|
|
Absolute deviation, 绝对离差, Y X5 D! q' c) f x
Absolute number, 绝对数0 z& h: @; p" i9 M f" }4 Q
Absolute residuals, 绝对残差
, B6 v: K: u* Y/ e7 p3 u4 sAcceleration array, 加速度立体阵) x1 A. t* w- B& A, L5 w6 Z
Acceleration in an arbitrary direction, 任意方向上的加速度
7 s! o# b4 W% d8 w3 g% D7 HAcceleration normal, 法向加速度
1 b0 \: d+ r; x' p7 W1 cAcceleration space dimension, 加速度空间的维数& h4 `4 H( M4 v7 W0 o0 G
Acceleration tangential, 切向加速度
2 i: @1 Y9 p& g5 ^Acceleration vector, 加速度向量
7 K C) U- t; W$ [3 ]/ SAcceptable hypothesis, 可接受假设
: I; F0 m# J+ _2 F7 LAccumulation, 累积* Z4 Y) E4 d8 ? T; _! M( E# n5 L
Accuracy, 准确度
y0 S% @% @. Z( T) Q xActual frequency, 实际频数
u2 N" w) ~* D m: K4 RAdaptive estimator, 自适应估计量
: t$ X) G( ]7 F6 iAddition, 相加
8 S! ~( D @! B/ l& R2 y: @Addition theorem, 加法定理
6 L7 f4 `3 s. R6 sAdditivity, 可加性7 f- a" B2 u' _6 L: X# W$ u) w0 S& ?
Adjusted rate, 调整率
5 Q) l% R7 T& P- i2 O: B* aAdjusted value, 校正值, |8 O0 O" k# n* ]& p3 D* t6 K
Admissible error, 容许误差6 s. Y0 ?- R& j5 J
Aggregation, 聚集性* `- p) c/ b4 t* |- X$ }
Alternative hypothesis, 备择假设$ a- j/ X7 {5 ?3 W0 T
Among groups, 组间7 _1 X0 m; E4 k) r# O+ B0 n
Amounts, 总量
' @+ Q$ K! D8 R f* R; v) @7 wAnalysis of correlation, 相关分析8 H( O% k, r \, c0 A
Analysis of covariance, 协方差分析6 n$ R7 p ^8 I: [8 ]
Analysis of regression, 回归分析
- H7 X# H" m; I( OAnalysis of time series, 时间序列分析
# e: U0 Y# m& A5 z9 v7 n4 y: VAnalysis of variance, 方差分析8 c: ^, y; ?1 D" S# Z4 g
Angular transformation, 角转换3 y3 }: | @. `5 T
ANOVA （analysis of variance）, 方差分析+ K M6 S/ q* o
ANOVA Models, 方差分析模型
3 `+ ~; j8 j1 `: ], ?5 m. r4 X* pArcing, 弧/弧旋
! W& M% C( r r7 \5 {Arcsine transformation, 反正弦变换0 L; L/ y# s. U1 n& Y; r
Area under the curve, 曲线面积
+ o6 l3 R5 Y/ `AREG , 评估从一个时间点到下一个时间点回归相关时的误差 6 F& z. g @1 g0 G _
ARIMA, 季节和非季节性单变量模型的极大似然估计 ' d: s. }! @7 i: b; Z4 z
Arithmetic grid paper, 算术格纸
* E$ C" _; n" ^% y! ^Arithmetic mean, 算术平均数* x$ H6 Y& C ~/ C) Q
Arrhenius relation, 艾恩尼斯关系
/ n9 E4 K" E gAssessing fit, 拟合的评估* k6 ]# J2 V R4 B+ _
Associative laws, 结合律
$ c E) ^1 Y" O& c9 gAsymmetric distribution, 非对称分布
" E! E3 F" B5 r- `Asymptotic bias, 渐近偏倚% D% Z2 _$ ^7 d9 N0 m/ v O
Asymptotic efficiency, 渐近效率
0 M; p; S6 a& P. j1 t$ V1 c1 W. _Asymptotic variance, 渐近方差
. C6 y0 s9 B2 D8 v _Attributable risk, 归因危险度
4 r# |, T+ e V: u- i4 lAttribute data, 属性资料* u- N$ s0 I1 q% x' S& Z1 y' _ u
Attribution, 属性% P7 _8 r1 Z# \+ P$ k3 I$ }
Autocorrelation, 自相关0 ^$ t! _* e* J! l
Autocorrelation of residuals, 残差的自相关
$ ~& K/ a k2 h3 jAverage, 平均数
) l" F# d0 @- _! T. }Average confidence interval length, 平均置信区间长度+ b. B! H" F2 L, f$ d9 l
Average growth rate, 平均增长率
; V; p% b/ X$ | [4 C% s" J7 B5 xBar chart, 条形图$ f+ Y6 L) f; a. m
Bar graph, 条形图1 Z' M, U! z, T1 x; V
Base period, 基期
! Q' T0 A5 n5 R: wBayes' theorem , Bayes定理2 v8 @: c* e g, Z. E& ?. u: z" ~
Bell-shaped curve, 钟形曲线
0 f' D3 s5 E- [; fBernoulli distribution, 伯努力分布+ w1 a$ K8 H1 X: z: I+ l4 y
Best-trim estimator, 最好切尾估计量
8 [; G: q# z: c/ J2 T( M/ CBias, 偏性
0 f; C# b' s% V- g# q0 G6 _Binary logistic regression, 二元逻辑斯蒂回归
/ a$ w+ x9 T- a. b7 kBinomial distribution, 二项分布' n/ S1 r$ Y# _+ |! C& c; u
Bisquare, 双平方
4 ]" V9 S3 L5 d6 |' ~+ D5 cBivariate Correlate, 二变量相关
& X2 j! t0 r8 d/ w- W3 ~Bivariate normal distribution, 双变量正态分布
0 d2 B: B7 t- j/ L$ \Bivariate normal population, 双变量正态总体0 C' J! P u: {. ~. p
Biweight interval, 双权区间
) {7 Z- | Y) o1 s% i7 c: ?Biweight M-estimator, 双权M估计量
# e F5 j" i; L0 F4 v1 Z) D9 ABlock, 区组/配伍组
% @: j# ?% e! B( j; ZBMDP(Biomedical computer programs), BMDP统计软件包' L6 {8 O A, P6 D5 m& S i
Boxplots, 箱线图/箱尾图. a$ m) o9 M* C# T
Breakdown bound, 崩溃界/崩溃点; ?9 k7 n; d8 f
Canonical correlation, 典型相关; n6 A* ?" p# Y$ G$ _! K8 Y7 v/ T. [
Caption, 纵标目
+ d2 R1 N9 `! y4 k1 N, m0 `7 n/ h1 iCase-control study, 病例对照研究
" E6 [! v1 u5 D7 R# s! \( i; x! A7 \Categorical variable, 分类变量
7 a! p3 S/ |2 N$ @# A" M3 a8 BCatenary, 悬链线7 A5 l- Y7 `* o
Cauchy distribution, 柯西分布; ]9 A E& M# `. M& e z
Cause-and-effect relationship, 因果关系0 \) N, M5 B2 N, d" c' D* Y& l v
Cell, 单元
/ b: _" I8 L) n" VCensoring, 终检
* |5 F5 o Y! i; h4 y' `Center of symmetry, 对称中心
- l. }3 u: A+ b* D* H; Y, rCentering and scaling, 中心化和定标
: f2 T. T- p. B U* |" K3 u5 BCentral tendency, 集中趋势
- ]2 Q7 @; X: j) L. @1 k& kCentral value, 中心值
5 [/ @; y; b3 f* j5 `CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
! x2 V$ N0 a: m# ^1 eChance, 机遇. z" B8 n8 \) S! A+ I0 ~) B
Chance error, 随机误差
" V0 y* Q6 g5 v" Q( I. G% ?1 MChance variable, 随机变量
! w% b* h" h( c1 ZCharacteristic equation, 特征方程
7 a* \9 D9 J& d0 @8 I# C/ ]Characteristic root, 特征根
/ n3 A: O' ]+ l- B) R4 qCharacteristic vector, 特征向量
) h. A8 _- Y+ B! |Chebshev criterion of fit, 拟合的切比雪夫准则6 w. R. ]7 P1 D
Chernoff faces, 切尔诺夫脸谱图. ?2 a& H* N5 [: ~( N
Chi-square test, 卡方检验/χ2检验1 N+ y: D& _/ ^3 B1 _/ i
Choleskey decomposition, 乔洛斯基分解7 n1 h( I" o( U' }& L* N( o
Circle chart, 圆图
5 a$ ^0 k+ B* T6 v4 {: DClass interval, 组距
' ?/ v5 y* K( xClass mid-value, 组中值" D3 H7 I& k- w- o' {
Class upper limit, 组上限' w( F& k# W8 B) H# @+ M$ `- \
Classified variable, 分类变量! K7 ]! @; n! I9 J( y1 H5 Y0 Z4 E2 {
Cluster analysis, 聚类分析+ t+ S6 [% l3 q
Cluster sampling, 整群抽样0 l* o# ? ` l j
Code, 代码
) t, f: ~% }4 d2 A* e2 aCoded data, 编码数据
2 A& ?& H7 m% ]Coding, 编码$ X) s; p- R2 Q" h2 J
Coefficient of contingency, 列联系数! x7 }, x9 G3 \( G& \- _( c
Coefficient of determination, 决定系数% @3 `; m% p9 e. a I+ X( S" }" V8 b
Coefficient of multiple correlation, 多重相关系数+ e# r3 M A" `
Coefficient of partial correlation, 偏相关系数
7 E$ T( b I! Q% a3 f' A, ACoefficient of production-moment correlation, 积差相关系数
9 R7 e; ~+ M$ H% i4 T" ACoefficient of rank correlation, 等级相关系数
) v; J2 X) H* R" i6 [Coefficient of regression, 回归系数' I2 B. x& E0 g% ?2 N
Coefficient of skewness, 偏度系数8 k/ U8 h' O, h8 o( h6 z9 m% S) ^
Coefficient of variation, 变异系数: q( B+ K2 o# T- j7 K
Cohort study, 队列研究
; |' ^( x8 i/ a3 CColumn, 列' E: F0 s4 M) c7 O2 H- {
Column effect, 列效应9 S) y* Y( }2 a' w2 ? a
Column factor, 列因素
+ z7 q+ W; x' e" f& FCombination pool, 合并
- g0 H& S9 }' hCombinative table, 组合表, K3 N2 J5 H8 S A; y: [1 T
Common factor, 共性因子
# M/ ?3 {: r' m i) d2 nCommon regression coefficient, 公共回归系数/ A1 X3 H1 W- C* n) i; [
Common value, 共同值
9 p1 Q0 G4 b! N' S. R- [Common variance, 公共方差
, q2 M: o2 k0 [Common variation, 公共变异0 _- b; [8 G2 J3 t0 x
Communality variance, 共性方差
6 W. P8 h6 Q* k6 |# Z8 fComparability, 可比性
( M; v3 I1 T" V# \Comparison of bathes, 批比较
( {5 l/ a. {. P* @' IComparison value, 比较值. m0 E+ X; d) Q4 O6 Q1 }
Compartment model, 分部模型
) |# C& v5 I; h) ^4 g8 hCompassion, 伸缩6 O( \+ |. j: I! r
Complement of an event, 补事件4 ]8 j, a# Y: q4 l6 Z5 A0 q5 N
Complete association, 完全正相关) s5 M/ `! I& ^: U6 [/ A& B
Complete dissociation, 完全不相关1 D' F' T* u- ~2 ~+ ]% E) r. F* h
Complete statistics, 完备统计量
3 ^( I$ ]! G# F( W; \: VCompletely randomized design, 完全随机化设计
' A2 m- w# B: wComposite event, 联合事件
; ^ m8 V0 H; JComposite events, 复合事件
6 l* N8 U6 c! t9 a0 H _Concavity, 凹性
) V0 s" z9 t G; d$ S: W: sConditional expectation, 条件期望, H: n$ e# d- w6 o% y
Conditional likelihood, 条件似然
: p% K; d; t2 k6 o8 @Conditional probability, 条件概率
! y' G- z1 A# yConditionally linear, 依条件线性
9 Z2 X3 ^* C- G, T3 Y9 d: a. w' MConfidence interval, 置信区间. T: r9 g8 j7 U% S
Confidence limit, 置信限7 q D8 _7 J9 y, N! e/ L# u
Confidence lower limit, 置信下限
5 J7 W+ ^" e- ?& k9 k: tConfidence upper limit, 置信上限
; \! t, Z/ \; w- S% {% e7 `+ q9 H4 q4 aConfirmatory Factor Analysis , 验证性因子分析
8 d; D; K4 {3 Y4 @/ n* hConfirmatory research, 证实性实验研究
H1 ` F l7 C4 nConfounding factor, 混杂因素
8 p1 V/ K3 H. T A2 zConjoint, 联合分析0 }( }: F" a" }4 f W
Consistency, 相合性
' F9 X: @+ Y+ G8 s* W) R* ]Consistency check, 一致性检验
# l' }0 X |. L% h& v5 X7 tConsistent asymptotically normal estimate, 相合渐近正态估计. J3 t D; \* Y& W/ Q H
Consistent estimate, 相合估计# r, I3 B, _" O) X# U
Constrained nonlinear regression, 受约束非线性回归
" u1 t3 u5 X. YConstraint, 约束4 K- F* N; `/ r5 N: G% h+ {
Contaminated distribution, 污染分布
- u- Y( v0 t: m1 j: T, @6 L/ RContaminated Gausssian, 污染高斯分布
|) {) ]& i3 P4 r: K- `- cContaminated normal distribution, 污染正态分布
v% q$ s! ?9 @Contamination, 污染7 n9 \0 ?+ P7 P9 b9 A
Contamination model, 污染模型4 b; G4 g5 o- r
Contingency table, 列联表5 o# k5 j. I$ R% c8 L' S( ^
Contour, 边界线
! F* X- F0 ^4 I1 fContribution rate, 贡献率
* Q' ?! M8 u0 R) J; m) ]/ `Control, 对照
8 h1 s! I; Z! _) A$ @2 S! J2 rControlled experiments, 对照实验
3 [1 U) i Z. i" s! [2 X8 DConventional depth, 常规深度
3 _7 K, w0 O& _! O0 B3 hConvolution, 卷积
2 j( f+ R& J: v+ V. M4 nCorrected factor, 校正因子
% \( g' r7 n; S1 o. gCorrected mean, 校正均值
5 ~. ^6 @, b2 ~1 E# OCorrection coefficient, 校正系数
9 C% ?; B0 b+ Y8 m* D; \Correctness, 正确性; S: N: {4 r8 _' x* W4 Z
Correlation coefficient, 相关系数; Z, o, G% k$ Z" ^9 i( F3 c
Correlation index, 相关指数
7 r4 B% O6 s1 ?% CCorrespondence, 对应5 M' O. ?9 {) i0 d8 E
Counting, 计数, s9 E# x- ]8 {9 k. Y7 @ q2 u
Counts, 计数/频数
& |% q$ F: H5 NCovariance, 协方差
+ `3 t8 A& \) `# r/ c8 bCovariant, 共变
: a# w* z: D4 G! lCox Regression, Cox回归1 w* l5 d: [, X: v6 |7 {
Criteria for fitting, 拟合准则& I* f* |* Y; `% i5 y4 s
Criteria of least squares, 最小二乘准则% [: { m& ~ y8 }4 D2 O: h
Critical ratio, 临界比0 g/ `6 Z" A7 w+ f
Critical region, 拒绝域1 V2 b8 z" Q. ~( o: h& w9 d
Critical value, 临界值
4 `+ {* \' u/ S% h$ h% k% ?$ QCross-over design, 交叉设计3 l% P" k: P3 y- G6 E, ]% l! {
Cross-section analysis, 横断面分析* m% Y; ~; Z0 `. [' ?5 ]
Cross-section survey, 横断面调查1 [$ U) j# Y* O( l. ?" o
Crosstabs , 交叉表 % y8 @, a* E6 L
Cross-tabulation table, 复合表- V( w9 V7 U3 k @6 ~3 {9 `
Cube root, 立方根
2 x. f- c9 G& L- U6 y$ L i* ? RCumulative distribution function, 分布函数
+ T( S9 B' \7 S4 lCumulative probability, 累计概率, F4 \ {8 a, L2 R* b
Curvature, 曲率/弯曲
! l5 y1 `& O3 ]4 O' ^Curvature, 曲率' ~# ~; d, b) Q6 I! D$ O; w
Curve fit , 曲线拟和 . A* M8 e, T0 x+ M
Curve fitting, 曲线拟合8 @# d' H8 ]+ P. a. F% T( i
Curvilinear regression, 曲线回归
/ ]* g- v0 L y% sCurvilinear relation, 曲线关系
! G* N5 ?4 I. X+ a+ ?- `Cut-and-try method, 尝试法; w( ]1 C K. j, P- h
Cycle, 周期
. w- O/ l2 @: j5 B p; T$ _2 zCyclist, 周期性
/ c. O: F0 ]9 Z' b7 ~" AD test, D检验
$ V; U3 d# G) e3 `% n: OData acquisition, 资料收集2 a% v; V8 [0 y$ e, G; u
Data bank, 数据库
, Z! U# i8 ^: e# LData capacity, 数据容量. X9 w; o3 V8 Y. b5 k& D E7 L
Data deficiencies, 数据缺乏) s" U1 N4 o* R; o# {6 n6 B& T
Data handling, 数据处理
: Z$ [6 R* k7 C: c. A' ?Data manipulation, 数据处理, u4 p5 a* }+ Z5 X$ ]
Data processing, 数据处理
6 ?0 `; G* v# i( ^; \% p2 Y) m1 A4 e$ ^Data reduction, 数据缩减
S1 h( @! p2 ]Data set, 数据集
$ C: e7 U* |5 a/ ^/ sData sources, 数据来源
- f( w/ d/ E7 q! ]8 Z4 x; a0 L* VData transformation, 数据变换5 S) a$ N+ A7 F) ]. y
Data validity, 数据有效性
+ D2 j& r+ W9 @ S8 d* eData-in, 数据输入
) Z1 |3 d# S$ e2 Q8 d4 VData-out, 数据输出, o- ^4 e7 x! V! ~3 Z
Dead time, 停滞期
$ {& Y$ Q$ u0 H9 zDegree of freedom, 自由度
" b# s. u! h. t+ c0 a+ l. [6 ~5 Y. Z$ \Degree of precision, 精密度
! i' L% L7 N; A- ]9 g, ADegree of reliability, 可靠性程度
+ [1 @# X5 V ^+ Z5 l( P/ I7 }+ hDegression, 递减
2 n3 E4 _) Z; I9 Z2 j+ N3 m: aDensity function, 密度函数
/ s9 h1 y" B& k L! @) xDensity of data points, 数据点的密度
. @3 [6 | t2 o0 d ^Dependent variable, 应变量/依变量/因变量7 j5 |1 c8 G, z! c
Dependent variable, 因变量
$ z8 R& _. E; ?Depth, 深度
- H: _. j4 w, i- B; K0 V0 c0 S1 t% tDerivative matrix, 导数矩阵
$ M: P' C3 a2 BDerivative-free methods, 无导数方法, X7 i, c/ @6 h" O
Design, 设计: J, R. z# }- f; \ N/ M" z
Determinacy, 确定性" S$ I e# ]' E
Determinant, 行列式2 ^1 @8 `: x0 Y7 C. ^0 |
Determinant, 决定因素
. O. ~4 X! b, i8 g4 VDeviation, 离差
5 h6 L) @# q) ~1 y3 i( j8 |Deviation from average, 离均差& B4 o2 n. ]. z3 Z. {
Diagnostic plot, 诊断图( _# R' ]9 \4 ^$ T; Y7 J8 W
Dichotomous variable, 二分变量6 ]5 H+ z2 v4 I: h4 I8 w9 M
Differential equation, 微分方程- B7 u% N M ~7 F9 c" \$ N
Direct standardization, 直接标准化法
& R* v& V/ S- t' U8 uDiscrete variable, 离散型变量! }! J c+ a; s- C; l# k
DISCRIMINANT, 判断
$ M, K) Y F; [1 oDiscriminant analysis, 判别分析
: O6 ` a7 Y! I/ l* J8 ODiscriminant coefficient, 判别系数4 \2 W9 C+ q+ v/ R: {0 F8 c6 Q
Discriminant function, 判别值
1 f# i- U/ P" ^. u) ]Dispersion, 散布/分散度2 D$ O9 L1 c8 M
Disproportional, 不成比例的
. B3 x7 i% K5 J+ f- D! A' [" BDisproportionate sub-class numbers, 不成比例次级组含量% E& |+ n( e, `- c' p. C. _4 ?% p3 M
Distribution free, 分布无关性/免分布$ o$ m2 m( O' e- ^
Distribution shape, 分布形状
8 }' Z% }, \' l+ r- B) I- iDistribution-free method, 任意分布法$ [' H# f& s. T' |. _# {
Distributive laws, 分配律) ~6 U7 F8 T/ G: f1 o
Disturbance, 随机扰动项5 D% i5 h, g5 W7 _# {% y/ z8 q
Dose response curve, 剂量反应曲线
3 Z, Z& R9 x& q b+ [3 ZDouble blind method, 双盲法
4 Y$ L# x7 k8 n+ E8 ^' jDouble blind trial, 双盲试验5 w( x4 A8 w3 |. g
Double exponential distribution, 双指数分布) `- m% ^8 G8 ?. z+ I2 q7 |
Double logarithmic, 双对数
* N$ ^0 F8 B" ^2 }) DDownward rank, 降秩
& i5 g. m; y, j7 L7 pDual-space plot, 对偶空间图
4 E+ M4 b1 f1 F5 j7 H0 _, IDUD, 无导数方法
, \8 X% C) t$ l# S- W5 I1 ^$ _, aDuncan's new multiple range method, 新复极差法/Duncan新法
# k2 z, S* e4 Q& w0 x, Z/ b* PEffect, 实验效应7 d/ v1 k7 \5 c5 K/ _% b+ l1 r
Eigenvalue, 特征值
' `0 X% Q: x9 c, x% {Eigenvector, 特征向量0 k8 D O( O) C: S, P) V. g
Ellipse, 椭圆
: v* [ ^2 H+ h2 YEmpirical distribution, 经验分布
3 a; X; u V0 e. r4 q, F X# GEmpirical probability, 经验概率单位+ r8 g! l8 b* H: D6 w
Enumeration data, 计数资料1 \& J- w' V) d ~2 W
Equal sun-class number, 相等次级组含量
0 y, P/ U+ {" H- @0 \Equally likely, 等可能
* z4 M$ Q! n8 n2 _. j9 }, \( `Equivariance, 同变性( L0 K/ D$ n7 N) ]' t
Error, 误差/错误
% P% U' K8 e: [1 jError of estimate, 估计误差5 J$ ?" f7 c2 u6 Y* c! u) ^' o
Error type I, 第一类错误
! z5 S: m0 H9 [* l" r$ j; ]Error type II, 第二类错误
0 s* @8 F$ n. C& w" P0 _- wEstimand, 被估量, G) A* }( Q" Y6 p# @/ t7 C
Estimated error mean squares, 估计误差均方% Z! L; k# V# G& c4 U+ Y, E, M
Estimated error sum of squares, 估计误差平方和4 O4 H( L3 q% c: Q1 a9 I
Euclidean distance, 欧式距离6 @+ ]7 L/ P7 u% }
Event, 事件8 ~8 F$ ^$ m' h, G! I( L$ |
Event, 事件
. X8 K. }8 y+ r' AExceptional data point, 异常数据点
{2 J7 h9 b: a" U% S% IExpectation plane, 期望平面
+ n& F8 k; ]; a2 dExpectation surface, 期望曲面
* u' Y" Y1 g( jExpected values, 期望值! N$ o6 I; |1 x
Experiment, 实验+ l z% q8 v: U4 B2 k+ j' c
Experimental sampling, 试验抽样
3 G0 u7 E) H4 Y" i$ {: j' n" G0 Y( J0 q0 SExperimental unit, 试验单位
0 g$ l; U% P# b1 j: ?Explanatory variable, 说明变量
0 G, j/ m+ E Y0 FExploratory data analysis, 探索性数据分析& M# {5 D, e$ H5 l2 d f
Explore Summarize, 探索-摘要
9 P O5 z" o; `6 _4 DExponential curve, 指数曲线
# B" @: n. P) B* B, F/ a: ?! qExponential growth, 指数式增长4 c( n9 C$ o. f) e" M( i& L; V8 \
EXSMOOTH, 指数平滑方法 & K- Y4 N; t, a* B8 @( Q; d. X* |
Extended fit, 扩充拟合: m& ]0 k# m: B+ Y9 H
Extra parameter, 附加参数
Y4 C8 B% A1 k t! l4 N8 sExtrapolation, 外推法
) e" R- Q$ U+ u+ JExtreme observation, 末端观测值
" e$ }3 M) ~ eExtremes, 极端值/极值, I; M- a, U* _+ k7 K( n+ I
F distribution, F分布 a. E5 o4 _( S
F test, F检验
: X! o- ~1 {/ f! p- W4 A. rFactor, 因素/因子5 V4 `/ J0 R6 v- L6 l- @5 ]
Factor analysis, 因子分析
/ x8 I4 k9 G0 k3 BFactor Analysis, 因子分析
$ b( q# V% w6 i9 wFactor score, 因子得分 0 g+ O0 M0 J. c
Factorial, 阶乘
7 N/ G+ W" c6 s0 q7 R- YFactorial design, 析因试验设计& Z/ E _( Z, G" x
False negative, 假阴性6 L. @$ K$ c! G7 b8 y
False negative error, 假阴性错误
* I2 s% W$ Z- ^2 iFamily of distributions, 分布族! j5 `3 K6 B2 g5 ?
Family of estimators, 估计量族) O# }7 [3 |8 U
Fanning, 扇面2 y! Q5 w) Y) j4 Y
Fatality rate, 病死率
7 m& Y5 {8 k! t5 t2 N1 g" OField investigation, 现场调查
9 }; Y7 e4 a0 n* dField survey, 现场调查
$ x% o; ~1 m( xFinite population, 有限总体8 C" s$ m$ J [6 ]* i( G
Finite-sample, 有限样本8 C8 ~$ I3 h* X2 a9 B/ F: W
First derivative, 一阶导数
8 w0 K, ^6 n" ]) MFirst principal component, 第一主成分 P+ C3 J; W8 k# j7 T$ k+ I5 E
First quartile, 第一四分位数1 j# H+ o" i! X9 a/ j
Fisher information, 费雪信息量# |* ?8 ?. l& N
Fitted value, 拟合值
0 S/ C# ^$ h$ M O- wFitting a curve, 曲线拟合
1 C9 [$ e: W. B) ^+ E6 F' lFixed base, 定基
6 P9 f: ], ^* c$ V5 YFluctuation, 随机起伏6 ?( t5 R" H- M% j1 V; A
Forecast, 预测
# W: o: g- V' t4 j* l( BFour fold table, 四格表
8 s) E' {) k+ eFourth, 四分点! p9 U H2 P& m8 K' B. R: X
Fraction blow, 左侧比率
$ \3 e' P$ j- i% S* W- z7 P4 l! YFractional error, 相对误差1 b5 ^: m( O- N4 O+ ]3 Q% D
Frequency, 频率
: O# O) _( u) jFrequency polygon, 频数多边图
* R7 U1 x, s- W* iFrontier point, 界限点
: c* N# B2 {' Z4 cFunction relationship, 泛函关系
# J) e6 T. {5 c! S3 VGamma distribution, 伽玛分布8 c; S4 Q4 N* n+ @
Gauss increment, 高斯增量
# z+ q& N2 V, z% g9 I, H) A) BGaussian distribution, 高斯分布/正态分布4 ?- V) `% c/ T1 d+ @/ f; a. Y
Gauss-Newton increment, 高斯-牛顿增量6 ~1 A4 j% a% H+ n+ n4 l
General census, 全面普查, n% U% ]& w4 X. U$ n) M4 Z
GENLOG (Generalized liner models), 广义线性模型 V9 m0 Q% _( k' e& D# h
Geometric mean, 几何平均数1 |/ X9 W# R6 G3 l
Gini's mean difference, 基尼均差
Z. N/ G7 Y: R7 g5 k2 C6 b9 \9 CGLM (General liner models), 一般线性模型
9 l: s \' r& H6 `- mGoodness of fit, 拟和优度/配合度
) |. i5 p6 g( O9 JGradient of determinant, 行列式的梯度5 q! O Y; |3 `- c% q: F
Graeco-Latin square, 希腊拉丁方. N+ i1 H) H9 h0 w
Grand mean, 总均值) a. _9 f8 O6 K
Gross errors, 重大错误' B& J: f' a! s, f
Gross-error sensitivity, 大错敏感度
/ }# y9 Q- |4 z8 }2 y9 A1 dGroup averages, 分组平均& W V4 t4 Z8 ]. c' H
Grouped data, 分组资料
5 T/ g" w2 _ IGuessed mean, 假定平均数
$ `7 O+ }& q% Y0 w- J% ?, J; qHalf-life, 半衰期
) `0 \$ E% G- U1 ] @- GHampel M-estimators, 汉佩尔M估计量 s: A \7 s m9 m9 Z: i
Happenstance, 偶然事件
+ P; m1 u8 Y6 }: OHarmonic mean, 调和均数0 _4 p3 h" |) _2 ]3 J( m
Hazard function, 风险均数% v& E, f1 `' S, d7 `7 ]/ M3 f7 P
Hazard rate, 风险率! p! ]( Z+ D* W8 h. H5 {) A
Heading, 标目 4 z/ ^, `( M2 e" P& [, `; W
Heavy-tailed distribution, 重尾分布
, O( S7 X$ x5 y9 PHessian array, 海森立体阵" Y1 K: r; Z! w% b0 K4 c
Heterogeneity, 不同质0 b8 s# F1 h. x* q1 K6 w" M9 [
Heterogeneity of variance, 方差不齐 2 ?6 p& i* m6 t, s! E8 O
Hierarchical classification, 组内分组
/ w0 `1 B/ g4 {0 B5 K" A1 MHierarchical clustering method, 系统聚类法
1 }' X0 ?9 k$ d& D& V8 ?# S4 m. ZHigh-leverage point, 高杠杆率点7 e1 _2 u- q4 A3 h8 J0 x
HILOGLINEAR, 多维列联表的层次对数线性模型3 l; N( N- @0 e B; R* E' z
Hinge, 折叶点
% ?( G, y4 d/ d8 D+ p0 LHistogram, 直方图
9 p9 G! m* S" T" uHistorical cohort study, 历史性队列研究
9 f" `! x9 X, `* wHoles, 空洞
! [! K& l7 K: F- c) c$ ^( u; OHOMALS, 多重响应分析6 I, U' R. ]( F: T! r% m
Homogeneity of variance, 方差齐性; V. Y. J6 a0 R7 i
Homogeneity test, 齐性检验
; ^7 c7 j0 X; {" {Huber M-estimators, 休伯M估计量+ C( q, T3 T) X4 Q+ v8 o" R. p+ E0 J
Hyperbola, 双曲线" h, p/ J2 p0 `# Y
Hypothesis testing, 假设检验
+ ^7 T# `6 B9 Z8 f8 v. ~2 T+ WHypothetical universe, 假设总体
# s+ p6 B7 c7 N$ w2 }8 T& NImpossible event, 不可能事件! A3 [) |" X1 a
Independence, 独立性2 v) g$ V' ~& P* v/ \7 [" @
Independent variable, 自变量
! ?6 h" e4 P0 A, j" |Index, 指标/指数
/ Z$ p& B0 n, RIndirect standardization, 间接标准化法1 m1 X: P) x4 e% m
Individual, 个体6 c3 A2 ~/ N' D/ C6 `$ ^
Inference band, 推断带3 _$ u$ b8 B5 j2 e, h
Infinite population, 无限总体
, `7 e& ?- p: `/ YInfinitely great, 无穷大
! F: ]9 c! C) r9 \- R4 vInfinitely small, 无穷小
. {$ e8 J8 x5 F' |Influence curve, 影响曲线
' Q8 y; q, A- h- m2 ?Information capacity, 信息容量! Z- u+ u. {& x" A
Initial condition, 初始条件* y- U2 d5 ]3 q5 l+ h5 S7 j
Initial estimate, 初始估计值
8 V* P. D1 ?# Z: ^2 `0 hInitial level, 最初水平
' [. Y7 K' h" D9 mInteraction, 交互作用7 s( M, ^+ g% S% \) M
Interaction terms, 交互作用项
" J# Z( s8 Z5 W$ ?Intercept, 截距
, P. J$ s+ C5 L+ yInterpolation, 内插法7 C6 S" |5 }# i6 D$ \( L* f c' o! q
Interquartile range, 四分位距1 g- f. O; k$ j
Interval estimation, 区间估计6 m( x: |3 M6 I% i
Intervals of equal probability, 等概率区间# s6 l0 `+ v y9 T; F
Intrinsic curvature, 固有曲率
" i. @, K7 @1 T2 ]Invariance, 不变性
) C, R2 d6 i ?Inverse matrix, 逆矩阵
8 Y. }6 G( O" j+ O% d! P# K2 hInverse probability, 逆概率+ |" F: H" h. w! `2 W: D) B2 j
Inverse sine transformation, 反正弦变换
: Y! J" G& \& w4 KIteration, 迭代 " R% v, A( w# _2 q: p- V
Jacobian determinant, 雅可比行列式+ s, Q! F+ [% y3 X/ b2 X4 Q% P4 D
Joint distribution function, 分布函数
* {: @6 m q0 U K( G# Z/ B; [Joint probability, 联合概率
( M5 w" l0 Q8 t) X6 A/ r! N) lJoint probability distribution, 联合概率分布: H% W, S& i" v B C& p5 H
K means method, 逐步聚类法
z8 {1 s$ e2 D: N+ w0 |8 `Kaplan-Meier, 评估事件的时间长度 ! W. Z; o: e! A! q8 E- s" H. A5 h# V2 }
Kaplan-Merier chart, Kaplan-Merier图
, h* E- r; s( `! V/ t' Z0 N A% M* fKendall's rank correlation, Kendall等级相关0 ]* b7 D8 P9 }, n9 U) Z
Kinetic, 动力学
" |$ ?7 T$ i) [( RKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
7 {* v2 l) J& ]Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验' d& B) l6 i# o& Y; q) {$ ]
Kurtosis, 峰度
% a Y1 _: _; c! d/ _Lack of fit, 失拟
7 l5 K1 \6 b$ ~1 Q( K- ILadder of powers, 幂阶梯
6 @6 j, \4 Y7 U( c2 F4 eLag, 滞后' i$ v0 y# x+ h1 z- S
Large sample, 大样本: f. z' j2 o' D" e+ E! U
Large sample test, 大样本检验
9 Y9 [4 u, r' ^" Y; \& mLatin square, 拉丁方
7 d- w4 J" Z+ f- ~6 [# XLatin square design, 拉丁方设计
, L3 p# N' g9 PLeakage, 泄漏
* k: o* z z( q0 h: q- O; y6 I* ULeast favorable configuration, 最不利构形1 y7 ~" C8 {; e! o
Least favorable distribution, 最不利分布3 p8 s& D# V( t) ?% R% c+ Q2 V8 o5 J
Least significant difference, 最小显著差法
4 l ~$ c) X3 u" U6 v, U& f* NLeast square method, 最小二乘法
" {9 o* P- |$ F8 O; {, R v HLeast-absolute-residuals estimates, 最小绝对残差估计
( [9 i! b& O1 o3 A ]Least-absolute-residuals fit, 最小绝对残差拟合1 d6 v" W, d; k ^* _
Least-absolute-residuals line, 最小绝对残差线
6 \& L) m9 `5 D, E& O# NLegend, 图例
7 ^! z! d$ ~0 ?! Q( t; ^L-estimator, L估计量9 F* {. k: P$ \- a7 m9 F/ r. |9 M
L-estimator of location, 位置L估计量
$ |% Z+ j' D2 ~- K' ]$ ^L-estimator of scale, 尺度L估计量
% T( }5 j3 p/ k5 s8 N: f0 ]* G, }Level, 水平& m5 T, f" `4 B+ ]8 B# I5 z
Life expectance, 预期期望寿命
. t. A" J F$ v7 p9 S! ^6 {7 ]Life table, 寿命表8 r. V) Y( t7 P% N0 f
Life table method, 生命表法
+ F- w1 t# W/ V" kLight-tailed distribution, 轻尾分布" I) B# Q& r) H) _9 ]/ O) X0 h& o
Likelihood function, 似然函数
& G4 d- N: _- v& ULikelihood ratio, 似然比
5 b/ j3 M0 S- d/ v% [7 Fline graph, 线图
3 R" g( q) |( _ h* G/ ] ELinear correlation, 直线相关
/ F( \2 ~! U3 @- hLinear equation, 线性方程' r/ f# v6 x( N9 J9 @3 e: x
Linear programming, 线性规划1 _9 H; D7 R5 J4 M3 q% w
Linear regression, 直线回归
d5 ]5 G. P, L" N9 E+ _1 @Linear Regression, 线性回归0 O, A5 f: ~8 u: f4 ]
Linear trend, 线性趋势
# F0 y7 a: }" c- s; W' e* kLoading, 载荷
' k2 H) [9 ?" f) j- pLocation and scale equivariance, 位置尺度同变性
u# j5 n J+ HLocation equivariance, 位置同变性; B3 K$ A1 z/ G8 c6 a9 v: R
Location invariance, 位置不变性& s _- h' g' r* c0 x# n4 j
Location scale family, 位置尺度族- {# c5 i' X6 \! h& K
Log rank test, 时序检验 5 ]4 Q, A- b) K+ [/ s% b! ^5 @
Logarithmic curve, 对数曲线9 q: C/ Q+ k& V) E6 y* `3 ]
Logarithmic normal distribution, 对数正态分布* u8 U5 k( ?" t7 x& M) R. i% Q( @
Logarithmic scale, 对数尺度4 n, y2 _0 C. m# Z8 y! {
Logarithmic transformation, 对数变换7 f/ M. S$ H1 o- K
Logic check, 逻辑检查
4 l' }7 r) ^. TLogistic distribution, 逻辑斯特分布
0 C) W* V/ R! q- N9 t( fLogit transformation, Logit转换
" Q t% u* i. p7 v$ T5 U6 ]LOGLINEAR, 多维列联表通用模型
% j3 u. a; I9 e& R4 V$ yLognormal distribution, 对数正态分布
' Y6 n0 O1 ]" hLost function, 损失函数
+ x7 x/ e5 @* GLow correlation, 低度相关
' ^3 u1 j- M# i/ \! D" M! kLower limit, 下限
( q0 _! O$ T" X9 x, f4 MLowest-attained variance, 最小可达方差* ^/ m1 ^4 c0 k* `
LSD, 最小显著差法的简称2 s" a) u" _% \
Lurking variable, 潜在变量, q; ^+ R/ i x( m9 {3 y3 W
Main effect, 主效应. j! m& w. n6 T4 G; ?
Major heading, 主辞标目& k) f. J8 Q! U4 g
Marginal density function, 边缘密度函数5 W4 R! B5 L8 m- s+ [
Marginal probability, 边缘概率
+ p5 P2 O9 p3 H& ?. W8 qMarginal probability distribution, 边缘概率分布
) v7 k0 @; c' h, b% F) _7 E6 D* _Matched data, 配对资料* e. N+ E$ j3 S1 k" R
Matched distribution, 匹配过分布( e2 g2 t! G, U0 L! \2 r8 x# ~% E
Matching of distribution, 分布的匹配
2 N8 B: N2 A' V6 aMatching of transformation, 变换的匹配
1 k4 f }, I3 aMathematical expectation, 数学期望3 B9 T( V+ `# ]% t4 P7 E5 Q% T! q# e
Mathematical model, 数学模型
; I r; K$ |* x4 b- \1 XMaximum L-estimator, 极大极小L 估计量* O6 {: C) w* f1 F9 s" c
Maximum likelihood method, 最大似然法
+ z7 ~; ~; U9 cMean, 均数# P6 @5 |8 ~6 D( O
Mean squares between groups, 组间均方: q) n7 F" w& r4 h5 R
Mean squares within group, 组内均方
0 [: ?5 b ?. ~" K( w5 cMeans (Compare means), 均值-均值比较
- J8 D. {9 X$ ?. eMedian, 中位数/ Q- B- S7 J. Y" x6 x$ n' z
Median effective dose, 半数效量5 \1 t5 b- e( T u7 A8 [9 j4 L+ O* H
Median lethal dose, 半数致死量9 {! i* w2 Q( q9 H7 E- d
Median polish, 中位数平滑
4 z/ [+ P2 g u2 P' w7 qMedian test, 中位数检验9 d7 O9 y9 M+ b8 Q
Minimal sufficient statistic, 最小充分统计量
4 y$ I+ L; T; `Minimum distance estimation, 最小距离估计" ?; A8 z/ k2 x; P
Minimum effective dose, 最小有效量
6 _; e0 q+ V% d' M& }3 ^Minimum lethal dose, 最小致死量
* ?$ o5 p( V u7 ~Minimum variance estimator, 最小方差估计量
2 c7 d; G! l' m( v2 _' x9 JMINITAB, 统计软件包) a9 Y: H% M5 `7 i4 z# f4 Z
Minor heading, 宾词标目
y7 u/ O4 @/ n' B/ q2 w, |Missing data, 缺失值3 ~ P2 w# X& y; d
Model specification, 模型的确定
0 M$ F2 T( V" tModeling Statistics , 模型统计
4 O3 d9 ~* T- @5 ~Models for outliers, 离群值模型
% h8 n' T) S) W6 L7 R& oModifying the model, 模型的修正
+ c0 B, }6 Z1 b; c0 j G: M7 vModulus of continuity, 连续性模
& d9 z2 f2 }; O% e: H4 ]9 tMorbidity, 发病率 - }% y0 `! G: M B8 n$ z( D
Most favorable configuration, 最有利构形
6 N* j. h, r0 T; Z9 M& lMultidimensional Scaling (ASCAL), 多维尺度/多维标度8 k" ^5 r% r( h8 C. H
Multinomial Logistic Regression , 多项逻辑斯蒂回归
; v4 \2 b$ ~( w: @/ i9 A6 {Multiple comparison, 多重比较
8 E; I$ _. P5 ^, Y. nMultiple correlation , 复相关" ]' q, z5 M e1 G
Multiple covariance, 多元协方差
2 _0 U" n" b2 R1 V$ k2 D9 h* lMultiple linear regression, 多元线性回归
T0 h- r& Q: A& ^: T7 \Multiple response , 多重选项
% k8 ?4 ?) s0 u. LMultiple solutions, 多解
+ C, W7 G; i6 O w' eMultiplication theorem, 乘法定理
, a: t, w& H3 i0 N# O) r" p, f5 rMultiresponse, 多元响应& h! G r# i. Q' ? n
Multi-stage sampling, 多阶段抽样
, o Q5 Y: X8 f# x; YMultivariate T distribution, 多元T分布
+ K5 q7 @$ K. qMutual exclusive, 互不相容. |, v; u7 z6 Z
Mutual independence, 互相独立( G2 T' r; i* k, N' [5 I2 T
Natural boundary, 自然边界
" x8 H0 g3 b2 gNatural dead, 自然死亡
) z# C" F. h; L- CNatural zero, 自然零; Q, f7 ^% ?8 B- o! A! B" u
Negative correlation, 负相关. t6 H7 p' `4 K7 }/ T4 K4 b$ O, ^+ T
Negative linear correlation, 负线性相关 T+ t' t( D4 {& d
Negatively skewed, 负偏$ J V2 k% Q6 H4 {3 E& E
Newman-Keuls method, q检验( N' m2 D- b1 \2 _; g
NK method, q检验0 r( l8 B3 v$ P
No statistical significance, 无统计意义" R) }* g2 n Y1 y1 x0 h- e
Nominal variable, 名义变量) ~7 [- p. U" l" z6 u Y* O4 M5 o
Nonconstancy of variability, 变异的非定常性! w" r6 v$ I- t& {+ m
Nonlinear regression, 非线性相关
6 T* e* {1 d% [4 m& G0 E: X5 MNonparametric statistics, 非参数统计" {- W: w6 K, z- Z) Y7 ]4 z# A! P
Nonparametric test, 非参数检验
# d8 ] l& o; X5 h f+ pNonparametric tests, 非参数检验2 n* F# E; R8 i4 _8 l' n7 F2 s
Normal deviate, 正态离差- e' S9 ^2 g3 V3 o1 p
Normal distribution, 正态分布
2 H9 y. v' q" _Normal equation, 正规方程组
2 Y" x( ]# B6 wNormal ranges, 正常范围4 z; y4 K1 h9 Q$ k) I
Normal value, 正常值. e4 `# r5 J$ y8 I* {
Nuisance parameter, 多余参数/讨厌参数
1 m q- E; R+ z0 q" C0 ^3 UNull hypothesis, 无效假设
_: K. U+ K. CNumerical variable, 数值变量5 ^0 H8 E! e6 S+ l/ Y" D
Objective function, 目标函数
& X& f- x! {2 z* ~3 v) g zObservation unit, 观察单位5 J# o6 W9 ^/ S- ]
Observed value, 观察值
; Q3 @4 p+ E' Q; l& R: EOne sided test, 单侧检验
2 j. g$ Q& f6 B0 T' f: W! M, `0 MOne-way analysis of variance, 单因素方差分析
! y3 J& a/ x& i. Y* `7 ~0 I8 iOneway ANOVA , 单因素方差分析3 b8 G9 L% b/ C6 W
Open sequential trial, 开放型序贯设计
7 I0 o, E; d# [Optrim, 优切尾
7 W6 ~5 c( u! ]. Z1 E8 s' ~Optrim efficiency, 优切尾效率
6 q, T& A/ K+ o* V5 XOrder statistics, 顺序统计量4 ]* @8 w& ?( u& H. ^# ?* L
Ordered categories, 有序分类
M5 f n" C" }" N/ Z7 x/ nOrdinal logistic regression , 序数逻辑斯蒂回归
- V2 B6 l* z7 Q' V2 f; a4 NOrdinal variable, 有序变量
E/ T! A: ~( D* S" K+ WOrthogonal basis, 正交基# V2 _9 S' |! h& D1 l
Orthogonal design, 正交试验设计7 O9 X4 b( B, h% c' b& J5 J' O
Orthogonality conditions, 正交条件
3 `4 S3 J" u: x: C" M' R- MORTHOPLAN, 正交设计
! S1 s" O, t5 ~Outlier cutoffs, 离群值截断点: M. |' ]6 r1 m1 D, H7 S! F: B6 Q
Outliers, 极端值
# l$ i- p0 K# H3 cOVERALS , 多组变量的非线性正规相关 3 n2 U& B. B1 C/ o
Overshoot, 迭代过度0 }! N7 A8 U* H1 m# ^ b. [- b2 A
Paired design, 配对设计; h5 M. D& u% j* c# s3 J: H
Paired sample, 配对样本
/ { d) A7 I) P6 E# ]Pairwise slopes, 成对斜率
2 {6 ~3 E* ?( b7 a/ KParabola, 抛物线
7 h6 Q2 V% y! b/ g7 \Parallel tests, 平行试验
0 i1 C& C6 l+ H( f5 r8 F- EParameter, 参数
, i& P+ o W" P, `; RParametric statistics, 参数统计; F8 w6 Y: h9 C. e8 }; @" ]
Parametric test, 参数检验' u+ @, a+ Y+ c4 k
Partial correlation, 偏相关3 {" X5 I) M* T/ E+ W7 w9 k' n
Partial regression, 偏回归9 L5 m7 j' u( b2 p9 j* ]0 z
Partial sorting, 偏排序) E, ]* e' B m3 D" t, I
Partials residuals, 偏残差
) u; U1 L, N9 J& P: m2 [7 N6 EPattern, 模式
* ?# q; c, ^1 W0 [0 a' H" PPearson curves, 皮尔逊曲线# ], S9 _* ?- w, q0 G5 y, M
Peeling, 退层
/ S" |$ k2 q, ^$ U( q9 F, M# sPercent bar graph, 百分条形图0 k. t6 u. t1 _+ J! {
Percentage, 百分比! [0 D9 Z) b5 L
Percentile, 百分位数 ?' Y# w4 v$ }( v8 }
Percentile curves, 百分位曲线/ i+ l; i d0 ?% {/ o
Periodicity, 周期性
/ o! O; r" [5 `& Z! A% [Permutation, 排列7 u+ M' s. d4 g
P-estimator, P估计量5 \# U! `0 A/ B: f! G/ z ]
Pie graph, 饼图
" u5 K, k* \/ _# e. `, I3 j! j5 c# h% PPitman estimator, 皮特曼估计量% }& @5 B! H7 j$ R
Pivot, 枢轴量
- X9 E$ ]* S, ^9 T1 R! F! IPlanar, 平坦( Q8 |: x0 H! V1 a( O9 W3 z
Planar assumption, 平面的假设
8 H* h! {' ?! E( X }PLANCARDS, 生成试验的计划卡: l$ }; L. ?$ m$ A- D: A4 F
Point estimation, 点估计1 n# V" J) ~. k; z) A
Poisson distribution, 泊松分布& Y. y9 Q2 R( |4 Z5 J2 |& V
Polishing, 平滑
" k% E& q! y f( Z; t: \0 APolled standard deviation, 合并标准差/ z& q$ p5 S% t, X2 E
Polled variance, 合并方差; @1 C' B& u1 W& c
Polygon, 多边图9 J- T7 X* ^" K( C9 x& G
Polynomial, 多项式1 G+ a7 h/ C; C1 R& W: F
Polynomial curve, 多项式曲线
5 n5 N9 F W9 d {" D% }Population, 总体
. T0 s* Z/ S" vPopulation attributable risk, 人群归因危险度
9 E& I9 X' n$ k6 ~. O7 @Positive correlation, 正相关: x6 t4 z* [3 D- q+ Y
Positively skewed, 正偏3 ~$ e8 ~( `$ r+ c
Posterior distribution, 后验分布& h8 @7 t2 g7 l: n* ?% e
Power of a test, 检验效能4 H. S' X( y5 a* S7 U
Precision, 精密度6 C9 {8 p% U6 j3 R
Predicted value, 预测值2 ^. w# e3 n' Q/ F0 v( l2 [
Preliminary analysis, 预备性分析: m w7 j+ R; D( W4 D0 s7 ?) y/ _+ B
Principal component analysis, 主成分分析. J! |. e V x" z K( d
Prior distribution, 先验分布
3 `0 B: D& A8 D6 `' e) NPrior probability, 先验概率
& N* F7 n b8 i8 {$ g6 SProbabilistic model, 概率模型7 ?; l5 T, H! @/ L7 X# c
probability, 概率
! e* |' y! J9 } w( l1 N* HProbability density, 概率密度
. _: ]6 J& `# u* y( n5 d' e# vProduct moment, 乘积矩/协方差8 G" Y& W2 C S @. \, h9 u
Profile trace, 截面迹图
2 _' q6 k& r x- B9 K; m2 VProportion, 比/构成比
7 W o, e/ T$ I9 }! O$ CProportion allocation in stratified random sampling, 按比例分层随机抽样# T# V! B, V3 A% D3 _+ f8 G4 w( n
Proportionate, 成比例
/ l: X: N( x2 t# C+ h% XProportionate sub-class numbers, 成比例次级组含量
5 J9 G: p; p, `Prospective study, 前瞻性调查
* n6 Q- j$ n% f* fProximities, 亲近性 : f" k5 S H) v
Pseudo F test, 近似F检验
& O! s% L+ B$ P* c; DPseudo model, 近似模型
, K6 u4 K9 w" f5 q' P: ]3 K6 SPseudosigma, 伪标准差
, E0 u( h) ~. Z! nPurposive sampling, 有目的抽样# I/ P, ^" ~# E! d6 R1 V @4 \
QR decomposition, QR分解
) ~) y' ^$ v# I5 }$ ^( ~( a$ TQuadratic approximation, 二次近似
& A3 A* [* C: @# @ f: p- D- yQualitative classification, 属性分类
9 `" [/ r4 d3 z( {( F \2 U1 ?% XQualitative method, 定性方法
K* I6 r0 [$ M6 W5 hQuantile-quantile plot, 分位数-分位数图/Q-Q图: D7 x) T) r0 W
Quantitative analysis, 定量分析
$ {6 Z3 T: h M. T* F3 g: NQuartile, 四分位数
3 }# S+ C o* d/ \Quick Cluster, 快速聚类
6 _- v. E7 i1 d; H3 dRadix sort, 基数排序+ v6 [+ S. G% L
Random allocation, 随机化分组2 g+ M) ]6 \2 _1 e) V
Random blocks design, 随机区组设计( t! I: q3 j4 p1 g9 s
Random event, 随机事件
z* d' R6 J7 O$ [7 }$ s9 B" B; [Randomization, 随机化5 c, r3 j7 s, u( @
Range, 极差/全距; F# E/ n' h( X6 H h3 ~. y1 P+ M& P
Rank correlation, 等级相关
7 o9 \& @ w; _* W$ p( ^4 m$ E& n+ ARank sum test, 秩和检验
: x. X5 \( T. r% eRank test, 秩检验
8 N2 {$ d3 C9 _1 s8 U, |Ranked data, 等级资料$ H+ s/ F1 A: A; Y0 T; C8 T+ ^$ w9 G
Rate, 比率
! t! ^" o v$ i; _Ratio, 比例
* W* g3 `; \8 s8 A3 h3 ERaw data, 原始资料
- ]/ f+ s5 ?" x7 o; P9 Z% l7 KRaw residual, 原始残差, r) b$ W/ b! B# g8 D
Rayleigh's test, 雷氏检验
& {2 X5 ^5 R5 hRayleigh's Z, 雷氏Z值 # j0 W9 l# p4 G: M, `6 N4 P
Reciprocal, 倒数' g/ v& Z# K3 a- c1 [& s0 K
Reciprocal transformation, 倒数变换7 h5 Y2 J( L. t$ m! N! N+ R9 h: l0 {
Recording, 记录9 N: Z' w/ J* H
Redescending estimators, 回降估计量6 {) @) ]! H" s: N4 E: z/ c+ R
Reducing dimensions, 降维
: h7 e0 r0 H4 x3 b" FRe-expression, 重新表达8 u" T W4 Y- Z
Reference set, 标准组 u" U# I9 F( k0 e% d; Y, @
Region of acceptance, 接受域+ r+ J2 j4 S J P. H- o6 |
Regression coefficient, 回归系数& G6 j, y6 \* }+ H" z/ H
Regression sum of square, 回归平方和
4 V; y6 p6 P. g- qRejection point, 拒绝点
7 |$ O( E5 x8 ?. R: X& [Relative dispersion, 相对离散度+ x/ B) d' l2 d
Relative number, 相对数0 _* r$ H' {4 V% D6 v
Reliability, 可靠性
- l" X N: s. A+ V0 I/ o# K& O- xReparametrization, 重新设置参数* q9 Q6 \' O3 d4 h" z* `& ]
Replication, 重复! ]1 ~/ I' b ~) n
Report Summaries, 报告摘要
7 f" m; }6 o' E% j4 S; kResidual sum of square, 剩余平方和7 ]7 ] n1 p0 L2 r
Resistance, 耐抗性5 o! U+ F) u6 t! b
Resistant line, 耐抗线
/ x9 b9 `- h; M8 ? o3 C- aResistant technique, 耐抗技术
+ I- N+ ]: {, bR-estimator of location, 位置R估计量' I. ^/ H2 j7 ?0 H g
R-estimator of scale, 尺度R估计量7 b7 c( R' J" N ]
Retrospective study, 回顾性调查
3 |' H6 O+ x! x! GRidge trace, 岭迹
7 c& X7 B4 s* x2 A" K8 |( i, D6 fRidit analysis, Ridit分析
2 |' e5 `# {. ]5 q$ q, _8 GRotation, 旋转& |0 U& u; g& b
Rounding, 舍入
" c6 w$ C n5 {1 }& pRow, 行- |: B( B& W3 k' I
Row effects, 行效应( F4 E9 z# H: {/ d m7 P: m
Row factor, 行因素9 p3 u1 j; R/ Y: l3 P
RXC table, RXC表
0 P* L' z0 P! `5 I7 b! nSample, 样本
7 P6 s0 r u$ v2 S1 k5 iSample regression coefficient, 样本回归系数
V7 Y$ x6 ?- b% X( d$ p) jSample size, 样本量7 Z1 k K4 R: w4 a1 b" `. s
Sample standard deviation, 样本标准差
! R# l$ F6 f3 i2 BSampling error, 抽样误差
& G8 G) g( a4 j) JSAS(Statistical analysis system ), SAS统计软件包
! v" W2 M) k3 v8 u# M5 mScale, 尺度/量表
6 M7 L+ k* {/ [5 }: J# IScatter diagram, 散点图0 `& O y% j: [: K
Schematic plot, 示意图/简图! `& V+ E, y+ H8 U4 n6 R7 `( x* \
Score test, 计分检验
3 T- p( r$ k* @- S( A2 `1 @Screening, 筛检
+ a9 `$ D& b0 qSEASON, 季节分析 0 ^# \1 X) N- `: e+ {8 c
Second derivative, 二阶导数, c5 `6 a2 T5 Q Z" ?7 V
Second principal component, 第二主成分- r! H5 z- g; ?+ Q
SEM (Structural equation modeling), 结构化方程模型
& Q/ q" j$ E9 OSemi-logarithmic graph, 半对数图
& E* Y& \2 r/ P* ySemi-logarithmic paper, 半对数格纸
) [6 [- C2 k, E+ ]5 ~& v# ZSensitivity curve, 敏感度曲线
2 h K3 o h. e% n/ M% ?Sequential analysis, 贯序分析
, @( v! t8 Z5 O2 V$ C9 vSequential data set, 顺序数据集9 O2 ]* d1 n% C b, [, q$ c
Sequential design, 贯序设计6 d/ n' R4 J* Q) t
Sequential method, 贯序法. h, l4 j; s! P+ m( X8 Y6 C& b( J
Sequential test, 贯序检验法9 A% g" l" v, `, G
Serial tests, 系列试验
" n. g* \1 X1 a& [8 {5 kShort-cut method, 简捷法 d. o3 f: v; M. P1 U" S2 b% S
Sigmoid curve, S形曲线
( b& D# F) A8 X5 v3 j" O' mSign function, 正负号函数
7 z5 s5 X" r6 {; I" U$ X1 b; PSign test, 符号检验& U- {. q8 J! M5 K- H8 B# y
Signed rank, 符号秩% u' ^. W$ j E7 I( n) M! d& K
Significance test, 显著性检验
9 g4 ?' G( H r mSignificant figure, 有效数字1 Y% V6 ^1 T3 ^; }
Simple cluster sampling, 简单整群抽样' c8 ?6 g0 o/ ~( t1 m5 g0 n
Simple correlation, 简单相关8 G) I/ w* P7 o
Simple random sampling, 简单随机抽样+ T3 x6 J6 T5 i
Simple regression, 简单回归
& e7 M5 j! _6 j, ]5 dsimple table, 简单表2 N' Z+ n9 L) S9 |0 h! A
Sine estimator, 正弦估计量! p1 r8 ?& T, C0 r3 q C
Single-valued estimate, 单值估计4 r3 i2 \+ @$ j* t2 l
Singular matrix, 奇异矩阵3 `8 J$ l: n i" y
Skewed distribution, 偏斜分布
* y; ?$ k! | aSkewness, 偏度
% g0 p: v( ?. B6 F- V% TSlash distribution, 斜线分布: V8 H U& f) Q$ ^( E' L! u: S8 {. |
Slope, 斜率
* e/ y' h5 @) O3 [& L8 n" x( O7 }Smirnov test, 斯米尔诺夫检验
' Q2 {, |1 N; N7 c4 W* z, p/ |8 zSource of variation, 变异来源
% r; L1 O; m; F- n* K1 ?Spearman rank correlation, 斯皮尔曼等级相关
' j/ t' N/ T' b! K! qSpecific factor, 特殊因子# E! t6 c; r: X5 d( ^8 g& ~, H# N( m
Specific factor variance, 特殊因子方差
( w" w9 t- h* U7 x/ Q0 P. R* _# {, TSpectra , 频谱( z! a# H4 l4 J
Spherical distribution, 球型正态分布
% |) ?9 z4 G, p r( ] kSpread, 展布; `8 `7 }) j" {, o
SPSS(Statistical package for the social science), SPSS统计软件包. a+ W. ?% k- ?& f5 \
Spurious correlation, 假性相关
4 V2 [( ?' [- M$ n$ YSquare root transformation, 平方根变换9 H6 x; n& [# x' o- c5 w
Stabilizing variance, 稳定方差- T x K. h5 ~0 H+ Q' X
Standard deviation, 标准差% D7 p# _' \5 L& H. D1 @% o9 H6 y
Standard error, 标准误+ B, T) [/ r. w \) f. N
Standard error of difference, 差别的标准误( f& ^7 @0 C7 }9 U
Standard error of estimate, 标准估计误差
4 Y: q$ m) Z4 t: fStandard error of rate, 率的标准误
r$ Z; R. o0 ^+ x s1 q% q+ g2 oStandard normal distribution, 标准正态分布
: i9 l8 B! _, O4 p$ R9 r8 v" b; AStandardization, 标准化: ?% Z0 I, I- I( \* K8 Q/ N$ S S
Starting value, 起始值
, L( C% Q7 Z2 y6 qStatistic, 统计量! @- Z( H8 j5 S- M: z- O9 Q. }
Statistical control, 统计控制" Z: r3 N; r2 c8 G
Statistical graph, 统计图6 X: }: z5 D0 b e' b8 l6 w- C: ^
Statistical inference, 统计推断
9 p" j5 g) a/ z( O" H# kStatistical table, 统计表
' q9 p# G3 }; E2 l5 ZSteepest descent, 最速下降法' v- S: T6 i4 r# @ X) p
Stem and leaf display, 茎叶图2 L g) n" z7 ^: D8 E6 x* W
Step factor, 步长因子# O, L/ {" |$ ^2 t* A( k3 k% E1 o9 g
Stepwise regression, 逐步回归3 X9 g7 R5 c- t. B1 E5 K$ [' {
Storage, 存
! D+ Q5 x6 a9 PStrata, 层（复数）
- ?0 N$ k% P) r8 N8 p f+ A ?4 bStratified sampling, 分层抽样% y/ J) a( y; }' F, E
Stratified sampling, 分层抽样
# z8 n5 m: j+ u" w! mStrength, 强度( R' @8 t( u0 Q" d# P# n9 U
Stringency, 严密性
# c1 R9 A% j& O% Z) g) A8 a* NStructural relationship, 结构关系7 _* |' P7 J' z3 W& J
Studentized residual, 学生化残差/t化残差+ j K% n0 O$ H
Sub-class numbers, 次级组含量
4 S+ \7 U9 n7 H1 X& z l) wSubdividing, 分割! n) m/ y; D+ g4 i
Sufficient statistic, 充分统计量8 R9 V5 Q5 j6 n& M( ^
Sum of products, 积和, t6 ?; ^3 x; G! u" V( a* b
Sum of squares, 离差平方和; N$ t* F6 m* d1 ]' a
Sum of squares about regression, 回归平方和
$ f! X9 B3 O+ Q; M' b9 X- i& h. FSum of squares between groups, 组间平方和: R8 A3 O% B2 ~) a
Sum of squares of partial regression, 偏回归平方和, x) k6 u4 K9 m$ v
Sure event, 必然事件
) d$ g/ ]1 ~9 j! ~( ]& }5 Q- LSurvey, 调查
/ g; R% T/ J$ g' X6 P c f+ q0 \Survival, 生存分析
% O0 J, U: U' m: S+ O) ?Survival rate, 生存率
* z: g* \% `4 C8 e( s; FSuspended root gram, 悬吊根图
; ]; e* n8 I! c$ Q9 S, ~Symmetry, 对称
: P) y1 c$ k% A. RSystematic error, 系统误差
8 `( o6 U; @0 U2 x* y3 o& [/ lSystematic sampling, 系统抽样
3 \$ y, W% r$ v$ L) ZTags, 标签+ t2 u& E* n* o' d+ U
Tail area, 尾部面积4 j# I( b4 b- W- N( Y: D# l
Tail length, 尾长. K: P) \8 {1 x2 Q# w) p5 p
Tail weight, 尾重; m) n7 n5 ~: m6 p
Tangent line, 切线
8 u5 G2 b) }% Z) _* q6 I1 fTarget distribution, 目标分布
! T, t( d( N0 \' N( e# P5 t4 TTaylor series, 泰勒级数2 j1 \+ c3 |: ~/ {7 e
Tendency of dispersion, 离散趋势! g& _( N I% J/ R' l) R
Testing of hypotheses, 假设检验
& U, K# [) G6 @- C* BTheoretical frequency, 理论频数
4 _5 k: ?* p* j% a: y/ nTime series, 时间序列
. x# l) M2 e' D, y4 w4 ETolerance interval, 容忍区间
$ i" c! K$ X' h' q6 s& vTolerance lower limit, 容忍下限( Y2 ?! }# d9 {9 F
Tolerance upper limit, 容忍上限
/ a5 j/ \% h5 Q. r7 S6 l3 @3 oTorsion, 扰率
1 m* f7 J1 ^2 H; ]' LTotal sum of square, 总平方和
0 l' h9 Q5 N7 JTotal variation, 总变异( @6 k9 B8 C' \
Transformation, 转换
+ j$ Y+ r! P: a: tTreatment, 处理
; D, L2 b( N" l4 c+ E; ?9 f$ UTrend, 趋势
6 ^* b* m' H5 Q! rTrend of percentage, 百分比趋势. D9 V+ Y3 \0 A9 C2 @9 i
Trial, 试验8 \: F' M* I' A/ z% x- _3 u
Trial and error method, 试错法
4 }( n: S' _, F) W: y- XTuning constant, 细调常数
9 J* v! \" S) D/ LTwo sided test, 双向检验1 Z8 I! c4 ^" I6 h- W1 f
Two-stage least squares, 二阶最小平方+ X' \+ t2 [* c: X6 [1 |4 o6 h
Two-stage sampling, 二阶段抽样
, m, A+ r( P8 ^4 I5 |( TTwo-tailed test, 双侧检验1 _0 n ?( I" [
Two-way analysis of variance, 双因素方差分析1 s( q- H# p+ O
Two-way table, 双向表. L5 P4 w w% F
Type I error, 一类错误/α错误9 Z' ^% x ?2 L4 J4 N- \' I8 Z
Type II error, 二类错误/β错误- e5 |) T- z0 e
UMVU, 方差一致最小无偏估计简称3 p$ t: |. l( k7 c9 }' }1 Y @
Unbiased estimate, 无偏估计
/ N1 F) I, N8 v& u+ E' KUnconstrained nonlinear regression , 无约束非线性回归
+ ?- W4 e$ O2 yUnequal subclass number, 不等次级组含量. K- S1 C' ^. t! t, c& n! [
Ungrouped data, 不分组资料
% W2 [ o5 `. a8 e9 _Uniform coordinate, 均匀坐标
% u9 l" R. j8 }4 t$ nUniform distribution, 均匀分布) i0 E# I% i3 L: b
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计) w, P8 Y% o$ g! c; d. c; @. }- N# S
Unit, 单元+ j5 K* G* W' i5 t1 M
Unordered categories, 无序分类
: s& n) P& r( }Upper limit, 上限
7 }) \+ V8 }$ o: Y. e- u; Y# BUpward rank, 升秩7 B M2 W2 j* H. i' ^
Vague concept, 模糊概念
1 a% I" t0 k2 x- {' h+ FValidity, 有效性
7 o9 v* T: @. U4 IVARCOMP (Variance component estimation), 方差元素估计
. p+ F' I- W: }0 O0 i; gVariability, 变异性
a) X3 V7 a+ |- `6 \Variable, 变量
1 F! F+ [$ h9 N6 y4 T- M- K* GVariance, 方差
2 w# u# @: U8 VVariation, 变异) c1 k& v" d# I9 w0 {5 l
Varimax orthogonal rotation, 方差最大正交旋转. m4 l: j J$ v4 p4 [+ A+ s
Volume of distribution, 容积
( [: h) `0 E! E' @1 R5 gW test, W检验8 U2 r0 C& U& r8 A8 I# p" k
Weibull distribution, 威布尔分布
. S* O7 c5 z* n6 p) N! @" XWeight, 权数! e7 T- V: q; I y
Weighted Chi-square test, 加权卡方检验/Cochran检验
8 m; V# a# b0 X+ ?) Y: ?Weighted linear regression method, 加权直线回归
" d* ^$ B; P: jWeighted mean, 加权平均数3 b5 s. q3 C$ o. @/ W9 ^0 z
Weighted mean square, 加权平均方差
. m# L( l4 h& j6 }Weighted sum of square, 加权平方和3 I5 Y- {- F. S3 O6 ^! q
Weighting coefficient, 权重系数
/ W. w4 L8 G) t+ Z' UWeighting method, 加权法
/ ^5 T5 f( H4 s; G) C; YW-estimation, W估计量
/ ]3 I$ W, h" i: m( |% eW-estimation of location, 位置W估计量
" [7 D' ] F' M3 mWidth, 宽度3 V% G- O. g2 ?3 e2 {* V, U8 U
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
+ G5 H& G* k9 @# p* I/ lWild point, 野点/狂点
7 w7 d' G, \# L) p) L1 S3 ]: QWild value, 野值/狂值
& [0 k! e! X7 ~( y7 A0 ]$ |( a& QWinsorized mean, 缩尾均值
- S% y3 n" D0 j% hWithdraw, 失访 2 t5 [: [8 K/ ?7 @5 S8 Z
Youden's index, 尤登指数. z9 `6 g" v' H$ q: Q" Z
Z test, Z检验
6 X% D- h$ o8 S* r7 |0 H3 AZero correlation, 零相关
- G* Y. C, y1 ?1 Q% bZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
