|
|
Absolute deviation, 绝对离差
$ |" e: n. x! C, w1 lAbsolute number, 绝对数4 B+ ]( f$ j2 k- U) L
Absolute residuals, 绝对残差6 r' R* @% y6 a9 }* n+ s5 |
Acceleration array, 加速度立体阵
, e5 Z: g; q- X" ?$ r( c- FAcceleration in an arbitrary direction, 任意方向上的加速度8 Y. A1 W$ ^ K% v/ v' j" q1 f
Acceleration normal, 法向加速度7 P* W3 ?9 b2 O- b8 }; n
Acceleration space dimension, 加速度空间的维数
3 ?9 \8 R A8 u, r. sAcceleration tangential, 切向加速度
, m; }3 x$ u h6 @8 cAcceleration vector, 加速度向量4 X" u7 F4 H/ G
Acceptable hypothesis, 可接受假设
# |' n3 ^3 ^. @+ c% a+ n; }7 AAccumulation, 累积
, j# i5 N' j1 `' eAccuracy, 准确度. i: b7 I+ ?( a: F/ v g
Actual frequency, 实际频数
$ a+ v a- P! ~9 o MAdaptive estimator, 自适应估计量2 ?+ D( y( S: n0 E* Y/ E
Addition, 相加: x2 u N" r1 b. K8 l0 G; j. _
Addition theorem, 加法定理
1 ?0 v. E; D8 KAdditivity, 可加性. e& I' u0 c, M9 o% f
Adjusted rate, 调整率
$ k1 e' N+ Y: q+ }Adjusted value, 校正值
& @9 o6 V9 v% t2 j9 JAdmissible error, 容许误差
# j/ q; q0 Q2 s% k' V8 ]Aggregation, 聚集性6 c: p% z9 S5 z& _1 ?, x
Alternative hypothesis, 备择假设
, w( U' p% v" O. MAmong groups, 组间
1 S( o; ^6 B( i* Q V; N& S- gAmounts, 总量, ~! j% d- h+ a: @7 G( O: v
Analysis of correlation, 相关分析
# c3 I- g+ Q9 ]$ y1 w. eAnalysis of covariance, 协方差分析) O3 J6 z* E/ h: s1 n5 A2 l
Analysis of regression, 回归分析( Z4 Y6 A' l, E0 F$ W' i* z
Analysis of time series, 时间序列分析
8 L5 M; b* F/ I7 C2 N hAnalysis of variance, 方差分析- c0 ]2 V7 {* h8 S8 g
Angular transformation, 角转换
9 I4 ]4 ^' I) S* E+ _: uANOVA (analysis of variance), 方差分析5 I% q+ s0 @, y' | _
ANOVA Models, 方差分析模型* i" d3 o. ?/ U; t/ d" H( e
Arcing, 弧/弧旋
# k) s9 a1 \: q9 W, q9 bArcsine transformation, 反正弦变换1 Q( O7 `$ f; M1 U' a- h7 Q
Area under the curve, 曲线面积
4 }/ |2 Y) G2 k1 b( T R. uAREG , 评估从一个时间点到下一个时间点回归相关时的误差
& `' E5 K5 p, w, l& M$ b- J: ]ARIMA, 季节和非季节性单变量模型的极大似然估计
7 m0 T& c. a( T+ [9 k% FArithmetic grid paper, 算术格纸
$ w1 _2 t8 R) AArithmetic mean, 算术平均数
r a* R/ R! F' [- `. a- d0 fArrhenius relation, 艾恩尼斯关系! `( F# b7 s& d' f0 V$ w* A3 U
Assessing fit, 拟合的评估
8 x9 _& _2 Q2 S* P' mAssociative laws, 结合律3 d1 x* L2 q6 X% g) k$ G& B
Asymmetric distribution, 非对称分布
, [1 t0 Q% q* F( Q& yAsymptotic bias, 渐近偏倚
0 I: N" e- j# _Asymptotic efficiency, 渐近效率* K. L, W* @5 U8 y
Asymptotic variance, 渐近方差
# d' ? D8 E: A% C4 T8 HAttributable risk, 归因危险度
- R6 F: h6 J4 p K7 M0 K; e/ cAttribute data, 属性资料! a: P0 f" M0 V h. n+ Y3 y
Attribution, 属性9 W5 a2 u, k Y' \% M- m1 l
Autocorrelation, 自相关
( r% e' o# x8 G6 `& K5 hAutocorrelation of residuals, 残差的自相关
6 j7 P( O! A! MAverage, 平均数9 n3 k# r# K% j' ]# j5 g6 E
Average confidence interval length, 平均置信区间长度
: Z% T! w* e; Q/ lAverage growth rate, 平均增长率
" f" @! T1 _$ ]. u2 \# qBar chart, 条形图, K' e+ y1 ~8 d3 n
Bar graph, 条形图$ e# O. {7 d. ~2 R$ s$ ?
Base period, 基期: u$ M3 i! Q7 u" ^, |
Bayes' theorem , Bayes定理 n+ Q+ k4 P+ V) E5 ~; B$ u2 l" |
Bell-shaped curve, 钟形曲线
- m5 Z1 L8 R6 g% v8 vBernoulli distribution, 伯努力分布. A( v+ j5 V% N+ t# T
Best-trim estimator, 最好切尾估计量
! E8 }* C8 Q; s) W" _# ?2 iBias, 偏性 a0 j% l/ ?' U' h3 a
Binary logistic regression, 二元逻辑斯蒂回归
) Y* {# d$ ~" d [% IBinomial distribution, 二项分布
0 d- v+ C6 k% k( N- u4 PBisquare, 双平方% g* y( V# L/ v4 A& S
Bivariate Correlate, 二变量相关( D4 H8 @, Z3 [- i9 S* r
Bivariate normal distribution, 双变量正态分布
( t! i4 o/ t) EBivariate normal population, 双变量正态总体
- |( [# F) P. y* P3 G) I* C0 mBiweight interval, 双权区间1 g! l9 A. w( d( _' J: g8 l
Biweight M-estimator, 双权M估计量9 U, M4 _# ?& e2 g9 ~5 W0 A6 g& C
Block, 区组/配伍组2 a! n3 j0 `. h+ n' t& h3 x" l/ V& J6 x
BMDP(Biomedical computer programs), BMDP统计软件包
; j7 Y) d+ Q# X& W7 lBoxplots, 箱线图/箱尾图
5 t$ F# j7 A0 pBreakdown bound, 崩溃界/崩溃点& F2 Y/ v$ o$ Q6 c; i3 M
Canonical correlation, 典型相关
3 b% t/ O3 w( ACaption, 纵标目) g& h& u+ N( V0 r: b- K( G
Case-control study, 病例对照研究
0 V0 @8 ?+ {( ~" ?5 {* `. TCategorical variable, 分类变量
% `4 y; V ^" J9 \ q3 h) K6 A. XCatenary, 悬链线6 `6 p' i9 r( m4 w7 P/ M
Cauchy distribution, 柯西分布
! }" D; ~/ N3 K4 fCause-and-effect relationship, 因果关系! b0 T& r [& v4 a+ G
Cell, 单元/ M" m( s. T/ Q6 e) x
Censoring, 终检
/ e# a" P2 l9 R+ @, v% a1 u9 {8 ~% bCenter of symmetry, 对称中心
1 S, d5 E: u( ^. d$ V+ y. MCentering and scaling, 中心化和定标
3 i$ I+ y, `# MCentral tendency, 集中趋势
. v4 M1 m* I3 K+ TCentral value, 中心值
6 b+ t% x9 t; ^+ ~5 r# WCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 F6 i2 ^7 r4 Y( V4 _
Chance, 机遇, |9 }9 z; \* l
Chance error, 随机误差2 C: E1 W# v K# t1 I) M
Chance variable, 随机变量' E" P! I) K; Y: _& t
Characteristic equation, 特征方程0 A% d9 L* A0 P; |2 s" o5 |+ v1 m! ?
Characteristic root, 特征根
0 O) `' t+ x6 G/ P5 UCharacteristic vector, 特征向量
6 l D! {+ k: a) B6 O! ?1 |# XChebshev criterion of fit, 拟合的切比雪夫准则* ^/ u( R! N8 n$ ~/ D7 O0 W3 {/ V
Chernoff faces, 切尔诺夫脸谱图# K" d; @+ B3 M9 E' P! o* C8 z
Chi-square test, 卡方检验/χ2检验
2 J2 k' t% U; `) W1 {& {Choleskey decomposition, 乔洛斯基分解) I, i/ ^ R- e, w$ B; B! {" ^
Circle chart, 圆图 & G9 K+ a m- e6 u/ s
Class interval, 组距
" z; K$ f) B. ?Class mid-value, 组中值* p0 `0 Y/ a, t
Class upper limit, 组上限1 }2 I3 t, E* c9 H+ @
Classified variable, 分类变量
( n2 L) u/ D& t& K+ r0 J& m* vCluster analysis, 聚类分析4 V- }' v2 _* \* D
Cluster sampling, 整群抽样 h2 b. n$ t" Z' |
Code, 代码
0 ?$ }* H! B+ L5 ^: B3 j6 T6 ACoded data, 编码数据! o. z( ^2 h1 b2 ?! b! |: s0 _3 ~
Coding, 编码
$ @8 W' y9 ^0 `3 B1 t+ K" {: c) |Coefficient of contingency, 列联系数
- [$ l; @7 B; B9 X) S7 wCoefficient of determination, 决定系数3 y3 H' X- S# I9 n
Coefficient of multiple correlation, 多重相关系数
# `( P" _' ?6 Y1 W8 c4 ZCoefficient of partial correlation, 偏相关系数
. A5 L- Z- n; t9 GCoefficient of production-moment correlation, 积差相关系数
( z2 Q) h- @! D& S3 lCoefficient of rank correlation, 等级相关系数7 q+ t: d: K5 A6 U) Z7 \( f0 _: Z/ c8 R
Coefficient of regression, 回归系数
) l, Z9 t. _( P8 j% x" F: Z& pCoefficient of skewness, 偏度系数4 j7 G/ F2 h7 t0 J: M" k$ y
Coefficient of variation, 变异系数
. ~ [3 Z4 f& c; l, j8 {Cohort study, 队列研究2 Z! Q$ `/ p. z, g* C1 |
Column, 列
* `0 ]# Y) ~* O2 W: X7 I; r3 UColumn effect, 列效应, _6 i2 I& q2 {" n! W
Column factor, 列因素
9 b- q% a' Z% W5 J1 MCombination pool, 合并
! x* s' P) V" PCombinative table, 组合表4 i/ L' H3 B( b7 a1 q
Common factor, 共性因子
* h6 _! x: n3 C# y; k1 W: h4 WCommon regression coefficient, 公共回归系数8 j/ x0 M5 I6 m _4 J. z1 [
Common value, 共同值& s& b& W: v& x: E5 g
Common variance, 公共方差1 G% g/ ]* J5 U" b1 p$ o
Common variation, 公共变异
1 D% C" A2 |" E% e1 nCommunality variance, 共性方差
% Z4 x q$ x9 A% l3 X! qComparability, 可比性! y5 Q5 F0 p3 N( j* {8 M& }
Comparison of bathes, 批比较
' M: C: x2 N# R5 @2 GComparison value, 比较值- O c' B% T/ h+ J+ Q
Compartment model, 分部模型2 Z8 {, R r7 q% n, S4 y1 Q
Compassion, 伸缩
' u' k1 F z6 N) l0 b; }Complement of an event, 补事件! l0 z; k! L/ J! R# a: _
Complete association, 完全正相关
4 L( P+ a4 |5 c' o# [; j8 z# f& IComplete dissociation, 完全不相关
# J% m, \3 }$ h) n% mComplete statistics, 完备统计量* v4 h. [ x% ^& o! V1 C
Completely randomized design, 完全随机化设计0 n/ `1 q1 S/ l0 p" C6 P* t
Composite event, 联合事件
- v, |6 {& J# a( V) lComposite events, 复合事件8 p& L0 a& G2 X3 Z- @& K( c
Concavity, 凹性
' W+ z5 _9 c1 @; G. h& w$ H5 eConditional expectation, 条件期望$ X8 y' l% J% |, z1 K8 H
Conditional likelihood, 条件似然
) y2 _5 F3 `: i8 [$ q EConditional probability, 条件概率- B& s; }" Y& ~ g0 e
Conditionally linear, 依条件线性
+ }* I& p: r, X& Z2 l" b; o, XConfidence interval, 置信区间
S( N9 l Z7 kConfidence limit, 置信限1 f- }; S( Y, s( C
Confidence lower limit, 置信下限
- R% @4 J* m" D. l" q9 g3 [Confidence upper limit, 置信上限
7 H: x& N, E) Q' n" T+ ~# LConfirmatory Factor Analysis , 验证性因子分析
2 z; C9 S0 u2 ]3 B1 j* \- GConfirmatory research, 证实性实验研究
# V" M! r9 ~! G/ \Confounding factor, 混杂因素+ ^% H0 P/ X5 h) p! M
Conjoint, 联合分析
) y- @* t$ m0 q9 ~( IConsistency, 相合性
h' ]4 w8 ?) M! _; xConsistency check, 一致性检验
% p6 Y( k, T6 C3 s6 n. n! F! M8 b" ~Consistent asymptotically normal estimate, 相合渐近正态估计
) R+ Q+ b4 h u2 w( n. T9 d" h, kConsistent estimate, 相合估计
6 D( c0 [$ [; r9 F- X' lConstrained nonlinear regression, 受约束非线性回归2 Y" v; j& c! T2 b! |' L' K
Constraint, 约束5 ~# x# G8 b1 d2 S
Contaminated distribution, 污染分布/ s3 i, I6 R M4 A; n$ b
Contaminated Gausssian, 污染高斯分布: Q& U9 G% \ X, k
Contaminated normal distribution, 污染正态分布
! D' C' {2 u9 k4 ^& q6 t4 s, q$ ` rContamination, 污染9 D5 P6 J% o% e# W- v2 F" s
Contamination model, 污染模型
& X4 K$ S& a1 T2 ^2 N6 _. vContingency table, 列联表 Z( g4 r& ~( E& \' `% }
Contour, 边界线( X' I( H L+ R
Contribution rate, 贡献率3 T* Z6 g0 C) l+ D: d1 `. @4 \
Control, 对照2 H, a% v' a4 ?6 P; ~
Controlled experiments, 对照实验
( ~& @( M( D8 `7 kConventional depth, 常规深度
4 `% @1 d/ X% D! s+ { N8 I ^Convolution, 卷积
: O2 H( J2 n6 n+ M; k& h6 a1 VCorrected factor, 校正因子
8 M0 V4 r; k7 H3 \% f# y0 } }Corrected mean, 校正均值3 K( _7 d9 t$ h! ^
Correction coefficient, 校正系数
( ~5 G; V' P4 Q4 m# cCorrectness, 正确性
" s# p. Y( H) \2 w3 zCorrelation coefficient, 相关系数
1 m/ n$ A) ~6 ]5 ]: l0 Y7 ?, cCorrelation index, 相关指数
# V0 ?8 @/ B2 q, f6 B/ G9 R1 ^* QCorrespondence, 对应
* t6 u$ N8 L/ D9 U" w2 ?% sCounting, 计数& k: W) ?5 j; q! k) k3 X: L
Counts, 计数/频数
1 J8 |( H" z# f, ^Covariance, 协方差
9 R1 M% v4 v2 t) V3 ?% L- J; `Covariant, 共变 2 d; Y" p7 J1 B9 z
Cox Regression, Cox回归
6 B: K6 U' |9 `& G5 wCriteria for fitting, 拟合准则
7 Q) z; g0 |0 u& ?Criteria of least squares, 最小二乘准则: N+ F9 v1 H5 r Y( h( I
Critical ratio, 临界比% W; B, W, l. Y; c. |% @
Critical region, 拒绝域
* U1 W' F8 _4 |; iCritical value, 临界值9 D- Q6 P2 v# p% Y5 C
Cross-over design, 交叉设计& f- I) | a! ]" X, m
Cross-section analysis, 横断面分析
; [# v* s5 j* I8 e* CCross-section survey, 横断面调查
( }% S# w: c' r4 [# F* UCrosstabs , 交叉表
: K2 j7 G8 ~0 pCross-tabulation table, 复合表
8 z% X; s& Y o8 ^; tCube root, 立方根# X! W' r: W3 Q* A) J
Cumulative distribution function, 分布函数9 K- y1 e9 b: n( f( w/ [
Cumulative probability, 累计概率2 q" Q7 w' u/ r
Curvature, 曲率/弯曲
0 ^. a: h! I7 T' m* N& K! qCurvature, 曲率4 i! U/ q5 T4 P
Curve fit , 曲线拟和
7 |% {3 U5 E! f* V: l' c- ~Curve fitting, 曲线拟合
7 B8 f T; l9 _4 G4 xCurvilinear regression, 曲线回归# }, R, _' q5 z' e0 z* }) o
Curvilinear relation, 曲线关系7 m" N c- t$ }
Cut-and-try method, 尝试法* c& N c; G5 c3 ?- a0 R
Cycle, 周期
5 \% ^7 G/ }" iCyclist, 周期性
: m" A. A6 n0 l% a, pD test, D检验3 [* G0 a" P3 C
Data acquisition, 资料收集4 T: `1 E0 z& Y& J# [+ M( R
Data bank, 数据库
* P$ Z5 Q6 O5 SData capacity, 数据容量
$ a5 m1 H4 e/ o) l2 d, l/ w0 A2 `Data deficiencies, 数据缺乏
% L5 B& P/ M/ Z/ ?6 C! S& FData handling, 数据处理, c% d( r2 z! T" E1 v; i6 O& T0 V
Data manipulation, 数据处理0 \- H* D: r: b3 N2 n: H6 l
Data processing, 数据处理* W1 |' h+ o1 `9 G7 Y; E3 v* V0 Y
Data reduction, 数据缩减/ f; r5 ~9 X- J7 l
Data set, 数据集
$ Z# {, f5 Q$ E2 e& n* wData sources, 数据来源
9 t8 e% N/ t6 e0 v% c; tData transformation, 数据变换
2 e# G6 ^8 r1 l& ~% KData validity, 数据有效性7 {+ {$ X7 U% P; X& J. T% B
Data-in, 数据输入
) z$ V2 A$ }" n3 D2 X* v' L4 jData-out, 数据输出
! b% O# @! n/ o0 `0 lDead time, 停滞期
4 d& K0 S4 d3 B" Z( dDegree of freedom, 自由度& I$ E$ N' ^2 H! I
Degree of precision, 精密度2 ~: e+ ]5 [& K" k8 m$ T$ i! V
Degree of reliability, 可靠性程度1 a# O: @0 U3 {8 O. T& q2 }
Degression, 递减1 v, K6 I: e; h! L, d$ }
Density function, 密度函数) d* `1 \. }" G' e$ V: T, s
Density of data points, 数据点的密度
/ G; U, q! U( bDependent variable, 应变量/依变量/因变量2 y) ~/ L$ N1 M) E4 D( k9 n
Dependent variable, 因变量2 ~$ x% Y( V) U
Depth, 深度
! y) O5 I: E5 s% K% |Derivative matrix, 导数矩阵
9 }. }3 U8 H# d6 { ]5 WDerivative-free methods, 无导数方法
/ U e- D9 X) c( X: L- X- l4 ~Design, 设计
. B- C# C1 u1 U) a: w3 dDeterminacy, 确定性" s- z @3 v4 f3 v4 Q
Determinant, 行列式: A6 ]! P& D* Z( U; Z3 b3 l
Determinant, 决定因素0 A2 V0 Z0 g* X
Deviation, 离差
* L- r: b: y9 U/ ~8 iDeviation from average, 离均差
$ v& Y5 Z- L" C0 U$ h, UDiagnostic plot, 诊断图
. ?! G0 h4 n2 X5 S; ^Dichotomous variable, 二分变量8 k! n( A9 j S: F
Differential equation, 微分方程( O u4 T. k- O; Z0 L# V4 \
Direct standardization, 直接标准化法
- |" N$ C# E$ y6 V' T( c( }Discrete variable, 离散型变量
8 e$ d, r: {- }: {6 zDISCRIMINANT, 判断 # U7 X% [0 X* d* g
Discriminant analysis, 判别分析: _9 h9 x( P4 |
Discriminant coefficient, 判别系数 C1 P7 o+ P0 q$ X, q: K
Discriminant function, 判别值1 l$ R8 |1 J6 S; N. _
Dispersion, 散布/分散度1 C h: b+ g% _8 N* f7 N
Disproportional, 不成比例的
/ f5 C0 o) C2 {+ s" cDisproportionate sub-class numbers, 不成比例次级组含量6 b0 w) y; E2 I- o' T
Distribution free, 分布无关性/免分布
7 M( ^! u1 g' P$ D( A4 D+ J7 [Distribution shape, 分布形状, f1 S+ m* `5 }4 Q$ C
Distribution-free method, 任意分布法
- [/ \$ n2 U- B% c! ?2 mDistributive laws, 分配律7 H* w1 ^2 q! U5 _6 M) i
Disturbance, 随机扰动项
! _& v$ }! l+ i6 |1 jDose response curve, 剂量反应曲线
, x2 F3 h {* l5 s8 TDouble blind method, 双盲法, Q0 B! t8 j" o1 U1 o G* u
Double blind trial, 双盲试验" e! E& [6 c: `. ^3 C7 A/ d! K
Double exponential distribution, 双指数分布
, x' N0 W, O$ Y3 |Double logarithmic, 双对数
+ H5 i% R+ u l* ?6 U, FDownward rank, 降秩
5 E- P* X6 U$ |+ r4 D$ } GDual-space plot, 对偶空间图
8 @; q0 O) D- B+ i' d! }& \DUD, 无导数方法) B; _: F& y f+ W
Duncan's new multiple range method, 新复极差法/Duncan新法/ B$ i* q" i* j6 }0 U+ {
Effect, 实验效应5 H* o9 N- E2 W) q/ E
Eigenvalue, 特征值: {! c6 u/ c4 N. q; B4 T* o
Eigenvector, 特征向量
' M+ X) v3 Y( U& T6 ^Ellipse, 椭圆" q2 M" P6 _% W
Empirical distribution, 经验分布
( p% ]* g$ b: X" ~: x: ZEmpirical probability, 经验概率单位
2 S2 h- G+ T" n8 c- Y) O! h! jEnumeration data, 计数资料9 n: S) i2 {& v4 I" U" F
Equal sun-class number, 相等次级组含量
6 w. u g: p) U9 l+ k* [Equally likely, 等可能
# P8 ?: P" f) ~/ I$ h. vEquivariance, 同变性
7 d( ~8 R1 k" M" i) t7 b; {4 bError, 误差/错误
8 C5 B {. O V* i( g8 q4 K, B$ f/ ~Error of estimate, 估计误差
0 r+ v5 H! A2 q" uError type I, 第一类错误
( ^% c2 P1 C2 Y% p3 xError type II, 第二类错误
: y. C; }$ I6 C4 e! F& B3 j$ E& Z3 k2 mEstimand, 被估量6 A3 K. Z w7 m" H
Estimated error mean squares, 估计误差均方* x# V7 ~# k7 A" P4 \8 c+ }1 S
Estimated error sum of squares, 估计误差平方和$ U( O7 Q# _/ J
Euclidean distance, 欧式距离8 Q7 C6 x2 M4 U0 \
Event, 事件/ F% G6 u2 H; A& h. x6 N
Event, 事件2 A8 R2 ^/ f+ @# G3 r7 Q$ B
Exceptional data point, 异常数据点
. {6 X( S. w& @* I! P# eExpectation plane, 期望平面: B3 O, J R3 ]9 }
Expectation surface, 期望曲面# e5 W" e3 J0 M c2 s- y# ~7 `& W
Expected values, 期望值6 u" `; a3 G; A% G6 Z% A* G3 P
Experiment, 实验
) O/ m- L) `1 D3 {- AExperimental sampling, 试验抽样; R6 W( P. ]( }; O, r; o& a& Y
Experimental unit, 试验单位$ ?, ^) g/ M7 _, A$ I5 t4 \
Explanatory variable, 说明变量# }, ?/ g/ b& a
Exploratory data analysis, 探索性数据分析' m# v# S+ `/ u) T' x/ j
Explore Summarize, 探索-摘要
# Q( Q! e! E, dExponential curve, 指数曲线
: N4 n% A w4 m& m* u) f. |Exponential growth, 指数式增长5 P6 \$ y' i! H
EXSMOOTH, 指数平滑方法
9 E! _3 C! q( ~4 {8 nExtended fit, 扩充拟合- k- s" p( S/ \
Extra parameter, 附加参数" y: p% [$ `8 G# _
Extrapolation, 外推法/ h& u2 M1 o6 p6 Z/ f! X
Extreme observation, 末端观测值
5 s9 J. U3 b4 c9 v7 Y( i$ s* ZExtremes, 极端值/极值3 f0 f* a: z. ^4 i$ ^2 ]# X
F distribution, F分布) ^) @/ N- i% I, W
F test, F检验
# V7 @+ U+ w. z2 x, e |Factor, 因素/因子
6 W }! s% v# U F- X$ xFactor analysis, 因子分析
3 c9 N1 P$ X) R9 A. B" m, p/ j+ z L: RFactor Analysis, 因子分析
% @( k5 d$ B( R" nFactor score, 因子得分
3 j- y# q5 O. [Factorial, 阶乘9 m4 [: V) `$ C" i
Factorial design, 析因试验设计
9 s' |- Z) l0 n, G/ e0 _, XFalse negative, 假阴性
1 S# b; M' ^; Z2 J- e5 ?8 r. C; sFalse negative error, 假阴性错误
% _9 T$ o8 X# }% U$ B: aFamily of distributions, 分布族 ?* ^& `" j1 ?+ k6 A, y, {% x
Family of estimators, 估计量族
4 Y! v7 }1 y! b0 [$ ?Fanning, 扇面
, `+ i' |/ ?+ m! |Fatality rate, 病死率" D# _8 ?5 n* _: ]* {0 P" A+ j
Field investigation, 现场调查
' H! ]% _! `2 }$ k/ EField survey, 现场调查
. F9 ?( B1 ]7 fFinite population, 有限总体
$ n9 n `. O7 sFinite-sample, 有限样本, W9 ^+ M9 O5 P3 t* h, G% G. h! u# e. x
First derivative, 一阶导数 [. ~- A% B/ ~4 q
First principal component, 第一主成分) }+ {6 y* _! ~; r1 h/ b Q
First quartile, 第一四分位数
4 _. X+ u3 r2 X0 I8 g: E5 ZFisher information, 费雪信息量
- Y& y3 k3 K/ m0 S1 i( FFitted value, 拟合值% d* z. x2 ~9 c* K) ~+ C( j
Fitting a curve, 曲线拟合
. Q, b8 K3 v+ ^1 G0 u0 }' OFixed base, 定基
1 j- E4 b. U9 z8 Z- LFluctuation, 随机起伏+ f2 n6 N: S/ g4 t9 S, Z$ v
Forecast, 预测* W) ~' W' t& D3 m
Four fold table, 四格表
: M3 Y( o0 u- Z* f7 ?6 eFourth, 四分点
9 o1 a0 m& l4 [/ W' G8 I, T8 ^Fraction blow, 左侧比率0 D; c- w @# ?! |4 d
Fractional error, 相对误差
+ W. Z- f8 s* p+ yFrequency, 频率
' ? T, z) W) |Frequency polygon, 频数多边图
4 _4 I+ M0 W4 j$ ?6 n8 ]Frontier point, 界限点4 T3 L; ^' n: v0 H5 v' v: M. j
Function relationship, 泛函关系0 i& _) g( t. u. o
Gamma distribution, 伽玛分布0 p& Q: w1 I2 H$ H: N
Gauss increment, 高斯增量- d, n) B* I$ B0 J2 p) `* A( W% r, t
Gaussian distribution, 高斯分布/正态分布
) v2 G5 U+ G; DGauss-Newton increment, 高斯-牛顿增量
# Q. ~: I6 c# T9 SGeneral census, 全面普查
7 Z0 ?8 Q+ u4 P6 f8 yGENLOG (Generalized liner models), 广义线性模型
$ [# Y( b3 j$ U( U5 [% XGeometric mean, 几何平均数' W! B7 M! H% y' J0 o
Gini's mean difference, 基尼均差
2 x, |9 s& I" f: e* S" ]GLM (General liner models), 一般线性模型
9 s# U) Q! d( gGoodness of fit, 拟和优度/配合度% e6 w2 z* s) i/ ~& ]
Gradient of determinant, 行列式的梯度
" Z% ]) v% e+ WGraeco-Latin square, 希腊拉丁方
$ L% z( K- ~5 X8 m/ jGrand mean, 总均值
# i; V9 h. U. k" GGross errors, 重大错误
; b8 g5 G& g- J! \! lGross-error sensitivity, 大错敏感度
" y. N4 s7 G1 ]! f% S6 M) L& R3 `Group averages, 分组平均
. ]" B+ Q( S- w3 {; j- O) @8 G7 GGrouped data, 分组资料% _4 B- w% h. }
Guessed mean, 假定平均数( {$ j) d! {) [# t( r- d
Half-life, 半衰期6 z' k5 T9 G0 }( |
Hampel M-estimators, 汉佩尔M估计量2 z7 j, |4 S" X0 k
Happenstance, 偶然事件0 J' _: X& ]# `/ [0 o) m
Harmonic mean, 调和均数
! H" p8 B$ O# ?/ Y4 zHazard function, 风险均数
! E c2 m( g, a7 U9 E2 H8 ?Hazard rate, 风险率
& f+ Z3 a; u0 ^3 s, p" d+ H% O$ hHeading, 标目 1 e: g7 x% {8 A" P$ X/ F* M; L1 c
Heavy-tailed distribution, 重尾分布
& c; }) z$ L& x$ D. X; zHessian array, 海森立体阵- B$ Q- P: W( o4 ?9 O
Heterogeneity, 不同质5 D U1 C2 d9 v: v6 U
Heterogeneity of variance, 方差不齐 6 g: [) O4 U4 ~0 j% O
Hierarchical classification, 组内分组7 |0 B. E1 n2 \9 T2 K+ o; n5 X
Hierarchical clustering method, 系统聚类法
& E9 j# F2 Z. [- d* HHigh-leverage point, 高杠杆率点
$ y6 j Q. b# [4 N g. GHILOGLINEAR, 多维列联表的层次对数线性模型
6 f! ]3 o7 `5 YHinge, 折叶点2 d/ q6 R2 n- j* u" Z% ~5 q
Histogram, 直方图3 k# J4 ^, x8 j8 o+ }
Historical cohort study, 历史性队列研究 " g1 k( [# h# N3 X" i( b! {/ d
Holes, 空洞
- e" M" B5 g- A4 N8 Z6 {, }* X$ WHOMALS, 多重响应分析0 ?% r# _4 _* h5 b. x
Homogeneity of variance, 方差齐性( H! | K3 S: \: [9 r3 Z/ }4 t
Homogeneity test, 齐性检验
5 W( q j8 h: ]; _4 oHuber M-estimators, 休伯M估计量
# Z( ^$ {: _& U' \. E" T. {. ?Hyperbola, 双曲线
5 `$ M3 D- d" O, K: M6 EHypothesis testing, 假设检验5 @% U2 l0 I& L
Hypothetical universe, 假设总体& e5 j$ w o! V+ t8 k% G
Impossible event, 不可能事件
$ @ p2 x' p7 d) A- H: ]Independence, 独立性
8 H% g K: i/ s9 ^Independent variable, 自变量4 r2 b; }# A, y; {. [" i) y# @2 g$ q
Index, 指标/指数
7 C1 h& W, g z t" ]* |6 cIndirect standardization, 间接标准化法4 A6 D( k3 d2 |0 A5 ?
Individual, 个体
. I, {( \7 F W/ N9 {Inference band, 推断带: p1 [! d, } M p: V4 C: Y4 m
Infinite population, 无限总体
) L1 o9 W0 I8 l; u$ g5 H, j2 \Infinitely great, 无穷大
G* g" S: K" ]6 z! ], s: ]- hInfinitely small, 无穷小
( b( Y4 N4 H/ P( \6 vInfluence curve, 影响曲线
7 C' j% J. A/ RInformation capacity, 信息容量
7 J( v( F8 ]9 W. ^Initial condition, 初始条件
# D" _ S+ u4 ?% Z9 I- XInitial estimate, 初始估计值: w; T/ ^$ `# z) X: o3 g4 {( T
Initial level, 最初水平4 b! U: m2 S7 P9 ^
Interaction, 交互作用
1 r4 ^' S! p, h( @5 o/ xInteraction terms, 交互作用项
) n4 T0 Z1 U' aIntercept, 截距
; l7 P* R$ ^0 y! q3 pInterpolation, 内插法
1 S, O ]# }) T8 `Interquartile range, 四分位距# _: e5 J4 y8 d) N7 ~* o
Interval estimation, 区间估计0 x2 B9 z- ]+ e: |
Intervals of equal probability, 等概率区间
1 l! e6 R; I, ^Intrinsic curvature, 固有曲率
9 s; R5 G* a5 x' `Invariance, 不变性
/ t d2 x* h+ ^% ]8 z( m0 }Inverse matrix, 逆矩阵* K5 Q. v% y( _& q
Inverse probability, 逆概率. i! P( O3 l( E0 w; ^- r) c6 ]0 d0 z
Inverse sine transformation, 反正弦变换: k% @, A/ x! Q1 S
Iteration, 迭代 9 W7 n: t: G% g9 r. r
Jacobian determinant, 雅可比行列式
0 U& }2 V) n6 a1 v& g/ K$ oJoint distribution function, 分布函数
2 L: Z7 F4 H8 E3 F! D; ?Joint probability, 联合概率
& `+ L6 a6 ]: |Joint probability distribution, 联合概率分布! O0 e/ [# j- H; o+ I0 a
K means method, 逐步聚类法
( t2 y0 |# x( J. l1 Y. G( ~3 bKaplan-Meier, 评估事件的时间长度 8 g4 { g0 O: ]& ^5 |
Kaplan-Merier chart, Kaplan-Merier图
# g% E$ o0 _/ o# RKendall's rank correlation, Kendall等级相关
2 b$ E5 s# X$ `3 E& CKinetic, 动力学
0 t' q; V4 D7 \Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
' [( G3 q* |# J3 S& j7 ~Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验& q, W' A) p h
Kurtosis, 峰度1 q8 y# C0 c5 o8 I8 b, ]0 c
Lack of fit, 失拟* _: p s k. N1 d; t% C
Ladder of powers, 幂阶梯
0 m, B. J% |4 @5 Y/ ]9 E% ]! KLag, 滞后' L9 v- i, s: K [5 T0 `
Large sample, 大样本
0 t/ V9 V ?8 Z* G7 W: Y% o/ QLarge sample test, 大样本检验5 j: F1 }, s( n; l: x# Y; ?9 ~' e
Latin square, 拉丁方
+ A/ \1 N& U+ TLatin square design, 拉丁方设计# p- j7 N- T. S7 I. e
Leakage, 泄漏; N1 y; B! S0 h& n
Least favorable configuration, 最不利构形
; V. m5 \+ O8 a% kLeast favorable distribution, 最不利分布: @1 f* v/ X- O: N6 k$ Z* a8 I
Least significant difference, 最小显著差法
! H8 u) e3 ?. o; @ X5 U, M/ ?Least square method, 最小二乘法
7 G: o" U- T3 i) K9 K6 h6 qLeast-absolute-residuals estimates, 最小绝对残差估计) I9 z* q4 v/ [- P
Least-absolute-residuals fit, 最小绝对残差拟合
* o/ I0 x' f8 ULeast-absolute-residuals line, 最小绝对残差线
# O3 @" Y3 G! h' ILegend, 图例
: _1 y$ c, I2 cL-estimator, L估计量" J- i/ x$ H4 H# ]% Z
L-estimator of location, 位置L估计量
# v7 V. f; d+ o+ K! VL-estimator of scale, 尺度L估计量
7 c5 K) x+ K, d& e( T7 lLevel, 水平* v$ ^( T. F: u1 _8 l1 J5 P
Life expectance, 预期期望寿命& D# E5 x- y4 K) }% e8 u
Life table, 寿命表! z' p, y: X2 L
Life table method, 生命表法
5 s G% Z' f% t* v+ r* l2 t: hLight-tailed distribution, 轻尾分布
7 v f- n8 ?& V N! i# oLikelihood function, 似然函数3 W x. L' a$ E+ z; i. M
Likelihood ratio, 似然比
& B0 F* M: }: G5 M; g! zline graph, 线图
7 P% ^$ h0 P, r+ E9 {Linear correlation, 直线相关
# A4 J, n, Q( p3 `" QLinear equation, 线性方程
: ^# ^1 g1 l' DLinear programming, 线性规划; b( v. q! e4 L% u' A3 P+ E% M/ z
Linear regression, 直线回归- A' k9 w. g9 k
Linear Regression, 线性回归( p6 N& R1 V3 i; q9 A/ L
Linear trend, 线性趋势
( q a4 D/ k0 ~4 ~% y7 pLoading, 载荷 2 c9 k4 \5 Y4 @# e5 s
Location and scale equivariance, 位置尺度同变性
) c# i' v' Y: e% G" @/ P) e. fLocation equivariance, 位置同变性5 O% @3 ^' ]! D) R
Location invariance, 位置不变性
3 A$ i& D9 w+ i& FLocation scale family, 位置尺度族
- Q- K L) n" b2 H* u* R& eLog rank test, 时序检验 ! Z0 V. ?7 I+ p/ z: P' V9 I
Logarithmic curve, 对数曲线
0 ]3 V i) a% h3 WLogarithmic normal distribution, 对数正态分布
" k9 s# q5 k1 T+ w: jLogarithmic scale, 对数尺度
1 `0 C. P& k1 |" @1 {/ V' d! H+ xLogarithmic transformation, 对数变换7 q( N* E% \1 W& k `" k1 H
Logic check, 逻辑检查
, G! C4 \0 T0 Y& k, CLogistic distribution, 逻辑斯特分布
7 X; U+ c4 t/ u" a4 O8 M: [# m# ^Logit transformation, Logit转换9 H! o+ b5 R: O6 z
LOGLINEAR, 多维列联表通用模型 " y+ R, Z7 v# G1 c' f
Lognormal distribution, 对数正态分布9 }0 i$ Q0 ] i4 [, J6 t
Lost function, 损失函数# ~$ f |7 T4 }, Z0 O/ D: ]/ D
Low correlation, 低度相关
2 u0 M: x9 L! S" ?: jLower limit, 下限- z7 M8 |4 n$ X3 A
Lowest-attained variance, 最小可达方差1 C- b5 U6 s+ I! I( s# O) r3 i
LSD, 最小显著差法的简称
0 d/ h7 p- b- s' ]; i0 eLurking variable, 潜在变量
0 A4 |2 |6 {* t% x4 L2 B8 @, }* CMain effect, 主效应8 h* X1 W3 ?$ b% V$ U, j2 c0 D
Major heading, 主辞标目! d2 y! D l( d8 S! S
Marginal density function, 边缘密度函数" p5 Q# L0 [$ T7 i% n2 R0 v
Marginal probability, 边缘概率+ q. f& H& m4 @/ d1 B5 g
Marginal probability distribution, 边缘概率分布
1 ~8 ]0 k8 q' _- S6 o7 H" R' TMatched data, 配对资料
- D' }: D7 F3 v( bMatched distribution, 匹配过分布# |" j9 [, U. T& K/ p" B+ v! Q
Matching of distribution, 分布的匹配
1 L" w5 k% V( z( N! [4 NMatching of transformation, 变换的匹配8 U$ v9 t0 {! s* m) Q4 v
Mathematical expectation, 数学期望
9 \/ Y- }0 a4 R( c$ jMathematical model, 数学模型9 U0 Z" P+ z5 ~; M
Maximum L-estimator, 极大极小L 估计量$ x7 x( j, E4 o" Z- ^
Maximum likelihood method, 最大似然法& M0 o: E8 Y. P4 K) P' M4 T& j
Mean, 均数/ c( i6 @0 G) H D5 S" C n
Mean squares between groups, 组间均方
2 b1 P- r1 E5 N* @Mean squares within group, 组内均方
7 G$ R- \0 N0 Y+ OMeans (Compare means), 均值-均值比较
$ e8 Z1 h2 l2 B9 {* P& gMedian, 中位数8 ~! \% v* p, }
Median effective dose, 半数效量
& ^7 @6 `( E7 VMedian lethal dose, 半数致死量" P! I; r7 S8 M8 A3 y& l
Median polish, 中位数平滑$ u P( R& J% j. J
Median test, 中位数检验0 Y7 K( G6 a! B$ @
Minimal sufficient statistic, 最小充分统计量
. C" v/ g! }6 M/ e0 u0 k o. qMinimum distance estimation, 最小距离估计
9 L" \( p( I. O7 z BMinimum effective dose, 最小有效量
' v* ?6 a+ H q! }Minimum lethal dose, 最小致死量) {; C8 j6 X5 G7 f! ` c
Minimum variance estimator, 最小方差估计量 R0 r: u8 q( Q$ j+ |2 {
MINITAB, 统计软件包
7 j: [+ [% H$ u6 G( T! i7 ]! CMinor heading, 宾词标目
% c: N* o/ c5 i, f2 v" H9 ~Missing data, 缺失值$ J# J, I; L) q# m" `
Model specification, 模型的确定/ `- p( g) t& A/ Y" b+ [( |) @3 s
Modeling Statistics , 模型统计
: _6 F9 C, d# k7 `! {/ KModels for outliers, 离群值模型
' }; X$ q- Q2 C# a: YModifying the model, 模型的修正
) p# [) a* o& [4 g5 M4 a8 cModulus of continuity, 连续性模
8 C$ K" t6 k* v1 o; }! r) j/ P3 F" xMorbidity, 发病率
1 Z6 L, o2 E+ \6 @/ X$ @) v3 SMost favorable configuration, 最有利构形
! |: a2 L2 \# @0 RMultidimensional Scaling (ASCAL), 多维尺度/多维标度
) P; \# b% x1 U* OMultinomial Logistic Regression , 多项逻辑斯蒂回归
" J; L$ s: K9 m7 U0 m- gMultiple comparison, 多重比较" o: y9 e+ u) x; b4 K Z
Multiple correlation , 复相关
0 _5 ~: p) V( {) Y" R! AMultiple covariance, 多元协方差
/ {, Z8 I% `4 e1 D" p2 Q2 k. N/ m9 iMultiple linear regression, 多元线性回归
: E9 l" E1 Z! {( i# R& C- f5 l, nMultiple response , 多重选项
5 L& _7 k/ |! G; y, L0 R; FMultiple solutions, 多解
( t# Q5 k' a# W$ K; xMultiplication theorem, 乘法定理
" o0 ?; `# m0 v3 V! w) Z( eMultiresponse, 多元响应& W0 p% K, h! l, v" a
Multi-stage sampling, 多阶段抽样
$ W1 L4 i' F- _. c+ M/ E" q4 V8 GMultivariate T distribution, 多元T分布: K, k8 T" ~9 k; O' S+ g# O
Mutual exclusive, 互不相容8 M2 v/ c C: _; n9 O1 q8 ^9 s
Mutual independence, 互相独立: x3 x7 k9 g) z% Y! C
Natural boundary, 自然边界9 w& d& d# n4 D
Natural dead, 自然死亡
; k) u: [2 p# w" ?2 a! v( lNatural zero, 自然零
8 Y% P( c1 W+ K8 ~Negative correlation, 负相关% l# J9 u, H# E3 ^4 l
Negative linear correlation, 负线性相关
/ i5 M2 F4 f6 n! ~Negatively skewed, 负偏
- {, Z1 x% i" F* q) E( b4 C1 c' QNewman-Keuls method, q检验6 c4 [3 F8 E4 ? k6 Z
NK method, q检验
$ s# L! F! I4 d! f/ R* aNo statistical significance, 无统计意义& ~$ Q/ v. I. `7 e/ U
Nominal variable, 名义变量
0 G7 b9 R( a0 a; t/ ^4 iNonconstancy of variability, 变异的非定常性& Z" _: W2 }4 _4 P9 w9 A4 o+ R
Nonlinear regression, 非线性相关/ W _7 E9 W- Z. N& j
Nonparametric statistics, 非参数统计# K+ G: c. z- p5 C# R
Nonparametric test, 非参数检验; n& _* Q' ^4 W' g" ^
Nonparametric tests, 非参数检验
3 w- k9 o" c5 }Normal deviate, 正态离差
* p6 L; D1 c& Z: _7 n7 U6 A3 |* B7 XNormal distribution, 正态分布
2 ^6 e+ e0 Q- k, [8 T% NNormal equation, 正规方程组 w. G1 @8 B2 ]4 w$ \
Normal ranges, 正常范围
- b T! m! E1 \' TNormal value, 正常值% i7 q2 L9 W3 F2 @3 d, d5 K
Nuisance parameter, 多余参数/讨厌参数- m0 X/ O1 N$ Z
Null hypothesis, 无效假设 8 z; m6 {+ d$ f! B+ b3 N- b- |4 w
Numerical variable, 数值变量8 }3 ^. l6 A8 g* z9 P
Objective function, 目标函数/ o% L) Q5 ^. {5 o, }7 o
Observation unit, 观察单位
* C J: p* K, z+ m2 |% t/ w( d( UObserved value, 观察值/ M/ v: O7 G# V) D
One sided test, 单侧检验
' C8 D! c% c* t8 i3 EOne-way analysis of variance, 单因素方差分析& X3 X* N" }2 ~! @* c! g0 y/ k
Oneway ANOVA , 单因素方差分析) ~" [8 [+ ]9 L. X; g: ~
Open sequential trial, 开放型序贯设计. @1 \+ h T% C9 H8 x/ g( ]
Optrim, 优切尾6 B- g; ~3 s2 w5 e1 B8 j
Optrim efficiency, 优切尾效率) ~7 M* ]& g( z. f' F/ J. {1 [
Order statistics, 顺序统计量% r) \# a+ G; c: ^6 E* Y' z. N0 v8 K
Ordered categories, 有序分类, \4 @' [0 M8 m+ S
Ordinal logistic regression , 序数逻辑斯蒂回归+ `7 ~, I3 u) R' s# U. u8 O0 _, @# L/ n
Ordinal variable, 有序变量! r* k! E* O M$ L5 _" |
Orthogonal basis, 正交基
. ^6 U5 l. p, \1 g c [# S0 w! bOrthogonal design, 正交试验设计
! l5 y2 g' S* ]5 z, A( COrthogonality conditions, 正交条件9 j, H: t& a6 K7 F1 Q! b" q
ORTHOPLAN, 正交设计
: E" O H; r7 xOutlier cutoffs, 离群值截断点
/ h( C- j8 v6 y! sOutliers, 极端值1 _/ W. [$ ]+ I) {
OVERALS , 多组变量的非线性正规相关
" L! i7 Z+ w1 G3 u$ @* QOvershoot, 迭代过度
! a' v# n0 z( v* ZPaired design, 配对设计 K* D3 d+ R6 Q, d# P8 P' b1 ]. \
Paired sample, 配对样本
7 R9 m1 l' W/ z$ c# ^6 a% cPairwise slopes, 成对斜率; e5 k* G" U+ Z# `/ Q: K2 B
Parabola, 抛物线
7 E0 i+ U5 Y' v# y: D% mParallel tests, 平行试验) C# k* c& k" q( q* t
Parameter, 参数
2 J: r+ {3 ~7 R) N$ I2 X5 \. AParametric statistics, 参数统计
! u4 G* l5 R2 ~4 \# ~Parametric test, 参数检验( [1 I7 ?2 n' i) h5 F6 Z8 W0 R' V
Partial correlation, 偏相关1 i. L# E! L- U# r
Partial regression, 偏回归: B. Y X2 b: d% |+ y7 a- h
Partial sorting, 偏排序) |* G$ I- W( B
Partials residuals, 偏残差
Y+ P3 [4 q W, Q3 X, T- s+ {Pattern, 模式0 J2 q* T& C( ~& M* `, K/ L
Pearson curves, 皮尔逊曲线
' y |6 O0 x8 `8 \/ O( X& WPeeling, 退层
; G6 j) i) J+ F7 E8 E0 BPercent bar graph, 百分条形图
8 \% v0 s! U9 X0 hPercentage, 百分比
' G2 @/ y. q' E \Percentile, 百分位数' I" v' T2 A. Z6 s/ d w
Percentile curves, 百分位曲线
0 u/ ~1 v: e. ~# @, Z" {; m3 yPeriodicity, 周期性- @* u2 O9 n: x
Permutation, 排列9 u, H% O# |5 O q% i$ L
P-estimator, P估计量3 [) |. o0 [ |3 M8 S
Pie graph, 饼图
% w! ]' |2 k, ]; W7 LPitman estimator, 皮特曼估计量
; k+ f+ t3 \$ |! RPivot, 枢轴量
! N5 |- m* [& C' APlanar, 平坦" O: ]$ n( W( I8 O
Planar assumption, 平面的假设
0 K3 B- x2 ^" X) r' q4 QPLANCARDS, 生成试验的计划卡, v4 `. L. I/ j$ m+ j/ T9 r
Point estimation, 点估计& M9 H3 k7 B0 ^4 N
Poisson distribution, 泊松分布% P( x% S+ n2 n7 I% ]# x
Polishing, 平滑
# G; S, y9 c2 CPolled standard deviation, 合并标准差0 y: J' q$ h! J& \3 c
Polled variance, 合并方差
+ t8 z9 _) Q' H- QPolygon, 多边图$ |6 b' e/ I0 P5 ?9 M1 h" O: g
Polynomial, 多项式0 B- X$ V, D# T4 Y
Polynomial curve, 多项式曲线
" F6 W L' b4 ?3 L4 w' R( C9 UPopulation, 总体0 I, P7 B) D) y
Population attributable risk, 人群归因危险度
, l, |4 I3 k N& j* U7 a/ CPositive correlation, 正相关
0 P# X! d. ~' n2 {3 nPositively skewed, 正偏
& h+ p2 u; o: a8 HPosterior distribution, 后验分布4 f3 B& O) i! A1 ^( W
Power of a test, 检验效能" l% Z0 \/ R) o$ `
Precision, 精密度
. b$ ~& z* }- ]7 Y9 B9 M9 B' K6 \5 |Predicted value, 预测值
& b# Z7 g7 o, SPreliminary analysis, 预备性分析5 f1 l- C4 {! n
Principal component analysis, 主成分分析2 g0 |" @* D) f4 K, k- I( i- P3 E
Prior distribution, 先验分布( v$ e* |- }4 U
Prior probability, 先验概率: w. e3 M' E7 [5 {
Probabilistic model, 概率模型% A- o: n0 r+ X+ W
probability, 概率
1 ~. j. G+ h& w- S, H" f. ~$ R; SProbability density, 概率密度# o8 G& C) O9 j; U) w
Product moment, 乘积矩/协方差 J( ?# P7 h- J4 W: Q
Profile trace, 截面迹图
) x6 G4 p" N( m yProportion, 比/构成比
. o7 Z1 W% ^% n2 b; o3 O' NProportion allocation in stratified random sampling, 按比例分层随机抽样/ k# x0 o7 A' y" |+ O7 I3 w* e! ^
Proportionate, 成比例
1 p+ K& j+ j6 Z- `, v. \$ N) hProportionate sub-class numbers, 成比例次级组含量8 }1 L- [! n& t t2 `
Prospective study, 前瞻性调查
! S9 X5 T# ?/ ^* PProximities, 亲近性
2 ?+ ~2 d( S: ~4 T7 jPseudo F test, 近似F检验
* \ [8 O9 U7 o$ HPseudo model, 近似模型
0 n7 S" O( n4 p) O6 T( APseudosigma, 伪标准差
3 z) J* f1 q' hPurposive sampling, 有目的抽样
! c. ?, m# `0 W+ Q0 |( PQR decomposition, QR分解
6 j4 ]( a5 M7 r8 `5 f! l. V7 ]/ uQuadratic approximation, 二次近似 c2 E8 P2 Q. S. t& t" L
Qualitative classification, 属性分类
. h- L. W+ z0 h+ {( _4 YQualitative method, 定性方法6 V! g) Z. J% x& h, M
Quantile-quantile plot, 分位数-分位数图/Q-Q图) Z4 ?/ ?: l% p5 S# _' F& ?8 a
Quantitative analysis, 定量分析
0 _8 q; x/ t+ NQuartile, 四分位数
! ~: K. T3 Y$ p" Z; ]Quick Cluster, 快速聚类
* g: t$ B" F# S# f9 MRadix sort, 基数排序, G7 V/ Z; i+ ?. r3 g7 e
Random allocation, 随机化分组
$ w$ K) n8 K9 A5 Y" J$ JRandom blocks design, 随机区组设计0 z/ \, T, S% o7 f2 s
Random event, 随机事件. b5 Y& t# L! Z4 l
Randomization, 随机化2 y1 S! l0 v2 q- ^
Range, 极差/全距1 u4 a% A$ N0 d3 O3 \" A% P( @
Rank correlation, 等级相关
7 z. x; V' Z- z, j; yRank sum test, 秩和检验$ r% D) z! @8 a6 T
Rank test, 秩检验. P3 Y4 W# Z% {/ y$ u6 P7 m7 N
Ranked data, 等级资料. t, K: p6 A) E% J, _& r
Rate, 比率5 ~2 z f9 }/ r
Ratio, 比例
# l; o0 T% y/ N. u7 i' LRaw data, 原始资料
" E# t0 [7 ~" h: ~Raw residual, 原始残差
3 P: ^: v" ]* s" a/ s9 rRayleigh's test, 雷氏检验
6 g# \- q" Y( U" `- n" A7 k, aRayleigh's Z, 雷氏Z值 : M6 _+ G4 v9 A0 J1 J
Reciprocal, 倒数, z8 i) q) `( c- v5 a, j
Reciprocal transformation, 倒数变换& n/ U! B6 ~7 X4 q% W0 ]
Recording, 记录/ }2 ~' @1 M! o; R+ [7 p' @
Redescending estimators, 回降估计量) G9 N7 p9 {7 G' C0 q) x! N
Reducing dimensions, 降维% m& I% O+ Z2 P1 N) w
Re-expression, 重新表达 [6 e s/ W9 v1 T
Reference set, 标准组
. W1 I. j7 R# W7 {6 y7 N* mRegion of acceptance, 接受域, K4 S" ]( q! y$ f, h+ K7 J
Regression coefficient, 回归系数
- C- q+ l1 b" s7 H/ N/ R) SRegression sum of square, 回归平方和5 y+ f! T* ]' Q9 @- u: [+ @% S
Rejection point, 拒绝点
. x* A; d- b2 c2 d* F/ a' }Relative dispersion, 相对离散度
1 R6 J6 I3 ?% x) w* ORelative number, 相对数
7 q8 k/ F3 ^2 oReliability, 可靠性
7 M/ ?) U, t1 B* g' jReparametrization, 重新设置参数3 F9 t! p0 w1 J& \
Replication, 重复0 x$ y# q1 y: B7 @
Report Summaries, 报告摘要
6 \( ~5 B% {: }* o( N& y6 dResidual sum of square, 剩余平方和/ i$ b" l5 y: x. h2 w9 l6 ^
Resistance, 耐抗性
: i0 j( N6 A7 D+ j3 H/ @Resistant line, 耐抗线; y3 K1 j+ z. F9 j% b; T$ ]. U( C) E
Resistant technique, 耐抗技术
$ n4 v% X' t) w) K4 }+ TR-estimator of location, 位置R估计量
/ d0 k) e% p# T, A( B$ G2 gR-estimator of scale, 尺度R估计量
9 n0 K5 w3 h, Q/ J' N. WRetrospective study, 回顾性调查% Z- `- K L. G3 f% j; G) L3 V) s
Ridge trace, 岭迹
: s! e# u; j% i) Q# n4 sRidit analysis, Ridit分析
6 C7 ?0 Y6 G* ^" E( D6 BRotation, 旋转% h# ?+ ^2 {% L3 L2 f- ?! N
Rounding, 舍入- b. y' y7 z, n( _# d
Row, 行
6 m# c. r- {; q+ Q4 x9 J' q' ], uRow effects, 行效应
7 j0 z( Z. y8 y3 t0 @0 w: G) }1 aRow factor, 行因素
+ V' D( F% I2 H; B. _RXC table, RXC表3 x9 x) z$ z* R& w
Sample, 样本0 F4 h. n/ X7 ]( `. M
Sample regression coefficient, 样本回归系数9 u0 @* l# F1 [; U/ }
Sample size, 样本量% c9 r: r/ n3 a9 X
Sample standard deviation, 样本标准差7 u4 _- \ J: \0 E l; J0 V* j
Sampling error, 抽样误差
. y6 V& {0 t8 X. |% tSAS(Statistical analysis system ), SAS统计软件包
! [ E( D3 Y. H; W: B4 W5 i1 C6 bScale, 尺度/量表- X' x+ P/ x6 k1 B: \1 I
Scatter diagram, 散点图7 @4 Q; N; R% P+ J3 N9 f
Schematic plot, 示意图/简图' G( ^+ w( p( d. s' I# U# g4 b
Score test, 计分检验
]0 G* r- H! R& VScreening, 筛检# h* i$ C. J) K: o
SEASON, 季节分析 l8 g# v, }2 P: h
Second derivative, 二阶导数
1 c$ `$ H# Z( tSecond principal component, 第二主成分 d! ^3 a3 L! C0 }, \" M
SEM (Structural equation modeling), 结构化方程模型 ( \+ K# w. k9 D+ b4 R7 C* Y# D. [. x& K
Semi-logarithmic graph, 半对数图
0 `1 b% w1 [$ p, l } W- VSemi-logarithmic paper, 半对数格纸& k1 T# G4 C& m+ D! Y
Sensitivity curve, 敏感度曲线' O! Q: \5 O5 Q7 J/ U
Sequential analysis, 贯序分析
: Q% v/ e! q+ ?' QSequential data set, 顺序数据集
7 n7 o2 G j& N& M1 _Sequential design, 贯序设计
( u( j9 R- r8 S# Y4 ^Sequential method, 贯序法" {, F: q- [! w% F! E
Sequential test, 贯序检验法 M: J# B* F: b. m
Serial tests, 系列试验
! X" B4 y5 R. A4 d4 R" zShort-cut method, 简捷法
6 g& c7 d3 `4 Y* p# ~$ ~Sigmoid curve, S形曲线
! l$ V f7 B7 M# X" |Sign function, 正负号函数) C% p! A" \+ w. j( |) E
Sign test, 符号检验
" E, f4 |5 b2 NSigned rank, 符号秩
% q! x1 z8 X; H6 f$ y1 ]5 |Significance test, 显著性检验3 v. y5 p* |0 {( E# M
Significant figure, 有效数字6 e! l z; T* K3 n5 v
Simple cluster sampling, 简单整群抽样+ ~1 b8 T1 d7 @! M/ C
Simple correlation, 简单相关% O6 j1 S2 P2 F( \# U [4 n
Simple random sampling, 简单随机抽样; W: ]2 Y* V+ _$ y: c
Simple regression, 简单回归
5 [, u1 H) x& p* J8 [% o; Esimple table, 简单表& Y4 V0 Q+ h: `% o
Sine estimator, 正弦估计量$ m7 P- q7 k: O3 G8 t
Single-valued estimate, 单值估计! I V8 _6 L" @, v' E
Singular matrix, 奇异矩阵
$ k# o6 L; S# @0 ?2 V) mSkewed distribution, 偏斜分布/ Q2 c1 K1 _! r! \6 {* y" B
Skewness, 偏度
5 g/ g1 q+ f2 v0 X7 V. W9 JSlash distribution, 斜线分布
# o, [, _9 e. t; M7 l9 PSlope, 斜率
; X/ s3 h' {8 w5 H2 Y/ i7 XSmirnov test, 斯米尔诺夫检验" w+ b0 ?: E3 F" F: l: r- q; \
Source of variation, 变异来源
5 O9 V& u7 @8 J3 z. L; YSpearman rank correlation, 斯皮尔曼等级相关
4 ~8 U3 e' I& ~" ]3 x( E4 JSpecific factor, 特殊因子
2 Q0 x% e% R1 e5 N/ Z% rSpecific factor variance, 特殊因子方差
9 M- |. ]) H' V: hSpectra , 频谱+ t) {8 G! t L, u5 {* O. c9 V9 |* t
Spherical distribution, 球型正态分布
6 w# @# |# v' J+ Y' ySpread, 展布
" y( r) {1 y% b, z9 `SPSS(Statistical package for the social science), SPSS统计软件包
& {' W' `* h- Q. H7 vSpurious correlation, 假性相关
/ G, z" \ y& D& lSquare root transformation, 平方根变换 q( U( k- J; s% n# v: P8 O
Stabilizing variance, 稳定方差3 q( y8 J7 R. R' T8 A
Standard deviation, 标准差
7 W8 _* h: ?+ e/ ?& X" e* GStandard error, 标准误. @- z7 ~+ I; G, {
Standard error of difference, 差别的标准误
& p T# O o" I$ w+ @Standard error of estimate, 标准估计误差
+ q: m% g' K0 bStandard error of rate, 率的标准误
8 a$ Y2 R7 e `' EStandard normal distribution, 标准正态分布1 H" j0 k, D- g5 \
Standardization, 标准化
4 Q ^; J( ?5 u/ }5 ^ m8 Z, KStarting value, 起始值
. Y5 j' u% _! B JStatistic, 统计量
3 N2 ^* O8 m1 E$ P. T! ]Statistical control, 统计控制8 M6 u6 q: W( a. {% d
Statistical graph, 统计图
& i9 I) t5 I7 j0 t U3 bStatistical inference, 统计推断& @) m7 z: s* c% O# r
Statistical table, 统计表- H; x0 i# b8 V
Steepest descent, 最速下降法( P7 \& d: t, P* _' ^$ v
Stem and leaf display, 茎叶图8 S/ S0 ?4 Y7 k5 J
Step factor, 步长因子
: C9 i9 z3 K# B4 ^; D7 z" rStepwise regression, 逐步回归
* C5 { f4 l- ]# X0 v0 uStorage, 存
4 ^3 X1 Q( V _) O7 RStrata, 层(复数)* B/ A4 d4 d/ c% ^
Stratified sampling, 分层抽样
# O' f6 r! e* S7 [. j& sStratified sampling, 分层抽样
8 x$ r* ?; f* E- @8 }Strength, 强度/ k' G4 Q4 a& P$ I" ?: p0 T1 o
Stringency, 严密性
0 _9 k! k7 T Y. X9 D$ H4 cStructural relationship, 结构关系) E3 B; a) H) U) M' z$ q
Studentized residual, 学生化残差/t化残差: f" S7 d6 P) V2 J4 G' x6 W
Sub-class numbers, 次级组含量( D. {& v5 m; h) I
Subdividing, 分割/ Z0 z0 U" N+ | K0 s& L( J
Sufficient statistic, 充分统计量) e& d* q( l2 R% j7 f
Sum of products, 积和0 N h/ }, s, M1 p+ l
Sum of squares, 离差平方和/ ~7 x, H! z$ \2 H+ A: P# ]' }
Sum of squares about regression, 回归平方和, a3 V' e4 }; i
Sum of squares between groups, 组间平方和8 X/ D4 c* |8 V* o2 T0 g' F5 {
Sum of squares of partial regression, 偏回归平方和& R+ X, o( N, R1 I* I7 p4 ` L5 z; G7 y
Sure event, 必然事件
/ v- e7 Q& t* g' w$ b; F* ESurvey, 调查
9 h* r6 g& `7 A E! ?! [3 JSurvival, 生存分析: H' X8 V3 |& Q$ v
Survival rate, 生存率
5 @/ g- @/ X5 y' M! w( S; oSuspended root gram, 悬吊根图- O( B3 ?) `( U; W2 x, `* f
Symmetry, 对称& o: i9 Z* C; |5 ? l) _
Systematic error, 系统误差
5 {3 g6 U# R. R9 l8 X( Z5 PSystematic sampling, 系统抽样: k0 y0 X9 F) Q3 L
Tags, 标签
' @" J/ L- I8 G3 k. m8 ITail area, 尾部面积
+ Q4 H7 \1 X1 R# p4 s" HTail length, 尾长2 S& [9 `& @2 p
Tail weight, 尾重6 b/ l! a3 \% L$ s. [9 m5 C/ Z6 g; i
Tangent line, 切线! v0 B4 m" P* D& U' T4 i
Target distribution, 目标分布0 _6 s" E9 T: c% h' a& I1 u7 N
Taylor series, 泰勒级数
6 k# [ ]/ m: L. y: C( y* l& Q* c# B/ uTendency of dispersion, 离散趋势
, c' n6 D1 i, M2 a* _; xTesting of hypotheses, 假设检验
0 j5 z: l# N& S [* N; B5 uTheoretical frequency, 理论频数
& m8 P; x# |, t( z. G2 A; ~% xTime series, 时间序列6 c0 _" G7 ~% y# a
Tolerance interval, 容忍区间$ T! v5 ?( M7 k. W: ], ?. ~
Tolerance lower limit, 容忍下限2 @/ g: g7 d1 y5 x% s7 |3 R' Y
Tolerance upper limit, 容忍上限 t8 H7 r: ~, Q3 ~$ y
Torsion, 扰率; z- [3 s7 `, M3 `3 s& a1 ?
Total sum of square, 总平方和* u9 O; y( I# y5 F7 r
Total variation, 总变异4 {, |, j$ |. r7 }9 z
Transformation, 转换6 @1 d# e- f- _! `+ Q
Treatment, 处理 [0 _' r1 o3 ]" e6 g
Trend, 趋势6 h) u l6 G0 ^7 a+ B
Trend of percentage, 百分比趋势
* {: `* i' G* y" j, t9 UTrial, 试验9 Y2 d, |! d9 Z- H$ u5 m" `/ j
Trial and error method, 试错法
/ f9 j a) D+ W* MTuning constant, 细调常数
( R. _- I x/ U J- HTwo sided test, 双向检验/ r1 N7 M! q" X2 E/ F) J
Two-stage least squares, 二阶最小平方8 p7 ^9 @ y* z2 r% y+ M
Two-stage sampling, 二阶段抽样
1 {* t N; f- LTwo-tailed test, 双侧检验
$ h$ Q- Y6 p S( iTwo-way analysis of variance, 双因素方差分析
2 @1 H6 k6 U2 }. G6 X# y( N7 X, E5 H" VTwo-way table, 双向表4 Q( K2 n7 S4 ?0 [- R
Type I error, 一类错误/α错误
! g4 D1 v& _1 I% @1 I5 \! l- |Type II error, 二类错误/β错误- I4 ^0 A! @$ h9 h$ t
UMVU, 方差一致最小无偏估计简称
: ]' Q A4 B( q2 m) X9 xUnbiased estimate, 无偏估计
; _$ Y0 V: i9 N7 L! ~) M& DUnconstrained nonlinear regression , 无约束非线性回归 k! w) H- l! C# E- n$ t
Unequal subclass number, 不等次级组含量& U- }' g. Z+ c4 ^9 P( @% t
Ungrouped data, 不分组资料$ e' X+ [: e' S4 C
Uniform coordinate, 均匀坐标" @, t; z* K% U+ \
Uniform distribution, 均匀分布
4 q1 z: x8 n9 E8 T; uUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
) i: `/ \* m6 b OUnit, 单元
: i8 Q p! j2 _% UUnordered categories, 无序分类2 e+ a! V. s# L" v
Upper limit, 上限
# j9 x8 B4 a5 i. F; [Upward rank, 升秩
1 k' f, r D- F3 S/ `0 t3 }. O6 PVague concept, 模糊概念2 y c+ \ M) ~! u7 B' K. C
Validity, 有效性
/ ]) E8 ]7 ]; }8 c0 ^VARCOMP (Variance component estimation), 方差元素估计% |" F; _, Y' _2 a/ C% w
Variability, 变异性
5 ?) E8 S6 i& q1 s jVariable, 变量
7 m% X3 n2 U, jVariance, 方差) x% n# O% V2 m
Variation, 变异
k2 T+ V9 |* D5 r3 }Varimax orthogonal rotation, 方差最大正交旋转
8 i c1 O+ O1 YVolume of distribution, 容积
* U# |7 p2 B( X; OW test, W检验
& B* s% K' o" S0 q$ }- MWeibull distribution, 威布尔分布) w& V! [' m1 m' y6 ^7 g
Weight, 权数' ?7 w2 g6 A/ e0 [
Weighted Chi-square test, 加权卡方检验/Cochran检验8 _ H V2 w0 {: T
Weighted linear regression method, 加权直线回归8 ~! Q c) o0 I1 @! e6 d4 i5 X
Weighted mean, 加权平均数
% y7 T0 e' C: J* y3 e7 Y* D8 c9 D5 GWeighted mean square, 加权平均方差
1 r9 n, C$ E. @7 I" \Weighted sum of square, 加权平方和
0 d x8 w k1 t+ d7 b# ZWeighting coefficient, 权重系数! r* g$ n! t/ h1 |0 B* [, T
Weighting method, 加权法 % n5 _% J, a* M
W-estimation, W估计量- B: j1 L7 V- a4 t0 _& j) E
W-estimation of location, 位置W估计量
* \) n( s& ^- W; N5 b. o# o: A: IWidth, 宽度
% Y5 n+ D* Z" |2 c; K7 xWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
& {/ F" F, w- ^- b$ WWild point, 野点/狂点' c f4 `7 |% z4 O
Wild value, 野值/狂值3 M+ i# @' R# D$ H6 E% L
Winsorized mean, 缩尾均值1 ]2 M* v4 ~% Q- n6 W( j$ t) c
Withdraw, 失访 ; O+ T; n* i' z+ o2 Z
Youden's index, 尤登指数
' y8 g5 } P! `5 N6 c( kZ test, Z检验5 `3 {& P4 p' `( ~9 n0 \0 M
Zero correlation, 零相关. P4 O# K+ c) u0 I' u: A
Z-transformation, Z变换 |
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