|
|
Absolute deviation, 绝对离差
% _6 M0 ^- q4 V' |, g" UAbsolute number, 绝对数% z5 R0 T7 i T& t9 i. t. Y- t
Absolute residuals, 绝对残差
; O% N% T* c# O4 k1 k Z2 M, j5 }! u( YAcceleration array, 加速度立体阵; Y" V/ L& [5 {0 t7 G: X$ G3 i
Acceleration in an arbitrary direction, 任意方向上的加速度
& e* {5 ~1 |8 bAcceleration normal, 法向加速度
$ I% {3 Q% B# E0 gAcceleration space dimension, 加速度空间的维数. z) h$ n# J5 d. ]' y1 O' c3 j' c
Acceleration tangential, 切向加速度% O4 z' B8 {0 g6 T1 H
Acceleration vector, 加速度向量$ }* h' d/ e) ^, r
Acceptable hypothesis, 可接受假设, p1 C( D+ ?, w- M
Accumulation, 累积7 R9 a& _9 ^" m8 b
Accuracy, 准确度
9 J3 j v9 g' v) a2 pActual frequency, 实际频数9 I" `* p6 A6 h7 z; F6 y) M
Adaptive estimator, 自适应估计量
2 W9 y9 R$ s$ g0 x, a) uAddition, 相加
8 z( I+ H9 w' j( UAddition theorem, 加法定理
& o6 d6 h- ^! ?1 p6 U+ JAdditivity, 可加性
0 o1 m# }% Y' ~Adjusted rate, 调整率* g6 n' d# h7 o9 O1 Z- g
Adjusted value, 校正值# J5 a" b; L5 D3 s2 R3 K8 \8 {
Admissible error, 容许误差
3 n% @& t6 i5 ~2 s3 q! s- j% L2 w. JAggregation, 聚集性
" f8 p4 f! w% a5 H. [Alternative hypothesis, 备择假设
5 O r/ u! m/ R0 g+ i$ X8 c0 XAmong groups, 组间
, K3 c, \! B4 b+ a8 m- O# o! O' aAmounts, 总量8 Z' P. T5 T* O) {9 U7 ~
Analysis of correlation, 相关分析
& E2 x- ^1 _1 e# t! `Analysis of covariance, 协方差分析
6 m a. ?5 p! `; y, z2 Y( TAnalysis of regression, 回归分析
0 M+ U4 j4 {) n, W1 i4 iAnalysis of time series, 时间序列分析" q s4 ~+ Q8 Z8 b2 d, t$ y
Analysis of variance, 方差分析- I) l! O0 X- v$ s* s- @& B/ f
Angular transformation, 角转换6 `! n q% V: s
ANOVA （analysis of variance）, 方差分析0 ~( D5 p D$ r- ]5 ~2 q
ANOVA Models, 方差分析模型& x' Q# x. n% O2 |. ]5 o6 J0 P
Arcing, 弧/弧旋
/ B2 ^, z' y" J% K6 CArcsine transformation, 反正弦变换
. G4 r8 T* k& ?4 N$ vArea under the curve, 曲线面积9 N$ g. C/ f' 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
) v( x/ Y. c# D$ T) M3 Y4 pARIMA, 季节和非季节性单变量模型的极大似然估计
[0 d F. q) oArithmetic grid paper, 算术格纸
( C0 h% a* @" s$ f9 W, d7 D: ^Arithmetic mean, 算术平均数, L4 ^6 h$ n: a9 U
Arrhenius relation, 艾恩尼斯关系
+ a7 ?' n( S9 o+ }Assessing fit, 拟合的评估
, U8 e$ D6 U0 z3 u0 }Associative laws, 结合律
' ~( L! ]: N3 |Asymmetric distribution, 非对称分布& j9 z; s7 y! h1 d" {
Asymptotic bias, 渐近偏倚
- B% o8 F. _; y& ~' f# }8 j8 m' aAsymptotic efficiency, 渐近效率
0 o* p( f& ~' n2 gAsymptotic variance, 渐近方差
' r% A$ N) v4 u4 PAttributable risk, 归因危险度
2 G7 l8 Q+ A) f0 M% A9 {" hAttribute data, 属性资料
9 p; K ^8 `, n% a% ^' \Attribution, 属性, S9 m* d1 F/ f. w1 q, O' `
Autocorrelation, 自相关* P9 f: d! o8 f
Autocorrelation of residuals, 残差的自相关: c4 u* }( |4 ~6 T' [! p
Average, 平均数
- {5 k0 n9 R& H) \$ s, I7 KAverage confidence interval length, 平均置信区间长度
1 U6 b; a2 H% o/ j: ]* D7 c( X/ EAverage growth rate, 平均增长率
, D( I/ S, _0 ?4 G6 aBar chart, 条形图; ?5 s9 }7 O) D* J" A' ~9 N
Bar graph, 条形图! \3 e1 {) [: P
Base period, 基期- y: A* @/ B5 ^# Y; Q3 t
Bayes' theorem , Bayes定理) I- n' u3 F$ E: b0 v8 k6 Y
Bell-shaped curve, 钟形曲线; ]+ L7 f6 h8 M5 A# {3 _
Bernoulli distribution, 伯努力分布
! ~1 p& N9 H; u% r7 T1 nBest-trim estimator, 最好切尾估计量: g! v/ C$ v- ]% `
Bias, 偏性 ?, d# R9 n( f3 P3 K! c3 a
Binary logistic regression, 二元逻辑斯蒂回归
* c9 g- Q9 Y- {8 vBinomial distribution, 二项分布
' b3 [5 S6 l! g0 kBisquare, 双平方" a$ d# l: L9 F1 h3 m
Bivariate Correlate, 二变量相关
% f! R7 h2 c( RBivariate normal distribution, 双变量正态分布$ z- X, J& f& j; c" o' C& x Q
Bivariate normal population, 双变量正态总体
5 G' C8 {8 X9 s0 @3 LBiweight interval, 双权区间1 k4 k8 a, e) k+ r2 y
Biweight M-estimator, 双权M估计量8 A4 a6 W6 T6 I' A7 f- A" u0 g
Block, 区组/配伍组
9 r1 |) s0 L* K |- Y; M. S, p0 `BMDP(Biomedical computer programs), BMDP统计软件包
7 \, N; r" u. \: M& w" y% V D0 HBoxplots, 箱线图/箱尾图
3 P3 b+ O) N2 B7 I5 A3 p) H/ ^Breakdown bound, 崩溃界/崩溃点
9 `1 d9 B" F) o7 Q" |, yCanonical correlation, 典型相关+ S4 @/ F' M3 C( M. i
Caption, 纵标目
: n7 ~" Y& M" E% O# ]* B5 ]Case-control study, 病例对照研究
8 X* J I, R9 G0 OCategorical variable, 分类变量
* a9 G+ z5 Y T! y" VCatenary, 悬链线# W5 ?: p# V) E# x) z& _2 i8 ~
Cauchy distribution, 柯西分布
! {, r4 J0 w+ o! w" \Cause-and-effect relationship, 因果关系8 s! j6 f# s$ d, f" ?
Cell, 单元
; [0 E% F+ e5 q1 \1 c! t2 Q3 ?+ RCensoring, 终检1 i- M# @& r9 o- N7 W
Center of symmetry, 对称中心
3 E: f1 c2 o5 A9 K; _Centering and scaling, 中心化和定标, r Q) H" a/ P& } r& L4 ]
Central tendency, 集中趋势
8 ^5 A5 C& r$ W' l: y ~+ y9 ^8 @Central value, 中心值
; U m9 s* y( v8 f2 v2 V. v2 X' hCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 Z. \/ C" B% t) Y' W$ ^% j
Chance, 机遇! p/ y9 h( \$ J' t
Chance error, 随机误差/ ^% N$ W9 |/ D
Chance variable, 随机变量% A, f. b8 \/ x5 b; |1 m
Characteristic equation, 特征方程
9 j$ [( M" x* K. a1 MCharacteristic root, 特征根8 O7 _. \. x0 @' |6 O7 [
Characteristic vector, 特征向量) N t# F. P) F& a
Chebshev criterion of fit, 拟合的切比雪夫准则
* o$ Q- P. j7 ^& e! L2 {& ~Chernoff faces, 切尔诺夫脸谱图: x7 X9 D/ v4 P% |. _* B( R
Chi-square test, 卡方检验/χ2检验- w3 V- k" K/ T
Choleskey decomposition, 乔洛斯基分解+ f, U2 @7 T! x0 {+ q+ i. ]
Circle chart, 圆图
; |# q5 b( t' m! V. sClass interval, 组距' u2 W8 z, O" P3 B
Class mid-value, 组中值1 p* ~- ~6 g# c( f! L9 t
Class upper limit, 组上限
! T- X. @' n$ @Classified variable, 分类变量& E; f4 ]1 r2 W1 o% k- K
Cluster analysis, 聚类分析
}. |0 n& ^6 q+ a$ pCluster sampling, 整群抽样/ j2 E, @* Z# s& ~5 j9 a
Code, 代码
/ i, ?: @& B+ d' LCoded data, 编码数据
+ l) C/ B7 o OCoding, 编码6 ?# p v! ]: J: \5 L: Z3 x4 v4 i
Coefficient of contingency, 列联系数
4 b! m# D g9 cCoefficient of determination, 决定系数
0 f# ]$ I r/ U2 W4 P$ {1 QCoefficient of multiple correlation, 多重相关系数7 I9 o6 c& Q5 }; y9 c, @" T
Coefficient of partial correlation, 偏相关系数
7 l6 M o6 C/ C/ n" n( F5 cCoefficient of production-moment correlation, 积差相关系数
3 H) ~! p) D& [Coefficient of rank correlation, 等级相关系数. ^ A: T. G: n/ z
Coefficient of regression, 回归系数
4 Z5 D8 G8 _0 ~( pCoefficient of skewness, 偏度系数" K* S( x* f' j
Coefficient of variation, 变异系数6 J9 d& S/ z, t% g& X
Cohort study, 队列研究
( C2 v- T1 g. g5 VColumn, 列4 p: e' \" X: E# G: {3 q7 d1 l' ^% j
Column effect, 列效应
) q1 v% D8 l' ~5 b, g" ^Column factor, 列因素0 a# q& u/ f; s2 k7 [8 a* d& O
Combination pool, 合并
8 ~- D9 F- }. A7 ]: e0 l( z! WCombinative table, 组合表" N* f) {( O6 g5 R
Common factor, 共性因子
( t# o t; x' I' P9 kCommon regression coefficient, 公共回归系数- U; }7 A: V# D5 J( t6 c
Common value, 共同值" F- L1 O% \$ h0 Y8 s# Z6 L! S
Common variance, 公共方差
* |0 T3 r; G ?2 u/ [# r6 LCommon variation, 公共变异+ V6 d' {. x% c4 M" S7 p* l
Communality variance, 共性方差
* w6 U( c* y- RComparability, 可比性
' N i2 R2 S) |' z' A" G+ I5 EComparison of bathes, 批比较* @& E* K- g+ h* o g
Comparison value, 比较值
9 {( x1 v! n6 ~% h& @* LCompartment model, 分部模型) |4 ~& x8 v" e: C E
Compassion, 伸缩& I: f+ t5 h% r* ]7 ]
Complement of an event, 补事件" B+ e- W, T/ S
Complete association, 完全正相关1 r" ^3 G2 P5 h+ M& {8 q# V
Complete dissociation, 完全不相关3 z3 ~6 i# f1 ^2 e( i; }
Complete statistics, 完备统计量
, g4 t, ^9 r; d, T9 o4 b& G# OCompletely randomized design, 完全随机化设计
$ S& H: G, o o2 N2 i7 |3 UComposite event, 联合事件
2 ?9 f! k- o% |* J% lComposite events, 复合事件
6 }; {) F( W0 F" GConcavity, 凹性. p+ i2 `, T1 Z2 `
Conditional expectation, 条件期望
6 A% n' c- K4 o9 ]+ {Conditional likelihood, 条件似然
3 Y) D2 [! W& gConditional probability, 条件概率* j& I, L2 j3 O$ L( m' U3 c
Conditionally linear, 依条件线性
7 _, p3 c; I# m; p: S) d, dConfidence interval, 置信区间4 ~7 D6 E$ N+ ?3 I: V9 `
Confidence limit, 置信限* g9 W ^9 |2 @% Y7 X5 ^ w1 A3 G
Confidence lower limit, 置信下限. D0 a9 L* s( C, H1 Q
Confidence upper limit, 置信上限+ ]# M+ N4 v0 w$ q) d) n2 }
Confirmatory Factor Analysis , 验证性因子分析: v5 c9 _* Q) u |
Confirmatory research, 证实性实验研究
8 N0 ], n- l. G$ p. O5 O' FConfounding factor, 混杂因素
) E, b" W; E- m! }1 Z& hConjoint, 联合分析
0 r( f: _5 f* e2 CConsistency, 相合性, Q) m4 m# |5 F$ s
Consistency check, 一致性检验
$ J! [9 c# [9 E* FConsistent asymptotically normal estimate, 相合渐近正态估计6 z' p8 ~6 d# ]& m+ w5 k' u
Consistent estimate, 相合估计
p7 B8 ?% b* zConstrained nonlinear regression, 受约束非线性回归
) F9 j" V) {; }. `, j; g9 lConstraint, 约束
1 E: p0 k" b- B" A) b- iContaminated distribution, 污染分布
" L; \, e, o- kContaminated Gausssian, 污染高斯分布
/ W9 P2 k! X/ k/ R% Z( ^5 t# J! AContaminated normal distribution, 污染正态分布
4 z m! I, |( c+ d1 vContamination, 污染
3 P$ v( V: W, g+ ~7 e! h4 YContamination model, 污染模型& N1 m, y2 M6 U4 X0 w
Contingency table, 列联表8 a$ K3 A8 b, G4 m4 Z
Contour, 边界线: M# s) \: g$ L7 A$ B: X% A
Contribution rate, 贡献率
3 o: l( D/ l2 [+ c5 oControl, 对照
3 D, M+ F; Y; r; b! pControlled experiments, 对照实验
) p- F" @8 b! V$ y' @Conventional depth, 常规深度9 L# L9 X- A% l8 ~" w) f6 v/ W
Convolution, 卷积
8 U4 {& w- v' |2 P/ y9 Z0 L+ ?Corrected factor, 校正因子
, g/ r7 L. f1 t& A6 ~Corrected mean, 校正均值( @* I6 D7 v# E) s: W) \* c, S, B: ^
Correction coefficient, 校正系数
- g/ u+ j/ l# o9 V6 iCorrectness, 正确性
6 G/ ~ f2 _, B. B" \Correlation coefficient, 相关系数
3 w# {2 |- S0 Y' T' ICorrelation index, 相关指数
# e; n$ j& ~: A, ]Correspondence, 对应4 z: t7 t, Z: O( ]
Counting, 计数
' O5 `/ c' h1 h J3 {5 jCounts, 计数/频数
- _- ^) ^9 c4 Q! Z" \* ]/ QCovariance, 协方差7 r; V2 A3 T2 G# m: F, m; Q& c
Covariant, 共变
( }. V$ b2 d7 g9 g' H6 C q |. H$ GCox Regression, Cox回归
w3 W6 d" i \; HCriteria for fitting, 拟合准则2 f# J8 y9 {# J9 d: Y
Criteria of least squares, 最小二乘准则7 y* W( p8 L+ y9 Z0 f+ \0 \
Critical ratio, 临界比1 ~% O5 y- g! `( e1 R
Critical region, 拒绝域
7 z9 T$ A8 |! H; F9 D: hCritical value, 临界值
, G" [ x" c5 c3 q8 }7 [' yCross-over design, 交叉设计
$ o5 F @; f# \8 H0 PCross-section analysis, 横断面分析 H" |% T5 g+ |! ? E
Cross-section survey, 横断面调查" u: @ S3 G- _2 Q& H! @& E' B( O
Crosstabs , 交叉表
' F; j" g" n; \ _# D2 DCross-tabulation table, 复合表
9 ?3 \0 [# W y) R0 x8 B0 n$ nCube root, 立方根
/ `" z" _# B" a* |Cumulative distribution function, 分布函数- f9 M! U' p1 B9 ~6 \& k
Cumulative probability, 累计概率
- `6 ^* j U* u& s# \3 MCurvature, 曲率/弯曲3 t7 m9 I% f; U4 L" u3 ~+ t# J( ~
Curvature, 曲率+ I9 N5 M( h" v' l/ }
Curve fit , 曲线拟和 / d- n% [" q: K( ~0 q& ]
Curve fitting, 曲线拟合6 t: i+ N* H( ?! N- \2 i9 Z
Curvilinear regression, 曲线回归
6 B5 V8 w+ B% s1 X( L% F& E' WCurvilinear relation, 曲线关系
- x. A& g, w9 D0 h) o7 E. xCut-and-try method, 尝试法
4 m, s- L& d! a( d5 {( p ECycle, 周期+ o F5 n. z7 a' B" U! O' \# _
Cyclist, 周期性
$ R- n( u! P# v" n7 S7 y7 P2 OD test, D检验
' [- X: `' r5 P- L" J8 w+ N' B& rData acquisition, 资料收集0 U, z2 n4 e6 e0 U* Y
Data bank, 数据库/ A5 _; O0 X2 N- G
Data capacity, 数据容量# ?9 w$ E( a( y( Q4 P% c. G
Data deficiencies, 数据缺乏, G! x' s8 F! z% E) p: [
Data handling, 数据处理
" m2 a- H7 _/ z1 ^' YData manipulation, 数据处理
; z* Q% g R- x& D- MData processing, 数据处理
. h& v) z3 V. ]! YData reduction, 数据缩减9 c& c5 |+ @. j3 i# V: [. p
Data set, 数据集$ Z" L5 K- q4 H( u
Data sources, 数据来源" n! F( A$ t R% V
Data transformation, 数据变换" i" M; m9 g, u- e
Data validity, 数据有效性# T, L0 q5 b1 ?$ t9 Z& v
Data-in, 数据输入' T+ \/ Y7 ?; L; F
Data-out, 数据输出
+ z) }! H# ~& r6 w- y& a. lDead time, 停滞期
) @' d9 p& q( T% }Degree of freedom, 自由度
$ }' k7 {1 ^6 b2 V# SDegree of precision, 精密度! C% ?( C) ~% ^
Degree of reliability, 可靠性程度
& H" X8 J4 c; `$ f0 j/ n" n5 o7 hDegression, 递减 [& F# b# I+ L/ v0 U/ T! \7 Y( v
Density function, 密度函数
`/ u# L& B3 I+ M6 `, ^Density of data points, 数据点的密度1 w9 D- [2 E+ I6 n
Dependent variable, 应变量/依变量/因变量/ S6 f" m8 x2 a, j" N- L
Dependent variable, 因变量7 p% B" u% a- N" i
Depth, 深度
; `/ N; H! X2 b* c& N* HDerivative matrix, 导数矩阵
7 a0 |- k+ [- sDerivative-free methods, 无导数方法7 c( B3 t9 S7 `; w( T
Design, 设计' K) r5 ~+ D/ y& ?6 e G& A6 I2 Y
Determinacy, 确定性# F! H$ J9 J+ N. d7 R R. r$ J8 L
Determinant, 行列式3 ?5 C! j& |& s5 O( M: D
Determinant, 决定因素' @# [+ [0 Y- a* y6 o' F6 k
Deviation, 离差 P7 u# Z C7 N- ~; i0 ^
Deviation from average, 离均差 Z2 x# v& U$ ]
Diagnostic plot, 诊断图2 |, m1 [4 O2 Y; h5 V* u/ v
Dichotomous variable, 二分变量2 u& j. n7 p* j& @7 n; z
Differential equation, 微分方程
4 T* f) g4 d+ I" v3 `Direct standardization, 直接标准化法
3 p# x; P/ Z& n4 ~ TDiscrete variable, 离散型变量( M! C- g8 k) W- t+ h; q/ o
DISCRIMINANT, 判断 1 \3 a+ {* k# Y; {
Discriminant analysis, 判别分析
' o- F: C3 k. t# n; Z# W7 fDiscriminant coefficient, 判别系数
6 I+ @( H, f! r; i) t# IDiscriminant function, 判别值
- P J% F7 w" }) z. r% y1 f) N7 IDispersion, 散布/分散度9 m! n6 j! D+ u' |6 x* y6 j0 H- Y
Disproportional, 不成比例的
: d( @5 I* ^# J# lDisproportionate sub-class numbers, 不成比例次级组含量" g2 F/ j; G9 j9 D; C' N1 K! T
Distribution free, 分布无关性/免分布5 `; U V1 \+ N! D1 {6 _; J5 H
Distribution shape, 分布形状
, {/ ?0 v2 H. E6 ]! y% o1 U0 ^4 X5 `$ kDistribution-free method, 任意分布法/ W4 U( M$ g: H& K* _3 H6 [
Distributive laws, 分配律; R) f' ?2 W9 M* y1 N6 k$ [' i; }
Disturbance, 随机扰动项! g& w) d5 Y: E- D6 v
Dose response curve, 剂量反应曲线
- @5 A! { h4 c" I s+ d$ }* kDouble blind method, 双盲法/ X, X, v+ ]1 l% c' a' I/ @' h
Double blind trial, 双盲试验0 o: n0 H( \ ^* K& e* H
Double exponential distribution, 双指数分布! ?% w: H E* R) }1 v# o& ?5 F: j
Double logarithmic, 双对数
: ~/ E) b; j& Y8 J; vDownward rank, 降秩
9 i; P8 Z% }" N9 c+ H% K# ^+ a& yDual-space plot, 对偶空间图1 w2 Z; u2 K- _1 V! b+ y
DUD, 无导数方法3 m* `: s5 W$ @$ f/ I A1 R
Duncan's new multiple range method, 新复极差法/Duncan新法
: c% y% V2 d# e! ^5 Z1 g/ SEffect, 实验效应, d# I) y" X7 a/ @$ @
Eigenvalue, 特征值
- t+ `+ |7 U2 m* Q. A5 eEigenvector, 特征向量( ^( x) F# y/ T0 ?) [6 T
Ellipse, 椭圆
7 {9 a2 E7 K. I5 lEmpirical distribution, 经验分布8 W* l2 x# h% v% J
Empirical probability, 经验概率单位
* I' ` T2 I: y) e. }4 @( s( KEnumeration data, 计数资料
7 r& Y$ a& F6 y: T9 h& @Equal sun-class number, 相等次级组含量& f7 h/ C% _7 Y2 o
Equally likely, 等可能
% Z: G( v+ p6 i3 [9 d3 u/ KEquivariance, 同变性& |0 d! u4 P2 Z! Q2 s
Error, 误差/错误" ?: D4 w0 M5 |. E; M" s
Error of estimate, 估计误差 f9 j; m3 |, C8 `8 X3 A
Error type I, 第一类错误
) D" a! `4 O- e ~' eError type II, 第二类错误7 t: M# {3 s9 G: H/ T% K$ C9 l& S
Estimand, 被估量; ^; E' J4 k2 Y5 ~) ^, ]& U
Estimated error mean squares, 估计误差均方
* v+ ]0 C% L5 f) A% N- cEstimated error sum of squares, 估计误差平方和8 _7 w. x2 E8 o6 b0 }
Euclidean distance, 欧式距离( |8 ^9 Z; \( |/ Z7 G
Event, 事件4 V a6 ^; m, A9 m7 ?
Event, 事件0 {4 E* L" e! q5 A& s( f* g
Exceptional data point, 异常数据点
* {: @3 A8 x% S. y* J; ?/ TExpectation plane, 期望平面
1 _, I" s4 V3 T* h B7 l' o6 I: C5 t! SExpectation surface, 期望曲面5 x) T2 h$ H9 E" ?2 U
Expected values, 期望值
! E( i: C8 a5 cExperiment, 实验
9 l, m6 R. r- V+ _Experimental sampling, 试验抽样% {, k+ |. s8 m& z
Experimental unit, 试验单位
. K( f9 s. |/ k8 U( mExplanatory variable, 说明变量
2 M$ E- a2 g$ h' y7 n5 t0 o" D5 HExploratory data analysis, 探索性数据分析
2 A# ?- o4 e0 I8 q; D! cExplore Summarize, 探索-摘要2 ~; s a0 |; @ z) U$ z1 ]4 Z* t* _) G1 R
Exponential curve, 指数曲线6 U8 i7 c7 z, j8 z7 @
Exponential growth, 指数式增长: Y/ j' {5 `. e4 E
EXSMOOTH, 指数平滑方法
. S7 B/ _: T" |' N& w$ {, e. dExtended fit, 扩充拟合4 v. a, j" Q. }, t
Extra parameter, 附加参数. ^$ v2 o/ A; L' {; [
Extrapolation, 外推法; @5 y3 j/ V" J, {% i1 c
Extreme observation, 末端观测值1 t* r% [ ]* ~# F/ z0 z
Extremes, 极端值/极值5 ]. _5 w3 v2 D7 \7 j: }! Y7 r
F distribution, F分布
8 R, `' _4 u" E' s( J0 DF test, F检验
+ \/ ~8 j8 N g5 G# c4 B& [Factor, 因素/因子8 S7 e! j9 T$ T8 |: |+ j: O0 a
Factor analysis, 因子分析/ [) ^# L; s' V3 @" R! u6 q
Factor Analysis, 因子分析
- B/ S$ H4 A* [) _4 DFactor score, 因子得分 : X. h+ L8 I. w6 _" H0 J6 [6 d, o. T0 E
Factorial, 阶乘
# C$ Y& ~/ O- D+ H1 B( e8 Z0 j4 gFactorial design, 析因试验设计
9 B9 ?! Z. M$ ^0 H3 XFalse negative, 假阴性
1 k, ^; L% |6 yFalse negative error, 假阴性错误6 c1 w' q1 x# ]7 S6 B
Family of distributions, 分布族4 q0 m# U: k! Y# l2 P" @6 ?; [! Q
Family of estimators, 估计量族
, |. Q$ a& x7 A9 e3 G- cFanning, 扇面
. Z0 S0 Q" }* P6 Q: K7 OFatality rate, 病死率
" [% n. i+ _( F8 g8 D) u+ bField investigation, 现场调查
6 j) J2 k+ v0 j, @/ v8 E( @) L! ~Field survey, 现场调查 a6 r( S' K+ S# { F/ ~
Finite population, 有限总体# s0 ]2 i' P9 p1 w
Finite-sample, 有限样本
4 A: {1 k6 t5 s. D) XFirst derivative, 一阶导数- d3 ]2 r6 m3 k; y9 X
First principal component, 第一主成分4 e# f# H8 \( r
First quartile, 第一四分位数
9 U$ `4 s& O1 J5 K1 p9 ZFisher information, 费雪信息量( `1 u# }, }9 w' L% t& f
Fitted value, 拟合值
4 ]+ |0 a" u+ n% F# r* s0 ?7 ZFitting a curve, 曲线拟合
/ H9 @: O% s* ~, o: QFixed base, 定基, |) L% ^* J; N2 d
Fluctuation, 随机起伏
8 C0 N9 b: M, n" w& P. K- }Forecast, 预测$ L& X! j5 P7 g2 l8 [
Four fold table, 四格表: U: U- i3 Z' E2 V- a- M3 Q
Fourth, 四分点 L* P! [: X/ G& U: W4 b& l
Fraction blow, 左侧比率
& W; R/ x' ~3 p, MFractional error, 相对误差2 N8 Z/ P0 O2 `; I" B" n7 b
Frequency, 频率; e+ o6 y A' n! B
Frequency polygon, 频数多边图- n2 U* i; s; D
Frontier point, 界限点
8 ~) R5 U' U; X1 t# xFunction relationship, 泛函关系" \4 b/ f. L9 {; N
Gamma distribution, 伽玛分布: Z0 l2 D" C4 m+ Z1 E
Gauss increment, 高斯增量# p) X$ s$ l% v# ]
Gaussian distribution, 高斯分布/正态分布2 b7 G! l, O/ x; N
Gauss-Newton increment, 高斯-牛顿增量
& [) `2 B! }3 W. A; s @* YGeneral census, 全面普查
2 n" G/ A2 i) D2 @3 eGENLOG (Generalized liner models), 广义线性模型
+ Y; N6 T0 W- N2 |Geometric mean, 几何平均数
% y+ e2 g* Y, B7 d, V& `Gini's mean difference, 基尼均差
4 Y# e4 Y; F& SGLM (General liner models), 一般线性模型
5 m( x$ S6 x; P5 N. N( G7 @1 P3 V+ `$ YGoodness of fit, 拟和优度/配合度2 r9 n6 C- q) U4 c$ o
Gradient of determinant, 行列式的梯度7 S Y( t! D- R, F. i
Graeco-Latin square, 希腊拉丁方
9 P( ~0 x# t/ l+ ]' f5 S& bGrand mean, 总均值
& N% u5 G, V; b2 R* @! e% g5 [Gross errors, 重大错误- C9 x( |* r4 d
Gross-error sensitivity, 大错敏感度
) K2 E9 \( c6 |0 Y. p! p4 ?Group averages, 分组平均, d3 f. F7 c) a' }- B% J
Grouped data, 分组资料
) a! P1 `% X$ ^Guessed mean, 假定平均数2 y. p) K) l# v+ q# x+ n
Half-life, 半衰期
, _" p3 e+ r8 M* `# h9 E8 m9 SHampel M-estimators, 汉佩尔M估计量
0 U( f$ S0 K! @0 yHappenstance, 偶然事件* o# \' r- v2 O& I$ X& C
Harmonic mean, 调和均数) Z& j5 A5 q+ ^
Hazard function, 风险均数- M7 u# i# C( G. U! N
Hazard rate, 风险率
4 @; ]3 Z. n) N9 p C( j9 tHeading, 标目 * e; |" W! h3 o1 d* O6 x: O
Heavy-tailed distribution, 重尾分布
% X! R% c0 V+ v d3 z5 FHessian array, 海森立体阵
6 m+ @* n8 V% w( ~( J0 [; cHeterogeneity, 不同质
K' M* G, a3 f0 U+ F% ] s% [Heterogeneity of variance, 方差不齐 . Y/ j, C' f9 |% W/ Z
Hierarchical classification, 组内分组: V3 ?3 }' l3 [# a1 I+ V
Hierarchical clustering method, 系统聚类法7 K s1 i2 J' V1 U/ F" h6 v
High-leverage point, 高杠杆率点
; g$ u; J1 S# e# C SHILOGLINEAR, 多维列联表的层次对数线性模型9 F, s1 z; X' h" o
Hinge, 折叶点/ o7 C' C$ Y. _1 M9 `' z0 c2 E9 i
Histogram, 直方图! o- h+ Z' W1 `3 Y
Historical cohort study, 历史性队列研究
8 z" H o. t4 A7 K. d9 KHoles, 空洞
5 O' @* o L$ Y" k: r! |HOMALS, 多重响应分析" _6 {/ v5 o1 U$ `) B
Homogeneity of variance, 方差齐性
) X" k5 ^% ?- fHomogeneity test, 齐性检验
9 B) |& q6 |6 U$ eHuber M-estimators, 休伯M估计量6 i, w! ~9 B% d l3 N% y5 `0 \2 \
Hyperbola, 双曲线
! M' N! u. i* {" sHypothesis testing, 假设检验* C3 Y7 L9 }6 B+ T' u
Hypothetical universe, 假设总体
) f1 ~' f4 T; F7 [( m% bImpossible event, 不可能事件
" ?6 k" i) o& ?2 P& m% CIndependence, 独立性& r1 g$ _/ @6 @8 ]9 m2 L _
Independent variable, 自变量
0 R0 a- G3 T9 }- x; n& ]+ u1 BIndex, 指标/指数( h4 k) K7 g, w# {
Indirect standardization, 间接标准化法
. p1 M; r0 Q. ~% `: x0 O3 QIndividual, 个体
4 P% M5 k0 }1 H5 `' w b4 ?4 VInference band, 推断带
$ q7 n. |3 C Y# S; n% ^Infinite population, 无限总体
: H3 j) H9 N6 r( T9 b) eInfinitely great, 无穷大2 i+ }8 ]$ p2 I
Infinitely small, 无穷小
0 X; t8 H. r% W% ^Influence curve, 影响曲线' E7 A! u+ @$ V- |" e' R
Information capacity, 信息容量
# K) u9 j: o; U/ Y1 tInitial condition, 初始条件) v/ J2 V/ n3 {; R. T+ }
Initial estimate, 初始估计值( @1 B# p2 y" j0 r0 G+ v7 V: v
Initial level, 最初水平
; Q! |. u+ ` xInteraction, 交互作用- v# D# u5 o, I Y0 J* d; l
Interaction terms, 交互作用项$ @9 L/ d* @4 v
Intercept, 截距. h( R2 }1 `/ K: W' s
Interpolation, 内插法
1 e& T/ U# ]0 V8 GInterquartile range, 四分位距$ x1 R( t7 |8 }6 m
Interval estimation, 区间估计# n/ `% v+ L: g$ c
Intervals of equal probability, 等概率区间2 d& c4 k2 ~7 A( F
Intrinsic curvature, 固有曲率6 w* A+ {* \3 E! z2 @' h0 @
Invariance, 不变性
. o5 g5 i% g _$ l- p4 yInverse matrix, 逆矩阵
1 Y' X% ~" l ]5 o! g& N6 M8 u1 oInverse probability, 逆概率
, Z% b+ [3 w8 K# X6 C! [Inverse sine transformation, 反正弦变换
8 N. w1 [# w8 KIteration, 迭代 6 [4 N; K- @% |& [# T
Jacobian determinant, 雅可比行列式+ ?+ f( d4 h& w% y! b; B
Joint distribution function, 分布函数 a! ]7 P' B8 d' d: d% K
Joint probability, 联合概率2 i: H2 c/ Y% ^
Joint probability distribution, 联合概率分布
- Q7 [% |. P4 D0 P+ M5 @+ XK means method, 逐步聚类法* s; |) c$ j) `2 \5 c( G
Kaplan-Meier, 评估事件的时间长度 ) Y% h. ~+ Q7 `
Kaplan-Merier chart, Kaplan-Merier图: x* F u. t0 C7 l( U& Z) K" [2 R
Kendall's rank correlation, Kendall等级相关
9 P8 J* e" \, O$ V* C2 TKinetic, 动力学$ _- a U+ k7 n- I9 m
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
1 Z9 d" g/ x4 V# u* n' @& H8 r LKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验3 Z; ~3 }% E; Z
Kurtosis, 峰度0 T r/ D# E/ C0 `( o# C
Lack of fit, 失拟$ H" _: v% q" i
Ladder of powers, 幂阶梯
], P4 X) g+ q0 q' O1 O& xLag, 滞后4 C2 G3 ~/ [: S. \, r6 u6 D. v
Large sample, 大样本
( o/ o0 T; w6 o2 y, iLarge sample test, 大样本检验
4 Q# P/ T, K* S6 pLatin square, 拉丁方7 K1 x7 Y+ ?; @' g
Latin square design, 拉丁方设计, U6 }1 ]4 U5 F+ K# {
Leakage, 泄漏
/ K2 j% ?/ }8 [; t8 s, {Least favorable configuration, 最不利构形" E: e! M( h U, K5 w1 @, C
Least favorable distribution, 最不利分布
" t7 M! t7 N" I0 }/ Y5 m; G% e4 hLeast significant difference, 最小显著差法0 B* I8 ]& B! }8 Y
Least square method, 最小二乘法
; S6 o m8 J- c7 ?Least-absolute-residuals estimates, 最小绝对残差估计/ S5 u+ \ u- c; @) p. |( y
Least-absolute-residuals fit, 最小绝对残差拟合
- K- J/ s8 s7 a) A8 `' MLeast-absolute-residuals line, 最小绝对残差线
$ n; C/ b: ~/ }3 U" t9 |Legend, 图例0 e: W2 ]2 [7 r: ~" t7 s' k
L-estimator, L估计量
1 c1 V, z: e1 z+ `* uL-estimator of location, 位置L估计量1 X. j H9 [9 M c4 v1 q
L-estimator of scale, 尺度L估计量
/ v5 I+ @% y& _1 h6 ELevel, 水平
3 t1 M% G8 d# C% Q/ eLife expectance, 预期期望寿命
1 Z2 v; ^; B, C- eLife table, 寿命表
% {- T5 u) S, kLife table method, 生命表法
# g ?& R! [* \5 c2 {5 a' {Light-tailed distribution, 轻尾分布$ ?8 |6 _7 W A" r& v0 o) z! [
Likelihood function, 似然函数% i& X" ~% p0 I
Likelihood ratio, 似然比
) v6 v. m7 q9 J. x+ i; y' z5 mline graph, 线图
+ ^: @& r* R! m9 c/ B! rLinear correlation, 直线相关
+ D7 c& t+ H. s3 Z4 g i' kLinear equation, 线性方程+ S/ A" e$ L: Y8 H8 z! [# {
Linear programming, 线性规划) n3 J1 F! E1 t# O; w
Linear regression, 直线回归# D3 y# e" P$ S: U6 g
Linear Regression, 线性回归
5 B, b* B5 o: y# `# C2 Y: r: \9 e, zLinear trend, 线性趋势# m2 C9 m% N, n0 s: p S0 C( _" h
Loading, 载荷 " \% }7 f6 u; u9 V" }
Location and scale equivariance, 位置尺度同变性0 ` O7 V: D& N2 q8 |
Location equivariance, 位置同变性( z% i+ n/ v0 `% L$ t$ o+ i
Location invariance, 位置不变性/ m4 r! L: m; S/ [: t
Location scale family, 位置尺度族
0 {- X% y2 Q/ X/ D0 {Log rank test, 时序检验
- ?& x; r: ]" n7 Q0 cLogarithmic curve, 对数曲线
) D% D7 e, c0 ]7 R3 u: TLogarithmic normal distribution, 对数正态分布
3 }% e- U( x8 LLogarithmic scale, 对数尺度
- ~7 a/ D8 }6 d9 T1 g& [6 GLogarithmic transformation, 对数变换
0 V* c$ u2 }+ SLogic check, 逻辑检查- V a T* C7 @
Logistic distribution, 逻辑斯特分布
9 G7 c; C' [* \# c7 L* [Logit transformation, Logit转换, ?" a7 u& V7 S6 L* H
LOGLINEAR, 多维列联表通用模型
2 X% M9 \# D! \Lognormal distribution, 对数正态分布& t4 a0 L5 x P3 N5 ~$ L) j7 K
Lost function, 损失函数4 ~8 Q5 J6 g, X2 P: {( t! W
Low correlation, 低度相关
+ L. n1 H% v+ W# U! C$ Q& k0 RLower limit, 下限
1 w: a( [4 |; F, ~7 j2 ZLowest-attained variance, 最小可达方差4 C7 H% F: Z! C
LSD, 最小显著差法的简称7 N* R& s& ]. j3 W! N4 |9 {7 E" z
Lurking variable, 潜在变量1 j& f2 e% O+ @4 G. k7 p
Main effect, 主效应- ^. Q+ G d! V3 G, P
Major heading, 主辞标目
3 k l( ^' L q2 IMarginal density function, 边缘密度函数
/ B: R, x; i7 X/ H* ^Marginal probability, 边缘概率1 u, E" Q' B& {8 z# w9 m- Q7 S
Marginal probability distribution, 边缘概率分布
! ?4 h: t' W. A- BMatched data, 配对资料
. e- j7 ^! O+ JMatched distribution, 匹配过分布+ c! u1 |3 l4 v. W8 D/ e5 O
Matching of distribution, 分布的匹配
# R' ?! {6 i, |3 D1 P9 NMatching of transformation, 变换的匹配
, x: m+ L- q9 ]; H8 QMathematical expectation, 数学期望
; Z2 v+ ^) v& L2 k4 C: HMathematical model, 数学模型
6 e# N: u2 [6 z7 K2 i% Q, \Maximum L-estimator, 极大极小L 估计量; ^) n7 L- N& V, q4 P
Maximum likelihood method, 最大似然法8 m) B+ R" D# V# K/ k+ i
Mean, 均数3 P8 T9 }) T0 c' t) L9 u
Mean squares between groups, 组间均方
- [: L# H Z9 c, t$ AMean squares within group, 组内均方
) P. F9 P9 ~' t, S" eMeans (Compare means), 均值-均值比较
7 h" h. P7 p) ~Median, 中位数
2 H8 T2 {. J' ]+ wMedian effective dose, 半数效量7 t3 u* Q, |8 ]6 s
Median lethal dose, 半数致死量3 Q$ C4 Q0 t1 j' R# I3 a2 Z2 X
Median polish, 中位数平滑+ y; C& q; m* u7 H" q. u
Median test, 中位数检验
) k3 ~% v6 g. |: p' q+ AMinimal sufficient statistic, 最小充分统计量
+ k% a4 f; O2 Z, s: ~$ pMinimum distance estimation, 最小距离估计
+ V" { J" _5 HMinimum effective dose, 最小有效量
/ r* n& l, x+ w5 ^6 ~7 rMinimum lethal dose, 最小致死量
6 Y7 G y5 d9 T/ gMinimum variance estimator, 最小方差估计量5 R' L8 u+ f2 }
MINITAB, 统计软件包5 R' b. V9 e8 F4 r
Minor heading, 宾词标目/ P0 x7 f! b6 b1 r- U
Missing data, 缺失值/ m/ v6 T& K/ b
Model specification, 模型的确定
; |! h! Z9 a# ?6 hModeling Statistics , 模型统计
. ]2 P8 j m* {5 R# z- m0 T/ `Models for outliers, 离群值模型( N9 [$ x: `6 K# ?6 d3 m0 R( W u: s
Modifying the model, 模型的修正4 }7 W5 i) h- _8 ^
Modulus of continuity, 连续性模6 V2 D: z# e, D3 X' c8 Y. p
Morbidity, 发病率 $ _) u9 l) L8 V2 V: |! i% z
Most favorable configuration, 最有利构形
" C! W% c2 _% C- M; f, H1 t1 ?' hMultidimensional Scaling (ASCAL), 多维尺度/多维标度
: N/ D1 ^7 B, n/ Q0 ZMultinomial Logistic Regression , 多项逻辑斯蒂回归0 u3 w3 H7 O* E. W0 T; ~
Multiple comparison, 多重比较
2 R4 I7 `, k" e" {; L* A7 Z* y0 NMultiple correlation , 复相关
$ M1 K' y9 Y: }3 S" {2 \6 F7 ~Multiple covariance, 多元协方差
! c3 R! H7 z! C* N% i" ZMultiple linear regression, 多元线性回归
/ d$ i; ?3 o. ^/ b+ _, o5 ~Multiple response , 多重选项
6 T" C- S- ^+ g% m( E3 p6 ]# F6 YMultiple solutions, 多解
5 U$ Z) f4 b) o1 [- W2 aMultiplication theorem, 乘法定理
! Z& F# b1 C8 _7 {" H, u3 `( q2 k& A8 ]Multiresponse, 多元响应! f$ S" z& `$ Y6 g. y% ` ]# z5 m
Multi-stage sampling, 多阶段抽样
6 M. c, l! ?0 n8 W% {# w: MMultivariate T distribution, 多元T分布
3 I+ t v2 A7 J; F4 XMutual exclusive, 互不相容
# Y4 i0 k1 i" B; \3 b3 ]5 wMutual independence, 互相独立
$ k4 k/ v" h" V" A8 ?& @1 b( TNatural boundary, 自然边界. M" D: b! k0 Y5 b- ^& _1 s
Natural dead, 自然死亡1 S5 o _2 d2 L" p& u: i* F( V! u
Natural zero, 自然零' N& l8 b4 S! R' c, u8 x
Negative correlation, 负相关# X3 j$ {1 Z; K
Negative linear correlation, 负线性相关
- p% j8 \9 b" i, ~Negatively skewed, 负偏1 r- t& o' m' o
Newman-Keuls method, q检验
' G" F. ?4 [1 @6 \6 J! s% eNK method, q检验
. [/ z, h1 W: W. {No statistical significance, 无统计意义
2 i; ?. t0 h1 w3 l# O$ a1 HNominal variable, 名义变量
6 y. t1 E8 q3 n% @Nonconstancy of variability, 变异的非定常性
7 B% j: z7 F+ D( s/ hNonlinear regression, 非线性相关) q! E! F/ n2 i
Nonparametric statistics, 非参数统计
+ g8 q1 }/ Y4 O, m; a# k. ~Nonparametric test, 非参数检验
/ ]: X$ ~/ I& K( UNonparametric tests, 非参数检验) F% T2 i+ x; V4 w& Q, n3 g0 `
Normal deviate, 正态离差
/ U5 S7 O, ~2 I3 M* G |% s/ yNormal distribution, 正态分布
5 j$ m! r5 `2 X: ?Normal equation, 正规方程组
9 ~/ w* e5 V1 q% U* d* ^Normal ranges, 正常范围
3 A3 `: P" r* ]4 @4 R4 RNormal value, 正常值2 k: E' D. o% b( J: b5 v" r9 E
Nuisance parameter, 多余参数/讨厌参数
" w) L3 E; Z. ?0 u/ BNull hypothesis, 无效假设
9 B! A$ K- ]+ Q1 c0 VNumerical variable, 数值变量
3 N: X- j# g$ j0 x/ JObjective function, 目标函数
a, _8 R+ l/ Y$ h# ZObservation unit, 观察单位
) ]4 o7 _0 N/ c! S; `+ V8 yObserved value, 观察值/ O/ O% c. g' c G. a
One sided test, 单侧检验8 H2 i& b3 I& N3 O6 h0 K
One-way analysis of variance, 单因素方差分析
6 B6 w; i" C# y4 f. t& o! |Oneway ANOVA , 单因素方差分析
. ?0 ]" Z: ?) z- d% F" p9 XOpen sequential trial, 开放型序贯设计
( o8 v& ?: o/ g3 S+ _Optrim, 优切尾. m( w. m6 U- n% q& x+ c% b
Optrim efficiency, 优切尾效率; z$ O2 g( {9 _, w3 H' y
Order statistics, 顺序统计量3 h4 i! x, X# x; z. T. e: T( Y; d( [
Ordered categories, 有序分类
" Z& v/ M& v& {) ]1 ^4 @# r; z0 E- UOrdinal logistic regression , 序数逻辑斯蒂回归7 A7 V' }" F. H$ x" H0 D/ e
Ordinal variable, 有序变量( s# a7 u, D2 r+ ?- O( n
Orthogonal basis, 正交基' X9 H6 N+ S& n5 i, R2 Z
Orthogonal design, 正交试验设计! }# Z; o+ C# }( L. @6 {9 C; |
Orthogonality conditions, 正交条件& Q1 b7 K- x5 L7 s
ORTHOPLAN, 正交设计
* b8 c: U# y7 R& X. Q& d2 gOutlier cutoffs, 离群值截断点
* W" U/ v" _0 B% r4 EOutliers, 极端值, G! @& x& _5 T- q. w' ^' w5 z
OVERALS , 多组变量的非线性正规相关 ! {# f" P, s$ F3 }" P9 A& }8 E
Overshoot, 迭代过度; V! `8 }, n5 T2 J# T
Paired design, 配对设计
+ ~0 n6 j7 K- lPaired sample, 配对样本: ]. T' n0 ~0 P5 E, r- I
Pairwise slopes, 成对斜率% C" ?% x0 ^9 f) j. K2 Q- W/ ]
Parabola, 抛物线! [) z$ L- W, M' N* o- E
Parallel tests, 平行试验' G$ j/ y2 d3 A) R# l# T
Parameter, 参数5 y1 ^3 Q( s5 f/ N m% b
Parametric statistics, 参数统计
7 P% P& f4 q! L' Y+ {# w% QParametric test, 参数检验
2 s- t( |- M0 T& J+ S8 yPartial correlation, 偏相关: R0 j' h7 w6 v+ B
Partial regression, 偏回归. o" `' w2 o: k7 h3 w8 j$ f
Partial sorting, 偏排序
7 ]; o* Z u0 V! qPartials residuals, 偏残差
! `1 u% v/ o( i0 IPattern, 模式) ^5 [4 X3 m& P
Pearson curves, 皮尔逊曲线9 E/ m( R4 O$ F- a/ A3 J$ ?
Peeling, 退层
t& }( m: x4 [2 |( X5 k! W4 ^Percent bar graph, 百分条形图
6 u/ T+ o* S; R3 j! A( A1 BPercentage, 百分比
0 K$ u& W# S0 [& q+ D& I0 m( OPercentile, 百分位数/ e- {9 P K/ x* e: Y/ i
Percentile curves, 百分位曲线9 S* D' _; U0 s( v
Periodicity, 周期性; B4 X5 T1 F1 e5 B6 f1 M9 K
Permutation, 排列
6 t# V b y) L2 n: @P-estimator, P估计量) y' s; ?( R2 r1 Y
Pie graph, 饼图4 H' o1 J$ D( {
Pitman estimator, 皮特曼估计量
" @$ J. g0 Q& A5 m2 y" O1 e3 q! ~: ]! KPivot, 枢轴量
% H' k- c) @$ K x) yPlanar, 平坦
3 s$ v+ v: Y: w) G6 d DPlanar assumption, 平面的假设
3 ]. ~3 U; B" f% wPLANCARDS, 生成试验的计划卡! v/ B4 d7 G6 ^) h0 |/ k
Point estimation, 点估计! [+ E# T, i5 x. S: p7 D
Poisson distribution, 泊松分布
8 T* B9 }! n) x' G6 b) XPolishing, 平滑
% [7 R" X$ a- p) x) u D5 APolled standard deviation, 合并标准差
5 F; l) k3 M' d" wPolled variance, 合并方差" k: e4 k( a& p& `
Polygon, 多边图
" x4 c0 [, z, Z6 \Polynomial, 多项式9 M! |( \2 v% n
Polynomial curve, 多项式曲线
/ `: g: U3 K. d! KPopulation, 总体9 z7 q3 N2 f4 G* U
Population attributable risk, 人群归因危险度& U1 [) b5 B8 a2 U$ i9 y
Positive correlation, 正相关
, \4 M& C6 E$ E+ S7 y# lPositively skewed, 正偏# R) z( I9 c: M8 g/ ]
Posterior distribution, 后验分布
8 B) i8 r/ u+ f3 y0 e# T4 lPower of a test, 检验效能* U. ]+ H7 H# b1 K4 p) Z
Precision, 精密度* I$ H$ i% T4 R, m, G5 f
Predicted value, 预测值, U( p3 J. K* g! q/ J+ d* t& U
Preliminary analysis, 预备性分析" `6 B, h3 D8 x/ e6 N
Principal component analysis, 主成分分析9 Z6 S) M8 n' ]" q/ A
Prior distribution, 先验分布
; {1 j7 I5 i# W" MPrior probability, 先验概率& M A& ]" @6 |6 r% @" f
Probabilistic model, 概率模型
# ^" O' j! y8 I( W: i0 i' r) vprobability, 概率1 w) Z) ?- E3 V1 e8 T( B$ S) U) B: T3 {0 Y
Probability density, 概率密度
0 B2 x( {8 f9 Z, w* \% M, VProduct moment, 乘积矩/协方差
& X% k; b3 r+ a( a! A K1 {0 k9 hProfile trace, 截面迹图1 j# d) A8 i; B
Proportion, 比/构成比6 C9 P1 J; w0 x4 |. X9 k- k8 \
Proportion allocation in stratified random sampling, 按比例分层随机抽样
4 e0 q4 @ n3 _$ F" k6 Z& h- O5 }Proportionate, 成比例
! J: `7 ~5 U' o5 OProportionate sub-class numbers, 成比例次级组含量# _$ S9 W5 q) b+ n1 G. c3 W
Prospective study, 前瞻性调查
3 a5 F* K2 Q+ z/ y eProximities, 亲近性 , `& ~2 C' G, ~3 u& S8 m- e
Pseudo F test, 近似F检验$ ?9 _# S* d$ m2 }9 E8 |
Pseudo model, 近似模型9 O9 m: k0 |+ `% ~4 d9 i' q# l* O
Pseudosigma, 伪标准差
7 ]( c6 T# ~4 @5 K- U+ KPurposive sampling, 有目的抽样8 i% `! {3 f8 G2 S
QR decomposition, QR分解6 D$ T6 V5 ?3 C4 z8 w
Quadratic approximation, 二次近似2 I) ~* b8 |. b/ l) D! F) Z
Qualitative classification, 属性分类
0 a! Q/ k m' H% f, L4 u& wQualitative method, 定性方法
' [9 A% y. o+ d9 k' M& a" UQuantile-quantile plot, 分位数-分位数图/Q-Q图
6 R1 j0 r# b/ @, U$ k. M8 \; o; fQuantitative analysis, 定量分析
( M* w3 t" a9 JQuartile, 四分位数8 f5 j( t. n& Y5 V5 i' \, V
Quick Cluster, 快速聚类
: ~ g6 Z& a) tRadix sort, 基数排序) X- m! A# E& B
Random allocation, 随机化分组9 F8 E& ^: j# ]' N. F
Random blocks design, 随机区组设计" @, v0 b; y% Z/ S
Random event, 随机事件3 }" O; m7 F7 J& i
Randomization, 随机化" {& \0 ~' v3 {) I: `: F8 _! \
Range, 极差/全距$ h7 ?2 v1 A8 X% C3 @
Rank correlation, 等级相关7 Z4 a0 d4 P/ p; |/ G' Q6 ^
Rank sum test, 秩和检验7 p, v8 G8 D1 ] b
Rank test, 秩检验5 s# e3 \! p2 |0 s5 m
Ranked data, 等级资料
+ t- X' r/ }! e4 e+ l. Y" S CRate, 比率- _& \* d- S# i9 M
Ratio, 比例4 i! M* R+ f1 A- g1 b
Raw data, 原始资料
: T7 ~ X1 T* MRaw residual, 原始残差
' N' n$ S& Y \& J6 ?5 R$ t5 QRayleigh's test, 雷氏检验
: F& `8 |' ]* Z: h( W/ \# ^0 {. a( rRayleigh's Z, 雷氏Z值
4 D$ g. F7 b: m9 e4 @Reciprocal, 倒数. x) o' D# T$ A( B* p+ v
Reciprocal transformation, 倒数变换
. e/ r* i! i$ Q. @Recording, 记录
; t4 \8 }6 [7 m* e: w- I# ]Redescending estimators, 回降估计量% [. a6 I; a4 e* S$ z" A8 z! K' N
Reducing dimensions, 降维9 S) r1 w& z9 B4 A" I( ?! c9 W
Re-expression, 重新表达
4 `& A3 i" K$ z0 u; p7 y: cReference set, 标准组
. r Y, w" i6 N& m8 I3 `- o4 bRegion of acceptance, 接受域# s9 C: z6 V) ~, F; O% r C
Regression coefficient, 回归系数6 H% E5 _; _7 P9 h- n
Regression sum of square, 回归平方和
( F6 h& Q5 x9 o6 D" Z# I) ERejection point, 拒绝点. R7 W0 U8 B& U/ Z1 Y' L
Relative dispersion, 相对离散度
3 h4 `; W" i7 c5 eRelative number, 相对数0 }( s& D9 B* G
Reliability, 可靠性
9 A3 [& ]+ k- s' hReparametrization, 重新设置参数
6 C( o/ D, @& A! UReplication, 重复; N" X4 h" L5 Q* G6 R
Report Summaries, 报告摘要: r5 c* a! _7 @
Residual sum of square, 剩余平方和$ A/ W$ J6 e' L5 }
Resistance, 耐抗性
0 Q' P' \! n, b M# ~9 c6 qResistant line, 耐抗线
/ C) S9 f% ^; P, A- [Resistant technique, 耐抗技术: E C; N5 h; I N. S: v
R-estimator of location, 位置R估计量
4 q; _0 T+ P% y. C% l5 QR-estimator of scale, 尺度R估计量7 o& Q2 P% t4 j5 |7 m
Retrospective study, 回顾性调查+ Y* L4 O2 }9 t3 a2 f
Ridge trace, 岭迹
# `- p- f( M: e! G8 e D( |5 qRidit analysis, Ridit分析
# [7 e1 v( ?# KRotation, 旋转3 h3 P! A" h% Q, f- w
Rounding, 舍入/ }4 v& t* Q3 l
Row, 行
_ G l4 o0 r# E7 IRow effects, 行效应
2 J- H2 `+ k2 a! P7 @! X4 pRow factor, 行因素
# d; Z" k7 S/ X/ B* u6 s+ E- W8 cRXC table, RXC表
0 I/ l! p$ _/ K% q# x& U4 |Sample, 样本
/ u, Y' ]/ `8 [ GSample regression coefficient, 样本回归系数
1 F; W0 G- I( y2 z$ LSample size, 样本量3 c' m3 Z* @ f
Sample standard deviation, 样本标准差
* y s9 F& C9 P% E9 j6 Q/ QSampling error, 抽样误差! y" p6 X7 F2 }# x5 n$ S
SAS(Statistical analysis system ), SAS统计软件包
: M9 |, W* y" g; O: H1 wScale, 尺度/量表6 Q7 l: A, o9 e6 \. _
Scatter diagram, 散点图. F. q D* g0 I5 ?% V! V7 m
Schematic plot, 示意图/简图 F7 L# |# q0 c6 D$ c
Score test, 计分检验6 F; l1 L! e) g2 o1 I
Screening, 筛检
p8 a; M2 Y) V2 @SEASON, 季节分析 ' v# X% Y. A5 Z8 e/ @( f' X+ Z! L
Second derivative, 二阶导数
) T; i8 p1 T: Y0 {! X+ x! d( d9 fSecond principal component, 第二主成分
! u* G3 Q7 c# T: X2 f* ySEM (Structural equation modeling), 结构化方程模型 ; M$ m9 }7 m* v+ D
Semi-logarithmic graph, 半对数图9 S4 P' _; D9 T% e e, V# q/ @
Semi-logarithmic paper, 半对数格纸% |( E4 j% v" G* j/ i
Sensitivity curve, 敏感度曲线' `% S% U: T2 X2 M
Sequential analysis, 贯序分析
, D- b, k/ ]* P8 n [Sequential data set, 顺序数据集* e6 f' `% F$ f$ [2 O- b
Sequential design, 贯序设计3 a2 d, x q2 C6 M7 K$ J9 I
Sequential method, 贯序法$ M5 _1 q' C6 y
Sequential test, 贯序检验法
3 u+ V5 m. g$ b" d: H. R( wSerial tests, 系列试验+ F% ^/ A/ `; B+ o# Z8 Z9 j
Short-cut method, 简捷法 4 x/ A6 Y2 d( G2 g
Sigmoid curve, S形曲线2 m# u+ s+ A: X' i$ k
Sign function, 正负号函数
) A& D( H; F# {9 oSign test, 符号检验
9 Z7 c9 ]; M* Y# dSigned rank, 符号秩" S! W3 F9 L, \# [& f" _& q
Significance test, 显著性检验
, G& n5 Y0 p% J- K2 wSignificant figure, 有效数字
: V( K4 y' h% y" C3 G7 i0 iSimple cluster sampling, 简单整群抽样. a. g* @+ e( R7 q
Simple correlation, 简单相关
, ]! ?' H5 ?6 ~4 R7 ]+ aSimple random sampling, 简单随机抽样
$ k5 V6 E x# \$ aSimple regression, 简单回归$ @) P4 l6 x" q" n
simple table, 简单表+ }+ A$ w: Z# ?: t; N# M; u
Sine estimator, 正弦估计量 K' x) ?2 I* A2 s1 F8 W
Single-valued estimate, 单值估计( @' ] a+ |( _( I
Singular matrix, 奇异矩阵
9 J: z- O3 k* k) b0 d, n) `& v* GSkewed distribution, 偏斜分布 R( u) L2 {* Q
Skewness, 偏度
/ n# j8 Z$ o$ p6 y$ LSlash distribution, 斜线分布# Z. F U8 q, o0 R, K
Slope, 斜率
7 V2 G6 r# Z. e: ?! v) jSmirnov test, 斯米尔诺夫检验7 `0 I: j* C9 N! [9 d) ]1 X
Source of variation, 变异来源
/ Q& U* h( a- g0 m- ^* hSpearman rank correlation, 斯皮尔曼等级相关6 I: u o S& h/ _! a8 B( c: G
Specific factor, 特殊因子
; y9 E9 x7 J! w: G! i% FSpecific factor variance, 特殊因子方差. r! k! v' o- U( \' ]9 U
Spectra , 频谱$ L6 X* L: \) j v4 D7 d& S
Spherical distribution, 球型正态分布# d0 K: c: u0 P: U
Spread, 展布3 g1 g0 _3 T* P! `. q" G8 K2 P2 H) M+ `
SPSS(Statistical package for the social science), SPSS统计软件包' H; M0 u. ?4 g' @
Spurious correlation, 假性相关0 x9 S' t) |2 f
Square root transformation, 平方根变换
1 @6 t. A& U) nStabilizing variance, 稳定方差3 v) @" S; b K) z) S1 t
Standard deviation, 标准差- ?, W$ F, y K% M$ @6 _) i/ J
Standard error, 标准误5 J K+ m z8 X6 c. l
Standard error of difference, 差别的标准误' n" B+ ~- `1 r9 P) @6 k
Standard error of estimate, 标准估计误差& P- d: U) A/ s: Y0 `
Standard error of rate, 率的标准误! n+ Z5 x4 E7 Y
Standard normal distribution, 标准正态分布
( d8 P' {2 D, O) V0 yStandardization, 标准化
6 w& r6 i5 p1 I* s# `- Z8 WStarting value, 起始值
6 w: p: z5 J3 a* ^- yStatistic, 统计量4 Z1 d: a( {( m' R
Statistical control, 统计控制
4 l2 a2 I8 V9 \/ x7 g- J }Statistical graph, 统计图
1 B) r" \; M' i' DStatistical inference, 统计推断
% ? }# y! W; jStatistical table, 统计表/ t: s% E3 n ]1 R3 K, h
Steepest descent, 最速下降法& L; ?: @& u1 V
Stem and leaf display, 茎叶图, I) |2 _/ g# N7 f
Step factor, 步长因子+ g1 N, Y9 w7 W2 L, D0 |# Y0 }
Stepwise regression, 逐步回归
7 K+ x& b; ^& A# TStorage, 存
! r+ m( z7 Y9 p5 AStrata, 层（复数）/ v: u" B8 s% w3 Y! B0 m
Stratified sampling, 分层抽样
5 u, T$ i* o; j2 ]! p' M8 ?! I3 x2 _Stratified sampling, 分层抽样% ?, A* T. ]; `! M
Strength, 强度* O5 T3 {( J" a: T- [2 k
Stringency, 严密性* ~2 E o" s$ `& ` Q, J
Structural relationship, 结构关系3 ]: D5 `% Z" k. R* S* X) `
Studentized residual, 学生化残差/t化残差! x2 U, u; C) w! z& s& m& Y9 c4 ^. e) `
Sub-class numbers, 次级组含量# ]: ^# u' \7 T; f) x
Subdividing, 分割
+ V* ^9 i3 y2 {" p; C2 R5 D/ d9 ?4 {* BSufficient statistic, 充分统计量: ]8 z# j6 m. a
Sum of products, 积和
( D! u1 V) W% r3 h; X! W3 fSum of squares, 离差平方和4 u- f0 J/ g, {% v
Sum of squares about regression, 回归平方和
7 b& E) c+ w8 Z6 d/ }& hSum of squares between groups, 组间平方和
5 L0 y- v/ z+ V: j4 _4 P/ wSum of squares of partial regression, 偏回归平方和/ L& \% A# O B" j7 J
Sure event, 必然事件. k! y+ t" Q+ @. ?
Survey, 调查
) G6 Z- r. z3 U0 V/ [Survival, 生存分析
! L2 E/ _# V% O1 A3 i. C7 PSurvival rate, 生存率
7 a8 }) m2 M0 e. `/ e- {Suspended root gram, 悬吊根图
; @& N4 W$ ^3 A+ `6 f! b( tSymmetry, 对称! k0 q0 ?& H2 P+ {2 e
Systematic error, 系统误差
5 M2 K5 R) K9 @0 O' j7 uSystematic sampling, 系统抽样
/ V$ x9 W/ F7 z S- e$ CTags, 标签
$ J! \" S* O! ZTail area, 尾部面积
+ q( _/ Y* h6 ?! eTail length, 尾长
! F' f: m: O! s$ X6 c3 ^Tail weight, 尾重- l: ?- r$ G+ Y, [( k. Y
Tangent line, 切线% H3 P8 ]4 y K6 e
Target distribution, 目标分布
7 T4 L8 Z0 C! R9 ^3 X( `8 v9 Q' KTaylor series, 泰勒级数
, P6 M# [+ H& `5 v0 v# B% eTendency of dispersion, 离散趋势& Y7 q6 |% n. [/ b
Testing of hypotheses, 假设检验/ g. |- z, u% H% u& B5 k
Theoretical frequency, 理论频数2 R1 ?2 W9 m, B
Time series, 时间序列
& p) f! Z i3 T E5 j% d0 u) ?Tolerance interval, 容忍区间8 Z' y k4 ]; w; I
Tolerance lower limit, 容忍下限4 D: b a7 H4 X& N/ M: @
Tolerance upper limit, 容忍上限) l* d/ m! ` _1 u+ L1 c5 \
Torsion, 扰率% m$ n( J6 K, p
Total sum of square, 总平方和
& t+ Z5 H7 ?& e: i0 Q2 M, n2 X9 RTotal variation, 总变异+ z( k8 d# ^5 p( d) b
Transformation, 转换
9 z+ n: _# A R' M- d+ yTreatment, 处理( `% v+ S& P$ ~, K! B
Trend, 趋势
4 T0 J9 O* d3 JTrend of percentage, 百分比趋势
5 F1 b @$ u( t- kTrial, 试验
" u3 B! L3 o3 f/ i- W# {Trial and error method, 试错法4 g& Z# z4 h/ m% ]$ {
Tuning constant, 细调常数+ [# y3 q" q; J% G7 {2 U
Two sided test, 双向检验
0 f5 K' w! \ F" { l9 e- k1 qTwo-stage least squares, 二阶最小平方
* d4 @. w/ ~. t* Q" c" r8 f6 lTwo-stage sampling, 二阶段抽样
. f: l& l. _! c$ S5 ITwo-tailed test, 双侧检验 f3 e" F3 B+ y4 V" e5 @
Two-way analysis of variance, 双因素方差分析
' L& L( X( I7 V |' V @6 y5 ETwo-way table, 双向表
$ i/ h2 z9 f# ?+ u* LType I error, 一类错误/α错误
' P5 V# P7 G% `/ fType II error, 二类错误/β错误
' W: R* j2 K5 IUMVU, 方差一致最小无偏估计简称. |; K. c T; g/ _! P( d/ ?3 o
Unbiased estimate, 无偏估计6 y' |; Z) c [& {
Unconstrained nonlinear regression , 无约束非线性回归: M3 a W& r6 Z v; {$ L
Unequal subclass number, 不等次级组含量
5 J7 p) O0 F$ r& DUngrouped data, 不分组资料
- O" ~' _) R' PUniform coordinate, 均匀坐标1 _% W8 x& M1 x5 C# X. x8 `
Uniform distribution, 均匀分布
+ W+ W6 d" z9 f) qUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( x" g7 @+ n+ D$ M% |Unit, 单元% m m6 X" s* F, U, @
Unordered categories, 无序分类( M. Q% Z1 V- \2 K/ n$ [5 x
Upper limit, 上限5 F" J- @6 F9 T" N, _' j7 O
Upward rank, 升秩' C q9 d* ^6 ^
Vague concept, 模糊概念
3 p; W/ Q% _% J, L C. S" DValidity, 有效性
) f1 K7 v5 K7 V" L/ W9 _( [3 v6 kVARCOMP (Variance component estimation), 方差元素估计' ] x1 ~0 k) n4 \4 T
Variability, 变异性
9 o) U" A/ W2 s% S% k) z% JVariable, 变量
' w! v- r1 e; LVariance, 方差
- r5 G- ] Y [. sVariation, 变异3 i( H2 f- p" ~( ?
Varimax orthogonal rotation, 方差最大正交旋转
- M) n* \1 q* j9 ?! L/ ^1 SVolume of distribution, 容积6 I/ @6 m$ m& ]
W test, W检验
3 m6 m$ s6 w u* S4 @Weibull distribution, 威布尔分布1 \& H" P, u4 H$ ?! U3 D6 ?
Weight, 权数
9 q6 }6 M6 M% h/ R, R& fWeighted Chi-square test, 加权卡方检验/Cochran检验1 C9 E2 W7 \, u2 l2 V" I7 e
Weighted linear regression method, 加权直线回归 b$ f- Y3 i+ S% o3 x
Weighted mean, 加权平均数
( n9 I3 Q. d! T- Q4 F6 c x% e8 aWeighted mean square, 加权平均方差6 p2 l. |* n( n9 D
Weighted sum of square, 加权平方和% C9 A9 Y5 {# v/ k9 m
Weighting coefficient, 权重系数& n; h* `/ E% D. [3 ~ y
Weighting method, 加权法 + Q0 p: m) d" G3 G& D Z# m) O
W-estimation, W估计量% Z! T1 O/ M0 z, N8 @& n
W-estimation of location, 位置W估计量& ~" P- o" e" |
Width, 宽度
% ]! [) I* I* l5 KWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
* w" D- g; ~8 C3 W6 F/ b8 \. ]7 ]9 eWild point, 野点/狂点: z: a3 _, M" [6 M; U
Wild value, 野值/狂值
. L2 X& T1 j# vWinsorized mean, 缩尾均值) {, B- H! |2 z3 N
Withdraw, 失访 & p" T: X1 R1 ]) P% ^4 u$ Y7 k
Youden's index, 尤登指数
0 ?# D. q7 F1 A) i5 LZ test, Z检验
6 F' U9 h T* E7 o/ ~Zero correlation, 零相关$ E$ v# s, A; S6 ~) E
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
