|
|
Absolute deviation, 绝对离差
- ^' f1 U( o* j# B0 VAbsolute number, 绝对数# N3 ~ O3 J8 G4 [: [7 v
Absolute residuals, 绝对残差
4 B1 |; E1 l$ |; nAcceleration array, 加速度立体阵
# j, N6 R" o$ |7 |( l; T ^# }5 uAcceleration in an arbitrary direction, 任意方向上的加速度$ a) V. R; ]! u7 _9 T$ B' O
Acceleration normal, 法向加速度
6 S+ ~ h* v8 @6 w0 e! @Acceleration space dimension, 加速度空间的维数4 e7 F4 v; @, X* x! `* o f5 F
Acceleration tangential, 切向加速度/ `/ q% e+ v' e
Acceleration vector, 加速度向量
) I+ L, j& v0 y, o9 l, n1 rAcceptable hypothesis, 可接受假设
" w+ |+ q3 U) L& d3 r5 R# d3 @Accumulation, 累积2 q$ J7 v6 @( G
Accuracy, 准确度3 |$ J* i B: I' f% Y6 o
Actual frequency, 实际频数
/ o& q9 z5 r) kAdaptive estimator, 自适应估计量0 g3 `" t& \; A0 H
Addition, 相加
) @$ P8 E7 g6 t5 OAddition theorem, 加法定理
7 ~( s2 X+ K) A/ M! fAdditivity, 可加性' s n J4 L* k0 [- i7 E
Adjusted rate, 调整率
( A7 g1 G$ f. K; u4 C! ^, tAdjusted value, 校正值
6 I, n- v- t1 i' E/ q8 F4 LAdmissible error, 容许误差
9 p( P& l7 w. @2 {Aggregation, 聚集性
, T( r0 x( l# [) @+ B! `- tAlternative hypothesis, 备择假设
8 g9 N: X, ^* w4 I' ]% h* uAmong groups, 组间$ x, n% J* N/ h( T! `9 @& c- M
Amounts, 总量
" u0 ~* B; J. d) S: s3 G7 vAnalysis of correlation, 相关分析
/ R$ K6 h7 p7 p# z9 o. L4 n5 d LAnalysis of covariance, 协方差分析
8 |1 {: Z* m* K% j$ S/ L7 Q+ T0 sAnalysis of regression, 回归分析
5 U6 t# N- V k( T5 l( P7 ?& aAnalysis of time series, 时间序列分析, X* F, S* }( v" V
Analysis of variance, 方差分析; q. T4 G$ ^/ a9 H8 o; U2 |3 p
Angular transformation, 角转换5 `2 s/ ?" e/ F: x4 z. o
ANOVA （analysis of variance）, 方差分析8 N4 |8 {! A4 j
ANOVA Models, 方差分析模型4 H& M" ^, l" F
Arcing, 弧/弧旋" @" {3 t# ?& t8 U# H: J5 z
Arcsine transformation, 反正弦变换- f4 K" B1 E8 C: V" R# S* w9 j5 k
Area under the curve, 曲线面积
/ n9 P+ P: K& pAREG , 评估从一个时间点到下一个时间点回归相关时的误差
+ z; n4 j3 r4 `. Q+ r+ |+ gARIMA, 季节和非季节性单变量模型的极大似然估计 2 f/ v" u# i$ S
Arithmetic grid paper, 算术格纸2 E8 a x; f$ _
Arithmetic mean, 算术平均数% y5 c9 F3 c4 [
Arrhenius relation, 艾恩尼斯关系9 y+ e! J8 z& k: F8 n1 Q* \0 c
Assessing fit, 拟合的评估- ^- j* ?- i4 }7 D' H
Associative laws, 结合律
2 M: V3 l2 F; `+ n- t/ V6 ]7 ZAsymmetric distribution, 非对称分布4 L1 G0 ^3 W! Z1 D$ G! Q9 u; t
Asymptotic bias, 渐近偏倚0 k' A8 {* H2 ?' D- i- d+ |6 s! C
Asymptotic efficiency, 渐近效率: ?" v0 S# X4 ]8 j- ]. ?
Asymptotic variance, 渐近方差
# ]0 \( i8 o+ _! h6 FAttributable risk, 归因危险度
$ H8 |: S! J, n+ F) F4 YAttribute data, 属性资料+ [4 t# O4 C/ ]; N5 p, ^. ~! M+ M4 V
Attribution, 属性
% I! m1 ^. M& G- m* Q' `Autocorrelation, 自相关4 V7 s# t2 O5 Z- g e
Autocorrelation of residuals, 残差的自相关
. D5 Y- x/ a; M- e5 P; KAverage, 平均数: f# G) t. K7 X3 C, ]5 v7 ~
Average confidence interval length, 平均置信区间长度
2 ~9 L2 P1 C$ nAverage growth rate, 平均增长率
) D% M- v* ~# N" A5 r0 [% A3 `Bar chart, 条形图
3 y7 n7 \% K9 @" SBar graph, 条形图$ |# n5 d. i, o6 d/ v
Base period, 基期2 h* `+ p- S1 Q$ h/ B( P4 W
Bayes' theorem , Bayes定理
- k9 h. f0 S: u7 T7 V3 u9 q& OBell-shaped curve, 钟形曲线/ g- H3 e3 p/ t3 h* x0 O3 E& P
Bernoulli distribution, 伯努力分布
9 \( C9 \4 p' Z4 v$ S, K5 p, D1 g7 p5 zBest-trim estimator, 最好切尾估计量
6 J5 h8 F# }0 r) e. G5 X7 MBias, 偏性
5 O/ G/ [) H' K6 S9 V4 ZBinary logistic regression, 二元逻辑斯蒂回归
5 n) m* s. ?" z+ M& ?Binomial distribution, 二项分布# ]6 |$ y( i. O. k: H4 m
Bisquare, 双平方% W8 Z0 r; n' o+ ~( p% H2 d9 F! ?
Bivariate Correlate, 二变量相关
. A% m; \& m! S0 u! b+ M& u" h0 tBivariate normal distribution, 双变量正态分布
( O+ ~+ _& M$ a5 j' G' P$ p/ XBivariate normal population, 双变量正态总体
9 M3 P5 C7 g: qBiweight interval, 双权区间# G- h9 K4 s* Y7 g4 F/ h! Z
Biweight M-estimator, 双权M估计量
7 e; w( c+ P0 K% r, ~& T3 mBlock, 区组/配伍组
" T! Z: x* [' R1 TBMDP(Biomedical computer programs), BMDP统计软件包
# y1 c/ [; [) q1 PBoxplots, 箱线图/箱尾图3 h3 {8 E i5 b" b" c
Breakdown bound, 崩溃界/崩溃点
' |$ [; o7 G+ XCanonical correlation, 典型相关! {0 K, b* U7 I
Caption, 纵标目
7 }5 N4 @* H! g+ }Case-control study, 病例对照研究
) h1 \, e( |7 t% w1 w' i& E$ A/ qCategorical variable, 分类变量
8 ]( R H; s+ P1 N7 QCatenary, 悬链线4 J: X8 e+ i9 }/ u
Cauchy distribution, 柯西分布
: K5 b( O* l# v9 ~' X# s# c7 R4 }Cause-and-effect relationship, 因果关系0 k- `" o- T6 v8 f% X; A& m
Cell, 单元6 T3 w0 W/ U$ g, R, U5 r. ?
Censoring, 终检; T7 j# j& A% D2 K" ~
Center of symmetry, 对称中心4 a) U. [, w8 R. U. I6 I* c" v
Centering and scaling, 中心化和定标
; { F5 w: h, L/ o6 d0 a" O' sCentral tendency, 集中趋势. j8 m s1 ^# F0 u7 W$ ^8 H& }
Central value, 中心值& {3 f# v& @! S) _8 z( q1 S) C: L
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测2 `8 r- P% \! G' d. |+ V' w I7 Y
Chance, 机遇& d1 D- h4 p; K; m7 ]7 d
Chance error, 随机误差% w" |2 T4 t5 u
Chance variable, 随机变量' N' x- @; s" ~: i" J9 O
Characteristic equation, 特征方程
5 B, i' T8 G9 A y9 WCharacteristic root, 特征根; C! C* F# {# ~; z3 W
Characteristic vector, 特征向量9 M$ [% H7 Q' C1 F# R* R
Chebshev criterion of fit, 拟合的切比雪夫准则
2 d4 `$ B: T( h# n& ^Chernoff faces, 切尔诺夫脸谱图
/ N9 J1 m; M; D% i: OChi-square test, 卡方检验/χ2检验; |. u" ~+ E* s5 A
Choleskey decomposition, 乔洛斯基分解
. Q+ s1 L ^5 O7 A5 T! ?Circle chart, 圆图 1 r' A( o6 h* `7 T
Class interval, 组距4 W! U, l6 _! R9 a. e
Class mid-value, 组中值
6 J9 t3 b( j& q5 P+ X1 F7 H3 sClass upper limit, 组上限4 C9 o0 p" d9 w' g7 {
Classified variable, 分类变量 c" u+ V3 M7 O3 }# c
Cluster analysis, 聚类分析
# C+ t+ @# z4 ^" k. A" Z6 ZCluster sampling, 整群抽样
# `, k' ~8 W9 [2 V2 l0 mCode, 代码* B$ X4 H. G7 c5 @8 _" r
Coded data, 编码数据
% n" Z, f8 M- O* tCoding, 编码: a" y( T+ O9 u: W
Coefficient of contingency, 列联系数
3 Y2 E) [ T7 W( i# L( Q# ACoefficient of determination, 决定系数
$ n1 i$ [ v9 ^3 u$ r( ]Coefficient of multiple correlation, 多重相关系数. v: g _/ F& ~! P7 r* r. m( j$ o
Coefficient of partial correlation, 偏相关系数
( M" y! }6 [/ Y& A# xCoefficient of production-moment correlation, 积差相关系数
) R3 U( P/ q; N5 n: s8 fCoefficient of rank correlation, 等级相关系数 P% d4 `; o6 }* C+ K O% P
Coefficient of regression, 回归系数$ z4 F) [& o1 C0 u
Coefficient of skewness, 偏度系数
, f7 R7 \4 q- }3 J) ]+ p- CCoefficient of variation, 变异系数
: k: o5 ]+ x/ o* S* LCohort study, 队列研究: A2 k( \7 ^7 ?4 O
Column, 列
( A/ V Q! b, `7 k) C. {1 IColumn effect, 列效应; i) e# P; l; {. @% }" o
Column factor, 列因素
+ {- {# W: Y1 ?! [Combination pool, 合并
5 R U* K+ n( Z7 DCombinative table, 组合表
& ~) L0 a0 `# h6 h5 f ~ i. N; KCommon factor, 共性因子
+ Q. l$ z1 e* G6 N+ o- TCommon regression coefficient, 公共回归系数 e7 h5 z0 `! r7 p- i) e. Q
Common value, 共同值) p2 Y" t7 Z6 R# h# b! g* U
Common variance, 公共方差
. c5 c; k, k8 N+ |3 `Common variation, 公共变异7 q' u% d3 u* W* ~
Communality variance, 共性方差* O8 n _( O$ f3 o( e! d
Comparability, 可比性- Q4 s# d9 d% [- ]% ]. d$ e
Comparison of bathes, 批比较" Y0 ~# [1 n# x
Comparison value, 比较值
+ s3 }1 t% }+ q+ f9 o0 K9 mCompartment model, 分部模型; }8 _7 g; Z* v! H
Compassion, 伸缩! v$ V9 Z2 L) j# x3 g- }* w
Complement of an event, 补事件
: a- H6 R }) x1 p) ~Complete association, 完全正相关
3 `8 W# w1 T. S7 I$ O; GComplete dissociation, 完全不相关
; a( y' m' |( h1 zComplete statistics, 完备统计量
- R1 Q1 e0 \1 j& I: i8 l- mCompletely randomized design, 完全随机化设计& `+ R7 h B5 i% {0 d
Composite event, 联合事件2 {3 H2 ` y: Z: P0 y
Composite events, 复合事件" W \/ e$ O; n5 ]) O
Concavity, 凹性
6 z2 ~* A" h3 n1 P3 MConditional expectation, 条件期望# q' L% ?% q, S$ M. N1 T4 Y6 E
Conditional likelihood, 条件似然
/ G3 Z7 V o+ p2 CConditional probability, 条件概率
. @5 [1 W/ P) {8 ^Conditionally linear, 依条件线性
" W2 K4 P3 B" D+ u$ s" qConfidence interval, 置信区间3 a% d" E/ w# Y) d2 p# t5 h
Confidence limit, 置信限
9 Q% ]+ I6 J: nConfidence lower limit, 置信下限9 A7 T* X K+ Z2 l# `
Confidence upper limit, 置信上限
) D# L. G6 m7 i6 W) M/ jConfirmatory Factor Analysis , 验证性因子分析% K9 Q+ U+ }$ [+ E
Confirmatory research, 证实性实验研究; {& m$ e, B& @8 W
Confounding factor, 混杂因素% D4 ~! \0 O. p; `3 y$ n. E
Conjoint, 联合分析2 }, c( t9 Q5 E( c! e" M4 f
Consistency, 相合性
9 x( G7 t V" j9 eConsistency check, 一致性检验
7 g7 o! k& [4 N! t2 dConsistent asymptotically normal estimate, 相合渐近正态估计
) N- q8 ~, i& r# O5 {Consistent estimate, 相合估计
6 E" p# d' R% B0 G5 eConstrained nonlinear regression, 受约束非线性回归
; D' F4 A2 ]8 N$ ?( vConstraint, 约束+ j. j( m+ V% K* U" T" i
Contaminated distribution, 污染分布
8 q# d% ~ |4 u9 p1 g) tContaminated Gausssian, 污染高斯分布
; G1 S0 B4 N( iContaminated normal distribution, 污染正态分布6 v1 `, R9 d' A0 ?2 f2 Y
Contamination, 污染
2 I6 ^8 ^0 [. l) gContamination model, 污染模型
$ P, R5 k# x" E* j& m0 y6 F1 o: DContingency table, 列联表
7 X: O' G/ p) [0 TContour, 边界线
) x/ x1 m% D* [) {& KContribution rate, 贡献率
5 l {/ G% n9 @0 _/ VControl, 对照
1 a2 w; I9 z$ m4 BControlled experiments, 对照实验
[. G- j9 G$ s/ S0 JConventional depth, 常规深度+ f: q l* e, @9 l0 @. M2 \
Convolution, 卷积1 M8 d! ~6 P4 W2 r4 O* ]( c
Corrected factor, 校正因子4 w) j1 H h8 S" ]- A7 [" a
Corrected mean, 校正均值5 o0 r$ U& `: V- O i/ M6 t0 g
Correction coefficient, 校正系数
8 h [4 D& ]/ w3 }$ I8 _Correctness, 正确性+ R$ `& C* {) d3 K0 {- i: R
Correlation coefficient, 相关系数& U2 z0 K& u1 o' o3 o( M
Correlation index, 相关指数' I1 q' H# w o% H( }4 X
Correspondence, 对应
8 `0 K0 [* [$ x4 j& K. {( E: [% e8 ~Counting, 计数8 ~8 `8 A3 @9 t' h
Counts, 计数/频数
, s% Z- P, _ v$ o$ sCovariance, 协方差3 Y9 |: \6 ~, _) a h3 N2 M2 z
Covariant, 共变
8 R/ |3 U3 O. D s* t2 Z ZCox Regression, Cox回归2 R$ }3 {* I/ e$ N
Criteria for fitting, 拟合准则( u9 \2 c& r9 K) H7 ~
Criteria of least squares, 最小二乘准则
( f! y8 Q4 F1 i" W# L3 t) WCritical ratio, 临界比- y" `4 A% p/ X$ G0 n
Critical region, 拒绝域
, E& B a) |/ i1 Z8 g; \( P8 ~Critical value, 临界值
. S" B. u) R6 I KCross-over design, 交叉设计6 N, _4 g& y/ c7 V8 i, ?* O2 t' w
Cross-section analysis, 横断面分析 [& q- C1 N0 d
Cross-section survey, 横断面调查1 H3 g. i5 C1 {1 Y' \4 `( K) j3 q7 A
Crosstabs , 交叉表 ( I F* G$ ]+ i
Cross-tabulation table, 复合表- A u- J6 c3 o& a5 s7 @2 E. Z: W I: t; e
Cube root, 立方根8 T4 H' M7 H' W
Cumulative distribution function, 分布函数' w" i) f @+ }3 Y* h7 T# G' ]
Cumulative probability, 累计概率
9 A5 p2 c. I, VCurvature, 曲率/弯曲3 g1 b @. f2 M3 O& M- n3 @9 r
Curvature, 曲率
/ O4 }0 W2 H0 m; S' h! T! ?Curve fit , 曲线拟和 5 }! v/ u* C: H: r! M$ x6 a, R I
Curve fitting, 曲线拟合9 Y; f5 {, X; b9 o! y
Curvilinear regression, 曲线回归
_8 K3 ~( X& B( F1 zCurvilinear relation, 曲线关系
0 F0 E$ P8 f" c# O& CCut-and-try method, 尝试法
+ F4 B4 _; y8 z, t; tCycle, 周期1 e0 o2 g6 p. |3 i2 f d" Y& I
Cyclist, 周期性1 U& w L+ v* O) F/ \! G; H
D test, D检验1 h' g: j0 A0 \+ N0 f
Data acquisition, 资料收集
5 G6 ~, ~( d q. t6 P3 L* k" eData bank, 数据库
) Y6 O- l7 D; I' h+ r, r- JData capacity, 数据容量" U7 K- C& M& P: C7 d
Data deficiencies, 数据缺乏
$ R0 @! e+ T+ @- k# i, ]& L& cData handling, 数据处理/ D; m' M) B' a3 W
Data manipulation, 数据处理
/ s8 g* \9 U* i' NData processing, 数据处理) d, U: `6 G! e( j( ]% r8 {2 q% s
Data reduction, 数据缩减0 x; r$ d" W" _0 N3 Y( \/ R
Data set, 数据集0 ^$ w* S( ^* V. H% z
Data sources, 数据来源; x" A5 ^% J5 c# X! D' g8 x) }1 d& t
Data transformation, 数据变换
* i: Q! ~# E0 VData validity, 数据有效性
5 L q- {2 A- k3 MData-in, 数据输入
" S5 C5 {+ W; s2 q) i& dData-out, 数据输出. J1 _2 L. E8 ?( [2 ~# j
Dead time, 停滞期
: d: ]! O+ t3 }& y# j% `Degree of freedom, 自由度. r3 R- R$ [# ~5 r" t6 F$ I
Degree of precision, 精密度
6 b0 V% f, K4 a4 d) K* z- G( jDegree of reliability, 可靠性程度
8 S1 e7 N1 p6 V) FDegression, 递减
# z: m* i7 Q2 @/ w- R' b% D1 ^Density function, 密度函数/ C4 X- Q$ x, o8 I, z4 A
Density of data points, 数据点的密度
. P% d1 i( B9 R6 D6 Y/ V3 ~Dependent variable, 应变量/依变量/因变量; b! b) F* {$ \! K6 l
Dependent variable, 因变量
' |- d/ U3 t' n1 H+ F n' }Depth, 深度) i! l* }, @, ^# K5 _5 U
Derivative matrix, 导数矩阵, {& ^" G, o B
Derivative-free methods, 无导数方法
; W" n- v6 K/ |. @+ W) T5 ~Design, 设计5 q ^( X- S- U% W: T O U0 e; U
Determinacy, 确定性6 y4 R: i9 i% ]" `
Determinant, 行列式
/ Y' ]" b4 f6 b% N# H* ?( v: DDeterminant, 决定因素
4 B7 F! B. }. X; _( v( ADeviation, 离差
1 p8 e* ^$ s3 s! \' @! L, EDeviation from average, 离均差
/ W6 n4 E2 O2 S; RDiagnostic plot, 诊断图
% N* t# y: Y9 I* R4 z! H& Y. U7 HDichotomous variable, 二分变量
- }6 O: |) a- U( h. c# tDifferential equation, 微分方程
9 D, D) f6 Q1 K8 Y- Y! _* KDirect standardization, 直接标准化法6 {6 F f/ n. i8 [& M
Discrete variable, 离散型变量
$ d' ?* [: \5 z$ w# H- lDISCRIMINANT, 判断
5 ^ j+ F$ m( ^$ S. i; v8 TDiscriminant analysis, 判别分析8 R+ Q! \6 V& P6 |% R/ N [3 ^
Discriminant coefficient, 判别系数1 \" N7 d% O5 W
Discriminant function, 判别值- B; y, w) _' u' g. _
Dispersion, 散布/分散度9 q! j/ t& B7 f% u
Disproportional, 不成比例的, ]5 {! q& [: L, S( u y& A; [
Disproportionate sub-class numbers, 不成比例次级组含量
# w- ^8 H9 I: R6 v6 m: O4 X: sDistribution free, 分布无关性/免分布
G$ A1 f' K( v+ A) v) l dDistribution shape, 分布形状
7 E+ N, x! A2 N1 @, j# @Distribution-free method, 任意分布法
1 M2 ?. b+ h- U7 ?" T5 tDistributive laws, 分配律0 f0 v$ \/ M7 j2 N4 X7 K. J" B
Disturbance, 随机扰动项
/ a, r0 D5 z: U' G4 HDose response curve, 剂量反应曲线
7 D n# G, p d) P9 z, WDouble blind method, 双盲法% |5 Z4 x* i* R* I
Double blind trial, 双盲试验0 b- k; E" d, S$ ^" _
Double exponential distribution, 双指数分布
# a& F" H: `; hDouble logarithmic, 双对数% D: r8 u2 _: ~; l
Downward rank, 降秩$ U( Z( w7 V) a
Dual-space plot, 对偶空间图0 B8 e3 u" r( s, W) I4 l
DUD, 无导数方法
9 ~8 M& z6 y O7 V% r% `) bDuncan's new multiple range method, 新复极差法/Duncan新法5 S" L( o. a2 G ?+ v" j, f
Effect, 实验效应# X) X1 u2 @: P/ c3 ]
Eigenvalue, 特征值
! Z9 p' C0 t G$ e* @. {. gEigenvector, 特征向量! c) p) s' b/ w2 y1 |
Ellipse, 椭圆
0 @! W/ ~( c; }1 H; ~# h" U: fEmpirical distribution, 经验分布
6 o- R1 z* {' t6 C# yEmpirical probability, 经验概率单位- l3 U8 p0 V/ M$ T N
Enumeration data, 计数资料
! b! ~ P7 i/ P% ]Equal sun-class number, 相等次级组含量) W% [, g0 y+ \) q+ B
Equally likely, 等可能0 ^0 |: A+ i, d; \) d' h* W `
Equivariance, 同变性/ n/ }' p7 w' h$ k
Error, 误差/错误
, |% G" Q8 n3 V, |Error of estimate, 估计误差
. O( W2 {$ ` w) W& N# _Error type I, 第一类错误: `1 _" k: i3 Q8 T# k
Error type II, 第二类错误' _- v; n: |1 \
Estimand, 被估量
3 b3 B, e- J6 z, v1 e; lEstimated error mean squares, 估计误差均方" ~& u0 V0 H7 N* P7 ?, `! k* d
Estimated error sum of squares, 估计误差平方和
3 T. R6 [' }3 z" ?) b. FEuclidean distance, 欧式距离
, Q, O( t, O' a. JEvent, 事件1 \" N& k; J6 W3 P! H
Event, 事件, C8 B5 U$ R6 }. J# h8 s, W3 p {
Exceptional data point, 异常数据点0 |) X& e( p( x; q7 w& h8 c
Expectation plane, 期望平面2 m( t7 v. [) G& p& `; g d8 y
Expectation surface, 期望曲面
' c/ z) S$ R/ l; S( E, nExpected values, 期望值
% q5 a7 |) \1 ~6 B9 X$ v7 h% yExperiment, 实验8 P: S, G$ h( t M& T
Experimental sampling, 试验抽样1 `# s+ Z9 P6 n# j9 Q
Experimental unit, 试验单位
( u1 ? d5 v# m( gExplanatory variable, 说明变量7 y8 e1 M7 t/ Z' n8 S
Exploratory data analysis, 探索性数据分析 a5 s! N7 d3 h+ m
Explore Summarize, 探索-摘要) m2 B# Y2 z. o# @4 q1 V# O
Exponential curve, 指数曲线) X% V8 y" f3 V2 @1 r! O( Z
Exponential growth, 指数式增长
% h5 g( h) V' ^: [! GEXSMOOTH, 指数平滑方法 9 W7 H' ~4 D$ @' M, n
Extended fit, 扩充拟合
9 y* L p0 l0 c8 jExtra parameter, 附加参数
! T7 C7 y- M0 j1 pExtrapolation, 外推法5 f! P5 s- T2 y( ~
Extreme observation, 末端观测值
' I2 d3 u% r, O& ?( e1 f+ B. ^ zExtremes, 极端值/极值
2 S- B1 a: ]: }F distribution, F分布
1 X8 ?% i9 {' e$ A& G6 jF test, F检验5 T4 T7 A6 v, V7 v' A
Factor, 因素/因子7 i, w/ Z1 B% K* G8 L& p& I% ^
Factor analysis, 因子分析
9 N. c( E4 Q# U- kFactor Analysis, 因子分析+ t% c K4 l$ {, {; [$ w
Factor score, 因子得分
/ y0 I. I% V4 ?* D0 |' [5 q4 \9 EFactorial, 阶乘9 v) a {' g! S9 [; i) x
Factorial design, 析因试验设计
& u$ C+ [* k4 ]0 mFalse negative, 假阴性
# q: u" }) t+ {% K6 @& HFalse negative error, 假阴性错误
0 [2 e$ F0 B* g) xFamily of distributions, 分布族
! q. Z0 M3 t) e [Family of estimators, 估计量族 @& x. g. G, K' J. Z& A
Fanning, 扇面$ C0 p& Z- A6 n
Fatality rate, 病死率
4 Q+ j8 [/ t& _( v5 T/ VField investigation, 现场调查 r: I. D, c U1 ?
Field survey, 现场调查# g' u- U6 ]9 g. W! Q
Finite population, 有限总体3 z9 g# o6 l q j3 g I* n8 q4 |2 [" I
Finite-sample, 有限样本. M& d& u; p$ O! N5 l) ^
First derivative, 一阶导数
' x% P- M8 d2 ^First principal component, 第一主成分
4 }" z! |9 M& pFirst quartile, 第一四分位数# q# y) _7 a* o( L, D7 |( s7 Q0 E
Fisher information, 费雪信息量* ^9 w: Z* V+ r
Fitted value, 拟合值8 I4 ^2 m: F& R) |
Fitting a curve, 曲线拟合& F) e' q0 ^7 H6 @( F* a. {/ H# O5 D
Fixed base, 定基5 t. P+ s: C4 X l! k
Fluctuation, 随机起伏
: r }. i: k% V9 w: ^4 AForecast, 预测3 j5 s+ j- H" k4 n
Four fold table, 四格表* g# N0 A* o0 s( S( D
Fourth, 四分点& X9 A# f1 q1 t* A7 T4 ~
Fraction blow, 左侧比率& h7 `( x0 d, q+ _% B5 i$ Z
Fractional error, 相对误差
8 l; J/ {5 V5 C1 X5 xFrequency, 频率- T9 u- M, E) `* a) i/ ?/ W2 R) b
Frequency polygon, 频数多边图7 h5 j9 f- E( c1 u7 k0 O
Frontier point, 界限点) @. p! y V8 e+ D1 Y
Function relationship, 泛函关系
- \' V* j& D+ P& A, dGamma distribution, 伽玛分布 Y2 g8 @, i6 a( Z4 [" D) T" N& {
Gauss increment, 高斯增量
5 |5 x, G/ M) ~5 h- fGaussian distribution, 高斯分布/正态分布% ]! T, n4 b/ v% Q
Gauss-Newton increment, 高斯-牛顿增量
# G* p5 T; @4 vGeneral census, 全面普查
3 a# p/ D2 k9 a# P" A4 E! A% \GENLOG (Generalized liner models), 广义线性模型 ( y( z% N4 ?( P: |
Geometric mean, 几何平均数, w2 D8 W) x; e. @2 y
Gini's mean difference, 基尼均差
' m9 a* w7 S5 [6 y: x9 H0 U/ B- LGLM (General liner models), 一般线性模型
& t' B+ I- c4 C( ?+ ~Goodness of fit, 拟和优度/配合度
. D1 s# g4 k! P( S/ U) x" fGradient of determinant, 行列式的梯度
, [! p- J. |4 l/ b, VGraeco-Latin square, 希腊拉丁方# l h h1 h" r* j: S* m7 U8 @8 b; u, k9 G
Grand mean, 总均值7 O) w: W# c" Z3 L
Gross errors, 重大错误
8 B9 x, W; i( F" p% ~. d4 JGross-error sensitivity, 大错敏感度
7 n5 [" B" b- ]. w9 X: q1 `/ lGroup averages, 分组平均# N1 o, p- I9 V% a4 Q
Grouped data, 分组资料# \; `7 W" q$ A4 z
Guessed mean, 假定平均数3 Y, u' f, i& F1 {+ y
Half-life, 半衰期; \. F3 U3 Z/ q, ^ @
Hampel M-estimators, 汉佩尔M估计量8 ?/ E" o, v X% f8 o
Happenstance, 偶然事件8 i& u$ E$ v/ W7 Q3 k% M
Harmonic mean, 调和均数% [7 W( `: W5 W5 d) N
Hazard function, 风险均数
# R+ w* T+ `' u0 `) T% Z! hHazard rate, 风险率
1 r; h+ D6 X* `Heading, 标目
/ T# i* X% g' B6 i0 U8 [1 [Heavy-tailed distribution, 重尾分布
( H+ M8 ^+ _. V: o8 G% IHessian array, 海森立体阵
" B: w- P" X2 K& ?Heterogeneity, 不同质. {; ^$ h3 l1 l' L
Heterogeneity of variance, 方差不齐
! s* W0 Q: Y, Q4 C1 q, I' O% lHierarchical classification, 组内分组5 g+ y; ~* F/ {; Y9 S, m
Hierarchical clustering method, 系统聚类法
. a* T9 I# z% U% [; b* y, S% N# P: dHigh-leverage point, 高杠杆率点0 J" L/ U' _* X4 W7 v! R
HILOGLINEAR, 多维列联表的层次对数线性模型1 _/ G1 X4 a- |6 h m! ~$ T
Hinge, 折叶点
) A7 u5 @" p+ p; HHistogram, 直方图$ }3 ~! A) H/ g0 v
Historical cohort study, 历史性队列研究
: C0 A1 ?% [: Q5 L" \ b% d6 ~. AHoles, 空洞( \* P7 Q! I& d1 T; i8 _
HOMALS, 多重响应分析
: f. c) n% u, P! Z+ QHomogeneity of variance, 方差齐性! g2 {4 n) O! X6 |6 M! l
Homogeneity test, 齐性检验9 g0 X4 X0 ?- R( s) C' ^* J
Huber M-estimators, 休伯M估计量
; N/ g( I, ` N- A2 hHyperbola, 双曲线
% P# l! b j K, zHypothesis testing, 假设检验
' g% u7 y9 \ q% u* y7 r# nHypothetical universe, 假设总体7 _& r- V' }2 e( v) I, P
Impossible event, 不可能事件7 _; N# [+ x- \/ a, `5 k6 r
Independence, 独立性
) c( O# x# x6 O* G3 u) }Independent variable, 自变量3 B8 Z) d2 @8 U+ T+ I
Index, 指标/指数, @6 c- s* I; ?! k0 q0 z% O# C
Indirect standardization, 间接标准化法
' C. h/ ?. r) y1 I* [ LIndividual, 个体
Q0 O2 I0 C& pInference band, 推断带# [: S. L8 a# n( h7 n4 H
Infinite population, 无限总体
9 E- L( T- z% P- J( q- I' dInfinitely great, 无穷大2 P1 _! T1 b! R; X+ j' v( O
Infinitely small, 无穷小
6 O1 @- b) L) D2 T1 f, M# cInfluence curve, 影响曲线2 m( t K% G; Z
Information capacity, 信息容量7 ^5 L$ {/ N! H/ A! L
Initial condition, 初始条件& J- O( D9 q, r }
Initial estimate, 初始估计值
, ?# g8 Z3 ?/ O6 v, F5 q1 o. ^Initial level, 最初水平0 b6 P# O: @* S3 X
Interaction, 交互作用1 P/ N- j- V0 m
Interaction terms, 交互作用项2 V0 X. d2 c0 A; s
Intercept, 截距
# R& Z1 A# l! f. o! C/ a1 @Interpolation, 内插法
$ g; P, D, p9 G* mInterquartile range, 四分位距
2 S9 ~6 }* c- _( h: T2 b QInterval estimation, 区间估计
e- C! D6 Q1 \1 \: S/ ]! {Intervals of equal probability, 等概率区间, V% l8 W9 @+ ~0 q
Intrinsic curvature, 固有曲率
# ]8 ?2 B' c* z. mInvariance, 不变性
+ l, m6 }) W, f, eInverse matrix, 逆矩阵) S. [/ [1 S0 [! m7 d6 Y" p
Inverse probability, 逆概率
4 S: `, R) Y, _4 F5 t- QInverse sine transformation, 反正弦变换
! A* F' I) S4 y- E$ jIteration, 迭代
7 h& j! F/ A5 ]7 j& c9 ~, l }8 nJacobian determinant, 雅可比行列式
% H; |' k' T# e: |" wJoint distribution function, 分布函数
7 `1 l# T5 \: l$ PJoint probability, 联合概率
4 n; S; B' f/ N1 {! ?7 _4 g) IJoint probability distribution, 联合概率分布
; q3 D" M5 [$ ]1 S6 x% u+ @K means method, 逐步聚类法* w- Y {* q: q! q0 u
Kaplan-Meier, 评估事件的时间长度 4 F: S+ u& b: d; [: C
Kaplan-Merier chart, Kaplan-Merier图
7 u; M( O+ b' OKendall's rank correlation, Kendall等级相关
& X# v" M- i; j3 NKinetic, 动力学4 q) d6 A) d8 p6 V
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
" r& r+ y# W% Y: s4 C- ]) H( ?5 eKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
# Y4 o8 j& L# ?+ x2 K, y% PKurtosis, 峰度1 t2 t! U+ I; [" J9 W
Lack of fit, 失拟+ e# {; {7 b/ d$ I8 m, ]6 x
Ladder of powers, 幂阶梯. B/ W3 o" k" o( _' G
Lag, 滞后& S% F. g% K2 W( s
Large sample, 大样本
& {9 Q& }' L( J) q+ m( S8 JLarge sample test, 大样本检验
y# ]8 h" Z6 SLatin square, 拉丁方
' C3 L& l( F2 h' J, ?! G+ e1 TLatin square design, 拉丁方设计* t x9 H: W2 u9 z
Leakage, 泄漏& ~2 O, J. Z$ P" O5 z
Least favorable configuration, 最不利构形
6 M* F4 p+ p6 j: w0 }6 \" oLeast favorable distribution, 最不利分布/ U7 J4 k' @3 i" `7 x5 F! ?( W- [
Least significant difference, 最小显著差法1 |* d' b1 o% h1 Q: N! ^/ y |& a
Least square method, 最小二乘法
* n8 Q- n# v F; e2 R; c: I0 M6 ILeast-absolute-residuals estimates, 最小绝对残差估计$ v) I7 ^; K4 S0 o
Least-absolute-residuals fit, 最小绝对残差拟合
+ g, X; J7 Y4 a# w+ T G6 k2 j5 GLeast-absolute-residuals line, 最小绝对残差线( O1 c$ m* M J1 J H& t
Legend, 图例
3 i7 |1 S# k7 u4 s: z* sL-estimator, L估计量
2 K! L7 u! p0 f1 w/ tL-estimator of location, 位置L估计量
1 h) }2 Y/ Y4 O* t+ z9 U6 d2 p4 KL-estimator of scale, 尺度L估计量& a0 k" C# x" {# f) m
Level, 水平
/ B7 G' |1 ]. W6 BLife expectance, 预期期望寿命
" r8 L8 m: C. h6 f9 qLife table, 寿命表
1 t6 h; U0 ~- O1 U: Q8 ] xLife table method, 生命表法8 ?. x ]% [# n2 q1 P# {
Light-tailed distribution, 轻尾分布) W9 ]4 u1 a9 ^# P4 [2 X, d1 B) I. u2 \
Likelihood function, 似然函数0 [( g, d N9 L& O t& |
Likelihood ratio, 似然比
3 q1 J+ N# q8 g4 O( q% t# x7 Bline graph, 线图
* p4 S- D) | e! c d1 g4 }6 s$ dLinear correlation, 直线相关
. U( V5 g0 P3 r% [5 sLinear equation, 线性方程0 d/ q% R' Y1 {, X5 R8 C( J; x; ~( S
Linear programming, 线性规划
# F( F, K9 g3 ]2 T8 OLinear regression, 直线回归
) |4 c, m/ |. V! X9 c1 p% \Linear Regression, 线性回归
0 o" h* t# j6 F% \& R4 j$ I' nLinear trend, 线性趋势
6 u: i* n K* U; m; ELoading, 载荷 a$ |8 ?- z1 r& c. ]1 a6 {
Location and scale equivariance, 位置尺度同变性
; D; Q2 x. _# H$ m" p; z; TLocation equivariance, 位置同变性" \- y% f0 t6 T: g0 J1 R" W9 x, z
Location invariance, 位置不变性1 ?4 ~ r* |2 {; i) ?2 G9 z
Location scale family, 位置尺度族# Q* i2 f7 {5 j [# W$ x
Log rank test, 时序检验
" o4 X& b8 w- o5 \Logarithmic curve, 对数曲线9 P3 r d& w4 Q) Y
Logarithmic normal distribution, 对数正态分布
% `) Y2 y) l, `% f; eLogarithmic scale, 对数尺度
1 g! O4 S" p; {5 @Logarithmic transformation, 对数变换
% u( P7 }/ y: r7 u( ]7 X. ~Logic check, 逻辑检查8 Z& ~& o2 k7 x+ r
Logistic distribution, 逻辑斯特分布
- ]) K: V' a9 v$ w- Y. w7 H& BLogit transformation, Logit转换+ u( q0 w. K9 n" t Q/ s
LOGLINEAR, 多维列联表通用模型
$ d1 Q, d/ [/ i9 V2 mLognormal distribution, 对数正态分布
. r. \' C7 K/ L# JLost function, 损失函数
$ ` T4 o# \" T/ H: JLow correlation, 低度相关
& _2 v, w( {4 L3 o c2 ALower limit, 下限# B3 V" p* Q- ]- T! c8 [
Lowest-attained variance, 最小可达方差6 w$ M5 b/ I0 j* Z% z0 K
LSD, 最小显著差法的简称6 d* G* o5 f8 j2 x' J- D, q
Lurking variable, 潜在变量
, q, N" I4 @( y( A! j9 HMain effect, 主效应! L" H. r# G P! C
Major heading, 主辞标目4 g, n r& `4 W' h& Q# @
Marginal density function, 边缘密度函数% u& H8 j- A7 N- B5 Y5 K+ e
Marginal probability, 边缘概率
& p8 _# A u+ |. m C) r! Z8 D/ yMarginal probability distribution, 边缘概率分布/ v1 j' H$ l) Q' L G4 l0 m( s1 s
Matched data, 配对资料
6 {( e; \, L9 {3 O7 i; z% CMatched distribution, 匹配过分布
, r" r5 E8 I% nMatching of distribution, 分布的匹配3 H/ w/ z. D, r$ \" R' w- ?1 ?
Matching of transformation, 变换的匹配$ @% W0 a( K7 o
Mathematical expectation, 数学期望
5 o' r8 h2 z( t: i+ B. QMathematical model, 数学模型0 O8 `; J/ I& Y
Maximum L-estimator, 极大极小L 估计量( @& m4 T+ @ p8 o5 d* g
Maximum likelihood method, 最大似然法$ d, c% A7 t* `9 b0 c/ x
Mean, 均数
' A* U" {+ U' qMean squares between groups, 组间均方9 j- z3 v2 k4 p
Mean squares within group, 组内均方
/ [0 s U: H S$ M# Y* C/ b0 JMeans (Compare means), 均值-均值比较5 G% `9 N! r# z1 q# p: g9 `
Median, 中位数
9 D# j( s# A1 k" ]- I. m7 X; OMedian effective dose, 半数效量
# E" T/ {2 `4 Y5 k. o/ K: v2 vMedian lethal dose, 半数致死量1 ]% l; Y" l9 A$ h$ B# e8 ?' D
Median polish, 中位数平滑
/ ]% {: H. A) T8 UMedian test, 中位数检验3 G4 E$ W1 e' ]$ r. _% n- R, `+ N) n
Minimal sufficient statistic, 最小充分统计量
) Z3 J' F, n, {8 v/ @9 M9 p$ i- w& LMinimum distance estimation, 最小距离估计" s, N [$ j& x! P
Minimum effective dose, 最小有效量
, h( _5 t8 F! ?3 i( [Minimum lethal dose, 最小致死量
3 }" b8 G4 q l* D+ C) L: VMinimum variance estimator, 最小方差估计量
0 R/ N* m; d c* IMINITAB, 统计软件包3 \0 Y3 E8 Y. |. e6 i
Minor heading, 宾词标目
7 {& h/ D0 f' z; u/ y t6 @5 PMissing data, 缺失值6 B7 A3 o; r3 S
Model specification, 模型的确定8 U3 c. u, m, V" d* l
Modeling Statistics , 模型统计* M# V* H7 F7 ]) Z; {) ^
Models for outliers, 离群值模型
7 k" x9 l7 z, T" f# t, qModifying the model, 模型的修正2 D! ^; n7 ?4 Z s& i0 g4 @. f& q" C
Modulus of continuity, 连续性模# a' y; U3 G3 F1 O- T8 S
Morbidity, 发病率
0 z- b5 w/ B, N* f- `Most favorable configuration, 最有利构形( k: L! a* U& y7 V1 V, d
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
n3 m7 c1 j: F( `) y* D1 `# oMultinomial Logistic Regression , 多项逻辑斯蒂回归
, U. X4 x X6 `6 A" v0 r* O* M' |Multiple comparison, 多重比较
, G2 d$ c0 c$ YMultiple correlation , 复相关
- ?! I y2 j2 xMultiple covariance, 多元协方差4 I m- i" }$ S- l
Multiple linear regression, 多元线性回归
. X: @! r7 k# RMultiple response , 多重选项
% _ s9 ?3 |, M6 T9 `8 Y/ }Multiple solutions, 多解
, m. D! y# Y) M6 L) H2 A C4 I; yMultiplication theorem, 乘法定理6 @# t5 o; @6 y% z( f4 T
Multiresponse, 多元响应# d( b8 @6 U o9 h, t" S
Multi-stage sampling, 多阶段抽样
; v% m7 M }% _: jMultivariate T distribution, 多元T分布8 O h# g4 I/ q- I7 Z" c2 K( n+ ?
Mutual exclusive, 互不相容
2 c9 u& k& d- T* u$ K! f" iMutual independence, 互相独立0 K4 E: c) U2 }
Natural boundary, 自然边界
- x8 z4 h! ~) A% k; _/ fNatural dead, 自然死亡
( S4 w9 ^% t! V/ nNatural zero, 自然零
! N, O0 K5 S0 G; f5 E3 L2 oNegative correlation, 负相关 W) c# f1 z+ v. j
Negative linear correlation, 负线性相关8 o7 ?6 M, E3 n% D9 \6 Q9 A3 D% R; k9 n
Negatively skewed, 负偏$ i( C( k" b. Y; U2 s% Q& x
Newman-Keuls method, q检验" M2 i$ C3 e4 U( f5 c
NK method, q检验
. Q7 N# B. f2 L% jNo statistical significance, 无统计意义5 v" R& r5 |+ m/ c) ^
Nominal variable, 名义变量
. d& H8 @: i" O3 lNonconstancy of variability, 变异的非定常性
( }' c f. G+ GNonlinear regression, 非线性相关
$ w V9 o4 q- l* |Nonparametric statistics, 非参数统计
' W. O5 f2 Z7 sNonparametric test, 非参数检验
: E1 w( P7 ?& g' A, n6 eNonparametric tests, 非参数检验
3 P, v: a4 C' z! |Normal deviate, 正态离差6 v5 ~7 e! f `& M, w' T4 v
Normal distribution, 正态分布" \2 [# N' ?7 \5 C8 d
Normal equation, 正规方程组
. B# O# E7 }4 c$ h/ _" INormal ranges, 正常范围/ i0 Y7 a, M6 o, |9 Y
Normal value, 正常值$ T. o5 N( X5 U' C
Nuisance parameter, 多余参数/讨厌参数
# G3 j/ l( A: [0 }* bNull hypothesis, 无效假设 8 l; x* y5 x: G/ ~" t3 }; C
Numerical variable, 数值变量
% t8 ?. z& ~9 iObjective function, 目标函数
9 n( z/ A2 U+ r4 y! v. D: W" KObservation unit, 观察单位( S" C+ v2 d! r, W6 y
Observed value, 观察值
; N5 l9 C2 J5 L2 b$ N; C* `1 WOne sided test, 单侧检验
4 K# { z. P6 @* U, s% ?One-way analysis of variance, 单因素方差分析6 z2 l& j0 m j
Oneway ANOVA , 单因素方差分析
$ k6 m4 ^ N5 o8 \: M. sOpen sequential trial, 开放型序贯设计
0 K% Q) k5 ?2 ]7 b. Q2 ^1 c, P2 qOptrim, 优切尾4 O7 A q1 ^% M+ x* z, b
Optrim efficiency, 优切尾效率
! n( a! F$ T( q1 V5 eOrder statistics, 顺序统计量" s5 V6 P, C0 F& [. t8 R
Ordered categories, 有序分类* A0 X. z" e. y5 |" r
Ordinal logistic regression , 序数逻辑斯蒂回归2 B5 Y4 a/ M% o1 ~8 w+ W {+ o
Ordinal variable, 有序变量
; r& H& u8 J: m$ h& i3 J5 BOrthogonal basis, 正交基1 y2 P- y( r& B) U. v! x; T, ]
Orthogonal design, 正交试验设计
1 Z9 E2 J, _* j; o1 E0 ?Orthogonality conditions, 正交条件
2 s# `0 [* ?% I5 e7 b+ ^8 E) }ORTHOPLAN, 正交设计 % F h2 N$ u0 \2 N: |
Outlier cutoffs, 离群值截断点+ A8 H* g( p& Y: k: \5 E) @ n+ f
Outliers, 极端值
5 P# l1 C8 x/ T: gOVERALS , 多组变量的非线性正规相关 & U* _2 i; D6 V9 L8 s$ n" e
Overshoot, 迭代过度7 Q+ b# _- T. P% |8 U
Paired design, 配对设计; Q; e! E% o+ F' z8 r
Paired sample, 配对样本5 c5 x6 ~/ s$ t1 C% d7 P
Pairwise slopes, 成对斜率7 i3 p$ A4 D& C& X
Parabola, 抛物线
5 a$ L! P1 R: Q& s2 E; EParallel tests, 平行试验
9 x) _2 ~6 G) A% U$ b4 {+ MParameter, 参数
1 ^. L6 b7 v0 f( Q- Z. k; U$ l' FParametric statistics, 参数统计
! Q+ s- |4 r9 r% L0 QParametric test, 参数检验5 g) _$ s4 F: S. @, K+ S! b
Partial correlation, 偏相关$ p. q! J" K' _# Q
Partial regression, 偏回归
% X/ u5 ~3 c' F: ePartial sorting, 偏排序
. y. b- B/ \! e8 ?0 J, z' CPartials residuals, 偏残差 B* H0 C* C1 r: K& H( u8 e8 P
Pattern, 模式2 K) g: a; M5 c/ R4 u; Y8 [# M' E+ P
Pearson curves, 皮尔逊曲线5 r. |! d" f& e9 P' X9 _1 T0 ?
Peeling, 退层
, @1 \! S$ ]: x- e$ y0 cPercent bar graph, 百分条形图
3 C& [& N3 Q3 O7 KPercentage, 百分比
/ F4 o* v% t1 _7 ^4 WPercentile, 百分位数
9 J7 w) p4 H3 ^% W' b0 y8 UPercentile curves, 百分位曲线/ ^1 t( t5 _% Z1 `- b+ |
Periodicity, 周期性- s7 F0 p& z4 Z! e9 Y) l* G* ~
Permutation, 排列( f* ]. X% Z R$ T b% c2 ]
P-estimator, P估计量' `: y9 B: `' G; u9 x
Pie graph, 饼图
, X: {; U6 G; I6 H7 Q5 FPitman estimator, 皮特曼估计量
1 D& C- ~7 \/ W7 p8 p: aPivot, 枢轴量5 h* f; {& ~9 T2 k
Planar, 平坦
5 d8 K2 F7 y$ c7 sPlanar assumption, 平面的假设" Z G t4 s2 ~6 B; o$ ^: Y3 B
PLANCARDS, 生成试验的计划卡! ?8 g+ s9 f; _2 i9 j3 Y
Point estimation, 点估计
7 b4 G8 K V, y& F* A' D- ~+ hPoisson distribution, 泊松分布
& ?2 _" M3 y* Q; V' nPolishing, 平滑
) y" w0 t+ Q' w; ]* B! y% H* oPolled standard deviation, 合并标准差3 i4 w- v5 R8 h: L, A$ e! t
Polled variance, 合并方差/ W9 B% W* S U# a% \7 ], O
Polygon, 多边图4 L/ P0 _- W: t9 G
Polynomial, 多项式
' x- o/ E w$ d3 |Polynomial curve, 多项式曲线8 G+ g" h" D/ Q/ x
Population, 总体7 d. l$ g" {! g ]3 r* o
Population attributable risk, 人群归因危险度
/ E) Y0 P% d% m" q% f; k/ K3 ?Positive correlation, 正相关
3 ]0 g; e+ A, r7 C4 z1 j% QPositively skewed, 正偏 P |4 y }$ `# W' v( W& H
Posterior distribution, 后验分布 U/ {7 V B# W1 M4 z9 P8 u3 \) o; u
Power of a test, 检验效能/ A1 u5 u5 D* g! K
Precision, 精密度8 z% S j' V# V3 A/ g' @2 ]
Predicted value, 预测值
' W: w3 r, N: | U* Z1 [4 xPreliminary analysis, 预备性分析
9 y% |8 U' c7 ?$ L$ f( B4 FPrincipal component analysis, 主成分分析5 b) n. @, K8 L
Prior distribution, 先验分布
+ P. s3 C6 ` f4 VPrior probability, 先验概率
; O3 i7 N! A" [7 s. O7 }; f" j+ [3 `Probabilistic model, 概率模型% M: K8 p+ B8 W7 m, Y. h5 j$ r
probability, 概率
' l3 ?. a4 D q" A2 AProbability density, 概率密度* P# c. n& T( j
Product moment, 乘积矩/协方差 s' C& Y" `5 ]2 J. S% L+ e
Profile trace, 截面迹图! z7 }) p7 Q/ ?8 M9 x4 f. ` v
Proportion, 比/构成比
. F4 ]1 U4 S, Q" [1 I9 \" h: CProportion allocation in stratified random sampling, 按比例分层随机抽样
" o6 y# P! k. u4 V: d2 l$ B @Proportionate, 成比例
. x# Y2 I2 G+ i. `# d3 I& q& WProportionate sub-class numbers, 成比例次级组含量
4 ^' P; y; H) E: R% a( {Prospective study, 前瞻性调查 Q, x# A, S1 a5 m7 l7 V ?
Proximities, 亲近性 ) J* K% M- q/ ]8 c3 W$ c
Pseudo F test, 近似F检验; q) |2 I# R* h6 k6 b: h& J
Pseudo model, 近似模型
. o* _/ I/ u- p2 _ nPseudosigma, 伪标准差6 v9 h! o, W# d/ G3 c- r7 Y
Purposive sampling, 有目的抽样+ r6 F$ u& u5 U4 s
QR decomposition, QR分解
5 H, m) h$ I- U' k, B/ g( |. {Quadratic approximation, 二次近似
, K g% |% z& Z0 LQualitative classification, 属性分类' W" r. x: u: U
Qualitative method, 定性方法
- b# T2 Y' [; |. L& [5 mQuantile-quantile plot, 分位数-分位数图/Q-Q图, V" P# c m$ ]1 i& s( ?
Quantitative analysis, 定量分析; E2 M: h& _0 |1 n
Quartile, 四分位数
8 w0 W8 G- i3 s! j. bQuick Cluster, 快速聚类) g% X. d* @% G8 i# J4 d
Radix sort, 基数排序" b1 d: R: f* [9 P
Random allocation, 随机化分组- c! d, n2 y* F6 a3 f% ~ _
Random blocks design, 随机区组设计, o/ ]5 w/ X: G$ P5 ?! K' X
Random event, 随机事件
! Y2 P5 B5 y6 `3 k6 CRandomization, 随机化; f- D( H6 \, `' X
Range, 极差/全距! ~2 ^3 q2 W8 p
Rank correlation, 等级相关
$ K" o% u u/ n3 }" IRank sum test, 秩和检验
9 ?" H2 X$ ~% E( c' J. GRank test, 秩检验* T0 c3 y" Z) N- W8 }3 p
Ranked data, 等级资料/ u. q) K, ]8 R: i6 {- S
Rate, 比率7 }8 h( v4 y/ r" p
Ratio, 比例
5 G' p* S; V. G1 QRaw data, 原始资料
. N( m+ q' S3 t+ |$ W3 L3 L eRaw residual, 原始残差. h5 o, ~0 z6 U' c# ]* m1 i( [- e
Rayleigh's test, 雷氏检验
3 p4 L' \1 d/ RRayleigh's Z, 雷氏Z值 2 `3 t" Q; N0 a" G% X8 T w
Reciprocal, 倒数/ X- M; [9 A' X# |' f0 K9 w
Reciprocal transformation, 倒数变换
8 d$ C' r2 ~: Y0 IRecording, 记录4 S( _1 U$ @3 A3 ^8 q2 @8 p
Redescending estimators, 回降估计量. \& f: S# N6 z+ r3 l
Reducing dimensions, 降维, `, Y! N8 s' K( F2 @% {; m% s# f
Re-expression, 重新表达
?3 R% d* m2 Q+ T6 [( d) a/ kReference set, 标准组
2 o3 n, Y: w1 p1 ?: HRegion of acceptance, 接受域
! F+ o1 r0 z* K) P/ yRegression coefficient, 回归系数
* J* {& e8 T$ A @Regression sum of square, 回归平方和
5 K7 o- {! P7 ^% @3 r6 ARejection point, 拒绝点0 i# o6 y7 y, ]9 J/ _' I3 k3 f
Relative dispersion, 相对离散度
# \, u( f9 \2 | k4 y p$ |Relative number, 相对数
; i g3 Z' k2 x. o. h/ T' a) PReliability, 可靠性6 \! y) |, v- X# P' v7 D
Reparametrization, 重新设置参数8 R- M! p5 S5 c3 @" l$ Y Y
Replication, 重复) @: B1 W* K9 o: W
Report Summaries, 报告摘要- M- D+ Y" }: A9 ]7 o
Residual sum of square, 剩余平方和
$ z+ U; E3 ?) D) H7 q1 @3 Y6 KResistance, 耐抗性
# [. D( @5 b0 Y, S" wResistant line, 耐抗线
5 |$ ? B8 m4 q4 r F; B7 B: E7 g. \Resistant technique, 耐抗技术
+ D4 ^' U4 I. r$ y4 R/ tR-estimator of location, 位置R估计量+ H/ g: {% x7 D0 }; k2 z6 W
R-estimator of scale, 尺度R估计量
7 |( Y4 C) u5 h( O+ ORetrospective study, 回顾性调查9 K7 Z8 A3 V2 ~
Ridge trace, 岭迹5 L r0 S! A0 Q2 A1 B
Ridit analysis, Ridit分析
! V( \5 i. T" x. d0 S3 k2 w4 wRotation, 旋转
. e3 T p5 h' jRounding, 舍入
, K# p$ i" V; E" E$ c8 lRow, 行
# b9 f ^' |- j" q3 |$ u" @Row effects, 行效应
. t. z4 m$ R1 z3 l7 |& fRow factor, 行因素& [& J) n; n+ q" a. K) ~4 Y
RXC table, RXC表0 O. k7 A" i% `. K& d6 n, u4 D% k
Sample, 样本
& ? y: W: N) A" oSample regression coefficient, 样本回归系数
: _% h! n1 m0 ]3 L- uSample size, 样本量3 T6 Q% i* B' c& P
Sample standard deviation, 样本标准差
( V9 R& B1 [" v' p+ qSampling error, 抽样误差
! x/ h+ z4 r) I; ]7 ~5 ]! y7 b& d lSAS(Statistical analysis system ), SAS统计软件包
+ d2 V g, g6 v1 c$ W9 U3 Q6 j/ EScale, 尺度/量表6 r0 p( v4 v& E/ @7 e p# B, s8 g
Scatter diagram, 散点图
- _4 `$ m8 ? d2 z$ ~- ?Schematic plot, 示意图/简图8 w6 L2 b4 g5 `0 [" x7 u& Q
Score test, 计分检验
" X/ \ s4 }9 a9 Z2 O# x) [Screening, 筛检7 j7 _, e/ c/ f. }2 v
SEASON, 季节分析
( V! H$ W& x) \" c# ^Second derivative, 二阶导数$ e8 o# C2 B* \" Z$ d
Second principal component, 第二主成分& y# v+ [$ D7 i' n$ o
SEM (Structural equation modeling), 结构化方程模型 2 e; b$ b p* P; e5 `7 M
Semi-logarithmic graph, 半对数图
2 ^! U+ {6 H' o i3 ^$ Y' C2 [Semi-logarithmic paper, 半对数格纸
. U* q6 U; f) m, HSensitivity curve, 敏感度曲线* c. i7 `# Z' B( T$ I
Sequential analysis, 贯序分析
3 g+ m* T# R& l9 L' U! i; L+ d! L# {Sequential data set, 顺序数据集7 j* x6 Z) }% \) @4 g: D3 L
Sequential design, 贯序设计: ]# S7 l8 u9 T: i) c/ {' `0 z
Sequential method, 贯序法4 P8 a; E+ K% @2 a4 w
Sequential test, 贯序检验法
: v& \# D, Y) X) l. PSerial tests, 系列试验
4 |+ q( h$ r& _5 OShort-cut method, 简捷法 5 z% K T- C% u5 D& O
Sigmoid curve, S形曲线) [: s) V! G( P# ]$ I
Sign function, 正负号函数
1 e3 j8 `1 {; \! }" S7 CSign test, 符号检验+ Q$ \4 N3 Z( X8 c2 ~/ p4 Z' Y
Signed rank, 符号秩
3 W" W- i. X3 t4 Q& m5 ZSignificance test, 显著性检验* r( `* \6 S _- k; l; ~- A
Significant figure, 有效数字- `: i1 u" y$ }) c2 B! F
Simple cluster sampling, 简单整群抽样2 V* f* k: D3 M3 V: l$ P' P: y
Simple correlation, 简单相关
4 ~6 O$ d% w! l. W7 R3 Y. q8 H. ]( lSimple random sampling, 简单随机抽样
: p* M: o! p1 j/ Z4 fSimple regression, 简单回归
6 ?' a0 r( Z6 Lsimple table, 简单表 A4 ^# q+ W0 r! L
Sine estimator, 正弦估计量& m5 W( K* u/ Q
Single-valued estimate, 单值估计
# b3 b8 c' x. [* W' [5 n; }. m7 rSingular matrix, 奇异矩阵
2 f( ^; h7 ?" u6 C, }# Z# v! v+ ASkewed distribution, 偏斜分布
. B8 j9 @7 _9 Q+ H6 A' n0 @7 ]Skewness, 偏度1 X. _1 i" s* ~% o- l f
Slash distribution, 斜线分布
# _& G& N& q3 K, ]; fSlope, 斜率
, O$ f. D# O$ x0 qSmirnov test, 斯米尔诺夫检验1 a: D) S. r! g: p
Source of variation, 变异来源
: ~* w; i/ h6 v3 b# HSpearman rank correlation, 斯皮尔曼等级相关
+ v& o, U' S: l4 F* ^* A* j+ z5 \Specific factor, 特殊因子
6 @7 I$ d# c. M" G* |Specific factor variance, 特殊因子方差$ J& _! A8 l% c# u
Spectra , 频谱4 A; n. T, ~0 b2 _$ U( D
Spherical distribution, 球型正态分布
9 L! o$ J* F# M/ J* eSpread, 展布' W7 L, W& n# [& H2 o/ t: a0 ?
SPSS(Statistical package for the social science), SPSS统计软件包
8 Z' D" v# d8 R. M9 F4 q7 BSpurious correlation, 假性相关
6 Q& @- o' ]) r; H6 mSquare root transformation, 平方根变换
9 ]& s* k( e$ a9 S% iStabilizing variance, 稳定方差8 |$ b8 P0 @8 h6 k% y- v/ T
Standard deviation, 标准差
8 {( ]* D' q/ I% W! g2 gStandard error, 标准误- f/ Z, \) _, r/ d8 S
Standard error of difference, 差别的标准误
4 ^7 _1 K2 ~! _/ EStandard error of estimate, 标准估计误差2 H% i) J$ x$ g0 k; ~
Standard error of rate, 率的标准误; U2 ?& t# ?+ f) |8 d( m" b
Standard normal distribution, 标准正态分布
" E0 e2 I* R8 O% y; c- l# K% \Standardization, 标准化! u6 C# \" A0 y0 G
Starting value, 起始值' D. O% c5 E* R5 D) W1 I
Statistic, 统计量
0 a9 O; {% K& ?. rStatistical control, 统计控制3 D9 u" k" q5 t# R; F; v
Statistical graph, 统计图
6 X/ W3 i- v h7 Q& v. m( U3 M0 L) y# y3 UStatistical inference, 统计推断; H: x3 _: G' y5 X! z4 L6 @
Statistical table, 统计表
N& h! w/ ~ c0 B5 T5 A+ Z. LSteepest descent, 最速下降法
" K0 L/ i8 O" A& D, b+ U2 MStem and leaf display, 茎叶图
. T3 o( B5 S8 o1 m! RStep factor, 步长因子
* K: @4 F9 x. e8 g" xStepwise regression, 逐步回归
2 C' F. D+ [" b( t1 ~) ~Storage, 存
( t% Y7 w ~1 {0 ~5 Z) G6 m# bStrata, 层（复数）
+ e# B8 M' X6 \( I( u5 fStratified sampling, 分层抽样
J" k2 `7 S i; H- s; `Stratified sampling, 分层抽样
& a$ O. }( J! S4 F& M( ]Strength, 强度
% k: L& K7 j2 P1 V" t$ }/ NStringency, 严密性% n2 ~- S" b; X; _
Structural relationship, 结构关系. h3 K7 l! r& m2 x1 S
Studentized residual, 学生化残差/t化残差/ c3 c% F. k- N6 A* u
Sub-class numbers, 次级组含量- R x- ~6 o f7 @. q+ u9 ~
Subdividing, 分割% @, p) e- r# v1 ]
Sufficient statistic, 充分统计量2 R& ]0 t2 V& h3 X: U
Sum of products, 积和
2 Q5 ? ? ^% }8 q& GSum of squares, 离差平方和
5 C4 o2 `( o4 mSum of squares about regression, 回归平方和, U- L8 r9 S2 e
Sum of squares between groups, 组间平方和6 q4 u% O# y& U) |
Sum of squares of partial regression, 偏回归平方和1 J! l- T* Y2 Q
Sure event, 必然事件
8 k+ B; C! {0 P" Q# p* a7 n5 rSurvey, 调查# ]) _7 z) g0 p! T
Survival, 生存分析) e/ w3 M s+ d
Survival rate, 生存率
- i, k* T6 w! w0 g6 E4 q+ l" mSuspended root gram, 悬吊根图7 }1 d$ E; z& I$ y, t+ u
Symmetry, 对称
5 J4 ~# c/ s U- T8 N7 Y: a GSystematic error, 系统误差; ~& [% E; v: f; e% Q- s# Q. h+ E1 Z
Systematic sampling, 系统抽样1 ~+ D) g5 W9 Z2 z% k, u
Tags, 标签
/ W1 }! _5 g( H, p" |Tail area, 尾部面积) n& X6 n+ _8 N: z5 j+ h; K
Tail length, 尾长
' Q: W' I7 a: T3 vTail weight, 尾重
3 J4 _ }; x) {% RTangent line, 切线
8 K0 t( ]$ l$ [9 g/ @7 Z; k+ y$ STarget distribution, 目标分布
8 x- C2 M8 a/ V* e6 hTaylor series, 泰勒级数
$ x' s9 H& o# }2 S+ j. qTendency of dispersion, 离散趋势
4 I; ~3 S8 K y: z/ v3 w# L" _6 {Testing of hypotheses, 假设检验
, m. O0 f6 h5 B/ x" r6 pTheoretical frequency, 理论频数% y* y1 u" N1 }% C' }7 R% k, O3 W! X4 {
Time series, 时间序列
, f; o8 f1 Q, s' [* A2 xTolerance interval, 容忍区间. N9 r# _3 u: G) h3 @9 j% b
Tolerance lower limit, 容忍下限
- r, {: t& N+ i, s! f; U1 `, a& D2 dTolerance upper limit, 容忍上限' r! U6 w7 e7 h ~
Torsion, 扰率! R4 l7 |% m! U8 n% A, ?( v! \
Total sum of square, 总平方和
# h5 `4 Q1 Z5 B. j' rTotal variation, 总变异4 g* v/ K* ~( Q/ F5 a/ H8 i' W) O
Transformation, 转换% A6 Q( O" R0 Y
Treatment, 处理
( l1 `5 L6 f) B& r! a6 OTrend, 趋势
; y7 Q6 G9 L: STrend of percentage, 百分比趋势
2 H# c) e- X! X0 s9 aTrial, 试验5 L. Y6 ] S; d& q- }7 \& z
Trial and error method, 试错法1 R: ?0 E6 ?2 x8 e8 f2 s: d
Tuning constant, 细调常数
/ k a: X7 m. h" \- K, eTwo sided test, 双向检验
7 _- D+ m" k; e8 `: Q. oTwo-stage least squares, 二阶最小平方2 w7 x9 t' `% T$ N
Two-stage sampling, 二阶段抽样0 D: V( o" J' {5 t) Y) f
Two-tailed test, 双侧检验
* B/ f! U% j+ g. Z! k, w5 TTwo-way analysis of variance, 双因素方差分析7 U. ?( L& O1 S' m+ f
Two-way table, 双向表
) R0 I; [3 N: ?1 ^! g# bType I error, 一类错误/α错误
1 Z. F Y0 V* w% O7 t7 rType II error, 二类错误/β错误
. b* H7 p' i$ g9 }9 k+ N; b8 WUMVU, 方差一致最小无偏估计简称/ @' I$ e& W: p4 f
Unbiased estimate, 无偏估计
2 a8 }# E- {6 o1 { r2 W% O7 q6 y% DUnconstrained nonlinear regression , 无约束非线性回归 V1 }4 K* l |% X4 [7 X& L
Unequal subclass number, 不等次级组含量
3 K7 P) ?1 n( A% {( LUngrouped data, 不分组资料+ G; q& r( w5 Y1 j0 M( W
Uniform coordinate, 均匀坐标
0 {5 o( d5 g/ G! S) K/ A; nUniform distribution, 均匀分布8 \+ B5 T. ?: Z( w$ x
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计' r, a ^9 n! S6 O! j3 s
Unit, 单元2 h- [+ H& U# V3 Z/ a
Unordered categories, 无序分类2 v- V" g6 I8 t j3 n
Upper limit, 上限, k* x5 D: ^6 |1 V
Upward rank, 升秩
, {( a5 I/ T8 L9 V, |# V' @# ZVague concept, 模糊概念
" d* k+ J) C M, {, y; B- ]Validity, 有效性/ s! ^6 `& @( P9 d: x" R& z: U
VARCOMP (Variance component estimation), 方差元素估计
; p5 x5 {/ Q* q q' Y" KVariability, 变异性' a: G$ B0 \! |
Variable, 变量2 ]- B- r( D6 q. w K) T9 ~
Variance, 方差
3 D& x2 D! E% T) ]( ~1 q gVariation, 变异& \) p3 U$ W& O6 Y" K; ^8 f, I! u3 _
Varimax orthogonal rotation, 方差最大正交旋转
' [6 ~1 Z; x0 w6 Z" @& b7 I0 i) ~Volume of distribution, 容积
U& z: N) C; [( c0 AW test, W检验
- k R7 M C5 `$ H2 |# `7 TWeibull distribution, 威布尔分布( O# Q) A. f' z4 S
Weight, 权数) U& R( V4 Y8 W, U& H4 M8 M
Weighted Chi-square test, 加权卡方检验/Cochran检验9 z: R: ?, U+ i4 T
Weighted linear regression method, 加权直线回归- _. V8 T. @$ g* w! A
Weighted mean, 加权平均数7 t; E# L/ a, {* H
Weighted mean square, 加权平均方差
! ^$ k! H% i' i& R ^Weighted sum of square, 加权平方和, m) w2 l/ E" j7 T* \
Weighting coefficient, 权重系数7 u! r: K# R7 q, f5 ]. R
Weighting method, 加权法 ; t1 {7 {6 _7 a" e
W-estimation, W估计量" y) M. H' }+ r& D
W-estimation of location, 位置W估计量8 Z% t$ k7 g& ^' } u
Width, 宽度' s9 e" ~ }7 ~& _& x
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验6 @1 B- Q. z: @* z
Wild point, 野点/狂点
2 W8 T: y4 {3 R/ ?2 Q7 wWild value, 野值/狂值
: x! B' n! ~- k0 ]+ RWinsorized mean, 缩尾均值( A+ `+ A1 r# o$ \$ M8 F; r
Withdraw, 失访 - @& G" b0 p6 Z4 F5 j
Youden's index, 尤登指数* q# e, y( z! m! h# s
Z test, Z检验
+ {3 c# y; I* p7 v, zZero correlation, 零相关) |. c& J) c' l' _4 j( D; }: D
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
