|
|
Absolute deviation, 绝对离差( n( Z, }0 S; E. K2 O* R; j9 V
Absolute number, 绝对数
% \5 A3 Q, g6 a- _+ c2 `2 m& yAbsolute residuals, 绝对残差" D( I8 T$ j: Y- b3 H ^
Acceleration array, 加速度立体阵
3 L- B. ] U8 N" }2 jAcceleration in an arbitrary direction, 任意方向上的加速度
6 x" x$ i3 p7 K* H# y) }1 oAcceleration normal, 法向加速度
. `0 g" {1 ^& B# x. ]Acceleration space dimension, 加速度空间的维数
/ K: \5 r0 | ]7 KAcceleration tangential, 切向加速度. U% [' {- c1 X% {
Acceleration vector, 加速度向量
: f( l; }& S: u9 TAcceptable hypothesis, 可接受假设" ?, K6 g% s8 B# M
Accumulation, 累积
% @1 b" }2 C" m( KAccuracy, 准确度
" ?8 r. Y" v: j6 E- B, hActual frequency, 实际频数! B1 @8 ?( {. D# j
Adaptive estimator, 自适应估计量2 @0 v: Z! z* T- v
Addition, 相加
* {5 @- h7 |! z9 e3 mAddition theorem, 加法定理+ y" h4 |9 `; a5 T/ s4 U- y+ m
Additivity, 可加性5 G. e% N* U& Q
Adjusted rate, 调整率
+ ]) D' O- l0 Q ^3 zAdjusted value, 校正值: A& o* Y& T# ^2 y7 h6 g1 T
Admissible error, 容许误差
4 E( e4 M& d2 ?' VAggregation, 聚集性
2 J3 i# b g$ _# [/ G! UAlternative hypothesis, 备择假设1 Y: z4 t4 O4 C8 C% |- L S
Among groups, 组间
. t* v- Y6 ?# j! r* B% E# T. @Amounts, 总量+ c- X; W/ s: m9 |: K: K
Analysis of correlation, 相关分析7 K; E) e% C& F6 c. }, N# ~0 ?
Analysis of covariance, 协方差分析! {; `: G2 Z1 Q" G# `2 {
Analysis of regression, 回归分析+ }4 G1 [- r! ?2 W
Analysis of time series, 时间序列分析
9 h+ c9 G2 [ NAnalysis of variance, 方差分析
# l5 |4 L9 l q/ }; y/ `3 B$ CAngular transformation, 角转换+ k# l/ T7 n* h& I T
ANOVA （analysis of variance）, 方差分析0 B. J0 F3 `7 [% c% y3 w; N/ c
ANOVA Models, 方差分析模型
, b" W4 S0 P4 ]+ j% \8 U$ U5 @Arcing, 弧/弧旋: _2 o; E) C% X `5 a
Arcsine transformation, 反正弦变换
5 n- @6 y# |) [7 N" }- ]Area under the curve, 曲线面积1 v; D8 X( {& W W6 C" h8 N; {
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
6 Q: F' C( Z3 l NARIMA, 季节和非季节性单变量模型的极大似然估计
5 h* \: s7 X2 g0 s/ B$ _Arithmetic grid paper, 算术格纸
0 o. j5 Q" n. O( Y7 v+ }Arithmetic mean, 算术平均数7 ]1 c3 s7 e6 r9 [
Arrhenius relation, 艾恩尼斯关系
, X# q. D+ u& y# p' g( SAssessing fit, 拟合的评估% A% J- F2 {" c3 O5 K
Associative laws, 结合律' {! M# Q) ^4 r2 F4 I
Asymmetric distribution, 非对称分布8 Y. U! M9 v' C H
Asymptotic bias, 渐近偏倚
, y- N4 |$ U! }! m; [; UAsymptotic efficiency, 渐近效率4 f" G$ d9 h: U5 z
Asymptotic variance, 渐近方差
0 |0 P9 A9 E ?2 `- MAttributable risk, 归因危险度. ~! K7 |% S5 d, \1 D9 M, K7 a
Attribute data, 属性资料 V# ~ [' ?* F& [
Attribution, 属性/ H( K$ @1 F0 `1 t. I
Autocorrelation, 自相关
: G' L5 C: I' W8 S% A$ {Autocorrelation of residuals, 残差的自相关
& J1 @3 ?6 \+ _2 cAverage, 平均数
% U$ B8 |' o9 Q" N2 ^: {) IAverage confidence interval length, 平均置信区间长度
: x: }9 b9 p( X: J# [" DAverage growth rate, 平均增长率
3 H0 k6 O& N1 i9 `7 j7 k* ^Bar chart, 条形图/ W: N0 u) T- [0 s0 N. M
Bar graph, 条形图/ D2 i* j6 `+ V" g5 E' `) \ @
Base period, 基期
( t5 I1 }/ k: D2 N GBayes' theorem , Bayes定理
- n9 R! g0 O9 Z) L4 M- KBell-shaped curve, 钟形曲线
7 _, ^$ [$ b$ Y% O8 ]* SBernoulli distribution, 伯努力分布
, i5 G" ^/ h3 b: DBest-trim estimator, 最好切尾估计量6 u8 E/ M. y: B1 F, u8 D
Bias, 偏性 {) ^* f* J* p
Binary logistic regression, 二元逻辑斯蒂回归
7 \/ \( E) v& o" ?( oBinomial distribution, 二项分布
0 G) C! c# U4 A$ c4 a6 fBisquare, 双平方: D( m' U; O/ X! I0 V9 q
Bivariate Correlate, 二变量相关* q w3 U% R7 o, {5 P) R4 `; q
Bivariate normal distribution, 双变量正态分布6 R4 x8 K+ g) p- ~: K4 a; _$ ?# E
Bivariate normal population, 双变量正态总体% m. ?9 l! S' m7 g; _
Biweight interval, 双权区间6 ^' z \+ z, B. L" ~! n, N" Y$ m
Biweight M-estimator, 双权M估计量# g9 ?4 ^- V3 Y% N2 l$ Z
Block, 区组/配伍组3 i* V1 d% K0 s" @
BMDP(Biomedical computer programs), BMDP统计软件包
. d- A v2 p- `' m, c2 O q8 |Boxplots, 箱线图/箱尾图- W9 Q; W5 {. a
Breakdown bound, 崩溃界/崩溃点
5 B4 x1 t0 l) v& l* jCanonical correlation, 典型相关
& ?3 |9 m6 v8 TCaption, 纵标目
" P+ m3 o7 B$ b! K. tCase-control study, 病例对照研究, v3 W9 `1 ~: Z7 B/ b
Categorical variable, 分类变量3 u2 ` G6 p7 Q2 E
Catenary, 悬链线
9 p" u) B4 e( @, fCauchy distribution, 柯西分布9 B, w) j% B, i" k4 J
Cause-and-effect relationship, 因果关系' ~. p! a5 A$ k1 }. Y& Y
Cell, 单元0 v! O& s3 l5 `- a3 R5 p
Censoring, 终检0 d+ g; N7 d' A4 N3 C# y
Center of symmetry, 对称中心2 k6 E3 a `; J) W/ R+ f
Centering and scaling, 中心化和定标6 v) ?4 \( Q+ G8 A5 O6 W
Central tendency, 集中趋势4 F& y E O1 M% A% _
Central value, 中心值$ t; Y% T1 E0 \, w' B7 o# |
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测) S$ G4 E7 A+ i, H% s
Chance, 机遇
5 s2 T5 W: ~: b# \Chance error, 随机误差
5 ?$ ]! \8 C6 c* J9 B7 y+ q2 E1 H: BChance variable, 随机变量
0 |) N+ C; W1 f( M4 C) w2 PCharacteristic equation, 特征方程
0 e& b; U4 W& v6 a6 k$ }7 H4 {Characteristic root, 特征根
5 L, t1 }6 w4 f0 ^8 d J3 C2 G$ S$ yCharacteristic vector, 特征向量 p5 Y/ A& \9 c2 [( ~
Chebshev criterion of fit, 拟合的切比雪夫准则4 a4 j, ]" o- B" g8 r
Chernoff faces, 切尔诺夫脸谱图
: H1 z( R8 L' QChi-square test, 卡方检验/χ2检验
e! u1 `" e4 V0 o1 E& |7 U% OCholeskey decomposition, 乔洛斯基分解# V& g) u* x1 R' X& o3 l
Circle chart, 圆图
" m5 g' F9 }5 Q7 @8 C. U- vClass interval, 组距) ~+ u% E+ v G. N
Class mid-value, 组中值; h2 |/ l: y, ], H g( S! d
Class upper limit, 组上限
# C4 c* P0 }: B# k- {- |( SClassified variable, 分类变量
) n& Z4 ?& V: b( a: r& R% d4 G1 DCluster analysis, 聚类分析
* C- W( R: h( L: j# _* L1 D8 V bCluster sampling, 整群抽样
& z4 @& {" P& s. vCode, 代码
, c: I5 p( |: M9 [$ l. x4 j5 |& hCoded data, 编码数据
5 }: y- Y. V9 y; t. _8 _( W+ tCoding, 编码 u/ M* q$ Q, @, q# ]4 V
Coefficient of contingency, 列联系数
. \7 `. D0 D4 K/ l/ d8 k: ZCoefficient of determination, 决定系数+ d+ r% v! n: F/ g- e. a
Coefficient of multiple correlation, 多重相关系数
& L; ^/ {6 g9 L( J' e8 lCoefficient of partial correlation, 偏相关系数% P: p/ E& d( J2 J
Coefficient of production-moment correlation, 积差相关系数
7 @# B( U1 h$ `* a! A* WCoefficient of rank correlation, 等级相关系数
9 P. U3 o8 W2 S/ k- JCoefficient of regression, 回归系数
( I5 e' z- K# c3 S# l7 YCoefficient of skewness, 偏度系数
- N) }/ g4 u: f# bCoefficient of variation, 变异系数& Q: a+ [) }: n9 A. y
Cohort study, 队列研究
, d4 y+ @. Z' E# W2 fColumn, 列
2 X/ i- i4 R, t, f* Y3 c! PColumn effect, 列效应4 t2 |$ Q/ k3 q$ u2 n# z
Column factor, 列因素
; |$ k% B! \( _' ?2 N$ V; d6 ^Combination pool, 合并, `6 Z! r4 O* J. q# u; D% i
Combinative table, 组合表
, i a; A( j; M: Q. _1 KCommon factor, 共性因子
# W7 i1 x* E/ KCommon regression coefficient, 公共回归系数! X7 \0 T0 H6 c) V) x: z/ a
Common value, 共同值) i' a1 C5 Z3 v' x" _- q" ]8 g
Common variance, 公共方差
, U* d0 g- t: q1 m6 N( OCommon variation, 公共变异
% H& j5 ?/ Q: oCommunality variance, 共性方差
$ U7 m* @& P1 z K7 q! g( k& zComparability, 可比性
' m6 D! L7 w+ @: m& A2 rComparison of bathes, 批比较' P- m6 X h0 h6 h" i
Comparison value, 比较值
# m9 C8 D" b. [- B F5 [Compartment model, 分部模型
+ `# W" R8 q7 `Compassion, 伸缩& J1 v% V5 [- N/ z) y( X
Complement of an event, 补事件6 e6 I3 J8 l7 J- o$ i. b
Complete association, 完全正相关
8 C1 H: b) H1 X5 OComplete dissociation, 完全不相关0 \" i' L2 ]% n1 V
Complete statistics, 完备统计量& P5 Y9 R+ `; T. T0 Y
Completely randomized design, 完全随机化设计. ?8 E! f; D3 S$ r% Z% {6 v
Composite event, 联合事件
4 L% D6 S. h' ~. b) j, k3 DComposite events, 复合事件
2 Y8 o1 H, i5 H6 ?Concavity, 凹性/ B( F# j8 P" ^7 }
Conditional expectation, 条件期望( N/ {2 {+ L. a0 j. A0 i/ F
Conditional likelihood, 条件似然
9 [; ^$ F5 A1 l" I+ Q4 BConditional probability, 条件概率
, b! q5 D r: A$ Y/ G$ @Conditionally linear, 依条件线性$ V4 |* H2 h( W8 j4 e) k2 H
Confidence interval, 置信区间- n1 k' U3 z& n& o* D
Confidence limit, 置信限' Z1 A, @4 C! w1 u7 }3 ]
Confidence lower limit, 置信下限, R) X$ M8 M3 o) v
Confidence upper limit, 置信上限( B0 g& n# {/ p, A: G' [$ c7 t
Confirmatory Factor Analysis , 验证性因子分析
) U5 A9 w9 |% e* @Confirmatory research, 证实性实验研究0 x# N, t0 X8 x, X& g
Confounding factor, 混杂因素: ~- Q; P! y/ O( l
Conjoint, 联合分析
0 ?& e2 C! {, J5 Y- MConsistency, 相合性
# i+ C- N: q8 l m: uConsistency check, 一致性检验
/ V% p' e% L9 o9 R% p$ nConsistent asymptotically normal estimate, 相合渐近正态估计2 w, x7 x+ T k$ _, \# T- @
Consistent estimate, 相合估计
9 x" D4 z7 l3 p1 A5 f* jConstrained nonlinear regression, 受约束非线性回归7 ?- P! |' D7 g+ ~% |
Constraint, 约束2 E; U& P( `9 J5 j6 y
Contaminated distribution, 污染分布
. d3 u; X8 m& w+ Q$ EContaminated Gausssian, 污染高斯分布 E5 @3 v4 R' a- u7 i
Contaminated normal distribution, 污染正态分布5 Q a' d# E+ ^1 ^; N! `$ V
Contamination, 污染0 Q7 J5 _: P+ T( F+ \4 C
Contamination model, 污染模型
8 |# }8 e1 x4 Q2 XContingency table, 列联表
" a# U' |# o& c' k2 } tContour, 边界线
3 f6 `, C9 n% q" t2 s# ?" x$ N. {Contribution rate, 贡献率
4 y" u! J, R5 @ n! T2 D/ S" nControl, 对照
6 u! Q' E8 {( \' S; @6 nControlled experiments, 对照实验. q' l' S# s* U2 J7 `# [
Conventional depth, 常规深度
2 ?+ Q' N8 A" a2 f) u. AConvolution, 卷积
, z+ A$ \4 w# i! eCorrected factor, 校正因子
# G( A1 i5 B0 _Corrected mean, 校正均值
% h8 E: E2 Y) b/ ^: j6 ECorrection coefficient, 校正系数5 v6 y2 d$ z3 q% A. H( u2 ~
Correctness, 正确性' J4 p5 Y! q" z+ X Q, R/ Z
Correlation coefficient, 相关系数+ D* s/ X( v0 N: C, W) w+ b
Correlation index, 相关指数
: j8 l% V+ w! G$ I7 MCorrespondence, 对应0 i# `, `. \) z) ^' n. L' D
Counting, 计数
% D/ i6 h) Q% o" G( zCounts, 计数/频数
5 g" j: l n. x2 c. iCovariance, 协方差2 g5 W; t5 P, s* ~8 B2 a
Covariant, 共变 3 v3 r0 P& O+ i+ }+ \0 c
Cox Regression, Cox回归
: c* Z) h( I4 m9 z6 H% qCriteria for fitting, 拟合准则9 h( Z O" C2 i6 y
Criteria of least squares, 最小二乘准则
1 }! r3 {/ [! r! cCritical ratio, 临界比
( Z, n' x6 a7 p5 d1 U# R& w* h! ICritical region, 拒绝域
, h7 N: g# T8 d- k3 ZCritical value, 临界值
~ R; ?" }+ U% m% ~$ SCross-over design, 交叉设计
2 ^# G6 ^0 m4 ?1 d' ]; |2 y" `Cross-section analysis, 横断面分析
; k9 J( |. V; W" l% e A2 `7 X; NCross-section survey, 横断面调查
0 B& n( Z* h1 n# U; m, u; B1 ECrosstabs , 交叉表
3 j, n' q' J. o1 N2 ^0 N5 t2 s. u8 ZCross-tabulation table, 复合表4 I4 f" N9 o% T& J3 ]. P5 i
Cube root, 立方根
8 F8 k+ o3 q3 I; |" v8 _/ J4 DCumulative distribution function, 分布函数
3 ?* L4 R3 Y2 D6 M* q2 lCumulative probability, 累计概率
# d9 T) p0 L/ M6 C' p4 L; [Curvature, 曲率/弯曲
& S$ f7 y# k/ A2 P" dCurvature, 曲率
, _: U& G2 P) K l1 rCurve fit , 曲线拟和
& W `$ t! R0 \ |: ~Curve fitting, 曲线拟合
* Z; ^# S2 i& [& J# W2 B1 cCurvilinear regression, 曲线回归3 h8 t, _, y# ?' J& T
Curvilinear relation, 曲线关系: w, X5 D! Y- ?9 P1 M
Cut-and-try method, 尝试法
8 w( N) |1 e; J. aCycle, 周期
) R! }( B& G0 L k2 A. ?Cyclist, 周期性
( z0 O4 H# S0 [1 ?( ^( I2 s: S& ZD test, D检验! }4 g6 k2 v8 G5 f7 O) _+ W- H
Data acquisition, 资料收集6 }. w$ j, F7 K' {0 {. S
Data bank, 数据库
9 z! e5 r( A# E k" yData capacity, 数据容量2 p% a8 M, @. s) r. p
Data deficiencies, 数据缺乏
1 H2 |! c; T8 ]' G& S) u; m6 SData handling, 数据处理: `$ G: a0 v6 O: e O/ \6 ]
Data manipulation, 数据处理
) [1 `6 b6 I6 AData processing, 数据处理
( h) c: A6 Y7 h2 h7 CData reduction, 数据缩减0 B0 F) |& g8 g; ~* o, v
Data set, 数据集# b( T; T* f2 X
Data sources, 数据来源
$ D$ Y% K% |9 M6 z# c/ bData transformation, 数据变换& |% Z# D" }/ Z) Z# R8 b* v6 E. v m
Data validity, 数据有效性1 S ?# Q2 V& L
Data-in, 数据输入
8 R" v. s& H6 L+ g& L$ l' ]; }Data-out, 数据输出
Q' |" Q8 p: X3 U( dDead time, 停滞期
( e) z1 c5 C0 I1 R) v) GDegree of freedom, 自由度3 I0 H% B, m9 y }- W: p; z- d
Degree of precision, 精密度+ Q* M: P5 u/ t) Q3 ]
Degree of reliability, 可靠性程度
3 B$ h4 E% ^( x, I' yDegression, 递减
! f3 z; c" F. U* a3 U1 UDensity function, 密度函数$ h% u3 C( L7 a' R6 q9 y/ ^
Density of data points, 数据点的密度
9 j0 j1 O4 Y( P! {Dependent variable, 应变量/依变量/因变量$ X% u6 H& E; Y K
Dependent variable, 因变量
1 o$ s' N6 ?! @# B8 y- ?: v e9 mDepth, 深度. [, {7 C/ c7 U: s
Derivative matrix, 导数矩阵
, S6 q! r" }9 K" Z0 V' n3 `2 I eDerivative-free methods, 无导数方法
6 G& [0 ]+ c7 P% |" Q9 _7 F4 iDesign, 设计
* ?9 T w" U+ y- |/ rDeterminacy, 确定性" G. ], Q8 A. F
Determinant, 行列式% D7 n4 i- k/ u2 g! w
Determinant, 决定因素2 ]2 d8 `2 Q6 o- F& l6 ^
Deviation, 离差
: q, @ h! v. |) [7 F5 Z. ODeviation from average, 离均差* k) ^" o; x. p% X, m1 n- E# A t
Diagnostic plot, 诊断图
- l7 v, k) R. U. O" f$ TDichotomous variable, 二分变量, I! T) R6 g: m3 I2 L; t6 X7 V
Differential equation, 微分方程0 `+ U9 L5 e7 v0 n( ]% o
Direct standardization, 直接标准化法8 w6 W. W, m: \# W: |
Discrete variable, 离散型变量
9 w. h% S* r+ o- f( t, `DISCRIMINANT, 判断
4 D! [6 q. V3 E( M+ EDiscriminant analysis, 判别分析1 |( u' A Y/ \; I0 n
Discriminant coefficient, 判别系数 y- t) F, C1 Q
Discriminant function, 判别值
0 U* i1 Q I* wDispersion, 散布/分散度
8 J7 ?0 u5 X( P( h; I# fDisproportional, 不成比例的% N5 z* X0 P# S i
Disproportionate sub-class numbers, 不成比例次级组含量0 }6 n5 n7 v* y" Q
Distribution free, 分布无关性/免分布
% l) |! h5 m7 K. RDistribution shape, 分布形状
0 q8 F0 M2 w, }" B# H3 d2 H# y( n9 b' j gDistribution-free method, 任意分布法: R# Z$ Q1 e# w. g! n
Distributive laws, 分配律
8 k: b, F- ~ [) @. x! T0 ODisturbance, 随机扰动项3 l2 [. \( Z0 _. G& @, Y- ~" p" e
Dose response curve, 剂量反应曲线+ P& {; q# b+ Z
Double blind method, 双盲法! Q9 b& }7 b/ N( m$ J0 k ]4 |
Double blind trial, 双盲试验$ m+ l, u: u1 ^, a. E1 K( M
Double exponential distribution, 双指数分布
9 F- h$ \; h5 a, k) t+ g* mDouble logarithmic, 双对数0 _5 H5 l0 e* D- \7 a8 i
Downward rank, 降秩
. d: n* G! [# k: u/ p: y+ Y* j$ MDual-space plot, 对偶空间图
( o* U% P* H% [. L% m9 }6 cDUD, 无导数方法9 Y2 \, r# U: q, V0 ^7 [. [
Duncan's new multiple range method, 新复极差法/Duncan新法
% i/ p0 O0 e8 l @3 _9 TEffect, 实验效应
. d; D3 {8 l2 G# ?8 ?Eigenvalue, 特征值
, a% D R( w9 d, E. E9 s" P. ^' jEigenvector, 特征向量
5 e2 d5 p8 y1 V* EEllipse, 椭圆" r x7 z0 a3 ?/ n7 L
Empirical distribution, 经验分布" J' E( R& L7 z9 |) \/ y
Empirical probability, 经验概率单位1 X% U" ?9 }3 `/ y! r: T% V/ ]
Enumeration data, 计数资料
( r) e7 n8 J/ i( p FEqual sun-class number, 相等次级组含量5 k8 m { D3 M
Equally likely, 等可能
4 N" w% y W% H/ Y/ F6 e: o5 X7 uEquivariance, 同变性+ G# L$ B# N* D/ u4 v$ `! [
Error, 误差/错误2 {& Y! }* b3 _; ? P+ P- y
Error of estimate, 估计误差7 K8 k2 G3 N3 p9 w9 E
Error type I, 第一类错误
& R" P3 [! o t7 m3 z# YError type II, 第二类错误
! x& m# w2 ^: c6 ]Estimand, 被估量' t& |+ \* N" C9 ]
Estimated error mean squares, 估计误差均方
% s; }/ z- Z- x) u2 h7 F6 O* ^Estimated error sum of squares, 估计误差平方和! m* U; t0 w6 C# L O
Euclidean distance, 欧式距离' r3 ` L. r# {3 f4 A @! q( K0 a
Event, 事件) e h2 W6 ]# ^8 u+ l. G7 {7 Q
Event, 事件2 O+ \0 l- i: A" L; a
Exceptional data point, 异常数据点+ R& {! R5 _( D
Expectation plane, 期望平面
3 F' J; y, T8 F* ~' OExpectation surface, 期望曲面4 W* G7 G, B9 j" M0 p1 P4 A6 }
Expected values, 期望值
% T. j& j4 x5 ]/ r* ]! d, J9 ^/ VExperiment, 实验7 Q% G# \5 C1 G+ x1 W. V
Experimental sampling, 试验抽样+ T: i g0 A% |# y; t- x$ d
Experimental unit, 试验单位4 C. f& W) K- Y2 n
Explanatory variable, 说明变量2 M: ]( G. |# y* a! T% T' E- c
Exploratory data analysis, 探索性数据分析
G; y" s" \% r6 T" d. _. OExplore Summarize, 探索-摘要
1 @7 s% ?5 H* t. S2 m) vExponential curve, 指数曲线
0 R& _6 i* H2 y0 h4 q, Z' P2 jExponential growth, 指数式增长; Z/ F% S c' s2 x4 R2 i
EXSMOOTH, 指数平滑方法
" _" [8 I) N9 x' JExtended fit, 扩充拟合
2 f& q9 k* w5 x5 s: c- U) B' gExtra parameter, 附加参数
) E* l" D( ?# [) EExtrapolation, 外推法3 x& I3 m7 j1 C
Extreme observation, 末端观测值
+ A: b) l( } ~ i8 hExtremes, 极端值/极值
. @# ?0 A2 z7 X1 K" s9 @F distribution, F分布
+ q7 C0 T4 @# D: C5 z" dF test, F检验( s5 F, J& r* o3 @: X! N; s
Factor, 因素/因子
% P* Q& N d4 BFactor analysis, 因子分析9 j I" T! d+ Q8 x* K
Factor Analysis, 因子分析4 {. C" ^; \8 B6 x) F' N4 d, W6 c
Factor score, 因子得分 - m6 h4 u+ l+ v( M9 ~1 Y U
Factorial, 阶乘
2 i# L" J8 r3 z: LFactorial design, 析因试验设计$ o: w) ?: J2 H( V4 h
False negative, 假阴性
+ }# J2 {4 i3 YFalse negative error, 假阴性错误: p8 L0 P+ n' _
Family of distributions, 分布族
# g$ t7 o# m5 I3 ]0 H2 hFamily of estimators, 估计量族
" D, }( x- B* E& W6 e' C mFanning, 扇面4 [$ o) E" u% y
Fatality rate, 病死率2 r9 a* }) z1 N p
Field investigation, 现场调查# `- u1 E" Z) j* y# s
Field survey, 现场调查6 @! F- Q5 J9 B0 @' e
Finite population, 有限总体' v w( M1 e% K' l8 c/ s$ i
Finite-sample, 有限样本
( c( w4 U' a$ X' fFirst derivative, 一阶导数8 |) d3 Q. b- d
First principal component, 第一主成分 T9 u: H' }% |& r& }
First quartile, 第一四分位数
. E. x7 g q' a* V# Y) m- T r, m- bFisher information, 费雪信息量
# [1 s, v6 T4 cFitted value, 拟合值) q1 ]" W. B& O/ \% p
Fitting a curve, 曲线拟合' M# t/ H5 B6 Y: S8 @$ |" u
Fixed base, 定基
$ q0 |6 p1 N) F+ r8 MFluctuation, 随机起伏' x$ P( ]# V; }, B: ?* a7 D1 [
Forecast, 预测
+ l3 s% @& g; N8 h7 `Four fold table, 四格表4 J7 d/ u% p n) z, L9 ^
Fourth, 四分点
" H# a) k) N% |4 FFraction blow, 左侧比率
+ C6 A- I7 V3 k6 _5 M2 j1 S: kFractional error, 相对误差
" _* T# {' e3 ^* E# ~' g& xFrequency, 频率; X X/ V3 U- a5 L' L8 [8 {
Frequency polygon, 频数多边图8 D5 l4 M2 n) L: l: I5 D- I+ U
Frontier point, 界限点: i x$ J f( A3 s5 Q) M" T
Function relationship, 泛函关系& D% i" V8 L/ m) ^# g' j; g) k
Gamma distribution, 伽玛分布
7 k8 V$ \1 s& u& r- c) MGauss increment, 高斯增量0 l: @( a. B1 W7 |) M$ u( P
Gaussian distribution, 高斯分布/正态分布( `) q* c1 u/ ~
Gauss-Newton increment, 高斯-牛顿增量; X. |- c4 j+ ]; {6 Q4 h
General census, 全面普查2 s% K+ y6 z! ?0 i+ A
GENLOG (Generalized liner models), 广义线性模型
1 N1 q) I7 W! f6 oGeometric mean, 几何平均数
3 {) L/ F+ S5 X2 ^Gini's mean difference, 基尼均差$ v( R$ b3 i* f- m+ k5 f
GLM (General liner models), 一般线性模型 6 o" w$ h) v+ y
Goodness of fit, 拟和优度/配合度
& t* h2 h& S! c# dGradient of determinant, 行列式的梯度$ R5 f2 G" p/ J3 |5 J: R
Graeco-Latin square, 希腊拉丁方
% n' ^3 K* w1 Y8 @Grand mean, 总均值9 L8 m( l4 O9 ?2 H
Gross errors, 重大错误
; l% ]& ~" |" v! KGross-error sensitivity, 大错敏感度" E0 _$ J5 g5 y0 _8 ]
Group averages, 分组平均
+ {6 F! h+ B0 M" W4 s+ }Grouped data, 分组资料
|' j6 n8 `: X0 nGuessed mean, 假定平均数
/ c* j1 p0 |; r1 k4 T$ M: GHalf-life, 半衰期
' R) R; m2 X8 O' EHampel M-estimators, 汉佩尔M估计量2 Z0 j1 b4 {; E, x/ V8 x2 G
Happenstance, 偶然事件
( X4 S! i% L9 z) j2 N+ u3 KHarmonic mean, 调和均数: {. M2 C: w) L5 }! g4 D
Hazard function, 风险均数
- E( g# Y1 [, u( {Hazard rate, 风险率
# f; D: E0 ?8 C: M1 x+ b% J/ jHeading, 标目
) H, k% M' w' ^8 u2 l" t% G9 L6 X# xHeavy-tailed distribution, 重尾分布) r! P( X# g! `! [8 `* |! D) ?. ~
Hessian array, 海森立体阵% V+ A( v) o6 J. v6 j
Heterogeneity, 不同质
8 g# _ ^( D% r6 a" J$ @+ J" wHeterogeneity of variance, 方差不齐
; i3 J9 I D$ ~1 u9 l. h. k! THierarchical classification, 组内分组8 H$ }. H8 D: q) m
Hierarchical clustering method, 系统聚类法+ F$ f$ F2 l5 |/ Z7 w* Z
High-leverage point, 高杠杆率点% B/ N7 Q7 i" ~) e0 j
HILOGLINEAR, 多维列联表的层次对数线性模型
" b! s7 D6 }# oHinge, 折叶点
- N+ t/ M1 O' s/ ?2 m8 |8 M tHistogram, 直方图
8 O0 @! g! y) QHistorical cohort study, 历史性队列研究
" o! s) \0 S. d% ]Holes, 空洞
9 r' h# T& X1 h/ bHOMALS, 多重响应分析% E! W5 C9 d4 w( T$ C
Homogeneity of variance, 方差齐性
, c* |& |! S" y9 T% d" EHomogeneity test, 齐性检验
/ d" E5 [" [8 P# {) O A+ UHuber M-estimators, 休伯M估计量0 _ V' Q; n0 W) b8 o/ ]# o
Hyperbola, 双曲线7 w) |3 K0 K0 J; R7 h, [8 f
Hypothesis testing, 假设检验* E& \; h5 W, ?- z
Hypothetical universe, 假设总体2 G- _9 q- f* [7 Q; {0 U
Impossible event, 不可能事件
/ n/ x6 X5 x! |8 I' C9 Q. ]Independence, 独立性
! K: H# E* I* Y! J3 _6 [% O1 RIndependent variable, 自变量+ O4 _& a9 h! K* M# S( y9 H
Index, 指标/指数
, x) r' v% G3 z; v0 |9 Z) Y& t- l( T/ aIndirect standardization, 间接标准化法
7 l1 |8 v: P4 o8 VIndividual, 个体6 u) H2 e7 X& a5 e( v& [- V
Inference band, 推断带4 |2 K7 K4 d( u i- Y
Infinite population, 无限总体! j* y; T, d! p
Infinitely great, 无穷大
6 q& X+ S9 r' m% M/ P IInfinitely small, 无穷小
; O) J* B; s0 l* X( e' x+ LInfluence curve, 影响曲线9 @3 j* \9 `2 C: ^. l6 B
Information capacity, 信息容量7 a4 a6 H w1 r* ]- [6 Z
Initial condition, 初始条件
5 l- u( I4 B' I% v4 _! qInitial estimate, 初始估计值8 M. G$ |1 m7 C
Initial level, 最初水平
0 @! Y4 i6 S( q' U( eInteraction, 交互作用
4 v4 D. l' r) ~2 OInteraction terms, 交互作用项
. \; ?& n4 W2 V) o( GIntercept, 截距# T0 l f! ^- O
Interpolation, 内插法
9 X( l, H; x1 K- C1 r6 KInterquartile range, 四分位距
- i1 B5 ^ a6 yInterval estimation, 区间估计! B: o1 j9 N7 E! ]* `! r
Intervals of equal probability, 等概率区间
, ]# t: z: `: MIntrinsic curvature, 固有曲率& w1 a$ }8 O1 ?
Invariance, 不变性4 a }6 s& N- ]- ~* x) ~$ W9 D0 K* ?: K
Inverse matrix, 逆矩阵9 K! h7 u7 S; G8 A& M* V
Inverse probability, 逆概率( S+ v6 E# s$ o! @& U
Inverse sine transformation, 反正弦变换
! O; T! {% [) Y t8 |# rIteration, 迭代 5 {: s, q; \- p
Jacobian determinant, 雅可比行列式
. V2 e/ G: G5 q6 `& I( uJoint distribution function, 分布函数
2 Z: V" H7 E* Y. o, c3 JJoint probability, 联合概率
( n4 @6 c! ~, n: ]5 D! M) NJoint probability distribution, 联合概率分布
% l1 ^' A% c, ?K means method, 逐步聚类法% I, o+ s0 N2 P( M/ V6 z; K) f+ d
Kaplan-Meier, 评估事件的时间长度
- e5 j; D& t: u) FKaplan-Merier chart, Kaplan-Merier图
3 ^/ h$ u0 m5 ^Kendall's rank correlation, Kendall等级相关1 D# P& |; R! x0 N8 l
Kinetic, 动力学+ d G1 L$ U1 x y* C# R2 C
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
. r0 j) l4 S3 m gKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验$ I9 t7 H, Z7 D; ]; v4 {
Kurtosis, 峰度
" i0 O) a+ Y* _+ f) H/ q8 PLack of fit, 失拟
) n2 A# H b1 Z, fLadder of powers, 幂阶梯
* n ?0 [5 f3 r6 O: E. g4 U! LLag, 滞后
2 f% Y/ Y) }( bLarge sample, 大样本5 `5 M) [/ ]/ R
Large sample test, 大样本检验
0 a! r E) C& F9 V2 ]7 yLatin square, 拉丁方8 r0 g8 K4 _3 l9 y' N
Latin square design, 拉丁方设计
( s, Z6 Q$ O/ TLeakage, 泄漏
6 U& A; G# {1 t" t4 \Least favorable configuration, 最不利构形& U p: {" s& J/ [
Least favorable distribution, 最不利分布
$ S3 U0 p- N. ?; E" t+ DLeast significant difference, 最小显著差法. H: x/ r$ G$ o" @0 V
Least square method, 最小二乘法( E( o; Z4 Q* M9 R
Least-absolute-residuals estimates, 最小绝对残差估计1 ?, O! ^+ Z# u' K. D) q/ `$ B
Least-absolute-residuals fit, 最小绝对残差拟合2 W! f+ e* Q+ Y0 w
Least-absolute-residuals line, 最小绝对残差线: A$ k+ `: l& D- u2 P$ ~1 m' ?
Legend, 图例1 o# D* F- [" w+ K
L-estimator, L估计量
% g7 \0 a- }& @- Z; NL-estimator of location, 位置L估计量
9 p8 B# D( Y' l' h E* [- KL-estimator of scale, 尺度L估计量. n$ ?0 R3 G8 x, }$ b* r( d2 e; Q
Level, 水平+ H! P* s7 [% a6 [( {
Life expectance, 预期期望寿命
; P7 ]( L! F' ^1 _$ }$ r5 A7 i& CLife table, 寿命表
1 @$ E7 ?8 Z9 M0 x0 x( E! k4 `2 l- KLife table method, 生命表法' s7 K: K6 n. b U m* s
Light-tailed distribution, 轻尾分布% D+ T& e8 S- c
Likelihood function, 似然函数
- L& v5 J( l" G# l# {Likelihood ratio, 似然比) h9 c5 B8 j! m3 ~& |3 Q
line graph, 线图* x4 r1 N8 q' t* }
Linear correlation, 直线相关
( k& ^; y/ I- Y/ V! b0 A: `Linear equation, 线性方程) b% h$ w7 N* n5 m# K j8 {% A
Linear programming, 线性规划4 l% D/ o9 }+ f# Z) }. r# t
Linear regression, 直线回归
9 D! z/ Z7 t8 k9 I( NLinear Regression, 线性回归+ X- H! A. N$ r8 z; s" O
Linear trend, 线性趋势
* `6 z; X! v0 p+ v4 mLoading, 载荷
) J" b3 [6 h0 `1 k8 hLocation and scale equivariance, 位置尺度同变性
6 F) q2 j3 b* h7 T- vLocation equivariance, 位置同变性
o: Q2 m6 [6 GLocation invariance, 位置不变性! F% L& N( {/ B X2 D
Location scale family, 位置尺度族
+ e: ^+ }; U4 C! H4 hLog rank test, 时序检验
- Z# R: F' M4 v3 |+ TLogarithmic curve, 对数曲线
) ]4 B, h, h) f4 R% `Logarithmic normal distribution, 对数正态分布
5 K# {/ n, B( g0 k1 }Logarithmic scale, 对数尺度
# ]4 ~% j( S; ~9 a* zLogarithmic transformation, 对数变换2 A- D; ?; K+ f9 u$ {5 E5 ?" i
Logic check, 逻辑检查8 x) ]9 g7 D/ W/ u6 w2 L5 X
Logistic distribution, 逻辑斯特分布8 r4 T. x3 g n' ~' S' U
Logit transformation, Logit转换! o! R1 t& V/ e9 F, g
LOGLINEAR, 多维列联表通用模型
# b/ ^3 p: t) u* x; sLognormal distribution, 对数正态分布
% S0 t1 o4 Y7 R- e3 z1 C" K* R: jLost function, 损失函数
* J* y9 t' v/ q7 VLow correlation, 低度相关
7 }- h- o( C: Z( ?Lower limit, 下限1 {- [) O3 X- A
Lowest-attained variance, 最小可达方差
; r: s- g: X4 I; t: ^$ R! L+ ELSD, 最小显著差法的简称
" w; u+ M% W7 k4 p Q1 ?1 cLurking variable, 潜在变量4 z. o1 ]/ t' w" |! f
Main effect, 主效应
9 w7 }/ l" h% b" B3 ~; F+ \Major heading, 主辞标目+ P- H7 S6 j& Y9 K* j2 f
Marginal density function, 边缘密度函数: r5 V+ M* \, B" B/ {# _
Marginal probability, 边缘概率0 e; ?" S) x' l- O2 x6 Y- }
Marginal probability distribution, 边缘概率分布
9 t+ v( t2 ^. A/ A# O- i" t* }Matched data, 配对资料! O& c& e1 p( Y/ n/ t
Matched distribution, 匹配过分布
' Q% o( j/ l3 b+ d' A: a5 BMatching of distribution, 分布的匹配: j8 V) p7 q0 s% ?
Matching of transformation, 变换的匹配
( \! G9 F# L' g3 hMathematical expectation, 数学期望5 a) F& F$ ^; h! O
Mathematical model, 数学模型1 W, G( p! ^+ t: ^2 J4 S
Maximum L-estimator, 极大极小L 估计量
u1 G: D0 m! T: h5 v$ }Maximum likelihood method, 最大似然法& @) N J' ]! Y' E
Mean, 均数
6 G8 r E7 z3 Q5 k' E; V0 W- ^Mean squares between groups, 组间均方
5 L; d% |1 w, G5 m# EMean squares within group, 组内均方
. D p6 K/ S8 @; {1 Q7 N+ L8 F: dMeans (Compare means), 均值-均值比较
4 C) B3 ^" q8 V& p$ YMedian, 中位数
2 \* _2 y" p0 DMedian effective dose, 半数效量
* l6 B8 G# P! d: m/ LMedian lethal dose, 半数致死量( f7 N" y2 Z' E- b
Median polish, 中位数平滑
. F6 X+ Q/ B7 XMedian test, 中位数检验
- Z, g! V* F) q. f! }, sMinimal sufficient statistic, 最小充分统计量
. A8 i7 z( _! j eMinimum distance estimation, 最小距离估计
7 x% ]! S6 Y3 K& ^, x" |Minimum effective dose, 最小有效量, V+ t8 i/ h7 c/ [0 W
Minimum lethal dose, 最小致死量* F) C2 _9 A6 X$ N, n$ t
Minimum variance estimator, 最小方差估计量
' g; F8 k$ V* G4 MMINITAB, 统计软件包
1 V: x p! Q; v' X0 X3 t7 OMinor heading, 宾词标目
1 u2 v& b4 H d6 f" \! GMissing data, 缺失值
) V( k% P+ ], Y9 \0 oModel specification, 模型的确定3 ]( R9 R7 m7 w; ^4 S9 `4 V$ H
Modeling Statistics , 模型统计3 ^& d& Z) F; |2 |% ^, P0 v
Models for outliers, 离群值模型
3 e7 V8 r4 G! C/ `0 J+ HModifying the model, 模型的修正: H, [# F" b; {" R# _( q& f, {% I
Modulus of continuity, 连续性模
+ y! q+ E( i2 c& t& oMorbidity, 发病率 6 t Y6 J# ?3 @$ v- I! ]
Most favorable configuration, 最有利构形
) Z+ \/ W1 o1 a1 _0 S7 ]Multidimensional Scaling (ASCAL), 多维尺度/多维标度
8 C) ]% V; K+ R! G0 qMultinomial Logistic Regression , 多项逻辑斯蒂回归
% q) @: t" V0 YMultiple comparison, 多重比较 j1 J* ^" @$ ~" f' r
Multiple correlation , 复相关 Q$ |) ~9 [8 O5 d( Z( q1 K
Multiple covariance, 多元协方差
0 r9 h6 [9 |0 Z5 E+ P! A/ ~Multiple linear regression, 多元线性回归, h" [8 @& A. `' l
Multiple response , 多重选项
4 P/ H R0 h: x1 WMultiple solutions, 多解
% `& U% o* f: ^7 ~! F; T! iMultiplication theorem, 乘法定理% n$ G4 P6 C. ]% u$ s, R9 E" T
Multiresponse, 多元响应/ W, V# u/ h+ {8 C
Multi-stage sampling, 多阶段抽样5 y$ J9 m x+ }+ Y+ R: b
Multivariate T distribution, 多元T分布
6 n( s' o# l QMutual exclusive, 互不相容
3 I$ ~5 B8 Q$ ~Mutual independence, 互相独立
) i( e$ g3 j" |! d- O( Z( fNatural boundary, 自然边界( g( o* q. [1 [$ e5 l" X
Natural dead, 自然死亡 i" A6 g- Z2 k1 p8 F8 M( {; s
Natural zero, 自然零) p' m# r6 ~( @+ P: ~- B+ ~
Negative correlation, 负相关
4 s" F' Z# x. M% ^( ~6 o0 JNegative linear correlation, 负线性相关) W/ j: b, d& g0 ^2 X1 Z
Negatively skewed, 负偏
6 j! F" O" e% v+ y9 o" tNewman-Keuls method, q检验, V% o2 {. \3 Q/ \' e
NK method, q检验6 b. R2 g! i% f0 I' ?7 T
No statistical significance, 无统计意义
* t! ^1 c2 ^8 U: ^% n6 ?: ZNominal variable, 名义变量
+ Z7 V1 u) g+ _. c% LNonconstancy of variability, 变异的非定常性
! y1 t! n- k2 U( NNonlinear regression, 非线性相关
+ y5 B. r; D( v) P# m3 W3 G$ l! fNonparametric statistics, 非参数统计5 q/ q1 ^; O7 I. q
Nonparametric test, 非参数检验
% p4 J' Y. C( H6 ]* ANonparametric tests, 非参数检验% l) ?8 _: i( N8 r: {
Normal deviate, 正态离差6 B2 E& F F+ m9 [7 J! o
Normal distribution, 正态分布& ^8 {4 C' P9 w0 u% |
Normal equation, 正规方程组6 z/ s6 f+ j( o9 B+ D
Normal ranges, 正常范围" J8 C- u' N3 a& S' x
Normal value, 正常值
! I, a4 ~& [: GNuisance parameter, 多余参数/讨厌参数
) p. L/ ^/ K6 n$ o' ZNull hypothesis, 无效假设 6 y/ b5 M" P% [; x
Numerical variable, 数值变量
9 C- D0 U1 C: c9 b; sObjective function, 目标函数' J- S0 a7 z6 u! O
Observation unit, 观察单位
* S1 H9 h4 T" Z$ a' L2 C: GObserved value, 观察值2 t! K$ H. @# C( z3 o
One sided test, 单侧检验
9 L: Y1 f( ?: D3 L; x; F3 wOne-way analysis of variance, 单因素方差分析: x4 q; R8 k- f
Oneway ANOVA , 单因素方差分析
$ z. Q1 h9 Y+ _' |% k5 e0 A) |Open sequential trial, 开放型序贯设计- s6 V4 V. x& J8 D# M
Optrim, 优切尾8 w$ r) ~' d7 f- q5 x; O9 s
Optrim efficiency, 优切尾效率
2 B+ [0 O5 r6 l. R1 LOrder statistics, 顺序统计量
& L; V" ~8 Z% ~5 M8 @# HOrdered categories, 有序分类
1 h: q; B7 y% N+ E2 zOrdinal logistic regression , 序数逻辑斯蒂回归
7 _6 V" t3 R6 N) p9 H E9 d& COrdinal variable, 有序变量/ g' [0 J; V/ {) O" W9 z
Orthogonal basis, 正交基& \/ y' T% b& z% V+ m
Orthogonal design, 正交试验设计. ]+ t) F; ]5 X. O# y$ W
Orthogonality conditions, 正交条件4 ~+ J0 S6 B {8 T, t3 K6 Q
ORTHOPLAN, 正交设计
) K, a7 d. ~% R# f4 F. ROutlier cutoffs, 离群值截断点
" [% ~) P4 |/ f k# w" j9 QOutliers, 极端值
& R& X: p* q# O9 hOVERALS , 多组变量的非线性正规相关 9 K+ e6 E" Y% b
Overshoot, 迭代过度
+ D. A2 b7 M/ `, M' TPaired design, 配对设计. H' k8 B) i8 J
Paired sample, 配对样本
$ K- M& l. ~) `- ePairwise slopes, 成对斜率* i! H/ @" `( H6 u# ?
Parabola, 抛物线( z, {$ O- v0 j, K
Parallel tests, 平行试验
. Y3 K; p& [1 b9 O8 Y: x. ^3 `Parameter, 参数
- i+ x4 D/ {4 t0 N7 S9 WParametric statistics, 参数统计
7 Q5 f% ?& e5 b3 wParametric test, 参数检验
4 b+ d# e% t8 r# GPartial correlation, 偏相关
: D. ^7 {2 M9 T. z( N: _: ?6 rPartial regression, 偏回归
. M0 P2 L' y. CPartial sorting, 偏排序
: M. n6 J6 i! t! sPartials residuals, 偏残差7 X- y& ?1 {! ~0 J" }
Pattern, 模式
# q; u- e8 V; Y$ P* Y8 sPearson curves, 皮尔逊曲线: Z6 O9 T& d" `3 {% w6 K; n1 q; y
Peeling, 退层2 b7 W- ^5 ^! H3 x3 o
Percent bar graph, 百分条形图
) W M% I, M- a: }, HPercentage, 百分比1 a: M- E2 r5 A' W/ P" i: G# f
Percentile, 百分位数
! ?7 K% I& I1 P* @: s& L) k. RPercentile curves, 百分位曲线
! u$ Q9 H; Q5 s* G; `% P8 l( VPeriodicity, 周期性
& ?7 b* h& Q$ g; Q+ ~Permutation, 排列( K- N3 z, U, [
P-estimator, P估计量
+ S" |7 |' O; a2 e9 P4 APie graph, 饼图! ~8 e5 q, M; T6 w
Pitman estimator, 皮特曼估计量7 E8 b, a& A4 q5 f; [, P9 N
Pivot, 枢轴量2 G$ l+ C& V4 j4 h" x/ ~# A( P! ~
Planar, 平坦# `( G1 k5 n. Z; `
Planar assumption, 平面的假设4 Z, i; j0 o( m8 o! ?
PLANCARDS, 生成试验的计划卡
$ [; n* o( k. _ T' y9 u9 a+ NPoint estimation, 点估计
! U0 O* P* o8 C3 K: B% @4 [Poisson distribution, 泊松分布
; b( v; T. p% Z' J& h q# ~2 G- F) cPolishing, 平滑
+ v" K- U; E: b, p+ c. RPolled standard deviation, 合并标准差
/ l; G& `7 H- W1 ?* CPolled variance, 合并方差
, `/ U2 K$ B2 e3 u- yPolygon, 多边图
( |8 ~0 R; S4 @" }/ t0 M. iPolynomial, 多项式
* t! K0 a U0 @+ w& S: c' m3 HPolynomial curve, 多项式曲线; v3 H6 k! k# Z' f; O6 @$ A) n
Population, 总体, r+ t2 r' c6 R8 z+ l C' {2 O9 D
Population attributable risk, 人群归因危险度
* L" R6 x! v; ]: f* ~: C4 @Positive correlation, 正相关
/ k1 ]$ m' O# R0 _" P0 a c, ePositively skewed, 正偏$ x% @4 Y0 C R k+ d4 X9 c4 O
Posterior distribution, 后验分布% ~, ]% t% N- S* v, C8 M: r$ u
Power of a test, 检验效能
6 b8 M; r' v6 g( D9 kPrecision, 精密度% l6 p, q$ V9 I% C* s
Predicted value, 预测值
- l1 F ~1 k( T% i' vPreliminary analysis, 预备性分析$ I) {/ `! m" z h8 g+ Q, D# L# ?
Principal component analysis, 主成分分析5 U/ B' a0 O* V3 n! o
Prior distribution, 先验分布: m' a6 E6 |& W/ M
Prior probability, 先验概率+ I0 S1 O1 i( E* A
Probabilistic model, 概率模型& C& E& I! w5 q) z, g
probability, 概率
# X- x' t, U1 M* G2 g' DProbability density, 概率密度
. {9 p' c7 e( @) t7 @; [Product moment, 乘积矩/协方差( L5 V8 k' Q: r2 M2 H$ H
Profile trace, 截面迹图' `& j' d. _: \3 Z8 ^
Proportion, 比/构成比3 w( U u; G8 E8 K! z! W
Proportion allocation in stratified random sampling, 按比例分层随机抽样; V7 u6 X5 Z- G5 B( H/ S" {& k
Proportionate, 成比例
2 c" o2 S6 u+ w- }) X+ F& QProportionate sub-class numbers, 成比例次级组含量7 k! ~7 s1 N. p) x. b
Prospective study, 前瞻性调查
$ X3 I' `6 s, t& u) ]; cProximities, 亲近性
' I. v9 }1 t+ e y- @) WPseudo F test, 近似F检验9 B& D9 k! w8 h# q1 ]
Pseudo model, 近似模型7 s- V0 H1 ^" v" E; s
Pseudosigma, 伪标准差
) V& W& D. }' v$ E8 g# OPurposive sampling, 有目的抽样 N+ ~+ C2 o) F+ v+ v
QR decomposition, QR分解
, B" ]# t4 [3 ]* W: t2 z& \) _Quadratic approximation, 二次近似# J( X: z2 H9 K' h
Qualitative classification, 属性分类
& U/ @& r) I! p4 {( wQualitative method, 定性方法$ c y8 E4 L- h$ V/ U! @
Quantile-quantile plot, 分位数-分位数图/Q-Q图
* R0 Y9 p% ^& j4 h! bQuantitative analysis, 定量分析2 i4 `, W9 u! Z: B
Quartile, 四分位数. W+ ~) ?6 Q$ c! L* G. }8 h
Quick Cluster, 快速聚类
4 W" |4 ~+ V) j1 T+ }% f% o! IRadix sort, 基数排序
& K. q3 i$ g' [, s$ _Random allocation, 随机化分组/ P0 |5 n+ C( o" r* O, o) l
Random blocks design, 随机区组设计5 _6 M o- I7 }+ i0 @3 l, Z1 k; Y
Random event, 随机事件" [$ g1 P4 @ u: w9 j9 r5 X: X
Randomization, 随机化) b; x# Z0 q# i3 ^: ^1 J ?4 y
Range, 极差/全距' M; w+ Z# | \7 V2 ^" q
Rank correlation, 等级相关1 a3 n* |2 a' ]
Rank sum test, 秩和检验
7 R( v& p! Q) qRank test, 秩检验
/ } Z; z4 W9 j3 [Ranked data, 等级资料
5 X) `( j3 j& C" k0 z1 X. h3 `4 {Rate, 比率) Q0 B* i+ F" ~' o1 A) J! }
Ratio, 比例+ ~% J, t" }3 Z
Raw data, 原始资料
: X: y. R5 T8 J: H8 {+ w4 @Raw residual, 原始残差; M4 @% |# G5 a( q
Rayleigh's test, 雷氏检验
1 L* E1 w* f$ a VRayleigh's Z, 雷氏Z值 ; G; v, r3 E. I" p7 u S
Reciprocal, 倒数1 u; j0 j9 }: @
Reciprocal transformation, 倒数变换4 V* x, I. ]% N5 @% \) P
Recording, 记录
6 D6 j. o% ?; O/ i4 eRedescending estimators, 回降估计量/ Y, F1 T9 n: E, q; H8 A
Reducing dimensions, 降维% w8 e" c9 Z" M% n1 W
Re-expression, 重新表达
( p/ o. y( j) e- \ n! `Reference set, 标准组. ~$ ^" v7 t1 t" d% b- ?
Region of acceptance, 接受域2 E: A; A+ z* f$ w9 S
Regression coefficient, 回归系数
( W; |* F) p! gRegression sum of square, 回归平方和' P, v5 l, g; A) U0 z
Rejection point, 拒绝点6 i+ m0 A+ L& l) s" R6 \& s* _# y
Relative dispersion, 相对离散度2 H6 a" \9 e/ g1 s R
Relative number, 相对数
% `1 L. g* X' C. }. K- kReliability, 可靠性
7 u; M" u. w9 P$ l( M) X! TReparametrization, 重新设置参数
C: y* W. ^; h7 p" r/ k, [Replication, 重复
) v9 h/ j' p+ J( z- }Report Summaries, 报告摘要; q9 |% @: r9 n) U& }
Residual sum of square, 剩余平方和
5 W: O2 B* e; y+ v0 P1 X D/ `8 EResistance, 耐抗性8 s7 _ K1 ~, l6 O! w/ p* y
Resistant line, 耐抗线8 N* A1 C" M, N4 [ b) T
Resistant technique, 耐抗技术
w4 B" w' }3 |2 QR-estimator of location, 位置R估计量) B/ R, ^5 a, G0 m9 ?
R-estimator of scale, 尺度R估计量
7 y- k6 a6 `2 q& fRetrospective study, 回顾性调查
A+ Z2 f! ^, wRidge trace, 岭迹
# {6 r! l$ o& y- j7 [% }Ridit analysis, Ridit分析
3 z |4 D& D7 @4 z) u YRotation, 旋转 u C& q* |, B
Rounding, 舍入1 E6 M2 |, [( z) k7 H' G
Row, 行$ _! N6 P! v0 X- y9 Z
Row effects, 行效应
: u( C6 o+ w% i& X0 p/ k0 s# j0 @Row factor, 行因素
: p. Y2 U+ V. I* V, u% YRXC table, RXC表( I! w# n" \3 M5 L$ t/ b
Sample, 样本
' j( s% A( H2 _% o7 V8 U6 w8 `Sample regression coefficient, 样本回归系数
; p( k* Y1 A; l0 O" V' p' h+ q- _* ]Sample size, 样本量
! R( }. g0 }! V; O& b$ @ xSample standard deviation, 样本标准差6 k' u* M0 G: a
Sampling error, 抽样误差
& `6 k6 ]* D1 C" n& jSAS(Statistical analysis system ), SAS统计软件包% E# }! o: K4 T! o2 \
Scale, 尺度/量表! y- a" j4 `3 W3 z9 a8 _' f
Scatter diagram, 散点图0 k% q$ Q8 o- x
Schematic plot, 示意图/简图 X9 p5 Z" B. \$ D4 {
Score test, 计分检验; c8 A) h! t* u$ f" _" E
Screening, 筛检
5 H+ }, @" t+ r7 P: b) R5 e( USEASON, 季节分析
4 T& A8 w1 Q5 z" P7 ^: E6 [Second derivative, 二阶导数. ` V) ~% S+ ~1 F2 l0 z
Second principal component, 第二主成分
2 j7 L5 x; W/ F& Z. s. N, q4 tSEM (Structural equation modeling), 结构化方程模型
# F( p6 t& t4 l, U/ ]Semi-logarithmic graph, 半对数图
- p& H: T u( ^Semi-logarithmic paper, 半对数格纸
9 F/ M4 i% B3 u- X" WSensitivity curve, 敏感度曲线' }6 o* j5 f' T1 T
Sequential analysis, 贯序分析
8 m' ^. \( W- n+ vSequential data set, 顺序数据集$ p9 B W; ]$ c; M; {
Sequential design, 贯序设计, V5 \3 k$ S1 I- ~8 o2 Y
Sequential method, 贯序法- J# r! U5 ^. F0 Y9 [
Sequential test, 贯序检验法
?4 j4 T8 n4 X* ^+ ~- J% ESerial tests, 系列试验# B. r2 j* Y8 _# ~' _ p
Short-cut method, 简捷法
, Z: w1 N; b. qSigmoid curve, S形曲线3 L- F! ~/ b8 R
Sign function, 正负号函数
9 K0 F; n) U% j3 c8 Y; H. tSign test, 符号检验5 w, u0 D% A- Q+ w: p
Signed rank, 符号秩1 F% Y* X& T. Y, x& J. O- t
Significance test, 显著性检验8 \4 |2 l8 `! o3 D8 Z4 J( P3 K* L
Significant figure, 有效数字0 x/ ~, ~4 A2 C8 u; z
Simple cluster sampling, 简单整群抽样
3 O( n5 Y5 i1 Z" o. ? d8 H6 eSimple correlation, 简单相关
* x6 E1 P3 {1 J; l" Z4 f+ C" {Simple random sampling, 简单随机抽样
' c$ U4 t D& ]6 xSimple regression, 简单回归
5 T4 A% r( k9 ksimple table, 简单表9 a; b$ v& U! }0 C" E
Sine estimator, 正弦估计量
3 x9 {. a7 w+ Q# u/ ?Single-valued estimate, 单值估计9 X( u O* n; J: c5 O* ^6 E! y
Singular matrix, 奇异矩阵5 X9 T V2 O; D; O4 v
Skewed distribution, 偏斜分布
& R4 ?; j4 d7 JSkewness, 偏度
, |+ ?- M% @, _* i* [4 T6 GSlash distribution, 斜线分布
/ N- U7 z5 I2 ^6 i3 S! E; N3 i1 JSlope, 斜率
, X% M' D7 D/ \, MSmirnov test, 斯米尔诺夫检验4 {8 x. V4 i) Y2 ^
Source of variation, 变异来源
/ t. g0 g7 z6 iSpearman rank correlation, 斯皮尔曼等级相关
! f* y1 ]0 z8 T: ?% U+ ~* v( mSpecific factor, 特殊因子
4 V7 W4 m! N" ^% vSpecific factor variance, 特殊因子方差
/ [; l M5 d+ F: cSpectra , 频谱
4 Z' X9 @3 X* w5 z* iSpherical distribution, 球型正态分布
$ n' g( A- i$ V+ X' {( mSpread, 展布* \& [/ D8 F7 }* m: G1 j8 s
SPSS(Statistical package for the social science), SPSS统计软件包* I5 O2 J3 R/ ]
Spurious correlation, 假性相关( r' l) c: D# j' v' f( c+ k
Square root transformation, 平方根变换+ y9 f3 R1 ^( i9 y) _( R5 j2 g+ b( g
Stabilizing variance, 稳定方差6 x( H- R$ ~0 y* T4 W
Standard deviation, 标准差
9 H' ]5 q- f: i) A! _8 f9 hStandard error, 标准误3 y7 z0 s, R+ k# ~) i
Standard error of difference, 差别的标准误% T( Y& _; e% ~$ x6 j3 Y, P
Standard error of estimate, 标准估计误差
( b7 T4 {) M: Q, ?, M1 ~3 o4 AStandard error of rate, 率的标准误
) h5 ]7 Y, b9 u2 }Standard normal distribution, 标准正态分布
( s/ f) q3 {0 Z$ t, m9 ^" a oStandardization, 标准化) r( U" g1 Y/ `* r/ _$ D
Starting value, 起始值
Z$ l# o, g2 w4 VStatistic, 统计量4 {: v$ s$ O; ^: m
Statistical control, 统计控制3 g3 G2 a8 H2 [+ Z2 V
Statistical graph, 统计图
% o+ w' |( ?8 S! ?" A, VStatistical inference, 统计推断) _' p% h+ H: y- q2 C( A/ ?. @
Statistical table, 统计表
( r w# `1 C4 m8 c. tSteepest descent, 最速下降法
3 w( ~0 G9 D0 E- I6 S6 P4 V/ bStem and leaf display, 茎叶图. R8 }3 S5 W* e8 J+ F
Step factor, 步长因子1 p) c) k$ P- l& I
Stepwise regression, 逐步回归
" ?+ u0 b( H, \, L/ GStorage, 存) |; B; \, |4 _$ `; ^
Strata, 层（复数）5 b3 c7 G- k7 k& l9 s4 I
Stratified sampling, 分层抽样 u5 G! r( }: D+ ]- T& }
Stratified sampling, 分层抽样
- p' _. x% t1 x8 c. E; R, @4 ]" ]! ?Strength, 强度
) ]' y5 K! U2 i" r4 uStringency, 严密性" s3 w) l" ?( J) h/ p' E
Structural relationship, 结构关系9 y& {, G( C) |+ w9 e" L* {+ \; b/ b S
Studentized residual, 学生化残差/t化残差3 y1 `, o& L5 k8 _. w' ?$ E/ E
Sub-class numbers, 次级组含量
% N0 n, v4 L" j4 u4 t O" QSubdividing, 分割; b; Z7 q1 o9 Q
Sufficient statistic, 充分统计量7 o; p2 {) U( W- y- D/ b& G2 k( u
Sum of products, 积和3 L9 F4 R8 I1 Z& N
Sum of squares, 离差平方和7 e S& U1 C6 @5 w( A
Sum of squares about regression, 回归平方和
* e2 F' h) _4 k# b J9 d, @Sum of squares between groups, 组间平方和' B4 Y y0 |- Q8 V! ?7 Y2 f3 A# w
Sum of squares of partial regression, 偏回归平方和
9 d( I0 {6 V' `: H( N0 oSure event, 必然事件
: l1 N8 L) t1 z5 c% Y4 q1 {Survey, 调查# J. F/ x3 E p8 V/ n& j, @
Survival, 生存分析0 u, \0 d+ [, z+ F; W
Survival rate, 生存率4 P- n/ p( p+ {& J
Suspended root gram, 悬吊根图
' z/ U! Q! d- ^1 T; b" [! ]4 u0 r$ S( ~Symmetry, 对称" Y* w$ r r' S d
Systematic error, 系统误差
5 a( N* Q6 I3 {8 W4 h: @& rSystematic sampling, 系统抽样* H3 x2 w: \/ ?" B
Tags, 标签! n+ ~: K4 `/ g. A% @
Tail area, 尾部面积2 I0 D5 g! t0 O
Tail length, 尾长& e7 t! D2 b/ D: O
Tail weight, 尾重
, G8 e3 d: D& M/ [6 V5 oTangent line, 切线
5 U a' }4 }, E: i% B5 i& {Target distribution, 目标分布
6 w9 r+ R! q# n' F: J2 ATaylor series, 泰勒级数
3 X2 ?( |7 s8 z7 I* t% uTendency of dispersion, 离散趋势
5 X6 M/ i: f1 C, Y a& OTesting of hypotheses, 假设检验# m( h) u. W( `! Z" H
Theoretical frequency, 理论频数
( \# @$ I) }9 m0 K* XTime series, 时间序列+ k4 o# r, D( c( ~2 A$ D9 D7 M
Tolerance interval, 容忍区间, p* T7 d7 S; n- j+ n. p3 u7 i
Tolerance lower limit, 容忍下限
6 e+ N* e( J) s- @" T1 w4 z2 rTolerance upper limit, 容忍上限) k8 l; u* v5 x% A
Torsion, 扰率, f/ v+ _! X' _/ R
Total sum of square, 总平方和
% W' _/ P) W2 ^5 `Total variation, 总变异$ I! k" ]' l$ _$ ?
Transformation, 转换# e/ }, K* _( Y+ u0 t) A5 i
Treatment, 处理
5 T' X* O. a8 B0 xTrend, 趋势0 h- E! R# v3 @8 o0 t
Trend of percentage, 百分比趋势
. [2 m s9 b1 J9 D" STrial, 试验" n9 { {5 s$ Y* |* Z
Trial and error method, 试错法, V/ x$ y# T; `2 T. l" @: m
Tuning constant, 细调常数# r5 ?' g7 u) G3 @% T
Two sided test, 双向检验
) l" `7 A2 g- f3 N; |' [+ kTwo-stage least squares, 二阶最小平方0 a. s+ |' E% j' `& i! \/ k. Z) k
Two-stage sampling, 二阶段抽样
$ G( b* @' J6 ]* s4 ?1 w6 X3 H' pTwo-tailed test, 双侧检验6 x; c4 _1 B" z. B4 a& N
Two-way analysis of variance, 双因素方差分析. E4 i1 D6 j7 [* N& {9 n1 f, k
Two-way table, 双向表2 ]9 G$ G$ R5 ]" G" s; j
Type I error, 一类错误/α错误
- x) B: A6 V) {/ E/ BType II error, 二类错误/β错误
# s4 A7 f" O! |) |1 TUMVU, 方差一致最小无偏估计简称% \5 f1 B% [1 S, h* {! p
Unbiased estimate, 无偏估计* ~+ B8 p% o7 r
Unconstrained nonlinear regression , 无约束非线性回归- O. \% p4 h8 z) ]) i
Unequal subclass number, 不等次级组含量
6 j& g% J0 g% j s5 X; LUngrouped data, 不分组资料% ^* t" l" A B. s2 ]
Uniform coordinate, 均匀坐标) A s1 r+ {. r; W* G) ~
Uniform distribution, 均匀分布7 u, r: u5 e; @+ h. Q5 D P
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计+ C* N: c- N) J% w
Unit, 单元
+ t+ a2 t4 f% E0 ]4 r- Z6 DUnordered categories, 无序分类
/ c2 I" N6 J+ l2 QUpper limit, 上限. y) w9 p: n& ?/ x0 i7 `5 k
Upward rank, 升秩. i( m, u. U6 j
Vague concept, 模糊概念# ^: m3 T' F! o
Validity, 有效性5 y. ]6 Q5 s5 \9 ?
VARCOMP (Variance component estimation), 方差元素估计
/ Y0 v* s3 I$ ?' y. tVariability, 变异性/ @6 n4 @( I; `4 i
Variable, 变量: I' m1 o" W- y/ ]5 t% k/ d
Variance, 方差
) b1 `. ~: k/ i) BVariation, 变异
/ F2 ~0 ^- Z4 o1 NVarimax orthogonal rotation, 方差最大正交旋转
! f: e/ ^/ ?1 y7 y9 |$ h1 `; {2 yVolume of distribution, 容积6 ~' G6 x! `! |+ z! ~* M
W test, W检验
8 i* q: E2 {* V0 G3 l0 ^) BWeibull distribution, 威布尔分布) U' o, f# c8 j ^* O3 `/ i
Weight, 权数
* E- v1 p2 [2 S6 R# wWeighted Chi-square test, 加权卡方检验/Cochran检验
, g1 e! f* L6 H8 T" f$ @Weighted linear regression method, 加权直线回归) C. k5 B6 v% s& {$ M+ I) ?
Weighted mean, 加权平均数
4 h/ B4 l' p6 R( LWeighted mean square, 加权平均方差
9 V- K0 s) \: ^7 M1 gWeighted sum of square, 加权平方和
& ?8 r. m6 G7 N7 S C! bWeighting coefficient, 权重系数
0 ?7 v# M R8 _$ O& {6 KWeighting method, 加权法 + {5 | _3 D( A" h* \ C+ F' @" n
W-estimation, W估计量
% G2 M' c! ^2 i8 CW-estimation of location, 位置W估计量% ~* m% ]( [! l, {2 f
Width, 宽度# Z1 g2 Y% R0 f$ A6 C- f9 G1 [
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验 U- a3 b) \, ], m) j ^
Wild point, 野点/狂点5 S* i# L% X8 F+ |7 L1 r
Wild value, 野值/狂值
! U: z- v, k+ F) x1 K& h0 S+ |7 qWinsorized mean, 缩尾均值
5 A- c+ _! X9 aWithdraw, 失访
. @% |/ z. I7 v: E4 ]! i# N SYouden's index, 尤登指数
' M7 l Y3 t6 w: v/ y. E1 EZ test, Z检验" {. y* i3 {- ~% B- l& D4 g1 S
Zero correlation, 零相关5 ]+ a/ O% H7 {7 [# x; J5 B
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
