|
|
Absolute deviation, 绝对离差+ E3 i! g$ ]9 d; l+ ?% T' l
Absolute number, 绝对数- b' T( b8 n, \4 n1 V
Absolute residuals, 绝对残差; H, T$ m9 y& R% o4 M7 A' x0 z
Acceleration array, 加速度立体阵
$ q3 W8 D4 p+ ]8 cAcceleration in an arbitrary direction, 任意方向上的加速度
: g3 b a0 z$ _$ L) _Acceleration normal, 法向加速度# N+ |- h! X8 R) l2 h6 ?
Acceleration space dimension, 加速度空间的维数
1 G8 s6 h" W" n* YAcceleration tangential, 切向加速度
& {+ \* d4 U' I7 F+ M R LAcceleration vector, 加速度向量# x9 k7 d8 @4 V$ ^# q' K2 m, n7 F
Acceptable hypothesis, 可接受假设
u/ ?8 v( v; j: }3 K0 z5 IAccumulation, 累积+ @& @7 E2 l9 z& m: D; y
Accuracy, 准确度
% M- ]/ G& Z" C% `+ }Actual frequency, 实际频数
' U" {# q) x$ T' sAdaptive estimator, 自适应估计量 A, r# k* ^9 M9 v, @; x
Addition, 相加+ V/ }* ^! z/ J8 P" T9 m+ N' x
Addition theorem, 加法定理, F5 E5 A, P" J$ ~
Additivity, 可加性9 g2 \8 K* ~1 @) V; K
Adjusted rate, 调整率
7 v: q8 v* E* M! p; {Adjusted value, 校正值4 n) z) Z/ {8 v& M- p3 a
Admissible error, 容许误差% c# h* P& c% Q6 U8 h
Aggregation, 聚集性
2 U9 E% W3 q: I4 e4 Y5 x5 rAlternative hypothesis, 备择假设
$ h. u( e3 W( p1 B) RAmong groups, 组间
5 v" I) ~7 m7 H" HAmounts, 总量
y s0 u2 f/ E( gAnalysis of correlation, 相关分析
0 c- a' i1 d8 n& f+ kAnalysis of covariance, 协方差分析5 {' F0 m5 F0 y( V) c
Analysis of regression, 回归分析
& {$ ~8 ]- {6 Z. EAnalysis of time series, 时间序列分析6 X( H; o. V8 y# ?; u/ I
Analysis of variance, 方差分析
4 n( Z) M; ?/ e/ lAngular transformation, 角转换
) i! E; V8 B' p0 n% EANOVA (analysis of variance), 方差分析
4 Q1 D$ j: N6 |6 s0 ~- zANOVA Models, 方差分析模型
, d$ M6 y& b5 w7 ~Arcing, 弧/弧旋
1 B; Z0 o4 B8 Z8 T2 DArcsine transformation, 反正弦变换9 d+ [5 b" I" \4 h5 Z# J8 l4 p$ p
Area under the curve, 曲线面积( q$ O9 m; U) Z2 U0 Z ?
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
4 l# {) z6 q, LARIMA, 季节和非季节性单变量模型的极大似然估计
, N! X8 V7 t" F0 t+ v) ?3 M3 DArithmetic grid paper, 算术格纸4 m! @+ \- m' |( A2 q1 r9 o: z6 A
Arithmetic mean, 算术平均数" h8 L: y# I* ?- D4 V% M7 J$ S
Arrhenius relation, 艾恩尼斯关系! F8 \& p% t6 S. r5 v! y4 K
Assessing fit, 拟合的评估" U. s# C' P+ F
Associative laws, 结合律1 k8 P/ y7 X1 M4 M+ [+ `& m
Asymmetric distribution, 非对称分布4 P" `6 S3 ]! z# b' G
Asymptotic bias, 渐近偏倚- n5 O( t" {. ]- r/ L+ S# p
Asymptotic efficiency, 渐近效率9 [- z% s/ k" D' ^; y
Asymptotic variance, 渐近方差
3 ^4 X" F0 W: `' p0 n: |Attributable risk, 归因危险度
" j2 J- Y8 r: LAttribute data, 属性资料; H- R6 ?1 [% _: I" d* B3 r% F
Attribution, 属性! m. o4 p! D3 ?* k
Autocorrelation, 自相关
# R1 n# }! E U/ c9 BAutocorrelation of residuals, 残差的自相关/ r% ~ F) O3 H7 i5 l3 I/ k0 w, N3 \
Average, 平均数
1 B8 b" L- c! j t8 H8 ^( PAverage confidence interval length, 平均置信区间长度' i- g7 b" m/ \* \4 C% [0 G: |
Average growth rate, 平均增长率
- f" N" c; z' C5 mBar chart, 条形图4 J5 x' R$ P# M% m2 w& m9 B
Bar graph, 条形图$ h0 s" h" D1 X2 M3 l7 W
Base period, 基期
4 ^1 Q+ y0 s* U$ u. G8 H2 O; hBayes' theorem , Bayes定理; D. W$ L, v$ G! C2 s. q
Bell-shaped curve, 钟形曲线0 u$ h" V5 w$ T2 j1 r: M
Bernoulli distribution, 伯努力分布/ \# Q4 s/ I3 ?; f3 A
Best-trim estimator, 最好切尾估计量0 j: w% j0 D7 S/ l# b
Bias, 偏性
. M8 F* q+ Q: K# u# D3 l [* O$ tBinary logistic regression, 二元逻辑斯蒂回归6 S( m0 j0 }" y% m4 ~ E: _
Binomial distribution, 二项分布
, j4 K0 V5 w% a5 nBisquare, 双平方* u% I8 O' V+ X0 b" j/ R
Bivariate Correlate, 二变量相关) b; X2 K( b7 T. l
Bivariate normal distribution, 双变量正态分布# L: a$ I' Z/ P0 I/ l
Bivariate normal population, 双变量正态总体. T3 u$ \3 s6 t" @6 k& K( l- b
Biweight interval, 双权区间& G O, t: [. G7 t& `7 n
Biweight M-estimator, 双权M估计量) z4 k# T3 ~0 h# S# Y. g
Block, 区组/配伍组" m. n$ I& \' E1 F5 U4 J% h! F
BMDP(Biomedical computer programs), BMDP统计软件包
A5 i e% ?% tBoxplots, 箱线图/箱尾图0 @* X: B2 l" P8 O2 m
Breakdown bound, 崩溃界/崩溃点
/ G& [" X; r# D& \4 C x8 OCanonical correlation, 典型相关
$ ?* ~) h' D5 {+ S4 p$ [Caption, 纵标目9 V2 E# b2 W! z
Case-control study, 病例对照研究% ^! i# I7 q3 Y" n( N# j. z3 t
Categorical variable, 分类变量
# v$ o, n: `1 l ]) ^Catenary, 悬链线
* c) J! J( w+ fCauchy distribution, 柯西分布
" l) n: r: p" v- G6 n2 k" n( pCause-and-effect relationship, 因果关系6 q' |& h* l8 F' E8 Q3 f
Cell, 单元
8 E- A* y: p4 o( z" pCensoring, 终检
7 ~, t1 ], i1 |: o# RCenter of symmetry, 对称中心- q+ ^9 @" g1 o3 a# R
Centering and scaling, 中心化和定标8 U4 @, u" N, Y ?. Z$ y( `" z w1 P) C
Central tendency, 集中趋势# q$ o7 S5 B B- |9 U
Central value, 中心值4 `+ e" l2 f0 L5 l9 v# {/ U Y
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测3 _' _/ l. D+ [4 t
Chance, 机遇
& H. b* u7 z9 p, Y) ? mChance error, 随机误差$ F" S( C( [) h& C
Chance variable, 随机变量
6 L x$ t8 q' @$ k% }2 P! LCharacteristic equation, 特征方程
5 D4 x; M# [9 Y. o( N( a6 LCharacteristic root, 特征根0 H6 Y$ H0 u$ A2 I) i+ Y
Characteristic vector, 特征向量% v4 i' c% ] b' i2 l, j
Chebshev criterion of fit, 拟合的切比雪夫准则7 F1 ]8 f1 d$ N1 [3 N
Chernoff faces, 切尔诺夫脸谱图" }, X% n& X1 C) A
Chi-square test, 卡方检验/χ2检验, ~' k- |' v5 L: Z2 P$ {; J/ ]& ~
Choleskey decomposition, 乔洛斯基分解
5 g) Z7 Y) V D% V. y% S0 oCircle chart, 圆图 ! c4 D+ A- I ^! h. Y2 g
Class interval, 组距
3 S+ M4 `; Z5 b1 UClass mid-value, 组中值
% O+ `/ e8 g4 c! D; nClass upper limit, 组上限
2 Y0 G1 Z7 |+ J- y' e' l5 Y' Y; ?# BClassified variable, 分类变量
) z+ y8 g* z( f6 z2 @Cluster analysis, 聚类分析0 y; a# K4 P, b5 y+ _
Cluster sampling, 整群抽样/ T# y2 W( l/ K! T- q+ w
Code, 代码
& p' u* I. Z! h. G: z" K5 Z) PCoded data, 编码数据
. I3 x& _+ X" O5 L5 U& NCoding, 编码
+ ^7 Q9 H/ D; U3 w# VCoefficient of contingency, 列联系数
: i4 @. l; d% Q9 G8 l. A2 V( N3 nCoefficient of determination, 决定系数) x. X, ^$ I6 x" p2 |+ V
Coefficient of multiple correlation, 多重相关系数, y9 d- M; U4 j* ?; I
Coefficient of partial correlation, 偏相关系数/ ]" W# n% ^' `) D
Coefficient of production-moment correlation, 积差相关系数
1 W! J* n9 a( s" R8 ICoefficient of rank correlation, 等级相关系数
/ {3 ]. l- y2 }& x9 bCoefficient of regression, 回归系数& ^" p1 ?2 r5 G/ O" m
Coefficient of skewness, 偏度系数+ q9 N8 ^: ]( G" c8 T1 n9 }4 i) G+ f
Coefficient of variation, 变异系数
. T/ @; p0 e! WCohort study, 队列研究
& _! ^8 c! W( @Column, 列" T3 G2 o4 I# D) g; ~, Z6 p
Column effect, 列效应
; L4 W! E; T8 a/ Z7 @Column factor, 列因素
$ ~( H0 R$ S* h- H8 b7 QCombination pool, 合并
s1 p* S6 A5 R7 R. j# DCombinative table, 组合表& ~- n' m' V# x1 F
Common factor, 共性因子
; Z/ @5 G( O7 v F9 sCommon regression coefficient, 公共回归系数
/ V# S) A+ A9 H6 u& r; lCommon value, 共同值) w T0 m3 E% y+ \- x
Common variance, 公共方差
# v- t6 F) ^* n: a3 RCommon variation, 公共变异
! Y1 E7 V0 Y8 O. N% ]; [* lCommunality variance, 共性方差
$ K% E3 T8 q3 rComparability, 可比性
3 S9 \# C8 E3 l% f! dComparison of bathes, 批比较; g8 c2 r) ]+ `! L7 l
Comparison value, 比较值
0 q) H# J0 \5 M" UCompartment model, 分部模型
/ N6 S$ w& D6 k' _. HCompassion, 伸缩
* ^8 t- h- X. a+ }% N7 V4 YComplement of an event, 补事件. u7 k4 P; c7 e1 }9 Y k
Complete association, 完全正相关7 W$ V( U8 s! {# w$ e- y
Complete dissociation, 完全不相关: S* ]+ v( F, n2 x" ]
Complete statistics, 完备统计量) ~, B5 u8 w3 L
Completely randomized design, 完全随机化设计2 J* `% Z+ E2 T$ ~
Composite event, 联合事件) k) ]) h7 L# r6 ~2 j
Composite events, 复合事件
9 o5 O3 P- }6 ~5 l& A7 X3 r3 dConcavity, 凹性
2 p% Y% m, x8 [. P9 y% Q) WConditional expectation, 条件期望
' X: ]* A* [; MConditional likelihood, 条件似然4 {. y ^2 X( E
Conditional probability, 条件概率
/ }# }* h2 \* b3 U J# TConditionally linear, 依条件线性; X' \$ i" g" H) m. p" O
Confidence interval, 置信区间
% M! S* O3 k% j; HConfidence limit, 置信限
s6 ]0 y- x+ Q: KConfidence lower limit, 置信下限$ `3 W0 Q# n1 p v9 ~! s, @8 G6 \
Confidence upper limit, 置信上限" k, ?4 ~6 Z9 b* t" f1 h% K
Confirmatory Factor Analysis , 验证性因子分析
4 d/ f8 s* t; x) E# m5 `Confirmatory research, 证实性实验研究 s5 ?8 u6 m7 _* [
Confounding factor, 混杂因素; C2 q# Z* e9 I
Conjoint, 联合分析
2 O" V$ }& H7 `) g0 j; b+ u( pConsistency, 相合性
9 K7 Q- C% g% b* WConsistency check, 一致性检验
0 e( }% x' Q- ?Consistent asymptotically normal estimate, 相合渐近正态估计
, @4 s8 j! V2 Z1 sConsistent estimate, 相合估计- {# b6 ^/ `: {9 E, ~4 _9 f
Constrained nonlinear regression, 受约束非线性回归9 Z! H3 D7 z/ t( F
Constraint, 约束. q0 h* s! c# d E
Contaminated distribution, 污染分布$ N( Y# k A* t
Contaminated Gausssian, 污染高斯分布
$ Z: W r/ ]. `& Z( I, NContaminated normal distribution, 污染正态分布5 \/ ^ D: Y7 W' ^5 U3 G( g: p
Contamination, 污染* y9 p# d4 s5 Z* `
Contamination model, 污染模型
7 W$ |2 [9 {1 a; ^1 \* M" sContingency table, 列联表) U/ M `9 z, b
Contour, 边界线. z; g r3 z5 h/ C
Contribution rate, 贡献率
( ]' p! I; [' ?! ~. ^Control, 对照
- N7 i( y3 W) u' K! F0 C4 I" _Controlled experiments, 对照实验
9 y( c# p- t1 i; F$ x) |Conventional depth, 常规深度
2 a! d6 Q6 _& V/ RConvolution, 卷积
; _( m/ ?+ C- d7 pCorrected factor, 校正因子' T% L; l2 o n# {. Q
Corrected mean, 校正均值' i" L3 ~) g! U8 k9 H! e' r
Correction coefficient, 校正系数" y c9 s2 F) B( ?, B( d. \- i
Correctness, 正确性% H. G. ]+ T# f0 l! L
Correlation coefficient, 相关系数
: p3 x. H* Q0 }% j. F0 S- fCorrelation index, 相关指数
. T% L6 L9 T2 d) o3 LCorrespondence, 对应
% w7 g- u% C( _Counting, 计数
1 c& g/ K/ N0 Y: I: N* ICounts, 计数/频数
( ^: J2 T7 d4 B2 @- ~% V W( y. ]1 kCovariance, 协方差% e2 [/ p8 I8 d- x* G
Covariant, 共变 . b! r, x. T# |9 Q- f6 e- ?
Cox Regression, Cox回归
2 y: A- q! c2 n5 ZCriteria for fitting, 拟合准则
, I3 ^1 \; D7 Y: ?) S* L5 MCriteria of least squares, 最小二乘准则- T9 `$ Y& v1 n' L! Z. S1 @
Critical ratio, 临界比% x0 X4 V; w9 _ @( K0 ]2 }
Critical region, 拒绝域4 c! ^2 X D( L# A t/ k
Critical value, 临界值0 T! z. W- K* a) D9 e* R
Cross-over design, 交叉设计- i3 {0 t- u2 e* d( i) Y
Cross-section analysis, 横断面分析0 h0 N2 {* G ~3 R- B
Cross-section survey, 横断面调查9 }. v0 }# \# x' N0 J
Crosstabs , 交叉表 7 p2 |" [; \' g* y- z
Cross-tabulation table, 复合表
# y& G+ x7 @- Y/ q3 FCube root, 立方根
, P0 P2 p7 u& b- k% X- m, PCumulative distribution function, 分布函数" a, H/ Z9 J% Y# A% Y
Cumulative probability, 累计概率( Q Q6 i' [! b% [
Curvature, 曲率/弯曲
B8 v6 m( {' v H5 dCurvature, 曲率0 o$ Q, C% T6 _! X6 b7 Q
Curve fit , 曲线拟和
! G3 u! ^5 O& H `: k* ?Curve fitting, 曲线拟合
2 i- d6 M T) b8 a, A8 wCurvilinear regression, 曲线回归$ Z$ M( |9 S O+ U& `9 K% v( y
Curvilinear relation, 曲线关系8 e G' b4 ^- N' _6 n" o; E" Z2 F1 G
Cut-and-try method, 尝试法
, N! L( K" j7 _# ~( h# n8 HCycle, 周期# D5 _/ x* w! k% ^* r6 I
Cyclist, 周期性6 L# V$ W% {+ N) B
D test, D检验/ K4 N( r+ y7 [0 j' V/ x- q2 a
Data acquisition, 资料收集# e' t5 S9 ]; _; E
Data bank, 数据库; A/ W0 w. \$ c
Data capacity, 数据容量4 u, R" E) @$ a7 f
Data deficiencies, 数据缺乏
* _9 ^; U. a: f z6 uData handling, 数据处理; H/ r0 @5 k9 N7 F1 O: @
Data manipulation, 数据处理
$ e" c) g. ]) ?Data processing, 数据处理
- |* n% x/ w5 R0 \: `Data reduction, 数据缩减8 G5 j/ `- A0 C2 g* s/ y3 W# l& ^+ I
Data set, 数据集; E/ u4 A, m+ S) ]/ `) T
Data sources, 数据来源& d' Q6 X+ M+ f8 }+ l
Data transformation, 数据变换2 I1 M+ Q- U2 F S3 T" d
Data validity, 数据有效性6 g0 ^3 e( |: B* S& F* V7 I
Data-in, 数据输入# e" N/ p0 A" P6 j: U
Data-out, 数据输出& y( C, O+ l) u6 k9 O( w9 g0 E
Dead time, 停滞期
- l0 J/ B) x* p8 t' ODegree of freedom, 自由度+ k, x4 a) l e; V' o: d2 ^0 h7 O
Degree of precision, 精密度
) t8 a9 h/ w; V8 K9 h7 {+ a# ADegree of reliability, 可靠性程度# R) ^+ N" |2 [/ I4 k! m
Degression, 递减, V6 L5 a- l* k
Density function, 密度函数
, j% c. x! I& Q# X2 ]Density of data points, 数据点的密度+ Y4 r8 d& ?) e, b2 y+ E* U
Dependent variable, 应变量/依变量/因变量. Z0 K3 x. r$ \! j
Dependent variable, 因变量
2 b0 N9 O5 _! N; S6 V6 J# x$ WDepth, 深度
( V, T8 j) k0 h! IDerivative matrix, 导数矩阵$ n0 w2 L7 }( W/ ?. h _, B
Derivative-free methods, 无导数方法
6 H7 \7 h; f8 B( p1 b! q& B. ZDesign, 设计
. d. B5 V9 ]/ P) [4 F- c( tDeterminacy, 确定性* u+ g4 | M" j. d
Determinant, 行列式
! Y# j% K- K. R6 o ~, _5 BDeterminant, 决定因素3 M0 a0 n. F z3 G
Deviation, 离差# g; M1 N* W6 @
Deviation from average, 离均差; A0 }5 E9 ? q' B& Q+ q0 y
Diagnostic plot, 诊断图
: [" g: I3 m0 y. D6 TDichotomous variable, 二分变量* O) { A7 ]( e# J3 @9 z
Differential equation, 微分方程
( I4 L8 ~9 p( y( ?' C" S' RDirect standardization, 直接标准化法
* h& Y! x( k8 d( P" n0 MDiscrete variable, 离散型变量
/ [1 q& S4 ^& A9 K+ P2 K- hDISCRIMINANT, 判断 # O' N; N. f5 L- f: Y
Discriminant analysis, 判别分析
5 e$ h3 l! o4 n6 E3 PDiscriminant coefficient, 判别系数8 p. c; H9 v+ s- \3 M
Discriminant function, 判别值
6 E+ A9 \! u% y- _( T$ y3 Q- xDispersion, 散布/分散度: k2 H4 k+ I, h, J4 ?! w( c3 N3 G/ I
Disproportional, 不成比例的
. R1 j; i& V& L" ` [Disproportionate sub-class numbers, 不成比例次级组含量3 f6 b% g, ~; z$ j
Distribution free, 分布无关性/免分布- ?% K3 N+ {9 H: X/ t( C% o* J, ~
Distribution shape, 分布形状
/ J2 j' m- V9 N8 ^Distribution-free method, 任意分布法% X/ T; [ @8 x9 u9 B
Distributive laws, 分配律
$ a/ ]4 y9 y2 u1 }) KDisturbance, 随机扰动项
9 {3 ^5 [2 O' d' u) h0 {! cDose response curve, 剂量反应曲线
' X' U) s4 n' m. j" @7 E. BDouble blind method, 双盲法; W# f& V# o; h( n$ E
Double blind trial, 双盲试验. N% M8 k D# n% p Q
Double exponential distribution, 双指数分布
0 v$ s6 q, L( G3 i5 DDouble logarithmic, 双对数; Q+ U/ ~6 d3 G) \; p7 r) p8 l: t7 b2 M
Downward rank, 降秩2 {& h/ y8 p6 w, N, y. z
Dual-space plot, 对偶空间图
. R& |( a, G: h' bDUD, 无导数方法
( y/ m. {2 S, N$ [% ?Duncan's new multiple range method, 新复极差法/Duncan新法( R( o. M' G+ l; J# f3 R
Effect, 实验效应
6 I5 k+ I: d$ L/ c5 l# B( GEigenvalue, 特征值
! X H/ A% y3 \ a6 [Eigenvector, 特征向量, k5 I( n9 {$ U. A9 q+ j, q
Ellipse, 椭圆
% v: }% ?7 s# M! `+ \) g" DEmpirical distribution, 经验分布
; w5 Q/ Q# ?- c2 T t, \6 E, ]Empirical probability, 经验概率单位* ~% K r- h# h I; x
Enumeration data, 计数资料! q& A" M& z0 f* r- p
Equal sun-class number, 相等次级组含量6 U$ {3 X- `2 n, S6 J; _7 M1 W" i ?
Equally likely, 等可能; q4 ?& h2 x0 O2 b* [& r8 Q. T
Equivariance, 同变性% J9 z' e- h% w2 O
Error, 误差/错误
& o% H7 J) a- [- G8 r. Z2 tError of estimate, 估计误差+ \5 r1 l7 T7 E8 {/ N. ?% N9 j9 |
Error type I, 第一类错误; j( E8 G8 u7 }; `
Error type II, 第二类错误
" s! H2 V$ o0 I/ t8 z$ W9 [, nEstimand, 被估量$ ^6 g4 [& k' ~% i% t
Estimated error mean squares, 估计误差均方
2 d1 S8 f% X% e- [Estimated error sum of squares, 估计误差平方和1 P! H1 ^% [) p% r8 X8 c6 U
Euclidean distance, 欧式距离2 j- \0 j [% }9 C- P4 d; a! E9 l
Event, 事件$ p' p. `9 Z8 F9 ?3 _+ Y+ L6 X
Event, 事件
0 v% y/ ^7 i R; B7 Q- AExceptional data point, 异常数据点
4 y$ x& w, B- m. `Expectation plane, 期望平面
6 {6 `- G- u3 E7 y/ F2 C) yExpectation surface, 期望曲面4 P @3 z: W$ U$ Y" `6 l4 f
Expected values, 期望值
& K3 y. H e5 E+ {Experiment, 实验8 y$ r. z- H1 v& r
Experimental sampling, 试验抽样
) e6 k. k$ e* h3 |2 WExperimental unit, 试验单位7 U) u8 Q" r* G4 Q( d9 k+ ~7 M$ W' X. h
Explanatory variable, 说明变量
2 c9 ]- P5 M4 ^! d/ kExploratory data analysis, 探索性数据分析( ?. z* n! Z3 b
Explore Summarize, 探索-摘要7 }/ {+ H. J1 O$ Z$ u
Exponential curve, 指数曲线
% Z' N6 A1 c$ G0 ZExponential growth, 指数式增长) e8 G& o, g$ a( ]' V
EXSMOOTH, 指数平滑方法 9 r# V% l% ]5 P9 A: N
Extended fit, 扩充拟合% i1 X3 E& \3 d8 z* B+ y# I+ T
Extra parameter, 附加参数
, Y% d+ a3 I U0 K* rExtrapolation, 外推法
4 p Y* c6 F9 TExtreme observation, 末端观测值
: B% `% a |8 h3 Z; y5 v- _& qExtremes, 极端值/极值
' c- Y5 D5 q w2 _F distribution, F分布4 c/ B- ~3 t( [ F' j
F test, F检验
# b N3 U4 j. g& @Factor, 因素/因子
. S; h, K. P z2 C" L# pFactor analysis, 因子分析
- L, L- K4 a( f$ A- L5 x6 sFactor Analysis, 因子分析
j: u6 p! O: G2 tFactor score, 因子得分
3 h+ J& U9 I* y; xFactorial, 阶乘, L7 V* Q$ N: Z% v8 m8 s0 R
Factorial design, 析因试验设计/ v1 k9 g5 R) u. T: L( }5 c7 E
False negative, 假阴性+ b8 r0 a' W, u
False negative error, 假阴性错误
( T, V6 J: O: }" b* ~Family of distributions, 分布族
6 ]+ d1 X: z& T% ~ Z; l; hFamily of estimators, 估计量族! j, I& F9 ?4 f' W l2 V
Fanning, 扇面: i$ t `. E( G l1 j( {
Fatality rate, 病死率
; L3 y9 ~: \& E& Y& XField investigation, 现场调查* F* |# J/ O0 V% G
Field survey, 现场调查
* a! K' u" a, x8 i1 X& D# fFinite population, 有限总体
" P+ W9 y0 Z& e6 S5 \Finite-sample, 有限样本
g6 p2 G# }& i5 t/ OFirst derivative, 一阶导数/ k/ J) A! a* {7 s! O0 q
First principal component, 第一主成分
& _6 B1 B: W: f2 T; f; mFirst quartile, 第一四分位数( h6 n; G; C ^, m7 D& K# T5 C
Fisher information, 费雪信息量
2 G6 E" G5 a; ^, z1 V! `- ]: `Fitted value, 拟合值" o6 Z3 |1 ^. b6 A7 M
Fitting a curve, 曲线拟合
+ v0 X: J8 n0 h% l# ~1 g) VFixed base, 定基9 C/ w q+ A; Q* c+ S
Fluctuation, 随机起伏
: D0 \& [8 D2 H4 a. tForecast, 预测9 z5 G3 F2 Z \' J) [
Four fold table, 四格表
( ?. E# f$ k- B7 u' _Fourth, 四分点$ D$ `% i9 _5 e- h3 \ b9 T D' E
Fraction blow, 左侧比率
) B" e9 R1 i% W! uFractional error, 相对误差# @3 J; l& N3 M( G, b: b
Frequency, 频率3 b0 R6 V* l2 _0 d( T
Frequency polygon, 频数多边图
' d: ?, O9 L1 }7 c7 x- q6 P! JFrontier point, 界限点
' k0 n. _" I/ M8 H7 b) v- B9 |+ cFunction relationship, 泛函关系
: D, ]( G& \+ g1 Y! O4 V/ r3 W4 n" eGamma distribution, 伽玛分布
3 J) f5 A4 D! i$ ]: p; VGauss increment, 高斯增量$ y( \ D9 x v" C7 y
Gaussian distribution, 高斯分布/正态分布, n" v& E6 K+ a& O' X" M2 B
Gauss-Newton increment, 高斯-牛顿增量
% A4 q$ h. b/ t+ Q& _General census, 全面普查
% t* z/ b, u9 V' b8 RGENLOG (Generalized liner models), 广义线性模型
3 _8 j7 v( d3 iGeometric mean, 几何平均数
7 P, g8 E* x3 tGini's mean difference, 基尼均差5 d0 f* x# u9 S2 b+ c
GLM (General liner models), 一般线性模型 2 s! P% }8 k* \) Q
Goodness of fit, 拟和优度/配合度
+ f& k( R# H( p) g$ o/ Y! b5 a+ BGradient of determinant, 行列式的梯度
' c: W" g# r) M, V. WGraeco-Latin square, 希腊拉丁方! R6 t9 j9 Z- Q: {5 ^- } A
Grand mean, 总均值
) _: \" S6 v# G2 ~$ l7 l: qGross errors, 重大错误
& U, O" }' A2 K6 I. x3 R+ ?Gross-error sensitivity, 大错敏感度
, O) e+ r4 a& _/ kGroup averages, 分组平均' M: L; K( e' K! ~6 I+ q
Grouped data, 分组资料
" y+ V# O+ D4 [: T( S6 mGuessed mean, 假定平均数7 P% H* |8 |9 X* A
Half-life, 半衰期: \: D& [' J/ z8 Q% v6 _; I
Hampel M-estimators, 汉佩尔M估计量: K# O- U; c5 ]
Happenstance, 偶然事件$ _- x1 T9 [. ~/ B/ t" S
Harmonic mean, 调和均数7 f) ], n. [! s: m: `1 b% G# d
Hazard function, 风险均数
* o/ `! w9 i0 T9 D% sHazard rate, 风险率2 V3 _% m/ A9 M
Heading, 标目 x8 i2 c8 t. d9 P; \7 ]
Heavy-tailed distribution, 重尾分布: t( O6 `: k6 o
Hessian array, 海森立体阵! k2 }6 y8 H% t2 T
Heterogeneity, 不同质
! k$ X/ s* c" {3 pHeterogeneity of variance, 方差不齐
/ F% f! Z; \5 @, c0 F8 Z' b% v% }Hierarchical classification, 组内分组' b- w1 p! K% z% f7 \! D: t" }3 A
Hierarchical clustering method, 系统聚类法
% F, ?0 X; F' z% t( f6 VHigh-leverage point, 高杠杆率点1 k# J% k# h) V! R r% n
HILOGLINEAR, 多维列联表的层次对数线性模型+ |+ H2 L8 [- ~9 x6 }' c
Hinge, 折叶点
& J R6 X' ^7 l; \( V( |Histogram, 直方图
7 \# b2 L2 P* F' ~9 Y$ ~0 \Historical cohort study, 历史性队列研究 & l" x- X! W, J; N2 H
Holes, 空洞2 m" [" U6 _ ]* I* h" T
HOMALS, 多重响应分析
9 o5 {0 G( [. P1 _+ L; |Homogeneity of variance, 方差齐性4 i8 k& G8 }# X# v" }- o
Homogeneity test, 齐性检验$ e% Q, D: ]2 q
Huber M-estimators, 休伯M估计量
3 e _) ?; }# g# T" q; C7 [9 t, aHyperbola, 双曲线+ w) {' P2 }$ N% r1 X
Hypothesis testing, 假设检验
$ s4 ?& Q# ?: O/ w4 d# w- QHypothetical universe, 假设总体, g4 \3 E( T2 g$ c, P3 z% d' a7 @7 K
Impossible event, 不可能事件
( S* |& ^: ^3 k! b/ R3 qIndependence, 独立性
" g0 W$ o& L" m; k7 s6 |/ ZIndependent variable, 自变量, c! j) q- _2 m/ \
Index, 指标/指数' J1 C+ I. o+ r7 D1 Z3 w1 T5 w
Indirect standardization, 间接标准化法
" _% k8 Z2 l @& x7 ^+ I9 f% \/ V; R9 BIndividual, 个体; R# z0 H5 N% v. w% O/ p
Inference band, 推断带
! E5 R. Z. h! ZInfinite population, 无限总体6 d7 _8 P& O7 j" `! D2 m+ x
Infinitely great, 无穷大; W+ g% |/ C9 h! `& M7 h6 \ k
Infinitely small, 无穷小
& r8 ]* g* c; R1 zInfluence curve, 影响曲线: W2 o/ O5 B9 e: @0 ^
Information capacity, 信息容量
3 \9 v" _5 s/ O9 |5 NInitial condition, 初始条件1 r' I' C; h U! q1 v- g
Initial estimate, 初始估计值1 U4 V0 ~$ I. ^2 j, }
Initial level, 最初水平- o5 a7 Z0 M8 S) U$ j
Interaction, 交互作用
! n3 `) j$ ]" n$ c8 O1 OInteraction terms, 交互作用项$ e: X* Q5 ]0 }" ~( d
Intercept, 截距7 U* V4 V, U2 G' u4 k, D
Interpolation, 内插法& {1 P2 s6 d$ _2 f
Interquartile range, 四分位距! T) \; M" L: Q% G1 S7 S
Interval estimation, 区间估计- Y1 q7 p* v. A' u9 p% z& z% H- \
Intervals of equal probability, 等概率区间
% I3 f/ l6 y4 {' `Intrinsic curvature, 固有曲率
! B' V3 Z# C& g& _0 bInvariance, 不变性
* Y$ I5 s0 F0 \; Q& p% ^Inverse matrix, 逆矩阵3 F% ~4 ]% U4 O0 e' s2 Z- I4 d
Inverse probability, 逆概率/ o- G+ x. i& m% w# F
Inverse sine transformation, 反正弦变换; k& E% ?8 A2 A
Iteration, 迭代 1 n, [! V* R6 ]0 L% ], u, t
Jacobian determinant, 雅可比行列式
3 d4 Y7 e, q* o$ e* H! XJoint distribution function, 分布函数 J% ^/ G& C0 k0 u7 ^
Joint probability, 联合概率
9 E. T0 k$ u3 n5 D4 q* PJoint probability distribution, 联合概率分布5 W+ ^9 O8 x, I% C$ C
K means method, 逐步聚类法6 o: j" Q3 Y5 W/ R
Kaplan-Meier, 评估事件的时间长度
6 q( m- R6 S' F! [" f3 pKaplan-Merier chart, Kaplan-Merier图, s, l9 g- t3 d C
Kendall's rank correlation, Kendall等级相关# k" @8 n+ E8 e/ F
Kinetic, 动力学
- R, ^! X' I2 B$ [Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验/ `, G7 p7 L* k$ _. m$ L! O# k
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
! }' ^" U/ l; |9 s: q. ~Kurtosis, 峰度
. X+ d3 k/ d7 Z8 y% z( HLack of fit, 失拟
# N8 ^# J4 d4 h7 C# LLadder of powers, 幂阶梯
$ _6 S) O# A+ jLag, 滞后
3 e, y( F0 H* g% eLarge sample, 大样本
9 v3 b* l1 P% N: CLarge sample test, 大样本检验4 I, z3 [$ Q- p* V# I) K4 H5 O
Latin square, 拉丁方
( p6 U* I! D" o9 o" ?Latin square design, 拉丁方设计& B3 K# i; E0 t% b8 Z' Y
Leakage, 泄漏2 Z; Z0 Z J ~4 s" Z" _
Least favorable configuration, 最不利构形
, p9 z& Q. }% T4 q, {" JLeast favorable distribution, 最不利分布/ }( f% v9 ~2 ?* V$ ~
Least significant difference, 最小显著差法7 t0 T9 U, B: t+ b
Least square method, 最小二乘法
# a5 A& X! l) y9 f( ?& _Least-absolute-residuals estimates, 最小绝对残差估计% [5 E/ E! ?0 N2 d; H! x
Least-absolute-residuals fit, 最小绝对残差拟合
: C2 H t& E( h, o. Q. H% SLeast-absolute-residuals line, 最小绝对残差线+ W5 q$ \$ @! m' s8 f$ K
Legend, 图例
0 o0 {) I9 d, [' }. U, P, CL-estimator, L估计量
$ x8 ?8 U/ E5 L% mL-estimator of location, 位置L估计量" }+ k, H5 G( t" \
L-estimator of scale, 尺度L估计量
$ j3 D& J6 x4 X9 X9 T! E* K3 K: N3 aLevel, 水平
: y$ F& g4 A' j4 n! m6 J- }7 FLife expectance, 预期期望寿命$ p+ U6 J V8 M/ v& N6 I9 j1 m
Life table, 寿命表
$ N" G1 p2 u# j9 z' KLife table method, 生命表法8 g, s1 t8 ?# l% e8 _
Light-tailed distribution, 轻尾分布& E/ \$ m4 f: Z( T
Likelihood function, 似然函数
7 R6 c/ o$ [9 GLikelihood ratio, 似然比
6 C) W7 l4 L$ h8 k* J/ oline graph, 线图% G. q, i5 T, L
Linear correlation, 直线相关/ n& A/ V0 H* G- h0 w2 I$ J0 A
Linear equation, 线性方程
1 F7 I9 d1 M; j4 Y4 U9 Z1 e' TLinear programming, 线性规划, ?1 A. H6 {- Z) x
Linear regression, 直线回归
* b$ P* Q! r: L: a$ p) F% k; y: xLinear Regression, 线性回归( ? ?) D0 K( D O6 [
Linear trend, 线性趋势; o% ^$ I2 q& ^0 u) I* k
Loading, 载荷 / x/ q. V. A; E4 _& t
Location and scale equivariance, 位置尺度同变性; L! l5 u4 @0 u1 K! W# u5 c8 k" Q! H
Location equivariance, 位置同变性
8 s% ?$ ^! u X6 } @: zLocation invariance, 位置不变性; P6 h5 ?' z" H3 d9 S, i# R
Location scale family, 位置尺度族
' g; o; Z7 t0 j1 oLog rank test, 时序检验 5 q7 X( j1 x4 B t
Logarithmic curve, 对数曲线
: s7 X* Q d* xLogarithmic normal distribution, 对数正态分布/ ]( w! e2 K. K) p% O: H# {: ?
Logarithmic scale, 对数尺度
0 J. J5 }+ x( t4 n E. R! t$ ZLogarithmic transformation, 对数变换- W' g1 i9 y" _4 b+ V- j. g, ]
Logic check, 逻辑检查5 m% W3 {9 h/ I d8 L
Logistic distribution, 逻辑斯特分布* l! v0 ~$ Z* r# u
Logit transformation, Logit转换% K& [1 T: ~. n; E% e ?
LOGLINEAR, 多维列联表通用模型 : Z0 W% L. q8 q, t6 l6 Y
Lognormal distribution, 对数正态分布+ D7 V) n2 Q5 \
Lost function, 损失函数1 i- E9 v( S( Q3 r
Low correlation, 低度相关
( S% E" Q5 x/ w1 U8 X! N: qLower limit, 下限8 b7 {0 d y* E" Y
Lowest-attained variance, 最小可达方差6 F$ j9 f/ c$ k
LSD, 最小显著差法的简称1 A% v( N8 N- G( s# I+ @
Lurking variable, 潜在变量
, r: p7 k8 J' N0 P9 z) F* @* ?Main effect, 主效应1 I9 n8 U% |( d' e9 T
Major heading, 主辞标目
c& m: A$ t4 N; R5 D' NMarginal density function, 边缘密度函数
1 b: y3 D" J; X4 b2 QMarginal probability, 边缘概率! k: f- L: v0 N& w1 s* S1 O
Marginal probability distribution, 边缘概率分布+ y+ B4 U+ X! z$ ^/ a1 F
Matched data, 配对资料
: B3 D7 B0 D) g3 L& q& xMatched distribution, 匹配过分布
9 f* n' v( `6 U& `7 `Matching of distribution, 分布的匹配
# s, H! x: {, GMatching of transformation, 变换的匹配
5 W. I2 i/ q+ l5 VMathematical expectation, 数学期望4 d8 E, V) [8 v K& T
Mathematical model, 数学模型1 I- ?6 ]8 O3 A8 H/ J
Maximum L-estimator, 极大极小L 估计量# E# a V o) e* ]% p/ f# a
Maximum likelihood method, 最大似然法% h5 U- f. x! o
Mean, 均数. O6 N2 I, ^; q) D: C7 y4 L
Mean squares between groups, 组间均方
' G/ Z( v3 P$ a% l# n9 _Mean squares within group, 组内均方0 l/ w# c3 \) f9 Y& j, Y
Means (Compare means), 均值-均值比较
$ h- V; x& N1 B6 g2 ?& ?1 KMedian, 中位数- n4 M& x& Q) \1 A' C, m
Median effective dose, 半数效量
/ m7 J% @+ ^: D2 |6 E) T. \Median lethal dose, 半数致死量6 @# P: Y: m! j6 c
Median polish, 中位数平滑
$ C1 |4 z/ i. }, W: [% N3 U* TMedian test, 中位数检验
( _6 n& u8 y/ CMinimal sufficient statistic, 最小充分统计量
0 ?/ }4 R" \9 F7 G3 r* |, MMinimum distance estimation, 最小距离估计1 S2 v+ m. L+ S0 g# f" F3 a! t
Minimum effective dose, 最小有效量& r J8 z, {, _& J5 ]2 Q
Minimum lethal dose, 最小致死量
6 }& A+ ] q/ v/ V( q0 PMinimum variance estimator, 最小方差估计量
; ]7 n5 t/ T, L6 g4 Q. QMINITAB, 统计软件包, V1 P h/ `5 J( b# @5 x
Minor heading, 宾词标目. b( e' c" m, z1 w
Missing data, 缺失值4 p. b$ s) d& F7 R- N
Model specification, 模型的确定
4 u4 j! r n4 a/ O4 C* aModeling Statistics , 模型统计 |8 U" q. T* G7 s5 @8 T
Models for outliers, 离群值模型0 y5 m; j9 ?# S( \. y; ]; M
Modifying the model, 模型的修正
; l7 |! {, T; U! t9 _3 aModulus of continuity, 连续性模 o- V2 r8 U) d
Morbidity, 发病率 , Z2 e) t, M- g. I& ~8 R
Most favorable configuration, 最有利构形
) {+ S& [+ V7 n) ~6 K9 O* BMultidimensional Scaling (ASCAL), 多维尺度/多维标度& m5 h2 {) H2 o: h7 @& J0 a
Multinomial Logistic Regression , 多项逻辑斯蒂回归& l- y& `: @. k# O: a0 ?$ _
Multiple comparison, 多重比较
- Z: m1 L/ L) u; j4 P$ M8 @5 hMultiple correlation , 复相关- w9 {- |& F; B, R
Multiple covariance, 多元协方差! T' h$ ?7 G" R: y/ `) g1 m
Multiple linear regression, 多元线性回归
- A6 v y. O9 b$ \! f$ ^' o8 DMultiple response , 多重选项. r- L8 [4 W$ i( H. A5 u& o
Multiple solutions, 多解4 e/ m5 F, E4 H4 B
Multiplication theorem, 乘法定理2 T% v, k$ d# d( k% a
Multiresponse, 多元响应" {, j# O. R* Q" F% Q6 n' p
Multi-stage sampling, 多阶段抽样
$ o) j+ ~* z$ {, P! I( XMultivariate T distribution, 多元T分布
7 |. R5 {" V3 t% \# B* K1 pMutual exclusive, 互不相容
) ~& u9 L/ V' Z+ U M3 BMutual independence, 互相独立
( O8 R0 f+ I- s0 M+ i3 z7 iNatural boundary, 自然边界
9 {* ^8 h0 C2 ENatural dead, 自然死亡% m ^& a S! U) _: X
Natural zero, 自然零# j/ v' r6 v: G& J# `6 z
Negative correlation, 负相关7 A% J+ w# Q% g/ v3 _" q- x3 y. Y) _
Negative linear correlation, 负线性相关
" v- K) I$ _1 F) m4 YNegatively skewed, 负偏+ r$ @4 u. G7 Z
Newman-Keuls method, q检验. ]/ w1 d7 ~) B1 \9 I7 y
NK method, q检验
+ X: b) b E$ T+ E+ @8 TNo statistical significance, 无统计意义# |; q: W8 J- V2 E- v: u
Nominal variable, 名义变量
+ ^8 D; I4 x) L# q, g3 LNonconstancy of variability, 变异的非定常性# `2 K% Q8 r7 } S0 P
Nonlinear regression, 非线性相关7 z- @5 K% u, u U( t1 J0 d
Nonparametric statistics, 非参数统计' K: P$ P3 a, T
Nonparametric test, 非参数检验3 X% i5 H+ Z1 k9 w+ S
Nonparametric tests, 非参数检验7 E1 s1 |3 l# g" I. E. {6 m& |# o
Normal deviate, 正态离差( m8 j k9 H# b
Normal distribution, 正态分布
$ @4 I" G2 y" M; b# |" \Normal equation, 正规方程组9 M3 t7 l6 @- r
Normal ranges, 正常范围
! x4 {; Y+ g9 b5 DNormal value, 正常值
3 ?4 m E7 L8 L; v( jNuisance parameter, 多余参数/讨厌参数
" r; A% Q& P- J7 VNull hypothesis, 无效假设
* B; r/ P5 Z3 P* ?Numerical variable, 数值变量
/ G) G4 p( M8 G( q4 ?+ FObjective function, 目标函数
9 L4 o$ b1 z) x- f' d& g3 D* zObservation unit, 观察单位
& P$ w5 F" I: w* h/ pObserved value, 观察值: k& A( h$ M6 A* q, f" T1 p
One sided test, 单侧检验
, K! d& |) z* @One-way analysis of variance, 单因素方差分析
1 _" s* ?- V3 p2 r! tOneway ANOVA , 单因素方差分析5 ?9 `$ ` Q. E) b+ k0 T6 u
Open sequential trial, 开放型序贯设计+ m; S, ^+ _, M5 Y7 z$ c6 ^
Optrim, 优切尾) O4 p6 m# P0 ?
Optrim efficiency, 优切尾效率6 |9 p1 ?5 O. {! M# Q- s
Order statistics, 顺序统计量
! g- O- o2 X3 ^4 ^& a7 [4 R9 `! O: M: DOrdered categories, 有序分类* Y4 N% ~+ L/ S4 X5 \& j4 y
Ordinal logistic regression , 序数逻辑斯蒂回归
W9 a# R6 l' r) VOrdinal variable, 有序变量$ I. `% F5 a1 {9 p3 z$ A
Orthogonal basis, 正交基4 g9 n7 L: w8 o& G' W7 T# q/ w
Orthogonal design, 正交试验设计
% s. j7 B9 T3 K/ |3 m/ T: D' |0 SOrthogonality conditions, 正交条件
! j( ^6 c3 `8 h# S1 Y. i! `& N! {ORTHOPLAN, 正交设计 4 O9 M2 S' l4 P( ]
Outlier cutoffs, 离群值截断点 g! G" z. X. P
Outliers, 极端值
. r" m1 w( V5 i \ nOVERALS , 多组变量的非线性正规相关 . L/ ?7 {9 G; q5 R c
Overshoot, 迭代过度, j# W9 \; x& ^& u. c
Paired design, 配对设计- D$ A* q8 O/ z6 G" m& u3 h/ f
Paired sample, 配对样本8 o2 F; L' `' E* L: X+ g7 j9 I
Pairwise slopes, 成对斜率
& Y! @* b- V9 `3 Z5 O1 @Parabola, 抛物线
( g) j; Y% p) @: q1 H, p# U7 j& LParallel tests, 平行试验
s: k% c T" Z3 m5 d' l7 S6 K% B0 ^Parameter, 参数, e* F9 U/ c6 B3 y
Parametric statistics, 参数统计5 c. R; l9 U( S, b5 _6 \
Parametric test, 参数检验2 e( _, d, }6 U1 z- ~* D2 l+ ]3 M' P/ i
Partial correlation, 偏相关# H; f ]% U- c! @, F
Partial regression, 偏回归) M' i' q1 g8 d+ b2 m
Partial sorting, 偏排序% g% t Q- @" g5 |1 B4 t3 Q
Partials residuals, 偏残差
. V# O/ F7 \0 GPattern, 模式
& M) h+ k: s- n# {! QPearson curves, 皮尔逊曲线
8 Q. R4 w2 \! p( \, }8 hPeeling, 退层
" A% n3 g8 E3 z* DPercent bar graph, 百分条形图/ h7 M3 J }" B
Percentage, 百分比9 ?9 o9 l+ O0 }3 I, ~
Percentile, 百分位数
; n9 s/ ]) k: O Q+ t) B: EPercentile curves, 百分位曲线
0 B2 h$ L( R% t, D4 A( @/ K- v0 ?Periodicity, 周期性
+ E, ]5 o5 i$ HPermutation, 排列& O: V% ~: ^2 b' a0 g" N1 Y! @
P-estimator, P估计量
6 f! s) c" B6 i) i) o0 cPie graph, 饼图
* G W$ O6 `$ ~7 gPitman estimator, 皮特曼估计量 r9 [& N! I: w' ^, G$ o' m
Pivot, 枢轴量
4 B% |' d- T5 Y$ T/ r+ c, `Planar, 平坦' {4 f" f! m( p/ ^% f' ^ K
Planar assumption, 平面的假设 K o; _: ]: |% a. x. n9 y
PLANCARDS, 生成试验的计划卡* U! O" z: c1 ^% G; q. |
Point estimation, 点估计$ e. K( D7 ~1 p0 E5 A
Poisson distribution, 泊松分布
( E; T! B9 s9 C" ?2 r: XPolishing, 平滑 K# z2 o3 M/ A7 v g) p6 L
Polled standard deviation, 合并标准差" E) w" c+ [, N$ V- \# X
Polled variance, 合并方差
5 a6 _2 O5 X$ `8 I) n/ zPolygon, 多边图
z- d, a' ?4 |2 K# k" [* W5 iPolynomial, 多项式# I; B$ C! D0 U+ E3 N
Polynomial curve, 多项式曲线* ?% o0 y3 J5 i: A
Population, 总体 ]1 E% i; J, }4 u+ H; D
Population attributable risk, 人群归因危险度
- x! S- \' x. x$ b1 gPositive correlation, 正相关
6 X# e0 G0 Z3 dPositively skewed, 正偏
8 ~; f* @. c; T2 w& M6 C8 lPosterior distribution, 后验分布6 |& y/ s6 H2 E5 J- M; [# N
Power of a test, 检验效能
# f; Z8 s6 ?! I& Q `' N' I4 j3 CPrecision, 精密度
* ~( w# u1 H2 o# D4 iPredicted value, 预测值
& _- W. p8 H- h$ M" vPreliminary analysis, 预备性分析$ X! z: l! |$ ]* n* Q$ G
Principal component analysis, 主成分分析
! V# y. o, Y; _' qPrior distribution, 先验分布9 d* A( K+ A* _% B4 j' j8 {
Prior probability, 先验概率0 c. \! W$ v9 r# G
Probabilistic model, 概率模型
+ h1 l1 p' W- R. ]* g0 M9 b, J- S; C" qprobability, 概率
# V6 T- a: r: M- W; @- h u0 `Probability density, 概率密度
$ _3 o! O0 I# J" M4 e5 ~6 DProduct moment, 乘积矩/协方差
k4 W( _4 [. {0 Q4 E: F5 W3 [Profile trace, 截面迹图* o. \% h$ x- J/ k2 Y
Proportion, 比/构成比 M L, d& T6 T
Proportion allocation in stratified random sampling, 按比例分层随机抽样; X O, X; {2 `& r$ J$ y: S9 j0 g
Proportionate, 成比例
1 h+ h ~# X1 V" H$ u- EProportionate sub-class numbers, 成比例次级组含量5 y9 Y. h2 ?+ R1 [' |5 s2 S
Prospective study, 前瞻性调查
& V$ V4 P* i- a# CProximities, 亲近性
. F; v- R8 W3 @7 m1 z9 K" H8 H4 MPseudo F test, 近似F检验8 j& v0 E u$ _* w" S2 ^+ g- [
Pseudo model, 近似模型
- v$ I7 d; P' R, r! [0 OPseudosigma, 伪标准差
/ l: a3 P5 W0 }; ~, m+ fPurposive sampling, 有目的抽样
" ?+ b9 a: _ ]% EQR decomposition, QR分解5 T2 d% C7 E2 x5 S& E- D
Quadratic approximation, 二次近似" \2 X- m) V( G2 ^
Qualitative classification, 属性分类
: g! L8 t- L1 g# K5 W5 zQualitative method, 定性方法7 e" H& G X8 i
Quantile-quantile plot, 分位数-分位数图/Q-Q图
: J8 a) {3 r& P$ KQuantitative analysis, 定量分析
/ A' v. A# F1 H, G) J6 NQuartile, 四分位数4 @3 r Z; v/ A2 v6 ` u3 [
Quick Cluster, 快速聚类 V6 w- Y4 k6 _6 R1 K5 b
Radix sort, 基数排序
: J% h: y L8 Y$ [5 X: g6 _- r+ e0 tRandom allocation, 随机化分组( S# D5 ~! n4 \
Random blocks design, 随机区组设计
, w$ J: o! u+ B% W- t3 ^1 j! QRandom event, 随机事件
$ _* F( N1 o, C; J+ VRandomization, 随机化& c4 _2 b+ |* P k" M4 ^4 y
Range, 极差/全距, ~$ U" e% q% k! b# E9 M# y) j
Rank correlation, 等级相关5 \7 |2 V H G- v" O! J
Rank sum test, 秩和检验' T# u, s: i% E) c( N) U5 r
Rank test, 秩检验
( Z. P% L$ z3 k6 x! [' O* sRanked data, 等级资料1 M9 n, P/ J/ h( x& ?; O N* P k: l# i
Rate, 比率
, R! K W6 ]5 p: E% S- A i/ d: A# QRatio, 比例
, y0 z& {* n3 p- oRaw data, 原始资料' |* |% [% z$ M7 w$ i% ^% I0 D" o
Raw residual, 原始残差/ h' q' L3 J: H
Rayleigh's test, 雷氏检验
" x i% A8 J' ]$ F) c$ bRayleigh's Z, 雷氏Z值
V* b' }0 p9 r' N3 g: Q5 H" T. nReciprocal, 倒数
3 b) Z$ ]0 X# b+ NReciprocal transformation, 倒数变换; s$ o# j7 ^3 S
Recording, 记录1 G% O1 P5 N" Z: u
Redescending estimators, 回降估计量
: j3 I% A# q4 ?9 u8 M1 @- fReducing dimensions, 降维
/ ~ G! c4 m+ e3 ~7 HRe-expression, 重新表达 r, k' t, [( r. S9 Z, ]) ]* G: E; u& z
Reference set, 标准组
$ Z4 `4 R! u I2 s- |% GRegion of acceptance, 接受域" t. O: S% K! m4 X4 ]7 {
Regression coefficient, 回归系数9 g5 q! k9 t+ ~+ ~
Regression sum of square, 回归平方和2 k$ P$ D7 B- Z
Rejection point, 拒绝点( }6 ^ A1 E+ v! A3 o* K
Relative dispersion, 相对离散度& Q+ f" P" ^; x6 [( F2 m& l3 G1 T' D
Relative number, 相对数
% b/ }5 P6 A( c; t/ {7 A- CReliability, 可靠性' U: G2 A" X* N$ e; j
Reparametrization, 重新设置参数5 c- q% T* [ g6 y
Replication, 重复5 h/ {' t2 A$ ^; G9 B
Report Summaries, 报告摘要
L5 ]4 R1 j7 o& w9 lResidual sum of square, 剩余平方和1 H6 c- Y" E8 d4 G6 Z) l7 l% C5 H
Resistance, 耐抗性4 l" @ ~1 R% M4 X
Resistant line, 耐抗线
- ]" U* D- ^# }* L, t+ \$ |% d aResistant technique, 耐抗技术
3 f. u- \" i; }+ s; T' X. H; H! s% aR-estimator of location, 位置R估计量
1 Y6 x8 z$ J. C! b# W( AR-estimator of scale, 尺度R估计量; [7 p7 e l+ k4 R3 r, D
Retrospective study, 回顾性调查1 S* d4 @! u8 a3 _% A/ w/ n/ y
Ridge trace, 岭迹$ e" [, M K Z
Ridit analysis, Ridit分析3 O9 j: Y$ n5 D! Y6 e- M4 M
Rotation, 旋转
9 G8 }7 U- e: F* q1 r6 [( vRounding, 舍入* J& n3 G% Y" ?1 z F/ @
Row, 行
' k. a0 z" O% r8 J) f: a# {2 DRow effects, 行效应; @$ Z" q! h( V- m( e! v4 @8 H8 x
Row factor, 行因素
; h$ E! F: b; [RXC table, RXC表$ H; N' O5 L* u) x3 c
Sample, 样本' V+ |4 K. P" Z2 l, i2 \( n( P( `
Sample regression coefficient, 样本回归系数
* d. P0 l# W" [; r+ y5 r, pSample size, 样本量$ Q# t- g- Y8 j5 B- x& ]
Sample standard deviation, 样本标准差& a- W) F0 l2 j: p1 G! N& e
Sampling error, 抽样误差
; E/ h* C1 D- B0 C# wSAS(Statistical analysis system ), SAS统计软件包
, T; @8 e0 B2 T$ |! k2 nScale, 尺度/量表. C3 \; u" _6 j5 s7 P: F
Scatter diagram, 散点图
! a Y4 g$ @0 f, i5 i9 KSchematic plot, 示意图/简图
. L5 Q! c* v. XScore test, 计分检验7 {9 T* ]5 x, A
Screening, 筛检
( m, c& x- Y2 o2 {4 NSEASON, 季节分析 + h# w- {& p+ T. @* c
Second derivative, 二阶导数
( y& H" h& [1 ^3 Y. w8 OSecond principal component, 第二主成分
4 R; x J( ?4 F6 @6 G/ xSEM (Structural equation modeling), 结构化方程模型
* Y( _6 p# s E R3 `Semi-logarithmic graph, 半对数图
: s7 v3 P" {7 Q+ RSemi-logarithmic paper, 半对数格纸1 k! A; T" p4 @+ C- M6 b
Sensitivity curve, 敏感度曲线. | m0 A+ Z2 _" O n
Sequential analysis, 贯序分析
) C8 K2 D5 Q# L) t7 \1 Q; YSequential data set, 顺序数据集
3 Q6 w* J6 X1 b8 Z$ @8 c% [8 SSequential design, 贯序设计) a2 l0 C1 R. U9 o9 x3 f: G
Sequential method, 贯序法
) w7 m: N, m" H" K) ~Sequential test, 贯序检验法5 Z" r+ y) Q6 l. L- a1 o. t5 d
Serial tests, 系列试验% y* H" X C) |: Y4 i Q
Short-cut method, 简捷法 6 ~( s" }) }3 t( h
Sigmoid curve, S形曲线' V$ @! H4 S! U: m" s/ O
Sign function, 正负号函数
/ e/ L5 r/ d" ~; dSign test, 符号检验$ s5 M3 u2 o, o$ b& h+ i$ z
Signed rank, 符号秩
/ W: p: A# o w( s& P4 R+ U' |/ ~Significance test, 显著性检验: K# J4 P, x: Q. J
Significant figure, 有效数字
2 y, [7 ^# s5 W6 @Simple cluster sampling, 简单整群抽样1 K6 z) ]" k5 _8 O% _) a1 y
Simple correlation, 简单相关
4 N) w \5 {( [, tSimple random sampling, 简单随机抽样$ `/ D3 t3 n+ J
Simple regression, 简单回归
8 H. O: F( i$ z& S" t) E( ^simple table, 简单表0 V' p. |7 b7 e) ^. W3 [8 a
Sine estimator, 正弦估计量/ M$ C2 W6 D/ S( w5 ^8 k/ v
Single-valued estimate, 单值估计
6 C% {( ~% ^9 ? Z S; |6 R/ W; `Singular matrix, 奇异矩阵- v7 h7 V/ f9 C; X/ l
Skewed distribution, 偏斜分布% G8 K7 w" M" y2 K7 B' b" @5 e2 h
Skewness, 偏度
5 M3 i0 y7 @# k* i7 ISlash distribution, 斜线分布
3 b1 h9 e! Q/ f; dSlope, 斜率: S1 Q L. y6 t1 E
Smirnov test, 斯米尔诺夫检验
- m+ P) }+ q" P) G# dSource of variation, 变异来源3 x6 q' }$ Z, L% E& W
Spearman rank correlation, 斯皮尔曼等级相关% `; j% x7 ?, S" b* J7 \# `
Specific factor, 特殊因子
* D. }5 Y% O+ B$ J& b$ hSpecific factor variance, 特殊因子方差& V8 l7 `& I j7 @4 J! `/ U- V
Spectra , 频谱
; m( s8 L" O) u2 L5 V; jSpherical distribution, 球型正态分布3 N9 q6 m7 x9 e ~. G5 Z! b
Spread, 展布
9 e/ N3 O, R# SSPSS(Statistical package for the social science), SPSS统计软件包8 o0 Y" T* s9 m2 D' [
Spurious correlation, 假性相关5 C J+ ~& W8 j
Square root transformation, 平方根变换
& M6 f+ W+ b& O9 WStabilizing variance, 稳定方差
! o6 n0 i/ {( K& x; sStandard deviation, 标准差
7 a) v' |0 k+ l; I; qStandard error, 标准误$ C) @9 O0 {; [; e% _% d
Standard error of difference, 差别的标准误6 v3 t: [) j2 ], o& z
Standard error of estimate, 标准估计误差
! j- M% S& m7 ^* _$ j6 jStandard error of rate, 率的标准误
7 L' L! {' X, Y: I: iStandard normal distribution, 标准正态分布9 J i! v1 Q2 [
Standardization, 标准化5 @! j/ u% x# x3 ]4 G- f& k# k! P" d
Starting value, 起始值
; |2 g5 u! ^5 I/ N. j9 N) ?' PStatistic, 统计量/ E' F4 Y: o2 i! I2 H; g
Statistical control, 统计控制% p; h# \+ g- W
Statistical graph, 统计图1 g! K% G- d) c- ]. E
Statistical inference, 统计推断( w% o% U3 ?, R# y
Statistical table, 统计表6 J3 q" i0 P S8 ?
Steepest descent, 最速下降法# B8 X# f& S% e" r
Stem and leaf display, 茎叶图
{. f9 Y( v& A: Y/ P$ N0 EStep factor, 步长因子
) G$ O# }$ {4 P1 `7 {Stepwise regression, 逐步回归
( i) y: J0 h; G- r8 J4 U3 @8 x: X5 WStorage, 存
% R. o- ?# _* \3 E' eStrata, 层(复数)
6 Y$ b2 r" ]$ Q" eStratified sampling, 分层抽样1 M( S9 F* D! }$ _$ J' m
Stratified sampling, 分层抽样+ |# A* e0 R% m/ `9 H% F& h/ t
Strength, 强度) a; d: I/ h3 x0 Q" D
Stringency, 严密性. V) R( q) g: r* a/ g
Structural relationship, 结构关系3 N, e# x# \# k% O4 D+ b
Studentized residual, 学生化残差/t化残差, N+ `7 k( `4 M4 h& ?* k
Sub-class numbers, 次级组含量
, p r6 `0 U0 r- s' g2 ^) {3 ZSubdividing, 分割
( T* v; q7 p7 b! M! f3 |Sufficient statistic, 充分统计量
3 l% _: S3 n! y0 E! x& A" CSum of products, 积和( c" `4 X- n1 F7 E; `- ^
Sum of squares, 离差平方和
6 I/ J2 W% X" P5 ^( LSum of squares about regression, 回归平方和1 t7 {% H1 R* k. P0 l) m
Sum of squares between groups, 组间平方和/ \" E2 n, T! Y0 b1 b
Sum of squares of partial regression, 偏回归平方和, i& a2 O/ m8 `- q6 _
Sure event, 必然事件
& t+ e1 u0 T9 p% E8 K: M- ~5 Z) dSurvey, 调查
. P( P5 g! t- OSurvival, 生存分析8 O6 q0 D+ _* a { k6 r z
Survival rate, 生存率
9 P" ~+ W1 e0 c' lSuspended root gram, 悬吊根图
1 J8 b7 k% u2 W4 f7 k4 |. lSymmetry, 对称; k' _) u5 F- ?: v5 x
Systematic error, 系统误差
y# g( ^+ c: j2 GSystematic sampling, 系统抽样. v1 ?* w: Y. l1 D! i
Tags, 标签9 m( y6 m& V: o
Tail area, 尾部面积
5 h5 ^1 e! c5 B% _9 R( E3 F$ ?( STail length, 尾长
; E$ x; m& a6 `& P( X7 ]Tail weight, 尾重: j) o) @/ {: t) L! Q& N9 N
Tangent line, 切线# z" g3 ?! K8 x( R& V, k: k
Target distribution, 目标分布4 l" L. N2 f/ ^4 }- e8 ^
Taylor series, 泰勒级数7 i1 I3 Y' N1 ]* H( ~( a7 y
Tendency of dispersion, 离散趋势3 ^! K7 x, K" \1 `3 `8 @
Testing of hypotheses, 假设检验
* `$ a. e2 {& p' hTheoretical frequency, 理论频数! {% b8 C* C- c7 K# \, R
Time series, 时间序列
( }$ B$ `8 Q7 oTolerance interval, 容忍区间
% ~; k/ Z4 V6 Y: r* [ y2 LTolerance lower limit, 容忍下限
O+ q$ t3 Z7 T2 mTolerance upper limit, 容忍上限
: y9 }* l' m+ J6 x( } q( ?Torsion, 扰率
7 e+ |+ [0 p! i0 M! t2 X% R& UTotal sum of square, 总平方和
9 A$ U* F" f: {: U; F7 j8 K# wTotal variation, 总变异
K; E) c3 ?: U+ e9 a" K) |4 f* eTransformation, 转换
* d# `& J$ U: ~6 P# @$ WTreatment, 处理
/ ^9 s5 ]. F& S& n+ y+ K" _9 H. gTrend, 趋势
6 T7 t' N2 ~# B: pTrend of percentage, 百分比趋势3 O c/ X" Q/ k, o" Z3 w
Trial, 试验' ?/ \& Z1 N. }
Trial and error method, 试错法0 |7 z% ~+ }! g/ Y
Tuning constant, 细调常数
. v8 @! F. O9 n& y* F8 |3 C: B8 [Two sided test, 双向检验9 F3 T7 _$ l; o4 z& {
Two-stage least squares, 二阶最小平方
* Y5 o% o ~% E' P5 X( iTwo-stage sampling, 二阶段抽样4 S# W: N; J4 b4 N" X
Two-tailed test, 双侧检验$ R2 d# A% n. O* q9 X
Two-way analysis of variance, 双因素方差分析
7 U* C5 W9 s& j) l7 bTwo-way table, 双向表: H' {1 s D$ W- j
Type I error, 一类错误/α错误
6 m& _; I5 \/ n. f% AType II error, 二类错误/β错误# I( [9 T3 ^" ~0 t4 v1 ^2 ^" \
UMVU, 方差一致最小无偏估计简称5 N7 x, L1 ]% Y
Unbiased estimate, 无偏估计
9 ?+ c: @3 ?* P8 SUnconstrained nonlinear regression , 无约束非线性回归$ F4 i- W7 d, C. h% D& I
Unequal subclass number, 不等次级组含量6 u: k. }! d6 b9 b* ?3 a8 s+ C1 q
Ungrouped data, 不分组资料, ?, n0 C8 j1 g- ~* r5 O
Uniform coordinate, 均匀坐标
- D& ^9 _ `& d) Y4 f9 YUniform distribution, 均匀分布; t! Z9 t K) {: S7 R' F( ^
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计; N# @2 v% T* k3 }8 h
Unit, 单元
- E2 P3 k) A( `9 K1 ^Unordered categories, 无序分类
$ N. k9 B/ l, s8 }' k& q( J* }) `Upper limit, 上限
% K2 Z% i/ q. l3 R+ Z$ }# FUpward rank, 升秩
, M9 [% l2 j" A2 B( AVague concept, 模糊概念
: Y4 g' O; G3 X. P1 tValidity, 有效性
+ H% w. y" V1 R7 w, y/ M- u1 KVARCOMP (Variance component estimation), 方差元素估计
, l% o& G6 L. NVariability, 变异性
; ^# }5 F7 ^' ^6 a2 MVariable, 变量
& l" ]; L# ~6 e/ [4 AVariance, 方差7 ^- N- h. j1 d: ]
Variation, 变异
7 X! W# p7 k- PVarimax orthogonal rotation, 方差最大正交旋转
2 j% R$ T# @) F0 ]Volume of distribution, 容积3 Q. D" Q% w6 [- _
W test, W检验$ s8 O& \5 |; n! }4 ]- q6 Y
Weibull distribution, 威布尔分布 K: u# }0 l8 O( e+ H: w
Weight, 权数
]! p9 Y# y* c( I/ s* o5 m; I' g5 WWeighted Chi-square test, 加权卡方检验/Cochran检验' l2 p$ {4 s8 h, K- r" o
Weighted linear regression method, 加权直线回归
5 j; ?; p; R. m5 ]! tWeighted mean, 加权平均数
: z% p- ^- U' J$ s$ CWeighted mean square, 加权平均方差4 T7 ^' ^0 D7 b. I# {; M9 T
Weighted sum of square, 加权平方和
, U- u S+ U) d$ d9 a% L) C+ QWeighting coefficient, 权重系数
1 m$ M; Q- w7 P% l& yWeighting method, 加权法
. v% C6 Y$ _) x/ UW-estimation, W估计量, C9 G i* w- ^) c% f
W-estimation of location, 位置W估计量
+ y$ z; H; C( i+ K' U; KWidth, 宽度/ P" B/ p! I% ^. }( \
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验! ^% L) S) s4 }* W* n
Wild point, 野点/狂点
, G6 O( m7 \( A- ^) HWild value, 野值/狂值/ |6 I. k5 I7 a4 N* q0 m
Winsorized mean, 缩尾均值 y2 P0 d( A1 R+ f, B. i3 A d1 g$ `
Withdraw, 失访
( a! e, q) j9 x2 x' Y0 g" eYouden's index, 尤登指数& I1 t+ B6 Q( s8 F
Z test, Z检验' I: A( P7 P$ y' Q) D6 d
Zero correlation, 零相关
) U3 W: j; l/ C+ f+ _* n- e' \Z-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看,没有账号?注册会员
x
|