|
|
Absolute deviation, 绝对离差
4 n* n0 `8 O9 g2 C# VAbsolute number, 绝对数9 R8 u+ }( e, i; u! O
Absolute residuals, 绝对残差
4 e3 J$ r# z, S* B7 x6 t% [Acceleration array, 加速度立体阵* _0 a* D+ F/ Z- l: x3 F; B9 F5 r- p. C
Acceleration in an arbitrary direction, 任意方向上的加速度
* ^5 H8 j) N+ u3 Q2 S J4 cAcceleration normal, 法向加速度# Q/ J! \# |5 K; ?
Acceleration space dimension, 加速度空间的维数
9 X/ m7 B9 f& r) W5 S0 c1 JAcceleration tangential, 切向加速度
9 S* z( H8 m0 ^" v; WAcceleration vector, 加速度向量- M3 r" B# |7 u
Acceptable hypothesis, 可接受假设$ G1 [' h+ l$ b6 Y+ H
Accumulation, 累积$ }. L, \/ t5 M9 g
Accuracy, 准确度5 W% x& j# a8 q- q
Actual frequency, 实际频数
1 a& Q) G. N1 n$ x. R; W* OAdaptive estimator, 自适应估计量
+ T/ t% X7 F$ kAddition, 相加$ T! c5 t7 S8 | M1 R
Addition theorem, 加法定理+ y/ r( l4 e T9 L( J' H
Additivity, 可加性
( E: l" B& n" l/ n$ w" XAdjusted rate, 调整率+ ]! F( A1 K1 ?5 q
Adjusted value, 校正值9 {; Q: [5 K# O) s ]6 P. e
Admissible error, 容许误差) h. d2 t- u+ }& X# K/ a$ W
Aggregation, 聚集性& O! m/ |- I, S& E0 l7 x$ q5 N5 F
Alternative hypothesis, 备择假设- t2 I9 y4 Y& V! ^& U5 E
Among groups, 组间
& F0 K! I' ?' L/ {( g6 `Amounts, 总量
* i( t# f% D& }Analysis of correlation, 相关分析' ~/ S5 q5 j6 G* F7 |' C' {3 s
Analysis of covariance, 协方差分析
) |5 n7 m: L+ f( S: |/ W0 j9 IAnalysis of regression, 回归分析4 T# L% F2 f8 \: a9 M' g8 \
Analysis of time series, 时间序列分析
* u" \: J- _4 X1 X. }Analysis of variance, 方差分析
0 v+ f# j4 {8 \8 I2 B0 sAngular transformation, 角转换" |5 d- {5 d+ ]3 [1 o
ANOVA （analysis of variance）, 方差分析
3 a; e' E7 r) L* x- g0 A7 @ANOVA Models, 方差分析模型
6 q9 @: h) [' UArcing, 弧/弧旋! w+ U) y$ ]# c6 b% k
Arcsine transformation, 反正弦变换
* ~7 K3 [3 z+ N6 k8 e4 FArea under the curve, 曲线面积 H; r6 {2 d9 }
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
# H9 W' q- S' l4 D4 ]1 ?! D* C/ [ARIMA, 季节和非季节性单变量模型的极大似然估计
& ^$ ~* h) G( j) T3 g3 _4 HArithmetic grid paper, 算术格纸
* O6 X6 M4 I) d+ h. r# uArithmetic mean, 算术平均数2 F* n% ^" A B8 t0 K! F6 z
Arrhenius relation, 艾恩尼斯关系* K3 ]7 S) N* k0 {& j e( K/ r
Assessing fit, 拟合的评估1 z/ g' Q0 r& a3 S
Associative laws, 结合律# R5 D8 P8 T3 Y2 t% [* U
Asymmetric distribution, 非对称分布
1 r' t! t9 M) K# W& E$ p* XAsymptotic bias, 渐近偏倚
v& W& y" D0 y, W l' G; ^Asymptotic efficiency, 渐近效率
- R1 @4 G" t; {5 F, l2 `Asymptotic variance, 渐近方差2 z3 W$ A( ^) T
Attributable risk, 归因危险度9 V' K) k0 E c! x7 [3 J
Attribute data, 属性资料 y2 K% u! Z: N" J
Attribution, 属性) p) j4 D/ l ]
Autocorrelation, 自相关& O' y, h6 v/ @' I7 m
Autocorrelation of residuals, 残差的自相关
3 s- B; p4 c% \Average, 平均数
6 g# A L* I* ? \' HAverage confidence interval length, 平均置信区间长度
2 ]5 |$ c3 l4 }4 H3 zAverage growth rate, 平均增长率
) a u" h/ P9 E2 X9 e" jBar chart, 条形图; g' E/ n+ |$ [) w! m
Bar graph, 条形图& |' N+ M1 g% v6 f/ E5 K% W
Base period, 基期4 {" O( r( b! L& T8 w" X- C
Bayes' theorem , Bayes定理
- \: s: u0 ?8 i: d; r$ x" RBell-shaped curve, 钟形曲线& q$ g5 [# W* S C: Z
Bernoulli distribution, 伯努力分布
/ r9 x& J+ E: x2 Z1 D2 L# tBest-trim estimator, 最好切尾估计量5 R* z( @5 S! z3 b1 W
Bias, 偏性
" ?1 k1 O, Z" c5 cBinary logistic regression, 二元逻辑斯蒂回归
; K6 G' e6 G* `3 CBinomial distribution, 二项分布* f. w# A) n0 s$ F& c
Bisquare, 双平方; [1 g2 z8 w) r y3 o
Bivariate Correlate, 二变量相关
' p3 `$ O1 r, F {$ f3 f) R9 q8 lBivariate normal distribution, 双变量正态分布
, J8 F6 v$ x- f; u. \Bivariate normal population, 双变量正态总体' V- x# ~& g+ u& B4 E: H
Biweight interval, 双权区间
( ?; s2 K8 T* D- GBiweight M-estimator, 双权M估计量3 z6 Z! e9 F: B6 ^& q9 E& ]: N
Block, 区组/配伍组# I, e# j' g; \% c3 ~! a
BMDP(Biomedical computer programs), BMDP统计软件包: b W/ P) ]$ ?% P+ Z% p* D
Boxplots, 箱线图/箱尾图1 m+ \7 A8 F1 Q* i1 G' s
Breakdown bound, 崩溃界/崩溃点4 w! D+ l+ b; o: M9 O6 X( I( p7 E
Canonical correlation, 典型相关6 `2 ^2 K& I8 s2 A( a" ?& k
Caption, 纵标目 O: s4 ], C# M$ V: s7 {5 s( L' u; e
Case-control study, 病例对照研究% u' ?, R* O) F: p* w
Categorical variable, 分类变量
. p) i d# k2 {; u: U1 ^( S+ e# @Catenary, 悬链线1 d7 l8 o! g7 O0 N
Cauchy distribution, 柯西分布
8 V. f: u+ F$ |* p6 l5 [- lCause-and-effect relationship, 因果关系
0 d$ M5 ]) O0 p# [6 m! p* e' P6 HCell, 单元# |( ~1 v; Y9 U$ {
Censoring, 终检9 P& W, C; U8 u y$ A
Center of symmetry, 对称中心 Y( r3 ~+ w0 l% Z" t+ i/ x! K5 A
Centering and scaling, 中心化和定标0 b" ~$ Y0 m" n+ B% H
Central tendency, 集中趋势
. t3 |# C! H1 E4 d0 sCentral value, 中心值
, x, o) ^8 x/ A3 X4 _3 nCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
1 ?) D: F8 H* [6 k; aChance, 机遇" V# a% ^9 i2 v
Chance error, 随机误差* Q. | ?$ ^2 Z
Chance variable, 随机变量% ]& p' M7 ]& s# X8 {' o
Characteristic equation, 特征方程# ?$ G: f; m/ h, o0 w& P2 X$ n
Characteristic root, 特征根1 }( c0 F ]8 [2 ~0 v
Characteristic vector, 特征向量0 o1 d8 U6 _0 p0 E; C/ F# J
Chebshev criterion of fit, 拟合的切比雪夫准则5 c$ p/ o4 k- ]# i0 I; h% ?
Chernoff faces, 切尔诺夫脸谱图
6 ^1 o% R( ~% c l' \. l5 D3 o7 MChi-square test, 卡方检验/χ2检验) Y3 T8 q1 ]8 Z+ E: e
Choleskey decomposition, 乔洛斯基分解
: e+ @5 J8 Z, A! i x8 P; fCircle chart, 圆图 # w2 l8 _' T8 k- c( P% z5 u
Class interval, 组距! d* H1 D. i5 o7 z6 t' {
Class mid-value, 组中值
% d% K& V7 k; ~) p! j: SClass upper limit, 组上限
9 ]6 p7 F( o! l3 S# ?- D# }Classified variable, 分类变量6 G9 \5 c. j) N# f" f& {% r
Cluster analysis, 聚类分析
$ {$ a: s2 ]8 y4 B! t8 I, y4 FCluster sampling, 整群抽样, v1 h0 u" M8 {: y! ^
Code, 代码 F! i5 j1 R4 j$ {; [
Coded data, 编码数据2 r6 ]# k! z5 ~% |
Coding, 编码4 r' L$ J6 S. y' I" l0 z1 R
Coefficient of contingency, 列联系数
: @7 T8 s3 Y( Q4 GCoefficient of determination, 决定系数2 P' h1 E4 C) J1 J' @3 J+ S
Coefficient of multiple correlation, 多重相关系数4 Z2 |1 O% }6 ^! O. E6 x) R
Coefficient of partial correlation, 偏相关系数
9 G2 |0 H `4 Q1 |. [& b: L1 }7 `Coefficient of production-moment correlation, 积差相关系数
; |; ?, E' J" ^8 {1 G1 c/ LCoefficient of rank correlation, 等级相关系数
" u5 T7 O$ w' e* BCoefficient of regression, 回归系数/ `0 s. ~# H# F
Coefficient of skewness, 偏度系数
, C7 ?, G& r$ F) h) gCoefficient of variation, 变异系数
7 c' Q: {5 S6 u2 ]: n# R% rCohort study, 队列研究3 e; M1 p9 R6 A/ P
Column, 列$ P4 f9 X6 r7 \/ J+ J5 l& q
Column effect, 列效应
* Z" D5 j) R: V5 U% a, Q0 R+ kColumn factor, 列因素$ c f6 B% M4 f5 e
Combination pool, 合并
9 b5 R0 X ]; N; WCombinative table, 组合表" ?0 {; D5 a, m+ w" N3 J$ G5 R) O
Common factor, 共性因子+ H# H: r X3 G7 y, @2 s( o; T
Common regression coefficient, 公共回归系数
% S2 W6 {, z! g8 Y M+ y+ D/ W8 G* `Common value, 共同值
. f3 Y3 V2 T+ I, V. d, K' H$ t2 \; |Common variance, 公共方差. L% Q+ ]+ {: {% w5 F; s. u+ s
Common variation, 公共变异
5 R5 m/ r3 ~/ n7 Y9 T) V5 BCommunality variance, 共性方差
3 |& v! f8 M6 MComparability, 可比性+ v" @9 d2 Y5 `8 o
Comparison of bathes, 批比较
' h. i; I7 U: k, RComparison value, 比较值5 i7 E+ h: F8 f- c4 B8 a
Compartment model, 分部模型
9 k" ~* m" i" A+ v4 f: pCompassion, 伸缩
$ h2 I5 a; K$ N. U5 J+ H( ZComplement of an event, 补事件6 h! D; [: j( `* ^$ j/ A
Complete association, 完全正相关3 ^5 }$ s( V, t8 z5 m7 x) `
Complete dissociation, 完全不相关
6 |2 Z3 @# e& \# ?& R* FComplete statistics, 完备统计量1 T# J) R& O& d3 _9 @
Completely randomized design, 完全随机化设计( s* z; R8 j7 h
Composite event, 联合事件
9 l% s) s2 g: `9 l9 sComposite events, 复合事件
. ?( m+ X3 A0 K9 uConcavity, 凹性, Q& f3 g* Y7 z$ @3 f& T Y! _
Conditional expectation, 条件期望2 D1 ?! `. }1 b0 x5 H
Conditional likelihood, 条件似然
* `! {- P! U3 [Conditional probability, 条件概率
# g+ _* T& K2 a) J j' {9 L/ |Conditionally linear, 依条件线性! d* Z+ |7 z- \! [2 c1 B! Y: @
Confidence interval, 置信区间: s2 O J) L. q9 D
Confidence limit, 置信限
; E1 \1 O: Y5 N+ XConfidence lower limit, 置信下限 q* F: |- |# p# I. W
Confidence upper limit, 置信上限
: r2 R7 Y* L- Q5 G1 cConfirmatory Factor Analysis , 验证性因子分析7 g. C- C" ~8 c8 B6 t! C# J
Confirmatory research, 证实性实验研究
( u3 O9 h! b( P1 jConfounding factor, 混杂因素/ Z6 b1 {; i6 X- M9 Y
Conjoint, 联合分析. h8 H! ?) {7 a" F/ W2 {
Consistency, 相合性
. ]) ~* N7 Y1 x+ r5 M9 x4 LConsistency check, 一致性检验
( b# r9 r* O2 f8 _$ K) aConsistent asymptotically normal estimate, 相合渐近正态估计. h" H& k+ I. H a
Consistent estimate, 相合估计 C* }' q" e" ^( K6 r
Constrained nonlinear regression, 受约束非线性回归
8 L* k1 b* E& o6 S' E% q+ mConstraint, 约束1 H% X3 ]. h: N9 p* z
Contaminated distribution, 污染分布
0 H$ i+ x: L" `+ SContaminated Gausssian, 污染高斯分布( T x9 \6 W( l# w* J' T
Contaminated normal distribution, 污染正态分布
9 A: I3 c& U, {7 G' Q8 HContamination, 污染$ ^8 T: G; P' w& @. n+ Z/ p
Contamination model, 污染模型: K- }* F$ v E+ K, d
Contingency table, 列联表
2 J- p) N: J$ f& E3 hContour, 边界线
1 v! d9 O& ?2 l+ C( y S; i: PContribution rate, 贡献率
7 g; k& s4 T# UControl, 对照/ j. m' ?8 x" f0 R
Controlled experiments, 对照实验
! M7 ~6 a+ `3 F$ v* T4 r3 u/ eConventional depth, 常规深度
) C' F4 ]! K' [$ T- S! `8 y; m. tConvolution, 卷积
5 O1 b, d. J% A+ y% ]Corrected factor, 校正因子: i: @# N; @! p0 J# P
Corrected mean, 校正均值6 y1 b& |; X+ X4 u+ H5 Z# Q
Correction coefficient, 校正系数
?* a3 Q3 l$ t6 J( z7 i. @0 OCorrectness, 正确性. B3 d3 T) N) q9 P' t$ n( H/ t1 N+ Z
Correlation coefficient, 相关系数
' o+ _6 M F8 o/ L3 u$ G1 jCorrelation index, 相关指数
, h# D+ T& ]9 a# |$ h" J( b" tCorrespondence, 对应
) Q9 ?+ }' w! H! k ~: bCounting, 计数
7 W$ s0 L8 P2 D. b/ p3 A! `3 uCounts, 计数/频数
( V. x; L$ ], D1 hCovariance, 协方差" x7 x; g R# s; n
Covariant, 共变
+ p+ a% D9 s* Y4 e0 I3 V+ {, d5 @Cox Regression, Cox回归8 y/ J( f' N: J4 }. e5 Z8 Y p
Criteria for fitting, 拟合准则
, p+ I, p6 J. q7 i vCriteria of least squares, 最小二乘准则
( l4 w) W: S9 |Critical ratio, 临界比4 G# |. I! l5 p5 W9 A7 s0 o
Critical region, 拒绝域
* x# B: H: m$ QCritical value, 临界值8 [ T- B9 i& f
Cross-over design, 交叉设计6 R9 K% U0 I( h' q" ^* E/ ~
Cross-section analysis, 横断面分析
4 b5 H& ?1 {. x2 e0 `/ t% ?# aCross-section survey, 横断面调查5 q8 F" i$ @6 i0 T' e3 \
Crosstabs , 交叉表 7 L* F5 z/ r; N, w
Cross-tabulation table, 复合表9 ~2 H: B# I3 M/ Y7 Q1 a5 |
Cube root, 立方根- e; l7 |( m' \/ c
Cumulative distribution function, 分布函数
( N% ~( I2 h; b: ]Cumulative probability, 累计概率 q( a+ A1 a( ]& K/ F5 K* N
Curvature, 曲率/弯曲/ Q9 y m4 _5 I6 z7 u: ^) `0 N
Curvature, 曲率
0 g& r1 b9 j" G7 Q% MCurve fit , 曲线拟和 $ A! y4 S$ ^. d& v) F( t: I
Curve fitting, 曲线拟合
9 W/ |' E7 |. A1 u% s# S1 m/ bCurvilinear regression, 曲线回归
8 R% l2 M2 d$ g( C, ~& s: ~9 SCurvilinear relation, 曲线关系
4 w4 V+ ?7 y5 A, l$ fCut-and-try method, 尝试法
5 V, g7 W- V- R8 b- H' e) ]9 \Cycle, 周期
6 q5 @% h( h! z. n2 O7 ?Cyclist, 周期性: s9 m2 V% \' K% `
D test, D检验 }6 L# b3 ^8 L" P6 {
Data acquisition, 资料收集
+ t' d) n. f& f& C" L- g2 jData bank, 数据库# ], R8 q1 d+ e1 _8 s* t
Data capacity, 数据容量; ]( y$ w A1 _" p; I7 n
Data deficiencies, 数据缺乏2 F% d# t( B1 q/ J& G# X" D p4 C
Data handling, 数据处理
% w1 I: M) N5 A3 w* e& W4 _2 s' KData manipulation, 数据处理2 a" B' A' }% d) Y
Data processing, 数据处理
/ e( w1 A4 w0 \7 Y- r, d, ]' BData reduction, 数据缩减! J8 O9 v' I- `7 @6 A
Data set, 数据集# a! F2 h9 k2 N/ i6 U+ S5 z
Data sources, 数据来源
1 @3 p d6 J6 V$ h' EData transformation, 数据变换
' P6 D7 E: M7 yData validity, 数据有效性
1 S; r: p: Y4 F0 c5 fData-in, 数据输入
6 b7 J; j, @1 H; v5 ZData-out, 数据输出8 U& Z& {6 n' _
Dead time, 停滞期
* f' l1 Q) N4 rDegree of freedom, 自由度
7 @ u" A) e7 ^" G7 [Degree of precision, 精密度$ R# d: z: A. f6 m( w' B
Degree of reliability, 可靠性程度
% e6 ^# G' B2 V1 U2 mDegression, 递减
6 m6 [! R/ G$ b# R! P& R. {Density function, 密度函数0 f T2 |. V, u' G) {3 o4 F
Density of data points, 数据点的密度
: _1 q+ {/ G b* S& H* [" S& WDependent variable, 应变量/依变量/因变量
m5 I3 Y5 {5 O+ u7 aDependent variable, 因变量
- L2 X; S9 ~4 v! SDepth, 深度- W7 P2 q! y- ^% X- }9 W
Derivative matrix, 导数矩阵) S9 H! |! f$ `0 ]6 z' v9 @; ^
Derivative-free methods, 无导数方法7 a; L2 f& _/ ~- D
Design, 设计
Z% X: B4 U5 P0 \2 \Determinacy, 确定性$ e4 _/ h9 }: U( m- a: z8 E; u
Determinant, 行列式
' Z& F/ V& i! I; l( v7 _+ x8 BDeterminant, 决定因素
% L6 D; d; n |/ f2 i6 DDeviation, 离差
! ~' m# ]0 {9 lDeviation from average, 离均差4 b4 v5 b* t$ ~" V; M
Diagnostic plot, 诊断图* ~5 h) B. x, `) u( Z& S
Dichotomous variable, 二分变量
+ J7 n& X# w9 ]& C1 aDifferential equation, 微分方程
9 B! q5 d$ b9 J. t! G1 `+ \7 fDirect standardization, 直接标准化法" \# D: a) M* e0 G$ ?3 ~
Discrete variable, 离散型变量
7 K+ r( l0 y: Y" i+ tDISCRIMINANT, 判断
9 Z5 j1 R" _2 r& A# m. ^Discriminant analysis, 判别分析
; n0 p! Q1 O8 a0 c8 SDiscriminant coefficient, 判别系数
6 P. q2 s- z7 n4 A+ r/ nDiscriminant function, 判别值: w# v1 o- k2 i, ]/ e; W' G/ S( ~
Dispersion, 散布/分散度
: ?- @0 c$ K' m& Q# l: WDisproportional, 不成比例的# J5 a; i5 Y/ ]. \. J e2 m3 |
Disproportionate sub-class numbers, 不成比例次级组含量$ e) O3 b+ F- m$ q- C" R" t
Distribution free, 分布无关性/免分布. m, E9 e r0 z; X* Q' n
Distribution shape, 分布形状
3 f9 E$ B. v. @7 GDistribution-free method, 任意分布法/ {: ]+ f) {. \
Distributive laws, 分配律# r. M, e( T1 k
Disturbance, 随机扰动项+ M3 O& J* L6 f/ g8 m ?
Dose response curve, 剂量反应曲线+ d$ p; V1 g ~3 d
Double blind method, 双盲法
, V; S5 T' d& x# ?5 b tDouble blind trial, 双盲试验
) A6 X7 S; i J9 k" k" SDouble exponential distribution, 双指数分布
% N( N% n+ r; u+ vDouble logarithmic, 双对数
( Q) c; c: A6 m; kDownward rank, 降秩7 i/ o3 R) E; d
Dual-space plot, 对偶空间图: W. _, Q" s7 x' Z k; x" i! n4 B. o
DUD, 无导数方法5 M5 H& v+ b8 ^6 g2 ^3 z. a
Duncan's new multiple range method, 新复极差法/Duncan新法9 J! h4 R* L% Y$ f" h
Effect, 实验效应; p$ ]. D: U* X; l( |( {2 L
Eigenvalue, 特征值
8 i. P( J. X3 v4 dEigenvector, 特征向量
- F& m0 R# u( C2 u( p& UEllipse, 椭圆& B: N0 l* n5 u& k* k( z
Empirical distribution, 经验分布$ l% n5 ~ ^! V3 A
Empirical probability, 经验概率单位
+ _) y8 A, n# P. S J( {, x: iEnumeration data, 计数资料
( g \$ [" Y9 m# U* Y/ XEqual sun-class number, 相等次级组含量3 `1 u3 M' J0 N* r6 u4 S" Z4 l
Equally likely, 等可能+ ?; Q, Z b9 u& V) K
Equivariance, 同变性
: f% x$ q) o4 ~$ y1 D# I/ LError, 误差/错误5 l4 O) q: n# q0 I
Error of estimate, 估计误差
& E5 _* h N5 w: V* o7 yError type I, 第一类错误1 ?( |' K" j8 _$ a8 P5 X
Error type II, 第二类错误7 W& i' D1 r9 V- Q! ]3 e) P
Estimand, 被估量
& r3 q0 c. j; s, H \- e' QEstimated error mean squares, 估计误差均方" x) R: a+ P" N7 m' s: C8 a. Z
Estimated error sum of squares, 估计误差平方和
5 r: \4 r2 S) ]0 J' QEuclidean distance, 欧式距离" B, }1 c2 I! W7 f) C; |/ B
Event, 事件
6 t# g& K! w' \2 s1 aEvent, 事件
P+ E) S A! h+ V+ T& X% W/ i0 WExceptional data point, 异常数据点. s4 G/ p' z3 ]/ s5 E7 u* K
Expectation plane, 期望平面
* }* s$ r1 p" J. G% ^- e- O) xExpectation surface, 期望曲面
; m0 ^1 G9 n F' }0 b, T( {Expected values, 期望值
+ `* ^: C+ G7 Z: N1 BExperiment, 实验7 N! Z3 X H: [6 s' B
Experimental sampling, 试验抽样# H& m: v7 P, V! k3 O: m
Experimental unit, 试验单位4 K. m) Q8 Z) n5 t
Explanatory variable, 说明变量
; z8 B* |" r; m7 ?* `Exploratory data analysis, 探索性数据分析1 N1 e' o: v7 ?# X; A0 x! t1 ~
Explore Summarize, 探索-摘要% G1 l. y' N7 J4 P3 C: Y2 `0 h
Exponential curve, 指数曲线2 N6 @' k3 X& `( i
Exponential growth, 指数式增长 T, M0 Y* a6 I6 a+ S
EXSMOOTH, 指数平滑方法
) c0 J5 d! i9 ?' [: jExtended fit, 扩充拟合
; X" m! _" Q/ R, A# QExtra parameter, 附加参数
) Y$ `! E, j) i5 {0 C* x! d! \Extrapolation, 外推法
3 m% o% O8 s4 ]; y j! m8 yExtreme observation, 末端观测值
; {, B; y7 X! Y* C' \+ @. fExtremes, 极端值/极值+ B/ g0 F4 V1 n5 J- l
F distribution, F分布
+ q; [, O D* U4 X! r8 x8 vF test, F检验
; T' r4 s8 t* w4 \2 WFactor, 因素/因子' Q. L- b: n }2 _. c
Factor analysis, 因子分析5 I8 e# S& |/ D, |
Factor Analysis, 因子分析
. ]4 ] l) }( E" WFactor score, 因子得分
0 `+ j) h p5 _4 s9 wFactorial, 阶乘
8 C! v9 [1 u0 S3 t, K* IFactorial design, 析因试验设计
5 I. o+ p' _7 F1 o; e9 X* i. bFalse negative, 假阴性+ q! F2 a% t9 ~' Z3 T
False negative error, 假阴性错误
5 J! n3 [3 i0 ?Family of distributions, 分布族
7 X, K7 B" d5 n$ o8 ~3 _Family of estimators, 估计量族
: _' K5 o0 ^ b. R8 y+ E5 c V: b9 LFanning, 扇面
7 z m9 a0 ~, NFatality rate, 病死率
2 W: ^. Q% a/ E, ~0 nField investigation, 现场调查
& l' |" w6 w1 h' \: m8 qField survey, 现场调查
. r+ s# y7 @" E: Y9 yFinite population, 有限总体3 t% `- J1 f8 Q% G+ \2 F
Finite-sample, 有限样本
( J' K; A$ j) }) ]5 ]* [3 h& U0 ?First derivative, 一阶导数
6 s1 L' m9 w2 r/ K+ sFirst principal component, 第一主成分
* \ ` Q# @6 f+ M" [First quartile, 第一四分位数# R. d- v4 @+ t1 ]
Fisher information, 费雪信息量
, N; [5 x' y& ~- _Fitted value, 拟合值
+ Y% b: b' o7 A) [ i; AFitting a curve, 曲线拟合
- i: K* A: ]* e3 J' h+ A' gFixed base, 定基+ \# i* Y+ g9 k1 W' `
Fluctuation, 随机起伏' Y- T+ ^; _/ W
Forecast, 预测
8 E7 W+ g6 q; S1 A. k5 E7 w& ?9 eFour fold table, 四格表
# F; k6 |/ G- j4 wFourth, 四分点
" Y( w& `" R* [ M& l$ U, K4 KFraction blow, 左侧比率
1 z# Q5 ~' M0 Q* rFractional error, 相对误差* I3 M4 b0 h/ x, ~* C' D
Frequency, 频率4 J( t' V, [& b3 V% W* G4 \
Frequency polygon, 频数多边图! [, o# k c# p' |
Frontier point, 界限点8 R, y- S" v) x1 n) e F
Function relationship, 泛函关系
, K, n' w3 H5 `: s8 mGamma distribution, 伽玛分布
' q% J. J5 J9 H$ S5 e3 JGauss increment, 高斯增量9 i# `/ A& F! x9 g7 J
Gaussian distribution, 高斯分布/正态分布! Y. Q8 A( _" s$ a
Gauss-Newton increment, 高斯-牛顿增量
1 l' G, ]% |! }* {General census, 全面普查/ l$ q! M; R+ I7 s$ j% O3 ^; f
GENLOG (Generalized liner models), 广义线性模型
! k- M: K Y+ v9 b$ jGeometric mean, 几何平均数. X* n) I8 E/ i
Gini's mean difference, 基尼均差
+ }/ {* b5 K( \7 ^* L% b+ D5 jGLM (General liner models), 一般线性模型
6 s; y4 l1 s& ~. s8 ZGoodness of fit, 拟和优度/配合度, ~& Z' G+ T* Q( E7 ]) s
Gradient of determinant, 行列式的梯度/ h0 C5 C) c! s
Graeco-Latin square, 希腊拉丁方8 W- m: a% I- L' T. F
Grand mean, 总均值
. Y& R; ^! W) R8 u, n6 VGross errors, 重大错误9 X" d8 M4 s# Z9 l& v
Gross-error sensitivity, 大错敏感度
% A$ u; H+ m' @* zGroup averages, 分组平均
, a9 u- K2 H6 v1 n! w/ U% ^Grouped data, 分组资料
! ~3 |% d6 J8 G c0 z3 JGuessed mean, 假定平均数
0 K; b. ]! \& p* L$ ]: cHalf-life, 半衰期
4 [+ q5 d+ w! `Hampel M-estimators, 汉佩尔M估计量
( [5 L& r+ L0 t% W' AHappenstance, 偶然事件. v" j+ o2 |9 C0 Q, @9 g
Harmonic mean, 调和均数2 v m1 a% h$ j6 G% O! p, N
Hazard function, 风险均数
1 g6 r/ b m, UHazard rate, 风险率 u$ y- q, _6 l3 S3 }! s9 e
Heading, 标目
; `8 z5 l& Z7 H0 A# vHeavy-tailed distribution, 重尾分布2 g5 ? I) Y! M8 ^# O
Hessian array, 海森立体阵1 v1 N& Y& ~7 X/ c
Heterogeneity, 不同质4 w# X& z& o8 a0 V
Heterogeneity of variance, 方差不齐 - z6 ~' V4 B8 H7 h6 y1 c: l
Hierarchical classification, 组内分组
7 t6 z/ @+ x; x" i1 |5 { c7 W/ d& PHierarchical clustering method, 系统聚类法
- y9 G* \; s* [' U# G# g9 x5 NHigh-leverage point, 高杠杆率点6 U* g6 [* B3 I' G: H5 |: ^
HILOGLINEAR, 多维列联表的层次对数线性模型, x9 x. X4 y4 c0 A3 @0 S/ a
Hinge, 折叶点3 D- l. p. i0 u
Histogram, 直方图! [1 |0 Z- }0 v
Historical cohort study, 历史性队列研究 * ]; ^5 K9 ?& L2 K. Q
Holes, 空洞
" O! Z1 G) s0 g2 C9 k' ]. w, NHOMALS, 多重响应分析# ?- s1 T' O# F( ?
Homogeneity of variance, 方差齐性" q X/ C! r% v' y) f. j4 s' m
Homogeneity test, 齐性检验
# D% S& u3 ~5 N( \4 mHuber M-estimators, 休伯M估计量. c3 Z8 m2 Y# g6 f5 C
Hyperbola, 双曲线7 g3 }8 e2 b) M' }! i+ b! v
Hypothesis testing, 假设检验3 h) j; `9 O4 p- ^
Hypothetical universe, 假设总体
% f7 Y7 I: P+ b) [Impossible event, 不可能事件
1 R& M0 H1 p$ @/ i' mIndependence, 独立性
& M% t- U1 U- L. \' G" `) eIndependent variable, 自变量) R3 H S# G) p" S
Index, 指标/指数& f& p# F* b: B) i7 @ `
Indirect standardization, 间接标准化法
; ^, q e/ b n/ H4 O/ ?Individual, 个体
3 O+ o9 [' Z$ i# r5 \Inference band, 推断带8 _6 }, S3 e2 T" r u3 `' ^. `) P4 v
Infinite population, 无限总体6 }' s% f7 {& ~+ q1 {2 l
Infinitely great, 无穷大4 u" r" w( R* u9 n+ z$ M
Infinitely small, 无穷小
t6 `2 p5 k8 r7 p: L5 z# u [: P: AInfluence curve, 影响曲线
# N9 L" d H4 S' M) eInformation capacity, 信息容量) z$ y A* E u# U. d; u
Initial condition, 初始条件
' ]# Z. o- Q, ~( jInitial estimate, 初始估计值/ u! A: d1 G3 e. m' H
Initial level, 最初水平7 {% S" j" r( w1 b- W- m
Interaction, 交互作用- o. Q8 V3 w" e2 s6 f$ n9 N# s" ?
Interaction terms, 交互作用项8 Q( E8 q4 N. n
Intercept, 截距
) H5 u7 N' s! G5 cInterpolation, 内插法
: K d5 b( ^' p0 t: H& g5 KInterquartile range, 四分位距2 p/ v5 t! Z+ }$ c9 y
Interval estimation, 区间估计, d3 V, h( ?3 m8 a/ o
Intervals of equal probability, 等概率区间
# C) E4 Z8 a. r3 G6 RIntrinsic curvature, 固有曲率
& t& F0 \3 J* Z6 _Invariance, 不变性: b) S6 ]# k. E0 w* {
Inverse matrix, 逆矩阵/ t' x T& _" q( F- ?; j% X
Inverse probability, 逆概率
" \; F8 w' G5 i$ j4 FInverse sine transformation, 反正弦变换) G! C( }5 ^5 T' q; |/ A6 V
Iteration, 迭代 # r' [; U3 U9 H) ] P
Jacobian determinant, 雅可比行列式
- ?: |/ r3 X# }2 {' D% z% ^: ]% r' cJoint distribution function, 分布函数
/ c7 i# r( u: P2 S- q% q3 {Joint probability, 联合概率
- m) w0 ? u" H% D- u+ P2 y1 D- |Joint probability distribution, 联合概率分布
! p% \$ h! ] ]/ oK means method, 逐步聚类法+ x0 X: c9 X+ n* p* R g6 V
Kaplan-Meier, 评估事件的时间长度
; d" ~ k0 h; P8 T5 b% Q" QKaplan-Merier chart, Kaplan-Merier图
1 H/ b4 t. Y% k3 B4 m7 VKendall's rank correlation, Kendall等级相关
& B; }+ `2 w# ?! l# @# i, a b7 BKinetic, 动力学1 S5 r4 M4 e% C8 C i n4 `
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
2 Q" ?) ?! A. y! M% W. ~# H: SKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验+ N# ]# B, p7 v* \* {; s
Kurtosis, 峰度
* c1 z# r- U( f9 z* {& A7 T/ Q6 ULack of fit, 失拟" z0 |. Q% z5 ?
Ladder of powers, 幂阶梯
& P! Y; ]* A. u# V- e. Y0 P/ k; }Lag, 滞后
& n; a' t1 Z1 W3 n7 t4 eLarge sample, 大样本
; Y- B" i# |% j+ @$ u( N+ x8 S VLarge sample test, 大样本检验/ T& K- i S6 }7 [. ]4 Y. |- u" d
Latin square, 拉丁方
3 h8 [( [# M9 V; {: {Latin square design, 拉丁方设计
% L* Y+ d+ @# s! q7 [' E+ wLeakage, 泄漏
0 E2 P2 R% [7 M+ ?3 m% [7 [Least favorable configuration, 最不利构形
9 {0 N6 ?" f% r8 aLeast favorable distribution, 最不利分布/ y! I4 m$ V, ^& V6 f8 v
Least significant difference, 最小显著差法( I, _+ G! J% ~- {; B
Least square method, 最小二乘法" {0 y! M6 y7 N7 `
Least-absolute-residuals estimates, 最小绝对残差估计; d c- f+ m% J- Y4 x! D; h) ` T8 ~
Least-absolute-residuals fit, 最小绝对残差拟合% H6 p( @2 }- Y* H5 Z
Least-absolute-residuals line, 最小绝对残差线/ }" L. x4 {4 N5 c3 O7 Y
Legend, 图例
/ K! y8 |& t AL-estimator, L估计量# F, }: w) z8 r- c5 P/ G
L-estimator of location, 位置L估计量7 }* E7 L8 h9 v- V* |) M
L-estimator of scale, 尺度L估计量' ]1 D2 m9 S1 U) u/ f2 B
Level, 水平
" _+ `) q" O7 G0 Y' P! ELife expectance, 预期期望寿命
$ Q: v6 B9 B6 p0 n% z& }- ~; @( TLife table, 寿命表
4 i- V: ^, c7 f" J8 eLife table method, 生命表法9 H7 i0 y5 P1 `
Light-tailed distribution, 轻尾分布
, ^8 v; {( d# Q3 u! nLikelihood function, 似然函数+ p% I% Z, I" k2 r$ i9 D! n% Y
Likelihood ratio, 似然比( f& o0 G$ C" [3 w
line graph, 线图, k# w6 i* y. A/ u/ M$ Z
Linear correlation, 直线相关
6 E5 M1 ]/ j3 M$ ^1 JLinear equation, 线性方程
- H$ c% r$ @0 A6 a4 H- ALinear programming, 线性规划
- }; v9 |' B5 l% {: y7 Z+ u/ \Linear regression, 直线回归. Q7 ]. v) P; {* w; z
Linear Regression, 线性回归$ n" u4 P3 F' l8 W) T/ y
Linear trend, 线性趋势
0 z& P5 K" D# e4 V7 DLoading, 载荷 ! W U) G! U' O' k6 b( f3 I" ]
Location and scale equivariance, 位置尺度同变性& n; c* C% j7 q: U
Location equivariance, 位置同变性1 V P! o( v( Q& \' y7 D7 a
Location invariance, 位置不变性
: G, n+ x4 X/ h" e7 A) HLocation scale family, 位置尺度族
; |9 w7 ~, O% k. |: R0 Z2 xLog rank test, 时序检验
& @* ~4 N& f- U/ h2 j& ?7 o HLogarithmic curve, 对数曲线
2 C X+ k5 t7 g" d! _4 @% P. MLogarithmic normal distribution, 对数正态分布
! W4 B" b& u1 ~. HLogarithmic scale, 对数尺度3 F- Q3 W2 g+ l1 {8 j6 I4 ]
Logarithmic transformation, 对数变换+ D5 B' \; \: V% T: l
Logic check, 逻辑检查
3 I' r" X# H4 V5 }2 s2 ?7 cLogistic distribution, 逻辑斯特分布
+ G8 B6 t# M- mLogit transformation, Logit转换
1 k3 k' S6 K& _4 [9 r4 f+ C' hLOGLINEAR, 多维列联表通用模型
2 ^6 d' B" s1 [/ n% gLognormal distribution, 对数正态分布- e8 a& m. P8 x7 C3 p
Lost function, 损失函数
9 x! G/ X7 p( b: F0 A* O- ?! Y6 ^Low correlation, 低度相关
+ v0 o: r+ b& L% c/ n' Z, GLower limit, 下限* Q& Q- p3 K# F W
Lowest-attained variance, 最小可达方差. v @2 p7 Q- Z6 _. i( g
LSD, 最小显著差法的简称- O* A; ]7 @: x* Y6 k: n
Lurking variable, 潜在变量- }2 E+ Z; Q1 P8 v& Q
Main effect, 主效应
M; b Z% B8 K5 j8 t# yMajor heading, 主辞标目) F4 ], B0 g) [! |4 o1 `& |
Marginal density function, 边缘密度函数 E5 j4 T7 X( r- i# y! ?
Marginal probability, 边缘概率
7 ^, m2 e& l3 F/ b( IMarginal probability distribution, 边缘概率分布3 { K6 i$ q# K# `" }# h- M9 o
Matched data, 配对资料
& G" B1 H. m, bMatched distribution, 匹配过分布$ f" l( m9 `: C& R
Matching of distribution, 分布的匹配
" B( U8 J4 z" P0 ^( \Matching of transformation, 变换的匹配 Q H3 q; T8 D7 m6 `
Mathematical expectation, 数学期望
, E- e7 E# j1 c$ A* \. y# FMathematical model, 数学模型
4 P, j5 O6 \) eMaximum L-estimator, 极大极小L 估计量2 Q- [! c+ V! P; `8 ?
Maximum likelihood method, 最大似然法
$ Z0 K' u& A6 k& J5 [: uMean, 均数8 o0 r2 {+ e% k0 Y
Mean squares between groups, 组间均方* a _- U8 n8 b3 a% f4 y. P
Mean squares within group, 组内均方
; l1 W5 a) Z- g; v' MMeans (Compare means), 均值-均值比较
% a2 `1 ] U7 \6 d; {8 }) |Median, 中位数
`9 B) ~9 z% O, R' O3 J, o# rMedian effective dose, 半数效量% v4 v6 V$ V$ Q3 [8 c. e
Median lethal dose, 半数致死量
% d0 w8 t m6 e! Y1 `. gMedian polish, 中位数平滑
$ Z, D. X( F3 N9 CMedian test, 中位数检验$ Y7 A0 [& p) y' a1 A
Minimal sufficient statistic, 最小充分统计量
7 R0 `2 u. M j% z# b* C: p$ B7 ZMinimum distance estimation, 最小距离估计
0 Y9 t6 u1 s1 f+ e2 q- F: SMinimum effective dose, 最小有效量6 E7 a9 W+ M6 `5 b9 M8 Z
Minimum lethal dose, 最小致死量
, `" @- S" O& ]3 WMinimum variance estimator, 最小方差估计量
+ R! z$ R; O9 C# z1 _2 S% u! {MINITAB, 统计软件包
5 l: T- }+ v# I, B/ [- q- T2 y, O8 }Minor heading, 宾词标目
" s1 }. c" U' @8 P; b9 [. IMissing data, 缺失值! y+ H) O+ U, J( A& K
Model specification, 模型的确定
' y7 b& B, W1 N& S- z/ }Modeling Statistics , 模型统计
+ }5 ^. t! x0 X" Z J4 p ^Models for outliers, 离群值模型
) f$ g5 G$ c" s9 HModifying the model, 模型的修正$ _% Y/ r4 ]; D$ _# H& ?" |
Modulus of continuity, 连续性模0 u( L4 `7 _) I- q$ j& J
Morbidity, 发病率 . c' v; {7 u; k
Most favorable configuration, 最有利构形
* f& D' C9 ~8 H" O% f% GMultidimensional Scaling (ASCAL), 多维尺度/多维标度
, P+ f! e5 L0 D6 }3 J' b2 JMultinomial Logistic Regression , 多项逻辑斯蒂回归
/ `) U+ S, Z$ [/ T/ @) aMultiple comparison, 多重比较
) k9 v6 W# b$ a7 I$ e. w1 ~( @- iMultiple correlation , 复相关
+ l; X- H6 q0 @2 [ V( |7 oMultiple covariance, 多元协方差
4 r- X* |: h8 Z% `Multiple linear regression, 多元线性回归: ~- t; x' ?5 M; G" j
Multiple response , 多重选项- B! \$ r+ u" }4 Y2 o6 \ j$ _; K* U
Multiple solutions, 多解
: V; x) g4 M& C4 xMultiplication theorem, 乘法定理
7 c$ B# \& ]( O4 a5 Z5 t: uMultiresponse, 多元响应
5 Z! e. Q. ~& xMulti-stage sampling, 多阶段抽样
, }; L* a! {; g% d2 e, TMultivariate T distribution, 多元T分布
+ K& U- c1 M# X) O BMutual exclusive, 互不相容- g) L8 q( U+ a9 V2 G
Mutual independence, 互相独立
" \- @0 f! D' i3 y2 e- ]% s2 oNatural boundary, 自然边界
e5 `4 ?+ d; O4 j" @$ YNatural dead, 自然死亡3 G. p$ H2 T4 n: P0 \1 a
Natural zero, 自然零
# g# c9 k6 D+ j- l4 ? m! G7 `7 FNegative correlation, 负相关
& A. h. C- K3 }* U# R- xNegative linear correlation, 负线性相关2 ?9 z, M! e P( ]; w
Negatively skewed, 负偏- a% @, |7 z1 M' E# L ]' F4 W) p
Newman-Keuls method, q检验
! Z, G' S4 C8 |$ xNK method, q检验
3 Z6 H9 I: i1 G, L% S/ ~No statistical significance, 无统计意义$ e4 s c2 {8 O* ~- z
Nominal variable, 名义变量
6 E) c- ^4 ^0 v; ^% K4 X) i: ~ w' Y+ v6 l# kNonconstancy of variability, 变异的非定常性6 Z' b6 d0 r* ? _) u& t
Nonlinear regression, 非线性相关. {4 _7 L- Q) \/ j
Nonparametric statistics, 非参数统计
P+ Q! o/ T; ~7 x' P; s1 qNonparametric test, 非参数检验, [6 i9 E2 M7 v: J8 A" L! h6 B
Nonparametric tests, 非参数检验
2 N2 m, g; F9 hNormal deviate, 正态离差' `* D9 N1 ^2 [" I
Normal distribution, 正态分布+ X: O1 ^4 q* p8 d4 R
Normal equation, 正规方程组
0 B( a* `8 j: @0 Q2 @9 X8 mNormal ranges, 正常范围
$ I, K2 r( t2 D: H1 BNormal value, 正常值- n1 i; n) E# n/ I& Q0 w. `
Nuisance parameter, 多余参数/讨厌参数+ ?2 G, [% U- f% e! ~7 V7 K6 Z
Null hypothesis, 无效假设
3 j! m& f6 A- F4 F8 @8 u- ^Numerical variable, 数值变量. V C! L+ M# T7 d' w
Objective function, 目标函数: J( l! a% S2 y, p5 n# l# ?
Observation unit, 观察单位
: T5 l" ]5 X; f/ `' n$ jObserved value, 观察值
* g0 j; d. O* g" A, DOne sided test, 单侧检验
& j: B3 J, F* t) k% l6 D; J: IOne-way analysis of variance, 单因素方差分析2 v& z& C; f- j' Z: n
Oneway ANOVA , 单因素方差分析
G8 Y9 c% t* _" S7 POpen sequential trial, 开放型序贯设计4 p' p2 g1 M b
Optrim, 优切尾
. ?- ?7 C: x8 i2 V e. ` NOptrim efficiency, 优切尾效率% o' d. J+ i6 d* S+ f# P# T5 e
Order statistics, 顺序统计量
4 S/ s0 Y. [# S6 s LOrdered categories, 有序分类
6 b' \/ j9 R1 b" }! @Ordinal logistic regression , 序数逻辑斯蒂回归
6 e6 n' @ E2 G; w+ z: |Ordinal variable, 有序变量
3 ?* R/ E/ f8 L8 P2 H3 U+ wOrthogonal basis, 正交基8 I6 w6 o, ~3 ?! r1 D9 t* o |7 @
Orthogonal design, 正交试验设计
: J( m2 C2 s5 z1 W9 M9 |Orthogonality conditions, 正交条件
2 Z; j3 Q: u }* S' BORTHOPLAN, 正交设计
p2 v1 x/ b8 H, KOutlier cutoffs, 离群值截断点& J6 G% _1 Z2 z! J' w8 ]
Outliers, 极端值. p: \8 _4 ] B5 D* L
OVERALS , 多组变量的非线性正规相关
% N; ]! ?% y- \( t$ d7 wOvershoot, 迭代过度
$ w* m) z$ g+ }6 W% R' ZPaired design, 配对设计
9 p, y: p+ j- u: d& i' kPaired sample, 配对样本
2 b; c! m4 f @0 }Pairwise slopes, 成对斜率* Q: s/ i( q$ i6 }
Parabola, 抛物线
' q. F- V4 S& F2 a* `" wParallel tests, 平行试验
4 u/ y( u8 l7 @ q) mParameter, 参数' H* Q0 X9 t. D$ I$ y- @0 r
Parametric statistics, 参数统计$ N+ G. r7 c0 `% a
Parametric test, 参数检验, s! x9 f" F' q4 j! S; e
Partial correlation, 偏相关7 W; U2 ]: h1 F$ W5 v
Partial regression, 偏回归
- T' G$ E! d$ A UPartial sorting, 偏排序4 X/ M! {1 t/ _. P
Partials residuals, 偏残差
- e/ p2 y! U% E+ aPattern, 模式( a9 f! ?2 \ Z( Z( V
Pearson curves, 皮尔逊曲线6 t( T) i* B( F
Peeling, 退层
$ \# l6 q7 y! U* W/ r: uPercent bar graph, 百分条形图' l7 Y8 x+ t* Y7 J$ \
Percentage, 百分比
' V, ]3 n/ q' ^Percentile, 百分位数
; ]+ |# C1 f5 T% A7 F2 f% S9 ^Percentile curves, 百分位曲线
5 F5 Q" z' d. q; S- N; c; uPeriodicity, 周期性2 e3 j2 O, o+ ^0 j) V+ \& a" O8 k
Permutation, 排列
" A# {* K$ v- a/ X# wP-estimator, P估计量7 s4 Q) _0 b* a3 ?1 Q
Pie graph, 饼图
' L6 R1 O. C) G, OPitman estimator, 皮特曼估计量- T) Y1 O/ k' G+ S9 `8 X' u" |, y
Pivot, 枢轴量+ T5 D& O4 m# e7 s$ f1 |* m
Planar, 平坦
) y! m/ g4 O; y0 GPlanar assumption, 平面的假设# ]3 T, M4 e2 h% B$ _" m
PLANCARDS, 生成试验的计划卡
* b2 K2 S' v) i5 @& ^( O& t( {Point estimation, 点估计
& r% m$ k5 V3 QPoisson distribution, 泊松分布, b" X7 v% H" A# f$ }
Polishing, 平滑% e3 y! x8 a0 L+ G. q
Polled standard deviation, 合并标准差9 b0 u1 h Y( T. [ O
Polled variance, 合并方差
- C/ J; ~5 C3 N+ e* x, ePolygon, 多边图' u1 c" a( ]5 C( N9 \. l! d" V
Polynomial, 多项式 w y2 Z' Z- K6 u5 Y, N' c
Polynomial curve, 多项式曲线
- g7 \! t5 C5 P+ jPopulation, 总体+ `: Q+ R: H5 m
Population attributable risk, 人群归因危险度 n, [6 y+ Z' C% l
Positive correlation, 正相关/ t$ R g. a- l/ [3 n
Positively skewed, 正偏# c5 E0 w) t8 k) Z* D
Posterior distribution, 后验分布- \# H. I7 x0 B* H% t
Power of a test, 检验效能
& W( G& u+ @( D+ D8 kPrecision, 精密度
0 f6 B, N/ q2 z9 e9 Y. \Predicted value, 预测值
' q" v8 s3 ^9 |, Q0 Z4 }1 k+ xPreliminary analysis, 预备性分析
: W4 Z( Z! N1 b- K/ {8 ~- GPrincipal component analysis, 主成分分析
( i" Y* Z+ ` ^8 ?9 \1 ]0 ePrior distribution, 先验分布
% r! F+ |( z) bPrior probability, 先验概率; V3 S9 j$ Q5 n; s+ W
Probabilistic model, 概率模型, f6 E' W! N/ Z0 h
probability, 概率
, w' |1 s9 Q u) `7 K* f3 S* JProbability density, 概率密度* E. L$ w* [. i8 H
Product moment, 乘积矩/协方差
4 |! ^' r% p% |0 i' j9 X* dProfile trace, 截面迹图
* M, ^1 X/ U* ?( e F7 {% h, s/ }; vProportion, 比/构成比0 D }5 d/ @4 L, Y$ m0 T! }( D Y
Proportion allocation in stratified random sampling, 按比例分层随机抽样' D/ X! k- g! e) X
Proportionate, 成比例
! `( x" T8 ?) fProportionate sub-class numbers, 成比例次级组含量. X- S$ C6 @7 y
Prospective study, 前瞻性调查
) ^" R7 I/ O' u9 `3 l7 fProximities, 亲近性 6 N0 Y" }; |) g6 \
Pseudo F test, 近似F检验. j" J! t' K1 o. E
Pseudo model, 近似模型
# p# V7 \' v% X4 ?& @Pseudosigma, 伪标准差
5 ^' J9 g2 x |0 L! G( N1 lPurposive sampling, 有目的抽样
, j1 S) T- w2 l4 g, PQR decomposition, QR分解& u5 C9 _8 A- E
Quadratic approximation, 二次近似, G, K1 x- }. @" ^+ z5 F
Qualitative classification, 属性分类) v; V$ I% W3 ^4 q; x6 w
Qualitative method, 定性方法. u' V; Y$ S- @3 ?* u- A3 a
Quantile-quantile plot, 分位数-分位数图/Q-Q图
7 h) f# ^% d! Z( N4 j1 x9 k3 W+ ?Quantitative analysis, 定量分析) F" b7 A4 j3 ~5 W0 ~
Quartile, 四分位数
7 B. ^1 a/ w' q' P/ T; `- _- tQuick Cluster, 快速聚类5 @- J; a& Y3 u
Radix sort, 基数排序
3 X2 e( H- C3 O0 m& F( H* ?8 YRandom allocation, 随机化分组4 |# f0 a; S# d/ b: d' s" `/ r
Random blocks design, 随机区组设计6 o& r8 m- K; Q) s) [& R9 z4 S
Random event, 随机事件
" H% i% s& r. l1 N L. `2 n, a+ [Randomization, 随机化" N: p3 ^3 {- ]8 S1 q, L1 o
Range, 极差/全距4 C5 r H5 b3 H. l
Rank correlation, 等级相关
3 ]% A3 o$ K! _1 _Rank sum test, 秩和检验
; z3 D0 l* I1 URank test, 秩检验# j# j8 U# z. z* @5 }9 k1 K' H
Ranked data, 等级资料; `2 c2 v- |% ]8 G7 Z5 `3 Z
Rate, 比率
' C- |/ q5 w& F, n1 nRatio, 比例
6 z1 W) q% c9 y' R6 B) q/ M$ r/ YRaw data, 原始资料$ T. b# I4 T% H) z7 \, J
Raw residual, 原始残差
) S7 u0 Z4 d" y2 }# [Rayleigh's test, 雷氏检验
$ [( ?6 l) H5 ^* \+ [; F6 d" e" t" ORayleigh's Z, 雷氏Z值 c! o4 K" ?! G, T! v
Reciprocal, 倒数
( N/ A3 u$ `$ v g" E' OReciprocal transformation, 倒数变换
m# Q% C5 r/ f! e+ ?$ y" }) nRecording, 记录. ^7 V% R- H) K- V" B: _
Redescending estimators, 回降估计量
& Z+ A( M* A8 n& @2 n+ ?) ]+ YReducing dimensions, 降维
8 T, G; N8 ~- k* Z/ cRe-expression, 重新表达9 q) M- H) @, u. ?
Reference set, 标准组6 O8 d9 c# M6 M# |* @% |2 N" _
Region of acceptance, 接受域
; K9 h9 g& ]( X/ iRegression coefficient, 回归系数& `/ a( J; \5 a* o# Z/ i
Regression sum of square, 回归平方和
7 u6 J' j$ _+ X: @1 N( _2 sRejection point, 拒绝点
4 W' g9 L X# X J7 C3 Z$ F6 }* _3 v2 ~Relative dispersion, 相对离散度, V: B$ H# k' \ o8 w; `/ h
Relative number, 相对数5 N5 y. f' p3 _
Reliability, 可靠性# j. x" }+ o' w: W* X( O
Reparametrization, 重新设置参数
" s1 L$ \. K' Q$ XReplication, 重复
- H) f, r l+ q3 i7 d1 j% JReport Summaries, 报告摘要: e1 V3 G5 w5 u# g: I3 K
Residual sum of square, 剩余平方和 f1 K( O# [8 Q& f) Z, @7 i% z" o
Resistance, 耐抗性1 u# N2 h3 o( I7 m3 g. f
Resistant line, 耐抗线
5 `! |2 E7 z1 Q! yResistant technique, 耐抗技术
; C# P9 S R' LR-estimator of location, 位置R估计量) V) a9 q; f, |2 E
R-estimator of scale, 尺度R估计量# M" h4 p& h8 K, b) S! ]
Retrospective study, 回顾性调查' b, @5 P, a+ C. D/ j* r' v Q9 v+ F- x
Ridge trace, 岭迹
2 ]- s0 G0 v( m& ?) M/ r5 JRidit analysis, Ridit分析8 B9 A2 I7 g, M. C" M
Rotation, 旋转' G3 V7 g* u8 G( `2 T
Rounding, 舍入3 y& _4 s' u, Y; y. H, Z7 U7 A1 y
Row, 行# t- u) V' @% w# L) T" L& ^
Row effects, 行效应% ^! A6 |0 e3 X/ g
Row factor, 行因素* ^" l2 w; X; `2 D0 E2 T
RXC table, RXC表
9 S- o& a; S8 l) Z) p) C2 V/ D8 [4 QSample, 样本" O) v+ D( N3 D* ^4 p
Sample regression coefficient, 样本回归系数
( |3 |5 F/ ^/ s7 k, P. HSample size, 样本量
, r2 i5 x3 G" _4 C. MSample standard deviation, 样本标准差) G. o/ r; F5 t5 ]; d, S6 a
Sampling error, 抽样误差
`, l# M- C Q/ C8 D1 JSAS(Statistical analysis system ), SAS统计软件包" r; U5 J1 P% O5 Q* _4 o' i3 o# l5 ]
Scale, 尺度/量表! _0 y) A5 y8 t6 Q0 v' l6 R
Scatter diagram, 散点图
% b: z- _' {( y% gSchematic plot, 示意图/简图 g1 a: p+ M5 m3 D0 Z" `
Score test, 计分检验; {& ^7 s4 R" m0 r! z0 S; f7 p
Screening, 筛检' x% S$ k. G( R1 @. Z
SEASON, 季节分析
$ s9 X7 \- k; K2 G, x: |Second derivative, 二阶导数/ \- U! G; E% r$ n/ v! e/ x( h
Second principal component, 第二主成分
' m, z* Y' G: J! FSEM (Structural equation modeling), 结构化方程模型 " e9 v9 r* h; F# q1 _" E
Semi-logarithmic graph, 半对数图6 C8 W1 G% [ |* q r& P3 Y6 r
Semi-logarithmic paper, 半对数格纸& }0 I# s9 N [: H T
Sensitivity curve, 敏感度曲线9 O6 x$ U; C8 h7 }1 i4 [( i
Sequential analysis, 贯序分析! T2 H8 ` U! q6 H& P- Y
Sequential data set, 顺序数据集
^% U7 f% n" h t: ^1 E5 d' mSequential design, 贯序设计9 S1 K# b. k7 Z. B
Sequential method, 贯序法
1 G2 y+ v, L3 m3 H% r: I9 ?2 Y- B0 w' QSequential test, 贯序检验法; r' k W/ p O+ O" z
Serial tests, 系列试验1 g+ Q* @0 P; A. l+ U- ?0 C5 c
Short-cut method, 简捷法
: \+ U$ ?$ A8 T F+ x6 aSigmoid curve, S形曲线5 v2 L' d- N) l8 a V
Sign function, 正负号函数9 b* {5 R# N: q& ]" Z- ?
Sign test, 符号检验
. X9 R& \$ S& Y' K, }7 O8 zSigned rank, 符号秩5 B' }. K0 S/ a5 v
Significance test, 显著性检验
, D* _& G! P2 }$ ySignificant figure, 有效数字& B8 h2 _" E5 V- F
Simple cluster sampling, 简单整群抽样
. N" ^' _" Y! P, XSimple correlation, 简单相关( m$ [( W x& s' l" G7 F: l D1 e8 F
Simple random sampling, 简单随机抽样3 e) u+ h3 T) e2 v/ `
Simple regression, 简单回归
* p: |3 Q: A1 d$ @simple table, 简单表
# z+ R+ o( ]& _8 @. E% T. [4 p7 QSine estimator, 正弦估计量
! R* w) S8 B/ j& Y j' r( bSingle-valued estimate, 单值估计7 M% z" Q* `2 E' \$ J
Singular matrix, 奇异矩阵
7 w+ I' Q z$ f2 ^/ oSkewed distribution, 偏斜分布
% T Q; K5 ?0 N! i- B2 qSkewness, 偏度 w1 K ~: A4 |, U, t
Slash distribution, 斜线分布
+ x V3 x6 n' WSlope, 斜率5 h. K( H9 i' ?" \7 Q7 H
Smirnov test, 斯米尔诺夫检验
4 o E. t9 t0 L) VSource of variation, 变异来源0 n" |6 v; g, a
Spearman rank correlation, 斯皮尔曼等级相关
r7 X" O7 W' l0 ?* X" [+ `9 G' jSpecific factor, 特殊因子
! b* @, Z5 Y# Q" u: M0 K; GSpecific factor variance, 特殊因子方差7 t6 |6 H% C7 Y+ c5 g+ v8 V
Spectra , 频谱; {4 F' a. o) {4 z" W$ f2 u" j
Spherical distribution, 球型正态分布' V$ N, n. T* _. s
Spread, 展布
: {1 w) n0 y# B7 [$ CSPSS(Statistical package for the social science), SPSS统计软件包
, M- Q7 y( C# b8 N0 B2 n' bSpurious correlation, 假性相关
3 p+ H" N; R& `, Q0 ~6 |6 G7 }8 LSquare root transformation, 平方根变换
$ H5 t! N+ o) \7 F4 |& ~& X. CStabilizing variance, 稳定方差
8 G/ f- b+ p+ \' |# r, S3 [Standard deviation, 标准差4 i4 s) a8 ~1 `# ?$ o
Standard error, 标准误2 q- ]2 W2 e" @* \, [
Standard error of difference, 差别的标准误# d$ C$ u; _4 ]5 w
Standard error of estimate, 标准估计误差
; P9 C; }. h# HStandard error of rate, 率的标准误
8 k4 ~- @2 f' l( t K% X' z9 mStandard normal distribution, 标准正态分布) G( t* p2 o a3 e9 k: n
Standardization, 标准化
7 e' J+ ^% R; \7 I7 f" r1 oStarting value, 起始值
$ M8 B1 D3 F, G/ q7 F |. @Statistic, 统计量# Y( v J7 F& K0 y: a2 G
Statistical control, 统计控制
# o* \* d$ ]0 w5 t) X0 K2 P! |9 ZStatistical graph, 统计图
# X. @2 \- b4 y# u4 m8 ]Statistical inference, 统计推断
+ B& ?0 C9 @1 g" M" L$ {: l/ ]Statistical table, 统计表
! m4 t A t& X6 }1 qSteepest descent, 最速下降法
: l0 V$ v! a" XStem and leaf display, 茎叶图5 I2 w# O/ J' M* o1 z( ~
Step factor, 步长因子
# J: `3 T1 h A% NStepwise regression, 逐步回归* S2 c5 q6 }$ A* Y; ^
Storage, 存
7 H" E/ S4 O/ o) \+ U9 \Strata, 层（复数）* ^* |( R' f0 h
Stratified sampling, 分层抽样
* r0 p) B- I$ g1 S1 [$ Q1 {Stratified sampling, 分层抽样, K% u4 g& B9 _4 l4 P$ }, u
Strength, 强度
6 [' V1 y! U2 c, e, ~) ?( X/ o. c1 qStringency, 严密性1 X6 r0 `- B( f; p F& x$ B
Structural relationship, 结构关系7 x( x8 B% r% ~# i0 `
Studentized residual, 学生化残差/t化残差8 q9 Y9 E* ?. l& x4 O4 L
Sub-class numbers, 次级组含量9 e4 D) O( r' X% A) w
Subdividing, 分割
: d& H+ ~- P7 n( N }" aSufficient statistic, 充分统计量
% v# }# g( @/ K! KSum of products, 积和6 {! Q2 q4 ]5 ^. L. z
Sum of squares, 离差平方和- y! K9 s, K$ @4 _* K7 v k; M* I
Sum of squares about regression, 回归平方和
: o! [3 I0 N. v% t' P; x2 ZSum of squares between groups, 组间平方和
9 b8 | s( b2 ?5 c) RSum of squares of partial regression, 偏回归平方和
/ D- E2 p8 J! e' @, uSure event, 必然事件
M# g' q" T, ~ e1 J% ^9 p& J* @Survey, 调查
: R1 ~9 y3 r+ m$ kSurvival, 生存分析
$ F' S8 T: C0 h, qSurvival rate, 生存率
5 ]" I; H3 w* |( H0 g4 B1 ?Suspended root gram, 悬吊根图
2 a# s" h Q" v" p3 m7 r" z6 R3 v, eSymmetry, 对称# E8 |; C6 I7 w
Systematic error, 系统误差
8 `# G: k6 S! E9 H% |Systematic sampling, 系统抽样
1 }7 P9 U) m& F, ?9 GTags, 标签 V3 {5 Q* s' B! } P* C
Tail area, 尾部面积
) D/ j3 d/ l8 U5 xTail length, 尾长& x( [" |) F# r: ~- \
Tail weight, 尾重0 W' I$ }- t/ n; ^' z
Tangent line, 切线 I; k: W/ D# [
Target distribution, 目标分布
6 R* C C; \ o; @4 KTaylor series, 泰勒级数
+ Q3 f8 r! c7 A- DTendency of dispersion, 离散趋势+ v9 s; C* o: D
Testing of hypotheses, 假设检验. I n. N0 e* x& V: `# e
Theoretical frequency, 理论频数9 ]7 z0 h$ s# ^
Time series, 时间序列
) y. R k+ R0 @+ S7 C6 QTolerance interval, 容忍区间, p7 p1 O, ~( Z
Tolerance lower limit, 容忍下限
- _% j+ ?. r: [0 t( n8 P+ d6 U. ?* nTolerance upper limit, 容忍上限& D2 c0 y& q& K8 x5 U5 m
Torsion, 扰率
- _- X+ j! l' U1 G( }Total sum of square, 总平方和
3 o# O1 c+ w3 n" q L$ U ITotal variation, 总变异
5 Y% s2 i4 S6 _# a. XTransformation, 转换, B3 r* {, h+ M2 O
Treatment, 处理
. {$ T, V: E8 S/ O0 m4 ?; iTrend, 趋势 `+ z# l' D* P+ Z. o: V
Trend of percentage, 百分比趋势
! [: Z/ B8 Y' s9 YTrial, 试验
/ o3 W! U: g/ {- zTrial and error method, 试错法
2 v6 c, l9 Z% b8 E+ p9 oTuning constant, 细调常数' q @6 q4 a0 o9 M k
Two sided test, 双向检验" K) D' R8 d0 F/ X$ }9 x" M
Two-stage least squares, 二阶最小平方
6 a: r6 C# c8 U( J- l" y4 TTwo-stage sampling, 二阶段抽样* u V( F1 G" O" |
Two-tailed test, 双侧检验
7 y6 {' Z7 A+ Q8 C# tTwo-way analysis of variance, 双因素方差分析$ A( D- }7 Y w6 R. |4 W
Two-way table, 双向表3 E; r+ U0 D2 p/ m9 Q7 U, g
Type I error, 一类错误/α错误$ P" M0 {2 c$ U- w+ D
Type II error, 二类错误/β错误: g$ S( D* x* ~5 M8 c! _
UMVU, 方差一致最小无偏估计简称' z$ e# g& ^' Z. o' h$ E
Unbiased estimate, 无偏估计, ^ ?2 {* s8 c& R1 x8 m
Unconstrained nonlinear regression , 无约束非线性回归
+ e9 }1 ^$ ^& W) NUnequal subclass number, 不等次级组含量
2 q$ w0 d! N' w: l- r5 A8 cUngrouped data, 不分组资料4 [" ?( Q, X7 j, c
Uniform coordinate, 均匀坐标
3 A! T9 Y( L# P' r& d- @Uniform distribution, 均匀分布; D& c6 C4 o6 {: d1 H4 D* x) E" K' R
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计, o. r' X# C: T2 o4 y
Unit, 单元
# x9 D! ?1 j+ ~& E3 L0 N! Z+ v/ ]Unordered categories, 无序分类
$ S) H" V4 V4 iUpper limit, 上限
2 Y! N9 V9 r. j8 [( J2 LUpward rank, 升秩
) f4 E: [0 R2 l2 x* SVague concept, 模糊概念6 ^* e, B8 n1 _" O! X* ]: f
Validity, 有效性7 Y: d, ]% p8 N. j6 W
VARCOMP (Variance component estimation), 方差元素估计3 B% z3 M& `, i8 |; H
Variability, 变异性 K2 K( D7 i, @/ d6 J
Variable, 变量9 M6 A3 @3 H; P" D3 H% @- Q
Variance, 方差7 L4 a. H1 `& u* d# M
Variation, 变异
3 ]% R7 D7 m u3 K) U+ l8 mVarimax orthogonal rotation, 方差最大正交旋转
! _+ I1 p! R5 G6 D! A4 h7 }; SVolume of distribution, 容积
7 h/ `& |4 k3 E+ C$ O+ z# P. w1 hW test, W检验4 [( w- H- Z/ n% n8 v. F) J
Weibull distribution, 威布尔分布
" _" \( v, @9 ` N% W! U2 i2 l6 AWeight, 权数
( {# a% p% H$ u& ?2 h( t6 k! g" zWeighted Chi-square test, 加权卡方检验/Cochran检验8 D+ A, h- o6 R5 m c, @
Weighted linear regression method, 加权直线回归
( a& K5 A; c* b; P7 K- ^Weighted mean, 加权平均数8 q& m5 H1 T$ G) V
Weighted mean square, 加权平均方差
2 o2 R: Z7 z3 yWeighted sum of square, 加权平方和2 x" b; k/ n: W: Q) {/ \
Weighting coefficient, 权重系数
$ U+ k0 i/ R* J& b& GWeighting method, 加权法 $ n5 a) Y6 n& D- r) F; R
W-estimation, W估计量
# J4 y* W% ]% ^& {0 nW-estimation of location, 位置W估计量
1 J- e8 S$ O, u4 Y- n. t3 P XWidth, 宽度" G# P1 U2 R. J7 U9 k* h: C
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验- u+ C7 `# K+ h& g2 E. d
Wild point, 野点/狂点; J2 e; s7 r( u L7 ]
Wild value, 野值/狂值
9 G7 x% w( q- p; w RWinsorized mean, 缩尾均值+ S0 u0 M v& a2 _ T0 M" H
Withdraw, 失访
2 U) E" f; O. qYouden's index, 尤登指数( j+ _( N4 U0 h0 A6 S" W; L
Z test, Z检验; q c. t6 m! D3 [" |
Zero correlation, 零相关
% M8 L [9 p/ FZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
