|
|
Absolute deviation, 绝对离差
4 V# K0 i* T0 L- QAbsolute number, 绝对数
; v J& D/ z+ U) iAbsolute residuals, 绝对残差7 I. Z2 }) G' _% \1 x/ f d+ }& K7 p
Acceleration array, 加速度立体阵
3 ]- j: K! K! {9 H) @) z+ |Acceleration in an arbitrary direction, 任意方向上的加速度
8 F# E8 O; T# l! oAcceleration normal, 法向加速度# ^2 z' Q8 y' s! S
Acceleration space dimension, 加速度空间的维数; j& P% [/ G% V- S6 l9 H& A, H: }
Acceleration tangential, 切向加速度
; C5 F2 v0 q5 l0 U# Z/ ]; R+ nAcceleration vector, 加速度向量
) W7 E0 E% @% P* _ S* ]# n1 O6 yAcceptable hypothesis, 可接受假设
( e3 U1 |( s; M( A2 GAccumulation, 累积) l$ B! _2 O2 K9 c- a. }
Accuracy, 准确度8 A/ n* y% `' q9 z& T
Actual frequency, 实际频数
# u4 X$ }6 Z" a- U0 ^Adaptive estimator, 自适应估计量7 Z# `% h& l+ ?
Addition, 相加" A/ A$ ~# d3 m" k1 L
Addition theorem, 加法定理" E. @6 a U3 a% t! L4 R. c
Additivity, 可加性
+ G7 t% `( w7 G3 ]Adjusted rate, 调整率
1 K( i# S4 Z+ ]/ Q tAdjusted value, 校正值% i% r* ?; K8 G
Admissible error, 容许误差
$ ^; O+ ?8 s' w" gAggregation, 聚集性0 V' O3 Q% l! K: ~7 b9 T
Alternative hypothesis, 备择假设
, w% `" v% n9 b9 N% m, F: X7 bAmong groups, 组间
& ~) p( M4 o) H9 LAmounts, 总量
+ \& ^8 [. }0 R6 w9 @- a, _" WAnalysis of correlation, 相关分析9 M' S$ D: `9 i! g0 y, y6 z
Analysis of covariance, 协方差分析, a) v+ E2 c7 a* v* {9 C# x
Analysis of regression, 回归分析
; ]( c$ r* M. |! f7 O4 D5 V, `Analysis of time series, 时间序列分析
2 ]2 K2 e' T, R, J. @5 ?$ a) kAnalysis of variance, 方差分析) `' w0 R( J: T1 D& a" @
Angular transformation, 角转换6 e2 _/ V+ L1 S K
ANOVA (analysis of variance), 方差分析
W$ H. y9 \# r, F1 cANOVA Models, 方差分析模型
& i8 t) T- m' d6 Q) fArcing, 弧/弧旋
) F; L8 Z9 n& \/ a2 D9 Z1 ?Arcsine transformation, 反正弦变换 `1 d& u2 V3 d: r
Area under the curve, 曲线面积
m/ x3 @: o: J$ v& f/ p8 VAREG , 评估从一个时间点到下一个时间点回归相关时的误差
7 u. F2 u: s# s, W9 V$ S' y* j1 uARIMA, 季节和非季节性单变量模型的极大似然估计
3 v4 l7 w. t7 m# t& \; i, cArithmetic grid paper, 算术格纸
. V ?9 C) V- Y. Q* p# \, [Arithmetic mean, 算术平均数
' ]4 u) K5 q1 R6 [Arrhenius relation, 艾恩尼斯关系( K7 I, l4 D- g! R. l g3 V& A5 l
Assessing fit, 拟合的评估( A6 v4 x- X& i! D0 V
Associative laws, 结合律
: c4 _7 _. w7 }6 J8 y5 v; pAsymmetric distribution, 非对称分布
$ A( \# I, ?6 S! I. v* C/ HAsymptotic bias, 渐近偏倚4 W0 ?+ \* N: q2 i% w0 u
Asymptotic efficiency, 渐近效率
/ ?3 S2 k3 }/ a/ A* I0 X: cAsymptotic variance, 渐近方差, r; Y" R0 |$ ]+ V2 k
Attributable risk, 归因危险度
+ s* t9 C5 [/ WAttribute data, 属性资料7 s. x% Q" Q% S* D0 Z" H
Attribution, 属性4 d9 r/ V; H3 `+ ?1 n
Autocorrelation, 自相关* a. i8 f" C% i
Autocorrelation of residuals, 残差的自相关
0 I5 J2 U# Y( i1 ~# P7 R# R1 NAverage, 平均数; i' f2 ^5 g& x# e( i7 ]
Average confidence interval length, 平均置信区间长度
3 M6 C+ B$ I& n; k& RAverage growth rate, 平均增长率
6 y( P5 a9 F" _: G" @) n8 ZBar chart, 条形图
! f9 E4 ~0 C0 R2 d6 G. @Bar graph, 条形图1 e8 D% B) E% J: I
Base period, 基期* i4 S/ y: L+ X- t c. M- B
Bayes' theorem , Bayes定理5 h/ D: c) x( J6 |7 h* l
Bell-shaped curve, 钟形曲线" ?$ k9 m/ A1 K% l% y+ _8 S
Bernoulli distribution, 伯努力分布
4 V9 c2 z8 k, WBest-trim estimator, 最好切尾估计量
( j9 ^, K. E0 [Bias, 偏性! h, h; |3 F4 d. c
Binary logistic regression, 二元逻辑斯蒂回归
* q5 w% E0 D$ k5 M. l' RBinomial distribution, 二项分布
6 g* f0 n! Q6 b8 X' U9 QBisquare, 双平方
1 X% K$ ?8 X9 O8 _4 j- m4 pBivariate Correlate, 二变量相关
% X+ d7 Z% N- p' aBivariate normal distribution, 双变量正态分布
) `' ~0 S5 J# _6 qBivariate normal population, 双变量正态总体 G( R: M3 r+ B$ [* P
Biweight interval, 双权区间9 p: W, O/ Y {$ E
Biweight M-estimator, 双权M估计量
+ ^, `# ?6 Y7 r ?/ [4 B# mBlock, 区组/配伍组
3 ]; Z \8 k D J" q" K+ J8 }BMDP(Biomedical computer programs), BMDP统计软件包
" f% \8 F) o" z, g# Z: TBoxplots, 箱线图/箱尾图2 j0 _* K: _) a% x3 n2 e3 g2 K9 E3 l
Breakdown bound, 崩溃界/崩溃点
$ x$ {5 q" l& ~1 f" ^: H7 `3 k# UCanonical correlation, 典型相关1 e3 a- x/ I7 N8 ]
Caption, 纵标目# ] l) \; ^" g9 ]3 j" S* R2 q; K
Case-control study, 病例对照研究; m4 x$ _! i0 v* y9 i8 R/ y1 V. r
Categorical variable, 分类变量
3 w0 _4 M; G$ N/ @: f# H V: DCatenary, 悬链线7 P a7 _0 f9 H- d% H& o9 g0 Z
Cauchy distribution, 柯西分布
1 K2 a |/ B& w$ m' kCause-and-effect relationship, 因果关系
- o* v( |# ~3 i3 PCell, 单元
# U5 r! j4 u8 V- c: `- nCensoring, 终检1 {$ d# Z7 t; b7 X# P& q( I y b, x
Center of symmetry, 对称中心
5 P# |7 H2 T& {$ K- f& `Centering and scaling, 中心化和定标( Q7 T7 W& c+ z+ C
Central tendency, 集中趋势
3 n) n6 r/ q, o2 G I! b' q9 q, \, {! ^Central value, 中心值6 r8 [% x' M1 U% `1 v; r/ |
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
$ z9 ]% Y3 W% h9 M4 [( S4 g% yChance, 机遇3 p/ m2 o I& E0 s
Chance error, 随机误差7 N0 t: t( R% S# ]. v/ P
Chance variable, 随机变量
% [% o+ Z/ F. TCharacteristic equation, 特征方程
5 w5 F5 D* T# z6 ~. B: xCharacteristic root, 特征根
- Z6 j0 C) M! ]* cCharacteristic vector, 特征向量
8 v7 F! E/ t, H7 pChebshev criterion of fit, 拟合的切比雪夫准则
: C$ K/ w" u9 D ?* C$ pChernoff faces, 切尔诺夫脸谱图
& V) A r7 H8 C8 R' J4 G6 ~& JChi-square test, 卡方检验/χ2检验2 p: Q _- N1 ^/ h% x+ h! D9 `
Choleskey decomposition, 乔洛斯基分解9 C& y! I5 p: \! O0 Z0 G# r: ~
Circle chart, 圆图 + ^, Q9 k! w4 l# w
Class interval, 组距
" m* E6 ^4 i3 F4 wClass mid-value, 组中值
; q1 \/ @ {) NClass upper limit, 组上限0 c/ @% {; w# z
Classified variable, 分类变量! w8 q$ U1 k- b* |, z' D% A2 s
Cluster analysis, 聚类分析
. {) s2 S; j8 H+ a# |) cCluster sampling, 整群抽样 B7 l- e- a+ S( O) W. G! @/ q
Code, 代码7 V. J0 z5 l- d0 e9 Q
Coded data, 编码数据
: u# x& ~) [0 VCoding, 编码
6 a4 k/ G1 Z* j5 I3 m. F" a/ iCoefficient of contingency, 列联系数
z: z) K8 E( I) D+ b' g5 ZCoefficient of determination, 决定系数- g# Q/ ?! ?8 l# A
Coefficient of multiple correlation, 多重相关系数3 d9 j4 g8 L9 T, |6 k7 N
Coefficient of partial correlation, 偏相关系数
1 q( c; j }( F9 c: d2 T' l# XCoefficient of production-moment correlation, 积差相关系数$ w/ n: y7 Y# y$ y5 _) D
Coefficient of rank correlation, 等级相关系数
5 M5 z# G- H- _; mCoefficient of regression, 回归系数0 `. b3 I2 p/ L+ I) t% C
Coefficient of skewness, 偏度系数
8 y6 J' ]7 A5 y6 c1 j) `# T1 P9 A& lCoefficient of variation, 变异系数
( p# o; d. {; t/ X( B; }4 N2 D) QCohort study, 队列研究
v [! X& p6 n* |/ bColumn, 列 j9 s) K- R0 v, s! b6 J5 j# `
Column effect, 列效应8 Y( a/ y9 ?/ Q# t
Column factor, 列因素
. q, }3 d3 Z' ]) w mCombination pool, 合并& Q$ x& A# r, s: O* z
Combinative table, 组合表% I4 J+ @* z3 ~* F. v. O" o7 |
Common factor, 共性因子
) G' b# L! h. B% M0 W9 eCommon regression coefficient, 公共回归系数
j+ x3 P& f) k0 XCommon value, 共同值! f$ X& k# j! V- R) _; k5 Q' p5 O
Common variance, 公共方差& j! Z6 L) |; {2 v. {
Common variation, 公共变异
- I0 P4 [5 t+ C/ C, [& U. n2 o1 s wCommunality variance, 共性方差
: o9 N, f1 X. _- o2 e( \Comparability, 可比性: n8 |9 J% ]% F, R% T
Comparison of bathes, 批比较% \" I C5 M1 C; w% N$ ^8 J6 I( I
Comparison value, 比较值
3 `- H6 F8 [- n4 CCompartment model, 分部模型( O, f) ~1 {& F* Y3 t
Compassion, 伸缩
4 |$ U. s+ X+ J1 ]) B! d sComplement of an event, 补事件8 X+ I* R1 b6 m( B4 K
Complete association, 完全正相关% C" W1 m6 ~) X4 R/ @3 `
Complete dissociation, 完全不相关6 T; _4 a4 `/ K" p! y% T8 w
Complete statistics, 完备统计量
/ u b( d' P& a$ N+ l0 MCompletely randomized design, 完全随机化设计2 X/ s( n8 T* i/ n
Composite event, 联合事件
/ [, ~/ n; L1 v eComposite events, 复合事件
7 Z' S6 t: c1 l' a) fConcavity, 凹性
% U, D" k5 H/ O4 T3 A3 l. FConditional expectation, 条件期望' P' D, z! Z% z3 r7 h
Conditional likelihood, 条件似然/ r9 n. X+ C8 ~9 g3 `1 u: ^
Conditional probability, 条件概率3 Q4 P% n C U' v8 a) I
Conditionally linear, 依条件线性
9 W7 q' k" `3 M- LConfidence interval, 置信区间
: ~0 n2 R9 X8 w" HConfidence limit, 置信限
: G4 h. p" v: O H( |Confidence lower limit, 置信下限
* j3 t. D" [- v+ [: S" X$ qConfidence upper limit, 置信上限
; O4 Z( t! k" | Z" TConfirmatory Factor Analysis , 验证性因子分析% P/ r" \' k9 D5 T9 G
Confirmatory research, 证实性实验研究
+ O+ Z0 O# [: b* s* jConfounding factor, 混杂因素" X8 g- A6 d6 v6 Y$ Y5 g. k
Conjoint, 联合分析
, u. v" }, l5 b! U) C& P( A7 M \Consistency, 相合性5 S" f9 L( N. `2 n2 _4 D8 F
Consistency check, 一致性检验
2 q1 M$ }3 H* o: j0 C% xConsistent asymptotically normal estimate, 相合渐近正态估计/ F! y, g! K& a) R# ~
Consistent estimate, 相合估计
) B( o1 x2 G5 a$ t9 C" aConstrained nonlinear regression, 受约束非线性回归0 d) B6 P6 }3 X- \# m
Constraint, 约束
6 n2 V" m7 U( L! H4 SContaminated distribution, 污染分布* Q' j. a7 b, v! G
Contaminated Gausssian, 污染高斯分布
6 q' v) g: U2 Y# L: }. R0 iContaminated normal distribution, 污染正态分布 F; a1 C$ C5 Z& [
Contamination, 污染
' p8 a g9 _4 n! c. o/ D. WContamination model, 污染模型
) T9 w$ P, [! D3 }0 }6 w; XContingency table, 列联表+ ]4 T: H v6 T8 c! J" D9 C
Contour, 边界线
' x* U( C& q: U1 I. h0 |Contribution rate, 贡献率
8 M$ o# Z1 C8 T5 Q7 hControl, 对照: T+ @; G6 W9 V, K% R8 y: t$ H
Controlled experiments, 对照实验* g) c% d A, }
Conventional depth, 常规深度. X. b# y3 z' d1 B/ o3 N) y
Convolution, 卷积& U6 ]/ K) W. f* L9 |9 Z* \5 w
Corrected factor, 校正因子& D) h0 \- o9 x+ i
Corrected mean, 校正均值0 A U& ~, J _5 @
Correction coefficient, 校正系数1 K, G2 [: g6 F$ \
Correctness, 正确性$ w9 _5 h( P# ^6 k
Correlation coefficient, 相关系数- y8 G3 }/ s' L- `, A; \& s
Correlation index, 相关指数
% p) f" A# _. s( O' CCorrespondence, 对应& |) D, ^$ Y5 X. [$ {9 m
Counting, 计数
1 Y) a4 B I, o! _ h; j. nCounts, 计数/频数8 m7 ~9 I3 R% v
Covariance, 协方差* k" m* x# m; }! _
Covariant, 共变 5 Q# m( \1 e9 h4 p; _; M$ b, W
Cox Regression, Cox回归
: P, o4 s2 G$ u6 |% J5 W: FCriteria for fitting, 拟合准则
, j4 B, c$ P5 w. D( c0 Q* B# nCriteria of least squares, 最小二乘准则8 [ C- e8 c$ I! P _
Critical ratio, 临界比/ Z' M' K( M! Q8 @0 U X7 Q S
Critical region, 拒绝域' g: \9 u1 N. Y( ]
Critical value, 临界值
" S4 R' l9 K/ x: ~* n5 ]$ d" DCross-over design, 交叉设计9 O9 q3 _3 g! |5 k3 _& Y
Cross-section analysis, 横断面分析4 _; J( U' ~% z. o$ [4 }- R: O% {5 l
Cross-section survey, 横断面调查! o9 R: P- Z* m' r& I8 p
Crosstabs , 交叉表
6 I8 U- O. U- J1 aCross-tabulation table, 复合表
$ P5 }% d; s0 o( a! tCube root, 立方根" _2 e* @! G; X
Cumulative distribution function, 分布函数
/ Y9 ^: p2 e4 }3 \Cumulative probability, 累计概率. r1 P5 j( o* r9 |, H$ ?- M. j
Curvature, 曲率/弯曲
1 W$ L$ j, d" C+ G2 S: C! lCurvature, 曲率
! h* c5 |+ K! L6 a3 fCurve fit , 曲线拟和
9 m) i. H! Q' W/ l9 G/ Y& {) {Curve fitting, 曲线拟合
& l9 g% j7 u+ p" D0 WCurvilinear regression, 曲线回归9 a) h6 s3 i+ e# K% W+ V* F
Curvilinear relation, 曲线关系
" y( Y' a5 M- P/ H! {- u( |Cut-and-try method, 尝试法
0 b; M+ ]/ X0 _' nCycle, 周期2 o+ n+ C. Z' t/ W; b2 o5 @
Cyclist, 周期性- ?6 c. A! ]1 p e* ?5 u
D test, D检验
! u7 M/ F3 s1 G( Q* ]+ [Data acquisition, 资料收集) i0 t& U* |! N6 ^- W" k) t
Data bank, 数据库8 k; x! a# C. i' C# x$ B
Data capacity, 数据容量: |. |' b6 x* [
Data deficiencies, 数据缺乏
! r5 n3 A6 D9 y- CData handling, 数据处理0 V& }; X- I1 ~) G
Data manipulation, 数据处理
9 ~6 e% n3 ?5 [+ ]# x* C/ h- OData processing, 数据处理2 c$ w2 ^! B3 t. z7 ]
Data reduction, 数据缩减, |6 s# C# Z0 {6 T$ ]2 o' P: L5 R
Data set, 数据集
# c" ]0 E+ s4 |" a9 X9 TData sources, 数据来源0 T; ^% N0 x. g( B# }# ?7 ?
Data transformation, 数据变换0 Z" P7 @7 {) M
Data validity, 数据有效性
4 X: T7 E8 `' y6 `Data-in, 数据输入6 [2 e' A) E6 Y
Data-out, 数据输出
& a5 r! Z" j3 @Dead time, 停滞期
: V( G3 S: b2 Y5 PDegree of freedom, 自由度
. t% t6 I' z, p! C5 b1 uDegree of precision, 精密度% F" e3 {, A/ W4 p B8 H" g; ?" b
Degree of reliability, 可靠性程度3 B9 x v& R' ^. m5 H- |
Degression, 递减( a+ [* T8 ]9 F
Density function, 密度函数4 J3 O" s7 Z6 n( B3 P
Density of data points, 数据点的密度
7 A; l; @" e6 [7 _Dependent variable, 应变量/依变量/因变量
3 F9 M+ D' e& F+ fDependent variable, 因变量
1 t+ j, x% C9 Z ?Depth, 深度! v. s, r0 H L) [; k% Z
Derivative matrix, 导数矩阵
3 C' A" j* {$ c3 J! o# gDerivative-free methods, 无导数方法8 o: ~: F8 j( X0 U
Design, 设计
! Q; Q- T( ^7 @Determinacy, 确定性
( L+ B6 {/ f) F( G: Z3 oDeterminant, 行列式& ?% v. [/ W( p/ M3 }9 U
Determinant, 决定因素1 y; s! T3 {% I
Deviation, 离差
4 t) |4 R' D h9 o2 {, uDeviation from average, 离均差
' a5 ]$ M2 K! P4 C, N* @8 m4 ?( U* E) _Diagnostic plot, 诊断图: F J1 I9 p0 o: p
Dichotomous variable, 二分变量% I$ F/ y9 B) M; t& s4 t' N
Differential equation, 微分方程& R7 c3 q: y& t5 M, |, C! p6 c7 ?
Direct standardization, 直接标准化法
. n% S' b3 S# A kDiscrete variable, 离散型变量
/ Z- K8 w; h- r* k8 L/ FDISCRIMINANT, 判断 # c& Q" x9 `* b* _: u, g5 ^
Discriminant analysis, 判别分析
5 P) r5 K, ]9 UDiscriminant coefficient, 判别系数/ p/ X d- w# F, ?/ A4 S0 ^
Discriminant function, 判别值
. ~7 S# e7 @8 c' a3 U* L, p3 J/ \Dispersion, 散布/分散度
6 E) p. A3 A/ @$ Z+ z! c: @Disproportional, 不成比例的
! d9 l, q% }! Q* ~9 sDisproportionate sub-class numbers, 不成比例次级组含量
6 m1 Z m( L/ S" I+ wDistribution free, 分布无关性/免分布) j: p( h5 v) Q" W+ X
Distribution shape, 分布形状6 V0 r, z H F! d3 e
Distribution-free method, 任意分布法" q5 J: r( U; C% @3 C* `
Distributive laws, 分配律
0 I4 ~8 t0 m( P' xDisturbance, 随机扰动项& m+ A* C5 S9 B3 J, T+ N: i' d
Dose response curve, 剂量反应曲线! z( v1 B% o, v+ O
Double blind method, 双盲法
- v" s9 k; @/ ODouble blind trial, 双盲试验8 F2 t2 Z% E- e r7 q/ J% G
Double exponential distribution, 双指数分布
& u0 e" u3 F3 m; ODouble logarithmic, 双对数
3 K3 D, p" o0 c/ T2 qDownward rank, 降秩9 x) K _' S/ H8 h9 }6 O9 J
Dual-space plot, 对偶空间图
. z0 Z/ m1 i& i. u8 K# \DUD, 无导数方法
( K8 f' ?6 C( U! l4 m' ]Duncan's new multiple range method, 新复极差法/Duncan新法3 d$ |! Y2 p5 W2 [0 E
Effect, 实验效应
4 Y# H: u5 b0 I9 D1 xEigenvalue, 特征值3 @( o5 _' _$ `) ]2 h9 b; `6 k" f
Eigenvector, 特征向量) X/ V: ^1 U& F! R( ]/ `0 F
Ellipse, 椭圆; v( _( D) K0 a7 {8 V( B* [
Empirical distribution, 经验分布5 G0 E$ i6 g' y) `: w
Empirical probability, 经验概率单位" ] i& c9 b9 W/ ^, [
Enumeration data, 计数资料3 p. J5 x- S# Z5 X% p/ Y
Equal sun-class number, 相等次级组含量
2 U, z! P% s& ^% C! A6 ~7 p/ GEqually likely, 等可能7 x. c% I1 L5 K6 w3 e) M3 O
Equivariance, 同变性/ g) d4 r9 G) s; H
Error, 误差/错误
4 H \9 s. C: A. gError of estimate, 估计误差
y9 B! J5 @0 t& R$ b. U) N9 eError type I, 第一类错误
2 O1 t, I) M+ m" b5 G9 m1 YError type II, 第二类错误
+ ?, u! I% ~/ d0 e/ q% gEstimand, 被估量
4 k; W: p7 J" l/ o6 \Estimated error mean squares, 估计误差均方
* {. D+ Z! R& @. _6 O- w/ OEstimated error sum of squares, 估计误差平方和
' o: Q! d7 {- ~7 N8 @( A BEuclidean distance, 欧式距离- F/ S4 k: A- S* l
Event, 事件
0 N- c0 u+ q3 k4 wEvent, 事件0 l& f' I; V% v
Exceptional data point, 异常数据点
& a0 r6 K5 z, O# q, m$ LExpectation plane, 期望平面! q# X5 B/ Y& v% i- H" x
Expectation surface, 期望曲面" f3 P: T& \ v% N! L! u% ]
Expected values, 期望值& p& N; s" |' U& S
Experiment, 实验
+ U8 }; ]$ I+ f: vExperimental sampling, 试验抽样 [1 n0 y; S7 D1 X4 q
Experimental unit, 试验单位% R6 \& n: s+ [: O" q
Explanatory variable, 说明变量0 P; |% _5 m- f( d
Exploratory data analysis, 探索性数据分析
' _8 \& K3 x2 c7 M. Q! f0 L1 s- y+ VExplore Summarize, 探索-摘要0 d8 @4 ^& \" c8 X
Exponential curve, 指数曲线
& i2 m6 i. z- W0 ]1 s- c# DExponential growth, 指数式增长
1 d: K; s, f6 I+ V) dEXSMOOTH, 指数平滑方法
: a8 _. `+ S6 t: G$ c- K- gExtended fit, 扩充拟合
. N( T% G, K3 X2 x& eExtra parameter, 附加参数3 H4 b3 T: ]) y/ V6 H" k
Extrapolation, 外推法
5 |$ b1 c# x) Q1 YExtreme observation, 末端观测值
4 Q# j8 w. A) ], AExtremes, 极端值/极值6 i3 x1 `& @; a: v Z" N
F distribution, F分布
. }, c k- w6 g! Y6 F* X) eF test, F检验
* b# M8 e; s# V% p/ Q. _Factor, 因素/因子( Y- o1 H# d5 J& K, U) s
Factor analysis, 因子分析% i6 k$ |9 n$ S7 X
Factor Analysis, 因子分析' b5 u) p9 i8 C5 C R: B" _8 e
Factor score, 因子得分
% D1 Y7 s' g* aFactorial, 阶乘* e* A# m# L8 g7 N4 E( T1 X
Factorial design, 析因试验设计4 Z+ |4 q4 r( [+ T, P
False negative, 假阴性; p2 _+ K7 P2 x# S8 Q9 ~
False negative error, 假阴性错误6 e4 M7 F# ?# u4 o( s
Family of distributions, 分布族
: r( f- Y9 D, y9 j8 ?Family of estimators, 估计量族 k- A; w: E+ l
Fanning, 扇面
. _8 O- [2 t, E4 BFatality rate, 病死率* u) Z6 ]; }' X! B7 n9 p
Field investigation, 现场调查
0 E( S9 ?/ \0 K0 T9 AField survey, 现场调查% K& ?6 Z$ K( z6 r4 p$ s
Finite population, 有限总体
* O8 m5 }4 w% `+ y* SFinite-sample, 有限样本! {6 } ^7 G3 ^: z! Y8 e0 G
First derivative, 一阶导数8 c! Z8 W% r8 ?4 A0 O. j" t
First principal component, 第一主成分
. O E2 H x6 h* a- JFirst quartile, 第一四分位数; k- i2 a% E: o6 c6 U, f
Fisher information, 费雪信息量( D# g+ E4 ^% O' f& s8 o8 [ K& m
Fitted value, 拟合值( y' C2 w+ b/ T) U
Fitting a curve, 曲线拟合
- u; l! a+ P0 RFixed base, 定基* T R* W" w, b( K6 Y" e
Fluctuation, 随机起伏( [$ R$ s- J! q/ g( o* n
Forecast, 预测+ ?) Y4 q% O4 m3 U$ b# t* s D
Four fold table, 四格表
7 D* s! G" L; _5 |2 XFourth, 四分点
8 N* K6 f0 F* U" F9 A: TFraction blow, 左侧比率7 Y! H! c6 `3 Y0 g
Fractional error, 相对误差
* r5 I( l5 O) V) ]8 v \Frequency, 频率
; }7 W* s! T& ]) y5 W( r* tFrequency polygon, 频数多边图3 w3 ]4 g3 T0 ^
Frontier point, 界限点$ D9 i1 K6 y# P+ r
Function relationship, 泛函关系
# ~6 [: h) Q/ iGamma distribution, 伽玛分布6 }8 E0 z' E; O& O2 P0 o- M
Gauss increment, 高斯增量
5 W& f3 j9 `6 n; y5 Q% y+ nGaussian distribution, 高斯分布/正态分布
" ~0 M( A3 ^! c. U% X5 n1 vGauss-Newton increment, 高斯-牛顿增量
& z+ \: v/ V6 I+ s$ mGeneral census, 全面普查
& T6 f; \$ J& z4 FGENLOG (Generalized liner models), 广义线性模型 # l" b& {3 _' M, V- t/ i
Geometric mean, 几何平均数
6 l. _5 }; y; I1 M% JGini's mean difference, 基尼均差+ G- X6 v1 S2 A9 p. K- R, m5 `
GLM (General liner models), 一般线性模型 2 U1 W+ \5 Y) o) @8 @( J# v: W
Goodness of fit, 拟和优度/配合度8 Q' S& P, k3 k+ q, h
Gradient of determinant, 行列式的梯度
5 R! m5 F) P' `2 M vGraeco-Latin square, 希腊拉丁方3 m* M, ^5 K# m3 ]7 \
Grand mean, 总均值
) [! D" s) J, Q/ s- X* [. IGross errors, 重大错误' T* M/ Q2 k5 J6 { \4 d2 _' s$ |2 G/ Y
Gross-error sensitivity, 大错敏感度. Y" v$ ^3 @$ Y' [6 w+ o
Group averages, 分组平均
! r# \0 _% g- @0 y w8 c0 w' tGrouped data, 分组资料8 d5 ^6 P7 ~- c R; `7 H0 t
Guessed mean, 假定平均数3 u$ i; E! z( T; `2 @! v; A! J M
Half-life, 半衰期
: m9 Q- S. `1 [: i6 p- T- E( tHampel M-estimators, 汉佩尔M估计量3 o4 S7 o# Z5 E- ^4 e$ B* I
Happenstance, 偶然事件# O$ E; O. Y3 u% _( f
Harmonic mean, 调和均数% p, W0 a% N; o* z
Hazard function, 风险均数' C9 c$ w$ ~! w4 t8 E
Hazard rate, 风险率 f& ]3 ?0 J: M* R5 @
Heading, 标目 " n: Z! R, A: L
Heavy-tailed distribution, 重尾分布
$ A/ ?, w. u& p9 `% H1 }Hessian array, 海森立体阵
3 Y& L( ]6 P2 k4 U$ N% j; e' _Heterogeneity, 不同质
2 S# A* V) n/ IHeterogeneity of variance, 方差不齐 ( Y8 {! n: M3 g
Hierarchical classification, 组内分组3 f8 O T9 L( I8 Q X6 |
Hierarchical clustering method, 系统聚类法
$ D# l$ ~8 F8 c/ b5 ^9 |High-leverage point, 高杠杆率点
. \9 w! v U' f9 U" Y9 vHILOGLINEAR, 多维列联表的层次对数线性模型
8 ?) D* j2 M- n% \Hinge, 折叶点( Y9 w" K) q* }: N
Histogram, 直方图# h: y0 _; R0 ]# Y* N8 f* j: B7 J" J! A
Historical cohort study, 历史性队列研究 ; p1 R3 O. f6 k6 C; }2 ]
Holes, 空洞3 k( I- \* i; z/ N+ d4 e
HOMALS, 多重响应分析# T0 ?9 J5 T. e& t% ^
Homogeneity of variance, 方差齐性# H8 j7 Z% }# t1 H- Y8 u
Homogeneity test, 齐性检验
- S! R7 Y: j" j0 r) dHuber M-estimators, 休伯M估计量
3 Y, _" J5 \% ?4 `, h/ R& }Hyperbola, 双曲线' G2 q' w& l3 y- B
Hypothesis testing, 假设检验) I3 x" R# O: z2 C
Hypothetical universe, 假设总体0 q$ F9 _4 u; A" L3 l
Impossible event, 不可能事件
3 t2 G- M0 e3 IIndependence, 独立性 A T% ?, U$ u: x/ E; E. n0 k
Independent variable, 自变量
7 y6 K# [" x% ^* X- iIndex, 指标/指数
/ K* s9 f9 q* t; x. x3 z7 P& kIndirect standardization, 间接标准化法3 S3 o3 |8 R1 { ]$ \
Individual, 个体+ J/ h8 @1 x) m2 b' ~$ \
Inference band, 推断带1 V! a1 t" N+ R0 c4 s0 m
Infinite population, 无限总体
. A! A( `1 ]1 B/ `4 }* @Infinitely great, 无穷大: ?& i( s8 o0 t ?0 W' H+ A
Infinitely small, 无穷小
8 b, b0 \4 c( k' n9 hInfluence curve, 影响曲线0 U2 a0 _7 \4 ?6 u. b# Z
Information capacity, 信息容量; W% a: b- P8 {; q
Initial condition, 初始条件
2 ^ q3 u$ p6 m* L) r/ tInitial estimate, 初始估计值
4 p# q, e, H& l/ E V, b9 s, mInitial level, 最初水平. X5 U/ a, h' L& j- S6 i
Interaction, 交互作用
- t- t- I* u2 yInteraction terms, 交互作用项, T" z1 R9 ^7 D7 i7 H5 r
Intercept, 截距
e' D8 Z9 Q) v# UInterpolation, 内插法
( M7 K9 H3 p7 f+ w* J" cInterquartile range, 四分位距3 j! U3 ?- q6 Q+ d6 o# l0 v/ Y
Interval estimation, 区间估计7 l6 r7 }( y- g1 E0 X, o. \# |
Intervals of equal probability, 等概率区间
& E0 U8 o. ]" A2 {( \& ^Intrinsic curvature, 固有曲率
" N2 d. C I1 e. f! JInvariance, 不变性$ I, G4 H1 _. {, i. Y+ N
Inverse matrix, 逆矩阵
) [0 N; U" A6 E4 r% L% f: ^0 tInverse probability, 逆概率
! U( [- J# k" B5 b7 P( `2 q1 mInverse sine transformation, 反正弦变换
1 T% o% p. x/ S, ^' R- {Iteration, 迭代 & C/ d- I7 P. ^# t
Jacobian determinant, 雅可比行列式, s5 u$ l4 o' P1 M: ]5 S
Joint distribution function, 分布函数
; C- c& O( a' @- w# i& Z2 FJoint probability, 联合概率
4 _9 x9 R$ ?) I+ P. [& yJoint probability distribution, 联合概率分布
6 ]8 K" m' [, }- S9 A* S+ X. CK means method, 逐步聚类法
$ h6 }3 g1 [) D, [9 Y8 @Kaplan-Meier, 评估事件的时间长度 7 g; r0 I' D# |# t! K9 i% |
Kaplan-Merier chart, Kaplan-Merier图
# Z, I( ^4 |! uKendall's rank correlation, Kendall等级相关
% I; J/ d4 u4 ^* j/ HKinetic, 动力学' K% x3 h, d1 i, U* r
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
' b+ m/ v k" z: z& G7 k& }Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验. K. K4 j; |, `. X/ M& Y
Kurtosis, 峰度
- y( t* s, a; s4 E" k6 B) P( DLack of fit, 失拟
6 o; w2 m" A1 A5 yLadder of powers, 幂阶梯1 Z) K" V" H _. D. J! L3 g
Lag, 滞后3 P# ]5 t; _1 b% ~, v5 Z# M$ A
Large sample, 大样本
# K! i$ t" J7 R6 U7 N0 d% q+ ^) ?Large sample test, 大样本检验
; \2 j: a4 {1 m! ?8 r, D3 x7 D, nLatin square, 拉丁方
- A1 f) e, v. \6 r2 X: G8 aLatin square design, 拉丁方设计
, D5 v/ Q! G" W* Y4 c zLeakage, 泄漏, f& l4 l0 M8 T: ^4 J3 P. X3 a
Least favorable configuration, 最不利构形- i0 v$ R- h, S9 m; d8 ?
Least favorable distribution, 最不利分布& y: S1 f% T1 q
Least significant difference, 最小显著差法
9 a# y2 M/ A2 ]' ^3 vLeast square method, 最小二乘法
5 {( }' w6 q; Q( w: xLeast-absolute-residuals estimates, 最小绝对残差估计# N# p- E1 P5 i8 x
Least-absolute-residuals fit, 最小绝对残差拟合' T- _% G/ W H) z4 A
Least-absolute-residuals line, 最小绝对残差线* |! t3 p e1 V1 |1 i
Legend, 图例
* J8 B7 @' H# r# S0 \; u: BL-estimator, L估计量
) N4 E/ t- c9 w1 B( K BL-estimator of location, 位置L估计量% i: B2 x8 u7 e0 e5 H" |1 X( S5 _
L-estimator of scale, 尺度L估计量8 E7 E( t5 A! d
Level, 水平- |2 ]6 N, S5 ?
Life expectance, 预期期望寿命
0 \! g! r, R: v+ w Z" r* NLife table, 寿命表4 Q. |# S+ U$ y+ @, W3 p
Life table method, 生命表法
. t6 M% J& ~8 |4 FLight-tailed distribution, 轻尾分布
+ {7 z, v( l9 E! L/ Z O2 NLikelihood function, 似然函数1 K' @4 F9 z# i/ [% r: V
Likelihood ratio, 似然比
, b s) I- j9 t# hline graph, 线图
9 Q7 S7 J/ G. P) f$ gLinear correlation, 直线相关2 ]! }; e6 @9 c
Linear equation, 线性方程
$ Q6 t c' G; |8 q( S. t+ {4 @+ pLinear programming, 线性规划
% H8 Y* q/ W, Q3 \Linear regression, 直线回归
) g6 d) v$ U! O# kLinear Regression, 线性回归6 _4 j2 [$ q* d D& p
Linear trend, 线性趋势# K- }; A3 o/ B2 P, W8 L3 x9 D
Loading, 载荷 ' g" d- X2 M( J+ I# V) J" i
Location and scale equivariance, 位置尺度同变性: h; H6 h2 A9 J0 x% j& B9 K
Location equivariance, 位置同变性1 w$ j/ H- S. V) T
Location invariance, 位置不变性
k- W2 r) \2 f# e5 Y8 mLocation scale family, 位置尺度族6 G, y+ j, u+ a3 K ^! [- B
Log rank test, 时序检验 1 g0 B# _- f9 k- n
Logarithmic curve, 对数曲线9 |2 _4 U* H' @( M
Logarithmic normal distribution, 对数正态分布6 F8 M8 x# Z5 P: {
Logarithmic scale, 对数尺度9 b4 h7 C; S8 H- l5 ]/ ?& ^
Logarithmic transformation, 对数变换/ x9 V0 i4 m: B+ m7 B
Logic check, 逻辑检查
0 s$ I! V; d6 R& l/ RLogistic distribution, 逻辑斯特分布. _2 U1 g: s4 s+ h- v* q7 o0 T
Logit transformation, Logit转换
* i) C1 I/ Q# @LOGLINEAR, 多维列联表通用模型
7 A# p3 P$ q \3 ^Lognormal distribution, 对数正态分布; M& @- J/ n7 A: w% i
Lost function, 损失函数
4 j e; h, F7 Y" o- ?3 rLow correlation, 低度相关
" ^0 ~( E; [- A" v2 y, SLower limit, 下限
! e. F) z" R* w+ k! ?, U7 |) [, o* Z" fLowest-attained variance, 最小可达方差$ c) P, H/ b( I; R! ^5 I
LSD, 最小显著差法的简称; J( b+ z- ]1 f
Lurking variable, 潜在变量6 q" ]4 F4 n6 K& M( D2 ?
Main effect, 主效应& r( q0 w* O- b, I' C8 R
Major heading, 主辞标目7 W, E7 l8 {, x3 s6 b; ~9 N5 E
Marginal density function, 边缘密度函数- P G, ~& A* c( q
Marginal probability, 边缘概率
" ?# P0 v. ^: [- lMarginal probability distribution, 边缘概率分布1 p- ?8 L Q" _0 ]
Matched data, 配对资料
2 ^4 I$ @# a5 K" O/ g( J" PMatched distribution, 匹配过分布
+ c) X' p! D# P; t+ rMatching of distribution, 分布的匹配0 R3 j. }7 {/ Q/ g8 e: n5 q8 r
Matching of transformation, 变换的匹配
- L9 ?% |4 D4 A& e3 cMathematical expectation, 数学期望
+ ]$ L; Z( S" ` E; V8 y& w0 lMathematical model, 数学模型! C. j& k) ^6 `* R" ?1 x5 G% B2 W
Maximum L-estimator, 极大极小L 估计量
# E8 t2 m3 s- TMaximum likelihood method, 最大似然法4 k8 U3 K( k2 [3 Q* G5 Q) e
Mean, 均数
( d$ t G e0 C5 L: V% R- [Mean squares between groups, 组间均方 ^$ X" [+ o: V$ h! ]; h
Mean squares within group, 组内均方
& F9 s# d O; Z4 l$ [# wMeans (Compare means), 均值-均值比较
2 ]' F$ Q4 z: Q! YMedian, 中位数5 j2 e. b( n$ x
Median effective dose, 半数效量
8 H2 B* v! R- r8 }0 lMedian lethal dose, 半数致死量( e4 H/ H. c, O0 G
Median polish, 中位数平滑
6 d/ F) r9 |. K! \Median test, 中位数检验
9 O2 ]% T/ s4 ^' Y$ S# wMinimal sufficient statistic, 最小充分统计量
% c, h* Y4 c4 |9 d# u; HMinimum distance estimation, 最小距离估计. B- l0 c+ R2 K" t/ B8 Q
Minimum effective dose, 最小有效量
. k" B# A+ i0 {Minimum lethal dose, 最小致死量+ }0 ?: Y. f( B9 S8 O
Minimum variance estimator, 最小方差估计量' ?$ W. M( Q3 }; [9 u: R- d, n) {
MINITAB, 统计软件包
, }/ ^6 ]& D. r* J) ^" c$ W. ]Minor heading, 宾词标目
; W) d2 G: ~; ^1 H$ ^Missing data, 缺失值. A* j4 l0 y6 V& H2 @
Model specification, 模型的确定& w" C! J" r5 w N" a& \+ Z
Modeling Statistics , 模型统计, ^6 E( q z& l) E3 B
Models for outliers, 离群值模型' G% b i$ _9 {( F2 S6 j3 l3 H! P
Modifying the model, 模型的修正% D, a1 U/ b& F6 g
Modulus of continuity, 连续性模
; |$ ? h# C! |Morbidity, 发病率
9 r9 U+ O* r: c3 N' E( TMost favorable configuration, 最有利构形
# X% H1 s7 }" U3 B. L4 YMultidimensional Scaling (ASCAL), 多维尺度/多维标度
* ?& U+ B8 N8 I2 a Q6 IMultinomial Logistic Regression , 多项逻辑斯蒂回归. a, [( a' \1 R; Y( G# r1 |
Multiple comparison, 多重比较/ K5 F+ J( f- v" c" W" ?0 N' f
Multiple correlation , 复相关$ k! `( f/ M" S8 i C( X' {* l
Multiple covariance, 多元协方差
7 A( C. v' B# M% ^4 o) T7 y0 B6 d( QMultiple linear regression, 多元线性回归
* s" b9 x0 L4 A& Y; D. ?Multiple response , 多重选项2 v% k* A0 `" j6 i
Multiple solutions, 多解7 A& G7 }. s) l
Multiplication theorem, 乘法定理 \( J1 C: N% C7 R; G3 z+ q
Multiresponse, 多元响应/ c% F' ]: ]1 b9 W. d
Multi-stage sampling, 多阶段抽样( `% `$ }: S7 I( Q; ~9 E; Z! V
Multivariate T distribution, 多元T分布
$ W3 G' N7 l2 a1 ?9 q) |- L, kMutual exclusive, 互不相容0 s& ^2 ?: n( t
Mutual independence, 互相独立
9 o5 {; e* y4 F- Y2 gNatural boundary, 自然边界; b# _2 w4 g% y$ T
Natural dead, 自然死亡, a1 e9 D- u9 p
Natural zero, 自然零
) [. H5 q+ z% L7 `7 D" tNegative correlation, 负相关# Q" n+ n/ r! U5 B0 w
Negative linear correlation, 负线性相关
; E7 C! n. a' ?' z" v6 mNegatively skewed, 负偏
+ X, X! f5 K w# eNewman-Keuls method, q检验9 i/ B7 c# ?; X7 @" }2 ~
NK method, q检验7 V, ^9 R8 z# F: H2 e% N `5 _7 |
No statistical significance, 无统计意义! O. R# H: e% N7 `. q$ X+ M6 p
Nominal variable, 名义变量
3 N8 j; B, O/ _3 v1 l) ONonconstancy of variability, 变异的非定常性' N6 o/ F& {* `% Q% S
Nonlinear regression, 非线性相关
1 Z5 j! [( u9 c1 E4 LNonparametric statistics, 非参数统计
0 d! z9 V$ H" M5 v7 sNonparametric test, 非参数检验
* c D" s' y7 Y& |9 xNonparametric tests, 非参数检验5 j( x) ?) ^% E$ ^! f. [
Normal deviate, 正态离差2 ^; H# {2 }9 ?. z% y3 R) k0 c
Normal distribution, 正态分布
7 ^( H2 z/ Z6 aNormal equation, 正规方程组# E7 A! Q7 t! X' z5 N: Z' j9 \
Normal ranges, 正常范围, h1 a O$ \+ ]% M) [; E7 N+ b
Normal value, 正常值
7 N! K0 f- C, E+ uNuisance parameter, 多余参数/讨厌参数0 }3 |. ^: v3 v% u1 r' ^% D U
Null hypothesis, 无效假设 % {9 C' G- |5 [! C
Numerical variable, 数值变量% h4 j" V; C' k
Objective function, 目标函数, q+ ~0 A) U) E8 H
Observation unit, 观察单位
! ?! T5 a" {3 y& `1 R5 uObserved value, 观察值/ e4 }) o ?" y% z1 r& t
One sided test, 单侧检验
: \$ B6 J1 l9 I9 c: ROne-way analysis of variance, 单因素方差分析
. K% M" p- ~0 G \; |6 v+ ~Oneway ANOVA , 单因素方差分析
% ?, P6 |; X! H" Q# NOpen sequential trial, 开放型序贯设计5 Z& s" F6 y8 {8 _( \) j0 P" M( j( A
Optrim, 优切尾
( x7 S, o( P9 R8 Z& ^0 NOptrim efficiency, 优切尾效率
9 }+ N2 D' G8 H* N. @& y& kOrder statistics, 顺序统计量! @! c+ ?9 c6 t; \& E
Ordered categories, 有序分类
. m$ f( p' V( E8 M6 I9 X9 Y' Z$ EOrdinal logistic regression , 序数逻辑斯蒂回归
8 h1 P- z% _& m6 ZOrdinal variable, 有序变量
$ @ H J% ~/ hOrthogonal basis, 正交基8 @- v' x! d4 v
Orthogonal design, 正交试验设计
) g t9 q8 j: \$ G' e; aOrthogonality conditions, 正交条件6 z' f( S. Y" B$ B6 @+ ]: U
ORTHOPLAN, 正交设计
& d3 f2 p/ n4 J" [5 G6 v: p/ W5 JOutlier cutoffs, 离群值截断点
! O6 G5 N/ c1 ?* `# [( d1 gOutliers, 极端值3 F+ l! S3 m9 f# c r0 V
OVERALS , 多组变量的非线性正规相关 / W/ X4 x2 x+ s4 o1 q
Overshoot, 迭代过度
3 Q$ }: W! o$ X5 @ v5 s! }4 z- N8 \Paired design, 配对设计+ e! Q+ A- e7 d% D$ Z/ b$ |
Paired sample, 配对样本. \% V. }/ G4 s, q! U# c S, t
Pairwise slopes, 成对斜率
K" I+ I. f: W7 ?$ ^1 L3 S* v$ |Parabola, 抛物线
: C* i/ v5 K, Z) s4 {: mParallel tests, 平行试验
4 Z; M: Z% j! y% t# | EParameter, 参数& d. s2 q3 [2 E7 Y8 B' J7 \
Parametric statistics, 参数统计- P0 D2 T: g8 K& v
Parametric test, 参数检验
* N8 u, ]7 t3 |8 L% P4 ^, ?Partial correlation, 偏相关$ }7 Y/ n0 P) y; W
Partial regression, 偏回归
9 W# {& R, i- U9 s0 wPartial sorting, 偏排序
6 o% v7 Y+ b) ]0 {( J& Q7 Y! pPartials residuals, 偏残差+ y7 a, K1 z: y* y. X
Pattern, 模式
" X9 y1 K3 g1 t1 S( kPearson curves, 皮尔逊曲线
0 V3 g$ L9 W( ^; n& |' PPeeling, 退层
) ?0 }# s" K$ [" I/ E( pPercent bar graph, 百分条形图$ U0 C. m& z9 T& x0 a& \
Percentage, 百分比
4 U q/ o. ? d! |, cPercentile, 百分位数) D4 J5 }- u1 e: X
Percentile curves, 百分位曲线6 i* G. t8 X7 u8 D/ P0 H: W
Periodicity, 周期性
{8 q* r! d S- zPermutation, 排列: T3 t9 A8 |7 ^' K
P-estimator, P估计量( T, X, d% {) Q
Pie graph, 饼图; N8 C6 X" g! W
Pitman estimator, 皮特曼估计量
0 ?) z" v9 A0 v" yPivot, 枢轴量
V# i( @9 P C+ T3 y) Z- IPlanar, 平坦
: p" @) i" ?, j, h( A0 i/ b- d; {! FPlanar assumption, 平面的假设+ C, W- x$ ^" o# k. `+ \7 ^+ c1 A
PLANCARDS, 生成试验的计划卡. \: h" [0 T. e! W# R* @
Point estimation, 点估计
/ N3 B4 H% K( |; J# l( M1 D, oPoisson distribution, 泊松分布6 F- f' a0 N" H: B1 V
Polishing, 平滑
9 E/ X( v9 y- |% Y) x4 W/ r. XPolled standard deviation, 合并标准差9 }8 v/ H3 i0 ~, m# K) g$ d% J
Polled variance, 合并方差% {5 }- P- y4 J; b# a
Polygon, 多边图
3 C; @' b7 X7 a' n5 z/ iPolynomial, 多项式
$ y3 ~* S3 T, R! e$ r. R( a% p; LPolynomial curve, 多项式曲线
/ R- }$ C j9 d! {Population, 总体
- C3 m' v- s) c- ^4 BPopulation attributable risk, 人群归因危险度
( S1 S$ O; t9 [1 G" V {. d# ], _; QPositive correlation, 正相关
f- Z2 F3 f) u, w% ?- @0 ePositively skewed, 正偏1 u. l, [1 E, Q" \! H
Posterior distribution, 后验分布- F% C/ F" V( O5 r* V4 p
Power of a test, 检验效能
5 \7 l1 _+ C2 u# w. Y8 S4 Z' XPrecision, 精密度; g% |2 g/ X$ m! b6 c
Predicted value, 预测值4 {6 v+ j8 \3 Y* F
Preliminary analysis, 预备性分析, a# e5 } s& |+ f( @
Principal component analysis, 主成分分析# b, m2 {, b% f' R' Z
Prior distribution, 先验分布
- j' t) D. @4 \3 O" ePrior probability, 先验概率! v4 ^& Y2 d3 X- W; y7 A
Probabilistic model, 概率模型, [' Z3 l% j' j! B; w! B
probability, 概率
# a( h: n5 S, _3 G" RProbability density, 概率密度4 |$ X2 u- t0 ?. t% X
Product moment, 乘积矩/协方差$ z' d: H! @) S0 s2 w( g0 D& U
Profile trace, 截面迹图/ S; O0 {. C8 B+ o2 e$ y
Proportion, 比/构成比9 Z1 ]& N4 _' E& }
Proportion allocation in stratified random sampling, 按比例分层随机抽样$ n! `- N, Y2 p: f
Proportionate, 成比例4 q4 Y0 K5 h$ E2 J" }5 L+ M
Proportionate sub-class numbers, 成比例次级组含量
* ~, s/ U1 [& m& JProspective study, 前瞻性调查% G+ b7 c3 m1 h! [( p3 C3 y3 r
Proximities, 亲近性 , L* ~# h; T! G" M# P+ s8 t& _
Pseudo F test, 近似F检验9 L5 X9 |( Y1 x& B- d
Pseudo model, 近似模型, x: @6 t$ i( R5 i. P
Pseudosigma, 伪标准差5 r, H H6 M: W% A, D2 @
Purposive sampling, 有目的抽样" n" [, P! |/ t* e; S0 v
QR decomposition, QR分解/ I! I, Z7 y) E' K
Quadratic approximation, 二次近似0 J6 k! s' M) |' @3 f. K
Qualitative classification, 属性分类
+ C7 Q2 v& A+ d! tQualitative method, 定性方法/ ]7 [3 j; X2 V1 M" K5 ]- Z# |( v
Quantile-quantile plot, 分位数-分位数图/Q-Q图
1 N4 o9 D' q6 {3 Z( }! y8 LQuantitative analysis, 定量分析
6 `- ]7 a/ K' Q: b E- K+ ~! V; \Quartile, 四分位数
* x7 F n/ _$ k+ \Quick Cluster, 快速聚类
* _' M" }% T7 ~8 s0 h) CRadix sort, 基数排序1 r: S, _2 o+ |+ W1 g: `5 q- X
Random allocation, 随机化分组( Y& W3 Z" |) r" ~
Random blocks design, 随机区组设计$ u/ u( C2 m6 P- m
Random event, 随机事件5 Z* j$ Y# g! A5 d
Randomization, 随机化- {+ U! I' p# ~2 D0 {) c0 x
Range, 极差/全距( x f7 G# S' i5 a* U
Rank correlation, 等级相关
( o! D3 E8 l& m. B5 c3 y lRank sum test, 秩和检验# K2 m' }& f' F, i9 ~+ I
Rank test, 秩检验6 `! i: v, Z, F( Y+ p% ~! b
Ranked data, 等级资料
9 ^ s; b4 b9 x9 h8 b" e: }Rate, 比率( s* q$ Q! D: L- [3 f, Q
Ratio, 比例9 j! Q: z2 e8 x% s
Raw data, 原始资料
8 `0 |: X% i J4 jRaw residual, 原始残差" S( l0 T- {( K# T8 R m
Rayleigh's test, 雷氏检验
3 p6 B$ a" `6 a: `: K9 ^# ORayleigh's Z, 雷氏Z值 ( _1 _+ r2 J1 c% m4 G; {; _. ]. A
Reciprocal, 倒数
8 U$ \" u' G8 f" \Reciprocal transformation, 倒数变换
, Y+ L" D- X8 @ h- ORecording, 记录/ q6 ? V! l9 T* q
Redescending estimators, 回降估计量" `- }: I/ m0 ]8 }9 p' V
Reducing dimensions, 降维# t; X: i4 k: z
Re-expression, 重新表达
) n) c9 J- P' [* LReference set, 标准组
) s+ L) f6 N9 B. YRegion of acceptance, 接受域
. \+ T9 z4 r0 u$ }; H" R) IRegression coefficient, 回归系数
* ~- {9 G2 e4 {, a2 e4 _0 _Regression sum of square, 回归平方和
/ H1 t c! E) p! r+ zRejection point, 拒绝点$ U# m, m/ \/ q0 \
Relative dispersion, 相对离散度9 B+ B* d o4 f' M; h ~/ |/ u# \6 N! J
Relative number, 相对数, q/ v' A2 P5 l2 N5 O( p2 q0 E! }
Reliability, 可靠性& ^: H5 b% Y3 ?( ]7 }2 e) {
Reparametrization, 重新设置参数
& J% ^3 y( t' A" D) m6 @Replication, 重复/ q2 D5 {/ e( Z$ t3 ~! m
Report Summaries, 报告摘要! T; P4 {: [% n* i; e
Residual sum of square, 剩余平方和% C" u2 Z1 k. q6 r/ @# [* }
Resistance, 耐抗性, r$ x0 \; {2 M
Resistant line, 耐抗线
4 ~1 ~9 y7 r% X4 U) r* VResistant technique, 耐抗技术
8 d; h, f! p1 T) Z% Y+ o% U& ~R-estimator of location, 位置R估计量
0 `4 ?: @0 h( `$ |( |9 ?R-estimator of scale, 尺度R估计量
1 X$ P' K+ [* Z/ {% }Retrospective study, 回顾性调查
3 O7 V5 F" A& k8 |' vRidge trace, 岭迹( H/ C( m/ m5 v# q* X! Y
Ridit analysis, Ridit分析
' @, J6 G5 N1 K; q7 C. sRotation, 旋转
; E) k% Q; Q o4 t$ L. B8 G% IRounding, 舍入5 ]) K0 w" h2 \6 S- }+ C# ]6 d
Row, 行+ Y1 u$ s Z2 `: |7 X0 o
Row effects, 行效应$ f( v* n3 ` i& o
Row factor, 行因素7 x# z. i v- a
RXC table, RXC表
, \/ ?$ }% Q, W) H7 rSample, 样本+ v* Z5 C' B7 |* f3 ^ w
Sample regression coefficient, 样本回归系数
5 `0 }: Z _5 t q$ t' P( ^6 M; RSample size, 样本量$ F2 g# r& t2 x
Sample standard deviation, 样本标准差
! T. q; ]% A6 Z+ iSampling error, 抽样误差, H" D/ k2 T# W5 q0 H
SAS(Statistical analysis system ), SAS统计软件包7 T, |3 ]: h; i3 p) ^
Scale, 尺度/量表5 _5 o$ N& L& s2 d5 W& X" l
Scatter diagram, 散点图
+ M8 M7 V8 u k* \Schematic plot, 示意图/简图' i% y1 `' u4 w/ @% t. y' }
Score test, 计分检验
, B, X; W! o& H3 _1 I/ G% HScreening, 筛检: O( x) n( e2 N& P& J( x- B
SEASON, 季节分析
6 v4 |1 O! p+ \# j. O1 G$ l$ PSecond derivative, 二阶导数
, x( {8 e- T( `: I7 h( OSecond principal component, 第二主成分! o/ F: W) p2 w) W3 O6 P
SEM (Structural equation modeling), 结构化方程模型 7 W0 s4 W6 i" I3 J1 F) a
Semi-logarithmic graph, 半对数图1 U. u. P2 m. S, @5 p
Semi-logarithmic paper, 半对数格纸
: m0 w* E# g, ^) m4 J, ~Sensitivity curve, 敏感度曲线/ j7 N( t' |3 {4 e" \8 l1 [7 w& H
Sequential analysis, 贯序分析+ I4 {) e7 M: O
Sequential data set, 顺序数据集
1 C; B4 L" G2 s [7 NSequential design, 贯序设计: ^* _! `7 r3 g$ H
Sequential method, 贯序法
) f# x; }4 F+ G( zSequential test, 贯序检验法
. X) t+ H' m7 W4 `Serial tests, 系列试验
& h' E H# b$ b( f2 yShort-cut method, 简捷法 ; j9 L) f2 u d9 S; U& ]' b
Sigmoid curve, S形曲线5 r5 I; E( z6 C) u7 f( n
Sign function, 正负号函数
& n. Q+ D0 ]. NSign test, 符号检验1 g) D0 L* f( Q4 N& _# N
Signed rank, 符号秩' y5 d2 k" O$ D; ]* t- d- O/ K
Significance test, 显著性检验3 T, n7 U0 o2 N( h- Z8 ^* A
Significant figure, 有效数字
, Q8 {& [0 j; o: a I# p: TSimple cluster sampling, 简单整群抽样0 |" Z! H/ P0 s
Simple correlation, 简单相关
9 ^# y. a7 j4 B0 `9 s: oSimple random sampling, 简单随机抽样
' t+ E* ]" a, [# cSimple regression, 简单回归6 G W1 e4 c; Z( e9 d
simple table, 简单表
( c: o( q/ H* a N8 M* ASine estimator, 正弦估计量1 n3 Y2 ^& E, `; d3 @2 m
Single-valued estimate, 单值估计; ]: n3 l D0 q1 [, v
Singular matrix, 奇异矩阵' }0 k9 S/ Y1 x/ F
Skewed distribution, 偏斜分布5 |5 ^& F4 S c: o& x
Skewness, 偏度, S& q1 i1 Z3 ^% Y+ ~1 k) {1 F
Slash distribution, 斜线分布
! e7 r( u( G$ O8 }Slope, 斜率) F, g4 {- ~1 M0 o( `3 l# O7 ^0 a
Smirnov test, 斯米尔诺夫检验/ N8 W5 `( X$ w3 c0 d5 Q8 R
Source of variation, 变异来源( x% [, w: E0 ?. n l3 F! c6 \
Spearman rank correlation, 斯皮尔曼等级相关) K p0 b# v# z6 Z6 f7 }
Specific factor, 特殊因子- e* A t5 g* v! p( G, W
Specific factor variance, 特殊因子方差
- k7 i9 C' S8 W8 C2 |4 c, }Spectra , 频谱
" m& y }* {1 k- p: vSpherical distribution, 球型正态分布
! B( b* D0 I& {" s R8 xSpread, 展布
6 S2 p J/ l4 a7 V/ ?6 P: q+ ?SPSS(Statistical package for the social science), SPSS统计软件包$ d7 o: W3 }2 s7 ]% q% } k
Spurious correlation, 假性相关. v8 z& c6 F* B1 P" V: g
Square root transformation, 平方根变换
' v$ ?0 c/ I& H. S% {- D1 e- ?Stabilizing variance, 稳定方差
i4 R+ j- }4 Z' G5 `" D' u# w, K2 H" _Standard deviation, 标准差
1 ~+ }9 x* y* H# ^6 @Standard error, 标准误
' F; Z1 r& v4 M6 \Standard error of difference, 差别的标准误
/ Z x8 a: \! D2 k$ d( W# EStandard error of estimate, 标准估计误差- |& j3 \) e1 K7 n0 W. k
Standard error of rate, 率的标准误1 T5 ?# @. Y# }+ _5 S8 H0 D1 z
Standard normal distribution, 标准正态分布7 b+ C6 `, ~5 U% z
Standardization, 标准化% m$ M, U4 Y% |
Starting value, 起始值
9 _% [1 c" O: \" S# d. y$ oStatistic, 统计量* h' z; l) H$ @9 ^
Statistical control, 统计控制
% A/ E. b, ]+ E3 n6 `Statistical graph, 统计图9 ~2 ]5 D9 f4 j% w+ z& h* J" y
Statistical inference, 统计推断
+ o5 f- s, h. ]+ n. W( h- o- f* X8 nStatistical table, 统计表
: ^7 h/ Z: p- h/ K8 B8 X3 t( BSteepest descent, 最速下降法
! P% x0 t2 }3 `( Y5 ^1 HStem and leaf display, 茎叶图: c" ]6 q7 h# A. ~
Step factor, 步长因子6 a" q" ?) S) b0 W
Stepwise regression, 逐步回归/ A/ t- [1 e, q7 w: J
Storage, 存) @' k0 ~6 A0 Z' n5 H& Y1 s+ J' J# ^! J8 S- |
Strata, 层(复数)5 W& _; E, k3 H9 s
Stratified sampling, 分层抽样9 P9 c5 \/ o2 x. }: k
Stratified sampling, 分层抽样) o% g8 I+ ^7 p. q0 p
Strength, 强度' d9 w' F2 V2 z" y
Stringency, 严密性& f1 r4 s& s$ i! V
Structural relationship, 结构关系, t3 W& y! R8 I8 ]) K; Q' a: U
Studentized residual, 学生化残差/t化残差7 m- |7 {: a z3 P- V" P$ z
Sub-class numbers, 次级组含量
9 d o5 P$ G6 X( R2 ?Subdividing, 分割/ K1 D8 j( f5 {1 T% K
Sufficient statistic, 充分统计量
3 D& o8 B( g8 i# g! V8 u0 @Sum of products, 积和
# Y4 l) l) S( D4 F# ZSum of squares, 离差平方和* u3 A5 Y- S* @) m5 e5 v
Sum of squares about regression, 回归平方和
0 w/ T5 e# W% o. r( PSum of squares between groups, 组间平方和7 U+ r; D- W9 Q: q4 M9 ~9 r
Sum of squares of partial regression, 偏回归平方和9 t+ b6 ^& j' z# f7 I. H& e, X
Sure event, 必然事件# M& }+ B2 z5 L; q; G
Survey, 调查/ u; t; d" {' d
Survival, 生存分析
4 |) |4 i9 Z- |6 dSurvival rate, 生存率1 d2 ]' s) ~; K, h9 F: N$ Y
Suspended root gram, 悬吊根图 D) A% v1 @' l% x' \5 @. |
Symmetry, 对称' Y% R4 }) T! Q+ A4 n
Systematic error, 系统误差
; b# d+ w y" _4 GSystematic sampling, 系统抽样5 L. E5 u4 m% ?! M
Tags, 标签8 a8 Y" E9 V; c3 m" g
Tail area, 尾部面积
& q: S1 t! q2 |# z7 `Tail length, 尾长& n. i( K! d. T' J2 i+ N
Tail weight, 尾重# N6 @) `# e) S
Tangent line, 切线
B2 n/ f2 t4 M( l( XTarget distribution, 目标分布
) u4 {, R8 E1 _: J) E3 cTaylor series, 泰勒级数
* t$ F6 \ P! _& p* rTendency of dispersion, 离散趋势
4 f7 \1 G! w# M3 u7 wTesting of hypotheses, 假设检验4 D( g7 ~8 \: S/ f. E# K3 o
Theoretical frequency, 理论频数# @7 S3 N* \( v o3 d& p
Time series, 时间序列
, H/ v5 p2 H! z. P6 ]6 p% {Tolerance interval, 容忍区间1 r- F( Y& C: j
Tolerance lower limit, 容忍下限
: h! E2 T% b8 l+ H/ \- c6 `Tolerance upper limit, 容忍上限' b u8 c, s, A) ^1 g
Torsion, 扰率. F+ k" }2 u5 q7 d/ e# U
Total sum of square, 总平方和8 n, U3 p# C4 {7 ?# J: Y4 w
Total variation, 总变异
* X( q! l' P' ]7 O( K g3 B- vTransformation, 转换
- w2 Y$ I) i2 k! w6 r5 `4 e- M( rTreatment, 处理% a+ c, ~; d, o6 d& b { \# p( {0 ~
Trend, 趋势9 ?% w& q- O# [8 B
Trend of percentage, 百分比趋势
V1 H; X9 p1 [1 g; @+ f* s: C4 K0 {; NTrial, 试验
; p+ |4 C+ ~4 k5 Y" RTrial and error method, 试错法, n4 o/ D' f. \* ?5 W
Tuning constant, 细调常数6 v0 q4 {8 p% f% U1 G
Two sided test, 双向检验
/ j+ z! K2 K1 T$ RTwo-stage least squares, 二阶最小平方
' I9 p! b0 ]5 sTwo-stage sampling, 二阶段抽样2 d: `9 f9 V& H& K3 y
Two-tailed test, 双侧检验! o% g& n/ x- h% W6 s8 n! w
Two-way analysis of variance, 双因素方差分析+ {' @( _7 E4 |3 r
Two-way table, 双向表
2 l& Y* P" ?6 w" C+ [2 lType I error, 一类错误/α错误
. E2 ~& E+ D* o/ {Type II error, 二类错误/β错误 r8 A Z) M( H) t9 |1 }
UMVU, 方差一致最小无偏估计简称+ W! g8 @. H8 m
Unbiased estimate, 无偏估计; {7 f: u; a, ^9 v. K* S! z
Unconstrained nonlinear regression , 无约束非线性回归9 C1 I& u1 C( T- n$ [
Unequal subclass number, 不等次级组含量
5 o1 r" B: {5 P) PUngrouped data, 不分组资料
6 h+ N8 y" }/ f0 t% \. E5 I/ z) dUniform coordinate, 均匀坐标
: j) t: V) s& C7 [- rUniform distribution, 均匀分布
! K# d+ l4 }- U+ TUniformly minimum variance unbiased estimate, 方差一致最小无偏估计" H u/ p H8 s4 O! t* l
Unit, 单元# C R( B& o- Q/ w* B- I
Unordered categories, 无序分类
( G! J+ Q& Z9 {: t$ x: }8 hUpper limit, 上限! ]* A9 E z' r! i0 G- L
Upward rank, 升秩4 d I, B8 Z4 b @, F7 }' O; [
Vague concept, 模糊概念: w. @6 b4 ~9 R6 S% H
Validity, 有效性; i0 i- j" s. ?. F
VARCOMP (Variance component estimation), 方差元素估计
8 l3 D# m& _5 C8 Q" |0 xVariability, 变异性
- J; j0 @9 `1 a0 ^+ i4 uVariable, 变量
) Q" {$ X/ [+ q! F: Z7 PVariance, 方差- E1 F2 v% ^* a% F& G- O
Variation, 变异
4 K; b% J* v% n. gVarimax orthogonal rotation, 方差最大正交旋转
( j4 H4 R% @1 E- `, e* z% ]# s& bVolume of distribution, 容积# u, B9 C$ i" i, S, l+ {2 |
W test, W检验
3 w0 ?$ I7 T3 q7 v" u7 Q: [Weibull distribution, 威布尔分布# O1 B+ N( R- ]1 p7 q2 w" U0 ^
Weight, 权数: v* {0 \* `9 Z
Weighted Chi-square test, 加权卡方检验/Cochran检验6 M7 I& h0 ], b
Weighted linear regression method, 加权直线回归
. p! v3 K! k/ H+ C$ o0 sWeighted mean, 加权平均数6 o- s/ @2 ?- p
Weighted mean square, 加权平均方差
) \4 o3 m& f1 m' ]$ zWeighted sum of square, 加权平方和
8 I8 U3 v3 B3 ]( J/ C: E9 xWeighting coefficient, 权重系数
* L/ O) D; z0 L GWeighting method, 加权法 ; A& z) s: m' y6 o4 o1 H; \8 G: i
W-estimation, W估计量
; t9 @4 Q# T+ P' N: vW-estimation of location, 位置W估计量8 M5 D( Y% K7 D
Width, 宽度
1 v7 i! @+ e! s" g5 i/ QWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
4 ] U' W. E0 r1 Q: B* bWild point, 野点/狂点8 t+ g/ v' u9 F1 I" j
Wild value, 野值/狂值+ N5 V% A) }; |$ C
Winsorized mean, 缩尾均值
; h2 n$ Q6 g5 t6 sWithdraw, 失访 ; b) f) ]; l) `$ z( t7 m) p8 T
Youden's index, 尤登指数
6 h; k; `2 q _2 E+ N' ]$ _Z test, Z检验4 e+ c0 K9 J/ G
Zero correlation, 零相关$ [& x! f. r* e1 I" _& h! `) F
Z-transformation, Z变换 |
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