|
|
Absolute deviation, 绝对离差& o% |" y6 u; \: L8 g
Absolute number, 绝对数. O7 `" i" S: J k- X6 s7 b" h
Absolute residuals, 绝对残差; J T9 V9 T6 K8 @$ _+ }: L
Acceleration array, 加速度立体阵" u0 l# V3 L- e/ q) \ u6 y
Acceleration in an arbitrary direction, 任意方向上的加速度
" G. @9 g6 q" q) pAcceleration normal, 法向加速度6 n; C0 `, Q5 h, ]
Acceleration space dimension, 加速度空间的维数
4 @6 {/ b/ W1 |4 c' G8 UAcceleration tangential, 切向加速度6 b9 O2 q% e; ?/ y* M1 {1 {1 b
Acceleration vector, 加速度向量3 J" {$ v6 C$ N( }3 Y2 u3 [
Acceptable hypothesis, 可接受假设
( y$ C% j/ P& k% _- k% sAccumulation, 累积: }) }$ ~% F! D# Z" {- n/ T; _; ]
Accuracy, 准确度
0 L9 R3 I" n* `- e3 b" h5 YActual frequency, 实际频数0 B1 I: a3 X/ u/ E% y8 b2 L
Adaptive estimator, 自适应估计量! A" Q W" d7 U( t+ h4 f; j$ ^
Addition, 相加8 m. h5 z* T$ f) |# v; ~
Addition theorem, 加法定理+ ?5 h7 `3 p6 y/ {0 C, O2 H" Q# `6 ~
Additivity, 可加性) d" k: I2 }& A O( @* j
Adjusted rate, 调整率% k- q3 \9 _6 ]% S& U4 x: D6 w
Adjusted value, 校正值2 C: {, O* I3 }! r) g
Admissible error, 容许误差+ M2 X/ c: B1 v* d* l( B
Aggregation, 聚集性+ ~6 h; G0 J# v9 E! N
Alternative hypothesis, 备择假设
1 {4 @# e" s. B6 U5 y; Y4 RAmong groups, 组间
# J4 ?: G8 W9 ?2 a3 M2 UAmounts, 总量
: s; O8 [! r! ?) q4 e9 ^Analysis of correlation, 相关分析
9 Y) O9 x; l" U6 c% i9 \8 |Analysis of covariance, 协方差分析
. C; _; O* I# k1 s9 p" t2 @Analysis of regression, 回归分析3 y( x y& F+ Q; e8 L0 V* b( i
Analysis of time series, 时间序列分析
$ r. B* ?. f* G, O& xAnalysis of variance, 方差分析
% \) d$ G+ H5 ?# K+ e5 w# V% K1 [Angular transformation, 角转换9 r, k" {' v# W' B. R* k, h
ANOVA （analysis of variance）, 方差分析
' C! w7 e1 I H# l# gANOVA Models, 方差分析模型9 W o$ Q; q! P( L# H8 U" W
Arcing, 弧/弧旋2 p4 N$ |) f/ D7 f
Arcsine transformation, 反正弦变换
( c" _1 k3 `1 i9 H8 Y! \; IArea under the curve, 曲线面积
, C- f2 g: E+ ]+ U6 t% K3 N* IAREG , 评估从一个时间点到下一个时间点回归相关时的误差 9 V- h6 ?1 q: _
ARIMA, 季节和非季节性单变量模型的极大似然估计
0 [" _% O7 f: n& AArithmetic grid paper, 算术格纸
" I+ K; ^# u* B2 k, L4 t6 w2 HArithmetic mean, 算术平均数
* [# S% p3 `5 @Arrhenius relation, 艾恩尼斯关系 a/ A" s) _' U' y8 G
Assessing fit, 拟合的评估5 p: O% |- E! X
Associative laws, 结合律4 u4 E8 S- D. m3 H2 p H
Asymmetric distribution, 非对称分布, k/ g4 |" A. e- y, Y# o: n
Asymptotic bias, 渐近偏倚
: ~) f0 O4 V- B. H2 f8 p0 N+ DAsymptotic efficiency, 渐近效率4 m/ r$ h& x' {+ [/ B# e
Asymptotic variance, 渐近方差
: F/ ]; Y2 \' A/ `# DAttributable risk, 归因危险度5 V1 _* f3 u1 {3 B: d: n* h9 d
Attribute data, 属性资料* y# O6 Z$ Y$ F% E
Attribution, 属性# d. Z8 z; Q W! w3 m
Autocorrelation, 自相关
3 I. e( V$ E- iAutocorrelation of residuals, 残差的自相关; d* N& {( H9 ^
Average, 平均数7 X/ q9 m8 p5 U; W* r; H
Average confidence interval length, 平均置信区间长度
, t% q3 t, b& b, `Average growth rate, 平均增长率- L: H3 R1 n: I1 k6 @
Bar chart, 条形图
% X( s9 g! y6 Q1 yBar graph, 条形图8 T8 P0 M' N3 F8 `0 C6 u. j- b
Base period, 基期2 J* Y j0 D9 j* ?/ C, f9 C
Bayes' theorem , Bayes定理6 C: d0 V, l& G8 ^
Bell-shaped curve, 钟形曲线, d7 L' K9 T4 [) Z& }1 V0 X
Bernoulli distribution, 伯努力分布# Z* P; c; ~- Y/ X& A1 Q
Best-trim estimator, 最好切尾估计量
+ K& i2 }1 s! U- dBias, 偏性
, C b4 S/ s& |' r1 |# X4 UBinary logistic regression, 二元逻辑斯蒂回归
! }- r& T- c) w9 _ I. k) i9 }Binomial distribution, 二项分布 |! g7 r8 K* H9 Z
Bisquare, 双平方, k1 ~ i# l0 N4 B6 e
Bivariate Correlate, 二变量相关
5 L) d6 `4 d- G. f, s3 @Bivariate normal distribution, 双变量正态分布. W& n& |& {0 s, Q- k" {# o
Bivariate normal population, 双变量正态总体/ a5 J/ |. S! }1 j6 d
Biweight interval, 双权区间
1 D& F/ A2 M6 }# BBiweight M-estimator, 双权M估计量: F1 e' G1 y$ B- e7 ~* K D
Block, 区组/配伍组
* }7 h$ g' U7 z" P; ]. @BMDP(Biomedical computer programs), BMDP统计软件包
$ ~/ f: H/ Q/ Z% \ tBoxplots, 箱线图/箱尾图. |3 F3 l+ |8 _2 O* n- P) b5 R
Breakdown bound, 崩溃界/崩溃点" N7 I6 s9 V L4 C5 I* j; s
Canonical correlation, 典型相关) n F6 j' q6 ^) w
Caption, 纵标目
; H; i2 R4 C4 G# r% VCase-control study, 病例对照研究0 S$ q: f; C# c7 ?; t/ I
Categorical variable, 分类变量/ D, z' J) L$ i, N3 q% V
Catenary, 悬链线
1 Y% P" w' h4 b, A' G1 pCauchy distribution, 柯西分布
5 F6 r1 F- J: I2 C% [4 q6 j- r9 p$ c$ XCause-and-effect relationship, 因果关系
8 ^, n8 t$ |; E/ I" R2 LCell, 单元) J' p) O+ z8 `# {! P
Censoring, 终检. P V1 d( i6 [- \" d$ o8 _- v/ v
Center of symmetry, 对称中心
l( C4 Q1 r" p- D3 b1 XCentering and scaling, 中心化和定标# P% j( }7 e8 p6 e+ R. Z, r
Central tendency, 集中趋势
' Q: V* ~. U% G; c8 _& K: l5 K. `9 SCentral value, 中心值" T7 ?8 i; o# u: C
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
" O' c5 @6 |- ~6 u0 J- LChance, 机遇
. R+ K* u( D: |3 j7 q0 ] EChance error, 随机误差
8 g: R2 ~5 A3 I0 Q# ]( u( K7 ?' ?5 oChance variable, 随机变量
: O* C; `1 X% H0 o' vCharacteristic equation, 特征方程
- D6 p4 f: ^9 H7 U; u# J3 k5 t! M- `Characteristic root, 特征根3 e& c# D' k7 N; P7 \
Characteristic vector, 特征向量
# {/ m! |' ^6 B. U$ z/ g3 fChebshev criterion of fit, 拟合的切比雪夫准则* N! T+ n. L* J3 F, I% q
Chernoff faces, 切尔诺夫脸谱图$ b5 W2 g$ S$ F, k1 N
Chi-square test, 卡方检验/χ2检验
, \8 u' [4 L, n* q- Z% yCholeskey decomposition, 乔洛斯基分解) L: {8 \1 C7 r3 v3 M1 u$ K2 a7 w
Circle chart, 圆图 . e/ o9 \ a! O+ x0 G4 n" E9 p& J
Class interval, 组距
; O. k. E+ B' ~/ v9 f, pClass mid-value, 组中值
9 a& V& X3 O/ RClass upper limit, 组上限
' O; W/ e0 ?: _: |9 {Classified variable, 分类变量
7 R! `+ B# j7 QCluster analysis, 聚类分析
! `2 h3 {4 c+ t" lCluster sampling, 整群抽样
3 M. J: z) s& n( Y3 x& O7 d3 [Code, 代码/ o4 O3 E- |1 U2 }
Coded data, 编码数据8 b- y2 ~& {* H* `
Coding, 编码
' g! @' N$ ~- m; [Coefficient of contingency, 列联系数. Q( g9 q: F" S
Coefficient of determination, 决定系数6 M% h5 J8 p3 v* i
Coefficient of multiple correlation, 多重相关系数/ E1 m) i$ |% O' ^+ n* B6 O4 x
Coefficient of partial correlation, 偏相关系数
7 o3 {8 h& \- N1 a- z( m& {# ~7 I' hCoefficient of production-moment correlation, 积差相关系数( X1 u. K; ^; ], n
Coefficient of rank correlation, 等级相关系数) t: W. S% ^# K# @( t! ?# P/ ^5 J z
Coefficient of regression, 回归系数
2 {7 b, X5 v0 ^7 O; r0 W. Y9 u* o$ }. b* F4 TCoefficient of skewness, 偏度系数# q& \, p( u' D- L( f
Coefficient of variation, 变异系数1 K7 s0 P, z* @/ E c/ }
Cohort study, 队列研究
0 i# d9 o4 y9 b2 kColumn, 列
) U4 ]2 ^9 a# rColumn effect, 列效应
) J5 e4 K4 R# NColumn factor, 列因素
4 `* n4 _# D6 d# k: l" gCombination pool, 合并 ~( L! a4 S) b( Q+ E# B7 n* m3 _! h
Combinative table, 组合表# G4 G9 O. E9 W1 W8 ]
Common factor, 共性因子: \: i3 ^& R8 I) S" A# M: m
Common regression coefficient, 公共回归系数
6 P& i5 b- ^+ e4 PCommon value, 共同值3 y4 \# U7 ]! T; a6 t
Common variance, 公共方差
; [4 F% z2 y3 @4 G P/ rCommon variation, 公共变异, c7 j' h# \' m; j( ^' o U( p
Communality variance, 共性方差9 U: p2 m- z/ v. F4 s4 e [$ T9 J- k
Comparability, 可比性3 v7 n& Z2 ^2 j( J4 R4 W
Comparison of bathes, 批比较
4 G/ E# t& S, Q6 G: R! JComparison value, 比较值$ ^1 m- C0 ?, Y( J# _0 n/ l0 N
Compartment model, 分部模型3 \" Y# b/ a: Q
Compassion, 伸缩
* P3 \/ K6 o0 |; l( s4 gComplement of an event, 补事件3 ]$ N2 Z8 J; e B7 Q) L
Complete association, 完全正相关1 s1 |" c; R X7 z- L
Complete dissociation, 完全不相关
) Z& t2 o# l1 u! j# ^* hComplete statistics, 完备统计量
^+ W( I! Q0 b- f5 _7 E6 w) @Completely randomized design, 完全随机化设计
. L1 S8 i, o3 {- w) @0 x. [Composite event, 联合事件
/ c( m4 D5 s) n* Q9 G2 X4 mComposite events, 复合事件1 Q [. O5 [1 I! R( y9 f
Concavity, 凹性& W2 d4 f3 T, R9 V
Conditional expectation, 条件期望
, M+ j2 Y0 S6 h6 _Conditional likelihood, 条件似然
; x( @* S" R0 i/ dConditional probability, 条件概率
+ f4 V# t+ R# y, p7 bConditionally linear, 依条件线性
6 G; G5 h6 \. z" _- ]6 nConfidence interval, 置信区间
3 Z% I3 S% r- ^8 P, }/ \# EConfidence limit, 置信限# V* `# F! y% s- v' t! u/ r
Confidence lower limit, 置信下限
$ B" ^: w& P, GConfidence upper limit, 置信上限# I b/ M' B: ]( |+ C
Confirmatory Factor Analysis , 验证性因子分析! |2 _4 g* s) t) ?) |' `
Confirmatory research, 证实性实验研究) ~! G+ Q" q; _, h- t" f
Confounding factor, 混杂因素
+ U0 ~" U o5 MConjoint, 联合分析
+ y: g4 u' ]& y% v- wConsistency, 相合性1 c9 {6 ]! ^( z- C
Consistency check, 一致性检验
1 M! y5 ?1 t' p: N i5 W" I% l4 CConsistent asymptotically normal estimate, 相合渐近正态估计" \( L9 J( B( f3 |! n* P- D8 Y
Consistent estimate, 相合估计
4 H$ J5 j& g4 @) I o; t5 X+ |6 hConstrained nonlinear regression, 受约束非线性回归% }/ B2 W( G) ~
Constraint, 约束
& H' a2 R2 a" h' LContaminated distribution, 污染分布5 ~8 A% O$ A+ ^' Z' C$ b
Contaminated Gausssian, 污染高斯分布 I3 P _, @4 n
Contaminated normal distribution, 污染正态分布
7 h2 F: L5 |0 `* @9 l1 G; VContamination, 污染4 H- X* V m) m" n: G$ @
Contamination model, 污染模型: G1 {1 X5 ]; c1 t# ]& p
Contingency table, 列联表& W- Z o4 c }; j0 \/ r) ]
Contour, 边界线
* ?% h( i7 }3 a) KContribution rate, 贡献率
) B9 m5 w* l3 e" |+ V5 h- |Control, 对照! L9 J$ C5 A3 L+ i7 R9 W
Controlled experiments, 对照实验
4 R- E8 x$ a: c7 y/ FConventional depth, 常规深度' p8 a; R8 @9 q6 g, ?" e
Convolution, 卷积6 {% H/ ~9 f$ k! x0 ]
Corrected factor, 校正因子2 @# y$ ]0 L# _- u' V
Corrected mean, 校正均值
; Q' @4 \+ A, |4 G% \2 E. BCorrection coefficient, 校正系数
1 f" @7 b1 L D. oCorrectness, 正确性
2 T4 F1 m+ z7 O0 T( [2 P* q( E% uCorrelation coefficient, 相关系数- Z7 Y6 T& [. v+ q/ U8 n8 t
Correlation index, 相关指数! Y f$ n- d$ [- [# R9 s: m
Correspondence, 对应2 r! m; A) s; [3 Q D
Counting, 计数& y7 u, W$ k3 P7 m/ U
Counts, 计数/频数
1 K) o9 _' }' gCovariance, 协方差0 d5 c. o8 ]! g
Covariant, 共变 & m* M( ^0 P. ?; I
Cox Regression, Cox回归
3 j# h9 Q: ~6 b- rCriteria for fitting, 拟合准则+ n$ G5 y" e! }& ?
Criteria of least squares, 最小二乘准则
& i% }5 s' `6 Y0 v3 l2 S9 o' [, jCritical ratio, 临界比, E) ], _, ^7 C7 d
Critical region, 拒绝域
# P8 j6 D: r* F( k, ?! Q, mCritical value, 临界值( N/ r. W# |% i4 H9 C
Cross-over design, 交叉设计
0 Q/ m% ~6 W. `4 qCross-section analysis, 横断面分析
7 f( q; i7 Y- D4 f0 w$ N" F. C7 ~Cross-section survey, 横断面调查
3 i0 o% c2 C! ^+ `# |4 q' c$ ACrosstabs , 交叉表 * f! y4 l ^7 Q1 K: d- n4 @
Cross-tabulation table, 复合表% ?0 k9 {$ B3 _2 O5 G5 \& u
Cube root, 立方根: a( V, i+ ?8 [, H( `6 X* V1 a' I
Cumulative distribution function, 分布函数) ?% c. p& c6 I7 ~1 t- X
Cumulative probability, 累计概率, ~; E6 W: x6 R
Curvature, 曲率/弯曲0 x0 w1 d! y6 \8 j; o2 y
Curvature, 曲率 E _' g+ x( Y1 w
Curve fit , 曲线拟和
* G& {/ [+ F7 U$ V) TCurve fitting, 曲线拟合
" S. k9 X! c0 ]9 BCurvilinear regression, 曲线回归* ~# t+ C0 W" j2 ~2 p& V
Curvilinear relation, 曲线关系
; \9 x+ f) H* MCut-and-try method, 尝试法
) Q, r) V$ N. D" O2 a0 GCycle, 周期: j; H' J3 u# H
Cyclist, 周期性 Z$ W# l {$ \- K: ]& {6 e# V
D test, D检验
4 F. C3 @& N, ]4 `4 x: X! j+ w fData acquisition, 资料收集
N" z( S& b" Z, _1 n2 RData bank, 数据库
8 V0 g. y9 A! v9 U( O2 D% x0 W4 GData capacity, 数据容量
# Q6 M5 Q( Q" r1 CData deficiencies, 数据缺乏7 a' c; }/ ?* n* q' H2 u8 W* L; Z
Data handling, 数据处理4 y* j6 ]% |& A% W
Data manipulation, 数据处理0 a6 t/ g @ R( b/ q
Data processing, 数据处理% r0 }; `# K: |
Data reduction, 数据缩减
) ?- \7 G; f0 s" F* D1 xData set, 数据集
+ h0 y' d0 D" K+ M1 Z1 k5 g B# vData sources, 数据来源1 k& z$ w% s5 \6 U) c
Data transformation, 数据变换0 x; B3 z( V: _/ t. W2 r
Data validity, 数据有效性
# _1 h$ _( q1 Y9 U, g$ @Data-in, 数据输入
8 [1 ?3 {5 w$ q8 ZData-out, 数据输出8 P; Q& d6 _; @/ W
Dead time, 停滞期
( m% N! @, b8 v6 j" m: ^8 YDegree of freedom, 自由度
2 f- y4 Y! I' y- \. V: ~: MDegree of precision, 精密度
3 S, K: t- H; _: `6 Y0 o! JDegree of reliability, 可靠性程度9 Y* Q$ h3 a4 D5 ^4 W6 [" Y
Degression, 递减
/ r/ r7 [3 P+ A( f4 pDensity function, 密度函数
- w( P' P1 i( Q( z9 u$ }) zDensity of data points, 数据点的密度
: |5 S( ^! E0 @Dependent variable, 应变量/依变量/因变量
# y+ q8 a o# n6 `( }! SDependent variable, 因变量
& B, d* l9 e; P0 MDepth, 深度! l% \- M' j) I! I
Derivative matrix, 导数矩阵. v! w" g& k& x& e! P- C: T) {
Derivative-free methods, 无导数方法
, T$ Z; n1 x) C. w; S' EDesign, 设计+ q) K1 v* t2 R- Y' W% Q* a
Determinacy, 确定性" N) j: u& V3 B) s0 A8 ~
Determinant, 行列式+ c* `8 C3 S+ {2 G( k
Determinant, 决定因素
D' _* h# p2 n& |Deviation, 离差
8 j' X+ Z- z3 Z6 D- l0 Q6 j7 aDeviation from average, 离均差 o( L3 N1 y3 M' m, O0 f, C* U
Diagnostic plot, 诊断图* w4 v1 Z4 I0 ]
Dichotomous variable, 二分变量
$ U7 |; C; ~+ ~5 A6 ]" F' K9 G9 BDifferential equation, 微分方程5 B% K+ r, i3 A$ [, F; L# T" |
Direct standardization, 直接标准化法
5 F5 F0 E' H) M3 S7 GDiscrete variable, 离散型变量# {. H) h6 ^. b" X, r
DISCRIMINANT, 判断
# Q/ G2 U. s; Z$ v3 wDiscriminant analysis, 判别分析
9 F0 \% B& M0 Q& Y8 ~/ @* ADiscriminant coefficient, 判别系数
6 t& {4 ^# b( B. m) v& B( J' EDiscriminant function, 判别值
6 \ x- m) z" @ q% vDispersion, 散布/分散度
9 p& ~5 A0 {$ t& B( fDisproportional, 不成比例的
+ k2 W4 J; f" m+ \" S4 q/ d1 d* LDisproportionate sub-class numbers, 不成比例次级组含量0 I) c! G; t6 D7 g3 a. R7 Z
Distribution free, 分布无关性/免分布
0 X1 i/ ]/ z; }9 BDistribution shape, 分布形状- Q5 v. ~0 \ ]* H, h! D
Distribution-free method, 任意分布法& U0 m7 b% k" J
Distributive laws, 分配律
% D9 K8 v( W& S& gDisturbance, 随机扰动项
8 k5 k. L* e% l% \: j% aDose response curve, 剂量反应曲线
9 K" r% N! Z5 q4 z0 T+ B1 H4 qDouble blind method, 双盲法5 |& c4 O, D4 [# W; O8 j' @0 P0 l
Double blind trial, 双盲试验
; Y+ E! {/ P& A2 Y/ iDouble exponential distribution, 双指数分布
: L3 Z0 [+ x; L: \" gDouble logarithmic, 双对数
( {1 y- _" T/ M- y, v% l2 pDownward rank, 降秩
8 Y; z& e8 x4 n8 rDual-space plot, 对偶空间图
; v4 g- l' |$ [, u+ B7 mDUD, 无导数方法; U7 i! G: j, m) j9 t: z( }% T3 b
Duncan's new multiple range method, 新复极差法/Duncan新法5 q, J1 J5 i. A
Effect, 实验效应$ D p% v O' r e+ N0 }
Eigenvalue, 特征值1 R( S1 s" C9 S" N- n- @
Eigenvector, 特征向量
6 Y5 c# l" |/ i" k: y7 DEllipse, 椭圆5 i4 [5 ]% e* B1 }* E7 ~" a, B
Empirical distribution, 经验分布
3 B5 d6 O! I+ CEmpirical probability, 经验概率单位( U- z$ X9 P9 x, S
Enumeration data, 计数资料
2 h" Z) h' e3 _4 w4 lEqual sun-class number, 相等次级组含量
7 a& r% n( b7 a/ D0 q/ kEqually likely, 等可能
% I( b, }( y" K$ v/ J- z# tEquivariance, 同变性
, E1 Z. o$ V) g) v! AError, 误差/错误
- b8 e' e% K! @3 CError of estimate, 估计误差
" j# R" J5 p; l1 R3 N+ }Error type I, 第一类错误7 j3 C2 F' ~6 `* L" {8 e5 I
Error type II, 第二类错误
% a2 `1 Y4 H2 k) s j% v2 lEstimand, 被估量+ }; q# t/ \7 p. d' z& u2 I
Estimated error mean squares, 估计误差均方
% `# Z, s8 {- Y3 C, u2 p4 V( `Estimated error sum of squares, 估计误差平方和" ~, @- h. X u9 I# `
Euclidean distance, 欧式距离
* C% w n1 T1 O: c5 l9 s/ v, OEvent, 事件) d% |# ~# @0 D; O1 k; O6 x
Event, 事件 P6 x! A! P: V5 c* ?6 P2 |
Exceptional data point, 异常数据点" m6 [% X$ T# w+ g
Expectation plane, 期望平面
4 ~; u" g) P! Z* yExpectation surface, 期望曲面& S$ Y0 I4 D$ u% q/ W! p8 k
Expected values, 期望值
5 }+ k, h' g$ ?Experiment, 实验 t/ V, n f' \( k4 s& s
Experimental sampling, 试验抽样* E) w) n, D) {
Experimental unit, 试验单位5 G' z6 h' Q" B8 u" [6 N& b h
Explanatory variable, 说明变量
+ v) ]# I; C& r! O0 o6 pExploratory data analysis, 探索性数据分析# o8 X( ~8 j! E, R) i
Explore Summarize, 探索-摘要
( {) |7 i# M7 [Exponential curve, 指数曲线
$ r" r/ a- Z; ^( l; ?Exponential growth, 指数式增长* o7 U- l2 ^ C
EXSMOOTH, 指数平滑方法 / X; ?, d2 X* ` T! ?6 C) p
Extended fit, 扩充拟合
! k) k) h, m0 @Extra parameter, 附加参数
; A8 f8 B+ }: y- z2 VExtrapolation, 外推法
6 ?: d4 }/ r; |, M( gExtreme observation, 末端观测值
$ B' Q9 d" P$ t) t4 Y* r1 AExtremes, 极端值/极值
5 \- t8 Y. N# L- E, `, S% P' W$ wF distribution, F分布
/ v2 `6 s+ G( A4 z4 [F test, F检验+ _& u, z3 T) w0 C; X
Factor, 因素/因子8 [3 s( F- d% ?* k! u5 [
Factor analysis, 因子分析
9 ]0 L8 r! O( {Factor Analysis, 因子分析0 B* C3 u- M; X ^! h! R7 A
Factor score, 因子得分 / P5 g; I. t1 {% n
Factorial, 阶乘' k9 u2 f; k/ h
Factorial design, 析因试验设计' p( h3 q, ^% _
False negative, 假阴性
( ]% T4 f! _( O3 k- j8 kFalse negative error, 假阴性错误
, m Z4 ~1 f& g4 E+ G4 W! GFamily of distributions, 分布族
' W2 a7 n, [4 F1 }4 a: OFamily of estimators, 估计量族- k3 F- M0 I6 k( N
Fanning, 扇面' X1 B+ J# {3 v8 r$ b4 [( H
Fatality rate, 病死率& s7 G8 z1 J/ Y: c" K
Field investigation, 现场调查* W0 Z. N! W0 ~9 l& I
Field survey, 现场调查
f% y! U# t+ c" @& {( ]1 I+ ~: mFinite population, 有限总体, }: i3 O9 g7 ]$ `
Finite-sample, 有限样本
/ J: N$ M |2 L$ @1 V- H. QFirst derivative, 一阶导数. ?- W6 N" X+ C$ ^2 c" ?7 W8 z0 i# a
First principal component, 第一主成分
4 h: H% o& E0 H2 T* m, g2 b& AFirst quartile, 第一四分位数
4 M) v6 g% c6 x2 \Fisher information, 费雪信息量
) @; K/ v7 ~8 q4 V: m. `Fitted value, 拟合值
( N$ Z9 B( p# U5 w- c/ W9 JFitting a curve, 曲线拟合
0 `& A) @$ |' q) [, t" Z3 S6 }1 aFixed base, 定基' |2 ^4 j1 M$ f, y8 J" a" l5 H
Fluctuation, 随机起伏8 `2 G) P T1 ?7 A# U7 l
Forecast, 预测
6 }1 b; d7 a) mFour fold table, 四格表& h" }5 l( { j
Fourth, 四分点! Z- _* F2 Q4 a7 o* b/ V1 C( P' b( R
Fraction blow, 左侧比率
+ U. Z5 m( P) ~0 r [0 wFractional error, 相对误差
7 Q/ w. [5 y. c7 Q( T$ ZFrequency, 频率
! A- i; R# C S& O$ \Frequency polygon, 频数多边图3 v+ u7 M1 v1 r0 \5 I7 w
Frontier point, 界限点, e) E6 z7 _+ d! `
Function relationship, 泛函关系! |* P9 P% [6 ?& j4 t i7 s3 y
Gamma distribution, 伽玛分布
; o! r: ^9 }7 sGauss increment, 高斯增量/ A5 m1 `) a( D" [+ W3 _* _6 a
Gaussian distribution, 高斯分布/正态分布+ l, q2 x5 `; B/ K& a) `' z
Gauss-Newton increment, 高斯-牛顿增量; _9 u d y S4 f
General census, 全面普查
2 S E0 |6 Q" r" _/ o9 Z8 yGENLOG (Generalized liner models), 广义线性模型
1 `! y+ g0 r+ Z! ?- u* _% l* S; ZGeometric mean, 几何平均数) ]" _0 F8 g6 e) s, ?
Gini's mean difference, 基尼均差
3 z; Z0 G8 [+ w: |GLM (General liner models), 一般线性模型
9 ~" x: m. U$ b7 c# G. sGoodness of fit, 拟和优度/配合度; p5 ?8 A6 O' e- h% I8 z$ j8 t
Gradient of determinant, 行列式的梯度
6 t6 ~' a& {8 \) U1 n1 ~7 sGraeco-Latin square, 希腊拉丁方6 z5 f& H( S9 ]4 M
Grand mean, 总均值; j5 d' v# z. Z# R2 Y
Gross errors, 重大错误
! M/ }/ X3 [; b' v: yGross-error sensitivity, 大错敏感度/ J$ W" z. u, r1 p
Group averages, 分组平均
9 Y! ^# u# G8 n' \. H) tGrouped data, 分组资料
# p! U, p M4 \Guessed mean, 假定平均数8 u# I2 x6 M* V
Half-life, 半衰期6 G/ x* ~! [* B* E: q! D; _" r
Hampel M-estimators, 汉佩尔M估计量5 k% w3 E. Z; G6 x; B& C
Happenstance, 偶然事件
' _- a( W0 `6 Z+ T) [Harmonic mean, 调和均数/ U" a" i; } \1 q
Hazard function, 风险均数
; B, F; D; S* `Hazard rate, 风险率
7 ^7 X( k( w/ ^0 k2 DHeading, 标目
2 p2 T, \5 u' A$ T+ i# s- `0 V* ~/ IHeavy-tailed distribution, 重尾分布
" P: y5 L7 s- E, U! {$ B OHessian array, 海森立体阵, b. \0 J, e( F3 e6 z
Heterogeneity, 不同质
9 i% E$ W) {/ L0 O8 gHeterogeneity of variance, 方差不齐
& J* k7 b) [' R* Z6 Z5 MHierarchical classification, 组内分组/ B7 b5 X) X# p( k
Hierarchical clustering method, 系统聚类法, C, _3 v& m3 H) ?2 C9 N
High-leverage point, 高杠杆率点, h' }3 E# E: I3 \$ {
HILOGLINEAR, 多维列联表的层次对数线性模型
2 M3 \& r k. x! P' {0 yHinge, 折叶点
$ e1 ?$ r' C3 \7 Z0 U( kHistogram, 直方图! V7 x V" @6 D3 C
Historical cohort study, 历史性队列研究 " f# r3 G1 V8 p& r& g- s9 w; L1 Y
Holes, 空洞3 x( V1 ?; q* p. a
HOMALS, 多重响应分析* h" t: }0 Q0 {( D" \6 B! |
Homogeneity of variance, 方差齐性
l0 I- Q5 o. o Y2 h, ?6 @) EHomogeneity test, 齐性检验
6 c& ^" E% r% b- X8 _Huber M-estimators, 休伯M估计量
# t0 e5 D7 W) p. qHyperbola, 双曲线
1 m; d3 S5 A8 C3 n2 Y' d& k5 qHypothesis testing, 假设检验6 q# b! M) }+ m5 f
Hypothetical universe, 假设总体
/ x8 E$ F1 C+ r9 ~; AImpossible event, 不可能事件1 |2 d# i$ v R
Independence, 独立性
$ M6 f; v* {0 E( L. r9 `Independent variable, 自变量1 e% d& B; P$ }2 _
Index, 指标/指数
! j0 H8 s$ s+ y9 WIndirect standardization, 间接标准化法9 R6 B9 g, l m4 l* N
Individual, 个体
- E! J) G# W4 xInference band, 推断带
H6 k9 a6 R5 _3 M4 [* iInfinite population, 无限总体
! [) u8 T: I# ]. G# l& `1 @) y" rInfinitely great, 无穷大
$ g: d3 w7 _. nInfinitely small, 无穷小
% x& z) |. n; h, |! `$ EInfluence curve, 影响曲线
! D4 p* @# X8 H8 n( d7 o, j T4 M" xInformation capacity, 信息容量" }4 ?% s0 o( @. ^
Initial condition, 初始条件
3 I4 s, h5 F& q. aInitial estimate, 初始估计值- g- Y1 Y+ @" w7 F( {
Initial level, 最初水平
' N" a6 f4 q! v$ dInteraction, 交互作用1 ^/ H, r- N5 d
Interaction terms, 交互作用项. ^- v! L+ L F
Intercept, 截距
# }3 h7 O5 l, [9 {6 h. V4 z0 PInterpolation, 内插法- f$ J s" a1 A4 L+ H- N
Interquartile range, 四分位距
# V& |) z- [& z0 z0 M- C& pInterval estimation, 区间估计# H5 L' y& G" \( s. Q- C0 w" o& m
Intervals of equal probability, 等概率区间6 z& j! E' @( E" M) t
Intrinsic curvature, 固有曲率# b/ h6 b, _6 R5 z1 Y; k
Invariance, 不变性
( n3 V& g+ @2 R+ u& k. z* OInverse matrix, 逆矩阵! \' |3 n- Z7 w9 o; ]
Inverse probability, 逆概率( G2 }8 }4 A! ]/ |; G
Inverse sine transformation, 反正弦变换
6 ^1 L9 H2 p, t6 W T2 aIteration, 迭代 * {) D2 U9 x: w5 p$ N# E
Jacobian determinant, 雅可比行列式
4 L% ? Z9 k( U* p( T6 S7 AJoint distribution function, 分布函数
% R/ H/ s" z# v- k. Y, |Joint probability, 联合概率/ V+ s9 l* \/ w# g# S5 W
Joint probability distribution, 联合概率分布
" h% n2 m) L5 o9 W2 `( v3 @4 D* vK means method, 逐步聚类法* o1 b7 ]+ J* z/ D! B: Q
Kaplan-Meier, 评估事件的时间长度
8 J# r" V6 O* k2 O& @. ~1 Y H8 UKaplan-Merier chart, Kaplan-Merier图6 Z, F" u$ ?8 x5 n/ w( g! Y; r
Kendall's rank correlation, Kendall等级相关1 V6 K X) B& W- z; [
Kinetic, 动力学5 h; N; `+ I( N1 J1 w8 d- `; S: t8 N
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验* o9 Y2 U% w0 O9 ?
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验" I8 a; p" G8 r, o' ~
Kurtosis, 峰度# ^/ |/ x: s. }8 J9 X, R
Lack of fit, 失拟
- a( S0 e7 [7 f6 r9 |8 BLadder of powers, 幂阶梯
( ~0 ?5 u" }' X4 n' ]Lag, 滞后" `$ Z5 V# Q+ [2 h/ v8 S/ l
Large sample, 大样本3 `6 z. I" e, @ g/ ]# B: F& D
Large sample test, 大样本检验
$ z! z! ~/ v" H9 V7 NLatin square, 拉丁方8 X% m! L! {' M4 w* X1 @5 U
Latin square design, 拉丁方设计$ W/ `" I* o j6 B8 O
Leakage, 泄漏 H( E- E4 k, h* N. Q9 h
Least favorable configuration, 最不利构形4 a1 u) D% E j
Least favorable distribution, 最不利分布0 O# n5 @) C' t2 h/ Y# ]- M* r
Least significant difference, 最小显著差法
9 H- ~% }1 ?6 v9 p3 F5 H- bLeast square method, 最小二乘法
3 L7 ~0 f2 l! dLeast-absolute-residuals estimates, 最小绝对残差估计
% e, `3 i. r9 gLeast-absolute-residuals fit, 最小绝对残差拟合) p9 D; ^. a- r; m1 i; E8 ~
Least-absolute-residuals line, 最小绝对残差线 I4 f& z5 c; Q" C
Legend, 图例
, E% L$ H0 M$ B) m' U( T1 I# Y9 KL-estimator, L估计量
. n0 Z5 G6 A2 N3 M1 o, C7 Q1 x% SL-estimator of location, 位置L估计量( Z, y8 `! r# `+ j7 B. W
L-estimator of scale, 尺度L估计量4 D! b. W* G3 K5 ]' g
Level, 水平/ e% [9 D1 O. d$ B
Life expectance, 预期期望寿命
9 G' b1 C; S7 J$ wLife table, 寿命表2 U4 z1 o6 H# s1 B1 F% Z
Life table method, 生命表法
9 Y" F$ l, y! K- tLight-tailed distribution, 轻尾分布
8 W: g8 j2 t! E; E& A( lLikelihood function, 似然函数( u6 ^' n% @' ?5 M, ^) @" G K/ A
Likelihood ratio, 似然比( i! g7 E$ t2 w0 c8 m0 Q" Y
line graph, 线图- i, I9 j" ?1 F2 d% n+ C
Linear correlation, 直线相关. s# E. r9 A/ n2 F$ v7 l6 X
Linear equation, 线性方程
. Q# J9 C( j3 m1 H( MLinear programming, 线性规划9 _; a9 [+ ]' y; I
Linear regression, 直线回归
9 J0 k: B. G/ Q, `; _0 LLinear Regression, 线性回归
7 v) t8 j, z( J: t$ E n" Z8 eLinear trend, 线性趋势
( v+ a( g K7 O- v1 {3 I% \Loading, 载荷 . a. e/ N( Q5 ~2 L1 m% T; c
Location and scale equivariance, 位置尺度同变性9 z# Q# Z: N. C, `/ A
Location equivariance, 位置同变性
2 p9 j; ]- f( P& L$ d* a7 tLocation invariance, 位置不变性. F% B+ Z! d( c% S
Location scale family, 位置尺度族
7 Q' g: M9 a* D7 ~3 D# [Log rank test, 时序检验 - \, q0 S8 t4 n+ f' d
Logarithmic curve, 对数曲线
# S! n& c% f2 L% g8 yLogarithmic normal distribution, 对数正态分布. q2 f- }4 i6 g2 n5 d
Logarithmic scale, 对数尺度; @+ F% |+ r# q; f0 `3 }( q
Logarithmic transformation, 对数变换
; m. q- o% D8 m; K/ ?; j$ H' TLogic check, 逻辑检查0 F E! B* v- e' j
Logistic distribution, 逻辑斯特分布
1 I5 j6 O8 ]5 b* y) I3 l# sLogit transformation, Logit转换' O0 |5 m8 r. L/ S2 Y$ q. P1 p7 |
LOGLINEAR, 多维列联表通用模型
1 g3 L( K# }$ h$ ]6 M, e; D7 ~8 gLognormal distribution, 对数正态分布
% m" Z- Y: I3 Y, A, SLost function, 损失函数
! d/ j' I7 g' }2 }- n- bLow correlation, 低度相关 X* Z) C: c# h1 \; T2 @# R
Lower limit, 下限* Z9 \$ Z: n6 E8 U2 G
Lowest-attained variance, 最小可达方差; O% r% U R$ T- ?+ E
LSD, 最小显著差法的简称( q9 W$ [5 `. t2 w8 y7 E' L
Lurking variable, 潜在变量
! Z# M/ Z4 Y; ]5 J. z5 bMain effect, 主效应, L5 m: ]6 q" M; _
Major heading, 主辞标目( Q) r1 F4 z8 ^5 }6 L4 E( ?& C
Marginal density function, 边缘密度函数" ~% h E: O6 R9 g! \( Z2 ?
Marginal probability, 边缘概率
1 X- I( j) j, \& Q# o2 Z" dMarginal probability distribution, 边缘概率分布 C. l1 M' c4 v9 w
Matched data, 配对资料
8 v" { t+ S; {2 S0 nMatched distribution, 匹配过分布& C! P/ P6 g* S. E8 J
Matching of distribution, 分布的匹配
5 @" X! P9 H3 {2 [' F: ]8 XMatching of transformation, 变换的匹配
" f3 p ]' ~$ {# y- JMathematical expectation, 数学期望7 C% i+ l8 k, Z
Mathematical model, 数学模型
+ h+ H7 _& r3 |! s* Y) T1 JMaximum L-estimator, 极大极小L 估计量
7 o: Z/ U- I" A+ d# C; i0 z. TMaximum likelihood method, 最大似然法
' k' b4 ?( O7 o& }Mean, 均数$ }5 z$ H' O0 ^2 T( n2 I
Mean squares between groups, 组间均方( U! |3 Z7 [' u, r: K
Mean squares within group, 组内均方7 ^1 u& u# H$ v7 H# ^
Means (Compare means), 均值-均值比较0 p3 L- _( u' ~- p- r u4 `8 ]
Median, 中位数
$ t4 p9 C! }9 x8 O1 x# a+ d! _. uMedian effective dose, 半数效量
* t4 s$ k2 ?" M9 a* j! d4 I; i9 NMedian lethal dose, 半数致死量
" z1 k' X9 ]9 N: g# ~$ rMedian polish, 中位数平滑% i" q. [7 L- O# T. c
Median test, 中位数检验 m, {3 z' E% p+ ]0 ` }7 z
Minimal sufficient statistic, 最小充分统计量 t$ x0 \. j# p
Minimum distance estimation, 最小距离估计" m& Q3 {% L2 u" [
Minimum effective dose, 最小有效量
: H: @; m# n- E9 {; WMinimum lethal dose, 最小致死量; O a1 z$ l+ x1 O6 _; w" \+ M, I( r
Minimum variance estimator, 最小方差估计量& n8 } p) h& a
MINITAB, 统计软件包) p4 ?2 a- l2 @
Minor heading, 宾词标目
! A' _5 N; J4 x5 O: dMissing data, 缺失值
& s3 ` M# T3 J6 z7 F4 gModel specification, 模型的确定
$ v$ M% U$ c4 zModeling Statistics , 模型统计
% K) P- n. }! f, JModels for outliers, 离群值模型. C% K6 O* y8 L- F
Modifying the model, 模型的修正
1 m: t; E# s. e" @Modulus of continuity, 连续性模# B( W, h) y/ ~5 k. J3 [7 P: G
Morbidity, 发病率
2 I2 a, D! Z/ S& ^* o3 i9 G* s3 DMost favorable configuration, 最有利构形
$ C* L& F* m: s$ T. I8 }# WMultidimensional Scaling (ASCAL), 多维尺度/多维标度
: @" }, K$ l A9 X0 \+ @4 Y8 sMultinomial Logistic Regression , 多项逻辑斯蒂回归, d. `9 k8 p2 u9 T$ s% [
Multiple comparison, 多重比较
; b, e2 v9 `3 u1 l# F2 uMultiple correlation , 复相关5 z, L8 B2 F3 j! W( i1 P
Multiple covariance, 多元协方差/ x; b% n! G) Y! t
Multiple linear regression, 多元线性回归
( w6 z! j& c8 A8 e! n" oMultiple response , 多重选项# r9 |* s$ u) U3 u' q) _# Q
Multiple solutions, 多解2 | B) I& e: f3 |
Multiplication theorem, 乘法定理
4 Z" @3 P. { FMultiresponse, 多元响应
7 T% a8 ~. J2 `& j) H8 `Multi-stage sampling, 多阶段抽样6 Q( t- a) y0 N9 R8 n4 S
Multivariate T distribution, 多元T分布
- m) X* _8 N1 D' ]5 g0 _Mutual exclusive, 互不相容# ^/ {1 J% X; \, C# X p$ e
Mutual independence, 互相独立
" ?0 t1 H1 C eNatural boundary, 自然边界
0 K5 c8 {6 Z- y Y4 YNatural dead, 自然死亡/ L% v8 l' K( _+ h
Natural zero, 自然零
* z# G" r6 e2 H+ U2 h/ F" SNegative correlation, 负相关
2 `2 A% t$ C4 v) ^& b/ UNegative linear correlation, 负线性相关
; Z# T6 U# ~8 m* e& ^8 QNegatively skewed, 负偏
" `7 q8 b0 b0 J( L+ lNewman-Keuls method, q检验
% [# B4 `' |" A+ DNK method, q检验
- p, u% t6 c7 M; O+ h9 P8 u/ m6 `! ONo statistical significance, 无统计意义: x. A* G6 V! M% y( ~. `& {
Nominal variable, 名义变量7 Y+ ~& z* p- [( m8 X% J, ?$ t" p
Nonconstancy of variability, 变异的非定常性4 [7 V1 K% D. Q, {
Nonlinear regression, 非线性相关. h4 u$ U0 q$ [+ l# E0 w
Nonparametric statistics, 非参数统计
5 \6 a/ x2 @6 w( ~8 P3 f, h" |, _/ UNonparametric test, 非参数检验( S, S. x4 t$ S- P4 ]5 S5 Y! n' d
Nonparametric tests, 非参数检验
) C; ^: B1 M2 ^% s, V5 aNormal deviate, 正态离差
6 j$ R$ ~& S1 m; E/ v- \Normal distribution, 正态分布9 B$ r8 {! j! b
Normal equation, 正规方程组
2 t9 ?4 J- o2 y* q9 A( Z: WNormal ranges, 正常范围
' d! D+ w; I! u$ z9 E" {! ?Normal value, 正常值
! K. A% w+ P2 ]; v6 L+ C/ o- }Nuisance parameter, 多余参数/讨厌参数6 F- \, ], k5 F) Q3 U
Null hypothesis, 无效假设 " l/ r' {2 ?9 r" c3 M ~0 S/ e
Numerical variable, 数值变量
* m9 ]% V- _* G& o# v8 qObjective function, 目标函数1 C: p- l, w. M
Observation unit, 观察单位- @" K, O+ S. E* t. c' R
Observed value, 观察值
* ]! ^ S& w, V- X1 j9 ^One sided test, 单侧检验' s4 i* z% M! c) F: f3 M3 S
One-way analysis of variance, 单因素方差分析
7 | M( y4 ^; E9 tOneway ANOVA , 单因素方差分析3 U) f! ^, H `- P. x7 p
Open sequential trial, 开放型序贯设计
1 n0 n8 |6 u% \( j1 l$ {3 G1 dOptrim, 优切尾) W* C0 f& }, i, y- ]6 A9 m( O
Optrim efficiency, 优切尾效率" \4 V* ~" s5 Q- B
Order statistics, 顺序统计量 Z/ o, X5 r6 ?3 z
Ordered categories, 有序分类
' N& o( x! l+ Q; W* f0 {, |4 ]Ordinal logistic regression , 序数逻辑斯蒂回归, c' F) S4 m' B9 U
Ordinal variable, 有序变量# v0 h7 p d( ]3 r+ }+ |/ t
Orthogonal basis, 正交基1 q+ R8 Z5 a# a1 x1 P- L3 Y
Orthogonal design, 正交试验设计
* b' q9 g" e/ t/ ]7 y% dOrthogonality conditions, 正交条件% ]- }/ B& O" N5 i
ORTHOPLAN, 正交设计 0 G: A% Q; E9 C4 |- A( S
Outlier cutoffs, 离群值截断点
' {, f6 p* D9 J: R; J) VOutliers, 极端值
0 p: N$ X5 s3 c a. MOVERALS , 多组变量的非线性正规相关 ) m9 ?" t1 M( o* C: Y) A" E
Overshoot, 迭代过度
: A( M9 N# \9 APaired design, 配对设计
6 G! c) y& |& z1 OPaired sample, 配对样本7 g' V3 Q: C- t2 C; T1 t9 A
Pairwise slopes, 成对斜率* b0 Y2 }2 ^& c4 o6 N3 I
Parabola, 抛物线' E/ k" l$ x" z w: a) @' t* a# Y
Parallel tests, 平行试验, K2 v( }" s6 u7 G
Parameter, 参数
2 Z/ E/ H4 Y L' A# N; ~Parametric statistics, 参数统计' T9 A4 m( ^6 M- c9 \% S9 B0 h
Parametric test, 参数检验
; o) a: P4 G, C! Y: E8 d( sPartial correlation, 偏相关
6 ~# I; p9 l4 Q* m- O: APartial regression, 偏回归
6 j. a& \( R7 `; LPartial sorting, 偏排序/ a0 M2 K# Q) H/ K `9 k) P
Partials residuals, 偏残差. G. g w+ v2 E$ a) j
Pattern, 模式1 }4 I* |0 i0 c, Z5 p
Pearson curves, 皮尔逊曲线8 ?5 ]( Y5 O4 u1 _0 C8 g
Peeling, 退层3 V; ]2 R6 [- M5 Q1 u! E R
Percent bar graph, 百分条形图' x$ P$ M1 ~* v2 J- ^
Percentage, 百分比0 i0 b# A7 r: O; {+ v: V. A4 W
Percentile, 百分位数2 w0 ?! C5 ]7 ~$ E& {+ I
Percentile curves, 百分位曲线* J) Z, A! j7 X5 z/ j
Periodicity, 周期性
3 t4 V" D/ o& @" ~( }+ |Permutation, 排列. c" n3 i" E# {4 Q1 l9 O8 R
P-estimator, P估计量( H5 y9 T* p7 R" t
Pie graph, 饼图0 W/ A) p* {2 r+ ~. B2 z/ Z% G
Pitman estimator, 皮特曼估计量4 F# u+ i' ]3 S. [3 I
Pivot, 枢轴量; y; [4 _: S7 j; f( v
Planar, 平坦
( e3 N% X, m. ]1 z6 i5 WPlanar assumption, 平面的假设
6 O. g1 `/ V/ iPLANCARDS, 生成试验的计划卡
' U6 L0 `2 V0 |" FPoint estimation, 点估计! `- o) I6 D: J- a
Poisson distribution, 泊松分布
1 ^% h( h$ c5 e( LPolishing, 平滑! Q" S* D1 S1 g; J
Polled standard deviation, 合并标准差
8 C3 J) h |! m/ ^8 X' c6 PPolled variance, 合并方差. \. N5 j( e! {- u
Polygon, 多边图
9 R/ Q$ q/ h& _. M" q) _6 kPolynomial, 多项式
9 W& s4 e7 I& m, jPolynomial curve, 多项式曲线, m/ e/ i0 ]% i6 `: E
Population, 总体
) J0 G9 d7 P5 c4 xPopulation attributable risk, 人群归因危险度+ s: a2 c: P) s: X. `# Y/ g* {9 ~ t
Positive correlation, 正相关- U9 A0 O" C" p6 O8 `8 \3 K! F
Positively skewed, 正偏9 y2 W0 J6 o% F1 M
Posterior distribution, 后验分布- S c) {: r6 b* P$ N
Power of a test, 检验效能
n* c, W. }/ r4 PPrecision, 精密度# F. t2 G: b& i* Z' ]
Predicted value, 预测值
# v+ }0 o0 X5 `! PPreliminary analysis, 预备性分析% J8 a3 a0 z# S' Y- ^: c
Principal component analysis, 主成分分析 F5 J- u Z; Z. _3 S. y
Prior distribution, 先验分布# y- K8 A( O! j4 Z& s
Prior probability, 先验概率
. ?/ u4 F% [( EProbabilistic model, 概率模型
& P" `6 A+ n4 E# l0 a# F9 ?probability, 概率
; I- k) {( @3 N) Y) n* N; Y! a8 {: PProbability density, 概率密度
t3 d9 k& P* [) [3 w1 |9 ]Product moment, 乘积矩/协方差
4 {; U0 I! n- P- u8 r$ _/ C5 RProfile trace, 截面迹图
5 ?; ^% R* U, t8 F1 a' G2 HProportion, 比/构成比
8 `6 ~! s! y5 |, N: S Q: bProportion allocation in stratified random sampling, 按比例分层随机抽样4 P! Z; ]) T* q: h
Proportionate, 成比例
) g4 I. c: D/ R0 h5 RProportionate sub-class numbers, 成比例次级组含量/ z g! g$ @& T4 c1 m) z F
Prospective study, 前瞻性调查
; B$ y7 d- v5 o& ]Proximities, 亲近性
0 t0 n- \/ ]" M. u3 a( D' jPseudo F test, 近似F检验
1 H& R( O' {5 y/ u3 v ~& SPseudo model, 近似模型
4 i) r( B3 A% c, `Pseudosigma, 伪标准差& z+ a: }0 E. ]' |
Purposive sampling, 有目的抽样
. a+ L( k4 a- A& HQR decomposition, QR分解% {- {8 @+ [, R: h a- F$ L
Quadratic approximation, 二次近似
5 z; m; } g5 F0 b4 UQualitative classification, 属性分类
1 i9 X/ _/ [* _; AQualitative method, 定性方法
7 V8 {; `3 @, M. E S* lQuantile-quantile plot, 分位数-分位数图/Q-Q图4 [5 Q4 i: ^$ T$ ]' O
Quantitative analysis, 定量分析
+ F: N* F0 R2 q9 p- MQuartile, 四分位数9 u$ A' A! J Z. V* f! N- ]
Quick Cluster, 快速聚类! g$ s' g n( t6 c V& }, C
Radix sort, 基数排序
; T! I; C; R S9 h0 |- ORandom allocation, 随机化分组
& U( k1 [" j8 w; u* w) xRandom blocks design, 随机区组设计
2 P7 x5 @( l% f, x# rRandom event, 随机事件
6 ?4 Q) e7 s1 G9 U* L% O8 MRandomization, 随机化6 w7 T8 V" k: g7 {" H) L9 J/ V
Range, 极差/全距
& C9 ] S8 y A- y- \Rank correlation, 等级相关4 Z5 q! ^/ I4 E
Rank sum test, 秩和检验
, }! Q( |& g) PRank test, 秩检验
) X2 L+ K. A% c$ V, FRanked data, 等级资料( z# M) a8 ?/ w2 o6 f
Rate, 比率
1 D6 @- B0 C+ ?& mRatio, 比例% A4 U& k. B% J8 `' z3 x. E
Raw data, 原始资料
2 ~! W, d `0 x7 ]& s% b9 p8 t4 x2 lRaw residual, 原始残差
& a: T7 n7 n% ^& J: \Rayleigh's test, 雷氏检验
. m+ n8 }% q9 C* A) A1 I% i1 }Rayleigh's Z, 雷氏Z值 " [; C4 F/ {1 r& y
Reciprocal, 倒数' x5 z; j+ k, M% l1 e
Reciprocal transformation, 倒数变换
% R0 ]3 p4 l1 R7 e* b4 y0 aRecording, 记录$ l9 v- K! @; s, I8 {
Redescending estimators, 回降估计量
1 A: O1 n+ F" T* MReducing dimensions, 降维
! p$ T8 v4 `, {7 J5 g7 V6 Q# _Re-expression, 重新表达
1 j% c5 i0 I2 Z' D9 e7 d# wReference set, 标准组+ b% }+ ? I6 S# N* o
Region of acceptance, 接受域' ~; X H- ~- N' ]; k
Regression coefficient, 回归系数
7 f: J, t7 T3 Y r5 G' b" V( P4 v! YRegression sum of square, 回归平方和
2 F2 P. [- S" J+ B* WRejection point, 拒绝点0 x! i: `8 M/ j! D4 b( s2 [% ~
Relative dispersion, 相对离散度
6 R0 a0 F' M' P3 y6 x7 V0 F' t$ MRelative number, 相对数
0 J, L# x; c& s+ n' |" \6 xReliability, 可靠性, u7 A" `7 `, }7 \3 `6 q- O& O
Reparametrization, 重新设置参数
% O# D F3 `9 b) x6 c; p1 [0 A+ aReplication, 重复
1 q; d, G" K; I# Q' ?& aReport Summaries, 报告摘要
# [* W6 l) z1 @) lResidual sum of square, 剩余平方和
5 F' {" I" s$ y LResistance, 耐抗性
4 \$ F; [1 F: ?% B7 RResistant line, 耐抗线
$ K4 r3 ]& c# c* |( s4 BResistant technique, 耐抗技术4 `( a8 [6 ?( K ~! |+ I; u- q7 @
R-estimator of location, 位置R估计量1 G- N: j! L: o% p
R-estimator of scale, 尺度R估计量$ H# ?$ r3 B, S/ X. w
Retrospective study, 回顾性调查
( P; {! h8 f( p3 ^2 iRidge trace, 岭迹
8 ?! R/ l8 I# T* w" E: YRidit analysis, Ridit分析
) d( `; X4 q& ORotation, 旋转
6 H' d( v# ~/ m+ f' P9 v$ \Rounding, 舍入% I Y3 x) p( i$ q8 R
Row, 行0 p% y' S: k* N% f/ P1 N
Row effects, 行效应, l0 V6 c( n4 Z5 H% s4 [ _
Row factor, 行因素# X: U, F7 @" \8 L. R% X; _$ F1 X
RXC table, RXC表! \" q7 Y$ T" I2 O$ c
Sample, 样本9 _: B+ t; H: @, C, V! _6 y/ M+ s
Sample regression coefficient, 样本回归系数0 X' q- f# Z( ], S7 O
Sample size, 样本量# |1 o/ \; C6 Y6 {( x! G
Sample standard deviation, 样本标准差: L) T& _+ B$ i0 M9 B" F
Sampling error, 抽样误差. ?0 z' p" F, W8 m5 S
SAS(Statistical analysis system ), SAS统计软件包
! P2 J7 }) a/ q+ hScale, 尺度/量表6 a. H4 F# a5 {
Scatter diagram, 散点图3 w! d; K+ @' f6 R6 a, j, z% M
Schematic plot, 示意图/简图
/ Q% }. d4 {# n V5 m& `; ?Score test, 计分检验2 N& m" |( G- r
Screening, 筛检
9 Y" G* o" v2 O% h3 D- Z# H* qSEASON, 季节分析 2 O" A2 s+ H: L0 v
Second derivative, 二阶导数
* x: d; Q; m4 c( dSecond principal component, 第二主成分
: o) K9 k5 i0 v0 k2 \) @SEM (Structural equation modeling), 结构化方程模型 / C3 J# m) J6 i
Semi-logarithmic graph, 半对数图
: K1 w9 ~" B' s8 ASemi-logarithmic paper, 半对数格纸 [) o: w+ M6 J, z, c
Sensitivity curve, 敏感度曲线0 ?4 a! c% g, f ~% ~. k) {+ S* g7 R
Sequential analysis, 贯序分析
4 y/ u) A" D" ~) g+ F7 eSequential data set, 顺序数据集3 s k+ e/ G/ @
Sequential design, 贯序设计( S# D& l4 r" A% M
Sequential method, 贯序法
% C3 A' L8 m& y( I1 JSequential test, 贯序检验法
# K3 e1 e, J9 w4 X6 jSerial tests, 系列试验9 {! z# ^; G7 A9 z3 l0 M
Short-cut method, 简捷法
3 _- K/ C5 q5 u/ X vSigmoid curve, S形曲线
- Z0 s2 P6 U x8 l- F: L3 N3 ?' a$ {Sign function, 正负号函数5 i2 Y% G: k* {$ o0 l3 l& J0 T' p
Sign test, 符号检验# j5 w+ Z' }3 \! i
Signed rank, 符号秩
/ }, Y+ O0 m' q% r# S* Q3 r/ E* RSignificance test, 显著性检验- Z' z4 z1 K8 Y6 {3 R
Significant figure, 有效数字# A1 d0 [% {! ?
Simple cluster sampling, 简单整群抽样/ t: \ M- s7 H4 t& w2 s" `
Simple correlation, 简单相关
# t2 i K* m0 qSimple random sampling, 简单随机抽样0 F2 H3 s [) b1 | i
Simple regression, 简单回归
/ L; n9 x+ v& ]& K/ J$ lsimple table, 简单表
7 I" G) U# j& E s0 D: ~* _+ G2 PSine estimator, 正弦估计量
: X1 Y% m% u( RSingle-valued estimate, 单值估计( e+ f$ h, w8 W" J" f
Singular matrix, 奇异矩阵
8 y! @4 \4 ?" Z9 |Skewed distribution, 偏斜分布
4 M$ L. f P: ]2 P- ]4 sSkewness, 偏度
9 A" T* Q$ V4 ~/ QSlash distribution, 斜线分布$ p) r/ C: e5 G7 D k5 y" k9 }2 [' K
Slope, 斜率
@+ s/ {, B6 p( ~Smirnov test, 斯米尔诺夫检验
( z0 e. F* A0 w, z( o7 nSource of variation, 变异来源
1 q6 n/ J: V; }* }1 X5 m O' @Spearman rank correlation, 斯皮尔曼等级相关
9 L6 o. E. D9 J# ?Specific factor, 特殊因子) [6 e/ N* m5 j7 H5 l- U) |4 Z
Specific factor variance, 特殊因子方差3 Q! g9 Y3 i) g- t9 w+ `
Spectra , 频谱$ S" w% Z3 ^- I. S7 W
Spherical distribution, 球型正态分布
4 z ` [. |0 w- U' QSpread, 展布 ?! n2 _ m+ v7 c! o2 b& x
SPSS(Statistical package for the social science), SPSS统计软件包
5 B8 M+ E, ^5 wSpurious correlation, 假性相关, P5 e6 w4 J3 w x) B
Square root transformation, 平方根变换
# e% `0 K) j8 u. k+ Z k- e$ sStabilizing variance, 稳定方差" R6 j" S) `8 E$ s3 y+ B; k* F2 n
Standard deviation, 标准差( i/ f; Z/ Y0 H& \4 T& w' t/ m5 N7 K0 q
Standard error, 标准误" {* u ~5 C0 G
Standard error of difference, 差别的标准误* g$ w# ~' g: ?- D) s' d% |
Standard error of estimate, 标准估计误差
0 g: k4 r- T: W- }Standard error of rate, 率的标准误
w: K5 A3 Q. }7 }. M3 }( \Standard normal distribution, 标准正态分布0 X9 y) U2 @1 v7 M* D# w2 D
Standardization, 标准化6 N1 k1 z8 y+ {" a1 M1 o1 |
Starting value, 起始值* V3 }+ u( X7 _! m3 O' I" N% r6 J
Statistic, 统计量
5 U5 Z* K( b2 m( WStatistical control, 统计控制3 h V, F: e( ^/ ?$ L2 E' K
Statistical graph, 统计图
5 o9 v0 H ?- Z9 ~+ U6 T5 M4 zStatistical inference, 统计推断
4 q2 x4 R0 x& n6 w, Q* i0 CStatistical table, 统计表, M5 R0 r" S( S: V/ q% c: b
Steepest descent, 最速下降法8 e5 P" L, c5 O3 Z1 A
Stem and leaf display, 茎叶图
# ~2 `+ L7 r; u7 [0 Q( ]3 ]Step factor, 步长因子
1 Y, O* D- q( Q6 N' LStepwise regression, 逐步回归! K4 T+ Q. l4 K4 P
Storage, 存0 {; A6 c8 {8 K2 |9 V% J% r
Strata, 层（复数）# V1 S; R: }% v2 L! B6 | o( u; a# E
Stratified sampling, 分层抽样; G2 G3 v/ X1 {3 Z# A/ X
Stratified sampling, 分层抽样
1 `8 ]3 O- p1 H; \9 Z, I3 eStrength, 强度( z6 {* q$ O4 G
Stringency, 严密性
, [5 u$ p \* I2 ]9 c6 _$ l: {2 K1 F: UStructural relationship, 结构关系- I& ^& G3 V: K) O0 Z8 q7 Y4 t
Studentized residual, 学生化残差/t化残差
- G1 f& h$ Y( mSub-class numbers, 次级组含量8 a N3 f8 C7 j8 S; A
Subdividing, 分割0 ?2 f% D1 q0 U
Sufficient statistic, 充分统计量, b0 Y& B2 @ v6 h
Sum of products, 积和6 C/ `0 _5 l* f3 r2 C6 _" O6 T
Sum of squares, 离差平方和
( |+ k# Q! A9 a1 Y2 GSum of squares about regression, 回归平方和
( x5 j# ?) g8 dSum of squares between groups, 组间平方和; Z2 H2 l( A% C; J! m* ~
Sum of squares of partial regression, 偏回归平方和
4 U' O( ]4 r5 NSure event, 必然事件
) N& q( \4 x& v/ s1 JSurvey, 调查
% }) ^1 B) p7 G: p6 b# z7 SSurvival, 生存分析
: h3 ?$ ] _! U, B2 p) z! z* G: vSurvival rate, 生存率8 [' [, s% c# H2 v/ M9 }
Suspended root gram, 悬吊根图# F9 T# D8 ~9 q6 f+ q# P
Symmetry, 对称: x/ y/ N" Q6 M- v) c0 q8 k
Systematic error, 系统误差
, |4 Q/ v, t( x# r& E8 s; MSystematic sampling, 系统抽样
p9 y; X# ? G/ ATags, 标签
5 }+ E/ e( K$ ^7 N5 z( gTail area, 尾部面积
2 \+ G9 I9 @5 T) gTail length, 尾长
" B0 g) Z6 r1 N5 T ]# S( aTail weight, 尾重8 G" i4 L! ?5 f4 \$ _
Tangent line, 切线$ j0 x5 z$ s' ?$ M2 M. X
Target distribution, 目标分布
% M( w; q' R2 wTaylor series, 泰勒级数
' r- p: { |1 J0 V6 sTendency of dispersion, 离散趋势
4 O0 I1 {8 ?$ CTesting of hypotheses, 假设检验3 x2 C7 ]1 I7 ^' w- B8 E
Theoretical frequency, 理论频数
% I0 s3 ?! j5 g% u* F7 d) V) ~Time series, 时间序列
6 m* x6 z8 D/ t( ?/ y% a2 b, BTolerance interval, 容忍区间$ q" g4 Z' T. f0 {6 p
Tolerance lower limit, 容忍下限7 [ d" L' D# B0 D; R5 u' J$ n
Tolerance upper limit, 容忍上限" U$ A% v. I) ?
Torsion, 扰率
+ V$ f# `/ n- X3 t. U* kTotal sum of square, 总平方和9 E$ @; S7 G. o) r9 R2 [
Total variation, 总变异* E5 r( k5 ^3 L" e% R( Z% Q# B
Transformation, 转换9 G$ x* K% z1 J7 r( h( l$ I g
Treatment, 处理% J# g% J# b3 g
Trend, 趋势
" B) b$ {# B! `% e8 B& ETrend of percentage, 百分比趋势
+ L( ~' t6 v+ F/ I; v2 s, p& FTrial, 试验
& C( d/ n% ?" i% Z- B( s' hTrial and error method, 试错法8 y+ D- `) V% p
Tuning constant, 细调常数; x3 T7 \4 R! F$ E, E3 u) w$ G# F
Two sided test, 双向检验
/ M3 z" {0 H* K# n; NTwo-stage least squares, 二阶最小平方4 I# }. b$ d2 n# R9 f
Two-stage sampling, 二阶段抽样0 F& s7 V3 `: L9 W o' m5 i/ b8 B
Two-tailed test, 双侧检验
) r7 c5 j1 j4 z9 H) lTwo-way analysis of variance, 双因素方差分析
% }% I9 T2 y3 f8 |: x* V# STwo-way table, 双向表
# E1 u) r# V6 t2 V; C+ MType I error, 一类错误/α错误
8 b& J+ M/ L4 f& c5 k& i$ z; EType II error, 二类错误/β错误) P5 f8 p! C: u* S% i) N+ C3 d+ M
UMVU, 方差一致最小无偏估计简称& g8 o! G" z! L4 w3 E
Unbiased estimate, 无偏估计
2 _) g% k! t3 f# O4 P6 EUnconstrained nonlinear regression , 无约束非线性回归
$ f$ E( Z9 }' g5 s8 Q. cUnequal subclass number, 不等次级组含量7 {# \9 ]0 B8 \" s1 A
Ungrouped data, 不分组资料
5 W1 i; k1 i W! @" v% bUniform coordinate, 均匀坐标. P# p" C: y# \7 s4 k: ]3 r
Uniform distribution, 均匀分布& R0 j7 Y2 p, b* Z
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计2 |+ v: f! ^4 m7 w: c0 E9 W$ n' T
Unit, 单元( E% N5 [; U" P& U7 a1 K% x' q
Unordered categories, 无序分类
% H$ L( A4 c6 FUpper limit, 上限! ]( k" T; p( B, D- t/ ^3 q, K
Upward rank, 升秩
+ y( E1 ?0 k! O% Y% fVague concept, 模糊概念
2 x1 I s; ^. u& b0 EValidity, 有效性- f+ [& J# [ n0 p: g# G5 T& Q
VARCOMP (Variance component estimation), 方差元素估计
; u6 }6 P5 Y3 x5 ?2 k" i5 l" NVariability, 变异性
+ e! F$ F# I* \# G, KVariable, 变量% x( n# _" \ s9 v2 i K
Variance, 方差
+ z [: x( M# X' W$ vVariation, 变异
7 b' Q: ~. H1 C8 y; vVarimax orthogonal rotation, 方差最大正交旋转( A; E3 u- x+ {, [& D5 h
Volume of distribution, 容积 c: e6 o( x$ e5 p
W test, W检验
4 k; v: T/ Y5 |$ oWeibull distribution, 威布尔分布! W. z' D, s% n& H: \; O" @
Weight, 权数# \' b& v2 F5 I. A! z0 J: P* f8 D
Weighted Chi-square test, 加权卡方检验/Cochran检验- U) H3 H. u5 [9 A1 g% F; z5 B
Weighted linear regression method, 加权直线回归/ X' x' ~) i, W! ^4 d
Weighted mean, 加权平均数
9 v1 ^ _. ?/ {- t3 N* Z* K: KWeighted mean square, 加权平均方差7 v% p* J# i2 j5 p
Weighted sum of square, 加权平方和3 z) Z; m# ~+ |# W0 w
Weighting coefficient, 权重系数( ]& d; [6 O% q0 ]+ v
Weighting method, 加权法 0 T5 }" d$ @- ]4 L/ L6 ^; f9 e
W-estimation, W估计量
- V9 V4 r/ k5 I3 l6 aW-estimation of location, 位置W估计量
4 L! b" o9 w- k4 R9 ?Width, 宽度$ @& N: Z" p& N0 k" G
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验6 s& q: v% y W) k# n: C& o
Wild point, 野点/狂点
o6 e5 z7 H' Z; g, p% Y- eWild value, 野值/狂值
+ L: x( y& s( a3 iWinsorized mean, 缩尾均值
P4 m9 h. o" C% s& @Withdraw, 失访
" k9 ]5 M9 ^; X; j/ h8 r: XYouden's index, 尤登指数( j; Q, b1 h$ p$ Z9 c8 k; S
Z test, Z检验+ u. r; } R& p* [ X, `
Zero correlation, 零相关7 u3 R( D# d9 e% h8 B( w/ q
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
