|
|
Absolute deviation, 绝对离差
) z7 i5 l0 t' FAbsolute number, 绝对数
( W) v0 x, v& t6 R! TAbsolute residuals, 绝对残差" ]7 K' V: l" J& ^8 F2 M7 N, l
Acceleration array, 加速度立体阵
5 N- I* K* h6 F; G" W% ?8 q+ AAcceleration in an arbitrary direction, 任意方向上的加速度
9 s( C# `2 t7 _/ s" r# sAcceleration normal, 法向加速度
9 c$ X3 P9 T9 K; |7 O2 [1 U( gAcceleration space dimension, 加速度空间的维数6 ]3 i7 K# k5 `$ z ]
Acceleration tangential, 切向加速度
# [9 h. T. Y `3 HAcceleration vector, 加速度向量
+ Y# c) E& @2 _' \" t% {Acceptable hypothesis, 可接受假设0 X+ ?2 F$ P0 U! R: @( h
Accumulation, 累积& |9 ?# Q/ C) K% X; D
Accuracy, 准确度* j) ]3 B" G U' b0 K! J
Actual frequency, 实际频数) R) u. v- g' K' e! P! y
Adaptive estimator, 自适应估计量
; t5 c# q2 |4 m3 G% M' A1 W3 FAddition, 相加' m* }4 {7 s9 V4 @( D, l. v
Addition theorem, 加法定理
# b) O# ]* Y& H% Z: R6 Y; kAdditivity, 可加性
4 K. g( I' I1 ^5 D7 EAdjusted rate, 调整率0 b8 R1 w4 P7 ]8 z* @
Adjusted value, 校正值& T3 p, h' H& Q4 B6 y
Admissible error, 容许误差0 [. N# K9 e. ], O
Aggregation, 聚集性
1 A( G! J& h% f( u+ z1 D0 o gAlternative hypothesis, 备择假设
7 k- o6 P( G# |# P. R5 sAmong groups, 组间
/ J+ o" k/ `2 tAmounts, 总量# y! m- h$ H, N; X
Analysis of correlation, 相关分析) @ f$ A' @. u
Analysis of covariance, 协方差分析
" X% c4 |" ^3 c5 a* `9 CAnalysis of regression, 回归分析* m& M2 a7 o! ^" ]5 L3 \
Analysis of time series, 时间序列分析
: Q- V) m7 M# y) CAnalysis of variance, 方差分析
$ q |% c' n+ ]5 nAngular transformation, 角转换! ^1 M+ o3 m P4 I* d
ANOVA （analysis of variance）, 方差分析
6 n" G, E; h+ \% C' z' P+ ]# PANOVA Models, 方差分析模型! Z( h. r/ J, J3 o* w! \$ u
Arcing, 弧/弧旋
8 j. C$ p! {+ H o5 w& tArcsine transformation, 反正弦变换
$ X% j4 Z4 y( gArea under the curve, 曲线面积: W/ y' F: a2 o
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 6 j9 S6 U: o/ P1 t' q( t# B1 Z
ARIMA, 季节和非季节性单变量模型的极大似然估计 & G* R3 g( \' o; v* h1 h m( C3 M
Arithmetic grid paper, 算术格纸9 [; x$ G6 _! W+ e) u0 q
Arithmetic mean, 算术平均数
' I. b# r+ L' K1 H2 `" ^2 FArrhenius relation, 艾恩尼斯关系
. ]$ B. s8 C* |* u/ ZAssessing fit, 拟合的评估& q+ q0 D, |, J
Associative laws, 结合律1 b/ S% L( _6 Z. i3 M
Asymmetric distribution, 非对称分布# p; {3 i7 O2 `
Asymptotic bias, 渐近偏倚
P" C) ?! H& B. ]) a, N" Q, I( cAsymptotic efficiency, 渐近效率; P/ K2 V) A; ]5 _ u Z! ~
Asymptotic variance, 渐近方差
1 ?/ H7 _7 {! H/ ] [Attributable risk, 归因危险度
* s; C7 c" I$ `/ \Attribute data, 属性资料
% t- }, ?0 e" l! Q6 f5 z _Attribution, 属性1 A7 F @" _( k( j& ^' C
Autocorrelation, 自相关
5 O" L9 H+ _! D2 v$ e% S6 n$ VAutocorrelation of residuals, 残差的自相关
$ Z$ i2 o7 l$ Q( S- Q* cAverage, 平均数
& d9 V/ D3 m+ I; @& qAverage confidence interval length, 平均置信区间长度
% W; \* W4 W3 T$ x5 V8 |Average growth rate, 平均增长率/ o% J' C' g* w+ Z6 Q" L
Bar chart, 条形图. Z% R( O$ y; w% Y$ K
Bar graph, 条形图
2 |- }( Z; V, z) j# Z. h, V6 o. ~Base period, 基期 h1 O6 w, D! A* V# B
Bayes' theorem , Bayes定理
* B9 R9 l' h+ _% z8 e$ p5 ~5 QBell-shaped curve, 钟形曲线
: J1 h# O) R) {* n8 ?$ ]Bernoulli distribution, 伯努力分布
9 O# C) U' q" G; T3 JBest-trim estimator, 最好切尾估计量
3 \- W4 U+ w3 R. ?8 h% H4 v1 \* F6 {Bias, 偏性
- Q9 q9 a0 o% o1 z) W0 mBinary logistic regression, 二元逻辑斯蒂回归
: h$ H" C( f! X O6 c& g: gBinomial distribution, 二项分布1 E) C) K; [ r2 e) [8 f
Bisquare, 双平方
3 b# t0 r6 l* c/ DBivariate Correlate, 二变量相关- \7 G" y2 d- B: v% U
Bivariate normal distribution, 双变量正态分布
' a" J4 D; E6 x5 X' d$ D7 W( GBivariate normal population, 双变量正态总体+ a" ?+ v$ Y0 z7 e
Biweight interval, 双权区间) T2 k1 c2 W) m0 y) `
Biweight M-estimator, 双权M估计量
+ \" L" J7 m/ i6 w) n. XBlock, 区组/配伍组
$ S( h: Y( Y( }" ^, Q0 iBMDP(Biomedical computer programs), BMDP统计软件包/ }! o3 ~1 ~3 Q5 O+ _
Boxplots, 箱线图/箱尾图
# }6 ~- k7 _ S4 w. ]0 uBreakdown bound, 崩溃界/崩溃点7 }; O2 B& r4 ~- ^- S6 Q( \
Canonical correlation, 典型相关' Q# O. h3 c, `# k9 y
Caption, 纵标目
5 s7 u4 h. X% k" ^) aCase-control study, 病例对照研究, [( ?0 e: `/ n) C6 T( [9 b) n
Categorical variable, 分类变量) q# C0 p( o @/ E) e. ], ]0 H
Catenary, 悬链线4 |, R7 v' L8 u2 I# ]
Cauchy distribution, 柯西分布
4 a/ a. B0 \% g) l) \9 Y7 aCause-and-effect relationship, 因果关系
& K9 S) h J/ x5 k+ P p, _6 K+ bCell, 单元1 c4 b5 a3 T/ Y1 x! F
Censoring, 终检 t! F7 u" q* |" E# {
Center of symmetry, 对称中心8 Z: |# P4 R9 e# P
Centering and scaling, 中心化和定标3 x+ r0 `4 c1 u4 \
Central tendency, 集中趋势
' [. A8 c6 v( q8 ]' r4 {* U5 vCentral value, 中心值
# O# @5 b8 E& w8 m Q; B8 s7 jCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
6 W! J6 c4 i$ j- e( UChance, 机遇9 ~- s& f1 h% P1 i+ \. }
Chance error, 随机误差
/ c* E/ G8 R" wChance variable, 随机变量
. F! j* m) S$ eCharacteristic equation, 特征方程 k* W! x, v7 [! I1 T/ Z# c# c
Characteristic root, 特征根
+ S$ N2 n( P. G }4 p8 zCharacteristic vector, 特征向量
6 |$ p3 s3 r+ {( ZChebshev criterion of fit, 拟合的切比雪夫准则
* O. H! T% I/ |' [5 p' R5 |* W! OChernoff faces, 切尔诺夫脸谱图
& x+ |$ @& y1 \Chi-square test, 卡方检验/χ2检验
- E0 l9 k4 v2 JCholeskey decomposition, 乔洛斯基分解 Y! t/ k: {8 u* @) b% {3 d/ B4 Y
Circle chart, 圆图
2 w% H" \9 @' G a& ^) h8 h# _Class interval, 组距
; `3 v8 U& t. z* P! I/ V/ oClass mid-value, 组中值$ U8 m6 W0 f$ D2 ^ ?: P. k
Class upper limit, 组上限1 t" A. H; F; H0 B- j2 E4 a3 s
Classified variable, 分类变量
4 P9 ]0 L9 s- @( n O9 ECluster analysis, 聚类分析# h/ Q$ G# F' j$ ]
Cluster sampling, 整群抽样 R F/ L8 o# V% t" y; i
Code, 代码. ?5 O3 {9 P+ W8 j# c
Coded data, 编码数据$ {' [" _% {( R$ i
Coding, 编码) M( H5 N' ?( c5 E v1 i8 @
Coefficient of contingency, 列联系数7 A4 C" F U* M; G0 v$ e9 ]
Coefficient of determination, 决定系数1 T3 H0 _8 A" c0 ^5 _ n& `3 W$ @
Coefficient of multiple correlation, 多重相关系数: _/ Z7 a" L" q, B3 g b
Coefficient of partial correlation, 偏相关系数. A, s7 z+ j5 @) m2 m
Coefficient of production-moment correlation, 积差相关系数
: [5 l1 v5 a! }) e" f4 P$ z BCoefficient of rank correlation, 等级相关系数) D L6 J2 z; O9 P7 b
Coefficient of regression, 回归系数2 w, P# ~4 s2 {+ w
Coefficient of skewness, 偏度系数$ M4 ~" b" d3 m3 H8 Y6 S5 E4 N* R& V
Coefficient of variation, 变异系数
. x/ T: `/ G- P5 o2 T6 }1 hCohort study, 队列研究
2 W# K* N1 M( O6 ^7 q! D7 SColumn, 列8 b) N3 W3 C% b* F" G- N
Column effect, 列效应# d) v# j1 q3 Z# U4 p; V% G1 f
Column factor, 列因素
4 F0 X) C+ l( r* V' x( W4 pCombination pool, 合并
( Q! A) ? g/ C7 Q& pCombinative table, 组合表
. I5 \+ b3 i2 UCommon factor, 共性因子
2 N6 F: q+ A! xCommon regression coefficient, 公共回归系数0 U2 Y& K$ Z1 u) t6 \0 h9 y3 b% A( S; `
Common value, 共同值
) O5 B' ]/ P5 p- DCommon variance, 公共方差
8 H- a" b$ Q6 G5 Y+ nCommon variation, 公共变异
+ `' J, \' W: z0 ~; h! |7 L) FCommunality variance, 共性方差
. m4 D p- {, d' KComparability, 可比性
; O9 Q2 d! W5 l2 M1 LComparison of bathes, 批比较- x# ~6 x* q; a
Comparison value, 比较值
3 O( ^1 t9 ~& B2 Q k( oCompartment model, 分部模型
; f- g$ g L7 D/ n( QCompassion, 伸缩
) i$ V6 G" r" y4 O" S5 E2 B& G! o4 ?Complement of an event, 补事件' y) O* [4 O6 J3 w1 l& B
Complete association, 完全正相关
+ g1 [9 c1 _# c- P$ J$ iComplete dissociation, 完全不相关5 h, V" O: M2 o& P- S
Complete statistics, 完备统计量
/ b4 k# a% ~$ R l4 `% V( j$ fCompletely randomized design, 完全随机化设计
3 A' R; A0 }( C* `3 zComposite event, 联合事件
- z3 o, y- c6 v: ?. q* K l# dComposite events, 复合事件
' O6 D. e; S5 x% z$ y/ z% }5 z% M% X# PConcavity, 凹性8 @3 l* U5 M# s" z9 O4 V4 E5 R
Conditional expectation, 条件期望; c1 x& F4 E3 r. Z' g, i2 S
Conditional likelihood, 条件似然
x+ x* T; v! k. y. XConditional probability, 条件概率
( h+ t m$ z/ l/ f) aConditionally linear, 依条件线性$ d6 S* M! n$ t2 G
Confidence interval, 置信区间
! T* L( B: z5 W1 I+ ~Confidence limit, 置信限* ~* f$ d$ O* Z. f" W3 O
Confidence lower limit, 置信下限5 P+ w5 I c$ h* m w& d$ N
Confidence upper limit, 置信上限$ M/ t8 j# f6 E+ G/ H
Confirmatory Factor Analysis , 验证性因子分析
# i {5 h- f$ C: xConfirmatory research, 证实性实验研究5 N4 O; R$ F% i- a
Confounding factor, 混杂因素6 g# W+ R+ P+ I$ x w
Conjoint, 联合分析" x D+ g, I, g, ^
Consistency, 相合性. u8 F1 W' G7 R& O( ]
Consistency check, 一致性检验- b- \6 E) F( b5 L
Consistent asymptotically normal estimate, 相合渐近正态估计
6 r5 G6 U! A0 L" MConsistent estimate, 相合估计' v8 V* B# R' N* I y6 I
Constrained nonlinear regression, 受约束非线性回归
j6 _6 C4 C X+ B1 iConstraint, 约束
& f! i1 E$ _$ d- N- H) c9 F+ YContaminated distribution, 污染分布* g9 p/ G$ {4 P) b
Contaminated Gausssian, 污染高斯分布
8 n" `6 h1 \8 J3 m3 {2 b" DContaminated normal distribution, 污染正态分布* _9 v% L8 b; B" T& d
Contamination, 污染
9 [4 `3 L+ g0 B- z6 E) ~Contamination model, 污染模型
3 g! ], M( z3 p+ c6 eContingency table, 列联表
8 b, i) m: W7 g2 s, B( [' F0 I; W/ EContour, 边界线, j5 S9 E! t3 A8 ^7 t
Contribution rate, 贡献率0 G4 \& T6 _. p
Control, 对照( _* _/ B( I. u1 A- U+ H
Controlled experiments, 对照实验
! C. p! {# L6 H+ Y. I" V! yConventional depth, 常规深度
# v! X4 j8 }2 h. U `Convolution, 卷积
2 Q: `9 S9 J& Z3 qCorrected factor, 校正因子
& p7 g; d% d- G- I! ?6 f6 C; SCorrected mean, 校正均值
* u; U0 N8 V9 z0 [9 i5 qCorrection coefficient, 校正系数
% V% S: J( @* I0 g2 ICorrectness, 正确性
; S5 p+ W- w* Y% SCorrelation coefficient, 相关系数
% K& B4 ^6 S# rCorrelation index, 相关指数; \- {8 q& z" j+ E1 ?: v! E
Correspondence, 对应5 [2 ^7 Y; M: n- \8 P- v9 f, P3 ^
Counting, 计数4 M, w+ K& i+ y$ e+ P5 V1 f
Counts, 计数/频数! I% W& \3 i0 ]" ^2 b; G% k+ `0 S
Covariance, 协方差1 x: Y; `% N) X" @$ q
Covariant, 共变
8 S& g! c' j" H$ y3 n" ACox Regression, Cox回归2 z# Y1 J3 D& E0 R7 e
Criteria for fitting, 拟合准则
) l, y! f8 ~7 @" c d& r0 i$ L1 HCriteria of least squares, 最小二乘准则- _. j% ~/ b7 o+ E9 A) [
Critical ratio, 临界比- b7 o. P$ u2 x
Critical region, 拒绝域/ O; G8 a* x% N9 i- ^
Critical value, 临界值
6 a1 n& D0 S" C! @( ~& U) `Cross-over design, 交叉设计
3 F5 _4 I: Y, W$ ECross-section analysis, 横断面分析" D# c: ` z. ~- g& }4 i" t
Cross-section survey, 横断面调查1 q7 s, t* d4 v5 t [! r/ N
Crosstabs , 交叉表
8 g1 k# t& T2 y) x8 t4 v8 Y1 DCross-tabulation table, 复合表
8 G9 l9 R) `0 \& FCube root, 立方根
! H* f( t, }$ m V9 hCumulative distribution function, 分布函数
. q6 a7 \/ ~' _% V+ SCumulative probability, 累计概率0 m. M }- V# s8 f7 l
Curvature, 曲率/弯曲
; k' T0 J+ w8 j+ y0 s" j4 rCurvature, 曲率- E) E" ?$ M8 A; _# O9 Z* n
Curve fit , 曲线拟和
# x6 p6 x- g& `" _5 |Curve fitting, 曲线拟合. E3 O* ~ ]2 @
Curvilinear regression, 曲线回归( x2 B/ R ^0 ?; Q) Y( ]! A
Curvilinear relation, 曲线关系8 e4 J& X6 m8 A& d
Cut-and-try method, 尝试法' M+ J& c1 G- a9 ?8 f a n+ _# x; Z7 E
Cycle, 周期
2 P5 B1 ~& R0 q5 OCyclist, 周期性
# Y. M6 h% c5 I! ]; ~+ yD test, D检验
& y& t8 ?: T7 ~& f. [Data acquisition, 资料收集0 W4 G" w; H0 e& h" _5 o" t j$ O
Data bank, 数据库
5 b4 v* U+ D3 U! @5 p4 JData capacity, 数据容量
0 g9 x/ x! [3 sData deficiencies, 数据缺乏1 k) [) l& U- B2 D h1 ?* o
Data handling, 数据处理
/ M. Y8 o% D$ H( V oData manipulation, 数据处理5 M4 L8 C+ U: ]" P/ B7 B' g
Data processing, 数据处理" |( Z# o2 p/ M2 w) x4 o0 d- O
Data reduction, 数据缩减# k, y/ ?2 B; ~; H0 C- |3 B9 T
Data set, 数据集
0 L$ u) \5 }$ j( F, N" T4 K4 e& {Data sources, 数据来源5 G3 d' R7 |' i+ R
Data transformation, 数据变换
; T9 ?( h% H6 I. M3 EData validity, 数据有效性% c% [- s# _ f4 I5 U
Data-in, 数据输入9 ?- }' ?' t$ K/ {
Data-out, 数据输出
~- z/ q; ? f: t# P3 ]" EDead time, 停滞期/ e; T$ m1 R9 W$ t- H& l% w
Degree of freedom, 自由度( B% g* S% {* e/ X$ W3 F% o; {+ q
Degree of precision, 精密度
; {, D# [4 @/ g4 bDegree of reliability, 可靠性程度: g; F, `6 w; i: o5 e( ]% u2 n
Degression, 递减" b- q l9 H3 ~4 e
Density function, 密度函数
7 Y7 X, G* E$ G# G& V* Q. RDensity of data points, 数据点的密度
~9 P1 o3 u, xDependent variable, 应变量/依变量/因变量. a; Y! q5 Y7 R" ?. U$ ?: O. |$ ^) k
Dependent variable, 因变量+ q# j0 t* X2 e
Depth, 深度
- X# D# {$ W( D) ~Derivative matrix, 导数矩阵
( e( E m+ V# G/ |5 _: ?3 `0 f! V$ LDerivative-free methods, 无导数方法
8 T% H& k3 d) n7 r, _+ d. kDesign, 设计, [+ t0 c. U( [* ]7 K7 R
Determinacy, 确定性# A9 x2 f1 a& m7 l4 c0 b! n5 Q0 U
Determinant, 行列式
+ ]. N# _7 @, |( I7 W5 Y- _6 mDeterminant, 决定因素4 X% [+ }! t. }7 Q1 s0 |$ m! J
Deviation, 离差
# {+ S5 L9 m7 J$ y6 X$ LDeviation from average, 离均差5 o9 i1 P9 `+ w' N$ U+ u
Diagnostic plot, 诊断图' L# m) ~8 r- ]& ^. C4 h. W2 ?# q
Dichotomous variable, 二分变量
9 w4 ^- e1 Z- B- ]Differential equation, 微分方程) ~6 `& S% w6 w8 _; B1 N, y: P
Direct standardization, 直接标准化法
. V; t- l9 h8 S! Q: ZDiscrete variable, 离散型变量
/ a5 U( g( |2 lDISCRIMINANT, 判断
: A! f/ N' b: j6 @/ N2 NDiscriminant analysis, 判别分析
7 e0 x* A6 ]) z7 O% FDiscriminant coefficient, 判别系数1 T6 J! M: N( |& _- e/ f. C" c) g
Discriminant function, 判别值8 L+ X9 }! _# p9 @& I0 i4 W/ }
Dispersion, 散布/分散度7 \8 p: ^9 B w( @- J9 e/ o, S/ R; g
Disproportional, 不成比例的
K$ ]8 n/ K& H3 d+ z9 MDisproportionate sub-class numbers, 不成比例次级组含量3 s# l& U( F5 V. N0 Y7 k, [. v @
Distribution free, 分布无关性/免分布
1 d* I; f# k$ ?, r6 v: [% QDistribution shape, 分布形状
& J6 K+ t; l. D6 h) z/ K5 d- \Distribution-free method, 任意分布法
( z2 p- ~1 D( ^5 m2 a0 S5 EDistributive laws, 分配律 b% v1 N) D, `) @
Disturbance, 随机扰动项
' P& |$ s% g \0 k0 l/ kDose response curve, 剂量反应曲线
) j# ^ R+ W! D2 O" L- ~0 d5 m5 \Double blind method, 双盲法( B. e. K; }: U5 d' [7 I9 H% D
Double blind trial, 双盲试验. ^3 Q' s5 Y$ `& D; q
Double exponential distribution, 双指数分布. T/ Q; [6 d3 b8 i9 T$ O0 f, o
Double logarithmic, 双对数
6 J7 s) ~6 @* u( _# a! PDownward rank, 降秩
; K( M! L3 N: {, o6 YDual-space plot, 对偶空间图
0 Z% z) S5 |1 G+ G9 Y) bDUD, 无导数方法 l) l% y+ P1 @/ j. A# o9 v& v
Duncan's new multiple range method, 新复极差法/Duncan新法# N5 L2 s+ Y! ^5 U+ j+ }3 W
Effect, 实验效应
, l9 P8 y3 B& T9 pEigenvalue, 特征值2 u$ r8 [4 a: h: A; W
Eigenvector, 特征向量
a3 i/ ^0 C& j" e& F7 @1 fEllipse, 椭圆
: F% E+ H# C- x+ U* R/ ]Empirical distribution, 经验分布
! J9 C+ Q* i, d8 c) ^Empirical probability, 经验概率单位
) t; F" Z+ x% pEnumeration data, 计数资料1 ?' u- H* p) l: {/ v0 n$ m
Equal sun-class number, 相等次级组含量* ]" K2 ~; T1 }1 V) l# i5 p: Z( g+ k
Equally likely, 等可能
& M7 y& }: q) I! ^7 p0 ]Equivariance, 同变性
* W. H' ] p8 \5 G# }; ~Error, 误差/错误
+ i1 [$ X6 f2 A" w5 I9 s' J2 x5 zError of estimate, 估计误差
# y! x d' D. v2 B; d" YError type I, 第一类错误
: ]! Y5 o5 K$ }8 y' \Error type II, 第二类错误- W$ D4 x+ K A) `
Estimand, 被估量
) ]7 N9 c" D/ Q! w. mEstimated error mean squares, 估计误差均方! c5 E1 h% l* D
Estimated error sum of squares, 估计误差平方和- \ J8 u6 V! k# Z5 ~3 i+ T
Euclidean distance, 欧式距离0 y9 D' G" r, ]! U4 E3 Z
Event, 事件
7 J5 X0 ^ X- [! x q9 g! pEvent, 事件- r% k# C& \# T- I
Exceptional data point, 异常数据点
. c1 n( W' I/ {- n; wExpectation plane, 期望平面9 W$ b0 p# l8 K
Expectation surface, 期望曲面
- A+ R5 h- R9 d: F3 i9 x# CExpected values, 期望值! E/ j5 U# q b/ ]
Experiment, 实验
/ U! U2 a. i5 v9 sExperimental sampling, 试验抽样; O+ M) v0 b7 R9 [* f% t# |( j$ A
Experimental unit, 试验单位: i5 b! w+ t: u( ^: N2 Z* A
Explanatory variable, 说明变量
6 ?; `2 r5 w* v+ m! n" W6 _Exploratory data analysis, 探索性数据分析
% K+ Y6 s2 W R8 BExplore Summarize, 探索-摘要
( A% \, @$ U- {$ Q; \Exponential curve, 指数曲线* D' C) v5 V4 J1 C8 T6 G+ e& `: `% H; X
Exponential growth, 指数式增长0 Y) G' i s, I7 c' a- w! m0 N
EXSMOOTH, 指数平滑方法
2 Q* q: K6 p& L& ^) g( k3 YExtended fit, 扩充拟合
( N& N4 j) i: C; lExtra parameter, 附加参数
/ \2 N( f6 }* }- }: d( RExtrapolation, 外推法6 ^, \2 X$ L3 J1 n* w
Extreme observation, 末端观测值5 R+ x( j: m9 P0 Y
Extremes, 极端值/极值8 E5 T2 P1 T$ X# q
F distribution, F分布: s0 s1 Z: d5 O" {! K! q. t1 M
F test, F检验5 L A+ |" \) @9 L2 B7 D3 Y! f( [
Factor, 因素/因子
5 k# F) N; E$ F% M( x+ S8 I$ |Factor analysis, 因子分析
/ K4 h: \7 K: T. fFactor Analysis, 因子分析
4 h# E, @8 c$ N7 p' gFactor score, 因子得分
+ q! A8 {9 v6 N0 [9 Y# HFactorial, 阶乘: B9 u- B5 p+ }4 l
Factorial design, 析因试验设计
( \6 P4 N& {& B3 X8 qFalse negative, 假阴性
0 [4 ~1 l% l" @2 d2 }False negative error, 假阴性错误% k ~ ^4 d" T3 @
Family of distributions, 分布族0 N' f! N& P7 T. G; x: J
Family of estimators, 估计量族
/ m" S1 [: g: Q( yFanning, 扇面& \" ^* Y v% a7 l3 A! r( n' P
Fatality rate, 病死率: r' k4 O3 O3 v
Field investigation, 现场调查) X7 o3 y4 I% z6 V' ~0 h( m- w
Field survey, 现场调查
+ X8 Y, N4 j. Z7 ^Finite population, 有限总体
0 K9 N) |: {3 E) t# @& i5 J$ V7 K+ ]Finite-sample, 有限样本) f h$ @7 [6 q
First derivative, 一阶导数 d+ B) s8 ?7 }1 ^6 p
First principal component, 第一主成分* T* V1 b1 g: T: m2 F
First quartile, 第一四分位数3 B6 O- d8 Y2 V& K$ v9 h% N
Fisher information, 费雪信息量& k* z# w' s+ p0 x: m+ o7 E
Fitted value, 拟合值. V0 z+ _5 V2 y/ J% Q
Fitting a curve, 曲线拟合6 e% F6 F( n. F, e5 Y$ M
Fixed base, 定基
& L& \+ q1 m# l) W& P5 ]9 PFluctuation, 随机起伏4 e. O8 Z5 t5 u! t; I) t
Forecast, 预测; Q7 }( ^# V' S
Four fold table, 四格表
- K& ]$ X4 Z" Z& z3 U) N0 c1 vFourth, 四分点" b# R/ i3 x. C2 a7 b5 I, }3 A
Fraction blow, 左侧比率: M# s9 b$ }1 P: a
Fractional error, 相对误差( U6 ?2 M P# y$ z
Frequency, 频率/ G9 N8 {+ \# ]9 s) O- M
Frequency polygon, 频数多边图
8 D7 Q! b. q3 M- Z8 ?$ zFrontier point, 界限点
& K3 Z( ?& l! ^" [9 v3 I- b& r2 ^Function relationship, 泛函关系
8 {( _' C% R! Z0 [- Y5 sGamma distribution, 伽玛分布( i' S) P& e# I `
Gauss increment, 高斯增量 u9 O' d2 `# \5 L, j- d
Gaussian distribution, 高斯分布/正态分布7 j+ w4 o: H9 t8 ?
Gauss-Newton increment, 高斯-牛顿增量
6 R* c7 S- I* ^% @: N9 x9 x- oGeneral census, 全面普查5 Z; L2 L u# k
GENLOG (Generalized liner models), 广义线性模型
( c' T) Q1 {. Q* q+ G" f/ DGeometric mean, 几何平均数9 A% T7 A) z; h u6 U+ V4 p' k
Gini's mean difference, 基尼均差4 w4 r/ X+ c$ t3 G: `
GLM (General liner models), 一般线性模型
* J/ O0 `) G7 S0 s1 z! A1 G: tGoodness of fit, 拟和优度/配合度
3 C) k! d$ Q# `Gradient of determinant, 行列式的梯度
' r5 s' S" c# ]7 o: ]% `/ b0 dGraeco-Latin square, 希腊拉丁方" \1 i! ^. L; Z
Grand mean, 总均值) z4 a+ U+ D3 m0 a& F8 z- _9 r
Gross errors, 重大错误' O2 g6 X0 M$ c8 V
Gross-error sensitivity, 大错敏感度
% x$ R" D+ \5 y5 B2 k7 l ^2 c0 QGroup averages, 分组平均
4 l1 p0 e# i: T$ WGrouped data, 分组资料7 J0 P2 Y# h! q5 q2 O: ~ V* f$ k; Z
Guessed mean, 假定平均数
/ Y- ]) O s6 t+ u4 E6 p7 HHalf-life, 半衰期6 H u, a, m+ p
Hampel M-estimators, 汉佩尔M估计量
! v# Y. m, e$ C2 NHappenstance, 偶然事件
& R4 c7 ~5 ]7 YHarmonic mean, 调和均数
G$ L) [$ R( YHazard function, 风险均数
( E* ?! r3 i1 G2 ^8 sHazard rate, 风险率. N. D& L) A7 c" V
Heading, 标目
& A/ [- p+ z5 A: T3 L8 IHeavy-tailed distribution, 重尾分布
( u* K# L8 Y3 Y9 qHessian array, 海森立体阵+ F& r: s j; L2 R* v' S
Heterogeneity, 不同质/ p. U3 o5 r5 `9 ^: w' C; Z: L
Heterogeneity of variance, 方差不齐 9 e9 }% m( X0 q1 j) i# \& c' g- G) v7 |
Hierarchical classification, 组内分组
' q) o! @" n4 g/ BHierarchical clustering method, 系统聚类法* @4 z0 V8 z: R4 m P4 a
High-leverage point, 高杠杆率点
& v+ `! P. B3 t' ]HILOGLINEAR, 多维列联表的层次对数线性模型. q3 l+ C% ~% |/ O, N8 n9 S
Hinge, 折叶点
1 j5 D; P+ G6 X7 `) jHistogram, 直方图) c3 U( c6 \6 D* J/ o; t2 v2 G
Historical cohort study, 历史性队列研究 + g1 z! S6 |4 X
Holes, 空洞
! B8 ^9 g Q" lHOMALS, 多重响应分析& N. d; e( ?, K! @
Homogeneity of variance, 方差齐性
; g: y/ n0 ^. d6 c& l# fHomogeneity test, 齐性检验5 B7 ?* Y& N2 J! [
Huber M-estimators, 休伯M估计量
9 O7 I, F3 b- b" EHyperbola, 双曲线
6 Y5 R( {$ E; {/ Z) ]# mHypothesis testing, 假设检验
% S: c& A" E$ ^3 ]1 M u- |$ t% ]! qHypothetical universe, 假设总体
. z! `* v1 {. S$ RImpossible event, 不可能事件0 w' ~5 j) H: P$ ]( Z
Independence, 独立性" F" E. y$ w; {% C
Independent variable, 自变量( _6 P' _3 _" B: A
Index, 指标/指数
+ t6 x7 M( r; l/ t3 A% `/ FIndirect standardization, 间接标准化法8 v' C+ ~5 M( P3 T8 M5 r0 n# A
Individual, 个体; H1 }! w" U/ ?; I6 {
Inference band, 推断带
# `* x, m5 j* ?$ C \2 G3 i( \Infinite population, 无限总体, D) O" ]8 j# s" I) a; O/ k2 y
Infinitely great, 无穷大3 T# {7 h6 z! y7 f3 v
Infinitely small, 无穷小4 e8 Z6 O2 `( {/ U6 V/ o% d
Influence curve, 影响曲线
) [. ~3 p& Z9 o! W1 jInformation capacity, 信息容量. G8 {0 L$ B# c" l& o: x
Initial condition, 初始条件
0 N- K+ w3 Z4 YInitial estimate, 初始估计值
* V$ U& W/ H- v ]6 eInitial level, 最初水平
; V. l2 n2 F# F6 f6 {Interaction, 交互作用1 Q( J9 u6 m7 ?/ A- \& {
Interaction terms, 交互作用项+ u7 R) d3 V4 U% O3 S$ o1 C
Intercept, 截距
2 m6 O* {7 [# l9 p6 RInterpolation, 内插法
3 Z# R3 ]5 t! s2 r3 @9 K5 x( MInterquartile range, 四分位距. z2 [8 b7 ^0 C( S
Interval estimation, 区间估计' {6 ]6 V: W6 P5 u8 w6 n8 m8 M$ X
Intervals of equal probability, 等概率区间- l) ^1 Z+ u3 |" h7 f3 `; q' i
Intrinsic curvature, 固有曲率2 p. T; w2 M7 V, y) {; T7 i
Invariance, 不变性
+ Z6 W2 s- i; F3 k' @9 \1 t/ P& {Inverse matrix, 逆矩阵& N1 o$ g" S" F6 y1 z9 P
Inverse probability, 逆概率8 O% z' e( k$ P' m
Inverse sine transformation, 反正弦变换
. p! ~, Z+ l* X \) IIteration, 迭代 ! }8 M. [4 _% t8 ~& F9 M% ]
Jacobian determinant, 雅可比行列式% c5 ~- _$ I. G! C4 r5 l3 ?' Q2 @
Joint distribution function, 分布函数: Y: t! Y; I/ h, n0 m- p
Joint probability, 联合概率
2 [( \$ R7 E/ v' _Joint probability distribution, 联合概率分布
) Y3 x% b* P% N2 c9 R) I" \K means method, 逐步聚类法- f+ {1 ?; O1 N2 t0 X0 Q4 Q* ^
Kaplan-Meier, 评估事件的时间长度 6 e. }/ b) \7 C" |8 {& T
Kaplan-Merier chart, Kaplan-Merier图) [! j B8 M* O {* s7 `
Kendall's rank correlation, Kendall等级相关- T! R2 G: R b% t8 L F
Kinetic, 动力学9 e9 l( e6 W- f* k: L6 c+ @
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
& A/ u9 Z3 c$ q/ ~6 [6 ?8 mKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
2 p v4 Y& k# n1 ]: xKurtosis, 峰度: L. `3 ?6 ]$ o+ \1 L* @
Lack of fit, 失拟2 P9 Q3 s& [# L& Y
Ladder of powers, 幂阶梯! z' n$ |- x8 N( m4 P4 O: p
Lag, 滞后3 ?% s( t$ w( ]0 S
Large sample, 大样本, L( V6 t( c1 c: e+ o3 M6 w+ ^& w( l
Large sample test, 大样本检验
' c0 {/ S& t. f% l, oLatin square, 拉丁方
" j2 S4 X1 i. A* V* q5 J& X$ f mLatin square design, 拉丁方设计3 m! ~- y, L) D6 }! ^) v9 G
Leakage, 泄漏
2 T# T- p0 r5 M! |Least favorable configuration, 最不利构形
4 H' J. U+ f, ~+ x1 s, c' wLeast favorable distribution, 最不利分布# I, k, r4 S9 B9 z9 \
Least significant difference, 最小显著差法
) Q. x( i% ]% B9 n8 L& Y& F3 ~# l1 NLeast square method, 最小二乘法 v5 i$ ]! o" n/ D" ]$ x+ |
Least-absolute-residuals estimates, 最小绝对残差估计5 s* H$ c5 H9 C) Y; v
Least-absolute-residuals fit, 最小绝对残差拟合! `3 D2 b% z7 `3 s% U
Least-absolute-residuals line, 最小绝对残差线
+ V( z. }. ^0 u* O( q( b: {. [Legend, 图例
7 S$ B, N Y, i5 P; p+ qL-estimator, L估计量
* S7 F$ D+ Z% ]# ~* R cL-estimator of location, 位置L估计量
2 a+ C) \- g9 R, [% i7 ML-estimator of scale, 尺度L估计量( j) K b9 d9 [* x# ~$ Z
Level, 水平' H( q! I* s m% Z- y w0 ]8 K
Life expectance, 预期期望寿命
4 R9 @3 j- i* v$ s* c" W1 A1 [+ XLife table, 寿命表7 I2 S% o& O# ]6 @
Life table method, 生命表法
+ T& y! C5 `; W4 f' q: W% h* K% iLight-tailed distribution, 轻尾分布9 B. F, a2 A% _
Likelihood function, 似然函数
. U1 g! z3 m) h! XLikelihood ratio, 似然比
0 u; K+ P1 D$ X# T% xline graph, 线图* X9 {4 \$ k" J* p3 M+ x
Linear correlation, 直线相关
( `3 {1 { H: y% q fLinear equation, 线性方程
2 M$ k( O/ v1 W) W. LLinear programming, 线性规划: W& Y6 n; a/ N
Linear regression, 直线回归
$ ?( x' h2 m" B9 r1 {& u# ]1 W! GLinear Regression, 线性回归- z5 H2 G. H( |( f3 ]
Linear trend, 线性趋势+ G6 l1 o* u: J- }3 v0 G
Loading, 载荷
' [ L* c" X. V4 b" r& bLocation and scale equivariance, 位置尺度同变性
{1 F) H6 V: c. ?/ M! D/ T6 rLocation equivariance, 位置同变性
& N8 }5 D( t) v, t6 s) cLocation invariance, 位置不变性+ m% E# s3 ?) y# u! T1 N+ `0 z
Location scale family, 位置尺度族4 I9 J- E6 d& ^: Q4 b1 M @5 m
Log rank test, 时序检验
u! I7 y: M: S' E) |* GLogarithmic curve, 对数曲线/ m2 f- y# h# \+ [6 u
Logarithmic normal distribution, 对数正态分布. t: u; e$ r. F+ O4 N7 s
Logarithmic scale, 对数尺度
: Y3 U3 |* c# \; i/ U' ?7 aLogarithmic transformation, 对数变换# W% \$ P4 q% g. t# T. s# v. X
Logic check, 逻辑检查
. n4 m9 N) z' |) |Logistic distribution, 逻辑斯特分布3 _' i" L0 l9 g9 g' f
Logit transformation, Logit转换4 s3 {" p9 q4 _: t) c
LOGLINEAR, 多维列联表通用模型 & H2 n2 E. V4 `* D6 g" N! R
Lognormal distribution, 对数正态分布$ \0 G% t* N1 \( w7 o; R
Lost function, 损失函数7 {8 H" h4 z* c
Low correlation, 低度相关" {( j; J: \, E
Lower limit, 下限% p* g. ^( [: |/ Y. h. K
Lowest-attained variance, 最小可达方差4 H3 N4 \9 P1 L, B. M1 {+ S
LSD, 最小显著差法的简称. t6 w# V) l; J% k; Y. K
Lurking variable, 潜在变量
( v- X5 e& ~3 }+ `& x( S5 S5 l3 kMain effect, 主效应
" g0 F; ` y ]' b) j0 B' ]Major heading, 主辞标目
! }- J& Q% F) ~* L: D7 [& ]Marginal density function, 边缘密度函数
/ H# L h( @, r/ dMarginal probability, 边缘概率
1 U) C( E. ` L/ B7 JMarginal probability distribution, 边缘概率分布
: {8 J# a# C7 I6 M( k& iMatched data, 配对资料
. i {$ o( F2 E- FMatched distribution, 匹配过分布- W* [/ i; C1 r" G0 L( O
Matching of distribution, 分布的匹配
3 k% C4 W& _/ U0 gMatching of transformation, 变换的匹配, e. H! `/ o( z* F7 h# t
Mathematical expectation, 数学期望
1 J7 N$ m9 V$ C( b, _Mathematical model, 数学模型
+ [; |+ u* i) i: T' V2 I3 h) m& K TMaximum L-estimator, 极大极小L 估计量8 M* G0 p: Z+ v; a, ?7 R' \
Maximum likelihood method, 最大似然法; z' w9 b/ M+ L0 ^; v6 j# N# }3 {
Mean, 均数; W; y4 U9 b/ k, h; I; C1 D
Mean squares between groups, 组间均方
; f/ O2 H( L- k+ E- lMean squares within group, 组内均方 a) ?7 V) _6 ~
Means (Compare means), 均值-均值比较
3 [: f' H) Y! I2 p; |, B8 \Median, 中位数- I) ]8 e' l. c/ ?2 \0 O+ t
Median effective dose, 半数效量
& y8 U6 G* N4 uMedian lethal dose, 半数致死量6 [$ O f0 p' m8 ~* ~, K
Median polish, 中位数平滑
+ B Z. y. ~$ L$ @; S* e FMedian test, 中位数检验7 E3 ]: H7 E1 B4 ]1 W2 \
Minimal sufficient statistic, 最小充分统计量- U1 w" C( x1 P$ S" j; e+ q
Minimum distance estimation, 最小距离估计- D% N: `1 M% y+ R
Minimum effective dose, 最小有效量
7 ^2 ^. a7 w4 w e. m# BMinimum lethal dose, 最小致死量
) I- h/ @9 O2 U$ SMinimum variance estimator, 最小方差估计量8 c; I9 k) F7 `! ]. M6 K
MINITAB, 统计软件包+ v- B5 A8 ]& ^
Minor heading, 宾词标目; R) c( u" n6 G4 A1 i( `; V
Missing data, 缺失值- B3 K+ {$ g, k& Z0 w) r
Model specification, 模型的确定9 q5 Q2 ^/ |1 o9 P
Modeling Statistics , 模型统计; K& w4 r) p: ]- \4 T8 Z! [
Models for outliers, 离群值模型3 n/ q6 M# b5 j
Modifying the model, 模型的修正
1 g' @" D7 y. q2 e9 a Z: h. A7 HModulus of continuity, 连续性模, D' f' i, B7 g0 Z
Morbidity, 发病率 8 z( `/ \4 x6 k2 J
Most favorable configuration, 最有利构形6 N9 Q W) _9 W# x
Multidimensional Scaling (ASCAL), 多维尺度/多维标度/ Z/ B1 @" r" B5 q5 m5 _
Multinomial Logistic Regression , 多项逻辑斯蒂回归
* M" T8 _3 [3 @0 u$ K. I8 uMultiple comparison, 多重比较0 J- b9 W. s$ h* V
Multiple correlation , 复相关8 s( z; B! E% b' p; Q4 f+ L+ t5 E
Multiple covariance, 多元协方差
0 H! C9 x9 a# |/ X5 D1 W* qMultiple linear regression, 多元线性回归. C* L* B" R7 z% K# r& W; i- S1 ^4 w
Multiple response , 多重选项
$ J' i7 t- |7 v4 U( fMultiple solutions, 多解+ z5 c, V, Y/ J; k
Multiplication theorem, 乘法定理
2 {; ?5 ]2 ?: e9 x0 }6 x3 {Multiresponse, 多元响应$ E3 b* U7 r! S' J9 A
Multi-stage sampling, 多阶段抽样
: V Q3 }9 R# J2 nMultivariate T distribution, 多元T分布& Z% B- d. {0 |2 x; S* p, O2 H0 k' t2 }
Mutual exclusive, 互不相容
- ^: B* @! Q! n! iMutual independence, 互相独立' i; K2 a- }8 V' B' a, V% l
Natural boundary, 自然边界
% Y+ u- I. j0 pNatural dead, 自然死亡
7 @; q( f" L" g. H: ANatural zero, 自然零
& g* N2 K z# `5 H" L! G$ H# aNegative correlation, 负相关8 C! J, H' k4 ~# `. X# S
Negative linear correlation, 负线性相关
# _' @. _" |9 N- W' E" ONegatively skewed, 负偏
) o- q* {! j5 j! MNewman-Keuls method, q检验( ~% \. l1 I$ a5 u+ z g
NK method, q检验
$ v8 l: R5 Z1 @5 MNo statistical significance, 无统计意义
4 R0 @7 Q9 P( ]Nominal variable, 名义变量
9 C5 @! }) \4 w. W( INonconstancy of variability, 变异的非定常性5 a Z, k, x9 T
Nonlinear regression, 非线性相关
4 {" V% a, @+ \% m Q2 U. \Nonparametric statistics, 非参数统计
}$ G% b! c3 e9 T0 H' FNonparametric test, 非参数检验
- ^- H$ X3 g; y# [Nonparametric tests, 非参数检验' p& n. H6 S& i, E. S
Normal deviate, 正态离差
! s; C% p' b& ^. r# [5 c. SNormal distribution, 正态分布
/ M; u9 p, G4 @Normal equation, 正规方程组
$ T; G- ^. M3 Q! h `& ZNormal ranges, 正常范围
1 A L, C$ x/ _8 e& p; xNormal value, 正常值" Y6 N0 l, `9 I5 O( ~' F
Nuisance parameter, 多余参数/讨厌参数& E. v3 n' x9 m5 C! e0 M/ _- o7 s
Null hypothesis, 无效假设
4 F! n: j' C* V0 N7 @2 ~Numerical variable, 数值变量! k/ X- ]% U. ], W
Objective function, 目标函数 _$ A. e9 K( N& Z$ O" V5 s) q: o
Observation unit, 观察单位$ R# Q& B1 |! S) e8 ~* L, ^
Observed value, 观察值- Y4 B t% Y4 A. S, J
One sided test, 单侧检验4 `+ y" ^5 p% F% I- J
One-way analysis of variance, 单因素方差分析
% Q1 n+ D+ |3 V* uOneway ANOVA , 单因素方差分析
0 B$ J' `3 T. Z fOpen sequential trial, 开放型序贯设计 ?% Y* o- H Y! I3 d% B7 G8 _/ v
Optrim, 优切尾! N+ O6 o9 F4 A/ }/ F
Optrim efficiency, 优切尾效率
; B, R; C8 u1 L$ |! ^Order statistics, 顺序统计量
$ o1 X# D4 o. n0 UOrdered categories, 有序分类
* J0 d7 h4 Q d! n% Y1 K9 {Ordinal logistic regression , 序数逻辑斯蒂回归
1 ~6 D8 {4 ?' i& r" kOrdinal variable, 有序变量) F* [6 m6 h7 ~
Orthogonal basis, 正交基
9 J/ S# A$ Q8 P O" f4 C) ]6 ?Orthogonal design, 正交试验设计
U; M% w* z. _9 rOrthogonality conditions, 正交条件/ N n7 _* M$ u, F
ORTHOPLAN, 正交设计
& r8 g& d% B3 P( a" OOutlier cutoffs, 离群值截断点
1 j6 c5 C/ P1 J, E* ?4 eOutliers, 极端值1 m2 U9 E( P0 C
OVERALS , 多组变量的非线性正规相关 9 S& E; d$ l( A9 T c& \! W
Overshoot, 迭代过度0 A( ]- }/ v# t6 F- e) N4 s' B% S
Paired design, 配对设计) u. Y. X; a+ D R
Paired sample, 配对样本
) V' y! g! a7 ^+ u6 T( fPairwise slopes, 成对斜率
- N8 G w2 O9 DParabola, 抛物线8 `+ o7 h7 O& j$ N' C. G
Parallel tests, 平行试验, q9 c. E9 S2 q% v0 X) }/ d
Parameter, 参数; U" r5 F7 S6 F& t6 I& x* j
Parametric statistics, 参数统计( O) [/ L( y3 D7 R
Parametric test, 参数检验/ Y2 j# |$ |9 U$ ]# e, z
Partial correlation, 偏相关
& c! M) ]9 M \Partial regression, 偏回归, a9 M- K+ Q6 ~
Partial sorting, 偏排序5 J2 E: O2 e; \# ^2 }/ B
Partials residuals, 偏残差
0 x: E6 z+ O8 L+ g) p n( {% DPattern, 模式
6 l' _( a) f& I' r+ SPearson curves, 皮尔逊曲线) Q$ S6 V: o+ [# B/ j
Peeling, 退层3 J2 P* l" U! G3 P4 {/ Y
Percent bar graph, 百分条形图1 o, d5 T# I! k' C1 Q0 a4 { J4 D
Percentage, 百分比
" p S% S0 J. qPercentile, 百分位数
# r0 O1 d4 t$ m& K, yPercentile curves, 百分位曲线9 J/ i' t4 a9 z; }+ G+ R
Periodicity, 周期性
6 Z3 Y, v% w9 v& K) K! ZPermutation, 排列4 L" o6 Q; n/ W% ^, l7 k0 C
P-estimator, P估计量
/ N$ j. n ]8 Z4 D% c$ qPie graph, 饼图, f4 v8 n+ h6 h7 o$ F. V4 w! A
Pitman estimator, 皮特曼估计量' o+ I1 I9 O8 d" J( q
Pivot, 枢轴量- k% C* |; B0 t! @
Planar, 平坦7 x+ A( `! O2 N2 h- b X K
Planar assumption, 平面的假设
7 Y1 S3 k1 {& s; t0 w& a# V" }8 |PLANCARDS, 生成试验的计划卡
e0 a8 T, ], p$ EPoint estimation, 点估计2 m: I0 U" |$ J8 u
Poisson distribution, 泊松分布3 L2 U' N6 t6 W! ]# [$ O+ q
Polishing, 平滑: \; R3 C3 @+ C' n% t4 I
Polled standard deviation, 合并标准差
( n; G O: h' `/ h. ?$ v2 gPolled variance, 合并方差- i2 z4 b/ i- I- P
Polygon, 多边图4 C7 b0 F p$ I' K& v
Polynomial, 多项式6 e3 E; w0 \" g; q1 f
Polynomial curve, 多项式曲线
* `/ T- L0 C. ?7 A) ]( b- KPopulation, 总体. m9 g0 Q ~$ w: c0 K
Population attributable risk, 人群归因危险度
/ [7 j# n" L! G$ `) w2 n2 t3 LPositive correlation, 正相关
P+ T- q, T7 Z8 A& m* }Positively skewed, 正偏5 Z' P2 l1 d/ \1 w z' M' p
Posterior distribution, 后验分布
( R- l6 p$ u3 P3 H PPower of a test, 检验效能$ O" \/ t' S9 U" t
Precision, 精密度
5 [2 ? S1 l: ?1 U) O7 \: ^3 O5 KPredicted value, 预测值$ w( `' d& e* S9 M7 W0 R9 X
Preliminary analysis, 预备性分析
6 }0 K3 j) h: d" g: yPrincipal component analysis, 主成分分析& ?0 |: ]+ H+ J6 P+ h
Prior distribution, 先验分布
1 U9 ?! s6 K" K4 k2 u7 \. t2 @Prior probability, 先验概率
; e4 P" g, A' r% Y( u$ R9 @Probabilistic model, 概率模型! j1 M7 C" Z o" _1 X' g
probability, 概率/ i; q* g- H, K w
Probability density, 概率密度
1 R/ ]/ ` E/ D6 V$ _; t" @Product moment, 乘积矩/协方差# ]1 \$ u6 y; E! J- q; C
Profile trace, 截面迹图
, ]( q& I, M1 U" k' y) v0 ^Proportion, 比/构成比
# i% u- d9 q! @+ l/ x- D+ _Proportion allocation in stratified random sampling, 按比例分层随机抽样3 x6 w O6 h( P2 q( C
Proportionate, 成比例8 }7 M" P& `" u m$ j1 z) h
Proportionate sub-class numbers, 成比例次级组含量: w, V9 \& l# A! {' p3 k- N
Prospective study, 前瞻性调查% [* g5 X3 `. Z
Proximities, 亲近性 ! v0 U. a- S" `$ G" O% h) F; \* A) h
Pseudo F test, 近似F检验
+ z) W- F; H' TPseudo model, 近似模型7 o- t6 ~& @% k6 @; A, S
Pseudosigma, 伪标准差
. q# D% H: H+ H9 p7 [Purposive sampling, 有目的抽样5 ~' Z3 t& S# @
QR decomposition, QR分解
$ ^! b! M! i4 M8 b( f. K+ wQuadratic approximation, 二次近似
. d6 P9 ?3 K9 S+ G$ r' h9 Y8 @Qualitative classification, 属性分类9 j. }7 Z2 y) b) p3 s8 G7 B
Qualitative method, 定性方法
; o; I( \) B; `( Z5 o" OQuantile-quantile plot, 分位数-分位数图/Q-Q图3 s6 I. W6 Q9 d! w
Quantitative analysis, 定量分析
3 z# G& ] j8 U( o0 [0 v" kQuartile, 四分位数; S5 s# b/ C; a1 \( x8 ?
Quick Cluster, 快速聚类6 K' @5 r$ g9 W: G" Z
Radix sort, 基数排序6 ^, Q: ~0 I, p l* {0 C/ F7 l
Random allocation, 随机化分组+ O+ G. A0 O9 L0 ]8 {
Random blocks design, 随机区组设计
! L R/ [+ }% T! U1 S/ fRandom event, 随机事件$ @. t: U! L% `/ p0 s1 P- [# X
Randomization, 随机化
$ Q, e' F8 z, b" T9 F- u/ gRange, 极差/全距
, t6 {) S5 R# d( o9 k' rRank correlation, 等级相关
6 }' }+ y$ I: z9 U7 ARank sum test, 秩和检验
6 ~& S/ K) G7 {/ @2 l9 |) [Rank test, 秩检验
$ ^5 v. i& d) y0 D- wRanked data, 等级资料8 A0 G" m4 @* |) h
Rate, 比率
4 t2 n6 d" f2 U' p# r) _) rRatio, 比例
1 ]6 w( P; R7 P: ? U0 l2 _Raw data, 原始资料4 z; ` f1 ~3 F9 z
Raw residual, 原始残差
& |2 O. o0 O4 D; w- _3 tRayleigh's test, 雷氏检验/ U0 v K3 o7 {. J
Rayleigh's Z, 雷氏Z值
- L y% R/ x; ^& i8 Q- _& HReciprocal, 倒数
1 X' L$ H! @# a7 U* y gReciprocal transformation, 倒数变换
: I" Y' Y: p. a8 f. o8 Y- xRecording, 记录) o* L. g( j2 t/ N# ]+ H3 L+ W* J! w" i
Redescending estimators, 回降估计量0 [1 A# H; Y+ E" |6 D
Reducing dimensions, 降维
3 u [6 ?* I& @; RRe-expression, 重新表达
% A9 Y2 ~8 ]) X5 ?4 oReference set, 标准组
! w% x9 \3 v1 K% [5 \Region of acceptance, 接受域5 b( Z) t- U; q9 ~1 d
Regression coefficient, 回归系数5 L, V+ V6 \ i
Regression sum of square, 回归平方和' i# A, n+ \4 I
Rejection point, 拒绝点/ X% Z1 B4 f4 j8 z% p g
Relative dispersion, 相对离散度9 q7 w. y% `) D( B; ]* a, ]
Relative number, 相对数
: h& Z/ t) _7 l' yReliability, 可靠性$ [- F, b7 T/ }" ]1 o' x
Reparametrization, 重新设置参数
( q& }' w" a8 c5 MReplication, 重复: o1 V4 F1 Y4 D
Report Summaries, 报告摘要& J) {, A( k" v" Z D0 }$ z" E
Residual sum of square, 剩余平方和
& S7 I7 u" P) w ]" J6 e+ E% oResistance, 耐抗性% x0 _: S( T2 w3 Q
Resistant line, 耐抗线* h: P( z$ P' R: t ~0 j
Resistant technique, 耐抗技术7 z. T* g# G+ A+ s$ G K* K
R-estimator of location, 位置R估计量% |* z: Y, v( j8 _& E
R-estimator of scale, 尺度R估计量
5 H( g$ c# ?. ^Retrospective study, 回顾性调查
9 _3 g5 W. }! Q# J& B2 PRidge trace, 岭迹2 e) E0 l, k3 X- ^+ v$ i" w) d
Ridit analysis, Ridit分析) W4 H- [. }3 x5 E
Rotation, 旋转
; y) N( q7 }) nRounding, 舍入
$ J" u/ _8 j# d' FRow, 行
8 {7 E: O% R* O6 @8 KRow effects, 行效应: e+ S! T' c! l, I8 g/ j' B. l
Row factor, 行因素
1 r! e: v; h% dRXC table, RXC表* F0 @4 v9 q" b
Sample, 样本' w: D7 t9 X. C" `6 [( M
Sample regression coefficient, 样本回归系数- b5 u' B2 S% q E3 w
Sample size, 样本量- C% }5 [0 z4 e2 a5 {2 q
Sample standard deviation, 样本标准差* T z8 ] p+ J
Sampling error, 抽样误差+ X/ Q4 v% W* K1 y% W! o q
SAS(Statistical analysis system ), SAS统计软件包
/ Q" w, p3 B- d4 Q; I0 A. q6 A9 OScale, 尺度/量表
8 k. i8 g( r* ] ZScatter diagram, 散点图
/ [4 M& j( J2 T N* jSchematic plot, 示意图/简图
' u* s" z8 G0 l1 C" x9 gScore test, 计分检验) j. W) h& \5 C8 m( @- O
Screening, 筛检. U; g' {* O! \$ g/ g; } A% z
SEASON, 季节分析 " C% s2 E( Y2 @3 {' x( V
Second derivative, 二阶导数
4 J1 ?0 Y7 f+ K$ ]" z; H# C$ YSecond principal component, 第二主成分
( C* h( n+ P- YSEM (Structural equation modeling), 结构化方程模型
" P4 m& f! z9 M* ?6 M# zSemi-logarithmic graph, 半对数图
0 }' c# s2 \2 eSemi-logarithmic paper, 半对数格纸! r, a0 N" ~. R2 E1 k/ S
Sensitivity curve, 敏感度曲线5 W7 X6 B6 r' z
Sequential analysis, 贯序分析( ^/ c9 w- {' j; z+ j0 }# [
Sequential data set, 顺序数据集* c; y- S7 F7 A* `* D2 }
Sequential design, 贯序设计
' _ C! ]. X. u& p. B% oSequential method, 贯序法
' l( w5 i/ ?9 D% I% v. `Sequential test, 贯序检验法
6 F1 f$ E& \% N) z* |. ZSerial tests, 系列试验
% P& R7 g0 `. l9 c+ H2 sShort-cut method, 简捷法 7 ^7 h: o# e2 n1 `5 A* _3 Q! @+ V
Sigmoid curve, S形曲线7 k1 R4 }4 d0 j2 c; S9 m4 O/ Q
Sign function, 正负号函数% n* p- [6 Z# W# u( L9 f. f6 m
Sign test, 符号检验 \4 A0 ^4 w0 k+ K
Signed rank, 符号秩$ k1 b# a5 S8 D* r6 u2 n, j4 @
Significance test, 显著性检验
: F# }' c1 a1 qSignificant figure, 有效数字
4 y3 y1 z5 |8 i% ISimple cluster sampling, 简单整群抽样
9 n3 p4 [2 _2 F# [8 \5 O9 uSimple correlation, 简单相关$ @% [5 P! z& k. U4 [
Simple random sampling, 简单随机抽样
6 I8 f2 W" r- x) n& G& r4 aSimple regression, 简单回归
7 v' t0 H5 d5 U9 ]/ P' ~simple table, 简单表
- f7 K4 Y8 Y2 }$ }Sine estimator, 正弦估计量: z. o8 V9 X, j1 s# l/ w" K
Single-valued estimate, 单值估计. C, L3 `8 _- h! x" m/ c. O
Singular matrix, 奇异矩阵
( {9 J5 l) x. PSkewed distribution, 偏斜分布8 G x$ E% C) _- `& D
Skewness, 偏度3 S( d; ^7 X, B! @
Slash distribution, 斜线分布- X6 f, {! d M5 w
Slope, 斜率
; I' o0 [4 g1 Z( X- C" X, t6 CSmirnov test, 斯米尔诺夫检验
4 l- ]. l5 Z) L1 ?8 y! jSource of variation, 变异来源0 `4 z { K9 v4 [3 k6 L
Spearman rank correlation, 斯皮尔曼等级相关
: z9 L) e$ O! D$ K, a+ L$ O4 HSpecific factor, 特殊因子
/ S+ R/ x% ^- [* B/ m) E MSpecific factor variance, 特殊因子方差
8 {: ]7 O( i h+ MSpectra , 频谱1 G, O. M. I( A, J) w
Spherical distribution, 球型正态分布# r4 y/ _8 F2 n& @0 L8 ~& t! q3 h
Spread, 展布
, E2 j5 S* j0 uSPSS(Statistical package for the social science), SPSS统计软件包, J' o3 J V) \) r2 H: c
Spurious correlation, 假性相关
3 D- a+ N8 d" n, S* B& ]Square root transformation, 平方根变换& G( R9 A6 ?5 s: `% c3 U
Stabilizing variance, 稳定方差
) m& \+ v7 u, E* s7 O9 O. u7 bStandard deviation, 标准差
8 v4 e! I1 C0 V8 U/ lStandard error, 标准误/ Y" X# u; g' T9 N& R2 x
Standard error of difference, 差别的标准误) m) V: A' T4 }8 O0 ^7 {
Standard error of estimate, 标准估计误差
, ^, [7 y* E( K: A+ SStandard error of rate, 率的标准误+ Z1 g" m9 ^$ b; V
Standard normal distribution, 标准正态分布 W1 E, Z+ t Q. v
Standardization, 标准化8 y! r& [# i( K% |9 T' ]
Starting value, 起始值, c' t0 u" v6 w0 t
Statistic, 统计量& ?- @! Z* B& R! ~
Statistical control, 统计控制
5 W2 t/ V4 @7 m0 PStatistical graph, 统计图8 A% D0 b9 C' A! I8 N/ u, \3 c
Statistical inference, 统计推断
5 k: k5 @$ p' K9 fStatistical table, 统计表# l9 E7 u- s# \) t1 j/ X
Steepest descent, 最速下降法
% S2 e/ b3 n( \: q& X5 f3 zStem and leaf display, 茎叶图6 h0 e0 U, Q, I) k5 U& n1 V7 o
Step factor, 步长因子+ c7 l6 R# c8 g0 I) N
Stepwise regression, 逐步回归
1 ^" b: Y8 W& S! H) I1 O4 D2 B4 `Storage, 存3 _4 O1 a8 r6 w; W2 ?# T
Strata, 层（复数）
# z8 x7 e# S& F1 p# \3 D& O* @Stratified sampling, 分层抽样
; U7 E9 s1 O/ ?: J/ p! lStratified sampling, 分层抽样
1 d: C8 a. y# ^. ZStrength, 强度4 l2 ^+ L2 G I j( b+ M
Stringency, 严密性7 U6 B4 o7 V. W+ {* A* X' `" c
Structural relationship, 结构关系
% E7 O" ^5 e5 h8 AStudentized residual, 学生化残差/t化残差4 n5 t2 M) }% \$ i
Sub-class numbers, 次级组含量
4 J M: ]: f0 c2 x/ W5 \$ L8 \' F+ FSubdividing, 分割5 A2 d4 n# B" _' H1 P0 h
Sufficient statistic, 充分统计量
' P% x0 A2 L& i* HSum of products, 积和
4 }& s' M1 N2 m. ~4 VSum of squares, 离差平方和
: J U( R- r/ {+ M$ K% ~4 eSum of squares about regression, 回归平方和 b; C: w3 s/ k- I6 |! D
Sum of squares between groups, 组间平方和+ v; z' M0 I" ]
Sum of squares of partial regression, 偏回归平方和
1 {" C2 ^( t* \' f. _9 `Sure event, 必然事件2 n, v/ V$ ]; ^) g$ p& i( N$ \
Survey, 调查: N3 g9 l' }& \
Survival, 生存分析
" [) z2 a7 K& _1 S3 P' p. n# Q \% XSurvival rate, 生存率
* I+ N5 d2 b" L2 M1 \+ `Suspended root gram, 悬吊根图
& M& q% @9 N2 D! ~Symmetry, 对称
& u! |3 h" F- @' USystematic error, 系统误差- @% A& R1 Z; j h
Systematic sampling, 系统抽样
3 h0 x$ w* l3 o3 k5 q7 |Tags, 标签
2 p9 N9 u( e, B$ Y7 y2 U( FTail area, 尾部面积
' G$ ~3 B# Z4 @) cTail length, 尾长2 ~9 n, Q" E2 c
Tail weight, 尾重. k; [2 J c/ ^& K+ @" l% k$ R
Tangent line, 切线
/ S4 H. D! _, g% P( A3 o' t l; DTarget distribution, 目标分布5 F/ h' _6 k1 U6 X3 G
Taylor series, 泰勒级数
- a0 W3 K3 d; I p" E5 PTendency of dispersion, 离散趋势
$ _ u P; D1 K- Z! |6 Y9 vTesting of hypotheses, 假设检验
3 J! X9 O% ]4 B: Y4 ^( t0 c! MTheoretical frequency, 理论频数
* g& X8 N: @+ }/ yTime series, 时间序列8 x) {7 c$ p l
Tolerance interval, 容忍区间
S# W6 k3 z0 q1 JTolerance lower limit, 容忍下限 j7 }( U( T9 C6 i+ W6 p( A- E
Tolerance upper limit, 容忍上限
5 ^" p/ r, w3 h! aTorsion, 扰率, p( |' [2 r/ h; h4 Z
Total sum of square, 总平方和4 k9 K/ Z3 ]# U H1 z7 k; g6 H
Total variation, 总变异. `9 @# R* d c. m& t
Transformation, 转换! M6 q3 l: K& Q6 c& @: j
Treatment, 处理1 G t) ]; ~8 l. R, {
Trend, 趋势
# y% ^3 X: S" ?- c0 @/ U, YTrend of percentage, 百分比趋势
* ]' \7 D' q% e$ b7 x1 u9 nTrial, 试验) R6 s/ W: d5 |- q; F+ `4 V/ O6 G& D
Trial and error method, 试错法
/ h w4 H6 d) t" r8 RTuning constant, 细调常数
+ X/ O6 I1 j: v# e4 j3 R/ x, D$ BTwo sided test, 双向检验9 s% ^. o7 U. _ M6 J
Two-stage least squares, 二阶最小平方
! g$ c# d: F! D g0 bTwo-stage sampling, 二阶段抽样" S+ l- w: @: }. t1 Y% O4 Q5 n
Two-tailed test, 双侧检验
5 W* R: M* L1 vTwo-way analysis of variance, 双因素方差分析
8 t$ W! N& Z' m/ _- ~Two-way table, 双向表3 ?$ ~+ e9 O( p* j) C, }! U* q
Type I error, 一类错误/α错误
* c2 V% ?4 K6 M0 G0 ZType II error, 二类错误/β错误
1 {# u( J+ n, C* g( R4 ^- K' d8 o8 uUMVU, 方差一致最小无偏估计简称2 @2 C3 t% b* {$ X
Unbiased estimate, 无偏估计2 S9 t6 Q$ Q% m! H
Unconstrained nonlinear regression , 无约束非线性回归: X. o; |+ f" \+ o1 `4 ?3 }
Unequal subclass number, 不等次级组含量
/ Y6 ^' P" A( xUngrouped data, 不分组资料
( L; z5 f9 s/ O$ zUniform coordinate, 均匀坐标: F' U7 e7 k8 C, l, t$ P: Y; K
Uniform distribution, 均匀分布
1 G3 ^4 u/ o: KUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
/ M4 K0 k8 F& K. s. N" w, \1 [4 u$ }1 iUnit, 单元
1 q* K' V+ [/ W. x A$ m0 eUnordered categories, 无序分类
; X; ?5 c0 j* NUpper limit, 上限
) K6 `& v a9 [( w7 `; hUpward rank, 升秩
( D7 z! [2 y5 hVague concept, 模糊概念
1 Q4 B' ?! U h2 Y7 tValidity, 有效性; M7 |$ H0 f, w' X2 c; c! B! H
VARCOMP (Variance component estimation), 方差元素估计& e) E% O2 d2 z% z
Variability, 变异性" b3 T2 K! v% S V% k/ `# _
Variable, 变量
/ p; O4 {. n% y$ S( x$ @Variance, 方差. q, L" o% K* O! s# @; U- X/ I
Variation, 变异( `7 ^1 e+ R( u
Varimax orthogonal rotation, 方差最大正交旋转& s7 g5 z- Z* p2 b
Volume of distribution, 容积; w* N9 |6 x( _2 j5 d) \! g4 b W- ^
W test, W检验9 P3 w+ V0 g/ ?$ R3 z: m
Weibull distribution, 威布尔分布
- Z. S( M3 o0 n q2 `Weight, 权数
3 d: P+ R) }7 J- J' `2 h% JWeighted Chi-square test, 加权卡方检验/Cochran检验
/ I0 P1 _. E) o% zWeighted linear regression method, 加权直线回归
. e- | G: U1 mWeighted mean, 加权平均数5 x8 {; B3 b7 d4 k
Weighted mean square, 加权平均方差6 }, T7 A$ U4 f4 k$ W
Weighted sum of square, 加权平方和! n: E! b/ r J4 |4 R! I% v
Weighting coefficient, 权重系数; ^3 v. v9 E8 v- r! _
Weighting method, 加权法 ! d8 ?1 i+ r u; }4 X& ?
W-estimation, W估计量
: K/ P4 M# N$ O K: ~( j2 IW-estimation of location, 位置W估计量
7 _2 n w! V% C* s* }- j# eWidth, 宽度3 I, l- T0 s" d6 Y! G q- {+ P/ d
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
0 q7 Z* u+ `; V+ L- jWild point, 野点/狂点3 S8 u* F+ I& |
Wild value, 野值/狂值
/ j! d) n% o8 e5 TWinsorized mean, 缩尾均值
5 Z0 o$ r) x# t* t; g a" bWithdraw, 失访
, k5 k& j$ [: h' a1 uYouden's index, 尤登指数
/ c/ o6 n9 T6 {" p" a! d# F BZ test, Z检验
5 h5 s' [2 K" g+ R& q# C( zZero correlation, 零相关. Z$ j) r+ ~; \; j
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
