|
|
Absolute deviation, 绝对离差
+ X: s: A f# lAbsolute number, 绝对数' M# M5 j& {. A; O2 w
Absolute residuals, 绝对残差
. r) c9 p8 q0 G# v! u! GAcceleration array, 加速度立体阵
5 H8 X+ ?: \& ~$ e2 m( d3 _Acceleration in an arbitrary direction, 任意方向上的加速度# M' l' ~! s* E' Q0 o7 A6 H% l/ a7 v
Acceleration normal, 法向加速度' n, Z( I- L, c5 ^
Acceleration space dimension, 加速度空间的维数$ s. i+ r- @: T$ H
Acceleration tangential, 切向加速度( q5 M' N: T+ K; \$ B6 w. w0 L
Acceleration vector, 加速度向量
8 W9 i3 b( k6 Q1 g5 @Acceptable hypothesis, 可接受假设
: D0 Y D' M; t$ F# k& [% SAccumulation, 累积' A4 P9 p5 n! T: k, w/ z
Accuracy, 准确度
& S3 S$ k p5 Y9 O) DActual frequency, 实际频数
; B4 A+ I; `$ p5 O+ {Adaptive estimator, 自适应估计量9 g7 v3 [& Q8 U8 E4 a
Addition, 相加) {+ y) R( c. e% C" U
Addition theorem, 加法定理( U* }' X! i8 p) Z( c
Additivity, 可加性( C3 d' [5 Z+ D+ H1 t
Adjusted rate, 调整率
& c( P0 Y _- ~' P( u) g' P1 F& `) _Adjusted value, 校正值# G# j9 r8 p( E% D$ G
Admissible error, 容许误差
, f2 Q4 m$ T+ d9 M: cAggregation, 聚集性
) g" |, A: S4 C0 j4 QAlternative hypothesis, 备择假设
3 ~4 Q7 s, q2 |0 m) v, C4 I' EAmong groups, 组间; N: ?! o. ~1 l0 p6 y' u' J& S
Amounts, 总量1 d/ |( N% h$ H/ u% _5 t' h; U
Analysis of correlation, 相关分析4 [! e( M; D' [* e8 @
Analysis of covariance, 协方差分析9 G& }& K9 e v( K, c t
Analysis of regression, 回归分析. @; N9 Y- x2 T2 f
Analysis of time series, 时间序列分析7 E1 q4 i/ L7 K5 x; b; B
Analysis of variance, 方差分析
! Z0 b4 O j- Y- N; A6 j0 nAngular transformation, 角转换3 [! C8 m% a$ ~; P" I. y
ANOVA (analysis of variance), 方差分析
8 \1 y! x' U$ _3 u+ MANOVA Models, 方差分析模型7 X( k, X' \% V. X5 ^! O' b
Arcing, 弧/弧旋, ~/ }% z: P$ T2 D6 |# {" D8 q Y
Arcsine transformation, 反正弦变换
: `* |0 ?- Q9 V) | fArea under the curve, 曲线面积
& f+ U$ { e+ gAREG , 评估从一个时间点到下一个时间点回归相关时的误差 3 p/ m+ ?7 Z/ y0 u8 x% z0 I" Y
ARIMA, 季节和非季节性单变量模型的极大似然估计 : x4 P* n. }; P! t8 G
Arithmetic grid paper, 算术格纸7 f7 b6 O* ^; M3 V+ b0 G
Arithmetic mean, 算术平均数9 E0 z F3 G" R: H
Arrhenius relation, 艾恩尼斯关系
" P- l" H' ^, n0 ZAssessing fit, 拟合的评估
6 R$ r" @4 S Q# PAssociative laws, 结合律! e2 p* w8 M/ ?: @) R. `
Asymmetric distribution, 非对称分布
; }/ ~4 [6 Q5 _; H9 j8 B" m! Y8 GAsymptotic bias, 渐近偏倚
- @9 M+ z$ X, B: }* G) HAsymptotic efficiency, 渐近效率+ t0 I+ X0 a( \
Asymptotic variance, 渐近方差8 r! Q! V# [4 l2 D
Attributable risk, 归因危险度% G* A- N3 N6 m+ o% H: e, y7 q
Attribute data, 属性资料: R& y+ M, O7 i
Attribution, 属性
7 B' K/ l4 I! b n" A$ `) nAutocorrelation, 自相关7 |7 o7 O! O# J5 R; {) N2 k
Autocorrelation of residuals, 残差的自相关
; }; M% E2 P# Y2 v lAverage, 平均数# D; O' ?7 ~& I7 @, W( }
Average confidence interval length, 平均置信区间长度0 k% M, I% d! e# {1 f; W0 I
Average growth rate, 平均增长率- q* B3 C+ ~7 J
Bar chart, 条形图
% t( @6 ~1 M' u# _Bar graph, 条形图
+ M) N2 X, R8 Z8 \$ jBase period, 基期
/ H- w8 ]) P; @* s: R& l. V) rBayes' theorem , Bayes定理
& X5 r3 u! W+ J; WBell-shaped curve, 钟形曲线( B1 u; ]+ \0 g( l0 s: c! L+ h5 o
Bernoulli distribution, 伯努力分布! u1 y2 K' ? C) p3 u
Best-trim estimator, 最好切尾估计量7 J! p, P# E9 V7 F/ _5 P2 Y& h
Bias, 偏性
* x |3 y4 p4 oBinary logistic regression, 二元逻辑斯蒂回归
" J3 @7 r; `7 L. E9 ~Binomial distribution, 二项分布
' r+ P& g( j+ @0 k, l+ `/ W+ kBisquare, 双平方
3 j6 S, Q H2 V2 [6 g. m- TBivariate Correlate, 二变量相关: O; |2 t; F3 _; O2 \, X
Bivariate normal distribution, 双变量正态分布
# @0 @& h5 ?) k. F0 H3 j- lBivariate normal population, 双变量正态总体, k% J, } V3 I# V, @
Biweight interval, 双权区间4 r. |6 D7 R3 p) ~6 J( I
Biweight M-estimator, 双权M估计量" N5 u- V" x. l1 K0 R# z6 S
Block, 区组/配伍组. x0 T) w2 [( l
BMDP(Biomedical computer programs), BMDP统计软件包7 I Q: @3 P& ]7 g
Boxplots, 箱线图/箱尾图
, q) g+ F$ s; N$ T: m: ?4 L' {Breakdown bound, 崩溃界/崩溃点# P2 K8 P( @* i5 D0 z; _8 K
Canonical correlation, 典型相关
/ q8 J" j3 y: q6 ]4 J4 eCaption, 纵标目 [# Y' ~4 I6 n' K1 b4 `6 q
Case-control study, 病例对照研究1 l& O1 h7 |7 W( C; z y) M. t
Categorical variable, 分类变量
6 Q/ d) [* z' Q0 tCatenary, 悬链线
9 ]( ~% {, A. d3 S9 {5 Z. D: jCauchy distribution, 柯西分布7 W2 Z0 ~+ p' P4 k
Cause-and-effect relationship, 因果关系7 \( p% Y! i2 n1 x
Cell, 单元$ s6 M7 P! n: l+ C
Censoring, 终检& ], Y. _8 O& V. c$ N$ B
Center of symmetry, 对称中心, c/ I% Y4 A0 z: O( E& b, {
Centering and scaling, 中心化和定标. n( A9 J; y2 T" L0 b
Central tendency, 集中趋势
6 Y9 Y4 [; ^' s0 m6 _. L& \9 VCentral value, 中心值
7 j7 [% G# \* @8 c* A# b+ xCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
, J, I8 ^% v. j0 |) Y6 A% v1 pChance, 机遇
/ k* }2 v r/ G6 i+ l- ZChance error, 随机误差
/ k/ B$ i' ^2 E& kChance variable, 随机变量
$ p( y! a7 R/ B, oCharacteristic equation, 特征方程( B* h8 z2 a. A1 K0 S* x
Characteristic root, 特征根9 P$ f4 z: [1 n) S( V
Characteristic vector, 特征向量
5 E& K4 G; Z& F: O* x/ B; `Chebshev criterion of fit, 拟合的切比雪夫准则
7 C0 ?# t- m0 ?, @Chernoff faces, 切尔诺夫脸谱图
, h _4 u+ z$ J k6 wChi-square test, 卡方检验/χ2检验/ N7 R9 W" } ^( A& A8 a; _
Choleskey decomposition, 乔洛斯基分解
; V; R; a4 Y2 t$ h: A4 [7 C+ nCircle chart, 圆图 % |3 i# G1 V1 y3 Z" M( r
Class interval, 组距
( r3 C& k0 Z0 @9 PClass mid-value, 组中值
7 O2 M! k. Z1 |Class upper limit, 组上限
4 N4 ^+ l' y( h4 U% R, \! `% fClassified variable, 分类变量# s8 }5 s% |2 Q3 d& y
Cluster analysis, 聚类分析
: F# L4 _ c+ C& o: v2 qCluster sampling, 整群抽样
+ R( S! {) D3 ~* Y! l4 _& WCode, 代码7 d# ~7 Q8 C) y8 e% C/ L9 i( T( i& s& U
Coded data, 编码数据
% c8 f0 }; H) H% L, kCoding, 编码1 d" k7 ~+ s; f. J
Coefficient of contingency, 列联系数
7 }' b# t2 |0 O) BCoefficient of determination, 决定系数
. A' N9 a- i5 p/ P% ]) \Coefficient of multiple correlation, 多重相关系数0 c4 o a6 F" N% {( K* T/ @& f% |# [8 U
Coefficient of partial correlation, 偏相关系数
{/ Y& a; w8 ^2 l, PCoefficient of production-moment correlation, 积差相关系数
, ]$ o/ |9 {8 g+ n" @Coefficient of rank correlation, 等级相关系数
2 {2 A- |: t: P3 NCoefficient of regression, 回归系数
( ~' D, P: x! X* O( UCoefficient of skewness, 偏度系数
$ z" [7 P8 l1 \7 H2 b+ z- Z# A9 ]" fCoefficient of variation, 变异系数
5 ]) W5 J+ o jCohort study, 队列研究& Z2 a5 o# a# \ l$ b$ t/ g
Column, 列
- m9 ? a% S4 a! r, B6 M. cColumn effect, 列效应) L7 ?& e% G ~# U. G7 ~
Column factor, 列因素) K6 ~5 m/ R- k* R
Combination pool, 合并 W# l M) v L, |
Combinative table, 组合表
0 V/ i# `: K/ C1 i; o. ECommon factor, 共性因子5 U" B) G0 n( }8 F
Common regression coefficient, 公共回归系数& w& {( |4 |8 k
Common value, 共同值( Z! o, U7 s/ `+ h5 L+ w
Common variance, 公共方差
9 |9 ]3 B- t/ t+ ^8 Q/ F: V6 ]1 ICommon variation, 公共变异+ h- U% z! ]8 f
Communality variance, 共性方差: h2 x; l/ `6 @( O+ v
Comparability, 可比性& }# P" h# i ~5 F, }
Comparison of bathes, 批比较
( X8 ^& ?# I4 o& a6 T8 t2 ?Comparison value, 比较值2 u5 D& K' ]9 y" h5 H
Compartment model, 分部模型 x* p, ?9 R9 M7 ]: \: |
Compassion, 伸缩
! O+ [ y) _# CComplement of an event, 补事件9 p0 M7 ~( z+ t- a6 z+ k
Complete association, 完全正相关
8 }& q; W: i& c& DComplete dissociation, 完全不相关) h8 {0 X4 D/ V9 t( j, Q
Complete statistics, 完备统计量
8 j. e" @' ]- F5 [6 t% v G( i. zCompletely randomized design, 完全随机化设计' F+ P6 _- i' H/ D# z5 @# a4 X
Composite event, 联合事件! V, I5 Q; W' V0 Z( w; y
Composite events, 复合事件
7 ]% E8 q( P1 r; c1 U% zConcavity, 凹性( S% I F0 S4 N+ w
Conditional expectation, 条件期望$ S" K4 A& O4 r H5 c
Conditional likelihood, 条件似然
I& b1 f9 i1 qConditional probability, 条件概率1 h& [5 U8 {1 ^4 F
Conditionally linear, 依条件线性7 G$ Y6 ?8 f* `, Q/ \8 a
Confidence interval, 置信区间 C& i( R2 A, z. p
Confidence limit, 置信限
$ q2 E3 m# c2 ZConfidence lower limit, 置信下限: d4 S3 r% t5 u) _) B1 b
Confidence upper limit, 置信上限" [; M7 _! o1 z9 c# e( |
Confirmatory Factor Analysis , 验证性因子分析
, z; N: m+ ]- iConfirmatory research, 证实性实验研究2 |2 j; } l; Q0 ]& u
Confounding factor, 混杂因素$ d5 G* |1 m* a$ U2 Y( X) t
Conjoint, 联合分析& k1 T9 S7 n9 U3 ~" d
Consistency, 相合性
3 ~1 s) N. o% f6 d# [5 ZConsistency check, 一致性检验
7 Q2 R) Q: \; V7 WConsistent asymptotically normal estimate, 相合渐近正态估计' D! D# Q) S% [% B0 G: H
Consistent estimate, 相合估计
' Y! i# P d* e1 w- v, c0 U5 Q' qConstrained nonlinear regression, 受约束非线性回归
W! e1 S. @ a' [" K% ^Constraint, 约束$ ^+ E* O& s. a- s5 B4 ]
Contaminated distribution, 污染分布5 d s0 L- l7 A- [4 [5 u) w6 V, H
Contaminated Gausssian, 污染高斯分布
4 F" M+ }! O, n/ y/ x, W$ dContaminated normal distribution, 污染正态分布
% ~: ^, c, i* ]Contamination, 污染
. \6 ]1 V4 z3 D3 J, mContamination model, 污染模型
6 N0 o6 d* q- m. o7 wContingency table, 列联表
e: D" q( z" m, E6 | M( K& W/ pContour, 边界线: R: S h$ B, Q1 |7 K6 B8 V
Contribution rate, 贡献率
5 R7 z! ^8 o& F, b$ E$ Z$ c$ vControl, 对照: `4 h+ B! Q, A- e
Controlled experiments, 对照实验* b4 k0 x. _7 ?. y4 G9 y _8 a G
Conventional depth, 常规深度. i2 A4 C$ c2 g* Y
Convolution, 卷积
/ l* [8 B3 D- _- Y9 M& LCorrected factor, 校正因子8 A6 X- Y" f) f$ m
Corrected mean, 校正均值& |9 A* G0 A* c A: H; t' S
Correction coefficient, 校正系数. `8 K- o& E6 y
Correctness, 正确性/ |( a+ @( n2 f- l# W2 N
Correlation coefficient, 相关系数
2 Z5 l" S! M, I2 O8 `. w) nCorrelation index, 相关指数
* `& }) |- U" y# jCorrespondence, 对应
1 P# \: m0 ]5 C- W" W. LCounting, 计数! k9 i5 f! |* l, D. ~/ m
Counts, 计数/频数( D9 @6 [( E9 q K! t7 n
Covariance, 协方差+ g. T7 v+ H1 J1 `" j
Covariant, 共变
$ R6 l) z" `: u; MCox Regression, Cox回归
7 Q, q" l1 l" p" q% g5 _Criteria for fitting, 拟合准则
; j, W( O4 U0 FCriteria of least squares, 最小二乘准则
) U) D5 i5 p3 a9 p! yCritical ratio, 临界比
6 m! B# P, s$ ^+ |1 S! JCritical region, 拒绝域4 | U4 k3 y6 k' i# x9 z4 g" ~. q
Critical value, 临界值
2 ], w( m1 D2 PCross-over design, 交叉设计
) o4 K! t, E+ Q$ L1 p3 x3 r: ^4 eCross-section analysis, 横断面分析
! ]: w; J8 z. y$ V7 K( |" Q3 ACross-section survey, 横断面调查" N6 q9 y9 P/ v1 W( X5 @# k* o
Crosstabs , 交叉表 / ?$ ?2 C! v3 c, i9 Z( I; y
Cross-tabulation table, 复合表( J2 A8 Z v- |4 H' i1 E
Cube root, 立方根; q$ a$ e' M0 X
Cumulative distribution function, 分布函数
* H0 ~7 S' f O- S4 PCumulative probability, 累计概率
( \1 i! i( y! N/ B ~& G$ l/ E1 yCurvature, 曲率/弯曲) @4 q, h% K s
Curvature, 曲率( e$ k1 L l5 ^) r
Curve fit , 曲线拟和
( A( B) C- H; w5 I, p3 u; DCurve fitting, 曲线拟合, w2 f0 ?' E, l$ P. u# z9 |
Curvilinear regression, 曲线回归$ v, m) z& N' v, E8 D- M
Curvilinear relation, 曲线关系
* b5 e2 v/ b& ^% PCut-and-try method, 尝试法
) @" b6 l- s* G$ }8 w& p+ T1 WCycle, 周期
% l- z2 z8 j( g, g0 k* N4 nCyclist, 周期性. K: g# q) M k
D test, D检验
. c& V6 h1 l* AData acquisition, 资料收集% e# ^8 b1 h8 f
Data bank, 数据库* ~: {; i7 q, V6 P" N
Data capacity, 数据容量
/ V( O$ {, p9 CData deficiencies, 数据缺乏* g* Y! U8 Z/ O; v5 E; X& ?3 h
Data handling, 数据处理0 y0 P e3 @. w/ l) V# e8 f) Z7 M
Data manipulation, 数据处理
$ Z6 P- f# S* L" f1 W8 AData processing, 数据处理5 l( z# z$ {+ W& [0 B' x
Data reduction, 数据缩减
1 K3 f4 o: ~. \& S; q b9 P1 XData set, 数据集2 `8 ^1 c8 K% T* d9 l* ^& u* C$ ^
Data sources, 数据来源
) h& G7 n; n6 f5 T" Q OData transformation, 数据变换
' Z9 y/ c u6 h- w3 G/ tData validity, 数据有效性; N( ^2 E: i1 E- q, S' \9 l! n
Data-in, 数据输入
" W p! `8 O' ^' Z3 Q0 pData-out, 数据输出+ @( [1 P% j8 V6 _. U! s& o
Dead time, 停滞期8 M% O/ Z3 T3 w( Y( \* a5 ?$ u/ b
Degree of freedom, 自由度
# f& V2 ~* U; n2 e7 o& {1 kDegree of precision, 精密度
% V# V- {, A: d# d5 y) |7 ?! o( ODegree of reliability, 可靠性程度5 F% |5 [& L: h! i2 a
Degression, 递减 q+ F( s* C c% F: u$ B' |+ w# a
Density function, 密度函数
# ?0 @ x6 D: Y; Y4 f& WDensity of data points, 数据点的密度
; k: |+ B5 r, X: o. C: R2 d. {Dependent variable, 应变量/依变量/因变量" n* J! O; }: k0 v% Z! Z3 I
Dependent variable, 因变量9 J$ \6 b6 L! u5 |: [
Depth, 深度, q% \, C7 v4 Q% D
Derivative matrix, 导数矩阵4 |" O: p% m5 _- M% B3 m
Derivative-free methods, 无导数方法
3 R9 G/ i, G; `1 C- ?1 SDesign, 设计* a8 Z$ \" O0 W6 @1 _, W, h
Determinacy, 确定性
/ {: B7 Y4 ~8 v1 c6 a# z& wDeterminant, 行列式
7 _5 D# S! @7 H: x: pDeterminant, 决定因素# |" D( B2 {8 \. C% f% W
Deviation, 离差
% e& W; {+ L5 p- z) j1 \Deviation from average, 离均差
: T+ l- d6 ^' l1 X. K& U1 k. tDiagnostic plot, 诊断图$ n; j" M* H( I
Dichotomous variable, 二分变量& m+ ^2 D* f" @# {
Differential equation, 微分方程
' \, H+ h* f5 F$ uDirect standardization, 直接标准化法
1 s( H) u* l" A9 F. s8 w# f, q; }Discrete variable, 离散型变量
. I, g: E: Y! l: {, p2 K8 X8 QDISCRIMINANT, 判断
4 Q% g# t+ ^. C" w1 EDiscriminant analysis, 判别分析
' y1 ]: ]8 p6 L9 L$ Z& b d: }Discriminant coefficient, 判别系数
: F* u$ U- W m) G( } |Discriminant function, 判别值
; r) y8 q8 f0 BDispersion, 散布/分散度3 z/ B U' e. r# `
Disproportional, 不成比例的
% u- N& k7 u( F2 R4 V5 GDisproportionate sub-class numbers, 不成比例次级组含量
$ W; {- L* K, `1 _ f' GDistribution free, 分布无关性/免分布8 `2 i6 u! D9 p! L* f3 x
Distribution shape, 分布形状
/ c" r4 u# z f7 {8 |Distribution-free method, 任意分布法- Z6 w' C. r' D i. W! N+ d7 B" `
Distributive laws, 分配律9 [4 k0 b3 S. {( `8 o+ i$ D
Disturbance, 随机扰动项2 J7 j3 v3 y% v
Dose response curve, 剂量反应曲线" ?! I+ l; V% m
Double blind method, 双盲法
; [# h' _1 K! S2 e2 MDouble blind trial, 双盲试验# C6 @9 ?" O: x8 D9 n9 v2 Z
Double exponential distribution, 双指数分布
. ]1 M7 H: W- z- t5 ADouble logarithmic, 双对数, l, _; A* m5 W, c, p5 Y* F
Downward rank, 降秩
t# T2 I3 K* [$ l7 d9 @Dual-space plot, 对偶空间图$ i/ }4 P/ [7 O o
DUD, 无导数方法9 F0 Z7 Z$ o4 n
Duncan's new multiple range method, 新复极差法/Duncan新法
" h+ w) d1 A1 O3 a/ d% K% b2 [Effect, 实验效应
! e4 T# u8 S: XEigenvalue, 特征值- w0 I' ?; O/ z" g9 e) d
Eigenvector, 特征向量
; h3 N' d' o) Y. J: E: `+ f7 [Ellipse, 椭圆+ Z4 x% g, q% K% b; f- F! ?" g
Empirical distribution, 经验分布
4 I" S" M0 i( J# \1 u2 aEmpirical probability, 经验概率单位
3 o+ T8 V& e$ m0 b# h- c* f9 R( A5 `- oEnumeration data, 计数资料: W6 V! P& h6 c8 b# b, R
Equal sun-class number, 相等次级组含量2 Z3 R o; Q& c J
Equally likely, 等可能
; b) V1 w, q+ Y( y6 S HEquivariance, 同变性
- F4 [, V$ n3 F& J, d4 uError, 误差/错误2 F2 S, b/ F5 a( A" R
Error of estimate, 估计误差& o! o- A. y0 P3 e
Error type I, 第一类错误
% @ m2 M* S: X, T2 LError type II, 第二类错误
, H7 w$ X3 }" A* p0 T0 KEstimand, 被估量( ]4 s/ O1 S0 |" z, _, p6 l$ u
Estimated error mean squares, 估计误差均方, G) O! \! O( |4 k6 X
Estimated error sum of squares, 估计误差平方和
8 r- x- o4 v" EEuclidean distance, 欧式距离
3 K, c- c2 T. s1 y2 dEvent, 事件& H! v* N7 o5 q9 K. P
Event, 事件
% y5 d% @8 |) pExceptional data point, 异常数据点
# b- t! q+ y4 tExpectation plane, 期望平面
! { T3 F9 I8 f5 e, V. rExpectation surface, 期望曲面
' f. Y: \# L- R- K- ~$ L& {0 VExpected values, 期望值) m: `+ E) [) O# o: H8 b
Experiment, 实验
& M/ b% |0 _8 y g; @Experimental sampling, 试验抽样" [( m. q- t* J1 P" ^+ O
Experimental unit, 试验单位
. c6 a0 a# h5 r* K8 b; E( DExplanatory variable, 说明变量' K$ G) N* W0 x9 Z; @
Exploratory data analysis, 探索性数据分析" [) c/ q+ g6 a# f( \- w( X
Explore Summarize, 探索-摘要
- P2 ^# L6 D, v+ f+ O& e+ BExponential curve, 指数曲线
: `' V$ E7 |6 i+ \* D6 ]Exponential growth, 指数式增长. O6 C* t: `: y7 m V! U) G/ g+ r) }5 H9 d
EXSMOOTH, 指数平滑方法 3 g# v. k" Q2 c% r" o) N0 I
Extended fit, 扩充拟合# C1 E0 P( _. W# q# w
Extra parameter, 附加参数
# k0 u) S ~4 _% TExtrapolation, 外推法
0 v3 i% U1 a0 _4 SExtreme observation, 末端观测值
1 {- J* }0 `" ^6 X% ?3 n" J, Y. LExtremes, 极端值/极值5 ?7 b# X# R. e: Q
F distribution, F分布
$ l5 M; W9 \* a' Z5 ^! H5 a/ s6 g* ZF test, F检验
8 v1 j$ K7 b) N9 R1 {Factor, 因素/因子% |# {, M( k9 J- X" x# r
Factor analysis, 因子分析+ g1 H6 |3 H+ R* P" E; |# y
Factor Analysis, 因子分析
5 c$ K7 B* [7 o) ]Factor score, 因子得分
% \* E$ c3 E1 f# D CFactorial, 阶乘& c4 x) D. v, |* y
Factorial design, 析因试验设计
" n( b H! E$ {+ r6 Q, ^False negative, 假阴性* a' ?- v" ~& v, `
False negative error, 假阴性错误; |2 X/ v) h9 C( o7 }5 G
Family of distributions, 分布族
2 E# U: ^/ [3 C; CFamily of estimators, 估计量族( o: d4 k( k {, t- I7 L/ m* Z Y+ n
Fanning, 扇面
/ g) `: I; B5 \8 UFatality rate, 病死率3 ?" @, ]6 E" u# J7 N, q
Field investigation, 现场调查
* ?% I+ D6 X% C7 ~Field survey, 现场调查
; y6 h; b1 R F, p8 aFinite population, 有限总体4 z. v) N+ B. ?+ ~
Finite-sample, 有限样本: x6 l9 n3 t M6 A5 _$ A1 ?3 J3 k8 W
First derivative, 一阶导数
6 o" v8 k, ?; X9 O7 t& `First principal component, 第一主成分
% H1 ~( v# c4 N& k* V5 |" D; aFirst quartile, 第一四分位数
4 [2 P8 A8 s0 y& A7 e4 EFisher information, 费雪信息量
5 D; `! Z5 B O% [: HFitted value, 拟合值
: Q3 I8 M! s `; e# s4 F) o! }Fitting a curve, 曲线拟合
! R1 r; V! N" I/ D( AFixed base, 定基1 p w+ H/ q' j2 j
Fluctuation, 随机起伏
) Z+ D5 ~) j$ q; m. q: y0 yForecast, 预测
m0 T; Q9 O! t) V5 |* k8 b7 e0 lFour fold table, 四格表" J' Q5 H: X9 Q3 h2 s8 R% Z$ U2 L
Fourth, 四分点
8 e' L" a$ @9 \7 P$ MFraction blow, 左侧比率) r( k- [- S1 \# Q: }; K% e8 Q. v
Fractional error, 相对误差$ [+ R: s9 O! v6 l
Frequency, 频率
- K$ j8 Z& ]! cFrequency polygon, 频数多边图. a9 _" C6 N2 |( B* @
Frontier point, 界限点
/ [: s) f4 s4 Z4 Z# ?Function relationship, 泛函关系1 A3 o: V+ `! d; u
Gamma distribution, 伽玛分布
- \! A n* N8 Z0 Z( O2 sGauss increment, 高斯增量: S6 E0 ?$ e# s# X5 L! E
Gaussian distribution, 高斯分布/正态分布5 g, | k3 N- F6 {9 w/ ?
Gauss-Newton increment, 高斯-牛顿增量+ U9 X- _2 `5 N4 u2 v
General census, 全面普查
3 f% z5 r. C& X, R# s) @: F) D- |GENLOG (Generalized liner models), 广义线性模型
8 T; X$ @5 f' J% L& VGeometric mean, 几何平均数
7 y6 s# C! a+ ~- j* q0 |Gini's mean difference, 基尼均差
, P6 `3 O2 M, C9 l( }* i; y% tGLM (General liner models), 一般线性模型 * W9 T9 y5 o9 A3 q
Goodness of fit, 拟和优度/配合度
" k8 y9 R' F$ r3 z# o. Y# r. IGradient of determinant, 行列式的梯度
# L% j+ {$ E, q: p- I/ f7 rGraeco-Latin square, 希腊拉丁方0 V1 W+ _' l# U" f8 ?: Y0 C) Z; a
Grand mean, 总均值
R& M5 A: \( w0 t1 B* I WGross errors, 重大错误
" j. \, n( D$ B* H7 z, `3 ]Gross-error sensitivity, 大错敏感度& X# b2 D/ w$ n/ v% i3 P7 v+ l
Group averages, 分组平均' f' ]% J1 K3 g1 q+ w9 h
Grouped data, 分组资料
! C' v! `/ G7 B- CGuessed mean, 假定平均数
- { E8 |. N* d; K" M2 N8 [$ _Half-life, 半衰期
) o( g4 _/ ^1 b$ _( a- QHampel M-estimators, 汉佩尔M估计量+ s6 P) V7 L0 t- O9 Q
Happenstance, 偶然事件
2 T+ q3 T$ r# \5 _Harmonic mean, 调和均数
! P( n" A8 m1 M* |4 U8 u% WHazard function, 风险均数4 e1 I9 r! h' V! a6 N
Hazard rate, 风险率
& Q `, Y& q8 z4 A `% mHeading, 标目
2 _! L( l7 f: n1 s, _$ J5 t7 T1 sHeavy-tailed distribution, 重尾分布5 R6 O B& Y, K! h% `8 O
Hessian array, 海森立体阵
4 u* Q2 ~; F' \* _ l B1 a$ X; ~Heterogeneity, 不同质
8 Z" O. V; d2 M; \8 r" oHeterogeneity of variance, 方差不齐 9 N; }0 z( d( O0 T) F4 |
Hierarchical classification, 组内分组' t# i+ o" D1 z y
Hierarchical clustering method, 系统聚类法& Q8 Z6 K- B' ^/ R
High-leverage point, 高杠杆率点; \5 R6 Q" D7 n8 h
HILOGLINEAR, 多维列联表的层次对数线性模型
: F( G3 {% i" }3 L% d: oHinge, 折叶点
) C1 Z( G2 G( J' VHistogram, 直方图- h6 D. M# \0 A& O7 e! P y
Historical cohort study, 历史性队列研究
9 ?5 Q& y/ l% d0 Q+ zHoles, 空洞
8 v9 ]* A/ Z% p" l; u# U% QHOMALS, 多重响应分析
4 ?% Z8 u+ u8 zHomogeneity of variance, 方差齐性- A- _$ I& F3 y" j
Homogeneity test, 齐性检验2 W5 _( X2 M1 u6 d3 V1 \7 f, v
Huber M-estimators, 休伯M估计量
! f- g! p: Q/ a5 qHyperbola, 双曲线
( u# O3 Y6 n( D; K9 HHypothesis testing, 假设检验
! p- k# i/ x- U/ Y$ uHypothetical universe, 假设总体% l- W! o- E& v
Impossible event, 不可能事件
. o! f; |% O; l0 d" J; yIndependence, 独立性- d I; Z# O- N
Independent variable, 自变量/ j* g: c- H6 ~1 S H3 e+ J
Index, 指标/指数- j& @: e0 l- e( U; P6 Q% o3 {
Indirect standardization, 间接标准化法$ o2 M! O, p- G+ A
Individual, 个体
* ~: o# p- Q% P; P; KInference band, 推断带
# O; g( S4 ~ ~+ @Infinite population, 无限总体
8 @6 g; m( F$ J5 MInfinitely great, 无穷大) O8 u6 J0 R, S& d# _8 y2 }
Infinitely small, 无穷小* e3 B# b7 J8 G' x
Influence curve, 影响曲线
. v" j3 z( S# g! y: T1 TInformation capacity, 信息容量
# v/ b r0 ]+ o) n& RInitial condition, 初始条件2 d# z0 X, ?/ L
Initial estimate, 初始估计值
6 X$ T: R$ \, NInitial level, 最初水平0 d. v5 y- F, s# @+ @( c0 U% R
Interaction, 交互作用
# G2 D, n! ^) {, C( q4 p0 ^Interaction terms, 交互作用项8 i+ R) l, g, e: H+ k1 w
Intercept, 截距
7 ^1 @, b' Y/ q! X/ q9 e1 mInterpolation, 内插法( _4 u! H9 m- h( d" D' i/ T
Interquartile range, 四分位距- d0 z4 R; _* w: e. X
Interval estimation, 区间估计
& H/ H" K& f# g; IIntervals of equal probability, 等概率区间, ^$ o! n) A J( ^+ ]% ^! B0 ?2 u& {2 H
Intrinsic curvature, 固有曲率; G( t" k0 _5 O3 u" K I/ ?; ?2 c
Invariance, 不变性
1 }: k# C% D0 J1 D$ R% dInverse matrix, 逆矩阵2 T$ V& K. I2 ], b
Inverse probability, 逆概率
( k9 ~2 l; s- Z) I' n0 u- hInverse sine transformation, 反正弦变换
% x8 V( k5 `, F0 T( U4 rIteration, 迭代 & |5 v. x' L1 U0 L/ w
Jacobian determinant, 雅可比行列式
& }6 ~, g0 I, a& Y# JJoint distribution function, 分布函数. t, m+ u; u, s( b+ f2 l
Joint probability, 联合概率& v" v& R* {" F, f8 m! K( C8 }5 Y
Joint probability distribution, 联合概率分布1 S5 A& b1 l/ ?# G& J! N
K means method, 逐步聚类法
. L1 S/ R5 j. J0 o2 bKaplan-Meier, 评估事件的时间长度
# P& Q3 S7 M$ BKaplan-Merier chart, Kaplan-Merier图
`5 N& N; b s8 tKendall's rank correlation, Kendall等级相关
4 W" b, p) S) x6 e4 _4 s, {: T) C' fKinetic, 动力学
, Q M& F2 |4 ^8 H, W; q" t+ kKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
/ A0 T, ~' b7 b3 q3 rKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
3 B8 G$ O8 |+ U) }$ p' Y; l" cKurtosis, 峰度
9 A7 e( \$ _: V7 PLack of fit, 失拟
9 l. J2 h% Z9 I) gLadder of powers, 幂阶梯
. e) g. D, R+ \, i7 J$ TLag, 滞后
. X( l9 n; C% j1 Q) a- t4 XLarge sample, 大样本
1 A+ `* L9 R5 {7 p0 `Large sample test, 大样本检验- j4 \' g, q/ k0 m: Q: k7 g% K
Latin square, 拉丁方. Q- T7 G- ?% ]9 \; W6 R1 P
Latin square design, 拉丁方设计
( f8 ]5 I, R; Q+ E; ]Leakage, 泄漏
8 s! @9 `- p( \. tLeast favorable configuration, 最不利构形. ~& J, [: t6 p$ [1 z) f
Least favorable distribution, 最不利分布7 D6 A$ w. A' L1 V2 ?
Least significant difference, 最小显著差法+ l% V8 A3 n0 R" c1 ?
Least square method, 最小二乘法' b! G7 ^6 `" j' B1 I" \
Least-absolute-residuals estimates, 最小绝对残差估计9 w8 E9 G r X* s, M2 P
Least-absolute-residuals fit, 最小绝对残差拟合5 B5 S, d. X$ @; {# Q
Least-absolute-residuals line, 最小绝对残差线0 X5 W" n% j$ `& x6 H" Z
Legend, 图例+ G& h* i- g6 R
L-estimator, L估计量, t6 T; N* M! U
L-estimator of location, 位置L估计量
- l, H+ G' H5 T+ Q* {L-estimator of scale, 尺度L估计量" n+ P8 I( o9 r1 T! R( p" q S
Level, 水平
" Z) F( n6 i" @2 ~6 YLife expectance, 预期期望寿命
, A5 l" a, d* Q! K3 HLife table, 寿命表' R5 k; r. Z2 b9 V5 Y
Life table method, 生命表法9 V2 b$ e/ x$ d7 G3 B
Light-tailed distribution, 轻尾分布
. T! v& @( x9 O" J9 mLikelihood function, 似然函数
6 G, w, W8 t/ Q/ Q8 _Likelihood ratio, 似然比
. I) ]: ^& I* |7 Aline graph, 线图! R# s' p8 ]/ l. i+ x7 W
Linear correlation, 直线相关
' @3 v& H3 K, Q: i7 F1 cLinear equation, 线性方程
* G, l& [! E# D ^2 ]Linear programming, 线性规划7 ~2 ?" Q5 x2 x7 N; a- X+ E. s9 P
Linear regression, 直线回归
( L$ Y+ }4 }1 M3 Q* P2 R; t! nLinear Regression, 线性回归
' f9 Q8 N* R. s3 |/ |, GLinear trend, 线性趋势
! B4 ?$ j3 e7 F- J: W2 o0 {Loading, 载荷
, w0 ?. [: ?( n' I" E5 N& C: I( q: hLocation and scale equivariance, 位置尺度同变性! u+ b% F& {# p, }; R
Location equivariance, 位置同变性6 \# Z$ q9 E8 C$ y! ^7 n
Location invariance, 位置不变性# ^* b0 `$ e' v- \
Location scale family, 位置尺度族
0 L8 ?# S9 X6 i, ~Log rank test, 时序检验 \0 l' ? U, |- ?4 O
Logarithmic curve, 对数曲线
9 S& K$ r9 l! w( mLogarithmic normal distribution, 对数正态分布
& v; a* h6 T/ v5 N4 G6 DLogarithmic scale, 对数尺度
- g' C- B+ i0 g S+ yLogarithmic transformation, 对数变换
# ~; C0 \9 r* v4 `2 j9 uLogic check, 逻辑检查
* U* g! [. u5 h; |8 PLogistic distribution, 逻辑斯特分布- H5 z$ D9 P' h% s7 J9 A! r
Logit transformation, Logit转换
6 F# f8 }$ e* ]# x, rLOGLINEAR, 多维列联表通用模型
- [) d1 j) g- g) N0 ILognormal distribution, 对数正态分布
' n* [) I$ m/ @8 ~5 pLost function, 损失函数& S. S* w4 n# K$ e
Low correlation, 低度相关
) ^& v- M2 j- {8 a' e2 TLower limit, 下限5 c4 P, y( w2 @* r, J p
Lowest-attained variance, 最小可达方差1 m3 a6 D/ ~* d: c+ x1 [
LSD, 最小显著差法的简称9 t7 V ^9 _ R$ d
Lurking variable, 潜在变量6 o5 X N7 d- O/ l2 o9 m, }
Main effect, 主效应; Y7 w. h7 H6 ], O
Major heading, 主辞标目
# G. `& L* }& VMarginal density function, 边缘密度函数4 L, i+ _! G+ y2 O" q7 `( r4 s
Marginal probability, 边缘概率
* F* H" y( r0 }# _Marginal probability distribution, 边缘概率分布3 \$ e! N; [) W# U+ f7 W" F
Matched data, 配对资料/ [7 {6 U. [; K' W7 Q
Matched distribution, 匹配过分布0 e8 H; l! ~1 @$ B% F7 D8 P; a
Matching of distribution, 分布的匹配$ c% c/ n7 u6 U
Matching of transformation, 变换的匹配" ~" h ?% e% V5 }# c
Mathematical expectation, 数学期望! Q0 C* G4 E& v( \4 h+ Y
Mathematical model, 数学模型 ]7 ]4 J s& T% {8 E! |
Maximum L-estimator, 极大极小L 估计量
# C, Z$ `! T0 P" |9 L( k' VMaximum likelihood method, 最大似然法" O1 R) m4 \% b5 t
Mean, 均数
3 i% _- n1 l ], [Mean squares between groups, 组间均方6 ~) u' ^' @: j& i
Mean squares within group, 组内均方% D" i; X9 D, U: E1 T
Means (Compare means), 均值-均值比较9 p6 s% [1 X; A% E9 K8 ]+ p
Median, 中位数7 W" n8 \4 x/ x, D5 a' x
Median effective dose, 半数效量
: y6 h6 D' m; r/ s: c2 ^8 |( {6 R+ v( ~Median lethal dose, 半数致死量0 T5 X. r: F$ _1 v0 u) l" D* k- c
Median polish, 中位数平滑
0 C- F+ a. [% G. `. z7 v( ^/ g, d& _Median test, 中位数检验
7 G& p% M5 n) w6 PMinimal sufficient statistic, 最小充分统计量
: ?7 u8 T3 q6 ~0 ?% X9 p0 |) ~Minimum distance estimation, 最小距离估计
5 D( t& z* q1 `% h: r7 ~Minimum effective dose, 最小有效量
/ d7 f* B" k: C$ v6 D9 ` U) O8 cMinimum lethal dose, 最小致死量
, c6 _4 G6 G! b3 r* yMinimum variance estimator, 最小方差估计量
& \5 g0 i$ J8 ^9 IMINITAB, 统计软件包
t4 j+ h+ ?( U9 e! R( p/ N' GMinor heading, 宾词标目
4 [! O8 H/ C, EMissing data, 缺失值
# B0 l! s3 |! h2 r" j; tModel specification, 模型的确定0 s+ h6 x4 I3 K/ n7 _
Modeling Statistics , 模型统计1 R, S6 C4 @) A2 t
Models for outliers, 离群值模型
* b, m3 ~5 ^& I: k! m: RModifying the model, 模型的修正 Q9 q- Y# k% ] w
Modulus of continuity, 连续性模
) c* _7 r$ [ ` o; O* k8 C8 M4 AMorbidity, 发病率
( a" R6 P! S' o" |4 G6 C: NMost favorable configuration, 最有利构形7 l& e2 j( R6 P& v2 s$ b: ?/ O- M: @
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
, Z; X. U- t/ g" SMultinomial Logistic Regression , 多项逻辑斯蒂回归 T% j8 x, V" `7 C; f2 X# r3 r
Multiple comparison, 多重比较0 E* B/ \4 w4 `8 B- n& F2 u A
Multiple correlation , 复相关, j p- y1 _' s2 m& ~
Multiple covariance, 多元协方差
G& E. X* v$ Q% O5 eMultiple linear regression, 多元线性回归: H. d! O0 \. O/ s
Multiple response , 多重选项
* n+ ~$ f3 {/ a' CMultiple solutions, 多解
0 a1 a$ W/ u" C( F0 f9 Y: RMultiplication theorem, 乘法定理
# l+ ]. O0 ~+ I3 |& j$ XMultiresponse, 多元响应9 F8 `8 X( P. r3 c
Multi-stage sampling, 多阶段抽样1 g9 s7 C7 {& L+ G J+ P
Multivariate T distribution, 多元T分布
! ]9 S6 K' T$ r7 M: @- U; sMutual exclusive, 互不相容
: x( x( ^+ x* xMutual independence, 互相独立
; \! _- {6 e8 i( l5 d! WNatural boundary, 自然边界
# s2 A% X3 H' ~* G0 lNatural dead, 自然死亡: i! Q* v6 E9 n
Natural zero, 自然零
6 U# D' q/ n k: l; U! I2 }Negative correlation, 负相关
1 |6 j' K' j _) Y! G0 d7 BNegative linear correlation, 负线性相关, G2 m0 d2 U8 U' p, e
Negatively skewed, 负偏
0 [) ~+ Q$ [* p7 yNewman-Keuls method, q检验
. r w, a* b1 ZNK method, q检验
( H! M4 y0 I2 m9 u0 j7 r$ |No statistical significance, 无统计意义: @6 m+ |" r6 M( J# ?" [: j0 j2 p
Nominal variable, 名义变量' D$ Q5 h2 B# v
Nonconstancy of variability, 变异的非定常性
0 u: O) R( K" Q5 gNonlinear regression, 非线性相关! D+ X5 I0 I8 }0 w% O5 `; c6 ?4 Q
Nonparametric statistics, 非参数统计
! ~. d- f2 u& vNonparametric test, 非参数检验6 I% p! p$ d0 A
Nonparametric tests, 非参数检验
' [! [( t8 I6 ^% i/ K& V" G5 D4 ANormal deviate, 正态离差
) w" u+ H' A- e% l& ]: dNormal distribution, 正态分布
W2 q" A+ x" d. dNormal equation, 正规方程组- O5 ^) [# h$ r) U- S* y9 t, G
Normal ranges, 正常范围, m! {, s8 A8 E6 |$ y9 `
Normal value, 正常值% R4 j0 @1 A7 K# z* C4 a
Nuisance parameter, 多余参数/讨厌参数/ Q; D* B5 w- C' `6 q( _5 y
Null hypothesis, 无效假设
' u$ i! ^; c( i4 W! j! L4 X0 CNumerical variable, 数值变量3 `: |6 f/ j2 d
Objective function, 目标函数
" Z# l( T9 Z8 x* f8 c/ OObservation unit, 观察单位
) U8 F: f7 A* s2 qObserved value, 观察值
/ I2 `# e& c( tOne sided test, 单侧检验3 t& s; {% X3 E9 b$ d% @
One-way analysis of variance, 单因素方差分析7 O3 q m7 ~- |' X
Oneway ANOVA , 单因素方差分析: }0 c/ F C9 W) ]
Open sequential trial, 开放型序贯设计
$ k% \4 w/ Q, d8 ^( eOptrim, 优切尾6 \1 h) Z9 @( P" ~
Optrim efficiency, 优切尾效率
; F' s2 e$ d0 H4 y( A3 f9 ^- OOrder statistics, 顺序统计量
" K* p8 R7 a' B5 ?Ordered categories, 有序分类
; F/ I$ V) X9 L$ }( }Ordinal logistic regression , 序数逻辑斯蒂回归1 K7 N/ m( Y% O( v; Z+ M
Ordinal variable, 有序变量
) l$ x+ g+ C8 B* l2 v6 }' ~4 J! Q- TOrthogonal basis, 正交基
9 T' r2 X+ P' N/ E4 m; oOrthogonal design, 正交试验设计( @- H7 K9 _9 ?8 E% B
Orthogonality conditions, 正交条件
+ N6 B% V7 x+ I4 p1 T, I( eORTHOPLAN, 正交设计
+ ]% ^# \5 c. z( r( G( oOutlier cutoffs, 离群值截断点7 R7 ]' Y8 b! X1 o; z+ C z
Outliers, 极端值* L g$ T0 Y, h) H$ V- k. c
OVERALS , 多组变量的非线性正规相关 / o/ i! U7 M6 R E! r9 y
Overshoot, 迭代过度
/ P. N6 w8 w7 e. f! _Paired design, 配对设计3 f Z0 B( e0 j3 o
Paired sample, 配对样本
; Q+ i7 _. k0 E- H" xPairwise slopes, 成对斜率# t8 m0 a% ]1 f2 p
Parabola, 抛物线
+ G* C( Q! Q4 g' l- u4 k7 EParallel tests, 平行试验
. t! X- f& \ l- G( Q0 L; I1 hParameter, 参数7 H, L* B) |+ R: V& ^5 S b
Parametric statistics, 参数统计' j0 V% K. g |
Parametric test, 参数检验
0 x! h; a& }/ Y W- m" ^* zPartial correlation, 偏相关
# r+ n: ^2 c* h3 K: U( K6 g) TPartial regression, 偏回归 l6 h6 }+ i9 t5 ~8 D; L
Partial sorting, 偏排序6 m# c% t' x5 f9 i- i5 o
Partials residuals, 偏残差
# r* v+ W- d+ g2 @* r+ x- ZPattern, 模式
/ x4 h1 ] _6 D0 L2 FPearson curves, 皮尔逊曲线# i! ~0 [, u# Y; Y: _1 b9 `
Peeling, 退层
2 |: @! _8 g- h6 e$ pPercent bar graph, 百分条形图
- V: m# t7 I) [5 ^0 iPercentage, 百分比0 c8 d* \8 g+ a" Q
Percentile, 百分位数4 V* b& H& Q0 J/ i& m; Y! {
Percentile curves, 百分位曲线- O6 y) u# s4 z. H# }
Periodicity, 周期性
* M. ], A- ^# {6 ]Permutation, 排列
, l, q6 V1 J" ?$ |6 WP-estimator, P估计量& i( v: ]) j+ W8 Y
Pie graph, 饼图: T, G4 o/ t3 i, m" E7 v
Pitman estimator, 皮特曼估计量1 C4 E8 ^+ F. E* }
Pivot, 枢轴量- y% e: h L% U$ \* Y+ S( V
Planar, 平坦7 c* o1 O: t* W1 {4 h4 L
Planar assumption, 平面的假设
( R, T; @0 e' F9 q% g3 j' P) A3 vPLANCARDS, 生成试验的计划卡, {: M2 x6 m! Z+ \
Point estimation, 点估计4 `, ^3 J$ q! B
Poisson distribution, 泊松分布
6 O0 k5 y' d8 O# GPolishing, 平滑* l1 b3 O& T5 R, T! r0 `
Polled standard deviation, 合并标准差/ U. S( s f" ]5 O7 O/ a/ ^- Y8 U
Polled variance, 合并方差
/ M9 K. f$ W' C8 G5 U# b, n4 NPolygon, 多边图
& m3 _1 q* Q7 ^, lPolynomial, 多项式; d4 l, F, g' M/ g4 a0 \1 Z
Polynomial curve, 多项式曲线
& ?6 ~3 h: _: e$ DPopulation, 总体% h- |0 V4 I7 V3 g5 R
Population attributable risk, 人群归因危险度2 f& F" Y' B% |7 D; u
Positive correlation, 正相关
( ?0 Z* l: ?' W; SPositively skewed, 正偏
+ f u$ X7 u3 c c. ?Posterior distribution, 后验分布
2 l0 y3 j. d9 G4 GPower of a test, 检验效能
( ^. a# c9 L& L9 J& ]" h O5 TPrecision, 精密度' o) a4 Y6 X% v j+ {" I; }0 L
Predicted value, 预测值" e! M" Q7 H) @. Q5 x9 C4 {' C! [
Preliminary analysis, 预备性分析9 E/ P4 e* u0 [, u l/ D
Principal component analysis, 主成分分析% } v2 ]: L- U* ]) v
Prior distribution, 先验分布
1 f5 P) R# y; @! F6 ^5 Q' mPrior probability, 先验概率4 r/ E3 f q6 j2 ~
Probabilistic model, 概率模型
1 ?, b& D/ U4 T6 o( h- d- x8 C3 I; }probability, 概率
! o' M. C& a( e* M- ^3 ZProbability density, 概率密度
: K% x# V) m9 N. F; _7 w6 D+ pProduct moment, 乘积矩/协方差$ u3 }" ]2 q5 q( G) n
Profile trace, 截面迹图
% @. i8 K3 b. F/ JProportion, 比/构成比- f# _3 F. v5 J- c* z6 F+ h, J5 d: x
Proportion allocation in stratified random sampling, 按比例分层随机抽样
0 _! R* b% V# J0 @% M% eProportionate, 成比例
- c" I; q5 `7 [* w9 y0 xProportionate sub-class numbers, 成比例次级组含量* A7 Y4 D1 W3 g: ~9 ]& Y* Y
Prospective study, 前瞻性调查
1 w& R: g4 v9 e( |: T' o4 s3 |Proximities, 亲近性 " b$ B6 Z5 |. d7 g9 u5 H
Pseudo F test, 近似F检验+ y! D8 ^ N2 _$ i9 y
Pseudo model, 近似模型8 r( g8 V, \( h
Pseudosigma, 伪标准差
5 u1 s. B/ h$ r1 F: ~ w( R! hPurposive sampling, 有目的抽样# W0 v& @7 @$ Z4 L
QR decomposition, QR分解 c Z* i) K; b1 Y
Quadratic approximation, 二次近似0 s) T$ a, P7 D! t
Qualitative classification, 属性分类
2 p) U/ p5 d7 p' j8 @8 P( kQualitative method, 定性方法
5 I9 ^: I6 |9 b9 s; z2 E0 g: R- F* eQuantile-quantile plot, 分位数-分位数图/Q-Q图
- p9 c1 J" u7 w- c4 @Quantitative analysis, 定量分析7 p9 u& U4 x1 a$ g6 [$ _2 v
Quartile, 四分位数
9 H7 @* ?1 o$ N9 H( FQuick Cluster, 快速聚类
9 B; }: l9 z' ^5 L4 [8 ~- [Radix sort, 基数排序
; h% Q7 K, g, ?$ I3 hRandom allocation, 随机化分组
. w, G [2 b. o( \4 B! URandom blocks design, 随机区组设计$ X: Z0 {2 T% Y& i9 F3 H
Random event, 随机事件, w, J! [! o4 R8 l) v6 i, t' @
Randomization, 随机化
+ t0 Q/ z) u) s E( F( mRange, 极差/全距
: z% ]9 g+ H* J( v6 D! `) w/ cRank correlation, 等级相关
1 s: W* G/ v0 x# _Rank sum test, 秩和检验
2 H; Y7 r2 G7 YRank test, 秩检验6 L/ |- U: T% B5 H$ U
Ranked data, 等级资料
6 a/ e" R4 Z: l8 O- _4 qRate, 比率: y- g8 J! W' ]1 G6 W
Ratio, 比例
+ F% T% i u$ x5 U: ~Raw data, 原始资料
6 {1 w) x/ y/ sRaw residual, 原始残差& N+ \# g! ?2 \9 w3 u8 C" p
Rayleigh's test, 雷氏检验: o6 x; w1 a1 G, ~( f" F. }
Rayleigh's Z, 雷氏Z值
- p6 j4 D* f( |6 j: D% v' RReciprocal, 倒数2 R6 R+ b% V& a8 u
Reciprocal transformation, 倒数变换
/ I h9 w/ k$ l8 v TRecording, 记录
% N. m) m, W. }( d0 SRedescending estimators, 回降估计量; r; Z' y, b5 z! ^& t. ?
Reducing dimensions, 降维
1 Z! m9 s' }$ u5 W4 L$ u( W5 ARe-expression, 重新表达
- h* t& E* n% V: MReference set, 标准组
% `6 X4 F5 K$ k2 H8 _/ PRegion of acceptance, 接受域
l9 O. e8 ?) a" O+ ~, ~0 c( \Regression coefficient, 回归系数
( ? H3 F% ^0 U4 v4 t/ ]Regression sum of square, 回归平方和
1 P" [7 f% X5 y9 h3 xRejection point, 拒绝点0 F4 n% C5 q7 q2 l0 W
Relative dispersion, 相对离散度: O. N5 g+ B, _% ~! ~. @
Relative number, 相对数
' v( }/ |% ~9 ]5 ~; G( U8 Z* v1 yReliability, 可靠性
/ L9 C; v- |# D) d0 d/ `5 K" ]Reparametrization, 重新设置参数
9 |+ @& x6 P1 KReplication, 重复
8 S7 u" I3 n& K& _( x: h4 T* P' |/ F; aReport Summaries, 报告摘要
! m9 |- _ n- w! ~# K5 kResidual sum of square, 剩余平方和 r5 R( W% Q3 ?. ?% V1 Q; X
Resistance, 耐抗性) y' a! z- U! R; W' w
Resistant line, 耐抗线$ S, u: i7 D' {1 ^6 }5 \
Resistant technique, 耐抗技术6 M' k! Z) a% O/ D1 A5 d1 h6 m
R-estimator of location, 位置R估计量. {! Y) o0 u7 H; F4 H
R-estimator of scale, 尺度R估计量- w6 A0 V; B* f2 r& j
Retrospective study, 回顾性调查
, _# D* f/ b2 E" c$ rRidge trace, 岭迹
( T O+ ~* n. s6 G" `Ridit analysis, Ridit分析8 r7 C& x( U" J/ g8 x
Rotation, 旋转1 A# q' I0 ^: r/ U. Z; [
Rounding, 舍入
1 j0 F& {9 F" h/ TRow, 行- x3 R( J6 P; e7 H* L1 \- j5 v
Row effects, 行效应5 J" {" C) N$ c" u
Row factor, 行因素# L1 _7 H/ q1 f- K6 K7 b
RXC table, RXC表
/ ]# U5 b0 j% }Sample, 样本- }7 z+ U2 _; i5 {- g3 I% T
Sample regression coefficient, 样本回归系数
) V' l0 X8 v( q" ^' h7 O( ~Sample size, 样本量
8 j: I2 [8 N+ g" f0 w& USample standard deviation, 样本标准差7 W+ o1 ~1 ^, e- q) |: L
Sampling error, 抽样误差
7 k. L: Z: a; JSAS(Statistical analysis system ), SAS统计软件包. J) V" H1 H. H# J0 M) O
Scale, 尺度/量表
6 Q8 j% _6 o/ y: n" Z4 v8 `! [Scatter diagram, 散点图1 {$ F4 o+ F& E) \/ \/ f
Schematic plot, 示意图/简图) _5 o' F( M' z2 w' f! _9 Y
Score test, 计分检验! ~' h2 f1 j, J5 W
Screening, 筛检" Q$ d1 [3 d' P% J+ f/ v2 X( X
SEASON, 季节分析 9 T# u* `. y+ L0 q$ f) [& R
Second derivative, 二阶导数
1 z0 F7 ` q9 Y5 }/ ISecond principal component, 第二主成分/ z! a/ l7 t8 K# l# M* U8 S
SEM (Structural equation modeling), 结构化方程模型 $ f* H" h) r5 z: o0 B
Semi-logarithmic graph, 半对数图
- M* K9 [' ^- [Semi-logarithmic paper, 半对数格纸1 @. E0 K1 t6 @
Sensitivity curve, 敏感度曲线0 L0 e, }0 r& p
Sequential analysis, 贯序分析; Z) g" U; N: x0 O) Q7 E6 d
Sequential data set, 顺序数据集
1 o; h) k$ t9 f* d, iSequential design, 贯序设计
, H8 D4 Z- k/ T$ hSequential method, 贯序法+ c+ M, K$ ]( A+ H9 X, o: p6 B8 l
Sequential test, 贯序检验法
1 X9 a- ?* z5 B3 ASerial tests, 系列试验
3 a7 Q" O; b: R8 Q/ l$ {3 [3 {8 ?Short-cut method, 简捷法 % S; l! o# h4 T# _/ ?
Sigmoid curve, S形曲线
! L4 {" T) A4 M6 N0 DSign function, 正负号函数7 b ^( T4 X6 q
Sign test, 符号检验3 m$ o/ B: c4 F9 r& G+ N5 G
Signed rank, 符号秩 O! a6 b3 C0 y( K6 A2 N* C
Significance test, 显著性检验3 @% d" V ~5 {9 Q# e0 x4 u9 G
Significant figure, 有效数字
' |( z8 D, @% A1 V8 iSimple cluster sampling, 简单整群抽样, [" r/ \. _2 a5 l
Simple correlation, 简单相关
; {5 w* H- n6 H8 f& w8 X6 n6 [Simple random sampling, 简单随机抽样# l" M$ l, u, m0 {2 T4 |5 K
Simple regression, 简单回归; G5 E' F, K# [. i; `: Q
simple table, 简单表" g' R4 I* K: o- V* f
Sine estimator, 正弦估计量4 h& A R' J Q
Single-valued estimate, 单值估计
/ } V+ b/ E; r+ s) [Singular matrix, 奇异矩阵
. v1 Q- P5 j/ H+ d: a0 g. B9 bSkewed distribution, 偏斜分布2 S) G i- U8 p4 M8 O7 h
Skewness, 偏度) L; ~4 D* y0 P; Q$ p
Slash distribution, 斜线分布
: K& z" N0 h1 Z; u( FSlope, 斜率! L6 s$ j, z" U. b3 z0 v
Smirnov test, 斯米尔诺夫检验
4 Z7 t' _* H4 k9 F& X; ?+ v5 QSource of variation, 变异来源
$ i0 t% U$ f4 x0 GSpearman rank correlation, 斯皮尔曼等级相关* u( E4 Q* M0 J, F
Specific factor, 特殊因子+ m; w& L5 g: u% Y6 m1 m. t Y) D
Specific factor variance, 特殊因子方差
: J C1 V" j1 w2 y2 f3 _Spectra , 频谱
$ J. q2 E* L6 z3 s3 ?2 SSpherical distribution, 球型正态分布! R' j% B. w1 `* g2 z7 d1 A" U
Spread, 展布2 b/ p4 M, y. x7 H# \/ ~
SPSS(Statistical package for the social science), SPSS统计软件包
5 d* k3 ^3 T& l9 ?Spurious correlation, 假性相关
8 {4 _5 b" R/ d5 oSquare root transformation, 平方根变换! c& I3 S* p( O
Stabilizing variance, 稳定方差0 f) | F$ r# E/ T
Standard deviation, 标准差: @3 m W! G- C" Q: E' k% n k
Standard error, 标准误
1 `/ v5 {& h, @. y Q$ E, M" S7 sStandard error of difference, 差别的标准误 U F9 \5 k+ A, w$ G5 ?
Standard error of estimate, 标准估计误差7 k# z/ e8 F. K, `& R( j& D( ^
Standard error of rate, 率的标准误; j" K' i8 v! E H
Standard normal distribution, 标准正态分布5 d4 N) A; V+ G) ^" \
Standardization, 标准化
4 Z* c: L, l5 h- t: iStarting value, 起始值1 Y2 x' ]5 N# d4 L; u9 A7 Y
Statistic, 统计量9 C% x6 M+ p" E9 @% o
Statistical control, 统计控制
$ g: T6 o2 V: ], t) |: ` |8 KStatistical graph, 统计图
9 U, k* |$ f4 M. }7 ^' dStatistical inference, 统计推断
1 ?8 ~" q# N6 { K# V* T/ j: {Statistical table, 统计表
/ _+ {" {7 ^* v- [# ?" S2 M% D4 aSteepest descent, 最速下降法; {1 j% I+ k! a) B
Stem and leaf display, 茎叶图. y% h, C$ q7 i4 K- R D: [+ O
Step factor, 步长因子1 _( c+ r: D: l- L: a; D0 M3 ~" b2 Z( p
Stepwise regression, 逐步回归9 _ c* ]- A! X* p: e$ o
Storage, 存2 ]) S2 \9 [: ?( ~
Strata, 层(复数)% Q7 k% _* I7 K& h3 m0 l
Stratified sampling, 分层抽样
8 i& b v9 A- A8 @Stratified sampling, 分层抽样
9 Q8 d* K8 E/ B; l5 e4 _8 P/ W zStrength, 强度# Q3 P% [0 H2 A6 F& B+ T Q
Stringency, 严密性- r% `# S/ @+ |' e! ?
Structural relationship, 结构关系
3 w( p2 v0 F( k+ ?Studentized residual, 学生化残差/t化残差% H# ^ N# ~1 e$ I
Sub-class numbers, 次级组含量3 r- ]0 V2 c1 r* K! L; Y: y
Subdividing, 分割% g; b% u! B P5 S8 c+ u, ~
Sufficient statistic, 充分统计量( n6 G) i7 b9 {2 N6 Y
Sum of products, 积和
& @, t( ~- U; bSum of squares, 离差平方和7 J( k8 |, N. ~! m0 z! m$ ?
Sum of squares about regression, 回归平方和% F/ Z$ G! r1 K; {. { s! ?
Sum of squares between groups, 组间平方和! O$ @% y/ A) k- G' ?
Sum of squares of partial regression, 偏回归平方和7 P: S9 E4 k" |( H
Sure event, 必然事件% Y: N( {' U! `" t
Survey, 调查
! R: ^ x3 M& y5 i: U d7 sSurvival, 生存分析/ u7 A2 `; ]. ^1 w; n
Survival rate, 生存率9 n. J) @+ u' ]! c3 C9 {. o# y
Suspended root gram, 悬吊根图
6 n% Y* T1 ^% Y7 JSymmetry, 对称3 H& {7 w8 X$ \
Systematic error, 系统误差
, n3 P) O9 r+ f- u ~3 KSystematic sampling, 系统抽样
+ v7 T6 |1 M$ Z, B7 STags, 标签
' e3 K2 q8 R1 U: p* zTail area, 尾部面积
( I. r& J" D3 z2 mTail length, 尾长! U8 s& c/ k4 x# K6 A( r
Tail weight, 尾重
7 d" q( X7 g) N: LTangent line, 切线+ W$ e5 E2 y: {) O
Target distribution, 目标分布. v4 i( W& U1 V$ w, V
Taylor series, 泰勒级数
& x- m+ z! G" b- i4 uTendency of dispersion, 离散趋势
/ u+ f+ n# @/ \9 U. k* x) sTesting of hypotheses, 假设检验6 x% Q; r& L1 w& \
Theoretical frequency, 理论频数
7 a% M8 E7 }/ v9 `Time series, 时间序列3 B9 |, `3 \1 b- x; I) f# ^
Tolerance interval, 容忍区间
7 T# X6 Q+ y) d2 LTolerance lower limit, 容忍下限7 C6 F* M* [6 G! m
Tolerance upper limit, 容忍上限
7 t/ p# d; G9 }$ jTorsion, 扰率
+ S: @: F$ }( s8 J2 ?' P; sTotal sum of square, 总平方和 M2 f, Z% R5 r* i& C* B% t/ O9 ]
Total variation, 总变异
% t- [: \* L' nTransformation, 转换
& H* Y$ H$ W) D5 x# l. \4 GTreatment, 处理
. a( }+ m7 ^/ b7 X- ^! ETrend, 趋势
8 ?* n' U3 r; @+ d2 u L- R9 d+ ?Trend of percentage, 百分比趋势: I2 E$ x# }4 u& P
Trial, 试验
$ ]6 I$ I9 s* I: jTrial and error method, 试错法3 b3 G* ?" p5 y6 u
Tuning constant, 细调常数. r0 V' i' Q# f- n3 E: ~
Two sided test, 双向检验
a* y3 c! M* A& r3 NTwo-stage least squares, 二阶最小平方/ l: j7 \- T: @* b
Two-stage sampling, 二阶段抽样
9 ]# y4 O* M: U1 [Two-tailed test, 双侧检验* J" \* g/ P6 q8 S7 l D
Two-way analysis of variance, 双因素方差分析
0 v% F2 |' j2 I! O% y( F# gTwo-way table, 双向表5 x) k. I* T C8 W
Type I error, 一类错误/α错误
r9 u$ w# [% Q. t# U! NType II error, 二类错误/β错误
m' O- t0 U' L* H- B! w; Y1 KUMVU, 方差一致最小无偏估计简称7 R4 Z7 R# O( L9 e' p2 M$ ]
Unbiased estimate, 无偏估计
$ X ]2 {8 Y- vUnconstrained nonlinear regression , 无约束非线性回归
. W7 p p8 K1 yUnequal subclass number, 不等次级组含量/ H( a4 n- {( z; \/ T0 S
Ungrouped data, 不分组资料% b& X" g- _$ X( e. S, L7 O
Uniform coordinate, 均匀坐标4 r9 V6 j. ~2 s& j0 U* _& `& W
Uniform distribution, 均匀分布% L" D' L/ V% l
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
' r6 M* N, }) J5 Q& J. CUnit, 单元
! E; E( Z1 v6 ^" D. a2 M4 mUnordered categories, 无序分类' Y# Q! t' ~$ s" Q
Upper limit, 上限
8 }/ l6 s( t- W: L j( @Upward rank, 升秩% ]( F+ Z1 [5 j
Vague concept, 模糊概念
1 R) X$ A, V, y' \. y+ ]Validity, 有效性
6 _! l# t6 }! U x L: ~VARCOMP (Variance component estimation), 方差元素估计6 N5 j3 k. ?+ X9 M( |; ^0 c
Variability, 变异性+ m: H( c0 ]5 K9 d) I6 x6 A
Variable, 变量
7 l3 M3 Q; m* R R& \6 ]# NVariance, 方差
: [0 n6 i0 a# Y9 B4 j u# VVariation, 变异' m0 j" h1 q, r) \9 u; Y
Varimax orthogonal rotation, 方差最大正交旋转
9 Y5 [2 l( B5 u. G, JVolume of distribution, 容积
J0 @/ i* s# V' `% WW test, W检验2 J$ @# G" c: i1 j9 A
Weibull distribution, 威布尔分布2 r5 {9 k7 b9 v& K* R
Weight, 权数8 Y, Z4 ^. d, [- t
Weighted Chi-square test, 加权卡方检验/Cochran检验: \! U3 J2 E% \% [! k% ]8 H
Weighted linear regression method, 加权直线回归# M8 O8 X) b2 U; E" z2 l2 |
Weighted mean, 加权平均数
& O5 P/ n6 Z5 _% r' Z# S2 ^% aWeighted mean square, 加权平均方差/ y) x+ Z9 D( `7 x
Weighted sum of square, 加权平方和! `8 [/ G# `4 d2 P8 ]$ W4 v8 x
Weighting coefficient, 权重系数
. e1 U" Z& w5 N! NWeighting method, 加权法
h/ A0 }% c. N' W5 v9 i: ?( ZW-estimation, W估计量/ A. L |) R* C5 E' H0 N" p' c
W-estimation of location, 位置W估计量( k, i A: a/ K: Z1 l7 ?0 k
Width, 宽度% g( [+ U6 r' S o, S7 J' @+ X
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验1 I- G* G4 g' P' q- S! H& Z3 y( `) B# s
Wild point, 野点/狂点 [- e+ e; G: n
Wild value, 野值/狂值$ T w4 ] O( p$ V, S; f. @6 l
Winsorized mean, 缩尾均值3 P/ M7 E& V4 K4 b0 ^/ [9 b- x1 y
Withdraw, 失访
' x0 ^5 T/ E0 s H9 jYouden's index, 尤登指数
: q( v% T/ k) W& O; cZ test, Z检验5 z8 d0 R9 K4 z4 ^, ^. c- h
Zero correlation, 零相关
) n6 ? n2 a2 h9 B9 cZ-transformation, Z变换 |
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