|
|
Absolute deviation, 绝对离差
1 A8 d% U6 A1 Q! Z$ K! yAbsolute number, 绝对数4 `' k7 U% O4 F- Y% q! y
Absolute residuals, 绝对残差
" \% z! y4 c5 I0 Z# N1 iAcceleration array, 加速度立体阵9 @' G) E( W- y8 |
Acceleration in an arbitrary direction, 任意方向上的加速度
9 O6 c7 Q$ y k! lAcceleration normal, 法向加速度3 J* ]' w8 E* {9 t: o
Acceleration space dimension, 加速度空间的维数( {" ], R& `/ R
Acceleration tangential, 切向加速度
' H/ b) w! r7 g/ `/ L" HAcceleration vector, 加速度向量0 y' }- i" l5 f( S7 ^2 V
Acceptable hypothesis, 可接受假设% ?3 a" x- r9 R5 ]8 t& v
Accumulation, 累积
4 [+ F& m* v M+ {3 AAccuracy, 准确度
6 I) Q8 P# ~) QActual frequency, 实际频数: T, N8 Q- t. V
Adaptive estimator, 自适应估计量
+ s5 {4 {6 a0 A# HAddition, 相加; e9 ^2 ^5 _- b: j
Addition theorem, 加法定理
* Y- x4 M( a+ B6 o# @7 {3 M+ N$ BAdditivity, 可加性
, j8 D+ D% z* D% U6 j* b! d+ d# Z8 UAdjusted rate, 调整率
@, G( Y& P' T4 s/ T2 jAdjusted value, 校正值% j \ X' l& s+ Q- N% N# d0 @
Admissible error, 容许误差# R- \- `" d) @( l2 D5 o1 i3 Q
Aggregation, 聚集性
6 Y" f2 x2 `. C$ [3 cAlternative hypothesis, 备择假设* s" a/ N7 K3 h7 Q/ Q
Among groups, 组间
0 l5 y9 d& o, `/ b0 MAmounts, 总量
( M) [0 c1 K) ]Analysis of correlation, 相关分析
% o2 s; T2 j9 fAnalysis of covariance, 协方差分析
) S' ]/ s; ^$ |/ a% JAnalysis of regression, 回归分析! V! ^, P- a$ q2 X. O
Analysis of time series, 时间序列分析
3 l# n' }. x! a3 v7 bAnalysis of variance, 方差分析! r& V( D, E6 H! F1 J, ^& O& L' F
Angular transformation, 角转换
, L0 \6 p1 B; YANOVA （analysis of variance）, 方差分析
2 @2 ?. X! X0 KANOVA Models, 方差分析模型! t+ C \! A- }" S k
Arcing, 弧/弧旋8 t& H4 Y& x ?/ ^) B
Arcsine transformation, 反正弦变换
z8 V% j8 A; r/ k$ hArea under the curve, 曲线面积
2 X9 M* [, ~& IAREG , 评估从一个时间点到下一个时间点回归相关时的误差 6 B' z% S8 I+ J5 X* u2 t( b8 Q" _ u
ARIMA, 季节和非季节性单变量模型的极大似然估计
1 U. j, E% r3 G/ p, AArithmetic grid paper, 算术格纸7 v8 S! m0 n+ v. `
Arithmetic mean, 算术平均数
) ^2 @* ]" U; FArrhenius relation, 艾恩尼斯关系 H2 A. {$ f$ `6 e1 J5 R% @
Assessing fit, 拟合的评估
) R5 I. S/ y7 a/ BAssociative laws, 结合律
7 r* H8 N$ H, q: g. w$ |5 ~6 n. Z; F, XAsymmetric distribution, 非对称分布
/ P0 e# S! M7 }- Z' @& z$ o2 b( gAsymptotic bias, 渐近偏倚4 b r% b6 Z3 D( `3 K) x
Asymptotic efficiency, 渐近效率0 o- E8 c. `! I" c5 [
Asymptotic variance, 渐近方差
3 Z1 z' l, |1 n+ E: `& _( qAttributable risk, 归因危险度; c) ]3 n6 k: U3 D
Attribute data, 属性资料
, U' p: d+ G8 d" ?8 FAttribution, 属性4 _0 Q+ E6 x+ b" h; D
Autocorrelation, 自相关
2 G) @) C( u, S, W5 |8 aAutocorrelation of residuals, 残差的自相关
9 B! P5 a, p" }0 D1 _Average, 平均数
8 S. c! E; G0 J; x! @. [4 u- @Average confidence interval length, 平均置信区间长度
% M6 E6 ^" H. L: r- mAverage growth rate, 平均增长率 C! B+ D" z: {; x
Bar chart, 条形图# O6 V' \1 I. ` X
Bar graph, 条形图# @1 i$ G. U5 a5 u/ z* k
Base period, 基期
; H. }: y4 K8 h @! j* J6 vBayes' theorem , Bayes定理4 z6 s( Y3 t+ w+ [ C+ Q4 P
Bell-shaped curve, 钟形曲线
) H) t. ~4 ~9 fBernoulli distribution, 伯努力分布3 \# U; L9 x8 O5 k9 }2 r' f
Best-trim estimator, 最好切尾估计量
) F; W& @* k/ ^/ Z2 r8 [8 G: x0 QBias, 偏性' f" u8 K2 [; _# m% K' m
Binary logistic regression, 二元逻辑斯蒂回归
/ |# t. d0 P+ D- f; Q1 PBinomial distribution, 二项分布
1 b' g2 I* l7 xBisquare, 双平方
( C' a4 y7 Q8 K/ {# L9 aBivariate Correlate, 二变量相关* e1 D0 r$ a5 n% `8 u8 c' Q
Bivariate normal distribution, 双变量正态分布1 I2 b5 z A/ z4 w4 ^4 z
Bivariate normal population, 双变量正态总体' L0 c$ A- r. c& w! b9 S
Biweight interval, 双权区间
" v1 N4 ^& g. w! y* D' JBiweight M-estimator, 双权M估计量
; Z1 S I2 b+ O5 G7 @6 v4 Y8 W! @1 MBlock, 区组/配伍组
& }/ @: R$ W6 U8 E0 LBMDP(Biomedical computer programs), BMDP统计软件包9 X0 t, S6 g: T6 p" }
Boxplots, 箱线图/箱尾图
5 `$ ?9 U" K' v6 P+ ^0 gBreakdown bound, 崩溃界/崩溃点
' A$ n" `, T5 C+ ], JCanonical correlation, 典型相关2 J% I' i5 t9 W% X1 ^' R
Caption, 纵标目% o0 J4 S1 C; g/ n
Case-control study, 病例对照研究
% u/ T& G( }' `Categorical variable, 分类变量4 O0 g- {- c& g# U! K2 _! D/ u% h
Catenary, 悬链线
' a3 D& {$ O Y+ z! s: F8 NCauchy distribution, 柯西分布
% F$ B0 |( r7 Z% }+ Q$ D9 nCause-and-effect relationship, 因果关系8 I- _* G+ x* n: t* d; O$ V' U
Cell, 单元) i" u3 L" J, R A7 O; p8 y
Censoring, 终检: g' w% q9 ~9 n" W& Y& O
Center of symmetry, 对称中心
- x% ]% v0 t2 \Centering and scaling, 中心化和定标/ ^$ e3 J" x3 t1 L: z& X
Central tendency, 集中趋势+ @+ U3 o9 _/ s9 ^8 u; R
Central value, 中心值3 p& Y' ~0 U( l$ K+ M( S! ]
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测: n' o" S2 x" c. [$ |; ?: H$ v
Chance, 机遇
% o- e$ q }: `* J" _Chance error, 随机误差
0 Z2 @( n4 C/ |; ~Chance variable, 随机变量6 _; D$ L4 c) o3 Z( b: j
Characteristic equation, 特征方程% c! s/ ?( {' T! @
Characteristic root, 特征根1 Y& |* Q9 s' k P* |, C
Characteristic vector, 特征向量
4 H0 `1 ] v4 j9 [Chebshev criterion of fit, 拟合的切比雪夫准则$ q0 C4 ~# p% A) C3 u. b/ f( ^
Chernoff faces, 切尔诺夫脸谱图+ Q' v4 H& W: d" U6 f9 U
Chi-square test, 卡方检验/χ2检验
& x1 b/ r# N& [& DCholeskey decomposition, 乔洛斯基分解
( e1 S$ t6 L( {0 _# FCircle chart, 圆图 1 z7 W4 t/ c7 u( q9 w! r8 e* z1 s0 c" ?
Class interval, 组距
4 u H6 v/ X) |4 p) S! ~5 eClass mid-value, 组中值5 s1 [) a* Q; C# f
Class upper limit, 组上限/ f7 o7 X8 c$ ]: M3 Q9 Q
Classified variable, 分类变量
5 e% d7 Q7 ^, Q: M. VCluster analysis, 聚类分析
: d; T3 O8 g& D$ V" `7 b% F; vCluster sampling, 整群抽样
: P. B# l7 a+ [Code, 代码
- v0 @! @' l* S7 M; E& ?Coded data, 编码数据& Q4 L! j8 Q. ?7 }' [$ u
Coding, 编码
- j# { T5 D4 I/ @Coefficient of contingency, 列联系数
' c5 d0 G; b9 ~9 `; `Coefficient of determination, 决定系数
' ?7 J! @0 O& v' J: @) ~Coefficient of multiple correlation, 多重相关系数1 O9 s7 m: p' b+ g; J+ S: v
Coefficient of partial correlation, 偏相关系数5 i. _1 q8 y7 }) t1 Y R+ d
Coefficient of production-moment correlation, 积差相关系数) k% \7 u8 ?! g
Coefficient of rank correlation, 等级相关系数$ H% y- j/ c. R# r* o. [
Coefficient of regression, 回归系数0 m- W. c9 {9 s! v
Coefficient of skewness, 偏度系数
3 M F6 x" M' QCoefficient of variation, 变异系数* @* `9 R# h8 w* W7 O
Cohort study, 队列研究
. h8 K" H: r* k0 hColumn, 列/ N4 p. X* z: G V7 a7 X4 b
Column effect, 列效应6 B7 D- c" U2 m
Column factor, 列因素' W4 O6 }/ [- `5 g9 c
Combination pool, 合并
8 i4 \6 M0 x& Q7 y# Q) zCombinative table, 组合表% z+ i* a8 U) p# l- S
Common factor, 共性因子
* A) `( B# Q9 Q4 \ K- d. LCommon regression coefficient, 公共回归系数$ k; I j" Y- x& e. ?+ X
Common value, 共同值
2 g4 h7 M' E3 }% j, BCommon variance, 公共方差* e( ?" G5 C( e* A1 {6 J9 o
Common variation, 公共变异1 s8 L j# r( D; @# f7 |; D8 C$ W
Communality variance, 共性方差5 \" J/ W; Y6 u; s# j
Comparability, 可比性4 H6 j- t# g- f' m5 y T. l
Comparison of bathes, 批比较+ \; k4 h+ n; j7 {! X2 h0 f
Comparison value, 比较值' F6 _- I y$ |) r* v
Compartment model, 分部模型5 n) `4 N3 O V' e% f
Compassion, 伸缩, x0 y, b3 A+ X" D) |3 f0 h$ E
Complement of an event, 补事件
( E7 X4 j8 w9 \" f6 GComplete association, 完全正相关
" W& D+ e* p m( {" h3 dComplete dissociation, 完全不相关
* [( E2 E4 n6 b S3 \+ ^) pComplete statistics, 完备统计量0 N& ]9 w6 l6 } P
Completely randomized design, 完全随机化设计
: {) f; S# f' ]Composite event, 联合事件) i8 p$ [! J0 O: ^5 `
Composite events, 复合事件
8 x7 v8 o/ {5 M; Y; ^. M+ j( }- sConcavity, 凹性
1 W/ V$ _% J* O, d( \8 `9 RConditional expectation, 条件期望+ Z$ F, R* H+ C& y( i
Conditional likelihood, 条件似然/ X) U$ C7 z* Y9 J: c/ c2 \
Conditional probability, 条件概率4 k/ i3 q/ n9 n' u9 N
Conditionally linear, 依条件线性
Y. k" O& c. DConfidence interval, 置信区间
6 R2 E8 [2 E2 G$ E) cConfidence limit, 置信限7 e' O- ^1 {* Z1 f" r8 }' i! U
Confidence lower limit, 置信下限
5 N" x: E/ N3 A+ _Confidence upper limit, 置信上限2 G6 q3 Y" e3 e5 Z2 m4 f% `. x
Confirmatory Factor Analysis , 验证性因子分析
* Q E& e; l: Z0 p4 M" b' u2 bConfirmatory research, 证实性实验研究! [" D6 Z: x' l/ b
Confounding factor, 混杂因素
" b4 u) l7 a2 G! wConjoint, 联合分析
; W3 ~2 L- n/ M; {4 i) |& ~' j( pConsistency, 相合性9 l8 N& T b" m6 j, r
Consistency check, 一致性检验
7 S" a) m) t9 a8 o* j# E" f6 ~* ^Consistent asymptotically normal estimate, 相合渐近正态估计
5 W5 Q$ h3 t9 P5 s3 ~+ I2 mConsistent estimate, 相合估计
) i6 [3 X! a9 c/ _$ LConstrained nonlinear regression, 受约束非线性回归) d3 F" N$ _1 I4 X! x7 X' |& K0 P c
Constraint, 约束
+ F9 M2 N" A/ f5 ~9 ^! @2 c% T/ sContaminated distribution, 污染分布. F" m g' t" v1 w, C" c
Contaminated Gausssian, 污染高斯分布
5 `. m' {8 M: Y: V5 g9 O$ oContaminated normal distribution, 污染正态分布1 u1 j$ J2 Z+ b3 D8 F
Contamination, 污染3 {; F& y- B, B, _$ [1 b% ^
Contamination model, 污染模型" c3 ^) _0 m: K- x
Contingency table, 列联表3 p' v" p$ }6 f. [# e% N7 R
Contour, 边界线% @& O3 Z/ h L+ @2 h: Y$ B
Contribution rate, 贡献率
; \. m v- R. H4 f& V5 f' fControl, 对照$ A* |; \2 o- C2 P' X! N
Controlled experiments, 对照实验$ m% l9 `6 h7 n; L+ n) |; V8 r
Conventional depth, 常规深度
& i5 X$ m% z0 N9 w* xConvolution, 卷积
% q! S$ U" b# QCorrected factor, 校正因子7 j8 t! B8 N0 G% c9 O
Corrected mean, 校正均值2 d/ q) c p7 R) X- ?* m% X6 R
Correction coefficient, 校正系数
8 r" p1 w* z. M+ |! G4 q1 v% QCorrectness, 正确性
+ Y% n% ^! y; F' i9 q- Q8 WCorrelation coefficient, 相关系数
* v: O' M/ f( w/ vCorrelation index, 相关指数3 @$ h/ j) p; M1 _
Correspondence, 对应2 v8 S3 P- Z0 k$ P9 [9 \
Counting, 计数/ k) |/ g0 o) }6 C
Counts, 计数/频数
! Y) U J" D% S" G1 B. C6 {Covariance, 协方差
% @. d! G- m4 `( H, KCovariant, 共变
! \6 E, \0 r6 nCox Regression, Cox回归
, a; z2 y6 G4 u: S$ RCriteria for fitting, 拟合准则
1 ^& O! l" |6 x r* sCriteria of least squares, 最小二乘准则
1 T. Z" r3 o- Z# Y4 OCritical ratio, 临界比
) W$ i8 k$ ?3 RCritical region, 拒绝域. v/ G$ i3 G5 a' c# k' A
Critical value, 临界值+ y" @4 O- c+ T% i- o
Cross-over design, 交叉设计
+ k9 F C0 y+ t% hCross-section analysis, 横断面分析2 x1 r, k- v+ D* o6 c
Cross-section survey, 横断面调查
9 C7 C) K* _- S/ u8 ?: n6 zCrosstabs , 交叉表
% F2 {6 |# [4 e$ s. Y% \Cross-tabulation table, 复合表: t. R, I6 \0 } S5 f
Cube root, 立方根) Y) l# g1 O' c0 U0 h
Cumulative distribution function, 分布函数
0 `5 |! t0 G, a( {3 p, FCumulative probability, 累计概率. A8 X- D3 h' O, t6 x' w" I2 z
Curvature, 曲率/弯曲
( i9 V1 T- @2 O" s: g0 A; N; MCurvature, 曲率
* q* B; m# t) w) q& XCurve fit , 曲线拟和 8 J! O% B a6 k4 E( \. o. j
Curve fitting, 曲线拟合
6 T9 |8 d8 N0 R0 f# DCurvilinear regression, 曲线回归
# K5 t( \! s4 X; Z# G/ HCurvilinear relation, 曲线关系$ L! k% _4 s5 o& @' r& O
Cut-and-try method, 尝试法
, f* U- Z1 @/ f* o. V) `Cycle, 周期
$ [, [2 l- p) k: f1 {Cyclist, 周期性
% S4 r' Y0 A3 o/ d8 }) mD test, D检验
. a$ o, C6 m7 vData acquisition, 资料收集5 }: n( y$ F3 K% r! p1 |8 K# S, N
Data bank, 数据库+ J9 d5 Z2 a1 Y+ T8 b
Data capacity, 数据容量- \+ ]% h7 y9 _4 P
Data deficiencies, 数据缺乏8 D. c9 @* A) w6 M( z
Data handling, 数据处理
, H+ j. {* I! VData manipulation, 数据处理
: B) i A' V5 I; _0 \' K# j7 [$ e, u! BData processing, 数据处理2 e! E+ a5 |1 X- y) T R& ^2 B
Data reduction, 数据缩减
, `# x7 |% M% N! LData set, 数据集
+ x7 |4 c- o/ f, r5 k MData sources, 数据来源1 O) d3 C, T5 y, I5 G
Data transformation, 数据变换
2 S0 i( s& S* x0 ]( v. lData validity, 数据有效性0 C2 ?) v( }0 }
Data-in, 数据输入# r: b3 C4 \% O: U1 }4 s8 o
Data-out, 数据输出. U" J. A! I5 d
Dead time, 停滞期
3 @) }0 q/ s' ]) A1 X( Z8 lDegree of freedom, 自由度! W8 w6 K; N& o$ h' R/ h' y
Degree of precision, 精密度
4 e. o( n+ f# E2 y' l0 HDegree of reliability, 可靠性程度
+ V; u+ c! A3 x& O( J) N7 x" KDegression, 递减+ s8 u. ?8 W/ d
Density function, 密度函数3 Q y6 ]3 \+ J5 w
Density of data points, 数据点的密度
5 K" m1 h, r$ g3 s( ?6 xDependent variable, 应变量/依变量/因变量$ y# l' W* B, Z$ D
Dependent variable, 因变量
7 j2 B+ T: o/ {2 v6 W# P* FDepth, 深度3 {, h% N# v, @ b- A
Derivative matrix, 导数矩阵# w& T( i/ p$ w! }$ {* m
Derivative-free methods, 无导数方法
( E) v- A6 _4 e5 T+ @4 z7 u* }Design, 设计
$ E+ k8 t# r8 `$ p; i6 n: V% TDeterminacy, 确定性
}, Q3 N$ r; zDeterminant, 行列式5 b5 {) g! J4 p5 H1 N+ {
Determinant, 决定因素+ v9 m% w2 E& W* |! c% y
Deviation, 离差: q/ @+ I0 p/ p( @7 \
Deviation from average, 离均差
9 `3 H h( F! ?/ M# i2 dDiagnostic plot, 诊断图
! d6 g9 @: S4 D' d9 h/ J, MDichotomous variable, 二分变量
5 ^% k1 j* c1 R eDifferential equation, 微分方程0 b2 w O5 q, l& e
Direct standardization, 直接标准化法
' U3 @+ |: j7 ZDiscrete variable, 离散型变量
) b& }! S8 Y& \. [3 ]* @DISCRIMINANT, 判断 & |; O% T, g6 G6 J5 [
Discriminant analysis, 判别分析" @# r0 Y4 h6 S: y! @' E
Discriminant coefficient, 判别系数( N0 u* H4 `, E$ O% E7 i
Discriminant function, 判别值: w+ m( ~6 @: i* k: n/ r% i
Dispersion, 散布/分散度; J3 v7 }& P+ t4 [7 @& R$ K" G, r
Disproportional, 不成比例的
% U( A; `: R a6 p9 F$ z5 N0 tDisproportionate sub-class numbers, 不成比例次级组含量
; o5 Z( m! v% |6 {3 YDistribution free, 分布无关性/免分布
; R3 G/ |9 `. ?! \6 H: Z' A) J# YDistribution shape, 分布形状
: O- U# u m) U0 W: x, |( qDistribution-free method, 任意分布法
4 v6 X3 s' P g7 @Distributive laws, 分配律
% R. ^/ V8 @8 d$ p6 RDisturbance, 随机扰动项
9 \! p/ ~4 ?3 p( ?Dose response curve, 剂量反应曲线 ?1 {# D8 f5 y( s
Double blind method, 双盲法8 d9 m5 ?6 Y' a8 W; Y4 G, s* P
Double blind trial, 双盲试验
5 G/ t! F2 c: a! j* j% yDouble exponential distribution, 双指数分布: k' N! k& h o: [ j8 j3 _) G# X6 W
Double logarithmic, 双对数( `+ k" Y5 I3 c4 J% U3 b) m4 s4 K
Downward rank, 降秩
+ n$ u* Z7 G; X& s3 _ `- LDual-space plot, 对偶空间图
5 q5 K5 G, y* W* q1 w$ N% |DUD, 无导数方法2 v1 X0 }% \: c, t. K4 _
Duncan's new multiple range method, 新复极差法/Duncan新法& p/ s7 {! g" D* K8 V
Effect, 实验效应
5 l" |5 M ~' U+ F( Y6 ?* ~' r) pEigenvalue, 特征值" P" t; F4 I* Z9 I9 M9 P
Eigenvector, 特征向量
, p$ s9 d" x8 g( @ ?8 O/ }Ellipse, 椭圆
8 y2 I( } D' B( B% f) P- HEmpirical distribution, 经验分布0 e& |' @# {* p* ^
Empirical probability, 经验概率单位$ Q$ J% W3 L0 E8 }: F$ N5 g0 P9 r, K8 R
Enumeration data, 计数资料
! h% p) ~% G: a4 s/ u" V4 u' y9 d3 UEqual sun-class number, 相等次级组含量
4 `( w6 F. W6 g8 NEqually likely, 等可能
: k" W; h- N4 t+ d' l: }: m" V k9 fEquivariance, 同变性4 g# P. \- ^4 }! U q; c- |
Error, 误差/错误
3 D' u F. S, s3 `0 ^* V9 WError of estimate, 估计误差
! Y" P1 H9 K3 g' s# U- tError type I, 第一类错误
y( D& Z9 i9 X6 R( nError type II, 第二类错误8 ^0 A$ @3 C$ q% f
Estimand, 被估量
7 M# O# y( V6 Y) n) i$ n0 I" A3 wEstimated error mean squares, 估计误差均方
0 t, K8 x# i; lEstimated error sum of squares, 估计误差平方和
* `4 f8 ?& n/ q8 U% ]+ KEuclidean distance, 欧式距离9 V3 I+ d* N6 E- b$ `: E# k% F& v
Event, 事件
; K) P( F1 }, |Event, 事件$ l7 d6 L+ O8 e+ A! W
Exceptional data point, 异常数据点
) Q' A$ S: h1 v/ T y M1 b& v6 WExpectation plane, 期望平面" n* q2 Q5 K5 m8 B2 G
Expectation surface, 期望曲面
8 o& m( n7 S* |1 ^Expected values, 期望值8 p0 }# R0 h. Z5 z; [
Experiment, 实验
2 m8 ]4 F' N% X2 ?+ ?5 w* `( RExperimental sampling, 试验抽样
$ e8 Q) A0 Q# m) o9 {- U. @0 sExperimental unit, 试验单位! n. }; j# x) ]3 k! j3 e% _ j
Explanatory variable, 说明变量
' B0 t( \ a1 L7 I# _( oExploratory data analysis, 探索性数据分析
. ^. Y! \7 r" n/ V: W( {/ ]5 fExplore Summarize, 探索-摘要
" p( U/ x9 `4 ?( [$ X5 b! \7 Y/ SExponential curve, 指数曲线
0 ?: c! o% l) f, o; PExponential growth, 指数式增长3 Y6 y0 [8 q q; N
EXSMOOTH, 指数平滑方法
" S, X$ G2 F% h4 L8 W4 eExtended fit, 扩充拟合# J, J/ {0 U! P) n3 u8 Y
Extra parameter, 附加参数( o# M5 I# F: i
Extrapolation, 外推法
! S( J; |) d r- a2 `' a: XExtreme observation, 末端观测值
) |9 n2 h, M( ]1 G9 t7 J& |Extremes, 极端值/极值
0 t: Q8 A+ A/ _2 h% ~; eF distribution, F分布
6 K m+ g5 i+ c8 wF test, F检验
( {6 F5 n N% M* e0 AFactor, 因素/因子
: s) Z: C7 b4 T! l2 P$ e3 F1 TFactor analysis, 因子分析
5 ^6 {+ b5 u7 I/ y% o$ QFactor Analysis, 因子分析; Y% J1 N4 O& Y- W' S& Q& U; c
Factor score, 因子得分 ) Q3 [6 I6 T" P$ Y7 P+ g# r. C
Factorial, 阶乘2 g+ @' u- f5 V, j! u
Factorial design, 析因试验设计' o/ X$ O( m1 F0 ]7 L9 x$ w) J3 J* s
False negative, 假阴性! o, z; Q& b$ g9 b7 k& V- K/ w. r
False negative error, 假阴性错误
, ~) b6 D6 D8 d( h' I3 HFamily of distributions, 分布族8 x$ E8 [- D2 p, u- `
Family of estimators, 估计量族
4 }+ c4 c4 {3 c0 MFanning, 扇面
3 w/ ~" d/ j0 V6 t q* q/ JFatality rate, 病死率3 S; L% c$ A( q1 U2 b1 W
Field investigation, 现场调查3 b$ _' k- C1 ^7 A, J+ S8 z, x% m6 F
Field survey, 现场调查
: j/ w U2 o, M( OFinite population, 有限总体, S' n3 K" d4 R& y8 t" ?% Q
Finite-sample, 有限样本* U S; n" X% G2 W# i( G
First derivative, 一阶导数
1 v) y1 o* t1 o+ r6 e8 ]1 kFirst principal component, 第一主成分9 W5 y5 s4 P' l y: M7 l0 s4 R
First quartile, 第一四分位数
, W, c. N$ D+ @1 Y' d( Y5 ZFisher information, 费雪信息量6 H: |) T9 I. C P# e; V
Fitted value, 拟合值
% ?! V4 Z( O: m7 HFitting a curve, 曲线拟合
+ p7 p$ U F6 l: d2 IFixed base, 定基
6 l. M- Z Q1 {7 L( x- M- MFluctuation, 随机起伏" x& K1 y: n6 k$ z" C" ]2 a
Forecast, 预测4 s2 |: a/ `% N: y4 ^
Four fold table, 四格表
; {+ c4 D+ ]0 O1 K0 @, k& ?. mFourth, 四分点
4 o- R; O# f- |Fraction blow, 左侧比率
3 t' t; \; R, j' h/ M* l$ T6 S; IFractional error, 相对误差) |5 Z5 s; K B6 ~6 b& ]6 J* a* R* y
Frequency, 频率+ e7 n- ~' r Y
Frequency polygon, 频数多边图
* \% r. K& Y/ S+ q, nFrontier point, 界限点! E* U: c X% N: ^& Y1 o
Function relationship, 泛函关系
# C `- y" `2 h$ w z1 e7 j! I7 ZGamma distribution, 伽玛分布/ {* D8 e9 w$ S5 D" h: L
Gauss increment, 高斯增量
! q9 ~# ?- D- G" _" S! y& b! M) kGaussian distribution, 高斯分布/正态分布8 c. e+ P' f1 ], J% y2 d6 \
Gauss-Newton increment, 高斯-牛顿增量: l0 Q) `* T, T
General census, 全面普查/ @2 N- U2 G6 \: u0 T
GENLOG (Generalized liner models), 广义线性模型 4 z) O2 H7 h* h7 a6 Y3 M& n
Geometric mean, 几何平均数5 x7 ]. }: d0 J- }$ k* \2 f
Gini's mean difference, 基尼均差5 ~4 j# L, m; D* @: ^ c5 w1 d
GLM (General liner models), 一般线性模型 `- B/ P* f9 d" c
Goodness of fit, 拟和优度/配合度1 ~7 x4 q) h1 c9 b5 q4 f
Gradient of determinant, 行列式的梯度
2 n7 J) p0 ~9 i5 ]Graeco-Latin square, 希腊拉丁方
|2 S; y- n5 GGrand mean, 总均值
2 W& d6 c' |1 B- I- ?Gross errors, 重大错误, m) w3 X; f# h0 ?+ R+ d
Gross-error sensitivity, 大错敏感度1 h2 j( V. S( b/ j
Group averages, 分组平均# @' e1 a! L3 Z
Grouped data, 分组资料
: ~9 c* k8 p( i" J* g" Q2 @2 rGuessed mean, 假定平均数9 j1 |1 K" a b4 x
Half-life, 半衰期7 F% `: q2 S8 Y5 j- I, T
Hampel M-estimators, 汉佩尔M估计量5 ?7 O0 }8 H6 [' o* D
Happenstance, 偶然事件7 W& [0 Q# J# B% Y+ ?# S
Harmonic mean, 调和均数3 r% d. p( ]% S, l
Hazard function, 风险均数" Q0 W& t: T, y8 a6 E
Hazard rate, 风险率
4 m. y& _3 O% Y: L7 V# j: x$ E* FHeading, 标目 1 R! k9 e8 R6 h" w1 B; `
Heavy-tailed distribution, 重尾分布
- f9 u4 N1 o/ m! }- Z: WHessian array, 海森立体阵, v/ E5 ?$ V/ e2 m4 D2 h
Heterogeneity, 不同质
" n! e2 m$ j/ k FHeterogeneity of variance, 方差不齐 / }# R* O* y! R4 {1 A
Hierarchical classification, 组内分组2 Q4 l8 `' T5 `; f" q$ _* f7 u9 V
Hierarchical clustering method, 系统聚类法. e8 y5 o* R3 ~/ g1 C
High-leverage point, 高杠杆率点
& C2 P+ z# c3 t4 ~; r: _& aHILOGLINEAR, 多维列联表的层次对数线性模型; W* ]! t1 }' g9 t5 ]+ s
Hinge, 折叶点! `2 t) q4 ~6 I0 y R
Histogram, 直方图
/ h' Q* r9 m/ u# v4 nHistorical cohort study, 历史性队列研究
# K3 C8 U. `) p' K# a# qHoles, 空洞2 A) e0 K% i+ p' D
HOMALS, 多重响应分析' o2 o2 X9 p$ k
Homogeneity of variance, 方差齐性
" D8 P4 [7 z- X, P' IHomogeneity test, 齐性检验0 q% @7 u& _$ R" K
Huber M-estimators, 休伯M估计量" E" w" s# i$ E! e" q/ x
Hyperbola, 双曲线/ }& `3 H& s2 s# |# o2 P4 P
Hypothesis testing, 假设检验
! L. I) w& H- Q% H6 w) H1 ^4 JHypothetical universe, 假设总体
1 V w/ l2 H7 y% S, X+ AImpossible event, 不可能事件: S8 S" |, A: G. X0 c; M) A: D
Independence, 独立性* o6 L% {, O) y# u
Independent variable, 自变量" l; w9 J# z9 y6 ^5 W1 G1 u$ e
Index, 指标/指数( B% v' X/ \# q) l
Indirect standardization, 间接标准化法
8 l4 L! I$ p; iIndividual, 个体
3 V) ]; [) z* o0 ?6 Y/ s% f' YInference band, 推断带: s) E8 N7 ^5 d. D* }
Infinite population, 无限总体' i/ b; `' T/ h: f: R: K
Infinitely great, 无穷大! ^9 p( q1 K( P0 C" s
Infinitely small, 无穷小- c/ v9 a) u# r% s0 `" x+ v4 \
Influence curve, 影响曲线3 t- c7 _5 V: p$ j! D
Information capacity, 信息容量0 g' v+ o: i) S8 n* A, r* F, E4 ?
Initial condition, 初始条件
2 y% D, [2 I' D4 }! W+ W8 ^: T- GInitial estimate, 初始估计值4 M6 ^# C0 {; M, O9 W) {
Initial level, 最初水平
- H0 L4 g7 Q& ~( {- `( w L8 lInteraction, 交互作用
( r5 \8 V4 {( U$ D4 \8 @' j8 `Interaction terms, 交互作用项' e9 n/ W) R5 y0 P
Intercept, 截距( U+ z2 C; a1 S( s+ q6 z: h
Interpolation, 内插法: T6 G2 B. g7 C2 z5 N2 t$ D* C
Interquartile range, 四分位距
6 I0 e7 {( k6 u0 HInterval estimation, 区间估计
* Z( R$ |$ r( p4 _/ UIntervals of equal probability, 等概率区间) w' x o: M( ?: W$ T7 q' P
Intrinsic curvature, 固有曲率
. S; u/ d, l/ {* y5 DInvariance, 不变性; `+ r& R0 k# _& q
Inverse matrix, 逆矩阵
* ^- m, ]5 ]* |8 HInverse probability, 逆概率5 ?( i" B# E* C! V" Y
Inverse sine transformation, 反正弦变换3 ?: M" B3 e# w! c$ h
Iteration, 迭代 , i7 D; I; p8 @; E9 b9 o
Jacobian determinant, 雅可比行列式2 H8 j) o$ u" s* @* t
Joint distribution function, 分布函数' V) B c7 M0 ^% |) ^
Joint probability, 联合概率, [: O# Z# C# W; U
Joint probability distribution, 联合概率分布; m" W k7 R0 P/ f: ~
K means method, 逐步聚类法
- H" R3 u \! P6 O( g4 lKaplan-Meier, 评估事件的时间长度
" Q' x# @/ {1 o6 ^. b2 zKaplan-Merier chart, Kaplan-Merier图
4 `9 \- ]0 Y9 g/ }Kendall's rank correlation, Kendall等级相关
p9 n) p; I4 p& ]6 P6 t) MKinetic, 动力学( P4 L" v* U/ l [1 ]. N, v
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
8 f( d/ l1 B$ k- y3 ?( l' wKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
! C9 G: A: {& j8 }& }. h5 EKurtosis, 峰度
: A8 w" x/ y2 K' `% ?+ gLack of fit, 失拟0 H- m- M, U# w i+ f- t5 _
Ladder of powers, 幂阶梯2 K# C# o: ^+ ]) G5 @/ \6 ~
Lag, 滞后% z, T/ @3 t8 U; m: t* w
Large sample, 大样本; S$ N! Z9 i$ M/ e7 }( o# F5 ~! J
Large sample test, 大样本检验! X2 v3 I. I# p
Latin square, 拉丁方
) B7 N8 R- e# X- Z8 m+ v0 e, CLatin square design, 拉丁方设计( z5 d4 ^, f, Y: `$ [! D
Leakage, 泄漏
: m9 k ]/ Q7 a% ~Least favorable configuration, 最不利构形
$ z& `; M: q5 F7 y$ h2 gLeast favorable distribution, 最不利分布
# q) Y/ G0 _( k& n8 n" lLeast significant difference, 最小显著差法/ k* t! _. x9 w: x- I0 [$ |
Least square method, 最小二乘法8 @+ ~2 u; Q1 j% ^* f
Least-absolute-residuals estimates, 最小绝对残差估计
) n4 s/ R, r4 W( S/ g( DLeast-absolute-residuals fit, 最小绝对残差拟合& p4 V, j# \7 m7 e# C
Least-absolute-residuals line, 最小绝对残差线
6 B4 u( k p' X. s+ aLegend, 图例" {' u6 {7 y+ {- _' X
L-estimator, L估计量, L9 O6 Y7 p# L" M2 Q
L-estimator of location, 位置L估计量
9 K+ \7 L" g! Z, N+ JL-estimator of scale, 尺度L估计量
6 g1 g( d3 t, n- r" v2 ELevel, 水平
0 Y4 Y# I; E# gLife expectance, 预期期望寿命8 J% y! A( O9 } w
Life table, 寿命表
* o* y! w& `9 _7 O0 q* j& |Life table method, 生命表法3 V' N( D; K- M" T" K
Light-tailed distribution, 轻尾分布
0 F! h; w4 {$ N2 t- p1 C+ ?Likelihood function, 似然函数
- g" ?; h9 D( o) {Likelihood ratio, 似然比
$ W, p7 M. [' f1 c6 v8 Cline graph, 线图# O" X! Y, }. N% }, ]0 ?
Linear correlation, 直线相关
5 T) d- _3 L/ P3 G& C: K' ~+ GLinear equation, 线性方程+ H( c- c: X+ [$ w4 e, i8 J
Linear programming, 线性规划
3 b0 K* \: A6 ~7 i: nLinear regression, 直线回归4 p' h2 B/ F3 N
Linear Regression, 线性回归
; T! k, e! V/ N1 h. t% BLinear trend, 线性趋势5 K0 R8 b3 }9 {0 |) z
Loading, 载荷
: Z7 _; `; f0 d3 MLocation and scale equivariance, 位置尺度同变性6 j) W- a9 H% @- z
Location equivariance, 位置同变性
# ?8 a: k, Y! u* y' S8 MLocation invariance, 位置不变性
E0 [' e0 N( W, Z. T7 U+ _Location scale family, 位置尺度族
- C0 L0 t. S8 {$ c/ G! p1 c4 ^Log rank test, 时序检验
0 r0 n, q* N' B6 ^Logarithmic curve, 对数曲线; l* b M: e9 V5 r
Logarithmic normal distribution, 对数正态分布+ \& G* g2 c% {% U- z$ h, N
Logarithmic scale, 对数尺度9 }4 y9 F# y6 P ~" J
Logarithmic transformation, 对数变换
1 y& q' ~( e# g$ ^) ]Logic check, 逻辑检查. [6 d/ E* M! D9 A; ^) b6 ]
Logistic distribution, 逻辑斯特分布9 _* L6 Z8 S1 h* n, |* z+ v' y
Logit transformation, Logit转换
+ ]7 l) T& C+ fLOGLINEAR, 多维列联表通用模型
3 D: y! S0 V, j" gLognormal distribution, 对数正态分布# ~. G9 C5 g9 z( @: q
Lost function, 损失函数! x, Y. d ^ w6 d& I" ~# c4 M
Low correlation, 低度相关
- G, F4 G0 C2 U# ~, H$ C! sLower limit, 下限5 Y! m4 E2 b- U4 M( Y
Lowest-attained variance, 最小可达方差
4 w. ~0 o! a! U8 M! q" W. J' M4 ELSD, 最小显著差法的简称
T# Y! ]8 n8 l( WLurking variable, 潜在变量
- Q. H. }4 |3 O5 J; L: ~$ `9 V' I5 w* G+ `Main effect, 主效应3 f# Q" r7 k, f* o$ u0 E4 A2 g
Major heading, 主辞标目# a2 } M! h4 w* s+ K& z+ i
Marginal density function, 边缘密度函数6 U+ ~' p/ e( k- k
Marginal probability, 边缘概率( @# i8 ]+ v0 X! M
Marginal probability distribution, 边缘概率分布
: d3 a* Y& u+ z7 \Matched data, 配对资料' [# [9 Y5 s* }: s6 w
Matched distribution, 匹配过分布9 ~# l t/ Z4 s
Matching of distribution, 分布的匹配, @% k) z! @' y5 N w
Matching of transformation, 变换的匹配% n( w+ h* t; H6 d: L
Mathematical expectation, 数学期望) G1 `2 G" G5 y2 Q# { p! r
Mathematical model, 数学模型
+ t7 s( G. L4 B7 W! D: dMaximum L-estimator, 极大极小L 估计量
. Q$ W1 b! T9 ^- Q/ F5 N9 d4 d% yMaximum likelihood method, 最大似然法
5 x/ L$ x. ?/ x* ]) }Mean, 均数9 q, C* T% q) \/ {
Mean squares between groups, 组间均方2 N: W5 k ?/ i+ r" Z
Mean squares within group, 组内均方
4 }# d; n' t. V8 iMeans (Compare means), 均值-均值比较: |- T- z% |) ?6 ]# E0 f: H+ Q3 Z8 M
Median, 中位数
) Y$ f1 `( b, ^. {+ D O3 x( M# C2 VMedian effective dose, 半数效量
% `; p# |2 P3 h& b9 W$ nMedian lethal dose, 半数致死量
$ ~. m" i. b( a5 M! D& V( kMedian polish, 中位数平滑
j. ] w0 t& C: J; `Median test, 中位数检验6 G+ L% `5 s- S1 F) C' b
Minimal sufficient statistic, 最小充分统计量
9 e' S3 X6 {. ~4 AMinimum distance estimation, 最小距离估计* G% g# w+ a( U3 t# A$ v
Minimum effective dose, 最小有效量' a$ a, J" Q8 M4 V4 ^* d% ?
Minimum lethal dose, 最小致死量4 _2 t6 h! {# J
Minimum variance estimator, 最小方差估计量2 ^. n3 R; s4 \ c
MINITAB, 统计软件包, s6 y; c/ m3 T
Minor heading, 宾词标目- m& l2 g! {/ Y! v
Missing data, 缺失值. n5 [/ I L& e' E9 U, Q: Z0 z
Model specification, 模型的确定3 G$ S$ g7 b1 B. E% S9 V
Modeling Statistics , 模型统计 B% W) ]6 I1 Z
Models for outliers, 离群值模型. C5 @2 {- h" f0 T8 } v% k
Modifying the model, 模型的修正
2 O9 ]: e: z. ^7 |: H* J- f4 PModulus of continuity, 连续性模
# B# o: o D5 X& G) q5 ?Morbidity, 发病率 # U9 }2 }& C: p5 \, r# U! X
Most favorable configuration, 最有利构形
* B, V5 @& L6 bMultidimensional Scaling (ASCAL), 多维尺度/多维标度
& x+ P f7 N0 K! @5 D9 Q6 FMultinomial Logistic Regression , 多项逻辑斯蒂回归
" V9 ?% p! `) i7 t; G" H6 NMultiple comparison, 多重比较
. y9 K' [+ _' q( v: w, _: `Multiple correlation , 复相关
$ J/ f$ S4 q! _1 d+ ]7 eMultiple covariance, 多元协方差
+ v. X+ a: m% z+ XMultiple linear regression, 多元线性回归
2 [# X* k) c! c3 `5 RMultiple response , 多重选项4 W! Z8 Q" k: v
Multiple solutions, 多解& L1 @/ v1 }$ e( C" }! {
Multiplication theorem, 乘法定理
B# R! e6 B" i/ JMultiresponse, 多元响应
! p4 f1 u( t9 V u/ n' {6 HMulti-stage sampling, 多阶段抽样& J' s! C$ X7 |# L0 N
Multivariate T distribution, 多元T分布8 C+ z" S ]6 A: ~; E
Mutual exclusive, 互不相容8 X& j) M% ]# c( A: ?8 A
Mutual independence, 互相独立
2 B: H- t4 E0 w& j6 }' Z* ?. ^, KNatural boundary, 自然边界+ t/ T' b$ E! s" J5 k
Natural dead, 自然死亡
) X! K* r0 A- g6 @Natural zero, 自然零( o6 [- J+ q$ |4 n
Negative correlation, 负相关' P0 y7 n1 Q/ J" m
Negative linear correlation, 负线性相关
1 A2 d3 W3 {2 C1 @& B! r$ y3 CNegatively skewed, 负偏
( l& y6 J5 V$ n5 rNewman-Keuls method, q检验5 D3 Z4 l8 n: m. @2 M1 ~8 s/ P
NK method, q检验 ]% e6 `8 L$ i- ^/ G- x; v
No statistical significance, 无统计意义2 z9 D$ @% n/ V9 J4 i S Y/ d
Nominal variable, 名义变量
" I1 W% s( E! a/ D8 }* UNonconstancy of variability, 变异的非定常性4 _& |5 t4 Q& n a
Nonlinear regression, 非线性相关
/ X* H* g* ?% NNonparametric statistics, 非参数统计
: I4 v& P4 @. ?7 B n5 fNonparametric test, 非参数检验
3 L5 p' u* H- W. J2 F0 ^5 YNonparametric tests, 非参数检验
/ F: j. n& ~7 Q* u8 B! M/ ZNormal deviate, 正态离差
+ M& m+ T; E1 r! F: a* sNormal distribution, 正态分布/ r9 \2 E1 B% \$ Z U
Normal equation, 正规方程组; t8 J7 K, [" t2 x
Normal ranges, 正常范围- @% |# R8 ` I
Normal value, 正常值. H- W. f. m3 I
Nuisance parameter, 多余参数/讨厌参数1 l5 j& k8 Q7 z6 I. w
Null hypothesis, 无效假设 & w! J. g, Z t6 o4 A* Y# w) |
Numerical variable, 数值变量
& r# V A s- `, y& O6 F$ kObjective function, 目标函数# ^& o0 B4 N/ c: N
Observation unit, 观察单位' a# r# I& l7 ^# w
Observed value, 观察值
5 s" q7 o0 u9 p$ P* e8 xOne sided test, 单侧检验
3 Y1 j5 J* Y% x" t- ^) G4 XOne-way analysis of variance, 单因素方差分析
; A* ]) e6 d' R- n! V3 r& cOneway ANOVA , 单因素方差分析
$ h' s3 D: ^, S- S, b3 ?; }( e b" yOpen sequential trial, 开放型序贯设计
/ }* W$ K2 B) b4 kOptrim, 优切尾8 \6 X' m/ q ?. Z5 }/ g3 I" @' _
Optrim efficiency, 优切尾效率
+ Z4 ^& Q, ]8 z% J" qOrder statistics, 顺序统计量: T( }) ]# E8 o2 x# K* [9 Q
Ordered categories, 有序分类
3 u; t! A1 P% \1 Z8 g8 {) h1 d0 XOrdinal logistic regression , 序数逻辑斯蒂回归7 y' [0 F0 ^. T; O) m! G$ v6 s- D4 N
Ordinal variable, 有序变量
; o8 {" o9 `$ \ b f' POrthogonal basis, 正交基
1 l0 D/ z! {8 x8 KOrthogonal design, 正交试验设计
' ~* y7 X% K e, E! dOrthogonality conditions, 正交条件0 T( E% m& X( U% B' M, R+ d6 p0 I9 a
ORTHOPLAN, 正交设计
2 b' e) ]0 Z5 q3 |- ]" e4 k/ QOutlier cutoffs, 离群值截断点4 K8 Y. f' E5 h( K: i9 V, X
Outliers, 极端值. Y, j' S, F2 ^
OVERALS , 多组变量的非线性正规相关
; E' W' a! E! l9 O# G, v7 {7 IOvershoot, 迭代过度
9 B% A& h- f7 p! V9 Y! ?7 }( aPaired design, 配对设计
, h2 T g+ T8 A0 D1 w& aPaired sample, 配对样本
) r3 U. f8 K+ Y i) ?$ J( fPairwise slopes, 成对斜率: J6 d9 B c+ O6 X( F, I
Parabola, 抛物线& \9 e! _& x& m
Parallel tests, 平行试验
6 M J' k$ [7 x, t6 ?9 `" \Parameter, 参数" G8 V' J' d) C# d: U I
Parametric statistics, 参数统计+ C8 k0 G7 e5 D0 |
Parametric test, 参数检验
% {1 Y$ J& x4 J5 J, ZPartial correlation, 偏相关: N* H% h% n; O( O
Partial regression, 偏回归
+ b7 A Z h1 W5 a' y- M0 J4 bPartial sorting, 偏排序- _' D) f. f0 o/ v( \% O: L9 W E3 `
Partials residuals, 偏残差
7 M3 ?4 X' M) fPattern, 模式5 N! H0 `2 E, O: m( f
Pearson curves, 皮尔逊曲线! x* ^9 ^# J9 H) S
Peeling, 退层4 C& Y+ L0 [7 {% `! y4 K
Percent bar graph, 百分条形图
6 n- T$ E% P' Z5 b: ]% N- z! ^: P3 tPercentage, 百分比
' J; `6 b- B$ C1 a: p5 uPercentile, 百分位数. x' J j; ~# `) [$ \0 E* a
Percentile curves, 百分位曲线
R N6 ~# e" ~1 v- uPeriodicity, 周期性+ ?, r, a1 C( ~
Permutation, 排列" C' M$ x- K: E2 v" g
P-estimator, P估计量# R( h# u4 R/ Y5 o5 o1 F
Pie graph, 饼图. _/ ?( w$ A& B4 Q2 X
Pitman estimator, 皮特曼估计量
/ Y! Z. b) b/ _0 YPivot, 枢轴量% z5 i v+ [4 K" H# |. t, l
Planar, 平坦% @; C) c, A' M8 m6 N/ v/ l& A
Planar assumption, 平面的假设
, I! Z, _0 G i/ OPLANCARDS, 生成试验的计划卡1 F7 T9 H5 t) x2 G! `
Point estimation, 点估计
5 b4 V/ Y$ n& t0 P7 y2 m/ @Poisson distribution, 泊松分布
. A3 U$ _7 K6 I( |- E% E! EPolishing, 平滑: k6 ` o7 m6 D+ o/ \3 {! q+ O
Polled standard deviation, 合并标准差
% M! ?& ~ Z& |6 {; LPolled variance, 合并方差/ M0 |5 p+ k, ], _2 R( d
Polygon, 多边图
& w6 s" t% [6 J; N, M' mPolynomial, 多项式' c. {( Y& ], W" P8 {4 l
Polynomial curve, 多项式曲线
1 q9 v$ L+ Z3 |* @; D2 o- zPopulation, 总体: \: L) Y7 h* k4 m. n3 e% e# L
Population attributable risk, 人群归因危险度
" T" |! n l) b+ E& D% Z7 wPositive correlation, 正相关& t9 X8 P2 _3 }) k* R
Positively skewed, 正偏* z5 X# _8 ?2 p4 I+ c0 H" b
Posterior distribution, 后验分布
* b6 F0 Z; B9 {5 Q) s/ yPower of a test, 检验效能
3 f+ y4 C$ l0 A4 B4 O) Z* TPrecision, 精密度2 o/ A+ n% Y& I: H
Predicted value, 预测值
$ n$ ^! M, w0 ]+ Q$ I1 _& _5 M; F# Z! ?Preliminary analysis, 预备性分析
( ^, {; q/ x$ T9 J7 I7 nPrincipal component analysis, 主成分分析
5 T( i$ E1 a0 uPrior distribution, 先验分布; W+ Q) Z3 x. V3 ^+ R! [. B" i( j
Prior probability, 先验概率- F0 S& I$ F B8 `6 p; {% X
Probabilistic model, 概率模型
. P0 {7 j7 j& S0 F8 W8 C, w2 mprobability, 概率
4 Q: ?8 j4 a: n6 ~Probability density, 概率密度
+ ?% A, n3 ]" r+ {* N" xProduct moment, 乘积矩/协方差
& _9 }3 F( I" b" S- o jProfile trace, 截面迹图: ?8 G0 v/ Z: k' D
Proportion, 比/构成比+ N& u9 N( T6 f/ ^- ^. j/ Q+ `7 u5 @
Proportion allocation in stratified random sampling, 按比例分层随机抽样2 p9 F' \# d" h' n, P7 W- T. b2 [1 |
Proportionate, 成比例
* @8 z' u4 h+ f$ F* F# F/ ?Proportionate sub-class numbers, 成比例次级组含量
4 N. {, L; R& bProspective study, 前瞻性调查
( D' @8 j% n: h1 w% UProximities, 亲近性
. J- D( y) n5 q5 rPseudo F test, 近似F检验* u( _9 c- p% w
Pseudo model, 近似模型
: z- w3 {7 \$ v5 b4 J& u) qPseudosigma, 伪标准差6 k2 r2 ^! d; d/ B( E: i' W( C
Purposive sampling, 有目的抽样
0 h3 v d" e2 p5 qQR decomposition, QR分解
2 _/ W0 [* Z% U3 z, G5 Y" bQuadratic approximation, 二次近似/ N! ^) d- |0 X# f( U" p( ?( z
Qualitative classification, 属性分类) y# l' ]# c" Z5 L: T3 j. m# q
Qualitative method, 定性方法
+ X2 X5 [) O: ]* GQuantile-quantile plot, 分位数-分位数图/Q-Q图8 F+ l, R4 i7 K, q
Quantitative analysis, 定量分析
8 p* [- |5 Y5 |0 B" vQuartile, 四分位数
! [6 Y1 u2 S# S- r7 x- t5 g& {( J) ]Quick Cluster, 快速聚类1 U, ^5 ~. V2 X6 J5 `0 w; ~
Radix sort, 基数排序" t( M/ J; }7 ^- Y/ n) v5 I
Random allocation, 随机化分组% \5 k3 M; d4 }; j
Random blocks design, 随机区组设计$ v! k3 ]3 n: ?" d% u! d* ~
Random event, 随机事件" F: r+ x& e7 T5 ^: U& K. b6 `
Randomization, 随机化# F/ o& o$ n: y" ~- C
Range, 极差/全距) n2 W/ \8 ? b
Rank correlation, 等级相关
. w; @7 R# \' q1 {; l* vRank sum test, 秩和检验
W" `" h( J9 g+ JRank test, 秩检验+ u0 o5 V, |! x# ~4 S
Ranked data, 等级资料* p' B' I9 U0 T3 L9 i! L( D t# q7 N
Rate, 比率' R. h7 o+ X# ]" Q, A1 ], ]" ?* M
Ratio, 比例
$ M j& F, d$ V. Q {2 o% V- n$ IRaw data, 原始资料
* b, M) |4 i; ]Raw residual, 原始残差7 p0 ~9 u( B) t4 p; d5 Y& [
Rayleigh's test, 雷氏检验- |2 e5 f- k# |6 T
Rayleigh's Z, 雷氏Z值 1 d% t N% J, O* O( t7 @2 ?/ j
Reciprocal, 倒数, e, @, G% n1 C3 a
Reciprocal transformation, 倒数变换
! a2 w7 {& X5 g8 h$ w+ PRecording, 记录+ Y' s9 d) K: d
Redescending estimators, 回降估计量2 K7 x& h2 }1 I3 b
Reducing dimensions, 降维0 r4 ?' {; o4 ^* ~
Re-expression, 重新表达
: n3 P \7 h |# V9 D9 V9 _Reference set, 标准组
9 `3 X& p* C; ]3 |; N: VRegion of acceptance, 接受域
) X' t8 X# W$ b; L z% @Regression coefficient, 回归系数) s7 i* p3 }7 [8 O8 H' [' O
Regression sum of square, 回归平方和
$ N" ]& y) P! U" WRejection point, 拒绝点
) n5 j2 M5 `2 R+ K" iRelative dispersion, 相对离散度
" Q' L& K7 A5 q9 p7 I4 V/ VRelative number, 相对数
) L: }- N# g7 t9 m. w- h- S: ~Reliability, 可靠性
" u. I( `& c% \0 {; `/ y% K4 IReparametrization, 重新设置参数% B7 l- ^ F- l* l% e" U
Replication, 重复
( |2 h$ T- M j* j/ O1 KReport Summaries, 报告摘要# @. W! e& P0 [
Residual sum of square, 剩余平方和3 {7 N% g+ K4 l; ~2 @' O9 V, J
Resistance, 耐抗性- ^+ ^" q" T" u; `
Resistant line, 耐抗线6 Z( k3 D. i; h. y O/ |' x9 j
Resistant technique, 耐抗技术5 J1 G6 d' I# S
R-estimator of location, 位置R估计量
6 t5 W* M) Q5 q$ x. g; ?R-estimator of scale, 尺度R估计量) M) s+ ~6 L3 f& o" v
Retrospective study, 回顾性调查9 y5 ]! z) ~, S6 H' a/ b% @
Ridge trace, 岭迹
% t# U8 n1 x; z. HRidit analysis, Ridit分析2 p2 y; G: \: L
Rotation, 旋转
, K' m! [8 Y$ dRounding, 舍入: P5 R0 f( `. T% C
Row, 行5 Q9 d: V8 ?2 f/ K, v9 u1 g v& |7 M# x
Row effects, 行效应- q( \: o1 U2 `: G& d
Row factor, 行因素6 }7 b2 S7 n' P
RXC table, RXC表. m4 c' c6 E9 Y* o l/ Q7 L
Sample, 样本 S1 Q& ]0 k' H& K6 s& x4 B1 C
Sample regression coefficient, 样本回归系数, h8 T9 E* d0 U- u/ B, z
Sample size, 样本量
/ W7 X8 y% v) W, D* X! }/ JSample standard deviation, 样本标准差
K' J1 L7 J. k' B) _6 PSampling error, 抽样误差
/ F: b7 u; w6 X. R k: E3 W! h( V4 wSAS(Statistical analysis system ), SAS统计软件包" t5 b0 b0 s z/ d
Scale, 尺度/量表
0 J# l6 {* p7 N3 D; JScatter diagram, 散点图; J6 j2 Q1 H4 r6 } I
Schematic plot, 示意图/简图$ S: Z3 o$ V! b! r. ~
Score test, 计分检验+ t. J' Y4 _* ~8 c) S3 j) i
Screening, 筛检
q7 j3 X1 c2 E- RSEASON, 季节分析
7 k' Z. F6 u+ S4 X1 E JSecond derivative, 二阶导数9 v& a& c: d, p/ B2 w0 W: T
Second principal component, 第二主成分: b& X1 W, @: x" B
SEM (Structural equation modeling), 结构化方程模型
o; H; U( s# M- S5 S+ L- w2 aSemi-logarithmic graph, 半对数图6 A: U( Y8 G3 p( a; ^
Semi-logarithmic paper, 半对数格纸
. o7 C% D: c3 D3 PSensitivity curve, 敏感度曲线
2 }/ d1 D8 |" F2 LSequential analysis, 贯序分析 a+ i2 D2 V. O7 n L
Sequential data set, 顺序数据集. w t/ }4 P9 m! K) \
Sequential design, 贯序设计
% n+ d) j# A. HSequential method, 贯序法4 z. v3 K" S, m3 b) C
Sequential test, 贯序检验法; J3 o M' E7 O' A3 [) b' X
Serial tests, 系列试验4 k* R) w" z6 r) s U8 F, Q3 W/ [
Short-cut method, 简捷法
, m3 F1 m3 b6 @& J" ~8 OSigmoid curve, S形曲线
t6 {3 @0 ~6 i: {. E, X3 A) H4 aSign function, 正负号函数
: X) A8 t3 z* o+ D- e# USign test, 符号检验- A& N% e0 y( { A% r! c w1 Z
Signed rank, 符号秩
+ T( B7 {1 ]' ]* Y9 b" i |8 TSignificance test, 显著性检验/ S2 o* f; x+ d, X. X
Significant figure, 有效数字
$ ~8 b* X: S6 Y- y; l( b& YSimple cluster sampling, 简单整群抽样& j) C0 Z/ M8 E6 O6 U! g+ w( _, x
Simple correlation, 简单相关
: ~ j2 e- E* u qSimple random sampling, 简单随机抽样
k6 @ m ^! p, PSimple regression, 简单回归0 O. M2 E8 Z3 H
simple table, 简单表
( r1 M$ d, I, t, B% Q2 OSine estimator, 正弦估计量
( e" d5 b8 F3 u/ QSingle-valued estimate, 单值估计
5 j) f1 \+ O, X, M9 }, H8 k7 sSingular matrix, 奇异矩阵
. y# \* t- [1 b+ K+ X+ sSkewed distribution, 偏斜分布
5 N1 v% L7 Z& } vSkewness, 偏度/ z W- ~8 |" _3 K0 p2 w: Z
Slash distribution, 斜线分布
+ n* ~0 P; Q# `* b# } X; a4 N8 _Slope, 斜率
: i5 d* k+ B$ T. J4 z0 S% mSmirnov test, 斯米尔诺夫检验
% Y0 n [+ n( V! D' V4 eSource of variation, 变异来源5 }9 G3 `" D2 s5 B7 ~
Spearman rank correlation, 斯皮尔曼等级相关2 h9 K/ E6 w. ^# F: V ~! u, q: X
Specific factor, 特殊因子
, I/ [: J- D# n7 ESpecific factor variance, 特殊因子方差
; g+ x' C6 x% W5 V4 t( q* I1 USpectra , 频谱$ f6 b2 L r- [
Spherical distribution, 球型正态分布5 u5 w+ Q( p! e1 \
Spread, 展布
! p( n8 O/ E; ~3 O+ @2 RSPSS(Statistical package for the social science), SPSS统计软件包- q: D! P' r# |5 c. p
Spurious correlation, 假性相关- C5 Q8 U7 h8 f* F* V
Square root transformation, 平方根变换! R( N& W P3 i% z" y
Stabilizing variance, 稳定方差9 {. }+ K. A w. d3 \2 a2 O
Standard deviation, 标准差6 `$ K8 G" l& k6 s# C- |
Standard error, 标准误, @. i6 i" D/ F+ V/ H+ G6 \" f6 q+ m
Standard error of difference, 差别的标准误 D' [/ C- w, t! {: O
Standard error of estimate, 标准估计误差6 F5 k1 z& T% Z) X! x) c; f3 m$ b
Standard error of rate, 率的标准误
7 {+ p9 d4 G+ s: V0 KStandard normal distribution, 标准正态分布4 u: X7 J1 m9 U' l
Standardization, 标准化
0 _$ |( k, L2 I! d+ S! [Starting value, 起始值
3 e9 w8 V- I$ @, f; S5 aStatistic, 统计量% I0 a$ B2 r' |& r
Statistical control, 统计控制
/ l4 P: V2 n4 NStatistical graph, 统计图
5 x1 k7 x0 I7 i3 H7 oStatistical inference, 统计推断6 q; u1 Q$ W2 Z; n5 |. u, y1 V
Statistical table, 统计表8 [4 e2 J: p4 [ L7 B" \. U" c6 p
Steepest descent, 最速下降法
9 B# E$ S' A Q8 @! ~5 @7 ?Stem and leaf display, 茎叶图# [" S1 s: S3 J, j3 M) X' |
Step factor, 步长因子3 ]" o- ?2 k& C& {; A& N
Stepwise regression, 逐步回归
( s! T+ A. u: R& L' `" DStorage, 存
5 O" ]; \. x: y3 q/ _7 hStrata, 层（复数）
4 H. t4 q W% U5 o- DStratified sampling, 分层抽样
5 D/ I0 S! u. |4 H) T, y, H+ tStratified sampling, 分层抽样
' I; t( Y) i' G( O% WStrength, 强度/ B; o- g& E. P, w2 z" z
Stringency, 严密性
% b- t: D f. M1 l1 a% s2 zStructural relationship, 结构关系
& l8 G+ Z1 Z: u( X/ K7 ?# q T' FStudentized residual, 学生化残差/t化残差6 R# c9 `5 R9 t6 k. R" n
Sub-class numbers, 次级组含量: ^0 |5 Z7 {7 I$ l2 ?0 o
Subdividing, 分割
4 ?' z& ]) y, NSufficient statistic, 充分统计量2 e1 A. D, Z5 G* k& e3 M
Sum of products, 积和) F: \! W/ y W" E( a
Sum of squares, 离差平方和
8 o/ U5 C/ R9 WSum of squares about regression, 回归平方和
7 o8 ^; n% H/ c t( a& [/ CSum of squares between groups, 组间平方和: i& f& V/ X( P% Z
Sum of squares of partial regression, 偏回归平方和" K% g0 U. o( J. J/ |1 c0 m
Sure event, 必然事件
6 G5 Z* Z2 T, K/ a2 t" Y5 Y/ |Survey, 调查+ u, |. J! L- F5 s! O7 O
Survival, 生存分析& Q3 n5 H1 U/ D& J, o! b( y$ ^: q
Survival rate, 生存率- h, l5 y$ _1 m) N
Suspended root gram, 悬吊根图) @* E2 V" r# E0 T
Symmetry, 对称
4 d- K$ L# w; C! @Systematic error, 系统误差
! X6 L6 f# Y: p; C& lSystematic sampling, 系统抽样
) W5 p" n q( Y0 vTags, 标签! L% H1 w, ]: ?# ?4 }: G! E
Tail area, 尾部面积
! r! J* H0 G) H HTail length, 尾长
6 i6 h7 N: l& @' Z+ x+ |Tail weight, 尾重
+ |9 K- `+ p: ]# [. [- Q( \. }Tangent line, 切线
5 ~" r7 B* C( s8 e3 c3 x oTarget distribution, 目标分布; R2 a- N8 ]7 X) ? q- |
Taylor series, 泰勒级数
# \6 o/ {' ~- F6 U# [5 kTendency of dispersion, 离散趋势
4 |9 a. x. h6 w4 ?$ k7 i" X9 i0 sTesting of hypotheses, 假设检验
8 `2 H) M! G4 s) HTheoretical frequency, 理论频数
% t4 C- N# E% E$ T! T OTime series, 时间序列& C j3 B8 n8 ]3 q' l: H9 K
Tolerance interval, 容忍区间
. [2 B# ~, t7 ^* p7 W$ KTolerance lower limit, 容忍下限
0 s. w' S p) h) `3 H( LTolerance upper limit, 容忍上限
! r( P1 x3 x+ _Torsion, 扰率
3 K: r1 B7 p2 PTotal sum of square, 总平方和& A X4 K6 c* Z3 J! M
Total variation, 总变异
7 w) {* T& \# Z$ ?/ }6 v% [1 hTransformation, 转换
! E0 N( ~3 F! ~: V2 ATreatment, 处理
6 A0 d$ @2 y+ y" U( t; D# \Trend, 趋势
. E+ z0 O# o) a6 }* v0 \4 BTrend of percentage, 百分比趋势
1 ]" i+ |9 w( [, I" z, ]/ e( TTrial, 试验
! n+ ~0 [4 Z* G' R4 n8 tTrial and error method, 试错法( i" @/ X Q5 ~
Tuning constant, 细调常数, t0 M2 H2 z7 R# m, ?7 p5 f
Two sided test, 双向检验2 I+ p% n0 t& i7 U' ^
Two-stage least squares, 二阶最小平方" c& m4 l; W$ Y9 z4 ?
Two-stage sampling, 二阶段抽样
% b" {- f3 D( c* v7 ZTwo-tailed test, 双侧检验% D: u- b' J$ _# k- A3 R1 p1 `8 {) \
Two-way analysis of variance, 双因素方差分析7 [8 T. c' O. H" B% Z a5 d# R3 N
Two-way table, 双向表, q8 r) A' Y! e6 R7 q- E `7 h
Type I error, 一类错误/α错误
& R. a9 R5 E) ?$ RType II error, 二类错误/β错误$ g2 y6 S: u* Q( r5 ~
UMVU, 方差一致最小无偏估计简称) ^; E$ ^- a' Z; s4 C
Unbiased estimate, 无偏估计
$ ]0 g# y: W2 CUnconstrained nonlinear regression , 无约束非线性回归
7 p: b( Q% x6 O( m& TUnequal subclass number, 不等次级组含量, h4 m1 h' z/ W6 }
Ungrouped data, 不分组资料
C7 v$ W3 f. h9 f% X! lUniform coordinate, 均匀坐标
/ K. C" |8 b9 q; P) J* FUniform distribution, 均匀分布/ p* b# n1 i) q
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计1 }1 L% s- w) q
Unit, 单元
4 J/ T- o3 f/ u' u( i7 m; |Unordered categories, 无序分类
F3 A5 o N+ Q9 Q) k3 x3 yUpper limit, 上限
" N5 m3 M5 o. G; w Z* B+ c/ AUpward rank, 升秩/ i: }1 B* F- R% j
Vague concept, 模糊概念# a' R" l) \) B$ t
Validity, 有效性
5 b, ^* G4 t7 m4 @. w" NVARCOMP (Variance component estimation), 方差元素估计
& m9 i, s& h& L) Y( MVariability, 变异性
& h0 e5 j( V9 Y( g3 H3 uVariable, 变量
2 C4 D8 X% F4 C, A& TVariance, 方差
. Z# N2 z/ W# }3 }Variation, 变异& |7 O' S/ s" O9 O8 E3 b W: j
Varimax orthogonal rotation, 方差最大正交旋转5 U$ ]6 ^9 N( O" {+ ^
Volume of distribution, 容积
n/ c* z0 w/ F' KW test, W检验
: `+ _3 b6 Y. |: Q. u- zWeibull distribution, 威布尔分布
# `6 G) |" E4 z: F( [( s* b( [$ M' n0 AWeight, 权数
7 a8 @! h' q8 tWeighted Chi-square test, 加权卡方检验/Cochran检验, m( I0 I' x. S# ^$ b/ J
Weighted linear regression method, 加权直线回归
: n0 _- z6 c9 yWeighted mean, 加权平均数% [, w( ]+ l R6 Q# m; ?
Weighted mean square, 加权平均方差
& ]$ {" c/ q* p6 }* B, ^Weighted sum of square, 加权平方和
, f$ E6 o7 r( K1 S( f$ ~Weighting coefficient, 权重系数
9 x2 e i! ~4 M* W3 jWeighting method, 加权法
! q' x* C% _4 R4 h8 ]9 ^6 IW-estimation, W估计量
" C9 a0 g) [6 z& J6 r9 zW-estimation of location, 位置W估计量* o: f4 E7 n: d R6 M4 S7 X, n1 q
Width, 宽度9 W. y( n& _! w% `( `
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验- M+ c% J0 |: ]
Wild point, 野点/狂点
; T* m; K& k. C9 S8 R! e) ?Wild value, 野值/狂值
8 O9 i' [' j) U# I* sWinsorized mean, 缩尾均值
: U/ @# e" d) X" WWithdraw, 失访 7 [3 x" k( i- N6 k" q+ A
Youden's index, 尤登指数
; y N4 A6 i, kZ test, Z检验( f% S3 B$ d8 f* k; _7 \: ]' v
Zero correlation, 零相关
u0 k7 g1 }, @# n8 W7 g' t) }Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
