|
|
Absolute deviation, 绝对离差& Q. o4 T$ S% K2 p
Absolute number, 绝对数: q' I/ g/ b) d8 E1 ]
Absolute residuals, 绝对残差, y7 Q$ H; M" @* q% L; y
Acceleration array, 加速度立体阵
0 o$ I" S$ G8 DAcceleration in an arbitrary direction, 任意方向上的加速度
& A# ~) G) Y; ~" v( r! L) ~- j- GAcceleration normal, 法向加速度
' [4 p2 E5 { t# ZAcceleration space dimension, 加速度空间的维数1 r" h. l4 b) K( G3 @
Acceleration tangential, 切向加速度9 Y+ J; p& m5 L/ @. `9 R
Acceleration vector, 加速度向量
4 T3 e. D/ L9 Q+ g: K- @ GAcceptable hypothesis, 可接受假设$ }: f9 [; Q! x( E$ n3 m
Accumulation, 累积9 ~" k( ^) T, S0 ^
Accuracy, 准确度
9 v- D+ p* P. \) L7 R( @9 R6 vActual frequency, 实际频数: r/ O& r3 R4 S9 J) [# {" k
Adaptive estimator, 自适应估计量
9 m6 A4 E. g8 h* m$ m7 B) ~- OAddition, 相加& J4 E+ D8 n2 D% p$ E) Y1 \# h
Addition theorem, 加法定理4 }# a8 A0 c4 ^6 e: o' Q# O
Additivity, 可加性
# R4 R; Z* t% o2 J, @5 Y: R. C/ LAdjusted rate, 调整率$ O/ x& [- e& {4 B
Adjusted value, 校正值4 _/ x+ ~3 r g7 y9 h* a2 ~
Admissible error, 容许误差5 Y$ a d+ X+ U/ ]9 I6 x7 w" k
Aggregation, 聚集性
$ F8 W: Y% U4 R9 L7 G/ @' PAlternative hypothesis, 备择假设+ Y i D4 b: m+ s
Among groups, 组间
% {; ` I, X) s) h9 gAmounts, 总量
$ q3 R2 a; o! i9 [Analysis of correlation, 相关分析
$ T5 O3 c8 @/ N6 {" u$ l& A$ JAnalysis of covariance, 协方差分析
* t: L2 I4 o8 b; VAnalysis of regression, 回归分析# g8 u. M" g. z$ m) b% J
Analysis of time series, 时间序列分析+ I" }2 }, G3 y7 G/ l
Analysis of variance, 方差分析+ t8 C1 R% q5 g& x4 d
Angular transformation, 角转换
0 X: o6 ~% z1 |$ iANOVA （analysis of variance）, 方差分析
5 T! r: u' W3 \- L' J/ DANOVA Models, 方差分析模型1 m. w, U! d$ u! S
Arcing, 弧/弧旋6 E0 K& c8 ? Q( `" r5 y8 Z
Arcsine transformation, 反正弦变换
2 U$ P- L2 |% e/ y# e. g) uArea under the curve, 曲线面积/ S; @8 q8 g) d0 R) ^+ J4 @5 g y
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 / m. F% B# ~$ g
ARIMA, 季节和非季节性单变量模型的极大似然估计
, F# `; p5 M) d. ZArithmetic grid paper, 算术格纸- p' X+ w$ ~* E: \; u/ t/ `$ E
Arithmetic mean, 算术平均数
* o7 t7 R4 {5 u; KArrhenius relation, 艾恩尼斯关系2 [8 `# G5 i+ i. y) G- p
Assessing fit, 拟合的评估; H* \0 B9 E, @" e" \
Associative laws, 结合律
u2 g' D* D7 c* y( HAsymmetric distribution, 非对称分布
" c$ r5 u6 l; p! Z, L" C2 F3 OAsymptotic bias, 渐近偏倚
7 R* {5 d, n2 @ p* eAsymptotic efficiency, 渐近效率: H, ^ \' x3 {9 T# z5 a
Asymptotic variance, 渐近方差% K+ u7 n/ C/ G: d1 t& }: ]
Attributable risk, 归因危险度
6 I/ ^7 f6 I/ H( R& u6 ]3 KAttribute data, 属性资料
; Q4 D& J4 M: g4 h% k; @Attribution, 属性
/ _4 S& k/ I2 S3 }/ t) b# G+ kAutocorrelation, 自相关
. W" O: X- l( \: q1 hAutocorrelation of residuals, 残差的自相关9 u2 L4 R8 D9 e( d
Average, 平均数' e! x' O1 O- _9 `6 n2 X- {" a
Average confidence interval length, 平均置信区间长度8 q& C' k1 C% S3 Q; g `; Q- s. T
Average growth rate, 平均增长率
u ` _6 z* O4 l. iBar chart, 条形图, h4 ^; V& O& |2 a! v/ `. k" F- v
Bar graph, 条形图
5 U3 o3 j& W" ?2 Q) g- SBase period, 基期$ C% C1 l7 A3 h) ~- D. P- \1 ?0 \
Bayes' theorem , Bayes定理5 H( W: d, e) g# M+ u. C
Bell-shaped curve, 钟形曲线; D$ f) H- \& G- u5 b
Bernoulli distribution, 伯努力分布3 w0 k/ r& }. Z! F/ o. Z
Best-trim estimator, 最好切尾估计量
0 Q2 U* `$ {/ L# Y( KBias, 偏性7 m6 F/ P: b. ]0 L
Binary logistic regression, 二元逻辑斯蒂回归
( _. \' ]* u: ?$ A/ ~1 HBinomial distribution, 二项分布
. z3 V1 s% n9 c3 ]9 d2 @Bisquare, 双平方
B+ I' U z' b% I6 C BBivariate Correlate, 二变量相关
W; Y+ u* w( qBivariate normal distribution, 双变量正态分布
# v* Y# n2 U( q+ a! [Bivariate normal population, 双变量正态总体& L- ^% F/ a1 W- v0 v
Biweight interval, 双权区间
$ ]0 ?& R) C$ F# zBiweight M-estimator, 双权M估计量( s0 \( ?* t( [: X
Block, 区组/配伍组
; b4 j& H% v& e' R: g j# HBMDP(Biomedical computer programs), BMDP统计软件包
2 n" F$ A; E/ x+ U4 W# ^9 _Boxplots, 箱线图/箱尾图
! p; D$ Z0 X' d5 j% T4 h7 v8 \Breakdown bound, 崩溃界/崩溃点4 l+ j" }3 M8 A) q
Canonical correlation, 典型相关
, @4 @2 [1 [, zCaption, 纵标目/ [& ^1 {5 ]- t8 O. D5 u; X/ x# a
Case-control study, 病例对照研究% N/ S9 _7 q I
Categorical variable, 分类变量2 B, P3 y- T# w- b
Catenary, 悬链线/ E" Z- u4 O* `' ]3 n$ t
Cauchy distribution, 柯西分布
$ \. I5 f5 ~; }Cause-and-effect relationship, 因果关系8 `+ K2 w! H |, }1 y( I
Cell, 单元
! |2 v5 A* |; K0 {. ~1 |4 c* CCensoring, 终检" U, h" s% N1 E6 _8 n
Center of symmetry, 对称中心 N2 b. B* w2 \3 k! e f" X+ }
Centering and scaling, 中心化和定标
. n# |8 l" k" ~ M9 r6 ^6 |Central tendency, 集中趋势! p' o& ^) c8 p& U* m; G1 M
Central value, 中心值
* `2 M/ ^% I( f3 S" h3 K7 YCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测4 r, Z5 }% T" h, l/ W* I
Chance, 机遇
0 l5 S/ B3 c7 i4 v ~) gChance error, 随机误差
7 B8 C3 o o) e6 }/ }' U/ I' hChance variable, 随机变量. u6 c; {7 T8 t
Characteristic equation, 特征方程
0 z2 l& N. l4 B, ~0 ]Characteristic root, 特征根' B, I1 j- c7 c- d* E8 E; i8 J
Characteristic vector, 特征向量
# z8 M( M8 o8 jChebshev criterion of fit, 拟合的切比雪夫准则
( O: M7 b, V# n( l$ NChernoff faces, 切尔诺夫脸谱图
8 u8 \" z% I/ E/ ^+ Y2 QChi-square test, 卡方检验/χ2检验
$ ?/ Q) y+ U8 r3 _- C9 |Choleskey decomposition, 乔洛斯基分解
4 Z" J( Q0 b; s& TCircle chart, 圆图 4 Z7 v" |) Z: j2 U* Z
Class interval, 组距
$ i- t1 U! j. Z/ s( C O/ tClass mid-value, 组中值
9 U9 V v* K; p) e5 f1 z5 I. ^Class upper limit, 组上限
# e! x1 ?+ {7 I7 j% r, }Classified variable, 分类变量
% c$ C% [ h* L$ i9 z- G# zCluster analysis, 聚类分析
+ G1 x: J! |2 _8 KCluster sampling, 整群抽样- e5 A" l. d: D& D6 ], G
Code, 代码
/ h6 a: o7 ^+ U5 I5 B1 K9 l& ~Coded data, 编码数据) _9 M- z" T, L3 h' {& F! m9 w. Y
Coding, 编码
; _- a- K E) ZCoefficient of contingency, 列联系数9 b- T# v+ p0 L5 g* v2 s7 R
Coefficient of determination, 决定系数$ n5 z8 C8 X# N
Coefficient of multiple correlation, 多重相关系数) R. j5 P9 A7 ?" R
Coefficient of partial correlation, 偏相关系数
) T) a( e3 P; R3 O% tCoefficient of production-moment correlation, 积差相关系数
4 y; V6 f% K" m' @: j- ICoefficient of rank correlation, 等级相关系数
" w$ e, [/ z- d& `Coefficient of regression, 回归系数
D0 V% A2 d S+ t5 ? \Coefficient of skewness, 偏度系数8 T6 d/ R; a2 ]' ]2 c- H
Coefficient of variation, 变异系数
1 e2 C5 x [. Q' v. R0 nCohort study, 队列研究
|. a* J1 K! b/ Y9 AColumn, 列: J0 M! W, \) n" |6 M
Column effect, 列效应/ F6 m* J3 V$ n2 `
Column factor, 列因素" z; x" c @) k/ P! |
Combination pool, 合并
: S+ J" C$ ]7 HCombinative table, 组合表/ g0 N* M9 v/ d( p+ w+ x# {) W9 B
Common factor, 共性因子5 `/ L- y7 f# y, U
Common regression coefficient, 公共回归系数2 v( j- g) Z c0 R
Common value, 共同值
- S- _( {5 K' v' G+ J5 j0 GCommon variance, 公共方差
- T9 N2 p @7 x! x- cCommon variation, 公共变异
" N% D$ q( C1 ^9 S! ICommunality variance, 共性方差
% r; Y! U# Y" ^* EComparability, 可比性
; o& `' r; H; Y+ o+ CComparison of bathes, 批比较
' O0 c' h, [5 HComparison value, 比较值9 n: I! f8 o# U+ V2 Q4 Q! Z
Compartment model, 分部模型. _' p( g, c" p2 e( M% `
Compassion, 伸缩* O" ^( O4 |# h
Complement of an event, 补事件8 t& O8 G" y/ O; J
Complete association, 完全正相关6 N7 u" y; A+ R/ i
Complete dissociation, 完全不相关
& p. y. v$ v/ C E2 d( v! gComplete statistics, 完备统计量
$ E+ d0 G3 L4 V7 aCompletely randomized design, 完全随机化设计
& c" r3 S) \. ?( p; qComposite event, 联合事件
7 t. F8 z6 z, T. hComposite events, 复合事件
/ L" u- r7 q+ f! HConcavity, 凹性$ R1 T6 n* G9 w7 O4 |* }. p
Conditional expectation, 条件期望
: i R* l1 @( }5 N( v" hConditional likelihood, 条件似然
+ Z- V0 C# D2 N1 y* o2 KConditional probability, 条件概率! R, w0 f( L7 A; N" E
Conditionally linear, 依条件线性
8 Q4 E9 g9 ^* P' \' s+ rConfidence interval, 置信区间
9 O2 z, \- y# c, J7 yConfidence limit, 置信限% D2 |" V2 v% q8 o' U
Confidence lower limit, 置信下限2 m1 T( A- H- z) M- r
Confidence upper limit, 置信上限
. I: c) l, K& t" ?$ Y% J# Y# AConfirmatory Factor Analysis , 验证性因子分析& ]% b) M- G9 U
Confirmatory research, 证实性实验研究; C, w$ @& S/ Q5 g4 U: \: |! c
Confounding factor, 混杂因素4 F0 a+ c. r- J/ O8 O c
Conjoint, 联合分析8 J# Z/ d% G8 q2 H. y B
Consistency, 相合性
8 q0 R7 s. w# Z% |Consistency check, 一致性检验' h, P% {- f8 p1 d
Consistent asymptotically normal estimate, 相合渐近正态估计
6 @( T0 E4 r$ V3 a h4 K' OConsistent estimate, 相合估计
' I, j! x( m/ O0 J& rConstrained nonlinear regression, 受约束非线性回归
& A9 E( k) B \4 I' S: fConstraint, 约束
3 I5 O$ V8 `/ A' J4 x4 X- gContaminated distribution, 污染分布
6 K/ `+ M5 d5 K: A& Y2 D2 s! lContaminated Gausssian, 污染高斯分布) l3 ?* ?0 B0 |% Z2 @
Contaminated normal distribution, 污染正态分布
" ^8 O7 a# e# R9 I" ~Contamination, 污染 d; A6 P; K3 E) q
Contamination model, 污染模型7 {& d# F/ j) G0 L& M3 t
Contingency table, 列联表1 w4 [' A& g: M$ d8 Q
Contour, 边界线
+ _1 r& V { c y6 G2 d" L6 AContribution rate, 贡献率
6 n- {4 N5 B7 ?8 X- q. E6 q6 sControl, 对照
4 f9 ~* p' M! k9 i1 k% XControlled experiments, 对照实验, v$ q( |3 d4 s4 v; U$ P
Conventional depth, 常规深度0 D' _) V/ ~) j1 U' z/ A, J
Convolution, 卷积
% x4 I7 K, A7 G. K/ S4 xCorrected factor, 校正因子
7 F% E, [! |' |& D9 LCorrected mean, 校正均值% _& v6 u* Z3 J' P ~5 F
Correction coefficient, 校正系数! p0 m- ?8 h6 {5 `
Correctness, 正确性5 @) N. t h3 @* O2 _) ?
Correlation coefficient, 相关系数
, q, D" l9 Q: E" YCorrelation index, 相关指数
5 ]+ {# o4 `. N2 ^* KCorrespondence, 对应
& _5 L Z% b! p# H. T* _" WCounting, 计数
& Z1 p W. A/ m0 ^+ F. e. JCounts, 计数/频数 W. P7 n9 }- ?2 e2 i) }! b9 S1 B
Covariance, 协方差) k8 p" W; Y2 Y+ z$ f) z
Covariant, 共变
w0 w& x0 n, \6 WCox Regression, Cox回归4 O: Z1 O4 y2 K( i
Criteria for fitting, 拟合准则
! \* B; d: D5 o# x y3 X5 bCriteria of least squares, 最小二乘准则& \0 X. |# g. c6 O! N/ P; A6 o
Critical ratio, 临界比& J3 m+ h3 f4 L
Critical region, 拒绝域
; h; y* M& `- G; S9 _Critical value, 临界值
7 Q& Q, G: c ~# `' P" xCross-over design, 交叉设计3 x! C, D/ D0 J `0 P1 a
Cross-section analysis, 横断面分析* p! l7 G9 R1 n8 d1 a2 z
Cross-section survey, 横断面调查
7 H3 [7 m C4 m9 u; V# h( @5 E K( ACrosstabs , 交叉表
) @: ^1 l7 b: u# m+ L X1 [8 [- `Cross-tabulation table, 复合表( z d" t+ x. V: Q" e+ E% x/ z
Cube root, 立方根
: E; {; S; l8 C9 L! S, p. ]0 kCumulative distribution function, 分布函数9 o4 I: C; \: [
Cumulative probability, 累计概率2 J _2 q. L) N/ x$ h }1 M C
Curvature, 曲率/弯曲
8 Q* x" X, G' \/ YCurvature, 曲率" k0 z; V% S4 ?5 Y- @1 |) T7 q
Curve fit , 曲线拟和
: c9 T0 U( d! d: |Curve fitting, 曲线拟合
, V, v6 D6 T; y+ H) j) N3 | PCurvilinear regression, 曲线回归0 K$ H. Z* k& E/ {: N% E5 V6 l
Curvilinear relation, 曲线关系" _6 z7 L6 v" v( s
Cut-and-try method, 尝试法& P q, E g6 w* Q- L( w
Cycle, 周期
6 |$ X9 O% E* B* ACyclist, 周期性
7 }9 V* p/ B7 PD test, D检验
. j9 O) L# v" bData acquisition, 资料收集5 z5 a3 _2 M% P% ]& d
Data bank, 数据库
/ ~1 q! t' a4 |- a% Q, w$ aData capacity, 数据容量" |0 K% X, Y0 e6 h9 Z8 N/ K, ?
Data deficiencies, 数据缺乏
) a) \' G& U0 }6 O& I# yData handling, 数据处理# p x( p- \+ v* m
Data manipulation, 数据处理
, t& ^; J+ w* D, g/ a, GData processing, 数据处理2 h q$ N" d) ?
Data reduction, 数据缩减
3 Z& h# K2 f# J' O# {) j) kData set, 数据集
* f8 G# n+ g2 E( {3 H wData sources, 数据来源
" M7 G% M: P" R& r* [5 MData transformation, 数据变换2 I7 x8 t. d/ u3 I" J7 G. E$ U
Data validity, 数据有效性7 f' a4 ]9 ]- J. R
Data-in, 数据输入$ q& M$ c5 \& T% ]& C+ Z
Data-out, 数据输出
# F6 ?- Q" }* p$ ADead time, 停滞期
9 V& W% c8 \( Y5 f) UDegree of freedom, 自由度' d# h( e7 b) P* S/ a
Degree of precision, 精密度- d7 |/ i, N8 |3 E( O
Degree of reliability, 可靠性程度
) P& o% [0 C! x5 DDegression, 递减- b: C' A: F( N0 c( Q4 ~- Z
Density function, 密度函数
8 d4 R6 o" T( Z7 B% PDensity of data points, 数据点的密度" Q2 p2 M4 T* p5 L8 L: R
Dependent variable, 应变量/依变量/因变量9 I6 k# i g h. d; a$ T/ E0 G2 B
Dependent variable, 因变量$ L7 ^7 T2 X3 q9 Z* e
Depth, 深度
1 E, M5 U! E8 ODerivative matrix, 导数矩阵 Y' n* z" r, ^1 c5 d/ W
Derivative-free methods, 无导数方法' W. @! y5 P* P. f9 K7 f
Design, 设计
: w9 e, r6 L/ ^8 w* W( {- H2 Y$ xDeterminacy, 确定性
* o' s/ `% q! ^4 v2 QDeterminant, 行列式+ [; o) L3 s" x7 a$ I3 M& \
Determinant, 决定因素: B# y& E4 J5 G/ Y/ F% O
Deviation, 离差* v' m7 v/ ~ ~. {0 g9 g$ {, [
Deviation from average, 离均差- H/ v% y/ h+ Z7 j% }* V9 ^
Diagnostic plot, 诊断图. M$ P5 n3 Q, Z- N9 b# {+ q# J/ p' R
Dichotomous variable, 二分变量0 U! q$ ?: R" }' o( [, [
Differential equation, 微分方程. y+ F4 _5 U) Q8 C l
Direct standardization, 直接标准化法. ?- B0 p: k# I1 c
Discrete variable, 离散型变量- a# I N, }7 }0 s! n% u
DISCRIMINANT, 判断
+ m, C) U, p$ N/ ^0 M iDiscriminant analysis, 判别分析: K' w y4 C" l* k2 R) T. y$ k
Discriminant coefficient, 判别系数' f/ n1 c; x* p$ o6 j5 I
Discriminant function, 判别值* @6 Z, Y/ Y1 ~* F* W( m: F
Dispersion, 散布/分散度4 E5 w* e5 v8 }, I2 w. J7 N
Disproportional, 不成比例的# [" B' D2 X" u% S# u6 m
Disproportionate sub-class numbers, 不成比例次级组含量
) v4 Z5 L" f1 z( U W m# QDistribution free, 分布无关性/免分布- ~1 S: l; I& [1 W4 A4 }' Y0 O: {
Distribution shape, 分布形状 P M% p3 I; e! e
Distribution-free method, 任意分布法
0 t/ \! i$ d+ J) r9 ^! GDistributive laws, 分配律
9 e" N9 u/ f0 J T( x: ADisturbance, 随机扰动项- l8 D) x( g/ g, M
Dose response curve, 剂量反应曲线
) Q: p# S1 r1 r0 {Double blind method, 双盲法$ g. w& y. e4 a
Double blind trial, 双盲试验% ]$ n9 e3 _% o Z3 R1 x0 i8 P! y
Double exponential distribution, 双指数分布
! Z/ s; x/ @- M7 [* aDouble logarithmic, 双对数3 w: R; P* h8 f' r, Q6 V% Z$ m
Downward rank, 降秩 U- F' P6 ^6 Y& L
Dual-space plot, 对偶空间图
9 I6 B$ a0 ~# dDUD, 无导数方法
+ `0 Z- Q3 l2 F6 _/ E. m* \. ODuncan's new multiple range method, 新复极差法/Duncan新法( L3 r# f1 T& Y' g. S6 Y1 y$ U2 i
Effect, 实验效应& U* O; j) i9 e
Eigenvalue, 特征值- x) h. h; a( T+ Y8 a; E' y
Eigenvector, 特征向量
( h9 d4 U$ Y1 C/ y( q; i3 NEllipse, 椭圆
: ^- A/ ]/ V( p9 q3 ~3 iEmpirical distribution, 经验分布
) U' o& @" k v- SEmpirical probability, 经验概率单位; B- q7 F: D. q4 Z% L e
Enumeration data, 计数资料
0 ~7 G+ t& e! W2 S+ OEqual sun-class number, 相等次级组含量7 c4 a' |% C0 J/ w$ R
Equally likely, 等可能6 ^- }; Q! K/ O8 m2 s# q
Equivariance, 同变性
) N Z: {* L' x' v+ CError, 误差/错误
3 X# l+ _0 v" [- uError of estimate, 估计误差
( p. t2 v& E! T. YError type I, 第一类错误
* v' ]& v6 N1 p/ j. u# fError type II, 第二类错误1 S/ j! B, T9 u: G7 e
Estimand, 被估量
5 x/ k. Y& }7 |, sEstimated error mean squares, 估计误差均方
, J9 \/ t) k( ^9 U" vEstimated error sum of squares, 估计误差平方和
9 x: o% d9 |+ D, xEuclidean distance, 欧式距离
8 g1 S# l, N9 m- |Event, 事件
* Y/ f! F& A- }3 S# x, [- i' SEvent, 事件' M+ Z# n( ]+ }1 j4 M
Exceptional data point, 异常数据点
7 Y+ j+ e4 x# |5 i$ @( w+ d* ~+ G3 |Expectation plane, 期望平面5 J0 ~8 Z: m! L( b. j
Expectation surface, 期望曲面
9 f: g/ O" K# R2 H5 yExpected values, 期望值3 T- z; a p' `5 r* _0 G1 J+ {! B
Experiment, 实验+ o( n5 F4 j8 \, I: y
Experimental sampling, 试验抽样
2 s: R* J- Q! R: Q4 H" f0 F: Y* tExperimental unit, 试验单位
! G. f( R) `4 N. |/ s: F. T: fExplanatory variable, 说明变量; R" F! x. c% X# \9 k! }
Exploratory data analysis, 探索性数据分析
~9 t0 Q; N' jExplore Summarize, 探索-摘要) E1 p! J7 v! l2 U
Exponential curve, 指数曲线- p+ G! B8 ~$ u+ t
Exponential growth, 指数式增长
2 O% s$ E C3 k8 b- w: D* ^' j! aEXSMOOTH, 指数平滑方法
! G& ]1 }* H$ N$ U: gExtended fit, 扩充拟合
$ M; _, I: z1 ~+ g+ u! n9 A) VExtra parameter, 附加参数. o7 N+ W2 ^1 v3 C" J7 g
Extrapolation, 外推法
2 i7 h# N- F; e0 x$ K* R" RExtreme observation, 末端观测值$ B0 I8 A1 M( ^5 N& ?
Extremes, 极端值/极值
5 K5 |+ L; a: a* `9 lF distribution, F分布
3 s. f0 q* E% l$ CF test, F检验
% D4 k0 X v1 {+ QFactor, 因素/因子9 @& C o* N4 I3 c
Factor analysis, 因子分析
' h" n3 P) V+ l% W+ a2 GFactor Analysis, 因子分析
. Y, Q5 I+ k$ c; [# A' q/ Z6 {. d! wFactor score, 因子得分
0 R2 o) t. P) u6 _Factorial, 阶乘
# W5 p; O( R' V fFactorial design, 析因试验设计% c4 t8 ?1 A ?5 h/ o
False negative, 假阴性
# w: G5 S, w- @. ^( }6 sFalse negative error, 假阴性错误: N' K9 n" v* Z7 P5 x1 I
Family of distributions, 分布族4 B# W' A/ C' @
Family of estimators, 估计量族" s. B5 i1 M" w
Fanning, 扇面/ |) `- ?5 d' R, ^; Z
Fatality rate, 病死率
9 q$ {* q2 @' L1 O! h3 ^Field investigation, 现场调查( V, O) I6 V# {7 C: V
Field survey, 现场调查( ?4 z# y9 B% W. b6 f( |) P3 T
Finite population, 有限总体& ^9 k5 H7 G6 x4 E3 c% ~5 J1 R
Finite-sample, 有限样本
1 P* {9 |% h/ p) ]- jFirst derivative, 一阶导数; K7 K' u, y! z! D. _
First principal component, 第一主成分+ L/ l" O- |5 L3 E% `6 R
First quartile, 第一四分位数
0 {7 b m! w: _7 U: NFisher information, 费雪信息量
$ u2 g# f# [8 i8 j8 ]; I) z+ iFitted value, 拟合值! L- |0 J# h4 T$ k& m
Fitting a curve, 曲线拟合- N4 r" }, ]( v
Fixed base, 定基0 B, |/ o* o0 ?( Z
Fluctuation, 随机起伏
* Z3 a1 m9 |4 s* M B7 h, _+ }! h/ K3 z6 QForecast, 预测9 n0 v4 X. @- n, v
Four fold table, 四格表
& Q' i: h+ b; Z/ TFourth, 四分点) b# |# P: Z; T) C9 N9 t( ?
Fraction blow, 左侧比率
# k. H. \4 c, x; [% }2 TFractional error, 相对误差
0 {, w3 `) N- _3 X! z3 cFrequency, 频率* z% Q# n+ s# Y3 E. g8 u. J
Frequency polygon, 频数多边图
, T4 W5 D' r5 _. W& z. d. y1 @Frontier point, 界限点
, l2 V5 \) X1 bFunction relationship, 泛函关系
+ d5 D& L+ y4 O* e f2 G9 N# RGamma distribution, 伽玛分布
5 M2 Z3 Q9 \. g3 b. |9 BGauss increment, 高斯增量
/ D" ~& P- L" i2 I' i4 fGaussian distribution, 高斯分布/正态分布, V% _6 y1 F" x& y8 N' W% X
Gauss-Newton increment, 高斯-牛顿增量4 K% u9 F8 q+ \
General census, 全面普查5 ~$ R: U: A2 @: C+ R) P
GENLOG (Generalized liner models), 广义线性模型 , C8 ` a+ ]+ X" a6 F! h5 |; i+ o$ _
Geometric mean, 几何平均数0 [& C* J( v* q# }
Gini's mean difference, 基尼均差0 J& k' v' U: l+ }) N# y
GLM (General liner models), 一般线性模型 & C' u3 p8 ~$ `% y6 E
Goodness of fit, 拟和优度/配合度
$ F$ C4 k& `- G9 n# qGradient of determinant, 行列式的梯度
8 |8 `$ J8 {8 V5 Z `3 D" }Graeco-Latin square, 希腊拉丁方
6 _1 M C' T! z5 B+ V6 tGrand mean, 总均值
0 j _1 d' o2 L& E B% rGross errors, 重大错误
# g6 W+ i7 l4 n! U; ^$ |Gross-error sensitivity, 大错敏感度
3 ]; q- W3 s! U7 iGroup averages, 分组平均
2 \4 t. m4 v+ W, hGrouped data, 分组资料1 Z) |/ [5 w# c( H
Guessed mean, 假定平均数1 P: N6 W; S. g- _1 _1 l
Half-life, 半衰期
, E) v/ t, R4 L8 D. KHampel M-estimators, 汉佩尔M估计量
' ]; ?4 ?1 B0 C1 uHappenstance, 偶然事件- A5 n$ t. }3 v
Harmonic mean, 调和均数
4 d4 e$ Z! ]2 V# k3 v8 |* t+ B/ c mHazard function, 风险均数) i- T, t' S' ~* g4 Z6 m) Z
Hazard rate, 风险率+ ]- j' r7 N1 w! p) A- g. t
Heading, 标目 ) a! k% x* x( f) f- ]
Heavy-tailed distribution, 重尾分布
* y! ]7 a. g# w4 t" YHessian array, 海森立体阵
' w3 w/ `- M5 [( {Heterogeneity, 不同质0 z8 |' _7 C$ c- g- J- u$ y
Heterogeneity of variance, 方差不齐
. S# M5 W* Q) _% j$ A. h' W* ~Hierarchical classification, 组内分组- q; \& ^; |) _' \3 Y
Hierarchical clustering method, 系统聚类法
* h. I! v! r* i f* ?- bHigh-leverage point, 高杠杆率点
+ |0 G$ |0 ^7 L! j9 P. NHILOGLINEAR, 多维列联表的层次对数线性模型
) I, l. x* ?( E- UHinge, 折叶点
0 J) n; n3 [% y gHistogram, 直方图
9 I7 ?9 C4 m5 p6 {+ a( MHistorical cohort study, 历史性队列研究 3 H8 B) x9 P- `+ }/ W) ]/ N
Holes, 空洞; q$ F+ t) q- D, T" O7 v
HOMALS, 多重响应分析
! [4 I# ?5 ?& A( _. N" U. xHomogeneity of variance, 方差齐性
/ Y$ W4 i& c( [- l, uHomogeneity test, 齐性检验
, i6 U: C$ \% v- N' UHuber M-estimators, 休伯M估计量7 [8 F8 a, u# U, @5 u7 a0 H
Hyperbola, 双曲线
- n! ]' Z; P& c# I, kHypothesis testing, 假设检验
( F0 r. _7 ^5 x/ l7 u/ e9 BHypothetical universe, 假设总体
4 m& j; t' n- J2 tImpossible event, 不可能事件% f7 f- I1 C, f7 l
Independence, 独立性
* c4 B9 f3 U P. c( N8 NIndependent variable, 自变量
4 C c7 _3 }: x8 n) w, TIndex, 指标/指数
, ?! |( S9 n. {8 Z/ UIndirect standardization, 间接标准化法. U& D: c& Q( i7 D7 O0 }
Individual, 个体
3 n. K- D# E. I- y, R0 w8 RInference band, 推断带4 o3 v) J E! N* B8 b; B) n# y9 a! L
Infinite population, 无限总体
/ W2 X- u+ s+ K7 V8 y% {" aInfinitely great, 无穷大& |0 F( e( X' }* T7 A X
Infinitely small, 无穷小3 s" x3 Q Y3 C Z
Influence curve, 影响曲线
6 Q4 H6 v' s" O: ]( s5 }( M# EInformation capacity, 信息容量
+ ~" F- e. \# t5 l7 cInitial condition, 初始条件
+ z9 Q9 ~1 f4 q( j UInitial estimate, 初始估计值6 l+ V2 Z2 {3 I. o. d" B
Initial level, 最初水平* u5 b0 {4 [6 q# V7 A
Interaction, 交互作用
6 D$ P# q% X0 W5 g, MInteraction terms, 交互作用项
) N. k, C3 }3 b1 b0 f, vIntercept, 截距( q/ F! |8 j9 [: E6 i. z& B: L3 o
Interpolation, 内插法# d3 G" ^. i5 q1 K T1 K
Interquartile range, 四分位距1 c# M1 H8 u- D" `
Interval estimation, 区间估计
) ~7 ^9 H. `/ }) d; \. C9 AIntervals of equal probability, 等概率区间* n" g1 |/ Y8 f) H: b; h) a
Intrinsic curvature, 固有曲率
! B- b6 p+ U- m l/ R: B2 KInvariance, 不变性
& L" f; y0 W2 j4 cInverse matrix, 逆矩阵
% C/ O+ [) V' |1 L5 L# ]9 NInverse probability, 逆概率. M' g* S* i. Z/ k* A5 i/ b0 W
Inverse sine transformation, 反正弦变换' C& H- N* G" A
Iteration, 迭代
, R) D9 b7 K. i6 S7 f+ x5 HJacobian determinant, 雅可比行列式
5 P3 E2 g% v3 [1 @9 B) J/ s: hJoint distribution function, 分布函数
* X; z9 }, e7 H- S- SJoint probability, 联合概率
& x( ]7 b% x1 u+ @1 RJoint probability distribution, 联合概率分布 u6 G! m5 u0 E% {+ d
K means method, 逐步聚类法
! l" K0 D% n8 dKaplan-Meier, 评估事件的时间长度
2 v# @" {/ K; e( O4 iKaplan-Merier chart, Kaplan-Merier图
- l" ^/ A* G+ M2 a, D/ Q6 i3 uKendall's rank correlation, Kendall等级相关# }0 V8 F7 O5 M. Z6 B( h- v/ a# @
Kinetic, 动力学# m. B& |5 G; g X: M+ ~
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
7 G6 @6 r7 s/ Q+ i" yKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
1 u# \ ~0 F" I! X) O0 w m. z6 kKurtosis, 峰度
9 s( x: p- X! a ELack of fit, 失拟
2 l1 i3 H; E) Z6 k$ e8 \Ladder of powers, 幂阶梯
9 y& l G) ]! \5 J) nLag, 滞后
+ N% c/ N* n: h: n) @' FLarge sample, 大样本
* W& P- o( @+ @# {1 oLarge sample test, 大样本检验1 w1 N I! Z" x- t
Latin square, 拉丁方" d- h; Q2 e0 l* N2 I* {/ \
Latin square design, 拉丁方设计
, S( J; |% ?4 N# v* GLeakage, 泄漏9 }9 F# Z! h/ M7 U) \% \
Least favorable configuration, 最不利构形2 X; n' z. o0 w
Least favorable distribution, 最不利分布! r" y" V" x) V8 L1 C
Least significant difference, 最小显著差法% |- g6 \9 D9 t2 v, \" Z) e* S
Least square method, 最小二乘法
% g" P1 s* Z1 ?7 Y4 b$ pLeast-absolute-residuals estimates, 最小绝对残差估计
7 P# A. o$ z1 ^7 P) v6 K) J0 jLeast-absolute-residuals fit, 最小绝对残差拟合
3 Q8 `$ x D# ]9 a) I. dLeast-absolute-residuals line, 最小绝对残差线
8 v% Z6 |& s; n9 q. b0 VLegend, 图例
+ N- E+ ~( v# }2 @0 A8 t0 I; o0 QL-estimator, L估计量
/ q& j( x' `& |. g& YL-estimator of location, 位置L估计量8 A! C. O- @, c. A- T
L-estimator of scale, 尺度L估计量0 B% b9 a4 F5 }5 e* i$ B8 k0 A1 y
Level, 水平( m" r0 c! A- m, a( \
Life expectance, 预期期望寿命8 U3 N/ |" q3 o8 R% B/ N2 y
Life table, 寿命表 c% m2 Q, {3 W7 Q0 p
Life table method, 生命表法
+ _/ O3 {( o$ g4 Z; _: u: xLight-tailed distribution, 轻尾分布/ |7 q6 h5 S! N# {
Likelihood function, 似然函数
& n6 w; V; j: `: ELikelihood ratio, 似然比/ c2 e: @# t$ ?' E
line graph, 线图) n& `. D- R+ ]/ Z1 a% f0 r
Linear correlation, 直线相关
3 ]7 H, j. V, m6 S( o, P( m$ Z7 _Linear equation, 线性方程
$ q5 g3 v& [) f3 QLinear programming, 线性规划8 A' |* Y- }+ M$ i: V
Linear regression, 直线回归4 Z f- C1 v6 `: e1 s
Linear Regression, 线性回归
& o+ _: m3 Q2 f8 D XLinear trend, 线性趋势; x9 a1 c0 c9 n: K& H
Loading, 载荷
6 t# z8 W! O# Y% M5 ALocation and scale equivariance, 位置尺度同变性) ?! N7 N4 c: M( O: q. a8 n" y
Location equivariance, 位置同变性% b) M1 K; Z6 L. ]" y* K
Location invariance, 位置不变性
+ S/ J" `" w3 @# d! J7 S( FLocation scale family, 位置尺度族: z6 p% t/ }0 n9 a& j/ }
Log rank test, 时序检验
0 d0 |% q% J8 i) OLogarithmic curve, 对数曲线2 @. Y+ u$ P9 O
Logarithmic normal distribution, 对数正态分布
' ~; M2 E9 x) P$ A5 n$ a! YLogarithmic scale, 对数尺度( u% {9 v+ b2 @
Logarithmic transformation, 对数变换
6 E( Z; `0 C, Y: QLogic check, 逻辑检查
/ G" J, b. R. q" g8 w8 i, jLogistic distribution, 逻辑斯特分布) l o4 D( ?4 W& T
Logit transformation, Logit转换
- u% C" i& J. h& L5 y# f0 oLOGLINEAR, 多维列联表通用模型
: f- o: { ?8 _8 q! bLognormal distribution, 对数正态分布
2 W( i$ M( ]1 W6 g- c0 Q! K3 q9 eLost function, 损失函数( f- U! K& f0 d
Low correlation, 低度相关9 Z0 V) ]2 |. O' E% n S, t( ]
Lower limit, 下限
) C% s9 \0 ` G7 {) @& |5 cLowest-attained variance, 最小可达方差0 ] f+ N; U0 M- b# k. F% w
LSD, 最小显著差法的简称9 @- S( M4 N1 B
Lurking variable, 潜在变量+ s3 [2 R X) [" B" Y
Main effect, 主效应. X# e; v% {0 k5 X( b8 B# Y g$ _
Major heading, 主辞标目
/ @5 L; t& ^' @3 K$ M% jMarginal density function, 边缘密度函数+ `# m8 r2 l0 ]0 e& N( U e5 F/ ^; m$ t
Marginal probability, 边缘概率
# ]/ g# ]+ p, ?Marginal probability distribution, 边缘概率分布
& g# ~: {" [2 T$ vMatched data, 配对资料
& U" n% O: L# Q tMatched distribution, 匹配过分布5 Y: s' K/ R, q9 X/ o5 ?* X
Matching of distribution, 分布的匹配
4 |- a4 Y4 P: ~+ o4 @" _. XMatching of transformation, 变换的匹配: S; d2 @! O! {" P2 o$ F
Mathematical expectation, 数学期望- b" y0 o) Q1 P% h* k# h; I
Mathematical model, 数学模型+ ?; \3 U. v. F$ ~+ q
Maximum L-estimator, 极大极小L 估计量
1 P, D. p8 g3 Z. ?0 _# f$ o0 z LMaximum likelihood method, 最大似然法5 D2 Y6 j" ?8 L+ N4 h! o9 [: w' o
Mean, 均数/ u1 F+ ?* y! m" c; O' v, ~
Mean squares between groups, 组间均方 i0 W; R0 m) X$ t. M; u' S
Mean squares within group, 组内均方
2 ~ q1 X; v$ Z7 @, \Means (Compare means), 均值-均值比较
' K; @! T" ^2 Z. B( W# qMedian, 中位数& T& L+ m4 N! S, M( S: z% j3 H8 O' g
Median effective dose, 半数效量: g) h7 v) m0 t+ ~& K% H1 Y
Median lethal dose, 半数致死量
; E9 ?5 C( L+ v0 Q$ XMedian polish, 中位数平滑
8 {6 U8 b# c# a! BMedian test, 中位数检验
! p9 W; ^( c2 n& |Minimal sufficient statistic, 最小充分统计量* \! r) Z1 m! Z4 L, l
Minimum distance estimation, 最小距离估计
0 E* J% O! W; E* YMinimum effective dose, 最小有效量* m" I$ c- ^9 T
Minimum lethal dose, 最小致死量
, Z% |( }, ]* C; d fMinimum variance estimator, 最小方差估计量
0 c. q6 [9 }! _' P- }- {MINITAB, 统计软件包, K! r0 ^5 R( C+ {
Minor heading, 宾词标目8 J+ V8 F/ N6 _) v% Q5 c
Missing data, 缺失值
; R4 t: l6 r/ t h* @! R& yModel specification, 模型的确定
7 {2 C: @/ p4 \- J; j0 e5 cModeling Statistics , 模型统计$ v3 ~: `) P* \# G Y! _
Models for outliers, 离群值模型
9 h: b- t( \5 ?: T$ w( _Modifying the model, 模型的修正* ?9 u/ ~5 k+ N# z/ A
Modulus of continuity, 连续性模2 k% Y$ _3 p; M% ^+ f9 {
Morbidity, 发病率 ! v6 r* b8 a; a+ @+ W3 x
Most favorable configuration, 最有利构形
0 C2 T" ]. E3 P8 ?1 j" GMultidimensional Scaling (ASCAL), 多维尺度/多维标度
4 p. D* C# U i5 D5 V. ^Multinomial Logistic Regression , 多项逻辑斯蒂回归- D" O% X+ c: {& l( U: r6 N
Multiple comparison, 多重比较
, X Z. f+ p% U+ T7 FMultiple correlation , 复相关4 X, l9 L6 X* _5 D0 D
Multiple covariance, 多元协方差" x) e+ P, a* {( B) W w8 Z
Multiple linear regression, 多元线性回归0 J* _/ ~- Q5 H8 H- F1 x
Multiple response , 多重选项3 Z$ |8 w# ?5 x6 r
Multiple solutions, 多解) w* ]2 ?. d9 ` F6 |
Multiplication theorem, 乘法定理* o6 I/ X: r. P
Multiresponse, 多元响应5 j! `& \. L& q! e7 I$ [5 P9 w
Multi-stage sampling, 多阶段抽样/ M6 d* ?" G* _ h- E; a& \
Multivariate T distribution, 多元T分布
1 [; ~5 L1 i& _9 o1 j8 ?Mutual exclusive, 互不相容" a: O3 p2 Z! \3 f, M' g( |* n
Mutual independence, 互相独立+ X% d4 X: k# }7 J* r
Natural boundary, 自然边界+ P$ ]) F1 t5 [: B2 d* k
Natural dead, 自然死亡. f' ?: @8 q% f; W" x# n0 K. R
Natural zero, 自然零
6 u1 d, Q% x$ Q# |5 Y/ V9 _Negative correlation, 负相关8 o$ R$ ?4 d4 y1 K
Negative linear correlation, 负线性相关
# m& f; A/ k% T7 MNegatively skewed, 负偏/ K' k: s8 f7 I0 o V, T
Newman-Keuls method, q检验
0 w0 ^8 B( J( ]6 R7 f; RNK method, q检验
' F" s( U6 N: W2 [2 DNo statistical significance, 无统计意义; N& ?$ N7 y8 F
Nominal variable, 名义变量& D! d1 R# u- b/ t) T
Nonconstancy of variability, 变异的非定常性
' Z e; Q% T5 O. r I# wNonlinear regression, 非线性相关
0 O5 v) m, u: C3 {7 iNonparametric statistics, 非参数统计
0 D, H L `: g! fNonparametric test, 非参数检验
( Y6 t: n& T) B! p1 y7 {' jNonparametric tests, 非参数检验
# d: y ~! y( SNormal deviate, 正态离差
; {! d9 l4 a6 F2 w; j$ ]; _3 bNormal distribution, 正态分布
# @7 r; ^5 a: Y* f+ w1 gNormal equation, 正规方程组# K2 q F" P$ @; b8 k0 ]+ A) Z3 I
Normal ranges, 正常范围' h8 Z g* `& G
Normal value, 正常值2 G& B4 K( l2 M+ G9 D3 @5 S9 v
Nuisance parameter, 多余参数/讨厌参数
! _+ D& `8 X% k, ~9 W ZNull hypothesis, 无效假设 / a) Z/ `7 b; S' \4 l2 k
Numerical variable, 数值变量
, G( N- ?/ `. Z( X0 H# |0 Z3 TObjective function, 目标函数
2 L* ^3 z5 C3 G& q4 Q4 AObservation unit, 观察单位
* E0 g7 w8 u, v0 V; BObserved value, 观察值4 V3 q' O4 X/ H. e6 W; }
One sided test, 单侧检验
2 S, Q, r% o yOne-way analysis of variance, 单因素方差分析9 {6 K* F/ Z( H5 n: [* B. v
Oneway ANOVA , 单因素方差分析6 f# r6 M( i& Z: {; ]
Open sequential trial, 开放型序贯设计
; ?$ T+ i9 q, ?6 D3 e( W2 xOptrim, 优切尾1 c9 a/ b a8 N! i) r% C5 o
Optrim efficiency, 优切尾效率: m6 \+ N0 \+ H5 ]2 o- P8 P4 F
Order statistics, 顺序统计量; t- W, g' o2 K, O% q$ n1 D
Ordered categories, 有序分类, o3 @, N* n3 p- G; X b
Ordinal logistic regression , 序数逻辑斯蒂回归
& K y+ E, F8 I" Y- ?0 W/ M- uOrdinal variable, 有序变量7 J( {! C4 u9 a, `8 ~. f
Orthogonal basis, 正交基5 a* }# |+ ^) F# N, s% L( [7 J- ]8 z( Z
Orthogonal design, 正交试验设计8 V+ i# \, z/ u" C7 e
Orthogonality conditions, 正交条件
* q7 @# {: @9 @3 R- HORTHOPLAN, 正交设计 & V# r" |* L, `% @; a5 w
Outlier cutoffs, 离群值截断点! [2 H2 v, L2 Y3 @& F# b
Outliers, 极端值
9 j; J% P7 K9 S* `9 aOVERALS , 多组变量的非线性正规相关
5 Z. G$ k( \# U- |& j7 p" C, X0 NOvershoot, 迭代过度
- J, F3 K% f3 A4 _: w$ \6 ~0 h& {Paired design, 配对设计, j/ @; z! S8 Q9 \; @
Paired sample, 配对样本
- C' k' v, J; Q7 HPairwise slopes, 成对斜率
; b* o) M! d; H( tParabola, 抛物线
- h6 G) t# x; K% U4 T1 nParallel tests, 平行试验
6 k" m! z: H9 i, PParameter, 参数
! O3 d: U. h1 F5 e3 jParametric statistics, 参数统计
/ s9 k2 l" `' q. ]; VParametric test, 参数检验
! F$ o$ D) y$ w' [0 } L% i8 o- ]Partial correlation, 偏相关9 x. i* O; V& _# w% B! T
Partial regression, 偏回归
1 G6 M4 m8 X4 }% }) vPartial sorting, 偏排序
" k& N3 [% L6 ^: u3 LPartials residuals, 偏残差; Z% A2 G8 g( A. w
Pattern, 模式) P/ u5 E6 {! j1 n5 _, J& i
Pearson curves, 皮尔逊曲线. r& L* |6 a4 i$ p, v
Peeling, 退层 z& @( o. l* g- z* F( O8 ?
Percent bar graph, 百分条形图
8 I* S1 E) ~; TPercentage, 百分比
* R8 z" N: z; z S/ U8 { X1 P9 ^Percentile, 百分位数
/ {' e7 O8 W/ Q" J9 \) XPercentile curves, 百分位曲线
% A5 e9 g2 c! E8 h. }Periodicity, 周期性# S$ e/ P) X; n- N
Permutation, 排列( d. s) z% ?1 n. s- ~
P-estimator, P估计量4 c+ i: k* L- G! k! e5 r( n
Pie graph, 饼图; U* e" `& a+ M% v6 Z8 b
Pitman estimator, 皮特曼估计量
2 r! k( O1 B4 Y" pPivot, 枢轴量" _5 A, B# s9 K% F8 D8 J8 q
Planar, 平坦3 ?5 K6 `& @/ Y# E* [. o( c
Planar assumption, 平面的假设- h: i2 C1 ~1 {5 _
PLANCARDS, 生成试验的计划卡! u j% ~5 p# {" ? l
Point estimation, 点估计2 J* ^% R) ]! d5 B! H
Poisson distribution, 泊松分布- d. G$ |, c5 i& q; B7 ?
Polishing, 平滑
$ p [! }9 k/ ^" M# n6 x% E# bPolled standard deviation, 合并标准差
1 I: Y4 k1 V: C2 |" h8 \2 `" DPolled variance, 合并方差
" e! n2 C, B5 v1 r4 jPolygon, 多边图
: b/ r; u- Q: Y2 U# fPolynomial, 多项式0 I" \( N7 C; M1 ]0 y2 j* Z. Q
Polynomial curve, 多项式曲线$ Z- j2 D4 p' v' l8 L' }0 w
Population, 总体
! e8 [3 d& a- a ~6 Q/ ?0 l4 j1 pPopulation attributable risk, 人群归因危险度
V+ H% h7 l- j( j# [! f+ O7 X" ?Positive correlation, 正相关: x* a) I3 N( D2 a1 p. m7 e( E
Positively skewed, 正偏
# O% G; Z! c/ M4 p; |Posterior distribution, 后验分布5 O4 R t0 }3 g8 m2 l
Power of a test, 检验效能
" ^, n, |4 l6 |Precision, 精密度0 f: |5 X- [+ k; ^8 v
Predicted value, 预测值
# v& L( L# g- D8 A j6 EPreliminary analysis, 预备性分析3 X, `1 p, T B: I( ?/ W8 ~+ i
Principal component analysis, 主成分分析4 b6 H2 k6 n" L, o9 d. `7 e
Prior distribution, 先验分布. W4 q* ^. `) O$ E) [% e
Prior probability, 先验概率( C2 _( v7 {! [) l* ?# ~5 l( Y
Probabilistic model, 概率模型8 @4 {5 u' n6 M4 f+ w) ~; L% H
probability, 概率+ L+ w/ h$ e5 C1 v
Probability density, 概率密度
, P& r ~2 D+ JProduct moment, 乘积矩/协方差; k& \* W2 k) d# H' Q N
Profile trace, 截面迹图
* K+ L( [% }! L" b1 X. c* rProportion, 比/构成比
% k$ _. _6 L6 @; oProportion allocation in stratified random sampling, 按比例分层随机抽样
* i* T& ^: S' D1 W2 D. o/ o1 {Proportionate, 成比例; r+ U" C- O% Q
Proportionate sub-class numbers, 成比例次级组含量
. r: X! }/ u5 oProspective study, 前瞻性调查% q! B* O1 ^, b8 o9 B E- v6 ^
Proximities, 亲近性
" b, p% l/ r: I+ N; r4 zPseudo F test, 近似F检验 d0 U D" n8 [1 i+ v$ f
Pseudo model, 近似模型
$ X( |/ v& _5 r H/ k0 X0 m8 B. CPseudosigma, 伪标准差6 m+ F) \4 T# ~3 n! Y- ]
Purposive sampling, 有目的抽样
% A% k Q" B* v) A1 _3 S; m5 KQR decomposition, QR分解
% w, N9 b/ ?( L9 f" ~/ gQuadratic approximation, 二次近似
' Z- A6 j! P. lQualitative classification, 属性分类% w1 w/ y( d+ P6 e1 t
Qualitative method, 定性方法$ V; ?8 m) ^/ l. P
Quantile-quantile plot, 分位数-分位数图/Q-Q图% J7 S4 b$ N3 I# w( ~& |2 v
Quantitative analysis, 定量分析2 C& A" m4 w& v$ U9 g3 V" f% \) Q, a
Quartile, 四分位数/ z: @( D* f! @
Quick Cluster, 快速聚类: D! [3 s5 A* e+ `
Radix sort, 基数排序" N) y: H/ X8 r; \) P9 U: y D
Random allocation, 随机化分组8 R" y4 I7 f9 [
Random blocks design, 随机区组设计) k9 j$ o! L$ o- J* e% V. F
Random event, 随机事件
9 S- m! R% b6 r+ s: nRandomization, 随机化
! y! j/ Y7 u+ `) |- j VRange, 极差/全距
( ?( I" K/ j% M9 C8 [3 v2 GRank correlation, 等级相关6 V( \7 \, R( I. d1 `
Rank sum test, 秩和检验
w+ d2 j* {4 }& QRank test, 秩检验; ~# C9 c1 B( g2 V, {0 C; B- @
Ranked data, 等级资料
$ u7 L6 g8 X6 s J6 ORate, 比率. M( I( d+ Z8 W7 b
Ratio, 比例
5 ]' _- w7 R& Z2 d+ B4 vRaw data, 原始资料
/ \" O1 O T+ W# Z- {Raw residual, 原始残差4 o0 m% S2 x( k; }
Rayleigh's test, 雷氏检验8 q6 ?4 g8 c' w( e9 V
Rayleigh's Z, 雷氏Z值 + B3 l, S% x6 T- s( c/ y
Reciprocal, 倒数
% s% d7 G1 l# Y, p, O, lReciprocal transformation, 倒数变换
# P& u. {5 f) u; O4 ~% M5 \7 ]Recording, 记录
$ H; c9 [: P2 fRedescending estimators, 回降估计量
) N& I; w& b+ e' e: v: OReducing dimensions, 降维
8 }* X9 |3 |' w9 p! C4 lRe-expression, 重新表达8 R* H+ D7 E1 |/ S8 z
Reference set, 标准组' G4 \/ `8 `+ {2 p6 z. A
Region of acceptance, 接受域
: }2 y9 v( B2 m2 W" MRegression coefficient, 回归系数+ T0 o7 e4 P: R/ r6 n. n7 v: ?
Regression sum of square, 回归平方和& d$ a9 `! }. i/ J: z- b
Rejection point, 拒绝点% q6 y3 a2 t+ R t
Relative dispersion, 相对离散度: ^, H2 x/ @. `* P
Relative number, 相对数, t( q3 X/ Z& Z8 q
Reliability, 可靠性
0 v7 {% k; ]' I6 j2 Q8 WReparametrization, 重新设置参数8 a' L4 y1 E5 ^: n, X7 F$ ^' Z5 B9 ?
Replication, 重复& j1 ?6 [2 J7 _4 H; F9 N4 {: C
Report Summaries, 报告摘要3 w- b" d- ^6 F* Z. U6 r$ @
Residual sum of square, 剩余平方和/ L( Z& q0 U/ \, Z2 ?; q
Resistance, 耐抗性3 h+ ?7 v, a2 R! M
Resistant line, 耐抗线. ?; `4 S* n/ Z6 a9 _
Resistant technique, 耐抗技术" q% v, s6 w! P! B
R-estimator of location, 位置R估计量
' V# |) b- i. T0 b+ TR-estimator of scale, 尺度R估计量
* \. G' V# `) g7 Z: P XRetrospective study, 回顾性调查
. P' M. \6 [( [" oRidge trace, 岭迹
& X/ u5 t' J' ~4 N) e$ F( mRidit analysis, Ridit分析4 [( r' Z1 {% s
Rotation, 旋转$ ^. {, C. A' n; k! q' l
Rounding, 舍入% b" `/ s) \7 S- d% P1 @5 I6 t/ V3 }6 P
Row, 行0 e- m& y# B8 Z' V8 p4 e1 Q
Row effects, 行效应
, |9 t; h9 W' G& n* E+ xRow factor, 行因素( P$ d2 i0 D/ P* T% a+ Z4 @" O
RXC table, RXC表6 H9 N: }% A1 H- F. _6 \) s
Sample, 样本
' h: E2 Q( e# ~) ?& T" HSample regression coefficient, 样本回归系数
9 v O/ ~9 U) k3 P) A" y& c! T# o0 bSample size, 样本量+ k# h1 j/ ^2 m' F3 D
Sample standard deviation, 样本标准差4 P4 G, K0 _3 k3 c" w4 h
Sampling error, 抽样误差1 R% T9 Z* a$ L3 P& g, Z2 D( T
SAS(Statistical analysis system ), SAS统计软件包
. _ X- a7 G' S. Q* m1 l; B4 \( q$ OScale, 尺度/量表
* r# Q* M% r3 u# cScatter diagram, 散点图
/ y; M. V2 w; W& W1 ASchematic plot, 示意图/简图" ?/ a* } d8 ~/ a2 p/ [" v
Score test, 计分检验. I$ t. t' F( y4 O) |! F7 |- [, U
Screening, 筛检8 l0 F) j2 c) \1 b& {! I
SEASON, 季节分析 & D' U1 I$ N' z& k% ^8 r7 `: m5 @
Second derivative, 二阶导数# ~& {& I, _3 h% @& h* @0 B
Second principal component, 第二主成分6 m* w+ Q2 L, }
SEM (Structural equation modeling), 结构化方程模型 " F' F/ w9 R9 n
Semi-logarithmic graph, 半对数图5 d1 S p0 v9 |( |" c
Semi-logarithmic paper, 半对数格纸
: m) i; T& y3 \8 E. u( V0 B- a! ~Sensitivity curve, 敏感度曲线$ f6 W: B: l K7 ?8 x
Sequential analysis, 贯序分析6 j9 @5 m# }; M5 z8 B
Sequential data set, 顺序数据集" K1 @) m- ?7 ?( ^/ a* l8 m) q! c* u
Sequential design, 贯序设计
& C6 P1 X' H" @Sequential method, 贯序法& T, u) h1 n, F: ^( D
Sequential test, 贯序检验法: `6 ]; ]5 `! K% _
Serial tests, 系列试验; d7 F0 @( U4 Y/ m
Short-cut method, 简捷法 $ u" q1 ^' M9 [& F8 _
Sigmoid curve, S形曲线
0 h" t5 q8 @9 J# kSign function, 正负号函数- e% D# V; k$ e# S u' ^+ z
Sign test, 符号检验7 C7 ~& d% w$ O! C1 i7 b. @
Signed rank, 符号秩
6 ^) x" X6 i8 K6 nSignificance test, 显著性检验
# G0 e2 l7 R* _Significant figure, 有效数字
. [; ?1 L8 D \6 g) O: |2 ^Simple cluster sampling, 简单整群抽样
4 A& i3 Y& h: T+ P- LSimple correlation, 简单相关
; B8 l4 c6 s9 f; g; P9 v" nSimple random sampling, 简单随机抽样$ x' P F; l- K# i1 d
Simple regression, 简单回归
6 e( @# |6 P$ q' P0 _( p& y: R9 Jsimple table, 简单表. @" K' w: ~4 F5 q
Sine estimator, 正弦估计量
4 r* u9 }+ r$ y) J0 a1 o1 r$ cSingle-valued estimate, 单值估计
2 B; K0 u7 y9 s1 l( U9 bSingular matrix, 奇异矩阵) o K6 t% I; x! v( ?
Skewed distribution, 偏斜分布
( Q% R% u- O2 m2 J# xSkewness, 偏度# Q9 t4 w& x+ e
Slash distribution, 斜线分布7 X; Q( I- O. n0 C5 e7 A8 j
Slope, 斜率
& q' y* _, U1 ESmirnov test, 斯米尔诺夫检验
( W4 U$ _' u/ B7 o' c+ R' TSource of variation, 变异来源
! D! @& `, W; A1 VSpearman rank correlation, 斯皮尔曼等级相关
% U- [; ?2 R, t; [0 j% |Specific factor, 特殊因子
1 b, G! J! a/ i; ]8 oSpecific factor variance, 特殊因子方差
2 s/ \) x" S/ J1 M1 Q- vSpectra , 频谱
3 i: O7 j m1 f7 m* Z8 L) x! gSpherical distribution, 球型正态分布, R) p, [+ x8 n9 T( t
Spread, 展布
7 ~. l2 ~/ G& f1 ?SPSS(Statistical package for the social science), SPSS统计软件包
) c d) d2 E/ Z' f2 ^Spurious correlation, 假性相关
) ~6 j4 {7 W* N3 o4 T1 mSquare root transformation, 平方根变换
" m% o& s! E3 a! o, u r0 VStabilizing variance, 稳定方差1 B( F: J# A) r$ b. A. e- l3 q4 p
Standard deviation, 标准差
6 d6 ^2 v! R, |& @. ^Standard error, 标准误
$ v, U- Q" `. |8 [Standard error of difference, 差别的标准误
: W2 p: {# N6 ?8 ~ \. K8 D- m' YStandard error of estimate, 标准估计误差0 `9 `" w: p0 }( q9 @9 p4 U
Standard error of rate, 率的标准误
/ F0 ]4 Y) W! C3 w; ]; z5 W6 g; x0 zStandard normal distribution, 标准正态分布
+ d. a, M2 N ^4 _, v6 ^' [, q' fStandardization, 标准化# G$ k. B' M; b; ]% D# ]
Starting value, 起始值
' M0 o A. U9 ^# j, ^Statistic, 统计量% F" S7 C) L8 Q# v& |
Statistical control, 统计控制
6 z+ x3 p5 c4 P: iStatistical graph, 统计图
& Y( @5 }- n) E: XStatistical inference, 统计推断
. H6 h9 W: m0 [Statistical table, 统计表
$ `- l; P% r. G5 H. NSteepest descent, 最速下降法
) v* V+ T0 d' K% w' kStem and leaf display, 茎叶图
& B2 Z4 b+ A9 Y: CStep factor, 步长因子! @8 B3 {+ U2 V
Stepwise regression, 逐步回归, h5 g+ `7 {# |, l
Storage, 存* j3 {3 ~( \+ x0 `3 U! a0 ^5 w; U2 Q5 V
Strata, 层（复数） a3 O! l0 s4 s% ?8 Z
Stratified sampling, 分层抽样
1 g, R: V. M+ I9 BStratified sampling, 分层抽样* v: W; C( W6 s' k/ W9 q
Strength, 强度
# |$ N" }7 U' ]2 aStringency, 严密性, J" W2 L: d# n. P
Structural relationship, 结构关系
3 o, ]% Z1 N4 E {. R* h/ {Studentized residual, 学生化残差/t化残差5 L7 Y2 R( m# k: s' M: K
Sub-class numbers, 次级组含量
! o/ k$ B' O7 ^$ `; O* DSubdividing, 分割1 R' j, O8 r) M( t E& ]/ L
Sufficient statistic, 充分统计量 e* j# {* p* \6 S; o0 G
Sum of products, 积和7 t/ n8 S: F( _3 D
Sum of squares, 离差平方和' y- a4 B+ [, u) y' c: l
Sum of squares about regression, 回归平方和* [! ~$ Y3 D' R/ K" b
Sum of squares between groups, 组间平方和
; N1 D, z+ T* ~) F/ q' ISum of squares of partial regression, 偏回归平方和1 O6 X; q" }" g5 m% y
Sure event, 必然事件% P; V: a$ }( g! O' j. n3 D5 \
Survey, 调查
" K+ g5 ~9 u+ k2 V) ySurvival, 生存分析; T+ ]0 O q2 X- S
Survival rate, 生存率9 X0 E8 @: f2 Q# ` A0 ~) D
Suspended root gram, 悬吊根图
, a N7 ~! v& W8 ?- fSymmetry, 对称8 `- R1 N. y c
Systematic error, 系统误差
0 T/ R& K1 {! K# nSystematic sampling, 系统抽样" n \- m( ~& v, y
Tags, 标签, K* J& A6 w) m% O$ n5 n0 [
Tail area, 尾部面积
5 ?( G7 ^3 g0 n, ]9 }Tail length, 尾长$ O4 j8 D7 L: r( f& w8 h
Tail weight, 尾重0 A& V% |4 O5 [
Tangent line, 切线
! U4 g& A: s! eTarget distribution, 目标分布
% v* G/ Z+ p" k) |1 P, z8 A) \Taylor series, 泰勒级数
1 f* [# n- m* l7 c. w) |Tendency of dispersion, 离散趋势
) [" ?. S# D" x& n2 p9 a" U M7 B; ATesting of hypotheses, 假设检验7 z5 M- y$ [# x; a
Theoretical frequency, 理论频数, w! k5 c; n: ^; F
Time series, 时间序列; B; C8 }5 Z! ~5 I$ I
Tolerance interval, 容忍区间; i4 S8 l3 a0 ~2 J- Z2 e
Tolerance lower limit, 容忍下限
, ~: _# a0 h+ D* m( f9 Z7 t/ jTolerance upper limit, 容忍上限
) }; G& [; F7 g; w+ F7 N. x7 XTorsion, 扰率
- A: F# g( [& b4 z3 FTotal sum of square, 总平方和
6 E: m1 H) S% J# n/ {Total variation, 总变异
# W3 z: b4 u# o% C3 c* N: D* r; h qTransformation, 转换
8 i9 p7 P5 s1 qTreatment, 处理6 @' D0 P: d9 \- a# {& J
Trend, 趋势. `8 U& s/ Y. y* c# P# h
Trend of percentage, 百分比趋势8 m) Q0 k8 ~) n& c7 g( p8 @
Trial, 试验, d4 \% Q: i8 F% ^2 ] K$ D0 \
Trial and error method, 试错法4 k6 ]) e) f0 T& f; z
Tuning constant, 细调常数/ u/ y5 d$ \8 D% W f; @& y) W- b' ~
Two sided test, 双向检验
1 l% D3 O% m7 s- jTwo-stage least squares, 二阶最小平方
6 R9 ]: c; V$ n; l/ kTwo-stage sampling, 二阶段抽样
5 J4 S( {! ^2 H! }) BTwo-tailed test, 双侧检验
6 M7 q) P$ R8 b1 F$ t- I% `Two-way analysis of variance, 双因素方差分析
( b5 w& O- p& c/ |: T% M6 eTwo-way table, 双向表
- U3 y# F! h* [Type I error, 一类错误/α错误, J& m# A! R; @% D( z
Type II error, 二类错误/β错误2 x# R1 S# z( U6 f
UMVU, 方差一致最小无偏估计简称
: j3 m7 g' z" u3 n/ u! Y4 R6 D: yUnbiased estimate, 无偏估计
: e8 B9 h/ h& F \' BUnconstrained nonlinear regression , 无约束非线性回归
! a/ t* J. O% P% T8 I& V) IUnequal subclass number, 不等次级组含量! T" @0 k9 f0 N
Ungrouped data, 不分组资料) M1 `# C$ H1 d$ _* U
Uniform coordinate, 均匀坐标' s/ o: Z+ Z! S2 F- V' S
Uniform distribution, 均匀分布$ D: a Y+ O7 d( ^& [
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计2 g# W$ M f* Z- Z( Z
Unit, 单元. F4 L1 ^# m) q1 X$ N" n4 z
Unordered categories, 无序分类9 q! N+ Y, {: s
Upper limit, 上限% i3 A! j" M- I# w; d Z/ u; y
Upward rank, 升秩$ x. x M4 y' J6 E6 z6 f
Vague concept, 模糊概念
7 x& u3 ]2 S+ V5 @( ^0 l# tValidity, 有效性
3 B3 P# j! I1 ~( p+ c; |: JVARCOMP (Variance component estimation), 方差元素估计/ p$ p" X! L+ e ^+ V) u
Variability, 变异性5 V: i/ R& K. s6 Y
Variable, 变量* c8 }- {: }+ S8 _' B9 v
Variance, 方差% m9 g& K2 E% g% V0 d* O
Variation, 变异8 q; g4 l) p C2 k; ~: c! j
Varimax orthogonal rotation, 方差最大正交旋转. R: f! P& h# y _$ _1 O$ k6 D
Volume of distribution, 容积- A# N& G1 z8 K }
W test, W检验
' ^$ ?3 d/ \' l) v; `3 Y) vWeibull distribution, 威布尔分布7 S" {, y; t1 E& `* }: g. w
Weight, 权数
" M3 T# t4 \/ G; h: _Weighted Chi-square test, 加权卡方检验/Cochran检验& W4 J8 s9 W; A* h( g
Weighted linear regression method, 加权直线回归
! U0 t/ A; J! a# Y( \Weighted mean, 加权平均数
5 n$ w" Y' E/ M7 u. eWeighted mean square, 加权平均方差
1 }7 L; D: h# GWeighted sum of square, 加权平方和' y# @3 \1 D8 U
Weighting coefficient, 权重系数
" U5 D6 T2 Z8 N' w/ x/ AWeighting method, 加权法
8 g1 I7 [8 ^+ ?- b \; X% h$ K- L1 |, DW-estimation, W估计量
- _- C; q/ U5 [# OW-estimation of location, 位置W估计量6 [9 P) h6 O$ \7 `% g
Width, 宽度# j$ O6 q. T0 G4 L6 {& f
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
7 [0 l( G% N4 `$ hWild point, 野点/狂点5 {% M' a! ` {/ c% |9 c
Wild value, 野值/狂值, f- V; P9 _7 T; v# h
Winsorized mean, 缩尾均值
' N# W9 x( \1 T& u$ aWithdraw, 失访
- v, A7 d; e; Q t7 BYouden's index, 尤登指数3 |/ W: s& D, y
Z test, Z检验
0 L! x g, ~: WZero correlation, 零相关( P# M6 ]0 d( ~7 ^- E) i
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
