|
|
Absolute deviation, 绝对离差
5 U2 A4 p8 `2 f/ v- PAbsolute number, 绝对数7 A0 {& k- x! S; _/ Q: |$ T/ |2 h8 M% n
Absolute residuals, 绝对残差
9 p0 B$ {6 s2 `7 x1 O9 ~ e& JAcceleration array, 加速度立体阵
. H! g( w! k6 ^: b- a/ uAcceleration in an arbitrary direction, 任意方向上的加速度: S) t" h: H8 O
Acceleration normal, 法向加速度
; \0 x @5 T6 ?2 R* A$ P8 dAcceleration space dimension, 加速度空间的维数9 M* m W" `5 m. ?# |! J! |. s; Q
Acceleration tangential, 切向加速度
- [: ^$ l& Z8 O4 D$ v/ Q5 i$ yAcceleration vector, 加速度向量" O3 C! d0 c4 h* h8 ?
Acceptable hypothesis, 可接受假设* Z9 t- k6 D& k( V/ j8 p. t
Accumulation, 累积
& H; I3 ~% G5 Y7 r; @" Y3 N. `Accuracy, 准确度) N7 g- Y$ a7 K2 n: {
Actual frequency, 实际频数- f: v9 j8 g4 ^# e9 E
Adaptive estimator, 自适应估计量
* r' [4 K6 M7 TAddition, 相加" i0 L6 s4 s! t2 n
Addition theorem, 加法定理
& ~4 E1 W& p) m& t0 z( TAdditivity, 可加性
% Z0 ?# ^/ ~! O( l, UAdjusted rate, 调整率
5 z( v$ ~. r2 U9 c# KAdjusted value, 校正值9 V6 o2 t; w& [, e& }+ A9 T
Admissible error, 容许误差
% ^! j5 E4 S' r! K4 JAggregation, 聚集性1 T: ^* M3 O _% [3 o# {0 i% G% E
Alternative hypothesis, 备择假设# Z- m0 p5 B- t: ^" v3 `
Among groups, 组间- c5 q; I6 E& g$ k, t+ }
Amounts, 总量$ E+ b |2 S U* n( u
Analysis of correlation, 相关分析/ x8 F: p* L' \/ {5 K
Analysis of covariance, 协方差分析: }! T7 C4 C( ^2 B* r9 G; R
Analysis of regression, 回归分析8 v c5 R( L4 R1 b$ Q$ I0 y
Analysis of time series, 时间序列分析/ d9 r, t& @& z9 t( P9 L1 U
Analysis of variance, 方差分析
8 N4 i* i1 r; u: fAngular transformation, 角转换' p0 u# T" R/ `+ l8 n
ANOVA （analysis of variance）, 方差分析8 d8 E+ K; J/ }' r% f" s1 `( W
ANOVA Models, 方差分析模型
$ L- r, Q2 y8 G$ e& e+ B2 [Arcing, 弧/弧旋! n, |5 J' }0 |- p& ]: m
Arcsine transformation, 反正弦变换
. O+ L4 U } |7 f& VArea under the curve, 曲线面积) s; g; K: }8 u% E! ]
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
- ^; N, O3 |3 Z. U) g$ {: M; t- J& |ARIMA, 季节和非季节性单变量模型的极大似然估计
( m# K- M7 j1 `5 YArithmetic grid paper, 算术格纸2 g* e0 [$ f$ p9 o& F7 c- Y& |2 G
Arithmetic mean, 算术平均数
5 K& c$ O8 h/ ~) KArrhenius relation, 艾恩尼斯关系
# s( C4 c, ]0 v/ @Assessing fit, 拟合的评估; o ~. `& r' Y( Y$ [% l
Associative laws, 结合律- Y8 {/ w% `! p3 j7 V' u2 M
Asymmetric distribution, 非对称分布
6 O4 L# A: O( @% S' eAsymptotic bias, 渐近偏倚
v% g9 c' f/ b' s5 B4 v& W. O6 _Asymptotic efficiency, 渐近效率. m- n+ U" r: x6 C0 {
Asymptotic variance, 渐近方差7 ^0 |8 P/ b( E+ }, r2 I3 c
Attributable risk, 归因危险度1 z, b& ], @4 j
Attribute data, 属性资料
! B4 m' C" a! S9 @7 XAttribution, 属性
/ I1 O8 l. P' UAutocorrelation, 自相关+ Q# s, ]" V! o2 b8 d0 p! @
Autocorrelation of residuals, 残差的自相关
8 V. \, ]1 F. r- v" M' BAverage, 平均数% V) O) w s: U. P. A A1 W8 h; a
Average confidence interval length, 平均置信区间长度
1 {) j9 p. \2 D+ q* VAverage growth rate, 平均增长率
2 d; }5 F0 X; @: o9 D3 e, gBar chart, 条形图
! I! d6 A# l! @, x n) K, GBar graph, 条形图9 \! D k* V" E6 Q7 O$ y6 Y5 J
Base period, 基期3 j" l0 f0 b* z& k- D
Bayes' theorem , Bayes定理. S U# R E# V1 ^
Bell-shaped curve, 钟形曲线2 U; S9 Z% O+ G$ `
Bernoulli distribution, 伯努力分布
% p+ F' s* i8 [% n" c( g1 oBest-trim estimator, 最好切尾估计量
/ z$ s) J0 ~6 y; f, QBias, 偏性
4 F* i% {' v7 E; i- s/ r" d0 zBinary logistic regression, 二元逻辑斯蒂回归
5 {) K5 b0 G FBinomial distribution, 二项分布
$ u4 z3 n- {9 IBisquare, 双平方
9 v4 Y) B1 L8 U/ f' mBivariate Correlate, 二变量相关
% q/ _, b* y( SBivariate normal distribution, 双变量正态分布* X- U( i: b3 y* D0 Y& `
Bivariate normal population, 双变量正态总体
! D2 E: H6 k* z/ c, A V8 XBiweight interval, 双权区间, v! g8 V' S. w
Biweight M-estimator, 双权M估计量
8 a6 ? f. p h* @! j3 ABlock, 区组/配伍组) }9 g5 G# S7 R7 n t$ @- k$ F
BMDP(Biomedical computer programs), BMDP统计软件包
! n1 J$ p& Y; GBoxplots, 箱线图/箱尾图
% P5 _/ e4 T8 L; ^# S5 d) h- ?Breakdown bound, 崩溃界/崩溃点6 h/ K# b- O& h: i' M
Canonical correlation, 典型相关
( ]: @' J. T* N2 V/ W* eCaption, 纵标目4 U$ m0 J0 }4 m, L- e- B
Case-control study, 病例对照研究9 _2 \( ~8 q7 k! z
Categorical variable, 分类变量
" m6 G# O% M6 W' P0 ^Catenary, 悬链线
: x& a& n2 j XCauchy distribution, 柯西分布3 R! W' m! g- e
Cause-and-effect relationship, 因果关系: B% {. C8 F$ k
Cell, 单元; {5 o; ` Q) L& b4 ]
Censoring, 终检" F- D0 N! {3 u: H3 @- C2 ^
Center of symmetry, 对称中心
U2 E$ m4 m% B$ UCentering and scaling, 中心化和定标
, K4 m! D4 ^- }+ KCentral tendency, 集中趋势
0 ^. V9 S, M7 j2 S4 k0 nCentral value, 中心值3 E3 d6 {+ b3 |* R2 T
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
" W7 N a! h, }Chance, 机遇
8 p0 J3 k( B# D* Z+ P7 ?Chance error, 随机误差) l# {' Y% u) R8 v
Chance variable, 随机变量! A. U6 w: h8 x- i. h3 ]) z
Characteristic equation, 特征方程; A- f5 V, Y. c2 n2 H
Characteristic root, 特征根
6 R5 |. b( f: S" S7 R9 QCharacteristic vector, 特征向量
- m& I7 J' Y" L+ {, o- pChebshev criterion of fit, 拟合的切比雪夫准则
2 |( w( p/ }$ cChernoff faces, 切尔诺夫脸谱图5 _3 W" p! \5 ?; S: g& {: f
Chi-square test, 卡方检验/χ2检验
r, T9 @6 s3 f; W9 B+ gCholeskey decomposition, 乔洛斯基分解
7 p8 _: q6 i/ \- YCircle chart, 圆图
" D7 I8 g8 y7 J oClass interval, 组距# Q/ O6 Y# P; ?2 F" o' I
Class mid-value, 组中值/ B. E& Q# ] C9 S5 z( f" N
Class upper limit, 组上限
/ _$ q0 @" S1 y1 b& f6 I: eClassified variable, 分类变量* [3 S% x8 u3 `5 ?' O* `
Cluster analysis, 聚类分析
- S2 w' G* P5 c z! D& n; W$ Z' MCluster sampling, 整群抽样5 q# D: i$ D( I8 }/ A" G
Code, 代码
9 a7 t. ?6 F# e" q8 W* Y8 ~Coded data, 编码数据
3 L: v2 n6 r0 m3 n4 FCoding, 编码
7 b1 ^4 j# X% Z+ oCoefficient of contingency, 列联系数
3 x* x9 y2 A- d: aCoefficient of determination, 决定系数
6 |$ D# D5 _; b4 G( _ z. m: iCoefficient of multiple correlation, 多重相关系数7 U1 n, h+ q$ ~+ x' F5 q& m
Coefficient of partial correlation, 偏相关系数
2 a+ F' s/ e$ e c5 _& J5 BCoefficient of production-moment correlation, 积差相关系数# @2 b: Q8 U) P5 F# m& b5 W
Coefficient of rank correlation, 等级相关系数5 I M" X$ b" H/ K
Coefficient of regression, 回归系数9 A' p' e% `/ {0 }) B
Coefficient of skewness, 偏度系数9 ` n' x+ U5 i& _2 q
Coefficient of variation, 变异系数) }8 ]- m. P N' j: P7 H* v5 U+ K
Cohort study, 队列研究# l. [9 \7 t& y3 M2 l p l
Column, 列
4 Q1 ]- a7 Z. ^! m$ YColumn effect, 列效应
+ I, z/ G- s2 Q: k9 z5 C( ~4 _Column factor, 列因素6 T1 d( i! Z) I1 D1 G3 D
Combination pool, 合并
: a; E, M) B! T5 c# g0 P5 sCombinative table, 组合表% ]4 d* k" T* L, g" S
Common factor, 共性因子, V: P5 E$ \2 W9 J8 g4 j3 c
Common regression coefficient, 公共回归系数: }/ Q4 p) F0 f' z/ _0 S
Common value, 共同值. c L9 |2 C% n) f/ C! J
Common variance, 公共方差
6 [3 J) y* Q4 xCommon variation, 公共变异! ~+ [# `. P! ~
Communality variance, 共性方差
( x4 P& C- ?6 P: P: x7 ]& LComparability, 可比性
8 \, Z; o2 l6 L4 x: A; TComparison of bathes, 批比较( i5 s8 k2 c& p& J6 i& Q/ a* _) h
Comparison value, 比较值
# R8 h+ u8 Z5 U: k& y5 U5 w& tCompartment model, 分部模型
1 c% y0 R B2 k6 R% w) h) d# SCompassion, 伸缩
) U( s/ _& K! v1 IComplement of an event, 补事件, U$ F9 g4 N% a2 O3 {2 J
Complete association, 完全正相关
& i( J! O' d8 z' X7 @# |8 YComplete dissociation, 完全不相关
8 E% @( G, M, C9 a$ jComplete statistics, 完备统计量# T) O; n4 m# C
Completely randomized design, 完全随机化设计
( n6 H. o) K1 T8 s9 @Composite event, 联合事件
1 ]; v I& B0 rComposite events, 复合事件9 Y+ g+ S. f5 o% z* X
Concavity, 凹性
( P, ?% H9 N( ZConditional expectation, 条件期望
+ }) u2 ?. }$ \0 Z7 \/ v+ u0 HConditional likelihood, 条件似然9 b* [8 {- z( L- k2 s; y
Conditional probability, 条件概率9 z2 |$ M' r. s
Conditionally linear, 依条件线性7 c. g5 q% X- J+ b6 Q
Confidence interval, 置信区间) W( C6 _% o* Q$ @$ V- a- M1 Y
Confidence limit, 置信限( a1 |" c+ W, L4 z
Confidence lower limit, 置信下限0 [- ?* d; m! o( o! a- Y
Confidence upper limit, 置信上限
4 S% s m3 H6 r) w8 `1 E6 ?/ z: xConfirmatory Factor Analysis , 验证性因子分析
3 q( W' C" L# k/ JConfirmatory research, 证实性实验研究
2 E) g5 {3 g/ _& T7 VConfounding factor, 混杂因素
; @% _: ^4 l6 r: S5 S& @9 r0 uConjoint, 联合分析
: H3 _4 t8 ^+ R" V0 B2 eConsistency, 相合性
3 B+ \8 n$ ~0 [; u, I. V( ?Consistency check, 一致性检验
# X- y) V8 E G$ B/ r! l# n" jConsistent asymptotically normal estimate, 相合渐近正态估计( j. m8 \8 \ {0 `6 q3 B
Consistent estimate, 相合估计: a+ j5 o% y4 ]7 h$ t
Constrained nonlinear regression, 受约束非线性回归
) U8 O/ s6 f% u( c+ }Constraint, 约束2 p; x4 k; g5 g; u8 o
Contaminated distribution, 污染分布
/ o2 A' Y7 v% S% w) L- c' T1 ~# xContaminated Gausssian, 污染高斯分布; Z$ g& G4 g( f8 V0 g
Contaminated normal distribution, 污染正态分布; _) u& L9 l' }" u. w
Contamination, 污染
: M. j1 ^0 e$ M( TContamination model, 污染模型
9 N7 |' G+ |( k* [" ZContingency table, 列联表
7 w3 v* f0 I5 f0 nContour, 边界线# M* h* I0 S$ p O& ]
Contribution rate, 贡献率+ `& \% e/ {1 R
Control, 对照) o" m0 P3 W9 B4 ~
Controlled experiments, 对照实验
3 `8 R5 D! k4 t5 [Conventional depth, 常规深度% o5 k$ [# Q4 ^# R/ `
Convolution, 卷积
9 @' v q' ` e2 F" DCorrected factor, 校正因子
: }* a8 Y7 D8 uCorrected mean, 校正均值1 C, _" ^! c7 A0 O- i
Correction coefficient, 校正系数1 _ e {$ U8 n( t, i* }
Correctness, 正确性5 C' w& k; g* Q' G R2 H
Correlation coefficient, 相关系数
9 h+ q0 Q1 K( aCorrelation index, 相关指数
$ j3 v3 D( m6 `- J& g I0 ^' Y* LCorrespondence, 对应3 o% Z/ [" n3 m4 @: O
Counting, 计数& C3 M$ C1 d, [ R7 q4 e
Counts, 计数/频数; J3 m" a( a3 N" q; b. k( Z
Covariance, 协方差
9 z9 i$ V; @) y8 L( I1 o7 OCovariant, 共变
! d1 S! `$ h( @( f- W# yCox Regression, Cox回归
3 c, z5 P( z; D; J1 ]$ ^Criteria for fitting, 拟合准则& D1 B: U# ^. a- a: N( ~$ \- |
Criteria of least squares, 最小二乘准则
- P; i" R% I* {2 p' p! z7 r" ~Critical ratio, 临界比9 G& i6 v( M% ]; |$ R
Critical region, 拒绝域' b6 h. r! k% l
Critical value, 临界值
' K4 w8 [% c$ ~# f, Q5 e- VCross-over design, 交叉设计6 i7 O1 [1 u. u6 h2 K
Cross-section analysis, 横断面分析# `! R! H" T6 s& ^0 p/ f% B
Cross-section survey, 横断面调查3 L/ w: J6 R, z- Z' F7 P4 f
Crosstabs , 交叉表
4 e+ G0 b6 ^% m0 a5 Q* L3 xCross-tabulation table, 复合表. U7 j2 R3 P9 j6 U; Y+ I8 @
Cube root, 立方根" ]% |, \* C8 V+ }0 y9 J
Cumulative distribution function, 分布函数* D. x7 C, F9 f; m2 H5 e
Cumulative probability, 累计概率
: D# Y: U' T' v) qCurvature, 曲率/弯曲8 P8 [: ?$ _! R$ i' v2 B0 r! p0 V
Curvature, 曲率
& C8 M$ }5 i$ ~3 y3 nCurve fit , 曲线拟和
( |& v- r$ s7 z4 h$ P2 }% ECurve fitting, 曲线拟合3 N8 X; F, u9 ~5 ~3 j8 C- x/ ?
Curvilinear regression, 曲线回归
+ Q, o9 N2 R' j4 RCurvilinear relation, 曲线关系
/ z$ p4 J, E1 c6 R# YCut-and-try method, 尝试法
( Z) C+ Y" Y0 v" K. ?/ e/ b8 \7 eCycle, 周期! n9 Z8 e' h, l) K1 H" s: C
Cyclist, 周期性
0 H- O' I/ d# {; {3 s5 K7 A) gD test, D检验- c/ `1 ^) A2 K I2 d, x/ u& Q
Data acquisition, 资料收集
. `$ a# m1 D/ n4 u+ Z* k4 GData bank, 数据库/ `# v4 C9 r. t. t4 | i4 m
Data capacity, 数据容量0 ?* G) z. z: C ^; m" ^7 k
Data deficiencies, 数据缺乏0 H% J5 W' I" a
Data handling, 数据处理. _2 {: i6 y0 Z( B5 w+ X+ ~' |
Data manipulation, 数据处理* y6 ^& x" y7 I1 Q* ?0 u
Data processing, 数据处理$ _: o J! O6 ]4 h" Z! x2 F
Data reduction, 数据缩减# R; n' u/ J# ?6 i9 ~5 D3 P
Data set, 数据集
' w& g( W7 r0 o% `1 e: r$ F4 sData sources, 数据来源
9 B/ }, }* D6 NData transformation, 数据变换+ E* g" Y) h; z: x: P
Data validity, 数据有效性4 Q3 w& |( U+ }' i3 u& D' E: N- |
Data-in, 数据输入6 p8 K' w8 P9 i) l3 d& l1 P
Data-out, 数据输出( m* I. t& P& E+ m W) P
Dead time, 停滞期1 G5 p, ~2 [# X9 ?6 E: c3 Q
Degree of freedom, 自由度: |7 u- n5 ~- B8 C+ d2 s
Degree of precision, 精密度
|2 J# e$ v* KDegree of reliability, 可靠性程度
2 y" ~2 y0 a1 B% t$ yDegression, 递减- w) T% J0 U+ G
Density function, 密度函数9 f$ h- C1 \# Y7 L# `# Q1 T& b) ^
Density of data points, 数据点的密度+ g# q/ p) v" c* n
Dependent variable, 应变量/依变量/因变量 I* S$ K4 k2 O" U
Dependent variable, 因变量" @7 f V3 [$ U" D
Depth, 深度
- @9 q4 ~4 T( h- IDerivative matrix, 导数矩阵
4 |, T! N" _% l8 ]) y9 U/ aDerivative-free methods, 无导数方法0 k4 Y9 S7 L! P
Design, 设计
8 h$ m# K4 ?, M' V+ d7 g& JDeterminacy, 确定性
; `0 G, }7 e& s+ C* vDeterminant, 行列式
, ]# X3 y+ N0 m& U7 ] oDeterminant, 决定因素 z8 `+ x, S2 f2 O
Deviation, 离差5 h+ G$ ]& ?6 E) K) N# X5 Y4 G
Deviation from average, 离均差4 f( Q! q3 g8 N B/ G, T- d" K
Diagnostic plot, 诊断图
H+ q8 D4 p7 V1 c. l J* `Dichotomous variable, 二分变量* J$ v3 q' [+ g1 h h2 Z5 i J* u
Differential equation, 微分方程
& F; r* h9 ? w. sDirect standardization, 直接标准化法6 t" U3 p2 C: K! v) B
Discrete variable, 离散型变量3 D, m+ }4 o& Y! Y* g! P
DISCRIMINANT, 判断 4 L8 Q! A; l+ V% |
Discriminant analysis, 判别分析! L: A5 G7 x$ H8 u$ S; i$ \
Discriminant coefficient, 判别系数
7 _1 v% U2 B! ^( x& D+ h6 [2 {Discriminant function, 判别值
: \0 J0 h0 ~1 J% nDispersion, 散布/分散度2 r2 }0 Z/ u7 J; G! m
Disproportional, 不成比例的% o2 }, ]5 b0 e
Disproportionate sub-class numbers, 不成比例次级组含量
6 j: w/ Q2 b, u2 q1 gDistribution free, 分布无关性/免分布
) U5 O5 O( |. E8 \; z* ?& PDistribution shape, 分布形状4 r8 Z7 E5 X; u! e& d$ z
Distribution-free method, 任意分布法
2 _8 B* v# m& y: \Distributive laws, 分配律 `, A+ a4 }$ D$ Z. K# s
Disturbance, 随机扰动项/ t- o6 m' w6 e% E! R: M T
Dose response curve, 剂量反应曲线
0 n' C' U7 _5 G0 ]+ F1 XDouble blind method, 双盲法
2 k! j8 Q" g" DDouble blind trial, 双盲试验
. [( g! W K3 C" UDouble exponential distribution, 双指数分布
# }! |3 K7 \6 u# }8 t- q9 ODouble logarithmic, 双对数, d0 X& D+ S# w' i6 h
Downward rank, 降秩
/ v1 _9 T! A7 b- o$ x( l4 [9 wDual-space plot, 对偶空间图) x- w5 z9 ]) E/ j' ^! m9 z/ c
DUD, 无导数方法
0 n" A0 G5 n+ n+ y) tDuncan's new multiple range method, 新复极差法/Duncan新法
3 H- k) M8 m3 F; A! z# w4 eEffect, 实验效应: n+ b4 s8 v2 [: \: D- x8 p
Eigenvalue, 特征值' r0 g1 {5 M Z( H2 h" q% Y/ {8 u
Eigenvector, 特征向量8 o$ V& ~% c8 h1 W+ U: R
Ellipse, 椭圆
0 g3 `# B l7 M0 IEmpirical distribution, 经验分布
" K) G. L8 Q) N5 U9 CEmpirical probability, 经验概率单位
: W9 \. ?2 h; N4 X7 v0 w& C; z4 FEnumeration data, 计数资料7 ^( i5 U n: F9 Z m
Equal sun-class number, 相等次级组含量
5 q2 K: V7 Y1 B9 cEqually likely, 等可能- D2 J' \' [7 @7 ^( `- k1 \4 j
Equivariance, 同变性
# z4 r$ U) r5 cError, 误差/错误
( z2 m& `& s# N5 AError of estimate, 估计误差
6 B. ]2 y- ]/ n* s) L% Z" o0 V Q! U$ AError type I, 第一类错误
9 y, F Q0 `& g- V0 y1 DError type II, 第二类错误
+ a2 f5 c# S7 X' s# D$ sEstimand, 被估量3 J. ^! C& X+ O* }1 @' M; d
Estimated error mean squares, 估计误差均方
; | }5 E0 Q0 S2 D8 L. {Estimated error sum of squares, 估计误差平方和 _5 h6 _' E, D/ P; M; w" t8 P
Euclidean distance, 欧式距离
" d! a/ D+ Q% \$ T/ X2 v. w: mEvent, 事件
! V7 K; k9 A: ^9 i) rEvent, 事件9 t1 P" H3 q/ N0 x1 x3 A' e' _
Exceptional data point, 异常数据点
1 K' z0 z/ u2 J: Z0 d& TExpectation plane, 期望平面
# V2 A, [7 P! R7 y/ g2 w7 UExpectation surface, 期望曲面. ^3 `/ ?' G9 p5 Y; U
Expected values, 期望值9 m7 `# K9 O% C
Experiment, 实验
/ N Z- s% O2 X! BExperimental sampling, 试验抽样
! h9 r$ e9 T% p# [/ ~5 B rExperimental unit, 试验单位' o) o, q ~$ ?' ]7 W
Explanatory variable, 说明变量+ W% F4 A3 T6 v3 t1 C8 H
Exploratory data analysis, 探索性数据分析, \3 Y1 L5 c8 S+ T- h/ J. i- O
Explore Summarize, 探索-摘要
5 @9 D# p1 e" Z, O( hExponential curve, 指数曲线
4 z2 I l& L7 @! F* C+ {Exponential growth, 指数式增长
; f2 q- ^$ \8 g% r A( y" J$ LEXSMOOTH, 指数平滑方法 " D* B, M- Y& ?$ P: e" @
Extended fit, 扩充拟合
( h7 q1 n D! ^6 H5 D w! w1 B( oExtra parameter, 附加参数
) I8 V+ ?% {5 ~9 NExtrapolation, 外推法% s4 m2 l% J* y
Extreme observation, 末端观测值/ [4 F/ c# d5 F3 c
Extremes, 极端值/极值+ I( K/ y6 ^2 X* R: {
F distribution, F分布# v9 l9 S; g% Q
F test, F检验
8 ]. f4 F# u. f- f+ t3 I. qFactor, 因素/因子
+ M8 b; n; q* p7 XFactor analysis, 因子分析' i1 O W5 O9 ]
Factor Analysis, 因子分析5 ~3 { s( o$ s1 _" H7 \% u/ b
Factor score, 因子得分 / C Z# x& E1 G$ k7 }" _/ x
Factorial, 阶乘
' t) j1 O- }8 ]2 }Factorial design, 析因试验设计
: Y4 P! r$ j6 e/ EFalse negative, 假阴性
: G1 Z* t7 {1 vFalse negative error, 假阴性错误( D, ~% a0 A+ J
Family of distributions, 分布族6 y5 t9 j9 T+ l: ]
Family of estimators, 估计量族
# o! N, U; A( c# h, n5 ?1 P# UFanning, 扇面3 X, f' k; x+ ^8 T2 v$ ?
Fatality rate, 病死率
@; P$ @7 S1 l; h: b& N. [% fField investigation, 现场调查9 s. l& y3 l2 y
Field survey, 现场调查
5 U* e8 X4 |1 R+ ~) U P8 \- FFinite population, 有限总体. p1 F$ T/ ?' y4 n( V0 v
Finite-sample, 有限样本" l: b) b0 m2 h* S. w
First derivative, 一阶导数3 H7 a0 C% Z7 q
First principal component, 第一主成分
/ {) c& j, U) l# ]First quartile, 第一四分位数
1 X+ z6 b% A$ RFisher information, 费雪信息量, |3 Z2 Q+ k4 G( S$ J
Fitted value, 拟合值
, a' t5 r% E: r* {. ]$ ]$ A# [0 TFitting a curve, 曲线拟合
2 d& w" o* h2 D9 u* v1 L- v, n+ ~Fixed base, 定基
' J* ?7 m( G- K0 XFluctuation, 随机起伏8 O5 g( O# G* S) ?2 H, f0 |, H
Forecast, 预测
! K: A1 }/ g9 X% PFour fold table, 四格表
; _7 K7 x" G6 r' j' IFourth, 四分点
6 T) k+ g( L( v5 o/ N6 kFraction blow, 左侧比率5 @8 C+ {, h9 C! o
Fractional error, 相对误差
! v( _7 Y$ n) b& ?6 s, V3 M mFrequency, 频率
# y' A, }1 m2 B9 t# N: nFrequency polygon, 频数多边图8 S6 V& R: v/ Y1 F
Frontier point, 界限点, l: W2 i* m/ x. w1 k+ ^& ^
Function relationship, 泛函关系" W" @. }: n& g" `" B, ?6 w% R
Gamma distribution, 伽玛分布
, u* {/ {9 V* K4 TGauss increment, 高斯增量: [3 {& @6 C; Z& L* ^
Gaussian distribution, 高斯分布/正态分布
0 @4 a5 V' B rGauss-Newton increment, 高斯-牛顿增量
5 Z9 H" [6 V6 @. W, lGeneral census, 全面普查# q) K* y# X- V; V+ [: a. r
GENLOG (Generalized liner models), 广义线性模型
! x' m$ r- [8 r6 C3 i% A: [7 eGeometric mean, 几何平均数, g7 @0 ?* j% v6 q
Gini's mean difference, 基尼均差
+ {1 C3 ]7 _) g, P3 r, DGLM (General liner models), 一般线性模型
% m D* {' d8 k4 YGoodness of fit, 拟和优度/配合度( y1 p/ m/ j" j" x; y7 q
Gradient of determinant, 行列式的梯度) O+ ^/ \8 z/ l. Q
Graeco-Latin square, 希腊拉丁方
- T" n4 t* l3 k( T) MGrand mean, 总均值; l" U3 f4 X( i3 {+ H/ Q, |! t
Gross errors, 重大错误
7 ~5 l1 Z* t' c d a) {Gross-error sensitivity, 大错敏感度
5 T7 H3 q% X2 P, J t) q' ?# {Group averages, 分组平均
5 ]! J+ j z9 [: b7 sGrouped data, 分组资料
0 b' m; T% c+ x+ D+ GGuessed mean, 假定平均数* F9 Y, F3 f, K& G- v
Half-life, 半衰期
' W4 _) \0 }) vHampel M-estimators, 汉佩尔M估计量( A4 i5 X9 Q5 h" P; {! I
Happenstance, 偶然事件% [4 B6 [6 c0 J8 p I" I, H1 U% {9 d; F
Harmonic mean, 调和均数
9 B# d9 @* h( k/ ?: FHazard function, 风险均数. G. @* i. H: a* p& d5 x
Hazard rate, 风险率
0 }. ?. C$ b$ h7 {2 HHeading, 标目 " S5 ~# X4 N. S) L
Heavy-tailed distribution, 重尾分布/ R. u1 k: ?# c/ c% f
Hessian array, 海森立体阵" E# n1 Q1 x M6 G) y* Z6 {
Heterogeneity, 不同质
* n( ]2 X4 W3 q0 y6 RHeterogeneity of variance, 方差不齐 1 [: ^1 h: P6 {; O8 e) |
Hierarchical classification, 组内分组; H1 a9 o6 _- s0 W- f
Hierarchical clustering method, 系统聚类法
9 S1 x. W3 B- J ]0 AHigh-leverage point, 高杠杆率点
" n, Z" v* M; ~: y. I+ rHILOGLINEAR, 多维列联表的层次对数线性模型
4 g N# s7 n" aHinge, 折叶点
1 W0 Q* y k; s/ o2 Q( u. fHistogram, 直方图
9 y ]% E$ b! eHistorical cohort study, 历史性队列研究 6 I7 ~. p: u$ |( y
Holes, 空洞$ }& x8 M1 v. p
HOMALS, 多重响应分析; v8 j8 B5 O- M. T0 t
Homogeneity of variance, 方差齐性4 i5 X0 g7 o- U1 e, @
Homogeneity test, 齐性检验# K/ `- p% p$ ^% V+ I
Huber M-estimators, 休伯M估计量
" c6 a! A: ]* q" {, N+ q' |1 z1 hHyperbola, 双曲线! a! `9 B4 S$ |/ I; @
Hypothesis testing, 假设检验1 I; w' `$ H" P
Hypothetical universe, 假设总体
5 F- ~+ h {$ K$ _3 D* e' Q, nImpossible event, 不可能事件3 X! r! g$ P5 C9 r/ ?% B; r
Independence, 独立性+ r& C3 s2 A; ?9 i. r- ?$ f
Independent variable, 自变量; ]" ]- _ e8 Y/ r
Index, 指标/指数" R7 U; ]1 @2 I& K- L; ?/ [
Indirect standardization, 间接标准化法1 y+ k: s9 e$ d+ h! K. f
Individual, 个体5 C$ |% h) N/ N4 m& }$ A. y: ?3 w* c
Inference band, 推断带! T! @4 h. w6 C! ^% M/ n- k
Infinite population, 无限总体& f# c/ s& W& c9 A1 u& [, L1 Z
Infinitely great, 无穷大
( _1 s/ N/ b* ~$ j: kInfinitely small, 无穷小$ k6 S8 X5 S8 P( D6 t5 _( r9 h0 q$ n
Influence curve, 影响曲线
3 \4 S+ z( u2 Z( fInformation capacity, 信息容量
$ F% ~$ E5 w' E' cInitial condition, 初始条件5 g: ^! F6 N& K" Q4 I+ A
Initial estimate, 初始估计值
R( t, {( C, H: o3 FInitial level, 最初水平
. D# R4 e, N$ k/ VInteraction, 交互作用* N5 I8 S( K4 J
Interaction terms, 交互作用项
4 s+ h7 f; P! o0 gIntercept, 截距
" w# l' w/ z% TInterpolation, 内插法
/ ]* E7 f. I" i# UInterquartile range, 四分位距) U5 q" m) b2 e, D$ D! Z- p t
Interval estimation, 区间估计
0 M8 F& ?3 H' E oIntervals of equal probability, 等概率区间
/ U# ?1 ^+ |2 D4 {7 |2 [0 \4 lIntrinsic curvature, 固有曲率: Q3 m: m. k& ^# z9 C8 R5 }6 L6 O
Invariance, 不变性
) z8 ]& j6 p( J3 ^) WInverse matrix, 逆矩阵6 y3 m: s; N1 |# u# ~. Y
Inverse probability, 逆概率. ]& [" | W6 |' D3 M' ~ R
Inverse sine transformation, 反正弦变换
6 S. Z6 f7 E8 ^, H5 ?5 UIteration, 迭代 & {' u7 l( Y& R5 Q
Jacobian determinant, 雅可比行列式
; A, N5 N9 Y9 }Joint distribution function, 分布函数
3 B" @" R' m% ^9 PJoint probability, 联合概率
' o- A& b) N; [7 {; G1 NJoint probability distribution, 联合概率分布9 A9 S8 s" V4 f3 I- X
K means method, 逐步聚类法) H3 K9 Z" O5 {; M
Kaplan-Meier, 评估事件的时间长度 . Y* W: X7 q. \2 J: _+ L
Kaplan-Merier chart, Kaplan-Merier图7 V, [9 Z0 c5 F" ^
Kendall's rank correlation, Kendall等级相关
Z0 ~" u, N; o2 I' o' rKinetic, 动力学
8 m3 P. w$ f3 c$ C1 m, fKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验& K f" `* Y! M _
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验/ M8 {1 X! w( y% ?
Kurtosis, 峰度
4 A, U3 y5 c- \2 wLack of fit, 失拟- W1 k$ x9 `) d* P6 d" E! r
Ladder of powers, 幂阶梯3 w8 I0 {% S$ j* T# C( Q: t# g! F
Lag, 滞后
" P- g- ^' o0 l; NLarge sample, 大样本! r& ~/ E* ]9 n: w1 }
Large sample test, 大样本检验
: _) {& C8 r, C, {: D) ^Latin square, 拉丁方8 b( A4 p3 b1 t4 T7 S8 L0 Q
Latin square design, 拉丁方设计
0 B. V1 I) c3 ]4 uLeakage, 泄漏7 X9 f9 B% v- j" U* W' L
Least favorable configuration, 最不利构形- O# |: S- R8 h+ Q$ p! E" {4 Z
Least favorable distribution, 最不利分布
8 z7 a( u8 K/ {3 uLeast significant difference, 最小显著差法
: T# a* h4 R* ]* U s v; QLeast square method, 最小二乘法! _" q6 a8 G+ E, m9 l" A7 o
Least-absolute-residuals estimates, 最小绝对残差估计6 D Q- [" Q9 W/ d% x
Least-absolute-residuals fit, 最小绝对残差拟合; l- |: e9 ^% J- T5 n; g
Least-absolute-residuals line, 最小绝对残差线
3 n4 r/ V; E8 i) D: ULegend, 图例$ [2 I' u$ F8 n0 X+ x7 B
L-estimator, L估计量
/ `: ^: i* \7 R0 }* z5 I" A8 oL-estimator of location, 位置L估计量
9 d" w4 H3 n N; C0 FL-estimator of scale, 尺度L估计量4 D2 C/ F) K- E% g! j+ Y6 N& E
Level, 水平( D+ L( Q8 q2 {( X8 f- k
Life expectance, 预期期望寿命, Z+ w' g3 o- ^% i k! h( {4 H+ H
Life table, 寿命表3 e. d+ B3 o5 X3 Y7 f6 N& m; P! S
Life table method, 生命表法- O7 x! o! @9 o/ G* O0 N
Light-tailed distribution, 轻尾分布# d ~* g& w, r8 f! K
Likelihood function, 似然函数* H7 H" Z; f+ t4 C% L. u
Likelihood ratio, 似然比
2 P; O6 h4 w" p {' L7 ~9 _line graph, 线图
1 R3 w8 c& p& G( @8 ^0 P! HLinear correlation, 直线相关
, m4 n( o+ x7 m2 \3 m. n) uLinear equation, 线性方程
9 K4 N! ]( C0 u' BLinear programming, 线性规划& j6 l: C! ~; E
Linear regression, 直线回归
8 C, a+ g5 M1 ~6 W: \Linear Regression, 线性回归) m' m+ t/ ?' T8 S
Linear trend, 线性趋势1 R7 W% S% ^% Y% l. n
Loading, 载荷 g$ i% F+ p4 ?9 ~/ z7 m J- _
Location and scale equivariance, 位置尺度同变性
4 c( f" j- Z* ~Location equivariance, 位置同变性! r/ a1 ]8 \0 G$ P$ z* n8 }: h& [
Location invariance, 位置不变性
+ Q, V& D1 s6 N) B' W5 E( l. s1 ILocation scale family, 位置尺度族& J/ j9 Q9 o0 A" R# V o
Log rank test, 时序检验
5 A6 Z) r) \, V& i5 L+ i9 ALogarithmic curve, 对数曲线) o# P7 |" h3 N- Z" S- J
Logarithmic normal distribution, 对数正态分布/ J3 P& o5 H1 A2 D0 X9 \
Logarithmic scale, 对数尺度
U a2 d# p( W0 q SLogarithmic transformation, 对数变换, ^8 r' g$ O$ T) c) F/ b; P
Logic check, 逻辑检查7 n8 _6 o1 m" y4 x* s
Logistic distribution, 逻辑斯特分布
( f; r; D. I9 z2 [( C9 hLogit transformation, Logit转换
& H$ m, Y) }! {LOGLINEAR, 多维列联表通用模型 ) Z1 Q, J2 G1 M2 |
Lognormal distribution, 对数正态分布& M9 C. i+ J* |0 O9 @& U& o2 b, }
Lost function, 损失函数
& Y, N- k2 _5 Y0 n5 ^0 GLow correlation, 低度相关
# B/ \/ }% I9 H1 vLower limit, 下限5 s. a0 b# {* E+ I! K
Lowest-attained variance, 最小可达方差
; m7 Q9 ^) A0 C# O/ {8 eLSD, 最小显著差法的简称
( v2 ?) L5 K1 H( gLurking variable, 潜在变量
7 ~; U4 i1 f* K0 XMain effect, 主效应& g+ l. X/ ?2 B3 V- _5 J
Major heading, 主辞标目: A ]$ L4 L) v% g/ n
Marginal density function, 边缘密度函数6 p. V3 p" @, W. B0 u
Marginal probability, 边缘概率
* d- ~1 r- [2 ?, F6 n& \7 `Marginal probability distribution, 边缘概率分布
5 i+ Z: y# Y! H8 S J- VMatched data, 配对资料3 f$ Y/ e8 P& b1 Z- |
Matched distribution, 匹配过分布
+ E/ Z% ?/ i! b6 rMatching of distribution, 分布的匹配4 T; V- K: ]* _" }/ s
Matching of transformation, 变换的匹配/ u5 L! e% Z& F/ n2 b3 b
Mathematical expectation, 数学期望
: u1 V0 `4 |1 _0 LMathematical model, 数学模型
: b* q2 y+ \3 e0 z. R$ MMaximum L-estimator, 极大极小L 估计量
! E( a3 a8 v) H* k& y2 J" s/ VMaximum likelihood method, 最大似然法
% @! C$ Q) V M0 T3 O9 @Mean, 均数
R M' C3 c! b5 t- c( L) FMean squares between groups, 组间均方( K" f. L5 c& z; A C
Mean squares within group, 组内均方, M3 B: n, D8 L3 L
Means (Compare means), 均值-均值比较6 d- `3 s9 U' L! j0 M! b
Median, 中位数
5 n# [+ ]! S8 w4 SMedian effective dose, 半数效量
+ |/ e' Z6 \. {) |/ [Median lethal dose, 半数致死量4 H& s9 k. W7 U( u& _' _9 e
Median polish, 中位数平滑
) A1 {: u* O# N5 A8 tMedian test, 中位数检验
% l; Z6 j2 D9 H8 eMinimal sufficient statistic, 最小充分统计量
4 a$ g8 w8 E( G( }5 v: f$ QMinimum distance estimation, 最小距离估计$ L) t) [% m" b, S
Minimum effective dose, 最小有效量
( y" @ q3 G P+ ]) t% NMinimum lethal dose, 最小致死量9 l4 q" z5 S% a3 {
Minimum variance estimator, 最小方差估计量
3 J) [9 \5 s KMINITAB, 统计软件包
: V e2 e6 N; R+ A" D! HMinor heading, 宾词标目
9 ~* \% x4 w. H+ Q4 Y4 NMissing data, 缺失值
& k5 I" V9 z, oModel specification, 模型的确定, d( J4 j0 K2 o" ?* G& E* q) A0 ~9 A
Modeling Statistics , 模型统计7 @7 G$ r$ W) H+ T
Models for outliers, 离群值模型+ X, U. _3 U4 r, b# W
Modifying the model, 模型的修正4 m; ?$ }& R; o
Modulus of continuity, 连续性模. b' _: D$ M0 L- s0 ^9 I" q9 [
Morbidity, 发病率 5 z' r# a# M! e
Most favorable configuration, 最有利构形( u P# n O l
Multidimensional Scaling (ASCAL), 多维尺度/多维标度1 p4 v; S* c6 b& t
Multinomial Logistic Regression , 多项逻辑斯蒂回归
! `) s2 y6 v- BMultiple comparison, 多重比较
+ j6 K# I' ~ n2 I' R) j* XMultiple correlation , 复相关
" w7 R# [% s1 BMultiple covariance, 多元协方差1 r0 `% O* R$ s7 R2 S! k( X
Multiple linear regression, 多元线性回归0 n: u0 w- w7 C1 q5 \5 w3 S+ u
Multiple response , 多重选项
0 j4 U* E5 V7 OMultiple solutions, 多解
+ ?" `' Q) u! x& j. uMultiplication theorem, 乘法定理1 o, b4 i+ X) a6 R
Multiresponse, 多元响应
" z3 Z7 |! c1 o) q) N+ ]0 ]& FMulti-stage sampling, 多阶段抽样/ p7 V1 |; k" G, A8 N/ [% |5 b
Multivariate T distribution, 多元T分布
3 q5 R9 o' A, I" tMutual exclusive, 互不相容! g# A& a; V) c% Y2 q" J
Mutual independence, 互相独立
8 T6 D1 q7 Q5 l' C% K9 yNatural boundary, 自然边界# l6 e6 P9 i; C9 b3 g1 L9 F! l5 o3 p
Natural dead, 自然死亡' W1 V! h9 f( A+ U5 p- `
Natural zero, 自然零, n+ s) ~. _, K; @
Negative correlation, 负相关% u$ C* L% L9 B/ z. r. L8 o5 c
Negative linear correlation, 负线性相关 t E' {; r' ~; k. d% g9 B' `$ S
Negatively skewed, 负偏
/ O# \$ u* p1 W- Q7 e! x7 xNewman-Keuls method, q检验
+ W; c" g5 v+ r9 S( PNK method, q检验% k4 ~* R1 Z* p. }" p
No statistical significance, 无统计意义
$ b' |5 G6 q* Z: G* kNominal variable, 名义变量
, H7 G* a. p4 Q v% H2 s# ENonconstancy of variability, 变异的非定常性) y( H' Q5 T1 {% @& }0 G( L2 P
Nonlinear regression, 非线性相关 x8 H9 o4 F! ]
Nonparametric statistics, 非参数统计/ J& z+ P' v/ c
Nonparametric test, 非参数检验
6 ~( }6 v/ L: {# A* ?* N6 R/ kNonparametric tests, 非参数检验2 c* q' N6 a# {0 X4 g/ ?" }
Normal deviate, 正态离差) V; K) H- ~- N% f
Normal distribution, 正态分布
$ m4 w6 H, ] A7 W" O& u, tNormal equation, 正规方程组
- n( Y" I" Z. U# ^Normal ranges, 正常范围
' c% @. M8 F0 \( m3 l9 u# kNormal value, 正常值
5 h; g$ @" _& D8 zNuisance parameter, 多余参数/讨厌参数# |/ a; c! i3 K* H0 ]8 h" W
Null hypothesis, 无效假设
& V. h7 d! k/ hNumerical variable, 数值变量
3 }/ c; i1 y" j9 pObjective function, 目标函数
/ e c9 o y- P! ~: I$ E- hObservation unit, 观察单位
6 Z7 |* E1 m g+ C1 q" \. m' uObserved value, 观察值 R0 U; q% K( w2 W
One sided test, 单侧检验
7 N" w- f$ Z _One-way analysis of variance, 单因素方差分析' W1 D" L! O+ ]6 Y7 j2 A
Oneway ANOVA , 单因素方差分析' Y7 B; X- T/ c/ r7 t& v; ]
Open sequential trial, 开放型序贯设计9 U3 {" ~) M5 t: g! V2 |
Optrim, 优切尾2 V8 [% X0 M3 H8 O+ B
Optrim efficiency, 优切尾效率
b% x" o8 m7 y) b8 }9 o& H& {Order statistics, 顺序统计量. q3 i1 y( v$ j4 j$ B% n
Ordered categories, 有序分类3 P \! T; t }/ F
Ordinal logistic regression , 序数逻辑斯蒂回归( M! X# r% ]8 m3 S/ n
Ordinal variable, 有序变量9 `( D* B$ K( t6 P; c, I* t4 m
Orthogonal basis, 正交基0 D6 G, S6 b2 l9 a n
Orthogonal design, 正交试验设计" |7 N( w1 T, L0 A9 N1 U. c
Orthogonality conditions, 正交条件
9 W6 t. ^: v J6 A% A) h4 k) mORTHOPLAN, 正交设计 : T u7 C, i+ k4 n
Outlier cutoffs, 离群值截断点& @3 S) {: t1 Q
Outliers, 极端值: H6 ^6 F6 C1 P9 r
OVERALS , 多组变量的非线性正规相关
* M! L7 b; B! Y0 C7 {0 \* D$ W8 C% UOvershoot, 迭代过度) l* Z) t# V7 u _* v
Paired design, 配对设计
: ?0 X& T/ Y" @, ^& r/ r5 j& O8 sPaired sample, 配对样本
- F) t/ Z3 N+ ePairwise slopes, 成对斜率
]5 A- @3 ?( F- kParabola, 抛物线
- u6 ?; t3 X3 n$ X3 F+ N: w( v7 ^Parallel tests, 平行试验
: U$ l9 c( m" p4 Q. N& I: o5 RParameter, 参数
5 M9 y; [; a; J$ L9 N6 eParametric statistics, 参数统计
" U8 B3 b) D8 l' q8 O1 Q, TParametric test, 参数检验7 X' r9 G- o* h, i
Partial correlation, 偏相关( r/ |( u# y8 b o+ f6 E& c
Partial regression, 偏回归
; g8 U& g T/ r% H6 Y" YPartial sorting, 偏排序
5 P, {9 |' q1 T" MPartials residuals, 偏残差* B$ F9 p/ D5 J v& h0 D$ g3 f4 b' V
Pattern, 模式
1 m, i' y2 Y1 r: nPearson curves, 皮尔逊曲线6 P- A6 p/ T: C" [) u* q* u2 B4 x
Peeling, 退层, b2 h2 P8 e$ S9 I
Percent bar graph, 百分条形图' [& G- l4 y1 X' L/ N5 S
Percentage, 百分比
: C, `2 O8 M6 F- z# TPercentile, 百分位数
7 F3 e- L$ N+ B; m0 KPercentile curves, 百分位曲线! s+ g2 V* p7 h( v, ^
Periodicity, 周期性
9 b& b* Z @/ D% I; D" q$ ~6 G0 ~9 TPermutation, 排列9 x( I+ z' m# D9 }. p! w. l
P-estimator, P估计量
' c5 D* o; `4 m" APie graph, 饼图
2 X R1 M j0 }% M) D* p1 FPitman estimator, 皮特曼估计量 u$ N5 k/ n+ x5 h5 c, a7 J
Pivot, 枢轴量* O3 [# N5 C. A2 T& g# S. n
Planar, 平坦
" w0 c* }; y) G4 H6 M8 fPlanar assumption, 平面的假设6 E0 m7 ?6 q1 h1 G+ [$ \9 o3 X
PLANCARDS, 生成试验的计划卡3 T8 A* N7 s2 w3 o: l+ @
Point estimation, 点估计8 D, ]$ ^# W! R% w, k4 e, e3 X7 J
Poisson distribution, 泊松分布; d9 A3 b. ?& h' R f" l Q" e
Polishing, 平滑
0 U5 m4 \3 ? ~6 f- Q; }# v$ p& aPolled standard deviation, 合并标准差
+ p* ]6 }& p3 k( @" QPolled variance, 合并方差5 |- f0 C1 [. Q8 n
Polygon, 多边图
2 [, x0 c j+ D4 N0 X8 jPolynomial, 多项式
9 Q0 J" u+ Y1 j. \ l# P! h" F7 CPolynomial curve, 多项式曲线
2 t' I2 r% |5 y; H2 V* tPopulation, 总体
7 _9 h- M- ?' p* F5 L8 LPopulation attributable risk, 人群归因危险度: _3 v$ ?. K V" o9 W5 e' T
Positive correlation, 正相关' D" t2 [ d) a; ^% s# d
Positively skewed, 正偏
; ^* J8 M- q! r. sPosterior distribution, 后验分布
) `2 X" @8 k8 JPower of a test, 检验效能
5 v! }' u4 N) Z- u" pPrecision, 精密度
, D/ `) U8 `9 `; v( CPredicted value, 预测值6 e: I; a7 L7 V" w* D$ h N' L
Preliminary analysis, 预备性分析2 U6 T, ]* i2 g! N
Principal component analysis, 主成分分析 V& C# A& l2 H, Q+ d. f
Prior distribution, 先验分布) p6 D/ m" \; L. }# D
Prior probability, 先验概率
7 k# `; t" \1 U: c, U( d4 OProbabilistic model, 概率模型
3 }. Y6 H- v$ S1 Y# G% x' zprobability, 概率( H; i- m% n) z5 ~9 g
Probability density, 概率密度
7 _$ y) c& o1 ~) B; b7 pProduct moment, 乘积矩/协方差$ d; D. N" j8 t* `) R! }! I/ P
Profile trace, 截面迹图
) B& y5 p# A$ @6 }9 OProportion, 比/构成比
+ _. M9 s5 Y; H" ^4 x, gProportion allocation in stratified random sampling, 按比例分层随机抽样
. N9 D; U+ Y" U. ] i" \% GProportionate, 成比例6 h8 G5 |1 @/ t/ C) h4 i* Q
Proportionate sub-class numbers, 成比例次级组含量
8 Q6 t' }7 y) c$ ]) lProspective study, 前瞻性调查
; _! L: o/ i! E z1 `7 kProximities, 亲近性
6 o9 V& V' l$ D2 }* S. vPseudo F test, 近似F检验
9 g; v1 D( o9 w8 W8 e6 x' mPseudo model, 近似模型6 A, D0 x/ o4 d1 I
Pseudosigma, 伪标准差
1 x0 z0 d" r) i1 Y) |/ ~3 M. N' i7 \Purposive sampling, 有目的抽样, V* ` r5 A1 S a
QR decomposition, QR分解" n+ c. a+ {: Y( u) ?; W
Quadratic approximation, 二次近似
# \7 n' a+ s. t& T0 t6 C; yQualitative classification, 属性分类% ?1 Q* f4 v+ `6 j" n+ f' s% a
Qualitative method, 定性方法
0 |$ d& [+ h7 s, N( x0 E3 ZQuantile-quantile plot, 分位数-分位数图/Q-Q图
( U: y |4 g' L. ?( t! TQuantitative analysis, 定量分析
! N) X, h5 N6 aQuartile, 四分位数
6 s; x) S. j* {$ ~% D9 A/ hQuick Cluster, 快速聚类
6 {! P- v" T& p0 o# _ IRadix sort, 基数排序
9 A! n" x! _* h/ o( d; ?" zRandom allocation, 随机化分组
1 {/ o u6 R- x. g( I# URandom blocks design, 随机区组设计
$ d" Z8 A& @6 d9 B, B# y, X6 ~' oRandom event, 随机事件
$ A8 `/ x2 D6 C0 {Randomization, 随机化
( H2 Q3 N* e6 n* W8 Q9 SRange, 极差/全距3 W/ p: w/ O9 F) D* e
Rank correlation, 等级相关: t, J" V( o% [" \0 g
Rank sum test, 秩和检验! n% O4 Q% ~; J
Rank test, 秩检验; R, g7 z& o5 j: m1 }
Ranked data, 等级资料2 i1 S8 F3 ]/ H
Rate, 比率# g! ^% W, z$ h% R3 {) q
Ratio, 比例$ J, w9 \. h7 C& f$ N' d) @
Raw data, 原始资料% p4 D, m6 M8 ~6 Q- q# W
Raw residual, 原始残差 _% b% R* H j: W7 o
Rayleigh's test, 雷氏检验9 a" o7 g" M* Y3 t8 z% Q
Rayleigh's Z, 雷氏Z值
?3 w0 Y3 T6 Z; u* A' Y: R- T* |Reciprocal, 倒数
3 V- H6 z; x- o# [4 WReciprocal transformation, 倒数变换/ {( P5 }$ X+ K, f) L9 i# d
Recording, 记录# b7 W: I. z1 R' ]) c0 B3 ~
Redescending estimators, 回降估计量3 N$ W+ x9 M# v; N
Reducing dimensions, 降维$ n% _' R2 Y6 ~2 ?5 h0 t+ G
Re-expression, 重新表达% X8 C, h" N9 Z* U
Reference set, 标准组
! D q/ |6 N K$ c8 ]5 ]9 P. YRegion of acceptance, 接受域
( R6 h- N& X( B7 I3 MRegression coefficient, 回归系数
3 [5 F$ l3 G1 F8 a. CRegression sum of square, 回归平方和
, z4 ^, F" c. k# x; fRejection point, 拒绝点
2 b p# T8 v7 ?- ZRelative dispersion, 相对离散度$ x: U# [- e4 a. z, n
Relative number, 相对数, C: @& V& J$ a4 {* [1 x- Y
Reliability, 可靠性
3 a% n# M2 a; h* k% hReparametrization, 重新设置参数
: `+ O7 P( X: w3 o9 E z+ hReplication, 重复
" X0 l7 y# T! ^; w. d2 BReport Summaries, 报告摘要. b( B, J# m% ?5 t
Residual sum of square, 剩余平方和
3 v2 n x# Q6 bResistance, 耐抗性
% t$ N+ d6 _/ R0 a) ~8 l- a4 ?) a& D$ i2 GResistant line, 耐抗线: Y/ M- A$ ^* s X! A* f
Resistant technique, 耐抗技术
* ~% m) f2 D6 Z+ X9 uR-estimator of location, 位置R估计量
3 ?" L. F/ ~) _- |2 BR-estimator of scale, 尺度R估计量
+ K4 m: h9 R4 L; PRetrospective study, 回顾性调查
, |5 E0 `4 U, W; _( ORidge trace, 岭迹
8 y4 a; C5 e+ xRidit analysis, Ridit分析3 J, R7 z6 h5 h* _1 a! p
Rotation, 旋转
! r% a; ]9 E& F. C6 O$ HRounding, 舍入 y4 p R5 |3 c( |
Row, 行- o. N) M# p- g$ a
Row effects, 行效应# Y5 q m! ~7 J* u
Row factor, 行因素% k8 F5 s/ T& q1 U& y$ C8 F
RXC table, RXC表
8 ^" J0 V& a- n4 ]* _4 SSample, 样本
2 _' b! H& ~- H( ?Sample regression coefficient, 样本回归系数
) J2 t+ e, [ f8 l4 aSample size, 样本量
' `4 l3 F; c, P; W2 gSample standard deviation, 样本标准差* M: t3 l$ g4 i) q: G* R) J; J) T
Sampling error, 抽样误差# x+ ?7 ^" U* Q, e. _7 [! Q
SAS(Statistical analysis system ), SAS统计软件包
0 M9 R) H% p6 w6 v- n$ jScale, 尺度/量表+ [1 w. c1 `8 o8 T$ O' O
Scatter diagram, 散点图' J* v# \& P- x- V) A6 a
Schematic plot, 示意图/简图
2 E/ Y* v* t0 J+ u2 YScore test, 计分检验
{+ U$ O3 e" P3 _3 D0 X5 zScreening, 筛检, {8 ~0 E7 F( A' d# f0 i. W
SEASON, 季节分析
* R( ]8 ^$ `" k( t5 D" ^+ qSecond derivative, 二阶导数
- B, P+ q3 j7 T% K8 @Second principal component, 第二主成分
! {% A- w8 b# OSEM (Structural equation modeling), 结构化方程模型 / d/ J! A" R$ Y. T' ~
Semi-logarithmic graph, 半对数图
8 p. x6 ^6 h) O BSemi-logarithmic paper, 半对数格纸+ S: i ^, z9 Y U- e
Sensitivity curve, 敏感度曲线: n7 t. N& k# M2 p
Sequential analysis, 贯序分析
1 `0 @6 i" S; k" A( ySequential data set, 顺序数据集
/ p+ z2 u7 ?% i+ XSequential design, 贯序设计
0 B4 I% O! z+ qSequential method, 贯序法, g" g! K2 I: q" k' L6 o3 [3 {
Sequential test, 贯序检验法
+ g9 b! p% T* k# e X& L! qSerial tests, 系列试验
6 d2 j$ \. \3 E4 t3 fShort-cut method, 简捷法
* A4 n- [; M: o4 {Sigmoid curve, S形曲线- ~9 X" j# M3 h! \& W$ H
Sign function, 正负号函数& t4 p( v) u) g" u4 b( L) E
Sign test, 符号检验
2 e1 W4 J% {: X6 _; MSigned rank, 符号秩
* N3 p# s# @$ s6 S! a, \% HSignificance test, 显著性检验1 R7 o0 c/ Z' f" N+ ~3 w: N
Significant figure, 有效数字- p. }8 s- W; r# n
Simple cluster sampling, 简单整群抽样0 j9 T2 G" S* ?
Simple correlation, 简单相关8 ?3 |9 r! u! e1 A2 U; Q. e
Simple random sampling, 简单随机抽样
4 f3 c" z' ?6 }' E) M: A( @3 ZSimple regression, 简单回归
' L. c/ v% a2 b% m ~( _: Qsimple table, 简单表
! a4 E, b- E& R; D7 `$ v$ gSine estimator, 正弦估计量 E5 d/ F3 m( i% Y$ S0 `# i! y
Single-valued estimate, 单值估计
8 s* q! U, [" o7 \4 `# NSingular matrix, 奇异矩阵
/ ]# Z7 F+ Q! ~4 j2 ySkewed distribution, 偏斜分布
1 D/ R! r5 X2 u. B6 s- ISkewness, 偏度
3 K, \" w! A O4 i' FSlash distribution, 斜线分布
* g4 k9 N e: ?- eSlope, 斜率
9 E4 r# g5 V' A& H# JSmirnov test, 斯米尔诺夫检验
: b, U+ |2 Y5 @% ySource of variation, 变异来源4 v1 v7 @, Q) x4 F: a+ _
Spearman rank correlation, 斯皮尔曼等级相关
3 e, G# L) ]$ HSpecific factor, 特殊因子
. S* p7 L$ A3 d7 @6 D0 E1 C! ]Specific factor variance, 特殊因子方差
# t# ?, K! U7 j0 C, Q' O: KSpectra , 频谱
; b0 U9 L: ?% a" ?$ ?2 k+ y# B, l0 kSpherical distribution, 球型正态分布 M- X6 S+ ` o
Spread, 展布
2 o& s' H% \$ `1 Q5 M$ x7 bSPSS(Statistical package for the social science), SPSS统计软件包
% ^2 A5 \4 b5 T; X5 R$ VSpurious correlation, 假性相关
0 W. W! |( ~! j1 `8 [( SSquare root transformation, 平方根变换
) ~) Z6 X) {- m% L* d6 p1 `Stabilizing variance, 稳定方差
' O L/ e. c* A+ C# e/ d; i) OStandard deviation, 标准差
( A7 n8 @, _3 N Q1 Z/ jStandard error, 标准误3 n/ {2 ?* |# O, p( s
Standard error of difference, 差别的标准误3 p. H& S$ [$ @) S+ c# [
Standard error of estimate, 标准估计误差
6 X% i+ W1 q7 tStandard error of rate, 率的标准误
2 ]. H( Q$ \3 |; z* M* ?Standard normal distribution, 标准正态分布0 J" V' S o" r% \. I
Standardization, 标准化
* u" |5 F4 V# C) q( yStarting value, 起始值' A, X( t, R- _3 v4 ~
Statistic, 统计量
; _& R: e1 z8 |, C7 jStatistical control, 统计控制: l) ^" z$ a% e( J' @
Statistical graph, 统计图( G$ q" i2 f1 X8 G
Statistical inference, 统计推断
) w4 [2 [6 Q- K( }$ c. p! Q% X; _3 mStatistical table, 统计表
- ^" O0 m( j% oSteepest descent, 最速下降法' U3 e9 i5 g5 ?7 v
Stem and leaf display, 茎叶图) w' R2 @8 A7 h1 ]/ ]
Step factor, 步长因子7 f: k; J4 [/ v: T3 {6 M" f( N; y
Stepwise regression, 逐步回归) \( R/ M$ K0 G6 H
Storage, 存: f Y; v% c) y( _: R+ h
Strata, 层（复数）0 l! x6 Q D" C( C* i Q+ ?5 ^, X
Stratified sampling, 分层抽样, ~/ s- M1 r; k
Stratified sampling, 分层抽样2 y2 c% C+ p# M6 X( d
Strength, 强度
' J+ l- {9 i" c, f: U: vStringency, 严密性% h4 A# D+ X3 T& ]' y8 n
Structural relationship, 结构关系$ p8 f: u& r' ?
Studentized residual, 学生化残差/t化残差
' A6 ~# O% V; {: ?" `! }. D" j# OSub-class numbers, 次级组含量) ^" R- F# W# Y. `# B: x
Subdividing, 分割4 b, p1 g( r) R; _, W
Sufficient statistic, 充分统计量
3 _2 D4 E9 A. t6 z1 U9 nSum of products, 积和
5 m3 ~ \( `+ @, g$ n. r% RSum of squares, 离差平方和
( u* o6 [1 _% g7 nSum of squares about regression, 回归平方和, a& F2 B- h4 W; L$ j3 Z! B
Sum of squares between groups, 组间平方和
6 N) G; J; L) L" K9 Z. `Sum of squares of partial regression, 偏回归平方和4 _% g2 x" Q' K9 ]% i. {) A f9 v
Sure event, 必然事件
* W9 @, _' C' X1 R0 mSurvey, 调查
+ ^6 K' i! D& `! P' w2 LSurvival, 生存分析4 _$ B5 h( `/ ^* e/ v5 ~
Survival rate, 生存率! {$ t0 g3 _% R9 N6 D4 q
Suspended root gram, 悬吊根图$ d/ V* I# x- g h: V) ]& A, _
Symmetry, 对称% T4 l" C, b8 I0 \; S9 C# S9 f: L
Systematic error, 系统误差) D/ p' _+ O) X6 S1 L! [) L ?
Systematic sampling, 系统抽样/ ?; L+ f Z" O' ]$ W. z
Tags, 标签
1 T, z3 _2 f- lTail area, 尾部面积' x- D! A( I8 P% O; t
Tail length, 尾长
$ f2 n9 p3 i+ b) z: r. ]Tail weight, 尾重
0 A9 B& @/ k4 F' O9 g! w' w6 ?Tangent line, 切线
5 L& |# t; Q7 n5 S. r! E. w: b; fTarget distribution, 目标分布2 g$ L( k% s7 {
Taylor series, 泰勒级数
2 o$ H7 b c2 G+ i7 t) ~Tendency of dispersion, 离散趋势
& U, a( T% e) P' n- @( P" bTesting of hypotheses, 假设检验
7 D! c; {( K. S& sTheoretical frequency, 理论频数3 n$ Y7 q, A" O: C+ i
Time series, 时间序列
: ^: B2 t( M9 b7 `+ ~% G$ K( ^7 UTolerance interval, 容忍区间! A$ N/ N( W) d; K! e
Tolerance lower limit, 容忍下限. Q5 e8 o9 }% |( h2 M. y* R" o' ?% M
Tolerance upper limit, 容忍上限; \ I1 G' m( G' s/ B7 v! m6 V" X+ Z3 s
Torsion, 扰率) b. k. {# C" ?9 Q% v& S' s
Total sum of square, 总平方和
8 V: S' p" b A1 K& LTotal variation, 总变异$ @4 `& S0 u# U9 y
Transformation, 转换' c' G- }; Y4 J- E; T
Treatment, 处理
/ V& Q ^9 l# GTrend, 趋势
6 m8 {$ ]' H2 B0 kTrend of percentage, 百分比趋势7 p( v( I+ e U' z4 p* J/ D# y9 Q
Trial, 试验7 u4 Z {3 i8 B1 v
Trial and error method, 试错法- o4 Q7 T3 {; g" {
Tuning constant, 细调常数
. d( ^, D& j# Q, z* i; o! ^Two sided test, 双向检验
# a: f% R I) g. s% OTwo-stage least squares, 二阶最小平方. ^2 a" _5 i% M+ ^8 i, K1 w2 n
Two-stage sampling, 二阶段抽样
S' t6 _# v$ P* V$ Z+ T- e' t" RTwo-tailed test, 双侧检验
0 V8 i! {' |9 sTwo-way analysis of variance, 双因素方差分析! b6 q4 g( w! X6 U8 V. Q8 Z
Two-way table, 双向表
$ r* ^1 C* {' p5 P1 J) c( ?Type I error, 一类错误/α错误
* t/ e' V/ `0 n9 \: m) CType II error, 二类错误/β错误
# {4 t% h# W' l( qUMVU, 方差一致最小无偏估计简称
/ x8 Q4 {, Q) E& R; q7 _Unbiased estimate, 无偏估计1 ?$ @( ~8 Y" `* l0 {8 u* D$ z
Unconstrained nonlinear regression , 无约束非线性回归
* H b+ X# \1 c; WUnequal subclass number, 不等次级组含量6 S5 _+ M# l- F
Ungrouped data, 不分组资料
* ]: P9 s. t& l! J' @9 [1 MUniform coordinate, 均匀坐标
' v5 \- K! |0 K+ f2 LUniform distribution, 均匀分布
9 C5 B* { S1 G8 G/ y) F9 \+ h& V' DUniformly minimum variance unbiased estimate, 方差一致最小无偏估计0 A1 B2 ^5 [5 t2 O
Unit, 单元
. D; U" r8 W3 ?: h5 HUnordered categories, 无序分类' |9 B" q: p8 R) y
Upper limit, 上限
/ F, a. Y% n$ w' P2 fUpward rank, 升秩5 m2 ?/ j4 s3 `: |. z+ g
Vague concept, 模糊概念
1 s$ H; G! x3 x+ e9 TValidity, 有效性0 Z3 V( ^/ ]# d( e: J
VARCOMP (Variance component estimation), 方差元素估计
! e& Y+ Z$ I& sVariability, 变异性
- v- B! g9 n: a1 c: S* UVariable, 变量" Q1 R. D1 O& t3 y
Variance, 方差
& Y! p1 Y& E! SVariation, 变异
6 Y5 o. w* L& p/ G7 ^/ K: Q' B6 EVarimax orthogonal rotation, 方差最大正交旋转% a! `% D) z+ S% r. C- ^+ @1 ]. p
Volume of distribution, 容积
- L4 C/ l( Y8 S) k2 ZW test, W检验
2 F, F2 Y+ N4 _8 X/ w* L" xWeibull distribution, 威布尔分布
6 e7 i8 ]! N- o) ^; `; sWeight, 权数, p8 P# l n# w& B7 o' f, t: Z- F: m
Weighted Chi-square test, 加权卡方检验/Cochran检验0 y: }9 }# h& m* S+ L
Weighted linear regression method, 加权直线回归: a! o; K! j$ P4 x# [
Weighted mean, 加权平均数
2 v1 K! A0 `1 XWeighted mean square, 加权平均方差0 Q& j" O0 [) [- I
Weighted sum of square, 加权平方和' a/ G7 }/ S9 p: x7 r
Weighting coefficient, 权重系数
$ C+ \! W& h4 H. \" s* g8 R) o$ ?% ~Weighting method, 加权法 " R$ B9 s6 n7 C c% [
W-estimation, W估计量) H( @9 G! E% I) d7 Y$ q
W-estimation of location, 位置W估计量
4 d V4 }# K4 x tWidth, 宽度
- k. R, d( g9 Q, ]4 v. zWilcoxon paired test, 威斯康星配对法/配对符号秩和检验6 h% ^& K; h3 b3 g3 {0 x
Wild point, 野点/狂点
% R3 l& K. w5 n4 q& s/ QWild value, 野值/狂值. f% @2 Z" w1 D7 I' H6 i' a+ J A2 w
Winsorized mean, 缩尾均值
+ e* }; d8 i) NWithdraw, 失访
1 s: s- y& N: g7 [" RYouden's index, 尤登指数9 I9 i4 N8 P4 Q$ h2 j% A3 q
Z test, Z检验+ i' o. n6 g/ p# P/ C) s1 ]
Zero correlation, 零相关: H: T! Z, N/ c7 j# T
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
