|
|
Absolute deviation, 绝对离差3 {4 B0 l$ z0 i
Absolute number, 绝对数4 |1 b; c- `+ {9 u
Absolute residuals, 绝对残差; @% ?) V! t0 A& `! I6 Z
Acceleration array, 加速度立体阵
, w& P3 l; a, i8 D [; b, ~2 aAcceleration in an arbitrary direction, 任意方向上的加速度
/ E' c: R5 v2 p- F! KAcceleration normal, 法向加速度
9 M; i+ K+ `, G6 yAcceleration space dimension, 加速度空间的维数
5 z* O4 w7 V8 I1 ?# L E jAcceleration tangential, 切向加速度+ `' c. L: T( c" [& `$ p% y- Q
Acceleration vector, 加速度向量
1 v1 P% a5 h2 m( \% s3 m% ]: mAcceptable hypothesis, 可接受假设8 K( K. Z4 E9 U8 M
Accumulation, 累积' E" x8 j. P& J3 e
Accuracy, 准确度
. ~0 C; y" d1 V. ]& c: I. _# UActual frequency, 实际频数
/ F2 y. H. `' g+ G% R! H/ PAdaptive estimator, 自适应估计量1 \/ R8 ^9 q$ L4 z+ ]2 c7 I6 \
Addition, 相加
$ a: N9 t6 Y2 n. KAddition theorem, 加法定理
n0 k! ^9 m8 x- D4 d( aAdditivity, 可加性
* t; N( n# H- Y+ [7 c/ c+ [. `. [* DAdjusted rate, 调整率# S" }3 y, k1 o5 G
Adjusted value, 校正值; j% Z+ x- M! p
Admissible error, 容许误差- @! c- B% Z j8 u0 n
Aggregation, 聚集性: T6 D* W( @. _6 \% W' Z" _
Alternative hypothesis, 备择假设
; {5 H+ z E I; g) `( ~: SAmong groups, 组间( R) E2 Q# G: t3 [0 H
Amounts, 总量* w' D$ j9 ^3 O, J) E
Analysis of correlation, 相关分析
9 ]+ Z) Y7 H& l1 b% }Analysis of covariance, 协方差分析0 l8 W* U2 d2 t
Analysis of regression, 回归分析
+ K# a* {: z" R1 {) y6 MAnalysis of time series, 时间序列分析; K0 k7 T2 B0 l' ~
Analysis of variance, 方差分析; Z" e* j# B( Z0 N5 `' `# N; H, g
Angular transformation, 角转换 [+ ~+ X! U: F
ANOVA （analysis of variance）, 方差分析
3 k/ c4 X1 K" u8 B2 E" {ANOVA Models, 方差分析模型9 q( n" {" B4 J# n
Arcing, 弧/弧旋1 J7 x+ L; L" a$ l5 m
Arcsine transformation, 反正弦变换0 O+ [# D+ Z$ ]$ i, f3 S
Area under the curve, 曲线面积0 x& q% b9 ~$ W% u5 h8 h2 v% g. w% v
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 ) L( N* X9 g Q/ G) ^" ?. F8 z5 t; S9 T
ARIMA, 季节和非季节性单变量模型的极大似然估计 q' x! ^- }: ]0 K# m
Arithmetic grid paper, 算术格纸4 _, E' f3 t+ Z2 X5 a! c$ o7 s
Arithmetic mean, 算术平均数
8 ^! U: l7 s3 Q1 Y7 e3 m" a6 K* WArrhenius relation, 艾恩尼斯关系% ~/ S! Z2 b' h; c/ d6 r
Assessing fit, 拟合的评估
2 t! W: f P0 DAssociative laws, 结合律2 N, e8 @- I; G8 v
Asymmetric distribution, 非对称分布9 A1 G' |! {: C* h
Asymptotic bias, 渐近偏倚
. P2 P/ F4 S! `. b$ FAsymptotic efficiency, 渐近效率- U/ U: r4 v7 @" \+ Q+ ~
Asymptotic variance, 渐近方差& z/ q8 U3 x: e& F7 ]! i. t
Attributable risk, 归因危险度7 D8 W; ^# m/ D$ ^+ e2 F
Attribute data, 属性资料8 Y2 B, |5 B. u' |
Attribution, 属性" W) T6 n3 d( i& K
Autocorrelation, 自相关
; |8 ~& P6 u0 ^; |" L0 [1 KAutocorrelation of residuals, 残差的自相关/ x7 Y4 C4 s5 t; v) Y4 y+ r. r( }8 ]+ l
Average, 平均数5 w) `" Q$ f9 w( [$ \- x$ `, y8 j
Average confidence interval length, 平均置信区间长度
r9 p; q5 b) Z9 eAverage growth rate, 平均增长率
/ ^+ `8 ^$ h1 S8 T# k$ d* q3 d* XBar chart, 条形图' V; t& @; q6 ~0 m/ g- E
Bar graph, 条形图, J$ A0 I9 c+ _# w4 w7 T$ ~( _
Base period, 基期
" p6 z* @: R5 I9 c+ h5 h1 lBayes' theorem , Bayes定理( S& _/ o5 y- w# s
Bell-shaped curve, 钟形曲线3 o3 R. o9 A2 E+ ^3 f7 U. M
Bernoulli distribution, 伯努力分布- c% ~+ E1 m2 d
Best-trim estimator, 最好切尾估计量
7 V5 g2 h- W( M. s, e5 t' Y: aBias, 偏性
( L9 d. Q% c5 {. F1 C4 I, nBinary logistic regression, 二元逻辑斯蒂回归
' M" Z8 q6 U( V; eBinomial distribution, 二项分布
; x9 k! p4 O" ?0 c* u- t5 n. H/ A" mBisquare, 双平方
1 {* x! ^4 X1 u% V" F& K6 ~Bivariate Correlate, 二变量相关! O5 |3 w" b1 F' q
Bivariate normal distribution, 双变量正态分布0 v3 T0 L" T7 ?5 B/ R1 Y7 C
Bivariate normal population, 双变量正态总体
8 j$ Z8 N8 [ S; T& q0 Z9 ?# [Biweight interval, 双权区间# w1 r+ D' y) a% d X5 o
Biweight M-estimator, 双权M估计量
/ {% C _' `! PBlock, 区组/配伍组
' Q6 g `4 z+ y3 z iBMDP(Biomedical computer programs), BMDP统计软件包
! ?. k4 v, h$ l. aBoxplots, 箱线图/箱尾图1 Q5 f+ f" l6 l- |. i
Breakdown bound, 崩溃界/崩溃点" R% n- @2 ]. C6 l# {7 {
Canonical correlation, 典型相关 y4 Y8 I6 h: q" @! f ^; K
Caption, 纵标目
+ r8 q! a6 S# c* l- U! c1 V4 _Case-control study, 病例对照研究# P& l0 K+ k5 |, x8 d6 z
Categorical variable, 分类变量
6 m5 k# h9 e: PCatenary, 悬链线
6 w$ p" A% T* H* iCauchy distribution, 柯西分布' M9 m; B& N5 |* j
Cause-and-effect relationship, 因果关系6 T: S; V# r- c+ L& w; F
Cell, 单元/ l' N) J8 b8 F
Censoring, 终检1 k2 D& t9 D2 I, o( }/ l7 w! O6 w
Center of symmetry, 对称中心
; G2 }; P$ b- f c" c2 x4 zCentering and scaling, 中心化和定标4 ^' ?2 x) h0 F2 f: ~! D$ N
Central tendency, 集中趋势
* j h4 K+ b) \% y/ kCentral value, 中心值
/ W' n( p/ ^ d8 k; q; @ eCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
) G- I$ x; Q x6 [7 yChance, 机遇
1 O# a% R8 Q# a9 C. @Chance error, 随机误差' o) O0 ~) {) `4 ~! ?
Chance variable, 随机变量( e& ]) e3 C" v. z" Y$ g- `3 g& p
Characteristic equation, 特征方程! y0 y1 r; C8 m2 z; N
Characteristic root, 特征根; d8 P a9 R) I1 X$ G+ W
Characteristic vector, 特征向量: A: d# C6 r4 Z1 Z% k
Chebshev criterion of fit, 拟合的切比雪夫准则4 ]) n2 i( ?" r4 F) L1 d3 W
Chernoff faces, 切尔诺夫脸谱图
: x D( p7 V, i% D) v8 Z2 WChi-square test, 卡方检验/χ2检验/ o$ D' s0 s# N( W
Choleskey decomposition, 乔洛斯基分解- _6 z6 r W; D T6 `1 C
Circle chart, 圆图
' L1 y1 ^' V2 @$ {: V5 J8 d9 `& J" iClass interval, 组距
& E) }/ r) I s$ w: rClass mid-value, 组中值: ~3 d) h3 d; q) D T
Class upper limit, 组上限' ?( {: p# j% L4 v* \4 l e( X
Classified variable, 分类变量/ s$ t& o+ |! O& H6 \
Cluster analysis, 聚类分析
( B1 x/ J0 [4 Z }! QCluster sampling, 整群抽样* \8 Q3 I# g9 x% p: e9 h
Code, 代码& P' G6 h6 }1 f' h
Coded data, 编码数据
* `1 S5 A$ B. w1 O: S/ C9 J7 F* mCoding, 编码
/ A1 |+ K% H; |7 {8 l; q+ SCoefficient of contingency, 列联系数6 ^$ T* v- m# @) O% A. D7 L
Coefficient of determination, 决定系数
- N! m/ w4 v; P2 Z0 s3 a) h0 FCoefficient of multiple correlation, 多重相关系数
% {6 ?, e7 l+ s" vCoefficient of partial correlation, 偏相关系数
# ~9 b( R# w, F; I4 }3 w& w/ BCoefficient of production-moment correlation, 积差相关系数
9 [* u4 p1 _$ ]% h: n- T- h4 dCoefficient of rank correlation, 等级相关系数8 B& Y- y3 L1 I* _$ G8 ^2 G
Coefficient of regression, 回归系数
+ C! Y- L! R. p5 b/ PCoefficient of skewness, 偏度系数$ n7 ]" |) X% ~4 z9 C2 D
Coefficient of variation, 变异系数) b) C) a- N, H* B2 ?
Cohort study, 队列研究
& `3 [* Q3 S* nColumn, 列; Z# W; |$ g9 d: h0 D K: d
Column effect, 列效应; `% J2 T& l9 U- r
Column factor, 列因素
5 ^! d6 b4 ^ [- F8 LCombination pool, 合并9 M Y8 u# @% I" H8 V$ B1 h8 A2 l
Combinative table, 组合表' X, j$ S- z; B* O$ r9 K
Common factor, 共性因子& \8 ^- T+ T$ I3 V0 S
Common regression coefficient, 公共回归系数! ~9 q, s L. a4 u7 V# y: c
Common value, 共同值
Y' z0 |1 Q0 J: V; ^, k) c/ lCommon variance, 公共方差
' k3 Q9 y% r: N; s) E5 MCommon variation, 公共变异
3 n# u+ I! l$ v' H& Y/ |Communality variance, 共性方差( k8 p$ @( A9 x/ ^% P
Comparability, 可比性
& S. y$ \3 C1 W8 W- [+ OComparison of bathes, 批比较) @$ z0 |2 ^8 J6 ~2 R
Comparison value, 比较值
9 \3 Q ^6 E8 [9 U) c8 a0 k$ p: {Compartment model, 分部模型
. g$ U9 N3 s4 W# }' z) m8 HCompassion, 伸缩
( g' ^$ `% r9 h( p- t; GComplement of an event, 补事件
: N I, P& d9 W E* M. [Complete association, 完全正相关
9 ?, W3 v! {" V: {% aComplete dissociation, 完全不相关
4 s, q/ B' q4 E4 k0 WComplete statistics, 完备统计量
z2 P% u- M5 Z; |0 L- Z( K; dCompletely randomized design, 完全随机化设计
& h2 `- a9 v, t: p8 L2 hComposite event, 联合事件8 Z! y6 Q; \0 f# h T I
Composite events, 复合事件
5 _) ~% ?& j/ ^( ?( C' RConcavity, 凹性
/ G. `" `5 E4 K; i! CConditional expectation, 条件期望- I7 `5 R7 P$ M: D7 S7 m
Conditional likelihood, 条件似然0 O; T" O; o& E* N
Conditional probability, 条件概率
$ B% U# O! z" Y+ {/ t0 I+ H9 C7 ]Conditionally linear, 依条件线性 Y$ O& d% z, R Y2 Z9 u
Confidence interval, 置信区间
2 n/ T8 R, C% x2 q, k, e( ^9 \3 qConfidence limit, 置信限9 o" i# s" E/ \: Y, J
Confidence lower limit, 置信下限
$ w) K. ?- i9 ?# \2 nConfidence upper limit, 置信上限
( q, b' [ A* d+ QConfirmatory Factor Analysis , 验证性因子分析
7 V7 C6 ]4 X1 ?- mConfirmatory research, 证实性实验研究
" J. d/ k2 q0 e& t' Z+ [( ZConfounding factor, 混杂因素
5 ~* B1 W" {8 o2 E! IConjoint, 联合分析5 d3 {. I2 A2 x1 p ^
Consistency, 相合性) B! u8 X$ M8 k8 u- U9 g; H
Consistency check, 一致性检验6 |% B5 M/ `$ F# t$ H
Consistent asymptotically normal estimate, 相合渐近正态估计9 Z y# c7 K: }! }0 B
Consistent estimate, 相合估计
# ?+ q7 b( A" @Constrained nonlinear regression, 受约束非线性回归- u. J& I8 j U6 O) z
Constraint, 约束1 M2 j* \9 _" `$ o
Contaminated distribution, 污染分布
3 Z8 ~& G# x$ q2 u7 ^; ~; KContaminated Gausssian, 污染高斯分布
H7 |1 u. @5 oContaminated normal distribution, 污染正态分布+ | T. @$ b! {9 _1 H6 Q
Contamination, 污染/ ]) j5 R b9 ~6 N; t5 w2 H
Contamination model, 污染模型
3 _# E! c; J# mContingency table, 列联表
% M, f* c- U" N/ D7 e( aContour, 边界线
$ {+ h' o7 v6 M7 T i4 VContribution rate, 贡献率
: o4 s. E/ h% r) t2 zControl, 对照
' z' D% d7 ]. H3 N: ^Controlled experiments, 对照实验( E3 Q3 a; {: H( o/ L# l
Conventional depth, 常规深度; B; V, i/ j( c8 n
Convolution, 卷积
7 w1 ]+ e0 p7 I0 x' Y4 s7 v0 m; SCorrected factor, 校正因子
, H! p1 u7 C1 ?/ H2 s- i; t' hCorrected mean, 校正均值4 O; {7 m# S) S: F2 I' z
Correction coefficient, 校正系数
3 e' |; Z/ q; @/ ]/ g. [. ]2 cCorrectness, 正确性% Y+ Q" ~, n$ O; E# b
Correlation coefficient, 相关系数
( E& F- @9 W6 q5 e; ^" m' rCorrelation index, 相关指数
0 c _9 ]7 a6 z6 d [Correspondence, 对应% `- P( W' v5 e; w( r- [( p) o. X
Counting, 计数
: [, E6 u5 P3 WCounts, 计数/频数
; o" ?9 X# k0 A4 W8 e* _ |Covariance, 协方差
( I7 U1 T9 k" R2 ]/ r' YCovariant, 共变
0 P1 z/ q; c) |( B/ w7 q9 oCox Regression, Cox回归
" ]+ j1 A: n/ |8 P, J+ h" wCriteria for fitting, 拟合准则3 \6 E2 R' ~; g: Z0 f& E+ O
Criteria of least squares, 最小二乘准则
& F2 o' T' t! ACritical ratio, 临界比
2 I e6 I% \ _9 x% t% U7 KCritical region, 拒绝域" Z' A2 V' `) `$ {
Critical value, 临界值
0 x/ S' m$ X# tCross-over design, 交叉设计, r' G. H, A* p2 V* q. O
Cross-section analysis, 横断面分析$ j! F( z, y6 u
Cross-section survey, 横断面调查
3 Z+ O# A' Y8 aCrosstabs , 交叉表
, e. G& [% u0 X$ D' y0 j; GCross-tabulation table, 复合表
8 g1 U- X6 m: V. d1 ^Cube root, 立方根$ k; n: Z7 k' N0 `% C. k
Cumulative distribution function, 分布函数
! d, H# a: w9 {Cumulative probability, 累计概率
u* G% ~( b0 u3 r! J; @. r- K! UCurvature, 曲率/弯曲& V0 \& z# ^5 w3 V
Curvature, 曲率
0 c# `: d* [/ O% k/ sCurve fit , 曲线拟和
4 i; l, ^* B6 O9 z# v* vCurve fitting, 曲线拟合0 J/ j, R& }4 v w/ f; y5 n
Curvilinear regression, 曲线回归
+ u2 |1 S4 `& g* U7 o& RCurvilinear relation, 曲线关系! F1 G2 A" _! l! |* J3 r
Cut-and-try method, 尝试法. Y9 `) ?2 ?& Q2 C; z7 q
Cycle, 周期$ h# ]7 T. a- Q$ W+ u* a2 v2 u
Cyclist, 周期性/ m [1 F! h7 S9 ?% z" z |7 H
D test, D检验
6 N" a7 N! W- T* W. G8 Q- pData acquisition, 资料收集
: J! B: |; x, `4 L7 CData bank, 数据库% [2 d* u/ {: L" d! M
Data capacity, 数据容量9 g, ?& b* X; V
Data deficiencies, 数据缺乏
6 V6 ]& F7 e( [ u. C `6 a5 f+ |Data handling, 数据处理7 Q3 I7 k) j3 A1 [8 a
Data manipulation, 数据处理
+ W3 a. x& i q G: NData processing, 数据处理
/ b( _- {" N" m9 o: j h$ h7 x5 E% HData reduction, 数据缩减
, t- M+ z2 x9 [- f' sData set, 数据集( L3 D' E/ {& B# [$ H- k
Data sources, 数据来源
- n! z( [# c% h6 ?7 E2 A* ]# [Data transformation, 数据变换* v- d& T; d2 u2 z
Data validity, 数据有效性: ^2 }& Q0 _4 Y ?+ e$ G/ D
Data-in, 数据输入" ~! A% M7 y8 n8 k% e6 \' v: Q% T
Data-out, 数据输出
2 _9 c# n# r! g# \8 XDead time, 停滞期
( j, t) n/ n9 U5 l5 R% w+ HDegree of freedom, 自由度
! w6 _* D+ q7 g) ]Degree of precision, 精密度
$ `" Z/ W( U6 u$ G/ X2 hDegree of reliability, 可靠性程度
& K" t$ f, a, _/ Y. XDegression, 递减& j: w, A! j; @' r
Density function, 密度函数
( u+ i+ w# e: r3 s3 d6 z# u2 Q# \ oDensity of data points, 数据点的密度" {$ Y4 D7 r! L y" a
Dependent variable, 应变量/依变量/因变量
+ l. H7 s# f6 Z0 F- K/ DDependent variable, 因变量2 x0 }* e4 |. r3 b' [( L
Depth, 深度
) E5 `: Q1 v4 a8 R2 c5 L4 r' TDerivative matrix, 导数矩阵5 J" S l' {4 z2 u
Derivative-free methods, 无导数方法, y& }2 }' ~ I* C4 L$ S' l
Design, 设计
& p3 ?9 L# H0 u T- ZDeterminacy, 确定性
: |! y5 W4 X6 W3 u2 YDeterminant, 行列式+ I1 g( b e/ b7 U9 i* e9 P. P
Determinant, 决定因素
/ M# y+ D; q, ~Deviation, 离差- j' Y! e3 \! Q i) o _
Deviation from average, 离均差
! O$ D7 H9 ]/ X* I$ h& \* N! PDiagnostic plot, 诊断图
4 [ l' p9 W2 s9 e. `: nDichotomous variable, 二分变量
+ K# @9 O I B2 s7 c+ y& m; Z$ E5 q7 sDifferential equation, 微分方程
( ^+ M& J; u8 R# I# _Direct standardization, 直接标准化法
# W& \) s- ]. c7 _Discrete variable, 离散型变量0 j& q9 H3 {4 T. ?
DISCRIMINANT, 判断
4 _3 p2 ?) l W" kDiscriminant analysis, 判别分析
2 f% \: S: b9 \Discriminant coefficient, 判别系数
6 L; G e e* q2 I& Q! CDiscriminant function, 判别值6 @! `6 T7 f' j0 M9 `/ {8 X
Dispersion, 散布/分散度
# _4 y2 Q3 t- g# W/ ~Disproportional, 不成比例的
% T$ N9 C3 R: D& y7 \7 LDisproportionate sub-class numbers, 不成比例次级组含量! b7 [; q4 O9 C. K" u) [
Distribution free, 分布无关性/免分布
& v2 P" q" B2 M) |0 R" fDistribution shape, 分布形状
: `; Y# b* _: j2 F) ~4 DDistribution-free method, 任意分布法
/ B" j4 n* W! \; K0 h4 W( lDistributive laws, 分配律
6 K8 {) J& S7 }- N+ TDisturbance, 随机扰动项
1 g# ?0 u- q6 EDose response curve, 剂量反应曲线
% d3 X2 e1 l& r4 ~8 K. ^" _Double blind method, 双盲法8 u7 C8 }4 S- Q9 w3 ?
Double blind trial, 双盲试验" t% e5 J4 d$ Y4 e: M! {
Double exponential distribution, 双指数分布0 l, \6 n$ }. s$ \4 z) f* z
Double logarithmic, 双对数
) H5 e* j+ A' u1 x, T1 A( _1 q% UDownward rank, 降秩# }4 |+ y+ z ?4 a+ ^ `" N2 x$ w
Dual-space plot, 对偶空间图
+ @% X' j1 g, FDUD, 无导数方法9 H' _8 n& @) V7 l0 Y) r
Duncan's new multiple range method, 新复极差法/Duncan新法2 r5 c: `. H% o+ L4 g& O8 N7 b
Effect, 实验效应
2 z: w7 J6 `8 P- r3 cEigenvalue, 特征值* J/ e( B$ S: \' l
Eigenvector, 特征向量
V" X4 A: _3 n5 I3 d5 r7 SEllipse, 椭圆* c" p. b* p# s' c4 s! _
Empirical distribution, 经验分布
& F- g) m2 b' E+ ^, N/ X6 z) BEmpirical probability, 经验概率单位! r, J4 E1 d u( e0 w9 { T
Enumeration data, 计数资料% S8 P% s1 d' b, M( n$ C7 j0 t
Equal sun-class number, 相等次级组含量
: u) n5 M9 ~2 ?% I! C/ d7 Z; h$ zEqually likely, 等可能/ V# w0 |" `* v5 {% l" b
Equivariance, 同变性" I3 k+ U: ?8 B2 S7 ^) B1 x# J
Error, 误差/错误; ]. S( i" W) p9 C
Error of estimate, 估计误差6 k' g4 S, y: U1 R8 s c5 e
Error type I, 第一类错误. i0 [7 q& ?9 {
Error type II, 第二类错误: J6 ]7 o$ T* ~+ a5 Y( T9 x
Estimand, 被估量
) }2 M K5 { nEstimated error mean squares, 估计误差均方
% A# G" c, Q/ {! Q2 ~) gEstimated error sum of squares, 估计误差平方和/ V7 z# w0 \+ P
Euclidean distance, 欧式距离
* i1 k' |2 j* nEvent, 事件
l' D' K5 g$ O( pEvent, 事件
2 w7 J' J- k3 ~, cExceptional data point, 异常数据点
, ?' z9 t* S# O( ^% Y/ V& oExpectation plane, 期望平面
% w a9 F3 x6 v m4 |Expectation surface, 期望曲面, `" `' K7 H; U" k; Q
Expected values, 期望值0 {; K; g# J; I* w( @2 ]5 d
Experiment, 实验
/ w5 S v$ s: {! q8 l$ hExperimental sampling, 试验抽样' [, t( P0 f3 u/ H( B7 n4 k
Experimental unit, 试验单位/ o: s" W. D0 e0 {. T. U! L
Explanatory variable, 说明变量
0 C! I* U$ x' k" aExploratory data analysis, 探索性数据分析, [0 L; c1 {0 B* W _ s
Explore Summarize, 探索-摘要; j8 n) C+ x8 l2 X' a9 Q, L
Exponential curve, 指数曲线
0 g, K* D! K A5 K R. SExponential growth, 指数式增长; s, [% S2 ~% \) }( S+ ~
EXSMOOTH, 指数平滑方法
$ G% `2 O# [; Z* g: x% [Extended fit, 扩充拟合
4 d! d+ H6 d: ?" @/ jExtra parameter, 附加参数6 p$ Z3 P$ Q2 s. n0 i( I
Extrapolation, 外推法( h1 |/ |4 G. D& z
Extreme observation, 末端观测值+ F9 a" c k2 @4 m. V$ e S+ p
Extremes, 极端值/极值
" y; r! B& W$ _) ~5 E4 a9 FF distribution, F分布/ A# W! l; w( G2 k) K& G
F test, F检验- V: h5 c" C9 S- C
Factor, 因素/因子
' T7 G3 p9 z# W" K O$ O& M6 EFactor analysis, 因子分析
1 W& L3 n4 m3 h+ tFactor Analysis, 因子分析
+ N+ N i! d; N1 P: @/ R; xFactor score, 因子得分 ' J N3 p$ \7 c6 F
Factorial, 阶乘
8 Y) \) O, ` n. L# e7 JFactorial design, 析因试验设计1 I7 U/ k* Z+ p: x/ [
False negative, 假阴性
" X) E9 T- f0 y- y6 x3 c% GFalse negative error, 假阴性错误
' W, a, f8 Q' mFamily of distributions, 分布族
7 }% S% J- U( M& ] m0 ?# FFamily of estimators, 估计量族3 f5 Z: S3 H7 n: }* |; {6 B% x
Fanning, 扇面
0 G5 T( {" |, S$ r9 JFatality rate, 病死率4 D/ j3 D8 J- M' t
Field investigation, 现场调查
4 c/ z: L# P* c6 DField survey, 现场调查; h" {0 m( K$ v+ ^# B4 a
Finite population, 有限总体
! c4 I* g ^! X2 X0 w7 [Finite-sample, 有限样本4 F% r$ z- X+ p2 z; @/ F' O: L* ~
First derivative, 一阶导数0 U: ?' B" ]8 c: l6 h, u
First principal component, 第一主成分5 t. v2 k' j5 ]" r7 o# Q0 D% a
First quartile, 第一四分位数
& J. Q2 |& \ u9 x" x. p! VFisher information, 费雪信息量 _3 v0 W+ C2 V. Z
Fitted value, 拟合值# H6 X* @% G5 ?/ k' a
Fitting a curve, 曲线拟合
2 T+ u1 s3 t% Q1 PFixed base, 定基# n1 u. h& l' y$ {$ j
Fluctuation, 随机起伏
a/ i9 S0 n5 [1 \! F6 X( V5 ?Forecast, 预测
6 m: y' d( k$ nFour fold table, 四格表+ B: I5 \0 O! X: C8 ^5 U
Fourth, 四分点
& [* ^ w3 V% VFraction blow, 左侧比率4 J! X# k c$ [4 q; Y( b" b
Fractional error, 相对误差
/ m! F1 i1 g" L5 Y6 M+ n, r5 FFrequency, 频率
, C, k2 B6 V8 F s" WFrequency polygon, 频数多边图. r8 {4 ~& O; S$ H# I. d
Frontier point, 界限点
, B7 Y% Z n) N- t( u' \3 m7 @Function relationship, 泛函关系2 j. z! M N r9 [6 x! `( ?
Gamma distribution, 伽玛分布9 b/ |3 a4 G( [ a1 S6 M' c% B, l
Gauss increment, 高斯增量
. p9 V+ k3 ^; H& }Gaussian distribution, 高斯分布/正态分布
P, \1 V: Y% w; r" H1 ~2 \7 e2 T& JGauss-Newton increment, 高斯-牛顿增量1 S. j& Y$ q1 c, g
General census, 全面普查
0 \3 w8 } d. o9 V2 v ~6 bGENLOG (Generalized liner models), 广义线性模型 ! e' b5 x* ^* H, L$ B% \
Geometric mean, 几何平均数+ r0 E8 C* ]. e* d3 ~
Gini's mean difference, 基尼均差1 g C* T/ G! [( k$ {' p8 w
GLM (General liner models), 一般线性模型
- k3 `! a1 _4 c8 _Goodness of fit, 拟和优度/配合度+ F% M5 Y2 x9 W9 S& r* [( Y
Gradient of determinant, 行列式的梯度
/ a/ ], N6 H/ v2 O( \Graeco-Latin square, 希腊拉丁方
, F8 a/ j) b( S3 d0 x" ~( rGrand mean, 总均值
+ F) K! V; }, V. wGross errors, 重大错误( D7 `3 K. H6 S: D# h
Gross-error sensitivity, 大错敏感度
# j& E. |) Q+ y" `" XGroup averages, 分组平均# F/ z$ p7 }- |7 @ _
Grouped data, 分组资料7 `, E3 X: c. [3 T: \5 y
Guessed mean, 假定平均数6 R5 Z0 w5 E( ?' X( j
Half-life, 半衰期
3 t" T: W+ \5 J+ @. ?Hampel M-estimators, 汉佩尔M估计量1 X$ a6 I# J8 _4 L# |& G" G' n3 L
Happenstance, 偶然事件1 y+ j1 X3 F) z1 `3 I, K! m
Harmonic mean, 调和均数
5 ]2 } j ~, y, E0 \" w) HHazard function, 风险均数& ]0 ]7 |4 w) G$ S5 I
Hazard rate, 风险率1 Z: @% \8 u8 O4 W+ b; y4 H5 F
Heading, 标目
+ C4 K* s" H7 v# XHeavy-tailed distribution, 重尾分布
5 W. \& [) e. w; `. A; @, EHessian array, 海森立体阵
/ h% M; I( O4 H8 {8 }5 |$ qHeterogeneity, 不同质# y# f4 g4 c2 e. G
Heterogeneity of variance, 方差不齐 2 v$ Z, o; N/ H/ `( T
Hierarchical classification, 组内分组
/ W' t8 t, q2 V- L oHierarchical clustering method, 系统聚类法
# |6 l8 O+ k* c# ]& S# GHigh-leverage point, 高杠杆率点2 A* j! m$ J$ L3 q8 H5 u
HILOGLINEAR, 多维列联表的层次对数线性模型. A1 p% V% t$ i) \( x P
Hinge, 折叶点
5 l: {4 S3 ` `/ Z$ ?Histogram, 直方图
d9 s+ p& X0 l4 tHistorical cohort study, 历史性队列研究
9 ^9 K7 k" q, ]6 f2 j- uHoles, 空洞
* F( V" e4 O/ r: ?2 T6 `HOMALS, 多重响应分析
\+ ^6 g/ W. i7 H" a' l& t! wHomogeneity of variance, 方差齐性% ~+ \3 C* F3 G4 L( [. [8 ^& t: K
Homogeneity test, 齐性检验7 Q( X& e+ _4 ^
Huber M-estimators, 休伯M估计量
, D5 c8 d, I# g0 K. y: ]Hyperbola, 双曲线
; v( e+ K8 N3 m" ?! ^8 W: }6 jHypothesis testing, 假设检验! d, }1 _8 \' U7 b6 |0 z
Hypothetical universe, 假设总体: \; C, O/ j+ l+ O
Impossible event, 不可能事件8 N$ v% f* g# @- Z3 S. r \; l, Q
Independence, 独立性
- {/ j4 ~. v" w* l8 p) W+ T/ eIndependent variable, 自变量6 e2 G* t/ L- P1 i' o7 M# v
Index, 指标/指数
4 i [7 T* \6 @. }Indirect standardization, 间接标准化法
; c! U# {# f8 a# F* ]( t* OIndividual, 个体
2 t4 p2 @0 Z2 z" w) @( N: QInference band, 推断带. _: H. A1 Q- f: s. {" c0 ?
Infinite population, 无限总体, {6 h& A( z! G4 @/ |9 k4 A7 |( o% L
Infinitely great, 无穷大
8 ~1 W1 v' I1 o+ _+ }Infinitely small, 无穷小% e5 o4 k0 @" a; r. F+ c
Influence curve, 影响曲线1 P$ ]9 Z9 P! M, U7 H" W
Information capacity, 信息容量5 F* c* w$ n, \0 g) G' `$ J0 T0 a0 Z
Initial condition, 初始条件4 c! i0 Q3 a( d7 ]+ m2 v+ N) M
Initial estimate, 初始估计值# K8 G; o+ Y1 B6 T! ?& ]7 N
Initial level, 最初水平8 v, I! x. _9 x8 n% L, B( A9 h
Interaction, 交互作用
+ o$ H+ W5 l3 b: BInteraction terms, 交互作用项
) k+ v9 e" g8 y! o: SIntercept, 截距$ @/ I1 j# \8 H1 @* ]1 I
Interpolation, 内插法
/ ^8 r. E0 v0 k* a& r KInterquartile range, 四分位距
7 `& O( Q! l" @' s. }& e# G KInterval estimation, 区间估计
. u; m' w1 S2 U) u" oIntervals of equal probability, 等概率区间2 s+ A) H2 z/ o! K1 O
Intrinsic curvature, 固有曲率
$ J; [9 I: e/ L# f* MInvariance, 不变性
5 M7 B) ~* E' A8 BInverse matrix, 逆矩阵
; U* M' |6 F2 q" Q, S7 w0 I$ ]Inverse probability, 逆概率
% C! I3 f5 d- y1 fInverse sine transformation, 反正弦变换
& C& n2 d- K1 \) d/ \Iteration, 迭代 : X# |- Q- z% [7 v* ]4 E0 f( X" {+ G
Jacobian determinant, 雅可比行列式# ]/ ~% x! F& ~- O+ }% A
Joint distribution function, 分布函数+ I9 l' W% C- v2 a
Joint probability, 联合概率5 l! i. L! H( L" v; S% t5 O. Z
Joint probability distribution, 联合概率分布
9 _( a. @; O6 y/ YK means method, 逐步聚类法2 Y+ `0 Y3 _/ W: u7 F
Kaplan-Meier, 评估事件的时间长度 % F0 f, l. k: k7 H- M3 \: E1 _- d
Kaplan-Merier chart, Kaplan-Merier图
9 a, v+ r0 Y9 I2 {* A X! x: Y: mKendall's rank correlation, Kendall等级相关# s% A" {; s- i% k; V' u
Kinetic, 动力学
/ Q) k9 W. W$ d7 JKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验% q' P0 Z! N* ]0 m2 Z5 e* x1 `+ U2 D
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验! H" p( C) _" N( s6 i1 Z) M4 `4 B+ N
Kurtosis, 峰度0 y, @5 F, s8 G$ l
Lack of fit, 失拟
# \! p" K6 N, G. n! fLadder of powers, 幂阶梯1 Y# B& R5 W5 k; S; L, o k& C# S, |0 ^# x
Lag, 滞后
" q+ c4 E1 ^7 O, HLarge sample, 大样本
5 |: Z9 X% c9 w% ~+ Q1 z6 ELarge sample test, 大样本检验
3 G# i7 J3 t' j* SLatin square, 拉丁方6 C( z4 h8 D0 P i7 ]
Latin square design, 拉丁方设计
8 L" T# f! q! g3 cLeakage, 泄漏2 t+ }2 l' o/ S
Least favorable configuration, 最不利构形3 j5 y0 x, _1 s
Least favorable distribution, 最不利分布
' Z& K6 p1 k6 O9 l9 y0 E9 B2 FLeast significant difference, 最小显著差法
7 r" {' R$ L/ z1 z2 ELeast square method, 最小二乘法
* ?# |% M/ J) j/ U, R. I4 sLeast-absolute-residuals estimates, 最小绝对残差估计
* k$ ^+ A; B* {' Q- `& YLeast-absolute-residuals fit, 最小绝对残差拟合' C a5 s* l/ g4 i" _
Least-absolute-residuals line, 最小绝对残差线
, E' [8 Y9 o+ E! @7 h1 f1 b3 WLegend, 图例- @, a! Y9 Z, E- d$ x
L-estimator, L估计量/ j: R! A5 E: h( E& k
L-estimator of location, 位置L估计量
# M3 [- ^$ i- l( X( b! u. N% t! GL-estimator of scale, 尺度L估计量% u/ ] y/ T. J" }8 S
Level, 水平: f; i; ?/ F4 r8 J G
Life expectance, 预期期望寿命
5 B' H% ]3 y0 D/ c) }% s; oLife table, 寿命表& E$ s& Z+ T$ D0 w" @
Life table method, 生命表法
" i( E) i3 ?8 KLight-tailed distribution, 轻尾分布 n) w8 h+ w8 U, y$ S j
Likelihood function, 似然函数7 ~9 F- w* W* _6 g; D/ V& p
Likelihood ratio, 似然比( i5 q: K8 ?# C0 S
line graph, 线图
' z( q5 t; z& h3 _& t" ^& bLinear correlation, 直线相关
5 Z& A1 l$ j# a8 h& SLinear equation, 线性方程1 N5 N/ j# b- e9 S4 b$ ]
Linear programming, 线性规划
4 l$ J. j- _/ \6 R& e4 oLinear regression, 直线回归. U, C4 }& ~. k1 a9 B8 n; p t/ p
Linear Regression, 线性回归1 n3 g2 I+ u) j8 G' X0 I
Linear trend, 线性趋势
N0 x# V$ S. l2 z. u0 ~Loading, 载荷
, G4 o- `' K, u/ M9 m+ T& s( ELocation and scale equivariance, 位置尺度同变性* f' }! j+ Z4 F: z7 X
Location equivariance, 位置同变性
W4 j* ?# H7 ILocation invariance, 位置不变性) R& @1 [8 q, g! {# i1 d% z. o y
Location scale family, 位置尺度族1 t- f1 z8 q) V @
Log rank test, 时序检验 3 Y0 d. C/ v! I
Logarithmic curve, 对数曲线
( `' e# G! r9 rLogarithmic normal distribution, 对数正态分布9 |4 ?$ _6 f0 t/ x/ r! l% J
Logarithmic scale, 对数尺度' ` e. ~$ J! V* w7 l" t6 c2 {; F
Logarithmic transformation, 对数变换
) V% n4 ^4 S* s+ \- }Logic check, 逻辑检查! G* q" ]1 u$ l: G* |# `) @
Logistic distribution, 逻辑斯特分布
. t! N/ l- d) r" ^8 `4 \5 {- cLogit transformation, Logit转换
* w) h3 |# }+ W2 w7 p2 W7 D2 [4 mLOGLINEAR, 多维列联表通用模型
. h6 _7 F* _- q8 N' lLognormal distribution, 对数正态分布 A; X9 j0 f! T2 W3 q4 D, l# C
Lost function, 损失函数; M; r# E2 Z: _5 q' x
Low correlation, 低度相关. X8 R: l& H0 f% D0 d
Lower limit, 下限7 \) \# ?! L* E) J/ W# y
Lowest-attained variance, 最小可达方差: g& K4 R( B" a% v: z$ ]5 ~9 S
LSD, 最小显著差法的简称* i' z2 ^' f6 t& d
Lurking variable, 潜在变量
% l3 C0 O8 u( q2 @Main effect, 主效应- X& P! x i6 [/ q
Major heading, 主辞标目
" t/ @, y f, _' f3 Z5 [Marginal density function, 边缘密度函数
4 g8 I: w" W8 J2 p$ g8 u7 D( g9 TMarginal probability, 边缘概率/ o3 Q# B8 C5 z2 o" o2 P. A
Marginal probability distribution, 边缘概率分布% j! B7 W; [7 [! O7 V
Matched data, 配对资料1 p4 U& i+ q' T& w1 y. H5 \
Matched distribution, 匹配过分布' {/ ]6 s H4 Y% M6 j
Matching of distribution, 分布的匹配$ y$ S$ G: X! n0 p' M0 X
Matching of transformation, 变换的匹配
* v4 f6 W7 W% Y$ u CMathematical expectation, 数学期望8 e) _3 w# F2 `- D' s& s7 O# ^
Mathematical model, 数学模型
+ \2 g+ X5 Q$ b9 ?/ J. x) gMaximum L-estimator, 极大极小L 估计量
7 h! q3 s. H) F# RMaximum likelihood method, 最大似然法: l9 J6 ^( ^2 i" }
Mean, 均数% O) A& P. ?- I( T9 X* c; ]* U
Mean squares between groups, 组间均方
) k8 K0 r$ H$ Y5 F0 NMean squares within group, 组内均方5 I0 ?% h% p, g9 z/ v6 u
Means (Compare means), 均值-均值比较
2 ~. u9 e5 O# R x$ P$ @Median, 中位数
8 z& h9 E% h8 Z2 \. }0 h# ` {Median effective dose, 半数效量! g( {8 g4 `: V3 q. h
Median lethal dose, 半数致死量
1 C; r. s1 b$ w) }0 U) _! TMedian polish, 中位数平滑
, |5 w6 Q0 N2 A: o1 rMedian test, 中位数检验' G# k- A3 C. N+ r& J, ?2 @
Minimal sufficient statistic, 最小充分统计量
+ R7 R/ @/ |% | b* o- eMinimum distance estimation, 最小距离估计
3 ]% m" x& P0 U" e( _! M9 h/ }Minimum effective dose, 最小有效量
0 x9 i) _9 ?; q& u) W, \6 \Minimum lethal dose, 最小致死量
I0 n% k, L) X2 K6 O/ CMinimum variance estimator, 最小方差估计量
% E9 Y+ i: E9 l3 r" f( ^8 hMINITAB, 统计软件包
2 Q8 v+ e' e3 s& z) v7 {Minor heading, 宾词标目: _- K% e/ b: n5 w
Missing data, 缺失值7 C% K2 R; F, h9 x6 g! Q! a
Model specification, 模型的确定) J, r% H6 s) m
Modeling Statistics , 模型统计
) Z6 a" C6 S W4 p- ?+ U. m' Q2 zModels for outliers, 离群值模型& K& _2 a- S) K4 W6 B
Modifying the model, 模型的修正2 B, b1 \' x6 } h1 h b
Modulus of continuity, 连续性模" U% c! k" H. }1 j
Morbidity, 发病率 * _. c- U( ~. t( w6 `
Most favorable configuration, 最有利构形& x U, j( a" L* F0 I" C9 t
Multidimensional Scaling (ASCAL), 多维尺度/多维标度8 c r; C: v5 i. k8 W0 j8 Q
Multinomial Logistic Regression , 多项逻辑斯蒂回归
7 q0 [/ ?( K& T9 vMultiple comparison, 多重比较
6 T9 K# V% g. m5 S; P) [Multiple correlation , 复相关
& w) @3 Y7 O5 J C) N/ q, B+ U! NMultiple covariance, 多元协方差
6 X$ i& ^/ U% ?6 HMultiple linear regression, 多元线性回归
8 v! ?! x, z& g2 |9 {Multiple response , 多重选项- T1 z2 d. d Y0 M5 X
Multiple solutions, 多解
. |7 p- e: t% J& a) {Multiplication theorem, 乘法定理
8 M1 W' B* i: ~2 y0 G; H2 f1 f oMultiresponse, 多元响应6 A& E D" j) ^/ J O6 y
Multi-stage sampling, 多阶段抽样/ n) _4 T1 y: P1 @( k0 R
Multivariate T distribution, 多元T分布4 r: r$ w; u D& h+ R1 R5 {7 s
Mutual exclusive, 互不相容
3 a3 n/ M6 h$ [1 l) eMutual independence, 互相独立
. L) H, I* j8 pNatural boundary, 自然边界
8 G( _5 b$ c6 p$ ZNatural dead, 自然死亡7 O! ?( S% t: X, w9 g
Natural zero, 自然零
) @, d8 S% k2 A1 \, g$ v0 J! zNegative correlation, 负相关
+ P; K3 N; y# r! j2 _! e& F3 oNegative linear correlation, 负线性相关
1 W% w$ O" s1 h, S4 H8 [9 `Negatively skewed, 负偏
* S `0 f8 f1 f2 ] a3 XNewman-Keuls method, q检验8 K5 i" v- V, V
NK method, q检验9 w/ @& E+ H) e1 i% i( h6 S+ O+ P0 Z+ F
No statistical significance, 无统计意义: p# z6 r& }6 p8 d: w. \
Nominal variable, 名义变量
' I, e* m0 S! A9 ^4 qNonconstancy of variability, 变异的非定常性2 G3 S6 _8 d# b4 u* A/ t
Nonlinear regression, 非线性相关( H& b, ]: W e) q3 e
Nonparametric statistics, 非参数统计$ ?) ?* m* r& C! C8 U0 T2 a- J3 Q
Nonparametric test, 非参数检验
2 q" ]4 k. H: O c; O5 l$ HNonparametric tests, 非参数检验
# t4 o9 Z6 ^8 w: a6 e$ l: \9 J5 tNormal deviate, 正态离差. Q3 T2 E7 {9 M7 u Q5 f2 _
Normal distribution, 正态分布0 u* @0 w4 s; p f) p( A, f( K) D
Normal equation, 正规方程组2 v2 b! y$ q7 {0 t0 Y( |# b
Normal ranges, 正常范围$ r# @0 N& q7 Q$ G
Normal value, 正常值
" L& Y) g5 B0 o5 fNuisance parameter, 多余参数/讨厌参数
2 {1 W5 n% `, `, m0 O3 e' pNull hypothesis, 无效假设 * L" w8 m& z0 b9 V: \+ z
Numerical variable, 数值变量
7 }, s2 s- k! {- i! K% QObjective function, 目标函数
( D6 R$ ^. ^' t# M; H b% U2 cObservation unit, 观察单位* A/ f& y' ^+ V* W
Observed value, 观察值
" t+ X: R& a1 y2 m7 ?One sided test, 单侧检验 l; a8 f$ d& C9 u5 k0 c% u
One-way analysis of variance, 单因素方差分析/ e9 @7 {5 P- H1 e( V6 \2 j O
Oneway ANOVA , 单因素方差分析
# T" o, X$ R& O2 r; a$ NOpen sequential trial, 开放型序贯设计
9 _ |- U$ Q' TOptrim, 优切尾
& o; N/ T! G6 f) ^8 }% VOptrim efficiency, 优切尾效率, Z* p, \( a- X3 p; ]; c
Order statistics, 顺序统计量
+ p& C6 G" M% ?/ K; `# X( lOrdered categories, 有序分类
- L. Y6 p" a& u4 [( J4 UOrdinal logistic regression , 序数逻辑斯蒂回归
) j6 W) O, a4 i4 V5 C5 eOrdinal variable, 有序变量" H4 B) Z2 ^: ~0 x2 c8 s
Orthogonal basis, 正交基
6 D1 T( [ o/ ~5 P: K% _Orthogonal design, 正交试验设计
' u a0 |! _( u1 z$ Q; BOrthogonality conditions, 正交条件8 F6 `/ s% a# \$ _0 _3 o
ORTHOPLAN, 正交设计
1 y2 c9 L: h; SOutlier cutoffs, 离群值截断点
' D$ K$ }2 C9 J' z/ ZOutliers, 极端值
! A; u9 y7 p( S3 X7 s7 tOVERALS , 多组变量的非线性正规相关 % ]& E7 C$ }* W, q7 t. e
Overshoot, 迭代过度
% p* Y, M) I5 g# K# d) CPaired design, 配对设计
' }5 \6 H. p5 o5 e9 a1 T& n) KPaired sample, 配对样本
- j0 i5 h3 \# _0 vPairwise slopes, 成对斜率
: [1 Q8 l4 ^7 [& }/ @ `Parabola, 抛物线
, a0 ?6 j5 n" B' {( SParallel tests, 平行试验
; D- c, _9 v q0 W1 t+ tParameter, 参数
. u- l- S6 \* M" nParametric statistics, 参数统计0 d" T3 a, L3 _: U
Parametric test, 参数检验
! }* _' j; b5 T0 oPartial correlation, 偏相关* E& p6 a. O5 z8 x% y& D8 G- J
Partial regression, 偏回归6 }: D9 Q$ Y& C9 T4 y
Partial sorting, 偏排序
; A/ `! j* e# T0 k) qPartials residuals, 偏残差5 q/ u4 T' v) u2 g, Q2 Z
Pattern, 模式7 ^( s8 A9 z0 x0 K
Pearson curves, 皮尔逊曲线) L* n0 e$ N }
Peeling, 退层
$ f# D& |! r1 K% f9 \, a* Y BPercent bar graph, 百分条形图3 k' H- J7 d5 j+ o
Percentage, 百分比: \" g+ \& h1 O: ^" r
Percentile, 百分位数
) F6 R8 k. x* q; hPercentile curves, 百分位曲线
0 l2 G9 N! g: D! q9 T7 JPeriodicity, 周期性
6 q: n+ Q! v8 w nPermutation, 排列
0 L: s+ Y# W$ F3 D3 q# VP-estimator, P估计量7 x& T' o. M8 m5 ]8 H
Pie graph, 饼图
& S d8 Q. d$ z( y! LPitman estimator, 皮特曼估计量
* W5 \6 X: R5 X* E& {Pivot, 枢轴量
6 D ], O" ~/ s& _1 q# r2 S. PPlanar, 平坦
, @; j6 C% F* N5 J( ~" h, m# @Planar assumption, 平面的假设3 H2 y, }% }6 ~/ l; @: t
PLANCARDS, 生成试验的计划卡
4 h* |5 t$ D5 o9 EPoint estimation, 点估计
5 j8 b: y, A9 q3 Z B' V2 nPoisson distribution, 泊松分布
3 s9 T4 c' v5 ~& t+ N1 h3 Y( UPolishing, 平滑
% U' s0 z1 ~$ `9 o9 J; n2 ?Polled standard deviation, 合并标准差
4 W4 ~* O _7 e" kPolled variance, 合并方差
q, B$ T! ?2 Y5 X) l E- w6 HPolygon, 多边图7 ~& Q `* T( L8 e2 d; K
Polynomial, 多项式
# y9 m! u; j2 jPolynomial curve, 多项式曲线9 K0 ]- J% a* |
Population, 总体
5 E4 ]2 {; B$ x) |Population attributable risk, 人群归因危险度
6 N) E X7 B% T7 r/ e1 T' e1 fPositive correlation, 正相关; J8 w3 n6 i2 K3 ^5 _
Positively skewed, 正偏
n7 ]# t7 ]' g. O' ^Posterior distribution, 后验分布: O5 }9 i% p L: p
Power of a test, 检验效能( u. f% U) z( D+ R$ H4 S- V
Precision, 精密度
- V g: p- p: `Predicted value, 预测值6 C! {7 B& Q9 _/ P0 T
Preliminary analysis, 预备性分析
1 D' Z; p/ _& A% EPrincipal component analysis, 主成分分析
& j3 L. N: [; T: |8 oPrior distribution, 先验分布% H1 ~& p! p4 ?( Y/ D; L
Prior probability, 先验概率/ q2 D# `2 \) N5 _0 H# ~, O; _
Probabilistic model, 概率模型
; `2 i8 l, I" `5 v7 ?3 Zprobability, 概率$ u1 d) f# G4 H$ F6 C; H. _$ F
Probability density, 概率密度2 S( ~5 e7 n, E8 B: b a
Product moment, 乘积矩/协方差
- R* R9 y" O. b( A; lProfile trace, 截面迹图
5 F: N% Z. r% R! H- [/ L* _Proportion, 比/构成比' U) J; m$ c6 P N
Proportion allocation in stratified random sampling, 按比例分层随机抽样
, \$ J0 Q, ], g: B/ Z# j' `: jProportionate, 成比例4 s! E h- S- \1 S$ q; v
Proportionate sub-class numbers, 成比例次级组含量! D9 j; O# Y& \7 e& s) m0 R
Prospective study, 前瞻性调查4 Z7 H4 `& P7 b- h1 S
Proximities, 亲近性 s; Q. S5 Z7 v+ O5 a
Pseudo F test, 近似F检验2 j) N! b& d) O* k+ Y+ j p. L
Pseudo model, 近似模型9 t2 i& {1 b; u
Pseudosigma, 伪标准差3 a% {* d) S3 g, N0 ]: ^5 l
Purposive sampling, 有目的抽样
% [, w) T0 O: D6 \QR decomposition, QR分解
3 e* z, q3 O% b! EQuadratic approximation, 二次近似
3 Y+ Y* n3 u: q) _( k! sQualitative classification, 属性分类
/ C+ b, }6 T" OQualitative method, 定性方法6 ^0 L, B* p: b) r1 d
Quantile-quantile plot, 分位数-分位数图/Q-Q图. `/ M; f6 G( O6 q
Quantitative analysis, 定量分析- W% L' u5 z. N
Quartile, 四分位数
8 E% |& S" h$ r# ]# M6 f# `$ pQuick Cluster, 快速聚类
% o( h5 D6 z& g4 VRadix sort, 基数排序. a& n, T }0 I0 N, {1 G0 _
Random allocation, 随机化分组
, x; S4 z! P7 }9 v! cRandom blocks design, 随机区组设计
- ?7 H! z' t* h3 sRandom event, 随机事件4 u) r% w9 M8 r9 F$ a
Randomization, 随机化5 H( C H! O8 M% D/ |: s1 I- j
Range, 极差/全距/ H! y; o- y& v0 r7 o
Rank correlation, 等级相关
; T) }4 [+ ~' G4 T* K2 r6 v/ `Rank sum test, 秩和检验8 r* F% _9 V" |2 l8 m% h
Rank test, 秩检验+ b2 p; M8 D2 P7 c. E
Ranked data, 等级资料1 E7 p, {& |) S( i
Rate, 比率3 p% G2 [/ I# R0 k! X, k
Ratio, 比例
" f+ O3 l/ m: ~. w( G# a4 ~Raw data, 原始资料
# V3 X' g" O9 C; ]1 A* \Raw residual, 原始残差
. d7 L) h" A5 s# H% ERayleigh's test, 雷氏检验, _' x; {# z$ \, m6 s; ]
Rayleigh's Z, 雷氏Z值 , r/ _* Q( f" P& _5 F% ?
Reciprocal, 倒数
; |7 `( O0 m. g! H& t9 MReciprocal transformation, 倒数变换" m5 @+ h3 B, e. i
Recording, 记录
4 Q! L& N% d$ s6 K- i% Z: x3 L' j9 ?Redescending estimators, 回降估计量3 N( m/ h" o: j$ @2 T3 E* d t: E
Reducing dimensions, 降维% }# d+ G6 c0 c( [9 {, W& x4 B- \
Re-expression, 重新表达
4 @4 T+ w. ~0 `: N( _: E6 UReference set, 标准组
+ f e M( J, W! JRegion of acceptance, 接受域
$ T! w/ r, c0 jRegression coefficient, 回归系数
" O, j$ N, b) y( O& L+ kRegression sum of square, 回归平方和: _8 a- F$ H8 |1 E- b2 ~& M
Rejection point, 拒绝点
. `" x E& B4 J0 i* m! L! I. ]8 ^% oRelative dispersion, 相对离散度
% \" k* Z4 E" k9 h8 oRelative number, 相对数
( n6 C0 s7 `" b% U9 Y5 KReliability, 可靠性
( \+ P% M) w+ T3 J6 a$ p1 V1 ?Reparametrization, 重新设置参数
5 U! z9 f) z0 ?7 g3 G% s) zReplication, 重复
+ f5 b( w0 Q3 r3 _! DReport Summaries, 报告摘要
1 J& I6 }, I% m) L5 x1 b) h. JResidual sum of square, 剩余平方和$ S/ i# M) A' U* h V
Resistance, 耐抗性% a, X3 x, \: ]9 `
Resistant line, 耐抗线( L6 i! N/ B2 L6 j7 q
Resistant technique, 耐抗技术
, C! q& n, {4 i+ Y2 j$ ZR-estimator of location, 位置R估计量
) v1 H7 e' H' ~5 J1 YR-estimator of scale, 尺度R估计量
1 m0 a8 k2 ~6 ]( w9 x6 ^/ S6 BRetrospective study, 回顾性调查
7 ^ G" }9 N, T6 @; G b# ^Ridge trace, 岭迹! k) w0 A4 `9 f0 V
Ridit analysis, Ridit分析
" w* U" M1 I$ |! k) \; }; URotation, 旋转
0 H7 a' y3 ^( x) K. \Rounding, 舍入
% e0 e# ?0 h9 lRow, 行
" s; s2 B6 n( w( u$ W6 u! {2 CRow effects, 行效应
$ h' Y6 B; y( u4 G$ J. ]Row factor, 行因素6 n+ t9 S$ F- d5 s H
RXC table, RXC表
2 N! W5 I- m* V, ]Sample, 样本% h" D4 j, _3 V; L8 D% `9 `
Sample regression coefficient, 样本回归系数: B0 r4 N1 h e7 V8 m7 W# G% L# u
Sample size, 样本量
0 S; s0 j# o( S" e5 o1 Z# NSample standard deviation, 样本标准差/ z$ R! U1 F4 y' N H( Z9 Z
Sampling error, 抽样误差3 K: ~7 |* k6 D j0 e
SAS(Statistical analysis system ), SAS统计软件包
8 H. }$ i, J6 ^Scale, 尺度/量表 @- ^. w- \3 M) p3 F2 W& J0 s% Z2 N! _
Scatter diagram, 散点图3 c/ m2 z0 T, L5 ?. l5 A5 l* t
Schematic plot, 示意图/简图. |% z- Z5 P. x; u$ c
Score test, 计分检验
& w0 y' x( t% K/ X5 kScreening, 筛检
% x' \3 j+ P+ hSEASON, 季节分析 + {, t& O% w. U5 l
Second derivative, 二阶导数
# C( g3 U& x1 j$ v8 ^( D2 PSecond principal component, 第二主成分( k0 W, k, ~& z+ U5 v. ]
SEM (Structural equation modeling), 结构化方程模型
: S/ L1 u! B' g, U* s* b& X" cSemi-logarithmic graph, 半对数图
* E+ _8 ]* B9 C. ?* q& o" sSemi-logarithmic paper, 半对数格纸
( x1 k) @$ D" O( g2 OSensitivity curve, 敏感度曲线
E' e9 Z ~% \; K/ k$ x/ XSequential analysis, 贯序分析
7 C/ J& C, `) ^- y$ J7 GSequential data set, 顺序数据集
: m2 f7 B: k2 L, x [Sequential design, 贯序设计
* y: J! T) F+ w0 o# U+ C9 l" ^! `) CSequential method, 贯序法5 W' Z* T, h u. H7 s. O2 @" \
Sequential test, 贯序检验法1 o8 v. \' \9 K' S) e5 w6 M
Serial tests, 系列试验
8 @1 T" M+ {0 E+ E0 @Short-cut method, 简捷法
( C1 Z: q0 B- J) W8 t7 q. HSigmoid curve, S形曲线% q8 E8 g3 O. ^" m$ @
Sign function, 正负号函数
" L9 z* @' w& o& G% C- L( oSign test, 符号检验
3 i2 ~7 Y. M- z% _Signed rank, 符号秩; H3 Y% t/ d; L4 g/ T1 l
Significance test, 显著性检验 E. y) Q; m3 U0 i
Significant figure, 有效数字2 }1 `3 {; h( b" y/ @2 m
Simple cluster sampling, 简单整群抽样& s( u# b6 @3 `$ A
Simple correlation, 简单相关& v6 t) Z7 K0 t/ A" m/ L$ O, y
Simple random sampling, 简单随机抽样5 Y0 H. D7 _$ L
Simple regression, 简单回归. a! {# ]6 z& e$ ]6 t! e ^
simple table, 简单表+ M/ [1 M$ H+ p |, t7 q* |! P
Sine estimator, 正弦估计量
/ _, g* K ^: tSingle-valued estimate, 单值估计
$ ^( f* C8 w ~; ?! f, vSingular matrix, 奇异矩阵
+ _; ~: o$ ^4 o# YSkewed distribution, 偏斜分布
& I* P) M( T; P6 A1 ?Skewness, 偏度
0 \+ R ?* A* a v) z. H: H/ @Slash distribution, 斜线分布
5 d D- R. x r3 {. xSlope, 斜率" Z; c( B" y( k7 F
Smirnov test, 斯米尔诺夫检验8 m& k( E: {1 d9 x" ?6 D* I
Source of variation, 变异来源
2 }4 m' D6 y$ |4 l2 OSpearman rank correlation, 斯皮尔曼等级相关9 c- b+ U7 J* h9 R/ N" U' A
Specific factor, 特殊因子
& j: b8 @. G ^* w& a' VSpecific factor variance, 特殊因子方差- ~; c( ^2 [5 z2 p
Spectra , 频谱
1 X* x/ M5 s% q1 S, j$ XSpherical distribution, 球型正态分布
" T; ]5 G0 H1 {% {& |Spread, 展布% S- U' w8 _ w& P, T
SPSS(Statistical package for the social science), SPSS统计软件包
" j( q9 L, _ q# d6 FSpurious correlation, 假性相关# A p7 E4 @" c
Square root transformation, 平方根变换
s8 G% Z2 e+ L7 g' g& r/ t G P% V- SStabilizing variance, 稳定方差
" ^ n0 R/ j5 p& d% @Standard deviation, 标准差
3 J& [( c o9 j3 vStandard error, 标准误
7 \, a9 D5 u& n! |3 _1 @6 v4 HStandard error of difference, 差别的标准误- E! h& T: f) o- i
Standard error of estimate, 标准估计误差
9 h* O( A3 }3 G1 SStandard error of rate, 率的标准误' C, }+ [7 ?2 X) ~
Standard normal distribution, 标准正态分布$ E: q, X6 E# s' b( P
Standardization, 标准化
0 B4 ~# ?6 S( ^! C. ?" [+ H, @Starting value, 起始值 ^! ^) S+ P& ]; \
Statistic, 统计量3 Q4 ]3 J" t3 J" z9 q/ w z
Statistical control, 统计控制
" x' g0 l$ _% N" AStatistical graph, 统计图3 L1 R2 J9 h; k, m
Statistical inference, 统计推断
; A/ d/ D* W' S* e! F; J4 pStatistical table, 统计表/ }+ |' p$ T$ e2 |7 v/ A
Steepest descent, 最速下降法" Z3 ?0 I/ }( Y3 ^" u! L7 X4 @& o
Stem and leaf display, 茎叶图. M2 `, g' }1 T+ S- w( o
Step factor, 步长因子
% E/ Z! J/ ]4 K+ O8 n, d# [Stepwise regression, 逐步回归
0 M, X8 S$ E5 X5 ~Storage, 存
$ t; T, F) W3 R1 l" B) FStrata, 层（复数）
) ~+ E, v) Z$ p. R) ?2 T& FStratified sampling, 分层抽样
% s: h" S# B, g& lStratified sampling, 分层抽样 V8 j/ K, ~8 J/ l, c! \+ B
Strength, 强度1 X: F% y% Z2 K H2 w# J
Stringency, 严密性
$ B' A4 ^; L/ ~Structural relationship, 结构关系* a1 g; @" n; P* l
Studentized residual, 学生化残差/t化残差
6 r) X! q7 {* g$ S/ B) vSub-class numbers, 次级组含量
0 X; @3 a. p, E+ w: r4 A: xSubdividing, 分割! d9 J* w3 w9 V# m
Sufficient statistic, 充分统计量
9 r: }; w- h6 T$ K- O! ySum of products, 积和
7 I! N1 A& D/ y: | BSum of squares, 离差平方和
j" @) f. p1 u& v- y) n/ r: |Sum of squares about regression, 回归平方和# u: n. o* @0 G6 T
Sum of squares between groups, 组间平方和
; s7 S, T! e& _4 F, w- hSum of squares of partial regression, 偏回归平方和
5 A1 z- |( e4 S* CSure event, 必然事件9 y; D- d3 B* H* C3 S( j
Survey, 调查, _" @0 {5 _; \! ^. i2 c
Survival, 生存分析
0 a% M; {* }0 d/ F' hSurvival rate, 生存率+ x) ?7 \6 E5 t
Suspended root gram, 悬吊根图
) D( O8 x5 N2 _Symmetry, 对称7 \# a; P- }+ B4 w
Systematic error, 系统误差% \) Z, @* Z1 R
Systematic sampling, 系统抽样4 A. I! u5 n2 q+ M/ ?
Tags, 标签
! ^# K4 X) }$ C, U) j: |, j# NTail area, 尾部面积
" X9 e+ }9 U% K0 fTail length, 尾长8 d) p0 ~8 u0 t7 R
Tail weight, 尾重
" ^3 d$ K* B% `, [+ b/ Q) dTangent line, 切线. `/ s7 Y1 n. J- ^$ X
Target distribution, 目标分布& v4 c1 u% I0 I! b3 y
Taylor series, 泰勒级数2 C8 P; N5 S( F I2 W
Tendency of dispersion, 离散趋势
$ @$ j2 U5 A- `# D1 R% ~$ xTesting of hypotheses, 假设检验
$ _9 k8 H5 P7 I/ C3 N2 A7 zTheoretical frequency, 理论频数
. [% }, Z, m0 V0 h: _& FTime series, 时间序列4 G) h$ w1 B* p# P; O
Tolerance interval, 容忍区间
! t2 S/ l9 H# aTolerance lower limit, 容忍下限
2 _0 B: a& Q' k2 NTolerance upper limit, 容忍上限4 Q/ O4 p6 r C9 M! ?' r" o
Torsion, 扰率$ _3 y& B1 c9 B/ S- z
Total sum of square, 总平方和
& j. K. ?/ N, PTotal variation, 总变异
+ Z$ R) M6 k& Q2 m+ k P) C' dTransformation, 转换
8 [3 r0 ~; \5 ]6 q' g. \Treatment, 处理
2 O, B9 G4 s/ G# STrend, 趋势
' K9 t _8 L0 U& x; m7 y/ P" ]' x% vTrend of percentage, 百分比趋势
: S: q/ G% D6 |Trial, 试验
6 B2 t" W1 j" n+ N- Z) aTrial and error method, 试错法" i& P% ]+ a" ^4 G
Tuning constant, 细调常数
! z, \! U) h. J2 L+ ^Two sided test, 双向检验
- U% b/ S8 g& Q8 C* D; a% Q! dTwo-stage least squares, 二阶最小平方2 W9 n/ t0 A( Z- `$ x# B" q7 a# S
Two-stage sampling, 二阶段抽样
) t" y! q6 L0 ITwo-tailed test, 双侧检验0 ^0 D) U7 B% Z( W) k0 [2 T
Two-way analysis of variance, 双因素方差分析& e) W9 f! L% z# H9 G) C
Two-way table, 双向表- M Y& k6 |9 Y/ c# C
Type I error, 一类错误/α错误
* @( N; s5 T& v3 dType II error, 二类错误/β错误6 _9 ]& E* x Y3 D# t
UMVU, 方差一致最小无偏估计简称
! P- V% E7 u) VUnbiased estimate, 无偏估计
2 E2 ~& A& e& F, r* aUnconstrained nonlinear regression , 无约束非线性回归* B" S3 o, v5 V A( l) @5 \3 i( L
Unequal subclass number, 不等次级组含量
% d( Q/ x, K3 D0 ^: R4 x# gUngrouped data, 不分组资料
. v* g0 q. r! l, n h# oUniform coordinate, 均匀坐标; L, q* n) E! V' Z
Uniform distribution, 均匀分布9 y* V3 f( P+ _ Q1 L9 o
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
0 \. q: `! t/ G. x) i& t# rUnit, 单元
4 x8 W/ b, d. y# F9 j2 ?' iUnordered categories, 无序分类! `% ]5 r$ C. ]
Upper limit, 上限
3 O# w- J4 G; u' v3 v0 jUpward rank, 升秩
g6 y3 K, j s1 s h9 m! DVague concept, 模糊概念 r( }0 r3 g8 I [! ?2 i3 j
Validity, 有效性
# L0 X& Q& Y( e/ I( U/ MVARCOMP (Variance component estimation), 方差元素估计) A# I. p2 E- o& Z
Variability, 变异性
' O. @# y% N) r6 }' D0 s9 TVariable, 变量 R0 s+ i& S' X" o9 A4 }$ S
Variance, 方差: l# x3 J4 d9 T9 {* X
Variation, 变异
0 g% w9 x9 }6 R4 O6 m) VVarimax orthogonal rotation, 方差最大正交旋转( d6 p% l. a1 w; C% j* i5 O
Volume of distribution, 容积. \: a2 A3 p J& t' O4 q
W test, W检验
! p& ~" ? X/ W4 b S( wWeibull distribution, 威布尔分布
, R% s% }/ }5 F: t' t1 GWeight, 权数& R1 S+ r3 Y! b9 }! `+ j
Weighted Chi-square test, 加权卡方检验/Cochran检验) e9 `/ _& ?: C: d4 ?) P
Weighted linear regression method, 加权直线回归! t1 _" M, C% K, O6 b6 l2 I, ]
Weighted mean, 加权平均数
1 F, C. u! P: C. ~7 e: JWeighted mean square, 加权平均方差 b2 U3 T, \) o! Q& T
Weighted sum of square, 加权平方和
$ V: ? Z7 \! ~4 KWeighting coefficient, 权重系数
% P8 I$ Y3 e+ z; M {Weighting method, 加权法
$ b) t9 j7 p* z: kW-estimation, W估计量
9 [( h7 u0 S: w BW-estimation of location, 位置W估计量
8 ~, C8 r- r! |0 V6 N* RWidth, 宽度
' Z1 ~* Y5 z: L% `2 K* S, k* p. a& N' }Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验2 a+ f5 o4 n6 O
Wild point, 野点/狂点& L3 U7 z0 O) }0 c: B. ]
Wild value, 野值/狂值
- s4 H7 A% M! e9 z. N' QWinsorized mean, 缩尾均值; [; V- O% i! y
Withdraw, 失访 7 {0 X7 h) f: `8 b$ R. t2 L
Youden's index, 尤登指数
7 x6 `( N$ c3 x- aZ test, Z检验0 x* \ B, _ g, ^' Z
Zero correlation, 零相关
6 q% q& x, V J0 YZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
