|
|
Absolute deviation, 绝对离差
7 K9 S+ S& _4 W% G1 `- gAbsolute number, 绝对数( ^7 q" t: u5 j0 k9 F. ?
Absolute residuals, 绝对残差
1 i* V4 E+ P) P& Y' D% \$ AAcceleration array, 加速度立体阵
6 ]8 S. H) z% @; DAcceleration in an arbitrary direction, 任意方向上的加速度
0 ~' o0 L8 M" Z: m% f/ tAcceleration normal, 法向加速度0 A! B6 [4 d2 ]% L6 r
Acceleration space dimension, 加速度空间的维数, }8 Y" a5 d) k4 x0 g" [* `
Acceleration tangential, 切向加速度
1 O# o* F7 f4 X5 T2 Z- V( ~( }Acceleration vector, 加速度向量
( ?4 [7 t- {' V" i3 {Acceptable hypothesis, 可接受假设
* m3 a% L/ f& NAccumulation, 累积
7 T& y* d% S) n/ ~9 pAccuracy, 准确度
7 R2 ?) Z% X: g0 yActual frequency, 实际频数
- Q# { }3 p) f0 b. I; R( J8 e kAdaptive estimator, 自适应估计量% @! R |5 `, Z. |4 h. w' G9 W* e# O& }
Addition, 相加
: i0 Q; d+ |* _: aAddition theorem, 加法定理5 }$ Z s3 K# W- ], L$ y/ e
Additivity, 可加性( a. s8 S6 X4 F/ D4 x# i
Adjusted rate, 调整率 u: q0 `! @" [# T6 \
Adjusted value, 校正值
$ G. m. V, y# t. J8 BAdmissible error, 容许误差6 m+ \1 O* X3 o" ^
Aggregation, 聚集性$ [( P9 z, y# B8 h# H8 U- ~
Alternative hypothesis, 备择假设
) r- t9 d; b* `# uAmong groups, 组间
+ b. z5 L9 `$ l) Z- xAmounts, 总量
( t/ K/ c- l* ^1 v' l4 dAnalysis of correlation, 相关分析
) x6 a7 |. s# K! K' A/ E6 iAnalysis of covariance, 协方差分析& x( f3 p' c* G% x
Analysis of regression, 回归分析) P3 S' x! @1 z& u! o( \
Analysis of time series, 时间序列分析5 t, M3 e! e4 L& \) T
Analysis of variance, 方差分析# h( C% D2 ]8 K X' \- n) z" |
Angular transformation, 角转换
4 z8 O6 I- r. E M6 Z, k' ]ANOVA (analysis of variance), 方差分析! L. Y* n. p8 D7 I( X q# h( o: U9 M
ANOVA Models, 方差分析模型/ k1 t, r9 w$ V# ^; F3 A. |
Arcing, 弧/弧旋" A" C$ U9 K: L7 T
Arcsine transformation, 反正弦变换
5 n0 R* A# \2 ~1 ~# IArea under the curve, 曲线面积) H, \# c6 P5 P& k: ^, w" Y `, d
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
- i. P/ K' d7 s1 e* q; C! }$ e. W* aARIMA, 季节和非季节性单变量模型的极大似然估计
7 k& Z1 _* S MArithmetic grid paper, 算术格纸( b) \2 U6 e% H( K- L# s
Arithmetic mean, 算术平均数 M8 X* s4 w, t5 Z, b8 S; b
Arrhenius relation, 艾恩尼斯关系& {% w) {8 Y5 I# L* r, I
Assessing fit, 拟合的评估5 |. P9 I' q: D
Associative laws, 结合律
& X r/ ~' Y" NAsymmetric distribution, 非对称分布
. y- k( G3 M9 e0 B% @) Q. l. y1 N+ TAsymptotic bias, 渐近偏倚- S$ `+ t5 ]! u& e) g9 Z4 y: Z
Asymptotic efficiency, 渐近效率3 w/ ]% ^( |+ E: w0 m
Asymptotic variance, 渐近方差
8 @/ B4 D6 ?6 G2 o9 d' c8 @( b. U1 PAttributable risk, 归因危险度
2 P* i( I( Z0 {. H5 D' iAttribute data, 属性资料
( K7 S# g6 X/ L/ }1 P ]& S. B6 n$ qAttribution, 属性
$ ?5 n$ _8 x) p$ S& Z: K RAutocorrelation, 自相关
E! N- c- o5 {2 sAutocorrelation of residuals, 残差的自相关" G! H X1 [( ~
Average, 平均数# n* M7 y: n" L# x3 ^+ H
Average confidence interval length, 平均置信区间长度
1 W0 N! ^ q* j( A1 jAverage growth rate, 平均增长率
0 y* I& Y3 y8 K: J0 |. {! bBar chart, 条形图
# ]3 b0 n7 y4 q* p" ^Bar graph, 条形图( ~* q- I. v# ^* G( D+ p
Base period, 基期
- M- D( m1 j3 }3 lBayes' theorem , Bayes定理" _, T; w _2 V1 N' }
Bell-shaped curve, 钟形曲线3 U7 Y- y% T0 B4 D. e3 w
Bernoulli distribution, 伯努力分布* }& d. q Q# c. j( H0 a! X
Best-trim estimator, 最好切尾估计量* f J: ?" @& F9 d4 ]- K% @$ p% F+ K
Bias, 偏性 ^$ m& A) [! h
Binary logistic regression, 二元逻辑斯蒂回归6 y1 D# m2 l2 A
Binomial distribution, 二项分布2 d& j R2 q! Z4 w0 f1 A" J6 x! X7 `* P9 u
Bisquare, 双平方
5 H+ ^1 f+ ^% F& JBivariate Correlate, 二变量相关$ A* i! C8 [1 U; w7 E* f
Bivariate normal distribution, 双变量正态分布
$ r8 p( L' h% BBivariate normal population, 双变量正态总体+ S9 J! \' q! Z9 }* n1 O5 v
Biweight interval, 双权区间+ x' C2 a4 U% x3 K) L+ n
Biweight M-estimator, 双权M估计量, T3 _4 W# P& u! O( ]4 q
Block, 区组/配伍组
9 F9 m$ S& M: s5 Q: HBMDP(Biomedical computer programs), BMDP统计软件包" X# [* }$ l: }" w* E* s
Boxplots, 箱线图/箱尾图% }, R% g5 u9 {7 |# s* q+ z% U* K
Breakdown bound, 崩溃界/崩溃点
; j( z1 H9 T( H0 OCanonical correlation, 典型相关
$ t' Q1 o: a. KCaption, 纵标目 A1 l" K" L& F7 f) V; @
Case-control study, 病例对照研究
V; z9 m" [9 [/ ?. z* H8 n7 s0 ~7 pCategorical variable, 分类变量
3 r9 [2 V3 u2 f2 k6 a) ~+ K+ |Catenary, 悬链线* N* M8 r4 c, I, r9 a0 f+ b
Cauchy distribution, 柯西分布
; v# x+ u1 f* H5 a6 cCause-and-effect relationship, 因果关系3 f, H: a# I( q6 `& _
Cell, 单元
6 I: K( p; C- c- nCensoring, 终检
3 r f' h7 H' p" j/ {' |- W5 lCenter of symmetry, 对称中心
" P9 X% T: K. n* d# O% @! ICentering and scaling, 中心化和定标. j- t; [0 S, ?1 M
Central tendency, 集中趋势' M: B. G4 n+ c L9 S, Z
Central value, 中心值$ w% w) l6 b8 I; w, `! ^7 T9 Y
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测! N+ z5 n( W- I* r
Chance, 机遇
9 B' q1 W q2 q' QChance error, 随机误差
( n1 \: O3 @0 T5 w' F4 k. NChance variable, 随机变量
1 Z, Z/ J6 s4 P1 N; XCharacteristic equation, 特征方程
7 ]: L) L+ N8 c# A7 aCharacteristic root, 特征根
' n5 X. b4 W4 [Characteristic vector, 特征向量$ _5 W( C! ~3 h- E F# v4 ?0 ?& }
Chebshev criterion of fit, 拟合的切比雪夫准则
& J( [% P0 Y2 j' I" @; [* yChernoff faces, 切尔诺夫脸谱图
j& h* Y3 G, h9 `0 o g; t5 tChi-square test, 卡方检验/χ2检验. T0 b7 ~' S# e( _% C
Choleskey decomposition, 乔洛斯基分解' K, }+ {3 A5 _1 D! x# s0 l
Circle chart, 圆图
: ~3 o0 }4 G3 E* k( G' SClass interval, 组距/ j( h5 z+ m! S9 w8 d4 P
Class mid-value, 组中值4 [# D2 V1 I' `3 v$ L/ H: Z
Class upper limit, 组上限4 a/ U1 V0 t9 |( l
Classified variable, 分类变量) C& P* G; p; L
Cluster analysis, 聚类分析$ [5 v3 Z& I" ? a) B6 q
Cluster sampling, 整群抽样
6 d9 n2 h* {% Y% m0 J% ]Code, 代码
) T+ i* E; D5 u' y0 Y5 u2 o- f' ?Coded data, 编码数据- \) v3 c. L t9 q- [; z
Coding, 编码! A V+ G" J! z: B
Coefficient of contingency, 列联系数
7 h: M7 `3 w. ^3 v p- @; XCoefficient of determination, 决定系数9 L7 e, K( L/ X; h, `, A; d) b
Coefficient of multiple correlation, 多重相关系数' ?8 f$ C! ?0 D2 s5 ^5 w1 N9 S
Coefficient of partial correlation, 偏相关系数
0 ]/ h) R% }6 x) tCoefficient of production-moment correlation, 积差相关系数5 E$ _$ W6 D: W8 ?5 D4 c+ o
Coefficient of rank correlation, 等级相关系数
7 W& g( v: N& S# L3 X+ @" J( wCoefficient of regression, 回归系数
0 q/ A( \* T+ sCoefficient of skewness, 偏度系数5 y$ h+ c: q8 x8 v/ Y
Coefficient of variation, 变异系数
1 q% A4 `. ~- `4 R& `Cohort study, 队列研究
. m9 \! W: t: {Column, 列8 L* ?/ @0 g2 e) e
Column effect, 列效应; M7 [. Q- _, Y/ `) ~, s+ `# p5 H
Column factor, 列因素
! r5 J0 \$ a5 RCombination pool, 合并2 {+ s1 p2 W- T+ \, i/ Z+ z9 R
Combinative table, 组合表! \/ m1 \3 `$ g' y
Common factor, 共性因子, A/ y S* M$ h2 o3 O* Q
Common regression coefficient, 公共回归系数
4 d k$ l0 v- C, }7 ?Common value, 共同值
+ d' g, j; j4 T; qCommon variance, 公共方差" d- z6 l1 O# G5 u0 g1 ?- w
Common variation, 公共变异
' H$ g$ p8 }- \0 y+ yCommunality variance, 共性方差 ^0 ^* F& T- \) q8 v
Comparability, 可比性
0 Z Z: T% n9 c% k* S/ HComparison of bathes, 批比较, E* V9 @* X" B
Comparison value, 比较值
0 h2 P; J; h) Y* @: b7 [8 LCompartment model, 分部模型
0 w n/ H3 v! B1 A0 l8 iCompassion, 伸缩
! h9 |& W8 c: R+ _Complement of an event, 补事件+ G, A: g9 {$ Q( L& w& l
Complete association, 完全正相关8 X0 ~0 ? _# ?6 v0 M o
Complete dissociation, 完全不相关1 X$ k1 q4 Y X) K; b- n) z
Complete statistics, 完备统计量) n# U; r4 S- d( }: m6 D ^
Completely randomized design, 完全随机化设计( f# } ?- L, n/ X+ [( k3 W
Composite event, 联合事件
1 Y9 L2 T$ Y( z1 D* `9 z8 YComposite events, 复合事件
( ?; \" S" p# ~3 `' I& S( W0 nConcavity, 凹性
$ x! }) W0 {5 S0 `/ h% NConditional expectation, 条件期望* {/ \' v5 [5 w8 j# ?$ B
Conditional likelihood, 条件似然8 x. h& O. k6 k- i# o
Conditional probability, 条件概率
( H) w ~$ _4 m. z5 n. UConditionally linear, 依条件线性% c3 o* t: N7 S4 L
Confidence interval, 置信区间2 Q% e: ?: ]/ S/ a9 }
Confidence limit, 置信限
5 a6 A, c0 T7 g2 {: J+ h7 `Confidence lower limit, 置信下限
9 a8 _2 l& |: rConfidence upper limit, 置信上限: t: D9 }; N9 x% d, J
Confirmatory Factor Analysis , 验证性因子分析* K# h0 }" x! [/ }0 o2 [/ v9 `
Confirmatory research, 证实性实验研究) V& y0 U7 H' o* `
Confounding factor, 混杂因素
& W: h$ }* V( r" s& [* j7 m2 X# _! jConjoint, 联合分析
2 |. o. }# m$ IConsistency, 相合性
+ d# F2 k8 j0 V4 E+ @4 e& uConsistency check, 一致性检验
4 B: y) d6 v' C4 {) DConsistent asymptotically normal estimate, 相合渐近正态估计8 y0 x5 e; s3 N: T7 l
Consistent estimate, 相合估计. [, c+ x' f8 V3 f
Constrained nonlinear regression, 受约束非线性回归/ v4 p1 n* D5 J% }+ U
Constraint, 约束# [6 |& Z# s E# `0 m* @' p
Contaminated distribution, 污染分布: F! s$ l, h, u3 `8 U8 G! j. t
Contaminated Gausssian, 污染高斯分布
j# z+ }, @ pContaminated normal distribution, 污染正态分布
! \# c5 |8 n+ A8 N8 }Contamination, 污染: S3 N, u% ]' c: X
Contamination model, 污染模型
1 d: R4 @4 k. e* q' P5 R qContingency table, 列联表
( d# Y& y" K9 v9 o# E) OContour, 边界线
' F& ?% t! \) ?8 OContribution rate, 贡献率1 s8 F; H& P8 C
Control, 对照7 i* Z% q* ]: B$ L* @
Controlled experiments, 对照实验
( {) [. ^$ w5 |; v$ dConventional depth, 常规深度$ o- l8 G3 W' B3 t
Convolution, 卷积# f% U1 P; Y% k$ O/ }
Corrected factor, 校正因子% V% N1 {& V. A) G* F8 J$ o
Corrected mean, 校正均值& ?8 Z& \% K# G4 _5 l
Correction coefficient, 校正系数
4 S' Q( q- y7 m, H/ a" B9 _+ dCorrectness, 正确性
& {5 H+ B1 _* NCorrelation coefficient, 相关系数3 _) i: \0 a. J7 c5 F
Correlation index, 相关指数3 I. [( E8 Y$ L7 ^% v
Correspondence, 对应
8 v; q6 d; A3 oCounting, 计数7 V( N. W$ }1 \( \3 k( Y$ r' f
Counts, 计数/频数
[% W9 B/ A3 i0 E) WCovariance, 协方差
/ |9 h4 `( c5 U6 n8 b" Y' ECovariant, 共变
9 }& P* v- B3 oCox Regression, Cox回归
3 ^ E8 ~! g* H% f+ ]% p3 g6 d5 cCriteria for fitting, 拟合准则; a4 S* {: m% X5 F
Criteria of least squares, 最小二乘准则
! [2 e8 g8 Q0 o8 N% h; R+ _Critical ratio, 临界比: a6 ~( H9 Y- b1 Q- ^" @$ {
Critical region, 拒绝域
1 x1 L0 d) K4 V2 U, B3 ECritical value, 临界值
, W( x2 R! [3 a$ u8 {; k+ i9 O' \ e5 LCross-over design, 交叉设计
9 G0 `" j5 _6 X- C4 z2 ^Cross-section analysis, 横断面分析
' ~2 P- p! d% j. vCross-section survey, 横断面调查
, `0 x) Z/ Q6 I- C: NCrosstabs , 交叉表 / R3 N$ z% q- n, N. Q
Cross-tabulation table, 复合表0 b" @7 j. `, S, u% C
Cube root, 立方根3 g$ Q/ L* r3 G( ~ S
Cumulative distribution function, 分布函数
! J& k! E( R, @/ L1 t, F, D ]; D' ?Cumulative probability, 累计概率. r$ \" ~. ~3 M9 n5 e& q3 T
Curvature, 曲率/弯曲
5 O1 C- z" f/ g5 C; F. N- {Curvature, 曲率
# U6 {* Y6 x- P% ICurve fit , 曲线拟和
& F; D2 |, r4 F9 cCurve fitting, 曲线拟合, m4 ?: a) l* U, b9 V
Curvilinear regression, 曲线回归
y) E4 v! p* y; b5 oCurvilinear relation, 曲线关系
* J( u6 v0 i* I6 P, C/ ZCut-and-try method, 尝试法/ ?8 L5 F. s0 I/ W8 r
Cycle, 周期. [5 J$ V% d5 |
Cyclist, 周期性0 j, Z4 K( b1 ?! N+ S
D test, D检验
' R% b0 B4 n' ]* JData acquisition, 资料收集
" R; e& T- }5 l1 X6 OData bank, 数据库
5 D! {# o a* l3 e* q# L* ?Data capacity, 数据容量$ e- ^* \( u6 v# X+ ~% {+ b& Z
Data deficiencies, 数据缺乏0 T3 q2 N$ q* h' n# u
Data handling, 数据处理
0 `+ X2 J6 d3 _0 h* N6 AData manipulation, 数据处理
. s! r1 M; N$ iData processing, 数据处理0 K2 M$ ]- t) I
Data reduction, 数据缩减
7 P$ z/ ~' e1 U% a y3 PData set, 数据集$ V& ^, {) v3 h7 k7 ]. `' K
Data sources, 数据来源) x3 `4 o) O' f. Q1 h$ J
Data transformation, 数据变换
t! U! k7 K1 O& U$ s, wData validity, 数据有效性
# [# V2 q+ r- o5 z; MData-in, 数据输入4 X {( e' ?& I- M
Data-out, 数据输出
5 a, i. d8 X0 v1 H' uDead time, 停滞期
4 I1 x4 F1 l9 lDegree of freedom, 自由度
3 K5 ?+ t5 K6 ]: o* GDegree of precision, 精密度
& e2 ^1 U8 w) d6 _ F0 ~2 jDegree of reliability, 可靠性程度
# [4 c) \8 c2 Q( v: |Degression, 递减
! L0 {+ R8 Z- ~4 WDensity function, 密度函数0 ]" w! b9 a5 ]2 c, A
Density of data points, 数据点的密度3 y7 u: j& w L- e F' A
Dependent variable, 应变量/依变量/因变量
+ l- q1 S5 F1 |- [) q( DDependent variable, 因变量$ U8 z9 e i0 R& c4 E0 {
Depth, 深度1 H# I2 A" p. R# ^1 B3 z
Derivative matrix, 导数矩阵
# G3 l! X# K3 N* I& fDerivative-free methods, 无导数方法
; Q: _; X- u) J' v" ^3 m* g) ZDesign, 设计
# x! d9 f- G2 J+ D2 Z" G* ADeterminacy, 确定性0 v: ^$ P' F' W U" i9 c$ H
Determinant, 行列式" j; x+ c, g4 f' L+ e
Determinant, 决定因素 g# W2 X6 g; f D& Q6 r7 c+ ^
Deviation, 离差; u) z d1 S4 C$ E; g6 f9 Z* Z
Deviation from average, 离均差
6 Q3 e. z0 X ` e9 g2 {Diagnostic plot, 诊断图# ^' D7 I6 _' ~' M4 T/ g. \
Dichotomous variable, 二分变量$ A/ | P( x$ p
Differential equation, 微分方程
, q* g3 o; q' S& N) I& oDirect standardization, 直接标准化法
2 m, \5 J, ?8 A; nDiscrete variable, 离散型变量4 ? \7 b+ u2 P. S
DISCRIMINANT, 判断 # ` e' R* ^) x9 E( Y ^# A7 Q
Discriminant analysis, 判别分析/ o% u' B& G9 s
Discriminant coefficient, 判别系数
. f$ c' ]; o3 C" h1 l7 @8 ADiscriminant function, 判别值
9 p$ f- K9 G" zDispersion, 散布/分散度% V) r1 _& \) T e
Disproportional, 不成比例的6 n3 T) h. I R2 M' S7 ^
Disproportionate sub-class numbers, 不成比例次级组含量0 B' D. T: g O' i! Z) ?- q
Distribution free, 分布无关性/免分布
3 a" x2 X2 ^* Z5 v( ?' c' LDistribution shape, 分布形状
1 b& h! Q5 j3 cDistribution-free method, 任意分布法
% s5 I2 o) V a& y8 s$ C6 \Distributive laws, 分配律
$ z5 Z3 |. o2 x; ~9 q# ?9 a4 HDisturbance, 随机扰动项
5 n. Q5 _$ V6 U& d/ `/ GDose response curve, 剂量反应曲线4 U- |: h. q' _3 l9 l$ k
Double blind method, 双盲法 I) ~. M$ i. h) j
Double blind trial, 双盲试验
/ F9 K$ G& W: oDouble exponential distribution, 双指数分布7 J* z9 t$ l. E2 a
Double logarithmic, 双对数- h/ n1 A2 E% {: N: O
Downward rank, 降秩
1 |4 A& ~1 l& cDual-space plot, 对偶空间图
6 g( q1 K! m# aDUD, 无导数方法( {% X" \( ]: r- k2 B2 }
Duncan's new multiple range method, 新复极差法/Duncan新法) u/ A/ u( O( i+ F3 T) ?& D3 I
Effect, 实验效应
/ S! D( B1 {, L6 g( h$ sEigenvalue, 特征值) N& b, F3 s5 m
Eigenvector, 特征向量
C$ f4 o* n& ]9 g8 sEllipse, 椭圆
! F6 B) C) f* e1 T% ~: I9 AEmpirical distribution, 经验分布
1 B" ^0 J; o8 m: mEmpirical probability, 经验概率单位% R- g% `' ~6 s9 z
Enumeration data, 计数资料
4 p+ v# K5 q" sEqual sun-class number, 相等次级组含量
1 b, e1 ]7 e* N# K* nEqually likely, 等可能9 i9 g* |9 L2 Q8 v
Equivariance, 同变性+ B7 c) v" R4 Z) v9 B* \% W
Error, 误差/错误
% ~) D j b: o; I' D, T# dError of estimate, 估计误差6 o) d) C8 E) \+ M3 y8 R
Error type I, 第一类错误
0 \# b0 N9 n0 ]7 z( b* y8 k2 xError type II, 第二类错误( o" [& n, Z, j6 @: }- w$ G
Estimand, 被估量7 w' L& M$ Z, V5 x" M
Estimated error mean squares, 估计误差均方; G' U7 _7 W( K- ~* Y
Estimated error sum of squares, 估计误差平方和+ h8 ^. v% t8 u! _
Euclidean distance, 欧式距离. e# Y$ [6 ]. C7 Q, a. H m
Event, 事件) @& ^% ?7 K8 T1 L0 p
Event, 事件3 ~4 E+ }+ D- }( u. d5 J! C, A
Exceptional data point, 异常数据点1 X1 h( \0 X, H- q1 a7 a0 S
Expectation plane, 期望平面% W8 c/ r/ K4 D$ f& _0 G7 }$ j- i
Expectation surface, 期望曲面3 K7 ~' ?7 z3 L" Y& t+ u
Expected values, 期望值: \* J& [! A* m; D0 N3 F
Experiment, 实验8 F+ D4 w% V# W! d
Experimental sampling, 试验抽样
. u" h- B' X8 q* L% Y9 I7 `Experimental unit, 试验单位
; h. V H0 L. {7 f5 H! W7 hExplanatory variable, 说明变量
" T# b, c3 {2 C3 gExploratory data analysis, 探索性数据分析
( U6 Q6 e5 z" |! ]( S* E, ~0 m5 nExplore Summarize, 探索-摘要
$ I8 S: O# _) d( S" `$ BExponential curve, 指数曲线
0 J& n$ r$ k- W6 A4 l/ Q9 X: W! V" m9 uExponential growth, 指数式增长
7 T. A, z% M8 v7 v: B$ Z9 ], yEXSMOOTH, 指数平滑方法
6 _4 t4 v: {5 I, w) }2 KExtended fit, 扩充拟合
: j* d# b, `6 N5 SExtra parameter, 附加参数
& k# y- F$ m) W y" V" h2 pExtrapolation, 外推法2 |& n! T2 |+ ^0 k
Extreme observation, 末端观测值
4 J: t" F. I0 K7 B/ HExtremes, 极端值/极值
! u+ d- Y8 A4 I8 Y. [F distribution, F分布% g9 c1 |3 z- n9 W9 d+ Q
F test, F检验
4 ~3 N% U. j4 G( {, _Factor, 因素/因子 s. @( A' _2 f/ H
Factor analysis, 因子分析
: d8 Y8 k, x6 V5 P2 X, [7 {Factor Analysis, 因子分析
/ e% O" E/ B2 b0 S# VFactor score, 因子得分 3 Y8 V) {* `5 @( Y
Factorial, 阶乘5 K: K, q. F0 I3 @5 M X' T
Factorial design, 析因试验设计/ B( I; g6 ]/ P, x8 p
False negative, 假阴性4 N& n% [& `) ~9 ]1 f3 H# y( b
False negative error, 假阴性错误( M# w2 s9 X8 `; X& p# A
Family of distributions, 分布族
" m1 o& V$ }% E0 k) B6 g$ ZFamily of estimators, 估计量族, b# g4 d) \3 r, ?5 h
Fanning, 扇面& |2 { c) G8 r% Z
Fatality rate, 病死率
- I. _' \* j; g8 M( _Field investigation, 现场调查. O) n) x" W0 R+ A. [! ^
Field survey, 现场调查
$ B4 m! l- `& R r, r% eFinite population, 有限总体2 q2 ?) x6 w$ Z) N0 `6 u
Finite-sample, 有限样本
& S6 v r' a5 U! aFirst derivative, 一阶导数/ o- N! o! l M# L# b
First principal component, 第一主成分 F4 ]$ g& w0 s- S5 ^
First quartile, 第一四分位数
# b# x; e9 O+ d* i/ `( G- ]Fisher information, 费雪信息量/ T" `% p' V0 v5 _: ? d
Fitted value, 拟合值5 p; G2 B2 b4 N* I, d2 Z( k; c
Fitting a curve, 曲线拟合
6 e, b2 M* J! F% t" \3 A3 G0 aFixed base, 定基
3 q% r. p# X. HFluctuation, 随机起伏
, s9 e' F0 N: fForecast, 预测# G/ k n( y5 G4 p
Four fold table, 四格表
1 J2 R, U8 [% F/ l. F: j" ~9 OFourth, 四分点+ H$ r2 l+ a5 ]' V; ~9 J) F: g! C
Fraction blow, 左侧比率
2 ]- @* {# \; |6 b# |6 \. zFractional error, 相对误差
3 N F6 X7 X6 A- M I; }; }Frequency, 频率2 N. i; V6 {; o( q
Frequency polygon, 频数多边图. g5 ?) S) ~2 y2 E
Frontier point, 界限点! C$ @% c4 S# |5 U" h! s
Function relationship, 泛函关系( R* m, [! ^' B4 U, H3 c9 S: }
Gamma distribution, 伽玛分布
9 q. F9 @2 H$ @1 O, o3 TGauss increment, 高斯增量. a+ n2 ?; Z e" O3 X' f
Gaussian distribution, 高斯分布/正态分布: `' I' E8 |5 o. c: A1 ?
Gauss-Newton increment, 高斯-牛顿增量3 m1 R$ a7 X) ?) F
General census, 全面普查
3 O3 v% c5 X: a# u- tGENLOG (Generalized liner models), 广义线性模型
Q" N4 Y- J+ S3 r# xGeometric mean, 几何平均数
2 l1 f, k& ?8 [& q) |' ~! o$ V* JGini's mean difference, 基尼均差
/ N! T7 d U2 g% r( }GLM (General liner models), 一般线性模型 3 N1 o$ H% N6 C, ]. ^( r8 c$ h g! }
Goodness of fit, 拟和优度/配合度! w, \1 A' c( l/ P" p! H$ ~
Gradient of determinant, 行列式的梯度: y6 b, x) \( @/ k" f) g
Graeco-Latin square, 希腊拉丁方
1 [" ]& C- J1 @ P6 x% k( RGrand mean, 总均值4 F1 g9 p* N; ]$ Y% ~1 u
Gross errors, 重大错误
% L, I7 |+ k% {9 f) eGross-error sensitivity, 大错敏感度- ?# N' R3 l" Q$ R6 ~# _7 f' \
Group averages, 分组平均
) C% v9 L% a# C/ i1 pGrouped data, 分组资料) _6 y7 {+ R2 Q$ ]# g3 j
Guessed mean, 假定平均数
1 Z1 L4 V X# a" b5 @- z: O! YHalf-life, 半衰期. \0 b: N5 ^7 k
Hampel M-estimators, 汉佩尔M估计量 h2 V& q8 [/ _# O
Happenstance, 偶然事件; W7 i8 k. M8 g! M
Harmonic mean, 调和均数1 w, j5 g! l% F% m* p
Hazard function, 风险均数
0 k2 _% k4 i& }. {: oHazard rate, 风险率- _2 ~" O0 C8 Z
Heading, 标目 3 Z" r: n5 O8 d7 t7 G4 K) j
Heavy-tailed distribution, 重尾分布
- e$ V& j- R+ X& o& y' |5 lHessian array, 海森立体阵6 `) v5 D& P) q! N! I
Heterogeneity, 不同质3 v# \# t1 G4 ] ?
Heterogeneity of variance, 方差不齐 5 K& @- ?+ X1 e* X
Hierarchical classification, 组内分组
- A/ l( t, b& Q5 z9 rHierarchical clustering method, 系统聚类法
9 B p, O/ B- v& x" O- sHigh-leverage point, 高杠杆率点3 T$ W: |8 t' U. z( U, k- b) J
HILOGLINEAR, 多维列联表的层次对数线性模型
- f1 ?/ O3 @8 w0 m. o# S2 y2 R0 JHinge, 折叶点
; Q( `4 N* l( T( O# c6 SHistogram, 直方图1 ^) I! E# C7 x; q( {
Historical cohort study, 历史性队列研究
6 n0 E% ~1 ~ Q* N6 ]Holes, 空洞
. u5 c# I8 M( U0 b0 }3 O6 _HOMALS, 多重响应分析8 p) I: A0 \( O
Homogeneity of variance, 方差齐性
; r+ h6 B& T4 K( VHomogeneity test, 齐性检验/ y; I3 }" n p7 e& p
Huber M-estimators, 休伯M估计量, I% H2 C. F" V+ ^
Hyperbola, 双曲线, n. m5 t5 n! h
Hypothesis testing, 假设检验% N: _& @" t+ k- `4 H
Hypothetical universe, 假设总体
8 @3 O/ W/ v' G9 y4 oImpossible event, 不可能事件
- b: M- m1 F: {; l. a3 _; sIndependence, 独立性
/ C! F+ A% j3 @7 s' i4 ]" t: JIndependent variable, 自变量2 l, h; t/ [% W; z: Y$ V
Index, 指标/指数
D3 v2 g# d3 V% Q4 KIndirect standardization, 间接标准化法
& P/ n8 f$ {( d; n3 L$ `Individual, 个体
$ I( ~' z& }. `. Z# wInference band, 推断带
/ S) f/ p1 }2 E* A' X R( GInfinite population, 无限总体; J2 z0 O& @ f- D: {. m* ^2 R8 v
Infinitely great, 无穷大
, j- T6 k' `* M( X+ O3 s2 p7 j8 A0 ?Infinitely small, 无穷小* s2 X# |) v. {9 k2 a6 O6 w
Influence curve, 影响曲线! T$ I0 S( L* \: _5 w2 f: b% Y
Information capacity, 信息容量
9 v4 I+ @3 S/ ? L# y" m5 EInitial condition, 初始条件
) W' w8 X: k+ f2 \Initial estimate, 初始估计值
2 L7 g" o! T' v% E8 r' o0 ~ HInitial level, 最初水平% s- }0 y2 o+ i% K9 m7 \0 z
Interaction, 交互作用
$ U) q& \3 Z: s6 Z) mInteraction terms, 交互作用项- X& f: R2 A5 w& Q! A
Intercept, 截距% ?9 s% O Y0 ^# N; }
Interpolation, 内插法
$ E P/ U+ i5 j+ W) V0 D2 C) h, HInterquartile range, 四分位距
3 O; j# O( D, L |! H* `/ LInterval estimation, 区间估计' E4 T$ M2 b% n7 T
Intervals of equal probability, 等概率区间4 j5 b8 j1 V$ r! E5 J+ b! k
Intrinsic curvature, 固有曲率
" K k! Y0 p' h+ }+ V% J0 fInvariance, 不变性
, n# y# C4 n* R, qInverse matrix, 逆矩阵
7 _) e- S: j; I/ f3 G+ b9 oInverse probability, 逆概率) i; B5 @# @' w
Inverse sine transformation, 反正弦变换( h5 w, y4 f5 s/ `4 o) E9 b. X
Iteration, 迭代
# |/ D* V1 [) z8 \Jacobian determinant, 雅可比行列式2 w$ t* W$ R3 o8 E, |$ q9 g% D5 C
Joint distribution function, 分布函数" `" t4 L) k9 E3 N3 l' V3 y
Joint probability, 联合概率
2 P: P! e% Z5 V( }Joint probability distribution, 联合概率分布; T# N8 J6 r9 W8 Z
K means method, 逐步聚类法
/ ?# ?) D+ B7 h/ \; j6 n* T* ]4 B. d, TKaplan-Meier, 评估事件的时间长度
( P% o% X7 U9 l! i6 VKaplan-Merier chart, Kaplan-Merier图- ~1 |; w% u- H+ r: y
Kendall's rank correlation, Kendall等级相关" `" \. p1 \# G7 I
Kinetic, 动力学, B8 ~) R2 ^/ E! I0 H
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
2 e7 s, g5 \( |: ?. PKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
2 @# R: o& R# s1 P! @Kurtosis, 峰度' z, B9 V1 H7 D
Lack of fit, 失拟4 i; V8 L7 |' P( U3 d4 Y0 ~- w. w
Ladder of powers, 幂阶梯4 b- d7 x/ T+ X
Lag, 滞后6 n: d: v$ v, i: X1 e
Large sample, 大样本! q, ?8 m, H3 M' G! B4 G% F B
Large sample test, 大样本检验
; u: B1 P& Z* Y7 oLatin square, 拉丁方$ l q+ ]7 N9 w2 ~/ M! w7 `+ q0 Y0 P
Latin square design, 拉丁方设计# i% V' F+ C/ M7 K q# t# p! Q: ?' ~0 W
Leakage, 泄漏* r' t( o: c0 C S5 \8 f
Least favorable configuration, 最不利构形
; [1 w. N. X$ o' TLeast favorable distribution, 最不利分布
# \( V7 @! Y/ WLeast significant difference, 最小显著差法
+ x, \. ^9 j# \0 h) \' b+ v" A. i6 KLeast square method, 最小二乘法
) z5 w4 [# O( ~1 ?! l5 l' p" \; KLeast-absolute-residuals estimates, 最小绝对残差估计
; q, M0 C0 P) {0 p2 hLeast-absolute-residuals fit, 最小绝对残差拟合% {% P& j$ m" N( Y
Least-absolute-residuals line, 最小绝对残差线: d" C# f1 J1 x+ @- o# ^. _
Legend, 图例7 L0 K4 @+ X, D
L-estimator, L估计量3 O$ m; `$ w0 e$ o
L-estimator of location, 位置L估计量
" D) m7 L* @& JL-estimator of scale, 尺度L估计量: ~& x% A' i6 i
Level, 水平% a) G6 D! o8 Y% d) V' c
Life expectance, 预期期望寿命$ w6 I' A' i1 W F+ n5 `; N6 D
Life table, 寿命表
% F1 a, E- w1 ?, Z: I; _Life table method, 生命表法2 O' p2 ]0 Z6 [9 j
Light-tailed distribution, 轻尾分布7 N' }7 y4 x5 d$ i
Likelihood function, 似然函数1 U! \8 n* p1 ^. l
Likelihood ratio, 似然比0 o/ H" @6 L( ^2 `8 i4 g2 O& {
line graph, 线图! r. Y4 y& ^& b& y1 q9 n) I# B
Linear correlation, 直线相关" _9 B' x+ b0 t* k
Linear equation, 线性方程
% u) x6 r/ b' h, U/ iLinear programming, 线性规划' K% x% A+ |6 s: v9 M
Linear regression, 直线回归
( g6 v* D2 B9 hLinear Regression, 线性回归6 u) G4 t9 s5 K" R
Linear trend, 线性趋势
, i' ~9 I" I! `- Z4 A8 BLoading, 载荷 ; h( }" C7 X6 c
Location and scale equivariance, 位置尺度同变性$ s$ I8 t& W' y# C0 P
Location equivariance, 位置同变性% D2 {* H* C& D
Location invariance, 位置不变性1 t7 t- k' f6 |$ X- i& q& c
Location scale family, 位置尺度族
4 R; ]& |, u# k- P- Q" V" C9 J) RLog rank test, 时序检验 3 A7 P; H8 c- _
Logarithmic curve, 对数曲线0 j0 }0 C6 o9 [& M& {0 N. s; k
Logarithmic normal distribution, 对数正态分布
* g: [) q( D# c4 C! a" }7 r# W% w' rLogarithmic scale, 对数尺度
) b. P# ~% m& ~, Q9 Z/ Y2 i/ hLogarithmic transformation, 对数变换& J- ?& \* h" g- s7 D
Logic check, 逻辑检查* x3 F/ }' ~9 M$ C& m8 h
Logistic distribution, 逻辑斯特分布% P; |3 ?6 i% v9 M1 T
Logit transformation, Logit转换( |6 w- o) h) \
LOGLINEAR, 多维列联表通用模型
( w0 i. L# _; \$ L, J' cLognormal distribution, 对数正态分布2 ]* [# d+ S0 ]! D
Lost function, 损失函数
& X# O4 P7 { Y1 M2 @0 a8 ELow correlation, 低度相关' z& E) Y/ Y% `
Lower limit, 下限2 M8 {3 a4 ~( R2 E' l
Lowest-attained variance, 最小可达方差4 s8 u, ^0 P) c9 W
LSD, 最小显著差法的简称- E; c# ~/ w% r: ~! V
Lurking variable, 潜在变量 d+ y9 L" @: z$ g
Main effect, 主效应5 P; D* ?; }$ ^% i% C# Y
Major heading, 主辞标目0 ]) i+ |9 w$ n- ^$ G
Marginal density function, 边缘密度函数' u( r6 a" t" L" s4 ^
Marginal probability, 边缘概率- |% H m# Q: D. V
Marginal probability distribution, 边缘概率分布
2 W) [# u) ^3 wMatched data, 配对资料4 e% m# b4 A+ H$ T# w2 | G
Matched distribution, 匹配过分布0 z- F6 x+ G* U/ B$ D, C! z
Matching of distribution, 分布的匹配3 R5 E1 |9 I9 S% \- n4 g' ?# U
Matching of transformation, 变换的匹配: X/ O, f( t; e" w; Y; v3 p: I2 U* l
Mathematical expectation, 数学期望
; h" r$ q. q9 A0 m3 u- G, XMathematical model, 数学模型5 b- C) S& K2 Q3 `" T
Maximum L-estimator, 极大极小L 估计量" r: p! P: b) Q0 b0 x$ j) [ ?
Maximum likelihood method, 最大似然法
# v* J: ` s) d. B6 L- QMean, 均数1 `* {! X$ C) Z( S
Mean squares between groups, 组间均方, J ^2 A3 _/ F8 c: \; [
Mean squares within group, 组内均方
5 Y t, f I! R# M9 @Means (Compare means), 均值-均值比较+ j4 ^) A! P$ |7 n0 R6 d* y4 G
Median, 中位数* i [) }" }4 A0 J5 g# H8 x9 V
Median effective dose, 半数效量+ _3 c# ?3 u: a! z: L
Median lethal dose, 半数致死量1 J" ~: V& C: }: z* g7 f
Median polish, 中位数平滑2 i% V$ A( K' n. T5 g; z8 `
Median test, 中位数检验
A; t6 u6 i1 I" _Minimal sufficient statistic, 最小充分统计量
$ {0 g) o, [% t' I% |& YMinimum distance estimation, 最小距离估计) k: `0 q2 c( F% s
Minimum effective dose, 最小有效量2 v$ E7 G2 H3 }
Minimum lethal dose, 最小致死量- c1 v# E1 U: L
Minimum variance estimator, 最小方差估计量, E; p& h8 s9 Q$ a4 z- S
MINITAB, 统计软件包
9 S7 ^ T6 ?: p6 i$ L+ Q3 ^7 pMinor heading, 宾词标目
& l# E* @8 n3 Y7 Y9 E9 ]# L# `Missing data, 缺失值, |4 H+ c8 O- K S
Model specification, 模型的确定
) B8 r) c) { [! u8 c0 |0 TModeling Statistics , 模型统计" M F& l& z; M8 J. u( @
Models for outliers, 离群值模型
2 h4 @* N! d1 [+ h7 z+ vModifying the model, 模型的修正
" D$ k8 i7 o6 \+ S+ d1 EModulus of continuity, 连续性模
2 f* K* c& N* t- q6 @. T' ]Morbidity, 发病率
# w! X, f6 I2 gMost favorable configuration, 最有利构形
, Q% z6 Y+ J3 ^+ M6 CMultidimensional Scaling (ASCAL), 多维尺度/多维标度8 D0 V9 [2 M) k7 @( s. x2 [. O5 {3 j2 U
Multinomial Logistic Regression , 多项逻辑斯蒂回归
$ ]6 p7 K; F# JMultiple comparison, 多重比较; c9 Y! j$ ^) {9 t
Multiple correlation , 复相关. j& G2 A8 c9 {. \ a
Multiple covariance, 多元协方差
, {" L% q5 r9 ~Multiple linear regression, 多元线性回归- A) f5 {3 g- E( Q0 o
Multiple response , 多重选项
$ s# d! t3 S( v; {: S5 N2 DMultiple solutions, 多解* S4 i; o" {8 y0 Z5 L& h' D4 N/ }
Multiplication theorem, 乘法定理
' O& P# q% y" a; b% s0 `Multiresponse, 多元响应1 W0 d$ i1 ^5 E2 {+ Y& i
Multi-stage sampling, 多阶段抽样8 F9 q- ?2 r9 Q% i4 u( M/ j- b0 `
Multivariate T distribution, 多元T分布
; F# c5 [3 Y7 v1 W: gMutual exclusive, 互不相容
8 `) ^& I4 U4 {- {. `Mutual independence, 互相独立
8 `5 D! O8 t, D, f# ZNatural boundary, 自然边界
& E4 L' ]* w! ?5 e; j! n' D- ANatural dead, 自然死亡8 O, T! ~# r5 h% [
Natural zero, 自然零
5 n. E6 C# [, |& N. O& {0 z# vNegative correlation, 负相关
1 o, ~ Y) C4 @' W( b. A( ONegative linear correlation, 负线性相关0 J+ B* l+ v; W0 t
Negatively skewed, 负偏4 V9 s; M {( C% V
Newman-Keuls method, q检验: f: d/ _* O7 B3 n2 ]3 G3 _+ l
NK method, q检验
" R& M$ @/ R1 n9 C3 @No statistical significance, 无统计意义 `; b0 \& F) [5 W3 t& y; R( t, L
Nominal variable, 名义变量# |) b+ \) ]$ |1 K- J. u
Nonconstancy of variability, 变异的非定常性
. X9 V- U! C7 W# x. ONonlinear regression, 非线性相关
; W# N$ U, `) N1 T# CNonparametric statistics, 非参数统计4 e6 z7 i% K8 G+ H* I
Nonparametric test, 非参数检验
1 D- c0 k- B' F( K% VNonparametric tests, 非参数检验
0 U, X7 a! D3 P5 }% L( y+ ENormal deviate, 正态离差
$ E7 S/ X# ^$ H1 @Normal distribution, 正态分布* U) V9 G! G7 C. ]- W" D
Normal equation, 正规方程组4 a& M/ [7 z( C
Normal ranges, 正常范围
% U) {7 o1 K; ]# K$ i. H" UNormal value, 正常值, l: z; Y" a$ Z% W' p
Nuisance parameter, 多余参数/讨厌参数7 V Q& P; I# H+ E" w
Null hypothesis, 无效假设
4 R6 r6 ^% r3 U6 t# m% xNumerical variable, 数值变量9 w4 U9 M, E# ?* p' a, K
Objective function, 目标函数 @, q, }4 o; e5 P- E
Observation unit, 观察单位
- {/ h, ] P! f6 q% L9 ~Observed value, 观察值3 s& `: Y4 E; a9 i$ o9 Z
One sided test, 单侧检验
# D _$ E8 U0 Z2 J6 BOne-way analysis of variance, 单因素方差分析 p, }4 m1 }5 s% }3 i3 s
Oneway ANOVA , 单因素方差分析/ B3 l# T5 V1 X! w5 Z
Open sequential trial, 开放型序贯设计( A3 g: u: [0 r' t' h1 [* P
Optrim, 优切尾
# P3 T, \: ~- p8 r1 m& l COptrim efficiency, 优切尾效率
5 R+ |4 t. U' I2 U, m. b# zOrder statistics, 顺序统计量
5 ?3 f, T% d& S% kOrdered categories, 有序分类
' ?- N, l/ T( k7 I5 I, r4 lOrdinal logistic regression , 序数逻辑斯蒂回归
, j4 v6 Y" N- gOrdinal variable, 有序变量9 v. A$ v% f/ g% R# G6 D; O
Orthogonal basis, 正交基0 G3 A6 a/ ^6 k( t6 S9 a
Orthogonal design, 正交试验设计
8 G8 {. b1 F# IOrthogonality conditions, 正交条件
9 N, E9 U. g0 V ?- X: b/ iORTHOPLAN, 正交设计
9 D4 f) k! I" b pOutlier cutoffs, 离群值截断点4 _9 `! G/ O3 Z' o
Outliers, 极端值
7 _( w& g7 B$ s; gOVERALS , 多组变量的非线性正规相关
- B2 O- K9 Y1 x# BOvershoot, 迭代过度
4 G& \' z" S1 B& A1 V# hPaired design, 配对设计
$ c6 h+ W" h7 I3 bPaired sample, 配对样本' W% L; O' O6 }$ T
Pairwise slopes, 成对斜率
. Y# t8 h+ K2 `2 V! E# t: yParabola, 抛物线6 w; |, L8 v$ o9 R h5 R1 ^
Parallel tests, 平行试验8 \2 G* m) E: G, H1 Z
Parameter, 参数
- p( t6 Z0 Z* o; k0 L6 IParametric statistics, 参数统计/ {0 i* d: K/ j; L
Parametric test, 参数检验
: t; y/ J+ z2 p4 q% g; m6 s$ a: JPartial correlation, 偏相关
+ R& l$ q1 f+ e4 ~( V& bPartial regression, 偏回归- B, j% Z3 f2 k3 e
Partial sorting, 偏排序
' N) Z2 v6 h' n! g- rPartials residuals, 偏残差
0 f. v2 Y: W5 b/ q( I- vPattern, 模式
( \- B) w( H+ k) _+ @, lPearson curves, 皮尔逊曲线4 u! R4 J. j. Z3 r4 s \$ l; j6 _
Peeling, 退层1 C1 q/ ^- i% h3 b6 ]; h2 N4 h
Percent bar graph, 百分条形图9 G- {/ n9 r% K9 i
Percentage, 百分比4 ^9 I8 s8 T) Z' L+ y9 b
Percentile, 百分位数
3 ]1 S) {: y# j: J) Y9 c9 pPercentile curves, 百分位曲线
: _- Q6 \. s5 b4 b1 {Periodicity, 周期性
% a7 d7 B7 d. w$ P( m3 V" P6 f- _Permutation, 排列! J3 X+ C% ]4 C) T/ U
P-estimator, P估计量
/ h5 B2 z+ N3 c8 t0 F$ WPie graph, 饼图. d! t1 E& Z3 ~/ `
Pitman estimator, 皮特曼估计量. ?; q+ \3 F' b' J: o3 i
Pivot, 枢轴量9 g; i- S3 i" N
Planar, 平坦/ h# I0 @% y) ]( T+ H
Planar assumption, 平面的假设1 R7 ^( x7 C& |) [0 J/ h- w* i
PLANCARDS, 生成试验的计划卡+ D( f+ I7 ^. j6 L2 j* l; ^
Point estimation, 点估计
. @( {6 j0 D- t A: t2 z6 X" ~ G3 W- iPoisson distribution, 泊松分布: _8 C6 e: k( A, i
Polishing, 平滑
& b! r1 b! o2 w: `# oPolled standard deviation, 合并标准差8 F+ D+ Z0 R0 u+ F
Polled variance, 合并方差
1 g8 n& L8 N( m) ~3 |/ ` Z, u( xPolygon, 多边图
: c4 v6 N& i( K% Q6 ?Polynomial, 多项式5 B( x" T) N9 O9 x
Polynomial curve, 多项式曲线4 u% E# u% q M j
Population, 总体
" [2 Y/ V- l0 p/ X o6 m0 TPopulation attributable risk, 人群归因危险度
+ Z$ n2 b" u" F" XPositive correlation, 正相关
, u1 w2 Q+ q1 B7 V f$ l, NPositively skewed, 正偏
+ g( D5 a5 O8 JPosterior distribution, 后验分布, Y/ p) L5 r& R: f! p8 W& e1 ^* f
Power of a test, 检验效能
X' s6 O w. a( {Precision, 精密度) O! w* L6 A; b8 z0 [( y8 _7 e2 q
Predicted value, 预测值) ^& b' C: U% g: a7 }* E
Preliminary analysis, 预备性分析
( Q- w9 o h; a4 c, aPrincipal component analysis, 主成分分析, ?; d& V! l: B& w
Prior distribution, 先验分布
2 Z3 n8 o& I3 M$ t2 rPrior probability, 先验概率
: f* v/ h. _) Y( W7 R# Y' xProbabilistic model, 概率模型
$ Q) @3 _& z$ x4 K0 s! ]9 u( o" \probability, 概率: O# Q7 X' u9 o) Y9 c
Probability density, 概率密度
" {/ G; e" B6 B ?5 I: o7 XProduct moment, 乘积矩/协方差
7 c5 z% X- q9 U4 v$ VProfile trace, 截面迹图
* U3 o: G' A; X8 s9 A3 Z+ CProportion, 比/构成比6 U( H+ G; `" Y" W4 @6 q: I1 `# r J
Proportion allocation in stratified random sampling, 按比例分层随机抽样/ ]( J S( P# I. f4 r$ b
Proportionate, 成比例
0 t2 ~+ J5 B4 s4 [Proportionate sub-class numbers, 成比例次级组含量3 L, w: C9 O, Q- z
Prospective study, 前瞻性调查4 G) ^# _7 @" j
Proximities, 亲近性
5 ^ L) {2 \* _( UPseudo F test, 近似F检验8 `" q' B- F' r& s" e
Pseudo model, 近似模型
7 a* [7 j6 H5 @1 `; {% rPseudosigma, 伪标准差$ ]& V ~' m9 \6 Z7 R9 b' C: _4 i5 Y
Purposive sampling, 有目的抽样
& P6 m, b1 s* ~! a5 X _QR decomposition, QR分解$ j0 P- X, U: X
Quadratic approximation, 二次近似1 q- r; F; ^" k0 u# g- r( x6 W
Qualitative classification, 属性分类
% p" ~6 b9 c; t# ^. w: M, KQualitative method, 定性方法
/ Y( k/ J* B# o# @Quantile-quantile plot, 分位数-分位数图/Q-Q图
1 ]# F. V2 V! Z6 x7 eQuantitative analysis, 定量分析( [ o$ n9 |! n2 F: |
Quartile, 四分位数2 E6 B: J0 _$ I* A
Quick Cluster, 快速聚类4 G& f+ ]( I* ]8 _$ U5 v$ j0 p
Radix sort, 基数排序, g- A: q7 y: R
Random allocation, 随机化分组" m: v9 @6 ]* g d
Random blocks design, 随机区组设计& v) T; r6 v: f* T% w/ T" {
Random event, 随机事件/ n5 m% Z3 F! l7 `! p( P
Randomization, 随机化* r+ t+ c! v. h$ H
Range, 极差/全距
e7 E% C' t; S l/ A. g7 D3 [Rank correlation, 等级相关0 O9 f6 G, d% U7 d
Rank sum test, 秩和检验. u6 N* u8 N5 k+ M
Rank test, 秩检验' t1 Y& ?( p5 R. u& y6 m& G, s" I! R
Ranked data, 等级资料7 q0 o3 W4 k7 @8 V3 d) |# F
Rate, 比率
# o( s6 v/ c; R$ a1 f; @+ d5 }/ XRatio, 比例
1 d- T5 T/ D" g1 a8 Z& HRaw data, 原始资料
; p6 X! d. K1 ERaw residual, 原始残差
+ h, ^2 J2 T% w0 ^Rayleigh's test, 雷氏检验
* m: h( X9 H @! j7 ]Rayleigh's Z, 雷氏Z值 ' h( v% f" z7 c8 b
Reciprocal, 倒数
! x! |& [1 p4 RReciprocal transformation, 倒数变换& m! Z$ Y7 n% i- b
Recording, 记录
4 h3 m. p9 Q Q6 s' \' WRedescending estimators, 回降估计量
. ]) P" o0 L: b! G" _Reducing dimensions, 降维; J" }; L1 l" j# V& b# V
Re-expression, 重新表达0 ?6 T3 X% P6 { i$ D% X
Reference set, 标准组' v' N" A% G' j7 J; Z& \# X) f
Region of acceptance, 接受域0 b2 a% Z( v( R, p( A3 b
Regression coefficient, 回归系数
4 @* e$ P6 e6 J3 o& d& aRegression sum of square, 回归平方和7 g8 M9 c1 X; }5 M i3 w
Rejection point, 拒绝点, G2 p$ R! l+ I. r
Relative dispersion, 相对离散度
0 h1 c4 A0 e5 KRelative number, 相对数* g. A( c* w: U7 A' @; t" P
Reliability, 可靠性1 c4 w' V3 H( b' H6 F
Reparametrization, 重新设置参数' o1 y; `: J3 R* N1 D
Replication, 重复7 S0 Y$ R. J) j9 q- o9 ] j6 ?
Report Summaries, 报告摘要. P' n4 f0 m" t' a5 j5 v9 ~, _
Residual sum of square, 剩余平方和
% k" E6 p' l4 Y5 p% h2 j( bResistance, 耐抗性
4 P! r p6 s8 K$ A3 ^' M G# MResistant line, 耐抗线
& S& W4 { p& wResistant technique, 耐抗技术3 y7 r. K) i. O4 j
R-estimator of location, 位置R估计量 R1 _$ E6 T4 H ?4 G. L" ^
R-estimator of scale, 尺度R估计量1 z( s3 j! V4 v4 X1 g4 Z' ]
Retrospective study, 回顾性调查
% N" e% T; O c! iRidge trace, 岭迹
& |/ i7 B$ t6 g: I3 ?' SRidit analysis, Ridit分析3 ^1 r/ i% c5 f8 I
Rotation, 旋转1 B2 v0 c! b1 P, g
Rounding, 舍入
: I- {, G% y% m/ I- l/ URow, 行
7 K4 [# B2 B7 q M; L: URow effects, 行效应( X2 D4 K U4 Z0 [# Y+ `
Row factor, 行因素# P3 o* w" T3 C$ a, u) m; J
RXC table, RXC表6 Q. S( o9 u1 e# ?3 s
Sample, 样本3 ?8 N) s9 N; m! K' [
Sample regression coefficient, 样本回归系数0 r( E3 A( |3 W0 r4 T+ G
Sample size, 样本量
* n( q) F1 x5 A `! K5 ]1 y9 e7 ~Sample standard deviation, 样本标准差
- m# @3 \1 V W: ISampling error, 抽样误差, q# {, x: A. j
SAS(Statistical analysis system ), SAS统计软件包: }6 p1 T( L. v: [+ u
Scale, 尺度/量表
7 _, W& i0 v1 FScatter diagram, 散点图5 g, i6 k+ z* e9 a3 D+ g
Schematic plot, 示意图/简图9 }, G8 ^( T) z e
Score test, 计分检验
8 B. D/ h% V. _6 M8 M0 R% c1 R& `Screening, 筛检+ T- ?0 g9 t+ z9 G1 l/ u$ e) D
SEASON, 季节分析
5 D9 D& Q, J7 }: F, S- N: S, _$ b1 zSecond derivative, 二阶导数8 Q. j" @5 a) F- X! Y! [
Second principal component, 第二主成分
4 K- S1 ]* S# C* S0 M* ESEM (Structural equation modeling), 结构化方程模型
; M- {0 ]! X5 ~Semi-logarithmic graph, 半对数图7 d, k# E" U% I$ Z
Semi-logarithmic paper, 半对数格纸3 O) D [- T+ M
Sensitivity curve, 敏感度曲线
. a9 A& H2 g& v6 RSequential analysis, 贯序分析5 Y) O" k( l% h; j% a/ M
Sequential data set, 顺序数据集& E+ F t& `9 S1 Y3 x8 j5 B6 {
Sequential design, 贯序设计
b6 ^2 d8 R* B: n: p9 _Sequential method, 贯序法 @8 a( X! h: b# F4 ^0 S
Sequential test, 贯序检验法6 b) i* q6 T0 _' I) K3 O
Serial tests, 系列试验" \+ R( b: R$ z9 z9 ~3 U I
Short-cut method, 简捷法
8 v% q4 ^- j4 X3 e, GSigmoid curve, S形曲线5 Y5 k$ X1 a1 U6 t/ G* d% d
Sign function, 正负号函数
9 w. [' E K4 i4 aSign test, 符号检验
" U- c6 T# s8 T! V0 J7 cSigned rank, 符号秩/ O2 b8 z- [" U! H' B9 K
Significance test, 显著性检验0 [7 M; o2 x; r/ r+ R% U
Significant figure, 有效数字
! P' b7 g# A& h0 ^5 n, XSimple cluster sampling, 简单整群抽样
- T# n" i' [+ A) V% K X0 s0 dSimple correlation, 简单相关
/ @* R0 w, F9 K- u1 R5 GSimple random sampling, 简单随机抽样
( g% J' |( I% q( o, g( M. {5 v) RSimple regression, 简单回归
% w) G) s# I9 P9 i2 e* N5 X. k7 Gsimple table, 简单表' _1 o* A" V" @
Sine estimator, 正弦估计量( N& x9 a& U# _, K3 u$ H
Single-valued estimate, 单值估计
) [! n% G* E+ ~0 N) VSingular matrix, 奇异矩阵6 G0 [5 P- l* C3 w
Skewed distribution, 偏斜分布0 L$ T6 x& |9 s+ V
Skewness, 偏度" x" e% F6 }+ a4 v
Slash distribution, 斜线分布7 G& `# V* @* u% k
Slope, 斜率
, X5 s) U& c& lSmirnov test, 斯米尔诺夫检验
- } a; l: d0 vSource of variation, 变异来源
2 W8 H# ^/ e. v$ DSpearman rank correlation, 斯皮尔曼等级相关
, ~- g( ~- d7 H- SSpecific factor, 特殊因子1 B: W7 E% W) F
Specific factor variance, 特殊因子方差
( v! [4 Q# h' G* q. c' K2 K" n8 u9 b7 F- OSpectra , 频谱
+ [7 Y% h% p+ [0 g4 h2 [Spherical distribution, 球型正态分布; j' h$ ~6 G+ `' V& H- {4 [
Spread, 展布8 j: ^" `- N# R' I; g4 \3 n
SPSS(Statistical package for the social science), SPSS统计软件包
) ^5 X2 K8 |. @! Y- H& v+ KSpurious correlation, 假性相关
) M7 n- L. t/ G; ?9 y3 G& bSquare root transformation, 平方根变换; r1 S) S- a, M) e3 u% {4 s
Stabilizing variance, 稳定方差# K. `" H" ~# v" l& P* ~ h. U4 x: K
Standard deviation, 标准差# Q d, ^) e' c. @+ b
Standard error, 标准误
6 @4 ?, w, G* J: O* o5 Z: hStandard error of difference, 差别的标准误) K B2 U, `( K* r& W
Standard error of estimate, 标准估计误差( C N/ T2 E7 L; d7 \
Standard error of rate, 率的标准误
: F- ^% d% R! b' l; l+ EStandard normal distribution, 标准正态分布0 S3 k/ E, _9 R* G/ n
Standardization, 标准化
% f9 I# i% o L3 ^# o6 G, LStarting value, 起始值
+ a8 c& u7 D3 T$ }: S KStatistic, 统计量
$ m) Y6 ~2 b; t' ^+ B, I4 qStatistical control, 统计控制
# i# L, f: A) Y S9 f2 uStatistical graph, 统计图
8 Q/ ~, Y; J" hStatistical inference, 统计推断; _: [1 A& s+ Y* p
Statistical table, 统计表
$ ]8 `* I- V* H8 q/ mSteepest descent, 最速下降法
1 W7 W, z7 g, j/ Z: Q1 |* MStem and leaf display, 茎叶图
; ~* @* d. w: m2 W) ~ p3 C y* ]Step factor, 步长因子
5 D2 P5 j6 M6 B/ k" b6 V( g4 PStepwise regression, 逐步回归! i$ x v8 I+ w# E7 O
Storage, 存
/ Y" q5 i8 A0 @: X, dStrata, 层(复数)- ^/ X$ ^6 x% v" j; c& { u! b3 Y7 q
Stratified sampling, 分层抽样
y5 g& L) `3 F, G1 ]" E: hStratified sampling, 分层抽样
& B% Q0 [$ @ h+ n# w4 ~$ dStrength, 强度$ ]+ S6 c7 i6 p8 ?8 o2 [
Stringency, 严密性
( z# F1 w& `) t; J" YStructural relationship, 结构关系
* l) e: x7 {) e* J9 I8 gStudentized residual, 学生化残差/t化残差
3 X% ]3 S5 ]' f. S: x# J6 x9 GSub-class numbers, 次级组含量
' ?9 f- @1 D2 }9 L" DSubdividing, 分割- c$ k N. r2 {9 z ]: M
Sufficient statistic, 充分统计量
( [6 T( J# D& V* USum of products, 积和9 |+ W! f( d$ U5 [8 U
Sum of squares, 离差平方和
& V T5 g/ G0 p8 W- D4 _( QSum of squares about regression, 回归平方和
3 D* J, k0 l' Z8 O8 g/ nSum of squares between groups, 组间平方和& X: y) r7 S0 y8 ]& t" q
Sum of squares of partial regression, 偏回归平方和 E1 ^! a; i* ^
Sure event, 必然事件$ ], D) n6 ]2 P/ [: z, r" }0 [
Survey, 调查- o: v2 u0 E* a: T: f5 r! @4 a
Survival, 生存分析$ O4 G6 m" H1 c0 Y: l" x; @. S
Survival rate, 生存率
1 i" ~5 o0 n- v0 ]( GSuspended root gram, 悬吊根图/ S) z, W( L+ B0 B
Symmetry, 对称
% W( w7 c* ~8 t! Z& l: dSystematic error, 系统误差$ ?5 d/ G' `7 F/ C E+ Z
Systematic sampling, 系统抽样) u$ {. I6 f1 Y4 Q& i) c3 D7 d
Tags, 标签& H* i. I2 h) i1 C: y0 C" h% Q9 h
Tail area, 尾部面积
' D$ H( M' t+ R# TTail length, 尾长
2 d7 s ]2 K5 `( vTail weight, 尾重
! w, L# T' x7 a& `Tangent line, 切线
9 ~! ?, t: J4 ~; P3 b6 c! PTarget distribution, 目标分布
: ]7 g1 w. Y1 |8 j/ b/ qTaylor series, 泰勒级数8 h7 O5 p1 V% r% D
Tendency of dispersion, 离散趋势
. T- m. a4 @- T. H6 z8 G0 dTesting of hypotheses, 假设检验" U+ y& ?% z4 R8 g: \: l# A9 u
Theoretical frequency, 理论频数8 W$ C5 V8 L6 i; m7 C3 Q7 d- y
Time series, 时间序列
8 V4 t0 q* O. q+ r' PTolerance interval, 容忍区间4 n$ g) }" h+ a4 ^; Q
Tolerance lower limit, 容忍下限
; ~( W3 K B6 d6 v4 q: c2 P# r9 A$ `Tolerance upper limit, 容忍上限. ?/ o' h# C( P7 \* ?
Torsion, 扰率
, _% E/ L ]% d. y9 ?: QTotal sum of square, 总平方和
+ Q# T- P( _% ATotal variation, 总变异
- `% S$ g3 G0 `0 u; x& T* `, TTransformation, 转换
9 x4 n9 {8 I1 e tTreatment, 处理
) D) n5 S3 D* ~, Q) |% J! qTrend, 趋势9 Q; K1 d4 r, \, q t, m; Q
Trend of percentage, 百分比趋势; O5 [ O. q! F9 D' l
Trial, 试验5 |) p, `! j7 F; r% N4 W
Trial and error method, 试错法
2 u+ t+ f2 G6 G+ X8 STuning constant, 细调常数. n, y8 `* i3 {8 g3 u, L& i4 f
Two sided test, 双向检验) D0 R8 |/ M G
Two-stage least squares, 二阶最小平方6 @1 b6 b0 j9 l7 B4 T; z R' T2 `7 `
Two-stage sampling, 二阶段抽样
* P) X1 \% |# U0 ?' \6 P( a4 S+ xTwo-tailed test, 双侧检验) w. ~& q3 p) W- v$ z7 X
Two-way analysis of variance, 双因素方差分析
# ~+ R( I4 \ ~8 w UTwo-way table, 双向表0 ?9 Z8 ~9 G. _) Z- A
Type I error, 一类错误/α错误
) K! E( y+ N/ _7 @7 YType II error, 二类错误/β错误 n+ o/ N1 b& X
UMVU, 方差一致最小无偏估计简称" P( E+ h+ I0 m" E+ c. L
Unbiased estimate, 无偏估计
6 K; e4 F& Y% p2 F8 O# J: [& BUnconstrained nonlinear regression , 无约束非线性回归
, R6 q; P* u( O& e) ]$ W! KUnequal subclass number, 不等次级组含量
# ]! x9 o/ V) z. W( ?8 GUngrouped data, 不分组资料
8 `+ T7 j! G9 nUniform coordinate, 均匀坐标
& H( g! X- T: ?8 E; }# ^% UUniform distribution, 均匀分布( _# [& u; y$ b
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计$ q/ i, {. r! ^5 H5 Y$ X5 u4 e
Unit, 单元
) o4 \2 G8 M; Y5 h% ?, X5 C/ e* N+ RUnordered categories, 无序分类
" }( i+ p) A; |Upper limit, 上限+ e* v& I! Y7 ` g8 |
Upward rank, 升秩1 d/ S5 u) J7 e0 @8 E/ o G* V1 T
Vague concept, 模糊概念! _$ U* }% ?& y& J
Validity, 有效性
$ F/ b+ Z) }% C. {* p5 qVARCOMP (Variance component estimation), 方差元素估计+ U/ V! M: f/ C9 v
Variability, 变异性
, ?# {5 v& A0 h& P; J& \Variable, 变量! b$ H& U/ o& C
Variance, 方差, c+ D8 c0 H, p8 y3 S" t
Variation, 变异; n: m! k$ s2 a7 \' {
Varimax orthogonal rotation, 方差最大正交旋转
& {1 q+ Q U) G& J% {, _: |9 rVolume of distribution, 容积
3 @3 F6 j# |0 b7 qW test, W检验" e. ~3 C2 f, W, ]1 H
Weibull distribution, 威布尔分布
/ p! g4 n" i+ u5 ? o1 i0 G: {Weight, 权数6 {8 d% ?/ ]3 \; n2 ^* L, P: _
Weighted Chi-square test, 加权卡方检验/Cochran检验
5 n0 L: Q% i2 E, J0 X$ a- @$ p0 wWeighted linear regression method, 加权直线回归
9 ~+ ]9 c3 C- `6 B- {4 g+ L# o1 BWeighted mean, 加权平均数7 x7 {, q' a7 U. j! n
Weighted mean square, 加权平均方差
& c4 V! F( u6 p. H' K0 D( `Weighted sum of square, 加权平方和
! p) ^" h# ` c @5 W. D$ XWeighting coefficient, 权重系数
5 x1 `# C. H2 @* C' JWeighting method, 加权法 - W+ [5 C# F" V3 o
W-estimation, W估计量
6 j. V5 L3 c9 c' @ L+ ^% x. F cW-estimation of location, 位置W估计量6 S. A; x4 X# m
Width, 宽度
; w: ?6 ~$ N( ?& Y& w9 `Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
% c/ p5 D! H v& @Wild point, 野点/狂点
. `/ z+ y3 p9 K1 n0 c7 \Wild value, 野值/狂值
3 ~, d$ L$ U7 |Winsorized mean, 缩尾均值
8 p* y- l) c* y1 ]3 G7 f5 N( ZWithdraw, 失访
$ G( W- O8 n1 m& g0 x4 p3 E5 b+ VYouden's index, 尤登指数
0 I4 m/ C. y. }: n$ b: _' UZ test, Z检验/ V' g" d% z& Z3 _7 \ k' _
Zero correlation, 零相关
9 l& s! g ~; C9 Q1 L1 }7 C( ]Z-transformation, Z变换 |
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