|
|
Absolute deviation, 绝对离差
6 z" p- M8 U" n' ^Absolute number, 绝对数
' e) k2 y, K3 \: x1 n1 CAbsolute residuals, 绝对残差3 A/ x2 |: S2 ~& B; v+ k
Acceleration array, 加速度立体阵
7 W o G e- cAcceleration in an arbitrary direction, 任意方向上的加速度2 {) }; |0 s: r% O6 T- J
Acceleration normal, 法向加速度6 n" u. F: a4 y# X B2 i
Acceleration space dimension, 加速度空间的维数8 f- s8 ~. p2 j. ]% x- p
Acceleration tangential, 切向加速度& b" |; w' C8 E+ R, z* A+ p- a
Acceleration vector, 加速度向量
0 \ P8 `8 j3 T. a( X* RAcceptable hypothesis, 可接受假设% a0 j7 F: ~& h! S. h! {
Accumulation, 累积
" W" ~7 c) p- A9 S( QAccuracy, 准确度
+ k" u) ~) ]0 `+ l w$ g& i' J. d+ lActual frequency, 实际频数 X& q% X6 I- i ?' `4 O
Adaptive estimator, 自适应估计量! j* j; `9 d( v
Addition, 相加; t2 n/ X# g9 s0 V8 k
Addition theorem, 加法定理3 [+ c1 t) C! l( {
Additivity, 可加性
( L) S* s% ]1 K/ |Adjusted rate, 调整率* l6 Z0 c1 C3 j! ^$ N r
Adjusted value, 校正值5 r1 P( i! G% t7 t* ~- o. E. V$ c
Admissible error, 容许误差3 p# E( S+ Q* x7 b
Aggregation, 聚集性' \% H9 F; M2 p+ @) \
Alternative hypothesis, 备择假设
- f2 A5 B! ^& P1 i# {% M3 X8 iAmong groups, 组间2 a% t; Y7 f, E' M$ x5 w; b
Amounts, 总量( d5 u J# s _- P: [3 _8 \; u
Analysis of correlation, 相关分析
" h# M9 u# ?" x) IAnalysis of covariance, 协方差分析
8 S/ E$ n$ @2 l3 j3 c& hAnalysis of regression, 回归分析
; k" p& T: j$ f* h8 ?% BAnalysis of time series, 时间序列分析
M& b& F6 H7 {2 x. ?1 RAnalysis of variance, 方差分析
: Q+ e. F8 C* HAngular transformation, 角转换- \9 i# B+ A l+ Y- U M
ANOVA （analysis of variance）, 方差分析 [9 } c; |) N8 Y. f
ANOVA Models, 方差分析模型# i: b3 P. ~4 J1 f6 A
Arcing, 弧/弧旋$ h4 u0 z6 H5 U6 f+ a, i! B0 j
Arcsine transformation, 反正弦变换
) k& A1 s+ d4 M$ PArea under the curve, 曲线面积
t# |% n# d9 D! AAREG , 评估从一个时间点到下一个时间点回归相关时的误差
t; l' D% x( ~# BARIMA, 季节和非季节性单变量模型的极大似然估计 ' S) m' U; M. c
Arithmetic grid paper, 算术格纸4 q8 W: J( g9 ^, K
Arithmetic mean, 算术平均数
1 n9 t/ B0 ^% T( mArrhenius relation, 艾恩尼斯关系
" n- Q! g+ I6 ?$ r" l5 }Assessing fit, 拟合的评估
4 x# S k: o5 K, M7 f3 FAssociative laws, 结合律9 C; e% b4 q9 t6 \
Asymmetric distribution, 非对称分布
) b: N" n: H: BAsymptotic bias, 渐近偏倚
; m' | r6 H P SAsymptotic efficiency, 渐近效率
) l( F2 Q2 Q% l! d2 V+ g tAsymptotic variance, 渐近方差
& u3 ^! g# p0 i8 _- y9 |Attributable risk, 归因危险度( V1 W9 N7 k `% H% j* [: Q
Attribute data, 属性资料' ^0 t2 K6 q3 t! u/ G9 L/ s* [
Attribution, 属性5 W0 b( {/ A, T( e U
Autocorrelation, 自相关, h+ a' E/ Y" z3 x5 E$ H. W
Autocorrelation of residuals, 残差的自相关6 V( j* F' A) {) ]6 U! `3 O
Average, 平均数 S4 }6 P+ L3 l: S5 V- ~
Average confidence interval length, 平均置信区间长度2 ~; D0 i- Z" X% i) Y" R
Average growth rate, 平均增长率! k# @9 w4 {! `, `" h
Bar chart, 条形图" X. s5 q8 F5 K% l3 T
Bar graph, 条形图# j1 y& v: y. d5 B/ u, R+ O
Base period, 基期+ k9 `, `5 G6 O; ~: e# I* ?' H& b
Bayes' theorem , Bayes定理% ?% R4 u2 ?' w% n8 T
Bell-shaped curve, 钟形曲线" T6 F# ?7 Q0 i/ H
Bernoulli distribution, 伯努力分布
! `- K R) ]4 Z+ Z* l8 k0 [Best-trim estimator, 最好切尾估计量: e# P9 w; r8 |, M6 @) u c% Y
Bias, 偏性
1 l) q7 f& w2 d' qBinary logistic regression, 二元逻辑斯蒂回归- m" v9 j# L- A( ~% _( R1 t4 ]
Binomial distribution, 二项分布
& [. y1 ^! ]/ q2 a2 g# gBisquare, 双平方5 j5 I% b7 i1 X
Bivariate Correlate, 二变量相关
% l8 J {7 V% l& CBivariate normal distribution, 双变量正态分布
* s; U. I6 R- ?Bivariate normal population, 双变量正态总体& G& C4 a! ~ l7 x0 c! V- d
Biweight interval, 双权区间
. D; U% y- g- y$ g+ }6 gBiweight M-estimator, 双权M估计量
3 }; J0 N3 N1 KBlock, 区组/配伍组' f$ J ?# P( o1 r r% K8 s
BMDP(Biomedical computer programs), BMDP统计软件包1 `) V2 f5 l; @# k% O/ n
Boxplots, 箱线图/箱尾图& l% B( g& m+ D- F Z: u
Breakdown bound, 崩溃界/崩溃点
. p5 `8 `5 A$ Y! ?Canonical correlation, 典型相关4 c4 [# r# e6 m+ L
Caption, 纵标目/ t6 j1 \4 Z; C R9 V" X& T2 p; M
Case-control study, 病例对照研究) O' P: i( E1 L4 {
Categorical variable, 分类变量
+ \$ K+ g8 @& Y3 lCatenary, 悬链线5 Q3 A1 a: x; z; f, C$ ]( ?# a
Cauchy distribution, 柯西分布
. F" u; c2 {) e; U/ W' u! s" jCause-and-effect relationship, 因果关系
4 H2 w# b' | B' \1 JCell, 单元
' P+ C# X* F. _Censoring, 终检4 Z: p: ?( s* a6 b! T
Center of symmetry, 对称中心# B% i$ F2 r; [' J" h
Centering and scaling, 中心化和定标0 u+ t; r( j N w7 C. y
Central tendency, 集中趋势
+ [! V" _ n9 @) ECentral value, 中心值/ a: C' H2 B' w1 ^* i7 u9 b/ E$ p
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测( Z1 N! O& o( c) Y0 J' ^
Chance, 机遇
0 ^$ |) d1 f6 X! I$ xChance error, 随机误差
) o4 v' {5 w' N3 oChance variable, 随机变量
3 V1 ]: d% l+ ?Characteristic equation, 特征方程
+ a* |0 f2 \' X {4 C& eCharacteristic root, 特征根$ R2 r4 q# q: c$ S' [5 t& I: {
Characteristic vector, 特征向量
2 ^! m+ D1 i1 q+ t4 D7 ?3 iChebshev criterion of fit, 拟合的切比雪夫准则
; g0 S. O3 ?- U4 m! K9 `Chernoff faces, 切尔诺夫脸谱图
1 Z, O% l- q6 e$ }3 ?* ]% j5 YChi-square test, 卡方检验/χ2检验
# K9 e& P9 N2 o4 f" c# LCholeskey decomposition, 乔洛斯基分解
x' t5 v( h% jCircle chart, 圆图 6 n, k1 z! a$ G q7 J, j) V
Class interval, 组距
' {: Y) L8 |# PClass mid-value, 组中值 P4 S3 e5 ?. Z( t! s
Class upper limit, 组上限- z1 ^" `- e) I! {$ r7 i; d1 D7 l
Classified variable, 分类变量3 {! K/ Q# `. k9 i, v) w6 c
Cluster analysis, 聚类分析: k; H1 O$ V; O+ x7 u O
Cluster sampling, 整群抽样! `" X7 d5 j- e6 U
Code, 代码
1 x+ t5 {; ?6 t' ECoded data, 编码数据
3 @# P2 w' r- L4 K h0 {Coding, 编码4 M. f3 Y. }6 B4 p: y* p* S
Coefficient of contingency, 列联系数$ W+ Y5 ^% i% C4 |+ r
Coefficient of determination, 决定系数5 V5 I- l* \7 a# ]/ Z, E3 S# \
Coefficient of multiple correlation, 多重相关系数
& Q; v6 F# p0 x I# A4 XCoefficient of partial correlation, 偏相关系数
' W7 k$ }) K! c! l2 xCoefficient of production-moment correlation, 积差相关系数2 V. X$ }' P9 v- x
Coefficient of rank correlation, 等级相关系数/ O) O' w& a; ~; z2 {
Coefficient of regression, 回归系数+ }2 |( H5 O1 h7 r
Coefficient of skewness, 偏度系数5 T8 ~! P, Y+ I
Coefficient of variation, 变异系数, s/ _7 H3 V, N' R. }7 f
Cohort study, 队列研究9 m" A# D! r) U1 k$ M1 W
Column, 列- E' ]4 V% c/ M5 o3 A7 d+ K4 d& _0 l
Column effect, 列效应8 Q# a+ K' b( [& C7 a* p+ h
Column factor, 列因素; F# A1 \7 j2 B' ?/ [
Combination pool, 合并6 b# H4 Y! \, ?% a" e' O$ F' x5 r
Combinative table, 组合表( `) R7 G6 T) M! |9 I
Common factor, 共性因子
/ a3 J1 \) `: ~1 {4 ]- ~. bCommon regression coefficient, 公共回归系数
, f. A! z! K( _% B! WCommon value, 共同值% k9 o3 ^- K9 e9 k1 E- U
Common variance, 公共方差
8 m; o5 x* K6 O7 L! |' }! xCommon variation, 公共变异 o+ {2 \9 Q5 C* k: F- Z' ]5 `
Communality variance, 共性方差! R% p6 N( V5 m+ J
Comparability, 可比性. U! {2 H0 D) y- |/ m
Comparison of bathes, 批比较
8 a- w1 J8 ^8 @Comparison value, 比较值* U( d& |% a s' i8 k2 T
Compartment model, 分部模型
) r: Y& B% f. eCompassion, 伸缩- p3 b+ ]5 M7 d, o6 m$ O
Complement of an event, 补事件5 W- V5 a) s6 P
Complete association, 完全正相关7 e: b( |1 N; M! q0 |8 s. \* y6 j
Complete dissociation, 完全不相关
4 S4 z0 e4 }' P8 P. NComplete statistics, 完备统计量$ H& P- N3 H/ ]( b% T/ I/ I: k# u' E
Completely randomized design, 完全随机化设计
2 e: B( U, Z UComposite event, 联合事件5 ?% F& d4 c# H+ r
Composite events, 复合事件. m1 I$ Q0 v/ I0 v; D5 k9 h
Concavity, 凹性
. m) o! Y9 O- O" U. x2 qConditional expectation, 条件期望1 }) E9 F1 V8 X0 S
Conditional likelihood, 条件似然9 A: V/ P& n1 h* B" ]( w
Conditional probability, 条件概率4 G7 o/ e/ c0 S- K3 V3 m
Conditionally linear, 依条件线性
4 w; d Y0 \% O6 GConfidence interval, 置信区间
V8 L7 Q0 _. y! ?" O# b CConfidence limit, 置信限7 s9 x* R* C" R
Confidence lower limit, 置信下限$ E' \9 n K+ g1 \0 w& _4 O* f' `' B
Confidence upper limit, 置信上限7 P: }' k% R! S9 Y' b9 S2 x
Confirmatory Factor Analysis , 验证性因子分析
; z. O1 \( H6 ~Confirmatory research, 证实性实验研究6 K" {- T' [5 H, z. m9 o" P
Confounding factor, 混杂因素
+ H" ?, R9 }* F0 X9 { ?& }Conjoint, 联合分析* f$ \; q, A- m
Consistency, 相合性
. o ^" Z- [, Z0 Q9 @, yConsistency check, 一致性检验( i2 Q& f+ Z: E# f, ?% ~
Consistent asymptotically normal estimate, 相合渐近正态估计" I+ O# g' s% E# | L
Consistent estimate, 相合估计2 Z3 y& H. `$ O) \5 G3 j# N8 Z7 e
Constrained nonlinear regression, 受约束非线性回归
+ z+ M0 W4 e' M8 K' SConstraint, 约束
- B% C. o! M2 TContaminated distribution, 污染分布- l$ n: A' D5 v
Contaminated Gausssian, 污染高斯分布, J+ D: S" Q+ h/ p0 w8 x
Contaminated normal distribution, 污染正态分布
2 o, n1 V! l) O4 b) ?% xContamination, 污染
; T5 n1 |% y2 v' jContamination model, 污染模型
4 ^2 |* a2 X5 H* _Contingency table, 列联表
5 {% [6 q" v, V. R9 gContour, 边界线
3 Q( X" u7 n7 fContribution rate, 贡献率
3 }5 ^, X0 F. ~/ S; d6 vControl, 对照: a1 u6 l5 x) f! a x
Controlled experiments, 对照实验) Q7 M* {& R: `: Z9 G
Conventional depth, 常规深度
4 z( Y' B# G+ r( o, f' `' y" }2 u: BConvolution, 卷积0 w% k; P+ F! j+ \
Corrected factor, 校正因子5 u4 Z G+ _/ D/ l6 T
Corrected mean, 校正均值0 i) |' S; S2 s9 r) u/ C# K
Correction coefficient, 校正系数: V- S7 \' J: e! j0 Y |! o/ H
Correctness, 正确性( C( a2 X, J# E7 p2 _% ]
Correlation coefficient, 相关系数
# N5 p# c3 e- r- @Correlation index, 相关指数2 `( }" q/ C, M. F {# d- ]& T
Correspondence, 对应+ v+ l" V$ a; V
Counting, 计数4 ^" O. m# ^, i% {- O7 ]
Counts, 计数/频数# S# C" u3 o4 Z7 q" u% c
Covariance, 协方差
]$ R* T- O4 G+ _5 {Covariant, 共变
, x6 B8 t" Z# ~- NCox Regression, Cox回归" s* a8 b5 P Q ^8 v |) F
Criteria for fitting, 拟合准则
) ?; M; {: A! w" s$ m0 ]: aCriteria of least squares, 最小二乘准则# K! A; T, Z$ ?% r6 c k" @
Critical ratio, 临界比
# f" I& e7 `% ]% I% E7 \( q a1 K% Z, a NCritical region, 拒绝域: _# W+ D& W6 F3 S' \
Critical value, 临界值5 B! T- g5 H, z9 a+ b/ b- R* p
Cross-over design, 交叉设计
7 D( G+ v) T6 _& U/ tCross-section analysis, 横断面分析
5 g! v6 Q' h; T$ F6 N* XCross-section survey, 横断面调查
7 N% g9 a7 R0 M3 R# TCrosstabs , 交叉表
, B/ S6 c/ y, w3 Q2 M; yCross-tabulation table, 复合表
& p" H( i! ]8 [3 M1 BCube root, 立方根# ~! X4 i5 a- E5 W1 l
Cumulative distribution function, 分布函数3 Y* |$ W( R3 Q9 H
Cumulative probability, 累计概率
4 Z6 \3 n0 m3 c3 F+ @Curvature, 曲率/弯曲/ V: {0 w3 N5 p$ r$ Z# a
Curvature, 曲率) N. ^! c4 E8 c
Curve fit , 曲线拟和 . ~+ k0 E7 l5 p% k0 I
Curve fitting, 曲线拟合: C: z2 y$ M9 S) N3 ?% N2 w
Curvilinear regression, 曲线回归
5 t+ S: J; }2 cCurvilinear relation, 曲线关系: V6 o5 d$ e/ X" Y+ ~0 W
Cut-and-try method, 尝试法
' |0 ]$ C5 a* O! d1 d# o1 PCycle, 周期* K& H! }$ z. V9 S. a
Cyclist, 周期性! j u. K, t) M( _
D test, D检验5 W7 [8 U) R" x4 J
Data acquisition, 资料收集$ s7 k+ x6 x( a5 H) g
Data bank, 数据库
& n0 H/ Q4 {( M7 Z5 L7 p2 O, pData capacity, 数据容量3 m* I1 x" Y1 U* t0 c7 ~+ O$ A# ?% M
Data deficiencies, 数据缺乏
' \/ M5 x" `. \& V% B3 @ @Data handling, 数据处理2 B( S1 m# k( L
Data manipulation, 数据处理$ }" C. z3 J, S$ n# _
Data processing, 数据处理4 V$ h O* [9 D
Data reduction, 数据缩减9 W5 ?/ U! O: ?9 Q" U
Data set, 数据集
2 o8 s/ D6 a4 a, tData sources, 数据来源1 Z% j$ I. b5 f: P& @
Data transformation, 数据变换
9 {: J, c2 d' c' h& pData validity, 数据有效性, Q4 u1 Q% h0 b# k1 W
Data-in, 数据输入; Q- d+ c& e) P
Data-out, 数据输出
! T4 L5 { ~. Q* z' IDead time, 停滞期! E0 C9 N4 M. f6 c/ x" X
Degree of freedom, 自由度/ v' o1 t, S; h _& {0 q
Degree of precision, 精密度
8 N0 Y7 K4 J" u' YDegree of reliability, 可靠性程度; e) i5 g$ y! d8 |7 C: y" _
Degression, 递减
4 E' j$ F1 d+ B, g. U# ]9 E' k3 fDensity function, 密度函数
+ `2 I# v& s, G# ?/ p4 \) ODensity of data points, 数据点的密度. |$ Q& X8 ?( M7 G: J
Dependent variable, 应变量/依变量/因变量# H" t( I& N) Q6 C+ f5 Z
Dependent variable, 因变量7 U8 @6 |/ |- F, j, N. T
Depth, 深度# J* [$ j3 m+ D+ \* ^
Derivative matrix, 导数矩阵
+ ^- c% Q; I' t6 kDerivative-free methods, 无导数方法
0 K/ F1 j u/ c9 q9 z9 X6 @Design, 设计: ^1 X8 u6 H2 A2 J- Q
Determinacy, 确定性# | d- V% a7 Y! d- S3 j
Determinant, 行列式
m, h! d" I; R0 V7 oDeterminant, 决定因素( Q: E6 I+ @4 ?' p3 G D$ k. |" B
Deviation, 离差! T$ j9 T3 n- S+ ^% e# F
Deviation from average, 离均差
5 E9 C8 l5 X9 F' D3 G1 {Diagnostic plot, 诊断图
8 b* O1 _' i( S; e4 @8 YDichotomous variable, 二分变量" E0 o. k. I' |0 K& R' r! F! a2 C/ X+ W
Differential equation, 微分方程
* Y" ?7 _1 A4 M( B+ T, kDirect standardization, 直接标准化法
% ^' W4 f( Q+ k6 f4 ^Discrete variable, 离散型变量
- W2 ?" g& N& K( A4 NDISCRIMINANT, 判断
+ y$ o) \' x6 UDiscriminant analysis, 判别分析
2 R P# C0 r: I: A: \Discriminant coefficient, 判别系数
+ b) P0 Z! P) j! pDiscriminant function, 判别值
$ h1 X" y4 e0 \Dispersion, 散布/分散度
2 C8 Z0 u' c) s; X4 l4 tDisproportional, 不成比例的8 Q5 s* U7 ]6 r+ X: D
Disproportionate sub-class numbers, 不成比例次级组含量
1 K# C1 N; g: G2 DDistribution free, 分布无关性/免分布1 D" j1 z7 U7 R5 X. d7 h/ O4 a, x
Distribution shape, 分布形状" K' C8 Y/ u: [5 e
Distribution-free method, 任意分布法
+ d0 u. g5 P: m' S! S. \5 E5 M* wDistributive laws, 分配律
+ _% a3 v8 j- }0 s2 K. m) BDisturbance, 随机扰动项' Z6 P' D( I" v, @7 k; J7 `; I
Dose response curve, 剂量反应曲线
* R, v5 s% ~3 h p( h, r/ T& Y oDouble blind method, 双盲法" Z6 w4 o% Z% o! @, b7 I, y# a: O
Double blind trial, 双盲试验' I! M( X* l' a5 o# K1 J7 O
Double exponential distribution, 双指数分布
0 a2 j4 [2 _% `Double logarithmic, 双对数3 g" I- C# n' |0 G: {
Downward rank, 降秩
$ B, d9 Y3 Z, {1 }Dual-space plot, 对偶空间图
) w, [0 ]2 {" Y# V: p; e1 QDUD, 无导数方法
( g5 ]* y$ M! I# U S# KDuncan's new multiple range method, 新复极差法/Duncan新法. U0 M" \ b) P
Effect, 实验效应
3 z9 Y# x* t; q+ [0 zEigenvalue, 特征值
) i7 g& @, B4 m& C2 ^8 SEigenvector, 特征向量9 ~+ K$ P& A0 v$ m3 O' a& a0 O M0 O) ~
Ellipse, 椭圆" c$ i3 d' t9 p' O2 L" n. Y
Empirical distribution, 经验分布+ J7 J0 q" J0 X
Empirical probability, 经验概率单位
8 m% C" r) ^& E2 K4 C0 U. `Enumeration data, 计数资料& s: s. G1 W; y* J( x% k. j
Equal sun-class number, 相等次级组含量4 P: | ]% x6 P( A$ `
Equally likely, 等可能
6 I. f% Y% A( x ^. Y" r; SEquivariance, 同变性, Q( W0 t- Q, f+ T5 E5 D* k" C+ X3 X
Error, 误差/错误7 N9 i% [+ x6 R+ S
Error of estimate, 估计误差
1 e8 O/ w2 i) E5 Z, A' b8 d1 oError type I, 第一类错误; t) w4 s( _6 i; ~) m* J& _
Error type II, 第二类错误5 Y& m: {6 V+ h
Estimand, 被估量2 F. T0 P/ ^" q: @6 k2 R# U6 q
Estimated error mean squares, 估计误差均方/ W2 m- r+ ?8 l- G% Z2 L0 u
Estimated error sum of squares, 估计误差平方和6 l, A; L* C; i2 `4 b4 L
Euclidean distance, 欧式距离
( T9 g# ~( e; i1 }* L& @Event, 事件
! C9 Y$ x, d" R( d2 w$ MEvent, 事件
! G1 B6 Q3 {5 f% o* f$ u' vExceptional data point, 异常数据点! X( h- O/ m: m g; I1 d6 {
Expectation plane, 期望平面' b# H4 Y% F9 c6 ?; V! V% v
Expectation surface, 期望曲面
" D; K0 A4 p( U: U! ^Expected values, 期望值
" W0 M' \4 Y, C2 wExperiment, 实验6 J% t% M$ T1 s
Experimental sampling, 试验抽样
9 Y; ~( m' |2 I1 }8 HExperimental unit, 试验单位
9 l4 C! ]$ ^* v5 V: S: ZExplanatory variable, 说明变量5 d/ s! h2 Z; z* s- D( i/ d
Exploratory data analysis, 探索性数据分析' n7 O2 P. y& ?, Q) h1 j
Explore Summarize, 探索-摘要2 ~; n) T( X% l& u
Exponential curve, 指数曲线- ~4 T Z* ?% ]# t. B
Exponential growth, 指数式增长
, V% k1 }, x* Q' ]7 R& {EXSMOOTH, 指数平滑方法 ! F! g+ k1 z/ z6 b* u) O
Extended fit, 扩充拟合5 C: S/ W5 T0 ^/ [- |
Extra parameter, 附加参数1 M4 `8 A& e- S- G
Extrapolation, 外推法* V8 J U" e6 e W( U+ e
Extreme observation, 末端观测值5 {, `+ E3 ~0 G9 V+ Z
Extremes, 极端值/极值
1 S' x8 P: o. w1 }- jF distribution, F分布2 D$ [' V B# \0 ]8 k
F test, F检验3 h2 Z3 q( q: p
Factor, 因素/因子6 b0 B) d3 j& G. @; M
Factor analysis, 因子分析
, R$ f M' Z6 ?1 CFactor Analysis, 因子分析
* {: S0 H( H- Q8 S4 t$ d: mFactor score, 因子得分
# G6 p2 L( \/ z M c' KFactorial, 阶乘
5 o1 u( W. a7 z4 n4 JFactorial design, 析因试验设计
0 B7 u8 X2 {( }7 L; ~8 c, zFalse negative, 假阴性0 ~3 \1 E' L2 o- p% o! {5 j
False negative error, 假阴性错误9 Y( Y o) x: \: Y9 g) H( u
Family of distributions, 分布族6 d- v1 L0 g9 S/ Q' B2 ^" g
Family of estimators, 估计量族
6 A3 ^7 K e( C6 aFanning, 扇面
0 R: ~" N! V. @3 v+ O# AFatality rate, 病死率
' s# }- o8 |9 W6 s+ pField investigation, 现场调查8 g3 Q( q5 ^7 o3 U% C Y- h. I
Field survey, 现场调查
" _. ~4 }1 h" J# Z& YFinite population, 有限总体, e# y/ o- Q9 x- p9 o9 k
Finite-sample, 有限样本3 K4 Z0 t& K7 Z9 n' |' V
First derivative, 一阶导数2 _1 a6 D6 G( n8 z A
First principal component, 第一主成分7 P+ h$ C R* A2 A" f6 _0 k
First quartile, 第一四分位数
) w& p/ W+ b* e- }4 ^Fisher information, 费雪信息量5 r) ~" C7 w3 L c
Fitted value, 拟合值 Z. m q! E; L
Fitting a curve, 曲线拟合; F5 n2 A( v; O, R: w
Fixed base, 定基* k7 ]/ O$ s9 V" a* A5 j
Fluctuation, 随机起伏/ r. l+ E* V$ _: F
Forecast, 预测+ E( p9 I# @* J" Z. x
Four fold table, 四格表5 d: y4 |+ [ O5 x+ H# d+ ^ B
Fourth, 四分点
2 a ]6 F r" K! v7 N7 E9 p8 _Fraction blow, 左侧比率
0 g4 l$ ~7 i! N ]5 P) m& H) hFractional error, 相对误差
# n- Q) u* n) b- dFrequency, 频率
% t4 _( [4 T" P$ L, x2 z( }5 l1 xFrequency polygon, 频数多边图( E# b7 F3 b- [, W8 f; [
Frontier point, 界限点
# o! ^1 ~0 n* l9 u: j+ O3 ~Function relationship, 泛函关系
0 V+ D; i5 I' v1 N& g6 nGamma distribution, 伽玛分布
( @+ }( ~! ]% t7 G1 \" B1 V+ jGauss increment, 高斯增量
6 f/ C4 s7 V; N0 ?' b: FGaussian distribution, 高斯分布/正态分布$ L# l1 h" q5 n* ~7 { k- a! W
Gauss-Newton increment, 高斯-牛顿增量3 z9 |- N ^% [0 m4 k# E' D0 r
General census, 全面普查* F7 u- u; |" i n
GENLOG (Generalized liner models), 广义线性模型
. W- z; E" D' e# u B7 U+ @, @Geometric mean, 几何平均数
( ~* O8 R1 Y" ^# ?9 yGini's mean difference, 基尼均差; _% h/ M9 o5 W7 o! y$ g/ f
GLM (General liner models), 一般线性模型 # c( j5 m1 D9 |5 A& b: a
Goodness of fit, 拟和优度/配合度
+ g( U! i1 A6 _! @" G, \Gradient of determinant, 行列式的梯度
- H! C- w% |3 ^" ?0 p2 lGraeco-Latin square, 希腊拉丁方
3 v! b6 W0 r/ g. p! E# VGrand mean, 总均值8 \( [8 s7 i/ J& X1 B: b7 }- \
Gross errors, 重大错误0 _3 Q9 F* p$ a) r7 I
Gross-error sensitivity, 大错敏感度$ ~' @2 m4 s! l' `% H7 V
Group averages, 分组平均# C0 Q; i& Z l B/ S- W2 R( q% _4 P
Grouped data, 分组资料
9 i/ G4 z0 G' K% XGuessed mean, 假定平均数
/ ?5 i) s1 b4 Y& ? FHalf-life, 半衰期, T( U6 P% P6 k3 I9 {+ Y- S
Hampel M-estimators, 汉佩尔M估计量( @ A% ?+ h9 ^/ d( Y
Happenstance, 偶然事件+ H1 n7 f ^/ U; j- j
Harmonic mean, 调和均数
0 l$ |5 k) p, c6 _+ c F( r* G* d' fHazard function, 风险均数
7 i g* F2 w3 w: k5 y9 b H0 E) ]Hazard rate, 风险率, [; j9 l; A% f0 h; s) L/ e
Heading, 标目
+ R8 S0 I+ p5 N; \! |) ~Heavy-tailed distribution, 重尾分布
% A% c# \* L( I* }Hessian array, 海森立体阵& X! ~. m7 Q/ c- X$ @6 S" M
Heterogeneity, 不同质5 i' I- ~& \1 k( O7 z
Heterogeneity of variance, 方差不齐 9 ]5 P, C2 v8 {: Z: O& x7 X9 `
Hierarchical classification, 组内分组. M$ ]7 F E* t! o
Hierarchical clustering method, 系统聚类法
+ u( l& f/ p0 S' p+ {4 M) KHigh-leverage point, 高杠杆率点0 d3 J2 K3 i9 h7 p7 j. M
HILOGLINEAR, 多维列联表的层次对数线性模型( T- ?( R) d! W
Hinge, 折叶点' x/ G, e, k: j! |$ h F$ e" \( ~" m
Histogram, 直方图' u: _$ F9 @- k# [% Z4 L9 O' |
Historical cohort study, 历史性队列研究 & C4 |( y$ L' |( E1 `, Z
Holes, 空洞7 H0 ]( ?5 k6 F3 O; {9 U: r. U
HOMALS, 多重响应分析
, U6 D$ |( k. ]; P5 R, Q5 w) }Homogeneity of variance, 方差齐性8 \% {% W: I$ |) D1 l
Homogeneity test, 齐性检验4 A7 L+ q4 b+ P9 K8 P7 {$ S& h
Huber M-estimators, 休伯M估计量
( f3 e" x$ ] j0 N' THyperbola, 双曲线
# j* ]: e+ l' E g6 [ GHypothesis testing, 假设检验' v6 m: r6 l% t
Hypothetical universe, 假设总体! A% ]+ t" y* m4 g: f6 d9 t
Impossible event, 不可能事件. A0 d' r8 A# w4 i" J
Independence, 独立性
& P5 A3 K- A5 C" [) k! EIndependent variable, 自变量
5 Y1 W$ G. n9 v# w ^' YIndex, 指标/指数
' \1 k! {+ l u1 N9 W0 L! dIndirect standardization, 间接标准化法
( G0 H& O/ B- d. P8 `1 w- t7 @% IIndividual, 个体7 v) G# b+ [/ ?! N3 O3 k' G
Inference band, 推断带) {! t, l+ p# `/ E. {4 a
Infinite population, 无限总体
* g* i6 U( C, E3 @Infinitely great, 无穷大& f, ^, g1 d% y& p- c
Infinitely small, 无穷小0 o% y* W( s C) f. q2 P
Influence curve, 影响曲线
' S0 c/ C2 Q9 `" U4 W% x# qInformation capacity, 信息容量
8 l q0 A3 L% I) q: a+ O& Z& i6 U0 _! IInitial condition, 初始条件
. x* n5 Y; X% H4 _; a) RInitial estimate, 初始估计值
( E B! }' b1 S5 y0 ~; q* xInitial level, 最初水平. k Y1 ] c. |0 s+ h0 L
Interaction, 交互作用8 N6 m/ I* G/ { v
Interaction terms, 交互作用项
5 E" X/ A6 V+ v5 kIntercept, 截距0 ]8 e5 U4 _+ G
Interpolation, 内插法8 e: j" ?% r8 y/ h1 \# a" F8 ~
Interquartile range, 四分位距
2 L% R+ J1 }' K. NInterval estimation, 区间估计
& ~8 B! b0 R7 k8 {# w2 F( wIntervals of equal probability, 等概率区间
( Y4 E3 d% M) q! a* H# XIntrinsic curvature, 固有曲率
/ Y# V5 q/ a0 ~5 k% v) SInvariance, 不变性, G% A, e( y; N) q" Z1 D
Inverse matrix, 逆矩阵
5 y/ U0 B) h" d0 \6 N7 d tInverse probability, 逆概率, _7 j1 q; I" r% N: t
Inverse sine transformation, 反正弦变换
8 N6 w+ \* K$ `9 p- J4 @Iteration, 迭代 * _3 R T% A B' L6 _! r: D4 V
Jacobian determinant, 雅可比行列式
) m/ [+ p, n" g8 q) M2 cJoint distribution function, 分布函数
( u1 X* c4 _9 e& Z: k' o0 ]Joint probability, 联合概率- S# t d7 c0 m2 P. m
Joint probability distribution, 联合概率分布
- s! k& h6 p. y( i2 t' }K means method, 逐步聚类法6 ^# }4 q/ `9 h) p1 E2 m
Kaplan-Meier, 评估事件的时间长度
9 \! K: m+ O. J1 k* rKaplan-Merier chart, Kaplan-Merier图
+ s/ F6 \6 ?) u& @Kendall's rank correlation, Kendall等级相关: B+ `- A* L0 p+ |
Kinetic, 动力学) `7 h9 R& s7 x+ ]
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验, T0 M! N( w; T7 w4 Z/ u
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
/ L) w# L7 a" l eKurtosis, 峰度) G6 k+ r5 o3 a
Lack of fit, 失拟; u: D9 W9 @* C5 c
Ladder of powers, 幂阶梯) F2 ]; G6 g' y+ f: m+ W
Lag, 滞后
! W; y6 e, W0 `; \% F7 H7 nLarge sample, 大样本
1 y) D+ [; }# `, }1 YLarge sample test, 大样本检验8 v+ ~9 e, p- j1 i" j' u1 p
Latin square, 拉丁方4 n7 D W3 O8 g
Latin square design, 拉丁方设计5 @. t4 I% ~2 x* d& `
Leakage, 泄漏
2 c) l1 V o1 d A9 RLeast favorable configuration, 最不利构形5 j9 J" F( R1 T: e8 G' ]: w; K- R
Least favorable distribution, 最不利分布+ z; f2 W+ Z) J% R, B
Least significant difference, 最小显著差法
" Q6 V( \- o, Q. g; N9 d, l7 U% [Least square method, 最小二乘法
+ a' d& u }& B, E5 jLeast-absolute-residuals estimates, 最小绝对残差估计$ r7 p; V. w, A3 j; S& C3 N
Least-absolute-residuals fit, 最小绝对残差拟合
3 s/ ^9 \! m( m8 }) {7 ~. [( yLeast-absolute-residuals line, 最小绝对残差线
6 B3 o* Q$ w( b$ pLegend, 图例
) g; K8 p+ k8 `4 e; }L-estimator, L估计量" j4 U7 ? W& J h, D
L-estimator of location, 位置L估计量
: [& N% U1 ?/ ~6 l' _4 q! {L-estimator of scale, 尺度L估计量3 U7 L& y$ [- M2 I1 S
Level, 水平& e4 Y- Q$ W5 Q2 m/ j' _
Life expectance, 预期期望寿命
; L1 \# }/ z5 G; `0 oLife table, 寿命表
* c* k% B* W# b2 `Life table method, 生命表法7 s0 N s! z6 o& H
Light-tailed distribution, 轻尾分布
, @- f. N0 J. \. d E1 ~% D* JLikelihood function, 似然函数
- [9 C) b3 [% j* e7 ELikelihood ratio, 似然比" P0 p7 z1 i: N4 M+ K/ O5 O3 w/ l
line graph, 线图
1 o/ Y! f# G+ F; M0 \, D) }Linear correlation, 直线相关+ ^( f4 w0 w0 n8 j$ I
Linear equation, 线性方程2 y% I+ C/ K3 r* |9 s
Linear programming, 线性规划+ ^. A+ D9 \3 v) l8 V
Linear regression, 直线回归
) A H- {* j' U* p% E" l! Y! ~1 P$ I1 CLinear Regression, 线性回归
0 {: Q! M: s: a* C; U1 B- s( I/ oLinear trend, 线性趋势
' {; a5 K# s( \) T, v; nLoading, 载荷 & d& j4 n1 s: l# F
Location and scale equivariance, 位置尺度同变性
1 Z5 F8 W. J, p+ F/ ?Location equivariance, 位置同变性
: O2 y$ l) L8 ^4 Z% ?5 H/ ]0 _Location invariance, 位置不变性
8 f& b* l( F) R1 r7 LLocation scale family, 位置尺度族: b, _4 ]# R1 G R& ]! r/ c# t: O8 ]
Log rank test, 时序检验
0 i4 e( K# {' J+ f" x% E' TLogarithmic curve, 对数曲线
6 c. _6 I. H+ i; q& {# j" z- M, ^Logarithmic normal distribution, 对数正态分布
1 ^( z4 c( M7 ?" L" w% z- Y' j# Q6 SLogarithmic scale, 对数尺度, O4 Z0 n O, Y1 S2 X: y
Logarithmic transformation, 对数变换
4 e' ~1 S& a% b2 ~Logic check, 逻辑检查) d5 Y4 t7 @5 m$ {" h$ x& i: K
Logistic distribution, 逻辑斯特分布% g8 Y& S6 ^7 j: u
Logit transformation, Logit转换! { L: H P9 o
LOGLINEAR, 多维列联表通用模型 D7 D t! n4 @4 z9 h; `. b
Lognormal distribution, 对数正态分布% y3 _7 c6 ?4 J/ F9 d5 I+ K$ ~
Lost function, 损失函数
5 ~+ n2 E4 q2 ^$ b- E. b; a4 E+ aLow correlation, 低度相关4 Z) T" \, @5 S* g" T
Lower limit, 下限
: { j# C6 ^1 w9 S2 [Lowest-attained variance, 最小可达方差6 y. |1 i, O8 P
LSD, 最小显著差法的简称
9 {* S7 M2 h+ u' HLurking variable, 潜在变量
6 } s, b( d8 _% \/ U( gMain effect, 主效应
( d" {+ e }, p% PMajor heading, 主辞标目; ^7 R2 _$ N0 G- X7 j9 s4 x- z
Marginal density function, 边缘密度函数* g8 `$ L3 V, v
Marginal probability, 边缘概率
# z8 g! i7 [& U" BMarginal probability distribution, 边缘概率分布6 e8 [1 \3 q9 u# b5 |
Matched data, 配对资料
2 z. S( \7 N% J5 CMatched distribution, 匹配过分布2 v- N8 H1 @; Q% P7 ]) B
Matching of distribution, 分布的匹配
: F( ^4 f* k/ ?, i! mMatching of transformation, 变换的匹配% g1 p# i+ C, ?, |$ ] C. n
Mathematical expectation, 数学期望
1 r( ]; v" N% Y- a, e4 iMathematical model, 数学模型/ @' Q* K2 e& n
Maximum L-estimator, 极大极小L 估计量# D9 L* n! a4 O, Q$ E7 a' a9 F
Maximum likelihood method, 最大似然法
& E- D0 t. o1 pMean, 均数1 M6 F( s- J4 H' l% g3 c+ [& {
Mean squares between groups, 组间均方) M8 w; |$ {! T: S* y
Mean squares within group, 组内均方+ _3 @/ L9 }- z# X7 h
Means (Compare means), 均值-均值比较
" e2 R) q. Q3 F) e0 \# y9 S) d( }Median, 中位数
, R8 H1 `( P; vMedian effective dose, 半数效量
. ?5 a# f1 E1 |$ k9 Q" @4 nMedian lethal dose, 半数致死量: @' a7 _! L! I% c. n
Median polish, 中位数平滑
& [% z& S7 b4 [! t( T# aMedian test, 中位数检验* h* l& C$ X( [# c! w
Minimal sufficient statistic, 最小充分统计量
9 r5 |+ k; F0 J. `8 MMinimum distance estimation, 最小距离估计/ v) R6 l1 M5 x9 D/ [- a/ G
Minimum effective dose, 最小有效量
7 r& z$ A3 Z, Q" }- P3 oMinimum lethal dose, 最小致死量' Y w$ j1 t& R+ p3 V; Y8 K
Minimum variance estimator, 最小方差估计量
% \; E6 P5 |/ v4 E+ v# QMINITAB, 统计软件包
, w) x5 e7 b+ |Minor heading, 宾词标目
! b6 Y! R9 f& O r; r6 LMissing data, 缺失值% Y1 j& K% X9 R3 T( E8 K+ p
Model specification, 模型的确定
% Q, Q; ?3 q, ?, p4 KModeling Statistics , 模型统计" l0 ]$ I4 l: O# M- f
Models for outliers, 离群值模型; v( Y" } J8 x" b' n
Modifying the model, 模型的修正
0 K/ `- H3 K( _% }Modulus of continuity, 连续性模. Y+ u+ K0 u6 K
Morbidity, 发病率
4 X; Y7 T; k+ @: J4 J/ i, uMost favorable configuration, 最有利构形% S2 u& ?" `7 Y9 p+ W5 z0 j
Multidimensional Scaling (ASCAL), 多维尺度/多维标度! W7 H# v1 k) ~+ K$ R
Multinomial Logistic Regression , 多项逻辑斯蒂回归2 C- Q: l( A) b' J
Multiple comparison, 多重比较
9 w" z, y# c: G5 Q; f' BMultiple correlation , 复相关1 n$ I3 Z8 w9 W/ V% v6 y
Multiple covariance, 多元协方差
2 U: e: U! p& H6 n' I0 M9 OMultiple linear regression, 多元线性回归- s# s8 ~* c3 C* C2 j
Multiple response , 多重选项
5 z% @4 q2 R8 w& EMultiple solutions, 多解
/ ^+ e: F& e3 ^! c/ UMultiplication theorem, 乘法定理
* n& e1 J K, K% u1 |0 i s& cMultiresponse, 多元响应6 x( P7 M7 K8 q) G( I
Multi-stage sampling, 多阶段抽样. e( J9 |# R& s) k/ _6 m- O" m
Multivariate T distribution, 多元T分布
5 N9 \9 s0 S1 l2 W1 P6 wMutual exclusive, 互不相容
4 i# w3 j/ m% e0 r! x; n, X- qMutual independence, 互相独立. J5 ]9 t1 q8 g, [2 \& K
Natural boundary, 自然边界
! Y" p' Z6 e6 |% X3 X& ~" n) HNatural dead, 自然死亡' ]' X* x7 g8 g4 z# ^6 M) I2 S
Natural zero, 自然零
) R/ t! Y# O% c8 S6 YNegative correlation, 负相关
. u, q6 e4 `" V& T/ XNegative linear correlation, 负线性相关
7 k& b O6 _3 E g# p2 r# Y( FNegatively skewed, 负偏
2 v* k. X) i3 ~* h l" o) wNewman-Keuls method, q检验! ]# T+ b) Q5 {; i! `- A0 n
NK method, q检验/ b% F, z9 v$ x3 Q1 N/ v3 {
No statistical significance, 无统计意义, w6 a! ~# F$ Z S5 l
Nominal variable, 名义变量
5 T2 k% _/ ^% \) S3 z( ANonconstancy of variability, 变异的非定常性
# a+ N# y8 d+ g: s/ C& i# p) q lNonlinear regression, 非线性相关
8 y, F4 |. |1 n8 Z& h# p5 ~7 ] e' j) @Nonparametric statistics, 非参数统计! [1 `& U6 {* g
Nonparametric test, 非参数检验
; W& k, }9 x3 CNonparametric tests, 非参数检验5 d9 c; b Z! W0 i( z, J* S
Normal deviate, 正态离差
+ |! v. C, e3 N; j" d; V3 INormal distribution, 正态分布
4 z9 ]) W. d) V \Normal equation, 正规方程组
W8 g, _$ L- i8 b) M) ^% \ LNormal ranges, 正常范围
8 O$ T0 p" h/ i4 M mNormal value, 正常值/ E7 F3 a O* X4 U: W' x
Nuisance parameter, 多余参数/讨厌参数1 |$ |1 l8 z+ O! i o# H# X
Null hypothesis, 无效假设
e2 O1 h$ c! N( @" \& {Numerical variable, 数值变量
' U( L* p$ M. B% EObjective function, 目标函数9 f3 w# t5 z8 E: G) ?
Observation unit, 观察单位
, Y# x* r" J% t2 t; y9 c8 EObserved value, 观察值* u) C" |5 k) ~! c5 R
One sided test, 单侧检验- M. C/ ?# X; K
One-way analysis of variance, 单因素方差分析6 V$ t" s/ p/ U0 |1 [* m0 y
Oneway ANOVA , 单因素方差分析
. j3 Q; Q* U* q2 }% eOpen sequential trial, 开放型序贯设计9 o) U5 x$ Q/ v& L6 m& H" Q
Optrim, 优切尾) d" z7 @' w/ ?4 z# f6 e5 @! G* w
Optrim efficiency, 优切尾效率/ t4 \) r; q' N2 `5 w2 _' n
Order statistics, 顺序统计量
8 X* M/ d3 s" z& n0 kOrdered categories, 有序分类, `6 ]1 Y0 ~7 B# P; A+ `2 [0 L: s
Ordinal logistic regression , 序数逻辑斯蒂回归: C8 W V- M3 Y" i2 u# A' \. n% \
Ordinal variable, 有序变量
# R {+ Y+ f" b$ G( }0 \* EOrthogonal basis, 正交基
( @1 @) o0 q; s7 G3 m/ rOrthogonal design, 正交试验设计
' n( `+ g) v, m" u* B$ U; iOrthogonality conditions, 正交条件7 W o6 B/ \" m
ORTHOPLAN, 正交设计
5 ?2 \) d& L/ u' z5 f$ bOutlier cutoffs, 离群值截断点
4 B8 K2 U; l* f \$ Y+ ~7 gOutliers, 极端值
6 d3 ^* ]" N' U9 r+ mOVERALS , 多组变量的非线性正规相关 ' Z" Y3 a/ m5 g0 u# h
Overshoot, 迭代过度% s. F7 P. x/ f3 e" P( X
Paired design, 配对设计
6 B2 l/ J# g2 g2 t8 e3 gPaired sample, 配对样本; w- b) \. B- j; @$ ]4 O
Pairwise slopes, 成对斜率
, e# O; ^8 m0 h* E8 aParabola, 抛物线
4 ]7 ~1 K) w4 v; _Parallel tests, 平行试验9 L4 U& }+ O+ J) T# n, Z
Parameter, 参数
9 G+ h% E9 k, t1 B; S+ U' [Parametric statistics, 参数统计
t" A- o! T3 iParametric test, 参数检验
4 L1 p2 Y# S7 Z2 r/ C+ FPartial correlation, 偏相关) k; I9 K$ V6 J- J5 |4 r& I
Partial regression, 偏回归# a! k* K; b; w: O \2 ]
Partial sorting, 偏排序
7 t/ f M. a3 R) }" WPartials residuals, 偏残差: ]+ l: A o9 G5 _
Pattern, 模式
+ \& s; f. i8 Z* \4 ?3 Y2 i9 c/ QPearson curves, 皮尔逊曲线7 K+ L( t1 f" `9 }) t; }
Peeling, 退层% Q |. b3 L! a0 I
Percent bar graph, 百分条形图% ]3 J3 @4 f! }3 z# c; z8 R% Y
Percentage, 百分比5 D1 l; c( B6 C9 f
Percentile, 百分位数
0 P( P9 ~: y9 j4 YPercentile curves, 百分位曲线
% G* x; G* F* ~8 W: Y5 zPeriodicity, 周期性
4 B, q2 j* V1 y: GPermutation, 排列' D' |4 ]" O3 R* G
P-estimator, P估计量
3 W9 w$ R z$ B! XPie graph, 饼图3 m" ]" J0 r6 r `- n. p
Pitman estimator, 皮特曼估计量5 e- |! C4 q! u& v8 Q, ?! L
Pivot, 枢轴量
. ]( `+ f- T6 ^! F, D2 {Planar, 平坦! B: p* [- u; C9 s
Planar assumption, 平面的假设
1 Y$ Y( `5 a E4 H. @# }PLANCARDS, 生成试验的计划卡. Z* s7 k. A5 O3 k
Point estimation, 点估计' E. ~$ L" c x. b! T
Poisson distribution, 泊松分布) }- }/ U- b! R5 e9 ?3 Y
Polishing, 平滑
- z! y4 O# p6 }9 t+ b6 |- I( XPolled standard deviation, 合并标准差: o; ~9 j/ H L) @
Polled variance, 合并方差2 c+ B# }7 m2 [
Polygon, 多边图3 Y- s; X0 F. U! I e! w
Polynomial, 多项式
! E8 U+ K2 K S7 }Polynomial curve, 多项式曲线) `9 r2 H2 s, P$ h+ d4 J t
Population, 总体
# ~' C& N' |& J" O- \! e7 w/ M. EPopulation attributable risk, 人群归因危险度
" g) T; R! c/ G+ aPositive correlation, 正相关% E# c) G& W% |; u; A& T
Positively skewed, 正偏6 _2 U) ?" o# Y4 L0 B& ^" {
Posterior distribution, 后验分布
- c6 I" m6 n6 q* v" z0 aPower of a test, 检验效能
$ V9 A3 M& e9 Y: [% CPrecision, 精密度; G' c( o; \4 G
Predicted value, 预测值( B2 ?; T% ?% S% O/ v
Preliminary analysis, 预备性分析
/ f q$ Z( o; p+ R4 Q- C. IPrincipal component analysis, 主成分分析
, N5 I; S! G2 {9 R3 YPrior distribution, 先验分布
$ Q# }+ o- I W$ I& y- W2 cPrior probability, 先验概率
- j6 Y9 y' n% i7 pProbabilistic model, 概率模型
3 s1 i4 g- ?( F/ u' Z( B% bprobability, 概率
2 c B+ }& K, j% L9 S" BProbability density, 概率密度
2 Z6 V6 G1 a4 IProduct moment, 乘积矩/协方差
% Q8 S% E5 n5 [$ e7 qProfile trace, 截面迹图
4 J1 O5 @5 w% ~# SProportion, 比/构成比
( O% z* K- O) d% T9 vProportion allocation in stratified random sampling, 按比例分层随机抽样
, f- h4 s3 i- N/ J- S0 YProportionate, 成比例" ~ m! ]; o' d3 Y; m
Proportionate sub-class numbers, 成比例次级组含量( b5 m1 p0 c9 E! o) b* _
Prospective study, 前瞻性调查
9 n/ x" Q# e Z- o% E0 \9 Z$ XProximities, 亲近性
: _" J& P3 P4 S. B2 S( Y* d; `Pseudo F test, 近似F检验4 [0 w! Y1 ?7 p# V, t
Pseudo model, 近似模型
2 F* }* L- x- } M' Q2 J! ?! C# EPseudosigma, 伪标准差
3 a1 V( _; {. W% ?" x$ EPurposive sampling, 有目的抽样' J: ^$ ^: O5 D- d' O4 W8 ^
QR decomposition, QR分解7 p# h3 B4 B+ A8 e N
Quadratic approximation, 二次近似5 g2 p. J t8 s' ^' E$ F! j1 r
Qualitative classification, 属性分类 W6 e* X+ L& j# q
Qualitative method, 定性方法
7 ^$ H; B. j% ^! g vQuantile-quantile plot, 分位数-分位数图/Q-Q图
; n4 k1 `) q0 k% pQuantitative analysis, 定量分析
; f- _; V7 R; d0 ?/ f' o6 b( RQuartile, 四分位数
- s% V; Q8 M9 V& F6 NQuick Cluster, 快速聚类9 Z; o6 w' q+ n9 D0 H$ Y, k0 @
Radix sort, 基数排序 F9 Z$ `% c! z* y7 \2 P+ t, W
Random allocation, 随机化分组
% M( q* w# ]1 _% xRandom blocks design, 随机区组设计. L1 B" ^+ y o) Z
Random event, 随机事件4 l* o8 u/ X* @. s3 r" w0 ~) |
Randomization, 随机化2 V8 I* E/ @, t
Range, 极差/全距
; [0 g+ z& \+ X1 hRank correlation, 等级相关# C1 `9 v! _! |1 i' L
Rank sum test, 秩和检验
b- u6 g9 n& ]" ^" O/ bRank test, 秩检验
0 K9 Y; X; S7 F; u3 I0 v' s3 xRanked data, 等级资料) n$ }6 P$ n3 w _* e2 L i
Rate, 比率
8 ]+ |$ N, Q1 w- mRatio, 比例
0 L. {1 g4 R% r0 K7 @1 dRaw data, 原始资料& c- \; H' e s* o
Raw residual, 原始残差
) `, i: b& }+ SRayleigh's test, 雷氏检验! i8 ~* a5 c! z/ p4 `
Rayleigh's Z, 雷氏Z值 Q6 v2 M% E; i7 I7 y
Reciprocal, 倒数0 |) k% G; b }- O: b; l* C3 r! X
Reciprocal transformation, 倒数变换$ d) Q1 P: t8 P9 ~; ?: Y! X9 b2 ]
Recording, 记录! M' @# Y1 B+ h ^6 I
Redescending estimators, 回降估计量. b/ A; \9 m* ~( h; O
Reducing dimensions, 降维
! ?3 g5 `5 K8 ?" b' f) z7 I/ NRe-expression, 重新表达+ M0 ]" T$ `3 g9 L: X; Q7 F4 q
Reference set, 标准组
4 m. j5 c( {' a8 l8 [# M7 yRegion of acceptance, 接受域
" L1 ?# {; O: O& D5 X/ @2 }5 aRegression coefficient, 回归系数1 i' V2 R" V$ ^& ~1 y, f j6 z
Regression sum of square, 回归平方和$ w# j* H3 ^( u4 ^ V: l
Rejection point, 拒绝点, G3 Y3 v- i3 w0 S
Relative dispersion, 相对离散度
! f I/ i' n/ D- r* x. K/ QRelative number, 相对数. ^& z s+ l I- G6 j; O" v7 c% Y9 T# k
Reliability, 可靠性3 {6 C: N1 o+ M. v! N0 U- K3 V
Reparametrization, 重新设置参数
' f9 r8 F6 w5 k; E3 wReplication, 重复
$ s8 R) Y3 `9 N, T0 a; f( k' MReport Summaries, 报告摘要0 S) E* x. f, V6 j: Z5 b0 j
Residual sum of square, 剩余平方和3 j% F1 J ]7 e* x8 E2 K
Resistance, 耐抗性+ W/ K- Z6 w( p0 e' k
Resistant line, 耐抗线
' W5 z6 d/ ?% W1 {Resistant technique, 耐抗技术
0 ], j" e2 w1 z- AR-estimator of location, 位置R估计量; s# G# h1 F/ j! g& e6 d& ~$ o6 R
R-estimator of scale, 尺度R估计量
9 {! Q! I& H P& K4 J0 xRetrospective study, 回顾性调查- ]# b- C( w6 |) F j# o
Ridge trace, 岭迹, |0 M( G1 v+ }0 P [0 S0 D
Ridit analysis, Ridit分析
% X/ O2 e h5 Z# MRotation, 旋转
7 B! b* D/ |0 q) ], rRounding, 舍入
+ {$ A/ a1 @4 ^( S s4 r) v" qRow, 行
. q. F: z* R' HRow effects, 行效应$ C5 q1 a$ N$ c3 p, O, t# Z3 _
Row factor, 行因素
; z. C( I! ?0 ?& U1 X; j& kRXC table, RXC表
- ?- C2 U7 H" J; mSample, 样本. O% q3 F2 }3 y
Sample regression coefficient, 样本回归系数
u0 { r# ^- R: D# ASample size, 样本量
2 d- w+ a5 b/ \& MSample standard deviation, 样本标准差
; P+ G# G9 _; U; u, ]9 sSampling error, 抽样误差4 k5 Q; `4 x s( A
SAS(Statistical analysis system ), SAS统计软件包
# i d, p; \' n; m9 m% yScale, 尺度/量表1 v& \ |/ C! B8 v4 T
Scatter diagram, 散点图0 c$ g8 }* I! e' w3 ]
Schematic plot, 示意图/简图
, l) U7 L& E* b' JScore test, 计分检验
$ y0 g" V! o( ~9 HScreening, 筛检
1 X' z9 _# A- z6 w. y8 g% N9 @SEASON, 季节分析
' q, X% M% B8 b/ ]# d1 [& T3 CSecond derivative, 二阶导数# M5 r2 t' c& N3 m
Second principal component, 第二主成分. n6 e/ S4 Z9 a; `8 x
SEM (Structural equation modeling), 结构化方程模型 1 J' f! U' [/ m* w9 L) F% e4 S6 W
Semi-logarithmic graph, 半对数图' b/ v# S& f2 K; ]! P0 L, S6 y! k
Semi-logarithmic paper, 半对数格纸
. H# ?0 {' L. @5 I+ {Sensitivity curve, 敏感度曲线# M' m+ w, k& t, M* I
Sequential analysis, 贯序分析* |4 X. i8 ?7 l6 T
Sequential data set, 顺序数据集
$ M K* S' R" {8 J. [5 E sSequential design, 贯序设计0 K! w% N( U) k" E7 o- C
Sequential method, 贯序法' p) M$ F! G7 z
Sequential test, 贯序检验法2 e0 @) b! `- Y1 j4 z$ }1 M r3 u
Serial tests, 系列试验9 M* B0 E& v: `. G4 P
Short-cut method, 简捷法 " v' N9 r, `8 t0 V+ f& P: C$ j
Sigmoid curve, S形曲线
& a7 L- n! I& |( cSign function, 正负号函数3 W9 A5 L& p* h- M
Sign test, 符号检验1 @& k$ f# f. D& s2 K" D
Signed rank, 符号秩
/ i: C5 A* \/ K( p& T$ FSignificance test, 显著性检验' f5 H0 u: A" B: o8 ]' `/ u
Significant figure, 有效数字
1 \: F8 w8 ~8 j; S3 M( xSimple cluster sampling, 简单整群抽样8 j3 G4 U& F: {. L, g! [# r
Simple correlation, 简单相关/ a$ `* Y6 C& }% L
Simple random sampling, 简单随机抽样: r. `7 M7 z( P/ f/ B
Simple regression, 简单回归- ^- U5 E. [. D$ m# F
simple table, 简单表9 r; B; ^# e" S+ O/ E0 y# i
Sine estimator, 正弦估计量
. m% [) @4 n! SSingle-valued estimate, 单值估计
* N( I) J' r n6 @0 ~+ ~' tSingular matrix, 奇异矩阵
' e5 r$ i$ h# `! z0 T6 JSkewed distribution, 偏斜分布5 |2 L$ J7 m$ S7 x# I9 N
Skewness, 偏度) i M w" x5 k3 h* I6 |
Slash distribution, 斜线分布
% q" P/ N( V6 X$ mSlope, 斜率) X* j8 m$ Y- ~- Y" c1 @! i2 D$ k
Smirnov test, 斯米尔诺夫检验# d8 z# g4 G& i1 c3 l. q
Source of variation, 变异来源
& U7 v3 @2 Z F K/ hSpearman rank correlation, 斯皮尔曼等级相关2 \, Y: |% m6 n
Specific factor, 特殊因子0 [( f: ^+ Z2 c0 R& E/ E- F% @ a
Specific factor variance, 特殊因子方差
: `6 M7 F% I+ j' Z) N/ jSpectra , 频谱4 _" V" a) M0 e$ W4 r
Spherical distribution, 球型正态分布
- Y) R2 |) n: N+ ~Spread, 展布
) |; o" f5 S) ?0 e+ [4 N6 d2 eSPSS(Statistical package for the social science), SPSS统计软件包* {" @- C" D3 i4 d/ C5 a- C
Spurious correlation, 假性相关
. P% [5 q0 q7 e, uSquare root transformation, 平方根变换9 X9 n; z" H" j. V
Stabilizing variance, 稳定方差
( k& l! y+ A/ g! a; j- KStandard deviation, 标准差8 g1 T( @" R8 i/ i2 i$ t+ H
Standard error, 标准误
( F7 ^& p0 V( _! s/ u5 n% A+ ^Standard error of difference, 差别的标准误
1 s( ~3 v( A0 QStandard error of estimate, 标准估计误差
; } d% G. X \, x( t0 Z4 \8 `4 TStandard error of rate, 率的标准误
* q a, P' q& Q* X6 AStandard normal distribution, 标准正态分布2 ^( K! K' l4 s* a
Standardization, 标准化
% Z& M$ r& y+ N9 U# _3 jStarting value, 起始值1 z1 e2 E( m: p0 @6 x! w$ T3 _) P- O! }
Statistic, 统计量: V( Z& R; n$ v& T& |
Statistical control, 统计控制* n/ p! h; Y( L" J
Statistical graph, 统计图& k, W! f2 Y$ f! i
Statistical inference, 统计推断- M, B, _; Q, M) t) b
Statistical table, 统计表$ k; u$ c% j! f
Steepest descent, 最速下降法
; j8 P% R, a; v! [6 m% }$ EStem and leaf display, 茎叶图
( I5 T; k. b/ x9 OStep factor, 步长因子
& ?3 |& i9 t" \Stepwise regression, 逐步回归
. A! q" c8 a# _" |/ G1 [Storage, 存
9 G& I) }% _0 b aStrata, 层（复数）
% k0 R! l% A- G4 kStratified sampling, 分层抽样7 k0 t) @4 f9 {- w; e6 p9 L
Stratified sampling, 分层抽样
, A* W1 r0 i1 j3 tStrength, 强度
$ F; F$ {$ N* z C6 h( J5 P( hStringency, 严密性
# X$ A- R# c5 d: o: i H+ u" UStructural relationship, 结构关系
3 Q4 e0 Q- X; ~: t& bStudentized residual, 学生化残差/t化残差
% k+ v# g/ V( c! d1 y. E% @: ESub-class numbers, 次级组含量, W) y, ]/ D: U
Subdividing, 分割6 I; D& ]) f' ]8 Y5 }
Sufficient statistic, 充分统计量, J% p1 h. R8 y3 ~5 x1 m7 n
Sum of products, 积和
, P* F/ p) {; u. G2 zSum of squares, 离差平方和
3 B e- U4 ^! l; `- tSum of squares about regression, 回归平方和
6 G- |1 @# u' K) H/ ISum of squares between groups, 组间平方和
6 N' v- g0 y( M7 J6 s6 [: I, VSum of squares of partial regression, 偏回归平方和
N- e6 S9 M7 x/ e! _% r' G% YSure event, 必然事件
7 E2 L" g2 R# p1 [8 R) ^Survey, 调查
7 e4 g4 z: z, U( t; |# QSurvival, 生存分析
0 M+ S5 R8 C) E, A$ M/ qSurvival rate, 生存率$ s6 I. V8 C: x* `3 ]! j5 @+ F
Suspended root gram, 悬吊根图* ?) \ | s+ c1 G" ^% G+ w, ]# G3 y
Symmetry, 对称; f ^( g l4 r5 T4 Y1 i& }
Systematic error, 系统误差2 R: {4 {. h! b2 l( y5 n8 O
Systematic sampling, 系统抽样
& M% h9 h2 ?1 i2 b gTags, 标签
/ ~7 v% r4 r/ |" u$ [6 U( j+ GTail area, 尾部面积( A$ s l# o6 N) o- p8 T
Tail length, 尾长% D; x6 I* O( m' s ?+ C% ~3 m
Tail weight, 尾重7 |( ^, ]" @* Y" d( l( l( F; U
Tangent line, 切线5 r5 C! N! z1 F2 ~. K+ A
Target distribution, 目标分布/ \* b" Q' G7 U
Taylor series, 泰勒级数
9 w7 p) P5 \. O+ ~* ^Tendency of dispersion, 离散趋势3 H" }2 |5 t0 b* ]* j
Testing of hypotheses, 假设检验! x& n* s% ?9 D
Theoretical frequency, 理论频数
# E; c% q7 ]9 o2 v. i; nTime series, 时间序列
: w/ f: a% B: M4 g- T0 @Tolerance interval, 容忍区间" ?$ _. M8 \( f
Tolerance lower limit, 容忍下限
' Y {7 a0 z2 ~! k5 Z6 D$ YTolerance upper limit, 容忍上限
" H! T( a+ `1 _( m) sTorsion, 扰率/ N. \: X- \4 t* S" p; W$ S, a) f% J
Total sum of square, 总平方和' {& D% y5 a1 O$ t2 C' R
Total variation, 总变异
+ O: G7 E, y: l1 Y# k1 ]+ ?Transformation, 转换
; Z2 w0 z' G6 }0 v% p2 J' tTreatment, 处理0 }7 x" i0 I* v. d( O
Trend, 趋势0 R, H- g/ p2 F" H; X+ c& U) e2 c0 N
Trend of percentage, 百分比趋势
5 g# b3 n3 _3 mTrial, 试验6 A( E- q2 e4 X; Y9 T
Trial and error method, 试错法
/ D* G8 K" O( [- g) rTuning constant, 细调常数
- ?3 O7 G. K, X7 V8 r, ^Two sided test, 双向检验6 H7 W2 d# E% ^& O
Two-stage least squares, 二阶最小平方7 f |2 W+ u7 w! m0 ^& v8 z& b7 `
Two-stage sampling, 二阶段抽样8 g' ~' N& A' t9 _8 l( q" K6 z
Two-tailed test, 双侧检验
# p1 f) K& [0 [* m1 XTwo-way analysis of variance, 双因素方差分析
" E: y" j5 O5 Y/ p6 P* X* yTwo-way table, 双向表
+ y" c6 E$ ^2 P( t8 M+ K7 \Type I error, 一类错误/α错误
% O3 s( @& C$ b& p, }Type II error, 二类错误/β错误
W- I" T1 \9 U3 G6 T0 GUMVU, 方差一致最小无偏估计简称
9 u/ h! r" ^; S+ ^+ [" KUnbiased estimate, 无偏估计
2 C j. T6 v' A/ L+ Z9 g8 ]Unconstrained nonlinear regression , 无约束非线性回归- x: d/ k* `7 _( z8 Z
Unequal subclass number, 不等次级组含量
' P/ D3 I( U- M& ]& vUngrouped data, 不分组资料
! A/ X! |1 X4 ^' Z) w& g tUniform coordinate, 均匀坐标
0 r3 \ e& r# R' V. R( t1 DUniform distribution, 均匀分布# o' ?# ~, h" U; q6 @
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计# {: g. g, E# w$ n# |' x1 d$ F
Unit, 单元0 G% ]( b! b: {# I l' \
Unordered categories, 无序分类
2 c3 C$ D& }. u6 N, ]& n+ ]1 kUpper limit, 上限
$ w2 m m3 W7 S4 D7 MUpward rank, 升秩5 `% u7 i0 s1 ]$ Y" L
Vague concept, 模糊概念( S7 I# p) ~7 J% W" W/ M( _
Validity, 有效性8 k' A5 V# d& b. h. u# {
VARCOMP (Variance component estimation), 方差元素估计
h6 |; c. T$ fVariability, 变异性% r$ ~% y& b( p: k
Variable, 变量
& T/ i9 K6 i+ I* `& q7 W$ }Variance, 方差
, y+ W9 g: Z$ H: j- i; R# F; K0 rVariation, 变异4 G7 ^: e' X& p) p; R7 A# L
Varimax orthogonal rotation, 方差最大正交旋转* b* X5 }, e6 x5 |: X5 f5 {
Volume of distribution, 容积
: W3 X6 P5 ]7 k! N4 W4 S" yW test, W检验
- C7 q7 C% a5 u7 ?6 @Weibull distribution, 威布尔分布; N3 t* b" K" } _- G+ ~. ]( u
Weight, 权数3 f7 O) W( S6 @& @1 x0 ^/ c
Weighted Chi-square test, 加权卡方检验/Cochran检验: N# D' N" I( q# s) \/ p
Weighted linear regression method, 加权直线回归# W9 I7 u$ m3 g% n8 l
Weighted mean, 加权平均数
! s$ N J# M6 eWeighted mean square, 加权平均方差
) G ^6 |5 L. |2 A6 ?/ s7 x& xWeighted sum of square, 加权平方和
+ N! w% K0 M: E9 N; [Weighting coefficient, 权重系数+ H) K5 _! d# T$ N0 e
Weighting method, 加权法
- E) }6 |$ }: m" KW-estimation, W估计量0 D: P- C( ?* P- P/ f |
W-estimation of location, 位置W估计量
' B% A/ K1 M. r; f% o8 M, a9 _Width, 宽度( |* S# d7 z( t. m
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验( B( ]- s% P2 W9 N: R+ v; Q: [+ Q
Wild point, 野点/狂点
% L8 s5 p8 g* E' f0 pWild value, 野值/狂值
4 u! d8 o8 N6 w( a! S1 YWinsorized mean, 缩尾均值2 `$ b" V6 }) ]" U* r, |
Withdraw, 失访
R* z8 Y7 k, W0 Q! BYouden's index, 尤登指数
9 m- q) I& l3 ]# ]; M& m" U; mZ test, Z检验4 r" E6 u6 a7 H9 ^6 ]
Zero correlation, 零相关
4 m2 n& t% F& ^/ n1 F2 IZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
