|
|
Absolute deviation, 绝对离差
4 u* z8 `1 X6 v6 j% I3 Z4 M9 ^" MAbsolute number, 绝对数- W: ^0 U3 m6 v+ C! m2 O: v' K
Absolute residuals, 绝对残差
2 ?4 K$ s$ [; UAcceleration array, 加速度立体阵
% x' T4 y3 D: V1 E/ `0 \Acceleration in an arbitrary direction, 任意方向上的加速度1 ` R7 q/ {( Q1 m" p J
Acceleration normal, 法向加速度
, R" c/ a$ D+ B) O+ j& _Acceleration space dimension, 加速度空间的维数
0 I) k1 R8 k# E# K" CAcceleration tangential, 切向加速度' k3 k k6 _, D: B1 Z8 B* z1 p
Acceleration vector, 加速度向量8 j. V* v' |, Z
Acceptable hypothesis, 可接受假设6 J8 D8 v/ Z" k9 g' y/ l; ~1 {
Accumulation, 累积8 r, M: ?* d# S, K) [
Accuracy, 准确度
2 M7 n. Y! k0 eActual frequency, 实际频数, t! r0 V6 Y: M
Adaptive estimator, 自适应估计量7 f: n0 @6 u: S2 T: b& M6 `6 X+ `2 i
Addition, 相加# H8 l& z8 X y; X
Addition theorem, 加法定理
" P) s- k, A; i/ N2 f4 g3 J0 i: zAdditivity, 可加性0 _$ u- \) ]- i* ]# G
Adjusted rate, 调整率
7 p6 _1 l% e, b- MAdjusted value, 校正值
2 W3 [! R) D3 Y9 d7 i5 w" ^Admissible error, 容许误差, k: e, J+ W' d6 Q
Aggregation, 聚集性
* b) `+ z0 N( e) b* xAlternative hypothesis, 备择假设' F9 w/ T( y# Q0 E
Among groups, 组间
+ Y: c, L$ W7 e7 x1 OAmounts, 总量8 g! Z9 ]5 O- _5 k
Analysis of correlation, 相关分析
7 |2 |- H) C+ k2 d% u2 b4 ]4 mAnalysis of covariance, 协方差分析
# J2 y3 i& u- A, w( j8 i3 g* J- NAnalysis of regression, 回归分析% I( }) Z. }$ s
Analysis of time series, 时间序列分析3 M% K5 ?1 U; B+ z/ u
Analysis of variance, 方差分析
: U" R+ x8 u! GAngular transformation, 角转换, T2 _% h/ G7 |" k; F! L* W
ANOVA （analysis of variance）, 方差分析4 E I( P2 x p9 t1 ?; R; X2 G
ANOVA Models, 方差分析模型
; \. M( X v5 R: ^Arcing, 弧/弧旋
3 ^! s8 B1 `+ B& D% @# |0 {7 YArcsine transformation, 反正弦变换
+ ~# l0 K7 q0 aArea under the curve, 曲线面积
2 _" a* T1 i/ A# X+ R ?- ?# _2 }AREG , 评估从一个时间点到下一个时间点回归相关时的误差
$ [& ]& U2 y& U& X! b# K! s% VARIMA, 季节和非季节性单变量模型的极大似然估计 1 y" s1 H% |; q% h9 s
Arithmetic grid paper, 算术格纸. V5 z7 O- z+ A
Arithmetic mean, 算术平均数3 V" t" R# W6 W: x
Arrhenius relation, 艾恩尼斯关系! Z% z1 l u4 `8 A! |; s' m
Assessing fit, 拟合的评估7 B/ Q/ G9 j' \6 [* B% Y( u
Associative laws, 结合律4 t/ f- i' c1 E
Asymmetric distribution, 非对称分布) J) c0 O: f( u- {! E Y2 {
Asymptotic bias, 渐近偏倚
5 B% ]7 {4 }1 |1 ?! z# R' jAsymptotic efficiency, 渐近效率
- K. Q8 D5 Y/ ^0 c- A" t8 HAsymptotic variance, 渐近方差
7 ~& [* u& {) OAttributable risk, 归因危险度
% T, W, Z7 _+ Z- @2 L2 ^. G$ z; uAttribute data, 属性资料
9 k( F; Z8 U$ g" F9 K! n: q: TAttribution, 属性1 \7 [# k- i. R Z( T
Autocorrelation, 自相关3 k& R1 i; x$ ^& Y" c1 ^: G
Autocorrelation of residuals, 残差的自相关5 c, a. x R& p+ x- P
Average, 平均数- r/ s* @# a9 X6 Y, t
Average confidence interval length, 平均置信区间长度 z8 a) ?' e; ~ ^) U
Average growth rate, 平均增长率
# B' v/ Y9 k9 W! y8 Y9 f7 E1 T& kBar chart, 条形图# P7 c9 R9 R0 z
Bar graph, 条形图1 l( ^& x B: ^/ u* _6 j6 w5 R
Base period, 基期4 W7 ^- g7 W0 y7 M
Bayes' theorem , Bayes定理2 t, h0 d& e3 e' A! k* g; O: b* u
Bell-shaped curve, 钟形曲线1 I/ i* L: o+ r; ?
Bernoulli distribution, 伯努力分布 c* D& n9 ]1 y5 [8 ]
Best-trim estimator, 最好切尾估计量
% b; ^7 ], }# x* ]5 Q$ j$ mBias, 偏性9 r$ Q6 \. r9 |% s6 x
Binary logistic regression, 二元逻辑斯蒂回归& B+ @) ?8 G5 [8 Q9 D0 w
Binomial distribution, 二项分布
5 T4 i% S7 U2 N' j- d% E$ K0 D# S% j3 pBisquare, 双平方
' |3 z6 @3 o. i: b9 C0 e1 g( MBivariate Correlate, 二变量相关
5 X- V# O* c, r! j E/ a/ MBivariate normal distribution, 双变量正态分布
( G) t4 l$ P7 p6 QBivariate normal population, 双变量正态总体
8 x1 l" `7 x$ a4 E! f9 [& q6 O0 FBiweight interval, 双权区间& K: K; L, T5 P6 j7 s8 A8 u
Biweight M-estimator, 双权M估计量
4 E) V6 K* \, sBlock, 区组/配伍组
" y9 L: l! N1 b! Y# s3 TBMDP(Biomedical computer programs), BMDP统计软件包
! N8 v7 ~* G! o% l4 @; \Boxplots, 箱线图/箱尾图
2 n& _6 b8 y; Q# g, kBreakdown bound, 崩溃界/崩溃点7 [- \$ F+ n6 A0 I
Canonical correlation, 典型相关
1 U9 ~4 B J' M# _9 ^+ r1 GCaption, 纵标目
D7 `$ O6 [3 h; y+ B4 g# ^% lCase-control study, 病例对照研究+ t- E6 b$ U. W
Categorical variable, 分类变量
" m& k- P, G" Z& k( iCatenary, 悬链线
. H! \' u! j: ~! b G- K8 i+ c% HCauchy distribution, 柯西分布
+ S" z+ I4 t f5 r2 u0 `# K! S% bCause-and-effect relationship, 因果关系. q6 T O& E. d
Cell, 单元
6 I. M* g. e' ?0 GCensoring, 终检- A3 q3 ~5 K+ U9 b- f
Center of symmetry, 对称中心" V6 l9 Q; L: o
Centering and scaling, 中心化和定标4 Y4 N9 J+ B% Z; D9 _
Central tendency, 集中趋势
2 S$ `. b5 Y) B, O- M0 u2 c6 r) d3 R, GCentral value, 中心值
7 E8 |+ |1 T" w$ c% S" X1 QCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
1 J& _! G* `( R5 j; `3 XChance, 机遇
" O; d) C" o, n$ ] |! }; ^Chance error, 随机误差
1 z" _5 E2 o) M4 H: pChance variable, 随机变量4 ~. L/ Z# L+ `
Characteristic equation, 特征方程
! B- W* c, j8 L9 F( b" M! k6 tCharacteristic root, 特征根/ V$ d9 D" h! s- { \7 T }
Characteristic vector, 特征向量. U; |! A9 [5 g# X" C
Chebshev criterion of fit, 拟合的切比雪夫准则
( Z, U5 o3 x: p/ O7 D% t9 Q6 W. [Chernoff faces, 切尔诺夫脸谱图 [3 W6 z4 g; F: J9 H
Chi-square test, 卡方检验/χ2检验
" d ~+ ~8 n. G4 W. z0 \% ]* |7 gCholeskey decomposition, 乔洛斯基分解6 ?4 b, U% A7 R0 x, w& n4 ?* q( X. A" Z
Circle chart, 圆图 0 o) ?* B& Z% J3 |, L. ?4 @$ c
Class interval, 组距
" V/ ^9 ?: B1 t- l4 C% WClass mid-value, 组中值
# p7 `- u! s; |, X$ c; l8 @+ HClass upper limit, 组上限
( k1 H9 [$ C1 nClassified variable, 分类变量7 Y% M; p5 b* a% e7 t2 r
Cluster analysis, 聚类分析
( }, a/ Y' z$ T$ pCluster sampling, 整群抽样
- J* ]1 i; |) \8 {" b0 CCode, 代码 X; g5 o" m) n$ E) o1 W
Coded data, 编码数据
# z" z2 P# Z. {# Q- jCoding, 编码0 {6 O2 N& G* c( `* O8 C! T
Coefficient of contingency, 列联系数
. D! m' O1 J- d% T6 x" wCoefficient of determination, 决定系数
% D) c! l ^8 p2 \. p3 B; gCoefficient of multiple correlation, 多重相关系数7 i# p8 J# U; w
Coefficient of partial correlation, 偏相关系数6 F* l! F( w+ U
Coefficient of production-moment correlation, 积差相关系数
* T& J$ t% D2 n& ^Coefficient of rank correlation, 等级相关系数
+ E% F3 U( P6 A& NCoefficient of regression, 回归系数
) N& r( t. l9 zCoefficient of skewness, 偏度系数& _ k; o, ]3 g
Coefficient of variation, 变异系数
7 F' W% |+ u! i# }: E, o9 T; WCohort study, 队列研究/ P/ D; Q$ A* p( `
Column, 列
& p* y7 f( \4 ? [9 d' n( a. |$ LColumn effect, 列效应; N2 }$ j! ]6 p3 g% X) [& [
Column factor, 列因素: R, h' P$ n3 p4 o
Combination pool, 合并
- ]1 G$ v5 o, {Combinative table, 组合表
% [' y: f k$ v5 L* ~Common factor, 共性因子3 l$ A- R" m3 @6 l- k$ f* m
Common regression coefficient, 公共回归系数, j' e; V4 u3 q% ^6 H) ]4 W
Common value, 共同值
! k3 \4 b" f% x- y9 L4 G0 kCommon variance, 公共方差" k& F( S8 ^9 i+ r& x" V( F6 M6 C
Common variation, 公共变异+ L9 K6 H. t6 O R% i1 T, r
Communality variance, 共性方差
6 u2 @0 ~2 ^, q8 E2 tComparability, 可比性
. f- ^+ {8 g: F+ |1 sComparison of bathes, 批比较4 i1 n. n( k6 K" D( |0 Q
Comparison value, 比较值( o m2 o* U8 P8 X
Compartment model, 分部模型
2 ?/ A6 U# `2 o. @ k |$ wCompassion, 伸缩
0 ^! L) j7 v; ?Complement of an event, 补事件
! `. j& y4 T# pComplete association, 完全正相关
" v w2 l1 ? s3 QComplete dissociation, 完全不相关: H) Q/ n+ h8 @( O( I0 P
Complete statistics, 完备统计量5 [3 a+ z0 L& U1 d) h
Completely randomized design, 完全随机化设计 d3 j5 b' q8 Y1 a' Y: P$ Q/ p
Composite event, 联合事件/ w/ F) P- `9 W" N2 y- N$ I
Composite events, 复合事件
: f O* G* H0 O1 b$ TConcavity, 凹性# D* @; @+ A. ~
Conditional expectation, 条件期望9 C3 A4 O& [/ q
Conditional likelihood, 条件似然5 n. M/ A0 B! \1 Z1 j7 M
Conditional probability, 条件概率
! d* x* B4 {. O4 D1 J* v2 ^; {, [Conditionally linear, 依条件线性
3 l9 i' }/ x6 E- A( fConfidence interval, 置信区间
' S Z* u' x$ t; W0 B) yConfidence limit, 置信限
) x; A: m' U. M" g. x4 \, xConfidence lower limit, 置信下限
5 K1 \, Q' B0 R+ d) dConfidence upper limit, 置信上限% R* N* k% y g5 U
Confirmatory Factor Analysis , 验证性因子分析
7 l5 m; Q x$ i8 KConfirmatory research, 证实性实验研究
' y( e% e! M. c" yConfounding factor, 混杂因素
6 W- [8 n" ^ K8 lConjoint, 联合分析
6 u3 P8 s2 y* L( p2 MConsistency, 相合性) K9 ~2 {) G7 z. }) Q8 u' P& x
Consistency check, 一致性检验: a# w& f: O# o; x# \' N$ Q9 p3 {
Consistent asymptotically normal estimate, 相合渐近正态估计4 ]: ?: {9 ~4 ^9 A4 x
Consistent estimate, 相合估计' X/ _ Y" c, A5 t
Constrained nonlinear regression, 受约束非线性回归8 C; ~ S+ F0 T6 l+ C
Constraint, 约束
& F" W# Z+ {% A' ?+ s1 MContaminated distribution, 污染分布
0 ^ ?; T2 Y0 V) K! J8 uContaminated Gausssian, 污染高斯分布- l2 I. |! n2 U3 C1 R" w. F! N
Contaminated normal distribution, 污染正态分布
4 F1 f" N% K: lContamination, 污染
" E2 w* `& Z5 ]. Q, `Contamination model, 污染模型8 t. E6 ~4 u1 i8 T
Contingency table, 列联表8 m7 j7 p8 r' M) v6 _ X$ J
Contour, 边界线
6 `; c- g% B5 N1 B. ~; HContribution rate, 贡献率3 F6 s2 _ z* F5 o7 l+ a3 Z
Control, 对照
& D$ @: N+ z' pControlled experiments, 对照实验
; N' e7 G0 f5 ]" u6 qConventional depth, 常规深度7 r/ u4 J6 M, W* k. b" ?
Convolution, 卷积
6 f/ S6 Z4 _* z( V& aCorrected factor, 校正因子
4 p0 y3 z) d0 K0 z2 r1 aCorrected mean, 校正均值; v) Z1 K; q+ ~$ ?3 V4 q# U
Correction coefficient, 校正系数) a" ?/ u# Y. `! z3 x
Correctness, 正确性$ ?4 p2 ?- B+ I3 h, p4 c
Correlation coefficient, 相关系数
2 c8 m0 A6 h$ C# u9 zCorrelation index, 相关指数- S) `7 Y. `$ P" i O
Correspondence, 对应
; n7 ]5 P( f" _, B+ S$ f% eCounting, 计数
" x- K- a8 n8 e) |# Y; K' FCounts, 计数/频数) m5 b' L$ M7 O9 {7 c
Covariance, 协方差
( J5 T3 a; ^/ |0 c4 u* p0 JCovariant, 共变 & Q& q1 m- F- _4 R8 r
Cox Regression, Cox回归
! p; P& _, L' @) V3 n4 H& U1 TCriteria for fitting, 拟合准则" \- [4 L; s7 p2 F
Criteria of least squares, 最小二乘准则& K: N1 f8 C4 `, c
Critical ratio, 临界比
5 t+ R! R' _* `5 UCritical region, 拒绝域
7 x5 k/ Q s& w7 y/ l& v. Q6 |Critical value, 临界值" l0 ^, j" A8 T
Cross-over design, 交叉设计
4 \" @+ Z5 S# S8 W5 U) g9 DCross-section analysis, 横断面分析
( `' y7 p- n+ z( X0 lCross-section survey, 横断面调查, b0 @6 h( w. n5 ]' L) F
Crosstabs , 交叉表 $ m8 N% O C( \, f' E: a# m
Cross-tabulation table, 复合表
8 R$ ~& }+ y+ `- L1 FCube root, 立方根
( K s; _# u4 E/ _$ WCumulative distribution function, 分布函数9 w; G! [5 Y& X/ \ G
Cumulative probability, 累计概率3 M# a6 {9 t ?* b2 o7 W6 t
Curvature, 曲率/弯曲2 d" \( k; s8 Y! J+ Q- P: w* ~
Curvature, 曲率! p0 z8 S9 R/ C8 Z1 s0 b: y
Curve fit , 曲线拟和 1 h5 f0 {* O# u, `
Curve fitting, 曲线拟合) \2 h2 C! ]/ j' h: R/ R8 V: }
Curvilinear regression, 曲线回归
6 O z5 n1 c3 b H$ |/ o. cCurvilinear relation, 曲线关系; F+ \) l0 E; A6 m# W; ~
Cut-and-try method, 尝试法
% H9 p- ?! w8 L1 K' t$ G% R* o& N: XCycle, 周期# v5 N8 G# Q# f7 S. l
Cyclist, 周期性4 Q6 t5 ?; n3 y' h
D test, D检验
$ ?+ R( `- A* ?) _! GData acquisition, 资料收集
1 S; m4 F K. K' H7 {/ S# l& C' y \1 ?Data bank, 数据库3 S% S1 I9 i! |
Data capacity, 数据容量
. m! W: T l' G! I* |+ SData deficiencies, 数据缺乏: D* E7 P9 M* L, i4 q
Data handling, 数据处理- ], z5 T6 E6 F5 D
Data manipulation, 数据处理
7 J7 ^. f8 N, v2 a! D! K( zData processing, 数据处理
( ~- ]$ c8 q8 {* E2 a5 D, B7 iData reduction, 数据缩减0 ~ K% z) \8 j3 d1 K0 R
Data set, 数据集1 n+ v% R& A) ^- }% [ S7 ?
Data sources, 数据来源3 l" F( A3 K' d/ h, U4 [9 _
Data transformation, 数据变换
& ~! W. K8 c1 ^! b9 uData validity, 数据有效性
# Z8 w; ^1 D Z7 K n8 DData-in, 数据输入- `& m8 U B7 F
Data-out, 数据输出
8 B# x1 C) E5 }0 [! ~7 GDead time, 停滞期
2 X( D, C+ O* }0 ADegree of freedom, 自由度* m( R4 M$ h6 v7 m% P
Degree of precision, 精密度" H! P/ p$ I; L. y
Degree of reliability, 可靠性程度
8 e: r1 ^, i; m5 t" d/ X: L# dDegression, 递减" H4 {# J# | a* L( M
Density function, 密度函数- I7 ]0 ]6 w V$ C7 w
Density of data points, 数据点的密度
) ` L+ f) m% L# p1 sDependent variable, 应变量/依变量/因变量
% S! Y4 e+ y2 q; bDependent variable, 因变量% R# P% j9 D% N2 R1 V
Depth, 深度3 P; y$ R- [" h& ~. w+ g
Derivative matrix, 导数矩阵' \. {1 K: M% y1 I' o( P( h' p
Derivative-free methods, 无导数方法
3 ~5 d7 \2 i2 hDesign, 设计5 q& q1 V; S- m3 r" R9 X, A
Determinacy, 确定性4 t/ g6 s7 \7 y
Determinant, 行列式# ?6 C9 u# D& a
Determinant, 决定因素" O0 R! s) m# `/ c
Deviation, 离差
4 |. N' x" F V t. C$ _Deviation from average, 离均差
# M, Z$ n* h5 [$ s: U. j" _& L! zDiagnostic plot, 诊断图
5 x1 j3 s/ Z' }9 nDichotomous variable, 二分变量
; M5 C; t9 J3 lDifferential equation, 微分方程
" s) L) H7 d: h( Q- ADirect standardization, 直接标准化法, u1 q6 W/ ?4 }4 d* n( C5 A. G" Z
Discrete variable, 离散型变量
* v3 Z) e3 J1 G# a5 r( F" V$ KDISCRIMINANT, 判断
1 A2 S+ v+ s5 w" [# o0 ODiscriminant analysis, 判别分析
6 c' t/ [0 X/ H* Z! U8 b# pDiscriminant coefficient, 判别系数
3 R7 d0 H1 B- k$ Q, E+ A2 nDiscriminant function, 判别值; d2 U+ q8 x: P+ R
Dispersion, 散布/分散度
6 H/ m P; u" z2 QDisproportional, 不成比例的$ Z$ G8 F$ f6 n( h
Disproportionate sub-class numbers, 不成比例次级组含量$ {: s/ L, u8 p+ X& v6 G
Distribution free, 分布无关性/免分布
1 t. q- y" P( k( o3 jDistribution shape, 分布形状7 q. n+ k: ]& s$ o4 C
Distribution-free method, 任意分布法5 Z* ^3 k6 ?' L( l! l
Distributive laws, 分配律: o+ m/ H, E; E! D) d5 Q( K# y" c
Disturbance, 随机扰动项 J% ]# t+ ]% d2 R
Dose response curve, 剂量反应曲线1 u: N2 Q. q0 n6 P6 \: F0 J4 V
Double blind method, 双盲法
8 u$ {, r8 ?* |( L: L5 ^Double blind trial, 双盲试验# h2 X& j: @ f5 M9 D0 m+ x! E
Double exponential distribution, 双指数分布
, k: m8 ^* d3 O$ \Double logarithmic, 双对数
5 v7 Y) @6 T1 f& ODownward rank, 降秩7 z2 f0 W n1 p/ T7 i! u
Dual-space plot, 对偶空间图
8 h/ @' b+ j; c: ?, bDUD, 无导数方法6 n1 ] W4 L4 M
Duncan's new multiple range method, 新复极差法/Duncan新法# c! r# p; V2 z4 ]" @; s
Effect, 实验效应
% w; z0 h5 p* S1 V% z9 kEigenvalue, 特征值
, K: N" T' d/ W* S( }+ CEigenvector, 特征向量
! b. x+ \ c- xEllipse, 椭圆
3 Z% q* f( [/ g8 `Empirical distribution, 经验分布
7 D" Z3 G% `# M* r& {Empirical probability, 经验概率单位3 t3 `3 X; U4 W$ c9 B$ R
Enumeration data, 计数资料
- s; ~9 A8 ]; D G2 I/ l3 B4 K8 F/ \Equal sun-class number, 相等次级组含量. `: q1 F |/ z" A$ U
Equally likely, 等可能
6 v) \5 U$ V) s' V% iEquivariance, 同变性
& `* q( D: s" L4 w4 i WError, 误差/错误/ S z U* f- |, h/ h
Error of estimate, 估计误差
4 j8 R& p+ {" R/ c2 W) B% DError type I, 第一类错误% c) ^, u5 f5 |: B
Error type II, 第二类错误
& e0 b- [ c$ @- k/ v& c8 XEstimand, 被估量
$ o, I6 R {) X- |1 p% T1 S$ `+ |/ qEstimated error mean squares, 估计误差均方
2 I; u) h+ ^1 y. r& }; DEstimated error sum of squares, 估计误差平方和3 a5 g* {4 t2 u
Euclidean distance, 欧式距离
* U k* K! Z, c* uEvent, 事件$ I7 f9 P. a6 d1 r# [
Event, 事件0 H/ @" q; n1 E; o8 x" g5 R9 C
Exceptional data point, 异常数据点7 W: H8 l' N+ }: {5 u5 E; q
Expectation plane, 期望平面
' m& h" [4 p4 R* @7 p5 l; k. cExpectation surface, 期望曲面- S& H# y) t7 z( s8 {
Expected values, 期望值+ |; R j/ g) C9 h( B# I! N
Experiment, 实验7 {/ b3 v- Q# ?5 D7 F
Experimental sampling, 试验抽样
3 e2 J3 c D. o! {Experimental unit, 试验单位 z0 [! T* M5 L- P3 s
Explanatory variable, 说明变量* ?4 r1 J% K% q' d
Exploratory data analysis, 探索性数据分析
' d* S. z& V0 [" m$ P$ j6 ^Explore Summarize, 探索-摘要* N9 Y# z/ \: L R
Exponential curve, 指数曲线! k( n5 C9 ?8 @: t- K
Exponential growth, 指数式增长
0 V Z& D0 D) G3 {9 QEXSMOOTH, 指数平滑方法
" P* \$ U5 q( y. D' \$ mExtended fit, 扩充拟合, n# ~; d ^1 d9 c) s4 Y. P8 b3 O
Extra parameter, 附加参数
$ f8 V9 h8 `* D5 g; qExtrapolation, 外推法
# U4 s% w8 E0 C; p" ^* \9 zExtreme observation, 末端观测值
/ g. [/ {1 q3 {6 D6 F; g) ^+ {Extremes, 极端值/极值
7 ]4 x$ N* a7 N% \7 Y9 u1 CF distribution, F分布7 S/ P$ j6 i, r1 ? ~0 d& T P7 \# g
F test, F检验
2 l2 q+ m$ S/ E- m1 N6 m# J) BFactor, 因素/因子$ q7 h* K4 A# }
Factor analysis, 因子分析2 R' l1 ]! y1 B" @2 N
Factor Analysis, 因子分析
# l" u1 r' X" u. a" j. PFactor score, 因子得分 6 L. P5 y+ N* V* W7 f
Factorial, 阶乘
$ c. w+ j' l0 a) E( K* JFactorial design, 析因试验设计
1 Y0 S9 ?. N( ]2 ~9 r- IFalse negative, 假阴性; F. \+ H" `* A& `/ F' F; o
False negative error, 假阴性错误2 S' G% y" H, A4 p& K7 J
Family of distributions, 分布族
+ I4 x: R! |& p6 @/ J+ q! jFamily of estimators, 估计量族0 `" ^! q! V3 F' Q: t& [
Fanning, 扇面: G5 L$ x: R! `
Fatality rate, 病死率
4 ?1 k [! {: r# w) VField investigation, 现场调查) \# Y# X( D7 q9 j, ^
Field survey, 现场调查4 ^0 c& h0 u' l6 X+ q$ v1 L
Finite population, 有限总体0 `, }( h" }" ~0 z- v
Finite-sample, 有限样本1 ] s6 q( v0 \1 n4 F. ~ z( Q& g$ L
First derivative, 一阶导数
. d. S/ ?" u( C* [8 lFirst principal component, 第一主成分7 S. v" m1 w/ i) a2 G) I
First quartile, 第一四分位数
; N$ `9 G! P+ }5 X0 j0 L# O9 I( LFisher information, 费雪信息量/ T6 K! D7 L: K
Fitted value, 拟合值
! ~4 Z1 {$ [7 E) `Fitting a curve, 曲线拟合% S: R6 m1 [! P" _+ D. K
Fixed base, 定基1 J- Z6 D( w0 x+ m+ a5 _
Fluctuation, 随机起伏
3 R: |, t% c( jForecast, 预测
! a4 l' n& H0 n5 o& Z& n9 A" zFour fold table, 四格表+ b. [+ N. Y0 N# i& p# Z& M" x
Fourth, 四分点
# ~7 s; C. Q6 B1 }( C U$ BFraction blow, 左侧比率
# a3 O1 D7 P/ e/ A2 FFractional error, 相对误差
! S$ Q9 [9 W: v/ B1 a; h9 JFrequency, 频率
7 A) O8 m7 j, K# Y$ b" VFrequency polygon, 频数多边图# X) A5 b3 C9 h' Y
Frontier point, 界限点
% ?( |6 i z' V* a5 G b UFunction relationship, 泛函关系
+ v3 p" \) {1 W. i/ ]- Y" o- U3 s8 cGamma distribution, 伽玛分布% h" n2 o. L8 z- z7 Z1 a8 w, c
Gauss increment, 高斯增量
" p9 l* f$ D: @3 w3 D. K8 ]; R0 h! TGaussian distribution, 高斯分布/正态分布
2 Q9 E5 G# P* p- Y. i+ GGauss-Newton increment, 高斯-牛顿增量
2 {+ P9 f4 G9 o+ H. l! @General census, 全面普查, E9 ?& k% q) q& L m
GENLOG (Generalized liner models), 广义线性模型 ) Z- b' s; E+ b6 H0 D0 G% p
Geometric mean, 几何平均数
! ] S" x4 r. \& KGini's mean difference, 基尼均差
! }: F3 x/ S6 a( p" g; |9 RGLM (General liner models), 一般线性模型
- K7 I+ ?9 H6 S. a* r6 s; AGoodness of fit, 拟和优度/配合度
# I4 G" g! A$ `( i) `Gradient of determinant, 行列式的梯度% k* l5 e# h) ?% W P
Graeco-Latin square, 希腊拉丁方: V. J+ q; [ R* F% @! R
Grand mean, 总均值4 t) D$ Y3 i( _7 n- B" N$ o
Gross errors, 重大错误( E; o( S K. O2 `5 G
Gross-error sensitivity, 大错敏感度& o: q5 o7 y% w+ K5 o. L$ S
Group averages, 分组平均: `2 T8 r) q' n( @% V
Grouped data, 分组资料
K! \! P0 C. Y3 c& HGuessed mean, 假定平均数& w; `' \( o! o, p
Half-life, 半衰期
7 L* ]" _5 Z8 C$ {Hampel M-estimators, 汉佩尔M估计量
4 Z3 h( t' i ?7 P QHappenstance, 偶然事件" [2 r7 U: P& t4 p) {
Harmonic mean, 调和均数
( q3 ]3 R6 l- W6 h/ cHazard function, 风险均数. j5 f) _& G4 w9 M0 i9 \
Hazard rate, 风险率
, a3 j2 o+ T' h5 Q, e2 k/ cHeading, 标目 " M% m/ ~% b B% a( u3 Q3 t
Heavy-tailed distribution, 重尾分布
- n$ } @, a' ZHessian array, 海森立体阵9 Q; U. R. n/ C8 j3 _; L0 B
Heterogeneity, 不同质
/ s% _: ^! e3 Y+ x' H+ X, sHeterogeneity of variance, 方差不齐 % z2 T0 Q$ H9 r& `( l S, [! @# H
Hierarchical classification, 组内分组) A! F# r. S- i0 x8 c4 f& W
Hierarchical clustering method, 系统聚类法! _. B! y8 Z% n- |
High-leverage point, 高杠杆率点
- n) E8 w; Q$ M$ J! LHILOGLINEAR, 多维列联表的层次对数线性模型1 L6 I4 p, A. G! m: B3 C4 T
Hinge, 折叶点
. ^" N) H- E. f2 b1 nHistogram, 直方图
& _5 j" S- i' t+ Q: ^7 u! sHistorical cohort study, 历史性队列研究
& |% D0 Z" S* @4 O1 W* lHoles, 空洞
9 t8 p& a8 Y* ^0 X- B2 ~' g# [( MHOMALS, 多重响应分析
: k i+ L3 k2 B( i9 `Homogeneity of variance, 方差齐性
8 t% `+ q5 K5 D- h1 h3 bHomogeneity test, 齐性检验
: O1 s4 T! k/ H- K) A3 IHuber M-estimators, 休伯M估计量 Y0 s$ k4 \' B2 U# t7 {
Hyperbola, 双曲线& r/ D/ X, n' ^6 S ?# w# i( T$ f( I
Hypothesis testing, 假设检验9 X4 T" _9 M5 B& x. T1 I" ~6 ~
Hypothetical universe, 假设总体7 y" `, U" k" C+ n" O! O
Impossible event, 不可能事件
" H0 l: d- Z% x+ E5 k* f, O! GIndependence, 独立性
% H( U7 L5 B/ O% V2 v4 B o$ qIndependent variable, 自变量+ k- y' H8 d a! ]
Index, 指标/指数) V2 U! t% Y2 e, E& I
Indirect standardization, 间接标准化法
: @3 z7 b0 } H" {3 [Individual, 个体
. F/ o& C9 ]1 T0 f0 v. \Inference band, 推断带
7 ^- K7 A: n2 _5 @- t0 D% TInfinite population, 无限总体
9 X+ r* {1 ^# A. Z- L& ~/ yInfinitely great, 无穷大( k6 R" D8 E5 V; n% C3 C. x2 u
Infinitely small, 无穷小
# d" Z; }" ^$ ~/ L$ y5 t+ MInfluence curve, 影响曲线. l3 J# H" }0 b) o; P- M
Information capacity, 信息容量
' @( C" H7 F$ |5 e6 N. Q( B/ r) ]) ]Initial condition, 初始条件
" ^" {- c# q' K) I; sInitial estimate, 初始估计值* v, k- c2 X0 S" M/ }
Initial level, 最初水平
7 V( G* ?/ a [5 O. O/ B: MInteraction, 交互作用
( @& ?+ o, B# j5 }/ bInteraction terms, 交互作用项
- c/ R' ~3 M" z+ o hIntercept, 截距, c: I$ `9 c+ r+ f5 E
Interpolation, 内插法
6 q: B. p4 j5 ?1 [5 |" e# P' z3 LInterquartile range, 四分位距0 i1 l* ^0 H, Q& \! [$ @
Interval estimation, 区间估计
6 M8 y+ L& ?3 s" f" I. z3 V2 M" FIntervals of equal probability, 等概率区间& G( g3 g- c+ P
Intrinsic curvature, 固有曲率
' R$ ~) x1 G8 ?6 h6 B. MInvariance, 不变性
; a- `8 q W" \3 f1 pInverse matrix, 逆矩阵
9 ]8 n1 z) a: G! nInverse probability, 逆概率$ X: ?# X: O0 m4 O& N& G2 y
Inverse sine transformation, 反正弦变换
% s: K, ^$ k* `: b0 zIteration, 迭代 , C4 Q) M- ~% d. _0 X8 o' f1 t
Jacobian determinant, 雅可比行列式
: q$ u- j1 V4 R9 y) Q7 G. z, wJoint distribution function, 分布函数
- |: Q7 `% J9 a6 S& \+ VJoint probability, 联合概率2 F& c9 j& ]; y
Joint probability distribution, 联合概率分布! g0 L% L+ z: c3 Q+ A5 e
K means method, 逐步聚类法
0 q% `! g- [% BKaplan-Meier, 评估事件的时间长度
3 M7 k: i! l3 K8 k# ]Kaplan-Merier chart, Kaplan-Merier图( M& Z0 L a: _3 F
Kendall's rank correlation, Kendall等级相关9 @, k: O; @. L$ ~
Kinetic, 动力学
$ E) G, y+ P0 ^' ?: \) Y0 o% hKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
1 _) U8 J3 Y# v: a& ]Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
4 T; I# z/ A$ k i2 _* F$ M9 ^! IKurtosis, 峰度
+ X- Z; I+ D w7 ?: @Lack of fit, 失拟+ Q/ {: m* y7 ?) I4 q
Ladder of powers, 幂阶梯
7 l7 Z& i' V. _Lag, 滞后
1 S: f# v- v! ~# e4 G$ r% Z0 C7 SLarge sample, 大样本
& v8 y' E/ Q2 y6 `1 C; gLarge sample test, 大样本检验
# E7 l$ c+ I5 Y$ s7 M! qLatin square, 拉丁方1 g$ E' ?* d* N- [8 f
Latin square design, 拉丁方设计
. K% C' C2 o+ I+ u iLeakage, 泄漏3 `% K) q: c" |/ K6 B9 }. c; `. c3 j
Least favorable configuration, 最不利构形! E( M. t! P* g" K3 C1 l& I
Least favorable distribution, 最不利分布
$ `* M, }: d# C- N* E9 yLeast significant difference, 最小显著差法3 s! F/ R/ k" G, T- s( Y
Least square method, 最小二乘法
2 ^* r+ d" G% D( f% h# T# Z2 RLeast-absolute-residuals estimates, 最小绝对残差估计
! @# I( I3 C5 D5 I3 FLeast-absolute-residuals fit, 最小绝对残差拟合! B+ w& t v& U; q; v0 _: I& g# q6 ]
Least-absolute-residuals line, 最小绝对残差线
0 X( i1 ?& f) g7 @) a( mLegend, 图例
0 Y5 [ v% G) v3 d X" W3 \; YL-estimator, L估计量
% m" ]! s- ?/ M6 R `6 ~0 o8 IL-estimator of location, 位置L估计量 {# |+ s( w$ p) E$ p$ r
L-estimator of scale, 尺度L估计量
+ c+ L. ]% h+ {! V' f) W' E1 nLevel, 水平: ]& h" R6 ?$ g& p' I
Life expectance, 预期期望寿命
5 M% Q7 o! J x+ y c; B! W& zLife table, 寿命表& Z6 k* B5 `+ E, w$ O
Life table method, 生命表法
, x2 K9 a3 p/ m* E3 k) `# w0 c8 c: dLight-tailed distribution, 轻尾分布
0 Y* s$ I$ B$ S( H# G+ }: ALikelihood function, 似然函数6 r' j9 M9 A6 u) b) q
Likelihood ratio, 似然比
4 e3 T' h: N6 h( Mline graph, 线图% V9 \8 S; K" o. e5 a9 Q* c, J
Linear correlation, 直线相关
* N/ U8 R# Q: s$ M* U9 RLinear equation, 线性方程% Z& G" A, ]4 `5 O' J. ~% c
Linear programming, 线性规划
" F- [) M9 B0 Z+ }Linear regression, 直线回归
$ l* G! M( ?# E% z8 mLinear Regression, 线性回归
6 H) W: `7 ]/ k, y+ t) KLinear trend, 线性趋势
' d5 u, K+ M: n$ l$ ^Loading, 载荷
& J( t, ~4 @* J6 k/ ULocation and scale equivariance, 位置尺度同变性
+ _/ k6 w6 ] R& A' t+ cLocation equivariance, 位置同变性. o! @; n& ] h% J/ c
Location invariance, 位置不变性
# j0 \& r! }! k3 ]: L! p; f: o' ]Location scale family, 位置尺度族9 B9 h/ \. }2 ~7 @$ ^: k
Log rank test, 时序检验
6 g) [# @- {# h, G5 z4 ~8 k" _$ VLogarithmic curve, 对数曲线 e6 F+ B5 _1 ?% c0 p8 N2 V
Logarithmic normal distribution, 对数正态分布% e) y8 W/ P/ I7 d' }
Logarithmic scale, 对数尺度( c3 J" w5 ^# Y
Logarithmic transformation, 对数变换
& O, p( W0 y: ?3 RLogic check, 逻辑检查" o3 M; b, ~9 |
Logistic distribution, 逻辑斯特分布
+ `4 N+ Z1 z8 oLogit transformation, Logit转换
, R6 P/ m( C1 F0 ]( M2 `+ a; iLOGLINEAR, 多维列联表通用模型 + O5 \4 A) y4 T$ h5 c: ~
Lognormal distribution, 对数正态分布
0 g; M" X" F- N/ u& \3 bLost function, 损失函数
7 F8 }2 N3 T% ~Low correlation, 低度相关. P; o4 j0 Y1 v: Z
Lower limit, 下限' o/ ^, L' C# V% c/ e: F
Lowest-attained variance, 最小可达方差
" J+ e W$ k) s4 @4 R3 E" r) ZLSD, 最小显著差法的简称5 v5 H6 k5 V) z& |6 v
Lurking variable, 潜在变量
. o: \1 y" s" w. b3 JMain effect, 主效应( n, W' S9 D R3 U7 j& Z: Q
Major heading, 主辞标目5 M$ O% m+ l! L6 N% t
Marginal density function, 边缘密度函数. u: c# r* d% y* S2 m
Marginal probability, 边缘概率2 m5 H' E% b" i1 Z; i% O. `
Marginal probability distribution, 边缘概率分布& J6 F8 `. X9 t, I
Matched data, 配对资料
# a* O8 g6 T& e! N8 c) GMatched distribution, 匹配过分布
7 y* |6 A, k! R2 uMatching of distribution, 分布的匹配
6 |7 n3 |( u6 ?" n0 r# q3 ]Matching of transformation, 变换的匹配
9 L/ h y; e' n# j# G+ zMathematical expectation, 数学期望" ~. v9 o$ H6 f; B! q) f
Mathematical model, 数学模型3 p( r( x" S; | l
Maximum L-estimator, 极大极小L 估计量
0 H y1 w1 P1 P0 HMaximum likelihood method, 最大似然法
/ C7 g" S2 u" O/ V8 SMean, 均数
- `* g" ^' Y0 ^/ HMean squares between groups, 组间均方+ }- R4 A/ t4 `9 P7 S: f9 f
Mean squares within group, 组内均方
$ y9 n# D% q8 [$ i$ G2 T6 lMeans (Compare means), 均值-均值比较. q( C9 H; U4 a( k* C, P
Median, 中位数
# |- ? B, H& h$ `4 d" VMedian effective dose, 半数效量
8 T _* o1 h6 l* J; oMedian lethal dose, 半数致死量6 s+ I% p0 a9 o4 B
Median polish, 中位数平滑 p1 ]# \" j, P, L# _1 `% x
Median test, 中位数检验
0 ^2 \, X' t- J+ r* a" z6 V7 m5 r# O, cMinimal sufficient statistic, 最小充分统计量
* X. @% @, m/ ~- \Minimum distance estimation, 最小距离估计1 ~0 G2 |+ T5 V% D) |
Minimum effective dose, 最小有效量( ^! y8 s/ i U4 {5 B6 ]. V
Minimum lethal dose, 最小致死量
1 t' P0 q1 R+ a6 Q2 s" GMinimum variance estimator, 最小方差估计量
: e) {8 |: Z+ ~8 w( L/ rMINITAB, 统计软件包. u0 L: C9 [1 k' ?
Minor heading, 宾词标目
. B( P+ p. J) |: Q( RMissing data, 缺失值6 ?+ p! F$ \ I! ]- c" O5 M: _+ ?) \, M
Model specification, 模型的确定, H1 a2 R, B$ }8 ^1 o# v
Modeling Statistics , 模型统计) {, ^6 K- F. j- _* W7 ~2 o8 p; C
Models for outliers, 离群值模型- C. w7 J5 a5 B% m* a4 |! o
Modifying the model, 模型的修正+ N. a, q% t" P1 L: B J
Modulus of continuity, 连续性模3 g6 d! x/ X' G5 y, ?; C
Morbidity, 发病率
0 F! e/ A }: ?5 l+ qMost favorable configuration, 最有利构形8 T. E1 H8 X6 H, W' E& h- q# C/ ~
Multidimensional Scaling (ASCAL), 多维尺度/多维标度- e4 `5 C2 P' j- Y6 x4 k
Multinomial Logistic Regression , 多项逻辑斯蒂回归
V' a2 P" A; I, I1 e0 @Multiple comparison, 多重比较! t0 r, g% u7 F% p! y" E3 n
Multiple correlation , 复相关
) X' q! k& Q+ ^! w4 W7 e* o- MMultiple covariance, 多元协方差0 L( [8 P1 U6 @$ H1 c
Multiple linear regression, 多元线性回归3 u+ B& }7 w; A* |
Multiple response , 多重选项
/ Q d% t4 R: }+ nMultiple solutions, 多解6 m1 T5 b( u8 _1 s# R6 ? M
Multiplication theorem, 乘法定理6 I5 ?$ E% y3 {9 @% Q- E' Q
Multiresponse, 多元响应4 L; @! o1 s5 r# ^2 x8 n8 H
Multi-stage sampling, 多阶段抽样
) J- [ ?$ ?* l, ~! O4 g( E2 M0 `+ g6 TMultivariate T distribution, 多元T分布& W! `* }$ L' n9 B9 N% h
Mutual exclusive, 互不相容$ x; R y8 e' F0 _) j, |* a
Mutual independence, 互相独立1 |5 j$ T( n6 R; r
Natural boundary, 自然边界# C7 z; ~9 I' _, _- j0 k: T5 f4 l7 s9 a
Natural dead, 自然死亡
, b5 I3 D( Z% sNatural zero, 自然零: k; B+ q5 J. A
Negative correlation, 负相关
* `/ E6 b* p# yNegative linear correlation, 负线性相关
4 k( e) h! z' lNegatively skewed, 负偏& a) s8 M* L% q# e7 z+ ~
Newman-Keuls method, q检验3 C1 Q2 o3 i: j- ]1 s
NK method, q检验) I1 P3 N& O1 s3 c
No statistical significance, 无统计意义7 M0 |+ L' \" E+ b. u5 C2 q
Nominal variable, 名义变量
/ E. k! Y( [: s) O6 A8 d% XNonconstancy of variability, 变异的非定常性+ y" P1 V7 s; T3 |- v$ Z1 g1 d- T
Nonlinear regression, 非线性相关# R) \4 A: w5 V
Nonparametric statistics, 非参数统计& Q9 y7 z, @: o; Y$ V$ e
Nonparametric test, 非参数检验$ h* h! H; S' m
Nonparametric tests, 非参数检验" x! j3 K) Q/ f9 E8 H3 Q4 J. s
Normal deviate, 正态离差9 M9 n0 p6 w" d1 e
Normal distribution, 正态分布 N9 M, h9 ^$ a
Normal equation, 正规方程组
# k' w! Y$ V+ t, Z& _* ?6 L, XNormal ranges, 正常范围$ d. K. _, L7 S( N( E* n
Normal value, 正常值3 c5 V* f5 Z8 @. Y9 }6 R
Nuisance parameter, 多余参数/讨厌参数8 B* {/ H5 l9 R) ^) ^8 M- f" m; M B% q
Null hypothesis, 无效假设 8 ?3 v8 x, ?% K6 e5 T# I
Numerical variable, 数值变量7 f2 H; W; m0 q' Z0 ?
Objective function, 目标函数
' r4 o( F) n# z3 h+ Q" ?) E' hObservation unit, 观察单位+ b& S7 ~" {! R! v
Observed value, 观察值: {+ a) a, W$ D. z# p
One sided test, 单侧检验
; i u, E3 z0 y! EOne-way analysis of variance, 单因素方差分析% J; i6 H1 k% J3 X' p6 m/ t: o; v
Oneway ANOVA , 单因素方差分析2 l5 t9 z, @3 d6 m
Open sequential trial, 开放型序贯设计
/ u1 D! S7 n* i, qOptrim, 优切尾
) o/ l; \/ B, y* J0 kOptrim efficiency, 优切尾效率
; ^1 W- U2 {( N& U4 a* OOrder statistics, 顺序统计量$ X1 W) b, t& _! a. x$ C& `( K
Ordered categories, 有序分类, r7 n! g$ m3 Q, g8 N; w D& p7 [7 f* l
Ordinal logistic regression , 序数逻辑斯蒂回归6 Z+ W9 C4 u- N6 D: R: x, l
Ordinal variable, 有序变量( _' V9 G* e& K" |; ?8 K
Orthogonal basis, 正交基1 J5 x9 W/ s3 v& ]7 R$ {
Orthogonal design, 正交试验设计, B- J2 `6 T& s7 {& [
Orthogonality conditions, 正交条件
. y. H! H8 r( U! |ORTHOPLAN, 正交设计 # U0 `+ d# {8 Z0 k
Outlier cutoffs, 离群值截断点0 p- _1 ?5 n E( x6 ?! M2 ^
Outliers, 极端值; ?( A6 n5 {2 q9 R+ H. o
OVERALS , 多组变量的非线性正规相关
) n1 u0 s4 a, M6 G K3 G) t! j- ]Overshoot, 迭代过度% R0 j7 x8 f" S
Paired design, 配对设计/ |2 ~, W) J% U* m, n* f7 R/ |( A
Paired sample, 配对样本! Y( Z) [* d8 K
Pairwise slopes, 成对斜率
) A/ S. Q1 y8 vParabola, 抛物线
- }# ?5 x$ K8 R8 a: WParallel tests, 平行试验$ M! L. X! j8 W& S7 |. [
Parameter, 参数
# s" P2 A: K$ O4 @% V' aParametric statistics, 参数统计
& p" k4 h0 o) r* L7 w9 ]Parametric test, 参数检验
: z: ?+ b% f& K6 z- zPartial correlation, 偏相关
, F) V0 L/ q1 O5 I3 `7 O6 o1 WPartial regression, 偏回归9 z9 M( ]0 E4 o1 e5 L
Partial sorting, 偏排序 a ?5 T; c% _
Partials residuals, 偏残差
2 {, l; K$ O4 Z* o$ ~ NPattern, 模式5 F/ V$ @% {7 c+ G
Pearson curves, 皮尔逊曲线1 B# M, v4 v% r: v6 A, P& D
Peeling, 退层
8 ~0 a1 M# i9 w ]( R y# XPercent bar graph, 百分条形图
" p+ F# d) O, x# KPercentage, 百分比
$ X1 K# R! e rPercentile, 百分位数
) F% w! P2 J7 n6 {: TPercentile curves, 百分位曲线2 |3 k$ ^8 U f; q2 E6 O2 |( k
Periodicity, 周期性+ B1 a6 K4 s- F! p( f4 i
Permutation, 排列
7 q" B3 w- k$ L% b! ]# [8 [9 gP-estimator, P估计量
% S% y" f1 |3 z6 x* cPie graph, 饼图
m3 X; W9 x5 {; I8 q* V' R1 hPitman estimator, 皮特曼估计量
$ g2 O& |6 J; zPivot, 枢轴量7 e5 A6 h0 @" T! z1 [# K
Planar, 平坦
, e: S( @6 i5 H7 Q0 rPlanar assumption, 平面的假设4 @: |. L, L0 q7 r9 U) k/ V
PLANCARDS, 生成试验的计划卡, x8 R; Q4 R2 ^' x2 d& U! J
Point estimation, 点估计5 l9 X! Y$ |6 c+ v4 ]3 ^
Poisson distribution, 泊松分布
6 b; ?$ o. n. a9 V& _Polishing, 平滑$ \7 N/ x' R( B2 @) ^) p7 W' p9 y
Polled standard deviation, 合并标准差' t& n- ~$ }: C. y) @
Polled variance, 合并方差
p9 o8 Y0 e4 J. r; \Polygon, 多边图7 z8 J: F" \- f4 A8 j# |2 B- s
Polynomial, 多项式
: }. `" K; I) ?) i$ r$ X* |Polynomial curve, 多项式曲线
6 r4 k! B% Q/ GPopulation, 总体
( P0 C' D) L% I/ F6 G$ x; `6 L1 ^2 GPopulation attributable risk, 人群归因危险度
0 m. ^! z' Q% g" CPositive correlation, 正相关8 N. z& l# {6 r( _+ Q0 `% V
Positively skewed, 正偏
4 J" T, \7 _% r3 ]/ ?- _5 u7 UPosterior distribution, 后验分布3 M1 a, `6 F1 w2 j1 B S
Power of a test, 检验效能
0 w' E7 F$ e% r7 UPrecision, 精密度7 h9 Z1 c" W" ]4 E6 x
Predicted value, 预测值
7 p6 k$ ~( t+ ]1 u" X/ m8 m- yPreliminary analysis, 预备性分析" t. d: e: I8 s8 Z i$ R8 f
Principal component analysis, 主成分分析
! T( ~! X1 M; h2 D+ FPrior distribution, 先验分布6 w A5 W& @4 g9 t" P- s4 v
Prior probability, 先验概率3 j6 y8 J1 \7 @9 k7 }
Probabilistic model, 概率模型8 c k5 l. _5 k" g
probability, 概率: G* U* [6 B! _
Probability density, 概率密度
- T$ p' z& p; M; MProduct moment, 乘积矩/协方差
$ c" f% k# U% ]; {7 t& NProfile trace, 截面迹图
* U! Y; G+ [1 y8 T0 U# kProportion, 比/构成比; j2 M( S, X* v' a* h3 L6 U# E
Proportion allocation in stratified random sampling, 按比例分层随机抽样
* H1 F0 R N# [9 B2 BProportionate, 成比例% O& t* o# W. `/ p& U" }
Proportionate sub-class numbers, 成比例次级组含量
; w N/ B- W9 [! QProspective study, 前瞻性调查
3 O' O) ?6 a% p5 @ q- e+ Y$ qProximities, 亲近性
, B: _" @3 A, T: D* l! jPseudo F test, 近似F检验
) R4 B2 v8 {' M2 C9 f7 zPseudo model, 近似模型6 ~: _; `5 e& }8 X% W8 D# e
Pseudosigma, 伪标准差
; [# [$ g. V9 N' `( ePurposive sampling, 有目的抽样3 K4 T( A0 t7 e7 o0 w9 O% \0 W
QR decomposition, QR分解
0 }* C9 V8 P: S* q1 A3 Z9 P+ Z: KQuadratic approximation, 二次近似
- j; E0 C& G* i- O, V' W. e4 \1 CQualitative classification, 属性分类
- ~3 d9 K7 u! JQualitative method, 定性方法
6 V9 b- I# g" c* R/ k9 EQuantile-quantile plot, 分位数-分位数图/Q-Q图4 E1 }3 v, b" _* W$ @4 h4 o
Quantitative analysis, 定量分析
0 I# D, C2 x9 h2 d! ?, s8 GQuartile, 四分位数
5 w- J% l0 S$ ^4 h" t8 F# `Quick Cluster, 快速聚类, R6 v0 e; |& |& X1 F, h
Radix sort, 基数排序
0 p: R8 Y- z% Y* h+ v# o/ H; ?: aRandom allocation, 随机化分组0 ]5 G" `" z6 s
Random blocks design, 随机区组设计9 W2 A( G7 N! i k% C8 I3 P
Random event, 随机事件
8 B* S7 s1 v+ L4 ?3 z# LRandomization, 随机化0 P* ^( r9 A, `% K4 ~
Range, 极差/全距5 H7 b5 i* Z6 Y( _3 f4 u i6 ^
Rank correlation, 等级相关0 k- t R. a1 C- [: N. s4 ^
Rank sum test, 秩和检验
. l( \2 R K( G+ h$ vRank test, 秩检验
1 N5 }- w x* L# C, T: dRanked data, 等级资料0 l6 @! d5 @; E c! e
Rate, 比率# q% N; S7 Z' f/ _4 L9 W
Ratio, 比例
; Q+ s7 d* @8 G) v! H4 w, |Raw data, 原始资料& H; n) C5 I8 i% y
Raw residual, 原始残差2 B# b9 ?+ A3 \: P
Rayleigh's test, 雷氏检验1 q1 `, T) A1 |% e' ]
Rayleigh's Z, 雷氏Z值
+ q8 j; @0 X# h2 E8 T& B, ^Reciprocal, 倒数
1 Q, e. k \; {0 GReciprocal transformation, 倒数变换
8 o2 ]) A* K+ F0 X4 `7 `& O( tRecording, 记录4 ~: M( F; K9 ^0 }$ Z
Redescending estimators, 回降估计量, U# j1 P1 L6 x2 `
Reducing dimensions, 降维, w! V$ X- R- h# G
Re-expression, 重新表达9 m6 H0 q' S8 L. x
Reference set, 标准组/ V$ V. i" U+ f- J
Region of acceptance, 接受域
( `7 Q+ y& M5 r/ t) f( p2 jRegression coefficient, 回归系数5 P' c9 c3 o( X- G" w, G
Regression sum of square, 回归平方和" ]8 @+ a7 S1 k, p
Rejection point, 拒绝点
5 R. Z t( p8 c2 Y+ ~# iRelative dispersion, 相对离散度
$ v* D7 g7 W$ I. IRelative number, 相对数
; u4 z! I5 x0 { M) [/ m7 [% XReliability, 可靠性
9 R/ g h, T% f* QReparametrization, 重新设置参数/ P9 x* x5 F/ z
Replication, 重复) o" O/ N: X2 ?! i5 t7 A$ u' M) k
Report Summaries, 报告摘要
* L6 g! e) D1 `2 i3 P7 v, v+ QResidual sum of square, 剩余平方和
7 p+ {- a2 b8 j# f6 MResistance, 耐抗性
% }* t+ t$ H! F- FResistant line, 耐抗线
1 ~& C/ y& ~" x) AResistant technique, 耐抗技术! m: [& G" r% d7 m' ^6 ` `8 f
R-estimator of location, 位置R估计量9 n% ~: M8 d' x7 J
R-estimator of scale, 尺度R估计量: S" A% ?3 G+ x! m, m
Retrospective study, 回顾性调查
, Q( J3 M+ ~2 V5 P* U* [' u& hRidge trace, 岭迹! o: j2 j J& ~0 V
Ridit analysis, Ridit分析
' i2 B" B$ h2 u/ B" ~# |% @* ?7 dRotation, 旋转0 _ I. f1 {9 \; m9 @, i) V x
Rounding, 舍入
7 e A# @* f& n2 ?+ KRow, 行
/ v1 B. G% B" D5 x2 M ]; F8 q: }Row effects, 行效应
" ^8 E4 M3 N) L0 C! h& SRow factor, 行因素
' C$ T- @' P4 a, ?% X/ hRXC table, RXC表* z! W9 p* K m" l9 u9 I: }
Sample, 样本8 G$ i6 J; O8 v
Sample regression coefficient, 样本回归系数
7 i2 b: H; b: W) K L) KSample size, 样本量1 u" K5 i; D' z) @& c9 C/ |, _
Sample standard deviation, 样本标准差
& u' M6 H. G' v; P) @4 I V1 ySampling error, 抽样误差
F2 ~% L/ |2 g9 ~( `SAS(Statistical analysis system ), SAS统计软件包
6 b' v. W" y% W4 I* X+ }Scale, 尺度/量表) \# F$ z# u b: z( S! d
Scatter diagram, 散点图 X4 `+ j& @3 S* l4 U5 z; L
Schematic plot, 示意图/简图
% @0 V3 h+ |- iScore test, 计分检验
% f {! ]4 p: Z% d3 TScreening, 筛检
% o3 X) B7 ^; e& gSEASON, 季节分析
+ X! D r+ ]) Z( D- z: h9 tSecond derivative, 二阶导数
9 k0 x5 O4 _% k) W S1 Q, z( iSecond principal component, 第二主成分
0 L1 J1 e& B) U* FSEM (Structural equation modeling), 结构化方程模型
" F w2 T# z* r0 U0 HSemi-logarithmic graph, 半对数图+ l; c0 q+ ~4 P$ T+ a6 F
Semi-logarithmic paper, 半对数格纸
4 k) g8 j8 a0 j* f \$ mSensitivity curve, 敏感度曲线( e r/ z! L- a
Sequential analysis, 贯序分析! }& a- I8 v3 n+ m/ ?
Sequential data set, 顺序数据集. q- N' y# q- {1 W5 j- X* Z
Sequential design, 贯序设计3 f; v/ U9 \, H! k" U
Sequential method, 贯序法
# Z! l1 \" s/ O1 b" G' f9 d hSequential test, 贯序检验法% M9 v5 K; I' z' ^ p, w' i
Serial tests, 系列试验6 s/ i# V/ @" g0 Q; J& W
Short-cut method, 简捷法
5 ~7 L, q5 G9 y# m5 @! GSigmoid curve, S形曲线
. P$ `, |5 W @8 A% pSign function, 正负号函数! C; q- g' s7 f4 C, t! v
Sign test, 符号检验
- X. W, _7 I3 R- `2 l# E) [4 |Signed rank, 符号秩: R) P4 M3 s0 t3 D; |' D* ~
Significance test, 显著性检验; B4 v: x- m4 t5 Q0 O
Significant figure, 有效数字
" L7 W) |6 l. wSimple cluster sampling, 简单整群抽样
* @( `# y2 _: t+ n, \Simple correlation, 简单相关
" ?, S2 f0 z- [3 W, q7 DSimple random sampling, 简单随机抽样
- S$ _8 w0 T: kSimple regression, 简单回归
M3 @ U) U2 Bsimple table, 简单表8 ?& `. h9 \6 r7 X ]. y$ k
Sine estimator, 正弦估计量
" \, D7 e8 Y% ISingle-valued estimate, 单值估计0 T% |' z E7 P8 ~6 `6 r
Singular matrix, 奇异矩阵% Z! Z+ F8 G' R$ b
Skewed distribution, 偏斜分布
+ Y( e( n: R9 {' eSkewness, 偏度
) V' Y( l- d8 \2 R( w' tSlash distribution, 斜线分布9 a) Q. C4 [' `" i) H6 B8 {7 H
Slope, 斜率
# d, P# F$ g4 I2 e/ T/ ISmirnov test, 斯米尔诺夫检验
+ B! ~/ U; _# G4 B( ^; _Source of variation, 变异来源( U* u H. n* L5 ^3 M
Spearman rank correlation, 斯皮尔曼等级相关
+ R* K' v! ? z& ~! z* }# |' c: LSpecific factor, 特殊因子: y+ k+ g r2 ]$ `) c& S/ B
Specific factor variance, 特殊因子方差
* u0 b [+ \ [Spectra , 频谱
( d; R- h s/ w( OSpherical distribution, 球型正态分布( L V$ c: ^5 Z, \# z, K7 U ^
Spread, 展布; e* y8 t) h) U
SPSS(Statistical package for the social science), SPSS统计软件包2 B K' h+ Y, r( a2 M
Spurious correlation, 假性相关7 d6 {# r" C* `# v( _
Square root transformation, 平方根变换- _, z8 _/ n7 Z' }
Stabilizing variance, 稳定方差. L! L. d c2 O; e" n9 }
Standard deviation, 标准差
: E% E% z8 |( D5 F) S1 fStandard error, 标准误
8 Y6 [* c1 a1 s) c3 Y( hStandard error of difference, 差别的标准误2 w J$ L+ O- ~: ]( `
Standard error of estimate, 标准估计误差- ~# k, p6 ?" t% {
Standard error of rate, 率的标准误
# ?( p8 `* b& x. o2 gStandard normal distribution, 标准正态分布7 c" R( u2 b) X) z
Standardization, 标准化
1 V6 W2 `. c C6 MStarting value, 起始值, n! t( e1 d9 P
Statistic, 统计量0 R9 y* g' q5 j* m
Statistical control, 统计控制7 L# _* M3 U2 u8 s2 `7 Z
Statistical graph, 统计图# J0 V* r" `# ~5 M6 [
Statistical inference, 统计推断
& M) z8 y# P9 |! z, V; OStatistical table, 统计表
$ O# N5 w, G7 l1 i' ~- OSteepest descent, 最速下降法+ Q& H/ X5 p6 v( C
Stem and leaf display, 茎叶图
- }' ?$ v5 f6 j% @" QStep factor, 步长因子
h! Q+ d. o( h- M! M1 HStepwise regression, 逐步回归
5 N: K- ?$ E% M0 a8 RStorage, 存
# ]' {$ a9 Y7 {& [Strata, 层（复数）
) |4 |. j+ x! TStratified sampling, 分层抽样
' l4 V; }7 a/ `( T! lStratified sampling, 分层抽样
3 z1 y- s& f5 f ]% H' sStrength, 强度
" }! h2 C% X# z2 Z9 {Stringency, 严密性
! J4 e" r* z5 r$ ~! wStructural relationship, 结构关系, z* A" Q4 m8 T; s
Studentized residual, 学生化残差/t化残差
, L* s: R& C' FSub-class numbers, 次级组含量, u/ u5 ~$ K! G& s( n% O
Subdividing, 分割- C- Z. ^9 w7 Y& m. V
Sufficient statistic, 充分统计量
: X! |: O4 ~3 I: k9 w3 pSum of products, 积和
- Q8 O4 Q& Q L5 NSum of squares, 离差平方和( i' _) K5 K% J5 W' P6 ~
Sum of squares about regression, 回归平方和
6 t1 I: [; D: A+ k9 uSum of squares between groups, 组间平方和
: C% P; }: E8 j9 vSum of squares of partial regression, 偏回归平方和
9 c; U- P5 K/ e4 g7 L. QSure event, 必然事件. L; H5 s* x! \1 V0 a; ~/ e
Survey, 调查
8 I$ j1 |5 ^7 I8 o7 k: {" rSurvival, 生存分析
2 f7 W( y I z0 JSurvival rate, 生存率
3 y) d; o6 {% h& JSuspended root gram, 悬吊根图
, k$ t; n4 G0 u3 G# u/ J/ lSymmetry, 对称/ R. S u! k6 {
Systematic error, 系统误差0 s# |9 B0 K* S2 U( l' h
Systematic sampling, 系统抽样$ q1 q3 }: x. w
Tags, 标签/ |; ~, I, [8 g$ o: a- }# n# x$ q
Tail area, 尾部面积
) x& ~- G4 l) d; k6 o, r! E% l5 a( ETail length, 尾长% d3 c& H% |' l! H2 M
Tail weight, 尾重% R4 ~6 o4 o7 c3 ~) ~* H3 q6 u
Tangent line, 切线. P, g) m1 r* x: y6 a3 R% G
Target distribution, 目标分布9 o6 @- h! V( u! ]# I
Taylor series, 泰勒级数
R) i" G/ Z2 f) A8 ?; ~7 nTendency of dispersion, 离散趋势
5 n% S; _5 B v; w! C4 I$ y$ OTesting of hypotheses, 假设检验
& O$ B" N. j* v6 U4 |3 W+ x& t& x( ETheoretical frequency, 理论频数
g2 p" ~+ ]: u7 M9 l4 d1 Z& r0 GTime series, 时间序列
) a, }1 U. q) K0 h# J/ d( VTolerance interval, 容忍区间/ t- C, l% S) y7 g) ?1 H P
Tolerance lower limit, 容忍下限
1 c9 g. {0 t2 ^, gTolerance upper limit, 容忍上限
# h: x" N: Z3 D% a$ Y; e$ X3 uTorsion, 扰率
2 V1 H2 y* e jTotal sum of square, 总平方和
& L* i! E# l5 gTotal variation, 总变异+ d; }9 d, A q+ J( v% O/ d
Transformation, 转换
3 T/ q" L/ y) K3 g, h |0 m0 ETreatment, 处理' c! _; H- O0 }& h" N0 b. i
Trend, 趋势: T Q4 |7 T& V$ x* x* w- S
Trend of percentage, 百分比趋势
) M1 L3 o H/ O' H4 t# Z4 DTrial, 试验& p/ C* P5 _4 ^6 ?& \" R
Trial and error method, 试错法
3 W2 E6 _) k8 u# c2 J9 F5 U/ @Tuning constant, 细调常数
/ n) m- x4 J: u7 S1 v0 h( HTwo sided test, 双向检验
/ s2 O$ H* d; h# t; v" O* X. cTwo-stage least squares, 二阶最小平方7 F3 K& u" q8 \8 ?7 [% j& F
Two-stage sampling, 二阶段抽样: k/ W) a8 A' h6 m8 D
Two-tailed test, 双侧检验
$ ~0 z0 ^& B- ~% W& L, ZTwo-way analysis of variance, 双因素方差分析
/ ]7 j# G L/ C4 V# F" eTwo-way table, 双向表 h" c+ h! A, @$ J9 G; t [
Type I error, 一类错误/α错误8 M. K% u' G8 \! E, ~7 I
Type II error, 二类错误/β错误
6 b) E( s: L7 W8 _5 D; P$ LUMVU, 方差一致最小无偏估计简称5 V: O$ C3 |9 E& }3 B
Unbiased estimate, 无偏估计+ t, Y5 L# v" P+ Z5 }$ G5 V
Unconstrained nonlinear regression , 无约束非线性回归8 r0 U# o3 W9 f* J6 U6 g% u0 ] ^
Unequal subclass number, 不等次级组含量
/ `$ D% P: H2 d2 Q1 ^Ungrouped data, 不分组资料, c9 w0 g% T1 `1 N, m4 D
Uniform coordinate, 均匀坐标8 f; }/ X( V& a! [- G' r
Uniform distribution, 均匀分布1 S7 Z$ v4 {2 W" C1 N& \
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
, r4 d- g: z- Z F% jUnit, 单元
6 E0 z) T6 b- AUnordered categories, 无序分类
5 i! F6 m* n. K* {. qUpper limit, 上限1 h; H% K2 h0 a+ \* B5 k- {" Q
Upward rank, 升秩
, a! v2 Y4 @0 `# i4 B2 b% t! X* WVague concept, 模糊概念
5 A9 j% C L% d$ q2 A/ E$ ZValidity, 有效性7 ? }! i+ o( Y
VARCOMP (Variance component estimation), 方差元素估计. l9 k' P6 p/ @/ q
Variability, 变异性
* f; c9 ]" @7 Y4 M8 y4 l# EVariable, 变量6 B- O6 ^1 a) U. u C
Variance, 方差
4 p! y* g2 y0 l L+ FVariation, 变异3 c- X, t2 H* t, W- \5 x
Varimax orthogonal rotation, 方差最大正交旋转
4 p5 j5 g0 P$ {3 C# j: L5 a9 }Volume of distribution, 容积9 I# [* r" N6 d; w$ q% B4 W: @) s9 i
W test, W检验 S h; B% z& T, Z9 Z8 R( Q) i* E' x: K
Weibull distribution, 威布尔分布; n# B n( _* A0 J( w, ]2 w$ S
Weight, 权数
; S$ I9 J/ W! s- I5 D' TWeighted Chi-square test, 加权卡方检验/Cochran检验% J1 R. M% Q: ^: d* \+ {1 r
Weighted linear regression method, 加权直线回归# t7 n+ `* P5 _
Weighted mean, 加权平均数9 q( o* t& H: q
Weighted mean square, 加权平均方差
- `$ x! E% {# P OWeighted sum of square, 加权平方和
3 v5 K- V8 c1 e9 i) I' ]& LWeighting coefficient, 权重系数& z& a% e1 V# Z8 L
Weighting method, 加权法
. X7 _/ h1 b" k8 mW-estimation, W估计量" }+ T! V9 ^6 e
W-estimation of location, 位置W估计量( T, Z2 O" B: ?9 x
Width, 宽度! T4 J5 ^3 k# o0 c. e( Q
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
( S9 e! _$ u! m- E2 J( h8 jWild point, 野点/狂点6 D( e V+ S4 e! y
Wild value, 野值/狂值
h' H2 Y/ Q# p- S* mWinsorized mean, 缩尾均值! Y. |6 j& v/ S2 I" S
Withdraw, 失访 ! _3 }1 s! C. {1 d5 L
Youden's index, 尤登指数
( p0 r! A2 l2 K& Q Z' tZ test, Z检验
% F0 X3 Y; f" MZero correlation, 零相关
: d! O! X* s4 y3 _0 ZZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
