|
|
Absolute deviation, 绝对离差+ ?# v9 f% Z* e6 j. L& [
Absolute number, 绝对数- @! T9 j6 B c
Absolute residuals, 绝对残差
7 }9 H! F9 J0 J: p) r' V3 y2 [Acceleration array, 加速度立体阵 D' [5 T( g" v( @* k4 D3 c: r0 G1 n
Acceleration in an arbitrary direction, 任意方向上的加速度
4 q. x8 t! u+ h! {Acceleration normal, 法向加速度
/ l- K# v' d& q- |Acceleration space dimension, 加速度空间的维数9 ]# _3 w& a0 F4 Z& B
Acceleration tangential, 切向加速度
- I' d7 a( ~1 M. oAcceleration vector, 加速度向量3 E' D0 v1 U3 W& s: ]" d) ^4 u
Acceptable hypothesis, 可接受假设, a. V1 }6 o' Z t1 m/ G3 u: i
Accumulation, 累积
8 i, d( e: i4 |; H3 z4 x$ hAccuracy, 准确度/ }: v4 L+ F1 h$ y; S L
Actual frequency, 实际频数, a' L. [ Y6 c- d& N
Adaptive estimator, 自适应估计量
9 D( V( D0 S R9 r; jAddition, 相加
, f6 H3 w4 z$ W8 y1 U f0 U" @Addition theorem, 加法定理4 t" b! r5 o( N
Additivity, 可加性
5 [! @# _; c; k9 a: sAdjusted rate, 调整率: Q. J% {# E3 _ F4 C( h- H
Adjusted value, 校正值
2 Z$ [0 o; B$ {; F+ H {- q+ w9 UAdmissible error, 容许误差2 S/ k' Q4 ]: s8 d0 p' f
Aggregation, 聚集性- U% A$ q3 }) E. T- l1 g9 I
Alternative hypothesis, 备择假设
* e6 X. _8 p- ]* S: t% P4 \) RAmong groups, 组间
: s. p8 @2 A6 n0 q" M; x: bAmounts, 总量; J$ d! K6 k* _( X8 }: v9 ]; `8 i' q6 S
Analysis of correlation, 相关分析
( M P8 u7 w, `' }% V' K$ j# \Analysis of covariance, 协方差分析
. k6 P( W1 A/ a+ A- B. KAnalysis of regression, 回归分析$ V" r* J3 n# j' m+ q9 t! ~
Analysis of time series, 时间序列分析" l0 c' `5 W/ h/ |" ^: J5 X
Analysis of variance, 方差分析
8 y8 A8 Z, w$ RAngular transformation, 角转换
) M1 F) G6 ^0 h4 E% l" q. n" e" S. SANOVA （analysis of variance）, 方差分析
: j* u. P( l0 aANOVA Models, 方差分析模型" E5 a* x! ?$ e
Arcing, 弧/弧旋' J8 K7 r, C% ` R
Arcsine transformation, 反正弦变换5 h! y- O: z, o9 Y' N
Area under the curve, 曲线面积
( Z" r1 V( l& XAREG , 评估从一个时间点到下一个时间点回归相关时的误差 + V1 h% e& ~, i% X$ w. F
ARIMA, 季节和非季节性单变量模型的极大似然估计
0 r3 ^; A. \$ k, Z7 k0 yArithmetic grid paper, 算术格纸7 U6 A( x b: {# d
Arithmetic mean, 算术平均数
- F7 d& @9 H4 eArrhenius relation, 艾恩尼斯关系. m& [: O; i- ~1 P5 _
Assessing fit, 拟合的评估# U) z. Z- D! h: y$ |+ C5 d; c
Associative laws, 结合律
@8 q% a0 f8 YAsymmetric distribution, 非对称分布/ U! r4 G, K$ o8 `7 w% |9 j# Z; c2 B# g$ E
Asymptotic bias, 渐近偏倚
) M9 s Q z6 z$ K2 |9 z5 X; GAsymptotic efficiency, 渐近效率4 S0 ~8 X2 B. x8 w" g; w# N
Asymptotic variance, 渐近方差& i5 m! a* `( D1 ~
Attributable risk, 归因危险度. X/ n1 V- Q0 X8 [" J! Z
Attribute data, 属性资料$ ^- r* C. _5 J: v0 g% {
Attribution, 属性
; f! a5 G, c1 }2 `Autocorrelation, 自相关) P+ J3 J# `& \+ Z0 A
Autocorrelation of residuals, 残差的自相关. c4 r0 m3 F3 G) }; C
Average, 平均数5 A( Y( C% V! |5 }. ^
Average confidence interval length, 平均置信区间长度
5 T# G1 Q8 n; YAverage growth rate, 平均增长率
1 i+ T: z3 ~" x. B: j# e0 V* C* uBar chart, 条形图* ^1 E8 e$ g7 B% C7 M2 ^8 z
Bar graph, 条形图
# C, n! u& T6 U- WBase period, 基期 L) f, h$ h8 u, l' w
Bayes' theorem , Bayes定理
9 M( i9 s, T/ n7 T( \. G' \7 bBell-shaped curve, 钟形曲线
9 V' C1 e) i2 z- ]: q$ vBernoulli distribution, 伯努力分布& u6 T+ I+ S% ~4 z1 J- L5 m( m7 s
Best-trim estimator, 最好切尾估计量
: K! R( h; ], [% S1 X- L, DBias, 偏性% `; ~, ^3 T8 M6 }% g3 A0 |, O: i0 L
Binary logistic regression, 二元逻辑斯蒂回归
9 s5 ^6 v8 `/ G, hBinomial distribution, 二项分布" j& w4 e# ~% H# T' Y- |
Bisquare, 双平方1 @8 `, t% {4 I A
Bivariate Correlate, 二变量相关
8 K1 \2 b X, u' HBivariate normal distribution, 双变量正态分布
: v9 G% j: v9 S) m8 TBivariate normal population, 双变量正态总体
7 a0 Q: Q. ]! z/ c' q0 ^Biweight interval, 双权区间$ D9 B/ c, s) E, }4 X, K! X
Biweight M-estimator, 双权M估计量
1 M, l2 {- r( w, @7 e2 n, u4 @Block, 区组/配伍组
% g0 r1 n. s" O3 F2 N3 TBMDP(Biomedical computer programs), BMDP统计软件包, D) U+ E1 j2 M; S3 n: a. A. |3 p
Boxplots, 箱线图/箱尾图
* B5 {8 w! u2 H+ p; g( bBreakdown bound, 崩溃界/崩溃点
5 o# s# H- X9 d) e: o2 f9 MCanonical correlation, 典型相关
- n' P% `% `; P+ E' PCaption, 纵标目/ ^; }' T* _- C9 T/ e
Case-control study, 病例对照研究, D7 k; O% s- P* B8 g2 l
Categorical variable, 分类变量+ l: l% ~9 K$ d* H8 d% V9 |* Y' ]& j6 B
Catenary, 悬链线
" Z* l2 Q* Q' d* W7 g) T7 bCauchy distribution, 柯西分布
, Y: [0 q; L" r0 e# LCause-and-effect relationship, 因果关系
- D; ~* ?8 h! [. NCell, 单元3 E/ b9 f( ^: m. K
Censoring, 终检" r! [# ~5 W- q% n5 {
Center of symmetry, 对称中心1 c& u" g! k# S. p) A1 H
Centering and scaling, 中心化和定标% {( H4 s4 { n* Q' Y3 ?8 |
Central tendency, 集中趋势5 t& C3 h6 z0 i2 h# q5 ^6 v' h
Central value, 中心值% [5 E/ Q) `5 L9 X% J3 W
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测$ Z+ s& o! L/ k
Chance, 机遇0 H$ C! c, |. j, _7 W: s/ ~
Chance error, 随机误差
/ _. ~- |+ k* p6 p( zChance variable, 随机变量
: i& o: K* d/ n8 lCharacteristic equation, 特征方程! m+ F, k- ` C: n
Characteristic root, 特征根
# N& D2 M4 x0 v! `2 nCharacteristic vector, 特征向量
. l4 T! s' t# M/ K* F$ q8 eChebshev criterion of fit, 拟合的切比雪夫准则
* t, n; n6 b2 |) r& s S3 rChernoff faces, 切尔诺夫脸谱图
3 q3 F; x# k$ Q6 s" P3 _Chi-square test, 卡方检验/χ2检验
6 u/ y1 l& x, b( j% _3 I6 ICholeskey decomposition, 乔洛斯基分解/ U% ]* B; D) @; s! |" d0 f
Circle chart, 圆图
) t) I7 r7 C$ B4 @ I1 s! RClass interval, 组距4 Q' s6 r! ]% N, \3 i6 ]
Class mid-value, 组中值9 Q D, ^9 o9 w3 f4 O, Y
Class upper limit, 组上限
) N. z( n' X MClassified variable, 分类变量
+ X2 R! |" r# v5 h3 r) [4 OCluster analysis, 聚类分析' E" S; ?: T/ i0 B$ }
Cluster sampling, 整群抽样% Z6 ]! |) I8 c2 b- w3 h
Code, 代码
3 X+ u% t9 l2 z; ?3 ?0 pCoded data, 编码数据
" G4 n) Z8 k3 W4 l. R% w! d' \Coding, 编码( {: y; t! O; g' ~
Coefficient of contingency, 列联系数
! i5 Y( V3 k* K; B3 |$ |* g5 uCoefficient of determination, 决定系数* h* t3 w8 |3 h- Z& c- u
Coefficient of multiple correlation, 多重相关系数
, C/ H" z2 y2 e8 QCoefficient of partial correlation, 偏相关系数+ t' O$ y' A! W. Z
Coefficient of production-moment correlation, 积差相关系数
# I/ A! G$ T1 [/ _Coefficient of rank correlation, 等级相关系数8 V; P! `. }1 u' y/ E8 p
Coefficient of regression, 回归系数
9 T, ~ V, Y" oCoefficient of skewness, 偏度系数
" w$ R V, d& \3 FCoefficient of variation, 变异系数/ h' w! f' d# z* h; A
Cohort study, 队列研究/ ?' {# L4 `1 n& W4 ?% H
Column, 列
: X1 L: H3 J$ k& I( k) ]: rColumn effect, 列效应2 Q& P( ?* o7 z3 K
Column factor, 列因素
2 |% N3 j& c* U0 }- TCombination pool, 合并; C' \% y, Y- e8 z k' o6 q
Combinative table, 组合表
: J! t$ P! c, G/ tCommon factor, 共性因子
. s# r: J+ Y8 `$ u0 a* n3 ^+ LCommon regression coefficient, 公共回归系数6 o- r9 y$ i- [4 ~, b
Common value, 共同值, l! t9 a& D" O8 m
Common variance, 公共方差
# z' \5 W- m9 o3 T5 SCommon variation, 公共变异7 _4 R" `/ M. H+ Q: D( Q& c
Communality variance, 共性方差" \* E2 g7 a$ W% n
Comparability, 可比性
3 N0 f* f" `' A$ CComparison of bathes, 批比较
/ M* I5 j2 m0 {2 c) GComparison value, 比较值: }8 d V/ E6 q' x( }4 K* A
Compartment model, 分部模型
7 ]8 |6 G6 W S- a4 X! Y4 f& @8 _Compassion, 伸缩5 ?3 n% l2 ?3 K
Complement of an event, 补事件& c4 {# s. @: d6 }1 ~' T4 b
Complete association, 完全正相关
1 j: w4 ?# {8 n/ z+ H6 T X9 y; R; m9 CComplete dissociation, 完全不相关
% i/ a1 m' }1 T! h8 h2 v+ nComplete statistics, 完备统计量
3 }( h: G, l, R9 l9 J# U9 ~Completely randomized design, 完全随机化设计
h) y0 u& {$ E: k8 J4 m# KComposite event, 联合事件
8 c+ N! y' L5 E" V* c$ Q5 lComposite events, 复合事件; [' W* l8 y+ u
Concavity, 凹性) R0 N' U7 H9 l' l# C! b
Conditional expectation, 条件期望# a M/ n& ]5 Q% N! i5 D+ E
Conditional likelihood, 条件似然 F, l4 N' c, e
Conditional probability, 条件概率
: `' O1 P h( n3 r$ V7 \' A! wConditionally linear, 依条件线性
7 T, _7 r9 }4 R& I3 A8 X0 q/ H8 OConfidence interval, 置信区间
3 H8 H7 G5 [, Y: A# O4 ?Confidence limit, 置信限6 ~, k9 ]2 v' v# Q' O% ]
Confidence lower limit, 置信下限
3 H! d3 W2 z0 AConfidence upper limit, 置信上限
' d) {# V8 c# o9 F9 b# Y! TConfirmatory Factor Analysis , 验证性因子分析
* |$ P# ^2 V n& G' aConfirmatory research, 证实性实验研究% V+ c( V- m2 i* K9 V+ c
Confounding factor, 混杂因素
+ ^3 f: V9 F% V$ G# p3 qConjoint, 联合分析9 _4 b- n! o" b& ?+ V; r
Consistency, 相合性
3 Z$ E$ t' p- D9 Y" jConsistency check, 一致性检验
5 c+ r& H* O$ i. q& I. d+ QConsistent asymptotically normal estimate, 相合渐近正态估计5 i5 w5 P; H6 H; p7 a' j% i3 `
Consistent estimate, 相合估计) x. P% |! [6 v2 y( \
Constrained nonlinear regression, 受约束非线性回归7 w6 A2 |4 I( u$ c) w! J- ?" E
Constraint, 约束
, h. d3 a& _; S+ n0 z! K) ]Contaminated distribution, 污染分布' w" C# e# \' n9 y
Contaminated Gausssian, 污染高斯分布, Y/ y$ s% [- Y7 I& f
Contaminated normal distribution, 污染正态分布0 u) b9 ?' h) q2 A5 \) x% z# k
Contamination, 污染- ]. V% S+ w1 d7 {
Contamination model, 污染模型
2 V; [* ^) n, j$ J, F0 Y$ GContingency table, 列联表
# p! _8 k4 a$ X0 `Contour, 边界线
5 C& S" `& \* y5 r& r) f5 p9 s1 j* o4 XContribution rate, 贡献率
2 U8 U7 T( Z1 P% A# j" Y0 xControl, 对照3 Z; Q* H- a1 Q( ?" t
Controlled experiments, 对照实验0 l3 r; K* Q. q' k
Conventional depth, 常规深度- m j4 ^" \6 O8 _* C
Convolution, 卷积
! y- g: h3 M0 y, OCorrected factor, 校正因子
$ ]3 d( Y c8 b% E/ @% qCorrected mean, 校正均值
8 e t; q. z- @% iCorrection coefficient, 校正系数
5 a! U$ g7 ~5 N5 T4 v2 CCorrectness, 正确性
7 I" g" Q# i9 T, f* pCorrelation coefficient, 相关系数* v; p. p9 A5 ] W
Correlation index, 相关指数
% U9 v3 d) N5 j a/ r c" uCorrespondence, 对应( T k5 d, \1 }
Counting, 计数
) k1 G+ Z2 l+ K8 Q) l; ^3 ^1 V- pCounts, 计数/频数
6 v! ?4 M' d. u5 T. K& `2 Z" E4 n% ECovariance, 协方差
. Y7 e0 Q( h3 q- HCovariant, 共变 ! [4 J* e% @2 ~1 G8 X
Cox Regression, Cox回归, Q: u* w1 \, F/ A
Criteria for fitting, 拟合准则8 g( n( I' N) Y- A0 {3 l
Criteria of least squares, 最小二乘准则- W! O t8 m2 \
Critical ratio, 临界比
- p% ]6 ?# q/ jCritical region, 拒绝域
+ U2 @; a, {( v9 w% G2 ?3 p6 fCritical value, 临界值: U/ Z: d) z& |
Cross-over design, 交叉设计0 s6 `. e2 C. h1 ?8 O
Cross-section analysis, 横断面分析
9 d, [4 t# i" J4 c2 o% Y; s$ sCross-section survey, 横断面调查
9 P* F" R/ \( G' g, Z4 R# eCrosstabs , 交叉表 $ _% H+ E0 z5 @: g$ y# ~
Cross-tabulation table, 复合表
) E/ [- Y+ G0 qCube root, 立方根: ?5 |5 y9 x& z E! i2 R N0 C
Cumulative distribution function, 分布函数
+ _2 S$ N+ j4 UCumulative probability, 累计概率
9 R" \) G7 j5 G yCurvature, 曲率/弯曲
2 \$ l3 k& ]1 vCurvature, 曲率
7 W9 S$ B% X! n( hCurve fit , 曲线拟和 : {. N" r% v+ l7 {3 G! Z% m
Curve fitting, 曲线拟合
& {1 Q( u# B* |% y0 SCurvilinear regression, 曲线回归
# _% |. P* ]" E9 q" lCurvilinear relation, 曲线关系$ z/ q$ R- a' A4 q6 N
Cut-and-try method, 尝试法
' g$ N" u2 t( ]: ECycle, 周期$ e( N" a" D7 p4 u0 O3 d% w: X
Cyclist, 周期性) z L, N. M# W4 A
D test, D检验
1 l/ v3 ]" r4 D) U `Data acquisition, 资料收集, G4 q( @8 J G! g
Data bank, 数据库+ \: Z( I7 A8 Y) L9 R
Data capacity, 数据容量) Z+ f# o& o! M% O( J- l8 J
Data deficiencies, 数据缺乏
( G( y, z, \( F& W7 A5 p RData handling, 数据处理' V0 z/ \6 t( J! ^
Data manipulation, 数据处理
4 D9 U% o5 h9 x4 A, k* iData processing, 数据处理9 x9 s& g3 n2 L5 h
Data reduction, 数据缩减
/ s* p& b* t- K% G4 \8 UData set, 数据集) o3 {- `* A# m+ I; _+ F; E
Data sources, 数据来源
8 ~* N+ b* Q& D' d2 sData transformation, 数据变换
6 Q; X- B3 i6 rData validity, 数据有效性( C/ a- ~( C1 f! x# K/ S
Data-in, 数据输入, Z, N, h/ H8 V
Data-out, 数据输出( e# t u! A! E: g+ p* N" N
Dead time, 停滞期
/ b5 |4 h% W/ M( RDegree of freedom, 自由度- @% s9 s+ p$ c
Degree of precision, 精密度0 v8 T9 q- P" v K% K2 P$ y$ o
Degree of reliability, 可靠性程度
4 S; m1 E: |9 @, [4 pDegression, 递减
; U. v+ K( ~, d! j9 ^" N! W. ODensity function, 密度函数
( T# \6 O3 U" ZDensity of data points, 数据点的密度
- I. _7 e# Y( mDependent variable, 应变量/依变量/因变量
6 X4 J/ j- i4 j m% x/ a5 K% MDependent variable, 因变量 q8 I: b; r' m! `! C- ?3 b. Q- U
Depth, 深度
7 B8 C' b$ o! W/ ?Derivative matrix, 导数矩阵
1 K8 t- V3 r0 D- F) f$ gDerivative-free methods, 无导数方法
- h+ B. }# D# s; _( J! LDesign, 设计
' w( O9 |+ \7 c% ~# c( jDeterminacy, 确定性/ `2 P0 t7 V$ A5 J( M# H
Determinant, 行列式
3 {2 Z i8 w) |5 |0 }Determinant, 决定因素
- _5 t4 h! X) p# eDeviation, 离差; X# r# m6 u5 ^' ^
Deviation from average, 离均差
( @! \' q+ W2 o; Y3 ^$ y* j) kDiagnostic plot, 诊断图
3 ]' R, v9 p6 e* D% u$ u w) ]4 BDichotomous variable, 二分变量
3 @5 j4 H, B" P4 R. sDifferential equation, 微分方程& z P0 S0 `; |& |
Direct standardization, 直接标准化法
y" S3 F Z! ]) J. kDiscrete variable, 离散型变量
2 P- J& o) x7 V0 f3 n" D5 e! r/ q+ ^DISCRIMINANT, 判断 " g% i0 x9 X) v# |( p7 D" E
Discriminant analysis, 判别分析. U% ~" E# U9 a" K: R- |2 d7 v
Discriminant coefficient, 判别系数
8 e3 o6 _' j$ _3 J( PDiscriminant function, 判别值. F$ t2 a% |. E. g8 x
Dispersion, 散布/分散度
" A% A1 M) f6 G( p* l( E% `Disproportional, 不成比例的6 i; Q& a5 s- N) h" K1 W% R
Disproportionate sub-class numbers, 不成比例次级组含量
L% H& }2 i0 ~6 LDistribution free, 分布无关性/免分布( ^& y5 C9 E, F1 B, x( ^6 T
Distribution shape, 分布形状
) z+ c/ p' _0 m1 VDistribution-free method, 任意分布法
' Y; C9 X8 {4 xDistributive laws, 分配律- ]) T& h0 B/ C; O" ?
Disturbance, 随机扰动项
* t6 Z: t: e2 N8 n- V( oDose response curve, 剂量反应曲线+ N- _5 k. T% G; K/ w
Double blind method, 双盲法
6 R0 S" | n- S4 dDouble blind trial, 双盲试验
& P6 |6 i6 |6 \! I" DDouble exponential distribution, 双指数分布7 W; n( V+ k+ k
Double logarithmic, 双对数
+ |/ \: o6 Y* P! SDownward rank, 降秩
/ @+ Q, b* J* [) B2 O# HDual-space plot, 对偶空间图
; @. Y0 c# ^5 V, X& @0 Z5 \7 q+ |+ H/ ZDUD, 无导数方法, o* G/ ^' @* M3 J7 }5 q1 V
Duncan's new multiple range method, 新复极差法/Duncan新法
2 K w* Z* Z0 V$ [Effect, 实验效应
' b8 U/ p5 l% I( g/ n, N+ d# wEigenvalue, 特征值4 m9 l4 y3 L" |- F& J7 j5 j( b+ e
Eigenvector, 特征向量# c3 S% J8 ?$ t
Ellipse, 椭圆: z Z! D8 c5 j/ G
Empirical distribution, 经验分布& M3 ?% y, f% o' C! v$ N* D, Z
Empirical probability, 经验概率单位
* w" A2 H" `0 r# f2 g" d) oEnumeration data, 计数资料' I3 x, {* g! ~/ u, M. ^- \( J
Equal sun-class number, 相等次级组含量
( @; w& H, t- q' E: @! `Equally likely, 等可能/ l, M4 l# d- K7 w9 j: `
Equivariance, 同变性- M! O) b! D* `/ Y9 T6 W
Error, 误差/错误* Z; v1 X' F$ n6 e( A- V
Error of estimate, 估计误差
7 f0 I! T, }% K j# qError type I, 第一类错误. c/ z% N& c7 q% U3 g' X4 z
Error type II, 第二类错误3 M3 u, L/ j4 K" V, T- b) e
Estimand, 被估量8 B0 N& Y1 {% I2 n S. Y
Estimated error mean squares, 估计误差均方- l$ ]6 V1 M: a' ]( _ `2 K
Estimated error sum of squares, 估计误差平方和
" e e9 W8 `6 IEuclidean distance, 欧式距离5 e( L7 N4 r8 ^7 F8 N4 Q
Event, 事件: r q+ Q- v* f1 d4 L3 }
Event, 事件* { V) t1 F4 V& [
Exceptional data point, 异常数据点. A4 J6 `3 i+ w8 N
Expectation plane, 期望平面
$ D K( \1 n6 B8 jExpectation surface, 期望曲面$ u6 ]/ F. [4 {' {0 }
Expected values, 期望值
% ^" H( k- Y* D: _& q: ` f- NExperiment, 实验
& A2 H& _5 M2 D% ~. E# |# i7 t3 m+ RExperimental sampling, 试验抽样4 V) l2 A; e9 O' h' X3 X. C
Experimental unit, 试验单位
/ L3 s7 W6 S1 d2 [- i9 A+ f% CExplanatory variable, 说明变量% ^% H. T% Q% ]" M8 n
Exploratory data analysis, 探索性数据分析
+ V5 c" [* S# u7 E! IExplore Summarize, 探索-摘要
' F# X8 N+ }+ B* I- V- ]Exponential curve, 指数曲线
$ P: k1 P8 I1 B/ S; |. qExponential growth, 指数式增长" z$ O# O3 y- i* M5 }4 o& t
EXSMOOTH, 指数平滑方法 . x% j6 L. G9 @+ w- z( L P. w8 Y
Extended fit, 扩充拟合9 Q* t2 T) h1 \$ U# t
Extra parameter, 附加参数) s: n4 }9 M3 o+ s
Extrapolation, 外推法
4 C( I& s+ J, U; P) }% y( iExtreme observation, 末端观测值
8 }2 P4 S: b: q$ L. xExtremes, 极端值/极值
+ I ^( t3 t0 c. P* U1 K9 B" DF distribution, F分布& |8 d% l9 T( O. i- T/ K' [" P
F test, F检验
4 B/ [) L9 {& {+ d# eFactor, 因素/因子! A, `, ~/ s! |3 z
Factor analysis, 因子分析
# ^$ u0 Y( i3 G" zFactor Analysis, 因子分析: |" D+ f5 P4 b# X& }
Factor score, 因子得分 & W& a3 Y1 V& `, y# |9 g
Factorial, 阶乘! l1 w! m' u! V. K* G$ _
Factorial design, 析因试验设计( [; o" z' S2 s/ {
False negative, 假阴性1 y! M- _# s3 s( [5 i
False negative error, 假阴性错误! |- N6 x8 W+ E
Family of distributions, 分布族/ B* \( i6 c6 P2 c
Family of estimators, 估计量族1 }) i/ g1 j5 P a. A7 y
Fanning, 扇面
# l* S! T' y: r/ H+ r* x9 J' tFatality rate, 病死率- _4 f. `: k1 U4 e! \ P
Field investigation, 现场调查
/ m) L; ^8 m% X: LField survey, 现场调查2 ~/ }. H/ n3 D$ w/ Z
Finite population, 有限总体) z2 _9 h* \ K' }9 W; ^8 a7 ^; q
Finite-sample, 有限样本+ }; B8 D0 _; L9 `2 j3 z% K- J
First derivative, 一阶导数
V7 ?: K3 h, D5 L5 k: x+ |First principal component, 第一主成分' F3 M% H( ~; T0 e4 K+ {
First quartile, 第一四分位数: S: c0 ^" E) t8 P5 @6 S- b" y
Fisher information, 费雪信息量
! w4 H: h' z) G, J: NFitted value, 拟合值+ |4 g2 t# q/ c6 H
Fitting a curve, 曲线拟合+ u9 M1 q( P) V3 r+ |- a
Fixed base, 定基$ }4 ^9 U9 E2 |/ Z5 G
Fluctuation, 随机起伏 [5 F7 { T9 | a0 W
Forecast, 预测% [6 G/ Y% f# R# }5 E0 E
Four fold table, 四格表
" c" L$ | m4 i, uFourth, 四分点" D; B! m( e6 V4 ~( T' u7 }& a
Fraction blow, 左侧比率9 i4 D7 _: V, }
Fractional error, 相对误差
( b! D G" r& b1 b! L- g: c- pFrequency, 频率
8 x9 s: [! ]: A. v, PFrequency polygon, 频数多边图& G1 G2 M* |% c# F1 c8 ~ `
Frontier point, 界限点
% A4 n: {, h8 m+ c9 q$ v/ H$ ZFunction relationship, 泛函关系
. k, ]1 E' J: o1 BGamma distribution, 伽玛分布2 c7 K7 C' M3 }: F; w! l; m
Gauss increment, 高斯增量
8 t- }) z+ |3 {3 o" e o/ C! _! L2 DGaussian distribution, 高斯分布/正态分布5 N$ Q+ o. V* _) b# [$ v! Z* _1 d
Gauss-Newton increment, 高斯-牛顿增量1 S5 i. O' c) g
General census, 全面普查
1 |& R4 B- \" _4 h+ W! kGENLOG (Generalized liner models), 广义线性模型 , [1 `3 P! G& u8 U; o$ U- Q
Geometric mean, 几何平均数- j9 H! y2 @! F5 g% e
Gini's mean difference, 基尼均差3 h; a8 l6 j3 }3 Y5 j6 s
GLM (General liner models), 一般线性模型 ) d' ~5 b4 @6 a" B# j3 I% U
Goodness of fit, 拟和优度/配合度: g: w: d! |! _' k
Gradient of determinant, 行列式的梯度% J2 _) g3 F- f
Graeco-Latin square, 希腊拉丁方
% b! L" T; a4 qGrand mean, 总均值
) {, ~1 g# ?9 a- k0 R6 W+ gGross errors, 重大错误
- L* B8 K! Y R) K) @Gross-error sensitivity, 大错敏感度+ X4 f& h1 ^5 q! P$ Q
Group averages, 分组平均- a' O. G! f: v4 E; W+ {9 t& ?; q
Grouped data, 分组资料4 Z0 k9 m/ k% [7 H$ l. h
Guessed mean, 假定平均数
1 w: g5 `" }# f. \Half-life, 半衰期
* ]! T- t) Z& g1 s: w" UHampel M-estimators, 汉佩尔M估计量
7 g0 c$ z7 b# G$ _0 THappenstance, 偶然事件
8 L' B6 q3 z5 a# `7 V# ~Harmonic mean, 调和均数
8 m, I9 S. b% R' b8 gHazard function, 风险均数
% y+ |6 e0 D3 k) s% `8 _% dHazard rate, 风险率
* d" e0 y0 n9 s: M2 s! l0 qHeading, 标目
W4 z: u/ \. ^0 h$ M) uHeavy-tailed distribution, 重尾分布
/ z9 V. P& m1 c7 G1 _Hessian array, 海森立体阵- g/ r, B6 u4 j7 j; z. F
Heterogeneity, 不同质" |/ w2 G; x& }! _+ G/ U0 n% ^! Z R
Heterogeneity of variance, 方差不齐
; w& O+ r) p: X, h. |Hierarchical classification, 组内分组4 L! Q% Z8 G. `; V! [. e$ i
Hierarchical clustering method, 系统聚类法& W8 _7 k) A; T- r) ]- n" s
High-leverage point, 高杠杆率点8 z/ z. ?& a0 B* c& ^! ~, a
HILOGLINEAR, 多维列联表的层次对数线性模型5 `& o. J; f( u' I. X) ]1 O# n
Hinge, 折叶点
) T2 c5 x7 O1 P% O6 e* qHistogram, 直方图
z2 y+ W- J7 @: w. ?, a5 FHistorical cohort study, 历史性队列研究
) [$ Q+ d' c* k9 cHoles, 空洞
) I" ^: Q H- L# G/ pHOMALS, 多重响应分析
, u# y& c) h, THomogeneity of variance, 方差齐性( t* e4 `; W' q
Homogeneity test, 齐性检验) @$ f/ v: e5 F+ c0 b
Huber M-estimators, 休伯M估计量 N6 g' g% T6 F& d# K7 I
Hyperbola, 双曲线
9 P/ q7 n3 R) lHypothesis testing, 假设检验+ H, |0 @: n. h; A4 A
Hypothetical universe, 假设总体- I/ X" a6 p" R, @* [
Impossible event, 不可能事件% a# t/ C/ o1 m5 K; ~5 i
Independence, 独立性
0 J R" @5 f- @2 y$ gIndependent variable, 自变量
2 Z' i6 e7 \" k' ^7 xIndex, 指标/指数+ Q) G. J3 q6 Q( e9 u
Indirect standardization, 间接标准化法7 Q4 ]& V s) i5 i( { ]7 Z/ k
Individual, 个体# f! Q& J3 |0 R( t# }
Inference band, 推断带
/ n0 ?- K2 j$ {7 _3 h! MInfinite population, 无限总体
8 f" @, H2 p- c+ h& N8 yInfinitely great, 无穷大
9 P8 v4 N+ o' {Infinitely small, 无穷小
5 W4 @$ t, z4 q, l" [ tInfluence curve, 影响曲线$ z& \3 |9 O8 P6 x' _2 T
Information capacity, 信息容量0 z2 ^/ l7 |% p+ e
Initial condition, 初始条件
7 S+ V4 u) e/ |4 Z0 ~Initial estimate, 初始估计值
" ?4 Z) C1 w& L5 j& I* T7 ZInitial level, 最初水平) s7 q, F, _: L/ X8 q6 ?+ D% P
Interaction, 交互作用
% ^9 v7 z" y% e3 W9 U( a% oInteraction terms, 交互作用项* [) d( w$ M$ x" m8 h
Intercept, 截距: M6 o' r* x, v
Interpolation, 内插法
/ {: K6 [7 \: E" @; tInterquartile range, 四分位距
# P8 V: K/ J! y" [: i+ R( e! fInterval estimation, 区间估计
% L4 o0 o* E1 sIntervals of equal probability, 等概率区间" i4 h" m! Y' Q
Intrinsic curvature, 固有曲率
- P( ^, ^# L7 b/ N/ r$ hInvariance, 不变性& e9 T& d% y L* k8 h) D& u/ `
Inverse matrix, 逆矩阵0 n. e- S/ W" a0 v
Inverse probability, 逆概率
' [- o* N; `. w p" m! FInverse sine transformation, 反正弦变换
; h' `, \) F5 Z! xIteration, 迭代 " {6 U6 {2 f9 s+ ]$ j+ Y# R
Jacobian determinant, 雅可比行列式
9 L/ f `5 i/ a' A6 B4 O+ p4 H8 O) aJoint distribution function, 分布函数# I+ Q4 U0 F# x- w) w/ J
Joint probability, 联合概率( R1 u# z/ F$ d7 y6 I$ }8 }0 N
Joint probability distribution, 联合概率分布
9 ]; D: Z# G0 GK means method, 逐步聚类法& p( ?% v* @! |8 B
Kaplan-Meier, 评估事件的时间长度 # U! Z9 C3 l! v6 W7 j3 ]+ [
Kaplan-Merier chart, Kaplan-Merier图6 ~, ^# N4 Y9 e' {
Kendall's rank correlation, Kendall等级相关! _2 m8 o i* B. }" q
Kinetic, 动力学
% d) l {" \! |Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
, y; b- |3 }" t3 q7 z5 OKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验1 h9 w4 @- d2 O, e
Kurtosis, 峰度
: F4 y/ n- G D0 @( ZLack of fit, 失拟/ t x, l8 N) h s7 y- `$ w
Ladder of powers, 幂阶梯. q7 p* s2 e# _ n- C. u
Lag, 滞后8 a: m7 z1 F: L# H: a& i5 f3 n
Large sample, 大样本
' q% M# ]- t1 S+ uLarge sample test, 大样本检验+ c9 N a7 q9 m- `( ^$ Q3 X
Latin square, 拉丁方
+ t' l3 \1 n% ]6 b# gLatin square design, 拉丁方设计# C q/ \- Z; y$ H3 a+ C& M
Leakage, 泄漏
0 c5 \' p. Z9 @/ }Least favorable configuration, 最不利构形
% J/ V1 S) y. _1 CLeast favorable distribution, 最不利分布
! A1 K5 E4 _ g5 n+ u! v& E$ VLeast significant difference, 最小显著差法# N' }$ Q, Y% |, t+ S
Least square method, 最小二乘法
' o$ i$ m% l9 ~% uLeast-absolute-residuals estimates, 最小绝对残差估计
/ m/ d( X: l6 [& Q! ]# HLeast-absolute-residuals fit, 最小绝对残差拟合8 p$ I3 Q$ V, A; B9 X
Least-absolute-residuals line, 最小绝对残差线
Z0 ~' R7 u8 F3 R Q- ELegend, 图例
& p: H4 H8 @. s. N3 `L-estimator, L估计量, J' a2 Q' |3 O2 f5 `9 v
L-estimator of location, 位置L估计量
5 S7 Z6 j1 G9 v1 A2 L: oL-estimator of scale, 尺度L估计量& o }) z6 H& u3 x P/ {9 r
Level, 水平2 D* }- `4 J$ T8 {
Life expectance, 预期期望寿命
2 t. j1 C$ C' {! cLife table, 寿命表6 K- o d& }4 D$ [+ R9 K
Life table method, 生命表法* C0 g4 J6 }+ z
Light-tailed distribution, 轻尾分布
# c$ H: `+ _! C$ P% h. yLikelihood function, 似然函数
6 ~* o! M) R' R) ^4 F5 p: [& A! pLikelihood ratio, 似然比
: w1 ]0 q8 y7 o4 `line graph, 线图
/ ]# O: E$ r# p0 `9 H& t8 I: eLinear correlation, 直线相关' ^+ `+ P* D7 o- ^, A, [
Linear equation, 线性方程3 h/ P* X/ H* j @) P
Linear programming, 线性规划6 J! P5 g1 [6 e8 C' L
Linear regression, 直线回归
: u0 I! O! x5 Q. C3 L8 x+ TLinear Regression, 线性回归/ T) G* U4 g! f% [( b1 W' s7 S* r* o
Linear trend, 线性趋势, H! r; w. p1 Y# p$ t
Loading, 载荷 $ k) a- a. w. I: F! }
Location and scale equivariance, 位置尺度同变性
% I; k$ ?/ Y# f: ]5 TLocation equivariance, 位置同变性4 G& y# k1 V7 I2 @8 w2 E
Location invariance, 位置不变性
8 d3 H, r( R9 o3 `Location scale family, 位置尺度族
; |% V( j: Y: p' u' i7 L7 KLog rank test, 时序检验 0 P$ V# I7 y9 w* n2 v- O+ T
Logarithmic curve, 对数曲线! x0 v0 Y' W+ x* q Q4 Q1 q( F
Logarithmic normal distribution, 对数正态分布' M6 a5 f, @8 k( V t% I: b
Logarithmic scale, 对数尺度/ b0 [9 S8 ~: Q) j
Logarithmic transformation, 对数变换; R2 K, A* b, t7 n! z
Logic check, 逻辑检查- x" x6 E6 v4 h+ H
Logistic distribution, 逻辑斯特分布
/ H, T; f$ \ MLogit transformation, Logit转换0 o( j8 F# g5 C- v& W, o" ]; S: W
LOGLINEAR, 多维列联表通用模型
4 V; N5 i4 z( w, q! I/ eLognormal distribution, 对数正态分布: Q0 P2 ]/ C3 @# s/ v, r
Lost function, 损失函数 @0 [# x$ }- t( g
Low correlation, 低度相关+ H% ^' k5 [! q* ?8 F1 k
Lower limit, 下限 q3 u1 q, ^7 }2 D
Lowest-attained variance, 最小可达方差% `4 X' H6 }/ l0 K. R6 d1 z a
LSD, 最小显著差法的简称
+ Z' t j2 C& A6 BLurking variable, 潜在变量( Y/ j, ]4 w# t! I, K3 K+ u2 b/ e
Main effect, 主效应
# h9 A3 j$ q3 MMajor heading, 主辞标目
; H; A: W: E3 E3 t3 x% lMarginal density function, 边缘密度函数% u2 f( }3 ~) A9 o' z; o! e; }
Marginal probability, 边缘概率
' V2 I/ v1 X# ]2 z) ]' jMarginal probability distribution, 边缘概率分布5 ~, h4 y5 Z8 k3 W
Matched data, 配对资料# B4 D- O2 K8 A, q. e* u; Z
Matched distribution, 匹配过分布
1 V3 A6 K/ g4 }3 ~0 c# RMatching of distribution, 分布的匹配* m2 I N5 p* t z
Matching of transformation, 变换的匹配2 e6 M2 P+ u6 s5 b6 y: k
Mathematical expectation, 数学期望0 {9 H3 o% s b
Mathematical model, 数学模型
& Q4 r0 H S+ |* n0 s3 t' r: aMaximum L-estimator, 极大极小L 估计量
5 n% [* c. i) k! `6 ^) EMaximum likelihood method, 最大似然法" L$ |" |$ Z* P8 V
Mean, 均数
. Y4 D( X' R2 z/ u7 J! YMean squares between groups, 组间均方- t! ^% r- }2 O0 f) v; p
Mean squares within group, 组内均方
# E- O5 Y1 w8 i2 o; ~, R* SMeans (Compare means), 均值-均值比较
! j+ P, w9 U& ]5 `" j5 L( mMedian, 中位数
5 N3 t: l$ C# z0 k$ M2 z) F5 k6 e- cMedian effective dose, 半数效量+ @; z8 F3 X0 P$ X8 `. D
Median lethal dose, 半数致死量
- `7 T7 f0 w% L' ^! DMedian polish, 中位数平滑
9 |. ~5 r" ?* s1 AMedian test, 中位数检验
% z, Y0 _3 i5 C* P* \# W& R* |Minimal sufficient statistic, 最小充分统计量
8 I; {) M3 Q* Y& w# x eMinimum distance estimation, 最小距离估计9 G$ x' _8 @4 _0 `! ?6 l0 a
Minimum effective dose, 最小有效量2 a' k. P5 G" X. p1 m
Minimum lethal dose, 最小致死量/ A6 g( o# r: q9 l; g
Minimum variance estimator, 最小方差估计量1 M' Y' D: W' b N2 }
MINITAB, 统计软件包" \( V. e% Y( Z7 V# j/ h! `+ [
Minor heading, 宾词标目
$ t! Y' \2 ~" \/ M( L0 s- q" MMissing data, 缺失值
) `1 P/ a/ L+ }' b! u; C- r/ [Model specification, 模型的确定
5 T8 p) q2 {7 C: X& MModeling Statistics , 模型统计
$ d, E/ I) m; U! W4 JModels for outliers, 离群值模型
; }0 v7 c3 R) T8 k( zModifying the model, 模型的修正
) y: K0 P$ @, u4 A% a( fModulus of continuity, 连续性模2 b9 j8 ?7 l8 m, r4 t" d2 J
Morbidity, 发病率
$ H0 F' c1 Y1 {3 |0 i y% v. ?Most favorable configuration, 最有利构形5 ]; I2 ^; R9 b/ G! d0 S" s. _. Z
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
, I% e2 z8 I# l& p' ?2 iMultinomial Logistic Regression , 多项逻辑斯蒂回归" i0 T8 s" U6 Z) e, T. X1 S! L
Multiple comparison, 多重比较
$ q: ^5 z$ V4 `. QMultiple correlation , 复相关/ [, A' F# A) o+ n- e3 N
Multiple covariance, 多元协方差4 Z. ~* P* [; | l, ~$ o, N
Multiple linear regression, 多元线性回归+ q( ?, D: V* M8 ^
Multiple response , 多重选项0 l e2 Q5 \( K ?& [5 x
Multiple solutions, 多解) Q, B$ Q' @. v( j
Multiplication theorem, 乘法定理6 w" Y0 R4 q# a% m8 C1 m* M v: Y$ U& }
Multiresponse, 多元响应5 T% s! d, g/ e. U0 v, `
Multi-stage sampling, 多阶段抽样/ m* ]! W' `& q1 Q* O3 G! f3 o
Multivariate T distribution, 多元T分布- N6 P1 }* a+ ~
Mutual exclusive, 互不相容4 G% e: n9 \, r
Mutual independence, 互相独立
u0 Y, s$ @( d& y# P$ u5 [# CNatural boundary, 自然边界
) Z& s6 ^: g5 h* ~% RNatural dead, 自然死亡
% u6 d: n9 R/ D& e# CNatural zero, 自然零
; C" F9 v4 |1 L/ H4 fNegative correlation, 负相关
1 _. |* @3 p# U9 f9 j& FNegative linear correlation, 负线性相关
7 H3 d% M' f3 z. bNegatively skewed, 负偏
% A! m% Q) _ y0 r5 VNewman-Keuls method, q检验 C- r. W2 L- Q) l8 j, q6 M+ e8 b1 `
NK method, q检验) r$ R9 u* R7 H
No statistical significance, 无统计意义
! D0 C# [% I& Z, A3 nNominal variable, 名义变量
8 j: @2 d) s- A0 ^Nonconstancy of variability, 变异的非定常性 s+ g: K1 h3 ]: J# u4 X
Nonlinear regression, 非线性相关 N, d) w+ K9 |% Z
Nonparametric statistics, 非参数统计
7 e' O' y( ]0 s0 f4 O) HNonparametric test, 非参数检验6 W+ X8 q% G, L2 E( u+ Z8 Z7 o# C
Nonparametric tests, 非参数检验 b' N4 z P3 \( X9 D
Normal deviate, 正态离差
$ s0 ?, X5 s m' DNormal distribution, 正态分布0 j6 _# X8 o" n( D7 ~
Normal equation, 正规方程组% S7 X: a5 `- Y) H
Normal ranges, 正常范围
( H- L( E+ |8 m( M$ I1 ~Normal value, 正常值 U$ r$ _6 h( r8 b! R. e( W2 V
Nuisance parameter, 多余参数/讨厌参数
9 ^ v1 P, _8 @/ i& a& Q- MNull hypothesis, 无效假设
+ u6 ^6 E7 Y2 _# lNumerical variable, 数值变量
6 A( b. @, R' `3 IObjective function, 目标函数9 F! o3 d: g6 @' r/ T
Observation unit, 观察单位
5 \* w$ \, y% G9 }/ H* QObserved value, 观察值
$ V! W0 b' [( VOne sided test, 单侧检验) J: s1 b* D1 a( n# W
One-way analysis of variance, 单因素方差分析
5 `, a; w, R* g! AOneway ANOVA , 单因素方差分析
" ~! o! J3 O7 r( S! ^9 A1 O LOpen sequential trial, 开放型序贯设计# f9 v0 ?0 K( d' i' C4 M8 @" T [
Optrim, 优切尾4 r& r) w3 F) G; o9 S
Optrim efficiency, 优切尾效率& F: H6 f' E, D; ^7 q
Order statistics, 顺序统计量
% P+ t- a f3 @/ Z0 |, ]Ordered categories, 有序分类
* J. t* h' ~; qOrdinal logistic regression , 序数逻辑斯蒂回归5 u, B& O: O' n% \9 n# G
Ordinal variable, 有序变量5 V, }0 Q1 `% H2 f2 H0 @8 L
Orthogonal basis, 正交基
2 x$ e7 p& h- p: Q9 uOrthogonal design, 正交试验设计
/ u/ C/ T) e+ x2 |: o! dOrthogonality conditions, 正交条件7 C0 A- Q2 G' J
ORTHOPLAN, 正交设计 % _/ j. G. }+ P
Outlier cutoffs, 离群值截断点
; L. Z9 p: n+ y) ]Outliers, 极端值3 I+ t, F' W. f% ^7 a- o* b4 z
OVERALS , 多组变量的非线性正规相关
/ T p! t8 B" Z/ b. L2 J# j% POvershoot, 迭代过度
8 e3 O( `* [3 A% I) oPaired design, 配对设计: }+ ]" e7 o7 F/ J3 x f" O- z5 c
Paired sample, 配对样本* J8 O4 Q5 ^1 N N/ H. \
Pairwise slopes, 成对斜率% y8 ]5 N* U. L8 j$ x
Parabola, 抛物线4 K. m! c- x" x1 q+ M$ {
Parallel tests, 平行试验5 J# E, N# S5 d) m, e; K
Parameter, 参数
) R n6 V5 k8 vParametric statistics, 参数统计% f! w7 E+ z% E5 K/ |
Parametric test, 参数检验
$ {$ F: l/ I2 ]' A$ U# g7 XPartial correlation, 偏相关
$ p0 z) M; r4 ~ |0 YPartial regression, 偏回归
3 ^8 P% \1 E. {3 k. {/ S; R+ ^. XPartial sorting, 偏排序
$ m. A# u" ^% Z0 r) {8 T4 oPartials residuals, 偏残差 y- d# Z% R+ o
Pattern, 模式& L2 ~1 R0 g: C) b
Pearson curves, 皮尔逊曲线
3 K6 V5 N7 ` K( E* Q4 ?5 x# B) W |Peeling, 退层
! J% W8 m; S1 C' \; N* o/ f2 DPercent bar graph, 百分条形图
! X6 I2 S2 J& w- t g" @Percentage, 百分比; I- f9 _) ^# V% n, b5 {3 x
Percentile, 百分位数
8 Q# k7 j; z; nPercentile curves, 百分位曲线+ T) g( c! A0 g
Periodicity, 周期性; v. G1 X8 J0 G1 S1 c* v- {' [
Permutation, 排列0 A6 g0 }' _ c( F( \& A% D) v
P-estimator, P估计量; r! o: T: z5 j$ S. x7 q X9 n
Pie graph, 饼图" W6 q4 P3 J7 Y: C2 g
Pitman estimator, 皮特曼估计量1 s4 {" p% \( y* q( @( s. m1 n! @
Pivot, 枢轴量
: N& d: I9 `5 { ZPlanar, 平坦
Y0 @) E. |+ ?, b3 A. bPlanar assumption, 平面的假设
. Z# j' F( K3 v1 A0 s& o+ WPLANCARDS, 生成试验的计划卡
3 [9 O6 |: ]# D2 `' K1 y* zPoint estimation, 点估计- F) h6 l6 {3 Q) r; Y& X
Poisson distribution, 泊松分布
1 C& S+ Y+ _; [& H bPolishing, 平滑
) n8 Z& L# Y! ]! W- \4 B/ ~Polled standard deviation, 合并标准差
! x: A- e7 x' d* hPolled variance, 合并方差6 R1 |' c6 ], K2 S7 a
Polygon, 多边图
' | j5 R5 ?5 K+ QPolynomial, 多项式' e3 Q2 x- c8 @
Polynomial curve, 多项式曲线- z; N. Y+ F/ a5 y
Population, 总体' j2 G0 w: C1 b7 g; H, E3 \4 w
Population attributable risk, 人群归因危险度2 S( j" y- I$ P5 n; o. o p
Positive correlation, 正相关1 a; R! T: P( f) F( g/ v; V2 h
Positively skewed, 正偏
) R! @0 ^7 s! `6 r/ ]Posterior distribution, 后验分布7 V1 V z; [3 l r
Power of a test, 检验效能
& z4 a! M! C4 U0 R5 aPrecision, 精密度
7 n2 f* E" I) M4 Y" e mPredicted value, 预测值
6 b; k/ X0 q1 x7 T; g# r% jPreliminary analysis, 预备性分析
u9 f4 I9 L3 M! a( {. Q' _Principal component analysis, 主成分分析
; q% i* @! e, I' i9 v/ J i) w& ?Prior distribution, 先验分布4 c6 ^& x: a( O! V# B
Prior probability, 先验概率
# ~( L/ J0 T3 u5 hProbabilistic model, 概率模型
4 p1 m9 c( G( ?. C6 }% J2 Y& |/ j+ ?probability, 概率
) D( R1 Q, k4 ^* A; l; d% G* KProbability density, 概率密度5 B9 }/ F/ E. w: \( n/ z# i* p
Product moment, 乘积矩/协方差
, D/ a% }5 c# Z( o. m( s- Q3 OProfile trace, 截面迹图
1 u" z! C9 m2 ~& VProportion, 比/构成比 P9 A! j) _. i) \, i( w4 w
Proportion allocation in stratified random sampling, 按比例分层随机抽样/ d5 x1 |7 {' G/ c5 z
Proportionate, 成比例
% V: {. D, V9 F6 qProportionate sub-class numbers, 成比例次级组含量
& G* ]) O- Y% T6 V( ~) d IProspective study, 前瞻性调查
, Y% H1 w' E" ?' WProximities, 亲近性 9 O0 g* D+ d. \0 w0 T0 O, r
Pseudo F test, 近似F检验
# _+ [; T/ n1 W) oPseudo model, 近似模型
7 |. q6 N1 W0 u" v# Y" H- n& PPseudosigma, 伪标准差; g: { e7 a" Z- r) k
Purposive sampling, 有目的抽样& F2 c2 `% X$ ?0 E6 e* _
QR decomposition, QR分解
$ t- i4 i3 s$ [. W: y% C; `, L7 F0 XQuadratic approximation, 二次近似3 n! P+ F" a* C) I& a9 M. n q# a; R
Qualitative classification, 属性分类
) f+ V+ S" z! s8 `8 \# B' _; ~Qualitative method, 定性方法
& Y! s7 ]" l& G# X. aQuantile-quantile plot, 分位数-分位数图/Q-Q图5 B, z% x8 W' N/ x- R" v$ ?9 C
Quantitative analysis, 定量分析
" Y ^4 v6 T8 G. l, g5 L4 vQuartile, 四分位数
2 y. E( o+ m+ }& O0 LQuick Cluster, 快速聚类
5 I2 A2 n: l% A) B/ H9 v- V$ y# sRadix sort, 基数排序
/ l& E$ @) w( aRandom allocation, 随机化分组/ n0 f4 p: |4 U, c& s- U
Random blocks design, 随机区组设计, _, s- ^( f! e
Random event, 随机事件
$ f/ Z& k& t% O6 dRandomization, 随机化4 y# g' L* z1 ^# Q1 V
Range, 极差/全距4 w( f- ~: X5 I7 U; M: |
Rank correlation, 等级相关+ k; N$ H0 S( e! u
Rank sum test, 秩和检验" t/ d2 J* A( u/ `5 {6 w2 J: u
Rank test, 秩检验
+ W) L2 e9 _8 C) x, u9 ?Ranked data, 等级资料
- U) B$ B i9 \- t$ _Rate, 比率
3 s% C3 y# u) N: O, z+ T" b- {Ratio, 比例
) E+ m, M" b/ V1 `Raw data, 原始资料
! u9 L' \. |# t0 w& M" L! aRaw residual, 原始残差: g. x' M* I' _2 z( ?" O3 U
Rayleigh's test, 雷氏检验
3 B: {- t9 v; A4 G! wRayleigh's Z, 雷氏Z值
5 d4 S/ q' c, e% S. v& XReciprocal, 倒数
; f/ M; T6 Z7 R: r# oReciprocal transformation, 倒数变换% \8 R. q' g2 M! ]9 {( w$ D& g
Recording, 记录6 |. l# z# V) O9 T- L2 y
Redescending estimators, 回降估计量
% |8 g" o% ?5 s2 AReducing dimensions, 降维9 U! L" ]5 r$ \8 P- r% u' r2 s
Re-expression, 重新表达: w) ?* L7 M# Z: N1 |6 a
Reference set, 标准组& k# y3 E N7 b
Region of acceptance, 接受域
- w/ E$ [; X. I/ W5 X/ ~Regression coefficient, 回归系数8 l, ]$ J5 _# [, g' r; Y2 P
Regression sum of square, 回归平方和2 b( ?. S. P) b K+ v
Rejection point, 拒绝点
I' e+ X, B p+ x" \Relative dispersion, 相对离散度+ A8 ~3 J8 k% t6 r" W
Relative number, 相对数
5 h* W: Z( ~* m+ f) [+ PReliability, 可靠性5 ~' h& L% U2 E
Reparametrization, 重新设置参数% l+ j, y$ X+ R$ h
Replication, 重复
! D0 n0 W+ O) i5 F# ]% OReport Summaries, 报告摘要
' o1 r/ G% x6 S4 E [" MResidual sum of square, 剩余平方和
! A# O+ N% H$ G, m( n2 DResistance, 耐抗性6 ^9 a3 m. b, u
Resistant line, 耐抗线
) ~3 ^5 @, \4 L1 hResistant technique, 耐抗技术2 d3 T# g# P% d" x4 m5 I5 ?
R-estimator of location, 位置R估计量4 {2 N5 J4 E( p3 {
R-estimator of scale, 尺度R估计量2 L$ g; Q v' ]8 D& M) }
Retrospective study, 回顾性调查' }! R p. n: t4 q) H6 P. Z
Ridge trace, 岭迹
4 j' D5 @8 q4 b/ d+ Z# F0 S: sRidit analysis, Ridit分析. ]' H2 {& p4 T$ `
Rotation, 旋转+ Q( m; a% e! y
Rounding, 舍入
" d6 G$ n. Z3 z: s2 l+ f1 ZRow, 行
2 O+ B* @1 y; e( }) P8 WRow effects, 行效应& p0 E" O/ i5 T7 W- l. {. V
Row factor, 行因素
6 ^8 B" `$ u: mRXC table, RXC表" T/ I; j( Q" f; P0 K# M
Sample, 样本
$ y( f: B3 K( m1 XSample regression coefficient, 样本回归系数
1 n) @6 Q4 V/ e# y q, z1 E1 _Sample size, 样本量
# p5 K( T# f, n# c" y1 USample standard deviation, 样本标准差6 T: u9 P( C/ q
Sampling error, 抽样误差4 |* D& w+ E" H! J) n$ X+ ~; c
SAS(Statistical analysis system ), SAS统计软件包3 l/ i& A6 l2 z8 {
Scale, 尺度/量表
! v( z' @; U% |. Y" yScatter diagram, 散点图
) v" ]/ `) d. h% h( G; e3 dSchematic plot, 示意图/简图
. |( M; o, S) ?6 x8 q5 mScore test, 计分检验
+ O; I- t- i6 o2 Y$ g( R5 fScreening, 筛检
. \, ~5 v5 w, K8 W3 dSEASON, 季节分析
% o. M {: P7 ]: R9 DSecond derivative, 二阶导数 j1 B0 B, j: Q, ^7 ~; U
Second principal component, 第二主成分
+ G& e. Q- t$ O3 T5 X z" ySEM (Structural equation modeling), 结构化方程模型
2 \3 O( F! Z$ L; }4 QSemi-logarithmic graph, 半对数图
/ j; M+ D; N% y: pSemi-logarithmic paper, 半对数格纸9 l) [/ F- m7 z4 r: r
Sensitivity curve, 敏感度曲线) m4 [4 T# `0 H1 C
Sequential analysis, 贯序分析' M) l( |7 L ^2 a3 n5 t& a. [; c
Sequential data set, 顺序数据集
/ ]5 I& T. S4 x% e X9 {: ESequential design, 贯序设计
b _6 w: C g9 x1 w/ W. ESequential method, 贯序法
! W. |- ?7 L( m! m! T( ~Sequential test, 贯序检验法
' M% J- g- W4 |) M7 i6 Y( g% P2 }Serial tests, 系列试验- m2 E' L( y7 D
Short-cut method, 简捷法 4 {: {! Z, A4 ~& q5 K! L V5 {
Sigmoid curve, S形曲线$ H5 J0 K( z$ Z/ R
Sign function, 正负号函数
$ F/ M% w1 w; U# u! N8 TSign test, 符号检验
* \3 {7 g* g/ d: WSigned rank, 符号秩1 J: K" {: O4 E6 {5 j
Significance test, 显著性检验6 `. g, _& o2 q" u
Significant figure, 有效数字6 t3 |4 `* y1 @
Simple cluster sampling, 简单整群抽样8 E% v$ ~3 Q# q7 k
Simple correlation, 简单相关
# z9 ~" ~9 N, }5 S! N2 {Simple random sampling, 简单随机抽样
$ R5 J( w; m! p- ?$ ?Simple regression, 简单回归: w$ B" X/ |$ ~$ g0 i) f8 Z
simple table, 简单表
- w* Q" t% d2 W1 _ QSine estimator, 正弦估计量
3 q" v2 Y# O+ F; |( K' Z' d% ESingle-valued estimate, 单值估计5 i" _5 ?$ @; K) K! ^
Singular matrix, 奇异矩阵
& I" I8 H5 l" Z7 J3 ^Skewed distribution, 偏斜分布* Z- T, o9 R2 h
Skewness, 偏度+ p5 O+ _$ l: A, o) n" c; v
Slash distribution, 斜线分布6 K* M# m$ {* C" e" D
Slope, 斜率; s! W# J" ~" {, A2 Q/ C
Smirnov test, 斯米尔诺夫检验. \# q5 p, u0 h! u$ V
Source of variation, 变异来源; Y d: \7 w4 D- W
Spearman rank correlation, 斯皮尔曼等级相关
7 @' x) m9 r( E+ bSpecific factor, 特殊因子7 x$ m4 }% \: N. p/ O
Specific factor variance, 特殊因子方差+ }" g9 N a' g/ J
Spectra , 频谱# Y- p9 s/ F+ i: ~1 p3 i# m
Spherical distribution, 球型正态分布2 i% a* G( k3 D8 D; |5 G9 @
Spread, 展布
K- ~9 \6 _6 M; U: z+ C, q& iSPSS(Statistical package for the social science), SPSS统计软件包
9 M' ?. {0 k7 M3 oSpurious correlation, 假性相关2 _' Y! D5 \% p; X
Square root transformation, 平方根变换' `* l1 G( C: O: w* X
Stabilizing variance, 稳定方差
; s6 Y% {7 v6 w# wStandard deviation, 标准差
# s; ~# u8 i* c, wStandard error, 标准误4 g" g1 |$ c7 C( p
Standard error of difference, 差别的标准误
8 x$ F" H; F: G( L9 P U6 d5 {Standard error of estimate, 标准估计误差
1 ]1 u$ b6 s P9 U8 `Standard error of rate, 率的标准误; I% D2 Q3 H$ Y# w; V, g
Standard normal distribution, 标准正态分布
( P2 @5 ]4 P) k7 Y" |# \4 e! zStandardization, 标准化- B+ D/ ?. `+ x6 o" a2 O
Starting value, 起始值* I' |" i8 \4 \4 I$ p
Statistic, 统计量8 I! N8 ]. z; O: Z
Statistical control, 统计控制6 w, Q/ [ O% D8 k5 C; p$ A- n7 u
Statistical graph, 统计图
& p/ F( X; h T) CStatistical inference, 统计推断
& H& v& X5 y z8 y4 OStatistical table, 统计表
" j7 A$ D# U/ a6 PSteepest descent, 最速下降法
* E) m3 r: _3 P, A( g* WStem and leaf display, 茎叶图1 `* A9 S: T! d2 ]
Step factor, 步长因子
0 `" N0 U \; g" z0 kStepwise regression, 逐步回归1 _5 l: J/ r. h( z# ~! f! B
Storage, 存
8 m" P( R: ]( Z, A; ^1 O* }Strata, 层（复数）
2 f# E& Y8 G( \; W4 W& WStratified sampling, 分层抽样
5 \: ^+ Q/ p# j7 T2 kStratified sampling, 分层抽样/ r: Y1 s' x5 H3 T( w/ A2 H k
Strength, 强度
9 y r* V# N2 ~) lStringency, 严密性
/ E! U9 }/ {( y; ~9 t5 bStructural relationship, 结构关系
" s" R* F. C; r- Y1 NStudentized residual, 学生化残差/t化残差$ }* ]/ p9 K5 f/ g
Sub-class numbers, 次级组含量6 I* |* _0 @4 _$ o# M$ N1 C+ g
Subdividing, 分割# h0 D5 C% O5 D2 T5 b; q
Sufficient statistic, 充分统计量
- p: s4 |. P& \0 c3 qSum of products, 积和
q; A/ e" n3 x* P6 sSum of squares, 离差平方和
/ c0 o! z( O0 `' k4 m, m, mSum of squares about regression, 回归平方和
) I. N: r/ ~( x7 XSum of squares between groups, 组间平方和
, h. J; p' t h: y* L) Q0 k5 C- zSum of squares of partial regression, 偏回归平方和 S! t! S1 j. q% y
Sure event, 必然事件
! j: s: ^) f+ H. |: O* w% z# T7 XSurvey, 调查, n: X7 e! [' t/ @, t1 F! v3 G
Survival, 生存分析
) t4 _3 Y" E' y- C1 }Survival rate, 生存率; Z& ~* R, L. w3 S- H- e7 j6 R, T! B
Suspended root gram, 悬吊根图0 l6 E/ E8 X# R" l5 N* Q
Symmetry, 对称$ X, k/ X6 ~; d: C
Systematic error, 系统误差
3 ^) f8 ~( i( g3 k. y# @$ @# c: xSystematic sampling, 系统抽样) @& u+ q3 P2 e. s/ J
Tags, 标签6 i7 H" K% ~7 y8 q8 y9 |5 i
Tail area, 尾部面积6 @, S2 S. s. n# l
Tail length, 尾长
1 O" c5 \- b1 T- DTail weight, 尾重! m& t3 D1 H% F9 ~( A
Tangent line, 切线6 g# ` H, O! F0 T. f5 z
Target distribution, 目标分布7 N6 ?$ S- q4 `& c: O0 L$ O# ^+ |9 u
Taylor series, 泰勒级数( h! B& K* s- I' N1 b
Tendency of dispersion, 离散趋势
6 W% b, m& [5 j/ x' O% @4 f! [Testing of hypotheses, 假设检验
. t0 u# O; H) _& k0 A) C! F. x& dTheoretical frequency, 理论频数
0 i4 @' C, E2 ]6 d( b: yTime series, 时间序列
4 p4 M4 i; j- d* `" ^Tolerance interval, 容忍区间
" m5 e4 q1 T6 B: {Tolerance lower limit, 容忍下限
- V4 \. l% |' ^7 lTolerance upper limit, 容忍上限8 T8 X+ q1 I# T# l' f: i- v1 m
Torsion, 扰率/ H1 m7 ?# v! {, l& A0 o* @& K
Total sum of square, 总平方和( T4 t- e$ M4 c$ e
Total variation, 总变异" S& \) p" i2 B; C! T: t) |
Transformation, 转换) n9 h& z1 ^# O6 | }% U( l N
Treatment, 处理$ M0 j+ b+ \4 ~3 q
Trend, 趋势
( N; \8 ?% o, [2 \. OTrend of percentage, 百分比趋势3 i/ c8 t$ E& r6 {
Trial, 试验. v% ~, @; D$ {+ u. f4 f, a
Trial and error method, 试错法
2 d. |( K2 Q" ~! C2 w3 lTuning constant, 细调常数) x/ A, T2 u, O7 X" {
Two sided test, 双向检验
$ x. Q& H1 w9 @Two-stage least squares, 二阶最小平方
% v6 a6 T3 V' Y) j5 v( h- hTwo-stage sampling, 二阶段抽样
- \/ `+ Z( O$ z5 QTwo-tailed test, 双侧检验, W1 b, D3 j! ]" \7 S* t
Two-way analysis of variance, 双因素方差分析% x+ w2 p# Z5 l) c- X6 r& h
Two-way table, 双向表
* j. _+ ]! Y7 H* b4 LType I error, 一类错误/α错误
6 N! o* h* ] j7 F6 xType II error, 二类错误/β错误
( s3 x' l! B: |UMVU, 方差一致最小无偏估计简称. `, r9 S1 J6 o9 n0 l& \# c' G
Unbiased estimate, 无偏估计& g# n( m4 d) a! r4 T" j* G
Unconstrained nonlinear regression , 无约束非线性回归
# D) K0 E9 d+ B- x' ^6 v6 r, wUnequal subclass number, 不等次级组含量
( X8 \: w/ @2 n- N: l# {4 h4 hUngrouped data, 不分组资料
, C1 a& _# X7 z0 W- Q& D+ Z1 g' Z( WUniform coordinate, 均匀坐标: z0 H. _6 b" h0 m
Uniform distribution, 均匀分布
! X) h E$ a3 y: }- ]) o% i' {5 }: aUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
, b1 q1 V, M) A9 y4 Q [Unit, 单元& i' P& q$ D2 S) c- e
Unordered categories, 无序分类# W. @" t7 }7 b! G" P7 p# `3 V9 a
Upper limit, 上限: P* r# E) B4 f& {( v
Upward rank, 升秩: f# s: q& y7 L
Vague concept, 模糊概念
2 x( S8 B. Z0 o: F; t* kValidity, 有效性4 p& R0 z i9 Q6 D$ Y% s
VARCOMP (Variance component estimation), 方差元素估计
; @. z, ?; V$ f6 H, c! D2 u* `( lVariability, 变异性
* Z c- x7 E" U$ PVariable, 变量! l. Z) E" h( z3 }
Variance, 方差1 d: X; F0 c8 j" @2 Q. M. E- `
Variation, 变异
8 j3 v: j( t( f9 F6 S2 F6 [% D# kVarimax orthogonal rotation, 方差最大正交旋转" |7 d( ?& M3 x) j# T" ?
Volume of distribution, 容积, X( W0 o" Y& P
W test, W检验: s- \: D) A% G4 G9 w* P
Weibull distribution, 威布尔分布6 B* i# o8 R. `& l+ f7 J' d
Weight, 权数% c: r; \, B+ Z$ S# A# U( o! ]
Weighted Chi-square test, 加权卡方检验/Cochran检验4 G2 h; c: o0 q% I/ t' S/ P, N
Weighted linear regression method, 加权直线回归
4 K! b L! Z0 |5 z) ]) [Weighted mean, 加权平均数' N$ p+ Y; i) q" {5 h* `. t, M
Weighted mean square, 加权平均方差
# W5 f0 n5 |: K4 q( d+ tWeighted sum of square, 加权平方和
0 h; Y. K; O' e x& C; m+ FWeighting coefficient, 权重系数
3 h8 s: i: K5 k, i& }5 fWeighting method, 加权法
! n7 r/ @2 B1 a4 {# x @ M$ EW-estimation, W估计量
9 n) R, C2 V* L1 u. Z' \, J7 C8 q( xW-estimation of location, 位置W估计量
% A* F0 ], `5 iWidth, 宽度
& M( L) O6 z+ G; j! k1 x( C/ ?Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验; `. @' f# @' x
Wild point, 野点/狂点/ ^2 v) C, q' k
Wild value, 野值/狂值
' }0 F8 Q% Q/ k. g8 mWinsorized mean, 缩尾均值* z! t7 p, ~" w/ x' j# m
Withdraw, 失访 / N' S8 p) d( L7 {; g
Youden's index, 尤登指数9 b' `. `) C5 A! P5 Q# l' z
Z test, Z检验
% X, F2 R5 t# Z1 }& N- SZero correlation, 零相关
* k, G4 r+ Q8 U5 N) ~Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
