|
|
Absolute deviation, 绝对离差4 b# g6 p. _/ Z( b' _8 y, F
Absolute number, 绝对数% V7 x# R& `' X9 t: o
Absolute residuals, 绝对残差" y P! V+ K. | `& S( X
Acceleration array, 加速度立体阵
, |+ v* e" P% Z6 o; rAcceleration in an arbitrary direction, 任意方向上的加速度% E6 q; U4 N; P: ~/ [: L
Acceleration normal, 法向加速度
3 ]7 s) D+ [$ Y7 ]; [% g# lAcceleration space dimension, 加速度空间的维数5 w& O6 i8 D) |5 I
Acceleration tangential, 切向加速度/ V. B0 F4 m6 n+ e$ J
Acceleration vector, 加速度向量
$ ^6 @' H% L( G0 M$ Z) HAcceptable hypothesis, 可接受假设
& ~! C4 B( j* \/ {Accumulation, 累积" W7 J' ~7 f6 @* H4 O1 N
Accuracy, 准确度
% w6 [4 S0 O) |* h( ` c. f& o+ h' WActual frequency, 实际频数
# D& l6 |7 d/ N0 i" |Adaptive estimator, 自适应估计量
" E! u4 E0 h2 J5 ]/ n4 Q0 cAddition, 相加
3 }- S7 E1 j8 rAddition theorem, 加法定理5 m9 ]- R+ D6 T, C4 f
Additivity, 可加性" q7 t$ c, i1 a8 d; \
Adjusted rate, 调整率9 _8 y7 u% u, z& d. d. K3 ~$ P
Adjusted value, 校正值6 c6 l( x2 [: F* M8 M
Admissible error, 容许误差
% I8 J. L7 o# W: RAggregation, 聚集性
4 V D/ l' e4 wAlternative hypothesis, 备择假设) E2 n; V, r# e% a, |/ N: P: J6 d
Among groups, 组间
: d% Q3 \/ Z* x0 E6 vAmounts, 总量
1 k @) n- V1 m6 o YAnalysis of correlation, 相关分析3 l6 {) [) |: f$ ]4 q
Analysis of covariance, 协方差分析
, e9 H! e8 I [Analysis of regression, 回归分析
1 q6 O! p8 T! A0 K; K% Y4 [Analysis of time series, 时间序列分析9 W$ L2 x# h- d' b5 r- g8 d
Analysis of variance, 方差分析. t' a( v; @& u
Angular transformation, 角转换
) [4 x1 }" V1 |# U }* NANOVA (analysis of variance), 方差分析
6 W. _/ [/ @" `0 d' ^ANOVA Models, 方差分析模型
7 z$ u- ?% F) d# i% mArcing, 弧/弧旋
: |8 V" P- X) r; S8 \% YArcsine transformation, 反正弦变换
4 ~, z' E$ w7 E: y& n# s' `Area under the curve, 曲线面积9 N: \5 S) m8 y. v) |
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
1 t# o6 K+ i& P* j9 {ARIMA, 季节和非季节性单变量模型的极大似然估计 / U% o4 g& m7 \ A
Arithmetic grid paper, 算术格纸/ Z$ l. O6 N$ q
Arithmetic mean, 算术平均数
: o h7 u! @/ ~0 i3 W5 rArrhenius relation, 艾恩尼斯关系7 g% l' f, n( @- A# E5 c/ E4 J
Assessing fit, 拟合的评估
0 Z [% {2 Y+ RAssociative laws, 结合律, J& A$ b! |1 P9 [+ Z; g
Asymmetric distribution, 非对称分布
2 y, U9 `- t# P& i9 l" g3 _Asymptotic bias, 渐近偏倚% w2 i% ] X$ z2 V+ p) u& E
Asymptotic efficiency, 渐近效率% h: P; ^7 J( g* d+ V& o
Asymptotic variance, 渐近方差* o" C0 j1 B1 w( J9 d
Attributable risk, 归因危险度
# l. ~" U V4 \) [, ?# |1 GAttribute data, 属性资料6 w( Q a- I' m" V+ \
Attribution, 属性
- i% c/ s9 {7 i. U7 tAutocorrelation, 自相关
" @3 ~6 @" d) ]( iAutocorrelation of residuals, 残差的自相关
& d0 m: m @' ]& w4 ]* W' ~5 kAverage, 平均数/ w/ j2 R2 k ]$ L k1 Z
Average confidence interval length, 平均置信区间长度% E3 D9 ]/ a: u. Q
Average growth rate, 平均增长率
: k4 g% |0 S+ H. Y4 w- [3 J* n5 K& ?Bar chart, 条形图! E; e1 [: U9 ]" o9 q! i9 e, r
Bar graph, 条形图
9 M4 M3 q4 T+ a) H- v5 BBase period, 基期8 b: K# }* v, [, | J2 x
Bayes' theorem , Bayes定理- L* [) a; U/ O. K2 Q" L
Bell-shaped curve, 钟形曲线! ]2 ~: G! L( z. b7 `) o- Z, b0 D
Bernoulli distribution, 伯努力分布/ ^* @. z' |' b8 G( I
Best-trim estimator, 最好切尾估计量* y$ L; o+ E) V- n; C2 f/ f( W! x
Bias, 偏性
, M, A. l" B! F) c; }* v7 z) _Binary logistic regression, 二元逻辑斯蒂回归" E& v- \" f j7 Y
Binomial distribution, 二项分布
/ Q5 H/ P) Y$ J% s T, g: n4 VBisquare, 双平方 `9 _9 ^4 }, y
Bivariate Correlate, 二变量相关
: c$ a' K3 S/ K5 Z/ hBivariate normal distribution, 双变量正态分布) e$ N: n% c' `# T/ h1 h3 i. W; J
Bivariate normal population, 双变量正态总体
; M9 J5 ^( M4 Z- e# m2 l! LBiweight interval, 双权区间 x( u/ I8 i @! Y6 f# e* \0 T) M
Biweight M-estimator, 双权M估计量( q5 |4 J% m& K- w+ c5 ]2 J
Block, 区组/配伍组% H7 a6 |* A0 |; R3 O' D- k
BMDP(Biomedical computer programs), BMDP统计软件包& z+ y, I# c5 B- C
Boxplots, 箱线图/箱尾图: A# W5 y- o3 G
Breakdown bound, 崩溃界/崩溃点
7 p$ m% X( p7 D, K9 vCanonical correlation, 典型相关
# f% \: v3 T( i$ s- E. X, h, @Caption, 纵标目
7 g" G( W4 A2 tCase-control study, 病例对照研究9 b$ ?3 X/ Q$ M8 O" @% P
Categorical variable, 分类变量$ \7 o& I9 ^) r9 z5 H0 K% I3 D
Catenary, 悬链线" k9 {% ]# u' v# Y6 ~
Cauchy distribution, 柯西分布: o8 w3 M7 K- N5 ^2 r1 [
Cause-and-effect relationship, 因果关系4 i; C% @$ B, A
Cell, 单元2 H, K4 ]: [- R$ P* G# Q5 @
Censoring, 终检8 R1 V- F/ ~& W: F3 \* D$ s N
Center of symmetry, 对称中心
2 R9 b+ Z @2 L9 o- UCentering and scaling, 中心化和定标0 c$ E6 k, y- S8 V/ [
Central tendency, 集中趋势% ^7 Z" d& Q1 E4 K/ P8 W
Central value, 中心值
0 s1 K( [" Z- x" d, i( ?* aCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测3 {( A# D: ?* E, r& K" r
Chance, 机遇9 Y: ~* D/ X. E, V2 T3 K$ f4 Y
Chance error, 随机误差
* Z! ^8 J# [' J7 c) CChance variable, 随机变量
+ [; a! l9 `+ ?9 ` h$ CCharacteristic equation, 特征方程
. W7 D5 h" R9 l4 zCharacteristic root, 特征根2 V: p) d; X1 W/ C2 S* d1 e- h
Characteristic vector, 特征向量
5 Y3 j: ?2 O2 A1 dChebshev criterion of fit, 拟合的切比雪夫准则
+ d# E$ p" e! T* j, j) ?Chernoff faces, 切尔诺夫脸谱图
# z* K6 I4 \9 v0 r( i7 wChi-square test, 卡方检验/χ2检验
0 N) ]' y' s2 mCholeskey decomposition, 乔洛斯基分解( Y+ {. o5 o' C" z% v8 N1 {( _, F! W
Circle chart, 圆图
5 S0 s8 t6 p+ u2 n0 ~3 YClass interval, 组距
4 T! u4 j0 M. b/ {1 n9 qClass mid-value, 组中值( l+ j' x/ `8 I- W7 j/ f/ [
Class upper limit, 组上限
V8 E& h6 j3 K5 o0 m6 Y8 w: n( oClassified variable, 分类变量7 P3 [) F$ S, m7 N$ T- X9 X
Cluster analysis, 聚类分析
* m' I6 G4 I% k. G) X v) [6 E$ {Cluster sampling, 整群抽样9 J' Y& Q1 Q. x
Code, 代码
3 l5 j2 }( H7 ^* qCoded data, 编码数据5 B1 K' F! X6 H8 W8 m, g/ m+ J
Coding, 编码
# f; P: B% M: p1 h0 f# WCoefficient of contingency, 列联系数
/ c/ M* w2 w/ Y# I. wCoefficient of determination, 决定系数
4 v+ t% }6 T9 Z" |. R. wCoefficient of multiple correlation, 多重相关系数! l q5 ^% b \4 x( c/ ?& H
Coefficient of partial correlation, 偏相关系数
8 D0 p; x% l8 E% g0 j/ w. p5 {* ^Coefficient of production-moment correlation, 积差相关系数) H9 P+ K. K, [4 L4 v( ^$ k
Coefficient of rank correlation, 等级相关系数" M+ q8 M3 I% C, i4 ]( b
Coefficient of regression, 回归系数
" O' A) J1 k8 }; N% T. P+ KCoefficient of skewness, 偏度系数. \- R0 H, E2 x) Z* } B
Coefficient of variation, 变异系数
1 @4 d7 D- r3 m5 s/ h- Q; [Cohort study, 队列研究) }: |4 j5 E8 ?
Column, 列8 C& \/ M; D7 n
Column effect, 列效应
1 e5 {5 R0 @% ^+ X2 ?Column factor, 列因素
6 P6 b$ O! N$ x. q/ cCombination pool, 合并
: H7 Q( @. k8 gCombinative table, 组合表
1 h/ r$ ?# z2 q7 F- j0 L( [. HCommon factor, 共性因子
# C( E. d, E3 ~! d q5 g% m! TCommon regression coefficient, 公共回归系数
8 k& m3 w, s+ iCommon value, 共同值7 z+ K& e6 c6 ^) x0 [3 l' h6 I% T, i
Common variance, 公共方差2 y8 g' V6 ?8 `' G' I5 A& Z+ c
Common variation, 公共变异
" w5 Y3 a7 }' OCommunality variance, 共性方差
0 I5 ]3 H; S3 F& {0 j$ e d! sComparability, 可比性7 o/ A N( r G* I; k7 a- J
Comparison of bathes, 批比较2 j; H" d/ k' U( n( N1 B9 ~3 v: z% {6 |
Comparison value, 比较值
& G8 A) x% l/ ?Compartment model, 分部模型
! ?' v# x. p8 K+ W8 WCompassion, 伸缩
$ n# I7 {- |5 X# UComplement of an event, 补事件
0 d' b* c5 r2 R; ? z. uComplete association, 完全正相关
" I+ `) b. Y/ |8 s4 fComplete dissociation, 完全不相关. l* V9 b& s8 P$ ]# s
Complete statistics, 完备统计量
M- x" Y2 n p$ NCompletely randomized design, 完全随机化设计
) c7 r4 T4 {% ~0 h) @9 OComposite event, 联合事件' j7 E- H# ?7 @
Composite events, 复合事件
- s/ g k: h0 `+ UConcavity, 凹性) |( D0 n5 @7 U
Conditional expectation, 条件期望+ I7 x# d5 k' k3 o
Conditional likelihood, 条件似然
. o! c% C C7 n# W: ]/ i9 yConditional probability, 条件概率3 {) U1 s8 n; X) u {" c W& F( J! G2 |
Conditionally linear, 依条件线性
& c. _4 i4 d. Y b! d9 H$ hConfidence interval, 置信区间
! W" u9 J/ h" o7 q$ L( |Confidence limit, 置信限
, s" n+ J! M4 m2 T7 H; K3 sConfidence lower limit, 置信下限1 J8 R7 P+ r3 x. x$ y0 G" f9 o
Confidence upper limit, 置信上限
, Q$ M R& m% p( w. f/ KConfirmatory Factor Analysis , 验证性因子分析0 f& Z4 P6 J8 b- X' o5 j9 o) e7 [
Confirmatory research, 证实性实验研究
, E3 S! H# E! P7 Q/ q6 aConfounding factor, 混杂因素
0 Z% P4 x, Y: V2 ] h; _Conjoint, 联合分析 r8 r: n& n" @3 P$ h/ n
Consistency, 相合性; n0 g! f5 ?: ?- r5 d3 T8 |
Consistency check, 一致性检验) H; x' @- l/ C& E
Consistent asymptotically normal estimate, 相合渐近正态估计
+ B" f$ W! z6 Q; RConsistent estimate, 相合估计
# m6 D% ]/ g& z5 n% VConstrained nonlinear regression, 受约束非线性回归 S4 M: L5 N' A* U- y% B8 U
Constraint, 约束
; b9 g* m" n. c- [, e6 O- b5 RContaminated distribution, 污染分布
1 r) q( a5 ] I# C3 ~, u4 hContaminated Gausssian, 污染高斯分布
0 j8 D; N! v0 v8 h% W- m5 \* F4 I& bContaminated normal distribution, 污染正态分布
3 d# s, t) f8 yContamination, 污染7 y2 K9 O6 q; s6 M# u
Contamination model, 污染模型6 o, U6 `8 J- u" g) a
Contingency table, 列联表 x, ^$ k) n" J- x0 i t( Q2 `
Contour, 边界线
8 H7 m: `4 Q7 k5 m! \Contribution rate, 贡献率
0 |, R4 E H* Z* `1 [Control, 对照
' N6 ^' \, B# n2 ^: \6 q8 D4 l9 f8 qControlled experiments, 对照实验
+ K# \- e3 ?1 ]. j W! ^% YConventional depth, 常规深度
7 o9 s& m; Z& c {+ U9 U3 x+ Y# nConvolution, 卷积- J0 S" O1 H! g* E/ D0 y
Corrected factor, 校正因子" B& m. W. g, B z* ]7 R4 z+ |
Corrected mean, 校正均值8 h, ]/ `. S# C. s$ G. v7 U+ P0 _
Correction coefficient, 校正系数
0 c/ Z; R+ h$ R6 ^3 yCorrectness, 正确性
* d0 K+ B- Y; I- ]5 hCorrelation coefficient, 相关系数2 |5 d( ~ n! C* T
Correlation index, 相关指数
5 J* g% ?3 Q9 E( r( OCorrespondence, 对应
) e' x/ j# R6 `' d: A1 cCounting, 计数
8 `5 Q3 Q+ c! N/ KCounts, 计数/频数
5 H" J6 c' j, f6 ]* k1 Q2 YCovariance, 协方差6 d0 w( R2 {5 h U
Covariant, 共变 4 |; i4 @/ D7 I/ i; o- Q/ v
Cox Regression, Cox回归
2 w0 o# I4 p3 w: X7 x j& ECriteria for fitting, 拟合准则" }" I3 N! i. s2 ^6 }" e4 U: m6 A m
Criteria of least squares, 最小二乘准则- p; p! f" N- _: T
Critical ratio, 临界比; R% d, c9 @* ?0 x) L. K; ^
Critical region, 拒绝域! |; T5 t5 R' q% }5 [
Critical value, 临界值
- c1 z3 p0 t. Z9 XCross-over design, 交叉设计 w& D" X5 |/ ?7 e9 B& i [
Cross-section analysis, 横断面分析
% ^) n$ u0 O% PCross-section survey, 横断面调查2 Q q; {& T @% N' e- ~
Crosstabs , 交叉表
" u. {8 Z9 ^7 p1 }% M) Q# ?6 bCross-tabulation table, 复合表) y. T- a8 s) V# g% p
Cube root, 立方根
" F/ {" o, ]# V+ h! I l& \, JCumulative distribution function, 分布函数+ X+ D) M9 W5 ]9 M8 J
Cumulative probability, 累计概率
' O; V8 z: d& K, w% M; J7 c& q9 ECurvature, 曲率/弯曲
. M2 V- v, w) W, Z& dCurvature, 曲率
9 l( [& a" \+ fCurve fit , 曲线拟和 * I9 u+ V/ O) S$ y7 I
Curve fitting, 曲线拟合. ^$ e$ z( Z- Z/ _4 ]- J
Curvilinear regression, 曲线回归
# x7 Q( p7 h' _6 u4 e: r' f2 DCurvilinear relation, 曲线关系
$ o( L6 k4 ]% V; DCut-and-try method, 尝试法: S/ L' {2 F8 S7 S+ z, t
Cycle, 周期
, X+ S0 y4 ~. \; j3 H& ECyclist, 周期性
& N" o7 j8 {# F3 C4 q4 SD test, D检验3 A- S) q5 T5 l3 m0 p+ E
Data acquisition, 资料收集
3 l: V8 c& e( wData bank, 数据库 g* t9 Z3 @$ D2 I* X
Data capacity, 数据容量) M: d$ Y( z0 j0 V; K% f
Data deficiencies, 数据缺乏
+ i! g8 J4 n) I$ ?Data handling, 数据处理
+ v B0 Q+ v' q* }# m; cData manipulation, 数据处理; m0 Q& I5 T* E8 c2 l) \& G' b
Data processing, 数据处理
7 d, o& p+ \2 EData reduction, 数据缩减
) O, w& o# Y" j4 JData set, 数据集
% y8 d' c6 b, ^7 L' RData sources, 数据来源1 U+ o4 H1 t: v# w4 J. @/ b
Data transformation, 数据变换1 S6 {/ `, C: h7 T
Data validity, 数据有效性; m9 w9 \) V( b2 b; i
Data-in, 数据输入
0 o+ _2 D+ C, }7 }$ uData-out, 数据输出
; \4 l( @9 R5 d0 A4 ]Dead time, 停滞期0 I' o5 y @6 z6 G
Degree of freedom, 自由度
3 j" o9 M1 S9 L" \2 x6 ^3 wDegree of precision, 精密度
2 N- [- A4 J- Q5 L. {1 r, x" S+ gDegree of reliability, 可靠性程度
a# y' f/ w1 B' u5 T4 tDegression, 递减; J' s/ o8 M# b6 j, Q* t
Density function, 密度函数
2 T; l4 m& r7 T6 dDensity of data points, 数据点的密度. }1 y$ O- d+ Z. H* W2 P4 Y. ^5 n9 p
Dependent variable, 应变量/依变量/因变量
4 m8 }7 r" Z& N% a6 nDependent variable, 因变量" f" m7 e$ {0 A+ J" M% D
Depth, 深度
+ ]3 w9 g) ~5 ?8 p* mDerivative matrix, 导数矩阵
5 o3 X* ]2 ^ pDerivative-free methods, 无导数方法7 O9 o, m6 b! k3 c
Design, 设计
8 j# U6 L- A; l. W! F" WDeterminacy, 确定性
) X# O) b# v) ?4 ^% U9 H4 D; G q% XDeterminant, 行列式
# j3 Z! u1 o- [Determinant, 决定因素
9 T# l' Y. ~# u* l8 u$ V, ZDeviation, 离差
, B7 y1 X4 R) W1 e' `3 KDeviation from average, 离均差6 a0 _+ l. ~: k# s
Diagnostic plot, 诊断图
* {- s% o* a/ @1 p0 g" FDichotomous variable, 二分变量
B$ }/ X: G/ @1 |* g" FDifferential equation, 微分方程
( D$ N, `( u. MDirect standardization, 直接标准化法( D% D2 L; z/ M7 m1 Q& D
Discrete variable, 离散型变量6 Y6 ^, A4 s+ b- A
DISCRIMINANT, 判断 ' c2 S7 F$ d2 \
Discriminant analysis, 判别分析! {7 ^" H# t5 Z" \" p( w# W' `; d' X
Discriminant coefficient, 判别系数1 g$ X/ ]3 p/ C2 _, a" L6 H
Discriminant function, 判别值
$ D* `& F- f# J# w, B3 vDispersion, 散布/分散度% f1 I0 X, {: \* ]# y0 n
Disproportional, 不成比例的
$ W6 e& U/ n9 u* UDisproportionate sub-class numbers, 不成比例次级组含量
' V3 H& a+ _+ u U* m7 n/ l5 XDistribution free, 分布无关性/免分布
d3 J3 T s, i0 e6 `: ]) l$ GDistribution shape, 分布形状# v% X' Y$ [8 m4 w+ m7 }
Distribution-free method, 任意分布法) f7 ]+ S9 C8 a) J6 I
Distributive laws, 分配律2 H0 b0 ]3 o# x
Disturbance, 随机扰动项; a: g3 N) Q( c- g! T: h4 g8 `! m' |
Dose response curve, 剂量反应曲线" L& |; i: Q% \# e, ?. O
Double blind method, 双盲法7 ^" Y$ G9 w& ~1 J
Double blind trial, 双盲试验
. Z- E$ }+ p9 y9 t& \0 TDouble exponential distribution, 双指数分布
2 b; z8 _7 j! J& B/ b& ~# LDouble logarithmic, 双对数
, w; h4 |8 y& g$ R( D1 P1 b/ HDownward rank, 降秩
# A1 e6 g4 h# z5 oDual-space plot, 对偶空间图
$ q D. k% j3 |% y7 N2 a) ^DUD, 无导数方法0 x G4 Q$ c. `# _: S& J" ~
Duncan's new multiple range method, 新复极差法/Duncan新法
1 r+ `! e7 }$ DEffect, 实验效应
( A9 u' @! u! C% I/ b: _Eigenvalue, 特征值
# S7 _* k& B) J# {4 r5 _Eigenvector, 特征向量5 c3 D" `( A+ j4 J/ P$ d Y
Ellipse, 椭圆
7 n: I5 v& t, z4 \, j3 ~. sEmpirical distribution, 经验分布0 K0 Q8 ] g0 i% _, E3 f" D
Empirical probability, 经验概率单位
5 I$ n( ?: O" j4 S& g& IEnumeration data, 计数资料
6 ?% u9 h! C& j$ T) }Equal sun-class number, 相等次级组含量" w8 R! U K& u; i( G4 v
Equally likely, 等可能1 n5 d1 L4 y1 T. g4 [
Equivariance, 同变性
: u9 J7 K2 H* X& h, ~Error, 误差/错误
0 L0 E. L+ i, _1 |& b# K$ xError of estimate, 估计误差0 y! T& ~( ^; W: P0 b
Error type I, 第一类错误
% R+ R/ D# N# U# mError type II, 第二类错误3 w' h! V6 x# {
Estimand, 被估量' G/ {- R e& m8 P+ A- C, k( o! `" z
Estimated error mean squares, 估计误差均方7 Y) U- i4 V9 u/ P5 X$ P' c4 m
Estimated error sum of squares, 估计误差平方和
+ F& C' x/ i3 o# AEuclidean distance, 欧式距离
8 L4 \5 k) y0 i7 k$ sEvent, 事件' S' p. D/ }1 w; X t8 s
Event, 事件: B% ^- m @ z/ z
Exceptional data point, 异常数据点8 n% }, W$ @) A% X
Expectation plane, 期望平面
% v0 V% L7 N2 X+ gExpectation surface, 期望曲面7 B0 j' k( H# {+ V, G
Expected values, 期望值3 t; T2 F! w; F/ D3 v+ U
Experiment, 实验) L3 G# Z: D B9 p' P
Experimental sampling, 试验抽样
/ A8 g8 _, k7 Q5 q6 u. V7 RExperimental unit, 试验单位
1 y1 N- b" o/ }5 \' |% R6 s4 d6 {! r/ SExplanatory variable, 说明变量' R" }) A# B: Q9 y d% i
Exploratory data analysis, 探索性数据分析
/ D, v1 k8 B4 B- SExplore Summarize, 探索-摘要- N7 [/ w9 D4 N0 G& F; i
Exponential curve, 指数曲线- n' o$ \8 ~% n( m. x2 o
Exponential growth, 指数式增长* m( g" u& M# h$ i! d5 M& F
EXSMOOTH, 指数平滑方法 + g n2 P6 i m; @
Extended fit, 扩充拟合0 z D8 v* |( u, O7 ]6 U* I( n
Extra parameter, 附加参数; ~5 w% X4 z$ R5 g- f
Extrapolation, 外推法
" V: F* @/ X4 H, I9 R# LExtreme observation, 末端观测值
7 S( h& h0 D8 K. V4 Y- bExtremes, 极端值/极值
+ m6 o- r5 G2 o2 P0 a( n5 s# TF distribution, F分布
$ D% S5 [4 q: P0 Y) J YF test, F检验8 m& ?& ~( ~6 L! C: e; s! B. q" f
Factor, 因素/因子
8 k- V; [# C+ A5 O6 N! f7 }+ MFactor analysis, 因子分析
4 ?% q/ y) @5 v2 ~) X8 }4 Y. rFactor Analysis, 因子分析* O' S& ?$ }# h, c/ X
Factor score, 因子得分
/ L$ e& D9 s( v% G& `2 a1 aFactorial, 阶乘+ h" c* e: Y6 M/ K' [
Factorial design, 析因试验设计# g2 X! p4 l9 E/ P: _: y
False negative, 假阴性
% S* ^4 X. Z3 r, C( |" a5 zFalse negative error, 假阴性错误
5 C1 ?& ^# x! K) x* bFamily of distributions, 分布族
$ N6 v6 B' O4 d7 yFamily of estimators, 估计量族+ r! ~: f" y# Z, y
Fanning, 扇面
1 a3 S8 l( P# u& L/ h/ e, ^8 ]' n6 qFatality rate, 病死率
$ f+ Q' }2 N' IField investigation, 现场调查4 Q9 c( A5 b3 ?1 w# Z; W" c
Field survey, 现场调查: ^5 \/ @' o J D
Finite population, 有限总体* i2 C" l8 Y$ Z
Finite-sample, 有限样本9 s% e/ t4 R: V- s5 W" v2 S
First derivative, 一阶导数+ X* b( E! e9 t! M* C) d& d. o4 y
First principal component, 第一主成分$ o+ X% r' S$ n) ^) N1 T
First quartile, 第一四分位数
4 z7 T) R4 w5 J3 m. G( NFisher information, 费雪信息量- d0 f: [+ d7 q; M B6 i9 e
Fitted value, 拟合值. J _3 }/ F8 W. E0 \+ v( q1 i+ f4 e
Fitting a curve, 曲线拟合7 ]: H8 X3 y/ k7 a% u
Fixed base, 定基
) ^* y9 o" B; x: r4 ]) Z# j! ?9 gFluctuation, 随机起伏
# b; b" L8 o1 T: wForecast, 预测9 S0 u* b" k. c4 B* G( R
Four fold table, 四格表4 O* {& y4 I2 F1 v7 A
Fourth, 四分点5 J2 L( ]" Y/ H* |
Fraction blow, 左侧比率) `* O% Y# s3 o" c% ]) B
Fractional error, 相对误差/ ^( {9 T' Y* k" U
Frequency, 频率( L# S& a3 y" v
Frequency polygon, 频数多边图8 B& X& c b2 b
Frontier point, 界限点
: | d# Y7 j( F, {% O* y6 X' cFunction relationship, 泛函关系% Q! i4 o; h) X7 c5 H" M1 x% {
Gamma distribution, 伽玛分布6 \# i; a* _6 t# `% s
Gauss increment, 高斯增量
; i# b' D, R9 Y; }Gaussian distribution, 高斯分布/正态分布
* [; X5 Q: m+ Z2 ~Gauss-Newton increment, 高斯-牛顿增量+ s' M+ z; J `+ ]- Y) Z
General census, 全面普查
3 [; u5 E5 f9 e' o( O |GENLOG (Generalized liner models), 广义线性模型 ) W2 U. l9 y, _ ]9 ^1 v, A. o
Geometric mean, 几何平均数( Q1 M% y/ {* A
Gini's mean difference, 基尼均差" V( M/ c1 g1 Y* g& i3 A, J
GLM (General liner models), 一般线性模型
( x) E8 `7 l9 ?5 E6 O( f, R+ j' HGoodness of fit, 拟和优度/配合度
X9 w' J, V/ h- b* S; ^+ Q& T! EGradient of determinant, 行列式的梯度
$ v8 s7 i2 S7 m; c) |7 n; p5 W: NGraeco-Latin square, 希腊拉丁方
) U( S& B/ e6 Y0 E* q- F/ _& iGrand mean, 总均值
* j- g; x1 s- E1 c; f$ ^Gross errors, 重大错误% h) ~3 h4 j c" s: U8 r
Gross-error sensitivity, 大错敏感度- b8 ^" N k9 ]' h0 `
Group averages, 分组平均6 Y2 @2 h4 \4 p% x
Grouped data, 分组资料
+ U4 q g* h! j4 l. P( lGuessed mean, 假定平均数
# K9 c* |3 x3 Q& z1 FHalf-life, 半衰期2 }7 Z4 }' u% q
Hampel M-estimators, 汉佩尔M估计量
8 G! B4 l I+ V- x" rHappenstance, 偶然事件
1 ?0 y# L$ C0 j* E/ bHarmonic mean, 调和均数0 r n9 T% T: v# c5 _3 [. y- {# p
Hazard function, 风险均数
, c0 v: W: e9 n! B4 w1 eHazard rate, 风险率
, u0 V5 x& M5 v, W: k7 a" f4 FHeading, 标目
8 j( ]' }, H" G# O/ p* DHeavy-tailed distribution, 重尾分布; n4 j5 x1 b& r& g F! n
Hessian array, 海森立体阵
' j. B5 x" R# Z. i, SHeterogeneity, 不同质
+ m$ X3 e4 K9 Q2 wHeterogeneity of variance, 方差不齐
: q# g1 }9 G3 \9 E% H7 S9 R( fHierarchical classification, 组内分组
% E0 K3 Q/ m# jHierarchical clustering method, 系统聚类法* |1 f+ j: E9 \; B4 F5 ] U
High-leverage point, 高杠杆率点
3 G4 }8 x, \. y& h" E, g+ b- mHILOGLINEAR, 多维列联表的层次对数线性模型
4 V4 i I4 l4 _2 [) T2 Z" ^" m% OHinge, 折叶点$ T6 q0 w4 g, O6 i/ b4 S4 r1 D+ h
Histogram, 直方图
, Q/ e+ }' D1 a% }- LHistorical cohort study, 历史性队列研究 * I% Z* d7 N5 V3 W& K3 _4 F
Holes, 空洞4 C1 e6 g. _ y8 U# W
HOMALS, 多重响应分析
# K7 L5 r6 u6 DHomogeneity of variance, 方差齐性2 L( w9 U( h$ C: |( Q
Homogeneity test, 齐性检验
2 p! @) K; o+ f) PHuber M-estimators, 休伯M估计量
2 ~6 d, e. P2 K, nHyperbola, 双曲线
# |, T, V0 \$ Y% o; \Hypothesis testing, 假设检验5 m" j! Z; t- S6 A6 B
Hypothetical universe, 假设总体
2 `0 k1 i# S5 |5 u& `( f2 fImpossible event, 不可能事件
3 j2 x( R* X( U: x8 eIndependence, 独立性+ W0 \" r' M% H& Q# \
Independent variable, 自变量
( h# s H' s" M) wIndex, 指标/指数
7 d5 s8 S% V' ^; {+ @4 Z9 HIndirect standardization, 间接标准化法6 Q3 { {$ ]8 t1 S" ~0 x
Individual, 个体
" O t& Z, p" z1 ~! n. |6 VInference band, 推断带
$ s9 j. |3 \5 @) [& ]8 kInfinite population, 无限总体
6 g; V. a5 d9 Y3 U: z7 S8 xInfinitely great, 无穷大0 p f' z) Z: O; n( g) r6 V
Infinitely small, 无穷小
( I q4 |; I/ E7 I9 gInfluence curve, 影响曲线
1 X3 ~2 g8 T, K- M5 m* LInformation capacity, 信息容量 p5 O6 i/ @) b: e
Initial condition, 初始条件
7 i6 T- H3 `8 NInitial estimate, 初始估计值- G0 [- }" J" A5 R- A' R
Initial level, 最初水平
3 _& e$ q6 ~1 yInteraction, 交互作用+ J% V$ P/ B; k( q
Interaction terms, 交互作用项
T" f" ]& Y. }9 [. \Intercept, 截距
! W1 U/ w/ }( P2 J: b( \3 @Interpolation, 内插法
* P0 a5 |! k6 h7 [/ qInterquartile range, 四分位距
0 a1 Y% M! ]5 p( E0 }* B, C2 aInterval estimation, 区间估计5 r d/ F* W% j3 ? K% ?( A% |
Intervals of equal probability, 等概率区间
- a3 p: u$ v, `' f9 e* k3 ]Intrinsic curvature, 固有曲率
5 I7 m7 }- F- U3 y- A7 q5 BInvariance, 不变性8 h! }3 L& h M
Inverse matrix, 逆矩阵6 G* K& Y5 ] u5 [1 e- c
Inverse probability, 逆概率
& z% y2 q! u$ Q% g' ZInverse sine transformation, 反正弦变换! y0 ^8 v3 O/ |+ l% [& i/ }9 a
Iteration, 迭代 ; M M5 t) B4 Q' M- s( l- \
Jacobian determinant, 雅可比行列式* e/ w1 J" H' K
Joint distribution function, 分布函数
. s) S F, K) o# D# J) J6 @Joint probability, 联合概率$ S: Y# @3 b; l' c$ `
Joint probability distribution, 联合概率分布$ A7 q% c; P( }. i
K means method, 逐步聚类法; ~" p! X, H' L; @$ p0 J$ s9 q
Kaplan-Meier, 评估事件的时间长度 ! u6 X/ m* j6 M7 z" A: s
Kaplan-Merier chart, Kaplan-Merier图. J; c% M/ L/ ~8 D, ]
Kendall's rank correlation, Kendall等级相关2 o' b7 L: U+ `$ s
Kinetic, 动力学
: C, D! f" T: z3 g, I" FKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
& }4 R ^9 Z* z/ |0 i1 GKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验' [, O* m8 i; ?) l' U
Kurtosis, 峰度
3 Q7 A! R. E2 s* t: o! t0 e; I. HLack of fit, 失拟2 L' X) W6 {4 v) e9 g e
Ladder of powers, 幂阶梯, E# k c1 u$ s
Lag, 滞后. B# X: d( r" ^1 u3 F0 c2 G( Q
Large sample, 大样本
. n9 r! ]+ H1 y; H7 SLarge sample test, 大样本检验
7 X0 y, y' z: `0 M( c0 c2 hLatin square, 拉丁方 w4 H* D; ^8 Y( I
Latin square design, 拉丁方设计
, \' o9 ~. \, Q- \Leakage, 泄漏
2 s! ~. O* S2 Q, n G5 ~Least favorable configuration, 最不利构形( s& D& T) }# Q! T" q2 [
Least favorable distribution, 最不利分布
8 a% K# A: d$ v) @' qLeast significant difference, 最小显著差法, u) \4 H& r9 t+ b
Least square method, 最小二乘法
% z4 Q% l F) o2 ELeast-absolute-residuals estimates, 最小绝对残差估计* V" D4 R+ A+ i, }1 ~2 k
Least-absolute-residuals fit, 最小绝对残差拟合
3 L. I) [1 a6 z# QLeast-absolute-residuals line, 最小绝对残差线
7 _# O% c! ?2 h D t: n7 LLegend, 图例
+ `% |! a; w: d0 uL-estimator, L估计量
7 x% Q7 F& B \) Y2 l$ U0 ^, @, FL-estimator of location, 位置L估计量
! I$ N% s1 w3 u8 c* d- |L-estimator of scale, 尺度L估计量
4 Q0 W3 e# n* M; r5 ^( c$ @) ELevel, 水平4 R2 l2 X; Z: H3 O- _
Life expectance, 预期期望寿命
! O) |4 j: Q; @8 }) E3 p5 sLife table, 寿命表5 r9 ~' } y5 ^6 Z
Life table method, 生命表法
% A7 r1 T' f4 n4 r" t% G& L) j" ULight-tailed distribution, 轻尾分布
6 O* r8 @+ L) f( uLikelihood function, 似然函数
3 }2 Z8 n2 L5 z2 Z& G$ mLikelihood ratio, 似然比' V* S6 [& G) n
line graph, 线图
* Q2 U7 P- T/ pLinear correlation, 直线相关: d% _; E: M% L, @: M/ P
Linear equation, 线性方程
) f5 s L& B, _& O+ I* |6 a2 PLinear programming, 线性规划
! B I( n/ [+ hLinear regression, 直线回归4 T8 }3 f$ n" V: `$ V: W# r" y- i
Linear Regression, 线性回归, J. h0 u( m4 ~
Linear trend, 线性趋势' y8 ^2 a2 T$ ?
Loading, 载荷 - U4 Q1 k) X# b; r
Location and scale equivariance, 位置尺度同变性
, S+ S2 A. U. \2 yLocation equivariance, 位置同变性& }* ~# h, J' `7 y0 }) ~7 a. B
Location invariance, 位置不变性5 ~+ ~! {1 c) ^
Location scale family, 位置尺度族
$ S( U0 P0 C KLog rank test, 时序检验 5 B6 d: j5 O/ m, {# r: i! K0 ~3 b7 K
Logarithmic curve, 对数曲线
- R+ {/ ~* Q: h5 R0 }0 }% SLogarithmic normal distribution, 对数正态分布5 V% d3 {( A7 V5 E3 L! f8 t" k4 E
Logarithmic scale, 对数尺度
2 D, @/ [9 I% R; yLogarithmic transformation, 对数变换
% G" D; g" \; Z0 f9 O& KLogic check, 逻辑检查
# I4 ^, B( c/ r- H6 |& g& QLogistic distribution, 逻辑斯特分布
" P6 C6 Y6 l/ M5 a% cLogit transformation, Logit转换1 S# c h0 j I: L' G
LOGLINEAR, 多维列联表通用模型 & S- ^6 |6 K% C/ }/ z/ T
Lognormal distribution, 对数正态分布" E j# p2 f/ Z7 k
Lost function, 损失函数* g! J: q1 o9 b# t5 i2 Q
Low correlation, 低度相关9 f0 y+ s$ B, ^+ u( m# ?
Lower limit, 下限6 w: R2 j- |3 O/ Q$ y6 W9 s9 e2 J
Lowest-attained variance, 最小可达方差% n) \* S, q5 ^8 k
LSD, 最小显著差法的简称 j- S9 V$ H/ T
Lurking variable, 潜在变量* D: m. A' A& x
Main effect, 主效应
; H7 y- {* O7 | TMajor heading, 主辞标目: P% o5 {7 |: L/ X6 n2 E7 A2 V7 r
Marginal density function, 边缘密度函数4 E5 Q: ~7 q7 x& F- w: F; N+ l
Marginal probability, 边缘概率, Z0 x8 i1 I6 `& _
Marginal probability distribution, 边缘概率分布
/ S- D% X( {3 K3 rMatched data, 配对资料
; Y1 @3 Q, y1 i" HMatched distribution, 匹配过分布
) l. d, I" F4 o! W3 p0 k7 l2 NMatching of distribution, 分布的匹配
. k+ N7 t4 l" V- `. XMatching of transformation, 变换的匹配
: }0 [ G. v: a$ n6 F7 Q; o; FMathematical expectation, 数学期望. y2 F/ S: k2 E3 v3 j
Mathematical model, 数学模型& k1 R3 \ Q+ U
Maximum L-estimator, 极大极小L 估计量
- G* C1 q$ q" C: E3 q( RMaximum likelihood method, 最大似然法
" _7 R* r+ n. h& a2 ?Mean, 均数
* p. L' t. i0 f& X* r1 ]; X9 HMean squares between groups, 组间均方
" H0 ^ \) y3 Q# xMean squares within group, 组内均方
9 i4 Y N1 P: j* pMeans (Compare means), 均值-均值比较% K3 ~5 v' B/ d1 v
Median, 中位数+ l! g3 o) E9 w2 L8 \5 ~# [. C4 s8 ]
Median effective dose, 半数效量: r& T9 I& X4 t) R! G4 _0 b; P* z
Median lethal dose, 半数致死量+ ]. R5 K. B4 U1 h
Median polish, 中位数平滑 I* C1 S( ~; h7 [% k
Median test, 中位数检验3 o( t- M* N! [ @$ f, a, F- u% l
Minimal sufficient statistic, 最小充分统计量 _! m- @" w* W3 m- C' D2 f
Minimum distance estimation, 最小距离估计
6 E8 T! s7 Q" H, d; RMinimum effective dose, 最小有效量
* T1 [6 @1 j" i! z c" [. jMinimum lethal dose, 最小致死量
6 t. u9 l6 B, D6 R2 }6 j: r* J$ R& X1 wMinimum variance estimator, 最小方差估计量; }5 G2 X% {) Z+ L- I
MINITAB, 统计软件包
/ I# D V( Y- u0 M, U" hMinor heading, 宾词标目! P( ~, `* |: G8 o6 c$ z
Missing data, 缺失值
P# v7 T3 e3 ~3 E" FModel specification, 模型的确定) \* u3 E/ @+ \1 h o+ Q
Modeling Statistics , 模型统计! w. [8 m" h& Z6 ]- _! c
Models for outliers, 离群值模型& ?9 `2 A* o! E. \2 ~
Modifying the model, 模型的修正
8 o+ u/ D1 D# e7 C: M9 H5 wModulus of continuity, 连续性模) b; \0 j+ |' S; Y9 I h
Morbidity, 发病率
) |6 C8 E3 p1 w& `" BMost favorable configuration, 最有利构形3 L3 c f$ |6 I* E. k
Multidimensional Scaling (ASCAL), 多维尺度/多维标度) O. y! M- J7 J3 [
Multinomial Logistic Regression , 多项逻辑斯蒂回归
% o7 ^, S/ a+ LMultiple comparison, 多重比较
5 e7 h/ a2 W6 ~0 \# _Multiple correlation , 复相关
' o2 j2 K; y6 z1 @1 ~Multiple covariance, 多元协方差+ S' i' r# _ i& r( U
Multiple linear regression, 多元线性回归0 z: D' [2 R- ~
Multiple response , 多重选项$ O( c/ E1 M4 r) M a$ _( n" @
Multiple solutions, 多解
9 X- Q G' f8 XMultiplication theorem, 乘法定理$ t! H2 }3 {- R" ]4 I
Multiresponse, 多元响应' \& l: u6 m6 L4 z5 N
Multi-stage sampling, 多阶段抽样
& A, m \9 m5 U: f1 n5 TMultivariate T distribution, 多元T分布, A, I" M( j7 H% L
Mutual exclusive, 互不相容 U' Q' O& ^ }& Z
Mutual independence, 互相独立
+ Q9 _- {* O6 ?2 }! q6 E7 rNatural boundary, 自然边界
7 o* V1 x3 l" u+ w; a( tNatural dead, 自然死亡
% @ }6 c3 P/ n* G+ }. O8 k$ QNatural zero, 自然零" X \2 b& c. M, f4 `
Negative correlation, 负相关7 s2 y, O8 E$ d, W c
Negative linear correlation, 负线性相关
% J, ]1 |3 Q* t RNegatively skewed, 负偏
# x L9 V9 [; H. k0 ~: |$ |2 W# KNewman-Keuls method, q检验
6 I1 R% m! n* U- z$ W) i; \NK method, q检验
0 b% b1 d: D0 u1 G' N4 GNo statistical significance, 无统计意义( w4 \& C6 B- R9 L% q* X
Nominal variable, 名义变量
+ F/ O1 l8 |$ sNonconstancy of variability, 变异的非定常性
p& I8 I3 A1 y! i/ ^Nonlinear regression, 非线性相关! S1 y; T- G" F" r9 c5 u8 @) ~
Nonparametric statistics, 非参数统计
/ H0 G) Z% D3 R/ U$ BNonparametric test, 非参数检验
4 n/ n' T/ a* iNonparametric tests, 非参数检验
- H$ x' B% f2 \: M1 i) T$ \/ KNormal deviate, 正态离差/ @8 K6 e! k* u
Normal distribution, 正态分布) E- m, ?' B G2 E% ]
Normal equation, 正规方程组5 z3 g1 n4 j( d
Normal ranges, 正常范围/ \& W: }5 @+ n
Normal value, 正常值
1 E* B9 m( x8 l5 ZNuisance parameter, 多余参数/讨厌参数
4 b( f4 p. ^# `( g' {0 g% {: Y% X5 T: vNull hypothesis, 无效假设
3 ~$ n2 S: D# I8 ANumerical variable, 数值变量
5 B. Y& g) M$ G& P7 W5 M* GObjective function, 目标函数2 J# b& j/ e5 @7 q* d- ~# c, o
Observation unit, 观察单位
3 m( X" c$ e) @7 H# TObserved value, 观察值
0 Z4 B4 c* T5 @( e- d3 }One sided test, 单侧检验
4 D% {# @/ ^. a$ l9 T" bOne-way analysis of variance, 单因素方差分析5 l( B3 Z. i! n" C! r# I
Oneway ANOVA , 单因素方差分析
9 X1 s% @' v- _6 {1 iOpen sequential trial, 开放型序贯设计& q9 A( r# c* R. P5 j
Optrim, 优切尾3 |8 g0 h T6 K' R2 l" A0 M
Optrim efficiency, 优切尾效率
4 W0 }) P1 G3 S; ^/ {0 m' _4 dOrder statistics, 顺序统计量
6 ?9 e4 \/ \5 q1 [* tOrdered categories, 有序分类7 v9 s* H7 N5 P+ i1 Z* m. D
Ordinal logistic regression , 序数逻辑斯蒂回归
' |1 G4 n& q! p' \# }3 P, N+ X; C. ZOrdinal variable, 有序变量
8 [# o! L8 O+ O& QOrthogonal basis, 正交基2 z7 ]" ~( |) A- u1 i
Orthogonal design, 正交试验设计
m: D- W- K" a- gOrthogonality conditions, 正交条件
$ T8 P# a4 P/ \+ B. gORTHOPLAN, 正交设计
' y' c- N1 s( U, q5 @5 P2 E; p5 UOutlier cutoffs, 离群值截断点
0 d4 j! Q0 W# WOutliers, 极端值
- [, p* P7 L# L0 m* qOVERALS , 多组变量的非线性正规相关 8 l& g; _5 d5 T0 c
Overshoot, 迭代过度1 Q, {5 n' I0 M
Paired design, 配对设计9 x$ ^" G# X: H: f+ ~; z' g& Z
Paired sample, 配对样本- R; v, N5 E1 g) r
Pairwise slopes, 成对斜率, A& \' o# }& Q
Parabola, 抛物线
2 ~- r; V# | xParallel tests, 平行试验( a8 l8 m1 q) K1 e$ @ @ C
Parameter, 参数& F& E7 {; b1 N+ E6 g& X
Parametric statistics, 参数统计* M D9 y: z; j! c9 ~" @3 I7 {$ G
Parametric test, 参数检验
0 D9 {7 |) Y' h xPartial correlation, 偏相关. Y! q+ G4 V$ A$ f
Partial regression, 偏回归
, J. t) F9 @) n" w, a. N) DPartial sorting, 偏排序
/ g' X" r9 I$ A1 w3 a m& YPartials residuals, 偏残差
" x6 L. P) u( v* o' }1 G9 R2 _Pattern, 模式9 a+ |. g. ~/ Y6 i
Pearson curves, 皮尔逊曲线4 M$ g8 O6 p) |2 K! }- R0 ?( p
Peeling, 退层0 Y( M& y! j! Q3 F: T6 h, P' k
Percent bar graph, 百分条形图2 G6 g: f, G; {; V2 E% x
Percentage, 百分比9 C) J) y: l& d0 N, q9 K) D% N
Percentile, 百分位数7 r# [. F/ ~7 Y
Percentile curves, 百分位曲线; I1 R8 z& {2 F3 D$ @5 \% K$ H' W
Periodicity, 周期性
* [, l0 o* T0 y) RPermutation, 排列
! p% j5 z0 c1 iP-estimator, P估计量' t+ e! }, U9 X) f! j9 J
Pie graph, 饼图0 k, z# b( |/ D5 ]# t/ ^( o1 C4 L- P
Pitman estimator, 皮特曼估计量# _4 ~+ d8 i9 i5 ?
Pivot, 枢轴量- |" v) ^6 @. y5 a. h' u
Planar, 平坦
3 y. |! j) W/ r& T2 MPlanar assumption, 平面的假设
+ j1 r% f2 _% X$ ePLANCARDS, 生成试验的计划卡1 g( o# h4 g) r- L' z
Point estimation, 点估计
. W& S% I; @+ j4 b1 }: j3 T1 ?Poisson distribution, 泊松分布
/ ~* I- \2 j$ @! p: j# k% x2 UPolishing, 平滑
( M5 f8 t- Q; h) r0 r% p t5 j9 y( c DPolled standard deviation, 合并标准差+ d" j0 [% f H% C
Polled variance, 合并方差- s: ?+ J1 `- G
Polygon, 多边图
( W s0 U9 R- l8 F: ^Polynomial, 多项式0 t7 L7 x2 D; }" G/ i+ H
Polynomial curve, 多项式曲线9 \; W* e& |6 ~$ w1 `) h
Population, 总体; |$ @ Y0 H2 V! ~' B% z$ J
Population attributable risk, 人群归因危险度
& r# d& U9 p# x O, W! ^Positive correlation, 正相关
) \2 {4 W3 e/ v, b, N! e4 pPositively skewed, 正偏+ p+ g( o) A; x% Q1 A u
Posterior distribution, 后验分布
X% n/ L9 u- j! ^Power of a test, 检验效能4 z6 ]. r/ q% _8 ^9 t4 \
Precision, 精密度
4 ]1 b8 s$ P4 s9 Y) ^Predicted value, 预测值- V" }7 ~: J' E: f+ A
Preliminary analysis, 预备性分析
+ I7 N1 ?" V, n% CPrincipal component analysis, 主成分分析
9 g1 R; H& w' B2 g/ {Prior distribution, 先验分布 K8 t' c, X% S$ _; y
Prior probability, 先验概率
2 R8 d. a- w* F# NProbabilistic model, 概率模型
/ x* a! x) v; nprobability, 概率
2 r3 J0 I5 p) ?( ?& @Probability density, 概率密度* c) g3 R/ \2 p, i E" y
Product moment, 乘积矩/协方差
1 D4 ~/ M! D& `9 y* |, MProfile trace, 截面迹图
: \ q4 ]/ X# J' \Proportion, 比/构成比
, X# \" T+ d9 i: @; ~Proportion allocation in stratified random sampling, 按比例分层随机抽样/ d+ b; W9 u: N
Proportionate, 成比例) {2 h9 Q& Z4 A& C: G
Proportionate sub-class numbers, 成比例次级组含量* J4 c2 [3 A4 v6 X* ?
Prospective study, 前瞻性调查' T2 A4 ~% [* E/ o6 X* I+ F
Proximities, 亲近性
5 p) C S9 ?( x2 {3 h. CPseudo F test, 近似F检验4 w5 T! s6 a/ k2 G' a2 y, F
Pseudo model, 近似模型
! ]& Y& ^7 u' B/ A" wPseudosigma, 伪标准差
. v) y' q; ]8 }' l9 G& l5 s3 G# |Purposive sampling, 有目的抽样5 O; y# f t! ~7 p/ D. a: a* A
QR decomposition, QR分解2 x4 e$ [! `5 J& ?- T+ o4 M
Quadratic approximation, 二次近似7 w5 j. y; h/ T* K5 o5 D& {
Qualitative classification, 属性分类
% N$ y' S3 a2 P4 u9 M" pQualitative method, 定性方法
0 A- w' n+ e; f+ j8 c* h- dQuantile-quantile plot, 分位数-分位数图/Q-Q图
0 q; n( G2 P2 v- W$ E" s6 U- LQuantitative analysis, 定量分析
- A- d8 d0 f4 @3 W) x! C1 P* | d- lQuartile, 四分位数8 @& h. _" E5 j0 h* A, b1 {
Quick Cluster, 快速聚类
+ h: |' u8 V$ SRadix sort, 基数排序1 P9 D) Q% ]/ x+ P8 A7 w. t5 L) U
Random allocation, 随机化分组6 ?0 u# }) f# _* c
Random blocks design, 随机区组设计6 z6 b' ]8 v6 Z
Random event, 随机事件
: W( I! u0 e% Z5 GRandomization, 随机化- B& v9 ]# x* j" S
Range, 极差/全距1 u% t( ] i3 O' g' E3 U( W% X
Rank correlation, 等级相关% l: V+ U5 K; E( F% u' y5 j* j
Rank sum test, 秩和检验7 U1 r8 n( Y- n, x1 ?- U! ~; F: j. I
Rank test, 秩检验. \3 r; \' |' h
Ranked data, 等级资料0 Y6 o5 [7 }8 {. N
Rate, 比率* A+ m" q" o2 ^- `5 o5 s; x/ j: z
Ratio, 比例, V$ Q, L6 M' e3 F* ^
Raw data, 原始资料; t* O- f- I7 p5 A0 \
Raw residual, 原始残差- F+ e/ b) T6 x: t+ j/ O; I8 ?& L7 V
Rayleigh's test, 雷氏检验
2 ` ]; Y, C" ~3 G. C$ @+ W" lRayleigh's Z, 雷氏Z值 % l& a+ F2 Q7 _4 @+ t9 |) o5 G% M
Reciprocal, 倒数
0 ?! C* Y- J' Q/ iReciprocal transformation, 倒数变换9 F( r# d1 W% y) Y
Recording, 记录; s. ?* Q! s5 H- T- `4 z
Redescending estimators, 回降估计量, H: R- r7 C$ B* }( C2 [
Reducing dimensions, 降维
4 i! Q- A" `9 A( Q4 ^, T. dRe-expression, 重新表达0 n* b' Q( S, Z6 G
Reference set, 标准组, D5 @5 B5 s" C
Region of acceptance, 接受域8 w, S+ [ W5 K7 h! u
Regression coefficient, 回归系数& E6 R$ w+ o" o* {4 L7 O
Regression sum of square, 回归平方和# S! e& v2 T6 E# B# e$ i' u. e
Rejection point, 拒绝点/ i [1 U' a9 T; O; s1 t
Relative dispersion, 相对离散度# o, ?$ z: M) c& h5 N4 g
Relative number, 相对数
& W# c! c+ Z$ I6 _5 NReliability, 可靠性9 J0 e' }8 Y3 G" C
Reparametrization, 重新设置参数
$ _, ]! y/ ], S0 WReplication, 重复( U7 |' l. b" x% u& [) O
Report Summaries, 报告摘要' t; u; ^ O6 k4 S& v
Residual sum of square, 剩余平方和
2 e6 l; J1 S! jResistance, 耐抗性: Z# d& g1 S. D1 B
Resistant line, 耐抗线( J# \2 H. V% V' Z
Resistant technique, 耐抗技术
( A# s5 V. f6 _1 S" U4 W2 _R-estimator of location, 位置R估计量
! @% i3 ~% ^- U* w2 jR-estimator of scale, 尺度R估计量& U1 F/ }! J8 }- l4 b
Retrospective study, 回顾性调查
: a! s/ q* j% qRidge trace, 岭迹
5 Q+ M0 d0 ?9 X# i' }7 P: r7 vRidit analysis, Ridit分析
. j! ^# p9 ?# u4 h& }& n0 m9 J3 _ ARotation, 旋转" \; {- d. n( ]$ n
Rounding, 舍入
% {) h5 D; E: ]# }4 C1 B' q- @. SRow, 行
( K) B& q3 j. W7 d( ~# I! XRow effects, 行效应% m- T" t& M g1 j5 g0 ~" J
Row factor, 行因素: ^) Y2 D3 F& }" `1 z3 i
RXC table, RXC表" ]! u8 ^, G8 a8 s" X# l
Sample, 样本
, W: x: m7 N( jSample regression coefficient, 样本回归系数2 A/ u1 p, p+ ~- `* k. }
Sample size, 样本量
% k7 V9 u# } S8 p( r2 wSample standard deviation, 样本标准差
3 e/ ]3 B# r1 s U: m' n4 xSampling error, 抽样误差( O& y: ]' z, Q. J
SAS(Statistical analysis system ), SAS统计软件包
5 ^! n* ^/ F" Z4 P! J! y9 V2 LScale, 尺度/量表* H) \+ h7 s: [3 _8 H9 u0 U
Scatter diagram, 散点图
7 p+ v& @! ]% P t. v; h$ T2 X) GSchematic plot, 示意图/简图 C4 {0 W0 |) }# |* J2 b
Score test, 计分检验
, C1 i( g$ h) ~# c6 MScreening, 筛检: J: V; i$ M9 }' e6 ^
SEASON, 季节分析
9 U" _- o* ^" |( E f6 D4 {! @Second derivative, 二阶导数
: @& B0 Y$ p( ?. PSecond principal component, 第二主成分% |0 V* K" Z$ D
SEM (Structural equation modeling), 结构化方程模型
, V, r& ~0 o" l0 oSemi-logarithmic graph, 半对数图. {2 Y9 r2 i8 `9 e5 D5 O
Semi-logarithmic paper, 半对数格纸6 ?5 |' H: s) s7 c9 h
Sensitivity curve, 敏感度曲线
5 o3 [. L# }, k4 ]9 HSequential analysis, 贯序分析
* o% `6 }. k% i/ z+ e2 b+ ]Sequential data set, 顺序数据集
9 k% W' w" D+ f) ?% k4 W" c. [Sequential design, 贯序设计
. _6 @1 ]; s; r7 z* q8 tSequential method, 贯序法
/ {9 q7 T3 e2 N- N. D5 `0 @. VSequential test, 贯序检验法3 n7 K# O I3 V" ~3 ?, E) R
Serial tests, 系列试验8 R. R$ F" r1 e) G% U1 t
Short-cut method, 简捷法
. t/ l8 k+ r9 p! l! W& H7 d, _Sigmoid curve, S形曲线% R; f2 D8 X2 J' i8 @' R" o2 |" D
Sign function, 正负号函数
1 Z& Y) z$ l! r) z* q$ [- @0 ^Sign test, 符号检验
; Q9 a3 H, [# ?/ d8 J+ K/ [Signed rank, 符号秩
: p# T. `- H4 f% p7 V' ZSignificance test, 显著性检验
& h" ?! K5 |% f. N9 hSignificant figure, 有效数字6 w0 _2 r& `/ B' v; l1 _
Simple cluster sampling, 简单整群抽样9 f% v, ?9 z) _' e
Simple correlation, 简单相关2 t" S( O c, _& O/ r
Simple random sampling, 简单随机抽样/ [: w# i2 t3 C; q m. d1 | F5 F
Simple regression, 简单回归
* |+ F$ Y0 ^0 O* hsimple table, 简单表6 X( ~. x7 _9 ?) N
Sine estimator, 正弦估计量2 C L8 Y1 x# [
Single-valued estimate, 单值估计
2 b# @5 |1 I! Q# ^3 lSingular matrix, 奇异矩阵
7 v0 c+ W5 ~: R) TSkewed distribution, 偏斜分布
* q" F) r. I4 x7 q* u4 p$ xSkewness, 偏度
+ N: d* N1 m, [: aSlash distribution, 斜线分布
9 A1 f3 O/ V1 T3 @7 Q6 @1 |9 d, hSlope, 斜率
2 A9 R9 ]5 M/ L+ [( I( C% r/ \Smirnov test, 斯米尔诺夫检验
: p" O# d. N J: zSource of variation, 变异来源
5 r, t5 p+ Y6 T0 w$ w3 VSpearman rank correlation, 斯皮尔曼等级相关. m3 E* X7 x( S
Specific factor, 特殊因子
7 \- H$ B3 Q0 nSpecific factor variance, 特殊因子方差
% k4 O% }1 K8 ?( pSpectra , 频谱
5 b! D/ ^, \& JSpherical distribution, 球型正态分布" _5 R/ o# ^* j( F9 a! {
Spread, 展布+ j: g* U3 o8 O: K) [% M. u6 ^
SPSS(Statistical package for the social science), SPSS统计软件包$ U# z9 A% s7 s* d
Spurious correlation, 假性相关$ }8 e8 o( r) d$ F) h
Square root transformation, 平方根变换 m/ V7 K. ~- a' U
Stabilizing variance, 稳定方差" ]3 q; b `8 \# |# y3 M
Standard deviation, 标准差
/ X$ H! G N9 o n5 |% d. qStandard error, 标准误# N* ^1 h! k0 A$ R9 b
Standard error of difference, 差别的标准误
/ O. v/ H5 S* A- i2 ]Standard error of estimate, 标准估计误差4 x. n* A$ A- G, N1 o9 C/ g( M2 _8 }
Standard error of rate, 率的标准误" r; o. d6 Y' M. \
Standard normal distribution, 标准正态分布
, i2 r+ Y: _' p* u- \3 {Standardization, 标准化
% A* h1 E, g$ gStarting value, 起始值- h+ r# }# u+ L/ L9 r+ @" S5 C! h
Statistic, 统计量
* g3 _( g+ Z0 o5 l N. SStatistical control, 统计控制
! \4 u% h7 N0 i6 t1 uStatistical graph, 统计图2 F+ ]3 C1 ] ~6 l3 X1 Z1 T
Statistical inference, 统计推断# G1 B$ l9 `6 _% f
Statistical table, 统计表
: O- D% E3 [; {Steepest descent, 最速下降法
( M% R. j) ^0 |. eStem and leaf display, 茎叶图
% h' \6 c' c0 T# y1 o+ B; p+ J* ^Step factor, 步长因子7 {9 M3 _/ l2 R# e" k
Stepwise regression, 逐步回归4 b) S3 d" ]' Z; r3 e; Z1 [- W
Storage, 存& k& k1 \. a+ I0 U: y
Strata, 层(复数)
+ P& R# {2 f! cStratified sampling, 分层抽样
! A l9 j+ |/ K7 IStratified sampling, 分层抽样
' u7 g* h5 h7 ~; I8 AStrength, 强度0 p4 T# Y) s$ \3 w& ^! C" H
Stringency, 严密性
9 a( U, e0 k2 `# V* Y! SStructural relationship, 结构关系
* \, H( b; S6 b/ B: b% yStudentized residual, 学生化残差/t化残差9 L, q) s" @! l) n
Sub-class numbers, 次级组含量. Y! h {* M) o- z, }# n5 {, k
Subdividing, 分割
' I( `+ }3 d0 o: t9 VSufficient statistic, 充分统计量( G9 G2 P. Y9 r* y- `
Sum of products, 积和
% p, Q# X/ }9 T. t9 _$ PSum of squares, 离差平方和
6 V9 x* A3 [, h3 R# k. }: ~Sum of squares about regression, 回归平方和2 ^1 `" a# A* r
Sum of squares between groups, 组间平方和9 m' O7 ? c* _+ l, i) [& }
Sum of squares of partial regression, 偏回归平方和
0 L4 V5 [- I8 M4 v+ FSure event, 必然事件
. ]/ m2 e* o- F8 MSurvey, 调查
) f8 {1 A# ^1 @5 o2 h! E7 |Survival, 生存分析, @8 N& K/ `$ s& b, S) b
Survival rate, 生存率
, `7 Y; F; D& E( V+ ^" ZSuspended root gram, 悬吊根图( A1 L) p% J0 \: Z" ^
Symmetry, 对称
0 E( I6 U0 z( V& \1 h; n; t) dSystematic error, 系统误差
, d8 U) n) W$ C; V8 ^" J7 ?6 ~Systematic sampling, 系统抽样
7 ?/ d; G* w5 d3 Q$ z5 O6 M' Y, I) DTags, 标签; @) N* i' G% P1 s) J! l
Tail area, 尾部面积4 _2 t Z1 T4 L2 u
Tail length, 尾长& V M4 J/ n/ v! U
Tail weight, 尾重* @+ y8 ]+ A9 F A, J% ^* Z; K
Tangent line, 切线8 i. ^7 e; k% P% n, t" a! w% n
Target distribution, 目标分布7 ~9 K- R. }3 [. ^1 p/ y
Taylor series, 泰勒级数1 B+ f& [3 V7 Q2 W5 y1 B! c
Tendency of dispersion, 离散趋势
3 l# f# t4 v! h* _9 f1 k* [$ S# sTesting of hypotheses, 假设检验; d6 K$ u. C' f9 W% r
Theoretical frequency, 理论频数2 e8 G. D5 k8 O8 I% ~% m9 r
Time series, 时间序列 h/ t% ?0 ^) Y8 n
Tolerance interval, 容忍区间
' P) H( T; K0 r" x8 \; eTolerance lower limit, 容忍下限
. n" B4 X- w/ gTolerance upper limit, 容忍上限
/ L, |& C e( ~* gTorsion, 扰率
, [; r: y8 F' a- oTotal sum of square, 总平方和2 t% a5 ]% T4 E- x0 c+ h
Total variation, 总变异
" |9 O4 O( Y0 K" J$ ?Transformation, 转换
* p8 ~8 h$ u/ K! J; KTreatment, 处理% E4 H6 M7 N5 a1 v
Trend, 趋势
. x9 N# f' [2 m! LTrend of percentage, 百分比趋势) i6 |- F- x5 X# V8 @7 ?
Trial, 试验$ A4 C" m7 |2 T8 V! U) J! b# r: Y- A+ c
Trial and error method, 试错法0 u" c- ^, E9 t! l' p S
Tuning constant, 细调常数8 X8 n% {# h9 u. w; c: b
Two sided test, 双向检验; {8 o2 B$ T) U- W- e4 X
Two-stage least squares, 二阶最小平方; `9 C7 E- K/ @7 Q
Two-stage sampling, 二阶段抽样4 |. l- X. d+ D
Two-tailed test, 双侧检验0 L Y& D% ]) E
Two-way analysis of variance, 双因素方差分析
: Z; v) b( k( K7 HTwo-way table, 双向表# m- ]1 [# X) y' d2 s. Q0 f( n
Type I error, 一类错误/α错误
" C& u6 P: v$ ]3 n. F" DType II error, 二类错误/β错误1 \2 W+ i+ i9 E* l' B7 f P/ g$ z
UMVU, 方差一致最小无偏估计简称0 ^9 m% r I, D
Unbiased estimate, 无偏估计
1 T/ x# L- R( V sUnconstrained nonlinear regression , 无约束非线性回归
/ j6 q5 P2 _+ b, n6 _! v1 [Unequal subclass number, 不等次级组含量$ l" L: N, w, S3 @
Ungrouped data, 不分组资料
) h) _9 L& b. b3 n* R! EUniform coordinate, 均匀坐标9 T7 p% m0 o6 j V: [ h
Uniform distribution, 均匀分布
# k, _0 x7 C: u0 `- c8 |Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
8 W5 Q4 ~- Q8 T* W0 Z) }( mUnit, 单元# Q: s, E/ B9 a* i+ d' [0 [! D
Unordered categories, 无序分类
0 A: l6 D+ g7 p" @Upper limit, 上限% k3 A, h2 R, k5 E1 E$ ?" X
Upward rank, 升秩
8 t- c5 x) g! n& Z( qVague concept, 模糊概念
5 l+ U% f+ C) p2 m4 ^5 }Validity, 有效性+ L8 W& a9 U9 P
VARCOMP (Variance component estimation), 方差元素估计0 S, W6 _5 J. B' J! I
Variability, 变异性
. I0 `3 P2 u, y( X2 i* `. k. l: q! |% HVariable, 变量( M) n2 V* q$ F+ s
Variance, 方差2 N* J; j; W7 D7 Z
Variation, 变异/ O0 b! [! u4 {6 ]2 q; V! n
Varimax orthogonal rotation, 方差最大正交旋转
* S+ w. V! A- t- @0 {' w2 ?& xVolume of distribution, 容积
2 k4 z+ G; u2 P x) YW test, W检验
' W$ h+ o/ t# S; OWeibull distribution, 威布尔分布
X. O: O( z/ ^* u2 pWeight, 权数
6 {% b% M( @% L9 `& p2 }% I8 WWeighted Chi-square test, 加权卡方检验/Cochran检验. @$ W! A; A% {3 R
Weighted linear regression method, 加权直线回归
. v' q5 {% b- @ r8 Z& B, hWeighted mean, 加权平均数7 x2 x, A; R- q: v9 V) X/ V7 z1 }
Weighted mean square, 加权平均方差* V, N9 {& T7 p0 i2 i3 I1 t& c8 M2 T! n5 _
Weighted sum of square, 加权平方和
2 M/ ~3 U# `) q3 P* R9 Z' KWeighting coefficient, 权重系数( d" B7 b5 ^3 V0 \! S! }+ }( z
Weighting method, 加权法 9 S2 ~' n( ~% r% t5 q7 @
W-estimation, W估计量
( ^8 n0 A/ h) b( y8 YW-estimation of location, 位置W估计量
3 l2 Q- n3 W$ U$ e9 O7 e# x5 ~+ \ lWidth, 宽度# ~3 e% n a+ W' E, V
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验+ V3 p0 ^3 M# T$ S- u
Wild point, 野点/狂点
, P2 _# s( o( u& sWild value, 野值/狂值
9 j1 ]# y% N0 r( _3 WWinsorized mean, 缩尾均值8 r c2 g6 P/ J8 ?0 R
Withdraw, 失访
" }) R6 A, t( c9 W5 J1 a5 y! j }. MYouden's index, 尤登指数
: A) z9 ?) o6 v ^1 GZ test, Z检验* ]5 w8 X- P- c: e+ `: [
Zero correlation, 零相关
- V+ o$ n% O. LZ-transformation, Z变换 |
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