|
|
Absolute deviation, 绝对离差/ n1 Q+ k* Y S* e% R
Absolute number, 绝对数( z5 H4 \$ ^; H# W; f$ c6 G
Absolute residuals, 绝对残差+ i% t- ^2 c+ i0 e( Q
Acceleration array, 加速度立体阵! \) v' J2 G# i
Acceleration in an arbitrary direction, 任意方向上的加速度
8 [6 g. Y" {7 [Acceleration normal, 法向加速度+ c( K% i5 x7 i. l- z. O/ E, Z
Acceleration space dimension, 加速度空间的维数4 j7 P9 g ]$ J. C
Acceleration tangential, 切向加速度
4 O- J5 L5 y5 R5 v5 Z' _Acceleration vector, 加速度向量; E* V8 o; Y& c
Acceptable hypothesis, 可接受假设
! J6 Z8 R/ L+ c6 s C4 y( c8 I& PAccumulation, 累积3 |: q5 l' A& C, o& l4 B% R
Accuracy, 准确度* C3 a: Y: q6 @
Actual frequency, 实际频数* A& A. m% k$ ~# m
Adaptive estimator, 自适应估计量
7 M1 C/ J1 g) A0 }! aAddition, 相加6 d8 a# s5 N( h" I
Addition theorem, 加法定理' ?- i/ Y7 f3 `( h# S7 W
Additivity, 可加性
u, U7 D( W+ M9 h( yAdjusted rate, 调整率
( S$ Q9 ?6 G7 f4 Y2 `( n9 A6 NAdjusted value, 校正值
; K5 n! [' C& y+ KAdmissible error, 容许误差
4 J! ?* p$ @8 MAggregation, 聚集性
# @; {# f9 Q& v) b1 x( j( M: D EAlternative hypothesis, 备择假设
! j/ y9 e; j4 S. qAmong groups, 组间' ]3 U4 S/ X$ e: H$ z* j1 H
Amounts, 总量
" k* o+ A1 ]# R& E# L3 a7 PAnalysis of correlation, 相关分析& k- w) N6 b: \4 n5 {
Analysis of covariance, 协方差分析
u) j5 F( ]& J# wAnalysis of regression, 回归分析8 M. R2 z, w! o$ j `
Analysis of time series, 时间序列分析
5 X) y0 {# B. ]7 ?Analysis of variance, 方差分析6 ]$ g$ Q1 H3 L% q6 X9 `% U' R/ o
Angular transformation, 角转换
% c" H+ ]- i' T) P5 ?1 _* d+ @: d8 qANOVA （analysis of variance）, 方差分析$ L: a; Q2 H3 j2 n
ANOVA Models, 方差分析模型
. ?4 [( ~0 |8 f0 i7 uArcing, 弧/弧旋
! N; w/ C9 v; T' f, K& kArcsine transformation, 反正弦变换
0 j& E1 _4 m3 A1 VArea under the curve, 曲线面积" r, v" V; X" D
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
2 l$ |$ W- c0 O ?' j8 EARIMA, 季节和非季节性单变量模型的极大似然估计 ( |* N4 P( }5 s1 {4 m1 j
Arithmetic grid paper, 算术格纸
# v* w9 b) v- m. O* A9 Q* W7 BArithmetic mean, 算术平均数: K3 s- o9 I( B
Arrhenius relation, 艾恩尼斯关系- Y! e0 q% q, P1 ^1 l- K
Assessing fit, 拟合的评估" A2 e$ S" y- h2 A7 u3 n, X" x& C/ k
Associative laws, 结合律% ?& b! E; `5 x8 |3 L7 P
Asymmetric distribution, 非对称分布! s- x! s8 d! y' E! v7 v r* O7 J
Asymptotic bias, 渐近偏倚( `& _- u# ~9 p1 I- W7 t! c
Asymptotic efficiency, 渐近效率4 R9 v' z% C* ]- U0 D# G* p( c
Asymptotic variance, 渐近方差! A- n d, r9 v/ M) x
Attributable risk, 归因危险度' v3 Y7 g& q; K9 P1 g
Attribute data, 属性资料& C) r* v7 B! w9 H
Attribution, 属性* o; F* |4 s! }
Autocorrelation, 自相关
$ B: o! W3 H8 [Autocorrelation of residuals, 残差的自相关6 z, `6 h: q7 {8 W; [2 X! X5 K7 t
Average, 平均数
- J: H# F4 F5 A: u5 eAverage confidence interval length, 平均置信区间长度5 A6 y: h( F8 s4 j
Average growth rate, 平均增长率7 y% H5 B, ]# b7 ^6 J
Bar chart, 条形图! D# p4 c0 r. K2 b ^2 ?, `5 x
Bar graph, 条形图1 f1 `0 C3 w, g X/ ]1 `3 d
Base period, 基期
1 f) }0 K/ F* c% G5 jBayes' theorem , Bayes定理
$ e. Y. C, S* N, w: F# nBell-shaped curve, 钟形曲线
3 ^/ F# L" N! eBernoulli distribution, 伯努力分布/ s. f: {% b. d7 O1 j# `4 a. J' s
Best-trim estimator, 最好切尾估计量
- g% I/ d, n7 VBias, 偏性. h$ T8 K; P! q+ G4 a
Binary logistic regression, 二元逻辑斯蒂回归
' N0 o( h% }. c; B* fBinomial distribution, 二项分布 j0 n' j' _0 P Q
Bisquare, 双平方
# u8 q1 \1 y% M" Y7 n; Y4 qBivariate Correlate, 二变量相关
4 ^# F- s3 c* P. h, ]Bivariate normal distribution, 双变量正态分布
* N' Y" c, Z1 E5 ^) f, FBivariate normal population, 双变量正态总体
' {: h( o5 J2 R# O' b2 C6 uBiweight interval, 双权区间# Q' K+ Q$ g" n8 o: y
Biweight M-estimator, 双权M估计量
9 \1 `8 q( `# k9 d8 EBlock, 区组/配伍组( i0 `* c5 t3 W4 n4 P
BMDP(Biomedical computer programs), BMDP统计软件包
9 f4 N# b' e, U/ h8 z9 I! m- pBoxplots, 箱线图/箱尾图2 A" u1 p7 n0 q Z+ n$ h
Breakdown bound, 崩溃界/崩溃点. J6 [# V5 ~+ X3 z
Canonical correlation, 典型相关8 w- D/ `* E& o$ g
Caption, 纵标目* }4 X. p4 h) b& R
Case-control study, 病例对照研究* j* s6 L7 q* e. W% S
Categorical variable, 分类变量
" j. x# Y* `6 }' m& \/ f6 cCatenary, 悬链线
* `1 _. n& z1 y& yCauchy distribution, 柯西分布1 `+ F( ]3 y! b& L& r) E$ r
Cause-and-effect relationship, 因果关系
5 `, l+ v' p; NCell, 单元9 {# G4 ?! Y H( Q0 J
Censoring, 终检
; `, i4 |( Y( L2 v# L8 ^Center of symmetry, 对称中心& M' i" u) @ k* P
Centering and scaling, 中心化和定标
9 r+ I( c( ~- P3 k% t6 QCentral tendency, 集中趋势
# c- Q& M. k. ^2 K/ W k( l6 RCentral value, 中心值1 q& R6 i/ [) _% v3 Q5 `& _
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
8 X5 k# z! j. [# D7 {' V; kChance, 机遇, `& K8 R* m; x1 o. ~/ X2 q4 H$ ~
Chance error, 随机误差
2 t l' Y, p! x5 ]Chance variable, 随机变量
' w$ D: d2 b/ Q. d" p8 g, kCharacteristic equation, 特征方程
, I8 |; q+ r' A: uCharacteristic root, 特征根0 l" d4 [, I* |' f
Characteristic vector, 特征向量
0 b2 z1 c4 L, ~$ wChebshev criterion of fit, 拟合的切比雪夫准则
7 V) P! [+ m+ f$ f1 q1 o9 D! r! IChernoff faces, 切尔诺夫脸谱图
6 l, a& W! X. l$ VChi-square test, 卡方检验/χ2检验2 B$ u% ~2 s8 T+ b/ }( a7 V% }" L
Choleskey decomposition, 乔洛斯基分解6 P" L; X4 J( ]' g' o
Circle chart, 圆图 & G; w- k3 ~; F9 C
Class interval, 组距$ y+ i* G- x7 e1 r6 C5 s/ V
Class mid-value, 组中值
. P: M$ l' d* l9 }Class upper limit, 组上限
* F t9 k0 B/ [. |Classified variable, 分类变量
' p" b! l/ X: B4 F# F$ r f1 M6 zCluster analysis, 聚类分析4 n4 Y4 ?3 {; t9 `% m2 L/ ]
Cluster sampling, 整群抽样
" x$ x: o; l5 i( l9 MCode, 代码9 g7 E! \1 q$ \, i2 v
Coded data, 编码数据
y; i$ M! s, v0 ]. B/ o6 }" t H: ~% XCoding, 编码! C8 m" G8 ~. Q, K8 h
Coefficient of contingency, 列联系数
) N! a9 S: M8 B3 {Coefficient of determination, 决定系数
. n6 i. g- x# o2 gCoefficient of multiple correlation, 多重相关系数
" R$ N( A* W* V9 W6 FCoefficient of partial correlation, 偏相关系数- A5 d0 E9 f; |" U' p
Coefficient of production-moment correlation, 积差相关系数# U* E' [4 l6 [7 Y0 d6 [; x
Coefficient of rank correlation, 等级相关系数& R: U0 [) R9 `+ k+ J* {: r
Coefficient of regression, 回归系数
: k+ b( I. f! T6 g @: {0 a9 UCoefficient of skewness, 偏度系数
; ~2 Y% y. g6 s5 H0 W0 GCoefficient of variation, 变异系数
8 G# G, p$ O2 N6 a1 @/ `Cohort study, 队列研究# Y" m t: H5 y8 c
Column, 列6 u7 @' @* a/ X7 P
Column effect, 列效应 g! k3 d5 ~* P- g9 K/ s
Column factor, 列因素* I) y* m) b+ ^% U2 [3 H
Combination pool, 合并- ]( N |" C+ } o" p: _
Combinative table, 组合表
, B1 y0 m2 i" o' g: QCommon factor, 共性因子 V9 a" K! |) D5 R. v7 J5 S& G
Common regression coefficient, 公共回归系数- K7 d+ C0 `' p Y4 c
Common value, 共同值" C/ K' e1 @+ _* G6 T0 @2 t
Common variance, 公共方差. S1 T" y) s# w! B" |
Common variation, 公共变异" ~' [. w3 Z- Z6 Y1 n8 O
Communality variance, 共性方差# R- W. S9 F r. D) J$ _: w: u
Comparability, 可比性
8 u0 ]$ K$ c# d JComparison of bathes, 批比较
$ e4 h F- ]1 yComparison value, 比较值8 e# s% y7 O/ A: }, m
Compartment model, 分部模型+ ?, i5 ]% O( U
Compassion, 伸缩
) k" H! b( r1 J$ mComplement of an event, 补事件0 P: z. ?9 m# X5 `% m& N& J9 ~# i
Complete association, 完全正相关
1 I# \6 D) m' A' B7 WComplete dissociation, 完全不相关 f9 Q# Z. p! _# b
Complete statistics, 完备统计量. g+ p" ?1 b$ L$ K7 f- r8 V
Completely randomized design, 完全随机化设计
. n- w) K! R8 p/ F7 M7 fComposite event, 联合事件
, I5 {! R% E% u: ^: EComposite events, 复合事件
; I% }3 d: |& |4 q& RConcavity, 凹性2 y n& q8 B" J% P# i5 w. {7 E& l+ ?
Conditional expectation, 条件期望
) b8 w9 d' n+ f$ k$ c5 ^5 `Conditional likelihood, 条件似然0 ~) H, _7 N7 M8 t. _/ z
Conditional probability, 条件概率# I! L; q5 `' v- a- Q
Conditionally linear, 依条件线性
E$ d% R8 T# {Confidence interval, 置信区间 ~& Z+ {+ w$ Y; v @* R7 i! Z
Confidence limit, 置信限
# x& v k1 J5 P0 e! wConfidence lower limit, 置信下限) j; u2 @0 e" p
Confidence upper limit, 置信上限
6 Q5 J U. i7 @8 A# w! bConfirmatory Factor Analysis , 验证性因子分析* G4 S3 k8 y6 n9 ^ o6 M
Confirmatory research, 证实性实验研究
! ^( a" w4 [' |: U0 J8 p7 S$ MConfounding factor, 混杂因素5 @* a# }) i6 w6 I* m
Conjoint, 联合分析& E) u5 B+ @8 Q
Consistency, 相合性
) M- ~( A" `8 t4 FConsistency check, 一致性检验
$ T4 s) u) D2 M" s/ {, EConsistent asymptotically normal estimate, 相合渐近正态估计
& G0 ~6 p0 X8 g; @0 XConsistent estimate, 相合估计. @5 H$ y( z) M8 C" h' m# }
Constrained nonlinear regression, 受约束非线性回归0 `# A* S- ^' Q
Constraint, 约束2 s5 q5 h) Y' {3 ~
Contaminated distribution, 污染分布
, q+ ]( {1 U) Z1 K- k) w. jContaminated Gausssian, 污染高斯分布( ~% L! ?" Y0 l! S; x* L3 F! \
Contaminated normal distribution, 污染正态分布* m5 `$ |% b, d. |1 v6 ~
Contamination, 污染
$ v: t3 q! V4 |/ ?% E+ G5 TContamination model, 污染模型7 p9 T( U4 m9 J) q
Contingency table, 列联表) P; Y+ |% G- S, [4 a
Contour, 边界线
1 h- y, t$ I. |+ O7 r* eContribution rate, 贡献率
' q# ]& q! a7 E: u U9 W) [ BControl, 对照; L# T* K! E" T, ^/ P
Controlled experiments, 对照实验
, O2 f7 b3 d, o& a) OConventional depth, 常规深度: v4 d" D7 B o7 r+ Z' D" Q
Convolution, 卷积" ?" l+ e3 t: i& I! y- S
Corrected factor, 校正因子 s8 J4 E$ q9 X
Corrected mean, 校正均值3 S' X# L* P7 L- N
Correction coefficient, 校正系数* O* Y$ H7 d( e/ V, t- q
Correctness, 正确性
! j! E3 K. M2 KCorrelation coefficient, 相关系数9 H Z+ S* `7 X
Correlation index, 相关指数6 N$ u- r- S- L/ Z
Correspondence, 对应
& y6 Q3 F# w0 m" q# k% j! mCounting, 计数
' W4 z$ T3 b" y/ T% eCounts, 计数/频数" { E6 k# i6 |
Covariance, 协方差
' s6 l% B* H, h* U; ?Covariant, 共变
6 O' k. T4 w! |) r1 n$ d2 NCox Regression, Cox回归
5 o0 |# l' r; j9 n: U/ q9 i% xCriteria for fitting, 拟合准则
; D" N" H% |* u) C( @0 C/ ]Criteria of least squares, 最小二乘准则7 @4 Q; a- Q$ V; o }, g/ P c) S/ c
Critical ratio, 临界比( }+ p% t" P# b! [7 v- K$ ~# L
Critical region, 拒绝域9 Q0 z1 Q& t( ~$ G! Q5 E' B
Critical value, 临界值
0 M! D5 ~/ s- C# P0 mCross-over design, 交叉设计
7 F9 O1 M E0 ]1 t4 `: jCross-section analysis, 横断面分析
" h8 V" T. J8 u' c* ~( O5 rCross-section survey, 横断面调查6 }$ i/ _3 Z# h+ ]/ N) Q! g3 N
Crosstabs , 交叉表 " R# D! F. {' [0 C2 L
Cross-tabulation table, 复合表5 Q/ y8 n$ S m! v( j" L, R
Cube root, 立方根. t! ?4 b0 r0 q% f, p
Cumulative distribution function, 分布函数, k9 Q# u4 V8 r4 K. a" \5 ~8 B
Cumulative probability, 累计概率+ L, r- Z8 H# U- ?* ?, i7 g
Curvature, 曲率/弯曲
8 g* g3 @5 f7 u4 J# s+ ICurvature, 曲率. S5 P. q( b4 e$ g) V2 | |
Curve fit , 曲线拟和
, H' y% p/ H) ^& Y2 P [' nCurve fitting, 曲线拟合4 e9 |7 M% V5 u0 G) p. K3 \
Curvilinear regression, 曲线回归
$ F, Z4 N; J6 ?+ dCurvilinear relation, 曲线关系
# t: P- f! i8 hCut-and-try method, 尝试法) ^& l, G) D; ~) e6 J
Cycle, 周期
% d# d0 S" J& K, ^, T, VCyclist, 周期性* z, E q: D' p1 j/ V1 l
D test, D检验+ p' q/ |/ ^7 V/ g2 J. ~1 L
Data acquisition, 资料收集
0 L- o3 L+ f) }Data bank, 数据库
( [; ?) r* T6 m) @% kData capacity, 数据容量
! c; y" ]" c5 C; Y- IData deficiencies, 数据缺乏5 X3 s9 F7 a$ P" m2 ^8 `: M% x
Data handling, 数据处理
5 w+ z! x2 f8 R2 e& I3 T; W/ cData manipulation, 数据处理
+ Z$ U8 i/ ^5 w) |" D; t* @Data processing, 数据处理
9 ~5 p. M; M* j1 w4 P0 LData reduction, 数据缩减# b6 G: `" [9 o1 G1 W: D
Data set, 数据集$ _% `. R& z' f: b
Data sources, 数据来源6 ]8 T- g% P/ {; n& b
Data transformation, 数据变换
0 f: l, Z6 j3 D8 {' a* hData validity, 数据有效性$ e2 {/ d* U3 D* o4 R9 c
Data-in, 数据输入+ I2 Z! _, z2 A" i4 |$ K& I
Data-out, 数据输出$ R: ^! @/ U$ G: a4 |8 p
Dead time, 停滞期8 v" k6 B' S" D4 H- d
Degree of freedom, 自由度
6 S9 i/ d1 H/ I+ I' v! q( uDegree of precision, 精密度- h( ~( {9 p6 h" ^' W+ R Q a
Degree of reliability, 可靠性程度
" X5 X& L" [9 E6 t% `Degression, 递减
! j8 I% C z- d ^: L$ N" {! E6 ODensity function, 密度函数
) F6 I- d7 Q6 A5 dDensity of data points, 数据点的密度" F( U% G; x$ e/ o- h, X
Dependent variable, 应变量/依变量/因变量
8 k- [" A& @- O- Q" d0 y2 T4 f2 nDependent variable, 因变量2 p) ~( P2 S# a/ p9 D
Depth, 深度' |% d; p6 L+ J3 K/ k
Derivative matrix, 导数矩阵6 G8 j) |3 [& h. }+ G
Derivative-free methods, 无导数方法2 w- p+ V9 S5 u8 J5 W1 W- ^
Design, 设计
% Q* I9 W0 s1 R7 dDeterminacy, 确定性8 A4 l9 o1 Y3 \/ [ [! B+ c g: [
Determinant, 行列式
) ], j0 N- K2 h- i4 ?. W7 wDeterminant, 决定因素$ [ j% ?& j- Q: z
Deviation, 离差
7 g B/ K, ]& ADeviation from average, 离均差
* T. [4 I) S9 r" l. j5 CDiagnostic plot, 诊断图
* `9 M' `# f$ J3 V( t& q, y; |Dichotomous variable, 二分变量
" N6 R$ A% v \7 ]2 eDifferential equation, 微分方程
) i+ d. |3 x6 e# ^0 |3 U: c: ^Direct standardization, 直接标准化法7 v$ v, y* e- D
Discrete variable, 离散型变量$ h0 V7 B6 F- n+ ?: b, b
DISCRIMINANT, 判断 " m3 R2 }+ F# a
Discriminant analysis, 判别分析
+ C/ M$ y3 Q' f: S: v. t! eDiscriminant coefficient, 判别系数
8 ~) u& ~4 E1 ?( u& K9 h. XDiscriminant function, 判别值
$ \* k; }- ]$ }7 I$ e- mDispersion, 散布/分散度6 H0 [$ b _ L1 A" D6 Q
Disproportional, 不成比例的
0 D9 P7 ]& B1 Y2 `; O( O- N8 ~1 T* YDisproportionate sub-class numbers, 不成比例次级组含量; V& a8 W. U8 ? L Q7 R, u& x* l, i
Distribution free, 分布无关性/免分布3 g4 Z4 r9 K2 ^# ^3 d. `4 B
Distribution shape, 分布形状5 i- N; a' P' n+ ~( N9 }
Distribution-free method, 任意分布法
9 N+ C+ |( C( FDistributive laws, 分配律
- E/ E" V5 Q, ] R- L) @/ hDisturbance, 随机扰动项
9 L( \2 ~6 h A* I+ r1 T" ZDose response curve, 剂量反应曲线
9 O2 v. g+ D# V" CDouble blind method, 双盲法+ d \/ F* j/ n) Z( y
Double blind trial, 双盲试验+ J" V: D. Q* Q
Double exponential distribution, 双指数分布
! [# @$ y1 x$ f" a/ V- N% ODouble logarithmic, 双对数
8 A. w8 R8 Z+ n8 ]9 U/ y$ c) SDownward rank, 降秩: @/ f( |2 v" v5 j7 T( @, a9 e
Dual-space plot, 对偶空间图# V: {% J' S2 X* X( z% _
DUD, 无导数方法
3 b6 s/ P4 ?' {9 @# i' eDuncan's new multiple range method, 新复极差法/Duncan新法
! q6 o3 a& e2 X0 b9 M$ l. |Effect, 实验效应% ~8 v; F8 [# ?2 K" u
Eigenvalue, 特征值
) r2 Y# U* A/ L) A" z, K, ] dEigenvector, 特征向量1 O: P4 V- @5 q5 |4 ~! I
Ellipse, 椭圆
# Y+ n4 f0 L. q- W5 Q, ^6 u! S" `Empirical distribution, 经验分布
% @) Y6 \' n. C. K3 YEmpirical probability, 经验概率单位
8 `1 \) q+ T: { V* B! v8 REnumeration data, 计数资料
. x3 E- F4 U% d# ?: IEqual sun-class number, 相等次级组含量
f- d+ }3 @4 I3 x+ jEqually likely, 等可能( q) |9 a J9 U
Equivariance, 同变性* B( ?: G# N/ T
Error, 误差/错误( C n' _5 {; p4 Q W+ u( M
Error of estimate, 估计误差# t3 q1 b* q, e( X Z2 f
Error type I, 第一类错误
' I. {8 P% y& T; m% `7 D; zError type II, 第二类错误. M* c( p. u/ ^# _# v( Y
Estimand, 被估量; Z1 d. K4 ~$ M% B Y7 O# ^
Estimated error mean squares, 估计误差均方
& M& m3 d0 J8 w" ~* y) T' _Estimated error sum of squares, 估计误差平方和. _# B* o- ^: c! Q: Q
Euclidean distance, 欧式距离* l' V: m) F& c# w# h/ d
Event, 事件
% ^8 S* {% c! y/ ^0 ?Event, 事件+ ~6 t% w( V& z' M7 \ @
Exceptional data point, 异常数据点, S% ^0 k" x% T' y/ _. P) d0 f
Expectation plane, 期望平面4 i2 ?8 k* R( Q3 T- P5 x- w
Expectation surface, 期望曲面
! \$ y, v& J8 k: uExpected values, 期望值" c1 p5 r5 ~6 n1 L, f0 }; z
Experiment, 实验
1 F1 z5 \- j U' {" q% ?9 j0 _Experimental sampling, 试验抽样
" ^9 ^% u/ t5 a4 H1 f5 RExperimental unit, 试验单位" C' Q5 V' v. f; S
Explanatory variable, 说明变量7 q- Z0 ` X' l3 {: M. F" M' h
Exploratory data analysis, 探索性数据分析
7 }' [8 @/ Q- m4 W; r* jExplore Summarize, 探索-摘要. B# V0 ~/ i( P3 U7 I6 P
Exponential curve, 指数曲线; P* I1 f8 X2 i$ |
Exponential growth, 指数式增长
9 b5 Y9 w) f3 h5 j# J' t- M( [- aEXSMOOTH, 指数平滑方法
, n* K7 {$ W: DExtended fit, 扩充拟合9 m1 J4 ~- n4 `' {2 D* o! I3 a; u
Extra parameter, 附加参数) Y s# y. H$ W5 u. ^$ {) S4 T1 u
Extrapolation, 外推法
/ r1 h0 @2 U3 @+ M/ }$ B! {Extreme observation, 末端观测值
+ y8 Z0 j9 y* S/ L w2 QExtremes, 极端值/极值+ Z9 X% C( ` R8 c, Z/ w
F distribution, F分布; o7 g$ C: z, N9 D
F test, F检验3 h6 N2 y9 U& T" ^+ r( i( {
Factor, 因素/因子- }( E( c* h. i6 {$ H6 Y
Factor analysis, 因子分析3 d' Y: ]6 ?/ {
Factor Analysis, 因子分析
! W" z5 |. V# w" y. r8 JFactor score, 因子得分
2 T9 ~5 X2 I) ^Factorial, 阶乘
) g: D3 A( `$ y GFactorial design, 析因试验设计+ Q6 I5 S) E% o' G) I1 n
False negative, 假阴性5 t3 `, h( @; l: k) j
False negative error, 假阴性错误
+ I! F7 d, b2 Z& w9 Z8 Q0 SFamily of distributions, 分布族
, g5 |6 J' x' wFamily of estimators, 估计量族
~9 m5 y" S6 n1 P& I# k8 pFanning, 扇面4 b; v9 c, }8 F6 l: k) W2 ~
Fatality rate, 病死率
$ t5 o! F: _' sField investigation, 现场调查
$ d+ X! ^8 Q h! VField survey, 现场调查- W6 k! V( `. |
Finite population, 有限总体
% ]9 }5 h/ Z0 D: I4 PFinite-sample, 有限样本3 ?! x& _% Y/ B! ?
First derivative, 一阶导数
8 ]& ?$ D1 {- E0 DFirst principal component, 第一主成分
, [# _! ?0 Y: ]1 }( h% QFirst quartile, 第一四分位数* ]6 j7 n2 K. k7 |0 ]
Fisher information, 费雪信息量( v6 X8 M4 n, r
Fitted value, 拟合值8 P: \; B: Y- n$ ~& v- n4 W+ H& M
Fitting a curve, 曲线拟合( q; G6 T0 T$ j
Fixed base, 定基) P$ r/ k/ m. p _4 Q ?
Fluctuation, 随机起伏4 O. ?9 O9 `2 {; M H
Forecast, 预测
- E/ W! u- u% n. KFour fold table, 四格表( v/ ^) k# g# p. B2 b& u
Fourth, 四分点
( \. o& a+ g9 G# @Fraction blow, 左侧比率
8 d5 ^/ g2 w, M% y) K' ^Fractional error, 相对误差
* I( A( P6 x/ X. m& |+ QFrequency, 频率& R5 n6 Y: Q) h' T
Frequency polygon, 频数多边图
) l8 N; B! |& j) T \/ ^+ PFrontier point, 界限点% x( _. o; E b$ N9 Q% a
Function relationship, 泛函关系9 x+ H4 C( m3 N: a4 v& D8 f
Gamma distribution, 伽玛分布
( ^: B6 w6 w( _' }2 N9 GGauss increment, 高斯增量6 p9 r4 g$ s; Y5 M
Gaussian distribution, 高斯分布/正态分布
6 z. ^$ d2 R, S: {Gauss-Newton increment, 高斯-牛顿增量" w; v( e3 X. A+ c1 y4 T2 J
General census, 全面普查
- K! ^5 P: `/ O$ TGENLOG (Generalized liner models), 广义线性模型 . {2 p0 O, S4 T2 k
Geometric mean, 几何平均数5 D) R! s/ u6 Z, P$ k$ X9 x
Gini's mean difference, 基尼均差. b0 r/ g- }4 r9 Y
GLM (General liner models), 一般线性模型 " v5 q. k) x. V; E
Goodness of fit, 拟和优度/配合度
& k' ]- ?/ X( r9 {% ^9 r5 VGradient of determinant, 行列式的梯度
( f: j6 i4 H$ B. v) r: RGraeco-Latin square, 希腊拉丁方3 r6 `# i3 k) i3 k- T
Grand mean, 总均值
* a, X; E2 ~$ q( _7 uGross errors, 重大错误' B2 C( S0 K9 A' l* z. s+ {9 a
Gross-error sensitivity, 大错敏感度: N2 o; c u5 w
Group averages, 分组平均
! G U/ e$ e8 k7 |' r' m, _Grouped data, 分组资料
$ |. k5 @5 c4 x O# I# ]Guessed mean, 假定平均数5 h9 H" o( O4 J# y
Half-life, 半衰期1 W3 U+ |+ J7 ~- f# i4 h8 g
Hampel M-estimators, 汉佩尔M估计量3 R' W/ W- W8 y9 a% X
Happenstance, 偶然事件5 y) m1 y4 _7 \, c% o- ]2 l
Harmonic mean, 调和均数8 q# G, M. Y- ^* K. d# G
Hazard function, 风险均数
. w: G# r6 L, s( Y( F" U; \( \Hazard rate, 风险率2 ~; ^# j8 c& b
Heading, 标目 3 s& X+ P8 h# L
Heavy-tailed distribution, 重尾分布
7 P/ `$ M$ g. z o# A- uHessian array, 海森立体阵5 n7 e4 f$ \$ y0 n' d9 c
Heterogeneity, 不同质5 y1 t- p( M3 \# \/ z0 p
Heterogeneity of variance, 方差不齐
* W* x& T' z% {9 {, x( [9 k( OHierarchical classification, 组内分组3 s; j% F0 R" d4 S, q
Hierarchical clustering method, 系统聚类法
5 l/ K0 D2 G+ _1 ?! C6 f* {High-leverage point, 高杠杆率点" J+ p# G* @3 e( M
HILOGLINEAR, 多维列联表的层次对数线性模型; Y4 A2 R) m% Z- ]
Hinge, 折叶点
* Y% g9 |% n3 u, h2 Y, SHistogram, 直方图
- t/ h7 F% X3 x# GHistorical cohort study, 历史性队列研究
( n5 M* V2 u' P6 Y# o- THoles, 空洞/ P0 Y% ?$ ~+ A3 _
HOMALS, 多重响应分析
, X j$ \2 H$ a, P3 D# p5 v/ cHomogeneity of variance, 方差齐性
, U6 K. X$ x& V0 iHomogeneity test, 齐性检验* X2 y+ U# g4 f3 C* y( T
Huber M-estimators, 休伯M估计量
: s1 Y+ b d9 q) j9 e. xHyperbola, 双曲线& ^( u, C2 N3 B# ^' P* y0 y
Hypothesis testing, 假设检验' t7 ?8 o1 L( ~9 P8 W1 j
Hypothetical universe, 假设总体1 F/ g' ?1 u7 J8 a7 B- U2 F
Impossible event, 不可能事件% U5 o s8 b3 w; @! A6 M
Independence, 独立性# w" C; g4 q0 J! S- r4 b
Independent variable, 自变量' W' d L$ ^; j" `* @! T
Index, 指标/指数
4 E; E$ e/ `6 V+ b4 J. M! O: RIndirect standardization, 间接标准化法# B" t. Q5 ^' A) \
Individual, 个体
5 `1 D; L/ D# pInference band, 推断带
7 k; w/ O& d, ~0 BInfinite population, 无限总体
/ ^8 } |; c( H `1 b3 IInfinitely great, 无穷大7 Q) X. G$ ^0 |: }: v
Infinitely small, 无穷小
/ y( g$ H! P, }: QInfluence curve, 影响曲线8 {/ H+ l& I7 i& V! b% `8 }# W
Information capacity, 信息容量( O) a4 z# w: R- n0 i7 W% L$ W
Initial condition, 初始条件
1 x/ G2 T. p+ B3 w! Y8 O7 nInitial estimate, 初始估计值
2 |; W T& ^% v5 ^/ YInitial level, 最初水平
( G+ ^% f3 K: ~5 E: X, N* _5 W3 fInteraction, 交互作用
/ h: }* N+ u6 EInteraction terms, 交互作用项
( d( g1 E+ x6 E) z- \Intercept, 截距
0 o9 `/ f# v4 O! LInterpolation, 内插法& I; \5 B. m2 o$ v
Interquartile range, 四分位距
) i3 C) W7 B. E) GInterval estimation, 区间估计
1 w2 V: ^; C; |+ Z$ f- B z L: PIntervals of equal probability, 等概率区间9 C/ f. k j' ^8 ]: K- u
Intrinsic curvature, 固有曲率
: I. d" f! Q% W( EInvariance, 不变性
5 X2 M4 P$ ~% L: `7 }! e9 \Inverse matrix, 逆矩阵5 o5 B9 s- N, ^$ [1 E
Inverse probability, 逆概率
# k& M1 l7 w P0 ~3 m* IInverse sine transformation, 反正弦变换
" ?" P5 n" u. D6 \6 H/ X: W! ?Iteration, 迭代
3 Y! e% Z# q' o* ]Jacobian determinant, 雅可比行列式
" `/ ~0 H, e/ ]# R+ Y) Z+ g! QJoint distribution function, 分布函数& y4 X, `8 x- i1 a9 [
Joint probability, 联合概率
1 D* \' n. ~8 s; Z$ }5 X6 nJoint probability distribution, 联合概率分布
1 @; U- w; t, ?/ e6 uK means method, 逐步聚类法1 n& Q, @1 t6 B( X
Kaplan-Meier, 评估事件的时间长度 / s- G* S# P4 ~0 E( }: F+ ^' F
Kaplan-Merier chart, Kaplan-Merier图) C. f$ b& [; p" u! _# }$ _
Kendall's rank correlation, Kendall等级相关: T3 [/ V2 @5 f9 |
Kinetic, 动力学$ V1 g. d$ v! A, P3 E5 Z$ S
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
- w0 H" V* r) fKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
+ G6 R# T% ~ L- V9 d# wKurtosis, 峰度
- J7 i r' u, N5 p* I+ q$ MLack of fit, 失拟' y$ Q' G9 ^ F
Ladder of powers, 幂阶梯* i* a( f* y7 a& q9 I o
Lag, 滞后
9 i) \% S: Y* d2 P$ t/ q qLarge sample, 大样本; a+ f: b* p: K/ F. T
Large sample test, 大样本检验
! `1 u4 ^. @7 XLatin square, 拉丁方
- O! S4 h0 u' y. @8 nLatin square design, 拉丁方设计7 |' ~- ]' u3 c& N5 U, H2 x
Leakage, 泄漏) r- g( @; ]. J* i3 `
Least favorable configuration, 最不利构形" F- A8 U. N! j7 Q
Least favorable distribution, 最不利分布0 `+ B/ H+ j, |8 K$ C* R
Least significant difference, 最小显著差法8 Z0 t# r. i1 W+ X7 I
Least square method, 最小二乘法0 o7 u2 `# t/ G
Least-absolute-residuals estimates, 最小绝对残差估计
! Y4 a) u: e- \Least-absolute-residuals fit, 最小绝对残差拟合
' B: @' C+ T3 q- lLeast-absolute-residuals line, 最小绝对残差线. ^) ^, o* @. K7 A- v
Legend, 图例
; E' I) y" P* @% y% `$ ~; c9 dL-estimator, L估计量
1 T2 ^, e5 q; p+ I' V1 iL-estimator of location, 位置L估计量% v: K+ }- m3 f9 D. H
L-estimator of scale, 尺度L估计量3 ?4 I$ E7 |2 e, ^8 W; H7 T( A
Level, 水平
) l3 H0 B, X/ `4 pLife expectance, 预期期望寿命0 V: \8 S- i# @% V& P3 o4 l
Life table, 寿命表
) e, E5 K, I J4 ?8 _Life table method, 生命表法
. \: }1 @1 l6 m- J4 Z) mLight-tailed distribution, 轻尾分布, m2 h, a% D/ k. L6 O7 F" `" k
Likelihood function, 似然函数. O U8 G7 m( H6 U+ J+ A ~
Likelihood ratio, 似然比
/ \& O7 h* E2 m0 bline graph, 线图
9 w0 [0 g7 o7 r9 g' b6 r- fLinear correlation, 直线相关
" @ ?4 @8 @( m6 D# v2 G oLinear equation, 线性方程
( g7 o' p. D: xLinear programming, 线性规划 r8 H, w* ?0 Q$ K$ b" |4 ~9 r
Linear regression, 直线回归
_4 I5 p6 u' r& I& g( O5 w7 P, tLinear Regression, 线性回归
5 o2 ^; i' y6 }Linear trend, 线性趋势
: m0 i% K2 G0 LLoading, 载荷 ! B9 w, H8 E8 I* i9 j/ p# c
Location and scale equivariance, 位置尺度同变性; f3 p( S! ~, a. o& t. q
Location equivariance, 位置同变性5 I& `7 w! R- E& Y' J
Location invariance, 位置不变性, S" ]. G: {8 H! S: d) U' ?
Location scale family, 位置尺度族5 [8 y4 X" O3 [: \+ m) k2 \, I
Log rank test, 时序检验 4 J4 O2 o% h+ ?
Logarithmic curve, 对数曲线
, ?! R* {1 X1 E: C* t7 Y. d2 JLogarithmic normal distribution, 对数正态分布1 V% z1 O1 o0 W
Logarithmic scale, 对数尺度
( B# x; t) \, D- ~9 x$ qLogarithmic transformation, 对数变换; e, w' j# ]# f
Logic check, 逻辑检查9 k" o$ c! }$ N" p- L
Logistic distribution, 逻辑斯特分布2 {' v! l& }- m' ]. T. S
Logit transformation, Logit转换/ k W- l5 s, k
LOGLINEAR, 多维列联表通用模型
9 @, P& j) d* m0 ?4 SLognormal distribution, 对数正态分布- j* ]) q* J; u H9 m$ ~: M
Lost function, 损失函数
6 n6 x. _: [" MLow correlation, 低度相关* V2 |% L+ D- ]: d
Lower limit, 下限
" B4 u) t- d' RLowest-attained variance, 最小可达方差
' U0 ^8 l/ A9 R( `7 v' |LSD, 最小显著差法的简称. R! C1 h) w4 L% }
Lurking variable, 潜在变量
6 b8 o5 {5 L- E+ l6 gMain effect, 主效应8 _* n( a* p% S; ]+ ?
Major heading, 主辞标目
# }0 I7 Q( @: t. f' O# w2 W% k; mMarginal density function, 边缘密度函数7 C; K/ t# j5 v% g! j# J5 h
Marginal probability, 边缘概率
0 j6 j4 G5 O; K) u: @1 EMarginal probability distribution, 边缘概率分布
9 [$ }. e: g9 TMatched data, 配对资料
$ x# h+ ~1 \ U% P6 e4 r3 PMatched distribution, 匹配过分布
4 h2 Y/ g2 F4 `Matching of distribution, 分布的匹配6 F- v' p4 Q) t
Matching of transformation, 变换的匹配
& B* k3 E: G0 I* IMathematical expectation, 数学期望
" K1 N6 N5 W) g: p3 S- ~Mathematical model, 数学模型) i& c, g9 W5 M
Maximum L-estimator, 极大极小L 估计量" K3 W- @7 f5 w
Maximum likelihood method, 最大似然法' I8 o6 K5 j' Y4 t4 X
Mean, 均数; x0 i. C$ Q6 M6 ?
Mean squares between groups, 组间均方; G3 z3 @, c9 D) I4 K
Mean squares within group, 组内均方: a; g5 K6 W) d* }" M3 c3 O1 D
Means (Compare means), 均值-均值比较
0 `+ [4 H: k" a8 K) }* ?Median, 中位数2 m: u5 g4 ~ x2 o( g# |% `
Median effective dose, 半数效量
1 b/ C- w. V# s' wMedian lethal dose, 半数致死量# V" b3 X& j9 F) r; K9 o* q- z5 n: `
Median polish, 中位数平滑$ `1 l) i0 f. b0 P5 P8 s3 d
Median test, 中位数检验
* Q( p8 \0 ~# h' LMinimal sufficient statistic, 最小充分统计量0 N1 E2 I# F! a8 K9 v
Minimum distance estimation, 最小距离估计5 b0 y% z6 ~5 C0 T6 m; h
Minimum effective dose, 最小有效量
9 i. ]0 ~% l8 m4 F0 W/ [! e7 kMinimum lethal dose, 最小致死量6 l5 Q9 U% t: |9 e7 o, R' |* ~9 ^
Minimum variance estimator, 最小方差估计量( p: @& b0 C: z* n7 n4 k. c6 E
MINITAB, 统计软件包1 w; @# Q* `; L9 n0 u" H
Minor heading, 宾词标目& U+ } ]$ w' \. o d3 t1 h) I- @
Missing data, 缺失值
1 N, D6 n" @! s& e/ AModel specification, 模型的确定. X2 t; n1 B5 u5 L7 Q
Modeling Statistics , 模型统计* {/ H7 X5 y$ S, l' c, M' F; P
Models for outliers, 离群值模型& l( c! ^- K2 t4 O/ i
Modifying the model, 模型的修正' B% \1 a# U$ i, }8 v" ?/ F
Modulus of continuity, 连续性模/ j/ `& N) v, B: R) e& D+ i
Morbidity, 发病率 4 H8 @9 l$ P- P5 q( ^+ h4 e
Most favorable configuration, 最有利构形1 j+ W4 e, ^7 f* z
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
8 o3 |0 Z1 v0 z5 XMultinomial Logistic Regression , 多项逻辑斯蒂回归* l5 ]4 |* N, v, s* ^
Multiple comparison, 多重比较7 [" J9 v m* s v
Multiple correlation , 复相关6 e1 ~' }$ n% E. r5 D; _5 J2 ^* i
Multiple covariance, 多元协方差
- ?3 X- O6 D7 Z( g+ mMultiple linear regression, 多元线性回归1 A7 s0 P2 t! v# o3 q# | V
Multiple response , 多重选项
. O" G5 Q/ v2 E, mMultiple solutions, 多解
+ R) ] W) d. V! f* `Multiplication theorem, 乘法定理" Q I+ Y9 C. C" r/ Y% T# f
Multiresponse, 多元响应9 N" {/ ?8 I, o U/ S& n9 ^( v
Multi-stage sampling, 多阶段抽样$ V4 N P5 g# W- r7 U
Multivariate T distribution, 多元T分布
0 ]0 c( q: z/ p% HMutual exclusive, 互不相容- R/ @# V9 Q: O, B% Q6 ?/ Z
Mutual independence, 互相独立
& \$ x: ?) C t5 [- `! g7 g* Q9 ^Natural boundary, 自然边界, Z; |% V0 k( r2 K" w; y2 Z
Natural dead, 自然死亡& x( ?) @" M- k, ]. F/ W
Natural zero, 自然零
4 {. H5 N. c$ C5 k" v% B' U# ]$ nNegative correlation, 负相关4 V2 f6 Q7 K* T2 w: W
Negative linear correlation, 负线性相关
7 I8 N/ B$ ]9 e) T2 LNegatively skewed, 负偏8 F6 ^+ L2 Z( p: j/ A
Newman-Keuls method, q检验9 W3 T* L/ C+ P: b* A. k3 {& g
NK method, q检验5 U% M# L, N5 ^5 L9 i
No statistical significance, 无统计意义
; E3 |( U7 w% d/ O2 r$ PNominal variable, 名义变量6 ^; G: L3 R5 T8 B8 a, y
Nonconstancy of variability, 变异的非定常性, n4 _9 q/ U& h' f+ A) ], ^" i
Nonlinear regression, 非线性相关1 J' u1 Q/ E! \! c6 N' ]$ i
Nonparametric statistics, 非参数统计8 \+ P$ M) C' q4 X% C, Z
Nonparametric test, 非参数检验
; f0 {5 N, M0 |8 D: i5 ~Nonparametric tests, 非参数检验
+ f w: e2 i! c4 d: `+ }) @Normal deviate, 正态离差, V5 |, R7 N2 J. o
Normal distribution, 正态分布( Y& B9 H& B x7 x0 M
Normal equation, 正规方程组
( K5 L( ?5 y Y- _, qNormal ranges, 正常范围
) d% Q7 b9 Y2 z, V$ }# bNormal value, 正常值/ q) S1 V( \: S: N- X/ V
Nuisance parameter, 多余参数/讨厌参数
5 D1 Q, G9 r) \Null hypothesis, 无效假设
0 P& ~! U( |9 @4 y8 yNumerical variable, 数值变量+ U* ~0 t' {0 B I4 c' S) k
Objective function, 目标函数% P, s2 }5 E# B! g% y6 F' F
Observation unit, 观察单位+ o6 J3 i/ n' ^ R8 |& Y# q4 K
Observed value, 观察值
, f' M% {$ Q! m8 |; x6 J E' GOne sided test, 单侧检验
/ c6 O% I! Y& EOne-way analysis of variance, 单因素方差分析, f- L0 q1 h, d6 ~, G
Oneway ANOVA , 单因素方差分析
+ |$ W5 j7 t% F7 X$ j. lOpen sequential trial, 开放型序贯设计 n7 ^4 M9 ?( Y
Optrim, 优切尾: B4 Q; G$ Z4 f4 c; z# C
Optrim efficiency, 优切尾效率
. R1 n: B( P4 p' \& x% F* JOrder statistics, 顺序统计量9 F3 ~1 F. G# ]/ ]* P3 z. |( |$ w
Ordered categories, 有序分类
5 w$ P! R, i: r' ~* bOrdinal logistic regression , 序数逻辑斯蒂回归* J2 X' [. K8 _# N% I, C/ n
Ordinal variable, 有序变量4 l7 z& j |2 s/ O
Orthogonal basis, 正交基4 ^# r- }" a N9 E7 A7 i
Orthogonal design, 正交试验设计
. F' d& D" L. K: J8 m2 {- fOrthogonality conditions, 正交条件
! m! z! X7 h/ e7 K& TORTHOPLAN, 正交设计
- G" W @/ E9 h- e8 `) b- C/ b3 VOutlier cutoffs, 离群值截断点
2 d1 X; w) a* j$ DOutliers, 极端值
6 Z" d) i% }0 z5 W& COVERALS , 多组变量的非线性正规相关
$ {6 `% L$ l8 lOvershoot, 迭代过度1 r; C7 r# o K4 l6 S
Paired design, 配对设计# R1 [& `* V% Y& N- I
Paired sample, 配对样本
. D6 |* l" l& ]% {0 Y. Z: \5 u$ {- YPairwise slopes, 成对斜率- }4 w" g8 W9 l; Z$ W: e
Parabola, 抛物线: N( k2 ], J& O# Y( a& M
Parallel tests, 平行试验
5 B% J' M( g5 w* h! yParameter, 参数
0 Y; f& e3 m `7 C1 z$ |3 yParametric statistics, 参数统计* B: d g+ C) A& S/ v7 `: h
Parametric test, 参数检验! H, q: D1 l J, w
Partial correlation, 偏相关
$ l7 d3 y7 y( M/ R; @" G* i2 EPartial regression, 偏回归
/ K% ]' v! ~* B$ O; l- BPartial sorting, 偏排序
$ i) m6 R& o" r) T) p/ G/ ]Partials residuals, 偏残差
' M" J6 I ?, g* T/ l# t3 ]Pattern, 模式' G$ W$ r/ s7 Q" N3 w# j. h
Pearson curves, 皮尔逊曲线- Z0 ?; B9 R( ~' `4 @
Peeling, 退层
# i, P+ K* x" q1 uPercent bar graph, 百分条形图( @8 ]' S0 J6 }8 P. \3 F% [
Percentage, 百分比& ^/ T, S* q) g8 l! I+ H, D1 F
Percentile, 百分位数8 d7 `; F: [# f5 p
Percentile curves, 百分位曲线" b1 I9 _* k; J! ~5 A# s+ [; V- R
Periodicity, 周期性- B0 \. Q/ X6 z: U$ m
Permutation, 排列
) ]! A3 [6 K) ]2 B+ T- P2 kP-estimator, P估计量& w) U/ u9 p: Y; r g
Pie graph, 饼图
& m, m( N' f) e9 U) ^; ^Pitman estimator, 皮特曼估计量$ D+ k+ L: N$ k- N. h ^
Pivot, 枢轴量& M. x: t- E A& d
Planar, 平坦
7 X8 k8 E7 L% T' s+ RPlanar assumption, 平面的假设/ A3 Y! d @4 `, Z
PLANCARDS, 生成试验的计划卡: ]! K% Y: A1 Q
Point estimation, 点估计2 d# l4 }/ O& O" H5 X I2 b- Z4 K
Poisson distribution, 泊松分布+ G1 r, w3 E4 }2 F, L8 O: I- m
Polishing, 平滑
/ }6 {3 \) }) A( K1 c% r3 _Polled standard deviation, 合并标准差
8 E ~: M0 p% e2 k- cPolled variance, 合并方差7 r5 K8 L6 E( N2 x# e2 W
Polygon, 多边图
! h, I5 M6 t VPolynomial, 多项式
h& D- J* e# E$ T! \Polynomial curve, 多项式曲线7 j @) T- ^7 }8 h( x
Population, 总体) q1 G: a' }5 N+ }: H# }9 Y
Population attributable risk, 人群归因危险度2 x0 Z5 v9 l3 @0 Z
Positive correlation, 正相关
7 J3 B" H9 F4 Q; `Positively skewed, 正偏/ Z* Q# F3 \( Y3 ^9 ~" U
Posterior distribution, 后验分布
; s$ q" Q! |7 @Power of a test, 检验效能
3 u! v$ s8 O7 q7 e6 Q+ l7 `Precision, 精密度
7 V, \; V* J6 `9 d: [Predicted value, 预测值# }% ^/ ]8 S) u4 C' L) S2 B7 @0 r
Preliminary analysis, 预备性分析- Z/ a& O, i6 K& W- D4 y4 G0 J5 m3 z- N
Principal component analysis, 主成分分析
5 ?! o+ ~# R1 {+ I' O' LPrior distribution, 先验分布
% U/ Z0 l( q" iPrior probability, 先验概率
. F+ M2 n2 V8 R/ ]! xProbabilistic model, 概率模型
; i5 I2 K) J& z0 h9 `1 lprobability, 概率
0 Z5 B+ u; L+ V5 I" HProbability density, 概率密度
4 D! |' g* G2 I e- gProduct moment, 乘积矩/协方差
, ?/ @% u3 [6 _! E4 `Profile trace, 截面迹图
' R7 a% i* b- v+ P; D% E6 zProportion, 比/构成比, d$ a, q3 A v1 u9 F
Proportion allocation in stratified random sampling, 按比例分层随机抽样
& V* O; b$ v% o: L# AProportionate, 成比例( k+ i) O0 ?% y( g) V) y
Proportionate sub-class numbers, 成比例次级组含量
' Z/ R- U @$ W# b+ ^ f& I9 |3 bProspective study, 前瞻性调查6 m$ l0 C" {! N$ V
Proximities, 亲近性 6 [! [- z1 h5 M
Pseudo F test, 近似F检验
" T' P L$ Q* w& {3 z) S3 D. @ {+ M8 RPseudo model, 近似模型$ |6 g8 e0 {0 l; U8 [4 W/ J( [
Pseudosigma, 伪标准差
) Q) i0 u2 j% y$ t" wPurposive sampling, 有目的抽样+ t% S' F4 l: S' X; o2 F
QR decomposition, QR分解
. w; v! t% q' Y8 W. w, oQuadratic approximation, 二次近似
. o9 L2 ^3 r9 I8 ]: y+ FQualitative classification, 属性分类. V0 |6 G* U+ f2 [0 t' b
Qualitative method, 定性方法
+ d3 {" c, n9 L2 ?) k, Q+ Q3 q5 fQuantile-quantile plot, 分位数-分位数图/Q-Q图
( ^3 ]* i, Q7 I4 V$ vQuantitative analysis, 定量分析4 X- V# |: G& z7 ^" R5 U
Quartile, 四分位数
5 L% L4 B: `6 M! ]- r7 o2 I7 zQuick Cluster, 快速聚类/ d6 R* f/ `3 F
Radix sort, 基数排序
. C* V: v5 z- |. BRandom allocation, 随机化分组$ p+ @* P/ }7 O' Z# l
Random blocks design, 随机区组设计8 H$ h+ L) V- C% c' V+ W, y# j6 i
Random event, 随机事件
! X) S% Y# Q2 Y! `0 P: sRandomization, 随机化
* D- x5 A: _/ ^5 X/ s/ E1 [+ {. iRange, 极差/全距/ J, p% \+ b, G* u% L
Rank correlation, 等级相关- W) S5 k) ]; i2 c% J+ S
Rank sum test, 秩和检验4 C% |8 N) R9 E( \; a1 s1 Y* L
Rank test, 秩检验
6 J5 v, p# V6 K6 GRanked data, 等级资料8 [4 s8 X/ F! X2 H: Y$ f6 Q
Rate, 比率
3 I) n; g8 w2 A+ A3 l' H8 K" [$ lRatio, 比例- W9 B) S J S" i
Raw data, 原始资料, M: d9 Q& {+ _
Raw residual, 原始残差
% E) {5 m* e; J. K V: y9 DRayleigh's test, 雷氏检验
# p$ ?4 W1 q6 o+ K* ^: Y/ [Rayleigh's Z, 雷氏Z值 ; L8 [' `- j% B- @
Reciprocal, 倒数! w. Y* U7 p1 t9 ?; \) |
Reciprocal transformation, 倒数变换" z- |& V8 _2 [* s
Recording, 记录
, {4 _/ `7 |5 Q b+ FRedescending estimators, 回降估计量: _1 K w% r$ k/ K" a' r' ^0 ?$ z
Reducing dimensions, 降维
$ Y2 {1 L* r. B, r0 vRe-expression, 重新表达
# g5 V i3 u: r9 I6 I/ i V6 d }/ XReference set, 标准组' F. {6 S' Z6 I" l M
Region of acceptance, 接受域# v% b( f3 K* t# V/ B b+ M
Regression coefficient, 回归系数
5 C4 E* W+ d8 n5 K! z- m( ~) R: wRegression sum of square, 回归平方和. i( b7 P$ K& s
Rejection point, 拒绝点
% q' r$ e& J+ W; s9 }' N' E& J: {Relative dispersion, 相对离散度
& d2 _, W: P9 ^" \: Z& {Relative number, 相对数
]6 V6 L, c$ F) l( ?Reliability, 可靠性
" D5 A0 u: T# TReparametrization, 重新设置参数
: N6 a# K/ [# F* {# JReplication, 重复$ _! M% G: ~/ g5 J
Report Summaries, 报告摘要
0 `. J, r. F1 UResidual sum of square, 剩余平方和
, v, L& `# \; K6 c$ UResistance, 耐抗性
! m- s4 h8 b3 K4 s- X0 m5 {* I6 {! `Resistant line, 耐抗线
* i1 J! x5 c2 j( g* Q; I, GResistant technique, 耐抗技术
! w" n- v" E" f) \R-estimator of location, 位置R估计量6 u0 n& D% _% \8 i# Y( s# j
R-estimator of scale, 尺度R估计量
) i2 O3 x# X. X9 iRetrospective study, 回顾性调查6 r+ A7 ^- ]7 E2 j5 A) f" q
Ridge trace, 岭迹
+ a: X2 F! `7 E9 L: CRidit analysis, Ridit分析
8 J0 z' q l8 m+ ]0 h- ~7 ?Rotation, 旋转( R2 }9 V ?6 x, r9 }
Rounding, 舍入8 V9 Y& b6 L! i- K" b4 |6 {& M
Row, 行
* D2 \; h: }. tRow effects, 行效应# X. Z" Q6 Q4 x
Row factor, 行因素3 G& z1 X. t4 R. G
RXC table, RXC表
5 V- }8 z! J4 r; o7 CSample, 样本
+ y" w! @, p0 L' m! ISample regression coefficient, 样本回归系数 ] R( O+ j. b3 O& y5 P
Sample size, 样本量
3 h. E1 }6 m9 y7 u& X. bSample standard deviation, 样本标准差0 {& B; z6 Q+ u) _; t0 H- ]: v
Sampling error, 抽样误差5 B3 W8 u( o. }5 G+ @+ f
SAS(Statistical analysis system ), SAS统计软件包
- n7 B% O$ \5 _8 a' s7 R# P6 VScale, 尺度/量表
( W& p5 H* L7 a! N, fScatter diagram, 散点图2 g5 D3 i' y7 q4 l
Schematic plot, 示意图/简图
+ L: W) K. w( B n; i' CScore test, 计分检验
) q) @+ n1 f& @. L b8 AScreening, 筛检2 W# J+ N9 J* f* @5 F# z' v
SEASON, 季节分析
z7 W9 n8 a$ e' fSecond derivative, 二阶导数
/ S; K1 X N; R, m- s( ?7 \Second principal component, 第二主成分" U" W3 {) ]# C
SEM (Structural equation modeling), 结构化方程模型 ( @$ Z8 Z2 z3 J( [( E2 D& s
Semi-logarithmic graph, 半对数图$ c4 X Y0 n( T# h$ I' |/ n' [' F
Semi-logarithmic paper, 半对数格纸
% J1 d9 O- F( l- w4 L* r2 T- h4 NSensitivity curve, 敏感度曲线
( W# ?; I$ Y8 Z( `5 F! k, hSequential analysis, 贯序分析: ^: X2 Q; Y5 Z( `
Sequential data set, 顺序数据集
7 K, K. U7 `/ d' R& t; C1 aSequential design, 贯序设计# U" ^* n l0 I( Y
Sequential method, 贯序法 ]- { I1 N9 D3 G t( K& x
Sequential test, 贯序检验法+ k6 x2 ~8 t# _% v. ?
Serial tests, 系列试验
, G( R; y! L( wShort-cut method, 简捷法 $ u2 f) w2 h) g+ ^ a# e- f
Sigmoid curve, S形曲线
: e/ J" |, o, {( L: DSign function, 正负号函数+ w) X* C+ m) v# G
Sign test, 符号检验
1 k3 w, F0 E) w. t- l2 t* TSigned rank, 符号秩7 `8 H; m3 \# a' `% g' y
Significance test, 显著性检验
: h- F, _$ n7 }Significant figure, 有效数字" b( }6 k! N. ?6 o0 [; s
Simple cluster sampling, 简单整群抽样) \. @ d0 a! h2 `$ G6 Q/ g
Simple correlation, 简单相关
3 O+ a& w+ `, e: OSimple random sampling, 简单随机抽样1 e- z" C( i3 G
Simple regression, 简单回归
1 O! N1 n) u' N+ `' S! osimple table, 简单表- o, e! b; N2 _7 X: Q+ Z. G5 ^% |/ L4 l
Sine estimator, 正弦估计量
0 a0 B3 _$ b2 T: NSingle-valued estimate, 单值估计! B+ y: \* N! P* V1 |3 K- K
Singular matrix, 奇异矩阵
7 i2 h6 S( I9 ]* OSkewed distribution, 偏斜分布: K0 u, z; \, `& _
Skewness, 偏度
; A. l$ v+ Y# ^2 Q! y+ PSlash distribution, 斜线分布
2 ?+ C6 f# P9 o4 U, r; eSlope, 斜率
% \/ Q6 ~" E5 u: j8 PSmirnov test, 斯米尔诺夫检验
e5 b! H G0 e2 h4 e/ TSource of variation, 变异来源) l+ f- O o4 r# m
Spearman rank correlation, 斯皮尔曼等级相关
/ |, u+ d$ V6 G& B/ c$ @Specific factor, 特殊因子; o7 e7 M& s) o3 M% {5 w* L
Specific factor variance, 特殊因子方差+ H- u5 v9 v- X
Spectra , 频谱
# c- k3 j' e+ ^8 {4 M. @9 vSpherical distribution, 球型正态分布5 P0 H) G3 m5 P( a
Spread, 展布
, N8 H+ `4 I0 `1 O9 NSPSS(Statistical package for the social science), SPSS统计软件包: g4 Y7 e+ m2 r9 x
Spurious correlation, 假性相关
/ X; L) K6 l4 r4 F7 ^- OSquare root transformation, 平方根变换
# e2 j, ^, }0 e2 ^, [Stabilizing variance, 稳定方差: g5 s1 z; ]/ {# N- ?
Standard deviation, 标准差
( ^# o$ w3 V3 {" C8 L. q9 G `& |: ~Standard error, 标准误
7 a+ J5 `* L* U* t0 }0 SStandard error of difference, 差别的标准误- F: ~7 x- B" L
Standard error of estimate, 标准估计误差7 @: Z& x0 H+ r6 a7 I7 B
Standard error of rate, 率的标准误$ [* {/ Z8 L" w/ M b' B
Standard normal distribution, 标准正态分布7 D/ s# V6 i3 q% L, I
Standardization, 标准化
5 o+ F% |( n5 v; ]) OStarting value, 起始值
" i8 j+ |( O) V% q( N- z' NStatistic, 统计量
9 a' Z3 w0 U3 z7 v1 nStatistical control, 统计控制
! u9 r. v. A8 P$ p {; O! @* {$ ~" z2 vStatistical graph, 统计图5 ~# c0 _1 u% ]! T2 y1 O' G
Statistical inference, 统计推断
" t6 E& N9 j g5 }! p9 i8 B: nStatistical table, 统计表- B( W* R9 ?; I: i0 j4 e
Steepest descent, 最速下降法
6 {* ?' ^5 y/ L2 a2 e+ aStem and leaf display, 茎叶图
8 E6 N3 X* C- o$ d7 { H/ R5 fStep factor, 步长因子; W- t+ I! A1 `4 h
Stepwise regression, 逐步回归
/ i, {, J' G4 S6 P" ]0 gStorage, 存7 W B, ~ I7 F/ i
Strata, 层（复数）
. z! ^* Z0 @9 i! ]9 ?. hStratified sampling, 分层抽样8 X8 L g- `. U K9 f8 ?
Stratified sampling, 分层抽样" v2 n& d4 ]7 s" E
Strength, 强度5 A7 x# X/ N) ?" Y# [1 T# Z; a
Stringency, 严密性
: o) }6 A/ f2 N8 xStructural relationship, 结构关系
+ I6 s$ x0 B5 h7 KStudentized residual, 学生化残差/t化残差
' J+ K, ?7 u- z2 NSub-class numbers, 次级组含量
8 a" O U+ T' U* bSubdividing, 分割& y$ ?- L3 d* S, R9 q$ o
Sufficient statistic, 充分统计量
3 \8 U# M+ S% {- q5 d8 iSum of products, 积和
" o7 Y$ }$ F: s: @Sum of squares, 离差平方和* Z0 e/ I6 e5 }+ I- G
Sum of squares about regression, 回归平方和
" o8 v( F( @+ r: | mSum of squares between groups, 组间平方和$ U+ u5 X) a/ a7 R- W
Sum of squares of partial regression, 偏回归平方和6 L1 ]7 ?; Q/ g% M7 q' u& V7 y
Sure event, 必然事件
/ i* X2 e, F9 ySurvey, 调查
$ R$ ]0 y0 o$ O7 |6 w+ A7 i7 X4 VSurvival, 生存分析
* h# ?' s: W5 W5 p# |8 cSurvival rate, 生存率
( d, J) M4 T+ M$ JSuspended root gram, 悬吊根图( V' @4 C, z' d1 r) A
Symmetry, 对称* U, ]7 b) W( p* S$ i5 L7 r
Systematic error, 系统误差9 L, l3 H# O1 Z7 W
Systematic sampling, 系统抽样: A# _) L. a2 T
Tags, 标签0 w) F0 {9 t+ S2 l/ g8 Y$ l" _$ b. t
Tail area, 尾部面积" p7 D: ~) E7 O3 N9 W5 N& R
Tail length, 尾长
+ S# H2 F6 e+ J. jTail weight, 尾重, {( C5 x! v X7 m# l; b+ T
Tangent line, 切线
6 I* R" y/ m9 n; kTarget distribution, 目标分布
, B# B& O, l8 w' S9 ]/ e" GTaylor series, 泰勒级数
. N# g+ E& T2 |$ ?1 d9 \; GTendency of dispersion, 离散趋势
% l8 G. V0 M, mTesting of hypotheses, 假设检验- p% Q4 c* Z, ^3 b8 ?! M# Z2 j) s
Theoretical frequency, 理论频数! d9 h8 c) k/ Y( T$ e# U1 h
Time series, 时间序列# V' e( X+ ^: x1 L/ E: [
Tolerance interval, 容忍区间0 i: \7 L }$ ~- U
Tolerance lower limit, 容忍下限
, {2 m" T. j x+ h9 a4 ?' xTolerance upper limit, 容忍上限
, z8 o% C* ^& @! P. FTorsion, 扰率
' I/ s. E$ s4 v6 ^Total sum of square, 总平方和
2 m9 Q' `4 {! W; gTotal variation, 总变异
% I) }# i* t8 N# n) [Transformation, 转换# |% C2 S" @& t
Treatment, 处理
' e" e( n4 ]0 g) X2 k0 e {Trend, 趋势
9 r$ U8 z" T' }- t; I4 UTrend of percentage, 百分比趋势, ^, v0 g" x1 U9 d
Trial, 试验
4 y( o* g7 h1 E6 J8 B6 mTrial and error method, 试错法; r: ?; d( `1 E8 A' k
Tuning constant, 细调常数
8 j. v! |4 \: Z. rTwo sided test, 双向检验/ b( z8 `+ z) W. k
Two-stage least squares, 二阶最小平方
6 e, ?( E# H, a( yTwo-stage sampling, 二阶段抽样' ?( z9 b8 m& O, M" w1 c
Two-tailed test, 双侧检验
" c% J" i) C+ n% ?$ g# k' ~' s4 uTwo-way analysis of variance, 双因素方差分析
2 o. C$ Y; o( k; t3 L& X; V& LTwo-way table, 双向表
9 u3 Y4 S7 s6 c& sType I error, 一类错误/α错误
+ \% k' b& @3 Z: ~, gType II error, 二类错误/β错误+ ^' E( S" |) s
UMVU, 方差一致最小无偏估计简称* k S) W: o' o1 Z4 p; {7 X. w
Unbiased estimate, 无偏估计3 Q2 C0 J+ X; S! d: b5 S. q
Unconstrained nonlinear regression , 无约束非线性回归 a9 a: |, _1 _8 i) a0 h) u
Unequal subclass number, 不等次级组含量
1 B2 w: B0 A4 KUngrouped data, 不分组资料, j4 E0 J/ \1 v" b+ p4 a3 } l8 V
Uniform coordinate, 均匀坐标4 E+ a1 B+ |# q4 @% s
Uniform distribution, 均匀分布8 ~( S5 N2 @8 O
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计4 P! _) }( D& ^8 z; ^# [
Unit, 单元
: V* W, m' d' {0 ? BUnordered categories, 无序分类8 K) M2 ^4 y8 a; P9 _* i
Upper limit, 上限, q, l! i% h, M0 w* Z3 t! e# w8 Y
Upward rank, 升秩
: }+ H+ I [6 E! j8 f( \: IVague concept, 模糊概念5 s6 Q; x2 A/ c$ x. V% S8 M
Validity, 有效性- J% w3 J2 [9 ~
VARCOMP (Variance component estimation), 方差元素估计; l7 p, ]- k# Y. H2 i! f. A5 g
Variability, 变异性
+ u: Z G, {8 T! K& cVariable, 变量, D3 a1 f% ?- p) ~3 b
Variance, 方差
6 s3 p8 d+ V# M4 h0 G/ vVariation, 变异
, u1 _9 z# p5 }7 t' |- B* O: L1 ZVarimax orthogonal rotation, 方差最大正交旋转
6 |2 o/ s& z. @/ ?- m( qVolume of distribution, 容积
5 d5 s& I7 U' ~W test, W检验' c2 z, } P! V8 j3 P
Weibull distribution, 威布尔分布
# P1 E# w1 u: CWeight, 权数
1 d7 y# r' `* F- h& H XWeighted Chi-square test, 加权卡方检验/Cochran检验
- O# C" X- V* EWeighted linear regression method, 加权直线回归
: b' j0 H5 ]4 y$ q3 lWeighted mean, 加权平均数
% \" W: }; N$ }: h& J* v6 [Weighted mean square, 加权平均方差
5 |) @6 g1 m/ y' Y7 [. sWeighted sum of square, 加权平方和0 X/ t! n8 Y1 Y' |# Y& g. k0 K- a
Weighting coefficient, 权重系数3 s0 v" R. f+ J! V
Weighting method, 加权法
( l8 P3 Z9 n- C" r) @W-estimation, W估计量
; E+ R! B, Z" l5 _# t2 KW-estimation of location, 位置W估计量
+ D! ]; a7 e2 N; G4 Y+ WWidth, 宽度
2 P0 Z w R$ v2 o: qWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
- y6 F! ]: Q; S0 {+ \! [Wild point, 野点/狂点
+ _1 E1 E% F' L8 S5 x tWild value, 野值/狂值8 p& }( ` k8 ?; y# f& G+ b
Winsorized mean, 缩尾均值
: O+ o, x* X8 }' v8 J: r2 PWithdraw, 失访 , j6 B# H. E& K# Y9 S" p
Youden's index, 尤登指数
% y- q3 ^8 n6 k7 V1 o/ fZ test, Z检验5 o. p8 l' b8 Z/ O- F# G; u- ?
Zero correlation, 零相关" q; W$ q9 v5 Z W
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
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
