|
|
Absolute deviation, 绝对离差
2 n' C2 M/ f+ r( `6 ]Absolute number, 绝对数) J# B" V( b9 m8 A
Absolute residuals, 绝对残差$ _2 b9 v2 _2 f* S" y0 O7 |
Acceleration array, 加速度立体阵
, T+ v- H3 V$ u4 {Acceleration in an arbitrary direction, 任意方向上的加速度
# Q( z" D" L- I9 M+ b' K% kAcceleration normal, 法向加速度9 ~% O: l% w6 m9 D% d
Acceleration space dimension, 加速度空间的维数
: e; G, C$ m' ~Acceleration tangential, 切向加速度
! z1 q( X/ Q. @+ }1 ~& P) j+ WAcceleration vector, 加速度向量
+ O7 h3 D3 [( X& ?/ e. }4 K; OAcceptable hypothesis, 可接受假设( \+ U: n" @! C
Accumulation, 累积, |! A% G$ \( q- v/ `! D9 p
Accuracy, 准确度# D$ h- B* G8 F" N
Actual frequency, 实际频数) i. R6 k4 z) }- v& X; J
Adaptive estimator, 自适应估计量
6 y# D+ e+ x! p5 xAddition, 相加 B9 R& r& E0 {5 a# E+ H
Addition theorem, 加法定理& B. R+ M. v9 ]& J6 ]
Additivity, 可加性' I+ M% V' Y/ K2 r+ J5 j
Adjusted rate, 调整率
( Z* Y) K7 ]/ { l( L4 b% E. c/ BAdjusted value, 校正值' _7 P) I: i' G% F# z7 P, x
Admissible error, 容许误差
5 u4 Y0 I( T( f" Q3 z8 p" ~, \Aggregation, 聚集性
" m8 O5 B8 X; z( r9 h* tAlternative hypothesis, 备择假设7 s% w z A' C# k1 i
Among groups, 组间
8 L. V# Q: T; @Amounts, 总量
0 b R- f# }- f$ w/ MAnalysis of correlation, 相关分析
9 U" \' F- c; A* gAnalysis of covariance, 协方差分析
2 f. k4 @" D5 FAnalysis of regression, 回归分析
2 b5 P5 e& o$ n" u% |: D: q3 Q& gAnalysis of time series, 时间序列分析. |! A8 e1 n- J6 N& K. Y! N$ B ^
Analysis of variance, 方差分析
0 f, c) D9 {$ u3 w/ G0 FAngular transformation, 角转换1 x/ Y. R. ? I: V* O
ANOVA （analysis of variance）, 方差分析
, n* v" E1 f' N+ S7 \# _( oANOVA Models, 方差分析模型) X) \$ r2 U, X% k0 g
Arcing, 弧/弧旋. C( e- X' s$ X. c( L
Arcsine transformation, 反正弦变换
; Z. d6 `0 M. W* N }" KArea under the curve, 曲线面积
: R) L( [2 R6 \AREG , 评估从一个时间点到下一个时间点回归相关时的误差
, Q/ Q8 J# V( j8 E5 T6 J/ ]ARIMA, 季节和非季节性单变量模型的极大似然估计
- e- ], s& K/ a8 b- R OArithmetic grid paper, 算术格纸
0 ^4 x+ K4 u# [ {$ F) z# h! \. pArithmetic mean, 算术平均数0 w+ r K) [5 C- c
Arrhenius relation, 艾恩尼斯关系
# o3 P6 Z8 E7 p+ }$ ^. sAssessing fit, 拟合的评估5 |5 K+ s0 }4 a9 A6 ?
Associative laws, 结合律
8 d0 D, [2 f4 eAsymmetric distribution, 非对称分布
' Z$ r3 d7 @6 r- Y- K! H% dAsymptotic bias, 渐近偏倚
7 k' [6 ~ N" |6 Y1 XAsymptotic efficiency, 渐近效率5 Z) {) {( a% X& {$ @
Asymptotic variance, 渐近方差4 A2 j' w* d3 L, a# T
Attributable risk, 归因危险度
) o s% @: I. ^) G3 QAttribute data, 属性资料- A( @4 H% C; b: i
Attribution, 属性
) y y5 | R6 P6 _9 U* i6 z0 y- \$ sAutocorrelation, 自相关
, d9 y4 ^; W( x7 e/ RAutocorrelation of residuals, 残差的自相关
: H9 T9 u- f% `8 c: r1 HAverage, 平均数
7 ]) n: }' o: G) v$ M8 ?5 `7 h6 FAverage confidence interval length, 平均置信区间长度( B5 ~" ]6 d9 ~# n( H
Average growth rate, 平均增长率
1 y) a; \) S( }/ Q) zBar chart, 条形图8 q- X+ m) M6 L! k8 L7 ~7 D% z* r
Bar graph, 条形图! ]3 N& K8 h5 ?- b9 d1 s1 m& U
Base period, 基期
% {8 @7 V4 e! x6 T9 } k' {& D9 SBayes' theorem , Bayes定理4 G) p3 p( \; j3 h& M- E: N/ b
Bell-shaped curve, 钟形曲线3 j/ Q$ M7 S Z7 `9 n" N6 Y$ a
Bernoulli distribution, 伯努力分布
+ f; k, ^! n% D6 t: ]Best-trim estimator, 最好切尾估计量2 N1 ~2 r$ |$ J8 r* Q: L5 Q
Bias, 偏性4 v# ~$ C/ r4 n
Binary logistic regression, 二元逻辑斯蒂回归* ^/ @' h w4 N1 H, v
Binomial distribution, 二项分布; f( r) w; e9 i$ ]9 K; {9 m
Bisquare, 双平方0 N @2 }; A' T8 h
Bivariate Correlate, 二变量相关
% D5 z3 X }; V5 W6 {Bivariate normal distribution, 双变量正态分布2 ] F) J# q" D# s d
Bivariate normal population, 双变量正态总体
+ d! u$ M w$ R- }Biweight interval, 双权区间
" V$ } ?: \0 f( `, u% wBiweight M-estimator, 双权M估计量
9 I/ _3 r w$ p( l: \Block, 区组/配伍组
# v3 y4 h- {4 B8 Z- U7 [: UBMDP(Biomedical computer programs), BMDP统计软件包2 H" u0 U0 \2 J: @
Boxplots, 箱线图/箱尾图4 ^/ ~* L9 T% V# o
Breakdown bound, 崩溃界/崩溃点
2 b" t" [3 u6 x! hCanonical correlation, 典型相关7 k7 T7 E* X! h$ G7 e' H% [
Caption, 纵标目
0 Y& ]1 a, J9 G1 M0 z O; iCase-control study, 病例对照研究
/ p# V$ C. @; _* `! e+ I5 a9 ]Categorical variable, 分类变量5 z0 C) W; X0 s* o0 G
Catenary, 悬链线
K" J4 X$ O3 w& _/ K) k* FCauchy distribution, 柯西分布
! ~; @3 `; t B2 E6 gCause-and-effect relationship, 因果关系# V" g6 g0 D! p
Cell, 单元9 r! \: D' G6 _4 ]' ~2 v
Censoring, 终检
: T- M# i, [2 G- _* m3 SCenter of symmetry, 对称中心- P N1 ?* [0 K+ V1 g3 H
Centering and scaling, 中心化和定标' F1 q) i" c- ]4 S- c! e( ^
Central tendency, 集中趋势: x! y- l7 P6 M; y* w
Central value, 中心值! g2 @ J& z3 _$ ?% W
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
. [2 l9 Y0 w( YChance, 机遇
5 {! f% Z: r; l0 s" G1 i, hChance error, 随机误差
! ~! K) G, v) k9 w3 i5 u) V' t( YChance variable, 随机变量9 s2 s7 p! R* X
Characteristic equation, 特征方程5 Q5 |. O0 R8 v# h i- L
Characteristic root, 特征根) r; K% C1 ]5 @1 M
Characteristic vector, 特征向量$ t- j' X% ?' T
Chebshev criterion of fit, 拟合的切比雪夫准则
% u$ }: m2 c8 O5 W, m& m1 |& GChernoff faces, 切尔诺夫脸谱图7 j4 j5 m+ ~2 P; \
Chi-square test, 卡方检验/χ2检验8 w% O) N. i! I3 C% f3 F
Choleskey decomposition, 乔洛斯基分解5 E4 O3 }; D' [. A9 a+ F
Circle chart, 圆图
0 t' |' F& }: T- Z2 \* _$ f8 {Class interval, 组距
7 ]5 y) d4 Q! C0 j# cClass mid-value, 组中值
; m; n* _ `% s8 P9 z' }+ c3 QClass upper limit, 组上限
* ~% o7 ]0 L* ?Classified variable, 分类变量
0 |/ z% l0 R: `/ b1 x, rCluster analysis, 聚类分析
" m- Q/ n9 A' E7 n- X, T8 eCluster sampling, 整群抽样! }3 ]! h# E7 N' f( t l8 ~7 E
Code, 代码
1 T, k) {& a! [% I) e& |9 iCoded data, 编码数据& [/ L. L3 b3 n- k5 P& }0 F* A
Coding, 编码) c" n4 q& L; s4 y/ h6 R
Coefficient of contingency, 列联系数
6 r) J6 M8 P+ s* G9 J w" XCoefficient of determination, 决定系数; ?$ g; V% |+ I0 v( V0 D
Coefficient of multiple correlation, 多重相关系数8 k" D& R' d$ K+ P& b
Coefficient of partial correlation, 偏相关系数5 {& V$ [' H) W! A Z- m# p
Coefficient of production-moment correlation, 积差相关系数
1 k$ i, y4 R2 L0 j' n! F UCoefficient of rank correlation, 等级相关系数% _ h; D- A- _
Coefficient of regression, 回归系数
/ s- c+ z$ o& E( j. h% W& tCoefficient of skewness, 偏度系数
; O4 }9 H8 a9 S+ Z1 J1 ]( V2 TCoefficient of variation, 变异系数
1 i% ?, D+ ?7 A4 W R+ oCohort study, 队列研究
; B0 ^3 X3 g, Q/ zColumn, 列
* A% ~- g& F' rColumn effect, 列效应
5 @) ?$ Q, r) q, c1 D' EColumn factor, 列因素
- h$ t3 ~' y6 JCombination pool, 合并
( j7 R/ e! h v, iCombinative table, 组合表
3 v9 H; L G4 a6 p, o- h7 LCommon factor, 共性因子
% T7 N9 Y# Z8 x( ECommon regression coefficient, 公共回归系数9 l. l2 A* I+ ^5 @# z
Common value, 共同值
$ t5 l) E3 l' |+ J; L LCommon variance, 公共方差8 B q6 e9 {, V6 ~ a! r6 g& l
Common variation, 公共变异* Y2 `; D2 f! m; |& ?
Communality variance, 共性方差
6 d0 Q# b' M7 H$ t8 BComparability, 可比性5 n/ j* ^: h" z% Q5 S# ?6 O# Q
Comparison of bathes, 批比较! \3 l; Z* w, z3 k& a- |& n8 Z
Comparison value, 比较值
6 o% P1 } t0 R6 o1 T: rCompartment model, 分部模型! t0 `/ E( F: f. a' X6 u0 m
Compassion, 伸缩 Q' E% x% b- ^' P
Complement of an event, 补事件
& x; \ C8 \4 [( d$ e# @5 zComplete association, 完全正相关# d3 j2 o# k5 a8 [4 S! V T
Complete dissociation, 完全不相关
+ ^, L/ F1 K( Q5 ZComplete statistics, 完备统计量
- l$ C _- I5 _Completely randomized design, 完全随机化设计
7 s5 e* Q0 ]$ o( o) RComposite event, 联合事件
. T' R3 F" x* OComposite events, 复合事件$ X2 |+ F1 e' a0 ]
Concavity, 凹性
9 ~7 `! G& I/ T; k) p' @9 l4 a! C8 @Conditional expectation, 条件期望9 k- }3 G6 W; y' h. `) _3 F _3 _
Conditional likelihood, 条件似然
) `+ x2 i$ g: Y1 b8 b( ], `Conditional probability, 条件概率
) O9 u! Q8 G2 Z( \! TConditionally linear, 依条件线性) W4 p. {" R9 z% D5 x
Confidence interval, 置信区间
: ?! N5 R" F' HConfidence limit, 置信限
) t: F8 v$ i- A* LConfidence lower limit, 置信下限
- B1 O- U# m. J! a7 A1 \9 {Confidence upper limit, 置信上限2 h; s+ G2 B# e0 Z
Confirmatory Factor Analysis , 验证性因子分析# W5 N9 O" E3 y8 `+ X5 B
Confirmatory research, 证实性实验研究2 e- \- B; _8 r: t6 n/ q- ^6 H
Confounding factor, 混杂因素" t5 I9 B4 \) F4 \4 Z U
Conjoint, 联合分析8 `" K* p! s& @+ O; ^
Consistency, 相合性* H' G4 e F2 p8 W
Consistency check, 一致性检验
S: U \2 y0 T2 p& \( m6 nConsistent asymptotically normal estimate, 相合渐近正态估计
* ^8 ?4 p3 {. H" A9 j) fConsistent estimate, 相合估计9 \* t) u" C! s) a/ P! i0 Q. S
Constrained nonlinear regression, 受约束非线性回归- n3 E1 H3 ~1 b7 ?& u0 f
Constraint, 约束
! S! v, I3 |! c, S9 o5 yContaminated distribution, 污染分布
+ C& k0 Q- {$ }6 HContaminated Gausssian, 污染高斯分布) i( a( |. Q) b( A5 F% v( _
Contaminated normal distribution, 污染正态分布( S' {! j" `% I+ q' h3 {8 s$ l
Contamination, 污染
4 t6 X6 X# J4 P) u% b1 T- PContamination model, 污染模型; V# L& r3 X5 ?
Contingency table, 列联表8 Z2 ]- Z) h; }* A1 I4 p9 Z
Contour, 边界线
5 `) _* Q8 E( \& x/ DContribution rate, 贡献率
! Y. x3 ]* }+ ]Control, 对照: h2 _3 U: H" x2 K
Controlled experiments, 对照实验: X# ?$ Q C/ p' \; {8 ?
Conventional depth, 常规深度1 F! V& l7 l6 }
Convolution, 卷积7 L" k* @. H: Z
Corrected factor, 校正因子: j0 o5 `0 G' h C6 u' ^
Corrected mean, 校正均值# a$ X1 D4 @0 i4 l% g* `) N
Correction coefficient, 校正系数
7 \6 ]$ S/ L6 [/ ]/ W) o7 P. {Correctness, 正确性# Q' L _6 i- z! Y
Correlation coefficient, 相关系数* x6 ~6 f/ }, s& }+ i! d# J
Correlation index, 相关指数 o u/ Y$ F: q: W3 l+ {# n+ g
Correspondence, 对应* Z$ J5 n+ C; E. s8 `! s6 ]
Counting, 计数
. W9 i9 `+ w5 l7 K' q; e5 b& [: xCounts, 计数/频数
3 n, r0 a$ S# T8 Y. l R- u1 \Covariance, 协方差
0 ]: H1 e8 M7 mCovariant, 共变
& S$ P+ b; V' [' MCox Regression, Cox回归8 g' J+ e6 c: o3 g5 `' N
Criteria for fitting, 拟合准则
% C5 q _8 b5 o O, FCriteria of least squares, 最小二乘准则" Z6 D- Y% P3 E% D) d1 e9 Q
Critical ratio, 临界比
# ~* y$ @7 ^' G3 c6 {2 Q) gCritical region, 拒绝域
/ _7 K% O6 F0 g, [# eCritical value, 临界值
% z6 X2 H5 Y3 N+ x |Cross-over design, 交叉设计
& q5 l( \) r$ X9 { t2 x5 B( o- ^Cross-section analysis, 横断面分析
- R& x, a4 t" A9 {Cross-section survey, 横断面调查
' V2 D: S8 V0 ~4 a" S; S/ lCrosstabs , 交叉表 " n# _& _7 [$ N: G
Cross-tabulation table, 复合表1 _3 W+ t1 r& m/ R/ s4 U: W
Cube root, 立方根* E7 _# w% k7 B) B& ^& z4 |
Cumulative distribution function, 分布函数
. O' p+ v2 r9 R" vCumulative probability, 累计概率
* h2 L# X2 r9 w7 [8 K$ Q! BCurvature, 曲率/弯曲
. {2 ^, I z+ a: z( M; ACurvature, 曲率
$ i! Z4 T% y, G7 \1 ~& a$ SCurve fit , 曲线拟和
- K4 w( V; c6 x, vCurve fitting, 曲线拟合
2 x3 _# f- O+ e# T6 D" s1 q* B8 ?Curvilinear regression, 曲线回归
' t; o* S5 a' ^# U; f5 y- m( `6 ~Curvilinear relation, 曲线关系
. a' o" u1 b O9 O$ x. }Cut-and-try method, 尝试法
1 P5 V, u) J/ @& @2 H; Q! pCycle, 周期4 ^/ n* H6 ]# {$ r4 C( ~) I
Cyclist, 周期性1 U% r8 }5 x' H4 E9 e, h
D test, D检验2 @, T; S3 T' Y+ c0 L9 A
Data acquisition, 资料收集3 M! ]" P3 X/ A( p0 S
Data bank, 数据库
; p& t+ m: ^. C0 f3 ~5 lData capacity, 数据容量
; N) R* l8 T9 s2 Z2 |Data deficiencies, 数据缺乏
2 E6 h1 U* i1 U' A! D; |Data handling, 数据处理
3 {- r4 G* q8 |4 p2 W) s" E I, sData manipulation, 数据处理
8 K2 {( o% X+ F4 B) W1 kData processing, 数据处理
8 K! t U/ @/ o( \0 t: uData reduction, 数据缩减
) p; s. ^+ Q' P, ~1 dData set, 数据集- l P' ?7 V4 s4 k
Data sources, 数据来源3 J( G% Z" h m% n# Q# R/ n
Data transformation, 数据变换" H4 Y5 C! Z1 Z; {5 G0 i5 |
Data validity, 数据有效性
- d5 ^$ t& w8 ~9 j j9 }Data-in, 数据输入6 i$ s/ ~4 |/ P2 q1 `3 ~
Data-out, 数据输出
8 E; E) j8 t4 G4 EDead time, 停滞期
. n: W3 G, c. h" u) gDegree of freedom, 自由度& o: ?$ R$ ~& [( v% f" B' L
Degree of precision, 精密度
+ {! W/ o4 k4 U0 z! G( SDegree of reliability, 可靠性程度+ P, _8 V1 v; h
Degression, 递减
) I' A- }3 b+ E k& o9 L: @Density function, 密度函数
! h) s8 H+ K$ I& B |, f5 xDensity of data points, 数据点的密度# P. E u/ i( e0 `' q; t
Dependent variable, 应变量/依变量/因变量
+ c9 x- f0 q; V& e$ j% h9 a% TDependent variable, 因变量
: I) @+ ]/ l; c& t. J* C7 n5 aDepth, 深度$ }* U; M5 ~: W$ S! N
Derivative matrix, 导数矩阵$ s- G% u8 i, U2 A* `5 ?% z
Derivative-free methods, 无导数方法3 ~% T& b9 m& p
Design, 设计 r! B5 t7 h- B
Determinacy, 确定性) X" y" W- o2 i9 M4 U" s3 G4 V$ c _! c* O
Determinant, 行列式
; Z$ S( t9 N! |" cDeterminant, 决定因素6 c. B4 r. R/ A6 v( i0 t
Deviation, 离差/ j# z- h9 x3 a A* I. m- X7 S
Deviation from average, 离均差
3 e# U! p# U! L) W, R: UDiagnostic plot, 诊断图4 G. w4 j. c% j; F+ E8 N* e% v
Dichotomous variable, 二分变量
; ]6 ^3 R, g: s1 x6 @4 L5 F* mDifferential equation, 微分方程! `+ l8 \" w) }5 o8 B6 M
Direct standardization, 直接标准化法
* ]$ f' P+ C4 z: O9 b A' f1 W+ ?2 FDiscrete variable, 离散型变量9 \" a( L4 j& L' y& u9 ?$ E. E
DISCRIMINANT, 判断 8 L& j4 ~6 S8 [4 ? B, T
Discriminant analysis, 判别分析
4 r# j- ]: D% p( bDiscriminant coefficient, 判别系数. S/ O* Q5 v7 d) E4 ~" m
Discriminant function, 判别值
$ S5 R) M% r( Q+ [- NDispersion, 散布/分散度9 c. S' g7 d3 i! A$ X2 n
Disproportional, 不成比例的+ ^- Z% }) ~! r9 J, k
Disproportionate sub-class numbers, 不成比例次级组含量
9 d, Q0 {, Q( U* Z2 `/ X6 ?1 A }Distribution free, 分布无关性/免分布
* L- K$ Y7 T6 c, r6 ZDistribution shape, 分布形状- F9 ^2 U( N$ z+ S' L
Distribution-free method, 任意分布法0 p) m- Q7 \! f
Distributive laws, 分配律
1 c' S2 i! \1 W$ F+ cDisturbance, 随机扰动项9 u% i: N( ?0 l4 [1 M
Dose response curve, 剂量反应曲线& c2 }/ a; }2 M+ r- C* ^
Double blind method, 双盲法 _6 X5 `. J) I. @0 {$ b* o4 g) t
Double blind trial, 双盲试验- ~2 s2 g) W' D
Double exponential distribution, 双指数分布
7 }/ R: P0 |! Z i6 A# ?7 KDouble logarithmic, 双对数
0 b( P% h# u) R% W* L0 _Downward rank, 降秩1 {! K# P" `! X3 n, j! c7 f7 C
Dual-space plot, 对偶空间图$ d& r: n2 {0 G2 ^9 P+ i8 r' N& x
DUD, 无导数方法
2 s4 x7 c" ~* i2 }6 _ aDuncan's new multiple range method, 新复极差法/Duncan新法) `( ~5 @ R0 O' _. A5 e
Effect, 实验效应
& F9 |8 S3 T0 o1 w9 gEigenvalue, 特征值3 z8 ^+ c9 p6 O/ _; p1 R
Eigenvector, 特征向量5 F, t6 ]9 e# y( b
Ellipse, 椭圆
% Q8 `& [8 r9 _: r% Y1 i# Z4 t# lEmpirical distribution, 经验分布
. n4 r8 P! [) |4 T3 j' `; QEmpirical probability, 经验概率单位
* ?% }+ |% b3 uEnumeration data, 计数资料$ r4 ^2 \% G B
Equal sun-class number, 相等次级组含量* |' V/ c" s" m& L0 j
Equally likely, 等可能
3 m0 ?- c4 w7 T8 cEquivariance, 同变性4 T+ R6 U/ ?; f" s) m9 B
Error, 误差/错误5 F. C' Q* w% q) V
Error of estimate, 估计误差
; o# t: M& p( [Error type I, 第一类错误
! ]/ I, Q0 H9 [Error type II, 第二类错误+ Z* V1 _& h' T, s
Estimand, 被估量
" i+ Y7 ?) r) K- a" w, X' A$ gEstimated error mean squares, 估计误差均方6 L x2 _( [ A
Estimated error sum of squares, 估计误差平方和1 U8 o* q+ u& W7 S$ ~* X" Q, Y2 Q
Euclidean distance, 欧式距离- ~# x+ b" N; \6 `/ L- z- _
Event, 事件3 ^2 X9 c9 k' G; `, Y
Event, 事件 U. `( S2 ]. i! g
Exceptional data point, 异常数据点
) m8 o% C) W. s5 B: {4 w; l- o nExpectation plane, 期望平面# A+ C' K4 c2 } v
Expectation surface, 期望曲面
6 {, w6 H& i% u8 \9 m7 qExpected values, 期望值4 T" e7 p8 d% k) |9 K; N9 w; V5 r
Experiment, 实验0 ~% N3 e4 G# F1 F1 t# c! w8 v
Experimental sampling, 试验抽样
) H7 Q/ Q6 p7 U! m/ Z" ]Experimental unit, 试验单位
" r: _8 |9 L* z$ X; l, P, gExplanatory variable, 说明变量& p8 }3 s. ]2 J2 G4 h2 J9 V& ]
Exploratory data analysis, 探索性数据分析1 _: Z2 o$ N* S4 s1 k
Explore Summarize, 探索-摘要
5 D7 M# b8 |) f1 A' h) n2 ^; z2 bExponential curve, 指数曲线8 R4 {0 I+ B4 b4 D
Exponential growth, 指数式增长
+ M3 }# E, T$ x* \" S9 iEXSMOOTH, 指数平滑方法
7 p+ i) x0 q6 {- H! Z+ [- iExtended fit, 扩充拟合
- X+ c$ } g1 V8 X9 r! y, F& K) t, }! BExtra parameter, 附加参数$ A. y8 W9 l0 q$ f* d _ O$ i
Extrapolation, 外推法
6 z4 m# S0 \2 `% vExtreme observation, 末端观测值. h3 c$ A+ L1 K/ E0 r* o& S: d% T' q
Extremes, 极端值/极值
5 Q7 m3 G. n8 c% m% V% R# aF distribution, F分布
* X! _1 F+ ~7 u7 b+ \F test, F检验' o' X% ?/ v+ U5 B; U2 }2 O9 }& t. j: h
Factor, 因素/因子
, \5 j$ |+ [$ ~/ oFactor analysis, 因子分析
D* p W6 v. k) TFactor Analysis, 因子分析
4 n4 v, z0 ]+ t6 vFactor score, 因子得分 & [8 f- G9 e$ O7 l# s. Q& r/ ~, K
Factorial, 阶乘3 j; A) G# t" U( w1 |! X- c. z" E
Factorial design, 析因试验设计
' f& [+ V" X" S3 CFalse negative, 假阴性3 \7 E, H7 c$ L9 I
False negative error, 假阴性错误8 Q; ?. f9 `! v5 G
Family of distributions, 分布族( f$ \# {4 Q& S+ u$ {/ |7 @
Family of estimators, 估计量族# A2 y1 O- E+ \% R
Fanning, 扇面/ a( ^( y0 n1 T
Fatality rate, 病死率
/ M- u8 z+ X' h hField investigation, 现场调查8 z( [' l9 ~$ i: y$ G
Field survey, 现场调查+ t( i* h7 ?1 I# g0 w. D
Finite population, 有限总体
. O2 q3 T/ T8 B$ r! eFinite-sample, 有限样本) ~* D. Z3 n o" p8 M. k
First derivative, 一阶导数
8 ]) h2 e: O' r( E3 ]& @First principal component, 第一主成分2 e0 s: i8 S9 V3 @; E' S
First quartile, 第一四分位数9 n! w# T+ z8 H
Fisher information, 费雪信息量% K1 w% H- `' q9 y
Fitted value, 拟合值: c- w9 @( K4 k5 j
Fitting a curve, 曲线拟合- ^+ V/ C4 U. V0 p$ q2 y- M
Fixed base, 定基; B2 l- A( I& S9 b# w
Fluctuation, 随机起伏; K" c/ _, O" o/ `% @5 i; w1 R2 q
Forecast, 预测
x f" y; J; qFour fold table, 四格表
: [' b- X9 A! I# Z# @3 qFourth, 四分点4 a& ^! b7 b) t% y
Fraction blow, 左侧比率/ P6 F- E* i! E: F0 h
Fractional error, 相对误差+ m( D2 p! c: I
Frequency, 频率& e3 j: U( X/ c
Frequency polygon, 频数多边图
; O3 G2 r2 R/ ^# {5 IFrontier point, 界限点9 A- u& P3 q9 o; b$ k
Function relationship, 泛函关系& O( i2 K( p. a+ i& g
Gamma distribution, 伽玛分布
" p% V. m2 p9 p6 n7 q# R ]6 ]Gauss increment, 高斯增量
# N/ H+ s" o/ ?. [Gaussian distribution, 高斯分布/正态分布
, q/ y* g; H. X) m( S+ n# DGauss-Newton increment, 高斯-牛顿增量
- d( m, C T) w: O' g/ h% YGeneral census, 全面普查- S9 w+ N: t3 \7 U0 g; l6 N8 F
GENLOG (Generalized liner models), 广义线性模型 , a* F; I h$ ^3 d& T% r1 J* p/ I
Geometric mean, 几何平均数6 Q, `$ c' E4 K) `5 P' p7 {- B
Gini's mean difference, 基尼均差" S6 J: F9 M! ~8 m- I
GLM (General liner models), 一般线性模型 ( s% T, V. P) \7 l% N7 S2 Y1 y2 n
Goodness of fit, 拟和优度/配合度
1 [5 E/ m0 C) E. q9 jGradient of determinant, 行列式的梯度" z% g) y( x. {; H2 J/ f0 G
Graeco-Latin square, 希腊拉丁方
# E7 a% h: ^- v! _6 g0 EGrand mean, 总均值
: h0 K: v1 T; n( r& ~ XGross errors, 重大错误: c, H4 x8 s! Y! i4 q0 y2 c. u! @9 |
Gross-error sensitivity, 大错敏感度
! A' ^. v, I8 X% w4 nGroup averages, 分组平均: x% r* g- t1 D6 T2 H. y
Grouped data, 分组资料
* B! r- J. `$ @8 FGuessed mean, 假定平均数
. `# P$ u. X0 {% U2 [+ f ^Half-life, 半衰期) ?4 w- W; @( y) E
Hampel M-estimators, 汉佩尔M估计量
+ |3 ?$ ^/ C" _( W- ~/ u0 N1 ]5 xHappenstance, 偶然事件$ c& ~6 K7 t) E$ D6 ^. x
Harmonic mean, 调和均数
2 O, N( r2 H' u& n1 [9 Q+ eHazard function, 风险均数
" [$ u& `/ J* f3 H2 K1 jHazard rate, 风险率
" E& e* e3 H" O E& MHeading, 标目 : h6 R, o2 \% u& {! U6 }0 ]% u
Heavy-tailed distribution, 重尾分布
/ a, L0 B6 _) y. Q1 j# B' lHessian array, 海森立体阵
& T, b1 c0 ]& _ c; LHeterogeneity, 不同质) |' A1 X7 n9 T" [, i7 q- _
Heterogeneity of variance, 方差不齐 " F% ^) L" s: q
Hierarchical classification, 组内分组
( y; O1 [0 b- C9 \8 b9 WHierarchical clustering method, 系统聚类法
) T" _5 |! ^( |High-leverage point, 高杠杆率点
- m) ]8 n; B R: mHILOGLINEAR, 多维列联表的层次对数线性模型4 V, B- ~$ K G
Hinge, 折叶点
+ s- s R$ p% Q4 L h$ Q% AHistogram, 直方图
1 I( q. u3 C3 xHistorical cohort study, 历史性队列研究
6 M% y7 b) @* w3 {6 Q, xHoles, 空洞
% U. {, y( d& w% }4 DHOMALS, 多重响应分析
1 B* Q: m- O8 r' b- zHomogeneity of variance, 方差齐性 j& A$ Y: `, P# c/ a) \& D0 n4 [9 \5 V
Homogeneity test, 齐性检验
% @8 W$ Z0 f; X. S' h2 m% hHuber M-estimators, 休伯M估计量# O3 c6 r) z) u/ m
Hyperbola, 双曲线
$ F; I: ]1 T* U" [0 xHypothesis testing, 假设检验
, \# H; f, a; D% r/ u+ XHypothetical universe, 假设总体+ d8 k5 a. F% }6 J& m1 @
Impossible event, 不可能事件
( o% N$ o; w" Y9 {& H$ c( mIndependence, 独立性9 ~5 E9 p; S; ?: \$ o5 T% Z3 {
Independent variable, 自变量6 W/ B1 p4 a; T3 u& `( S
Index, 指标/指数8 K7 l! \' x, Q6 e& t
Indirect standardization, 间接标准化法 h# H; x1 r7 c
Individual, 个体
1 d; m6 a4 M7 U- m' }Inference band, 推断带( K( }& U7 [' L3 z
Infinite population, 无限总体
% i# i) B3 C( u8 f/ x/ BInfinitely great, 无穷大 A3 l3 q; | A) I
Infinitely small, 无穷小
) m e3 Q; s) N* HInfluence curve, 影响曲线
5 d4 g0 |- K; ]+ N# `Information capacity, 信息容量
0 O) t4 n& b$ W# @8 MInitial condition, 初始条件, N4 v. U9 q: M }" ?' s/ @
Initial estimate, 初始估计值
; v1 O+ e0 ?) I' mInitial level, 最初水平
i0 f9 ]0 n- P) ]% ]Interaction, 交互作用9 ]9 P/ q( V* t9 a* }) J% Q
Interaction terms, 交互作用项6 h0 O2 G" T/ h" K# C
Intercept, 截距
) {% X" `+ b2 ]4 e6 ^* |5 KInterpolation, 内插法
7 e& f8 Z% _/ A% w DInterquartile range, 四分位距# t, Q( v& m- t* R8 R7 v
Interval estimation, 区间估计
7 @+ k3 Y, ]" `6 f$ u" DIntervals of equal probability, 等概率区间
5 o2 R7 _# F3 W2 z6 yIntrinsic curvature, 固有曲率
6 i$ s; d6 x+ r( q) H% T1 e' p3 B" GInvariance, 不变性$ o9 ^* i" M/ f2 I+ S
Inverse matrix, 逆矩阵% t, I. U1 F4 O" L# l/ M8 [0 B' a
Inverse probability, 逆概率
( a! ?" Q$ N/ i; c" R( ZInverse sine transformation, 反正弦变换! n$ U' f1 v6 }
Iteration, 迭代
0 _3 e, h6 F+ v8 S' T" hJacobian determinant, 雅可比行列式
6 B; R& N7 C- Q( B- FJoint distribution function, 分布函数7 N. G$ K# r( _+ c) I& Q9 J" ?
Joint probability, 联合概率6 q2 J( q1 ]) H/ ^
Joint probability distribution, 联合概率分布
5 B% Z1 _1 T, w) h. k% x& x3 {5 ZK means method, 逐步聚类法( y& R" |1 s7 A1 L
Kaplan-Meier, 评估事件的时间长度 0 F# i2 M% h" T7 _# F' p0 ]
Kaplan-Merier chart, Kaplan-Merier图
. Z6 m4 q2 i8 H$ jKendall's rank correlation, Kendall等级相关6 p$ ]+ Q$ w: ~
Kinetic, 动力学
o6 \0 Y2 q% A0 L- p" ]) w3 L- oKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验% q5 b7 m! n: B" O5 S7 b
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验# b- b0 `( I2 L" z0 X9 W
Kurtosis, 峰度( \+ y4 h9 {) b8 S" \/ }0 q% p
Lack of fit, 失拟) p# ~ m' r" U% u
Ladder of powers, 幂阶梯
C: g3 f8 ?, s* P% u0 i0 ELag, 滞后
; X( N; `1 ^8 [% K3 ]6 qLarge sample, 大样本- Q$ ^% R6 L/ L
Large sample test, 大样本检验
6 t1 C* ]' c: H& T+ RLatin square, 拉丁方
% N, K/ `: d# ~% s g5 D; NLatin square design, 拉丁方设计
' B- s. V4 p. q6 ~7 G3 d' _Leakage, 泄漏
8 g) v4 a* R) ^+ C7 h9 Q" z4 {Least favorable configuration, 最不利构形
) V4 ?2 L. d( p5 oLeast favorable distribution, 最不利分布5 O8 J8 d! c ~/ X
Least significant difference, 最小显著差法
0 P: _' t) Z! }3 Y. m7 Q2 r% P$ [Least square method, 最小二乘法
/ p& U- U: h* ~3 O! h$ e! ELeast-absolute-residuals estimates, 最小绝对残差估计" S. |6 v2 b# f8 d, a
Least-absolute-residuals fit, 最小绝对残差拟合
: [1 l+ [0 u7 ~ r5 l2 [Least-absolute-residuals line, 最小绝对残差线4 Y5 A X8 l7 p
Legend, 图例( |( K, [' _/ }( X6 R8 `; r" Y- C7 [
L-estimator, L估计量( |0 d4 s2 c$ g, T( E
L-estimator of location, 位置L估计量
2 A* ^" B( ^( v6 rL-estimator of scale, 尺度L估计量) o$ W8 c# U5 w: d3 g. M
Level, 水平* M, G: E. o" O: b9 I
Life expectance, 预期期望寿命
5 p, x2 D: s) l7 mLife table, 寿命表4 T1 p7 H" ~7 y* _& O9 R, o6 R+ E% x! @
Life table method, 生命表法; k5 d0 U8 M: K: m0 i
Light-tailed distribution, 轻尾分布) Q# U( L; w2 @% L$ {8 k' }
Likelihood function, 似然函数
7 |# T$ {9 }2 ^* CLikelihood ratio, 似然比# H+ R" O; ?7 a) E* r0 }# |
line graph, 线图6 y1 _, m8 N: Y7 {) I
Linear correlation, 直线相关
) o' Y( c0 N: |1 R7 Z' zLinear equation, 线性方程; @/ x: x0 q( _) Y% {& {
Linear programming, 线性规划
$ a5 _6 D: A7 L; W+ `8 G$ x/ d1 LLinear regression, 直线回归% b4 }2 C/ I6 f7 f: R6 t* I7 y7 M
Linear Regression, 线性回归$ H3 U) P' D/ @2 ~! P6 e
Linear trend, 线性趋势) B9 z7 x- P! W7 K
Loading, 载荷 2 F. z, I' N. B; G! `
Location and scale equivariance, 位置尺度同变性
+ m5 n# t) V/ ]: x- N: CLocation equivariance, 位置同变性
6 b8 d/ Z/ \2 k8 ELocation invariance, 位置不变性% r5 D, k- z/ Z" X0 q4 \8 |
Location scale family, 位置尺度族: F/ G0 r% m" W
Log rank test, 时序检验 ! [6 a# | O- z
Logarithmic curve, 对数曲线
" o( X; Q) S6 @) C' v: uLogarithmic normal distribution, 对数正态分布9 }& p1 |+ `% D: b) W
Logarithmic scale, 对数尺度
8 z2 ^9 ~0 e. @8 Q' g5 J: |' t/ tLogarithmic transformation, 对数变换
5 f; Z Q! T& H+ i; FLogic check, 逻辑检查# C; F& V, Y" @% D: [7 E5 K
Logistic distribution, 逻辑斯特分布
5 @) b# t/ y5 F. PLogit transformation, Logit转换% D. `% e3 T5 u9 _1 T. P
LOGLINEAR, 多维列联表通用模型
' |& R' d9 Y& {0 zLognormal distribution, 对数正态分布
0 H! m: [4 a3 c' @ LLost function, 损失函数! p6 C4 Q5 b( e. ?, [0 I5 U l- N3 I. v
Low correlation, 低度相关
+ T3 |- V9 {2 s- c" A$ c. ALower limit, 下限
' _, p3 R7 e9 x4 U4 K; CLowest-attained variance, 最小可达方差2 H8 _: M) P2 L3 G
LSD, 最小显著差法的简称+ F; [8 E. x, j, p8 t) U$ w
Lurking variable, 潜在变量
9 d" X; U7 ^# t1 gMain effect, 主效应
`3 M( ^! w! A! P9 e6 t8 ^* UMajor heading, 主辞标目
0 R2 F. [' p$ N$ h9 ]: A& G. {/ AMarginal density function, 边缘密度函数
# b, f x4 C3 e& p5 `: b" o2 {Marginal probability, 边缘概率
* m8 H+ y# }% K1 N2 m% u3 vMarginal probability distribution, 边缘概率分布
2 H/ e6 P# f$ E, G: ?Matched data, 配对资料
6 d% G+ i* k+ ~2 m4 G" r/ j# NMatched distribution, 匹配过分布
i! e# K: G" {% @ x" t8 y0 \/ r0 GMatching of distribution, 分布的匹配# d, I( A5 L$ v8 w
Matching of transformation, 变换的匹配# D3 R* Z8 w/ N3 N
Mathematical expectation, 数学期望
- ?* ?; c( u$ S5 o& U$ g: @Mathematical model, 数学模型; q: g! w/ L- |# I/ u$ p. K
Maximum L-estimator, 极大极小L 估计量7 Z+ L% N1 i! u3 ?7 ~7 ~4 y, }4 M; J5 i
Maximum likelihood method, 最大似然法
- b: M9 ~2 z% K7 w5 N2 r4 n$ V5 EMean, 均数
. k% e z/ S9 k2 V- E5 I1 U' i. mMean squares between groups, 组间均方
3 [( e0 R8 {$ `& }& Y. k( IMean squares within group, 组内均方: }1 |+ C2 p3 T/ }, Z+ A3 \$ X3 j, V
Means (Compare means), 均值-均值比较
5 ^ @5 G- z9 _& l6 i$ VMedian, 中位数
. _ S6 ~3 I$ N0 d( N( GMedian effective dose, 半数效量* d8 ^, Z6 ^0 m% d7 n ~
Median lethal dose, 半数致死量
1 t, m* G! `( h7 cMedian polish, 中位数平滑' |/ A6 i* N8 q" v5 {- g* T, c+ G
Median test, 中位数检验3 o4 k' {; W9 E
Minimal sufficient statistic, 最小充分统计量0 q5 f" M( f1 o/ m! w- f
Minimum distance estimation, 最小距离估计
+ b: e! K& w+ T9 D y) ?5 iMinimum effective dose, 最小有效量2 @6 X6 g! [% z7 Y; p
Minimum lethal dose, 最小致死量
9 o% l# o9 w% G% ?' N3 b9 ?Minimum variance estimator, 最小方差估计量; z% I+ F+ e* A" g, I
MINITAB, 统计软件包
9 x# C7 S* g* Q! ] K' EMinor heading, 宾词标目
# B& j3 R3 v8 x7 [5 EMissing data, 缺失值
) e: U6 O' V) n. q D$ VModel specification, 模型的确定
4 p. q+ h3 m$ ]0 n" `( s8 ?Modeling Statistics , 模型统计
3 C' T3 ~: j: Y# |- NModels for outliers, 离群值模型; {) O9 y% X/ [5 ?
Modifying the model, 模型的修正9 C9 m9 K) f+ _& V) u
Modulus of continuity, 连续性模: J H8 Y1 k I% i5 A; @" |% D& w
Morbidity, 发病率
: r' t9 E5 j: T; t/ xMost favorable configuration, 最有利构形4 _/ u4 r, k8 }4 F
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
% z6 ~, u% |1 a0 i! T, @( e5 ?* JMultinomial Logistic Regression , 多项逻辑斯蒂回归- s( D$ B A* L n. M8 r5 @+ p1 j
Multiple comparison, 多重比较
! @; w4 `2 w6 UMultiple correlation , 复相关& T( x, \; t& n- y& h. W0 A( O
Multiple covariance, 多元协方差
( y; o6 r! S! f6 P- ?4 kMultiple linear regression, 多元线性回归
& a+ k6 H+ l# L N% lMultiple response , 多重选项0 n9 U# n6 U) f
Multiple solutions, 多解
1 c. @( j4 o0 w; D/ K7 [% B: H# N: ?Multiplication theorem, 乘法定理% c5 G3 O4 U9 }/ d
Multiresponse, 多元响应! r/ T# i& x8 B& Q+ G( h
Multi-stage sampling, 多阶段抽样; P( S; T+ m% b u O
Multivariate T distribution, 多元T分布
7 z) A5 ^" K3 V9 tMutual exclusive, 互不相容# s: v8 c: u' Q4 \) L; A( x
Mutual independence, 互相独立8 q% i3 @, N+ z, e9 y1 p5 ~
Natural boundary, 自然边界) O" q( D' h7 {$ R
Natural dead, 自然死亡
5 l# d1 Y! E% z( X5 ONatural zero, 自然零
7 g# Z4 K/ z6 y" _Negative correlation, 负相关% _4 U) ^2 D" f1 h; ^1 }3 A
Negative linear correlation, 负线性相关
4 F9 d6 d" q5 W) j7 yNegatively skewed, 负偏3 U D% J2 t% U
Newman-Keuls method, q检验
" R9 S7 c5 @ m: i# [0 _' WNK method, q检验
" o* d, M9 ]3 c3 Y3 a. JNo statistical significance, 无统计意义
' |9 I# `% R5 M- QNominal variable, 名义变量! A6 z6 q- g- L; I* t8 c
Nonconstancy of variability, 变异的非定常性
2 L$ _; ~) }2 E6 [/ o# a/ t' ]Nonlinear regression, 非线性相关& M7 n- j2 O! a( U4 K% G) h3 d* R
Nonparametric statistics, 非参数统计% v9 h/ s# j, G9 k- ^. z
Nonparametric test, 非参数检验
6 e6 Y- e: s" W3 [& ANonparametric tests, 非参数检验
& ]& `' ]% h6 f' U/ L! gNormal deviate, 正态离差
: o0 T8 Q" T+ x- h$ b4 m3 ^Normal distribution, 正态分布
# Y0 `- l; r) W! ]9 M* c' MNormal equation, 正规方程组
1 A7 v: D% N+ ~& LNormal ranges, 正常范围: P3 R) y0 S% K# h7 C0 B
Normal value, 正常值/ ]1 r+ P# M: o' |3 t
Nuisance parameter, 多余参数/讨厌参数1 S0 G) w, W+ ]* }* ?
Null hypothesis, 无效假设 & t# Y7 [6 W: h" K
Numerical variable, 数值变量
' \* z5 o$ n D9 w- u6 ?: E9 l7 iObjective function, 目标函数/ W" i8 W5 z/ [6 x2 u
Observation unit, 观察单位
, U' M0 y" {* [7 l3 t! WObserved value, 观察值
0 f$ F; s8 [! ?$ q1 t3 GOne sided test, 单侧检验
2 _' n* c2 `# n; d' ^One-way analysis of variance, 单因素方差分析
( H% B5 G& g }6 s6 N- E( JOneway ANOVA , 单因素方差分析
% L$ { r7 A( [7 \( QOpen sequential trial, 开放型序贯设计
" C5 H; y% N8 W! X* ]/ YOptrim, 优切尾
! n: Y" \5 E: M5 D2 {0 ]. H% sOptrim efficiency, 优切尾效率4 s6 R7 ]) J( _9 A8 p- B- W
Order statistics, 顺序统计量
3 L# d/ f4 \+ h7 b8 R% X& AOrdered categories, 有序分类3 u5 |% W# l/ @) [' d7 Z# c+ t0 o \
Ordinal logistic regression , 序数逻辑斯蒂回归
# o) Z! T( ]. r- }1 COrdinal variable, 有序变量
" [9 l9 S1 F( v$ J6 DOrthogonal basis, 正交基
3 `! p: C. X2 V p- m- J# oOrthogonal design, 正交试验设计5 `" n, r3 F7 q* g; q, @
Orthogonality conditions, 正交条件6 I1 F0 X0 H) J( a' x
ORTHOPLAN, 正交设计
2 f7 H/ X) ~7 A( fOutlier cutoffs, 离群值截断点
& e; @' c8 Q% r9 z; yOutliers, 极端值) C1 F0 R; K' D6 b6 T
OVERALS , 多组变量的非线性正规相关
6 k0 }8 c0 l( _Overshoot, 迭代过度
4 f# @) o/ K8 V1 PPaired design, 配对设计
* Q* V% C* U+ j9 zPaired sample, 配对样本 A$ E+ j& H- d, o
Pairwise slopes, 成对斜率
, y6 r0 J2 [2 C) H8 Q7 c/ `Parabola, 抛物线
5 [& Q2 j9 C0 W9 m* u/ e3 h; CParallel tests, 平行试验( X6 ?- k1 \( P5 o; Y7 q; z/ u
Parameter, 参数+ p9 G7 _7 g) }/ w, w, x
Parametric statistics, 参数统计
6 T; _( k w* ~Parametric test, 参数检验3 I" }4 s/ |5 i$ m8 m
Partial correlation, 偏相关& [7 Y! Z% S. [8 z U1 n2 T6 b7 T8 u3 q
Partial regression, 偏回归, H2 v1 J, k7 v- a4 z. V
Partial sorting, 偏排序
& x T* f/ d) n! e2 J( OPartials residuals, 偏残差) S3 `" y2 Q) d1 ]9 Z* \) c2 R' j. l; _
Pattern, 模式; M) q8 a) s* ?: o
Pearson curves, 皮尔逊曲线& _" G: e' A9 `- V3 ~
Peeling, 退层5 c4 j( F! f7 g% A# @1 ]
Percent bar graph, 百分条形图# g( }3 \, m* I
Percentage, 百分比
* I- X9 E* l: v! o2 \Percentile, 百分位数% C! ~+ E- L/ I$ {# b& C1 q7 H
Percentile curves, 百分位曲线% s! k, v0 ~4 n9 h
Periodicity, 周期性
* U. n1 ~1 A' E6 w7 }Permutation, 排列" ] J* l8 l' }; f& j8 X0 G
P-estimator, P估计量
/ R4 C1 z9 k) z {7 z: Y7 A& ^! mPie graph, 饼图7 ^- c" a7 V2 e' }5 |
Pitman estimator, 皮特曼估计量- d( W1 a# H3 }" x1 ]
Pivot, 枢轴量& v" a3 }: g! }
Planar, 平坦
1 [- \9 t& ?! r$ G5 d! Q5 }; `Planar assumption, 平面的假设: W6 V+ v5 F, q. p9 \1 T
PLANCARDS, 生成试验的计划卡
0 M9 z4 [4 ^/ G+ @6 gPoint estimation, 点估计2 [1 m0 ^' G; l# b) m- Q4 L
Poisson distribution, 泊松分布
0 l. ^6 f7 {. QPolishing, 平滑
( U1 L8 @( Q, S' [( }; JPolled standard deviation, 合并标准差
* N g' B8 w% c: E$ g6 fPolled variance, 合并方差
?4 G! Z* l$ Y4 j6 vPolygon, 多边图
/ c% N9 T5 V$ N$ c6 K7 _Polynomial, 多项式
! ]- f/ y! [% Q0 H- X9 ?* r+ UPolynomial curve, 多项式曲线, b5 |5 M( O& [
Population, 总体
& O( Y, p( N4 G1 N( i; FPopulation attributable risk, 人群归因危险度 D5 H e U) j$ W
Positive correlation, 正相关: {! C& b8 r2 t# c) C' e5 e
Positively skewed, 正偏" v+ N3 G/ m" c; z9 W) J
Posterior distribution, 后验分布
) p3 B7 E, f( R4 w: NPower of a test, 检验效能
/ V9 P# J K, [$ Y! }$ N8 NPrecision, 精密度
0 i; o0 p5 s: r4 `4 C( R4 OPredicted value, 预测值
( q; x' W: N7 B- tPreliminary analysis, 预备性分析
- M- p. j, f" hPrincipal component analysis, 主成分分析
5 v) { H6 h; n1 @: hPrior distribution, 先验分布' J3 I* r4 ^! v" e4 g; ~) o( z
Prior probability, 先验概率8 b+ h) S7 \! z3 |
Probabilistic model, 概率模型
, x0 C+ T& a! O) k2 |7 sprobability, 概率* v2 j2 v8 f% K P
Probability density, 概率密度
3 [' O2 e1 t, P6 R& u$ r3 Q6 CProduct moment, 乘积矩/协方差" F2 ~3 L5 v. M! R
Profile trace, 截面迹图5 h3 \( l" d& K
Proportion, 比/构成比
0 b' P1 e d; f7 fProportion allocation in stratified random sampling, 按比例分层随机抽样9 i! P1 N$ [. o$ T7 T$ h1 x! F, {
Proportionate, 成比例' u% U& N. d8 Y8 h6 H9 L
Proportionate sub-class numbers, 成比例次级组含量+ `, `) M$ ~7 k+ X
Prospective study, 前瞻性调查& w# q7 ^. {. z( L
Proximities, 亲近性 , x1 F9 z% t0 e6 M' r% D V
Pseudo F test, 近似F检验
- m; ~8 m/ j( H! i. D8 x5 w4 x6 c+ H9 _( s' }Pseudo model, 近似模型4 e$ |, D6 g0 Q: A2 f" t4 X
Pseudosigma, 伪标准差
" t o; s; ^% i: g. }; N0 ]0 Z3 ~Purposive sampling, 有目的抽样
: P8 p# P5 ?& _. \' w$ `QR decomposition, QR分解- s$ e0 } t. Q( Z+ v! L9 U* m; d
Quadratic approximation, 二次近似
$ Q; m3 [ k5 c1 O% F: GQualitative classification, 属性分类
% @% h- g M/ Z5 w+ aQualitative method, 定性方法6 K( y: o) o% Z6 P' D3 M
Quantile-quantile plot, 分位数-分位数图/Q-Q图
: p* v" X- }: V$ v. `4 MQuantitative analysis, 定量分析3 u" h( K! N- {0 D
Quartile, 四分位数
6 |5 o6 r8 y- J- m7 dQuick Cluster, 快速聚类
0 A/ B# g0 D L; U1 c, U: _Radix sort, 基数排序
1 o r" E& r& V4 Y5 j( \+ ORandom allocation, 随机化分组
, p* ?- Q; p. nRandom blocks design, 随机区组设计* }5 u0 j8 x8 @) k& ?
Random event, 随机事件+ x: v- c- ?% [& |
Randomization, 随机化
+ `0 o! J" x" S; DRange, 极差/全距 r5 U/ q' y8 b: V+ N# [3 Y
Rank correlation, 等级相关6 S% }4 l }) P/ O; ?
Rank sum test, 秩和检验
' \% t6 @, c3 A# p6 J" cRank test, 秩检验& K7 Q% R$ B% n* b+ N# r+ H
Ranked data, 等级资料. v" b! L7 I$ |' r, X) K$ ]4 h# j
Rate, 比率9 y- @6 S3 z8 O7 j* ], `4 V+ a! Y
Ratio, 比例. s3 a) @9 _9 k
Raw data, 原始资料
1 ^1 }7 }$ k% p3 R$ E1 |# l" E. O: b, PRaw residual, 原始残差3 c7 L6 b+ f& ^8 g: ~' E
Rayleigh's test, 雷氏检验
, R' P" |5 v* f( ?Rayleigh's Z, 雷氏Z值
; \3 e7 X7 L" P& `) g# t6 m4 C9 hReciprocal, 倒数, F/ e1 ] q/ A" A1 |
Reciprocal transformation, 倒数变换
5 K6 S8 c# F/ S6 A, {( y' lRecording, 记录
! L' u5 n* t# x0 mRedescending estimators, 回降估计量
# M( T* \ e) }' fReducing dimensions, 降维
& Z _0 G$ j9 U' T$ CRe-expression, 重新表达/ Y, X: X" Z3 M! ~+ g, E
Reference set, 标准组" N5 L# l" s( w2 A1 e
Region of acceptance, 接受域8 f* d. Q) i' {) {
Regression coefficient, 回归系数) S( {6 ^: G+ z2 k
Regression sum of square, 回归平方和4 A5 A, S% s. E6 _7 t
Rejection point, 拒绝点/ v/ F* U$ }5 f8 {
Relative dispersion, 相对离散度% C$ L4 H; j5 b7 Q' H
Relative number, 相对数. n7 Q, N0 A" l' v5 i
Reliability, 可靠性
' b; D* R6 N, b, }Reparametrization, 重新设置参数
1 p4 Y: Q, t+ o# t% v9 ]Replication, 重复& ~; {! f9 I- |1 p0 |" Q
Report Summaries, 报告摘要! {; j' ]3 l( m
Residual sum of square, 剩余平方和) V3 J6 V" B. g; q* ]6 _
Resistance, 耐抗性
; f( n( R# v+ a2 A" {# W- `Resistant line, 耐抗线
6 K# n: U& D- V' B1 H0 p! WResistant technique, 耐抗技术 S0 u2 X& F# x) E( b% K! \6 b
R-estimator of location, 位置R估计量
2 S* A+ ~ O! d+ o7 r& K; GR-estimator of scale, 尺度R估计量
& D/ K, M8 }& D% w6 L+ i1 [6 O2 PRetrospective study, 回顾性调查% ^* a8 E* o) X2 K- N" a3 [& _
Ridge trace, 岭迹
0 r+ {6 M4 t& t6 j NRidit analysis, Ridit分析3 A V. K' W* M$ T q+ o! _
Rotation, 旋转0 q" R/ R# Z/ ?+ e* R
Rounding, 舍入
5 G4 h1 J5 z% O/ j& [" w O3 H. HRow, 行
$ n2 T; i* D& w9 G3 QRow effects, 行效应
( s8 E7 [1 ^ b" D$ Z. T- [1 l& ~Row factor, 行因素
# \) ?: Q$ O" uRXC table, RXC表% }2 n. j$ m- _ Q, U& N% ?
Sample, 样本
/ [* |/ c6 e% f6 o) A- k' |1 ]Sample regression coefficient, 样本回归系数- D4 Y: i" H7 e8 N2 ~$ c- z
Sample size, 样本量
2 ^! V) w' \8 E: nSample standard deviation, 样本标准差4 ^; ~' C3 k, e4 M$ F
Sampling error, 抽样误差. y1 \& w) H7 m$ {
SAS(Statistical analysis system ), SAS统计软件包 P. T' V& s8 }! C- x
Scale, 尺度/量表
3 Z: d6 B2 J% b& m( i( U0 ]Scatter diagram, 散点图
) Q- B2 i+ y: j+ m- HSchematic plot, 示意图/简图/ |/ p& H" J4 i3 q
Score test, 计分检验 O& f# ^: V% h% j( q
Screening, 筛检
/ Q9 d3 U; R9 c0 `: g$ _; U GSEASON, 季节分析 ) N( v8 T L1 A0 e6 V% P; A# S5 y
Second derivative, 二阶导数! g+ S3 r$ ~' h3 G
Second principal component, 第二主成分' J2 t" o6 x5 J$ q, x1 E
SEM (Structural equation modeling), 结构化方程模型
7 I( E. C d/ \0 I) w% \6 YSemi-logarithmic graph, 半对数图
9 z; C; T4 u6 V7 M0 H: i7 K9 [9 BSemi-logarithmic paper, 半对数格纸
+ @2 o f' j; t+ \& w$ b$ wSensitivity curve, 敏感度曲线# H( W1 j. {* y$ O! h9 [- l- l
Sequential analysis, 贯序分析9 Z) [: D5 x# @, E2 n H4 H( [
Sequential data set, 顺序数据集
1 a6 L2 G- f, }5 wSequential design, 贯序设计
; D) b0 \& b9 ]6 S" bSequential method, 贯序法. V" O5 {# {" T5 I
Sequential test, 贯序检验法# l/ j9 J# x- ]
Serial tests, 系列试验
7 R9 u. I3 O: YShort-cut method, 简捷法
3 k+ |) o+ _. ?. {1 ^7 s3 DSigmoid curve, S形曲线
, M' m. X+ {, z. W$ W- ]Sign function, 正负号函数5 [8 D" x0 y2 G
Sign test, 符号检验
! l' E; Z! y% M+ T7 }5 ^5 aSigned rank, 符号秩$ E. }8 Z+ ]: U" l
Significance test, 显著性检验0 W- b; {$ m; Z+ W& l% G2 V
Significant figure, 有效数字4 E6 |4 m( c: I! w3 b& e
Simple cluster sampling, 简单整群抽样
0 v8 \, g. O+ xSimple correlation, 简单相关
( ?; ~" m) O3 Y7 e# x( oSimple random sampling, 简单随机抽样( @: a6 z; V. n* P% b: u7 y
Simple regression, 简单回归; {$ z. D+ o- L0 s$ J! e. k& f
simple table, 简单表
! M. h8 [0 x7 b" n# v. ZSine estimator, 正弦估计量
' x2 e$ I( G, \: D8 w2 l. q5 GSingle-valued estimate, 单值估计, T" `% U5 @0 ~% M
Singular matrix, 奇异矩阵: N+ u! A0 W3 Z% q1 ^
Skewed distribution, 偏斜分布9 _, K/ g/ Y; Z) p2 n
Skewness, 偏度 A: H% `1 c0 D$ k; w0 Z
Slash distribution, 斜线分布9 @! w, l) }! N) Z' n' S: P
Slope, 斜率
9 h# v) p9 d# J- p: WSmirnov test, 斯米尔诺夫检验
7 c. U9 i/ O! S3 j; \. ~0 Z& XSource of variation, 变异来源
( ^" r& k$ z" j8 `, VSpearman rank correlation, 斯皮尔曼等级相关0 _; g& |1 |4 f$ {0 O" Y# C
Specific factor, 特殊因子, B, s* r i/ S$ V g% B
Specific factor variance, 特殊因子方差
/ X d: B3 k0 w9 `1 jSpectra , 频谱
! k6 m+ r5 Q/ O. z: CSpherical distribution, 球型正态分布1 D U% |; ^) w/ M
Spread, 展布7 ]2 p, g# P4 G* F4 K7 p7 Q- x
SPSS(Statistical package for the social science), SPSS统计软件包
2 h' o0 }& s% d6 a9 }$ m6 C( h$ ISpurious correlation, 假性相关8 p' d' }) o/ {2 U
Square root transformation, 平方根变换6 r( O: Z; p$ Z) f" Q$ T" Z# v
Stabilizing variance, 稳定方差
& _5 P6 n! ]1 m, sStandard deviation, 标准差* i4 A$ z3 b5 ` G% l( [* a1 \6 e
Standard error, 标准误! k; A& w$ t& O9 ]
Standard error of difference, 差别的标准误
( Z6 S) F: t4 hStandard error of estimate, 标准估计误差# F) X* m8 s2 s: H* L: {
Standard error of rate, 率的标准误# _6 L6 T! q2 N) n: @! Q
Standard normal distribution, 标准正态分布) _2 h( W# N* d8 ]) c
Standardization, 标准化
1 \. x: l4 R4 Q! o# W1 gStarting value, 起始值
" G8 r! g$ R$ Z3 Q, ~7 ~+ a! eStatistic, 统计量! ^2 Z% U8 f/ k, t. ^$ a
Statistical control, 统计控制
* S1 c" x8 H2 CStatistical graph, 统计图
# ?6 E( p% C6 o5 i; c7 @1 wStatistical inference, 统计推断
5 v/ Z" R- S p- o, wStatistical table, 统计表+ ]" o1 E+ F! p+ M
Steepest descent, 最速下降法
, `' ^/ N- S) s5 M9 FStem and leaf display, 茎叶图, N/ y- K/ i/ w* G; ]7 }- z. V
Step factor, 步长因子8 V7 V4 p4 S. d% A8 m
Stepwise regression, 逐步回归% U, r+ F* V: E& p' Q1 Y+ {
Storage, 存, ^. U- }" I% V5 v
Strata, 层（复数）- w: b2 [& x+ j8 t8 I
Stratified sampling, 分层抽样
3 b% e9 J" g& d3 D) }/ A0 KStratified sampling, 分层抽样
$ k4 j. n* i6 e$ C5 OStrength, 强度
" [# m* Z& Z# x3 sStringency, 严密性
8 P N" P* x6 o7 {! e: CStructural relationship, 结构关系/ O6 f: v& p% F! K
Studentized residual, 学生化残差/t化残差+ Z3 z0 c$ M) P# N7 B# {0 S" t: @
Sub-class numbers, 次级组含量# y% Z+ v, K6 |* B/ l
Subdividing, 分割+ M3 n/ f( Y2 [4 n, F
Sufficient statistic, 充分统计量6 @- O6 T+ ]7 O: d/ H7 L" b
Sum of products, 积和
: T! b, g) e8 K" ]) I! h$ A, ?Sum of squares, 离差平方和
0 F! ?! V8 ]8 L; ]Sum of squares about regression, 回归平方和* v% s, c4 T) }5 [# I4 R9 y9 _8 [
Sum of squares between groups, 组间平方和
+ W* B4 l+ N. N) \6 |8 X/ e. aSum of squares of partial regression, 偏回归平方和% l8 Z) M9 ^/ b5 l+ e0 z _0 v" }: h
Sure event, 必然事件( G" E. S& w! S8 m, C6 f0 A& K
Survey, 调查
% |* A, s7 Q/ D) Z9 H `Survival, 生存分析& f @2 i0 d( {* X; d; @' N; e0 f2 F
Survival rate, 生存率* w$ H( N0 {9 T
Suspended root gram, 悬吊根图& ^/ k+ e5 V5 B
Symmetry, 对称: D6 E, p- Q" o
Systematic error, 系统误差
* U* b q- V ySystematic sampling, 系统抽样# r0 ~# o7 X9 T
Tags, 标签- |+ G- R) Y u# v
Tail area, 尾部面积) v% w5 `* D; p! `
Tail length, 尾长) s) Y( Q/ {$ \, S
Tail weight, 尾重
7 x& Q y! e* ~: c. H% M/ \, X7 [; rTangent line, 切线; z1 r; ~" H# F6 x
Target distribution, 目标分布8 v1 K& Q, p% L" F5 w" t' d' ^; k" J
Taylor series, 泰勒级数, B, o: m9 L, `
Tendency of dispersion, 离散趋势2 p, P/ D8 V' V) i
Testing of hypotheses, 假设检验
3 r' \8 W; V, T9 xTheoretical frequency, 理论频数
. h1 c, R9 q7 k4 e5 B( jTime series, 时间序列
- A |, {5 o- L% H: STolerance interval, 容忍区间
8 B9 f( z6 z \% A; H. \, KTolerance lower limit, 容忍下限
" I* K! \ h; q9 QTolerance upper limit, 容忍上限: A6 r7 v# u' U$ z: N! U8 E
Torsion, 扰率
' p2 y' x$ q# w8 oTotal sum of square, 总平方和
' P2 `+ t4 y7 q" W' i' E+ x5 @1 STotal variation, 总变异
! |* @9 N; H' k$ T+ g$ y+ eTransformation, 转换) \, s4 ^" Z! z2 k
Treatment, 处理. P! B* V L$ d2 k$ F
Trend, 趋势
) {" w8 U5 d, |. i+ H) ^: F! STrend of percentage, 百分比趋势
/ z! G2 {* ~8 H4 L( bTrial, 试验
) j% t9 ?8 u6 n j, Q8 |Trial and error method, 试错法) G$ ] s @" f$ t
Tuning constant, 细调常数
% p% R7 _4 q0 I* L& oTwo sided test, 双向检验
/ I% T" B4 \6 v. b+ g5 WTwo-stage least squares, 二阶最小平方
" m% {9 e( T' l4 X/ CTwo-stage sampling, 二阶段抽样4 R/ n; N; \4 h6 F- }
Two-tailed test, 双侧检验
( {5 ?3 o+ S- mTwo-way analysis of variance, 双因素方差分析
( X/ ]# X9 B+ I5 sTwo-way table, 双向表) a2 f1 K3 m9 Q& j4 a
Type I error, 一类错误/α错误& ^: J: x( U; z1 p7 }0 Z: A
Type II error, 二类错误/β错误% E( \2 K1 i( d+ N# o2 l Q
UMVU, 方差一致最小无偏估计简称 O. Q8 Y' |0 R0 o
Unbiased estimate, 无偏估计
, m, y# Q8 \; T; J8 UUnconstrained nonlinear regression , 无约束非线性回归' C& e/ S. d0 m0 C
Unequal subclass number, 不等次级组含量7 k. D, s* @4 m/ h1 u! X
Ungrouped data, 不分组资料
) U7 l0 v6 l. f' bUniform coordinate, 均匀坐标
/ L$ t% w' j: O5 iUniform distribution, 均匀分布5 r% s0 m. I8 s6 ~
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
l# I; } O4 b9 m7 b3 HUnit, 单元+ z; X$ _; s# y7 O4 B0 _4 x
Unordered categories, 无序分类, }# r! l9 h+ _( C' R0 h& @
Upper limit, 上限
- Z" j0 [ R/ u" L2 h) e1 iUpward rank, 升秩
5 J' r6 {& p ~9 @, o. T( }Vague concept, 模糊概念- l6 f" w" F; C8 ~' ^* P( H) } K
Validity, 有效性! O5 p1 Z5 a! h2 X v
VARCOMP (Variance component estimation), 方差元素估计8 i$ O$ |% }1 H+ F2 n
Variability, 变异性0 e& l" X/ s8 Z8 Q
Variable, 变量* W) L. {, e+ [( C$ B, C7 j
Variance, 方差
; k, V+ l3 _4 L! L% X! wVariation, 变异1 A w3 \" H1 @! O- G
Varimax orthogonal rotation, 方差最大正交旋转9 O$ X. }, A0 D5 \ M$ D, t% q
Volume of distribution, 容积* \" L: _- _, p, _4 W
W test, W检验
k: K2 w% u) G$ {( xWeibull distribution, 威布尔分布1 k: K* D4 m# k7 c: V" ~, `0 T7 N
Weight, 权数
% N T v+ M$ v6 CWeighted Chi-square test, 加权卡方检验/Cochran检验
. x3 h B% h1 l* M. x# O& ]Weighted linear regression method, 加权直线回归
7 n0 o+ F( k% Z# b8 V4 tWeighted mean, 加权平均数
* g% E; d: j2 N- T6 j7 v% S# xWeighted mean square, 加权平均方差( h7 A+ d( r' T) \
Weighted sum of square, 加权平方和
0 G9 Z) [! L3 s8 Y; h4 x; Y% AWeighting coefficient, 权重系数
& L, h% Q6 ]- @0 ^3 m1 CWeighting method, 加权法
M7 H+ o5 `& s: r5 A' tW-estimation, W估计量, T, c8 x. N* T7 Q4 L6 K6 y( Y
W-estimation of location, 位置W估计量' F0 B: d: [. D0 C$ h) v* a
Width, 宽度: [7 i3 N9 J3 d, o+ D3 N+ F
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
5 n% v3 d) m5 `8 ?' b! h" OWild point, 野点/狂点& Y0 W5 P" `' B$ h
Wild value, 野值/狂值8 n& H3 V+ Y# e4 A' y5 _: r
Winsorized mean, 缩尾均值# r% T4 |/ |7 K2 O
Withdraw, 失访 2 F9 w+ l0 e' r0 e0 t
Youden's index, 尤登指数6 {+ j( i% p4 D* h
Z test, Z检验
% [) B5 G( a! @0 E4 M. P2 lZero correlation, 零相关
& u6 O9 {; P) I9 K" D: {7 o* hZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
