|
|
Absolute deviation, 绝对离差, y: ^* v( Y7 e) e$ G3 \' m
Absolute number, 绝对数* S) X5 q% W0 h# L- N7 M0 k
Absolute residuals, 绝对残差3 ]8 s8 F( i, j& `
Acceleration array, 加速度立体阵
! w$ D# z; e, DAcceleration in an arbitrary direction, 任意方向上的加速度
& e/ Y2 Z3 z$ F, m0 P1 h& tAcceleration normal, 法向加速度
; X; ^- y& r; u* TAcceleration space dimension, 加速度空间的维数/ O" C' i( t* P$ C- f% `
Acceleration tangential, 切向加速度
% a) j6 T. E6 I! v3 S- \Acceleration vector, 加速度向量
8 U' ^2 L; c+ H2 j! {' t, P: TAcceptable hypothesis, 可接受假设% I* q: F! A& |" ?$ ]; w% h9 M! m1 ~
Accumulation, 累积
) N8 H( i5 u2 E2 z* ~Accuracy, 准确度6 w5 e/ `: k( }! U$ O4 ]6 \! _
Actual frequency, 实际频数
" Y3 ^4 W6 R9 K& H6 V8 v" A, NAdaptive estimator, 自适应估计量
. v% f0 t8 o1 M$ @! X2 `& qAddition, 相加- V- g$ A$ y* n$ h p
Addition theorem, 加法定理1 n2 s9 I& ~4 i& U \! J2 x: @& m5 H
Additivity, 可加性
# ~! z7 Q k" v0 \3 HAdjusted rate, 调整率! B: B/ f; t5 m' Y( d
Adjusted value, 校正值* K, }0 R2 x* \) M, f) n1 K9 ?& p
Admissible error, 容许误差0 v5 @3 Z: X& {' r5 }0 c
Aggregation, 聚集性
1 {3 z$ n1 A) k- EAlternative hypothesis, 备择假设7 I1 N3 j0 P+ u0 K8 c* Y
Among groups, 组间
/ M* Z1 l/ F' J6 Z \Amounts, 总量2 c5 O7 B1 h' u ]% S0 U5 ~
Analysis of correlation, 相关分析8 `. R1 g# r( @+ u
Analysis of covariance, 协方差分析
- ?" _8 G# i) |& G+ H0 cAnalysis of regression, 回归分析4 A4 e" D5 _# _. ~( i! T9 V0 f$ Y
Analysis of time series, 时间序列分析
% y5 c( h) L. oAnalysis of variance, 方差分析 l( @7 ~# W/ s% v% _, v
Angular transformation, 角转换% L4 j% A) k F) r+ d+ P4 O# H
ANOVA (analysis of variance), 方差分析5 l* `! O- x. Y$ k0 s2 A! `
ANOVA Models, 方差分析模型
' U" T3 n% g- c3 ]& aArcing, 弧/弧旋5 A* N0 A# ^9 X4 V
Arcsine transformation, 反正弦变换1 r5 M/ o7 P( k6 O
Area under the curve, 曲线面积6 A9 p! L2 i, j! a+ d
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
" }( `! F9 G# Q% X. o, z, s5 R( QARIMA, 季节和非季节性单变量模型的极大似然估计 - ]+ E1 x7 I/ {# T- q9 g3 N8 ~( Y
Arithmetic grid paper, 算术格纸& H1 S+ R$ S) R0 L) |' g
Arithmetic mean, 算术平均数
) Y; }( C4 {) Z# B9 u7 h) u: @$ J# CArrhenius relation, 艾恩尼斯关系0 j4 I+ x' {( \% L; g/ J# j r
Assessing fit, 拟合的评估
. ] }: q2 Z% H3 |7 r/ fAssociative laws, 结合律
* G7 c! {# r. ]* _8 n% mAsymmetric distribution, 非对称分布' B' ^) G0 M5 t
Asymptotic bias, 渐近偏倚
8 ~8 o4 C/ L5 ~: U( [- |( \Asymptotic efficiency, 渐近效率
/ z1 X* d$ B' n4 F* cAsymptotic variance, 渐近方差2 C U2 n# i' x
Attributable risk, 归因危险度
3 I9 W6 K1 d# N: _Attribute data, 属性资料
' c2 w) F) X$ D) k! a* U. }1 t' TAttribution, 属性
% I* A* _4 H# \; |8 QAutocorrelation, 自相关
; `+ p: U( J% a9 ^$ gAutocorrelation of residuals, 残差的自相关' N% d- Y7 @% \9 Z
Average, 平均数
2 U# n6 X8 ~0 C+ o T# `Average confidence interval length, 平均置信区间长度- J: C8 j0 @- F9 g+ y
Average growth rate, 平均增长率
- V9 U& ]; j2 lBar chart, 条形图+ F5 T/ y q5 b9 y: F
Bar graph, 条形图3 f- U$ B# @5 K V( |' I
Base period, 基期8 K' \; J/ ?, W { s4 B) z
Bayes' theorem , Bayes定理
4 ^. ?! q+ g8 DBell-shaped curve, 钟形曲线7 B4 X% { N# N6 |: o( E# k
Bernoulli distribution, 伯努力分布
# v$ X/ n5 {; b; O3 t8 fBest-trim estimator, 最好切尾估计量$ g1 {* E4 E: K4 [8 v: x) N
Bias, 偏性
" P) u7 T0 O4 C! C- G: e& k3 aBinary logistic regression, 二元逻辑斯蒂回归, H8 v' j* J$ G# z( ^. L
Binomial distribution, 二项分布, t( _3 k& @7 a
Bisquare, 双平方1 `- P8 C& o+ i4 \5 i3 R
Bivariate Correlate, 二变量相关
; m+ C9 U0 P6 {5 q, _* VBivariate normal distribution, 双变量正态分布
4 e7 t. V8 ~5 F" w. P8 W5 O( _1 r6 ^Bivariate normal population, 双变量正态总体
: P4 p8 G! p- N! K5 h+ ]( FBiweight interval, 双权区间
( D0 g* h- ]3 E) q3 k; q$ _/ IBiweight M-estimator, 双权M估计量+ X/ g; e' E/ I/ f' }! Y
Block, 区组/配伍组3 H$ C: S7 i) g2 ~. U
BMDP(Biomedical computer programs), BMDP统计软件包5 v$ G: i- r: O/ l$ I. q
Boxplots, 箱线图/箱尾图 t* v W) \# I
Breakdown bound, 崩溃界/崩溃点
- K4 W( [; }. |/ }/ I1 DCanonical correlation, 典型相关
7 E* s( z" v: Q+ ]! }: ]. Q8 SCaption, 纵标目
3 P' @' h, N2 S; q9 A6 e4 r) X8 UCase-control study, 病例对照研究
- b" {! l& X# o* b; aCategorical variable, 分类变量
* C* f: M# C% ZCatenary, 悬链线
3 ?0 Y* Y w9 x1 [; [ xCauchy distribution, 柯西分布! U4 e$ d% {0 F1 C$ X9 Z0 L( d, [! Y
Cause-and-effect relationship, 因果关系- f, N9 m, u; U0 Y" Q
Cell, 单元6 P: I6 n( k- y
Censoring, 终检# F; c: q- `5 g
Center of symmetry, 对称中心) ~$ P' h/ P' W$ \, A2 n/ U/ o2 t
Centering and scaling, 中心化和定标
0 e. g$ F% b7 k9 |& ZCentral tendency, 集中趋势" u3 `, @7 y* A& ^
Central value, 中心值( l* W* r t" P8 W! Y3 f
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测5 @& A9 l, P3 M/ O
Chance, 机遇
6 L$ Y7 M0 k7 d4 A5 [Chance error, 随机误差1 q% S3 O+ x1 U' R/ w
Chance variable, 随机变量$ Z/ e2 R q8 g4 s! A$ r5 c2 g
Characteristic equation, 特征方程
7 F: C7 x( |( s6 V; [Characteristic root, 特征根
$ ]8 T) ?! B* A _8 [* zCharacteristic vector, 特征向量6 s" c$ H( Y6 X1 a+ h* [
Chebshev criterion of fit, 拟合的切比雪夫准则 c4 E: _7 K9 ^! E* h0 q5 q Q, D
Chernoff faces, 切尔诺夫脸谱图1 c/ r. ~" t: R# N' z
Chi-square test, 卡方检验/χ2检验, P* A+ N& h, R# z! i# D
Choleskey decomposition, 乔洛斯基分解7 y8 [/ ]6 Z+ B* w' g- K
Circle chart, 圆图 - V# [5 C( ]4 j. z4 H
Class interval, 组距
1 M. E7 r c4 Y& w. mClass mid-value, 组中值 k7 S; L9 r0 B g- W" x9 V/ z( {
Class upper limit, 组上限5 I* K6 o6 t5 w& X& t( c4 M
Classified variable, 分类变量+ I9 ~4 ]1 _' f6 j1 O. d
Cluster analysis, 聚类分析
& ~# _+ H+ l0 }2 ]- t' JCluster sampling, 整群抽样+ M4 { m7 T7 W3 B' V, V! g/ v
Code, 代码% p9 r+ G W5 r0 F! L/ B. V+ e5 e
Coded data, 编码数据
/ f8 H: n- K2 E4 ]Coding, 编码; ^- f; `- S+ B3 G3 E! J
Coefficient of contingency, 列联系数
+ E7 p' K/ {3 r! Y1 a: l) R9 CCoefficient of determination, 决定系数$ T0 i1 w: f/ ~, n; b
Coefficient of multiple correlation, 多重相关系数8 V8 R1 X: z8 e
Coefficient of partial correlation, 偏相关系数
) j V7 q) R6 yCoefficient of production-moment correlation, 积差相关系数8 J2 V9 v7 q# Y; `0 }& c. R3 Q- F
Coefficient of rank correlation, 等级相关系数& H, O I4 u# u* C1 y% I3 G! m2 M( K
Coefficient of regression, 回归系数
1 D, m2 l& v8 X! M, t; I% pCoefficient of skewness, 偏度系数) ?, Z3 B5 J6 X+ X& L5 H( L
Coefficient of variation, 变异系数
- \# y; ]7 A" s" GCohort study, 队列研究
+ Y/ l* O9 G/ O8 JColumn, 列# k, Z! K9 [/ v) o, Q* Q+ |8 C
Column effect, 列效应2 a3 b" N$ L1 d& w b
Column factor, 列因素
B& Z$ W2 q7 T9 sCombination pool, 合并1 C. g' v o4 H" j' F- S
Combinative table, 组合表
6 Z; f4 R& p/ A+ }' z4 h/ X- MCommon factor, 共性因子$ D& f' W+ w- f3 X& r$ O1 t9 s
Common regression coefficient, 公共回归系数$ d3 w* L( H$ N4 r
Common value, 共同值
2 L4 _0 k) I8 E+ b2 v+ H" W* |Common variance, 公共方差
( X3 N- X' u; S5 A7 X1 N6 rCommon variation, 公共变异
$ i- K; m$ V( q& d; e! u+ X. ^& N* w: JCommunality variance, 共性方差( _ |1 o( K( |( S6 d
Comparability, 可比性7 B1 y- g9 D8 `0 r+ {7 _
Comparison of bathes, 批比较
* [2 O9 F! i4 GComparison value, 比较值* x, e6 U. c& g2 x7 k
Compartment model, 分部模型
! V# ]. @ e: x9 x/ F6 X4 [5 OCompassion, 伸缩' V$ X Z/ ?5 L* x2 f0 ]
Complement of an event, 补事件) {2 P9 D) [9 w! y
Complete association, 完全正相关1 z) ^8 @' {" A- o
Complete dissociation, 完全不相关1 Q" [7 [# [- y6 I6 X
Complete statistics, 完备统计量
; _# A {2 @( o( d9 bCompletely randomized design, 完全随机化设计0 R5 G" _/ }1 |0 ^* e/ r7 }
Composite event, 联合事件5 n9 c9 _1 K3 \& s2 G( U5 E: ]
Composite events, 复合事件
* l% k; [) S n7 K: hConcavity, 凹性
- z* z& R! j/ r" V. q |- YConditional expectation, 条件期望
( {! u. e, J9 tConditional likelihood, 条件似然
. J k5 @0 N# r6 GConditional probability, 条件概率
, E9 B, {: x) j, o, M1 z$ u3 DConditionally linear, 依条件线性* B- K, t" k$ `. T. W$ f7 v0 y
Confidence interval, 置信区间& U& {( v( B' l2 x# L
Confidence limit, 置信限 p5 \) L- W* O$ ?
Confidence lower limit, 置信下限
# J- _# G5 m+ D6 M$ [Confidence upper limit, 置信上限
' _7 X5 ~' q7 H9 v3 L" S4 q* E- q* {Confirmatory Factor Analysis , 验证性因子分析% J8 n" f, Q- N. b5 y) m
Confirmatory research, 证实性实验研究
; p1 H t8 L N3 ?" e- `6 G8 BConfounding factor, 混杂因素) r8 r4 V3 ?/ C3 q3 D
Conjoint, 联合分析
8 d$ j8 U, w6 u0 t! ?, sConsistency, 相合性) O: x9 Y0 x# o1 H' D7 r6 F
Consistency check, 一致性检验' F2 S+ N0 m/ v7 o% b9 D
Consistent asymptotically normal estimate, 相合渐近正态估计
" G2 j3 P7 |( U7 F7 HConsistent estimate, 相合估计
3 B; L9 w7 w0 i% ?0 o( {Constrained nonlinear regression, 受约束非线性回归" h3 s; N: r+ m8 j
Constraint, 约束8 j' c8 u/ u8 n
Contaminated distribution, 污染分布5 n4 q4 ~6 b; B$ S
Contaminated Gausssian, 污染高斯分布
7 b1 s6 c1 ?; A/ G) LContaminated normal distribution, 污染正态分布
/ B2 b+ K# ]' {+ ^( _5 ^* t* wContamination, 污染) @8 X/ \+ W* T
Contamination model, 污染模型
9 Y& F. w1 m8 I' |% F b, ]( eContingency table, 列联表
0 s( ^5 a8 I, A# _1 X5 ZContour, 边界线
! ?( `1 N& a" M4 h9 X9 I3 `" v* lContribution rate, 贡献率
/ K! o9 o# {' L& D% xControl, 对照
/ D6 N3 F. f: P" C& X6 W; ]Controlled experiments, 对照实验
$ i2 S+ p4 Z, z7 s4 n$ v" rConventional depth, 常规深度
, y% Q6 g1 D5 j% g" ]0 aConvolution, 卷积
" l; ?% M5 ^( H( H# H- ~Corrected factor, 校正因子. {) y. ~5 \8 H Q- E, a8 U
Corrected mean, 校正均值
6 p" m9 {6 w8 S2 N" P( P* ]Correction coefficient, 校正系数' H2 N" C$ `+ K/ j7 |
Correctness, 正确性$ U: y$ j8 L/ u2 z8 v0 Q3 y7 `- d
Correlation coefficient, 相关系数
$ C) m1 T6 ]1 }4 o& O4 W4 sCorrelation index, 相关指数( k, j7 j4 \0 V# o3 g
Correspondence, 对应. m9 y' V3 V9 s+ a5 s- z) C
Counting, 计数
8 `: n1 o5 `8 S* x) P5 o8 uCounts, 计数/频数
6 Y! a* Q* r. [/ R7 bCovariance, 协方差
# J a+ {. C: ?/ WCovariant, 共变 : H e$ T0 k( C8 t
Cox Regression, Cox回归0 Z" q+ B* ]1 S( j! o* _5 u
Criteria for fitting, 拟合准则7 b% C% U8 P- a( X. e+ u- V' ]
Criteria of least squares, 最小二乘准则4 Q7 {/ c8 g4 X9 x: R
Critical ratio, 临界比
1 U w' D1 t( K% ^0 iCritical region, 拒绝域/ Q* V: h- n( b8 i( q
Critical value, 临界值
& K) F# n! Y; E+ k C: w% X& r. }Cross-over design, 交叉设计5 v) t5 \& R3 K w& B* @7 U8 g2 @
Cross-section analysis, 横断面分析
, T. |2 R- J+ U- c$ mCross-section survey, 横断面调查* ]% D4 B5 v6 R3 u4 h& n5 j5 F4 ?
Crosstabs , 交叉表
- C; a! r3 B% o; G( NCross-tabulation table, 复合表
) ~- F4 x" _% j, b8 w' M4 mCube root, 立方根# W" |5 B6 ?) W
Cumulative distribution function, 分布函数
" J& v/ a+ z- {* \6 t7 }2 mCumulative probability, 累计概率
* s$ w9 g2 Q( f1 ?4 k6 y$ g' }Curvature, 曲率/弯曲
6 Z6 X1 s) I1 `+ q. wCurvature, 曲率 m6 Y: G" _8 P. R( E
Curve fit , 曲线拟和
+ F- [; H# Q4 u7 F, W# X; P% C. rCurve fitting, 曲线拟合
* N; \# r7 ^* y1 l2 V0 DCurvilinear regression, 曲线回归
1 m+ l' o) q$ C( ~( ^" [/ P9 U3 SCurvilinear relation, 曲线关系' A: e3 j3 o, p
Cut-and-try method, 尝试法
6 [2 ]/ l, [- MCycle, 周期1 l% c5 L4 A& \- @4 a4 M
Cyclist, 周期性) m; E# f- s' P
D test, D检验
?$ | U9 }7 W0 H8 OData acquisition, 资料收集
0 p5 i4 ^ X# I* P: ]Data bank, 数据库% l A( C+ P+ V
Data capacity, 数据容量
1 r1 O- h. j' w7 O0 hData deficiencies, 数据缺乏
4 i# T2 }+ `6 A0 eData handling, 数据处理, ~! W" W5 c$ o* u. G% F4 [1 |4 y
Data manipulation, 数据处理" Y5 A& ^, ^$ X- O2 l; J
Data processing, 数据处理
9 T) q: N5 ]3 B3 O: A1 w7 wData reduction, 数据缩减
' C0 e$ r4 ~1 j" l. |0 zData set, 数据集- d3 F0 A- I. p) l
Data sources, 数据来源2 m) w; P) |; K; |8 a
Data transformation, 数据变换7 N4 c" S* P& M* ?
Data validity, 数据有效性
% q) f6 Z2 [3 P( yData-in, 数据输入* f; v) t1 T" j8 v9 k
Data-out, 数据输出
( Z9 H8 u2 h* Z7 o8 G! y' ^( k& k# @Dead time, 停滞期; f2 I& A: m- m% G
Degree of freedom, 自由度
: C3 |$ Q, V& e, WDegree of precision, 精密度
B6 P% L& r) h7 }4 vDegree of reliability, 可靠性程度9 p) _; `; }1 o3 s8 Y" z" q# A
Degression, 递减
& B" ]5 }+ u2 F rDensity function, 密度函数2 |- p( j* J3 z0 _6 b$ F
Density of data points, 数据点的密度% D" |0 Q6 R+ B4 f
Dependent variable, 应变量/依变量/因变量$ S3 T/ K& v5 ^" x
Dependent variable, 因变量! w, l$ G* A2 f
Depth, 深度0 g/ g( h" w3 A6 P, @
Derivative matrix, 导数矩阵; O: B* a9 H6 p% }/ G" B
Derivative-free methods, 无导数方法
, f! q0 E5 A' @2 wDesign, 设计0 a { w4 C8 X$ \6 a0 I
Determinacy, 确定性
: k6 x( a$ m2 P6 ?- v& jDeterminant, 行列式# ?/ S+ @+ l0 {1 Z, r2 \: {
Determinant, 决定因素- ], v: j4 d0 y- `7 ^, N/ Q
Deviation, 离差& u) X3 |! o1 r* X1 s( c
Deviation from average, 离均差
3 W/ _$ f4 e Y* cDiagnostic plot, 诊断图
8 `) E9 S( Y. i0 ]Dichotomous variable, 二分变量
) H* C0 u0 ?6 b* p9 F. L }Differential equation, 微分方程
8 f2 U/ G- m7 z. r+ cDirect standardization, 直接标准化法
4 k2 @4 Y ]/ G% Z2 A/ t- }Discrete variable, 离散型变量
# z! Y B! t! h. |7 P7 KDISCRIMINANT, 判断
2 p4 |, P z$ C/ }5 }, bDiscriminant analysis, 判别分析
& J5 u% I' ` O! j1 XDiscriminant coefficient, 判别系数
$ o3 H6 I, F* h; s, S* W7 }Discriminant function, 判别值
: v% X- Z) @. c& g, E$ m* aDispersion, 散布/分散度
* e! P0 s% p2 d8 t6 ADisproportional, 不成比例的8 W0 i1 V4 ~# j; C* B+ E& L0 D$ F. z
Disproportionate sub-class numbers, 不成比例次级组含量
0 R& d/ r. ^' _) `1 nDistribution free, 分布无关性/免分布
0 _% S+ q# H5 J# c' qDistribution shape, 分布形状, E( i9 v4 I7 T) A/ e2 {9 s8 }
Distribution-free method, 任意分布法
! W7 ?2 G/ z* s; _Distributive laws, 分配律
& _1 k1 e2 \3 v2 Z, _# b* jDisturbance, 随机扰动项! X1 Z; a# f0 Z7 _; }: T- X
Dose response curve, 剂量反应曲线
' l0 m0 X( h) UDouble blind method, 双盲法( f( _4 _& F" h, L: i
Double blind trial, 双盲试验' c5 I: j- k3 J& H* N& x) ]) ~
Double exponential distribution, 双指数分布
8 W5 h t/ g6 z7 L+ f- V% R7 ]) ?Double logarithmic, 双对数9 `. P4 a9 G1 \
Downward rank, 降秩2 N6 t6 R7 K @% k0 X4 m" J! H9 \
Dual-space plot, 对偶空间图
/ d) j3 B% w& b4 TDUD, 无导数方法 ^9 C+ Q! b8 } F/ T, O% {; b
Duncan's new multiple range method, 新复极差法/Duncan新法
9 f$ P3 ]- f; MEffect, 实验效应! b& i0 D8 z, V* j) ?
Eigenvalue, 特征值
4 y F. o9 X& {# S, [: Q/ jEigenvector, 特征向量2 j" i; C0 s3 X' ?- r k
Ellipse, 椭圆
/ V/ ^$ a/ T9 z8 F( OEmpirical distribution, 经验分布& ~. C& ~' W- `5 Z2 [
Empirical probability, 经验概率单位; ]' O: a0 Z: k3 ^8 X4 s3 C$ _* B* X
Enumeration data, 计数资料
( T9 f" X" Z5 b3 eEqual sun-class number, 相等次级组含量
' J2 X* x6 |4 c; A, l9 _Equally likely, 等可能$ t' K% c( I& H/ B/ e5 L, L
Equivariance, 同变性
. g/ i* e8 p% q( Y- @Error, 误差/错误
0 P) F8 T. ^* y9 U& s. ]Error of estimate, 估计误差
3 @, M d3 e7 b: v$ O8 f- eError type I, 第一类错误
. g* M6 _2 i/ Y2 f7 pError type II, 第二类错误; \' ?* Q1 B0 U. k m
Estimand, 被估量
8 p7 N/ s2 m" b$ K: F$ t" [/ m+ WEstimated error mean squares, 估计误差均方
/ |3 M+ r# z; c2 M5 n& ZEstimated error sum of squares, 估计误差平方和
; j/ }* T% S; ?! \: C0 d( U, Y$ WEuclidean distance, 欧式距离
7 o2 y0 O) W% N2 C- a( S, ]Event, 事件5 y$ a S# N/ p: U2 m5 B
Event, 事件+ S; \7 L6 y; @. {- B$ r
Exceptional data point, 异常数据点
7 a' X! [! {6 x( o" wExpectation plane, 期望平面- p1 ~3 ^$ w7 q$ U
Expectation surface, 期望曲面2 U9 [& e7 ^6 Y/ F: v8 [
Expected values, 期望值! `' b! C$ S0 b2 x$ l1 h& _
Experiment, 实验
* W; g. y: C1 wExperimental sampling, 试验抽样
0 m5 Y1 ?0 ?7 G" Z5 R' y; z9 g% CExperimental unit, 试验单位 g# Q6 z( w8 K7 @- d0 F: S4 Y
Explanatory variable, 说明变量
; T0 Z' i, D, W; Y9 y4 R5 JExploratory data analysis, 探索性数据分析
6 i8 J# ?* B$ m, C a0 V' TExplore Summarize, 探索-摘要- A8 C- y1 x! T# i( I" o3 X1 b( q
Exponential curve, 指数曲线
% E. k* [( `, [& T/ M4 I! Q; TExponential growth, 指数式增长
, c! F' B* U4 sEXSMOOTH, 指数平滑方法
: N( l% S: ]: M [7 D4 z( zExtended fit, 扩充拟合, C% m2 N8 c+ P3 n/ N( O3 ^
Extra parameter, 附加参数
9 g) V; Q6 d( b/ r7 }5 o2 Y: y2 `Extrapolation, 外推法; Z8 J: w7 v6 I
Extreme observation, 末端观测值' B3 y7 R8 E. p
Extremes, 极端值/极值% p; x5 V' f$ x# u( f1 Z* F. O
F distribution, F分布
+ \8 B% P' P8 N, B7 qF test, F检验
. z2 t) ~, E: KFactor, 因素/因子
4 G- a* D% o2 a" iFactor analysis, 因子分析
; L% ?) l" Q+ C8 Z' `; [' m+ T/ v$ NFactor Analysis, 因子分析- d0 T: [( ]0 ]( e- G/ _
Factor score, 因子得分
% S+ J$ r4 o9 EFactorial, 阶乘
$ Z3 n% G. a. Z4 w) C/ T0 yFactorial design, 析因试验设计
7 {" i& p y! R+ O* RFalse negative, 假阴性+ H. p: ]1 k9 f/ i0 O
False negative error, 假阴性错误
# h! O, y ~: q; TFamily of distributions, 分布族
* j% @7 m, ^8 K# J" M- K' f: M% jFamily of estimators, 估计量族
- B( |8 N2 J: v3 J6 J n) yFanning, 扇面, p! z% `, m( P& H- ~. E9 K
Fatality rate, 病死率
+ K- v) l) w! `- X; y1 V+ YField investigation, 现场调查8 n- {' x5 J2 g: s
Field survey, 现场调查% k: _5 @. @( J; F# s5 c
Finite population, 有限总体
& {) z% H3 y8 V! K- a% V1 QFinite-sample, 有限样本9 n+ q! Y( ~8 v0 X* n2 S
First derivative, 一阶导数3 ?9 E/ v" f3 E6 r+ _( x
First principal component, 第一主成分0 m8 }: W, I9 u! I9 J
First quartile, 第一四分位数0 c8 ~7 @+ |# E4 @# l- w: J
Fisher information, 费雪信息量
! n9 X+ N) _2 m' `Fitted value, 拟合值
, ^7 A! f8 D! v9 X/ \# ]6 c nFitting a curve, 曲线拟合
0 {+ F% ?+ y% v- A, p. }& mFixed base, 定基
+ I6 o0 M+ ~; Q1 iFluctuation, 随机起伏8 V$ @5 n# o9 g3 x
Forecast, 预测8 x6 p, ^! O& \* B6 i% y! q2 [
Four fold table, 四格表
/ K$ `8 k% f9 p* {5 @- GFourth, 四分点
& t# G8 C' \7 N* P, @Fraction blow, 左侧比率
4 [6 G5 c7 [1 }* tFractional error, 相对误差
9 Z* H, g8 E/ h f; SFrequency, 频率
4 S9 K- a3 U9 \3 U0 `- _% k, `" aFrequency polygon, 频数多边图
7 P$ i6 ~9 c3 R2 A+ r4 i a9 h- XFrontier point, 界限点
1 v% y% b# K9 q6 n1 E% z: nFunction relationship, 泛函关系) C( N; C, [0 j/ b, X
Gamma distribution, 伽玛分布9 m% Q+ r% s% E5 ?$ [6 e
Gauss increment, 高斯增量' X. D/ Q* H- A( C9 t
Gaussian distribution, 高斯分布/正态分布+ J9 f8 T! v' U& @- ?5 B2 ~
Gauss-Newton increment, 高斯-牛顿增量
8 x: L0 m V" g [General census, 全面普查- T0 Z) ?3 F7 m7 B3 l. M0 l. ^8 n
GENLOG (Generalized liner models), 广义线性模型
/ o+ Y1 m2 i- ^$ k6 J% y$ fGeometric mean, 几何平均数
! o9 N* x2 @3 x) p4 K3 `! m1 SGini's mean difference, 基尼均差! z9 G. w8 U e& v/ t- C9 z
GLM (General liner models), 一般线性模型
4 a6 k, w+ l; v9 U4 g. t$ jGoodness of fit, 拟和优度/配合度3 W X* F, j4 v# ~* I7 w4 ~, \' x
Gradient of determinant, 行列式的梯度" l( s* b7 \% J2 z
Graeco-Latin square, 希腊拉丁方
* a X' d0 ]1 L, K+ g: \% M+ `Grand mean, 总均值2 c4 r5 |: E( X- x$ ?: G& D$ f
Gross errors, 重大错误
. s1 H4 ]; k& F& H2 ~Gross-error sensitivity, 大错敏感度
" ?5 O3 h; k( s, g$ M4 y: O$ [1 }8 GGroup averages, 分组平均
- ~- S+ z& L2 [9 \1 x2 S: H* oGrouped data, 分组资料2 p# X1 J8 q& B. D
Guessed mean, 假定平均数. {5 v2 y0 \% P% g: [
Half-life, 半衰期' j% V4 h& q. N& ^6 M4 r+ ^. P! [% r
Hampel M-estimators, 汉佩尔M估计量/ n! @ S1 T6 V' |& _
Happenstance, 偶然事件' e6 ^) f' v9 ^
Harmonic mean, 调和均数
7 U+ ^2 D( g& p4 k' mHazard function, 风险均数' W6 W. t" ?9 c" f# t4 \* t1 T; h
Hazard rate, 风险率; F$ K4 j/ L7 j
Heading, 标目
+ U' n( Q0 ~' g! ^Heavy-tailed distribution, 重尾分布, {2 N0 v3 F2 f( d* j
Hessian array, 海森立体阵
! u( ^7 e4 J; f7 e9 O* ZHeterogeneity, 不同质; B3 h2 d" m Z2 e. ~2 ~
Heterogeneity of variance, 方差不齐
# I. H/ j% v# p2 u1 ^# fHierarchical classification, 组内分组, m2 N( s4 g4 w8 y
Hierarchical clustering method, 系统聚类法
4 d) e/ t2 P( C' a+ ~' w1 ~. N+ QHigh-leverage point, 高杠杆率点
4 Z* n- U7 b0 I) ?HILOGLINEAR, 多维列联表的层次对数线性模型
! d- a8 ]" ^: LHinge, 折叶点
1 Y1 T& P) D L. {Histogram, 直方图- I: F3 x2 e$ e% E. Q/ q& t- a5 Q3 O
Historical cohort study, 历史性队列研究 2 _2 r2 @* `+ r/ z$ q
Holes, 空洞0 j5 |9 f; O- _$ Y* q9 ]- F$ Z. G
HOMALS, 多重响应分析
* }& Y j3 D$ A2 }6 SHomogeneity of variance, 方差齐性4 D) ]0 T5 p9 d
Homogeneity test, 齐性检验
# [, f0 L! v' R% o) DHuber M-estimators, 休伯M估计量
2 r8 A& e ^1 s! E% lHyperbola, 双曲线
3 p$ O* t* T! Y6 ?, v& ^( {" hHypothesis testing, 假设检验6 I! q! I/ L# A1 h" k
Hypothetical universe, 假设总体
6 o$ P( u, H2 e9 h# Y% lImpossible event, 不可能事件
! l2 i9 ]7 v/ @Independence, 独立性
! J& l8 S' b* X; JIndependent variable, 自变量2 o/ d3 e0 N5 C( j: ]
Index, 指标/指数
% u% I$ s* ?, m* XIndirect standardization, 间接标准化法
- J1 y5 e" s* [. V3 P" d1 e+ RIndividual, 个体
% c7 [5 }& q. k! b# }Inference band, 推断带# z: s2 V8 i: c; X1 y3 H
Infinite population, 无限总体
/ c/ l* j! P$ H) t8 ]! W+ Y$ ?, @Infinitely great, 无穷大
9 d* A+ H8 S. D$ B# uInfinitely small, 无穷小5 @& P+ u) G, d6 f1 m- h) ?
Influence curve, 影响曲线
: X% O. Y0 L* d5 d% Y4 w0 wInformation capacity, 信息容量; L" F8 O6 I) w4 f1 h9 S! F5 I* ]$ G, R
Initial condition, 初始条件
, y3 q; V9 U4 A2 g) O9 \1 A2 K8 s3 q' uInitial estimate, 初始估计值6 o- J) J1 z7 c' Q8 \& J, @- P
Initial level, 最初水平
" Y) P4 Z# L, Y* M- ?* gInteraction, 交互作用
$ V& \( g/ C9 \- a5 P3 O3 QInteraction terms, 交互作用项
, n+ W6 s9 Q3 l: `1 V5 `Intercept, 截距
, {4 c1 j* F% P3 ]Interpolation, 内插法$ d3 N4 v; P% o0 Z8 D) Q) p
Interquartile range, 四分位距
2 t5 z8 x0 k5 R% wInterval estimation, 区间估计
5 ]5 A; N2 g) j5 ]3 [5 qIntervals of equal probability, 等概率区间
0 y7 ?" f5 k. R0 K7 D) X* K eIntrinsic curvature, 固有曲率& |6 }) L" D0 F; k b
Invariance, 不变性( ] t" C# L" T$ }5 d( ~0 c' c
Inverse matrix, 逆矩阵
9 G3 O3 ~" Q2 g6 [" [3 V" [Inverse probability, 逆概率" U( P" G0 i' a
Inverse sine transformation, 反正弦变换' j/ p, N9 @' e6 m* M. \5 Y
Iteration, 迭代
; E) k" I8 P7 U$ cJacobian determinant, 雅可比行列式' u' s. a/ B) w R
Joint distribution function, 分布函数
/ z6 h. H; l2 I! `& b4 ]6 mJoint probability, 联合概率
% }+ J/ `" O3 u' G+ `# u9 ^Joint probability distribution, 联合概率分布
' @, e6 k2 k: c( `K means method, 逐步聚类法$ D5 g! u7 q/ \; J8 ?
Kaplan-Meier, 评估事件的时间长度
$ W7 u( k, f1 X. v& JKaplan-Merier chart, Kaplan-Merier图/ r/ c" k6 J+ z3 M- S' N" \
Kendall's rank correlation, Kendall等级相关% }. A) x- l7 U; Q; R+ F0 e. ]. s
Kinetic, 动力学
8 U4 V$ h# P/ _) \6 p0 u, z/ FKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验* _& U9 n- I. m
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 w( u; i2 |& m
Kurtosis, 峰度
6 k/ ^; {' k ]" V# l3 U$ [Lack of fit, 失拟
A1 P' f r ]4 T: C% wLadder of powers, 幂阶梯" ^! V" E l5 ]( Q$ @ @
Lag, 滞后
; W( N/ J- C' P3 ELarge sample, 大样本5 }1 W# c9 Q; x
Large sample test, 大样本检验7 M# J e/ c; N" W( e {
Latin square, 拉丁方
6 a1 f2 ?1 |: b# kLatin square design, 拉丁方设计
9 O& W9 n$ f) C) V, E- W+ X j% gLeakage, 泄漏
2 ^' v3 X$ U8 M c% N, K5 F3 ELeast favorable configuration, 最不利构形
0 q% _2 V, Y ^0 ZLeast favorable distribution, 最不利分布9 p+ T8 `, l, f
Least significant difference, 最小显著差法- I4 @5 S* g: R$ ^+ O9 \* |
Least square method, 最小二乘法
5 ]$ m" R1 i* QLeast-absolute-residuals estimates, 最小绝对残差估计
8 p" A7 j9 B2 {+ J( WLeast-absolute-residuals fit, 最小绝对残差拟合4 F, Q' u( b5 l! L0 j! D/ T8 N
Least-absolute-residuals line, 最小绝对残差线6 m. c! S, [# z: K+ ^1 [
Legend, 图例# i. D/ Z( M* f
L-estimator, L估计量
& l& Z2 f0 n3 XL-estimator of location, 位置L估计量( S) j: Y& [ H1 K' y$ p6 _$ c
L-estimator of scale, 尺度L估计量
; }8 @3 n' c6 D6 Z" ?Level, 水平
: K9 S3 A. L6 ?$ w8 \5 WLife expectance, 预期期望寿命/ D+ R* _+ i, ^% E
Life table, 寿命表
* e+ \2 X$ u' a( d4 qLife table method, 生命表法
0 q+ L* j* [5 K$ [7 KLight-tailed distribution, 轻尾分布( s4 [0 J5 S& w& ?: y2 _
Likelihood function, 似然函数
7 l& `5 P+ ~0 Z7 dLikelihood ratio, 似然比
8 F+ k9 {. C& T2 X5 pline graph, 线图, Y3 I1 l! X, `5 ]1 N
Linear correlation, 直线相关
1 R6 n# |3 l4 MLinear equation, 线性方程
8 Q* t2 o* C% n5 z+ B0 I7 `: lLinear programming, 线性规划
% d2 a- [1 I N3 V1 lLinear regression, 直线回归7 x$ V7 T- |6 M$ X5 _1 }" h! t
Linear Regression, 线性回归# |' w/ h3 w; ^* t2 E3 V
Linear trend, 线性趋势3 ^) J. D* ?. |1 u% u
Loading, 载荷
" Q& Z; K# ~8 L z" Q% r0 m% SLocation and scale equivariance, 位置尺度同变性
3 ?4 \3 I: C; I1 h: v6 r8 s: D# TLocation equivariance, 位置同变性6 \% J3 f3 b. M( o6 M' L2 A
Location invariance, 位置不变性% _1 i% X9 L! e: ^1 V" U, ^2 H0 j, g0 S
Location scale family, 位置尺度族/ Q- _/ J& E U0 n3 L: y
Log rank test, 时序检验 ' o- Q% Q {8 Z" V6 J/ q( E, Y+ Z
Logarithmic curve, 对数曲线
4 X2 l& J6 G0 I7 h2 I( cLogarithmic normal distribution, 对数正态分布
! a& @. Q8 n# cLogarithmic scale, 对数尺度) N! `+ y; S: r
Logarithmic transformation, 对数变换
. |# E; M0 @* ~* X; Y" [Logic check, 逻辑检查2 l/ x9 s. ]5 [) |2 O- ~
Logistic distribution, 逻辑斯特分布9 T" N; {. k% ~* [* t1 m- J
Logit transformation, Logit转换
" u+ x, s- e; y8 g3 `7 @$ oLOGLINEAR, 多维列联表通用模型 ! @# H G ^2 J# A3 x
Lognormal distribution, 对数正态分布, T e2 z$ R1 }9 p+ y1 K
Lost function, 损失函数
d: R2 Y" j/ u$ y+ L TLow correlation, 低度相关
2 O. f6 M1 }5 E' t2 c6 kLower limit, 下限
; z" q. s1 E# ?) X/ v, @Lowest-attained variance, 最小可达方差! ?) M/ C9 K3 Z+ T# f. F) u0 g
LSD, 最小显著差法的简称
- p3 V/ a; l H# l% H- [' wLurking variable, 潜在变量
0 m/ C% b0 _* v4 Z4 a/ D* UMain effect, 主效应
8 J" }% c; t$ W8 C" HMajor heading, 主辞标目2 O$ q' p3 j( t8 X
Marginal density function, 边缘密度函数% I2 q5 W- m& T5 ^% h- u
Marginal probability, 边缘概率, J# f) j9 J6 |
Marginal probability distribution, 边缘概率分布
w) z" N4 t% x* kMatched data, 配对资料
% O, h& R& S0 f: Y& h8 \: T+ [Matched distribution, 匹配过分布8 m6 U9 H! a. R5 C7 R& Y3 Z
Matching of distribution, 分布的匹配
) T& c, r% d# ]8 _# n, NMatching of transformation, 变换的匹配
& x" b8 O& u" IMathematical expectation, 数学期望( a/ v" S* r! ?3 G5 h% d1 `
Mathematical model, 数学模型
. J" g; U! Z/ {$ ]& ?5 O, Z2 oMaximum L-estimator, 极大极小L 估计量7 [* G3 [1 p, c. U$ _
Maximum likelihood method, 最大似然法
! Y& l2 Z) |1 G7 N2 ^/ xMean, 均数
" V4 b) c6 U7 p: @% nMean squares between groups, 组间均方! U. T) A2 N! C' `1 b& B" Q, i& {
Mean squares within group, 组内均方0 ~9 M+ ~# o7 E4 m9 j
Means (Compare means), 均值-均值比较
) y9 Z! d- c$ _# v. |( [+ WMedian, 中位数3 a w$ f* t e* V- E
Median effective dose, 半数效量
4 f) | f& k! s' e" h5 z9 VMedian lethal dose, 半数致死量/ p8 \+ L7 }7 m0 f8 [
Median polish, 中位数平滑7 d' h. j z4 F: s& W
Median test, 中位数检验% n% [+ W$ Y2 J$ X; `3 p+ |6 `
Minimal sufficient statistic, 最小充分统计量" d; G% \! a) X/ W4 j& a$ r- G
Minimum distance estimation, 最小距离估计
8 u# u2 ?! A' ^3 mMinimum effective dose, 最小有效量2 Y5 D: j/ [& j9 \2 ~! h) k' n' ]
Minimum lethal dose, 最小致死量, |; ?2 ]& h O/ ?
Minimum variance estimator, 最小方差估计量0 H8 F1 F D1 d* _
MINITAB, 统计软件包* n: T( \/ z9 k) w! u5 C4 R( a
Minor heading, 宾词标目
/ f; V' ], P3 n1 C0 b% qMissing data, 缺失值
. y. k; R' d) E/ O' _( o) xModel specification, 模型的确定
! Y+ [% D$ d4 WModeling Statistics , 模型统计& W4 M' [& w, Z
Models for outliers, 离群值模型+ q8 h! b7 L: ^
Modifying the model, 模型的修正; g+ d! K4 _2 ~4 y* v+ h% J0 S" ^
Modulus of continuity, 连续性模; Q1 v6 ^% h9 e) [
Morbidity, 发病率
* _4 F( [; v6 B4 BMost favorable configuration, 最有利构形
# W4 l4 A1 p& x" { E7 Y6 jMultidimensional Scaling (ASCAL), 多维尺度/多维标度
( c/ f# \" R7 F2 y+ zMultinomial Logistic Regression , 多项逻辑斯蒂回归
7 {0 l1 E6 R9 j: u% B* _- \Multiple comparison, 多重比较8 P& I( v H& Q( I& `9 G
Multiple correlation , 复相关3 |9 D# @3 E& D8 Z
Multiple covariance, 多元协方差
( d. C. `& S7 F8 V7 WMultiple linear regression, 多元线性回归- y' o3 g4 Y9 g# X
Multiple response , 多重选项5 g! D* c& I' b0 H9 Z4 a) A) a
Multiple solutions, 多解
/ c# p) V4 ?! s: W; Z1 V% CMultiplication theorem, 乘法定理6 M: h; n; t5 n0 f# s+ F, M# g
Multiresponse, 多元响应
8 U( l6 Q% P- ?6 WMulti-stage sampling, 多阶段抽样 N/ n# V0 {; h8 w: i
Multivariate T distribution, 多元T分布0 O5 {5 L4 @3 h
Mutual exclusive, 互不相容
3 F+ \% n+ v- y0 \1 S. d/ \+ PMutual independence, 互相独立
4 Z9 m. o+ _) J% Y( E- d; HNatural boundary, 自然边界* w& a. J K( ^" n
Natural dead, 自然死亡
0 T( T8 W% E! X: I( {" `4 t! ^; iNatural zero, 自然零
; v$ y3 h1 L; K0 D3 WNegative correlation, 负相关
6 |. t5 R$ e& }' D0 tNegative linear correlation, 负线性相关% a+ a3 v! s, E' \9 U6 O
Negatively skewed, 负偏
0 S, [+ `8 |; A3 u( @/ Q3 VNewman-Keuls method, q检验
. V6 k3 V% v J4 t2 a7 _0 lNK method, q检验
3 o& X5 i3 r, C' F+ X2 J) F8 h" BNo statistical significance, 无统计意义2 ?# |, R+ s/ H: l) U. J
Nominal variable, 名义变量8 L6 v G* y! v* i! Y
Nonconstancy of variability, 变异的非定常性1 I/ s! D. ~4 {3 m5 E
Nonlinear regression, 非线性相关& n3 ^6 Z/ S' @$ X
Nonparametric statistics, 非参数统计 o6 H$ J. x0 {$ x! X5 D
Nonparametric test, 非参数检验' m, g' A$ `! A( l D8 o% x
Nonparametric tests, 非参数检验
7 w3 B* L5 J: Y$ T L0 kNormal deviate, 正态离差# B0 A( m% T6 B$ r4 A! d0 s; X. R/ e
Normal distribution, 正态分布1 w1 X' l+ }1 A( r: H' l" D5 ]6 C; {
Normal equation, 正规方程组2 m5 O" {5 w# Z: X
Normal ranges, 正常范围
0 ?4 A& j7 w. W+ V+ eNormal value, 正常值2 e4 c4 K. w1 u) n* D
Nuisance parameter, 多余参数/讨厌参数6 b9 f- v4 s7 z( c' _6 ~4 q$ F7 W- h
Null hypothesis, 无效假设
9 H7 W+ [* G7 R0 A2 ~& o. uNumerical variable, 数值变量2 b# w, U( a- _0 `9 R( W0 _
Objective function, 目标函数
% f: {# u ?0 U8 OObservation unit, 观察单位; {, s% J/ S/ | J W! x0 ?
Observed value, 观察值; L/ M5 f& n4 G0 B5 m
One sided test, 单侧检验8 d% ]: s1 \. I2 V- ~2 Z3 {: y
One-way analysis of variance, 单因素方差分析$ t. i' w- |" v- ~6 V
Oneway ANOVA , 单因素方差分析
% r( w! M8 a5 POpen sequential trial, 开放型序贯设计
/ u. f* w0 q2 P2 F% |Optrim, 优切尾
+ |. m* f( t/ f# DOptrim efficiency, 优切尾效率
; P& h8 G4 E0 XOrder statistics, 顺序统计量
0 {; r4 f+ J3 i) x# Q3 DOrdered categories, 有序分类' _* p7 f* m4 G
Ordinal logistic regression , 序数逻辑斯蒂回归. y; w& a }. J. T7 ?
Ordinal variable, 有序变量
8 l) m4 v1 _: [, d3 X9 q: K0 gOrthogonal basis, 正交基
$ Q9 J# T( C8 B* [Orthogonal design, 正交试验设计" ]9 }: x8 o R3 r# I# G7 m2 K+ G. A
Orthogonality conditions, 正交条件$ s) ^6 N) n3 j8 Z" U# c
ORTHOPLAN, 正交设计
) E+ _* E! i% O7 I- V$ HOutlier cutoffs, 离群值截断点- K" ~ g/ m5 b6 v
Outliers, 极端值
* @. a! h$ ?. b7 I" VOVERALS , 多组变量的非线性正规相关
# \) ^; }% Z$ b9 R) ]" tOvershoot, 迭代过度) A" Q$ r# C, [. M/ d
Paired design, 配对设计
' ~3 N5 a; w4 N- A* r5 Z, zPaired sample, 配对样本9 Y5 L& ]6 h' h* Q+ O+ E
Pairwise slopes, 成对斜率
. N- j0 L- X( x& I5 rParabola, 抛物线
_5 D" x% r9 n( rParallel tests, 平行试验
( d# N' K: j H. z4 F+ uParameter, 参数
& ^4 y/ o% A3 _; d8 ^- MParametric statistics, 参数统计
: M2 N1 P* ^# n$ f5 k i0 DParametric test, 参数检验
( t5 f4 t+ s" w. Z4 {! ]5 HPartial correlation, 偏相关2 Q$ T9 {( d) p, }- g
Partial regression, 偏回归
, W) B; N9 _( B. o3 y/ R! N) fPartial sorting, 偏排序- B( ~. P( R; c" G' p
Partials residuals, 偏残差
4 I7 D8 P; D k7 m4 uPattern, 模式
, V" \, O$ m, R% i' QPearson curves, 皮尔逊曲线
4 x9 ]5 e7 J+ n- y- |Peeling, 退层, F, o- K9 U+ O3 r7 f! K& g3 h
Percent bar graph, 百分条形图
9 k1 E5 s ~4 d6 G( iPercentage, 百分比+ G" q$ U2 B4 c: E$ B
Percentile, 百分位数: ?+ [4 `4 l( ~' i2 }" t! G
Percentile curves, 百分位曲线
4 N! ~$ D0 |$ |9 ^6 ]Periodicity, 周期性
2 Z2 z3 q& D* s+ N: ~+ j+ oPermutation, 排列
: J9 }' S) U5 N8 Y9 x' PP-estimator, P估计量
* W7 m* S) z& N3 [5 tPie graph, 饼图+ E( W& K! p: z( n: H; n
Pitman estimator, 皮特曼估计量
. A3 L+ w/ n8 x" c t6 N1 BPivot, 枢轴量
8 f% s# }- _# E3 a2 e/ G4 XPlanar, 平坦8 j( g z$ [# e. P) h' L
Planar assumption, 平面的假设# ]% a" k ~5 o6 \+ j
PLANCARDS, 生成试验的计划卡' r- n9 J! p7 \6 |
Point estimation, 点估计
0 `& l6 P1 y5 F' ~2 i/ YPoisson distribution, 泊松分布8 w% W5 a1 l6 y) ]6 T3 Z6 I
Polishing, 平滑% z6 B I; \. @' ~0 A3 h) A
Polled standard deviation, 合并标准差3 y* @0 R& N) w. |9 L! @
Polled variance, 合并方差& Z9 y- |( z8 M: y/ G3 H
Polygon, 多边图; h0 ?5 U9 d4 Q2 u! [1 j
Polynomial, 多项式3 n0 e3 z8 U" G: S
Polynomial curve, 多项式曲线
; p; D# f+ \2 z9 T4 yPopulation, 总体
' e8 ?! f" X; C: W* |# {Population attributable risk, 人群归因危险度6 P1 @' C* e8 R6 W) r, V
Positive correlation, 正相关
' q$ Q7 z9 t( C8 k) x8 V! F* ?Positively skewed, 正偏" |; O0 N$ \: x8 N$ l2 [2 }
Posterior distribution, 后验分布
0 L! ?7 y9 g8 ]; @: J2 [3 pPower of a test, 检验效能4 J1 z, X/ A4 V6 P, J
Precision, 精密度( I) M' o7 z) k1 U
Predicted value, 预测值* i. O1 U; v9 F& i5 z6 L$ U2 K3 B
Preliminary analysis, 预备性分析0 A* x# O! _4 Z" X, D
Principal component analysis, 主成分分析
1 b6 x7 S; p# [0 S# ZPrior distribution, 先验分布
; T$ C- _+ x1 ]/ Z' ]! aPrior probability, 先验概率
D! M$ } T: p/ ]* M3 cProbabilistic model, 概率模型$ Z4 N9 K* v5 T
probability, 概率
* H- a$ ]/ A4 mProbability density, 概率密度( w2 {, c- l* L, p2 U1 s
Product moment, 乘积矩/协方差
, t3 c. T3 w" x: v, O' g6 CProfile trace, 截面迹图* p6 B3 q! N W T
Proportion, 比/构成比
8 N7 Q+ Y8 X+ R/ l+ q. HProportion allocation in stratified random sampling, 按比例分层随机抽样) t/ X( e8 o, I; S. O# V. U
Proportionate, 成比例
9 o6 ]; J2 k5 [4 ]Proportionate sub-class numbers, 成比例次级组含量
% T5 d- X; U6 f7 G8 e A. lProspective study, 前瞻性调查+ @+ P8 G8 u$ l+ q+ c
Proximities, 亲近性
& z6 g4 r" A( o5 O0 x' |Pseudo F test, 近似F检验) h1 Y/ ~, n% \& n4 ^
Pseudo model, 近似模型; {; D8 r* r$ Y9 l" w" |
Pseudosigma, 伪标准差
% r {7 H$ [2 P6 p( HPurposive sampling, 有目的抽样
% P3 P# t6 z0 \! yQR decomposition, QR分解
# Y5 ]6 i9 X$ y. Z T) uQuadratic approximation, 二次近似
. z8 g% C9 H4 r* pQualitative classification, 属性分类
3 e, b% a: g0 o. c% W' IQualitative method, 定性方法9 M- P* s ]9 i4 L( B
Quantile-quantile plot, 分位数-分位数图/Q-Q图
9 j, [# ^ v9 F6 \: SQuantitative analysis, 定量分析
$ k- F8 n6 M9 U1 G$ C3 I( I2 MQuartile, 四分位数
+ i4 \+ F D2 r* FQuick Cluster, 快速聚类
2 k" }6 b1 D( Y5 u3 gRadix sort, 基数排序
* I# ?" P. E+ k9 P9 G$ l6 k4 kRandom allocation, 随机化分组
. n# t! p& k9 B8 M; W. GRandom blocks design, 随机区组设计
4 b& h* }$ x1 i, ~1 y: N; n8 VRandom event, 随机事件1 P( h& {$ ?. v7 f
Randomization, 随机化- _1 C+ n) O: { k
Range, 极差/全距: W1 \/ v, G X% u0 c1 p) m( A5 v
Rank correlation, 等级相关
- h) M4 N# j7 t4 E+ jRank sum test, 秩和检验
: t3 x9 R' s) M- }: I. z- b6 iRank test, 秩检验4 g* m7 z6 @( U
Ranked data, 等级资料8 S6 X' N* M4 \% j8 z" X. [2 {
Rate, 比率
, q& R, P, D/ R# m3 _Ratio, 比例
6 [) W# [0 u1 f+ v4 i7 W( mRaw data, 原始资料7 D% t5 E1 n+ N) G. ?- s
Raw residual, 原始残差+ M- q/ q% r9 O5 u, H
Rayleigh's test, 雷氏检验
C7 Q7 i; s1 VRayleigh's Z, 雷氏Z值
! K1 g1 E2 r! o; l3 t: g/ WReciprocal, 倒数
& ?2 k. [' V3 n5 N0 j3 u$ X8 hReciprocal transformation, 倒数变换
1 |$ E. Y1 [' Y+ LRecording, 记录
! C1 e, X" a( m0 O$ u9 ERedescending estimators, 回降估计量2 k( b, h7 t8 q1 A4 `1 l
Reducing dimensions, 降维, t, @4 G9 e. B/ u/ p
Re-expression, 重新表达
$ g9 ~9 }; X( E" E+ ?! VReference set, 标准组
8 \3 p7 B' M7 J# c- c X% x5 RRegion of acceptance, 接受域
4 V# J' |9 }# H7 I$ b$ x5 iRegression coefficient, 回归系数9 N0 {' r4 h9 c7 y) h8 _
Regression sum of square, 回归平方和
7 y7 A! `! N! i' {# \Rejection point, 拒绝点- A9 o! [& m; z. R0 A; ]( i3 Q
Relative dispersion, 相对离散度
$ k1 [' x; ?! f* ~9 r6 @Relative number, 相对数
! \- \' G8 k0 c0 mReliability, 可靠性8 i' N7 ~. S7 R
Reparametrization, 重新设置参数
/ t+ K. f8 k0 Z. X+ m6 wReplication, 重复
$ s2 r \# a/ K! R+ ]Report Summaries, 报告摘要
3 L+ N; D$ W) BResidual sum of square, 剩余平方和
- J; s# @ I' U8 W. c; QResistance, 耐抗性
4 v7 b3 }+ }5 p0 R/ IResistant line, 耐抗线, M1 h" ~. ]2 ]4 F
Resistant technique, 耐抗技术8 C* b, J# j6 b5 }
R-estimator of location, 位置R估计量! T* S- p" }8 ]9 R
R-estimator of scale, 尺度R估计量
% G; [# K/ d, n# a( [8 T8 j+ oRetrospective study, 回顾性调查) M) b9 m$ a+ r
Ridge trace, 岭迹! m Q: K$ P, N* G1 X# o5 l
Ridit analysis, Ridit分析
' a/ J- @* r" Y, p% G3 {Rotation, 旋转
. S' T% { z2 S4 u4 d! @8 k" J' ~Rounding, 舍入
7 c2 M( F$ ~3 \* M" e: HRow, 行, q6 o ^7 `; U, a7 B" M& f
Row effects, 行效应2 S: Q/ W3 P. }9 e/ T5 j. u
Row factor, 行因素
' e7 I4 t* K! {RXC table, RXC表
: h, ~6 W6 q3 S. WSample, 样本1 s/ _% U. a/ ~' B2 A+ @, h# u
Sample regression coefficient, 样本回归系数
; y' v- j4 }5 HSample size, 样本量
1 f& i i. d* \. P; M, w$ hSample standard deviation, 样本标准差
' y# c* |5 y1 CSampling error, 抽样误差! F r7 M0 S1 G% r- b- O' |
SAS(Statistical analysis system ), SAS统计软件包
, R4 _- X3 o8 G4 O) \4 Y; k6 G3 K# PScale, 尺度/量表
/ k" E' u) F" R0 PScatter diagram, 散点图- P: ~6 t% c T4 n; I
Schematic plot, 示意图/简图
3 h/ Q) J7 w4 n. E( i5 qScore test, 计分检验
4 o. _- L7 c6 d$ f. K2 L3 pScreening, 筛检$ d& ]* C" ~, @ B. Z3 |
SEASON, 季节分析 7 L- z, n% E/ B
Second derivative, 二阶导数
% E' p% D, R2 q- gSecond principal component, 第二主成分/ P) P1 l, s# k. T, h
SEM (Structural equation modeling), 结构化方程模型 3 d5 |9 W7 T$ y, U* m6 a
Semi-logarithmic graph, 半对数图- [$ s# {2 ~$ P3 G
Semi-logarithmic paper, 半对数格纸* o, _1 m [) F% x% s& F
Sensitivity curve, 敏感度曲线
- G9 ~- O- ]1 SSequential analysis, 贯序分析0 v z7 ~7 a( X, w
Sequential data set, 顺序数据集; f. a' v: O% D G; w% L5 E
Sequential design, 贯序设计8 i1 G1 d( E" ~1 P2 }( ]. [! [# R, I
Sequential method, 贯序法$ L% o' l" N2 @
Sequential test, 贯序检验法2 S. t, N0 ^ @
Serial tests, 系列试验2 u$ j$ v( A" ^
Short-cut method, 简捷法 / B3 C7 l6 e) i- t
Sigmoid curve, S形曲线6 k* y, Q8 d- z( Q8 ^- Y
Sign function, 正负号函数
1 e% b- U4 [3 A' E% ySign test, 符号检验
6 r$ V9 E( ?6 ~8 t" o3 NSigned rank, 符号秩* I; ?1 @* S' H" f z
Significance test, 显著性检验5 e8 e: N" Q) ^' S
Significant figure, 有效数字+ C7 ?' s$ T* G: R
Simple cluster sampling, 简单整群抽样
4 J; T4 B1 T0 Z4 S; A& VSimple correlation, 简单相关0 o$ h$ Z" z' D6 e% b- H- S2 ^
Simple random sampling, 简单随机抽样
# e' Z1 R' F) RSimple regression, 简单回归
8 D( B+ f2 [6 c5 O5 }simple table, 简单表 I& H. P% x1 d4 Z' L8 O
Sine estimator, 正弦估计量
7 I, c% C; j' bSingle-valued estimate, 单值估计
% G: b R6 h) C9 aSingular matrix, 奇异矩阵- S& @6 Q- P! f+ f+ l9 y
Skewed distribution, 偏斜分布
* k" O4 w# h1 l, CSkewness, 偏度/ G x; e5 }# R3 z
Slash distribution, 斜线分布
& w" f$ ^4 V+ f, \' q% cSlope, 斜率- P- j0 I) ]$ \3 Q% e; v% H9 s6 g
Smirnov test, 斯米尔诺夫检验
- p6 h. V3 E& i- PSource of variation, 变异来源
0 E/ D% u! P( Z6 c8 zSpearman rank correlation, 斯皮尔曼等级相关
( `3 d( W$ y/ }$ jSpecific factor, 特殊因子
0 s. h/ f6 f9 n: [Specific factor variance, 特殊因子方差; o) ]+ i% R2 N: d( Z. A+ b
Spectra , 频谱% p9 v8 t& d. A, F0 t& I2 c
Spherical distribution, 球型正态分布
+ h- v, j- E1 OSpread, 展布
6 p, U. L7 |+ T+ F0 ]" Y7 I8 hSPSS(Statistical package for the social science), SPSS统计软件包7 Q5 ?! M) ^9 a; l7 _5 Y
Spurious correlation, 假性相关
2 q i: \) s9 P9 R7 u0 q* h& NSquare root transformation, 平方根变换
* O' [9 r! W y7 F5 eStabilizing variance, 稳定方差( I/ L, \. j8 Z4 s
Standard deviation, 标准差; @5 j" s; f2 j
Standard error, 标准误
8 s% z! }/ Z( c' b) L" LStandard error of difference, 差别的标准误( L2 y4 t- E* ~) n7 Y1 |
Standard error of estimate, 标准估计误差+ L) D) {) U7 a% d) f1 Y. g
Standard error of rate, 率的标准误
3 M! k$ K& R; ?# ~Standard normal distribution, 标准正态分布) M" C# m; e& {+ h& i+ G; z2 C
Standardization, 标准化
m6 W2 O7 B6 M0 c6 YStarting value, 起始值. l1 G' { V0 a7 w
Statistic, 统计量( u& R3 O$ w) g9 I9 C1 ~
Statistical control, 统计控制
2 M* W1 p8 M; Y) j5 eStatistical graph, 统计图# P; t8 N- p4 \2 Y3 q7 o N5 n
Statistical inference, 统计推断' V# ]+ M% l% H
Statistical table, 统计表
3 k- |: f% Q @, |Steepest descent, 最速下降法
6 Y2 |2 t( \- q, LStem and leaf display, 茎叶图$ \! k1 c) H1 T; X4 }
Step factor, 步长因子
: ^ L- w6 }4 bStepwise regression, 逐步回归
/ c& T2 r0 n m' Y: e2 c, e. V, XStorage, 存! T- ?4 @; f, Y+ \9 k! S9 g
Strata, 层(复数)1 K$ [, M# h5 f, g1 G
Stratified sampling, 分层抽样- p" M* q/ @' E# ^) J
Stratified sampling, 分层抽样
& d0 k+ C# X- H& c# _Strength, 强度
$ p/ w: Z" W; e3 r" `6 r) ZStringency, 严密性* Y5 g- O7 ~ S& V- [8 \0 ]
Structural relationship, 结构关系# n, n. S o {% p9 s4 a
Studentized residual, 学生化残差/t化残差
7 G6 J' ? n3 o7 C ZSub-class numbers, 次级组含量
* r5 B w! O( g) C: H- h5 HSubdividing, 分割7 m; l+ A7 U$ k c* Y8 a& r/ T
Sufficient statistic, 充分统计量
+ Z2 @! k5 }! e" Z) QSum of products, 积和: z8 l8 x9 f# {3 w0 ]7 P% c# S
Sum of squares, 离差平方和
5 g; m2 v/ E: W( zSum of squares about regression, 回归平方和
7 z: F% c) P. u9 @/ ZSum of squares between groups, 组间平方和& S6 B0 u) t. w( ?# S6 Q
Sum of squares of partial regression, 偏回归平方和" J2 G! C" ?, d6 q1 H3 G) }! ?+ H o; h
Sure event, 必然事件
/ t" X+ c& u; Q1 Q0 i2 W" ` uSurvey, 调查
0 J, |6 K. j. [3 k% ^Survival, 生存分析6 P6 a; T9 w( V5 Q- _
Survival rate, 生存率
& I1 v( @: w% l+ Z1 kSuspended root gram, 悬吊根图
* f& {3 v6 G" |6 ~+ ]% nSymmetry, 对称: T& k7 m0 m0 g' }8 u2 E$ A; J
Systematic error, 系统误差9 [. Q5 V% {' ]/ v
Systematic sampling, 系统抽样+ Y4 a, A1 U4 v7 L' g
Tags, 标签
' [4 }, Y$ |9 W& S3 n( f+ qTail area, 尾部面积
1 B" I' j1 J" e9 @9 H, C" k- }Tail length, 尾长
0 F- w- V' z" x9 LTail weight, 尾重
7 ?, s- O! T+ J+ U- y, ^" g' s9 ZTangent line, 切线
# E& P' U3 n2 U% Y; |, NTarget distribution, 目标分布
" C: D4 c' H( u8 `0 m! e# e& m1 kTaylor series, 泰勒级数
4 ^; J" u( ~6 _/ hTendency of dispersion, 离散趋势
, R6 N8 |3 {* E% R) E, e& K9 ~Testing of hypotheses, 假设检验% b# i0 L+ ^$ S7 Q4 x! Q# s
Theoretical frequency, 理论频数! _( |3 u( v% ?9 V' P/ I" u. g+ D
Time series, 时间序列7 `9 F( U: {1 D! X0 E0 V
Tolerance interval, 容忍区间
7 s- F2 J! s( q( J: x( ]8 mTolerance lower limit, 容忍下限
0 M( V" g6 T$ D/ XTolerance upper limit, 容忍上限! {4 g# B, S0 T' @
Torsion, 扰率' X/ J' S- d$ m3 d2 o/ S1 c4 [
Total sum of square, 总平方和' {7 g* h7 b) j8 Z
Total variation, 总变异1 u* R0 N# P! U# m- s5 @
Transformation, 转换
4 c n) R9 }4 d% h4 hTreatment, 处理
. ?3 w7 x: s- H- i3 k7 LTrend, 趋势
5 @7 Q* {% G' y& rTrend of percentage, 百分比趋势
7 U: }/ Q# H% BTrial, 试验
1 S# ^" ~% \* \2 ITrial and error method, 试错法
y# Y @/ x* M {. k4 g5 R; kTuning constant, 细调常数
U: T" |5 d( Q% z! eTwo sided test, 双向检验
( j9 _3 H8 A6 l2 a u" `( X/ TTwo-stage least squares, 二阶最小平方 Z8 W( m$ O7 U* ]/ R, M( {
Two-stage sampling, 二阶段抽样
: n" L9 J8 k7 e$ y V% x4 CTwo-tailed test, 双侧检验8 ?/ d4 P W5 `) v, a7 @$ d) R5 l
Two-way analysis of variance, 双因素方差分析
/ ]; Y4 b" t6 g' C% A5 oTwo-way table, 双向表: U% a0 Q" l, T P& K% G, W7 G4 q
Type I error, 一类错误/α错误, E1 ^8 _+ ?6 |, N- A$ K- k" S
Type II error, 二类错误/β错误# J% q) |* c2 G$ u* ^
UMVU, 方差一致最小无偏估计简称
) \; x W6 m" AUnbiased estimate, 无偏估计; Y7 ?: t5 F1 ^/ B) A
Unconstrained nonlinear regression , 无约束非线性回归, G5 V1 r3 L( R/ X
Unequal subclass number, 不等次级组含量7 L4 j6 `8 e: L7 l
Ungrouped data, 不分组资料' B6 P' H8 Z3 V
Uniform coordinate, 均匀坐标
% l r& ^! Z7 J/ x" h. LUniform distribution, 均匀分布
3 z( F8 p o n) m3 o1 FUniformly minimum variance unbiased estimate, 方差一致最小无偏估计. @" N+ X- U5 c
Unit, 单元
7 n. r& C9 o3 b% q% o; qUnordered categories, 无序分类
- F9 F3 X1 @/ f* qUpper limit, 上限, L4 }6 b/ m& W( p
Upward rank, 升秩( l9 B" K+ a4 O! H7 M
Vague concept, 模糊概念$ k0 Z$ U& d8 f0 V9 p2 ]+ d
Validity, 有效性
( c4 h. s7 c9 b/ F6 aVARCOMP (Variance component estimation), 方差元素估计% V2 @- S& ^, V- B, U5 R* i: x; s% v
Variability, 变异性 ~0 ~9 J( R$ A; A
Variable, 变量( v; ]: d/ G0 a# A/ u
Variance, 方差
! y& V6 u0 m0 {8 x l4 [( }& gVariation, 变异; f7 `) }+ w( s# k
Varimax orthogonal rotation, 方差最大正交旋转, l' u' G" i+ ?0 S" ?. m
Volume of distribution, 容积3 X5 Z4 j# t& [' s. X
W test, W检验& R+ W2 {# h: Y6 I. `& O0 L
Weibull distribution, 威布尔分布
3 C. x2 p3 k+ y' \7 G6 @Weight, 权数" J4 }( N2 X# C# y Z# l( o5 ?: q- L
Weighted Chi-square test, 加权卡方检验/Cochran检验
4 k+ F! Q: k& ]5 X vWeighted linear regression method, 加权直线回归) n( w/ Y" A e0 x8 A
Weighted mean, 加权平均数3 a# u7 t$ i* l/ H) @/ s( z
Weighted mean square, 加权平均方差
) ^: J, A7 r; V6 [! |8 J; BWeighted sum of square, 加权平方和/ Z# o+ x1 |' R- Q
Weighting coefficient, 权重系数& u+ X- a+ D$ ]+ }7 [0 P$ `1 M
Weighting method, 加权法
0 B8 a) S9 n- R! hW-estimation, W估计量3 Z1 Y: p) u* \( |% R
W-estimation of location, 位置W估计量( u# K$ w: Q; |6 b" x
Width, 宽度$ E, ] N- G* c' D! C0 _
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验. W- I4 M5 E6 }9 D* Z5 H% g4 e9 } V; k
Wild point, 野点/狂点* q: ~* ~/ x& B) ^6 J% M6 z
Wild value, 野值/狂值* B+ K) z9 V; B# W! \/ S- `6 L
Winsorized mean, 缩尾均值
; `9 }, I5 K8 d+ ?" U% R+ X! QWithdraw, 失访 5 q) ]7 m2 v5 M/ j' p
Youden's index, 尤登指数
6 F, ~2 g- P, qZ test, Z检验
) }) {/ l) U8 e& t/ a; bZero correlation, 零相关
3 J2 a% t' A! g JZ-transformation, Z变换 |
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