|
|
Absolute deviation, 绝对离差
/ m$ w* `$ w4 E" |Absolute number, 绝对数
3 S5 x# a. L9 s0 `Absolute residuals, 绝对残差
) ]* u4 B5 }7 Z6 P6 EAcceleration array, 加速度立体阵
$ d& @: Z8 Y$ ?7 \3 {: ]% L/ J; }7 |! f+ [Acceleration in an arbitrary direction, 任意方向上的加速度5 c4 Z$ z, a$ Z# ?' F
Acceleration normal, 法向加速度' J3 P) ?. f7 l
Acceleration space dimension, 加速度空间的维数
" u0 W5 N% x7 L* w8 [, n/ WAcceleration tangential, 切向加速度6 P5 C3 _, A9 q+ e) _ p5 S1 |
Acceleration vector, 加速度向量' X) d- {7 G3 T. V& L& K
Acceptable hypothesis, 可接受假设9 [- Z4 l8 p5 C3 \5 d
Accumulation, 累积( S/ R5 B5 Q' R- G( a9 |' w2 o( c
Accuracy, 准确度
; U7 P" R7 h0 q7 r* K% z' U. E0 I" _Actual frequency, 实际频数
- i3 V% n" c b/ E; h' {Adaptive estimator, 自适应估计量& `% D; H# Y/ ~" ?. m% f
Addition, 相加, n5 B. v1 D: v+ a, j) i
Addition theorem, 加法定理
& w7 o/ X& ~8 ~! L% U( Y/ vAdditivity, 可加性
9 A' n7 A* k$ r9 hAdjusted rate, 调整率
! r9 L5 a3 x. g4 o5 i, U! P, W* fAdjusted value, 校正值
4 \0 n* |' t% zAdmissible error, 容许误差
9 a' m0 d4 g0 u d6 v' LAggregation, 聚集性6 |6 ?8 R- l8 n2 ~# s- L
Alternative hypothesis, 备择假设
& J- b9 x2 D( d8 _* X# f3 LAmong groups, 组间
7 T! I- b- ?* @Amounts, 总量7 @5 }7 q2 j9 r; {. U7 L( A
Analysis of correlation, 相关分析
$ G! L3 `% e: C% ~9 `) PAnalysis of covariance, 协方差分析
7 x5 a8 B4 Y2 T \9 z, \Analysis of regression, 回归分析
$ _# N1 d% m' ~0 LAnalysis of time series, 时间序列分析( k6 h0 B1 @0 z! l/ A5 p$ V' n
Analysis of variance, 方差分析
; D7 a; E) j) bAngular transformation, 角转换8 y; |- i2 n; X* d
ANOVA （analysis of variance）, 方差分析
! u' k8 n$ @0 KANOVA Models, 方差分析模型7 w6 }0 Y$ m u# t* \ E& `
Arcing, 弧/弧旋
( S! `; D. {# bArcsine transformation, 反正弦变换$ h+ L$ r# g$ Y! Q
Area under the curve, 曲线面积! F3 T) S4 a- G% t' P
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
9 C+ I: O @& U! mARIMA, 季节和非季节性单变量模型的极大似然估计 5 d8 ^8 C6 y2 B. b, f' I( e
Arithmetic grid paper, 算术格纸( S* T) K8 t! F" k. @
Arithmetic mean, 算术平均数$ z% _4 x( E# y
Arrhenius relation, 艾恩尼斯关系) ^! k c' l5 Q; O, }$ v5 F
Assessing fit, 拟合的评估0 j, M' U- ^* L0 O V
Associative laws, 结合律
% E4 D U- c! ?5 n8 hAsymmetric distribution, 非对称分布7 o; Y) P L, `' Z
Asymptotic bias, 渐近偏倚
# P* O2 t$ {+ [ i* Y0 g" O2 jAsymptotic efficiency, 渐近效率
! B$ _ P- b1 b2 x+ Q8 @Asymptotic variance, 渐近方差; Q3 F$ x0 e8 G/ }
Attributable risk, 归因危险度
/ r' h) f' A) ~& X% j" W2 JAttribute data, 属性资料
; `/ I8 |* T! f7 DAttribution, 属性" T; Z. L) u2 c) i
Autocorrelation, 自相关
6 O. p0 H/ m3 L( w- o gAutocorrelation of residuals, 残差的自相关
7 i3 Q2 o. P. k# q r* ^$ B$ F# B1 kAverage, 平均数2 L5 |3 \& d6 D) A% m* F& G
Average confidence interval length, 平均置信区间长度) [. ^* k, y8 J: `
Average growth rate, 平均增长率, d2 ^$ ?& d' S& t' }" o% ?) y
Bar chart, 条形图4 x! l4 j% F' u
Bar graph, 条形图/ S) w" i) q F' p4 v
Base period, 基期
+ A; N- M% e- y& T2 {Bayes' theorem , Bayes定理5 ]0 w- ?: @7 T: `5 k2 e! \! d* r
Bell-shaped curve, 钟形曲线
* [/ O2 l4 Y. p4 C1 x9 Z& yBernoulli distribution, 伯努力分布, }8 {/ z( a* E$ z: J1 H' r$ B- P
Best-trim estimator, 最好切尾估计量' L0 q" J1 c+ _( F
Bias, 偏性9 y" A) H1 ~* f! \( K9 a7 [# \8 y! V. e
Binary logistic regression, 二元逻辑斯蒂回归. N, k' _9 [3 |7 P
Binomial distribution, 二项分布9 s: E' f8 F9 ^( ?9 E
Bisquare, 双平方4 ^5 X* b7 R6 l8 d( s& y/ f! [8 }8 Q
Bivariate Correlate, 二变量相关
4 C0 z4 _0 X( q$ E Q$ Y4 n; v) t+ T# |Bivariate normal distribution, 双变量正态分布* n) o/ f/ t3 o. \) p2 Z9 s
Bivariate normal population, 双变量正态总体& }8 Q4 l- [1 j6 C+ ~
Biweight interval, 双权区间
- D$ M: J* }, M8 u( eBiweight M-estimator, 双权M估计量
$ v- P' C* M. W8 `) j' g' tBlock, 区组/配伍组# I- J! C/ l' Q, ^2 Y& i; H6 p
BMDP(Biomedical computer programs), BMDP统计软件包
U y! ]5 E& g9 w9 h1 `Boxplots, 箱线图/箱尾图
% L/ U% ?. C. Q( S! Y( XBreakdown bound, 崩溃界/崩溃点: D5 B: M0 k8 W/ i; h# q: r1 Z
Canonical correlation, 典型相关8 [3 X& q# X* X. f S
Caption, 纵标目- G, A# i3 f' T" T" |' Y5 X' B
Case-control study, 病例对照研究- h& I" [* y7 E, v) t7 A9 {/ V
Categorical variable, 分类变量
( b) t) d) W9 t& MCatenary, 悬链线
* I! i& l) U2 u5 fCauchy distribution, 柯西分布( k6 y( Z* }& n$ e3 k9 b( c
Cause-and-effect relationship, 因果关系
$ X2 E3 ]1 j1 RCell, 单元
" U {: Y- D/ _/ l# O' P3 ~Censoring, 终检
' w( w: L/ t- @, l3 jCenter of symmetry, 对称中心
; `3 C6 I0 y* J- O, Z' c; RCentering and scaling, 中心化和定标
; y) [7 y e x9 {Central tendency, 集中趋势
! L- d' P9 s+ l- mCentral value, 中心值8 B! S/ g# {! i' ^: F) k
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测! J% W0 ~% V x/ _# G+ r
Chance, 机遇
M. U$ V( T- h7 {! k' Q, e9 MChance error, 随机误差
8 U/ s! \/ G, ]" rChance variable, 随机变量
2 m8 K6 l& g3 i0 jCharacteristic equation, 特征方程* }; d* D' D7 {8 T# w
Characteristic root, 特征根
& h9 ^2 b3 i- J$ D/ vCharacteristic vector, 特征向量
( D8 K5 A+ j. V9 `) a0 t0 eChebshev criterion of fit, 拟合的切比雪夫准则1 P. _5 w8 }! Z0 v) o9 f
Chernoff faces, 切尔诺夫脸谱图# O$ _# R! Z2 @/ `) o8 B
Chi-square test, 卡方检验/χ2检验
" {0 s- X( U7 E6 kCholeskey decomposition, 乔洛斯基分解
B/ R5 j# n. `Circle chart, 圆图
8 U$ K1 X }5 u/ CClass interval, 组距+ u! R: @# m+ G& m9 l
Class mid-value, 组中值5 _) s8 i+ o0 G
Class upper limit, 组上限
' {6 r% [# `; z5 RClassified variable, 分类变量
" T* D" s7 _* a! iCluster analysis, 聚类分析
- N% z0 S* W/ l* b, G1 F& @Cluster sampling, 整群抽样7 P: y% n0 b9 B! B% y
Code, 代码 K, e0 J, Z" [! m* I2 c
Coded data, 编码数据
0 Z3 n+ c* Q: p' d+ ]1 W0 r) D2 jCoding, 编码7 s1 ~8 x" A* @) i( V6 T
Coefficient of contingency, 列联系数$ e/ W$ W5 |! G, d0 \4 y R% i
Coefficient of determination, 决定系数
0 u# z% B! _: iCoefficient of multiple correlation, 多重相关系数
: g# ~- y2 e7 i( PCoefficient of partial correlation, 偏相关系数! F7 U# @$ _3 N" Y; R% f: T3 d
Coefficient of production-moment correlation, 积差相关系数( C8 w! F" G9 `1 A2 j) p7 O- z i
Coefficient of rank correlation, 等级相关系数7 S F) _" M8 D' r! H+ Q6 f
Coefficient of regression, 回归系数
. f3 M, G0 v/ M) u8 i% GCoefficient of skewness, 偏度系数
. {1 X; W- V3 o4 F% c/ G3 C* YCoefficient of variation, 变异系数2 \# _$ d* O: D
Cohort study, 队列研究3 C B: ^$ ?' ?
Column, 列
; l3 V& Y) y+ ^ c( }* pColumn effect, 列效应
9 ~) v6 j- A9 g, t, b# E% YColumn factor, 列因素) C# J3 J0 S- b! t: s* Z7 t
Combination pool, 合并7 f4 z X7 A- q
Combinative table, 组合表
7 Q& n9 n/ P/ j; X- b$ lCommon factor, 共性因子- ]! n( c, j* Q( }
Common regression coefficient, 公共回归系数
/ [& F9 D! h. O6 ` KCommon value, 共同值
7 {' e2 c, ?! F% d$ C+ oCommon variance, 公共方差2 {4 K1 @! W. X5 K( v& e* k
Common variation, 公共变异
; c3 \$ G8 `9 o# ^Communality variance, 共性方差/ _* n0 S; u+ L/ \. F3 W3 @
Comparability, 可比性
+ M! }( f" O0 yComparison of bathes, 批比较
! p& x0 ^) e& u6 K" S: o) b9 X* MComparison value, 比较值
/ O, f. L6 @4 zCompartment model, 分部模型) X2 B+ A( e$ k6 ^- k
Compassion, 伸缩
% f& H6 e; X3 r# g) U( l ]- yComplement of an event, 补事件
6 C1 G' Z3 b- B6 B) h" {; yComplete association, 完全正相关
/ ^/ p. m. Y. H- IComplete dissociation, 完全不相关3 G' k8 O8 f3 ?0 k; [
Complete statistics, 完备统计量$ _/ B- f6 ?2 I* U
Completely randomized design, 完全随机化设计
9 z! V8 m+ J$ ~Composite event, 联合事件8 \ p d% Z- l* Z9 [* R
Composite events, 复合事件1 E; l/ P% n; W$ @0 e
Concavity, 凹性
) [5 c) \+ F, V! m. e0 o" \Conditional expectation, 条件期望
! Q/ ~! i/ z! w4 H' q1 JConditional likelihood, 条件似然
+ F4 k) k( d/ f; g8 @2 Z. t1 ?7 }Conditional probability, 条件概率
. s' f2 P; G( k1 O& d( U7 e FConditionally linear, 依条件线性
/ h8 _8 S* O# a% k3 Y. i' DConfidence interval, 置信区间
]0 ?* n k$ }: j# @% FConfidence limit, 置信限 Y( e7 ^5 F6 B& c4 ^
Confidence lower limit, 置信下限3 V" D' w& \. A
Confidence upper limit, 置信上限8 c, U2 \- b6 ?
Confirmatory Factor Analysis , 验证性因子分析; l, h3 g$ m* @; Z$ A. \$ J2 s6 K
Confirmatory research, 证实性实验研究% H% `) B$ p% n) c1 S' x
Confounding factor, 混杂因素5 t {' k6 b$ v9 L/ P
Conjoint, 联合分析
8 g+ \; Z5 k8 y' W$ v* U: S3 g" `Consistency, 相合性
+ j/ Z7 N, q: B7 l; G4 ~Consistency check, 一致性检验' ?* p7 M3 U& T. ?" W
Consistent asymptotically normal estimate, 相合渐近正态估计7 i1 C/ b& G% ]3 q* l
Consistent estimate, 相合估计
1 w3 B6 c# _7 d: W% eConstrained nonlinear regression, 受约束非线性回归
5 K5 C; g" W0 F+ g. P5 a3 O5 {, _Constraint, 约束
& h/ q- R% r0 ~! z" @Contaminated distribution, 污染分布
& y: u( ^7 x1 DContaminated Gausssian, 污染高斯分布
$ h% `' @- ^0 F" [4 l6 I, _" G; m+ ZContaminated normal distribution, 污染正态分布1 K8 f* i' X1 K
Contamination, 污染; R' k+ D+ J1 E" q. G# L+ R5 H. e/ m
Contamination model, 污染模型) G5 `7 r9 x8 j' P [7 u
Contingency table, 列联表
9 X- S! h. X- ~( Q6 O( hContour, 边界线 N# \% F, g) q
Contribution rate, 贡献率$ f5 F) E8 \+ n: y0 j
Control, 对照
# D$ _+ T# E- jControlled experiments, 对照实验, I% L! w; |$ ^ M2 r( P
Conventional depth, 常规深度
8 _2 c5 {4 a% ?6 t. rConvolution, 卷积
9 D1 T6 Q5 I; g- L5 B& H: |' c/ L* Y: SCorrected factor, 校正因子; z) _( E6 [7 @/ P) `) g6 v; ]
Corrected mean, 校正均值' |, O4 C' N0 \/ T t. { L
Correction coefficient, 校正系数
% _ h- G4 J8 E2 A# Z: gCorrectness, 正确性8 }2 _6 I$ j* H7 m7 b2 Z6 @1 r+ j
Correlation coefficient, 相关系数
& }7 J' [; m4 W; b2 N, u9 SCorrelation index, 相关指数# L1 [. ^: c) d( y: s, b
Correspondence, 对应
7 f! k$ M6 Y/ ]4 KCounting, 计数
2 n6 [3 z. K# u3 d! GCounts, 计数/频数: j6 f/ u# Q; c
Covariance, 协方差
: i+ O* Z% @- ECovariant, 共变
. S( p l* s ?1 t& z6 MCox Regression, Cox回归
' g6 }$ B9 m2 T: |! e9 Y% }+ O- N* VCriteria for fitting, 拟合准则
) {# l1 K2 q* {" l$ @. PCriteria of least squares, 最小二乘准则& o I4 V; M, ?, }
Critical ratio, 临界比
" a1 g# u& f* K$ H2 G7 dCritical region, 拒绝域) B; l7 V% V2 v, u$ U- O
Critical value, 临界值
5 F% k0 q+ B, n& E x& B( CCross-over design, 交叉设计4 i2 V3 X+ {! T5 v
Cross-section analysis, 横断面分析
% C7 P. W( v! [1 zCross-section survey, 横断面调查
' }, x0 A Y ^6 d$ {0 E1 L5 \8 vCrosstabs , 交叉表 4 W0 v8 X. H+ M9 A( j: Z
Cross-tabulation table, 复合表9 S' C) w3 {& C
Cube root, 立方根
! Q1 _4 O$ x& T6 C1 BCumulative distribution function, 分布函数
+ W) [ S5 K2 ]# j, n# {Cumulative probability, 累计概率( L$ X, Y& ^+ O
Curvature, 曲率/弯曲
7 b7 v4 I1 @7 c+ W) wCurvature, 曲率
" O$ f7 w _( _9 S( ] SCurve fit , 曲线拟和 ) v, q0 n2 f* V$ N! ~
Curve fitting, 曲线拟合
' h0 N) T! e+ c0 \0 ~) ~Curvilinear regression, 曲线回归, U1 V; ^, t( r* E6 |
Curvilinear relation, 曲线关系
8 K% I4 o: ?( G7 BCut-and-try method, 尝试法- n# g R0 g! E) g2 a+ o
Cycle, 周期* ?" g- k" u+ i1 k1 m# S4 F. m0 j0 v( y
Cyclist, 周期性" `1 }' _! E7 [5 g
D test, D检验
# L! l1 A I0 l* vData acquisition, 资料收集/ ?- C$ l" X/ U/ T1 E. D9 J
Data bank, 数据库% [0 S/ k! m* N+ D k- L1 m
Data capacity, 数据容量/ `# L; b! e3 e; {6 M
Data deficiencies, 数据缺乏
* p6 F% U& U/ r0 s9 {9 b( wData handling, 数据处理
9 {! I# e0 @# C' UData manipulation, 数据处理1 X/ a* t: ~6 ^+ i
Data processing, 数据处理
/ |2 y2 @" ^+ D' {, u+ n# s* ?Data reduction, 数据缩减7 j* e+ r7 w4 k" \; ^' A0 t, ?$ h% A
Data set, 数据集% T- X# | c* ?2 h: J. I
Data sources, 数据来源* i9 c( y# b/ e6 f" X, h
Data transformation, 数据变换- f! s4 f: I5 P8 f% J/ q
Data validity, 数据有效性) [+ S# x$ m& h4 J9 ?' {; ~
Data-in, 数据输入
7 ~: _: ~+ S o3 c: i7 ZData-out, 数据输出2 k2 U! U" b$ k# c
Dead time, 停滞期# l1 N( W- R5 _( H' y9 u D0 N4 J1 j
Degree of freedom, 自由度! _9 @$ ?* I: B# M
Degree of precision, 精密度
6 @( R7 m" C4 p, K9 ~( ^, v- [Degree of reliability, 可靠性程度0 Z" j* m: ]( W9 f k- \
Degression, 递减
0 L* ` T% {4 ~" r' TDensity function, 密度函数
7 p6 q0 h9 k" S& b+ eDensity of data points, 数据点的密度+ N# Y0 Q* F2 u M2 [! I
Dependent variable, 应变量/依变量/因变量3 Z" _1 A. }, I7 r5 _5 Y! q; H1 @
Dependent variable, 因变量0 _* X9 D5 u8 A, f4 p
Depth, 深度9 n4 n# j; m: g _
Derivative matrix, 导数矩阵
# z h+ W( M+ C; A6 x: JDerivative-free methods, 无导数方法 j0 x0 u9 u" u8 f& G" x: T+ h
Design, 设计6 L X8 f. d0 V
Determinacy, 确定性
7 D8 t/ k# r$ t% ?. mDeterminant, 行列式' z; U4 T( `# E+ [& U, p# a1 z m
Determinant, 决定因素/ I: V& Q6 c6 j5 {) P
Deviation, 离差
, ?3 h7 v; @0 K0 q8 uDeviation from average, 离均差 F) `7 t9 `2 D
Diagnostic plot, 诊断图% h1 I9 l. L6 o8 u
Dichotomous variable, 二分变量5 p. I* y# Z! n, C& G& A
Differential equation, 微分方程* S# y* d/ l5 F8 I& x) u6 \$ L
Direct standardization, 直接标准化法
% }2 Y( Q% [* a lDiscrete variable, 离散型变量
+ u( t; m# @* _! [' oDISCRIMINANT, 判断 2 m, U* s# }5 P3 }5 P
Discriminant analysis, 判别分析
9 Y) j @0 v+ w. K, y1 H5 @Discriminant coefficient, 判别系数
6 U+ v. J: M+ T2 wDiscriminant function, 判别值
6 a4 t7 \( g& g t7 G% ZDispersion, 散布/分散度( b- U& I8 [8 f. \: r; Q3 }
Disproportional, 不成比例的
& H) p9 R- v- T4 ADisproportionate sub-class numbers, 不成比例次级组含量! b! }" j# \4 Y8 g2 [
Distribution free, 分布无关性/免分布0 _5 w' K1 M. [6 w. i
Distribution shape, 分布形状1 v8 T" E3 G# T# Y9 t6 z
Distribution-free method, 任意分布法# G c+ @) d1 q( i, L j* J! i
Distributive laws, 分配律/ c. j$ j) d& v) R; A) ^( q
Disturbance, 随机扰动项
& Y* t5 O2 m) }8 I! [* Q) L6 Q/ p/ T0 HDose response curve, 剂量反应曲线
( W+ s0 |( ~/ yDouble blind method, 双盲法
+ k/ t) W/ G: Z, G! }/ fDouble blind trial, 双盲试验; c; W$ C. T8 ?- A4 @ I
Double exponential distribution, 双指数分布8 w/ r% u1 N/ n
Double logarithmic, 双对数
9 D2 M. ~; C8 [$ S1 W% rDownward rank, 降秩
Q$ c2 g/ Y- B, [9 O v' m) W. nDual-space plot, 对偶空间图( @! X' x3 Y) |2 f& _: F V
DUD, 无导数方法; A% q( l$ v* T# ?& u5 I
Duncan's new multiple range method, 新复极差法/Duncan新法
( K) [+ _! I% d& j$ yEffect, 实验效应
( l* m! \, \3 {, qEigenvalue, 特征值/ b# L+ s0 F/ N+ N
Eigenvector, 特征向量1 H5 \9 v: k6 g' }
Ellipse, 椭圆5 k( G: e+ N2 L# x n+ D0 g; p
Empirical distribution, 经验分布0 Z) _; Q- ~$ F9 s
Empirical probability, 经验概率单位
. I3 {, u' S1 z5 {Enumeration data, 计数资料
/ u& V% u% X: x8 O: |5 IEqual sun-class number, 相等次级组含量
4 V) z8 x, K8 t8 o2 S. r! lEqually likely, 等可能9 q( S( c4 F. D' c7 E2 ~
Equivariance, 同变性
7 b( h$ E, m) a: Y7 d0 |* C5 F1 B, [Error, 误差/错误
' m* U5 L- X) l2 a; iError of estimate, 估计误差* O: _- m) L* C* |, H+ G
Error type I, 第一类错误( P6 D0 U; F3 k% `6 @; \1 z0 C
Error type II, 第二类错误4 ^1 o* K( j5 M7 ?4 w, o5 |4 E
Estimand, 被估量
5 e- u8 ?: a8 G; \( SEstimated error mean squares, 估计误差均方
; O' p; C8 @' A2 @7 IEstimated error sum of squares, 估计误差平方和9 }$ {+ V* y. N
Euclidean distance, 欧式距离
. C4 g9 c- A4 W( V0 m& r" c( s+ E* ~Event, 事件) n7 _, X' ?9 K0 n/ U7 i1 _6 Y. {
Event, 事件! ~- F3 x0 F A2 _5 q4 V. b6 ~
Exceptional data point, 异常数据点
7 r7 a/ c% ^& R( @. i/ c" }Expectation plane, 期望平面1 k$ {1 A% R, X, s
Expectation surface, 期望曲面+ S4 P. \ q: U! [" `
Expected values, 期望值
: w! V- Z! n0 H: d9 U6 p8 ^Experiment, 实验
# E" c+ P0 {8 NExperimental sampling, 试验抽样6 f- a% x4 o* @
Experimental unit, 试验单位
4 l* Z% d0 {9 RExplanatory variable, 说明变量
0 w- u( Y1 O1 U1 ~# ]Exploratory data analysis, 探索性数据分析
6 W# `: j" r7 m" yExplore Summarize, 探索-摘要
) z* s: D& T& G) V, {, B' b1 ]Exponential curve, 指数曲线* S# H7 Z# a# p& u# Z
Exponential growth, 指数式增长
6 G& }* q6 u1 P+ d# _/ cEXSMOOTH, 指数平滑方法 6 } q% S, e5 }7 r
Extended fit, 扩充拟合
6 @& F. F5 q) K- I4 XExtra parameter, 附加参数6 W! d2 h( U' X, k
Extrapolation, 外推法+ g, a$ ^* J7 u8 G0 x x0 l, x. s, Z' J
Extreme observation, 末端观测值
; W% x$ F$ m9 w6 o: ^Extremes, 极端值/极值
, k8 R$ b2 A( _5 B& n1 HF distribution, F分布
4 i& ^( G* ?9 VF test, F检验
6 ~0 j e; z, S- HFactor, 因素/因子
$ |: C% W5 r6 f" g( ^% m( W2 `Factor analysis, 因子分析
4 }, V0 v( g% h, z- e6 lFactor Analysis, 因子分析
' Z, D# ]5 f) v- pFactor score, 因子得分
( @6 w+ q( x, w* E' WFactorial, 阶乘
" K9 R% X& f% C: g$ n; wFactorial design, 析因试验设计: B, r! B' ]) t9 d- E3 i! C1 A, }- ~
False negative, 假阴性
7 q3 D/ ^: Y) J+ z, L- w' K. M3 fFalse negative error, 假阴性错误
- a- X0 S& @. j2 ^3 w% gFamily of distributions, 分布族
) U3 z- u3 c I: M$ Y2 cFamily of estimators, 估计量族+ ^) Z! I( O k1 V" Y) j
Fanning, 扇面2 ~- @5 _. P/ I5 C1 @ n
Fatality rate, 病死率
. \9 F, F* G% xField investigation, 现场调查
9 I8 _2 h7 Y" v# uField survey, 现场调查
8 \$ ~! o1 J5 y t9 zFinite population, 有限总体
3 m2 J8 |& B/ P# w6 a# i/ ?- ?: Y6 dFinite-sample, 有限样本
. j/ ?. @9 e6 a$ E& SFirst derivative, 一阶导数( z! B, Q$ s! U% p8 [6 c' x/ Q
First principal component, 第一主成分6 Q3 K2 o( b( ]0 T5 E
First quartile, 第一四分位数7 d9 ^0 `8 n, X0 o1 ]
Fisher information, 费雪信息量
2 s7 ]! Y+ c) Z% W5 f" r! [+ rFitted value, 拟合值: U7 I4 X9 W) Z% _
Fitting a curve, 曲线拟合
) A) ?: }/ X, N5 qFixed base, 定基
+ N/ V8 y5 \; F9 R% A! HFluctuation, 随机起伏/ @3 w% n2 M0 V, ]3 I9 E. O, Q
Forecast, 预测% n1 S, t4 |" p; T
Four fold table, 四格表- ]1 x T+ W1 t \4 ~+ ]3 |- z; g1 r
Fourth, 四分点5 W+ Y3 J. X r) V& W0 Z* N
Fraction blow, 左侧比率6 S' Y+ [4 k3 z+ @
Fractional error, 相对误差
; `* Q8 p! `: N; HFrequency, 频率( Z9 [8 O" `. l' [( \+ Y* s+ g
Frequency polygon, 频数多边图" p7 k7 p7 S# h# k) k2 v
Frontier point, 界限点
8 j& i4 I% F. F q# i6 @% RFunction relationship, 泛函关系
. K" _% U% d1 \0 G" FGamma distribution, 伽玛分布
2 o5 j( {& L4 hGauss increment, 高斯增量
' c+ Z9 E& z4 Y& c$ AGaussian distribution, 高斯分布/正态分布
: L5 M1 K0 E* YGauss-Newton increment, 高斯-牛顿增量
' k2 ^8 [* W+ Z0 B; W; zGeneral census, 全面普查4 d" `1 ]) P. n: L4 t' b
GENLOG (Generalized liner models), 广义线性模型
7 u% ~2 u# O" J7 g* Y) ~* aGeometric mean, 几何平均数! t; s& V% w6 u3 a% v& b7 E
Gini's mean difference, 基尼均差 L" S) l$ M" k* d. p
GLM (General liner models), 一般线性模型
[. M: O% p: X2 e: \4 NGoodness of fit, 拟和优度/配合度5 Y& ?+ s6 j* M7 C
Gradient of determinant, 行列式的梯度; N' u+ j8 }# Z3 E7 y
Graeco-Latin square, 希腊拉丁方/ T8 Q. g, I- n" v# i9 S5 p/ Q
Grand mean, 总均值2 v( M7 h0 Q) L' i6 [: X7 o
Gross errors, 重大错误0 Q, {) O0 w2 {+ t* |+ l
Gross-error sensitivity, 大错敏感度7 A' J; j( B! b/ w% k
Group averages, 分组平均
7 m0 h8 P9 ^3 Y6 @/ dGrouped data, 分组资料
9 c1 _ }* H( [3 Q" WGuessed mean, 假定平均数
0 i7 S( y" w4 U2 ?Half-life, 半衰期7 U2 o4 e) {6 D
Hampel M-estimators, 汉佩尔M估计量
/ X, K+ v0 F6 C/ ^: O K" R* rHappenstance, 偶然事件
9 Y4 D" x( ^ c# OHarmonic mean, 调和均数
# X& R7 M$ o. O4 P& V6 [6 |Hazard function, 风险均数
0 P+ A7 k9 z- O6 ]1 `4 E% ?9 p KHazard rate, 风险率
, o) [1 V1 C9 q& VHeading, 标目
) m2 M7 u1 W& P o D2 `Heavy-tailed distribution, 重尾分布3 @8 S5 {! |- U
Hessian array, 海森立体阵; D) P6 O6 h* L- ?* H
Heterogeneity, 不同质 P7 a; T2 } H9 d! |
Heterogeneity of variance, 方差不齐 & z% ]( v2 y6 A- l- i/ t
Hierarchical classification, 组内分组9 E0 J; E( z. Q D' c# T
Hierarchical clustering method, 系统聚类法- \0 ]+ U5 p6 a$ l. }3 w
High-leverage point, 高杠杆率点" e0 h/ @# N' u6 u+ b
HILOGLINEAR, 多维列联表的层次对数线性模型7 I' F9 g' q# t4 ?: H" S
Hinge, 折叶点/ `) p' B3 z+ z; _; E. e
Histogram, 直方图3 Z. O; M# U' E+ l
Historical cohort study, 历史性队列研究
# G2 D8 S* o: mHoles, 空洞
0 {- g! e% {3 VHOMALS, 多重响应分析! z& D& F! T! u- O
Homogeneity of variance, 方差齐性" [) [% z2 Z' w' t& U) d( q
Homogeneity test, 齐性检验6 _; G _. I. _- @1 j# F
Huber M-estimators, 休伯M估计量+ b; X1 n* |& ^ d3 G
Hyperbola, 双曲线* }0 ]* M% J1 u' e3 e
Hypothesis testing, 假设检验- J4 w @6 Y& f6 w8 Z* E
Hypothetical universe, 假设总体
* |0 o/ g+ ~# X5 d2 ?0 xImpossible event, 不可能事件
" L% O" K- ^! `% n) t/ gIndependence, 独立性, J! d/ u2 F8 d0 `# d9 g# p+ z
Independent variable, 自变量 b; J$ E9 M- x8 L
Index, 指标/指数' K/ C- }- |9 V# ? M1 f, s/ b
Indirect standardization, 间接标准化法
/ {$ `; K7 W+ m( JIndividual, 个体* m' r V# Y/ r) q0 E
Inference band, 推断带
1 d' l% U; W8 @1 q. eInfinite population, 无限总体; X5 O5 K7 v6 L' j9 D1 C9 n5 @, k6 N
Infinitely great, 无穷大/ b8 l! E. j( A% Y- M$ C" {2 h
Infinitely small, 无穷小) v. K4 s9 ]8 z0 w$ B5 @
Influence curve, 影响曲线/ r* v' x; K* l& @
Information capacity, 信息容量
5 r* E' N' _( C7 J. zInitial condition, 初始条件& h! a( `9 s# G3 n) m" E* r& ^
Initial estimate, 初始估计值
. P% z8 e Y( c0 sInitial level, 最初水平
4 Z+ n* j4 N' p' u" H( ]& vInteraction, 交互作用. e9 T. x0 a S* s8 \4 p* v/ X4 E1 G
Interaction terms, 交互作用项
0 L: p1 ?( p! P$ ]4 t. c# T/ G7 [$ TIntercept, 截距
; p- p- V: G" Q' Y; M' h- oInterpolation, 内插法
3 [/ [$ V) f6 M, ?& D+ ~% VInterquartile range, 四分位距9 U$ c& S9 u' j9 }$ z0 E4 i& s S& { K
Interval estimation, 区间估计2 `0 O" Q; P* Y8 U; c' e; v" J
Intervals of equal probability, 等概率区间
7 L8 I7 \( C! _7 Y8 N1 Z* dIntrinsic curvature, 固有曲率
1 h k/ g* n+ n3 BInvariance, 不变性
8 A3 [& y9 D: J' `% w+ ZInverse matrix, 逆矩阵$ i9 \& ]; ]7 q1 O, _2 ]$ l/ o, a7 `
Inverse probability, 逆概率
5 h. u' ^0 h5 W% v+ [$ V( bInverse sine transformation, 反正弦变换. s* _* t) E% |* a) Z9 J
Iteration, 迭代
* s9 J7 T( d, v0 |, sJacobian determinant, 雅可比行列式9 |. P; V2 \1 t( Q! F" x
Joint distribution function, 分布函数/ s. s+ O M% r! e6 C$ O
Joint probability, 联合概率* Y% c" |1 r9 {7 }2 m; u [
Joint probability distribution, 联合概率分布
# t2 R8 ^0 H# `$ J* X& V* NK means method, 逐步聚类法
& p" v% V1 M! q3 @6 g, nKaplan-Meier, 评估事件的时间长度 6 J& z9 {* P8 z* f: c1 W
Kaplan-Merier chart, Kaplan-Merier图$ k6 _, v+ C2 P6 I7 f3 v' W, }
Kendall's rank correlation, Kendall等级相关
% o/ F- {# C8 I& A: ?! KKinetic, 动力学
* n2 T" J. Z2 d. DKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验: h: h- T$ X5 t7 e& N D1 ]
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验" i3 D) o+ \5 l2 e% M' {
Kurtosis, 峰度
7 J8 |- n% d( s+ xLack of fit, 失拟2 m3 a: a6 n" W9 {% U. N5 J2 h
Ladder of powers, 幂阶梯+ D2 I( g, J2 K/ H& g0 m
Lag, 滞后( p3 W& U4 E5 |+ G4 w7 O, o# {
Large sample, 大样本
, k$ V2 O5 c4 \Large sample test, 大样本检验. ?. h/ m. w' N* t" y
Latin square, 拉丁方, R' _$ ~5 `) o2 Q, f: K; [
Latin square design, 拉丁方设计0 y4 X% V' u* p! [
Leakage, 泄漏% z' o7 d: K) ]+ S5 T
Least favorable configuration, 最不利构形
( S @, p$ y5 Y' \) ~: ZLeast favorable distribution, 最不利分布
" A" q: J. ~, i" a; m4 V* MLeast significant difference, 最小显著差法: g6 f- T( ]* F1 @, Y. `
Least square method, 最小二乘法0 l1 D3 X8 s( j% l6 C& D/ X
Least-absolute-residuals estimates, 最小绝对残差估计1 U6 b j4 T4 L& }: A
Least-absolute-residuals fit, 最小绝对残差拟合6 c- H/ S Y/ o5 Q8 R6 t7 G
Least-absolute-residuals line, 最小绝对残差线( _. ] Q" U; b! `% d, b0 A# |( i* l
Legend, 图例
! P @( V0 [( M+ h% p% o" a# @L-estimator, L估计量
0 N) X8 j5 c; e" ?L-estimator of location, 位置L估计量
2 `( E% V3 X! b: O* w" BL-estimator of scale, 尺度L估计量* H# N$ |: l2 o1 @
Level, 水平$ `) I8 z3 h" _! b
Life expectance, 预期期望寿命
# o" q1 N' T8 ^( B4 h d8 KLife table, 寿命表3 ] H( I1 l& B& y; u
Life table method, 生命表法
3 e, _% d, ^- q2 B+ cLight-tailed distribution, 轻尾分布
4 Q6 P4 w9 x0 {. ~8 {$ l( gLikelihood function, 似然函数, u! {, K7 h% E
Likelihood ratio, 似然比
# ^1 N i1 k) T, u. ?line graph, 线图" u) R9 w. X, c
Linear correlation, 直线相关
# F3 j& P; h' r2 [8 z4 K% T4 D5 DLinear equation, 线性方程) l* J, [& e$ {% I' n
Linear programming, 线性规划5 {' g+ y! ~$ D& z7 h+ U3 f
Linear regression, 直线回归
1 N( Y1 k* z& N! U1 bLinear Regression, 线性回归
: }7 Z2 |6 J `. B6 D$ p. I7 LLinear trend, 线性趋势& V1 F; t2 h: C5 Q/ b) W9 a
Loading, 载荷
, W1 U( Y6 T! P1 n8 {- B/ aLocation and scale equivariance, 位置尺度同变性! p! V( L8 g! S) h$ M, ^
Location equivariance, 位置同变性9 s* L6 Z, g# E+ J8 O
Location invariance, 位置不变性
/ z; Q/ Y* ]- d- j1 o/ T6 jLocation scale family, 位置尺度族
; d, D% r$ m7 B5 ^Log rank test, 时序检验 0 u, O+ y6 V+ @$ ~3 O
Logarithmic curve, 对数曲线
' o4 l( m+ M1 LLogarithmic normal distribution, 对数正态分布8 u# l( x$ }- G7 W/ H) d! ~
Logarithmic scale, 对数尺度
; {! e* C$ @+ D: ~# Y6 Q: fLogarithmic transformation, 对数变换
. X+ Q! m! E' j* t, m* }Logic check, 逻辑检查: u8 }% p: B; c
Logistic distribution, 逻辑斯特分布
3 U6 ^! I0 E- T j" ^Logit transformation, Logit转换
; I! z: c9 {( Q4 Q5 P0 LLOGLINEAR, 多维列联表通用模型
7 t& G/ O0 L& {, q# U3 PLognormal distribution, 对数正态分布
) Y% o- x. B2 r$ mLost function, 损失函数* @& c( p# ~+ p8 Y
Low correlation, 低度相关
1 h% {4 x6 s- h+ s5 y. CLower limit, 下限7 y) |2 m2 J% u
Lowest-attained variance, 最小可达方差. B5 k* \! T( |, j; q' g
LSD, 最小显著差法的简称6 {0 O( P2 d5 a) u" t! b3 ]
Lurking variable, 潜在变量' d8 _2 C! @' r. j; T
Main effect, 主效应
1 g2 b6 u9 z/ X7 B+ _1 m6 ZMajor heading, 主辞标目
- C. q# f/ k" P/ `! I8 x: HMarginal density function, 边缘密度函数+ X5 C7 `. Y9 P# U: }" {2 W
Marginal probability, 边缘概率
+ X! z: c1 [$ H9 ?3 DMarginal probability distribution, 边缘概率分布
' n1 w& u4 Q" Y$ @. L6 a R2 z- @Matched data, 配对资料: h) j: o1 Z. m: _
Matched distribution, 匹配过分布% u! k& @ T. n
Matching of distribution, 分布的匹配
/ w. k1 F& r1 ~$ n$ x+ E7 uMatching of transformation, 变换的匹配) B. u5 s3 `9 Y ?" v. L
Mathematical expectation, 数学期望9 ^8 @: ?8 i$ V7 d* \ y4 B0 a
Mathematical model, 数学模型
P- A6 \+ r+ f/ R5 ?1 E* i6 |Maximum L-estimator, 极大极小L 估计量5 \7 E) ^5 ~& b; e( P1 n! d
Maximum likelihood method, 最大似然法% ?! I8 W3 m- f! a- H+ E! {" _8 m
Mean, 均数
7 j6 E* ^' T- hMean squares between groups, 组间均方
, i+ u- \0 D' f# ]4 M2 W4 ]6 XMean squares within group, 组内均方( _$ h) \3 f1 b- R7 D
Means (Compare means), 均值-均值比较- j: E9 K# J U/ S
Median, 中位数
. o( g6 [/ F- x4 n* QMedian effective dose, 半数效量
* ~1 ~* Q9 B+ OMedian lethal dose, 半数致死量* Q6 e* l* `3 [ o2 n% f
Median polish, 中位数平滑! b; x& Z8 }7 s4 |1 G
Median test, 中位数检验
& ?2 F; i" L; y6 b8 |+ P/ y# I' W% {Minimal sufficient statistic, 最小充分统计量 p( n- t" d/ F/ X/ c+ A
Minimum distance estimation, 最小距离估计
- O% H/ Z( R2 Q zMinimum effective dose, 最小有效量
8 K. Y+ m' q) x8 c$ I1 y' tMinimum lethal dose, 最小致死量5 a; g: P+ u6 S* E% O) S
Minimum variance estimator, 最小方差估计量2 a4 f: Y) x, o" i$ K
MINITAB, 统计软件包& W9 _7 a y# f3 ^
Minor heading, 宾词标目
1 g3 X- Z' w6 B, ~& jMissing data, 缺失值
2 u( r3 Q% T! k# s DModel specification, 模型的确定
; Z; u$ `3 Y$ x$ d# KModeling Statistics , 模型统计& M( v8 f7 T( K8 G9 M, j
Models for outliers, 离群值模型" M3 x+ A9 M# Z6 W& w2 X) o1 N
Modifying the model, 模型的修正
6 _, [4 m) D0 r. u' c& I- `Modulus of continuity, 连续性模3 x: a% D" _) P6 ~. |$ _
Morbidity, 发病率
0 `( r K/ ?# h7 Q5 @6 L8 BMost favorable configuration, 最有利构形
' U. H4 @4 m% W% {0 f6 fMultidimensional Scaling (ASCAL), 多维尺度/多维标度
! V+ N: _ X* w3 U* z% L4 nMultinomial Logistic Regression , 多项逻辑斯蒂回归
; D' v6 y j( C7 k( IMultiple comparison, 多重比较
7 t; V/ ~ N" A3 G; _Multiple correlation , 复相关) ^( O( S8 h- H( v
Multiple covariance, 多元协方差. p3 U8 o! `: x: W8 r% D
Multiple linear regression, 多元线性回归
5 m0 t- `6 {4 H) t; K% `2 W. s4 T/ vMultiple response , 多重选项. k$ n q8 R# @6 }6 M
Multiple solutions, 多解# T4 E( R' H* @
Multiplication theorem, 乘法定理- _7 N$ w# C. e" _- e
Multiresponse, 多元响应
2 J9 r- K G- N% X* a: c& h8 PMulti-stage sampling, 多阶段抽样
: k% z+ G7 b# J9 q" _0 KMultivariate T distribution, 多元T分布' S7 ]; T0 g7 M
Mutual exclusive, 互不相容5 b S9 I7 f3 Q3 W$ m1 e
Mutual independence, 互相独立9 l3 T7 Z: F8 ?8 u+ ^6 D
Natural boundary, 自然边界4 w: r- S' H3 B# h+ V
Natural dead, 自然死亡' c. T/ Q1 k, T$ Q. k( Z/ R
Natural zero, 自然零/ p- `. E/ c0 v( U0 x
Negative correlation, 负相关, k" E, c4 h6 ]# ]
Negative linear correlation, 负线性相关
$ t! A) ?. K4 j8 f6 f+ n. A2 L8 m8 ~Negatively skewed, 负偏% p* f i* R4 u
Newman-Keuls method, q检验
* N! z$ B! N9 a3 ONK method, q检验
) o9 u6 W. M# K7 f4 ZNo statistical significance, 无统计意义# Y! S/ F/ V9 v" o7 U+ Y q0 l5 a% W7 X
Nominal variable, 名义变量
Z* ?" B8 i2 n; I J: A2 }2 O, ANonconstancy of variability, 变异的非定常性' @ z: F, l! h
Nonlinear regression, 非线性相关4 K' [& Z- h1 A% C5 E
Nonparametric statistics, 非参数统计# @/ Q( G# U* g( q/ L) n& _8 U8 `9 j
Nonparametric test, 非参数检验( S! p4 `' m# a7 s9 c. [
Nonparametric tests, 非参数检验" p( C( x3 a; e2 i: D0 t
Normal deviate, 正态离差
) z8 F# z* I1 \! wNormal distribution, 正态分布% q( d6 w3 O& M/ J, \
Normal equation, 正规方程组
! w/ _; r$ ^# H0 Z1 K7 ]8 u- LNormal ranges, 正常范围5 }& @5 O( B6 W0 j. B( Q) ?& v' l
Normal value, 正常值
- |6 i9 ?7 u4 {, H; UNuisance parameter, 多余参数/讨厌参数
' a8 b+ r! ?" m/ Y. j8 |" Z& y0 ?Null hypothesis, 无效假设
2 a. r5 R' `3 m( |6 ANumerical variable, 数值变量, `9 h% f8 }$ \5 W
Objective function, 目标函数
% Y3 w1 V) R7 r. B# V2 ]: hObservation unit, 观察单位2 c+ b: {% a; C& _8 e7 Y8 h
Observed value, 观察值6 c5 }, g' h }0 B9 b- C" t
One sided test, 单侧检验
: L2 }8 W% n, c. `4 ]6 z5 o* }* MOne-way analysis of variance, 单因素方差分析# u( k7 q' Z7 o* h
Oneway ANOVA , 单因素方差分析" ]' X E3 q% o J+ S
Open sequential trial, 开放型序贯设计1 f' X R1 j1 [) s! z& G
Optrim, 优切尾, b( Q7 K3 `! `% [
Optrim efficiency, 优切尾效率
: U' z0 i# [* j0 P$ S$ i iOrder statistics, 顺序统计量" D" @* u1 G( Z( v' v
Ordered categories, 有序分类
# g& o4 c: f( o; ]* wOrdinal logistic regression , 序数逻辑斯蒂回归
8 x( U5 R9 D' n# m/ g3 f+ s$ xOrdinal variable, 有序变量# U7 `# U' n! p$ N5 D5 |5 x* y; `
Orthogonal basis, 正交基
8 K1 L, ~# z8 m$ |+ IOrthogonal design, 正交试验设计
" T# m$ W, O/ h0 BOrthogonality conditions, 正交条件
5 R) F9 e& @. GORTHOPLAN, 正交设计
, K! K7 m3 \1 ]' V# |+ LOutlier cutoffs, 离群值截断点
) s* w* I1 s% d7 l' d3 \- {9 pOutliers, 极端值
8 u8 ~# K9 H) kOVERALS , 多组变量的非线性正规相关 ! J2 U9 B2 ~3 E) Q9 a: _
Overshoot, 迭代过度( G- D5 {% q( l' R) K4 | U. ]
Paired design, 配对设计
9 p2 U0 [3 N3 C4 b+ a$ T( TPaired sample, 配对样本
7 S5 V$ N$ p+ F5 X+ |0 E6 ZPairwise slopes, 成对斜率; H* F2 w& ?4 b. q
Parabola, 抛物线
2 X0 j% w! y. y' D; [Parallel tests, 平行试验
! Y7 k; M% {6 O5 Z% }Parameter, 参数
0 B5 z$ k/ I+ b H' P: qParametric statistics, 参数统计. q. m) C( y& F* d
Parametric test, 参数检验
7 w3 k/ I% ~. \1 }3 m* O3 xPartial correlation, 偏相关
' y. [+ |1 B4 ~( H. Z% v9 aPartial regression, 偏回归1 b$ w1 A" l8 s2 s
Partial sorting, 偏排序7 R; P5 |- v: f# K
Partials residuals, 偏残差
8 G6 }! R5 p, @8 i& PPattern, 模式
: l0 U" |# l, j; X7 |Pearson curves, 皮尔逊曲线
+ n7 W, T( N7 _) y0 _Peeling, 退层7 ?/ p4 H4 @/ Z% H; b+ n- I- |
Percent bar graph, 百分条形图
, E% z7 h# s) T1 e9 _5 b3 [$ t {Percentage, 百分比
) {6 j( u9 h* W" Y+ X1 ~8 q- RPercentile, 百分位数& Y1 D- m# x+ l
Percentile curves, 百分位曲线
$ I$ `" v6 A1 H' cPeriodicity, 周期性
8 L W! n% E6 n+ }5 Q- kPermutation, 排列
$ m1 S r2 @; K3 w dP-estimator, P估计量
- g+ q( x( ?2 n% w1 d$ z& i1 E+ vPie graph, 饼图
. g. H2 T2 t0 D9 x% a, E* {2 iPitman estimator, 皮特曼估计量
' T4 t6 t z' Z4 J! H- JPivot, 枢轴量
7 M& y! Z1 c& cPlanar, 平坦8 ?3 Y1 @9 P2 N* p/ W+ o8 z, y, c
Planar assumption, 平面的假设
7 P% N8 G3 v `# Y' P/ jPLANCARDS, 生成试验的计划卡
8 Y$ n& f, m2 o7 Y2 `& ?$ V/ [Point estimation, 点估计 r# ]* G; S4 Y z; s
Poisson distribution, 泊松分布) h2 |! F+ ?6 `, E
Polishing, 平滑
& `6 {7 G+ u5 s6 R% \Polled standard deviation, 合并标准差
/ x2 O; ]6 h$ L- z T6 [$ NPolled variance, 合并方差
+ p7 o' l) W, MPolygon, 多边图3 g! O6 d/ ^/ E3 ?
Polynomial, 多项式
) W) J2 B$ j8 {* L; NPolynomial curve, 多项式曲线
+ _4 ^9 D% D+ B& T, I6 o5 gPopulation, 总体6 j1 B( @" v, q3 B0 ^9 s2 t
Population attributable risk, 人群归因危险度! L, M) F) P- z
Positive correlation, 正相关0 i# B6 i m' c7 R! j% _9 o5 P# A
Positively skewed, 正偏
$ V- a+ X, ~5 @. p4 l. h! FPosterior distribution, 后验分布
2 d+ d' p: ?; `9 {2 DPower of a test, 检验效能
2 z' H! W3 a9 m$ t" N) M/ `" yPrecision, 精密度# v2 K) B; [9 w- j2 ~
Predicted value, 预测值 j6 R" b# ~$ `2 U( f
Preliminary analysis, 预备性分析
8 v3 k) r7 z) h. m( mPrincipal component analysis, 主成分分析- F6 G1 n0 F- W$ ^
Prior distribution, 先验分布
* j v! }. b1 ?9 p/ q: FPrior probability, 先验概率
- z% M$ U+ s" w0 W) E; yProbabilistic model, 概率模型# @( W+ O- o9 S' M$ n- m( p
probability, 概率 Y. ^" U! o5 `, [
Probability density, 概率密度! g" t# X, b6 }9 N
Product moment, 乘积矩/协方差
# |5 F+ H+ \8 B3 v' S: ^: X$ T( _Profile trace, 截面迹图# S7 Z' R; K' v- r- M* }
Proportion, 比/构成比
! D! F2 {+ P. t( l7 X3 DProportion allocation in stratified random sampling, 按比例分层随机抽样
7 o0 Q4 C& S. q/ U6 @# Q3 [ `Proportionate, 成比例% X) h) N8 I) g3 p
Proportionate sub-class numbers, 成比例次级组含量
, y8 |/ L& { U I2 DProspective study, 前瞻性调查
3 y- I1 ^/ h9 y! g1 T1 h& Q% ?) L( uProximities, 亲近性
9 o5 ^$ X% \; v y. RPseudo F test, 近似F检验
# N! m7 y6 Y8 J9 w: B* ]: k0 XPseudo model, 近似模型
, E. K+ S3 ^; R# g6 wPseudosigma, 伪标准差
% ~4 h! i6 k; d2 a+ U6 V8 TPurposive sampling, 有目的抽样
1 m8 ]+ _1 n* ]QR decomposition, QR分解/ S$ x- A3 [! b. A, b
Quadratic approximation, 二次近似
2 q' ~: h) U: A" P8 SQualitative classification, 属性分类; t+ X" ]( Q2 ~6 _7 v4 F$ @5 @
Qualitative method, 定性方法- ]; I9 ?! Y& M# ?9 K; g
Quantile-quantile plot, 分位数-分位数图/Q-Q图6 y/ c% _$ v2 z6 w( {4 @
Quantitative analysis, 定量分析+ M% R2 F( s7 L5 [0 m# P G
Quartile, 四分位数) j4 q; c# G4 m( Z( {% z
Quick Cluster, 快速聚类
' Y& Z* }3 I8 y- J4 _. cRadix sort, 基数排序1 r1 [; G5 m; i1 G7 n
Random allocation, 随机化分组
8 G0 q* |3 o5 \8 I" hRandom blocks design, 随机区组设计' u$ f. u' U8 O. o) V
Random event, 随机事件( h. A: O1 e) X. A
Randomization, 随机化7 j( ]! N; N1 X& m
Range, 极差/全距
( i- ^) I9 E4 @4 r2 Z: O6 m1 xRank correlation, 等级相关/ q% S( U4 h+ A& V; L. b* ?
Rank sum test, 秩和检验0 O) K# c. [2 c( g2 ^
Rank test, 秩检验
6 o# N) Z* H( ^7 MRanked data, 等级资料
: L2 g; b2 g3 V" nRate, 比率1 }) o6 v: t3 b& `
Ratio, 比例( R) E+ A% I' G: r' l/ X9 ]
Raw data, 原始资料" N& j! E( ?9 H' Y8 V! k a
Raw residual, 原始残差
) y" Z. v1 k h3 N* U1 ]4 x5 o+ IRayleigh's test, 雷氏检验
1 ]5 J& J1 X9 K1 J4 }# e3 q0 hRayleigh's Z, 雷氏Z值 5 c8 k, i- E$ i* y3 c6 `$ U1 d
Reciprocal, 倒数
, A3 e+ ~8 {4 C6 s" N- c1 h# zReciprocal transformation, 倒数变换
5 t j% x6 K& V& J# S6 SRecording, 记录& O& I5 w+ K4 Z4 i2 o# X
Redescending estimators, 回降估计量 _0 y" ?' a0 [1 {6 T
Reducing dimensions, 降维
3 q3 ^% f4 k0 U. DRe-expression, 重新表达
1 t% @3 m$ j! H7 GReference set, 标准组
; |! ^1 l8 ?8 q4 ~5 DRegion of acceptance, 接受域' |! Q' K& g5 G/ M4 `
Regression coefficient, 回归系数" [3 P5 S- O* x1 A" o4 g) y* U
Regression sum of square, 回归平方和
- @( B0 m6 E9 f9 tRejection point, 拒绝点8 s: t! u% @! `
Relative dispersion, 相对离散度$ @6 E6 v# X! c
Relative number, 相对数3 W( |9 d1 Y0 G! V* y# L9 n
Reliability, 可靠性
& s: a0 H$ W) A1 V- @Reparametrization, 重新设置参数. L) ~" z4 J/ ~9 J
Replication, 重复: B) [& k% u+ f: T2 F% k
Report Summaries, 报告摘要
5 H7 x. H4 M7 z3 U+ aResidual sum of square, 剩余平方和) h, x& d; E% H0 M
Resistance, 耐抗性 s: X6 o6 Z; k. o# S% I
Resistant line, 耐抗线; P/ S, t6 Q7 P ^1 N- w+ S& _
Resistant technique, 耐抗技术
, ] N7 E+ y- B: X' _0 cR-estimator of location, 位置R估计量% e& O D8 [( u. W5 ^- o
R-estimator of scale, 尺度R估计量
7 C& P0 C/ d2 m0 p9 T; u' aRetrospective study, 回顾性调查& H3 r0 l) R5 \
Ridge trace, 岭迹6 ? k$ K3 a4 u2 n3 f
Ridit analysis, Ridit分析
& m' u* M/ N% \. [Rotation, 旋转) H6 d& e6 p/ v9 x& g! L
Rounding, 舍入
9 W, ]2 g c0 X5 [( `% ERow, 行
4 h- k6 K4 ~2 R; J& h( E0 JRow effects, 行效应
& Y; _) A* h+ `$ \Row factor, 行因素& N$ B+ t5 a2 t" K
RXC table, RXC表% q" W4 A8 @$ Z3 y. v0 N3 n
Sample, 样本# j: h! u: k1 y& I8 I! x1 ?
Sample regression coefficient, 样本回归系数
$ ]9 q4 c# a0 g# TSample size, 样本量
/ q3 P' Y, f' T6 oSample standard deviation, 样本标准差
# {2 a) `& w; n7 XSampling error, 抽样误差
' _# B- n7 B, \. A, `; BSAS(Statistical analysis system ), SAS统计软件包5 P* v/ j! X4 _# l/ l9 U! B' t
Scale, 尺度/量表
" \% [* B# q( b7 VScatter diagram, 散点图" p/ _/ g: u) R0 c
Schematic plot, 示意图/简图
& J, z% {9 K# S" L7 H4 y* U' e( |4 LScore test, 计分检验( E1 y* s, T8 f0 l
Screening, 筛检# U. D; y# {4 A7 |4 t y% }9 u
SEASON, 季节分析 # Z9 G, F: d& L& O. _4 P
Second derivative, 二阶导数
/ v/ R4 X, z+ U& {7 KSecond principal component, 第二主成分% e6 Q( G) J }6 |
SEM (Structural equation modeling), 结构化方程模型
4 g: m# |9 k' F' BSemi-logarithmic graph, 半对数图% U- ^" O4 `/ {7 B+ g ?' `
Semi-logarithmic paper, 半对数格纸' t! S4 C e0 I0 ]
Sensitivity curve, 敏感度曲线
; J! f; Y/ p7 W: TSequential analysis, 贯序分析
2 x. e& P- Y4 b& S% x- l* Z7 ?Sequential data set, 顺序数据集
6 A& f+ L, V) s( G( a. s. J& ~Sequential design, 贯序设计, y* ^+ Q, n) U
Sequential method, 贯序法
o& y* K- r. b9 TSequential test, 贯序检验法- B4 J, S; S$ ]+ t
Serial tests, 系列试验
1 |# ]% I6 } u, Z) A& ?. NShort-cut method, 简捷法
3 b1 _' D' G7 J* W1 g! DSigmoid curve, S形曲线) p( S% h" u* W7 x
Sign function, 正负号函数3 c6 l/ b3 _7 f
Sign test, 符号检验' _" H t3 n7 F4 o
Signed rank, 符号秩
# k& L$ |& W) j/ X/ R" j- F6 cSignificance test, 显著性检验0 Z5 g* ~) t: S1 @) a Z/ Y7 \
Significant figure, 有效数字
, V0 I: D& |- B' H: p& LSimple cluster sampling, 简单整群抽样5 j( p0 L1 @8 C: X
Simple correlation, 简单相关
+ b& u/ E/ H" [& v- LSimple random sampling, 简单随机抽样
( U* `3 T0 u+ }' C/ l8 N3 hSimple regression, 简单回归
2 T* |# {9 n# ksimple table, 简单表; g& ?- T+ I0 W! U$ u! {8 ^5 u
Sine estimator, 正弦估计量4 f% a2 x" h/ T' C0 e7 m1 r; N
Single-valued estimate, 单值估计
6 S# v+ c* ~$ G: {. t- `Singular matrix, 奇异矩阵
3 f6 O" _3 x. G4 l* ]Skewed distribution, 偏斜分布, L4 W' F! I/ n/ n
Skewness, 偏度
0 p+ p& m% X+ k4 K( P( fSlash distribution, 斜线分布9 Z3 z M% ~& u2 s/ q" S1 X
Slope, 斜率
* c+ U' h7 i, z( ISmirnov test, 斯米尔诺夫检验+ C+ B" e) s- w& }7 w3 t* k! v
Source of variation, 变异来源: c% |1 U8 K+ n
Spearman rank correlation, 斯皮尔曼等级相关: n( J, x3 q0 k4 ?( `
Specific factor, 特殊因子
- Y9 \+ |/ |8 Q3 T9 k: `8 KSpecific factor variance, 特殊因子方差
( ?: \5 ~# [5 a9 ^+ T# {Spectra , 频谱
3 a$ u8 m# f: m+ P' c- V: c5 CSpherical distribution, 球型正态分布% B6 |( L5 H+ y! w2 |2 r& D1 e# H
Spread, 展布' L9 ]7 y/ {) O" L8 Q7 e! y) s
SPSS(Statistical package for the social science), SPSS统计软件包5 T7 S, ?# Y' z+ L) B6 P0 q4 J0 N
Spurious correlation, 假性相关
9 K1 y2 m$ g( |% TSquare root transformation, 平方根变换6 C9 ?' m8 O' D3 o j5 U7 H$ K
Stabilizing variance, 稳定方差
: I1 L& E$ ?8 o4 ^9 C/ E- mStandard deviation, 标准差
& y m" V! a, N7 ~. |/ [Standard error, 标准误+ E( F r0 L1 h$ c; o0 q( L
Standard error of difference, 差别的标准误! o0 `' Q. V# C& `) S% R
Standard error of estimate, 标准估计误差0 M- l6 N( v. S& y$ D: o* s' i
Standard error of rate, 率的标准误1 M7 s% _1 H* S5 d* K& u
Standard normal distribution, 标准正态分布
5 I8 Y( ^8 u0 f' f: _Standardization, 标准化
! e4 d6 `" ? @1 W9 U S8 x1 NStarting value, 起始值1 S" L5 A0 \7 t8 i1 N8 l1 R
Statistic, 统计量! C: ~, o* I( G5 Q: @. Z
Statistical control, 统计控制0 m2 Q7 s9 O, ^4 E" k, L2 y
Statistical graph, 统计图$ G( @1 f, L2 ^2 ~ m& S
Statistical inference, 统计推断* d" L0 _) F# v
Statistical table, 统计表6 n* w9 y" \$ T3 f: W1 d
Steepest descent, 最速下降法/ ?& Z" V- K# O" a; T$ Z h% _
Stem and leaf display, 茎叶图
7 A" X/ R; O. VStep factor, 步长因子
; b: b/ ^$ m5 u/ ?$ x8 vStepwise regression, 逐步回归
9 L# r2 r* q1 l% n* TStorage, 存
" c8 m( [0 |3 A8 ^3 BStrata, 层（复数）1 N" ]# ]. b2 t1 y Q5 l. {% o
Stratified sampling, 分层抽样( o9 `" }/ E- \: G7 }+ c
Stratified sampling, 分层抽样4 e4 d J- T, z! c6 c: S5 C. E
Strength, 强度
' ^% G! J/ L6 f6 L' U) w% ZStringency, 严密性& t$ q) K( Y" Y8 N9 _: S% Q
Structural relationship, 结构关系
$ W$ ^& s0 }7 w0 V. q: h3 @Studentized residual, 学生化残差/t化残差
! D- F# b) w+ c2 qSub-class numbers, 次级组含量
3 ^, U/ Z" K+ N1 c5 t! q; PSubdividing, 分割
/ |* g, j4 n9 `( t) [, t# \Sufficient statistic, 充分统计量
1 q* _) z6 {) Q; l( cSum of products, 积和
. U: B) ~. Q! B, ^: G) t: SSum of squares, 离差平方和
8 O! P6 c0 [! z( b5 u; dSum of squares about regression, 回归平方和
- X" g" M; m3 B( z" ASum of squares between groups, 组间平方和
4 [! |) h8 W5 x* F; D0 GSum of squares of partial regression, 偏回归平方和" A& l2 R6 C0 l7 z4 r7 U
Sure event, 必然事件
# H6 h& p- A" ?' _( X7 SSurvey, 调查/ l9 z# r$ o8 v
Survival, 生存分析 ^! v3 ?% x, @* p9 Q
Survival rate, 生存率; W6 H" U7 I5 \% E5 f# }3 y9 `
Suspended root gram, 悬吊根图7 \: k$ g! q" g# |2 K, s, H8 a
Symmetry, 对称& G' ~ m0 {+ h. z8 j% Z
Systematic error, 系统误差7 w" [! c/ A: U! v; c" x8 c
Systematic sampling, 系统抽样
; h% }! [8 ?) ~5 DTags, 标签8 R; [/ ^9 E" k. b0 `
Tail area, 尾部面积
0 @ y: V+ A+ B; I6 iTail length, 尾长- U: H4 R# T9 R+ Q5 w
Tail weight, 尾重! t( `! G& t) `7 X; P
Tangent line, 切线9 L; c. J5 |: e! C" r/ Y
Target distribution, 目标分布: j# P3 N+ e$ `
Taylor series, 泰勒级数/ i; C6 a1 f" Q* f$ R
Tendency of dispersion, 离散趋势
2 l6 |* T# I- k" m9 BTesting of hypotheses, 假设检验9 a& J, s3 |' _+ J7 y
Theoretical frequency, 理论频数. X) u! w+ l- E% Z% P" c* G
Time series, 时间序列
) X4 r0 c' z3 ^/ uTolerance interval, 容忍区间
4 d- M w" W8 d0 ^6 W0 Z" zTolerance lower limit, 容忍下限
/ Q& K4 P% Z0 V! h# RTolerance upper limit, 容忍上限' s4 B% q5 h, @
Torsion, 扰率
# |4 A" E6 ` A: _$ l+ t% nTotal sum of square, 总平方和1 e* d& l3 l, g. j
Total variation, 总变异3 t( @: O: M1 H2 H) e- o
Transformation, 转换) b; b9 E3 B- B5 b1 P! v" m
Treatment, 处理0 v; o# x7 Q0 ]! b( Q4 C6 Q# R. Q
Trend, 趋势
" P8 |4 z; F5 X! w2 m3 V( kTrend of percentage, 百分比趋势, B" J( O( C9 H( x- o* @9 a/ A+ O
Trial, 试验
$ E8 O9 X/ l( M% k- x# uTrial and error method, 试错法
$ W$ d- `/ A, a: \4 Q. OTuning constant, 细调常数
6 {$ L, M8 e9 m# H, h- v, J$ @4 WTwo sided test, 双向检验
4 f& V% c: G6 N* k M S- e( U: J; OTwo-stage least squares, 二阶最小平方" x$ a- p4 }' w* Y
Two-stage sampling, 二阶段抽样
6 s6 N' j5 n [: o. Y0 ?/ ?1 DTwo-tailed test, 双侧检验
0 J2 i! a! c6 s2 c3 R' L" U7 QTwo-way analysis of variance, 双因素方差分析9 b' y0 G. e5 G7 b' }
Two-way table, 双向表. ~3 c2 F( v* Q
Type I error, 一类错误/α错误
1 _1 h% k2 D1 R3 ]0 w( v6 l5 I9 k( FType II error, 二类错误/β错误
& U& X) `% k! _4 I% CUMVU, 方差一致最小无偏估计简称
+ S! [7 I( Q1 P. M6 MUnbiased estimate, 无偏估计
8 u9 ^* U* [1 G$ g5 `: L: f! o+ mUnconstrained nonlinear regression , 无约束非线性回归
) z. B3 \$ R, }+ vUnequal subclass number, 不等次级组含量
+ ^7 |0 z' y$ w& ?- P# `/ @Ungrouped data, 不分组资料
5 t" U! t& [* VUniform coordinate, 均匀坐标; ^/ O. A# ~: L; |8 T% ^$ K
Uniform distribution, 均匀分布
" v% [' U$ R" P+ k3 N d( \# [Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计0 z: B- w% l/ ?1 V! C+ u5 Q' o
Unit, 单元
: r+ x6 j: a' ^3 Y$ e, |Unordered categories, 无序分类* G! S* _8 l( B4 d {
Upper limit, 上限
7 I; y& n k, a1 H8 GUpward rank, 升秩
* W- J6 q" `( _! ]6 ~Vague concept, 模糊概念
! G9 R3 m8 |# k( R! kValidity, 有效性. A8 V9 s! }7 _" `4 I/ v D
VARCOMP (Variance component estimation), 方差元素估计
7 t$ j1 L8 g1 Y& Y3 h3 @Variability, 变异性
+ j& V* d/ l0 dVariable, 变量
$ [5 u2 k+ p; e; [. `Variance, 方差
9 l! ~8 j4 k6 K0 r* k" x) O% tVariation, 变异( K+ n8 Y- w( m2 e) l. U
Varimax orthogonal rotation, 方差最大正交旋转
3 f9 z8 U9 x" F( UVolume of distribution, 容积9 e: A" b; t4 r$ E) p
W test, W检验
4 _# y+ T' k+ J4 e$ \6 gWeibull distribution, 威布尔分布4 a, A* f- ?- I9 ]% L" |1 [
Weight, 权数
4 ?: G1 |/ [5 [: f' sWeighted Chi-square test, 加权卡方检验/Cochran检验
1 a/ u2 x- G- h" tWeighted linear regression method, 加权直线回归. r; q" v" ^, @& m- n" M5 o
Weighted mean, 加权平均数* a( c1 n/ }2 Q' Z8 W% [, L" b
Weighted mean square, 加权平均方差( s! e$ ?' e% w. E) G$ V4 f
Weighted sum of square, 加权平方和7 S/ ?. |/ n _ L J' y
Weighting coefficient, 权重系数8 |8 d) Z- y) _1 [) Z
Weighting method, 加权法 5 O5 E, K* |* L/ w! b
W-estimation, W估计量
* f8 ]; A2 v+ @; iW-estimation of location, 位置W估计量
; A: k& n' J$ J1 LWidth, 宽度
' O# V3 V! `( a+ A5 SWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
, M( H, M1 |5 S0 F5 D( V) @6 HWild point, 野点/狂点# x. {4 @: K4 ~' v+ n3 W
Wild value, 野值/狂值
' b8 J: P6 ]* Y4 c3 Z2 }Winsorized mean, 缩尾均值- a2 e7 n) [& }5 P4 X
Withdraw, 失访
2 e3 Y ?4 Y( ?1 MYouden's index, 尤登指数9 }6 O( \. _# O9 v% O; L8 H& V
Z test, Z检验7 F( V5 V8 }6 r \3 v: e
Zero correlation, 零相关
- t/ e, W# w& K5 ]! fZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
