|
|
Absolute deviation, 绝对离差
: q) @+ G8 j% I3 MAbsolute number, 绝对数$ E4 K5 W9 {* A2 y: b
Absolute residuals, 绝对残差
' s9 b" Q- v/ K3 G5 N9 v6 P. w) sAcceleration array, 加速度立体阵
) e5 v$ V" `/ g7 M R/ L. V s, kAcceleration in an arbitrary direction, 任意方向上的加速度* N) \4 ~+ L% x _1 R- P
Acceleration normal, 法向加速度, c. [& S1 G% h) q1 {& m
Acceleration space dimension, 加速度空间的维数
) R% v9 i) w4 HAcceleration tangential, 切向加速度. ^* w0 D/ t$ Q
Acceleration vector, 加速度向量
( w2 H+ D: \; K0 ` aAcceptable hypothesis, 可接受假设 f' h0 J: `, L; k" G; ]) C$ ?
Accumulation, 累积
, t" w4 ?" p) M7 fAccuracy, 准确度
* G- E4 ~7 W6 X* _2 f3 t4 d; `Actual frequency, 实际频数% Q2 u! k ?' g* Y8 c. w
Adaptive estimator, 自适应估计量
- k0 n+ j. T2 h3 e0 e3 KAddition, 相加
1 e2 U9 F6 D a1 L- X gAddition theorem, 加法定理5 D( \, j4 q6 e$ J) W( Z4 M
Additivity, 可加性+ |$ _: O9 `3 ?
Adjusted rate, 调整率+ w% K- n, a ]' p1 w( H" H/ ?
Adjusted value, 校正值! ^) i5 k' {" k% T6 ^
Admissible error, 容许误差
/ G1 g6 E% r" F- x! d: pAggregation, 聚集性. _7 _2 s4 X2 t0 ]0 s" p* `4 r
Alternative hypothesis, 备择假设
# P2 b6 p2 a/ ?9 \; W+ BAmong groups, 组间* z. L1 P) f3 v P7 g- I
Amounts, 总量
, @' ?: w+ w& U3 C* cAnalysis of correlation, 相关分析1 q" R7 d, A$ L/ [
Analysis of covariance, 协方差分析
5 d" v# m5 L* m3 q$ k9 M8 p1 v, f* D/ E- GAnalysis of regression, 回归分析8 Z* \, |" C. o m
Analysis of time series, 时间序列分析8 i$ }9 d7 C; E0 J' O8 C& x4 W, y
Analysis of variance, 方差分析+ A+ F/ X0 e; X+ h! f, p2 K, o
Angular transformation, 角转换
% ^2 U' {7 f; ~ r9 YANOVA (analysis of variance), 方差分析: E$ u4 j3 L; s( W0 N! o* j3 n
ANOVA Models, 方差分析模型& d" g1 r& X6 ?% N& d% Q& r2 A
Arcing, 弧/弧旋
9 e c8 I: r# A# S1 r, z, dArcsine transformation, 反正弦变换8 R; ^2 R: k; z( H$ D" D7 q
Area under the curve, 曲线面积
/ j( x+ E: @& @( S" S. ~AREG , 评估从一个时间点到下一个时间点回归相关时的误差 3 b; \' {9 b" u) ]% A. f1 V
ARIMA, 季节和非季节性单变量模型的极大似然估计 4 H$ u" x/ f1 E& Q' B% R' t, k* Z& V( H
Arithmetic grid paper, 算术格纸
) O8 T! T9 m4 R. ^8 gArithmetic mean, 算术平均数; T# l9 V. h) m, _) d+ V
Arrhenius relation, 艾恩尼斯关系
" H) f5 v* r! M# e% n* b: t+ sAssessing fit, 拟合的评估; V: ]% B: b" i
Associative laws, 结合律
0 W$ r# p! }( A" [, ^! rAsymmetric distribution, 非对称分布
1 T8 E7 T2 {1 U6 C# l& ^Asymptotic bias, 渐近偏倚
5 q* K* g; O% d5 g( q$ r" A8 sAsymptotic efficiency, 渐近效率
M& G# y. ^1 M' L/ WAsymptotic variance, 渐近方差
$ E3 ^' C# n3 t5 {; b4 M4 s$ v' XAttributable risk, 归因危险度$ U0 V/ u0 R0 x+ m1 @9 C8 p! X
Attribute data, 属性资料
7 b0 _# R. e5 @7 v$ F+ H7 D+ |Attribution, 属性
( y+ d: r9 J0 o. BAutocorrelation, 自相关0 ]" e s7 o7 p5 ^9 ]" B
Autocorrelation of residuals, 残差的自相关
+ j2 r* ?9 m4 TAverage, 平均数
6 ^7 T- @! w6 ~/ R$ _Average confidence interval length, 平均置信区间长度( F/ x( y5 m* {% x
Average growth rate, 平均增长率. K( f2 }( `: {! n* Y- D
Bar chart, 条形图
- F K( M5 ^& V+ q* w8 mBar graph, 条形图
% V* B: n8 Q8 `# d& HBase period, 基期
* o& }0 n7 t WBayes' theorem , Bayes定理
$ J+ `. z/ i; bBell-shaped curve, 钟形曲线2 Z+ }) A$ N1 F9 `( e* t
Bernoulli distribution, 伯努力分布8 n6 ^* `8 A* s( M5 u2 S
Best-trim estimator, 最好切尾估计量
/ r& e4 R* P! c1 L9 LBias, 偏性
5 e/ P1 ^4 |( h2 h" t- TBinary logistic regression, 二元逻辑斯蒂回归
/ b* v* Z5 G/ eBinomial distribution, 二项分布
; j& U# x6 w: E5 P, ]Bisquare, 双平方
& T5 Y- A; C4 F/ u6 S( `6 P( dBivariate Correlate, 二变量相关% i/ q! i+ @3 R; ~; N% R0 T
Bivariate normal distribution, 双变量正态分布
) w, Z+ n0 a* _5 P3 |; GBivariate normal population, 双变量正态总体8 Z* a a& G s: b9 ^
Biweight interval, 双权区间# a5 q N' H# r: Z/ h( N8 ]% D
Biweight M-estimator, 双权M估计量5 }. o) v: c X: ~5 j# e8 R* t" R1 k
Block, 区组/配伍组- `/ q/ u- e- f* j' t9 P
BMDP(Biomedical computer programs), BMDP统计软件包
# b' s$ w7 S7 }5 j4 y3 `Boxplots, 箱线图/箱尾图) `% @: O* [3 W6 k
Breakdown bound, 崩溃界/崩溃点3 r1 z. T( A( z/ `" [
Canonical correlation, 典型相关
. B; T; Z# d7 f7 H5 }Caption, 纵标目5 x2 M. o& `/ `4 N& r: f
Case-control study, 病例对照研究# ~/ A1 _5 q: E9 e2 n5 L
Categorical variable, 分类变量
$ @) D# T" l- w9 W% L9 N5 BCatenary, 悬链线( S M8 B) `# E* q, b7 @# d d
Cauchy distribution, 柯西分布
9 W* F' {+ x. ?, }5 ^Cause-and-effect relationship, 因果关系
6 Y% s% ]* H) s3 w5 ?/ ]Cell, 单元
$ k+ p% \, Y$ [) `Censoring, 终检5 `% O/ U. o( X. {% i
Center of symmetry, 对称中心
, v! C1 d4 d2 k: jCentering and scaling, 中心化和定标# J' D! E- s5 b
Central tendency, 集中趋势
+ e# e% e; R3 @7 p* cCentral value, 中心值6 d2 W3 b% u. v1 W. a, G
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测 Y, Q- `9 M4 e) B
Chance, 机遇
" c- e7 i& z3 @, g: o6 t) TChance error, 随机误差- P! r) N& ~0 b1 Y
Chance variable, 随机变量
. V- ~; E: {6 _: MCharacteristic equation, 特征方程
2 Y, ]! i0 J4 t+ e$ i9 I8 rCharacteristic root, 特征根
0 r4 z+ h9 N$ M( }* p9 rCharacteristic vector, 特征向量
, I( \: R9 F! q& L: WChebshev criterion of fit, 拟合的切比雪夫准则
" z* X3 _" e, K- @ L! F7 B" }! `Chernoff faces, 切尔诺夫脸谱图
/ n T& d+ y3 Y H( IChi-square test, 卡方检验/χ2检验# Q6 X" u$ V6 Z+ _, [7 P9 e# E
Choleskey decomposition, 乔洛斯基分解
: Z" M* e% N, {3 N) ^" QCircle chart, 圆图 7 Z- D( e) m2 _6 E3 f F# I
Class interval, 组距; T2 B) R- }/ u2 I4 g
Class mid-value, 组中值
$ A g$ Z! R+ M6 dClass upper limit, 组上限' [+ B) X+ S$ B/ B* O2 E, P
Classified variable, 分类变量
* A) _- u' X+ W. ~0 _& y1 bCluster analysis, 聚类分析
; _- U% P. T% RCluster sampling, 整群抽样
5 O, m! B- o0 v' {Code, 代码
, @* ~3 ~* [$ UCoded data, 编码数据
+ q8 e- v; t! ~8 d, PCoding, 编码, u5 r1 b* ~- { d9 l
Coefficient of contingency, 列联系数1 J/ K' ^ O& j8 t3 e
Coefficient of determination, 决定系数
B, l4 D* P- i4 r& tCoefficient of multiple correlation, 多重相关系数 g: y: n8 Z( J; Y. p" V$ ~
Coefficient of partial correlation, 偏相关系数1 J) ]4 i, N% r! ~( c
Coefficient of production-moment correlation, 积差相关系数+ v* ^ _1 H5 ]) X0 \- P6 c
Coefficient of rank correlation, 等级相关系数
& d8 X1 [# n8 o0 XCoefficient of regression, 回归系数5 }* W$ H2 {' W& `
Coefficient of skewness, 偏度系数
$ I6 q* w4 [& [Coefficient of variation, 变异系数& E; H; ^. c1 O& {, a* O ]
Cohort study, 队列研究6 | J: {" d9 _# O* A7 |3 n8 K
Column, 列; |8 O8 M& @+ ~: T
Column effect, 列效应
4 X! |5 A4 N3 XColumn factor, 列因素- G) N; u% X1 G
Combination pool, 合并4 H0 [. L) O- i: [, z
Combinative table, 组合表
2 a4 o$ w2 Q: F+ C+ d6 b7 ~Common factor, 共性因子
8 h: B9 a( G! m9 h% lCommon regression coefficient, 公共回归系数
( L. C# t8 I* S+ X* ], ] f" C0 sCommon value, 共同值
7 l$ e1 d) ^( E# p& W+ Z2 \! BCommon variance, 公共方差5 Q; t# i( s) \7 `. f- a) S, O! C
Common variation, 公共变异
V3 I3 ~% L, S: [7 bCommunality variance, 共性方差1 {; s: Y3 c; x9 f/ ^* D: a
Comparability, 可比性
G; \8 J$ C6 I4 hComparison of bathes, 批比较
/ h& J/ |' i* D2 CComparison value, 比较值
2 V# V* s) P( W( @% E7 x( M1 u, xCompartment model, 分部模型
) v+ v }. f8 I8 l3 ~Compassion, 伸缩
; J/ } E9 n$ G; bComplement of an event, 补事件& w8 e1 [0 v7 E7 l9 k# J- S+ B
Complete association, 完全正相关& r2 [0 Y) P [( t
Complete dissociation, 完全不相关! I0 ~5 c6 x+ @0 G
Complete statistics, 完备统计量; T- {+ b! F& P* e! L* v* A1 @4 |
Completely randomized design, 完全随机化设计
8 b8 z4 _- G- ?, B# X4 [$ v! fComposite event, 联合事件2 x" U0 |5 G- N# }: v. T
Composite events, 复合事件) `& U6 J' y1 Y2 T0 Y% ~3 i
Concavity, 凹性
2 V/ l$ u" K4 V- z4 IConditional expectation, 条件期望
8 K4 ~4 t) t6 R% f! y& e. mConditional likelihood, 条件似然* L& T8 `0 c9 K! x
Conditional probability, 条件概率( p0 F u9 v' @+ P+ n# m" `
Conditionally linear, 依条件线性
/ z6 ?" x( g3 pConfidence interval, 置信区间3 X1 q5 {! D$ {, X$ W& _! l& q
Confidence limit, 置信限
$ E" i5 }9 S; a! S6 AConfidence lower limit, 置信下限- k: s% Z3 H5 F; c4 n
Confidence upper limit, 置信上限& P' N% [, y7 D7 |
Confirmatory Factor Analysis , 验证性因子分析
6 A5 g3 S+ ~" z4 DConfirmatory research, 证实性实验研究* V( A' H! d. [, k/ n- m. l
Confounding factor, 混杂因素- z {6 [% S( {9 P
Conjoint, 联合分析
& Z6 p" j! s. i3 ^Consistency, 相合性" b; K+ n/ I: W: G* p
Consistency check, 一致性检验3 |6 k4 R9 ^$ P. ~; _* E5 O p
Consistent asymptotically normal estimate, 相合渐近正态估计
* a, N, E0 r* q+ b7 c% u/ a a! ~' IConsistent estimate, 相合估计7 f$ ? x) @! J* ~% J$ _# b& P
Constrained nonlinear regression, 受约束非线性回归
$ x9 d7 K$ T, I" z- \! b% AConstraint, 约束; r2 [+ |7 V8 e4 H
Contaminated distribution, 污染分布
& d# P7 M$ x8 O* jContaminated Gausssian, 污染高斯分布
7 V4 C0 V8 k; o" k5 }Contaminated normal distribution, 污染正态分布, @' F2 w/ Y+ o
Contamination, 污染 T" x( C6 v. K7 k; v1 V" {
Contamination model, 污染模型
8 M+ @- g* V- J6 |, k8 G1 E% L- dContingency table, 列联表
# A5 H5 Q% O' ?. w8 P. JContour, 边界线
) w; v* t( G* @; v5 o0 L, yContribution rate, 贡献率
. o3 ^. l4 u: _2 W# O) U/ C0 gControl, 对照
# U: v2 ?, `/ e. \& qControlled experiments, 对照实验' [: \0 j+ h. b; S
Conventional depth, 常规深度3 R& h* w- h K+ t% N$ ^
Convolution, 卷积5 W" Q6 ~; i0 s! g" c: |3 X, D4 [
Corrected factor, 校正因子7 g5 F- E* b& w5 z% k6 q& v
Corrected mean, 校正均值
' U# x7 r/ s5 N6 |Correction coefficient, 校正系数9 I3 |+ i# V: G3 i0 Z/ Z% e
Correctness, 正确性
o) g) _* \7 K0 Q0 `7 mCorrelation coefficient, 相关系数) r2 U9 h8 O$ e3 \, ]/ V, f
Correlation index, 相关指数- V' q* A: R1 `6 s# x
Correspondence, 对应
7 ?8 {) [6 w! U' \$ KCounting, 计数
7 W/ Y9 O( S( c, }Counts, 计数/频数
! ]; V- r9 ^9 _* I5 WCovariance, 协方差
0 l {& t5 M! J; q- \9 WCovariant, 共变
8 X) z8 h: h$ `6 fCox Regression, Cox回归" S* t$ T' o% U
Criteria for fitting, 拟合准则
7 M) p9 X# q7 c3 {+ `# {) o7 A' ACriteria of least squares, 最小二乘准则
1 d f6 B0 s& W' l% {Critical ratio, 临界比
$ `; a& |9 ?. rCritical region, 拒绝域
2 k$ S. m& R$ ^' w! s7 SCritical value, 临界值
" W7 B4 L. Z; A4 L& a6 pCross-over design, 交叉设计0 s) _- \$ K- d# b* t
Cross-section analysis, 横断面分析
4 r8 K( y. ]$ N5 `% X) P0 P. XCross-section survey, 横断面调查
& b; p1 g) Y. G. |* z+ }. bCrosstabs , 交叉表
/ r: p% R) ]; N/ ]0 h6 gCross-tabulation table, 复合表
$ {5 M7 c7 O% VCube root, 立方根# h; j9 Z, ?, Z2 G: K" z
Cumulative distribution function, 分布函数5 }! y& O/ v5 w$ y4 e# T; E7 ?
Cumulative probability, 累计概率
0 X0 G5 `. P$ g% q, {- R4 J: ?3 h- pCurvature, 曲率/弯曲8 ^3 P6 M2 b+ [5 x
Curvature, 曲率: B. b5 ?3 Y+ M; E* p4 X8 y
Curve fit , 曲线拟和 4 K i2 C2 D% C6 l( E7 ]2 C5 a" ?
Curve fitting, 曲线拟合: |9 j' p) I2 y. N0 ~
Curvilinear regression, 曲线回归8 C! k8 ]$ ^% e& P$ s- p
Curvilinear relation, 曲线关系
* D# m: M- M7 ~+ |Cut-and-try method, 尝试法: B0 a) M, R, A& |% n! ]- m0 b# h
Cycle, 周期1 n1 X& ]! R1 A2 @! [5 g2 A) q
Cyclist, 周期性
$ {2 V& ~- X ]: n5 k/ q) [D test, D检验5 T4 d- K- N) K2 r% X- P. D" D# [
Data acquisition, 资料收集& U! P3 q) i6 D& D6 M6 ^
Data bank, 数据库
2 `5 z4 s' I4 ^& f6 CData capacity, 数据容量 _- V& H6 s# U
Data deficiencies, 数据缺乏
7 h1 C! t9 j. LData handling, 数据处理
) r4 a& l' Q' g% GData manipulation, 数据处理
6 T1 g) J- Y( G% BData processing, 数据处理8 q* i! u! e9 ?7 K( F7 h
Data reduction, 数据缩减) X0 v. b+ a: O7 B5 m2 K- X
Data set, 数据集
7 C- u0 F- @6 y7 A" BData sources, 数据来源" h0 r" y! Z* o3 _, g
Data transformation, 数据变换" ^. K" T4 R9 w; R. P1 v
Data validity, 数据有效性' W3 m- q N9 {( n% Q
Data-in, 数据输入
8 _# S$ V$ |, J6 ^1 @ q S& w* qData-out, 数据输出) Z0 ]5 b" [1 S$ G- m/ k- b
Dead time, 停滞期
2 [8 B. e/ X: Q5 G+ sDegree of freedom, 自由度2 n& j# Q8 H/ _! s0 D2 _4 ~2 n+ f
Degree of precision, 精密度
3 X) A( P4 p# Y) t0 e& Q4 S* EDegree of reliability, 可靠性程度
& z% m" |; b. Z4 n0 G: Q, HDegression, 递减
6 d9 o+ Q4 B5 F2 \6 a/ ?( SDensity function, 密度函数
2 `" @% a, j2 h* QDensity of data points, 数据点的密度
, N% t# w" y# i* d# hDependent variable, 应变量/依变量/因变量
k C: t; H* A O JDependent variable, 因变量
$ B S( W' P/ f2 \; o* }Depth, 深度% C# r+ P9 S" P
Derivative matrix, 导数矩阵
8 f- I& u& `- p8 Z1 Y% X! L4 DDerivative-free methods, 无导数方法
( r: B+ D% R% p1 N2 S/ ~- WDesign, 设计
0 o/ n1 @( `+ d$ Q$ G& ]& {Determinacy, 确定性
; X* e/ {# _; M; W2 e" Z& K* pDeterminant, 行列式. l3 h. o8 b( H$ r- R4 u! m
Determinant, 决定因素: p5 [& l. P4 y8 B1 r, A
Deviation, 离差. ]+ W$ X; C, ~& {6 ~& E' x& i, i
Deviation from average, 离均差; d; }) s6 a8 f4 C, z" h6 r
Diagnostic plot, 诊断图+ ?8 z/ {' y- N& [# H
Dichotomous variable, 二分变量/ M1 j1 s5 M6 a" Q$ ~0 I
Differential equation, 微分方程
) ?' O/ z1 C/ |3 p9 ] v* |# dDirect standardization, 直接标准化法6 e9 Z+ O2 F" L% ^3 ]
Discrete variable, 离散型变量
* _) A$ d* d2 \; T; y2 K# VDISCRIMINANT, 判断 ) _* Q: o2 t7 T \; l4 k; d# Z
Discriminant analysis, 判别分析1 D) l# P1 |. M2 C' Q$ s
Discriminant coefficient, 判别系数: p( P, u4 c, S+ p: k- p7 F
Discriminant function, 判别值/ V; @; a" ?4 u* m
Dispersion, 散布/分散度 P, F- S0 F$ N& M& v( r5 o
Disproportional, 不成比例的! e3 t. n6 Y* [
Disproportionate sub-class numbers, 不成比例次级组含量
& Y2 q. g, G8 Y) t( YDistribution free, 分布无关性/免分布7 d. Y; ^9 i" n& ^2 ~
Distribution shape, 分布形状2 W$ d2 N! E4 x' b
Distribution-free method, 任意分布法
2 p) Y7 A" a- T) m% o& I+ k; {Distributive laws, 分配律- X" x2 b R! O; m& w* v/ D a
Disturbance, 随机扰动项5 \# h/ F7 ^) ]; `6 A
Dose response curve, 剂量反应曲线& n4 X T( A0 `5 B/ v! `7 u
Double blind method, 双盲法9 V" d( ^* k9 j
Double blind trial, 双盲试验1 X5 K( l3 ?2 x: q) b$ M
Double exponential distribution, 双指数分布
3 }: w# d# m* J3 h% NDouble logarithmic, 双对数0 A! j. l# b* X3 A$ s8 e
Downward rank, 降秩
# i+ V% T; V9 ^! T9 V: ZDual-space plot, 对偶空间图8 y4 c% p- K, w8 f/ c
DUD, 无导数方法
1 _3 B$ p* x9 }' {% SDuncan's new multiple range method, 新复极差法/Duncan新法: \( A8 ^- k1 T. ]8 U0 i% R& k
Effect, 实验效应
6 P T9 R$ L9 D' j+ z# pEigenvalue, 特征值+ }2 T/ |7 N7 k! D7 u
Eigenvector, 特征向量; P( n7 O( t$ g9 p0 K5 g. L- i4 f
Ellipse, 椭圆
# K% S/ o2 r( I) Q( \: XEmpirical distribution, 经验分布1 W/ g P! u8 Z/ f2 A: a
Empirical probability, 经验概率单位
, k% r, Z$ `& R9 X# uEnumeration data, 计数资料7 y6 w7 ?6 s" ~( f, S6 g2 t$ j0 ?
Equal sun-class number, 相等次级组含量4 Z( y5 f( U6 ^# N/ x$ `( i0 O
Equally likely, 等可能
; f( Q( `+ L( }7 V: ~& t6 Z7 `Equivariance, 同变性
+ J3 i7 S: R& T2 F# m& _8 ^8 q' V: vError, 误差/错误' ]6 y% Z& U7 _$ h& C- g
Error of estimate, 估计误差* ?7 n# c) ~: n6 D: ^) v6 t
Error type I, 第一类错误( }4 k1 Y, D$ c: u- a% t
Error type II, 第二类错误
# x' x' _! ~% i: e$ i# y& yEstimand, 被估量
C- B! b6 O# t* B2 dEstimated error mean squares, 估计误差均方
0 `2 Q* B [1 }6 h0 o5 ^' ~Estimated error sum of squares, 估计误差平方和
( j/ w$ V, s: K6 }5 h; L7 fEuclidean distance, 欧式距离
* t Y$ A: A& E( t/ C- cEvent, 事件
+ ]! H# r# R9 Z* ?Event, 事件; q* T0 `) s! \
Exceptional data point, 异常数据点2 Y0 a3 C$ v; [: Y& c2 p5 j/ v6 u
Expectation plane, 期望平面
0 D2 B/ F4 T% d8 e+ E* IExpectation surface, 期望曲面 I0 I0 C& z" k J7 u4 x; B
Expected values, 期望值, M; ^0 l" J/ I7 C! A q+ x
Experiment, 实验
' G1 ^* ^1 U* Z( |- `' _Experimental sampling, 试验抽样" L y: Y& n$ I1 [0 o) g( l1 e. |
Experimental unit, 试验单位! [. _5 }; M$ ~) z: E2 U7 ?& @( S
Explanatory variable, 说明变量
6 p1 {( k p: Q- Y {2 Q: ZExploratory data analysis, 探索性数据分析
1 F- ?% T) X7 zExplore Summarize, 探索-摘要6 k- y( i- Q5 B1 j3 A) S2 s
Exponential curve, 指数曲线4 P, A9 z j, |& l9 I" T' q0 N5 H
Exponential growth, 指数式增长) ]# t% C8 n3 F
EXSMOOTH, 指数平滑方法 6 X" ~5 ?: { _4 ?- _6 C
Extended fit, 扩充拟合) @3 w1 B1 H( X! j
Extra parameter, 附加参数; k! ]5 _; Q# r' Y/ d2 o
Extrapolation, 外推法% ~/ g/ T. x# o/ _, Y0 u4 S& o
Extreme observation, 末端观测值
0 g$ w3 B2 v- {. I% ?Extremes, 极端值/极值! [! o6 T y* C/ b" m1 e" ~* V' ^
F distribution, F分布
. g7 ]# F; e3 [2 [% GF test, F检验
0 e3 Q1 v( e5 t6 b0 v. sFactor, 因素/因子
0 G+ y* c3 k) \7 KFactor analysis, 因子分析0 p+ s7 o& ~9 K |, |2 m
Factor Analysis, 因子分析3 V7 U$ D) ^" i1 `/ o
Factor score, 因子得分 / @' [' ^: g( U1 W
Factorial, 阶乘5 \- g9 }" x5 a: { v8 `% }
Factorial design, 析因试验设计
7 u$ z3 w8 l- a4 R, bFalse negative, 假阴性
7 X) B' {2 |- g6 d$ Y7 pFalse negative error, 假阴性错误6 i$ o& y4 u7 Q
Family of distributions, 分布族
1 v4 t3 p+ ~; C: X P9 vFamily of estimators, 估计量族: }5 R2 ~# ]% r$ F6 d; A$ \
Fanning, 扇面( R: y1 g; |: w% W# i
Fatality rate, 病死率
1 u2 p7 S, [' j9 U$ QField investigation, 现场调查
/ [3 c5 f$ `) bField survey, 现场调查# l' `7 B$ \* S9 T
Finite population, 有限总体
% B% \4 i9 s- e4 LFinite-sample, 有限样本
7 |, o! A1 G8 w0 V) o. YFirst derivative, 一阶导数
5 e2 S: ]6 E3 @- s, X7 VFirst principal component, 第一主成分) t5 f! A1 J9 u0 a2 z* S
First quartile, 第一四分位数
! u' d. a0 f! W9 K) l! {/ F yFisher information, 费雪信息量* @! T1 r( }9 r7 |0 M7 r
Fitted value, 拟合值
* Z. y/ [) _# J3 U$ E @% eFitting a curve, 曲线拟合! t9 h: u1 @% z9 k9 R1 i* P8 _8 x9 _
Fixed base, 定基9 P8 d' G+ k: m% Q8 i; ?) f9 P
Fluctuation, 随机起伏. l$ z* ]7 C% s8 y8 f$ S, n: S6 f
Forecast, 预测* z* z6 Y9 A3 B! H1 I. S% G% B+ p# |
Four fold table, 四格表( ]( I& x9 k# I; ]' C& o
Fourth, 四分点
# {' r8 x/ O4 e' G" g. wFraction blow, 左侧比率
o6 x' D+ j% b7 JFractional error, 相对误差3 r B# c' R" D8 ?% e6 O5 n: w' j
Frequency, 频率
3 J' C& M* a6 m1 CFrequency polygon, 频数多边图; H3 k: ]7 k/ X a Z% J' R
Frontier point, 界限点2 p! N1 q: ~0 w* C h; T# E, l c; Z
Function relationship, 泛函关系5 P4 `; i% u4 h
Gamma distribution, 伽玛分布9 I& t( T4 Z: U7 s2 Y0 }4 ?6 E2 j
Gauss increment, 高斯增量
s/ ^5 I! I5 `Gaussian distribution, 高斯分布/正态分布- V0 o, s+ }7 N4 m* e u9 H& _
Gauss-Newton increment, 高斯-牛顿增量& Z, A u) }& Y6 A/ l' t
General census, 全面普查2 V2 I8 r1 O) i/ `! y
GENLOG (Generalized liner models), 广义线性模型
8 t' j5 q8 k' ]Geometric mean, 几何平均数
6 M% O* r( @) d! ~0 j2 L: B) O# ?4 vGini's mean difference, 基尼均差6 J) s4 {! [& t" l
GLM (General liner models), 一般线性模型
" s7 {, T/ r' y, r5 |" `0 n# NGoodness of fit, 拟和优度/配合度
, n( X$ P) S2 X" F% T4 sGradient of determinant, 行列式的梯度* r+ v) z. O5 |- _, _8 o
Graeco-Latin square, 希腊拉丁方/ E$ b& H1 {( a6 [1 a
Grand mean, 总均值
u" e0 k, V3 A* N" O& I5 x1 IGross errors, 重大错误6 S( |4 O1 i1 y6 u! X8 }
Gross-error sensitivity, 大错敏感度1 t4 ~" s1 `! H1 t
Group averages, 分组平均! s. j L4 @4 j5 ^* c
Grouped data, 分组资料
9 }; Q# w; H6 l9 E, x+ eGuessed mean, 假定平均数" L- M% D0 c7 D0 v: L
Half-life, 半衰期
7 M4 x- V- n3 G: U$ W- B& mHampel M-estimators, 汉佩尔M估计量
1 S0 B# e# e+ I$ yHappenstance, 偶然事件7 V" T! g2 J% H
Harmonic mean, 调和均数
" d4 w( e& {+ d) F3 H! F- KHazard function, 风险均数
i2 ?. s1 Y% t" T8 Y4 D2 xHazard rate, 风险率
- T+ m* c9 ^" G) G/ I5 j/ a# wHeading, 标目 ) `9 J9 w6 `! L5 D- }. U
Heavy-tailed distribution, 重尾分布0 a1 h0 v9 H5 Q+ y$ s
Hessian array, 海森立体阵
9 T* ]2 U: o3 T- \8 u0 oHeterogeneity, 不同质
7 v4 R$ o8 d8 O) _Heterogeneity of variance, 方差不齐
( c/ t. P2 h m$ L; t0 DHierarchical classification, 组内分组
7 p2 r# X* E% VHierarchical clustering method, 系统聚类法
% G6 ] C2 V5 J$ JHigh-leverage point, 高杠杆率点
) D$ i& ~5 {" z: ~+ F& QHILOGLINEAR, 多维列联表的层次对数线性模型+ c% k% M2 D. Y0 P" n
Hinge, 折叶点
; S' M8 ^6 h$ z/ n; E; ~3 _Histogram, 直方图
, _" r: } L: E Q! D' N) qHistorical cohort study, 历史性队列研究
0 V* D8 g: c) v( q3 ^Holes, 空洞
4 N- M8 q4 t4 C9 w0 z M+ VHOMALS, 多重响应分析* l" G& e D4 ^* w; Y: a
Homogeneity of variance, 方差齐性
q9 D9 X) o" m# EHomogeneity test, 齐性检验* I8 z/ i8 S' L f; I
Huber M-estimators, 休伯M估计量
- N7 x3 D% y: {6 {Hyperbola, 双曲线
, D; G: a3 @, d) ^Hypothesis testing, 假设检验
! D- v3 E) I4 C5 uHypothetical universe, 假设总体8 |- G' o, i; j" M: {
Impossible event, 不可能事件
+ Z1 u/ u1 ^1 s" |) _. {Independence, 独立性
- I. L! E0 W' \7 c; N y6 qIndependent variable, 自变量
% f% d4 W! `+ mIndex, 指标/指数
) e, r+ I' g& X5 M8 I7 {3 iIndirect standardization, 间接标准化法
) n- Z4 Z& m# ]7 r2 UIndividual, 个体
2 o& T3 C7 T$ `% Z5 CInference band, 推断带* I% Z( F# A% [% N! _+ s% w: ^: x) L
Infinite population, 无限总体' Y+ Y. Z% x2 o
Infinitely great, 无穷大
1 Y2 p9 R- `) k$ Q9 `! J9 GInfinitely small, 无穷小
+ e% o4 U" j' r2 L* _Influence curve, 影响曲线 H! s2 S% \7 x
Information capacity, 信息容量* D' i9 F) Z0 D; O* u- X
Initial condition, 初始条件
2 X" y9 v6 l) E6 N: T% J5 W, S% ]Initial estimate, 初始估计值' Z. n+ \ V1 U! L% [! b% G
Initial level, 最初水平
8 l1 y# ]2 [. K, g" D; rInteraction, 交互作用3 }9 E' l+ m& Z5 O' D
Interaction terms, 交互作用项
2 Z( s5 y. c/ N1 O8 m: `Intercept, 截距
) e, m/ k. O) }7 z3 T/ u% bInterpolation, 内插法
5 _# }* i( H! ?6 @2 mInterquartile range, 四分位距: K7 E1 }7 m' s; ? ]2 o$ r; a
Interval estimation, 区间估计
K' k, T& T5 q0 ]! x# n& E, VIntervals of equal probability, 等概率区间
3 [! z# ^ ?0 c# mIntrinsic curvature, 固有曲率0 M% }- }3 w* {
Invariance, 不变性- x0 O$ x# A8 A- s# r; B
Inverse matrix, 逆矩阵
+ u6 _* |% _! i2 M0 C4 X1 |* PInverse probability, 逆概率
& e8 X; I; E& B1 x8 z4 M( `Inverse sine transformation, 反正弦变换
9 c, K g- ~ V) m+ B* Z: |Iteration, 迭代
1 O/ I1 F# V1 |/ Y5 d6 ZJacobian determinant, 雅可比行列式
! g0 q+ m6 X& q/ gJoint distribution function, 分布函数' u9 O2 d1 c) T+ _# Z9 d/ L- q
Joint probability, 联合概率# c) ?) ~! N. E; a q9 Z/ a
Joint probability distribution, 联合概率分布 p; g6 ~) a- N6 Y8 s7 _
K means method, 逐步聚类法
) q4 p: b; f+ V( {' s) D# {0 h9 p7 CKaplan-Meier, 评估事件的时间长度 0 K. B4 X* w; V3 t) d, J
Kaplan-Merier chart, Kaplan-Merier图( `0 |. E6 B& F5 j3 S' j2 ^5 P
Kendall's rank correlation, Kendall等级相关
: B! A+ H& q) G! lKinetic, 动力学
5 g3 V; w: W# i! ~. E# b0 pKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
; T5 M- W; B& r+ I$ E, gKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
5 k% J: A& K$ n D5 y4 e7 eKurtosis, 峰度" s) d1 G, ]" u0 S6 Z4 ~. ]5 ?
Lack of fit, 失拟
& y9 ?- V* E2 @Ladder of powers, 幂阶梯
# i v2 \3 E) _. \* e( tLag, 滞后
7 E r" d% h8 ~0 @! ULarge sample, 大样本: F3 t9 U6 I0 [. g: @; R% D
Large sample test, 大样本检验9 q0 ^* B' A; |% r/ w, j" O6 \
Latin square, 拉丁方, Q* H8 H" [* A. A% q3 {7 p9 }
Latin square design, 拉丁方设计
@+ z1 _8 Z* N4 u/ V. xLeakage, 泄漏
1 Z+ V7 K& J% V7 ^9 ?5 ?Least favorable configuration, 最不利构形
" g/ p- l: Q+ C4 K+ nLeast favorable distribution, 最不利分布$ X1 b0 S" ^! [$ A) z) G& r0 h, e+ H$ |
Least significant difference, 最小显著差法; v, [+ A( Y3 \4 q' q$ |) i" H
Least square method, 最小二乘法
$ d3 k$ K/ N: b1 r5 ILeast-absolute-residuals estimates, 最小绝对残差估计
' h {5 Q3 ]* |! ]8 WLeast-absolute-residuals fit, 最小绝对残差拟合
& s( k" L+ M z6 I# `8 R2 K- WLeast-absolute-residuals line, 最小绝对残差线. _2 {) s$ a8 d" w
Legend, 图例) _/ e, T+ Z6 \- k' j3 Z/ \
L-estimator, L估计量
5 Q' ^+ J. p* e0 q) C5 vL-estimator of location, 位置L估计量
% L4 C+ Z' L* CL-estimator of scale, 尺度L估计量
* Y# q# Q% }! U9 S; oLevel, 水平
% ]. x1 A/ f, C' E' A6 d' \Life expectance, 预期期望寿命
1 O$ s- h, F& m/ m% CLife table, 寿命表0 `; f! z% O) B
Life table method, 生命表法
2 m6 R5 k$ j5 K6 D% GLight-tailed distribution, 轻尾分布9 J, U9 {& U, B4 q q
Likelihood function, 似然函数
5 H4 U9 L* a# V, n) OLikelihood ratio, 似然比7 ]1 I5 f; P" S. N3 A- R* z
line graph, 线图
" _( T) u/ T% ^Linear correlation, 直线相关& m0 f' @" ^4 L# S- }) C* Q' J
Linear equation, 线性方程
- ^) c% W& Z* M) v) \9 U8 zLinear programming, 线性规划
) j+ p/ y* [! _* m# OLinear regression, 直线回归
3 V% m$ H, o+ \- t. e- t! }+ ?' Z/ ` sLinear Regression, 线性回归" I* w! o9 ~! N: K6 r0 c
Linear trend, 线性趋势
, D+ z& ]1 ]& T8 v( kLoading, 载荷
2 b$ {- K9 s& n5 ^# m& L* U7 u2 d/ iLocation and scale equivariance, 位置尺度同变性/ B6 m B R; a4 F; x0 E+ ^
Location equivariance, 位置同变性" e, l1 s7 U u# F
Location invariance, 位置不变性! B7 P: W% G4 v2 T# G9 Q$ Y
Location scale family, 位置尺度族
$ U3 Y3 S) @, h f( `Log rank test, 时序检验 ( E2 c, p$ H& o0 T( s
Logarithmic curve, 对数曲线
( @! g1 `1 h% F$ `Logarithmic normal distribution, 对数正态分布
' Z0 d/ h8 I; @Logarithmic scale, 对数尺度
0 H- K( k! f v, }+ z% s( u% XLogarithmic transformation, 对数变换
" M8 O0 U: v1 y- WLogic check, 逻辑检查
% V- c5 g2 T+ c4 cLogistic distribution, 逻辑斯特分布
% H6 u: ~5 l1 fLogit transformation, Logit转换% a! i- M# e6 w0 f8 ~
LOGLINEAR, 多维列联表通用模型
2 X: Z& F" Q: @- ?- K; K; \3 {Lognormal distribution, 对数正态分布
- L# ~3 K' v4 b6 L$ dLost function, 损失函数
( ^3 V$ o" z6 b/ b0 r' e5 f& w* k6 kLow correlation, 低度相关
# Y/ w7 }0 V0 G; T" Q7 U6 W0 GLower limit, 下限4 w( b6 L- k- Y( G$ x
Lowest-attained variance, 最小可达方差
" f" o1 M% ?/ v) ^9 u) x* ULSD, 最小显著差法的简称- k ?1 Z8 }) l. v- ^8 G& P, G
Lurking variable, 潜在变量
4 l" i" b& w; H! g& [' GMain effect, 主效应
# _' S" {% n3 a3 ~( x. VMajor heading, 主辞标目
& h" ^* h$ H/ V CMarginal density function, 边缘密度函数' w0 D6 q/ m6 k, Y7 x
Marginal probability, 边缘概率( g+ ~" G: Z% g% q5 S1 i4 a' [
Marginal probability distribution, 边缘概率分布# }* @& k4 B0 Z, T1 o# N
Matched data, 配对资料" g! G2 N2 R* J9 _- r6 V2 \
Matched distribution, 匹配过分布$ P( q/ ?$ G) P7 y5 i
Matching of distribution, 分布的匹配# x% Z. l) j: g7 j) ^
Matching of transformation, 变换的匹配
( `/ [1 O+ [9 J& D1 U1 RMathematical expectation, 数学期望
# ^1 f$ Q3 A0 d+ `* K: _; I- mMathematical model, 数学模型
: b& T; p# b) a: \# Z* q4 xMaximum L-estimator, 极大极小L 估计量
4 F# M" [( r6 \+ v! DMaximum likelihood method, 最大似然法
' g' M2 C6 s; o: j0 k% M/ TMean, 均数
8 }7 ? {9 [8 n, \2 QMean squares between groups, 组间均方
' T' [8 S, J! x2 c( C1 UMean squares within group, 组内均方
* p1 c+ b* l2 {' Q& _4 fMeans (Compare means), 均值-均值比较- A; o# h7 i' \3 R, t
Median, 中位数: U; m( z7 g' G
Median effective dose, 半数效量
' y1 c- a9 X# Y/ A7 CMedian lethal dose, 半数致死量' y2 h& ~0 i* I7 O* B
Median polish, 中位数平滑6 C( Y2 {0 G+ g# S( v+ o
Median test, 中位数检验
* _; X, Z# ^' s6 M* ^( b2 R) \Minimal sufficient statistic, 最小充分统计量
# F, `1 i& h: N- J3 cMinimum distance estimation, 最小距离估计( W# A4 c R2 }
Minimum effective dose, 最小有效量
: ]7 | v# O0 P; D9 h+ `1 ^Minimum lethal dose, 最小致死量
) v& z) O. S6 B$ @$ n! }, EMinimum variance estimator, 最小方差估计量, M& J' Y; i( j# w7 |
MINITAB, 统计软件包2 n- I# }+ n& h
Minor heading, 宾词标目2 Z4 w2 D( U: {3 X1 ]& ~) l
Missing data, 缺失值/ ^4 O7 n: Q. Q5 y+ k" j
Model specification, 模型的确定3 s0 |0 V5 K: ^+ x; V$ h
Modeling Statistics , 模型统计
/ z5 e$ F3 e- UModels for outliers, 离群值模型& d7 w$ V [* D# z1 d
Modifying the model, 模型的修正
/ M* c* b- H# f+ pModulus of continuity, 连续性模8 f5 Y1 K1 g, f7 o
Morbidity, 发病率
2 G+ M" y% |6 [Most favorable configuration, 最有利构形
& s$ o. @( `. H8 zMultidimensional Scaling (ASCAL), 多维尺度/多维标度
2 B# c& h1 K4 L2 M/ UMultinomial Logistic Regression , 多项逻辑斯蒂回归: U% n( I# d1 p+ i
Multiple comparison, 多重比较* P7 X/ W+ Y. Y, f M5 G2 l
Multiple correlation , 复相关3 ]: M. W9 x4 C3 ^0 l
Multiple covariance, 多元协方差
; m- ?+ r1 P7 S: ]2 J1 D9 w3 s8 mMultiple linear regression, 多元线性回归
- H9 Z: O: D* O4 m5 H1 B, D2 A' f* kMultiple response , 多重选项. U1 `# K" u. U# R1 M* L1 a
Multiple solutions, 多解
8 ^. Q$ ]( h& H( DMultiplication theorem, 乘法定理% B8 b2 R+ g" i! N( B; n" ^
Multiresponse, 多元响应# U; l; b3 R- e9 N [2 b ^6 W/ q
Multi-stage sampling, 多阶段抽样- R% i2 Q: L$ d8 k! O) k' L, b" O
Multivariate T distribution, 多元T分布
( d4 h. h1 k$ K1 HMutual exclusive, 互不相容
+ k2 U- W9 S3 A$ C; @Mutual independence, 互相独立 m) l2 c" n; h$ p, U
Natural boundary, 自然边界
7 ]" p! ~% J& j5 N% H" VNatural dead, 自然死亡3 ~+ V: v9 [5 n& r+ X
Natural zero, 自然零
* ^5 P6 Z0 R) o1 S+ ?% u, y. WNegative correlation, 负相关! N" ~( K7 ]$ V% C; H% u: V
Negative linear correlation, 负线性相关
$ g" [: `& r; oNegatively skewed, 负偏8 U' |/ s' z8 ^, I4 O
Newman-Keuls method, q检验
7 f% f3 \& X* _) K* w: i- L! p$ WNK method, q检验+ q* m' ]" t' z5 A! a
No statistical significance, 无统计意义
! d7 |* s0 Y. b ENominal variable, 名义变量
: z, b( V0 K: @" e. @Nonconstancy of variability, 变异的非定常性 F+ j' l0 w* l0 R* w
Nonlinear regression, 非线性相关
* Y& ^3 A6 W% b5 NNonparametric statistics, 非参数统计
8 x F$ X- J( `$ l7 S N1 xNonparametric test, 非参数检验3 W' `3 ~; Z( I( o7 x1 b! k! d1 e
Nonparametric tests, 非参数检验8 C2 D f, U! z2 e
Normal deviate, 正态离差9 {) W$ M! j- t& x: s6 `
Normal distribution, 正态分布2 [2 X) ^- B4 D6 I6 w
Normal equation, 正规方程组4 R0 F% P) x6 ~) S c
Normal ranges, 正常范围
2 `# \8 i. \5 m. T' KNormal value, 正常值" t1 u. d6 o% f' Y+ Q( d! d
Nuisance parameter, 多余参数/讨厌参数
1 L8 |9 {( ]- u8 j NNull hypothesis, 无效假设 $ F2 B! L) L, f0 z# x6 t
Numerical variable, 数值变量3 V( Q; J& r' C% }6 y
Objective function, 目标函数( z7 L: b' s, q1 R5 F
Observation unit, 观察单位
6 t" N6 c" X' T+ L: v* CObserved value, 观察值
* v" ]. w' ~9 p$ R) _( Z% KOne sided test, 单侧检验
; [, J* d& O1 OOne-way analysis of variance, 单因素方差分析
' _$ h9 l7 o- G0 d3 x a% o- `Oneway ANOVA , 单因素方差分析& I6 u J: v2 ? }1 _
Open sequential trial, 开放型序贯设计% E6 I* l7 F, X' E4 O
Optrim, 优切尾( @* H- q; s+ B% y2 k! x$ @
Optrim efficiency, 优切尾效率0 Y9 B& [$ b' `6 T# Q4 C" ?' A
Order statistics, 顺序统计量
# f4 b, k' Y Q$ @9 _ sOrdered categories, 有序分类
) K2 K& ?, h) j8 [1 oOrdinal logistic regression , 序数逻辑斯蒂回归7 D) K+ |8 y& w( f: X @/ |! K
Ordinal variable, 有序变量
# `# r7 _9 v6 h5 j* V4 G K! A' ~Orthogonal basis, 正交基( O4 [# Z! o3 D
Orthogonal design, 正交试验设计; l1 v, H/ R% H0 f% W
Orthogonality conditions, 正交条件7 m; u- Q# `6 `5 Q" v v: Y
ORTHOPLAN, 正交设计 + q2 Z7 @ P; ]8 f6 w n
Outlier cutoffs, 离群值截断点/ y O; ?# l- P8 g; E
Outliers, 极端值2 H0 j! F n7 z. T0 g H+ t
OVERALS , 多组变量的非线性正规相关 4 @5 ^; C% B) ?7 S8 ?3 R9 @
Overshoot, 迭代过度
. Q! e0 Z, k8 p. WPaired design, 配对设计6 ?. ^6 D' Q7 ~1 |) s9 [$ A I7 p
Paired sample, 配对样本3 N% J; \( ]- `" G4 C6 A
Pairwise slopes, 成对斜率& \% ]3 X y _* [$ n2 W! `
Parabola, 抛物线
7 L$ o* }5 ~# O5 b% h0 G( aParallel tests, 平行试验4 X: R0 v4 d( E; S
Parameter, 参数$ F% J" f* M0 y7 v1 @) R* _( U, p
Parametric statistics, 参数统计/ ?2 Q! m* T5 @; T) M2 k( K! y( ^
Parametric test, 参数检验
4 M& }5 X- I4 ]" a) j }Partial correlation, 偏相关7 b* p6 w3 Y8 m
Partial regression, 偏回归
$ U- o0 R' A+ @% U* W' rPartial sorting, 偏排序& v6 G9 z- @4 q3 b) E1 B
Partials residuals, 偏残差, }% f. u' p, {1 t' D
Pattern, 模式$ @ K1 f" e1 i( _/ \
Pearson curves, 皮尔逊曲线4 m* P4 G1 z2 T/ I# N1 Y& Q
Peeling, 退层
% c; x% G; |0 g% Z8 @Percent bar graph, 百分条形图
4 E' C- t( y* M" P& l. uPercentage, 百分比) z6 ~6 r, d, _7 N! W! G$ f* k6 \5 r
Percentile, 百分位数: S. u/ Q% H9 x: ?, n1 v
Percentile curves, 百分位曲线, a+ t/ L1 k8 O' w y0 r' I/ O) M
Periodicity, 周期性% N' L' Y# ^: ]2 x) J! }/ H
Permutation, 排列6 X) g! c$ `3 N: f3 N" y
P-estimator, P估计量
. N" z% ?6 J0 [$ I f" P0 |Pie graph, 饼图
4 G0 f# n( w% `6 d( WPitman estimator, 皮特曼估计量
6 _: G7 R3 z9 ?: |' S( IPivot, 枢轴量
0 i( g4 r& E" D9 N5 s* E ~Planar, 平坦
5 m& q5 U, j- T0 _8 t" PPlanar assumption, 平面的假设
. C v! f! g+ K+ N1 _PLANCARDS, 生成试验的计划卡
0 G6 ~3 P8 U: }4 Q, f: |2 a0 Z, aPoint estimation, 点估计( v. c% |: `, c( v
Poisson distribution, 泊松分布0 C( k/ E8 o7 {8 W0 `. L% j6 W
Polishing, 平滑7 T9 b3 t2 d1 L3 F- w5 d
Polled standard deviation, 合并标准差
9 s ^2 @+ O5 j( g0 @Polled variance, 合并方差
9 x, d( R; A" ^* p* APolygon, 多边图
+ a& N. _ `7 }4 QPolynomial, 多项式
: x3 ~- U c7 Q Y. Y: ]) qPolynomial curve, 多项式曲线/ g; \( B2 x* u' ~4 _/ Z
Population, 总体! D. H% [$ P& V% Y7 W
Population attributable risk, 人群归因危险度
8 m2 E" @5 w5 {, ]' SPositive correlation, 正相关
5 o, r6 \8 w RPositively skewed, 正偏
7 f' [, l: q8 P8 I. b: MPosterior distribution, 后验分布% U% r- s3 }" W3 {" _; s
Power of a test, 检验效能' i6 K+ z# f6 g& I
Precision, 精密度
$ h2 a* x- }1 i" J! |$ e" M7 ePredicted value, 预测值 M. i! ?$ Y/ }/ R, U
Preliminary analysis, 预备性分析
7 I# n1 H. @8 }" q1 f) M! uPrincipal component analysis, 主成分分析
8 X6 n9 ^( x1 Z2 `Prior distribution, 先验分布
6 q W F7 f a/ |5 ?Prior probability, 先验概率
; P4 U; R8 l- m! CProbabilistic model, 概率模型
: D3 G! h" w4 Fprobability, 概率! z( s3 B4 L8 i4 B I
Probability density, 概率密度5 h" |4 k7 `" e. b
Product moment, 乘积矩/协方差
" c1 s+ R! g) FProfile trace, 截面迹图
6 V0 \6 o6 B$ ^. MProportion, 比/构成比
H" h' H; m& _0 PProportion allocation in stratified random sampling, 按比例分层随机抽样 t5 w3 X9 A, I$ d- X( I/ V' v$ ^. }
Proportionate, 成比例" X, P' d" \$ Q4 S0 v/ b
Proportionate sub-class numbers, 成比例次级组含量
9 y. a1 z. i4 _5 V3 B/ wProspective study, 前瞻性调查" e# i2 h; |3 w p
Proximities, 亲近性
1 W( [3 p5 k- @0 `/ m/ [% }$ s' n/ oPseudo F test, 近似F检验
. M; Q9 S% F7 b: V; I8 G8 rPseudo model, 近似模型+ W/ O( D$ j/ G$ o' x( _
Pseudosigma, 伪标准差/ R, T0 R5 p- [% ^' t3 {: r) k$ c5 _
Purposive sampling, 有目的抽样/ N f2 I. J0 F3 g" }3 m# S
QR decomposition, QR分解* X9 G# Y# ^+ w
Quadratic approximation, 二次近似
% \% q4 Q! F; A8 V( L2 p3 d' DQualitative classification, 属性分类- i. ~, C2 t" L1 j- h
Qualitative method, 定性方法. V8 T& V: r, I) H2 }
Quantile-quantile plot, 分位数-分位数图/Q-Q图, q8 G1 \0 ?, B2 b2 u6 V2 ?
Quantitative analysis, 定量分析9 [4 e C, R# n, n
Quartile, 四分位数
) }9 P" [6 s; a* A, `Quick Cluster, 快速聚类
3 P4 N; b! e2 U7 |: w0 Y' |3 RRadix sort, 基数排序
0 W! r* B x# M4 O5 [Random allocation, 随机化分组2 s! M; N* \. S/ u- h3 p1 a
Random blocks design, 随机区组设计
' T" ?$ q- F8 T7 r4 w, Q$ nRandom event, 随机事件
1 J; P; z/ Z; q8 y3 G$ d$ gRandomization, 随机化( F, U& X$ {# n0 @
Range, 极差/全距" z: R, i% ~+ E1 ?9 A
Rank correlation, 等级相关* ~9 n; i W# a
Rank sum test, 秩和检验
{" g# _* b& h2 I& L9 g! ARank test, 秩检验, N6 U2 x; `& i! j! Q. `8 t
Ranked data, 等级资料' k7 s' q4 R- i$ Q) {- V8 g
Rate, 比率; X4 f/ q) m2 _' E
Ratio, 比例. I, H2 h: U) j- G2 ~" J1 E, n" P2 p
Raw data, 原始资料5 e9 e9 x f+ y i
Raw residual, 原始残差
) s3 n/ n6 P, H7 H; P) LRayleigh's test, 雷氏检验
% u3 S7 { ]' B" M* W* u0 yRayleigh's Z, 雷氏Z值
" q" v$ C8 b# L$ O5 uReciprocal, 倒数' y% U- P# @' _1 j* ~
Reciprocal transformation, 倒数变换) G$ N* Z, x2 b: R8 |# I$ l* m6 V& k
Recording, 记录( s, a6 ^; V$ p2 Q* j( `8 K
Redescending estimators, 回降估计量7 X7 d w5 g2 b7 ]& j
Reducing dimensions, 降维
/ |2 ^! h" J: ^( ]4 c4 n4 X1 A9 fRe-expression, 重新表达
2 d) s2 }# M- e# O. ]1 j& CReference set, 标准组
% z2 j' ~" ?# h/ J5 [Region of acceptance, 接受域" S, o, _7 l2 I6 A0 {% ]) `
Regression coefficient, 回归系数/ o( ~ w1 V4 w' _" ^
Regression sum of square, 回归平方和
1 g6 y2 L2 w, D6 F/ LRejection point, 拒绝点1 |' r1 V8 S# ]; f4 O
Relative dispersion, 相对离散度+ x! r E U3 A2 W
Relative number, 相对数
4 M% I0 y: {( l' `/ FReliability, 可靠性
5 a& ^! e+ ]* U! }% i1 _( W5 nReparametrization, 重新设置参数+ Y5 x: h2 N3 l( {( I! ~
Replication, 重复& J( U# {9 g; Z. G1 J* j
Report Summaries, 报告摘要
. ~# r n& K. W7 ~3 x$ N2 cResidual sum of square, 剩余平方和: O# }/ }. o# e
Resistance, 耐抗性
4 d/ E6 _3 k g3 x! ~0 T" @, bResistant line, 耐抗线5 p. M+ m2 a% ~
Resistant technique, 耐抗技术- ]' \4 o4 d- r" c, ?9 c8 M: H
R-estimator of location, 位置R估计量+ c$ a9 g2 o$ a5 P0 N8 T5 J
R-estimator of scale, 尺度R估计量; h5 k( Z- x% q$ ^
Retrospective study, 回顾性调查
y) p9 j8 _$ y& D- |Ridge trace, 岭迹; Y+ C) W* I: p7 p* V0 w& h1 ]6 y
Ridit analysis, Ridit分析
# F7 t8 u* q+ h+ n$ @Rotation, 旋转3 t9 S& a8 h4 a8 d) r' w. H$ P
Rounding, 舍入3 ~1 i) }6 m3 }
Row, 行: K! p7 S9 M" t: k. q
Row effects, 行效应; H2 _( Q0 d, f; P' r, c2 s8 W) X
Row factor, 行因素
: N, @' z: n |+ I( oRXC table, RXC表
3 V; @( C+ @0 O3 @' }Sample, 样本3 e3 b1 A: O' u W) }' N& k+ n
Sample regression coefficient, 样本回归系数2 {$ m& y" I& C6 g1 r; z
Sample size, 样本量
9 r- j9 T# j; x. K- {4 ?Sample standard deviation, 样本标准差
' R, ~; j, C( `$ NSampling error, 抽样误差1 }0 F* x* V7 T; |8 ~- i; k! A
SAS(Statistical analysis system ), SAS统计软件包. ~) o0 W& s- i* B% {3 ~ }
Scale, 尺度/量表
/ \, |' Y. A/ j& r0 T) e0 [- WScatter diagram, 散点图4 K" q) O7 R2 K' d
Schematic plot, 示意图/简图
4 n: Y, ], g( G2 {( N/ ]6 T+ jScore test, 计分检验
1 r( D, Y1 U. ^& ~ c2 a; ZScreening, 筛检
# c$ U+ A8 L2 Y3 _4 q( ASEASON, 季节分析
6 {* f6 q# p) g. HSecond derivative, 二阶导数
# ~+ r8 X% E! Z3 LSecond principal component, 第二主成分8 M3 v0 D6 S( G& x( p/ {. @3 U
SEM (Structural equation modeling), 结构化方程模型
( P) {/ S, v% HSemi-logarithmic graph, 半对数图
0 N4 m$ B( f5 I. m' K1 P2 SSemi-logarithmic paper, 半对数格纸
" b$ q+ P, t2 ?Sensitivity curve, 敏感度曲线! b# h5 c6 r/ q
Sequential analysis, 贯序分析
$ c2 a6 M" M0 [1 P- ]Sequential data set, 顺序数据集3 c) ^9 W& A' U T" U) |
Sequential design, 贯序设计' F" x) D% j2 J* E
Sequential method, 贯序法
) X9 _4 q5 i* KSequential test, 贯序检验法
4 O/ R. g/ \3 o6 U2 O! xSerial tests, 系列试验
% J! j3 n( a) W% n8 E- C- eShort-cut method, 简捷法
( P* G( K3 @" Y" O; u, C xSigmoid curve, S形曲线
& Q3 k" `5 M2 s" _# A7 QSign function, 正负号函数
5 y' z. o: K- r7 s. F# qSign test, 符号检验
* j; B: [# V6 K: ]1 n( JSigned rank, 符号秩% d( F# m9 s2 M5 {; {
Significance test, 显著性检验5 L2 C, r" m/ W. n: |
Significant figure, 有效数字0 T( l: E8 E: a5 h, T6 r5 b
Simple cluster sampling, 简单整群抽样
; g, ^9 W4 F7 g6 f7 V O8 }Simple correlation, 简单相关- G R# }. O5 v3 @
Simple random sampling, 简单随机抽样) |% L- m1 a! G2 G+ c! i! k4 T
Simple regression, 简单回归
* D3 Q3 W$ }/ V: w; G* g) x7 _simple table, 简单表
; o+ j' G t- N6 y, G! XSine estimator, 正弦估计量7 J6 u. n3 f! d0 m
Single-valued estimate, 单值估计% U8 A* x* h2 y( p, E' l
Singular matrix, 奇异矩阵, g- p' T( X$ l5 N$ M
Skewed distribution, 偏斜分布; [. e/ j4 K' b9 l% V( V. v
Skewness, 偏度
6 o+ k7 @+ S }* USlash distribution, 斜线分布
3 C/ K: U$ e6 Q4 n/ F- p4 {) aSlope, 斜率$ V" m# L; H% Q2 T
Smirnov test, 斯米尔诺夫检验
; t5 Y: c- f( g2 a9 lSource of variation, 变异来源' K! ^6 s; u+ {6 A- Q, @: f; P' G
Spearman rank correlation, 斯皮尔曼等级相关' p3 k( `* O& x( y* ]
Specific factor, 特殊因子
2 `4 T5 W# } d) D: ] i! h( [3 _1 s+ _Specific factor variance, 特殊因子方差
: X$ b( A3 |- h7 ?! a, J. r* YSpectra , 频谱6 z. {) K) g& T( f
Spherical distribution, 球型正态分布, ?9 w3 [6 v' g5 F2 y8 e
Spread, 展布
7 V' x% Y2 }4 E: p# f2 e" TSPSS(Statistical package for the social science), SPSS统计软件包
, P6 z: d5 Y! B- r9 ^Spurious correlation, 假性相关
3 D% |2 t. s: k$ v, l) J! KSquare root transformation, 平方根变换+ v9 X% r8 G6 Z, Q7 ?
Stabilizing variance, 稳定方差) ]$ i0 \& v, T/ A _+ ~4 s2 |
Standard deviation, 标准差, Q' d* g" e5 i3 B
Standard error, 标准误
8 T' V" S& D t" A+ v# v, gStandard error of difference, 差别的标准误
* x% `0 v) s# [( c1 E* NStandard error of estimate, 标准估计误差
$ V- ?9 O9 A# l* CStandard error of rate, 率的标准误
' n) ^- ~1 C' H5 A* S4 ]' dStandard normal distribution, 标准正态分布
+ C5 @$ h( p: W# zStandardization, 标准化- S: p7 S# l8 @1 u2 h* w
Starting value, 起始值
+ }; f3 Q+ }- Y6 C+ E; y5 uStatistic, 统计量
3 ^: l0 v, z! OStatistical control, 统计控制* n# \! u5 { b4 j" Q
Statistical graph, 统计图9 k* d% e- F; l1 } A0 N' h5 f! @9 h
Statistical inference, 统计推断
! M7 `+ x% R2 r( G! W5 k xStatistical table, 统计表
2 y! Y8 r0 e1 J/ QSteepest descent, 最速下降法
# T! E( a( [: n, a( _* u) fStem and leaf display, 茎叶图# m x& g8 e R7 {' ^
Step factor, 步长因子8 V# o! M/ B y8 C5 a$ V
Stepwise regression, 逐步回归
; Y @$ h. ~8 ^' o/ Q: DStorage, 存
6 o; g: F2 z T' \& S" `Strata, 层(复数)
% [1 P3 q8 w) |! T9 T8 j# v4 {$ MStratified sampling, 分层抽样( V, \8 Z2 c) y+ m% I
Stratified sampling, 分层抽样
2 k5 S1 W* e) V+ |- [* ^+ J jStrength, 强度
- N; v4 i: v$ R1 A, n0 A& c% S/ V( fStringency, 严密性" o* i" }; V5 v- d0 {1 w
Structural relationship, 结构关系
; E8 b4 Z& Z8 E. j# b$ C2 XStudentized residual, 学生化残差/t化残差
' k8 o) [$ H5 z/ P' L+ z1 HSub-class numbers, 次级组含量
/ ?/ W9 V. f) v) qSubdividing, 分割; G. V( |/ |" D a: ^# V
Sufficient statistic, 充分统计量
5 X9 t5 t/ i* J/ k3 w' }& OSum of products, 积和- L) i8 Y& l' q
Sum of squares, 离差平方和8 g0 [6 b( B( R" K" o$ K
Sum of squares about regression, 回归平方和! F; _" h, J+ i4 ^/ M( c' |
Sum of squares between groups, 组间平方和5 G& t# k9 H7 I
Sum of squares of partial regression, 偏回归平方和
0 s- W6 v) a3 N2 X3 X" w v+ mSure event, 必然事件8 B& Q4 ?7 \7 L& @
Survey, 调查* c p# g; Y, Y4 T# H4 ^
Survival, 生存分析; V1 l$ x! i( N2 _& G4 ~& @
Survival rate, 生存率
0 [8 z2 H/ Y/ L8 i% ^Suspended root gram, 悬吊根图) z4 N! ?4 h: q. J9 _, R" G
Symmetry, 对称
0 u' s7 W, }0 A( i# A! S1 \/ ESystematic error, 系统误差
1 v0 t! A0 f6 }3 lSystematic sampling, 系统抽样
$ v! v( \* \4 jTags, 标签
# C8 o9 X" e( dTail area, 尾部面积+ O0 ]; @3 Y6 I, K' D
Tail length, 尾长
- l" m% L& k. XTail weight, 尾重# O2 z5 {( v3 @9 r) ?$ X) W* n
Tangent line, 切线
3 S* o$ _& O4 b! aTarget distribution, 目标分布
9 j$ a4 O# L$ }+ [# fTaylor series, 泰勒级数
* z: j7 a4 Q H% K2 NTendency of dispersion, 离散趋势2 G3 h% C- u& E1 t3 ^7 Z
Testing of hypotheses, 假设检验8 ^, z& K$ K2 O9 P5 j
Theoretical frequency, 理论频数
1 v' e% t+ g$ [0 R7 ~- [% M6 KTime series, 时间序列; V# g/ I0 L* X/ y
Tolerance interval, 容忍区间
+ [0 ^# E- b$ ^. b+ `6 `1 ?Tolerance lower limit, 容忍下限- I2 `# Q! _3 ^& e' f m
Tolerance upper limit, 容忍上限: J5 c" w+ ^5 J/ d7 k/ @: A
Torsion, 扰率
* ~5 `( M+ b) g1 j3 w5 ]3 uTotal sum of square, 总平方和' Z: t; E' q5 }5 G7 _$ x x$ k$ X
Total variation, 总变异+ l8 |1 ~+ y4 }+ l o3 t, p
Transformation, 转换
, @7 } P2 m4 l( y$ xTreatment, 处理
. O* j7 H/ V0 D' G1 i& hTrend, 趋势
/ U y& y7 j4 J( eTrend of percentage, 百分比趋势
1 B1 U1 x6 j# V2 e4 r% p; VTrial, 试验' `5 p5 ]. k9 A
Trial and error method, 试错法' q; _4 O2 r, y) T. q4 g, ]
Tuning constant, 细调常数9 U$ l5 [) v8 d
Two sided test, 双向检验: B: C# |8 j. u( r/ u. o
Two-stage least squares, 二阶最小平方9 T/ V8 F8 O$ _" E% H
Two-stage sampling, 二阶段抽样3 Z* h$ i! l: E6 x% o( _: F
Two-tailed test, 双侧检验) r- s ?7 {" f/ y! P
Two-way analysis of variance, 双因素方差分析9 q' D5 i- P) y4 ]
Two-way table, 双向表3 Y; H- e8 I: j1 F2 S4 j
Type I error, 一类错误/α错误
, \* k- n3 U3 W( D+ X5 V# z9 sType II error, 二类错误/β错误
) X6 b. l( _1 T0 k6 i$ X s/ gUMVU, 方差一致最小无偏估计简称
1 B. a/ K: C, O$ D0 E- hUnbiased estimate, 无偏估计
+ n, n5 J) m$ o& _Unconstrained nonlinear regression , 无约束非线性回归6 `5 u- P: d* ^/ r, D
Unequal subclass number, 不等次级组含量
4 F7 c* b1 ?/ G$ n, Q CUngrouped data, 不分组资料/ d" x! I" G( D; q6 @9 u% B' I1 C
Uniform coordinate, 均匀坐标9 ]& A, f9 n. s* W1 g$ C l' [' f
Uniform distribution, 均匀分布0 R9 J6 t! I* e, h3 o. R
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计# F2 s* q6 ]3 N# P/ u/ T
Unit, 单元8 w4 }; z0 P5 f! i# R \+ }9 T
Unordered categories, 无序分类2 |9 X, c- ~9 q8 r B9 D3 L
Upper limit, 上限: `/ l, J: x, {/ O8 u
Upward rank, 升秩
% u! |" n' t) n ~3 @0 zVague concept, 模糊概念: J( z; u7 W8 u6 x) X$ L
Validity, 有效性. @! p! k, A% O/ O$ ^/ }3 G
VARCOMP (Variance component estimation), 方差元素估计
8 h. a7 y. k% d0 T4 X+ J( b, LVariability, 变异性1 n+ u, R7 Q! y9 P) X& n
Variable, 变量3 w5 s9 ^! z6 q" N. o2 k2 A6 w
Variance, 方差
1 V% l4 c0 `1 p' g+ @' e2 r0 ?Variation, 变异: |( D+ k3 N$ D* e- G; q
Varimax orthogonal rotation, 方差最大正交旋转
, z& j0 `2 |& @Volume of distribution, 容积 ?: J& g2 j9 d. M% r( j# I
W test, W检验 O3 C* F5 U/ q$ r) X' a) Y8 F$ _, D9 n
Weibull distribution, 威布尔分布
7 g( X& ~% c; E# D9 D' ZWeight, 权数
8 {; x/ ?* `- Q. OWeighted Chi-square test, 加权卡方检验/Cochran检验, Z+ V3 t3 @8 \% `/ ?
Weighted linear regression method, 加权直线回归
! R3 [ i% X# d% x' S- P3 V8 FWeighted mean, 加权平均数
2 Z9 x, |, \6 j2 Q3 Y2 R2 kWeighted mean square, 加权平均方差" U3 H0 S+ e! J$ c# N# R2 C
Weighted sum of square, 加权平方和
2 M+ e- A' M1 l; gWeighting coefficient, 权重系数: V3 F9 ?% @; X& {6 `
Weighting method, 加权法
' X6 ~# Y! s, t/ |W-estimation, W估计量
$ v3 x. A; V6 c+ qW-estimation of location, 位置W估计量
$ P7 T1 E9 `8 v1 oWidth, 宽度
+ Z- _2 u6 P' R' VWilcoxon paired test, 威斯康星配对法/配对符号秩和检验/ X) M- Z8 o* N- Z. C( ]
Wild point, 野点/狂点! z7 u: N- m0 q, R. A, Y
Wild value, 野值/狂值: y2 g3 _' m0 [) i9 K4 `
Winsorized mean, 缩尾均值3 y+ Q4 @ W2 B4 f6 M- W. M
Withdraw, 失访 0 d! \" G' ], G0 ?# s3 l& f( Q
Youden's index, 尤登指数
: d8 Z j/ H DZ test, Z检验
3 q9 Y! ?0 i+ [Zero correlation, 零相关
" i5 {' j4 x1 `# L# q4 \. }$ GZ-transformation, Z变换 |
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