|
|
Absolute deviation, 绝对离差) u) `- y) w5 |$ v; U
Absolute number, 绝对数
6 o- U" l5 q# y3 qAbsolute residuals, 绝对残差
* J: y1 Z$ V2 LAcceleration array, 加速度立体阵- m8 s+ F; y% s
Acceleration in an arbitrary direction, 任意方向上的加速度6 ]7 c% E' |5 x
Acceleration normal, 法向加速度
4 G8 k3 S; I4 l( u1 G7 \Acceleration space dimension, 加速度空间的维数
- z9 ^, b9 t1 ?1 C) {3 A/ ~6 hAcceleration tangential, 切向加速度
! E8 A( J, R' T# mAcceleration vector, 加速度向量
; T4 a( ]7 `2 W) ^& }Acceptable hypothesis, 可接受假设
% R i( v( K; I3 qAccumulation, 累积& q- @9 z' w# k6 R! K. K+ h. L
Accuracy, 准确度
, f2 d: Z% c, L% j# U' \8 r D; eActual frequency, 实际频数
* n) L2 h" O/ D0 T& KAdaptive estimator, 自适应估计量
( B! o5 w0 _; IAddition, 相加- |, D1 q1 V8 ` N
Addition theorem, 加法定理
, e; P' t! T; m7 IAdditivity, 可加性( j& U, s1 T* a$ }
Adjusted rate, 调整率4 f' g: w7 b, d* N* f
Adjusted value, 校正值
6 Q) I) G6 Q2 I% `; pAdmissible error, 容许误差
: E8 x6 k' ^2 F) p7 J2 OAggregation, 聚集性3 I# x2 H9 A: E. X( C
Alternative hypothesis, 备择假设
, n. A( ?6 b) }Among groups, 组间
* N0 z( K6 Y9 R+ M7 AAmounts, 总量4 C: o& Y! g1 a" j2 |9 m
Analysis of correlation, 相关分析( ^$ N% s& Z! D$ Y% Y
Analysis of covariance, 协方差分析
/ c9 G9 p; e6 C; F4 F' RAnalysis of regression, 回归分析3 u3 _) |" r V% Q( {( `
Analysis of time series, 时间序列分析
6 o4 u& o+ Z5 ?* }& oAnalysis of variance, 方差分析4 M; j1 y# x/ @
Angular transformation, 角转换
8 V0 ]8 ^7 V8 v# jANOVA （analysis of variance）, 方差分析
3 q" A# Q9 t0 ~ANOVA Models, 方差分析模型; V& i# |: t' M" M
Arcing, 弧/弧旋- l. y4 H7 w7 ?: N, x( G1 n
Arcsine transformation, 反正弦变换
; t$ K' {6 o$ @ N# [% dArea under the curve, 曲线面积0 X, Q# u$ @7 a& `9 r; _: c
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 # U6 y/ h* J. i: G2 ~
ARIMA, 季节和非季节性单变量模型的极大似然估计
! {5 U) l2 W% n8 q% L6 eArithmetic grid paper, 算术格纸
+ j. c4 O* W$ T& |1 e9 ~( uArithmetic mean, 算术平均数
9 Q1 W# |7 X3 L! F/ d- yArrhenius relation, 艾恩尼斯关系' L+ B8 c7 @" @$ e( v
Assessing fit, 拟合的评估
* y/ e" f4 a% p/ y/ sAssociative laws, 结合律
" V7 G; h0 _& X$ \$ K5 VAsymmetric distribution, 非对称分布, T6 m' l5 k2 P, V, ?7 i
Asymptotic bias, 渐近偏倚
0 Z( {% |, K* ?' {0 J$ bAsymptotic efficiency, 渐近效率* z7 B5 T; l ?7 l. ?$ F. T3 {
Asymptotic variance, 渐近方差
Q- [& r% m3 ?1 B8 z, \Attributable risk, 归因危险度
7 Q5 S% L" @! w8 |Attribute data, 属性资料
/ o2 w$ f1 d0 S% |3 u) @+ ^Attribution, 属性% O, L3 g T$ ^2 s5 g
Autocorrelation, 自相关% w" W3 a' A) y8 H- ?9 _
Autocorrelation of residuals, 残差的自相关
: R# t+ X0 v! R& r4 E4 z* {. DAverage, 平均数4 D" A8 Y, I) J3 a( N
Average confidence interval length, 平均置信区间长度
# ^# M+ o/ O* P4 A" f; Q7 @$ K- E# jAverage growth rate, 平均增长率3 v! M) t! v- L8 d. z9 \: _
Bar chart, 条形图6 V1 m" f* b1 t! I1 F# a& L
Bar graph, 条形图
9 B* M( m1 y g' g) H+ y& mBase period, 基期
. u! d6 e6 f, b( IBayes' theorem , Bayes定理
" X% r3 p( M( }. T* T) G2 B uBell-shaped curve, 钟形曲线
) y* ]! ^- _; o& E7 A: h- `0 ~Bernoulli distribution, 伯努力分布5 ?4 z) `* Q" O( W& Y
Best-trim estimator, 最好切尾估计量) }# W6 g7 ]& J( @4 h1 @
Bias, 偏性, i( T# e' }) @, y3 A- @
Binary logistic regression, 二元逻辑斯蒂回归
3 r! d% |: a: B: {Binomial distribution, 二项分布
# b7 C3 ]( u z1 I- ABisquare, 双平方
/ c7 W8 D8 c6 j( \7 gBivariate Correlate, 二变量相关; d' \1 {) w% ~+ F: h' U m E. K
Bivariate normal distribution, 双变量正态分布
# c% j1 I* H% ?5 a) a6 ]" hBivariate normal population, 双变量正态总体
& H8 l! U# B1 T ?, H" w3 u% V, k6 wBiweight interval, 双权区间
4 b- U( \. ?0 n/ `Biweight M-estimator, 双权M估计量
# g7 Q8 T- P3 H+ D9 PBlock, 区组/配伍组
* b0 |( ]8 z( jBMDP(Biomedical computer programs), BMDP统计软件包" D- L2 J- l1 S/ Y# C, o3 X
Boxplots, 箱线图/箱尾图
G5 _! L/ z4 Z# C; a$ x$ aBreakdown bound, 崩溃界/崩溃点
, X( t% l" T# e: k: iCanonical correlation, 典型相关. `7 S6 P+ Z) _
Caption, 纵标目1 y* t, l: \% N" h+ ~
Case-control study, 病例对照研究! |; K7 I/ v# a( M: K' y/ s3 U6 |
Categorical variable, 分类变量, S: X& E! O# w8 o) n
Catenary, 悬链线! o3 O h4 v# S q9 d
Cauchy distribution, 柯西分布
$ A& l' y; B9 a: u, L" l# `9 c: ?Cause-and-effect relationship, 因果关系
9 n/ ~ ] `+ s& D& yCell, 单元! s" J- G k7 s$ t3 q
Censoring, 终检
2 h' q) D* j' A2 {6 DCenter of symmetry, 对称中心1 p6 L6 a/ E1 P
Centering and scaling, 中心化和定标
8 X) l5 j5 R$ r9 q- u1 ACentral tendency, 集中趋势' c. I5 W1 j" }+ c/ V
Central value, 中心值' k# c5 Z7 K; j
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测$ I9 H6 H0 H6 b2 V: E+ e9 J! z
Chance, 机遇
1 P* f% r& A: m5 A) YChance error, 随机误差( s- C: r# i3 q5 s' i& v! K
Chance variable, 随机变量
- d, b! W8 {& A5 ?* e: u2 wCharacteristic equation, 特征方程3 U1 y8 k b$ I. I3 V/ ^
Characteristic root, 特征根- S( _* s5 d+ J9 U/ C( h @8 x, d
Characteristic vector, 特征向量/ P" p# r% Y. _6 R- F/ M
Chebshev criterion of fit, 拟合的切比雪夫准则
* ]7 d0 n7 _: V) oChernoff faces, 切尔诺夫脸谱图6 u. ?6 `- Y0 v3 i2 W7 o
Chi-square test, 卡方检验/χ2检验
t+ R6 o) S6 m' V% M z) p; ECholeskey decomposition, 乔洛斯基分解' E5 h7 P( G3 E% r5 C$ w/ r- ?
Circle chart, 圆图 B9 v6 R& A A
Class interval, 组距5 P- Q* R) a( w e9 W: l
Class mid-value, 组中值
% W& n# c1 X* @, k* _Class upper limit, 组上限1 C- v! }, H5 P8 j5 w
Classified variable, 分类变量0 `+ b; B# H: ^1 q
Cluster analysis, 聚类分析
3 k$ B) {5 l- z" X7 W. BCluster sampling, 整群抽样3 R/ a" d, x. t7 W# r- ?1 J
Code, 代码: }! {8 {- x& R3 g; \
Coded data, 编码数据' i* }6 O1 R# h; |# `/ D q5 N) X
Coding, 编码, w6 _% M# ]# v" I" S
Coefficient of contingency, 列联系数
; `* ?2 P f( Y0 P7 y* ]9 eCoefficient of determination, 决定系数
0 N' T3 _5 y8 b$ hCoefficient of multiple correlation, 多重相关系数" Y" m ~/ r0 [! q+ d: b0 t
Coefficient of partial correlation, 偏相关系数2 a, b* g# ]! m
Coefficient of production-moment correlation, 积差相关系数/ X* A2 @% R" P7 } ?5 V3 a1 d
Coefficient of rank correlation, 等级相关系数/ M4 [. R+ J" g9 l* j- y0 M5 w1 p# g
Coefficient of regression, 回归系数* W! J1 B3 ?( b) c5 l9 E) n
Coefficient of skewness, 偏度系数: y/ i, ]& u i) o) F% ~3 d
Coefficient of variation, 变异系数2 S, Q" f/ @# X
Cohort study, 队列研究 _7 L1 r0 m9 [
Column, 列
% Y, ]- Q/ h4 T fColumn effect, 列效应
3 W6 V2 o; m6 ?. iColumn factor, 列因素
! u9 {$ z f; N; K; y! r: BCombination pool, 合并
' C1 Z7 m. Q. VCombinative table, 组合表
, }5 Y5 C( N1 h+ b- MCommon factor, 共性因子9 H! f( h+ `0 Q7 V4 {6 M
Common regression coefficient, 公共回归系数$ E+ C9 ^9 f" ^! a" m# W) R. b5 D! Z
Common value, 共同值6 N' W5 ~$ o1 d; R) b
Common variance, 公共方差) w5 u5 a* a0 r, H, t& P; h/ i* P6 Q
Common variation, 公共变异
1 T8 C9 U* o; |9 \1 T* t2 sCommunality variance, 共性方差
M5 w& t' v& T" G3 _Comparability, 可比性) } p, V+ Q$ J
Comparison of bathes, 批比较
1 d1 i: I1 N( T3 MComparison value, 比较值
- [; e& y6 q. i- b; tCompartment model, 分部模型; j7 U8 e B: G; `2 T' H
Compassion, 伸缩7 ]- h4 P1 M( |( Q
Complement of an event, 补事件- ` H9 F. g; q' y' ` h- `5 `- Q
Complete association, 完全正相关
- |' a" b: W0 i! g. {0 M1 OComplete dissociation, 完全不相关
6 ]4 {+ p' V) N X1 V6 NComplete statistics, 完备统计量
/ ^& f2 R. h* i0 t8 L7 |Completely randomized design, 完全随机化设计0 C/ J5 f. x9 v# m* f
Composite event, 联合事件
6 }3 O$ t/ d0 WComposite events, 复合事件
8 D' J% i4 j8 |) [* C! S. iConcavity, 凹性
* A3 @) a, k9 w/ U5 r% _Conditional expectation, 条件期望. E- `3 I$ R$ @& w/ Z3 A# D
Conditional likelihood, 条件似然" T! n0 U; |6 _6 h6 H
Conditional probability, 条件概率
6 M3 i7 z# p1 OConditionally linear, 依条件线性' r' o1 I# y6 K0 O1 P4 W Y
Confidence interval, 置信区间! n' U" G9 } i4 E
Confidence limit, 置信限7 b4 r$ s" k3 t8 v
Confidence lower limit, 置信下限
/ p+ I% x; s# G# MConfidence upper limit, 置信上限
4 Z" C4 D8 c0 fConfirmatory Factor Analysis , 验证性因子分析- V0 }9 P2 T( \2 ~4 x) H
Confirmatory research, 证实性实验研究. Z5 \- Z8 F) e- f0 _. k2 i
Confounding factor, 混杂因素
% d7 R6 Y' q, n0 wConjoint, 联合分析) u2 x* l! X* u4 L9 p, @
Consistency, 相合性% K; V. |: J: s+ e' ~. m7 @7 p# a
Consistency check, 一致性检验; d/ M9 w: Y! M" s! I
Consistent asymptotically normal estimate, 相合渐近正态估计
* w; U# M: R4 S% R* W, rConsistent estimate, 相合估计
, M6 u; k9 v8 G( b+ S5 X ZConstrained nonlinear regression, 受约束非线性回归5 g4 E5 f2 k8 a% e/ }0 I
Constraint, 约束
1 `, A7 h" n# YContaminated distribution, 污染分布
4 L6 Q4 B' m; l- A, h! n& [; K8 Z# {Contaminated Gausssian, 污染高斯分布
E& ^: F* I ]. qContaminated normal distribution, 污染正态分布
9 G" c v7 o) H% WContamination, 污染
2 t8 r; {! V0 D$ }/ ]+ T( SContamination model, 污染模型8 d4 Q F9 K" v6 r9 ^
Contingency table, 列联表7 Q/ c! p/ @- A2 g" o
Contour, 边界线 t8 g4 T+ t" x7 W5 ~
Contribution rate, 贡献率2 ^9 B/ F0 G! }1 `
Control, 对照
; t! B" q# V i( K2 K4 w5 D# O& CControlled experiments, 对照实验$ D2 v! |! r ^" I( u; D
Conventional depth, 常规深度7 I2 ?) N$ X6 l4 u# L% V
Convolution, 卷积/ F6 ^) Y4 T( z" ?: ~
Corrected factor, 校正因子
4 V- Y. n7 y9 v2 R" VCorrected mean, 校正均值1 L( O7 W' c8 {$ ~
Correction coefficient, 校正系数
1 h- }7 ]3 M0 F. W+ p! K( g, PCorrectness, 正确性# j: S, E& A+ _9 c* e* w
Correlation coefficient, 相关系数
5 Y$ n2 g, @* [/ rCorrelation index, 相关指数! {6 j( [2 Y4 e4 E7 M1 l4 [ E
Correspondence, 对应3 n+ G, P( X/ ^0 A$ C: l, r
Counting, 计数; r' t) p) Y/ N$ I* T/ j1 ~' J& E: i# P
Counts, 计数/频数
2 |3 h, L' k, D( `5 \) [Covariance, 协方差( R2 H% n1 X4 ?6 o
Covariant, 共变 ) L+ Y, ]" v2 q$ g0 k+ b
Cox Regression, Cox回归: p8 k, P* ^# h/ \. m
Criteria for fitting, 拟合准则
* P# r3 K" J; ]9 [4 KCriteria of least squares, 最小二乘准则
! z0 g G: e' z' wCritical ratio, 临界比
5 u4 ~4 ^4 h3 w" }( DCritical region, 拒绝域! q) V2 c9 h: z- y( d
Critical value, 临界值
; d9 W! K7 ]/ T; Z) Q5 ZCross-over design, 交叉设计
" E) u" B' @# X/ d- a+ f6 LCross-section analysis, 横断面分析' e) A( E% w W9 M) L# c
Cross-section survey, 横断面调查: e' B/ @6 _; O' m7 c
Crosstabs , 交叉表 . C1 [0 _, z) s: G3 L
Cross-tabulation table, 复合表$ l. e2 m$ V0 t7 z6 q: i
Cube root, 立方根4 p* r! L3 h$ @; J/ e
Cumulative distribution function, 分布函数* T8 n$ w. `; X0 c8 M' J
Cumulative probability, 累计概率
1 C4 ~+ E. T. M' A GCurvature, 曲率/弯曲
c1 I u& P, Q6 PCurvature, 曲率. M: v' D0 T. U% u9 {5 m+ O, _/ M0 r
Curve fit , 曲线拟和
2 Q5 `6 B$ E1 y2 T+ E4 m# k7 O gCurve fitting, 曲线拟合# F) d5 H( |2 L( T$ M* `
Curvilinear regression, 曲线回归
$ j; f6 r* q' s- {- jCurvilinear relation, 曲线关系, G# p' Z @3 C) @, M/ H/ R5 M
Cut-and-try method, 尝试法& Q# ]# `7 M. X8 M% v- _" f
Cycle, 周期
6 y5 Y4 k8 k5 n- y9 XCyclist, 周期性
% ?+ C: t& b6 i5 o0 ]. L- ID test, D检验, E( e4 _' ^4 k. W! K4 x9 ?
Data acquisition, 资料收集( Q, I3 c7 f. o$ }% S5 I/ I. P: f: L
Data bank, 数据库! J' R3 g- W( Y
Data capacity, 数据容量9 I4 N. W4 ]! ^1 E8 a9 D5 k3 c
Data deficiencies, 数据缺乏* O/ c, G, W. D; G
Data handling, 数据处理8 @) y$ u) n! T6 R7 `
Data manipulation, 数据处理
. s6 @1 \+ A+ b* s$ NData processing, 数据处理, E: J* o' @$ c' Q9 @7 V
Data reduction, 数据缩减6 Y; E9 U' R* p4 |. E$ J% \+ Q
Data set, 数据集
1 Z. Q$ E, e% Z8 n" A' sData sources, 数据来源
5 `; V0 n* e0 j# TData transformation, 数据变换
v7 v- Y; d1 hData validity, 数据有效性/ x2 \/ m# a* L, A+ R6 ?
Data-in, 数据输入
. U0 F7 N5 e0 G) {- f4 jData-out, 数据输出
+ D9 s3 h3 E; E' e5 v+ H/ A% ZDead time, 停滞期" N5 P j N; x3 g
Degree of freedom, 自由度4 V, Z$ s+ I; C2 w* E3 u# b$ y7 b2 y% ?
Degree of precision, 精密度+ }8 @5 v0 S4 w9 {" \6 f& \3 g
Degree of reliability, 可靠性程度2 t( W! Q/ B7 A6 d6 J
Degression, 递减- o) h, A' W0 W' y- P) ` x4 o
Density function, 密度函数
X) S" H' h7 p0 {6 T: j) l, hDensity of data points, 数据点的密度2 N! z/ f6 S, S9 G
Dependent variable, 应变量/依变量/因变量" c; r' ?* \4 R- X4 W! m
Dependent variable, 因变量( J& L6 a5 D1 A! X5 I- j' A
Depth, 深度
/ x- d7 J% v1 J1 k2 LDerivative matrix, 导数矩阵
) X( W( q0 y7 J ~( v! tDerivative-free methods, 无导数方法
( H& c3 i3 s% C) C9 j* ^Design, 设计 w3 v% T5 b+ s/ }+ E" [/ _4 a
Determinacy, 确定性
- R0 U5 _$ W" P V1 g; k HDeterminant, 行列式) E! r; d* ]$ F' }4 D( S. a
Determinant, 决定因素( [) a1 ?6 H0 R# }3 {
Deviation, 离差
- |3 W% o$ O$ T; E0 p8 CDeviation from average, 离均差
3 J' l$ [8 e5 J/ ]: E' `; fDiagnostic plot, 诊断图
1 U4 }& m/ O/ w, uDichotomous variable, 二分变量
% R6 S* C. S* x/ {7 G4 BDifferential equation, 微分方程
1 j" J! `* A6 X) x; L9 z% F* RDirect standardization, 直接标准化法
# v f6 D9 V. m3 }# q0 z# NDiscrete variable, 离散型变量/ E6 I4 V9 d2 f- C7 r
DISCRIMINANT, 判断
8 X, |' \* T0 o. v$ O/ fDiscriminant analysis, 判别分析. B5 z- ^/ ^( K, @% b, j- r8 g, h
Discriminant coefficient, 判别系数7 `/ j7 E7 I4 W0 x
Discriminant function, 判别值
0 b1 ], ^/ _& f. W6 I$ {4 pDispersion, 散布/分散度
$ Y2 W5 c+ t3 pDisproportional, 不成比例的
% N6 F% e6 ~, f* KDisproportionate sub-class numbers, 不成比例次级组含量$ y$ V/ W: I1 r
Distribution free, 分布无关性/免分布: W8 ]# q; @0 e9 [7 q. i
Distribution shape, 分布形状. X5 H- N- {- v6 H
Distribution-free method, 任意分布法6 g8 }! |& P8 ?8 ?+ }9 y
Distributive laws, 分配律
, p2 C9 g, E2 c% {Disturbance, 随机扰动项. `% Q2 c1 k- H% W3 ]
Dose response curve, 剂量反应曲线% b- |4 w! d! a6 |1 s! a- N
Double blind method, 双盲法
5 k' d0 X+ @: S" V/ HDouble blind trial, 双盲试验$ [4 I. Q9 _6 O
Double exponential distribution, 双指数分布% g+ q* s$ }& i' w) g+ u( i
Double logarithmic, 双对数
3 `9 |, ^6 s- HDownward rank, 降秩
# f" A6 [0 `+ s- T& lDual-space plot, 对偶空间图
& ~# ~$ H3 C% SDUD, 无导数方法
' N% ]: Z/ W0 d s/ h" oDuncan's new multiple range method, 新复极差法/Duncan新法
* Y- ?' |$ N" w( i0 N0 v3 ~8 o) t: cEffect, 实验效应4 f0 \5 e" F% {) W
Eigenvalue, 特征值3 r, M g/ Y; ^& @8 S- L* Y
Eigenvector, 特征向量8 N. v! ^7 P. U/ z( N) m
Ellipse, 椭圆4 E9 B* D3 w9 L* V! ?0 L! w8 v
Empirical distribution, 经验分布* j1 c8 c& i# L$ T
Empirical probability, 经验概率单位
% [. D. Q1 B- Z1 S2 OEnumeration data, 计数资料
5 b. q. c5 f# M! d8 h% C4 [3 _Equal sun-class number, 相等次级组含量
7 J6 n6 D/ r; n" G, S" jEqually likely, 等可能
% a9 F) k, u, k9 d! s; yEquivariance, 同变性4 K3 I/ f4 r2 W
Error, 误差/错误% W# l& u0 c: `1 q4 i
Error of estimate, 估计误差# A- Y+ u7 G7 {- z3 e- q1 N5 S
Error type I, 第一类错误$ M! e+ \7 v8 ]. Z% K& B
Error type II, 第二类错误4 E7 u8 s2 S1 ~ X( I" m
Estimand, 被估量! W v1 k/ i1 e% Q+ B1 v5 m
Estimated error mean squares, 估计误差均方: v4 \8 D8 P8 z1 \9 ~% R3 s! K
Estimated error sum of squares, 估计误差平方和
7 s) H3 }5 s0 c5 @& N7 m% [Euclidean distance, 欧式距离9 I- f( P* d5 N; i1 U ^
Event, 事件: K1 C. m$ X2 x6 |# `# Y; T
Event, 事件" `: X: e. W# X3 d3 f1 ^' E
Exceptional data point, 异常数据点
: ?: o _9 |1 F+ \7 S* \Expectation plane, 期望平面
/ G* u, h4 H! v, q! ^# QExpectation surface, 期望曲面
) E% E7 G4 I" Y- CExpected values, 期望值3 a- y+ c! _) d: I
Experiment, 实验* `- c/ w9 M4 S( r
Experimental sampling, 试验抽样
! L& b6 `' u! a6 j( `( p& ]Experimental unit, 试验单位; L' @' V3 Z/ {4 @5 g( A2 a
Explanatory variable, 说明变量- s2 S& h. h; u3 V, [+ v+ q( q v
Exploratory data analysis, 探索性数据分析* ^" {, L a8 G4 p7 c# U
Explore Summarize, 探索-摘要
! F) O( z8 n/ |8 cExponential curve, 指数曲线4 N% R; z) X! D2 Q0 u
Exponential growth, 指数式增长 J8 L6 n- e: ?. |# Y& {1 ^
EXSMOOTH, 指数平滑方法 & i0 @) S3 S! O0 e
Extended fit, 扩充拟合
. ^8 v# n' B" y1 G. dExtra parameter, 附加参数) U0 e( s+ g( J" L. b1 e# C. x! ]
Extrapolation, 外推法
8 X9 ^! ^/ ^7 H1 nExtreme observation, 末端观测值7 S$ Y6 _. q! S0 g: ^' L5 j+ C1 ]
Extremes, 极端值/极值. Q' H2 M) U) Y# i5 s' H/ n
F distribution, F分布( b" J; ^* w1 e, M% N8 t
F test, F检验2 [8 i9 ~$ x. Z
Factor, 因素/因子' @7 i0 O: @1 Q
Factor analysis, 因子分析
* s" p: Y2 y3 W; r6 i: M# ~Factor Analysis, 因子分析6 |# y! r+ Z* r1 S% P2 V" p0 q# P
Factor score, 因子得分 a! i' Q, v. V, m( V9 ^
Factorial, 阶乘$ y0 _3 i9 R0 e; i5 j
Factorial design, 析因试验设计
! t2 s4 D# A" G UFalse negative, 假阴性
5 W" E; d; q/ gFalse negative error, 假阴性错误
c( Z h1 V, `. R BFamily of distributions, 分布族
) f3 k! e4 C" D3 uFamily of estimators, 估计量族
/ G# u# Z& b4 |# R" BFanning, 扇面& p4 b' v8 D. W
Fatality rate, 病死率
7 o$ e1 O3 h$ }Field investigation, 现场调查
# X4 g: X8 ], qField survey, 现场调查
% x1 y4 c( C" E% e( J% ?" v5 NFinite population, 有限总体
# u4 m% f/ z5 {) N7 j! h4 m" aFinite-sample, 有限样本: _: l" `, ^9 M" h$ H( Y
First derivative, 一阶导数% t0 q5 U: D% M8 ]) b
First principal component, 第一主成分. B+ d- ]! @& E0 X
First quartile, 第一四分位数) p7 t0 e5 A% T- h$ u: l
Fisher information, 费雪信息量! B. ^6 B5 r' W/ _/ j
Fitted value, 拟合值
: B6 K3 e# `/ X! O7 ?' [1 `Fitting a curve, 曲线拟合
3 ^8 P+ k' S4 z' U& C) O3 Y( `Fixed base, 定基
5 _8 _, `' H2 h; {Fluctuation, 随机起伏
9 A& h- B0 \" j/ [8 OForecast, 预测
$ A- a: K) z2 p- J' WFour fold table, 四格表* Q" D. F9 P) d$ x3 ?
Fourth, 四分点
: F7 ^8 z f% E s9 QFraction blow, 左侧比率6 k8 ~$ s6 `0 a/ N0 v0 u% r/ S
Fractional error, 相对误差
8 v( N2 k2 t4 VFrequency, 频率2 O+ n8 t, L7 Y5 {7 z
Frequency polygon, 频数多边图
; _/ V, U! T3 T, e/ |Frontier point, 界限点 d9 @/ m/ U* Q' |" _' N. X
Function relationship, 泛函关系$ M l# Z3 a! _: A1 ^
Gamma distribution, 伽玛分布% O4 [9 r6 i$ u) }1 U) c4 i
Gauss increment, 高斯增量1 n/ i. j$ [) a* b& q n
Gaussian distribution, 高斯分布/正态分布
3 o1 {. A* n! u0 D6 G5 aGauss-Newton increment, 高斯-牛顿增量% p. ~& l; H$ t: l0 |7 l
General census, 全面普查0 V0 k0 W9 v- N+ {
GENLOG (Generalized liner models), 广义线性模型 4 _5 |* p" r' H% M- ], U
Geometric mean, 几何平均数
; x, c! d P2 ^1 T+ mGini's mean difference, 基尼均差
# [$ c# U! M/ o1 b# f$ y9 cGLM (General liner models), 一般线性模型 3 k6 I5 k5 h: a9 j, N
Goodness of fit, 拟和优度/配合度; w, I; q1 m, g( ` R
Gradient of determinant, 行列式的梯度
& t% P# P3 ^" ~4 h% E$ _Graeco-Latin square, 希腊拉丁方9 T0 M+ y' }+ E) e! t9 P
Grand mean, 总均值
?5 J5 N i9 v# t: d* ?0 R8 YGross errors, 重大错误
" k% [3 j/ B) e( w6 BGross-error sensitivity, 大错敏感度1 d+ E& V: N. Q! K" [5 B7 z6 I
Group averages, 分组平均
8 n Q7 O( f6 j" G( @' MGrouped data, 分组资料
6 l* S+ l S% r E& zGuessed mean, 假定平均数/ ?; n3 m) [, G& `3 K
Half-life, 半衰期
+ Z M4 V- z$ }" UHampel M-estimators, 汉佩尔M估计量( [3 s. k9 V- r' w; I
Happenstance, 偶然事件5 z& L/ h' E9 r' X0 R
Harmonic mean, 调和均数
8 t( s) [2 `" L8 P% n8 sHazard function, 风险均数
4 ?. P( f c3 ~2 PHazard rate, 风险率% [ ^5 a8 I$ S0 |0 ?
Heading, 标目
|/ c& H& z. e8 _( x% mHeavy-tailed distribution, 重尾分布3 E' n+ u3 G! H5 b7 w) b
Hessian array, 海森立体阵3 a1 H! B/ e1 o. x
Heterogeneity, 不同质
$ x: u1 I, n) D h5 ~Heterogeneity of variance, 方差不齐
4 n+ P. K3 G1 G- s" n1 nHierarchical classification, 组内分组
- N# H5 E1 W, M4 \5 u& }# m8 F( HHierarchical clustering method, 系统聚类法( I# P4 M$ ]6 {: ]* w7 n9 v1 f8 [: n
High-leverage point, 高杠杆率点0 J- s; B9 E! l5 [7 R: C
HILOGLINEAR, 多维列联表的层次对数线性模型 ]2 I' [2 ]8 ~
Hinge, 折叶点
5 q y! V5 i8 W0 v, \( j* C- SHistogram, 直方图
# k* S' g' l9 z) _9 L. ]& IHistorical cohort study, 历史性队列研究
+ ~! q: O# X% O/ f6 ^7 \5 KHoles, 空洞
# G+ t2 W' U: F6 r9 NHOMALS, 多重响应分析% y6 H$ {- c& j( U% I
Homogeneity of variance, 方差齐性
1 f) B- H: P5 h4 @. k3 d! n9 t: Y1 ~Homogeneity test, 齐性检验
, x) U5 X% R3 C! P" U+ W" AHuber M-estimators, 休伯M估计量( l, O) z, ~+ R& g7 n3 W
Hyperbola, 双曲线4 O/ Q( y1 Y& Q; x
Hypothesis testing, 假设检验- T$ @. D6 n& V, L- V8 M2 j6 n( X% u
Hypothetical universe, 假设总体
/ v# D+ g2 E/ E$ uImpossible event, 不可能事件3 ~* S" i1 h/ Z: `% @6 {
Independence, 独立性' _; s6 E5 O; \. z, ^+ }; i* P
Independent variable, 自变量
) P, w3 t8 B. }: K& h QIndex, 指标/指数5 k: j5 B9 r8 e1 o, G0 L0 [- N
Indirect standardization, 间接标准化法/ c% h0 h% y9 A9 }% v. s) a: l
Individual, 个体7 k- m2 p) G" A( `; h2 ^
Inference band, 推断带+ M6 w" X4 u8 W
Infinite population, 无限总体8 m- N! ~: W( z5 p* [
Infinitely great, 无穷大3 E$ d8 ~) o9 t) I" P( D+ ~
Infinitely small, 无穷小
0 Y8 i* g, S5 L/ B- w9 E. S. aInfluence curve, 影响曲线
5 a$ [& Y- | F! h9 LInformation capacity, 信息容量
8 g5 K8 Q3 E# e- e' e2 J. cInitial condition, 初始条件, {2 k+ |$ U6 C0 A* t$ w, [: U
Initial estimate, 初始估计值
3 y6 W$ L1 K! U3 x% m3 DInitial level, 最初水平
8 O: e7 G, U8 i2 P5 PInteraction, 交互作用
# J/ B$ k2 m# M3 w5 O4 |Interaction terms, 交互作用项! h$ v/ F0 L; O# @# p
Intercept, 截距9 ^$ x! ~- V# e0 n
Interpolation, 内插法
* G# x s" F0 J6 C, ~Interquartile range, 四分位距1 Q+ G* S: g: p7 a0 E/ {
Interval estimation, 区间估计
% Z+ [: _0 W7 g5 J, j6 y9 x; FIntervals of equal probability, 等概率区间1 f, B4 e8 Y7 N4 U% S9 W+ c
Intrinsic curvature, 固有曲率" R, R' P7 u; c3 D& a2 d) z
Invariance, 不变性% C6 a1 U0 A/ h4 X: x
Inverse matrix, 逆矩阵
, ~( D! v% X4 k- t' {: j2 xInverse probability, 逆概率
$ i2 r+ n2 R7 C4 `+ M1 EInverse sine transformation, 反正弦变换
! R7 x5 Q5 {1 ?0 S) BIteration, 迭代
8 ~) N- t9 v) l5 h$ WJacobian determinant, 雅可比行列式0 c2 I5 M. y' T/ i- g1 U4 w
Joint distribution function, 分布函数; F: t3 g6 D7 v- X
Joint probability, 联合概率/ y* I! @5 ~! B, v; ~2 _
Joint probability distribution, 联合概率分布# w2 q, h0 B; j9 `7 j9 a7 z s
K means method, 逐步聚类法
% \: W5 I! m3 W) K2 v6 XKaplan-Meier, 评估事件的时间长度 p; k3 \8 \* Q: ]! a
Kaplan-Merier chart, Kaplan-Merier图
+ c& H/ Q! M/ V- vKendall's rank correlation, Kendall等级相关
; S s! I; V3 l4 y6 xKinetic, 动力学 l/ u; T/ @; ?3 e. h1 |" |
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验: N' ~- _6 R6 d3 f3 Y" j r! j
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
3 f& x3 ~$ W5 L) pKurtosis, 峰度
1 }# B0 T u6 u: {" D |Lack of fit, 失拟' u. [! C/ c6 k5 O1 {5 ]. u
Ladder of powers, 幂阶梯: g! p6 r, Z( M, l9 K
Lag, 滞后
1 Q+ [2 ~ d) D) b8 xLarge sample, 大样本
4 Z, s6 d$ o1 p5 XLarge sample test, 大样本检验% f) l9 ~& D* r' ?0 l# b
Latin square, 拉丁方
1 Z: O% a% C, s( z7 JLatin square design, 拉丁方设计$ a4 t8 F! _! b e
Leakage, 泄漏; @6 [# v! _$ p1 [4 R: ]
Least favorable configuration, 最不利构形* b* N3 h" D) V- M5 U$ \, p* P
Least favorable distribution, 最不利分布$ p2 f4 V3 z3 V6 k7 N
Least significant difference, 最小显著差法
% |5 Q+ e' D$ z* `Least square method, 最小二乘法; g l% ?1 T8 v9 S6 W
Least-absolute-residuals estimates, 最小绝对残差估计
0 F& L/ }1 }" ?/ J% ALeast-absolute-residuals fit, 最小绝对残差拟合5 W" [ p+ w. Z. y q
Least-absolute-residuals line, 最小绝对残差线
& M2 b& p+ J F/ u4 F0 wLegend, 图例4 d0 \6 E* t0 Q: d
L-estimator, L估计量8 W$ s- `# p; R
L-estimator of location, 位置L估计量
& Z: ^ @, d) e1 a/ ^L-estimator of scale, 尺度L估计量
; ]( L- Q+ X+ n# y4 @6 ZLevel, 水平# s8 @( [2 n8 _2 Y
Life expectance, 预期期望寿命" y1 z5 J9 G" l! n
Life table, 寿命表
& [8 u6 D- ?( {4 f) R WLife table method, 生命表法
! I" h1 @% v8 I% H A$ j. G' r% _Light-tailed distribution, 轻尾分布' o2 [3 b! e8 z. [
Likelihood function, 似然函数
* `! V6 l, _8 jLikelihood ratio, 似然比
* u% j$ q t: v7 cline graph, 线图) a9 x6 {, ?3 I7 h3 V: q
Linear correlation, 直线相关! e+ F. d: m! A3 I
Linear equation, 线性方程
" a# u9 o* F- _1 O3 V# U5 I2 N* Z9 s) cLinear programming, 线性规划
+ ]; p6 c) z v5 j8 w% OLinear regression, 直线回归3 f- R* g7 [' }) A( l" c
Linear Regression, 线性回归
6 K( B& s: Z4 g1 v. |Linear trend, 线性趋势) z2 [" ?# y+ z4 l* k4 ]& J3 Q X9 ?
Loading, 载荷
5 H& l8 b) W8 F* I; x( ZLocation and scale equivariance, 位置尺度同变性
9 z- u% I+ x, M2 QLocation equivariance, 位置同变性! Z2 s: J! t. i& z
Location invariance, 位置不变性& h3 i9 q. ?4 g; v' K, _
Location scale family, 位置尺度族
& \+ O i. n4 q' wLog rank test, 时序检验
+ n e z. I3 MLogarithmic curve, 对数曲线
/ q0 j( p2 O( }$ n. v2 T4 _Logarithmic normal distribution, 对数正态分布( E, G+ |# q% C& l3 A; O5 @
Logarithmic scale, 对数尺度
- \* J' ~: ]' \: D2 h6 [Logarithmic transformation, 对数变换, N, P+ a. p$ ^( E' \; O& Q
Logic check, 逻辑检查5 j D* k R4 O p( g) J
Logistic distribution, 逻辑斯特分布2 l V# G/ P) V
Logit transformation, Logit转换) c, V$ b! F; Q4 o1 F4 M+ N& [, H
LOGLINEAR, 多维列联表通用模型 A$ K* m; y' D3 G6 ~
Lognormal distribution, 对数正态分布
5 u" \1 s$ e+ H, C6 d) e- KLost function, 损失函数
8 j. x5 y" ]& S6 h J7 FLow correlation, 低度相关9 D% k* y$ |9 r2 V" b: J
Lower limit, 下限, E* \* y6 i2 a& T' S' v- i
Lowest-attained variance, 最小可达方差8 m0 A7 _$ R$ R4 Z6 l4 z2 N5 ]3 b
LSD, 最小显著差法的简称4 t. t7 |& P( F6 ?, \
Lurking variable, 潜在变量
1 `- x% m6 ]$ e6 jMain effect, 主效应
# n6 U# j7 T( q, j) r: w6 mMajor heading, 主辞标目- F6 M- q+ I7 G- E
Marginal density function, 边缘密度函数$ l7 z4 @6 R0 U, @2 Q; z9 N
Marginal probability, 边缘概率
% @1 g$ c7 T! d) N' j3 nMarginal probability distribution, 边缘概率分布
% N7 c! ]7 D; Q f! O" @Matched data, 配对资料$ N9 Q( e% U) C' o
Matched distribution, 匹配过分布
6 E C4 n/ M5 L( ~1 jMatching of distribution, 分布的匹配% {3 m% y+ y3 O. \" [0 @4 L) Z
Matching of transformation, 变换的匹配: p+ K' B4 V5 L7 i9 ?2 J' n
Mathematical expectation, 数学期望
$ M3 o: J# T2 P1 p% G( a% N6 D, oMathematical model, 数学模型% N# O2 S3 S( K
Maximum L-estimator, 极大极小L 估计量( {& m3 n. g8 I9 j! C% r
Maximum likelihood method, 最大似然法% i/ [: {3 v/ a
Mean, 均数
# u! q; |( [' Q7 q- I$ ?3 n/ DMean squares between groups, 组间均方+ m& q5 s& h, r2 {0 O
Mean squares within group, 组内均方" u8 j1 I4 v, `# D1 O& e. @
Means (Compare means), 均值-均值比较
) z: J/ k' Y3 ~; ?; {Median, 中位数6 L. u8 Q9 N/ U$ d: F2 D4 h
Median effective dose, 半数效量) u* |2 d5 P% u
Median lethal dose, 半数致死量3 `* o- E! k$ b, s' e9 `
Median polish, 中位数平滑
: d7 ^$ [" y: d+ T0 NMedian test, 中位数检验 ^: O. ^5 X# l" n
Minimal sufficient statistic, 最小充分统计量
( E; W5 y- g0 J, a1 l9 l' S) m+ wMinimum distance estimation, 最小距离估计; |9 \" E. C6 e
Minimum effective dose, 最小有效量4 l; Q' z- R0 X: h r, ^" @" Q
Minimum lethal dose, 最小致死量
' |# b* q7 s! |Minimum variance estimator, 最小方差估计量
8 l$ s6 }) \1 m1 HMINITAB, 统计软件包
! k9 O |# p3 WMinor heading, 宾词标目5 t6 H$ c' J* z' Z. j
Missing data, 缺失值
' O+ T& u/ _! C8 o2 TModel specification, 模型的确定% k& H' E# v* d" u
Modeling Statistics , 模型统计
( l* p& ~& Q" a( r% ?: p9 dModels for outliers, 离群值模型
: o( ]- y. R7 }0 hModifying the model, 模型的修正6 ^' x' M0 D% |1 C: V& q
Modulus of continuity, 连续性模
% H8 _, \& M6 Y) J4 TMorbidity, 发病率
' W) r7 r$ ]% lMost favorable configuration, 最有利构形
* u5 M- T& |3 U3 e8 z, tMultidimensional Scaling (ASCAL), 多维尺度/多维标度( F' \; |" d. g+ b
Multinomial Logistic Regression , 多项逻辑斯蒂回归
0 J) [& a! c, {Multiple comparison, 多重比较9 W! d* C2 t4 p+ [* t8 Z
Multiple correlation , 复相关
) R3 M6 l( u* v1 KMultiple covariance, 多元协方差
' G( @" ]' L# I) q1 E* L6 `Multiple linear regression, 多元线性回归
- v0 H; Y% Z$ s! c9 IMultiple response , 多重选项
* f" {, H$ ^. W8 B8 m3 G v' O# V! `Multiple solutions, 多解- s S* N! ~, F+ ^( o
Multiplication theorem, 乘法定理
; q( n6 `. C1 J/ N4 s- R9 i7 EMultiresponse, 多元响应
4 j& y& W. O. O2 VMulti-stage sampling, 多阶段抽样
+ l, X9 H' i [Multivariate T distribution, 多元T分布8 @5 w4 `6 _" i3 B
Mutual exclusive, 互不相容
5 \% M7 ^9 E2 a0 Z3 `$ pMutual independence, 互相独立. o. v" h$ |8 z# B- \* o" B7 d
Natural boundary, 自然边界
8 e+ i8 @0 m) _' N+ o' F* f$ v- sNatural dead, 自然死亡; t% S/ b' j. r- |. G
Natural zero, 自然零
: t6 w: P L- g* @- O: R6 x7 nNegative correlation, 负相关( }+ j# M! n0 F6 O
Negative linear correlation, 负线性相关. s# R* F4 x: h" A) i
Negatively skewed, 负偏* `3 K) a5 v: z! x! ~' X/ L t5 i
Newman-Keuls method, q检验
& j7 J) ]( V9 m/ dNK method, q检验8 A) Z4 _- ]6 W3 d* P9 K1 z
No statistical significance, 无统计意义
9 t" A( ^. D, Q* K# iNominal variable, 名义变量
" s+ L ^- D3 w- e o! W7 p" ONonconstancy of variability, 变异的非定常性
: |2 S d& i4 C$ K9 g5 RNonlinear regression, 非线性相关
; x( d; S/ u+ DNonparametric statistics, 非参数统计
' f4 N O( a1 Q; h) }6 ~Nonparametric test, 非参数检验
. P7 W; {* ^- Q5 Z; J* `( zNonparametric tests, 非参数检验* J- o5 a2 p8 U
Normal deviate, 正态离差
9 Y+ h8 Y& R$ V( w- y# @) [- G7 ONormal distribution, 正态分布6 O7 V/ O# d+ `+ F3 O* l
Normal equation, 正规方程组0 L( _" w: t U$ B3 P
Normal ranges, 正常范围% L4 O: N( y) i" c: ?+ K& z
Normal value, 正常值4 ?( e$ P. z) M3 O
Nuisance parameter, 多余参数/讨厌参数
G$ P' Q4 E# ~6 ~- G oNull hypothesis, 无效假设 7 `1 i: n, A' `# O- ~) j3 A) u
Numerical variable, 数值变量
$ x g! m% J3 F1 D" ^Objective function, 目标函数
5 P6 [8 }$ ^& j1 H! {Observation unit, 观察单位" x/ @- n" s; ?5 ^* C
Observed value, 观察值2 B X$ ~6 W9 s& e4 {& n
One sided test, 单侧检验0 i) y- J: f9 Z& N
One-way analysis of variance, 单因素方差分析
2 v( I( d6 l- |1 f# N3 VOneway ANOVA , 单因素方差分析9 ^$ d- V6 @; Y' p* z
Open sequential trial, 开放型序贯设计
0 W, ~5 K4 Y: n5 L$ \1 QOptrim, 优切尾8 d8 d6 x8 }+ C0 V
Optrim efficiency, 优切尾效率$ M' d) J# k/ j7 d" d) m
Order statistics, 顺序统计量. ?; Y9 n* D* l
Ordered categories, 有序分类
, C# j5 C) F$ B7 l9 `3 v" o: EOrdinal logistic regression , 序数逻辑斯蒂回归
2 s' H4 H* u0 R5 T ZOrdinal variable, 有序变量
. H# U$ o. C5 QOrthogonal basis, 正交基
( f2 t% J" G+ @; x H/ YOrthogonal design, 正交试验设计
! ]7 x# a. I F. h9 FOrthogonality conditions, 正交条件! }% [9 z6 a; V5 u e
ORTHOPLAN, 正交设计 . x2 S, J1 d6 l$ B$ S
Outlier cutoffs, 离群值截断点
* r3 a8 e+ D! {- FOutliers, 极端值' ~8 m$ o+ A' O/ v9 W6 \8 X% H
OVERALS , 多组变量的非线性正规相关
0 l, }; v4 i9 L9 sOvershoot, 迭代过度) `! L, X' @2 u, ^& `
Paired design, 配对设计
* w p2 _5 \2 A1 s1 r9 NPaired sample, 配对样本
; {2 x1 y. s+ N0 S- Q7 ~% B/ hPairwise slopes, 成对斜率6 n2 s& `2 r% R" \9 v; N- D
Parabola, 抛物线: B- j |5 ]- F1 @
Parallel tests, 平行试验% c: Y7 b! |* O, x2 O# A
Parameter, 参数
+ i& S0 {' _' J ?3 dParametric statistics, 参数统计
: E6 O: c8 r) V# T; P' l3 Q' _Parametric test, 参数检验/ n" q: T* [! z7 l7 E& ~
Partial correlation, 偏相关
/ F/ y1 D* \5 C* w0 [1 ]3 z' Z* [& OPartial regression, 偏回归
6 A7 e% `. V4 |9 c* C; RPartial sorting, 偏排序2 h5 A2 B6 h7 m
Partials residuals, 偏残差
" W2 R* F; J, ^Pattern, 模式* `" a8 D+ e. Q7 `5 W# T
Pearson curves, 皮尔逊曲线
# X) y8 L& U& _- h$ TPeeling, 退层
: Z9 A+ o& ]; p5 m [" C% c5 G$ T* xPercent bar graph, 百分条形图
2 b' _2 r7 i( ^' N- `0 aPercentage, 百分比. U0 y' ]! U% g" f6 {% r$ }
Percentile, 百分位数% L4 G& N. ^5 q8 }) `; ]
Percentile curves, 百分位曲线: W8 w, L. x, J! U0 x8 z* N$ d
Periodicity, 周期性
% G3 L7 B. c a, |1 KPermutation, 排列8 B' W: v0 Z2 ]
P-estimator, P估计量1 f: }) l5 z+ A$ Z1 Y
Pie graph, 饼图0 X0 l2 t# s6 ^+ x- T/ O& s
Pitman estimator, 皮特曼估计量
) `* O( }7 \& @Pivot, 枢轴量' q( c* V: r; K9 @0 Q3 N! B4 b
Planar, 平坦
0 X+ X- i( d( j; KPlanar assumption, 平面的假设$ _/ z; l& i% v/ a+ `
PLANCARDS, 生成试验的计划卡
2 j* p Q# x i/ MPoint estimation, 点估计, M$ M& ~: T. I/ C( F/ F" r5 C
Poisson distribution, 泊松分布. Y. ~% }/ E5 T0 _
Polishing, 平滑3 A8 k2 M- Z( l! Q- ~
Polled standard deviation, 合并标准差
3 @% a- [7 g$ y9 ~' W. ]Polled variance, 合并方差
& i" \0 y; }2 @' uPolygon, 多边图
, e9 z9 K, u/ ]/ c& m' V7 p! ]Polynomial, 多项式
( v* Z- ~, N5 a! r6 a' HPolynomial curve, 多项式曲线
, [8 x- H5 F/ dPopulation, 总体
, j( v7 ]3 c7 L7 U, Q0 uPopulation attributable risk, 人群归因危险度
0 R3 P/ t. g5 hPositive correlation, 正相关
7 P1 f) n; J5 @- C6 ]! z7 v+ LPositively skewed, 正偏
3 p* }" @5 Z1 W" |. ]3 LPosterior distribution, 后验分布. W. E% c5 [! X- p. C/ Y& e% m
Power of a test, 检验效能
/ h. @1 I5 q2 H; `Precision, 精密度8 @( l9 }# `( [& k
Predicted value, 预测值" M6 i) d8 h, A0 C
Preliminary analysis, 预备性分析
9 d* F3 M1 E. w( ?! ^Principal component analysis, 主成分分析
) M$ w9 `2 L8 i4 v* DPrior distribution, 先验分布5 O) C6 F2 F4 {% l8 b( C. a; |
Prior probability, 先验概率
' h* w d' [' b$ i: TProbabilistic model, 概率模型# J5 o! P: B, o: Z
probability, 概率 C- Q" r D5 F) C7 Z" `
Probability density, 概率密度
9 O2 h/ X, H I) \" J" L, }9 GProduct moment, 乘积矩/协方差
3 d! B; P" X3 n5 KProfile trace, 截面迹图: j0 I0 D7 x0 W. t
Proportion, 比/构成比
/ `# x8 U4 i/ ?* `/ CProportion allocation in stratified random sampling, 按比例分层随机抽样
- W2 E0 ^' u6 U% YProportionate, 成比例
+ G# l# `( ^" L& dProportionate sub-class numbers, 成比例次级组含量
& j. ~; U; b% s! BProspective study, 前瞻性调查
5 ^! @ I* p0 O4 r% P$ AProximities, 亲近性
: b0 C1 m. H! c, w4 l4 w" {Pseudo F test, 近似F检验2 K. I# T8 f9 F3 W
Pseudo model, 近似模型
! z* ], K; |# q* W4 oPseudosigma, 伪标准差
' }% ^- ], X- H* f3 Y! u$ dPurposive sampling, 有目的抽样8 c: N9 z# D: J' d! m
QR decomposition, QR分解* a: I5 o b9 d
Quadratic approximation, 二次近似; P9 `" ~' i3 i+ T- W
Qualitative classification, 属性分类2 |* V7 {5 F& C2 |5 Y+ q
Qualitative method, 定性方法+ I+ }4 w) L, v' R: E; a2 |, h
Quantile-quantile plot, 分位数-分位数图/Q-Q图% K1 f9 `) }5 g; s5 |8 M
Quantitative analysis, 定量分析) u7 S+ T; X F5 M" l
Quartile, 四分位数+ ?# R/ H& X" P! p: {+ M- D2 P/ d5 p
Quick Cluster, 快速聚类
7 R# `# I# X; c S! wRadix sort, 基数排序
+ h* u) k) ]' M* ^, ]6 V) X! ]+ pRandom allocation, 随机化分组
% _8 U- P' w% N9 U" T5 k. vRandom blocks design, 随机区组设计6 x, F: a: s, |
Random event, 随机事件1 }" T! Y9 @" C/ j' e
Randomization, 随机化
4 @: L) K5 g6 |. YRange, 极差/全距
6 Z5 B; P4 n! C: s. L9 o. LRank correlation, 等级相关3 ^ l7 t9 y. Z" |! J8 _
Rank sum test, 秩和检验
" `3 i5 ^! p6 _5 M5 TRank test, 秩检验* E& W0 U) @9 w5 r0 f' c
Ranked data, 等级资料3 N& m0 `# M) p9 _2 ~5 @
Rate, 比率
; `) Q/ w% B" t0 T, KRatio, 比例 Z; v9 [2 n6 [3 z
Raw data, 原始资料( Q& G9 d0 G2 G/ k k3 C* Q+ }0 E
Raw residual, 原始残差. c) P5 A9 a, B |6 J. \
Rayleigh's test, 雷氏检验
5 I$ h; Z7 e. \- e) o% }0 j/ C3 xRayleigh's Z, 雷氏Z值
: {8 C5 E* j; t/ iReciprocal, 倒数
7 {- k! d" K$ Z' n/ f: jReciprocal transformation, 倒数变换
' q2 ]' v m: p6 XRecording, 记录! N/ q1 _! b* o, ^3 ]" W x
Redescending estimators, 回降估计量
% x! j$ f9 h8 n( SReducing dimensions, 降维( y5 C1 C* H; g. x }. Y" U
Re-expression, 重新表达
2 N$ d `' d5 `' j' CReference set, 标准组 j" }% p, R" Q% F# A7 V
Region of acceptance, 接受域 t A- G; b& B( W5 @
Regression coefficient, 回归系数
4 U) H. F5 I2 e& `+ [+ v' c; yRegression sum of square, 回归平方和
& T4 q9 B. \3 V% qRejection point, 拒绝点0 @/ r+ B- f* H$ r$ k
Relative dispersion, 相对离散度2 Y8 p7 N* \0 l) b9 x' N
Relative number, 相对数
f% y. n7 w# a! ^2 PReliability, 可靠性7 V. R' i5 m0 W6 ? | j% U
Reparametrization, 重新设置参数+ ^3 G3 `+ x3 h% B3 F3 F
Replication, 重复+ l8 \, W, p3 B% n9 o4 z
Report Summaries, 报告摘要
2 {9 j3 w+ c: H3 f) {6 x% cResidual sum of square, 剩余平方和
% n3 m' e" k7 X* Z# UResistance, 耐抗性$ F& i h1 k- B N/ o0 {
Resistant line, 耐抗线, Y' u" T. A1 T( x
Resistant technique, 耐抗技术
% o! L0 j2 }# }3 u- ~; gR-estimator of location, 位置R估计量9 `- `' ]( r+ C7 N
R-estimator of scale, 尺度R估计量
/ m1 g8 x. V4 L5 W) Z) K4 o6 \3 nRetrospective study, 回顾性调查 i6 [! Z6 |3 _: |
Ridge trace, 岭迹
# S# D3 U6 ?% J6 nRidit analysis, Ridit分析
; v6 \. t, ^# q1 P9 {9 eRotation, 旋转
# G+ R- N$ d- ]2 m# kRounding, 舍入
! [( @7 ?1 e0 @+ L( [9 u- I9 GRow, 行8 k: I* G3 k. h1 i8 y0 N- T
Row effects, 行效应
1 n' B9 b! i D/ g. \1 A5 z9 WRow factor, 行因素1 Z& _" ?, ^; x
RXC table, RXC表! {$ y- Q4 ^* A. F g0 Z5 z
Sample, 样本4 p5 P( h+ U* T3 t
Sample regression coefficient, 样本回归系数
7 f, X( P5 c$ P! a; \" g5 WSample size, 样本量- F; P. U% y% S; C) ?0 N. M0 C4 |
Sample standard deviation, 样本标准差0 r) T) u8 A3 Z
Sampling error, 抽样误差
0 d4 U {- e M% ?6 O3 MSAS(Statistical analysis system ), SAS统计软件包
. L$ Y, J- z7 Z7 N) h) PScale, 尺度/量表+ A3 } W( y) x/ {
Scatter diagram, 散点图2 N; @: ~( z2 \. p/ V _" p2 Y: w
Schematic plot, 示意图/简图
# r; J3 u' ^9 m" {# k8 VScore test, 计分检验2 [+ Z. j ~# Z( v
Screening, 筛检2 l$ L* Y' e, X) J* W1 g
SEASON, 季节分析 + v, }5 [" {* N. K1 O
Second derivative, 二阶导数7 d. T1 e; R$ |. ~3 W" N9 q5 r. X) @
Second principal component, 第二主成分" K6 r6 j8 F6 n8 J- u
SEM (Structural equation modeling), 结构化方程模型
, C( q: [. D6 c: ESemi-logarithmic graph, 半对数图
" k7 ?8 ~+ M2 CSemi-logarithmic paper, 半对数格纸
# w. Y4 A* x4 D+ \1 N$ Z* I5 ESensitivity curve, 敏感度曲线
! M; U; Q2 X0 U. R2 d9 Y: F" O `/ V& NSequential analysis, 贯序分析7 X! O& ^4 Y0 V' f* s" x6 u2 Q8 u
Sequential data set, 顺序数据集
; P$ n; k& i9 E9 Q6 u- T5 GSequential design, 贯序设计 f% n+ o& p% ?9 J! p
Sequential method, 贯序法
) O; G4 m2 x) sSequential test, 贯序检验法( v V* f" F) G
Serial tests, 系列试验. b0 U7 V2 W1 q* |3 ~: P3 A
Short-cut method, 简捷法
# A6 i$ o5 a ~& I" c- VSigmoid curve, S形曲线! `$ s; I' @$ n9 ^* W
Sign function, 正负号函数
* S% ~4 X- e. q r0 i6 z. LSign test, 符号检验" S& T# Q6 c% B
Signed rank, 符号秩
" D$ z+ [ m9 V# oSignificance test, 显著性检验
8 b* v+ c& v- W2 C% c2 g- aSignificant figure, 有效数字
: A- i* A8 x8 @$ y* ]Simple cluster sampling, 简单整群抽样
% e( A6 `' `% i1 F4 E7 t! L% TSimple correlation, 简单相关
1 b6 c" V3 J2 N- H" p f" |Simple random sampling, 简单随机抽样
6 j0 t. e; {6 f. d5 y. ?Simple regression, 简单回归
8 z& L8 \- q( b+ }2 osimple table, 简单表0 P/ K6 E' u8 `. n! }
Sine estimator, 正弦估计量
- d0 J! g$ \2 Q- w% t2 N( n( }Single-valued estimate, 单值估计! j' b& ?& W. s/ I' e
Singular matrix, 奇异矩阵
% ^- \/ | a3 @# v1 nSkewed distribution, 偏斜分布
7 }7 }* o6 a; M2 XSkewness, 偏度0 N/ I5 _9 H% K1 n
Slash distribution, 斜线分布
% H7 [3 B+ B* r7 Q; {# o! G; OSlope, 斜率
F4 z0 P& _8 @1 x# c0 m: GSmirnov test, 斯米尔诺夫检验
1 @! d2 N' z3 I: k( x @) r+ mSource of variation, 变异来源& F4 L8 Y& u* F1 v! r: y x
Spearman rank correlation, 斯皮尔曼等级相关
5 h/ W+ {( X/ T% C) Z* ^- ?+ [; bSpecific factor, 特殊因子" H4 F T4 `9 T# c, m$ u0 {
Specific factor variance, 特殊因子方差5 Y& R4 ^+ u6 y! O8 r
Spectra , 频谱2 P- G( `, F) t2 ?
Spherical distribution, 球型正态分布, r2 p& e; N1 p9 T! ?/ Y
Spread, 展布0 G; r9 I) |8 }: z
SPSS(Statistical package for the social science), SPSS统计软件包+ ~ U, c- a) L7 F+ |4 D
Spurious correlation, 假性相关- ^! O( [- R0 N0 ~9 h
Square root transformation, 平方根变换
' ~1 N. ?: I; v- ^8 k/ OStabilizing variance, 稳定方差
3 _3 @' h7 {$ @4 t: ~% ~* YStandard deviation, 标准差3 D9 ]7 l+ Q. L
Standard error, 标准误
6 |& v. H' D9 ^6 b) ZStandard error of difference, 差别的标准误
* y1 N( r- J- r6 ?. b' k dStandard error of estimate, 标准估计误差# t3 e% d" H7 Y3 h
Standard error of rate, 率的标准误& d: Q- p2 o) b1 L- v% L! _4 z8 ^
Standard normal distribution, 标准正态分布8 M- x+ w; m/ ]! X; \, ^ W
Standardization, 标准化
% z) Q, T. w& R1 d6 \Starting value, 起始值6 a# W! A3 b3 T# s
Statistic, 统计量9 D0 M3 J T, C0 ]$ C
Statistical control, 统计控制; c# ~; r( F9 |0 s% u
Statistical graph, 统计图4 N; z5 V5 E+ Y- b0 M% |$ z
Statistical inference, 统计推断3 w! d$ I9 X; @; D5 ?" u3 `4 [ F
Statistical table, 统计表
8 Q# a5 g5 s& y; j# s4 r8 ISteepest descent, 最速下降法0 f& S1 j3 L1 X3 G- r, z0 }1 Q( R# `
Stem and leaf display, 茎叶图, G8 R) ^9 C" S0 r# J( t4 C
Step factor, 步长因子
. \& b! c' Y6 u; x) fStepwise regression, 逐步回归
7 [/ t( y/ ^3 Q! |Storage, 存5 K0 x4 k w5 u1 M5 ]" M; ~
Strata, 层（复数）2 D4 H; V* e. L; V
Stratified sampling, 分层抽样9 H0 Y6 C# W' g# @7 o' U' J5 I
Stratified sampling, 分层抽样* ?) ]$ s% n- o& r# h( E
Strength, 强度
$ S9 p3 k" i, E4 KStringency, 严密性
4 u$ O. g" k8 Y- g! y0 [. ^Structural relationship, 结构关系
+ v( g% C) z6 n+ u: zStudentized residual, 学生化残差/t化残差
5 `0 d W' |2 [ N4 I1 TSub-class numbers, 次级组含量4 S4 k% d9 C7 L: I/ o4 X) [# \
Subdividing, 分割, i' o- R3 `3 P9 r
Sufficient statistic, 充分统计量
5 p/ r/ m7 L, i4 D! r5 ?Sum of products, 积和
% L& n, c" T) CSum of squares, 离差平方和
5 i" W1 R( a5 M+ X& j1 jSum of squares about regression, 回归平方和+ b' y5 Z! t5 n4 A6 _5 g6 d) k! P! N
Sum of squares between groups, 组间平方和
) l, d. W* y6 d4 _& FSum of squares of partial regression, 偏回归平方和 o4 z. w, D& a; j- H4 g' C0 |& W
Sure event, 必然事件
; i, `3 h i" ~" Y& sSurvey, 调查
3 r1 f2 Z& Z W; j) ^/ R- V, RSurvival, 生存分析
u! E) ]+ @. v8 q7 A4 f/ RSurvival rate, 生存率; _& [- l( A8 E) Y9 G& K
Suspended root gram, 悬吊根图
) F" D% M& C( M+ k( }) ?- f( z& ?7 oSymmetry, 对称 @, `0 {8 v. S4 V- N" d# R0 f
Systematic error, 系统误差
6 V6 ~; v9 c* l5 C* Z: x1 v" E; OSystematic sampling, 系统抽样
; G( ?% b. ~ Z( g4 O( DTags, 标签" [+ z' K: E- S, o
Tail area, 尾部面积6 t2 W. o: E- Q# X" m1 I3 C
Tail length, 尾长+ n# @5 M7 H8 }
Tail weight, 尾重
6 u6 \- s3 V1 H( L5 MTangent line, 切线
' j4 F$ r* H4 \" T9 tTarget distribution, 目标分布
$ H# W; V" b- j0 s2 bTaylor series, 泰勒级数
; L& }, J; Z$ |6 W3 p- qTendency of dispersion, 离散趋势
" n' Q$ P3 S1 o& k+ u0 e( U% ATesting of hypotheses, 假设检验
8 X+ v( U" ]: p9 U+ ?Theoretical frequency, 理论频数8 U! h1 ]1 v% r0 P
Time series, 时间序列
, F' a4 u/ y i+ y$ D0 WTolerance interval, 容忍区间
7 O2 i+ S6 {9 E9 p) j; fTolerance lower limit, 容忍下限) d d2 K( l! x$ I3 r# w$ `
Tolerance upper limit, 容忍上限
. ^# ~7 S/ y6 G6 D- PTorsion, 扰率
1 N) } Q, P2 y. w# tTotal sum of square, 总平方和
" D7 K* Q% h. VTotal variation, 总变异
5 d! Q- u% T" S' W) F: x4 PTransformation, 转换
0 y4 a, d1 t% H9 K/ iTreatment, 处理
# ^2 z/ t$ ^* _) ~/ ZTrend, 趋势5 C; J. a( z3 v* K/ c" c
Trend of percentage, 百分比趋势
% C j5 f5 E# G0 ~, hTrial, 试验 ^8 O1 E0 g* _$ T
Trial and error method, 试错法
/ @! @/ L: |3 q: mTuning constant, 细调常数
9 x, K( i0 h7 Y* Y( [& sTwo sided test, 双向检验
0 E- w+ ~" K7 n/ H' WTwo-stage least squares, 二阶最小平方# A2 n1 r. l; @( y: V
Two-stage sampling, 二阶段抽样) ^/ d+ A, J. u1 a
Two-tailed test, 双侧检验* v7 ~5 M$ ~8 m5 j+ M) J% X
Two-way analysis of variance, 双因素方差分析. H: x8 ^" H9 _
Two-way table, 双向表& C% I& {5 j: C+ r9 z
Type I error, 一类错误/α错误' \) C* }0 D* X
Type II error, 二类错误/β错误% V- p, \) }/ |# f( h7 ~4 t3 `
UMVU, 方差一致最小无偏估计简称
. S/ Y8 w4 G2 N8 X3 PUnbiased estimate, 无偏估计
" D$ l5 H0 g* q5 |$ }: fUnconstrained nonlinear regression , 无约束非线性回归& P& A' f" D3 R4 S) Z/ ^+ K& N2 H, O
Unequal subclass number, 不等次级组含量
% }* f. v9 M9 T2 Z1 s; w$ O }! nUngrouped data, 不分组资料9 v: B- |: B4 v" ^& y
Uniform coordinate, 均匀坐标* t, D6 S1 U% K1 G) z
Uniform distribution, 均匀分布
% d3 f L; k: xUniformly minimum variance unbiased estimate, 方差一致最小无偏估计& D6 b2 Z9 h0 `' a
Unit, 单元
! E) O+ [3 Z1 D. E( zUnordered categories, 无序分类
8 e2 K+ W1 H$ t4 ZUpper limit, 上限* Y; i: d& `; x0 l
Upward rank, 升秩* F/ c" L1 m5 @4 p8 K0 l% h
Vague concept, 模糊概念
2 s* B6 y; x7 h" Q$ I* W8 aValidity, 有效性
7 p( o" e! W' r. m* xVARCOMP (Variance component estimation), 方差元素估计# E; W5 i+ R1 e5 _. A+ e0 N
Variability, 变异性
+ A4 E' K) w: M$ u: sVariable, 变量
9 ?8 i7 Z2 W6 n% y L: e! O; gVariance, 方差
6 a6 U& f2 V: i. l# w/ kVariation, 变异7 b( k: \' G4 }8 a2 u- P. K
Varimax orthogonal rotation, 方差最大正交旋转
8 V& U( [7 L% r- k4 h9 S, c/ YVolume of distribution, 容积
- F- @* ~$ B6 w4 O9 ~$ [4 u! f( X4 pW test, W检验
+ J0 s5 M2 {, O; N# R9 hWeibull distribution, 威布尔分布 m! M! x) A1 L4 ]0 Y: r
Weight, 权数3 X' M" N% L; B3 z
Weighted Chi-square test, 加权卡方检验/Cochran检验
$ E! x# T1 Y; h% h* EWeighted linear regression method, 加权直线回归; m6 w1 K% \7 a" q
Weighted mean, 加权平均数
# M4 C; k! b! G/ v# MWeighted mean square, 加权平均方差
5 g& C) C: e# P+ aWeighted sum of square, 加权平方和
; }, }# f8 w. s$ [- D: D8 HWeighting coefficient, 权重系数9 U' V/ O- g D, L: i- }
Weighting method, 加权法 6 q, @: q6 n H2 t, k
W-estimation, W估计量% m0 y3 S1 |: [6 J( C7 O+ n+ c7 r2 N
W-estimation of location, 位置W估计量$ X1 ]3 L! K& ^; @. x6 o% K: ^
Width, 宽度, F: i4 Q3 V Q" H* q0 x: I
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验) k( N. Q; D9 Y0 Y7 d& W# L$ D- b
Wild point, 野点/狂点% d1 o5 i' C- a3 D' E( C
Wild value, 野值/狂值
$ _8 e7 M4 s7 `' ?* wWinsorized mean, 缩尾均值
, G5 `0 T2 q0 z: a6 V, l9 ~Withdraw, 失访
+ k4 Y' a- |2 s! s8 ?$ F3 B9 PYouden's index, 尤登指数' w, L: K1 n, Z5 G# d
Z test, Z检验8 ?: _- l; R* q" S
Zero correlation, 零相关
3 D" B6 m0 c5 T, Y& @- V" p. qZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
