|
|
Absolute deviation, 绝对离差
/ i' @6 x4 D' ~9 J( o hAbsolute number, 绝对数% c# F6 t. J' l2 n4 w# j x
Absolute residuals, 绝对残差0 T' l' J6 }/ v6 H/ ^: K
Acceleration array, 加速度立体阵 x& F+ X9 V6 F- y7 D
Acceleration in an arbitrary direction, 任意方向上的加速度
9 `7 C' K" \0 q1 C. GAcceleration normal, 法向加速度 I& t) o T1 X' S% b8 M! f
Acceleration space dimension, 加速度空间的维数* e, m g, n2 {% ~$ t/ a
Acceleration tangential, 切向加速度
6 `* `8 g8 p+ S& q9 yAcceleration vector, 加速度向量0 V. m1 N6 B; ^7 s% J
Acceptable hypothesis, 可接受假设% m% K: x- w- ], A# h% o" V7 i& ~' P
Accumulation, 累积0 h1 F3 b1 d) h$ V
Accuracy, 准确度
" L$ P& [ y' C3 \8 r9 C [+ |Actual frequency, 实际频数
! r- p9 C9 Y: s( b" n/ E' l2 dAdaptive estimator, 自适应估计量" S/ c+ A) X U* t/ E6 `
Addition, 相加
) J) `; a+ S" }- n- T9 F7 pAddition theorem, 加法定理! {5 Y2 l. T: h# O
Additivity, 可加性+ n/ L2 D N3 l( Q$ o3 s% J1 ?9 [
Adjusted rate, 调整率+ E- `* N. E# u; M- t* d' ]
Adjusted value, 校正值
/ I8 _! G/ s5 eAdmissible error, 容许误差
; V% U; `+ ^6 d, W/ Y) I& CAggregation, 聚集性5 ~' [ m/ B+ J
Alternative hypothesis, 备择假设
* o8 U0 }1 y) C' \3 D# |Among groups, 组间
. D& r$ f- N2 s: ^ F! ]3 QAmounts, 总量# k4 x" S5 ?6 X* m
Analysis of correlation, 相关分析
& H3 B/ D" W* p' Q) N b; ]Analysis of covariance, 协方差分析& ]( g2 c: g/ m* X( v ^
Analysis of regression, 回归分析+ ~9 f& G, b( a) ~' k5 v* T x
Analysis of time series, 时间序列分析* x+ i3 P( b8 C7 J ^2 _
Analysis of variance, 方差分析
6 s0 M+ a1 z6 n' KAngular transformation, 角转换; u4 C" a' {7 E- I+ B* {% u5 |5 K
ANOVA （analysis of variance）, 方差分析" s- [3 X/ n5 Y- K* J- C
ANOVA Models, 方差分析模型5 z1 l% w8 e6 S' F7 V6 J- K
Arcing, 弧/弧旋/ e4 Z( M3 i/ l$ S
Arcsine transformation, 反正弦变换
$ p! y( a: D Z# wArea under the curve, 曲线面积
8 N: y8 M/ L8 Q2 U4 RAREG , 评估从一个时间点到下一个时间点回归相关时的误差 4 [" @' \9 o* q( o1 a! h k
ARIMA, 季节和非季节性单变量模型的极大似然估计 $ p) e# b D" x6 A+ Q, W
Arithmetic grid paper, 算术格纸
; @, f6 P* o4 `5 PArithmetic mean, 算术平均数
. r6 M) ~- J! ^5 {) C3 gArrhenius relation, 艾恩尼斯关系
2 b7 E9 u! P- l+ m: ^Assessing fit, 拟合的评估 R+ h* M6 ^ G0 |% @+ S
Associative laws, 结合律
, {# [; V' e, q5 [0 jAsymmetric distribution, 非对称分布% G. l. k( O$ K! K U
Asymptotic bias, 渐近偏倚
* R' k6 s' j5 j7 d$ z) b: U- w/ ?Asymptotic efficiency, 渐近效率
r, m% z: F( R- l, T2 Z( j/ V! |( s+ vAsymptotic variance, 渐近方差
& c0 G; g# ~" B! ~Attributable risk, 归因危险度
! k9 \9 D9 `: Z$ jAttribute data, 属性资料! E c9 `4 f4 y& n4 ^! S$ R8 a
Attribution, 属性- z3 A' a: R5 c
Autocorrelation, 自相关; _" ^: H9 X& M7 w
Autocorrelation of residuals, 残差的自相关
# ^, b- |$ {7 r2 XAverage, 平均数
2 j: |; _. H, }8 uAverage confidence interval length, 平均置信区间长度
/ B5 Y* G+ E; R( u+ b5 D3 `- wAverage growth rate, 平均增长率) h* h* D$ Y! `- P
Bar chart, 条形图
: A$ |: N' S9 e/ y- w1 \/ n# fBar graph, 条形图, i) M5 b( l" _; M2 A6 v. b+ [" E
Base period, 基期
( ^" w. R* }9 c: @- dBayes' theorem , Bayes定理
7 s# z2 F8 n1 @- g( QBell-shaped curve, 钟形曲线
( X6 x }! x9 U6 n4 p/ J" Z. p/ [Bernoulli distribution, 伯努力分布
) Z7 c! L2 h5 |5 ?5 w4 a7 O+ ~4 NBest-trim estimator, 最好切尾估计量
2 r7 g( z6 c$ j* ^Bias, 偏性
- V/ S' }2 n. g( `Binary logistic regression, 二元逻辑斯蒂回归& T( q- R- P8 T4 S* L6 ?8 i* o$ V
Binomial distribution, 二项分布 ^- ]* H, i4 `
Bisquare, 双平方! a' V$ s4 _2 G
Bivariate Correlate, 二变量相关! y; B2 t; Z3 Y1 H/ G4 W' P1 ~
Bivariate normal distribution, 双变量正态分布
* N- L' ?' U; a( i+ ~Bivariate normal population, 双变量正态总体
( F+ e" w% s5 D1 G3 [" rBiweight interval, 双权区间2 y. i7 M9 v: O6 U: I
Biweight M-estimator, 双权M估计量
$ n& c- t' ?5 EBlock, 区组/配伍组
& c' @( r, w! `BMDP(Biomedical computer programs), BMDP统计软件包' I# s1 P1 o# {
Boxplots, 箱线图/箱尾图
- a$ d: V% w3 Q! r4 aBreakdown bound, 崩溃界/崩溃点
8 o1 m5 b1 m* c" ~8 C; eCanonical correlation, 典型相关
0 b8 X j ]& ^; [2 BCaption, 纵标目
! A+ L8 Q0 _* }" u: y% FCase-control study, 病例对照研究" |$ h' X7 ^: u. D! U( O7 P
Categorical variable, 分类变量! S& ^1 u v6 N
Catenary, 悬链线" d0 j1 x. `% ? _2 k8 z
Cauchy distribution, 柯西分布
! F' E2 p6 _; j. z2 N, v" z! oCause-and-effect relationship, 因果关系9 x! K# C1 a3 p- P# H& P
Cell, 单元) k: d) x0 s3 M# T! i
Censoring, 终检+ J3 {; ~- F" E! l# s, |
Center of symmetry, 对称中心
' E9 \. Y z: l4 t; [Centering and scaling, 中心化和定标
2 z- l% s/ E1 |; V1 D2 Q4 I' xCentral tendency, 集中趋势) G& @4 a& ~. H" f% B
Central value, 中心值
+ ~0 A l" P, V. B& T* QCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测" M& S9 ^% ~7 O6 [
Chance, 机遇
, J" Y7 L4 h; K1 V, t ?Chance error, 随机误差
8 c2 V W! R. ]# U% c OChance variable, 随机变量
6 J7 D% _0 C2 }" q* eCharacteristic equation, 特征方程
$ n6 Q: \+ u- A) b8 qCharacteristic root, 特征根
- }) m1 M) V. a5 h$ d7 j; bCharacteristic vector, 特征向量
% T. ]6 H4 G; J! ?% TChebshev criterion of fit, 拟合的切比雪夫准则
% N6 c9 O% Y6 p3 A+ t4 C7 PChernoff faces, 切尔诺夫脸谱图
, Y0 X- r# H1 W5 i2 M2 o5 B" K( fChi-square test, 卡方检验/χ2检验; v# L4 N5 @% n$ W/ W
Choleskey decomposition, 乔洛斯基分解
- w n4 i: j. }Circle chart, 圆图 & m5 Q5 g+ Z% h5 m$ u0 Q3 c
Class interval, 组距; q- a9 n( A" B$ U( H, D
Class mid-value, 组中值2 P) \; }0 O" f, J
Class upper limit, 组上限# g7 C" f% Z3 I' T) Z, _6 ~
Classified variable, 分类变量( o+ j3 T* e1 D! E. l
Cluster analysis, 聚类分析
" Z6 a# F. C9 DCluster sampling, 整群抽样) ]$ l3 Y- ~( ?: \
Code, 代码; Y# p6 e6 r; p
Coded data, 编码数据
+ m5 N- U& J2 l1 ?0 F# l) JCoding, 编码/ T L; X7 s/ f: T' v
Coefficient of contingency, 列联系数+ g8 M0 \1 N5 R& a# W; H7 |
Coefficient of determination, 决定系数
8 w% G+ j( Z P; J3 HCoefficient of multiple correlation, 多重相关系数) G) s/ b0 U9 B4 j
Coefficient of partial correlation, 偏相关系数
0 i2 Q* J: ], {Coefficient of production-moment correlation, 积差相关系数
* k$ H/ a( L! I) NCoefficient of rank correlation, 等级相关系数
3 \# d3 O& z9 V4 s2 o/ tCoefficient of regression, 回归系数. Q% E" M) {7 A& i/ F/ m j* f
Coefficient of skewness, 偏度系数- z/ h! t4 U1 `- A) h
Coefficient of variation, 变异系数+ F) x8 }' _7 ?: w: H) y& e. y& d! D
Cohort study, 队列研究8 p9 v* _8 S) i% {; O* w
Column, 列% J; P& T' ~1 _: ?9 B
Column effect, 列效应
/ K# t: M! Y1 f+ C( jColumn factor, 列因素
; p' b* G8 d! k$ Z# `4 mCombination pool, 合并
6 `+ m* R# _2 _7 r9 S0 sCombinative table, 组合表
) ?5 f6 ~" ?8 j" E8 q3 I; e0 ]Common factor, 共性因子
N) l% m+ s) e0 |! [Common regression coefficient, 公共回归系数
9 e7 e) n9 F5 SCommon value, 共同值2 G$ r# }3 _" [8 s" l
Common variance, 公共方差
2 J2 G) G: L1 _/ o5 cCommon variation, 公共变异) K9 I1 S# h2 Y- z5 C" n$ q
Communality variance, 共性方差
5 v7 Y- w3 B" V" lComparability, 可比性
a6 X5 F4 }* e* rComparison of bathes, 批比较
( u$ B8 e7 @3 F8 A5 c" sComparison value, 比较值
& @. _; C4 k3 B- ?# e% V: |Compartment model, 分部模型
' ?: m8 b2 W- `Compassion, 伸缩
" {+ Y+ m. O4 f) j, a: j* [Complement of an event, 补事件2 X4 B q0 j( k6 |- E
Complete association, 完全正相关
, J4 W, D- E6 F9 sComplete dissociation, 完全不相关
- H/ Q8 _% o5 `& b" YComplete statistics, 完备统计量
6 C3 B0 w) _) U; L$ M& hCompletely randomized design, 完全随机化设计
, w4 _+ f( z) A, ^* zComposite event, 联合事件
( ?& Q# K$ H. }Composite events, 复合事件
% E6 D6 B2 R! E$ q8 A. t1 W5 I; eConcavity, 凹性
3 ]7 m9 }. _! T" u$ kConditional expectation, 条件期望7 M+ r- z w1 ?' A1 ~5 u S
Conditional likelihood, 条件似然
/ E9 U0 P8 R6 H5 x D! L/ nConditional probability, 条件概率
& V- a6 G/ |$ J+ uConditionally linear, 依条件线性( R5 C; ^' J; r; v4 O
Confidence interval, 置信区间$ ?6 L; C& A! F! O( l, t! a
Confidence limit, 置信限
3 Y$ ]* k: B# x8 {: `4 TConfidence lower limit, 置信下限( ~- R" g! F5 u+ ^$ z4 @
Confidence upper limit, 置信上限
$ Q( `! b9 @/ Z, cConfirmatory Factor Analysis , 验证性因子分析! g3 {) {/ d9 `% l+ _
Confirmatory research, 证实性实验研究
9 U- B* z& _4 i' a' \2 R+ G" EConfounding factor, 混杂因素3 i J0 v, V! R
Conjoint, 联合分析% R( X$ G0 q$ \3 `2 H2 q
Consistency, 相合性
* {* A' ?6 h1 qConsistency check, 一致性检验
9 p: F: z% \4 e4 Z1 h% \( ^4 x( zConsistent asymptotically normal estimate, 相合渐近正态估计1 }/ I; L5 W5 }
Consistent estimate, 相合估计, k) X3 h3 |9 T6 ~" u0 ^5 U
Constrained nonlinear regression, 受约束非线性回归
- u0 |- ~$ G6 ~8 g/ m' i+ SConstraint, 约束; z6 j2 {! ^# P& z, Q/ ]# f1 B A/ g! H- T
Contaminated distribution, 污染分布
8 c1 N2 U' y$ K/ G% W& aContaminated Gausssian, 污染高斯分布
9 @' B5 \) S1 E8 a cContaminated normal distribution, 污染正态分布# \- U Q4 n7 H& K
Contamination, 污染4 E8 O2 Z! x' Q/ `2 i
Contamination model, 污染模型
; c* F% S# j' ` Q- wContingency table, 列联表1 h% P7 v5 W S' E/ h; B
Contour, 边界线7 w, R5 Q/ u2 l. d* M( I: J9 A2 n
Contribution rate, 贡献率
( v& d( y2 {' Y9 E2 u3 `+ N4 o/ Y: nControl, 对照: t0 O' X+ \: d4 P. V& x+ `. C
Controlled experiments, 对照实验3 d4 u, U; [- e0 _! I5 P) n
Conventional depth, 常规深度9 I2 d. B8 w0 z+ n1 l! g$ c' v
Convolution, 卷积9 `% t6 j: @2 j9 L$ Y: D- G7 w7 k
Corrected factor, 校正因子
, O) c$ V# o( A8 R4 b3 Z0 uCorrected mean, 校正均值' j1 O7 M9 i) `$ y8 p% Y# \
Correction coefficient, 校正系数9 t* w- Y8 h, Z: z! Z
Correctness, 正确性
1 \% p5 J3 @5 t* _5 PCorrelation coefficient, 相关系数
: T/ @6 B ^. B, YCorrelation index, 相关指数+ `9 r" x) T6 P0 h+ X/ y, i; N
Correspondence, 对应9 G# d d7 M- c+ w1 a9 D
Counting, 计数% I7 [. B1 R/ K! G# g/ P
Counts, 计数/频数# m: C0 ~) X! u( H) I6 o1 S
Covariance, 协方差0 @9 u& X0 U2 m5 j' `1 I
Covariant, 共变
' z4 }0 g- J9 p* K4 M/ ^Cox Regression, Cox回归, ]9 X$ r, O8 ]- d! t% P' C
Criteria for fitting, 拟合准则3 O- L1 H. m$ e Q7 Q7 z7 \
Criteria of least squares, 最小二乘准则
9 x( X. N; N* d/ rCritical ratio, 临界比
8 g: s u. z& n7 [$ vCritical region, 拒绝域
/ O' Q, y. E+ {& T) FCritical value, 临界值) ]! z4 D& j7 u* x( i) q
Cross-over design, 交叉设计
5 P& ]1 t0 @2 HCross-section analysis, 横断面分析
, I" h2 s1 s% YCross-section survey, 横断面调查
$ u. [2 }0 a4 q3 r1 [5 RCrosstabs , 交叉表 0 g7 A# }9 e7 b8 ?
Cross-tabulation table, 复合表" a+ R! [. |: p; ]7 L; b9 C
Cube root, 立方根" A4 H( \; ?% u" A- K. b6 q
Cumulative distribution function, 分布函数
0 C6 I, W" z+ o# v8 L0 y7 X6 m1 uCumulative probability, 累计概率
; J7 ~3 o' d. l* x4 |* N# a4 lCurvature, 曲率/弯曲4 Q0 ^3 f, q# y2 f% K
Curvature, 曲率- N% s: X, ]* |6 u
Curve fit , 曲线拟和 ( a+ F3 r' d: [( g! U1 D7 H7 C
Curve fitting, 曲线拟合3 k/ x/ n3 b5 |7 `8 R
Curvilinear regression, 曲线回归
: n1 }& } }4 O- @' l6 y) T* cCurvilinear relation, 曲线关系" M3 }3 i6 S* O) j
Cut-and-try method, 尝试法
g+ o( ~4 q' V( W7 l: j. x" H0 BCycle, 周期/ h; t3 |0 b3 I
Cyclist, 周期性. h) c6 O& A; [. W0 D' p0 G1 Q
D test, D检验
8 ?: @2 S7 i( v1 ~* dData acquisition, 资料收集9 m( k3 f1 C8 t* }1 e
Data bank, 数据库9 ~0 @3 I& n* Q" ]+ E" @5 H: F+ }
Data capacity, 数据容量: q+ F' Y# j; Y* s1 T. |0 @& z
Data deficiencies, 数据缺乏; P6 y& |, w4 G( A; L
Data handling, 数据处理
0 _3 U, a4 m' x! c( nData manipulation, 数据处理
4 `4 [; g3 S# B% B9 \3 U) ~3 nData processing, 数据处理
7 a/ o" u. s3 B$ c4 C/ CData reduction, 数据缩减" E% ]& t) a0 L3 R
Data set, 数据集# \$ G. }- z0 X# r* `
Data sources, 数据来源
+ Z4 ~+ S) E9 u% g1 L" UData transformation, 数据变换) P5 H X3 ~# W# M0 b
Data validity, 数据有效性
* o" E( b4 V1 I/ kData-in, 数据输入
2 j8 r! c) p2 P7 W3 N( hData-out, 数据输出
' p3 M) e K: p, ?/ K1 Z5 }2 s* wDead time, 停滞期
8 C* B1 I% q' x9 f# IDegree of freedom, 自由度1 |, x; i3 M9 w4 Y: u: `4 U: U1 s
Degree of precision, 精密度
, D6 l# `& W- a" S9 rDegree of reliability, 可靠性程度
$ e: M4 ~. G9 f* V1 ~Degression, 递减
5 u% l+ w- v+ U( V$ ^Density function, 密度函数
- x" O. N) Y; f* }0 R( e* S" GDensity of data points, 数据点的密度
4 B. y0 ?+ K$ R+ SDependent variable, 应变量/依变量/因变量
7 i) Y: q! \# J6 P: a" jDependent variable, 因变量
, J7 @" q3 R ]+ y: PDepth, 深度$ }. ~0 y. H# v5 X5 H" n b
Derivative matrix, 导数矩阵! X' M8 C+ G- k' N# Y# L/ S. Z: x
Derivative-free methods, 无导数方法- A6 {- x8 P0 X/ g
Design, 设计
! ^8 j r2 x' P$ ^" nDeterminacy, 确定性2 W) B' H5 D1 ^* E( w
Determinant, 行列式) m7 p& j8 ]2 z w. o
Determinant, 决定因素7 L/ j5 Y( n2 ~- @& V- T( @
Deviation, 离差
6 H3 r v8 a6 k$ C% ~% vDeviation from average, 离均差
5 _( f/ ]/ F/ Q0 Z; h- Z8 WDiagnostic plot, 诊断图
' ^7 T& c8 h. F& i8 E+ @/ tDichotomous variable, 二分变量
' }5 o) N5 Z5 T. Q* |2 w" i" u8 ~Differential equation, 微分方程
7 r% m( o3 D5 b# v" B2 }* MDirect standardization, 直接标准化法, ^! d0 h$ [. U
Discrete variable, 离散型变量
& R7 y# V2 S" M) K: EDISCRIMINANT, 判断 " j$ t9 O* f; A
Discriminant analysis, 判别分析
( N. E) `. w1 ?! s! x7 Q+ Z! eDiscriminant coefficient, 判别系数1 ?8 `6 t2 Y9 h9 U! `+ [1 ~6 \
Discriminant function, 判别值
+ [9 `- P& X- o6 Z# U' bDispersion, 散布/分散度! A5 Q4 \. I( }# I. y b
Disproportional, 不成比例的
, v/ \% T8 V6 F, F4 B! ?: W3 ]Disproportionate sub-class numbers, 不成比例次级组含量
$ i* D% k' x4 Y* \Distribution free, 分布无关性/免分布
$ H* @4 _# m% |. l" l; q% C8 J" zDistribution shape, 分布形状
( e) ]$ l+ n$ _1 PDistribution-free method, 任意分布法
/ b5 S3 |" o) I1 U1 zDistributive laws, 分配律# w9 E8 g3 u$ ?5 d* {# s4 [( p( F' e
Disturbance, 随机扰动项% f1 F: d4 h. ^8 a9 l
Dose response curve, 剂量反应曲线
. C8 b+ n# ?" p4 b9 ZDouble blind method, 双盲法
7 ~' V" [6 h" Z8 _2 |- zDouble blind trial, 双盲试验
{ w3 W4 T- h. n9 `Double exponential distribution, 双指数分布( k6 }) p6 S J! F' F
Double logarithmic, 双对数
( \; {7 v9 @- _0 SDownward rank, 降秩
" x; G2 t4 G: ?+ |5 sDual-space plot, 对偶空间图
$ V) `9 M6 i5 l) C* ]4 NDUD, 无导数方法5 F& l/ M+ h: b0 _
Duncan's new multiple range method, 新复极差法/Duncan新法
0 x3 \; M8 R0 Q: |8 G& V! ]$ l PEffect, 实验效应, V) }3 Y" C: x$ x
Eigenvalue, 特征值
# K0 J. s4 b8 p" H) m3 P1 m* bEigenvector, 特征向量
$ v( W+ e2 N1 w7 O' yEllipse, 椭圆
3 f8 o1 Z, p/ b- e6 S) P" uEmpirical distribution, 经验分布0 J* V$ K6 a& @$ B, ^
Empirical probability, 经验概率单位$ N" b6 {* s) B- s4 ?1 x
Enumeration data, 计数资料( `0 y4 N7 ^ \* ~9 g
Equal sun-class number, 相等次级组含量4 P8 g% k+ _% y) ?) d1 D& m
Equally likely, 等可能
K1 l! P/ P8 b0 W# o1 Z# ]: c% m9 `Equivariance, 同变性
) f6 h+ b5 k; pError, 误差/错误
2 c5 \ L- X% s. ^4 DError of estimate, 估计误差/ S; J: U& r8 d2 b7 q
Error type I, 第一类错误* _ u/ D& w; W$ I' S1 B6 H X0 `
Error type II, 第二类错误# Q8 X" z- i2 e5 m* q- E
Estimand, 被估量7 J& Z5 _3 l8 I7 D0 ?0 }+ }
Estimated error mean squares, 估计误差均方0 P \% g; T ~: C4 e0 a/ g+ s
Estimated error sum of squares, 估计误差平方和
) F+ r, w9 G9 v# i, Q* CEuclidean distance, 欧式距离
7 K J; q% C- _! R0 tEvent, 事件7 j6 _. O1 _" n& q1 F
Event, 事件
8 f5 A$ |+ F* N9 C9 eExceptional data point, 异常数据点* k6 m3 v8 n4 I5 [. L6 O+ I
Expectation plane, 期望平面& C5 I7 K' O | _' F
Expectation surface, 期望曲面& N+ j. u& O6 {
Expected values, 期望值8 `! S! x5 \+ J6 q
Experiment, 实验
" x9 t: i9 M, t( C9 XExperimental sampling, 试验抽样3 ]- ?# N# Q' O5 Y
Experimental unit, 试验单位" W4 Z! ~' C( H- _
Explanatory variable, 说明变量+ t5 h6 ?- s1 H. [! n4 h
Exploratory data analysis, 探索性数据分析8 T) h! f! q) S3 N- k% _
Explore Summarize, 探索-摘要
' p; P) a: g1 Y% V6 pExponential curve, 指数曲线
9 n8 x* g; b) ]7 y- uExponential growth, 指数式增长
) k& z6 ~! `% _! C! u$ W2 QEXSMOOTH, 指数平滑方法 ' B$ D! ]5 o0 H- B2 E' o. ^' _
Extended fit, 扩充拟合) I& b% ]: U ^
Extra parameter, 附加参数* H- E9 I7 x% b! S+ e$ `3 ?
Extrapolation, 外推法
( b3 w5 ^+ J% Y ?2 Y0 aExtreme observation, 末端观测值
- \) W5 g- e5 r( _: P: e* R% z# eExtremes, 极端值/极值- a% C3 |" H, D6 w! U4 w. t
F distribution, F分布1 o& X- J( b, E" k/ a5 z- z/ v, I
F test, F检验4 W: c$ I" X3 W* m$ y Y* L
Factor, 因素/因子* v0 p: D- A# R( C V+ h
Factor analysis, 因子分析
: W P, m: X2 j* M' sFactor Analysis, 因子分析1 k" J, A8 S% C+ @7 D, D
Factor score, 因子得分
- m1 T. s5 p* n" ] P# AFactorial, 阶乘
. _5 @$ a3 y6 W V# L7 D6 n% q3 yFactorial design, 析因试验设计
/ B9 D$ W5 o) a$ B. N2 W) D9 c6 _False negative, 假阴性$ u+ t- a% Z$ Q- ]2 J6 N& |2 x
False negative error, 假阴性错误
) E: ]+ |! @9 @: MFamily of distributions, 分布族
. ?6 z+ \; j- {1 b+ s$ pFamily of estimators, 估计量族
2 j0 [; |6 R* rFanning, 扇面/ q2 f. G$ v8 g+ O$ ^! ^
Fatality rate, 病死率
' k5 q9 k" N1 Q6 Y8 z% U( @, eField investigation, 现场调查
: b, L0 o8 x5 v( @3 S$ P) B8 Z: `Field survey, 现场调查% ]0 W4 \6 Z7 D: s6 Q* L# {8 [* H
Finite population, 有限总体
- G" x6 a+ C9 Q% q1 n, UFinite-sample, 有限样本+ ~- L5 f: I7 O
First derivative, 一阶导数
) N R" T# J$ s9 u; [! O1 q/ mFirst principal component, 第一主成分
' B; a4 p* K' |+ P* S VFirst quartile, 第一四分位数
! _- W& B9 K0 W/ z( Q: V; XFisher information, 费雪信息量
' I! {' a D! h7 g0 PFitted value, 拟合值
" z: C' K$ w2 T! o6 ~8 gFitting a curve, 曲线拟合
* y& L+ F, G+ _! f& tFixed base, 定基
8 C! m/ k; g. J1 XFluctuation, 随机起伏6 ^, t! o& z* D, h/ @% ]& o! Y
Forecast, 预测* q) U" M. d% T: g, x
Four fold table, 四格表
3 F% ]7 c5 f! i- b9 N8 nFourth, 四分点, V' ^1 L' S8 y! s& Z/ k
Fraction blow, 左侧比率" b& M5 j1 y. m( [- l* p6 d
Fractional error, 相对误差
1 M6 d, l/ Q V$ A) f XFrequency, 频率$ k$ S$ Y4 B/ j; n! p) P6 h
Frequency polygon, 频数多边图5 M2 o) R0 o( J
Frontier point, 界限点- N6 I: Y" _6 E3 h% y
Function relationship, 泛函关系& j! u& A* M1 ]6 m( I& X! o# a
Gamma distribution, 伽玛分布! z* j$ z6 N$ b: L' S
Gauss increment, 高斯增量7 Z! L2 w# g% x
Gaussian distribution, 高斯分布/正态分布
3 d' ^: S2 ^& ?( ~* aGauss-Newton increment, 高斯-牛顿增量
3 u( q! j/ C9 H5 o( Y+ ?: CGeneral census, 全面普查
3 M" H2 c' Y: \2 ]7 KGENLOG (Generalized liner models), 广义线性模型 / h$ p$ l# I1 y0 J/ E
Geometric mean, 几何平均数1 G$ {' Y O: e
Gini's mean difference, 基尼均差
( V b$ F) ?8 X( o* I xGLM (General liner models), 一般线性模型
2 ~+ f" G3 e6 ^# _, RGoodness of fit, 拟和优度/配合度& n" n8 a( L4 K- y) e! t1 p
Gradient of determinant, 行列式的梯度, {3 _4 A' G2 U E* s5 n, e
Graeco-Latin square, 希腊拉丁方 z- e, q2 i/ B3 o" y. m# S) Z
Grand mean, 总均值/ h1 ^9 R* m6 e+ e& g
Gross errors, 重大错误
- B# P, a4 Q- F- m* V+ {Gross-error sensitivity, 大错敏感度3 V9 ]0 F0 k- V
Group averages, 分组平均2 R5 e! D. c; e5 f
Grouped data, 分组资料8 b: k: X, ^ p: M/ @0 ]7 W0 q7 Z
Guessed mean, 假定平均数' f/ f; J6 d& B6 T7 s" o
Half-life, 半衰期
# g4 W5 P$ [, d1 o, S6 E+ t/ bHampel M-estimators, 汉佩尔M估计量
' |$ Y# I! N% v; ]' G2 yHappenstance, 偶然事件 U7 h; l( N6 X2 J
Harmonic mean, 调和均数5 T9 S$ k5 _6 k. C6 v. j
Hazard function, 风险均数4 T4 R* F% j2 Q* `/ c }$ d
Hazard rate, 风险率7 M' q( k7 m9 J/ m& h7 J: P( z4 S
Heading, 标目 " `, | p- s6 O7 A! I1 L
Heavy-tailed distribution, 重尾分布& v/ B' A9 U! t5 N9 }+ Y8 {! K, u
Hessian array, 海森立体阵
+ t* n' \/ T% ?, z4 ^Heterogeneity, 不同质1 v. f" A+ s8 S& n6 b
Heterogeneity of variance, 方差不齐
0 a3 n; v% g" G! s4 n; a, c# sHierarchical classification, 组内分组
2 ], ~8 F3 X& X, ?Hierarchical clustering method, 系统聚类法
6 c+ w/ T8 Y2 eHigh-leverage point, 高杠杆率点, u& h( P" g" {+ y8 t
HILOGLINEAR, 多维列联表的层次对数线性模型
# l( B; T1 e) b/ d# d3 p8 q% v% qHinge, 折叶点, `6 H; E0 Q" Y( N( U$ t" J
Histogram, 直方图1 Y2 m- Y- P: ~% ?4 v
Historical cohort study, 历史性队列研究
% y: a* \( R6 D* ]+ I6 H0 V$ zHoles, 空洞
) m3 l( ]& n5 _1 X, n; S: NHOMALS, 多重响应分析$ O' j. [* R5 }' _/ m
Homogeneity of variance, 方差齐性
" i" k' u/ N" A5 r6 r' EHomogeneity test, 齐性检验
4 Y* u/ _! j8 H8 G0 Z1 S6 P0 N+ CHuber M-estimators, 休伯M估计量
- c0 }0 `$ F( K3 }' SHyperbola, 双曲线
5 K1 G$ b a" Y% T" n) [* PHypothesis testing, 假设检验
# ]# d# i. |& U' xHypothetical universe, 假设总体/ ]3 J5 U' C$ W* ^2 Q# c" J/ j
Impossible event, 不可能事件
* v; i2 z" @4 e% y( AIndependence, 独立性
1 A5 A+ {0 K' p7 u+ F3 SIndependent variable, 自变量
% B: F6 }$ u5 {Index, 指标/指数
/ \1 N/ s2 y5 s- H) q7 HIndirect standardization, 间接标准化法
- b1 k) M+ g1 E0 Q" L9 d+ }Individual, 个体
5 R( `% x! _! ZInference band, 推断带$ P9 Q4 [1 ?2 a: M% H
Infinite population, 无限总体
/ k3 p) A7 |+ C' [5 [Infinitely great, 无穷大
) ~: `# ]) O; _8 Y' UInfinitely small, 无穷小
) W! r5 n) I) V3 [: E3 |Influence curve, 影响曲线: i7 c% ^& O& b d* E6 G0 X& e
Information capacity, 信息容量
) e' I. h; r3 E' c% \Initial condition, 初始条件
; Z3 f; K( t* n8 h$ V5 yInitial estimate, 初始估计值) b% I# L5 O+ ~( [3 n
Initial level, 最初水平- L) H$ f4 t7 S- f& Z1 d. _+ ^) t
Interaction, 交互作用4 l4 x8 e7 Y! s) V1 j- `
Interaction terms, 交互作用项
7 {. V* ?" s$ E6 q/ E/ H4 jIntercept, 截距1 K5 Y g7 [& M/ D; F
Interpolation, 内插法' |2 u/ x+ H. l& f D+ r( u% h
Interquartile range, 四分位距
5 {) E- @" B/ {( FInterval estimation, 区间估计
- C, h) X5 _* H; T) s* C% g3 wIntervals of equal probability, 等概率区间
) ?2 \3 l9 j6 c' u* jIntrinsic curvature, 固有曲率) u- ^7 R7 @1 `! x1 G) W5 D, p% z9 B
Invariance, 不变性5 S! Y: ~9 k3 h" u
Inverse matrix, 逆矩阵1 c( I! w# I* b+ i5 @1 E5 B9 j' J
Inverse probability, 逆概率% K3 N/ h' z* ~0 E
Inverse sine transformation, 反正弦变换
- R5 I2 ?; l# {' a" ]Iteration, 迭代
9 U G# V, T3 J9 q2 ~3 U1 ^# gJacobian determinant, 雅可比行列式5 P7 O7 n& Y# O1 ~& v
Joint distribution function, 分布函数
0 ]- R" M% P+ t) M* hJoint probability, 联合概率$ i# b( q5 l# i7 A B# q
Joint probability distribution, 联合概率分布
; Y, T$ S+ k, ]8 j% n- HK means method, 逐步聚类法
0 q I* A$ n1 B7 L3 H% L& b% r2 wKaplan-Meier, 评估事件的时间长度
. h( a# {% a. ?/ H% p) L) `) L) TKaplan-Merier chart, Kaplan-Merier图
) a! W# I9 h: [+ ]Kendall's rank correlation, Kendall等级相关
0 a. d' }0 \3 n" bKinetic, 动力学
. y- |7 O& o9 [" {* T8 F0 @7 G8 ~, |) yKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验& o1 Z G" ]- e# f
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 W( r. d/ b) b2 r$ p
Kurtosis, 峰度! o: M- ~' ~# `' ]; ?; ~
Lack of fit, 失拟9 I+ a8 D: j- X* V. H6 X
Ladder of powers, 幂阶梯/ `6 O" }* D( c
Lag, 滞后' E% A* S) Q" X
Large sample, 大样本
' r: ]4 R- `* c) s2 U5 ^' ?Large sample test, 大样本检验
0 b9 c4 ^' n! s) D0 f; ULatin square, 拉丁方! ?& w2 r! p1 m
Latin square design, 拉丁方设计
J: v2 G0 n8 y: |+ t6 \Leakage, 泄漏0 s9 }/ N/ `7 _: X( k: m; L3 l2 B
Least favorable configuration, 最不利构形
- c3 u# t; n$ lLeast favorable distribution, 最不利分布
. ?! L. g" R" g/ k' n( pLeast significant difference, 最小显著差法
8 i, R/ C. i e) H9 z( g* B- Y) [Least square method, 最小二乘法
( T: C% j8 z) T+ QLeast-absolute-residuals estimates, 最小绝对残差估计" p" T; m* h4 j& y1 ?( g2 h/ t
Least-absolute-residuals fit, 最小绝对残差拟合
9 }5 e% e8 }0 Z# O6 ELeast-absolute-residuals line, 最小绝对残差线3 z f3 i3 R) J3 y( n, [# n9 i
Legend, 图例
. W* Q7 Q8 |$ F2 r; L9 qL-estimator, L估计量& q' A4 d+ x0 t
L-estimator of location, 位置L估计量* V& l2 z! ]5 P0 K' n; A: D
L-estimator of scale, 尺度L估计量
) {' x8 [; n% KLevel, 水平3 U' w: x/ s' s: U M
Life expectance, 预期期望寿命
3 r" D& I ?+ ^# o0 c6 SLife table, 寿命表
2 f; q; I7 R: Q$ NLife table method, 生命表法
) l# I% }, k+ g, ^% LLight-tailed distribution, 轻尾分布
1 w' }$ c6 j$ _3 m; \0 wLikelihood function, 似然函数
4 E* T* J/ {: J$ P/ a4 {: a( Y, M" cLikelihood ratio, 似然比
1 w$ x4 R0 z+ V- w' i( d. pline graph, 线图6 h6 I: H& I8 l' ~& q0 B4 s$ S# h% n1 i
Linear correlation, 直线相关
# S; Y1 N" q2 F& Y7 @Linear equation, 线性方程
4 ?' Q( N, z' r7 S% J) n" _Linear programming, 线性规划
, q* `( O0 e0 a0 BLinear regression, 直线回归
0 z! w+ b- j7 VLinear Regression, 线性回归7 y. F2 a8 z0 T1 g
Linear trend, 线性趋势# H+ M6 H7 m( w! ?" i& ~
Loading, 载荷
: J8 D$ h, ]8 I1 i! y6 h6 nLocation and scale equivariance, 位置尺度同变性- V$ W# n& S; Y1 D8 d: M D
Location equivariance, 位置同变性, O, R4 W6 A! Y5 y$ n
Location invariance, 位置不变性3 H# J/ A) U, I: m& l
Location scale family, 位置尺度族2 j. R3 F5 q H5 [$ v4 e, x$ H
Log rank test, 时序检验
: O K, a( ~8 A9 F9 fLogarithmic curve, 对数曲线
# ~2 |) e$ R. N: N+ o( f; T! PLogarithmic normal distribution, 对数正态分布- m& F. @: b( t! g7 X5 n
Logarithmic scale, 对数尺度
6 @3 u, R2 w. \; A7 I5 j- tLogarithmic transformation, 对数变换
4 P, _; n1 T' @Logic check, 逻辑检查. E4 f% C) k+ x k# O
Logistic distribution, 逻辑斯特分布
' I8 w6 U! g5 [* Y j3 S2 l2 \/ |& uLogit transformation, Logit转换
! P3 v! \) r) t A- DLOGLINEAR, 多维列联表通用模型 3 ?' d* t4 J8 c# J
Lognormal distribution, 对数正态分布
& f! o* P$ [4 _& k( ]Lost function, 损失函数7 w, C5 Q8 L4 f, |' j
Low correlation, 低度相关1 D6 A$ a! t6 ]9 w
Lower limit, 下限
# j3 o( X5 h( w! @$ OLowest-attained variance, 最小可达方差
* }, E. e( a8 x5 Z8 `$ [LSD, 最小显著差法的简称
, I+ h# Z4 Z& A4 R' v+ {$ @Lurking variable, 潜在变量
: ^3 o& z2 l8 x: W4 ?; zMain effect, 主效应* M$ x' t- @! L+ G( v; I7 P
Major heading, 主辞标目" T( S) a! r+ T7 b; C% B% y; x4 _$ I
Marginal density function, 边缘密度函数3 C4 D% Y- l$ c) `+ n/ r- R
Marginal probability, 边缘概率
o$ W( D+ v9 l$ F# A z( U) rMarginal probability distribution, 边缘概率分布- w. v, S9 Y+ x5 W
Matched data, 配对资料
0 i( v" I$ n& y3 t+ b) g4 e, M% @Matched distribution, 匹配过分布
& A7 h! \8 C# `5 OMatching of distribution, 分布的匹配
" @. i# {' b; T! s9 ^$ ~Matching of transformation, 变换的匹配( f0 H7 Y4 {! w" [$ q! \- }) y" ~
Mathematical expectation, 数学期望/ X- k6 m# N" n0 [: T# M& A
Mathematical model, 数学模型
; m3 q" o- c$ u P( BMaximum L-estimator, 极大极小L 估计量& Y6 e E5 C: R/ `5 V
Maximum likelihood method, 最大似然法1 x. n1 T: g7 ?% K) e
Mean, 均数6 `+ d1 V9 n, e! u
Mean squares between groups, 组间均方
) g+ t# y; O B* QMean squares within group, 组内均方# f5 Z+ b6 l1 X1 w
Means (Compare means), 均值-均值比较
( k3 ~4 k) J. p5 {Median, 中位数/ D0 R2 ], X4 O( Z' k$ ~. J
Median effective dose, 半数效量
; m* o( l b1 }; {1 HMedian lethal dose, 半数致死量3 [6 l& T) a; u' s6 N
Median polish, 中位数平滑
# }' G( a5 y* hMedian test, 中位数检验
- u, q; v6 f8 Q1 ]7 A, u& h. PMinimal sufficient statistic, 最小充分统计量
# W. }3 w7 z: D$ N* Q. o( g! Z4 rMinimum distance estimation, 最小距离估计0 q$ z$ z, _- ?
Minimum effective dose, 最小有效量
5 U& n4 }* O& E/ S7 o; N' T+ tMinimum lethal dose, 最小致死量- O# }& k3 A/ b+ n+ E2 X* D5 e6 @9 U
Minimum variance estimator, 最小方差估计量
5 s3 z( Z2 m7 \- O, aMINITAB, 统计软件包 m8 I. s4 W/ o
Minor heading, 宾词标目
! A) T( G" l, Y/ T' YMissing data, 缺失值
8 i! c4 |- R. E7 gModel specification, 模型的确定/ J+ O" U+ X% @ E- @
Modeling Statistics , 模型统计
8 M$ e& v9 b6 x( C8 NModels for outliers, 离群值模型
7 e- K# l. C, J2 A6 Y, q6 N. ZModifying the model, 模型的修正$ r& N; M% E: p- u0 y. |% e2 \
Modulus of continuity, 连续性模
* P, f3 O, Q( [* T& d+ _Morbidity, 发病率 . v1 F0 ^% i( `& J
Most favorable configuration, 最有利构形
7 ?3 |8 P% X5 I2 U0 @Multidimensional Scaling (ASCAL), 多维尺度/多维标度
) u I0 {% d9 H7 Z0 X3 y# b7 F0 rMultinomial Logistic Regression , 多项逻辑斯蒂回归
) D$ m& Q6 T$ OMultiple comparison, 多重比较3 `+ V$ w3 ~5 }
Multiple correlation , 复相关
! u9 Y2 B: Z9 p; M5 O+ z4 SMultiple covariance, 多元协方差
$ f v) V6 N G7 A6 u/ iMultiple linear regression, 多元线性回归
, F) j8 I% H- ^5 x- S6 a6 {Multiple response , 多重选项8 w2 c! C; k/ q" l
Multiple solutions, 多解" p M8 k5 M" S, ], Y
Multiplication theorem, 乘法定理, C$ @- c) x3 T' z, J& y9 G; f1 _
Multiresponse, 多元响应* s& ]1 s) C) ^: h7 b+ l1 n
Multi-stage sampling, 多阶段抽样. M# E% c' D8 P8 }
Multivariate T distribution, 多元T分布
( k& |, t# c" g, }: r, y$ TMutual exclusive, 互不相容9 {# e# i d o9 E$ G. V/ e( l/ E
Mutual independence, 互相独立7 Y1 l: \( R# Z2 x. Z
Natural boundary, 自然边界( v' u# d: g3 a M* P
Natural dead, 自然死亡
; T( i+ [! a. [' \8 {; pNatural zero, 自然零: d- |5 r4 ~ Y; v% [
Negative correlation, 负相关$ h$ z6 m& s! g7 w: J/ P0 P2 f
Negative linear correlation, 负线性相关
( L; @7 Q: v1 g7 F5 ~' X+ yNegatively skewed, 负偏
. |7 B2 t, I) T! e& p B6 PNewman-Keuls method, q检验* J, k3 Z" n) _' S9 t& W
NK method, q检验* r4 C) z; l7 ?) i, x8 N
No statistical significance, 无统计意义
# ^5 _# O [# X) U" w, i0 vNominal variable, 名义变量8 k2 N1 R, o q2 C% R4 G
Nonconstancy of variability, 变异的非定常性' l- P9 R6 c! X7 L& ]: G, o# C! V
Nonlinear regression, 非线性相关
0 Z; W+ l9 t& P! z% gNonparametric statistics, 非参数统计
' t# Y" j7 A pNonparametric test, 非参数检验* z ~# X1 x1 V
Nonparametric tests, 非参数检验# b, x: s% Q1 `. y. T( _' I
Normal deviate, 正态离差* e9 _8 u9 K/ T
Normal distribution, 正态分布
& L& G' ?3 ]( `4 X3 U) bNormal equation, 正规方程组) E6 b$ w3 c* h: ] o
Normal ranges, 正常范围( |3 ^+ b7 X% f# E2 k' @
Normal value, 正常值9 a! r1 A! v) F% N+ P9 Z
Nuisance parameter, 多余参数/讨厌参数
7 E! o4 n+ X% u3 `+ gNull hypothesis, 无效假设 $ n" @0 K( x) Y) ^: _% m& O
Numerical variable, 数值变量8 _4 L7 z1 k) r* J
Objective function, 目标函数% Q7 S5 c ?2 L% f3 W- X9 ^; p
Observation unit, 观察单位
: o/ z' w% D8 z! j$ KObserved value, 观察值8 e, N( G; y( i% W
One sided test, 单侧检验
' G0 X% D: t' _8 DOne-way analysis of variance, 单因素方差分析
, H8 D/ M% F2 o/ gOneway ANOVA , 单因素方差分析& \& }5 P/ D" \$ F: C
Open sequential trial, 开放型序贯设计
3 |+ C# p3 U6 s% @Optrim, 优切尾
* g8 Y6 P3 C) Z; g& x8 F' COptrim efficiency, 优切尾效率
( E& m+ L6 F. C4 d' {4 GOrder statistics, 顺序统计量4 } y; t2 ?# Z( y8 P0 U6 v
Ordered categories, 有序分类
0 r7 x1 E1 M( g0 t1 P2 X# F/ kOrdinal logistic regression , 序数逻辑斯蒂回归
+ a. x) i p5 zOrdinal variable, 有序变量
0 Z# u# Q& V# }Orthogonal basis, 正交基/ M& L1 h# o9 c+ G
Orthogonal design, 正交试验设计
7 I6 s, C. E8 v. v$ i2 I- \; HOrthogonality conditions, 正交条件
/ b* C/ ~+ X4 s* SORTHOPLAN, 正交设计
3 b. a- Z& s3 `% G/ QOutlier cutoffs, 离群值截断点! T, W1 @) t2 c( m" B7 u
Outliers, 极端值& H \/ I- j# {" ~0 \
OVERALS , 多组变量的非线性正规相关 & i% T! C9 U* ^+ T3 A
Overshoot, 迭代过度
6 _* A6 B; u) Z/ Y6 g3 q; Z* gPaired design, 配对设计' d, R2 A9 ~, O+ f; y/ v# o8 G# w5 [
Paired sample, 配对样本
/ D3 X, K. P9 M3 n* ?, x* ^Pairwise slopes, 成对斜率) i9 o: b x8 Y5 |
Parabola, 抛物线 ?4 y7 A) k# o$ R
Parallel tests, 平行试验2 k6 N7 [9 F* p6 m# K, c* f
Parameter, 参数* t: E; S/ b2 N0 g T& x2 M
Parametric statistics, 参数统计+ I9 _; o6 Z. L% N9 ~# m
Parametric test, 参数检验
; _3 G3 X/ U, p: A! VPartial correlation, 偏相关& i7 U, b6 U. G) {
Partial regression, 偏回归5 z' }" t& r7 ?. [3 F- k
Partial sorting, 偏排序, e+ N5 H' K7 U& J) z. M
Partials residuals, 偏残差
" ^$ t! ^1 Z+ pPattern, 模式' b" }# a' U! h, N1 C
Pearson curves, 皮尔逊曲线3 S3 { }9 l: @) @' {2 o* [0 }$ L7 u, a5 N
Peeling, 退层1 Q* \8 ~( o- X5 [; C/ |4 g
Percent bar graph, 百分条形图
2 q; v/ X9 Z/ \8 R9 V1 r- }Percentage, 百分比' Z) G3 \( Q9 r9 {; S
Percentile, 百分位数) A8 [( S1 P: \/ b7 K$ W' s! H
Percentile curves, 百分位曲线2 O5 }$ s4 v: \# p% N1 |3 l+ r$ O
Periodicity, 周期性
8 V, p. E, B, K& _$ hPermutation, 排列' X8 V A. a/ d" L I. |
P-estimator, P估计量
9 ^# N6 F) i: G1 b' g* x8 UPie graph, 饼图
( k+ z; }2 M. @5 uPitman estimator, 皮特曼估计量. t2 a) U% m' O% B' U# q# B
Pivot, 枢轴量
( o' F1 s8 v2 Z; U/ e/ @Planar, 平坦
# k! l" N2 b: b1 U$ EPlanar assumption, 平面的假设" m4 Y8 x+ z9 L& Y% i) i" A' a
PLANCARDS, 生成试验的计划卡
8 _$ J2 V/ D$ R) mPoint estimation, 点估计! i6 M. P- J: b- ]% n t* c
Poisson distribution, 泊松分布$ i# K$ x; u6 ]* Q" y4 m
Polishing, 平滑0 l( d5 Z/ X# d& M& \
Polled standard deviation, 合并标准差8 e" B2 X% T, F5 Q: A
Polled variance, 合并方差
! V, I: O: c8 j4 f6 WPolygon, 多边图9 I6 Q2 h, w! ?! {8 @
Polynomial, 多项式
: X; K8 h, h7 s7 a; J7 w" V* lPolynomial curve, 多项式曲线
+ \& \: J2 e/ ^( u$ ePopulation, 总体) [, i# Q1 [* U5 v$ _+ g$ M, k
Population attributable risk, 人群归因危险度
' @4 [% v+ h% ?6 @Positive correlation, 正相关
, v6 [( }, k3 E7 T" lPositively skewed, 正偏
" g+ h& d, c7 x; mPosterior distribution, 后验分布- \. S+ l! U: F0 K; |8 ?# i3 x" i' C
Power of a test, 检验效能* G0 n5 N9 h3 R4 P
Precision, 精密度; L% @! m$ L5 R+ ^3 g
Predicted value, 预测值
- |- E" k2 ~! B' lPreliminary analysis, 预备性分析# f3 w% W- N9 U( ^, U
Principal component analysis, 主成分分析
5 h- t1 x0 I/ t9 zPrior distribution, 先验分布
% w/ w! j( _' t2 e7 H! q4 M$ ]Prior probability, 先验概率
$ U/ x. R; z( o& p2 f# IProbabilistic model, 概率模型
}: F- u: C8 ], K5 w4 y ?probability, 概率
& V$ r! K: E8 }. \+ K# fProbability density, 概率密度3 g @: f% {+ s# G0 J. Q/ t5 I2 ^. S8 r
Product moment, 乘积矩/协方差
8 [$ f0 Y* T: [( z# b4 bProfile trace, 截面迹图( Q( o1 t- R2 T* f6 @, [4 ]& E
Proportion, 比/构成比
0 ]4 |* g2 ]. V _Proportion allocation in stratified random sampling, 按比例分层随机抽样) C( D Q _1 G/ E" h' k
Proportionate, 成比例* e/ A: \5 ]5 @- V2 h8 O1 o3 Z
Proportionate sub-class numbers, 成比例次级组含量6 I& L7 i# o7 v, L' N/ D) g6 Y! ^
Prospective study, 前瞻性调查
5 d9 K7 l6 g' ^3 M7 MProximities, 亲近性 * _9 i! i& w+ v! Y% b
Pseudo F test, 近似F检验
5 T2 c" F! e4 U: n9 Q# {* E, OPseudo model, 近似模型6 N" O! U! z& r" ~' K! I$ w9 x8 I
Pseudosigma, 伪标准差
5 p0 l+ z1 p9 @+ ^# j j' SPurposive sampling, 有目的抽样2 r9 d/ {( q8 E) I X8 x& z) z( j3 M; o
QR decomposition, QR分解
) Q$ X5 a% _+ _; u! hQuadratic approximation, 二次近似
& m, L6 x" a b gQualitative classification, 属性分类8 G$ a' a0 p: x
Qualitative method, 定性方法% @& I3 f' ~$ ~7 c" P
Quantile-quantile plot, 分位数-分位数图/Q-Q图
+ z) G) @9 ?5 tQuantitative analysis, 定量分析& f0 M, ]3 r! ?8 U" Z8 {* K
Quartile, 四分位数
2 v) e( m/ f- t$ z$ AQuick Cluster, 快速聚类
- `) v" d3 K0 |- W; L; fRadix sort, 基数排序
7 r! c4 a+ B/ e% y7 vRandom allocation, 随机化分组
! G+ K2 D! @# Y1 P- l1 CRandom blocks design, 随机区组设计
4 b& c1 F/ N. n hRandom event, 随机事件4 r. v& ^# ^- I& r" E- v
Randomization, 随机化
7 ~3 {0 d/ z6 c# d+ \& f: E! v$ xRange, 极差/全距
0 U3 W2 R( o7 i" [+ \- rRank correlation, 等级相关: [% D9 [ e8 G; @# r3 a+ E
Rank sum test, 秩和检验: l2 w- Q# Z3 q, h' @' I& y& @7 `
Rank test, 秩检验
# Z* w( D% _! |5 _: PRanked data, 等级资料2 S& Q0 T5 o* O- K5 v
Rate, 比率
* s" r5 v: O& z9 @5 ?' l5 {/ IRatio, 比例
4 U1 i# c2 _( M# q* ~Raw data, 原始资料) K6 ]1 d1 W( I* h, ]# b
Raw residual, 原始残差& O) k. j( C7 c. x _
Rayleigh's test, 雷氏检验
! `( U5 P5 M1 { a3 @Rayleigh's Z, 雷氏Z值 5 ^: r$ S- a. O) J4 @% [
Reciprocal, 倒数
" R1 j' u% I j1 J! k8 E8 B5 y0 w* }Reciprocal transformation, 倒数变换& x% u, h. n1 S
Recording, 记录0 c+ m; O, d; e. M t; E
Redescending estimators, 回降估计量
1 M+ V' Y3 b3 {2 z" t# E, s1 wReducing dimensions, 降维+ F8 q* ~& S3 G6 U! z8 R
Re-expression, 重新表达
0 i; }" e1 p+ v. Z( H; VReference set, 标准组8 Q1 ]: N5 K3 W4 B& ^( e9 }+ V) r
Region of acceptance, 接受域6 {7 j& B9 k7 H- v1 Q8 B
Regression coefficient, 回归系数
* M, K7 ~- U& b7 c- NRegression sum of square, 回归平方和- O; l& Z% h# A* c$ W9 K
Rejection point, 拒绝点" J8 ]& g! d: s$ ^6 A/ ^9 Q
Relative dispersion, 相对离散度' \' i8 c3 i% S9 }
Relative number, 相对数) F; \0 u G3 @8 b7 g
Reliability, 可靠性
: D$ A" x |* o; @9 aReparametrization, 重新设置参数7 E0 |# O1 P/ n& [
Replication, 重复
, s6 [/ {. b. n. g2 D9 y5 `Report Summaries, 报告摘要
) e5 F5 g+ T+ p7 M$ R/ _6 ?Residual sum of square, 剩余平方和
9 U+ n+ r! |! }6 g% VResistance, 耐抗性5 M3 L6 w2 K/ p
Resistant line, 耐抗线# ?4 w. U1 ~$ \. o
Resistant technique, 耐抗技术
& N( z& A+ s* s0 ?7 q( r2 WR-estimator of location, 位置R估计量: z3 n ]0 t! ^
R-estimator of scale, 尺度R估计量
# u, L( a2 |2 b1 H6 QRetrospective study, 回顾性调查
) y- G: v* v: f: S6 b3 W' wRidge trace, 岭迹: f4 Y* a9 ? p8 x
Ridit analysis, Ridit分析
6 O$ |& o0 m+ g8 {Rotation, 旋转
1 n# B- J& m5 v! G# o2 W% q% _Rounding, 舍入
# y1 V t: Q) K9 [9 Z9 F5 aRow, 行
7 u5 \# U+ H5 @Row effects, 行效应
. r" ^# F/ C) v$ R/ M8 KRow factor, 行因素
6 ` W5 r# b* c' \. ~7 S: RRXC table, RXC表6 ~5 `9 j& F4 m1 o! _
Sample, 样本0 m4 U7 Z' s4 w) A: Z/ V5 T! |
Sample regression coefficient, 样本回归系数
( z" \# U+ t! ^6 r2 `7 W- XSample size, 样本量+ M: r2 T0 ]* I
Sample standard deviation, 样本标准差& q- W; N9 p8 O* D- c0 p+ B! Q
Sampling error, 抽样误差3 H8 X4 g* K( m8 E7 h3 B2 K; n
SAS(Statistical analysis system ), SAS统计软件包8 g# N2 \$ f3 i% ]) P$ T, H
Scale, 尺度/量表
; }( w" u6 ~" x0 I+ bScatter diagram, 散点图
+ j/ _2 c$ j7 j, ^( J% r+ O% \Schematic plot, 示意图/简图5 B q% m* _- J, P
Score test, 计分检验
* {. [) n: y6 R% s2 RScreening, 筛检5 k4 F2 a& U! H; ?& g
SEASON, 季节分析 8 F3 R4 \' {2 Q) L/ f9 J. ^% N
Second derivative, 二阶导数
% r, S2 I6 b/ E9 S& g1 W$ HSecond principal component, 第二主成分
0 S3 F1 q( _5 M" B3 f; YSEM (Structural equation modeling), 结构化方程模型
6 w7 y# z# v9 ^' t$ `+ MSemi-logarithmic graph, 半对数图6 u* _2 ^+ @ w" Y4 f+ T! X4 P |
Semi-logarithmic paper, 半对数格纸
& F2 E7 W$ \( a1 \Sensitivity curve, 敏感度曲线5 M$ Q" S0 ]2 ~& a! d* h3 V- g8 x
Sequential analysis, 贯序分析- M% L; t) t; X+ ]+ D: p, @
Sequential data set, 顺序数据集
3 u. o# `, R0 x: ASequential design, 贯序设计
$ k/ E5 P$ Q) @! Z+ K* KSequential method, 贯序法
# p3 J: t2 P; z. I: iSequential test, 贯序检验法+ U8 c! \! r' X' h8 Q2 N5 j0 c4 f1 O
Serial tests, 系列试验
5 v7 ^, s3 v5 u6 w8 wShort-cut method, 简捷法
5 Y8 Q1 L3 r6 BSigmoid curve, S形曲线9 h: a6 S4 I" k/ V" }
Sign function, 正负号函数1 m! A: K G2 ]) _" {$ _
Sign test, 符号检验
9 k' v, p5 x7 O( d: jSigned rank, 符号秩
; A; c0 B" R- Q; T% mSignificance test, 显著性检验
( H" a Y3 R6 \8 E- n, FSignificant figure, 有效数字! J" l7 w! s4 B! j5 }# H, }6 t, T
Simple cluster sampling, 简单整群抽样( i; L$ i* O! r+ r4 F' F* y) G
Simple correlation, 简单相关
}1 A1 ?/ t1 `! FSimple random sampling, 简单随机抽样
! r; i6 q- {' u! N2 I8 vSimple regression, 简单回归0 h: |+ X, T& O) Q* k) @
simple table, 简单表- R$ Z. l% G# T! S" e
Sine estimator, 正弦估计量
) d( x" ]+ S# w4 F/ xSingle-valued estimate, 单值估计
* _( P* b, O7 h; Z+ w5 I6 _Singular matrix, 奇异矩阵
6 E9 _$ n0 G/ }; C, O7 x+ xSkewed distribution, 偏斜分布0 l. {. n! O( L6 I1 C
Skewness, 偏度. [. P; H9 w0 h; E! b* g7 ^
Slash distribution, 斜线分布
c/ J: M2 r: T, gSlope, 斜率
4 r* F Z+ A# G8 t, vSmirnov test, 斯米尔诺夫检验
* D' X9 ~" \! |$ P( y/ D6 USource of variation, 变异来源
: f9 k* g* M2 y( Q7 i3 }/ ?Spearman rank correlation, 斯皮尔曼等级相关
/ H6 N8 n9 Y( ^ f. rSpecific factor, 特殊因子
3 v1 H w: D) Z8 L {* BSpecific factor variance, 特殊因子方差
) F5 v7 n# \. `& m0 W5 ASpectra , 频谱
$ S& C* G) C* ^7 ?! z9 J+ uSpherical distribution, 球型正态分布
( J: q" j c2 d \9 `& x! w) CSpread, 展布- s1 U w% x) n4 @3 p% l" g0 A
SPSS(Statistical package for the social science), SPSS统计软件包
: L5 X, {. H" _7 GSpurious correlation, 假性相关
& B: D; i! E5 A( |( o. i$ o, SSquare root transformation, 平方根变换) r: y* ~1 w6 R( X4 I, h+ J
Stabilizing variance, 稳定方差
$ e- g( L; o; ^3 e+ X+ aStandard deviation, 标准差) }9 M7 _# l# K; J
Standard error, 标准误
( t! s) h, o& g$ HStandard error of difference, 差别的标准误- k1 ?$ f: J3 l3 H) p& h5 A
Standard error of estimate, 标准估计误差# t8 r" f \7 F" a! X3 k
Standard error of rate, 率的标准误4 |/ q+ @0 N# X& N
Standard normal distribution, 标准正态分布
5 a) f$ r! o: M2 ~* |% `9 t" SStandardization, 标准化
5 x+ h! T1 ^/ ]% n; s9 uStarting value, 起始值
9 V. C% C5 O+ n$ r8 [: ^0 }, YStatistic, 统计量) R3 g2 G% _, u5 p2 D8 G' x
Statistical control, 统计控制
]& X0 E0 Y0 S& p, f$ s1 [Statistical graph, 统计图
" ?7 ] C, A D- y+ p6 _8 iStatistical inference, 统计推断
9 R9 l! Z. N% f# T4 D! K" rStatistical table, 统计表& D2 F+ }4 O* T
Steepest descent, 最速下降法8 [# t$ M, V5 v: M( J2 T
Stem and leaf display, 茎叶图- K g w3 A, A: R+ z( Z
Step factor, 步长因子5 c+ k6 [ e; r9 V/ Q+ b1 u
Stepwise regression, 逐步回归' w& ]0 I3 u; r8 }; e% t7 D8 S+ |
Storage, 存( y' Y# n9 {& A' y$ @! F
Strata, 层（复数）
4 v. ?: N& h6 _( g# }Stratified sampling, 分层抽样6 J7 K* _+ h0 r# k- r9 |& r0 m
Stratified sampling, 分层抽样$ ?: ^/ r7 C3 O$ f- `1 S1 E
Strength, 强度
6 _3 F2 E2 x& @# W( i! |Stringency, 严密性; s8 x7 s1 g+ W F% k
Structural relationship, 结构关系
/ D: G' T) F9 d$ d+ o/ PStudentized residual, 学生化残差/t化残差; d6 |# l+ f9 `4 ?7 M. i
Sub-class numbers, 次级组含量, R. x/ U. m) \
Subdividing, 分割
1 V% X# E5 X: c+ L# p- USufficient statistic, 充分统计量, J/ }3 t5 S( r ?7 C. @& h* ^/ Z( t
Sum of products, 积和
( d. r: h$ p1 t- k0 k& D. SSum of squares, 离差平方和2 x7 [, n: o1 W3 e' n) }6 M
Sum of squares about regression, 回归平方和1 r* J7 Z5 h* X. l
Sum of squares between groups, 组间平方和4 Y+ ^: r3 C( @/ U( T {1 {! |
Sum of squares of partial regression, 偏回归平方和
2 G. }8 |8 }" C& u0 dSure event, 必然事件
( z6 Q9 V! |- GSurvey, 调查9 G$ p. h7 C- J% `; i% Z+ k+ Y
Survival, 生存分析
. Q; `, q4 }1 b! J( e) R* GSurvival rate, 生存率
! R: \( f/ [9 cSuspended root gram, 悬吊根图
" s0 D5 h* M# @: _0 h j+ VSymmetry, 对称
, M6 U5 o1 u9 U( F9 \! _' FSystematic error, 系统误差
- {5 T4 [, w- ?% j- {Systematic sampling, 系统抽样& p, ?. y) S! H4 b
Tags, 标签! _5 a4 j Y3 j) r% v; {, h
Tail area, 尾部面积8 I2 m" T' g) ^
Tail length, 尾长
( i, e" |; b# t6 FTail weight, 尾重
2 q" V4 S2 O/ _6 Q1 e0 F4 a4 X5 N8 KTangent line, 切线
; W4 |* I( V- D( nTarget distribution, 目标分布, c% m! D# b0 t% _
Taylor series, 泰勒级数
% z3 f% _5 Z) m2 u0 r5 yTendency of dispersion, 离散趋势1 ~# ]$ c D5 Q+ m' O; ~- a b
Testing of hypotheses, 假设检验
6 L$ j8 N P* A, j% K0 e" aTheoretical frequency, 理论频数5 O, B) L0 y0 w% g v
Time series, 时间序列
- a3 X7 B8 i# f0 `% `Tolerance interval, 容忍区间3 K$ I' ?2 Q$ {+ m! V* F6 c* O+ @
Tolerance lower limit, 容忍下限
3 X! x6 k3 S# c: V' a$ B$ y a4 MTolerance upper limit, 容忍上限
* W3 \/ Y) L4 o7 T! v6 u* wTorsion, 扰率9 K3 J: ~! z* L6 h$ I+ q
Total sum of square, 总平方和$ p: k! J1 A+ B9 r' [. `" o
Total variation, 总变异( q$ M( i( J5 Z
Transformation, 转换
3 X! A1 L; q8 c, }; U5 ?Treatment, 处理
X, a& z: m+ a8 w7 [+ LTrend, 趋势
/ U! H/ i8 h* `, w* W6 ]+ sTrend of percentage, 百分比趋势2 f/ L: J* N0 ?* }9 O# w
Trial, 试验
0 V) S- h5 E6 I/ y+ e( dTrial and error method, 试错法3 i% R4 ?8 s) Y- l* W
Tuning constant, 细调常数0 _: ?" F7 b o( l
Two sided test, 双向检验+ g" J4 N- J# v' S
Two-stage least squares, 二阶最小平方6 u; D9 G' w% a. Y- [7 m+ j, z
Two-stage sampling, 二阶段抽样% }: J& G4 B+ J, `/ F+ z
Two-tailed test, 双侧检验
2 R: F$ N- ^4 ]; V; [: H; mTwo-way analysis of variance, 双因素方差分析
, f( P" C# E5 \+ b. NTwo-way table, 双向表" t1 k5 R: O- |; h% n" v! Z- m2 L. c
Type I error, 一类错误/α错误. x# s# G! ]% w9 q! z1 H" k/ E
Type II error, 二类错误/β错误
9 ^4 X z! I" e2 f* ?* RUMVU, 方差一致最小无偏估计简称# ~: x6 }. a; z% T
Unbiased estimate, 无偏估计6 ]8 @& ?/ q! ]- i, N
Unconstrained nonlinear regression , 无约束非线性回归3 o6 b* L6 R! @: r
Unequal subclass number, 不等次级组含量+ Z5 M) I6 u" \: O
Ungrouped data, 不分组资料
2 y" u! b9 \5 A3 AUniform coordinate, 均匀坐标
6 R7 K% J g* d) bUniform distribution, 均匀分布
+ Q* D: v& ^4 H( w3 a7 nUniformly minimum variance unbiased estimate, 方差一致最小无偏估计+ `5 N2 E, ~! n$ z5 R: s( k
Unit, 单元
, z1 T* x4 O# W( `5 kUnordered categories, 无序分类
/ x2 W2 S# ]5 mUpper limit, 上限/ r X: f% }2 O/ x" c
Upward rank, 升秩
$ G) Z. y3 @$ jVague concept, 模糊概念
) Q1 e' ]2 f+ J: h- n" {# pValidity, 有效性% d1 w8 A5 f' i$ N% z
VARCOMP (Variance component estimation), 方差元素估计
- O+ T1 W: r6 h' vVariability, 变异性
7 I q" i D: C0 l T4 lVariable, 变量
& c: k9 W! D6 e: W) y0 XVariance, 方差 g# ?$ Y2 Q9 i
Variation, 变异
. n: s- [8 b0 `. ^. QVarimax orthogonal rotation, 方差最大正交旋转
5 W R5 M# m/ [8 hVolume of distribution, 容积
; v. O {& U: g' E+ x) k) ~W test, W检验* J- [& z6 Y, K" s' p# _; j
Weibull distribution, 威布尔分布
+ P6 t( ~' [8 K3 pWeight, 权数8 j. n" G. x5 n
Weighted Chi-square test, 加权卡方检验/Cochran检验* U% D6 z* b/ j( _! I! [
Weighted linear regression method, 加权直线回归- x# m/ s& M& ^4 q6 p& b
Weighted mean, 加权平均数. M; i0 ?% o2 h& C& b3 l* i
Weighted mean square, 加权平均方差
6 E) O3 H6 s7 o6 i- XWeighted sum of square, 加权平方和! r* Q5 \) H, H$ G9 }8 V! ^
Weighting coefficient, 权重系数 ?) F7 ?( } b0 \( P
Weighting method, 加权法 ; q4 k" Y+ U' d' C$ [# P- E0 s
W-estimation, W估计量# e+ Z7 i" n. H
W-estimation of location, 位置W估计量% }( B( [. J% F0 ^, _; ^
Width, 宽度
' V7 M4 \8 J3 e# o2 }9 ^3 F' n% }Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验* k6 m( N4 ?. J9 E! B# H; `4 n
Wild point, 野点/狂点, t( Y+ o9 d* z! Y1 }' R: A
Wild value, 野值/狂值
3 _: O. Y$ n+ D9 f; n0 u+ c$ T yWinsorized mean, 缩尾均值
0 ^0 z+ h1 g+ T5 o* c2 kWithdraw, 失访 0 k( P8 a G( O. _8 d1 D
Youden's index, 尤登指数 j9 e- ]0 T3 k5 G. k
Z test, Z检验
* W, V5 l+ F+ u+ x9 m7 `- pZero correlation, 零相关7 M; N6 O" `$ Z. e1 n% n
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
