|
|
Absolute deviation, 绝对离差
- h( U# E7 v2 y1 QAbsolute number, 绝对数
6 Q8 r4 A2 Z9 O* y/ @' wAbsolute residuals, 绝对残差
, Z0 t+ |7 ]/ X4 r! E3 N: b* W7 pAcceleration array, 加速度立体阵+ O; X/ c; X# j& Y- C- f6 q0 j
Acceleration in an arbitrary direction, 任意方向上的加速度
6 \- C) O% U4 w6 u% ~7 L% y5 L1 `Acceleration normal, 法向加速度) c, S! a9 G7 w$ z. F8 b. ]' Z, Z
Acceleration space dimension, 加速度空间的维数
8 p" a4 W/ m9 f1 q3 tAcceleration tangential, 切向加速度: t* n( l# [3 K. |& T6 x
Acceleration vector, 加速度向量6 \: h; t# e. \( w" c* @! B
Acceptable hypothesis, 可接受假设
9 ^$ u* F% K' d1 \: W) a$ SAccumulation, 累积
% [" l) r6 c% x# t* ~3 x& i/ u1 rAccuracy, 准确度: {$ f) l' _7 {! c) d
Actual frequency, 实际频数! b* j4 ~; _! I& E7 w2 M+ I m
Adaptive estimator, 自适应估计量
% [% O* s/ U s5 KAddition, 相加9 a9 j* J1 S7 O3 R# I0 [
Addition theorem, 加法定理
- u3 U5 \! j4 M( p6 J9 k& c" {( [Additivity, 可加性
9 ~ O$ T! A: Z# j! PAdjusted rate, 调整率
. e7 M ~$ ] ^& vAdjusted value, 校正值
& H3 X# C' D" `1 Y/ }9 F' t9 dAdmissible error, 容许误差
) f" o) O2 H; v4 `! ?Aggregation, 聚集性8 n. ?. r5 O a4 Y
Alternative hypothesis, 备择假设7 ^9 y* s# c7 b R2 `$ W) w
Among groups, 组间
, {. W& i- G" o5 qAmounts, 总量, s# e; P0 l* n
Analysis of correlation, 相关分析
2 A$ w0 F5 t) U4 p, W1 U" wAnalysis of covariance, 协方差分析
) B( m' c5 N. @/ oAnalysis of regression, 回归分析
, j/ q2 z0 T! ~7 uAnalysis of time series, 时间序列分析
# q9 m, ^9 x( v) S {$ _' @! ^Analysis of variance, 方差分析
( f+ H7 A6 ]1 ^4 T$ sAngular transformation, 角转换( n" E+ y, p+ I
ANOVA （analysis of variance）, 方差分析" ? Z' Z0 i9 z* e0 R" E
ANOVA Models, 方差分析模型) u0 g' i: [: A) j' g$ q8 l
Arcing, 弧/弧旋! i6 [# G& d4 j! R
Arcsine transformation, 反正弦变换
7 w# v0 ^- N) Z7 o& Z7 W1 {Area under the curve, 曲线面积
1 ^, ?3 \* D: K, k6 TAREG , 评估从一个时间点到下一个时间点回归相关时的误差 4 G4 Z7 e. }# f! X& ?8 _
ARIMA, 季节和非季节性单变量模型的极大似然估计
8 i6 J" c8 K( l) ^ Q+ kArithmetic grid paper, 算术格纸
8 g+ e& A& D' e# L3 e: } h DArithmetic mean, 算术平均数; e2 Q( g2 u7 e2 I0 `
Arrhenius relation, 艾恩尼斯关系7 x* z4 R2 d/ D
Assessing fit, 拟合的评估6 R% R% ~+ }4 K
Associative laws, 结合律
/ p8 O+ L8 a0 N. d- ~5 t3 v* }" u2 lAsymmetric distribution, 非对称分布( i T* v+ C: Q* @ v* q( g
Asymptotic bias, 渐近偏倚* N2 r7 w8 E) n! p0 @3 Q+ F4 E
Asymptotic efficiency, 渐近效率' d% s7 Q& m# g$ Q& y [% ^0 ^
Asymptotic variance, 渐近方差
+ H* C; a' j& s& s. ~7 T9 m, gAttributable risk, 归因危险度& s5 P1 S. L) |, A
Attribute data, 属性资料
2 Z3 Z4 Q! g7 Q" k: O; V& z; ?Attribution, 属性 k+ r9 m# H9 r# k% g6 k
Autocorrelation, 自相关
; l/ L1 ~9 W% `" d7 v+ @Autocorrelation of residuals, 残差的自相关. R7 X) |9 Y! U# k
Average, 平均数7 q/ i. E* ]8 R: d# ]
Average confidence interval length, 平均置信区间长度( U$ f0 b7 K9 Y0 q @
Average growth rate, 平均增长率; }% X2 q" I3 f; V2 S9 [3 s) W
Bar chart, 条形图# g, b O+ f. y3 l3 B. `# d) p
Bar graph, 条形图
& r- j) ^$ Q) E7 T" ^. k# vBase period, 基期8 c/ T4 l( _' R' I: P
Bayes' theorem , Bayes定理
' {7 |% N$ R8 M4 n' h. T! N" YBell-shaped curve, 钟形曲线
2 V* B8 s+ E% W, A- PBernoulli distribution, 伯努力分布7 W4 D0 ?: ]5 c. E* a; M5 s+ H
Best-trim estimator, 最好切尾估计量9 p! o* \7 ]8 K# X8 G
Bias, 偏性
. V' l3 H( l$ sBinary logistic regression, 二元逻辑斯蒂回归2 t6 u" @( A* o1 y. O$ e
Binomial distribution, 二项分布
/ t- M J0 ?' m& V6 YBisquare, 双平方% X" Y1 k1 G0 b
Bivariate Correlate, 二变量相关
" I0 m% ]6 `7 x2 A! gBivariate normal distribution, 双变量正态分布
( k. K/ W' i; A: M( u1 H0 kBivariate normal population, 双变量正态总体
( }$ l0 G% y( W9 S+ YBiweight interval, 双权区间
; F) m& L' _+ L$ e& s1 p7 _Biweight M-estimator, 双权M估计量
1 C. d* Q/ H" f; F5 h- eBlock, 区组/配伍组
g% i' i6 B' p5 S3 L2 `! wBMDP(Biomedical computer programs), BMDP统计软件包
& U+ [( p/ D& ]5 B) LBoxplots, 箱线图/箱尾图1 I# ?5 { v8 T6 m. @! A
Breakdown bound, 崩溃界/崩溃点" H) ~( n+ K) J0 h( P
Canonical correlation, 典型相关
5 p$ r4 n2 ~9 ]/ h' d% JCaption, 纵标目! f9 o6 }, s! Q8 G1 ^3 R( ? s
Case-control study, 病例对照研究
8 h) U6 S0 ]" U# xCategorical variable, 分类变量, r0 O: D# D9 o9 d: J% }8 ~
Catenary, 悬链线
% A1 o% U: k, h* N& m" \$ iCauchy distribution, 柯西分布
& A+ e0 c; I; b) B& D1 K3 P& Z8 dCause-and-effect relationship, 因果关系
" {9 k c: V( j( UCell, 单元; Q" E$ T5 D6 d; q3 \
Censoring, 终检! A. V0 E4 ~( K
Center of symmetry, 对称中心
/ _3 F/ `( n+ q$ \; d% L" UCentering and scaling, 中心化和定标3 O0 Y5 x/ b8 {5 `+ O
Central tendency, 集中趋势* {+ ]* W, f- `" w/ G
Central value, 中心值
) [+ N/ D: J l9 P, E$ A% P6 yCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测 |- g: F$ ~+ L
Chance, 机遇
4 z/ \2 Q% h2 o) KChance error, 随机误差; Y; e, v* Z8 L7 s: A# W
Chance variable, 随机变量
7 b8 m; F2 x$ y& n4 R" o! qCharacteristic equation, 特征方程$ ?8 S7 C8 ?" C% h
Characteristic root, 特征根
, N$ j: s. }3 I9 _# X% U: v0 hCharacteristic vector, 特征向量
9 Q9 {) E" E* x, t5 \6 z/ qChebshev criterion of fit, 拟合的切比雪夫准则
6 L1 ]8 M; Q/ {7 N0 K6 n- P$ rChernoff faces, 切尔诺夫脸谱图/ |5 T( i. g" X' B) L9 P' ~8 h
Chi-square test, 卡方检验/χ2检验. e+ H+ M- s# Z$ B- p) _: k3 m4 J, H
Choleskey decomposition, 乔洛斯基分解
) a1 `8 s! b0 J5 `4 k, x$ F6 C0 OCircle chart, 圆图
* m( o) r* C0 Z8 e+ N- X8 Q, T# t2 M fClass interval, 组距. K0 k" T) @& a) Q0 O: U8 d
Class mid-value, 组中值$ K5 i$ Y" H) k* f3 M" g0 i
Class upper limit, 组上限/ |" ?3 e7 F1 I2 M" w7 p+ B
Classified variable, 分类变量! P; O9 }1 p# k" A+ v+ Q4 D; R' k
Cluster analysis, 聚类分析! L; b0 i) L$ z
Cluster sampling, 整群抽样
) n9 u! H# z! j! pCode, 代码$ E- k6 Z' G$ y; N+ k0 J% `
Coded data, 编码数据
# T/ `* Z' T' j2 g2 V; E* R' mCoding, 编码
" d Z; {2 |& X9 D5 j2 LCoefficient of contingency, 列联系数
# ?7 m9 L6 l/ H7 n# DCoefficient of determination, 决定系数; Y" r$ G% G) O* k+ o2 Q4 r* a
Coefficient of multiple correlation, 多重相关系数
V7 J: _% ?. N3 o' j8 TCoefficient of partial correlation, 偏相关系数4 Z- o2 `% M9 ^2 l
Coefficient of production-moment correlation, 积差相关系数
# G5 y0 b X+ FCoefficient of rank correlation, 等级相关系数
, d# c" R% S( s, e2 g, r# i0 @ FCoefficient of regression, 回归系数
; Z+ w& k V4 Z% @! p5 n+ ~8 ]' iCoefficient of skewness, 偏度系数
3 z7 \) r, B1 vCoefficient of variation, 变异系数
! P- v1 M6 n# |0 d! b- w. q+ bCohort study, 队列研究
# x. l/ k, v& K* sColumn, 列) l- Z- Z% }' }$ q
Column effect, 列效应; g; G* B" G2 A* l& X- a
Column factor, 列因素# F# |& r( b" d1 i0 m9 ]
Combination pool, 合并
7 J) ~6 k! \9 l* E( UCombinative table, 组合表
" d1 Q6 G7 o0 ~/ ` t9 eCommon factor, 共性因子
& ~2 N s! Q0 F- E: L' \$ a4 ZCommon regression coefficient, 公共回归系数 F4 m: r+ x: G& B" \9 a
Common value, 共同值9 I. a7 p, ~0 \& j6 ~( K
Common variance, 公共方差" c h) e- g; F, ~. z# t% M L
Common variation, 公共变异
! B" c! d4 X6 l0 Z" Q bCommunality variance, 共性方差( j! x' k2 R7 x
Comparability, 可比性
' c! R+ ]3 }- J9 s/ A1 H5 @: nComparison of bathes, 批比较8 j: T% j* v3 m$ _- [: S- {
Comparison value, 比较值1 d5 W; N0 S: [: W# L9 W
Compartment model, 分部模型
2 J$ o1 _- E$ `5 Z+ s# L0 C5 Y$ M/ @Compassion, 伸缩
9 x+ x* S8 l3 K' [( V# x+ _( y$ KComplement of an event, 补事件7 A: I7 `4 p$ z0 U
Complete association, 完全正相关: a2 O8 ^0 z+ Q" b
Complete dissociation, 完全不相关
, b0 ?% o+ r6 ?' x% t* j; ^4 s+ Z' B9 RComplete statistics, 完备统计量4 p- T5 V8 c' }6 ~& d. F0 O; ]6 p9 \
Completely randomized design, 完全随机化设计8 Q6 ?/ T6 n; j2 m7 F; |
Composite event, 联合事件
5 p1 f6 ]2 E& \5 w! BComposite events, 复合事件
1 b3 U+ y& n8 Z+ u- dConcavity, 凹性
; N% Y, q# w* D: E6 MConditional expectation, 条件期望+ `! B5 y" O k( ?
Conditional likelihood, 条件似然: ?( E8 h ?( N9 m- s' W
Conditional probability, 条件概率
, @4 m# D& K3 z* R! `Conditionally linear, 依条件线性
; v/ z* c" {, p4 Y) e, I! X! _Confidence interval, 置信区间# v4 \8 I/ N" w
Confidence limit, 置信限
2 ?3 A% ~! x/ a+ c1 t8 d, fConfidence lower limit, 置信下限
* y7 G% V8 p; _4 KConfidence upper limit, 置信上限. Y% a0 `8 g, R( a- ]
Confirmatory Factor Analysis , 验证性因子分析. k. s1 {: D0 f
Confirmatory research, 证实性实验研究5 l# H8 K7 }' C$ }0 D3 [ w" c, s
Confounding factor, 混杂因素1 Q$ ^# a% X. \
Conjoint, 联合分析
* n" E/ t# v5 j; q. XConsistency, 相合性+ F$ L; r( v/ q$ ~# B- I
Consistency check, 一致性检验
& W$ z) d" @: b$ eConsistent asymptotically normal estimate, 相合渐近正态估计/ w' b8 h. y2 B; D1 X/ D1 Z
Consistent estimate, 相合估计
3 P% N5 p( u( i7 N# OConstrained nonlinear regression, 受约束非线性回归
) c# ?5 |# i7 r- JConstraint, 约束
# j, `# K- q: f- j2 ^/ o! fContaminated distribution, 污染分布
9 Q# S' y0 J# V T* EContaminated Gausssian, 污染高斯分布
$ ~# m( i- i% hContaminated normal distribution, 污染正态分布
; O$ B( V B4 U( ~& A& L9 _* NContamination, 污染1 m2 p7 H n; T* i5 F5 p
Contamination model, 污染模型
1 m( t' V" ~+ f1 |$ T, DContingency table, 列联表
* N# X" y" U) e; CContour, 边界线
: k1 }! n, M* v/ T( w; UContribution rate, 贡献率
8 S k! B% |+ y. aControl, 对照
( X$ r$ `+ l1 R( f8 d0 fControlled experiments, 对照实验5 f5 J$ l: |+ |3 X5 |8 D* J* Z
Conventional depth, 常规深度
$ y& M9 }/ C9 u7 SConvolution, 卷积0 }- ]7 t: }2 `# V% x
Corrected factor, 校正因子
+ P% F8 s/ a' |( j& x% c! H9 |; WCorrected mean, 校正均值1 P3 E5 \/ y. A: R$ ^
Correction coefficient, 校正系数8 v4 R f$ S: h
Correctness, 正确性
, a# f* D( ~7 W4 r: w PCorrelation coefficient, 相关系数
. _1 o% u, x: Q1 k4 u; d# o' MCorrelation index, 相关指数3 i8 c: x# H- `! j: A$ r- d
Correspondence, 对应
9 H5 h" q& e( _3 i; p5 fCounting, 计数
6 k. o1 r6 n& i0 L4 ]Counts, 计数/频数0 w* o7 O% K5 W6 O* q& c* R9 G
Covariance, 协方差
. H1 n) F3 _" s" Z3 W# F RCovariant, 共变
( ?9 F5 P3 \4 Y2 ACox Regression, Cox回归& x2 M& J) S' o% x% A
Criteria for fitting, 拟合准则! c# j ]( k: S1 \8 m2 O) @
Criteria of least squares, 最小二乘准则
, k0 Z6 o5 ?& e yCritical ratio, 临界比6 e2 n7 o# ]* }. Z
Critical region, 拒绝域
" y8 n, i3 ? w9 f/ z [Critical value, 临界值
# u1 Y: v1 _+ FCross-over design, 交叉设计
% H5 y( J+ o7 Q- ]$ ?# c, U uCross-section analysis, 横断面分析
2 k: i/ n# E' @5 gCross-section survey, 横断面调查% G- Z& L. n& E/ S' I3 C
Crosstabs , 交叉表 + @, R% D& }: l7 R, s
Cross-tabulation table, 复合表
- t" S1 y2 _4 Y2 V! Q# MCube root, 立方根9 M! Y: ^7 W, R5 E# f9 |
Cumulative distribution function, 分布函数) S$ V7 u0 v% f" U/ Y) b
Cumulative probability, 累计概率
+ a% j, `/ }0 K$ @5 e1 O1 E+ _Curvature, 曲率/弯曲! W2 \6 x6 a+ N
Curvature, 曲率
2 x1 P& F- |: X6 x* {0 B1 aCurve fit , 曲线拟和
7 n7 Q) m. @$ @2 n3 {3 f) M& JCurve fitting, 曲线拟合" C- j6 [% d3 a H8 ?5 f$ {- p
Curvilinear regression, 曲线回归$ P+ d+ k) Y$ t: r6 R O! w6 \3 J
Curvilinear relation, 曲线关系. P5 a' g9 f) {6 N' a
Cut-and-try method, 尝试法
& g9 l! `9 k6 `( ]Cycle, 周期
% K \& O3 }' W4 b* L& NCyclist, 周期性& Z# j% P' j n0 W$ u7 P* ~
D test, D检验
- d% S6 _* e* `5 n }: wData acquisition, 资料收集/ k8 r/ A3 ?2 d+ Q0 Q
Data bank, 数据库- P# v; b1 z1 L% A. g
Data capacity, 数据容量6 T2 {: p5 u8 @% B% O, k
Data deficiencies, 数据缺乏
7 `. A' x& D5 X0 I2 ~Data handling, 数据处理$ U" p# s5 U3 j: _
Data manipulation, 数据处理! j4 u: \ d/ {) p+ O* r
Data processing, 数据处理
* G' {0 E5 C# l, S" |6 j" F( i# c3 cData reduction, 数据缩减
5 }8 }# ~7 B5 U9 w& p9 c5 Y# UData set, 数据集
, G' I( j3 V; q! h" `* pData sources, 数据来源
* ~' U5 c, Y0 w" o; X* V" `Data transformation, 数据变换
5 \* Z, X3 w; U- `, v0 j! m7 f LData validity, 数据有效性
+ ~2 K8 w$ c, s N$ {/ v' FData-in, 数据输入
, P3 h0 t7 o8 M' cData-out, 数据输出 b, _. Y! H+ O( T" B8 Z3 d
Dead time, 停滞期
7 u1 P9 W2 s: q# [' NDegree of freedom, 自由度
- ?6 b9 q P% Q1 Z) eDegree of precision, 精密度 Q( \: e1 A2 o0 H' J2 r
Degree of reliability, 可靠性程度, O9 U; ?" m# w5 s q6 B
Degression, 递减
1 J# B# g- S4 u" N9 w7 lDensity function, 密度函数; ], e0 `# o7 J/ ?" F0 B7 I! |
Density of data points, 数据点的密度, o" K0 G y, P, N9 `* {. p. C/ }
Dependent variable, 应变量/依变量/因变量0 A' ]& D& |4 f( y2 d" s. e
Dependent variable, 因变量9 r; h3 S; @3 S
Depth, 深度# k# U# H3 W/ e. Y! x/ D
Derivative matrix, 导数矩阵- X( \5 [/ C# m: I
Derivative-free methods, 无导数方法
) F. I' X2 S3 u/ H+ |Design, 设计
' ?* K1 x: S2 ]% G3 b" gDeterminacy, 确定性
6 q2 q. |9 ~2 E# x+ @' w! l) FDeterminant, 行列式
0 o y/ [: J z5 t; a$ n$ y7 PDeterminant, 决定因素! I) u4 `! k- R8 O8 u* m, d
Deviation, 离差
8 G% H% x- z+ t* Q5 N; `4 d' {Deviation from average, 离均差) [9 g5 U" }& H* |- H
Diagnostic plot, 诊断图3 x" W( q0 q& @; a4 K5 l7 Z
Dichotomous variable, 二分变量 e' q& Y) k& U$ K: l w5 I
Differential equation, 微分方程
) F( V6 _5 X& \+ VDirect standardization, 直接标准化法
l2 t- _( w! y2 B, @+ J2 zDiscrete variable, 离散型变量& I/ E( b9 v+ y7 y4 _. K: G2 \( W, X g
DISCRIMINANT, 判断
. P2 P( ?7 \# G: ~5 y5 l$ G+ NDiscriminant analysis, 判别分析! P3 Q7 ^0 G1 ^+ _3 O1 W
Discriminant coefficient, 判别系数2 n/ h G# k9 K V* r
Discriminant function, 判别值
" x# e" y& Q- M+ j( m( ?% cDispersion, 散布/分散度" q1 P% M# d* s5 n3 e8 K7 V) Z
Disproportional, 不成比例的
" m( c/ R; P' eDisproportionate sub-class numbers, 不成比例次级组含量4 x. q7 U# i0 q) r2 K, K
Distribution free, 分布无关性/免分布
, g' e& }7 }" g/ f/ |Distribution shape, 分布形状
~5 L S' \" _8 G, tDistribution-free method, 任意分布法
' l# V6 q# ^$ M, h/ d& CDistributive laws, 分配律( h4 o; q+ X# w, G
Disturbance, 随机扰动项' N9 d& H2 a ^: h. y! L: Q
Dose response curve, 剂量反应曲线 U/ a/ k# w% [2 T
Double blind method, 双盲法3 d6 I( @8 X9 j7 ]- ]& I& \1 m
Double blind trial, 双盲试验/ n% ?6 |2 Y3 |
Double exponential distribution, 双指数分布
1 n8 C: j0 X) e* pDouble logarithmic, 双对数
, d' x5 w( G/ Q0 M1 A9 FDownward rank, 降秩
; ]9 }2 k- u6 ~0 O( N/ _6 b4 NDual-space plot, 对偶空间图% {6 q' w6 {' ]) Z! O9 e8 c
DUD, 无导数方法
# [) |- q9 M) z( i' P! ?! \Duncan's new multiple range method, 新复极差法/Duncan新法; m; h; @- {2 ?( X$ j
Effect, 实验效应
, D* H. X: T! q% ^7 ]6 c! D) L4 rEigenvalue, 特征值( l! I5 M' v% ]! K
Eigenvector, 特征向量
; p7 I: c1 Z9 qEllipse, 椭圆
2 \' a# B) e3 ?" B! O2 Q; i W7 TEmpirical distribution, 经验分布
) U' b5 M& z+ ]Empirical probability, 经验概率单位
5 a# x! P8 D6 }; j/ A6 [/ @Enumeration data, 计数资料6 ]2 W9 x# S( E+ a9 b" n; C0 ~) X
Equal sun-class number, 相等次级组含量/ j! R8 L7 n, A4 p8 R7 b( G
Equally likely, 等可能* b: v, P' P- A) n4 @9 O; |
Equivariance, 同变性. d5 K' F: K' B% a% v
Error, 误差/错误! Y# @" b1 X( B4 J
Error of estimate, 估计误差
5 V: h/ k3 b9 FError type I, 第一类错误
5 X3 Y0 r$ U, N! q( zError type II, 第二类错误
; f3 @/ d: l1 M$ P; iEstimand, 被估量
7 D5 L& U6 h* _: u7 @Estimated error mean squares, 估计误差均方9 v; q3 J: h/ T- F/ C
Estimated error sum of squares, 估计误差平方和
2 K2 p+ w# m& M8 ?Euclidean distance, 欧式距离( k* r! R! w+ t
Event, 事件$ ?- U F6 ~7 h! [+ J0 a
Event, 事件
0 y& E/ L5 l& fExceptional data point, 异常数据点
' V4 z$ W& d3 C8 uExpectation plane, 期望平面
/ c) `! _4 S7 G5 cExpectation surface, 期望曲面- A1 C9 l2 v$ L. |
Expected values, 期望值0 ~6 L& z6 C/ V! ^! X" r
Experiment, 实验
1 S6 p! D7 I7 }' F5 M4 i6 Q6 vExperimental sampling, 试验抽样4 W# Q$ D0 k* L& f
Experimental unit, 试验单位( {% d! b0 |, u* b E5 E2 H5 U F+ n
Explanatory variable, 说明变量2 K) {+ @, s8 @9 q6 h% U
Exploratory data analysis, 探索性数据分析
& Z* Q3 J, f$ C4 N% CExplore Summarize, 探索-摘要
+ d5 U) f) h; H _Exponential curve, 指数曲线
, H" y0 F3 W( I' L" C& Q6 L, U9 m8 W+ c5 qExponential growth, 指数式增长
) [/ E0 l, v* i; w; \EXSMOOTH, 指数平滑方法 2 V' r# b: g- q2 f
Extended fit, 扩充拟合/ f: S7 N9 T$ y& V4 K( K
Extra parameter, 附加参数8 i" C% N8 n; [8 V3 g v! a/ d/ U
Extrapolation, 外推法
1 [+ l7 i& n) hExtreme observation, 末端观测值0 u- o) w7 t# f" m- d' }, T* p. Q
Extremes, 极端值/极值
* _ |+ W9 I. V3 bF distribution, F分布
5 [) t, ]: X/ b! j/ n' k5 }5 qF test, F检验: o7 t) ~: A; P d/ z' v% }% T* N
Factor, 因素/因子( W `2 V9 k' \; R0 c
Factor analysis, 因子分析, M" v$ L# s2 _ h8 x0 ]
Factor Analysis, 因子分析3 S. N* J: {: I0 ]! q. ]9 ~
Factor score, 因子得分
( \5 Z3 D: A/ gFactorial, 阶乘8 y% r3 ]8 D! D0 |
Factorial design, 析因试验设计
) a" l6 M2 C$ c' JFalse negative, 假阴性! o0 l/ R* B4 c$ L( c
False negative error, 假阴性错误
0 a# G6 s( q* \3 q% O% wFamily of distributions, 分布族3 D8 Y7 U2 X7 g$ x- K0 Q: R
Family of estimators, 估计量族( i4 E) D2 u9 B$ B' r
Fanning, 扇面) f7 V' l6 f3 e
Fatality rate, 病死率
; c; G$ i# } ~" A+ F& R$ eField investigation, 现场调查6 n6 p' z/ v" v5 @
Field survey, 现场调查
8 Y- a; s4 \ _; m, {4 a8 TFinite population, 有限总体
' h% o) f4 L3 s4 {3 Z0 QFinite-sample, 有限样本
2 X% k0 a6 E3 ~3 c1 dFirst derivative, 一阶导数
* c9 D6 X, j" |& \$ u' tFirst principal component, 第一主成分
2 K+ k9 f3 E/ y+ R( I( Q& @First quartile, 第一四分位数8 b( B4 N0 l |) k, I
Fisher information, 费雪信息量! k# B# n1 e8 B
Fitted value, 拟合值; n" P6 A, N: {( V$ m
Fitting a curve, 曲线拟合$ m- p. d: k$ T; [' o5 h
Fixed base, 定基! J. w0 }# Y1 u+ s* @; Q# s
Fluctuation, 随机起伏
9 I6 V. X8 T! z6 kForecast, 预测
! m1 A& r: T3 _( ~4 hFour fold table, 四格表" |, |2 y; } p
Fourth, 四分点
, X+ M" C( ` w5 hFraction blow, 左侧比率
0 C0 r* v% e% j3 WFractional error, 相对误差% c$ c+ V5 I: [
Frequency, 频率) u0 ?- [* r) C; q1 k8 C/ ^
Frequency polygon, 频数多边图
( X. D4 K9 @. [% f* s5 |* X% ]# wFrontier point, 界限点
# D0 G9 ? O7 aFunction relationship, 泛函关系* O6 W* D6 }( K5 x, q' ^- B
Gamma distribution, 伽玛分布
& @2 E& V( c( B7 Z* `1 l' h0 XGauss increment, 高斯增量
0 a) u; }% w. b2 p$ Z4 xGaussian distribution, 高斯分布/正态分布! A2 \# {: p% x2 i! u2 ~# H
Gauss-Newton increment, 高斯-牛顿增量$ S E0 {) r- h$ N, s/ C
General census, 全面普查
3 d" K" r5 b- J5 E$ T# NGENLOG (Generalized liner models), 广义线性模型
" `- \- W! K: E n* d6 G @Geometric mean, 几何平均数% u" a j7 D0 M1 F @! U
Gini's mean difference, 基尼均差, I8 F. z! k+ B; k' n* R/ U |* B
GLM (General liner models), 一般线性模型
" _, X4 c( e4 {8 o L# dGoodness of fit, 拟和优度/配合度
0 j& ?5 s( C9 n6 v. ]& ^& k! ?8 bGradient of determinant, 行列式的梯度
% J0 m" G$ p2 D U( {; W1 j& HGraeco-Latin square, 希腊拉丁方9 r& F4 |8 Z* a' @' c) \
Grand mean, 总均值
7 s L+ o8 W8 GGross errors, 重大错误0 {0 w6 t5 S7 e" X
Gross-error sensitivity, 大错敏感度
; J* {% B9 x# XGroup averages, 分组平均6 p# O& f9 K% j
Grouped data, 分组资料
. b3 s6 F- r }Guessed mean, 假定平均数4 K1 Z$ G. Y$ d3 J
Half-life, 半衰期* [6 k* e. u! I9 z2 o% {3 V, n
Hampel M-estimators, 汉佩尔M估计量
0 ^" g0 J5 L* Y" x, p* THappenstance, 偶然事件
2 t# |% b, \- C5 B' lHarmonic mean, 调和均数
% h7 C5 n% w/ |# {7 q2 u1 P, t9 fHazard function, 风险均数, q7 P9 V/ J% j: y) r# I
Hazard rate, 风险率
, [+ [+ Z3 N+ s7 z. o: \Heading, 标目
& V! r/ g$ H% y5 HHeavy-tailed distribution, 重尾分布
) S, x! C! y) t/ n* x4 N" G1 Y& DHessian array, 海森立体阵& M( a: s6 v2 M) z
Heterogeneity, 不同质
' y: J: E* Y! R* W9 c2 ~5 Q4 l! DHeterogeneity of variance, 方差不齐 : x# W2 u7 a; x1 f4 r5 Q
Hierarchical classification, 组内分组
5 y- C& }6 K9 D4 L% fHierarchical clustering method, 系统聚类法
5 M% W3 g- k: A" l" A$ @! m( THigh-leverage point, 高杠杆率点
+ ^! _! S" g, _HILOGLINEAR, 多维列联表的层次对数线性模型3 k$ ~9 O5 Q. h; N
Hinge, 折叶点4 A/ L5 S1 e* E! A/ ^
Histogram, 直方图
- ^ J8 i* k. \/ M/ k9 o Y8 FHistorical cohort study, 历史性队列研究
* q, b* k2 I. T- `' |+ c, O/ NHoles, 空洞# t/ {3 N! b B/ B$ A8 d
HOMALS, 多重响应分析
3 t6 [" v9 b& C( ^Homogeneity of variance, 方差齐性5 O* I5 l G* Q* b2 L
Homogeneity test, 齐性检验
% Y- x; N# @/ }* s4 `4 VHuber M-estimators, 休伯M估计量 O2 P( `/ O5 m2 J- t* e. O3 h
Hyperbola, 双曲线0 i! L6 g2 B |0 q7 V6 U' n+ F ^
Hypothesis testing, 假设检验$ ^# u" w: {, r, M
Hypothetical universe, 假设总体8 K; n9 G9 y3 o" N0 }8 J: M" }, t* H
Impossible event, 不可能事件, i5 C$ a; r$ x$ }9 h0 |5 F1 }
Independence, 独立性8 {9 y" X7 B) H- Q3 Z
Independent variable, 自变量; s2 _1 C- U9 ?- o# g- |1 |& _ b4 f. m
Index, 指标/指数
2 T+ h# {1 |( ^Indirect standardization, 间接标准化法
7 F W" L A! G5 I9 P5 |Individual, 个体
; Y L3 e" F$ u) \" q" ^7 ?/ f2 E3 |$ oInference band, 推断带
+ ^$ @+ l9 y1 z8 j j- L) ]Infinite population, 无限总体2 f' C9 S2 e; `
Infinitely great, 无穷大
; {9 R- O, U+ _- cInfinitely small, 无穷小6 e3 P, A9 B9 J0 H
Influence curve, 影响曲线- q, @* v% I% W) ?- ~8 F! V
Information capacity, 信息容量, @+ V. ~ s1 c$ _3 }7 B- e- ]: M
Initial condition, 初始条件
8 e9 U- T( E/ wInitial estimate, 初始估计值
7 L/ o4 X$ u5 |Initial level, 最初水平( Q- L5 ?: ~$ p5 ?& S1 b# G% n
Interaction, 交互作用* \0 Y# J6 F, R/ P
Interaction terms, 交互作用项
& f1 j3 G1 x% Z- E* _- Y) }Intercept, 截距. x2 w+ ^3 F" C+ P1 w8 Q
Interpolation, 内插法3 C' v' E4 z' [ ?( `- l, Q+ X3 u
Interquartile range, 四分位距
) `) b* @( z9 R( M* rInterval estimation, 区间估计% K8 D+ R3 W8 t" e
Intervals of equal probability, 等概率区间
7 ^+ _; f( L; P9 bIntrinsic curvature, 固有曲率
# U8 C; R" N( C& _2 [5 q: eInvariance, 不变性& Q* p# K7 C Z# V9 I y- |9 h' J
Inverse matrix, 逆矩阵8 J& W4 t' F" W) g
Inverse probability, 逆概率
1 A9 N. S& ]% x" C% I1 D% [7 HInverse sine transformation, 反正弦变换
- p8 h: e5 O+ d' n/ qIteration, 迭代
0 ^( w' A4 T! l A( i. `Jacobian determinant, 雅可比行列式$ e% a: o( K2 C
Joint distribution function, 分布函数& X, C5 m( Q* \6 w
Joint probability, 联合概率
7 r# \. H/ K6 z# A5 Y5 QJoint probability distribution, 联合概率分布
" d. Z4 |4 D2 k0 b# E tK means method, 逐步聚类法
1 n9 @6 K6 o5 y2 ^0 V' o$ bKaplan-Meier, 评估事件的时间长度 $ f) V. |. Q/ L6 s
Kaplan-Merier chart, Kaplan-Merier图8 j5 g: O% O% t8 [8 u
Kendall's rank correlation, Kendall等级相关% T7 B; Y N( G( h, d9 O) f% n" I$ N
Kinetic, 动力学
- o. f; @; z0 O/ OKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验+ V9 B" @' L9 J) X3 @. a. z
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
3 i0 L# L- \1 h' f* N/ cKurtosis, 峰度& t- o; a6 p' p7 g
Lack of fit, 失拟
! O, {( u ?4 @7 BLadder of powers, 幂阶梯0 ?4 v/ t$ p1 \. P8 |: q
Lag, 滞后( ^% b* S( g- N" a. Z' T8 q) c" ?
Large sample, 大样本
1 @) ~1 f! q& q3 p/ f) `1 D+ j8 HLarge sample test, 大样本检验- T/ r4 o+ Q/ H$ R2 h7 e0 Q+ ~, _" h
Latin square, 拉丁方
7 V7 K$ `! k. ~) C, _. |# XLatin square design, 拉丁方设计
5 s/ T. k2 P( H3 n& d0 ?% P5 uLeakage, 泄漏8 h! P2 c0 O/ q; O/ y& r
Least favorable configuration, 最不利构形
7 F* I% _) M c& n) x9 l7 qLeast favorable distribution, 最不利分布' T# a0 r) Z! {
Least significant difference, 最小显著差法
C/ C, h: c. mLeast square method, 最小二乘法
+ X, @" u0 w' `Least-absolute-residuals estimates, 最小绝对残差估计4 `* S" W: f+ p, E
Least-absolute-residuals fit, 最小绝对残差拟合0 R! U9 {9 v% c
Least-absolute-residuals line, 最小绝对残差线
% d3 V& r8 N- |( ALegend, 图例
* }/ J& L* a0 E4 V2 }8 G- }" K8 FL-estimator, L估计量
8 O7 B9 W8 _' Q, d9 HL-estimator of location, 位置L估计量4 A) h2 @, H0 I
L-estimator of scale, 尺度L估计量
' y' h- a: F& j$ p$ |Level, 水平3 o" y+ |5 j9 \9 O' L$ a/ n! x
Life expectance, 预期期望寿命
7 N! @/ _3 p1 J! _! bLife table, 寿命表
# n: t/ ]6 @" k. L, L( eLife table method, 生命表法
) Y l' j4 t4 Q" P' Z MLight-tailed distribution, 轻尾分布( M$ @" [, f. n' F$ {+ |
Likelihood function, 似然函数4 m7 A. d( p$ g$ I; ^4 \
Likelihood ratio, 似然比; x/ G: l- U9 q+ C9 H! R, K
line graph, 线图. g! G- J, c+ D8 M
Linear correlation, 直线相关
5 d& E% d2 s2 ILinear equation, 线性方程
1 f9 \6 e9 f/ x% @4 |" `Linear programming, 线性规划
- h+ `3 _' S& F8 \' |8 QLinear regression, 直线回归
7 s3 t6 l8 s# B6 g2 Y, RLinear Regression, 线性回归1 Q# a# S b! q: m2 y1 w* E
Linear trend, 线性趋势
9 E) P$ S4 l, [, F% L/ `% aLoading, 载荷 $ [3 \- k3 _8 ?# h( @9 a5 f6 v
Location and scale equivariance, 位置尺度同变性) d' \! c* e i* V+ b
Location equivariance, 位置同变性 Y( H% s" X2 \# J( ~# L
Location invariance, 位置不变性# G3 ~' N& n" }3 T, Z+ n
Location scale family, 位置尺度族7 U* V7 H# B% G4 V' Y2 O
Log rank test, 时序检验
! |5 T2 i! z5 F* ^" v8 _1 ^, D+ [1 `Logarithmic curve, 对数曲线4 G: B5 S3 D1 h
Logarithmic normal distribution, 对数正态分布
& V' s4 {5 q2 m7 C, `3 T1 fLogarithmic scale, 对数尺度
. ?- P- u$ {; j: W) Y) H) D! ~Logarithmic transformation, 对数变换, u/ f( l% b; x# L
Logic check, 逻辑检查( p3 W" z' }. L; M2 }
Logistic distribution, 逻辑斯特分布
% g' D# \; d6 O( DLogit transformation, Logit转换2 k# r8 |3 q5 c2 S2 X* Z" x- U1 n
LOGLINEAR, 多维列联表通用模型
% l. C! H/ |; c. BLognormal distribution, 对数正态分布
% W+ a' P6 X- BLost function, 损失函数
" E/ Q# H/ O- X& \Low correlation, 低度相关3 e/ Q; Z3 n% b: \- Z
Lower limit, 下限
! A" }* r) {' H! a) ~, o7 uLowest-attained variance, 最小可达方差( P. l! B) S T% z* H& v2 p, y4 f1 L
LSD, 最小显著差法的简称
3 T6 o# C% _# p5 ^Lurking variable, 潜在变量
. x9 |1 U& Z$ { Q6 T! JMain effect, 主效应) W$ {3 \6 e& D4 Q* }
Major heading, 主辞标目
2 v$ i- ]$ C, n/ Z' A0 w k2 ZMarginal density function, 边缘密度函数" W& n8 o# L* g! q* S( U1 i
Marginal probability, 边缘概率( ?, X2 H" a% t* X& l: y
Marginal probability distribution, 边缘概率分布
2 V! I2 v$ G7 ?& ^0 A# `4 I2 [Matched data, 配对资料
" G ~$ t% N6 g+ B9 x" i/ YMatched distribution, 匹配过分布6 b$ A: z7 X# e7 A- \3 ~' V
Matching of distribution, 分布的匹配9 t/ H/ K; j5 g# y
Matching of transformation, 变换的匹配2 X6 [1 J: ]& _5 f/ ]' i! b
Mathematical expectation, 数学期望( F% K3 N6 v3 H
Mathematical model, 数学模型$ s, f) l% ?0 k: ^) P+ a
Maximum L-estimator, 极大极小L 估计量
' Y" ]6 c# l- [4 JMaximum likelihood method, 最大似然法
) L$ i4 L2 _) V4 r8 K4 v1 _Mean, 均数+ M7 r. ^0 }$ T3 F p% f4 G
Mean squares between groups, 组间均方! W1 _& S/ r- ?* Z& A5 y# K( C7 \
Mean squares within group, 组内均方: w8 J4 p4 v5 G2 I5 p* j( L! | ?' l
Means (Compare means), 均值-均值比较
' `& _+ y4 y* a3 Y' FMedian, 中位数2 d8 ]% S1 X1 y0 Y8 j `) S* l1 n
Median effective dose, 半数效量
8 D: _0 V. q( V3 d2 JMedian lethal dose, 半数致死量
2 E$ R% R8 k: L3 A& j1 q$ DMedian polish, 中位数平滑" d; m: f" z$ w2 G( `5 E) h: u9 R
Median test, 中位数检验
$ d- z+ t0 i; t- EMinimal sufficient statistic, 最小充分统计量( }+ B, u" g8 a
Minimum distance estimation, 最小距离估计
5 f: Q8 ^6 e4 {Minimum effective dose, 最小有效量
) K/ K( v+ S" |0 |; _5 a# pMinimum lethal dose, 最小致死量; N- T' i7 ]% Y
Minimum variance estimator, 最小方差估计量- `4 s, [6 u1 r) t i. x" g
MINITAB, 统计软件包
& W* M ~8 e4 Q! s, }0 K/ H+ rMinor heading, 宾词标目3 x( F: ?9 A$ W. t& [8 M) @6 y8 |
Missing data, 缺失值
$ ?% [- Y& S0 z% C* N3 |6 NModel specification, 模型的确定
2 y; Y9 \: O8 J% VModeling Statistics , 模型统计+ m* n6 f3 x4 d- j0 G0 v, K
Models for outliers, 离群值模型
1 _1 I4 b$ ^ Z. W3 ~9 bModifying the model, 模型的修正) \6 w% A8 Y# N4 |5 O a
Modulus of continuity, 连续性模* N9 t' J( [; g+ c c
Morbidity, 发病率
' [% _7 D, J& O/ Q7 I" OMost favorable configuration, 最有利构形
1 J% n+ d: q* o' BMultidimensional Scaling (ASCAL), 多维尺度/多维标度6 Y) Y" q, m$ v
Multinomial Logistic Regression , 多项逻辑斯蒂回归
) l+ y# a2 ^2 i0 a. wMultiple comparison, 多重比较9 }" q, Q% Z, x1 r4 L5 B9 ~
Multiple correlation , 复相关8 c% J+ }0 _1 h! q" g) A
Multiple covariance, 多元协方差
' P6 r9 u; [% A" H3 |, X" SMultiple linear regression, 多元线性回归% t; w- c- T8 S; Y/ n
Multiple response , 多重选项
. h3 j$ o+ l* D' oMultiple solutions, 多解
% P: a( q( q. s( W3 C$ G3 F$ `Multiplication theorem, 乘法定理2 }6 G! S! `/ _- D2 |4 W' |
Multiresponse, 多元响应# t9 W5 C7 v' V8 K$ R
Multi-stage sampling, 多阶段抽样
, u; o' U3 a4 J$ g! T& {Multivariate T distribution, 多元T分布 R0 j0 g3 j5 @2 v* L
Mutual exclusive, 互不相容( U) `9 S# d1 ]7 N- l, t
Mutual independence, 互相独立+ Y k* h, L6 P* p5 A+ r) a
Natural boundary, 自然边界
+ n4 F+ I5 Y/ A! lNatural dead, 自然死亡
1 N6 P( n& l' N0 l% C9 fNatural zero, 自然零8 I% _6 e8 c' `# Z2 g
Negative correlation, 负相关4 K6 B/ N5 Y3 H7 c+ x* G
Negative linear correlation, 负线性相关
: h6 ]2 N9 o1 X2 MNegatively skewed, 负偏
' t' J. ~" i- `* mNewman-Keuls method, q检验+ K9 P; m) [ X# ?/ S1 n: V3 K# ^
NK method, q检验7 X; K) T. i' T6 R d7 p; ^# J
No statistical significance, 无统计意义
+ v; b4 H; M0 p& ]& H/ n' }Nominal variable, 名义变量. ]7 I8 }4 K/ g- _% R
Nonconstancy of variability, 变异的非定常性& Y, { t, c8 ~ w6 M- |6 ?8 j
Nonlinear regression, 非线性相关
; ?( V7 @2 S/ G$ m9 }Nonparametric statistics, 非参数统计1 M2 ~' W% l9 z0 h
Nonparametric test, 非参数检验( Y4 |* ~- N4 v5 W3 S
Nonparametric tests, 非参数检验
1 J1 ^ W' g' E8 g8 ]4 H& h% L& ]Normal deviate, 正态离差+ A1 ^1 C) k- i
Normal distribution, 正态分布/ T/ p5 ]9 T7 e
Normal equation, 正规方程组: @$ o0 `& U( ]! _4 H4 ]
Normal ranges, 正常范围) C! j. g) N- J! t2 E) b: t
Normal value, 正常值
* M: v5 K) ~( n* V3 ^Nuisance parameter, 多余参数/讨厌参数
% r3 y3 j1 M- oNull hypothesis, 无效假设
* Y5 l7 C" G; `Numerical variable, 数值变量
D% O4 |' o1 v) |& \Objective function, 目标函数7 z4 Y2 q& z. e
Observation unit, 观察单位
! v4 M( L# q6 H6 l ?9 tObserved value, 观察值/ Y6 y6 {% }: O
One sided test, 单侧检验
M; a/ Q' _! B" _7 Y* G7 g; vOne-way analysis of variance, 单因素方差分析
9 a* u3 c+ u9 V S* q% z; Q6 qOneway ANOVA , 单因素方差分析 v8 Z T, A: ?- I- X
Open sequential trial, 开放型序贯设计/ C& b5 u2 W/ K, G
Optrim, 优切尾
K, L( A- |( J8 b' tOptrim efficiency, 优切尾效率
v4 I/ L5 |8 j# rOrder statistics, 顺序统计量& a) t. C# \* ^* ]7 c/ z x% w4 U
Ordered categories, 有序分类0 [) `7 g; o: T& l% [* e& E0 V
Ordinal logistic regression , 序数逻辑斯蒂回归 o8 X" `2 k F3 A5 }! v Y
Ordinal variable, 有序变量
5 e2 [) g' a4 [ e$ BOrthogonal basis, 正交基- f! F- o* u1 F/ [
Orthogonal design, 正交试验设计 \- a; X5 ]9 `9 s: B- f2 o
Orthogonality conditions, 正交条件
3 [! J$ e& H( `6 ~$ y( p2 t" P' yORTHOPLAN, 正交设计
9 z, F3 n( h- {( P% QOutlier cutoffs, 离群值截断点
% _3 g- W% C3 aOutliers, 极端值
. j3 G! \& r7 r4 d* a: c. S; w) e/ COVERALS , 多组变量的非线性正规相关
4 N! h/ m m G6 u* bOvershoot, 迭代过度
4 f9 A7 v$ E6 n' DPaired design, 配对设计
( h6 \2 ^4 `0 r4 c3 B5 Z$ wPaired sample, 配对样本
! d4 T* P5 c; J: aPairwise slopes, 成对斜率
( Q# l* G* W$ N% v0 ^* lParabola, 抛物线/ }: N1 g$ {! I8 n x: Q. J, k8 J4 {9 q
Parallel tests, 平行试验 m2 Q: d9 ` X7 }" P
Parameter, 参数
0 ^9 m! O3 h2 B8 R% V% pParametric statistics, 参数统计
* `" e+ M/ h8 f0 X* O8 BParametric test, 参数检验# E4 y9 |, M1 m1 B$ I
Partial correlation, 偏相关
1 ^# T% J6 T# v0 y, hPartial regression, 偏回归
B4 Z& }8 e/ `Partial sorting, 偏排序! Y+ w. [. T% A8 O$ n+ Z0 N9 F6 x
Partials residuals, 偏残差1 y4 W$ _3 @/ b7 z6 Q6 `6 v
Pattern, 模式
8 ]) I- @6 C- QPearson curves, 皮尔逊曲线
F/ z0 Z3 ]1 e6 i- I A* WPeeling, 退层
1 P# J; O! {! {4 B& TPercent bar graph, 百分条形图
3 [& Q. Z* X: aPercentage, 百分比
0 b. E f7 l$ e; c: QPercentile, 百分位数
; [, w* y$ I8 C P0 Z2 fPercentile curves, 百分位曲线( `" P1 j! u1 b. \" v4 P1 Y4 s ?
Periodicity, 周期性
- \5 {; z: c- [1 l* s. V2 \7 i. YPermutation, 排列 n- n# c( x& [, Q% E
P-estimator, P估计量7 J+ z( p0 j* N! e2 w0 C
Pie graph, 饼图* a9 N( ^) l2 R) n5 N, P/ g
Pitman estimator, 皮特曼估计量 \7 m; E* e; e1 h$ R, x
Pivot, 枢轴量
) ?8 b& @# r9 lPlanar, 平坦0 q; R& h9 h9 K3 z2 | n
Planar assumption, 平面的假设
. k, ~8 T* |2 P/ XPLANCARDS, 生成试验的计划卡' _2 E$ A5 P3 B
Point estimation, 点估计
5 U+ J) Y# H8 f# Q, l+ ]Poisson distribution, 泊松分布
7 |% D+ ^9 [0 aPolishing, 平滑4 z6 m: J& M( U1 q. N8 T+ I
Polled standard deviation, 合并标准差) h" A5 v3 |. j- m* ^% u
Polled variance, 合并方差
/ h" b6 n' N; KPolygon, 多边图3 {4 p- X7 f3 Y+ V- e3 N/ P- z. Y4 z
Polynomial, 多项式9 y& p8 a4 p% ^3 o7 y! `5 i
Polynomial curve, 多项式曲线: S& P9 s8 F& z! h4 `; _
Population, 总体% s. q9 k2 y3 z
Population attributable risk, 人群归因危险度6 F: _% d& H3 ~) l" a
Positive correlation, 正相关" u# @5 H7 F/ c! _
Positively skewed, 正偏' _& ^1 j2 r' f- O( V
Posterior distribution, 后验分布
2 n) g* P" t( DPower of a test, 检验效能
) T* t+ G5 K( E1 E4 ?; BPrecision, 精密度
, T Z- S! X3 u# j, F! h9 O5 XPredicted value, 预测值
4 i! o$ S9 J1 R7 ^' k2 d: |Preliminary analysis, 预备性分析
* G: r3 x6 T$ e/ ]6 ]1 q+ cPrincipal component analysis, 主成分分析+ }( _0 o( |- G% A4 H- o
Prior distribution, 先验分布$ g" b9 p% X8 I$ J+ G
Prior probability, 先验概率2 m- C* G' m) J, z
Probabilistic model, 概率模型4 I" L; E' r0 N2 |5 Y7 d$ E% p
probability, 概率% i! h: ?0 l3 j1 X1 P3 w) a4 E
Probability density, 概率密度6 V! W% y* M T
Product moment, 乘积矩/协方差- |4 o* p6 [2 b. Q$ D
Profile trace, 截面迹图) x# x4 _1 k. p- T7 |) U
Proportion, 比/构成比
5 R+ P5 C$ p9 d$ X2 q6 X# e6 }7 w% PProportion allocation in stratified random sampling, 按比例分层随机抽样
" N/ h) E7 a& `Proportionate, 成比例0 C5 ^- _% X* ]
Proportionate sub-class numbers, 成比例次级组含量# `' x( a6 ?0 c2 H: q9 h7 P
Prospective study, 前瞻性调查
]& Z8 ~! o2 o$ sProximities, 亲近性
: O# ~4 v% W' ]3 d* ^9 nPseudo F test, 近似F检验. v2 y9 v. c1 A4 l9 m+ u7 ^! G
Pseudo model, 近似模型1 l% M2 L8 M L0 c( ~$ ~
Pseudosigma, 伪标准差5 i+ j$ d9 x, R$ b
Purposive sampling, 有目的抽样
9 t# T8 k5 w0 y6 w4 ^5 \QR decomposition, QR分解; F* \3 S' y% Q* |, x* v
Quadratic approximation, 二次近似. F3 s$ U2 C+ L5 m6 o
Qualitative classification, 属性分类
5 p6 s* l6 \- |! _$ i \Qualitative method, 定性方法7 r# O! q- s% V( a5 K' t! P
Quantile-quantile plot, 分位数-分位数图/Q-Q图
/ C$ h) S' s' j5 V* B- sQuantitative analysis, 定量分析8 p2 L# Z2 m; c
Quartile, 四分位数
) z% G$ ~+ g6 G- GQuick Cluster, 快速聚类
) O A3 t: z) [* c, n8 RRadix sort, 基数排序
9 \6 \6 K, _+ a3 R0 P' `& j" B6 iRandom allocation, 随机化分组
) H G U) J/ L* g6 qRandom blocks design, 随机区组设计
' A3 ^0 D: M1 C# K0 Y! v# H- e: IRandom event, 随机事件' `3 E2 N# b: I3 i& F2 Q9 _
Randomization, 随机化
4 b% b6 u8 ~0 O5 |Range, 极差/全距
; ]! q- g. T! }9 V0 JRank correlation, 等级相关' m& Z- j+ s# H/ i
Rank sum test, 秩和检验
) Q1 U5 f% W2 ^- I. d) l. `Rank test, 秩检验4 {, Z$ }* @( j
Ranked data, 等级资料1 E- f( p, S. ]& `6 Q
Rate, 比率/ x& M( a* Y, a
Ratio, 比例
6 X! ^# v$ v; }0 k) G# w) wRaw data, 原始资料: r" N/ r. L" z1 U
Raw residual, 原始残差& W2 j1 R+ Z/ ~, u
Rayleigh's test, 雷氏检验
3 T* M$ K2 p* g8 O7 mRayleigh's Z, 雷氏Z值
, k8 [ I2 V/ o! B% qReciprocal, 倒数
+ t* m" ~9 \/ `Reciprocal transformation, 倒数变换7 q$ k+ |- C1 k! W; j6 W
Recording, 记录 M0 ^' A% \4 V3 P% o2 }+ }9 y
Redescending estimators, 回降估计量
+ }6 F2 H: m) e& ]9 F" ~8 tReducing dimensions, 降维: g) \" x2 Q2 H5 @8 U' ^& v
Re-expression, 重新表达5 g5 H" n9 ?$ i% L* L
Reference set, 标准组
! g% b+ Z0 {, m7 b4 mRegion of acceptance, 接受域
3 W4 U" M, y* L! U+ o+ C# g# g/ q' ]Regression coefficient, 回归系数
& y' N1 K* C8 n& iRegression sum of square, 回归平方和
Q/ k! K: q7 I+ }( J& q; aRejection point, 拒绝点" J U D, m+ ^
Relative dispersion, 相对离散度
7 r) b" ]; I; _: o7 l+ Z7 A6 uRelative number, 相对数
" O. h1 U) x A: lReliability, 可靠性
6 b. j! y" h$ t' M& M( l- wReparametrization, 重新设置参数
3 B0 ]6 G9 `) b$ U% UReplication, 重复% `/ |9 Q4 S# A3 ^# l9 m: B4 f
Report Summaries, 报告摘要1 V6 m+ @( y) k
Residual sum of square, 剩余平方和. }, U$ f4 ~/ i
Resistance, 耐抗性
2 R- I0 @/ Z! I, s0 Y9 m1 u- H& AResistant line, 耐抗线! Y7 }3 t; P0 z z
Resistant technique, 耐抗技术
. C1 P2 u/ i: J( t0 \2 B- w8 {R-estimator of location, 位置R估计量+ ]; }+ F7 e# C# b4 A! s
R-estimator of scale, 尺度R估计量3 [' i2 h7 y: z$ z5 T1 i
Retrospective study, 回顾性调查# n8 q; q; c! k4 l
Ridge trace, 岭迹
( c- H2 E) B8 g; d/ ^( B& N: o6 aRidit analysis, Ridit分析. a) R( m4 _' i3 ]7 |
Rotation, 旋转
3 u7 m" L+ p5 \; n3 G* A& r# ]6 FRounding, 舍入# s8 R. I" c) e" P' w" l6 s" _
Row, 行& ~$ @- H1 O# ~
Row effects, 行效应
3 j# V8 a4 ]9 J4 K( E% e3 XRow factor, 行因素
7 D" H ?% o7 j# b. ARXC table, RXC表
# F1 Z/ ]8 |: g; z5 ?) S+ zSample, 样本
1 q0 O ?' n- [/ p+ `, PSample regression coefficient, 样本回归系数* S+ g( M7 k5 c
Sample size, 样本量
+ K; b5 g& x9 L8 uSample standard deviation, 样本标准差- e& T1 a4 i, @
Sampling error, 抽样误差: b8 D0 m) W4 u7 `8 f
SAS(Statistical analysis system ), SAS统计软件包- `4 n0 A& S' W
Scale, 尺度/量表
1 q3 s/ c% x2 q+ j# G7 ?Scatter diagram, 散点图
4 r1 ]2 p9 }! i" U9 U7 I& H; ZSchematic plot, 示意图/简图( t5 {& I0 L i
Score test, 计分检验
. V) g0 S+ @8 l/ F/ b, E/ o3 p5 yScreening, 筛检
j% L/ l# o% N( L& R0 T" RSEASON, 季节分析
$ n) l) u4 o5 B4 o* ]4 P" `7 b rSecond derivative, 二阶导数2 Q; G: {/ s/ [3 @0 j
Second principal component, 第二主成分
' E2 R, m% e+ mSEM (Structural equation modeling), 结构化方程模型 0 W I5 y) T# Y' \" U, n$ }
Semi-logarithmic graph, 半对数图- w3 k2 }2 f/ `: C# n* P
Semi-logarithmic paper, 半对数格纸: x) k1 U" H$ l' f5 |5 h
Sensitivity curve, 敏感度曲线
+ l( e' ~# q# u/ v* I, U$ C+ hSequential analysis, 贯序分析2 W1 ]8 E0 J# f, g( E4 _. G
Sequential data set, 顺序数据集. v; T" R( J9 T# U6 y8 j
Sequential design, 贯序设计
% v6 `) {& M/ {# x0 {$ i1 pSequential method, 贯序法5 M( s; |& }1 a" z2 J
Sequential test, 贯序检验法
2 k. f! a5 a( ~! ^5 v7 FSerial tests, 系列试验
- {0 m- }1 d( Z8 B* N) v0 [+ n% IShort-cut method, 简捷法
1 }& a& _! G. g' i) F; ESigmoid curve, S形曲线
5 g8 g* f' ^! O! L5 R! V; p( o$ BSign function, 正负号函数
2 C- Z9 x: O) |1 d& n! ~7 kSign test, 符号检验& P6 A1 E2 A/ d5 l/ S! X4 ]
Signed rank, 符号秩8 f+ O2 r/ w/ o% @+ q1 [2 _
Significance test, 显著性检验( n- m. C& M5 a4 x& q5 F# e9 O% F9 U
Significant figure, 有效数字
6 f+ ^1 S+ b. i; q/ DSimple cluster sampling, 简单整群抽样' B7 f' b9 D1 ]/ N" {) j) `, v4 s
Simple correlation, 简单相关9 J& i+ b6 O9 q) \% a) a
Simple random sampling, 简单随机抽样# Y# a, m. I4 p; C
Simple regression, 简单回归' G- T6 y7 z2 Z- _' [3 q7 X I/ E1 O
simple table, 简单表
$ W, W. ?4 d3 l8 y& U& h5 W% cSine estimator, 正弦估计量
: ^8 ?1 [$ ^$ ?& @; F+ z! a, XSingle-valued estimate, 单值估计
) I7 ?* l$ G6 M- {- p& N, tSingular matrix, 奇异矩阵
0 ~% g* _9 T7 L/ T& ]6 g& E7 qSkewed distribution, 偏斜分布; M) j& M- o) \: b
Skewness, 偏度
% Q7 e# j3 j1 r4 q& y: t( KSlash distribution, 斜线分布
6 |& \4 j2 b* i$ p r' X; bSlope, 斜率
; v& ?$ i- P9 w% a9 c6 O0 F0 G# l9 ~Smirnov test, 斯米尔诺夫检验# _/ a& e0 X0 l, p0 |$ _" B& k
Source of variation, 变异来源% E: v5 ~& ^0 j
Spearman rank correlation, 斯皮尔曼等级相关 K8 N% O6 b; f
Specific factor, 特殊因子/ L# t) ]. {" a" A
Specific factor variance, 特殊因子方差$ N- l, a6 W; z" [
Spectra , 频谱
4 B$ W/ L( R1 {: U0 r% BSpherical distribution, 球型正态分布1 W* o( [7 @+ i0 h9 F* ~# u8 z3 g
Spread, 展布0 |$ h. t3 z- W4 ~: y% |: t
SPSS(Statistical package for the social science), SPSS统计软件包0 M, a( F/ N3 K8 [1 q
Spurious correlation, 假性相关
- Y1 x0 T6 D) ~6 k/ v9 q& PSquare root transformation, 平方根变换
0 v! G) s7 T& _$ W- Y! YStabilizing variance, 稳定方差
: ^$ W5 f6 |/ K7 m% f0 ]Standard deviation, 标准差2 o, \# y4 z8 w( z1 `! G% E& d
Standard error, 标准误
+ d! M) Y7 c: q# q w1 tStandard error of difference, 差别的标准误 o: N& q$ Q2 f
Standard error of estimate, 标准估计误差2 z$ d. J$ Z6 X( m& `
Standard error of rate, 率的标准误0 Y) j2 ]! n, D4 }; ~" ^) w
Standard normal distribution, 标准正态分布
" f9 ]. l& b6 e, ^2 G, h# dStandardization, 标准化
6 X; ~/ o6 v9 Z$ U. \Starting value, 起始值/ f1 T9 Q0 g8 |& f8 Z
Statistic, 统计量
/ Z1 E: B5 {' Z( A2 I8 A, s3 d" fStatistical control, 统计控制
- ^0 j, F( y8 s3 C0 LStatistical graph, 统计图' r) S$ j& ~- g; \. [6 W
Statistical inference, 统计推断
6 d' |6 M9 } [; ?4 s8 V4 xStatistical table, 统计表- B4 K/ J# @- K1 C/ A
Steepest descent, 最速下降法
; V" M7 c: i6 i; z3 L( s6 c& mStem and leaf display, 茎叶图
) E- I8 O) |1 @5 h$ V* s" Q9 EStep factor, 步长因子& X$ N6 h0 F/ l, R4 o8 i; t
Stepwise regression, 逐步回归7 t, ^1 t+ c' B+ s1 P2 n
Storage, 存
" o: q! H3 W0 [ b: B: HStrata, 层（复数）+ i- @- J; o$ l: \
Stratified sampling, 分层抽样
) T$ h& r5 U; c6 ?+ Y. nStratified sampling, 分层抽样
- D' p% v h8 t6 d/ GStrength, 强度) D, \* P# h' v I# U( v
Stringency, 严密性
' z. J! |: H5 `3 n1 [4 FStructural relationship, 结构关系
. E% |1 R# m( Q# Z. S9 IStudentized residual, 学生化残差/t化残差
; }$ B6 P$ n# O! j2 w$ }" QSub-class numbers, 次级组含量4 G, Q1 \8 Q8 A2 j7 F! ]4 \% o5 @
Subdividing, 分割& t, v ?- x/ X4 F
Sufficient statistic, 充分统计量
+ [" B6 t; s& U* SSum of products, 积和7 Z n- Z1 P# E7 E
Sum of squares, 离差平方和+ M4 |3 ^& ]" w: h% Q }+ u7 d
Sum of squares about regression, 回归平方和
4 c# r. Q! M7 KSum of squares between groups, 组间平方和
( e; v7 g7 y# @. R9 iSum of squares of partial regression, 偏回归平方和
* S" N9 |. V5 ]% \- \Sure event, 必然事件, z* j) o8 ]8 r2 T: ]! D0 e
Survey, 调查' s% b* `$ _ n8 v% ^
Survival, 生存分析# m! t& }5 q3 x( e: }- K+ L+ ~
Survival rate, 生存率
# Z _+ d8 r; rSuspended root gram, 悬吊根图 ^" V6 W# ~- Y# n3 X
Symmetry, 对称
- {. e. f1 H+ k; xSystematic error, 系统误差
4 i; g$ R& x4 h% b7 t. G1 _' VSystematic sampling, 系统抽样) t# T1 r3 ]" ?. v
Tags, 标签
( q4 P" m' x/ UTail area, 尾部面积6 L2 ?2 O: f9 T( L
Tail length, 尾长$ ?- z3 e- S5 E! X" \- e
Tail weight, 尾重
# L: G. Q9 k" \9 t' lTangent line, 切线
3 _; C+ \7 Z) tTarget distribution, 目标分布
0 k8 K; ~8 `; CTaylor series, 泰勒级数4 ^) _/ S% F) P9 }& Q0 i# s0 U
Tendency of dispersion, 离散趋势
& y2 ]& ^- N* {4 V* BTesting of hypotheses, 假设检验
! g& F3 Z( q( p7 G |7 E1 @Theoretical frequency, 理论频数
, i3 S; |' B Y3 ETime series, 时间序列3 k4 F% j# b9 i7 F7 b
Tolerance interval, 容忍区间; H0 Y: m, i% a2 C. j: g
Tolerance lower limit, 容忍下限
( a5 A4 Z- G( U8 n0 Q6 V' C6 NTolerance upper limit, 容忍上限: [ i( T, J+ {3 u3 @9 d, u) h
Torsion, 扰率
: h; g* t! b0 q1 X+ ZTotal sum of square, 总平方和
& A+ S, X! v/ X1 cTotal variation, 总变异
3 A9 H& G7 K3 gTransformation, 转换8 j3 W; q4 Z5 R' s4 k
Treatment, 处理# S" ]! A+ s) V# b* N
Trend, 趋势4 S* y3 f. u! x
Trend of percentage, 百分比趋势
5 e; W/ N- g- ]7 P* mTrial, 试验" q" c0 I* G* V* O
Trial and error method, 试错法$ T' S M% O& p2 W9 \
Tuning constant, 细调常数
. R: o6 y. @% T& }6 g- Y( D$ J& S5 b+ mTwo sided test, 双向检验
$ |! w$ B v6 b' |0 d: DTwo-stage least squares, 二阶最小平方- H/ p9 N4 I6 i& @! f
Two-stage sampling, 二阶段抽样
4 H* P/ Z# V) R4 _' \% G% ]Two-tailed test, 双侧检验
8 ]0 y# L: x- T) {% mTwo-way analysis of variance, 双因素方差分析0 y8 J, R2 K- I
Two-way table, 双向表
" D8 {1 G/ y2 d* l% t3 p' @- }Type I error, 一类错误/α错误+ s, ?! G9 E, ~. Y4 l
Type II error, 二类错误/β错误& o8 v' D2 V! R9 r+ C. ?
UMVU, 方差一致最小无偏估计简称9 Z5 ^: X# R$ k1 o9 s; N% ]
Unbiased estimate, 无偏估计9 }- Q" K% ]/ ~
Unconstrained nonlinear regression , 无约束非线性回归6 m5 a0 J2 ]. f' ?
Unequal subclass number, 不等次级组含量
- Z, i2 Y) ^$ w9 _( LUngrouped data, 不分组资料) Y$ w; [' p' m# B% n' \* g
Uniform coordinate, 均匀坐标% Y; j% V. B$ y; ~9 S% I
Uniform distribution, 均匀分布
; V1 _8 z6 f6 ^0 L( K4 FUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
& H7 _7 Z. b- R4 A9 Z: h0 K4 L& aUnit, 单元
+ s" f$ p& _# g# |: C& M# O& t, mUnordered categories, 无序分类, i% s1 W' M- J9 e$ b8 Q3 Y
Upper limit, 上限' z% n ?2 o' y% L0 p
Upward rank, 升秩% N' Q! B( J0 |$ r
Vague concept, 模糊概念
; u9 T8 I# j, c% l. [" i5 vValidity, 有效性
: w. T2 O Q4 n7 V+ ^, [. oVARCOMP (Variance component estimation), 方差元素估计
* f9 T$ Q' K. n, q# A& MVariability, 变异性
# P0 b* i" _% t& }, ?Variable, 变量: S: K& I, d4 X- |# _6 u
Variance, 方差
/ B. }) ?2 }/ Z9 q7 p! V; ~. k- ZVariation, 变异
/ v& }" L2 T! DVarimax orthogonal rotation, 方差最大正交旋转) @7 x; b5 Y" J( U6 u
Volume of distribution, 容积# a$ U, z0 D1 b& a" t' O7 ^) k$ t4 E
W test, W检验
4 q1 q9 r( b. O' Y) G+ E/ HWeibull distribution, 威布尔分布
E9 v$ d2 o& Z# w: [5 rWeight, 权数
8 K2 x6 U/ ]! [& V/ RWeighted Chi-square test, 加权卡方检验/Cochran检验' b# y' \3 n$ _! W; Z* R. R4 a
Weighted linear regression method, 加权直线回归: V8 ^, k. U9 K% H7 A1 T: x
Weighted mean, 加权平均数, @+ {% K! O$ `( _ _ n: f) g
Weighted mean square, 加权平均方差6 z& F% o$ T0 {& {; y4 P+ g0 d- [
Weighted sum of square, 加权平方和5 c& b! N0 a+ O; S
Weighting coefficient, 权重系数4 B) N' a( v3 m) V8 E X
Weighting method, 加权法 ; {; [; \0 J9 Y) R8 d) l) D, C; Y
W-estimation, W估计量
/ I; O& e5 {$ d9 F. ~# V1 FW-estimation of location, 位置W估计量
+ j1 u6 j# I2 A/ t+ j$ p- x. fWidth, 宽度 k3 S* l3 {/ ~2 ?
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
) S6 E$ u4 B+ ?+ cWild point, 野点/狂点
) T1 U+ b4 N! f0 C6 Y/ WWild value, 野值/狂值
/ G$ d' e" j# j0 _Winsorized mean, 缩尾均值
v+ `" _ J, wWithdraw, 失访
7 w1 E W5 S7 ?! V$ { U. M6 ~Youden's index, 尤登指数 r: a( f3 t* ^
Z test, Z检验( o9 I/ i' z* ^; ~& x2 I3 L
Zero correlation, 零相关8 `3 `, P$ Z( v2 c' M$ w) p
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
