|
|
Absolute deviation, 绝对离差2 Q& t K7 p% F2 q
Absolute number, 绝对数
% ?3 @. h8 M. C1 aAbsolute residuals, 绝对残差5 @2 G* y H5 l
Acceleration array, 加速度立体阵8 `2 {5 T0 g% b8 T# P w2 ?
Acceleration in an arbitrary direction, 任意方向上的加速度
# b! X( v C0 \# f% p; K" OAcceleration normal, 法向加速度$ \# d5 j8 M5 t5 [& M; _ x# W, ~
Acceleration space dimension, 加速度空间的维数8 ?3 L; w! o6 D Z4 n8 X- o7 y
Acceleration tangential, 切向加速度
4 J* q) }( j8 A; |Acceleration vector, 加速度向量
% n R. `( Y1 V0 u2 M4 gAcceptable hypothesis, 可接受假设
8 E: @* |+ F( ]5 [! N5 B3 u7 AAccumulation, 累积2 a- L6 r; [; Q; R, s) Q
Accuracy, 准确度
- l" A" H/ N: d! fActual frequency, 实际频数
$ G( O S& G: {0 \4 w/ d( k/ c" O- v' ZAdaptive estimator, 自适应估计量; j8 ?. J0 W V$ S9 N# A$ G
Addition, 相加
9 S! n( ^6 l4 N# n0 z: vAddition theorem, 加法定理( M4 k0 _5 P7 ]4 P
Additivity, 可加性/ t0 w! }- @; ~& p: O# u
Adjusted rate, 调整率
" a2 m2 w; e) h* zAdjusted value, 校正值8 n0 C1 A, \3 |; M% T% c2 N3 c# k7 o
Admissible error, 容许误差; J* Y3 m/ H1 T9 M3 Q4 g6 E" i
Aggregation, 聚集性9 @9 R9 R ^" U' C; h" U; F: O
Alternative hypothesis, 备择假设6 f2 T' f" [; I" g6 q+ {
Among groups, 组间
6 R7 p' M1 M6 Q5 eAmounts, 总量9 E3 F+ ~( k, S
Analysis of correlation, 相关分析
1 W2 G2 E+ D. ?Analysis of covariance, 协方差分析
+ v5 f( c7 b9 X' E* p1 h4 O; |Analysis of regression, 回归分析& H* m: i3 r& f1 ]: p8 k
Analysis of time series, 时间序列分析1 l1 p4 P3 _5 `$ [7 m
Analysis of variance, 方差分析5 l+ o4 s6 ?2 ^; b2 Y: O# i( }
Angular transformation, 角转换
! Q* g) I5 @$ S3 ^0 k& L" ]2 x* AANOVA (analysis of variance), 方差分析: W- j, j. s* _- W# _
ANOVA Models, 方差分析模型$ K6 o; e% \4 u3 h4 L
Arcing, 弧/弧旋2 S" i( t. Q: F* M( s+ P
Arcsine transformation, 反正弦变换+ o% I" m8 ]* Q+ x" o) ]
Area under the curve, 曲线面积
( R) Y; ^! _) f/ PAREG , 评估从一个时间点到下一个时间点回归相关时的误差 3 D7 Z7 P8 \" N7 l- ?
ARIMA, 季节和非季节性单变量模型的极大似然估计 , Q* v: C0 [# r5 z7 x
Arithmetic grid paper, 算术格纸
9 U; w$ p9 \' [# }9 UArithmetic mean, 算术平均数
! C9 {# B' A* `" PArrhenius relation, 艾恩尼斯关系4 B% g2 }: H2 ]; H5 G3 X
Assessing fit, 拟合的评估
9 a c0 S- v0 k- F9 YAssociative laws, 结合律
; N8 p3 T' k; ^! N" @$ OAsymmetric distribution, 非对称分布
+ b# {: X& v- ~2 `+ ^' M! aAsymptotic bias, 渐近偏倚# w( v0 X: W5 T( A$ Z o6 x8 U [. ^; [2 E
Asymptotic efficiency, 渐近效率
: i6 U1 `% R" G& A3 H( m% \) M2 }Asymptotic variance, 渐近方差, C; f0 I0 \8 ]8 Y. n4 t
Attributable risk, 归因危险度7 I& i: d1 G) I0 S" X5 t0 L
Attribute data, 属性资料$ i1 o1 H$ W# k% D
Attribution, 属性! Q& ~) J* b8 o- |9 t
Autocorrelation, 自相关9 {+ f0 A$ P) C$ K7 `
Autocorrelation of residuals, 残差的自相关
, f. h- K, b% _Average, 平均数
' h+ H+ W0 z6 L3 Z, rAverage confidence interval length, 平均置信区间长度' o: X5 g: U5 \* \5 d7 W
Average growth rate, 平均增长率
7 Y& f# ?0 _1 Y. O$ SBar chart, 条形图9 T/ x/ D* f+ m* y
Bar graph, 条形图
' s8 l W( t- C! @Base period, 基期' @+ e9 A* \- w& R; f. e* J
Bayes' theorem , Bayes定理7 ?4 f3 g% C" c5 t y* b. x
Bell-shaped curve, 钟形曲线9 r- w( K t! a4 y1 e& h0 H
Bernoulli distribution, 伯努力分布
4 y' u" w8 n3 U* n$ E5 q/ VBest-trim estimator, 最好切尾估计量
( ~0 T1 b: j7 m" X3 c! F; `5 fBias, 偏性6 A6 d, Y- M0 W8 p, u2 I
Binary logistic regression, 二元逻辑斯蒂回归
* ?. T7 ~ F0 _9 F' ABinomial distribution, 二项分布+ o* F( h! E9 d2 N& Y
Bisquare, 双平方
& z" I* o$ f, r, a1 ^- K) ^Bivariate Correlate, 二变量相关
4 I5 ~. @9 S( e. _8 ]Bivariate normal distribution, 双变量正态分布
* c! E* D J9 o0 WBivariate normal population, 双变量正态总体) [1 r: i" j( v
Biweight interval, 双权区间% t* l' K8 ~( {
Biweight M-estimator, 双权M估计量2 ~8 l; O N# _" e( n
Block, 区组/配伍组
9 q' U& e; w* n* J, m6 {% z+ mBMDP(Biomedical computer programs), BMDP统计软件包# E S. b+ N: V( j0 V
Boxplots, 箱线图/箱尾图- U5 q- @ R- {, C! f
Breakdown bound, 崩溃界/崩溃点; P- D. X' j# @9 J1 f5 X
Canonical correlation, 典型相关
" e. X1 L3 f- ]& z' O- CCaption, 纵标目' f5 \" `" r% H' [/ ?( E
Case-control study, 病例对照研究
% _( e$ U: L/ @* ?Categorical variable, 分类变量$ J8 s, ~4 e8 `9 a" @
Catenary, 悬链线' {3 \. J& ^& X. R% i0 f* ~# c
Cauchy distribution, 柯西分布/ T& r& o0 M. N! U( V
Cause-and-effect relationship, 因果关系
7 ` g4 E- V) k( z t& oCell, 单元; O' _# p T4 v0 h+ T
Censoring, 终检( O; ~! j, U% F$ i! j; t5 x
Center of symmetry, 对称中心
$ h, R3 D* l( H+ f! {Centering and scaling, 中心化和定标7 a x9 Z# v. L9 x9 I% ^
Central tendency, 集中趋势+ `5 e6 A5 o+ c
Central value, 中心值
6 w f5 q! h" z# `$ L' z, GCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测1 r' |0 ]. |/ T; ^+ l& m8 o- ? w
Chance, 机遇+ f- Z& v! ^- M* c; t
Chance error, 随机误差
2 v/ _- F9 }* |+ ~2 D3 MChance variable, 随机变量8 |' P! T/ @5 k
Characteristic equation, 特征方程' h' Y5 n+ O3 k
Characteristic root, 特征根
: O2 D% s8 P* z- |+ v1 Q: z" Q( ~Characteristic vector, 特征向量
" ^6 e4 g( Z1 [, OChebshev criterion of fit, 拟合的切比雪夫准则
/ k5 O; X: p/ q$ W( U) hChernoff faces, 切尔诺夫脸谱图
) m/ c' c1 F% E" J# jChi-square test, 卡方检验/χ2检验" k8 k6 p+ E) d; n3 W0 x- I4 ?
Choleskey decomposition, 乔洛斯基分解/ G$ P7 i, v# O( p- k
Circle chart, 圆图 : {% q' J. g7 ?/ l2 f
Class interval, 组距% k8 t: B2 h, P6 L4 R
Class mid-value, 组中值
6 T1 T$ s7 s* d$ i% Y; z9 LClass upper limit, 组上限
* o- K/ u! \4 m/ a* @2 MClassified variable, 分类变量
* u. I' H- g* M5 c8 xCluster analysis, 聚类分析
# Z9 M( T- D4 w- ~- X1 w) mCluster sampling, 整群抽样
" O0 X! [$ S- {# C' U' bCode, 代码
! X* Q }" E0 g6 e3 o- x* v1 zCoded data, 编码数据
# {/ Q) e; H7 GCoding, 编码% c( \" |; o! W7 D* O4 l1 _* g, s" f
Coefficient of contingency, 列联系数
. u: D8 [) v4 \" t! ~3 cCoefficient of determination, 决定系数
5 n; \# g2 |" K# }& {; T+ T) h9 ^Coefficient of multiple correlation, 多重相关系数
; @. n- c3 M7 i6 I. GCoefficient of partial correlation, 偏相关系数
) p0 w1 |& k7 d, J" x) _Coefficient of production-moment correlation, 积差相关系数
" {/ \2 m/ |# o7 o# }. TCoefficient of rank correlation, 等级相关系数0 I) t4 M/ a0 P
Coefficient of regression, 回归系数
D/ U6 s3 ^( q# B! ICoefficient of skewness, 偏度系数: J# ~& g6 A: S( w, j
Coefficient of variation, 变异系数
, u R* X4 s, o# HCohort study, 队列研究+ {8 J1 {9 n z
Column, 列9 B* A- [; |4 C6 s
Column effect, 列效应1 y- u$ n% E h- u9 J0 _
Column factor, 列因素
, H4 d8 z4 b- p6 F3 Z/ @2 UCombination pool, 合并
+ \$ {7 |: G) cCombinative table, 组合表. ~9 e8 s) _- n8 Y% U( k& O
Common factor, 共性因子
, G# N! \, M/ ? p. N1 I0 eCommon regression coefficient, 公共回归系数0 j. }* y, g0 h6 p! P% H
Common value, 共同值
! l6 G! g% \3 Y9 V% |Common variance, 公共方差
7 B- [8 m. T d% L( i |3 `' ^Common variation, 公共变异
# K2 C' ?* Y8 w5 p! t5 y% l: sCommunality variance, 共性方差
+ b# m' S# w1 sComparability, 可比性
- U: y3 K1 ` aComparison of bathes, 批比较
- m8 A: t" Q& \2 sComparison value, 比较值
. ~8 {6 J' B8 m- ?9 i' QCompartment model, 分部模型
8 b3 ~- C/ }% GCompassion, 伸缩
. ?; _* k6 q8 u9 YComplement of an event, 补事件' ?: V" Q0 d# j7 U7 A! t
Complete association, 完全正相关) j9 K7 v" r& W& O, \" U$ O7 s$ g
Complete dissociation, 完全不相关
7 `8 T. p- X# @+ ^Complete statistics, 完备统计量7 r3 e3 l0 x. g0 x
Completely randomized design, 完全随机化设计$ M0 ~+ d- L- n; U' C
Composite event, 联合事件
3 G W- I# F9 [4 eComposite events, 复合事件" v4 {- E) U3 R2 I4 r5 L1 r( W
Concavity, 凹性2 O# e& k) v1 @ F
Conditional expectation, 条件期望& @ d( X; J' Y4 s
Conditional likelihood, 条件似然# y; R4 O* I% M- S! T
Conditional probability, 条件概率: j, Z! p0 {6 i# R
Conditionally linear, 依条件线性* z _* {9 c2 s u, N
Confidence interval, 置信区间
# d$ ]% w+ k" N- |- x& w/ EConfidence limit, 置信限$ G. S- x" {5 v5 X4 P- H
Confidence lower limit, 置信下限
, f: @7 R/ k2 d) D4 L$ i: t! eConfidence upper limit, 置信上限
# i. r' r' N7 Y) Z$ h# ?Confirmatory Factor Analysis , 验证性因子分析) X* S- q% Q6 {6 @; Y
Confirmatory research, 证实性实验研究
# j: Y: x7 Q; \$ a' A2 T" UConfounding factor, 混杂因素 z0 Y* c; G# q2 B3 `; G
Conjoint, 联合分析, T/ I' m# u+ u
Consistency, 相合性
! m7 e; u8 L- S9 {" L$ cConsistency check, 一致性检验8 \! F" g: k, _9 R3 J/ t/ _
Consistent asymptotically normal estimate, 相合渐近正态估计# J8 n3 K5 B3 p5 l1 N0 W
Consistent estimate, 相合估计
: y4 g s! ?" ~# X' j$ ]Constrained nonlinear regression, 受约束非线性回归
6 w: o. @9 ?7 c, g, f$ L- xConstraint, 约束
]/ l. M! n5 k7 a6 z$ J; G6 GContaminated distribution, 污染分布
2 {% k# Z& R0 k1 ]9 i1 WContaminated Gausssian, 污染高斯分布
6 s, j+ n/ Z7 U7 v9 M) x6 `Contaminated normal distribution, 污染正态分布
! y8 f2 [+ W, K+ g6 ]% l3 hContamination, 污染1 u9 K: J- z/ }- \
Contamination model, 污染模型* f( e/ ~& B# r% ?$ Y
Contingency table, 列联表
! v; C6 C, N0 SContour, 边界线) Z4 d5 X6 w7 p, r( j/ e3 V
Contribution rate, 贡献率
8 \$ {& J: C( M3 jControl, 对照
: M' r: _' d0 G8 U& C6 \Controlled experiments, 对照实验
5 {" R5 ^# c/ ]( n6 O: g! U1 |) yConventional depth, 常规深度6 n8 S1 z* W \& I- D- G9 x
Convolution, 卷积
2 w1 ]) L8 l$ E" eCorrected factor, 校正因子
9 Q( x% s, t; n$ h2 gCorrected mean, 校正均值
5 H( l/ V1 E- u$ t% @( v Z8 OCorrection coefficient, 校正系数
; H) A) d4 T C DCorrectness, 正确性: x" R7 q' x+ P# D. Q
Correlation coefficient, 相关系数9 x$ r1 k8 n3 D! `; F$ X7 q1 {
Correlation index, 相关指数* i/ D! x: J8 o" o: `
Correspondence, 对应
7 n& d) M0 Z6 t' [- KCounting, 计数
) G# v; m' B: P* }Counts, 计数/频数
% ~7 F; ` }) A" j# aCovariance, 协方差
2 S2 s# w7 q% c1 ]' ICovariant, 共变 ; R9 _' V+ C( q& _" a: G- c- e
Cox Regression, Cox回归
% c. u" P. J- @! ]Criteria for fitting, 拟合准则
- `! n. ]& t0 a" yCriteria of least squares, 最小二乘准则 B4 D$ ^ ~) U) W/ l
Critical ratio, 临界比
6 w; T7 ^" }3 K! tCritical region, 拒绝域
/ Q* p- ~: D) F! oCritical value, 临界值
7 [4 c- z$ t" I, K7 G( B% ^* sCross-over design, 交叉设计% ]- V9 C7 U% l2 `- ^
Cross-section analysis, 横断面分析
1 g9 ?. M! r* K4 t2 E2 m2 T3 V8 u4 UCross-section survey, 横断面调查& ]0 p/ S \$ c# `
Crosstabs , 交叉表
& {8 X6 n9 h& a# lCross-tabulation table, 复合表8 f$ J1 s- c8 y( {, N
Cube root, 立方根1 U5 Z/ l, _4 t( O
Cumulative distribution function, 分布函数- l, F2 G: O- R. j5 A% q1 l# v5 p
Cumulative probability, 累计概率
, k1 D; s/ `+ Z2 K" F7 P/ RCurvature, 曲率/弯曲% s% f0 \2 {' b
Curvature, 曲率- R2 Y3 d6 ]! S
Curve fit , 曲线拟和 " X$ G5 Z% P% \' _) C: i8 `
Curve fitting, 曲线拟合7 h# R7 \! r0 o
Curvilinear regression, 曲线回归
' z O5 `% N( ^ m# XCurvilinear relation, 曲线关系1 _4 H! M2 s* `. {" ^
Cut-and-try method, 尝试法% \8 G1 y+ X1 f+ g& \- j
Cycle, 周期
! z* Q: k* n! N: ?" @9 pCyclist, 周期性6 o% d+ b# T9 E7 K3 { L
D test, D检验
( u) {2 q4 y2 p/ u. F! nData acquisition, 资料收集) S% O; t. C# V9 X0 d/ [ i
Data bank, 数据库
! W2 x- Z. t2 pData capacity, 数据容量
6 {% ~7 B- {7 B1 p! v7 UData deficiencies, 数据缺乏) [; ]4 A1 c. a9 a
Data handling, 数据处理
6 X4 F. m0 _7 w: w% AData manipulation, 数据处理
% S5 B- S7 S$ _ qData processing, 数据处理8 O6 |: V# f( g: Y
Data reduction, 数据缩减
6 X+ j- z( Q" I8 C; v6 h( EData set, 数据集
5 k) \9 m- g" P, ?0 IData sources, 数据来源
W$ |) {7 A+ P- c0 T. rData transformation, 数据变换
" w6 O! M4 q% U7 A7 ?6 M( O( EData validity, 数据有效性6 N( A/ m- |, d
Data-in, 数据输入2 g9 m6 Q5 A w& y$ L# Y+ u: p
Data-out, 数据输出* K7 S$ t# H! a5 c0 b
Dead time, 停滞期9 x. m" |+ u" m: x9 i
Degree of freedom, 自由度' L2 b4 _0 n V# k# O8 A) J
Degree of precision, 精密度! C4 V" O" V( \6 K- L8 \
Degree of reliability, 可靠性程度" ?6 a" G9 j% L3 j9 r
Degression, 递减' ^- x4 y4 {6 ^; K
Density function, 密度函数
+ `8 h( o+ h0 W) k2 S) ~, QDensity of data points, 数据点的密度
+ q. k; p, l; i" k+ r, ` B; lDependent variable, 应变量/依变量/因变量; S8 r% }3 R. V5 J" E
Dependent variable, 因变量
2 l i% o- i7 l! mDepth, 深度
. K7 H. @ @5 H/ b; Z7 C; ZDerivative matrix, 导数矩阵
! L1 [) y3 J2 X9 }Derivative-free methods, 无导数方法. m) z0 o: i+ A8 Y
Design, 设计2 F1 S/ g' ~9 H
Determinacy, 确定性
9 U1 `7 w# X# `Determinant, 行列式7 |) t+ |: C- z9 P) K; Q% m" P$ I. R
Determinant, 决定因素
- ?' h: m0 G; l% dDeviation, 离差4 C3 v5 f2 g8 i, P' i% t
Deviation from average, 离均差
. n) k) @3 Q, k6 p6 i) b3 KDiagnostic plot, 诊断图) K1 ]2 K2 G, B, Z& Y! ]8 h
Dichotomous variable, 二分变量 p' n N# w1 u
Differential equation, 微分方程
2 s, }4 i" B% J8 J) nDirect standardization, 直接标准化法( i4 I0 F# F, R7 V
Discrete variable, 离散型变量
n! j7 ]4 ?- l1 x' y* SDISCRIMINANT, 判断 8 E# b! j2 z3 \+ V& J
Discriminant analysis, 判别分析3 U$ r1 d& y* z( l1 b( K
Discriminant coefficient, 判别系数, G# {2 M* t# L5 o" x
Discriminant function, 判别值" @3 k$ W0 _3 Y, d6 B2 m- i
Dispersion, 散布/分散度4 a, q* k: j2 @* p2 u
Disproportional, 不成比例的
9 Z! _7 \9 ~ @6 t6 I+ W; l, M( kDisproportionate sub-class numbers, 不成比例次级组含量
7 ]1 ^; T( D& I& ]! s; pDistribution free, 分布无关性/免分布: g) m- M5 z5 p9 f; h9 x
Distribution shape, 分布形状0 f0 |: ` A2 d: Z l* r& L7 r
Distribution-free method, 任意分布法
/ d b4 e0 U5 H4 F3 v$ s5 PDistributive laws, 分配律7 E. J0 o. c6 k9 D$ V
Disturbance, 随机扰动项+ k! N2 M Z1 @0 k& W. V
Dose response curve, 剂量反应曲线
/ A) K" }7 C0 s" f/ DDouble blind method, 双盲法
) D5 ~; p8 _; m4 R! j0 ODouble blind trial, 双盲试验
, L4 L Q- J0 m9 PDouble exponential distribution, 双指数分布
/ \& V# g s$ M: T0 ZDouble logarithmic, 双对数
2 D* l1 S% R" D% r8 L2 YDownward rank, 降秩+ |" {5 O3 [/ E
Dual-space plot, 对偶空间图2 O( v$ r6 F; `% x m6 D
DUD, 无导数方法
" L& H# p0 M$ b$ F3 R3 [( t0 eDuncan's new multiple range method, 新复极差法/Duncan新法
2 ] r0 Q9 `; ^6 R, IEffect, 实验效应8 \/ a2 N5 @5 f
Eigenvalue, 特征值
. D# f9 z @# r. u/ x) K. K3 ]+ VEigenvector, 特征向量
: B( Z; b" a1 [ _& m6 }7 I- U' PEllipse, 椭圆+ N( M- Y6 E) k8 ]
Empirical distribution, 经验分布
( b8 a/ K( y/ H5 l" C( Z2 w$ `Empirical probability, 经验概率单位5 L5 v( J4 a1 G6 h r( t
Enumeration data, 计数资料
8 @8 F9 v( W& BEqual sun-class number, 相等次级组含量
& W* [2 |* ]! TEqually likely, 等可能( r* j3 @4 M$ {, X0 ~
Equivariance, 同变性
( X8 k) d7 z6 K! j- F% Z/ ^Error, 误差/错误
9 C0 F" I. V. ?1 ?! gError of estimate, 估计误差$ x2 Q( f+ J' Z0 J
Error type I, 第一类错误
# y# q# _6 |1 L: UError type II, 第二类错误
8 l; M! Y" u- v) m, p; S& O8 H8 L- A9 VEstimand, 被估量
- X6 a9 w! e5 [* H; C& [Estimated error mean squares, 估计误差均方
8 h E; y: Z" F# QEstimated error sum of squares, 估计误差平方和
1 X% z7 b" |$ sEuclidean distance, 欧式距离$ R) k9 d: I1 y; F' W
Event, 事件3 l8 W. y# X3 M: M
Event, 事件
( [" X! t" M, m9 N; @+ vExceptional data point, 异常数据点9 W/ T8 |5 C s1 M8 x3 w' Z* P
Expectation plane, 期望平面
2 A! O2 f" n7 S0 a; U8 C( ZExpectation surface, 期望曲面
. o9 z7 I. z# mExpected values, 期望值
6 F; q& E) |- vExperiment, 实验3 M# y2 j4 i2 E) ]/ A: N
Experimental sampling, 试验抽样! A/ g C. T+ n) a* Y
Experimental unit, 试验单位
6 \6 F* v0 l+ J' o% S7 ^: FExplanatory variable, 说明变量% c# Y( u3 B# V6 |; Z9 V% }, I
Exploratory data analysis, 探索性数据分析
1 y) [& e" Z) ~# ^Explore Summarize, 探索-摘要4 k. h5 {! s% M' W
Exponential curve, 指数曲线
/ M* P8 S" N% I8 hExponential growth, 指数式增长
+ A" J$ G6 e% V% ?0 f$ IEXSMOOTH, 指数平滑方法 ! f$ B+ ]9 N* T5 A5 f
Extended fit, 扩充拟合
! v* m- W1 @, f& T7 Q5 oExtra parameter, 附加参数
( d& @: ^/ ]7 m+ o# EExtrapolation, 外推法
, t6 D$ t3 L8 E% ?- hExtreme observation, 末端观测值
( J; k+ Z/ ]* V9 p8 ]Extremes, 极端值/极值
6 I3 D8 \, Q w' O7 P }0 u. uF distribution, F分布
6 g: E! Z, R& k$ P; z' e X1 ~& eF test, F检验
: s$ r8 {7 U8 z3 k! @Factor, 因素/因子$ {3 b' o6 e3 s1 i% r2 ?# g
Factor analysis, 因子分析4 I& K7 l; f+ j1 n/ Z2 f
Factor Analysis, 因子分析$ i0 c/ m5 w: ]" [% q1 M- r) o
Factor score, 因子得分 ; S: [! w3 L ~; a" N- X) v
Factorial, 阶乘; h+ P6 X$ c1 p5 t
Factorial design, 析因试验设计# F7 H2 ?$ f' h& f; s2 C, t- Z5 e
False negative, 假阴性% a* Q9 n" F8 a: i8 H% I
False negative error, 假阴性错误0 L& s' @ X- E) f) ^0 l
Family of distributions, 分布族0 B, Q ?# [: B7 U
Family of estimators, 估计量族
% b- E R! L# l2 ?' C# jFanning, 扇面# ~( B8 L3 }* i+ l+ V# K; r3 U
Fatality rate, 病死率8 f2 T$ U4 ]/ x/ T& |9 s
Field investigation, 现场调查
1 v4 l& {6 N' K( l3 F, eField survey, 现场调查5 j# @, ~5 ~) y
Finite population, 有限总体) E+ K' ?4 S. J9 l' z# z
Finite-sample, 有限样本+ ]# r% {3 r+ {
First derivative, 一阶导数 S' R6 A5 ^; C9 q7 }
First principal component, 第一主成分; L8 w' s- ~" w4 X
First quartile, 第一四分位数7 \( M8 q& L3 E0 P
Fisher information, 费雪信息量
# U1 O; T. U2 j1 f( l ~Fitted value, 拟合值1 n9 Y. q: M7 s, ^) Q) ^5 f
Fitting a curve, 曲线拟合* @5 K x$ s2 j- n y
Fixed base, 定基
- b' U) V: N/ y- Q3 BFluctuation, 随机起伏0 U( h0 f# b8 v* F$ I
Forecast, 预测
# }# E3 |5 ~0 }, t1 r1 i1 hFour fold table, 四格表
9 ]! }8 f8 U- o- o# D4 Z5 j$ wFourth, 四分点
/ Y. x( R' e. h, |Fraction blow, 左侧比率
0 w: `3 A. a# i! W9 PFractional error, 相对误差3 s3 M: F. n5 c' ~) m' j
Frequency, 频率
3 o$ Z+ Y/ h' ^' A& @Frequency polygon, 频数多边图; F* K! l9 P- v7 v( Q
Frontier point, 界限点4 [9 \+ q" P) S0 ^6 y0 \
Function relationship, 泛函关系# Z8 ]* `$ b* {; C& ?, E( ?* R
Gamma distribution, 伽玛分布; ^; \- Q" x: F% t- o
Gauss increment, 高斯增量3 a- N( A3 a( I0 |2 o% P3 m4 B
Gaussian distribution, 高斯分布/正态分布$ u* z# M3 ?# @/ T( _. @
Gauss-Newton increment, 高斯-牛顿增量
. C! @) S* K O N0 XGeneral census, 全面普查, G7 h. H$ T3 x2 ` z4 E
GENLOG (Generalized liner models), 广义线性模型 1 u8 N& o2 D6 I' O+ ]
Geometric mean, 几何平均数4 z& c3 m4 ^; `2 j: B# A5 |
Gini's mean difference, 基尼均差
V$ i+ F; ~' y3 c' hGLM (General liner models), 一般线性模型 ; m$ e1 M, H8 d' J: D
Goodness of fit, 拟和优度/配合度
/ Q6 H, }) \* _& K; j5 _: FGradient of determinant, 行列式的梯度+ V$ ?5 f1 T% t# Q5 ^5 M
Graeco-Latin square, 希腊拉丁方& _8 ?4 T& L& e+ A/ L6 c; I
Grand mean, 总均值( |* j& i: ]9 v* i3 d9 v
Gross errors, 重大错误2 K) b+ I% B0 a! t4 e* t
Gross-error sensitivity, 大错敏感度, F- w5 C& P5 C0 G. a, R: }
Group averages, 分组平均$ a+ i8 k- G/ u* L
Grouped data, 分组资料% q" |% Y R' q( D
Guessed mean, 假定平均数
5 O/ l+ o9 W1 dHalf-life, 半衰期
0 y9 L7 g" G, ~" dHampel M-estimators, 汉佩尔M估计量
* ?* c z" \) J8 F$ R- {* iHappenstance, 偶然事件
, r) g- j0 B3 ^% VHarmonic mean, 调和均数) Q# |# ]& d5 \0 {' f6 S
Hazard function, 风险均数. S. q3 Z2 T! e& D, V9 i; s
Hazard rate, 风险率
$ z* i" I# I# Z9 @3 WHeading, 标目 2 O4 b( ^- S: a. L
Heavy-tailed distribution, 重尾分布
6 e+ A/ O' G8 I+ e( N* M' B! p/ hHessian array, 海森立体阵
$ z) V) u3 [* ~9 |4 THeterogeneity, 不同质
# G% s$ G _/ AHeterogeneity of variance, 方差不齐 - z2 N- C, @* T
Hierarchical classification, 组内分组
6 s% I. h4 o; W6 E* d9 B' Y4 D* S! t6 uHierarchical clustering method, 系统聚类法
& r: r6 v1 n9 r1 Q: tHigh-leverage point, 高杠杆率点
0 Q8 `: z9 Q5 R, ?/ K8 ?HILOGLINEAR, 多维列联表的层次对数线性模型
; g% ^$ y0 f0 k! q n8 W ]0 cHinge, 折叶点! o! D; K6 C/ s- u' n
Histogram, 直方图
8 r& l' ]% X3 T% L4 }8 \6 GHistorical cohort study, 历史性队列研究 7 U: `; u1 Y [, ]; c
Holes, 空洞# s; p; r9 T) b6 D c' d
HOMALS, 多重响应分析1 a( Y/ H6 o6 ]- U) d
Homogeneity of variance, 方差齐性, D7 V# h6 [6 A$ h' W3 g% K
Homogeneity test, 齐性检验/ x, J! W7 Q6 U8 D$ |
Huber M-estimators, 休伯M估计量5 L9 m& } d; q& b2 ~. O4 L
Hyperbola, 双曲线0 @1 j _. Q4 a3 ~
Hypothesis testing, 假设检验
h0 k4 z) ?- ^: }7 r; PHypothetical universe, 假设总体
; \3 r; U4 k: o6 B i4 b% N$ EImpossible event, 不可能事件
0 `. c+ b* p8 N8 ]7 Y8 aIndependence, 独立性
h8 o0 l3 w: Z$ TIndependent variable, 自变量4 D8 t4 s9 |" x9 h) l
Index, 指标/指数
; j/ @6 x) ]/ f5 C$ ]Indirect standardization, 间接标准化法: \" d) ]) B( E, P6 y( x
Individual, 个体0 y+ ?, M: [, [' W
Inference band, 推断带! S, y: s6 @2 a" J
Infinite population, 无限总体
( t" {! p$ l, G0 M( D' H1 b, _: o- ?Infinitely great, 无穷大
+ z: @( S" T! J1 P& ?6 oInfinitely small, 无穷小
( Y" h. S0 L# H5 \7 c" q1 PInfluence curve, 影响曲线
, ~4 S- G/ J8 T+ F, CInformation capacity, 信息容量
6 b) _" Q$ \3 O1 CInitial condition, 初始条件* h1 K1 L8 |* n$ [
Initial estimate, 初始估计值! S( E7 {& A' h* Z
Initial level, 最初水平+ N' l( B, F4 V
Interaction, 交互作用
% \. J. l8 l( k+ f# CInteraction terms, 交互作用项
5 i$ d; s0 e5 d/ C4 {; |4 WIntercept, 截距2 z/ [0 u% ]8 b2 e2 _1 W) x% B
Interpolation, 内插法' G" f! p. `% i
Interquartile range, 四分位距
4 S* S9 u- H( W$ c) AInterval estimation, 区间估计1 p$ ]+ J) z) L4 {$ s, ]" d: x+ ]
Intervals of equal probability, 等概率区间
( j1 b4 r5 D* z8 SIntrinsic curvature, 固有曲率( I0 o( H( H) R6 X* x+ ^: _
Invariance, 不变性
, N, H9 l9 Y/ x9 q# I! D8 f& cInverse matrix, 逆矩阵
" K) j$ z8 f7 s" L! sInverse probability, 逆概率* e) \; r( G& b
Inverse sine transformation, 反正弦变换
) A! O2 D9 i5 @' p- Q9 l; LIteration, 迭代
' a- ~7 [# y% uJacobian determinant, 雅可比行列式
; T }2 _# a; ~: }Joint distribution function, 分布函数
$ A6 w7 e/ I3 O qJoint probability, 联合概率: i3 p3 @! S- Z0 C2 @
Joint probability distribution, 联合概率分布
. f8 X3 w0 i5 t/ CK means method, 逐步聚类法# v1 Z0 R( H& ]4 u
Kaplan-Meier, 评估事件的时间长度 0 B, `" S- }2 z, {& F7 \ x8 u* x: w& ?% [
Kaplan-Merier chart, Kaplan-Merier图
( K9 i; D% F5 h4 Q4 R) s5 hKendall's rank correlation, Kendall等级相关* a8 s$ M$ _+ v. K
Kinetic, 动力学9 G* y- e' i2 b9 y8 b f
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
' t# s) b7 A1 I' g& `6 }$ Q3 b! zKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
$ F8 L# }0 U; F TKurtosis, 峰度
4 Y3 i5 X/ O6 B, Y2 I/ Q/ SLack of fit, 失拟$ A5 _, V7 [* T* D
Ladder of powers, 幂阶梯
7 Z' n2 @( `$ T2 t4 c. dLag, 滞后) i6 [7 y: q3 _8 M& v3 @6 r
Large sample, 大样本# F& o1 [0 R/ J/ E8 n8 d0 J4 u
Large sample test, 大样本检验
2 Y% [1 b; c2 L1 @7 C5 ]4 GLatin square, 拉丁方6 @$ ^# W3 F, b D
Latin square design, 拉丁方设计
4 y5 H2 O. [1 J ~9 ^# m6 {Leakage, 泄漏- B) N0 W4 k6 @# F) X. R- F: G# k
Least favorable configuration, 最不利构形
# E* [+ G1 u* [- s* aLeast favorable distribution, 最不利分布
0 s, U- \# f" pLeast significant difference, 最小显著差法/ y6 j- @- N* N+ F$ W
Least square method, 最小二乘法+ _- u" ~0 Y* I8 [/ V
Least-absolute-residuals estimates, 最小绝对残差估计
' }. b* g+ |+ A$ @4 I( LLeast-absolute-residuals fit, 最小绝对残差拟合2 W& `& `3 N1 U+ a9 N: ^1 d6 E* i
Least-absolute-residuals line, 最小绝对残差线
; V7 o* _% V% ELegend, 图例
8 l% z, ?6 ~, O U" `L-estimator, L估计量
$ g+ D" Y. c: C. W+ u6 H' @; lL-estimator of location, 位置L估计量
% L4 l6 }2 h; q/ d% |: f+ ML-estimator of scale, 尺度L估计量. [! k5 i: g. {) F% F. N1 M5 D
Level, 水平/ x [$ x/ c' o# b2 i/ B
Life expectance, 预期期望寿命. R" `% w' W5 m w+ A
Life table, 寿命表
7 e9 Z. E- F, Q W# k0 o9 u: x* P) yLife table method, 生命表法
# E- u- n8 ^5 M N: Y7 KLight-tailed distribution, 轻尾分布9 L' W: q: A9 [: v+ |( ~1 G/ r' O! ^0 `
Likelihood function, 似然函数: b# }5 j& d$ b' V
Likelihood ratio, 似然比
7 l6 ]' H3 }4 K1 G0 Dline graph, 线图. w' H5 f a2 G7 M s
Linear correlation, 直线相关
( e: h$ b0 P$ m9 K7 t" bLinear equation, 线性方程5 K+ X$ z4 I, N
Linear programming, 线性规划8 b6 M. |5 M# C9 P; ~# K
Linear regression, 直线回归
3 U) V$ c# O y1 I H2 dLinear Regression, 线性回归1 s/ i( R; f2 N& u
Linear trend, 线性趋势
' r' ^9 G9 j! k5 ~: j! C7 o, P1 WLoading, 载荷
# a- |! l' k( Z$ x7 _8 H# BLocation and scale equivariance, 位置尺度同变性
6 |6 e' w5 B- M8 s) fLocation equivariance, 位置同变性
. ~, u" F; G3 i0 B8 | \9 l6 t7 rLocation invariance, 位置不变性+ B, R2 E4 Z& v9 ]: o3 p
Location scale family, 位置尺度族# Z3 e3 o ~5 U$ Z' e9 a
Log rank test, 时序检验
1 e, S0 C X: D. j# a) T/ ZLogarithmic curve, 对数曲线
1 ~ U/ Y0 ?- qLogarithmic normal distribution, 对数正态分布
% X' |3 k `7 P+ H* NLogarithmic scale, 对数尺度/ G" }: u- R9 r( b4 k U
Logarithmic transformation, 对数变换
0 \, @: @+ ^ F: Y( DLogic check, 逻辑检查4 x4 h3 a; E, N
Logistic distribution, 逻辑斯特分布
6 X9 U$ V i2 b6 w! ?! \* nLogit transformation, Logit转换
* k4 {+ {* Z/ c# cLOGLINEAR, 多维列联表通用模型
$ w5 h( X" D3 n5 X4 ELognormal distribution, 对数正态分布- P; k2 e' q8 i5 a" d6 `
Lost function, 损失函数" k. Z1 A( O) j3 Z* W/ ?- \
Low correlation, 低度相关
+ u* O, _$ A) q& C: e5 d4 z/ FLower limit, 下限
7 F7 W! Q. c, c0 u: oLowest-attained variance, 最小可达方差
8 h5 L1 t& m- z* kLSD, 最小显著差法的简称$ ]( i0 k3 S+ [+ G: R6 D
Lurking variable, 潜在变量 u; h% h) B" \" v6 P+ y
Main effect, 主效应
# e! J/ @/ G7 r( M: c% v( Q! [Major heading, 主辞标目
4 [" Q0 ~& [8 r3 |( a9 n4 BMarginal density function, 边缘密度函数
; I, X: I/ \3 B3 P1 mMarginal probability, 边缘概率, n7 s4 o$ c7 n$ U
Marginal probability distribution, 边缘概率分布3 S* |! a2 D$ I, D
Matched data, 配对资料
]$ e, ?: S0 [. iMatched distribution, 匹配过分布
% w; `3 c" y- y. k' b/ fMatching of distribution, 分布的匹配
* b ^7 R' @% X0 Z4 m! N @Matching of transformation, 变换的匹配+ ?3 V6 `0 G u, v2 @3 T
Mathematical expectation, 数学期望
/ R, S; b# M% q1 J7 aMathematical model, 数学模型
( ]/ J7 K' g6 nMaximum L-estimator, 极大极小L 估计量
8 t7 _$ V0 H8 c4 w7 `Maximum likelihood method, 最大似然法
( H0 _# {4 x# pMean, 均数
# w% I3 u6 X0 r6 W1 ~Mean squares between groups, 组间均方
& D9 m; ]3 ?, J/ |6 Q1 V7 \* dMean squares within group, 组内均方& t5 R F: t5 n( y2 u/ o
Means (Compare means), 均值-均值比较( H2 l3 t% ]3 N7 L
Median, 中位数
$ L# W# b5 M* c; BMedian effective dose, 半数效量: F, H" G( E$ {( K
Median lethal dose, 半数致死量9 q* [( F+ B" y0 d( V t
Median polish, 中位数平滑: g) [" c! u: H/ l- v$ `
Median test, 中位数检验$ y! p; x" z" ?
Minimal sufficient statistic, 最小充分统计量, B0 W- z& M6 q& {( Q
Minimum distance estimation, 最小距离估计
* {3 E7 X y1 K C" zMinimum effective dose, 最小有效量
6 Y# Q+ q/ i$ k' ^Minimum lethal dose, 最小致死量' E8 J) B& f) A, A
Minimum variance estimator, 最小方差估计量+ { g3 L h* E6 a
MINITAB, 统计软件包
( M* g* I7 T9 \ K( OMinor heading, 宾词标目8 f9 a; Z& J ~+ q: ] e7 ~
Missing data, 缺失值
8 S& R# }2 G9 v/ E" G4 oModel specification, 模型的确定2 W: l; }3 e! j% j! S" W2 u
Modeling Statistics , 模型统计
- z1 S) N8 }2 D" B; O9 Q, SModels for outliers, 离群值模型
/ t9 I5 R' v; e/ A' N% ^5 c+ q* WModifying the model, 模型的修正! i9 Y& G% {( C
Modulus of continuity, 连续性模
8 Y0 g( c" X& ]6 q9 w, E$ qMorbidity, 发病率
* m; d; X: y* e: w3 kMost favorable configuration, 最有利构形
* }% S/ }1 O p- _' |, NMultidimensional Scaling (ASCAL), 多维尺度/多维标度
8 j+ E1 d7 @% v5 c6 \Multinomial Logistic Regression , 多项逻辑斯蒂回归+ f6 A5 `8 L0 E& A- F
Multiple comparison, 多重比较( Q) e! H& U, W5 K" h. S( m1 P1 r
Multiple correlation , 复相关% ~# |" ?( C' w6 U2 G, a9 `3 e
Multiple covariance, 多元协方差$ u8 M. F% V7 I4 u$ P
Multiple linear regression, 多元线性回归
5 K6 \2 p( m! VMultiple response , 多重选项
, m2 Y& l' G5 T8 ?/ R, xMultiple solutions, 多解
6 C1 l1 w3 r( U! EMultiplication theorem, 乘法定理7 W" X8 @0 ?; K% Y' ]: @! u! S' W' x
Multiresponse, 多元响应
) m' H b. `$ M( \2 zMulti-stage sampling, 多阶段抽样
1 w- q) W: J+ ? a m% UMultivariate T distribution, 多元T分布7 i `5 I6 r) E( p& D; s" e
Mutual exclusive, 互不相容
8 x* m$ U9 J# z: Y2 N; j$ iMutual independence, 互相独立
, Q% T. n7 K' C2 F& a3 yNatural boundary, 自然边界
$ H% g. }/ Z2 D3 UNatural dead, 自然死亡
0 D. N" M6 Y6 q6 J3 M$ SNatural zero, 自然零
* s& A4 N9 U5 Z- b {6 cNegative correlation, 负相关
* L ^0 {. }1 p% QNegative linear correlation, 负线性相关" ?) v% R1 t h7 H" ~6 b {: ]# U
Negatively skewed, 负偏, R, Y! X; w }$ L; L
Newman-Keuls method, q检验
6 @+ U7 d2 e! pNK method, q检验
# O) Z' c' W! o y- u- aNo statistical significance, 无统计意义
7 o- s; D6 g! T# d8 {/ o$ {Nominal variable, 名义变量 l$ h" x7 |& T1 p9 }; W8 S
Nonconstancy of variability, 变异的非定常性
! V! K- t- z8 f4 g3 @Nonlinear regression, 非线性相关7 a; r* I& T: J; _9 c$ C4 o
Nonparametric statistics, 非参数统计: }6 f, o9 J/ m5 [8 ]
Nonparametric test, 非参数检验
% v G* ~- M6 ENonparametric tests, 非参数检验
$ i7 W1 _* n' T4 rNormal deviate, 正态离差
8 [4 m3 ?# ^& I, f3 j& TNormal distribution, 正态分布) h" e% D( M p# }) K
Normal equation, 正规方程组- s% X8 e. e) d8 J) O% k, m4 o
Normal ranges, 正常范围
/ n# T- @7 e& Z n9 v( Z/ }Normal value, 正常值
+ R, g6 f6 `& f) _# {: l% @) R6 kNuisance parameter, 多余参数/讨厌参数
8 ^% ^ H$ ]! p8 l1 UNull hypothesis, 无效假设
0 C& j8 b5 y0 M9 E- e9 FNumerical variable, 数值变量+ Y1 h' ~* y# B
Objective function, 目标函数) Z' H* q4 y. g0 s4 w U
Observation unit, 观察单位4 J. M! p7 q" s8 V1 d
Observed value, 观察值2 g7 k. [; a2 \, K) b( }' p
One sided test, 单侧检验2 F, ^4 ~3 E* b% l' X1 O# I
One-way analysis of variance, 单因素方差分析1 s# ]; e; U' f1 h7 u" p( b
Oneway ANOVA , 单因素方差分析
: h4 ~ Z$ s/ {4 tOpen sequential trial, 开放型序贯设计
2 {! ~1 _8 z U, V, t$ `% F8 S& NOptrim, 优切尾
`5 Q$ t0 W% ~, R1 A% NOptrim efficiency, 优切尾效率, U7 ]) h) D' o1 E8 d3 K
Order statistics, 顺序统计量
" r6 N; J' k2 t7 T; e7 z! EOrdered categories, 有序分类
. U+ r6 V3 W! |1 G2 y( s8 s ]Ordinal logistic regression , 序数逻辑斯蒂回归; a* ^. b0 g. d2 O! G
Ordinal variable, 有序变量5 k2 e& g; B* S2 Z% h- x
Orthogonal basis, 正交基4 |4 Y: [' U0 w+ \$ ^
Orthogonal design, 正交试验设计
& l9 m4 a& a3 b L# O- iOrthogonality conditions, 正交条件
* T- s0 ]% t z% P0 H; d5 p; j+ OORTHOPLAN, 正交设计 5 ^) L. i& Q7 L2 B- l6 b) t' j5 N* v
Outlier cutoffs, 离群值截断点5 b" m( v4 p8 f) Q/ t" k
Outliers, 极端值' |5 X' x! i1 k0 j5 T
OVERALS , 多组变量的非线性正规相关 " i# ?% N3 x) J
Overshoot, 迭代过度. s+ z/ ?2 M: C) U& ^* i+ @
Paired design, 配对设计
( l+ c. `7 @- b* w9 ^Paired sample, 配对样本8 n' l1 ^5 U+ w6 ?* R& }. Z4 g
Pairwise slopes, 成对斜率7 H, q0 z. m+ i* s! ^- g
Parabola, 抛物线
2 m6 I7 }% K5 _Parallel tests, 平行试验2 R$ x/ A! R: V6 n1 ?
Parameter, 参数! l& |6 f$ ?2 ^: t
Parametric statistics, 参数统计
( v- y( K2 h- D$ [8 r: O6 HParametric test, 参数检验$ K7 ~2 [. d: ?2 r b
Partial correlation, 偏相关
" B/ ?! I. ]6 D) e7 f7 k, j; tPartial regression, 偏回归
, ?7 v( d: z; BPartial sorting, 偏排序: L y) q; J! _' y4 w4 M0 o
Partials residuals, 偏残差2 K3 J J, ^$ m7 l/ R6 b0 S5 A+ ?
Pattern, 模式
: }+ _2 I+ @. N% i# N7 nPearson curves, 皮尔逊曲线0 Q" k2 l$ J1 _7 m. V* k; {
Peeling, 退层) o# j0 v( |/ L( @2 w1 A+ A$ p
Percent bar graph, 百分条形图
$ P; m3 w5 O# ? g$ M9 ? O8 b& hPercentage, 百分比
5 B; `! f9 \) @. GPercentile, 百分位数
5 V% w8 c% W% q; k! T' LPercentile curves, 百分位曲线# q( H9 s7 l7 ~6 i0 i( q
Periodicity, 周期性
' U( f: ]- t2 z) y+ ePermutation, 排列1 T+ }: }! m3 @4 \
P-estimator, P估计量. {8 J6 V7 I( q1 o; u J1 u! d
Pie graph, 饼图
1 x( ^1 M5 [# rPitman estimator, 皮特曼估计量
! _4 k' z4 k7 E6 w. ~. K3 C, hPivot, 枢轴量9 o( ~9 x4 N O* p0 j( ?" x
Planar, 平坦7 O3 I2 U0 u/ g8 C0 x! r$ H
Planar assumption, 平面的假设 b% {! Y' x2 g3 C, P9 ^7 e
PLANCARDS, 生成试验的计划卡+ Q- n: [ ]+ U- C5 E0 P& v
Point estimation, 点估计" L- k, a. K, v. w8 H6 c
Poisson distribution, 泊松分布
' ?6 t8 }5 U% W) ePolishing, 平滑4 l* H6 s' X; o+ b7 ~9 i
Polled standard deviation, 合并标准差: D: _. p" V4 d3 [6 d) y
Polled variance, 合并方差( z6 {: D& ]7 e9 ^7 k8 J
Polygon, 多边图8 Z$ g u7 ^3 K8 K
Polynomial, 多项式4 S, j+ i K# D! n3 J
Polynomial curve, 多项式曲线 I; n8 ~& A2 T8 O! X' j6 F: H; [
Population, 总体/ ?* R0 @8 B& ~$ F
Population attributable risk, 人群归因危险度5 m6 _/ \1 p3 I9 Y3 p( A
Positive correlation, 正相关! p. q. t& `: ^# z, ]4 p
Positively skewed, 正偏: ?3 y4 T5 I6 V; S- f
Posterior distribution, 后验分布/ l) `- I; ?2 ?
Power of a test, 检验效能. `$ z$ @+ v$ T2 I! y
Precision, 精密度) V9 t; ~. j1 d9 s
Predicted value, 预测值! P2 W/ ]' t. V
Preliminary analysis, 预备性分析4 z/ \ `$ |/ X8 W5 H/ X3 J/ u
Principal component analysis, 主成分分析8 G9 f S3 C2 y0 M' J9 y; u6 O
Prior distribution, 先验分布3 l0 m3 z- {; p D5 ?" l3 _* L0 [
Prior probability, 先验概率; c* k8 Y9 L, l! h& d+ q8 b2 h" q
Probabilistic model, 概率模型
( Y1 w( @( G& W5 k bprobability, 概率3 B d! Q& `. S6 c. v
Probability density, 概率密度
# ^) B$ Q+ D( x' c! u. p+ [3 x8 uProduct moment, 乘积矩/协方差- I- y b2 Y j4 P& I2 m
Profile trace, 截面迹图
1 M$ G) F- x# m+ d8 D0 tProportion, 比/构成比0 o8 g9 K( M9 ^& B8 E
Proportion allocation in stratified random sampling, 按比例分层随机抽样
- l7 m( _, O: j$ z! M2 MProportionate, 成比例1 _9 S. ~$ e0 R5 }
Proportionate sub-class numbers, 成比例次级组含量
8 v5 |* h4 L3 o0 b9 W- D6 ^Prospective study, 前瞻性调查
9 K8 c) A- ]& ~; OProximities, 亲近性 " [! H( A8 z2 [* j+ V* A
Pseudo F test, 近似F检验6 }$ [# F. g7 Z
Pseudo model, 近似模型) [" r- X' R8 o: v% l! N
Pseudosigma, 伪标准差5 z6 ]. Z% u' ?
Purposive sampling, 有目的抽样
. g' ]/ F2 H" h$ G/ {# R3 [' GQR decomposition, QR分解7 q! _3 Z1 T) e( |. w
Quadratic approximation, 二次近似/ a" p0 y) g: v+ X/ G3 s: f
Qualitative classification, 属性分类6 |# _) p) [0 Z# m1 S; n
Qualitative method, 定性方法
% B4 e* R7 U" y, w( ^Quantile-quantile plot, 分位数-分位数图/Q-Q图# K9 r" W4 D! o' r1 p
Quantitative analysis, 定量分析
7 `( L2 e- Q- G5 V8 _Quartile, 四分位数
* {9 _/ B: z6 w6 o2 |7 o8 bQuick Cluster, 快速聚类# ?) ~' S# [) P
Radix sort, 基数排序0 G* n1 I2 b! d- K
Random allocation, 随机化分组
5 X6 ^# @) P1 o9 r$ W5 u. l2 {; vRandom blocks design, 随机区组设计, y( ~6 Q. d$ E6 | x
Random event, 随机事件
: f; W5 Z' V4 g$ a2 @+ \Randomization, 随机化# u- k3 _) f4 `% [+ }
Range, 极差/全距
( I) P* h5 a0 C5 a: {! xRank correlation, 等级相关
/ r9 W: F2 y1 o6 |$ _& o0 h ]; ORank sum test, 秩和检验
: |6 J# n* z4 @& m2 O l! RRank test, 秩检验1 S% n1 H k6 F2 b6 p, Y' p
Ranked data, 等级资料
, B' f6 ~' p' K) J* MRate, 比率
7 i" d8 s! m* sRatio, 比例# ]& S/ ]- Z L, {
Raw data, 原始资料: _: A2 S. y) t+ Y
Raw residual, 原始残差
* T6 j& N2 g+ X% ARayleigh's test, 雷氏检验( r# e* S( i b$ C0 ?
Rayleigh's Z, 雷氏Z值
" \8 d, h: L. P1 k5 a3 ^Reciprocal, 倒数. c: ?, f3 c5 {, H4 j, q
Reciprocal transformation, 倒数变换
: Z1 r9 L/ e! R0 _- S/ k( }Recording, 记录
0 o# W" C; G- Z! ]3 m# J3 X) xRedescending estimators, 回降估计量
3 q7 h) X+ d$ @* j3 {1 W; lReducing dimensions, 降维
6 L. U0 Q( M5 s' z! j4 bRe-expression, 重新表达
`1 L, y. l( ^ n ]4 ^Reference set, 标准组
* Q) ~5 r: b% |5 m9 g. @Region of acceptance, 接受域
6 D* P9 P8 Z& T3 C, A. Y+ M, IRegression coefficient, 回归系数9 a% o5 R5 S" z0 M6 m
Regression sum of square, 回归平方和
A; k7 g* A, XRejection point, 拒绝点
I2 _' Z7 a5 k2 @, H- l+ tRelative dispersion, 相对离散度
' v: T9 H/ ?3 R0 y9 F6 `2 HRelative number, 相对数" c( P; Z2 F6 h
Reliability, 可靠性
$ H& m- j6 f% U+ j/ v! EReparametrization, 重新设置参数. S; K% z& c9 |( R2 d Q0 F- D# A: ]
Replication, 重复# K% _* }% I& r
Report Summaries, 报告摘要
6 ~' Y# o2 C8 `& t5 gResidual sum of square, 剩余平方和7 u5 g; J( m% C- Q& |8 K
Resistance, 耐抗性
, q+ o/ j+ v5 i- cResistant line, 耐抗线3 \+ J' u% j' i8 w$ P
Resistant technique, 耐抗技术5 i8 @8 D& L2 X! l. Q- I- J- e; m
R-estimator of location, 位置R估计量
8 i4 z! x8 I7 F3 kR-estimator of scale, 尺度R估计量
0 j/ A9 j* [4 L) D0 |, X% I$ [* W$ bRetrospective study, 回顾性调查- t" a ^! I7 @
Ridge trace, 岭迹2 A! l8 A# `5 K6 ^* ?3 G+ {
Ridit analysis, Ridit分析# q* F' _$ e4 S& y( V. U2 n$ V
Rotation, 旋转
( T( s/ A7 T# I" g/ S) n( ORounding, 舍入' I. e r9 _# @% p/ O/ [
Row, 行1 D3 X1 @* z9 q2 a7 @
Row effects, 行效应: z) e: }" O) f8 V7 }
Row factor, 行因素4 }3 y V0 r% p1 m6 E
RXC table, RXC表
% F. M( J0 _4 t/ h5 USample, 样本/ d+ x& {; H, U/ P% M0 G
Sample regression coefficient, 样本回归系数
# c9 J u K. `# ]- \" ~/ MSample size, 样本量 [& [3 V& a' y7 y* R( r
Sample standard deviation, 样本标准差& G$ _$ j9 x$ U; {& z* x
Sampling error, 抽样误差! V' i5 x1 B. r. \
SAS(Statistical analysis system ), SAS统计软件包; y; M% m0 u3 U/ W
Scale, 尺度/量表9 U* Z; {/ s" i6 V0 D" N' \9 X$ ?
Scatter diagram, 散点图! c% u" C4 q7 Q' |, k
Schematic plot, 示意图/简图7 C4 n @& S$ v- N9 Q9 Y1 R
Score test, 计分检验
% [7 J& H6 d" P% @1 vScreening, 筛检
! w( K6 x3 i- L% \: RSEASON, 季节分析
* w j* x4 s2 z! d$ n' H% zSecond derivative, 二阶导数$ Y2 }' R7 _9 c1 m# _" p( z
Second principal component, 第二主成分7 S* \: M2 N$ F6 G2 l2 U
SEM (Structural equation modeling), 结构化方程模型 ; `( f X9 B! O8 o/ w7 z
Semi-logarithmic graph, 半对数图
6 N' G- U- u. X9 N7 Y: jSemi-logarithmic paper, 半对数格纸
: F2 r# r" `3 ?) F9 HSensitivity curve, 敏感度曲线) x' f% F' i! m7 D$ W
Sequential analysis, 贯序分析
0 V3 t$ S: V0 RSequential data set, 顺序数据集
- L2 q9 g9 i8 ASequential design, 贯序设计
$ T9 A6 D6 z/ J# fSequential method, 贯序法
$ M. c) X6 q# ?2 R# L gSequential test, 贯序检验法. o0 Z' ]' G4 S& h9 `5 T
Serial tests, 系列试验) j2 r$ p* @+ U
Short-cut method, 简捷法 ; ?* ~; e- G" @' Y% x
Sigmoid curve, S形曲线, Z& r: I8 }1 c* u+ D# z& t
Sign function, 正负号函数 v7 `( Y! |+ b, g9 `/ n9 c0 f
Sign test, 符号检验
4 w: n* c ^5 U h1 Z3 S/ `5 i1 u/ [Signed rank, 符号秩
5 Z/ f' V# y: u3 W) OSignificance test, 显著性检验
( Y e( M- K/ J+ XSignificant figure, 有效数字2 g6 e- I) K; l; t/ @
Simple cluster sampling, 简单整群抽样. _7 D6 ~& N6 S, _6 c6 l
Simple correlation, 简单相关; a' L5 e. V: X/ L
Simple random sampling, 简单随机抽样
! ^, ]7 P4 ]: bSimple regression, 简单回归# G' X8 }# L- a L* ?( r
simple table, 简单表
9 P5 j& b3 n, z6 E2 W. L8 mSine estimator, 正弦估计量- j; j$ K( W) K
Single-valued estimate, 单值估计- F" Z6 {) F' V7 i( _
Singular matrix, 奇异矩阵+ a2 c2 W* L$ |, b. J, t7 r/ s0 J
Skewed distribution, 偏斜分布& F5 g; g( j2 ?, H1 |7 s
Skewness, 偏度
$ ]6 ~0 b7 ^) u W# ?1 LSlash distribution, 斜线分布
; j( g( ]7 Q. R- p: w) }( PSlope, 斜率
/ W% e8 I T9 P; zSmirnov test, 斯米尔诺夫检验
+ g: E" f& R1 {* ~ o: ISource of variation, 变异来源! T& s3 }* |9 G2 d, Z' H' q
Spearman rank correlation, 斯皮尔曼等级相关5 s) j/ {9 m- \
Specific factor, 特殊因子
3 P4 w) i; G1 `; i( k2 Q1 XSpecific factor variance, 特殊因子方差
6 k4 [2 G: O: X4 @Spectra , 频谱: t$ O8 p3 j' |' v
Spherical distribution, 球型正态分布
2 q# }- b2 _4 A9 y: b( fSpread, 展布2 l$ d- `+ i3 a7 K$ I. ]
SPSS(Statistical package for the social science), SPSS统计软件包 p) ^" o0 c" a% A- H0 v, M
Spurious correlation, 假性相关/ D4 f- B- Z6 O) W9 b
Square root transformation, 平方根变换. w( |* r5 K' T) k# W3 E
Stabilizing variance, 稳定方差. }0 [) s7 x' D% | T' Z% ]
Standard deviation, 标准差
$ t) f/ I, M( H+ J: vStandard error, 标准误& N. X/ X. }# S7 R N0 s
Standard error of difference, 差别的标准误. Z* ?3 `! P+ k' Z% \; j! O( c0 K
Standard error of estimate, 标准估计误差1 f# a$ a& X& ?3 U+ t5 A2 s" }
Standard error of rate, 率的标准误
! o% g; |8 ^! PStandard normal distribution, 标准正态分布
9 Y) ]: g6 ~% N: r4 N2 SStandardization, 标准化
, \9 S0 X$ n3 B! \0 UStarting value, 起始值+ d$ H+ t5 e. t, }! }. ]
Statistic, 统计量, U, f, ~) Q: }- n+ b5 i0 K& t+ t
Statistical control, 统计控制/ \ l+ E) N+ l4 t
Statistical graph, 统计图9 R0 P. j$ B+ V$ d" f0 r
Statistical inference, 统计推断
6 F2 s! y" g3 `4 R# T$ g4 d8 i7 gStatistical table, 统计表) V: g# s$ y2 C* `" {
Steepest descent, 最速下降法# q4 O6 V/ v: s3 U. o" x
Stem and leaf display, 茎叶图1 l9 f7 j& S/ j: U. Z
Step factor, 步长因子
% X6 g0 K2 i& p- `4 H1 |& H: LStepwise regression, 逐步回归
, Q: j& z5 g zStorage, 存
( F: W: Y7 W; XStrata, 层(复数)/ g: ^6 w7 k1 s4 _; d/ H+ ]
Stratified sampling, 分层抽样
# H$ P& p+ k' |Stratified sampling, 分层抽样
- A) D* X; _; ]9 D% K! U% T& n6 |Strength, 强度
' s3 F8 d0 p k5 Y! RStringency, 严密性
8 C1 C4 B+ ~8 U1 VStructural relationship, 结构关系# ~/ \; D5 W" @% O$ H W
Studentized residual, 学生化残差/t化残差
# `# B1 F: P1 D \; `Sub-class numbers, 次级组含量
/ K1 \3 L! I$ {Subdividing, 分割
J; e: h4 X% J6 m/ W8 kSufficient statistic, 充分统计量
; p& @/ J, q" @3 m$ T6 l2 ISum of products, 积和
5 e* v, H% l6 {Sum of squares, 离差平方和
# o' j# q8 v$ O# O% c: {& ] D; OSum of squares about regression, 回归平方和. ~ @9 I# i u7 P0 A
Sum of squares between groups, 组间平方和2 {2 s {/ g8 t$ A X$ Q, D- ^0 g
Sum of squares of partial regression, 偏回归平方和
$ K* H, F& r: ?' J% ~( E' H8 n' fSure event, 必然事件7 N" O$ O+ b0 O3 [
Survey, 调查
- E5 D. |/ R+ DSurvival, 生存分析) C) b8 X: D6 s: q
Survival rate, 生存率2 R: o& H: h$ k/ _0 [6 S8 C
Suspended root gram, 悬吊根图
* @( I$ a/ h4 R6 F$ n& F6 b7 tSymmetry, 对称
* t2 h( f! f/ v" N) X' WSystematic error, 系统误差/ b6 k- N0 h3 H: H+ q/ K
Systematic sampling, 系统抽样( v1 C1 H9 C+ y( ]( Y0 `
Tags, 标签
: P4 `% K( U! E5 {6 FTail area, 尾部面积
- P& ]& O0 D; N9 o: m6 D- MTail length, 尾长+ z; f, p+ B) E
Tail weight, 尾重
! M4 S% v3 a& ~7 gTangent line, 切线
7 o( i7 w; b! TTarget distribution, 目标分布
' }6 }8 {% _: L* D, z" f9 M8 LTaylor series, 泰勒级数
" @; X& S b: i2 m+ b( |Tendency of dispersion, 离散趋势6 f1 }4 [( Z# Q8 _4 L* {& C' T( J
Testing of hypotheses, 假设检验1 X0 Y( S- u$ f4 ~6 b2 S8 O- @
Theoretical frequency, 理论频数; `/ t. t$ A+ r
Time series, 时间序列
/ c, p% S, m' T4 OTolerance interval, 容忍区间
) ~. T8 L2 v# J% I0 X5 U4 tTolerance lower limit, 容忍下限
7 E, q, C& a) q( c$ PTolerance upper limit, 容忍上限
; `8 \& ]) k5 C8 ~* |: ^% e8 e* B6 i; A ^Torsion, 扰率- D/ x# l7 ]1 Z
Total sum of square, 总平方和
* Y9 b$ B x1 P6 u& JTotal variation, 总变异! }1 t6 W4 c# A
Transformation, 转换 g2 X9 ~3 }9 } e
Treatment, 处理* o0 X' n- @. S ~( Y" V+ x
Trend, 趋势+ n4 x: X7 j: _- |1 V" L3 V
Trend of percentage, 百分比趋势$ @( i$ a* {) i
Trial, 试验2 _1 Z8 u* a( r) \
Trial and error method, 试错法
2 T2 \6 ~, Z% zTuning constant, 细调常数: `% \* U& @2 Y, C1 s
Two sided test, 双向检验
7 ?4 a+ ?: z" Q" FTwo-stage least squares, 二阶最小平方2 A" Y& A* z: u% a) k$ `; M
Two-stage sampling, 二阶段抽样
& M$ V+ k% W+ }8 J2 sTwo-tailed test, 双侧检验9 E$ G" s* S9 e8 i7 n3 I7 C
Two-way analysis of variance, 双因素方差分析+ V1 }& ]" }$ Y$ x! j, M
Two-way table, 双向表
. |; O( K- A8 _) }Type I error, 一类错误/α错误
9 r# P+ T8 q* wType II error, 二类错误/β错误; A5 |( _9 x `
UMVU, 方差一致最小无偏估计简称7 m. f! X+ P/ W% y6 s$ B
Unbiased estimate, 无偏估计: E$ q4 \5 z2 X7 j- g
Unconstrained nonlinear regression , 无约束非线性回归+ \" m) e& D. X+ }2 A" j5 g( k
Unequal subclass number, 不等次级组含量
& F! V) i$ F7 K1 V c8 m$ F$ MUngrouped data, 不分组资料+ D/ T0 x) M: d
Uniform coordinate, 均匀坐标
5 D: P5 X; j2 MUniform distribution, 均匀分布
/ ^0 x9 X% _6 x0 B0 f L3 s& K5 yUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
. Y6 b4 W$ E; SUnit, 单元4 e+ x' |& V( v- J) a( J8 z8 t
Unordered categories, 无序分类
8 E& X! @6 U& N) ], [, e! w& ?" JUpper limit, 上限4 F2 z# a$ G6 y N& i2 u3 R
Upward rank, 升秩
3 G( e8 c3 G2 t; vVague concept, 模糊概念: j* O7 z3 M- u+ Y
Validity, 有效性
9 j6 }( I6 ?8 F# o, _! Q8 aVARCOMP (Variance component estimation), 方差元素估计8 D* n u; n4 `; O
Variability, 变异性0 j: Y- C5 ^ _* P+ m7 o) [) B& r; E
Variable, 变量! ~/ ^2 |/ a, X$ y4 X
Variance, 方差5 D! U- L+ \% _$ W M! D' f
Variation, 变异
4 K( n& z J9 @/ R9 r" y. gVarimax orthogonal rotation, 方差最大正交旋转) I, c$ N$ Z0 @3 `' p7 e2 ^ D
Volume of distribution, 容积5 q3 s) P) `1 W4 W l* E1 Q" m7 O
W test, W检验) b0 L/ y* q! g
Weibull distribution, 威布尔分布- K* c# B' H1 M( S6 n) z
Weight, 权数
* }0 m2 q; ]/ {2 F: m2 j5 lWeighted Chi-square test, 加权卡方检验/Cochran检验
' J# @7 ]# u6 S1 f6 f& _Weighted linear regression method, 加权直线回归
$ R* q. s2 Z5 L9 E9 Z6 uWeighted mean, 加权平均数" l6 R- \/ [: w: T6 C6 i
Weighted mean square, 加权平均方差
, k$ u, p6 ]) r( y, A' ?Weighted sum of square, 加权平方和/ e% z( ^) j- ?( s
Weighting coefficient, 权重系数2 P! U3 g, o8 L" X
Weighting method, 加权法
- m* }8 e) i+ A1 h9 a$ kW-estimation, W估计量
: B" d2 }; @1 DW-estimation of location, 位置W估计量
+ N% |! |1 [* ~# R- pWidth, 宽度
( Z+ t* m( F- AWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
3 s5 k+ X$ n) {# gWild point, 野点/狂点! j/ d" x7 M; C5 @. ?# ?4 n( s- f# v
Wild value, 野值/狂值
5 ^# R, o6 H8 P0 PWinsorized mean, 缩尾均值# @! r+ |" G# L) [
Withdraw, 失访
5 o) x$ F/ s5 ~# B" Y) QYouden's index, 尤登指数
# b: s6 Y5 G/ t' T3 x; M2 g5 r" _- U9 [Z test, Z检验6 k) b3 ]! d$ S: B! d- W) w- V+ y
Zero correlation, 零相关
& V+ l: ^% g8 L9 Q, r3 F! pZ-transformation, Z变换 |
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