|
|
Absolute deviation, 绝对离差9 h) s: h! g% K' `$ Y0 r5 W
Absolute number, 绝对数
- u& W% ]) x i1 K+ Z4 j1 @Absolute residuals, 绝对残差+ ]$ d4 D; t X; B) ^
Acceleration array, 加速度立体阵
& G4 M! Q z8 v. }Acceleration in an arbitrary direction, 任意方向上的加速度- E* v2 J, r- [+ @) D- H8 t" \ ` }+ }
Acceleration normal, 法向加速度7 r' v. Q* U4 G
Acceleration space dimension, 加速度空间的维数
1 t. Q4 w9 v0 C' ]; O: DAcceleration tangential, 切向加速度
1 e2 S8 ]0 N7 l; C& IAcceleration vector, 加速度向量, P$ L! g4 W0 l: x2 ]0 \* x
Acceptable hypothesis, 可接受假设2 [/ y+ @* g- d# i) p
Accumulation, 累积
3 r1 S3 N' m, v! E$ v ~7 aAccuracy, 准确度
" q1 ^( @- a5 D1 _5 m% {: p; YActual frequency, 实际频数
7 @/ h8 f: j% `3 l- Y z/ G sAdaptive estimator, 自适应估计量
6 J: q" h; M7 V0 E2 QAddition, 相加& Y0 P( k. @* _9 M$ W) R! R1 J
Addition theorem, 加法定理
# U7 Y4 K7 j4 p9 [2 ?7 N/ e ~Additivity, 可加性+ f4 T- D, w# m( v. b0 y
Adjusted rate, 调整率; ^1 B: ?9 ^# |; Y" m
Adjusted value, 校正值8 ~% s' A; Z; J9 f
Admissible error, 容许误差% } H4 u1 B- ]! @
Aggregation, 聚集性
- L) t% g) u: h# T% t( E# {1 HAlternative hypothesis, 备择假设
+ ^# [0 u0 A2 j, o; NAmong groups, 组间
3 l4 f& {6 c- Z. q3 C8 GAmounts, 总量; f3 x6 J$ b' g4 w0 V9 l8 E
Analysis of correlation, 相关分析6 {8 m9 Z$ A' f9 R; T# I) t
Analysis of covariance, 协方差分析* T9 v$ R% w/ b5 S+ D5 T. k; s
Analysis of regression, 回归分析
. b1 g- i! [- I7 {2 h% }Analysis of time series, 时间序列分析; v5 i; r! ?3 g! H
Analysis of variance, 方差分析2 p* s& g; d( v Z" G; h7 Z
Angular transformation, 角转换
% M' I" B) s( O0 s1 r7 A6 a/ sANOVA （analysis of variance）, 方差分析
% ^' d( z: O8 |, g( O8 M8 xANOVA Models, 方差分析模型2 U) z: h: A1 k: n
Arcing, 弧/弧旋3 l: q; \3 J9 e$ O/ K
Arcsine transformation, 反正弦变换" n# l- Z, L0 @- S/ V2 D( K
Area under the curve, 曲线面积
. w! T. q; a- v2 N) K( V" cAREG , 评估从一个时间点到下一个时间点回归相关时的误差
' \& e) A: B. @ARIMA, 季节和非季节性单变量模型的极大似然估计
/ E- Z8 `# B S0 aArithmetic grid paper, 算术格纸
* C2 W- E" x9 {3 C$ D/ A$ |: KArithmetic mean, 算术平均数( J3 `5 T* }3 |5 p
Arrhenius relation, 艾恩尼斯关系0 D: |- K7 @. K0 g7 Y2 M
Assessing fit, 拟合的评估
. ^7 B, G a" T# L8 dAssociative laws, 结合律+ M+ g) L. }. B, ~2 W% d
Asymmetric distribution, 非对称分布/ G, K* |2 F- w, T- b9 m5 a% ~
Asymptotic bias, 渐近偏倚
& _! q9 \4 Z1 x3 W) g3 D& iAsymptotic efficiency, 渐近效率
( z8 y! Z5 W+ t2 ]: a: D9 FAsymptotic variance, 渐近方差
& o8 J+ Z) S/ L+ X# n" h! c; HAttributable risk, 归因危险度+ [3 u# D0 r5 Z. c
Attribute data, 属性资料, p: M1 D: x) x. c) c5 u& ^
Attribution, 属性
3 H. Y5 R! z* {) E* U: x+ {Autocorrelation, 自相关
# N; y! I0 P1 _Autocorrelation of residuals, 残差的自相关: J: \! M* I0 G7 r; ~
Average, 平均数. R6 [: ^9 F3 x9 f9 d0 s( |
Average confidence interval length, 平均置信区间长度
* J) J4 V5 o" M+ q) _Average growth rate, 平均增长率) d6 @: Y5 z. X t _2 k4 d
Bar chart, 条形图
* X4 {8 }# n4 \1 HBar graph, 条形图4 u1 A( Z3 R2 A; m* ]" g2 Z
Base period, 基期
3 E- s `; n1 `! _# w$ ABayes' theorem , Bayes定理! V3 \! r8 {' M" @$ E
Bell-shaped curve, 钟形曲线
1 A# _ ]" T2 k/ {) j. H1 T+ M7 ZBernoulli distribution, 伯努力分布
* L+ \7 S* u1 @: \7 X7 ~9 ABest-trim estimator, 最好切尾估计量0 t# @3 j6 J2 { `. c+ K0 ~
Bias, 偏性2 p: O# o2 S1 r0 A& `! Y
Binary logistic regression, 二元逻辑斯蒂回归" ]# O% u' m S% }0 n) e; }, `
Binomial distribution, 二项分布
0 {, G) G2 O. N5 l- P8 o6 bBisquare, 双平方% X: K% S! j8 ?
Bivariate Correlate, 二变量相关 r0 d% N1 i k4 T+ C9 P
Bivariate normal distribution, 双变量正态分布" b/ C( j; J7 v1 N* _4 F& O
Bivariate normal population, 双变量正态总体2 i+ F: f# x/ _* d! D
Biweight interval, 双权区间# I7 V, ?0 C5 T! p
Biweight M-estimator, 双权M估计量
' ]/ r) U7 V% O( K* DBlock, 区组/配伍组
3 o5 R9 s! L6 t3 b e$ s) DBMDP(Biomedical computer programs), BMDP统计软件包
s: G: U8 r- _/ [1 j2 iBoxplots, 箱线图/箱尾图
) d' S4 m/ p2 Y7 q! u" d3 w3 CBreakdown bound, 崩溃界/崩溃点
* o: Q- }+ H. i8 `Canonical correlation, 典型相关
% u: C+ |( [6 \9 T4 S% u, W$ v/ SCaption, 纵标目/ N1 V) f1 s* W. I5 I. Y* ?
Case-control study, 病例对照研究% w- V* z' k7 Z4 E8 g
Categorical variable, 分类变量
' \* O2 D, y z) q$ vCatenary, 悬链线8 D+ N1 W$ u. t' F9 G6 J% G0 W
Cauchy distribution, 柯西分布1 H- {6 L+ i& @( U5 m. p
Cause-and-effect relationship, 因果关系
! |6 ]& L/ J+ T/ o! C' oCell, 单元; |# a5 _. g2 ~0 d
Censoring, 终检
; t& y5 Z+ [) K/ PCenter of symmetry, 对称中心
5 b( _/ k, k5 K. K; ICentering and scaling, 中心化和定标
/ |2 S2 C& i3 }8 k7 ]* T3 eCentral tendency, 集中趋势, J- F6 k6 x% b$ H8 N+ h. i
Central value, 中心值, n$ P/ V* K6 @
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测+ r+ S5 j. s! W7 p* ^
Chance, 机遇
5 N2 Q, ?4 E4 h- V: i) zChance error, 随机误差. `: W3 o% {+ n0 n8 v: _
Chance variable, 随机变量
( X; p8 v/ ^& X) H( MCharacteristic equation, 特征方程, S7 C, y: l3 {
Characteristic root, 特征根
8 Y9 ?7 A2 b, J! u+ D1 cCharacteristic vector, 特征向量1 B2 I& I3 D) s Z! X6 Q2 `
Chebshev criterion of fit, 拟合的切比雪夫准则$ P( Z- ?4 h8 H# b& z* }
Chernoff faces, 切尔诺夫脸谱图
+ Y/ v' T+ `5 w9 _9 ~; Q# hChi-square test, 卡方检验/χ2检验
/ e8 T5 _( G" B7 RCholeskey decomposition, 乔洛斯基分解
$ J, }/ x7 s k$ v8 j2 JCircle chart, 圆图
0 @2 V9 e- w. y: n, }' eClass interval, 组距7 M( O' H& f- |# ^6 d
Class mid-value, 组中值
. _1 X9 f% E6 w& N! OClass upper limit, 组上限9 v k9 U0 Z+ j% o+ J
Classified variable, 分类变量 O4 g$ h6 f, w; d: l
Cluster analysis, 聚类分析
, k! t( B [$ z, BCluster sampling, 整群抽样
" A# x3 T l4 B6 z9 }Code, 代码
! n! O) z2 A: K# h7 f4 [Coded data, 编码数据
! a1 z; X1 b9 [5 z$ R$ zCoding, 编码" y/ e5 F/ |0 u8 `
Coefficient of contingency, 列联系数
" O+ ^5 S- W4 [, h" l: GCoefficient of determination, 决定系数
& N2 @: |% P6 ] u6 ]6 N4 lCoefficient of multiple correlation, 多重相关系数
: i' q7 v" Y& G/ O$ GCoefficient of partial correlation, 偏相关系数$ l& k7 ]# J& q3 l1 t9 c
Coefficient of production-moment correlation, 积差相关系数& }- {0 a& c$ g
Coefficient of rank correlation, 等级相关系数
1 Q4 X1 \2 x5 ~( t9 D5 v) HCoefficient of regression, 回归系数
& q9 @# e/ K% z! F& u8 J: KCoefficient of skewness, 偏度系数+ S# A: K8 L3 o) Q. Q6 A
Coefficient of variation, 变异系数0 [/ U* p1 A! ?' k: _; d
Cohort study, 队列研究
; k7 ^; z; e }$ C# ^Column, 列2 H0 S1 }" s% J( }, U7 \. D1 j
Column effect, 列效应, r' i; E: x+ C, M. w$ k b! b
Column factor, 列因素0 W. N; u5 |: N5 _: j9 e+ X# Z9 T
Combination pool, 合并
# ^* t& D7 A' _* d9 J: }' [' eCombinative table, 组合表, z$ L) r5 X1 p- }
Common factor, 共性因子
3 i' c9 M* p0 K dCommon regression coefficient, 公共回归系数- l# w( s5 x/ _, _3 p; l7 g% f
Common value, 共同值* M3 j5 ] w9 G3 R1 q( v
Common variance, 公共方差
9 {, {, ~# n: H6 Y+ ~7 L9 cCommon variation, 公共变异
+ A$ {& l* J2 b9 t6 O1 K! JCommunality variance, 共性方差
- @ h! z' t) b+ l& j( xComparability, 可比性0 R2 [8 e( r& Y! j- N
Comparison of bathes, 批比较
# P3 G8 q, h+ C6 ~" ~& n; l! jComparison value, 比较值
7 i7 ~6 u+ L+ [0 ` x/ K0 ^' \+ @Compartment model, 分部模型
. N* V9 N7 K3 U- v! p+ |' mCompassion, 伸缩9 g. z( [: S1 H6 `
Complement of an event, 补事件0 _" b a7 z3 o8 Y* z& B I `" V
Complete association, 完全正相关
" S3 A3 L& _, o3 TComplete dissociation, 完全不相关3 C& M5 }/ o0 P/ m, a
Complete statistics, 完备统计量
+ K$ W3 J2 J1 y5 @0 [Completely randomized design, 完全随机化设计
# A' @) Y8 k/ {) h1 m: AComposite event, 联合事件
* a* K; v1 @- hComposite events, 复合事件4 Z& ~# g6 ^( Q- {( B7 ?
Concavity, 凹性* k7 a8 J h" J( m0 r5 Q6 O
Conditional expectation, 条件期望/ y$ Y" X7 S4 b% u0 o/ o' v6 J
Conditional likelihood, 条件似然
$ m& d% T z mConditional probability, 条件概率
+ G: K) H2 E/ ?3 Y1 @8 YConditionally linear, 依条件线性- {. N0 j( h2 Q9 e; q) Q6 v* y
Confidence interval, 置信区间% U% H7 H6 N2 _; _
Confidence limit, 置信限7 O- k( z! a& h: Z
Confidence lower limit, 置信下限1 X5 C7 U) Q' q
Confidence upper limit, 置信上限 l v: C2 l7 s2 W4 f6 z' g
Confirmatory Factor Analysis , 验证性因子分析& ^% R: J& O# t& x% C- ~$ M
Confirmatory research, 证实性实验研究! R& K& o: b& c) H" A5 x
Confounding factor, 混杂因素
) Q6 M* z# E& q, OConjoint, 联合分析' `# \, ^4 W' P5 C% r
Consistency, 相合性
& ]/ q; y* e8 P" h2 Q" n6 t# eConsistency check, 一致性检验
9 u" x9 x! x7 E4 eConsistent asymptotically normal estimate, 相合渐近正态估计: i( W: w# \3 o5 F2 a, i8 r: t
Consistent estimate, 相合估计- R* P: a3 v# p& ~
Constrained nonlinear regression, 受约束非线性回归
, X4 i- ~; L2 B: D' y# SConstraint, 约束/ l8 t T( K7 Z4 J
Contaminated distribution, 污染分布) j2 b% i$ c4 _
Contaminated Gausssian, 污染高斯分布
C* J+ m3 j9 ]- yContaminated normal distribution, 污染正态分布" B# s3 p: d/ Q+ {
Contamination, 污染" y+ f6 S/ p/ p! P
Contamination model, 污染模型
- N* q* W) U. d( T$ u% V8 VContingency table, 列联表* v6 a) ^- I8 I/ O
Contour, 边界线% F* H) W) f* E! \! v
Contribution rate, 贡献率 K. Z: d3 m L1 |, y1 W J1 n( `, M
Control, 对照0 N9 g/ _4 ]% O7 l6 a. v
Controlled experiments, 对照实验0 A$ }1 M' e! s0 X+ v
Conventional depth, 常规深度3 H q/ L% [, P2 m2 m
Convolution, 卷积, }2 y1 e$ T* k1 M5 D% U
Corrected factor, 校正因子
% _' ~" t) z+ bCorrected mean, 校正均值1 j7 t( v0 B2 g; X, G; K q( {# @2 C* @
Correction coefficient, 校正系数5 d" F: o+ D; i9 k
Correctness, 正确性
$ C Y5 B: X( j9 T& C' \. SCorrelation coefficient, 相关系数
8 T; @8 O5 x6 R" ECorrelation index, 相关指数" P0 D A- `7 Y4 Y" v
Correspondence, 对应
0 O2 |: F" s& E4 aCounting, 计数6 \4 _ R. ]' w. H/ q
Counts, 计数/频数
* i) ]9 ^8 w7 ]3 c6 v& V' E! _7 FCovariance, 协方差
* {0 E" Y' x# m0 O( OCovariant, 共变 ; g4 z: m- w+ Y; O$ i( n9 w t& W: w
Cox Regression, Cox回归& M% `) b' A l, r, d+ }3 k: g7 k
Criteria for fitting, 拟合准则
( {4 X5 m" A U0 H" n4 O9 g" fCriteria of least squares, 最小二乘准则3 e& c' ~" c w. [
Critical ratio, 临界比
# u) u/ L# P% S) v8 l J HCritical region, 拒绝域; |1 g6 b) J4 K' r! @2 t1 S
Critical value, 临界值+ d! h. X. l1 o# U5 y* m
Cross-over design, 交叉设计. m0 H; P4 |0 `( K. b
Cross-section analysis, 横断面分析
$ r$ _5 Z3 c; w2 X6 I4 JCross-section survey, 横断面调查% s2 |- K, E5 h6 t# Q! o3 A w: n- W
Crosstabs , 交叉表 # N) j% k: p8 E. O- I b( k
Cross-tabulation table, 复合表, C9 A) x8 E# g
Cube root, 立方根( x1 ]# A: A" a3 c3 {% d* j) V) w
Cumulative distribution function, 分布函数8 v0 c o; x( T% N
Cumulative probability, 累计概率* M/ K( M; ^" m
Curvature, 曲率/弯曲% R) J( A1 E7 E: ] l; C
Curvature, 曲率
; Z& s5 S( k1 Z, _Curve fit , 曲线拟和
) a1 x/ n- J( o8 X+ HCurve fitting, 曲线拟合. ~, e w# Z# w8 k9 l' I9 e
Curvilinear regression, 曲线回归
s3 x0 {3 {' x# L2 K5 F/ H! v' eCurvilinear relation, 曲线关系
- i, L7 k. i% w; c% J& V- mCut-and-try method, 尝试法
: b N0 Q- {' T1 _6 z/ |" k( Q8 `Cycle, 周期
! f+ {4 ~. o6 ]2 rCyclist, 周期性
5 A) ^! _! v! F$ ?D test, D检验9 V3 u% G; q9 X5 b
Data acquisition, 资料收集
2 D9 [! c! |" i) ^1 N3 UData bank, 数据库
! Z5 [6 l# H5 n5 D& J$ o/ n ~Data capacity, 数据容量, q4 @# ~4 m! x6 ?
Data deficiencies, 数据缺乏" [/ n" @8 A5 d5 _" Z
Data handling, 数据处理
+ X9 J$ q {: P& V( NData manipulation, 数据处理6 N4 G* Z N7 z9 S1 \
Data processing, 数据处理
, O4 n# @: D0 P1 z: V/ B/ ZData reduction, 数据缩减% O$ F. h4 w' r& t, K
Data set, 数据集
" I2 d% w/ p9 m8 x8 N& h2 B1 `Data sources, 数据来源. Y; P4 q! l s5 k- F
Data transformation, 数据变换% h6 G2 V5 C8 w( F
Data validity, 数据有效性
- Z5 S1 h; f. d9 DData-in, 数据输入
o+ `3 t9 o( |! d% zData-out, 数据输出/ v0 N4 v3 d6 A' ]
Dead time, 停滞期
4 {. K; x9 u: }. {, n2 J; J: GDegree of freedom, 自由度- G* p0 Z* I* w0 A' H+ T6 c
Degree of precision, 精密度
# ?: M+ P1 q R; lDegree of reliability, 可靠性程度
% R6 p k3 _. {0 W6 VDegression, 递减. T! ~$ C5 q% x, x3 v/ h! t
Density function, 密度函数
" k$ ^6 P. H: I( ?' RDensity of data points, 数据点的密度' m" O# t G" I d
Dependent variable, 应变量/依变量/因变量/ B6 r7 M: Q, n0 O
Dependent variable, 因变量
' ]- j1 o7 W4 s# d2 B# a9 bDepth, 深度
' {2 b" ~" b0 HDerivative matrix, 导数矩阵
8 l+ a7 T" P8 B7 TDerivative-free methods, 无导数方法 E6 X# Z+ p* c" f- G
Design, 设计: I3 T4 z5 P2 i3 o; \
Determinacy, 确定性
* B1 O' s2 e4 L7 c" r: IDeterminant, 行列式, _1 y- }' M* w2 U, M1 G4 X
Determinant, 决定因素
$ r' q" T/ g6 ?5 U6 uDeviation, 离差/ F: `3 C" U2 A% ~! B" J! I, k4 P
Deviation from average, 离均差( y |7 N/ P4 S
Diagnostic plot, 诊断图1 s$ a. X1 X, s
Dichotomous variable, 二分变量) e( R) i. a8 S* ?
Differential equation, 微分方程
0 M+ W8 Q2 A6 X& F* y( iDirect standardization, 直接标准化法& I$ r, \( V- p/ o; h" Q* L
Discrete variable, 离散型变量! T0 r1 I6 o' T, m. j
DISCRIMINANT, 判断
q9 m h3 k* `4 Y5 k( rDiscriminant analysis, 判别分析
' ?- o- U+ I# G! W) ZDiscriminant coefficient, 判别系数( N' T# _4 Q" |2 g+ f
Discriminant function, 判别值& `4 H4 l$ ]7 ^# w- w. n
Dispersion, 散布/分散度: r9 R8 k" `/ k' Z$ B2 K1 M
Disproportional, 不成比例的
4 Z( m# b! n& k8 s. jDisproportionate sub-class numbers, 不成比例次级组含量
1 r' T4 C! M! a' i$ zDistribution free, 分布无关性/免分布* W- L& @" l- V% W$ E( e) \- Z" _
Distribution shape, 分布形状& }1 L+ I' I7 ~2 u
Distribution-free method, 任意分布法7 H) Q: l# ~& Y/ G9 \" u
Distributive laws, 分配律
5 N4 f8 {" H# \! s! X# Z' \& ZDisturbance, 随机扰动项
1 d' c, s$ h; s/ J8 WDose response curve, 剂量反应曲线
5 l! S3 o# z4 N, cDouble blind method, 双盲法* \/ ^5 r+ l6 D9 n* g+ G8 E' X- L% K
Double blind trial, 双盲试验3 d( M' q$ N# E- g; e5 ~' W5 A
Double exponential distribution, 双指数分布
( p7 p' q0 G- I) yDouble logarithmic, 双对数
/ w/ @7 ~, v/ f% T: V, ^" QDownward rank, 降秩2 Q# `2 G% X# K$ n
Dual-space plot, 对偶空间图, t' m# o8 @7 ~* Q3 D
DUD, 无导数方法) ]" x p% S* ~2 o' }! m( u b0 Q
Duncan's new multiple range method, 新复极差法/Duncan新法9 g3 X; W; V) B( ?
Effect, 实验效应
3 Z6 r3 x4 n! o* ]Eigenvalue, 特征值& B. h2 `' E. }- i
Eigenvector, 特征向量
8 [8 V' [, X3 Z# C( x9 o0 sEllipse, 椭圆
0 r" ~6 u" W- ~, J. H- S/ w% NEmpirical distribution, 经验分布. d/ J- K% _! K. ]
Empirical probability, 经验概率单位3 |1 f+ k# [$ f
Enumeration data, 计数资料
) e+ L. F! F3 w& C6 qEqual sun-class number, 相等次级组含量. m* N8 F' {% g0 \$ x6 [
Equally likely, 等可能
# l, v* g6 n i0 _ d0 iEquivariance, 同变性+ J0 Z8 l5 L. A: X
Error, 误差/错误 A& Q, l9 A- R7 k
Error of estimate, 估计误差
6 M1 r9 F9 o8 M5 P6 O+ [" Y' f7 fError type I, 第一类错误5 N e+ d8 Z9 n, [$ j6 E
Error type II, 第二类错误
) @9 o3 {; g; Y3 q7 PEstimand, 被估量
d1 e5 }/ m! P& Q; N6 M& b1 kEstimated error mean squares, 估计误差均方 a. F3 q- O! {+ S8 g
Estimated error sum of squares, 估计误差平方和
' {" S# S4 S. L7 QEuclidean distance, 欧式距离; m5 k% T6 K. O8 I0 f& x D
Event, 事件
`! T1 j. D! v7 OEvent, 事件
: O6 @& R8 p) s% |Exceptional data point, 异常数据点 S/ n' w! p w8 V y6 b, l7 N7 \
Expectation plane, 期望平面
- I- B; V% q. P( U3 N& zExpectation surface, 期望曲面
/ l3 R e9 O: GExpected values, 期望值# G$ Q0 d7 _; ]8 }) C! V
Experiment, 实验
/ K" ^; F8 e* j' C3 Y+ L+ {Experimental sampling, 试验抽样" t6 k$ u$ m5 U( \+ y( c
Experimental unit, 试验单位
' U; _+ p$ i! w# w: |( N. {5 g4 s, @Explanatory variable, 说明变量
$ T- e9 b9 P& e' H7 W+ c, kExploratory data analysis, 探索性数据分析" p( ?8 R0 B7 Y! H: d4 B7 b# Z5 K
Explore Summarize, 探索-摘要# q; ?2 K8 h4 z* t# V
Exponential curve, 指数曲线! j# E2 c% ~0 V
Exponential growth, 指数式增长' h9 Q6 }' U0 B" d7 x
EXSMOOTH, 指数平滑方法 o- r$ ^. n" m: |
Extended fit, 扩充拟合5 V) m( [4 {. V' W
Extra parameter, 附加参数# r/ |$ |. V8 s+ Z6 _, y
Extrapolation, 外推法
, e5 M4 x/ W$ O0 }0 K& m' s. TExtreme observation, 末端观测值
Z) ]% I; C. w8 Q* UExtremes, 极端值/极值
7 \+ M4 Y. Y. E$ E! A: hF distribution, F分布* q; t0 N7 P8 ^
F test, F检验* d7 u4 s; n' R& \0 x
Factor, 因素/因子
$ `( p. r* a H0 m6 C" {1 M. K6 \) [Factor analysis, 因子分析
7 Z" J/ |/ H; RFactor Analysis, 因子分析
5 }+ c+ M9 t) |8 n V. q4 e, hFactor score, 因子得分 % f0 r+ g/ E, d( [, t
Factorial, 阶乘8 `' R& o2 M8 w0 ?
Factorial design, 析因试验设计3 G0 Z; v: m% f* O) B# _
False negative, 假阴性
# T: s/ ~7 d# ]. Q: C+ p; M* V# CFalse negative error, 假阴性错误$ k g( A2 \9 @' j+ p" u
Family of distributions, 分布族5 P2 G& [; q6 R" ?( k
Family of estimators, 估计量族
' s+ H2 @# d8 u: }' E IFanning, 扇面
4 R6 D6 U9 n+ Q6 WFatality rate, 病死率7 T' N1 f) \ L: X% g- y* ~
Field investigation, 现场调查
" j$ j9 z7 [* c8 }/ ~) Y* {Field survey, 现场调查
) W2 [2 n8 k$ L; W4 e2 f0 s( wFinite population, 有限总体' Z' s7 _: Z2 X: I4 l4 y1 h) Q
Finite-sample, 有限样本+ W. m1 s* q* v# Q2 ~ z8 l
First derivative, 一阶导数
4 s- _( a+ j7 E+ u! I+ D" BFirst principal component, 第一主成分# o& O9 o# T0 H/ W X, U
First quartile, 第一四分位数% h, o0 [* q% X0 q/ q+ X/ o* ^
Fisher information, 费雪信息量! |8 i9 Q, j( K, F# }
Fitted value, 拟合值
* U7 y! z' [- X9 p* k' aFitting a curve, 曲线拟合
: f& k) P3 k2 j/ L" KFixed base, 定基
: Q3 e8 c) o- W6 w$ ^& M! eFluctuation, 随机起伏+ K$ y$ [8 e( i6 C9 d6 ?: X
Forecast, 预测/ }1 ?3 _% d7 I) w+ t
Four fold table, 四格表
, Q9 ?$ l& C0 f' I+ NFourth, 四分点8 _. m: }2 W" H# C
Fraction blow, 左侧比率2 i! _0 W3 s- O/ R8 @7 v8 z
Fractional error, 相对误差
' ~* R: ~7 d' b5 y" D0 RFrequency, 频率% v1 h6 o6 [3 u8 W m9 W. r
Frequency polygon, 频数多边图! m% n8 |# t. ^3 l. Y. R# \
Frontier point, 界限点
m' r) k f2 X4 ^Function relationship, 泛函关系
5 R. D* X4 a& Y' ]2 [Gamma distribution, 伽玛分布
- G; t/ F* L: {Gauss increment, 高斯增量
, z* \5 } v2 y! J- r. ]1 GGaussian distribution, 高斯分布/正态分布" `; w/ V( n8 y( V7 |* F/ H/ I( d/ n/ j
Gauss-Newton increment, 高斯-牛顿增量; U2 T- Y, W- s3 A. `# R' a
General census, 全面普查8 s7 k: k1 l, v8 b" g9 ]( F! Y
GENLOG (Generalized liner models), 广义线性模型
# f9 |, L/ r1 R7 a% w2 N& \Geometric mean, 几何平均数/ e4 k0 m* ^$ F8 u9 K
Gini's mean difference, 基尼均差
8 C% s2 N, d5 l6 [( m- Y8 S7 p, WGLM (General liner models), 一般线性模型
+ A6 L2 M, R, X' N) tGoodness of fit, 拟和优度/配合度
) w8 f- B, N3 d5 u- k6 m8 ?" TGradient of determinant, 行列式的梯度
" n4 w3 t' i) D, OGraeco-Latin square, 希腊拉丁方! i" O7 J- _* q
Grand mean, 总均值
R4 r* M4 h" y+ {& H# ^/ \: tGross errors, 重大错误
. l; B* s4 }, G* q. {5 pGross-error sensitivity, 大错敏感度0 c4 G- U% s+ g! W5 Q: o' s+ R
Group averages, 分组平均: ?0 L! n- w6 b& f% s
Grouped data, 分组资料
) }8 y# l3 z- g+ uGuessed mean, 假定平均数. `& _, ^4 `; G4 m4 Y
Half-life, 半衰期
% Q W7 A! N5 MHampel M-estimators, 汉佩尔M估计量
3 D! i1 p3 e$ U0 M3 q: F4 CHappenstance, 偶然事件
: l X+ w3 } [/ _+ p7 ~Harmonic mean, 调和均数( V* M$ i( k7 w3 D' |/ [! t
Hazard function, 风险均数
# l1 C- o! ?/ w, kHazard rate, 风险率
3 ^- g' ^% C; Z+ ]" oHeading, 标目
6 T: q( h% h, IHeavy-tailed distribution, 重尾分布, q+ w5 R+ ~1 _/ R$ f* z
Hessian array, 海森立体阵
3 |+ D* V. E9 [7 j! y' V' O& S* {Heterogeneity, 不同质
* h' J) p8 t. p- z, F3 d3 Z' b! iHeterogeneity of variance, 方差不齐
; t& l* p6 |2 i$ c- m3 yHierarchical classification, 组内分组
# h: i/ w' b" `; z$ W, ~9 h) j, |3 h2 CHierarchical clustering method, 系统聚类法1 I8 X, W' I: [- y
High-leverage point, 高杠杆率点, C! I5 B! D/ Q! w' j/ w
HILOGLINEAR, 多维列联表的层次对数线性模型! s, o7 m! a8 z4 h( n
Hinge, 折叶点( Y; w. n: W( D* p. g! P8 {7 g
Histogram, 直方图
' N# c0 v+ T* @; {- ~. i" k! D- ^Historical cohort study, 历史性队列研究 1 E) L; ^; x# Y3 f( U2 x4 I
Holes, 空洞 N6 [# I- ^" |5 A
HOMALS, 多重响应分析
: I o ]) x; QHomogeneity of variance, 方差齐性; D) s+ k( Y9 \: d8 m$ ~5 C6 ?
Homogeneity test, 齐性检验# P: d! E" l& C9 p
Huber M-estimators, 休伯M估计量
6 z& ]) W: h1 E2 ?Hyperbola, 双曲线
2 L5 ~; B7 D. a8 m) m- {2 bHypothesis testing, 假设检验
( P* z A& [5 v7 _7 O8 vHypothetical universe, 假设总体
, i6 ^- x; e4 p- i5 L4 J: o A" JImpossible event, 不可能事件
* x" l1 A9 V$ T$ Z6 x' T. w) L* {Independence, 独立性
# V; l- ?# H$ w8 S3 tIndependent variable, 自变量* V6 s0 E p. H4 |8 x
Index, 指标/指数
# i: S" d4 Q- V- A1 p# Q$ [' n, n% QIndirect standardization, 间接标准化法 ^& J+ R0 Q9 E, V
Individual, 个体2 n6 ]. b, t# K e' V# M1 i
Inference band, 推断带
0 r+ }% E$ X! B4 L& lInfinite population, 无限总体
& H$ D$ m2 [4 W/ YInfinitely great, 无穷大5 H7 D& O& @9 [- U4 |0 H8 X) d
Infinitely small, 无穷小
v8 l! b) y3 c" U+ `+ j; UInfluence curve, 影响曲线. S' X- v3 }: r0 g. n6 S2 U: m# N
Information capacity, 信息容量; w+ J0 `6 b3 b/ Z5 L
Initial condition, 初始条件3 V4 A& Q k& w' a' C
Initial estimate, 初始估计值
& C3 \# N0 w* r% I* S7 l2 UInitial level, 最初水平
( E6 F: t! m& s& X. @Interaction, 交互作用
/ r7 C3 }4 W, T0 H" mInteraction terms, 交互作用项
. V, J+ h: J8 J$ OIntercept, 截距: n& {; O; D$ a) S) y1 `
Interpolation, 内插法
) p" S* O! \! W* R5 L0 ?Interquartile range, 四分位距1 x/ O1 y8 S$ {! L
Interval estimation, 区间估计
; q/ n; X& k0 B8 g4 S5 [( pIntervals of equal probability, 等概率区间
+ ~9 v, R" A* Y7 eIntrinsic curvature, 固有曲率# H4 b o6 h# ~' V
Invariance, 不变性4 |6 A+ B0 E6 p% ?6 }6 Q! o
Inverse matrix, 逆矩阵
0 }7 n1 j* t F/ J% H% w0 i; pInverse probability, 逆概率
! r* Q9 K0 ~5 u0 M( g. w! {Inverse sine transformation, 反正弦变换
9 D) o0 M+ Q3 k% BIteration, 迭代 * b# s; ?% B; `3 \+ `2 V. ~
Jacobian determinant, 雅可比行列式
0 R0 Z4 v5 v8 @% VJoint distribution function, 分布函数9 q6 J' M7 n2 U& U) g
Joint probability, 联合概率' b" i9 V L( _! m; O, g
Joint probability distribution, 联合概率分布
7 q" f. |; G5 a- S5 cK means method, 逐步聚类法
/ }& @3 c/ W& [$ L- L: _; ]( q/ gKaplan-Meier, 评估事件的时间长度
5 u/ q {! }9 v2 I8 J( jKaplan-Merier chart, Kaplan-Merier图
" \9 e+ d# T4 ^+ H' |* d7 uKendall's rank correlation, Kendall等级相关, i. L/ D8 j' k6 Y0 _$ {
Kinetic, 动力学
# ^+ k; m5 C# @7 B+ }; D% j5 C$ lKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
0 L- r7 ~) v, z8 @3 w! x( ]Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验, D7 t, y! A$ |) N! N
Kurtosis, 峰度
& z% \) b4 a; m3 }+ s, ]3 |0 ?Lack of fit, 失拟
6 o: k9 V# a2 N1 z9 z! eLadder of powers, 幂阶梯$ j/ k4 o _! Q: }( e
Lag, 滞后' j) n: j+ f* b v8 L7 M' k
Large sample, 大样本
- f7 z4 Z6 L3 F% s3 Q* FLarge sample test, 大样本检验- ?9 n5 v0 T* `% T: [" | S/ G* k
Latin square, 拉丁方. z9 c( [& z" L: r3 W) Q+ \
Latin square design, 拉丁方设计# F2 @8 T4 N1 v6 J1 e
Leakage, 泄漏& A( |6 L! @( }- |
Least favorable configuration, 最不利构形
2 Y) ]- a' y l. t% g' t% iLeast favorable distribution, 最不利分布4 t- f* \# }/ e8 l5 s% \; K
Least significant difference, 最小显著差法
" a2 B, t+ [$ g% |( U! ^6 f6 \3 OLeast square method, 最小二乘法' |# r: C$ w. T; u/ _8 b$ }3 V) F5 c
Least-absolute-residuals estimates, 最小绝对残差估计
9 e* g8 ?5 \' m8 i) j7 T" qLeast-absolute-residuals fit, 最小绝对残差拟合6 e- c8 k0 r" A* F5 G9 `
Least-absolute-residuals line, 最小绝对残差线
$ ?" k4 _$ ?) h8 P# qLegend, 图例
1 j" E* p# }0 L5 Z- K# L9 U Y6 OL-estimator, L估计量
2 S/ \# D$ g3 H" J1 l2 Z% L1 rL-estimator of location, 位置L估计量
6 {$ X9 b& z% P, ?L-estimator of scale, 尺度L估计量
$ s& j: R0 B; ?: d) ^Level, 水平9 p1 z4 s4 H5 n9 j, H
Life expectance, 预期期望寿命: o9 ^# `* Y" N, L) A& d
Life table, 寿命表
/ v$ \$ D$ ?# T3 z% }, CLife table method, 生命表法% I$ T2 [9 f. \$ F: a$ |
Light-tailed distribution, 轻尾分布$ D) I: U$ R9 g& s9 q% F4 V1 n
Likelihood function, 似然函数
2 N' O; x6 L' Z ]4 v; n3 QLikelihood ratio, 似然比
$ }+ J/ F& x. V9 I( G6 c7 uline graph, 线图
. g* `5 m8 I* S9 ZLinear correlation, 直线相关0 v, z, {3 t0 O$ t2 l
Linear equation, 线性方程7 B0 }: x1 M# Z2 Q* ^) y- L
Linear programming, 线性规划! K9 P$ S4 Z2 E5 r
Linear regression, 直线回归
8 a; k% W5 i8 ~: [0 m' Y9 Q- uLinear Regression, 线性回归; t) i% K/ m0 O) W
Linear trend, 线性趋势- Q8 m6 x! K4 }5 s
Loading, 载荷
" K- K I6 [; nLocation and scale equivariance, 位置尺度同变性 g; K% t+ j k$ _5 H: e, ]5 u
Location equivariance, 位置同变性7 ^4 y+ q5 n2 X6 b
Location invariance, 位置不变性
4 C. W; R0 f- z4 q* S3 |9 ^- F+ CLocation scale family, 位置尺度族. N0 l0 J2 q" w) k8 z4 q" C0 y. u
Log rank test, 时序检验 6 g0 N+ ?% y8 L
Logarithmic curve, 对数曲线7 L" J; w% ?* l4 Z4 [3 i# ?
Logarithmic normal distribution, 对数正态分布
2 X4 Z0 s$ m/ `2 qLogarithmic scale, 对数尺度; k1 v8 R; f) W) N( C
Logarithmic transformation, 对数变换
7 H# f; H1 G2 g |( y1 m( @Logic check, 逻辑检查" T1 `9 T/ J* Y/ i0 d
Logistic distribution, 逻辑斯特分布
3 [+ q$ H/ s) v& u3 c/ p1 F2 SLogit transformation, Logit转换
8 w7 h5 w) D+ o) y: [- {LOGLINEAR, 多维列联表通用模型 4 \7 k2 S9 E( V4 V0 p8 ^
Lognormal distribution, 对数正态分布
" e+ Z, q: l& ?0 D/ ^* b0 w. mLost function, 损失函数! z$ x5 N8 |, V3 }
Low correlation, 低度相关 ~- ]* g0 {. ]% d7 r
Lower limit, 下限9 I$ ~6 l0 N- t5 N; {; e4 m
Lowest-attained variance, 最小可达方差. i% A# z) T% D
LSD, 最小显著差法的简称
+ Y; A: A. b* J* r8 l' [1 b0 yLurking variable, 潜在变量
1 C3 o% a. }6 Y' c R% DMain effect, 主效应
% k B) j6 m! o9 J( UMajor heading, 主辞标目0 l* J* T1 n' D- @8 Y5 A
Marginal density function, 边缘密度函数3 ^3 w1 s9 `7 W& }
Marginal probability, 边缘概率) I8 ]( P/ p: A7 h5 \/ r- g
Marginal probability distribution, 边缘概率分布" {% E) C3 M* R$ l: U
Matched data, 配对资料
; u8 C7 F& q0 m) Z( k3 c6 jMatched distribution, 匹配过分布, d2 j) H3 w, d" @
Matching of distribution, 分布的匹配 B. d0 ^ \( w. ?
Matching of transformation, 变换的匹配; O3 j3 e O8 N' b7 n
Mathematical expectation, 数学期望
+ ^/ j- e* T+ C6 w* T* H" ~Mathematical model, 数学模型. m1 z& w: N+ p. g1 s
Maximum L-estimator, 极大极小L 估计量
+ b1 d' o# A9 b- j1 MMaximum likelihood method, 最大似然法4 V1 C; z& m( ?# s
Mean, 均数
) l; A# g9 k3 ]$ o6 M# M+ O' u6 c0 zMean squares between groups, 组间均方
; Y! X( B& O8 r% z- C8 [Mean squares within group, 组内均方: U. Q# f* ^$ Y" r$ y3 D7 L
Means (Compare means), 均值-均值比较
/ @! Y) b3 C) B- S8 HMedian, 中位数
* h* t* j; x+ o! t# m! P9 a& H0 f- uMedian effective dose, 半数效量 B& T; S! z( i8 @
Median lethal dose, 半数致死量( k+ d- r: z4 S: p! I1 |
Median polish, 中位数平滑! _9 O3 g& j2 H- v! {
Median test, 中位数检验7 i, C8 l% s- i0 t( i6 l1 E
Minimal sufficient statistic, 最小充分统计量0 I) |9 C8 j1 @: {
Minimum distance estimation, 最小距离估计
+ k2 W7 }5 h1 [5 M- UMinimum effective dose, 最小有效量
( ~) B/ o! w5 S0 l+ z9 pMinimum lethal dose, 最小致死量
, `+ T q9 \9 g2 c) vMinimum variance estimator, 最小方差估计量
% c& A# s2 s! [ qMINITAB, 统计软件包
, ]. R3 W* `, s9 U, NMinor heading, 宾词标目 _, S7 |6 J/ L* A3 @
Missing data, 缺失值
L* a0 L, s! M1 jModel specification, 模型的确定9 A8 F) ?/ M0 k
Modeling Statistics , 模型统计
6 r( S3 {" J) l, s( gModels for outliers, 离群值模型
2 Q' F( R, I" r, e! A/ b" BModifying the model, 模型的修正" Q" J% t6 w+ P! j
Modulus of continuity, 连续性模7 J1 P3 v, D; j" b1 j, I5 X
Morbidity, 发病率 7 i& |0 E# ]7 D# ?7 @ y! }1 P1 g
Most favorable configuration, 最有利构形
) I$ ]! P, ^. f7 CMultidimensional Scaling (ASCAL), 多维尺度/多维标度
; L& N3 P& e1 }* }" pMultinomial Logistic Regression , 多项逻辑斯蒂回归
j" c X8 U3 O* V8 }; o# \6 cMultiple comparison, 多重比较
, K4 Q, k- @" Y! L0 s9 O% k8 ~( a/ Q; yMultiple correlation , 复相关- v+ m" V8 N! @) V0 R
Multiple covariance, 多元协方差
8 S t' M/ _9 z: ]: w4 n5 TMultiple linear regression, 多元线性回归, } _. ]! j9 `- k- w" q
Multiple response , 多重选项4 _) k; P- _$ x4 `$ F
Multiple solutions, 多解5 r) D4 B, C9 A0 W" `
Multiplication theorem, 乘法定理. K$ I" R" {$ Y; {
Multiresponse, 多元响应9 a2 ?, R% k+ l- q S
Multi-stage sampling, 多阶段抽样
! X) a2 M# w& W! Q" x+ QMultivariate T distribution, 多元T分布
Q/ h6 P# |4 X" N# iMutual exclusive, 互不相容
j1 z5 W5 o/ k6 S j5 [' Y+ MMutual independence, 互相独立
. f' n; R F# ^& q/ ?8 WNatural boundary, 自然边界, Q8 J8 A& o1 }
Natural dead, 自然死亡 @8 g: j: X: P) {# i& i2 V
Natural zero, 自然零/ f) V) H5 }, G! `$ b
Negative correlation, 负相关' i% z* w% T% ^6 S
Negative linear correlation, 负线性相关
! S4 r* t0 F+ O' jNegatively skewed, 负偏
, O$ `9 W0 I3 l. CNewman-Keuls method, q检验
! l& a7 H' t) h, {NK method, q检验
p( O. e( N% b# T! m9 k0 ~No statistical significance, 无统计意义
7 U. N2 ~- b8 e9 O: Z) aNominal variable, 名义变量+ D( N- G% `& w& y
Nonconstancy of variability, 变异的非定常性' W8 {0 A. S/ {5 Y/ n' h8 b% R1 [
Nonlinear regression, 非线性相关
1 P' M2 z1 l& qNonparametric statistics, 非参数统计
, f" Q( x5 E( K" L6 M6 m+ L9 e8 e7 ENonparametric test, 非参数检验
7 g. ?, F+ ?: r; X: s$ z yNonparametric tests, 非参数检验
% n* G, v$ h% U( p1 T7 T8 SNormal deviate, 正态离差; t6 ?) F# L5 Y: X
Normal distribution, 正态分布
/ L n6 t6 i* [Normal equation, 正规方程组% E! D6 t" j6 {0 e
Normal ranges, 正常范围
* A$ r5 g$ _" PNormal value, 正常值$ q+ t: V6 C2 z4 @. W% @
Nuisance parameter, 多余参数/讨厌参数+ O# {5 M. a7 X! W& V w
Null hypothesis, 无效假设
- U, L0 K* D3 C- p' |# u7 F) s9 VNumerical variable, 数值变量
% r3 w: J' n" K1 H3 {Objective function, 目标函数; v* M0 B2 ^' n' ^9 F" G& T. [. K
Observation unit, 观察单位; S+ Y- n- W6 t( y% t
Observed value, 观察值
$ ^' Q% j5 l. V# J1 uOne sided test, 单侧检验$ r3 g2 Y+ Q5 x* Q g1 q. ^& u) E
One-way analysis of variance, 单因素方差分析
R9 a0 p( l. Z% A) aOneway ANOVA , 单因素方差分析- {% N; r( }, u) r5 f
Open sequential trial, 开放型序贯设计 t" I" ?8 i& }" j8 F$ s8 ^2 K4 B' a
Optrim, 优切尾
9 k( s& r7 _$ A# R7 {8 d8 uOptrim efficiency, 优切尾效率
* {3 y* U& R" c6 m, ~2 O0 qOrder statistics, 顺序统计量
5 _7 |1 g5 |5 I+ l3 ?7 bOrdered categories, 有序分类. n- h m6 g' s( [( e* S- B
Ordinal logistic regression , 序数逻辑斯蒂回归& S# @0 n: o: Z8 h% _2 `& _
Ordinal variable, 有序变量
; F8 Y! x: o, ]" r4 {+ l ~$ WOrthogonal basis, 正交基; p: p6 r- M5 y9 H2 ~9 O g6 K
Orthogonal design, 正交试验设计
4 S" R0 d( y9 }+ s! POrthogonality conditions, 正交条件! |% u, B( P" w5 R+ ` @, I
ORTHOPLAN, 正交设计 ; {* q" R: t% T7 S& v
Outlier cutoffs, 离群值截断点" P1 a. v6 q. J) ]" l
Outliers, 极端值/ t/ Q+ m# w! [% ]4 u" M2 f
OVERALS , 多组变量的非线性正规相关 : i" R4 A7 s$ u# j. k
Overshoot, 迭代过度* N- ~; Z+ Q' R# Z/ B! u
Paired design, 配对设计
! @% Q4 _0 b) _# g( `Paired sample, 配对样本
, ]2 `$ {4 m$ z7 W9 z; V. @$ I) rPairwise slopes, 成对斜率
~% l; c- u3 ?% ~& ~ HParabola, 抛物线/ {( Q6 H6 j- a
Parallel tests, 平行试验/ \) z% B- u7 ~) r$ E+ x
Parameter, 参数
3 u, X% }8 Q7 m/ y& q" b$ ^Parametric statistics, 参数统计: U4 m( S6 j; n* P8 T- V
Parametric test, 参数检验$ p' N- [* Z5 ]& }* C+ S
Partial correlation, 偏相关
x4 z( _, {9 N2 i7 n) w8 m* A3 [; _Partial regression, 偏回归
' D4 M2 X4 E3 T: u' YPartial sorting, 偏排序2 T: n* y; A3 Y) m4 U( P$ ^% A
Partials residuals, 偏残差6 Z! b" u. Q' P; S* W# q% E) m. D
Pattern, 模式/ o/ T' i. O6 V( E
Pearson curves, 皮尔逊曲线9 z6 J" k" Q& d, Y9 N6 b7 q
Peeling, 退层
4 [ F" f& M5 A5 wPercent bar graph, 百分条形图8 P1 ~7 {% K+ Q9 ~5 {
Percentage, 百分比
, k) {3 D3 M, A/ z7 P3 _Percentile, 百分位数* X6 e4 u3 E. l
Percentile curves, 百分位曲线
3 Y' }. j3 D* uPeriodicity, 周期性
4 J' b: g/ S _ `! {& L1 PPermutation, 排列
$ D8 z! T- u# |0 o- [4 q( nP-estimator, P估计量
: q' v t) B0 T# L* d8 Y' NPie graph, 饼图: c3 N2 I" z3 K( _6 o' l0 Z
Pitman estimator, 皮特曼估计量' v( ?( r+ E7 D6 @2 @
Pivot, 枢轴量
2 P/ ]! t! E: _ F' jPlanar, 平坦
( t' j. A: i7 b" Y* mPlanar assumption, 平面的假设- H5 @4 r! @) _7 k) p4 H
PLANCARDS, 生成试验的计划卡
. n' `: h% E4 } gPoint estimation, 点估计% ]& w6 _- X0 }" Q, s
Poisson distribution, 泊松分布
8 S# C) i) R$ `! W6 y4 cPolishing, 平滑
j% `( A; N$ M# rPolled standard deviation, 合并标准差" x' D) ^. o4 U
Polled variance, 合并方差
b1 c& i4 q3 _; H! e5 |Polygon, 多边图 Q) w! P3 k: w( C }9 P1 U
Polynomial, 多项式0 m9 L# x. J5 H# j
Polynomial curve, 多项式曲线
( p, y$ a1 T1 R: Y/ t9 ZPopulation, 总体
/ O1 d3 O: m" K% ]Population attributable risk, 人群归因危险度; }+ M) }- w8 r) y; ~
Positive correlation, 正相关+ T, K0 C7 ?( c7 w0 L' N& a& C! ~
Positively skewed, 正偏
. a- Y5 c$ o) LPosterior distribution, 后验分布" ^& Z0 y0 X! U9 d
Power of a test, 检验效能, l+ X% V3 {2 O5 X! s
Precision, 精密度2 W m+ N0 N6 w* g
Predicted value, 预测值
+ _: A, I& z/ D7 d% ~" nPreliminary analysis, 预备性分析# U2 x/ H) c8 X* E* @
Principal component analysis, 主成分分析- T% H, f( `" |0 ^
Prior distribution, 先验分布
2 C# m6 [, ?; pPrior probability, 先验概率
7 Q5 }# e: B9 X/ N# ]Probabilistic model, 概率模型
) y2 ?5 G6 c. p6 {8 Wprobability, 概率% D5 l6 J6 y& g) B' _
Probability density, 概率密度
- F% x* ?2 M, }) WProduct moment, 乘积矩/协方差
9 H8 Q# p/ a3 Y5 i( M# ]9 b WProfile trace, 截面迹图
8 z; P9 {" i" ^0 F5 uProportion, 比/构成比, u d3 i& Y9 n% s: \1 J! I9 A9 C; \
Proportion allocation in stratified random sampling, 按比例分层随机抽样; y! g6 `. W; [4 f
Proportionate, 成比例
* v6 ~$ n/ a: {* `Proportionate sub-class numbers, 成比例次级组含量
4 v: l, f. |: [. E( WProspective study, 前瞻性调查! Y0 B" `% p/ g# x
Proximities, 亲近性
; b7 N7 d+ y: c, `' v' dPseudo F test, 近似F检验
% b0 N$ M6 j6 {6 LPseudo model, 近似模型
' A& j2 V2 ]0 l( h1 U' K }/ pPseudosigma, 伪标准差9 _+ u) |0 |) u
Purposive sampling, 有目的抽样( ~ Q. q9 D9 R9 k, O W
QR decomposition, QR分解$ ]* p& S& s- N0 D) `7 ^: Z0 g) D
Quadratic approximation, 二次近似, G! r% h- \* x, k! Z, F( M
Qualitative classification, 属性分类8 _2 A# @/ Y1 N2 B X U
Qualitative method, 定性方法
* e/ r4 V1 W* G" ~0 {) b" ]Quantile-quantile plot, 分位数-分位数图/Q-Q图
% d: [& b1 C4 f6 z yQuantitative analysis, 定量分析
' e8 y' a- `5 N3 f5 _+ WQuartile, 四分位数
- }7 r5 n) K1 W& dQuick Cluster, 快速聚类
- d# Y' f1 g5 |) _5 ~( BRadix sort, 基数排序" P5 s _. t7 E/ h/ [
Random allocation, 随机化分组$ i' T& x/ t$ i: t# d7 Y
Random blocks design, 随机区组设计: R/ v5 L& d5 N8 o1 R: u1 _2 p
Random event, 随机事件* V1 Y. a% ^1 e
Randomization, 随机化; a- r& d- K% K/ G$ s$ w
Range, 极差/全距
- w: @" x! x& q1 n Z/ c2 CRank correlation, 等级相关( I- G. O, a7 H$ \1 b" {. m, N
Rank sum test, 秩和检验! G6 |- f/ ]! m. s0 b; L
Rank test, 秩检验
9 k$ f) g% l( M; YRanked data, 等级资料- R5 `( @& K; Z/ g q
Rate, 比率) a% A; l9 E( U+ m' J% [) ?. {
Ratio, 比例8 A4 @% I) o0 b0 G0 y
Raw data, 原始资料
- x: h5 K: S! N+ V- l& LRaw residual, 原始残差
7 t5 w7 t- M# b }! R! R0 }Rayleigh's test, 雷氏检验
1 D1 m( h6 n1 HRayleigh's Z, 雷氏Z值
4 u) y/ A# S) h: C: K2 i* \; IReciprocal, 倒数
( c- }! t1 F8 o- M$ g4 m, o: XReciprocal transformation, 倒数变换) ?1 X" w- m3 }7 O" v
Recording, 记录
4 k* M M' A6 Y7 l; URedescending estimators, 回降估计量& V/ |; c1 j/ t* L- D1 r/ d0 P
Reducing dimensions, 降维1 }4 X$ n" {' V8 W
Re-expression, 重新表达" h% ^+ d8 y0 I) [0 K x4 Q
Reference set, 标准组$ g+ k y9 I7 ?% `
Region of acceptance, 接受域
2 ]: L* l. T, K" YRegression coefficient, 回归系数# L6 }8 T% w+ \: P5 y
Regression sum of square, 回归平方和
0 J' H5 z" a4 Z0 q/ C2 ZRejection point, 拒绝点
- \, v, i$ E6 i. R2 T. ^* wRelative dispersion, 相对离散度
$ y8 B6 w% Y1 T$ @, oRelative number, 相对数, y! ~0 u2 ?9 P. R' }3 `) u( m
Reliability, 可靠性
5 ?+ j' P ?6 e$ x" Q% KReparametrization, 重新设置参数& i' X, W2 Q* x7 r
Replication, 重复) ~ O# \( ]! [6 p. G" P1 Q0 ^
Report Summaries, 报告摘要& u9 a8 _( ^, |9 E( k2 }1 B( d
Residual sum of square, 剩余平方和
6 D( f% y+ l6 t4 R' @Resistance, 耐抗性
/ U: z5 K0 m# X6 r9 ^! ~: d# ~Resistant line, 耐抗线
" w$ n$ A( Q( PResistant technique, 耐抗技术
1 F6 J L2 ] c( q% HR-estimator of location, 位置R估计量% T5 f' o* W) f5 `$ [2 _
R-estimator of scale, 尺度R估计量1 m- o% H1 ]" |4 Y7 G
Retrospective study, 回顾性调查
. s, ?; r9 Z+ l5 qRidge trace, 岭迹
. B! s T: `4 e0 ARidit analysis, Ridit分析; F5 W8 R. n$ n
Rotation, 旋转% X5 j9 n: N9 g+ A! r
Rounding, 舍入
; Z9 }# C4 a4 L, @% |( BRow, 行- ]5 J+ H B# V% U( w n! v/ j
Row effects, 行效应- I4 a$ J. g& T' B
Row factor, 行因素
) c/ _" V7 u( |$ i% X* wRXC table, RXC表
; ~! N3 g0 w$ p' [8 d7 k7 LSample, 样本
% C; P& }/ T, t. p0 VSample regression coefficient, 样本回归系数
) L6 e' n3 m# j2 Q+ ~" q3 _& QSample size, 样本量
, V. T d8 c9 @+ @9 G/ U: WSample standard deviation, 样本标准差6 t, V( k; c/ `( d( W* ~
Sampling error, 抽样误差
1 X F, q) O7 g$ N; c; |/ x f" DSAS(Statistical analysis system ), SAS统计软件包. F6 A( A7 ]& L8 n4 ]- I
Scale, 尺度/量表
* e3 n. [" G b( b8 s; g- G& YScatter diagram, 散点图( P* E+ a4 g" \- |9 d
Schematic plot, 示意图/简图- n1 S" n) |' N. ~% u. M
Score test, 计分检验1 K! [) h" R) o8 H. n U/ @
Screening, 筛检( E& T5 G# o0 t/ H+ C( M
SEASON, 季节分析 4 u" j( D1 K4 [. _7 `
Second derivative, 二阶导数, l" E. v& }+ z7 ^ a1 w
Second principal component, 第二主成分) X9 ~1 a( `# S1 c$ Q
SEM (Structural equation modeling), 结构化方程模型
+ g9 E. E. P) ESemi-logarithmic graph, 半对数图& W) g' ^" Z2 H# c3 y
Semi-logarithmic paper, 半对数格纸
; G) P# z: b) p% [3 ~( s9 PSensitivity curve, 敏感度曲线- o# [- F& |1 o" Y/ a1 V
Sequential analysis, 贯序分析4 v) B0 g3 S b3 K1 y+ Y8 g
Sequential data set, 顺序数据集1 T+ l( M* X0 X6 x6 j& K! L8 ]
Sequential design, 贯序设计! ~0 a( n. u8 ]) u# ^5 m
Sequential method, 贯序法
b, D7 ~+ ]/ `5 CSequential test, 贯序检验法
w/ ^* `: R+ B5 U' ~! nSerial tests, 系列试验1 N* b7 h, m. v. {( \7 ?( g
Short-cut method, 简捷法
( e% S; U# n8 Z8 L- TSigmoid curve, S形曲线
0 J7 S, e' T* \& q% \( v0 SSign function, 正负号函数- A. v% J! @' _' c
Sign test, 符号检验
! g4 D. Q: x$ {) [Signed rank, 符号秩4 X0 z) r8 O0 `8 B( }5 A- E
Significance test, 显著性检验
- U$ [4 j1 M$ ?0 ?4 fSignificant figure, 有效数字" V5 i( B7 o& V1 g
Simple cluster sampling, 简单整群抽样
. T( `6 K$ N& N7 H# u: Q/ }! nSimple correlation, 简单相关
2 ~# q; ]- [ b7 `; I/ oSimple random sampling, 简单随机抽样! \( I. x' h9 n. n+ t
Simple regression, 简单回归0 r3 W/ i+ B( E: ]: b8 [/ G
simple table, 简单表
2 O* Y# v9 b, ^' q! L* mSine estimator, 正弦估计量: G5 Y5 @6 f3 |
Single-valued estimate, 单值估计; ]7 l" J) g# |% C# y! Y
Singular matrix, 奇异矩阵5 b/ f8 G _# l6 _/ |3 Q G9 c
Skewed distribution, 偏斜分布" C6 x- O ^6 X K
Skewness, 偏度. d4 o( C7 K* T7 a+ D" R
Slash distribution, 斜线分布
- @4 w' Q! _' ~5 ]( o zSlope, 斜率/ r0 h6 O) U& E& ^" d) ^; r t
Smirnov test, 斯米尔诺夫检验
- O+ D. z1 t/ U9 E) g" ESource of variation, 变异来源# L3 F6 _7 ]1 x: b! W6 y1 S( a
Spearman rank correlation, 斯皮尔曼等级相关
: B- Z. L# X) W5 V' nSpecific factor, 特殊因子
: ?1 f) n$ w- i/ B# J; U i; ASpecific factor variance, 特殊因子方差
/ p0 A9 g" N. s. ~7 [3 R8 ]. t# ^- C/ QSpectra , 频谱
7 }/ P2 I5 B+ e) \Spherical distribution, 球型正态分布
; h1 x5 f9 }% G1 mSpread, 展布1 u# k8 q, [( ?, `
SPSS(Statistical package for the social science), SPSS统计软件包
' V' f; h2 y- bSpurious correlation, 假性相关
- y" y& e4 a6 j% r3 jSquare root transformation, 平方根变换; ^# T% c) u- A# |! x
Stabilizing variance, 稳定方差2 [/ Y; E) L" Y" z1 G1 B
Standard deviation, 标准差1 y0 d$ C3 P9 v9 N
Standard error, 标准误
8 o% ^1 t# @% N WStandard error of difference, 差别的标准误
" G& W( P6 l; K8 A9 OStandard error of estimate, 标准估计误差( z% J: g' ?$ p
Standard error of rate, 率的标准误4 A( s! i$ d! t2 P) N
Standard normal distribution, 标准正态分布
' V2 H; t* c6 C4 B3 v" M0 OStandardization, 标准化
7 X2 w n; R- N8 ?% iStarting value, 起始值+ s3 k9 t' _: W
Statistic, 统计量% N8 r4 `; k9 P" ]- r6 o
Statistical control, 统计控制
2 u8 H0 N a0 a8 Q9 ZStatistical graph, 统计图! z/ @7 ?6 o( i1 A6 C6 p+ G2 o
Statistical inference, 统计推断
$ s9 X) Y% M: o5 m/ L' }* u eStatistical table, 统计表' [4 E7 s1 T+ V: y
Steepest descent, 最速下降法( h- d) ]( k5 x4 k/ G. R) F5 L8 y
Stem and leaf display, 茎叶图
/ `! }$ W1 @2 i6 z- C7 AStep factor, 步长因子
! k& g3 I" m" U& MStepwise regression, 逐步回归
7 R8 s1 Y1 F+ H. O' R( |% MStorage, 存
1 |0 c( |3 z h) J; G0 xStrata, 层（复数）
7 B0 ^! I) g& m/ R8 sStratified sampling, 分层抽样
3 a: h% m7 Q3 A# R) r5 F' }Stratified sampling, 分层抽样8 Y/ M! Q ?8 ?; y. F
Strength, 强度% p4 I/ g* }! r9 N3 e) O
Stringency, 严密性; o' ^1 h7 k R! i- a: n$ A2 c8 H
Structural relationship, 结构关系
9 ]( g; c4 d. f gStudentized residual, 学生化残差/t化残差; T0 _$ T" V( o' w9 C3 S
Sub-class numbers, 次级组含量
: F7 k0 e5 _( NSubdividing, 分割
1 I+ q/ u1 E: kSufficient statistic, 充分统计量" a/ g3 T3 n4 {, m: S
Sum of products, 积和4 S- a; C8 L; M- |
Sum of squares, 离差平方和
2 C: W% ~: T, S9 X, L" dSum of squares about regression, 回归平方和
3 g. f/ H. b& y& qSum of squares between groups, 组间平方和
9 K/ i; q/ b! ~0 j9 o. a( I/ S. ?8 aSum of squares of partial regression, 偏回归平方和
8 @$ e8 a9 Z: I3 _1 g; H; XSure event, 必然事件$ L1 A( u$ S, t H- t; L" _
Survey, 调查
$ y9 I( x, o% y5 d' |2 U# BSurvival, 生存分析$ Q9 b6 D8 k1 f% {9 z2 j
Survival rate, 生存率" {4 K7 |( k! W+ Z
Suspended root gram, 悬吊根图
, o& \, A3 Z" VSymmetry, 对称- h1 \1 x* c1 V9 P7 S
Systematic error, 系统误差
$ X6 @. m4 [ P9 t6 SSystematic sampling, 系统抽样7 i% r" f" ]9 p$ E/ @
Tags, 标签; ^# T( O) i* y( K3 V
Tail area, 尾部面积
, _+ V; s3 i* x' P/ sTail length, 尾长
0 O4 W8 K* I/ K! A2 VTail weight, 尾重1 A8 Y4 I# H+ \5 c7 P$ V) W2 g
Tangent line, 切线# W: J. Y2 d2 N" I
Target distribution, 目标分布
& ~1 A6 r8 a$ I0 y, d$ Z% ~Taylor series, 泰勒级数
" P) [, V1 k9 q7 q% u' CTendency of dispersion, 离散趋势7 j8 I# v) z; X$ d6 A t h; c0 e8 ~
Testing of hypotheses, 假设检验! k: i1 m! k( }
Theoretical frequency, 理论频数
6 w( H& O& v! QTime series, 时间序列, ^5 A- @( I9 W' C
Tolerance interval, 容忍区间; Z4 ?1 B+ ]( }8 f I- ?
Tolerance lower limit, 容忍下限
# `% ^0 i/ E+ H8 S# ^# cTolerance upper limit, 容忍上限
" O9 N5 b! z/ l2 f& K. _Torsion, 扰率, A* j) c1 x/ K
Total sum of square, 总平方和
$ @+ j- D; Y/ B2 i; a7 h) {: F! @$ PTotal variation, 总变异
6 @! t* _8 h; U9 k: Z/ @Transformation, 转换7 l) Y1 h5 w8 M' v: e2 y. T
Treatment, 处理! c# q6 D+ R6 [" S" P- i1 e* ?
Trend, 趋势
9 F, U5 _2 B' [( aTrend of percentage, 百分比趋势
$ V" X7 C1 y) y4 G$ CTrial, 试验/ {0 B8 h U! u2 t/ y
Trial and error method, 试错法
4 p! f. V8 V" M" p8 u7 b( HTuning constant, 细调常数
$ J8 e2 o7 V: o0 C9 KTwo sided test, 双向检验% L& |5 t6 j, p: D0 u
Two-stage least squares, 二阶最小平方
9 s& @' V. \! t2 z1 fTwo-stage sampling, 二阶段抽样
/ _8 T6 V, r$ v4 D; aTwo-tailed test, 双侧检验% L3 B/ u! H5 P( g! b4 H
Two-way analysis of variance, 双因素方差分析- ]5 ]' N5 s/ C0 P
Two-way table, 双向表4 K/ h. S3 w. N# a$ ~
Type I error, 一类错误/α错误8 ~' m4 j+ C/ M7 N3 F2 L( [1 [
Type II error, 二类错误/β错误1 Y% d9 ]8 `9 a+ R% l, `
UMVU, 方差一致最小无偏估计简称1 P& A" S' y. q- x
Unbiased estimate, 无偏估计
8 [) D) [. E) Y3 ^1 s- j- ^' K0 Q: DUnconstrained nonlinear regression , 无约束非线性回归- M/ e4 k5 |; d7 S8 I: M8 k/ O% s
Unequal subclass number, 不等次级组含量/ L- T. h& s& C ]- P, m
Ungrouped data, 不分组资料
$ h& `6 z* B# e7 t3 a' x- QUniform coordinate, 均匀坐标; T. I3 ~/ p# }2 W* B2 R
Uniform distribution, 均匀分布
) D0 s. }& v. }Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
" y' N" o8 E P6 V! e5 A7 IUnit, 单元
; X, z! n! q5 P# G6 Z" YUnordered categories, 无序分类
! r0 V$ ^' ^8 ?, W( w/ }" c9 W) jUpper limit, 上限# w$ g. R1 H/ s% @( D s
Upward rank, 升秩
" P- C2 A: y$ A; O3 m4 L/ o( B. g, AVague concept, 模糊概念& k$ ]1 C" D8 N2 _+ N3 D
Validity, 有效性
. T% U, p3 J! ^ O% H4 ~$ }VARCOMP (Variance component estimation), 方差元素估计
1 _+ o) h: K4 u. |! v2 S& `Variability, 变异性
+ p1 t. S7 e$ D( N: |& iVariable, 变量4 U8 k: p/ R3 F- G
Variance, 方差, A ?& B0 X% ~: N
Variation, 变异
: G3 b7 i4 F E6 v- PVarimax orthogonal rotation, 方差最大正交旋转
1 l ^# A+ n6 K4 m- P+ W: N( C9 uVolume of distribution, 容积1 L( c+ { x& D& |% x U0 l; p% y
W test, W检验/ G" v7 F! ]+ w5 b, ?( Q
Weibull distribution, 威布尔分布# Z) H1 @* j4 _! ?
Weight, 权数" S' @4 a" {3 l/ j6 ~2 Y3 }
Weighted Chi-square test, 加权卡方检验/Cochran检验, k' ~+ P" M) R2 g$ R+ m1 Y
Weighted linear regression method, 加权直线回归9 d7 x# `7 G5 l! J% _) P
Weighted mean, 加权平均数/ X }) S+ x" j/ z" N. b0 v
Weighted mean square, 加权平均方差
" j i, _7 [+ U; ]' A# j7 _ wWeighted sum of square, 加权平方和: O; i4 w9 `+ h# `- i- J
Weighting coefficient, 权重系数$ d5 l) K5 w7 z. f j
Weighting method, 加权法 8 U3 q4 x( u, j) i
W-estimation, W估计量
" R/ C, Z3 x1 T0 K/ HW-estimation of location, 位置W估计量3 Z8 G6 w. `: x. W+ u; }
Width, 宽度
7 [/ \8 A1 o6 z9 o" J NWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
0 ]* x1 U# V$ f7 VWild point, 野点/狂点
$ K/ F( F9 _4 t. v- XWild value, 野值/狂值
+ f& l& e5 K3 t9 cWinsorized mean, 缩尾均值. @! j4 f) j% O, ^2 |7 R
Withdraw, 失访 ( p7 z, h0 x0 n
Youden's index, 尤登指数
( o( T; Y+ w: ^& [/ s7 aZ test, Z检验
& ^, l/ ^4 Y2 |1 U$ G' O oZero correlation, 零相关
- z1 m; N9 _) c# @* W/ E. FZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
