|
|
Absolute deviation, 绝对离差" T0 u5 | v' a0 J% F+ Z1 P
Absolute number, 绝对数
% u1 B4 |. e7 f$ y$ tAbsolute residuals, 绝对残差
" k0 c1 [& g/ S$ TAcceleration array, 加速度立体阵' y5 b6 e+ l4 b, \( J2 N
Acceleration in an arbitrary direction, 任意方向上的加速度. L5 J: {7 W+ J% l p$ d2 W
Acceleration normal, 法向加速度
9 ^7 l. L$ A" n7 A5 s+ i+ WAcceleration space dimension, 加速度空间的维数3 G& s) H0 A! D) q) c5 w+ P0 K3 u" O
Acceleration tangential, 切向加速度
4 c' H& P ?& j, ^( CAcceleration vector, 加速度向量, z; h& ]- M! m' ~3 C3 R4 V
Acceptable hypothesis, 可接受假设
9 s X% G8 M4 P7 aAccumulation, 累积( m" Z/ W0 D4 C" C/ |+ u
Accuracy, 准确度
+ d f1 G. i4 @! q) b5 l; FActual frequency, 实际频数+ c) B1 [* a9 U, A, b- {7 U
Adaptive estimator, 自适应估计量# |! w7 ~( \1 B* C; b% ~& d: d
Addition, 相加
* {% W; E! X j. f3 o* d0 fAddition theorem, 加法定理1 j0 A- e9 ^: Z7 B
Additivity, 可加性4 d2 I4 p1 r: a& M1 O
Adjusted rate, 调整率: e1 ^& O+ C1 q( q
Adjusted value, 校正值; X Y7 T- I h) w" I
Admissible error, 容许误差) X# ?+ |+ `$ f7 i* ^; Z( A' N; \
Aggregation, 聚集性
$ ` v- d4 B& I! N/ |) C! T& mAlternative hypothesis, 备择假设
% k9 f( l3 p6 u6 u4 v: h) t, RAmong groups, 组间! u" t1 v+ R9 @" C- i
Amounts, 总量
- X( d/ O& b" F% L |; eAnalysis of correlation, 相关分析: B$ \- N2 \) F, J/ F6 a9 D
Analysis of covariance, 协方差分析
6 ~4 o$ e" `7 r1 iAnalysis of regression, 回归分析
4 s! i- f) Q9 x4 X, w0 EAnalysis of time series, 时间序列分析" d& Y7 m- `3 A
Analysis of variance, 方差分析' x% q2 z. E- R" V2 r- k' f- s
Angular transformation, 角转换
8 r; G6 q/ h! K9 X+ N( oANOVA （analysis of variance）, 方差分析1 u. ~9 S0 X1 r8 v* l
ANOVA Models, 方差分析模型
0 j% Q1 a' {+ ~: RArcing, 弧/弧旋
9 V/ t: {, x, u+ {Arcsine transformation, 反正弦变换, M. X+ E$ i! k# O
Area under the curve, 曲线面积/ \9 `3 h. N* r
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 % D% c8 c# L1 F6 M6 Q
ARIMA, 季节和非季节性单变量模型的极大似然估计
8 Z1 o8 l: }9 wArithmetic grid paper, 算术格纸
8 O0 R6 R! ?# o! V8 JArithmetic mean, 算术平均数; p- ^3 J& k# d- |8 y
Arrhenius relation, 艾恩尼斯关系
1 b* P, q4 K0 u+ q9 ~7 f' G& ^Assessing fit, 拟合的评估7 c" A0 B `1 K: v2 d: r3 b
Associative laws, 结合律
3 M: \, e; G: s% @' d+ hAsymmetric distribution, 非对称分布 Q( }% K3 v! W0 Q' Y. k2 B$ d( E$ F* z
Asymptotic bias, 渐近偏倚& K ^5 Q6 y( E9 V) n5 J4 x6 X$ N
Asymptotic efficiency, 渐近效率% @; n: S# S# q9 i6 {7 R& s! ]2 d
Asymptotic variance, 渐近方差
0 |/ q! {5 H0 Z+ F% G- B4 e* n0 aAttributable risk, 归因危险度
5 a. R8 G/ K- n& `/ ~Attribute data, 属性资料
b1 R+ b4 Q4 v9 @; j( d' C) B/ U$ aAttribution, 属性& m& ?2 l; P5 c4 `0 B. n8 y
Autocorrelation, 自相关
5 q" B$ f: c. h# e4 o! D: rAutocorrelation of residuals, 残差的自相关
; l' q# J( N1 y3 ? |Average, 平均数. t2 ^* B2 r. o
Average confidence interval length, 平均置信区间长度: {2 f$ k5 k3 `& T+ ?
Average growth rate, 平均增长率
( m! L d+ E2 p S- PBar chart, 条形图
% Z7 E/ U) y+ W% w/ eBar graph, 条形图
- S9 j. l8 K3 ^7 A1 Y! C6 ?8 uBase period, 基期
* J3 U' T- _5 A2 h* H o# iBayes' theorem , Bayes定理6 t4 N8 k* I6 i4 T6 A3 c, u4 T
Bell-shaped curve, 钟形曲线/ [3 p8 I, Q' S9 G% U& m
Bernoulli distribution, 伯努力分布6 \& `, Y8 {5 ^# W
Best-trim estimator, 最好切尾估计量
! I, M) a. z, g4 N* L8 xBias, 偏性& e$ Z; @4 E0 K1 a: [6 V: C1 ]. W
Binary logistic regression, 二元逻辑斯蒂回归
( y7 c& d3 C1 UBinomial distribution, 二项分布
5 Q2 D9 C/ M, e) J' uBisquare, 双平方 F7 V* Z$ Y5 h2 i! c$ x: z: _
Bivariate Correlate, 二变量相关8 X+ h+ N0 g/ t: ]4 \7 F
Bivariate normal distribution, 双变量正态分布! U; K% d$ c: C8 g: |" c+ S/ h3 n
Bivariate normal population, 双变量正态总体
' Y( n9 [8 S- G5 ^ ?. _. _& K; f9 ^Biweight interval, 双权区间
6 M) Q; d) M, l* k# B8 o P4 ZBiweight M-estimator, 双权M估计量
4 X' z5 a! V/ Z: ?Block, 区组/配伍组
* q* a+ E8 ?! e: G4 t, X- ?" A+ kBMDP(Biomedical computer programs), BMDP统计软件包2 a; F3 Z' r2 {/ r
Boxplots, 箱线图/箱尾图
8 @* [; t1 u! J& d4 x( d/ Y, L0 _Breakdown bound, 崩溃界/崩溃点
9 _4 c. g0 j$ X/ ^. C( r" `7 uCanonical correlation, 典型相关
$ w! Q9 \ @5 }9 ]* E% _% LCaption, 纵标目( h R7 V' H8 w9 R
Case-control study, 病例对照研究
8 F- t r8 _0 e0 A7 R- ?% `Categorical variable, 分类变量: u. S- A+ f/ m
Catenary, 悬链线+ T. D0 H& k2 b: k- ]; S
Cauchy distribution, 柯西分布
/ r9 H* H+ H9 t, v) ICause-and-effect relationship, 因果关系5 Q+ ]1 X" {" T$ r% U/ s
Cell, 单元3 T0 ~4 V' |8 h
Censoring, 终检0 S( p: b. \. N' d
Center of symmetry, 对称中心
5 C k: x1 q. m. _; [! ECentering and scaling, 中心化和定标4 _0 T5 e Z) W7 u8 D) x
Central tendency, 集中趋势
4 @% N, \- L! Z6 u" a. b; X+ cCentral value, 中心值
4 x) @2 z' z: D) ~: N$ v$ Z+ D7 e0 mCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
" S% D" S; p+ ?* o3 nChance, 机遇
% S- }5 U' p5 HChance error, 随机误差0 T D/ ?! q3 p4 c' e) v9 F
Chance variable, 随机变量% Q J2 }4 }0 X; v/ x" I7 Z) V' [
Characteristic equation, 特征方程0 l# N# |% H& `. \ S7 B% r( D
Characteristic root, 特征根
3 x; \7 y: y0 E s9 X* } }) YCharacteristic vector, 特征向量
( G1 O3 V2 r& O- Z" ~Chebshev criterion of fit, 拟合的切比雪夫准则
8 Z7 z- D" \; @: Y/ qChernoff faces, 切尔诺夫脸谱图8 Z% H& n, z' p* e* r0 B- p: G
Chi-square test, 卡方检验/χ2检验
, m7 C6 a u! h! o. ?Choleskey decomposition, 乔洛斯基分解) [; x. d: E* G: R: J/ r
Circle chart, 圆图
* B6 M2 v) u+ t CClass interval, 组距* ~5 S% H/ a! V7 f I: L
Class mid-value, 组中值
& E; t) ]" W# b0 `1 i% X# Y' ]Class upper limit, 组上限- t9 b$ R+ L n( S3 {8 C- C) V
Classified variable, 分类变量% ~2 x/ c" j! a2 f9 h+ q9 V8 j4 |$ \
Cluster analysis, 聚类分析
% o: O( N8 {% }9 n6 G/ e. \Cluster sampling, 整群抽样$ m6 y5 b& ~ B' w$ n# w- i8 q
Code, 代码
7 I5 @7 T5 J4 s! D& G& L/ aCoded data, 编码数据/ {; E# r2 T" g' U! A9 S: W
Coding, 编码. D' J3 ^, A) o% r
Coefficient of contingency, 列联系数
d1 j) J: x, d# _Coefficient of determination, 决定系数5 \7 B" e u8 f' L
Coefficient of multiple correlation, 多重相关系数! s) [' M/ M Q0 h
Coefficient of partial correlation, 偏相关系数3 N+ T" z/ `( X' Y3 G; D
Coefficient of production-moment correlation, 积差相关系数7 F$ J. O& _5 F+ V6 S) C$ f
Coefficient of rank correlation, 等级相关系数6 i- Y2 B" A, N- P) Q
Coefficient of regression, 回归系数/ h1 ]! r" P$ K% ^: G
Coefficient of skewness, 偏度系数9 p9 d1 G: A" e1 z
Coefficient of variation, 变异系数
% ?6 n2 j3 G" I( ]6 m2 P3 gCohort study, 队列研究
) w+ g% S, O4 N) ~4 V: D& l$ VColumn, 列3 q4 _& z' F- H# X3 h, W% ]4 J
Column effect, 列效应( b7 H I, ~5 e( E
Column factor, 列因素/ c2 t2 v+ T) O2 ?
Combination pool, 合并* C8 k2 ], u8 f8 V' c
Combinative table, 组合表 n) g9 u% V: f& _% H* j
Common factor, 共性因子
' Q1 ~# P; i/ p, B: sCommon regression coefficient, 公共回归系数( E/ D+ U( m0 q" C* z7 s
Common value, 共同值9 c" w: @; ]9 {+ t" \7 J
Common variance, 公共方差
{2 b' \% h. A# R( rCommon variation, 公共变异
7 l; N5 @3 l' e* cCommunality variance, 共性方差
9 P8 y8 o( V7 h5 G9 E$ uComparability, 可比性
. f8 [; c. f) U: K/ s2 z4 ^Comparison of bathes, 批比较
! ~9 s8 j( a# D* QComparison value, 比较值, E( D* V' U8 i
Compartment model, 分部模型2 U$ W3 t/ g/ v: g- s; g& U, d) M. Q
Compassion, 伸缩/ r/ P3 {- |8 N0 F
Complement of an event, 补事件# H/ ]1 U( y# F6 m
Complete association, 完全正相关
1 { `" w. U0 |2 L: R) `Complete dissociation, 完全不相关
9 ?' |3 c8 \% j4 G' gComplete statistics, 完备统计量
/ j9 T! }& O8 q' C! @: ~8 |Completely randomized design, 完全随机化设计- y# L3 i( X) j. ]5 m; }. f
Composite event, 联合事件6 H; |3 D3 b- k1 ]/ ]( I4 x& k
Composite events, 复合事件
# D/ w' c, c" \/ s3 N* mConcavity, 凹性
) ^- s8 N0 x; s7 z& jConditional expectation, 条件期望- e" |+ }2 J* o: f: ~6 _
Conditional likelihood, 条件似然& u! I$ E- J+ L$ R. e3 N3 h; O; D# Y
Conditional probability, 条件概率. [- }* @- y5 j$ p- g8 S
Conditionally linear, 依条件线性* M. f- C! O m; G: H
Confidence interval, 置信区间, B2 ^6 U+ {! Y, F4 O" E; ^
Confidence limit, 置信限. a7 A f# s( O5 X
Confidence lower limit, 置信下限9 n9 S5 E# X' r
Confidence upper limit, 置信上限8 V2 P/ K0 y2 F& p: i/ N% x. E
Confirmatory Factor Analysis , 验证性因子分析
# C+ B7 L+ y7 ]0 v5 HConfirmatory research, 证实性实验研究
- L: L8 [: a5 \. x7 gConfounding factor, 混杂因素
7 e [7 Z' o/ r: wConjoint, 联合分析
! O( l& z8 ^& cConsistency, 相合性: H3 j( X. e- H5 w" y5 Z3 b J
Consistency check, 一致性检验7 d/ ]# y, J3 J' `& H% w% {
Consistent asymptotically normal estimate, 相合渐近正态估计
$ `2 E, b' s) l' D& @Consistent estimate, 相合估计
% O H; o ^4 Y/ p' \) a, ]Constrained nonlinear regression, 受约束非线性回归
! q' N9 b$ w/ r/ k) G' F9 F" G7 oConstraint, 约束
$ [* G& I* ^. d) @/ HContaminated distribution, 污染分布
' C4 ^" G) m+ t8 eContaminated Gausssian, 污染高斯分布1 o! u9 ]+ g% P9 ]
Contaminated normal distribution, 污染正态分布
6 a- Z& H5 k9 P+ i. I, [Contamination, 污染# N: H4 e' q n" O( F& d: o
Contamination model, 污染模型
" ?% c7 L7 L4 h7 {. ?2 `9 OContingency table, 列联表/ f1 w& q4 I7 d: ~0 }% y
Contour, 边界线
6 R9 m0 E. d5 y6 \7 C6 eContribution rate, 贡献率7 n# X5 J5 \' L- J: i H
Control, 对照3 e4 y1 g! e y7 w/ E2 _- o& t
Controlled experiments, 对照实验! y: ^ ^4 f0 j4 P* D M
Conventional depth, 常规深度- b+ \- C5 ]" ?: {
Convolution, 卷积# F, h: x$ M! H& i- `1 R
Corrected factor, 校正因子
: U' Z+ H. ?: j) b' S/ }# v, QCorrected mean, 校正均值& h. O' w1 O& w
Correction coefficient, 校正系数# Q0 \3 ?: H1 b* Z) R8 `* k! n1 u7 a
Correctness, 正确性
! u$ M/ f# `- nCorrelation coefficient, 相关系数4 r! W& D9 ], C2 \7 ?- Y
Correlation index, 相关指数, G- u7 f* C X) C3 T
Correspondence, 对应4 }5 W- p& w, C# c, W7 G$ H
Counting, 计数: r8 r, r5 P2 p7 r! a
Counts, 计数/频数( Y8 _) C/ k; m2 s: e& J
Covariance, 协方差 v% G4 m" I- k& _# E) J4 u, e
Covariant, 共变
* y$ h/ m# i. r% X( c9 K* L; rCox Regression, Cox回归
3 p- b, L& t! ?" B$ f% m |Criteria for fitting, 拟合准则- |$ A, U$ b; D L, k5 \$ X
Criteria of least squares, 最小二乘准则( D; ^9 \( z7 r3 {5 ^6 [
Critical ratio, 临界比0 B& l! L' F; i, o- E
Critical region, 拒绝域
4 r! a) l: s( R: H1 t- R3 P" f2 FCritical value, 临界值) l4 K0 U- O# F$ l) R
Cross-over design, 交叉设计
" U# C( u. w" l7 k& L# k$ b0 jCross-section analysis, 横断面分析
, w8 x$ L; \* q7 v: j+ P _: y- DCross-section survey, 横断面调查; c2 H- @8 f' u: R# |% \& l
Crosstabs , 交叉表
7 N5 U1 B3 L% n+ D9 T+ tCross-tabulation table, 复合表& w+ e0 y4 ]' \8 m4 J2 g
Cube root, 立方根. s+ k+ J5 I$ `6 [; W4 P
Cumulative distribution function, 分布函数
7 B4 L9 q' j' zCumulative probability, 累计概率8 `# l5 Q) q0 t0 w
Curvature, 曲率/弯曲: B/ z2 D0 ^1 F2 y& c
Curvature, 曲率' r& x# j* k& F/ Y2 Q% s" d' T
Curve fit , 曲线拟和
! E' {3 s7 o& O* y8 NCurve fitting, 曲线拟合5 o) v: \' X7 A" ~9 ?3 ?
Curvilinear regression, 曲线回归
: m/ P4 Q+ p- S3 RCurvilinear relation, 曲线关系1 f* C# g* }- {1 c
Cut-and-try method, 尝试法" d* W2 S& K# |" E
Cycle, 周期
8 A9 h: |( U9 I1 vCyclist, 周期性
$ v& _# D1 d; uD test, D检验
: D9 Z. j2 o0 V P9 l4 G: ^Data acquisition, 资料收集2 B, g7 F! I3 ^+ A% D2 K$ f
Data bank, 数据库
, J$ E, H! R5 ?6 ~3 W5 rData capacity, 数据容量* G: u7 C3 I) g& b* L* F
Data deficiencies, 数据缺乏+ ~, g: D8 B) {
Data handling, 数据处理
& M' q* h; ~" h4 kData manipulation, 数据处理! P/ I6 B4 U$ Z5 i8 K
Data processing, 数据处理
3 K3 a! N) T( |0 \$ JData reduction, 数据缩减
0 U U1 G! R" m' _Data set, 数据集) E8 b" R9 T- r# N$ c
Data sources, 数据来源
$ C7 j$ v6 ` U d8 |: lData transformation, 数据变换
8 P4 Q( O- P! N" H$ F# y5 ?Data validity, 数据有效性* C: G6 P8 |8 \. h6 L- w
Data-in, 数据输入
" D z$ ]3 k+ }# A$ V6 B6 KData-out, 数据输出. U" a" _ A( a" U/ @+ T/ s
Dead time, 停滞期& X! d, m! A+ e \
Degree of freedom, 自由度/ k& E6 E7 }( v7 `+ B0 z- k# D
Degree of precision, 精密度
6 T* A9 E8 C4 X1 q" QDegree of reliability, 可靠性程度
6 C4 X T6 r9 g7 YDegression, 递减
+ V' K# T. {8 |9 ?$ K& sDensity function, 密度函数
- j8 e. }; q. f- ?) ]Density of data points, 数据点的密度
; G6 s; B- J; pDependent variable, 应变量/依变量/因变量5 C/ V* x5 k. U4 G
Dependent variable, 因变量
2 K$ y! Z) N" H2 b% o9 `5 y9 M- QDepth, 深度
2 t$ C. ]2 g2 M+ m! t6 k# PDerivative matrix, 导数矩阵3 [& w8 d& @, F5 |, H
Derivative-free methods, 无导数方法
/ c' N, |: B. d' w! j8 qDesign, 设计4 ^8 E, B7 O' H
Determinacy, 确定性
9 F% _7 ~( v) NDeterminant, 行列式' B1 V; R" I8 F" _
Determinant, 决定因素
' P3 t* X/ l( Z8 {' s1 u5 yDeviation, 离差
) N, u! g& ` {) xDeviation from average, 离均差! J/ ^$ l! q7 S
Diagnostic plot, 诊断图
- w( y3 H/ e: @) ]6 QDichotomous variable, 二分变量
9 Z3 d# y" [9 {/ y6 Z1 qDifferential equation, 微分方程
; q# F9 }6 |) g3 aDirect standardization, 直接标准化法
% P4 {+ T4 o7 H4 {9 YDiscrete variable, 离散型变量
' b# I g$ k8 p: WDISCRIMINANT, 判断
& G$ U( l2 N9 z' r d& m/ {Discriminant analysis, 判别分析6 B+ s0 T) r1 i4 ]
Discriminant coefficient, 判别系数
& P) ]. N# a8 x0 c: cDiscriminant function, 判别值
# E3 s4 c* x( B' ?9 ]. l% V7 bDispersion, 散布/分散度/ k/ j/ B* k w" m! r
Disproportional, 不成比例的
/ G# {! k4 r* N4 ]' R9 c. WDisproportionate sub-class numbers, 不成比例次级组含量
6 D. S8 {5 F. ^0 A0 @$ o/ EDistribution free, 分布无关性/免分布
/ G. b4 s6 U6 c2 r. W0 b) Q; ZDistribution shape, 分布形状
) J S5 }0 Q; sDistribution-free method, 任意分布法1 l) \8 j% s4 x2 l) M
Distributive laws, 分配律" b% Q/ i- {' k; n
Disturbance, 随机扰动项) H! v5 R) a3 u( t# q# |3 q
Dose response curve, 剂量反应曲线
$ [+ |; _' |. ]8 J- sDouble blind method, 双盲法) ]! j4 n3 n- ]7 W! E! |8 m
Double blind trial, 双盲试验
, [% I% q: u5 a) {9 oDouble exponential distribution, 双指数分布
. q$ f9 x# a/ c) h5 M/ W6 ^Double logarithmic, 双对数9 M S: f( [* B% Y$ ?1 T
Downward rank, 降秩; \3 y( h/ k2 R+ X+ [
Dual-space plot, 对偶空间图
$ q( [0 q5 ` eDUD, 无导数方法3 G7 h7 F0 [ B# X/ q+ h8 q
Duncan's new multiple range method, 新复极差法/Duncan新法
$ D" ~6 |" g( d4 X( K) uEffect, 实验效应0 K) f) ?0 y: p* i
Eigenvalue, 特征值
/ ^9 r: x, _1 k% t% WEigenvector, 特征向量
& ?1 x1 h T5 A5 u2 D: R& F2 eEllipse, 椭圆
: \+ x/ R, w7 y }- eEmpirical distribution, 经验分布
$ o- U. f- I0 @Empirical probability, 经验概率单位! S' \. A6 W5 a$ J; R w, J1 Z+ }
Enumeration data, 计数资料6 X( K7 A" \+ L+ r5 B, g1 S
Equal sun-class number, 相等次级组含量1 a0 Z6 k; u0 L* C0 U; L1 ~
Equally likely, 等可能
0 Z& j, |9 ?& ^- o; VEquivariance, 同变性. S7 y* M' X4 k1 `$ @5 }( W, A: Y
Error, 误差/错误
0 y0 @& X1 D0 M3 n! s5 n3 r0 fError of estimate, 估计误差
3 K( M4 y4 Y5 Z7 _# yError type I, 第一类错误: C& }) }2 ?! \8 F
Error type II, 第二类错误
) _" j+ M4 N0 S: \# ?+ c3 K9 bEstimand, 被估量5 U7 b$ ^9 E z
Estimated error mean squares, 估计误差均方1 r9 r: r, Y2 |- h, p* N
Estimated error sum of squares, 估计误差平方和
7 y" W' R; I" M. ]Euclidean distance, 欧式距离 K4 h: p( A$ l( H( I3 Q' y
Event, 事件4 f5 n [, V9 r, Y2 B* H
Event, 事件( \) m$ K6 e1 H, K( F$ ]
Exceptional data point, 异常数据点
$ o& J& i# S [# F6 X* ?Expectation plane, 期望平面
7 ?! `7 {+ d& s+ G7 a$ S. S9 s+ iExpectation surface, 期望曲面" `( N* |9 f! y% V2 G* x
Expected values, 期望值
8 Q- u9 N* R* O4 B E- dExperiment, 实验. C4 i2 F- V5 Z$ C# r/ H0 @! Y! }
Experimental sampling, 试验抽样
O/ p( [# Y1 C( BExperimental unit, 试验单位- _; \/ W4 z3 u: ~ v, h- P
Explanatory variable, 说明变量
* o0 H- B- Y2 Z# j$ YExploratory data analysis, 探索性数据分析
+ z9 `/ ]" S* ^Explore Summarize, 探索-摘要
! r$ V1 k2 ]. F1 n1 I6 fExponential curve, 指数曲线$ }+ f; w; j; c* B: l& r+ D
Exponential growth, 指数式增长! y6 b% D U% t5 K( G/ p
EXSMOOTH, 指数平滑方法 # e4 T- N3 M3 N# _. ?3 T
Extended fit, 扩充拟合* O2 L) _' _' W* n9 R
Extra parameter, 附加参数
$ z( }5 s$ @, j4 G1 nExtrapolation, 外推法
( T+ }0 f2 ] H2 v7 zExtreme observation, 末端观测值$ b9 z; Q6 E; b! p) x- Y
Extremes, 极端值/极值
# f1 `1 E/ T) N+ W! qF distribution, F分布9 `1 F8 ^9 E; [& C- G
F test, F检验
, b6 }$ M# z: ~) V$ F2 jFactor, 因素/因子
$ R6 Z8 h$ [2 i2 d' }Factor analysis, 因子分析
9 e( U* G" g8 IFactor Analysis, 因子分析& c, |* t* p* Y# a( s# j( L
Factor score, 因子得分 ) e# L3 Q5 s2 o# I& r/ m- o) @
Factorial, 阶乘
) Q. c5 k( ~, O8 @3 R& GFactorial design, 析因试验设计& w. _) U' m7 d2 s
False negative, 假阴性
$ w3 l& v4 i. DFalse negative error, 假阴性错误 V4 t0 j2 e' {: h% k: L% P3 ]9 j
Family of distributions, 分布族0 f$ A# _5 M4 N/ o. Y$ A
Family of estimators, 估计量族& L6 z0 o4 d/ y' U; Y
Fanning, 扇面8 F) ?, N! e) ?7 ^" P
Fatality rate, 病死率
/ o# n* h3 T9 |& \' z0 L( t- b% QField investigation, 现场调查4 r( `$ Q/ Z0 e9 q, Y9 _, o7 d; \
Field survey, 现场调查
6 {% H4 i2 x0 g4 B& I0 \+ s6 E! SFinite population, 有限总体! v5 [4 m6 `0 U
Finite-sample, 有限样本
( n' a% A8 `4 MFirst derivative, 一阶导数, a/ f% i0 _ j- c) C2 V' P
First principal component, 第一主成分
# J+ T' L" S. `3 {* ]- U; wFirst quartile, 第一四分位数
( m8 j6 }+ h% eFisher information, 费雪信息量' p( z" E: s/ Z. u+ n- R+ c
Fitted value, 拟合值
' l, _/ [1 D. m! z9 @Fitting a curve, 曲线拟合9 }% y, u" a& |+ Z
Fixed base, 定基
+ w& v1 ]- v% j8 vFluctuation, 随机起伏' {: K4 L- z+ Z0 D* ?& {
Forecast, 预测) C) H5 M0 d. V/ }- o) b
Four fold table, 四格表2 L; l/ }2 y9 b2 r; U
Fourth, 四分点
2 w: d$ k) u3 NFraction blow, 左侧比率0 E* i, ~. f. z
Fractional error, 相对误差
_0 c7 o) g/ \5 C: X! O9 TFrequency, 频率
8 V! s1 P7 y) |$ o; B1 UFrequency polygon, 频数多边图 H/ O9 B3 K1 u; b( t
Frontier point, 界限点; n9 i3 U9 ?! o& }
Function relationship, 泛函关系
9 ?7 v* _, ]/ I; w7 X% B( LGamma distribution, 伽玛分布, Q; b$ C& u5 k5 |$ {. [$ [. Z0 {
Gauss increment, 高斯增量1 z$ G$ x$ y6 d" W$ y+ r
Gaussian distribution, 高斯分布/正态分布' M: V: K2 K4 S- ]8 j1 d/ T! f5 n
Gauss-Newton increment, 高斯-牛顿增量7 w* A' w8 {9 ]$ k
General census, 全面普查
/ J' t G$ X( r* M) W" y7 \& _- ^/ HGENLOG (Generalized liner models), 广义线性模型 . {2 Z% d) g, Y) f
Geometric mean, 几何平均数
1 E0 N$ b% E# [$ d' iGini's mean difference, 基尼均差, c! U- @' \4 Z l# C" v
GLM (General liner models), 一般线性模型 , J/ J; G& B8 Z3 @7 [1 F0 s
Goodness of fit, 拟和优度/配合度2 ~6 H6 Z7 H* M8 }8 ]: C" u. |
Gradient of determinant, 行列式的梯度
, c4 R4 H! h" WGraeco-Latin square, 希腊拉丁方1 ~& J7 V k2 l5 d& g
Grand mean, 总均值
/ ~# [! B ?6 M0 [2 O) c) AGross errors, 重大错误, V- x+ S9 g, h" b5 [
Gross-error sensitivity, 大错敏感度
8 H8 g2 y3 H) n3 I6 gGroup averages, 分组平均
4 N) ]* n O7 j0 E9 t( q& rGrouped data, 分组资料; i, n" n/ r# N+ U. D8 [
Guessed mean, 假定平均数
7 I g; _4 X8 N* ~5 }: [7 xHalf-life, 半衰期
; {* a8 H/ A" S* h, wHampel M-estimators, 汉佩尔M估计量
6 l* h( |- t0 ~$ t( JHappenstance, 偶然事件
, Q' X' O: m+ `7 O& WHarmonic mean, 调和均数
- J, B! T& o9 Q5 KHazard function, 风险均数/ v; D# i/ I! d$ w u
Hazard rate, 风险率7 g; l/ u" p1 K1 D- R- m! m
Heading, 标目
7 }4 X/ V! ^1 LHeavy-tailed distribution, 重尾分布/ B V. F& ?8 I' m: ?: {
Hessian array, 海森立体阵
9 E+ s% e# ^ H8 RHeterogeneity, 不同质
O. @! Q* _/ O6 ^Heterogeneity of variance, 方差不齐 , p" Y! y5 A/ \8 O3 n1 E* P
Hierarchical classification, 组内分组
: u) y* \7 E: l( A; `8 @& o! H; kHierarchical clustering method, 系统聚类法1 J9 ^& V+ {- C. G' \
High-leverage point, 高杠杆率点) F1 A+ p3 E( @6 o. u8 q
HILOGLINEAR, 多维列联表的层次对数线性模型
6 `! S# i- H* Z7 X" H0 pHinge, 折叶点. Q( H$ S3 m0 {2 H; b
Histogram, 直方图$ E# B: x6 _+ E
Historical cohort study, 历史性队列研究
0 a$ f3 B$ o! @5 c9 ?1 O. V& WHoles, 空洞
& L2 ]# \* a4 P9 H$ sHOMALS, 多重响应分析
, c- f/ o: p% r* o! q. s IHomogeneity of variance, 方差齐性
0 }& e. @3 G; _Homogeneity test, 齐性检验 M9 Y2 x+ x" X2 ?& H: R6 x( F' A" j
Huber M-estimators, 休伯M估计量
4 i( L" l5 }5 Z! s& G4 p: tHyperbola, 双曲线
2 H7 A$ _; N! k2 |% _: hHypothesis testing, 假设检验
" ~" P6 |5 Q) R* {* }Hypothetical universe, 假设总体
' B2 n, d2 X; q+ r. h3 b" RImpossible event, 不可能事件
( c: z! }: g! y* EIndependence, 独立性3 ^6 S6 `3 J/ e0 C3 P
Independent variable, 自变量# X$ g; n! j) @3 h4 A0 h$ e s$ e
Index, 指标/指数
3 G0 P, F$ r. c+ y: h0 v3 a2 G9 YIndirect standardization, 间接标准化法8 W Y0 I9 F- J6 U& m) Y% m
Individual, 个体
; d& ]) l6 C) B SInference band, 推断带: M+ Y: q" t8 `) g! o
Infinite population, 无限总体. x; z/ Y5 h4 F/ L1 K
Infinitely great, 无穷大
! B; Q2 X6 n( X0 ^, O S( Y8 X, F4 E9 hInfinitely small, 无穷小
8 R6 D' Z1 W' U" @' k, V7 `3 HInfluence curve, 影响曲线7 a" B+ ?7 }5 s* x4 U( v) _
Information capacity, 信息容量- _- ^# q# D7 r, l; o# F, {
Initial condition, 初始条件0 k: Z8 u/ \9 E3 Y' ]
Initial estimate, 初始估计值* T. V# V! `- ?9 c2 A
Initial level, 最初水平
7 W0 e& a8 c8 }5 pInteraction, 交互作用% r4 X8 v8 ~; A) v* C
Interaction terms, 交互作用项
. e( K7 U; K9 d7 ?Intercept, 截距2 a$ e# f- e1 c% J" `% Q, P
Interpolation, 内插法6 U" @( X. B2 V4 ~4 B8 c% C6 M% _" X
Interquartile range, 四分位距
4 \; P0 e; ~3 @4 X) m% \Interval estimation, 区间估计% V3 j( l# w( ^$ A* O& m& W; ~
Intervals of equal probability, 等概率区间
, e, d$ ` j$ G& z8 L& gIntrinsic curvature, 固有曲率3 p$ c. ^* H; d2 I& W/ A
Invariance, 不变性
; P% `) ?' |3 hInverse matrix, 逆矩阵2 x0 s2 l4 m7 u9 x
Inverse probability, 逆概率
2 A; @( R/ T3 mInverse sine transformation, 反正弦变换
1 M1 C4 A; h6 E" _Iteration, 迭代 1 r6 m/ {8 h! N+ @" M
Jacobian determinant, 雅可比行列式
. ?+ W) v. B( yJoint distribution function, 分布函数2 c# f6 }8 C I/ X* s
Joint probability, 联合概率
; u0 M E9 i$ L! {" B- S: DJoint probability distribution, 联合概率分布' O5 G' e6 y4 K+ ^$ i6 B
K means method, 逐步聚类法2 r7 `2 v8 b- U1 y! t: y3 \+ E; }
Kaplan-Meier, 评估事件的时间长度
# B* @% t* |4 [) d& @Kaplan-Merier chart, Kaplan-Merier图
, u1 r# D" n7 v- S! A5 HKendall's rank correlation, Kendall等级相关' s9 s% Q# @1 g4 d. H' N, o
Kinetic, 动力学
8 e; a. f, F4 k; B. i4 }* EKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
1 v8 P) ^, g7 Z- H6 L/ S" ]2 DKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验" O/ n- M$ _: r* R! Q
Kurtosis, 峰度
2 T/ |6 V# n7 B9 u) a J5 P( O' aLack of fit, 失拟0 _0 c) b' R# W
Ladder of powers, 幂阶梯+ ~8 H5 K" ?/ Q$ Y }
Lag, 滞后; C% {& V! O' W( g
Large sample, 大样本
1 l+ l' `2 W( i& ^0 b- e7 VLarge sample test, 大样本检验7 ~$ K8 }. c8 W- V3 ?, }% O8 E
Latin square, 拉丁方$ I; H2 @' n' @5 r- y
Latin square design, 拉丁方设计
( z) M2 a6 A( o8 c3 bLeakage, 泄漏7 H/ A+ g3 K2 J( p. @
Least favorable configuration, 最不利构形
( W- }% o* n5 KLeast favorable distribution, 最不利分布
+ @2 l. Q7 _; A4 r# I. J% ~. cLeast significant difference, 最小显著差法
0 A- Z/ t# { T8 L' ~. q+ FLeast square method, 最小二乘法9 |; Z: H7 s G8 x' T2 J. S
Least-absolute-residuals estimates, 最小绝对残差估计
& s0 l6 I8 i. k) R* L0 vLeast-absolute-residuals fit, 最小绝对残差拟合
& b) s" m5 d* ]: G# ?' ELeast-absolute-residuals line, 最小绝对残差线
6 w# u" T3 A2 b _1 JLegend, 图例
* Z3 T4 L, x6 ]/ u2 P% BL-estimator, L估计量$ F$ S* j8 J2 m0 K/ K d" _
L-estimator of location, 位置L估计量! @2 V: W) {" Y. P
L-estimator of scale, 尺度L估计量
, d, b9 \( @9 S1 T0 l* c+ [# C4 _7 SLevel, 水平
$ w7 A9 d: Q8 ]* h! ^3 HLife expectance, 预期期望寿命
0 l' j; l) `1 M0 p6 S) kLife table, 寿命表
1 f! F( G6 o3 p; f6 m3 c }Life table method, 生命表法
: m4 k7 c' z, {. n" kLight-tailed distribution, 轻尾分布3 Y" j' z# ~4 t4 X( q1 W
Likelihood function, 似然函数
$ f% |% X# M, N% G% g: ZLikelihood ratio, 似然比
; J4 F. I& E! d& s) z* @; U- ]line graph, 线图4 m6 c4 z+ T; u- c' K7 x% ~! a* j: |
Linear correlation, 直线相关
- y. P4 N( V* i3 Q8 RLinear equation, 线性方程
# a. Q9 q* n" J3 {7 F1 L- FLinear programming, 线性规划5 M' F* m* k+ P; [4 N
Linear regression, 直线回归
1 `9 x' ^2 c3 S& e( d! g4 G8 K! pLinear Regression, 线性回归6 H5 S3 S$ O) c4 `; `" r
Linear trend, 线性趋势
9 Y+ W" {6 ~5 I6 q a8 L! SLoading, 载荷
/ k m* W* X# x1 eLocation and scale equivariance, 位置尺度同变性
; y# |* F2 @3 t w6 D% TLocation equivariance, 位置同变性) T4 C9 G V7 {+ Q
Location invariance, 位置不变性
, n# O/ I' k2 r5 U- M3 xLocation scale family, 位置尺度族; G, M/ j4 m: X! d. ~& Z2 W& ?
Log rank test, 时序检验 " H6 o- a5 P" o% T
Logarithmic curve, 对数曲线) \ z$ P4 a8 g* k2 B& W p
Logarithmic normal distribution, 对数正态分布 o5 x3 ?/ a0 F4 R" c+ X
Logarithmic scale, 对数尺度( i/ u' ?7 G! Y, J+ o& t9 H
Logarithmic transformation, 对数变换6 z$ }4 c% ]% O5 Q g8 q9 N3 @
Logic check, 逻辑检查 E( P# t, ]% k8 n
Logistic distribution, 逻辑斯特分布
' G" F2 \& H- v1 X6 U6 XLogit transformation, Logit转换
6 z4 |7 V M9 V5 k1 CLOGLINEAR, 多维列联表通用模型
# A8 z5 e5 c# [Lognormal distribution, 对数正态分布3 T6 L$ p0 f7 [7 q
Lost function, 损失函数* C/ I/ L6 c* k H+ g2 P' V
Low correlation, 低度相关1 K% O# `$ z5 u7 U- g3 }
Lower limit, 下限
4 t( }0 G, [4 W) ^Lowest-attained variance, 最小可达方差( G/ H! a0 D0 m3 f) l
LSD, 最小显著差法的简称
# k0 |, `4 B4 ^% M: zLurking variable, 潜在变量
0 h* \7 W$ a1 {5 ~) o) eMain effect, 主效应
! O* @4 {# ?! A% j& A0 R! lMajor heading, 主辞标目9 m; {$ S% ?% f# {# ]
Marginal density function, 边缘密度函数) ~% T D$ _/ i8 U" |3 \4 q
Marginal probability, 边缘概率
6 p. K' l% A# m A7 R/ D. {" pMarginal probability distribution, 边缘概率分布
" b8 C n/ k k! B9 C5 X4 }. q8 Z* [Matched data, 配对资料6 R& y0 {" k7 ~0 X5 q4 Y5 h
Matched distribution, 匹配过分布
7 s( \) C( p9 Z9 t' ^, aMatching of distribution, 分布的匹配
* Z0 D l: S9 v" s( Q" HMatching of transformation, 变换的匹配
2 r3 X3 z; p( t [8 VMathematical expectation, 数学期望7 _# A- q- J o/ `- f9 ]& y! G# ~
Mathematical model, 数学模型0 e% e1 \# c. G& w+ O4 w
Maximum L-estimator, 极大极小L 估计量
& O- `4 I7 a6 \Maximum likelihood method, 最大似然法
5 Y9 P: R+ v- dMean, 均数- \- B+ J U0 j; u4 \
Mean squares between groups, 组间均方
6 f5 {% n" x* Y" j. b7 k/ ZMean squares within group, 组内均方
! A, D* Y% R- E- iMeans (Compare means), 均值-均值比较
$ t6 `" s4 S2 |) x' e- |Median, 中位数
! V) Z) b% e; d+ ?8 x7 I; h! DMedian effective dose, 半数效量
0 W- y- w, v- ?6 AMedian lethal dose, 半数致死量+ U5 v. N; ^2 z/ o" q1 ?; R
Median polish, 中位数平滑
' L" U+ M8 @# O, mMedian test, 中位数检验$ c: P$ p5 [0 |1 P! A
Minimal sufficient statistic, 最小充分统计量
o0 x, a/ t0 n* ~9 kMinimum distance estimation, 最小距离估计
* p1 G6 M4 _$ G6 p; LMinimum effective dose, 最小有效量% h; }+ B j7 |6 S$ x4 u! B7 q F
Minimum lethal dose, 最小致死量
- S# g3 @" }- u7 K$ @7 u: G: J" CMinimum variance estimator, 最小方差估计量
3 J! l& \. |& t* |7 W. F% OMINITAB, 统计软件包
2 q- g7 s2 \2 x. w4 y$ c' jMinor heading, 宾词标目. _( c# z. [ O, j, Q' _
Missing data, 缺失值' Q- g% n6 G, r/ n+ L
Model specification, 模型的确定9 ] m2 Q! S y! Q/ Z# g0 D- n7 Y
Modeling Statistics , 模型统计
4 ` O/ e+ Z7 O& N% Y6 XModels for outliers, 离群值模型
' f' x2 z8 d% r% o6 Y6 n) o* c9 aModifying the model, 模型的修正: F- l) s& G# P+ p
Modulus of continuity, 连续性模
: _7 p* W5 Y8 n1 |' K" BMorbidity, 发病率 # u9 W0 s+ {6 I& `% {5 C- i& J5 v/ g
Most favorable configuration, 最有利构形
9 K1 P5 d$ v- LMultidimensional Scaling (ASCAL), 多维尺度/多维标度* A1 [# f* A- P i. N& B
Multinomial Logistic Regression , 多项逻辑斯蒂回归0 k+ P( |( Y; S0 w/ G/ B+ u. g
Multiple comparison, 多重比较
* v/ l0 Y y3 ^" M8 NMultiple correlation , 复相关
' J h4 f. S, `' S; F" y8 EMultiple covariance, 多元协方差1 g) P) s& A" H [+ q
Multiple linear regression, 多元线性回归* C3 m5 r4 A2 l. q8 F, |( C
Multiple response , 多重选项
; c$ o7 s% Q# Z; m( ^, W, xMultiple solutions, 多解
- x7 E. v& J o9 P2 L% I2 L8 X+ U; ?Multiplication theorem, 乘法定理( }0 n( F( s. j4 K
Multiresponse, 多元响应
4 f& x, p0 l- Q8 @# R3 ZMulti-stage sampling, 多阶段抽样
* F" {! }% [5 o) }$ UMultivariate T distribution, 多元T分布% m) d0 c1 t& s; r J, N% z
Mutual exclusive, 互不相容
- s; Y( Z9 c9 qMutual independence, 互相独立
4 W- ?8 p3 q: P( }, A6 }4 ONatural boundary, 自然边界
# g4 l" b! c0 b$ ~+ JNatural dead, 自然死亡' Q+ _! D2 y/ t& O' V
Natural zero, 自然零
9 f& e# g! V5 r/ xNegative correlation, 负相关
* M) {6 O* T" H$ I1 kNegative linear correlation, 负线性相关7 |$ E. ?" ?' w, l: v
Negatively skewed, 负偏8 R. r. d' A- q# m$ U8 f
Newman-Keuls method, q检验* f6 b% e- j8 n5 z% e
NK method, q检验
- c# H3 z5 m/ J$ FNo statistical significance, 无统计意义
+ h3 K4 d9 m8 ~6 l7 G9 I c+ `* pNominal variable, 名义变量5 E6 E7 P1 B$ P0 X
Nonconstancy of variability, 变异的非定常性7 R6 r7 w4 g; A1 W
Nonlinear regression, 非线性相关
0 f$ }) }$ i! m- NNonparametric statistics, 非参数统计% _# z- T0 y! z8 @# a: ^+ |! \
Nonparametric test, 非参数检验7 N. S% v. v. K) N- V- c9 V
Nonparametric tests, 非参数检验
0 s! f5 L8 k$ eNormal deviate, 正态离差
3 B, G0 X q, p$ a1 t0 WNormal distribution, 正态分布5 }8 e, T* G& E5 }
Normal equation, 正规方程组; g& K$ }& l( f \0 k5 N
Normal ranges, 正常范围( c- J; H; I/ q) R9 q
Normal value, 正常值* V+ t+ C# T2 S& R j/ V0 B
Nuisance parameter, 多余参数/讨厌参数9 I" E2 S4 G2 o
Null hypothesis, 无效假设 + S* i$ B% v' Q6 C1 R! k3 j
Numerical variable, 数值变量
! D, Z& t5 s/ p# g$ WObjective function, 目标函数
& S8 J b4 u6 q) O' SObservation unit, 观察单位
! A& G# f8 P/ u) d+ \+ J+ BObserved value, 观察值
' `3 \9 P p* }! qOne sided test, 单侧检验' b* `7 Y _6 K6 k( A
One-way analysis of variance, 单因素方差分析
C3 g6 Z5 F |, u( `6 yOneway ANOVA , 单因素方差分析7 b) k' J! u/ z* r" ?7 z/ \. W
Open sequential trial, 开放型序贯设计
! v; q! v4 D, O% YOptrim, 优切尾
1 H$ } r' Z4 V' ~# O& }: LOptrim efficiency, 优切尾效率/ x# ~2 ]; ~9 G/ p8 J+ a7 |7 E
Order statistics, 顺序统计量+ {+ S' y6 L7 K9 o7 v% n
Ordered categories, 有序分类, R' E/ b6 o# k5 p. w
Ordinal logistic regression , 序数逻辑斯蒂回归7 O, J$ o, _9 g+ _, J% l
Ordinal variable, 有序变量5 M- l9 o4 `, O# q9 Z
Orthogonal basis, 正交基
1 t, W5 w, g) f2 ?Orthogonal design, 正交试验设计
2 z" Q4 g! y- N& Y! O1 dOrthogonality conditions, 正交条件: L5 M. l. U" g! o
ORTHOPLAN, 正交设计 2 U* B5 d9 t) Y4 M. K
Outlier cutoffs, 离群值截断点
, A/ i/ M) P1 N) @2 D4 BOutliers, 极端值
. l s2 R" K1 G4 m; vOVERALS , 多组变量的非线性正规相关
0 s' T& p) y& l7 |( Z# U4 pOvershoot, 迭代过度2 Y# e* w" P( _6 E( _
Paired design, 配对设计
X: o6 x2 ~& `/ [ C& VPaired sample, 配对样本/ e- L# O. \" I$ _/ F
Pairwise slopes, 成对斜率7 I- }& I$ i9 W, |8 c1 E
Parabola, 抛物线; @9 I+ Q) v! Y2 ~- [: f
Parallel tests, 平行试验
0 c# N8 n- N! C; l3 C; `Parameter, 参数
f6 x/ Y( G( s5 yParametric statistics, 参数统计
* _7 C) M+ m& o+ vParametric test, 参数检验5 O- _. ~6 R- x; e' S
Partial correlation, 偏相关2 P( a1 f* i0 Q/ @+ J
Partial regression, 偏回归
* Y/ L9 w8 U/ S KPartial sorting, 偏排序6 y+ N% X1 i. g# s+ r7 _
Partials residuals, 偏残差
Y- G, P# h- G. C- fPattern, 模式
/ d9 f8 k0 n) ~ z4 JPearson curves, 皮尔逊曲线- `; w' r. ~) k; Z. v, r
Peeling, 退层
7 v$ `1 V! J+ P( \7 H8 A+ j wPercent bar graph, 百分条形图
3 K! ~( u& `* j% F5 o' T: p2 LPercentage, 百分比
& f' F9 \3 o" t$ y$ P( j" K. j/ ~" MPercentile, 百分位数! T. V. s0 A- M/ S! s
Percentile curves, 百分位曲线 v6 i8 P, o$ n
Periodicity, 周期性
4 {7 ~$ u1 T0 hPermutation, 排列8 W* A- r3 B/ u) m r
P-estimator, P估计量
! k7 K$ J9 E% ?& A0 x# dPie graph, 饼图3 X8 i7 i5 L" Z* P
Pitman estimator, 皮特曼估计量
# p$ {- l$ g- ?% }Pivot, 枢轴量
& s. Q$ \ I6 r$ G ^$ ]" HPlanar, 平坦+ X) S- S" W* x
Planar assumption, 平面的假设
- `6 z1 N' T4 N2 x; p' U, h/ I2 wPLANCARDS, 生成试验的计划卡: N y" i; B' p! x1 @
Point estimation, 点估计
7 f, G7 c5 }# i* d0 S. @Poisson distribution, 泊松分布
; r7 j7 b H/ {) g2 o/ iPolishing, 平滑
% C( @! G! J! x8 H; f) v% t+ lPolled standard deviation, 合并标准差
. e q5 w/ R5 V% o }* ?Polled variance, 合并方差
6 a) }) p# J7 k: M" w; |; O' HPolygon, 多边图% B9 c9 Y, b* O* _6 W: f: A
Polynomial, 多项式
0 q8 C+ F1 q% LPolynomial curve, 多项式曲线9 Y7 I9 t+ P0 r* d
Population, 总体
. K6 {- ^ V5 N; z# k* vPopulation attributable risk, 人群归因危险度
' x" ^ C9 |& {Positive correlation, 正相关- S3 m+ g9 P# b
Positively skewed, 正偏
3 L" y6 \9 K9 d. W, s* t: oPosterior distribution, 后验分布
9 f I) }$ E EPower of a test, 检验效能" C Q2 n; g* @
Precision, 精密度
* U3 s- L' Z" [3 Y% A8 V0 BPredicted value, 预测值
/ C2 z: N& ]. {Preliminary analysis, 预备性分析
) S4 y0 H' N6 JPrincipal component analysis, 主成分分析
) O6 N4 d7 A) x2 t1 o; \Prior distribution, 先验分布 M$ d V: r& T$ v) T
Prior probability, 先验概率
. c& Q1 v) k0 F" `% Q1 X) Q& eProbabilistic model, 概率模型* c3 [# r3 q5 l! s0 m
probability, 概率
8 L/ B+ M# I. g1 f/ B; Y; B/ ]Probability density, 概率密度
8 M2 ]6 A, ]5 m Q% q# b- { gProduct moment, 乘积矩/协方差4 R- `# z( Y; Y7 @, ]. y
Profile trace, 截面迹图
+ e& g4 u$ X3 C. \) \/ F1 RProportion, 比/构成比. j2 u* {9 I5 B: f
Proportion allocation in stratified random sampling, 按比例分层随机抽样9 i* |- P! A) b
Proportionate, 成比例
+ w* ~& X- b$ F# [: X. lProportionate sub-class numbers, 成比例次级组含量
& `! E {7 O% l0 W7 MProspective study, 前瞻性调查
+ r7 T5 ^ T' V! J% RProximities, 亲近性
% d( J# x5 F- Q1 j8 J& kPseudo F test, 近似F检验" l5 g* @7 n' \6 r) A" e
Pseudo model, 近似模型
$ `, S' f$ |! c* O; k9 \5 ~. ~Pseudosigma, 伪标准差
- s$ E: q; r/ h9 ^Purposive sampling, 有目的抽样
, i4 A4 A7 _4 D) A" @2 ?QR decomposition, QR分解
7 {' D" ^- D+ A4 A3 [3 o' ~Quadratic approximation, 二次近似# p" }! Y( i4 A' J/ x6 e! m
Qualitative classification, 属性分类
! S9 G8 M, J8 n4 pQualitative method, 定性方法
2 ~1 J* ?. C; [) [" d% zQuantile-quantile plot, 分位数-分位数图/Q-Q图
; Y! a6 R+ T% ]3 Y4 D4 Y ZQuantitative analysis, 定量分析: f1 f" X! i2 ^( F: Y0 e
Quartile, 四分位数
6 e' d, i& a0 E, E1 J, Y7 ~" {3 _Quick Cluster, 快速聚类, i/ y0 S+ `% N, R7 a5 ^4 [: _
Radix sort, 基数排序' b0 M: h7 ]; Z
Random allocation, 随机化分组9 y, }- O; w' {" M- D3 F1 j
Random blocks design, 随机区组设计" d% o- x. ?. _8 t; N+ V
Random event, 随机事件0 B% A: S; `4 c0 V& K
Randomization, 随机化
9 u: }8 V8 @$ L- P P8 p+ ARange, 极差/全距4 D" Q! R0 s( S' t! p* y% |
Rank correlation, 等级相关# q/ \. Y: p6 j' u6 C6 t- e
Rank sum test, 秩和检验
0 G- S' j8 s" _ I0 N1 W1 VRank test, 秩检验6 N& z0 N/ T P# k
Ranked data, 等级资料
& }2 z8 c9 u) ^% d! g$ YRate, 比率4 E! l E$ N8 |# }$ ]
Ratio, 比例, _4 T1 G4 M O' t# i
Raw data, 原始资料
% L s; |% E$ c) j, h/ zRaw residual, 原始残差9 B1 j' m* ~ k6 Y8 D. E( |, o
Rayleigh's test, 雷氏检验
& ~7 ^9 O9 m3 S8 t# z5 ], c( jRayleigh's Z, 雷氏Z值
9 V7 j; N* h! l: E0 A, {. K4 YReciprocal, 倒数
# W3 Y0 b6 `9 K6 I6 `1 k, OReciprocal transformation, 倒数变换
4 L* |6 i1 u! _. yRecording, 记录
) A, a0 }, j$ F6 U* s6 \2 lRedescending estimators, 回降估计量
# V( Z5 S, e# z0 \# c1 wReducing dimensions, 降维$ e* |0 g y: g5 ^ M3 q
Re-expression, 重新表达' L, y, O4 _% d' @2 t: B& [9 r
Reference set, 标准组
/ D. P! s7 \ O$ c) R, w$ C! B4 YRegion of acceptance, 接受域6 M! H/ O1 o" `& J# \6 Z3 i
Regression coefficient, 回归系数- Y$ S. I5 E% ]( F& N, |
Regression sum of square, 回归平方和
8 r$ Q; ]0 G0 g/ N( `$ {Rejection point, 拒绝点; K) f* }0 j6 E- H7 F4 V+ T; z
Relative dispersion, 相对离散度; n5 F, ]" K& e) m5 Z
Relative number, 相对数% G0 O; \4 x v- z& x
Reliability, 可靠性
8 U1 c1 l: C. _Reparametrization, 重新设置参数
0 \4 M9 ~4 ^6 ]$ n1 l& I& |Replication, 重复
1 x- i; y$ s* j! \" Y0 CReport Summaries, 报告摘要
1 w' }' R7 d- G( r& QResidual sum of square, 剩余平方和& v; x0 f, {: I& u. f8 o
Resistance, 耐抗性
, p( E6 H* N0 L: SResistant line, 耐抗线3 g& t6 ?( C# J
Resistant technique, 耐抗技术
. }( u- q! [# g7 H' mR-estimator of location, 位置R估计量0 x8 i; V$ Y' n3 m
R-estimator of scale, 尺度R估计量! G% b; _% D, X. Y
Retrospective study, 回顾性调查& F& ~9 R7 I; t& J7 ?( w0 A
Ridge trace, 岭迹
3 b h% t) i9 ^. O4 PRidit analysis, Ridit分析
8 u, i& @& W. Y* R0 ^) ZRotation, 旋转
5 T' H8 O2 g, c6 B8 KRounding, 舍入
$ d+ o4 X9 ^" C8 cRow, 行7 E* b! d3 U0 q0 }+ @
Row effects, 行效应; H; M! w9 l# p7 y: Q
Row factor, 行因素6 Q- B* c1 y R) q' z+ {
RXC table, RXC表1 ^9 s; u# j- K$ u
Sample, 样本
% ?* v1 F$ f+ j5 a* sSample regression coefficient, 样本回归系数
4 A* U6 {$ p) o' k# ?& {1 _$ ESample size, 样本量
* D$ ?" b% K( \( gSample standard deviation, 样本标准差$ b; K/ M5 ~! a/ W% X2 M. l" N. i9 Q
Sampling error, 抽样误差
, {4 t6 s+ j; A. I3 @& L7 i! tSAS(Statistical analysis system ), SAS统计软件包0 Q5 e' m2 L! ?! w9 M4 P0 W
Scale, 尺度/量表! e7 T: O# n: h1 L V
Scatter diagram, 散点图
8 U7 @+ C }/ |9 d% wSchematic plot, 示意图/简图
3 D& s8 U1 d) I: U$ G" |Score test, 计分检验
0 }2 d; \$ m- f# U' rScreening, 筛检
! p* f( U: Q) Y, _( [0 zSEASON, 季节分析
* n; N. A, L: \5 w& H$ m. BSecond derivative, 二阶导数" T, E6 d0 k) F1 X' W1 @
Second principal component, 第二主成分/ @9 C% |- Y: u5 a Y+ a; t
SEM (Structural equation modeling), 结构化方程模型 ( O/ q' W! P5 m; s1 ~/ ?" K$ }
Semi-logarithmic graph, 半对数图
7 W& \& X. U9 a5 RSemi-logarithmic paper, 半对数格纸
7 _# B; j$ L+ ySensitivity curve, 敏感度曲线 M- w& }8 K6 [ p& Q
Sequential analysis, 贯序分析1 ^: j9 Z/ Z/ Y u5 N1 P: u$ ?, P4 d+ b
Sequential data set, 顺序数据集7 `4 Q* K9 ?" K$ ]7 N
Sequential design, 贯序设计- t7 @: |& B& S: \% H: {% @8 A
Sequential method, 贯序法( ~# I" A( U: |; o
Sequential test, 贯序检验法% g# `! Z7 @. v/ ]
Serial tests, 系列试验7 H* Z# r0 y. \$ S
Short-cut method, 简捷法 * V1 @) C2 ]% Q# o5 A. n9 B1 l. w
Sigmoid curve, S形曲线
0 w# ^! O- ^/ R% bSign function, 正负号函数
+ P6 W3 p: T6 W/ ?3 y) X& iSign test, 符号检验4 ?, |/ [7 m! K! J% ?6 M/ }4 D
Signed rank, 符号秩
* g/ M/ F+ @& ]& y$ q9 d( TSignificance test, 显著性检验1 f( q, k* L0 |( s7 K# b. @8 q0 O A
Significant figure, 有效数字. {7 `2 g+ }3 L7 y$ V
Simple cluster sampling, 简单整群抽样
( R7 S& C; A9 w- j. H; s. PSimple correlation, 简单相关. f& D8 b' b% d7 h* D0 b2 Y* j
Simple random sampling, 简单随机抽样( j3 b2 U& J! {% z) b
Simple regression, 简单回归
2 p( x$ l' D+ \: Bsimple table, 简单表
) T! f' L3 w& k, KSine estimator, 正弦估计量9 t0 C3 X% A4 ? Z# h h7 e8 b6 x4 F
Single-valued estimate, 单值估计$ u$ `; j$ h5 {5 c2 {3 X3 J
Singular matrix, 奇异矩阵
. n* [* L6 h3 C& d8 w4 f8 MSkewed distribution, 偏斜分布
' v8 W; h. ~# J9 F: ISkewness, 偏度
, S+ }9 K5 D2 q9 b7 u/ F" \Slash distribution, 斜线分布
9 J- i: W' E) XSlope, 斜率0 v% R U1 {6 X6 R4 Y+ C" T7 a
Smirnov test, 斯米尔诺夫检验9 W) K. o2 |$ s1 E
Source of variation, 变异来源6 r5 y' C6 B0 \$ G) ^; a9 t
Spearman rank correlation, 斯皮尔曼等级相关! }$ T' k$ }3 L$ H1 W3 w( b: @
Specific factor, 特殊因子
Y4 q: u, L5 i- k8 xSpecific factor variance, 特殊因子方差
! q l/ N) W7 q2 z6 Y% c+ l8 hSpectra , 频谱2 A& X6 n* T9 H6 R, i& u2 g
Spherical distribution, 球型正态分布
5 g) O9 p5 a3 _4 \Spread, 展布/ x& `0 d& `. e/ M2 d, \, _2 @
SPSS(Statistical package for the social science), SPSS统计软件包% \7 g& r; t5 L" v9 k
Spurious correlation, 假性相关
' V; z; W/ ^/ e8 ~# p9 q8 {Square root transformation, 平方根变换0 Y& j* G* _* L7 U& B/ R! H; b
Stabilizing variance, 稳定方差- {' {" c1 Z* [8 D1 w
Standard deviation, 标准差
& ~ N3 S' o7 J) k) n+ sStandard error, 标准误
' c5 v# R+ s8 n! _8 x4 EStandard error of difference, 差别的标准误6 b/ g. \1 f8 H
Standard error of estimate, 标准估计误差
! A8 w5 r x' Q* v9 FStandard error of rate, 率的标准误, h4 ^: p5 v- O7 O, n
Standard normal distribution, 标准正态分布
1 k) [& h( X8 S1 X! bStandardization, 标准化+ y$ m- V( h/ A5 d1 k
Starting value, 起始值
0 d" v% | x# v2 V& }+ n/ @' wStatistic, 统计量/ ]- a2 A# ?: i- @
Statistical control, 统计控制
4 R) w' J- P9 f( j) T2 ]% nStatistical graph, 统计图
: d8 E: q1 l; O' lStatistical inference, 统计推断& R7 ^* F8 Z6 W) x* r: X& A( i# D
Statistical table, 统计表
; b, q8 |* G% ^5 \Steepest descent, 最速下降法% d |8 r+ i, u: w, _( m' }
Stem and leaf display, 茎叶图0 o& W, q% ?/ N% Z4 I1 J3 u* E4 c7 z, K
Step factor, 步长因子9 d! a: M, s8 V6 {6 ?- w; Z0 D
Stepwise regression, 逐步回归' r3 O5 S! {: h' p$ A+ P$ P: }- I
Storage, 存
- ?* N1 H+ Z# x) m& R4 ZStrata, 层（复数）( l; B6 a! _/ T1 Q" c
Stratified sampling, 分层抽样6 }( f( `( G3 y1 w6 ^
Stratified sampling, 分层抽样
2 B! m! G; |! h0 qStrength, 强度% w6 d0 d4 S u, S2 A* w
Stringency, 严密性
: U3 u. m6 r/ c- `! e# [Structural relationship, 结构关系
8 l* |7 y5 J. E' iStudentized residual, 学生化残差/t化残差
( b6 |; R7 H- ~6 m U1 JSub-class numbers, 次级组含量
* j' y$ K' v" c; ?0 ZSubdividing, 分割1 U- i. @# A# v+ O
Sufficient statistic, 充分统计量
7 Z# G3 E0 A/ w2 ~8 }7 W& X; _# e: DSum of products, 积和
; T5 R6 {' a$ C7 [, kSum of squares, 离差平方和
% [* z* C4 l, F, J- J0 MSum of squares about regression, 回归平方和$ e* Q0 p3 j, K9 x5 ^
Sum of squares between groups, 组间平方和( H$ V+ y G0 a! \5 b# B
Sum of squares of partial regression, 偏回归平方和
& P# y9 v$ c3 b7 s& F8 P6 ESure event, 必然事件
D1 E, X( a' p; u' J8 O8 w0 o+ YSurvey, 调查9 F2 U& Y1 x3 {
Survival, 生存分析
: b* B9 w( Q) tSurvival rate, 生存率* H4 y) r' z* I/ s4 W$ u% U, r
Suspended root gram, 悬吊根图
7 n! u) o) J- s: {# RSymmetry, 对称6 j6 l0 {7 b, |% q7 `( M* | { H1 ~
Systematic error, 系统误差
( G& s' N7 T! x$ F, oSystematic sampling, 系统抽样% M2 D* a7 O$ o+ e0 V" x% Q
Tags, 标签
" m8 q# E0 ~ aTail area, 尾部面积
9 s# a: g# }6 Q; mTail length, 尾长
8 ]' ?. S/ H+ ?9 G8 hTail weight, 尾重
/ Z9 ?! t" o8 sTangent line, 切线
! K( Z* @; A( j8 k' hTarget distribution, 目标分布
0 j& [; z; n( c' \& a- ?Taylor series, 泰勒级数6 e% ~" J; e1 I- g1 i1 \% f
Tendency of dispersion, 离散趋势
2 v F4 M8 G' O, \ g! \Testing of hypotheses, 假设检验/ Z' v+ ]* A8 L
Theoretical frequency, 理论频数
# ]( `2 \9 u+ XTime series, 时间序列
8 V M' G R- X9 P6 v pTolerance interval, 容忍区间
; H" [4 U& {1 A4 [& g( y/ f$ kTolerance lower limit, 容忍下限
) h6 |2 w {, D* dTolerance upper limit, 容忍上限7 k9 N$ h2 x7 t7 R/ n
Torsion, 扰率$ E& x, W3 w3 `! z2 K5 n
Total sum of square, 总平方和, K8 e! A4 ]$ b9 W$ T6 @+ S
Total variation, 总变异
t1 p7 L' N& \% ^; c. STransformation, 转换6 O9 v% i7 F. B8 Q5 S# f/ d" x
Treatment, 处理
+ m/ s3 v/ z# ~( W4 W: f( OTrend, 趋势
7 L; T- Q( s K( L& b! A oTrend of percentage, 百分比趋势
8 U, h/ v0 S) r, J. {6 m$ n1 ^. c! FTrial, 试验) h$ Z5 [0 k$ r
Trial and error method, 试错法
4 L2 A- M C1 J k2 a% G1 QTuning constant, 细调常数, m. P1 q/ B$ C& X
Two sided test, 双向检验2 \, w! } ]! A
Two-stage least squares, 二阶最小平方
- X* _8 E& B9 WTwo-stage sampling, 二阶段抽样( H, [* n+ n1 w4 c* k, W
Two-tailed test, 双侧检验1 |1 U# ?, h4 e3 x. o- B5 U3 G
Two-way analysis of variance, 双因素方差分析7 E( p* W1 \) [: B
Two-way table, 双向表1 m3 h/ i3 s; l; f g
Type I error, 一类错误/α错误
$ V ^, o1 ?# U: y M, u* t* }Type II error, 二类错误/β错误+ [8 D' }/ o, D/ P* f
UMVU, 方差一致最小无偏估计简称/ {5 e6 N. r3 K
Unbiased estimate, 无偏估计3 L1 I# F0 m( e. h& n; X
Unconstrained nonlinear regression , 无约束非线性回归
: t/ F3 M8 [. V; u! lUnequal subclass number, 不等次级组含量
# C$ S# K( h+ A* }1 Y( pUngrouped data, 不分组资料. w- G J6 ~& _! v; f$ r. [
Uniform coordinate, 均匀坐标: E( b4 ]6 t! P( t; D0 W7 F
Uniform distribution, 均匀分布
1 u V/ H& l$ h, O( C( {Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
0 W( A5 n0 D- z" MUnit, 单元1 b/ ]7 O C2 v$ ~
Unordered categories, 无序分类8 D+ [( t6 `/ l8 b8 l1 P( W* W+ [( |
Upper limit, 上限
6 z) X- c- F# w* J3 qUpward rank, 升秩
6 }% G- A& }% ?6 mVague concept, 模糊概念* s4 i; K4 a* B+ G" a) h& ~" @
Validity, 有效性9 E( _8 E6 z0 k& Y" t
VARCOMP (Variance component estimation), 方差元素估计: ~0 D# g1 {; c0 {, Z9 k
Variability, 变异性' n4 Q' l. v0 b
Variable, 变量$ |0 x# O; l" r- q
Variance, 方差
) S' z$ l3 l: C6 E9 o, FVariation, 变异# w. _* p; p$ z% E* G4 ~
Varimax orthogonal rotation, 方差最大正交旋转 f% M, a3 e* S% K d$ h1 j
Volume of distribution, 容积
* ~7 R* h2 z, nW test, W检验3 v( w3 S# Y* ]' M* o
Weibull distribution, 威布尔分布$ @! T) P; B q4 l7 F/ q
Weight, 权数
3 b5 v4 |0 h3 M4 i: j2 U* t. a# fWeighted Chi-square test, 加权卡方检验/Cochran检验
/ {$ o0 Q3 p1 r: z; z! E5 g5 RWeighted linear regression method, 加权直线回归
. _% n- J# y& i8 q b- DWeighted mean, 加权平均数) A) S- v- G, D; ?2 F4 A
Weighted mean square, 加权平均方差/ R X t( O2 C$ ?
Weighted sum of square, 加权平方和
" V, ?8 Y P: C& e4 ?$ [9 B4 T0 f) iWeighting coefficient, 权重系数
% Z! I' K& J& ^8 K; E, D( M3 ^! ]Weighting method, 加权法 1 {& f, X1 m) J N) `7 @9 S
W-estimation, W估计量1 O) _7 M Q( |1 ]
W-estimation of location, 位置W估计量% f u; C+ H1 }& R8 M- O
Width, 宽度! y+ E( V" f# R6 C T
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
" ~4 ]( O) S9 HWild point, 野点/狂点
$ J- u x; T% y) aWild value, 野值/狂值# g8 z& J" @2 W0 j$ K
Winsorized mean, 缩尾均值0 F: O& W& _/ u
Withdraw, 失访 D# C0 a" L g8 p" [9 I
Youden's index, 尤登指数
" O2 }; G# C1 ^$ FZ test, Z检验1 z* b0 \ s/ y( E9 r
Zero correlation, 零相关
7 Z3 Z S0 E- J3 k( d, ZZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
