|
|
Absolute deviation, 绝对离差" J: q$ e4 t% R
Absolute number, 绝对数6 |7 Z3 G) ?9 }' \2 v2 c
Absolute residuals, 绝对残差
7 o2 D; m3 N" w) y( K3 ~/ w" |( MAcceleration array, 加速度立体阵8 T) x- v, z4 W3 [4 `0 j
Acceleration in an arbitrary direction, 任意方向上的加速度, e* X! ^2 L$ I( _0 `* k$ W
Acceleration normal, 法向加速度: u m& f# F" y1 V" ~
Acceleration space dimension, 加速度空间的维数
+ @2 \' u5 j: M9 w6 _3 [* D+ rAcceleration tangential, 切向加速度7 V8 j2 s- H& J' a/ g
Acceleration vector, 加速度向量
2 E) Y: S& p4 L+ r' _2 [Acceptable hypothesis, 可接受假设
. p. o3 H0 }( u% LAccumulation, 累积( }* H) @& Y0 {0 o. A
Accuracy, 准确度- C, h2 S8 t8 [
Actual frequency, 实际频数
! i' v: S, d* h$ h0 t& s6 @Adaptive estimator, 自适应估计量
/ s8 [ P6 f; _Addition, 相加
2 v- ?9 f5 F: p9 G& [+ Q) F4 cAddition theorem, 加法定理1 A. x8 S1 A& q, n6 u( M! _
Additivity, 可加性
. B" ^5 V. z0 u# M2 k |& G+ X- @Adjusted rate, 调整率8 x8 \6 U) \/ c/ t
Adjusted value, 校正值
# x7 B* `1 a) XAdmissible error, 容许误差, j% I' B0 Y y8 z8 B0 A$ P7 R
Aggregation, 聚集性+ v- _. a% `% \! e
Alternative hypothesis, 备择假设
' a* p; ~- X8 vAmong groups, 组间
2 U3 [& _8 c. S* N: @ g4 DAmounts, 总量1 f' x- B% a3 a: ]! x
Analysis of correlation, 相关分析
* c! n. p, I. t D6 G; O6 k5 @& C: DAnalysis of covariance, 协方差分析) G+ f+ ^7 _( y% q6 J
Analysis of regression, 回归分析3 K8 v4 \4 w2 @1 w' j* v8 S
Analysis of time series, 时间序列分析
3 H, P# H6 @" B, {8 j0 p1 F( D7 jAnalysis of variance, 方差分析
+ z% k y5 d5 Y$ s5 w2 u7 @# ]- CAngular transformation, 角转换; i5 U# h$ F5 N; Z% c
ANOVA （analysis of variance）, 方差分析
( n4 H/ H3 e, Z- q* @ANOVA Models, 方差分析模型0 V; G4 L! O& h: W2 c* J
Arcing, 弧/弧旋# x2 ?" Q; \0 T) v4 D$ {( Z
Arcsine transformation, 反正弦变换. u; ~/ B6 X; a. Q6 D# x( O
Area under the curve, 曲线面积* ~9 l b) c: z4 B: {" u c
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 ; b3 W- L' ?2 o" |& z: C! l- Q
ARIMA, 季节和非季节性单变量模型的极大似然估计
9 D8 l8 H2 a" E) m. CArithmetic grid paper, 算术格纸
+ {) N, X. @% X9 vArithmetic mean, 算术平均数4 F8 ~# k6 x) w1 G
Arrhenius relation, 艾恩尼斯关系3 r) h7 Z9 I( X0 e+ _+ D" N/ I
Assessing fit, 拟合的评估2 B3 g1 \, g% S. Y6 q) x3 S7 g; [
Associative laws, 结合律
& {3 w' x* v: `8 z( x2 t/ w. \Asymmetric distribution, 非对称分布
# u8 M4 P* {3 J9 lAsymptotic bias, 渐近偏倚* B5 p4 m( O |1 L" D
Asymptotic efficiency, 渐近效率; K7 `( j( n2 q g; m3 x$ f/ E
Asymptotic variance, 渐近方差
* ]$ A3 k6 W+ ~" Q! f: ZAttributable risk, 归因危险度1 I5 `( X$ s4 [1 A% ^8 G; H
Attribute data, 属性资料6 o9 N/ d$ t! E$ O+ i
Attribution, 属性4 E' e# y* g ?6 b& E
Autocorrelation, 自相关- A+ Z# N6 t% v
Autocorrelation of residuals, 残差的自相关
7 j7 m6 l1 e3 R" h+ VAverage, 平均数- \! J; ^! {4 P: G2 l8 |4 A8 A
Average confidence interval length, 平均置信区间长度% b0 p6 Q6 F2 A' V! L
Average growth rate, 平均增长率
5 s& A( Q0 B% ?& t9 g& o. nBar chart, 条形图. P8 r* w5 t( s$ Z$ [0 e' P
Bar graph, 条形图- C V% I2 K" H& L3 Z4 ?4 {2 o
Base period, 基期: K& x) o! O4 r' }
Bayes' theorem , Bayes定理
( ]+ e, l( V3 G/ nBell-shaped curve, 钟形曲线
' i. v% b1 Y- H# Q7 G5 eBernoulli distribution, 伯努力分布
( F; u: q" Y; c8 F8 ^Best-trim estimator, 最好切尾估计量0 C1 N8 d5 v# c9 |/ `, O
Bias, 偏性& F3 V( W9 X1 S# y9 C7 {
Binary logistic regression, 二元逻辑斯蒂回归
( g' e5 |! w( h& B9 `$ IBinomial distribution, 二项分布
8 k5 c1 }2 {# ^: o- RBisquare, 双平方
2 R' p# J- E! h. ~, X9 b- I# k0 IBivariate Correlate, 二变量相关) }' B9 G$ t3 l$ ~" e3 V
Bivariate normal distribution, 双变量正态分布
% i0 d; {, A! U/ H% L5 dBivariate normal population, 双变量正态总体+ r0 Y. q, N8 p$ V8 y5 |( i
Biweight interval, 双权区间" P p' z4 ~! x) ?5 m# e
Biweight M-estimator, 双权M估计量. _. ~8 g$ k' h; S
Block, 区组/配伍组
6 @4 g' l7 ?* l7 F9 K1 xBMDP(Biomedical computer programs), BMDP统计软件包. b* V: t" u% B0 H+ H$ n3 _( ]
Boxplots, 箱线图/箱尾图' D2 H& ~4 u- ?5 b" c
Breakdown bound, 崩溃界/崩溃点
5 U5 I5 z- s3 [2 F* _Canonical correlation, 典型相关2 M l3 \5 {6 L
Caption, 纵标目
/ q8 A( g8 A: a( wCase-control study, 病例对照研究
0 Z4 d8 V0 J6 |& ^; h1 MCategorical variable, 分类变量
8 f3 x( i1 w) X' ]1 x* e9 }" QCatenary, 悬链线
- Q8 B, w+ A% S, ^- D0 U vCauchy distribution, 柯西分布
. \3 O' L" R, X) q+ n6 qCause-and-effect relationship, 因果关系
/ ]" g$ x# o: C! yCell, 单元5 R( N6 s3 R) i$ V. D+ J* O
Censoring, 终检
; k: o+ _7 {6 N! iCenter of symmetry, 对称中心
6 E( t6 _9 ?$ q$ B3 n0 KCentering and scaling, 中心化和定标
" ^9 A i! w. f4 j( GCentral tendency, 集中趋势
' I9 c* G n. I I9 DCentral value, 中心值
7 F& M, L6 v4 H+ ]+ B8 p+ }CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测* o: H2 }5 [9 Z0 B, M
Chance, 机遇
" t0 i3 F% z5 d7 f2 z# E9 l" QChance error, 随机误差+ @; Q* Y( e, |$ U. M
Chance variable, 随机变量5 m$ Z! r/ R$ E% @" E! B: m' Q; w3 k+ T
Characteristic equation, 特征方程
, j9 Z: D- I3 U5 q5 R2 SCharacteristic root, 特征根( G- `) l9 h3 \ T3 P' i
Characteristic vector, 特征向量1 D/ K- b% D+ U8 Q
Chebshev criterion of fit, 拟合的切比雪夫准则& I! h. C* \+ S
Chernoff faces, 切尔诺夫脸谱图5 k; P6 b* ]+ B Y+ U! S1 W
Chi-square test, 卡方检验/χ2检验
* |! z: ?1 r) y# C `9 t$ VCholeskey decomposition, 乔洛斯基分解
! L6 x: x9 R* D& SCircle chart, 圆图 & q6 X# I) p3 e$ I1 |+ {
Class interval, 组距
9 ]7 v% @4 D. m; t# E' ZClass mid-value, 组中值7 J h# i( f" G5 T% Q
Class upper limit, 组上限
: ?( ?# v4 c. X- k/ RClassified variable, 分类变量4 s4 Y4 C6 z% I
Cluster analysis, 聚类分析
9 @' P. N# e- ~( D: ]& B: mCluster sampling, 整群抽样2 E: I6 z9 I. d8 \7 `
Code, 代码' s- d. a- d2 Y; K1 e- I
Coded data, 编码数据7 o$ e+ f. E( j8 q; k$ t
Coding, 编码# k7 v- x( S( |- F
Coefficient of contingency, 列联系数. W" y# c `4 E, T0 L* O; w& h
Coefficient of determination, 决定系数9 [/ {: P; k, x' \3 l' o
Coefficient of multiple correlation, 多重相关系数0 ?" |) i/ C7 \0 \ b
Coefficient of partial correlation, 偏相关系数
5 r8 o* n; a2 b5 n4 l& KCoefficient of production-moment correlation, 积差相关系数
& S+ q3 j2 ~( b0 q, t; r: y* kCoefficient of rank correlation, 等级相关系数; o+ T2 z. p* I/ N; i) V9 N
Coefficient of regression, 回归系数
: E; }% f' d8 k3 L: g: s+ Q4 w) WCoefficient of skewness, 偏度系数
5 s9 z3 |9 ^+ ]% j uCoefficient of variation, 变异系数9 U8 e5 Y8 i2 M( \4 K; x6 V4 p8 d
Cohort study, 队列研究& c# c& |6 }$ |5 X* T) J2 x* A/ y
Column, 列6 t: \* _4 K& c) r
Column effect, 列效应
- O" Q2 j* O0 v( W: IColumn factor, 列因素
* c" ~8 T. z6 f/ e! n; n9 C2 {Combination pool, 合并
; g, j- K( D2 o" NCombinative table, 组合表% W! ?0 { m! m1 v/ I
Common factor, 共性因子/ a) _9 k! Y- V
Common regression coefficient, 公共回归系数6 V- J, ~. e% i/ K1 ^0 L2 W) w! t
Common value, 共同值+ Q6 }$ W3 c/ B, _5 `2 ^" I8 ], {/ B
Common variance, 公共方差! _' \% r4 }+ W j5 ?
Common variation, 公共变异3 ]. y6 B( D, m3 X m) b- s
Communality variance, 共性方差
c" Y; u, S3 c: t8 g9 F9 e! s2 KComparability, 可比性
- @* e( g4 R: p7 v0 n, c* t& }) YComparison of bathes, 批比较
6 k8 E/ b x0 F0 K8 qComparison value, 比较值; ~, F1 u% h0 \) V9 j1 l$ m
Compartment model, 分部模型
7 P' j" ]8 Q% k9 K; lCompassion, 伸缩& @, p% | c7 X' C2 B$ x! E
Complement of an event, 补事件
' X5 L. a- r2 ~Complete association, 完全正相关
3 Z L' Z, e& a8 e- ]- nComplete dissociation, 完全不相关( o* d8 }# ^( t0 J6 K
Complete statistics, 完备统计量
$ c1 r/ { Y4 R0 u, R0 nCompletely randomized design, 完全随机化设计( H, i4 H: h: y0 q2 J( H
Composite event, 联合事件
: B2 I. L3 x" u6 k' f3 eComposite events, 复合事件
& U+ @! h4 D- o. D @Concavity, 凹性
5 B9 _6 L9 N; @( p$ i6 d* J7 kConditional expectation, 条件期望
+ s; |# w1 G3 B" n' p3 G) r8 BConditional likelihood, 条件似然
, W) a1 M) T& f6 {Conditional probability, 条件概率
?$ Z4 }% h0 V$ m" R9 [Conditionally linear, 依条件线性. w* U- s p: G4 W/ ?/ i% [8 k
Confidence interval, 置信区间
4 V, t {$ C4 j! D1 q7 OConfidence limit, 置信限
! t2 F% q. O" q$ TConfidence lower limit, 置信下限7 X! o$ u# E1 y- a6 t- s
Confidence upper limit, 置信上限
9 K! e1 }0 F6 g7 U( r8 ?Confirmatory Factor Analysis , 验证性因子分析
2 b% v1 H0 J! Y1 nConfirmatory research, 证实性实验研究) Z, O( d& O1 M' ^
Confounding factor, 混杂因素9 w( B- z7 f6 D \. F' @
Conjoint, 联合分析% \0 ?: C, b5 h1 o: A8 E
Consistency, 相合性( p3 f9 T4 }/ w9 s
Consistency check, 一致性检验
* _ r2 U" \8 n- O, P1 ]! O. gConsistent asymptotically normal estimate, 相合渐近正态估计
|9 \9 A9 `+ M+ p: VConsistent estimate, 相合估计8 m/ m8 A6 u8 K; x
Constrained nonlinear regression, 受约束非线性回归; R+ f3 ]% L5 l
Constraint, 约束
3 ^# V3 t4 G, G: bContaminated distribution, 污染分布+ G+ u4 v' s0 ]1 g
Contaminated Gausssian, 污染高斯分布8 C" [% y" i( A2 N% g4 {/ ~4 a
Contaminated normal distribution, 污染正态分布
. Q( |$ m8 ?- Z; X* r6 q9 |Contamination, 污染
) B6 x6 d; E G, B' Z/ O/ rContamination model, 污染模型. ?" d" \! n6 C. |% j
Contingency table, 列联表! @4 K6 S! [ r
Contour, 边界线& c# q! I/ o1 @* X6 U
Contribution rate, 贡献率$ m# N) [& P* H) Y1 E
Control, 对照7 f: {4 A: ~% A0 \
Controlled experiments, 对照实验
z0 Z& S/ `) i3 l, M1 w. AConventional depth, 常规深度
3 i+ i( B- i. }4 U' y7 ?$ @Convolution, 卷积: N' }) L- k3 Q, ?& C& f7 B+ h: D
Corrected factor, 校正因子
( L5 j$ Y' z$ ?- {# HCorrected mean, 校正均值
% @+ [1 J# I3 H' O1 @6 ?Correction coefficient, 校正系数$ L; G" T7 I6 n0 p0 g! k" }
Correctness, 正确性
9 Q# O" V" H( d9 o9 Q) oCorrelation coefficient, 相关系数
5 ?; ]$ u: x/ [( n- ?, F2 xCorrelation index, 相关指数
; `) p1 l9 v2 n7 ? B2 bCorrespondence, 对应
3 W- l' z0 L- w7 iCounting, 计数
* `9 c5 ~ h1 ^/ ^, `Counts, 计数/频数
) o+ }6 l( z# O6 D& \3 o) LCovariance, 协方差8 |+ y8 ]& ?4 C+ `
Covariant, 共变 % Y& S+ |0 }" _% U* k2 N. b& O
Cox Regression, Cox回归3 r- _/ d! ~$ W; d" s) K; Y: E) L2 c
Criteria for fitting, 拟合准则
$ F/ H; N; X, a& i9 Q6 CCriteria of least squares, 最小二乘准则
0 j3 ]1 x+ Y% Z- M% V( hCritical ratio, 临界比
- r' J7 a: h4 L9 k9 HCritical region, 拒绝域4 j+ u8 h `: |+ Q4 q; q
Critical value, 临界值* I( {8 R( V1 q' k
Cross-over design, 交叉设计, m1 D8 z" Q+ [. z! L0 W8 x1 `& T
Cross-section analysis, 横断面分析
$ t' l7 \, `3 _) H7 s2 ~8 |& oCross-section survey, 横断面调查
4 X3 y+ p7 b2 u4 [2 S) OCrosstabs , 交叉表
% c/ d- q( R( k0 SCross-tabulation table, 复合表
: r& M$ R+ [0 p+ G0 ICube root, 立方根' ]8 x# j- z$ o) y% v
Cumulative distribution function, 分布函数7 M+ j0 r- M+ k, I2 \# N: ^
Cumulative probability, 累计概率
# D: Y* ^- e6 I% }3 x+ R& _* h5 _Curvature, 曲率/弯曲- a1 N9 M3 z$ v: ^) b
Curvature, 曲率( |4 \; t6 |- y4 C# k$ S2 I0 s+ r
Curve fit , 曲线拟和
0 G- _7 F/ J! B" _. ?+ ^* YCurve fitting, 曲线拟合, L4 X, d6 E, @
Curvilinear regression, 曲线回归
5 f- Q, a5 `% PCurvilinear relation, 曲线关系3 U( P4 Q( ]. h& I7 J4 P8 P
Cut-and-try method, 尝试法2 G2 v" `5 h, L9 w
Cycle, 周期
1 x3 t) s4 }& b2 s" J3 \$ V$ ^Cyclist, 周期性. V; U! I: l7 _: B0 \2 o( O
D test, D检验
0 B# h3 _4 q- Y2 w4 `Data acquisition, 资料收集
; R4 p7 C3 b3 E$ I6 K1 t$ KData bank, 数据库 f5 O: ~& U5 J, \6 H" q4 F
Data capacity, 数据容量2 m" q: V$ `" b+ T3 `: ~
Data deficiencies, 数据缺乏
6 ~$ \/ V5 H% ^; cData handling, 数据处理8 A( p! N( Z7 G3 _+ D8 q5 l
Data manipulation, 数据处理; `; F& e/ e: h+ w2 I
Data processing, 数据处理
1 J7 i/ d: @( l7 {2 }+ i) ^% LData reduction, 数据缩减/ w2 g! d5 L7 ^( t* R D# u6 M; N1 X
Data set, 数据集( H3 `2 U% ]2 i G
Data sources, 数据来源
+ n2 ]0 [0 c* u2 SData transformation, 数据变换
& x! \! i1 m3 B% _Data validity, 数据有效性
4 I0 u4 t4 Q- r7 }* s8 z! }: dData-in, 数据输入
& E5 R) {1 t! |Data-out, 数据输出
, x: |/ B- u( u9 e( h: M- [) \- }Dead time, 停滞期
0 a( K9 @% M' L$ D! kDegree of freedom, 自由度* k6 W9 Q; D" V
Degree of precision, 精密度( S/ o; ^1 [$ g
Degree of reliability, 可靠性程度% O$ @3 T* \: K! c# w% ~' n
Degression, 递减
: o( E* x/ c M( A! g+ CDensity function, 密度函数
' W8 X, u' N- m8 |' |Density of data points, 数据点的密度
5 N4 ^ D: E7 b# S& eDependent variable, 应变量/依变量/因变量
5 B4 E( N5 m. k- O) |+ g4 N/ [Dependent variable, 因变量
; Y. H. b, e0 C, u* SDepth, 深度
- c- E* o5 ?+ z; _ {Derivative matrix, 导数矩阵3 d9 H: m" q/ `, h$ O6 \
Derivative-free methods, 无导数方法6 J) k- D2 g! t7 h2 n
Design, 设计% H) x1 w6 Q& ?" Z8 E u& R
Determinacy, 确定性
! J+ [- R. G2 _/ M6 Y' aDeterminant, 行列式+ E0 w2 F9 s( E# H; f
Determinant, 决定因素
( K; S- H% m% d3 m7 E3 jDeviation, 离差
$ B# v) e6 Z# r3 _2 ^- M gDeviation from average, 离均差 u h* X/ ]& s; i2 P! N
Diagnostic plot, 诊断图
$ M L7 v2 D! \, |! c9 WDichotomous variable, 二分变量1 S' G, J; L* r; m
Differential equation, 微分方程. q G, y* @- d4 v! [2 _: Y
Direct standardization, 直接标准化法2 |/ J8 ]* W x$ h- }0 Q
Discrete variable, 离散型变量( U4 }' l( R- v2 w
DISCRIMINANT, 判断
1 N0 i1 y I, x, ]7 {) uDiscriminant analysis, 判别分析* F/ Q1 q7 j% H' Y
Discriminant coefficient, 判别系数
" e: U T4 {6 xDiscriminant function, 判别值
! m4 q1 @9 S4 J) {Dispersion, 散布/分散度
; t; J, q5 ? R2 \& [% \6 ~+ I# XDisproportional, 不成比例的( N1 K2 k2 i' s
Disproportionate sub-class numbers, 不成比例次级组含量7 `3 d$ U0 j" r% g9 W
Distribution free, 分布无关性/免分布& N; a. T- G2 ]9 u
Distribution shape, 分布形状 u7 D$ C6 x, M6 E o& o. C, d5 W
Distribution-free method, 任意分布法# H8 Z2 h, q* ~8 E% `
Distributive laws, 分配律
+ T4 s& c6 J( t* wDisturbance, 随机扰动项* B: G) ~) x/ l8 P, _$ W
Dose response curve, 剂量反应曲线: J/ G! B; J! k
Double blind method, 双盲法3 J, K1 X1 d8 T+ B4 s9 F9 e; m
Double blind trial, 双盲试验
7 w7 B: W' K0 u' R/ \Double exponential distribution, 双指数分布
6 M. j4 `4 R0 X* yDouble logarithmic, 双对数8 y! S4 S/ _( d) w( p
Downward rank, 降秩2 |; h. R# d( I% e; _2 V6 J
Dual-space plot, 对偶空间图) S4 K, J7 Z% x" Z1 E8 J& V
DUD, 无导数方法. d7 I2 p; R0 W, z: |
Duncan's new multiple range method, 新复极差法/Duncan新法8 c$ @' @2 U( c! U# ?
Effect, 实验效应
/ A0 V$ E7 Q; iEigenvalue, 特征值
$ y) V# S) p* U$ L0 ~Eigenvector, 特征向量
2 I0 e: P' x$ o+ c0 wEllipse, 椭圆8 x, ?: S; u# X5 B1 Q
Empirical distribution, 经验分布
0 Z8 X) D" G& k$ b7 L, L. y% hEmpirical probability, 经验概率单位* d1 J* \3 B, l3 Q& @
Enumeration data, 计数资料
) r9 p% L6 B' x7 l+ ]# tEqual sun-class number, 相等次级组含量* i/ N8 h4 Y8 k1 P6 a% H
Equally likely, 等可能1 s ^. l( N8 \" ^4 j
Equivariance, 同变性 Y2 Q5 v3 `" A3 y) w
Error, 误差/错误8 w$ u, y- f% ~: [/ Y& L
Error of estimate, 估计误差2 z( K% C0 x6 R9 f; u' H6 g& J. T! I; i
Error type I, 第一类错误
* g; v$ O# [; d0 ~. cError type II, 第二类错误, E* r; o( r6 q# e0 T7 J, b
Estimand, 被估量 w7 J& }( W& J2 Z. F
Estimated error mean squares, 估计误差均方
& l$ [( m1 h+ R$ W9 m4 iEstimated error sum of squares, 估计误差平方和8 Y) e, z6 }% V0 [8 B7 T0 a& r
Euclidean distance, 欧式距离
3 e- b1 g# p# a. V J( v4 O! NEvent, 事件' n9 I! L# g: }) ^
Event, 事件 T: _2 C2 t, e+ r. [# d3 U
Exceptional data point, 异常数据点! ~$ o" n; u' X2 |- s" p
Expectation plane, 期望平面
$ X3 {1 z0 b8 O( Q' @- m7 f* NExpectation surface, 期望曲面& M7 m' _4 p8 W& W2 B# U J
Expected values, 期望值+ O7 C& A0 j2 ]- ?
Experiment, 实验
7 p2 S* a0 } _3 FExperimental sampling, 试验抽样
9 H7 H) ^0 n. d# ?4 g6 rExperimental unit, 试验单位( o% e) i0 b" @8 ~
Explanatory variable, 说明变量
" r# g: i8 [. x" }: j4 sExploratory data analysis, 探索性数据分析
0 _# _4 {# ~) iExplore Summarize, 探索-摘要
, j5 |& q6 W5 n; Q1 fExponential curve, 指数曲线
( r1 q! ^! f+ f1 C8 p' b2 S8 BExponential growth, 指数式增长
+ A/ q* }. e2 k$ FEXSMOOTH, 指数平滑方法
$ a& j* i7 M7 l3 I2 b, TExtended fit, 扩充拟合
5 |' G' A' x5 j8 P1 i/ f8 VExtra parameter, 附加参数
( O, X Y' S$ p, p; R, D. s9 A" s7 tExtrapolation, 外推法# d4 a. W; s R. w, B
Extreme observation, 末端观测值7 [" A% l' i- ~5 R4 Z3 z5 M, \
Extremes, 极端值/极值9 Y+ Q* b8 Y9 V5 i5 d$ H
F distribution, F分布
3 q, Y8 U8 x; P1 u* M; {F test, F检验
8 T2 W, L _0 zFactor, 因素/因子# ?9 D( \) ?3 r: U
Factor analysis, 因子分析' B) b& `; p0 F/ ?/ `3 g+ A* Z+ O
Factor Analysis, 因子分析' x( x# q c$ f1 d' D' {3 h1 c
Factor score, 因子得分
2 j0 T7 C3 r2 l' kFactorial, 阶乘' r7 b# @. {" _8 y
Factorial design, 析因试验设计
; J7 z ]5 C9 v- aFalse negative, 假阴性
( i) ~5 P7 n# [2 ]5 V3 V! NFalse negative error, 假阴性错误' s2 S3 c, P0 b- z) f+ B1 f
Family of distributions, 分布族
- B8 s" A$ H! N+ }# Z: {: m- KFamily of estimators, 估计量族 O' v# J6 {; W2 P0 f% [- \' r7 @
Fanning, 扇面 t! Y1 C+ {$ D/ L
Fatality rate, 病死率
7 }4 e b) y' ?+ z6 Z' UField investigation, 现场调查 o' R9 R6 }& F, z" U
Field survey, 现场调查
8 l/ D% \ i N3 ZFinite population, 有限总体
' _2 o0 {+ y& ]! P! T: l# FFinite-sample, 有限样本
) J0 f. k+ o$ H& oFirst derivative, 一阶导数
/ O) a6 \/ X# J6 J" _9 ?First principal component, 第一主成分1 {; j$ Y: O7 [/ b% b6 e6 u: k2 z
First quartile, 第一四分位数" Z6 p5 }$ P. C8 J3 _; N* d
Fisher information, 费雪信息量6 L( r2 `/ E/ w/ y; G7 k# L7 S
Fitted value, 拟合值, |! D6 M# W" F) l
Fitting a curve, 曲线拟合
i7 F8 e9 T' C& ]Fixed base, 定基! a2 @% ?( ^0 B9 }& Y
Fluctuation, 随机起伏
6 s \' [8 T9 u0 |1 sForecast, 预测) \5 h' Q' B$ w+ B( n9 B5 Q0 j
Four fold table, 四格表
* G7 f% s. R6 i0 {( x) [Fourth, 四分点2 G: e8 L/ f" g$ F
Fraction blow, 左侧比率/ v& s3 n7 J: d$ D
Fractional error, 相对误差
7 Z- G* j& h6 ?Frequency, 频率
# D+ X* K" I- ~4 {/ r+ pFrequency polygon, 频数多边图
3 k3 d! i* z5 U7 M6 _Frontier point, 界限点/ M3 P& u5 U6 q' q6 ]3 S4 d
Function relationship, 泛函关系
6 D! m' D- R. r+ q0 pGamma distribution, 伽玛分布
0 A: {. v8 n# ?' J8 CGauss increment, 高斯增量
5 A; f$ C0 ~; Q1 ^' \4 _Gaussian distribution, 高斯分布/正态分布2 }5 L& n+ W9 |. f
Gauss-Newton increment, 高斯-牛顿增量4 Y( |* B) C5 a7 l \
General census, 全面普查: Z: _" f" O* n$ b
GENLOG (Generalized liner models), 广义线性模型
( o, c9 m0 r: \% o! o uGeometric mean, 几何平均数
0 N) d# t A3 g# t5 `9 MGini's mean difference, 基尼均差1 T- z* b5 ~ E# L( R+ C I
GLM (General liner models), 一般线性模型
% X; O8 u0 n2 u7 G: k9 ^' tGoodness of fit, 拟和优度/配合度
3 h! \8 H8 z* u { E0 TGradient of determinant, 行列式的梯度
1 `3 l; S; D# Q' s% _+ K! S" CGraeco-Latin square, 希腊拉丁方
1 h: ?, y3 z$ H9 bGrand mean, 总均值
3 u% D1 k- s. C7 P9 @Gross errors, 重大错误
. Q4 g# f+ }/ Z: |7 z- ]+ vGross-error sensitivity, 大错敏感度/ N( \2 T. z% k$ u6 E# x
Group averages, 分组平均2 o& \9 `, s, v) `6 _" G, ~, ^
Grouped data, 分组资料& Y T1 U; }9 \( m7 c5 v7 o
Guessed mean, 假定平均数) Q8 O# p7 a5 A6 q( Y
Half-life, 半衰期2 A* o. j9 @- }) ~! a
Hampel M-estimators, 汉佩尔M估计量% z4 u8 T! H- O+ f M) w. b# N
Happenstance, 偶然事件1 A5 S9 K/ S q, N8 V9 T. |6 Y
Harmonic mean, 调和均数* h0 \5 ^' E+ f; I" x. p. o
Hazard function, 风险均数& v4 t& z/ O5 L& Q, T: Q: Z( O
Hazard rate, 风险率
/ W; n& ~! V+ y- o, [, e! v/ oHeading, 标目 9 w3 p; w1 X7 D! |
Heavy-tailed distribution, 重尾分布9 B z+ s T# _3 C. K
Hessian array, 海森立体阵, s& t2 X+ g4 x3 u9 f
Heterogeneity, 不同质( z2 P; l% q# o2 m+ O
Heterogeneity of variance, 方差不齐
t9 s2 ]1 s$ |2 E4 n) Z8 H6 \4 [Hierarchical classification, 组内分组) e" X0 |. z8 Y7 ]
Hierarchical clustering method, 系统聚类法
! E* J( l& ^. a& o1 P1 YHigh-leverage point, 高杠杆率点4 ` _0 \' A: h( \
HILOGLINEAR, 多维列联表的层次对数线性模型
! ^) g8 U( M" r. W+ ]8 w* ?Hinge, 折叶点
8 o2 \# J, N/ B) l2 {7 A4 THistogram, 直方图
5 F2 x2 q: {9 G' s1 { J' u8 b3 lHistorical cohort study, 历史性队列研究 2 ^* S2 t) p' W% K
Holes, 空洞- b! w% P: \ F- k1 D2 x
HOMALS, 多重响应分析$ H; a7 [+ O. H
Homogeneity of variance, 方差齐性9 p S- R+ s8 r; ?0 }2 B
Homogeneity test, 齐性检验
) P8 A5 x) {7 S+ a. w. HHuber M-estimators, 休伯M估计量. ^; [2 A3 d0 Y3 a7 n4 |
Hyperbola, 双曲线' _: Y3 R6 x7 ?2 X3 g# I' D+ I
Hypothesis testing, 假设检验" l' H \- p7 T# `; c0 ~' j
Hypothetical universe, 假设总体9 _- F* T" ^( [# ^ b: y
Impossible event, 不可能事件
: M' |# S( ~# U5 A3 I: j3 j$ NIndependence, 独立性% d( T! L8 K3 c
Independent variable, 自变量
5 p7 d* M1 a6 b: s! ?, n0 KIndex, 指标/指数
9 n5 [$ R/ E% lIndirect standardization, 间接标准化法
0 F9 z; J9 T" g& f/ z) CIndividual, 个体
) @) X2 I3 d$ P3 U! ]) ?Inference band, 推断带
6 E$ s g3 ?& bInfinite population, 无限总体
- I7 W3 L6 C: zInfinitely great, 无穷大5 w7 k8 r! a) H- a B) x
Infinitely small, 无穷小
. g9 ?/ ` v6 TInfluence curve, 影响曲线
1 l, k3 K s( yInformation capacity, 信息容量0 [; o0 v) F v. R( w! E, d
Initial condition, 初始条件
5 c; N: b2 S1 V# wInitial estimate, 初始估计值
5 X0 r+ L) v! Z6 b9 ~2 E n# aInitial level, 最初水平
! C- ^- J+ q5 B" YInteraction, 交互作用
+ L a. K# i+ B5 s# E pInteraction terms, 交互作用项
/ h' b. T$ N/ S) Y) X7 K. SIntercept, 截距- U% H$ @$ p' i4 e4 D
Interpolation, 内插法, ?" F6 z' _/ q' }0 b' g; M8 v
Interquartile range, 四分位距; o! j' \' b- U. y, Y) ` g2 {
Interval estimation, 区间估计
3 I3 z9 k( A( R" T2 }) \Intervals of equal probability, 等概率区间
1 H4 N% ?) f: D2 b: c, E: E1 _Intrinsic curvature, 固有曲率/ Y0 r. F/ L3 b. b7 @$ n
Invariance, 不变性
! v$ @% o/ R% t' lInverse matrix, 逆矩阵
+ `8 ~% S* L! T& Q- ^0 L' TInverse probability, 逆概率
" G k) p1 h: I$ m5 k7 t) XInverse sine transformation, 反正弦变换7 t w/ Q; S% k8 Y
Iteration, 迭代 % Q2 X5 _7 n$ u! }9 Y
Jacobian determinant, 雅可比行列式
3 b3 y+ M& Q" k: V3 G6 |Joint distribution function, 分布函数
3 W% T; U, y$ C% B( Q' }Joint probability, 联合概率7 l, \7 H; Z: v9 P1 K
Joint probability distribution, 联合概率分布. ^& m( p' ?) l' G
K means method, 逐步聚类法) \( H1 e" a- b1 C) S# x
Kaplan-Meier, 评估事件的时间长度
9 m- _6 E( L' `Kaplan-Merier chart, Kaplan-Merier图
& H# P) m& U% ^6 BKendall's rank correlation, Kendall等级相关
4 v! E1 Y1 K! d0 |3 D! @% C9 gKinetic, 动力学
, c/ G+ Y, k9 s S, w, N) D- ]Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
7 ?. ^* O6 \' H3 i7 _) yKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验# J9 t0 s r! G! p% s. k
Kurtosis, 峰度- l( J V5 q: |7 X5 P& `4 ]' F
Lack of fit, 失拟
: c8 j- i) o* L1 U3 DLadder of powers, 幂阶梯2 |4 M: t& @3 X2 N+ S
Lag, 滞后* r. O, x% q7 Z
Large sample, 大样本0 I3 `& Q* f8 f l! o; C! C
Large sample test, 大样本检验% L& H6 D* x; e* o" d
Latin square, 拉丁方1 C3 y, v8 L% O( N0 J3 g, Z5 D
Latin square design, 拉丁方设计' ?; y. u8 j, [+ N/ q
Leakage, 泄漏. d! h/ D" v o$ G
Least favorable configuration, 最不利构形
2 y1 ]& w8 k( ]( eLeast favorable distribution, 最不利分布
8 ?. g. X2 Q. {$ ?5 ~6 w7 bLeast significant difference, 最小显著差法( }8 u0 y: X; M3 O- U
Least square method, 最小二乘法/ x0 x" i6 |& Z2 l* s. ^5 F$ _
Least-absolute-residuals estimates, 最小绝对残差估计' b! e: ~, \' n: s; q. s( q
Least-absolute-residuals fit, 最小绝对残差拟合7 }( ~* X9 b. [
Least-absolute-residuals line, 最小绝对残差线
$ v! q; R, o# y& m4 YLegend, 图例
2 I7 a0 U. O. t7 S5 n& E+ s+ g+ `L-estimator, L估计量9 I1 a# @3 r) _4 l* p
L-estimator of location, 位置L估计量1 z# Q; Q% b! ]( D7 y- `
L-estimator of scale, 尺度L估计量
' h5 |: ?( G( m) _Level, 水平. t, O2 S% k& h) C
Life expectance, 预期期望寿命
: F+ k6 I6 \1 g$ xLife table, 寿命表
) r; X0 l: K& a9 p U5 rLife table method, 生命表法
5 e2 { u0 A" _9 o; oLight-tailed distribution, 轻尾分布' `0 G- ]$ V5 t3 o# R
Likelihood function, 似然函数- D3 P2 C) [/ u
Likelihood ratio, 似然比
( ]5 H4 Q6 Z8 l* }$ Oline graph, 线图: `( [% v. T/ O' M& x
Linear correlation, 直线相关$ e, [9 E, D# T j% L
Linear equation, 线性方程
' a) ^# x X# _9 o2 z* q( LLinear programming, 线性规划 R3 C# ~# f5 T( R% }. i' U3 G1 p
Linear regression, 直线回归
" _; z2 u5 u0 Z3 b, H, h1 LLinear Regression, 线性回归
; s7 J) B4 ~& tLinear trend, 线性趋势8 B+ `2 T) m% W% A5 r8 r- x
Loading, 载荷
2 y0 L) E0 _. o$ c4 [: L T& ELocation and scale equivariance, 位置尺度同变性9 ^8 V' B6 D& ~9 x: r
Location equivariance, 位置同变性& T! w( T; u8 T( d
Location invariance, 位置不变性$ T% t! ^9 ]. t1 i2 i* e/ K
Location scale family, 位置尺度族, Y' r7 L4 Z$ B& z# \- T% @4 H
Log rank test, 时序检验 7 t$ l' L$ v( s1 h+ o/ { D
Logarithmic curve, 对数曲线
: v+ [! R+ ?0 @+ @" Y N: o1 t/ QLogarithmic normal distribution, 对数正态分布5 \, @ o6 X+ p# }! @: r4 J, C( `
Logarithmic scale, 对数尺度
# B8 T# ]8 H. R8 u6 Z( @. J v' {Logarithmic transformation, 对数变换
/ N5 M: i9 @, R. d! _- oLogic check, 逻辑检查( s% z/ t! m. s2 n$ W, F6 Z
Logistic distribution, 逻辑斯特分布7 W+ F) B6 D2 B: y" Z: H2 j
Logit transformation, Logit转换
. x) g5 a8 Y& V: Q7 lLOGLINEAR, 多维列联表通用模型 " g& R T% J; a* T
Lognormal distribution, 对数正态分布' R. M5 z# P$ j
Lost function, 损失函数) f/ G( ^: _# U6 W
Low correlation, 低度相关& H. M9 g& s; H% |' V! S$ K3 M+ }
Lower limit, 下限/ l8 J6 ]+ ` B! L
Lowest-attained variance, 最小可达方差% |6 D# A C- k/ c9 _% Z" T4 ?
LSD, 最小显著差法的简称
* M, p+ Y$ i. g5 MLurking variable, 潜在变量# m# e& H4 ~* w9 u j: G$ k1 y
Main effect, 主效应
5 G9 ]: w# a5 o0 n" J: M# yMajor heading, 主辞标目
" z/ Q) y2 d' W- d1 zMarginal density function, 边缘密度函数, K; J/ U! j: w! v v
Marginal probability, 边缘概率- g; T7 I2 @1 Q6 }4 D# ?
Marginal probability distribution, 边缘概率分布
/ Z# v- w) i3 y; zMatched data, 配对资料
& L( F: u5 a G6 aMatched distribution, 匹配过分布
1 B, J" J3 R" y/ W* d# CMatching of distribution, 分布的匹配$ B0 g, v. l0 r. ~" Y. D. a( ^3 Y- T
Matching of transformation, 变换的匹配
, l4 j4 E) U5 pMathematical expectation, 数学期望# W2 l5 Z% K4 K3 {. ^
Mathematical model, 数学模型- y' ^7 ^0 C' H6 M1 q* @$ m; @
Maximum L-estimator, 极大极小L 估计量, Y* ~; v/ j* d/ X/ n
Maximum likelihood method, 最大似然法2 O& t1 u2 i" K8 m9 D
Mean, 均数/ B2 z6 P( Y0 ]4 t c
Mean squares between groups, 组间均方4 y# H( I2 Q5 t
Mean squares within group, 组内均方/ K" D6 {" A9 m
Means (Compare means), 均值-均值比较
; d" r7 L& b8 ?* d4 K/ l1 GMedian, 中位数
3 @9 B/ R- e" o! SMedian effective dose, 半数效量% W& G& ?) q: I6 ] `$ E
Median lethal dose, 半数致死量1 @; N5 H( Y5 @8 K( R2 O$ n
Median polish, 中位数平滑
. Z% i0 X8 f. }9 b/ m& WMedian test, 中位数检验
7 C9 ^! e+ U- M1 o* c* C, Y* dMinimal sufficient statistic, 最小充分统计量
) |! c* c, ?- j4 G" yMinimum distance estimation, 最小距离估计
0 Z K7 E) _9 y bMinimum effective dose, 最小有效量$ X3 K2 ^6 V1 I) o4 U
Minimum lethal dose, 最小致死量
* Z- F& {. ]6 b( P9 \Minimum variance estimator, 最小方差估计量$ q, ~- P* u% e
MINITAB, 统计软件包
8 a% H: j5 T; Y/ NMinor heading, 宾词标目
+ f& M6 M" f9 i7 P2 yMissing data, 缺失值
0 e9 a7 r7 ~7 Z6 l, m: x5 X/ c# UModel specification, 模型的确定5 _. M1 U2 y1 U, J
Modeling Statistics , 模型统计9 G: A" I$ Y, e6 V8 G/ C1 h
Models for outliers, 离群值模型
1 B8 ~+ ^2 q1 G% B; l' RModifying the model, 模型的修正2 B( I: U" \6 e. }) I
Modulus of continuity, 连续性模6 P; O8 O5 V- T# u8 L2 }
Morbidity, 发病率 ' c+ P4 b5 d" a$ `
Most favorable configuration, 最有利构形4 p& j6 Q( O( v% c) e. T# |) z
Multidimensional Scaling (ASCAL), 多维尺度/多维标度/ V% X; `% o, ]
Multinomial Logistic Regression , 多项逻辑斯蒂回归
: T$ S) I/ ]8 |" C" ]Multiple comparison, 多重比较
8 B5 k! a+ A; |8 cMultiple correlation , 复相关
; K: L: K8 s/ U/ H- Q1 e' ZMultiple covariance, 多元协方差4 A' N. _ b7 _: s4 C5 l9 Z- z
Multiple linear regression, 多元线性回归8 o* j$ q2 ^& }3 V3 y) e6 U
Multiple response , 多重选项
+ d1 g; l' Q1 E, W6 ZMultiple solutions, 多解
( I; |1 o, S& o8 BMultiplication theorem, 乘法定理
+ _" ], d1 e4 ~1 GMultiresponse, 多元响应
3 t3 H( f- I, `0 cMulti-stage sampling, 多阶段抽样
6 j0 \1 Z$ N9 O/ v: d3 ?( {Multivariate T distribution, 多元T分布) {! I9 k2 D4 a* Z. w# X2 X
Mutual exclusive, 互不相容
( L2 L8 h( e RMutual independence, 互相独立
2 D. p$ Q. e$ J/ P JNatural boundary, 自然边界! P( C4 r9 k- r: G; F8 E q, n
Natural dead, 自然死亡; D1 Y6 j4 @) }% a; B, o; ~) V
Natural zero, 自然零
X0 p3 V* Y- q' a, RNegative correlation, 负相关" c+ m# @7 Q9 V$ Z) v* z3 M6 f
Negative linear correlation, 负线性相关
- D' m z/ C V+ hNegatively skewed, 负偏
- Z5 g4 c. f0 r. L$ h* uNewman-Keuls method, q检验
7 l! d- Y6 N8 k: @NK method, q检验$ T0 ?: M5 c# o+ e. J9 k. X9 w
No statistical significance, 无统计意义
+ X. O( }4 Y- G- gNominal variable, 名义变量1 e9 u9 ]% G9 {
Nonconstancy of variability, 变异的非定常性- Q" V j/ k9 v* b# N
Nonlinear regression, 非线性相关3 ^6 M3 ^) [, X3 T3 _+ ?
Nonparametric statistics, 非参数统计
! m+ {9 h1 N) INonparametric test, 非参数检验6 A, n, L. A5 k* {/ s x7 \& w
Nonparametric tests, 非参数检验
9 a. s% R! ~& m5 ]! `! F5 X" xNormal deviate, 正态离差( k5 R4 h- i8 s$ ?
Normal distribution, 正态分布* v" F: l7 X0 B
Normal equation, 正规方程组
% T$ _- e+ v/ d3 UNormal ranges, 正常范围
x3 u4 f( t1 p; R6 ]3 B4 l1 rNormal value, 正常值 Z) x5 s/ Q k7 U k" n) T
Nuisance parameter, 多余参数/讨厌参数0 n5 o, A! g/ w6 z. e9 v# V1 w! c% h
Null hypothesis, 无效假设
: @9 F( S( l2 yNumerical variable, 数值变量- T+ w( q1 M! U# h$ } B6 z, p
Objective function, 目标函数( \+ M! S; P9 c2 w4 r
Observation unit, 观察单位. y, {2 F+ e; V) T$ y( D
Observed value, 观察值
& O4 r/ ?6 m j0 O$ ]0 l$ o4 YOne sided test, 单侧检验
0 X+ ]/ e, W S* J2 aOne-way analysis of variance, 单因素方差分析7 k; s: Y; l S+ [
Oneway ANOVA , 单因素方差分析
+ L1 F1 }8 @3 c2 w: v D2 u6 OOpen sequential trial, 开放型序贯设计
O) u" ]. d) B( `Optrim, 优切尾- h) j+ b' @7 x3 b
Optrim efficiency, 优切尾效率5 ^% Y: j5 q5 c3 R* j! s! U# A
Order statistics, 顺序统计量
9 L& h- B4 d5 U" nOrdered categories, 有序分类9 G* f: q& S# P: d1 B. ]
Ordinal logistic regression , 序数逻辑斯蒂回归
. F: I9 X; ]. z q' g* t5 B4 WOrdinal variable, 有序变量5 I- L* h+ Y6 h! _1 \& U0 I
Orthogonal basis, 正交基
- t p# Q' @/ _5 MOrthogonal design, 正交试验设计
" C% j7 S; K" y. {2 B5 QOrthogonality conditions, 正交条件
5 N+ ]) P5 b2 C; o( u+ wORTHOPLAN, 正交设计
3 B. u2 V" Y# C' y6 l; T' pOutlier cutoffs, 离群值截断点
$ Q0 o, s+ d9 o6 A- [5 {! xOutliers, 极端值8 h+ p- }# U- k% T% A6 Q: G5 Y2 d
OVERALS , 多组变量的非线性正规相关 5 g Z+ N; _) o2 b4 Z: R8 V- K
Overshoot, 迭代过度' m( Q* f: e# H4 ^1 X+ \5 ?
Paired design, 配对设计
0 `% F6 U2 m7 L0 c/ y# e4 B# pPaired sample, 配对样本
' X8 @. b8 _* } I* X: _Pairwise slopes, 成对斜率# W9 A7 G- I4 W5 j8 `/ l
Parabola, 抛物线
+ S) B# k w7 W5 i- x) MParallel tests, 平行试验
( v) Q7 f% L' r; W A) ]Parameter, 参数
% w) j- ~9 E7 _7 f7 N( g8 G% SParametric statistics, 参数统计* E2 j: s6 u0 P. N) }
Parametric test, 参数检验
. H6 l% l9 C8 b/ RPartial correlation, 偏相关
( K0 @, U2 B7 J5 e' f6 l, bPartial regression, 偏回归
9 V7 \8 e$ S z* \# x# ~4 cPartial sorting, 偏排序1 e. r, A; [- o4 f
Partials residuals, 偏残差
% e6 w) l" m a3 H0 T3 A5 ^Pattern, 模式) n ~5 ?/ d( E8 S7 s8 X1 m4 `
Pearson curves, 皮尔逊曲线
4 u# n4 ]3 N* QPeeling, 退层
7 n0 |; `! Z3 @( ~. EPercent bar graph, 百分条形图6 c+ |3 T* c/ U! [
Percentage, 百分比0 L; N- o/ r8 K) R
Percentile, 百分位数
( [0 N6 F& B4 o5 `0 Z5 u% W$ RPercentile curves, 百分位曲线
$ z, ~( ^ M# ?7 o- P0 x g1 FPeriodicity, 周期性
2 F9 I. G" k1 Q6 tPermutation, 排列
3 R1 k% t) ]8 N! DP-estimator, P估计量' l! c; U3 E% P7 w
Pie graph, 饼图2 d' A! ]/ O; \
Pitman estimator, 皮特曼估计量& \* N; B: W' g4 u, w# l. a( w
Pivot, 枢轴量
+ Y2 t8 ?; Z$ EPlanar, 平坦
$ X" l3 t; O% e% v! D) XPlanar assumption, 平面的假设# Z! U: v% a& t$ O9 T
PLANCARDS, 生成试验的计划卡& L+ Y9 k5 p* m- X. ?
Point estimation, 点估计8 I" Y+ G& u3 G" o9 [# C! E2 b1 d8 i
Poisson distribution, 泊松分布
- g% d9 a. i C( ?) c8 ?: K' RPolishing, 平滑4 n" Z% ?9 b n. J
Polled standard deviation, 合并标准差
7 s; [' B" l" Z% y. @2 tPolled variance, 合并方差% Z' k( H& K. B0 W; m9 n) N7 f& b
Polygon, 多边图
. [( O v, U4 l2 ~Polynomial, 多项式
, k1 { }# L% S5 NPolynomial curve, 多项式曲线
" x) w* B* c6 T# {$ BPopulation, 总体
1 v% x( ^- Y) R, d6 o! hPopulation attributable risk, 人群归因危险度$ @0 s5 o1 e! j
Positive correlation, 正相关" ]* }* b+ z# ]: V9 m
Positively skewed, 正偏) y: r* n T, V: M
Posterior distribution, 后验分布
% i. R, n1 r3 s- D+ tPower of a test, 检验效能' l% c: U T ]8 p& S0 J/ I
Precision, 精密度
$ L7 J: T4 F. d& mPredicted value, 预测值
5 Q' _8 d: c. L! D1 |Preliminary analysis, 预备性分析+ K& r- Q* r% x" I4 v( ~% N
Principal component analysis, 主成分分析2 v3 \$ n' _4 J( {; z% l
Prior distribution, 先验分布
* q1 m5 ~( J2 T* Y- FPrior probability, 先验概率
/ }6 n& F5 M0 x5 @% W( OProbabilistic model, 概率模型! d1 d- R8 u, {0 m8 ~) Y
probability, 概率
* P/ {/ T2 u8 R/ ^' ?- {Probability density, 概率密度
9 `, c; f' @ C4 WProduct moment, 乘积矩/协方差
7 V+ U# C; M4 z6 f/ A' GProfile trace, 截面迹图% c! g# c/ Q# H0 D2 z1 K
Proportion, 比/构成比+ x* m) X( R% o6 W2 c
Proportion allocation in stratified random sampling, 按比例分层随机抽样
& l, u h4 u, {5 OProportionate, 成比例
7 t" I1 a q# h. t' h% _Proportionate sub-class numbers, 成比例次级组含量1 M; v( ` s! ?& ^+ C( W/ W
Prospective study, 前瞻性调查
# ^# J' g& Q" ]8 [% } eProximities, 亲近性 ( p3 o) l. V9 J2 C, V: y6 n& ^
Pseudo F test, 近似F检验/ V+ W h$ g$ [: q
Pseudo model, 近似模型
7 t" F0 Z$ Q) n1 ~6 S: @7 RPseudosigma, 伪标准差: E) J/ l5 v8 O+ `; O- m
Purposive sampling, 有目的抽样! e7 t* D& S2 K. B" R9 \( U
QR decomposition, QR分解/ L3 N$ O3 w2 _6 v
Quadratic approximation, 二次近似
3 t! M/ N, f: Q) @. bQualitative classification, 属性分类! G' V) Z& o, G- L! S- L
Qualitative method, 定性方法
" ~9 G6 L/ e1 O9 S1 k- OQuantile-quantile plot, 分位数-分位数图/Q-Q图
1 B* v2 {! A/ r, u/ c; }Quantitative analysis, 定量分析, n8 p8 M- A! v, _! e
Quartile, 四分位数
0 [) u& f5 ?: t* [Quick Cluster, 快速聚类
; }" ]" F% w u! o2 J2 v$ KRadix sort, 基数排序( b ^% x! ?5 k( G
Random allocation, 随机化分组( X5 \, _$ v2 Q
Random blocks design, 随机区组设计
3 @ W. w: n* j9 ?% A4 MRandom event, 随机事件3 i0 a1 s' O, i/ ]( m( _
Randomization, 随机化
0 ]1 w% t& u7 O: [& D: g! ~8 HRange, 极差/全距+ v( z2 o. _ ^& A4 A
Rank correlation, 等级相关
6 L0 R8 r+ H% k/ y7 V7 @Rank sum test, 秩和检验& `6 `* }+ n6 V H6 S) F( w0 h0 i
Rank test, 秩检验
* i$ k4 I! @1 K; Y. GRanked data, 等级资料
, M* U; r6 P" T# O6 {9 K) iRate, 比率
* z* ^, i6 ?; [Ratio, 比例
( u; {- s6 U1 \% o- LRaw data, 原始资料
0 R0 s% X* }% f2 NRaw residual, 原始残差
! c2 i( x3 X& C; Y; jRayleigh's test, 雷氏检验
# {+ W; t* {& D) X/ E' oRayleigh's Z, 雷氏Z值
$ Q: \$ ^6 k/ o, o7 qReciprocal, 倒数! d3 e2 P/ {, O$ Q
Reciprocal transformation, 倒数变换
8 f9 S$ A3 A. C- Z7 C1 HRecording, 记录
) R) [4 f! J; f, o VRedescending estimators, 回降估计量
! r& g5 ^" X+ ^& }Reducing dimensions, 降维
, C, \; I9 V3 g. w3 kRe-expression, 重新表达
^/ w: p) Q2 g) N3 \- Q. iReference set, 标准组
+ z, J8 |7 s/ BRegion of acceptance, 接受域
7 x: A! D5 l3 o7 \0 M" D8 I+ XRegression coefficient, 回归系数6 d8 \4 m( d5 v4 W
Regression sum of square, 回归平方和, B- G8 e3 b4 v6 x
Rejection point, 拒绝点2 K* b7 g# C, z4 E% ~& W) N. S
Relative dispersion, 相对离散度
w( p) }8 {% I" G' DRelative number, 相对数* ~2 L: L7 g; f+ [# Z/ {# p
Reliability, 可靠性 e/ e: I) T* M8 i! F
Reparametrization, 重新设置参数4 g7 x O; w- v( T$ v1 h1 s7 c
Replication, 重复' v- k% X* s/ H% r
Report Summaries, 报告摘要/ p1 @8 F+ w% j! ^1 h
Residual sum of square, 剩余平方和9 } D1 d* ?. F1 ?
Resistance, 耐抗性
! {, q* ^3 k; CResistant line, 耐抗线2 _0 b* n1 e5 j0 j8 _8 `
Resistant technique, 耐抗技术4 y; E, @. ]8 o2 V) x
R-estimator of location, 位置R估计量
; r9 G7 D0 ~7 Q. u$ y! ?3 Y; FR-estimator of scale, 尺度R估计量
( L( V* ~$ p i0 F5 f8 @% D" x5 ZRetrospective study, 回顾性调查6 {& t* P* \* A+ o0 W) x
Ridge trace, 岭迹
& p) x5 ^: L: k H3 S rRidit analysis, Ridit分析: E* S! p$ {* r" ] K; k
Rotation, 旋转( D8 a B5 o9 T9 ^
Rounding, 舍入. U5 S4 D0 O1 A# X7 W3 `5 R* f
Row, 行 P1 D, U+ ]% e$ v( v; r1 f5 r8 P- Q
Row effects, 行效应$ {( H4 v* s9 J) G( J5 J* o8 A+ ]
Row factor, 行因素
7 @7 i4 y2 C$ |RXC table, RXC表
Z& a I* c# B5 xSample, 样本) j; d2 Y- ]7 A, Z$ W
Sample regression coefficient, 样本回归系数: t; f7 R& E" }, l- [5 Y
Sample size, 样本量
" b/ X0 p/ S+ B- ]" ]1 O c# r3 |8 kSample standard deviation, 样本标准差
' G/ K2 y& O$ Z5 ESampling error, 抽样误差4 ^, g7 x% `! d1 l
SAS(Statistical analysis system ), SAS统计软件包
( @- E$ i! I8 y. ~9 M; `Scale, 尺度/量表# n0 B( y- f: k: ], V- E8 H; O+ Q( c
Scatter diagram, 散点图
! M6 F4 {0 V* _3 R$ ?0 iSchematic plot, 示意图/简图
X/ d7 {! v3 o7 C) V. V# o; ]Score test, 计分检验
( F+ A& o$ U: RScreening, 筛检+ G9 [8 |; V- l. R* t
SEASON, 季节分析 8 N, k7 ^& i$ O. o8 Q- J2 _
Second derivative, 二阶导数. Q' S5 g% a4 l& Q1 b* X0 \1 c
Second principal component, 第二主成分
/ o% c1 y8 b4 M' y# _' pSEM (Structural equation modeling), 结构化方程模型 9 D& Y7 ]7 S$ }' ?! b2 p
Semi-logarithmic graph, 半对数图
1 N' u: q! y+ O: j. [" W5 P7 VSemi-logarithmic paper, 半对数格纸
; g) S- `, X) V K2 g7 e2 aSensitivity curve, 敏感度曲线
+ @8 \! Q3 |4 f: j' y/ ESequential analysis, 贯序分析: r6 }/ V7 r0 w, N. E3 E) Y
Sequential data set, 顺序数据集2 I6 n7 O" o$ o: K( w" i9 M: I
Sequential design, 贯序设计
6 `" A1 A( v$ \# @7 ]) |% |Sequential method, 贯序法5 H* O) c* h( q. p, m( Z" r
Sequential test, 贯序检验法
8 n; s- _+ V U; zSerial tests, 系列试验
6 R: q# O2 z+ mShort-cut method, 简捷法 : W. o* ^, ]( l
Sigmoid curve, S形曲线
+ K j) N4 R. D- S- ^2 VSign function, 正负号函数
( k. N$ @. V3 K/ [# J# CSign test, 符号检验/ X: ^0 g# F. f l0 F4 p5 H& d
Signed rank, 符号秩
; z( `4 S( p* r* C1 q& z) gSignificance test, 显著性检验' ]- F2 a/ {# A# }; K
Significant figure, 有效数字7 v2 ]( K2 W3 |: ]
Simple cluster sampling, 简单整群抽样5 h7 h$ T1 u* b" h
Simple correlation, 简单相关
5 ]; n. {- W, T- A' \Simple random sampling, 简单随机抽样. U2 k$ q, b4 I+ [
Simple regression, 简单回归
3 F$ q( s5 Z) u& qsimple table, 简单表
1 W7 P4 c) R, j+ p4 s8 hSine estimator, 正弦估计量
/ t6 G' n3 q" X- Y9 \ zSingle-valued estimate, 单值估计; ^* m* |, [9 @9 x8 o6 U
Singular matrix, 奇异矩阵. s6 V6 ?% g+ P4 R p2 S
Skewed distribution, 偏斜分布! o0 {: A4 Y" K" ~; `. \
Skewness, 偏度
" A+ V. N; ^3 R# e, L- N2 Y$ iSlash distribution, 斜线分布
3 ^+ r) Q/ t) RSlope, 斜率* O' y# X- h" M L
Smirnov test, 斯米尔诺夫检验
1 [* W. C1 K9 e: V; I9 @Source of variation, 变异来源
6 V, I3 p' X4 X1 rSpearman rank correlation, 斯皮尔曼等级相关
% G N) ?* N8 E: c( V3 m+ eSpecific factor, 特殊因子
$ x5 e' Y4 F3 w5 \- V, @Specific factor variance, 特殊因子方差
' T1 F" N" ?% |8 W SSpectra , 频谱
8 J ~' i9 n% Z: N9 \ M6 E5 u3 `: ySpherical distribution, 球型正态分布2 B5 U& K+ p" I- M8 f+ `
Spread, 展布5 d& l' K4 r3 V
SPSS(Statistical package for the social science), SPSS统计软件包! A9 d4 L, c2 ?7 D/ h5 P0 a
Spurious correlation, 假性相关" x: |# I3 v% @* }* y) I U- P
Square root transformation, 平方根变换0 ]$ r' E% X s4 [0 |6 G
Stabilizing variance, 稳定方差
v- M' @. y7 ~; ^& @6 L. fStandard deviation, 标准差9 n2 Y; i6 k/ N* c p& Z. ?
Standard error, 标准误
3 Z4 c" ?5 Z: x& m9 h4 h* Z/ OStandard error of difference, 差别的标准误
! ~7 @/ c3 q& `Standard error of estimate, 标准估计误差1 r& F% S9 y' ]" P q/ b o+ G
Standard error of rate, 率的标准误$ a7 ~( N) \# W0 K a
Standard normal distribution, 标准正态分布, b! r+ x4 D6 e
Standardization, 标准化* u8 }: Q7 z+ |( |% ~
Starting value, 起始值" Q6 t$ O# x+ J+ W' @
Statistic, 统计量
+ x: Y7 i5 R+ x! p$ x0 C, C+ vStatistical control, 统计控制: D& j! H0 u+ h" F
Statistical graph, 统计图
* O1 E5 C/ j) t$ A9 W/ NStatistical inference, 统计推断
$ Y" F) I; \4 n: `; B6 G. V7 UStatistical table, 统计表
' I0 @. C8 G$ R" G( eSteepest descent, 最速下降法* j* j- C9 l0 o
Stem and leaf display, 茎叶图, M# Y* u+ s7 R* Q& Z
Step factor, 步长因子' m3 ^4 j' {! b! n7 B' S
Stepwise regression, 逐步回归
5 ~9 s2 F2 L, ?/ T( r3 @Storage, 存2 Y G z# \* G- A0 T
Strata, 层（复数）
/ Q$ l5 k, w! @Stratified sampling, 分层抽样
: P' u3 t2 ?: c% bStratified sampling, 分层抽样
" m f3 w$ K- j% GStrength, 强度) |/ E2 H$ x0 Z! j* L
Stringency, 严密性- @; l% k% F$ z1 R2 u- `) W
Structural relationship, 结构关系
; G+ |3 P0 u& E0 m5 CStudentized residual, 学生化残差/t化残差
, ?1 X5 P* `# @Sub-class numbers, 次级组含量
5 x7 t* s: s; R, D% `8 E- WSubdividing, 分割
8 D$ U" W: t8 B& q6 q. z& |8 uSufficient statistic, 充分统计量
3 D& w$ V: R$ s: m% I1 RSum of products, 积和
% I8 i1 N" l7 v' X, k/ l g/ fSum of squares, 离差平方和
4 t+ M9 k- w1 z/ T- }Sum of squares about regression, 回归平方和# R1 N+ Z0 U7 s. j; i
Sum of squares between groups, 组间平方和
2 U [- P7 H/ V9 ?. o* d4 }5 JSum of squares of partial regression, 偏回归平方和* }+ o8 I3 o! c8 e+ j
Sure event, 必然事件
$ U) p% a& F4 Z+ H6 JSurvey, 调查
' x S1 D. c( C6 m, y4 lSurvival, 生存分析
5 J" c2 Q+ L' m1 QSurvival rate, 生存率* _+ S3 S* q K- k7 j1 @/ v& }3 M
Suspended root gram, 悬吊根图0 O, e2 H% W1 f8 t7 Y4 s7 n
Symmetry, 对称
$ B$ w- ]5 S* m) p) uSystematic error, 系统误差' H( q9 f { e. Y2 x0 a) Z
Systematic sampling, 系统抽样+ k* b( n2 o) l; C% G" W
Tags, 标签7 u( @% z" n& P: m" D
Tail area, 尾部面积2 P9 b- y& G. o# t7 D
Tail length, 尾长
! x" Z" y( c: ~- n: [" y7 uTail weight, 尾重6 ^0 \8 Q! b$ T
Tangent line, 切线0 B4 p+ u$ i7 f: \( y. d
Target distribution, 目标分布
8 x2 l8 g$ Z2 F6 T$ Q4 fTaylor series, 泰勒级数+ t* S$ i$ o1 p) H% J
Tendency of dispersion, 离散趋势' L+ c' [: L4 K
Testing of hypotheses, 假设检验1 O: w) ?( n7 A# }7 C( G
Theoretical frequency, 理论频数
8 v, e1 _+ _1 R3 Y( u5 Q' U: z; \' NTime series, 时间序列+ W8 ?9 V* w* N" K8 v
Tolerance interval, 容忍区间
7 P" B" g$ q' t0 J3 FTolerance lower limit, 容忍下限
* m: F/ p% M- k5 [Tolerance upper limit, 容忍上限
9 f& @. p3 O f @Torsion, 扰率; w X2 w+ ?& Y8 n) D" G- L6 y
Total sum of square, 总平方和0 ]) a* E3 h- z' f% \0 m; ^( `7 X
Total variation, 总变异
$ W V' R* \2 g$ D9 gTransformation, 转换
H( C, u. H9 K0 TTreatment, 处理
; W( b. ?% ]& z" S+ i XTrend, 趋势/ g2 N6 w! K5 h2 u2 z
Trend of percentage, 百分比趋势0 x& {( I1 L& @9 g6 \0 B
Trial, 试验
' U2 r" X, A& n1 c4 ^Trial and error method, 试错法" W$ E% j7 q% f: @. a6 @
Tuning constant, 细调常数
) g7 l( i. ^: v2 F3 J: l* PTwo sided test, 双向检验/ p' o8 I8 K8 Z: w7 [1 ?. H
Two-stage least squares, 二阶最小平方
# P: Z( ^& _& s0 l0 L7 OTwo-stage sampling, 二阶段抽样& G$ H( ?. g3 ^; e
Two-tailed test, 双侧检验
+ p' w& [- i1 {- `Two-way analysis of variance, 双因素方差分析1 j8 D4 w& `7 D: Z! N1 R) |, x
Two-way table, 双向表
7 z4 B( S! s [1 J3 g$ wType I error, 一类错误/α错误
) ]0 [5 k1 e$ v( y5 AType II error, 二类错误/β错误 t- e8 D, U; Q h( k* O6 N
UMVU, 方差一致最小无偏估计简称4 c$ X7 c% ~1 ~) m+ C# Y& ?
Unbiased estimate, 无偏估计3 T p1 T) l8 ~; U6 H
Unconstrained nonlinear regression , 无约束非线性回归+ w5 G4 V2 `4 v9 F& W* s
Unequal subclass number, 不等次级组含量 q( f5 a1 d4 K. _7 m% D
Ungrouped data, 不分组资料! E! }+ K9 t. C' ^* k' [1 L
Uniform coordinate, 均匀坐标
) _) N6 j* \9 ?" a2 yUniform distribution, 均匀分布
) `. C* \( M& d. b7 C+ gUniformly minimum variance unbiased estimate, 方差一致最小无偏估计& V3 ~: s# [+ g! N3 ^
Unit, 单元
; h. g _" C# s( D# }1 A0 N6 ^Unordered categories, 无序分类$ S/ ^' W! M1 X
Upper limit, 上限
7 ?+ U. }& S* X6 ?1 S0 W; fUpward rank, 升秩
6 B# B3 _& F; V! `3 n& H/ ^Vague concept, 模糊概念# @& V/ {0 X, U" E# S0 i
Validity, 有效性. H- V+ b; f$ t. A
VARCOMP (Variance component estimation), 方差元素估计- W! k `; l2 V4 K9 L, p
Variability, 变异性: S" U+ o3 c. U" ]' @8 n
Variable, 变量" S4 L: f* u2 t7 g* Q& Z+ E
Variance, 方差
& K& l/ C f( t' G, d8 b% _Variation, 变异* j% X7 s, w/ b( ^2 o' u! X
Varimax orthogonal rotation, 方差最大正交旋转
# U" L& Z* a' A. Q; p* vVolume of distribution, 容积7 g- [8 i; }" v |2 G
W test, W检验
; |; x) t" X: p( [Weibull distribution, 威布尔分布
! |. ^: F8 ~( O8 `/ hWeight, 权数
Y6 V( _) O1 \/ i, l4 YWeighted Chi-square test, 加权卡方检验/Cochran检验
$ j3 N5 a, j( s; v" N$ y5 J5 A# fWeighted linear regression method, 加权直线回归
. f# ~2 F w" n6 N. R" Z7 l5 O2 [Weighted mean, 加权平均数+ E5 C& [' D) j
Weighted mean square, 加权平均方差! j! s. z s, W! g! |2 }1 p; F5 |/ K- b
Weighted sum of square, 加权平方和) R9 \& R0 P! ]1 J
Weighting coefficient, 权重系数
7 X0 }1 j: o5 E, q# ]Weighting method, 加权法 H) a: A) u8 f$ B/ a' G2 A- K
W-estimation, W估计量
6 h- G5 G* y) \$ z0 ~& K0 O# a5 EW-estimation of location, 位置W估计量
" R: k; q: [3 _4 L2 `Width, 宽度
2 s1 g& C6 K6 ]Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验' \: U6 B) S6 M8 u3 b) r: E. @
Wild point, 野点/狂点
( O c7 T* \# s) K1 IWild value, 野值/狂值' Q7 M% F3 g4 o; a# N* j
Winsorized mean, 缩尾均值7 h4 p. B& \/ c
Withdraw, 失访 : x% b5 D) o, l* v2 O+ ?+ u
Youden's index, 尤登指数- A8 J1 J/ S3 y8 v, H# m5 Z! q- W
Z test, Z检验5 t2 E' Z3 b) r5 V1 y
Zero correlation, 零相关
7 C6 o2 }7 G- ~1 g' L. yZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
