊拉丁方 X& ?( s! `6 |) s$ t: u
Grand mean, 总均值/ p( [( N- R; _9 |
Gross errors, 重大错误
1 R- e* h& {' _- D# cGross-error sensitivity, 大错敏感度
C/ J8 |' q: c' j# R* bGroup averages, 分组平均
$ z7 r2 S! {" D& N4 cGrouped data, 分组资料5 w1 w' M4 g( F# S. V2 q
Guessed mean, 假定平均数
9 S# L+ g) r5 d! FHalf-life, 半衰期" l4 ?# ^, S, G6 j' c
Hampel M-estimators, 汉佩尔M估计量
" o. ~- q# f( ?& eHappenstance, 偶然事件
2 J1 [' ~1 _- N9 j' d6 H# hHarmonic mean, 调和均数
# `: L4 e4 ^* K1 r6 r0 FHazard function, 风险均数
4 o( c! \9 ?; r7 Y* nHazard rate, 风险率
2 ~* E2 S% { E0 hHeading, 标目 1 J3 i$ z0 y5 z0 c9 z
Heavy-tailed distribution, 重尾分布
# o- S9 m4 R4 E& _4 o X& YHessian array, 海森立体阵* D$ _. L9 x9 o' m' B/ D
Heterogeneity, 不同质( H W9 ~/ C! @; ^
Heterogeneity of variance, 方差不齐
8 ]: |! Q6 r4 E7 _/ qHierarchical classification, 组内分组9 ?8 J- k8 M! A$ @( h9 }
Hierarchical clustering method, 系统聚类法3 `1 r) X1 N; D _. n( r
High-leverage point, 高杠杆率点# {- u4 f' z2 b1 {5 \. B; ]( M
HILOGLINEAR, 多维列联表的层次对数线性模型
: x- }1 \- a2 F" F4 P: \Hinge, 折叶点1 e; v6 _6 V. P8 n6 N( C7 ?
Histogram, 直方图
# r; k5 P K- P) U: K* v5 |Historical cohort study, 历史性队列研究
1 W f. ?6 c2 t* f% Q4 g, F9 q+ T2 VHoles, 空洞9 u0 a4 D( s ~9 j" c6 b1 @
HOMALS, 多重响应分析
' z! Z ~+ A4 n6 m% QHomogeneity of variance, 方差齐性8 C. f7 k3 Q1 ?0 H' Q) `
Homogeneity test, 齐性检验6 b. E$ X/ g& i# ]' P; D, N2 w
Huber M-estimators, 休伯M估计量
" A+ Y* b: r$ H2 `5 m& sHyperbola, 双曲线+ A; p/ B X+ F- u/ I6 S
Hypothesis testing, 假设检验
9 ?1 L% ]6 y+ B0 {. f8 R( uHypothetical universe, 假设总体
; O f' u* J: b. `4 PImpossible event, 不可能事件4 B' a! o* p7 l# N. w8 M" I
Independence, 独立性
3 H* K5 n- u: h! g) n t" R% ZIndependent variable, 自变量! i) G7 ?- N! ^2 ~3 W/ g
Index, 指标/指数
5 M6 G# o+ E1 K/ JIndirect standardization, 间接标准化法
& E* b4 a1 }6 v& J, lIndividual, 个体
3 ~' I+ O) s0 b+ `. t0 dInference band, 推断带0 }8 n* @0 O9 o: V T
Infinite population, 无限总体
, U# M6 y- z! Z# |$ K! ~* T" Y: pInfinitely great, 无穷大7 T) S6 |: u7 Z% F
Infinitely small, 无穷小
! N2 F F+ z$ S. G" pInfluence curve, 影响曲线# h: [8 w s* E
Information capacity, 信息容量
5 w5 n1 ~/ q, H: n4 B1 RInitial condition, 初始条件$ a6 E+ g# A+ t$ S- i- D' i
Initial estimate, 初始估计值
* I" W7 H- _) m& JInitial level, 最初水平- D7 N0 ?* |* G% `8 E
Interaction, 交互作用1 z% v! {$ j4 j% Z3 I
Interaction terms, 交互作用项
7 X4 L* g$ C' ^6 RIntercept, 截距
1 B0 j3 B, v8 x. n! G- d- pInterpolation, 内插法
# z6 ]4 R) K- a: i2 cInterquartile range, 四分位距2 D% E3 H; |7 x' }* i& Y% \+ _
Interval estimation, 区间估计0 D a" U* r' ?/ i7 z3 H4 V5 L
Intervals of equal probability, 等概率区间! @6 R% e8 D: D0 x! \5 A1 \- y
Intrinsic curvature, 固有曲率
& m3 k3 d' Q# L& w2 V! yInvariance, 不变性
; f* x/ [0 j I8 @% UInverse matrix, 逆矩阵; `) v8 P/ n# L" ~8 E
Inverse probability, 逆概率
% |4 I; q) x n$ Y- O& X: @Inverse sine transformation, 反正弦变换
3 f/ E" O& x1 b) t7 ^) B1 H+ wIteration, 迭代
2 R7 o' A+ r- s/ `Jacobian determinant, 雅可比行列式
7 j3 L: h3 ]: J6 K/ xJoint distribution function, 分布函数
' G# |. ?, I0 C2 A0 qJoint probability, 联合概率
& F& P, i5 N" t5 R9 \Joint probability distribution, 联合概率分布# h; H- `0 a) C- H$ d5 n
K means method, 逐步聚类法
) P- r+ k( y+ @5 l$ U, K! ]" \Kaplan-Meier, 评估事件的时间长度 & _; `0 t) X& f" |7 r
Kaplan-Merier chart, Kaplan-Merier图
1 ^# _; l r2 o' w$ ]9 U2 F- oKendall's rank correlation, Kendall等级相关" J/ u1 F# D1 b1 \3 u5 o' Z2 [" M0 a
Kinetic, 动力学* V3 |# b$ \' q1 U* y' {/ d
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
H3 R) m& m) bKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
) M; Q7 K2 Q. l/ Y2 SKurtosis, 峰度# Q; g# B0 E7 D4 @6 j7 ]
Lack of fit, 失拟) }2 @$ I! m: m7 y
Ladder of powers, 幂阶梯
! s( e5 [) h2 ?Lag, 滞后4 q2 ]: j* j5 d( }+ c. Y9 A
Large sample, 大样本5 q9 p$ H- X% e3 B) {
Large sample test, 大样本检验
9 F; s8 e1 q+ i K* T7 ?Latin square, 拉丁方1 e( o, _+ i2 m4 u8 A
Latin square design, 拉丁方设计
& F8 W- S" ?$ }3 A8 @# w, {Leakage, 泄漏
+ h" [& r- \' T6 l$ F" aLeast favorable configuration, 最不利构形( K+ u1 i+ @- Q* Q6 x& G8 m7 \9 K
Least favorable distribution, 最不利分布- t" Z* q& d- ]" r
Least significant difference, 最小显著差法
& f2 v7 V1 U- i" {$ H0 m* N6 E( TLeast square method, 最小二乘法) A0 y7 ?+ h& O* V& I
Least-absolute-residuals estimates, 最小绝对残差估计9 m% o- O0 @1 O& J
Least-absolute-residuals fit, 最小绝对残差拟合
: E0 l: N m4 F2 |% ]Least-absolute-residuals line, 最小绝对残差线- p4 E) Q) J5 K. A. Y1 T
Legend, 图例3 j+ [: v; T# n1 ~# a! M
L-estimator, L估计量, ^. G) o" I+ M3 b
L-estimator of location, 位置L估计量
0 I9 S! N; U) I. M& a DL-estimator of scale, 尺度L估计量( { x4 A. K; r
Level, 水平
7 _9 z9 F# W2 t; ?& R) v- U! |Life expectance, 预期期望寿命% F) Y+ D' _. @7 d- S0 `5 S0 y
Life table, 寿命表
: h' {/ Y9 v) h8 i/ }Life table method, 生命表法" Q& t! i& m2 m4 y& s, A7 r' y
Light-tailed distribution, 轻尾分布
6 C% @* o& ]9 z, J4 QLikelihood function, 似然函数* F1 D2 }6 E2 D k$ G5 @% j7 O
Likelihood ratio, 似然比/ I# P% [1 @" `1 E8 y9 O! p9 M7 }
line graph, 线图6 w5 w+ q7 {$ c2 z+ L
Linear correlation, 直线相关
2 \% n9 k1 O4 ?& QLinear equation, 线性方程) y2 j) g% `4 z. D7 ?
Linear programming, 线性规划! o0 M' ?6 N1 L8 X# X
Linear regression, 直线回归
P' i) s1 Z; eLinear Regression, 线性回归' p" H. S% y9 L8 m
Linear trend, 线性趋势
4 k+ P7 H' q# w; }; V" BLoading, 载荷
2 c) I' {7 m% G' U1 tLocation and scale equivariance, 位置尺度同变性6 u! X/ @- n6 J7 d- c) o. L2 e3 v/ j
Location equivariance, 位置同变性$ ?: m$ t) U* Q" S- o
Location invariance, 位置不变性6 g4 ^' h& O: y2 P) _/ c
Location scale family, 位置尺度族! g9 ` U( G1 e- d2 H- d2 R
Log rank test, 时序检验 1 Y: I- R2 ^! i! t0 M
Logarithmic curve, 对数曲线6 F% c9 U) |' m/ p
Logarithmic normal distribution, 对数正态分布
- r+ Z/ a7 \4 {, U3 d1 }Logarithmic scale, 对数尺度3 X2 {; j5 z: K1 Z7 R$ g7 ^+ \
Logarithmic transformation, 对数变换& _3 A0 j/ y. r( H
Logic check, 逻辑检查
; Y- f) Z" I6 m! mLogistic distribution, 逻辑斯特分布) q% }: @( a* t& G$ m C
Logit transformation, Logit转换
* m) y! W. H! W# g, `+ ^LOGLINEAR, 多维列联表通用模型 $ o1 ~6 v* E9 i
Lognormal distribution, 对数正态分布
1 H- T3 P6 \1 J# i/ b& GLost function, 损失函数. T9 F) h1 w+ c7 r
Low correlation, 低度相关
+ M% V# F3 M$ p) X* m: BLower limit, 下限) x- h$ q* u3 t# E9 u+ x
Lowest-attained variance, 最小可达方差# w! s$ l) |. A1 n# M8 v
LSD, 最小显著差法的简称
5 C$ a' T# x3 ?/ FLurking variable, 潜在变量
( [% o+ @" |$ w/ F" b+ \) gMain effect, 主效应
: Z% _" M# ~6 K* nMajor heading, 主辞标目6 p' x/ ]7 F, R- C+ ^* X
Marginal density function, 边缘密度函数" a! D r0 s6 B' L9 m
Marginal probability, 边缘概率% R" b1 K/ {! t2 L0 V+ j
Marginal probability distribution, 边缘概率分布
8 ?/ j2 d# K( Y z: k6 S9 D1 w7 jMatched data, 配对资料! y% {- {' U1 g" [$ ~1 b9 E
Matched distribution, 匹配过分布( ^2 S/ f5 r# J1 C: x6 Z
Matching of distribution, 分布的匹配
* E/ u( ~% X& F# c# H1 }# vMatching of transformation, 变换的匹配/ h8 U% P7 j$ D3 X8 @
Mathematical expectation, 数学期望1 C! {7 v$ O4 }& P
Mathematical model, 数学模型/ B2 s6 O: @1 a/ b
Maximum L-estimator, 极大极小L 估计量3 o' C/ l8 j2 K5 p/ A
Maximum likelihood method, 最大似然法
# D9 F! G# S) i1 ~, [2 AMean, 均数& \+ `7 D& j, [5 y- I9 {3 c8 o7 @
Mean squares between groups, 组间均方2 H- ]( l" l2 T/ A2 ~
Mean squares within group, 组内均方
) l6 D. o4 d' k1 [. xMeans (Compare means), 均值-均值比较8 D, ?" D& x! y) G! W& }3 }3 u
Median, 中位数& z. {1 X$ h, i+ K! @3 J0 S
Median effective dose, 半数效量4 x9 d7 @2 J8 P: m
Median lethal dose, 半数致死量
5 M5 ]2 b( E" v+ C+ X# t/ ?" {' LMedian polish, 中位数平滑. s! J% y. n5 A! A0 B
Median test, 中位数检验, o8 y1 j$ S0 R H5 K. q
Minimal sufficient statistic, 最小充分统计量
' U4 R1 ~* f }$ Q- RMinimum distance estimation, 最小距离估计
( Y. }, o2 H3 a" S7 V& N0 X ~Minimum effective dose, 最小有效量
6 p: k; H2 c. R+ N1 _; fMinimum lethal dose, 最小致死量
l$ ~& I% e3 O. a6 h. [Minimum variance estimator, 最小方差估计量
- G$ a% c- @- _& F8 H/ v1 B3 u7 hMINITAB, 统计软件包4 B2 P, n- k' e, @" |; D, \
Minor heading, 宾词标目2 z! d4 }- o# r) H9 N' r% C
Missing data, 缺失值' g5 Y" V q$ I4 G/ Y! K/ f
Model specification, 模型的确定
- o9 i: @: S& W& T# _Modeling Statistics , 模型统计
. _- P; s9 H" |: y! j+ KModels for outliers, 离群值模型* H$ x8 n5 J C+ n% J' @6 G
Modifying the model, 模型的修正 E* q V$ n: _' u
Modulus of continuity, 连续性模
, M6 o2 n& O& h; }% |. E' K$ GMorbidity, 发病率
$ h$ g/ W, \ G" C% U3 i3 @& }Most favorable configuration, 最有利构形) N8 T: C5 ~& u+ R- L8 b
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
1 U! \0 j w* y p& K; sMultinomial Logistic Regression , 多项逻辑斯蒂回归
/ c" _5 P; l9 x# Y+ D0 `" wMultiple comparison, 多重比较
- }2 T: R( z3 ~( H9 g; ?Multiple correlation , 复相关
) @9 c: v6 c8 M$ R9 |, T2 n0 V; HMultiple covariance, 多元协方差
; ?3 P" }% C2 o9 f5 h& A& aMultiple linear regression, 多元线性回归7 {. \# Q/ q% e3 I" a3 R
Multiple response , 多重选项
5 ^; V. F c* R6 z! }7 ^Multiple solutions, 多解0 l9 C& |% }$ ~" c
Multiplication theorem, 乘法定理
& H7 I% t9 }: H# M2 l. e, O7 MMultiresponse, 多元响应+ u' l( O3 n9 M$ \- j
Multi-stage sampling, 多阶段抽样% E" s; W6 S) W: S0 V4 M- E
Multivariate T distribution, 多元T分布' ^8 u% S: O/ W; `, w& m& ^( O
Mutual exclusive, 互不相容
. o7 A! u' J- Q! w+ w7 p8 mMutual independence, 互相独立
6 a8 ^. N$ J$ Z0 s& ~9 SNatural boundary, 自然边界& t# F$ k1 d! t! I' W
Natural dead, 自然死亡
' c3 B2 T% ^0 xNatural zero, 自然零# Q; Y- G, F8 \' y" p
Negative correlation, 负相关* ~1 ~4 m1 m* a$ u O
Negative linear correlation, 负线性相关
& ?6 Q& e; [2 b _Negatively skewed, 负偏
" _/ t0 J5 ^0 b. sNewman-Keuls method, q检验4 X$ `; R% y8 M* A. T1 s
NK method, q检验. B4 S( N ?# c y9 n0 n) r& G
No statistical significance, 无统计意义
: t& E+ x5 @) v* G$ u0 u7 }+ mNominal variable, 名义变量0 i0 G+ u k$ W2 X/ D$ _/ k
Nonconstancy of variability, 变异的非定常性
: h* k7 `1 ~6 c0 PNonlinear regression, 非线性相关
$ N8 x. t9 M5 e) x% r |Nonparametric statistics, 非参数统计
% }1 a, U" v: P5 b5 P/ N/ jNonparametric test, 非参数检验
. G4 s/ u& ]/ j' j/ o& INonparametric tests, 非参数检验7 E. |: m* a9 W+ V6 |
Normal deviate, 正态离差
" o- w0 s" n8 {* g- a; @Normal distribution, 正态分布
7 _0 E1 y! L. s" r# W0 S+ KNormal equation, 正规方程组4 v1 B$ a2 a! Q
Normal ranges, 正常范围+ B9 z2 i/ p3 }2 O
Normal value, 正常值: ^1 B1 m0 y: t" z
Nuisance parameter, 多余参数/讨厌参数2 @+ d+ D6 g2 M# e p+ n
Null hypothesis, 无效假设
: b1 ?' I X0 M2 r0 \) LNumerical variable, 数值变量& g) `: D: S+ @, M' Q1 k" x
Objective function, 目标函数
- b7 t* J, p: \Observation unit, 观察单位1 a/ ~3 c6 i& ?6 r+ V5 v# B2 G0 I$ j
Observed value, 观察值5 ]3 a7 m# P: C! i2 o; x, z: |
One sided test, 单侧检验
2 p: O/ |, i# H/ s* O* o( iOne-way analysis of variance, 单因素方差分析
$ X5 ]4 H+ Z, j1 ^2 w% ZOneway ANOVA , 单因素方差分析
1 i! C4 Y5 u! B, F* G/ aOpen sequential trial, 开放型序贯设计
. y- k. N& Z) e/ i* I6 \& JOptrim, 优切尾6 ~: o; _* n+ n8 |9 w0 P. U" B
Optrim efficiency, 优切尾效率8 Z0 i# J" [( J |
Order statistics, 顺序统计量* ]# n- |. z' i2 M j
Ordered categories, 有序分类
5 x: Q! Y% }# ]Ordinal logistic regression , 序数逻辑斯蒂回归" k( c& k% c& g! \) Q) q! q% w) R
Ordinal variable, 有序变量
1 \ n: x% [, ?. |2 }Orthogonal basis, 正交基3 m# q. q- g0 L; b' t% y& s
Orthogonal design, 正交试验设计: V5 d0 w1 R2 {& s& v$ C1 P) {
Orthogonality conditions, 正交条件# }! p) R1 P. X8 s! I; C+ U# h
ORTHOPLAN, 正交设计 ' e& j* k& y# J0 I
Outlier cutoffs, 离群值截断点
* w+ z' |8 n; a* y: mOutliers, 极端值4 F+ b$ \, Y5 a7 ^) s8 q+ S4 V v
OVERALS , 多组变量的非线性正规相关 5 t p5 V6 Y+ R# R/ U: @' m7 u
Overshoot, 迭代过度* a3 b% z/ Q2 U; e; |1 U! ~4 M
Paired design, 配对设计
3 C7 n" C5 y4 n! U- J8 Z9 rPaired sample, 配对样本
N9 L: {8 R4 m _, DPairwise slopes, 成对斜率
& Z3 h5 z% u# b6 BParabola, 抛物线9 k N) G5 x8 c' h* O
Parallel tests, 平行试验
0 s, g. |3 v" T& NParameter, 参数' v4 N$ Y' n: q* Z0 s
Parametric statistics, 参数统计
& _; S+ ]( w" v0 O2 v2 BParametric test, 参数检验' A- w$ v; L1 x# a4 L1 U
Partial correlation, 偏相关
0 H; m% A+ j1 R6 f0 h% @Partial regression, 偏回归- k B9 e8 X: n: U; f9 l
Partial sorting, 偏排序
) o+ e( q6 U( ?2 r, L+ [9 c- V) D2 tPartials residuals, 偏残差. s; O8 g7 K1 W
Pattern, 模式+ {. ^* d4 a* {
Pearson curves, 皮尔逊曲线
* ~/ D2 l, e0 IPeeling, 退层
' J' d$ z( z% {5 J, }% a4 m3 j- TPercent bar graph, 百分条形图
; r r* F. b* g/ ^% F2 QPercentage, 百分比
- O- f. O; K1 l. s: xPercentile, 百分位数1 l4 Q" g! O) H4 Q) [0 Q
Percentile curves, 百分位曲线
; X# V8 v8 \) V4 APeriodicity, 周期性
, g4 M3 B" |! @' ~. H0 iPermutation, 排列
& d$ o# T" D% H n5 W; C8 o& H. C" A+ DP-estimator, P估计量3 H8 D: L# n' s' D( u W
Pie graph, 饼图
# c+ F+ Y+ n+ V7 u: x% `3 CPitman estimator, 皮特曼估计量
( D1 e/ S7 P) y& j2 A! J9 V. W( `6 l; gPivot, 枢轴量
% u6 U% k7 I1 Y% W RPlanar, 平坦! I& o1 O3 M/ N+ b1 B2 b! b. i
Planar assumption, 平面的假设4 C# b: ~3 k; `- j" ^& N$ O
PLANCARDS, 生成试验的计划卡, J s, f5 H) ]0 |1 a2 Q3 A3 Z% ^1 u
Point estimation, 点估计
+ P( y' n+ i' p1 d ?- oPoisson distribution, 泊松分布4 C$ O. ?: t) q9 k0 ~3 @
Polishing, 平滑# k0 v6 p" J4 F( ]3 a
Polled standard deviation, 合并标准差: b1 W# M3 R$ g4 \
Polled variance, 合并方差) ^8 c& M# M& D, P, W; [3 \
Polygon, 多边图
/ }/ g" o; Q) i! z6 xPolynomial, 多项式
7 U" V! u' q0 G; c& J+ `: _Polynomial curve, 多项式曲线 M& R7 V. f1 s% l2 g2 r
Population, 总体$ F" v5 K) r8 s( b
Population attributable risk, 人群归因危险度
. q1 H! q) T3 TPositive correlation, 正相关
5 {1 o1 u) _4 [0 L6 vPositively skewed, 正偏6 K$ V- U! B2 _. Y2 g/ e- t9 n. a
Posterior distribution, 后验分布
3 n4 s9 T" Y2 A. xPower of a test, 检验效能$ t$ i6 k- ]7 W
Precision, 精密度
; t; {8 v5 }4 W3 u5 BPredicted value, 预测值 e" }0 \3 i' B: [7 b% V2 f+ u7 B* b
Preliminary analysis, 预备性分析
) o) X9 p6 A: i9 F NPrincipal component analysis, 主成分分析
0 k1 d! t1 V1 d5 M( _% \8 ]% ^7 ]Prior distribution, 先验分布( w9 y# }' B- e4 ]0 q4 W2 u; Z
Prior probability, 先验概率0 B0 P2 j2 i6 C+ B d
Probabilistic model, 概率模型" D' e& ?2 |2 c8 _$ s/ }' r: R0 N
probability, 概率
+ V! v! e) J, ^, x. ^Probability density, 概率密度
: E$ N$ W. K$ ?* cProduct moment, 乘积矩/协方差
4 o6 t; r( y2 M, RProfile trace, 截面迹图
2 a3 V' j* O& t7 r2 F9 a, h' H. a6 d9 QProportion, 比/构成比
: [& e$ A% J4 T4 t4 O5 x/ h- IProportion allocation in stratified random sampling, 按比例分层随机抽样 G7 [" A7 \. v6 g
Proportionate, 成比例
/ q. z. j6 f9 [Proportionate sub-class numbers, 成比例次级组含量# U# f7 ?5 v# S1 H
Prospective study, 前瞻性调查: ]( ~3 ?4 q9 ?' ?: Y- O" _6 E
Proximities, 亲近性 ' _+ K% H, S6 x$ W; P
Pseudo F test, 近似F检验
1 `! _' R7 V" o; _9 ]' A% TPseudo model, 近似模型
$ e- h/ a$ ?9 C2 uPseudosigma, 伪标准差 k9 m9 U' z \ P7 C5 z7 ~' T* }
Purposive sampling, 有目的抽样
( m3 }$ F2 e4 H. o5 g: hQR decomposition, QR分解8 f8 y: b' t8 B5 A6 S
Quadratic approximation, 二次近似3 a" w8 u% V* }$ ?" X' l
Qualitative classification, 属性分类; T+ L. c9 v1 C5 ^" T1 h% u0 f
Qualitative method, 定性方法
1 X" i, p, u8 o9 g! k2 JQuantile-quantile plot, 分位数-分位数图/Q-Q图
/ Q9 E6 S5 H; yQuantitative analysis, 定量分析& l) }4 A& @4 F
Quartile, 四分位数# }6 u* H; d4 d4 {0 r# M
Quick Cluster, 快速聚类
. m$ Z/ y. g2 hRadix sort, 基数排序. g3 {7 X7 o2 `5 l9 u+ C
Random allocation, 随机化分组
5 z" K: {3 ] a& T" pRandom blocks design, 随机区组设计: P m# r, B. B, r0 _& n
Random event, 随机事件
/ T% V3 S. K. l. x4 |5 K0 J4 Q$ FRandomization, 随机化
1 q( R0 H! z7 W4 n+ Z1 u+ xRange, 极差/全距. ]9 ^6 |% k3 T2 W; c! m: T
Rank correlation, 等级相关3 i1 z, j+ `4 T$ L } C; K* D9 h
Rank sum test, 秩和检验& V# S! L, M. P0 v
Rank test, 秩检验
9 ?6 e8 y% u( t. ]: TRanked data, 等级资料) E) ?# C! \0 v5 L
Rate, 比率. [- E8 ^7 O: |$ H
Ratio, 比例
. m* i: W' C$ v! y, u2 q+ |6 dRaw data, 原始资料
) W1 E( B7 c* Y P2 z" NRaw residual, 原始残差
1 A# g# w% K0 z7 \" bRayleigh's test, 雷氏检验& T" c9 A# Z$ Q& r2 o9 V7 l
Rayleigh's Z, 雷氏Z值 & s2 A# E) n, D( G7 l
Reciprocal, 倒数1 U; ?; N% m, L8 f0 h e8 X
Reciprocal transformation, 倒数变换, }( z3 C7 X. s: h6 ~1 @: m) f0 N
Recording, 记录+ O* P5 c% U$ V. Y
Redescending estimators, 回降估计量
& A) r% I% J" m# V1 }Reducing dimensions, 降维
4 n9 N- j( g" WRe-expression, 重新表达
$ A+ o0 B3 m2 @; M v! X7 [Reference set, 标准组' U! L/ q- ~. M- n0 ^0 d
Region of acceptance, 接受域
5 t; }1 ?/ A" r; g; O dRegression coefficient, 回归系数
& K( f8 m1 E- X0 xRegression sum of square, 回归平方和
3 b, Z6 j' d' DRejection point, 拒绝点% }7 Q, R ~: ]' y, Y4 q( ^" [
Relative dispersion, 相对离散度
/ k: e9 w, q3 l& E, B- G- o6 e; c6 iRelative number, 相对数
6 q) a, u% h, v% I: y# w0 a7 CReliability, 可靠性
0 _6 a" S) O& m) h8 A) A/ U5 kReparametrization, 重新设置参数
2 h6 p& F: @0 k# N: `+ oReplication, 重复
' i9 f0 P' k$ x: J( y) p% l' VReport Summaries, 报告摘要
: z- e* q! g9 W+ i; A2 O& LResidual sum of square, 剩余平方和' k( [; F. C; _# X
Resistance, 耐抗性
( `3 v9 P; j* q* x. L# VResistant line, 耐抗线
6 d, X6 Y$ `5 K* \# p6 | K. fResistant technique, 耐抗技术 x' k9 Y5 X0 j- a* |( P
R-estimator of location, 位置R估计量/ P$ ^0 t- g- {9 J$ f
R-estimator of scale, 尺度R估计量8 }. S9 b2 @4 C
Retrospective study, 回顾性调查
" M; S2 Z: ]+ G" `( t {( R1 _* JRidge trace, 岭迹+ `' b+ [) `7 U: S
Ridit analysis, Ridit分析8 @" ^& I, w K; L6 k) |& v' p
Rotation, 旋转
, p& w1 `0 k, }4 E8 H9 j5 h$ C5 |# vRounding, 舍入- Q( z1 w2 k3 y9 N1 a6 m
Row, 行
! f Z! `) E1 RRow effects, 行效应 `/ R4 J6 x6 F1 ^" D3 ]4 g3 a
Row factor, 行因素
) ?, e2 [7 d; FRXC table, RXC表& s! i& ^- U# V( l1 Q: b" t$ q0 m
Sample, 样本; K3 l7 o; @4 n/ Q6 F" a
Sample regression coefficient, 样本回归系数
+ S! c# D0 v$ n \" ~' R6 x' bSample size, 样本量3 F# Q' C# ?- ^, D( s: ?. y w
Sample standard deviation, 样本标准差
( ~. S& ?2 t; L% m2 x/ qSampling error, 抽样误差9 i3 \! T- k5 r i b$ Y' j! h
SAS(Statistical analysis system ), SAS统计软件包. o% ` H, L8 s: Z; F" G
Scale, 尺度/量表6 X! X! t4 R2 @9 v; j, g @
Scatter diagram, 散点图
c1 ?5 |' t4 L" f( w. JSchematic plot, 示意图/简图
+ d7 p+ H) N6 T; |% h8 G! U$ mScore test, 计分检验9 ]5 b1 }( i1 y5 j+ u
Screening, 筛检! o9 M/ o: s3 |7 S: k/ y
SEASON, 季节分析 8 S8 b3 T: C3 {, \
Second derivative, 二阶导数; t; i% W, I: V$ p* ?
Second principal component, 第二主成分* V& v! x9 v% \
SEM (Structural equation modeling), 结构化方程模型 8 q, o. E, @5 [/ I) a% @
Semi-logarithmic graph, 半对数图
0 t* q/ I. I4 p% fSemi-logarithmic paper, 半对数格纸8 t, W, T q( o6 u
Sensitivity curve, 敏感度曲线
" w4 w7 D! D2 T# n: t3 I" iSequential analysis, 贯序分析- v. R/ X9 a/ R! o O0 ?% G/ o
Sequential data set, 顺序数据集* i% ^2 {! i% |+ w1 a2 H( c
Sequential design, 贯序设计
! Y- p1 x# j4 u" L! e4 b& |0 TSequential method, 贯序法
5 U) Z4 L& T( c8 vSequential test, 贯序检验法$ W+ @9 X t" b' c7 X8 h( K
Serial tests, 系列试验3 h! y' S5 E9 _
Short-cut method, 简捷法
) m# }5 ^( b# DSigmoid curve, S形曲线
" _. E6 t+ a+ Q+ s" O# W( {Sign function, 正负号函数4 K0 H4 S) q) w" `: N2 m
Sign test, 符号检验8 _" ]# Q) A/ B* E2 x
Signed rank, 符号秩
7 \! Y" O" A4 [# R8 RSignificance test, 显著性检验3 N4 G# e1 ^6 b
Significant figure, 有效数字
+ k1 x/ N) y5 j Z6 xSimple cluster sampling, 简单整群抽样
: }4 e* G: y9 MSimple correlation, 简单相关1 x6 i* v. ~' }
Simple random sampling, 简单随机抽样0 t& Y) l. {$ h" q# r1 w
Simple regression, 简单回归 n- ^4 _9 n8 K3 a' s
simple table, 简单表- b; A1 G$ n% f2 n9 X6 \3 r
Sine estimator, 正弦估计量4 [# Q) y1 c" j: e5 w9 m
Single-valued estimate, 单值估计, }8 P% N% Z' w* W9 Y/ _) [; y
Singular matrix, 奇异矩阵) _: y. u5 R) @( l# {
Skewed distribution, 偏斜分布% @2 ~+ E& g9 k
Skewness, 偏度
( c/ u3 V9 } d5 C# jSlash distribution, 斜线分布) Q5 v+ j" C$ K
Slope, 斜率2 u2 l( A1 `% m3 D# i3 ~% M; d4 ?2 B: u
Smirnov test, 斯米尔诺夫检验
4 X: i' X1 o4 I, C. S; P2 WSource of variation, 变异来源
@) y% E2 s. e! CSpearman rank correlation, 斯皮尔曼等级相关 c, g5 ]1 z8 T' a Q: z* b/ _- a7 T( ^( W
Specific factor, 特殊因子- M5 z- q+ A1 w3 `& ^9 I
Specific factor variance, 特殊因子方差
# A- M$ t' y0 {& GSpectra , 频谱( O# L5 l& G% {+ ~$ L; _
Spherical distribution, 球型正态分布2 {, d2 @3 r1 t) q9 V. X/ \0 B# ~
Spread, 展布+ ?+ Q2 G* z0 C# v: g' {4 K
SPSS(Statistical package for the social science), SPSS统计软件包# Q; O9 H- r: X9 j
Spurious correlation, 假性相关5 |+ E" N. ]) y. u. }
Square root transformation, 平方根变换, D; c$ x& m" P/ T
Stabilizing variance, 稳定方差8 c" B9 J0 d; ^" h! H: j! |
Standard deviation, 标准差% Q2 X8 t5 ^4 ^% h3 i& a/ @) B
Standard error, 标准误
0 H3 \: ~0 G8 q5 M+ TStandard error of difference, 差别的标准误
: X" s: j7 t1 E# ^5 `Standard error of estimate, 标准估计误差
/ y3 t& O: S' |! r6 w; HStandard error of rate, 率的标准误
0 d% o. o% z( n2 h4 \+ IStandard normal distribution, 标准正态分布
, I. _- g. \, \! gStandardization, 标准化
7 c% A! T- Y$ z% B* i* |# j+ C! zStarting value, 起始值
5 _& ~0 G" O S3 f/ ?% q. W6 zStatistic, 统计量
8 ?) R2 r7 l* R" k/ m( N4 _Statistical control, 统计控制
7 b* Q" ?% N2 TStatistical graph, 统计图. W' f! } w* I, C* i* M; C: l
Statistical inference, 统计推断) h/ F# `, I ?7 Y
Statistical table, 统计表/ l1 c9 |1 |# M
Steepest descent, 最速下降法
% g6 q! h$ o! k" R7 `) KStem and leaf display, 茎叶图! P, T+ R( U5 _( a
Step factor, 步长因子
# r1 @6 y2 d# Y" n$ }; {" ?0 jStepwise regression, 逐步回归( [( B ?4 U- H6 B/ D7 m. s
Storage, 存
/ ] [4 O0 ]8 _$ @6 F' uStrata, 层(复数)& Q; _- I2 T; @; Z& m1 A
Stratified sampling, 分层抽样
9 Y! ?! L0 Z" R/ h w7 ]- RStratified sampling, 分层抽样: [7 X9 T/ M" k8 D; G4 u8 ?
Strength, 强度
' M; ^" k% H7 VStringency, 严密性; o' F7 `. B4 i: _+ v, N# o0 Y) _
Structural relationship, 结构关系7 J; I8 S, g$ n& w* q
Studentized residual, 学生化残差/t化残差
/ m8 L- O0 Z* @$ H- kSub-class numbers, 次级组含量
2 R5 ]9 i7 g2 O! X# ]0 W% S9 |Subdividing, 分割/ |0 y3 X' }' s: v& E7 ^
Sufficient statistic, 充分统计量, z8 Q1 A/ I- F v3 y
Sum of products, 积和2 C6 Y8 ?4 t5 a% z4 V; L2 F4 _6 w
Sum of squares, 离差平方和0 S5 t# d& y. Z# C+ c9 r
Sum of squares about regression, 回归平方和
, d( Q- I4 t2 K" b. WSum of squares between groups, 组间平方和7 j0 C/ [ U! P* L- h) K
Sum of squares of partial regression, 偏回归平方和% p2 F+ D5 ^+ d, X0 a0 d" q) E8 ?
Sure event, 必然事件
( [& v, h" S4 x& NSurvey, 调查0 w- z/ n( q8 G9 @) m
Survival, 生存分析
( t, p$ W/ L+ a4 b; TSurvival rate, 生存率
/ @3 t0 e$ ^) z+ O. Y5 G" iSuspended root gram, 悬吊根图
/ E! v4 S% x7 W1 f xSymmetry, 对称9 x, j; J3 g1 U2 P. a, k" A
Systematic error, 系统误差' E) ~; i0 W M- U8 R4 R. [
Systematic sampling, 系统抽样: ]& W: o2 X( q# q/ H1 |1 a
Tags, 标签6 {6 c8 D) D/ n/ C$ U
Tail area, 尾部面积
+ Y0 \1 X* X U1 kTail length, 尾长
: K5 R2 s: ]# W& D" _Tail weight, 尾重6 a, \0 G3 _5 {
Tangent line, 切线
+ [& b9 r$ F: m! C# U' j( C& hTarget distribution, 目标分布, f5 d( w9 U2 w; v/ J+ k' W
Taylor series, 泰勒级数" q F1 D, Z2 M4 k! n
Tendency of dispersion, 离散趋势
1 o. P( }* q# M$ ~Testing of hypotheses, 假设检验/ S, A+ o9 e% `$ x' I
Theoretical frequency, 理论频数
6 `5 r0 Q. [+ O+ Q1 V$ U; RTime series, 时间序列
5 x. m7 b: T: [* a; @0 l* ^" oTolerance interval, 容忍区间5 k5 g2 x" Y4 g3 h8 s# o( i) F
Tolerance lower limit, 容忍下限
7 m3 `9 O1 m- @$ T8 b6 d$ PTolerance upper limit, 容忍上限" J, V- B. j+ n) b
Torsion, 扰率
/ Y2 m* M1 q X6 |8 E+ d) i) iTotal sum of square, 总平方和
5 t) b/ K; e1 |+ h6 PTotal variation, 总变异
4 x" x# U6 ?, n. N" F3 \- [. zTransformation, 转换
" P! A0 n* t) V+ |3 E0 d u3 eTreatment, 处理: Y. E$ N3 E w. A4 U
Trend, 趋势
& v5 c9 t" p1 \' b; ATrend of percentage, 百分比趋势4 e6 O# c9 S3 v$ [& w3 v
Trial, 试验7 q5 b5 m4 f4 o
Trial and error method, 试错法
6 u. o; P# \! Z5 l! ]; e2 X% v" b: NTuning constant, 细调常数8 [3 j- q5 s6 M% s% F) w
Two sided test, 双向检验
- A3 Q0 Q( G3 G7 X7 @Two-stage least squares, 二阶最小平方
' ]8 U1 }! M7 a: t. E$ K8 }) _Two-stage sampling, 二阶段抽样8 a Q) r7 ~# `' I
Two-tailed test, 双侧检验: d; G% p& B4 c4 z2 U
Two-way analysis of variance, 双因素方差分析
. m* J/ l8 D) o0 CTwo-way table, 双向表
! a; C# F" ~% u5 G+ _) w+ L% mType I error, 一类错误/α错误+ B# _& I" _3 u
Type II error, 二类错误/β错误, u8 N9 a- s8 W3 _& u( ?9 v
UMVU, 方差一致最小无偏估计简称% I$ \0 M8 F* k Y
Unbiased estimate, 无偏估计
3 L5 M1 d8 p, u3 @/ V) DUnconstrained nonlinear regression , 无约束非线性回归
5 ]; D0 O' f+ C+ J" wUnequal subclass number, 不等次级组含量; K* B5 T2 m. Z2 q0 e9 L8 L* x
Ungrouped data, 不分组资料
+ W$ [) p3 Y8 Q/ c9 S, ?Uniform coordinate, 均匀坐标; ]5 p) M/ \0 ?( }
Uniform distribution, 均匀分布% w1 W7 P5 F7 E9 _3 z- m; r
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计$ W3 }# @0 j* ^. B" G F
Unit, 单元) w3 {* P1 f$ a) ], e) K
Unordered categories, 无序分类3 j9 m) g: Y& u/ _1 Y
Upper limit, 上限( x/ s8 I: t/ U+ q' a
Upward rank, 升秩. G5 C4 W! I+ D9 e7 q+ t# V3 g
Vague concept, 模糊概念
/ W7 Y3 q( g' ] f8 }0 wValidity, 有效性
, q5 o& X, a. N2 N. ~VARCOMP (Variance component estimation), 方差元素估计
" Q- N! a0 ^. Q xVariability, 变异性
4 \. g0 f0 s$ a$ P$ a7 o/ F3 oVariable, 变量/ _7 f) @" m$ N+ r6 q
Variance, 方差+ z2 R% d# a0 j L
Variation, 变异/ Z5 F$ t) S5 q! C$ X; ^
Varimax orthogonal rotation, 方差最大正交旋转
7 `2 i3 m4 l4 @Volume of distribution, 容积/ S: W1 H6 }7 s$ M; I% Z$ t" B
W test, W检验" e% `8 h+ X7 s) U
Weibull distribution, 威布尔分布
' C% s' G1 ~- @: nWeight, 权数, Z. ~% i% u7 R. q' H
Weighted Chi-square test, 加权卡方检验/Cochran检验
( I, N( @5 M: o8 EWeighted linear regression method, 加权直线回归
5 b! L5 C1 {* I$ `" U5 sWeighted mean, 加权平均数. [% X0 A, @$ ^0 L9 R# n
Weighted mean square, 加权平均方差- Y w& K/ v9 V+ \" L
Weighted sum of square, 加权平方和
6 w/ F/ L6 t& F" d. x6 |/ gWeighting coefficient, 权重系数( w" |, `1 {9 O
Weighting method, 加权法 # q$ U: H R& |, S1 t. N) ^
W-estimation, W估计量$ D# k0 x. R& ~$ n9 R# J0 ]- Z! M
W-estimation of location, 位置W估计量
! {; d, n5 y- x1 S. ?9 lWidth, 宽度; e( B4 q9 v: p, B
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
0 S: H1 j) r7 [1 c6 G2 J' fWild point, 野点/狂点
+ T: B- o% j ?6 b9 MWild value, 野值/狂值, ], g8 ]7 g q. L5 z
Winsorized mean, 缩尾均值$ [3 E6 c% H; `9 z
Withdraw, 失访
8 h0 z8 R# W5 P$ T% W( M/ IYouden's index, 尤登指数0 _% M4 u+ z3 a. k0 K
Z test, Z检验 I1 T* Y% ?1 [$ a% @ f5 J
Zero correlation, 零相关
2 n* {: m5 I3 JZ-transformation, Z变换 |
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