|
|
Absolute deviation, 绝对离差4 h) I+ Q) @+ b9 o' m- Q0 s
Absolute number, 绝对数# f& j% F& c5 g$ ~& D
Absolute residuals, 绝对残差
0 Z/ Z9 s- @) ]0 |Acceleration array, 加速度立体阵
7 G) H# o0 G3 Q. r I! IAcceleration in an arbitrary direction, 任意方向上的加速度
1 R% t* N2 k, j. R3 S/ xAcceleration normal, 法向加速度
- T2 `+ M; h) e$ @( g" L; k- NAcceleration space dimension, 加速度空间的维数
( T) |, i7 K9 V+ CAcceleration tangential, 切向加速度% D6 @, }3 W! I. {1 {3 X* T; ^
Acceleration vector, 加速度向量0 g' K" ^# D6 Z7 l ^
Acceptable hypothesis, 可接受假设! K" P# G- o& D0 Z# d7 H3 h- H* y
Accumulation, 累积; n" F; t' b, R5 T$ B0 O
Accuracy, 准确度
5 A; @1 y% i1 i" gActual frequency, 实际频数
/ |& @" a N8 zAdaptive estimator, 自适应估计量
) s! t) J5 X/ HAddition, 相加* v- h' E0 ~" l/ v% z
Addition theorem, 加法定理. Z2 l) ^4 @) a
Additivity, 可加性4 M9 z5 g6 A ?; |
Adjusted rate, 调整率! h0 x1 c4 R0 Q$ [5 W
Adjusted value, 校正值
- X* x. q! S# [6 Z; R6 N& F4 M. dAdmissible error, 容许误差
+ b$ V0 m( P: i. g; h* y" LAggregation, 聚集性* s3 ]( I5 M* c$ Q6 b! H: r
Alternative hypothesis, 备择假设7 W6 E, B3 J E$ A- p7 d
Among groups, 组间) [( Q+ C$ { B# {( b
Amounts, 总量
6 b+ x; @8 m8 dAnalysis of correlation, 相关分析; O3 Y5 i! x6 E/ \) |' @' j
Analysis of covariance, 协方差分析1 ]& b$ n* i) R z2 }
Analysis of regression, 回归分析( _# w1 }) Z* B" Q7 s( H
Analysis of time series, 时间序列分析
" V) Q2 Y/ r; C' BAnalysis of variance, 方差分析0 J) h1 y7 ?8 s: y) G- N
Angular transformation, 角转换5 U5 k/ Q, p4 `1 N& |3 j0 }
ANOVA (analysis of variance), 方差分析
! `; m% \" S: d9 CANOVA Models, 方差分析模型
) L: Q' U7 N+ J* B0 R5 a9 W" YArcing, 弧/弧旋
M" w0 I' H- @6 E0 D1 }Arcsine transformation, 反正弦变换8 J1 L6 A- n& U
Area under the curve, 曲线面积
) G V4 \ G% ]) [: k' yAREG , 评估从一个时间点到下一个时间点回归相关时的误差
6 a4 Y( m! o* ] VARIMA, 季节和非季节性单变量模型的极大似然估计 . Y, I" K9 r$ Y; I% U: X
Arithmetic grid paper, 算术格纸1 h* \7 b! j9 ]# O0 J
Arithmetic mean, 算术平均数
; h# {, f1 D( W! g7 }& [4 s cArrhenius relation, 艾恩尼斯关系
5 S$ l6 P' m$ iAssessing fit, 拟合的评估6 U1 b G4 I; F3 d8 B- Y
Associative laws, 结合律
! I5 r7 K7 Q; M. q. YAsymmetric distribution, 非对称分布/ g" s/ R+ k2 s. ^+ ^
Asymptotic bias, 渐近偏倚. E" i4 J! z! \2 F% p2 {
Asymptotic efficiency, 渐近效率
/ A( ?9 U2 u2 E. |7 W3 V, E: \2 jAsymptotic variance, 渐近方差" `, X. z+ }9 B4 R
Attributable risk, 归因危险度
6 _2 e% s6 m0 j" ZAttribute data, 属性资料
* G R3 B7 O8 LAttribution, 属性5 o$ i; p- p7 W
Autocorrelation, 自相关, z& s ?2 T* V6 ^' P5 M4 q. `
Autocorrelation of residuals, 残差的自相关9 a8 R! {) p+ Q5 ~' h" Y( J( D
Average, 平均数$ T: [: @8 f$ e% ]
Average confidence interval length, 平均置信区间长度; J! B5 h! h* R9 P" N4 d0 z/ b
Average growth rate, 平均增长率
1 K, S7 q' W% ?* v1 X5 dBar chart, 条形图& q* j7 ^0 ?0 ]. N$ y
Bar graph, 条形图0 M. f) L* {/ H! \
Base period, 基期
3 J! D5 ^; {2 {: KBayes' theorem , Bayes定理% ]8 w; K1 w4 Z, e7 f/ P* S6 e( M1 X/ T
Bell-shaped curve, 钟形曲线
% X$ y4 T& V7 O9 K m2 QBernoulli distribution, 伯努力分布0 g @* P" c" l3 I$ r! d8 \0 E
Best-trim estimator, 最好切尾估计量
& k8 E& H+ v" e" dBias, 偏性
+ G( ^8 V! O' x# W6 H% rBinary logistic regression, 二元逻辑斯蒂回归/ |- c( M5 O# B6 R) h0 f; N7 y
Binomial distribution, 二项分布( x& H' e" K9 i" ^! W. y( f
Bisquare, 双平方
* F( ^' o9 s* hBivariate Correlate, 二变量相关
; M x! ]$ y$ G; C9 WBivariate normal distribution, 双变量正态分布
' ~ w8 a* ^( P$ H) F' G: i' |Bivariate normal population, 双变量正态总体8 H0 q" V& ~5 c( O) y! e
Biweight interval, 双权区间/ S2 \) {2 L: n. r
Biweight M-estimator, 双权M估计量
/ y9 U* P* x3 [& p9 X! {4 ]Block, 区组/配伍组% a; G9 s! h( I
BMDP(Biomedical computer programs), BMDP统计软件包2 G5 f8 w7 @8 i" u; Y ~' G! D
Boxplots, 箱线图/箱尾图# W6 j! Y. \$ [. w7 m
Breakdown bound, 崩溃界/崩溃点: b6 e" v, Q0 {9 {
Canonical correlation, 典型相关# r [; [1 Q" |
Caption, 纵标目
+ d+ b% A6 g6 B1 s- _& ] tCase-control study, 病例对照研究" m: g/ L% x, X$ Z
Categorical variable, 分类变量# |! C+ p' \& H. q( P
Catenary, 悬链线% n2 R [& H; E: n6 V6 Y9 H: X
Cauchy distribution, 柯西分布% M) g( M! Q7 | q& E7 {
Cause-and-effect relationship, 因果关系/ t7 l( K7 o7 d, l
Cell, 单元4 K2 x q4 w& s+ e5 ]
Censoring, 终检1 T4 ^1 I% z0 {
Center of symmetry, 对称中心9 p" y, u" F3 C9 |
Centering and scaling, 中心化和定标; u, |' B& p) i# |. {1 K+ l
Central tendency, 集中趋势
! z; E5 P& E! |; L/ G0 uCentral value, 中心值
0 P. Y9 [4 S* U0 Y5 ~! d FCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
$ \6 A6 q8 B, ~2 \) NChance, 机遇6 \* s2 j* ~) O+ R+ T# D" i
Chance error, 随机误差
2 g+ J ^! L/ |2 ~# l$ MChance variable, 随机变量
* I, Y7 B7 a" L: d& {Characteristic equation, 特征方程
& |) x2 p6 i7 S) v' X$ dCharacteristic root, 特征根
3 w* C. P( j! R. d! F8 TCharacteristic vector, 特征向量! ?/ \% C3 q5 w A, x/ T6 F5 x7 F
Chebshev criterion of fit, 拟合的切比雪夫准则
, C) _! G' c$ {2 W& ^$ aChernoff faces, 切尔诺夫脸谱图
. D# E3 z# f9 Q8 }( n. Q! OChi-square test, 卡方检验/χ2检验
* R( C3 ~0 |2 e9 k! i3 ICholeskey decomposition, 乔洛斯基分解
: \! p% N# B8 Y2 t' t! W, ACircle chart, 圆图 ( G; ~- S0 A$ J
Class interval, 组距' o X( ^; Z1 K+ K, t( g. \7 \
Class mid-value, 组中值
) f7 X+ @# V. M/ R2 `Class upper limit, 组上限2 a+ E; r o! v
Classified variable, 分类变量
( L/ q3 f/ r' q& Z% ZCluster analysis, 聚类分析# m! r( @) S! T
Cluster sampling, 整群抽样
. ] W8 I, R& U5 N0 ^/ iCode, 代码
% G7 E& W$ |) vCoded data, 编码数据- s5 n7 M+ Y2 x6 H
Coding, 编码% |# }( G% k" v6 K
Coefficient of contingency, 列联系数
- b8 ]* f5 A4 W5 u& m: a0 D4 _Coefficient of determination, 决定系数5 v: A" i+ N T2 H; K
Coefficient of multiple correlation, 多重相关系数
# Z# ~3 k _2 Y; n; x' ACoefficient of partial correlation, 偏相关系数
+ U# [4 R# y+ s* O$ mCoefficient of production-moment correlation, 积差相关系数
; a3 C- {' s/ [/ i, M$ rCoefficient of rank correlation, 等级相关系数+ N l, P8 ?5 e
Coefficient of regression, 回归系数5 f3 `: A1 W/ {0 \
Coefficient of skewness, 偏度系数
4 [0 I; g1 P3 P' d2 b/ jCoefficient of variation, 变异系数
4 m+ l. a* {8 _: J/ o- }# E" A! Q7 S* uCohort study, 队列研究
8 Q) o. J9 x4 O6 `4 }- zColumn, 列
. ~2 V& E: j" W( m7 ]5 qColumn effect, 列效应6 s: x& G) e, Q$ N2 {
Column factor, 列因素
5 h' D3 q0 x1 Z: YCombination pool, 合并
& `& V0 x6 _& w. ?- gCombinative table, 组合表
6 D; e- ? U; HCommon factor, 共性因子+ n1 _. {! D, s3 d/ V; x
Common regression coefficient, 公共回归系数. s% m3 p: d& `9 z8 ~
Common value, 共同值7 B8 S/ A; Q5 ^$ I2 V: ?4 c8 I2 D' \
Common variance, 公共方差
% V. z# c9 p; f7 a. \, YCommon variation, 公共变异, p% ~; N% l5 M
Communality variance, 共性方差% z S- G) t4 ^6 l
Comparability, 可比性
: T3 D: C+ H# y2 x. n9 a, XComparison of bathes, 批比较
, R: m" X! v$ `" B* d2 j% fComparison value, 比较值0 [0 J# ?) [; k$ Q
Compartment model, 分部模型
* ~5 ]7 G( `+ q0 {Compassion, 伸缩
' l! z# G. w6 D; x7 Q5 cComplement of an event, 补事件: W, I8 ?% Y. N
Complete association, 完全正相关+ h& G* y0 \; ~2 Q
Complete dissociation, 完全不相关( A- r$ R1 Y/ I& w8 {! u+ s
Complete statistics, 完备统计量) o. }4 |- L+ n' M+ p+ X
Completely randomized design, 完全随机化设计1 Q7 p- y |0 ^
Composite event, 联合事件4 ~" D( r% I; C
Composite events, 复合事件+ K! B' @" E7 j$ L
Concavity, 凹性
' e* ~3 z$ F9 M* C3 G' ~' R7 W# EConditional expectation, 条件期望
) i" ^' t; E! r# |2 |0 Q" J0 W, @Conditional likelihood, 条件似然) R3 l. \* u( q( l3 J: O% f
Conditional probability, 条件概率
8 D& S# H" u; y& rConditionally linear, 依条件线性7 j0 \# Y$ L0 [2 f8 }
Confidence interval, 置信区间( ~: w, Q' S3 f2 p) q2 x; Y
Confidence limit, 置信限/ ~" G9 Y3 s: W% O
Confidence lower limit, 置信下限
% Y$ O# W) u3 [2 w5 vConfidence upper limit, 置信上限
) p! N7 {; h: YConfirmatory Factor Analysis , 验证性因子分析
0 T5 a' j* r, r) `. vConfirmatory research, 证实性实验研究0 [5 l: X& ^6 ~
Confounding factor, 混杂因素
/ p+ a3 u; |5 [% R% qConjoint, 联合分析
7 F3 {2 J6 o3 C) F) I9 q2 n& vConsistency, 相合性/ O' K6 z( U( z; h# j5 B5 Y
Consistency check, 一致性检验
) D8 f$ O+ ^5 v" K' A- w) k/ q6 `6 WConsistent asymptotically normal estimate, 相合渐近正态估计
5 B" ]" m7 Q* e2 ~8 V# M2 BConsistent estimate, 相合估计
" k/ X2 \1 L/ BConstrained nonlinear regression, 受约束非线性回归7 \' e8 x) a- @* O! O6 ?! G6 g# p
Constraint, 约束
: u4 M+ V ? h4 p3 c+ b) X( @Contaminated distribution, 污染分布# c: ~ L5 `0 t- R
Contaminated Gausssian, 污染高斯分布- v' T0 v" a/ D( d, w5 w2 f: i
Contaminated normal distribution, 污染正态分布. M! l1 {) ~% l' G1 L5 x
Contamination, 污染# ~) G' J- n* w5 d+ r0 B
Contamination model, 污染模型
# }7 l' r/ T1 e9 w: D9 hContingency table, 列联表' @/ m( L' w0 j7 G4 s
Contour, 边界线
8 X2 F* H9 |' C5 d0 \8 `- gContribution rate, 贡献率0 I- W$ ?. x* z/ l& q. O# P8 a2 m
Control, 对照
! ?: f0 J3 W3 S# K( H7 W0 Z, fControlled experiments, 对照实验" i. `3 Z, C8 Y' ]" D, ~7 H3 b
Conventional depth, 常规深度/ b x( D0 b& M: ]3 N
Convolution, 卷积
- E! C( e1 w( N" iCorrected factor, 校正因子, |4 j8 |; D6 E9 c: A+ F8 l( g
Corrected mean, 校正均值7 P+ ~7 m; U' {0 v
Correction coefficient, 校正系数
2 R% X3 {4 y# d8 X/ WCorrectness, 正确性$ k8 g/ u* J1 q/ v# B @ p0 x n
Correlation coefficient, 相关系数
; S* f( T# S! S( H2 K JCorrelation index, 相关指数& @$ I( d' j1 t) o( r2 {: z: _& X0 R
Correspondence, 对应! H8 A$ p- @6 D* ]8 {% g7 V
Counting, 计数
2 v: x4 c9 ]9 d; R6 Z$ L* f- RCounts, 计数/频数
* q) r& R4 {+ ~6 E/ gCovariance, 协方差
( a/ u7 v E+ x; ~* Y& FCovariant, 共变 2 Y- G7 R+ g* k( B
Cox Regression, Cox回归
u- k, r/ B" b2 O# C. o; qCriteria for fitting, 拟合准则
+ G! T: j4 L/ W9 J9 d* t' v8 m# BCriteria of least squares, 最小二乘准则+ j+ ~/ u9 [2 w' }
Critical ratio, 临界比+ {0 P9 c$ Y: J: w( G
Critical region, 拒绝域: `% m& V# l# y" Q
Critical value, 临界值
3 f: Y9 ?/ s2 J9 tCross-over design, 交叉设计
* k) O1 C3 o. a: S" q2 K9 r! S+ dCross-section analysis, 横断面分析, ?* v j- o0 h# u5 j
Cross-section survey, 横断面调查
& s* w! K5 r8 M6 x: iCrosstabs , 交叉表 * Y) S3 E! d7 F9 g- n
Cross-tabulation table, 复合表# l; b$ X- d, E! D
Cube root, 立方根" E$ m9 ^" l" G* s2 L' J
Cumulative distribution function, 分布函数
, q# [( n7 _6 U5 hCumulative probability, 累计概率
' k" Z; T" ^- l/ v1 }+ jCurvature, 曲率/弯曲
# u: L& Q5 v& WCurvature, 曲率' o5 Y3 l6 |3 U7 F& j
Curve fit , 曲线拟和 # ?& |+ m1 F ]+ u' c1 m2 x6 O
Curve fitting, 曲线拟合8 F. u7 _8 F; t% [
Curvilinear regression, 曲线回归
; I2 @; M: ?/ M! ]2 ^9 V" I1 m* UCurvilinear relation, 曲线关系
" [) {8 {( g5 g* PCut-and-try method, 尝试法
. R# W4 v! s3 t1 V2 L6 e" KCycle, 周期
% _8 V3 ^ e: v: _6 q# w9 t5 C9 BCyclist, 周期性5 V0 f: J# b2 y3 | j
D test, D检验
2 V: g) J& A" Y3 A( U) @' LData acquisition, 资料收集
) ^. A! G: H7 qData bank, 数据库
% l5 d' R7 I/ D" I; [. ZData capacity, 数据容量" ? e- G, m' Z6 c# [" i# c5 f3 d a
Data deficiencies, 数据缺乏
h- Q% d$ \$ C# KData handling, 数据处理
' P: ]& A# T" N2 D6 QData manipulation, 数据处理 s ]; M* {6 `" o) W3 |. a+ _
Data processing, 数据处理% d: E$ n1 Q( r7 ^( n+ g
Data reduction, 数据缩减
3 k% i! m0 k! `, F' dData set, 数据集
9 p# I6 p. s6 D6 t* g' Q7 ^$ PData sources, 数据来源6 m4 C8 E) v3 { i' u
Data transformation, 数据变换
( D* \& C1 B$ E$ F8 GData validity, 数据有效性
. [' M( R0 @- e+ O. mData-in, 数据输入3 L) z) h. c# y9 i% m
Data-out, 数据输出. _! T2 [: {1 v2 O( Q' T! }1 e
Dead time, 停滞期$ M; Z9 Y8 i- Q
Degree of freedom, 自由度
, @/ T& Z" C9 ?Degree of precision, 精密度2 U. P# v; U# s/ y
Degree of reliability, 可靠性程度4 s3 l) G4 P3 \$ J: |
Degression, 递减
; o) n- W7 {( bDensity function, 密度函数3 i4 r2 N0 `: C0 p3 C0 c. M
Density of data points, 数据点的密度- F+ j* q, e' H6 @" \: }: V- `8 F
Dependent variable, 应变量/依变量/因变量* l# H0 Q. t, ^) c; m
Dependent variable, 因变量4 e1 W; |7 i6 G& e0 v
Depth, 深度
+ g# y- x1 _4 p( LDerivative matrix, 导数矩阵
0 K. b& n/ p+ `- u9 G5 UDerivative-free methods, 无导数方法8 i7 T# \: N2 R
Design, 设计
5 [7 D0 P' [1 h" C( _4 x& _8 pDeterminacy, 确定性& j1 q( D9 E" }& H8 b7 f
Determinant, 行列式) A0 D- p/ e, b" P1 }' O+ @
Determinant, 决定因素) t/ h" G: J& E; w8 [
Deviation, 离差
5 y: |0 e7 B+ h# v) YDeviation from average, 离均差1 ]- A* H- I0 f
Diagnostic plot, 诊断图1 f# ~/ ]; l" j$ t
Dichotomous variable, 二分变量. ~" y6 W: G; V9 B
Differential equation, 微分方程9 i7 d; T. M# e
Direct standardization, 直接标准化法# u. o% N# g; u
Discrete variable, 离散型变量
& W5 \. @4 w8 f+ G7 L7 RDISCRIMINANT, 判断
- a* F+ ` H& Z. |Discriminant analysis, 判别分析; s5 C2 u* x7 A- Q# H
Discriminant coefficient, 判别系数
% H3 a: D3 w1 X; {Discriminant function, 判别值
! [$ `9 A" S9 bDispersion, 散布/分散度
7 b- A1 g' S' ~Disproportional, 不成比例的
, B/ |/ J( p! j/ C* @/ _$ i- KDisproportionate sub-class numbers, 不成比例次级组含量
0 e' {: T* Z1 x3 l2 pDistribution free, 分布无关性/免分布
8 }1 h" K& r6 ]Distribution shape, 分布形状
9 u' E* B+ c* v/ `' b+ e, oDistribution-free method, 任意分布法
) p% m. ]8 E% C3 h- f! ?, nDistributive laws, 分配律
5 I* f/ A! h* a) J2 L3 v0 L0 zDisturbance, 随机扰动项
9 W# }5 A0 J! SDose response curve, 剂量反应曲线, M& U9 `! P, J4 Z! z+ |; m. y9 V+ d
Double blind method, 双盲法
8 j6 H# v+ o2 H2 I4 S" Y( ^Double blind trial, 双盲试验
9 F5 j, X# u5 \/ \2 V: {& \' ]Double exponential distribution, 双指数分布1 x$ K0 t" n- ?& m. w7 ^# A
Double logarithmic, 双对数) l9 \: W! a& F9 [6 F
Downward rank, 降秩
9 e( s6 [! y. a, n# pDual-space plot, 对偶空间图+ W4 B# B% U& _. O
DUD, 无导数方法7 Y! o- v( L9 k
Duncan's new multiple range method, 新复极差法/Duncan新法" A r( l6 ~. i$ L% D, i6 |
Effect, 实验效应 z3 X8 B9 H7 K
Eigenvalue, 特征值
J3 s D, A: ` h9 _Eigenvector, 特征向量
' C7 Q: }# Y5 R) M T" HEllipse, 椭圆1 `: b; b! R1 X8 a6 }+ I
Empirical distribution, 经验分布9 K; {5 W! {4 B
Empirical probability, 经验概率单位
5 e6 N5 ?3 \; G* \. d/ sEnumeration data, 计数资料
% ^% Y/ J# L0 O7 B& L! f3 N- jEqual sun-class number, 相等次级组含量
' X( t1 `" c$ S% P8 PEqually likely, 等可能8 }8 q5 A; @7 O1 m/ O; ~
Equivariance, 同变性4 v; R- @' k/ T( I% R8 y' I, j% r u$ i
Error, 误差/错误" s; A ]4 O5 X3 [( P( H
Error of estimate, 估计误差& z+ D. n. {& A
Error type I, 第一类错误
# L6 M! d0 }5 } @, {/ H. ^! x# sError type II, 第二类错误1 H. [" G' V' Z5 f( L' |. e$ c. Q* T
Estimand, 被估量
( t4 g' P3 l! b$ _8 EEstimated error mean squares, 估计误差均方" v* w" m8 p! x, J
Estimated error sum of squares, 估计误差平方和/ b4 j; i1 o, z, e2 y* y) C9 J
Euclidean distance, 欧式距离
/ W) a* n j" P) f1 R8 E* b: ]+ REvent, 事件/ s$ p4 W5 D: ? S. O7 w% w
Event, 事件2 y2 G/ v! ^7 |: p6 k* |6 f
Exceptional data point, 异常数据点: h$ d/ }% X5 W" E
Expectation plane, 期望平面
p; k2 ?0 k3 I0 G2 i) GExpectation surface, 期望曲面/ i0 d" o1 \" G
Expected values, 期望值
& O, R) A. V5 y4 F, T0 F7 AExperiment, 实验4 }$ t" ? E1 J
Experimental sampling, 试验抽样
: X6 }# [- k) e- }4 gExperimental unit, 试验单位
; C8 @- j3 @, u4 r1 I" P; LExplanatory variable, 说明变量
4 m/ S% |' Q5 u* |+ R: o) bExploratory data analysis, 探索性数据分析
! _5 n4 Y, o9 x, ?Explore Summarize, 探索-摘要
0 e& D5 }: I( R: N- s; b4 s0 nExponential curve, 指数曲线/ l# z- [! ?1 m; I) D" _& w
Exponential growth, 指数式增长
- U4 ?; m) J$ p8 d: oEXSMOOTH, 指数平滑方法
5 [1 x8 F4 L$ P( e; u! rExtended fit, 扩充拟合
1 z- K' i) N% B; [, gExtra parameter, 附加参数
! A2 T% ?) C" C: yExtrapolation, 外推法
3 \2 h( |8 |! q: tExtreme observation, 末端观测值
3 S8 d3 D" |$ I4 _( O# @' c0 {: K" KExtremes, 极端值/极值9 L* f1 H! l5 t5 m' W( @( u& j
F distribution, F分布$ b$ Z* {7 m% n& B5 {( k* D
F test, F检验
Z) V5 \7 \7 F# DFactor, 因素/因子" {5 d0 `. \/ h0 M1 T+ |
Factor analysis, 因子分析
% @9 c- Z/ O3 n3 D R; ?) U* x* q4 rFactor Analysis, 因子分析' o5 E" f5 x% a: p' b3 a
Factor score, 因子得分 9 U+ x4 D/ L% v$ y" j7 s+ t
Factorial, 阶乘
- u8 x# n8 Z& e2 f l9 TFactorial design, 析因试验设计8 _3 O5 B h1 z
False negative, 假阴性
* x$ k; g9 }5 L# E7 C$ xFalse negative error, 假阴性错误8 ?; R9 b6 T/ H! q
Family of distributions, 分布族
) C8 _# w" H( N0 R$ u5 HFamily of estimators, 估计量族
2 r5 O9 R1 P8 l% sFanning, 扇面- M: W0 Z" t. F! s! N8 {
Fatality rate, 病死率
0 ]8 G4 _' P* J/ P* VField investigation, 现场调查
; ?9 }9 {4 F$ D2 e; |" qField survey, 现场调查
9 V" s9 i9 q0 @, rFinite population, 有限总体- P r3 z# r( f n; o
Finite-sample, 有限样本
1 w @# X5 O2 w& `- C1 ^First derivative, 一阶导数: O4 L3 F) @. Q* Q4 }% `
First principal component, 第一主成分: B5 L; f% V, {5 [4 ~ X) f/ b$ ^( k
First quartile, 第一四分位数
* u. U+ D/ T7 {2 l' _4 jFisher information, 费雪信息量3 j/ E4 H+ {. B( C! ?
Fitted value, 拟合值
! \8 x! H+ P P0 P. R* U5 EFitting a curve, 曲线拟合
' ^, S" ^; q" O3 z2 e+ IFixed base, 定基# A( q+ s( S6 O7 G
Fluctuation, 随机起伏. ?# W r7 Z% L1 v! b
Forecast, 预测5 Y# R' v1 y# G! Y$ G% b8 ]. ]
Four fold table, 四格表
7 R# d" v& C3 ^ r/ C2 pFourth, 四分点/ @) N" b4 w; S* ]2 i
Fraction blow, 左侧比率
6 g1 G7 k+ |% S7 A9 {+ ?Fractional error, 相对误差; @) c4 l( Z0 I+ g
Frequency, 频率! F% i& O; H% V- o# L8 [) K) h. y
Frequency polygon, 频数多边图' G- T7 W- D0 i J' D" V! S0 `
Frontier point, 界限点) B2 g! @" c' E1 |+ Y9 Z( f
Function relationship, 泛函关系! C, x6 u6 y2 B" K+ x9 C1 \
Gamma distribution, 伽玛分布* [! t4 J8 ~3 i# h1 ]
Gauss increment, 高斯增量
- v1 Z+ i& X" w QGaussian distribution, 高斯分布/正态分布$ u1 K+ ?% Q {0 a& I, s+ I
Gauss-Newton increment, 高斯-牛顿增量% H9 J& o S) B- ]
General census, 全面普查; C' f" y1 H4 X: ~( u# r% a9 ]
GENLOG (Generalized liner models), 广义线性模型
Z- O- P2 e9 [1 Y1 U& a5 mGeometric mean, 几何平均数
/ n( k" e* ~8 j S; l) ~Gini's mean difference, 基尼均差' X" H7 [: @" W- _" J' L) \3 } m3 S
GLM (General liner models), 一般线性模型 6 n& L( S3 m# `' P" x& H
Goodness of fit, 拟和优度/配合度
! B5 ?; Z+ M7 ^; l. ?) PGradient of determinant, 行列式的梯度
/ y/ ^/ S& ?: _4 ~/ e* BGraeco-Latin square, 希腊拉丁方5 S1 ]% ]0 F! U' S* ~; j
Grand mean, 总均值
' `( ?& V/ y: E vGross errors, 重大错误. O3 m. O; T; [- W: f& F, L
Gross-error sensitivity, 大错敏感度
4 L% `. X# K! K8 t" SGroup averages, 分组平均4 L' Q" X/ Y/ |! q
Grouped data, 分组资料& X _0 e6 q4 {# H4 H) n( g
Guessed mean, 假定平均数' I5 E- e! x Z6 X, n
Half-life, 半衰期5 r! o; L$ K% b( n
Hampel M-estimators, 汉佩尔M估计量: ]. Z) j. _+ [9 S' j( B
Happenstance, 偶然事件' a7 M/ d. U/ g2 E. p6 c( u5 E
Harmonic mean, 调和均数
' A, P( H2 K" U; C! b1 A7 s2 g0 PHazard function, 风险均数& T* |) X/ x# P* t( m( ?5 E+ e
Hazard rate, 风险率
( G/ W6 S2 A" n, W$ j- F% K, `Heading, 标目
# C' Y9 ?9 ]& w& y# u8 XHeavy-tailed distribution, 重尾分布& o/ U8 e' a- A% \+ Y2 h9 {. W
Hessian array, 海森立体阵# H& g0 a3 q. {' ]/ ^/ H! }) v; N7 p
Heterogeneity, 不同质
( [8 U ?. Y" ^. {3 l2 l3 I+ q* U, H6 aHeterogeneity of variance, 方差不齐
5 L# T0 J# O5 G9 ]3 \; t4 F1 eHierarchical classification, 组内分组
4 _7 r6 n, W& ~" g' J4 w/ Z, HHierarchical clustering method, 系统聚类法
; ~; k% v5 B7 q8 c5 u* dHigh-leverage point, 高杠杆率点
8 ]3 A- w/ @" c* w: M* H3 BHILOGLINEAR, 多维列联表的层次对数线性模型
/ g* C; I/ g1 J! z+ lHinge, 折叶点! z* H8 ]* Q- `" O, q
Histogram, 直方图1 `1 x$ t( B- A" l7 W4 P
Historical cohort study, 历史性队列研究
1 t# U( @4 K; I9 ^$ t) VHoles, 空洞8 R; v0 @" C* J7 z
HOMALS, 多重响应分析
+ B" M# j9 G8 [3 t- ~7 `Homogeneity of variance, 方差齐性. X$ @) w' ?; j. q2 `
Homogeneity test, 齐性检验
b T# z+ G9 YHuber M-estimators, 休伯M估计量% V1 ?9 m, f, l+ F; Q+ M! r
Hyperbola, 双曲线: G1 B/ g# E! R9 ?. P7 k
Hypothesis testing, 假设检验- U Y0 v. e& H2 c/ z2 {0 w1 y
Hypothetical universe, 假设总体0 u( I5 e# V2 i8 B
Impossible event, 不可能事件
) F _. ^) h" Y' e9 F4 zIndependence, 独立性
, k# j* b o. |% Z( ^Independent variable, 自变量' U0 Z1 ~0 A- O, {8 _
Index, 指标/指数& Z2 G. Y4 i! T" ]: T& f
Indirect standardization, 间接标准化法
1 W0 R, ?3 H. V* c) W. H, C+ LIndividual, 个体6 k0 P2 ?+ [, }; T
Inference band, 推断带4 _( Q* \; [: X, U" N8 i
Infinite population, 无限总体
' ?$ R! l5 ?4 Y5 }4 R3 kInfinitely great, 无穷大! M3 ]6 H- |" X$ J2 W0 X. q7 y
Infinitely small, 无穷小
. ]) h6 c4 U; H) y% N, @; wInfluence curve, 影响曲线
) J4 c j8 e# ]" p# T2 @3 NInformation capacity, 信息容量$ B/ c1 y5 h" e) r9 K1 L7 P0 w$ C1 Z
Initial condition, 初始条件
" B- k( Z! N+ H. h5 l7 bInitial estimate, 初始估计值
+ F, V- o0 q% f' MInitial level, 最初水平0 M% q* D* ~3 H* Y
Interaction, 交互作用
a/ B0 z$ `& ~" ?6 A! IInteraction terms, 交互作用项
# F; m- r$ e' ~, m+ R! v- s( ZIntercept, 截距
' d% _! ^* W' H4 H4 h2 A! A4 IInterpolation, 内插法
, @3 V3 J3 M- o& G6 J4 |; s4 ?: h! FInterquartile range, 四分位距/ g4 j+ f5 H( p2 t0 S/ N$ Y
Interval estimation, 区间估计& i$ X5 n8 @0 x7 h$ b. G1 u3 A( N
Intervals of equal probability, 等概率区间& j/ \# |3 U! z% s8 \. h
Intrinsic curvature, 固有曲率1 t! T% S: P- R0 G& Q0 M: x
Invariance, 不变性% K5 |9 [% ?, m- F$ U& ^0 B
Inverse matrix, 逆矩阵1 J# Y; m- w$ E& `( L3 c
Inverse probability, 逆概率
; s4 d! V" x& ?/ a2 q/ D: `Inverse sine transformation, 反正弦变换) g* j0 R6 z3 ^+ t/ e
Iteration, 迭代 ! ^" Q$ N8 h, k
Jacobian determinant, 雅可比行列式
8 V+ W3 j) r1 kJoint distribution function, 分布函数
8 H* |# }% H5 o3 i$ b7 ~Joint probability, 联合概率
* p4 E! T# m$ r8 B1 Q7 D2 }2 G; n ZJoint probability distribution, 联合概率分布& x, T0 T( N m2 `4 o
K means method, 逐步聚类法
' i& W9 Y0 J% cKaplan-Meier, 评估事件的时间长度
6 E- M9 [* D+ ^# f. }6 u+ r# eKaplan-Merier chart, Kaplan-Merier图) ~6 Z, E4 }: j9 ^# A4 @! f, O* I
Kendall's rank correlation, Kendall等级相关) I% B& M* [9 ], n& w0 x: z; K
Kinetic, 动力学9 I! o! X- Q9 W' R+ T7 O, S
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
# A" H: m% j- [3 H" YKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验3 c/ M- c% p9 l! {
Kurtosis, 峰度
/ W3 H8 w7 w# D4 ZLack of fit, 失拟
9 j1 [8 c5 m5 K f: o( D/ @; t+ ^Ladder of powers, 幂阶梯
: z3 G0 {! W; h( ~+ A) SLag, 滞后1 ^- q* u# E" h% s
Large sample, 大样本
8 P$ X8 a" X ]9 ?' ?! ~Large sample test, 大样本检验, Q/ ?& a% ], P% I3 P
Latin square, 拉丁方0 M2 M. v, ?' g' X8 L
Latin square design, 拉丁方设计
2 d9 `& l) L* ]$ y2 I! qLeakage, 泄漏
+ x. p3 s. f" ^Least favorable configuration, 最不利构形8 j. ?5 v) R+ ~8 b
Least favorable distribution, 最不利分布
# \- i& ]' r- h4 W: a3 ILeast significant difference, 最小显著差法
0 |- P( l N3 P' ]5 PLeast square method, 最小二乘法
* T+ m8 k9 Y8 a# @Least-absolute-residuals estimates, 最小绝对残差估计. J. e* x0 I9 v M$ W
Least-absolute-residuals fit, 最小绝对残差拟合7 c" ^) A, X- b
Least-absolute-residuals line, 最小绝对残差线 j/ H s9 c# t; ]
Legend, 图例9 {+ K" `* P S" G9 _* t
L-estimator, L估计量; x$ N1 X, V; a
L-estimator of location, 位置L估计量/ a9 |6 Y" S& }9 |3 ^
L-estimator of scale, 尺度L估计量, x. ]6 H7 ]* M& e0 ~$ G$ Y" p6 Z
Level, 水平
* M% q$ A$ s' ~9 ^5 j" ILife expectance, 预期期望寿命) {. ?0 }; Q( g& v) `
Life table, 寿命表
$ _3 z3 k) X* X- @$ SLife table method, 生命表法9 S5 d& |9 s0 |
Light-tailed distribution, 轻尾分布
, B6 ?) o3 f+ Z0 uLikelihood function, 似然函数
8 N6 r& b& |- R4 i9 ALikelihood ratio, 似然比
' \7 Z/ }+ \# G0 i9 uline graph, 线图3 Y" Z; ]) j6 `* k/ Y3 r$ e2 s
Linear correlation, 直线相关
8 ] y. t) E$ k" s0 Q& A& SLinear equation, 线性方程6 e) P. o, N4 @8 |
Linear programming, 线性规划
2 n0 K( |, r+ @0 GLinear regression, 直线回归; \9 \% S$ X# m
Linear Regression, 线性回归
# A% ~3 R6 u, XLinear trend, 线性趋势; Q# h# u, V1 D1 q
Loading, 载荷 & H$ u4 \6 N7 f
Location and scale equivariance, 位置尺度同变性# d0 o* m: c0 Z- {& ^( V5 k
Location equivariance, 位置同变性) g' E2 i6 `7 K3 ~+ L
Location invariance, 位置不变性
2 {; |" |' B; x$ n; lLocation scale family, 位置尺度族0 I8 w$ Q2 k0 h) u1 F8 H
Log rank test, 时序检验
- E+ M7 u5 }% ?8 ^8 |7 cLogarithmic curve, 对数曲线
5 ]) ~! O' x. c8 g5 B$ OLogarithmic normal distribution, 对数正态分布
+ v4 x" ~0 {1 dLogarithmic scale, 对数尺度1 k- i1 d/ N, h( L# Y, Z6 Q- V
Logarithmic transformation, 对数变换 X/ x* \; L5 r/ n( N) R( D* W
Logic check, 逻辑检查
' Q5 n& ]# P2 \/ ^! c9 U5 {+ |Logistic distribution, 逻辑斯特分布+ f8 g+ b' I) g
Logit transformation, Logit转换; k* B+ |; J- \
LOGLINEAR, 多维列联表通用模型 6 F7 n+ p; ?+ V: S* b
Lognormal distribution, 对数正态分布
& Z: Y/ j( H2 Q& R; _ n# h0 pLost function, 损失函数
( m# b8 X; ~0 M2 o; P9 R6 t& B; `Low correlation, 低度相关* J0 [7 P. {% s( ~4 a
Lower limit, 下限' q3 }% ]! n0 t
Lowest-attained variance, 最小可达方差- F5 s/ l! V- |# Q7 r2 k
LSD, 最小显著差法的简称6 A0 C7 X( D+ H
Lurking variable, 潜在变量( O/ `$ l* _" O! ]4 q0 m
Main effect, 主效应
+ i- E2 y2 Y: M' m ], J% h% L2 DMajor heading, 主辞标目: b) s, I! N8 G+ F* B2 G
Marginal density function, 边缘密度函数8 ~ s$ {9 j% N& }6 ~
Marginal probability, 边缘概率4 l! f* O. d; }1 F9 h) _
Marginal probability distribution, 边缘概率分布
# A/ g( O0 C2 P; m/ J: k/ }Matched data, 配对资料
/ C$ Z$ W# X6 ^# gMatched distribution, 匹配过分布
3 h' _- t1 R/ gMatching of distribution, 分布的匹配
, B% W$ x! f+ Z- r cMatching of transformation, 变换的匹配) n, d3 ?6 M% y" ?7 y) ^
Mathematical expectation, 数学期望4 b, p1 Z" J+ U
Mathematical model, 数学模型
. \ P' X4 f: U. u* i/ H& H( z: ~Maximum L-estimator, 极大极小L 估计量% Q+ o" S' S5 a; t3 b) E( a
Maximum likelihood method, 最大似然法
# @# y7 L0 n1 N% {0 kMean, 均数( X8 {8 T+ I$ B* J' ^ ?4 a
Mean squares between groups, 组间均方
( ~5 w9 H4 J. x- }3 J/ oMean squares within group, 组内均方
5 l% d' m. N6 E! f! `Means (Compare means), 均值-均值比较/ c- ^* L2 L( m0 H' ]; M
Median, 中位数1 _+ R' A7 t" P2 V7 G4 J) \5 B
Median effective dose, 半数效量
- k1 M+ s& ]0 CMedian lethal dose, 半数致死量
8 |. l& u# s% R, s1 o0 YMedian polish, 中位数平滑: m/ [9 V7 r; m# g7 ^7 O; X
Median test, 中位数检验
. x8 r( N+ [+ [' @9 `" KMinimal sufficient statistic, 最小充分统计量1 ]* A$ j! ]& C! E3 z+ I( u
Minimum distance estimation, 最小距离估计
/ S" b7 t+ i" ]0 zMinimum effective dose, 最小有效量1 v5 }- h6 v9 T0 o% b
Minimum lethal dose, 最小致死量 C* z" Z7 z+ k3 j$ M
Minimum variance estimator, 最小方差估计量+ s2 A- U; {$ N
MINITAB, 统计软件包: v/ s$ t9 f) B: ~) z7 T) e2 K
Minor heading, 宾词标目
7 R8 t* j1 S7 nMissing data, 缺失值- c' J6 A# {9 k% n1 S
Model specification, 模型的确定6 d: X1 }0 S. I+ g' N1 i/ ]
Modeling Statistics , 模型统计
! Q1 G( J& r& bModels for outliers, 离群值模型
7 \1 T: s8 r: Y& g9 e: xModifying the model, 模型的修正9 k& ^0 i" T* d# D/ d6 |$ F
Modulus of continuity, 连续性模) m3 z' G/ ]" h$ A) N+ W7 \! ]
Morbidity, 发病率
+ ?5 X- y) d$ FMost favorable configuration, 最有利构形
3 I# O! K, |* _! V9 s4 ?! N' v e- z: FMultidimensional Scaling (ASCAL), 多维尺度/多维标度, l: ^& t5 F* b- h5 I5 e+ | k
Multinomial Logistic Regression , 多项逻辑斯蒂回归
^8 y/ g- ]$ S$ A& ]8 J. hMultiple comparison, 多重比较
' y1 A# ^* f" _0 bMultiple correlation , 复相关
. p( f; {8 e, a! jMultiple covariance, 多元协方差
# Q2 ]" E! f) {, N4 {( V7 RMultiple linear regression, 多元线性回归5 _& y4 y. n- L2 Q: c
Multiple response , 多重选项) I1 S+ H% V9 |' Q5 ^
Multiple solutions, 多解9 s! a" I" c7 y- X3 J* Z1 A
Multiplication theorem, 乘法定理
' l, v2 [+ D0 x! F0 kMultiresponse, 多元响应7 q* X, ^/ V0 \5 | ]6 ^. T+ d
Multi-stage sampling, 多阶段抽样
) ?8 i5 _0 o9 h: V$ v( r+ qMultivariate T distribution, 多元T分布2 }, v. b# `' N* x
Mutual exclusive, 互不相容' R# Z$ L) i6 Q
Mutual independence, 互相独立+ f, v& r1 k2 q4 L5 c0 p
Natural boundary, 自然边界- r0 o2 f6 Q! m- H9 x+ P; T' i
Natural dead, 自然死亡
% G$ I, F3 f5 S9 H) hNatural zero, 自然零( o6 u+ v }" r# u% d2 z. f
Negative correlation, 负相关0 U6 t& n9 H* k- X2 M7 }
Negative linear correlation, 负线性相关
N2 C# f( \1 z- P' MNegatively skewed, 负偏
9 v$ F" s6 j* h3 e5 g9 y& GNewman-Keuls method, q检验
% N2 F8 |# n4 X# L/ INK method, q检验
' o9 w @' N/ X% f) w( k; DNo statistical significance, 无统计意义
, {9 O% x( c8 `Nominal variable, 名义变量! t9 p1 L2 U6 l
Nonconstancy of variability, 变异的非定常性. U2 Z) n- n0 O- Y% {% h+ \8 b
Nonlinear regression, 非线性相关, l3 k: ^+ B7 b B( o' d
Nonparametric statistics, 非参数统计
: j) p% ]3 T: C* `$ C$ zNonparametric test, 非参数检验3 I# v# v5 |* x" }4 A
Nonparametric tests, 非参数检验
- E" V% }( E: b+ N2 }+ zNormal deviate, 正态离差) `; k, x; m+ O( v' ^8 b* d
Normal distribution, 正态分布
! A- ]5 ?! s" j+ O; S6 {# zNormal equation, 正规方程组
Q2 C J2 ]5 \8 @' WNormal ranges, 正常范围
' d# y/ ^2 a8 i+ U7 J7 a8 QNormal value, 正常值
' u% i( |% t) v/ tNuisance parameter, 多余参数/讨厌参数: h( B: b: j0 p7 m
Null hypothesis, 无效假设 0 u0 d) J- m; x
Numerical variable, 数值变量
4 I* u1 W" h3 A n- n. ZObjective function, 目标函数
0 s: k8 f; J4 O0 ?4 f: V- z2 |Observation unit, 观察单位
# @, J3 g: ]9 }Observed value, 观察值- }8 g3 C# U$ t _/ e
One sided test, 单侧检验" G8 W8 t4 A7 O: C8 w3 E" h7 Y
One-way analysis of variance, 单因素方差分析& I, Z3 {: `. Q1 Y. s3 Z4 d+ k
Oneway ANOVA , 单因素方差分析
- G0 ^: H' w, S2 P2 j$ |Open sequential trial, 开放型序贯设计
& g+ B; ]' y S: ^Optrim, 优切尾
0 j3 ~ ]& q0 o' H; ~) J; ]9 ZOptrim efficiency, 优切尾效率$ l5 y$ T' L6 M% J" B+ ?4 @
Order statistics, 顺序统计量
6 V5 T5 w8 r0 d, G, q! yOrdered categories, 有序分类, V4 c; Y9 R! v' h) F! v+ N
Ordinal logistic regression , 序数逻辑斯蒂回归3 r! R- M" o$ W V: b
Ordinal variable, 有序变量
, Q' d& H% M7 [4 y: dOrthogonal basis, 正交基& {9 e4 s7 a$ e
Orthogonal design, 正交试验设计3 | H3 i6 q7 q2 V' _
Orthogonality conditions, 正交条件% i# [! @: r: M2 G+ P& l8 j
ORTHOPLAN, 正交设计 2 v, P: k% Z2 j9 [. u
Outlier cutoffs, 离群值截断点; O! O- y' |1 o: ?: A
Outliers, 极端值
# P5 ?: \& m/ q$ V3 ]# JOVERALS , 多组变量的非线性正规相关 ' X8 e3 n0 V0 G
Overshoot, 迭代过度
$ e- o8 N. {7 ~2 hPaired design, 配对设计6 o' i" A" i+ i" ~8 |- N
Paired sample, 配对样本8 Y8 Y3 K% v" T) J2 u# @
Pairwise slopes, 成对斜率
4 D& T( b& t7 ~/ [Parabola, 抛物线$ q( \0 n% D/ D( U5 b
Parallel tests, 平行试验
( l9 I. f5 _2 [Parameter, 参数
1 F# b5 K, c* f4 I& ~Parametric statistics, 参数统计
- A4 Y2 O: \ w$ K# L3 [2 vParametric test, 参数检验( o. v3 p$ l9 j6 @
Partial correlation, 偏相关
% u) r! M" _; Q$ ]+ G3 H$ DPartial regression, 偏回归
* C1 Z/ C4 l& SPartial sorting, 偏排序
2 _; h2 O0 g0 G- v7 PPartials residuals, 偏残差
4 u* t$ \, ~5 [* H+ k/ VPattern, 模式
3 X0 n% e0 K0 x1 s3 ZPearson curves, 皮尔逊曲线
2 A5 e2 ]) G) m( _: APeeling, 退层! D& K" u4 `( w, ^
Percent bar graph, 百分条形图
8 h5 ~( G) Z% T; WPercentage, 百分比
. ^. ]1 F r" ~* u* Q3 B K# jPercentile, 百分位数# m$ E" Z+ O, ^2 b' g: @
Percentile curves, 百分位曲线
7 P; X" L2 M' ?6 i. ?Periodicity, 周期性: L& Q* K7 g7 Z' P& R$ V9 x: t: M' S
Permutation, 排列
\$ L; T L! v* c& A" H# X) KP-estimator, P估计量
V, Y9 y0 B' Z! sPie graph, 饼图
, s! G4 x6 {9 B& J/ n$ r( i# }Pitman estimator, 皮特曼估计量
9 F ?' s$ b* |Pivot, 枢轴量' n! E- f3 ]4 C8 X
Planar, 平坦. e+ }& h2 y9 J
Planar assumption, 平面的假设* m; F# Q8 Q7 B7 @3 E
PLANCARDS, 生成试验的计划卡& f6 D1 g/ a) h/ W0 M
Point estimation, 点估计8 {. A* ~# U: c4 R/ Y
Poisson distribution, 泊松分布- E8 w2 H8 q( F% |0 j" g( D9 B
Polishing, 平滑2 F9 P/ l0 H6 K2 F# |
Polled standard deviation, 合并标准差
( K; i& Q6 V" k1 I& V k1 `- m2 {Polled variance, 合并方差
) X* v7 N* w; U- @Polygon, 多边图# n1 a. }1 L; g: Z/ J
Polynomial, 多项式0 B8 Q4 O* R# p7 V* ~
Polynomial curve, 多项式曲线
: V; B) a" p" F+ B0 OPopulation, 总体
. I1 Y* z3 k+ [ M% zPopulation attributable risk, 人群归因危险度0 ^. `$ j) x3 {/ x: a2 G$ I) G
Positive correlation, 正相关; Z3 `3 @+ J! g1 B
Positively skewed, 正偏( i! [/ x* M( L$ t) \+ ` y
Posterior distribution, 后验分布
, I3 x# I7 ~6 k5 lPower of a test, 检验效能
4 j6 I( J) d( n3 lPrecision, 精密度4 e# i, Q5 e" W" \' c( o; N
Predicted value, 预测值5 Z; U& B, g/ ?- h2 L
Preliminary analysis, 预备性分析9 I3 F8 y7 {( a- y' \5 Q0 }
Principal component analysis, 主成分分析
- q5 k4 f R, E/ d; @* O, GPrior distribution, 先验分布% s6 ? r! P! V' m
Prior probability, 先验概率
. i7 x- K* r: N( rProbabilistic model, 概率模型
7 ?9 @+ t+ J+ W% L4 W% @& ~probability, 概率
2 Z9 ?3 J$ o+ B q! P9 \4 j7 bProbability density, 概率密度
1 G* T9 d; i0 jProduct moment, 乘积矩/协方差
( P8 `5 o. ?6 ^4 A! ]- r, I4 FProfile trace, 截面迹图
% W) |4 s5 s% {6 {5 s% BProportion, 比/构成比3 J6 y4 o; J6 q) f
Proportion allocation in stratified random sampling, 按比例分层随机抽样4 ~" x" ]4 t- H# f9 k) Q
Proportionate, 成比例
" Z3 E- V: \" H$ k# u) ?. {Proportionate sub-class numbers, 成比例次级组含量5 V5 s- g, v6 J" }/ H
Prospective study, 前瞻性调查; S* ~2 C: r# Y. S
Proximities, 亲近性
- X: C* k0 U* ?0 o& e( CPseudo F test, 近似F检验
) U4 j; k/ t- @* u7 YPseudo model, 近似模型
& n+ U" G' p( ?Pseudosigma, 伪标准差% P0 K/ e0 c, s G
Purposive sampling, 有目的抽样' [ i* V1 m2 L; v$ ?
QR decomposition, QR分解& j- W l9 D% {& X3 ]8 w- v; H! F
Quadratic approximation, 二次近似- ]7 ]# i* p4 o: F% z7 E" T
Qualitative classification, 属性分类, W9 i* Q4 Y! Q! G( x7 U& X
Qualitative method, 定性方法& N0 e# B) b, u& e& L1 `
Quantile-quantile plot, 分位数-分位数图/Q-Q图# I- E0 Z$ Q K1 j8 F
Quantitative analysis, 定量分析( a5 M- X! L$ q* g6 |. N! Z
Quartile, 四分位数
% j+ M7 \$ i/ H1 f! g4 v5 WQuick Cluster, 快速聚类
- U e3 b4 p7 {& r6 URadix sort, 基数排序
) W4 g, Z7 b& ^* h0 URandom allocation, 随机化分组0 c r6 c. s* P- Z# ~% T; A" u
Random blocks design, 随机区组设计+ X; B l$ l* f
Random event, 随机事件
0 ]# z# n0 {" B: X4 h4 _3 ORandomization, 随机化
) P' p; k" t! R6 R. b9 MRange, 极差/全距
# e2 L- r+ j2 T8 {, }Rank correlation, 等级相关" g5 ~5 |: c. a1 v
Rank sum test, 秩和检验9 k8 c4 B v- S1 u
Rank test, 秩检验1 w! o9 j0 u* q( Z+ @
Ranked data, 等级资料- u& C* [ r% x- `" C
Rate, 比率' V0 \6 r" M& w* L
Ratio, 比例% A2 [/ t+ [9 c7 q8 W/ S+ m3 Y
Raw data, 原始资料% k1 i7 M& W7 {2 g
Raw residual, 原始残差+ ?# ]; y* t: Y O
Rayleigh's test, 雷氏检验- B( b$ V7 q( H# _7 }; {
Rayleigh's Z, 雷氏Z值 v0 x; x ~' S* { w* |: r+ a4 W
Reciprocal, 倒数* I# A* s" S& O$ {
Reciprocal transformation, 倒数变换* r+ s+ K. b" p* J6 I( e. b* U1 r. k
Recording, 记录
. U Z, A; N1 B/ T/ d D/ Z8 `Redescending estimators, 回降估计量
/ m. s' H8 M$ Q7 b3 G, H5 i5 K! ~) VReducing dimensions, 降维
& t* l8 O: o- |1 t2 Y+ j6 M" ~Re-expression, 重新表达
2 z3 A9 A6 I9 W* PReference set, 标准组
7 K; U+ B3 t3 PRegion of acceptance, 接受域
; {5 d6 d+ B) G0 h9 lRegression coefficient, 回归系数
) Q: D% Q/ f' H/ S% WRegression sum of square, 回归平方和2 L1 l& O2 h. [3 A% ~
Rejection point, 拒绝点8 Q0 J) u- g! T
Relative dispersion, 相对离散度/ g4 y4 {4 {) W1 ?+ @
Relative number, 相对数
7 t f" e. C% i7 L% ZReliability, 可靠性
- X- d9 H) P3 [0 _9 _4 I6 o( L6 \Reparametrization, 重新设置参数: j0 s! @( B# _1 N2 T7 {
Replication, 重复1 _0 e! O, E8 f V" y
Report Summaries, 报告摘要
# X2 r. A0 e7 k( C( gResidual sum of square, 剩余平方和
4 ]6 ~$ Q% n2 E& v5 e7 {& U1 ZResistance, 耐抗性 w" H, p5 V' y( l" U: ?6 x1 S9 ^
Resistant line, 耐抗线
/ i( f. l, b" ?: ~7 I1 rResistant technique, 耐抗技术
4 A; L* b0 a4 M2 i( n( DR-estimator of location, 位置R估计量5 O% Y3 T" F" H
R-estimator of scale, 尺度R估计量
3 e/ a3 K, v* _) w$ ^0 xRetrospective study, 回顾性调查* U Z$ {! J [7 p4 P* Q% I5 D
Ridge trace, 岭迹, Y! H: E5 U4 V0 t! f
Ridit analysis, Ridit分析8 H/ D& X* ?- ~' E6 ~: E
Rotation, 旋转
4 W; k+ R+ P5 z) t5 e8 aRounding, 舍入
1 x3 e0 ~( J. f6 ?7 g7 ]" w3 @Row, 行 L8 G8 m% {9 n" a! s; i) A# T
Row effects, 行效应
0 W+ U2 b6 C& C# `. c) BRow factor, 行因素
1 |4 {& Y, n4 J' r" x: F! \RXC table, RXC表
2 s( I6 a$ L$ X/ VSample, 样本
8 Z$ r8 V/ H0 kSample regression coefficient, 样本回归系数
1 u; a" c. N. w2 PSample size, 样本量; r1 C- s# V7 G" r8 Q/ a/ q, S
Sample standard deviation, 样本标准差
; H7 Y I( P# aSampling error, 抽样误差
! C: A7 f% W3 F) PSAS(Statistical analysis system ), SAS统计软件包
6 w/ |- |1 J3 R7 B s1 K5 n& ZScale, 尺度/量表0 `" }" f. q% v& {2 G$ @
Scatter diagram, 散点图
L x) o. M& [" e- tSchematic plot, 示意图/简图7 E7 l4 W0 V4 x; _- s F
Score test, 计分检验/ K- U5 Y/ L4 k( [
Screening, 筛检4 L+ G. W* z& N" A5 a+ H4 A/ a! Z
SEASON, 季节分析
& O2 G. I1 D. \( K+ s: Q8 h+ }Second derivative, 二阶导数
' y2 r! l3 `! k! LSecond principal component, 第二主成分
% q9 v& m5 H2 c' c+ v% gSEM (Structural equation modeling), 结构化方程模型
/ h8 I4 V$ ]. C$ I# ZSemi-logarithmic graph, 半对数图( u" _8 K6 @7 X5 Y; f7 P8 _
Semi-logarithmic paper, 半对数格纸) K' W( Y" D$ B. o* F
Sensitivity curve, 敏感度曲线
# d9 N2 U" N! D( [+ ~* sSequential analysis, 贯序分析
) f1 c& f, t- J) tSequential data set, 顺序数据集: F3 l6 L' I: p g: j6 O
Sequential design, 贯序设计. q8 g4 V$ P2 W, n
Sequential method, 贯序法
( m# w) E9 Z8 b1 kSequential test, 贯序检验法* }+ G! e. o8 } z
Serial tests, 系列试验" a }$ C' ]) Z7 {
Short-cut method, 简捷法 * e& A$ U5 l9 O$ U8 E
Sigmoid curve, S形曲线
; U! u8 u/ j( D2 @! Y* KSign function, 正负号函数2 @+ N( D- S) R- D
Sign test, 符号检验
* k( }, Y, x1 `/ T+ nSigned rank, 符号秩
/ F+ X, z' r4 a4 q* s; w5 GSignificance test, 显著性检验7 k" H4 [: i. x9 w1 \5 W. @
Significant figure, 有效数字3 d: L$ \2 |( F( A
Simple cluster sampling, 简单整群抽样
. M% U/ a0 v# f! s6 \0 o OSimple correlation, 简单相关
) J0 \& P. n2 KSimple random sampling, 简单随机抽样
/ t4 k: Y0 s# {5 R b4 T3 E7 NSimple regression, 简单回归/ z1 W9 Q; i2 S% b0 Y' y: h3 @
simple table, 简单表
3 b' P! G) L i1 vSine estimator, 正弦估计量8 D/ H0 |/ d4 W X
Single-valued estimate, 单值估计
9 @/ Z' c2 Q2 k4 HSingular matrix, 奇异矩阵
! |' `, [" a" ]( F) WSkewed distribution, 偏斜分布
/ W* o9 V" \3 o9 Y3 c0 K! OSkewness, 偏度
" X1 z; W5 X) Z7 W. z$ B5 MSlash distribution, 斜线分布# ~2 i+ [& ?/ [: H! {' r9 G4 D
Slope, 斜率. D* a, s2 a+ [, b. W+ {1 W& n! |
Smirnov test, 斯米尔诺夫检验8 A9 d- z$ K3 C9 H5 r* C
Source of variation, 变异来源
: E$ C2 h7 t H X; GSpearman rank correlation, 斯皮尔曼等级相关! L, g1 w( |4 D) J) Z3 ?
Specific factor, 特殊因子
6 j9 i+ J& ^ X( n& d# |, FSpecific factor variance, 特殊因子方差; T, i/ s/ A$ I- [$ E
Spectra , 频谱1 l( `9 |9 @! Q: y3 G5 g
Spherical distribution, 球型正态分布
# h+ c6 [* S' u) w5 o( K3 JSpread, 展布
/ [' q4 Y. V* A/ T9 u' q+ T; eSPSS(Statistical package for the social science), SPSS统计软件包
6 C9 j w1 h j, n6 YSpurious correlation, 假性相关$ U) p u. g/ ~; S( y
Square root transformation, 平方根变换
1 o1 y1 k4 i. p/ f/ j# Z3 I! |Stabilizing variance, 稳定方差1 H5 u+ ^( i/ I4 ]4 H
Standard deviation, 标准差5 L' r; f( M" Z1 z
Standard error, 标准误0 {% ]% ^8 q6 C& w) {" Z7 ]7 b
Standard error of difference, 差别的标准误
1 N# [# ?2 [1 bStandard error of estimate, 标准估计误差
5 E0 S P1 Z+ h9 o0 b" }Standard error of rate, 率的标准误4 t Z0 B, w6 O& {
Standard normal distribution, 标准正态分布3 Z# G6 |, M& k
Standardization, 标准化. l J3 \' M" X) z! b
Starting value, 起始值
5 ]2 e6 _; U* P( N0 j. aStatistic, 统计量
& @$ l7 h( V" h, A, `Statistical control, 统计控制
* \) B ]' |7 x( V0 m7 iStatistical graph, 统计图
) T* O9 `% P$ UStatistical inference, 统计推断& H& ^6 V% \# p I1 t9 f
Statistical table, 统计表0 b# @0 Y& r T5 U( S# ~
Steepest descent, 最速下降法
% t0 v, `8 H; T" h LStem and leaf display, 茎叶图0 Y2 y9 ]3 s" o) v. i- }
Step factor, 步长因子8 A( a: p& n# `' C& d& v
Stepwise regression, 逐步回归2 t q5 {# F+ R! w
Storage, 存6 x" v6 o1 e1 U
Strata, 层(复数), j& l5 W% _. K1 R
Stratified sampling, 分层抽样3 z, l* c5 A) x
Stratified sampling, 分层抽样
' w6 f" |/ [8 _Strength, 强度
# j5 j Z( j; M5 IStringency, 严密性' X+ A' {' z2 P3 u
Structural relationship, 结构关系
" O, e3 ~: n' t) ]Studentized residual, 学生化残差/t化残差
0 r6 S; A6 u. |3 e. i5 GSub-class numbers, 次级组含量
) O4 O. ~' F+ M% |7 N4 ^: tSubdividing, 分割
1 c& w/ A6 P$ J7 J$ d0 FSufficient statistic, 充分统计量! |! v4 S. h, {" W4 [
Sum of products, 积和! s' e! b- x0 r- K0 H1 x
Sum of squares, 离差平方和
, ^- ~6 v0 x/ o+ ?) uSum of squares about regression, 回归平方和' N \/ {) C6 W) x6 c
Sum of squares between groups, 组间平方和
$ { V) d8 T) E9 U2 P1 `Sum of squares of partial regression, 偏回归平方和
; N1 U w3 p9 h* v$ X. XSure event, 必然事件
+ s7 `$ I6 f: n" F2 cSurvey, 调查; Q0 d1 M* w' v7 Z
Survival, 生存分析
. z4 p- E! T) U3 kSurvival rate, 生存率
8 |& x4 i& r- L6 y$ fSuspended root gram, 悬吊根图
" Y* c% |7 X$ J0 s( SSymmetry, 对称
5 \* s9 S' e _8 e1 nSystematic error, 系统误差, ^( ]: {, ~5 A; t- d- o* R# a
Systematic sampling, 系统抽样
: F0 B2 G9 f) M, C3 Z1 V9 b0 f9 sTags, 标签! E. W/ k! F( G y! r
Tail area, 尾部面积
/ h& Q' D+ g+ M/ M8 STail length, 尾长: Z4 {* F! b( s, [2 D
Tail weight, 尾重
7 i, H) z7 j( G2 {2 q( W4 U4 zTangent line, 切线
+ s! P7 ~8 |/ L% qTarget distribution, 目标分布# R# v+ L5 ?: K( j& z! ` F# l
Taylor series, 泰勒级数3 L u8 s: T4 ] f. x! m( ]# Q i
Tendency of dispersion, 离散趋势; g* r8 O8 B' s" j2 g% I: p
Testing of hypotheses, 假设检验3 {5 y' [# E3 q4 k; a0 L
Theoretical frequency, 理论频数
! d# v% _! N& h6 G" \Time series, 时间序列
% x; i! }- F) H' m9 |0 m5 ~Tolerance interval, 容忍区间- l4 a/ h/ [# l6 X# N8 v
Tolerance lower limit, 容忍下限
1 x6 i: O; J1 D8 N$ A$ gTolerance upper limit, 容忍上限+ Q, @# _- ~3 V3 L/ W; A
Torsion, 扰率
5 B6 {; _! Y8 r4 x7 R5 Q; eTotal sum of square, 总平方和
+ K9 Y5 P% W, R8 T+ dTotal variation, 总变异
( G3 g y( i) A- P# W. ` G" q1 DTransformation, 转换
* c+ I6 \& p1 N7 S$ XTreatment, 处理& U: `* O% A# u2 p+ ^1 k
Trend, 趋势
6 {1 e, s$ {" c7 I3 p. UTrend of percentage, 百分比趋势) I7 {( g" B8 d/ G( ]! X" ?
Trial, 试验
6 K/ x4 v& c- FTrial and error method, 试错法
! }3 d) V9 p2 A, |7 L) h# Z' M8 {Tuning constant, 细调常数3 ]4 w4 y4 g0 l& d. q- K7 J5 R
Two sided test, 双向检验
9 x6 R4 I k4 L, u$ s( QTwo-stage least squares, 二阶最小平方
. t/ @7 G( G4 P) o+ q3 N! jTwo-stage sampling, 二阶段抽样
/ j) j, o! h6 G) M+ eTwo-tailed test, 双侧检验! }8 S+ _6 A. G
Two-way analysis of variance, 双因素方差分析
3 y+ @. k0 r. {0 |0 h$ LTwo-way table, 双向表' a; L6 \" q/ [8 ?) }
Type I error, 一类错误/α错误9 C3 l# o4 ^/ q- w" G8 d
Type II error, 二类错误/β错误0 T, ]2 E2 d* k
UMVU, 方差一致最小无偏估计简称6 ^* @( f c$ q8 Z/ x! b# W2 C
Unbiased estimate, 无偏估计+ Q' i1 P' F' W; \& ?8 l
Unconstrained nonlinear regression , 无约束非线性回归
2 l+ T! }/ @% j! m; CUnequal subclass number, 不等次级组含量: ?5 y: m) Y% }6 ?& @. E- A6 F
Ungrouped data, 不分组资料
* J5 F) V- D2 bUniform coordinate, 均匀坐标/ z; a& W( w% M* k" d
Uniform distribution, 均匀分布2 V; y( F; z T- `. h/ a. t
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计7 _4 D& ]$ |1 p m+ c8 l% b
Unit, 单元6 m+ G8 z4 A& s" v: @& A
Unordered categories, 无序分类
2 N" P4 B1 }( l2 u+ b9 vUpper limit, 上限1 {$ n D' [3 Y4 T5 _9 e
Upward rank, 升秩1 w9 d) U+ e j
Vague concept, 模糊概念* z8 K( d% R! s( u0 a2 B
Validity, 有效性" I3 m: ?7 o' s7 x3 V3 G' v! \2 v1 u
VARCOMP (Variance component estimation), 方差元素估计
8 T4 O1 h/ A+ Y2 _Variability, 变异性
# t2 W* U5 I" x9 wVariable, 变量! p) B3 O/ {% f
Variance, 方差
" \. J/ k% f: q' OVariation, 变异. l; L' e) j: e* C: C! G* _+ m
Varimax orthogonal rotation, 方差最大正交旋转6 G: k/ s6 I( d l; N
Volume of distribution, 容积) r$ o2 b* o" a' N
W test, W检验
1 E9 _7 T% F+ Y- ~Weibull distribution, 威布尔分布
, m) ^8 ^0 s W. W; bWeight, 权数
/ N* i6 e/ ^) y, \6 oWeighted Chi-square test, 加权卡方检验/Cochran检验
# G3 r: }2 C- J& O4 k' x. ~Weighted linear regression method, 加权直线回归- L3 E" I$ B8 w# _
Weighted mean, 加权平均数
; |& v6 Q$ X' M6 U* A5 ~% wWeighted mean square, 加权平均方差
) ]& K; v5 r0 c- s; |3 _Weighted sum of square, 加权平方和
J* x+ Z: m/ o oWeighting coefficient, 权重系数3 V5 J' L& ~1 W9 I. W. x% w7 v
Weighting method, 加权法
- I# c4 R: t; y. r$ P# cW-estimation, W估计量
/ o+ X9 a5 G! ^- wW-estimation of location, 位置W估计量 O' l8 ?& h2 v/ c; K) m7 n
Width, 宽度1 u% z7 a" ~% Q. q. ~) n
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验# ~9 D% _3 J( I% \$ g7 S6 c
Wild point, 野点/狂点
: p" ?0 I, Y3 `! A4 z2 uWild value, 野值/狂值
" R3 B) [0 y" O+ f NWinsorized mean, 缩尾均值
8 U% _4 G4 U' e' W, LWithdraw, 失访
5 A2 w0 E( O) ?' G3 W; P. ^9 wYouden's index, 尤登指数( t9 u# z0 ?! R& o+ N, v& w$ o' S
Z test, Z检验
/ K `1 I- C, j. d6 WZero correlation, 零相关% Z& M% I% k2 }0 ^8 ?- F, O2 ^! l( v
Z-transformation, Z变换 |
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