|
|
Absolute deviation, 绝对离差
4 M$ r9 i: o; l$ X/ xAbsolute number, 绝对数
& Q5 P% Y5 e% w1 a/ bAbsolute residuals, 绝对残差
) _, u+ B4 i# M* W1 WAcceleration array, 加速度立体阵6 U: O7 M/ l6 N! ~6 y
Acceleration in an arbitrary direction, 任意方向上的加速度2 a- o- j; K# C- e( I& w, X
Acceleration normal, 法向加速度) t& h7 U: {: r9 {
Acceleration space dimension, 加速度空间的维数9 K# ^/ s# e+ l0 b1 F. m* Z
Acceleration tangential, 切向加速度+ S3 i' d7 B5 c. W8 J
Acceleration vector, 加速度向量" d/ _, F9 E3 R0 @, X' o- s
Acceptable hypothesis, 可接受假设' o P+ v- Z6 F. D# f4 [
Accumulation, 累积
5 U% ~/ w' L7 @4 E OAccuracy, 准确度
' s f) I) n2 y4 TActual frequency, 实际频数
3 n ^5 x9 `$ _1 A, X7 @4 UAdaptive estimator, 自适应估计量
2 e% Z6 s7 _' Q% S, IAddition, 相加
" \% J$ U4 v1 G* S: _Addition theorem, 加法定理
( X. B ` O& C' E$ q* K2 b4 \Additivity, 可加性
8 y( E% w2 J3 l1 Q. g+ [Adjusted rate, 调整率) y' _7 @# p5 ^& Q9 p `- m
Adjusted value, 校正值 e5 i* P8 t I
Admissible error, 容许误差
$ R& e4 S/ @! f9 Q1 |3 e6 n7 SAggregation, 聚集性% P8 X7 q3 a" \6 }7 ~2 h
Alternative hypothesis, 备择假设
# x5 e% H1 G8 I* Q, mAmong groups, 组间: E; w+ Q* y# E9 z. K
Amounts, 总量/ Z5 [1 A" R' ]2 \
Analysis of correlation, 相关分析) o' a9 e5 _ z# U3 _- a
Analysis of covariance, 协方差分析9 U' V% t, g. n3 j1 J
Analysis of regression, 回归分析
1 E- |, H* Z; F8 z* H7 ^9 ~Analysis of time series, 时间序列分析- ?, E, k1 _7 X3 b, b# T% O3 \( u6 y
Analysis of variance, 方差分析
9 O8 n+ X5 _, @5 t! l/ DAngular transformation, 角转换
, ~/ d8 h# }6 Z$ A! b' LANOVA (analysis of variance), 方差分析
; C/ ^* k# L5 C. [" _( MANOVA Models, 方差分析模型* Z9 n) i& M$ Z- |
Arcing, 弧/弧旋 H8 |2 g6 J" N1 m+ s/ @& z
Arcsine transformation, 反正弦变换
& k5 h4 ^7 U3 L E: u9 YArea under the curve, 曲线面积
4 f% y# L% B% y6 O ^( D3 BAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ! o( I# L, b% Q. q2 A
ARIMA, 季节和非季节性单变量模型的极大似然估计
: G% N% J/ ], h, Z3 {* w8 j4 `Arithmetic grid paper, 算术格纸
+ [& I0 c" f( T2 J, qArithmetic mean, 算术平均数4 N" S3 t6 g0 X% N. z* q
Arrhenius relation, 艾恩尼斯关系9 N/ u9 A2 H# S' D) C" Z% @
Assessing fit, 拟合的评估
: ]# T& W% l9 R: U7 OAssociative laws, 结合律3 l& g% w0 a( I- w
Asymmetric distribution, 非对称分布) S0 c X. x9 l0 S
Asymptotic bias, 渐近偏倚
) X- P2 u7 ?- T- Z/ mAsymptotic efficiency, 渐近效率4 ?- Z# C# x* G# A, j- @) s/ d
Asymptotic variance, 渐近方差
- I6 P( ]) N+ x; w: f% jAttributable risk, 归因危险度
9 m7 K/ \* w8 q) O3 RAttribute data, 属性资料3 }, W: E" B4 e! q& B# F5 }4 R+ c% G- Q
Attribution, 属性
; R7 B) j8 X9 Y, kAutocorrelation, 自相关+ `- [1 I/ w; y5 N( T
Autocorrelation of residuals, 残差的自相关* E$ X, C8 q# w! f6 z$ C6 r; z+ ^ g
Average, 平均数( O/ a4 B/ ~. |: q
Average confidence interval length, 平均置信区间长度
" z6 [2 H% U$ e1 w6 ^# ]' CAverage growth rate, 平均增长率
$ Q+ a u! P( R2 l+ KBar chart, 条形图+ o, ?, I6 w0 p" f% j
Bar graph, 条形图
+ ?$ v. |- t$ V: w8 [3 yBase period, 基期3 I$ e& ]: \! x" ]" L5 h6 b: Y
Bayes' theorem , Bayes定理
; \) a) D/ I, A/ E/ u, ?; YBell-shaped curve, 钟形曲线$ X# d6 W: n+ W+ ~$ T( B' `( o. s+ a
Bernoulli distribution, 伯努力分布' H' ^" ^2 M$ a
Best-trim estimator, 最好切尾估计量
+ N5 L$ i% j3 H- d+ DBias, 偏性5 M6 b) G( j. I) N$ i8 U1 E4 B
Binary logistic regression, 二元逻辑斯蒂回归 q5 P* L2 K( x1 u/ t$ [; ^7 ?
Binomial distribution, 二项分布
[: t( X( L# ~2 ^, c: ^" aBisquare, 双平方4 S9 y" ^* t( p# ^* p# N
Bivariate Correlate, 二变量相关) D# ]' X: W; E8 Y
Bivariate normal distribution, 双变量正态分布
4 ~ C' H! [1 s, Q. sBivariate normal population, 双变量正态总体
; I$ s a2 p" l6 b+ O" K; s5 _Biweight interval, 双权区间
) C- w! r7 x! ~6 e1 x' B5 fBiweight M-estimator, 双权M估计量5 K2 G2 d9 T/ u
Block, 区组/配伍组1 q2 i q* A4 W, z. e8 W& g
BMDP(Biomedical computer programs), BMDP统计软件包. l1 V' l: ^7 t
Boxplots, 箱线图/箱尾图7 R- l' Q6 r9 h2 D
Breakdown bound, 崩溃界/崩溃点
* O. U' F' }7 w; Y0 \+ \9 t+ yCanonical correlation, 典型相关
1 N* I6 @+ T/ G8 b, D1 ?7 e8 BCaption, 纵标目
; r( W. y. }& u1 ZCase-control study, 病例对照研究
9 i/ [& U& h; o+ p% kCategorical variable, 分类变量
P0 `) N2 s, C0 oCatenary, 悬链线
% \6 m- Q& O. K* d, NCauchy distribution, 柯西分布
! w3 K/ _0 F4 c( cCause-and-effect relationship, 因果关系
a8 i, Q! S- a% D( D2 t! Y3 ]( I" YCell, 单元4 \4 ~. K6 j6 ~& Y
Censoring, 终检; o9 D3 t$ a H
Center of symmetry, 对称中心 |# }- Z3 W- ?' I. c2 i& n
Centering and scaling, 中心化和定标
! L5 R/ Q, r( g5 a+ g8 Q" q \Central tendency, 集中趋势
- k' Y/ Z1 D/ k1 H1 Y& FCentral value, 中心值
- z2 K+ V# c; O0 fCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测* b3 }4 ?: z P& S3 p! b8 m6 h
Chance, 机遇; j' n( @/ _8 S2 e" @
Chance error, 随机误差
- Y& T) t) Q. w5 K( k ^. |Chance variable, 随机变量+ j# J1 [9 Q# p1 H
Characteristic equation, 特征方程( ]( M2 Q# T) N" H* K, P: P
Characteristic root, 特征根
' u6 \! G; {6 N2 L, r: W& j- tCharacteristic vector, 特征向量/ X/ u" E) F0 Y7 C- `( _* {
Chebshev criterion of fit, 拟合的切比雪夫准则
0 |& P2 g/ B, X$ u- _7 s3 Y8 B: N n" XChernoff faces, 切尔诺夫脸谱图
5 Z4 J& t) r! @Chi-square test, 卡方检验/χ2检验
! @% m; K m4 m5 D- o. uCholeskey decomposition, 乔洛斯基分解
% R5 [ n- Z1 z9 b3 y2 YCircle chart, 圆图 6 f G, y4 ~$ [
Class interval, 组距& F4 k* I. l8 E/ V$ T) E9 Z" M. H5 }
Class mid-value, 组中值
# D) W, T0 |1 P; SClass upper limit, 组上限5 x( Y! ~; G( h' ~. x! j
Classified variable, 分类变量% I, U" @" ^) f% r% L) s
Cluster analysis, 聚类分析5 V* B* w( B& k6 E: b: k X
Cluster sampling, 整群抽样
5 b% z% t5 M: h v3 E1 w& _# FCode, 代码
( _ _- [, H) }" g0 UCoded data, 编码数据$ i" h' |- g0 \9 M0 K. c& k
Coding, 编码 ?: [1 j0 I3 Y% T9 V. n" |
Coefficient of contingency, 列联系数' d) I2 W- g! M c5 y1 B. L
Coefficient of determination, 决定系数
4 s( }1 P7 K$ r/ u; @$ TCoefficient of multiple correlation, 多重相关系数( L, x5 v1 g. s' \& x
Coefficient of partial correlation, 偏相关系数
4 A/ ?; [0 ^4 W3 L( Z* \Coefficient of production-moment correlation, 积差相关系数
' p: j0 A2 k! u5 o- U& P! u yCoefficient of rank correlation, 等级相关系数4 ^5 q% ?4 _- Z! o" C0 H
Coefficient of regression, 回归系数
# d+ N" u3 ~$ z9 s( HCoefficient of skewness, 偏度系数3 Y: s+ ?5 K9 ]
Coefficient of variation, 变异系数* f$ K0 A6 C- j; x9 q/ b+ j+ D
Cohort study, 队列研究
2 d J9 V7 l' C l: CColumn, 列4 P" O: Z* [& Z4 c
Column effect, 列效应$ X4 n3 S7 _1 R' ]5 B
Column factor, 列因素9 `) e; g) T4 S5 N4 Q' T
Combination pool, 合并* q* c9 v5 ]. b- S
Combinative table, 组合表3 d9 M# R1 [$ z, j9 G
Common factor, 共性因子
0 c8 G) r+ f1 C9 |! @6 g4 C! t6 ]( {Common regression coefficient, 公共回归系数8 k5 J( Y8 E% D8 y' x+ b3 P
Common value, 共同值
+ t3 S, @* ` x9 K& x5 b* E8 ^Common variance, 公共方差
3 C9 ?- e0 V" _9 @$ c# V' ?Common variation, 公共变异' \) `8 i& a i+ C+ A- `& f
Communality variance, 共性方差
- e( B. s9 \* E0 t. NComparability, 可比性+ J5 B# T1 f6 ~0 k
Comparison of bathes, 批比较$ f* \. d0 \! w( c1 n+ Y, I
Comparison value, 比较值' v+ a/ G' u3 X1 C! \6 x/ p
Compartment model, 分部模型
$ a Q3 Q2 t3 A2 h7 K/ zCompassion, 伸缩
# e* H$ L: k; q2 RComplement of an event, 补事件
/ [4 V6 O* b; E1 y. OComplete association, 完全正相关7 O2 A8 S0 u: x1 U
Complete dissociation, 完全不相关. o( k2 Z) x& i7 ^: a! ~
Complete statistics, 完备统计量
) m0 z' _2 @2 _* t. e3 W+ ~, nCompletely randomized design, 完全随机化设计" e/ Z4 {. U7 E: m
Composite event, 联合事件$ u. J9 b; F% L C5 `
Composite events, 复合事件
! t( }5 c7 H& z( n: eConcavity, 凹性! L8 e& x& \$ N3 I4 I
Conditional expectation, 条件期望
1 J9 Y) r8 }8 u3 x6 ]7 Q: WConditional likelihood, 条件似然) K! l+ r( W3 \" G w N
Conditional probability, 条件概率
+ b1 L$ O; Q' f% y! q4 N. wConditionally linear, 依条件线性
' m! r& x" `7 t8 r: ]1 j1 o) EConfidence interval, 置信区间
' Z6 g. ?+ ~+ h0 ^- F4 o) uConfidence limit, 置信限( W! L$ r! H8 m' s
Confidence lower limit, 置信下限9 q" Q: Z! l4 V& R8 ]2 d' j8 m
Confidence upper limit, 置信上限
7 Y `% I i0 d: u# n" ~: bConfirmatory Factor Analysis , 验证性因子分析
9 E) H8 Q8 f7 N# Y( uConfirmatory research, 证实性实验研究
; w$ m* k! y& }4 R4 ~Confounding factor, 混杂因素
) A9 }2 b& x) G5 O* N# B* uConjoint, 联合分析
# Q/ S0 f: `$ dConsistency, 相合性4 q+ L- _1 ?' M0 i2 K# Q2 R
Consistency check, 一致性检验2 E/ u/ b; U- p5 `! \
Consistent asymptotically normal estimate, 相合渐近正态估计
1 C' G8 q4 z0 TConsistent estimate, 相合估计# _* ^" S& E! l: v9 D4 _% O, m# F
Constrained nonlinear regression, 受约束非线性回归5 Z8 ~2 j- m+ r6 f9 Q8 b
Constraint, 约束
0 z7 Q7 D& E4 j+ @0 ^7 _3 I+ {Contaminated distribution, 污染分布3 h2 t4 O* U0 k# [1 D) k L4 `
Contaminated Gausssian, 污染高斯分布
7 z$ F, d$ a( [, T! `Contaminated normal distribution, 污染正态分布
7 m7 h+ o" D& B+ E! bContamination, 污染: W$ a3 i' E* `" a4 r
Contamination model, 污染模型
' Q0 f1 f1 Q0 J. x* t& a2 F8 r1 lContingency table, 列联表+ ?* ?( u7 c- V( Y: P u0 b9 a' T
Contour, 边界线
6 @, u6 h, t$ i3 x. i# S! aContribution rate, 贡献率
( a9 z4 l% i9 e% X& I7 X8 v( f5 FControl, 对照9 r u7 M# F$ d6 K
Controlled experiments, 对照实验
! t; |/ {' k" C% L% B$ HConventional depth, 常规深度; R( G' T/ G6 Z$ h" z; E
Convolution, 卷积$ Y' L5 s P$ j# K' c
Corrected factor, 校正因子# H. H: z! M. N) ?' c/ L' v% S
Corrected mean, 校正均值
; R- u. B; K/ fCorrection coefficient, 校正系数
3 `) f8 K+ O: lCorrectness, 正确性2 r! Q8 F3 X. u. r- ?
Correlation coefficient, 相关系数+ E" S' e: w- X) o4 x+ }
Correlation index, 相关指数
- m+ x( Q% b% ]Correspondence, 对应
6 `, B6 }; t% Y$ W* m, kCounting, 计数
, u; ~# G( i8 Q7 H& h* u" [Counts, 计数/频数9 A1 r' F& ?7 a, r+ T
Covariance, 协方差
9 q! G! ~2 P( }1 F7 t5 QCovariant, 共变 2 C" C3 e( v1 q# ?7 v# U- W+ V
Cox Regression, Cox回归
9 f6 s8 q' I8 N5 ^Criteria for fitting, 拟合准则9 B% K4 [- }* A4 f# S" k+ n9 Q9 g
Criteria of least squares, 最小二乘准则( w0 P- { C" ]
Critical ratio, 临界比
, H! ?2 b$ _' I+ O3 `! fCritical region, 拒绝域/ W* x' O' G/ ^$ g; M5 v
Critical value, 临界值
) @5 R! M0 q9 a, w; xCross-over design, 交叉设计; [& `, P. @( e: S* c4 P% R8 O! g
Cross-section analysis, 横断面分析
4 w3 x! C$ W' ^/ F( ]2 RCross-section survey, 横断面调查
! x1 T% n+ t- c# G9 @) {( U2 z' xCrosstabs , 交叉表
8 \$ _7 l; _1 Q dCross-tabulation table, 复合表
* s( u1 r% z+ P% |5 u$ dCube root, 立方根
1 d/ G5 \' o$ a4 X" P, p: b- F& ZCumulative distribution function, 分布函数
* ^9 y# ~6 y0 |( {$ SCumulative probability, 累计概率* u( n/ h2 }1 z; i
Curvature, 曲率/弯曲
4 Q6 M5 X1 }2 W. g+ }) pCurvature, 曲率
0 Z4 k1 A' a2 H7 q/ s$ kCurve fit , 曲线拟和
, s5 e z$ H4 C9 GCurve fitting, 曲线拟合
7 V+ A% |2 B) O. B+ y' xCurvilinear regression, 曲线回归
& h. ^ D, V" j" A! [# s; zCurvilinear relation, 曲线关系
% k; f6 D, I, l, `4 r( u: QCut-and-try method, 尝试法- F r/ @/ W: e+ E3 j
Cycle, 周期# h5 T: ?! r9 [( q3 X' _/ ]- M
Cyclist, 周期性
- R) g: L7 b$ c3 v1 ^. kD test, D检验
6 f: G/ C+ o- ^# gData acquisition, 资料收集
; P% k* h& e/ \$ }2 v! A; S( Q6 UData bank, 数据库
O5 `5 |' Z0 j' P" qData capacity, 数据容量5 T6 Y; N3 T2 @, [6 E0 v5 L" x
Data deficiencies, 数据缺乏 M, I5 `* [5 I( o
Data handling, 数据处理
9 i0 ^2 p7 t2 e! |, ZData manipulation, 数据处理( Q3 @8 f+ v+ n* ^
Data processing, 数据处理4 u0 X( ` K1 N6 q
Data reduction, 数据缩减- y2 u2 f" Y) A n# f5 s6 ? `% t
Data set, 数据集& B+ g; B# {3 ?" n
Data sources, 数据来源
; Q( [+ O# K: v, B2 lData transformation, 数据变换
8 X, e7 ?# m8 d v. z# H+ Y, pData validity, 数据有效性
, _* y2 c: k* v3 C0 V5 y, }4 q; `Data-in, 数据输入
: u7 P1 \: }) \% W" eData-out, 数据输出
; ~% S* ^$ ^4 _2 xDead time, 停滞期
( S2 }1 W: K" ~- [Degree of freedom, 自由度
0 w: B) c$ ]+ E* [+ tDegree of precision, 精密度) G) ^1 n1 s: P2 f. V* G/ Y# A* C6 p/ S {
Degree of reliability, 可靠性程度
|, u+ {" R6 R# _2 cDegression, 递减7 |4 k3 }. W! J1 C2 o0 t
Density function, 密度函数3 |/ {( _2 O, ?; y1 a; q; B8 B
Density of data points, 数据点的密度# r' N) g+ V8 v4 ^1 a2 M! b0 S
Dependent variable, 应变量/依变量/因变量
" z6 g' _4 f$ X( h* ]* c7 E. RDependent variable, 因变量" L* J0 K2 D9 O0 b2 S! {
Depth, 深度
7 Z. q+ G$ ?* ?Derivative matrix, 导数矩阵
7 i! u! `& o) _( M; m( CDerivative-free methods, 无导数方法
! |0 k5 Z; ~; @Design, 设计
6 {% @( @2 a+ j7 }; r1 F5 B2 l; WDeterminacy, 确定性
2 D/ |7 A4 ~$ ]' ?5 G+ yDeterminant, 行列式
4 }- |# c' N+ Q2 {9 Q: ~Determinant, 决定因素7 r' w+ k4 [2 g& N5 D
Deviation, 离差
2 ?: p8 N4 e* EDeviation from average, 离均差( w, o f; P( l9 `' V
Diagnostic plot, 诊断图
. b( G, L+ }0 P/ }# iDichotomous variable, 二分变量
( h/ q" @! Z4 N6 H4 e6 Y+ M( k3 pDifferential equation, 微分方程
! m" v# p8 c1 C( q& l6 `Direct standardization, 直接标准化法
. e+ | a. g$ V3 O9 o6 _4 A, rDiscrete variable, 离散型变量: M1 a/ e! f% u/ W. D) s
DISCRIMINANT, 判断
4 d/ t |! M0 i5 ]; HDiscriminant analysis, 判别分析; q8 O! B" h7 W% K! `9 [
Discriminant coefficient, 判别系数( X9 F+ h7 p' T# T( [* B, k4 B
Discriminant function, 判别值, u6 D9 o3 D+ k1 Y
Dispersion, 散布/分散度8 q) q. _. Q+ }" o& O
Disproportional, 不成比例的
6 P, S. a' H# q% Z1 W, P9 gDisproportionate sub-class numbers, 不成比例次级组含量6 h6 \7 r2 w2 O- C1 E0 b, r
Distribution free, 分布无关性/免分布
2 Z+ s3 {$ S. oDistribution shape, 分布形状
! c: @5 z* i: `5 v3 ]: o3 s) t5 `, bDistribution-free method, 任意分布法# m* B$ T+ l* i% [5 l) f |
Distributive laws, 分配律
6 n6 |+ z/ p! z/ o. E, vDisturbance, 随机扰动项$ F) ]% J5 z' U/ @* ^' c
Dose response curve, 剂量反应曲线. [) `9 W2 F" v/ H m, Q' j
Double blind method, 双盲法
2 r( m: p$ F* `8 U7 ]Double blind trial, 双盲试验! g f/ J# \% J } I2 Y
Double exponential distribution, 双指数分布: D, s" M7 O& V/ G: ^
Double logarithmic, 双对数
7 m; j0 A# `) vDownward rank, 降秩7 y# `1 A7 F- M
Dual-space plot, 对偶空间图$ K: M( E" f. s
DUD, 无导数方法
8 D2 | o. P! Y( l3 qDuncan's new multiple range method, 新复极差法/Duncan新法+ k4 g# a8 I/ g
Effect, 实验效应) K; ^4 _8 C% u0 {. H8 @2 h/ P
Eigenvalue, 特征值 u# m. E+ I K7 t6 D5 Z" [0 k/ k
Eigenvector, 特征向量2 N b i) G! s9 _- k! V% h! {
Ellipse, 椭圆# u2 _: N/ B* _0 W, H. v5 H* a% w
Empirical distribution, 经验分布6 y# J# r Z0 e: u: K% h$ L# V
Empirical probability, 经验概率单位9 \. K4 O* g# b( ~6 }, @# q
Enumeration data, 计数资料
+ y: x' P8 S- x" s1 gEqual sun-class number, 相等次级组含量
1 Z g/ }& N# U: PEqually likely, 等可能
+ j( E0 m8 J9 r1 u) ]Equivariance, 同变性/ j$ c- S4 m. A8 [* _+ z5 O
Error, 误差/错误
: x) Q1 L' `1 m7 M* W+ ?Error of estimate, 估计误差
# a* X, v% U, L9 i7 V, x' M. E+ gError type I, 第一类错误, d+ }8 m! K7 D6 q, x9 a8 |
Error type II, 第二类错误
+ r/ y! j6 H- C( x+ VEstimand, 被估量
1 _6 q5 T2 k' ~" }, @* |$ Y$ uEstimated error mean squares, 估计误差均方5 J, t/ |% N$ F0 m3 w
Estimated error sum of squares, 估计误差平方和
9 `: A1 A% l4 C% n! u4 O% rEuclidean distance, 欧式距离2 L4 B" d2 E3 [% V2 G. r
Event, 事件
' X) y$ n* W3 Z1 _% B0 ^7 j+ ]- tEvent, 事件
1 T2 l3 i; J# o$ {9 I7 m! N+ PExceptional data point, 异常数据点
" }& @2 [8 U+ NExpectation plane, 期望平面! N0 E6 R2 b3 H7 j6 e- C; X
Expectation surface, 期望曲面
. ?$ o- B& D, {, B6 s% qExpected values, 期望值3 } Q# @6 G& B9 X
Experiment, 实验- b' P7 V3 D( S. ^
Experimental sampling, 试验抽样
) \# Z0 k6 V6 n8 o/ M$ c& c1 LExperimental unit, 试验单位
2 W0 D$ L# W- r0 H& L9 EExplanatory variable, 说明变量6 H% J+ P1 |6 G* ~3 w# J- p1 p K
Exploratory data analysis, 探索性数据分析
9 G/ e" Y8 N9 E" UExplore Summarize, 探索-摘要
- M5 Z4 _" M7 @* V! dExponential curve, 指数曲线
6 o" E5 ?2 L& c5 D/ \Exponential growth, 指数式增长8 ^- p' F4 U: v1 ]
EXSMOOTH, 指数平滑方法 & I0 a7 _( r7 a
Extended fit, 扩充拟合, [' ^$ v5 p: x" W; ^7 L
Extra parameter, 附加参数
) N, h7 u* l3 ^/ X, l, w- hExtrapolation, 外推法
# s2 _$ v" a( F& Z0 V7 TExtreme observation, 末端观测值5 f$ n- w" o; N0 X8 X0 U9 Y
Extremes, 极端值/极值
1 `( r2 L0 E$ J# N) T4 H. wF distribution, F分布! @, v1 M, l" E+ V" ~
F test, F检验9 m4 z* n" V. V
Factor, 因素/因子
! k4 p* r3 E; L H8 aFactor analysis, 因子分析9 B3 S- q* q0 d- I; Y$ ?
Factor Analysis, 因子分析/ f3 H* y4 u" |
Factor score, 因子得分 / e, ]3 Y0 e* j' [7 b
Factorial, 阶乘
* P" w1 O' S& v7 T4 ^7 x T% MFactorial design, 析因试验设计
9 ~1 _" R: C$ H' F0 d2 D+ iFalse negative, 假阴性
; i2 t7 b0 u' D8 FFalse negative error, 假阴性错误
! |9 o$ C6 ~+ C- zFamily of distributions, 分布族: g1 P% {2 ^) ]0 I8 p
Family of estimators, 估计量族- @8 j$ L( P! a: T( G. k3 A! Y0 m
Fanning, 扇面( |! `, }; K; M: |/ r( y3 `" ~
Fatality rate, 病死率
% J7 A( _. ?/ k/ |Field investigation, 现场调查
- f) p" A6 [; L: Y/ E0 {Field survey, 现场调查
* R/ C, h1 q; X% nFinite population, 有限总体2 P% z4 J. N' c+ G, C, y
Finite-sample, 有限样本
: s" B, u8 k3 R, I0 J6 n. B$ W4 {$ n/ x8 BFirst derivative, 一阶导数
2 c4 ?, @0 n, _6 U% D; tFirst principal component, 第一主成分
" n# v8 j4 }1 qFirst quartile, 第一四分位数
# W( V+ O8 h) s z( U( V' yFisher information, 费雪信息量: ~9 L$ x8 i2 @& X/ q6 q
Fitted value, 拟合值
( P2 j6 n% d2 |* l# h+ BFitting a curve, 曲线拟合
w$ ^" \) R$ Y3 l, Z# oFixed base, 定基
9 D1 v' U5 J' I" a- } P" }+ y) r. lFluctuation, 随机起伏
- u1 o5 ^* E3 E( i$ fForecast, 预测
- Z. n8 K% i$ k9 G& ]. v# HFour fold table, 四格表7 U5 N+ y: i" ^+ p3 a& r+ N; b( z
Fourth, 四分点( o8 U' |/ ]2 ]
Fraction blow, 左侧比率+ x1 E* B$ p8 `& b* b( q, ]) ~) d
Fractional error, 相对误差( f/ c- d3 d$ } K1 k
Frequency, 频率
$ w! q Y1 d# k( uFrequency polygon, 频数多边图( o* v3 [. n, |0 }' q& ^3 R7 ?
Frontier point, 界限点
2 i7 @% F+ t1 y ~; f; l$ FFunction relationship, 泛函关系# I0 V: z$ @5 M# u# y0 N
Gamma distribution, 伽玛分布
( p# M' f) G" hGauss increment, 高斯增量& E3 {) y4 e1 z) N
Gaussian distribution, 高斯分布/正态分布/ J9 u' z/ ~' `+ s# d9 d
Gauss-Newton increment, 高斯-牛顿增量" K$ b8 R$ P& K
General census, 全面普查7 U' `" _$ [5 w7 K: u" y
GENLOG (Generalized liner models), 广义线性模型 0 J) V5 R6 [! z
Geometric mean, 几何平均数
2 N7 [# J& e+ ^/ PGini's mean difference, 基尼均差) }: w1 ?, O; F
GLM (General liner models), 一般线性模型
; S; q# f4 X% ^8 a6 m; wGoodness of fit, 拟和优度/配合度0 T5 f' I( K. k
Gradient of determinant, 行列式的梯度
, Q5 O4 `7 p% R+ J4 M! {' oGraeco-Latin square, 希腊拉丁方
5 w- ~: p4 C5 B b9 w$ a: ]% Y$ iGrand mean, 总均值
9 o# f& z% u/ WGross errors, 重大错误( E4 O6 y, ?. d9 \/ ]% r2 L. w
Gross-error sensitivity, 大错敏感度( E! H3 ?, V# D& y) |- y9 X* T. [
Group averages, 分组平均. A$ w/ o/ l: x! ~! G2 I W7 f: [
Grouped data, 分组资料
5 Q: J4 Z. @, r- y. A2 ~Guessed mean, 假定平均数
! o; Q# F/ H% O: o2 iHalf-life, 半衰期% x9 \" o# e: W4 @0 A
Hampel M-estimators, 汉佩尔M估计量
; o$ v) V) Q" J: }" A# EHappenstance, 偶然事件& M! I; x" p; ]# Z6 ]% h8 U
Harmonic mean, 调和均数8 F+ g4 L, S% [& O5 E8 G; y, d! p) n- h
Hazard function, 风险均数 C! o$ F% f2 W6 j. O' J% X
Hazard rate, 风险率
; T7 L/ |; f0 V. C% {Heading, 标目
6 y0 i- W+ }% _' B, l: ZHeavy-tailed distribution, 重尾分布; q, G! i7 ^* |% f, W% r7 Q G7 c
Hessian array, 海森立体阵" ]9 ]! y/ Z- o1 e' Z" j) Q
Heterogeneity, 不同质: A( @: l. m% n+ Q9 P
Heterogeneity of variance, 方差不齐
: P- H6 t* o% X) B- JHierarchical classification, 组内分组
9 {3 |+ ^: G ]Hierarchical clustering method, 系统聚类法, `/ s5 B3 U. n! s" ]' F
High-leverage point, 高杠杆率点- o7 g( e% f' h& Q0 v$ D
HILOGLINEAR, 多维列联表的层次对数线性模型) M. G( X. Q! `/ e+ i
Hinge, 折叶点
; |. ^5 b0 m; r! e% g/ u- uHistogram, 直方图5 ?- i+ \# y* Q* X; l5 p, G/ R
Historical cohort study, 历史性队列研究 % J8 L* D4 L+ c U& `
Holes, 空洞
0 }4 d1 o" k7 ~, x0 h* NHOMALS, 多重响应分析" X. L/ W) t9 t; u, n8 Z4 f
Homogeneity of variance, 方差齐性; o( L- n( V3 R- S
Homogeneity test, 齐性检验, ^2 |6 R& \5 }. k2 |# \% K
Huber M-estimators, 休伯M估计量
( D8 U! w: ^4 U+ ZHyperbola, 双曲线8 v% B0 D! }& N2 S
Hypothesis testing, 假设检验# N$ @6 R8 V7 P+ @* B. x/ z/ W
Hypothetical universe, 假设总体! {4 A' E, G9 [* A: u# x# [' o; }
Impossible event, 不可能事件. I+ {- i; b: k% j) a+ Q3 k# {; J Y
Independence, 独立性8 o" B# Z# }% a" y/ g3 R
Independent variable, 自变量$ r4 |- P$ r" w, r9 }
Index, 指标/指数
/ d9 s6 f2 y- RIndirect standardization, 间接标准化法
) P8 [+ B. g* y9 f: m/ hIndividual, 个体# @! f$ L9 ?. [" j# k2 Y4 ^
Inference band, 推断带 _/ H' f$ \- l. ~ C
Infinite population, 无限总体" J( d5 M! o- B7 C3 o; G
Infinitely great, 无穷大* @% Y5 C: L# h! U/ g' V
Infinitely small, 无穷小
- W5 I. X$ w$ v, rInfluence curve, 影响曲线
* x+ T% M/ G' u% h j, v HInformation capacity, 信息容量
/ v; H1 m0 ]& J+ s; r, W7 H% W9 mInitial condition, 初始条件7 [# }& C6 k& P! U$ [. u
Initial estimate, 初始估计值
c4 {1 n# O2 f* C; gInitial level, 最初水平/ I1 k5 z5 @- I/ E1 ]
Interaction, 交互作用( K3 Q; g* ]2 F1 K; q$ q
Interaction terms, 交互作用项
( b* {2 g8 `/ mIntercept, 截距
" F: H6 i0 r: Q) d: v9 {" v, S6 o: dInterpolation, 内插法
9 u N. G. _; m# `, s: A4 AInterquartile range, 四分位距6 i6 {' E9 G5 ]1 F0 w; v
Interval estimation, 区间估计
8 [% ?$ p& Q; D d0 rIntervals of equal probability, 等概率区间3 c' L, O7 L+ W% J# F" \) ?
Intrinsic curvature, 固有曲率
/ t3 x8 S9 q. m9 p" NInvariance, 不变性! s2 t; T/ h' |6 f0 ~: X% G
Inverse matrix, 逆矩阵
% i; y9 S, m' ^$ S8 N; K EInverse probability, 逆概率
/ Y0 `6 I1 ~8 ?6 i; G& l2 VInverse sine transformation, 反正弦变换
' W9 o [8 |0 p1 f' o( c+ qIteration, 迭代
! a7 J, J7 P% S) _1 o' H# BJacobian determinant, 雅可比行列式
4 e, C9 J& ]! P/ Y7 N5 pJoint distribution function, 分布函数
1 D- P: c5 H, _% }4 P+ EJoint probability, 联合概率" w" H, X q$ l7 r9 S
Joint probability distribution, 联合概率分布0 D& }7 B* V7 q3 t" x! i. s: S
K means method, 逐步聚类法 c1 P# [: r P% E$ j( T
Kaplan-Meier, 评估事件的时间长度 % I+ F* V/ H" q/ s$ V3 O/ q
Kaplan-Merier chart, Kaplan-Merier图
1 f5 V }5 ]* H7 E T0 nKendall's rank correlation, Kendall等级相关
( j+ a/ w* o9 w6 V( I7 f! QKinetic, 动力学
/ s$ c0 E P: _* D+ V- ?* M. GKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验3 z3 ]) R6 o6 I3 O% ?8 ]
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
R4 z8 a+ b' M m2 h* d9 ?' N% X( M, gKurtosis, 峰度
( l3 J( j" o# ?4 v& g* G' |$ BLack of fit, 失拟
' v3 o4 l2 {' V# ILadder of powers, 幂阶梯4 w0 g s; v8 j- x U
Lag, 滞后5 _/ F: _) n+ ?# R: h
Large sample, 大样本
6 V$ J- g% _$ n3 YLarge sample test, 大样本检验
8 t+ m; Y0 F) e; v4 R/ ~& f# l* o& uLatin square, 拉丁方$ g+ `/ G2 o" L+ O
Latin square design, 拉丁方设计' ~+ J% \' _7 E' i( M! c
Leakage, 泄漏9 s# y: i: l3 {+ f$ G, T
Least favorable configuration, 最不利构形' J a7 W6 i1 ?1 {4 B) d
Least favorable distribution, 最不利分布
2 L2 B; G" P8 OLeast significant difference, 最小显著差法
8 C4 P0 O* M9 W3 v p! p3 RLeast square method, 最小二乘法' d8 F2 V' w9 l$ y8 R5 v; y/ N
Least-absolute-residuals estimates, 最小绝对残差估计4 p( \( S S/ b: a# s7 }0 N: T
Least-absolute-residuals fit, 最小绝对残差拟合4 w4 `' M9 `# t# L$ l+ V
Least-absolute-residuals line, 最小绝对残差线
: V! c4 R$ S" u; RLegend, 图例
+ O& Q/ Y7 l4 d% k9 X: rL-estimator, L估计量
5 B8 A3 t' x& ~3 Q0 V6 K E; d+ uL-estimator of location, 位置L估计量5 Y3 M3 D3 ?0 h$ q; T' V! Z0 A
L-estimator of scale, 尺度L估计量
: ~. V- v8 E1 V! W2 n, _9 }Level, 水平/ [0 I0 b! v* S
Life expectance, 预期期望寿命
~5 E' T+ z, lLife table, 寿命表
0 G) ^( h$ L, c" c5 mLife table method, 生命表法
+ n* e! t7 l3 u0 R9 b5 z0 MLight-tailed distribution, 轻尾分布# i6 l# U9 L8 V3 L1 H; f& ^
Likelihood function, 似然函数
% S. I' H/ S3 p+ k+ hLikelihood ratio, 似然比
$ g; U! o m( O! ]) J( _line graph, 线图
, p+ E( H7 L9 A9 U+ N3 ULinear correlation, 直线相关
. H0 k4 F: H9 }. z* M# v0 m: w. LLinear equation, 线性方程
, \* I& x+ {# u' e: RLinear programming, 线性规划: b; T) c% Q% K5 A
Linear regression, 直线回归1 @; P+ Z, \* d5 H6 y+ j
Linear Regression, 线性回归
! n' h" n% q2 rLinear trend, 线性趋势9 M8 ]% }6 R' M* k. h
Loading, 载荷
% \* z" w1 o* _& s" dLocation and scale equivariance, 位置尺度同变性+ ~ k6 l# x8 d) k
Location equivariance, 位置同变性
( S* r+ P7 C: Y* o% G6 ]1 oLocation invariance, 位置不变性
$ O7 A4 L1 } k I: U: q4 WLocation scale family, 位置尺度族
+ d; Q6 H9 F8 P' m# PLog rank test, 时序检验 ! p8 m9 U5 z- d+ M
Logarithmic curve, 对数曲线
- i6 M8 w0 Z6 X H( d6 u: W) S( wLogarithmic normal distribution, 对数正态分布
) A7 m s' a; P- CLogarithmic scale, 对数尺度. h9 _: e6 ?" G0 V+ p# n: M
Logarithmic transformation, 对数变换& e( M4 f7 Y' {; f* ~" \# _' V
Logic check, 逻辑检查% q" Y0 n3 J. V% k0 v' ?
Logistic distribution, 逻辑斯特分布. `# n5 F8 }' h5 Y% i6 y, S) R
Logit transformation, Logit转换0 X x4 m! }2 |$ r2 I& C
LOGLINEAR, 多维列联表通用模型 ' N6 E& X: h) V
Lognormal distribution, 对数正态分布2 d' A, N5 w; [1 b. @- Y" b4 Z* ?
Lost function, 损失函数8 z! |% y3 P5 u; g" O3 W7 Z; c
Low correlation, 低度相关) s. ^# D9 q4 p4 t+ \4 U
Lower limit, 下限9 N' I+ u( `8 X; d9 z/ U
Lowest-attained variance, 最小可达方差* i* y; ]7 t, t9 a+ Y K' k
LSD, 最小显著差法的简称
' r9 _. e3 ]* [1 @) M4 ILurking variable, 潜在变量
" k: |; l5 B0 v8 u O2 oMain effect, 主效应8 E, K/ ?% |! n# o3 k
Major heading, 主辞标目4 _8 V# x8 e4 I3 m% G
Marginal density function, 边缘密度函数
) i7 P' u d6 n* m1 s! XMarginal probability, 边缘概率) _+ J2 `" ~3 Y$ f5 I1 e8 D3 B
Marginal probability distribution, 边缘概率分布
8 V: h0 X( |+ [Matched data, 配对资料
9 O& e; [, ?0 ^; F! N' x6 CMatched distribution, 匹配过分布3 @$ Q' M% d. [9 ?1 L5 s1 }! `
Matching of distribution, 分布的匹配
/ X3 t0 u* \/ K1 q# t8 rMatching of transformation, 变换的匹配
4 ^8 m& y( x0 O3 a$ KMathematical expectation, 数学期望
+ @( Y% |+ {9 A* w' R+ W7 OMathematical model, 数学模型2 l3 r- [2 n+ P5 Q' d" Y: H) d% @
Maximum L-estimator, 极大极小L 估计量& n" }- `) E2 N- y5 Z \# B
Maximum likelihood method, 最大似然法
: Q- b1 [7 G3 @, c6 jMean, 均数3 U# d( l# x& k. W' a
Mean squares between groups, 组间均方4 t# y; c0 y* h: X# y6 h& N. I
Mean squares within group, 组内均方/ s: B1 C& q# }( @* \
Means (Compare means), 均值-均值比较' y4 M1 H0 P7 `2 c; ]
Median, 中位数- a K8 L7 l0 [: C- v2 N9 P* X
Median effective dose, 半数效量9 i$ z) _# [2 Q7 L0 h" r, s' b
Median lethal dose, 半数致死量
" J- p [: U/ D8 w; I5 x0 L! J# VMedian polish, 中位数平滑3 T" l% e. {) M, a* u3 V" A1 `
Median test, 中位数检验4 w! p$ U& @6 V
Minimal sufficient statistic, 最小充分统计量
( I# X; _( \9 S; h* A7 i; }( |Minimum distance estimation, 最小距离估计+ U; k$ t# j7 K& v: e9 U3 E+ G
Minimum effective dose, 最小有效量; q+ d- l+ X1 m2 q3 N
Minimum lethal dose, 最小致死量! y; s" X. `" S5 O& A# G' @2 ]
Minimum variance estimator, 最小方差估计量, C3 D1 s+ `% T3 ]6 k! y6 G
MINITAB, 统计软件包 a, _0 D# g8 t# a7 k5 D
Minor heading, 宾词标目
7 |& [- Q+ V7 @2 G: tMissing data, 缺失值
; e* ^/ B* m. B" B" T: TModel specification, 模型的确定
# V0 G3 z/ F9 k9 CModeling Statistics , 模型统计
+ t0 _0 D3 L% tModels for outliers, 离群值模型
3 M, N' [' Q% l3 L+ O ^Modifying the model, 模型的修正: G$ P4 Q( K$ }6 X6 `5 A5 s- }
Modulus of continuity, 连续性模* q4 S+ x0 \3 F: c. D: P
Morbidity, 发病率 M3 f5 A6 Z& m, ~: y5 C
Most favorable configuration, 最有利构形9 p. m4 j/ Y; S& ]6 `% b& t
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
0 J( C9 m# N1 @4 E' x7 Y4 NMultinomial Logistic Regression , 多项逻辑斯蒂回归3 [+ b" m: z+ O3 a O/ a L7 n7 [
Multiple comparison, 多重比较* V3 z0 W7 Z: Z7 n- J) o4 T2 w7 d
Multiple correlation , 复相关
/ c1 ~/ n P& \- h; h/ MMultiple covariance, 多元协方差. |. W2 p2 G) k" I, V4 J4 b
Multiple linear regression, 多元线性回归 P: F: c' Y8 t/ G- a2 m6 Y
Multiple response , 多重选项
6 {, l1 F- S: ]$ Z& O" K/ t( z1 SMultiple solutions, 多解
" P! A' a% y: l. z/ D5 ~! RMultiplication theorem, 乘法定理
7 v8 {5 P @; z1 {. s+ H* w" GMultiresponse, 多元响应$ N4 [8 U2 `" E' o
Multi-stage sampling, 多阶段抽样
3 N/ @2 ^7 i1 \Multivariate T distribution, 多元T分布
% h; b) f1 m4 A. J4 R" X! N6 g& IMutual exclusive, 互不相容$ p0 f) V. w; }) Q O
Mutual independence, 互相独立
+ ~2 U8 l; d. Z, o0 C# `8 M) ^Natural boundary, 自然边界
" @+ O$ u- L" @. _& s. Y i8 MNatural dead, 自然死亡
5 T$ E: C( Q* |/ @Natural zero, 自然零
2 f$ \4 l/ _9 {3 N1 v+ c8 gNegative correlation, 负相关
! u5 A; N2 a. R, t- I; K. J# xNegative linear correlation, 负线性相关
+ O3 i+ ]5 y0 b. Y3 kNegatively skewed, 负偏
( w' T4 G' o* K2 LNewman-Keuls method, q检验6 O3 h4 }3 j' v1 l* d0 M3 W; N$ t
NK method, q检验
7 W6 ?' ?5 K* h ? Y# F' sNo statistical significance, 无统计意义4 I# x0 W+ c( s9 D+ Z* g E
Nominal variable, 名义变量' ^9 Z5 F/ f+ v. {) R
Nonconstancy of variability, 变异的非定常性
- m, k/ ]/ {. yNonlinear regression, 非线性相关5 K0 b9 R) f6 J; q7 c/ E( ]5 Q/ q$ W
Nonparametric statistics, 非参数统计
9 x0 Z x6 Z9 o; Y% V' P% ^Nonparametric test, 非参数检验2 ^8 d: R" U, g: r/ D7 S
Nonparametric tests, 非参数检验
* Z% N* Y1 a4 K/ xNormal deviate, 正态离差7 N$ @! H4 I( Z1 Q
Normal distribution, 正态分布+ g5 G+ q& V. m4 |5 d0 @' M- ^
Normal equation, 正规方程组
# ]1 s8 b2 l: C' \" ]. bNormal ranges, 正常范围+ `9 H: c- i+ w4 X: Z$ d2 c
Normal value, 正常值
$ [) d/ L* N2 H. i1 _/ q5 H/ QNuisance parameter, 多余参数/讨厌参数: R8 P2 y2 n( C# D) B( t
Null hypothesis, 无效假设 ! E8 C6 D: W1 |) @# h4 n
Numerical variable, 数值变量4 [0 w- x( F1 u$ u
Objective function, 目标函数: m. l) R4 p; F' m/ {& T
Observation unit, 观察单位% M& \7 E2 T7 V, l' ?. a9 c
Observed value, 观察值6 m( ~: a7 i& B4 Z: n7 E2 e8 Q
One sided test, 单侧检验# @$ \: N2 c# |" R8 {4 e
One-way analysis of variance, 单因素方差分析: ]8 K" z* E1 Y( e* ^- E
Oneway ANOVA , 单因素方差分析
; a2 p$ o* S2 o0 W$ W7 O: ?Open sequential trial, 开放型序贯设计3 a4 o/ P# N3 i9 {3 V" b5 \ C# U
Optrim, 优切尾
- }0 p9 U/ z+ ~" B# K h" p) DOptrim efficiency, 优切尾效率
" j# g& Z7 o7 aOrder statistics, 顺序统计量' R! @( f5 G2 k% U6 {
Ordered categories, 有序分类- E6 A z3 H8 x' h7 c
Ordinal logistic regression , 序数逻辑斯蒂回归7 x, a2 u5 ~7 X) v4 c
Ordinal variable, 有序变量
# R" Y0 N. U: k" H( c5 kOrthogonal basis, 正交基8 E3 u9 a5 D, p3 z; F
Orthogonal design, 正交试验设计- p7 x# Q8 Y6 A5 @9 \& D! ?
Orthogonality conditions, 正交条件
/ a9 R7 Q* ]% a) MORTHOPLAN, 正交设计
( z/ r! U$ j/ P% rOutlier cutoffs, 离群值截断点
8 m! h% x& J% k. NOutliers, 极端值
1 w6 a. M) C4 I/ R3 f J# }1 g1 k7 b! J$ XOVERALS , 多组变量的非线性正规相关 , l+ z$ w3 Y8 `* [
Overshoot, 迭代过度
5 B" ^9 b2 L7 u) jPaired design, 配对设计
4 i* P. e6 f6 [4 V0 e, {4 APaired sample, 配对样本
+ x8 c1 v# q0 ]1 ?) G: Q( KPairwise slopes, 成对斜率
~' l. k% a. q) x2 Y! xParabola, 抛物线! d6 r/ }1 n" Y5 f( C
Parallel tests, 平行试验
% e$ B8 d) }% y" C% l- w* A# qParameter, 参数, W3 N, N9 G- y( |) `, |( Z- P
Parametric statistics, 参数统计
6 n# h2 _6 u! o$ ZParametric test, 参数检验! e) u& f2 q8 g2 l0 i, v% x
Partial correlation, 偏相关
! H4 ?( t4 q7 |4 F$ LPartial regression, 偏回归% X4 h' O3 `$ U) u+ K
Partial sorting, 偏排序
4 R$ d" q% i( ]Partials residuals, 偏残差$ X p/ h3 C- k3 x) r
Pattern, 模式0 M, u/ U4 j" @3 i
Pearson curves, 皮尔逊曲线; P0 n3 U# v& S7 X) `, `% X
Peeling, 退层
' S- m9 d9 l7 j G5 Q3 xPercent bar graph, 百分条形图
* x* z' T2 B* I4 @6 Y/ A' _Percentage, 百分比
) B% N+ y0 y# g1 BPercentile, 百分位数! l1 Z" {8 `: }2 \' S4 u! ?9 \; l
Percentile curves, 百分位曲线% d* _3 b5 ]% V% \
Periodicity, 周期性# ?3 @8 H7 }& D
Permutation, 排列
% J) A' t+ ~. j0 @+ m9 LP-estimator, P估计量3 _% v* D8 K# i8 e2 n# C9 y
Pie graph, 饼图& ~$ a' N0 y2 w4 p8 `+ m- W
Pitman estimator, 皮特曼估计量2 ]0 `. f9 j( K' k3 d8 Y
Pivot, 枢轴量/ s0 x" ^9 P. w' W2 i$ V8 \
Planar, 平坦
) {" i1 \2 z1 s% B4 J2 dPlanar assumption, 平面的假设7 g/ r/ k2 e* O2 b. L! M
PLANCARDS, 生成试验的计划卡& M" J$ z+ F5 v" O' K
Point estimation, 点估计
& [6 o1 Y: u6 K BPoisson distribution, 泊松分布
7 a; b5 t6 \( d+ d; H3 Q. iPolishing, 平滑
' D0 }" s! P" N# Y+ ~7 v: R% `$ d, GPolled standard deviation, 合并标准差2 a; m( x! y* w0 f. l
Polled variance, 合并方差. C( y1 b, g. M
Polygon, 多边图
& Y8 @( D6 J3 k1 W: ~# P' bPolynomial, 多项式
" f5 f$ L2 q: Q( {% ?Polynomial curve, 多项式曲线" Q2 j+ L- u e, m$ b' B
Population, 总体
( G. e+ j. G: S/ t7 |& ]% b- gPopulation attributable risk, 人群归因危险度7 K5 R( l& e0 [- x- F
Positive correlation, 正相关9 R! x* k( ^* \+ t8 s
Positively skewed, 正偏: F2 T5 ^6 Q% E0 J1 D# Z C
Posterior distribution, 后验分布* W( h5 o, Y2 c r, u8 s& T
Power of a test, 检验效能. v5 ?* V0 h$ y' \# b. z
Precision, 精密度! N- R, k, o3 d
Predicted value, 预测值( g8 z ^$ L* t6 h) M* H6 m6 T
Preliminary analysis, 预备性分析& i$ c7 Q$ ^' O5 V/ ^
Principal component analysis, 主成分分析: u$ O4 N2 L1 c& y0 m! k
Prior distribution, 先验分布# B* j* |* R; C* }/ H, u, ?& Q( @
Prior probability, 先验概率0 |4 b; V% S0 j& j7 g6 {5 {
Probabilistic model, 概率模型3 T( t! x) T3 j6 E. h& z& d
probability, 概率
; V. O0 t# ` }7 [' W) [Probability density, 概率密度
- }: R: {% T# eProduct moment, 乘积矩/协方差
! b6 F% c% K: c8 }5 @. aProfile trace, 截面迹图, E3 d6 i3 F, g6 P
Proportion, 比/构成比
" w* h& _* F9 @2 mProportion allocation in stratified random sampling, 按比例分层随机抽样: Y- W6 i% C, R
Proportionate, 成比例8 T( t) K# \ w* s& l& ` H
Proportionate sub-class numbers, 成比例次级组含量
8 |' `# a8 h; R5 P; V/ C4 k) RProspective study, 前瞻性调查% [8 D6 y1 ^. X6 l( U4 y
Proximities, 亲近性 2 b+ r8 R/ A; L
Pseudo F test, 近似F检验
3 N J* ?" y! C3 G0 Q) uPseudo model, 近似模型. d, K9 F. x! T7 ]% k: w
Pseudosigma, 伪标准差! q4 P' L$ K+ K& J" ~/ n" A3 R# u
Purposive sampling, 有目的抽样* N$ W4 j6 A/ R3 g. K
QR decomposition, QR分解
" P9 c2 g, M2 V# r% g sQuadratic approximation, 二次近似
% U7 Q% s8 V) aQualitative classification, 属性分类
( e/ F3 M2 l* k+ fQualitative method, 定性方法; r. e8 k1 a4 L0 s0 z9 g+ o
Quantile-quantile plot, 分位数-分位数图/Q-Q图3 n8 C) Y# K5 @9 \: b$ t$ S2 N5 Y
Quantitative analysis, 定量分析7 |2 b0 H* ~0 ~9 g# ` u J
Quartile, 四分位数/ R' b' k! V3 V! V
Quick Cluster, 快速聚类
; O- L5 y# t. n: Y; gRadix sort, 基数排序 L Y# a, g! z5 B, V/ g( Y
Random allocation, 随机化分组
5 [' Q* L. Y9 r0 z2 ~Random blocks design, 随机区组设计
: v" z8 M0 {; ?8 B- y$ O& D- aRandom event, 随机事件1 i/ B; L3 I. D+ z; Q
Randomization, 随机化( K0 A% z4 G) Q6 V' X4 ~
Range, 极差/全距
' T# X4 V' z. nRank correlation, 等级相关
$ h3 V& k4 h# d6 R/ t# bRank sum test, 秩和检验1 n" R7 i! l; M
Rank test, 秩检验
- r4 X' X+ R: `, q4 H. [" tRanked data, 等级资料
" G1 }3 k. S; @& a2 _+ a, v% zRate, 比率
( c- I' @. V/ n; r" vRatio, 比例3 A6 w$ M$ H# X; ^% p( I* {
Raw data, 原始资料
1 X: {( @2 F6 d3 k* u& d- \7 eRaw residual, 原始残差
; N9 |5 n# T2 P% F3 N; [ |0 xRayleigh's test, 雷氏检验- g" P4 i* B2 w2 [4 w1 G
Rayleigh's Z, 雷氏Z值
% L" B& V7 Y, w. B$ @; G y! K) MReciprocal, 倒数
, |/ w I0 H" j7 WReciprocal transformation, 倒数变换
0 K+ Z+ Y* N9 J/ ^Recording, 记录! e9 ~% I: N0 c0 z' v
Redescending estimators, 回降估计量/ p7 e7 d* X) p- k5 N R2 h% B
Reducing dimensions, 降维
( V$ }: ~2 y# L: l2 N+ ~Re-expression, 重新表达6 ?% a, {6 E. }1 `: O0 ~" D
Reference set, 标准组. r2 G. f) ?* h
Region of acceptance, 接受域8 S$ W6 q+ ?3 r2 [' l) x
Regression coefficient, 回归系数
8 S- M$ I1 P0 r( @7 MRegression sum of square, 回归平方和
% F: Z6 P' j5 k F$ _, q- yRejection point, 拒绝点
@' A# v, R+ e( L2 U0 ]. HRelative dispersion, 相对离散度! `* r8 a1 G& I9 B/ w# {
Relative number, 相对数1 f& y+ f$ Q3 h/ e* H9 e% g
Reliability, 可靠性) F; w4 p3 @* K9 z0 u- v) k2 h' V( W
Reparametrization, 重新设置参数
/ z, W: H/ y; w" C1 c. R r2 d) E0 lReplication, 重复
+ e5 }7 B; |; ]: |/ |Report Summaries, 报告摘要1 C w1 B A% n0 i8 y" L
Residual sum of square, 剩余平方和& O S0 ?' T, D6 o
Resistance, 耐抗性
) n- ^& E2 ^1 o/ Z! c! z$ yResistant line, 耐抗线
P' Y% y! e" {% Y. m# u0 yResistant technique, 耐抗技术- G( L) ]9 c3 Q
R-estimator of location, 位置R估计量
3 q+ [6 d0 R E! S) XR-estimator of scale, 尺度R估计量# k4 @1 A/ e5 E7 G E- b1 E
Retrospective study, 回顾性调查# M ~( j- e% b+ u. n* N
Ridge trace, 岭迹
3 i' Y0 V+ x) Z! ?# X {Ridit analysis, Ridit分析: A1 }; `. J2 u5 `( p( a
Rotation, 旋转
9 h. d; w! D# |" n% {Rounding, 舍入- ?+ A: ^: y$ g8 Q' b
Row, 行
; c/ Z" D. m7 u/ p9 d+ vRow effects, 行效应& O( k; k- a4 \( t
Row factor, 行因素, P6 _2 r6 H0 Q
RXC table, RXC表
( E7 }' a: f* ^Sample, 样本. _; ^) ?0 y5 S7 z+ b
Sample regression coefficient, 样本回归系数* r, J% `. l3 D$ j0 ^
Sample size, 样本量
|3 ?/ B& H1 A" }Sample standard deviation, 样本标准差/ p( I+ B5 V$ Y& V, r p$ c* p& i
Sampling error, 抽样误差
& ]$ R9 P9 u$ J: p2 O& M, B! J( S) \SAS(Statistical analysis system ), SAS统计软件包
6 b$ @ s- @# `; {/ kScale, 尺度/量表
! w5 [8 G3 a, K/ fScatter diagram, 散点图
" U) C( j+ E4 v& u2 F: KSchematic plot, 示意图/简图
' h+ e, f. _, P( [Score test, 计分检验5 r6 f. V! U+ W% `, j
Screening, 筛检
( ^& ?# V$ @+ t3 R/ e/ SSEASON, 季节分析 ; H0 u# C/ Q. c8 i# ^, |4 _ l
Second derivative, 二阶导数+ `5 i, d( F& U) M- J7 p N; S1 n) N
Second principal component, 第二主成分0 @ ]0 O9 o# `1 H4 _, `
SEM (Structural equation modeling), 结构化方程模型
! ?1 d) G; _& T' O7 B( R. W0 YSemi-logarithmic graph, 半对数图5 l# Q, `( l. n* k
Semi-logarithmic paper, 半对数格纸
0 W* d8 X7 B0 g6 R% p, sSensitivity curve, 敏感度曲线
3 C/ H% m' r% t& K" U/ F7 }5 a& WSequential analysis, 贯序分析
* [+ j( B1 I+ P0 s+ }: f0 P9 ~6 h) _Sequential data set, 顺序数据集
) [/ N2 W) u( HSequential design, 贯序设计
& {9 F$ o/ @0 I# c1 USequential method, 贯序法
2 f+ S0 s H5 ~& l! B5 s- T NSequential test, 贯序检验法 {# O3 _, w0 L! r% t1 _
Serial tests, 系列试验
0 [7 n8 O1 Y' m$ @9 R3 EShort-cut method, 简捷法
! \$ d0 j* |8 }7 K9 kSigmoid curve, S形曲线
" E: o. p9 n/ ^Sign function, 正负号函数
# U1 F$ s& m( w% H4 JSign test, 符号检验- s! t: v* N" S3 `" I
Signed rank, 符号秩
" ?! e. |' Y$ Z6 T9 u& JSignificance test, 显著性检验& D3 g, z2 }- j9 Q5 t( ]7 S1 q
Significant figure, 有效数字9 h8 ^" T1 R7 q! a) k" N
Simple cluster sampling, 简单整群抽样
6 s8 u1 b% y/ `" G3 Z+ { \Simple correlation, 简单相关 ?9 [& Y" i6 v% I
Simple random sampling, 简单随机抽样( C8 l0 m' M( Q) |( J
Simple regression, 简单回归: h. k A8 f B
simple table, 简单表
) @0 P/ I3 P ]4 `3 b7 ^6 qSine estimator, 正弦估计量
; n0 R } q3 y+ C9 J" m" n; h5 c. JSingle-valued estimate, 单值估计
, R+ r: N1 c/ [/ f# j, @) gSingular matrix, 奇异矩阵
, |" d! Y& Q$ O0 dSkewed distribution, 偏斜分布( R6 F6 V9 {$ w) U
Skewness, 偏度6 E2 t! w8 j% L1 m! S
Slash distribution, 斜线分布" b; k M- v. S- ?( d5 O
Slope, 斜率' O" i: j. Q7 B
Smirnov test, 斯米尔诺夫检验
, H9 @% Q. J5 x- JSource of variation, 变异来源
1 g; N3 y, b0 _4 r0 W) D3 mSpearman rank correlation, 斯皮尔曼等级相关2 w" j, S, m9 Q0 w. ~- G
Specific factor, 特殊因子
! X+ W# }/ q; M6 ESpecific factor variance, 特殊因子方差) S6 k+ W3 a& \: ]$ ~. ~/ i4 E& M/ w
Spectra , 频谱
1 `1 e K4 p# ?+ ^Spherical distribution, 球型正态分布
5 H. w" `8 E9 U; ^Spread, 展布
/ L2 w- k8 t9 s5 @% JSPSS(Statistical package for the social science), SPSS统计软件包
. H! c9 l2 b+ s8 Q3 z8 Z' \6 ~Spurious correlation, 假性相关5 z' Q) r% f/ S# @. p4 |* U/ z* `) _
Square root transformation, 平方根变换# Q( [6 Z9 m) j% {- g1 F
Stabilizing variance, 稳定方差. A, Y2 S, ~, W6 q6 t
Standard deviation, 标准差
3 n. m7 @: U9 ?8 |6 O! Y3 xStandard error, 标准误5 S% l7 z! A# ?8 d8 t$ Q# S
Standard error of difference, 差别的标准误) d9 ^" ]+ D R0 @
Standard error of estimate, 标准估计误差( P% t# ]( G; |$ C; D
Standard error of rate, 率的标准误
% M# Y L8 l% ~0 rStandard normal distribution, 标准正态分布
1 r2 b1 h. I4 fStandardization, 标准化' ?. R* l9 E& {, i$ O# Z
Starting value, 起始值$ B3 }' ^3 R: R! G8 C' f- @% \$ ?1 r
Statistic, 统计量
9 q+ ]7 `! i# ^. IStatistical control, 统计控制
+ d( O& S; E8 W- Z! p! K) t& xStatistical graph, 统计图
5 a9 }8 r" R1 z3 Y+ KStatistical inference, 统计推断
6 Z) J' F5 l3 M# QStatistical table, 统计表
3 l9 R9 N% [* E( mSteepest descent, 最速下降法6 d% Q1 ?6 p0 o5 v
Stem and leaf display, 茎叶图2 ^7 \ }+ n: e4 Y
Step factor, 步长因子
/ [% U' d! R2 P% g" o6 X/ CStepwise regression, 逐步回归
. Y1 D/ t+ c7 g8 ?" d: P) O$ PStorage, 存
; A) ^) F: T6 `+ q( `Strata, 层(复数)+ m5 v$ G* m+ z& S5 Z, @
Stratified sampling, 分层抽样8 j3 j, _4 n( A& }% w% [
Stratified sampling, 分层抽样, E f8 j$ B! Y8 O! m* X8 I
Strength, 强度7 T. N. l3 T9 [) V g, A0 ?
Stringency, 严密性
' V3 `. w3 {9 v/ B" m4 r7 J' |. B, NStructural relationship, 结构关系: @ M* w% r$ v4 \
Studentized residual, 学生化残差/t化残差
' ^; N3 H/ U* ]9 K: |- O# qSub-class numbers, 次级组含量
/ k7 g2 R0 E& n8 Z9 R' ^$ w$ wSubdividing, 分割
# W4 T3 F5 O) b. OSufficient statistic, 充分统计量& U' N5 J9 W2 }: C! H
Sum of products, 积和2 h; @7 }" n6 N4 s
Sum of squares, 离差平方和
# K1 I8 Y+ P/ y) kSum of squares about regression, 回归平方和
! W% @2 ]$ J' RSum of squares between groups, 组间平方和
: k& t' l T! A2 |# ]Sum of squares of partial regression, 偏回归平方和
n* _' J2 ~6 V+ F! z! L/ I1 y4 kSure event, 必然事件0 ~- ~: h, N) l' L0 [
Survey, 调查
6 }6 l8 V, J1 I% i% F* vSurvival, 生存分析
+ s! D- ^# E! S& l( V$ ]0 R( h8 BSurvival rate, 生存率- Q6 }2 w2 L4 ?" _- ]
Suspended root gram, 悬吊根图
) k f+ d- y5 _! H# ~! F2 @7 }Symmetry, 对称
" `' h, ^& N5 BSystematic error, 系统误差2 e2 z# }6 W6 O7 k. _6 c0 E
Systematic sampling, 系统抽样9 f9 G) ]% C1 j/ }1 s$ s+ U7 W7 }' p
Tags, 标签
2 |0 ]0 G$ ~0 C2 ^Tail area, 尾部面积
9 A+ D) g% O+ ~) w" h9 `. I3 `Tail length, 尾长& [( n8 ?% P1 E- `) P x
Tail weight, 尾重9 H1 |& X( w$ e h9 Q
Tangent line, 切线5 a+ m1 E% ^* T- ~8 Z
Target distribution, 目标分布
3 T. j' C- N9 p E/ g7 g: yTaylor series, 泰勒级数2 [ e' T2 z2 l1 g
Tendency of dispersion, 离散趋势% j4 y2 S. T& U. \; V
Testing of hypotheses, 假设检验
3 T) O; H8 k/ W" B+ K, v- ]Theoretical frequency, 理论频数
/ e, |! b- k3 q9 K1 m, q" TTime series, 时间序列
1 q" L$ M& x- qTolerance interval, 容忍区间
- w6 Z+ X0 D4 GTolerance lower limit, 容忍下限4 ~: u% f d$ f) o, `. S, D: I
Tolerance upper limit, 容忍上限. e* ]( {2 |) \6 t" N0 ] D
Torsion, 扰率6 r! A% D2 e+ `" c! v
Total sum of square, 总平方和
$ f- z0 o& c8 F1 `Total variation, 总变异
1 ] c- }9 ]8 b+ h/ u4 _! w/ I0 W2 _Transformation, 转换
7 g9 h9 _! [& f. ?Treatment, 处理
+ a3 G7 p+ l4 H* a, M" UTrend, 趋势
1 w) d# ~1 s1 c: f Z4 S9 aTrend of percentage, 百分比趋势
L1 K0 ?/ q: o! v* E, {; L3 I* ?Trial, 试验) K' W1 s" g% c0 m* c) v
Trial and error method, 试错法0 x8 p! t3 f- b+ m0 L' X6 \, M/ f
Tuning constant, 细调常数
: W# L& m3 e+ Z+ i" A, y( kTwo sided test, 双向检验$ e# x$ \2 `, ^0 b
Two-stage least squares, 二阶最小平方
0 \/ s- ~& X$ X% dTwo-stage sampling, 二阶段抽样: u9 o' \; U- M/ k# z5 `+ o# |- D
Two-tailed test, 双侧检验
?1 M- Y- I1 F; V8 L) i! wTwo-way analysis of variance, 双因素方差分析
R3 ^7 `! q4 F( [- D+ LTwo-way table, 双向表' U- D6 g; V: v8 X$ n8 T! D& Y
Type I error, 一类错误/α错误8 _1 C- T6 A$ [; K$ \9 [' Z3 c
Type II error, 二类错误/β错误; N$ j6 x1 w2 p) I1 x
UMVU, 方差一致最小无偏估计简称
) _2 ^7 F* n/ @( U0 A! ^/ vUnbiased estimate, 无偏估计; W2 u4 \7 q; _( j0 x
Unconstrained nonlinear regression , 无约束非线性回归- e# ]) Q$ i( X
Unequal subclass number, 不等次级组含量
& ^5 f8 C" x, ]2 u5 eUngrouped data, 不分组资料
4 K7 E) o Z* U V& E7 G5 f& JUniform coordinate, 均匀坐标
, w% y0 q4 [& C( u, w+ R/ kUniform distribution, 均匀分布
/ p: r3 |$ _9 f6 h3 V) l4 a6 ZUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( F0 B: m& X( }' ~- A1 KUnit, 单元4 p4 i. {9 p9 s. B4 _
Unordered categories, 无序分类
0 e- p6 c, c& oUpper limit, 上限
1 J) W6 }7 Q1 i, z# x# U$ vUpward rank, 升秩
# w& x- G, H' w6 d0 j9 VVague concept, 模糊概念7 u: h3 @( h/ M0 S1 p4 S
Validity, 有效性
2 ^, O$ h+ F; k3 D9 sVARCOMP (Variance component estimation), 方差元素估计
# @5 |. L W8 xVariability, 变异性( c/ g7 t; E3 s8 }( r
Variable, 变量: C0 d1 T' K: j- g& h) T4 d
Variance, 方差. {7 d* X: W' T0 |6 p2 c- d
Variation, 变异
( I! X& E' i Z1 CVarimax orthogonal rotation, 方差最大正交旋转
# v- J- X- Y, T: cVolume of distribution, 容积
9 ?: n, T' C. i: }- K0 m/ n% yW test, W检验
2 B0 F! g4 z* A) v; ^$ wWeibull distribution, 威布尔分布
# f7 F, R2 ~# BWeight, 权数
- G9 w; A! q# B; n9 xWeighted Chi-square test, 加权卡方检验/Cochran检验
/ t2 K1 l, @' L, N( i' B- CWeighted linear regression method, 加权直线回归- d$ h5 w! C: }: k! F J1 `
Weighted mean, 加权平均数* y: P+ k( d+ m& |0 j
Weighted mean square, 加权平均方差4 B& h# z h0 x! }, S5 D
Weighted sum of square, 加权平方和
: _ d" m: b( S3 sWeighting coefficient, 权重系数
+ \3 _5 z" P! `8 y. V% x/ _2 |Weighting method, 加权法 % R0 U$ }& g( i% q/ Z
W-estimation, W估计量
$ w) }5 ], |5 tW-estimation of location, 位置W估计量) ?1 B: }8 ? B8 Q; ~( r: a5 U
Width, 宽度* U7 @8 ?: ~0 t$ [% z+ C) L5 c! m
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
2 f0 c y: _0 |: {$ R9 ^8 HWild point, 野点/狂点
/ |) j$ K5 u: F/ z6 L$ OWild value, 野值/狂值" z0 k/ u) }; ~2 Y* o
Winsorized mean, 缩尾均值
0 g$ ?9 e# D/ P3 h6 v& R6 [0 iWithdraw, 失访 # f2 H. Y$ `! L3 C- Z+ A% X
Youden's index, 尤登指数7 B$ g# f; Y: r5 w) b5 s2 R( v
Z test, Z检验. }0 e& E7 T# i: [% ?' c, ^
Zero correlation, 零相关0 `+ x2 N- \* \
Z-transformation, Z变换 |
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