|
|
Absolute deviation, 绝对离差0 K @! \6 D+ i) M
Absolute number, 绝对数
% }, v: E- j6 i5 O: S; bAbsolute residuals, 绝对残差0 R1 o- R! M d) f3 p$ r+ c" \
Acceleration array, 加速度立体阵
+ u- A9 M0 d& b# S1 x7 VAcceleration in an arbitrary direction, 任意方向上的加速度* M1 s) p( @+ ]3 L! S! o b
Acceleration normal, 法向加速度 C' I4 A2 b# L6 F! @+ a6 H
Acceleration space dimension, 加速度空间的维数$ v- [6 V5 V) O: C: Y1 z% c
Acceleration tangential, 切向加速度
) j0 s, S9 x( Q- FAcceleration vector, 加速度向量
1 {9 r: D5 N& B& m/ pAcceptable hypothesis, 可接受假设
3 W! ^+ g7 h( y; fAccumulation, 累积
) R9 x' T7 R+ H+ Y& l* E# Z! aAccuracy, 准确度" d7 x* H# _, P
Actual frequency, 实际频数8 w$ U, z- V0 d- v4 K- ^# z
Adaptive estimator, 自适应估计量0 m E0 T9 H. a* |2 u, Z
Addition, 相加5 Y. H* ]: G! y' I$ S
Addition theorem, 加法定理. c7 V) A7 X" S" R
Additivity, 可加性# V8 l5 l9 I% e9 x
Adjusted rate, 调整率
9 y; P7 r1 H+ f. |Adjusted value, 校正值
5 j' b' `; ]3 J, S$ Z, |: ZAdmissible error, 容许误差8 M. [/ w& b! e9 ^) W9 }; v6 P8 ]
Aggregation, 聚集性
+ Q* S4 U6 p6 i% g3 ~: x/ rAlternative hypothesis, 备择假设4 j8 m: ?$ g, S, E( p G2 T: E
Among groups, 组间2 e# C# ~4 e4 h
Amounts, 总量
. u- S! v X; [0 ZAnalysis of correlation, 相关分析: `2 x, `1 n L6 E7 Q6 b9 S+ F( \" G
Analysis of covariance, 协方差分析
0 o' u) u Y9 `Analysis of regression, 回归分析
" n1 [/ s3 \' B. R% s! u+ k6 {6 gAnalysis of time series, 时间序列分析) S" w( X/ @' | w
Analysis of variance, 方差分析
; Q1 B6 z; H5 ?5 EAngular transformation, 角转换/ k) A7 v4 M8 F, K7 G! H% n
ANOVA （analysis of variance）, 方差分析! A2 N6 A; F. Q0 u. P
ANOVA Models, 方差分析模型
8 [' m# X4 `' l7 t' p' k- gArcing, 弧/弧旋
C: e; q) h. I! r4 _Arcsine transformation, 反正弦变换
9 x! j3 C: C0 ^Area under the curve, 曲线面积
; E9 H. @: |, C: ^2 ]AREG , 评估从一个时间点到下一个时间点回归相关时的误差 7 H) L2 {# }2 x$ m
ARIMA, 季节和非季节性单变量模型的极大似然估计 : }, B7 X) f: C% y" K/ }. H" ]& G4 ?
Arithmetic grid paper, 算术格纸
. b2 [' d4 Y1 @& R e0 w( VArithmetic mean, 算术平均数6 q* w# q3 W* R" _- {; t1 M
Arrhenius relation, 艾恩尼斯关系9 r7 ~9 v9 v/ c% A
Assessing fit, 拟合的评估
* z1 e" f7 o# N* w0 g: wAssociative laws, 结合律* R" }6 z% o {! E. B+ T
Asymmetric distribution, 非对称分布/ f: i |% v6 Z8 p* m. k
Asymptotic bias, 渐近偏倚3 \8 }+ x: u$ {6 p
Asymptotic efficiency, 渐近效率6 ^: k0 `' j4 _ M1 {, u
Asymptotic variance, 渐近方差( T% w, v$ n; T+ }: k( e- c5 p( E
Attributable risk, 归因危险度' u5 z* a: I+ y5 |& a. N! P
Attribute data, 属性资料
$ v8 P$ _( z9 e1 T: _" mAttribution, 属性
# f8 H2 n1 p. V8 E; }Autocorrelation, 自相关
# s5 X4 w9 Y5 ?0 }; r8 U& W9 h( AAutocorrelation of residuals, 残差的自相关0 C0 h$ `- A X3 i+ J5 \
Average, 平均数; H7 `/ Y5 ?' K" ?3 |
Average confidence interval length, 平均置信区间长度
7 c' {' o, L5 O, K: ]Average growth rate, 平均增长率
* z1 B9 r! C7 s. L1 lBar chart, 条形图* ^) p( ~1 c" t2 h
Bar graph, 条形图5 M) {; A5 i& W
Base period, 基期/ \! S# w% `; a ]
Bayes' theorem , Bayes定理. _, A0 [% O+ M+ o/ ~
Bell-shaped curve, 钟形曲线
! Z3 u- b7 Q+ Z0 L) l: ~9 M9 yBernoulli distribution, 伯努力分布 R; J1 }/ D8 O' m- C
Best-trim estimator, 最好切尾估计量4 }: r% R! F7 a- }1 l
Bias, 偏性
* H2 t6 f) N0 ?! Y5 I- `6 C9 gBinary logistic regression, 二元逻辑斯蒂回归: z! B' {$ [. Q! Y
Binomial distribution, 二项分布6 e/ H9 H2 m0 Q) A, D$ B; j
Bisquare, 双平方
- g, L7 H. X( Z1 T% e1 tBivariate Correlate, 二变量相关
/ J7 j. f! h5 G* d! q7 z. bBivariate normal distribution, 双变量正态分布( a, S) x4 D0 b6 _
Bivariate normal population, 双变量正态总体
; c4 Y# }" F& P. Y6 g$ sBiweight interval, 双权区间2 ?, h; [2 B r u; v0 Z; t0 y
Biweight M-estimator, 双权M估计量
6 a0 w- F) v4 r& M4 b5 LBlock, 区组/配伍组
/ R$ q9 I( Z3 M5 @1 j- kBMDP(Biomedical computer programs), BMDP统计软件包, H3 X& n9 Y4 T) _2 N; @, ~
Boxplots, 箱线图/箱尾图, D1 v9 \; ]+ b( K' q; d1 y
Breakdown bound, 崩溃界/崩溃点8 I4 }0 P" I0 @! J& G1 Q& c
Canonical correlation, 典型相关2 [. B0 ~2 T, w* N8 g( K
Caption, 纵标目
) ?! B$ i4 G, oCase-control study, 病例对照研究
8 g) Q+ D$ X( w. v, wCategorical variable, 分类变量, p" s E8 K1 l) M* T3 Z# T
Catenary, 悬链线
( o3 D$ T0 i" a8 J& n$ G) D' h/ tCauchy distribution, 柯西分布
! I: N( }# B1 C% D7 i$ K) QCause-and-effect relationship, 因果关系. v U! P1 J; i5 c9 f7 R
Cell, 单元
5 {& R; b7 f% n: BCensoring, 终检
6 Z, }% t% ?, `* i- nCenter of symmetry, 对称中心
, z: ]) Q% h0 s$ g$ {# CCentering and scaling, 中心化和定标
8 D+ }# z y5 ?# P. }# n0 XCentral tendency, 集中趋势
3 Z0 z' p7 S" m# ICentral value, 中心值! [ p; J& r; r) Z1 s: a+ G% a
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
2 Z: G* W' N0 a0 p8 @Chance, 机遇
/ `- X1 I6 ^% x" q( R) l" KChance error, 随机误差8 |8 P+ D- q) [5 ?/ O( h( p: q
Chance variable, 随机变量( d* S% N0 }' v
Characteristic equation, 特征方程
- Z' c3 ^: a4 |+ I$ S6 |Characteristic root, 特征根6 y4 s: i8 H: q9 E L0 @3 O
Characteristic vector, 特征向量
' s/ @7 d a, V1 G" t6 g3 cChebshev criterion of fit, 拟合的切比雪夫准则
2 ^- r' b( k, j# ?2 DChernoff faces, 切尔诺夫脸谱图# F& X, [7 [3 c- g
Chi-square test, 卡方检验/χ2检验
& }7 u+ X+ C0 C- m2 NCholeskey decomposition, 乔洛斯基分解5 O& {5 R& K0 B! I
Circle chart, 圆图 : o+ Y+ B) y! C' U# L9 i `
Class interval, 组距1 q2 C; K# G2 ? u3 ^& w
Class mid-value, 组中值) t3 }+ F1 T* | g
Class upper limit, 组上限7 s/ v* @) m- m7 r
Classified variable, 分类变量
* K8 O6 h5 {" CCluster analysis, 聚类分析& n9 `- u$ k" U3 D
Cluster sampling, 整群抽样
0 S. D- \+ Y9 I) L+ G! h, c. BCode, 代码
" E2 C4 k2 w3 v: g* OCoded data, 编码数据9 q+ k9 L7 `% ~$ N4 V& m" P
Coding, 编码
( F8 a" ~; ~+ U& Q8 n; E3 ^3 \8 [5 LCoefficient of contingency, 列联系数% p+ [: m& ?. D! `6 D. }2 E8 B
Coefficient of determination, 决定系数& J" z* W) D: a* n5 F
Coefficient of multiple correlation, 多重相关系数
2 Y$ q4 H& S0 n, f0 `$ `3 KCoefficient of partial correlation, 偏相关系数4 ?, I' R, I& C
Coefficient of production-moment correlation, 积差相关系数4 K# y/ D2 C) L$ `. V* ?
Coefficient of rank correlation, 等级相关系数, B2 k5 n0 m( U- `- H" ^7 M
Coefficient of regression, 回归系数; S& L6 o" e+ ?: a
Coefficient of skewness, 偏度系数
0 f! R: {3 P' N# \& ^8 B' jCoefficient of variation, 变异系数9 {; U" `; c7 ]' u2 {! J/ v
Cohort study, 队列研究+ W1 J1 d- D" @" y0 H
Column, 列
; |! q4 X/ O/ u- {2 \$ u2 i. ` }- aColumn effect, 列效应
) V5 G, @; n+ e I8 P9 m, zColumn factor, 列因素
/ y: T [3 U2 y8 _; `Combination pool, 合并9 P- n% G- X; B
Combinative table, 组合表5 o( V: f! ]/ N9 b9 e8 }
Common factor, 共性因子0 u. e& B3 h% d6 g3 p+ n! S8 D
Common regression coefficient, 公共回归系数
5 R% R, _ M$ D" i* QCommon value, 共同值
0 b6 U5 N3 r' \3 }3 {Common variance, 公共方差, z2 U2 v: Y. i5 d7 i( S
Common variation, 公共变异
: C# r7 d8 C% Y5 v3 eCommunality variance, 共性方差
7 l3 U. X) E& a( J r A$ XComparability, 可比性& T1 m: d( k# i* k, U
Comparison of bathes, 批比较
9 S" r6 {, k& x8 {# d# t* t5 oComparison value, 比较值
4 H \, s ]1 C5 mCompartment model, 分部模型
5 S0 [) r7 O0 C' ~Compassion, 伸缩
* i' A- u' R8 `% B1 q4 gComplement of an event, 补事件 F: d- n. m8 C O. p1 q* k
Complete association, 完全正相关
1 F# h3 B# _1 P) c. ^/ t$ L2 PComplete dissociation, 完全不相关5 U/ a. A! N: e0 u7 |
Complete statistics, 完备统计量& h# v& I* D, U1 N4 Y) \6 r
Completely randomized design, 完全随机化设计
- ~! q1 \ a# T! @( WComposite event, 联合事件
( i- ~8 B& v+ c, AComposite events, 复合事件5 s2 L! p1 C3 O( f% K. m3 B# N
Concavity, 凹性
8 K; `$ Z' ]0 t( p; a( \. y+ ^) NConditional expectation, 条件期望, E' u T, G: q/ e7 s2 O0 m. ?! _
Conditional likelihood, 条件似然
" t) `- h2 L+ G: qConditional probability, 条件概率& P/ t( D& V$ A3 o- L% K f
Conditionally linear, 依条件线性
o' h8 S1 O x/ K0 \! vConfidence interval, 置信区间
0 Y" [: }) G( {! s6 ]Confidence limit, 置信限( Z! ]! v$ S* k$ [ b: Y" t
Confidence lower limit, 置信下限) @7 v8 `* `; w$ [! R" k
Confidence upper limit, 置信上限
7 D6 N% R) Q8 e7 RConfirmatory Factor Analysis , 验证性因子分析
0 Q* q0 f6 J. N G! Y5 ]Confirmatory research, 证实性实验研究6 o, X8 ~( d/ |
Confounding factor, 混杂因素
6 Z9 x! J% y+ \# ~& ^$ M- t" NConjoint, 联合分析7 F" A4 |$ Q9 H" m) H# {
Consistency, 相合性
4 W+ e6 ?, B6 Y3 ^Consistency check, 一致性检验
! W3 _) x/ g. K- `, r" s. h' iConsistent asymptotically normal estimate, 相合渐近正态估计& R4 E2 k6 q+ N
Consistent estimate, 相合估计
7 d" k% x3 n \( \Constrained nonlinear regression, 受约束非线性回归
, W+ I0 [ \/ K7 J7 e) q3 hConstraint, 约束
" Q, E, P3 S- L; n: S' K1 {Contaminated distribution, 污染分布& k, L+ i' e3 F5 h) T
Contaminated Gausssian, 污染高斯分布
# m2 T4 \. a2 A+ @$ ^2 qContaminated normal distribution, 污染正态分布* t- a# i/ M2 Y) [3 a, E0 q
Contamination, 污染
1 F% f _3 h0 C+ \Contamination model, 污染模型
) n% a1 f* r8 G% V. X- sContingency table, 列联表% y- L& j$ |9 ?& f) e( z I O8 ]& }
Contour, 边界线' O) ^9 o- h+ u0 X& k" Z# r$ _
Contribution rate, 贡献率
4 i! ^0 q( u% z9 H* p- rControl, 对照
2 l$ ~- D8 ]7 l* }7 R7 TControlled experiments, 对照实验
) u0 u/ R" [8 i7 @' b) _4 q- YConventional depth, 常规深度
: \9 k8 b5 m3 t- I! X% rConvolution, 卷积6 U7 M+ W3 C5 l4 [
Corrected factor, 校正因子/ r% d& s9 {. {6 L# M
Corrected mean, 校正均值 b0 X9 L3 j, z8 U' e
Correction coefficient, 校正系数
- P' h/ j7 R3 E6 x0 ~Correctness, 正确性9 H" Z8 a( ^9 j" [! m- y3 l+ Q
Correlation coefficient, 相关系数
: V- V+ r7 i# y) n% Y: RCorrelation index, 相关指数
1 p. K$ J! m5 q2 {- ?Correspondence, 对应! U, @' w% N5 F4 S0 M- D
Counting, 计数2 c; A/ |+ t' N: v% Q0 K
Counts, 计数/频数! {0 z9 N; w1 \, f: p) T, O
Covariance, 协方差
7 E( l0 F5 z% x5 \Covariant, 共变
8 U" b7 }" ~3 I0 i! T" nCox Regression, Cox回归; o: \/ E; W6 ?: p
Criteria for fitting, 拟合准则
# b( \8 d; F3 b! h! H3 {2 jCriteria of least squares, 最小二乘准则
% d" p/ f' w) m# O, O0 r6 a2 j3 d6 xCritical ratio, 临界比
9 s# E) }$ K3 M* Q, H* v* D# tCritical region, 拒绝域
+ o) q) T3 @3 k, @. t) M/ iCritical value, 临界值7 n4 o# B& U( R, @4 z
Cross-over design, 交叉设计
6 J0 l- M" [7 @# N/ lCross-section analysis, 横断面分析
, E6 A' e" e: A3 S n2 l: G: h: mCross-section survey, 横断面调查
) F# }! u: c0 ACrosstabs , 交叉表 , c4 n/ w$ L2 ^& k! \' s
Cross-tabulation table, 复合表
. l' N2 Q8 a8 C6 @Cube root, 立方根
" P" Z& ]% Q( N9 nCumulative distribution function, 分布函数
, ?/ l+ f& L& C: q# gCumulative probability, 累计概率
6 ?. G$ p8 W2 PCurvature, 曲率/弯曲
: S3 I6 B; p9 @3 Z) A {Curvature, 曲率$ o8 ~+ F4 b8 J% ~; x& v0 q/ K! F
Curve fit , 曲线拟和
+ A! @+ \/ i$ ~% |) _Curve fitting, 曲线拟合
7 v2 n. S! ` z6 LCurvilinear regression, 曲线回归
( X+ N( k w! o9 `+ y2 d0 D1 ?1 lCurvilinear relation, 曲线关系2 h3 p& _, X1 \9 U* v5 k' g
Cut-and-try method, 尝试法0 O" k/ `! c; D" B; X
Cycle, 周期) ` H8 S8 v! b; R" O E
Cyclist, 周期性
$ e0 x( X6 R" k* P9 SD test, D检验3 M1 ]: K$ z9 W2 e4 d# o2 Q
Data acquisition, 资料收集
9 P$ ?* [( {& Y: VData bank, 数据库
3 s. z5 i& ~6 ?Data capacity, 数据容量
. N B# z# E1 h+ b' ]Data deficiencies, 数据缺乏
+ l6 e" Y) b6 L# m- FData handling, 数据处理* b' i- t2 N# T) y9 Q1 j
Data manipulation, 数据处理" v/ O+ R5 _0 `( c. r6 g' y' {
Data processing, 数据处理! ]8 V1 Z( N; B1 o
Data reduction, 数据缩减( y; c y; ~/ N' O- v+ A
Data set, 数据集
8 ?! A7 R" y, K, R3 i) N3 T& m$ x9 hData sources, 数据来源
* {, n' R; i# t5 f. g VData transformation, 数据变换
% c; v& k0 @+ a! ]. MData validity, 数据有效性
3 Q1 d; K2 {* O7 \! Z+ w' bData-in, 数据输入
2 y6 `0 |0 O3 v' E/ T4 K- gData-out, 数据输出
+ K# a0 O2 q6 V( F6 pDead time, 停滞期" Y& T) }6 @& D3 T% T! g5 s
Degree of freedom, 自由度+ K4 S) {4 I+ o: g8 ]
Degree of precision, 精密度* }/ u- w6 A3 f) f/ Z- [# O/ g
Degree of reliability, 可靠性程度. Y! K/ R' s) O. y
Degression, 递减
* F7 o! F9 L! z: L, X/ s6 eDensity function, 密度函数7 R- n& b+ R# I t, N, [
Density of data points, 数据点的密度
, _( O0 A& P1 [# k2 {8 x: |Dependent variable, 应变量/依变量/因变量; O1 @9 C( C0 e' [" S4 P6 C: o
Dependent variable, 因变量
8 c2 p t; r. ^: {& l9 F* D! @Depth, 深度$ ~5 R7 d5 k6 J0 j8 U
Derivative matrix, 导数矩阵3 j2 l# t3 h4 c0 z8 u( k+ v
Derivative-free methods, 无导数方法! F3 |) B5 p. o# N
Design, 设计
" v$ B" O2 L- K; [( _. a8 \Determinacy, 确定性- [& ^% I5 w7 x
Determinant, 行列式
: e" B& ^3 O+ J( B; KDeterminant, 决定因素
- C4 p4 \9 m0 f. ?, Z1 J! lDeviation, 离差
& V9 ^7 s' r( N/ a/ SDeviation from average, 离均差
) t! E. _7 l* D. ~2 F- n/ i1 ]Diagnostic plot, 诊断图( L; s/ L: _# w: @* u; m( Y
Dichotomous variable, 二分变量
" E* _# n' X; R Z( x$ C dDifferential equation, 微分方程
7 G5 w5 ~2 m) G7 `6 P5 P& I7 iDirect standardization, 直接标准化法
3 @3 U" x( ~7 i* B3 SDiscrete variable, 离散型变量/ \5 [$ I$ \" y; ?& A) C( N
DISCRIMINANT, 判断 8 m# y: J+ E" J+ b4 E* F0 q
Discriminant analysis, 判别分析
0 ~4 E8 u. K- U# CDiscriminant coefficient, 判别系数8 X3 d7 w I" H# J9 e$ w* f
Discriminant function, 判别值+ c- h1 \0 o2 Z' R
Dispersion, 散布/分散度% O; J/ g9 F+ X8 K+ E+ j" a
Disproportional, 不成比例的" L( N& a+ i" n& v0 M+ J# P
Disproportionate sub-class numbers, 不成比例次级组含量0 X# R6 y" I, s+ _2 D6 I! _
Distribution free, 分布无关性/免分布3 B3 f* z7 t/ s: W9 A9 r6 h
Distribution shape, 分布形状2 N) c& W% r9 P+ j, V
Distribution-free method, 任意分布法
9 r* o: i7 H2 K0 U" N/ j: w: j1 oDistributive laws, 分配律
1 R( m$ w8 M: w6 ]/ ~& W$ hDisturbance, 随机扰动项
8 t+ Y2 b, n: P0 }" IDose response curve, 剂量反应曲线
( ^1 n' ^, E. B" I, \, @9 D5 J! mDouble blind method, 双盲法
6 I Z' G* E! q& [4 t( sDouble blind trial, 双盲试验2 G% f: @! w" y
Double exponential distribution, 双指数分布
" V% d. e" ]# A% FDouble logarithmic, 双对数
* M# D1 q$ Z* ]Downward rank, 降秩
3 P8 Y2 ?2 K' {4 J! k2 FDual-space plot, 对偶空间图: M1 Y; a9 L, L
DUD, 无导数方法) C% T: t1 Z& M3 |# E/ T, C
Duncan's new multiple range method, 新复极差法/Duncan新法
. ]& k) k4 L* z7 wEffect, 实验效应
2 p/ x f. [& |0 e1 q$ FEigenvalue, 特征值$ w1 z& r( B: @0 c
Eigenvector, 特征向量
# E8 u! j/ E. G7 e& ^# OEllipse, 椭圆
( G, y" _: X0 P. h' b$ `# sEmpirical distribution, 经验分布4 g7 {7 N2 b3 ?8 ^; k/ W
Empirical probability, 经验概率单位
% b) h: s/ F7 yEnumeration data, 计数资料' p3 A* f# g( O/ k% a* a
Equal sun-class number, 相等次级组含量
6 ~! \' E* b' t/ ZEqually likely, 等可能# Z8 J( t3 l8 }0 ]& X4 y$ q: _0 j" u
Equivariance, 同变性9 c3 X( A n& @, e: l6 v9 K1 {
Error, 误差/错误. @( E' l, S: s$ M2 w% Q
Error of estimate, 估计误差, A: V) ~# P2 Z' T
Error type I, 第一类错误- ?( \. T0 j" G) O9 d! W
Error type II, 第二类错误, \. K2 z/ ]% G# C6 S
Estimand, 被估量
, T* b- |$ ~1 Z& s6 K$ p# z% UEstimated error mean squares, 估计误差均方
4 \# p4 K" J9 {/ R) h- QEstimated error sum of squares, 估计误差平方和' M, g0 H6 T) y* e" D3 w9 ~
Euclidean distance, 欧式距离
* {, N* Q) a$ t* r CEvent, 事件5 L* a: C5 E+ o7 |: o
Event, 事件
6 K& A0 ? ?( D2 q) BExceptional data point, 异常数据点" b0 B* I9 f, C d3 b% V9 [
Expectation plane, 期望平面9 C' X6 Z6 W2 Z5 T; D
Expectation surface, 期望曲面1 Q: Y6 W6 w% v" `6 y# |
Expected values, 期望值( p0 G! Q- R- ]0 k( u% G6 \: p
Experiment, 实验/ h5 @2 @0 @! [
Experimental sampling, 试验抽样; W+ p5 ~8 E% Y5 H9 F# ]5 }# o) ~/ A
Experimental unit, 试验单位4 j$ |0 K6 e1 ]% Z( e
Explanatory variable, 说明变量
0 V! T+ G8 r8 M9 i2 b1 w0 sExploratory data analysis, 探索性数据分析
6 M' o- F6 i. \Explore Summarize, 探索-摘要
6 p! ]3 {) @/ ]4 Z2 J" XExponential curve, 指数曲线5 X* M4 Y' T" S+ ^
Exponential growth, 指数式增长
1 P% [( k9 r; [- V9 m& x" SEXSMOOTH, 指数平滑方法 , V( D( K: M7 ?/ B7 x! Y# o' r
Extended fit, 扩充拟合1 K+ |+ n/ c e' u. W' s
Extra parameter, 附加参数
9 ?* J, n7 d0 l3 v% z" I/ yExtrapolation, 外推法
! T; m- V9 w$ A( C* E O2 g, KExtreme observation, 末端观测值! J* V$ i h. Q4 C# E8 @1 k2 j
Extremes, 极端值/极值
: z7 v/ T: @& n- [& u# |& rF distribution, F分布
* g: [7 v7 c# J V7 s1 DF test, F检验
6 D2 V8 K2 J( O! zFactor, 因素/因子 j; w) v( }5 Q
Factor analysis, 因子分析
3 s, ^1 y7 N/ }8 B/ PFactor Analysis, 因子分析
! Q7 @" Y0 [! S3 E# wFactor score, 因子得分 3 O! m i6 p: w4 m% F
Factorial, 阶乘
: o1 A- R8 Z* w. i- GFactorial design, 析因试验设计
* U/ U( Z5 O6 [! f0 O$ _False negative, 假阴性# m" Z1 ~6 g& x; V9 H2 j
False negative error, 假阴性错误2 l V( \3 j! O# N; W
Family of distributions, 分布族 ?1 G' ~7 k) V
Family of estimators, 估计量族
' d% v" e% |6 _! N$ s f8 |( m( qFanning, 扇面
# Q& B& i& g! P z; h; j: KFatality rate, 病死率$ K- w$ e. }' B; @8 s6 h9 R
Field investigation, 现场调查
$ y+ m: I: s5 k: l& {9 HField survey, 现场调查% c2 X3 Z: u1 U1 b3 m0 q
Finite population, 有限总体2 r; O, M; \6 a8 L
Finite-sample, 有限样本- M9 a$ t& R! z) G9 M) V, ]
First derivative, 一阶导数/ D' T2 }5 c1 Y/ ^+ w0 Z+ H6 b
First principal component, 第一主成分
1 r1 E8 `2 q( t6 P! Q- B+ q( u' RFirst quartile, 第一四分位数; L& p# U$ s* M
Fisher information, 费雪信息量
: {, ~1 q) K+ [, A; c& jFitted value, 拟合值. Y. t0 S6 _$ f, b
Fitting a curve, 曲线拟合
' R* w6 E1 o& T4 k5 m) U) rFixed base, 定基 ^& c4 \: \1 t/ S [/ s, K
Fluctuation, 随机起伏
; n' Q1 \0 [/ N6 l% N3 b/ S& AForecast, 预测: ^4 \4 J$ i1 g8 E, z; o
Four fold table, 四格表
7 R; ^0 Z$ E2 W5 e' {5 U: WFourth, 四分点8 \1 ?- C; R0 } m
Fraction blow, 左侧比率
8 J! q" l0 J, x5 K% A) {$ S( OFractional error, 相对误差 H B/ N. ]( b# b
Frequency, 频率+ v' K* J0 C; P7 U
Frequency polygon, 频数多边图
9 \0 K, e) P! y# b o# ^- ?Frontier point, 界限点
( `- A* Y g0 X4 [' hFunction relationship, 泛函关系
3 X7 w5 ?1 ^7 p; qGamma distribution, 伽玛分布. O7 x9 h) l/ S8 n! r( K
Gauss increment, 高斯增量
& z5 i6 N* F. q. U! \% g# CGaussian distribution, 高斯分布/正态分布" u/ {& \( V7 i" |. u
Gauss-Newton increment, 高斯-牛顿增量
1 \( F/ k* q) |" ^General census, 全面普查
4 K9 m+ j; O% g, cGENLOG (Generalized liner models), 广义线性模型
, }* ~' w7 h2 E9 j8 d; @, UGeometric mean, 几何平均数1 \4 I+ p- r9 e. {5 X
Gini's mean difference, 基尼均差
# j! ~; \* O" XGLM (General liner models), 一般线性模型
( k' S, G- k1 K- B! @: Z# GGoodness of fit, 拟和优度/配合度 b9 c$ N4 x+ |6 C6 M
Gradient of determinant, 行列式的梯度9 D2 q* L3 p7 Z- M: V- P
Graeco-Latin square, 希腊拉丁方
- M' w( Y0 Y1 w, l! iGrand mean, 总均值% b& d& h# K4 h5 P
Gross errors, 重大错误( ^: K: y9 v& L
Gross-error sensitivity, 大错敏感度- d6 o/ W$ ~$ Y8 d$ U* [* j
Group averages, 分组平均/ r! ?. K6 L- k$ {1 I+ d1 ?% B$ y
Grouped data, 分组资料! t2 g% ?1 O% G8 l; p- _5 r
Guessed mean, 假定平均数0 T4 @* F! j' B$ a( K4 `
Half-life, 半衰期
( [7 e4 U I% B2 D% ^, DHampel M-estimators, 汉佩尔M估计量: \" }5 _+ d+ Z a
Happenstance, 偶然事件
( Y5 z/ }. A7 YHarmonic mean, 调和均数
- g1 _% \+ n* a" {# L* K% @Hazard function, 风险均数
0 Z2 b& h9 {9 q7 n% e, j7 JHazard rate, 风险率& \3 y" k3 D/ Y, q
Heading, 标目 2 L' v7 N0 e' P8 B8 s) M# [: C/ D' A
Heavy-tailed distribution, 重尾分布
8 e2 q7 o0 W* o wHessian array, 海森立体阵
4 v* \3 h4 o0 T+ b% n0 {) d! f, b DHeterogeneity, 不同质2 y; N$ W: m% I6 L# Y5 A P
Heterogeneity of variance, 方差不齐 9 v& L0 O7 c V% G$ [- p) l- m) G
Hierarchical classification, 组内分组( x$ u, i$ ~! r. b& d Q E
Hierarchical clustering method, 系统聚类法3 T- O: Z0 r) f+ }, r
High-leverage point, 高杠杆率点
$ b+ K& j; M1 y# m$ ~HILOGLINEAR, 多维列联表的层次对数线性模型
; A; r/ G) U. n% u' A7 C5 RHinge, 折叶点. }5 g: u O+ j! x, N1 k
Histogram, 直方图5 Q! x5 h; X# G) N0 _* A, }
Historical cohort study, 历史性队列研究 3 V' g5 n$ R3 B* t* k2 d g+ m
Holes, 空洞2 ? h1 l: t2 g
HOMALS, 多重响应分析* `3 Q2 |' [$ D. x: n) Y
Homogeneity of variance, 方差齐性
* v5 m$ u3 K- vHomogeneity test, 齐性检验
( r2 K# g% k; _# pHuber M-estimators, 休伯M估计量
+ d: e8 S: W; R- MHyperbola, 双曲线# V" G! L' l- g& N* @# r0 C
Hypothesis testing, 假设检验( J- V. g8 r3 _8 @" L. g
Hypothetical universe, 假设总体' H' X' }7 g: e; p2 a1 r3 f+ @
Impossible event, 不可能事件7 v) n- o. g! p
Independence, 独立性
( Q; o% X; ^5 V" TIndependent variable, 自变量
0 e; d# ?# s0 o& X E! ^Index, 指标/指数 U0 b! z. j% F. A ]* Z2 S
Indirect standardization, 间接标准化法
" k4 Z5 J: e3 i5 I, O f8 _Individual, 个体. ^1 S# z5 l5 B
Inference band, 推断带
/ M% C& f9 A, H; F+ XInfinite population, 无限总体/ J& G; l7 Z* X
Infinitely great, 无穷大& V2 @) }5 F) Y0 P% c% R) `' Z
Infinitely small, 无穷小
: v- U2 d! R4 h' {% oInfluence curve, 影响曲线$ `* w2 Y7 K" z) Y3 K& x* V' G4 G
Information capacity, 信息容量
! S. _6 r; v8 Q+ {, P N) AInitial condition, 初始条件
$ o$ V' p: s& S* KInitial estimate, 初始估计值
4 d& X3 }- C$ X3 d" {# K% \: a, ?Initial level, 最初水平
; ]5 p- E' p' N- e3 D4 |4 o iInteraction, 交互作用2 j; O! a y, s0 i6 B
Interaction terms, 交互作用项& M$ Q' {2 R9 _6 s: J+ Z
Intercept, 截距% S8 I; [8 K2 G! B* w& n+ h
Interpolation, 内插法
% X% b3 g0 o' `1 ^- L3 }1 DInterquartile range, 四分位距
1 v% y& n5 {& z5 pInterval estimation, 区间估计
9 r' w: j( h' q9 @1 JIntervals of equal probability, 等概率区间9 H6 P. M- A1 N' B- ?( q* a* e$ Z3 P
Intrinsic curvature, 固有曲率
1 m+ [. H3 C; q) K: IInvariance, 不变性# S& \ j! ?3 h/ T3 \" C
Inverse matrix, 逆矩阵1 a' v1 C* B1 z8 L
Inverse probability, 逆概率
+ ~2 k+ A! C6 B5 t0 b+ x8 T( ^Inverse sine transformation, 反正弦变换
P, \ P3 r2 `9 M; M6 W" vIteration, 迭代
( ?2 R, H- i5 Y5 }& O& OJacobian determinant, 雅可比行列式
5 X$ g* R P6 ], wJoint distribution function, 分布函数
% y) B7 ]# U' M5 B7 f+ ` p9 A8 ~- uJoint probability, 联合概率6 D1 O4 {; N* G
Joint probability distribution, 联合概率分布
5 p. W- c2 D* K/ X# h1 H0 CK means method, 逐步聚类法
1 _0 K1 D. N0 Y9 U% ?- }6 PKaplan-Meier, 评估事件的时间长度
2 k/ U3 _7 z* @# D3 [( F& jKaplan-Merier chart, Kaplan-Merier图
: I9 k! } q2 P- K: P$ n4 T- tKendall's rank correlation, Kendall等级相关% K0 |7 J0 _' \" L$ I, [
Kinetic, 动力学
3 @1 s/ V% b' ^# O3 ~/ t' F& }Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验1 ]0 y4 j1 H/ t2 H
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
; u4 S( @2 E8 e" N+ @ S/ g- B/ d2 `/ EKurtosis, 峰度
5 C! ?( y5 `9 Y* ALack of fit, 失拟
* t0 g) g3 h! r3 ]. U6 T! a" hLadder of powers, 幂阶梯
) @' e0 l6 H" P+ z' l) z/ W, v$ G/ p+ lLag, 滞后
1 k. Y! o0 o- GLarge sample, 大样本( i: z1 L" V2 C
Large sample test, 大样本检验: L0 ]- f7 X" }* z j2 a/ A
Latin square, 拉丁方
5 ^; d- o# c7 i' e% ]1 ?/ B% x* ELatin square design, 拉丁方设计
: K L- V V/ E4 R8 m v& y- K, Z. WLeakage, 泄漏
4 ] K1 V# o6 ]1 f/ _5 B( \Least favorable configuration, 最不利构形
$ Y: v+ }6 y4 g% ~8 DLeast favorable distribution, 最不利分布
; u- A& O& o: d) NLeast significant difference, 最小显著差法
0 z3 {1 w7 S! |. d- fLeast square method, 最小二乘法
& a7 _ Y- M x' {* d: qLeast-absolute-residuals estimates, 最小绝对残差估计
! s0 O) r$ E. {+ ]2 g& N7 N" Q) KLeast-absolute-residuals fit, 最小绝对残差拟合0 b6 P5 e. w) \& p5 E
Least-absolute-residuals line, 最小绝对残差线$ M0 e( p" g( o: Z" m7 Y# t6 ]( _
Legend, 图例
! b+ y4 b6 U; t, [L-estimator, L估计量$ }$ b; {) m; p/ F6 q5 ?
L-estimator of location, 位置L估计量
N- m- P( ?; } V0 {$ j' SL-estimator of scale, 尺度L估计量
R2 B; K9 {, [8 e+ xLevel, 水平
: B1 w5 o& G% O: XLife expectance, 预期期望寿命2 S( O7 f, S# B. C+ `: n, n
Life table, 寿命表3 C% K3 ?/ b/ Q3 H% l
Life table method, 生命表法
& o/ X c+ n/ Y/ ]% F7 HLight-tailed distribution, 轻尾分布& Q! [. f' p0 T7 y& C
Likelihood function, 似然函数 _) e# w9 V( @6 U7 x
Likelihood ratio, 似然比) q8 C2 b- ?3 n3 J3 v2 D1 @) z, f
line graph, 线图8 L; X$ S) ^% g, _; i. |4 v) U
Linear correlation, 直线相关! F1 S* ~$ f: `6 J
Linear equation, 线性方程' `5 j4 b# S: ]9 k* I
Linear programming, 线性规划# E2 W. e/ h' r2 V0 y# b
Linear regression, 直线回归$ t' k: J# Y) d9 [* q4 w* f0 F
Linear Regression, 线性回归& K& ?1 I$ n5 W/ j3 `) V
Linear trend, 线性趋势3 Z( O" o, T& v8 f8 {
Loading, 载荷 * y! W; D( Y$ C9 x8 l
Location and scale equivariance, 位置尺度同变性4 B9 H2 E) B) G* Q, V; C: j
Location equivariance, 位置同变性
7 u) q( G; L# j* lLocation invariance, 位置不变性
5 }6 A0 a9 b+ w0 w5 q4 `& lLocation scale family, 位置尺度族
. A# S) Z. Z% A: F" ~( WLog rank test, 时序检验 3 a T7 X4 k4 L; l0 n/ P. S
Logarithmic curve, 对数曲线" O W1 {* D2 v6 j& R- [
Logarithmic normal distribution, 对数正态分布
1 I7 D) ]9 s) n- RLogarithmic scale, 对数尺度
, F; X7 H. p$ c( _6 ^Logarithmic transformation, 对数变换2 O6 }* ?* h: q: k& ?7 L$ I
Logic check, 逻辑检查
* p: z H; S5 j: k O+ WLogistic distribution, 逻辑斯特分布1 V4 l& H8 |, \, e- i {
Logit transformation, Logit转换1 B8 n- p: g) W" C5 i1 G" s
LOGLINEAR, 多维列联表通用模型 + j+ o) C& M/ h7 X$ V: m
Lognormal distribution, 对数正态分布
+ F- ?2 p: m0 B. Z8 NLost function, 损失函数( r* n/ g6 s h: M, s
Low correlation, 低度相关3 i6 P* ?+ O" q6 X
Lower limit, 下限
3 f: L+ l0 K* J* t( X# ?Lowest-attained variance, 最小可达方差
$ |0 R; X, E5 |& X! S' LLSD, 最小显著差法的简称
! k. V/ A3 m! n+ zLurking variable, 潜在变量
7 s* J- H5 f0 y" [' FMain effect, 主效应$ l2 l6 k5 Y u6 w$ g
Major heading, 主辞标目9 z. P5 Q! @1 z( q. l2 N& _
Marginal density function, 边缘密度函数
$ O2 f2 {) Y9 zMarginal probability, 边缘概率) E7 N' P9 Q V# n, }
Marginal probability distribution, 边缘概率分布; H9 A# |; t9 e' G. r, G1 f
Matched data, 配对资料
* I! `7 e. |! g4 i. N( BMatched distribution, 匹配过分布; _6 c: {, S& d- U7 i. ^
Matching of distribution, 分布的匹配
3 w: D; R) H% p9 |% P$ lMatching of transformation, 变换的匹配1 I' R0 Z. P0 z( C
Mathematical expectation, 数学期望
% Z9 g) Q" q" uMathematical model, 数学模型
' n: }, }: _+ T3 J! G7 kMaximum L-estimator, 极大极小L 估计量+ Q, K9 c( E# M" q8 b7 ^- F! q
Maximum likelihood method, 最大似然法6 K5 t9 s+ T0 B; E; k( t$ u5 ]4 u
Mean, 均数
, o+ \ c( v' j5 I& VMean squares between groups, 组间均方; B ?8 L" C. _1 A, ^* z: c
Mean squares within group, 组内均方
: ~! M& e" W& aMeans (Compare means), 均值-均值比较4 u' k6 t, S) g; E! A6 g
Median, 中位数
8 M( c; r* b% C: BMedian effective dose, 半数效量
5 H: V" G, g! y) F4 ]Median lethal dose, 半数致死量
. Z3 T& ?* ?( Z. [* oMedian polish, 中位数平滑
/ @# k7 s$ `0 yMedian test, 中位数检验
9 O- V. h2 N. e8 W& f0 U- _5 fMinimal sufficient statistic, 最小充分统计量
: K* b. U/ f" E8 HMinimum distance estimation, 最小距离估计# _; H; K/ Y6 R8 N1 \% V |2 K* e
Minimum effective dose, 最小有效量
$ s7 R% O* |, W+ H2 HMinimum lethal dose, 最小致死量; L8 f/ |2 D" T# z9 q
Minimum variance estimator, 最小方差估计量1 S9 H/ l7 J2 ^8 w
MINITAB, 统计软件包
+ s4 \% E5 K, f5 N: H) L4 T0 ~* `" MMinor heading, 宾词标目
8 a6 u3 J6 t+ o# ?6 E- zMissing data, 缺失值! Y2 N& [( Q: C/ o% `
Model specification, 模型的确定
$ ^1 n! {& T( J% [0 C) `Modeling Statistics , 模型统计
4 u- I, o% j3 \+ ?/ B& |Models for outliers, 离群值模型
: l1 R% q7 r* p, GModifying the model, 模型的修正3 }! v1 s$ M1 @
Modulus of continuity, 连续性模
* V. @/ C' y ^: {' k" Q' e7 gMorbidity, 发病率 5 S5 s, v2 Z' B
Most favorable configuration, 最有利构形
% f1 t, |( [ E$ B- Z9 {; JMultidimensional Scaling (ASCAL), 多维尺度/多维标度
+ n$ e- @ V* m: \2 }' RMultinomial Logistic Regression , 多项逻辑斯蒂回归
. z& E: b: f fMultiple comparison, 多重比较% b/ \! Z' K B, x3 V4 A. z
Multiple correlation , 复相关
) W/ k% A$ x" h9 l# iMultiple covariance, 多元协方差) A: |3 ]; D1 V$ l! V# o% ]4 O
Multiple linear regression, 多元线性回归
5 y5 m5 ?: P) s% f0 c4 p* y! VMultiple response , 多重选项$ u' A; [! q" P4 A
Multiple solutions, 多解 N( {6 G0 @, r) F5 W6 k
Multiplication theorem, 乘法定理( O' x: r0 L9 |+ F5 C. [1 |
Multiresponse, 多元响应
( h/ C S* u8 o' {. X8 x7 X# QMulti-stage sampling, 多阶段抽样
8 j7 u1 A ]0 b$ w& CMultivariate T distribution, 多元T分布3 q8 E) d" `. z6 A' o
Mutual exclusive, 互不相容
2 O. Y1 H3 O. ]Mutual independence, 互相独立
- T. A: W5 F+ J4 l: x' ~* c+ _3 lNatural boundary, 自然边界, i) n4 h' i) N3 I8 R
Natural dead, 自然死亡
; h( D% M* A( D) |Natural zero, 自然零7 h: d9 H" B" D9 h4 v
Negative correlation, 负相关( S# B7 l7 g& P* i; X, d* T
Negative linear correlation, 负线性相关% L! |! A& P; Q! f
Negatively skewed, 负偏
; z6 N5 ~" s! w* v4 gNewman-Keuls method, q检验
) @/ G$ a9 ? G9 |% INK method, q检验* G" w" |. ]3 F: F+ v- w
No statistical significance, 无统计意义
: |8 K$ M* I5 x! z7 N4 i) T B0 vNominal variable, 名义变量+ |* n+ j' w: u+ i6 v9 `
Nonconstancy of variability, 变异的非定常性
j9 s; `/ d' |+ @5 I7 j7 T* sNonlinear regression, 非线性相关
$ F' `, l% M: I( a( k9 w) g FNonparametric statistics, 非参数统计 c3 ?" f4 M U$ ~( T5 b
Nonparametric test, 非参数检验
+ @6 M6 c/ ^6 X' r8 o2 q6 wNonparametric tests, 非参数检验6 ^& c$ R* V+ i$ D- T$ E) _1 f
Normal deviate, 正态离差0 M3 y1 Y% \6 [9 Q: d
Normal distribution, 正态分布/ N4 u& p/ F, ~% T( K z2 |( r. }% w
Normal equation, 正规方程组
8 I( S0 u$ n5 x, ~9 ]5 `Normal ranges, 正常范围
7 p' s6 a% _9 b- }Normal value, 正常值7 w2 A5 H" M% t! L( k
Nuisance parameter, 多余参数/讨厌参数4 Q% T: Q( s; k# h9 F& d
Null hypothesis, 无效假设
% e* U- ^) l+ K. J6 r+ ANumerical variable, 数值变量
+ @$ R+ E# A9 aObjective function, 目标函数$ {$ h2 F! \5 @) ]0 e- Z* I6 I. {9 U; C3 y
Observation unit, 观察单位
' N" @/ @* V+ A0 sObserved value, 观察值 F! g+ f& z% ~% [+ |
One sided test, 单侧检验
) p' J o4 \7 f4 A6 ~; I2 aOne-way analysis of variance, 单因素方差分析
0 ?/ N, o0 B, o( q( dOneway ANOVA , 单因素方差分析
1 E7 l9 y$ j- \Open sequential trial, 开放型序贯设计2 ]- q! G# z" w# M7 i
Optrim, 优切尾& r; {9 s. A( K, V' X: ]& }
Optrim efficiency, 优切尾效率2 B, y; I Y6 ~, X3 y' U
Order statistics, 顺序统计量& e* W! P& ^% {6 z" [
Ordered categories, 有序分类
3 K* b) D, `) X; G% }Ordinal logistic regression , 序数逻辑斯蒂回归
) b" g$ [! c5 j. V+ @2 HOrdinal variable, 有序变量) T# `$ x D B" R- p
Orthogonal basis, 正交基( g, j3 x" X. q( q! R
Orthogonal design, 正交试验设计8 _3 u0 h" l6 ?/ K* h: f/ k/ R
Orthogonality conditions, 正交条件0 ~$ t( ~% c0 R7 e; N* [
ORTHOPLAN, 正交设计 4 t) h: \$ s+ n- X' Y- P
Outlier cutoffs, 离群值截断点
! g" R+ n% `0 H' Z" Q3 R$ | hOutliers, 极端值. G" m; f5 K. C, C
OVERALS , 多组变量的非线性正规相关 $ d( F0 c7 B: |; E+ t
Overshoot, 迭代过度* o ]( {7 y& a6 i A
Paired design, 配对设计
1 x9 l) V; K& D( `( W' K4 B; ^Paired sample, 配对样本- I5 c2 d4 W: ]1 B, l' t
Pairwise slopes, 成对斜率% e% q1 W0 b$ f1 v7 o
Parabola, 抛物线& r2 e; [, @( I$ Q y3 ]
Parallel tests, 平行试验% [8 |5 V/ N% _, r4 Z& e& U$ _
Parameter, 参数
: Z- l& P4 k2 A4 `/ R; o6 z+ fParametric statistics, 参数统计
# v s7 l; d8 q4 P4 `! G0 }Parametric test, 参数检验
6 ?# w/ v6 _/ g) NPartial correlation, 偏相关" L* o- `1 h ] Y& e9 G6 \
Partial regression, 偏回归
% `* g U7 k! ]' bPartial sorting, 偏排序
2 }- E1 V% S+ |( k* {Partials residuals, 偏残差. y7 y2 k4 A) D* Z2 P& U. S0 {# h
Pattern, 模式
- r7 x3 S. X- k" dPearson curves, 皮尔逊曲线
; ]7 p1 }' C7 W {/ E0 c, t `3 X5 ^Peeling, 退层
7 _6 o$ S' x1 K1 ~, c4 T# N: ?! v/ APercent bar graph, 百分条形图
5 q+ K H- {* Q a: cPercentage, 百分比
6 a e& n; F$ Y2 K, L4 \Percentile, 百分位数: |. G' G+ Z9 @5 L2 E: L S) K
Percentile curves, 百分位曲线
% M. y+ M5 }3 OPeriodicity, 周期性
% P) d2 G( o ~0 X- ^5 XPermutation, 排列
" ~: I- x& R0 _" U& CP-estimator, P估计量* E9 C x( }- M$ n4 J t, @7 ~- x
Pie graph, 饼图' Q6 Y- `! H2 y3 E( y
Pitman estimator, 皮特曼估计量1 c9 @' r7 z8 h( S8 e0 y( O9 P" ~
Pivot, 枢轴量
% i2 x( T' Z' x" SPlanar, 平坦1 m& R7 L* w& E* O
Planar assumption, 平面的假设
1 N- _1 \0 w! r/ l) K1 v$ M1 S& ZPLANCARDS, 生成试验的计划卡
, @* J: I6 L0 @, T, A3 SPoint estimation, 点估计. u, d+ O* G* Z% H Q T6 J7 c
Poisson distribution, 泊松分布+ S+ i( t8 S8 Y* W4 g# k
Polishing, 平滑$ D' Z- _7 }$ |$ g
Polled standard deviation, 合并标准差
4 Q% r n0 x. [% M) ?6 s1 Y; H6 OPolled variance, 合并方差
# x+ |. v" g5 CPolygon, 多边图
9 p5 O$ Z# Y; q$ F. h+ k4 xPolynomial, 多项式
4 j/ w4 Y/ @* d( g: @5 G4 A- rPolynomial curve, 多项式曲线% _4 q- Y( o& B6 L) Y5 y
Population, 总体* Q* ~, R5 n. y) D& v* L
Population attributable risk, 人群归因危险度
0 W9 O6 D. B8 t+ O P: cPositive correlation, 正相关0 X# O3 b. M/ Z& ?( v
Positively skewed, 正偏
/ q) J5 H, L( }2 ?! H& `Posterior distribution, 后验分布
. ~/ j! J, e. gPower of a test, 检验效能9 @5 H1 h, j7 |) x
Precision, 精密度# X% X& X; o% ], s6 t4 r
Predicted value, 预测值3 M# Y' T9 U8 r5 k. f& ~) l7 n9 G" \4 R
Preliminary analysis, 预备性分析1 z8 X% U5 |% q; q3 s4 n( G
Principal component analysis, 主成分分析
5 E x, E8 a6 D L/ BPrior distribution, 先验分布( E" s- A8 f" n$ ]$ p' G. g
Prior probability, 先验概率( ?0 w1 F$ t; [1 n! l/ }. g0 \0 u
Probabilistic model, 概率模型2 ?* X7 _; E4 W- `3 E* \5 s
probability, 概率
) L. [& o1 a* M& p4 c oProbability density, 概率密度
) E% j' Y; f% N5 K! GProduct moment, 乘积矩/协方差/ \; n U' i% p0 q, Y: I
Profile trace, 截面迹图
9 s3 Q. d- V7 zProportion, 比/构成比* `/ R/ {1 k) y+ w
Proportion allocation in stratified random sampling, 按比例分层随机抽样
2 V+ V" @- x zProportionate, 成比例0 |3 F1 X* \" E: ~# |8 z9 e! k
Proportionate sub-class numbers, 成比例次级组含量
& x$ B' A! i$ U4 c7 H, ^; {Prospective study, 前瞻性调查2 u2 q7 c9 w' C5 I! t4 B5 h
Proximities, 亲近性
4 N5 \& r! C3 E& x* ]Pseudo F test, 近似F检验
4 j1 W. K6 G; _2 O# APseudo model, 近似模型
: A& f$ y( H, ~0 u8 b4 qPseudosigma, 伪标准差6 E+ s8 p9 a, d0 n+ {1 L! X1 |- d( ~
Purposive sampling, 有目的抽样
+ {/ B3 I* n9 X# GQR decomposition, QR分解3 B' C6 q3 u! p1 E
Quadratic approximation, 二次近似& {+ V5 p7 o, i5 D2 \' g, S' p$ J# h
Qualitative classification, 属性分类
3 T) R8 F! g( `+ J% nQualitative method, 定性方法
" I0 J, | \' l8 JQuantile-quantile plot, 分位数-分位数图/Q-Q图! m3 W! n; v5 [. Q$ Y% J
Quantitative analysis, 定量分析
b R) Y& [- f7 Z2 ^& w6 n# NQuartile, 四分位数+ ]6 B& F7 G2 p
Quick Cluster, 快速聚类# N; U# F8 J2 k2 W; c
Radix sort, 基数排序
* e n# y% Q/ HRandom allocation, 随机化分组
J4 x# A& F4 \( ?$ V( Y$ Z3 [Random blocks design, 随机区组设计
C: `& @$ K) pRandom event, 随机事件- n1 C% T& d4 j/ |8 D6 r S/ F. D
Randomization, 随机化2 t0 n9 \: p. B! W. ^" I( S; r
Range, 极差/全距
* ?5 k( n, |8 _; x& SRank correlation, 等级相关7 X7 n2 e, C' o( g2 B2 r
Rank sum test, 秩和检验
- Z9 W8 ~2 d+ N# J9 V, rRank test, 秩检验
5 _+ l8 h! l, z$ I2 pRanked data, 等级资料: p0 V: Q1 X- e
Rate, 比率
: T+ |& H/ c. f ]/ j+ KRatio, 比例
' O0 o @/ o. u9 ZRaw data, 原始资料
e5 ]8 N7 B8 ERaw residual, 原始残差
9 l7 P3 M7 e+ ~/ |Rayleigh's test, 雷氏检验* ]! j, p& e3 d' A, U
Rayleigh's Z, 雷氏Z值
2 e0 S) ?7 Y1 A/ N7 a1 |Reciprocal, 倒数
1 v" k% F& d' l5 c5 l0 e6 JReciprocal transformation, 倒数变换) @8 q" |# D4 B
Recording, 记录 @7 F. e8 w/ O H
Redescending estimators, 回降估计量2 z/ ?4 e: D$ R2 Y& N) n
Reducing dimensions, 降维
) ?" U/ F4 M4 @0 f' I/ y2 x' h' k, fRe-expression, 重新表达9 M3 B! J! b$ [. e: ^
Reference set, 标准组
0 n! O" Y& D: J0 R9 z9 Z/ |& fRegion of acceptance, 接受域
* ~) ^' j) u% |- o& eRegression coefficient, 回归系数
5 [/ h% b6 K3 X# V' H- e% V, hRegression sum of square, 回归平方和
; ~& o5 W& x" ~/ nRejection point, 拒绝点) T- P2 M+ l [# u4 E3 b
Relative dispersion, 相对离散度
3 q- z' }% S# L2 ^) ZRelative number, 相对数+ {( K$ w H9 H& H6 z+ z) R1 d
Reliability, 可靠性
. [( A+ v% {1 Z& w9 wReparametrization, 重新设置参数
2 I; j# q- |2 J1 dReplication, 重复
: a+ m6 a9 G5 V, g. ~* SReport Summaries, 报告摘要- `, O( l: ?$ l& f* V v: h
Residual sum of square, 剩余平方和
: w8 y: v: `, }& U# F2 Z: RResistance, 耐抗性
6 R4 f, r5 m- |% [/ t# Q) h! ]* wResistant line, 耐抗线, C- L; J- K l7 E1 s D! \8 A
Resistant technique, 耐抗技术
* y4 w. c+ c# z9 o5 Q# UR-estimator of location, 位置R估计量
/ z6 A0 H9 f+ k: _R-estimator of scale, 尺度R估计量
6 H( G, M* @) a6 {1 Z' GRetrospective study, 回顾性调查3 f+ r% d$ G5 p! m
Ridge trace, 岭迹
( e/ g% O( `+ Y* k* I+ b$ q* TRidit analysis, Ridit分析/ N5 _* L+ U# ^7 J2 ]# o4 E4 s
Rotation, 旋转
- G( x, Q7 D: w' s. U/ H- n8 kRounding, 舍入
) {% u$ b r0 Q+ Y) c: ?. GRow, 行1 E5 K0 I% o* r4 X: \! v" m) e: q
Row effects, 行效应
8 p9 m0 o/ q8 n' kRow factor, 行因素4 [, ]5 |/ g. W3 p9 p
RXC table, RXC表
; B, A" X& v" w, a. k6 O, vSample, 样本
& s5 N$ _( b" lSample regression coefficient, 样本回归系数
% R8 V+ g/ o+ f1 tSample size, 样本量
3 n8 ]/ D4 K. k: j3 @3 q; R4 t* p' p* vSample standard deviation, 样本标准差9 ~. T9 |! @; q" P
Sampling error, 抽样误差
. V% T% \/ ]. N+ \% f( b2 E+ KSAS(Statistical analysis system ), SAS统计软件包: H0 U+ b- Q) P2 U0 v$ }# I9 m
Scale, 尺度/量表3 n% k8 T3 Q! R: ]5 Z) Q
Scatter diagram, 散点图
0 S! l) u3 V/ N) n! RSchematic plot, 示意图/简图1 k5 W! q8 V a2 Q
Score test, 计分检验6 H- X; P! E: P/ A- O; ?0 g
Screening, 筛检
& R* p8 ]5 T# P/ P6 |SEASON, 季节分析
$ i% O5 k S* b3 K( Z8 TSecond derivative, 二阶导数# x6 C# F3 L+ W( F" ~" K
Second principal component, 第二主成分* ]2 z7 ~/ l+ }8 O6 o) l) n* F
SEM (Structural equation modeling), 结构化方程模型
2 \5 N; J1 ~4 f- NSemi-logarithmic graph, 半对数图
; T7 t' d0 v" r& _Semi-logarithmic paper, 半对数格纸
! K3 k+ S7 A* w# l" f3 N' p. c) i6 JSensitivity curve, 敏感度曲线
" U" i& n5 V+ ]& B* V4 tSequential analysis, 贯序分析2 |% f) T$ v1 r3 _
Sequential data set, 顺序数据集
8 d2 @8 J9 B o8 hSequential design, 贯序设计! r2 L8 I) P: _9 M! B# C5 W& W
Sequential method, 贯序法- V1 K* y7 x: a
Sequential test, 贯序检验法
( z4 J0 ~- E; h# b7 FSerial tests, 系列试验) y1 O% m3 N, J4 n6 C0 p
Short-cut method, 简捷法
6 t6 Y7 i- O* e" `+ }* Q2 @Sigmoid curve, S形曲线
& K9 j+ I. _& w9 VSign function, 正负号函数
. Q+ P; o6 h' u( j+ M5 {, TSign test, 符号检验
8 q" B5 j8 j( @# \& KSigned rank, 符号秩
1 N3 l6 s: y# Z' ]& u9 OSignificance test, 显著性检验+ q2 t+ V0 B7 l4 O( T( i. Z8 k. [
Significant figure, 有效数字9 r+ x" R# f, J9 ]) r. i5 P+ ]$ a
Simple cluster sampling, 简单整群抽样* O" u% C. Q; _$ A: a% D
Simple correlation, 简单相关7 K1 L" Y. g3 ^+ |9 ]1 p1 z$ m
Simple random sampling, 简单随机抽样
0 x; }8 W, j0 W) a$ {/ ]- ]Simple regression, 简单回归
h2 j% Y+ k9 H. p: H* S: Hsimple table, 简单表% B! a" M% l2 H) J& P2 f& _9 W2 \9 B
Sine estimator, 正弦估计量3 a" Q. v0 h8 ~8 x% W3 L9 \7 @
Single-valued estimate, 单值估计" a+ Q: x. M7 w$ g/ }; N
Singular matrix, 奇异矩阵
& o- E* g2 n5 \- PSkewed distribution, 偏斜分布
9 h5 t: h1 e+ |4 l! ASkewness, 偏度
$ i' E% V; f6 Z. l9 ?, {% F# PSlash distribution, 斜线分布1 ]3 ?( r: d9 N
Slope, 斜率
5 l9 d( J0 Q) t- pSmirnov test, 斯米尔诺夫检验7 j: I/ r/ O9 V8 t& S
Source of variation, 变异来源
8 M9 H5 V+ V- |Spearman rank correlation, 斯皮尔曼等级相关, p+ T1 \0 w) a2 x6 I2 A1 g( H
Specific factor, 特殊因子
" f8 z8 R* \' s. M$ }* lSpecific factor variance, 特殊因子方差
6 n6 G7 I6 Q2 nSpectra , 频谱. c* i0 Q- N# F/ O
Spherical distribution, 球型正态分布
E6 Q8 Y/ W, c. N9 ^- @+ h/ mSpread, 展布8 H2 [5 o ?5 K H- A! B
SPSS(Statistical package for the social science), SPSS统计软件包' h+ W+ y" k1 q
Spurious correlation, 假性相关! U' Q# p' l0 I6 @+ M& ~: d
Square root transformation, 平方根变换' y. t) i% w4 t' w$ d/ L. W
Stabilizing variance, 稳定方差
3 K% _; X$ N+ E2 l! E7 b/ ]4 J1 k& UStandard deviation, 标准差
* w/ P q( a' O+ b1 BStandard error, 标准误0 \7 ?1 D" U( C4 t6 `
Standard error of difference, 差别的标准误
- L5 N: N; Q5 \% O( gStandard error of estimate, 标准估计误差1 y. m3 {. `" X( ]1 d
Standard error of rate, 率的标准误
- E& I# P- g6 X! w8 zStandard normal distribution, 标准正态分布( ]8 F( P2 e: Z
Standardization, 标准化4 Y8 ]7 {5 ?$ t6 i
Starting value, 起始值
. e) i; c6 c; c0 r8 pStatistic, 统计量
) Q2 Y% x/ X$ ^" Q- hStatistical control, 统计控制' Q0 O8 Q6 h+ z* e% ?7 x
Statistical graph, 统计图: D9 s# s! l( a
Statistical inference, 统计推断0 r: p% O2 Q( C5 H* D. G
Statistical table, 统计表
2 m- V# r' A$ j9 DSteepest descent, 最速下降法
C/ f8 E& b1 F: ^6 |Stem and leaf display, 茎叶图: W. b( j( |9 e% J# g" E
Step factor, 步长因子
" a# o3 n4 g" R3 DStepwise regression, 逐步回归
; G" L" [2 H8 pStorage, 存
; |1 o8 ~, c" X# ~9 ?3 \( Z% NStrata, 层（复数）
( ^+ O- E& j& J7 B) A3 tStratified sampling, 分层抽样
; H" l1 q; l) Y4 Y9 R' G) U9 Q2 R+ QStratified sampling, 分层抽样, p8 ^. X8 Z( J" K) h" n9 o+ y
Strength, 强度
4 b. s' V0 S- T$ `. NStringency, 严密性* c/ [' \0 ]" A
Structural relationship, 结构关系0 ^+ t) u# [/ }9 H' b
Studentized residual, 学生化残差/t化残差
- t, u' c7 A8 G' H6 J* OSub-class numbers, 次级组含量
0 t4 }8 B: E. l, `, o) ^: KSubdividing, 分割1 o2 y' Z; [7 H- d& q3 t
Sufficient statistic, 充分统计量
; i) ?, a2 R- }+ q( M, ^8 F" TSum of products, 积和$ S& T4 R7 c9 Q7 I4 |8 f# s
Sum of squares, 离差平方和4 [( j& L1 F3 i! @ B( [2 {
Sum of squares about regression, 回归平方和8 v0 R1 b% N" F- G2 w4 ?9 d
Sum of squares between groups, 组间平方和4 g; @8 y, o1 I% i, i3 i+ I
Sum of squares of partial regression, 偏回归平方和* O" b9 N p! n+ K8 l+ L6 b
Sure event, 必然事件
E, L/ v/ {9 \8 ^+ z, F) h; r. ^Survey, 调查# |" Z8 S# k) f
Survival, 生存分析
" C& A- b+ r; s3 v' @, RSurvival rate, 生存率1 j$ T9 t& I) g3 U* V
Suspended root gram, 悬吊根图& j+ V S; j7 s' z, t/ s- A
Symmetry, 对称( y! T) f* r" _& X/ [" M7 f: q$ x
Systematic error, 系统误差1 V: m- \3 G0 _* |
Systematic sampling, 系统抽样
$ A' ~8 Z% ?/ U9 ?7 i7 X* _" fTags, 标签$ q; e) [5 L: i% ^2 \, g1 I
Tail area, 尾部面积
1 J+ @" k' h6 y8 S+ q; i0 T6 U4 D2 hTail length, 尾长
' G0 M2 x* }* U# T$ qTail weight, 尾重9 M* U/ a' W: m, L. ^9 H- U
Tangent line, 切线
9 ]* K8 ^: f, OTarget distribution, 目标分布0 I, W" l2 o7 B1 r: H
Taylor series, 泰勒级数$ s' A- A L e- O' M3 I5 `
Tendency of dispersion, 离散趋势5 W* r* C: \6 c2 C2 I
Testing of hypotheses, 假设检验3 L+ D/ N0 u' D; c
Theoretical frequency, 理论频数4 @: Z' B6 L5 x \0 ~7 A' d
Time series, 时间序列$ C( |, F0 v( \& S$ \5 {
Tolerance interval, 容忍区间9 O7 E8 Y8 }* k# W
Tolerance lower limit, 容忍下限2 q* W) U$ \4 g7 N/ s# D
Tolerance upper limit, 容忍上限
- x5 U' B4 O. R" r8 S2 d8 KTorsion, 扰率8 ?/ z. T% \3 a" C; B* _
Total sum of square, 总平方和' i. A) ], K) C& m1 I
Total variation, 总变异* I5 V b3 B0 W1 x) c/ K* Q
Transformation, 转换" ^; Z6 r! Q1 t, ~* Q% w
Treatment, 处理# W( s" f3 S& s) W
Trend, 趋势% ^5 V0 d- n2 m* ^. n+ u* F
Trend of percentage, 百分比趋势
. x/ M5 _+ I* q/ y, d0 BTrial, 试验1 ~/ A4 B/ f" I: }4 f/ X
Trial and error method, 试错法
, A) E) z$ M% l# `3 KTuning constant, 细调常数
" _0 i/ G! q E' TTwo sided test, 双向检验0 N- r' e, J% j0 S; y
Two-stage least squares, 二阶最小平方- R* S" I' c( `) U" K, O9 g0 a+ N
Two-stage sampling, 二阶段抽样
1 u: H/ @# ]% A9 o7 B7 I& i( bTwo-tailed test, 双侧检验4 f5 @' ~* \- Y3 {; U
Two-way analysis of variance, 双因素方差分析/ w, i. M% d* G" ^/ y8 _
Two-way table, 双向表/ g" @: s: _$ m/ D8 O4 y
Type I error, 一类错误/α错误! Z! H! w- `5 e4 p" ]( k; ~
Type II error, 二类错误/β错误
r3 c. ]. g8 c& LUMVU, 方差一致最小无偏估计简称
2 u) B) ] Z7 N+ x) lUnbiased estimate, 无偏估计0 _ z. a$ P6 d/ ]! w. o. N( Y
Unconstrained nonlinear regression , 无约束非线性回归" S7 j6 j2 K5 u1 t. k. g# f4 H
Unequal subclass number, 不等次级组含量
# y4 A- S k& e3 I- G" ]/ QUngrouped data, 不分组资料8 z4 ?% ^% \5 o1 L4 Z! e
Uniform coordinate, 均匀坐标 [! |4 c `6 D* C. p7 Z
Uniform distribution, 均匀分布! k" V" t) g0 s2 E/ H
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计6 |3 z" v2 T" G
Unit, 单元, [. ]3 }' a. W
Unordered categories, 无序分类9 [5 C7 i# t9 c* ^, O
Upper limit, 上限2 ]) C5 Q: w& B0 n% U, t6 v/ j
Upward rank, 升秩; y$ a! o3 |* `
Vague concept, 模糊概念
* }% p1 c- {$ d3 `& rValidity, 有效性
2 @" Y7 x8 N5 L% f: I" z7 CVARCOMP (Variance component estimation), 方差元素估计
' p8 |6 N8 u3 t5 b! o8 |2 o) uVariability, 变异性
7 J+ `/ K& Z+ f: M& e5 \Variable, 变量
! x* t& R- j! X/ s/ \Variance, 方差
' B& b4 j6 n& `! n. `/ rVariation, 变异 Z9 R$ ^, t) w J
Varimax orthogonal rotation, 方差最大正交旋转
1 i+ U$ F7 N! U4 w8 tVolume of distribution, 容积5 N/ c3 H: I+ A( L- G( i
W test, W检验
6 h, f3 c$ o/ q9 p% @0 B; XWeibull distribution, 威布尔分布. `! q* s4 i& |) x$ a' k' J
Weight, 权数2 V2 H1 C* B/ t8 d4 O. w
Weighted Chi-square test, 加权卡方检验/Cochran检验
! J) N- Q( W0 T0 h2 T2 R& }* UWeighted linear regression method, 加权直线回归
' l" j0 {+ D$ }1 n1 Y8 b. w+ \Weighted mean, 加权平均数' a6 X D% Y6 r$ I
Weighted mean square, 加权平均方差. B* \* w! D0 J x9 r, i
Weighted sum of square, 加权平方和$ r6 c( {' [, U* _
Weighting coefficient, 权重系数
1 y+ a+ Z0 Y5 o* J0 l! T0 [Weighting method, 加权法 ( R% K; n7 ~6 J9 }' L Q0 c
W-estimation, W估计量* W: Y: Q( L0 { z$ Y+ Z& ~7 Q
W-estimation of location, 位置W估计量4 x5 i) \) O- a- k9 S0 m' f
Width, 宽度
! U$ V5 Q' |* L2 }; pWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
$ _7 |3 t7 j$ Y, d" t" |Wild point, 野点/狂点" O8 ~$ ^' s4 S7 N( o& R
Wild value, 野值/狂值2 X I1 D: |6 G* {
Winsorized mean, 缩尾均值
3 E, E3 Y( z' m$ l0 g; ~5 u! \Withdraw, 失访
' ], ^# m4 G/ D* d- pYouden's index, 尤登指数 D" d# N: i0 j( m
Z test, Z检验+ m; U% v" F+ C
Zero correlation, 零相关( X: c6 I# t) a; }2 S1 X7 C
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
