|
|
Absolute deviation, 绝对离差' P& Q: R6 W- y; N: l0 ^
Absolute number, 绝对数! c% ?6 n4 ]( s* a! s) W
Absolute residuals, 绝对残差+ V* Y9 R( I+ @2 [0 R( O/ E/ y
Acceleration array, 加速度立体阵' k Y- x. f2 i$ \9 z& {' P
Acceleration in an arbitrary direction, 任意方向上的加速度
5 z6 c6 q% z t9 xAcceleration normal, 法向加速度
0 Y% d! N* S/ PAcceleration space dimension, 加速度空间的维数1 N/ l# e) O8 `# C, s: F
Acceleration tangential, 切向加速度2 [$ v7 g9 h3 f3 ?5 S
Acceleration vector, 加速度向量# e2 P( u4 V) }; [2 ]
Acceptable hypothesis, 可接受假设: s: ^! {* u3 L0 K
Accumulation, 累积- |9 [6 } j! E6 ~: ]* p* m
Accuracy, 准确度1 X: j" J/ T- Y* S2 Z
Actual frequency, 实际频数
/ z0 ^+ y) X4 |$ WAdaptive estimator, 自适应估计量4 k3 w5 w$ ~5 Q) r4 I# B. I- s% c
Addition, 相加
& b3 t [2 j8 c, I2 H$ B/ nAddition theorem, 加法定理% _. F( O" Z3 A. T# K" O" ^& c; z
Additivity, 可加性
, b# f' g# ^+ }6 D$ F: x8 GAdjusted rate, 调整率$ H3 J) n$ H0 ~3 j) N' N6 W
Adjusted value, 校正值' k4 y* b7 A: S0 ?9 w0 A1 G5 _
Admissible error, 容许误差; Z9 O# B% Y8 |3 Q& X6 y. q0 ^
Aggregation, 聚集性
+ N7 C1 J( U) [4 OAlternative hypothesis, 备择假设( a# n8 L- }$ E2 Q" W# i; B. K
Among groups, 组间+ K9 {+ L# ^( Y8 H, }' v
Amounts, 总量" } q5 \4 W C- b, G7 l
Analysis of correlation, 相关分析* y6 s" s0 @, ^/ Q- h# ~. i
Analysis of covariance, 协方差分析
$ b1 Y% d4 P8 D- pAnalysis of regression, 回归分析% z. D+ O: o! `1 N: i
Analysis of time series, 时间序列分析% G: u) b% G3 T1 a$ f
Analysis of variance, 方差分析0 I$ h9 i; V$ D4 ^4 ^$ j8 u
Angular transformation, 角转换
8 o& K- H' ~3 ZANOVA （analysis of variance）, 方差分析- B" P5 q. N+ S* j
ANOVA Models, 方差分析模型
9 `& n. D' M0 ^1 u0 T! tArcing, 弧/弧旋
0 V) ^0 f( b4 IArcsine transformation, 反正弦变换! b. \* y5 B3 T0 v9 @. A2 N: p
Area under the curve, 曲线面积- X5 F1 ?5 h6 T( X3 ?' f/ O
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 3 }9 B! D2 B! A2 ~
ARIMA, 季节和非季节性单变量模型的极大似然估计 . ^5 u$ e/ g2 D: t* A4 h
Arithmetic grid paper, 算术格纸
$ X% v/ \$ H: W. I# R |Arithmetic mean, 算术平均数
' f0 c) h0 Q# ?! G: c e, LArrhenius relation, 艾恩尼斯关系 N! H; d F0 u6 @
Assessing fit, 拟合的评估0 y* B! D3 x1 ?) Z1 h; r
Associative laws, 结合律
& E5 \2 z( X* d3 V9 n) YAsymmetric distribution, 非对称分布
: P; x0 [0 m0 @8 _! c4 v$ L- gAsymptotic bias, 渐近偏倚
+ B5 f9 n& q/ s! K# h& SAsymptotic efficiency, 渐近效率
, f" e5 N; t) P0 |% T0 BAsymptotic variance, 渐近方差
* h0 r' N$ q* j" DAttributable risk, 归因危险度
2 U# u8 t; ^: F. d. {% M, S+ BAttribute data, 属性资料
. z' }+ g$ e P1 W. W+ bAttribution, 属性) ]" Q7 a: g, C7 U* n+ j
Autocorrelation, 自相关
7 h; E! L" |; O; q1 AAutocorrelation of residuals, 残差的自相关1 h6 h) s8 c7 F8 T" A& R
Average, 平均数
4 Q( F0 L* f& G& s( UAverage confidence interval length, 平均置信区间长度" g# P& [4 b0 G8 [7 {) ?
Average growth rate, 平均增长率- U7 ~+ Y2 V! e# y# b- A0 a: W+ S
Bar chart, 条形图1 {7 N8 y/ B% W
Bar graph, 条形图
; W/ x& Z" s0 h0 E* D. IBase period, 基期9 A* b% v# k/ \ _# B V
Bayes' theorem , Bayes定理) g" ~$ J6 E4 |( D$ G5 @8 C; E
Bell-shaped curve, 钟形曲线
0 Y1 e$ ~% }" w- R, q( ]Bernoulli distribution, 伯努力分布
, a! ~1 [# a3 u- q2 z8 bBest-trim estimator, 最好切尾估计量
7 R; b" h+ ^4 {/ F) E( }, VBias, 偏性, l5 Z7 B" F+ C$ n. o, h
Binary logistic regression, 二元逻辑斯蒂回归2 q' J( @5 T) j7 Z: x- U T b) r
Binomial distribution, 二项分布
; g2 w: H# _9 K& q6 O3 NBisquare, 双平方6 G; j4 W, K2 Y5 P
Bivariate Correlate, 二变量相关
# T! g8 C, M* T6 @* p- `9 aBivariate normal distribution, 双变量正态分布
4 u9 W+ t1 w: X6 [' aBivariate normal population, 双变量正态总体/ p: _0 f- I. t, g$ f3 e* a' e7 a
Biweight interval, 双权区间7 s ?/ B8 F# B
Biweight M-estimator, 双权M估计量
* I' ?$ H, V- E c! I( S4 yBlock, 区组/配伍组7 V9 M0 t+ f( n, q$ g+ {4 n
BMDP(Biomedical computer programs), BMDP统计软件包
- y6 G& Y2 S7 X g4 D+ u7 UBoxplots, 箱线图/箱尾图/ G/ @* }7 b) p4 t+ m, P) N
Breakdown bound, 崩溃界/崩溃点
1 @3 E+ P1 r3 i: @9 ?4 QCanonical correlation, 典型相关
7 Y9 ~; D1 c. _. Z5 ]; Q# tCaption, 纵标目+ e6 b+ F( `9 c) M9 `/ }: c
Case-control study, 病例对照研究4 L0 l0 J% c0 d
Categorical variable, 分类变量
) d. y! a9 q/ {, g6 h; Z v# nCatenary, 悬链线
9 m& A- J' ]7 |$ ~& V% U6 k2 E2 L `7 RCauchy distribution, 柯西分布7 q$ q- ?2 P4 _; q' T( s
Cause-and-effect relationship, 因果关系
- f" t& r" ]3 C9 ECell, 单元2 W Z; y2 m3 I6 [
Censoring, 终检
2 V' [% g: q2 i2 Q sCenter of symmetry, 对称中心; S7 w! m" q: ^
Centering and scaling, 中心化和定标
$ ~- ^" g3 O, e% v" Z' k; ^5 e' ^, p% FCentral tendency, 集中趋势% S' R( [% a8 D# c7 m% @* C+ l
Central value, 中心值
! q- {! z/ P$ |7 E& k/ E7 UCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测2 A* A7 X; d5 O7 r5 X2 s% b9 L
Chance, 机遇8 h: I1 s2 e6 h
Chance error, 随机误差
( P# k4 V0 [3 I, P/ bChance variable, 随机变量
: J( o9 U, o/ q e U F- CCharacteristic equation, 特征方程
- c2 {# J. T5 P9 p! xCharacteristic root, 特征根3 r$ e4 e, C$ L/ K
Characteristic vector, 特征向量
/ v0 }/ ]3 U- {7 k( @" |. vChebshev criterion of fit, 拟合的切比雪夫准则& Y& \6 E! P& B3 A. Z
Chernoff faces, 切尔诺夫脸谱图
7 l) Q( L( c. u: H/ XChi-square test, 卡方检验/χ2检验8 A3 W% \) K% \2 u
Choleskey decomposition, 乔洛斯基分解
1 g( L6 {/ k4 \( V0 iCircle chart, 圆图
/ v. O7 H4 k; Y8 F. d- [Class interval, 组距
2 C' W5 a6 b; U U* \' u2 [( d# i" |Class mid-value, 组中值. O5 W8 @ B; j2 A6 G' O
Class upper limit, 组上限
, R$ r: ~0 V2 A8 X! Q" U+ ]' n3 |Classified variable, 分类变量
0 P0 |+ n) r9 R- hCluster analysis, 聚类分析% r2 T" t0 h4 p- c. X4 {
Cluster sampling, 整群抽样. P4 V* G7 n% A0 h2 E
Code, 代码$ x- E( v4 L8 f- ? b1 l
Coded data, 编码数据
9 K' n% }2 Y" ]2 t) {Coding, 编码
8 z; F! q0 z4 V& S( H' a' NCoefficient of contingency, 列联系数
) |: y. K' S! l# `" w( q6 HCoefficient of determination, 决定系数
8 @4 M) L+ i8 nCoefficient of multiple correlation, 多重相关系数
s/ @+ _7 {: v9 T- e( @: ~7 A0 RCoefficient of partial correlation, 偏相关系数
4 o7 @/ O/ L8 N5 e/ e% CCoefficient of production-moment correlation, 积差相关系数9 n# }3 B- w$ R9 J& J) M
Coefficient of rank correlation, 等级相关系数
/ u$ k5 b% |7 T. rCoefficient of regression, 回归系数
0 w3 c4 J& z) M# s( K. a4 MCoefficient of skewness, 偏度系数
; T) x' T+ M* ]" f; GCoefficient of variation, 变异系数9 i9 C" X/ U; q+ D) H: l K. {: d$ E
Cohort study, 队列研究
" e7 v2 p5 l2 d) u# i7 ~- J) Y5 f; W NColumn, 列
0 e/ M2 f8 j) K, wColumn effect, 列效应6 z/ C1 X0 Q% R$ x0 a6 M; I
Column factor, 列因素
, f" c0 A0 Z( [1 r: kCombination pool, 合并$ W7 J: d j/ `" _- Y
Combinative table, 组合表
. i) }* t1 v B+ ?4 H ACommon factor, 共性因子
1 [" T2 A* p$ n, p) j" @Common regression coefficient, 公共回归系数; z3 {: p: i; h5 [6 _
Common value, 共同值
* l" z: C9 n/ L% G# p6 M' l2 mCommon variance, 公共方差" j% Q# ~! X( _# P+ C& F
Common variation, 公共变异5 z* q6 }1 ^* \! z2 O
Communality variance, 共性方差
4 x* ~% n- K9 M& VComparability, 可比性# m. Q! i: j6 O
Comparison of bathes, 批比较; m/ l$ s$ U* I0 i$ q M" U3 p
Comparison value, 比较值" H2 D8 E1 {. G) F1 n( a# z
Compartment model, 分部模型
P8 I; `! R# n# s5 f3 w& FCompassion, 伸缩: L; |: S7 I5 P9 n4 v
Complement of an event, 补事件' i4 }) z- I/ g3 h# E s
Complete association, 完全正相关- m* ]' @# ^. U! e9 W: N
Complete dissociation, 完全不相关: x" a9 m" V. q2 P& L) E; \5 u
Complete statistics, 完备统计量
: K# H6 x" S( d- L; X) w& yCompletely randomized design, 完全随机化设计' I% J- ]7 P' k7 j2 A
Composite event, 联合事件
/ _, ^* ]0 O8 ~9 b) u* JComposite events, 复合事件
; D j: A( U, dConcavity, 凹性5 u* [, i6 H A0 R( m5 k8 b4 w9 ~1 u
Conditional expectation, 条件期望( {- ?/ G' q9 @: S+ P7 P# Q4 U6 n
Conditional likelihood, 条件似然
7 O% U) l) }! u% _. i3 M* K/ zConditional probability, 条件概率
5 B- l# E" {/ r+ |) tConditionally linear, 依条件线性3 o. Y9 ?' n: c# W* K
Confidence interval, 置信区间
0 V4 t' ^. f0 `6 K7 [3 h NConfidence limit, 置信限; r7 f1 T7 L; Y- W5 j1 \
Confidence lower limit, 置信下限( {/ K0 S W. v* L1 \3 r/ \% i& [! k
Confidence upper limit, 置信上限: x3 y- v& b/ Y X) M9 }% f
Confirmatory Factor Analysis , 验证性因子分析8 ]1 l) m \7 y% z$ w9 |
Confirmatory research, 证实性实验研究
2 ?$ `. |5 Q# `1 `, ? n+ UConfounding factor, 混杂因素7 U3 I X0 L+ g9 {; c
Conjoint, 联合分析
7 V' q2 \9 e# r" `" [: e3 IConsistency, 相合性2 o9 X, d/ l) k1 C% b$ ?4 n
Consistency check, 一致性检验
) b k, Q4 g, v- t1 OConsistent asymptotically normal estimate, 相合渐近正态估计
: x6 f7 r; @ M, i: VConsistent estimate, 相合估计
3 y# H' I$ p; @& BConstrained nonlinear regression, 受约束非线性回归
$ u1 q+ C9 h" M& [Constraint, 约束$ H/ G8 ]+ D9 ]) F
Contaminated distribution, 污染分布4 z0 M, r. w) K0 a, P8 c9 s0 d
Contaminated Gausssian, 污染高斯分布
1 x0 q4 y" ^% k7 C) p' zContaminated normal distribution, 污染正态分布
3 U% B- G/ n6 L# z' W* N$ dContamination, 污染& e1 t( I! S5 d0 {
Contamination model, 污染模型
- L! U3 s; x5 \0 [3 b6 Q `Contingency table, 列联表0 R" x% `7 n0 Z0 U
Contour, 边界线9 k) N% t7 Q5 R- w5 U5 r
Contribution rate, 贡献率, R4 f7 \: t' B6 n% \- X$ Y
Control, 对照
W+ i+ z7 ^1 N7 D4 V9 R2 NControlled experiments, 对照实验
, {3 h7 F& [7 L) F4 H( m. aConventional depth, 常规深度
8 e6 z" y% D6 t# t2 T# H; l8 S5 u' h c7 ^) IConvolution, 卷积
0 [ g7 Y# G0 r, o8 V7 u+ rCorrected factor, 校正因子
+ j, g3 v" O5 r7 V; v5 QCorrected mean, 校正均值6 e; `& X8 g: G8 y$ X# P
Correction coefficient, 校正系数. |7 c2 K/ ~+ }& b. Y" d: L5 I
Correctness, 正确性7 ?2 J0 h/ h& M8 g) L$ B
Correlation coefficient, 相关系数; U( Y9 j- t% `. H: Z8 E' I' m
Correlation index, 相关指数 N" W! L9 C s8 ]9 S
Correspondence, 对应
8 P( d6 z. _1 |5 q" nCounting, 计数
4 C; b. c m2 D1 ^- r( [Counts, 计数/频数
* j" S# m" I2 | J1 r. `' ~Covariance, 协方差9 Y& r2 q) y* D5 Q$ K. {
Covariant, 共变 $ |" ]* V9 ~/ ~! a
Cox Regression, Cox回归
. Y1 }7 |0 J- mCriteria for fitting, 拟合准则5 y8 W) `4 U1 a5 U
Criteria of least squares, 最小二乘准则* m0 m) b Y7 P- D/ b' L
Critical ratio, 临界比- y1 E; G6 E4 ]) y/ X$ b- ^
Critical region, 拒绝域/ R& k& x7 o1 Q5 ^1 P' t8 e9 H
Critical value, 临界值7 o7 n1 G6 X; B- m [! S7 u5 D
Cross-over design, 交叉设计
( T5 R# I* [% R1 ECross-section analysis, 横断面分析
( o( n4 o+ c c- c6 }/ b- H6 `Cross-section survey, 横断面调查
: k( ?8 |; }, g8 ]Crosstabs , 交叉表
- J2 i2 Z3 u: H$ g) [* {+ gCross-tabulation table, 复合表, M% M2 {" @* F+ c0 G
Cube root, 立方根
/ `: }, N2 f. n" t8 d$ JCumulative distribution function, 分布函数
2 n B$ H; x) t; xCumulative probability, 累计概率: h, O0 T! T7 d( F
Curvature, 曲率/弯曲3 a2 k) n8 k& s2 {4 k# T6 ~# j
Curvature, 曲率
% \% |2 v8 h0 d1 {) J8 |& BCurve fit , 曲线拟和 8 k& e+ N0 J) x O& s* f; n
Curve fitting, 曲线拟合
/ Y5 \* a2 q8 WCurvilinear regression, 曲线回归
, j, s0 {% m4 V- `# lCurvilinear relation, 曲线关系3 T5 N: x2 p- q8 s" _" d, R2 M6 G
Cut-and-try method, 尝试法
5 J5 @; w. o0 i( e% }- `1 B/ uCycle, 周期, I! l4 L5 n, Y/ b3 i/ u
Cyclist, 周期性
4 v7 V: z* ~8 f9 |) j2 w4 n+ {( qD test, D检验
. Z+ w9 z3 i: Z% z# z$ d9 x) F- gData acquisition, 资料收集
& B! c t* f+ ]0 N7 ZData bank, 数据库2 m6 g6 w, G6 q; r9 e, n' E
Data capacity, 数据容量8 Q6 `& a0 @' ~: i+ @# N
Data deficiencies, 数据缺乏
/ V/ U6 |3 z9 G# MData handling, 数据处理% |5 m! l6 n; l0 [4 D9 t
Data manipulation, 数据处理
Q9 h6 L2 u; o5 P( uData processing, 数据处理& q* ]! T9 o( j* Y) l" L
Data reduction, 数据缩减' q1 K2 j8 L$ v s0 \1 |
Data set, 数据集
1 d r" `3 A% C3 I6 T6 \7 mData sources, 数据来源& X1 @. W/ l4 N7 u
Data transformation, 数据变换
/ g. N8 F$ k" k# w8 p/ xData validity, 数据有效性
# m3 L* r8 D/ @' {6 l' T. G" AData-in, 数据输入0 U/ B' c$ F% t0 q' K$ T
Data-out, 数据输出# a# n& i$ r' R' w$ ^; }
Dead time, 停滞期7 v& c# v+ q5 X, Y2 W$ q
Degree of freedom, 自由度6 H1 C5 w/ p7 V. ]' R" a8 V* x
Degree of precision, 精密度
1 \. l7 h+ ]( BDegree of reliability, 可靠性程度
# ^7 Q/ ?# w n# k/ uDegression, 递减7 S0 u* j% q- n3 g7 M
Density function, 密度函数 }( s, n0 ]1 A+ H, _3 p
Density of data points, 数据点的密度% G- I" {& q3 r$ T! h0 v+ {
Dependent variable, 应变量/依变量/因变量) G, e/ Q+ t* x
Dependent variable, 因变量, g0 a4 h, f, G3 v3 d! q+ {7 u
Depth, 深度
# _( t% N7 P' K& m3 a4 N: rDerivative matrix, 导数矩阵) h3 U7 S5 r4 J; }* L8 x0 y
Derivative-free methods, 无导数方法
* P2 v; {* o. f/ WDesign, 设计7 m( m3 W0 M0 X8 x# {' `8 Y& E
Determinacy, 确定性- P$ [* n: \2 c3 [0 _
Determinant, 行列式
, p- q; x8 |6 t! Y- F$ e3 TDeterminant, 决定因素# f% U* x: z! u+ f7 S& ~- B/ ^
Deviation, 离差
9 f8 D- m9 z' ^. V3 X0 ^) PDeviation from average, 离均差: A$ S2 Y a; J0 p' x- u
Diagnostic plot, 诊断图
f) v- y" X4 O, L9 _0 E' O' N, CDichotomous variable, 二分变量7 s5 b+ n6 W- J& j. @
Differential equation, 微分方程! Z/ r7 g7 l* z k9 g# a0 M
Direct standardization, 直接标准化法
8 V' ]1 g* l: | x4 s- K) j* V) Z3 tDiscrete variable, 离散型变量
$ L$ ]1 s- `( nDISCRIMINANT, 判断 3 A- r% l" ? i! {* Q6 W
Discriminant analysis, 判别分析
! i& k0 h# Q+ b# y2 A0 sDiscriminant coefficient, 判别系数; [- @9 _2 [3 j" c8 j8 {0 t c
Discriminant function, 判别值4 L/ H% V$ Y+ ^; i
Dispersion, 散布/分散度3 t/ j( H( w: s7 o. r$ T
Disproportional, 不成比例的
% ?; z% J" N" ]/ D. X. iDisproportionate sub-class numbers, 不成比例次级组含量" X3 K7 p5 T- M/ C: f, ~
Distribution free, 分布无关性/免分布6 O3 \# B( c1 g6 l
Distribution shape, 分布形状$ E" O& R0 V0 g0 Z; c3 e
Distribution-free method, 任意分布法
7 F8 m; a" ], R9 R( V( KDistributive laws, 分配律
7 O& d& ~7 D F. z) n+ a% p0 k! vDisturbance, 随机扰动项
: n# b9 B$ |4 @5 UDose response curve, 剂量反应曲线0 X/ k. y' U; R6 D! O+ Q
Double blind method, 双盲法. Z/ J" Y4 |+ k
Double blind trial, 双盲试验
/ }3 I2 `/ P [/ N* ~$ J, N2 ODouble exponential distribution, 双指数分布: c/ H. [- J u2 \
Double logarithmic, 双对数
D% y% k3 {9 kDownward rank, 降秩
; P1 h; x0 u2 a2 _3 tDual-space plot, 对偶空间图
8 t! C3 {3 h* cDUD, 无导数方法, Q6 c# r. v% W. x2 I2 ]& U
Duncan's new multiple range method, 新复极差法/Duncan新法
7 c+ }( d: ] xEffect, 实验效应4 o% Z$ w) M$ g1 U
Eigenvalue, 特征值. A' C( g' t9 D
Eigenvector, 特征向量
. ^1 ^" K5 K7 J+ n6 E( ]1 BEllipse, 椭圆" f2 Z# F+ |6 W7 N! k. z) b: B, D
Empirical distribution, 经验分布0 ~- G7 ^9 x1 }4 ~
Empirical probability, 经验概率单位5 B7 Y7 y( _: Y- P
Enumeration data, 计数资料
4 v3 [/ l9 ?- U' x, DEqual sun-class number, 相等次级组含量
$ D# S. m6 g# iEqually likely, 等可能
, s7 L, h( ?3 E& x9 q4 X7 H7 z3 j pEquivariance, 同变性/ w. i, ^6 @% ^; E6 @" N, d& a
Error, 误差/错误
% ]' Z1 p& w" k7 P0 oError of estimate, 估计误差9 g3 b7 G M. L- T
Error type I, 第一类错误, O4 ]. R5 b, s. U0 i: z2 e
Error type II, 第二类错误
7 |/ n) d9 h6 _7 \# {/ iEstimand, 被估量; {4 ~1 y0 ^, L( L. O: \4 Y9 u
Estimated error mean squares, 估计误差均方
8 }( z7 f" P& S/ f- {Estimated error sum of squares, 估计误差平方和
4 H2 G, v4 u6 |) E4 G( ]" X8 ~Euclidean distance, 欧式距离
. [# f P7 b6 W5 s: {: @Event, 事件( k/ N% w5 X! t' ?# n; v/ L" U) F3 l
Event, 事件
9 m3 R: w+ ~: f8 k9 n( P* yExceptional data point, 异常数据点
1 R% }6 H7 w9 O" J6 b- i% mExpectation plane, 期望平面) G6 h/ g- R. _1 V" ~9 o2 x l
Expectation surface, 期望曲面
7 I! C6 p7 u: \& |: `8 f' zExpected values, 期望值
2 d& K$ B$ M3 d: Z( H1 j6 I1 kExperiment, 实验2 P) {1 ], m2 M2 J& e
Experimental sampling, 试验抽样" j* J. U- m1 a, @% R
Experimental unit, 试验单位
4 W4 m8 D, U1 g* Z% ~. ]Explanatory variable, 说明变量 |' x( Y; C( V
Exploratory data analysis, 探索性数据分析
9 h9 w4 ~) t; [- wExplore Summarize, 探索-摘要
# d+ _( e" m/ X' w N1 c+ eExponential curve, 指数曲线6 o8 q- ~ r( U
Exponential growth, 指数式增长; v% q2 a/ p$ P. D/ K9 C! p
EXSMOOTH, 指数平滑方法
# Y! {5 U$ z& f! H3 O, E6 V+ E" ^Extended fit, 扩充拟合* a; c% {1 S' L B$ [8 w; t+ o! n
Extra parameter, 附加参数
/ O0 W3 k, i" d- W/ e+ hExtrapolation, 外推法
. A5 h: q0 M! PExtreme observation, 末端观测值
& f3 F8 d2 A8 pExtremes, 极端值/极值6 Z9 [' ^& `3 j, U6 @- f) n
F distribution, F分布
6 H8 O y, q4 NF test, F检验
6 r1 i; u+ h# {3 c. i3 J1 g! @Factor, 因素/因子( T/ T7 |( V) r
Factor analysis, 因子分析
; Q( k+ K" a% z0 s( @$ h3 Q- mFactor Analysis, 因子分析; c: j9 a+ A9 @
Factor score, 因子得分 7 L- M2 `+ W( ?: k/ T# M# v
Factorial, 阶乘
$ P3 g4 e E" d, A) S$ j& I8 LFactorial design, 析因试验设计8 p/ o- k- v! k) @3 @% G1 E, V
False negative, 假阴性
' @! q' _; w' N& sFalse negative error, 假阴性错误* D! z( M0 _8 |- Q3 s
Family of distributions, 分布族0 U7 S6 q v- n' e) }' p6 P
Family of estimators, 估计量族
4 H$ _% N' f4 m* {' m/ A+ n$ C# TFanning, 扇面5 m) Z" k* e1 r8 o6 q4 E3 f u# {
Fatality rate, 病死率1 x4 V* p5 o( V' m: D
Field investigation, 现场调查
7 V: _( {# R5 N/ i3 l% }) MField survey, 现场调查
( u2 ~1 I8 c; z& f4 h; Q1 ]Finite population, 有限总体& v, V. o, ]8 X3 k3 S5 D0 e
Finite-sample, 有限样本% O" |' t ^ l( [3 I! u
First derivative, 一阶导数% k& V8 u0 X' x# Z
First principal component, 第一主成分" R: A Q( p Y+ k# Y5 x
First quartile, 第一四分位数
/ s- `" r% s, ]" p2 AFisher information, 费雪信息量5 R/ F( c9 _/ e' Z$ }: i4 E
Fitted value, 拟合值' A7 s/ G' s& n1 H+ p# E+ S
Fitting a curve, 曲线拟合
2 @' [$ _7 H- e7 ^6 \1 B9 [9 DFixed base, 定基) ^& Z. K# ]$ N2 H7 g# e v
Fluctuation, 随机起伏6 i4 Y# Q" ? \- w5 f
Forecast, 预测5 N8 N0 c& u( ^/ S: H
Four fold table, 四格表
. d/ z/ v6 T c) U. rFourth, 四分点
" u' p& P' a* d7 U2 A$ FFraction blow, 左侧比率: {! k. b/ x' H) z
Fractional error, 相对误差 U/ R9 D' G; L: c/ Y! ]( m% K
Frequency, 频率
- `0 M' e! e- @0 D8 ?Frequency polygon, 频数多边图
6 V: `6 H* X* pFrontier point, 界限点
- S: F. v/ `9 c: \% ~0 A) ?Function relationship, 泛函关系
* v' t: M! L- ~; A" o a/ a( O" KGamma distribution, 伽玛分布
3 v2 I/ t- Z5 J6 H* @* ^- h/ lGauss increment, 高斯增量
0 \: G6 t' V5 NGaussian distribution, 高斯分布/正态分布! C8 H# H3 h! t G
Gauss-Newton increment, 高斯-牛顿增量
9 j: S; u3 R1 o+ L+ FGeneral census, 全面普查
2 F! a8 B% U/ E4 Z6 DGENLOG (Generalized liner models), 广义线性模型 % G; s+ l6 C5 R2 u3 Z
Geometric mean, 几何平均数
( D& V; V7 e/ G' z: p$ J; kGini's mean difference, 基尼均差
% [2 E! X2 b: \& E( L' n2 i1 XGLM (General liner models), 一般线性模型 & ~1 d! Q2 f; e0 L
Goodness of fit, 拟和优度/配合度
2 W9 s- `* F+ K; _' \Gradient of determinant, 行列式的梯度
" p7 I0 K0 _; m7 zGraeco-Latin square, 希腊拉丁方: y7 U& } n& b% `7 j$ E% Y7 c5 W
Grand mean, 总均值
. k; P; J3 Y) s$ T% HGross errors, 重大错误8 y% \& u3 c" N, ^1 i
Gross-error sensitivity, 大错敏感度
: P0 J3 E2 ]5 t0 j2 L: M6 V+ |3 o1 qGroup averages, 分组平均2 F% m$ j4 g: d: Q3 W T, Z8 |: X
Grouped data, 分组资料9 O0 Q6 B+ C6 x7 l! R5 g& W' K
Guessed mean, 假定平均数
[7 a+ }3 ?* C/ o; b8 T" @! y+ y" ?. o* fHalf-life, 半衰期
u! Q& a1 ~: zHampel M-estimators, 汉佩尔M估计量
, O$ g, y4 C; q2 @Happenstance, 偶然事件 X- d; t0 v( f4 A: ^3 g- G: [5 e {
Harmonic mean, 调和均数
" O& Z& a! a* R5 Z7 J9 U) o2 [Hazard function, 风险均数: { b/ ~( _' g; Y+ A
Hazard rate, 风险率
6 p6 n5 y' q6 E, o: L5 \% ]6 ?Heading, 标目 5 V7 O1 v& r2 D& |; t, v' F
Heavy-tailed distribution, 重尾分布: Q% ~! X3 U9 N6 m& j* |8 K
Hessian array, 海森立体阵
1 l1 G9 h, } e$ v+ r: }1 V: \0 kHeterogeneity, 不同质
+ v2 u6 D1 R1 q. {+ t0 dHeterogeneity of variance, 方差不齐 1 C! o- z, ~- [9 z8 l! k
Hierarchical classification, 组内分组7 \8 p# W |- g% J' F
Hierarchical clustering method, 系统聚类法
6 _4 R+ p5 ^8 P% y5 l, c& z4 [High-leverage point, 高杠杆率点
" R) J, ~: ~' x1 OHILOGLINEAR, 多维列联表的层次对数线性模型
+ p( N% P: i. \( jHinge, 折叶点
, }3 Y1 g. j! E D }8 eHistogram, 直方图4 ?0 ^, v2 d j6 ^, m
Historical cohort study, 历史性队列研究
. s( O0 Q+ x$ b* K8 c* _Holes, 空洞
% H9 l# U+ n5 f6 ^" ?3 QHOMALS, 多重响应分析
: D6 p) o0 g# Y3 }. y: S7 b sHomogeneity of variance, 方差齐性2 z& E) [% Z8 Z& P9 [
Homogeneity test, 齐性检验1 g* n( n# H. ^
Huber M-estimators, 休伯M估计量7 m3 O9 W$ o" r$ o$ Q* N1 F
Hyperbola, 双曲线
8 I2 P4 w. @# VHypothesis testing, 假设检验
5 H) _# ]- e; b" F+ WHypothetical universe, 假设总体
; K& W c$ a3 a2 OImpossible event, 不可能事件
' G: r% Q) c* q3 T/ A2 D. V# y9 a: FIndependence, 独立性
2 ~3 c) N* M9 T2 {: b; F/ @6 gIndependent variable, 自变量/ A* i- y* M8 Y( f! n0 }' e# l
Index, 指标/指数3 |& v9 a+ m4 E: F' w
Indirect standardization, 间接标准化法, x8 h# v1 z4 S
Individual, 个体- s1 _! W; D7 G
Inference band, 推断带
, ?% @7 m5 _- l5 }* P/ ~* B9 fInfinite population, 无限总体
5 n( D6 ]$ O- CInfinitely great, 无穷大, x7 j" t. }: z6 a/ B
Infinitely small, 无穷小, ^( Q, {4 ?" G. a: U
Influence curve, 影响曲线: U/ @1 m5 n `; [" ]. r) a) H9 @5 T3 @
Information capacity, 信息容量
3 e$ Q! Q( E! Y4 p: g. AInitial condition, 初始条件
" u1 n! ?7 Z7 {1 s' E$ H. ?Initial estimate, 初始估计值9 T+ Y* d, @% G0 H' v
Initial level, 最初水平, Y+ L' ~2 d0 V. J" A& |. @
Interaction, 交互作用
. \# h* ~3 |! p) i" E1 E- \: FInteraction terms, 交互作用项
! D3 z% f1 }- b* q2 c0 WIntercept, 截距
, P$ R9 @* f( w5 o6 l" m ]Interpolation, 内插法- i% h7 G. @7 u6 v; s+ f0 o* Y
Interquartile range, 四分位距( f' I; Z q5 n; T* d! b! h- l
Interval estimation, 区间估计) N: N# M3 z# g! I. H5 z: z
Intervals of equal probability, 等概率区间
' U$ t# Q. j% b8 KIntrinsic curvature, 固有曲率
/ a$ y/ \; V. B* ?; UInvariance, 不变性
0 q3 i3 c8 {; l. q% E7 LInverse matrix, 逆矩阵
/ r p. C% V. K$ a$ y# |: ]Inverse probability, 逆概率0 o8 c$ J. O4 d8 {$ m) f9 e
Inverse sine transformation, 反正弦变换/ E# X1 X: e) p2 e' ?
Iteration, 迭代
: W4 A$ v9 a# w' @* j; f" D" sJacobian determinant, 雅可比行列式
# N/ M: K2 j$ B! E( \! z# sJoint distribution function, 分布函数* z! P7 g# m$ Q) Z0 B" T c7 h( b# C: o
Joint probability, 联合概率. J. r3 }( D& H! R# d
Joint probability distribution, 联合概率分布+ y3 t0 Z8 j, ^2 M6 V+ z
K means method, 逐步聚类法* C3 h5 X& k2 W( z6 E G
Kaplan-Meier, 评估事件的时间长度
7 G& Y) d$ }% p( m& V+ ]/ q. nKaplan-Merier chart, Kaplan-Merier图' k: v y% l& Q( _1 K
Kendall's rank correlation, Kendall等级相关/ t7 M( B. r2 `2 \/ c( S
Kinetic, 动力学; ^' G$ H; A4 n# L, @) r
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验, K4 Y6 s2 s4 M3 K/ X, R) d x
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验, {: u3 k+ G, `% G- g& K
Kurtosis, 峰度
- y; n6 ~1 C2 {4 U. e2 hLack of fit, 失拟
. t9 A0 r* z7 W3 r. T. a+ p* ILadder of powers, 幂阶梯
0 Q G7 M, L- t U$ P* F2 zLag, 滞后
9 h4 L( i! Y9 k/ VLarge sample, 大样本% }! y+ c/ q" @' s% Y
Large sample test, 大样本检验$ u* w5 S% u: W/ Q
Latin square, 拉丁方0 y3 ~- }. _' H* ~4 `* W
Latin square design, 拉丁方设计, L% J! |+ A K& x. _
Leakage, 泄漏; L1 f+ o: ?+ \. u
Least favorable configuration, 最不利构形
& |* H6 S/ M( SLeast favorable distribution, 最不利分布, i k* r3 `+ _, c) }
Least significant difference, 最小显著差法
8 u) M; s) |- Y; [% ULeast square method, 最小二乘法
# S* V- F( \$ {8 z# wLeast-absolute-residuals estimates, 最小绝对残差估计9 {6 ]+ y; c, A! t8 p o( R
Least-absolute-residuals fit, 最小绝对残差拟合7 f$ f$ K" i/ b1 _6 s, y2 ~- |
Least-absolute-residuals line, 最小绝对残差线
. e. D5 A! L- V9 Z# F& QLegend, 图例" ~6 N: m$ t1 b4 k
L-estimator, L估计量1 V( c) t; g$ L* Y( @
L-estimator of location, 位置L估计量
) d3 R a, o3 @6 o0 aL-estimator of scale, 尺度L估计量7 V' l% `' E& [* R, U6 o1 i# r, q
Level, 水平
: {. {6 H& F+ E; T: TLife expectance, 预期期望寿命4 r* C8 ]# g, H, l. l- B
Life table, 寿命表
( f# x9 n1 K: |8 m p; ELife table method, 生命表法
( E; G1 W8 n4 c# f; y: x+ DLight-tailed distribution, 轻尾分布
9 W* J! d8 p8 B& d! B2 QLikelihood function, 似然函数
# L7 e: G2 _: ~ {9 E' k0 eLikelihood ratio, 似然比
) H' ~; s0 H9 [2 k4 @2 {line graph, 线图, c' b- D% z& m3 b3 ?- \. A
Linear correlation, 直线相关# x" S h$ C$ t
Linear equation, 线性方程2 {- D1 F" }+ r1 g3 ?) U
Linear programming, 线性规划( T( K8 C$ y8 @
Linear regression, 直线回归
* s ~4 u1 O- d5 XLinear Regression, 线性回归
4 `/ K: Q) E. G! cLinear trend, 线性趋势
+ N! k5 f+ p# W, bLoading, 载荷
6 t* w: s1 D- d- r; V% T) }% g6 mLocation and scale equivariance, 位置尺度同变性
/ h9 j/ R% M+ i R1 T+ oLocation equivariance, 位置同变性, E4 L7 j! C# [
Location invariance, 位置不变性. c# S) U- Q6 C: z( P& ^9 t
Location scale family, 位置尺度族- J5 }4 w; z5 F& Z) h
Log rank test, 时序检验
; s1 _5 z+ m. i9 E+ {- _( o3 uLogarithmic curve, 对数曲线1 C3 }) S4 g) U4 s- `) d5 M
Logarithmic normal distribution, 对数正态分布$ N1 }/ q& H' M5 B
Logarithmic scale, 对数尺度
$ ~% m0 \- }1 W+ p, K1 }Logarithmic transformation, 对数变换' K2 B3 B; U& Z+ k0 [
Logic check, 逻辑检查* [1 i- |5 j& e! q e
Logistic distribution, 逻辑斯特分布5 Z7 y Z( R! m l0 Q1 k
Logit transformation, Logit转换- s8 x* h4 i3 @. J% n6 w/ b
LOGLINEAR, 多维列联表通用模型 $ V W& ~+ f! O3 m6 a
Lognormal distribution, 对数正态分布
" D3 ~' D" z1 ?. o+ bLost function, 损失函数
+ Z) `+ E' h0 b& i- E3 i$ YLow correlation, 低度相关! W: }# `5 c7 V6 e+ C$ Z6 @9 h- ^
Lower limit, 下限- u2 k) q9 u% C% O1 Q
Lowest-attained variance, 最小可达方差
" H l# a( m) hLSD, 最小显著差法的简称
% c+ s. W+ C% c1 JLurking variable, 潜在变量8 v6 e! }" ?! T- e. l) i5 k
Main effect, 主效应
9 V+ [+ g: Z9 a! `/ c$ ^Major heading, 主辞标目9 L7 P5 P1 q6 m, g/ }% ?
Marginal density function, 边缘密度函数
" g% @% ^( N# }+ C. ]& tMarginal probability, 边缘概率
( C! [* T- _. L ]3 d# p" wMarginal probability distribution, 边缘概率分布7 s$ ?) p& e7 I! s
Matched data, 配对资料
S B X& S2 {3 M) tMatched distribution, 匹配过分布
+ l% e) B' \! sMatching of distribution, 分布的匹配! l3 d0 k) F; B
Matching of transformation, 变换的匹配
8 {6 |5 I# W/ h& k3 |: \: S6 z7 GMathematical expectation, 数学期望) `0 C6 m) \# X' D t
Mathematical model, 数学模型8 R( H1 M+ {' z& N; B. A
Maximum L-estimator, 极大极小L 估计量
: p+ t% g* J3 g; i# D @Maximum likelihood method, 最大似然法
- ?7 ]5 |/ n- Z! o0 h& J: t3 xMean, 均数% E' h8 c1 J! G
Mean squares between groups, 组间均方
3 h( }+ p2 f) C( m c6 Q8 C7 FMean squares within group, 组内均方7 h2 E1 A0 z, P$ Z, Z6 Q$ {
Means (Compare means), 均值-均值比较
( G. }( A& j" }- o+ ^- e2 C! ~0 ]Median, 中位数
4 h( Q% y2 Y6 C4 W0 |/ h! xMedian effective dose, 半数效量! U Z/ Y$ A; Z/ M0 s1 M4 m$ L
Median lethal dose, 半数致死量
* d, u$ O& J" nMedian polish, 中位数平滑# t- s9 H4 E7 Z3 {) I5 J
Median test, 中位数检验3 a/ g, W. \9 M& z
Minimal sufficient statistic, 最小充分统计量5 J8 Z9 @. O/ L" x0 B2 ?5 ~3 ?
Minimum distance estimation, 最小距离估计0 _# R2 b ~- h8 m
Minimum effective dose, 最小有效量
/ j0 O. o$ a' A* b% P- m* ~% ]Minimum lethal dose, 最小致死量
: E* R$ V$ h9 f* TMinimum variance estimator, 最小方差估计量
" a1 ~3 Z& S; u* C/ Q+ w. xMINITAB, 统计软件包
% N7 @1 h7 Q9 y/ S: g! _Minor heading, 宾词标目; A; w' [8 g1 p0 C( H7 r
Missing data, 缺失值& M, c8 V+ s. W+ ^% x+ j: Z5 o
Model specification, 模型的确定. a( u1 L, L1 O, D: U1 Y+ u
Modeling Statistics , 模型统计# F$ F) [% U0 t: i. s
Models for outliers, 离群值模型
. R: c- P! N; Z5 SModifying the model, 模型的修正: x8 L) e- ]/ c+ }1 Q5 l3 i, |
Modulus of continuity, 连续性模4 Z0 K, A0 z: K% } @+ t9 e; r$ V6 K
Morbidity, 发病率 % D& c9 ?& y4 M- f8 u
Most favorable configuration, 最有利构形
2 |9 v5 s' L, s2 J% {* F( V, bMultidimensional Scaling (ASCAL), 多维尺度/多维标度7 D) H$ W$ [: x: p
Multinomial Logistic Regression , 多项逻辑斯蒂回归
] |* s& @1 {- mMultiple comparison, 多重比较, n: A% E# @, m" A( ]9 u# |
Multiple correlation , 复相关
) B `% i( `$ O0 R" o2 h; B" B( OMultiple covariance, 多元协方差
( c/ t ?1 e; }( x E) aMultiple linear regression, 多元线性回归
- w) f! d) d, T; `2 [# n% D$ NMultiple response , 多重选项
' Y0 c% W' L7 v c' D( K! bMultiple solutions, 多解
: ^0 \/ Q& X0 V' t' v) hMultiplication theorem, 乘法定理
5 v" G7 K: V& m$ i/ W: q, v9 k+ bMultiresponse, 多元响应# v3 e7 y3 C% g. N3 `2 p5 L: D
Multi-stage sampling, 多阶段抽样
% J$ x! l R2 Q- z# xMultivariate T distribution, 多元T分布* E* E! N* ~0 @5 q( W
Mutual exclusive, 互不相容
6 n7 A7 w( \: JMutual independence, 互相独立
8 o/ n. g! \: {( KNatural boundary, 自然边界
# [+ W- r- L d8 dNatural dead, 自然死亡; S- a( G4 e7 J# q _. p: U9 ~# q
Natural zero, 自然零* S B2 z% ]& ]: |
Negative correlation, 负相关
( ?% d& F$ i0 \+ i" {- J; XNegative linear correlation, 负线性相关 K* c- J A( U* }5 h
Negatively skewed, 负偏
- R" m, v3 R5 ?* W) U( C/ pNewman-Keuls method, q检验6 }9 y' }; B0 Y/ r5 g% X9 b' J
NK method, q检验
6 Q$ Q7 `4 }/ R+ X8 XNo statistical significance, 无统计意义
! U3 S# O+ e4 G$ pNominal variable, 名义变量
1 l3 m Z+ }1 P6 g) G6 c: ]8 gNonconstancy of variability, 变异的非定常性; _# r# r! X( m9 _3 y1 Q
Nonlinear regression, 非线性相关
3 F2 j: c$ T7 [' N3 i8 ^# u: DNonparametric statistics, 非参数统计6 U) r: }9 M& \, |
Nonparametric test, 非参数检验. ?$ d u) X6 Z4 U/ p6 Z, f- {
Nonparametric tests, 非参数检验1 u4 U7 v+ [; o5 V
Normal deviate, 正态离差
U. o" w G; t. ]4 N5 M: @. jNormal distribution, 正态分布
: p2 I; Q( M* o) [- C# v GNormal equation, 正规方程组: T9 V* _& `/ F6 ?" U
Normal ranges, 正常范围 Y) S$ H6 ^: y1 ~; B3 R. U; [
Normal value, 正常值
; t8 E4 s/ B9 b; {: {$ nNuisance parameter, 多余参数/讨厌参数 s! v( p' [% W X
Null hypothesis, 无效假设
2 _: ?9 ]1 j9 f& ZNumerical variable, 数值变量
' {0 H' p! }8 T; T: m3 ^/ D% ?Objective function, 目标函数
! z5 z* Q X2 U* a+ H, HObservation unit, 观察单位
1 W- l# |- C7 ^" gObserved value, 观察值
$ y* S" O# q* c3 V! b! m6 d% |One sided test, 单侧检验
1 w. P! d& Q* _' `+ IOne-way analysis of variance, 单因素方差分析1 a9 v. D$ B: s) ]# z
Oneway ANOVA , 单因素方差分析& b7 ^6 E r, K2 Q/ x
Open sequential trial, 开放型序贯设计
4 `" M3 B; m! a# ?% F" rOptrim, 优切尾) u+ t7 G$ u, f" ]" P$ v
Optrim efficiency, 优切尾效率% L7 _8 F4 W/ f5 c& E' ~2 _
Order statistics, 顺序统计量
1 Y* J+ K0 v2 z" P* W: k8 v5 Q" ?Ordered categories, 有序分类
6 B$ W5 X9 g+ \Ordinal logistic regression , 序数逻辑斯蒂回归1 j7 \* k l& _" [" b: O3 j
Ordinal variable, 有序变量
' O. @1 W `# ?$ @0 u3 Y' bOrthogonal basis, 正交基
9 S# s/ O% }: {/ f4 l G8 ROrthogonal design, 正交试验设计4 I) {/ Z* M6 \/ Y9 w/ b
Orthogonality conditions, 正交条件2 I' y% |- N' L$ o
ORTHOPLAN, 正交设计
& |% H! l: [! e, E* Z+ \0 ^5 D, P0 \Outlier cutoffs, 离群值截断点4 D2 H' u! c2 w) @5 t
Outliers, 极端值9 q) p! u+ h7 [/ Z0 R
OVERALS , 多组变量的非线性正规相关
: W1 B N, d {; c- y# A: H8 zOvershoot, 迭代过度
3 L! E0 W% H$ D: XPaired design, 配对设计; v0 ]$ |- u8 J% F9 r* U
Paired sample, 配对样本; \7 }4 c7 ]7 c2 v6 P& |' ?) C
Pairwise slopes, 成对斜率
$ D( X" x" j; T, C9 h u- m" _1 kParabola, 抛物线
) v. d. L+ K* g* y% ~4 f b( UParallel tests, 平行试验- h3 {, D9 Q6 }, }1 n, O3 h
Parameter, 参数
, |- {2 i1 x/ H ~! l$ T7 Y+ FParametric statistics, 参数统计4 A; Q5 I" d" \4 m
Parametric test, 参数检验$ `0 f% Q- e& r; Q" e0 z0 E
Partial correlation, 偏相关
) Z* o7 _* `+ u2 h# ePartial regression, 偏回归
+ G" n( }! n9 TPartial sorting, 偏排序
% Y* [8 ?7 Q( l( GPartials residuals, 偏残差
% t% X4 I, @1 i4 w' e. w9 ?Pattern, 模式
3 G; O7 W' Z Z# Y. rPearson curves, 皮尔逊曲线
) Z2 `2 \* N) w& l' V6 z2 GPeeling, 退层 F2 f9 n& J$ [2 d7 ^5 M6 G
Percent bar graph, 百分条形图: o" f8 I( T8 }
Percentage, 百分比! a3 }5 w* d) u. s+ l
Percentile, 百分位数( m2 v. l4 R1 N0 ]$ O- s
Percentile curves, 百分位曲线" ?/ A) R' @6 B2 @$ K
Periodicity, 周期性
: h8 l$ X: _" `. q! JPermutation, 排列8 J1 y4 N S! |. g7 {7 B
P-estimator, P估计量8 s1 M; A# p% X3 n" {
Pie graph, 饼图
* h* Z! K# v. w, T7 MPitman estimator, 皮特曼估计量: d: y, _+ {! q; W4 @4 a9 K1 ?( p
Pivot, 枢轴量
4 q! W+ l) ]% n, E n0 [9 xPlanar, 平坦
1 A3 d+ Y1 Y8 ~2 m6 d7 WPlanar assumption, 平面的假设& {) A# C1 u6 C/ O/ r, e
PLANCARDS, 生成试验的计划卡9 l. t) g1 t8 P, d3 `" N
Point estimation, 点估计
5 e5 Z4 X- Y5 P+ u& e+ yPoisson distribution, 泊松分布7 @& }0 ^. X, n+ b1 D
Polishing, 平滑
0 o" S- E+ L9 d. y. P3 H. APolled standard deviation, 合并标准差) p) O( j; ]- n+ q
Polled variance, 合并方差
& R9 T. ^3 C0 J8 ~/ A2 |Polygon, 多边图
4 A" `3 W7 T" `% ]+ mPolynomial, 多项式4 G" v9 {; i- p7 M
Polynomial curve, 多项式曲线
% S: n/ O% b4 T9 l8 |' jPopulation, 总体
; l% q y( ~6 h) d* kPopulation attributable risk, 人群归因危险度
7 Q8 D1 W/ l5 o% VPositive correlation, 正相关
4 F% e8 m% {6 {9 W+ hPositively skewed, 正偏
, Q3 h+ c5 k+ n$ _Posterior distribution, 后验分布
' `( G, }1 m8 x O0 s( hPower of a test, 检验效能# W! e; D# Z" X
Precision, 精密度4 E1 N1 I8 U0 v+ N' S- s8 s
Predicted value, 预测值8 o( Z0 @% I4 N* L5 f4 f0 G; G
Preliminary analysis, 预备性分析7 ~/ A/ n" E l8 m- d2 L O3 R: @
Principal component analysis, 主成分分析
% [5 _3 }: [6 K$ K3 L/ [9 r9 ePrior distribution, 先验分布8 ]# f: p+ k' e: ?: h. K) }
Prior probability, 先验概率! S% r$ I* }1 x9 _ Z) h6 J
Probabilistic model, 概率模型
* Q$ P% h9 ^. n9 Pprobability, 概率
% p- V7 Z! s- U' T( @, m$ W* eProbability density, 概率密度
2 F- N" W; g. _" p2 S4 vProduct moment, 乘积矩/协方差
A* n( N# I5 y, A5 w; X" J7 lProfile trace, 截面迹图
. H1 R6 H0 Q. ]% u$ R: l! \Proportion, 比/构成比
4 ` |# ~, G. g) H, ]2 IProportion allocation in stratified random sampling, 按比例分层随机抽样 P2 w) K. S! g. T+ A* ~
Proportionate, 成比例) L3 f% x! H9 f5 e) n0 p! s! v
Proportionate sub-class numbers, 成比例次级组含量
?9 e8 K; n6 R! G1 f- cProspective study, 前瞻性调查
& [3 c( w' Z: i% Y6 m* t$ }9 X9 wProximities, 亲近性 * ^7 Z5 O# i8 Q; |* C, i! j
Pseudo F test, 近似F检验
; x2 l r9 }% ^% oPseudo model, 近似模型8 E# Z7 D, }5 p
Pseudosigma, 伪标准差$ D2 w4 Z7 F. \7 R) E
Purposive sampling, 有目的抽样( v; R9 K% g! L- k
QR decomposition, QR分解6 B/ P9 I! k4 H P& D
Quadratic approximation, 二次近似3 P" h2 f! m# B. \9 k ` B
Qualitative classification, 属性分类
# D( V; Q8 E, I( F7 bQualitative method, 定性方法
- Y- o0 Q, s: A$ L( _ i0 z, ` N5 WQuantile-quantile plot, 分位数-分位数图/Q-Q图
) R$ O# N% O+ i K, M3 W9 FQuantitative analysis, 定量分析
% }+ I5 W3 w" ]- h1 {- R) |Quartile, 四分位数
% g: }" F7 q1 F0 w LQuick Cluster, 快速聚类
1 f- y! D* F, b" bRadix sort, 基数排序& n. E$ d3 D E2 j9 p8 z) b, B
Random allocation, 随机化分组* m9 z" t/ b" _( p
Random blocks design, 随机区组设计1 b: ?/ {: U) [9 u& q- p5 z
Random event, 随机事件- \+ b! [: z! v/ |
Randomization, 随机化
. B( J* n! K7 G. d: G! |/ TRange, 极差/全距
7 ^9 I" ?' O3 |6 Z( ^8 s0 PRank correlation, 等级相关
* M5 e, n' l$ q% w& |" }Rank sum test, 秩和检验
' U0 ~3 V }3 ]7 a/ `! l3 x) eRank test, 秩检验
" C& H3 T1 e+ P6 r4 I6 URanked data, 等级资料
, I) u6 b# q( E" g4 d1 x8 rRate, 比率- F1 {0 c9 m4 ~9 g/ S/ V
Ratio, 比例; M" i3 V% N9 Q# p, G; \# l
Raw data, 原始资料
) ~4 p$ I4 O5 F1 G q% nRaw residual, 原始残差0 m9 P: i* u% |4 H( r/ S( i
Rayleigh's test, 雷氏检验
+ A9 x* o; I( C( T9 z7 o1 mRayleigh's Z, 雷氏Z值
x" B( o0 @! p7 XReciprocal, 倒数
$ a( a+ r0 \) QReciprocal transformation, 倒数变换* T$ z" z* ?/ \. H; w: C
Recording, 记录; M+ B- E& G0 |! I! r9 L
Redescending estimators, 回降估计量
& k" H1 j4 b2 o% GReducing dimensions, 降维
0 ?* a8 U9 @, O7 N, j2 b! q2 [Re-expression, 重新表达$ E7 D* k) Z- a X& V, A
Reference set, 标准组. E* i9 z5 ~9 n# T# H% }
Region of acceptance, 接受域! A9 E* `5 T$ Y: n1 ]* W- R
Regression coefficient, 回归系数/ g- @/ m" V" z' T1 I( L# e: [
Regression sum of square, 回归平方和7 ]# c- Q6 A2 b2 D- v% j5 N
Rejection point, 拒绝点+ S) H" b5 P H9 b9 f% P7 U
Relative dispersion, 相对离散度/ G$ t2 u0 H3 k; ]% I% V8 G; x
Relative number, 相对数1 ?/ f" f, i: J% ?5 e: ~# H
Reliability, 可靠性* y ~4 H* }7 @9 |+ o* M
Reparametrization, 重新设置参数/ E8 Y' ~4 u% L3 S' q" c& ^
Replication, 重复/ I0 p6 \! t9 N. m
Report Summaries, 报告摘要
. T3 @/ {/ n* E/ L. OResidual sum of square, 剩余平方和
2 X6 ~. z0 @+ M/ ~; F }) E* lResistance, 耐抗性
& j% {% ?5 W. Z! g' w2 eResistant line, 耐抗线
' n7 h+ b3 j. Q: V4 M& E! W1 A" |Resistant technique, 耐抗技术8 y( z1 \8 C$ F3 x) t ^
R-estimator of location, 位置R估计量
0 N* l8 e- d9 p! N8 `R-estimator of scale, 尺度R估计量
- y/ W. ` L# }Retrospective study, 回顾性调查 P4 y$ d) o5 Z% \
Ridge trace, 岭迹% G m5 K7 b6 h
Ridit analysis, Ridit分析' ?$ H; V4 t1 K9 ~+ s f
Rotation, 旋转
5 `7 ] ^7 v5 ?1 a6 j0 v' l! GRounding, 舍入
: t% x5 q' M/ m2 k9 Y2 wRow, 行
! h# D- P* h3 h, o% m, n. l, jRow effects, 行效应1 O* \, X4 }* ]5 H. |
Row factor, 行因素
* G6 E; B3 D; L! NRXC table, RXC表! l# c1 H& I/ X/ Z/ J
Sample, 样本7 S2 Q; @' _$ g' H+ h
Sample regression coefficient, 样本回归系数4 s& ], w. h% n: X. C
Sample size, 样本量
. Z- e( w* b1 {# B! [- E pSample standard deviation, 样本标准差2 Y* o$ E" p2 k2 G! y
Sampling error, 抽样误差" X0 `/ x# F q- X7 G; U
SAS(Statistical analysis system ), SAS统计软件包; R+ ^, D/ ? }. O$ ?. t
Scale, 尺度/量表
6 U. {2 a( ~/ s- P) [ Z' d' b! q# c) ZScatter diagram, 散点图 T4 q; f% n5 j
Schematic plot, 示意图/简图
& x5 C" Z2 m3 j5 c4 ]/ J) e) gScore test, 计分检验
5 I5 F' Q& c# D8 V/ J* m+ m* FScreening, 筛检; z( M0 ^, h+ {6 n; R! q1 a# ^; B
SEASON, 季节分析
9 G. h( V0 m3 ~% aSecond derivative, 二阶导数
0 K" c1 {, Z% y% L+ B4 a" T2 J% F9 SSecond principal component, 第二主成分( j. |1 `" S& n9 H% G( c
SEM (Structural equation modeling), 结构化方程模型
# L2 q- w3 j8 ]) x, D2 s, DSemi-logarithmic graph, 半对数图
# N! B+ b/ T& N+ XSemi-logarithmic paper, 半对数格纸
3 g; s! H/ N# m% D, t0 o( xSensitivity curve, 敏感度曲线! D7 a% w0 |3 w+ r, P
Sequential analysis, 贯序分析8 Z3 \' }2 ^# ^% z: R* d- e9 [
Sequential data set, 顺序数据集; n/ \' H8 E! J' d U# ?
Sequential design, 贯序设计6 y6 _6 O7 l V, e
Sequential method, 贯序法
- X K1 R; K, zSequential test, 贯序检验法
8 `1 c( n+ K* |- b4 m& a+ i" d! [Serial tests, 系列试验
# v* `+ n0 o! ^5 A$ v8 }Short-cut method, 简捷法
$ k5 B9 ]# ~; I( @Sigmoid curve, S形曲线: r) I8 A3 s( T9 i9 X
Sign function, 正负号函数
2 |7 [# |, D, J; ~0 J" W ]Sign test, 符号检验
" s! v/ m& f H3 y% G; }! ?Signed rank, 符号秩
* x4 A0 `' ~+ Y' U K8 j" j( kSignificance test, 显著性检验
3 s! z# j; i' oSignificant figure, 有效数字6 {- C) k0 a ~, R( X& R* h& U2 p: B
Simple cluster sampling, 简单整群抽样
% }4 p7 b- y/ P9 q4 u0 v, z/ @; uSimple correlation, 简单相关" j' T3 w0 R$ p7 Q/ `
Simple random sampling, 简单随机抽样
1 X% R# g; ~! E6 y3 ]% @5 DSimple regression, 简单回归
* s |0 C; z0 Q! Y% N2 u/ |3 Qsimple table, 简单表
- [. k. x- w: T3 SSine estimator, 正弦估计量
8 w+ k" L- \) }1 _Single-valued estimate, 单值估计% b) d0 g9 @ l6 T5 H# X5 `$ k
Singular matrix, 奇异矩阵" P+ k k H) g( J) p* F
Skewed distribution, 偏斜分布
f- ~9 |2 U2 N2 pSkewness, 偏度
+ B5 `- x$ u- \2 |- ^Slash distribution, 斜线分布
6 {* |# ^/ ^ c' n; A& x* [Slope, 斜率4 x7 O' ?3 q- D4 x9 R2 {+ O
Smirnov test, 斯米尔诺夫检验' g; G4 v. n8 r" L' u
Source of variation, 变异来源2 r- [7 B( }% _- c/ S" Z( o4 I S6 \
Spearman rank correlation, 斯皮尔曼等级相关! o% N S: ]4 Y, a, s- _# W
Specific factor, 特殊因子- D2 J2 \+ _3 G, e$ P
Specific factor variance, 特殊因子方差
9 Q4 o6 \, s. V0 P: CSpectra , 频谱, q. _+ A5 B% B# D- ~
Spherical distribution, 球型正态分布9 k0 W: Z, y% h
Spread, 展布3 Q( I! g$ V* ~4 a
SPSS(Statistical package for the social science), SPSS统计软件包
+ `! S* W J4 K( A1 `2 qSpurious correlation, 假性相关
* w2 ]2 O6 P) N4 O. u( cSquare root transformation, 平方根变换: e: B0 s+ L0 l, u& G' P
Stabilizing variance, 稳定方差/ H/ d' i$ c7 g2 U% Q. V4 U4 ^
Standard deviation, 标准差) V/ h+ X0 n$ j
Standard error, 标准误
0 I2 ?: |% h6 h+ w8 bStandard error of difference, 差别的标准误. Z3 ]; J1 c/ v% t% |# U1 ]
Standard error of estimate, 标准估计误差+ X& V" O% a. J
Standard error of rate, 率的标准误
7 j& b& v Z8 d2 D' ]+ k$ gStandard normal distribution, 标准正态分布
5 W; P6 [; H2 A# X% w; q7 pStandardization, 标准化7 a S1 P/ ]' j" K
Starting value, 起始值
2 P$ A* S! x& I5 b. RStatistic, 统计量
' a3 S; r' m2 I; \+ N% m2 F% WStatistical control, 统计控制) u+ f5 F6 I* O* v$ x
Statistical graph, 统计图
' U, s! A% C* P1 x# \' h' q9 VStatistical inference, 统计推断
: a% u8 h' D) ^- V1 mStatistical table, 统计表$ Z- ~$ P9 B! O/ A: S
Steepest descent, 最速下降法
7 T% j& x( e5 i9 k2 EStem and leaf display, 茎叶图- d% ?( u: D$ r6 W
Step factor, 步长因子
" t) t9 r& O5 } {4 Y4 w3 oStepwise regression, 逐步回归* ?" u* c* @" Q1 g
Storage, 存
7 H: {! P# n/ p T7 jStrata, 层（复数）* N6 y" p/ h Y* ~& \
Stratified sampling, 分层抽样; e3 m* n% u O3 \# j
Stratified sampling, 分层抽样3 O7 a& w; b* z
Strength, 强度
( K1 I3 Y. e2 k: qStringency, 严密性8 Z0 e& J/ b( B' P" C2 Z
Structural relationship, 结构关系9 N% [$ w* t. K4 [: ?6 a1 `0 l8 f
Studentized residual, 学生化残差/t化残差
0 S! T/ b5 j2 P. _. ?' ~/ k7 FSub-class numbers, 次级组含量
3 ]6 l& t. ?6 J1 M4 T3 Z: vSubdividing, 分割
. c1 y, y/ ^ S5 k9 A1 lSufficient statistic, 充分统计量
& d( F* I8 e4 j% _ ~+ `% gSum of products, 积和
( V* g# T0 y Y0 n) F8 uSum of squares, 离差平方和
+ Y u+ m9 a8 eSum of squares about regression, 回归平方和
( n! R1 m% f2 u0 _8 zSum of squares between groups, 组间平方和
- Z% P4 j0 Q: t* V3 B @, j- O9 mSum of squares of partial regression, 偏回归平方和9 f, j6 t: ~& R' v# Q0 {
Sure event, 必然事件
% F7 ~0 M* y8 M+ s, }Survey, 调查
S: ?0 q# s/ r& }3 eSurvival, 生存分析% i g; R# H6 i" Y
Survival rate, 生存率) g: M% [/ v7 A
Suspended root gram, 悬吊根图
, S; c. y, }/ v3 M" PSymmetry, 对称4 n5 v& v, s) k$ m" r
Systematic error, 系统误差
2 H6 F# S* z! [9 M3 Q5 e9 O/ zSystematic sampling, 系统抽样" {9 Q, l m5 i
Tags, 标签2 r G+ X* s( q& ^. B. E
Tail area, 尾部面积: u8 B3 M+ z) M! X4 k" p
Tail length, 尾长7 q4 u* q9 S2 N+ ^5 X |5 I T: p
Tail weight, 尾重
: x! U* a* ?+ G3 y5 N/ a, g, J7 }# DTangent line, 切线$ H4 S t+ I2 q
Target distribution, 目标分布
$ I5 n5 F: x; \/ h/ P% V) J: o8 Q/ hTaylor series, 泰勒级数2 G8 V0 ~7 T }3 q& G
Tendency of dispersion, 离散趋势
) ~2 B3 R( z2 Z) D4 lTesting of hypotheses, 假设检验
) q0 b8 C# v8 ~- v9 A. _3 C2 qTheoretical frequency, 理论频数
; C/ A( `" z) S3 A _Time series, 时间序列$ H5 j, c* r c+ U* |1 n( k
Tolerance interval, 容忍区间
3 C* l5 g9 P: \5 mTolerance lower limit, 容忍下限
, P ^8 ^% L; A1 W G& ATolerance upper limit, 容忍上限0 x+ ^8 C3 y V. E( ^1 B4 k5 f! o/ u, t: f
Torsion, 扰率
6 M- N' d& r0 u. K2 sTotal sum of square, 总平方和
d; x: f" z; Q8 z+ P) nTotal variation, 总变异
3 H& ^7 B# w! H! J& fTransformation, 转换
1 a4 r' a$ f4 `Treatment, 处理
3 N9 _4 N3 q: O# d. WTrend, 趋势
! M; o! S2 D+ h, VTrend of percentage, 百分比趋势1 {' d4 A3 h: ?/ e0 z" w( {
Trial, 试验! j2 y3 s8 t4 u2 T
Trial and error method, 试错法1 B3 k9 J2 y* y
Tuning constant, 细调常数
. e# p' F/ {5 t+ [+ Z7 `7 o1 ?Two sided test, 双向检验0 j% c( C2 T2 L% o& f+ J2 N
Two-stage least squares, 二阶最小平方4 @+ f" H) u" }! U: N
Two-stage sampling, 二阶段抽样
. Q. ^! s. w% p+ d7 B6 L! }Two-tailed test, 双侧检验) D% `- f8 ^* u# I1 P
Two-way analysis of variance, 双因素方差分析/ F+ K/ |" f7 |& L2 A, U; M: D u
Two-way table, 双向表' p- l+ s% e! ~$ v4 `
Type I error, 一类错误/α错误- \4 L3 c- E9 f8 ^, {
Type II error, 二类错误/β错误
7 }9 L; D1 Z& S" M3 m9 P+ tUMVU, 方差一致最小无偏估计简称, H+ X$ o' `" ~
Unbiased estimate, 无偏估计
5 E$ a/ \9 L7 W; a( GUnconstrained nonlinear regression , 无约束非线性回归
8 n, y, T& Z- ?" bUnequal subclass number, 不等次级组含量
& r& m4 n' C% @Ungrouped data, 不分组资料
% e" ~, y; {2 M7 tUniform coordinate, 均匀坐标; B; u! @! A4 o7 f
Uniform distribution, 均匀分布6 v7 B4 B3 i' U4 D; m, q
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计, R! |# h! V! W3 g+ x3 k
Unit, 单元3 w& e$ @( e$ x1 K q
Unordered categories, 无序分类1 e7 f1 Y% C7 U4 i# z1 S
Upper limit, 上限
3 y0 p7 Z( t( D D$ MUpward rank, 升秩
1 e" F/ L1 a+ E* C G0 q# J7 E6 {Vague concept, 模糊概念/ o& m" _4 J" F7 x
Validity, 有效性
" v/ l$ ^. g1 E7 qVARCOMP (Variance component estimation), 方差元素估计+ {* Z& V+ U5 v+ b$ O
Variability, 变异性
h& B Q; s+ m7 v0 d$ WVariable, 变量
5 W) X; s7 u3 d8 CVariance, 方差
8 S# ]+ m3 X4 d5 O, u9 GVariation, 变异
X& u9 l1 y" e7 k& q) b7 }Varimax orthogonal rotation, 方差最大正交旋转6 `6 V2 R G7 h) @3 p9 p$ L
Volume of distribution, 容积
8 K8 g" |, \2 r0 j0 yW test, W检验+ x9 _4 I2 i5 M: e; K4 S8 ?" w
Weibull distribution, 威布尔分布 g7 S5 D1 F' ]+ Z" V2 f# c" V
Weight, 权数
% `0 q- `$ Q1 t7 I2 r, ~( _Weighted Chi-square test, 加权卡方检验/Cochran检验% D, ]- ~" A7 e
Weighted linear regression method, 加权直线回归& N' N, F! t& V
Weighted mean, 加权平均数
* O8 x9 n( n2 _% ^Weighted mean square, 加权平均方差% P" u, [5 a0 m! q& T
Weighted sum of square, 加权平方和
7 E% |# ] U) i3 IWeighting coefficient, 权重系数
/ B/ p4 P$ a( H! o9 PWeighting method, 加权法 & _7 M( a; l% `( o$ {/ L& ~
W-estimation, W估计量1 `# p+ _* w. Z
W-estimation of location, 位置W估计量2 G. _' ?, A& [6 m4 i1 s* _
Width, 宽度
8 g* `8 M! M- R. p' F7 IWilcoxon paired test, 威斯康星配对法/配对符号秩和检验/ N [) S5 a9 e* F B. z6 h
Wild point, 野点/狂点
% J+ @5 ~: I+ w0 IWild value, 野值/狂值3 o2 b: {6 j: R0 a8 O2 H G
Winsorized mean, 缩尾均值
! j! V: w6 S& T6 QWithdraw, 失访
- z# \/ U: {# ^9 k$ g% s; KYouden's index, 尤登指数
$ M% o- {1 w6 b, vZ test, Z检验" c( P }9 n2 P/ ~* n5 y4 }2 f
Zero correlation, 零相关2 T* t: b9 q D; r# V- s! u
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
