|
|
Absolute deviation, 绝对离差
; g4 q2 k7 Y3 d" b7 UAbsolute number, 绝对数, \; k7 u T: a' U: g; X
Absolute residuals, 绝对残差' d$ t4 `0 [: E! k# a2 `7 {) S
Acceleration array, 加速度立体阵' p9 M3 t. x. X2 t8 r
Acceleration in an arbitrary direction, 任意方向上的加速度# v, c! k0 i# g6 n# O. e5 P( K
Acceleration normal, 法向加速度
3 y! s4 ^3 i. ^ Y. U0 g& [Acceleration space dimension, 加速度空间的维数" K1 H* [; V6 O5 e
Acceleration tangential, 切向加速度
H6 f% p! ]. G+ u; z8 WAcceleration vector, 加速度向量+ D S8 P& t+ P" C& T+ _
Acceptable hypothesis, 可接受假设; Y2 j! j8 H; I! ]# ]$ J5 j
Accumulation, 累积
# A( [: Q( {, T3 i. T' fAccuracy, 准确度$ ?: ?7 X. a" M5 g; z
Actual frequency, 实际频数* b/ L" X9 u: S8 f& o/ l
Adaptive estimator, 自适应估计量
3 ^1 U) s8 [% a, a( q! `1 p6 U# M2 {Addition, 相加$ E1 M# a9 G6 U# r3 r6 y
Addition theorem, 加法定理
, J$ D# Q- Z* a$ M( G/ L' t9 GAdditivity, 可加性
( Q3 f% C! q- m$ p0 R5 W- Y6 OAdjusted rate, 调整率# _/ v; \, U t0 x
Adjusted value, 校正值( x* Z; ~! p/ ^" T
Admissible error, 容许误差# B* s8 \8 P" E6 Z. X. X0 W' N
Aggregation, 聚集性
/ P3 N9 M! m6 k+ L5 pAlternative hypothesis, 备择假设
+ |8 _8 G( C1 o! e5 rAmong groups, 组间
; t f* h* s. ?4 I9 ?3 `: GAmounts, 总量
" U/ o" k+ l1 JAnalysis of correlation, 相关分析
# B2 m$ z. J3 v. k9 B2 cAnalysis of covariance, 协方差分析; r1 X4 `4 D" u
Analysis of regression, 回归分析3 H$ X% ^9 p( ~. o
Analysis of time series, 时间序列分析: L8 ^8 j( V ]# d
Analysis of variance, 方差分析
2 \, x* Q: y0 x3 oAngular transformation, 角转换
9 w8 w6 C3 O+ d6 t0 t, |, A* EANOVA （analysis of variance）, 方差分析
7 e" r9 Y/ R, |( D% t' D1 rANOVA Models, 方差分析模型
0 y2 F" `* B2 f$ z5 DArcing, 弧/弧旋+ r6 @3 l5 P6 k$ O) z( [, N. K
Arcsine transformation, 反正弦变换& e* z' M- M+ @9 u
Area under the curve, 曲线面积
6 r& m- [- c4 ]. p( ~" J( gAREG , 评估从一个时间点到下一个时间点回归相关时的误差 5 a0 Z! b2 m# V7 u4 g+ r( v
ARIMA, 季节和非季节性单变量模型的极大似然估计
' H o' v. I- D! ?: F# G3 i, CArithmetic grid paper, 算术格纸
) W$ P2 P7 |$ A7 _; Z, ^9 rArithmetic mean, 算术平均数9 ]2 K, a. @1 ~
Arrhenius relation, 艾恩尼斯关系
" G' w8 @2 P, N |1 ~" v! FAssessing fit, 拟合的评估/ p/ y V R% g- Z( s
Associative laws, 结合律
" ?' r# H0 \$ T. Q0 E; [5 i/ xAsymmetric distribution, 非对称分布
3 |; ~5 m) Y( t) fAsymptotic bias, 渐近偏倚
5 t1 V2 f! t- W, c: W4 f) eAsymptotic efficiency, 渐近效率- b( E7 v+ b4 [% h
Asymptotic variance, 渐近方差
6 P5 x, E( h% Z4 T3 j! e- `8 d S( Z0 aAttributable risk, 归因危险度6 e# I p" E% b3 Y# x" ]
Attribute data, 属性资料
: f9 x' C4 T3 m: YAttribution, 属性
# H! P, R- ] N7 ~Autocorrelation, 自相关
/ G; v" @7 F, s4 a( R6 hAutocorrelation of residuals, 残差的自相关
! G1 c' c3 s: L4 J' T1 Q7 rAverage, 平均数! \5 j) E. l) k# [, ?
Average confidence interval length, 平均置信区间长度2 b! Z$ W1 T& M
Average growth rate, 平均增长率* z: ^5 _! A4 `5 M( m$ `
Bar chart, 条形图
3 N( e i9 R) F( c, W5 M, d% `Bar graph, 条形图& f+ b; I' i! o$ r q0 l
Base period, 基期
3 S, g9 ~3 s ]7 jBayes' theorem , Bayes定理$ k9 b9 L4 u B' h; E2 x+ q7 w
Bell-shaped curve, 钟形曲线/ S/ N$ H# Q" ]. e- X
Bernoulli distribution, 伯努力分布
2 ~6 n; W; R8 o+ I/ s$ |1 j: iBest-trim estimator, 最好切尾估计量7 W B& n7 x, P/ e
Bias, 偏性
' ?" G6 s) [2 \Binary logistic regression, 二元逻辑斯蒂回归
% ^5 F: E9 M& q$ z* f( gBinomial distribution, 二项分布
; O7 ^$ r$ ?* c C8 IBisquare, 双平方) A+ E8 b; T3 _
Bivariate Correlate, 二变量相关- j, ]: W# h4 k- \9 Y. g) {
Bivariate normal distribution, 双变量正态分布
1 X1 D! F3 M( P( Z3 u& Z5 ?0 O+ M+ f' _Bivariate normal population, 双变量正态总体
+ H- W7 C0 a9 `0 ?Biweight interval, 双权区间
# H# R% t+ F5 F2 X( iBiweight M-estimator, 双权M估计量
9 m( k7 K6 N) K+ ~9 \2 HBlock, 区组/配伍组" l" k$ ^( {! E d4 l/ |" {# m, a" n+ y
BMDP(Biomedical computer programs), BMDP统计软件包) Y$ A$ v7 z3 Q
Boxplots, 箱线图/箱尾图
% h2 l, V( n7 L* PBreakdown bound, 崩溃界/崩溃点
% S* s2 L8 j* J5 eCanonical correlation, 典型相关; e! O6 s" n M1 z! L5 I
Caption, 纵标目
! o1 X$ g# R0 G) _% E& `/ nCase-control study, 病例对照研究
% t/ m# u D! w- O' Z% E6 x1 h rCategorical variable, 分类变量
& i; Y# ]$ e, Q( L3 ECatenary, 悬链线
) V- [. l+ {0 M5 z O" gCauchy distribution, 柯西分布- n" \5 ]7 U8 i6 d
Cause-and-effect relationship, 因果关系
1 _7 L0 e9 ^5 s7 \: z4 q0 YCell, 单元6 r4 |0 h0 D6 o" ^! I6 ?# M" m
Censoring, 终检0 T9 @. g3 ?) b6 |& D6 c# x
Center of symmetry, 对称中心
! E1 P. H4 n; I1 K" q+ f. v9 WCentering and scaling, 中心化和定标; h# X. h5 B; ^- g! v2 q. \6 R T
Central tendency, 集中趋势
9 k5 \* R# L9 V5 V9 \ ICentral value, 中心值
* |9 o4 k( h1 |CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
* M: F" w; P" B, ~% `% m0 KChance, 机遇
" f" R4 }, ? V7 t; t& e% p% D, yChance error, 随机误差. y5 a. k. S3 `$ b' O/ H% Q4 U, f
Chance variable, 随机变量
7 N. R5 t- q7 X% GCharacteristic equation, 特征方程
* _; o& t$ j3 S0 E) X4 kCharacteristic root, 特征根& j+ G* F. ?1 |4 @2 U/ c
Characteristic vector, 特征向量# Q' q6 F# A" H" W1 H* W0 _
Chebshev criterion of fit, 拟合的切比雪夫准则
( F; y _+ R3 T+ E# K# k9 ^* v( bChernoff faces, 切尔诺夫脸谱图
$ Y4 d8 ?1 s; \Chi-square test, 卡方检验/χ2检验
/ i! `. a6 @9 U! M% \# y4 k( BCholeskey decomposition, 乔洛斯基分解( {6 }; j$ F. v
Circle chart, 圆图 ( x X5 L3 V$ W& T* B9 f' |
Class interval, 组距
' o3 h" \8 y0 f2 a2 W' g8 dClass mid-value, 组中值. a5 r, w8 D* m* h
Class upper limit, 组上限3 J$ E% V; G. _% m9 k1 E- N
Classified variable, 分类变量
( `" r4 T R* ]1 t6 P, e/ kCluster analysis, 聚类分析# p# k! a) w. b$ ^# i
Cluster sampling, 整群抽样
1 C' B# o- M0 P) O. R8 V _Code, 代码
/ G5 t1 }+ U- Z+ v. e3 X! v* F MCoded data, 编码数据5 u% \6 a% U: m% k4 \+ h
Coding, 编码 O3 \. N, c O6 W7 K; m* ?' f' l. Y
Coefficient of contingency, 列联系数
: q$ f" H7 j5 u5 _1 r- V3 OCoefficient of determination, 决定系数
, _( T8 B2 Z5 x) ZCoefficient of multiple correlation, 多重相关系数' L' v: m, u! ]9 m
Coefficient of partial correlation, 偏相关系数+ A5 G" y% F8 U7 h' o
Coefficient of production-moment correlation, 积差相关系数
6 H1 h$ s: E2 J' g! TCoefficient of rank correlation, 等级相关系数
. W8 b$ E* u8 \. lCoefficient of regression, 回归系数: S6 V, N" w! Y
Coefficient of skewness, 偏度系数
8 i& o. F5 l0 zCoefficient of variation, 变异系数
+ v" P/ V! w, s7 |, e2 _, JCohort study, 队列研究
. o4 J* u2 \3 P) Q. X1 c7 zColumn, 列, @3 F* p9 u6 l* d N
Column effect, 列效应
" P* U+ n' c, q9 h( }Column factor, 列因素3 Z- E w, ^0 L+ A" `4 \! B* b
Combination pool, 合并
0 I' w- Q% A( `% j, N0 Y) yCombinative table, 组合表
6 ^" }! t0 r# {, HCommon factor, 共性因子9 H4 Q& X6 x& F: [# Q+ Z
Common regression coefficient, 公共回归系数8 ]( l6 w3 @* q1 i' K& E& A/ t
Common value, 共同值
, m- _1 ^. C% ICommon variance, 公共方差" K' P5 W' {; {, r
Common variation, 公共变异
- q% O9 T, g8 Z' _7 oCommunality variance, 共性方差
) g) B( ~+ p0 h7 y( l* E5 v3 pComparability, 可比性, I& ^, k1 d& g9 i
Comparison of bathes, 批比较
+ b) H% ~ ]3 ?Comparison value, 比较值
8 @6 W4 [3 ^& \4 a- V9 ?Compartment model, 分部模型
, |- o" P" l" Z( @: z# wCompassion, 伸缩
3 o$ L. ]; G+ P7 R4 S3 LComplement of an event, 补事件) I" |3 u5 T0 x; a# f, @7 B; S/ g
Complete association, 完全正相关* b) G( @0 u+ `* x( V
Complete dissociation, 完全不相关, `$ r. ^7 x s
Complete statistics, 完备统计量: f& T( D l: x2 ~6 _( c7 R
Completely randomized design, 完全随机化设计
8 V7 s- F% v2 F+ X* u/ sComposite event, 联合事件: u9 |$ u# I9 s7 H- v w! v# _& B
Composite events, 复合事件
" U; n. ]. S% U* }# h+ a: J. X) LConcavity, 凹性/ f; [ G' Z1 l5 I3 ]: p
Conditional expectation, 条件期望; i# K' W: o& O7 c
Conditional likelihood, 条件似然
0 x- k- V2 r6 h+ aConditional probability, 条件概率
. I/ e0 R0 U; ]4 eConditionally linear, 依条件线性
. @8 M( r1 l5 g- A7 z5 oConfidence interval, 置信区间
5 ?' {) } V+ d5 X/ ZConfidence limit, 置信限" a: d* o" Z* ^& `3 G) {% d
Confidence lower limit, 置信下限+ e9 x5 B2 r- d5 ~: Q/ V+ e
Confidence upper limit, 置信上限
$ N$ I5 q3 m* t$ v3 x% o4 XConfirmatory Factor Analysis , 验证性因子分析
) g, K+ c6 F" m5 NConfirmatory research, 证实性实验研究
- d6 U# ?( P, \6 E. UConfounding factor, 混杂因素
8 h- x& w# ~7 d6 \3 cConjoint, 联合分析. a8 O. G, t- p2 L
Consistency, 相合性
, T( I8 m. O2 W" l- B+ r* f/ vConsistency check, 一致性检验3 \5 a, r& a/ l* D6 Y
Consistent asymptotically normal estimate, 相合渐近正态估计
" z* K2 G$ Y2 O' x& A- eConsistent estimate, 相合估计" O( j; d- S* |
Constrained nonlinear regression, 受约束非线性回归* d @; g% ^6 }6 ]) f$ [
Constraint, 约束
; s! H" [( Y: R4 tContaminated distribution, 污染分布
2 i' l3 j3 ~# k+ J8 C1 pContaminated Gausssian, 污染高斯分布
0 O: _& r# \2 K; x. f# T7 g) r8 JContaminated normal distribution, 污染正态分布, _: J4 C2 S' Q5 G" k0 d$ E5 J
Contamination, 污染7 Z1 `6 M! ~' l: r
Contamination model, 污染模型& S0 p& \) s5 O) W3 [; S, {8 x
Contingency table, 列联表& Q& u( I7 T8 x9 z: b4 G
Contour, 边界线0 d8 X0 m0 J( a ~: t8 p, Y: a3 v
Contribution rate, 贡献率
3 `9 ]* S, o* V/ c( r+ \Control, 对照3 g0 K* N8 s: c9 s; q
Controlled experiments, 对照实验
9 A, K& @3 { d7 r, I" e! g" S* h* xConventional depth, 常规深度3 i- T1 |( V* L8 Y5 u* R2 p
Convolution, 卷积2 W" F; B) j. R( ?$ t3 ~
Corrected factor, 校正因子& P( e1 h) `' @: J
Corrected mean, 校正均值
# ?+ z) d4 F- SCorrection coefficient, 校正系数4 W9 \5 F3 A R9 {" P/ t* @
Correctness, 正确性
+ ^& w( H1 o& V) }, LCorrelation coefficient, 相关系数
- x8 N# U0 x. J* [8 `Correlation index, 相关指数* ]7 H8 R8 y& O. n
Correspondence, 对应
: i& t% ]. ^- U4 I$ \$ h: t. iCounting, 计数
/ R$ A P3 h' `1 U9 UCounts, 计数/频数; S7 i% E& }2 K; q2 i+ R7 G2 o9 I
Covariance, 协方差
, K4 e7 K6 h& U7 z1 XCovariant, 共变
9 p& H! P) X5 z/ MCox Regression, Cox回归8 j) T, c$ e& h- Z
Criteria for fitting, 拟合准则
" J$ } M% W; |9 B+ n- J5 F9 sCriteria of least squares, 最小二乘准则
$ O" ]) l6 D/ X3 ] ^: ]6 M& v0 eCritical ratio, 临界比( F8 @/ ^. {& R5 Q
Critical region, 拒绝域
+ r) G8 Q2 b. x! x: @; k8 m, QCritical value, 临界值
) h5 f; o5 d- a+ X* F) J* @Cross-over design, 交叉设计
3 R; O& l1 X# u3 H9 uCross-section analysis, 横断面分析 W1 E# S( y: K' s; m. m5 v6 W
Cross-section survey, 横断面调查
* B, K0 [4 }2 V- Y! p# I! TCrosstabs , 交叉表
* [# j; K/ D. h ECross-tabulation table, 复合表 X( e* k! ^! H8 o
Cube root, 立方根0 G: b5 ?: |/ S8 o
Cumulative distribution function, 分布函数
9 Y: h @) a* b5 ~+ I% b6 l8 VCumulative probability, 累计概率' I1 H; T( g/ o* V; P! ]7 p4 i8 ~2 E1 a
Curvature, 曲率/弯曲
" I9 g% w' L7 q$ C% @Curvature, 曲率
* w' l4 }0 j3 [4 jCurve fit , 曲线拟和
f) t, k: y2 J7 } z* ~/ s- Q. u2 uCurve fitting, 曲线拟合+ g% m0 F& B1 G l% w$ K, x
Curvilinear regression, 曲线回归3 S7 I- b8 r* ~( C" T6 L# w
Curvilinear relation, 曲线关系; x7 {9 W$ A) F8 \; H
Cut-and-try method, 尝试法
0 G# {- T" h4 L0 V! Y) OCycle, 周期
2 c6 r, w5 d) c/ D6 g& ]" LCyclist, 周期性( y9 s$ p7 \! r4 v0 b( R
D test, D检验
! [& i$ [* f0 L+ A" }: @4 zData acquisition, 资料收集* l7 t& T5 ?# S
Data bank, 数据库
8 v+ y- w$ r" {* @5 [+ ?Data capacity, 数据容量
5 F2 v2 x, a) S% gData deficiencies, 数据缺乏4 `+ D8 z( G; l- W. g
Data handling, 数据处理
) `8 X2 G5 _6 VData manipulation, 数据处理1 K$ o; ]3 R, J4 ~( x2 P
Data processing, 数据处理
8 } O/ ]1 L- F7 J2 x7 C/ V0 R& N( [Data reduction, 数据缩减+ G8 E1 @+ _ d5 W: @0 Q/ z$ L( T
Data set, 数据集
# ^; t: a) |( |0 ?( B: |Data sources, 数据来源
% o5 O, A: k# O6 d0 t' [Data transformation, 数据变换
# }( M) J; ?, c( G% j1 A/ YData validity, 数据有效性, e8 @( j. C) M3 x4 o
Data-in, 数据输入% b4 A. y) d. c8 C) W- [
Data-out, 数据输出* l- I( F* ~& X0 O1 u& m
Dead time, 停滞期, R1 b$ J3 z& j( n8 t- E+ o
Degree of freedom, 自由度
8 W" q: q7 O* oDegree of precision, 精密度- u) Z. p9 h- w
Degree of reliability, 可靠性程度
8 Z$ V* V1 h6 XDegression, 递减
7 E+ a5 f# _! X8 M0 g/ q2 _6 T4 vDensity function, 密度函数
0 |! `) a: j4 l7 M1 |* u, j+ bDensity of data points, 数据点的密度
: X$ d4 g1 o3 ~Dependent variable, 应变量/依变量/因变量
; p. A/ w: c. x/ Y3 ]' [Dependent variable, 因变量
' _/ i! U, P% ~2 B0 _8 q. EDepth, 深度
$ M8 @; F3 x7 v6 [) B& i' @Derivative matrix, 导数矩阵/ G) D+ l3 g( m$ Q& \' c. {
Derivative-free methods, 无导数方法
, X+ |! Z$ H& f( ?' n0 eDesign, 设计8 E- L' p% a7 F( [6 C
Determinacy, 确定性
0 I# u' P: o. V+ G0 LDeterminant, 行列式+ T+ a6 {( \/ @. M- B
Determinant, 决定因素5 W, y! m$ L# q7 D# N7 b* R
Deviation, 离差6 c% k; i; S1 E' o: a
Deviation from average, 离均差
/ b1 {& `5 P" d- u$ Z: \Diagnostic plot, 诊断图# d' t& Y! Z$ Z- v
Dichotomous variable, 二分变量
' Y- n" |- G1 }2 `. @% KDifferential equation, 微分方程" S4 [; h' u# D
Direct standardization, 直接标准化法
! n+ {1 G8 l7 S$ d' ]3 w* LDiscrete variable, 离散型变量
/ q2 p& x: M( {1 ]8 D8 aDISCRIMINANT, 判断 & p1 u. ^& d4 p5 L
Discriminant analysis, 判别分析
3 Q! e8 ~8 C; ]( k+ [# ODiscriminant coefficient, 判别系数
1 l# N0 j! ?- ?; [Discriminant function, 判别值. ^6 y6 q; Y) l9 n) \& ~/ {
Dispersion, 散布/分散度
- _( b8 H4 Q% w) G0 A+ s+ ZDisproportional, 不成比例的/ A, |0 n" M( T5 A
Disproportionate sub-class numbers, 不成比例次级组含量2 {# B9 ?. o( S* G# m2 K9 y
Distribution free, 分布无关性/免分布
% E m+ [. T; Y( O [Distribution shape, 分布形状, {0 V/ `$ j {$ m
Distribution-free method, 任意分布法
2 o" X: l" x3 m" N0 s& WDistributive laws, 分配律
& D7 H. G# A; M& \# v1 ?3 eDisturbance, 随机扰动项5 f3 U I# \% S% h
Dose response curve, 剂量反应曲线- H- C; d; g& T( M/ U
Double blind method, 双盲法' ~5 n7 }' u4 n9 M3 r' |4 s
Double blind trial, 双盲试验( R' ]7 h$ \# M4 _6 D }' q
Double exponential distribution, 双指数分布
6 @3 P$ z! O: a. r3 iDouble logarithmic, 双对数
% W2 e( O3 X, u! XDownward rank, 降秩0 l! e6 d4 v, }8 {# {" \& F
Dual-space plot, 对偶空间图7 g2 a6 ~& e B* y Q0 J
DUD, 无导数方法 U1 p# |- }, W- {0 `, b/ I
Duncan's new multiple range method, 新复极差法/Duncan新法- V- x: A' Q' M j- c6 j
Effect, 实验效应9 y7 N0 E. N5 e: z# F# t, v
Eigenvalue, 特征值
0 m9 ^: [& z& m5 FEigenvector, 特征向量% | R: C8 I" u/ C! k+ [; N6 ]
Ellipse, 椭圆% f) F# \/ y8 ?; {3 r
Empirical distribution, 经验分布
" X1 }& c9 N# S6 e; B3 HEmpirical probability, 经验概率单位7 ` b& B6 U+ f8 d* G0 z. q
Enumeration data, 计数资料
1 C3 K- g* K- d! q6 i; q FEqual sun-class number, 相等次级组含量) Y4 E; k3 c2 v& X; f* ~6 J, k# Q
Equally likely, 等可能
V3 V! s1 g" M: c) G. QEquivariance, 同变性. ^( C' P0 y1 b9 W. X, B
Error, 误差/错误
3 H4 p! E/ f& |' o; R7 g6 WError of estimate, 估计误差: D4 D# T; }/ E1 g2 v ]5 p
Error type I, 第一类错误+ T. b- E N: m8 V% H& I5 w( F
Error type II, 第二类错误
7 E1 G. L( u c! B% Y9 f5 dEstimand, 被估量
, H6 K# D! u8 {* n. F, fEstimated error mean squares, 估计误差均方* n- g# F) v, P4 k- N
Estimated error sum of squares, 估计误差平方和" _# V2 Y, w4 M2 u/ C. p
Euclidean distance, 欧式距离7 ] O% c3 K# L: G
Event, 事件
. {% }" [3 G5 c3 J1 O- QEvent, 事件
( c; S$ E% ~4 g+ P8 AExceptional data point, 异常数据点6 b. J# z) N% q
Expectation plane, 期望平面
/ z0 D# p8 t* O# h) B# {3 jExpectation surface, 期望曲面
3 c6 e+ `0 [" I4 h4 w& dExpected values, 期望值1 c5 C$ j# H3 P: Q9 c. k
Experiment, 实验# V c5 ^- M2 z) d8 m& m9 K* y
Experimental sampling, 试验抽样
4 ^* [, g7 T( I7 S8 f+ wExperimental unit, 试验单位( m5 _& s2 H: ?9 r4 K
Explanatory variable, 说明变量
7 ?0 `+ W9 F% j3 oExploratory data analysis, 探索性数据分析
8 \. y( h' E9 h4 k5 V4 S; LExplore Summarize, 探索-摘要5 U k$ Y2 s M8 s* P+ Z
Exponential curve, 指数曲线6 ]& J7 ~( c1 p1 y& |7 r$ B
Exponential growth, 指数式增长
3 F# o( p8 I9 NEXSMOOTH, 指数平滑方法 ' _ I4 L7 K' f" m( o
Extended fit, 扩充拟合
; d, P3 ]# v9 e2 VExtra parameter, 附加参数
& f6 }! |5 n6 z1 P; h7 a+ YExtrapolation, 外推法" R: z; q( l; a; g# o9 f+ z
Extreme observation, 末端观测值0 w" `& a, z! W& F, l. }
Extremes, 极端值/极值
7 w2 r% Z% N3 r9 n7 |! v- bF distribution, F分布7 X6 Q5 @5 J7 U
F test, F检验& W* j3 s8 O0 ~& {0 ^# y9 k
Factor, 因素/因子
1 K" N/ S+ M, Q7 pFactor analysis, 因子分析
9 Q+ s" ?( F& X( R8 hFactor Analysis, 因子分析
[6 e# i' g. r2 W% d5 ?Factor score, 因子得分 * {& Y, n7 c* N+ N. x: L% F
Factorial, 阶乘
# ]2 K( }. d* ^& w' \4 t( E$ P( |Factorial design, 析因试验设计
( Y6 B" M/ a cFalse negative, 假阴性
9 H3 o) H) A: A3 s7 c- X. E* ^False negative error, 假阴性错误
- r& G6 D& l1 nFamily of distributions, 分布族
% p, R8 t7 `$ V1 u+ zFamily of estimators, 估计量族
9 `- O Y/ n, \9 cFanning, 扇面
+ n! X" P& `, t( @( Z! LFatality rate, 病死率) w- V" p: S2 E' F
Field investigation, 现场调查
) ~$ R7 s" U6 {0 {$ ZField survey, 现场调查
) C, f. X: @6 HFinite population, 有限总体
# Z5 X6 B, x5 @! Z) p' {Finite-sample, 有限样本* X$ z& W0 Y0 K. V% f0 S6 F
First derivative, 一阶导数7 ~9 D, o7 ~+ H4 U- r: T8 W* \
First principal component, 第一主成分
8 O2 w0 P& f- O# J9 {First quartile, 第一四分位数
/ k8 M, y/ C$ zFisher information, 费雪信息量
( A( [ s! z. K) K" @Fitted value, 拟合值; f g9 ^6 C" G! S* T/ g
Fitting a curve, 曲线拟合
; O+ w. ]6 L5 P# r2 l4 F. tFixed base, 定基1 R5 K& U' W: f* o# B
Fluctuation, 随机起伏9 {8 ~# h( K7 W" u0 R( J1 l- }1 U8 M6 N
Forecast, 预测- o$ b& z' w+ u2 y
Four fold table, 四格表# o! u8 G( E; O7 I
Fourth, 四分点
, F1 x4 e2 r1 J" Q. ~Fraction blow, 左侧比率5 W$ s! K$ t# v" }
Fractional error, 相对误差
: a& w) e0 z- M2 d# N) oFrequency, 频率
$ G7 V4 E6 X2 D! U) YFrequency polygon, 频数多边图9 K& \7 G/ E" m: [9 \! L
Frontier point, 界限点
$ B$ L. S" V9 jFunction relationship, 泛函关系4 I' z! t, ]5 }. A7 a& c1 X
Gamma distribution, 伽玛分布3 c, m+ q/ B3 `6 F
Gauss increment, 高斯增量# K* o4 k1 R, r
Gaussian distribution, 高斯分布/正态分布
+ D) X9 q* _& a+ fGauss-Newton increment, 高斯-牛顿增量" i2 V+ E. ?' I: l$ y# U
General census, 全面普查, {% y3 B' _: J
GENLOG (Generalized liner models), 广义线性模型 ) |1 J6 n* b! X& K$ v
Geometric mean, 几何平均数
7 u) h" A& `* ^+ ZGini's mean difference, 基尼均差( `* b0 Z$ S& D2 z
GLM (General liner models), 一般线性模型
" c, O3 r/ L' M+ }2 s& R5 ` Y8 ]Goodness of fit, 拟和优度/配合度4 s; d8 k8 @2 p5 A8 k
Gradient of determinant, 行列式的梯度
. l( n& x& v6 ~7 r3 YGraeco-Latin square, 希腊拉丁方- l' V z+ n3 D D/ I3 |7 t/ v
Grand mean, 总均值& s& J8 d. o4 h5 E3 u4 ~9 O
Gross errors, 重大错误) ]- h! H& L7 W' F( V
Gross-error sensitivity, 大错敏感度
& y* |/ h" L1 rGroup averages, 分组平均8 r: ]7 ^" Q q
Grouped data, 分组资料
8 w/ {# P1 a, V6 ?" S4 v6 IGuessed mean, 假定平均数
7 D9 H9 ? K# G, T7 EHalf-life, 半衰期1 U! d1 I* E: R& Q. a n8 g
Hampel M-estimators, 汉佩尔M估计量
: Z; ^- C4 a! j/ W& Y- v/ NHappenstance, 偶然事件+ X' t$ k0 R$ C
Harmonic mean, 调和均数
6 k% u$ R! @/ W4 h h7 THazard function, 风险均数2 ~% r* |' p/ D3 M0 X
Hazard rate, 风险率, } o% X/ N$ z/ J3 R- o3 q
Heading, 标目
$ Y0 h J. K6 ]- P( RHeavy-tailed distribution, 重尾分布; q6 V$ h! Z+ e) m# W) \2 n( G
Hessian array, 海森立体阵5 v4 I J* D9 {& v+ T
Heterogeneity, 不同质* ^- p& }8 _9 T; X6 t
Heterogeneity of variance, 方差不齐
) ]- t6 j7 a5 G$ M( f- kHierarchical classification, 组内分组$ c' {3 m, F) R' i" d! k
Hierarchical clustering method, 系统聚类法! a" c2 f4 k) c# E1 v$ }/ N _: f
High-leverage point, 高杠杆率点
+ z, b7 v3 M% V; p! i+ S3 OHILOGLINEAR, 多维列联表的层次对数线性模型
; Y" L5 y. R* H9 ]7 @0 I" Y" `Hinge, 折叶点
2 G# M Y8 Z) x! eHistogram, 直方图5 c& N! w+ s! T) q% M+ Q
Historical cohort study, 历史性队列研究 9 v- G- ^/ M4 K! X( u7 ^
Holes, 空洞
c" [! {' x7 r4 p( y1 l2 k/ tHOMALS, 多重响应分析9 |# R5 q+ L. B" o# ~$ W' u6 C
Homogeneity of variance, 方差齐性# Q0 |8 E7 P6 b3 ]0 e
Homogeneity test, 齐性检验
0 w/ ^1 z' h% P rHuber M-estimators, 休伯M估计量
6 E7 L7 \* [# nHyperbola, 双曲线+ _0 `2 k2 R( r1 `# \- `( c; r& [: @% ~7 }
Hypothesis testing, 假设检验
( H6 U+ ?( J0 j. w/ qHypothetical universe, 假设总体- Y. f2 h7 y- l
Impossible event, 不可能事件
4 \2 V$ N4 r! Z; `Independence, 独立性7 h- j% ]" w7 Y' y1 f5 j, R! n( S
Independent variable, 自变量
8 U) G0 J1 W% D- z sIndex, 指标/指数
! }! i P P. T5 o' K8 i ?$ mIndirect standardization, 间接标准化法
1 P5 `3 g. L1 |6 I, AIndividual, 个体
0 y& ?0 }. ^/ X' g. C! XInference band, 推断带, u) C4 J2 L" S, _2 k/ F* b
Infinite population, 无限总体) a: h. ?8 o6 D; V) f, P
Infinitely great, 无穷大; k* v* i" c3 ?- @0 F
Infinitely small, 无穷小! R3 M- g2 i$ ^' k; U4 X# c
Influence curve, 影响曲线0 N! o4 a$ K+ P% P" R
Information capacity, 信息容量2 U7 [! k$ H* H( Z0 O7 _
Initial condition, 初始条件5 G8 k- S7 u3 I, r4 K# u
Initial estimate, 初始估计值' {# p( X! Q. { W0 R- S5 }' p
Initial level, 最初水平. R# Y+ s( ?; Z2 x0 _: h- u
Interaction, 交互作用# Y, v- _9 |7 h. d
Interaction terms, 交互作用项
3 \9 Q$ y b+ X; c( d+ R! xIntercept, 截距
e7 M2 O1 U) Q: ~. h0 _1 GInterpolation, 内插法
7 T9 t: l0 z& \1 r t) j7 s9 L! n% mInterquartile range, 四分位距& O/ C* Q. F: t" F
Interval estimation, 区间估计/ r+ _( e' I) X* A$ H2 K
Intervals of equal probability, 等概率区间
t+ J/ }- |( cIntrinsic curvature, 固有曲率
g: X& p3 d: u/ ]Invariance, 不变性# G; w! B% f% L$ b3 J' k
Inverse matrix, 逆矩阵' j9 B5 a) [& w3 L3 v2 C0 g: M
Inverse probability, 逆概率
0 }9 K+ T: B1 S! l) p. a8 J9 pInverse sine transformation, 反正弦变换
7 J+ M8 V# Y# ~3 |. q# |) UIteration, 迭代 / a3 H! K9 X6 W- {! }, T
Jacobian determinant, 雅可比行列式( z2 [0 e( [; s s g4 _
Joint distribution function, 分布函数# Y: F \$ E- d$ U* g* h* q
Joint probability, 联合概率
r& a" ^) ^) ~' x* ]- x' E- ]Joint probability distribution, 联合概率分布 l! R0 O3 P, i; k% ~$ D6 t: O
K means method, 逐步聚类法9 c+ C k$ G3 D& e
Kaplan-Meier, 评估事件的时间长度 ; ?( Q1 S. r3 n1 Q- |4 K
Kaplan-Merier chart, Kaplan-Merier图
# T2 X6 I# p: Z$ s/ q$ F( JKendall's rank correlation, Kendall等级相关
; p* t9 e/ B* K% c$ L, I/ B. R7 PKinetic, 动力学5 P7 U2 K8 q# {2 m
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验, \$ F/ [( f/ F5 b6 z2 m
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
! W2 i) p l! e# P2 @2 s; vKurtosis, 峰度0 g4 s# K) g% e4 b* _0 {# n- A
Lack of fit, 失拟
( E$ J. l: h' W/ R$ ?Ladder of powers, 幂阶梯" f6 B4 h# L/ \! u9 Z& o; o: z& Q. }
Lag, 滞后
$ [0 o, G% F1 [0 S( j( JLarge sample, 大样本& {. D1 K2 h' X% B& q8 h2 u
Large sample test, 大样本检验% w( K: M- g9 }4 I
Latin square, 拉丁方5 k7 f1 U& X8 E+ T
Latin square design, 拉丁方设计' w: {7 f7 `) u( I2 B/ J
Leakage, 泄漏
. l1 A, W4 [9 G i; g" J8 ^# q6 hLeast favorable configuration, 最不利构形! V3 v2 B& A+ [# Z8 Z8 k1 c, d
Least favorable distribution, 最不利分布8 r6 {$ W S0 {6 ^+ I0 G q
Least significant difference, 最小显著差法+ \* c* b# v% p! m0 d/ \( m* j; T3 H
Least square method, 最小二乘法: @6 [- c5 \ h& n
Least-absolute-residuals estimates, 最小绝对残差估计. l: @ ~( Q& a5 M9 C
Least-absolute-residuals fit, 最小绝对残差拟合; T0 @' H$ x1 n/ Y! V" T7 ^; W
Least-absolute-residuals line, 最小绝对残差线
9 j7 e, R! I/ D' h4 v ?Legend, 图例
7 k' p8 @4 B9 X# A; qL-estimator, L估计量 e! g5 \) f* j9 H6 I/ R3 V6 @3 ^7 y
L-estimator of location, 位置L估计量
1 J1 b: O! u' eL-estimator of scale, 尺度L估计量* Z: w0 f5 B7 D
Level, 水平) E; q# J; ~4 J4 U; z. |
Life expectance, 预期期望寿命
Q1 R9 O/ @8 K% A. h+ k' JLife table, 寿命表3 X+ g1 }5 F) M( b8 G2 \$ Z
Life table method, 生命表法! [/ x, ]) p+ ~1 G
Light-tailed distribution, 轻尾分布- i8 G) g% B/ ]5 l
Likelihood function, 似然函数3 b/ h0 u( ~) s) d
Likelihood ratio, 似然比
/ G! A, c) X- X+ a3 Lline graph, 线图
+ B. ~8 {2 u& v2 `# MLinear correlation, 直线相关
; U3 I4 g& \1 {- R5 C) K- p. \& Q* R8 QLinear equation, 线性方程
6 B; d1 t t8 R; o! lLinear programming, 线性规划
( @: _, i( O* W" {, z$ ELinear regression, 直线回归1 T% d' k7 e5 c5 q. }* J
Linear Regression, 线性回归. X5 U: l& v `' F j
Linear trend, 线性趋势# J) X, A' M; E# g* @
Loading, 载荷 / n& E# C0 P" l
Location and scale equivariance, 位置尺度同变性* O+ W; o3 Q# n5 H1 E) |* B* u! a
Location equivariance, 位置同变性3 n- j8 m1 Y: e j
Location invariance, 位置不变性- Z4 A& d- ?- L5 F
Location scale family, 位置尺度族# m. \7 K. g2 j9 h* J
Log rank test, 时序检验
3 }& x. y0 u {- ^6 YLogarithmic curve, 对数曲线
! n; `' b/ m E& q% mLogarithmic normal distribution, 对数正态分布
2 E. R f' S7 y3 jLogarithmic scale, 对数尺度6 o- P) ^& G" O! e9 m6 T; D( R
Logarithmic transformation, 对数变换) Y6 c7 H, e% z
Logic check, 逻辑检查# c1 `+ u0 a9 G: i' Z7 w
Logistic distribution, 逻辑斯特分布( P5 I# A3 L9 I: }
Logit transformation, Logit转换* K9 t0 R: e$ n" ?" j, m& e. ^
LOGLINEAR, 多维列联表通用模型
( \8 M; e1 i5 I+ r, L' w( s* w0 rLognormal distribution, 对数正态分布# F& `. g% t( z
Lost function, 损失函数
/ U9 s: X; Z j& P8 S$ SLow correlation, 低度相关
7 P4 c( Q' l& l! iLower limit, 下限 L/ c3 O' l. N# j$ n' z
Lowest-attained variance, 最小可达方差
2 e/ R' }( n; g7 J0 M# nLSD, 最小显著差法的简称- c& ]' M* y% F1 o4 Y0 B. i
Lurking variable, 潜在变量: p; I' }! t/ v) n0 k: z
Main effect, 主效应$ ?) h7 |) h+ @" F& L, _ L* ?
Major heading, 主辞标目
E. c ]4 a1 z: X* ?! c2 R9 i% \8 y* dMarginal density function, 边缘密度函数% w& {8 r0 r# f$ m P j
Marginal probability, 边缘概率
8 t3 K, a9 t! ]7 A6 b( q2 B: vMarginal probability distribution, 边缘概率分布0 g! _ z8 g l7 M& y
Matched data, 配对资料
0 Z$ H e5 [- ]: u# p5 CMatched distribution, 匹配过分布
0 J1 i. S N7 R5 Z* Z+ nMatching of distribution, 分布的匹配
- J7 |4 r' t* _: Y1 _Matching of transformation, 变换的匹配
, g. L! S3 N$ T5 BMathematical expectation, 数学期望0 s' E/ F5 J8 S( `# g3 _9 ] U
Mathematical model, 数学模型
+ m/ B" z) e+ e" _6 pMaximum L-estimator, 极大极小L 估计量
3 R8 m8 P( C4 ~' {Maximum likelihood method, 最大似然法% H0 i" M: m6 D- @) u- l4 P$ @; c
Mean, 均数
0 I+ g: X8 m% L7 \Mean squares between groups, 组间均方
0 w6 O! S% p$ W8 W/ h% yMean squares within group, 组内均方
, v) T+ t: d$ p2 u9 I0 }Means (Compare means), 均值-均值比较
, _0 T3 K- X; {; yMedian, 中位数
, x7 u! E8 [4 e7 ?/ ]Median effective dose, 半数效量
- C& h6 N2 x$ tMedian lethal dose, 半数致死量
( N3 D) A/ T n5 M) LMedian polish, 中位数平滑
, [6 X% c% t; ~. K# P9 Z9 xMedian test, 中位数检验+ F( T6 I* p/ F2 a$ Z0 V
Minimal sufficient statistic, 最小充分统计量 |1 ]( Z* y. s6 X8 _8 A
Minimum distance estimation, 最小距离估计
$ R+ k: j" b% E( N+ I4 c# s, NMinimum effective dose, 最小有效量
. j1 _) T+ p( U; x. sMinimum lethal dose, 最小致死量
( Z( x+ d; B& g5 C; E+ H2 }Minimum variance estimator, 最小方差估计量
% l% d B' C }) U7 y+ J. |$ m% O2 TMINITAB, 统计软件包6 T3 a: h* {# \% N# T: U6 s& E
Minor heading, 宾词标目
* a; l2 ?. ]3 z- Y9 }% D9 dMissing data, 缺失值0 z6 b8 X* K. r1 R! S. j
Model specification, 模型的确定
( d- \) m1 o4 r) X$ \! |- s0 NModeling Statistics , 模型统计+ ~0 q& r6 n! _! f( }
Models for outliers, 离群值模型
7 ?6 l. k7 F/ k/ n; EModifying the model, 模型的修正
( m" q5 L; B! k! z7 T# f8 y. {Modulus of continuity, 连续性模2 A+ v8 t4 F9 _, J7 ^/ S3 I
Morbidity, 发病率 / |5 |* y+ Y4 d" A4 T
Most favorable configuration, 最有利构形
" Z7 O* K* p6 `; h; ^/ t) N; bMultidimensional Scaling (ASCAL), 多维尺度/多维标度
6 R8 ] J2 x" }5 @- BMultinomial Logistic Regression , 多项逻辑斯蒂回归7 n4 U# g, K9 u' S+ g: a
Multiple comparison, 多重比较
! O: p5 o' ~5 O8 D9 pMultiple correlation , 复相关
' G9 }2 M$ K: Z4 e- nMultiple covariance, 多元协方差9 d: }, ^7 J: S. [( }. k( }# I- X
Multiple linear regression, 多元线性回归
( j4 y$ C8 N D0 ?7 Y/ jMultiple response , 多重选项
0 u& P( r, p4 C) nMultiple solutions, 多解# A2 m6 a& @) n E6 n9 i
Multiplication theorem, 乘法定理' C* s( p7 k& U+ u3 [2 w( N
Multiresponse, 多元响应8 \3 K6 d. b$ N& s! W; v" s
Multi-stage sampling, 多阶段抽样
[) X' g; v, q$ y( h! I+ dMultivariate T distribution, 多元T分布
' j6 @5 ~. |# g: l$ I; sMutual exclusive, 互不相容6 c% x! Z" q% g U R8 ]
Mutual independence, 互相独立8 J: ?. z% _8 Q: k( M
Natural boundary, 自然边界
* u! \( l \9 S; K9 f2 zNatural dead, 自然死亡
/ X: X; q8 R% H8 h5 n+ N9 tNatural zero, 自然零- \8 M n* s& ]3 f
Negative correlation, 负相关
$ S8 S! O* S3 Q1 G4 @; ^+ VNegative linear correlation, 负线性相关
+ c% A# F" [2 NNegatively skewed, 负偏$ y2 F* ?. u' A" q6 A2 _7 X
Newman-Keuls method, q检验3 M' q* q5 Z" a+ H' }; }
NK method, q检验
: _3 U: w+ Q7 i. l* iNo statistical significance, 无统计意义- T* M. y1 y8 [7 z# p5 w, K/ Z& s
Nominal variable, 名义变量; w1 F g) h5 K( l
Nonconstancy of variability, 变异的非定常性
0 Q- L5 A2 N' F8 u1 e8 dNonlinear regression, 非线性相关; d" N$ T1 n# I6 {" ^; R( \8 i
Nonparametric statistics, 非参数统计
8 @2 d4 |" p) [8 ^& GNonparametric test, 非参数检验+ O: I6 ]+ M2 q% Z& f+ C
Nonparametric tests, 非参数检验
6 w1 c1 W8 f$ J& nNormal deviate, 正态离差8 U% D3 V; P' w: @5 X4 I" r' W
Normal distribution, 正态分布# `6 [0 i- w4 {. q% D9 N5 ?' |4 m
Normal equation, 正规方程组
6 l! }$ p& u% R& ?Normal ranges, 正常范围
- B0 B( j y# |3 K2 d, ]Normal value, 正常值4 ?$ Y* Z4 f- I& z( e4 F
Nuisance parameter, 多余参数/讨厌参数4 H4 B5 ^. n+ Z, G1 T3 ?. F6 y
Null hypothesis, 无效假设 * `: r; l9 Y0 |1 n' ]4 n. \
Numerical variable, 数值变量
_* |$ `2 Z* M) p5 {0 S7 s( WObjective function, 目标函数
* T. ]( ?' W6 s J" o" VObservation unit, 观察单位
/ R& O. |9 q! v" |Observed value, 观察值' f* P( l/ k$ _/ ?' g. r+ g0 e1 I
One sided test, 单侧检验$ m/ w" W) r8 B! w5 @7 R( {
One-way analysis of variance, 单因素方差分析" m' s3 U a9 C; V* ^
Oneway ANOVA , 单因素方差分析' B, S6 @5 C' }; o n5 T7 {& u! G
Open sequential trial, 开放型序贯设计. V8 @0 L7 x0 D7 i
Optrim, 优切尾7 Y5 M' L G8 U& D& k6 G
Optrim efficiency, 优切尾效率/ G/ f8 o6 \8 x- S- Q9 n
Order statistics, 顺序统计量& h6 X$ v" X- M4 {
Ordered categories, 有序分类
/ O' v: w- c, J( I* QOrdinal logistic regression , 序数逻辑斯蒂回归
$ o8 t: q {5 G$ u: k }Ordinal variable, 有序变量
6 l% @: v8 k0 ]) ]Orthogonal basis, 正交基
3 T1 g5 B9 d1 i! f8 A8 gOrthogonal design, 正交试验设计
# l" ]% i; _/ POrthogonality conditions, 正交条件% p: F6 r% Z* Z4 k
ORTHOPLAN, 正交设计 8 r* m: l! p" _% k
Outlier cutoffs, 离群值截断点
+ n, M; P3 I% W! R' kOutliers, 极端值8 L. ` F( }/ X( m6 [0 w
OVERALS , 多组变量的非线性正规相关
) j d* ~8 ~; r9 J' A- NOvershoot, 迭代过度7 c" o3 @% n) s# ~# b3 p- _8 D( F; q
Paired design, 配对设计
: g$ g1 _1 {1 V8 j: ^! O/ }5 X2 _Paired sample, 配对样本
i$ L* |8 P' _. kPairwise slopes, 成对斜率5 @; v- e, f* X9 G' h) n X
Parabola, 抛物线% Y! \- w4 V2 _2 k5 _0 j6 c
Parallel tests, 平行试验* c/ G% i5 L9 x* ?
Parameter, 参数
% F+ z; ^1 q* U4 e/ N7 dParametric statistics, 参数统计" l8 d% q6 \. N* f" O* L2 W0 k
Parametric test, 参数检验
) u1 S0 g& |$ G* r- `9 H6 y4 x) UPartial correlation, 偏相关
* T: g& O* x2 e- y# vPartial regression, 偏回归5 \* D8 q2 E2 |' W; D" C5 i) T
Partial sorting, 偏排序
) S. E7 [* o( W( G+ }Partials residuals, 偏残差
) G4 B& W/ u1 q5 a) {. @Pattern, 模式: J9 E2 d* a. F- J1 c: Q
Pearson curves, 皮尔逊曲线
: e9 L& t1 Z( Q9 [. n4 k1 nPeeling, 退层1 q' u0 g5 U+ k7 A! G! a& `
Percent bar graph, 百分条形图: u) p; `; q. }, s
Percentage, 百分比
( C( W7 q: D3 A% U* N+ m) pPercentile, 百分位数
4 Q' O6 g/ T7 s5 Z6 XPercentile curves, 百分位曲线
: Y5 t3 N3 x/ b. q* JPeriodicity, 周期性
# X! g; b3 Z& oPermutation, 排列/ j2 q$ n. M7 o
P-estimator, P估计量
& ]4 c5 Z5 k8 R' {+ JPie graph, 饼图6 }, f( i) @, x: @% T
Pitman estimator, 皮特曼估计量) m( Y; L! e: X& I
Pivot, 枢轴量) D( |8 e' ~" l2 t! n/ H& o/ Y6 G8 j
Planar, 平坦
, w: Q, v( t2 OPlanar assumption, 平面的假设
: f% ^' a# D i% V$ F9 P* @& J# Y0 ^PLANCARDS, 生成试验的计划卡! M. v M1 d( x
Point estimation, 点估计
; w1 C# a! U$ F/ J1 b# V) gPoisson distribution, 泊松分布' W. c/ u4 i+ H8 a
Polishing, 平滑* K0 t7 u$ S) t0 m
Polled standard deviation, 合并标准差
. n# O: ^: P) Y9 CPolled variance, 合并方差+ ~0 P6 w. m; g4 @; n, ?5 l8 }
Polygon, 多边图
6 L, |* K/ i4 P1 `2 y3 pPolynomial, 多项式5 N; M6 Z' c$ i' L
Polynomial curve, 多项式曲线
3 f% c/ U2 e) L! F Y; p# o4 k+ R+ [Population, 总体
8 d& i/ g3 w2 u" Y( ~Population attributable risk, 人群归因危险度
% ^0 `( g0 f* [3 k: c+ _7 OPositive correlation, 正相关5 `1 y# f2 A' ^7 p% n2 a& Y
Positively skewed, 正偏
9 H- G' Q% u1 F, E2 ?) j# _9 G$ X, bPosterior distribution, 后验分布
! ?1 i' ]' I$ T4 e% g+ U1 yPower of a test, 检验效能! [; ~1 T1 J+ b2 j
Precision, 精密度
8 J% S# z% Y6 C. v* cPredicted value, 预测值
1 t8 Y7 Z: |6 F) G8 K) m, Z1 z, S ~Preliminary analysis, 预备性分析# p; s* ]4 J, u$ g+ r4 D
Principal component analysis, 主成分分析
/ S: R5 k& W5 x5 N' RPrior distribution, 先验分布# |5 Z: A9 A- `7 G+ w# b3 f
Prior probability, 先验概率
- N" G; F% K9 x% a) }3 |# NProbabilistic model, 概率模型
7 ^. J3 @8 y* h, u9 Cprobability, 概率
5 N1 q: |0 ?+ m3 J6 s6 E) ^( ^Probability density, 概率密度
* A1 G: `2 O3 G, rProduct moment, 乘积矩/协方差
+ Y" ~/ D6 w) N$ J' j5 JProfile trace, 截面迹图
7 I+ o3 D& @' q- oProportion, 比/构成比
8 [) A3 y. S+ c* u6 _Proportion allocation in stratified random sampling, 按比例分层随机抽样
- _5 W, o6 {# v6 \* Y: \, B6 k. |Proportionate, 成比例3 ]" s) D! U8 Q! W! i9 b
Proportionate sub-class numbers, 成比例次级组含量
( `2 X) {0 G: h- x, Q ~Prospective study, 前瞻性调查
/ ~- y. u+ ]0 Z6 [Proximities, 亲近性
( f2 Q" `0 ^8 x( f4 uPseudo F test, 近似F检验* ^ _, S. W7 h* M1 m4 B! x
Pseudo model, 近似模型5 G" k- x* B9 w
Pseudosigma, 伪标准差# j5 Z$ }5 b z
Purposive sampling, 有目的抽样
+ t1 w# r2 a! `QR decomposition, QR分解
& p2 d* B+ D7 |+ W% yQuadratic approximation, 二次近似
( [3 V b+ V/ A& p! K0 bQualitative classification, 属性分类# Z6 B/ P1 _: `& F0 f
Qualitative method, 定性方法
! j$ U6 z2 g9 M% Z6 D2 oQuantile-quantile plot, 分位数-分位数图/Q-Q图
, i3 l0 U3 F- f7 n/ aQuantitative analysis, 定量分析( {4 ^# d1 H$ s6 h( |9 P% F4 e/ y/ i
Quartile, 四分位数
$ i' ~, Z9 F/ m8 yQuick Cluster, 快速聚类
9 |6 U4 Q8 y" I8 ], `! g, _' URadix sort, 基数排序2 \6 E5 _4 D: C% b5 e
Random allocation, 随机化分组
1 P6 }0 z! K, x5 i' Y. oRandom blocks design, 随机区组设计
3 n/ b% y% ?9 K2 r# ~Random event, 随机事件
9 [, l$ h$ h- c8 k+ j9 f4 L) l" URandomization, 随机化
. a# y6 ~* q# H. C* E. {Range, 极差/全距
6 m6 X# A. U" `9 b' k% ZRank correlation, 等级相关! i3 s# J" l& B# B8 h
Rank sum test, 秩和检验8 z' T) ?1 \, A3 H( ], {
Rank test, 秩检验
. f: v; T* I9 m) M& U [4 D) uRanked data, 等级资料% Q! N+ b# L0 N0 ^
Rate, 比率
4 G: e2 h8 Y" ^( D) [6 d; d( D6 PRatio, 比例
8 \0 f0 m; b: i j, t7 F1 tRaw data, 原始资料: S- R* k+ N% D" |, Z
Raw residual, 原始残差) E5 H8 t/ j& R( V; x
Rayleigh's test, 雷氏检验# Q" Z0 F1 e4 [+ f: f
Rayleigh's Z, 雷氏Z值 * I% S: g) R; D1 ?- x9 _$ O
Reciprocal, 倒数$ @- R2 P! V7 K4 ^- p# s
Reciprocal transformation, 倒数变换
8 B. D A" b; C" m. Z' }Recording, 记录4 V) m# p h9 }1 o
Redescending estimators, 回降估计量
3 ^3 m5 U* E7 y/ Q2 r7 B8 q/ h9 |Reducing dimensions, 降维* S! ?: n# h/ Q* ?: C9 p
Re-expression, 重新表达# V4 J7 B, f O1 I3 X5 U. D5 ]
Reference set, 标准组* t" A8 K1 ^/ P- K4 @# Y
Region of acceptance, 接受域
0 t5 h h$ X# y0 y( c8 LRegression coefficient, 回归系数- H. V, [4 i3 C9 B: G& Y
Regression sum of square, 回归平方和
8 r1 x7 t$ N" B" A& pRejection point, 拒绝点6 ~2 A9 [2 ~0 K
Relative dispersion, 相对离散度! } T9 I- l- Y5 r) l
Relative number, 相对数
5 Q, K4 a3 t9 f# l, ?Reliability, 可靠性! h8 L- w6 R3 n* i
Reparametrization, 重新设置参数
( y2 D0 N( y! x4 H" e& g2 r* i3 XReplication, 重复
1 g i9 u" p. H2 J$ q. v( jReport Summaries, 报告摘要
" N9 {' C; l/ f nResidual sum of square, 剩余平方和" e" d/ M2 Z% [8 ]
Resistance, 耐抗性 ^) g8 L, W v. h1 d, e
Resistant line, 耐抗线; _' N" N* G/ Z- K- [, M, F
Resistant technique, 耐抗技术9 d( B4 S3 a; h
R-estimator of location, 位置R估计量3 H$ v5 G2 @- P7 f8 E# o
R-estimator of scale, 尺度R估计量
) w2 ]/ i. h+ r* v/ n2 I% N! gRetrospective study, 回顾性调查: ]( @: F% `# V8 g }2 x5 d+ O
Ridge trace, 岭迹
1 L* M- n- t7 p6 QRidit analysis, Ridit分析
% L/ [. _2 [$ [/ FRotation, 旋转
* t+ F9 [5 `6 D; u: A7 M2 pRounding, 舍入
) h- D8 Z# ? C V5 zRow, 行
% e/ I0 \& l: C/ b" _8 p+ i$ TRow effects, 行效应
3 B- H3 u* d+ v0 ]* |: MRow factor, 行因素* y5 e3 J) u/ t# E
RXC table, RXC表
+ a; a9 ~/ D8 L X x) ?+ a1 XSample, 样本
9 o* U% J) ], p, J9 b" H1 xSample regression coefficient, 样本回归系数: k& C6 c6 b+ ~* S- s& V
Sample size, 样本量9 C2 K' a% | E* r! F5 Q3 R+ d% o
Sample standard deviation, 样本标准差
% c6 P8 a4 }' H3 B6 hSampling error, 抽样误差
8 H" y; o# a& ?6 PSAS(Statistical analysis system ), SAS统计软件包; O5 p- j7 l- ?+ | r
Scale, 尺度/量表
8 f* X) e! G; gScatter diagram, 散点图( m. n# l$ H* x# ~3 D
Schematic plot, 示意图/简图: J5 r! f$ |0 z6 T9 ]! \
Score test, 计分检验
# f% y; e& I7 |8 }Screening, 筛检6 ^: t; j" v3 ]/ x# X' K
SEASON, 季节分析
; b, k4 y) [! W; f2 p8 r; w1 z6 SSecond derivative, 二阶导数( L# f0 v% I- @/ x2 j5 B
Second principal component, 第二主成分
. H2 `" ~ Q1 j, P5 T' V# USEM (Structural equation modeling), 结构化方程模型 / L P( f6 Y- J/ _
Semi-logarithmic graph, 半对数图
; E2 ^3 C# j/ K0 b1 M1 r2 GSemi-logarithmic paper, 半对数格纸
- Y' S4 W7 b# w" B+ ^, fSensitivity curve, 敏感度曲线 J$ C: W$ ^0 F- {8 H; `
Sequential analysis, 贯序分析* W8 r" `0 m" t
Sequential data set, 顺序数据集9 i" @0 \6 `+ U( V
Sequential design, 贯序设计
; L* ]& B h) o# c/ l) oSequential method, 贯序法) r$ j) x9 r4 a. y; a7 g& c
Sequential test, 贯序检验法' y0 d; l- M- ~. K# m
Serial tests, 系列试验
! z# P5 O; \+ x+ E& Y: y& M1 e: YShort-cut method, 简捷法 ' l d& g) j% F9 ^. ?
Sigmoid curve, S形曲线- B6 `# _- Q6 @7 j9 @+ `! U8 N
Sign function, 正负号函数/ b) k, W, m( R2 f5 U
Sign test, 符号检验
" J* A* u/ T! _8 |) Y! U" [; @Signed rank, 符号秩
' `8 w4 |% l8 N% j6 nSignificance test, 显著性检验: O7 _- d4 B% t. W
Significant figure, 有效数字
$ I4 [# O, t) o* y7 n' P9 @Simple cluster sampling, 简单整群抽样
, H" o2 p/ X* M5 j1 NSimple correlation, 简单相关+ ?8 q1 j' `2 B4 b' o, @
Simple random sampling, 简单随机抽样1 t" z8 t/ L8 Q2 [6 P
Simple regression, 简单回归
2 O5 @9 `; P) v' {simple table, 简单表
; A& S1 }# K( gSine estimator, 正弦估计量
% Q" W; V2 ?( B7 F0 X' B6 d/ ~1 ]Single-valued estimate, 单值估计
+ f2 Q! d3 ^1 Y/ F& xSingular matrix, 奇异矩阵
5 D; ]+ R2 @" N# B# q' e& G+ \Skewed distribution, 偏斜分布. f: Z; E+ h; \0 v7 ~$ _$ l* r
Skewness, 偏度
# m' O& I0 [. `" E6 g, r: eSlash distribution, 斜线分布0 S" Q& D; B" ]3 T2 N1 g
Slope, 斜率
" k5 l+ P' A3 h4 g6 _( W% N. D! rSmirnov test, 斯米尔诺夫检验
: N4 B Y/ C" q: @0 b! d- aSource of variation, 变异来源$ Y" i: I! S! A; t( Y' e$ |
Spearman rank correlation, 斯皮尔曼等级相关2 T, w4 W# O q% p
Specific factor, 特殊因子
' I+ j- e5 s1 m) [) y+ aSpecific factor variance, 特殊因子方差
9 ?6 y; W; I4 S6 }Spectra , 频谱$ l; _: r! ^2 L) G$ p, v1 Z
Spherical distribution, 球型正态分布
# B+ t. D1 i( ZSpread, 展布9 M/ p. |: ~/ B$ d" q9 D3 ^/ f# K
SPSS(Statistical package for the social science), SPSS统计软件包3 u0 R& ~! L. j% m+ p
Spurious correlation, 假性相关8 a$ F |8 h% l) S& C
Square root transformation, 平方根变换" U# u# `4 T/ I; e6 j$ q0 C
Stabilizing variance, 稳定方差! {3 c6 I2 D" S4 E# X
Standard deviation, 标准差
: a3 a7 h. K4 nStandard error, 标准误; o6 m Y# Y E7 W3 N q% t
Standard error of difference, 差别的标准误
5 i; k& i+ N- a, W& |Standard error of estimate, 标准估计误差
0 K' z# m' `2 wStandard error of rate, 率的标准误
' N/ }4 B2 [/ d8 Z2 x* l8 B4 `) R. K) rStandard normal distribution, 标准正态分布
- |! D, v% x; t; S$ fStandardization, 标准化
N; L( @5 w9 `8 r6 RStarting value, 起始值
* Z, q1 t" ~( m9 m) l' ^& sStatistic, 统计量8 \ }' T: Z; ]- a/ b: ^
Statistical control, 统计控制
) P$ q; B. b- B; R7 }Statistical graph, 统计图. W8 u# U4 |: A8 K% U
Statistical inference, 统计推断8 B. }/ U$ D2 F } t0 q. @; m
Statistical table, 统计表) ?0 t: @4 O @' t% p( c' n# |4 J/ ~
Steepest descent, 最速下降法
) Q/ h9 ~$ l) b' W6 LStem and leaf display, 茎叶图
) \" v4 h* ?$ {% O4 U$ E5 rStep factor, 步长因子( Y; R' o. K9 D7 z
Stepwise regression, 逐步回归5 S* C3 n: |7 F: O$ v' Q" T" J9 p
Storage, 存
# ?8 W- ]& o: t! J- u# nStrata, 层（复数）
. L" D! @+ M) c3 B* _+ c% R$ fStratified sampling, 分层抽样
! H3 @0 v. c6 O# @0 OStratified sampling, 分层抽样
4 I* U% \8 Q" JStrength, 强度. q: r! o3 v- s
Stringency, 严密性
; w1 ]- _$ R9 Q9 nStructural relationship, 结构关系% d/ s9 f' L2 k5 E* Y- d5 B5 X
Studentized residual, 学生化残差/t化残差
( D, w2 S+ X. z; {% Y" e" f+ d1 Z+ ZSub-class numbers, 次级组含量1 \" I2 T- p9 Z- R# p N! u
Subdividing, 分割6 I1 t, R$ C' V
Sufficient statistic, 充分统计量
# c9 Z/ f5 G; A8 y0 s) dSum of products, 积和
" e3 K- M3 N, N+ G2 F& iSum of squares, 离差平方和
: m3 H* v% t: @; \$ ?Sum of squares about regression, 回归平方和
4 X0 K& [' \1 K: u" mSum of squares between groups, 组间平方和& X1 U8 r: s7 U
Sum of squares of partial regression, 偏回归平方和7 P, D1 `# r, `0 G, t+ g- K
Sure event, 必然事件
$ Q! Q6 E: U; w. T& ~( d, L9 D/ VSurvey, 调查% P+ p8 n% E% `' y
Survival, 生存分析; j% H7 \" a X
Survival rate, 生存率
`5 ^+ D( S7 {# Y& k NSuspended root gram, 悬吊根图# X- }, p2 B8 K
Symmetry, 对称3 o" ]; I* h* h) Q& j" F, b
Systematic error, 系统误差
+ I' p ~4 m+ k+ z3 X0 J- bSystematic sampling, 系统抽样
, z0 d) F1 |; L zTags, 标签
6 R8 Q; u; m8 R m! uTail area, 尾部面积1 C1 d2 L$ Q* Y# ~! O* [) H9 c& k
Tail length, 尾长0 F+ t, g! J; n/ q' `
Tail weight, 尾重
' H9 L& ~" H* y2 H2 OTangent line, 切线( c* r! T: f$ f8 C% `3 h
Target distribution, 目标分布$ n8 O% g. F( l- ~+ o% {
Taylor series, 泰勒级数" O5 f/ F$ M- e) H2 Y& l2 `# K; w9 R
Tendency of dispersion, 离散趋势9 x& d" V$ D' t2 d; U1 b6 w" t
Testing of hypotheses, 假设检验
l4 p6 F# H0 D. i6 \Theoretical frequency, 理论频数+ L2 d2 z4 I5 t* k
Time series, 时间序列' x+ Q \- |8 O) R' _3 _
Tolerance interval, 容忍区间
- ]3 z8 V' A4 @. z( p- }8 [Tolerance lower limit, 容忍下限9 B% |" O! e, D2 f9 U0 r3 m! E2 C
Tolerance upper limit, 容忍上限
8 l; T0 {0 ^4 m& B+ j0 U3 ETorsion, 扰率, |) D2 }0 n2 J; J
Total sum of square, 总平方和
; @3 H. h' I- Z+ R, ~/ uTotal variation, 总变异
4 P- }! S, d; o8 B& M3 {Transformation, 转换
& ?. S; @3 C$ R* v5 n9 cTreatment, 处理5 f4 b% y: G# F% l% b2 c) p
Trend, 趋势8 h" A2 Y& d4 D1 T
Trend of percentage, 百分比趋势
" w/ F6 |6 _8 `, [: r6 gTrial, 试验7 _; R7 g5 ^! g, l& C7 H
Trial and error method, 试错法
, R; U' K, m6 C7 [Tuning constant, 细调常数/ x2 V( _. M K8 d; ^4 a
Two sided test, 双向检验+ Y9 F' G( B! g2 H1 [% y) J# b1 U9 W
Two-stage least squares, 二阶最小平方+ k; K& \) K6 p+ S2 w6 I2 R, \
Two-stage sampling, 二阶段抽样0 N2 B: z( x N; x
Two-tailed test, 双侧检验+ q& P/ }" {' K2 N) L
Two-way analysis of variance, 双因素方差分析+ X. L/ Q2 |% x/ w
Two-way table, 双向表" U5 ^! D6 {, r4 @/ J1 T5 X
Type I error, 一类错误/α错误- p9 d* _9 _: `! K- u* `* M8 n8 j
Type II error, 二类错误/β错误
. L; \; `% ~" J+ h" Z: b' n, rUMVU, 方差一致最小无偏估计简称: b* G) G; P* {/ H! b" J
Unbiased estimate, 无偏估计( S; \; S% `" H9 K8 |
Unconstrained nonlinear regression , 无约束非线性回归* c* ]/ ]6 p9 Y& S0 c }, v C7 _
Unequal subclass number, 不等次级组含量: C4 r+ v% V ]1 U! L7 Y0 t
Ungrouped data, 不分组资料
# n+ H* Q9 M8 n z# q; ?8 S% dUniform coordinate, 均匀坐标
+ k* L8 @2 k3 R+ v" e; sUniform distribution, 均匀分布6 c$ B* k6 P% y6 d6 C( n0 h4 E
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
6 n: L0 O& A& a0 r* V% I) @: @) j+ GUnit, 单元( T$ z* i9 p# u+ Q& d
Unordered categories, 无序分类
" E* t+ {: w: \# _; mUpper limit, 上限* R5 A7 l" c4 r, C
Upward rank, 升秩4 s& z7 g- } B, I. D6 B
Vague concept, 模糊概念
# B8 e- o R( e2 s0 g7 I! c( d& s- ]Validity, 有效性2 m" l; |% |" c8 X$ s6 @
VARCOMP (Variance component estimation), 方差元素估计
' M% [/ V, W5 z. g; r, _% yVariability, 变异性
# R$ h% \, a- XVariable, 变量
# \8 B# W7 d! Z) Z3 I/ FVariance, 方差# E, [! V5 w8 \
Variation, 变异* j Q i% e0 Y4 N- k5 t
Varimax orthogonal rotation, 方差最大正交旋转
3 T5 B; ]/ \6 e" \Volume of distribution, 容积
0 c6 {2 ` j' fW test, W检验
) S k' Z2 {4 V# w V" Z% b% gWeibull distribution, 威布尔分布/ }5 h5 T9 y: y! j, Q+ s$ R
Weight, 权数/ @" Z% i' Q( C8 ~* B. x
Weighted Chi-square test, 加权卡方检验/Cochran检验2 X- D8 i! M& b" V$ t- Q& l9 ~
Weighted linear regression method, 加权直线回归
$ S* u3 w+ h' YWeighted mean, 加权平均数* e4 W( i* v9 q# h
Weighted mean square, 加权平均方差1 Q5 j+ i) Y2 }9 h/ l W3 t; F% ?
Weighted sum of square, 加权平方和, ]4 y5 P$ I: i$ }. q
Weighting coefficient, 权重系数
" T5 i& H( Q8 W4 I2 {' G: bWeighting method, 加权法
3 N: o& Z T9 Z! s C5 w7 GW-estimation, W估计量
5 w# h" R) H1 ~' _% H: k u7 z/ RW-estimation of location, 位置W估计量2 j( q7 K5 {/ v: X g% L
Width, 宽度% m1 k; H: q0 w- T, Y
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验4 O# n& R( }$ {3 e+ v/ x
Wild point, 野点/狂点2 G& `+ _. M u8 k% E
Wild value, 野值/狂值
1 m, N" [& ^" ~7 J# JWinsorized mean, 缩尾均值
1 d! l1 M2 ?3 N' uWithdraw, 失访 & i& L- ^7 K0 n( K8 D* F
Youden's index, 尤登指数% f! S# v. D8 [' _! @" J2 ?
Z test, Z检验; u% ]7 n% t: \3 Y/ H; |
Zero correlation, 零相关
5 ^ {: d" X; H2 a1 f7 gZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
