|
|
Absolute deviation, 绝对离差/ ?; i( |5 ^7 M0 s' B
Absolute number, 绝对数. k8 i8 D: j- g! j! `2 Q: R3 n+ w5 l
Absolute residuals, 绝对残差) Q a9 r) F+ P7 N7 r8 g. {. k
Acceleration array, 加速度立体阵: K" x: `" a$ v5 `* t) [0 J8 F% m
Acceleration in an arbitrary direction, 任意方向上的加速度- `5 ^- I! Q" f6 T# z
Acceleration normal, 法向加速度. }7 ]8 T% {+ O8 V
Acceleration space dimension, 加速度空间的维数
1 B4 c! t3 {7 ]; e$ c. @# P# e6 ?; ~Acceleration tangential, 切向加速度5 K E9 V0 A6 N# K
Acceleration vector, 加速度向量
9 u5 Q+ x) J! |0 h3 O. qAcceptable hypothesis, 可接受假设# c" V5 h( V7 W7 G! }& m: J" ^
Accumulation, 累积6 r1 u1 ]9 w; J2 T0 ~; j- t
Accuracy, 准确度' K" n& t. X; q, U# j3 O9 _
Actual frequency, 实际频数7 ^2 D/ } u: B
Adaptive estimator, 自适应估计量. ^& P, n9 M- x- b) Q4 X) N+ H: t
Addition, 相加
6 B, l) A" [2 ^% N' Q: k ~Addition theorem, 加法定理; A4 }5 y, X O+ ~, Z' T
Additivity, 可加性
$ @- c: P, K0 t, E+ G8 L( Z4 t0 X/ kAdjusted rate, 调整率3 B5 H6 N8 c& p3 E( n: x- t
Adjusted value, 校正值
, i8 C t1 D- OAdmissible error, 容许误差8 x, a; n6 m" i" v$ P9 U
Aggregation, 聚集性2 _- ^; [( d* h& m
Alternative hypothesis, 备择假设1 O$ Y) w: ^$ i6 r* B* f% N
Among groups, 组间
1 o% u$ R8 ]+ m6 B% ~Amounts, 总量
! z4 |' p! {. Z' f3 [1 { r' VAnalysis of correlation, 相关分析* R7 O6 P. A: A# M" H" q( L
Analysis of covariance, 协方差分析
# ` d+ M& i8 L( C9 I. k: _Analysis of regression, 回归分析
. c/ l8 [# q6 f0 N: c$ ^6 S! HAnalysis of time series, 时间序列分析! u% ?3 i/ O' a: [5 Y
Analysis of variance, 方差分析4 O2 n. s5 X8 s& c( g5 P
Angular transformation, 角转换
6 _( i: q9 m g% MANOVA （analysis of variance）, 方差分析
, {" p" q/ p, d V! X: B) C# ?ANOVA Models, 方差分析模型
g6 E( u b% \; ]1 r) v" t: D) cArcing, 弧/弧旋1 E Z3 E1 m' i$ |/ k* o
Arcsine transformation, 反正弦变换
" ~# o1 n1 L9 }8 {Area under the curve, 曲线面积+ w D7 B N# v: t9 B5 d9 M
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
5 K* Y; J `( N' Z- H8 SARIMA, 季节和非季节性单变量模型的极大似然估计 : Y8 x2 f: x: V5 ^1 l6 U% c
Arithmetic grid paper, 算术格纸" V1 ~6 z& `" B5 ?; y
Arithmetic mean, 算术平均数4 E5 z( e- y3 ^3 f, g
Arrhenius relation, 艾恩尼斯关系
" v T3 D- ^; H. F1 E% G' v% ]: @Assessing fit, 拟合的评估
1 N4 B/ S2 @% V; {Associative laws, 结合律
% c( [, t# M4 w2 l0 M$ iAsymmetric distribution, 非对称分布+ V2 ]- ^+ T% a6 y
Asymptotic bias, 渐近偏倚
/ M7 d- ^- M# t7 S- X1 D6 fAsymptotic efficiency, 渐近效率
' G- j/ m" {( k2 q; j5 T- gAsymptotic variance, 渐近方差. o+ ]3 e1 h4 o
Attributable risk, 归因危险度, E4 i+ B; L3 j& G/ W7 E" j! F9 W
Attribute data, 属性资料' @* i' ]! O; J* R
Attribution, 属性9 M3 u4 j1 t6 H- F8 p- W* Q6 K
Autocorrelation, 自相关
$ o0 p% [( y8 f( [Autocorrelation of residuals, 残差的自相关) J0 r! D8 k- K9 U
Average, 平均数% \- d* Q- j+ b3 G3 M2 M
Average confidence interval length, 平均置信区间长度
1 L, s. b8 k- y0 {Average growth rate, 平均增长率
3 V5 h0 p- e2 M1 j/ |Bar chart, 条形图
( R- l; P' {* W; F" t4 GBar graph, 条形图
6 s/ k/ L. M8 x2 [# M9 e* L4 yBase period, 基期
7 W8 X$ d* V! o# k KBayes' theorem , Bayes定理) W# J/ `( T- U9 M3 K* ~
Bell-shaped curve, 钟形曲线
7 J- F c2 [. u! W2 FBernoulli distribution, 伯努力分布
/ k1 k( v0 c7 U* K) yBest-trim estimator, 最好切尾估计量
" u A, K# c$ @8 i+ @2 K. F5 ?Bias, 偏性. O, C; W# O. l; x
Binary logistic regression, 二元逻辑斯蒂回归
0 }. {: r; \7 t9 D9 CBinomial distribution, 二项分布! s1 p# d9 v, b; F0 x3 w
Bisquare, 双平方, f; {! }, s, Q% N0 J3 B
Bivariate Correlate, 二变量相关! ?/ U1 J$ W; l8 }3 y
Bivariate normal distribution, 双变量正态分布
0 {# L% ?7 H8 u5 c* nBivariate normal population, 双变量正态总体
1 ], D+ P( K( ^+ DBiweight interval, 双权区间8 }) s# f. ]3 g5 h6 V: K3 D
Biweight M-estimator, 双权M估计量
0 g% P; E$ b3 `Block, 区组/配伍组
6 F1 b n( a( B" L; |( iBMDP(Biomedical computer programs), BMDP统计软件包4 a; A n- c$ F& p/ B+ p
Boxplots, 箱线图/箱尾图- P9 i, _4 ]( m/ l, K, M8 E
Breakdown bound, 崩溃界/崩溃点) h/ Z: k# r Z' o
Canonical correlation, 典型相关$ v& F$ i! o+ F h' ~
Caption, 纵标目
# T: M3 C+ I% XCase-control study, 病例对照研究
; i M% A: L. C* LCategorical variable, 分类变量
( c w4 g7 X! p* A i3 |) YCatenary, 悬链线2 V1 E' l" @: `" C$ T" G. A+ z
Cauchy distribution, 柯西分布
4 C1 k) P% H- Z0 r' ?* P- {Cause-and-effect relationship, 因果关系
$ z! w1 p5 y+ G. R4 VCell, 单元
( ?, c+ x6 M: S4 b- r9 m6 eCensoring, 终检) z' Y8 K' `; N6 [# f i
Center of symmetry, 对称中心& W7 d" h+ W+ T# n* `1 m( A7 D
Centering and scaling, 中心化和定标4 ]- R) |4 |! g; b" u! t% v
Central tendency, 集中趋势. z4 h' w+ Q P4 I( f$ N
Central value, 中心值) C) D! E( a2 f( O# o9 _
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测5 a0 a; {% k: O2 O3 r6 v
Chance, 机遇
* d' s5 ^* d; dChance error, 随机误差
$ I Y) _+ f' m! C, }Chance variable, 随机变量3 t0 G. T1 T, L& n
Characteristic equation, 特征方程: R; G+ ?, D# m
Characteristic root, 特征根3 p. ?( I' }1 {8 X& @5 u
Characteristic vector, 特征向量. L# c% z4 T: G1 O% R" g
Chebshev criterion of fit, 拟合的切比雪夫准则4 i0 Y+ {' R1 E
Chernoff faces, 切尔诺夫脸谱图
. f- o6 o/ k( S5 ?, D/ rChi-square test, 卡方检验/χ2检验
! C6 f; _( m' \7 n* w% |0 nCholeskey decomposition, 乔洛斯基分解; A7 Y1 z) j3 }3 O! L/ J# q1 K; t$ V
Circle chart, 圆图 . y+ r7 g7 f4 h! }! B
Class interval, 组距
) I/ J1 [! v4 t6 @, {6 |Class mid-value, 组中值
: e+ n+ t* c* b9 ]5 C# _- XClass upper limit, 组上限
0 u, [! O4 d Q M1 p- qClassified variable, 分类变量
2 w/ }- k* L2 o, G" ^Cluster analysis, 聚类分析- Y* h" B' ]' K) A, M# T* t4 ]' l
Cluster sampling, 整群抽样/ k' ]& A c/ J$ v# F, T
Code, 代码! F* N3 i* ^, H; o: y. O
Coded data, 编码数据7 e- u$ u* ~8 T* d9 X- g
Coding, 编码1 ~) g6 q/ V2 w' g" }7 z& ^& P
Coefficient of contingency, 列联系数$ T9 ^7 F9 ~, ~" d6 ^3 x; o
Coefficient of determination, 决定系数 T' G. G6 S+ f7 t& e9 l @/ t
Coefficient of multiple correlation, 多重相关系数
( M* r# [2 \$ k1 pCoefficient of partial correlation, 偏相关系数1 k, {* l$ T! s/ }% X. C0 f
Coefficient of production-moment correlation, 积差相关系数. G- z5 d. R3 |
Coefficient of rank correlation, 等级相关系数$ q7 K* I9 h" m* C; N
Coefficient of regression, 回归系数# e4 \/ {% S. f
Coefficient of skewness, 偏度系数
8 d7 M2 [( Y+ [/ l8 \4 ?Coefficient of variation, 变异系数7 Q* u* v Z7 c. ~! i8 {- N
Cohort study, 队列研究
" `0 a$ Y, S; |2 TColumn, 列7 m/ x, E( h) O+ ?* A5 O& E p
Column effect, 列效应3 C2 B" G7 r. i# R( F
Column factor, 列因素
v8 b3 R1 z, V' }( \- j' fCombination pool, 合并, t* _1 y$ ?' c
Combinative table, 组合表" x3 b; n& |3 c2 H6 G) ~( t+ _
Common factor, 共性因子5 y) v; a4 r2 S4 Z- p- M
Common regression coefficient, 公共回归系数
* z# b. k6 y0 g, ?( Q- O; jCommon value, 共同值
' t; T- J/ M3 t9 ~" y/ pCommon variance, 公共方差8 @0 k# k: `- l0 q* `8 H7 `; R
Common variation, 公共变异! z4 ?" R7 o% Y: m
Communality variance, 共性方差* Y; P: L6 _# Y' O W7 v3 H q& U4 x
Comparability, 可比性
' W: }# H& @9 v- G1 u( gComparison of bathes, 批比较6 V- ]7 v2 P+ q; |
Comparison value, 比较值" w/ f5 K" |" w
Compartment model, 分部模型9 |( ^1 U# X' e: S" l
Compassion, 伸缩
# S2 P1 z4 L( i+ m' zComplement of an event, 补事件' _) Y9 ~' h) C5 }
Complete association, 完全正相关0 ]- L* ?1 v5 {: ^! w
Complete dissociation, 完全不相关, l, Z, F: G; B+ s* y1 c% k
Complete statistics, 完备统计量! f5 n$ i5 S% s. Z+ d$ u
Completely randomized design, 完全随机化设计% ?; @9 ]- {/ e
Composite event, 联合事件
$ R) r r; n" l+ HComposite events, 复合事件 L" d4 r4 i& B8 Q
Concavity, 凹性5 k$ @' k1 {8 D2 s5 Y7 N
Conditional expectation, 条件期望
; h, E6 U6 j6 |Conditional likelihood, 条件似然9 G$ Q1 V _% ^+ f( {7 i
Conditional probability, 条件概率
5 r2 i% E' S7 b+ Z) xConditionally linear, 依条件线性
& U; h' U' X. J5 [- ^# w: UConfidence interval, 置信区间
9 Q: @7 K9 z6 r7 p! MConfidence limit, 置信限
& Y7 b" m9 E- S" ~, NConfidence lower limit, 置信下限
o8 S" {% B6 XConfidence upper limit, 置信上限
( ^5 E T6 N& qConfirmatory Factor Analysis , 验证性因子分析
' Q4 R" v9 e$ |3 F$ j; W0 PConfirmatory research, 证实性实验研究 f% N; q& c2 P8 U& E' X0 j# S4 B' @: R
Confounding factor, 混杂因素% z' P" |" n; c# r) _5 K6 x7 f
Conjoint, 联合分析
, x3 @, m+ M. @8 A6 R2 [Consistency, 相合性
/ S6 V3 }! E. M b7 W3 ^Consistency check, 一致性检验% R2 L! _6 Q/ b5 P7 E
Consistent asymptotically normal estimate, 相合渐近正态估计
+ [7 F+ G) Z# y* L; iConsistent estimate, 相合估计8 v$ e: V' H- A1 `( b. L! q7 Y
Constrained nonlinear regression, 受约束非线性回归
& Z1 z/ v* S) n7 U5 AConstraint, 约束! L/ }. g: w4 @0 a3 I+ A! t
Contaminated distribution, 污染分布2 L0 r0 Y; R" O- n j
Contaminated Gausssian, 污染高斯分布
% Y8 c* `/ `' ^. F# y1 eContaminated normal distribution, 污染正态分布# Z% {& i: T: {& X: p6 c; [
Contamination, 污染* E t( W% |) K, y" Y
Contamination model, 污染模型/ }" z, X% g; K! N l3 W, n8 |! n/ U
Contingency table, 列联表( P3 b( w! V! M+ S; ~
Contour, 边界线
9 ]0 [9 ], s. M! [$ o: rContribution rate, 贡献率
5 E/ {7 x# E; f- T( e$ Q9 \5 PControl, 对照2 Q; N4 j( _& o0 H; y5 T" V
Controlled experiments, 对照实验
; H! U- T$ E3 E- T' F& ^' \2 SConventional depth, 常规深度
. w2 W7 \$ a8 l) t1 mConvolution, 卷积8 m: @' i) i) y- l* j- p! U3 E
Corrected factor, 校正因子
9 H# K) ~0 N3 e. C8 @Corrected mean, 校正均值
# `2 G" }5 x, RCorrection coefficient, 校正系数
6 N% v, K' s- M# {' k# y: | t7 E% c' PCorrectness, 正确性
& q6 X. k. S% ?Correlation coefficient, 相关系数4 H& F0 ?5 e3 ^# A! W: p8 S8 R* t
Correlation index, 相关指数
+ m: ]. `$ L7 ^/ a5 v" kCorrespondence, 对应) G$ \& o/ k8 n: P y o) h9 O) Y
Counting, 计数4 u6 a% I" V* B6 R6 g# Q$ [
Counts, 计数/频数
$ w2 q- H7 C/ ~# ?% T' cCovariance, 协方差
5 t' ^3 G$ R t R% g9 y: yCovariant, 共变
9 D# P$ I+ Y' Q' d: qCox Regression, Cox回归
. e2 |( u e1 H+ l% P+ e3 b9 bCriteria for fitting, 拟合准则
# |( E- I# R9 ICriteria of least squares, 最小二乘准则
% [* _- X7 C1 R7 sCritical ratio, 临界比
; s* Z. M5 ^) @# \Critical region, 拒绝域
/ M0 a6 ]' h/ c" j9 m( kCritical value, 临界值3 G2 g" H' u( U. k
Cross-over design, 交叉设计
: g% f3 }! i; `6 \) CCross-section analysis, 横断面分析5 u6 o1 b$ K; x! f" t
Cross-section survey, 横断面调查
* _* J% x5 y: \. ]Crosstabs , 交叉表 6 \ C5 L ?: f/ ^
Cross-tabulation table, 复合表( {/ j1 x5 B' Y/ @( u2 N) M0 P
Cube root, 立方根
( Z3 ]2 f1 o# U @) h7 i. \Cumulative distribution function, 分布函数# B8 \/ `# m% b$ _" F! y
Cumulative probability, 累计概率6 v: \: s% ] [
Curvature, 曲率/弯曲4 E p' b' O. b# D/ x% ?% H- }
Curvature, 曲率
: j4 V, k& ]+ ~3 Y$ z6 _/ `Curve fit , 曲线拟和
! f6 j" \5 j' Q3 nCurve fitting, 曲线拟合: H9 ~" I' \; w, A: s3 _& h e
Curvilinear regression, 曲线回归* |* t& @+ p& @; U% O- T
Curvilinear relation, 曲线关系5 I/ H5 f- D+ v0 ]/ b7 {' h; s
Cut-and-try method, 尝试法4 c0 W: {. P6 e% V, ]
Cycle, 周期7 v8 }/ N. j" }8 E* M' f
Cyclist, 周期性% H, u! D- g5 A* P) D0 Q# o
D test, D检验
5 z2 B) X9 |6 g+ X aData acquisition, 资料收集+ I! G4 N) C7 u) T$ o
Data bank, 数据库8 O: r! p$ l( B
Data capacity, 数据容量
9 f+ x* q" x, m, PData deficiencies, 数据缺乏3 ?* T2 a- d5 z% x/ Z+ M# x
Data handling, 数据处理% B4 {! ^- C0 `# t
Data manipulation, 数据处理8 |( W9 u9 Z" P: B
Data processing, 数据处理6 p7 J0 ~7 Z8 H3 {( [( h
Data reduction, 数据缩减
' v' k$ C* m7 m+ E% FData set, 数据集
! m1 e7 o, O) t7 _5 K( \- w* r, AData sources, 数据来源' W9 N, l0 Q1 l( O f7 a3 o4 G
Data transformation, 数据变换' y2 W, g- ^6 o, a6 N
Data validity, 数据有效性
# t* E* o4 m( u r. TData-in, 数据输入
- q9 J. T- u/ e1 x8 {Data-out, 数据输出
7 x7 K$ p$ g! Y* {3 F2 y& rDead time, 停滞期
1 ]' J! ]9 l* ]! w5 l2 UDegree of freedom, 自由度% G' H8 W0 {! f: \) q1 \* q* k
Degree of precision, 精密度; y, r$ U, _5 u
Degree of reliability, 可靠性程度0 q1 i. {/ K. F' v
Degression, 递减4 A- @" t; @; T; p
Density function, 密度函数
, N- `( S7 g, k5 NDensity of data points, 数据点的密度) x% Y3 `5 D) L: s& M; z8 F5 f* O5 Q( O
Dependent variable, 应变量/依变量/因变量
2 A( q) R" H3 t; X C3 u" ?! \Dependent variable, 因变量: c* y; s* X$ a. g/ |4 y4 B" e: S& w
Depth, 深度- M' x$ s6 {0 P+ g! } X0 \
Derivative matrix, 导数矩阵7 G6 ~/ g/ z3 I9 A5 S
Derivative-free methods, 无导数方法
$ b$ W2 Q$ S( Q: p8 z3 {/ {Design, 设计9 [) D( ]6 T, t2 d5 z- \- @! E
Determinacy, 确定性
5 K( q/ ]* X9 Z/ X8 `Determinant, 行列式
$ B0 n" l3 Q5 z; RDeterminant, 决定因素
- X) t8 a6 x8 q0 n9 K) nDeviation, 离差: [6 Q9 W8 J- p3 f9 Y7 Z% ]5 J/ \# k
Deviation from average, 离均差6 K4 m1 \% I8 [$ z# O! M! [
Diagnostic plot, 诊断图/ U! K9 d3 P9 F& M( ]6 n4 ~: t
Dichotomous variable, 二分变量# L: m9 P$ q! T6 P& N( V7 d5 \
Differential equation, 微分方程, z5 H- c# Q0 p, W0 `9 a
Direct standardization, 直接标准化法
}$ L6 r5 R! xDiscrete variable, 离散型变量
! w6 @% Y) L1 H1 J) t( nDISCRIMINANT, 判断 : G- d+ k5 ^1 I5 Q# E; E
Discriminant analysis, 判别分析8 G/ E8 J5 H+ ?" ~3 F+ o
Discriminant coefficient, 判别系数
/ e, i2 F* _; C0 [" ^Discriminant function, 判别值
. P5 [! R: l3 O, {2 G9 ^; H" gDispersion, 散布/分散度8 E: F, P2 m$ A$ ^, r+ f, O
Disproportional, 不成比例的
& y; i! r+ G: Z0 B, _Disproportionate sub-class numbers, 不成比例次级组含量
# g' ~) w% n% K6 ?2 g* R: C4 fDistribution free, 分布无关性/免分布7 n2 { z2 N, F$ ?/ J- S
Distribution shape, 分布形状% G: r0 g7 j+ ~* o0 U8 y
Distribution-free method, 任意分布法
* _1 `, I/ ?" I0 SDistributive laws, 分配律
1 F2 W' F9 U8 FDisturbance, 随机扰动项
( @2 H" y+ `3 y8 j- F' c+ M. vDose response curve, 剂量反应曲线
. E) b. d- c& c; |1 n7 m1 [Double blind method, 双盲法: O5 c% A, }/ q4 G6 B
Double blind trial, 双盲试验4 [. ~$ d6 o* v7 c$ {
Double exponential distribution, 双指数分布4 [4 G1 e% ]; S( v7 K' k8 `
Double logarithmic, 双对数
# n2 b3 j8 U* h& {1 GDownward rank, 降秩
/ N' U2 F; w& V3 RDual-space plot, 对偶空间图
1 ?$ S' o1 p- u/ qDUD, 无导数方法
+ G/ t% T0 g; t) D H# f; K8 ADuncan's new multiple range method, 新复极差法/Duncan新法
5 M+ k* W o& a; p1 D ]: zEffect, 实验效应
; i! e4 w# c9 i8 DEigenvalue, 特征值2 S6 _. l9 J8 x# B$ i5 {9 c8 `& e
Eigenvector, 特征向量
( ~0 v0 \3 ?1 I KEllipse, 椭圆! p. P% k. p- K( t s
Empirical distribution, 经验分布* s4 g5 g# T$ x
Empirical probability, 经验概率单位
6 S: i+ V6 R8 V" F; ~8 `" TEnumeration data, 计数资料
+ @3 O* a! x8 Z2 p3 dEqual sun-class number, 相等次级组含量) }2 Z' K0 F' _9 S5 L. k
Equally likely, 等可能0 E% H( W J% f$ G+ t% w# p7 r- Z
Equivariance, 同变性
8 M- O/ g+ w, r' o: YError, 误差/错误
- T7 D( c2 ~ L2 p. eError of estimate, 估计误差
1 R% O, i- ]+ K1 ]9 p7 m( M" `Error type I, 第一类错误9 z* r. g/ }0 f) K& G
Error type II, 第二类错误
" D8 m: |. E+ d7 R) W* D6 V1 o2 v* QEstimand, 被估量- x5 H. V. h. Y& a8 y
Estimated error mean squares, 估计误差均方4 w- \) V" `7 m2 x! B( H
Estimated error sum of squares, 估计误差平方和: c5 r: K: D9 F1 B3 |- R
Euclidean distance, 欧式距离; j4 u+ I1 p9 b6 A# t5 f* f
Event, 事件
' U6 ~6 h4 N* M" |" {0 K2 u# G7 {Event, 事件
% y3 [/ \( x9 k) CExceptional data point, 异常数据点9 D/ B, J& Q* k1 K% P/ E* ]
Expectation plane, 期望平面1 ]0 u, f8 B9 G# Q" F8 L+ p+ c( y
Expectation surface, 期望曲面
3 g% d# o. r7 Z8 c' Q. l( U4 eExpected values, 期望值5 n* ?! X& y+ K5 v Y; b+ ]2 q; z
Experiment, 实验: \& o/ X. e6 L, z
Experimental sampling, 试验抽样
, Y* W: u* Y5 r B7 U# l# XExperimental unit, 试验单位# w; f8 \; {) f/ m3 X. u
Explanatory variable, 说明变量
, p4 F/ @/ E' t: O# a/ ~, M2 WExploratory data analysis, 探索性数据分析
3 ^+ @7 \2 I4 i; I( c+ L% v* wExplore Summarize, 探索-摘要
3 S) U7 j% y7 p2 Z4 Z) SExponential curve, 指数曲线" _( g/ U0 d2 p/ Q2 ?6 a
Exponential growth, 指数式增长# b1 l; n8 p8 p
EXSMOOTH, 指数平滑方法
% q" I% c* p9 T5 n" i! b( pExtended fit, 扩充拟合6 P8 ] d% v4 Y2 B
Extra parameter, 附加参数1 v6 q+ X6 N6 s% o$ |; ]
Extrapolation, 外推法
6 K3 G8 D3 l: D/ gExtreme observation, 末端观测值6 Z3 V G# j0 z4 E8 h4 ^, F6 ?" c
Extremes, 极端值/极值
% S# O7 Y* P1 _. xF distribution, F分布# J6 f/ h5 U5 [" k5 b
F test, F检验& F) i9 B% P+ V& W0 n8 p: [& e1 \
Factor, 因素/因子: U. X( u+ F" w( j3 F8 A
Factor analysis, 因子分析
& A P/ D4 X% }2 |Factor Analysis, 因子分析
# \& s0 Y+ m8 ~- QFactor score, 因子得分
3 h$ {3 ^; Y* k( w5 S, oFactorial, 阶乘
( j! C1 M, \/ f, B9 pFactorial design, 析因试验设计) I* ]3 d: f4 _! K U
False negative, 假阴性
( I0 B, M, U2 X/ Y4 W# D! GFalse negative error, 假阴性错误+ ^1 i$ _' ~- g( f7 c# T' x
Family of distributions, 分布族
8 N: o4 d' n+ BFamily of estimators, 估计量族
9 f* F8 G. A6 ^Fanning, 扇面
; `5 `, h, K8 P5 d8 M- p" H0 qFatality rate, 病死率
! s0 M' ^) V, {* T4 j/ G* F) {Field investigation, 现场调查3 ]9 Y. `( C7 L
Field survey, 现场调查5 |: |# C1 O3 H: Z
Finite population, 有限总体; u- Y' B3 q- g; u8 \- C% C X
Finite-sample, 有限样本+ O F- [# F5 ^/ Q+ P. n/ L- a5 d
First derivative, 一阶导数2 x: f; D: }4 u [% {
First principal component, 第一主成分9 k2 C9 o5 l7 C4 T! q- |3 i2 t
First quartile, 第一四分位数
: j1 {) @ [, MFisher information, 费雪信息量9 _+ ?0 _, M) s3 L9 h9 }' \
Fitted value, 拟合值
/ n# R* T9 y( n0 g. }, UFitting a curve, 曲线拟合
, e. k, }" Y( C* {. m1 rFixed base, 定基" r' s8 L. Z& d ~3 e. u, X, K
Fluctuation, 随机起伏
) x$ u1 a. A1 f/ _. v cForecast, 预测" f: E$ z! f4 [ t8 G
Four fold table, 四格表
- F3 q. b0 N" }$ YFourth, 四分点1 o4 C$ j+ W+ H
Fraction blow, 左侧比率$ I1 \2 m. b `: m/ n* L
Fractional error, 相对误差
' w+ r# K) V0 JFrequency, 频率/ w, c0 x1 s! q* G& H
Frequency polygon, 频数多边图. Y! X8 H3 A8 a/ |. \, M& z0 j% k1 [# f
Frontier point, 界限点
, S: S/ R& ]- n8 w! z) X7 NFunction relationship, 泛函关系
! g6 u) W5 _4 _6 E3 w( AGamma distribution, 伽玛分布# r, @% |$ {( `0 Q: j
Gauss increment, 高斯增量' S4 l+ S/ }/ C# E6 H
Gaussian distribution, 高斯分布/正态分布+ ^0 a! O! s7 T1 Y/ X
Gauss-Newton increment, 高斯-牛顿增量+ s7 _& S$ ^6 ^, o
General census, 全面普查- o( R. s& _+ p3 A f, l5 G3 V6 S
GENLOG (Generalized liner models), 广义线性模型 / [0 z2 B8 Q! [5 F: Q0 `
Geometric mean, 几何平均数+ S; Q9 U9 q5 l2 X3 \
Gini's mean difference, 基尼均差
0 ?6 K/ @: a( }- r! ?, y* eGLM (General liner models), 一般线性模型
8 i. I, L/ @/ ]$ u6 R; ?2 a" yGoodness of fit, 拟和优度/配合度
2 T K5 @3 B; u. y- p' GGradient of determinant, 行列式的梯度
/ m5 y9 @1 \1 v0 iGraeco-Latin square, 希腊拉丁方+ u8 f. j& j: i9 D
Grand mean, 总均值$ C) {# y2 e& v+ |, N6 y) d% ^
Gross errors, 重大错误
1 w8 w _! j" iGross-error sensitivity, 大错敏感度
7 k& e: i6 W# `; n8 `' }% A( s# yGroup averages, 分组平均' w4 Z; B* D6 {* a S
Grouped data, 分组资料$ E( u0 j, E" y) r; z& w' }% I8 T( e" m
Guessed mean, 假定平均数& A# m u5 l1 N3 L$ O/ Y& b: U
Half-life, 半衰期& G' }3 Z0 g' y- l1 E1 Z
Hampel M-estimators, 汉佩尔M估计量, J# a6 I7 x5 a) }( X, A( n
Happenstance, 偶然事件 P5 \0 u/ Q" c* L% X
Harmonic mean, 调和均数
( U V9 A* ]" F4 [5 oHazard function, 风险均数" q M4 m5 L1 G: ^2 O& a
Hazard rate, 风险率* O/ m9 y% `" E4 |/ \4 c
Heading, 标目 / d ?7 c& c: r6 |
Heavy-tailed distribution, 重尾分布) A& ^' ]+ u* k. ~; `
Hessian array, 海森立体阵
4 s0 w0 a( r& B- k2 W0 M0 }& |Heterogeneity, 不同质3 K3 s9 F0 ~) Z0 N+ ?
Heterogeneity of variance, 方差不齐 " [0 C; {* i3 k) R% y/ E# z! q
Hierarchical classification, 组内分组! E6 l# t7 H. ~1 b/ {! m* j
Hierarchical clustering method, 系统聚类法
9 d3 _- Z3 m5 h L0 P H. e1 n' OHigh-leverage point, 高杠杆率点
4 X1 c" ~8 S" A# K8 A: VHILOGLINEAR, 多维列联表的层次对数线性模型5 Y' L( ~2 t+ I
Hinge, 折叶点( X) W! p/ V+ _$ C( N) F) `$ `
Histogram, 直方图
, n6 w. Z. f& i) t7 D3 c" mHistorical cohort study, 历史性队列研究
" V" l$ c+ c8 \6 V8 VHoles, 空洞8 d1 n$ E0 [. W" @. C
HOMALS, 多重响应分析& n- ^' v2 _3 q% f4 q
Homogeneity of variance, 方差齐性
* p* a) p4 n" a- L6 OHomogeneity test, 齐性检验
) i6 f( E! O$ H6 @2 M, I* KHuber M-estimators, 休伯M估计量, S3 L8 B+ d" p, B+ b& ^
Hyperbola, 双曲线9 [( j2 g) C E; J* v
Hypothesis testing, 假设检验& }$ m, Z4 U. p1 S- w4 f( e, o
Hypothetical universe, 假设总体
& h2 c) d8 z" SImpossible event, 不可能事件3 [. v# V! ^9 G
Independence, 独立性
9 H) I( T! f3 @7 UIndependent variable, 自变量
3 y* `! Y3 x+ @% ~$ l( R Q$ q2 S4 HIndex, 指标/指数+ H' n3 n- J' }/ o: s$ d' _, _
Indirect standardization, 间接标准化法2 L% ~1 W1 _6 a' p, v" |
Individual, 个体
$ Z# M& C( m9 l; s) PInference band, 推断带4 ]" s" o- `5 T; M+ a" d( E p, @, J: q
Infinite population, 无限总体" S- h2 E ], C9 {7 i2 n1 Z
Infinitely great, 无穷大
8 i, A" B7 P8 UInfinitely small, 无穷小) Y) M1 F# K( [1 R. z% Z- k7 E- j% ~
Influence curve, 影响曲线
" T( j( Z- m6 R+ w/ pInformation capacity, 信息容量0 a( F- t" @6 w o/ L# Y
Initial condition, 初始条件7 @/ i# ?: R& @+ T. H# L+ Q) u
Initial estimate, 初始估计值
& s. \+ g8 X5 L3 HInitial level, 最初水平
3 b+ O0 M5 m* y1 r! }7 j% qInteraction, 交互作用+ X2 }9 ]+ H' Y w* M
Interaction terms, 交互作用项5 |6 a0 ?2 H' m+ n+ |! ?% L
Intercept, 截距
7 I: {) T4 E2 S* g( K" q- zInterpolation, 内插法" }4 V* e& {" w) n% u& s# y0 k
Interquartile range, 四分位距) [& ~5 U, R7 Q/ Q/ F# m+ ]* e! c
Interval estimation, 区间估计: p( M; A0 Z" B- \6 }- ]
Intervals of equal probability, 等概率区间
' u3 {/ N6 }& A1 T/ `% FIntrinsic curvature, 固有曲率0 S }4 k l# [! K$ ]; w
Invariance, 不变性
2 S9 g0 [! R4 f H3 pInverse matrix, 逆矩阵
. c: l; ^7 ~9 vInverse probability, 逆概率! ?1 F% P" W9 y
Inverse sine transformation, 反正弦变换
0 z1 Q' a0 W* H8 z0 r* d" x& ~Iteration, 迭代 ! @( ^/ x; U) {- M! s5 [1 F6 k5 q
Jacobian determinant, 雅可比行列式' {* f$ M2 i- r2 P1 T
Joint distribution function, 分布函数3 O8 C# W& s/ S7 W6 @, r& z" _
Joint probability, 联合概率
1 {" n5 E# ~2 }5 H5 D/ |" x# K9 X* vJoint probability distribution, 联合概率分布+ i0 ^$ k) {! f Y* k0 e4 ]! V. v
K means method, 逐步聚类法# j7 T2 \9 A9 S V- A4 A8 d
Kaplan-Meier, 评估事件的时间长度 ' n! O, o0 P: _1 m# n
Kaplan-Merier chart, Kaplan-Merier图
& n% @ X$ [3 PKendall's rank correlation, Kendall等级相关
1 d8 i4 D7 D+ `Kinetic, 动力学# N& T' U/ _0 ~) \7 h& T5 R" G) L
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
8 X" q5 s x: g6 m: uKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验- {% a% A* {5 v7 n; E) P
Kurtosis, 峰度
, l% b* f- i/ d1 yLack of fit, 失拟$ ]+ k# H- E$ i8 S9 i7 h
Ladder of powers, 幂阶梯, ^/ p. G k+ @* }1 P& u! D0 |
Lag, 滞后0 P6 d$ S; C; [ s9 ~: c4 D
Large sample, 大样本 L/ w, g4 J& G, J
Large sample test, 大样本检验
7 z) K; _2 M. Y: p3 {Latin square, 拉丁方
" Y9 Y( A, O4 A5 XLatin square design, 拉丁方设计
! @. g5 j v0 K1 u; b+ z: x, yLeakage, 泄漏
6 E; m9 E- T+ `8 F, CLeast favorable configuration, 最不利构形0 }" D1 V# Z) v5 j, a+ g& k
Least favorable distribution, 最不利分布
' H2 X1 S( S( _2 Z9 Z( x2 nLeast significant difference, 最小显著差法
; P: Y U @: xLeast square method, 最小二乘法# `! F( m) K# D5 T
Least-absolute-residuals estimates, 最小绝对残差估计6 |2 A0 r" h4 ]4 R: S
Least-absolute-residuals fit, 最小绝对残差拟合
! I9 \# a, ]& i! L3 x4 x+ qLeast-absolute-residuals line, 最小绝对残差线
1 U* u9 T2 Q T/ F* m) L& rLegend, 图例
j3 }" a/ P8 ~$ ^" AL-estimator, L估计量
. J- \8 j" l, E$ bL-estimator of location, 位置L估计量
: B* f! d7 L a: J" SL-estimator of scale, 尺度L估计量
/ ^2 l: C. M8 NLevel, 水平
& F7 u( ~) O2 ]6 [' u! ?6 QLife expectance, 预期期望寿命" x- K" n+ h8 A) t1 O% w
Life table, 寿命表
& F1 i7 |+ v' \1 ~Life table method, 生命表法
* t8 T/ p5 h; R( J3 sLight-tailed distribution, 轻尾分布
+ T, s: K# f# n; i- G4 P RLikelihood function, 似然函数
* H. U8 ~/ ?, ]5 L6 YLikelihood ratio, 似然比7 W7 i- z" Z) x1 d! @ v+ V0 |( \4 @
line graph, 线图
4 C6 j2 x- Y- S& hLinear correlation, 直线相关
. a% M% h8 F2 {7 T8 G5 sLinear equation, 线性方程0 U: _6 H( y1 e5 b
Linear programming, 线性规划; N+ ^( l. m9 \/ Y/ |* ]
Linear regression, 直线回归
' m) @% F3 ^! ]Linear Regression, 线性回归
0 X/ ?1 z! u1 [/ H# KLinear trend, 线性趋势
/ E7 O5 _1 {) sLoading, 载荷
! U) P& {; C7 ~5 U) Y1 l* WLocation and scale equivariance, 位置尺度同变性
1 L1 L; |) R, r$ G3 L ?, bLocation equivariance, 位置同变性
/ u* {. F _ s" G2 LLocation invariance, 位置不变性% ~0 H) U$ `1 z6 a l8 a8 N8 [# y
Location scale family, 位置尺度族! O8 k2 Z( [5 @# E
Log rank test, 时序检验
2 Z) M7 f& {' y' KLogarithmic curve, 对数曲线
* [$ G& _/ T* n5 x3 a. S2 |Logarithmic normal distribution, 对数正态分布4 q9 i) k; n0 t8 c% e
Logarithmic scale, 对数尺度6 E( V& N- z( F" D
Logarithmic transformation, 对数变换
2 s, ~3 |( t/ h9 y0 uLogic check, 逻辑检查* A# X9 S3 k+ b: b# ~' B1 G( e. `
Logistic distribution, 逻辑斯特分布
* I3 z1 i [' {6 a" t) w+ \1 MLogit transformation, Logit转换
# Y. ~- Q7 I4 {LOGLINEAR, 多维列联表通用模型
. \- d7 e% k. E& b3 mLognormal distribution, 对数正态分布- Y* o& U) z: N# c( G
Lost function, 损失函数# C( }. y3 ~2 t) ~! O; O* V$ N
Low correlation, 低度相关; X- I4 n7 J% o
Lower limit, 下限
, P8 R& g; E S2 `( N& a! h9 P) L9 R4 FLowest-attained variance, 最小可达方差
j6 @; o' q) j Y* N5 dLSD, 最小显著差法的简称! Q$ m E, t! \6 D7 J0 z( b) r, K
Lurking variable, 潜在变量
/ U+ f7 H" h/ m; J0 l6 f) Y ~Main effect, 主效应
0 z7 B; x- y" f, ^( Q* qMajor heading, 主辞标目, q+ T5 W! f+ y0 O/ e+ \& o
Marginal density function, 边缘密度函数1 u% P3 s- i* u6 B) s1 F
Marginal probability, 边缘概率# X/ G3 B( }* R/ j4 h- r8 \) d
Marginal probability distribution, 边缘概率分布9 w- i' a& J- `- f
Matched data, 配对资料
7 p F; [6 x3 q- W. hMatched distribution, 匹配过分布: q; Q0 F8 P R$ T
Matching of distribution, 分布的匹配+ }# u! a% I) G% s+ M
Matching of transformation, 变换的匹配- W1 ^4 n6 i; |8 o& a" }. {& a
Mathematical expectation, 数学期望% `* k! v6 k- d6 W1 g) E/ }
Mathematical model, 数学模型+ d/ j9 X; D- R/ R, E2 m
Maximum L-estimator, 极大极小L 估计量5 Q. |1 q5 ~9 b( A. l
Maximum likelihood method, 最大似然法 [$ Z0 d5 E9 u5 b+ ~
Mean, 均数2 V9 }- k x) R! Z2 [
Mean squares between groups, 组间均方
" M0 _4 }3 C7 ~8 H2 s, _0 n; SMean squares within group, 组内均方& R, m9 S9 _. i
Means (Compare means), 均值-均值比较
% M* q4 O, t7 X) p1 A" ~* P6 OMedian, 中位数4 a. v6 u- `$ k% A! T
Median effective dose, 半数效量
3 f9 x8 }' [# w/ s) `4 IMedian lethal dose, 半数致死量
# h) R( p# o) I5 d0 {Median polish, 中位数平滑9 x! [$ D. W- x3 i: s
Median test, 中位数检验
' H3 u+ Y0 {( u* X! a. N- h$ nMinimal sufficient statistic, 最小充分统计量
?1 `7 J4 S. y( O' w* q! EMinimum distance estimation, 最小距离估计
! k& m/ ]( C: c" \Minimum effective dose, 最小有效量" a2 D3 u% L4 \. \% J
Minimum lethal dose, 最小致死量, M5 K1 M) p$ Y
Minimum variance estimator, 最小方差估计量$ O3 y! z1 V9 x- F
MINITAB, 统计软件包5 Y! t+ O1 e }3 o1 e4 Y9 ^
Minor heading, 宾词标目) y1 y0 |: H0 l6 }8 N. F8 O
Missing data, 缺失值! A: E7 l& `: b3 |1 l- |0 j
Model specification, 模型的确定
$ U& K5 O8 g- M5 O( i& bModeling Statistics , 模型统计8 ~, O/ k6 Q! y+ b2 ?4 j
Models for outliers, 离群值模型
. L- _8 j+ V5 G; ^) Z# @7 YModifying the model, 模型的修正
8 L) \: ^! `, f( d- NModulus of continuity, 连续性模) ~9 }( E# z- b K1 g9 Z: M6 t& t
Morbidity, 发病率
8 S: {$ ~; s6 @Most favorable configuration, 最有利构形% a% o% q9 ^4 W8 g! ?: v6 G
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
; r. \/ A# H3 {# c; `7 T6 ^/ {Multinomial Logistic Regression , 多项逻辑斯蒂回归7 X) c! j5 x0 m* T
Multiple comparison, 多重比较
: s8 r8 }: {% B! ?2 _/ CMultiple correlation , 复相关
! R# X6 d1 X" B3 d$ c/ CMultiple covariance, 多元协方差& D1 T' W a" V7 ^2 ]
Multiple linear regression, 多元线性回归
. x1 r$ g0 [' ?) e0 P: AMultiple response , 多重选项
- z$ b5 h$ o: W" [2 G FMultiple solutions, 多解, C D2 n5 F( }1 |" w5 |6 u
Multiplication theorem, 乘法定理
( L" F3 ?0 h" Z: ~Multiresponse, 多元响应
9 J$ K3 _1 y% j! a, c6 }4 jMulti-stage sampling, 多阶段抽样) [! x2 v ~! h/ v( I7 K
Multivariate T distribution, 多元T分布: T) w( v3 N2 n$ y& G t/ l: Z
Mutual exclusive, 互不相容
5 F6 K# v1 Z+ ?0 KMutual independence, 互相独立) c$ X/ U. r8 R8 s/ [
Natural boundary, 自然边界# s4 K) M3 m: j% E4 L# ^
Natural dead, 自然死亡/ x9 c* G+ u8 F/ t/ \
Natural zero, 自然零
+ w# C+ C, h2 Z5 C0 I3 pNegative correlation, 负相关2 a2 B4 A. {5 g) s
Negative linear correlation, 负线性相关
& u/ g( t4 M( k. s6 ~9 [Negatively skewed, 负偏& Z5 W: w/ F( i% C4 r
Newman-Keuls method, q检验
* |0 E$ D' D) Q; U7 P! d3 ZNK method, q检验& L. e2 r0 y* B7 O+ f/ Q
No statistical significance, 无统计意义
- E) l; S$ K- u! y; T7 Q% B+ U% MNominal variable, 名义变量
8 G; H" n: X4 ]) z. {& p2 ?Nonconstancy of variability, 变异的非定常性4 v' V# i2 y2 T: o Y) N; {* [- q
Nonlinear regression, 非线性相关
* ?! o6 j/ n' L9 `Nonparametric statistics, 非参数统计$ {+ p5 ]0 j0 K: D
Nonparametric test, 非参数检验0 a/ f" ^( _& O( x' a, B
Nonparametric tests, 非参数检验
) y) }+ ]* u E, o5 @! G7 h. y& G5 hNormal deviate, 正态离差$ Z! ~/ v, U3 T" r7 v- M1 e
Normal distribution, 正态分布
. Y' @( H3 c0 S7 a! P: ANormal equation, 正规方程组
; X$ F; v/ X; V* g# |Normal ranges, 正常范围* y7 m( ~' `: Y3 A
Normal value, 正常值
# n9 L/ W% z3 Y2 G5 L' A, t* |# |Nuisance parameter, 多余参数/讨厌参数, X% o( R, t7 Y; o/ K
Null hypothesis, 无效假设
. ]% p; _' \( j/ ~Numerical variable, 数值变量/ ^, M4 m, }2 ?3 m
Objective function, 目标函数! l" P* w x) c
Observation unit, 观察单位6 B: e1 E7 R- g
Observed value, 观察值7 l' j# T7 G" X ?6 ^0 W6 g2 p
One sided test, 单侧检验
4 p. m/ V% W$ d+ h8 FOne-way analysis of variance, 单因素方差分析
0 V# O e! Q. f& \2 Q+ _Oneway ANOVA , 单因素方差分析) L: O2 z2 m' C* @; n) p" E
Open sequential trial, 开放型序贯设计' u3 b7 K6 e; M* K' f% Z$ F# U
Optrim, 优切尾
/ i5 X1 H5 ?1 W2 r6 W# C; wOptrim efficiency, 优切尾效率
M8 X7 y) B5 L( ?1 IOrder statistics, 顺序统计量
# E4 @ a5 |' r1 QOrdered categories, 有序分类
7 H& a- Z* {, [Ordinal logistic regression , 序数逻辑斯蒂回归# w/ _3 y( c6 f' t% G" h: f
Ordinal variable, 有序变量
# _( G& j8 }! z, |' wOrthogonal basis, 正交基0 D1 i' q5 s% d+ d4 [
Orthogonal design, 正交试验设计
2 n+ s! s2 M7 M$ `8 f5 z7 OOrthogonality conditions, 正交条件+ c3 H& [* ?, n1 d8 e& e9 q" Y/ j1 C
ORTHOPLAN, 正交设计
# S" D0 i/ s. y( g* y1 T4 WOutlier cutoffs, 离群值截断点
1 p/ j N$ Z. S( E: s& N0 B9 s6 tOutliers, 极端值7 ^) @% L! v) ^; K+ x
OVERALS , 多组变量的非线性正规相关 ' r0 X, B) s6 P; k2 L
Overshoot, 迭代过度! I% j. F4 ]1 s8 N d6 s7 E
Paired design, 配对设计
# \& B9 V% Y/ yPaired sample, 配对样本
+ Q* {0 B2 s" s# QPairwise slopes, 成对斜率
% Z6 B ?& I& x9 yParabola, 抛物线: ?% G+ ?' a& |/ H: f7 ^6 l h
Parallel tests, 平行试验9 D# B ? a( c, L' o# _0 I
Parameter, 参数
# g, X+ `0 O3 ~; u* h: D9 j' u( qParametric statistics, 参数统计' Z3 s4 g. s+ ^1 W* n' I' c
Parametric test, 参数检验
; w" M, Y, k9 t% f7 m! \) m( }Partial correlation, 偏相关
C. N; Z4 s' f; X9 ]7 K5 aPartial regression, 偏回归$ O8 K; T: q: `/ }& Y/ `
Partial sorting, 偏排序2 f% j2 k; }4 W) ]: {9 ^4 J- z
Partials residuals, 偏残差
2 i! i$ g" [: ]Pattern, 模式8 E/ R- p4 M3 R$ D9 ]# @
Pearson curves, 皮尔逊曲线
0 @# u# {* K" W+ ?3 i* ePeeling, 退层
$ q" w: I+ r, J, C4 R0 ~4 j0 APercent bar graph, 百分条形图8 c5 ^& }0 t( a7 @. G; L& u) u `
Percentage, 百分比
. a0 L. Q5 \% PPercentile, 百分位数
! D+ H& i( J; s: }* TPercentile curves, 百分位曲线
) q2 |# s' _7 F6 d1 _, zPeriodicity, 周期性5 I3 r; z3 t7 W" w. V! V
Permutation, 排列
' {7 `3 K( V8 XP-estimator, P估计量
8 G9 l( m* p( d/ V( I0 LPie graph, 饼图# a* _, q2 ^; a5 l% z/ y
Pitman estimator, 皮特曼估计量
' K' q# [" k4 ]. E; w$ SPivot, 枢轴量
, D% e5 _. K m+ P; n9 ^! qPlanar, 平坦
4 e+ y% R* ]7 u. YPlanar assumption, 平面的假设
0 x. e. t H4 g7 z+ f9 zPLANCARDS, 生成试验的计划卡9 q& Z0 L9 S% E. o
Point estimation, 点估计
* |( ~, Z3 l7 w( X+ v3 A# D& C/ e8 pPoisson distribution, 泊松分布
' R; e* g( O5 g1 j; |# C1 oPolishing, 平滑
: g2 k( {( y2 x# _Polled standard deviation, 合并标准差5 b) s# G: z ^8 `
Polled variance, 合并方差+ C+ U# G8 w3 E; T# ` l3 r* [2 T
Polygon, 多边图9 z& d1 x! ^& i& b) ?% T2 A
Polynomial, 多项式$ n, e! M( L# m
Polynomial curve, 多项式曲线( P# Y7 |. x0 |
Population, 总体
6 Q; q9 c/ I$ T5 o6 FPopulation attributable risk, 人群归因危险度
) l' z* P# l0 iPositive correlation, 正相关
$ c* f/ O) X; ]2 ^: sPositively skewed, 正偏; a/ [4 }5 o7 d8 h* q2 |/ i. D
Posterior distribution, 后验分布1 Y# t7 m! N1 ~3 f0 o3 N8 ]
Power of a test, 检验效能
( q+ {" u: n! N# ^- d ?1 HPrecision, 精密度; D% `. _/ S) V9 o7 j
Predicted value, 预测值. ^: E* ]5 t9 S* o6 L" ?3 [! c5 O
Preliminary analysis, 预备性分析
- K& c7 {. m, E4 b J+ VPrincipal component analysis, 主成分分析
' b) y# W, o. {+ hPrior distribution, 先验分布( _; V: ?$ d$ F7 D. u5 g/ o7 C
Prior probability, 先验概率: w: N7 q" c- p( K
Probabilistic model, 概率模型% U: M) B4 h& V- p
probability, 概率
{( S6 T; b. A" |: n* @Probability density, 概率密度
. l( |' m/ h' D* j2 }& `: @7 TProduct moment, 乘积矩/协方差$ \+ ]+ F/ {% W/ [( _* b
Profile trace, 截面迹图$ Y, h( `: B" B
Proportion, 比/构成比
1 C l& u& D% a* L$ q7 ]8 xProportion allocation in stratified random sampling, 按比例分层随机抽样& X; B" N9 \- M3 w
Proportionate, 成比例
' U5 b! s3 D+ G, W, Y( Q/ a/ lProportionate sub-class numbers, 成比例次级组含量
h& j% Z! |3 b V L3 hProspective study, 前瞻性调查
- r" M9 R: }; ] O3 |" MProximities, 亲近性
3 B/ E( v$ I7 W0 G$ q! E5 d4 _Pseudo F test, 近似F检验
8 M2 `3 l" Q. P1 j8 r9 S0 B8 a" S; CPseudo model, 近似模型
8 p4 f2 I6 }" d" E: D8 e: iPseudosigma, 伪标准差* y( @ O2 s& E% U6 n7 x+ u
Purposive sampling, 有目的抽样, ?: C- W/ |, d2 g5 [8 t( `, u7 i2 K
QR decomposition, QR分解
" B! c" {3 Y% s; ^6 M" v" p1 uQuadratic approximation, 二次近似
5 O h5 w* g5 G5 o0 @Qualitative classification, 属性分类
" `' y7 Z0 Y1 p4 [: d% yQualitative method, 定性方法' j4 u+ z& j4 }0 T$ J( v# s
Quantile-quantile plot, 分位数-分位数图/Q-Q图
8 `$ s1 L. q9 ^: i- [7 KQuantitative analysis, 定量分析* p8 a, ~: X8 ?1 g* {* s1 _1 d, y
Quartile, 四分位数" p7 X: w. M! ~* m4 h
Quick Cluster, 快速聚类
6 G, q* ^ I" ZRadix sort, 基数排序
; t& x+ `$ V% _: x% GRandom allocation, 随机化分组. z% @4 p# A3 P, S
Random blocks design, 随机区组设计
u8 W p9 |/ HRandom event, 随机事件
. c4 t9 O9 z3 v" e' C. pRandomization, 随机化
; p* A! y) l" T, f4 o3 m. ERange, 极差/全距1 E. F% R; {8 ]5 X) j$ C F b9 B {
Rank correlation, 等级相关% Z/ l. O% h$ V8 L0 ?, ^* K
Rank sum test, 秩和检验
, Y- E+ W3 |$ `$ g2 G) iRank test, 秩检验
# {/ p3 G3 `5 f& gRanked data, 等级资料6 c/ h6 X8 G# c+ n1 r
Rate, 比率3 `7 S8 ?3 b# }/ S4 l5 A$ G6 i
Ratio, 比例$ t9 E9 W8 s4 o/ H$ O) a- I- Y8 M
Raw data, 原始资料
4 w6 E. l( B/ `+ v: P* v8 {Raw residual, 原始残差
! D' b8 m6 @6 lRayleigh's test, 雷氏检验
* T2 F1 J$ d. `& G0 CRayleigh's Z, 雷氏Z值 / W) ]$ e* _0 b
Reciprocal, 倒数: _8 e/ P& t+ D/ E' C7 y. ?
Reciprocal transformation, 倒数变换
5 v# l- t: Y; R7 x/ qRecording, 记录
( ~( c0 _# ^7 s; U9 jRedescending estimators, 回降估计量# s& a( \6 E( g& L6 [2 S2 d5 L" J
Reducing dimensions, 降维
: S' b8 f7 @0 P; A9 F8 a" {) _0 V# eRe-expression, 重新表达' d; I; l& \7 r0 v" [
Reference set, 标准组2 ^- f5 d* b3 ]& ~
Region of acceptance, 接受域
" d$ A2 o+ _* ?! u5 U( C- qRegression coefficient, 回归系数
* j- E& D; f# p) ]Regression sum of square, 回归平方和
* M& E- i0 F) iRejection point, 拒绝点9 ?1 P: ^: L8 d! q
Relative dispersion, 相对离散度
! H1 G" m( t3 {2 p! L( a8 a' gRelative number, 相对数
$ m O. K* O2 p$ z/ `9 AReliability, 可靠性: C) |. x4 N: C& S. _
Reparametrization, 重新设置参数& P+ m, q% U, Q1 w% A, ]/ {
Replication, 重复
* O9 N, N U4 N) HReport Summaries, 报告摘要
0 x) H6 ^) j, g8 ]Residual sum of square, 剩余平方和
' m0 |9 f6 @3 x4 A- _. SResistance, 耐抗性
" F: c i8 v. Y) kResistant line, 耐抗线
1 f j5 u1 _: X6 ?# NResistant technique, 耐抗技术3 F3 y2 |7 ~ F
R-estimator of location, 位置R估计量, I+ y, E( f- a* y8 _: I+ D8 }
R-estimator of scale, 尺度R估计量 W. n8 q) ?8 ~: B
Retrospective study, 回顾性调查
- D7 w4 t+ J# r7 g5 S) J& MRidge trace, 岭迹
! b8 \. }; \4 q) s2 ~2 c) {Ridit analysis, Ridit分析6 M/ ~9 J3 @' H; ^, T" g
Rotation, 旋转
, n& T) _ @4 Z7 n, g$ bRounding, 舍入; ?. h4 c C& E, g( T3 r
Row, 行
) L4 T3 z6 u: }1 V1 SRow effects, 行效应1 |/ E/ v. N5 [& Q, p$ v$ y9 O
Row factor, 行因素
2 {) T$ b+ D% U3 M" k' P* ?" a8 dRXC table, RXC表
, X& j( s/ p, v9 N+ }' j" [Sample, 样本
' G3 ^& K' n7 p' E& Y e6 l' q: @Sample regression coefficient, 样本回归系数% z+ O# z8 G9 k; i
Sample size, 样本量
6 x: |) S2 n3 K3 L4 V/ `; M% qSample standard deviation, 样本标准差
+ V. n# N0 r: r4 o$ i$ vSampling error, 抽样误差
5 m, U( U% @1 _+ q% }2 {1 T- _SAS(Statistical analysis system ), SAS统计软件包
# d' K, i1 s3 X5 D2 QScale, 尺度/量表, L" b0 F$ m# j3 Y
Scatter diagram, 散点图
/ ?6 ?2 [& }8 A Q: g' ?: \Schematic plot, 示意图/简图
- T ?$ @9 G( z( {$ N& ]" U: Z# GScore test, 计分检验1 D1 P% Q" x: T2 j" @
Screening, 筛检
9 @# l2 x" r r/ s! O m; TSEASON, 季节分析
8 |6 x% C* v2 {Second derivative, 二阶导数
# ~+ p2 O' S+ ?# ]4 g& uSecond principal component, 第二主成分. V4 ]/ Q; P' V& Z
SEM (Structural equation modeling), 结构化方程模型
2 f9 W, `& F L; dSemi-logarithmic graph, 半对数图 I% {1 J) J; k! H5 e
Semi-logarithmic paper, 半对数格纸
1 z2 F8 L- U. Q( E# {1 `; ISensitivity curve, 敏感度曲线+ `5 k& K. r" t8 p5 @
Sequential analysis, 贯序分析
( K3 A/ ]7 \' L" Z# A8 q. uSequential data set, 顺序数据集, R! l5 Y9 N0 P/ N
Sequential design, 贯序设计
3 I& W6 V3 ]. G+ ySequential method, 贯序法
. y* E$ u8 O# bSequential test, 贯序检验法
4 k( W4 }2 H$ D( G' O( _Serial tests, 系列试验4 |! I# N$ O! b4 t3 z
Short-cut method, 简捷法 % t( T V& v& b6 _% O8 }& _
Sigmoid curve, S形曲线9 _& F( q. B; e' c+ G# D5 t0 n4 o
Sign function, 正负号函数
0 k: @8 v! |( _) S) R+ ?3 }! x$ ySign test, 符号检验
+ u$ a: b) W* P; uSigned rank, 符号秩
6 Y# e; Q2 L3 \1 J# |Significance test, 显著性检验
6 Q& Z" Y2 I: o: i$ RSignificant figure, 有效数字
8 ^5 ~ u5 p. KSimple cluster sampling, 简单整群抽样
/ | t. w+ S. S4 e& C+ ~- XSimple correlation, 简单相关- y/ Z5 O$ ~9 u( K+ T2 f
Simple random sampling, 简单随机抽样
- ~8 J, `# s* K; p" N8 o) w3 DSimple regression, 简单回归. b/ B9 p7 [1 J* g
simple table, 简单表
( e% h" L& ~/ i) Q$ z, QSine estimator, 正弦估计量4 `# n4 f! m+ P, F2 B9 R
Single-valued estimate, 单值估计
9 f6 \/ I- k+ e5 n0 r6 b8 xSingular matrix, 奇异矩阵
; t% ]1 j$ @2 t: B. L8 m1 vSkewed distribution, 偏斜分布0 h. G% p& s5 L v, H) V
Skewness, 偏度
. M. t; E$ l% u7 \" ~Slash distribution, 斜线分布! Z) U% O) Q( b* Q4 x! D
Slope, 斜率
7 c% Y' @" \9 K* _. oSmirnov test, 斯米尔诺夫检验9 F6 u5 H4 Y. L, P+ `+ V& v
Source of variation, 变异来源
# U6 d" c) I5 a0 kSpearman rank correlation, 斯皮尔曼等级相关) A0 ?0 |* L! q7 p2 |: V" ?8 U; \
Specific factor, 特殊因子! F4 q: w7 [ h! R* `. o; \
Specific factor variance, 特殊因子方差# x6 o. S/ X6 U
Spectra , 频谱4 L$ |% V5 b7 z* c( E9 l) \) p7 T
Spherical distribution, 球型正态分布
+ O) k" H6 Z3 w9 lSpread, 展布
& K+ v2 K X$ o" Y1 w. b! ESPSS(Statistical package for the social science), SPSS统计软件包1 s9 L% E9 J1 k3 }: ` D' c& d5 a
Spurious correlation, 假性相关% v) [9 E$ ^* a# _5 I6 A! y
Square root transformation, 平方根变换7 D) x1 {* I! p! J# Q
Stabilizing variance, 稳定方差
7 W' [( T& M A3 e% l$ @6 c& cStandard deviation, 标准差
" Y, w8 \4 q+ D, q) `$ mStandard error, 标准误* T4 J# {3 j2 [9 {9 w4 W5 X' c- `
Standard error of difference, 差别的标准误, O. ]& X& ^! y O
Standard error of estimate, 标准估计误差5 v' f% F+ S; ?# n5 F
Standard error of rate, 率的标准误 g8 c9 o2 i1 M# @$ D1 k; t
Standard normal distribution, 标准正态分布
4 K3 J, X' n0 N8 @& |$ g) B- sStandardization, 标准化& ] U( x$ J. e
Starting value, 起始值7 t0 B1 h+ D7 m# c
Statistic, 统计量
; }1 [1 X3 c6 a! G. y; f! PStatistical control, 统计控制
- A$ M+ _9 w7 W' e: C, q* L, i4 G/ }% ?Statistical graph, 统计图6 M# p5 w0 i2 A) H
Statistical inference, 统计推断$ d8 ~& H7 N1 |$ p
Statistical table, 统计表! m5 r- A: E9 |3 k
Steepest descent, 最速下降法
! H1 M& @- x$ }% H# ?+ D0 Y* nStem and leaf display, 茎叶图; a% i$ ~9 R5 O7 M. g
Step factor, 步长因子, {9 ?/ o1 X* C# U% g3 M) e
Stepwise regression, 逐步回归" r: z/ c% O0 W( ~! o$ T; s
Storage, 存
; D& V1 t7 o* X. d& |2 M# S4 p9 EStrata, 层（复数）
2 O. \$ y% p2 p TStratified sampling, 分层抽样
# V# |- y- P# f4 G9 r1 tStratified sampling, 分层抽样
8 v. m$ q2 ^1 h9 q9 I8 oStrength, 强度
+ D% `9 Y; |1 i9 ~9 }" }7 Z" ZStringency, 严密性
, x9 d( K$ L8 C* `0 c4 rStructural relationship, 结构关系6 W$ Q' p& c2 b# Z W- W3 S2 e
Studentized residual, 学生化残差/t化残差) e! z1 u1 L- J- I
Sub-class numbers, 次级组含量( Y: m* I ]2 G0 D x: B
Subdividing, 分割
8 d$ |6 E; V. {$ p% {* FSufficient statistic, 充分统计量
$ @' ~9 k! N9 |- P6 \: FSum of products, 积和) w7 \& F: l5 y5 ~/ t: _
Sum of squares, 离差平方和) D, P f7 q9 [( y
Sum of squares about regression, 回归平方和% f! }7 I5 C0 T2 g+ q
Sum of squares between groups, 组间平方和8 S H' }* C0 o, {( n1 x- T# ~
Sum of squares of partial regression, 偏回归平方和' u9 z9 u p3 a* s* n) ^& U
Sure event, 必然事件
: c/ L! {% F' uSurvey, 调查/ H" P7 q9 Y8 E9 |# _) S ?
Survival, 生存分析/ S+ C& w: G0 c7 v A0 ?" N
Survival rate, 生存率
. j& o( z, j5 OSuspended root gram, 悬吊根图1 O' \0 g. d/ E; }& s o
Symmetry, 对称2 p- n7 h# P* j5 U' B& g8 ?- u
Systematic error, 系统误差# `' G! d, E$ Y$ t* C3 ^
Systematic sampling, 系统抽样& Q- f$ R( n# N3 {$ p Z2 j. |8 y
Tags, 标签
# Y/ i% q; T* }+ R" U$ tTail area, 尾部面积
8 L# Q. P5 ? g% n; C' FTail length, 尾长
: |; h( D, l7 H5 C, }Tail weight, 尾重+ u* a9 O* b: k+ {2 H- V& J
Tangent line, 切线0 _) k$ S! j2 w4 ?
Target distribution, 目标分布
7 p A! i& C8 w: x$ g4 VTaylor series, 泰勒级数. i) }( j3 M" m6 E
Tendency of dispersion, 离散趋势
9 M6 v# |% n8 D# Z7 t6 lTesting of hypotheses, 假设检验) K/ \! Q! b$ ? _ e
Theoretical frequency, 理论频数7 T) d- D" P$ W# J/ O3 B1 U! D. ^
Time series, 时间序列
5 g% U+ m3 I5 v. X3 ITolerance interval, 容忍区间
: W( d! B( f) K; y8 @Tolerance lower limit, 容忍下限
9 J( Q8 R- k( YTolerance upper limit, 容忍上限
1 k6 w: Y* M( o' W0 OTorsion, 扰率
% a3 H0 W: Q, qTotal sum of square, 总平方和" Q2 v3 @0 F" C t" W5 M+ N
Total variation, 总变异
/ v: m$ v' x& w) TTransformation, 转换$ q$ u6 G. t: a5 V' f/ h: |& f. Q
Treatment, 处理- L8 R- X, y% @& f6 k0 ~
Trend, 趋势
; p0 P! v* Z2 |5 f+ k. YTrend of percentage, 百分比趋势% ]# ~2 D/ E& ` ]9 t* v
Trial, 试验: c: j5 S) Q0 w* L" P+ [
Trial and error method, 试错法
" O$ t" \$ H U6 D: VTuning constant, 细调常数
( v* e8 f7 ]) ZTwo sided test, 双向检验
" q4 \5 T" t0 FTwo-stage least squares, 二阶最小平方
2 T" [/ S- S c$ {' G( @; t- Y0 V( dTwo-stage sampling, 二阶段抽样
; h7 j2 `$ U8 p- `5 r# r/ STwo-tailed test, 双侧检验
' T, \+ o; _3 i! OTwo-way analysis of variance, 双因素方差分析
, `, J" R' x; ^Two-way table, 双向表& T6 F, J$ ~3 {: w/ G, e% i
Type I error, 一类错误/α错误- ^, m4 `2 a/ d7 B0 y! S) M6 G
Type II error, 二类错误/β错误. S4 V5 d' G3 t4 ?8 `1 x9 h
UMVU, 方差一致最小无偏估计简称7 j% d2 G, ]. I
Unbiased estimate, 无偏估计
! |1 b3 P0 Q& ^# T) eUnconstrained nonlinear regression , 无约束非线性回归5 {4 B, U+ t, v/ \
Unequal subclass number, 不等次级组含量: c# x' | ] k# f
Ungrouped data, 不分组资料9 b% Z3 _0 y, L5 m& \) ` A, P; o+ t
Uniform coordinate, 均匀坐标
/ l$ L4 `8 @9 E7 q' O/ KUniform distribution, 均匀分布" N: E4 M$ b3 @7 N, n2 a
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
' b/ T8 ?1 u* k% B) u1 O+ ]! q- TUnit, 单元
0 @* @) w# D" u$ PUnordered categories, 无序分类
" ]1 p+ q U* K2 uUpper limit, 上限
) j; i0 J- l! A+ Y# Z) FUpward rank, 升秩( D% ?1 B8 z. P' H3 e3 U: N, @ z
Vague concept, 模糊概念
7 E4 C" }1 l- x' Z/ F7 RValidity, 有效性' n. ` v( U G$ I/ s
VARCOMP (Variance component estimation), 方差元素估计
" S6 ]" i9 O1 S; m ZVariability, 变异性) [& A* A9 O6 v
Variable, 变量% d2 o$ a. |6 {. _, E9 ?
Variance, 方差
/ P& ^7 T) f) B( L/ s# iVariation, 变异
# C3 x! ^0 J3 S9 x& nVarimax orthogonal rotation, 方差最大正交旋转
7 x- B1 T2 j' _- QVolume of distribution, 容积
* _" ?7 i% D0 O* k. ]$ GW test, W检验7 t- D! b! O% }8 t" r: {
Weibull distribution, 威布尔分布$ X( |# W: s- s* s
Weight, 权数( j d: [# Z) z6 r5 n
Weighted Chi-square test, 加权卡方检验/Cochran检验' r* m8 i h+ y8 l- \
Weighted linear regression method, 加权直线回归4 i/ i. P) G/ @
Weighted mean, 加权平均数& R( f9 R( `2 ^: N3 B9 J: f
Weighted mean square, 加权平均方差
. @# H+ z* a) L: y+ VWeighted sum of square, 加权平方和. @( R7 d2 {. Q5 N5 I
Weighting coefficient, 权重系数* h( |. D' O# g q
Weighting method, 加权法 O9 L. K s( o6 l# ^7 e
W-estimation, W估计量7 x# K) s( n6 w
W-estimation of location, 位置W估计量
1 `; @- p) L+ j7 i5 V6 X* ?. IWidth, 宽度* ~5 j) x: q6 X; f8 \3 w' Y
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
2 ~ j: S6 c0 s7 m$ SWild point, 野点/狂点
5 Z5 J7 x' M8 G8 mWild value, 野值/狂值" H5 {( x0 \: c2 ^2 g- F2 O
Winsorized mean, 缩尾均值) S1 O, j2 f8 }/ v+ d
Withdraw, 失访 1 M7 M! b; C' D( b! |7 ~0 S
Youden's index, 尤登指数4 U3 F; |& U( V, G/ s* f) K/ t8 u
Z test, Z检验& f9 ^1 E9 M2 p/ ?& f# V+ D t
Zero correlation, 零相关
# {. s. j0 q- Q) @7 g9 s1 h' VZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
