|
|
Absolute deviation, 绝对离差
: u/ E8 s, `3 X( Y- o9 XAbsolute number, 绝对数# z3 s' J# j: \
Absolute residuals, 绝对残差* ^% G+ ^4 P; {3 a; C$ N
Acceleration array, 加速度立体阵! O- k7 c: \# E) P9 {
Acceleration in an arbitrary direction, 任意方向上的加速度3 p/ z3 c( o- J8 f; y! j
Acceleration normal, 法向加速度( F! a; z- w3 z5 K" I
Acceleration space dimension, 加速度空间的维数9 L$ c; u4 F$ I0 G$ p W' Y- \. V
Acceleration tangential, 切向加速度9 r! R! O2 p& r, c( k" s9 T
Acceleration vector, 加速度向量
' V1 ?& L8 r# p) ^- zAcceptable hypothesis, 可接受假设/ N0 s' w' `/ T6 S
Accumulation, 累积* r1 q. U9 l" y
Accuracy, 准确度5 s: G! y4 L$ p; n/ f
Actual frequency, 实际频数
/ t# A5 A/ k+ m* a$ I X' R9 S5 ^Adaptive estimator, 自适应估计量
! o! x* K) Y, h9 TAddition, 相加3 K% n$ k" G) R' X6 z1 T2 u
Addition theorem, 加法定理
; i }/ t% t; \Additivity, 可加性
' w7 h! y; F( S0 e1 ^' C0 eAdjusted rate, 调整率* Q6 F* d; E/ I" B$ c P
Adjusted value, 校正值
^( Z; g5 |% d' u) oAdmissible error, 容许误差7 N& J4 m( E5 p+ c6 |
Aggregation, 聚集性* |) F' ]+ ]5 V/ ^0 S' W/ s
Alternative hypothesis, 备择假设
8 j, o' f$ u! l" v5 e/ d; y, sAmong groups, 组间/ k" a, {) I* \( R5 c$ `2 i! S
Amounts, 总量
! v: M! \/ w6 XAnalysis of correlation, 相关分析8 c V; Y3 H0 p; o
Analysis of covariance, 协方差分析
8 Q( M" M& L/ U8 MAnalysis of regression, 回归分析
/ C6 t" H8 y. ]0 hAnalysis of time series, 时间序列分析
% ?2 l8 L7 m% w4 R' LAnalysis of variance, 方差分析
8 q d/ a& G. `/ }8 }Angular transformation, 角转换+ h% e6 ]1 \9 @# L, w; {9 F' r
ANOVA （analysis of variance）, 方差分析
2 U. S/ r8 _7 YANOVA Models, 方差分析模型! p, _5 g2 U, r
Arcing, 弧/弧旋, H5 \% ]' A4 Y- k
Arcsine transformation, 反正弦变换
! \6 v; X4 O; e" AArea under the curve, 曲线面积
3 j% |9 {% y( a+ p& iAREG , 评估从一个时间点到下一个时间点回归相关时的误差
2 X4 D, R* l# X0 iARIMA, 季节和非季节性单变量模型的极大似然估计
. p8 i6 [2 I# I( B- |! _Arithmetic grid paper, 算术格纸9 Z4 f x) _ v# Q6 Y+ l" B, L5 o$ D
Arithmetic mean, 算术平均数( \- h: p: |! [9 [8 U5 z" `
Arrhenius relation, 艾恩尼斯关系: p- I! A2 J! k4 M! U% h( ^
Assessing fit, 拟合的评估
, I9 f/ t4 _. T6 A4 TAssociative laws, 结合律7 f- T! m4 N0 ^
Asymmetric distribution, 非对称分布
$ J4 M! I/ d. `) L4 NAsymptotic bias, 渐近偏倚
?5 N; S( c0 S2 W! z7 b% SAsymptotic efficiency, 渐近效率5 ?4 f0 z8 V6 x7 r& B7 Y. M$ S
Asymptotic variance, 渐近方差
, \" F9 m7 p- x) R0 P! uAttributable risk, 归因危险度
. K- o$ x! X: k' ^ U. eAttribute data, 属性资料 @2 b. V9 k8 u# i9 M) x
Attribution, 属性
3 |; A" B6 P I' lAutocorrelation, 自相关
$ l4 G% X: Y& @6 B' ZAutocorrelation of residuals, 残差的自相关
! `8 A8 K0 I3 X# ^' m uAverage, 平均数3 t: ?- S! X2 Z% W$ a! V
Average confidence interval length, 平均置信区间长度7 X& X% u' k3 h5 p% f9 A5 ^
Average growth rate, 平均增长率+ l. G+ `1 p1 k. @" H( Z* a
Bar chart, 条形图
. s+ b' [; a: G; G0 d" G1 YBar graph, 条形图
, Y: V( x' a$ g4 w! dBase period, 基期0 P- @, j8 }6 g" V9 g M/ Q) m
Bayes' theorem , Bayes定理5 q- }; A/ g& A5 e" ^$ v" y
Bell-shaped curve, 钟形曲线& Z: j/ f/ k o" j1 S% C* m( I
Bernoulli distribution, 伯努力分布! y" B% }/ N: _% V) S* {
Best-trim estimator, 最好切尾估计量 h0 T& c1 ~/ t! Y
Bias, 偏性
4 B# N R+ J6 s/ Y& YBinary logistic regression, 二元逻辑斯蒂回归 f8 e( K( y# v8 L) |) C
Binomial distribution, 二项分布0 w( V$ z/ Y- D" f
Bisquare, 双平方% L2 I- Z; x! C0 ^$ N
Bivariate Correlate, 二变量相关: x0 d0 c1 {6 r0 d
Bivariate normal distribution, 双变量正态分布5 {3 R) S4 U2 C n% v/ ?4 m1 W
Bivariate normal population, 双变量正态总体
0 @, {+ R4 U5 G1 ^Biweight interval, 双权区间
8 o* ]; r, |" ?4 z3 E& QBiweight M-estimator, 双权M估计量* f4 n' i8 s) M4 O, q6 g
Block, 区组/配伍组
$ Z4 h7 g/ j& Z( n1 ?/ cBMDP(Biomedical computer programs), BMDP统计软件包; V; y* A! e8 z4 z4 p
Boxplots, 箱线图/箱尾图
) @) |( d! {- IBreakdown bound, 崩溃界/崩溃点# q. ^9 i: L* M, ^7 |
Canonical correlation, 典型相关" h9 ~; c/ d2 {) m+ w4 h5 ]
Caption, 纵标目8 p* |$ \% A( Y1 {& _
Case-control study, 病例对照研究6 P7 ^; I: h5 h2 y
Categorical variable, 分类变量
0 t& S& X6 T0 X& V; HCatenary, 悬链线+ K4 v% T5 f9 i
Cauchy distribution, 柯西分布
8 M, Y* E- Y( R1 x" r1 R/ SCause-and-effect relationship, 因果关系6 H' F6 Y2 M1 x6 q \
Cell, 单元
2 {8 d2 w+ c$ M& ~8 n6 uCensoring, 终检
5 M! `% E) o4 w" YCenter of symmetry, 对称中心
! m8 o$ R) j! a3 }' K. x2 p: yCentering and scaling, 中心化和定标
! ^1 `( ]: |+ x" |Central tendency, 集中趋势
: ~) {0 i4 Q+ w9 x% J1 @Central value, 中心值& J+ S: T c, b, J, J! F# N r& X3 G
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
4 ?$ L6 A' k" b4 j: {Chance, 机遇' r/ ~: ~: H# `5 Z7 O
Chance error, 随机误差
! N+ F. s8 m& n& ^9 t) O# D! N aChance variable, 随机变量0 z# T0 p' b8 F4 B5 R5 m
Characteristic equation, 特征方程9 ~, o2 }3 i, I7 p' X( q0 v
Characteristic root, 特征根
& j3 H, C- R7 C# z% W0 `Characteristic vector, 特征向量1 j+ \- U2 m- j
Chebshev criterion of fit, 拟合的切比雪夫准则' d% G2 S/ A6 G. n
Chernoff faces, 切尔诺夫脸谱图 o! `/ h5 _/ P9 e4 v
Chi-square test, 卡方检验/χ2检验
7 R8 Q& T( v- u5 ZCholeskey decomposition, 乔洛斯基分解
# `8 d; Q. ?( w# }) \! x/ uCircle chart, 圆图 - z8 K! P' _ l8 Y2 Q# }
Class interval, 组距/ A9 c" N& y4 L, C1 G
Class mid-value, 组中值
2 U4 D, W1 Z* C" H( i6 s' }Class upper limit, 组上限5 Q/ f: [- i: T" V6 b# b, H2 S
Classified variable, 分类变量
7 o: L* g1 T2 D+ uCluster analysis, 聚类分析2 K0 V# J( T/ J4 H, [. S8 d( [
Cluster sampling, 整群抽样5 E E- @) H* s4 h8 G7 m3 U% m
Code, 代码
9 O7 Y; w- `& D" [% {8 NCoded data, 编码数据
' O! y8 B- k& O6 E# tCoding, 编码
1 R# y/ H9 @& v7 Y) e+ FCoefficient of contingency, 列联系数* i" [% r; B! x; I0 F
Coefficient of determination, 决定系数
7 c7 C( [! p. c2 U7 a! E+ bCoefficient of multiple correlation, 多重相关系数
! j h$ p5 d0 bCoefficient of partial correlation, 偏相关系数1 F' T* A2 F* {9 }( h/ v- E
Coefficient of production-moment correlation, 积差相关系数
- U) X$ ^+ o B; TCoefficient of rank correlation, 等级相关系数
5 z( z( k; \9 k3 TCoefficient of regression, 回归系数6 q" E& m2 t) S* d$ ?# W
Coefficient of skewness, 偏度系数8 E1 T( ?6 o( e1 ?+ \
Coefficient of variation, 变异系数
# T0 Q- h- Z# J. p% ACohort study, 队列研究
2 V8 P' ?$ f& K$ X2 q' AColumn, 列
: c4 }- h1 w* D4 M& t! {' ^Column effect, 列效应
! D% @4 @2 `4 I7 t, CColumn factor, 列因素
$ T7 }% ~; R5 r: w3 G' h. h3 oCombination pool, 合并
' f' |; t7 f9 J" F" J! LCombinative table, 组合表4 x) m0 \5 [0 A+ X# o5 l
Common factor, 共性因子
1 \: J3 J4 w# g/ _Common regression coefficient, 公共回归系数8 Z2 d0 A" h) i; M1 Z. t" u2 w
Common value, 共同值
# n/ b I* F- k! ? \! U. J* aCommon variance, 公共方差' A5 g* b( D, ]0 a0 R' F3 W5 D7 H6 {
Common variation, 公共变异% `% {# N2 `# Z- W Z1 N* l
Communality variance, 共性方差8 w$ H) D) Q3 {% }4 |' Z) i3 b6 E
Comparability, 可比性
6 Z8 [; q+ G/ ^Comparison of bathes, 批比较
$ S- o2 ?7 G2 L+ N+ D5 ZComparison value, 比较值7 _" K9 i% E" \6 G
Compartment model, 分部模型' C% h$ b" u$ m
Compassion, 伸缩; j* y( i! {. e6 ~& w
Complement of an event, 补事件
# G, B; {6 k9 `; m* nComplete association, 完全正相关
& U, P0 `, M1 d" x& G7 \' E5 F8 gComplete dissociation, 完全不相关* U0 A' _8 U) H8 R V
Complete statistics, 完备统计量
2 b: |2 ?! H9 K' W& I: LCompletely randomized design, 完全随机化设计
3 l. r) |) [* f2 |, [$ SComposite event, 联合事件
% x X; Z2 t+ W3 ^9 @) u8 a3 D2 @9 @Composite events, 复合事件
* |4 ]/ A2 B9 m3 q+ O) ~Concavity, 凹性
' }7 `; ~" J! ^Conditional expectation, 条件期望4 H, f2 c& c( Y( P
Conditional likelihood, 条件似然
8 C' Z5 C% L: b+ \ f- TConditional probability, 条件概率
; w! o7 @- r0 W8 dConditionally linear, 依条件线性, n. A* [; O i+ v3 l
Confidence interval, 置信区间
5 i3 g# |4 O5 d+ c# qConfidence limit, 置信限% h) |/ `; n9 p2 b; d5 { X3 ?! O
Confidence lower limit, 置信下限
) L% c7 n7 ~: I' NConfidence upper limit, 置信上限
0 n4 C2 T# q% W. `- iConfirmatory Factor Analysis , 验证性因子分析
$ \3 S: E6 K2 `( \" qConfirmatory research, 证实性实验研究, ~' e. B. E7 c6 S( M x- w
Confounding factor, 混杂因素' C5 T7 N* w+ ]2 U# j/ Y8 P
Conjoint, 联合分析
3 v' i, r" s% A/ \8 r! DConsistency, 相合性9 {8 `8 B7 ?0 ?- A+ H
Consistency check, 一致性检验
6 g* i% Q1 V3 x: \6 P9 AConsistent asymptotically normal estimate, 相合渐近正态估计
, J* A1 {- a& EConsistent estimate, 相合估计
- `% r! g2 p J. _* @Constrained nonlinear regression, 受约束非线性回归
/ H- A9 H! e, I6 _Constraint, 约束2 _& s& x6 Y* d! ] x
Contaminated distribution, 污染分布2 w/ C% ]9 F4 P$ K
Contaminated Gausssian, 污染高斯分布
. {8 s, d+ P$ m+ c! b6 kContaminated normal distribution, 污染正态分布/ k6 w2 Z1 U9 q5 o, s3 z w7 |
Contamination, 污染* {( [# [: V* H! p5 b+ [. n+ S. Y
Contamination model, 污染模型
) n9 a: O& V0 N9 O# S% E: y, ?Contingency table, 列联表1 P4 q7 W4 W/ w/ m; ?
Contour, 边界线* l- H! T6 @: U) m- a1 r
Contribution rate, 贡献率5 D0 X1 J* n3 e
Control, 对照
4 l) ?- z- K3 j# m9 q, ?7 b! nControlled experiments, 对照实验, W4 y$ n+ \( ^4 z8 J# V# i
Conventional depth, 常规深度
4 ]' t! l ^" J/ K$ k! |# B5 qConvolution, 卷积 u: J0 n' z9 u) S# q4 Q4 W
Corrected factor, 校正因子6 }6 ]1 B5 Z3 U, u' s" C
Corrected mean, 校正均值9 B% q- d" I& f+ g9 d2 X: G
Correction coefficient, 校正系数
0 N t7 P" W) d) F3 }: ]4 lCorrectness, 正确性
p; o" ?) G3 bCorrelation coefficient, 相关系数6 S% w& R4 x0 W
Correlation index, 相关指数. q* q: f5 o: {; J4 ~$ n) l7 ?
Correspondence, 对应5 S3 X4 R) a0 G+ V
Counting, 计数 N7 r/ C/ Q$ \
Counts, 计数/频数
! ^8 U0 C! i- Y+ bCovariance, 协方差
0 O3 D, ~9 z$ wCovariant, 共变 ! ~% q2 e0 ~/ K6 j1 e8 A, ~8 a, c" I
Cox Regression, Cox回归
' f0 ~ z8 e `" x/ \( _6 LCriteria for fitting, 拟合准则
; e" b" u. Q* K0 nCriteria of least squares, 最小二乘准则
5 M% ]5 l6 S" W& {8 WCritical ratio, 临界比
$ X* T! j& ^& e/ [1 l; ECritical region, 拒绝域
0 g6 o M# K$ r5 I2 @( o" JCritical value, 临界值
; ~/ z H) ?3 A$ g! S: rCross-over design, 交叉设计0 H; t6 A( b+ w2 }+ l$ }' H
Cross-section analysis, 横断面分析
& e, \; E, d# _% o+ d T1 vCross-section survey, 横断面调查
% \7 R0 w5 H" wCrosstabs , 交叉表
4 J9 H$ }( \! y3 ?Cross-tabulation table, 复合表
0 u- U% r, r0 ]9 m8 GCube root, 立方根
# g5 c, X4 Z# X' {Cumulative distribution function, 分布函数" _( f0 b* Q$ E X' q3 D! V
Cumulative probability, 累计概率
) c; Y* p3 L( QCurvature, 曲率/弯曲' H' }. Z( H X
Curvature, 曲率
7 K3 \8 g+ X R& d4 g: V5 C/ TCurve fit , 曲线拟和 $ \; u! q9 ~" p; U8 v
Curve fitting, 曲线拟合6 g8 y- r! H3 N) u* K4 t
Curvilinear regression, 曲线回归
3 G$ o0 J7 E/ |; D/ tCurvilinear relation, 曲线关系
% B) n5 N. n& b z: F# k& B8 d+ b }Cut-and-try method, 尝试法
/ \ M) F* z% Z( @0 NCycle, 周期2 u2 \% i. V9 m6 @( O0 V
Cyclist, 周期性* q' w; ?( X0 z& L t: N* D& v
D test, D检验
* D; @8 c% O& s( \9 b5 x) s' m/ nData acquisition, 资料收集: {+ V$ B! Z5 \# ?
Data bank, 数据库! Q: \1 D6 J" F4 M* v
Data capacity, 数据容量 }+ A$ o& F( ~$ D+ b% T
Data deficiencies, 数据缺乏# a, j* }% R0 ?$ N
Data handling, 数据处理6 v1 ]6 H. i0 x0 { h, J3 I
Data manipulation, 数据处理( ?' @5 A) f8 l( ~# i8 X9 X
Data processing, 数据处理* B% T- g, }5 e7 G
Data reduction, 数据缩减
6 ?8 Z/ N. O( p% C4 aData set, 数据集
# u! p3 F5 e6 `+ F, C3 hData sources, 数据来源2 E! V5 U+ I4 F; Z9 h" v) W% N) m
Data transformation, 数据变换
0 o2 D! ]- l5 ?! A7 _+ tData validity, 数据有效性- ~! l/ I5 C" j9 j8 u2 d" T
Data-in, 数据输入2 l$ l# i$ ^- p% e8 J
Data-out, 数据输出! i7 x- Q% z7 t" S0 D4 s w" p
Dead time, 停滞期
M8 S. c/ d+ M5 jDegree of freedom, 自由度
, Z% M9 K9 N. ^3 \6 H# JDegree of precision, 精密度
4 V% Q% U4 [* K5 o, yDegree of reliability, 可靠性程度
2 P0 v4 G" ^/ U+ d. M) `9 V2 U% c% p# {Degression, 递减) ]/ `2 m* C4 E" B6 x
Density function, 密度函数! Z+ a% V R) R: H
Density of data points, 数据点的密度. ]; a" g0 p8 D% q% G) v
Dependent variable, 应变量/依变量/因变量6 J! A5 r9 O+ Z" \# \
Dependent variable, 因变量
+ \; e3 L" \6 I2 l% D+ f& ]Depth, 深度# ]( O. v! Z# C) H
Derivative matrix, 导数矩阵
$ N# Z; C' C, A7 h: @# ODerivative-free methods, 无导数方法% p) r5 O& } l4 I1 ^( {- z
Design, 设计
" @5 e; r( F) ]2 W, ODeterminacy, 确定性& k& ^& r% ^; N: F4 I8 H$ X2 _2 C
Determinant, 行列式
M. b/ L8 o# V: s1 o! q! K4 ? ]Determinant, 决定因素
2 o& k9 E' Z- X4 y3 DDeviation, 离差8 Q+ {9 t# }) f- h: a; Z; I4 S
Deviation from average, 离均差* K& x# [' E, a+ Z# P# `+ U
Diagnostic plot, 诊断图
$ N2 r1 U2 T8 q, {( }7 VDichotomous variable, 二分变量
- t9 N* W8 I5 W6 H+ Q6 J' BDifferential equation, 微分方程
7 b& D# F& o+ E. _Direct standardization, 直接标准化法! p6 L+ }! l2 g- {# K4 l1 _
Discrete variable, 离散型变量/ Y9 d1 n1 \. b/ k
DISCRIMINANT, 判断
1 y# c3 O2 z/ y3 j, }Discriminant analysis, 判别分析$ O" |8 F5 T/ w" C; M# z P
Discriminant coefficient, 判别系数2 q( U+ L: f4 n f
Discriminant function, 判别值
2 z. Y$ O- V# r+ l' o4 a( XDispersion, 散布/分散度
; \6 \9 w6 O* V3 d9 }8 d9 KDisproportional, 不成比例的; k( `8 h1 b; o: d S/ F) y8 Y
Disproportionate sub-class numbers, 不成比例次级组含量8 F* u z0 H2 a3 R. {6 {5 Y
Distribution free, 分布无关性/免分布: U! ~0 S2 z5 Z! ?
Distribution shape, 分布形状
, z: a( v: I! V; K4 n/ wDistribution-free method, 任意分布法
% Q6 N) J: r% z% F4 g' ADistributive laws, 分配律
# z; D& u5 z- S1 b: M" c% \Disturbance, 随机扰动项
7 t1 S; [+ D: v7 V l1 iDose response curve, 剂量反应曲线8 | h4 ~! F* ~5 D/ s. g7 J4 v
Double blind method, 双盲法7 K. O1 x8 E0 t9 s8 t
Double blind trial, 双盲试验9 `& Y8 c y% C0 L$ R7 X6 J) n
Double exponential distribution, 双指数分布
' ^2 g( c! K# ^' u- @Double logarithmic, 双对数
+ r3 B; t+ P0 Y. R$ rDownward rank, 降秩) m H) z) c7 E+ v( c: B! F$ a- |
Dual-space plot, 对偶空间图+ W5 B" q7 ?" q' P- H
DUD, 无导数方法; O9 J, {3 x8 N" [
Duncan's new multiple range method, 新复极差法/Duncan新法; O; v9 `- A$ I {, l. L1 s) u
Effect, 实验效应
/ a* @( w W3 ]. w. [" DEigenvalue, 特征值0 S, a+ p+ Q `3 M
Eigenvector, 特征向量
+ w7 }$ J1 ?4 p/ I0 o# e3 VEllipse, 椭圆* W1 [, |8 k7 O
Empirical distribution, 经验分布' W# K7 \3 W* P. {( }
Empirical probability, 经验概率单位. }. [! e/ Q3 r \) h* t" G
Enumeration data, 计数资料
! T6 |. G; h1 y! y/ V8 UEqual sun-class number, 相等次级组含量& o/ a+ P) t9 x8 i' l4 C6 N9 \) D
Equally likely, 等可能
6 m* m0 u& ?/ Q7 AEquivariance, 同变性5 I$ {, s' ?& z+ o
Error, 误差/错误
/ x2 c1 m2 z( J. q( uError of estimate, 估计误差# d9 K# R7 { z; t
Error type I, 第一类错误7 n# y/ H- k9 v: K, \+ g
Error type II, 第二类错误$ G N) B0 y% r7 \/ {
Estimand, 被估量- \( v3 z& {# v/ s7 {( ^5 g0 C
Estimated error mean squares, 估计误差均方1 ]' y) V" A- ?. d3 Y, C3 n/ {* ^
Estimated error sum of squares, 估计误差平方和8 R. L+ a2 \: |- R
Euclidean distance, 欧式距离
: n( @, d0 k4 \! N# l hEvent, 事件. K9 ^3 M, o8 P3 _' E& g
Event, 事件
0 j& F; ~6 u5 V1 \: GExceptional data point, 异常数据点) ^" u/ D: t! H4 a
Expectation plane, 期望平面
( B8 J* y" v! @* k0 C) Z# qExpectation surface, 期望曲面' r. M2 u+ b' }/ q3 o
Expected values, 期望值
3 \# e! d4 b# Q, ^! gExperiment, 实验8 @- a& R7 [) U$ X8 E3 [7 K
Experimental sampling, 试验抽样: y8 b( ?$ a5 _3 `; t
Experimental unit, 试验单位
% H, a# B/ B, @4 b- X# n& o- z: tExplanatory variable, 说明变量: q+ a* b8 a+ A% a0 u
Exploratory data analysis, 探索性数据分析
2 ~; B% _: t* u/ U+ R' j* fExplore Summarize, 探索-摘要
* v! g) ?+ o- [% JExponential curve, 指数曲线9 z/ h/ C1 N: {% B! z3 ~# A$ \/ h$ i
Exponential growth, 指数式增长
- H9 j/ J- ]& `5 mEXSMOOTH, 指数平滑方法
' G( Z g! g' Z" J( A9 P3 V BExtended fit, 扩充拟合
( y' M" C3 K* _$ t; d8 }Extra parameter, 附加参数3 y2 T6 m" M1 T; o5 p
Extrapolation, 外推法
# I( A# S: f8 n8 w6 w8 PExtreme observation, 末端观测值
5 @' X( ]# z2 `- h3 qExtremes, 极端值/极值6 y8 J: ?# ~8 Q) X
F distribution, F分布
% ?2 z I9 O! Q( YF test, F检验' x6 I, z! d6 ]$ }0 q
Factor, 因素/因子$ Y- o& s& [) F' G7 v% I, I: `
Factor analysis, 因子分析
" Q$ `% A" a( ?9 H5 N+ ~' LFactor Analysis, 因子分析
; E: h4 n6 F2 n7 v2 O+ oFactor score, 因子得分 8 \ {5 W$ M" l7 a) n
Factorial, 阶乘5 r1 d# t3 a9 x- M$ b7 ?3 g: O, T
Factorial design, 析因试验设计
1 t5 l& o9 T, l4 p' F3 LFalse negative, 假阴性0 r$ {: S, ~. C f+ I0 e4 Y
False negative error, 假阴性错误; h1 c$ s7 O8 \. a7 B( r7 [
Family of distributions, 分布族
* s/ z; e" g6 lFamily of estimators, 估计量族
1 \& J- Z7 b+ j) k# A7 Y' j) L* v3 ^' tFanning, 扇面2 X) _9 d2 I6 B& n! {
Fatality rate, 病死率5 C+ a. {' ^ R
Field investigation, 现场调查
; H! b W. d+ {: GField survey, 现场调查
& U4 F+ J- d7 v4 H* \$ L# a6 v: `Finite population, 有限总体! Z; `, v8 Q0 u
Finite-sample, 有限样本: o- F% d& a* C) v \/ R
First derivative, 一阶导数2 L, }% v. g4 S, h, j' `2 m
First principal component, 第一主成分
: u1 m+ q! L- \+ G& g9 l2 P HFirst quartile, 第一四分位数
. s ^0 s' P; S p% v- O& G& PFisher information, 费雪信息量
- _, I# g% T: E# G/ NFitted value, 拟合值# L" O; H) ~0 B$ o
Fitting a curve, 曲线拟合) h' d! k' _$ {& S
Fixed base, 定基
4 K" J" \- b4 h; HFluctuation, 随机起伏
, k9 H; F$ |6 Y7 T' UForecast, 预测
+ B& Z; s; Q- V" l& H- vFour fold table, 四格表
& F6 ]; J0 Q& Z" L3 X+ I0 rFourth, 四分点
' ^6 n5 ^- S8 g2 L) Y _) S0 Z5 m CFraction blow, 左侧比率
3 n9 q, @7 ^( ] O; n. k0 _6 O2 d! mFractional error, 相对误差 ^8 m+ [9 W; O: U7 e' Q7 ?+ V9 k
Frequency, 频率
# R! I' S# W' E& wFrequency polygon, 频数多边图, [9 n& V0 t- |( p x. P3 v
Frontier point, 界限点
/ V4 _5 E. `* ]4 Z2 TFunction relationship, 泛函关系
4 H" W- p) N. S) d& k4 jGamma distribution, 伽玛分布
+ t5 m* V+ \4 Y) y1 A% \Gauss increment, 高斯增量: J% W) O. Q# G: q# d
Gaussian distribution, 高斯分布/正态分布' z1 V$ p% T! v9 @- \
Gauss-Newton increment, 高斯-牛顿增量
8 r! ^% p7 i7 B/ D8 PGeneral census, 全面普查
% G! Y3 J: E D' g0 o6 m9 qGENLOG (Generalized liner models), 广义线性模型
' k. e; T( j( \/ ?! q J. c9 FGeometric mean, 几何平均数# _/ o5 _" ~; [1 E0 `/ ~: v
Gini's mean difference, 基尼均差/ g9 h6 A8 X- `+ t, k" W0 y* ?3 A
GLM (General liner models), 一般线性模型 u+ y9 _7 P( x4 W; n6 P. p" W
Goodness of fit, 拟和优度/配合度
5 }1 [$ N" P/ ^/ ^; [8 c2 ]1 UGradient of determinant, 行列式的梯度
8 f3 P% i' U5 v7 \& u+ K; ^Graeco-Latin square, 希腊拉丁方
9 o* \. Y! w0 U8 W0 Z- \' nGrand mean, 总均值7 e6 |" x4 q4 i; K
Gross errors, 重大错误/ I8 p; z% v1 M0 Y& Q2 C3 f
Gross-error sensitivity, 大错敏感度9 |' w- T. B, C* o s
Group averages, 分组平均
; E1 u$ j9 P0 e7 V A0 H; Q7 v2 MGrouped data, 分组资料; D. ~$ }6 ]6 G4 S4 X2 b. Z
Guessed mean, 假定平均数
% |- H s0 m$ THalf-life, 半衰期$ j1 ^' Y8 a9 ~& g$ x6 E& j
Hampel M-estimators, 汉佩尔M估计量
4 G4 m H& |4 @5 QHappenstance, 偶然事件4 I6 j/ J, _, W3 P% o
Harmonic mean, 调和均数
& p' @) P2 H b& L# d3 GHazard function, 风险均数
# L& l, n: O0 E7 A$ P3 qHazard rate, 风险率, L; F z# f6 V$ j6 \; l
Heading, 标目 ' y% j) J$ p0 o& [4 x! f) [: {
Heavy-tailed distribution, 重尾分布
- {. U* ?, [& I% [3 ?! Y! BHessian array, 海森立体阵3 y! K U9 y2 z+ g8 y9 |9 ]2 u
Heterogeneity, 不同质0 }5 R/ H3 j# D* S/ D. u
Heterogeneity of variance, 方差不齐
9 l4 \: \& m! t, X4 @, FHierarchical classification, 组内分组. S, T9 N5 T3 R! s+ W6 A4 f8 A
Hierarchical clustering method, 系统聚类法
& m H( K/ v% Y/ {0 v# EHigh-leverage point, 高杠杆率点! m9 r6 p t4 j E. n# ~
HILOGLINEAR, 多维列联表的层次对数线性模型% B; t# g+ l# U7 B4 }4 q, G- B8 s# [
Hinge, 折叶点
6 m: O( T) l' w7 xHistogram, 直方图
* s. k/ e5 ~) J$ p1 k' {Historical cohort study, 历史性队列研究 ! a9 f& u% K d: f3 N
Holes, 空洞
6 {7 P( T1 U3 v% L/ n6 D4 |+ c1 gHOMALS, 多重响应分析- [0 t t5 E9 |* I( W
Homogeneity of variance, 方差齐性1 K6 O9 j2 S/ w& ~+ V1 q/ I
Homogeneity test, 齐性检验* }% p& d& |$ h! x& L0 v1 ? G
Huber M-estimators, 休伯M估计量
& E; e$ J7 n3 N4 U! CHyperbola, 双曲线( a: V$ R v) v& k
Hypothesis testing, 假设检验
( O0 R" G5 n b8 j0 CHypothetical universe, 假设总体
, Z: r9 y& w/ J+ |4 IImpossible event, 不可能事件8 q4 b+ Q8 ]7 Z6 [" ?$ R( a: T
Independence, 独立性
* v" G0 r5 }0 C& `Independent variable, 自变量
" s/ Y% v& |, s7 n8 t ~6 I: b9 e OIndex, 指标/指数' C8 K9 t% l) _3 H
Indirect standardization, 间接标准化法' j- q, W0 P& [0 L$ ?
Individual, 个体
7 l( } k+ u9 {( f) z8 FInference band, 推断带2 g3 x: p5 D; ?6 Q, A% x. g
Infinite population, 无限总体$ ^1 V# W/ ^/ D7 T# r& M
Infinitely great, 无穷大1 t$ W+ B+ R6 j% J) n' l' w1 V
Infinitely small, 无穷小
) I9 m0 l" i/ Q( SInfluence curve, 影响曲线8 G4 ~: L M1 X/ k
Information capacity, 信息容量2 t0 a: l7 }. ]) D) G3 U) T' ~2 W
Initial condition, 初始条件
" p9 F7 `; y3 g! Z/ N. ^7 C3 a9 O; WInitial estimate, 初始估计值, R9 } y; E8 h6 d$ ^* X
Initial level, 最初水平/ W& E- I% P H+ x2 _; m
Interaction, 交互作用
2 h" T( Q) u& Z% v6 F2 d- Q& UInteraction terms, 交互作用项
+ E! m3 u- _; z( OIntercept, 截距
1 s0 p" H9 b5 uInterpolation, 内插法
3 z# c) l; Q3 Y6 EInterquartile range, 四分位距5 H, U X3 F, ]# u4 M6 ^$ s
Interval estimation, 区间估计
* |. f" T2 s8 `0 xIntervals of equal probability, 等概率区间& G4 m' f5 @0 h1 ~+ J
Intrinsic curvature, 固有曲率
$ ~% c. K: m; `) SInvariance, 不变性+ O1 W) |; L# E
Inverse matrix, 逆矩阵
+ Y% x; X9 e! K. V/ O3 `4 j% @Inverse probability, 逆概率
6 k( e+ ^; e" x; @1 U( {Inverse sine transformation, 反正弦变换
3 c8 t, w; V7 [& v yIteration, 迭代
" }. |' x+ D- L7 h1 r' zJacobian determinant, 雅可比行列式' n3 V% h* @" N$ X, n: W
Joint distribution function, 分布函数
0 q7 j9 i5 t! }! t5 Y& gJoint probability, 联合概率
) J& u# n* o Y; L/ I. k* fJoint probability distribution, 联合概率分布
# N9 d O: ]! M. t0 DK means method, 逐步聚类法. k1 j( L& t" W1 E% j* q
Kaplan-Meier, 评估事件的时间长度
9 i/ @, v) d$ z7 G, e7 LKaplan-Merier chart, Kaplan-Merier图8 D, L: J* Z# J# t, ?0 F# F! E
Kendall's rank correlation, Kendall等级相关
' H/ O/ M! p) ^- Q; YKinetic, 动力学) ? Z1 J7 z' X
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
2 w- w, M! ^9 ^$ JKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
9 c8 x* x$ N: V' y! SKurtosis, 峰度
! A% V* ~5 S# D% M' c) x9 O$ lLack of fit, 失拟0 S5 n* u' ~, q
Ladder of powers, 幂阶梯
, E) e/ _$ F/ h8 JLag, 滞后! x; B. t! @; X4 o* _* B! f" [
Large sample, 大样本4 n4 A3 m4 M8 }; Z. P
Large sample test, 大样本检验% R6 q6 y0 C R2 v& }, U; @ q: \. k
Latin square, 拉丁方& Q) j' s& s/ N; D; j! S
Latin square design, 拉丁方设计. A [% S# ]2 m" l/ B: z5 N
Leakage, 泄漏6 o( h7 a* a2 D( G( O
Least favorable configuration, 最不利构形
' o. U" g. b; C8 BLeast favorable distribution, 最不利分布
5 d+ O! F( y/ H% r( h& {Least significant difference, 最小显著差法0 H2 p4 W: @7 @8 l+ E/ g& A3 ?- `
Least square method, 最小二乘法! x( f$ T9 q! R" t+ w) d0 Y" b( k
Least-absolute-residuals estimates, 最小绝对残差估计
& ?# {5 X: n7 u* n& rLeast-absolute-residuals fit, 最小绝对残差拟合
0 }6 z Z( y2 hLeast-absolute-residuals line, 最小绝对残差线
+ K/ T8 w. }# ILegend, 图例; b8 J. |& j$ \5 i+ c. u/ g& [) L/ Q
L-estimator, L估计量. Q6 W# ?6 {+ `6 X
L-estimator of location, 位置L估计量& ~3 z* u" ^3 z; m
L-estimator of scale, 尺度L估计量6 u" R/ e& j5 J$ n
Level, 水平. F5 S7 [& e5 k# e2 w" U
Life expectance, 预期期望寿命
8 S, f( J. U$ B3 \# z h+ a- ~Life table, 寿命表
7 M) t4 I: Y) o& |+ h/ t9 U+ a! OLife table method, 生命表法" ~6 s7 Q) y" {9 X) E7 L
Light-tailed distribution, 轻尾分布$ d+ }1 U# M7 }1 t
Likelihood function, 似然函数# E" H, D2 M( O& W* |
Likelihood ratio, 似然比
5 d6 j1 u0 \* u1 ^6 U* dline graph, 线图
3 K! Y: E' \9 v1 Z' ILinear correlation, 直线相关 H- g6 ?! v6 ?( l
Linear equation, 线性方程; K4 j. J. V: a0 P
Linear programming, 线性规划! @( S4 l* R( L) o* K
Linear regression, 直线回归4 _7 ]+ ^4 f3 P
Linear Regression, 线性回归) i) @' K K5 f5 z( E% |
Linear trend, 线性趋势8 _% u2 l+ w9 g: Y9 I
Loading, 载荷
6 X- p+ `# u9 QLocation and scale equivariance, 位置尺度同变性0 q, v7 q5 b' [4 v. B4 W- \
Location equivariance, 位置同变性
$ C' R+ p1 v- L# n, t# Q- xLocation invariance, 位置不变性3 g: B# H, B0 c" f$ ?; e) C$ X4 n
Location scale family, 位置尺度族
: c5 @/ `# K9 r8 f9 g9 GLog rank test, 时序检验 " h4 n0 H4 E0 j
Logarithmic curve, 对数曲线
) A1 s+ X( k# lLogarithmic normal distribution, 对数正态分布
- [; F8 O7 L# F/ O9 xLogarithmic scale, 对数尺度2 i. W0 `2 o: q* G
Logarithmic transformation, 对数变换
/ a! p2 B$ P+ h1 v8 H, l. YLogic check, 逻辑检查
* a( G! ?' g) \3 F7 P- E# kLogistic distribution, 逻辑斯特分布0 ^% J, t/ `- [- c
Logit transformation, Logit转换
8 V, h: b% w1 A. |LOGLINEAR, 多维列联表通用模型 9 ^/ {" ~" N$ e- d
Lognormal distribution, 对数正态分布, J( O8 ?6 F& H/ i$ s
Lost function, 损失函数; z# ^8 u1 r5 J3 U6 I9 k
Low correlation, 低度相关7 |' k/ Q4 Z$ M- M- n& a# D
Lower limit, 下限+ n! b0 m8 ?2 M# a3 w2 y* P' M
Lowest-attained variance, 最小可达方差* | _4 V$ j* b# m5 E
LSD, 最小显著差法的简称& d+ c3 S4 F5 {7 e# s# J
Lurking variable, 潜在变量2 A4 U; ^, K; L( l
Main effect, 主效应
5 g; O, Z9 X2 V+ I, f- TMajor heading, 主辞标目/ I) L6 g% s5 b L5 c* ^6 ` u
Marginal density function, 边缘密度函数
' B% i7 _9 F/ B2 u1 WMarginal probability, 边缘概率/ p* h: m8 s' `0 Z# y% v
Marginal probability distribution, 边缘概率分布
. U# x6 G5 @. S: i5 p! h& GMatched data, 配对资料3 R! H2 m5 G0 Z- \1 Z& O. t6 f
Matched distribution, 匹配过分布# t& R" l; `& W% b3 t- n" d- X: {
Matching of distribution, 分布的匹配
9 b! F4 [* `# `) gMatching of transformation, 变换的匹配
* N# H2 }% i* X: f# f& |6 EMathematical expectation, 数学期望" u; m! u! D: \5 ?0 E
Mathematical model, 数学模型/ y7 u% L" Q- H2 U7 F4 \/ m
Maximum L-estimator, 极大极小L 估计量1 {# L4 b2 M/ F9 R3 R0 K
Maximum likelihood method, 最大似然法1 F( r' x' {. B3 z
Mean, 均数
4 d8 `6 G* @8 O6 q" t) T nMean squares between groups, 组间均方6 i$ {. \- F* G' }( Q" P$ P2 L% c
Mean squares within group, 组内均方6 c6 g$ L3 E4 P w* @9 ?
Means (Compare means), 均值-均值比较: q, z1 t0 P, R, x& I- M% g
Median, 中位数9 s; O: }' ]1 Q0 v8 @
Median effective dose, 半数效量
& L' t' s: o7 J& b! B" C: ZMedian lethal dose, 半数致死量
! F6 V. V7 t0 k) PMedian polish, 中位数平滑5 ~# A" O" q' I; s7 S- R. S( k1 g
Median test, 中位数检验
3 L7 H A" l8 z& T0 B4 hMinimal sufficient statistic, 最小充分统计量
) [) m, E- g7 T) N0 iMinimum distance estimation, 最小距离估计: Y3 s4 r" q0 B* z
Minimum effective dose, 最小有效量
, ~3 ?+ f/ Z; m* `# |Minimum lethal dose, 最小致死量
) W) e' ?, v1 j1 W6 AMinimum variance estimator, 最小方差估计量4 g* A; J* _' o2 y( a; G% n
MINITAB, 统计软件包
* u$ d- x" H- Z$ `Minor heading, 宾词标目 i. r5 p5 H u* Q/ n- z
Missing data, 缺失值
3 U& C9 \9 U S5 h% DModel specification, 模型的确定
! N/ ~9 j4 ^4 wModeling Statistics , 模型统计
. @/ b: i3 w2 q4 oModels for outliers, 离群值模型
) S! a3 d4 S: I t0 ^! yModifying the model, 模型的修正" @* e0 B5 o: \9 Q# J/ a3 E/ j
Modulus of continuity, 连续性模; W* X# y p- B) w0 v. U8 |" r3 f
Morbidity, 发病率 . q) i) b w$ w" \* @/ }( W
Most favorable configuration, 最有利构形
% c" B4 C, k! O) iMultidimensional Scaling (ASCAL), 多维尺度/多维标度
/ J5 z$ R" X i- a6 |1 y2 JMultinomial Logistic Regression , 多项逻辑斯蒂回归3 \5 `2 z' R, B" \
Multiple comparison, 多重比较; m' i: a, j/ u2 S: [/ }/ k- x# P
Multiple correlation , 复相关
H* s. a8 {: N4 ?& ]/ E! g% LMultiple covariance, 多元协方差
# N7 E9 C4 Q) \8 {' YMultiple linear regression, 多元线性回归$ b8 w+ B* Q) `) Q1 O) ^
Multiple response , 多重选项
6 x6 G1 E1 C7 y! c2 p$ \0 `2 y# ]Multiple solutions, 多解! H7 b7 \; x% ?1 @" N
Multiplication theorem, 乘法定理
3 K) n1 T+ d( K( a3 f! B* F4 eMultiresponse, 多元响应. h6 D/ x! e( B3 ]' \8 ?
Multi-stage sampling, 多阶段抽样
+ L6 ~& @3 J9 A3 W; a: u4 }8 TMultivariate T distribution, 多元T分布6 i i. _- z; [ s$ \3 \$ C
Mutual exclusive, 互不相容 E- m# @9 ~6 z5 W6 `9 i
Mutual independence, 互相独立
/ P% N, e1 i: BNatural boundary, 自然边界, m/ e3 S& v/ O
Natural dead, 自然死亡- i7 ?/ p; \8 O# ?- e ` t6 O' u6 q# U
Natural zero, 自然零
: w. M: ^, L+ A. bNegative correlation, 负相关
' E. q8 b7 r, V' tNegative linear correlation, 负线性相关% ^6 b' I% S* O3 ?% N4 s
Negatively skewed, 负偏
0 D- s6 @' l3 ONewman-Keuls method, q检验
5 {/ v7 q. _2 o/ ^/ yNK method, q检验
% H- f7 n* D( V* h9 b% CNo statistical significance, 无统计意义
/ h) n+ c+ d2 G3 i, L; MNominal variable, 名义变量! U. f7 ^ V; S: D ^
Nonconstancy of variability, 变异的非定常性
' U- u- {; J* d4 G9 ~' Z# zNonlinear regression, 非线性相关1 H: F& `! L* `; i" Q0 R: O' k H
Nonparametric statistics, 非参数统计
; z) V, G# e: c6 y. q3 r3 R4 W8 SNonparametric test, 非参数检验: r c3 u( z" d! X- N& h
Nonparametric tests, 非参数检验. P6 h' t7 v# \% K9 t4 p
Normal deviate, 正态离差) u3 k; Y# u: l7 z; ?" ^; O
Normal distribution, 正态分布" G0 ?! b$ {% g) h- W# }" k4 T
Normal equation, 正规方程组# B* W* v m( ^+ R5 g, k6 E% ~! D
Normal ranges, 正常范围 g9 j0 O) O/ Z$ O$ D, D
Normal value, 正常值: V v1 j- q7 o3 x8 g; q
Nuisance parameter, 多余参数/讨厌参数
2 f: T. y6 }: O0 S# D' mNull hypothesis, 无效假设 " ?9 m- Q5 I7 |3 c4 J
Numerical variable, 数值变量! C1 R; M! ?# u0 g# X
Objective function, 目标函数5 D' ?: A$ p* n& m; r8 S% g1 A( {
Observation unit, 观察单位# ^; G* v8 T. P
Observed value, 观察值7 D8 I& X: x- O5 [
One sided test, 单侧检验, S( e' I" _# E! O9 A
One-way analysis of variance, 单因素方差分析
$ b6 c( Z' c' C( X/ f; gOneway ANOVA , 单因素方差分析% m2 M' E8 ?5 u) n
Open sequential trial, 开放型序贯设计
- d" |9 K7 A q- K/ c7 HOptrim, 优切尾- _' B3 g: e4 d) t& u
Optrim efficiency, 优切尾效率7 |4 O9 R. R6 y/ d
Order statistics, 顺序统计量( U7 @) O0 K1 [& E/ K9 m6 ~" R
Ordered categories, 有序分类. u# ^" U' f; Q0 C6 G4 I) [
Ordinal logistic regression , 序数逻辑斯蒂回归; G6 C% c/ p4 X0 h! j% C) s0 p8 A
Ordinal variable, 有序变量: M! X1 K- t2 B; ?( X2 l" t: D
Orthogonal basis, 正交基 \. b0 W9 P$ n4 C
Orthogonal design, 正交试验设计
- a% g5 \+ X* ?Orthogonality conditions, 正交条件$ b& ?8 {+ }5 J& ~2 U1 S8 X
ORTHOPLAN, 正交设计 " {) p* f/ T3 s+ l% \3 C
Outlier cutoffs, 离群值截断点
, b" B; ?* l( W' c: D3 N OOutliers, 极端值
3 f6 R1 H5 y z9 ]OVERALS , 多组变量的非线性正规相关 7 n* h* t: x6 t+ }* N' _
Overshoot, 迭代过度
) I% |3 T- T' E2 ]/ KPaired design, 配对设计, R0 {* ?# @1 F& w" n
Paired sample, 配对样本
; a+ d3 a" l# G1 ?7 kPairwise slopes, 成对斜率
$ s) P6 V7 @4 q1 a( x6 jParabola, 抛物线8 u/ Z7 h# @; b( t6 h" l p7 S& ?
Parallel tests, 平行试验
# C6 w: ]$ s/ G* t0 HParameter, 参数1 F b- m" E. B! S9 c) c6 [ S7 Y
Parametric statistics, 参数统计
/ H; g8 {5 V' D x4 A- fParametric test, 参数检验
4 H/ e2 K/ q) A1 iPartial correlation, 偏相关
; ]6 U" S# b! S6 {% qPartial regression, 偏回归
& J$ O& @0 U5 I7 g( {6 Y+ z' ZPartial sorting, 偏排序% k& Z) K7 l5 F1 `; g
Partials residuals, 偏残差
& X b5 i" E, u" c) ~ ]4 b( m* nPattern, 模式
9 P' }" _, _) ?9 M3 ~6 V# bPearson curves, 皮尔逊曲线7 o- g8 ~: Q( {; N* v% \
Peeling, 退层$ {9 Z/ a3 l$ y4 _+ \$ j+ J1 ]+ c6 V; x
Percent bar graph, 百分条形图
; @) I% L8 u. EPercentage, 百分比
) C/ X/ l" n7 D- w% \8 BPercentile, 百分位数
) r/ j7 k5 |3 k% o; G. `3 ZPercentile curves, 百分位曲线" P* Z: K: ^; E
Periodicity, 周期性* I" b, |% C6 ^. E9 O
Permutation, 排列
9 R- G3 P1 \3 x! h! H7 E( k# s% ] mP-estimator, P估计量
% K4 \, R7 u; J& _( LPie graph, 饼图
& n0 D( \& j+ DPitman estimator, 皮特曼估计量
# M+ c# ?7 z; e4 R8 X+ KPivot, 枢轴量
4 a% D8 k- \! G& }6 tPlanar, 平坦
6 |7 r6 d+ }+ k+ v- P8 z" WPlanar assumption, 平面的假设0 x# p. x6 y" H. Q8 C0 b( P; l
PLANCARDS, 生成试验的计划卡- S& s1 u9 @% {# B
Point estimation, 点估计
4 J2 E# b: }; s6 L8 y6 XPoisson distribution, 泊松分布
# F- s! Q" W8 l- W/ {2 c& D: nPolishing, 平滑 c$ N' K |7 F- k3 B, Y
Polled standard deviation, 合并标准差7 k, u/ y- f) O! S+ K; A, b
Polled variance, 合并方差4 M- x# d, G$ `9 a: Q2 p5 d
Polygon, 多边图- V8 G' e8 X( S; ]& N, j
Polynomial, 多项式8 x% B! I) P4 c8 n) U
Polynomial curve, 多项式曲线
& q. I: B/ g$ X/ C/ vPopulation, 总体0 C! [6 }1 m7 A f
Population attributable risk, 人群归因危险度4 G1 V7 b( l' N- c
Positive correlation, 正相关" E4 o0 f" S* {# W
Positively skewed, 正偏
% l) Q% A* w5 v% yPosterior distribution, 后验分布
' V& f( ]6 k$ X5 ^7 _! s7 y3 uPower of a test, 检验效能
4 ^! u V7 u& |4 L1 g4 kPrecision, 精密度
?* T/ }7 x7 h+ FPredicted value, 预测值7 L- u8 e+ E3 k
Preliminary analysis, 预备性分析
! `# i# J! H2 n! e& |Principal component analysis, 主成分分析! ]" e- C) L, P' c; Z5 m5 ?" Q
Prior distribution, 先验分布
8 z/ ]. @1 l1 @& O8 T) P; JPrior probability, 先验概率- u# M: _" L% W; Y" V0 g
Probabilistic model, 概率模型
: `/ O# n' c9 |& fprobability, 概率& h. M! b6 z6 |9 n7 \- b
Probability density, 概率密度
" n8 f% n* ~% u8 X0 XProduct moment, 乘积矩/协方差
2 j, ^+ h& L: j; b* {7 a4 N* e0 dProfile trace, 截面迹图3 M* D" ^7 \' b! H2 V" A; e6 O
Proportion, 比/构成比2 z& q$ I' Z: c! X+ b0 \6 E
Proportion allocation in stratified random sampling, 按比例分层随机抽样
( d0 b2 z& ]0 M- a- rProportionate, 成比例
8 l2 J6 y5 W1 m" OProportionate sub-class numbers, 成比例次级组含量5 B/ L' b! Y" Q- K; a; C
Prospective study, 前瞻性调查% K: q# ]( `, } n
Proximities, 亲近性 " w8 V+ A6 i+ g# K5 _
Pseudo F test, 近似F检验, s6 h+ M! _4 _! [" \1 a/ k8 [- p
Pseudo model, 近似模型
# i2 J) Z ` E7 fPseudosigma, 伪标准差
# E& K5 ^ x. s, R5 fPurposive sampling, 有目的抽样
' m0 v( k6 R- ]8 K; YQR decomposition, QR分解
8 w+ q$ \! T. r2 F8 {7 M! Q) ?Quadratic approximation, 二次近似- Y7 H' Z; S/ K+ R0 s2 A! v; g
Qualitative classification, 属性分类; _; m% Q2 q0 L5 I) f) b
Qualitative method, 定性方法
$ c/ Q* a* i7 P6 V6 lQuantile-quantile plot, 分位数-分位数图/Q-Q图
7 z7 l& m3 s& l! g& O& Z% P' qQuantitative analysis, 定量分析
$ Q2 A! r) s) O4 J( hQuartile, 四分位数; d# d! [) s0 O. W+ U; P- F& i
Quick Cluster, 快速聚类
2 w6 g$ J/ I" G5 eRadix sort, 基数排序- _7 T; b, g Q& v/ Q* D
Random allocation, 随机化分组
' {4 y' j2 `( G9 [- c: PRandom blocks design, 随机区组设计7 o4 L9 y% _4 K, _8 M% I$ \% K
Random event, 随机事件
! K/ h7 H% M! Z% q. YRandomization, 随机化" U' p! d5 \0 B
Range, 极差/全距0 K; E! ~! ^7 ]% H6 O
Rank correlation, 等级相关/ T0 V2 r2 ^' P# w6 e! O, |7 u& F* ~
Rank sum test, 秩和检验
% k0 Y1 @( C/ o! K. HRank test, 秩检验3 G& W1 f! @: X: i8 w8 n& K
Ranked data, 等级资料8 y+ c8 |- D9 E% S# Q1 @; }5 Q
Rate, 比率
/ v' a8 t5 _. f) uRatio, 比例
# K5 s r* w* b8 i' ~1 o5 j4 sRaw data, 原始资料% Y @9 H. J0 i2 p. z% Q
Raw residual, 原始残差
: j. }* `6 s& F7 M' R5 J! @- pRayleigh's test, 雷氏检验8 i3 r/ F! W) ]
Rayleigh's Z, 雷氏Z值
4 ], w4 f; d7 m* C4 y5 z& hReciprocal, 倒数: e" Q$ l* @' \+ d3 H
Reciprocal transformation, 倒数变换
4 e7 M) f$ n6 S8 p- B1 BRecording, 记录3 d j5 y0 G8 |3 Y; g
Redescending estimators, 回降估计量2 [. u, R% q5 \! i5 p
Reducing dimensions, 降维
2 N' z% z" Z* _Re-expression, 重新表达6 G$ d. a# d% y- T; d8 q" T2 E
Reference set, 标准组2 a* k8 Z2 K+ Q7 M" H
Region of acceptance, 接受域
: S% S$ c C* ?) c" f' ARegression coefficient, 回归系数
( s( }" y9 }' m+ ^0 [ hRegression sum of square, 回归平方和( s# V% y- K+ u
Rejection point, 拒绝点* X G! D& O' N% U
Relative dispersion, 相对离散度: j! z V# ~" h( @: N- n- s; K
Relative number, 相对数
/ q+ n6 y/ U# v" `: U6 g( e3 PReliability, 可靠性/ w2 ?5 Z c# \- O
Reparametrization, 重新设置参数# C+ ?# S1 o) ]5 Z/ O9 I' C
Replication, 重复6 ]# |; X& I% ^1 z7 m
Report Summaries, 报告摘要1 ~+ l" V C' `- S6 C+ x
Residual sum of square, 剩余平方和- k ^8 |! W6 }
Resistance, 耐抗性
7 o4 f+ k; [7 M6 q8 a8 hResistant line, 耐抗线2 [2 d) }7 n' h
Resistant technique, 耐抗技术
4 _+ E9 I9 r TR-estimator of location, 位置R估计量7 B/ W9 l* L) w5 n) V
R-estimator of scale, 尺度R估计量
3 m, m8 Y$ N, H$ {" T% vRetrospective study, 回顾性调查
2 J h; `: a* l, l4 fRidge trace, 岭迹
8 G/ G/ {: V' J1 M2 e1 u! FRidit analysis, Ridit分析
) i% A6 Y* g8 a) D g2 d# KRotation, 旋转) I- ^8 q% C$ g+ `6 P: l
Rounding, 舍入
% W& Q: N" ?! \Row, 行
2 K5 K9 d- X; r% r j) o% N/ [Row effects, 行效应
1 T ]% O& w" H* tRow factor, 行因素
1 ^ C' b/ @3 Y' U+ t% |7 z' z$ jRXC table, RXC表# V/ i' v/ ~5 x1 w R4 K' O
Sample, 样本
0 ~: A) H) p: ~- b5 W) SSample regression coefficient, 样本回归系数# B2 a9 L# I3 D, n
Sample size, 样本量
! F2 W( C- ~& g: }5 a8 W$ E$ n* ASample standard deviation, 样本标准差! ~/ e- b& }- k
Sampling error, 抽样误差0 C$ Z$ M" w" C: L$ O" l
SAS(Statistical analysis system ), SAS统计软件包
3 W* E+ o$ j# G2 f/ I( J# GScale, 尺度/量表
" h8 v1 j! P" `& u& p; z3 E' l5 dScatter diagram, 散点图
" p' d8 \4 o; m/ XSchematic plot, 示意图/简图2 G) a/ W3 d* z8 X& B. h( ^
Score test, 计分检验& x7 ]2 k' r3 R+ S) M
Screening, 筛检! j2 |2 [7 r' E; i- [8 V2 m
SEASON, 季节分析
* g) p( f# x* \Second derivative, 二阶导数# w% h$ r8 T- q& P. z* j
Second principal component, 第二主成分) D! ?5 k; b* B6 o! W9 \" ^. j
SEM (Structural equation modeling), 结构化方程模型 , ?, y$ D/ V" v$ Y8 X
Semi-logarithmic graph, 半对数图
2 Y3 M5 h9 y6 N1 o, [$ C3 A9 A& Z# WSemi-logarithmic paper, 半对数格纸
0 Y$ T+ u% i+ {6 |) c' NSensitivity curve, 敏感度曲线
3 c9 Q A2 w% lSequential analysis, 贯序分析1 y" w/ c5 m" A3 f9 {
Sequential data set, 顺序数据集
! T* q' \4 u2 V9 K$ s6 q; l0 [Sequential design, 贯序设计3 B7 ~3 A/ I. X& ?/ `6 N L
Sequential method, 贯序法; y) ?/ t/ {+ R: s
Sequential test, 贯序检验法% g7 Y, D! J+ J" {" J: s* k
Serial tests, 系列试验7 E0 r- Z0 K" ?" T6 i
Short-cut method, 简捷法
9 V! G! d$ O( n3 j2 C kSigmoid curve, S形曲线
# r' W) B$ r# r' w; P7 o) DSign function, 正负号函数
7 k$ L, ~4 z- Q. |- qSign test, 符号检验
& c" U% R* m1 w2 u: R- X% sSigned rank, 符号秩
) o/ V$ K: Q- |# b$ r4 w# ~1 eSignificance test, 显著性检验9 _- B) j# v0 S2 M6 P y1 I
Significant figure, 有效数字* P% C- \* c9 |# W5 c
Simple cluster sampling, 简单整群抽样
C( e) W, c6 fSimple correlation, 简单相关! ~/ H3 b; o& ]; A$ t! N7 Z
Simple random sampling, 简单随机抽样
A, j v. D. h8 _$ {8 j# t eSimple regression, 简单回归
" ~. B; y0 ?0 f( C' A# U* N# Z# jsimple table, 简单表
k, p% f/ _7 {/ zSine estimator, 正弦估计量6 j% ?+ k) T6 U
Single-valued estimate, 单值估计
) V9 [% p& { K3 }; {, Z* L( @Singular matrix, 奇异矩阵
; m* f8 Z4 j0 M1 j% kSkewed distribution, 偏斜分布. G# v4 w# l' z# B4 k; ?2 Z2 G
Skewness, 偏度
2 r5 A0 L5 d' a$ PSlash distribution, 斜线分布7 S5 O- g% b2 c, S$ G3 n
Slope, 斜率# s: r" y3 t: o: ]# l6 Z: i
Smirnov test, 斯米尔诺夫检验
( w( D* e1 Z5 N! K1 [4 iSource of variation, 变异来源
% w0 T2 i- s# @8 RSpearman rank correlation, 斯皮尔曼等级相关
) x1 U2 R9 L7 a- Q! v' ]$ J7 `Specific factor, 特殊因子
/ a3 v! u; R8 [ s$ qSpecific factor variance, 特殊因子方差" \) W' X4 }7 H. q. r0 i% @, A$ R4 L
Spectra , 频谱
2 K( m* n0 m9 l* a$ _Spherical distribution, 球型正态分布& F6 i, A7 u& T5 ^+ r
Spread, 展布
p4 T0 d' _4 x. x6 f4 JSPSS(Statistical package for the social science), SPSS统计软件包
+ w( c7 X$ w+ ^+ rSpurious correlation, 假性相关
+ Z* \* T! S8 x6 ^1 U( VSquare root transformation, 平方根变换
# B; m. Z* _6 W4 V8 [4 \% rStabilizing variance, 稳定方差
+ ?# U0 d) d t- q6 o' zStandard deviation, 标准差- B; ]2 Q5 V+ _& d {. N
Standard error, 标准误; W2 G" z. V: }" Q; v V
Standard error of difference, 差别的标准误
) x: z# N& s0 X- x! ~Standard error of estimate, 标准估计误差
7 R# H: z1 l! C0 D. K1 \4 W5 ?Standard error of rate, 率的标准误6 G/ { N! g R+ F
Standard normal distribution, 标准正态分布8 m7 D$ p+ i% K' g2 K' y' @9 j3 x
Standardization, 标准化& P# A/ |% C! \; |$ h/ T
Starting value, 起始值6 m/ x- n0 ]1 j4 m% Y3 @ ?8 ]3 H
Statistic, 统计量
+ o# P" U0 z. I! L$ HStatistical control, 统计控制
2 e0 a# Z/ P: w5 S- [Statistical graph, 统计图3 D3 E* `, U% U5 X+ t% r9 i
Statistical inference, 统计推断! v. Y* Q5 @4 w7 W7 V
Statistical table, 统计表1 U& Q" v+ Z2 o. ?& L
Steepest descent, 最速下降法
& `2 {! F6 R- n4 w4 ZStem and leaf display, 茎叶图
m# g8 @4 C3 O0 u, E7 \Step factor, 步长因子
$ Y4 ?9 f; X! N( v% ~3 QStepwise regression, 逐步回归/ m: c- w+ D% ?9 ?* b4 L' i& H3 ?
Storage, 存
# O o5 \6 M3 Z2 @6 SStrata, 层（复数）' Y4 c/ f0 h( D! r
Stratified sampling, 分层抽样
/ X1 v" D5 m( X) Y7 Q" \/ {Stratified sampling, 分层抽样8 y* Y/ [$ K" t6 D* \( h
Strength, 强度
& r' |' x# E+ p: GStringency, 严密性2 G7 q3 O7 K0 m; H
Structural relationship, 结构关系
5 m7 \; p* Q( l2 ] V1 F2 V( uStudentized residual, 学生化残差/t化残差! Q" v/ T4 P2 ^1 Z* D
Sub-class numbers, 次级组含量
( c3 J8 |5 ~% T9 ]Subdividing, 分割
0 }; L0 }; g+ J3 h G' T4 k/ {Sufficient statistic, 充分统计量
5 M& }8 m1 D4 N4 n8 I/ l- T6 d6 eSum of products, 积和" O! E" ^ g8 K* N
Sum of squares, 离差平方和
3 G) o# G K( Q, i! A! ESum of squares about regression, 回归平方和
) V4 o9 Z* [: D+ ESum of squares between groups, 组间平方和
5 L! C+ t+ W9 e# L Q' @9 FSum of squares of partial regression, 偏回归平方和* ^4 t, @3 V8 m; G6 S% z0 G
Sure event, 必然事件2 O, B. k% r; _
Survey, 调查
$ i* w5 f* b% s# c: A- vSurvival, 生存分析( }5 B1 W$ W- q! A; {" @; |
Survival rate, 生存率
- j2 R. q) `2 {$ B$ d' u4 ISuspended root gram, 悬吊根图
f! Z! k% O2 t3 ~2 [1 V9 v4 ISymmetry, 对称0 P4 z" `) B4 Z5 y7 J- j* C' L: a
Systematic error, 系统误差. x8 R8 n* P* ^& z) |+ F
Systematic sampling, 系统抽样
$ s- O1 m/ I( B5 M0 ]0 E4 eTags, 标签
+ C' j% e& f0 o8 d z5 P$ eTail area, 尾部面积
, R5 J9 b. P9 ?& P# M+ P, ~+ WTail length, 尾长
; \1 v/ \; K$ G) w8 h7 oTail weight, 尾重
: F9 P! N( E ^5 N# xTangent line, 切线* i' B* O, u- Z1 I- W9 @
Target distribution, 目标分布5 I& {) o5 k4 n$ b0 I- y4 J/ e) r
Taylor series, 泰勒级数8 w! }, c B4 N' ^
Tendency of dispersion, 离散趋势
* n# u) r5 J8 ~# z& { q- a6 p4 jTesting of hypotheses, 假设检验5 b: X% D, S& Q4 y( q
Theoretical frequency, 理论频数
- W5 `, ~$ x( v- O+ STime series, 时间序列5 s' o& S5 M/ |9 Z$ x8 Z0 M# v9 } f3 N
Tolerance interval, 容忍区间7 q) [8 M" {. _6 K+ v
Tolerance lower limit, 容忍下限
* y# e) ^# L8 D! S \5 QTolerance upper limit, 容忍上限' K i9 m w# G ]: I
Torsion, 扰率
! |/ e% w% { m) T0 aTotal sum of square, 总平方和
0 H7 r8 [. X& J+ VTotal variation, 总变异! }" B+ F b" j7 x" g9 w
Transformation, 转换
) M$ X3 a! W0 z5 X7 [( c; wTreatment, 处理
4 {) A0 m/ W. l4 u0 DTrend, 趋势
. L5 L; A8 h* ^Trend of percentage, 百分比趋势3 C7 B; }( o; ^5 u
Trial, 试验& F. W/ z+ H$ X O
Trial and error method, 试错法- g- w9 _8 x; Y( b! |4 d2 C
Tuning constant, 细调常数6 }0 q) d+ |7 l& [5 C; z
Two sided test, 双向检验
, }$ F* G5 m% j2 r: RTwo-stage least squares, 二阶最小平方2 a4 R# R5 {) E* q7 d
Two-stage sampling, 二阶段抽样
& r% F* Q, ?. y) n5 D1 T4 gTwo-tailed test, 双侧检验
6 M/ @8 l0 O# }Two-way analysis of variance, 双因素方差分析
' |9 ^4 B% ~4 G0 J$ Q+ v- Z8 Y9 HTwo-way table, 双向表
L; Q- s7 [7 Y9 o3 \; \, hType I error, 一类错误/α错误+ @, x( L$ |5 {0 b6 ]
Type II error, 二类错误/β错误% _0 l: J5 `8 ]
UMVU, 方差一致最小无偏估计简称
. x' F6 ~6 x3 l" g* \' f1 nUnbiased estimate, 无偏估计
) ^/ \0 _7 H3 g1 G. F: K1 W, tUnconstrained nonlinear regression , 无约束非线性回归
) S1 O d' Z% pUnequal subclass number, 不等次级组含量
# H `$ N5 `& rUngrouped data, 不分组资料4 E% V0 r+ L. c# J3 S
Uniform coordinate, 均匀坐标& U' q' M9 k% k9 _5 j
Uniform distribution, 均匀分布/ m$ L+ a) d. u0 h' G p- q4 W
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
4 R( |) j# s7 U2 s3 P# P9 [8 R$ FUnit, 单元
7 w; h3 a* N) \Unordered categories, 无序分类
& I# [5 B3 N8 n9 l' LUpper limit, 上限
o7 s/ O& h& pUpward rank, 升秩0 `& b4 n/ C* T3 U; v3 @
Vague concept, 模糊概念
8 }2 L% a: s0 K) ?Validity, 有效性
" J4 M" h- |9 {) [; e" T l" @* tVARCOMP (Variance component estimation), 方差元素估计6 J1 S' t6 A5 c* i6 a7 \2 U4 M
Variability, 变异性& E3 |0 B/ e* N
Variable, 变量
, b) A8 q# M- B7 {Variance, 方差 d$ x# k, T( S& y b
Variation, 变异
+ n1 c4 b- |$ sVarimax orthogonal rotation, 方差最大正交旋转 E8 V! X+ O5 a4 E) H9 }' }
Volume of distribution, 容积0 h1 e" t2 g/ g) ]2 B0 e/ `2 |8 M
W test, W检验
/ M c6 f5 T* L: e9 j/ MWeibull distribution, 威布尔分布
' n# {9 e1 e9 q# t9 ^Weight, 权数4 [# N; ~9 R8 L1 [& ]% k# p
Weighted Chi-square test, 加权卡方检验/Cochran检验
/ v" G2 }8 |7 `( o0 O2 Q& q! PWeighted linear regression method, 加权直线回归
/ \$ i- p' o1 v. ?! @. |Weighted mean, 加权平均数
! t: m4 ]( j/ d8 Q/ I$ p, K4 Z/ _Weighted mean square, 加权平均方差
+ W' o9 i, w6 \! ?Weighted sum of square, 加权平方和
7 J' U# r7 p b& f1 N; Y oWeighting coefficient, 权重系数
0 I8 P# P$ C6 }Weighting method, 加权法
) ~, |: d: P( }( U6 ]W-estimation, W估计量
9 W8 X/ o3 w. }8 w6 KW-estimation of location, 位置W估计量
1 Z3 f+ a6 ^8 K w! l T3 dWidth, 宽度0 L7 s9 n) k0 d
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验 T. [( s" L, X" J/ O& k
Wild point, 野点/狂点7 }5 z1 ~/ X/ d5 Z: M
Wild value, 野值/狂值2 Z+ a' n l" _& @' S( s4 d- i
Winsorized mean, 缩尾均值
' @, M) S8 F& ~7 m9 WWithdraw, 失访 ! n& B3 w3 f( A( N
Youden's index, 尤登指数
" R% _( f: M; iZ test, Z检验
" Y/ z' Y; D, y; kZero correlation, 零相关' v# k8 I+ O3 X7 M: x. A
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
