|
|
Absolute deviation, 绝对离差
. c7 x. m. ]1 ~! H6 J1 W2 _4 [; P4 f5 dAbsolute number, 绝对数! K6 s4 i8 k3 L. v
Absolute residuals, 绝对残差, \& Z" p$ x+ J, V
Acceleration array, 加速度立体阵' m6 N) ~0 ~. ]4 f! B, ~
Acceleration in an arbitrary direction, 任意方向上的加速度7 O( l3 L* f3 h0 S- {
Acceleration normal, 法向加速度+ \+ K% p% x/ v! h
Acceleration space dimension, 加速度空间的维数2 j) Y1 O- M4 S3 ^$ m
Acceleration tangential, 切向加速度
' O! ~& s: E- c, @4 x& U3 `' ?Acceleration vector, 加速度向量; K# d. S) z* Y
Acceptable hypothesis, 可接受假设0 a3 x" F9 \/ T' F0 [- }' P
Accumulation, 累积
1 X0 K, k e7 I2 U" D3 ^* KAccuracy, 准确度
9 E! u' a. ?& |Actual frequency, 实际频数) S; L6 z+ B, W4 T. L& e) J
Adaptive estimator, 自适应估计量- W' x0 X }. }9 z/ N1 q
Addition, 相加0 c4 `3 a1 F5 e
Addition theorem, 加法定理 ?( H/ _7 v' w; c3 ?
Additivity, 可加性
5 C: K' s b! k1 T, KAdjusted rate, 调整率
& t" C9 t# L% C' VAdjusted value, 校正值
' \. Y, M+ ?6 c! o; f' WAdmissible error, 容许误差
6 P# B, o2 L& U" R1 e- sAggregation, 聚集性
/ y* S; e: C, q# I4 o/ k0 k, tAlternative hypothesis, 备择假设6 Q. I1 V" _: o5 u1 M+ W) E
Among groups, 组间6 [1 R4 D" {0 C5 F7 M
Amounts, 总量
6 X- C- M0 N% M* e1 P! pAnalysis of correlation, 相关分析& ?. S: V4 r) a% O
Analysis of covariance, 协方差分析
' P/ |. t- K1 P# b, ~! f3 ?Analysis of regression, 回归分析
( |/ F4 _: C2 x* KAnalysis of time series, 时间序列分析1 V: n: X ]! |" b) @# D) @
Analysis of variance, 方差分析
3 w) c' L9 H; o2 B3 \& q6 GAngular transformation, 角转换
' c# N+ z1 ?( ^+ N! y" A9 m& pANOVA （analysis of variance）, 方差分析
* S& {% q4 @, y$ q: K& DANOVA Models, 方差分析模型
% |- ~/ e5 ]. V, SArcing, 弧/弧旋7 B# e6 h9 _* F# t6 P0 n
Arcsine transformation, 反正弦变换
, z) z9 o2 f6 |( I3 A5 jArea under the curve, 曲线面积
8 f2 k9 D4 |& ^# E. G( V# NAREG , 评估从一个时间点到下一个时间点回归相关时的误差
, U+ Q9 z$ i* K- iARIMA, 季节和非季节性单变量模型的极大似然估计
( r. o* C/ H/ i* ]5 P" K+ c aArithmetic grid paper, 算术格纸
/ c4 |' F* ?; U$ v$ zArithmetic mean, 算术平均数
4 q8 W; X5 [ f% y. RArrhenius relation, 艾恩尼斯关系3 x3 d, d' I: C6 L
Assessing fit, 拟合的评估4 ]- z7 T+ n6 @: j" ~1 Q/ `* ]
Associative laws, 结合律
& V9 p+ v8 G6 v2 a9 i) |/ E8 tAsymmetric distribution, 非对称分布1 C9 |5 Z. p- j2 L
Asymptotic bias, 渐近偏倚0 p) I. E5 |. {( c
Asymptotic efficiency, 渐近效率
2 O0 g% Y, @4 R5 T+ ]Asymptotic variance, 渐近方差0 ^3 p8 n- s% Z* ~/ R4 ?% D6 H* z5 K
Attributable risk, 归因危险度
3 `2 Z) g' |' [ |9 h1 bAttribute data, 属性资料
* [" ~0 Z" w6 z8 q3 Z7 A$ h5 rAttribution, 属性
) k0 z2 B6 d4 O! u/ |5 zAutocorrelation, 自相关
. h# D2 t1 E7 `: xAutocorrelation of residuals, 残差的自相关6 A, s, e8 W) C
Average, 平均数
2 H' f( L# P: n& H7 r/ B6 mAverage confidence interval length, 平均置信区间长度! D6 k1 X/ w6 J4 A+ y0 ?4 r4 _
Average growth rate, 平均增长率3 }8 t* t& a! t/ C5 s
Bar chart, 条形图" g2 Y" U; @% b3 m
Bar graph, 条形图
* s- P! {8 G3 u7 e/ JBase period, 基期. B! [& i1 o( a, Z0 K* W' N; z) Z
Bayes' theorem , Bayes定理
$ g& s4 B0 u/ L5 TBell-shaped curve, 钟形曲线
2 X# |( T) f4 z6 }* }5 ~- t2 MBernoulli distribution, 伯努力分布
% F6 N& w& d$ _; VBest-trim estimator, 最好切尾估计量
- x: l& x; v3 k4 YBias, 偏性1 g# y/ Q; F, d( b* G( B
Binary logistic regression, 二元逻辑斯蒂回归) p0 |; a; U' T8 H& }! _
Binomial distribution, 二项分布
/ l1 V. Y+ @6 s; y" f1 r3 e' C6 z& x! _( RBisquare, 双平方
) ?# B( g( X$ Y& eBivariate Correlate, 二变量相关
7 G) L* Y1 x! h) [0 fBivariate normal distribution, 双变量正态分布
+ n i5 ^) E$ ~" A5 cBivariate normal population, 双变量正态总体
9 u7 c* H6 k5 ~0 LBiweight interval, 双权区间
5 P) o6 u" i2 F) N% WBiweight M-estimator, 双权M估计量
4 d; H4 A: D* _: X; \* fBlock, 区组/配伍组
. n& f8 W) ]6 wBMDP(Biomedical computer programs), BMDP统计软件包0 \ O. W+ i% `# ^
Boxplots, 箱线图/箱尾图2 K+ p3 l! Q1 ^5 E1 _( P" _' v! ^
Breakdown bound, 崩溃界/崩溃点9 w& a' I1 h0 b+ i9 B Z/ h
Canonical correlation, 典型相关
9 ~0 @4 b s; PCaption, 纵标目8 G+ ?. K a* P6 z5 s) |
Case-control study, 病例对照研究
7 `- u. Q0 Z1 B! O0 f1 mCategorical variable, 分类变量' S6 b' V# o) p
Catenary, 悬链线
6 _) _, l% p8 P3 U' Q( `8 YCauchy distribution, 柯西分布: ^/ @5 g7 T/ u, \* x) j# \
Cause-and-effect relationship, 因果关系
! u3 d4 F2 H3 G& nCell, 单元) V7 ~6 }/ i8 f: O$ v
Censoring, 终检8 n/ c; p. z4 ]' G$ d
Center of symmetry, 对称中心7 b4 O, ~& Y* {: [& _$ d* g, J" Z, D
Centering and scaling, 中心化和定标
3 k4 f; N) i$ g7 I2 X: a* ^Central tendency, 集中趋势9 K# U% ]- U# D
Central value, 中心值
% O# w5 H! K. ^. m6 `' iCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
8 N$ J3 }- R3 z! c. kChance, 机遇
$ u: H0 U1 r! o z& ^Chance error, 随机误差$ |; L N& b7 A# T! l
Chance variable, 随机变量
1 t7 [$ d9 [4 i' cCharacteristic equation, 特征方程' A. j m- F. l" c: [; y0 ~
Characteristic root, 特征根% a$ p' s) M' Y. n
Characteristic vector, 特征向量2 T. @4 w9 w8 ~5 r
Chebshev criterion of fit, 拟合的切比雪夫准则5 R$ Y8 c" I2 ?+ B$ _/ r
Chernoff faces, 切尔诺夫脸谱图4 B+ C* ?: q4 E1 C! |1 y* w; f
Chi-square test, 卡方检验/χ2检验
0 D9 g7 n+ N; o2 x- oCholeskey decomposition, 乔洛斯基分解$ Z7 r# V+ }" e N& n1 ]
Circle chart, 圆图 ; n7 k, C* C6 p, e4 `4 B- y
Class interval, 组距
! |+ i1 A- X5 ]/ z0 M' kClass mid-value, 组中值2 {4 P k# d. O4 p9 |# F
Class upper limit, 组上限) m g; b0 G6 s% W ]
Classified variable, 分类变量
" L% |$ n+ P* \6 d! ~% gCluster analysis, 聚类分析- G) o4 a- f1 Z# e% i
Cluster sampling, 整群抽样* R; m8 E, ~3 d% |: X \+ B$ ~/ {
Code, 代码
+ h2 |+ n5 p! U! [Coded data, 编码数据
$ ?! Q/ s% V# L* e9 r' z7 K$ L- b8 ~Coding, 编码8 \# t( C* b) g$ d, ]
Coefficient of contingency, 列联系数
4 I3 ]; F8 [! b5 aCoefficient of determination, 决定系数
- t! [. S) j, }* ICoefficient of multiple correlation, 多重相关系数. c" @: X+ [/ \
Coefficient of partial correlation, 偏相关系数
q8 g z: d7 R! CCoefficient of production-moment correlation, 积差相关系数/ _( u% R3 w' x% d' r1 P) T6 e. k
Coefficient of rank correlation, 等级相关系数 ?; ?. c7 B" O
Coefficient of regression, 回归系数- i4 {; M6 h9 i# [ ?4 i5 G& R
Coefficient of skewness, 偏度系数( B9 Q' O: H7 @7 u1 e' A
Coefficient of variation, 变异系数
& G# Y- Y. P9 y6 V8 LCohort study, 队列研究
+ l, f5 Z/ N9 w7 Y+ JColumn, 列7 L9 E: j# L! A8 q" A% k
Column effect, 列效应$ [* j5 A2 a$ ?* S
Column factor, 列因素3 `4 Q, M5 P7 i' y+ F9 @5 X
Combination pool, 合并
" P6 Z0 Y" o0 ~. |) FCombinative table, 组合表
7 Y& P- W$ R# f7 ]( O( k/ @0 e, W) VCommon factor, 共性因子5 F" m6 c) P* [5 E* S2 t" L! l- P
Common regression coefficient, 公共回归系数 W- f" ]8 q6 f5 V5 p$ Z& O* [/ E& W! a
Common value, 共同值
/ h& B) [, l7 \: [ JCommon variance, 公共方差
8 ], v' `8 ]: k c, ^Common variation, 公共变异
$ T# l" s% z9 CCommunality variance, 共性方差" m" ~6 U! }8 ?6 G9 {- Z8 m( |
Comparability, 可比性
+ [) y3 x7 d% ~. j# b' v! HComparison of bathes, 批比较
0 b( g |* q* }' X \Comparison value, 比较值3 e5 O1 N2 B$ _# _$ M
Compartment model, 分部模型
+ P9 x& Q% ~3 G* n/ I3 P0 L" `Compassion, 伸缩
/ r- i' U$ o; w& O! Z/ B3 Y) {Complement of an event, 补事件
8 U2 X: t" i0 b! J: v7 jComplete association, 完全正相关6 W0 R3 R0 y8 Y& i
Complete dissociation, 完全不相关0 m- f( Z' u; _" P) T2 k5 ^! G9 h+ M
Complete statistics, 完备统计量/ Y B- }' l% s
Completely randomized design, 完全随机化设计; u. u% N4 k2 ^- C( A* }
Composite event, 联合事件
5 F g# o n5 ?$ ~( LComposite events, 复合事件
7 w" @2 b" C! S; {7 n8 iConcavity, 凹性: s: S S! Y" }
Conditional expectation, 条件期望+ w1 V& L6 J) M9 U" N4 m
Conditional likelihood, 条件似然
6 Z V* R/ u2 Q* hConditional probability, 条件概率) {2 v p8 h2 ^' z) ?8 D
Conditionally linear, 依条件线性( ]4 O1 v2 @% d4 j1 z$ U$ T# X( _
Confidence interval, 置信区间6 S5 F4 W% B5 [ U6 L2 L0 f- x
Confidence limit, 置信限! X/ g9 c% x+ u0 a& l4 ]. Z* i
Confidence lower limit, 置信下限4 K* \8 d, s7 [2 d$ A7 l
Confidence upper limit, 置信上限) m" F) \* f+ \, [
Confirmatory Factor Analysis , 验证性因子分析5 Y. ^1 O- ]( F" c9 V
Confirmatory research, 证实性实验研究. u: b) N4 Y$ f
Confounding factor, 混杂因素/ Z" T4 V2 X0 Z) B# p9 y6 W
Conjoint, 联合分析
, @: `! F0 A' S# j$ R1 p5 M! _Consistency, 相合性
: k3 j! I# l3 \7 D4 n @Consistency check, 一致性检验% U7 |* D) n/ J
Consistent asymptotically normal estimate, 相合渐近正态估计* S" Z) w; }& a. B
Consistent estimate, 相合估计
) k! M% Q. ~, |$ a4 t% c* fConstrained nonlinear regression, 受约束非线性回归" t% ~* B# v" k+ M
Constraint, 约束& A* Q: l. u" l8 X1 s! |
Contaminated distribution, 污染分布
2 k0 B# }' V- l- \4 m( sContaminated Gausssian, 污染高斯分布4 D: z$ x& C1 b: x7 ?2 G0 r
Contaminated normal distribution, 污染正态分布
- ?. _0 G- g! wContamination, 污染
/ c' n/ f1 k% _Contamination model, 污染模型
8 q L9 B7 g W( M" vContingency table, 列联表7 R' Q! y/ u2 A# M! l
Contour, 边界线
, C5 J [% K1 ?8 k) @Contribution rate, 贡献率
: L) _8 N9 r0 l6 j5 j2 OControl, 对照. A) L5 c. }& K6 {5 g* O+ Q- w1 e
Controlled experiments, 对照实验2 ?1 v( E+ P3 S( F$ Y3 y
Conventional depth, 常规深度* [3 J/ t" l1 {2 c* |! H
Convolution, 卷积2 v! o1 t! @+ V. r& Y8 B% B
Corrected factor, 校正因子
- ~' g8 z! ~% J8 I1 |6 GCorrected mean, 校正均值 O% F* ]/ N, }( M( i; ]
Correction coefficient, 校正系数
; n7 }0 Y: |, {' e Q( E% h7 z( a. KCorrectness, 正确性
3 V) J6 U3 B" T2 h7 _9 dCorrelation coefficient, 相关系数
& B& f6 O; e2 S; GCorrelation index, 相关指数
4 b0 A3 p, d- O7 y6 k' c! ZCorrespondence, 对应
) h% ]$ i( q( xCounting, 计数
' }% H0 n. H5 B# T3 RCounts, 计数/频数
! @: _! s& W7 m6 |+ P7 ^6 O+ n5 ECovariance, 协方差
) E7 D w0 t) t3 ^2 t7 c0 WCovariant, 共变 9 |0 Y O0 B" v8 D
Cox Regression, Cox回归, \+ C7 d2 R3 p
Criteria for fitting, 拟合准则4 Y+ B K0 m/ G8 o3 q% E! U) S8 V
Criteria of least squares, 最小二乘准则
1 ?2 b, @( x$ I4 VCritical ratio, 临界比0 R) i: o' R/ R ?
Critical region, 拒绝域
: Y+ ^1 \) f$ h: T& K7 k$ jCritical value, 临界值
+ W0 t4 K5 x3 \/ n2 uCross-over design, 交叉设计; C' n `8 \* o9 F5 ]; F( f" c7 l) Y
Cross-section analysis, 横断面分析1 y( }7 Y& l6 _( B- |* \
Cross-section survey, 横断面调查
3 |# n0 ~) u0 h8 \Crosstabs , 交叉表
8 a6 [: I, l% CCross-tabulation table, 复合表9 O& Y# d3 z8 {7 A
Cube root, 立方根( D0 K9 A) y( I F& N5 p& F8 @) e
Cumulative distribution function, 分布函数
+ X" O4 x3 g/ YCumulative probability, 累计概率
0 {* Z9 G8 A. n) g9 r' E) aCurvature, 曲率/弯曲( z- y5 T0 g/ M x& V. l, x+ o
Curvature, 曲率
* @5 D4 Q1 l r/ a1 `2 hCurve fit , 曲线拟和
+ G5 }0 z$ C* `9 ZCurve fitting, 曲线拟合
. h ^) C7 A" |Curvilinear regression, 曲线回归
, n1 y* B3 c! P1 `: m2 r9 kCurvilinear relation, 曲线关系2 o" _7 P" l2 G
Cut-and-try method, 尝试法6 l6 d' ?- h" x# Y3 Y o/ N+ f
Cycle, 周期
1 P# l8 o6 P: `( Q2 nCyclist, 周期性
+ o o C( t% |0 G+ T2 b jD test, D检验
0 @+ X& T* i# c# \* ^Data acquisition, 资料收集
, n) P$ Y( v, w$ a. c. MData bank, 数据库9 e: J9 i' M' D. j
Data capacity, 数据容量
4 y: k+ ?( s+ J5 y# ?/ @Data deficiencies, 数据缺乏1 E) A/ T, L1 R1 a$ @4 _+ a
Data handling, 数据处理
( H$ y" [/ g) ]Data manipulation, 数据处理1 z/ c, I) h4 E `/ d
Data processing, 数据处理
: d) n4 H6 y. h! E7 N0 i0 uData reduction, 数据缩减& |; j9 x1 c* O: Z& R( _
Data set, 数据集( k: E$ v# O! X4 n8 m2 T2 W
Data sources, 数据来源
4 f' n, X4 d! e# qData transformation, 数据变换5 K, g1 G' T4 ~; j4 Q( m
Data validity, 数据有效性
5 `2 O$ H) q/ e- [4 S1 f& pData-in, 数据输入" o( k0 k/ B7 B! W; Q
Data-out, 数据输出
; u! w$ f; E8 @: MDead time, 停滞期; {; [; f6 L$ E3 @. M
Degree of freedom, 自由度
& V8 I3 `0 k2 r, _+ J( X. {' sDegree of precision, 精密度5 g( w" d- N4 ~9 p- Z- ?
Degree of reliability, 可靠性程度
7 m6 T0 \* U- xDegression, 递减
" c( R/ f3 a1 a4 v. WDensity function, 密度函数! I4 `$ y* h+ ~
Density of data points, 数据点的密度
( x: V2 g3 S; h% k0 t8 lDependent variable, 应变量/依变量/因变量
& P6 n" ?& l/ J/ [Dependent variable, 因变量) p& J' t/ `* q3 D5 h! e
Depth, 深度
+ O& M# [: `' y$ c2 HDerivative matrix, 导数矩阵& G/ U! C3 o* L: N" s. S) R
Derivative-free methods, 无导数方法% t5 X" e0 i9 ]
Design, 设计3 z; ~& k) D$ o! X2 r( R( ^. l: d
Determinacy, 确定性5 L4 M" K% e0 E/ p4 \
Determinant, 行列式
+ l; E5 t2 ?$ `# A0 |, nDeterminant, 决定因素# D$ B. L" L0 _
Deviation, 离差
C" c& g8 e! r0 U6 N, Y, }5 v3 i1 bDeviation from average, 离均差
$ s6 H a6 |1 S$ ?& g5 I) ~Diagnostic plot, 诊断图$ ]' q# t1 N8 r8 o s
Dichotomous variable, 二分变量
5 S9 ^3 Q. ~2 F5 l- c; I6 F" }Differential equation, 微分方程! g( F p; c5 p
Direct standardization, 直接标准化法
$ ~! r1 ^ I j1 Q: c5 BDiscrete variable, 离散型变量% K8 N! G: j y! W3 m, T
DISCRIMINANT, 判断
! {3 ~5 I' s8 i6 z2 h2 U7 {& q$ u9 h: MDiscriminant analysis, 判别分析
6 E. Z1 c0 ^. z0 H ~1 NDiscriminant coefficient, 判别系数; C0 ^+ V% z4 G& R# K
Discriminant function, 判别值$ h: M0 p6 ?! G
Dispersion, 散布/分散度
1 D$ v) {$ C6 Z8 XDisproportional, 不成比例的
& t+ \, }* l" |$ `% |Disproportionate sub-class numbers, 不成比例次级组含量
# g& a3 b |& ~" m1 `5 I+ nDistribution free, 分布无关性/免分布0 c! F2 E% L2 `/ O% M7 p
Distribution shape, 分布形状! v9 j0 o. M { ?5 U
Distribution-free method, 任意分布法
, _3 ?$ N5 X0 \$ G, ]' o6 D; B ]Distributive laws, 分配律
$ h' C. A' J, ?2 mDisturbance, 随机扰动项9 m7 L+ y5 D0 F+ }+ x5 f
Dose response curve, 剂量反应曲线
4 W! _/ S4 V& Q) U' }& i" L2 WDouble blind method, 双盲法6 {2 c5 S/ H" b) ?) k
Double blind trial, 双盲试验9 l" @+ d6 i, C
Double exponential distribution, 双指数分布7 G+ v% V8 I( W0 I
Double logarithmic, 双对数; g! {( F; t% `7 ?% m
Downward rank, 降秩
( h, j( P v5 m: O/ N. PDual-space plot, 对偶空间图
5 p4 D9 \6 s* M' o) UDUD, 无导数方法
* T# T/ F" L5 ~3 G3 W$ aDuncan's new multiple range method, 新复极差法/Duncan新法
- m* c/ a; T5 J4 U6 E/ sEffect, 实验效应- {' ]+ |( {- r& I( N' s
Eigenvalue, 特征值" D& K7 B- B5 f. H
Eigenvector, 特征向量
% H! Z5 P$ ~* r3 [Ellipse, 椭圆
" i7 u B9 {" Z* vEmpirical distribution, 经验分布 u* j7 c4 _9 d$ j Z/ G2 m" v. U
Empirical probability, 经验概率单位
5 r( J- o9 l5 G- t1 A! hEnumeration data, 计数资料7 B7 p% T. p5 V% Q' C
Equal sun-class number, 相等次级组含量3 |0 S. w+ ^8 z3 d) M/ q3 K
Equally likely, 等可能
" |. M4 i9 O( zEquivariance, 同变性
# T9 A+ R; g# Z$ A: B% S3 m5 RError, 误差/错误" D5 k9 i! Q4 Q* i" B
Error of estimate, 估计误差$ H8 S1 q# M K3 h5 @7 N* g( k
Error type I, 第一类错误
( L& O+ `0 J! H' X. O* F Y) O5 Y0 VError type II, 第二类错误$ `: w' x. r7 T' _6 N
Estimand, 被估量3 }! l1 L$ j* t$ I z
Estimated error mean squares, 估计误差均方
& p1 `, P5 f. u; M! A# R/ @Estimated error sum of squares, 估计误差平方和1 `2 p G( r$ C3 S
Euclidean distance, 欧式距离
9 `7 a/ n+ l1 `Event, 事件* ~9 c7 K/ D+ M$ o$ J, ^
Event, 事件
# a3 ]( x: R, p1 `# u7 hExceptional data point, 异常数据点
( M$ G) B' J: _6 {% A5 n) wExpectation plane, 期望平面2 m# G; u$ D# \# N
Expectation surface, 期望曲面
4 \. o/ d( v# i5 u1 e( iExpected values, 期望值5 ]' a. S: A" |4 Z1 j& @
Experiment, 实验- N. y5 z+ M" q- F
Experimental sampling, 试验抽样 C8 n4 w6 L m% r
Experimental unit, 试验单位* d/ M& l: H7 A/ H( m( @6 C' v
Explanatory variable, 说明变量 M# P' h' e6 |
Exploratory data analysis, 探索性数据分析
% q7 X( W" E- rExplore Summarize, 探索-摘要
/ k7 @- d* z3 RExponential curve, 指数曲线( Q9 Z" O! P' ^9 ~7 s* B" v
Exponential growth, 指数式增长4 T5 ?. | A, ?- r1 Z
EXSMOOTH, 指数平滑方法 2 q- k0 o9 [8 ^) P/ f
Extended fit, 扩充拟合( q# y" J8 H2 |. s1 T: U) x
Extra parameter, 附加参数
4 Q" ?: Z% e1 @& s, aExtrapolation, 外推法
0 V9 f h1 @; |) H( _Extreme observation, 末端观测值, L# M* y9 A+ z6 w. A
Extremes, 极端值/极值
. S9 l/ R" Q& f- D( ZF distribution, F分布
' n, k; ?, m. w0 HF test, F检验
4 h. L8 M0 b6 h1 O' Z, a; ]4 lFactor, 因素/因子. }* O% v, ^4 B5 N
Factor analysis, 因子分析
5 o0 A' n+ S r& j+ u; ]8 AFactor Analysis, 因子分析
- C& M& l$ y |1 P! T0 w2 zFactor score, 因子得分 3 z5 }! m1 N% J0 P" A s
Factorial, 阶乘+ G" F- u! _+ e. u
Factorial design, 析因试验设计
( P" L0 ], V' U% @' w& x2 U, SFalse negative, 假阴性
7 i* e, q, F- V B; LFalse negative error, 假阴性错误
1 o/ ~( Q$ V3 l hFamily of distributions, 分布族- D) x3 F. O# U: @8 n0 ^( P
Family of estimators, 估计量族7 Q6 g) B8 s) J7 @3 }) Y$ i3 f u
Fanning, 扇面
/ {9 }! M3 d8 oFatality rate, 病死率
+ Y1 Z' I3 _" M+ _9 cField investigation, 现场调查; C! H3 V4 H5 F2 m! H9 C
Field survey, 现场调查
) z/ t3 b( t* u8 pFinite population, 有限总体
2 P; n6 i, ]5 i8 \7 ?Finite-sample, 有限样本, O" @; t" s- C, F! j( x
First derivative, 一阶导数& c; H, j# {7 ^$ k0 H8 |* Z
First principal component, 第一主成分! c* y5 W& `7 i8 A: V" N
First quartile, 第一四分位数. j* e0 V5 ?" h* n
Fisher information, 费雪信息量
}& v' S f- JFitted value, 拟合值
* ]2 ]0 C% b+ j+ V8 PFitting a curve, 曲线拟合
( [% d# x0 }4 Y( B, p! GFixed base, 定基/ V% e k4 B; H' V2 `" O x
Fluctuation, 随机起伏# [7 B. U3 A( J
Forecast, 预测
' e/ f' K4 N VFour fold table, 四格表
2 R7 r# }; S1 w5 x! {1 Q, w8 N; v7 KFourth, 四分点
" Q: I9 C4 i: u% g- w% B% @1 OFraction blow, 左侧比率! u% k, f9 s: ^! m
Fractional error, 相对误差: j( }2 O2 f' ~- {# h
Frequency, 频率% a# H& u! F5 N" S) y% ~
Frequency polygon, 频数多边图
. x( f- {" X; H7 L, d$ k0 NFrontier point, 界限点
9 T! Y/ ~: U$ e3 MFunction relationship, 泛函关系0 E# d: a& p* a
Gamma distribution, 伽玛分布( \4 b5 E3 R5 z5 ~* h+ }- ~
Gauss increment, 高斯增量6 }' Q5 o1 X. J: ~6 ~4 m' Z
Gaussian distribution, 高斯分布/正态分布+ J! O7 m5 m0 E/ M- U" Z& B4 B& N
Gauss-Newton increment, 高斯-牛顿增量& f6 O6 K% U+ Y9 w+ [% f: K
General census, 全面普查/ P3 D1 t# g$ s; ~- J }6 R
GENLOG (Generalized liner models), 广义线性模型
4 l2 Q! F4 ^1 T# y" ?Geometric mean, 几何平均数/ V1 `. ?! R1 S7 d, ^) E
Gini's mean difference, 基尼均差
( a0 L% z0 a* j h0 hGLM (General liner models), 一般线性模型
6 X; D% \# U; l, c' F% TGoodness of fit, 拟和优度/配合度
l& M/ T) L( G3 b! dGradient of determinant, 行列式的梯度2 C* ]4 ] t, e X2 {) A
Graeco-Latin square, 希腊拉丁方: X$ L1 G6 _2 s# O! I+ Q
Grand mean, 总均值 x/ Z% I2 X& Q* L3 h6 L0 @" P* m
Gross errors, 重大错误
& A# F+ d/ D( y0 MGross-error sensitivity, 大错敏感度4 J8 [* ]# o( a/ u
Group averages, 分组平均3 V4 Q5 E( B$ W- v+ t
Grouped data, 分组资料0 d3 y5 }$ ?& }& K; J
Guessed mean, 假定平均数% G. C& u; t+ S% o8 w# i1 r
Half-life, 半衰期
* K; Z0 B7 S* {9 n6 pHampel M-estimators, 汉佩尔M估计量
5 _; B* G2 r5 E( A/ M! A* SHappenstance, 偶然事件
) E, G7 ^8 h* L: m4 ?- QHarmonic mean, 调和均数+ j8 V) w/ S9 n$ |, \
Hazard function, 风险均数: X! S# \- b9 A0 D4 j
Hazard rate, 风险率
2 A' `6 R7 U" s3 T' x3 }Heading, 标目 4 p( G; v# }; ]3 j/ e& H p {
Heavy-tailed distribution, 重尾分布
- D# s( P8 x* ^4 m$ j$ ~Hessian array, 海森立体阵
7 _( W2 p4 g) D9 b. S+ lHeterogeneity, 不同质
( I1 x! n; L1 F( L, Z' \Heterogeneity of variance, 方差不齐
' ~5 J+ k+ m) t1 |4 IHierarchical classification, 组内分组
( T+ M, f% n3 JHierarchical clustering method, 系统聚类法
5 s% B: n0 S, @9 J0 s" iHigh-leverage point, 高杠杆率点4 A1 c- p2 L4 n. \+ x+ a
HILOGLINEAR, 多维列联表的层次对数线性模型8 a% Q) u% N3 |+ m; m9 K
Hinge, 折叶点! k9 R/ \, l1 L2 M$ v3 y
Histogram, 直方图. r2 K5 l9 [7 w. f$ _) N
Historical cohort study, 历史性队列研究 ' {( v; R) j5 A. p- ]7 w; _
Holes, 空洞
0 \3 M3 y' L) O9 AHOMALS, 多重响应分析7 X% F; H0 D. q" [, _7 i7 S6 h
Homogeneity of variance, 方差齐性
( b$ o; V! b1 w+ ?& t0 iHomogeneity test, 齐性检验
7 c- S: g# m1 I( F3 e7 b" {Huber M-estimators, 休伯M估计量
, f, k$ |- T1 h/ g1 Y' e( nHyperbola, 双曲线6 @2 R: X1 A* q, `) q
Hypothesis testing, 假设检验1 z4 ]$ G; m3 ?' P( S* T9 W1 F: }
Hypothetical universe, 假设总体
8 F, N+ [" g: U/ A8 IImpossible event, 不可能事件
& ~/ G' O6 Y. U6 T" I* ]7 xIndependence, 独立性
* J7 x( y Z8 R oIndependent variable, 自变量0 Y+ E, c. ]! B
Index, 指标/指数6 `4 m" I: [0 y5 `' B
Indirect standardization, 间接标准化法+ j- `# ^$ @' g8 G, V" o
Individual, 个体
2 x- y/ Q; Q4 ~% WInference band, 推断带5 l$ _" W/ |, G+ `$ X. R
Infinite population, 无限总体/ b& n! }; C% w0 v. ?- t
Infinitely great, 无穷大- N' W/ \& i9 O$ D" u8 P1 G6 J
Infinitely small, 无穷小
% N4 ^) r, l9 Q0 q3 kInfluence curve, 影响曲线+ {7 q! M, p1 Z* n4 z2 d* N5 X
Information capacity, 信息容量. O, |7 y$ F3 Y2 {+ l# n7 l
Initial condition, 初始条件
4 O$ g0 T) O* m6 `* R: Q6 ZInitial estimate, 初始估计值* G- j7 x; T/ [8 ]
Initial level, 最初水平
* l1 R' q9 x+ \' V9 T. V& M9 bInteraction, 交互作用
$ |- ]3 t: w# i7 q6 ^, l, vInteraction terms, 交互作用项2 k( Y* R4 T$ w4 H! ?6 f: U
Intercept, 截距/ d0 {1 U! m( S6 [( w7 A" p
Interpolation, 内插法
9 E9 R& \" x$ [- MInterquartile range, 四分位距
' _8 W' R. k b7 M- WInterval estimation, 区间估计
- z' t6 Y3 s; s% @" rIntervals of equal probability, 等概率区间
; d" T& D! i0 X4 R8 ?8 RIntrinsic curvature, 固有曲率; f H: h' f! a7 L
Invariance, 不变性9 h9 z+ R! m% L1 C y1 e# w, E
Inverse matrix, 逆矩阵
" o0 Q( I) `4 t% P7 l- DInverse probability, 逆概率
; L: l' K4 ^/ M0 d% T. f1 GInverse sine transformation, 反正弦变换( F+ \. a+ b" v7 X, D& v
Iteration, 迭代
. ?. L d- u3 p+ vJacobian determinant, 雅可比行列式! K! ?7 `- P1 t: b& M4 s) I/ }2 r0 O
Joint distribution function, 分布函数7 e g" S! a ~- s) L( D, w- ?, x
Joint probability, 联合概率1 t5 J. U5 w& U, P# S4 a
Joint probability distribution, 联合概率分布 x* T* z& H H4 T( W" ^$ Q6 c5 {
K means method, 逐步聚类法1 L" c& H* b! K! f* [6 R
Kaplan-Meier, 评估事件的时间长度
" {# j) }/ M. [ B/ ]1 k4 A- N% W5 Z, f$ XKaplan-Merier chart, Kaplan-Merier图3 |. b1 G+ q& _0 s4 v5 y5 c% @
Kendall's rank correlation, Kendall等级相关+ R n" j8 \0 e3 M5 r9 U$ w- s
Kinetic, 动力学; f7 e/ q5 l Q
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
& q7 o1 ?" {9 ~. R1 zKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 ?6 x& N6 k+ Z/ U8 H# W
Kurtosis, 峰度0 l# x# [, b' ], Q) |9 c
Lack of fit, 失拟# H/ l- i3 j9 V+ X# c+ v: Z0 n2 A
Ladder of powers, 幂阶梯; U h! M. ~% ^* F) s$ A
Lag, 滞后1 @; c! d. Z9 k. h6 M! C# Q
Large sample, 大样本9 C( H3 @5 e: u4 D: R3 T. {# |
Large sample test, 大样本检验) |$ \2 |0 E9 s
Latin square, 拉丁方7 w* Z( D, e% q, I0 A2 W8 K
Latin square design, 拉丁方设计$ N9 C, M# Y; Q" o! o
Leakage, 泄漏, m* z6 d! C3 [: G! T
Least favorable configuration, 最不利构形1 S- D: }2 V5 O% ?
Least favorable distribution, 最不利分布
2 {! h T% V4 ILeast significant difference, 最小显著差法
3 Q1 T* F9 b. E$ P9 e7 H- [0 dLeast square method, 最小二乘法
1 c1 ]8 T2 o- b# {- v0 L! i" CLeast-absolute-residuals estimates, 最小绝对残差估计
{2 a! H5 }( PLeast-absolute-residuals fit, 最小绝对残差拟合
2 k! U4 @( F) Q H$ F7 SLeast-absolute-residuals line, 最小绝对残差线
: e' E( |, ~! P' `7 M- M' \Legend, 图例
6 c/ z2 D7 U2 y" u- XL-estimator, L估计量. x0 r( ?6 c+ f
L-estimator of location, 位置L估计量
0 {6 ~! M, S! b5 e4 vL-estimator of scale, 尺度L估计量6 \6 W1 ]4 C; E) r9 P, `3 ]( @
Level, 水平1 o+ ^' i( E+ j$ I* s
Life expectance, 预期期望寿命
' T" A8 p7 l: x* J8 CLife table, 寿命表
7 m- E" P5 h6 e/ F( Z; iLife table method, 生命表法
" _- e- P1 N6 y2 oLight-tailed distribution, 轻尾分布$ A) u+ F+ n0 r; z" e
Likelihood function, 似然函数# K' k' X' _+ S* Q; m
Likelihood ratio, 似然比
/ M4 f7 F. C: b" t1 P/ hline graph, 线图
0 l$ ], G* l4 d- v3 E% ELinear correlation, 直线相关0 y5 z% g: n$ U/ C
Linear equation, 线性方程9 Y: Y% c, d* p+ M' ?, y# f, V
Linear programming, 线性规划6 w3 [+ }8 g& o* y) ?8 T+ U
Linear regression, 直线回归
$ X0 R, b% I( M/ ?" `Linear Regression, 线性回归
* N1 ^- n6 w* s! ?Linear trend, 线性趋势
! J! o4 \+ x# }% i& s% ^Loading, 载荷
! S- U7 f, a7 w4 @Location and scale equivariance, 位置尺度同变性1 V$ S i( o/ |% T( o) q
Location equivariance, 位置同变性; b/ W# o: K% X
Location invariance, 位置不变性* v/ S5 o |# p2 L7 } q5 }
Location scale family, 位置尺度族1 {' j i( ^* E& n
Log rank test, 时序检验
; r: V2 z% E2 Z/ p# E4 W. Z! i# a8 HLogarithmic curve, 对数曲线
- L4 p Z( \! F9 A* vLogarithmic normal distribution, 对数正态分布' Z9 Z9 E) ~ U% c* a6 D" O6 G
Logarithmic scale, 对数尺度
5 ^* w: Y0 c- C/ e5 pLogarithmic transformation, 对数变换' C2 \" W; I6 S8 d( {' M
Logic check, 逻辑检查
8 A: C' i* ~: }( O5 ^Logistic distribution, 逻辑斯特分布0 p, t! ?0 [5 i9 ]( T- p, P
Logit transformation, Logit转换
! n: q: r# U7 J1 X, ~ lLOGLINEAR, 多维列联表通用模型
" t( C7 F' n% Y7 J5 ]& }Lognormal distribution, 对数正态分布" l$ p: n, ]8 S: u- M0 {
Lost function, 损失函数
/ K. N4 y: }( u9 j' s1 ?Low correlation, 低度相关 H4 d% q* V- z3 V' A/ N- |2 W
Lower limit, 下限) w7 i4 l* S% A
Lowest-attained variance, 最小可达方差
3 a1 J. ^+ b1 d+ F6 W9 o& \LSD, 最小显著差法的简称; ^4 H* D5 B8 A+ K3 j% q5 Z- j
Lurking variable, 潜在变量- ]: v8 {% P! H4 v1 O3 v
Main effect, 主效应5 G6 _, W' ~+ @
Major heading, 主辞标目. D) F+ W7 }" `* K
Marginal density function, 边缘密度函数
* d- f5 ?. O7 d' h$ v o- bMarginal probability, 边缘概率
! m! C; ]3 [$ hMarginal probability distribution, 边缘概率分布8 m$ U3 V9 m) A) e- `- @3 n- D1 G* @4 c5 D
Matched data, 配对资料. n* }3 T* _) E5 ]& A. K" O y
Matched distribution, 匹配过分布
# W5 Y* E3 P8 p0 |Matching of distribution, 分布的匹配
* Q0 z5 F, c+ I' j0 l( T+ QMatching of transformation, 变换的匹配% n0 Z3 C0 V l- a& U
Mathematical expectation, 数学期望5 b4 P+ Y* z! G1 `
Mathematical model, 数学模型0 O3 N2 j$ ]5 @- Y+ ^9 O
Maximum L-estimator, 极大极小L 估计量$ h, ~9 P/ H% A; k" y
Maximum likelihood method, 最大似然法
- | s% F% q0 N/ [Mean, 均数
8 E2 r- I3 \0 \2 V! Q; A$ N# l& IMean squares between groups, 组间均方# x' v+ f1 W" i6 ?! i/ h- H
Mean squares within group, 组内均方) m% K# j* b$ C6 {! f+ d
Means (Compare means), 均值-均值比较9 p2 Z0 `1 }2 g. a& `( l1 U
Median, 中位数4 k& H1 a' h0 K. e" N' p9 p
Median effective dose, 半数效量 z4 B+ }6 ]. S. }0 X; p% l
Median lethal dose, 半数致死量/ R6 A- p$ c, k5 h% B( r4 E3 \8 l9 K
Median polish, 中位数平滑
6 s+ W C! r, N9 ~Median test, 中位数检验
2 o8 t& V7 K0 O) F" R9 I$ lMinimal sufficient statistic, 最小充分统计量+ m7 ?1 t9 M' [( `6 p+ a, Y9 o/ m
Minimum distance estimation, 最小距离估计! A) g3 M! D$ A- t
Minimum effective dose, 最小有效量
+ m9 |, y3 _7 r! K: U0 g7 G* AMinimum lethal dose, 最小致死量6 J8 v) }4 E: C# z5 b
Minimum variance estimator, 最小方差估计量2 x1 _ j# E! m: D( |/ d: `
MINITAB, 统计软件包( B2 v( C( R) \2 H
Minor heading, 宾词标目5 ^! g4 s e) [+ ?
Missing data, 缺失值1 j- _ e' v4 o; f
Model specification, 模型的确定4 M( ?7 W6 A% m( o( Z; u+ j
Modeling Statistics , 模型统计5 a. g3 M$ a3 }; j
Models for outliers, 离群值模型5 ^" Y4 b3 ~ i; t
Modifying the model, 模型的修正
, z& [$ A, x$ \5 ^Modulus of continuity, 连续性模4 m! Y3 {+ P/ ^6 R
Morbidity, 发病率 6 V3 \( Q2 X4 W
Most favorable configuration, 最有利构形* ]3 y7 y" I7 u/ _8 C$ H* B- h
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
# T9 a4 S( F/ P1 H7 g' UMultinomial Logistic Regression , 多项逻辑斯蒂回归* s$ {4 I" M* N
Multiple comparison, 多重比较7 u, V- j6 D" i* w Y
Multiple correlation , 复相关$ Y3 m8 d- o" g+ `6 _6 ~: ?+ a
Multiple covariance, 多元协方差5 m# D% C. M6 ~! u5 Z
Multiple linear regression, 多元线性回归
" J5 d7 ~% m7 SMultiple response , 多重选项
. _1 ^1 t9 H z, j8 d. t: b) n7 }Multiple solutions, 多解
1 I% N; C0 Q% m" ? @Multiplication theorem, 乘法定理
) l4 e1 I P) H3 ^% N5 [# Q2 dMultiresponse, 多元响应/ G. Y5 U1 x- y; }, N. c
Multi-stage sampling, 多阶段抽样
: R/ F" z: J; i/ W5 _1 {: g" ~; UMultivariate T distribution, 多元T分布7 n8 f5 d% \7 k( N9 Y) l: S, G6 [
Mutual exclusive, 互不相容/ W* i x& a9 J; l/ P6 k4 H" x
Mutual independence, 互相独立5 j" t1 k6 {1 K5 B! A1 E8 u
Natural boundary, 自然边界, h5 a4 b9 n$ \0 a0 L0 c9 U
Natural dead, 自然死亡. I1 Y! Z0 w/ }! n E W
Natural zero, 自然零; i9 Z" ?; G2 l; q. s
Negative correlation, 负相关
6 O/ S* v2 J! m4 K9 Z+ ANegative linear correlation, 负线性相关% n8 P: O6 z- G y& H3 l$ M
Negatively skewed, 负偏' i& M# q$ ~" |) R
Newman-Keuls method, q检验# Z* Y; m: W" w1 J6 `/ x7 @* }0 q
NK method, q检验. G1 i" x1 J$ r/ w. _1 P3 ~0 p
No statistical significance, 无统计意义' c( O- ]0 r: v8 C! E0 b6 L9 Y8 M
Nominal variable, 名义变量
& f3 s ]+ X, INonconstancy of variability, 变异的非定常性! L5 D H2 o6 F- N
Nonlinear regression, 非线性相关
- e( F1 y8 v% n6 p Q% dNonparametric statistics, 非参数统计
4 W* ]! F7 M2 m' h1 NNonparametric test, 非参数检验& Y7 d: k( j% d
Nonparametric tests, 非参数检验
8 P9 y5 G3 Q, A0 V) \9 \Normal deviate, 正态离差
+ V( Z, \- L- f* xNormal distribution, 正态分布( W+ [0 s8 o. ^# S4 ]- |5 H" @- t
Normal equation, 正规方程组
5 e3 Q+ Q: J; _. \2 j8 ^Normal ranges, 正常范围" p0 Z6 [' U! {' j
Normal value, 正常值! n* o+ s) p# }, m
Nuisance parameter, 多余参数/讨厌参数* n* I3 O# t6 a v7 H6 S1 k7 T" k
Null hypothesis, 无效假设
. ?. l1 S1 n% D$ o& A/ R8 v- R7 N' ~Numerical variable, 数值变量
7 `' r" g% {% J4 R r7 }Objective function, 目标函数7 A7 T- g1 {' @# x: ~( x/ g' R
Observation unit, 观察单位
8 Y3 I/ I( o7 y" dObserved value, 观察值9 O* B5 ]. H$ f) ]& }; R
One sided test, 单侧检验
8 c# N1 O$ c7 x+ VOne-way analysis of variance, 单因素方差分析
$ m, @7 J |- o( zOneway ANOVA , 单因素方差分析
9 i" i+ Q+ L4 ROpen sequential trial, 开放型序贯设计
! M5 Q! E, t8 L8 y) [& O& ?Optrim, 优切尾
V1 {: I" q- kOptrim efficiency, 优切尾效率# @" \! \* v% }; N! _+ J
Order statistics, 顺序统计量
; g3 G2 h- X* t2 S2 WOrdered categories, 有序分类
* _8 j! V( r9 F4 [* U/ f5 `Ordinal logistic regression , 序数逻辑斯蒂回归
; d) _" h0 {4 H7 VOrdinal variable, 有序变量' Y# j# |: T) T5 m, G
Orthogonal basis, 正交基0 Z$ t4 D4 k. a
Orthogonal design, 正交试验设计
/ r' g3 K1 n% O' V- x5 ^Orthogonality conditions, 正交条件
p( N0 i* D6 j7 t. f# g$ ?. }4 c2 WORTHOPLAN, 正交设计 ) a6 t% ^* D( d& U. y0 k
Outlier cutoffs, 离群值截断点
+ w% C# N4 U# ?, S" e: MOutliers, 极端值7 G' r. S, \6 e& `5 o
OVERALS , 多组变量的非线性正规相关 + F! Y f( [$ S8 m
Overshoot, 迭代过度7 i+ M* a% A' Q+ v
Paired design, 配对设计
\% S2 T$ |. }; q cPaired sample, 配对样本% A0 `$ G6 B* `$ v0 Z$ \3 h
Pairwise slopes, 成对斜率) `7 N/ ~5 U% `6 @+ @2 V4 G
Parabola, 抛物线- p% `2 c1 V. g8 U5 l
Parallel tests, 平行试验8 k+ h" E. l, y& C, {
Parameter, 参数: |+ _4 P4 E/ t# q$ K2 I: T
Parametric statistics, 参数统计7 z- D& F o- n- S. B) k
Parametric test, 参数检验
+ I% O7 W4 N7 i4 BPartial correlation, 偏相关
- k4 n4 O; R* g* o- J: }. D8 ?5 |Partial regression, 偏回归
8 j; D2 J+ D3 ^; jPartial sorting, 偏排序0 {! `+ E2 Y8 r3 N5 T0 q
Partials residuals, 偏残差, H3 S# Q3 G2 [
Pattern, 模式
( C* J. I! R( H2 RPearson curves, 皮尔逊曲线
5 f y( Z" {# J* }1 cPeeling, 退层
, e3 M! V% P% U. }" t6 RPercent bar graph, 百分条形图" |* |: S# X1 w3 N
Percentage, 百分比* L& z5 r0 E/ ]# }4 Z
Percentile, 百分位数5 v- ~8 Y7 o5 J- b C
Percentile curves, 百分位曲线, H5 Q( U3 K; q4 }9 z
Periodicity, 周期性
( A2 n& `0 L+ Z6 I3 z& OPermutation, 排列
5 f! A# Q3 \5 `4 NP-estimator, P估计量: A' `! ^. g+ m, L& o
Pie graph, 饼图
9 x5 G6 w, m9 E9 a+ ]0 YPitman estimator, 皮特曼估计量* R) N- G- z# T9 _7 |! R
Pivot, 枢轴量
# i s! @0 @2 l0 iPlanar, 平坦
& D d8 d, D2 j9 B, `: V+ K& kPlanar assumption, 平面的假设0 B, h3 M. G R% C
PLANCARDS, 生成试验的计划卡8 w& K: \0 p5 }
Point estimation, 点估计- z. T9 j' a. U: H; x
Poisson distribution, 泊松分布
% F3 B7 x5 N' r% x0 BPolishing, 平滑7 s! D- S! m' S2 y% w: w1 }2 f8 q0 e5 n
Polled standard deviation, 合并标准差
( X" Q- _1 ~7 G1 U4 LPolled variance, 合并方差
. E- [/ H& G6 }1 p8 z/ LPolygon, 多边图
\* Q! q% e. g+ w+ HPolynomial, 多项式
0 p+ x0 D, a% e* |, jPolynomial curve, 多项式曲线
; x( p, c) \& ?6 W! PPopulation, 总体
0 T/ W4 G6 `: m7 f1 zPopulation attributable risk, 人群归因危险度* F% R' M: h( F( D
Positive correlation, 正相关: G/ V' U+ y( L5 a5 |
Positively skewed, 正偏) R" z' c+ b: e+ K! l1 p- ^. `
Posterior distribution, 后验分布4 p0 e& ]2 n9 b: ^# [' k
Power of a test, 检验效能6 F, w# v2 B' V$ |% C0 S7 r7 C/ Z
Precision, 精密度
8 g2 t) v0 l- b, o- fPredicted value, 预测值
6 s. C! F2 m9 I1 z+ oPreliminary analysis, 预备性分析: U Z* Q; N9 M2 ~2 j1 x
Principal component analysis, 主成分分析
* E- Z1 A: L2 U4 k5 P7 B jPrior distribution, 先验分布
+ k6 J$ t& W5 p3 G: m. p8 @Prior probability, 先验概率1 w9 W* @& h# G8 ^, I# U
Probabilistic model, 概率模型! x& ^: ?/ N7 x8 i" g6 N
probability, 概率2 j- m7 v- B" _8 e8 a$ K' w- n
Probability density, 概率密度
( a, D2 Z" T/ w7 I* uProduct moment, 乘积矩/协方差
, z4 u* t ~' K" T) K* ?- \, e- zProfile trace, 截面迹图9 G5 ~* M) C9 | q( d7 K8 O: G
Proportion, 比/构成比" G+ J5 i6 s' |
Proportion allocation in stratified random sampling, 按比例分层随机抽样* T: n, F j: ^6 ]9 E1 U' X( ^/ _
Proportionate, 成比例
( @* Q4 _) P' S, fProportionate sub-class numbers, 成比例次级组含量
& ~; i e+ D# ~/ L# z5 GProspective study, 前瞻性调查% K( q! O6 F) B) i7 t
Proximities, 亲近性 ) l- _8 r( b& H/ f$ L
Pseudo F test, 近似F检验
& _) l# u0 R( D. l+ N: A" L2 H8 iPseudo model, 近似模型7 e/ T9 r2 C5 J H4 q+ p% F
Pseudosigma, 伪标准差7 {, [4 ~# q" ^
Purposive sampling, 有目的抽样, m% l& [+ C6 U7 ~& |5 C( e( b
QR decomposition, QR分解5 |9 @1 }8 ~" g+ Q$ g- |4 g5 Q0 n
Quadratic approximation, 二次近似8 S6 Y0 A0 s; _3 T' B
Qualitative classification, 属性分类
" O- e; u- i; aQualitative method, 定性方法. q9 _+ W, F0 I. t) v( d3 B! P
Quantile-quantile plot, 分位数-分位数图/Q-Q图3 l; A8 A3 r. P1 ^
Quantitative analysis, 定量分析
4 x. ?- b/ u! p3 e! ?Quartile, 四分位数2 w* ]2 v n2 {& x7 H$ }
Quick Cluster, 快速聚类& P/ ?3 W4 T; @9 Y: B8 G
Radix sort, 基数排序( C4 K, f/ |0 \5 p1 A
Random allocation, 随机化分组
) W5 b5 {2 Y' p6 \Random blocks design, 随机区组设计
( B: |3 ]4 j" D& DRandom event, 随机事件. i/ Z3 b K. m* f! e
Randomization, 随机化% v3 M Y& D5 Z3 f' Y& K# s
Range, 极差/全距% m" [! {6 p" ]) p; \% ^ l o
Rank correlation, 等级相关
1 a1 K3 i! a' ?4 FRank sum test, 秩和检验0 R" g$ Z) o" K$ K
Rank test, 秩检验5 `# `# \( d, N; m
Ranked data, 等级资料
0 J9 s! u {( \5 X* GRate, 比率* ?$ ~' N% _- k) q
Ratio, 比例
1 _) b3 y q" T; i9 B# R1 r( g! }Raw data, 原始资料
" N8 J2 Y& q5 s+ Y/ {3 WRaw residual, 原始残差
. @$ y4 L+ W6 e* Y8 s5 E/ QRayleigh's test, 雷氏检验# ?' Z* C' ]4 d3 e
Rayleigh's Z, 雷氏Z值
% a- b7 u0 F( g' v# @+ {4 T2 ~, I2 {Reciprocal, 倒数: R: }. m! ^, H" x8 X1 l
Reciprocal transformation, 倒数变换
8 b/ `' j. z7 c; d& ]Recording, 记录' G1 O* e/ M/ J: `8 Z: v- B' g
Redescending estimators, 回降估计量
3 ^0 Q! Q9 M) Q* U. S2 D$ `Reducing dimensions, 降维/ I, F) O/ i3 X4 w/ c
Re-expression, 重新表达
2 e; g' p$ z* c, T' U: u9 zReference set, 标准组
' ]9 q; e- j2 x8 A2 r: GRegion of acceptance, 接受域) L' x1 _) r0 r; A+ v% m
Regression coefficient, 回归系数1 B3 Z0 n- W. y$ W* m r7 p, W. k
Regression sum of square, 回归平方和
1 I9 n9 F1 ~" @2 i6 ^/ g+ DRejection point, 拒绝点
; b+ a8 d' u- S P* i# bRelative dispersion, 相对离散度
' [5 |% T' L# I) I1 x, ARelative number, 相对数
8 q0 \9 Y- g" mReliability, 可靠性 G4 Z M" j1 N+ L$ _0 X6 j
Reparametrization, 重新设置参数
% g3 d2 r4 k# W: z9 i; h5 ]* JReplication, 重复
; h9 N/ s! Q6 gReport Summaries, 报告摘要
( d0 ]8 ^ j( p8 P1 w& RResidual sum of square, 剩余平方和" E; l3 G8 v- }! a/ E0 A/ s
Resistance, 耐抗性
/ C6 P& Y7 i, _/ F0 YResistant line, 耐抗线) G4 ?. h/ L: z' s- J( I
Resistant technique, 耐抗技术
@( X4 G, Q3 @R-estimator of location, 位置R估计量
4 ]# W& `3 \5 c) ?& {R-estimator of scale, 尺度R估计量. b: w/ n" P |6 O/ y: y" X( A
Retrospective study, 回顾性调查: m0 {+ b( A8 X( z: a
Ridge trace, 岭迹! I$ l* g( Z% i* t- g _% ^9 k" h
Ridit analysis, Ridit分析: v; S8 F# \" d, M
Rotation, 旋转
- i3 D+ R% f8 \/ p. Y: iRounding, 舍入, r- M6 o% A! O" Q ?
Row, 行
& r0 Z( a# X7 `5 l# p+ lRow effects, 行效应
- q( M$ Z) s7 {7 F) @Row factor, 行因素/ Q7 l& B% M& j" L* }7 G
RXC table, RXC表
. k: ]+ K7 `" W: i, O* O( sSample, 样本: _) T, M, z7 y2 p0 \
Sample regression coefficient, 样本回归系数
9 | g( z6 ]% y R, m8 wSample size, 样本量, ]7 I$ D" K- k+ R' S5 b
Sample standard deviation, 样本标准差
! {" T# T4 c: i. i3 M9 E' O/ Y; OSampling error, 抽样误差0 z, p7 |$ W# @+ s* P' y- |
SAS(Statistical analysis system ), SAS统计软件包
' c1 K) P$ x# P( @+ SScale, 尺度/量表/ C/ X6 G( S- c `
Scatter diagram, 散点图
4 H- Y0 O& B& X& QSchematic plot, 示意图/简图
1 a! u- q) M, q' C: a- KScore test, 计分检验
. N& ~+ x5 ?; ?% Z( W7 _! `9 ^Screening, 筛检7 Z" c5 A- J$ h* h" y1 |) r: F
SEASON, 季节分析
. B7 g2 s7 D5 V7 ]( C) }, hSecond derivative, 二阶导数
$ f+ ?. A, m6 k. c. mSecond principal component, 第二主成分
" Z; X. `% O# CSEM (Structural equation modeling), 结构化方程模型
4 [4 I' A D- o4 rSemi-logarithmic graph, 半对数图
" S0 S' A; f. n) ^$ p' DSemi-logarithmic paper, 半对数格纸
& L: G0 Z- f2 B" T6 Y" KSensitivity curve, 敏感度曲线8 n" a" h9 C, \% e. i
Sequential analysis, 贯序分析
% Z X7 P$ N' G8 a% O+ e3 }5 T. P& YSequential data set, 顺序数据集
' @* P2 |1 ~- E# Y" ~( VSequential design, 贯序设计( j2 X B6 U1 f# k/ I' S+ B! T
Sequential method, 贯序法5 |6 M. y" M9 [7 Q2 {
Sequential test, 贯序检验法
7 P( D8 {: F* p4 x/ s+ b& T) _Serial tests, 系列试验, n2 L7 ]0 p+ s' e( l
Short-cut method, 简捷法 ! u. G3 u; c) l {% T5 \: k' L
Sigmoid curve, S形曲线! R# Z ~. p5 F( [1 |: {$ Q% U! h, M
Sign function, 正负号函数, O/ d3 g& h' m; a' ^
Sign test, 符号检验
+ r7 o2 r$ k! L5 X, bSigned rank, 符号秩
; C* {- M7 _0 ]8 V( D- aSignificance test, 显著性检验
5 [8 Y# s0 P; u) {Significant figure, 有效数字. K% b! z0 d) g7 {+ Z
Simple cluster sampling, 简单整群抽样7 C$ S( J' x w; b- h* E
Simple correlation, 简单相关
9 {9 I4 A3 h+ [4 A3 @Simple random sampling, 简单随机抽样5 e3 n9 t. o0 O
Simple regression, 简单回归
4 D% g6 h$ l$ u5 o. asimple table, 简单表
, i! E# p2 R. ?0 ]2 n0 m5 M: NSine estimator, 正弦估计量" _ N( B' k" H% n$ ~2 C. l
Single-valued estimate, 单值估计0 ]7 G9 B; r) \/ \8 U
Singular matrix, 奇异矩阵
. `. [4 `. ~4 z9 y- RSkewed distribution, 偏斜分布
# H( K/ Q* i: u# `Skewness, 偏度) T9 z5 s6 d# Y# D" h' p8 h
Slash distribution, 斜线分布
2 o8 c. B0 @6 e9 r% RSlope, 斜率
7 o( o- a* _, @Smirnov test, 斯米尔诺夫检验
& r% C5 [; B. e5 h0 T9 W$ ?Source of variation, 变异来源8 |; c5 Q' d+ D0 l4 [& B2 [: t- N% a& v
Spearman rank correlation, 斯皮尔曼等级相关1 f* i' d0 L; M4 l
Specific factor, 特殊因子( Z1 v0 v2 L. g3 J; N0 `8 d# X8 y
Specific factor variance, 特殊因子方差
6 A. S9 M6 F: O/ Y2 n# HSpectra , 频谱) B' L7 B; d9 Q/ o' {2 |4 x
Spherical distribution, 球型正态分布
" b9 a8 @* e% k; H) P0 wSpread, 展布
* n. g9 P2 y% Z4 sSPSS(Statistical package for the social science), SPSS统计软件包
( [0 r) f0 e* z$ wSpurious correlation, 假性相关
8 @) x4 K' q9 k. ~2 `Square root transformation, 平方根变换
3 s/ K6 V0 Y2 w, y' d3 k# HStabilizing variance, 稳定方差2 M3 T6 E/ U/ Z9 h$ n! @
Standard deviation, 标准差8 m1 p' B" e7 A1 F3 Z0 x8 k
Standard error, 标准误
0 r& k: Y1 A1 e) sStandard error of difference, 差别的标准误
- X/ b# x& F# X; m9 b1 gStandard error of estimate, 标准估计误差$ ?. c. n. ~8 u5 J
Standard error of rate, 率的标准误5 G; `4 I, y+ Q
Standard normal distribution, 标准正态分布. o. K, p# c/ t* f I# j1 v
Standardization, 标准化( ^. n6 d8 `. e
Starting value, 起始值
, [% w& B8 `2 m9 G5 `Statistic, 统计量- |, E6 r" O& b/ D: v% r$ d
Statistical control, 统计控制
" ~! a& H' F$ C1 r8 j( X7 tStatistical graph, 统计图! Y6 R } U# q1 y" {( u# s |
Statistical inference, 统计推断7 Q# A* H3 R$ T0 ~! |
Statistical table, 统计表6 C; S* k0 z2 ^% F! M
Steepest descent, 最速下降法5 E- Z/ N; W9 o9 s( K) J
Stem and leaf display, 茎叶图: T; r# T# Z A! {
Step factor, 步长因子& o' g* U% \& E* G# ?& M2 K8 k8 ]% j# [
Stepwise regression, 逐步回归! o6 k+ C8 Z' {0 V! s
Storage, 存
9 Y3 W" z7 T0 |; _- f3 C6 x' q1 }' Z! hStrata, 层（复数）
5 x* b' s2 w9 E2 z) qStratified sampling, 分层抽样* c, s) a1 `/ f+ } u8 N. N
Stratified sampling, 分层抽样
: i. s# ?) P3 e7 gStrength, 强度
. S$ p+ i; \2 g8 {' a" P0 H9 ]Stringency, 严密性
N# O6 A' ], `1 G! d' D- kStructural relationship, 结构关系
9 p8 M) r" I# ~9 mStudentized residual, 学生化残差/t化残差+ ?2 d6 A# @, ~: v
Sub-class numbers, 次级组含量' U2 [: }7 q& c, L! ?
Subdividing, 分割/ w5 S- b R2 ~# ^0 m
Sufficient statistic, 充分统计量( K7 `' L% l% u+ l" y- j
Sum of products, 积和6 y- a, f" c$ q' d) g, `- x; m
Sum of squares, 离差平方和8 M" o8 s) p0 W( G! t& j# p
Sum of squares about regression, 回归平方和5 D# ?- g ?, I9 u; \" M2 ]
Sum of squares between groups, 组间平方和3 a# Q6 `4 `4 I/ |! c
Sum of squares of partial regression, 偏回归平方和; f4 \8 E& W' V- _. l& L8 n9 }+ ?' k
Sure event, 必然事件
6 q; y2 C$ C) F7 T$ [0 f# ASurvey, 调查
$ `( f& P$ a: e1 k& W* E8 s5 F$ jSurvival, 生存分析
/ h% g4 g9 J3 `( wSurvival rate, 生存率
( v/ `" N% K/ |Suspended root gram, 悬吊根图
d$ d' |; q' `' `Symmetry, 对称1 G' J* ? K. X4 ^
Systematic error, 系统误差* u) g- E" T1 o" j; n9 P% Q
Systematic sampling, 系统抽样! o& b3 d6 h0 V/ B
Tags, 标签
- N# I! A" K6 X$ w$ ?% HTail area, 尾部面积' A/ n- I% S0 O+ S. E
Tail length, 尾长
( p: q* R; S( e0 s" i# i5 hTail weight, 尾重
) g" R( h, M1 w7 l- a) M' gTangent line, 切线# |( G Q2 |* J0 t$ P
Target distribution, 目标分布: t$ J1 r8 [6 G4 W% j$ {: K
Taylor series, 泰勒级数( k& [5 f/ P! F0 l2 c4 j
Tendency of dispersion, 离散趋势
0 m# s0 j& ?; j4 K4 kTesting of hypotheses, 假设检验) V, ^2 w- i; x: w/ Z% {% V# N3 T
Theoretical frequency, 理论频数
( f8 S: O4 ]" n. LTime series, 时间序列
7 i- ^+ P! u N! v; z" CTolerance interval, 容忍区间
$ n, u3 O5 ~! c) P! FTolerance lower limit, 容忍下限) y) Z* C9 V m' s9 d* k
Tolerance upper limit, 容忍上限8 t* {% M8 k8 z9 w7 Q( a" |
Torsion, 扰率
$ _% q, t) v* m1 ?1 I) B4 Y( STotal sum of square, 总平方和! T9 K* T8 `" m; W* T- B, v! b
Total variation, 总变异) |; [6 u# m" K8 j' Z2 B/ i
Transformation, 转换: p) a' S- l+ K
Treatment, 处理, J, k' ]4 H) [" f1 E8 D2 _9 x
Trend, 趋势7 V, S5 f4 v: ]6 h9 l, Y
Trend of percentage, 百分比趋势% c3 L7 J) `* E8 d
Trial, 试验( J$ H4 J# ~" Q! z
Trial and error method, 试错法
& \6 I0 |2 _, Y) H( hTuning constant, 细调常数 v# i, [: c! L, o0 g2 Q# h
Two sided test, 双向检验
" j. {, d" z. [( |Two-stage least squares, 二阶最小平方' D0 I9 X2 L9 R
Two-stage sampling, 二阶段抽样3 n8 J( f# }. m+ y3 h; l; e) U
Two-tailed test, 双侧检验4 M( j9 _6 j: n* s/ G3 ~
Two-way analysis of variance, 双因素方差分析
; e+ H F/ r5 A% D8 QTwo-way table, 双向表
" _% b, E/ O |* D7 f% ]Type I error, 一类错误/α错误2 I2 [6 v# t) D
Type II error, 二类错误/β错误8 h' N0 H2 Q. w* J9 p, }# I
UMVU, 方差一致最小无偏估计简称
5 Q" z5 j& P$ J4 A/ P" wUnbiased estimate, 无偏估计0 u+ [2 q2 q. ? J2 b
Unconstrained nonlinear regression , 无约束非线性回归
$ |, K# F+ N9 r2 b& m, mUnequal subclass number, 不等次级组含量/ I% i' V0 v* K }% H# Y! j
Ungrouped data, 不分组资料' r5 }, ]& F& y$ y6 e4 {$ O* [! t
Uniform coordinate, 均匀坐标- Y. P: g* q0 U2 _* x" C: D
Uniform distribution, 均匀分布
' E$ ?! N5 ]6 x3 V" ~Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
9 s! Y5 m; @3 }# h, l4 NUnit, 单元
% I* l8 q' T# _Unordered categories, 无序分类
- H: O* z8 ]7 mUpper limit, 上限
3 a: F7 l: X1 Z0 b3 JUpward rank, 升秩* y) J# _8 G; L8 A9 K K
Vague concept, 模糊概念: V- u, m6 w0 Q; H- w M
Validity, 有效性4 P& f1 Y* s# ]5 j
VARCOMP (Variance component estimation), 方差元素估计7 r1 _& N2 b0 e$ h' G
Variability, 变异性# \2 v* e% B2 e4 j( v# m
Variable, 变量3 ]' w' Z: k% e4 g7 e% o( |
Variance, 方差6 a, F ^# ^+ z1 O* a, ~, W
Variation, 变异+ j5 H' m* k7 x9 P# v
Varimax orthogonal rotation, 方差最大正交旋转+ u0 ] R" f8 s' y3 K
Volume of distribution, 容积) J( N( ~$ B- B! V; \5 l
W test, W检验
' z0 c7 U; l' WWeibull distribution, 威布尔分布
2 u0 Z' I" U3 \9 C: O9 Q* `4 rWeight, 权数* v& D, U I( V( t2 c" u
Weighted Chi-square test, 加权卡方检验/Cochran检验
0 W$ `/ r% j1 h& o; y5 S9 aWeighted linear regression method, 加权直线回归
9 Q8 K" D& q( y1 [Weighted mean, 加权平均数7 ^+ U9 }! l; R5 v
Weighted mean square, 加权平均方差; T% a3 ]% I8 p9 z$ J6 v& P% c
Weighted sum of square, 加权平方和
) V5 Y; _3 F! C1 \$ _6 kWeighting coefficient, 权重系数& g0 a, Z. P2 ]* E% @/ I5 d3 t
Weighting method, 加权法
8 p3 z5 H) C4 |. N# b3 i+ x6 xW-estimation, W估计量
/ ^3 v9 ~0 Q& M- W3 t7 Q }. ZW-estimation of location, 位置W估计量
5 g- @# ]% K& y$ OWidth, 宽度! B2 [, ?5 ^( x1 l i5 q5 {
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
: a- Z0 ~; d$ x1 e8 JWild point, 野点/狂点1 g t+ M2 o7 p0 w
Wild value, 野值/狂值6 t- }& k4 H( v r
Winsorized mean, 缩尾均值, B( z' a: S J9 o+ j
Withdraw, 失访
7 @" S' M; M) n6 Y( |Youden's index, 尤登指数
! ` ]+ \% R+ K( `! b8 lZ test, Z检验
1 ]- A( w, g$ D0 NZero correlation, 零相关
* E; G+ S, {8 I- t: {Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
