|
|
Absolute deviation, 绝对离差
" _ z8 p3 }' V+ I+ c- t qAbsolute number, 绝对数
) F) y8 @" q7 WAbsolute residuals, 绝对残差
: m6 L2 k% o% S/ XAcceleration array, 加速度立体阵0 {. b4 T- H* C" }, h" i
Acceleration in an arbitrary direction, 任意方向上的加速度
7 K6 C) h. j7 i, c. b3 |: ZAcceleration normal, 法向加速度
0 l# t0 E, R) t( \+ }: VAcceleration space dimension, 加速度空间的维数
/ G0 }9 g; a3 B3 |- sAcceleration tangential, 切向加速度
7 w/ ^+ t5 t$ _. O6 ]Acceleration vector, 加速度向量- y0 i5 q8 J$ a) P9 X5 h
Acceptable hypothesis, 可接受假设( W# U2 v$ x1 K: e$ t7 \( l. O
Accumulation, 累积: k* u- x b! _8 a7 V9 ~- w4 |
Accuracy, 准确度$ J$ R1 r8 g5 y7 W
Actual frequency, 实际频数
, ]' _" }4 }' z" r' S) s, f$ pAdaptive estimator, 自适应估计量
+ Z: B$ F e) c' w& w6 w" pAddition, 相加
$ k3 I* E4 J7 N4 b7 F" \% CAddition theorem, 加法定理
* a! X4 J" m! n$ G) tAdditivity, 可加性
L: g' ]* z5 b. NAdjusted rate, 调整率
1 P* a$ y3 g( G1 U# BAdjusted value, 校正值. E$ Q. ]7 a+ V3 ^6 {
Admissible error, 容许误差
; s! y: Q' {" t" u& OAggregation, 聚集性
8 L1 d4 k" m/ @Alternative hypothesis, 备择假设
% r4 e7 X" T* H) e) QAmong groups, 组间
3 b+ l/ Q! t( x8 A8 wAmounts, 总量
k' _( T U+ \5 b3 nAnalysis of correlation, 相关分析
9 F9 r6 I/ p; W$ ~# E; }. zAnalysis of covariance, 协方差分析
9 j; ^& g: m$ S5 W; T, [6 s5 HAnalysis of regression, 回归分析
: a* G3 V$ v2 WAnalysis of time series, 时间序列分析6 _4 [" t8 U* l
Analysis of variance, 方差分析
$ Z4 o8 i# N! x* iAngular transformation, 角转换
: l' _* f0 W# x hANOVA (analysis of variance), 方差分析6 P' s: K2 x2 k( m
ANOVA Models, 方差分析模型5 S; ]. Q! ~/ K0 r
Arcing, 弧/弧旋! A$ `" P( d5 s4 F* n
Arcsine transformation, 反正弦变换$ Q& k1 S) m/ l7 w' Z8 m
Area under the curve, 曲线面积# z* }! j( n/ ]7 G- t1 ]
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
` W, Z* h4 V2 {; S) W1 e: F: QARIMA, 季节和非季节性单变量模型的极大似然估计
t; Y1 s+ d- zArithmetic grid paper, 算术格纸7 H$ ~- k* ^. o: ^0 M% b
Arithmetic mean, 算术平均数
* q* }* Q9 j# W* N/ bArrhenius relation, 艾恩尼斯关系
4 i; a, o6 @% T; s8 W) P: {Assessing fit, 拟合的评估# a/ @. j! O$ N: r
Associative laws, 结合律. B2 p# s& a, g/ k
Asymmetric distribution, 非对称分布' J J" {# m% e( _9 u# t' x: R
Asymptotic bias, 渐近偏倚
1 k9 [! T+ q" ^8 r# u4 Z0 g, d1 LAsymptotic efficiency, 渐近效率& ?" l' |) U9 F) h, N
Asymptotic variance, 渐近方差
$ `2 q* [7 u! N0 P. z; z9 U1 \Attributable risk, 归因危险度
0 i+ M. l7 y" t- `! @Attribute data, 属性资料+ g8 l0 O5 L" h9 O* n
Attribution, 属性
) Q" ^/ p0 N: ?9 Y4 q( A4 aAutocorrelation, 自相关! K2 d6 G7 X, N. {$ n& l/ I6 ]7 I5 ~
Autocorrelation of residuals, 残差的自相关
* L. O6 l) ?1 A9 V7 P0 |+ \Average, 平均数
; k( j9 S- J5 WAverage confidence interval length, 平均置信区间长度4 p: N" Y! n# V
Average growth rate, 平均增长率2 R! n% Y5 p( `% h5 ]2 \
Bar chart, 条形图
2 q5 j8 K. L* O& W2 ^! tBar graph, 条形图1 i2 P( G- l( z9 W3 m6 j
Base period, 基期
2 V! P8 ]/ y5 W, ABayes' theorem , Bayes定理6 |( E3 H8 T( V; k+ l7 Y+ q- Y
Bell-shaped curve, 钟形曲线
: w8 M8 Q, M4 `( C8 V5 T+ O7 zBernoulli distribution, 伯努力分布
) o/ F& A( h9 y* q! |Best-trim estimator, 最好切尾估计量; J7 I4 H. H* z% n) f$ z
Bias, 偏性
+ t! H6 |, y' c2 f; n0 M1 X: ZBinary logistic regression, 二元逻辑斯蒂回归
) h# E: T% d$ FBinomial distribution, 二项分布/ j$ Y7 b- N% G7 }: D% V
Bisquare, 双平方
( m, `4 a* h# r: v0 EBivariate Correlate, 二变量相关
|: P' R: T& s7 W! n; _8 x2 D' pBivariate normal distribution, 双变量正态分布
$ d& i/ K1 i. g" WBivariate normal population, 双变量正态总体% X' k1 Q) {+ c, z
Biweight interval, 双权区间
# O) f3 T4 c# {2 A) I wBiweight M-estimator, 双权M估计量 X+ A2 H8 Q% J. C: K
Block, 区组/配伍组
' I$ j8 f9 w- \9 WBMDP(Biomedical computer programs), BMDP统计软件包
' |4 k0 T" q5 {+ D9 w; m; xBoxplots, 箱线图/箱尾图# w8 C, o: o$ p8 ]6 x
Breakdown bound, 崩溃界/崩溃点
3 V3 X3 B+ y9 Y- j; xCanonical correlation, 典型相关
2 S$ n- E) a' V3 t3 f0 O* ICaption, 纵标目8 v j% l9 }& s, ^* [8 \9 z$ }
Case-control study, 病例对照研究
, q* D8 Z. U; j# _$ S# e3 jCategorical variable, 分类变量
, @/ Y1 ^9 c1 g" UCatenary, 悬链线
9 c/ B: I4 ^+ | B1 {; H* dCauchy distribution, 柯西分布
* G5 M& V7 W: j" `, h! u* m- MCause-and-effect relationship, 因果关系6 D0 Z8 w+ B+ B% F1 o8 ^
Cell, 单元
; `; Q. t& R: U* X B, D. ^& o, r" l3 I- @Censoring, 终检5 W$ {# `& c8 t' x' p( p% Y( F* |4 m
Center of symmetry, 对称中心/ @9 L$ [! g1 v0 j
Centering and scaling, 中心化和定标
. ^+ A. c3 P9 V8 ZCentral tendency, 集中趋势4 ?' Y$ B1 S7 Z# I
Central value, 中心值' ?/ U1 b- z% v2 q- V
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
) x; u" g! u2 q' pChance, 机遇0 j: p: W- d) A0 `, i, i
Chance error, 随机误差4 A8 N H/ ^9 w7 V7 K( j4 v
Chance variable, 随机变量
1 c& S$ b$ D& xCharacteristic equation, 特征方程
/ b2 L3 J# B$ JCharacteristic root, 特征根" H! f8 E$ {2 P2 U- ~8 \" g) x' _
Characteristic vector, 特征向量6 o: v, B: L- `1 R c- R
Chebshev criterion of fit, 拟合的切比雪夫准则. p, X) `* F4 H# m2 k
Chernoff faces, 切尔诺夫脸谱图$ t2 v8 I; x$ B
Chi-square test, 卡方检验/χ2检验/ l% ~' C, h" c
Choleskey decomposition, 乔洛斯基分解
2 p' W% l, `, j" } PCircle chart, 圆图
: a$ X- z& n* S# F3 @Class interval, 组距, v, u8 {; q0 `6 }$ W6 \- j6 C* Y
Class mid-value, 组中值
, \& k0 F2 ~3 T; _1 {Class upper limit, 组上限
) r5 E$ E3 n& ~( IClassified variable, 分类变量
& h' T: m# g/ p% a; j& dCluster analysis, 聚类分析* {* T9 ~# i @' B- U+ r" J
Cluster sampling, 整群抽样
& u* E% E8 E9 G9 T1 CCode, 代码
. P2 z% Z- S( q: E. @$ g* HCoded data, 编码数据" |+ b1 C' }$ S
Coding, 编码$ U2 N$ [- L$ F8 _: {# _( J
Coefficient of contingency, 列联系数
4 h9 G t; v3 k+ zCoefficient of determination, 决定系数
' M7 s* k$ C; p3 C, c) B) J$ gCoefficient of multiple correlation, 多重相关系数2 o, c% t- H( I
Coefficient of partial correlation, 偏相关系数
/ f, ]# J/ G1 aCoefficient of production-moment correlation, 积差相关系数
0 J1 o% q. e0 M" X* ACoefficient of rank correlation, 等级相关系数: i, C: K3 n( X4 l
Coefficient of regression, 回归系数0 G# ~8 I5 M4 n& @# X' I
Coefficient of skewness, 偏度系数
- r+ X8 ^: {+ w. E! vCoefficient of variation, 变异系数0 _& }8 @9 ^3 O0 O
Cohort study, 队列研究' F/ t. e: t9 N. {, R) _
Column, 列
) s* m' ^6 U0 q' I& g W) l0 X' ~Column effect, 列效应
/ ?4 u' N. z# G: CColumn factor, 列因素
" ^/ k1 G- u' c4 a9 A) aCombination pool, 合并) s h' R( ~/ f; N6 B' V
Combinative table, 组合表
, w% y# R5 c/ W- r/ Y6 V$ PCommon factor, 共性因子9 G8 r) }3 V6 ^$ B2 Z6 v% g8 Y
Common regression coefficient, 公共回归系数6 |& X, R. M# f6 P v1 W
Common value, 共同值% V4 `; ^) Q8 q6 U" F
Common variance, 公共方差+ e8 Z9 o1 F! J7 ~! T
Common variation, 公共变异
' L" W- ?# L2 w$ f) g5 B, G- ~1 hCommunality variance, 共性方差' z5 ]. k" `$ E
Comparability, 可比性
9 b6 S R# w) ^; _Comparison of bathes, 批比较
, }- Q; }8 U x3 |0 S9 @- HComparison value, 比较值
: W! m7 e7 _4 P, \3 L W1 eCompartment model, 分部模型( X' V8 @4 }: C- Z' I+ X0 P
Compassion, 伸缩
' w% ]! @+ f- O. }) L/ A. RComplement of an event, 补事件2 O. | Y: g- X- E; r9 w( {9 P, u" |1 \
Complete association, 完全正相关+ v q9 [& o3 y. K# k V3 C
Complete dissociation, 完全不相关
; f( d) R# y4 `0 FComplete statistics, 完备统计量
: P. K$ A5 H" N2 p3 C) r8 t# xCompletely randomized design, 完全随机化设计
# z( t* } `2 yComposite event, 联合事件$ v) M/ h" J6 @- K) j& y% H
Composite events, 复合事件
! D* q0 v B2 ^% [Concavity, 凹性
" J% r2 G, a/ `' tConditional expectation, 条件期望& h0 F6 D x* [4 R+ v3 f
Conditional likelihood, 条件似然+ n9 D. g1 T( v$ d# R
Conditional probability, 条件概率( @5 g" g/ n1 H: ^7 ~8 Z
Conditionally linear, 依条件线性' n# ^/ ]4 s5 ?7 a. s
Confidence interval, 置信区间% L% j7 h' D4 F( k" s1 D0 a U
Confidence limit, 置信限
; ?7 W& x9 r6 P( m5 wConfidence lower limit, 置信下限
6 E C* d; t1 GConfidence upper limit, 置信上限
8 T5 @& }8 x ~- y* B9 MConfirmatory Factor Analysis , 验证性因子分析
* s, Z1 ~2 b$ p0 \Confirmatory research, 证实性实验研究
3 X; O3 k2 b) f: xConfounding factor, 混杂因素& u" ]# Q9 Q! L3 `2 `3 ^* z" B
Conjoint, 联合分析# D4 Y- f% `; Z& k! l+ O
Consistency, 相合性
) o; @, s. u9 q" {Consistency check, 一致性检验
: |. n* i7 ?7 \! xConsistent asymptotically normal estimate, 相合渐近正态估计- G* m8 h3 u4 b: y! H- a$ U
Consistent estimate, 相合估计. w7 ~' ?; d2 g. J' ?
Constrained nonlinear regression, 受约束非线性回归
6 i. i8 `8 T2 g% O* ^Constraint, 约束$ a/ `+ v; M* s' B8 M( K5 R# X! N
Contaminated distribution, 污染分布) g# d2 P: j: V' F( n/ \
Contaminated Gausssian, 污染高斯分布
& Y8 Z2 m/ {/ Y9 J% |' MContaminated normal distribution, 污染正态分布
5 k* d. L2 Z3 S2 kContamination, 污染
; u, N1 w$ H/ y3 V" WContamination model, 污染模型
; l7 b, l" J* B/ uContingency table, 列联表$ M( M M: @* e/ t4 {
Contour, 边界线
1 v* T& ]% B* Z3 S8 A l' N# N& B5 VContribution rate, 贡献率
' E$ F/ G! ]) z5 F7 z4 k j6 g+ dControl, 对照$ B' q1 u( M; i" m+ |( h# w
Controlled experiments, 对照实验
7 R. L) d! u1 z/ o) rConventional depth, 常规深度
0 }! g/ U2 Z" E+ m3 g! q1 {Convolution, 卷积
2 f: K% I: Q! `" [& N( nCorrected factor, 校正因子. c7 p: L$ U" `
Corrected mean, 校正均值
6 U7 o/ o; Y4 g9 OCorrection coefficient, 校正系数, S5 m* }8 }# H" c1 L, ^: G6 f6 U
Correctness, 正确性! t- _- @9 m5 W9 T
Correlation coefficient, 相关系数; v- {% B7 y6 X: ?% J& e8 G
Correlation index, 相关指数' r* O( t; f. f# K: K
Correspondence, 对应 u' O6 d u" z' w
Counting, 计数
+ H; r: O( |9 U( W: U/ y: g1 u* iCounts, 计数/频数5 @: y/ O6 Z# e5 \$ L
Covariance, 协方差
0 s& O3 C; i/ u- k1 D: zCovariant, 共变 " E% N! A, ^- k% S, k
Cox Regression, Cox回归
- s, H$ @4 r8 |# S. ICriteria for fitting, 拟合准则
! [4 G: Z! J' P5 {5 OCriteria of least squares, 最小二乘准则
, Y j3 T9 X! @' j1 zCritical ratio, 临界比9 Y1 Y# M( V; T9 [9 F
Critical region, 拒绝域
V- q/ x; b" rCritical value, 临界值6 y8 P. V1 ? Z7 _' E
Cross-over design, 交叉设计
6 H, I7 x9 u9 Z! b! F4 kCross-section analysis, 横断面分析
. j7 B$ _. X. Z, lCross-section survey, 横断面调查
! Z3 w) i* V/ D+ M% w/ d# jCrosstabs , 交叉表 , F+ M, V/ X U3 O
Cross-tabulation table, 复合表
9 [" f, _/ Z/ Q3 V# |) r0 w/ ECube root, 立方根( H/ R& f* I9 E$ G$ e8 w' X
Cumulative distribution function, 分布函数
* G0 T. E6 h$ |Cumulative probability, 累计概率' {+ L" T1 P5 c
Curvature, 曲率/弯曲
2 r- i$ O4 B8 tCurvature, 曲率
" l/ E& t& y; ^0 [7 D, ^3 ^# CCurve fit , 曲线拟和
& K8 u1 t4 A1 }. v' VCurve fitting, 曲线拟合
% W% }* i+ j- k& w5 ?6 SCurvilinear regression, 曲线回归7 ~$ l- J4 l& ^* f
Curvilinear relation, 曲线关系* n# T6 ?6 T: Y1 \$ `
Cut-and-try method, 尝试法
% ^- B& l7 Z0 xCycle, 周期& j- C, K2 `# _9 a- R6 s
Cyclist, 周期性
$ D5 W/ U/ A/ L3 z+ i+ V! yD test, D检验) m/ ]5 }- b3 N' A
Data acquisition, 资料收集
% M; C! U, Z: y1 n, yData bank, 数据库* P+ T* _5 {6 }. C: R
Data capacity, 数据容量% g9 ]2 c+ k: U1 f& f
Data deficiencies, 数据缺乏, U" Q& X( v" J( y7 N
Data handling, 数据处理2 [: D& D9 d1 V6 z& W$ M% s
Data manipulation, 数据处理
3 Z- T* T/ ^5 m+ [$ m. @9 bData processing, 数据处理# |! _% J& A2 D- b0 q
Data reduction, 数据缩减
4 |: y6 i2 w$ u1 rData set, 数据集6 v+ V# d4 `2 z. ?( v+ e
Data sources, 数据来源8 Y. A: p6 o2 Z& [. a+ V
Data transformation, 数据变换, y; F' Y' A' S5 {7 w9 z% K
Data validity, 数据有效性2 q4 L( b/ s# V5 Q2 J1 U1 k5 h* q
Data-in, 数据输入4 |) n O/ O- K5 F
Data-out, 数据输出/ F: [8 W- ~8 a$ U M! T
Dead time, 停滞期
% G' d. Z$ m3 K3 pDegree of freedom, 自由度$ T V. }0 S& T2 C! U" ?
Degree of precision, 精密度) r5 r% M9 @+ _& c+ a' h' ], O
Degree of reliability, 可靠性程度
4 I" R' M r6 g$ QDegression, 递减/ E( ^3 g# i1 O9 I$ S# Z
Density function, 密度函数0 x& M! e* e7 I4 v) G; q4 |
Density of data points, 数据点的密度
+ q0 W) O1 _ K# `6 vDependent variable, 应变量/依变量/因变量+ J& `2 V9 z0 I) ?7 t. n" @2 {# b5 k
Dependent variable, 因变量1 W2 p9 C/ u; w" N9 \
Depth, 深度
, d# L2 | ~ N, |# KDerivative matrix, 导数矩阵 T0 O3 V4 S" W
Derivative-free methods, 无导数方法
4 g) |$ X( g; xDesign, 设计9 [* m, E0 J3 G9 {/ j. @9 D( j
Determinacy, 确定性
" G$ O* z7 c7 N3 |( I% pDeterminant, 行列式+ J- u Q7 \4 I/ H
Determinant, 决定因素& ?6 [; Q# v4 W2 \; y( \8 _
Deviation, 离差$ d/ V) R# r- @, ~% j
Deviation from average, 离均差
, N' [/ H) h: J& B$ g6 KDiagnostic plot, 诊断图! o, J) u6 R1 g0 W
Dichotomous variable, 二分变量
. U' E9 A- _7 D! x9 d. V" NDifferential equation, 微分方程. {, Q1 F( [) h- [4 H, d( \
Direct standardization, 直接标准化法
; H3 f, v. ]/ k! N( o4 CDiscrete variable, 离散型变量
! r( ^' t! v6 qDISCRIMINANT, 判断 ( u- W. N4 p. s! R# T( Y
Discriminant analysis, 判别分析8 k3 X- Y% u6 \/ Y
Discriminant coefficient, 判别系数
n; }0 A$ G+ G4 j$ t7 j) O ~9 {Discriminant function, 判别值. { J! i" T3 `4 a+ a5 _4 K5 M
Dispersion, 散布/分散度
$ G& b% Q& d# }( E) Z5 RDisproportional, 不成比例的
, C+ u5 v. u. A$ S9 w: b YDisproportionate sub-class numbers, 不成比例次级组含量! u* z( n& d# Q- t1 Y4 B( d5 t( p3 {5 m
Distribution free, 分布无关性/免分布
2 b+ ]1 A" `, QDistribution shape, 分布形状' d2 g! q- |8 |' |
Distribution-free method, 任意分布法
0 P/ X& R# m( q1 R. F+ ^Distributive laws, 分配律7 N, H7 ~+ N; C7 n0 J" g
Disturbance, 随机扰动项1 e& v; P; K. ]3 ^( i
Dose response curve, 剂量反应曲线
% i0 o8 b) R* Y* c1 TDouble blind method, 双盲法
" S9 q' s H Q7 SDouble blind trial, 双盲试验
8 P3 \$ Z8 h" F& d: `) Q( xDouble exponential distribution, 双指数分布
4 X8 `6 q# T& l+ G+ k5 W0 RDouble logarithmic, 双对数5 ^0 t) C. l/ U
Downward rank, 降秩8 n% a! B: Z/ Y, @( C2 N
Dual-space plot, 对偶空间图+ s6 `4 `( Z% w8 a* Y
DUD, 无导数方法
2 m7 e* X$ m# i: ADuncan's new multiple range method, 新复极差法/Duncan新法/ h/ S+ d) P( Z9 {$ a |/ W
Effect, 实验效应9 N( e+ ?* B- \& X3 g& L
Eigenvalue, 特征值" l3 ]& G/ O( l6 _$ r+ w1 p
Eigenvector, 特征向量
8 d$ f; ]" [1 I" {( g% x* JEllipse, 椭圆
# C! u' \# D9 i7 [- @. l% n! lEmpirical distribution, 经验分布% h, h ]" @2 d+ V4 {
Empirical probability, 经验概率单位: w, y# R+ g7 {; w: Z% q0 N
Enumeration data, 计数资料
/ @: j) v. O5 R2 [7 [- j3 g$ VEqual sun-class number, 相等次级组含量
' V/ ~. T8 f) {. ^" ]; `Equally likely, 等可能* g" h, g; ]% R( R; V" N9 x
Equivariance, 同变性' n2 v$ a5 o! B: p/ L( g: p/ `
Error, 误差/错误# B y9 _4 `; K" }! T
Error of estimate, 估计误差! }( a& o. E( ^$ ^1 j
Error type I, 第一类错误- |4 |' J( ]( f9 W, N$ ^
Error type II, 第二类错误
; M6 O i4 y: EEstimand, 被估量. V( L R: I6 a* H7 l1 r. q
Estimated error mean squares, 估计误差均方0 X0 M3 Q: N9 z: K' Y
Estimated error sum of squares, 估计误差平方和, |1 d. {% G) K9 ^/ Z' `9 {( e
Euclidean distance, 欧式距离
2 k# ` O9 l C5 ~2 s% @% _/ H' CEvent, 事件
7 U8 ?8 f7 \" ^6 oEvent, 事件
7 r2 l5 l9 {' [( _ U* j2 ~Exceptional data point, 异常数据点! H& u1 `. C g$ a
Expectation plane, 期望平面
( b1 } a3 E! DExpectation surface, 期望曲面
0 z6 k' x% @: |# d. yExpected values, 期望值4 d) \: X3 u" B- c S" h
Experiment, 实验6 q8 T8 {! R3 n/ D8 l2 C; y
Experimental sampling, 试验抽样% e4 ^) B. P2 ]
Experimental unit, 试验单位
. E5 B. a* L# E6 yExplanatory variable, 说明变量
, X2 r) j& g0 K, VExploratory data analysis, 探索性数据分析
0 Y, w# B5 F" k" X! vExplore Summarize, 探索-摘要: A. K3 Y2 \% R( l; Z
Exponential curve, 指数曲线( n( w% |4 [' B# t; H
Exponential growth, 指数式增长
" Q, ^- E; q3 k4 B9 h2 X& m1 UEXSMOOTH, 指数平滑方法 3 V- @. k" V6 \
Extended fit, 扩充拟合
( ?2 d6 e1 T, V$ b+ C+ }4 ^% DExtra parameter, 附加参数7 |1 Q/ h9 f& d8 ^* l
Extrapolation, 外推法
3 X0 p* b- M4 W5 u0 }8 N3 R/ pExtreme observation, 末端观测值
/ M- G' N2 A) F3 e/ v3 j! IExtremes, 极端值/极值
$ J. r! n+ l0 oF distribution, F分布) L& Y9 p9 W' E% X0 E$ A+ E! k
F test, F检验
6 w) E. h) m5 W, H9 `+ t( u, t2 u( qFactor, 因素/因子
* ?. T- m/ ~9 l" i# |9 D: WFactor analysis, 因子分析/ o8 P9 o+ o% C- z2 f G- b$ ^+ A c
Factor Analysis, 因子分析
, I0 E3 }% ?( ^) gFactor score, 因子得分
# x, `7 o3 n6 C2 X. HFactorial, 阶乘
. o9 _7 z3 M% S, l/ dFactorial design, 析因试验设计
5 Z) L6 U# k" D$ O) |" \8 @4 ]8 B: EFalse negative, 假阴性
, ^0 T5 T$ `9 P9 Y. t, z( z% \$ @False negative error, 假阴性错误
' B3 z4 i! w3 oFamily of distributions, 分布族2 J! K; u+ t- Z: Y+ q& c
Family of estimators, 估计量族" o+ W% J3 m+ L! T" p4 R
Fanning, 扇面
3 C# ]% j- I3 Y' W3 l# d! SFatality rate, 病死率
% q7 r" P5 }' cField investigation, 现场调查
' j. o6 f4 Q8 v8 S0 c6 GField survey, 现场调查
) Q6 f7 c5 c5 C4 K7 O, ?1 r) rFinite population, 有限总体) H) t* j; T6 O$ N- n
Finite-sample, 有限样本
0 V' Q. y+ [6 d3 U/ J7 y# X* CFirst derivative, 一阶导数, @! p- u5 P( |5 z4 A/ v
First principal component, 第一主成分+ X2 D- G4 h& T) d
First quartile, 第一四分位数4 f9 j0 w$ K, U. V
Fisher information, 费雪信息量
, E4 X3 D; w) u9 l/ H7 P* A# v# Z% fFitted value, 拟合值5 f5 j! @# z; ~, q& a" S! n
Fitting a curve, 曲线拟合
+ \0 \! q7 u4 R7 r7 v/ bFixed base, 定基
: i1 q5 f4 X! l3 Z- V4 YFluctuation, 随机起伏
& U. I* V% k3 G8 f+ \Forecast, 预测
& I' U! I& w' x2 H) A$ m0 E; x; ?3 g1 }1 NFour fold table, 四格表9 I& l: y4 B+ D
Fourth, 四分点9 Z; \* P5 _& X- R. J8 s' `
Fraction blow, 左侧比率
: T! r, s) O5 A0 J+ ]3 PFractional error, 相对误差
% f) L# _3 `, n- e" w2 `Frequency, 频率* m1 W/ V; J0 ?" N
Frequency polygon, 频数多边图
% F7 |9 Z, Z2 [7 SFrontier point, 界限点
, ]; p% r4 C9 n% a; ]' {4 S2 A( `Function relationship, 泛函关系
' t2 d: S$ b5 ?. N) pGamma distribution, 伽玛分布; M2 }0 d! @0 {
Gauss increment, 高斯增量# g% w# `" Q! a" ]- B
Gaussian distribution, 高斯分布/正态分布- B" h1 F% G' `2 J5 ]
Gauss-Newton increment, 高斯-牛顿增量 [ w' b* W+ l ^+ z% @+ I6 b* W
General census, 全面普查# W2 x6 c5 P. L7 U
GENLOG (Generalized liner models), 广义线性模型 2 x D: a# i# c: a( G: T
Geometric mean, 几何平均数2 |7 }. `9 V8 w. j& Y& R1 t( j
Gini's mean difference, 基尼均差
) e' H3 k: f' X* @( W8 wGLM (General liner models), 一般线性模型
$ ^- C8 \( V/ E- j- SGoodness of fit, 拟和优度/配合度9 J- S) Y. u9 r9 M! N1 Z! `
Gradient of determinant, 行列式的梯度7 c9 o. [, x* D4 m B- u
Graeco-Latin square, 希腊拉丁方* r5 [' N( S) i; ^2 ~6 |7 \; \7 d
Grand mean, 总均值
' B2 m/ a3 \, M8 M. zGross errors, 重大错误% f7 s8 n5 _3 q: C; g3 G
Gross-error sensitivity, 大错敏感度. q6 i3 t5 ^, g% ^9 V- j. O
Group averages, 分组平均
% m1 G4 |9 P$ ?2 @+ OGrouped data, 分组资料
% N6 U6 u4 S- h; b. j. ^ w6 k/ lGuessed mean, 假定平均数
1 a2 n' o4 c0 l+ X, U0 ?* K! gHalf-life, 半衰期
' H1 l- A8 S3 D9 O- X" KHampel M-estimators, 汉佩尔M估计量
" q" O- d5 o% [& Z5 ~% ?& ]Happenstance, 偶然事件
$ e6 l4 I& ]7 T" F' g5 qHarmonic mean, 调和均数
# C) r8 } V0 }9 B+ `Hazard function, 风险均数. ]5 B. _: ]& }
Hazard rate, 风险率
9 W4 j- B8 w, p# m- XHeading, 标目 7 g& E& i# @! E/ \) o0 s
Heavy-tailed distribution, 重尾分布& D# w& X. j% u; R; a# w
Hessian array, 海森立体阵% ]8 e! t# m o" U9 w
Heterogeneity, 不同质3 y+ w+ n; ]0 K) G5 [ d
Heterogeneity of variance, 方差不齐 # [: _) ?; v( a5 A" \+ G
Hierarchical classification, 组内分组; o+ Q% ^1 M1 L7 n8 \
Hierarchical clustering method, 系统聚类法
0 u0 |8 g x7 K* R( Y& gHigh-leverage point, 高杠杆率点
# i( g: l9 N! e. NHILOGLINEAR, 多维列联表的层次对数线性模型
* c0 M7 A+ [5 {% K/ g& {8 Y) O' {Hinge, 折叶点
& { ]4 z) K+ ]7 |* FHistogram, 直方图
; Y0 n9 _* z0 r/ f& Y) IHistorical cohort study, 历史性队列研究
7 O/ b8 W0 J5 M/ ~4 H1 eHoles, 空洞
. a+ u/ j, B% x$ G" k, hHOMALS, 多重响应分析- t5 U' ~8 S& J$ L
Homogeneity of variance, 方差齐性( }- _4 l- l" P2 B! X9 [4 {( G
Homogeneity test, 齐性检验
$ `& Z9 ^. a3 d/ IHuber M-estimators, 休伯M估计量
/ j1 o, {8 e. k! cHyperbola, 双曲线+ y9 i& R) Z* T1 m' \# K2 G3 u4 p
Hypothesis testing, 假设检验4 ] N( I5 V* p# m+ D- g9 i
Hypothetical universe, 假设总体1 ?, a6 `' V- D
Impossible event, 不可能事件, I, y% X! T; Y {
Independence, 独立性* x6 x+ U, M( o, i- p# X" H9 A
Independent variable, 自变量% N' ?% G6 X9 V. z: w1 K9 f# d
Index, 指标/指数
}, E+ l. `8 Q5 o! h' P7 @Indirect standardization, 间接标准化法
z. T8 I; C9 jIndividual, 个体
8 _1 D/ O, C* J& T% x2 NInference band, 推断带4 m! Y( A2 T" Q0 E, _
Infinite population, 无限总体4 e7 ]5 Z9 o( p8 v% s7 b2 h3 A5 G
Infinitely great, 无穷大
6 `3 s# }) X" I. y; ?Infinitely small, 无穷小( B: Y7 p& M! j4 b- N1 m. g
Influence curve, 影响曲线
9 _) G! P$ ]; u* G! P2 K0 t/ rInformation capacity, 信息容量
4 _+ F+ R% [' m2 U1 J* qInitial condition, 初始条件
2 j. n( G% m$ a" K4 ]+ W- sInitial estimate, 初始估计值. g0 C: ^% r8 G; ^: d
Initial level, 最初水平$ u2 ~3 P: F3 B$ m
Interaction, 交互作用
5 `. m0 v: v8 C' R aInteraction terms, 交互作用项
( V& F: {( D7 n' a. W' f2 IIntercept, 截距8 Q4 F. L) p$ Y- F2 e" A: a& S4 j
Interpolation, 内插法
5 @! @3 E2 _0 i0 O& {Interquartile range, 四分位距
3 K! |* k2 N8 w X$ k3 PInterval estimation, 区间估计
: d- D8 \" F O: \' k- oIntervals of equal probability, 等概率区间
0 O" }" `0 T% k6 ]+ TIntrinsic curvature, 固有曲率
& T" J4 H+ T6 J% N0 `Invariance, 不变性
) ^9 P. ^' f, H8 p/ IInverse matrix, 逆矩阵! v9 K' x" M; P- }9 y
Inverse probability, 逆概率( W h0 F- v/ w* b" r
Inverse sine transformation, 反正弦变换) R- a# h3 H- E3 c8 ^8 y* U
Iteration, 迭代
$ h6 d0 p* l8 q. ~Jacobian determinant, 雅可比行列式1 B8 V6 O0 p7 U7 |3 u/ d. p" O
Joint distribution function, 分布函数$ N+ t" w- u( w7 G6 A8 m) E
Joint probability, 联合概率5 U9 a5 i; r) O! R6 w9 z4 J
Joint probability distribution, 联合概率分布+ V6 I5 S5 x$ z* ]5 ^5 F% c3 m
K means method, 逐步聚类法9 i7 Z) N8 D) S j4 G: A. b8 }& m
Kaplan-Meier, 评估事件的时间长度
$ s Y3 |/ u$ ]" C6 P' OKaplan-Merier chart, Kaplan-Merier图( _. v* {+ C5 w; `; i: a9 [
Kendall's rank correlation, Kendall等级相关2 _4 E8 V5 l7 S2 D b
Kinetic, 动力学
- X, P% ?$ N' H7 O2 K- }Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
$ u; X: x, E! J. _Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验( P, Y) ?, w f5 @6 I: F
Kurtosis, 峰度2 K; c! g* U# i9 M& F" P7 O
Lack of fit, 失拟8 @0 m4 Q' W" A3 e) [
Ladder of powers, 幂阶梯
' ~* X" B' W; J- a+ OLag, 滞后
) L: G! t+ ^1 M& g. TLarge sample, 大样本
& @. g& y/ Y, Y/ Q' v; tLarge sample test, 大样本检验
; N3 {( E( g: w/ b( B- }9 bLatin square, 拉丁方
% Z- F+ ?; u4 TLatin square design, 拉丁方设计
{1 @- L% n4 U% ZLeakage, 泄漏
0 L, Z* r/ e1 J3 ULeast favorable configuration, 最不利构形
# c, P$ T0 a9 b/ |% ULeast favorable distribution, 最不利分布4 Y# L, s0 H! |2 H* Y! c
Least significant difference, 最小显著差法; y7 L) R" A9 @# L$ s* b: i4 [
Least square method, 最小二乘法! k4 X8 m3 j9 M' W% b/ `) ?! H6 o9 d
Least-absolute-residuals estimates, 最小绝对残差估计/ o3 }$ g: r2 Y
Least-absolute-residuals fit, 最小绝对残差拟合
0 S7 S: l4 Q; h$ L- l5 M, n& b& _Least-absolute-residuals line, 最小绝对残差线
+ a Z1 t% k/ l7 H; ]Legend, 图例
' t2 t. K9 L/ @- P' fL-estimator, L估计量& w5 e6 h5 y& d
L-estimator of location, 位置L估计量
- v6 O T; }/ a r. cL-estimator of scale, 尺度L估计量
# F$ L1 I( B/ {+ U7 p! r6 FLevel, 水平
+ ?2 D; t- B5 f8 S0 @3 ILife expectance, 预期期望寿命& `: X# S/ K1 E0 n1 _& M: c
Life table, 寿命表
# z' m7 q. l' D& SLife table method, 生命表法
5 A; F8 v# z8 j0 ?$ l- K! a1 A7 s- zLight-tailed distribution, 轻尾分布$ }1 n! {- M1 s+ n. z
Likelihood function, 似然函数
, x0 p4 E5 C jLikelihood ratio, 似然比
" a4 G$ v& v9 t/ Q1 b1 tline graph, 线图0 L! [) G; @; @- P' P) O
Linear correlation, 直线相关
; S3 e/ ]( f! W8 L2 C6 QLinear equation, 线性方程* b' n; i* Z: R- m
Linear programming, 线性规划
0 P, i7 m& T& z" M! K/ X9 `Linear regression, 直线回归
- a% ]9 J: Z3 Z* HLinear Regression, 线性回归
, U, Z/ i, L" u: ~; }: bLinear trend, 线性趋势, n( ^) Z% C4 `
Loading, 载荷 & A+ a+ G/ y D8 T( X
Location and scale equivariance, 位置尺度同变性
) ^" G' h" ?2 U! K, u. |: _Location equivariance, 位置同变性
4 A) s0 |3 u* s% ^& _! s' l/ j/ ELocation invariance, 位置不变性
3 f- S: Y9 k- r# ^1 }, xLocation scale family, 位置尺度族
' E: b$ e4 s! z* [' e2 KLog rank test, 时序检验 . e" h+ c! v) Y5 l# ^; `
Logarithmic curve, 对数曲线
1 } D' d( m# h9 L; _0 @' pLogarithmic normal distribution, 对数正态分布
7 n/ F; l4 I: M- ^Logarithmic scale, 对数尺度
& ]0 ?- f/ Z4 V& QLogarithmic transformation, 对数变换
9 A8 V6 Q3 ]% `) a1 V6 r/ hLogic check, 逻辑检查5 s5 V( e& V9 N2 n7 K
Logistic distribution, 逻辑斯特分布& M( E1 u- ]! l3 f4 \6 o# \
Logit transformation, Logit转换
+ _5 |+ I& ?, _1 B2 n# f$ T0 SLOGLINEAR, 多维列联表通用模型 6 ^) A( g6 A# z3 \
Lognormal distribution, 对数正态分布+ H- O7 F# X$ ~5 ?3 E& {# s+ }* ^
Lost function, 损失函数
- @; w" Q# p* D! c5 DLow correlation, 低度相关* P$ O2 _% R: E& o1 D% g
Lower limit, 下限
5 u2 [1 O. v# m jLowest-attained variance, 最小可达方差) |# n: o- o$ |7 s+ C5 q) g
LSD, 最小显著差法的简称
7 d: `+ e% @# l/ Z& \Lurking variable, 潜在变量, [0 J0 `* \" a. L* J( ^
Main effect, 主效应: m1 z9 |% m) R& \" i/ e/ V
Major heading, 主辞标目' o: u3 ?3 n; X* y+ `/ D* g
Marginal density function, 边缘密度函数) K) h `# g" z5 l
Marginal probability, 边缘概率& ?7 P3 g' U% x: [! R
Marginal probability distribution, 边缘概率分布4 ?. a. E& v. ^! }# D/ d- L! D8 C" n
Matched data, 配对资料
+ J( m5 F2 S7 O" [8 jMatched distribution, 匹配过分布
" a" o- B4 D7 t0 AMatching of distribution, 分布的匹配3 k, L- [1 `! n1 D2 k" B" N
Matching of transformation, 变换的匹配) s6 u& o* k. k8 I5 M ?9 F$ p9 R
Mathematical expectation, 数学期望5 Q4 P8 ?' o8 l/ a5 y3 b1 e/ q/ t% A
Mathematical model, 数学模型
1 z4 @8 E$ l* ~7 WMaximum L-estimator, 极大极小L 估计量
6 a% t/ i6 U& @) ^+ ?Maximum likelihood method, 最大似然法$ H* [: G3 R! i. B% W
Mean, 均数9 h! N1 W5 a: u s4 ~. T4 ]
Mean squares between groups, 组间均方
# l. _$ ?8 V9 E* zMean squares within group, 组内均方
& C1 a) t) `! v5 h6 c1 `- yMeans (Compare means), 均值-均值比较
# @8 Q7 d: k: y4 g3 J3 G+ GMedian, 中位数- a! T# K/ W% z7 b
Median effective dose, 半数效量
8 q3 ~0 O0 Y9 pMedian lethal dose, 半数致死量
# `7 n! t( G- @# F; }- YMedian polish, 中位数平滑
3 {4 D6 T8 Y; q+ I7 q! {Median test, 中位数检验
& j5 N8 W- O0 G7 a1 h$ NMinimal sufficient statistic, 最小充分统计量
$ Y; E8 I7 I5 u+ PMinimum distance estimation, 最小距离估计, X, u- U4 S$ P0 W
Minimum effective dose, 最小有效量; `$ I* [3 c: Z+ `
Minimum lethal dose, 最小致死量5 \2 ^: p& @9 f% P/ y
Minimum variance estimator, 最小方差估计量
5 l) Y, t1 H7 c% p. F O+ z: g/ i4 `5 RMINITAB, 统计软件包' u7 J2 P Z' U1 h3 F
Minor heading, 宾词标目
$ }* i5 F) z, G" S6 kMissing data, 缺失值
3 z7 m8 q0 c" A/ }* ~4 h0 }Model specification, 模型的确定0 s* G# o# X; `& ?; ~
Modeling Statistics , 模型统计# g% `1 n! h! t; g* e
Models for outliers, 离群值模型! c3 c; e" r1 Z& i3 W( l' o4 z
Modifying the model, 模型的修正
D% @% P7 k' ?Modulus of continuity, 连续性模& p0 c- \3 t8 a0 L
Morbidity, 发病率
! f( @5 n/ A' ZMost favorable configuration, 最有利构形
5 G& Y9 `, m0 Z S+ |' j( c- dMultidimensional Scaling (ASCAL), 多维尺度/多维标度
: b4 ^: X& e, E& c9 P5 a5 I; h+ U, M$ Z ~Multinomial Logistic Regression , 多项逻辑斯蒂回归) P, P U: [( }1 V7 m) P
Multiple comparison, 多重比较( W1 F. w; m& t$ k; C& P: Q2 a
Multiple correlation , 复相关9 t! Y9 `# d. j$ o
Multiple covariance, 多元协方差8 T' V4 g3 }5 \5 [
Multiple linear regression, 多元线性回归
5 a7 j0 \( I- p: M; V' k+ Q qMultiple response , 多重选项
1 `1 y" C4 ~% d: ~6 K8 e, YMultiple solutions, 多解1 f& _% B' s& ^, ?7 ?5 ^7 U
Multiplication theorem, 乘法定理
% r4 p: M- l+ k1 q: t; eMultiresponse, 多元响应' p: {* p5 A0 x3 h) P
Multi-stage sampling, 多阶段抽样2 p! t2 R' e0 [; l8 |- M5 P
Multivariate T distribution, 多元T分布
3 y5 @9 i8 C4 {# p) Z4 n4 oMutual exclusive, 互不相容* z! j0 S7 A/ w- @" ?9 r
Mutual independence, 互相独立
0 S: H$ l* x0 f- {- ?" _' yNatural boundary, 自然边界
! V3 x, ^+ b8 @1 u0 HNatural dead, 自然死亡* K" i0 R6 V" q u7 F
Natural zero, 自然零
+ C" e& }" t# k0 } n" UNegative correlation, 负相关
. K7 Z4 X! V1 k4 u" Z1 @Negative linear correlation, 负线性相关+ G% J& u4 {+ M! G' M3 u2 n9 w
Negatively skewed, 负偏 \" L' f6 w9 L* S0 o, U* n' f9 W, s
Newman-Keuls method, q检验
+ ~+ ^3 {. n R: X, mNK method, q检验+ o) h/ h6 t: g K
No statistical significance, 无统计意义6 P; \+ N( m5 e$ X
Nominal variable, 名义变量; V' Y, l! M% j( M' c: \+ j. F
Nonconstancy of variability, 变异的非定常性6 X( u: C" s; N+ g
Nonlinear regression, 非线性相关
5 v/ p1 F$ E! s0 uNonparametric statistics, 非参数统计1 k6 Y5 T! e* q( G/ f
Nonparametric test, 非参数检验
# K3 V/ ^5 |- wNonparametric tests, 非参数检验
7 t" f; o! t" _6 `2 pNormal deviate, 正态离差
" l4 H, P4 {7 x& w6 g* jNormal distribution, 正态分布2 K) ~4 H4 l9 r7 d
Normal equation, 正规方程组" R3 j/ l. ?4 J6 |3 W
Normal ranges, 正常范围
: c+ ~& s" n' d& P" XNormal value, 正常值- E l1 G& r, H& c/ \7 s% b, ?
Nuisance parameter, 多余参数/讨厌参数
" q6 m. D! p u- k- t5 XNull hypothesis, 无效假设
% m, d/ I; `5 M, ^* k* rNumerical variable, 数值变量
) e: i' d: N1 d/ i' ?% t' G) ZObjective function, 目标函数) _8 L& Z; b$ n3 Z/ U4 L
Observation unit, 观察单位! ?. V- P: q5 R) b
Observed value, 观察值
3 J5 Q3 e. N3 R7 Q, oOne sided test, 单侧检验
7 y' l' O( p/ i3 P6 ?* ?One-way analysis of variance, 单因素方差分析+ D a# }% ?4 a& y
Oneway ANOVA , 单因素方差分析
! @* M2 S* l5 D9 Y# IOpen sequential trial, 开放型序贯设计+ X' O5 v* V# c# X' @8 s9 l' ^
Optrim, 优切尾
4 p- C' `0 h( U/ v( pOptrim efficiency, 优切尾效率
" L! U, ~: R. Y" i0 ?) tOrder statistics, 顺序统计量
8 g- T3 g* g! r; Y7 qOrdered categories, 有序分类2 L5 Y+ v" N+ n) H1 R
Ordinal logistic regression , 序数逻辑斯蒂回归
; N+ o( b/ _6 POrdinal variable, 有序变量/ `0 |6 @; D1 t; D8 S
Orthogonal basis, 正交基; _/ u z; Q o% m& b/ s& n$ U" A, R
Orthogonal design, 正交试验设计
& H% A1 C) |( u- dOrthogonality conditions, 正交条件
7 S, j8 p4 T; ^" F3 d8 QORTHOPLAN, 正交设计 . w9 {, ]/ H, d! u
Outlier cutoffs, 离群值截断点
. A9 [4 z9 a& [3 ]- c+ S7 I5 uOutliers, 极端值8 z' \" G9 H5 [3 {4 a. i& r( _
OVERALS , 多组变量的非线性正规相关
, i" t, T8 y1 x, ^$ MOvershoot, 迭代过度( L: b6 i! W' t; A; k* n. E
Paired design, 配对设计3 e4 y, ^, F2 z3 q, ?4 C
Paired sample, 配对样本
5 x2 \( T, J7 L/ l) y5 XPairwise slopes, 成对斜率
4 o a+ L4 P7 A* ~$ a0 l; zParabola, 抛物线
8 ?' g$ G2 g( D. L7 VParallel tests, 平行试验
( I* y8 r$ J% ?. Y( x2 SParameter, 参数
9 R7 ~7 q" k: Y9 L- V! I0 ~Parametric statistics, 参数统计
2 \: [' ] c: M% j* {. xParametric test, 参数检验1 B* x/ c1 G' {8 }3 f* a R6 G" a
Partial correlation, 偏相关' e; t8 I m# n' O( d
Partial regression, 偏回归& C- V" H9 Q) h
Partial sorting, 偏排序- F+ G1 k4 W s6 Z! G4 L4 R
Partials residuals, 偏残差8 `" [/ L. `) s
Pattern, 模式
& m4 I/ g) Z# n& W3 J* e3 R# iPearson curves, 皮尔逊曲线# r+ O& ^. X/ Q6 n7 F) w) ?
Peeling, 退层 q, }, `; T/ S
Percent bar graph, 百分条形图/ O) x3 A3 F* P- H( C8 n% c
Percentage, 百分比
" G# p. \/ H& z$ UPercentile, 百分位数 a; W' m1 o- ^. ^. c/ M9 s
Percentile curves, 百分位曲线- d. ?" V" {9 Z1 I( I+ ]( u
Periodicity, 周期性
1 [; n9 ]$ h9 O* A5 U, f0 ]Permutation, 排列; K# h* J( c, v0 u
P-estimator, P估计量7 j" Z/ `9 L! X; D/ r; q# Y' E
Pie graph, 饼图6 {9 ~$ }5 F5 u3 R8 f1 g3 x4 P- G
Pitman estimator, 皮特曼估计量( C; n6 v: m7 d& ~8 u: r' R, \2 L
Pivot, 枢轴量
4 m, ]* W9 b7 a6 c( XPlanar, 平坦0 w) B5 c( s1 ?, D+ k4 H( K, o2 ^
Planar assumption, 平面的假设) b0 v" B" R' i' K T
PLANCARDS, 生成试验的计划卡' }/ x: h. i9 w* I1 e, N
Point estimation, 点估计6 R# R9 b& h; p- T! L& O) C
Poisson distribution, 泊松分布
) t. ^ e9 j- r& d" @7 \Polishing, 平滑
" T. @& r& N: \Polled standard deviation, 合并标准差
( M& V7 P' _0 ]( H. lPolled variance, 合并方差
# C9 v3 m+ d, z! n5 hPolygon, 多边图
4 V0 D/ R$ ~, v& N, Y# iPolynomial, 多项式
; v& K( V3 j" X, B. A7 t$ BPolynomial curve, 多项式曲线; G' }' H2 b! m, y
Population, 总体
' [& f) m) |1 e4 gPopulation attributable risk, 人群归因危险度
5 D6 r& G! K: ~Positive correlation, 正相关$ n! N; I$ @& S1 R! j' O% e/ A
Positively skewed, 正偏
# Q. M' L7 t( L- E( E% RPosterior distribution, 后验分布
4 e9 l* z1 m0 b7 [5 k8 g( ]( UPower of a test, 检验效能: @1 v; e5 V6 i
Precision, 精密度& S) Y C- L9 a4 h2 J4 d
Predicted value, 预测值
2 n- c G0 [. X0 l' ^Preliminary analysis, 预备性分析
( ]$ }4 e; P' \7 n+ |Principal component analysis, 主成分分析" ~9 `1 e5 O- n6 \7 `3 ^; R
Prior distribution, 先验分布
* m' o' J: W9 m4 \) TPrior probability, 先验概率
( ?6 k4 q$ l# l, M- b& ^: jProbabilistic model, 概率模型" g/ J$ D1 d3 Z6 f6 y+ S u
probability, 概率9 [ i; P( F8 s6 L5 b+ M
Probability density, 概率密度- X4 Z. k- P3 p7 Q u
Product moment, 乘积矩/协方差
6 o/ v0 f M* ]Profile trace, 截面迹图8 _1 l0 k5 c7 }5 s# Z- Q* l
Proportion, 比/构成比
9 R8 k6 f, o% Y! {% w. g+ SProportion allocation in stratified random sampling, 按比例分层随机抽样' B9 ]0 R" S% X/ F; |, b( v
Proportionate, 成比例
$ M, ~$ {: O. T1 D+ LProportionate sub-class numbers, 成比例次级组含量
m$ F0 z3 m/ \$ M. Y! P* EProspective study, 前瞻性调查
; t/ ]0 _" i- D# t* ?) F5 zProximities, 亲近性
& F3 {4 w g( MPseudo F test, 近似F检验
7 F |9 z \- I. `2 MPseudo model, 近似模型
; W E% k7 J5 o' S# Y! I IPseudosigma, 伪标准差- [; L, Q( u( G5 F2 W
Purposive sampling, 有目的抽样
D* _# A: M+ JQR decomposition, QR分解
4 y' f2 s7 b- a0 t2 yQuadratic approximation, 二次近似
?( ^+ R. |7 fQualitative classification, 属性分类
8 n+ \$ h0 d2 W. CQualitative method, 定性方法/ v3 _/ a% }8 V" L
Quantile-quantile plot, 分位数-分位数图/Q-Q图
0 Q: t2 J, f8 h) d; n, xQuantitative analysis, 定量分析2 [9 Z3 G3 P' C7 J
Quartile, 四分位数
7 j" p- T( n1 F! h! y# g4 V2 `Quick Cluster, 快速聚类; v+ e5 p- `% ^! S# ~; j
Radix sort, 基数排序- E5 w1 V6 d- o: J0 m
Random allocation, 随机化分组
) G5 R0 C" Q0 I( j. d* NRandom blocks design, 随机区组设计
: k; s: H( S: Y& \4 gRandom event, 随机事件
0 M8 e/ M" f# k9 L/ x7 fRandomization, 随机化
6 T% A" s1 Y Q* P7 GRange, 极差/全距$ {% ^: J. d# ~# H; h( p
Rank correlation, 等级相关8 ~# x9 W, }/ b! y0 `
Rank sum test, 秩和检验
3 z3 v* d, ]5 C3 A# w) s3 C, `3 _Rank test, 秩检验: Z8 |; M5 D& G6 ~# H$ x; ]* R( J
Ranked data, 等级资料
2 M7 `, L3 q4 p$ G9 ?# |Rate, 比率
# R& [+ M0 v$ Y0 \ S1 Y) SRatio, 比例
; O8 A/ v+ E+ s" Q8 tRaw data, 原始资料
% H x. M" L9 G: b0 E# TRaw residual, 原始残差
" O6 Y; g+ l) @- gRayleigh's test, 雷氏检验- k, @8 s8 y c! \4 D! _
Rayleigh's Z, 雷氏Z值
5 [, S. M$ D3 z4 X. F+ }3 uReciprocal, 倒数
6 k$ g# z O. H' R4 nReciprocal transformation, 倒数变换" v1 F2 R* B- F' U+ E
Recording, 记录3 E' D. R: M6 y% L( v" }) \
Redescending estimators, 回降估计量3 k& P# I9 K) v3 i4 X' w: p
Reducing dimensions, 降维
, }& u* t' s- p1 }( o1 W- l- D- G, vRe-expression, 重新表达
( W2 l7 o5 A0 }. n# L0 C* X. dReference set, 标准组- U9 K5 Z4 J% d! A
Region of acceptance, 接受域
0 K S! w8 V1 ]* O, D. D) HRegression coefficient, 回归系数, ^- y2 S% K& w! g
Regression sum of square, 回归平方和2 U/ D. X8 Z8 N/ o
Rejection point, 拒绝点
$ s1 i6 U. R% f! |7 r' nRelative dispersion, 相对离散度+ j$ K; k6 b3 Y0 [7 w' r! Z7 |
Relative number, 相对数
; r& `7 J2 M5 DReliability, 可靠性
+ y, F6 [$ A6 z, v3 fReparametrization, 重新设置参数3 o) z( b5 h7 q; H4 J j
Replication, 重复
; B5 w2 c4 o% f w. g/ nReport Summaries, 报告摘要
4 {) q9 V$ d4 iResidual sum of square, 剩余平方和! q, A5 j. y7 W" u& G( r3 r
Resistance, 耐抗性& S* C5 W7 u% @) b5 k2 d* E3 g
Resistant line, 耐抗线9 _! L' \& ~% i7 d+ F0 e. l
Resistant technique, 耐抗技术
, [5 a, p) o3 \3 R3 vR-estimator of location, 位置R估计量
- p$ B( \9 {# L& y% PR-estimator of scale, 尺度R估计量
$ [& K* Z2 @ s6 [2 xRetrospective study, 回顾性调查$ M2 U5 J1 p9 I( V& E9 y
Ridge trace, 岭迹, ?' ^4 z/ e H/ g$ w
Ridit analysis, Ridit分析! `- x6 l. `5 g( ~
Rotation, 旋转
) }! g+ Q- {& y/ s3 hRounding, 舍入
" |. ]' n- C, L, a4 l% lRow, 行
$ x- N+ M+ k$ ~, YRow effects, 行效应" ?; e4 |$ D" a6 c0 X
Row factor, 行因素
7 t6 O. S/ X& b+ URXC table, RXC表6 K% u8 I1 E4 V1 Z" a- x
Sample, 样本
5 M$ k& X$ }" x& B; lSample regression coefficient, 样本回归系数
; J/ H6 F( S# WSample size, 样本量
( q( d# O4 o: e- O$ h5 ESample standard deviation, 样本标准差
; s; [4 [9 V- L: NSampling error, 抽样误差
- G# F) B$ U$ ]9 v6 u, H3 bSAS(Statistical analysis system ), SAS统计软件包. |. w: {9 V9 h2 J' U
Scale, 尺度/量表+ J D. B4 V- z" U
Scatter diagram, 散点图
: N& P. [; N3 q$ l) A' WSchematic plot, 示意图/简图
& ~ T/ q. m7 Y( bScore test, 计分检验
) ?7 v. } I1 E+ r l- ]: @Screening, 筛检 K+ D: N( z6 g7 T* e1 U
SEASON, 季节分析
9 h! a9 I k; M8 j0 d4 }8 J7 gSecond derivative, 二阶导数
1 e5 h' \' H& oSecond principal component, 第二主成分& a2 q. d( y! g. Y# Y% V
SEM (Structural equation modeling), 结构化方程模型
" T+ X2 z: J( M. bSemi-logarithmic graph, 半对数图
. f; R f7 _$ N5 uSemi-logarithmic paper, 半对数格纸
- H! V7 w+ Z3 y1 F! N" c+ R: ^Sensitivity curve, 敏感度曲线
' i! H- G% p) x$ j2 q4 g' R0 f1 ]0 ZSequential analysis, 贯序分析, c7 ]& c; t+ @. c" j0 Q3 M! _
Sequential data set, 顺序数据集4 m& f2 K2 E4 ?; K+ a0 L
Sequential design, 贯序设计
4 K S" J- V3 g3 {* y- {Sequential method, 贯序法# N- ?( x$ w1 |3 V% Z- Z; S. [2 \
Sequential test, 贯序检验法
' r! A H4 d) q) Y" JSerial tests, 系列试验* c' c, Q( D, u5 i
Short-cut method, 简捷法
3 a3 x: p$ X2 @0 VSigmoid curve, S形曲线9 t1 P. ?9 m. o) Y9 u4 W9 L
Sign function, 正负号函数' t; n& e8 n+ s: O
Sign test, 符号检验0 U( g ^* j- _6 R& x
Signed rank, 符号秩% d' G8 s4 }0 T: M
Significance test, 显著性检验 `$ M6 W/ A, Q0 S9 m. [& x
Significant figure, 有效数字
; C, L- i! z0 E! pSimple cluster sampling, 简单整群抽样0 b1 Y# g9 B7 f9 q
Simple correlation, 简单相关
) r! x( _. R3 ~Simple random sampling, 简单随机抽样
' | C( T4 u) }Simple regression, 简单回归( O3 i. r- b9 o0 o
simple table, 简单表5 ^& r o2 K/ r+ _% d/ n
Sine estimator, 正弦估计量3 Q% _$ w! B! A/ F; C5 }8 \
Single-valued estimate, 单值估计; V/ h2 k' y8 i. k% }, R" V! J
Singular matrix, 奇异矩阵1 Z Z- x( e4 x, \( a& ]# s% F
Skewed distribution, 偏斜分布
: m1 D! \# m% D' pSkewness, 偏度, p: ^. o2 N- D
Slash distribution, 斜线分布
5 U, F. [; I1 G& I9 W3 h/ n8 c5 KSlope, 斜率; v) y# ]3 @9 e, e' z1 h
Smirnov test, 斯米尔诺夫检验
0 B% i* v6 S8 U9 y* NSource of variation, 变异来源, c/ v9 e0 P2 g/ Y8 h; ]2 q
Spearman rank correlation, 斯皮尔曼等级相关3 H9 n5 o' J% e# t; A3 q
Specific factor, 特殊因子
' ^/ W5 n. d7 FSpecific factor variance, 特殊因子方差; g1 F/ F# Z. [: f8 Y7 ?" F
Spectra , 频谱" b9 {6 i& D* F4 H8 z
Spherical distribution, 球型正态分布* e. i _- o8 n/ r& r
Spread, 展布0 L7 ]4 F# U. G' \% h
SPSS(Statistical package for the social science), SPSS统计软件包
( \3 u* C8 j2 `2 J" M' {# vSpurious correlation, 假性相关0 \5 W' p; O% R9 B0 m% J
Square root transformation, 平方根变换9 h2 Y0 b5 l9 p! P7 K
Stabilizing variance, 稳定方差5 U1 m& g6 x; t5 Y6 M9 I
Standard deviation, 标准差' x# v2 X1 C3 }8 u; K5 i; y
Standard error, 标准误
6 N0 v6 d" g& }* Z' ] DStandard error of difference, 差别的标准误
% e' _- ~. t, Y: RStandard error of estimate, 标准估计误差
/ Y, T# u6 u! R' \! L3 G+ ~Standard error of rate, 率的标准误/ X$ U: d& ?6 A0 B8 e- F4 F2 F. \
Standard normal distribution, 标准正态分布* z) X; V2 M# ~4 B
Standardization, 标准化$ `% R' b6 q9 F- U; O
Starting value, 起始值
% J2 o1 C% A1 X( p1 Y, HStatistic, 统计量
0 Z) g6 I% m# ^ @2 x* CStatistical control, 统计控制
6 i' m8 t$ w1 KStatistical graph, 统计图4 f. o7 _( s5 P; L2 z
Statistical inference, 统计推断
?7 d3 o) c7 ^$ oStatistical table, 统计表
: t; Q- r1 b. K; j' u: ~Steepest descent, 最速下降法, B$ D( [3 h9 I+ q/ H
Stem and leaf display, 茎叶图
+ v3 H7 {4 u4 U8 m' G+ BStep factor, 步长因子6 ?$ `% Y2 Q u; u( c; L+ F
Stepwise regression, 逐步回归
) `8 z" o7 Z8 K/ u* e2 ^1 W- `: ~Storage, 存
+ }6 ?3 p R5 S; tStrata, 层(复数)
5 ]& d+ R1 Y9 d. }Stratified sampling, 分层抽样
/ H8 v" q/ R- Y' t- YStratified sampling, 分层抽样3 f* R3 g6 B) w8 Z2 S: h
Strength, 强度1 q6 W6 O" k5 i' W
Stringency, 严密性9 T! F! C, W* u2 S' e
Structural relationship, 结构关系
* J1 g5 }2 d$ q( {; H7 e+ XStudentized residual, 学生化残差/t化残差
$ ? l+ V8 {( v! o6 D' K% N W5 [Sub-class numbers, 次级组含量
9 T9 ]0 @6 i0 K! BSubdividing, 分割! J: E: ]# }2 Z! d4 }" Y; W: ]
Sufficient statistic, 充分统计量
5 Q$ c" y ~7 N+ A% l% XSum of products, 积和9 A7 g# K7 ^; }% Z1 |
Sum of squares, 离差平方和
# S9 b5 E3 e" T: Q/ ?Sum of squares about regression, 回归平方和
5 J+ g$ p3 n! w5 o* T; r+ f9 m& m- J; jSum of squares between groups, 组间平方和
' S0 \; l& {1 y+ L9 H2 USum of squares of partial regression, 偏回归平方和
# f! i O8 n; @ d; gSure event, 必然事件
; l- r0 c4 ~9 {0 sSurvey, 调查
! m" H5 c# z3 H9 rSurvival, 生存分析
0 z; Y8 A4 g5 DSurvival rate, 生存率
& g# [3 N3 N3 r6 V* R5 ^" S: KSuspended root gram, 悬吊根图7 P' H) p7 M- ^. M8 z7 w
Symmetry, 对称% m$ E$ `( v& q- s+ O
Systematic error, 系统误差7 g6 T3 N c% P4 q! u
Systematic sampling, 系统抽样" X3 G% V( P1 d
Tags, 标签# I$ y6 i5 w3 }1 F
Tail area, 尾部面积8 I" {" R# h" B5 T+ d1 i
Tail length, 尾长8 t/ V* t6 q ]7 h7 p
Tail weight, 尾重
" Y; |5 |/ k9 N b* J. D/ UTangent line, 切线% p6 e4 `9 {/ d/ X% q& ]6 j+ ~
Target distribution, 目标分布$ i$ `- y( a" x& U7 Y6 ~) P* m% j7 Y
Taylor series, 泰勒级数* y& Z4 K7 {& I& ], N+ a. e4 e" F
Tendency of dispersion, 离散趋势4 B) D4 V+ ^- i( t* X& U8 z
Testing of hypotheses, 假设检验
" J: m2 }' S+ V0 gTheoretical frequency, 理论频数1 k( w q3 o5 r# L+ {0 D- @
Time series, 时间序列
$ p" F, j" A! J# j _% U, UTolerance interval, 容忍区间
, U6 k E9 d, x& g" [Tolerance lower limit, 容忍下限
# ~) _; V$ b. f; HTolerance upper limit, 容忍上限6 [5 D4 d( h6 F4 u; ^1 t
Torsion, 扰率8 H8 k4 v! d9 D4 y2 y7 e9 f
Total sum of square, 总平方和+ {1 } u( \& _# v0 O
Total variation, 总变异; Y" z6 k: R2 C0 G$ Q" ^
Transformation, 转换6 k3 H5 N+ |7 ?+ @
Treatment, 处理
: b( C$ m& Z u/ l3 eTrend, 趋势$ m! y% d" `% E' Q7 `
Trend of percentage, 百分比趋势
S. ~5 L7 O- GTrial, 试验
0 g# C" ^6 B# qTrial and error method, 试错法2 M; o' ?/ J" T
Tuning constant, 细调常数
9 @4 Q) D1 _! s+ d/ H* H d: ZTwo sided test, 双向检验; a c3 `/ {2 P' A( C1 e
Two-stage least squares, 二阶最小平方
; C6 m. s; ^: k- rTwo-stage sampling, 二阶段抽样
; w5 L) R+ q& s* \9 k2 M3 BTwo-tailed test, 双侧检验
" b& u0 z% x: z; q9 q2 o4 w: vTwo-way analysis of variance, 双因素方差分析8 T) f. v! ?3 P, z3 n
Two-way table, 双向表9 {) ~. \5 x, i1 X" M3 J6 w
Type I error, 一类错误/α错误) n0 V1 A' i8 B7 p! T/ |, G
Type II error, 二类错误/β错误
# p" r. W* t# b: p7 ]9 uUMVU, 方差一致最小无偏估计简称. o/ u5 L4 I7 D% R9 [, v
Unbiased estimate, 无偏估计
h8 F0 S4 v7 g6 {) B# l( JUnconstrained nonlinear regression , 无约束非线性回归
9 L$ u7 s1 G& i2 Q& P5 o0 cUnequal subclass number, 不等次级组含量& q5 p) J/ H- d! |& y1 K1 O6 l
Ungrouped data, 不分组资料0 ^1 B1 J! ^. i( F2 p$ a
Uniform coordinate, 均匀坐标) L+ i: }% t+ z( j6 d9 l: n( D
Uniform distribution, 均匀分布
8 t2 O8 T6 v0 a9 h% j6 e: C8 B( D; `Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
! P& |9 _3 M* m* W: kUnit, 单元2 G4 Z% ?- d7 A+ D# k
Unordered categories, 无序分类6 s' O. l5 K6 d8 \
Upper limit, 上限) ~* a$ W, ` V' o2 R0 p0 V9 ? R
Upward rank, 升秩3 `, @% R+ g( B
Vague concept, 模糊概念
7 c4 ^1 n% `( v l& a. {& KValidity, 有效性4 ^1 K6 |9 Q. S
VARCOMP (Variance component estimation), 方差元素估计
b1 K7 w! C, X) x3 {4 ]6 J; t+ jVariability, 变异性& M1 a4 C; ?- @* d" f
Variable, 变量2 K- D% Z1 r3 C& z+ i) M+ r5 q2 }
Variance, 方差& \* b5 l' ?: J1 M/ H
Variation, 变异7 B+ S4 `+ z+ Q- w
Varimax orthogonal rotation, 方差最大正交旋转5 f- Y( j/ ~4 t& w" A
Volume of distribution, 容积
" i/ q( j- K/ o; v# aW test, W检验2 e% S) P2 A: i; Q8 D* Q5 X+ z
Weibull distribution, 威布尔分布; g, p/ I" O3 d0 w: \
Weight, 权数3 l) U! f0 C; G4 }9 d7 V
Weighted Chi-square test, 加权卡方检验/Cochran检验1 m4 Q* ]5 a) Z: l: f4 H
Weighted linear regression method, 加权直线回归
( {* M# L: L/ M# [* ^% OWeighted mean, 加权平均数- I& A$ l$ s" A
Weighted mean square, 加权平均方差- @$ r' t0 K' D7 }2 Y& C" Q
Weighted sum of square, 加权平方和
: j6 ?* [9 i- n7 nWeighting coefficient, 权重系数
4 y, m# p9 {, W7 k( c+ tWeighting method, 加权法 / K2 y- g) A2 u! u* H% V
W-estimation, W估计量
% l) w9 M) _3 UW-estimation of location, 位置W估计量! P0 h. @) u( _3 P0 L' N
Width, 宽度
( m! Y/ R( S1 j0 Z0 YWilcoxon paired test, 威斯康星配对法/配对符号秩和检验6 W7 X% j: y1 B! ^. m p q
Wild point, 野点/狂点* a" A# v2 c) _/ e G8 k: t2 [
Wild value, 野值/狂值
- x1 a' `( V. J! u* b/ IWinsorized mean, 缩尾均值
, }9 | `( r/ A" _& x$ QWithdraw, 失访 7 h( f" G2 Y8 I
Youden's index, 尤登指数0 ]5 A. |( P: S" l4 L9 v
Z test, Z检验
/ Y# j: v1 `% G' { x0 MZero correlation, 零相关' C, x9 W5 N% i/ B, h; i
Z-transformation, Z变换 |
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