|
|
Absolute deviation, 绝对离差
2 v* H6 M9 z) Q2 y9 F5 z8 U" J4 bAbsolute number, 绝对数
2 L) c# e7 ]+ r- U3 w7 x- g( UAbsolute residuals, 绝对残差2 l1 u! N: g3 B7 U7 `
Acceleration array, 加速度立体阵! @# K! ~. W/ ^# K! d6 Y3 E
Acceleration in an arbitrary direction, 任意方向上的加速度
4 x0 u. r" B7 M9 K& vAcceleration normal, 法向加速度* D) i* x' K% ^- X; q7 b
Acceleration space dimension, 加速度空间的维数. {' M" a1 o! y- U
Acceleration tangential, 切向加速度( e( ^. v. v# c s
Acceleration vector, 加速度向量- w* G$ A- l( y8 w* N4 F
Acceptable hypothesis, 可接受假设8 y- K) Q( i8 p3 n
Accumulation, 累积2 T; F: a/ y3 O6 y; ^
Accuracy, 准确度( z& ?6 e( a M9 K. ?+ F
Actual frequency, 实际频数
; Q* [! O2 |& K u( F$ A7 TAdaptive estimator, 自适应估计量
- x) t: e1 a2 _' B2 D8 B. s$ O. y/ yAddition, 相加2 {/ t* U3 K$ a% H7 `) [/ e, j
Addition theorem, 加法定理! n6 R; _- v+ m" b0 i
Additivity, 可加性) X, k+ X8 ]" X% U! c: Z* J
Adjusted rate, 调整率
. h2 k2 ]/ D) s5 PAdjusted value, 校正值% h/ V A$ F( H7 F# h& d- H
Admissible error, 容许误差6 P, ~ n7 s, w9 }; T {
Aggregation, 聚集性
" h9 S$ @1 r% S" V7 c6 u% G- @. `Alternative hypothesis, 备择假设, h H& T0 z3 U' }
Among groups, 组间
' |/ m( b. K3 F( @2 O4 fAmounts, 总量! Z S, w: u0 Q% @5 f1 \* e% S% J
Analysis of correlation, 相关分析( n; P& ^7 g; t3 H3 o
Analysis of covariance, 协方差分析3 C6 v2 r6 \) O
Analysis of regression, 回归分析$ W1 l! B+ ?, X5 M
Analysis of time series, 时间序列分析
1 `. \: j! S4 NAnalysis of variance, 方差分析
7 Q0 ?- d8 G. H+ B7 NAngular transformation, 角转换- ~) ]! A; y# Y
ANOVA （analysis of variance）, 方差分析
# ^2 N( m1 [& x; E) oANOVA Models, 方差分析模型: M- k* s5 {( G2 L7 u
Arcing, 弧/弧旋# F/ f. F! ]; y
Arcsine transformation, 反正弦变换
) s5 u) K0 @. q$ |$ a0 \7 `" F" N. zArea under the curve, 曲线面积
4 j, i+ A: B- eAREG , 评估从一个时间点到下一个时间点回归相关时的误差
( x/ U; a2 p+ e8 ]ARIMA, 季节和非季节性单变量模型的极大似然估计
3 p* b2 r# f0 Q, ^" jArithmetic grid paper, 算术格纸
/ B+ E, @* N6 ]9 c3 ~2 GArithmetic mean, 算术平均数
' K: { n+ G( x+ }) {0 s& _% u5 RArrhenius relation, 艾恩尼斯关系7 i+ S4 h- o% ?! f
Assessing fit, 拟合的评估; u* G3 [( j5 s3 v
Associative laws, 结合律
4 O% {: S7 i7 V- k. YAsymmetric distribution, 非对称分布
$ ?4 [9 b7 R4 p+ `, ], J2 E! PAsymptotic bias, 渐近偏倚
9 U! V! ?3 u4 Q a- WAsymptotic efficiency, 渐近效率3 Q" ^- b E3 J: v! h
Asymptotic variance, 渐近方差
9 w3 B5 a% r! N, N( hAttributable risk, 归因危险度
1 D- u, B$ Q' ? b3 aAttribute data, 属性资料
/ W0 g( e9 R1 d0 vAttribution, 属性6 T& p! N8 L7 [+ L m
Autocorrelation, 自相关1 T& g: e* a8 o. w7 p# b/ `
Autocorrelation of residuals, 残差的自相关5 r/ Q$ ?! R" g. b9 P( _1 F
Average, 平均数
* @+ ?- L- r1 U# j- m" k( x- c! e! ZAverage confidence interval length, 平均置信区间长度
, g1 o: C0 ?2 B& K2 ^4 [" [1 MAverage growth rate, 平均增长率
# a4 [! H" {# z3 Z7 tBar chart, 条形图4 d$ X0 B0 }/ u# p- V( d
Bar graph, 条形图
' B( E9 ]& _" {8 R' W5 BBase period, 基期/ w. `2 a$ b! Y. n% A' ~
Bayes' theorem , Bayes定理
' z4 g- n4 {2 N" hBell-shaped curve, 钟形曲线# |5 b+ p1 ^! `9 i) B6 n0 J
Bernoulli distribution, 伯努力分布- @/ M# i6 ?1 _( E- ?- K9 L! S
Best-trim estimator, 最好切尾估计量/ @) l5 N% W# e- ~& B
Bias, 偏性
; Q" p9 d b3 n8 K6 ]0 i9 W# P! w5 @- ]9 mBinary logistic regression, 二元逻辑斯蒂回归- c9 y) l) {* c9 {" {+ {, v
Binomial distribution, 二项分布+ @# u y9 q' P; ^
Bisquare, 双平方
$ y0 T. X, p2 t0 Y% y1 ]7 o) R \Bivariate Correlate, 二变量相关
- `! h" o4 r9 t: Y3 wBivariate normal distribution, 双变量正态分布
! T) J: R' J5 l# JBivariate normal population, 双变量正态总体
( b0 P4 v, k* v+ E. K0 EBiweight interval, 双权区间. S( I1 m& t1 k+ J. X
Biweight M-estimator, 双权M估计量) J- E) V$ ]- g/ q; _
Block, 区组/配伍组
" P( G( ~# E/ L& e {! aBMDP(Biomedical computer programs), BMDP统计软件包
6 l" ]9 | p Z' \3 J7 w+ PBoxplots, 箱线图/箱尾图
* X. Y% w4 A& i8 m" z$ C' Y; |8 ^1 cBreakdown bound, 崩溃界/崩溃点
- E& c- K) h6 r8 }Canonical correlation, 典型相关6 ?$ f- x+ n- x! `9 w' Y. F5 `# ^
Caption, 纵标目
! L; G2 o/ C8 h# M# Z/ @Case-control study, 病例对照研究4 C/ q! l/ m. R. t- P
Categorical variable, 分类变量7 I9 p# c; E: i9 r+ W; o$ ]
Catenary, 悬链线
+ O- \0 L7 v( A3 ECauchy distribution, 柯西分布
) [* \5 F/ P0 t" H8 B# ZCause-and-effect relationship, 因果关系) e: H/ t1 o% y' k( Q1 b
Cell, 单元
4 f6 t8 ^, G& L3 |4 ~; Q* [7 SCensoring, 终检! z2 l+ P3 C( T- X; [/ T) L
Center of symmetry, 对称中心" i3 _ R r T# R/ Y
Centering and scaling, 中心化和定标
: D- g B# |; u+ E' k8 X( {Central tendency, 集中趋势5 W! p v7 e4 c* l1 q
Central value, 中心值( M* E( ]7 C& `. o" z4 i' @
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测5 G0 |2 G: p! ], c$ t
Chance, 机遇" T r4 ~$ M9 u" A- _
Chance error, 随机误差
N' a6 r" r1 M, Q) }' j- HChance variable, 随机变量 X5 k. T/ E) k+ I" |! T" Q M' s
Characteristic equation, 特征方程
; l {! \9 I! t( F, i5 N, ICharacteristic root, 特征根
0 q4 E- ]0 k5 m9 n* A$ J/ F O/ fCharacteristic vector, 特征向量
$ V% o5 K" o3 H. m C1 |/ A8 zChebshev criterion of fit, 拟合的切比雪夫准则
. v2 q: M f0 ^2 F6 X- z/ }) z7 ^. O7 rChernoff faces, 切尔诺夫脸谱图
# x8 \$ u% b7 G% a+ VChi-square test, 卡方检验/χ2检验
; p$ t8 u3 X9 ?Choleskey decomposition, 乔洛斯基分解
& o7 `" [# g5 y# U$ U% vCircle chart, 圆图
4 E" O3 U/ G7 D0 F2 qClass interval, 组距
- s0 J5 B- t* \8 _+ |% ?3 qClass mid-value, 组中值
/ }4 g+ s/ D0 {4 U( Q5 [8 PClass upper limit, 组上限
2 ^* h% D. j) R' T; U% K4 MClassified variable, 分类变量$ K) L6 {/ I/ P1 c3 Z; i& L1 P
Cluster analysis, 聚类分析
4 H: @- I+ z. n" V4 y0 s! p7 JCluster sampling, 整群抽样+ x( \! R5 O$ v. e
Code, 代码4 ?* U9 o% ~( i* M- K* V
Coded data, 编码数据4 I8 a4 ^/ h2 W3 ]
Coding, 编码
c. P7 e' B4 q# j# y$ SCoefficient of contingency, 列联系数3 B7 X+ f/ N. b: q
Coefficient of determination, 决定系数/ I- s. ~ _4 u5 n& [) r
Coefficient of multiple correlation, 多重相关系数
3 z5 J( c4 R- oCoefficient of partial correlation, 偏相关系数# A( a6 B7 p8 R, m6 D' D' ]& m% q
Coefficient of production-moment correlation, 积差相关系数; {* F1 `. ~! a7 w
Coefficient of rank correlation, 等级相关系数
2 M) A- B) ~3 H! _Coefficient of regression, 回归系数
0 P3 b/ i' d+ G% T. |0 X" z* qCoefficient of skewness, 偏度系数
- U: g G2 q5 ~6 `* D' jCoefficient of variation, 变异系数( x# [$ M l/ T- I) H. ^6 M$ E! w
Cohort study, 队列研究
) [ l' T2 |" [6 aColumn, 列' Q* I3 v) ]' E7 S5 |, f: C6 g) ?
Column effect, 列效应' A6 f7 Q& X0 y* u+ B
Column factor, 列因素
7 E1 E5 w0 |. L' `2 qCombination pool, 合并, X- w$ i, T, }% u$ N+ S
Combinative table, 组合表
* n2 L8 e5 t J2 ]- U fCommon factor, 共性因子
& Y; i: S' b* Z. m0 QCommon regression coefficient, 公共回归系数) `3 d+ V$ Z s4 D8 z
Common value, 共同值
- G: t: ?% b' S' W# r9 sCommon variance, 公共方差% V$ k. |+ y+ r& }' v
Common variation, 公共变异6 u# \: T0 m8 ? ~' d. |, X @
Communality variance, 共性方差& i0 W, D& x9 d' |1 C7 L8 J/ d
Comparability, 可比性+ m) r" v& o, f* G, p, k+ L6 W, W
Comparison of bathes, 批比较
% c1 U% Y6 a) E! F$ \ YComparison value, 比较值# c! Q: d1 w# h& W( s
Compartment model, 分部模型
* j7 h; l7 E/ e2 n5 xCompassion, 伸缩
. m. t" x: ?: z7 l zComplement of an event, 补事件$ u6 t/ Y* D3 c Z
Complete association, 完全正相关2 m' [& k% ] y% X a( F
Complete dissociation, 完全不相关. I/ E% ~6 P# k! q F
Complete statistics, 完备统计量
' R; z" E# {. t6 M5 QCompletely randomized design, 完全随机化设计& ?$ q! F- c7 s7 W; K9 n$ I
Composite event, 联合事件
( l/ e0 w# t3 G1 C3 z* v+ V- NComposite events, 复合事件
, \3 p: N' G" Z4 r" ?/ \Concavity, 凹性% Q z! h& W; T+ J' s* l
Conditional expectation, 条件期望! a, h- R b8 G
Conditional likelihood, 条件似然7 y% Y8 N6 ^9 H8 |. r9 ~9 l
Conditional probability, 条件概率
5 s7 m# _& g9 Q3 CConditionally linear, 依条件线性
$ t: H! E7 g( H! |6 G2 fConfidence interval, 置信区间
0 b* A5 i2 L7 HConfidence limit, 置信限
# n* [1 e0 H3 C$ A, X5 o0 }Confidence lower limit, 置信下限/ x: B0 O% I% u0 G* _
Confidence upper limit, 置信上限$ E& P0 r X- P7 x `$ _: E
Confirmatory Factor Analysis , 验证性因子分析
. y0 } g. T C. ~2 u8 I4 TConfirmatory research, 证实性实验研究0 I: {/ a( m; b( w7 ^; w0 t/ T! H$ C
Confounding factor, 混杂因素* C& |% U. l& ~) x# S
Conjoint, 联合分析
& }* P6 T, O6 N4 H, V9 D- PConsistency, 相合性; b; V" s, l' Y6 @9 `
Consistency check, 一致性检验
" H7 b* D. j" N9 \Consistent asymptotically normal estimate, 相合渐近正态估计
% @% A$ E6 H7 q3 A& Q/ b8 IConsistent estimate, 相合估计, ?, U @* c$ W# m- t
Constrained nonlinear regression, 受约束非线性回归* a+ A0 ^% C2 r* h) Y. ~7 g
Constraint, 约束8 N$ u3 ~$ |( E. M
Contaminated distribution, 污染分布5 n3 U4 I5 j3 @ C2 U& b/ C( X
Contaminated Gausssian, 污染高斯分布) L% S$ @* {2 z; p! J, A
Contaminated normal distribution, 污染正态分布7 D; x# q: v$ \0 t3 p! v( L/ `
Contamination, 污染
) Y) p! W- S# C5 H2 l5 L0 T4 e1 LContamination model, 污染模型- m* P& N8 g% M, q% e4 ]
Contingency table, 列联表
$ P* T! ?$ L8 k6 M9 S" PContour, 边界线
5 l7 C1 D1 `) V) X0 Y2 `Contribution rate, 贡献率( G( h' G% H. B+ l$ B, Q1 B% J% W8 b
Control, 对照
1 }1 }, E/ b: \7 K/ |1 aControlled experiments, 对照实验6 `( p0 z9 S+ C
Conventional depth, 常规深度
+ c! L @1 f7 S; P4 AConvolution, 卷积0 q6 L5 ?2 X( D7 @' C" f
Corrected factor, 校正因子
' I# k9 D6 j* cCorrected mean, 校正均值 e4 _$ Q- @- Y
Correction coefficient, 校正系数
3 T$ T% g$ r6 h/ X0 z' S3 hCorrectness, 正确性) ?6 Q, f% X+ t: Z" d8 h
Correlation coefficient, 相关系数! U0 @: |1 c3 [5 v A# s( G
Correlation index, 相关指数
% y' L* d: }( _( vCorrespondence, 对应
+ E( A, i f, A1 }. XCounting, 计数& C. K( B( s5 {
Counts, 计数/频数7 ]- D! A r8 ]5 N& j3 n+ O# ] o
Covariance, 协方差' \! C$ a8 M+ v5 n6 h
Covariant, 共变
! K% o0 d2 i, M$ `! [6 A% r P2 JCox Regression, Cox回归
- H5 _: [3 o: M. P& uCriteria for fitting, 拟合准则
+ x7 K0 ^9 i" Z, |Criteria of least squares, 最小二乘准则
! t. {1 M# A: y; M% x. z# QCritical ratio, 临界比2 ^/ x b$ x, X. a5 B Q% J* \' \
Critical region, 拒绝域6 m6 ^4 ], U( c, B8 |' s) N! X4 Y
Critical value, 临界值& n3 o% @! H5 v0 n
Cross-over design, 交叉设计2 e# s! u) b/ }1 y5 \6 d4 z
Cross-section analysis, 横断面分析
; h- z) H ^: X7 c7 o9 OCross-section survey, 横断面调查7 v1 T- H/ R j8 \1 R. i" N% w+ K+ e
Crosstabs , 交叉表
0 |2 X+ z2 ?6 G k- ] JCross-tabulation table, 复合表
# V5 R) K7 \; u( l- t; P- `Cube root, 立方根' a' t& ]; U( w( E* {
Cumulative distribution function, 分布函数
; O ]" R4 H% }" ]; E( @% u9 @$ {Cumulative probability, 累计概率7 V3 u# A$ O. y
Curvature, 曲率/弯曲2 K& K" z2 g: {* c" ~, Z- ?
Curvature, 曲率
. V; T+ A9 X) b7 UCurve fit , 曲线拟和
, j* Z9 `* M1 n0 u; V: GCurve fitting, 曲线拟合2 Q; J1 {' U. _8 P6 H0 g/ r- O
Curvilinear regression, 曲线回归 r# `* J, T- \3 E" w
Curvilinear relation, 曲线关系
1 z% R. @) z0 N( R: H eCut-and-try method, 尝试法9 P+ C3 ?, Q- M4 j; ]. ?2 m k
Cycle, 周期- s, Q' u4 I* t6 j
Cyclist, 周期性( `, T9 }0 ?, U" w7 n" G& X) Y
D test, D检验3 B# y! z, T, ?
Data acquisition, 资料收集* ^7 V- O2 I( {! e% w0 V0 B
Data bank, 数据库' p# x: [" {) @, D" i- [
Data capacity, 数据容量8 j# e2 i- f" g6 F
Data deficiencies, 数据缺乏; h8 K3 k% d: w6 m9 `5 X+ q) J
Data handling, 数据处理
2 d$ P. x& t- A, `" ]& U. XData manipulation, 数据处理# h3 W% M+ V) f/ |
Data processing, 数据处理: E" S: i m! A
Data reduction, 数据缩减2 m) e/ ^# m: E
Data set, 数据集- w/ h7 A5 [" C. z4 B, Q; S! G
Data sources, 数据来源
% K1 V* {4 H/ YData transformation, 数据变换
- o" o1 C2 Z+ Y/ y5 MData validity, 数据有效性
9 o X. g( A" _' vData-in, 数据输入
9 u `6 {3 V! n. c4 J2 D# H! o- JData-out, 数据输出2 S7 `! Y& `! Z. B1 P
Dead time, 停滞期. D: ^6 Q P. d
Degree of freedom, 自由度7 F8 h( w9 N% P( X1 B2 O9 \
Degree of precision, 精密度 @; k; h/ w1 Y1 {" ~5 d1 G
Degree of reliability, 可靠性程度7 F3 ^3 a3 w _2 l
Degression, 递减
+ w m" b P; r+ {7 |Density function, 密度函数
$ m* g( F! d! Z5 z. ]" |: HDensity of data points, 数据点的密度
2 i* n- {4 w- X" D* P8 x- w3 kDependent variable, 应变量/依变量/因变量
1 l" q7 p( O: J6 @) V1 N! UDependent variable, 因变量/ ^' O4 f; g; ?& @% S7 h
Depth, 深度
8 U6 ^. V. f- R# hDerivative matrix, 导数矩阵4 L' ^7 a, z" K( v
Derivative-free methods, 无导数方法
5 n' u& t5 R: lDesign, 设计
3 q8 X1 g3 D' zDeterminacy, 确定性
" @ Y% q7 Y8 i. e* iDeterminant, 行列式
& b( P. R- h5 A8 T/ Y [' MDeterminant, 决定因素
1 A6 }4 T% C1 w) q9 `, k% _Deviation, 离差' |- b4 e/ h) q( Z4 X
Deviation from average, 离均差
& T% c" G2 Y/ J8 L, u% RDiagnostic plot, 诊断图6 @8 v, w1 t8 X/ Z E$ T: T8 ]; C3 t
Dichotomous variable, 二分变量
; l$ a$ S5 K( K' f' K8 r2 Z5 K8 @Differential equation, 微分方程6 B) Y/ D4 j c7 y( H, w# ^- K( }
Direct standardization, 直接标准化法* a0 F6 U' A: T \, |$ k
Discrete variable, 离散型变量' |3 L# P! U2 \# z h
DISCRIMINANT, 判断 0 @+ p7 s) ?& W$ b- p5 Z1 h! p3 L
Discriminant analysis, 判别分析
5 F9 g; Z" \$ w2 t+ G+ A& yDiscriminant coefficient, 判别系数3 m8 T& Y7 S/ @: y$ @. U$ K0 r
Discriminant function, 判别值
/ I' v& N0 I9 R6 q8 C, DDispersion, 散布/分散度
) y5 P/ }3 s4 f0 J4 x2 YDisproportional, 不成比例的
9 @) D+ t/ | q* w& aDisproportionate sub-class numbers, 不成比例次级组含量0 d) b' z. e- z! Z p' Z
Distribution free, 分布无关性/免分布
' x& v* F) ?( z. \9 Y3 VDistribution shape, 分布形状) o, ?: m' K% o5 T
Distribution-free method, 任意分布法
' O, i* d2 O8 gDistributive laws, 分配律9 O* g( m2 s& c+ k
Disturbance, 随机扰动项
B& W: a6 i8 u0 x% k3 Z$ i( xDose response curve, 剂量反应曲线6 k3 l% U! A7 G/ _) b: u# x! r
Double blind method, 双盲法$ z5 s% h" e b) G
Double blind trial, 双盲试验1 S1 R( s" n5 k& y2 `& E3 O
Double exponential distribution, 双指数分布
( J$ [. O( D% @1 \- e/ I2 zDouble logarithmic, 双对数
l6 Z: I; U. U _4 F5 DDownward rank, 降秩
, c9 K. L3 k2 mDual-space plot, 对偶空间图 z0 o: Y' |% N
DUD, 无导数方法
1 Z; l. b2 w0 Q5 n1 HDuncan's new multiple range method, 新复极差法/Duncan新法+ q) N! s2 j- T6 H1 `5 v
Effect, 实验效应8 y1 F: W. @& T, g* K0 `1 U G$ f T
Eigenvalue, 特征值
, R: i9 F( U, VEigenvector, 特征向量8 g) V1 u4 b" c
Ellipse, 椭圆
' s" n5 P: D8 L9 H) p4 `1 q" S8 a7 X4 yEmpirical distribution, 经验分布; F3 E* N3 e6 _
Empirical probability, 经验概率单位7 m1 S: f" I& ?% P, W x
Enumeration data, 计数资料
4 n1 l- `4 g) l( OEqual sun-class number, 相等次级组含量( B$ Z- v! [/ p. {& {! k
Equally likely, 等可能
1 I( v. L2 O) _. `4 _% ZEquivariance, 同变性
2 g/ e( ]* ~3 }+ {Error, 误差/错误9 l$ l8 z% u- U7 U$ }* i
Error of estimate, 估计误差
# G, |( [3 E. J! I+ a; s6 m* `Error type I, 第一类错误
& s0 \8 V9 K4 W8 I: V1 A& UError type II, 第二类错误, f& G) |, M `. S' F
Estimand, 被估量
! A J! i' K2 N9 E$ JEstimated error mean squares, 估计误差均方7 J" Q- @8 o; ]
Estimated error sum of squares, 估计误差平方和% o p3 v9 A/ R, n+ c
Euclidean distance, 欧式距离
) T2 X1 c- G8 T: f1 bEvent, 事件+ Q0 U- |; S7 X. M7 Z
Event, 事件' t3 f- M2 U8 i: V
Exceptional data point, 异常数据点
3 Y; f3 H6 X; T" x% qExpectation plane, 期望平面
# y# y/ p. q, L. W( b! sExpectation surface, 期望曲面* `6 L( H6 V# a
Expected values, 期望值
5 n" {9 a( c; e9 X% kExperiment, 实验
4 M1 e' I* U. \% e2 |/ o' N, [$ sExperimental sampling, 试验抽样/ u* \# I7 A4 g( A f
Experimental unit, 试验单位& a2 C4 k2 b( G
Explanatory variable, 说明变量
, }9 K* p! x5 E7 ~1 }Exploratory data analysis, 探索性数据分析
1 v% m# b. ?4 |) j5 k# OExplore Summarize, 探索-摘要% P$ C- G1 j' l9 D4 t, a2 X
Exponential curve, 指数曲线
& [9 m* W3 F6 X) I/ G7 Y+ s( qExponential growth, 指数式增长. l/ n7 |2 z. s- J4 V
EXSMOOTH, 指数平滑方法 $ a4 }) {0 ^) U
Extended fit, 扩充拟合" I1 g1 a, a4 p# F
Extra parameter, 附加参数
4 ^+ L+ P) B, d' u: B }Extrapolation, 外推法, y! U( x8 x' N# z
Extreme observation, 末端观测值& k# l+ _. X" a$ _' X9 a
Extremes, 极端值/极值
7 U# q/ h+ ~: x- H; J* ~F distribution, F分布
( N4 b. o1 T' g' B b$ aF test, F检验9 b* U7 D# i4 \# R7 e: j1 t9 c* P
Factor, 因素/因子0 x9 I5 A$ j. J7 m6 m% `
Factor analysis, 因子分析, g& B/ i1 z# ^* y: `0 i
Factor Analysis, 因子分析4 r1 b! G+ H# ?6 `2 l$ e- S
Factor score, 因子得分
$ a, m$ r1 V4 E U, dFactorial, 阶乘
( p- |" o0 X8 s2 ]; dFactorial design, 析因试验设计9 R P; j5 C4 W8 u- S
False negative, 假阴性- z, x7 s2 s7 | n
False negative error, 假阴性错误
' z$ B$ ~. Q' CFamily of distributions, 分布族
3 M. j7 w& E9 y: {" I Q/ rFamily of estimators, 估计量族) f/ I. Y1 F" G" f* w! }% ^. E
Fanning, 扇面
* U7 e! g( ^3 b8 I- ]& t$ }( _9 |Fatality rate, 病死率
" G7 e7 F* v3 W/ ] ^Field investigation, 现场调查2 O5 v5 O, ]0 l" s3 ]! a/ [
Field survey, 现场调查
* [$ i0 _/ g' c8 K0 F* q2 R( tFinite population, 有限总体
3 i$ D! [ Y; f7 z1 R2 }5 LFinite-sample, 有限样本
$ W$ R* ^: F0 y& |1 @/ V1 vFirst derivative, 一阶导数* _/ x" j& x; P }4 c# ^
First principal component, 第一主成分1 |, e& ?* W! n0 X$ G5 M% s
First quartile, 第一四分位数& U" o _7 e/ Z$ m
Fisher information, 费雪信息量
* e( A6 S7 T& @2 W, w3 c8 r$ zFitted value, 拟合值
: } U0 d# B, \2 e8 _Fitting a curve, 曲线拟合
0 v. m P" E- uFixed base, 定基
. z. ]0 z: r, L& \& CFluctuation, 随机起伏$ `9 D8 E; y) {% O
Forecast, 预测
( \9 M: B2 v- X( |4 EFour fold table, 四格表3 ]5 C% a2 J% a4 w1 |% u
Fourth, 四分点- r7 [0 y2 C7 Z2 X; a
Fraction blow, 左侧比率
6 E. E" v( K- p r% _" tFractional error, 相对误差, {' \* M V& m+ N
Frequency, 频率 F, k1 `, {1 L x* L t5 z9 b# W
Frequency polygon, 频数多边图
0 m, P! F7 ^4 s# p; ?2 v) FFrontier point, 界限点% Q) }5 h; `0 {0 C% s; [% n! A1 L
Function relationship, 泛函关系
8 f5 p$ A/ ^; Z& e3 {5 FGamma distribution, 伽玛分布
% l& H7 i" M- G5 z: i1 g$ `& pGauss increment, 高斯增量
( V, ]" c' k( Y/ _* w. {' YGaussian distribution, 高斯分布/正态分布- k* O) ~( G, H& N8 f
Gauss-Newton increment, 高斯-牛顿增量
, d- t* n) M% e6 R1 HGeneral census, 全面普查6 e( ?, K) E5 K! I9 M2 h
GENLOG (Generalized liner models), 广义线性模型
% K( J6 {5 V3 A( A$ ^Geometric mean, 几何平均数
. ]8 v6 {$ C) K1 zGini's mean difference, 基尼均差% |) M( U$ O: e" |. T
GLM (General liner models), 一般线性模型 2 ?& I# w; q9 r J4 u2 |
Goodness of fit, 拟和优度/配合度; F) O: D6 ^2 v5 e; u
Gradient of determinant, 行列式的梯度$ i# a9 F; B% i5 V' Q4 _, ]/ h( g
Graeco-Latin square, 希腊拉丁方
4 _1 U% W, e2 D$ z$ ], eGrand mean, 总均值1 l7 K! S0 d4 }. [- W9 ^
Gross errors, 重大错误( Z" O0 b6 T$ \5 b8 L
Gross-error sensitivity, 大错敏感度! t6 D) J+ g9 ?: F0 q4 ?3 g
Group averages, 分组平均, M1 S" c J |+ a9 N0 m9 N' o
Grouped data, 分组资料
4 h% H* J. @6 q8 |4 AGuessed mean, 假定平均数- b- v& T, o2 |7 R7 `
Half-life, 半衰期+ @* k e7 W$ V# [1 p5 C# z0 ?
Hampel M-estimators, 汉佩尔M估计量8 }0 X/ y' ^) P- ^( o- L) c& D
Happenstance, 偶然事件
, Z6 P' X8 z" p% ]+ d: OHarmonic mean, 调和均数7 g3 l7 D1 Z2 o/ ?0 @ }4 t8 I
Hazard function, 风险均数( a+ F5 u9 l9 M; c; M" k
Hazard rate, 风险率
/ Z9 V: X1 k3 ]% P- THeading, 标目 * t' }$ G: y8 R/ v! q! m* R
Heavy-tailed distribution, 重尾分布0 a q5 p. @% ^" @/ U: h3 ^
Hessian array, 海森立体阵
# c6 j+ |3 `6 B3 x( Q7 w( FHeterogeneity, 不同质: t/ r; H, e- e# [- H/ i( N
Heterogeneity of variance, 方差不齐
2 Z! Z: ~2 Z+ A$ v' d, M d" g$ \Hierarchical classification, 组内分组
7 h |. H% ~( OHierarchical clustering method, 系统聚类法
" b1 s5 {! k3 J5 C) FHigh-leverage point, 高杠杆率点
, U4 W& H3 ^5 U! }. s- |9 BHILOGLINEAR, 多维列联表的层次对数线性模型: w- {3 C" \0 g* U4 t6 `$ K
Hinge, 折叶点3 _5 H% t$ ^; Y, v
Histogram, 直方图
) q8 Z" B8 n: d( P% pHistorical cohort study, 历史性队列研究 3 |0 }% m, A* \" `2 O: k- F9 N
Holes, 空洞
: C2 r' o: f/ U, T8 K, o7 e! d! OHOMALS, 多重响应分析
' z3 P" y% a: oHomogeneity of variance, 方差齐性
8 ~0 S; a5 z8 V6 SHomogeneity test, 齐性检验
$ V# u. |6 r" M* C/ \Huber M-estimators, 休伯M估计量" Z' }* D# p! t3 `2 _
Hyperbola, 双曲线
3 o% T( u2 A A; C9 R$ sHypothesis testing, 假设检验
7 D% b& [ K# e; l, |3 dHypothetical universe, 假设总体. e. X' Z! z( X2 P4 x' O$ Y. ^
Impossible event, 不可能事件
5 v/ o/ T- C* n, j" Q/ cIndependence, 独立性. S: ?( \/ J5 n4 u8 |! z
Independent variable, 自变量& `4 {5 s) x% r! _) m. g9 }
Index, 指标/指数# t% a, k# E5 d; }
Indirect standardization, 间接标准化法: Q# Q3 d. y# C1 {0 x) E
Individual, 个体1 y/ c: {9 k L" [6 I
Inference band, 推断带5 f+ X7 f! t8 m! m7 M# r8 s
Infinite population, 无限总体4 M) H9 ~) r/ j9 \" `0 C, M9 W
Infinitely great, 无穷大
/ s$ v; Z) l9 O5 a. ~4 T3 V2 ?( f. CInfinitely small, 无穷小
; i+ R4 a1 M7 O5 F% i3 aInfluence curve, 影响曲线
+ K! m* E# ^; F) UInformation capacity, 信息容量
5 d+ X8 K7 @ W3 f' L7 p$ _$ R: yInitial condition, 初始条件
5 h% {( w+ P- C: N4 a7 MInitial estimate, 初始估计值
5 v4 o% { u$ a: R. v6 NInitial level, 最初水平 p( c# I% b) t
Interaction, 交互作用 R' b0 g3 i* J9 p' e. r% k
Interaction terms, 交互作用项4 T' E2 p" N" ?
Intercept, 截距4 x8 h! b0 e( a& B( Y5 @9 c
Interpolation, 内插法
3 N# p0 [) A9 G( {2 E. hInterquartile range, 四分位距
+ X6 p" U2 t: p0 S2 C* g1 `, yInterval estimation, 区间估计
7 }# C/ O( P. ]% w8 J* }* aIntervals of equal probability, 等概率区间) q( a8 {- {8 s( \# z! n( v$ k
Intrinsic curvature, 固有曲率, P3 _ h8 n3 y6 i* |7 A: B8 q
Invariance, 不变性6 _& g2 ?5 |1 [+ A
Inverse matrix, 逆矩阵
( k# g. R* `( E Y8 v( ]Inverse probability, 逆概率
: G7 k& r9 P0 K# j; k5 G& K" sInverse sine transformation, 反正弦变换
o) ^2 N& b7 O/ A5 K/ dIteration, 迭代
. t: a3 `" P2 O4 V8 O! yJacobian determinant, 雅可比行列式- h' n2 H8 B% ?9 s1 Q% V
Joint distribution function, 分布函数
8 F5 {4 \* L' uJoint probability, 联合概率 M( a/ V& l, {' R7 e1 f
Joint probability distribution, 联合概率分布) J% |5 H1 d! H* b) |: P
K means method, 逐步聚类法
3 T' H! p1 w* bKaplan-Meier, 评估事件的时间长度
) X* \ k# b/ t6 w3 HKaplan-Merier chart, Kaplan-Merier图
5 `% I! c$ X( r* pKendall's rank correlation, Kendall等级相关
4 s% x: R- G# E2 P4 KKinetic, 动力学
0 X; |' ~% |4 t/ OKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
+ S! t9 u* ^" P1 ~Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验# C |! g7 m; {
Kurtosis, 峰度
& u! p4 ]5 r2 Y% G, P% [Lack of fit, 失拟
: H# H+ z3 H8 u5 [. JLadder of powers, 幂阶梯) ], a- k) K# a/ G- B
Lag, 滞后, h; Q0 z" K( O* b
Large sample, 大样本
) G5 h3 r1 c5 {9 Z5 ULarge sample test, 大样本检验3 N" F3 Q ]2 f3 A9 J
Latin square, 拉丁方8 P2 e! W* `# S5 S x5 s4 Q' x
Latin square design, 拉丁方设计
( u6 {+ q$ n. {0 p2 xLeakage, 泄漏. ]! m3 |( q! I O7 [3 x! X
Least favorable configuration, 最不利构形
- u5 M7 C8 q3 W3 ZLeast favorable distribution, 最不利分布
; d7 S1 z& {. o, GLeast significant difference, 最小显著差法
$ ^3 ^5 q. s [4 J: Q& \$ cLeast square method, 最小二乘法
' v* C, r; x3 m1 D3 [6 r2 k4 J" wLeast-absolute-residuals estimates, 最小绝对残差估计
. j& i/ `3 K9 m5 |Least-absolute-residuals fit, 最小绝对残差拟合
8 `+ L1 y8 {% _3 H E% uLeast-absolute-residuals line, 最小绝对残差线
2 q7 Z# N% W9 |/ fLegend, 图例' t9 i# g1 I8 y% f5 L
L-estimator, L估计量
C! @ \9 d: n, Y) [L-estimator of location, 位置L估计量
% Z4 [1 p% ~: k$ S* D! gL-estimator of scale, 尺度L估计量( h/ X, r; `) G8 n
Level, 水平- u. e/ L; r3 I7 f
Life expectance, 预期期望寿命
* L1 P# M6 p2 }8 j M# X$ i" |Life table, 寿命表
# `9 c1 J3 X4 W2 ?" b, \Life table method, 生命表法& @& K/ Q4 }4 u( {" M
Light-tailed distribution, 轻尾分布& X5 l! F: |1 I! w* r
Likelihood function, 似然函数5 n* F2 R7 |% O/ y
Likelihood ratio, 似然比
: y D7 j2 |" ^5 i: m5 C* `line graph, 线图
* M! ]' |! _3 p4 W; E/ ELinear correlation, 直线相关7 p8 I! t0 { X# G- @1 _
Linear equation, 线性方程
. K# A6 i7 u& G( E- O2 C" h$ [Linear programming, 线性规划/ \( ^6 [# S7 t/ {& {! E
Linear regression, 直线回归
% J) s1 k, T) ^' T1 Q, G ?Linear Regression, 线性回归$ Z1 a( J! }& X0 \2 i# G
Linear trend, 线性趋势: j! A7 q% q" w3 o- B7 \2 u
Loading, 载荷 . I9 n$ F0 ~' u, m
Location and scale equivariance, 位置尺度同变性& _( l% f" e c
Location equivariance, 位置同变性
- e7 Y V: E6 Z% U7 a6 |' U* y' BLocation invariance, 位置不变性" k, n# s; [2 I" h: R: ]; c* c
Location scale family, 位置尺度族3 V) y+ a" t1 U
Log rank test, 时序检验 ; s q0 h1 y9 P8 D6 ]
Logarithmic curve, 对数曲线 P0 S6 D2 o! q7 h
Logarithmic normal distribution, 对数正态分布0 W+ b* l5 J$ c- m6 w
Logarithmic scale, 对数尺度+ J! S: }- }3 `4 N6 T9 S
Logarithmic transformation, 对数变换# B* J5 o6 ?; Q( s, O% K& {/ B
Logic check, 逻辑检查& `9 @4 g4 _ e1 w4 x
Logistic distribution, 逻辑斯特分布5 @" l+ A: h# L" E$ k
Logit transformation, Logit转换, F6 ~4 u/ I! F9 V9 {% Z8 M2 ^
LOGLINEAR, 多维列联表通用模型 ' L, b. S% ~4 V
Lognormal distribution, 对数正态分布
( ~/ |" y# O: O7 cLost function, 损失函数
# S9 l9 R0 c; Y( r8 MLow correlation, 低度相关
0 u6 U/ O+ J) U, f, u. F/ e+ F5 ^Lower limit, 下限
( x5 `; e! g- z: s/ d1 v7 A) xLowest-attained variance, 最小可达方差' E% N% \' u9 L, E! r
LSD, 最小显著差法的简称7 ~0 t. t% p( p# c: Y
Lurking variable, 潜在变量
" J% L0 B$ C8 ~# |! iMain effect, 主效应
) I& P$ g+ j% b9 S, Q' j! bMajor heading, 主辞标目
) p3 A: k6 e, F1 [( ]Marginal density function, 边缘密度函数
7 v. Q, l; [* M) ?; U3 jMarginal probability, 边缘概率4 G* @$ Q' R( z/ L
Marginal probability distribution, 边缘概率分布
3 R/ Y" T) X( Z# x$ O3 tMatched data, 配对资料+ V; N# {8 |9 y. ]* a
Matched distribution, 匹配过分布
* i/ _0 n9 g$ H/ Z& b+ D2 HMatching of distribution, 分布的匹配
- Y7 H9 R; U- kMatching of transformation, 变换的匹配
, S" z4 T" B# n8 R9 `. a. d! U/ RMathematical expectation, 数学期望
! e! F2 c' ^ iMathematical model, 数学模型
0 k, Y! w' [( X% ~Maximum L-estimator, 极大极小L 估计量
. o# Y1 c1 r/ x1 }9 u6 vMaximum likelihood method, 最大似然法
# V" j$ R6 w8 M% V3 v- V7 HMean, 均数; r8 V* I* W; h. t' e
Mean squares between groups, 组间均方8 {7 T! Z1 `* L4 y* M
Mean squares within group, 组内均方
8 A3 X- T& Z3 T: L; fMeans (Compare means), 均值-均值比较: s+ N3 ~! @, G7 n7 i
Median, 中位数
' U' m; J* G; j! K# S5 CMedian effective dose, 半数效量
* F& T+ `9 Z" |7 b4 |0 vMedian lethal dose, 半数致死量
& R! b" k4 D0 t* [3 V; U, y3 I3 mMedian polish, 中位数平滑
2 O$ N. p; c3 S$ E- s8 lMedian test, 中位数检验
X) m, b9 @" \+ e! wMinimal sufficient statistic, 最小充分统计量
0 i! g) M) ?% S( J; A" b" j8 ZMinimum distance estimation, 最小距离估计
4 {9 h/ t; e5 iMinimum effective dose, 最小有效量+ G6 [# |9 R8 B$ T. _' C
Minimum lethal dose, 最小致死量
/ J; N. ]( M$ a# PMinimum variance estimator, 最小方差估计量
. k0 F3 A1 E0 g- m) F2 l1 E2 bMINITAB, 统计软件包
+ r; a" t3 O- AMinor heading, 宾词标目
! X o) {0 W4 A, U0 V5 `Missing data, 缺失值6 t8 u8 ]; d: m. x% ~
Model specification, 模型的确定4 D( s, M$ }5 y7 X, |# {
Modeling Statistics , 模型统计
! r3 T) v3 F% Q6 V. g2 h, W# w: j. ]Models for outliers, 离群值模型
) M9 Y- d$ E# z( |Modifying the model, 模型的修正
+ e6 e" P: S7 g' X- T/ R UModulus of continuity, 连续性模8 k; M( `* P0 @' ]* H% A4 _2 T
Morbidity, 发病率 - V! u0 ^3 S& `* y0 D
Most favorable configuration, 最有利构形
. u. T. l1 [' mMultidimensional Scaling (ASCAL), 多维尺度/多维标度# ~8 E! Q. P: S
Multinomial Logistic Regression , 多项逻辑斯蒂回归5 v) _8 n8 P! q8 I, ]3 h5 I8 e
Multiple comparison, 多重比较$ S+ O, e6 x" S3 O& ~" L
Multiple correlation , 复相关
8 m# z) S) f6 m dMultiple covariance, 多元协方差
$ m! |7 t+ N! Z: C& n# I6 f1 ZMultiple linear regression, 多元线性回归
3 Q4 Z& E. C+ ~6 vMultiple response , 多重选项8 w- [7 S. v4 `' A
Multiple solutions, 多解' d$ \5 A) E! ?7 i, D( O
Multiplication theorem, 乘法定理
% x1 L( R1 _% t9 m2 h" J( d2 @Multiresponse, 多元响应
& ]' U- b$ }6 [/ ^8 T9 DMulti-stage sampling, 多阶段抽样
' U9 o$ }( N; @$ C# |5 oMultivariate T distribution, 多元T分布 ]. z" D7 H; i% @. s; L" P% g; T
Mutual exclusive, 互不相容0 x8 j! U5 A$ H+ D
Mutual independence, 互相独立
& L0 n8 o5 ~5 G) K8 e8 I8 pNatural boundary, 自然边界! x* [' w- C! c9 T& q/ Q4 M
Natural dead, 自然死亡
+ P5 G- t; Q2 M7 w4 wNatural zero, 自然零% o. I- b5 B' E' k: D7 L
Negative correlation, 负相关
7 N2 V, Z0 h0 Z# k( c+ t. |- M+ _Negative linear correlation, 负线性相关
# T' h1 G3 q/ _; o1 C1 T8 x- F/ U6 QNegatively skewed, 负偏
2 D' H2 ~8 ^& F! n6 ]Newman-Keuls method, q检验3 N @7 e+ b8 B9 z8 _
NK method, q检验
) H& d5 O' F: n3 e8 wNo statistical significance, 无统计意义
( h! f) ~1 G; i! ^% _Nominal variable, 名义变量
; {6 |* t: z# r. w8 SNonconstancy of variability, 变异的非定常性
) f+ w p& p; c8 P/ V1 n4 L) a0 |8 JNonlinear regression, 非线性相关$ ^, T" k' j4 |0 J$ [& \
Nonparametric statistics, 非参数统计: G8 ^9 b8 `' g1 P+ h
Nonparametric test, 非参数检验; b6 g% H" i* l, ~
Nonparametric tests, 非参数检验
4 @0 L. A j/ T( E8 uNormal deviate, 正态离差, y: D9 h) c1 t, G! F3 f
Normal distribution, 正态分布$ U" i; q% O) O( z7 J
Normal equation, 正规方程组# {' {/ j" d( p* q
Normal ranges, 正常范围2 d) w$ s8 G( k: ~# k
Normal value, 正常值+ @# u: o+ Y# C6 F8 t1 B5 s: B
Nuisance parameter, 多余参数/讨厌参数3 P. e4 H# ? {
Null hypothesis, 无效假设 $ m( M& G. b& S; Q
Numerical variable, 数值变量; o, x6 \8 p% n8 C: s4 B
Objective function, 目标函数
# O" s0 O# ~) ], ?# |Observation unit, 观察单位$ p7 ]6 v6 m/ F4 U( s4 I
Observed value, 观察值
1 a! x& H$ f! E" cOne sided test, 单侧检验; Z7 ~) v, q1 M0 O$ K+ A; @- k
One-way analysis of variance, 单因素方差分析
% Z' ]2 Y3 k- OOneway ANOVA , 单因素方差分析
* r# @2 j+ B/ B$ W9 kOpen sequential trial, 开放型序贯设计
8 L# X% d# \7 v2 u/ q# f3 }Optrim, 优切尾
. b& m1 Q) S f( N# @% l/ F. KOptrim efficiency, 优切尾效率+ c6 I/ p: P) I$ u
Order statistics, 顺序统计量- Q& ]8 B7 f9 f4 E' V1 Q. ~
Ordered categories, 有序分类, q4 i9 W. r+ i3 k
Ordinal logistic regression , 序数逻辑斯蒂回归
, g* [% n. \# d$ `1 g5 l) ~. u; hOrdinal variable, 有序变量
2 u, @6 k S! M7 j+ FOrthogonal basis, 正交基
, L. `% i' m' F2 m) T: I9 \Orthogonal design, 正交试验设计
) {4 n ?$ V1 g& {5 x- Q3 KOrthogonality conditions, 正交条件
+ F8 k& c3 [ k `5 d3 o$ tORTHOPLAN, 正交设计 ( }+ ]% Z$ @( L G
Outlier cutoffs, 离群值截断点0 V1 _! o; K. Y0 n+ ]
Outliers, 极端值
" c6 d2 L1 D6 e D5 F8 ^OVERALS , 多组变量的非线性正规相关
, {$ [/ t* a. r7 m* [, i' DOvershoot, 迭代过度
- R! J7 n0 i7 h1 E- K; S+ qPaired design, 配对设计
$ ], T7 |2 X1 YPaired sample, 配对样本
( M+ x$ {' ^5 N0 kPairwise slopes, 成对斜率
( l/ I" G! Q- l x! YParabola, 抛物线- u2 C3 v. a' l% x3 a- i
Parallel tests, 平行试验5 y a) l& g+ I' X9 y; \3 n! d
Parameter, 参数) A& n. ^2 T/ J( q1 `
Parametric statistics, 参数统计8 A4 P) \9 m9 u: Z J
Parametric test, 参数检验# r8 T4 }/ U0 a4 X+ q j: N# u& H
Partial correlation, 偏相关9 O) s: P! ?) }6 `0 O" S F% M& X
Partial regression, 偏回归
: Z! U, H8 k5 S/ EPartial sorting, 偏排序
6 _5 ? f- N* C; {' @+ p. X4 qPartials residuals, 偏残差
* e( x+ `8 l" gPattern, 模式" Z+ M9 l t7 ?5 `
Pearson curves, 皮尔逊曲线
. E# Q, \" `4 ~Peeling, 退层! x( [; ^9 o0 M/ m3 g
Percent bar graph, 百分条形图
5 K" e8 ?+ n1 V' R; k1 \Percentage, 百分比3 Q* h" }: c% X. S
Percentile, 百分位数3 ~, S$ Q( r, U0 m) p
Percentile curves, 百分位曲线
( d7 g( v, l, B8 XPeriodicity, 周期性
: ^* X, X% A6 z, e, d; h5 bPermutation, 排列/ g' T O, l3 f$ F$ c
P-estimator, P估计量
+ w6 `% @0 a1 D, A j7 n. j" d1 LPie graph, 饼图
8 G( _0 z- V9 ]8 ?$ ~8 v) @+ sPitman estimator, 皮特曼估计量, Q2 @7 C8 k: Y$ o; [, @$ J) u. W: K
Pivot, 枢轴量
8 b- Q, Y7 E% ?; |' `Planar, 平坦) d4 p) b$ E: J. u" }
Planar assumption, 平面的假设. Q& a& R. a' a: ]8 r
PLANCARDS, 生成试验的计划卡! A: V' m* ]8 P
Point estimation, 点估计
6 G" L2 `4 U/ S3 |7 O, x: nPoisson distribution, 泊松分布
. }' f$ Y' a5 O; q# aPolishing, 平滑
9 |& p: B `# T3 k9 _) H. O" BPolled standard deviation, 合并标准差
! w& b' j, i* {: s6 QPolled variance, 合并方差
^/ ]' I5 V3 u. h2 iPolygon, 多边图
& Q; Y8 `$ @' O$ ~! l; qPolynomial, 多项式
x7 X4 A' x3 p+ ~Polynomial curve, 多项式曲线
( H( n0 [5 h$ g) yPopulation, 总体
: J4 E/ W* i$ j/ OPopulation attributable risk, 人群归因危险度4 B4 o2 C& C( y+ R( }# ^% P
Positive correlation, 正相关
7 ?7 k! V& f8 x# L1 L0 DPositively skewed, 正偏
3 q" m' E7 P7 B/ U2 A% mPosterior distribution, 后验分布! y6 p8 O* M6 x
Power of a test, 检验效能1 h* l6 n2 w+ c% J
Precision, 精密度
+ s0 Y( f2 {1 P6 e" JPredicted value, 预测值
% m( g& R' [+ A- W+ a1 m! VPreliminary analysis, 预备性分析
8 K$ A& w* B! r% b, P r: k- E& LPrincipal component analysis, 主成分分析/ f( U( [% n& c5 L' F, [7 U
Prior distribution, 先验分布$ m) |* b% \/ W* C7 Z: F8 y
Prior probability, 先验概率 ^9 N5 N6 m! f2 v
Probabilistic model, 概率模型% m0 @4 m( l2 B. L1 ^
probability, 概率
6 ~' r) K; D9 p7 V! bProbability density, 概率密度
' t) V# o# e' }% ` Y8 AProduct moment, 乘积矩/协方差3 f& m% s( r: T' g4 w1 n
Profile trace, 截面迹图+ {3 P6 j X0 m& ]1 O4 k/ p
Proportion, 比/构成比
( m) C0 u! M+ E4 [ T1 E. r. hProportion allocation in stratified random sampling, 按比例分层随机抽样' U, g& s5 o h9 A1 S" c
Proportionate, 成比例; o7 Y5 O+ h7 A( f
Proportionate sub-class numbers, 成比例次级组含量
3 S0 d: {( @7 `! HProspective study, 前瞻性调查% T9 R( x# r) j3 q
Proximities, 亲近性 4 U' t' g& ?6 Z
Pseudo F test, 近似F检验
. K) C) T4 \% F) ]9 OPseudo model, 近似模型
6 V+ Y+ g" j* `6 P! _' H* J/ ePseudosigma, 伪标准差! x, n3 Q9 B; s9 J
Purposive sampling, 有目的抽样# m/ l& ^9 L. b! `& J4 G5 z
QR decomposition, QR分解8 v6 V0 t' R0 \$ [
Quadratic approximation, 二次近似$ g% |* t" g. e
Qualitative classification, 属性分类1 L0 d% O. K- W
Qualitative method, 定性方法) T1 Q1 _ L9 W
Quantile-quantile plot, 分位数-分位数图/Q-Q图
2 U: u S% g5 kQuantitative analysis, 定量分析
& i9 ^" U% W) Q5 ?Quartile, 四分位数
* `- t+ Q% Y# Y, ZQuick Cluster, 快速聚类/ V; ]/ v3 X# p8 N9 }7 [
Radix sort, 基数排序
; V& @& s+ S7 F0 sRandom allocation, 随机化分组5 `$ I3 k$ ~6 q8 j
Random blocks design, 随机区组设计% R- F; f' x7 Y W- _: M, a8 ^" _
Random event, 随机事件" f( o; s* u* L/ @8 u+ O
Randomization, 随机化( e9 G) s8 C# ^% `5 D$ e* t0 ?7 o
Range, 极差/全距
5 P, d, I) `9 H5 O' eRank correlation, 等级相关
; N9 f5 f1 r4 n+ V0 gRank sum test, 秩和检验
' p* O2 i4 L, v0 m) j$ Y: {Rank test, 秩检验
$ Y( u: i+ ^* C f+ [Ranked data, 等级资料& o7 h0 U% z/ ]5 o0 p$ r
Rate, 比率8 m, I" n8 O. Y' T! m
Ratio, 比例& K6 `" F7 M( Q+ K
Raw data, 原始资料9 y5 ?2 ~) W4 ~ n0 x H* M
Raw residual, 原始残差
; Z4 w2 r! K- c# o; V! L$ N9 ?Rayleigh's test, 雷氏检验
( P# w# l) o, s- bRayleigh's Z, 雷氏Z值
; o& C4 O8 { w+ F& {Reciprocal, 倒数
3 g* @0 r, }8 U5 U& v) K9 D7 TReciprocal transformation, 倒数变换
6 O+ z+ ?" K$ b$ ~Recording, 记录
, g* ]+ ?* I1 LRedescending estimators, 回降估计量4 s% U4 w/ E* g' m, B7 T
Reducing dimensions, 降维6 \- Q( H. u' ~, z
Re-expression, 重新表达$ z; t2 t8 O, b J [
Reference set, 标准组
/ O% U9 C2 i8 x B& T! k MRegion of acceptance, 接受域
! a/ H' H* `, J* V) gRegression coefficient, 回归系数( M+ V: c$ b4 X! H1 h% P
Regression sum of square, 回归平方和6 m! F, k1 N6 W+ r1 I3 E
Rejection point, 拒绝点3 V' ^' n K1 m' ^
Relative dispersion, 相对离散度& z( l3 |2 G. G1 z1 V
Relative number, 相对数! b4 a' n7 C# u; A: A6 c
Reliability, 可靠性
3 X" K" w/ ]0 I1 GReparametrization, 重新设置参数
$ \& k1 p3 t6 i; b) hReplication, 重复. ^+ C# ?1 v( M. J6 C- j! n
Report Summaries, 报告摘要
4 L2 R( u2 p; b; aResidual sum of square, 剩余平方和 D, |2 c) L `8 ^3 ]
Resistance, 耐抗性2 Q) V7 {# p ]) n8 S" z
Resistant line, 耐抗线
. y, J* } Z9 d# }0 m/ u6 ?Resistant technique, 耐抗技术
; M: h2 C( t' sR-estimator of location, 位置R估计量
: A: s7 e2 @4 RR-estimator of scale, 尺度R估计量
u1 b# W5 Q3 E8 |1 r; O+ X( TRetrospective study, 回顾性调查
( ~1 ]4 G0 D2 r; X/ r" QRidge trace, 岭迹
" b% C, T" F& k4 S$ n+ uRidit analysis, Ridit分析
/ x3 i X8 C/ y2 t4 g4 _Rotation, 旋转
7 |# @# l! L; l( Y# {9 h; {Rounding, 舍入" V2 M ^( x1 I' ]' V
Row, 行
. `6 V" r# b1 v- W( DRow effects, 行效应$ g* [$ I5 m! b" p
Row factor, 行因素
/ V* M+ H0 G& j* ` cRXC table, RXC表- X/ C- z, e4 \
Sample, 样本
5 K' ]: T1 x! A# `% BSample regression coefficient, 样本回归系数. f) I7 @$ R1 l' \
Sample size, 样本量
5 ]% `4 ^( N G) t) r( ISample standard deviation, 样本标准差+ n. X2 P! J4 Z$ u, Q- y! @
Sampling error, 抽样误差
5 K' @1 p& C' F4 ~SAS(Statistical analysis system ), SAS统计软件包. l& I' R. C! V0 \
Scale, 尺度/量表
* }2 e" u; |2 r9 Y& T$ J( oScatter diagram, 散点图5 ^8 h1 t9 F3 T+ X$ f' e8 h
Schematic plot, 示意图/简图
" A) I" N& A1 s: TScore test, 计分检验
) t; z: [2 C/ I! _+ C2 n% P# ]: RScreening, 筛检0 `" x3 }) J! ]0 I4 `; v- I8 i: V
SEASON, 季节分析 8 b5 [2 W# o5 e+ s5 I
Second derivative, 二阶导数
3 k# Z/ \3 u3 J" O5 cSecond principal component, 第二主成分7 [* t" ?* n9 j/ f
SEM (Structural equation modeling), 结构化方程模型 " \3 F: Y8 e; K$ W, w W
Semi-logarithmic graph, 半对数图
7 X0 o$ |4 \' K: \' y1 {$ ?8 |+ {Semi-logarithmic paper, 半对数格纸; ^6 w9 z" {1 t% m
Sensitivity curve, 敏感度曲线
$ M7 y. o/ Q+ i6 k& i. BSequential analysis, 贯序分析7 U% q. r l \. V L
Sequential data set, 顺序数据集7 b6 N; w) ]" Z U
Sequential design, 贯序设计: q' Z9 V! K2 t" K$ F
Sequential method, 贯序法
5 y0 \2 }1 j2 P2 r- F( |; B. D, x" hSequential test, 贯序检验法2 f1 t# S5 z+ e0 A9 ?# s3 H' v2 g
Serial tests, 系列试验; y! d4 }5 K/ w" a {% u
Short-cut method, 简捷法 ( d5 x! U E) |- Z0 Q
Sigmoid curve, S形曲线, W4 z0 j- a4 r4 w0 k4 h
Sign function, 正负号函数" d7 O4 t; y, a" ?: Y2 d$ s, q y
Sign test, 符号检验+ ~4 R1 W3 X* k3 `; O% L0 |- L
Signed rank, 符号秩. U' G; r2 F5 n! f: z- n) H
Significance test, 显著性检验
* }$ G- m$ h" k9 v3 e% B7 i) JSignificant figure, 有效数字8 L% X$ ~: W: t4 p. S: ~
Simple cluster sampling, 简单整群抽样
1 D7 ?! K6 _: \/ M; cSimple correlation, 简单相关: m$ Z6 e5 H2 q
Simple random sampling, 简单随机抽样
! l1 N. A" \, m; P" G0 c" eSimple regression, 简单回归
7 e1 j( ^4 i8 Y, m) e6 Isimple table, 简单表& e# c/ Z) p0 C
Sine estimator, 正弦估计量
% r5 c5 v$ S/ c# a& q$ _Single-valued estimate, 单值估计$ C) X* e. Z4 ?. H/ D
Singular matrix, 奇异矩阵8 {, M. p. {) F/ x
Skewed distribution, 偏斜分布/ B- p |8 s) c/ |, t7 _2 W
Skewness, 偏度. c: S; H/ Z9 ~( ~7 U# x
Slash distribution, 斜线分布
" X1 L7 l0 S) U& T2 [0 }Slope, 斜率
* c! m/ L9 X, a2 M& }9 s% U; M, nSmirnov test, 斯米尔诺夫检验; L' w1 K, o- d _
Source of variation, 变异来源: R9 Z3 c# N- f& A4 e3 Q+ O) f
Spearman rank correlation, 斯皮尔曼等级相关7 ]; {5 E: a+ D3 j8 n
Specific factor, 特殊因子9 ]0 ]* O. p& y4 \! C2 u
Specific factor variance, 特殊因子方差1 L! V5 {; I8 C6 K- B
Spectra , 频谱( b! ~9 ~5 k$ N! s
Spherical distribution, 球型正态分布9 ~ G* r" k6 a3 U C4 r f
Spread, 展布: |6 ]5 x7 v+ k
SPSS(Statistical package for the social science), SPSS统计软件包: z, `! A( }: \; s8 P* H9 u
Spurious correlation, 假性相关
0 z) v4 d! L( g1 H! oSquare root transformation, 平方根变换0 y1 s! T: e8 c, R# L4 b% r
Stabilizing variance, 稳定方差: \( A5 u* U' z. C- U" |# Q
Standard deviation, 标准差4 `1 Y+ d. N8 m, t {* _ B* c. m
Standard error, 标准误0 }" E: s1 }' b! A* d9 d" T3 l3 i
Standard error of difference, 差别的标准误& z" d( Y, _) T" Z7 i5 R* m4 b. l
Standard error of estimate, 标准估计误差 z1 A) a3 T# I5 a) O
Standard error of rate, 率的标准误
' J- e; t( _: k7 c8 V& DStandard normal distribution, 标准正态分布
7 u8 k% G( ]7 k* iStandardization, 标准化2 I$ a7 F1 l5 E5 ^
Starting value, 起始值2 m) }" t l; i: K" E9 n
Statistic, 统计量
( \. t |. z" S2 B( U, u4 mStatistical control, 统计控制* ]; u; A3 N# o; W
Statistical graph, 统计图* O2 V) Z+ D" u2 i5 `: R5 t
Statistical inference, 统计推断% N. o! N I& U* T k- f
Statistical table, 统计表
! V% D! q( _ B1 m/ @! fSteepest descent, 最速下降法( p4 N% ~0 J- ?5 X
Stem and leaf display, 茎叶图1 c# j+ C* _ b) C: s+ E3 s" h
Step factor, 步长因子3 y% N5 T% |# B! e% y% Z# u
Stepwise regression, 逐步回归/ h! D+ ]& }& n
Storage, 存
/ M5 l9 V0 F2 `* hStrata, 层（复数）
* n- S1 y: ` U4 n8 X1 R+ `Stratified sampling, 分层抽样 r4 i- w9 V6 L8 _2 o: g
Stratified sampling, 分层抽样
6 x& D/ ^2 l- x8 Y. kStrength, 强度
/ x: Q5 T$ g; d' u y: ]Stringency, 严密性 B8 s, F) o6 S4 O: b7 i
Structural relationship, 结构关系" d1 R0 R9 H7 o! Z+ O
Studentized residual, 学生化残差/t化残差% d* e& W# \$ b, F$ K
Sub-class numbers, 次级组含量
+ K8 k2 d: f3 C, _# r4 `Subdividing, 分割
& p. _" Y- T# e6 h$ fSufficient statistic, 充分统计量4 ?2 l8 ?( ^6 i3 z
Sum of products, 积和3 g+ Q4 b: E$ Q8 g& Z, i9 P
Sum of squares, 离差平方和" t v* D' M( [& H. Q
Sum of squares about regression, 回归平方和
) d: J1 k9 x: Q. d7 [5 NSum of squares between groups, 组间平方和
% f! p U s( Q; T, l7 USum of squares of partial regression, 偏回归平方和% ~$ _: o$ [4 K
Sure event, 必然事件% G9 `. v b b1 J! i& ?
Survey, 调查+ y) n# X5 m+ U+ U. `9 E. Y& e5 N% j" g
Survival, 生存分析 x$ s$ L, G$ W) g* {8 E3 ?
Survival rate, 生存率
9 }( H/ F2 d% \( VSuspended root gram, 悬吊根图" m; M0 \/ u" r* G" Z
Symmetry, 对称
+ h: X4 A6 v) I6 c2 {# C: |) Z2 z0 _Systematic error, 系统误差
% H3 D" ^+ `/ ESystematic sampling, 系统抽样
~6 m- h1 }. Z! l WTags, 标签3 Z1 b* @1 _+ A' u
Tail area, 尾部面积
; v: {4 t& ~" R3 A+ lTail length, 尾长
1 H, \( ^* k0 ^* }Tail weight, 尾重- |9 R; C$ T- u @6 H9 H; b
Tangent line, 切线6 N6 k/ d2 A- {$ o- ]6 o* t
Target distribution, 目标分布
7 M0 r1 o2 R; U/ lTaylor series, 泰勒级数! n# w3 b5 q# L$ ~$ ~9 \2 a
Tendency of dispersion, 离散趋势# r& d$ ?% ]: H6 y- f# ^9 F- g
Testing of hypotheses, 假设检验" s. g2 z* Q. o4 K5 B
Theoretical frequency, 理论频数4 |& ]! m5 u- V
Time series, 时间序列
0 ~( }6 j* H+ B* d1 O% X3 _Tolerance interval, 容忍区间/ p l% Y2 Q8 y' u& E/ x$ G( P
Tolerance lower limit, 容忍下限( _& K& o4 e3 z, b) a1 I* t7 u
Tolerance upper limit, 容忍上限
; D; Z4 c1 T, d2 X& a0 L* `# ^Torsion, 扰率& x6 I% |3 H% d3 I2 I) u
Total sum of square, 总平方和
8 y: A2 k3 U0 pTotal variation, 总变异
I& u) F( e6 ^! w. L1 KTransformation, 转换3 y. z3 r ?; u# n
Treatment, 处理
# u" U5 K3 W, oTrend, 趋势3 B, m4 q) {; O& Z$ U- h+ s
Trend of percentage, 百分比趋势2 W) k5 L q, Q9 |( u, p* c; b: ]2 E
Trial, 试验( Z6 W( B ?( o a
Trial and error method, 试错法
& p# s* V! g+ y( ITuning constant, 细调常数
. J' C8 r# Y( xTwo sided test, 双向检验
$ Y* s" o( `* eTwo-stage least squares, 二阶最小平方( K7 N$ c b( S2 Q2 q. Z: s
Two-stage sampling, 二阶段抽样. }' x5 R0 `- l5 q# ]" u- z
Two-tailed test, 双侧检验3 \- \4 Y4 q3 Q. ?/ x9 Y
Two-way analysis of variance, 双因素方差分析
- c; f5 U5 d! B$ XTwo-way table, 双向表
& @2 W6 r9 D/ X7 y7 O+ EType I error, 一类错误/α错误
1 _$ ~* n; F7 G# I; X6 @! zType II error, 二类错误/β错误2 p$ ^* @7 Y' z
UMVU, 方差一致最小无偏估计简称7 k3 W. Z) U; s% X( a
Unbiased estimate, 无偏估计
7 X( O4 _) ], ^7 vUnconstrained nonlinear regression , 无约束非线性回归
& g6 |2 S8 U, K* BUnequal subclass number, 不等次级组含量
% P# }9 T# }0 i' E+ z6 YUngrouped data, 不分组资料; }/ y. D( t7 l: Q6 k
Uniform coordinate, 均匀坐标
7 d( W5 a$ E q9 v, kUniform distribution, 均匀分布
, p4 \% F+ b; c5 Y$ KUniformly minimum variance unbiased estimate, 方差一致最小无偏估计2 D/ |$ Z% o1 Q2 A/ U
Unit, 单元2 a0 s" L6 H" a
Unordered categories, 无序分类
* o# J7 }! _: Y* S1 c9 ZUpper limit, 上限; V5 D6 @: i7 }( } m; V
Upward rank, 升秩# K: n% [: Y2 [0 n2 {3 T6 G
Vague concept, 模糊概念: T/ R' U$ F p8 w. _
Validity, 有效性
8 N/ ~# ?# @$ I3 CVARCOMP (Variance component estimation), 方差元素估计2 Q# [" _# Y/ _+ z
Variability, 变异性
# z& p2 j- A; p, Y, hVariable, 变量# o; a! N# Z7 X" N' k
Variance, 方差
$ p# D: o) |4 v/ H9 Y! \7 J6 v/ iVariation, 变异
2 q3 ` [) V: j! P! b+ C. BVarimax orthogonal rotation, 方差最大正交旋转0 r' E% M P5 g7 f
Volume of distribution, 容积' K% s' ^; u& S
W test, W检验- l8 |" W$ ]: t" t+ s3 {: x
Weibull distribution, 威布尔分布
2 G2 p/ e5 v2 j) U( {1 s& u9 Q3 kWeight, 权数
" K) I6 b' q8 R, B' jWeighted Chi-square test, 加权卡方检验/Cochran检验
% z) k5 m! p+ L5 t2 Z4 `: GWeighted linear regression method, 加权直线回归- c" k1 V% Y3 l* W
Weighted mean, 加权平均数; b7 b! ~! Q7 Y( H! ?: p- T* C
Weighted mean square, 加权平均方差( W v# K- R$ W% D% J
Weighted sum of square, 加权平方和
5 z6 q7 ?4 Y, k) F4 Z) d* ]Weighting coefficient, 权重系数% t* a$ U# f0 k q+ H
Weighting method, 加权法
5 |+ Y5 R% y) z9 _0 hW-estimation, W估计量' d2 P- w/ v" h. x0 K; |
W-estimation of location, 位置W估计量& [. ^. H( j. \3 H- v; z6 n
Width, 宽度0 Y T& f0 _' ]1 b1 R
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
7 {; H4 _2 m/ W' l9 ~2 |! S; hWild point, 野点/狂点+ m& R9 l l( ~6 _( m( g" k! s( g
Wild value, 野值/狂值' E M2 P. p' I
Winsorized mean, 缩尾均值
, o2 Z7 O! E6 D# W! F4 jWithdraw, 失访
* M0 T: S) N- L0 C6 R9 vYouden's index, 尤登指数
y& I: s% q) NZ test, Z检验( x" q. _; G" v& u) O
Zero correlation, 零相关
0 f/ e5 ^, B0 L, E+ VZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
