|
|
Absolute deviation, 绝对离差
% x' s/ d" K6 a) a- {3 KAbsolute number, 绝对数/ D1 v. w$ z& J" K4 D" e
Absolute residuals, 绝对残差
, T" f1 K& o" }+ qAcceleration array, 加速度立体阵
5 ^$ i: V( M& M+ cAcceleration in an arbitrary direction, 任意方向上的加速度7 @5 G: F2 Z& P; ]+ J5 K/ @4 w
Acceleration normal, 法向加速度! q8 ]0 F, H* K# e$ @+ g+ J4 o8 H. n
Acceleration space dimension, 加速度空间的维数8 g% @% @8 R5 o( t- c @! |6 V
Acceleration tangential, 切向加速度4 D1 T9 n+ d5 e- y2 p+ V m# H
Acceleration vector, 加速度向量
$ } s7 Y9 f, z* X2 tAcceptable hypothesis, 可接受假设
- N" Q1 Z" c$ ~& uAccumulation, 累积
8 f1 V F- c+ n% IAccuracy, 准确度
; F6 v. I5 j- h5 j; o0 C$ Y! }Actual frequency, 实际频数# t" i9 G# P2 G6 j" l. Q# q
Adaptive estimator, 自适应估计量4 m/ J8 i, y, x( C9 L7 I
Addition, 相加; ~ M$ a8 M9 M
Addition theorem, 加法定理
( n: A# i5 ?" G$ M" `9 GAdditivity, 可加性- h: a, \ M' W \
Adjusted rate, 调整率+ P9 p/ ]% @$ x. D$ b8 i
Adjusted value, 校正值
8 I3 P! X0 W1 d! B# g' f5 V7 jAdmissible error, 容许误差
8 i; }" k; m& c* [, H0 p, |, }Aggregation, 聚集性
+ X# g- ?7 ^( s' N3 s3 _) o$ N% E6 J' VAlternative hypothesis, 备择假设3 h3 W6 C0 k& }: E* `0 y0 |6 C8 H' K2 Y1 q
Among groups, 组间# p: @% T U1 ]
Amounts, 总量
, Q* f: w8 d I/ o" W9 VAnalysis of correlation, 相关分析
2 \ n* R' x0 \, g5 QAnalysis of covariance, 协方差分析2 r$ o: O! N% r* U% }, n3 Q
Analysis of regression, 回归分析
A2 B3 X( W4 W' v6 n$ _Analysis of time series, 时间序列分析 J& b: V$ F9 p$ G/ ~. e
Analysis of variance, 方差分析2 Z% D' M5 W# R" }) y2 G3 H
Angular transformation, 角转换; c1 ^4 N0 ~- |
ANOVA （analysis of variance）, 方差分析" p9 {4 \# c5 b- @0 s
ANOVA Models, 方差分析模型- o( v- n' {' D, f$ b
Arcing, 弧/弧旋1 O6 Q/ g* e* v
Arcsine transformation, 反正弦变换
! Z9 k$ G% G% ?# I3 e, c% ?Area under the curve, 曲线面积
; f/ ]+ Z K. N% U5 \4 u4 R+ C8 _AREG , 评估从一个时间点到下一个时间点回归相关时的误差
# F* s6 T8 m% {4 L5 kARIMA, 季节和非季节性单变量模型的极大似然估计
8 V- N; F! r! BArithmetic grid paper, 算术格纸7 M' f0 H Z7 m9 v: _6 e4 _
Arithmetic mean, 算术平均数) @8 Q5 ]8 y3 J' I. ~
Arrhenius relation, 艾恩尼斯关系
, j8 G% y; }) ]/ A) j vAssessing fit, 拟合的评估% s& n% J4 P' R3 ]& r+ l+ ^
Associative laws, 结合律3 s+ c& ]2 Q# `
Asymmetric distribution, 非对称分布$ l/ @( ?( \5 U! V1 c
Asymptotic bias, 渐近偏倚6 p' ^' A; H6 U. Z. d2 a6 |
Asymptotic efficiency, 渐近效率9 z- J! Y! ]3 v% ?2 v
Asymptotic variance, 渐近方差
8 L4 E2 {! w2 ?/ J6 E" b$ h$ T, p rAttributable risk, 归因危险度
/ z h$ }7 b! A. ^Attribute data, 属性资料
7 Z" W$ e' W4 i OAttribution, 属性
0 a5 a7 U! b% ]0 f2 d5 rAutocorrelation, 自相关& r) p# _9 o3 }8 ]$ y
Autocorrelation of residuals, 残差的自相关! o& J% K! a0 Z' L( b$ w5 ^
Average, 平均数3 V" I7 a& g! b$ \
Average confidence interval length, 平均置信区间长度
7 z' C @' N4 w9 ~, ^Average growth rate, 平均增长率# _5 |6 C7 i. z5 Z8 \
Bar chart, 条形图
% a/ D( q+ r& k2 j9 V {Bar graph, 条形图
" V( I/ T, H$ eBase period, 基期/ g9 ]! _7 Y3 n$ r
Bayes' theorem , Bayes定理
! H$ W7 X) i1 i0 Z- t. C1 }Bell-shaped curve, 钟形曲线+ K/ Q2 G( G: V# C
Bernoulli distribution, 伯努力分布& e/ D- A! J9 Q0 ~# t" N
Best-trim estimator, 最好切尾估计量
a: i. O# d& \# j# mBias, 偏性0 e* B% T1 J; w% ^- B& E) P/ w
Binary logistic regression, 二元逻辑斯蒂回归2 u" w+ v( \1 R$ p
Binomial distribution, 二项分布: z# ~: N8 x% o+ B" A3 v1 l
Bisquare, 双平方5 I5 d. m% Q% `! k. j% j8 c* M
Bivariate Correlate, 二变量相关
: Q0 v, n% D& ]9 OBivariate normal distribution, 双变量正态分布, Z) \0 C$ L9 d$ S
Bivariate normal population, 双变量正态总体
6 E' ]: I9 _9 yBiweight interval, 双权区间
8 U1 a; P9 m. x& W1 YBiweight M-estimator, 双权M估计量
4 a* e& p* q# o% oBlock, 区组/配伍组6 @: i6 ]% K/ i/ g
BMDP(Biomedical computer programs), BMDP统计软件包
0 f' T( j) y s1 TBoxplots, 箱线图/箱尾图
, ?' v$ E( A2 z; u# q1 T; B/ w; gBreakdown bound, 崩溃界/崩溃点+ n. a+ G9 [2 q/ ?+ F' S
Canonical correlation, 典型相关
2 d3 ?7 `' y5 H# j: U4 G8 _. m" LCaption, 纵标目. f3 I/ `6 K8 @/ D
Case-control study, 病例对照研究3 T$ o: G5 c1 N; `
Categorical variable, 分类变量, ?; U3 X& H, @5 H9 W9 W
Catenary, 悬链线9 Z1 N$ ?2 | _8 u% F1 |. x3 c
Cauchy distribution, 柯西分布3 p1 K9 _: C0 t" n) H+ F
Cause-and-effect relationship, 因果关系
; R* A7 L( q1 |7 J' L) \4 r- cCell, 单元
# D1 Z5 w" w; V- m( ^8 tCensoring, 终检
8 b9 V: R, E, uCenter of symmetry, 对称中心. j B. I: e! F* y! b% k0 h9 U
Centering and scaling, 中心化和定标
# W; k% g* x: U& OCentral tendency, 集中趋势
+ L2 J. @* b+ X; h8 s' u cCentral value, 中心值
( F) I2 h8 `- S- j wCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测0 b, @+ C, z$ Q. @* Y
Chance, 机遇
0 i( \; z l5 e3 KChance error, 随机误差
; G t. ?1 Y' E( z( r# {Chance variable, 随机变量5 }4 j5 z5 v' f
Characteristic equation, 特征方程
W( R+ f! |" g' g% sCharacteristic root, 特征根
. R6 G4 U/ z9 O- l8 d9 }9 fCharacteristic vector, 特征向量! g6 w! \9 I% d6 n
Chebshev criterion of fit, 拟合的切比雪夫准则
+ K) p4 F% v2 Y1 p2 f) gChernoff faces, 切尔诺夫脸谱图
0 H7 K- s% W3 VChi-square test, 卡方检验/χ2检验
" D; v$ R* k' Z" M; pCholeskey decomposition, 乔洛斯基分解
) P7 d' a" Z/ J' mCircle chart, 圆图
m- J+ s: S. _# u/ aClass interval, 组距0 s+ U# q1 v8 W8 y+ k& e0 f
Class mid-value, 组中值, i0 q$ Y$ G# \# v
Class upper limit, 组上限
# X* ~6 u/ }* o4 A5 U& zClassified variable, 分类变量
0 }) e8 Y3 N( V8 X' I E& wCluster analysis, 聚类分析
. X8 V. S4 v8 v2 W- ^2 g6 r1 o; vCluster sampling, 整群抽样
, P; Y7 m! X$ H& J* k& L8 mCode, 代码
. x! X8 B8 B+ Y' E5 d( T8 u5 u+ `Coded data, 编码数据 B2 X. j7 f" E; E* ?
Coding, 编码 D5 M1 L) a; _( z
Coefficient of contingency, 列联系数
: \# U' I9 b% j* Z3 Q+ CCoefficient of determination, 决定系数
0 F/ f7 X, }* k F6 PCoefficient of multiple correlation, 多重相关系数% g) C4 H) h* G8 g' S. Z; V l
Coefficient of partial correlation, 偏相关系数$ x4 `: `9 m+ F j( D
Coefficient of production-moment correlation, 积差相关系数0 ]8 ?0 Z: ]' ]+ z" \! a5 d0 L
Coefficient of rank correlation, 等级相关系数3 Z* j. ]( r9 R3 C2 V8 B1 Y0 I( T
Coefficient of regression, 回归系数' S1 u. y v# C, _! w
Coefficient of skewness, 偏度系数
. W7 A! J: o8 b* S8 {* HCoefficient of variation, 变异系数 z* ]. C" m/ n7 C' {
Cohort study, 队列研究
1 `& h% k5 }7 k& h+ ^1 OColumn, 列+ X, r3 [' X2 h+ n4 f @1 T' s
Column effect, 列效应
- G% J8 [+ Y9 i0 V5 xColumn factor, 列因素/ ~2 n3 j1 K- T& M! P% |
Combination pool, 合并: T% w% X& a4 `4 I9 A9 @
Combinative table, 组合表: ^4 ~$ j/ W1 P, D4 \0 a
Common factor, 共性因子2 Z/ R `9 ]6 {2 t
Common regression coefficient, 公共回归系数
Z2 U2 [3 u/ S. ?Common value, 共同值
9 ^. C( a9 V/ {1 P# I2 E2 ?" oCommon variance, 公共方差
8 d; R( x2 l* e8 u$ DCommon variation, 公共变异2 @! x0 _! [& a2 [8 D3 E
Communality variance, 共性方差3 c& H, ? ~* h7 O6 P/ X9 f$ K
Comparability, 可比性4 ^: k' y; k" O8 m
Comparison of bathes, 批比较
0 ^8 D E; s# G% O9 L. OComparison value, 比较值2 e1 v/ i. y/ x; B# U# l- V8 g
Compartment model, 分部模型
1 C- X* c7 W8 z0 G! i, hCompassion, 伸缩7 O2 P2 _0 {" L: r
Complement of an event, 补事件
( P! r' |- T- h8 @4 v* ~Complete association, 完全正相关. \2 s4 U$ M/ a" `' W2 l
Complete dissociation, 完全不相关
7 c, R. Q( q( x A1 y$ i# JComplete statistics, 完备统计量4 F' y6 j! ~( G( d3 n2 D5 H" W
Completely randomized design, 完全随机化设计' d7 K C& Z3 u9 S( d+ h2 p
Composite event, 联合事件
; L" C. j7 c/ F, i. p- UComposite events, 复合事件
1 s# y$ o y7 c5 l3 KConcavity, 凹性 D& `- L4 T _5 _ {) j
Conditional expectation, 条件期望
: k, V- K# r( XConditional likelihood, 条件似然) s/ [6 a! s# P2 [, U6 r
Conditional probability, 条件概率
/ b3 b z; E7 N3 r7 S7 jConditionally linear, 依条件线性
( O' {' V1 }, f7 j) d' M7 T- G3 e- [+ h% F2 EConfidence interval, 置信区间
8 I1 I$ r9 p$ o; dConfidence limit, 置信限
; D8 S& D6 L6 i2 O9 IConfidence lower limit, 置信下限
0 j! h6 d5 Y+ y9 h" K3 wConfidence upper limit, 置信上限2 \: k v3 W# h1 r; j( m4 m* E7 e
Confirmatory Factor Analysis , 验证性因子分析
6 `* \" Y- _% ?% UConfirmatory research, 证实性实验研究0 ? J4 H" V2 q3 W3 ?$ z
Confounding factor, 混杂因素0 x" J/ p" K8 z8 I2 ^# U
Conjoint, 联合分析
% J9 O9 s+ y( d mConsistency, 相合性
8 C3 {) P+ {* H" N. h1 J8 aConsistency check, 一致性检验
& N8 ~' r$ y( t7 O3 L+ WConsistent asymptotically normal estimate, 相合渐近正态估计
1 Z) G; P& t0 c$ a9 jConsistent estimate, 相合估计
6 w. O% s; H# n' t3 g$ tConstrained nonlinear regression, 受约束非线性回归
% f* W$ e! y7 C/ QConstraint, 约束
+ ?! k: S, ]5 Y3 xContaminated distribution, 污染分布: j0 s' b! }6 J+ ~6 Q$ s: K1 }3 o
Contaminated Gausssian, 污染高斯分布
7 x1 \' |6 g% M7 m& l: W& t# YContaminated normal distribution, 污染正态分布' J) K) N$ ^/ \% u4 h
Contamination, 污染
5 L0 B& d8 p h& t4 a8 j2 UContamination model, 污染模型 O6 ^+ s# b: V% A# h3 }8 |6 o
Contingency table, 列联表) |5 `. o5 b- [, V4 Y# [$ p* v6 _
Contour, 边界线3 D% X! e6 l0 d& M3 s' r) a
Contribution rate, 贡献率
; ]( @3 S, s; sControl, 对照! G! \% L5 Y5 ]( Z' s
Controlled experiments, 对照实验 I9 h, I6 s& ?9 t6 P. ?# E1 e
Conventional depth, 常规深度
( l- {9 E0 W& I) R2 C% U: H- O2 t( XConvolution, 卷积
! m- @ S3 z5 R" o" TCorrected factor, 校正因子8 J/ K. O* k( b3 x9 i# U+ }( Z! C
Corrected mean, 校正均值
5 U9 \$ V* Q! X8 e0 h8 NCorrection coefficient, 校正系数
7 ^" P5 {2 |5 D$ N* m; DCorrectness, 正确性
6 j# T- s' r+ I" Y2 Y9 ?Correlation coefficient, 相关系数) H, L0 G. S4 k
Correlation index, 相关指数
4 d9 p! y" C, kCorrespondence, 对应
, ^4 u6 C2 t0 o3 V2 yCounting, 计数
( l8 ^4 z' v' s2 n( aCounts, 计数/频数 h8 c- k8 q5 `: I$ t3 K) q& X
Covariance, 协方差
. {) c4 V( a3 e# P7 q7 OCovariant, 共变 . D, r. ]+ c- @4 D
Cox Regression, Cox回归
! J8 a. E7 F" b! G7 S" E, ICriteria for fitting, 拟合准则
9 r: p0 v3 y: @. k' aCriteria of least squares, 最小二乘准则
( P% K4 `, [ W$ T# A( J# JCritical ratio, 临界比( D7 E% [" N0 j: p
Critical region, 拒绝域$ {9 C( w3 `0 b8 M$ D7 ^% R
Critical value, 临界值" |+ P1 Y. S- f9 I
Cross-over design, 交叉设计
! E1 F' _9 g$ G4 t- FCross-section analysis, 横断面分析
, s9 z& l/ v! {0 c; DCross-section survey, 横断面调查
* n1 r3 z7 ^/ v! @Crosstabs , 交叉表 / D0 ?3 q! P3 |4 D0 v+ _. }5 h+ M
Cross-tabulation table, 复合表
/ Y( z) S6 e: C2 [Cube root, 立方根' l2 U7 m. }6 e X
Cumulative distribution function, 分布函数2 k% z$ M7 Y3 Y( W% l2 L
Cumulative probability, 累计概率2 b2 Y6 W) W2 N- z2 U
Curvature, 曲率/弯曲# E' ^ @. ]3 @# i
Curvature, 曲率
& A$ r6 ]3 t- n* rCurve fit , 曲线拟和 : s1 y2 v% l8 D( k! u. n/ R# ^
Curve fitting, 曲线拟合4 `% I6 [* z( M( t' d4 w
Curvilinear regression, 曲线回归& r1 u+ o# A/ V/ `9 @- d
Curvilinear relation, 曲线关系
. r2 R e. D7 D! ^Cut-and-try method, 尝试法
: q1 D# O& ^' ]. M8 u: h% QCycle, 周期9 y9 C1 O; y( n6 B F$ ^ o0 B, l9 J
Cyclist, 周期性 C. g* I. f! W. R( [# M$ b* f
D test, D检验
6 g8 X% y/ A. K" i' CData acquisition, 资料收集
Q7 r9 \* k9 x0 U! TData bank, 数据库: y2 D& o E6 f# I5 V6 k
Data capacity, 数据容量8 c" W& g7 { u. V, }% G, ]+ @- l. p
Data deficiencies, 数据缺乏4 d2 c1 s1 B e, I
Data handling, 数据处理
8 @) A! k1 P, t* N9 y( |: Q+ C pData manipulation, 数据处理8 ]; j. S8 Q: t" ~, U
Data processing, 数据处理2 w4 T( q' I9 l2 \; u& A' A4 O- h
Data reduction, 数据缩减5 d a. T+ R, F d6 z3 {
Data set, 数据集! O! G; {; i( M$ B
Data sources, 数据来源7 u' x4 c3 h* Y
Data transformation, 数据变换2 F; h9 ?6 x$ R
Data validity, 数据有效性
b0 r y5 M/ b$ G @5 F1 k$ X& YData-in, 数据输入
1 e' Z! l2 d. i4 P& a! g8 rData-out, 数据输出 w7 U8 S' J+ l
Dead time, 停滞期4 X; Z3 s+ T4 U6 S3 v0 O2 B5 I
Degree of freedom, 自由度( W* i- h- Z+ | R# l! H1 G1 f
Degree of precision, 精密度1 Z0 r8 l' Y' Z; I [
Degree of reliability, 可靠性程度9 s! x1 X% a; h# i3 g* X
Degression, 递减. a2 q9 l% W0 I2 M% [. D
Density function, 密度函数0 M0 |1 r* H: c4 T! n
Density of data points, 数据点的密度
! {4 U+ T( s! `1 \; YDependent variable, 应变量/依变量/因变量% G5 @3 J( q* Y6 _3 \" I0 L- ^
Dependent variable, 因变量
Z9 y5 `+ s7 l/ T+ }Depth, 深度
- A: o5 {5 G* R9 K2 D8 K; k( uDerivative matrix, 导数矩阵8 r3 o9 f5 {; X l
Derivative-free methods, 无导数方法" K. f" U* ^5 D( q& E2 p+ N
Design, 设计+ g4 y7 ]4 V6 [- j9 O8 c) D
Determinacy, 确定性; y& m4 u; Y i- H, @! b! f# X" e
Determinant, 行列式
* B4 p6 b$ Z9 y# J4 o8 D% `' wDeterminant, 决定因素8 ]. K# C) ]# ?
Deviation, 离差
) i2 o& S' L- L* ?4 sDeviation from average, 离均差
+ Y3 z& c1 _$ k' yDiagnostic plot, 诊断图
+ {" }* h9 O. QDichotomous variable, 二分变量
3 a* [- \+ R- }$ xDifferential equation, 微分方程2 p) Z, R1 C5 O4 W: \
Direct standardization, 直接标准化法( R* O( O* I# x1 o7 B5 |5 R8 `& {
Discrete variable, 离散型变量
- e- @6 _, y% j# i2 }DISCRIMINANT, 判断 6 s) u7 h' ?$ j7 d1 T' ~
Discriminant analysis, 判别分析4 C+ u+ n7 G3 t0 B
Discriminant coefficient, 判别系数7 ]. X9 y5 u/ F1 ^4 \7 R$ s
Discriminant function, 判别值: F" F) P+ @' o. S M
Dispersion, 散布/分散度
3 F! ]; x; }7 n( c# h$ ?- F0 qDisproportional, 不成比例的
: p+ V# {% L2 P7 e2 mDisproportionate sub-class numbers, 不成比例次级组含量
; Z' G' C, Q/ p4 Z9 x) \+ PDistribution free, 分布无关性/免分布! v3 j2 W$ g7 ^# e0 B
Distribution shape, 分布形状3 M- Z @. D! @) W
Distribution-free method, 任意分布法
' }/ J' S) n, b6 i! q6 d5 K5 nDistributive laws, 分配律
+ O# `8 m: r" H$ o o6 v8 U% v" {; bDisturbance, 随机扰动项/ g7 S- D6 j0 x
Dose response curve, 剂量反应曲线
, a% {$ ~$ s& U" E, a( sDouble blind method, 双盲法- R& r w6 P8 T
Double blind trial, 双盲试验
( a$ c( A, u9 ?3 {+ xDouble exponential distribution, 双指数分布
" x5 E+ l; f7 z7 M* ~& pDouble logarithmic, 双对数
, \& D; \; h; l* W; v V4 A1 p3 cDownward rank, 降秩6 F4 l, S9 H2 f8 b
Dual-space plot, 对偶空间图- M6 l& H% }: ~8 A3 [: k3 U
DUD, 无导数方法* }& Q( `& z i. U) r2 I
Duncan's new multiple range method, 新复极差法/Duncan新法
' _" ]1 Q# g/ D+ N3 W9 QEffect, 实验效应# C% @0 H0 Z R e3 f4 ]3 \4 ~
Eigenvalue, 特征值
5 w7 f: o z6 p) A5 JEigenvector, 特征向量
3 U4 y$ R( K# s$ Z8 Z: sEllipse, 椭圆; `2 a m& [( N' M8 F
Empirical distribution, 经验分布
]5 h4 T- n" o8 tEmpirical probability, 经验概率单位
% `# J0 e+ N6 R3 OEnumeration data, 计数资料! L- V- w8 w/ Z7 M- B- E& M' S
Equal sun-class number, 相等次级组含量
* \7 z: N& r6 A2 i6 LEqually likely, 等可能
9 Z6 Q# C3 ^0 W5 JEquivariance, 同变性
! m. D/ g* D- b# x U* @Error, 误差/错误
- |: H m* X1 D) A0 eError of estimate, 估计误差
, A4 Z" E% Y4 qError type I, 第一类错误! \7 [+ p& o$ q" w @6 v6 }
Error type II, 第二类错误/ K5 L3 H' c" X
Estimand, 被估量
2 c/ Q5 m7 ~2 a8 G5 LEstimated error mean squares, 估计误差均方
- j/ p6 X% ]8 L1 qEstimated error sum of squares, 估计误差平方和7 c- ^( O" s# D( ]
Euclidean distance, 欧式距离/ |6 M- b. s8 k+ b( O: p/ f1 a
Event, 事件7 p7 h: @0 B$ h6 W9 s& c9 p
Event, 事件
* ~7 ]$ A L; d1 _Exceptional data point, 异常数据点
9 l5 f; o {1 T* H+ B, fExpectation plane, 期望平面; z7 x9 |: R/ s
Expectation surface, 期望曲面5 N/ @8 j9 A6 H% d: s
Expected values, 期望值4 P; \) ^( ]/ V4 V: [- |; j9 n" R
Experiment, 实验
. s0 P) ]9 c9 [( {5 T1 X! c7 DExperimental sampling, 试验抽样2 G! W7 S5 k$ d: n9 N& A" D! M9 s& k
Experimental unit, 试验单位6 c0 b8 O3 {# ] V! j0 U# H; |1 L
Explanatory variable, 说明变量
1 L4 g H; i7 C0 K* UExploratory data analysis, 探索性数据分析3 u! E4 n6 ^3 ~/ `$ Y
Explore Summarize, 探索-摘要
& I2 C9 [2 ~6 q8 V# I8 nExponential curve, 指数曲线
- m# h9 q( N# t9 g ~Exponential growth, 指数式增长
$ q8 [3 J+ ]8 t+ q7 {% ]/ GEXSMOOTH, 指数平滑方法
2 q- h. y2 v0 s1 M, j! zExtended fit, 扩充拟合+ f; L! D7 ~' E
Extra parameter, 附加参数+ a6 J, m. x3 N( t4 n
Extrapolation, 外推法# |5 {& M" ~7 _* J; c3 P7 R
Extreme observation, 末端观测值5 x+ b$ K& g# n) h' Z
Extremes, 极端值/极值
7 Y. N( F( x* C( b8 l/ O& oF distribution, F分布# _+ h2 R$ E; W/ j% f) t; t% u
F test, F检验
4 T. c" Z9 Y7 a7 X8 X1 RFactor, 因素/因子1 v- R$ x5 m) `, Z. N
Factor analysis, 因子分析8 h& I. a4 F( k
Factor Analysis, 因子分析/ J: i6 G3 Q/ L
Factor score, 因子得分
5 ~0 A9 ]' T: T1 H: f5 _Factorial, 阶乘
/ W( u- ^ P' ]+ AFactorial design, 析因试验设计& m5 c" y! Z0 m6 n& Y2 f. g w% a
False negative, 假阴性
3 f# Q; K: A& `4 W/ w5 g4 {# j: dFalse negative error, 假阴性错误9 C3 |) T' s9 B
Family of distributions, 分布族/ s: R$ y' x7 j( Q# a4 _
Family of estimators, 估计量族
- k! @! A" F6 @# S' O8 x7 `Fanning, 扇面
3 N) M( J. x( X3 I3 yFatality rate, 病死率' V9 M5 P, ]' E& Q
Field investigation, 现场调查
8 [" G$ I8 p4 x" l+ ~Field survey, 现场调查+ E9 _+ X5 e5 o6 _7 e5 l: T
Finite population, 有限总体/ r$ N+ d% ?6 p, [/ }5 o
Finite-sample, 有限样本
0 Z; ~+ y2 e- F3 F( ~; Z" LFirst derivative, 一阶导数( x" z+ Z' Q* b, |. x
First principal component, 第一主成分
; G) A# B4 W8 pFirst quartile, 第一四分位数' G; i: L' l p2 w) u$ N3 a
Fisher information, 费雪信息量) |7 x& M7 A9 y3 q
Fitted value, 拟合值
$ {3 V8 i2 ~: `% [- dFitting a curve, 曲线拟合8 |8 ]) s- ?' f* e9 q* w
Fixed base, 定基
7 U$ M# K% F, v* WFluctuation, 随机起伏
0 m0 Z# p! Z, U# f" ~$ @# IForecast, 预测. E2 z2 s8 s5 E# B9 { l
Four fold table, 四格表. y& j: a6 n' [% p
Fourth, 四分点
7 s, m; P$ F9 ]8 {, u! g# |Fraction blow, 左侧比率
) r4 p3 T, n+ X' I: T' }. b/ n. PFractional error, 相对误差 S0 ]8 c8 m& `! w9 l- ]( h
Frequency, 频率. ]4 Y+ ^0 p1 \. H
Frequency polygon, 频数多边图
$ {' O( X! m! gFrontier point, 界限点( K, d+ y' z. j# n- n# A! M
Function relationship, 泛函关系
" N& ^, f B' O- SGamma distribution, 伽玛分布0 \. e& H, q2 Z- w& w8 c
Gauss increment, 高斯增量0 ~; j9 `/ K2 u" U* R, {1 k3 c7 A
Gaussian distribution, 高斯分布/正态分布. J9 E+ ?* w7 p( a- R1 ?: s$ }
Gauss-Newton increment, 高斯-牛顿增量
6 {; J9 D* J* X1 p" W/ G# P7 mGeneral census, 全面普查
! d) m; p1 N* C9 |2 qGENLOG (Generalized liner models), 广义线性模型
- ]9 A; d" u, J6 ?Geometric mean, 几何平均数
1 R8 x, \! B7 E* L* vGini's mean difference, 基尼均差0 F7 }3 q# j+ Q* D+ o& ?4 @4 J" W" f
GLM (General liner models), 一般线性模型
- F; q' I3 b+ M5 J) X! {Goodness of fit, 拟和优度/配合度
8 J# ^7 {- i. w" u& q% B2 {5 cGradient of determinant, 行列式的梯度1 S1 y( z2 G& j; t! T8 F, m
Graeco-Latin square, 希腊拉丁方4 q9 B m% K" t. h7 S
Grand mean, 总均值
# G H# V2 @/ O& G8 f* y/ oGross errors, 重大错误- J% ^0 Z k. y% t# o
Gross-error sensitivity, 大错敏感度
1 ~# r _- p$ b$ }# AGroup averages, 分组平均# B- L9 U2 Z h, k5 ?
Grouped data, 分组资料
2 z2 }' y; q' N! _* F* FGuessed mean, 假定平均数: a' A; A6 \) l' ?! J p# c
Half-life, 半衰期
1 p9 f* z/ X6 D5 q7 m, hHampel M-estimators, 汉佩尔M估计量
$ i& S# o+ T7 tHappenstance, 偶然事件2 T4 P F0 c; X7 ^0 U
Harmonic mean, 调和均数: \0 M) K0 Z1 s) n
Hazard function, 风险均数
4 l! x# j) }. p9 O( ~! d z3 k* L. nHazard rate, 风险率$ b) E; o1 T/ |9 [& z2 ~
Heading, 标目 * C( K" m& i" F0 L' _0 v0 y% [
Heavy-tailed distribution, 重尾分布8 k4 U; t/ x+ ]- M" D& g
Hessian array, 海森立体阵
G3 j6 [! G& x- \Heterogeneity, 不同质
& Z( `9 f" \# W1 @Heterogeneity of variance, 方差不齐 ! y- t! O. r Y: i+ C# z0 v
Hierarchical classification, 组内分组
% r" D( |% i5 y% \- UHierarchical clustering method, 系统聚类法
( Y8 J4 Q! [6 g3 Q; DHigh-leverage point, 高杠杆率点
# O, }$ C. ]/ y) o h6 p2 BHILOGLINEAR, 多维列联表的层次对数线性模型' Y$ S; D" }5 H5 x3 T
Hinge, 折叶点
~+ C% S+ P. C5 L. h3 `6 _. @0 u9 ~Histogram, 直方图" c$ `$ W' G2 Y* E- |! _8 ~! { |
Historical cohort study, 历史性队列研究 ; H2 x9 _2 Z% P+ O* f
Holes, 空洞
2 l9 k4 Y, s) u+ j# D% a: eHOMALS, 多重响应分析
2 I; T& M/ x% `! eHomogeneity of variance, 方差齐性
2 U; V$ D7 U+ w) QHomogeneity test, 齐性检验. F2 ?8 V. b' }9 H3 w" Q) R
Huber M-estimators, 休伯M估计量
6 y( b0 p4 V" \/ XHyperbola, 双曲线
# v. D5 H! K6 Z+ O P9 g& v3 G" wHypothesis testing, 假设检验$ e$ C6 N' k* O& u5 Y6 w( c
Hypothetical universe, 假设总体
1 X7 T, N6 K e' o; j& z8 J8 g; T2 wImpossible event, 不可能事件
& h, p% C. Y1 X% [0 A% ?6 yIndependence, 独立性1 Z. a' D" U }5 ]6 S7 u! `" z
Independent variable, 自变量
- z' P7 J3 S0 ~: u9 G; |3 gIndex, 指标/指数% D& A* S* S D$ o
Indirect standardization, 间接标准化法# z5 ] Q- W3 T$ h
Individual, 个体
2 x4 c9 z% f3 N$ u! ]) z- HInference band, 推断带% ]$ v& ~6 x2 W( b" U! j
Infinite population, 无限总体: w/ N7 M% R$ m3 U5 M
Infinitely great, 无穷大. i# Z" E1 x& Q$ ^3 R
Infinitely small, 无穷小8 I& A5 ^2 ]8 X8 i
Influence curve, 影响曲线
. V$ \ m0 {( l# t7 I! gInformation capacity, 信息容量
+ ?0 b. F' I% }6 s" G4 i0 ?Initial condition, 初始条件
+ P3 b% t* W# v# W/ k; B) [$ VInitial estimate, 初始估计值
4 ^ z f1 \/ o$ r( S# eInitial level, 最初水平3 Z5 q: S% V7 V: l3 f, b1 ?
Interaction, 交互作用
$ p% a4 I* E& q: b. w' L: @Interaction terms, 交互作用项
, X$ }/ s) r6 u5 T- U( ZIntercept, 截距
3 P3 I0 @& A' @0 M5 d& d; tInterpolation, 内插法
0 `, b7 U4 l/ {& ?& FInterquartile range, 四分位距. N5 B5 |) ]" y' Z
Interval estimation, 区间估计& q, {" ^' O: D- [
Intervals of equal probability, 等概率区间
! f h( Z |2 {% q) vIntrinsic curvature, 固有曲率& }$ ^* {; w1 g. f# q
Invariance, 不变性
& u4 U' T) V+ Q: w* ~Inverse matrix, 逆矩阵
% v* M' o) x) DInverse probability, 逆概率
! @ Q" O/ U- f7 ?9 F+ f+ E* [4 M8 cInverse sine transformation, 反正弦变换& i" h4 m% V6 V* k* T* ^
Iteration, 迭代
, O1 C u# B. t- D4 q) E4 Q9 x+ KJacobian determinant, 雅可比行列式
9 m: g# ^, L9 a% H1 OJoint distribution function, 分布函数$ C. `: e8 C: L6 C
Joint probability, 联合概率
, Z7 R! n1 F- J1 I( |2 i* L1 m+ \0 n& YJoint probability distribution, 联合概率分布
- n5 @' v9 T2 D2 y( U" `7 RK means method, 逐步聚类法
7 L0 p5 v% D9 o0 p5 i% O+ pKaplan-Meier, 评估事件的时间长度 / D8 P+ F' r" E+ b2 S5 k* n
Kaplan-Merier chart, Kaplan-Merier图
8 }& Z. o& ?, rKendall's rank correlation, Kendall等级相关
5 K- Y; ]( d7 O; i. {' \Kinetic, 动力学0 Y" o" P+ Z: z+ w; N; c6 d/ d( f( O
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验# C+ G" Z" c! U- |: V
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
" O5 a3 O9 Q, z/ ^Kurtosis, 峰度
3 _( |! h! k% E. [% t& F3 qLack of fit, 失拟7 w* W# x" B2 I% I* |6 Q
Ladder of powers, 幂阶梯! a3 O7 g+ [5 E5 g7 O
Lag, 滞后
5 e% ]5 f g+ m R5 yLarge sample, 大样本! f% E' H% y% x9 Z& Y8 l# `: q
Large sample test, 大样本检验
$ N6 G* s! Y9 M( MLatin square, 拉丁方
\6 K. B" E! c" tLatin square design, 拉丁方设计
4 l- ^+ |. I' P Z1 s1 uLeakage, 泄漏
' m1 w# a' t- ]" \; DLeast favorable configuration, 最不利构形! h! p0 z( X( n( b8 d" L! R
Least favorable distribution, 最不利分布
% J9 O2 n; u- a3 g( L4 nLeast significant difference, 最小显著差法 b' `' x: l8 S0 X+ F0 x$ A
Least square method, 最小二乘法
8 q7 h& b4 [2 ~' |Least-absolute-residuals estimates, 最小绝对残差估计
6 A( S, N3 j6 u+ DLeast-absolute-residuals fit, 最小绝对残差拟合. T; \* X: z f
Least-absolute-residuals line, 最小绝对残差线+ _7 \; Q& P' q4 R/ k
Legend, 图例 ^+ D! f) Q0 K4 u( Y
L-estimator, L估计量% m2 U. R* c$ e. F8 S" R
L-estimator of location, 位置L估计量
; z8 x5 _- m* ]L-estimator of scale, 尺度L估计量
% e8 H: }. t* { ZLevel, 水平7 @# a7 r( L, E1 f) ~
Life expectance, 预期期望寿命; K, J2 g. D9 b
Life table, 寿命表
$ i) _& p1 Q6 Q$ ~- i2 WLife table method, 生命表法' j# f. s& z3 n4 Z$ U
Light-tailed distribution, 轻尾分布
1 u2 o1 t* U8 x' lLikelihood function, 似然函数
- }, c- t8 |: A+ q' R* qLikelihood ratio, 似然比! U: _! y- n; d3 J" @! [
line graph, 线图+ o: M5 b( `, x4 P
Linear correlation, 直线相关1 L+ D% c2 I, U5 ~
Linear equation, 线性方程( s& e. I8 }. ?6 X
Linear programming, 线性规划
& s+ L9 b5 c, D* O) q: ILinear regression, 直线回归7 b/ Z/ Z j8 H7 x- W, \+ ?
Linear Regression, 线性回归
; I5 H& m3 ?1 i1 q5 ~4 f# RLinear trend, 线性趋势0 i* V& Y F6 K: M
Loading, 载荷
2 o0 s; V1 b3 c4 OLocation and scale equivariance, 位置尺度同变性1 S7 Q4 d" W, |) o
Location equivariance, 位置同变性
0 {) H" G7 I1 L3 BLocation invariance, 位置不变性; l) d* A$ Z7 P* ]% ~* H7 U% d; `
Location scale family, 位置尺度族
) l, O$ W, B; c2 z1 F; V7 g- t2 OLog rank test, 时序检验 * c$ g; d" l; z. c5 ~
Logarithmic curve, 对数曲线
( N2 h1 ]" D3 T: P: J) Q: Q/ nLogarithmic normal distribution, 对数正态分布
9 R7 j Z3 S* L, J. X6 WLogarithmic scale, 对数尺度
; z; n: D+ v- \# e( t2 A( K" k; \7 ^9 `Logarithmic transformation, 对数变换& G; Q% M3 `- b w
Logic check, 逻辑检查/ T/ B# K0 m3 W2 p
Logistic distribution, 逻辑斯特分布
5 k! m6 n6 A7 n$ H4 D" ELogit transformation, Logit转换( M* o% n$ H- T, B# N
LOGLINEAR, 多维列联表通用模型
& J; y. z$ e* m( o9 e5 U5 o$ B3 i1 V3 T5 WLognormal distribution, 对数正态分布
) d! e. J; x8 u. ]4 u: v% DLost function, 损失函数5 t) w9 ^$ b/ Z/ I- G1 o6 m
Low correlation, 低度相关9 t. z% p" f2 E" A, j5 b0 q% [
Lower limit, 下限
5 s/ v% r3 B% @3 z- ^* [! oLowest-attained variance, 最小可达方差* X' h1 @5 @" L' U& J
LSD, 最小显著差法的简称
( r0 i4 H+ C" h3 f! D6 o) gLurking variable, 潜在变量
: |/ C8 v0 V& h& Q" W. }) ^Main effect, 主效应7 U6 o- _/ ]. {- y9 Q3 x5 R
Major heading, 主辞标目0 d- F" v7 x% J2 w5 a
Marginal density function, 边缘密度函数' y- H J; ~! y5 t& [7 F+ d) ]# y
Marginal probability, 边缘概率
8 Z( V1 Z. Q' I: i3 dMarginal probability distribution, 边缘概率分布. h- p" P2 W/ Z, P! C6 R5 P
Matched data, 配对资料
2 C0 N- V0 y& o$ K7 u+ N: n, YMatched distribution, 匹配过分布. U }4 I- h% ]- o% Y C
Matching of distribution, 分布的匹配- ]" c" S8 u5 s+ G) H0 k
Matching of transformation, 变换的匹配4 {8 N) h8 f7 y8 p' j; {
Mathematical expectation, 数学期望0 A# W& \! f3 V. q
Mathematical model, 数学模型( i5 p$ f9 d. Z6 f, v+ U& s
Maximum L-estimator, 极大极小L 估计量
. P& r! S5 V$ F, {Maximum likelihood method, 最大似然法9 U& D: M/ c% a6 {) P
Mean, 均数
0 I+ a% D0 ~5 n G& Y, \Mean squares between groups, 组间均方) }6 R/ {2 J1 F; X, S9 ?% f
Mean squares within group, 组内均方
! u: r5 J; g! u. n. w# _" ~ LMeans (Compare means), 均值-均值比较" v: a4 H' N( A9 o* Y- e
Median, 中位数
9 l$ ~5 k1 K. V# x: tMedian effective dose, 半数效量2 u) J# r/ X+ S5 h' ^( q2 ^
Median lethal dose, 半数致死量
x# L0 ?5 g+ P. \Median polish, 中位数平滑
+ c" V: C8 o" x7 I5 qMedian test, 中位数检验7 i3 y1 O9 E$ V: V' R" v& R- A- v) }0 t
Minimal sufficient statistic, 最小充分统计量) G8 |. ^) C2 L8 r( h! L x5 S
Minimum distance estimation, 最小距离估计
1 B* ?! d4 Z( W$ C( FMinimum effective dose, 最小有效量/ m! P* ^5 y1 ]7 p K' T* H
Minimum lethal dose, 最小致死量
/ b! V+ r% ~0 KMinimum variance estimator, 最小方差估计量6 v) [0 w+ e7 T% X
MINITAB, 统计软件包
* \4 I6 Y& B, m2 t* W* W2 e l+ jMinor heading, 宾词标目- j( T% A5 \1 ?
Missing data, 缺失值( \! F. r0 W8 B0 ?! P0 `
Model specification, 模型的确定, p$ C! [, h i8 }7 `
Modeling Statistics , 模型统计2 g- U' [0 u* e9 s3 b8 t* |
Models for outliers, 离群值模型8 N8 I* y( z! ^9 v
Modifying the model, 模型的修正
, s8 f2 m% a) A6 L/ k4 c( cModulus of continuity, 连续性模3 a' s+ O% l6 f! D- F. \
Morbidity, 发病率
5 ]9 ?+ ~& Y( C: Q2 K8 C+ F6 nMost favorable configuration, 最有利构形' v. z, O1 U( Q# l2 N
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
$ y/ s8 l. r/ |5 C& l m+ |4 oMultinomial Logistic Regression , 多项逻辑斯蒂回归
+ |2 w- m8 X( j. k- }: X5 UMultiple comparison, 多重比较6 X: F% E8 R7 z& E, h' f
Multiple correlation , 复相关
- i) ?5 H1 A$ a7 KMultiple covariance, 多元协方差
! R" n' U, Z4 K NMultiple linear regression, 多元线性回归1 j* l2 j1 ?9 z' p6 p( e6 h3 f
Multiple response , 多重选项
$ r7 z, B. c9 q: y$ l7 LMultiple solutions, 多解
9 M9 n/ T3 f7 LMultiplication theorem, 乘法定理
F' x+ I; o, w4 i8 f: IMultiresponse, 多元响应
( U6 ?0 y1 c( L! V# T3 `Multi-stage sampling, 多阶段抽样3 @! M* ]0 Q0 ?. m* c3 O) s
Multivariate T distribution, 多元T分布4 H8 x( f! g+ D7 b# s
Mutual exclusive, 互不相容$ R. I- V5 s8 f+ \' m/ F0 E
Mutual independence, 互相独立! U; Z% h8 z6 L5 i4 ?
Natural boundary, 自然边界
; o& |. Z7 u; }5 `) pNatural dead, 自然死亡
4 y# ~3 r8 g8 T% S9 q- YNatural zero, 自然零. q0 P2 A, ~) J6 T
Negative correlation, 负相关# F) |0 O( {# O: A& ~( |
Negative linear correlation, 负线性相关; m8 z, ]9 q. i |$ h
Negatively skewed, 负偏
' ?" j( Z2 c9 K% i6 F* O _( }/ S0 B! XNewman-Keuls method, q检验
5 B) Y" M+ f; \# S# D- D! INK method, q检验 h4 s, O% l9 I& b0 i( n! j
No statistical significance, 无统计意义- L& A) @& e9 J
Nominal variable, 名义变量! H0 x8 C1 b5 Q0 N, P. d
Nonconstancy of variability, 变异的非定常性
5 s/ h9 e4 \% ]# V/ VNonlinear regression, 非线性相关
4 x* C. A! z7 k0 e1 V" M+ mNonparametric statistics, 非参数统计! ?9 v" E0 W7 i# G; _( V5 Y
Nonparametric test, 非参数检验
' H: a: ~: Z& V" G) eNonparametric tests, 非参数检验
1 W9 y P2 q& o& P g0 `$ w3 YNormal deviate, 正态离差
" ]3 K" L2 ?) I2 }; wNormal distribution, 正态分布
/ g' j$ P$ d2 |% V3 Q1 l7 O0 TNormal equation, 正规方程组6 T' G: \4 Y! Z& B5 v
Normal ranges, 正常范围
* _) V, {5 u2 M9 TNormal value, 正常值. T; R) |4 O' W* B
Nuisance parameter, 多余参数/讨厌参数0 P7 z6 o4 c0 p! z
Null hypothesis, 无效假设 : G4 b7 ~) L) _3 N; V' n0 R! z
Numerical variable, 数值变量! @2 e# U8 q- F( ?7 U
Objective function, 目标函数+ e+ L0 V6 o% o' E/ i
Observation unit, 观察单位
9 l( c. m0 ]/ Q7 FObserved value, 观察值+ T4 m( S8 k" y, Q/ o7 t9 [. L5 ]
One sided test, 单侧检验6 {9 _6 R4 \) p. @) T8 J" u
One-way analysis of variance, 单因素方差分析. s& Q' c) F7 H: S% m' ]
Oneway ANOVA , 单因素方差分析8 h# ^0 I/ Z0 p' f# i" C: s
Open sequential trial, 开放型序贯设计
7 k5 K' e6 [, q' o4 A3 r5 e& s5 jOptrim, 优切尾
8 \! D( Z# W( Y! k" l$ aOptrim efficiency, 优切尾效率6 T4 a$ X9 l& g! _9 N
Order statistics, 顺序统计量
: C8 ^8 j0 B2 S8 e3 j1 tOrdered categories, 有序分类6 c3 y: l8 F& Y" G$ ]
Ordinal logistic regression , 序数逻辑斯蒂回归/ e6 B$ o. ^, a( ~9 q
Ordinal variable, 有序变量
7 }1 r4 R" R/ l# Y9 N- }+ M6 YOrthogonal basis, 正交基
- J7 L# I) x8 A" T# [7 h* [; POrthogonal design, 正交试验设计& `6 X" H; x. a8 U
Orthogonality conditions, 正交条件9 d5 M9 [$ W1 x0 `- K' K
ORTHOPLAN, 正交设计 ' s: K( z5 i& d' V6 G0 X' Q
Outlier cutoffs, 离群值截断点
2 {" |! z- O5 J0 M. `0 MOutliers, 极端值+ }* L0 w! M" V7 ~) b
OVERALS , 多组变量的非线性正规相关 ' f! z5 U- P; f
Overshoot, 迭代过度- \& V3 `: I; i
Paired design, 配对设计
8 j+ ~1 ]$ [; ]6 Q' f. T; Z# ?$ }Paired sample, 配对样本
/ N1 K# L+ t- uPairwise slopes, 成对斜率; x9 M6 b6 `' d& u
Parabola, 抛物线
1 a( k& }7 R& J5 A) a } h* SParallel tests, 平行试验
7 O j* _0 ^8 z& {+ G& hParameter, 参数
* Z" m9 i# `7 hParametric statistics, 参数统计' q g9 `: `2 i1 B* C! D9 e
Parametric test, 参数检验
P, [ q: j; W5 J7 DPartial correlation, 偏相关
7 p3 D8 a" @" p! H7 p1 ]+ x9 }- JPartial regression, 偏回归
) x- H$ L- H/ v/ JPartial sorting, 偏排序- u- I) _0 F- f
Partials residuals, 偏残差+ l8 A# E4 l! N& r& |
Pattern, 模式- R5 F- ^1 H) @$ d; q4 b f$ K4 _
Pearson curves, 皮尔逊曲线
U- P$ m5 V( b& c; ~" E9 cPeeling, 退层
) o6 u- p8 b* K" D% @Percent bar graph, 百分条形图3 F' n( Y7 W3 Q$ S" `% Y" _1 ~
Percentage, 百分比! T. X+ d, v: d% o" c
Percentile, 百分位数
5 l- o4 }$ N+ w! R1 d. DPercentile curves, 百分位曲线
9 P2 t8 h* ~& O$ {1 dPeriodicity, 周期性6 N/ e2 N+ I' b h8 x
Permutation, 排列
. B' X* T ~2 `' \: |8 x* M0 uP-estimator, P估计量' Z+ C( ^" [9 M$ z$ m
Pie graph, 饼图8 H* X) D& _) T, c2 I( Z' r! `
Pitman estimator, 皮特曼估计量
. z: t9 v! B" Q, p) O3 n4 d2 lPivot, 枢轴量% C( A: `+ \. N# S- _
Planar, 平坦
0 {- K u8 r9 }7 I. gPlanar assumption, 平面的假设
" D1 p1 k) {0 v* N' [PLANCARDS, 生成试验的计划卡
5 r& ~% R3 z2 fPoint estimation, 点估计1 N, r8 j' |3 c- B% c1 k* E" q
Poisson distribution, 泊松分布$ B: I8 f3 C: @- b. C8 s3 c/ A
Polishing, 平滑
4 s) g/ S9 p2 U" vPolled standard deviation, 合并标准差. X5 {9 D. f$ V& d: J" ^" Y
Polled variance, 合并方差. e/ M6 x/ ]4 t2 F
Polygon, 多边图" n% U% o: F7 t1 @7 J
Polynomial, 多项式
& w* v- J8 I1 ?Polynomial curve, 多项式曲线
, p6 F8 @. K4 j" }* j/ g c7 NPopulation, 总体
1 w1 w& E U6 c1 iPopulation attributable risk, 人群归因危险度
9 o5 _3 L% H+ n; NPositive correlation, 正相关' _+ O( N9 `& _0 F5 f
Positively skewed, 正偏: W$ z |& S9 W3 x- Y7 Y
Posterior distribution, 后验分布8 v$ b9 d# w$ `+ T0 c( c
Power of a test, 检验效能
/ z9 p" w8 X# Z/ D6 ]Precision, 精密度3 |5 ]) J8 R& b4 p
Predicted value, 预测值" `8 I* K- |1 v5 J/ |1 a
Preliminary analysis, 预备性分析6 N6 V7 A1 _. P5 s5 c" U
Principal component analysis, 主成分分析
9 u) q) t2 L0 A6 R$ O4 z3 W8 NPrior distribution, 先验分布: E2 }/ e* D, ~6 p$ A q
Prior probability, 先验概率
1 @* ]9 U$ I1 m9 X2 B. KProbabilistic model, 概率模型
5 a4 \" c9 A) Vprobability, 概率# E) n3 F7 f+ b9 J4 f: I5 v
Probability density, 概率密度 }7 v5 O* |- u% I: [# ]8 n* W& S
Product moment, 乘积矩/协方差9 \& M! w& Z# a/ H' |
Profile trace, 截面迹图5 b$ z: ^( _& Y4 p1 u
Proportion, 比/构成比4 p% v8 g2 m% V
Proportion allocation in stratified random sampling, 按比例分层随机抽样. Y6 n" d9 v3 g) a3 ?/ r; E; m
Proportionate, 成比例
/ m* i1 s* k- @& q* z" @0 pProportionate sub-class numbers, 成比例次级组含量$ q4 s9 z2 Y; ]8 f2 V
Prospective study, 前瞻性调查0 W2 y, b8 c) g9 j
Proximities, 亲近性
0 M( O8 L2 _" {4 _' XPseudo F test, 近似F检验" ^9 Y/ T q& F
Pseudo model, 近似模型
. a; \. P4 }7 i5 sPseudosigma, 伪标准差
7 g2 a" J( e; i) G7 HPurposive sampling, 有目的抽样
2 |% A Z7 e! a2 W% F3 Z3 B* fQR decomposition, QR分解
# A5 [& M: P0 P1 I: e2 E. T* T2 }Quadratic approximation, 二次近似( d" T2 z3 t5 t2 j
Qualitative classification, 属性分类3 {! N6 a* c# b* |" A: M
Qualitative method, 定性方法5 k% l% W* \" r
Quantile-quantile plot, 分位数-分位数图/Q-Q图
$ V" ^+ A. `4 H" U4 y- I+ a" B6 IQuantitative analysis, 定量分析
. X+ E3 s; V& Y* N8 O) w/ ^7 N% WQuartile, 四分位数
2 H+ `. z: u/ m; U( IQuick Cluster, 快速聚类
" R) ?9 O- H! M, a, ?Radix sort, 基数排序7 ?5 M# A3 X3 n- Q
Random allocation, 随机化分组
7 W4 u% ~/ @- e' v3 v, qRandom blocks design, 随机区组设计4 C4 r* k$ p" j" v/ a- H
Random event, 随机事件
: Y9 Q& F6 N# y( n) q$ H& ?Randomization, 随机化
. t+ |& x: i% f+ ~* {) X+ ~$ hRange, 极差/全距
# @" p0 ]/ M3 t" B# ~# a# l* n2 {Rank correlation, 等级相关! w: P) o1 u8 \
Rank sum test, 秩和检验
+ v0 k( y0 s5 V4 l$ U( S* `$ l f& XRank test, 秩检验
) V- Z5 U# \( jRanked data, 等级资料
/ U" P2 C W' LRate, 比率+ k! g% @* n! w8 y
Ratio, 比例
" Z% k( j0 J. e/ cRaw data, 原始资料2 [: d8 Y# g7 i7 N- ~4 i) y. D3 ^
Raw residual, 原始残差
6 }7 ~1 ]9 s) F/ }: `6 t! q- H4 u9 VRayleigh's test, 雷氏检验
- v% i! K) ?" {8 P7 J" @: p+ SRayleigh's Z, 雷氏Z值 9 v& x! E" M' J4 K
Reciprocal, 倒数+ T9 [# P( `- O- A
Reciprocal transformation, 倒数变换
. p) D& T6 w' e, ?/ dRecording, 记录
* W& U9 L3 ?/ ^; rRedescending estimators, 回降估计量; i2 W' G4 ]5 K' f1 p
Reducing dimensions, 降维
/ ~$ e6 z9 A; jRe-expression, 重新表达# I: }' f8 E) p' b: U5 d2 ~
Reference set, 标准组* V- Q) Q. L+ d" ~( C9 J. ]4 i4 o
Region of acceptance, 接受域
6 S$ p6 f" i: \ @! T& {Regression coefficient, 回归系数6 Y+ f) a' J' ?2 K
Regression sum of square, 回归平方和
+ R* j$ X0 {+ N- D& zRejection point, 拒绝点
4 l9 h# | H& x/ PRelative dispersion, 相对离散度
; S$ g8 v2 T" z; SRelative number, 相对数9 V4 F& F6 |* j: U( v6 e% k3 j
Reliability, 可靠性! r& R* c* A- K% M: d: f
Reparametrization, 重新设置参数
+ O- q0 ]6 Z+ I+ I" MReplication, 重复% R: P* g1 A/ L! g8 C) f, s
Report Summaries, 报告摘要" `; f5 l+ L+ ]3 `- F* D; m: R
Residual sum of square, 剩余平方和
6 a; I# N4 L0 m1 Z6 b, p5 y1 g! `Resistance, 耐抗性
& f v; ] Q1 o2 kResistant line, 耐抗线7 P- B5 B) z, P X
Resistant technique, 耐抗技术5 X( S( Z' k4 h( `
R-estimator of location, 位置R估计量
' }% E, J; _$ e; Q0 Q: P, fR-estimator of scale, 尺度R估计量
/ e# Z p S! a k/ v3 L9 `5 g. sRetrospective study, 回顾性调查
! u" M# B. Q+ ~" l/ _! w. _Ridge trace, 岭迹( ~3 K) d* O% g* w
Ridit analysis, Ridit分析6 Q& `/ u3 O+ T1 U- ?
Rotation, 旋转- `5 E4 G; ^; @; _" \% S
Rounding, 舍入# H1 q, a' T2 r8 S
Row, 行
3 s( L3 l0 I+ g: ERow effects, 行效应
, t+ ?+ D2 Y- J: E/ ~Row factor, 行因素
4 ^; I3 w2 c# a$ `) f# k i+ NRXC table, RXC表% F6 @4 Z. h$ S+ u5 O# A
Sample, 样本
7 `8 n& M! _- f% d9 ~Sample regression coefficient, 样本回归系数
& }7 a) e! J! ~+ q" _" Y' {) BSample size, 样本量* ~/ Y9 `1 ?: B' p3 m" t
Sample standard deviation, 样本标准差
& k% t& d" `+ P' c6 Z7 `Sampling error, 抽样误差
: ~( q; D5 Q7 A5 A" i% cSAS(Statistical analysis system ), SAS统计软件包- {7 R# p% U! u7 k
Scale, 尺度/量表
5 X, J! ?1 [. v7 u- t' a$ U. a& k. MScatter diagram, 散点图$ t! D* X v, P/ f
Schematic plot, 示意图/简图
; G2 m0 l2 B7 r0 X uScore test, 计分检验
0 B5 b4 \1 `% f0 |2 m3 T) VScreening, 筛检2 ~5 [1 _: s1 o0 ?
SEASON, 季节分析
) l& V( F1 ]9 QSecond derivative, 二阶导数' {1 j' n( ?$ h. f4 }. p8 r3 y+ v
Second principal component, 第二主成分6 t5 }, E! z# T& R8 v, w
SEM (Structural equation modeling), 结构化方程模型 A7 X0 k9 w! h3 g2 ?
Semi-logarithmic graph, 半对数图2 A( }: u5 e' d' K
Semi-logarithmic paper, 半对数格纸
7 k g$ z. ^" R+ |6 t4 e# ZSensitivity curve, 敏感度曲线" ]3 b; J: s1 [3 e+ n
Sequential analysis, 贯序分析: W! W8 s! P6 D3 }* b+ |8 I
Sequential data set, 顺序数据集% @. m4 C+ g! y) ^& \; \4 T' @; X
Sequential design, 贯序设计 i$ n" q( n/ J- ^( D" u+ @
Sequential method, 贯序法
/ c7 p4 [$ n7 _9 x- X q4 wSequential test, 贯序检验法* Y& D3 x4 K; D* e' W
Serial tests, 系列试验/ I' f0 U5 [9 c& C, z+ h! M
Short-cut method, 简捷法
4 I$ V: N( n0 g* N- HSigmoid curve, S形曲线
: C9 y' o' J9 R2 uSign function, 正负号函数, p. ^' D' ]: J2 g" w/ c% G
Sign test, 符号检验9 S/ f) f( {$ m E5 H
Signed rank, 符号秩) H. I3 k+ k# s. O$ j1 [0 `6 S
Significance test, 显著性检验
6 J) p9 e! m6 ESignificant figure, 有效数字7 K' W; W( t0 U" N9 h9 p x
Simple cluster sampling, 简单整群抽样
3 Q: I8 W$ ]+ ^$ _4 i+ l4 qSimple correlation, 简单相关
. W$ G% s; p- e' @2 V8 PSimple random sampling, 简单随机抽样8 ?* i3 V8 F: A$ y
Simple regression, 简单回归
8 ]5 p6 `4 l" p9 z# o! }simple table, 简单表
, ?. X [! c7 K5 ?! lSine estimator, 正弦估计量
; N+ }, W. J) U# QSingle-valued estimate, 单值估计
3 P3 b1 Z$ H- y! m# a5 _4 i6 P; ZSingular matrix, 奇异矩阵; {! Y- s& k; ~& E
Skewed distribution, 偏斜分布
2 W; ]3 Z+ ^' Q1 A4 W# x3 O% ESkewness, 偏度
6 _7 ~, G2 _9 ]) b6 w* c, mSlash distribution, 斜线分布
5 c2 x2 r9 }: U% {9 k' S+ kSlope, 斜率4 A- `5 m0 h1 m, ^
Smirnov test, 斯米尔诺夫检验2 B9 v1 w3 L& x6 \
Source of variation, 变异来源
3 r2 K2 A- }: hSpearman rank correlation, 斯皮尔曼等级相关
$ B1 {) d0 L9 k: l8 u- b" qSpecific factor, 特殊因子. o8 q. g* }' |! ], Y# y: g
Specific factor variance, 特殊因子方差
8 L) F$ ?- a$ U$ }; iSpectra , 频谱
/ E ?" L- |& ^3 O8 d+ S, e6 \( ZSpherical distribution, 球型正态分布# t$ H1 ^! M& e9 W
Spread, 展布4 P; \ j& Y1 p% _/ I4 z
SPSS(Statistical package for the social science), SPSS统计软件包; i( X( ?5 ~6 X! W& i) x
Spurious correlation, 假性相关, A' N3 s3 h! Z8 O" @5 l0 ^% g
Square root transformation, 平方根变换
2 I; g7 w% K' C+ RStabilizing variance, 稳定方差6 b, _3 A! [# N
Standard deviation, 标准差2 a4 z* `9 E' a
Standard error, 标准误! a" N0 w* A1 [( K# g! x' Z
Standard error of difference, 差别的标准误3 \$ c1 @ @0 b9 X+ S* X5 |
Standard error of estimate, 标准估计误差
* P4 g9 o2 P5 e) E% OStandard error of rate, 率的标准误' j# v+ ^! E8 e1 \0 s' |
Standard normal distribution, 标准正态分布5 W6 f* F7 O) f* ^$ f
Standardization, 标准化( D N- @2 R$ m- Q$ O
Starting value, 起始值
' e2 J6 A4 ?; pStatistic, 统计量& d8 `0 Q3 g8 A. I0 r3 R
Statistical control, 统计控制% V. i; ~! j4 X S- a3 i$ k
Statistical graph, 统计图
% R0 Z& Q+ c- ?2 Q5 Y. ?3 \8 W- CStatistical inference, 统计推断
7 s7 U, B9 K4 YStatistical table, 统计表
) F1 i) K# q8 m- W, s: ]1 O0 |Steepest descent, 最速下降法0 |. ~) `3 Y0 u5 ^
Stem and leaf display, 茎叶图
1 V3 s& Y2 p0 f- k" P6 KStep factor, 步长因子8 o6 k/ f3 ~0 g, w
Stepwise regression, 逐步回归7 u5 `* U; O1 F
Storage, 存
) J0 H$ V/ ?; U _% yStrata, 层（复数）$ B. [. Y- l: H0 F7 w# I3 g
Stratified sampling, 分层抽样, S. w+ ^5 |0 W" s/ h
Stratified sampling, 分层抽样$ O# G) d# a+ m3 s) B& {
Strength, 强度7 c# _# T# z M( d' y! ]9 R( E
Stringency, 严密性' `' I. ?3 {6 |
Structural relationship, 结构关系
& e! s8 C6 g( {' ZStudentized residual, 学生化残差/t化残差
4 b& V T2 E% zSub-class numbers, 次级组含量
: G+ L2 s+ G! j( i8 n& g5 I5 RSubdividing, 分割; |* O: N: e- m
Sufficient statistic, 充分统计量
\/ l; x7 M8 @% n8 oSum of products, 积和( t5 e7 [' o1 T' J: j$ L
Sum of squares, 离差平方和
" f0 l# u1 t4 J) Q L- ISum of squares about regression, 回归平方和
; k" C* }7 R- N0 K: k: BSum of squares between groups, 组间平方和- S3 Z# ^0 Z7 Y) h
Sum of squares of partial regression, 偏回归平方和
: U7 \" G, Z6 sSure event, 必然事件 W' P9 O! A" y) A8 a
Survey, 调查/ G4 c" O& p; i, f8 b; Z
Survival, 生存分析3 q9 A7 `$ c/ @& V6 Q, N- J
Survival rate, 生存率
) W$ _3 ?! _ W# q, |Suspended root gram, 悬吊根图
: `4 l2 E' m- @0 R& i9 tSymmetry, 对称
( `2 C, g. u# sSystematic error, 系统误差
u0 M b2 A: iSystematic sampling, 系统抽样8 u% H% S; `' q: d. M# p c. ~: Q
Tags, 标签
8 t( S, x: K g# s9 x9 p2 j: rTail area, 尾部面积
9 K. S4 w" r/ o& E1 hTail length, 尾长
8 I5 ^+ Z1 N9 ?: z' R; _/ iTail weight, 尾重) P7 G9 I7 e4 d
Tangent line, 切线
0 t/ H. z, N# h2 @. c% R0 U' ETarget distribution, 目标分布
* N; b+ G' ` ^7 cTaylor series, 泰勒级数" k/ S" G) K( x2 j% F! v
Tendency of dispersion, 离散趋势) Z# M0 Q) }5 J7 O' v3 L+ ?
Testing of hypotheses, 假设检验8 C0 b, g' u/ l
Theoretical frequency, 理论频数
9 r5 ^3 ?5 C! n- ?. Z% UTime series, 时间序列
! D) S: @& N: c" a7 STolerance interval, 容忍区间
: G! m4 {% X6 q" ?6 i+ DTolerance lower limit, 容忍下限" \5 e% T+ j. Z* `2 g$ R
Tolerance upper limit, 容忍上限: C' c, Q! W k9 z+ ~
Torsion, 扰率, t; G" y+ K" Y) H! }; A
Total sum of square, 总平方和" H, U. ~1 H. c: U" C1 n& v+ g
Total variation, 总变异
! ~' I4 y/ m% r, f v2 LTransformation, 转换/ E/ S& a; G& O, V* M G
Treatment, 处理, A1 m0 t0 i; d; \
Trend, 趋势
2 q; m( g8 ?' f5 BTrend of percentage, 百分比趋势
5 O( [3 a9 M+ S; W- fTrial, 试验
( b0 W* F* ^( ^5 UTrial and error method, 试错法! j, }* ^2 q7 [6 {; j' I
Tuning constant, 细调常数
" n0 \' [% H" }. mTwo sided test, 双向检验
: n) s2 o( \8 ]4 PTwo-stage least squares, 二阶最小平方" N! U1 h4 Q: o' w5 p/ A8 o
Two-stage sampling, 二阶段抽样; f i3 L" \0 s) o+ X. g
Two-tailed test, 双侧检验
8 B0 Y; V( h8 ZTwo-way analysis of variance, 双因素方差分析9 w& j5 P4 z, ` j' I
Two-way table, 双向表8 D R" s9 s3 r7 _" H d& ?
Type I error, 一类错误/α错误' M u; _: m: P6 `
Type II error, 二类错误/β错误! i" ]: r" n) _% Z! i9 z8 k& a6 r
UMVU, 方差一致最小无偏估计简称7 P. f8 G! U- s6 o
Unbiased estimate, 无偏估计7 a5 k) _$ D3 W1 j" ~" Z6 T# z( t
Unconstrained nonlinear regression , 无约束非线性回归8 L8 j- `0 k; _1 T6 h. d
Unequal subclass number, 不等次级组含量
) s. W' D0 u* B. d# LUngrouped data, 不分组资料
- T# ?* [5 W l% WUniform coordinate, 均匀坐标
+ I! _, C) c; MUniform distribution, 均匀分布. \7 x# E+ p2 y. K1 U
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
& l/ k3 t% W# L2 o* x/ S9 TUnit, 单元" z& W. o7 S2 {8 c& M
Unordered categories, 无序分类
1 J8 q2 h" y- v* T8 kUpper limit, 上限2 B8 f) K- k" P! Y) B' W
Upward rank, 升秩
. F8 y0 V) Z' F5 v, G0 qVague concept, 模糊概念* P4 U& I( V: j
Validity, 有效性6 u6 g* I H! W8 _! {
VARCOMP (Variance component estimation), 方差元素估计
4 R2 M! r( v$ z# p9 N0 MVariability, 变异性( Y: Z& h0 i! z0 W' b! l9 D
Variable, 变量
# W8 s F* i) r# j6 bVariance, 方差
3 Q0 E7 d+ }" N# e" G' bVariation, 变异+ z- V/ i5 x* J4 z2 Y$ k/ z
Varimax orthogonal rotation, 方差最大正交旋转
# e4 g2 z" Y# E2 G& d' L+ FVolume of distribution, 容积# A. o& i4 j) o2 D, J$ u1 ?1 J0 \
W test, W检验& V& x/ ^( ^5 d k
Weibull distribution, 威布尔分布
4 z0 |& Q5 p+ j/ XWeight, 权数
! ^4 o; H* e; \Weighted Chi-square test, 加权卡方检验/Cochran检验. ?6 j( U) g8 L1 `$ K
Weighted linear regression method, 加权直线回归; c$ }' Z; s. A; @
Weighted mean, 加权平均数
+ P* E+ D7 g/ I8 U7 lWeighted mean square, 加权平均方差/ G( O, g+ a0 L" a* ?. ?8 e
Weighted sum of square, 加权平方和
* K5 {' n/ v1 Y7 i' j1 a2 o/ a0 sWeighting coefficient, 权重系数% U9 b1 a/ B; {( X0 y2 O6 b
Weighting method, 加权法
1 _# X! ?& o5 |% e3 N, XW-estimation, W估计量8 a% z! v/ v+ e
W-estimation of location, 位置W估计量
3 a8 f: ^2 T' U8 v" JWidth, 宽度. u) l' x$ D, R4 c! b' |( V
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验5 b: o% D5 p7 r- ?# T9 B
Wild point, 野点/狂点
) ~: Z4 S4 z5 F! m; x8 V& _Wild value, 野值/狂值
3 @( p. ~; r2 c& ?9 }Winsorized mean, 缩尾均值
7 a% j4 M+ ~2 Q, ]Withdraw, 失访
6 v1 J; B) H3 D; s. zYouden's index, 尤登指数
- f! @2 I# F! j" J4 {Z test, Z检验+ D5 y- S% r4 d$ {& e6 r8 F
Zero correlation, 零相关
' d% c4 B7 R- Z, iZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
