|
|
Absolute deviation, 绝对离差
2 u8 j L& S8 ^' eAbsolute number, 绝对数3 H% D$ z0 b5 x0 G
Absolute residuals, 绝对残差# W; Y( J9 N& W: c3 o" v
Acceleration array, 加速度立体阵
' b; N7 \, [. F; Z8 Z; K6 YAcceleration in an arbitrary direction, 任意方向上的加速度" F; [+ ?0 J; r. |+ X" f) _9 M5 F
Acceleration normal, 法向加速度
; r3 U7 s- ~" }+ k0 h3 _1 }Acceleration space dimension, 加速度空间的维数: h6 M9 Z% s$ T2 a
Acceleration tangential, 切向加速度% l' `8 [/ J( c: A1 [
Acceleration vector, 加速度向量$ X7 o& t( b4 t$ u) T+ T% {1 p" h& U
Acceptable hypothesis, 可接受假设
: Z/ o$ C5 G+ h8 u) \9 S' g3 s, w% qAccumulation, 累积
& S- ]% b1 m7 M: s/ e6 j" VAccuracy, 准确度0 O3 g5 ]9 ?. s6 U. A ^
Actual frequency, 实际频数( i; a3 Y# \ L% u" h6 ?
Adaptive estimator, 自适应估计量9 i9 z4 D3 R7 a
Addition, 相加 z0 \$ ]- Z' f \& @0 Z3 g
Addition theorem, 加法定理2 C) X2 w; O' }, k, L0 ?6 E' v
Additivity, 可加性
" c. o0 b1 ?2 S HAdjusted rate, 调整率/ j8 Z% a& [4 O- T" l
Adjusted value, 校正值# j# k0 g' B9 J- e- u7 z
Admissible error, 容许误差
% D% |% [4 x; u7 }" yAggregation, 聚集性6 T2 [, y& n7 g- d5 ?7 ?- s
Alternative hypothesis, 备择假设. s5 H! }4 j! N/ E+ R
Among groups, 组间
' h0 b: G" ~1 F+ j p! \$ |Amounts, 总量! \9 z* [( z! d$ @7 d
Analysis of correlation, 相关分析
1 F' m9 Z" r; `Analysis of covariance, 协方差分析
% Q! X. h5 ]5 v- MAnalysis of regression, 回归分析
& @$ L- k" Q: l. J% @9 cAnalysis of time series, 时间序列分析8 P1 F# B9 y. S8 V' T
Analysis of variance, 方差分析! k. y8 S) j3 L' @- f; P) J
Angular transformation, 角转换+ B' Q6 |( }2 ~; N! f# ~' w, `
ANOVA （analysis of variance）, 方差分析
9 {* ?" W* Z+ W% s; Y* M! mANOVA Models, 方差分析模型9 W. N" p3 B2 A3 f6 a
Arcing, 弧/弧旋. F' G I1 K' ]! E4 d- B, w
Arcsine transformation, 反正弦变换
( A5 v4 j- P8 P( T; n* a8 W/ qArea under the curve, 曲线面积
( v7 L D1 P3 K! i4 n* gAREG , 评估从一个时间点到下一个时间点回归相关时的误差
9 {7 D- U$ ~ {ARIMA, 季节和非季节性单变量模型的极大似然估计 " ? ]- _; Y! ]. p6 S
Arithmetic grid paper, 算术格纸' v7 P0 c6 r ]% h+ a: v" A
Arithmetic mean, 算术平均数3 H$ _% A+ z) G3 I w w$ f+ M( _
Arrhenius relation, 艾恩尼斯关系
) y5 j Y+ }2 D$ m. M8 @5 hAssessing fit, 拟合的评估; g$ X! V) `5 I$ i% }2 U; w+ x
Associative laws, 结合律
! i+ @8 A% c# j4 z1 A$ \4 HAsymmetric distribution, 非对称分布* B! @- g3 ?6 L8 e5 [: n
Asymptotic bias, 渐近偏倚" n0 x: ?, x. @/ W4 p
Asymptotic efficiency, 渐近效率
* S6 C1 d( c1 n4 e) e$ @Asymptotic variance, 渐近方差& z& W: W \7 J+ d% [
Attributable risk, 归因危险度7 d/ I1 ]5 j& o% F5 C
Attribute data, 属性资料% L, @( j1 { @, [
Attribution, 属性
$ a0 I9 k4 I( W3 }' W" wAutocorrelation, 自相关 r9 [$ J" x& G L
Autocorrelation of residuals, 残差的自相关 J v& n% {7 Q2 L' E1 r) W
Average, 平均数
- d$ i7 v d( J( xAverage confidence interval length, 平均置信区间长度
- N; i# b7 x E) f, M+ u% @9 x; fAverage growth rate, 平均增长率
) [9 j. e/ N8 E7 q x- ]3 @% sBar chart, 条形图
4 O/ V1 [ }" P- @8 V* ?Bar graph, 条形图" k5 k( f% G8 y. g4 \# u
Base period, 基期
- X7 i. C% Z7 _& }5 J1 H/ O8 d$ K+ {Bayes' theorem , Bayes定理
: y' [% g# j7 s- H; l: e2 a, H3 zBell-shaped curve, 钟形曲线& i/ `5 v: ]- I% U. S$ y; Y
Bernoulli distribution, 伯努力分布5 V) i. c# F4 P8 D
Best-trim estimator, 最好切尾估计量
* j7 B' e- E, R9 r/ l7 @Bias, 偏性
5 E) H3 C! n* c* R0 s) u t7 N6 ?Binary logistic regression, 二元逻辑斯蒂回归+ W8 H4 W6 X) L# ]* t3 v/ P, G
Binomial distribution, 二项分布
* x4 L/ [8 ^$ U, R9 b ?1 lBisquare, 双平方- l* Y9 Z/ U8 ` c1 p* E1 |4 w
Bivariate Correlate, 二变量相关
- d( l0 f: v1 W4 M# L7 ABivariate normal distribution, 双变量正态分布
$ t+ v, W. A# F3 }# n4 MBivariate normal population, 双变量正态总体8 U7 H! D8 s7 `5 w
Biweight interval, 双权区间) q& V& G. [/ _1 _; O
Biweight M-estimator, 双权M估计量$ H6 e1 c/ [% r' _
Block, 区组/配伍组' E& l; q9 |4 E! h/ ]6 x
BMDP(Biomedical computer programs), BMDP统计软件包
$ ?' Y$ @$ q% _4 WBoxplots, 箱线图/箱尾图
* H9 I4 D6 y; o7 V; qBreakdown bound, 崩溃界/崩溃点- _3 J! d( {+ P
Canonical correlation, 典型相关9 W G5 d) c) S5 W, r
Caption, 纵标目2 f* _/ H" h7 b* G6 N8 t
Case-control study, 病例对照研究2 x- B: z" F) P! u
Categorical variable, 分类变量
& P1 o- m3 ~1 H! g* ECatenary, 悬链线* }8 j8 T* V, H3 h/ b
Cauchy distribution, 柯西分布
8 C, `8 B; r* MCause-and-effect relationship, 因果关系: e8 R# s8 M/ ]2 k
Cell, 单元5 n! j% ]! i" _4 T5 V
Censoring, 终检
/ A1 W" m; R eCenter of symmetry, 对称中心
, C0 U+ r. l f% e4 h8 A- vCentering and scaling, 中心化和定标1 L$ x6 z# ~6 F, f
Central tendency, 集中趋势0 O& m7 t2 w/ h: a1 O5 b
Central value, 中心值+ [& z# ^+ Q# f: r7 v
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
+ n x7 L* @, ]7 qChance, 机遇
5 `7 P3 M& F8 G0 c4 LChance error, 随机误差* E) D: M U0 a
Chance variable, 随机变量
3 s/ t( t( V; o7 Y8 `, d0 I2 d" {: [Characteristic equation, 特征方程
% J. p `4 W4 b1 J7 v/ a6 Y% D; I. @Characteristic root, 特征根
& K" n3 b% N; f vCharacteristic vector, 特征向量4 }' L5 J5 l% c1 v9 k2 z; k; t
Chebshev criterion of fit, 拟合的切比雪夫准则
h: b! F! q$ k1 @2 UChernoff faces, 切尔诺夫脸谱图
[2 O. F1 z0 b. _5 n$ g2 p$ X9 U3 \Chi-square test, 卡方检验/χ2检验
. i' g M: e" P! R# KCholeskey decomposition, 乔洛斯基分解
( t. W* x- x7 g5 y2 T4 TCircle chart, 圆图 ) f, @: T* C2 m* D2 p7 i5 |2 N( m
Class interval, 组距
) K9 W: o C6 M; G2 a! hClass mid-value, 组中值
# ?! Q4 b) }/ |; ?& g# d! x" ZClass upper limit, 组上限
" L3 S' R' B$ W* hClassified variable, 分类变量
7 L. t+ _- C2 m+ g7 OCluster analysis, 聚类分析
) h9 v* |. w& _" A$ ACluster sampling, 整群抽样
) Q3 v# z3 @9 |2 |- } \4 x: e& yCode, 代码! `! C+ e* ^8 f) @& ^
Coded data, 编码数据
* {, X+ p$ G; C) |6 z( ZCoding, 编码4 M& n( ?" c: ?
Coefficient of contingency, 列联系数
; G, t% T$ J7 p2 Z9 H; _/ CCoefficient of determination, 决定系数& g8 t9 Q+ w1 `$ f+ e9 ?
Coefficient of multiple correlation, 多重相关系数6 ]6 A0 a' J6 ^# I. G
Coefficient of partial correlation, 偏相关系数
3 D @9 P2 w+ @( A' iCoefficient of production-moment correlation, 积差相关系数" Q `+ [+ p Z9 |
Coefficient of rank correlation, 等级相关系数, @+ s1 s% A0 x; _' k0 c0 e
Coefficient of regression, 回归系数
; `# O! {' m. }% n! ^ H% X, TCoefficient of skewness, 偏度系数/ i9 q8 ~. z6 U, }
Coefficient of variation, 变异系数/ i- P5 v3 c! | w
Cohort study, 队列研究! e! ?" Z* D4 O s% B& D l
Column, 列
4 V1 `8 `1 U! gColumn effect, 列效应/ m7 O; T/ ^6 z1 d' {
Column factor, 列因素! j4 m; p/ U4 M. {% o8 \
Combination pool, 合并) ~+ O+ r U/ B c) K
Combinative table, 组合表
, O/ ~, @3 i+ A) e; RCommon factor, 共性因子0 p0 E9 y; S* o6 M. c4 @ w/ H
Common regression coefficient, 公共回归系数
: O/ L) X% m! L3 X! LCommon value, 共同值8 v) ]1 }: |1 ?4 }
Common variance, 公共方差# ^, ~5 s* j' l2 u3 S: T) ]6 D
Common variation, 公共变异
d p0 u2 V/ zCommunality variance, 共性方差
2 T- G4 j `" w7 t4 \Comparability, 可比性
7 C/ m; H1 U0 o; j2 |Comparison of bathes, 批比较
9 |- ]' {6 h' Y3 h" i3 KComparison value, 比较值$ z" n3 n) v" x8 }
Compartment model, 分部模型+ d( h5 Y V) o) ]- Q9 _) B( O
Compassion, 伸缩
; M M4 ~- ]7 t0 t/ Z! L' @# }. ]7 O) VComplement of an event, 补事件/ S0 X: ?7 o& b, B
Complete association, 完全正相关
/ K- k: r- |' N- u8 YComplete dissociation, 完全不相关( o& ?0 D! s1 _3 w9 M. d
Complete statistics, 完备统计量
' N- V- j/ ]0 x) O: S3 K4 K' ?Completely randomized design, 完全随机化设计- d/ r/ o. Q3 Q& Z- k
Composite event, 联合事件
; V' D& l1 }+ s; x; J& t& J5 BComposite events, 复合事件
3 B) @+ r* b, g8 x- I" g. M& J3 h* SConcavity, 凹性
# u) @6 c( K" _' {! OConditional expectation, 条件期望
( ]7 i) W' X7 J7 v1 }Conditional likelihood, 条件似然$ H# o: G% G& u
Conditional probability, 条件概率
; O0 W: |) n6 v* ^Conditionally linear, 依条件线性 c$ P) \; [: r3 ?8 \
Confidence interval, 置信区间$ N! x( {* Q6 l6 R
Confidence limit, 置信限: d+ S, _$ C* k) O
Confidence lower limit, 置信下限
' I" Z) p) d, v) Y+ DConfidence upper limit, 置信上限: N' Q/ p- \, X! T
Confirmatory Factor Analysis , 验证性因子分析
/ p w3 A+ Z+ C: o; }Confirmatory research, 证实性实验研究
" G: E) e) G2 E3 MConfounding factor, 混杂因素0 D9 H4 q) u+ v* v% K
Conjoint, 联合分析6 ]' O! Q6 y3 C- ?3 R0 d/ Z
Consistency, 相合性! M$ l2 Y! l c8 R2 s9 K) C
Consistency check, 一致性检验& z* O6 S2 t: G+ C9 Y
Consistent asymptotically normal estimate, 相合渐近正态估计
' b, o7 o U3 y& c6 x9 wConsistent estimate, 相合估计' |: v% @ F: h
Constrained nonlinear regression, 受约束非线性回归7 X& ~& r# }6 U; U* s" m9 T5 g
Constraint, 约束 r& p/ i/ Q0 h3 A
Contaminated distribution, 污染分布6 s! x8 G: f( r. H$ \5 z
Contaminated Gausssian, 污染高斯分布+ i8 Y! S5 Q7 E4 t& j" ^7 \
Contaminated normal distribution, 污染正态分布
/ z- N, y* @+ d. ~" O/ J7 ^* CContamination, 污染
4 i" r1 N. T5 U0 @& n' Z% G: CContamination model, 污染模型; B/ F) O/ }& T! R% ]# d
Contingency table, 列联表
+ S0 B( \. c1 v2 ]Contour, 边界线) z3 ]2 ]7 h) A |, o2 T+ T D
Contribution rate, 贡献率
" x0 u; D. f9 e6 S8 TControl, 对照
( I$ U, r; \: L. j, B0 J0 [9 @Controlled experiments, 对照实验( o0 D, Q3 O* U# y6 f
Conventional depth, 常规深度, [. e6 e0 f! {& Q* x
Convolution, 卷积
3 T" O5 B, _3 jCorrected factor, 校正因子& J& ^/ s: R+ k$ [: @
Corrected mean, 校正均值/ V t, i$ Y' A) a4 K6 B! \5 ?- X
Correction coefficient, 校正系数) o3 S7 w8 ?8 G5 Q& t, W8 m! `8 s
Correctness, 正确性" t0 {7 f+ R0 |6 ?. W. f7 Q
Correlation coefficient, 相关系数
, E2 F q$ p0 h4 o0 bCorrelation index, 相关指数
& b0 G. }! R% R* \2 H9 Z8 gCorrespondence, 对应
& k9 P8 A) l0 G2 ]+ c* gCounting, 计数( R2 P) S4 c. K
Counts, 计数/频数
/ O4 O4 r+ z; _' ?! OCovariance, 协方差2 K) L: t6 X" C
Covariant, 共变
) u& i: r; {9 [! L' ?4 h9 P* }Cox Regression, Cox回归( o+ z7 V6 |$ @4 j( e# b
Criteria for fitting, 拟合准则
. D6 Z- p7 P2 K$ U/ Q( M. ?Criteria of least squares, 最小二乘准则
& |+ Y: }, R) QCritical ratio, 临界比- X# J- M! c, C1 g2 H
Critical region, 拒绝域2 |6 k( a+ C3 |' }* @
Critical value, 临界值0 @, n; Y/ _3 a* p% `
Cross-over design, 交叉设计4 X" N4 P0 J y: K& G
Cross-section analysis, 横断面分析+ B9 e/ `, R; y
Cross-section survey, 横断面调查
! y' Q' U" y4 ?% e; G! g" WCrosstabs , 交叉表 6 N3 x0 B# W2 n0 f+ }! ~# `
Cross-tabulation table, 复合表
) z! } B9 c. j7 @2 E Z& yCube root, 立方根) Y2 j8 b) \) K% X: }3 A
Cumulative distribution function, 分布函数5 x8 `9 l8 {) h0 L/ {
Cumulative probability, 累计概率
$ l8 y! R& Q& s, bCurvature, 曲率/弯曲& Y+ a5 g# u; P$ ]% ~
Curvature, 曲率0 f6 D; k1 H, q# {( x2 d. j- L
Curve fit , 曲线拟和
: v5 B- B5 n5 W8 _ V7 Q" U. jCurve fitting, 曲线拟合
5 J$ ]8 k8 o: u) t7 E; zCurvilinear regression, 曲线回归1 W, k! ? @8 ~3 ], H/ D
Curvilinear relation, 曲线关系9 @6 V- j+ `9 z9 D
Cut-and-try method, 尝试法0 Z1 I# t# @- h) j# U* O6 ^) c4 s
Cycle, 周期
7 f G4 T. B, `' q3 BCyclist, 周期性1 R% G2 X$ z/ o
D test, D检验
, ?' D6 A+ ^& r7 i Y& w' @8 g/ mData acquisition, 资料收集
3 E2 T. J0 \5 U" K6 z1 B gData bank, 数据库+ Y4 j+ h; @$ G1 S; |7 E
Data capacity, 数据容量+ P+ z3 e. B5 Y
Data deficiencies, 数据缺乏5 C6 \" D& e/ } W
Data handling, 数据处理
, z* x( e* a9 R0 WData manipulation, 数据处理4 U- V* d) d" G
Data processing, 数据处理& h* V7 x5 s4 g1 C, h& P
Data reduction, 数据缩减$ K: L) R' `! f: w O
Data set, 数据集
3 ~* Y% a% z8 ^# D$ r/ cData sources, 数据来源1 `5 |# l5 Y1 ~0 s/ S% @* A3 V
Data transformation, 数据变换: \+ A. ]# h' n$ F
Data validity, 数据有效性* z% Y* M' B' V) f8 Q3 x9 P
Data-in, 数据输入
7 T C3 X# s8 R: d3 b$ PData-out, 数据输出$ R6 y# f8 K% [
Dead time, 停滞期
6 T. Q( ] L2 g7 t* i/ B* }6 l% \6 TDegree of freedom, 自由度7 I; G; P3 M2 p0 g5 Y4 @0 Y
Degree of precision, 精密度
+ C! a2 V. O j% I' F! WDegree of reliability, 可靠性程度$ \+ _+ X& l& |5 P2 ^) b3 _, t
Degression, 递减
' c8 \2 j; V5 a4 C9 [! qDensity function, 密度函数
1 N& E7 o- \% Y( y* cDensity of data points, 数据点的密度
6 k8 I8 B/ E5 D% ?% I# \- sDependent variable, 应变量/依变量/因变量
8 ?7 f, b/ Y) z! \- {Dependent variable, 因变量, e* _/ R( }5 ~
Depth, 深度
6 B) m( m, u H# W l8 vDerivative matrix, 导数矩阵% _# Y9 Z5 W; v1 G; |; N1 d
Derivative-free methods, 无导数方法5 Y% @# H8 k% x' I$ y: o; K* Z
Design, 设计
+ z1 F* i8 Z7 K( eDeterminacy, 确定性
# r. j6 R/ G l/ F* a$ bDeterminant, 行列式 k5 b5 o! b* @8 P g, G$ J d9 ?6 b
Determinant, 决定因素
: ?# H) h( \9 S4 q1 U2 ODeviation, 离差
1 ?! l0 v, [' Q, k( U9 X; @. mDeviation from average, 离均差
+ X9 _" u8 @& w$ l$ E; ~Diagnostic plot, 诊断图$ }& Z% i8 ?8 M+ B# u# J d
Dichotomous variable, 二分变量7 _7 g8 ^3 {( F9 }; T
Differential equation, 微分方程
. e' b( K' _1 n7 ]/ dDirect standardization, 直接标准化法
% p! A9 G8 |/ DDiscrete variable, 离散型变量
2 L( h' U+ v8 Q& B) k; m& QDISCRIMINANT, 判断 : o& P2 E8 u/ b2 K, O; R) P7 e
Discriminant analysis, 判别分析
" G7 `9 w; A0 Y$ M O1 k5 u8 K0 GDiscriminant coefficient, 判别系数. m' } Y8 ~9 Z: w& ~' ~2 Y
Discriminant function, 判别值
( Q3 v; K: G; P! S# ^) dDispersion, 散布/分散度
) p1 {; [ j& a. U2 n; O7 hDisproportional, 不成比例的
7 O. K6 s! K; Y3 u* UDisproportionate sub-class numbers, 不成比例次级组含量
% |0 X4 @/ w0 }9 t6 c4 Q& FDistribution free, 分布无关性/免分布
$ N* P3 N# ]# z! GDistribution shape, 分布形状+ R6 M2 b9 t! ^) z0 _
Distribution-free method, 任意分布法' d+ ? T7 r6 u2 p0 }& V2 Q
Distributive laws, 分配律
; b" ^3 _' p" r" YDisturbance, 随机扰动项
1 }! e& Y) z' a' j3 ADose response curve, 剂量反应曲线$ d- X! u7 r2 A1 ]- `& u/ ?: f+ F8 _
Double blind method, 双盲法
7 \7 }' b1 Y; _, Y/ |/ bDouble blind trial, 双盲试验
0 `' l$ ?# @& z. DDouble exponential distribution, 双指数分布
5 y1 o3 h3 W( P% z! V- fDouble logarithmic, 双对数
6 z$ j5 d" c- g3 A F' L$ BDownward rank, 降秩
7 ~% Q, a" a3 V4 H3 cDual-space plot, 对偶空间图
6 }) [' F2 h" FDUD, 无导数方法8 X# C: v6 {$ v: t( |* s+ L& o- U6 ^
Duncan's new multiple range method, 新复极差法/Duncan新法
8 C- U; i4 _8 _7 D! TEffect, 实验效应
7 {3 S2 O0 |) H4 U/ CEigenvalue, 特征值0 o0 X$ c5 h# B3 T8 r
Eigenvector, 特征向量
+ S/ L2 [9 k/ J! g/ fEllipse, 椭圆/ p w7 h- @/ T9 i& `
Empirical distribution, 经验分布& e6 _4 z5 n4 }
Empirical probability, 经验概率单位1 p! g. u$ {% `0 Z
Enumeration data, 计数资料
! ?( P) I( J; F kEqual sun-class number, 相等次级组含量( g5 k6 E& P/ e$ t
Equally likely, 等可能
4 M. d& C5 r+ v) p% xEquivariance, 同变性
$ c A% q$ u: s H; `$ EError, 误差/错误
+ H2 M3 h. e2 n4 pError of estimate, 估计误差/ U6 S$ ]9 @+ o" x5 p+ g% n
Error type I, 第一类错误7 n; d2 V3 w) u9 ~4 k% r" ]: s
Error type II, 第二类错误
% @. r8 t% ?" [- ?2 m. i: @+ cEstimand, 被估量
3 L1 s) w/ D" S. N! U; `! ^( TEstimated error mean squares, 估计误差均方
( L% k3 }/ I4 W. |Estimated error sum of squares, 估计误差平方和2 a, a m; h0 R) W' f, D! ]
Euclidean distance, 欧式距离, B/ z/ O* t; z# h5 P
Event, 事件7 N" {+ L0 o" {2 ]' n
Event, 事件( n+ @5 W: o5 S, d+ q5 z
Exceptional data point, 异常数据点
; ^$ _3 s% v7 g0 B# u& aExpectation plane, 期望平面
7 R& ]0 E$ p! Y' mExpectation surface, 期望曲面
- c# x- m5 l6 S: @3 \2 ]" aExpected values, 期望值
9 M- L/ Y5 ~+ }) p! |6 c) EExperiment, 实验
) \0 \( O" ^# eExperimental sampling, 试验抽样 g5 N) ? s; l* g1 k
Experimental unit, 试验单位
8 d8 r* [! L0 ?9 |( A$ D$ \Explanatory variable, 说明变量' c4 S( A( n" f6 q
Exploratory data analysis, 探索性数据分析, u1 R. A# q( l5 d
Explore Summarize, 探索-摘要
% L! f0 N/ ^. U* @2 |Exponential curve, 指数曲线
# X# q# L- X3 H9 ]Exponential growth, 指数式增长% X8 f2 K6 n& E" F
EXSMOOTH, 指数平滑方法
; h m- }$ F- d5 MExtended fit, 扩充拟合; M' U: o/ K7 x, Y5 o# h
Extra parameter, 附加参数, r, N" W H( x% C& ?
Extrapolation, 外推法" U) \# r; P5 i( Q6 c8 u
Extreme observation, 末端观测值# R7 _/ b* V0 C3 M6 r. S
Extremes, 极端值/极值/ C% K8 |! ] f/ A8 r7 P0 j5 n) v
F distribution, F分布) { P1 t4 b% u5 ~
F test, F检验8 E3 V7 _9 f6 v3 N
Factor, 因素/因子% F0 ?6 i4 X+ Z2 h2 k
Factor analysis, 因子分析
1 f6 ~" J- O1 B7 C4 l6 Y+ k4 x0 MFactor Analysis, 因子分析3 I- W) |/ ]# Y, G8 L+ I
Factor score, 因子得分
- m0 T. Z- ]8 R/ o+ {7 AFactorial, 阶乘
5 W0 F. z1 N$ F, `* ?Factorial design, 析因试验设计: s' u3 D4 B3 k$ v% }' @9 m7 T* y
False negative, 假阴性( y) K# i' v9 t& c T2 A1 a4 L$ ]
False negative error, 假阴性错误
5 h; ?+ P" b- V/ P0 F Q2 n( m/ k- \Family of distributions, 分布族5 `: E; ]' {" w% U$ V1 }* ^
Family of estimators, 估计量族
, ?" J$ k- C' Q+ f/ ]Fanning, 扇面
' f; g2 ~& w- Q: e1 E: y7 S% JFatality rate, 病死率) \8 h5 E1 L4 p$ j7 X
Field investigation, 现场调查
. o3 T4 ]# b9 p" y+ CField survey, 现场调查# [0 K/ N- ]/ `% y o0 E/ K; \6 `
Finite population, 有限总体! C* y' M( n) f& T+ x2 [: p2 @
Finite-sample, 有限样本* `6 F, o9 w- i* F! \( e# B$ Z
First derivative, 一阶导数
: l8 z/ H( m! N% XFirst principal component, 第一主成分( r/ `% `: n# {# a
First quartile, 第一四分位数
% A/ n1 P: @( w3 y% Z! FFisher information, 费雪信息量
+ b, M6 N, ~9 C+ S5 [# |" W+ I( HFitted value, 拟合值6 o, B: l4 J+ b+ z* a* X
Fitting a curve, 曲线拟合5 k5 M+ L2 w f/ F5 l) t9 v
Fixed base, 定基
0 Z" e& f6 L3 P. M+ Q+ N/ YFluctuation, 随机起伏* j {6 V5 M/ ]8 C/ x
Forecast, 预测: P! P6 R3 i, @# w
Four fold table, 四格表
+ G) w$ w N# t& h+ j% WFourth, 四分点
9 ^' ]. X7 V( nFraction blow, 左侧比率
. n& ~1 {. `6 F, ?: I5 zFractional error, 相对误差- S0 w W! G$ y# x
Frequency, 频率9 Z0 o: l0 t6 g9 e
Frequency polygon, 频数多边图
) D2 Q1 x3 ]4 R9 I6 }+ HFrontier point, 界限点- B$ I! x. |; m9 a& X
Function relationship, 泛函关系
& ]6 o% M! M# b9 C% _- ]2 C. hGamma distribution, 伽玛分布2 \ m7 w/ a: z) k$ w! U' _
Gauss increment, 高斯增量
' ~) i7 T Q9 tGaussian distribution, 高斯分布/正态分布/ u2 G( K( c. Z& F
Gauss-Newton increment, 高斯-牛顿增量+ Z& u* c4 m" y& o! q
General census, 全面普查, p9 H: Q) S. W0 I8 F
GENLOG (Generalized liner models), 广义线性模型 " w' T3 q5 \. O
Geometric mean, 几何平均数: r( {* M3 a- w% Z. G& l
Gini's mean difference, 基尼均差! _+ `. P% {1 f' n% z' J! F
GLM (General liner models), 一般线性模型 ; Z8 J4 P! v; J$ M- i' D1 e
Goodness of fit, 拟和优度/配合度 R! t# j g5 }9 i, q- Q
Gradient of determinant, 行列式的梯度
& E& t. [) W9 @6 }. SGraeco-Latin square, 希腊拉丁方3 N" Z! e( D9 P$ ~3 P
Grand mean, 总均值
v& D# Y2 s; D5 R) B3 u" N! Z/ dGross errors, 重大错误: H4 C7 a# M" _- ~. j3 `# p B
Gross-error sensitivity, 大错敏感度
" ]: c8 \$ U: c& ^0 P2 l7 FGroup averages, 分组平均 K2 r) F k Z: R* l
Grouped data, 分组资料 |/ l" c9 }) |& I9 M0 o8 o# v1 g
Guessed mean, 假定平均数
9 N6 q3 K2 v4 G! Q# V `Half-life, 半衰期
% c+ u1 l+ k% I5 _4 f2 H; I8 z7 ?Hampel M-estimators, 汉佩尔M估计量
7 B: _5 o% w6 j9 {- v" zHappenstance, 偶然事件) o* Q6 F* p, }, z3 ?1 i
Harmonic mean, 调和均数
5 N$ t: x" u0 ]. X" V0 h' q. ?4 dHazard function, 风险均数
/ H" g! W. S& J) F! y$ _6 [Hazard rate, 风险率$ e+ g6 H9 u8 r9 M" M
Heading, 标目
3 r1 D7 ^$ y: U U# bHeavy-tailed distribution, 重尾分布
; C. t9 M! E" f+ M( K1 t( w+ b& d: rHessian array, 海森立体阵2 D; }( Z: z- v1 s$ q
Heterogeneity, 不同质. r* d. q/ t& E; S7 |+ h; s! t
Heterogeneity of variance, 方差不齐
1 X+ g, k. w4 FHierarchical classification, 组内分组
: e; o0 e& d( LHierarchical clustering method, 系统聚类法7 w( ]1 [! l. h4 F5 W, f# g
High-leverage point, 高杠杆率点
+ x$ p o) ?$ [' p' ^HILOGLINEAR, 多维列联表的层次对数线性模型% ^# Z; Q0 N# U
Hinge, 折叶点1 x4 {% v7 e( t/ }& U: m
Histogram, 直方图/ @& M* W( e' ?/ H$ R$ c
Historical cohort study, 历史性队列研究 " G7 o$ Y/ ^- W. D3 |2 d
Holes, 空洞
5 }! d$ g3 z8 @ H+ X/ a: wHOMALS, 多重响应分析
$ C4 l2 C* ^! Q& q: } n9 IHomogeneity of variance, 方差齐性
4 t9 x; u3 _3 n2 U7 C0 X5 [7 `) sHomogeneity test, 齐性检验( u# }, \8 k9 E4 n
Huber M-estimators, 休伯M估计量7 V: T4 ~' a9 {/ d- |3 ~
Hyperbola, 双曲线
" _$ @) _+ @9 i+ Q3 n; r aHypothesis testing, 假设检验$ v* p$ v9 ~( m% g$ X0 r' X
Hypothetical universe, 假设总体$ g/ c' M3 J7 c$ n, y y
Impossible event, 不可能事件! y$ f$ c& m; w4 \8 ^
Independence, 独立性0 a" D, |. u" \
Independent variable, 自变量0 o `; U5 M) `6 X* c" H# O! `0 ^) |
Index, 指标/指数* ?: v5 F7 @) l) J
Indirect standardization, 间接标准化法
* c, w D' y8 r( UIndividual, 个体
4 V5 K" b: A6 J2 E. z2 FInference band, 推断带
7 H1 V5 H& M2 S; G' }) M4 C+ ]5 zInfinite population, 无限总体
7 Q4 d- v: w& ~, ?Infinitely great, 无穷大" v5 i: F6 u; x2 N. _ N& F
Infinitely small, 无穷小; Q- D9 P, }& M2 t
Influence curve, 影响曲线
1 _ @6 r2 A1 ^, fInformation capacity, 信息容量7 _8 Q6 F1 V2 |3 [( ]' n. ~, W
Initial condition, 初始条件
* V3 T0 M3 ~2 m9 Y, |; EInitial estimate, 初始估计值; [7 x( [+ c# z/ T' p- P- z7 `
Initial level, 最初水平% L8 H% V M- A e. f' C
Interaction, 交互作用$ v8 q" t5 ~$ \6 ]: j8 E. Q) p( |. c
Interaction terms, 交互作用项
5 M, L6 |& G7 J! x/ ]4 NIntercept, 截距7 y% P5 V* E/ v# |8 M
Interpolation, 内插法
/ a* L, b* P# R1 g. lInterquartile range, 四分位距
% Q' y* r& ]- S E5 S! i3 OInterval estimation, 区间估计% A, b/ v8 {" w: l
Intervals of equal probability, 等概率区间
0 \0 | U" C# u( M2 v2 U0 iIntrinsic curvature, 固有曲率
+ M' E+ j1 ^- H j" [' zInvariance, 不变性8 e+ [8 K8 h8 q3 H+ q" \0 q2 V
Inverse matrix, 逆矩阵% g& J8 w) n; K5 I% |0 X
Inverse probability, 逆概率! y. x! T4 u: e K
Inverse sine transformation, 反正弦变换9 A$ M! R! A; I0 H1 a& f4 w
Iteration, 迭代 & m) B& x: z* M- m `* x0 [" ]0 i5 h" i
Jacobian determinant, 雅可比行列式
) O$ ^ M) c4 r3 q1 }3 @6 c. bJoint distribution function, 分布函数
; M) h V# f! d4 A9 xJoint probability, 联合概率
; y6 V, ?5 H2 `0 c- k7 gJoint probability distribution, 联合概率分布
. E, Z x J1 ?, Q" g: zK means method, 逐步聚类法% b- y3 }3 ^$ _+ m/ k" K5 D
Kaplan-Meier, 评估事件的时间长度
9 N* u+ G, o2 V! h/ v& G9 T% |Kaplan-Merier chart, Kaplan-Merier图
- Y* w; j) [1 D1 U0 X; `+ fKendall's rank correlation, Kendall等级相关$ h7 I: \5 U3 X: I) F# o
Kinetic, 动力学5 w) o! a: X6 l$ L
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验, r+ o8 F% V/ Z( }2 F+ {" M4 C
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
1 z" B; ]: {* _2 zKurtosis, 峰度. }8 P# d9 T+ Q4 N. F1 f$ {
Lack of fit, 失拟# e6 W7 x5 r& z0 H4 m% E- v
Ladder of powers, 幂阶梯% a$ l4 i5 g+ y
Lag, 滞后
T( K8 S' f* D7 ?5 ~; [3 n( KLarge sample, 大样本5 l% x: i$ A C2 s2 I
Large sample test, 大样本检验
- t4 @+ @- ?; r9 ~# h9 h0 ?4 gLatin square, 拉丁方6 l8 y+ S7 g- f7 H! @
Latin square design, 拉丁方设计! d6 @+ @; k* s) W+ l7 D( A) c
Leakage, 泄漏
* n8 H: J- k; bLeast favorable configuration, 最不利构形# y7 ^3 K3 s6 w3 W
Least favorable distribution, 最不利分布
1 Z, m- _1 K; t1 u( l8 oLeast significant difference, 最小显著差法, Z m$ g8 o, j9 E' n
Least square method, 最小二乘法. y0 i. H* r4 p9 ^, M( J' J! m
Least-absolute-residuals estimates, 最小绝对残差估计
1 [. E+ n9 _& A, fLeast-absolute-residuals fit, 最小绝对残差拟合6 }/ X& L, m. Y7 n) p
Least-absolute-residuals line, 最小绝对残差线
6 K" F; `4 _9 k7 ~, B* LLegend, 图例
9 D6 h, \ e- }9 H5 B5 Y5 M) wL-estimator, L估计量 d" F( [$ s K- \8 E) A. a+ [2 b
L-estimator of location, 位置L估计量+ l' l# y7 v1 r7 B+ ^2 p9 P
L-estimator of scale, 尺度L估计量
9 }. @- i `9 a) G; ^. mLevel, 水平/ M" _% M) Z) Y7 O( w1 x
Life expectance, 预期期望寿命
$ g# [; N% P; K0 qLife table, 寿命表
9 V. t! O$ }9 Y4 {Life table method, 生命表法
2 l" ]/ E- r6 R# \" X- u0 T9 U+ fLight-tailed distribution, 轻尾分布
+ ^% T7 V* @# W- HLikelihood function, 似然函数6 ?' N$ Z9 r5 S% e
Likelihood ratio, 似然比
- K: l5 ^8 G7 F9 Y; l3 vline graph, 线图
, D; x9 ]8 Q/ Q# HLinear correlation, 直线相关9 A% y; z" j3 r; _( g
Linear equation, 线性方程; B/ @' ~. @) ?* ^% x6 c x
Linear programming, 线性规划
: A. h: A; ]) W$ G2 M* {% W; ?Linear regression, 直线回归, }/ H; B& ], C. ]
Linear Regression, 线性回归. r3 i- ?* c t5 W& y
Linear trend, 线性趋势
5 P+ D" N$ r/ ~, v* M" F* y% yLoading, 载荷 " H7 q4 ]3 w5 ]" O
Location and scale equivariance, 位置尺度同变性6 L/ c1 G p S Z
Location equivariance, 位置同变性! ~7 r( t( _: i w* D0 D0 I
Location invariance, 位置不变性
( y `1 U) H$ cLocation scale family, 位置尺度族
9 {# \: f2 N7 X, z; b3 H2 Q2 _/ qLog rank test, 时序检验
+ B4 B1 S. P$ |) k2 f& @Logarithmic curve, 对数曲线
6 c1 J' _( [+ z. ?Logarithmic normal distribution, 对数正态分布
9 t, E6 Z! Z' `$ {0 Y4 l" DLogarithmic scale, 对数尺度
# m. u1 `! \* Z; c" L/ v# z, j0 LLogarithmic transformation, 对数变换
! c4 G7 E6 \6 \Logic check, 逻辑检查% ]7 c/ Z7 J: `$ z. I
Logistic distribution, 逻辑斯特分布
0 R& P0 N+ ] M0 U) F9 Q& y0 q$ hLogit transformation, Logit转换
( r5 ~! A+ @& _. gLOGLINEAR, 多维列联表通用模型
" E( R! J- l: h, l" @3 L' _* n0 [Lognormal distribution, 对数正态分布
8 P5 ~6 C" w) |' \3 X, qLost function, 损失函数
% @# R. Z3 N2 I" V1 cLow correlation, 低度相关" d* `. k! f1 g
Lower limit, 下限
5 ^+ v0 S# E" f2 y! Y" W7 w3 XLowest-attained variance, 最小可达方差' p! T! c# }* P: [
LSD, 最小显著差法的简称
9 m# C8 e. A3 ]. |7 x' T. s3 DLurking variable, 潜在变量: `1 i( L) I9 x# \. k1 p/ X h& B
Main effect, 主效应8 g6 ~! d& C$ y9 I
Major heading, 主辞标目
8 {$ I$ N0 ~* }1 k k5 U+ yMarginal density function, 边缘密度函数; @6 m( W; \4 B. D2 l7 b$ h+ {2 R
Marginal probability, 边缘概率/ m7 n- q) y! ~4 q# \ X
Marginal probability distribution, 边缘概率分布
0 t# s" f2 {& C' z3 ^# I- WMatched data, 配对资料; x! @9 a" N! [0 C3 _& R
Matched distribution, 匹配过分布( w# c( t+ a9 [# B- G
Matching of distribution, 分布的匹配7 [" d+ ~; g3 W2 l* m! c
Matching of transformation, 变换的匹配
1 ^: ^. `3 V9 K: `( \Mathematical expectation, 数学期望
8 c1 O+ }/ m- s1 S6 [- ^Mathematical model, 数学模型! C+ H7 k9 M/ _& P, h1 C1 {) ]
Maximum L-estimator, 极大极小L 估计量0 q) S% m0 ?) d4 \0 O" S# }9 G
Maximum likelihood method, 最大似然法
: ?+ [" h6 [' qMean, 均数
$ ]. `# w7 f1 U4 D: k( I" UMean squares between groups, 组间均方0 E$ t- ?) m& C% d
Mean squares within group, 组内均方! _5 ?; S1 G- u' p' X' ^0 C5 Q. Y
Means (Compare means), 均值-均值比较. Z( x$ [" _, D* Y
Median, 中位数$ c7 K8 M5 v- o% x! e' X/ v
Median effective dose, 半数效量* L/ `9 D8 S* L
Median lethal dose, 半数致死量" S( G$ ^+ e& b6 d' d: N
Median polish, 中位数平滑
" M g) \+ g9 ]Median test, 中位数检验
5 j% | Y; F6 N# |6 c9 JMinimal sufficient statistic, 最小充分统计量. e6 @" ]" n' _
Minimum distance estimation, 最小距离估计
. j: R4 H0 H0 [: bMinimum effective dose, 最小有效量' u- @5 Y( i' T
Minimum lethal dose, 最小致死量$ C' r, _3 @" c2 n5 \% a
Minimum variance estimator, 最小方差估计量
/ a W2 e: R' k1 ~MINITAB, 统计软件包' W* t U1 n/ G
Minor heading, 宾词标目* m5 G. Y; G1 u
Missing data, 缺失值" H1 w4 p7 ?) l2 \
Model specification, 模型的确定
* U z8 A8 Q8 [( lModeling Statistics , 模型统计
% `+ Q1 I. o( AModels for outliers, 离群值模型
0 |9 T6 H7 T- XModifying the model, 模型的修正
- K0 y9 ?% s1 {6 k) f4 i# Q0 MModulus of continuity, 连续性模
% Z9 z7 {2 ^( I$ d) C$ o' IMorbidity, 发病率
; C( l5 S( }( h2 ]+ mMost favorable configuration, 最有利构形
/ t2 _$ g9 m' C4 ^' z: f& ~; KMultidimensional Scaling (ASCAL), 多维尺度/多维标度
3 u- n/ F4 D% O8 z1 i3 e# g# [Multinomial Logistic Regression , 多项逻辑斯蒂回归3 g9 `$ r+ i# C' f w9 W
Multiple comparison, 多重比较8 e' A$ {5 e: [8 L, h z0 O
Multiple correlation , 复相关 S" y# r5 G7 Z9 V* U+ W* }
Multiple covariance, 多元协方差
$ X: u4 A8 o5 h/ yMultiple linear regression, 多元线性回归( K; ^+ N. m( ]( O. V5 y
Multiple response , 多重选项
9 o5 B5 c& c* j& Y, S) W( ?1 [Multiple solutions, 多解
- h, E" q2 M9 ]" Q3 oMultiplication theorem, 乘法定理
& N/ Q ` f7 SMultiresponse, 多元响应! d& q# H2 Z1 H4 w( P _
Multi-stage sampling, 多阶段抽样
+ [: Q0 E( z! K4 Y4 B2 [, W D' C/ X" RMultivariate T distribution, 多元T分布
) f5 _5 f$ Z8 u: C6 t$ n; WMutual exclusive, 互不相容; ?* j+ F2 q6 m- e
Mutual independence, 互相独立
1 _! q9 Q3 C& v4 B6 @. \Natural boundary, 自然边界
4 x, g8 ?1 ~( E/ P1 w$ ENatural dead, 自然死亡1 i7 P" ?6 f% { l/ ]: [
Natural zero, 自然零, G- l7 F4 M8 r' H: F% P: K
Negative correlation, 负相关
" z4 l/ j: }+ q: I# F4 {- w, bNegative linear correlation, 负线性相关
6 a3 ]$ R3 {$ p: V1 U/ }Negatively skewed, 负偏
3 }# g1 g+ j* d% \: E" K: ZNewman-Keuls method, q检验" v n; f/ T, k+ z' J. h
NK method, q检验! B, r/ ^3 ]2 D1 A9 M
No statistical significance, 无统计意义
1 e: P; M% j& A, fNominal variable, 名义变量4 w* t9 {7 Q1 c
Nonconstancy of variability, 变异的非定常性: w! Z2 g: {: Z' x! v
Nonlinear regression, 非线性相关
0 \; F% Q2 r: f- u) VNonparametric statistics, 非参数统计
8 w% `6 b" t4 q' h: nNonparametric test, 非参数检验5 V2 \% R% s- P8 y3 K) ?2 T
Nonparametric tests, 非参数检验" Z" W- F9 g" q, c- e" P
Normal deviate, 正态离差
. G6 E& |! _- m) j7 \& D3 K7 nNormal distribution, 正态分布2 {& `: n. @; w- q5 x( Q0 J
Normal equation, 正规方程组
' d4 D2 Y5 X7 |" d6 f( X$ `Normal ranges, 正常范围& Z- ^7 s; r1 S, b
Normal value, 正常值* S; o% e- e/ E3 t1 v7 ?
Nuisance parameter, 多余参数/讨厌参数
8 M- m$ Z1 d1 p0 [# v6 vNull hypothesis, 无效假设
" a* z8 e, h& B) F( |" QNumerical variable, 数值变量; c0 ~4 F2 R2 v6 i- u' i
Objective function, 目标函数
# |$ V [ b; [ _7 g. l6 tObservation unit, 观察单位( L" n: l& n _0 n
Observed value, 观察值: y2 g5 O! P3 R
One sided test, 单侧检验5 p% p+ Q/ d8 ~ u- G: s z
One-way analysis of variance, 单因素方差分析6 B ]4 e. n: O3 q
Oneway ANOVA , 单因素方差分析9 B" V! k' y7 k8 P
Open sequential trial, 开放型序贯设计
1 U$ c8 r) m: tOptrim, 优切尾
$ H7 u- z+ X3 C& G5 A7 j0 XOptrim efficiency, 优切尾效率! q+ J& |; ^+ q2 C) ?
Order statistics, 顺序统计量7 ~. q, ^/ }! k+ P% E
Ordered categories, 有序分类
$ J0 `' r I) X( x5 f4 ]Ordinal logistic regression , 序数逻辑斯蒂回归! V, t: t8 ^/ v& E) P7 Y* h
Ordinal variable, 有序变量
; |/ w0 H0 H( Y+ {+ B8 O6 q; cOrthogonal basis, 正交基- x) L4 N5 ?) K0 B; c
Orthogonal design, 正交试验设计
: P4 E) e9 `/ g: hOrthogonality conditions, 正交条件
/ C' ^& W* s( d9 `4 u1 KORTHOPLAN, 正交设计
( G5 R6 |0 ]9 ^9 h* W) QOutlier cutoffs, 离群值截断点
3 }9 n( j( i% O9 h- E K, x4 ZOutliers, 极端值
$ R8 a7 i/ _3 L# {1 y; E. `OVERALS , 多组变量的非线性正规相关
: ]2 _3 v0 A+ k c; Q( ?- L% pOvershoot, 迭代过度
K* Q+ B: Q, kPaired design, 配对设计- a2 ]2 }* q& N* x o8 D
Paired sample, 配对样本
' v+ o. N0 A7 f4 ]Pairwise slopes, 成对斜率
+ v K% R ~# y" N7 UParabola, 抛物线
: q& i+ O7 | o4 U- pParallel tests, 平行试验3 e* L% T# w) ^/ p2 h- F1 |' @
Parameter, 参数# {8 H" f) t# r; F% \, C
Parametric statistics, 参数统计
) p6 e, V0 w7 g* ], s9 XParametric test, 参数检验
* I: D* m6 d$ ` t0 f5 g8 hPartial correlation, 偏相关
3 W& y% A% |8 G3 m) cPartial regression, 偏回归+ b- U5 C. j; [; k/ t
Partial sorting, 偏排序* z; n, G% s1 J" R% K" d
Partials residuals, 偏残差& \9 c- S$ R$ s; x
Pattern, 模式$ s2 H0 W6 @/ `1 l( r }1 W
Pearson curves, 皮尔逊曲线
9 n$ E7 g6 q5 g% o: ]9 x% ]# n1 r f9 YPeeling, 退层
- D; \0 G& ?# j! W% pPercent bar graph, 百分条形图& |2 z5 q2 Q, F* ?8 @7 p
Percentage, 百分比
- ~7 v/ |4 X! D8 a V; w/ E Q$ YPercentile, 百分位数9 t5 d: [8 A+ k& ?( W* N
Percentile curves, 百分位曲线
0 S1 G$ H/ G% XPeriodicity, 周期性
: h; w; X+ Q2 NPermutation, 排列
# X8 G/ J7 x" Q1 N" t1 J* |5 QP-estimator, P估计量
# X; p. y; t$ O: o' h# ^0 e6 yPie graph, 饼图2 q" V% G" z2 }' J5 C u ~
Pitman estimator, 皮特曼估计量; {1 \; N+ ?1 b- ?6 w6 J
Pivot, 枢轴量
+ z3 @7 n, _+ N( J5 ~5 T8 k" nPlanar, 平坦+ ~& C& R0 i: X( a* A/ y$ o: Z# A
Planar assumption, 平面的假设
% n: p- c3 v" n9 z" O* {& U; kPLANCARDS, 生成试验的计划卡
) W) \7 Q' I7 G& L+ k6 uPoint estimation, 点估计
" R/ N3 o9 N5 VPoisson distribution, 泊松分布! F+ e( `" h# v, P
Polishing, 平滑! F% z, v! `$ x5 c2 C- e% o6 N
Polled standard deviation, 合并标准差4 O1 ?. U9 I) `0 S
Polled variance, 合并方差
7 B" Z G& c% A$ L: W# APolygon, 多边图
( v7 ` r) F$ W# ^( A) z, sPolynomial, 多项式
+ a; c7 D3 z, c8 }! F7 cPolynomial curve, 多项式曲线5 u7 m1 I2 }; n
Population, 总体1 N i; s! z8 G, X. Y3 X$ J
Population attributable risk, 人群归因危险度
: Q; h! c& M" n9 i) O' BPositive correlation, 正相关
. z) o& F+ u. W! O. j% k8 _Positively skewed, 正偏
8 {5 i; j8 S3 h$ P. `) FPosterior distribution, 后验分布4 m: y& ]' I" d& |5 Q7 B4 g
Power of a test, 检验效能5 e( D+ Y% W& x" q9 T
Precision, 精密度
1 N! E2 v; J9 r0 s8 {1 d" o* N1 dPredicted value, 预测值
) J2 Y0 N$ k. e+ z! Q4 U7 QPreliminary analysis, 预备性分析+ R/ Y' [5 N* y) }: ?) V
Principal component analysis, 主成分分析
: B- t2 R% N1 s4 |/ z. X1 X, JPrior distribution, 先验分布$ z" l9 Q i% \. p
Prior probability, 先验概率
7 o5 J3 _* I. }8 H3 m8 v: aProbabilistic model, 概率模型) z4 c6 h- U% E5 e( Z" P
probability, 概率! F3 C O, z& @9 g# D% f4 X" A
Probability density, 概率密度
/ B9 s+ s& E; a) i6 a9 }Product moment, 乘积矩/协方差% Z- e- E9 x, W# w" p2 C
Profile trace, 截面迹图9 @; a% [2 d7 r6 Y% [
Proportion, 比/构成比$ Q) R$ K4 O) l% f" O' S
Proportion allocation in stratified random sampling, 按比例分层随机抽样; Q" v/ o& X( }5 \0 e4 u
Proportionate, 成比例
0 y# A) z7 @6 l& n% FProportionate sub-class numbers, 成比例次级组含量' T8 c7 S! r9 d
Prospective study, 前瞻性调查
5 k' c7 b" j4 EProximities, 亲近性 $ @& x( m5 Y' F4 d G
Pseudo F test, 近似F检验) @4 h7 B. X$ {+ o. f
Pseudo model, 近似模型
* V* B# F* {* G) Q0 q$ q7 {Pseudosigma, 伪标准差 d+ C; P$ ~$ l9 ], D* ]0 A
Purposive sampling, 有目的抽样9 l, U% J4 v2 N# n7 L: x: U' V
QR decomposition, QR分解5 }/ L( N1 J7 }: j% a8 \
Quadratic approximation, 二次近似
( F% d8 v' C% Y2 TQualitative classification, 属性分类
( Z, S @# N- N( |/ i8 ~Qualitative method, 定性方法; H: v/ c. P0 k0 c# k& A9 n9 a! ^ R
Quantile-quantile plot, 分位数-分位数图/Q-Q图
: y: \) c- U" I) E, h1 K; dQuantitative analysis, 定量分析; ?' P i$ D/ g( \
Quartile, 四分位数( {2 F+ O5 i# h0 X
Quick Cluster, 快速聚类+ @6 ]2 F _& e0 H, J0 r5 @" M/ `" q7 D, h
Radix sort, 基数排序
: z* y& _, s. l( z" B0 A0 l0 I5 dRandom allocation, 随机化分组
6 G( @+ E( c5 X4 t' Y5 K% b( uRandom blocks design, 随机区组设计
7 B0 ]5 r8 {& i+ DRandom event, 随机事件9 U1 w- j+ s2 u. u2 o
Randomization, 随机化
1 q" x6 B D. K9 S% yRange, 极差/全距
! C3 B' S5 q/ I+ BRank correlation, 等级相关8 m6 t9 J" u2 S5 T, p
Rank sum test, 秩和检验) V& p7 H5 P/ A& F+ E* y& @
Rank test, 秩检验
7 u8 e% V. h+ B( _3 x! m$ d& g9 ?' |Ranked data, 等级资料
8 p! Q, b4 f$ F- o1 d8 gRate, 比率
& x& |3 F) {9 A) v* ], uRatio, 比例* z, g7 u' H& W. H+ N
Raw data, 原始资料8 |; W1 U: f1 i$ g2 J) c! |( x
Raw residual, 原始残差
) G) \, R5 m: n; U; z% h0 b. {Rayleigh's test, 雷氏检验3 e8 ~: n3 }. b0 {0 e6 W) m& I( h
Rayleigh's Z, 雷氏Z值
3 W! n( q5 j5 `Reciprocal, 倒数 S& A. `5 ^1 C
Reciprocal transformation, 倒数变换
( s& S3 t& E, J8 y- RRecording, 记录
, v. S1 b0 }5 R. tRedescending estimators, 回降估计量2 N/ n1 j4 W) ?
Reducing dimensions, 降维) T0 n9 P/ w5 k& D E
Re-expression, 重新表达
; [$ m3 q# a* F9 o. E/ rReference set, 标准组( y. p# B- J4 U/ W. ^, d
Region of acceptance, 接受域
2 O5 @. k9 o- _5 v7 _( E- w. W- dRegression coefficient, 回归系数; H1 g9 v8 [. n5 l
Regression sum of square, 回归平方和
J+ `% c+ a- K) J4 h4 |Rejection point, 拒绝点 e( h7 W" H! C/ p5 b6 q) } k
Relative dispersion, 相对离散度, H: f! n. z9 |3 k' F5 s. `" N, r
Relative number, 相对数
9 H9 ]# S1 M3 W8 w$ B" d6 ]$ Y# pReliability, 可靠性
6 |7 e h9 L3 M1 C) OReparametrization, 重新设置参数* f1 B, D: e4 R$ M, e/ v0 o
Replication, 重复
- o4 G+ S' T- V$ H% }Report Summaries, 报告摘要. V! [6 {# t2 |7 J3 b' d7 n
Residual sum of square, 剩余平方和" U, A( m3 A/ m7 R
Resistance, 耐抗性
8 M' W9 Z7 I# `1 ~' g. K! FResistant line, 耐抗线
& z- s) P7 B; D# T1 OResistant technique, 耐抗技术, ?0 I3 |5 S$ D
R-estimator of location, 位置R估计量6 k$ c; X4 l/ Q9 Q
R-estimator of scale, 尺度R估计量
m- P. H2 v, v" n7 N) ZRetrospective study, 回顾性调查( W) N! R8 _; z" Y' ~+ l3 t: w
Ridge trace, 岭迹2 E" Q# U. H- Y
Ridit analysis, Ridit分析9 f3 u( i) U) n( U9 I5 x# i
Rotation, 旋转, ^% e% Q O/ ?3 M
Rounding, 舍入' [' H6 w* z% g0 u; u
Row, 行1 }3 s5 l6 h/ e3 {+ z9 R
Row effects, 行效应* q) T" N7 }/ A8 d
Row factor, 行因素
6 V# P4 A) K- G7 A; WRXC table, RXC表7 C, _' b. {6 Y/ ^1 C
Sample, 样本
5 F; [3 R% T0 qSample regression coefficient, 样本回归系数- h; P8 l; D; D9 `3 {% f7 }+ E2 q
Sample size, 样本量, d7 t, N+ I! d. r6 B# G$ N: p. B
Sample standard deviation, 样本标准差# t. L7 S G0 K( F
Sampling error, 抽样误差3 x1 _+ X% Z# M% K
SAS(Statistical analysis system ), SAS统计软件包
1 @. D3 h0 V4 h( k- ?# oScale, 尺度/量表0 n+ v" E3 [' i: \6 p+ `! Q
Scatter diagram, 散点图6 g% y" ?- Q! h9 H
Schematic plot, 示意图/简图" q+ e( J2 C- K/ w, X( L
Score test, 计分检验" v. {8 M$ k1 p# f$ a: K
Screening, 筛检
7 E: p$ [' h. O' Q& Q+ B6 m+ cSEASON, 季节分析 % J. }5 `" @4 ~$ }
Second derivative, 二阶导数9 R) k6 C* `" h( S" ^9 g
Second principal component, 第二主成分- d( Z/ _# Z3 d
SEM (Structural equation modeling), 结构化方程模型
; T0 T+ L4 t2 w9 X d5 l, xSemi-logarithmic graph, 半对数图
. L0 q- N5 K# I- bSemi-logarithmic paper, 半对数格纸9 W- Y$ A* K% B( e; ^
Sensitivity curve, 敏感度曲线1 H* @* J X+ x1 K2 N+ S5 a
Sequential analysis, 贯序分析9 k7 D" V0 e7 X& _$ E
Sequential data set, 顺序数据集
) |* P# Q4 F5 k: ]Sequential design, 贯序设计
5 b% G6 r3 y. F& n; M2 H4 F, mSequential method, 贯序法1 w3 c8 r3 [) P6 R$ B% b
Sequential test, 贯序检验法8 c9 \+ U. K7 e
Serial tests, 系列试验+ M+ W4 O8 {* m9 U, H. }
Short-cut method, 简捷法 $ I c; L/ y* J/ {2 ]
Sigmoid curve, S形曲线
* A) |4 i# @# h( d" g+ U* D# OSign function, 正负号函数2 y/ M: V4 h3 w) c. x
Sign test, 符号检验8 f, W1 o- J9 }2 j6 J
Signed rank, 符号秩
% S' W& \; f3 hSignificance test, 显著性检验
; D2 r& X8 `7 ]$ w( ^& R' wSignificant figure, 有效数字- L8 l( [0 a) P, T+ }
Simple cluster sampling, 简单整群抽样/ l* {5 `) I% e8 \2 a. z
Simple correlation, 简单相关0 O7 y+ L* t7 i4 j+ A
Simple random sampling, 简单随机抽样7 Z% H) }, x) ^: k2 h
Simple regression, 简单回归9 q+ w/ q& C2 ?$ U# X: k
simple table, 简单表6 s! L3 z5 k9 X7 F) z g
Sine estimator, 正弦估计量
' f8 c5 \* r9 y/ _8 lSingle-valued estimate, 单值估计
4 {4 R/ r' T' ]1 j cSingular matrix, 奇异矩阵$ o5 \1 [" w4 F, \* q, t
Skewed distribution, 偏斜分布# u8 G6 z6 \9 b8 K' k7 m
Skewness, 偏度
/ S, N) _- e, f( H# U$ ]0 M' N4 FSlash distribution, 斜线分布+ G. u! ]6 d, U+ n t6 k6 X2 ~! g3 i
Slope, 斜率& z" |4 Q1 D2 p' d
Smirnov test, 斯米尔诺夫检验
# B: o+ j; x- \: WSource of variation, 变异来源
6 x9 d. Y* Q! }3 X: WSpearman rank correlation, 斯皮尔曼等级相关
1 ?+ I% z \* u: a; nSpecific factor, 特殊因子
. l( |/ x7 j' O( g8 O! p3 w8 U+ VSpecific factor variance, 特殊因子方差3 a( P) t' o% U. f+ F" @7 d! b; p
Spectra , 频谱
3 G; X+ P. }; [) `Spherical distribution, 球型正态分布
4 N" a; A5 k5 U, p ISpread, 展布
5 r. n- M! S" }+ ~2 D, \SPSS(Statistical package for the social science), SPSS统计软件包
' W- @2 r( X: o' I. b9 JSpurious correlation, 假性相关
5 k' g. u( r$ A+ F+ k3 H6 xSquare root transformation, 平方根变换6 B! Z( t5 h; k
Stabilizing variance, 稳定方差0 ]- o E" k/ f; G
Standard deviation, 标准差
$ g8 R$ s+ c. h4 a1 rStandard error, 标准误
& k* E# A+ V2 u! d) sStandard error of difference, 差别的标准误8 p5 _& V# G5 w$ Z- b& y' Y
Standard error of estimate, 标准估计误差
; J. |# ^7 t3 Z* ]Standard error of rate, 率的标准误7 Y- L; ~6 z' f( v
Standard normal distribution, 标准正态分布, q( |% v# C6 U2 h& {7 `* v
Standardization, 标准化% ^ `$ G9 [# n8 p1 y
Starting value, 起始值3 s) o9 `8 l* K& n, ^5 B
Statistic, 统计量
0 {9 U0 c6 d6 q+ \1 i1 Y! o2 X& L; xStatistical control, 统计控制
* p- j( G8 @4 |& vStatistical graph, 统计图" W/ P. Q! D5 Z, z2 `! E
Statistical inference, 统计推断% ^) Q' ]4 f6 G8 V5 ]1 s
Statistical table, 统计表
# s& l) b- ?/ s3 E/ ]$ |Steepest descent, 最速下降法6 i% p: t! E0 \
Stem and leaf display, 茎叶图9 [0 ~$ x' {9 N/ j+ J2 U
Step factor, 步长因子
/ n: f' M% a* J0 i0 t7 W8 nStepwise regression, 逐步回归
5 u+ G6 Q) J/ g* P( V- W! BStorage, 存( m- x* B. D3 T1 X
Strata, 层（复数）( O+ m/ J* }/ w( u
Stratified sampling, 分层抽样9 i! B& w, h( V
Stratified sampling, 分层抽样# B4 q& \7 m7 x; R- E3 w# I; ]
Strength, 强度
' a( z$ X) G' ~6 M, hStringency, 严密性! h' C. q: d" h, E# l" S% Y4 j/ e$ |
Structural relationship, 结构关系, h, G- _2 X/ m- T
Studentized residual, 学生化残差/t化残差
5 [1 S% M R; o( }4 M; W' ZSub-class numbers, 次级组含量6 @0 i4 n) o8 ^* ?
Subdividing, 分割
. l. h! ^. ~' { a) e& P5 y2 z2 ?Sufficient statistic, 充分统计量
" j0 X* ?& C d F* z3 qSum of products, 积和
7 O! G, W7 f$ x7 ]+ f2 lSum of squares, 离差平方和4 s# ]# V" D; d, C7 q2 W
Sum of squares about regression, 回归平方和
* T/ U4 j( ~) |+ H+ O, p9 W# ISum of squares between groups, 组间平方和
5 g. a: U: W: DSum of squares of partial regression, 偏回归平方和% s/ j7 O6 }: F, c, z- y
Sure event, 必然事件+ }& e$ }$ q! Z# d
Survey, 调查+ i/ m& S; C) b3 G' A* o
Survival, 生存分析: t0 f$ _% D' G" R
Survival rate, 生存率# F" u; C- Y& p3 o& b W) G$ A3 c
Suspended root gram, 悬吊根图
+ V) { p* f& d. e. ESymmetry, 对称) m, ~, ^9 l L" Y+ A
Systematic error, 系统误差$ ?, [% J+ O! d/ L6 ~8 V& l$ @3 t
Systematic sampling, 系统抽样
. l2 c7 L# W( pTags, 标签: s9 x3 @ E" h1 N
Tail area, 尾部面积4 p3 Y0 U8 n H& F8 R/ C
Tail length, 尾长; U) C2 r. s5 V S# g0 J
Tail weight, 尾重/ T1 u" r2 {" ^- a
Tangent line, 切线
* l) O4 H4 f( m% z8 F" s6 y! nTarget distribution, 目标分布
0 Y5 `9 j6 p/ h0 r! J7 {' {& Z4 aTaylor series, 泰勒级数1 F4 h/ N, t! s9 `. ]& T& C0 D
Tendency of dispersion, 离散趋势' l% B! l% l4 L ~( l
Testing of hypotheses, 假设检验* e% B, m1 w: O3 O2 b. k9 P
Theoretical frequency, 理论频数
. N# v, Y4 g0 Y' V1 aTime series, 时间序列
/ `3 S9 @; a1 m1 n* q/ A, WTolerance interval, 容忍区间
! ]) g3 a" o) Z9 V6 cTolerance lower limit, 容忍下限
9 J' I. V' ?3 E6 x' O5 CTolerance upper limit, 容忍上限# ~4 R4 [* N0 a( x! U" K, o% ~
Torsion, 扰率
# z, f# j; Q) n: S/ pTotal sum of square, 总平方和! N6 c( R0 J1 d5 n% e
Total variation, 总变异$ v8 S+ ^1 A( ~7 z& ?
Transformation, 转换
6 {* s8 [4 M0 }7 X7 hTreatment, 处理
% O; G. x Q% J& d# fTrend, 趋势
% N$ Q7 F6 r3 a0 BTrend of percentage, 百分比趋势: ^ N+ \" T' \8 l) a8 n. I4 Z3 }
Trial, 试验
5 t' s4 b, F+ H- f4 N" {Trial and error method, 试错法& i5 g2 B/ q k1 U \. s! G; E+ U
Tuning constant, 细调常数# w+ ^( y' m; }# }
Two sided test, 双向检验+ d1 C; A, w. i( a. J
Two-stage least squares, 二阶最小平方3 b2 X* G# U% a1 P% m1 u' Q' g
Two-stage sampling, 二阶段抽样* q9 x! I @8 n) V$ B
Two-tailed test, 双侧检验* S6 l4 ]9 `: d, e
Two-way analysis of variance, 双因素方差分析6 S( ^. m- T- O2 w2 M! ]' f
Two-way table, 双向表
; s( W' y- i8 f1 m; G2 n5 ?Type I error, 一类错误/α错误
i* G9 o" G. I. W" z9 JType II error, 二类错误/β错误8 r" L) S- w' i( j
UMVU, 方差一致最小无偏估计简称
1 ]% t0 e1 l) O; x# dUnbiased estimate, 无偏估计
: t; M0 M7 e' p! O' j4 JUnconstrained nonlinear regression , 无约束非线性回归
. R" {9 _7 Y: {: K7 V, XUnequal subclass number, 不等次级组含量
3 h) u9 K7 g, B& G5 h7 v" `; fUngrouped data, 不分组资料
/ U5 t/ t+ _) s% I$ [4 `Uniform coordinate, 均匀坐标
5 B2 d5 u3 V1 a7 lUniform distribution, 均匀分布
" F; t: F! o3 [8 E3 iUniformly minimum variance unbiased estimate, 方差一致最小无偏估计+ ^7 H# v' P; `$ ]( Z0 b
Unit, 单元
6 z' a2 v& d% N; m8 lUnordered categories, 无序分类+ E/ A8 \& M0 P5 w( R" i7 d
Upper limit, 上限3 ^* q1 h$ Z0 A' ?
Upward rank, 升秩
( B4 r6 e% V9 _0 X/ j6 k$ [Vague concept, 模糊概念/ \2 J" Z6 b5 R$ R9 ]+ v- S
Validity, 有效性5 M. b; C9 U2 \! H- ~* V
VARCOMP (Variance component estimation), 方差元素估计- g i' L7 w( Y- s
Variability, 变异性
( d9 c, p: Z1 `' z4 XVariable, 变量
2 i% p: | E: s( ^+ fVariance, 方差
9 [9 ~" ] M7 g3 Q) k QVariation, 变异
1 t6 I* l" N \3 c! Q, NVarimax orthogonal rotation, 方差最大正交旋转
3 |3 j4 @& }% c4 G( L$ ~+ w; p) hVolume of distribution, 容积, c3 F' _8 ^: ^' @$ C( G6 a
W test, W检验% {, h5 W* _! }8 _
Weibull distribution, 威布尔分布
' v6 h0 g' |9 S( i& J6 _: s+ \* j/ VWeight, 权数) d1 h0 l: Q1 o. d* z( I" _* \
Weighted Chi-square test, 加权卡方检验/Cochran检验% r; r o0 x$ ~& D2 ^( @
Weighted linear regression method, 加权直线回归
6 n- u+ n0 z; cWeighted mean, 加权平均数
) {* H9 V* V( ]1 u$ q L4 M0 r6 PWeighted mean square, 加权平均方差: H# h" f1 n8 o" a( Z7 Z) L
Weighted sum of square, 加权平方和" U0 R* Z+ N7 Y
Weighting coefficient, 权重系数
V9 L' i- U! `Weighting method, 加权法 , }4 P4 X, G7 [, w }
W-estimation, W估计量: S) `6 I; y1 d. L) ]5 K8 k
W-estimation of location, 位置W估计量
2 a( b; X' a- J1 mWidth, 宽度
+ y- j2 B) F0 [9 v$ r9 ^/ r/ D9 a( g4 RWilcoxon paired test, 威斯康星配对法/配对符号秩和检验" a7 k$ f$ ~ x* o0 _
Wild point, 野点/狂点
4 i4 \2 }( W% S' u9 k8 b+ p& H% P7 QWild value, 野值/狂值
( U2 D, `: y* WWinsorized mean, 缩尾均值 z7 J0 p; V; X0 I6 s' S
Withdraw, 失访
3 i; B8 V) H4 `! A6 Z5 oYouden's index, 尤登指数
; s% j" q7 \( x3 m- b) QZ test, Z检验* \( F1 _6 ^% v9 j" [
Zero correlation, 零相关
0 C8 n8 b9 \9 L+ P$ ?5 R. FZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
