|
|
Absolute deviation, 绝对离差; x- n1 R4 \. ?7 ^- B8 k5 ^, P7 F" c
Absolute number, 绝对数
2 S: G* U) ?* ^- n% N2 h. j: \Absolute residuals, 绝对残差
* A; D8 _( ~7 z7 X4 t/ m' v. HAcceleration array, 加速度立体阵" n* T1 V, _, q& J' A M# p
Acceleration in an arbitrary direction, 任意方向上的加速度0 d" Y5 ^) Z" M z
Acceleration normal, 法向加速度9 I; P4 X) S+ j& Z" z
Acceleration space dimension, 加速度空间的维数
4 i) L. l$ F& H, r Q( y6 pAcceleration tangential, 切向加速度
/ c# ?: f) E% LAcceleration vector, 加速度向量: F4 F, v9 G( D( w! `% U j7 Y: N6 o
Acceptable hypothesis, 可接受假设& [9 H4 x' o$ K4 e7 @
Accumulation, 累积
* c1 n9 `4 i6 wAccuracy, 准确度- g& g2 l4 D" }; {7 D1 K, B6 _# r: V
Actual frequency, 实际频数4 I# U! v5 _* w7 K5 M/ M
Adaptive estimator, 自适应估计量- k/ F3 D9 \, w3 E! k- Y3 K
Addition, 相加: D9 ?5 A9 J7 g7 D+ n
Addition theorem, 加法定理
- Q8 `* q" X. i: B" C0 S/ n0 rAdditivity, 可加性
; e: U1 Z* h9 c1 @4 @Adjusted rate, 调整率, Q2 J/ g$ u2 P
Adjusted value, 校正值
/ ~& _" w' ]: N$ y8 {5 G1 MAdmissible error, 容许误差
- a6 w3 q( p. P X8 }% RAggregation, 聚集性' |3 t+ C- s; A, Y3 f2 _/ c9 p# C
Alternative hypothesis, 备择假设: L% Q) w' L" R$ z9 s7 j# B
Among groups, 组间
% g/ ~, V3 M- B R' YAmounts, 总量3 w; j3 u9 s+ s2 o
Analysis of correlation, 相关分析$ \1 N9 m' Y/ Q/ P. l4 \0 @
Analysis of covariance, 协方差分析4 U! s& Z& x4 t! ]
Analysis of regression, 回归分析
: ?3 n" w: k/ J7 N- ?Analysis of time series, 时间序列分析) G: X# h. [# S
Analysis of variance, 方差分析
! t+ I2 n* @$ V6 k9 e0 U ?Angular transformation, 角转换
z" M7 T- ~8 K) [+ sANOVA （analysis of variance）, 方差分析
3 K: s7 K1 n9 ~, \8 p* iANOVA Models, 方差分析模型- H6 D# z1 V' Q0 e+ E% H+ @5 y
Arcing, 弧/弧旋
/ D4 r1 A' X4 L: e- Q, {4 i0 r" t. C2 CArcsine transformation, 反正弦变换! x) {% I- l5 a p2 Z R g8 T
Area under the curve, 曲线面积1 a7 Y I9 g" a
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 7 C1 l) q2 B: Q& m9 b; U
ARIMA, 季节和非季节性单变量模型的极大似然估计 : W# B" |6 i3 D! X# d
Arithmetic grid paper, 算术格纸* S i! \+ r! s+ ?
Arithmetic mean, 算术平均数* V, f9 W9 J" F8 Z
Arrhenius relation, 艾恩尼斯关系( U1 Z% f+ e* T3 F( J" P
Assessing fit, 拟合的评估* P) ~6 _9 B" _
Associative laws, 结合律
& X' x% Y9 s; Y8 E# u5 @Asymmetric distribution, 非对称分布0 b6 V* u# g) N' `# j/ p! c
Asymptotic bias, 渐近偏倚
1 y- x! Q. s2 ~ Y1 z6 uAsymptotic efficiency, 渐近效率
/ p$ w$ p. O; E: ^* `. B5 N' oAsymptotic variance, 渐近方差
* H6 M1 q: ?1 I2 u5 F/ l! B3 [* nAttributable risk, 归因危险度4 ]9 d- j2 v! a2 v t, h" T
Attribute data, 属性资料1 y; Z4 Z0 r9 m% O6 j
Attribution, 属性
5 X& V& e& H' n1 N! eAutocorrelation, 自相关% k4 s J' O' `
Autocorrelation of residuals, 残差的自相关) Y) g& x& v* _8 p( V C
Average, 平均数; v7 @- u, O0 i- e
Average confidence interval length, 平均置信区间长度
a' @, Z* r, ^- J! A8 NAverage growth rate, 平均增长率
. v- @7 l" G, U0 l. o- L9 \Bar chart, 条形图
! Y1 f( g$ l+ x& O% f2 n6 [6 DBar graph, 条形图& [0 W( S0 C% x# C# [
Base period, 基期
: h4 P7 D, s: dBayes' theorem , Bayes定理* H; V0 G k/ m! b& C& B
Bell-shaped curve, 钟形曲线
; B, }1 V3 R! zBernoulli distribution, 伯努力分布- h. h& E" g* E: s: o! Z
Best-trim estimator, 最好切尾估计量5 ^* J2 M' R3 I4 a. u
Bias, 偏性
& L/ }7 L+ @+ m& A' I2 a! g. B2 GBinary logistic regression, 二元逻辑斯蒂回归/ C' w# V$ m3 v
Binomial distribution, 二项分布4 u9 {! T) F% f6 W% M, E3 `
Bisquare, 双平方
L- M O1 K" xBivariate Correlate, 二变量相关
% {- ?, q. g$ _, T; S7 o: m9 sBivariate normal distribution, 双变量正态分布& V" {% L! i' l5 x/ C; F! X
Bivariate normal population, 双变量正态总体
# I9 V: ]+ Z% F& S5 ^Biweight interval, 双权区间
0 z s$ C# o! E" ]4 ~! QBiweight M-estimator, 双权M估计量0 C) L# a1 i! l8 P
Block, 区组/配伍组6 c+ O" h3 O# L) b1 b' y
BMDP(Biomedical computer programs), BMDP统计软件包0 V) S2 R& Q) r* {4 g0 I
Boxplots, 箱线图/箱尾图
" F; K0 v! c" qBreakdown bound, 崩溃界/崩溃点
% ? I) k2 G: [0 QCanonical correlation, 典型相关
9 `' M9 L0 h% y6 F' YCaption, 纵标目6 z h( P3 H5 V$ N7 _- h% f0 e9 C
Case-control study, 病例对照研究3 e2 H( H- c1 b
Categorical variable, 分类变量3 [. H9 }4 m' y( s" L
Catenary, 悬链线9 `/ k& y5 K( G' L( A
Cauchy distribution, 柯西分布/ U* _3 i, Z6 b5 U" x
Cause-and-effect relationship, 因果关系
o% O5 x0 q! W2 {) lCell, 单元 D0 U; M4 B! R6 j/ o
Censoring, 终检
2 k' j9 c4 P4 j/ c w' qCenter of symmetry, 对称中心3 S: m" q4 {% v* T, a2 f
Centering and scaling, 中心化和定标/ u5 v! p4 S) u; u
Central tendency, 集中趋势
3 D; b' D4 @7 wCentral value, 中心值
: }2 {( ]6 z8 {( z6 RCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测/ _. U! p$ I$ j u5 F
Chance, 机遇
6 v) i: o1 Y3 \- _% r7 xChance error, 随机误差
. K- u) a, F3 y p( O/ B$ _Chance variable, 随机变量5 r! H' [! z. \4 Z
Characteristic equation, 特征方程
z/ J9 y% N* S( X. }' s! G# GCharacteristic root, 特征根7 ?0 y5 `) x$ y7 D2 e
Characteristic vector, 特征向量0 l7 ^0 Z" i `/ l' s5 g) b9 l$ K+ K
Chebshev criterion of fit, 拟合的切比雪夫准则- C! @) W* a. T8 r8 o. o% o
Chernoff faces, 切尔诺夫脸谱图
( N* w( [) S Q, C% u% i' X kChi-square test, 卡方检验/χ2检验
J+ R" z0 P% H' I) BCholeskey decomposition, 乔洛斯基分解. I; m9 h1 H2 d4 ~6 E
Circle chart, 圆图 * h8 @) S% M4 I
Class interval, 组距4 O" u4 m' l% f) M- d$ u; w
Class mid-value, 组中值
* g9 x, q6 H4 Z( F4 C0 M% H1 zClass upper limit, 组上限' \- K2 }' F" b% O Q& F' \9 f, \- A& d+ F
Classified variable, 分类变量
0 ~4 J2 V) }6 e9 y+ b$ ?7 g- gCluster analysis, 聚类分析
. E9 f' j# }( FCluster sampling, 整群抽样7 f* F0 y% P! o# u* n/ Y4 c) r( h! c
Code, 代码; K' g0 |3 C" }# M" H* A
Coded data, 编码数据. V0 B: K3 H$ l" F
Coding, 编码$ h( y3 c. b G N$ J
Coefficient of contingency, 列联系数5 H. W* Y, @8 e+ X
Coefficient of determination, 决定系数1 x% q! @- |5 d! ]9 {+ i2 C; D
Coefficient of multiple correlation, 多重相关系数& f1 K$ k2 b6 k0 I! n1 N6 ~7 E
Coefficient of partial correlation, 偏相关系数
9 W. e6 p2 N8 G1 z [, g. T& B+ n: OCoefficient of production-moment correlation, 积差相关系数
; F w6 u# H1 h3 M* v- Z$ }Coefficient of rank correlation, 等级相关系数
* d) P3 \3 a# uCoefficient of regression, 回归系数5 }" I4 { W+ v( J' j
Coefficient of skewness, 偏度系数
+ |; `8 b! E6 E/ rCoefficient of variation, 变异系数1 r6 ?* p& P+ ~- G
Cohort study, 队列研究# p( p C0 v2 h& q
Column, 列+ g/ W6 ?, e, u& v3 k
Column effect, 列效应. k" B" ? ~! M2 p+ ]
Column factor, 列因素
7 Q3 k5 n% {; x2 C' v, e* [Combination pool, 合并
& k# |5 N0 l) C* f/ ~. fCombinative table, 组合表
( ^0 V/ X* ~5 ~* \/ ~Common factor, 共性因子
3 ?* s1 t7 \3 a: V! _9 Z% O" L( f+ cCommon regression coefficient, 公共回归系数6 f7 c6 ~: l$ S; t% \9 c. ~
Common value, 共同值; l1 c2 b% f" M5 r" K
Common variance, 公共方差# W+ i( E" k3 ]3 M
Common variation, 公共变异
5 y- u* D3 M7 L+ ~ p l( h: KCommunality variance, 共性方差/ X2 U: o" f+ x/ ` j, M
Comparability, 可比性1 @2 s0 E( N8 m. t
Comparison of bathes, 批比较
4 `/ G1 H K, a/ T& g& ^Comparison value, 比较值. S9 ?3 q' C: x
Compartment model, 分部模型" W5 Q9 i2 _, `- M, k& A) |+ C+ ?+ y
Compassion, 伸缩
/ @7 [# T( P/ u8 C# y, FComplement of an event, 补事件5 A; Q5 i2 k) P- p- S) H- y! q
Complete association, 完全正相关7 C, d1 v* z! d
Complete dissociation, 完全不相关
! y7 o* O7 O1 a0 h3 |8 n% c1 nComplete statistics, 完备统计量
5 W# v( ~- ]( ^& i: u& C9 lCompletely randomized design, 完全随机化设计 m7 ~; a4 k% O- W
Composite event, 联合事件
* }$ t4 T& b/ g$ N5 K) B; KComposite events, 复合事件# A9 ^: L; r- |: c' @& g! U' u
Concavity, 凹性- G1 {( G7 g4 c; x& u) |$ z; X" T, ?) }
Conditional expectation, 条件期望
; G3 o9 H5 w7 e) C; h8 |: nConditional likelihood, 条件似然
# }4 d- e, K8 h% ~# i2 fConditional probability, 条件概率% ]1 O. ^/ v7 i6 l$ F
Conditionally linear, 依条件线性+ X# J; z. o8 s) z. D4 z: e7 y4 v
Confidence interval, 置信区间
- h* x/ p% n& XConfidence limit, 置信限
" `" ?6 Y( A: w" } x" U7 qConfidence lower limit, 置信下限
4 ~! t& E% H2 aConfidence upper limit, 置信上限
8 n4 d$ ~; K W5 O' U% l" DConfirmatory Factor Analysis , 验证性因子分析
0 k' A1 q' b, ^9 z8 s( p( V, G; eConfirmatory research, 证实性实验研究
( h( W4 \; t6 s/ e( d2 S& sConfounding factor, 混杂因素# \$ B7 p% p- R) e0 F r4 \6 W& n
Conjoint, 联合分析& I9 b5 a; q. n" ?9 j
Consistency, 相合性' @: X: f8 k0 S6 I
Consistency check, 一致性检验9 Y6 A1 ]8 N- H& ?+ @3 ]2 G
Consistent asymptotically normal estimate, 相合渐近正态估计$ W9 h7 n0 M% @0 I2 j: } _1 B( n1 l6 r
Consistent estimate, 相合估计( R: n) Q O' |6 W' I: x# D
Constrained nonlinear regression, 受约束非线性回归
6 a0 X5 d) j2 o- J0 A3 zConstraint, 约束
+ o# O# N9 A; R: q/ ZContaminated distribution, 污染分布+ m, w L" |. R: h. T
Contaminated Gausssian, 污染高斯分布- C9 T: { n- E
Contaminated normal distribution, 污染正态分布; P, L/ l/ D1 Q/ E$ G
Contamination, 污染
/ T- z, z% K) uContamination model, 污染模型
' O& V$ I7 n: F* oContingency table, 列联表$ _. l4 K m% n
Contour, 边界线 R) s3 s6 c+ B; I0 \8 m
Contribution rate, 贡献率$ B5 z2 ^) F5 ~% |, q( n& V
Control, 对照* X8 ]/ v0 P, K
Controlled experiments, 对照实验2 K+ Q3 g% T: h" h! k" l8 m1 a7 |
Conventional depth, 常规深度
0 V# \- ]" {2 X# J2 i* AConvolution, 卷积( y6 v& \6 X9 A; ~0 d4 p
Corrected factor, 校正因子
5 V. b' U9 P9 B1 T: N* C8 hCorrected mean, 校正均值
0 N5 K" j* k" D9 j& A. A5 HCorrection coefficient, 校正系数) [% ?# F5 Z- B& ?4 v4 y( L3 }* b
Correctness, 正确性0 ~3 C/ }; u i& ^ t B* u
Correlation coefficient, 相关系数1 h& [# h3 h. w# Y5 u. ?5 c
Correlation index, 相关指数
/ [1 E" _! T: l6 ^* bCorrespondence, 对应5 i- a$ a# a9 }: E+ [5 q
Counting, 计数
4 T9 X8 @& r1 M% w. j9 Q5 @Counts, 计数/频数
' W: o; [2 R7 Y6 y0 n0 ?Covariance, 协方差
& F$ l7 @0 H. vCovariant, 共变 ' {( [: _* s; n% y) d4 ]! S
Cox Regression, Cox回归
% z. C4 u% v1 a5 @" lCriteria for fitting, 拟合准则3 G( U; |% C: B" Q; T) Q; [
Criteria of least squares, 最小二乘准则
% a1 R" x; n0 m0 SCritical ratio, 临界比" v* I) J! r/ t* t) l! z
Critical region, 拒绝域+ ]5 W5 K# ~) m, N* `
Critical value, 临界值: J! Q0 i6 Y+ c. a3 W' R" \0 e
Cross-over design, 交叉设计4 _) {& K s" L3 P
Cross-section analysis, 横断面分析9 S! K2 i* ~. T k' I2 L
Cross-section survey, 横断面调查
1 ^; C& e- b7 s: TCrosstabs , 交叉表
9 T0 Z l3 Q8 H: i6 yCross-tabulation table, 复合表
( M$ m9 o& t& h+ s* Z. l& jCube root, 立方根* H7 d) d+ Q& q4 O
Cumulative distribution function, 分布函数. }2 i) n% U6 m: S T
Cumulative probability, 累计概率1 W/ D- P/ k1 i5 H
Curvature, 曲率/弯曲3 I& t& @8 e, K6 {( M
Curvature, 曲率
# i. s0 `1 d( R" CCurve fit , 曲线拟和
; X6 a. k* f$ ~Curve fitting, 曲线拟合
4 v. \+ A! h3 Z4 jCurvilinear regression, 曲线回归
4 ?' ]+ G2 s, a6 W$ Q# f/ i, T9 c- R! ]Curvilinear relation, 曲线关系
' [0 w2 n( P* r: `Cut-and-try method, 尝试法! `( b" b. v. c
Cycle, 周期, A/ F* i* p( C7 b# a
Cyclist, 周期性
+ i* Z5 a0 x: L" F4 Q. F, iD test, D检验3 C. [# {$ G% O- G
Data acquisition, 资料收集
3 @ x: L0 Z9 e2 V; g* K8 UData bank, 数据库
5 L N1 `# `8 N& M5 J. RData capacity, 数据容量. j/ F- C7 u2 R2 u, S5 ?
Data deficiencies, 数据缺乏) G0 X% d+ ^3 Z7 L% B/ q: c
Data handling, 数据处理/ c; b8 \# b& o \! L9 o3 S% z' n
Data manipulation, 数据处理9 j- O. s. D' p. D
Data processing, 数据处理
. u3 e1 a6 [) a* DData reduction, 数据缩减
; {0 k5 J# ]) Y- J/ B! O2 AData set, 数据集9 G Y5 z' F9 F% \: `
Data sources, 数据来源. l- `$ F1 @; {3 W9 Q
Data transformation, 数据变换
8 B! G# r" |: r$ F) cData validity, 数据有效性! e( W! J9 h/ |3 V3 x
Data-in, 数据输入
+ h# C, @1 ^3 b+ v) E' `Data-out, 数据输出% S, y. @+ m' e6 I
Dead time, 停滞期
# B2 o# O! X% x, g( H& NDegree of freedom, 自由度
* O8 X) B& [5 S, UDegree of precision, 精密度
# w3 x* R4 e0 T4 `! `5 jDegree of reliability, 可靠性程度! S! P9 y( E' K; R. y+ p) K
Degression, 递减" j) C$ l. D0 p! A; P/ _
Density function, 密度函数
" t! g, n5 ]. j) ?Density of data points, 数据点的密度
4 ^8 b2 _8 m; z/ T6 R7 B/ n8 rDependent variable, 应变量/依变量/因变量
2 \, M' D2 J& F- |9 s% `Dependent variable, 因变量
$ j, G1 ?2 V7 ~7 Z! _! R! D9 p$ EDepth, 深度
: a5 P2 f) E5 m' M4 ?' EDerivative matrix, 导数矩阵% f4 F# T) m8 z1 I# a2 J' Z: ~
Derivative-free methods, 无导数方法2 r& E1 Z+ e9 y# u' N" z& n- G0 q
Design, 设计' H" |, e( m g+ M2 W9 z! ]
Determinacy, 确定性
; U/ C! m- n& W7 v, {5 r! }( \Determinant, 行列式
Q* ]. I9 i, vDeterminant, 决定因素# ^$ W8 C$ {. \
Deviation, 离差: L6 K3 _8 o R8 P2 Y
Deviation from average, 离均差
6 `; W( E* j' [ i% {7 ~Diagnostic plot, 诊断图
3 W% }! f8 q- h9 ZDichotomous variable, 二分变量
4 u2 R8 e7 W# ] z- n# Z0 a0 jDifferential equation, 微分方程& s! l. M. i; M; T1 k
Direct standardization, 直接标准化法 R3 U* j3 H$ G) X# A
Discrete variable, 离散型变量3 i2 f7 O, R$ N9 D5 j8 e
DISCRIMINANT, 判断
- x, }# @8 Z0 A/ E+ }" UDiscriminant analysis, 判别分析/ D$ Z) t1 O2 v# q
Discriminant coefficient, 判别系数: [( n5 v: @" ^; E4 m4 `
Discriminant function, 判别值
1 R/ ~: B7 F) Q: S: a; pDispersion, 散布/分散度. y: G3 J7 k( p! X0 D# m
Disproportional, 不成比例的1 H9 u2 F" {- L! Q }
Disproportionate sub-class numbers, 不成比例次级组含量 p. e2 h3 h7 P
Distribution free, 分布无关性/免分布
1 p r1 `& \8 t* V( pDistribution shape, 分布形状
3 w. m0 s, j( r7 sDistribution-free method, 任意分布法
8 C i( Y% V2 _Distributive laws, 分配律
2 F2 t$ {/ t% P" h0 tDisturbance, 随机扰动项: f# y5 l" \1 g2 n
Dose response curve, 剂量反应曲线$ ~& J0 L+ W' Y
Double blind method, 双盲法% Z- `. p8 C. B1 X$ r
Double blind trial, 双盲试验
7 s) w7 D1 Z9 v5 NDouble exponential distribution, 双指数分布
( }6 w- {$ l- Z' T1 xDouble logarithmic, 双对数# C# @% c, z8 y, M n: `
Downward rank, 降秩
, \ J( A* p2 N/ c k' h" \. TDual-space plot, 对偶空间图: N2 O) _% x4 T! \* c( W
DUD, 无导数方法
" o; k e1 h; |( o5 C+ Q+ W" qDuncan's new multiple range method, 新复极差法/Duncan新法4 f" O' a7 f" T
Effect, 实验效应- ^% w8 _ B, u. V- z8 B
Eigenvalue, 特征值
2 z7 B1 Z( h) i9 u# S' GEigenvector, 特征向量5 B2 W1 R U% h' J
Ellipse, 椭圆
! |9 g7 j% u9 X( hEmpirical distribution, 经验分布
5 e. G P4 W! S1 N% y# k' k! wEmpirical probability, 经验概率单位( a8 T+ L& c f8 l; h. U2 v
Enumeration data, 计数资料
4 }! P8 l( U+ mEqual sun-class number, 相等次级组含量4 B7 ~5 y& e) x6 l$ H
Equally likely, 等可能
6 r& y( ]' {& {# t, `4 \Equivariance, 同变性4 A; [6 h$ l5 V2 @3 l. y# Q: f+ Y
Error, 误差/错误
" S0 ]% [. F/ U3 u; fError of estimate, 估计误差1 ~3 i, b& O: b0 u; K7 o6 d
Error type I, 第一类错误
* @7 S* t* d/ q9 DError type II, 第二类错误' Q5 V+ c1 g+ P8 S/ i6 {. w7 _! f
Estimand, 被估量3 _7 Z: a. g* I9 |
Estimated error mean squares, 估计误差均方
' i/ a* }' Y; [1 ~0 f# l7 }Estimated error sum of squares, 估计误差平方和0 t/ m" v4 \9 V- r
Euclidean distance, 欧式距离: n; L+ u% M# Y" g' y7 |2 G6 U$ G
Event, 事件
% ^" J3 H- J x) A$ E% hEvent, 事件
$ w& v" v7 P: U: ^ tExceptional data point, 异常数据点5 q- i: r' d! f
Expectation plane, 期望平面 |6 `9 o: \1 ^
Expectation surface, 期望曲面
J" n. F; }" q# S; MExpected values, 期望值
/ s: A) L6 u* j1 GExperiment, 实验
$ B$ p0 L3 }* _, B: B! sExperimental sampling, 试验抽样- H* ^/ U( F) D6 ]4 {, C
Experimental unit, 试验单位
+ X9 d1 k+ Y9 U0 }+ bExplanatory variable, 说明变量
2 k5 x' p, X" pExploratory data analysis, 探索性数据分析# Z% g8 G( ~& u5 J5 ^$ _
Explore Summarize, 探索-摘要( c3 k8 V( P3 r( c4 |
Exponential curve, 指数曲线 s! {, @( g6 n9 z
Exponential growth, 指数式增长$ U1 z: P8 Q( _ @
EXSMOOTH, 指数平滑方法
3 M w; ]' t7 o! ?Extended fit, 扩充拟合, ^, e/ l- \% ~1 h" C7 A; G
Extra parameter, 附加参数
$ A% x" Q& t7 d6 F; k7 A) M2 c7 ^Extrapolation, 外推法# A% b0 W' s; ~0 r
Extreme observation, 末端观测值
7 Z1 `6 @0 Q$ K1 b i2 k( VExtremes, 极端值/极值$ e9 x3 u$ e% X6 o$ e2 A6 `
F distribution, F分布
! p2 C& Y8 j: N( Y6 zF test, F检验5 E9 \; I0 t+ e6 Z! c! Y" F
Factor, 因素/因子5 u1 U/ b7 f- M" U& D* j
Factor analysis, 因子分析
. H5 ?' y! Z& a3 M" O% v) Q2 q! t$ wFactor Analysis, 因子分析" Z( ~3 O/ a3 h' k& W5 o6 ]
Factor score, 因子得分
2 n; x: j0 Z5 }+ gFactorial, 阶乘
7 v6 l/ K" g' k! ^" t: _Factorial design, 析因试验设计' \' a; b- g7 @
False negative, 假阴性* v+ F( g0 E5 s! B
False negative error, 假阴性错误
( N- Q- b- y1 v( _& OFamily of distributions, 分布族
! {* o3 P7 f# b( eFamily of estimators, 估计量族
" t) y- C+ V+ p4 a$ DFanning, 扇面
4 i* }" l% n( ?Fatality rate, 病死率+ c e w6 t. o. h1 W9 a2 k8 b# n
Field investigation, 现场调查% ]; y% ?' X; K k7 w
Field survey, 现场调查
; Z* w6 M3 O$ a2 W- EFinite population, 有限总体- _, b! u6 E& c, r7 {
Finite-sample, 有限样本' E% l, m$ I. R
First derivative, 一阶导数
' j+ I: | B9 ~) I$ s: HFirst principal component, 第一主成分0 {7 P! r# R0 W k4 i/ \
First quartile, 第一四分位数6 B$ {5 F# f( i1 v- _
Fisher information, 费雪信息量
# l6 V x7 `+ p+ V6 IFitted value, 拟合值( A5 ~5 {5 ]9 d! ~: n2 [0 v
Fitting a curve, 曲线拟合: W7 r: z/ r6 U- X
Fixed base, 定基& z( H9 E4 ~9 q- U: `3 F0 y
Fluctuation, 随机起伏
9 O2 E+ @5 O# h8 z+ U$ l2 lForecast, 预测
" `; f7 A/ {: M/ M ]1 pFour fold table, 四格表
; g2 A8 M4 d, W0 s D5 i# jFourth, 四分点
6 n8 ^( u! x; H4 S SFraction blow, 左侧比率- G! K% \. f7 m' l% ~. w
Fractional error, 相对误差
* ~0 K3 e1 V0 n4 o; v1 Y' _Frequency, 频率4 V# f# K# V! v. q; y2 G8 n
Frequency polygon, 频数多边图! I& z; h* g" C* e8 Z
Frontier point, 界限点0 E! u- i2 C( g" c3 ~6 ]
Function relationship, 泛函关系( v- X9 l- J2 y
Gamma distribution, 伽玛分布
) v& K) f4 `* Y A! UGauss increment, 高斯增量
9 e' q3 A4 P& ?0 vGaussian distribution, 高斯分布/正态分布
. j; M3 c1 P# D- e# s) J8 |8 v: rGauss-Newton increment, 高斯-牛顿增量' [# k) i9 d% O2 x6 P9 x1 E$ G/ Z
General census, 全面普查3 ]1 i# Q, t: P4 \+ y
GENLOG (Generalized liner models), 广义线性模型 4 _6 |/ J' B) G7 T
Geometric mean, 几何平均数, w" @# P3 M0 Q; A* k- y+ d$ G4 `' C. o/ S
Gini's mean difference, 基尼均差
" q9 G/ k7 J/ [GLM (General liner models), 一般线性模型 % s$ }* d- ~6 k+ b R7 a
Goodness of fit, 拟和优度/配合度
3 e& \$ I8 G* ^ A0 uGradient of determinant, 行列式的梯度0 X1 ^- K/ b1 h3 U/ s( W* S: S
Graeco-Latin square, 希腊拉丁方
' Y1 |# I" ]- u# \$ O& RGrand mean, 总均值! e% [ b7 R9 ~2 K, p. x
Gross errors, 重大错误3 M2 j3 q8 E2 d9 D
Gross-error sensitivity, 大错敏感度. [1 R. `- c1 f8 }5 Z
Group averages, 分组平均: B# J( @( y0 n/ s! u. x
Grouped data, 分组资料
! S$ ^2 I& }1 E; j3 g& IGuessed mean, 假定平均数
4 d% {# X. V; x0 o& VHalf-life, 半衰期$ Y! Z# K" D- a( ^4 s
Hampel M-estimators, 汉佩尔M估计量: a' W# y% ~& K! z: k0 p' B
Happenstance, 偶然事件
; M# k3 ~4 W! t: m4 t8 g; PHarmonic mean, 调和均数
. E/ I# z! _: ^" U5 D: e/ O% jHazard function, 风险均数8 T. [. y9 ]% _2 p8 R' w4 A
Hazard rate, 风险率
0 O$ Z; x) t) ?& \0 eHeading, 标目 * S, p Q6 w7 @+ q
Heavy-tailed distribution, 重尾分布
( D8 W6 k9 F$ n: z" r z5 w& H5 n- zHessian array, 海森立体阵. {- t8 M N+ m
Heterogeneity, 不同质$ Q. k! L- f g r* ^
Heterogeneity of variance, 方差不齐
# U& A7 g( ]# b) e- rHierarchical classification, 组内分组 y' g9 U1 i- @ @9 P: w
Hierarchical clustering method, 系统聚类法
9 G2 d7 f$ L# w- c3 T6 b: kHigh-leverage point, 高杠杆率点) @9 I+ M' j1 z
HILOGLINEAR, 多维列联表的层次对数线性模型
o: B$ H/ J1 q; uHinge, 折叶点3 j4 u) M. r: w5 T3 I0 Q7 T! {& N
Histogram, 直方图8 B. b5 v0 @% |8 w
Historical cohort study, 历史性队列研究
9 q0 Y8 ]+ Z# V" f' {( {: ^' o! hHoles, 空洞/ V! s( B8 o8 p
HOMALS, 多重响应分析 @ f5 u; _ _+ [
Homogeneity of variance, 方差齐性
# T" g9 u; f$ b2 J9 pHomogeneity test, 齐性检验. a2 ]7 ~5 y6 G
Huber M-estimators, 休伯M估计量$ I8 p9 F& N0 V5 x: u- `2 @0 X
Hyperbola, 双曲线/ k, `" p- o2 g* O
Hypothesis testing, 假设检验( [' b6 q4 p7 ?. y+ [
Hypothetical universe, 假设总体5 d9 `0 Y5 k/ ^* {" @
Impossible event, 不可能事件/ c: L- i$ r3 m( b% P4 [
Independence, 独立性
# ^+ _5 F5 Q8 T! ^Independent variable, 自变量% k. N- o% C& E1 J* S
Index, 指标/指数
/ o* T/ `% Z6 W' M2 e- Y6 RIndirect standardization, 间接标准化法
0 H, ]/ i6 w3 j' tIndividual, 个体
5 J. Z7 J. w6 G( C' X2 x2 m- N) pInference band, 推断带4 Q7 K R0 G3 n
Infinite population, 无限总体
' d" X7 N# s5 }/ S0 G" ~) W; k% B' eInfinitely great, 无穷大
, R: T: v) H+ s+ p) P( b; w; TInfinitely small, 无穷小
; r6 M5 x( @+ KInfluence curve, 影响曲线" w. S7 P3 G* p+ j* r2 Q
Information capacity, 信息容量8 G$ W) `: R9 r1 s
Initial condition, 初始条件1 t8 m, g0 \: k
Initial estimate, 初始估计值
, L. @, P$ q& F7 {; oInitial level, 最初水平
6 I4 e7 u. d9 e/ t5 SInteraction, 交互作用
, |2 e5 n. U, u& S! FInteraction terms, 交互作用项& c6 H4 d! c8 n# i) M
Intercept, 截距7 i7 ?( L- r( d8 b! J8 y4 q
Interpolation, 内插法
. h1 y* e+ K- k4 |Interquartile range, 四分位距! c7 D/ W. b3 f, P
Interval estimation, 区间估计
5 {9 D a" a9 O, TIntervals of equal probability, 等概率区间
, ]* F" i9 x1 `* S! W% `! R4 C3 cIntrinsic curvature, 固有曲率/ v$ N$ V$ m* \+ [) B; ^; A
Invariance, 不变性 \! X/ V; @2 @+ i( E9 D$ e: I
Inverse matrix, 逆矩阵4 G1 _: Y# h; t- j2 i
Inverse probability, 逆概率+ h+ [+ U6 e' D
Inverse sine transformation, 反正弦变换* d/ S! [- G- v9 e8 _8 ~" G3 o# j8 h
Iteration, 迭代 ! { e6 X. w* X* F9 K% g
Jacobian determinant, 雅可比行列式 ]# r1 c2 c k$ k. T
Joint distribution function, 分布函数3 P* I6 t: B: _( n9 `" X) h
Joint probability, 联合概率
. Y6 |0 O' C% @0 dJoint probability distribution, 联合概率分布; {6 c6 _& y1 D8 n
K means method, 逐步聚类法
7 L, P. t4 J) c& ~Kaplan-Meier, 评估事件的时间长度
' |+ ]- w: j- A6 ^# QKaplan-Merier chart, Kaplan-Merier图5 H9 n% F4 Q! I# a6 P9 n, O
Kendall's rank correlation, Kendall等级相关
" {: O9 `. Y! \, |6 MKinetic, 动力学4 h0 ^ _1 r% E
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
) I) S- }3 w/ x: n/ U# |Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
% G; }5 @8 M8 R2 F# n1 ~* V; PKurtosis, 峰度6 k! @5 y" `6 B y; K
Lack of fit, 失拟9 i8 C' n" w, J# _
Ladder of powers, 幂阶梯9 o- Y) K$ P% W6 A4 E7 ]8 }3 f
Lag, 滞后
, R& ~2 T) t. ~5 W8 V( yLarge sample, 大样本
M' Q$ g1 C& Y* p" rLarge sample test, 大样本检验
( ^0 _+ B O# RLatin square, 拉丁方' j2 m+ ^- x3 C
Latin square design, 拉丁方设计
- J+ ^) Y: W% a1 S2 S* G# {Leakage, 泄漏
3 v ^3 ^" K. h. K+ Y- p- R. ALeast favorable configuration, 最不利构形
% I& o. @! y9 ]3 u% ]" RLeast favorable distribution, 最不利分布# S1 p4 t5 K: R* O( }! A4 c' v7 X- Y
Least significant difference, 最小显著差法* t& b/ A: d6 v# T: T9 Y$ L
Least square method, 最小二乘法9 }# f% d, Y$ i6 C3 ]
Least-absolute-residuals estimates, 最小绝对残差估计
( f, \) m& K* r$ Y% zLeast-absolute-residuals fit, 最小绝对残差拟合
+ h- v4 y; I, H% MLeast-absolute-residuals line, 最小绝对残差线; x% c0 G0 l; P1 v' r$ Z
Legend, 图例
" t2 Y K3 n3 A/ F2 h( AL-estimator, L估计量
6 q2 o3 f8 t" P' f' U' y; t! SL-estimator of location, 位置L估计量' F9 T& p" P( h+ s
L-estimator of scale, 尺度L估计量, R6 n- J0 C# f
Level, 水平
4 z" I8 f$ b& P8 Y; `/ p- ALife expectance, 预期期望寿命) U* |0 j) X: `5 Y0 |( h
Life table, 寿命表# ^5 a6 h |% D% \$ q5 `
Life table method, 生命表法( E3 G5 }/ Z S7 ]
Light-tailed distribution, 轻尾分布8 u9 j: C1 C2 o$ u8 \ d' I
Likelihood function, 似然函数# p/ C. Q' W- x8 ?
Likelihood ratio, 似然比" n! ?1 p* X3 ^0 @' c) t6 X
line graph, 线图
5 L" h+ c) b) u# s# ALinear correlation, 直线相关
1 j- D, L4 p3 I( `Linear equation, 线性方程
8 I. Y# t, e0 @: p) NLinear programming, 线性规划: B5 n4 ~& Y6 |: b j
Linear regression, 直线回归( Y8 e. I/ t, E! s
Linear Regression, 线性回归0 J% Y1 G' M: {& c0 |
Linear trend, 线性趋势3 E+ c$ n+ \. D2 U. P
Loading, 载荷
& f7 [$ ~' u; jLocation and scale equivariance, 位置尺度同变性
& O3 O" @5 W& f. o- @8 P- R( b9 |Location equivariance, 位置同变性" I$ N, _$ W6 ~- H% p+ s
Location invariance, 位置不变性
x' A \0 j( K+ G6 F- ~9 s" q/ C0 |& ZLocation scale family, 位置尺度族
; Q3 t. P9 @3 `) ~* U5 M7 Z' s! ]Log rank test, 时序检验
2 F2 ]0 [! E9 w }6 {6 g' bLogarithmic curve, 对数曲线
1 @8 l% W% h) `5 v* z' _, V+ d& Z" ^Logarithmic normal distribution, 对数正态分布' F9 |' C, l( {6 i b
Logarithmic scale, 对数尺度
9 r5 r7 F% g: n) ^# X" g% NLogarithmic transformation, 对数变换, a# l e) K( [3 l& B6 Q
Logic check, 逻辑检查
2 u/ L0 R1 Z. P& ]3 eLogistic distribution, 逻辑斯特分布( ]' c/ \ g. N. q# q2 n& R
Logit transformation, Logit转换
' K- o7 n* s1 `" `: I4 aLOGLINEAR, 多维列联表通用模型 0 ~' k6 r% o8 v( `! H2 F
Lognormal distribution, 对数正态分布
) Q$ D7 H+ _" @. }; SLost function, 损失函数7 u1 N: b. H" j2 q2 X
Low correlation, 低度相关) J, u; q2 n$ K& C) q2 u
Lower limit, 下限
; ~: T! H2 `& Q- VLowest-attained variance, 最小可达方差+ H4 K: E" i, [+ o
LSD, 最小显著差法的简称! S4 e% r0 i4 l0 e
Lurking variable, 潜在变量- @9 i* J( w/ v! t) X2 \6 e
Main effect, 主效应
# G3 X4 H: @1 V' |' s8 v# ^Major heading, 主辞标目
9 g6 T4 | D: F3 H7 @. k0 GMarginal density function, 边缘密度函数4 f( u# ?3 O5 J
Marginal probability, 边缘概率
$ w3 F2 ]# B: W# _9 {1 gMarginal probability distribution, 边缘概率分布+ t& p& i6 q* }* |) c
Matched data, 配对资料1 T( ^# r0 U( k% S
Matched distribution, 匹配过分布
8 Q. i' |% p y8 hMatching of distribution, 分布的匹配9 E) [# M0 c3 b% @. e3 ?
Matching of transformation, 变换的匹配7 H3 B" s# U7 ]2 X4 @
Mathematical expectation, 数学期望
" |6 l% w* P$ _+ [, Z' `) uMathematical model, 数学模型
: Z2 s8 p# i+ l. PMaximum L-estimator, 极大极小L 估计量
z7 ?9 _8 w- Z$ h! o# c3 ]Maximum likelihood method, 最大似然法. Z. d; V: M: b$ }
Mean, 均数
+ U' `$ |: R) \' g1 w% sMean squares between groups, 组间均方# [( i! h8 q6 i% ?5 \, M- i+ M. z
Mean squares within group, 组内均方1 g6 f6 D$ |* O/ U1 y! S5 T3 Z) Z# H
Means (Compare means), 均值-均值比较
( u6 w+ P1 h% w' E% ~# p, W5 MMedian, 中位数; S( a* o5 v6 R: F6 A7 s: T
Median effective dose, 半数效量. `$ L& n: z3 H
Median lethal dose, 半数致死量
- A# G) |, O4 q6 f9 XMedian polish, 中位数平滑: V0 m) P6 W- L$ i! W: V1 p
Median test, 中位数检验
6 g* X4 w, o' n+ R) kMinimal sufficient statistic, 最小充分统计量
) W+ p1 e" k: B, C; A: `4 WMinimum distance estimation, 最小距离估计
2 H; ?. c+ s+ ?6 _4 u) o, rMinimum effective dose, 最小有效量# t5 U2 r7 ~% F$ t% V- [
Minimum lethal dose, 最小致死量
0 `0 w2 B; H# b" Y. QMinimum variance estimator, 最小方差估计量% i+ I% R/ I& _) B2 x
MINITAB, 统计软件包5 ^3 c/ f+ x, [, D: W' k; N
Minor heading, 宾词标目
7 j$ h3 a! n7 w& L0 XMissing data, 缺失值+ w' {# s P- A3 H( h* \
Model specification, 模型的确定
& h3 g3 h7 c+ tModeling Statistics , 模型统计
, T9 m- C9 V C7 WModels for outliers, 离群值模型1 A0 c. f J/ s4 v# e
Modifying the model, 模型的修正& C+ c8 B, W! Y! M7 \0 E# D
Modulus of continuity, 连续性模
# r( z# H+ X4 g6 kMorbidity, 发病率
1 Y1 g: M& M [/ _Most favorable configuration, 最有利构形
% C7 ]2 w, R* U1 a/ X+ Z2 TMultidimensional Scaling (ASCAL), 多维尺度/多维标度0 p! C: [. z$ w, V0 p7 \
Multinomial Logistic Regression , 多项逻辑斯蒂回归/ y% u) u: i, N3 x9 u& R. x
Multiple comparison, 多重比较
" E4 K: ?7 a- ]" [% mMultiple correlation , 复相关
0 M+ M* W: f. `- e4 [Multiple covariance, 多元协方差* ]( x1 F" n+ d5 Y) K2 _# Y
Multiple linear regression, 多元线性回归
: k, ?5 i1 e9 b- L2 O. J8 [; N9 {6 R0 \Multiple response , 多重选项, o9 y: Q( ?9 i6 j" V3 r
Multiple solutions, 多解
6 {& X3 D S0 c& z2 EMultiplication theorem, 乘法定理
" U: w! V$ A- IMultiresponse, 多元响应
2 A* ^% s! I# z) \9 R7 oMulti-stage sampling, 多阶段抽样& N& h7 Q+ X/ F. v* r a/ } G$ g6 g
Multivariate T distribution, 多元T分布" W( D6 Y z$ E2 S) K
Mutual exclusive, 互不相容
/ P/ {* ?( w' Q# |) ^/ u. HMutual independence, 互相独立
9 Y: q- a" O' ~) E* hNatural boundary, 自然边界
9 \; ]* n& a- x4 y/ {Natural dead, 自然死亡
0 Y y, q' h2 u" ?+ ^# ZNatural zero, 自然零4 l$ m4 g- [+ q; f$ _; d- N
Negative correlation, 负相关1 i/ J: Y$ k) c% S: J7 I
Negative linear correlation, 负线性相关
7 {8 Z* N ?: T2 N# |5 MNegatively skewed, 负偏$ G' N1 q. U9 K) g
Newman-Keuls method, q检验* y. L5 O; i9 l" v/ N& `
NK method, q检验
5 A Z# m) `6 v1 GNo statistical significance, 无统计意义) {% {+ f. V+ G) [& Y
Nominal variable, 名义变量% X) B3 `& |+ J+ \+ O, i" X0 h+ m
Nonconstancy of variability, 变异的非定常性% {$ j. e% Z# b. R
Nonlinear regression, 非线性相关. a/ I8 e; L i, A6 S. R
Nonparametric statistics, 非参数统计/ n+ w( `1 ]6 ^$ F$ L8 U, I
Nonparametric test, 非参数检验4 c3 F6 K% R; M7 W
Nonparametric tests, 非参数检验
$ S# @$ H* @$ ~' H- e: kNormal deviate, 正态离差
j( k: j( Z! L1 uNormal distribution, 正态分布) m. t3 I! ]! O1 `5 [
Normal equation, 正规方程组* x7 v* d3 S6 R5 R$ w4 f3 W
Normal ranges, 正常范围
8 U3 v0 m8 c2 G& P5 }' |* b* t ENormal value, 正常值
8 S( R! d% d8 Q$ WNuisance parameter, 多余参数/讨厌参数
2 U/ O/ _ t# h, f$ V( @Null hypothesis, 无效假设 / d0 H- }* e% z2 u9 r7 v' n) M
Numerical variable, 数值变量7 B$ P$ y8 ~4 ?/ z. d: v" x6 x- h
Objective function, 目标函数, ?* t* D5 J2 S
Observation unit, 观察单位; M) y2 y6 G2 n7 t1 A! G1 j
Observed value, 观察值; f+ Z$ h( H0 q* \ h; f
One sided test, 单侧检验
0 a. P1 L: C2 aOne-way analysis of variance, 单因素方差分析+ T, r9 k, F/ }4 Y* ]3 E0 j8 ~
Oneway ANOVA , 单因素方差分析9 b' b3 E2 F$ l" o& ?
Open sequential trial, 开放型序贯设计0 p4 z0 p" K9 i& K+ J7 V
Optrim, 优切尾
' P5 ~8 e$ C3 i( \Optrim efficiency, 优切尾效率: Z. M$ m9 A5 J0 ~ G' d# x
Order statistics, 顺序统计量
2 M- ], [3 c6 u7 {Ordered categories, 有序分类* |: ?" g c9 S. P# x8 c
Ordinal logistic regression , 序数逻辑斯蒂回归
K' D4 I3 M! y9 jOrdinal variable, 有序变量3 g6 Z; h+ H: \- ?, ^
Orthogonal basis, 正交基8 ?0 Y# N: B' H" I" _
Orthogonal design, 正交试验设计
! m- ?, N" B1 u o- {Orthogonality conditions, 正交条件
; b; q. a( L, s/ t+ dORTHOPLAN, 正交设计 0 F1 k# F, y0 B5 n& B/ s* A
Outlier cutoffs, 离群值截断点
3 C5 l5 k- @ |! LOutliers, 极端值
" S9 D( Z c e" `* k |2 X3 N% E3 COVERALS , 多组变量的非线性正规相关 8 ^$ b% U+ T f; ^. m% F- e
Overshoot, 迭代过度8 M ?! V9 T; @, _7 m: Q6 @! B' `
Paired design, 配对设计2 ?5 n0 _' @, k6 w' C8 _; u6 Q
Paired sample, 配对样本
; q5 h# @# R0 h2 n$ z" i2 IPairwise slopes, 成对斜率4 T" n2 }4 X# s5 y* i" j+ H7 q
Parabola, 抛物线3 U5 N3 r( k0 U5 E& b# g! e
Parallel tests, 平行试验
# f; c8 C3 @% f" L* SParameter, 参数( N, Q" \0 o2 ]$ U6 C% P0 e
Parametric statistics, 参数统计6 w2 z* N4 J* c/ ]
Parametric test, 参数检验
) X$ J/ l0 d5 hPartial correlation, 偏相关
- i0 G2 m2 F" ePartial regression, 偏回归
8 o' X, f. L: K/ pPartial sorting, 偏排序3 D; l- X- W6 x
Partials residuals, 偏残差9 M: i( l+ U2 \7 D9 { y7 S0 b
Pattern, 模式
6 ^5 M$ C7 E, e' H' @9 F- d+ JPearson curves, 皮尔逊曲线8 e$ G3 W# a4 s% m+ ?
Peeling, 退层
7 Q" _( {1 ~( c5 Z0 P8 aPercent bar graph, 百分条形图
, i8 Q2 I3 |5 o- P7 pPercentage, 百分比
' t- `4 { _0 {Percentile, 百分位数
. n9 `4 E" V4 P! `, R( _Percentile curves, 百分位曲线
* P7 [( {) h. h$ K, d$ u& cPeriodicity, 周期性) s; n& {( \$ c
Permutation, 排列
7 F3 O! v6 t, A% d7 M- j' Q; QP-estimator, P估计量* O7 ?! {0 D" `- H5 @4 G. D
Pie graph, 饼图
4 d. N3 P3 e, m5 vPitman estimator, 皮特曼估计量% j; m3 L) W2 ~$ ]2 G+ w8 [9 e5 {
Pivot, 枢轴量4 f$ r. a9 R/ z% C
Planar, 平坦 w- W$ I- t, D# [6 G* Y0 @
Planar assumption, 平面的假设
7 @; z: n8 s' p6 c. }* l9 H6 B# d" ePLANCARDS, 生成试验的计划卡
z% v* k2 M8 ]Point estimation, 点估计1 x& _5 Q, T+ @2 r! f" E
Poisson distribution, 泊松分布
8 m) W p; V/ ?- mPolishing, 平滑
9 O" g2 _9 r- ^! H; |. r. k( cPolled standard deviation, 合并标准差
$ O7 _; g9 R* C. [Polled variance, 合并方差/ N( F) N1 c) F) G, u5 @3 N0 {8 X
Polygon, 多边图 U% j2 a- n- c6 v
Polynomial, 多项式
8 B; t/ U7 P: J5 CPolynomial curve, 多项式曲线5 x0 l/ @2 t U( P8 y
Population, 总体: k' \; C9 Y; _
Population attributable risk, 人群归因危险度
( c# P2 p! m+ _1 ? t; hPositive correlation, 正相关 U2 D% ]' o c. i" ^: Z
Positively skewed, 正偏
4 b! d W* l$ f! _' jPosterior distribution, 后验分布
4 w8 p2 g' {* I6 A0 P0 X$ k0 iPower of a test, 检验效能8 l/ A1 h$ B) y" V2 n6 `/ [8 j
Precision, 精密度
. p0 b5 V) t3 a4 I! G' P; bPredicted value, 预测值8 j% U1 D2 Q6 Y& T; q
Preliminary analysis, 预备性分析
0 |$ U& p: L9 r% {- |! iPrincipal component analysis, 主成分分析
- q- Y8 r- D" I5 i+ p8 v pPrior distribution, 先验分布
' Z/ B$ P# G% h* T8 VPrior probability, 先验概率) |. N# N" O9 s9 v, W) U8 o
Probabilistic model, 概率模型
- c) k( c+ F7 O" p: l uprobability, 概率; s6 D% J- L' R& _% A- M
Probability density, 概率密度; [( p, C3 S f# ]
Product moment, 乘积矩/协方差
8 W1 N2 |$ t/ Z' LProfile trace, 截面迹图9 P% x& i1 b/ g4 z7 F% {
Proportion, 比/构成比
' @# E+ f1 v7 M% x @1 z; eProportion allocation in stratified random sampling, 按比例分层随机抽样8 b1 D: q! ]3 r1 W" S7 R
Proportionate, 成比例
( X/ _0 t, Y1 x+ \! o s' wProportionate sub-class numbers, 成比例次级组含量
) j3 F' U, C" GProspective study, 前瞻性调查
) w3 ]) U6 n# DProximities, 亲近性 * r% ~9 g9 h2 I& S! C
Pseudo F test, 近似F检验0 ~* X9 u- W. }* P5 {* S
Pseudo model, 近似模型
6 l# q# ~ N' D+ _9 UPseudosigma, 伪标准差
, }5 r5 J3 `% q7 RPurposive sampling, 有目的抽样4 U, D, V- M6 Z5 f% i- c V
QR decomposition, QR分解5 ^1 n) r0 `( J
Quadratic approximation, 二次近似; C5 c2 @8 u# Z2 @9 X7 O
Qualitative classification, 属性分类/ m. k: X5 ?" |' e7 G9 U
Qualitative method, 定性方法
' g& s7 V1 k& h% L" b, Q% ?Quantile-quantile plot, 分位数-分位数图/Q-Q图
5 Z1 h& S' q- A7 F0 QQuantitative analysis, 定量分析( v. m. x# [ Y
Quartile, 四分位数' r/ R( [& G$ Q+ X6 c$ R
Quick Cluster, 快速聚类
J9 l; D7 V/ j8 a w, o! y; GRadix sort, 基数排序
; q" ^4 @" V* }Random allocation, 随机化分组
8 C: E0 Y6 v1 H& j/ GRandom blocks design, 随机区组设计' k3 A7 R* |% m d0 Z5 ^' \
Random event, 随机事件
+ J0 q( h/ ~. ^ B iRandomization, 随机化& ?6 r) h/ l& B% X0 C. s1 z
Range, 极差/全距
. Y7 m [ h/ p- ?6 jRank correlation, 等级相关% S' t8 k9 t! u% h. L) D
Rank sum test, 秩和检验
. k% S: P8 z4 T X* JRank test, 秩检验
* |! o# t7 r5 K+ q" [: yRanked data, 等级资料
' `0 m/ ^% C4 e7 U% WRate, 比率4 Y2 ^& e7 V2 J( ^( z6 a
Ratio, 比例2 }2 D v+ B1 s
Raw data, 原始资料* f( I3 z }9 ^2 }
Raw residual, 原始残差3 Z; q/ v& h+ ^7 S2 L3 d/ v
Rayleigh's test, 雷氏检验
/ ^+ P3 F' A" K2 @0 wRayleigh's Z, 雷氏Z值 * i" I- k! {! m* z- v& }
Reciprocal, 倒数
0 d6 @" J, ~, Y' d7 W! AReciprocal transformation, 倒数变换9 u# b9 M1 R0 c" E& u) q. ^, E
Recording, 记录
* I v6 v" s/ v4 @. |4 m# o% wRedescending estimators, 回降估计量5 d1 f: t9 F% ?% s" r" O
Reducing dimensions, 降维
: j0 O. F5 O8 c- o/ t+ sRe-expression, 重新表达
. d( q' D6 s6 x1 R7 Y; RReference set, 标准组
- T& \* M- o# w( v9 g$ D3 sRegion of acceptance, 接受域
0 u, ~0 H3 }* L' L( s9 oRegression coefficient, 回归系数
* \' G a( X7 A5 L& aRegression sum of square, 回归平方和3 {' \" X0 g$ m1 ]1 |/ d
Rejection point, 拒绝点
1 `# U; r6 R, u& g. pRelative dispersion, 相对离散度
: v; q$ M' L; r( S, D/ f0 NRelative number, 相对数# L" n3 B h( `* Y; M6 U
Reliability, 可靠性: t/ t: G8 @! P9 i
Reparametrization, 重新设置参数
5 H: z/ s8 f2 K9 D1 }! r, j+ v# xReplication, 重复) ~$ g9 z2 b6 a* Z" z, T7 W
Report Summaries, 报告摘要
( Q) C; j" y8 @9 ^* n5 q" \8 lResidual sum of square, 剩余平方和3 s) Y4 d) y0 ]2 e$ O
Resistance, 耐抗性; @+ z5 o! c+ e( z4 j
Resistant line, 耐抗线3 G/ c5 r& ^5 y6 h; Q u ^
Resistant technique, 耐抗技术. }- W4 r/ `1 b* A
R-estimator of location, 位置R估计量. E9 K% l; Y% c& q, d
R-estimator of scale, 尺度R估计量
+ T/ ~0 w9 r: t, U* |' kRetrospective study, 回顾性调查
, F! O* J1 `% x1 d! lRidge trace, 岭迹* V; ^/ F& S5 A" L1 M/ R+ h
Ridit analysis, Ridit分析* v r- S5 _8 u& k7 B
Rotation, 旋转# q8 t" l/ \) o/ A7 `; R
Rounding, 舍入
' e) [0 f& K* B. o6 d0 CRow, 行& h! ^$ a, @7 v: A
Row effects, 行效应
- y/ Y. n8 X+ y) M- j( I/ C+ `6 s9 IRow factor, 行因素- W! a* ~ _& V+ r( ]- w
RXC table, RXC表' X) q' G! I, H) c' D
Sample, 样本) Q1 T$ }5 L( ` {& r5 E
Sample regression coefficient, 样本回归系数 u' n1 D) T2 l! ^, N d3 U& y. I
Sample size, 样本量
7 T, ?! E( r! c) QSample standard deviation, 样本标准差
, B& {' d1 L9 F; S/ y0 h: tSampling error, 抽样误差
5 D6 g, g8 S% Z% kSAS(Statistical analysis system ), SAS统计软件包! P) [+ p+ I( H, [" C9 L2 t5 Z+ B
Scale, 尺度/量表
( T* E; k6 ^& E7 ?5 iScatter diagram, 散点图( Y3 u+ l( z3 e" g o; Z2 H
Schematic plot, 示意图/简图$ A% n5 j2 e6 A" B
Score test, 计分检验
6 h2 _, T2 R5 j& T2 t$ O+ oScreening, 筛检* f/ @. I. D$ K
SEASON, 季节分析 ) ]! B) ~$ w0 P7 p4 ?) H
Second derivative, 二阶导数
# x5 C* J i# M8 k! {Second principal component, 第二主成分
! Z6 y" U9 X. tSEM (Structural equation modeling), 结构化方程模型 . h6 [8 ^0 U/ v& A. A7 k
Semi-logarithmic graph, 半对数图6 M# C$ t6 Z/ z# w+ R
Semi-logarithmic paper, 半对数格纸
( h& Y( N% R9 M; U# N" u& ~( gSensitivity curve, 敏感度曲线. c# a- b8 O- t& o1 B4 r" W
Sequential analysis, 贯序分析: u! I0 E1 t' G0 D# C" p0 b
Sequential data set, 顺序数据集! Q0 N8 ?& d1 x$ _( d+ {
Sequential design, 贯序设计* e8 F# w8 M( G& Z6 \! `
Sequential method, 贯序法
5 B) B" [7 i( Z6 g+ ^Sequential test, 贯序检验法6 j& j1 D: ?- [. ]9 t& K
Serial tests, 系列试验3 |6 {. x5 D+ g, O/ Y4 ]7 }& s
Short-cut method, 简捷法 1 ~, W e/ }9 b4 T p
Sigmoid curve, S形曲线$ H- N) f, J) g" r
Sign function, 正负号函数
/ F0 u( ^- d& e$ j& m/ ]Sign test, 符号检验# h' k @7 g) n/ c7 w
Signed rank, 符号秩* g) E o6 n7 Q& H8 }
Significance test, 显著性检验; f" ~9 w* B' f$ |( O8 F7 Y; Z
Significant figure, 有效数字
9 L" c( A, q( A, C$ u4 ?) {1 ~Simple cluster sampling, 简单整群抽样
; J# T7 g* e% ]8 f! x MSimple correlation, 简单相关3 B8 s& W8 X6 y2 Z# y
Simple random sampling, 简单随机抽样; o, o0 ` d2 l" N
Simple regression, 简单回归
) n: y8 N h: w) B- Qsimple table, 简单表3 N% b. k2 l/ u" G; j9 S
Sine estimator, 正弦估计量
4 F$ r% M0 h( U0 NSingle-valued estimate, 单值估计2 y4 `- P; p; e
Singular matrix, 奇异矩阵
" L5 Z" t' _6 f) USkewed distribution, 偏斜分布
+ g8 q( Q, S/ r9 u0 a* i9 q+ WSkewness, 偏度3 I: ?0 M- _. b3 S- Z
Slash distribution, 斜线分布
" b5 g% o5 L2 ?) }Slope, 斜率
: d; ?# E3 l* z( z4 w; q8 O7 HSmirnov test, 斯米尔诺夫检验# P5 F5 X( m; H
Source of variation, 变异来源+ F6 Z& N6 _, c
Spearman rank correlation, 斯皮尔曼等级相关
2 M1 {6 a7 S3 L) `Specific factor, 特殊因子9 H* O: k" r2 L! f0 ? C
Specific factor variance, 特殊因子方差
+ j8 ^/ h% a( T( CSpectra , 频谱
8 u' j" P: l& L3 n/ xSpherical distribution, 球型正态分布& g+ Z' C+ g$ b/ P8 `8 f6 y1 g
Spread, 展布
& K' x0 ^) h' H0 ^- u; GSPSS(Statistical package for the social science), SPSS统计软件包
2 N/ `( }5 N2 m4 Z ZSpurious correlation, 假性相关
8 w/ @! F# Y/ o6 JSquare root transformation, 平方根变换
# q7 m8 ?- J7 g6 A" o6 x rStabilizing variance, 稳定方差
( ~% g5 i9 C7 G% T1 m6 dStandard deviation, 标准差
0 ]1 \) o: K) L6 t MStandard error, 标准误
0 M, n) I& n: C' p8 s& qStandard error of difference, 差别的标准误; u2 o" A" q, _, L
Standard error of estimate, 标准估计误差* a6 z' H1 k2 z% \ x, {
Standard error of rate, 率的标准误
3 B! |3 G# z! ~5 W! nStandard normal distribution, 标准正态分布. w% L8 N8 z8 c$ E8 q
Standardization, 标准化4 r; d( f& ~- \) z$ t
Starting value, 起始值
- P, p, \1 s, G, i9 |2 ^3 NStatistic, 统计量
& I* k# b- U. R4 p+ HStatistical control, 统计控制
8 _. W& j( i/ z0 j% Q! |! }& vStatistical graph, 统计图6 L; H3 \) R* M% \ K& b$ l
Statistical inference, 统计推断
& M8 w# u1 v& p- j5 l, tStatistical table, 统计表
$ t" S8 C8 o, b" Z* `) B: QSteepest descent, 最速下降法
/ b. N8 q6 {5 L$ X7 w/ qStem and leaf display, 茎叶图 B# r$ J3 t1 b! \' h6 x
Step factor, 步长因子* B% L! s2 T; _) B0 X# O
Stepwise regression, 逐步回归7 U6 r4 J0 j2 K& I+ N. |' E( [
Storage, 存
3 U! i4 e6 Q0 V0 X1 B& b9 T4 t2 ]Strata, 层（复数）
4 e. P& J7 e3 |4 J9 j: KStratified sampling, 分层抽样
7 R! F3 V, h8 C) v- S+ xStratified sampling, 分层抽样7 R' a) l7 y) @! g! x2 h3 R
Strength, 强度* Q; e4 X/ H& w! e7 o. J1 |
Stringency, 严密性! l! o. ?, ~) N$ l2 F$ |! k! X
Structural relationship, 结构关系
6 V& K1 c' w. @6 EStudentized residual, 学生化残差/t化残差1 Q* D# i7 Z8 `; ?2 r t8 U# l
Sub-class numbers, 次级组含量
2 o0 c& X, r8 @& R8 r: t9 xSubdividing, 分割
5 \6 F( v% h2 K# W5 A" w" m" a" F2 mSufficient statistic, 充分统计量5 m S9 X4 N% k# a
Sum of products, 积和* M4 z# _* E% }6 Q5 N3 K2 d9 k0 o
Sum of squares, 离差平方和) e) G. i. H# s+ Z/ W( |& L1 |$ M$ F( K
Sum of squares about regression, 回归平方和& `3 a2 @9 ~8 O$ C# P1 D3 X: a% ]
Sum of squares between groups, 组间平方和! V( v. K( e- d: D( C
Sum of squares of partial regression, 偏回归平方和' }4 W! q L5 ^3 q. x( n1 }0 r
Sure event, 必然事件
* T# t3 f. G& A, SSurvey, 调查' R8 |% t! V1 h. J5 [
Survival, 生存分析
" x$ B: ?% X: K: w) Q/ rSurvival rate, 生存率/ X) p' z9 @9 ?( S
Suspended root gram, 悬吊根图
- t) Y& F. ?6 s A5 bSymmetry, 对称) Y4 X7 ^$ `# F, e& ?& d
Systematic error, 系统误差3 a$ b6 U7 L3 ]4 v9 G$ |# Z
Systematic sampling, 系统抽样
4 z1 O( w# ` ~. k k0 U3 c+ Z: S" jTags, 标签$ q0 h8 b2 R; \' A- T5 P5 W" F2 S2 z
Tail area, 尾部面积
7 x( X" A( Y7 w) e9 [, wTail length, 尾长
) n$ K# i" L' X9 k; S7 \& y# iTail weight, 尾重% U. A# T7 K) i: l9 h9 T
Tangent line, 切线: ^; }1 }+ h2 J+ Y/ V9 c+ S
Target distribution, 目标分布
3 g) {* B8 }0 ]# ]) C) oTaylor series, 泰勒级数
* O" q; L5 K( i+ ?7 f* m" F! DTendency of dispersion, 离散趋势) g p/ B( T0 s: @. a; W, `
Testing of hypotheses, 假设检验9 P F, x3 r4 [1 f3 q; W
Theoretical frequency, 理论频数4 Y. A! D" j2 a, | A1 G
Time series, 时间序列" N. O. v6 x( C1 V
Tolerance interval, 容忍区间) m. ]; V8 l3 z* C y$ B- ?( S
Tolerance lower limit, 容忍下限5 w4 c+ N. v+ ~7 \4 r
Tolerance upper limit, 容忍上限- x* u8 K. c& b
Torsion, 扰率
- K1 F7 Z5 S5 K; Y" ITotal sum of square, 总平方和0 j7 n C; c. g- h' w3 q |
Total variation, 总变异$ ?8 Y% O3 P, P1 ]) q/ X" |
Transformation, 转换
: F" p5 b; f. j4 v# d$ R" gTreatment, 处理
& ?8 B1 s& H8 D( ?* f+ p! uTrend, 趋势 I# `* \3 l7 k5 n1 A0 X S8 S
Trend of percentage, 百分比趋势
! i9 p# v7 o9 H( U. e1 ?0 HTrial, 试验
! j; w* f, y X+ XTrial and error method, 试错法# \3 U+ ?7 F( a. z# |/ U, J
Tuning constant, 细调常数" ^9 J" q, M& D# B' ~( L7 ?
Two sided test, 双向检验
+ S2 j. @7 f. S# B0 @) nTwo-stage least squares, 二阶最小平方
; \& ?+ ^8 y: W( UTwo-stage sampling, 二阶段抽样
+ S+ f4 C% `) H5 c* ^1 hTwo-tailed test, 双侧检验
3 N( M) x2 `+ yTwo-way analysis of variance, 双因素方差分析! m3 N) x9 {# [+ D: `
Two-way table, 双向表
; F) S) K' M( K( x9 wType I error, 一类错误/α错误# \, q) J. _* y8 o4 N4 l
Type II error, 二类错误/β错误
% g" C: F- f) kUMVU, 方差一致最小无偏估计简称9 a+ h R1 Y8 R# A, b* ~
Unbiased estimate, 无偏估计
( X k l \3 ]1 E, h) HUnconstrained nonlinear regression , 无约束非线性回归' {& A% q% V, {7 P* R
Unequal subclass number, 不等次级组含量
0 R5 q$ E. }- s* sUngrouped data, 不分组资料
( r2 o! O1 F) } [Uniform coordinate, 均匀坐标& \; J" B4 w4 g6 S( B( ~
Uniform distribution, 均匀分布
* X/ ?. B L! Y6 U) x# EUniformly minimum variance unbiased estimate, 方差一致最小无偏估计& Y& i N. n% ]
Unit, 单元/ i4 a5 ]+ t+ E4 s
Unordered categories, 无序分类7 M( n! ^* K. c7 t
Upper limit, 上限
" G/ F l4 o+ t n1 z& f2 pUpward rank, 升秩
/ B/ m2 ]* p* j9 gVague concept, 模糊概念) T2 K" _. M* S! E4 \) ?
Validity, 有效性5 U8 a4 ~- [% Z% E( u9 M- Z
VARCOMP (Variance component estimation), 方差元素估计
- A$ O) E e N& g; K# X) F* O+ r0 H$ [Variability, 变异性
. S. h' ~9 g1 O) x1 t; m/ e' n7 D5 U7 wVariable, 变量
! N6 y& Z6 |7 JVariance, 方差
1 { m; |; S1 W: x6 b& R' bVariation, 变异
# M; ~" x4 L' v7 z+ N; |; ~- XVarimax orthogonal rotation, 方差最大正交旋转
3 Y# G# c- o5 X5 P5 CVolume of distribution, 容积
/ ]% U' [& w; [& _+ SW test, W检验( \8 n# }. ^- U1 |. Q1 M I; K
Weibull distribution, 威布尔分布
+ f$ D2 v* ^7 pWeight, 权数
& h; v" |" Y6 s) u7 w$ bWeighted Chi-square test, 加权卡方检验/Cochran检验! r7 W4 u' P/ m. A
Weighted linear regression method, 加权直线回归
4 L5 u ?) q' e4 }" F1 [Weighted mean, 加权平均数7 ^3 H7 {3 `: M9 X8 J
Weighted mean square, 加权平均方差9 w) v$ C% m. b& Z) k9 J2 U
Weighted sum of square, 加权平方和2 R/ [- o# ~! j
Weighting coefficient, 权重系数* `, k8 R( W# k8 ~& n
Weighting method, 加权法 ; r6 k/ E; o0 x2 C
W-estimation, W估计量
1 Q4 Y+ u+ f( l7 Z* ^W-estimation of location, 位置W估计量
8 ^* C, z8 a) e$ b2 T5 cWidth, 宽度
" r+ o" l: a) cWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
# I8 ?) Y6 p' P6 d+ lWild point, 野点/狂点
( W% h% Y' F$ T4 dWild value, 野值/狂值
) x% o9 s. u) qWinsorized mean, 缩尾均值
0 ]& l* a) j2 Q, Z9 Q. \7 jWithdraw, 失访 : {) z; U' D# G2 c6 y
Youden's index, 尤登指数
# g1 g; c6 x& U2 r. J3 o" UZ test, Z检验
& {, e. ^5 D# ]4 R. H3 T$ LZero correlation, 零相关
/ ~/ H) e% \( A( P$ W* V5 T3 }0 ?3 yZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
