|
|
Absolute deviation, 绝对离差
- K+ S0 i) b# v* UAbsolute number, 绝对数" t0 G! S2 Q9 R* D4 p
Absolute residuals, 绝对残差
% k Z6 c0 X9 {( Z5 U& jAcceleration array, 加速度立体阵 D; u9 a- F0 g4 g
Acceleration in an arbitrary direction, 任意方向上的加速度8 |# B% e! l) a" i- n. V! K
Acceleration normal, 法向加速度
2 T7 H3 Z7 U. i' fAcceleration space dimension, 加速度空间的维数: U6 I' o8 Y/ H5 }, S% Y. [9 J- ]
Acceleration tangential, 切向加速度- \! v: F) w5 K' c# S/ {
Acceleration vector, 加速度向量" @, ]! `- u \+ f3 _, g/ D5 R
Acceptable hypothesis, 可接受假设$ E5 r6 z& a5 B/ T1 y: f
Accumulation, 累积
1 Q) p# |; E, _9 `' L" c' zAccuracy, 准确度
, q- q5 `- n& ^! e8 kActual frequency, 实际频数7 m6 ], _. r) q4 q9 [
Adaptive estimator, 自适应估计量0 s! Y3 r1 W% G" p. \8 A/ S
Addition, 相加
9 |5 I. e8 @, y- S' u/ \/ aAddition theorem, 加法定理
1 Z6 P. ]/ r' ~( c9 w) }Additivity, 可加性, O: ~, Y' T- Q3 N( W6 ?
Adjusted rate, 调整率, k$ A0 e3 e' Y9 p' G1 l' t
Adjusted value, 校正值
: f3 W, O3 h1 L7 sAdmissible error, 容许误差
9 p5 F4 V7 N+ i2 R+ XAggregation, 聚集性
1 C- c) A; i) h! A' q6 E: ]( AAlternative hypothesis, 备择假设
' l9 ^$ a, j& ]; F, @ A3 HAmong groups, 组间
9 ~: r& Z! B7 T3 R7 m8 v" \Amounts, 总量8 Z0 ~/ g8 D/ k7 P' t
Analysis of correlation, 相关分析
2 C# V: x3 b2 ?9 h) ^% cAnalysis of covariance, 协方差分析
( e5 x- B$ E7 T8 w8 v- OAnalysis of regression, 回归分析4 L: f g9 z+ I7 B! m
Analysis of time series, 时间序列分析
0 G* h& Z) `! U) F9 ?, b1 @. ~Analysis of variance, 方差分析$ N0 g% Q$ ]. L$ r
Angular transformation, 角转换
4 N3 U$ b( k0 m9 c* DANOVA （analysis of variance）, 方差分析, Q7 X" ?9 P' y7 O) W! \
ANOVA Models, 方差分析模型: r! }7 U' K( A
Arcing, 弧/弧旋
+ L! `+ ]- R0 h1 f; {& zArcsine transformation, 反正弦变换7 y, }. |# |4 A% Y3 l: n# L( S
Area under the curve, 曲线面积
8 U/ I; Z! M+ }. F4 _1 c% r$ xAREG , 评估从一个时间点到下一个时间点回归相关时的误差
% [0 a: \: w2 p9 ?) \! uARIMA, 季节和非季节性单变量模型的极大似然估计
! U5 K' s h1 @( ^Arithmetic grid paper, 算术格纸$ H8 A1 b- x+ G# u7 O1 A n0 ?
Arithmetic mean, 算术平均数) v, N' d0 R, ?1 g# L
Arrhenius relation, 艾恩尼斯关系! r8 c+ \/ v& L: L- _# V" p
Assessing fit, 拟合的评估4 I9 _, K. Z7 s1 L% w0 U
Associative laws, 结合律
$ W! _% X" Y9 W' J; h% c! Y9 Q& uAsymmetric distribution, 非对称分布1 o0 I* Q( |# L* ?) K% r9 r
Asymptotic bias, 渐近偏倚, j6 d# c4 w: r. ^0 Z4 `
Asymptotic efficiency, 渐近效率
4 s( z, a( {' I* n7 M9 eAsymptotic variance, 渐近方差
9 ]1 R+ C7 _8 Z" J: w; SAttributable risk, 归因危险度/ C8 U# Z5 Q3 y) o2 e6 l! t
Attribute data, 属性资料
% O3 ]7 z, O1 N& x7 |; `Attribution, 属性
2 h: ]7 u% y) U, PAutocorrelation, 自相关
6 K. i+ _+ r6 uAutocorrelation of residuals, 残差的自相关
$ k: v- }7 `4 m8 b% v! [Average, 平均数
+ U5 g3 B% v% u* v- p9 VAverage confidence interval length, 平均置信区间长度
7 y: N. q. q- D6 \# D/ JAverage growth rate, 平均增长率
% E% j5 n; J* g, wBar chart, 条形图" N0 _; \6 H. g& j3 S
Bar graph, 条形图* Q& R0 T) T" j5 W" ?
Base period, 基期) t+ v9 T) E' V4 v! ^
Bayes' theorem , Bayes定理
j3 @. s5 M6 l. o8 \5 U9 BBell-shaped curve, 钟形曲线
9 F9 O) n z/ QBernoulli distribution, 伯努力分布
( a: j& a. p) M& H9 i iBest-trim estimator, 最好切尾估计量
. i; J* Z( i5 c/ VBias, 偏性
( D1 c) v# Q5 Y" f J) ZBinary logistic regression, 二元逻辑斯蒂回归
& J7 \+ E, \( V* ?: E9 z5 sBinomial distribution, 二项分布
( Q3 b$ s0 S" f) I8 p' H. qBisquare, 双平方; V1 C! D' `% k% t
Bivariate Correlate, 二变量相关
2 \/ C# H1 ]) \! O* a% V0 ZBivariate normal distribution, 双变量正态分布3 \% o5 G% Q6 x3 Y
Bivariate normal population, 双变量正态总体% h* E4 B! Y. L' s7 L
Biweight interval, 双权区间
* g7 L* N+ t h8 aBiweight M-estimator, 双权M估计量 E6 c9 w p( j6 }, R& Q( \6 }5 l
Block, 区组/配伍组+ x+ ?. _% m0 x; @) L: o
BMDP(Biomedical computer programs), BMDP统计软件包; R: W, }4 Q' v' u9 v2 Y
Boxplots, 箱线图/箱尾图
! @& T7 y5 N7 N; q5 m9 t6 q SBreakdown bound, 崩溃界/崩溃点' h4 d6 a. u2 @7 w
Canonical correlation, 典型相关
& {+ H7 X2 F2 v3 V! z( eCaption, 纵标目$ L. V/ [, F6 `9 e2 Z
Case-control study, 病例对照研究6 y; d3 k3 p0 ~1 E9 k; t1 U' D
Categorical variable, 分类变量
/ o; s8 U. G/ l+ ~; v, \3 C' hCatenary, 悬链线$ X- A8 ?: B4 J; t2 Y1 A9 i
Cauchy distribution, 柯西分布
6 P1 t' u& v. S1 ECause-and-effect relationship, 因果关系5 x, L! a; X4 [9 u8 |, m9 v
Cell, 单元
8 U, { @0 x: z" }5 H' CCensoring, 终检
7 }5 H( f3 j. \# OCenter of symmetry, 对称中心
, L1 P/ G1 E% U& n) bCentering and scaling, 中心化和定标
: ]3 g( R* G( l$ g. [0 m! {Central tendency, 集中趋势
9 i7 v1 ?6 C+ e+ ^0 xCentral value, 中心值2 h5 C2 H/ R) Y# O1 J Y
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测* O* p! W' h, ?6 ^* L! n7 E
Chance, 机遇7 i' J' Q0 N" K& [1 r/ C; Z: Y
Chance error, 随机误差
* T% j& p8 m+ _8 L0 e9 L; CChance variable, 随机变量% U$ W5 ^& ?/ z% G
Characteristic equation, 特征方程& _# g4 \: f+ X/ T- E
Characteristic root, 特征根
9 L' V0 R Z( j( }& zCharacteristic vector, 特征向量
- p) f7 A$ r/ J9 n6 m5 v& y# ~Chebshev criterion of fit, 拟合的切比雪夫准则& }' w3 M3 ?# j7 ^9 f9 v
Chernoff faces, 切尔诺夫脸谱图% @4 e- R/ s/ J
Chi-square test, 卡方检验/χ2检验8 l: {9 v0 p J" q
Choleskey decomposition, 乔洛斯基分解
7 W- u! x/ f% `6 K& C% gCircle chart, 圆图 , ~3 T4 _- t1 e9 E' Q* b
Class interval, 组距
* S3 c: S: ~ f7 l; [8 i UClass mid-value, 组中值
; t' a# A( K0 ~% P. x( g" P+ ?Class upper limit, 组上限( c. _+ N; W9 W* ~3 ^" w
Classified variable, 分类变量8 F1 }8 r' Y8 S9 s6 P9 p5 S B
Cluster analysis, 聚类分析
& p1 @# M! h) |! o; KCluster sampling, 整群抽样9 X$ L( ? z; f* `. q4 g" u" z( m' J
Code, 代码" I8 O2 p2 ]8 T/ X
Coded data, 编码数据 h9 o) @3 k4 q0 O! t; v
Coding, 编码
% Z- P" h7 M+ \5 GCoefficient of contingency, 列联系数& ?5 R: w9 w5 @) V4 O5 n; G: D
Coefficient of determination, 决定系数2 L: w3 N5 ^& s( f
Coefficient of multiple correlation, 多重相关系数# i) K* x+ n% h9 H8 A1 [9 Z
Coefficient of partial correlation, 偏相关系数$ q( {* N9 q( }! O+ ~
Coefficient of production-moment correlation, 积差相关系数7 q. A5 F3 e4 p
Coefficient of rank correlation, 等级相关系数8 w9 p: o) }: F6 J2 D: z
Coefficient of regression, 回归系数
+ U3 f n, r. r$ }Coefficient of skewness, 偏度系数
' ~7 t2 M7 y+ [Coefficient of variation, 变异系数% u4 G! q8 R. V: Q
Cohort study, 队列研究$ [- C/ ?; U% B5 e9 F
Column, 列' T- x, o1 o. c: X8 g4 V+ o2 [
Column effect, 列效应
) B0 L6 T$ _' gColumn factor, 列因素1 }; I" y+ K# A/ w
Combination pool, 合并
8 Y+ [5 ^% T9 D8 P: ECombinative table, 组合表% W4 Z7 o* J: P- j6 J- |1 a
Common factor, 共性因子% k6 p0 f1 G8 ?" Q& U, `
Common regression coefficient, 公共回归系数+ E4 g2 s! @6 ^- s/ Q
Common value, 共同值4 J$ @0 P; Z3 }4 v V
Common variance, 公共方差8 P) R) G. ^4 v
Common variation, 公共变异
% H& L4 P, j$ ECommunality variance, 共性方差& P6 u" n- M( h2 `( h7 S) y. n
Comparability, 可比性
6 J/ O m% s1 h0 c4 x" c/ D7 W' IComparison of bathes, 批比较! a" e) E; `' f+ V
Comparison value, 比较值
6 _6 b$ ~4 w% lCompartment model, 分部模型! N, c& H0 ]( X( C4 Y8 i# ^2 \( S
Compassion, 伸缩6 f1 X$ X R r7 g
Complement of an event, 补事件6 V$ J# U y/ u- D" C" s$ @& ?
Complete association, 完全正相关
9 _% b S& O' _Complete dissociation, 完全不相关
! S. s3 N: I7 b4 zComplete statistics, 完备统计量% w; D- m( p" N6 \4 ]
Completely randomized design, 完全随机化设计1 a1 t9 {1 \' L/ { N |6 J5 u
Composite event, 联合事件2 K6 M- I4 @3 h% b. D) }$ P
Composite events, 复合事件
, d9 F* w7 z" ~0 c# HConcavity, 凹性; P9 s" k) K" j& q& T9 k
Conditional expectation, 条件期望
3 W: N0 ?$ r1 O0 IConditional likelihood, 条件似然
" m" X9 M. j4 P+ sConditional probability, 条件概率
2 c( X$ ]! x; l7 w! V aConditionally linear, 依条件线性
$ z5 ?' P" J; ^ d, MConfidence interval, 置信区间
9 ]+ M6 D0 n+ \2 J! z: yConfidence limit, 置信限
1 s O( G: P! p# TConfidence lower limit, 置信下限
4 b& Q% T0 s; Q4 V! a, zConfidence upper limit, 置信上限
- T6 i: I& L% e4 [/ w- ?3 dConfirmatory Factor Analysis , 验证性因子分析; n! M& [. d- f, w9 O. H# O. @
Confirmatory research, 证实性实验研究
; P3 L# r6 { Y% t0 t4 y# K% cConfounding factor, 混杂因素( M7 r' Y F, C1 g0 s
Conjoint, 联合分析
6 C5 m( \1 B( y# F# AConsistency, 相合性# v+ Z& ?9 t3 g- p: e
Consistency check, 一致性检验2 K p% c: ~, ` j) {- w
Consistent asymptotically normal estimate, 相合渐近正态估计
! x, j: ^/ [6 ^5 M4 K9 XConsistent estimate, 相合估计
6 \' u9 ? P# H8 z/ T6 T8 lConstrained nonlinear regression, 受约束非线性回归; Q: d ?! C2 ^" E m
Constraint, 约束
, X! q$ m( j* fContaminated distribution, 污染分布0 x5 Z3 Q. \& H- ]) L; Z) s I
Contaminated Gausssian, 污染高斯分布
3 S# R ]% g9 C4 m. [% L- SContaminated normal distribution, 污染正态分布
) T' h" l4 g5 UContamination, 污染
; y& t) c, _6 Q* i! bContamination model, 污染模型, w/ K7 K; e, n
Contingency table, 列联表$ I. r7 b6 Q, C+ W9 Z7 V% h6 P/ ?
Contour, 边界线( E. _, w6 i; Z1 F: N3 {7 c! c
Contribution rate, 贡献率" P/ V! O* G4 Z$ o
Control, 对照
9 O2 P# `% s! WControlled experiments, 对照实验 x k3 J: S' o+ E: i! t: Q
Conventional depth, 常规深度
. e) L, N* D* ?2 c. E3 fConvolution, 卷积
3 [2 h( ]' V" R. t3 |8 B5 ]; ]* bCorrected factor, 校正因子& |" N3 f2 O; f& K5 ?
Corrected mean, 校正均值( @- E$ y! d' g9 i
Correction coefficient, 校正系数
( E: ^) z: n, S) Q3 A& [5 T) {Correctness, 正确性
$ R( B' X1 D9 d6 r# CCorrelation coefficient, 相关系数) c* V3 ^! t, P+ n: y9 C7 H7 e, }
Correlation index, 相关指数3 V" I# F' E5 N! E7 u
Correspondence, 对应
+ e: |" t' w( w+ ], oCounting, 计数; q+ o4 M+ o+ c( f) q/ j! R
Counts, 计数/频数
6 ?$ h/ I- V0 |$ _% PCovariance, 协方差2 L. T4 k% [; Y* A& F
Covariant, 共变
* t* C R5 p* b+ ^Cox Regression, Cox回归
1 T. t4 d# ~) }, w6 b3 q" q/ vCriteria for fitting, 拟合准则
/ v/ i3 U8 Q) l; w# M' U4 WCriteria of least squares, 最小二乘准则
7 _: ?6 ? ]$ JCritical ratio, 临界比; Q! q# S5 O+ ^3 y; V, l4 W5 N" K
Critical region, 拒绝域 k1 W; z/ ~' P* j1 h: X
Critical value, 临界值
5 J+ r6 L2 {+ C- OCross-over design, 交叉设计5 m0 s1 Z+ q& G" T
Cross-section analysis, 横断面分析' d. Q7 F3 i4 i" z% ~5 H
Cross-section survey, 横断面调查4 f4 M) L# [5 x. R6 H/ j6 T
Crosstabs , 交叉表
3 z' t5 `: _4 s) _4 \: Q2 i3 eCross-tabulation table, 复合表
' j7 t' d% s( \/ L* `) SCube root, 立方根
" D# u$ L# f, T# ?, yCumulative distribution function, 分布函数* R7 @9 J$ w5 h5 G( s% N+ i1 L7 b" ]: O
Cumulative probability, 累计概率7 M5 T. ^5 l# J- p A
Curvature, 曲率/弯曲0 ^; @; ^: b+ L
Curvature, 曲率4 a/ a/ k6 ^: M3 z2 M
Curve fit , 曲线拟和 * ]0 f# k( m; Y+ E9 Y6 s, s
Curve fitting, 曲线拟合+ G+ o; p7 ~' [
Curvilinear regression, 曲线回归
; V# l! L8 b. R- ~5 mCurvilinear relation, 曲线关系
% v9 p3 Y3 ^+ q mCut-and-try method, 尝试法
' k# n: ~, d) K0 ^( m5 G) z; SCycle, 周期
- z: ~( e( V8 H7 _. yCyclist, 周期性
( p1 U9 w3 b3 ^4 D2 d/ AD test, D检验
$ W- T- Q4 y$ J, l: g, I9 k( Z9 g' wData acquisition, 资料收集: H8 a% |" h* L+ `% |
Data bank, 数据库
/ d0 W2 [* M N$ B9 }3 w' \- Q* AData capacity, 数据容量, f0 ~/ N7 Y' X d+ o$ W! j: P
Data deficiencies, 数据缺乏
t5 n5 x) E4 K2 T: N. lData handling, 数据处理' L G. [* A7 ]# M7 j5 _
Data manipulation, 数据处理7 h6 ]8 X: ~( Y( y, d& \
Data processing, 数据处理 r3 y& C6 n% ]* ]; K5 E: Y
Data reduction, 数据缩减9 W' d9 X0 S) y; \
Data set, 数据集
% G- [1 Z# a" W( U7 VData sources, 数据来源
) i4 P/ w7 K# X% |Data transformation, 数据变换
/ m) U5 A: r* g* R, P( c! EData validity, 数据有效性; ?2 P7 M5 C( g1 h% C
Data-in, 数据输入
" t' a$ O1 Y" @/ `& sData-out, 数据输出
: c( t& A5 b: }) d2 cDead time, 停滞期
7 H# p: W# U& p }Degree of freedom, 自由度
. ~ J- l( C, d+ F- U+ }: }8 s! PDegree of precision, 精密度# j# ?+ m4 C3 s' s) d
Degree of reliability, 可靠性程度
5 M u& a& j1 x$ F" t( I( n& NDegression, 递减0 V, c: b; J3 i3 {2 u
Density function, 密度函数
/ U( z- D6 O9 G0 l& R& L: p9 f% _/ h1 ODensity of data points, 数据点的密度8 R6 t; f! _; `
Dependent variable, 应变量/依变量/因变量
8 M6 G3 r& ]8 }Dependent variable, 因变量8 h1 k$ d- e+ p' |
Depth, 深度
4 b& Z2 \4 l7 H/ v/ M+ n ]Derivative matrix, 导数矩阵# W) s ~. E7 d# `4 S* N! X' }2 z
Derivative-free methods, 无导数方法, L' N9 D9 `7 S! k% G, K9 }" R4 O
Design, 设计
4 K; F. w& q6 d% [6 yDeterminacy, 确定性2 T* a; [7 T# T! `% C3 ~ p& ]
Determinant, 行列式
9 I6 u, U7 G w7 |Determinant, 决定因素+ m; X; h/ d2 v0 ~% C
Deviation, 离差
: u. d A, i8 ^; j W! T% D- dDeviation from average, 离均差! B# q( ~7 R0 v. \6 e8 t g
Diagnostic plot, 诊断图
! P: v! J9 m) d* Q' @0 qDichotomous variable, 二分变量
2 d( Z, G; x2 m w% } vDifferential equation, 微分方程
+ C) Q0 C8 h$ q- yDirect standardization, 直接标准化法
' D$ X5 p5 b. Z0 [Discrete variable, 离散型变量
# i8 k4 Z! R9 i. O1 T# S% M1 g$ uDISCRIMINANT, 判断
. V4 a0 R, N/ r& XDiscriminant analysis, 判别分析
* R, M( P" `: [2 P; ODiscriminant coefficient, 判别系数. T) i" n- j+ G" e6 _7 u$ g
Discriminant function, 判别值
9 e5 Y' G* m9 I6 fDispersion, 散布/分散度) Z. I- ?. \$ ?, P" T6 d
Disproportional, 不成比例的 N2 i- c$ E# K. ~% q9 @) z
Disproportionate sub-class numbers, 不成比例次级组含量4 p/ f' }' V: p' E; W
Distribution free, 分布无关性/免分布; U+ J3 d! N! N0 t. a( o
Distribution shape, 分布形状
* H) g. L7 J5 t* w2 \9 V/ @$ RDistribution-free method, 任意分布法. X$ h# r2 x! D9 w) X
Distributive laws, 分配律7 B: c( B& {# K1 R
Disturbance, 随机扰动项5 t4 z, r: d2 Y; `" F
Dose response curve, 剂量反应曲线$ v5 d$ Z# E. [+ M1 m: Y
Double blind method, 双盲法
3 ]1 t6 b( {3 d* XDouble blind trial, 双盲试验
2 S- ^ J0 Q4 j5 c/ c# |Double exponential distribution, 双指数分布
9 t* P9 d" R2 w9 z5 ]& {5 ~$ `Double logarithmic, 双对数
3 [& w6 j) Q. p+ ~9 P1 QDownward rank, 降秩 A" J6 n1 V$ p* B6 v
Dual-space plot, 对偶空间图- |' g! U. `, B
DUD, 无导数方法
* Z4 q3 O: `' j- i& U! w6 @Duncan's new multiple range method, 新复极差法/Duncan新法
, {( a4 F2 c4 J. A, U' l8 ~, p( S5 aEffect, 实验效应
! E5 y/ n0 j. L) k5 k/ UEigenvalue, 特征值5 [8 a0 C5 i9 K
Eigenvector, 特征向量: I* E1 V& v. d, A! d
Ellipse, 椭圆
# b3 A$ t! f; n9 [/ U8 |0 y% YEmpirical distribution, 经验分布
1 j# }7 v4 T; p- hEmpirical probability, 经验概率单位
* g6 E a( J7 M. @+ _Enumeration data, 计数资料6 B8 _1 G9 ~/ d0 u o
Equal sun-class number, 相等次级组含量! {: @# l) N' P# s7 ^
Equally likely, 等可能
6 b: U) C: z J: G- G- X' U0 OEquivariance, 同变性& s* o0 {* S% @5 b
Error, 误差/错误3 P+ q5 o/ {0 ]# H8 [! ^6 M8 h
Error of estimate, 估计误差0 P6 \+ {( c0 y' J- x& k
Error type I, 第一类错误
. ]; r' ?3 D3 Z4 z. lError type II, 第二类错误3 W) c$ P3 X6 N; \& d
Estimand, 被估量' w2 T* n5 K [+ i- W* {/ K+ S& j
Estimated error mean squares, 估计误差均方" D$ B; J9 D2 i& J
Estimated error sum of squares, 估计误差平方和
& c! U4 r$ k% UEuclidean distance, 欧式距离. a' I3 D Z9 O" E4 M9 o/ F1 ~
Event, 事件, T! [" C* g6 D) v
Event, 事件
4 j5 z$ k4 C3 `* H6 b4 SExceptional data point, 异常数据点5 E6 z7 k8 J8 n
Expectation plane, 期望平面
' q5 |/ s; y% q6 T# j1 }+ k6 ?6 H. WExpectation surface, 期望曲面! a: g: H! V/ k
Expected values, 期望值
7 q; _* P6 D" T4 C Z2 ZExperiment, 实验' t N5 Z- I( ^5 k+ k. |- M4 V
Experimental sampling, 试验抽样
, }# r) E4 M$ p% {' j1 i7 ZExperimental unit, 试验单位
+ q5 U6 y; _! r7 u7 y# yExplanatory variable, 说明变量, [6 [/ J4 d) C9 J4 |9 \9 I* k
Exploratory data analysis, 探索性数据分析
8 P% y/ {, A! ]2 j& U: `* DExplore Summarize, 探索-摘要
: i( Z! k q- Q8 {0 OExponential curve, 指数曲线3 G# e& ~9 L( O; W( ]. n) q
Exponential growth, 指数式增长6 h/ r- h8 N" G+ g' L$ }
EXSMOOTH, 指数平滑方法
' T& W$ [* n5 k2 \' r( B+ j& NExtended fit, 扩充拟合
5 d8 Z1 _7 f$ cExtra parameter, 附加参数: n E2 ~ `! ?% V# ]
Extrapolation, 外推法
7 B5 @0 ^) F% G4 o% E- |Extreme observation, 末端观测值
, \- E# Y6 s9 K- r* S1 sExtremes, 极端值/极值
8 k2 u5 f6 p7 mF distribution, F分布
; f( W9 i, a/ L( l7 D1 Z6 T& i) oF test, F检验
# r' x; K: ~2 Z* kFactor, 因素/因子2 a& Q/ k- m5 g' G# T* l
Factor analysis, 因子分析. B2 E7 W# _* y
Factor Analysis, 因子分析9 _, O% ?9 A5 Q% y$ E$ }% T
Factor score, 因子得分 ( r2 P3 A5 J: |0 v- o2 a1 O
Factorial, 阶乘
7 b; n# }/ Z! \; k& K+ H1 TFactorial design, 析因试验设计
* n- B/ {6 P6 |& j4 I+ NFalse negative, 假阴性! G( _: N C9 c |7 V
False negative error, 假阴性错误
% T- P8 f% k4 LFamily of distributions, 分布族
* R7 M7 I$ X; X2 c, d* f, ~Family of estimators, 估计量族6 ?/ E2 U4 A6 H
Fanning, 扇面2 T0 ]/ N4 d3 _8 t6 K
Fatality rate, 病死率
, r' W9 D! l: O6 b: V3 S% lField investigation, 现场调查/ W: O6 V$ _. c* G; e6 [# X
Field survey, 现场调查
: @' V8 Y6 Y8 BFinite population, 有限总体# k, B0 t" \& u; e
Finite-sample, 有限样本
9 U# |6 Y. y, `- V% z+ i2 zFirst derivative, 一阶导数1 v+ P0 v% x5 q0 I; C( I _) n
First principal component, 第一主成分5 V. A* v# L# ^, G6 H% j$ g6 }
First quartile, 第一四分位数& e, d9 h# L2 `/ ]! H. W y
Fisher information, 费雪信息量) p' @7 `3 p! }/ Y- g& E
Fitted value, 拟合值
/ T" N( }6 c0 q6 G8 }Fitting a curve, 曲线拟合, l2 L$ \/ y9 K4 f, z
Fixed base, 定基! `; ?4 }. F2 x. J$ C" L/ b# H
Fluctuation, 随机起伏0 l: }$ p& K: v- e [" _
Forecast, 预测
: \9 U1 B7 r4 z% G$ u5 K% fFour fold table, 四格表
3 u* K6 t% v* F* l1 f# mFourth, 四分点+ w2 U: N1 i! ?7 b
Fraction blow, 左侧比率1 Y! g" k& M7 c! z& y) {$ K
Fractional error, 相对误差
' K2 j% E8 l. h' i1 M( oFrequency, 频率8 n; {8 j8 k8 A$ \8 E3 r* \5 x
Frequency polygon, 频数多边图/ G1 E o" ~4 b
Frontier point, 界限点. ^4 B5 \$ M& j, @3 |0 H
Function relationship, 泛函关系
6 m" O+ k! K: AGamma distribution, 伽玛分布. R4 c& k! B- X$ h. b- f
Gauss increment, 高斯增量
4 x3 o9 I2 L# H v2 b; ~8 {Gaussian distribution, 高斯分布/正态分布3 P: }6 Y- g: H& A
Gauss-Newton increment, 高斯-牛顿增量
+ r9 B2 Z, I5 W: FGeneral census, 全面普查* A q+ N7 e( l; D' Q1 I$ m
GENLOG (Generalized liner models), 广义线性模型 % v# r. u7 o+ B7 z+ O5 P. W
Geometric mean, 几何平均数
8 a1 I* _# d* X+ U( NGini's mean difference, 基尼均差- q+ i5 j/ i7 A- T" z
GLM (General liner models), 一般线性模型
; R2 g, @$ r7 O( p4 H- b2 h/ HGoodness of fit, 拟和优度/配合度
- R$ `5 | i I9 J. i5 Z& h2 G+ JGradient of determinant, 行列式的梯度6 Z* i7 `5 _0 ?
Graeco-Latin square, 希腊拉丁方
5 m3 x+ r4 Z$ e5 `; ?! L: ]Grand mean, 总均值0 e; X2 k6 K% D% Y q; ^/ s
Gross errors, 重大错误
6 W/ G+ s# O+ b/ Z% H; V; f7 ]Gross-error sensitivity, 大错敏感度
8 H& n7 l% L. x$ HGroup averages, 分组平均" v2 d6 `! `: S9 R: s6 ?
Grouped data, 分组资料
+ L. _# i4 f( G- uGuessed mean, 假定平均数
; \" f8 Z! P) `* \Half-life, 半衰期1 ~2 [8 P1 {7 \# R' l
Hampel M-estimators, 汉佩尔M估计量4 ?6 P2 F3 e3 Z
Happenstance, 偶然事件
' o, z$ b! h1 i* u5 ]Harmonic mean, 调和均数
5 r% R6 D2 v+ i9 JHazard function, 风险均数
( N" \6 r# W6 O) Q3 A; V# THazard rate, 风险率
7 Q/ R! A/ c$ yHeading, 标目 9 j9 [+ Q6 Q7 |7 W
Heavy-tailed distribution, 重尾分布
4 o/ {# @! I5 t' ?- g0 VHessian array, 海森立体阵
0 v) S+ i) c. i3 BHeterogeneity, 不同质8 R3 K% ]5 F1 {# x3 x
Heterogeneity of variance, 方差不齐
7 }) X, G* K C: t+ nHierarchical classification, 组内分组
. p$ i) f) k" G/ L" [# A; kHierarchical clustering method, 系统聚类法
9 M1 S& s1 N# D8 g) z0 v1 jHigh-leverage point, 高杠杆率点
. x9 u- _) z9 T& B. t: N, QHILOGLINEAR, 多维列联表的层次对数线性模型
: {7 _4 f, C$ g5 ZHinge, 折叶点0 J) Q/ M0 \/ m E* b/ u
Histogram, 直方图
! f% [* f4 d; ZHistorical cohort study, 历史性队列研究 3 @, k( o( d! m
Holes, 空洞, ]7 V$ U: z: b
HOMALS, 多重响应分析( J! e" E/ c1 k: I2 Q T N# \
Homogeneity of variance, 方差齐性
B$ \3 t& |3 sHomogeneity test, 齐性检验8 }1 ?4 d& I1 {5 ^3 F) Y% i
Huber M-estimators, 休伯M估计量
) r8 ~1 R5 w" |6 Y3 o" vHyperbola, 双曲线
* h/ {1 x0 z K5 Y% PHypothesis testing, 假设检验
9 `1 g/ s6 W0 E$ ~& u! FHypothetical universe, 假设总体2 {) b% B. I7 l5 c$ @* H
Impossible event, 不可能事件
/ l1 P) Q( G# VIndependence, 独立性
0 _* G# ?0 U4 F1 a' z( YIndependent variable, 自变量( m0 m' M5 X& Q$ l2 L l+ g/ N I
Index, 指标/指数
0 Z: Z! U' t# I* s2 D" o2 qIndirect standardization, 间接标准化法
3 b9 m7 I! v# Q: xIndividual, 个体8 N5 X* V2 n* x# p2 B
Inference band, 推断带" b/ ]1 U+ _* O4 n, \& h
Infinite population, 无限总体
, D7 q2 |! g. MInfinitely great, 无穷大% \, H7 R0 V' c: A
Infinitely small, 无穷小
! K" i, g. ~6 h7 b: _Influence curve, 影响曲线
+ G Z* Q/ x3 c0 t4 g& }, NInformation capacity, 信息容量" P3 X; ]' J4 I4 p9 q
Initial condition, 初始条件
" Z* }. I! a4 JInitial estimate, 初始估计值6 H6 O; ?' _* z2 t6 _0 L: ]
Initial level, 最初水平& j- U0 |7 v5 Z7 o
Interaction, 交互作用8 Z& |7 M8 K2 |0 Q0 C
Interaction terms, 交互作用项1 I9 p D4 B4 E. j
Intercept, 截距$ e7 _& N0 E" ^# \
Interpolation, 内插法
J8 K% [; S) U- GInterquartile range, 四分位距8 W/ @( G) A, t8 L4 b! t0 y
Interval estimation, 区间估计
' N0 ~9 t& g; Z' n* b) M( GIntervals of equal probability, 等概率区间) B K7 @. @# L( x$ B" Q* T0 g, S6 [
Intrinsic curvature, 固有曲率, W! R8 |7 o# ^* b2 V+ P
Invariance, 不变性7 v/ t( {. T8 E) [, M
Inverse matrix, 逆矩阵
- b( ~9 S: ^7 \7 P) XInverse probability, 逆概率" G; q' S( s. r3 w6 q
Inverse sine transformation, 反正弦变换, S2 l3 B' v7 m( \2 J
Iteration, 迭代
n8 K# X9 N% n) nJacobian determinant, 雅可比行列式" w! a- c* Y' I; b) K
Joint distribution function, 分布函数
/ T& U* x6 l E; BJoint probability, 联合概率
9 g \7 `7 U" c9 d' C+ K, H0 BJoint probability distribution, 联合概率分布
" V; I2 E O7 Z6 U! IK means method, 逐步聚类法
4 h2 V% H x/ }. z9 z" B. {Kaplan-Meier, 评估事件的时间长度
- J5 x, \+ n: c tKaplan-Merier chart, Kaplan-Merier图. \2 Y$ g" e8 _+ ]0 r
Kendall's rank correlation, Kendall等级相关
6 ]: z) d( t8 P# V+ L; uKinetic, 动力学7 F3 i8 g) ~& M, m1 I0 g
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验& w$ m/ D/ ?5 w+ I/ [( ^
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
& n8 G+ r* n" l/ s) H+ NKurtosis, 峰度" g+ e$ n/ y7 d( l! c: U4 }
Lack of fit, 失拟# a, P X4 n3 L" P" T
Ladder of powers, 幂阶梯: F3 c2 f0 Z( }/ S5 T3 |4 }2 ~
Lag, 滞后- g& `8 y" N2 ^6 ^* S
Large sample, 大样本/ v3 P- a0 R. i1 y
Large sample test, 大样本检验
% C7 e+ o7 M; X) tLatin square, 拉丁方
2 @9 ?" T N4 \' B& r9 rLatin square design, 拉丁方设计
. s h/ U) H& P% z) ZLeakage, 泄漏
2 x4 p' }0 P( x, x' d8 rLeast favorable configuration, 最不利构形 W" v9 @# Q6 a b K5 Q2 x$ P
Least favorable distribution, 最不利分布
% d* X. Y: x B, j" F4 Z" {7 YLeast significant difference, 最小显著差法+ T, C- r* e# X. S. V$ _
Least square method, 最小二乘法, u5 K8 _) H! H8 V& e9 _) t
Least-absolute-residuals estimates, 最小绝对残差估计
# t; y7 P" `. |' U2 NLeast-absolute-residuals fit, 最小绝对残差拟合: W% j0 N! E: C& y% F% l
Least-absolute-residuals line, 最小绝对残差线
& t; ] C; | M6 @; T; tLegend, 图例
/ W: R' [* N" A3 KL-estimator, L估计量8 P0 {) \3 F# b+ y; I- H$ N* A4 Z2 J
L-estimator of location, 位置L估计量# F9 g8 b- e9 L- d6 F
L-estimator of scale, 尺度L估计量
' N+ a: |$ @: _; j, p( b/ DLevel, 水平
* [9 T- ~, S# X, N9 t, wLife expectance, 预期期望寿命
6 D5 W& Q9 L9 ?' k3 v D3 @Life table, 寿命表
% [8 n, a2 d& Y2 I, VLife table method, 生命表法* v2 R7 M! V: A0 S' N+ H
Light-tailed distribution, 轻尾分布- L- E) Y# D7 Y$ }
Likelihood function, 似然函数
. ]) D9 c' }4 { H/ P/ {! t. Q7 LLikelihood ratio, 似然比
- E4 m1 s4 z0 yline graph, 线图' @% V. N; U8 ]- r7 [, h! V% l( {
Linear correlation, 直线相关
* k3 a8 I4 d* e: h4 S; q- Y$ uLinear equation, 线性方程
) M' O% S# D' U2 C( \9 A! ^+ ?Linear programming, 线性规划, ~; b% G7 i6 h5 f9 X0 G8 S& F- {6 y
Linear regression, 直线回归4 ~: C V! Q' s" |5 Y; s3 {6 m
Linear Regression, 线性回归5 }. ?! W) x' x' ~1 m
Linear trend, 线性趋势
$ T4 p( d7 Y6 E* g7 KLoading, 载荷 0 `- _( x4 M6 B4 M6 Y M
Location and scale equivariance, 位置尺度同变性4 ?0 s1 N0 H, l
Location equivariance, 位置同变性' V4 U2 s4 b& W7 r, @9 B" B
Location invariance, 位置不变性* O6 M7 g9 G9 H: A+ p2 t
Location scale family, 位置尺度族: e7 |* b( t% ?/ K3 y
Log rank test, 时序检验
2 O. S: P: F4 |6 h. k3 L; }Logarithmic curve, 对数曲线
$ f8 w' j' X. M1 ILogarithmic normal distribution, 对数正态分布 k, t8 J" H0 m
Logarithmic scale, 对数尺度
) x- I2 w2 ^6 t( P8 D7 bLogarithmic transformation, 对数变换
# L, Y+ D# B: J# K+ e: @& o9 hLogic check, 逻辑检查- J( Z% J. u4 I
Logistic distribution, 逻辑斯特分布# ]& S0 `' R, {" o9 U/ Q
Logit transformation, Logit转换! o/ V9 ?* j4 \7 S0 S8 N/ j" f
LOGLINEAR, 多维列联表通用模型
; w) w& L/ y: gLognormal distribution, 对数正态分布
# ]! u+ l0 {) ]& X0 L- ELost function, 损失函数( {- N3 r7 N" y& M+ z& t/ P
Low correlation, 低度相关, ]- E% C+ P1 J% `! N y
Lower limit, 下限
! k9 R4 m) {: iLowest-attained variance, 最小可达方差
, y$ i. A: T% i- b* i7 Z) GLSD, 最小显著差法的简称
- ?. v1 x) D8 `' `Lurking variable, 潜在变量+ O" N; o+ V* _
Main effect, 主效应
$ B3 }& V' D9 d4 W* FMajor heading, 主辞标目
0 ~6 s+ U; k5 H( _Marginal density function, 边缘密度函数
# b1 s* T' ]' y+ j& pMarginal probability, 边缘概率
# w# p; { R+ t: b# y; JMarginal probability distribution, 边缘概率分布, j. F0 i8 M: z, Y3 F
Matched data, 配对资料 }, |& N" @. ^9 T: o/ S! _" H
Matched distribution, 匹配过分布
, ], v+ {- L- d- G$ Q% ~3 H; b( RMatching of distribution, 分布的匹配- z& p9 s8 S) D: K
Matching of transformation, 变换的匹配: V7 A" D3 K+ ?! R" z9 K2 M
Mathematical expectation, 数学期望
, i7 j# V; Y+ C: uMathematical model, 数学模型' m6 c* a4 ^: ?0 ]
Maximum L-estimator, 极大极小L 估计量
( r9 N- ]- z9 a; U7 ^# a- VMaximum likelihood method, 最大似然法
, ^3 k( U' z; K- c& j i+ KMean, 均数$ R1 v& s' g+ X( B, I" y& L
Mean squares between groups, 组间均方 x( A4 I' r0 |- t9 i
Mean squares within group, 组内均方& b( {2 R' T, o+ e z9 k9 g
Means (Compare means), 均值-均值比较: B/ e6 ]# e; c k+ i
Median, 中位数. x6 Z8 a7 o) {( ]" b9 p
Median effective dose, 半数效量) o) k* U$ u x9 S( A8 G/ B% L
Median lethal dose, 半数致死量3 k! f7 g# i7 {: D" K' V7 n
Median polish, 中位数平滑
8 C" J0 d, s$ ~Median test, 中位数检验7 U7 I; e% v" r, Y7 z
Minimal sufficient statistic, 最小充分统计量
. n% G2 ] V8 m( Z: TMinimum distance estimation, 最小距离估计0 y% K3 ]4 i5 A4 A: _& U$ ]6 Z
Minimum effective dose, 最小有效量0 C' i6 |) z4 t( g& J3 _
Minimum lethal dose, 最小致死量7 _ n3 y; g' v& w
Minimum variance estimator, 最小方差估计量6 }2 @1 V+ I, D8 \: d4 F5 G( [5 Y
MINITAB, 统计软件包1 r4 C5 h% Z' I2 L
Minor heading, 宾词标目" s& d" M8 ~" r+ N$ ?
Missing data, 缺失值; T9 q8 r- r _1 B4 S& T
Model specification, 模型的确定
1 R G/ j0 ?3 r+ P- s% b9 SModeling Statistics , 模型统计0 x7 T; p( B8 O% s
Models for outliers, 离群值模型
. ^; Z* \) r* t: dModifying the model, 模型的修正% ^/ T/ u( \* B! O. A+ m# i% F& Y
Modulus of continuity, 连续性模* h" X/ W8 \7 H o; ?! T
Morbidity, 发病率
$ |5 ^- x* x! Z( i' p5 }Most favorable configuration, 最有利构形
0 J! a/ e- \/ N& u: AMultidimensional Scaling (ASCAL), 多维尺度/多维标度5 l, |6 n3 C' b- W: d
Multinomial Logistic Regression , 多项逻辑斯蒂回归
* y; N& q5 J' H$ YMultiple comparison, 多重比较
! H6 d0 n9 Z! {0 @" lMultiple correlation , 复相关" N# G+ l% H2 p1 Z, i
Multiple covariance, 多元协方差
|& J5 S) `7 Z- e3 b) qMultiple linear regression, 多元线性回归( W: G) Q" b8 @' _
Multiple response , 多重选项: a5 t: {3 Y: f! o
Multiple solutions, 多解' _5 `6 L: F6 t
Multiplication theorem, 乘法定理+ g* j% v3 ?. {' c U
Multiresponse, 多元响应
/ f% o0 ] C; R5 F6 g* o6 DMulti-stage sampling, 多阶段抽样. a5 C: P. ^/ C+ Z9 x( B
Multivariate T distribution, 多元T分布
+ D9 R) i- p( o# z7 ?Mutual exclusive, 互不相容
]- B2 T$ U5 W6 ^( ^Mutual independence, 互相独立
7 F( b; E3 [& }6 r7 d3 q# E& i9 nNatural boundary, 自然边界
; u9 U4 T3 m8 F' i6 R6 n/ oNatural dead, 自然死亡* ~ |! j. [4 U5 E8 s/ e% }7 g" A
Natural zero, 自然零
4 Y J8 ~3 f+ y0 b" G. z- JNegative correlation, 负相关4 H. f% @5 A& ]5 h8 F! C- c
Negative linear correlation, 负线性相关# p" J" w r: L' J. s! C
Negatively skewed, 负偏
, ^1 s% R& g9 k' t9 DNewman-Keuls method, q检验
- }5 L8 H# ~8 {NK method, q检验3 A2 Q. r Q. P/ B$ @
No statistical significance, 无统计意义* C/ o2 b: C t K
Nominal variable, 名义变量# U1 _' ?7 A; U8 P6 T
Nonconstancy of variability, 变异的非定常性 B# B# t F6 k1 @2 x: r
Nonlinear regression, 非线性相关4 y! E* Y5 N' K( I7 ~
Nonparametric statistics, 非参数统计 `8 R& \% S+ U6 `$ c5 j# G
Nonparametric test, 非参数检验! k. I& g1 {$ L' p# @
Nonparametric tests, 非参数检验
. W: c. ~* R$ }6 }% z! W; y6 lNormal deviate, 正态离差
" q: @, g% _, C8 s! yNormal distribution, 正态分布 h3 `. s' Y2 y( V7 M0 P* K
Normal equation, 正规方程组
* T* ?/ s: j7 V" W$ GNormal ranges, 正常范围6 m3 M; v. i2 i- S" a) E* ~
Normal value, 正常值
2 e) C' U' q; hNuisance parameter, 多余参数/讨厌参数: T4 U/ p! m: r
Null hypothesis, 无效假设 q% W9 @1 p# n4 z+ k& c/ f
Numerical variable, 数值变量
. E$ e6 ^" S, X3 ]9 [0 l" TObjective function, 目标函数
" d+ y3 {. ]" j( I3 t/ V1 B8 YObservation unit, 观察单位
* ~( f/ l7 ~9 M. JObserved value, 观察值
: \' s) }1 q+ q6 F+ b( t2 u! }: QOne sided test, 单侧检验
; k' ~0 I# B4 q! o( b/ n# GOne-way analysis of variance, 单因素方差分析+ {9 n- `- W% `9 s
Oneway ANOVA , 单因素方差分析7 n; W" |4 I% e4 ` z* x( V( X- g$ n
Open sequential trial, 开放型序贯设计" p% ~: ^! B6 V- s
Optrim, 优切尾
( y6 j4 z+ f6 l! yOptrim efficiency, 优切尾效率
/ u* ^2 ]8 s m, `Order statistics, 顺序统计量
5 r1 Y: _7 `$ kOrdered categories, 有序分类5 K$ R# J7 Y% x. Y1 F0 m
Ordinal logistic regression , 序数逻辑斯蒂回归 L2 z0 Z7 c z3 r
Ordinal variable, 有序变量3 Z& n; b/ h2 q( c( D
Orthogonal basis, 正交基! ~/ `! I% e' O* J
Orthogonal design, 正交试验设计* j2 g5 L' \' {; ^9 L
Orthogonality conditions, 正交条件3 n5 R2 {8 b; X8 ]9 @
ORTHOPLAN, 正交设计
- j3 {- @5 o% L4 KOutlier cutoffs, 离群值截断点 K2 j+ k5 S Z- C6 ?
Outliers, 极端值# q' a: l" _3 X& ~' [/ |
OVERALS , 多组变量的非线性正规相关
0 J$ ~" P w" _/ {, N! ~8 W) M. {Overshoot, 迭代过度
5 w# d9 @; c) I& u, sPaired design, 配对设计
; _) B, Y, t1 Q5 L. z- s) W# C% qPaired sample, 配对样本
! U/ p: l# F7 G6 j4 b# I/ hPairwise slopes, 成对斜率$ c% Y4 L$ N3 ?) q& B0 J! J& G$ E
Parabola, 抛物线& N) ?8 t3 S- f7 j" D
Parallel tests, 平行试验& V4 S) b f* c5 s$ \$ o# H
Parameter, 参数( F$ w2 l- H# U$ |. B2 B
Parametric statistics, 参数统计8 h( ~7 Y9 p! ?" Z
Parametric test, 参数检验3 y% |& V, J* x! H
Partial correlation, 偏相关9 o$ ~' x0 A ?6 B$ {
Partial regression, 偏回归
* S9 U$ i# r( _+ a+ C2 |0 K e3 LPartial sorting, 偏排序5 E) c! `- P3 F2 R6 G7 p& P/ L
Partials residuals, 偏残差
& d, V; [, `. g3 O# MPattern, 模式% t5 D0 n/ Q4 I/ [ ~
Pearson curves, 皮尔逊曲线0 c& ?$ \( x6 I3 E9 J# c
Peeling, 退层0 f. l; y$ J" }, j* @0 b
Percent bar graph, 百分条形图
) B' f, [$ H1 L4 kPercentage, 百分比5 Y, T9 {: c1 F9 Q
Percentile, 百分位数
) d; H) D6 }+ oPercentile curves, 百分位曲线
4 @3 i! F. A, B/ hPeriodicity, 周期性
. L6 \* L4 o3 q% t) p {7 iPermutation, 排列
7 Q- V% \% ~& u" F. X4 g D6 WP-estimator, P估计量
3 k2 \1 D- T1 r: T; ^Pie graph, 饼图
' z! |0 ~: ?4 b6 \Pitman estimator, 皮特曼估计量+ B7 K$ B+ E( S C
Pivot, 枢轴量
/ Q: K+ Z& i5 h) |" ePlanar, 平坦+ {% H) J6 d" [, [4 u7 E z, R) e# A
Planar assumption, 平面的假设/ U1 ]* e& c$ Q; t8 O, s6 Q2 K2 b
PLANCARDS, 生成试验的计划卡' O- \" F& K' B6 T( m
Point estimation, 点估计
. g& ^1 m& [! a3 J: LPoisson distribution, 泊松分布. y# F3 i# i& u: K! F$ A3 ?
Polishing, 平滑. K E; C$ V1 w; U' q
Polled standard deviation, 合并标准差: q1 o; h) B4 d" a8 m
Polled variance, 合并方差9 ?- S7 g( b( f. J1 o
Polygon, 多边图/ Y8 d2 _% O, k+ |" S1 z$ v
Polynomial, 多项式8 u$ q* F2 V/ H* r# a! e
Polynomial curve, 多项式曲线& U) y1 E8 `) R1 T
Population, 总体! z; ?1 X3 |' y+ R
Population attributable risk, 人群归因危险度
2 D; n" f i- C# `Positive correlation, 正相关
) Q' M& r$ F' O* c! D3 KPositively skewed, 正偏# ~- [, R' z _; V2 I1 ]3 k% k z+ i
Posterior distribution, 后验分布
7 }$ L% H- G; r5 K& n/ o1 fPower of a test, 检验效能9 Y; x0 v; l* P! L9 ~
Precision, 精密度
1 K* C3 m# r u/ l4 e* gPredicted value, 预测值5 b1 F( _& D5 T) i
Preliminary analysis, 预备性分析
. f- Z9 }% ~9 G- Y( ~Principal component analysis, 主成分分析
3 e6 y- G9 b# U$ I* _: {Prior distribution, 先验分布2 s4 c# s- u/ y6 f/ L* v' ?5 H
Prior probability, 先验概率5 H8 }* F" X% |
Probabilistic model, 概率模型0 _5 r( d' l# H. j' i
probability, 概率# z" t" g" p3 H" T( B M$ s. p2 a
Probability density, 概率密度
6 k3 q+ T' z- p$ b0 j3 yProduct moment, 乘积矩/协方差
& ` C9 F+ c' h: W; CProfile trace, 截面迹图
' S0 U6 ^% p; G1 V$ j, a" EProportion, 比/构成比# d+ g2 v4 h: u) e$ _3 n
Proportion allocation in stratified random sampling, 按比例分层随机抽样# @% [. H$ H) ?
Proportionate, 成比例4 a' B: X- m) d7 a) G0 r8 l
Proportionate sub-class numbers, 成比例次级组含量9 X. u8 n7 q5 L' n0 Y: u2 ~
Prospective study, 前瞻性调查0 m: |! s5 r; F. Q. b8 n- z
Proximities, 亲近性 ' w' h1 Z8 a; D% U: C. k0 g, _
Pseudo F test, 近似F检验
: A( J+ N- q7 m1 m7 w8 ~Pseudo model, 近似模型/ @5 g) [9 r# f& X0 p
Pseudosigma, 伪标准差
' K9 u0 W) @9 c. x- Q, q9 oPurposive sampling, 有目的抽样
4 o j" H9 e% FQR decomposition, QR分解
! Q( ]" t: v7 d. GQuadratic approximation, 二次近似% l6 t, T; G; {1 M8 f
Qualitative classification, 属性分类3 F& Y* b: \- |
Qualitative method, 定性方法
- p1 x3 U5 j8 r: A% r0 b$ VQuantile-quantile plot, 分位数-分位数图/Q-Q图% @* x2 Y6 a* C, F
Quantitative analysis, 定量分析
& g$ [7 w* ?% h$ xQuartile, 四分位数( b- ]; B# O: E$ m
Quick Cluster, 快速聚类
/ l, v+ l2 j3 r( R+ v$ IRadix sort, 基数排序' Q* ?* B% Q6 o* h- A
Random allocation, 随机化分组1 J4 K; A5 i( @
Random blocks design, 随机区组设计
6 i( {& X8 V' jRandom event, 随机事件' t0 ?3 W1 E2 j" g- C4 k2 F8 y0 A
Randomization, 随机化8 _- q! U. O% r! q& A5 E9 @; e0 n
Range, 极差/全距0 H: m. B6 y1 {
Rank correlation, 等级相关4 y' j. Q+ k5 E1 P5 e& v
Rank sum test, 秩和检验
4 I9 i( J9 |! |' `9 o1 K; kRank test, 秩检验
, D* p8 i! Q( \% d5 JRanked data, 等级资料( J0 g" j7 N4 i' \' ]8 ?- U
Rate, 比率
W) Z$ w& |# y) ~& `Ratio, 比例
" c" Z% _$ `/ J9 Z' F5 ZRaw data, 原始资料& ?2 x! X" a6 @+ e. ?9 @2 a
Raw residual, 原始残差9 h0 P5 T( m4 [
Rayleigh's test, 雷氏检验
7 O5 i, Q' Y2 kRayleigh's Z, 雷氏Z值 8 d: `# R! O k7 E
Reciprocal, 倒数0 k# Z/ E$ o1 P7 r3 m
Reciprocal transformation, 倒数变换) g. @# _' v) f) c9 o7 @/ |
Recording, 记录/ y9 J9 }( J5 W# t' K
Redescending estimators, 回降估计量
& Z, F$ Y7 p; ]5 S9 i8 `1 D7 E2 ~( RReducing dimensions, 降维2 o8 r0 l; G$ N
Re-expression, 重新表达. z! c# o* x- n: P
Reference set, 标准组
* C+ K. E9 C- SRegion of acceptance, 接受域( [1 t9 b. Y6 H
Regression coefficient, 回归系数# P8 q& g: o$ n% _
Regression sum of square, 回归平方和
4 r) `" p u9 H1 y' r- A( v) VRejection point, 拒绝点
, F$ w, X8 O" V" x0 {* HRelative dispersion, 相对离散度; Y- q" u2 g% j
Relative number, 相对数
?: v: [+ K- z0 L6 M- p& ]Reliability, 可靠性
9 p4 F/ _( z9 } J+ H- nReparametrization, 重新设置参数
7 C) u `5 y+ r$ ]9 `Replication, 重复( \) _ C+ U4 H" F' F4 d* h' Y) U
Report Summaries, 报告摘要
- H9 |3 u& @. o x I( TResidual sum of square, 剩余平方和
9 A) P( l A/ v0 O6 QResistance, 耐抗性4 j# I5 f H" u8 n5 p0 @
Resistant line, 耐抗线
: [6 m6 w/ C" u$ ~" h, CResistant technique, 耐抗技术! X: Q- i) T' l W
R-estimator of location, 位置R估计量8 D- K3 Z3 @8 {. C; r( J0 m
R-estimator of scale, 尺度R估计量
; w- |% T, Q) e [; QRetrospective study, 回顾性调查
: R7 a4 y: P K! JRidge trace, 岭迹
2 m& ]& \) ^6 S6 x) b0 P5 |3 x+ }Ridit analysis, Ridit分析
6 a7 C# k! C1 f _" M, m, L' [4 pRotation, 旋转
% c4 D. r7 C0 J9 E" cRounding, 舍入
( f% v7 }/ ^8 B# ?- mRow, 行# \& U( y& q7 u+ P7 q( {( c
Row effects, 行效应/ `, p% l0 Q* p
Row factor, 行因素
1 a( u0 F, [: s5 j& }RXC table, RXC表7 o3 S H z- l J$ o+ i! S4 F
Sample, 样本& x2 s& Q0 U# O% U( e
Sample regression coefficient, 样本回归系数) \' v+ l- p% `- ^' m R2 S
Sample size, 样本量% T; n: ?/ @* z3 p/ H& s
Sample standard deviation, 样本标准差9 V' t" O: s1 V( V1 E: Z# B
Sampling error, 抽样误差. i9 k$ h6 ^" w# V
SAS(Statistical analysis system ), SAS统计软件包/ F& d1 N# }5 x# e+ |' C1 A) ~
Scale, 尺度/量表8 x( V' p3 I3 j/ O
Scatter diagram, 散点图2 g x; f4 P. {/ D: _
Schematic plot, 示意图/简图: J# W1 b8 |5 U2 u# c; j4 i Q* c
Score test, 计分检验: E" O8 i* T! o0 M! _
Screening, 筛检
. e, I [# W3 N$ gSEASON, 季节分析 " {/ V5 {: {: n5 t! ]* E
Second derivative, 二阶导数$ h0 R$ p: X( d4 W
Second principal component, 第二主成分
) P& {- I* z u# S9 r7 i' {SEM (Structural equation modeling), 结构化方程模型 0 z) w- d/ e, A0 V5 }) g) P1 a
Semi-logarithmic graph, 半对数图
- O$ b% u4 N* S& w6 U/ RSemi-logarithmic paper, 半对数格纸
! d4 j0 ^: W- a6 g4 n; l: oSensitivity curve, 敏感度曲线* `! `+ q8 l7 r: K: A
Sequential analysis, 贯序分析" h0 n! m" z A1 i* O0 o5 ^
Sequential data set, 顺序数据集
& B2 B' P1 E9 o7 U' E+ hSequential design, 贯序设计
, z' o3 f! u- ^7 E. ?5 r4 TSequential method, 贯序法; X% d w O2 `0 Q1 o6 m8 c5 \8 |
Sequential test, 贯序检验法) y d4 _! V4 Z, c) {
Serial tests, 系列试验 p; c/ ?* S7 ]5 }
Short-cut method, 简捷法
. b( x* }7 k6 g# hSigmoid curve, S形曲线' D+ V" c, C" y2 n6 ?- I
Sign function, 正负号函数
% V$ l4 `# {& ?Sign test, 符号检验
6 R; g2 @2 I9 y+ {# j' ~2 x1 h, qSigned rank, 符号秩
( U- n j) ?- x: mSignificance test, 显著性检验" F; p8 g# |4 a, j x
Significant figure, 有效数字
+ {+ q5 J1 j/ DSimple cluster sampling, 简单整群抽样
& r7 `" @; S( S# D1 i' ~) U) f$ cSimple correlation, 简单相关7 C) E5 k) e. U, q% Q0 ~
Simple random sampling, 简单随机抽样
' h/ W. U- U: T4 OSimple regression, 简单回归: h% D5 `1 q: D( F8 y$ d L2 l/ W
simple table, 简单表5 C, ]' E: x$ W$ r
Sine estimator, 正弦估计量5 Y( r4 W9 T9 K0 ^" b! ?. J1 k- d
Single-valued estimate, 单值估计 ]" e2 ?8 i k& A
Singular matrix, 奇异矩阵
+ I7 f- P3 X! I0 `- TSkewed distribution, 偏斜分布. Q# J1 v3 f' C; }% h, |! s7 w @, }
Skewness, 偏度 l5 a, q' M3 G
Slash distribution, 斜线分布
. `5 J) k+ P0 ESlope, 斜率$ g& o6 w1 g1 P u
Smirnov test, 斯米尔诺夫检验2 |# p/ r. n* ^, u$ Z; z
Source of variation, 变异来源
1 K* L$ K. _% a5 `/ RSpearman rank correlation, 斯皮尔曼等级相关
4 g5 g: [% K8 _Specific factor, 特殊因子2 c7 D$ H: c; \) q% j1 v
Specific factor variance, 特殊因子方差
6 e+ N7 y0 X8 [* _. t, [- z9 CSpectra , 频谱
; a) S4 L4 s7 RSpherical distribution, 球型正态分布/ Q! y0 ~' ?" b2 C8 a: w
Spread, 展布, {/ g8 j$ O8 R- {1 [; m
SPSS(Statistical package for the social science), SPSS统计软件包
/ Q8 |( L% }& c( KSpurious correlation, 假性相关! G; V0 D6 B/ W; h; o
Square root transformation, 平方根变换- C: L9 X d6 {3 T! z
Stabilizing variance, 稳定方差! [. Y% i; x' k
Standard deviation, 标准差
: P$ T$ r" |: H( |Standard error, 标准误
0 T. j" [; k# E z* d |9 `Standard error of difference, 差别的标准误) D' W1 n0 X) L+ H
Standard error of estimate, 标准估计误差
$ ?6 m1 B, S$ s* I* y# cStandard error of rate, 率的标准误/ I4 @$ Y3 A* D: j/ T2 q2 f
Standard normal distribution, 标准正态分布: i/ C' Z0 \- ?5 F2 z' B8 `/ ^/ h
Standardization, 标准化
7 c$ r# \0 `& i' a" c3 r2 y" t5 nStarting value, 起始值
4 ~' Q, f: f7 ?7 w' @Statistic, 统计量, U' u3 x6 v- S/ _
Statistical control, 统计控制, T6 W, R! T7 C& }" D/ [
Statistical graph, 统计图3 w6 C$ O6 U y' X7 }) i
Statistical inference, 统计推断
) p6 V' U5 [9 J$ i( a7 RStatistical table, 统计表
, n& }6 j1 v' C0 `6 E" z. ~Steepest descent, 最速下降法0 [& {2 F/ S8 r# z7 ~3 W
Stem and leaf display, 茎叶图
4 l% C2 o# C0 E' n1 oStep factor, 步长因子* G5 r/ w. J5 l, i
Stepwise regression, 逐步回归
6 e( B1 ~/ u4 j- j; A" X/ TStorage, 存
5 o1 A% |# v, ?2 H- c5 h4 uStrata, 层（复数）
" n" v. s. P# p( |) D7 q7 y( PStratified sampling, 分层抽样
' l3 f+ D9 i; C& w$ S3 f- _Stratified sampling, 分层抽样
$ k$ i% p3 v( W5 ~) l0 ~Strength, 强度
5 o- Y: E% I+ T# a) Z0 d3 yStringency, 严密性4 r; i. y4 ?: m7 ^5 P# z
Structural relationship, 结构关系
, X$ A" l* m$ D0 T4 VStudentized residual, 学生化残差/t化残差
; i& K" g6 O# ^4 c' ASub-class numbers, 次级组含量0 Q N9 {# m D% u! ^
Subdividing, 分割
4 J! m( L! J6 O" g; B r+ LSufficient statistic, 充分统计量7 T4 n3 k- i9 n, p' Q$ E' @. R/ e! {% Y
Sum of products, 积和
" j) Z; i- c, ]# f# W& n+ _Sum of squares, 离差平方和* [5 s5 r, H B
Sum of squares about regression, 回归平方和
5 Y) T8 J S# I& l) n r: `Sum of squares between groups, 组间平方和
) ?/ c3 i" j% g, LSum of squares of partial regression, 偏回归平方和
3 N* b3 x5 r, I4 _: ?Sure event, 必然事件) @6 _: r# \. E/ R; J( N# q- G
Survey, 调查
7 Y) f, l. d9 e9 m1 JSurvival, 生存分析2 u7 ~+ n+ M: f' E0 }
Survival rate, 生存率. I5 q+ _# ^8 c9 Y
Suspended root gram, 悬吊根图
$ I) [6 w0 r1 q3 P, O3 WSymmetry, 对称
. h n) g0 J. d: N& V4 O8 {+ oSystematic error, 系统误差
# c5 |% ~1 F9 jSystematic sampling, 系统抽样
5 F5 Q/ G) i: ~6 c7 bTags, 标签
+ d2 ]! {9 s4 HTail area, 尾部面积
( |( r! A/ W; f( N- S0 e- R9 W# STail length, 尾长' T( O R, `( K2 j
Tail weight, 尾重% \! [0 Z! b2 N# d% k
Tangent line, 切线2 x5 N( b- }' V% N; _
Target distribution, 目标分布
* O1 B# a, E3 [Taylor series, 泰勒级数
. ^+ W+ p% e2 N. L( ITendency of dispersion, 离散趋势
5 k8 ?0 I1 S4 jTesting of hypotheses, 假设检验' Y. m) V& r2 r* ~4 J6 |% I* Y
Theoretical frequency, 理论频数
2 m3 x+ m3 p0 K% x* _2 B8 S2 n- sTime series, 时间序列
! w* \. y6 Z3 @/ aTolerance interval, 容忍区间
6 J% [, g% ?! C/ ~Tolerance lower limit, 容忍下限
( r7 C- Y; ^; ^2 g* C: O/ jTolerance upper limit, 容忍上限
/ ^- |) A/ ?: G/ [$ Q+ r; F; Z; ?. r0 pTorsion, 扰率/ a9 g$ P4 w- O' y( j! J
Total sum of square, 总平方和
1 o/ U3 G/ J3 J% hTotal variation, 总变异9 [' m7 [. o, z% c. S6 {
Transformation, 转换
$ v. A: s" s o% b6 u9 ^Treatment, 处理* |: c/ k" b' F
Trend, 趋势
6 z" x7 D; H& L& d6 N ^" X( N VTrend of percentage, 百分比趋势
7 L, @( p( j% T) n; G: v( @2 d" @: {Trial, 试验
4 O" w( F f4 |" W+ Z9 STrial and error method, 试错法* ~ B, S7 K {" L8 R$ B: K
Tuning constant, 细调常数
+ q7 V: h2 [6 i3 v& Q2 K! a3 ]Two sided test, 双向检验
3 P1 M2 U% ], x2 LTwo-stage least squares, 二阶最小平方* A) O. H0 y) D, u0 h
Two-stage sampling, 二阶段抽样
5 h: p+ L$ J' ?Two-tailed test, 双侧检验9 g4 t6 n- z4 u0 _: @
Two-way analysis of variance, 双因素方差分析
+ p' Y f" i5 }" n& L# O+ J0 L6 STwo-way table, 双向表
) I" v) ~7 o8 d7 yType I error, 一类错误/α错误. z" } p: Z `4 I4 A, F
Type II error, 二类错误/β错误
( q8 b/ v; u( K) gUMVU, 方差一致最小无偏估计简称! A7 t3 D, q) h* K+ t9 F
Unbiased estimate, 无偏估计
" s4 Q& x, P% ~; S: O! j0 y/ B( ^$ P( J$ |Unconstrained nonlinear regression , 无约束非线性回归& S E9 D! f' C- |( c$ p7 v }; ~0 q4 G
Unequal subclass number, 不等次级组含量( e0 M0 x, c1 Z2 w9 ]" X$ A
Ungrouped data, 不分组资料- b4 Z4 y2 J0 {9 A- k
Uniform coordinate, 均匀坐标% Z I8 d! f: j' r6 Z& B$ T- _
Uniform distribution, 均匀分布" k f+ ]( K, v% O% u5 @
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计/ N# [' i* k& p# q! C7 n, F! V$ J
Unit, 单元+ v% \8 I4 }9 V* H4 {4 K2 ^
Unordered categories, 无序分类1 `, K" G+ U4 l0 V7 E [% C
Upper limit, 上限
- L5 A) o9 s* x! KUpward rank, 升秩, v+ N$ m0 w! q A
Vague concept, 模糊概念9 r) g9 D' p: [3 b1 l/ g4 X9 ~
Validity, 有效性2 ]9 C. n5 B8 b9 }
VARCOMP (Variance component estimation), 方差元素估计) {! i+ ?' _/ F) q9 A8 o% F" j
Variability, 变异性
8 H2 U6 t4 n9 p! ~6 ~Variable, 变量 B6 |9 i; V( ?7 |4 ?; l' u8 {
Variance, 方差
' ]+ S' w4 X- s: s# M# s) k" z. K5 uVariation, 变异
- A1 `. A J9 [5 x zVarimax orthogonal rotation, 方差最大正交旋转
4 v5 Z5 p4 o" t4 gVolume of distribution, 容积" ^, Q, `1 p9 `- S
W test, W检验3 N% e6 c2 O) e( |1 u- |9 d. _
Weibull distribution, 威布尔分布, I* ?* B. t8 Z, G* O4 Y" k0 ]
Weight, 权数
; I0 Y7 @" ?* N! oWeighted Chi-square test, 加权卡方检验/Cochran检验
9 f4 C4 d, b9 p6 Z0 PWeighted linear regression method, 加权直线回归
" n2 ?# c: J' ]% K3 e: F. lWeighted mean, 加权平均数5 d' R' W* U& K R
Weighted mean square, 加权平均方差
, g7 G- x( X- j. {8 BWeighted sum of square, 加权平方和
' E" ^; r9 k/ P N: T; eWeighting coefficient, 权重系数* e7 s! I5 H o
Weighting method, 加权法
3 F- F4 {7 I1 c# j0 X. @3 WW-estimation, W估计量! }5 g) {/ x# v+ z* r3 h+ f
W-estimation of location, 位置W估计量
9 ~+ \) i$ f0 r2 F3 a! mWidth, 宽度/ { [( M9 g7 G1 E" z& {
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
5 `2 x5 O7 I, f8 kWild point, 野点/狂点
8 A- c# Z2 _+ L2 M7 O1 [( vWild value, 野值/狂值
/ {6 W5 ]# K1 nWinsorized mean, 缩尾均值8 Y6 F2 D3 f2 f, n# }5 [; b
Withdraw, 失访 0 O K. B8 @6 M9 R* Y( X/ n
Youden's index, 尤登指数
: u* E0 I; s" `5 W* }% FZ test, Z检验
6 ~3 x* x* o6 Q% yZero correlation, 零相关
7 x" c% z8 i4 e" _ Z+ CZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
