|
|
Absolute deviation, 绝对离差
0 x! O. Q( ]0 Z. lAbsolute number, 绝对数
/ P' t* z5 s: D2 x- T* ZAbsolute residuals, 绝对残差
( ~- h6 `! x1 z. O7 p. F0 ^Acceleration array, 加速度立体阵
; x+ u0 Y; I2 G9 i/ `5 V- bAcceleration in an arbitrary direction, 任意方向上的加速度
! w: ?2 W. \, o2 P2 IAcceleration normal, 法向加速度. j- ~+ R& j/ \; `
Acceleration space dimension, 加速度空间的维数
1 Q/ W% x: O. M6 K& zAcceleration tangential, 切向加速度: [# \* _1 x$ w' n; _
Acceleration vector, 加速度向量
[ _* x3 I+ \- {, Z5 ZAcceptable hypothesis, 可接受假设+ O' F6 P6 v- I$ U; R! w2 J
Accumulation, 累积6 `* ^/ D; M9 i% J
Accuracy, 准确度
/ d. G; ?+ m) A6 x1 l' g5 c5 AActual frequency, 实际频数
% ]8 Z2 p# ^' q7 |/ nAdaptive estimator, 自适应估计量$ b# F* c, U5 R, @2 }' M
Addition, 相加
& d. {( p& ?* @Addition theorem, 加法定理
' V+ W6 ~. L9 V oAdditivity, 可加性/ j- x$ N, u. s+ V3 M! C6 T
Adjusted rate, 调整率9 Y$ n" {1 o9 ^# p
Adjusted value, 校正值
- {# w1 G/ ~) q9 P$ ]3 E8 DAdmissible error, 容许误差+ {+ W- k) y) D; W- S: t. Y: Y
Aggregation, 聚集性) x- o0 A q H% e* X9 p3 R
Alternative hypothesis, 备择假设
7 K8 Z% ], t- k5 n4 M* Z/ h3 iAmong groups, 组间, D, c. T# c- _8 b n( Q. V2 R4 j w
Amounts, 总量2 A4 p W4 ^( L. }3 K" |0 O9 p* Q
Analysis of correlation, 相关分析
8 }4 a1 k2 X* x, O0 U/ kAnalysis of covariance, 协方差分析$ ]: \5 `- e8 b* N% E
Analysis of regression, 回归分析
1 f* l: e9 I, g! bAnalysis of time series, 时间序列分析
* U; D0 q& `( d2 gAnalysis of variance, 方差分析
9 n$ g8 n3 B$ x, C7 Z4 H4 DAngular transformation, 角转换+ z( I' n$ @2 w3 m& C0 i; P% R
ANOVA （analysis of variance）, 方差分析
/ S6 a( W0 y; pANOVA Models, 方差分析模型
; u8 s2 V$ h6 h- O2 `Arcing, 弧/弧旋1 d8 U B# I+ E7 r& o
Arcsine transformation, 反正弦变换2 e! {6 W3 h0 E) V: s
Area under the curve, 曲线面积
6 L6 S$ a1 L9 o& m9 gAREG , 评估从一个时间点到下一个时间点回归相关时的误差 & I5 k, g0 X# a" G: F9 S
ARIMA, 季节和非季节性单变量模型的极大似然估计 0 ^3 I3 E- B- H! x* r
Arithmetic grid paper, 算术格纸2 C: g0 |" ~- x0 n" m8 d1 {- {
Arithmetic mean, 算术平均数
2 ^+ V& p, U& w; `$ t- L+ q1 {Arrhenius relation, 艾恩尼斯关系
& j, p# P; \% p0 k2 v$ yAssessing fit, 拟合的评估
$ p* z; \$ S; D4 R: {1 NAssociative laws, 结合律$ L# D+ e" T# S" d, g
Asymmetric distribution, 非对称分布
1 q0 X% S" \- y8 w+ L! PAsymptotic bias, 渐近偏倚
- U( i" G/ B* S2 Q! P! IAsymptotic efficiency, 渐近效率
9 z( D9 ^( y# r* bAsymptotic variance, 渐近方差( S0 g ^2 |) J+ X! Z0 w
Attributable risk, 归因危险度
9 }( z- v H3 L# d1 [+ [Attribute data, 属性资料/ {; ~$ ]! j' j' Z. `& L, ?; b! o
Attribution, 属性$ U/ {, U- S% H$ I. |; {+ r' e
Autocorrelation, 自相关
- h+ ?$ X9 r5 }% t2 V! L$ rAutocorrelation of residuals, 残差的自相关
! o# C5 X3 l$ P; w3 u9 fAverage, 平均数
/ x' x+ ` X4 Y5 {Average confidence interval length, 平均置信区间长度4 |9 z+ S" U4 d1 F4 M8 m
Average growth rate, 平均增长率3 M3 n, E# d2 j
Bar chart, 条形图* x3 f- L+ h* H. |+ Y
Bar graph, 条形图. A% K# y* l/ Z, r; U0 s
Base period, 基期
! q2 h1 J. D' L# a3 _Bayes' theorem , Bayes定理
# S* V5 z8 O: P2 VBell-shaped curve, 钟形曲线5 N: ?5 _: J7 u- Y" G, n$ @0 L
Bernoulli distribution, 伯努力分布8 X1 L, l E9 |( M* W. R
Best-trim estimator, 最好切尾估计量8 N; _ [- v/ s. ^
Bias, 偏性' s3 U+ v% R4 h0 o' h! q6 ?; J+ Z
Binary logistic regression, 二元逻辑斯蒂回归
7 _4 C7 e5 ?5 k; O$ WBinomial distribution, 二项分布$ K+ ^/ `4 E) g) z9 E
Bisquare, 双平方
. r d, n4 T# Z" A0 o3 A2 C iBivariate Correlate, 二变量相关
) e% R& v9 ] J% RBivariate normal distribution, 双变量正态分布' k) \! s) n3 W' [( `" X. m
Bivariate normal population, 双变量正态总体
/ G5 N, P2 z# S3 ~) Q4 zBiweight interval, 双权区间
5 z, o8 |) W1 V' `( @Biweight M-estimator, 双权M估计量% ?' f8 _$ g( N$ \3 P
Block, 区组/配伍组: x- D8 I* |$ ^7 J8 U1 J
BMDP(Biomedical computer programs), BMDP统计软件包
9 i0 Z* D0 }/ s- v# yBoxplots, 箱线图/箱尾图- t( \# g! f" o, o, Y) t; r
Breakdown bound, 崩溃界/崩溃点) Y5 N, ~8 ^( a8 y6 Z6 U+ A
Canonical correlation, 典型相关" M( Q* [0 V- n6 X! {
Caption, 纵标目
: `* S% g @1 sCase-control study, 病例对照研究
4 W4 b. H( z$ A6 Q; m* {4 mCategorical variable, 分类变量5 [" x5 {( E" t) ^
Catenary, 悬链线7 n& t; N, r9 m/ q Z
Cauchy distribution, 柯西分布
$ i# H R0 S' e6 w5 DCause-and-effect relationship, 因果关系
' J& s9 ^% d; X& I X |2 rCell, 单元
$ Y0 D0 W4 h# y" [- v: W: y- Z- XCensoring, 终检
' s: `4 n# q* d& U( q1 |, L- ^, b6 u* dCenter of symmetry, 对称中心$ |; G# E y, R8 G( W. C$ z
Centering and scaling, 中心化和定标/ d6 h; w9 h& x' |" G* T
Central tendency, 集中趋势
# H0 z) F6 J) u2 r8 a3 P: k8 GCentral value, 中心值" d) D- O' k4 M5 k- n
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测 A, X# f& W" I8 @* @$ i3 S
Chance, 机遇
, M7 p4 H- U- GChance error, 随机误差- Q& x! a0 t) l* r" f z+ f, P7 `
Chance variable, 随机变量
3 Z. {6 K& c% T2 N7 g/ MCharacteristic equation, 特征方程6 @* H5 o9 b2 r
Characteristic root, 特征根
4 \: j$ | m+ C0 JCharacteristic vector, 特征向量. ^6 I# l! S: A$ H
Chebshev criterion of fit, 拟合的切比雪夫准则
8 H( X6 J: C1 w7 A) H: l2 YChernoff faces, 切尔诺夫脸谱图 K8 l, p8 s% `6 m
Chi-square test, 卡方检验/χ2检验
5 E+ I, _/ Y o, t5 GCholeskey decomposition, 乔洛斯基分解
6 |5 D& w& R9 k% r0 FCircle chart, 圆图 : h& d$ v6 z5 f( c6 L, Y' g2 D
Class interval, 组距
. H ~ H/ T$ G5 S0 { c, YClass mid-value, 组中值
' B; f9 G2 P% D! aClass upper limit, 组上限' P; S7 P- Q/ F* K* A
Classified variable, 分类变量
4 N) n1 O: K. s) LCluster analysis, 聚类分析
8 ]3 S* P! h9 e8 w, h- t8 BCluster sampling, 整群抽样
; J, J, \. f3 o, }Code, 代码! S. X; a6 p! J! A; M! Z7 }
Coded data, 编码数据
5 U% d& `6 K$ {2 R6 g. B: h( J3 b3 ECoding, 编码
2 p; d3 m( y0 x, |: E' g4 ACoefficient of contingency, 列联系数
0 O5 [5 L }, ~Coefficient of determination, 决定系数
2 v( R6 v4 b) ? d0 zCoefficient of multiple correlation, 多重相关系数
5 ~! p* X2 _. K# a2 ]& rCoefficient of partial correlation, 偏相关系数& {$ X1 z# O ^8 ]: s9 E
Coefficient of production-moment correlation, 积差相关系数
$ j# A0 A1 F1 j! pCoefficient of rank correlation, 等级相关系数$ K9 y5 |8 s( q
Coefficient of regression, 回归系数
$ ~- Z& Y% X# R# I9 s: }* E3 g9 n4 CCoefficient of skewness, 偏度系数
! q! J: b* v9 U% dCoefficient of variation, 变异系数
- ~* q* t6 u8 `; `+ p3 k [Cohort study, 队列研究
. n& ^, B( n$ y$ n& v1 YColumn, 列! j- O3 p9 Y" b" z
Column effect, 列效应
' Y" ]6 C4 q& T4 [! }3 yColumn factor, 列因素
% \/ p; [* a3 C1 W: ?# XCombination pool, 合并
0 p$ X! v) j. N% ?# dCombinative table, 组合表
" k7 r% X( p; @/ H( y, iCommon factor, 共性因子
9 s& F" d" C; A4 A: k' m: ~Common regression coefficient, 公共回归系数+ x( q) |3 G& {3 l0 G# |/ Z1 f
Common value, 共同值' A# O7 w) v9 _" d
Common variance, 公共方差8 q: [4 u* F" c* `6 ~% t5 f7 z$ K
Common variation, 公共变异: I9 a, D& n1 R& _; H! V
Communality variance, 共性方差
0 F+ h7 w5 W- c4 Y3 NComparability, 可比性7 ?; _' l, E# s' s" {9 i3 c! z4 W. Y
Comparison of bathes, 批比较
+ }; ~4 W4 q% {% l0 Q. m2 D [Comparison value, 比较值
; ~4 M2 l+ A, V y& FCompartment model, 分部模型; x3 ~- N( \. f: ^, T0 c
Compassion, 伸缩
0 r, |, L- W; X# p8 g, {Complement of an event, 补事件
& |! ~: r& m- Q- nComplete association, 完全正相关; L0 A7 ]8 A$ `% p u
Complete dissociation, 完全不相关
/ U& k* x4 {3 F nComplete statistics, 完备统计量# [$ }0 w4 \+ b r( S- @& w. A& k9 I+ C. m
Completely randomized design, 完全随机化设计0 E5 V3 z( w% D$ O( S) q
Composite event, 联合事件
( T! Q* i6 l2 f a# Q+ jComposite events, 复合事件
$ h& S+ D% e9 xConcavity, 凹性
' ?8 j6 [- ?- U( c! b4 aConditional expectation, 条件期望
7 w4 j5 M; Q2 v7 _* M1 F% XConditional likelihood, 条件似然! I z" l" R0 k7 K/ F
Conditional probability, 条件概率" L+ g2 f. N4 B$ n& X. Y: y/ s
Conditionally linear, 依条件线性- @/ Q- s$ Y- K: A2 ]
Confidence interval, 置信区间* E( m) `3 K v, Q* L- m
Confidence limit, 置信限
: e) K, Z0 ^& YConfidence lower limit, 置信下限! H c. i( H. M( R5 F0 z9 J
Confidence upper limit, 置信上限
3 |3 ^- U" S" C8 SConfirmatory Factor Analysis , 验证性因子分析
! L/ `. O" c' dConfirmatory research, 证实性实验研究
" _0 @( U! C' {Confounding factor, 混杂因素
. L& {4 K" s- b4 u0 S$ O1 XConjoint, 联合分析0 ?# l0 v4 S* k& B
Consistency, 相合性
8 J% b! t/ p9 ^/ k' h9 J1 J6 C% r" hConsistency check, 一致性检验4 }; C+ p0 ~$ @
Consistent asymptotically normal estimate, 相合渐近正态估计0 A, c% u% s6 I0 w7 N0 [
Consistent estimate, 相合估计5 H f$ ^5 ]0 X) m+ e- ~9 N0 V* G
Constrained nonlinear regression, 受约束非线性回归
, ]# n- [% N6 V$ L3 wConstraint, 约束
( s# R$ F T& T) l# SContaminated distribution, 污染分布! ]! v, ]% M. P- D( U z! i; B
Contaminated Gausssian, 污染高斯分布
3 M; `3 C$ Z/ _9 ?Contaminated normal distribution, 污染正态分布& U; x+ v& n8 V3 w( B, S
Contamination, 污染+ L# w3 M6 v, l) i% v! R
Contamination model, 污染模型$ [' W3 O2 V& }- i; a
Contingency table, 列联表
! v; {. \/ ?) aContour, 边界线1 u6 _# K" g2 c/ Z
Contribution rate, 贡献率
9 _9 ~9 G8 i) ?9 U# d! I! f, LControl, 对照: d9 r# q; x. d7 s/ r5 B& b
Controlled experiments, 对照实验+ t" @1 }; b1 Z% p0 B
Conventional depth, 常规深度
% L' P T! a. oConvolution, 卷积+ p4 E3 |$ d" \ q) z4 F* m
Corrected factor, 校正因子
$ i' Y; Z( N2 U% NCorrected mean, 校正均值: ^, {1 e; W% n" D
Correction coefficient, 校正系数
; n& g1 W* U7 d; m$ {Correctness, 正确性
/ `) t0 h$ k2 ?Correlation coefficient, 相关系数9 ?8 R9 {2 j% Z0 a6 f
Correlation index, 相关指数
* O- d4 H' U1 v7 \ {3 N5 wCorrespondence, 对应
- h6 S9 R1 N6 p% I5 }+ p: P2 wCounting, 计数9 s+ U& b: W" w: o2 F2 v8 Z" ~
Counts, 计数/频数7 W' x* s4 K: `0 i: d! v" }
Covariance, 协方差 B. `$ `# {& a9 X* a) {+ n
Covariant, 共变
4 ]! F8 E# b# {8 sCox Regression, Cox回归
F# N. k+ P( f. [4 ?Criteria for fitting, 拟合准则) J" S" N, A9 v- W
Criteria of least squares, 最小二乘准则
8 F$ U. _2 {1 G: u) hCritical ratio, 临界比
5 Y: X) [+ G2 K$ CCritical region, 拒绝域
% q& K4 U0 C1 N( D9 VCritical value, 临界值
0 j! d& B/ R. mCross-over design, 交叉设计5 {% l9 x! P" u! C# B( x% ?$ a8 h
Cross-section analysis, 横断面分析4 g) ~( O- b4 A; L
Cross-section survey, 横断面调查: [9 j1 N' e. G3 A" B5 Z
Crosstabs , 交叉表
" |; L1 D7 ^: qCross-tabulation table, 复合表
' x/ Z! F. f% r! s0 v- xCube root, 立方根
' x3 C* y# x5 \4 j. u) N$ q, z; F: uCumulative distribution function, 分布函数
& g# p+ E V- j+ L7 H0 P/ S9 Q0 dCumulative probability, 累计概率2 G4 X4 z( r% h/ S
Curvature, 曲率/弯曲; e7 n% m Q4 v3 l. K8 X- P
Curvature, 曲率6 @8 B: d: q: Q: u0 p- W
Curve fit , 曲线拟和
# v3 k, \" x7 }) T! ~Curve fitting, 曲线拟合
% |, ~ S9 Y; O" |Curvilinear regression, 曲线回归
. s: n7 i* }; V3 uCurvilinear relation, 曲线关系+ F2 t/ n8 M1 b: C* _( a
Cut-and-try method, 尝试法
: c: M2 e' U& Y3 @9 e+ KCycle, 周期) ] ^6 {5 i# j! L1 L
Cyclist, 周期性 {6 o2 Z# A* c: O# [. S
D test, D检验
8 ~. k* q9 |9 ]0 B# ?Data acquisition, 资料收集7 j" y9 S9 G- m1 g
Data bank, 数据库
+ {5 M0 v( L' s( X# j! OData capacity, 数据容量
$ t4 F+ \- R- [& E2 V4 ~# _Data deficiencies, 数据缺乏3 x$ ~% Y# u9 W- g, G
Data handling, 数据处理
Y# c) o9 I, \7 x! t: G2 ^Data manipulation, 数据处理) g: K. G4 d& q B$ G$ R# J
Data processing, 数据处理8 [4 b& [4 g9 l7 _8 Z% D. j$ f
Data reduction, 数据缩减8 z4 F) ^0 m" O
Data set, 数据集
! U9 T7 G" C* [8 u! {( N, {Data sources, 数据来源
, q- ~$ R" C+ K: XData transformation, 数据变换
& u5 X# s$ \, kData validity, 数据有效性
6 N9 S/ C R( u# x' LData-in, 数据输入
7 s- l1 Y3 U! u" x& U3 B8 F2 }Data-out, 数据输出5 D; A! G( ^5 M( I
Dead time, 停滞期5 j& u/ E, T+ M0 I
Degree of freedom, 自由度4 P! T# k. U$ c+ E; M' S
Degree of precision, 精密度
9 M, L* A |! O& F5 E- {Degree of reliability, 可靠性程度
: q5 N ^( p; f4 t$ yDegression, 递减- t) x$ z) I) C5 [
Density function, 密度函数
5 J* L' H# D! S" N1 d, m5 yDensity of data points, 数据点的密度; e$ h% h2 _# \. C
Dependent variable, 应变量/依变量/因变量! F8 o" U* G1 a! z9 D' R9 ?3 m4 H2 [6 j; L
Dependent variable, 因变量
+ Z: \6 F. E6 O: X3 `Depth, 深度- Z/ X7 U/ m/ h
Derivative matrix, 导数矩阵
& ~$ `, O8 V7 H" Z" vDerivative-free methods, 无导数方法
+ M8 ]/ K: P* G; }' z6 t1 I4 }5 ]( ZDesign, 设计# O* e9 E0 b/ S' T/ p
Determinacy, 确定性
% A8 q% J. W* Y; R/ W; o% X: n) `( `Determinant, 行列式
5 a0 l# g5 n; n2 ZDeterminant, 决定因素
+ V! _: U/ W% zDeviation, 离差
" Z% e2 X. ?" LDeviation from average, 离均差
8 X! C! |! z7 i, k; K) TDiagnostic plot, 诊断图7 O; O0 A' Q7 V* n0 c( h! Y) H: U% i
Dichotomous variable, 二分变量
: [" \. a5 r) i- V' ]; r: tDifferential equation, 微分方程
) N3 s, f5 C/ R3 E* BDirect standardization, 直接标准化法
2 I$ q+ p9 q6 X3 I8 V/ s; o' E# pDiscrete variable, 离散型变量
/ w. _. b) |( s5 E2 B+ FDISCRIMINANT, 判断
; L* @ B; ?$ O( e9 sDiscriminant analysis, 判别分析! G/ H E1 X3 |" a
Discriminant coefficient, 判别系数
) \$ `8 m' Z- V) R; }8 aDiscriminant function, 判别值 x! ^/ `- ]- b$ d5 O* e* P: j0 m
Dispersion, 散布/分散度8 M6 Q7 ]7 a5 w5 }8 I. _
Disproportional, 不成比例的* z! D+ T! h! b3 g+ r5 G
Disproportionate sub-class numbers, 不成比例次级组含量6 z4 M# F! n- A3 N' y W: [, R7 M; g% h
Distribution free, 分布无关性/免分布
2 {# {( U3 ~7 V9 q8 oDistribution shape, 分布形状+ |2 }: c- A; J/ d# _* Q
Distribution-free method, 任意分布法
) H7 k4 r- w" h7 {9 t/ g, nDistributive laws, 分配律# E! I6 r" p- [$ h) U& z
Disturbance, 随机扰动项
& F) E; `+ G; N) X- G$ n0 dDose response curve, 剂量反应曲线% ^( L" V5 B$ l# ]. I$ t) b( k
Double blind method, 双盲法
1 z' t; r) n+ j& q) zDouble blind trial, 双盲试验
+ e6 W( N5 V+ W; m+ MDouble exponential distribution, 双指数分布$ R, q, ^. U( g, p* M& G% E: s* A
Double logarithmic, 双对数( S# Y! p9 X- Q- m o$ i6 k
Downward rank, 降秩, G8 V6 U, u0 t% v; B0 E
Dual-space plot, 对偶空间图8 v$ h7 j4 o0 F0 d$ a) r. H# r
DUD, 无导数方法
/ u6 E2 U- O& c, p% ^- TDuncan's new multiple range method, 新复极差法/Duncan新法
( A) A9 e2 r5 J; U/ d9 C. rEffect, 实验效应: O! J a$ d; x# w. g& w c
Eigenvalue, 特征值8 z! k( u& {3 p: d& O3 e
Eigenvector, 特征向量6 E) f0 P+ C0 d; z" x' k
Ellipse, 椭圆% N0 x9 {8 O9 [/ R- G
Empirical distribution, 经验分布# l3 |9 H( \2 G" k% E# o" B
Empirical probability, 经验概率单位8 L9 T7 {3 {; X" U- r3 |
Enumeration data, 计数资料
' P6 Q0 P& H7 b5 I* a9 {4 QEqual sun-class number, 相等次级组含量& a/ M3 A3 _. z3 j) }
Equally likely, 等可能
- S" Y( A+ o7 X; z8 R; C4 GEquivariance, 同变性
$ @: Q3 d4 C+ c$ y; Z7 EError, 误差/错误6 s/ n( i; X; @5 g8 D( b
Error of estimate, 估计误差
1 d3 L) \# ~0 t. zError type I, 第一类错误
1 M# j/ A& {6 h# v- j( K" RError type II, 第二类错误3 f. a6 W! m0 O0 d$ }% }+ V
Estimand, 被估量
7 ~2 F: a# L/ Z5 B8 fEstimated error mean squares, 估计误差均方
2 a' G. }- j% G# i$ H% W9 @6 ]- M3 iEstimated error sum of squares, 估计误差平方和7 {( S* y/ ~/ k) O2 [# L7 g
Euclidean distance, 欧式距离5 f9 \3 y: p& C" r' m
Event, 事件5 A$ J* a' e0 A; Z; x
Event, 事件
5 B! ]1 \" y& |5 gExceptional data point, 异常数据点# {7 J P3 o! ~; L8 a E) b0 g- G0 J
Expectation plane, 期望平面2 J, _! I4 I B& b: m
Expectation surface, 期望曲面$ ~- Z3 W0 N$ B. s8 P
Expected values, 期望值: u. s0 y. J5 q+ ~7 E
Experiment, 实验
( v" y8 {9 d+ _$ z- w$ Y6 }4 h" xExperimental sampling, 试验抽样! [& M' O/ H. U! J# X; U) a u
Experimental unit, 试验单位( K, w3 O' V% D6 o- E; A
Explanatory variable, 说明变量& G1 S! N- f% e* `! H
Exploratory data analysis, 探索性数据分析
. N$ z7 f( W% WExplore Summarize, 探索-摘要7 R3 S6 t ?: B D' s- K3 V
Exponential curve, 指数曲线' K9 o. P6 c. i& ^* U
Exponential growth, 指数式增长1 t3 a+ n9 y- l! O# \
EXSMOOTH, 指数平滑方法
) v* T$ C4 L f v9 K$ [* JExtended fit, 扩充拟合, U! X9 {7 W/ G& h' a h/ I' P! d
Extra parameter, 附加参数
1 b' I8 a) V* P$ c% k" @Extrapolation, 外推法5 i" K8 ?! {; @9 r O6 l; ^
Extreme observation, 末端观测值+ c1 N- t3 ~! p) u1 X c6 ]. l
Extremes, 极端值/极值
. J* J6 }/ [7 K5 N qF distribution, F分布
i. c3 h" J, ~/ _F test, F检验; M7 I1 F5 u8 B" ~
Factor, 因素/因子
% c4 q; |4 H" I3 O$ HFactor analysis, 因子分析7 [+ I0 ^. n& M* r0 |
Factor Analysis, 因子分析* K. T9 } l0 }/ q5 r7 N
Factor score, 因子得分
, e V2 A5 g- E0 [: B! g& PFactorial, 阶乘- {, O" b( b! Z0 i( K2 `/ P
Factorial design, 析因试验设计
2 Y- a% R$ q/ S% VFalse negative, 假阴性+ \! b9 C. P+ V3 K6 f# H
False negative error, 假阴性错误
$ a" R$ k2 x. x D d6 lFamily of distributions, 分布族
& s" ~* D% G* H2 @, BFamily of estimators, 估计量族
$ I9 h3 @! h6 i2 s! AFanning, 扇面
- ~/ z* U' i8 q7 _Fatality rate, 病死率
0 H! K) N5 j6 y N* x" q! V* }Field investigation, 现场调查
d1 ~9 c5 B3 e! B* FField survey, 现场调查, k5 e n" D" K" [( w, I4 A! W
Finite population, 有限总体
' i, S S1 m' Y4 ]3 y. E5 HFinite-sample, 有限样本( ^! l' ^- ^+ i+ b
First derivative, 一阶导数
5 O- ]+ }' W1 r/ H" c3 ^First principal component, 第一主成分
, N! K' F/ Y# N, a, J) _First quartile, 第一四分位数
* U! @6 \9 L7 ?" K9 t- R0 n$ ?Fisher information, 费雪信息量2 P+ V7 @& k/ c# p% C
Fitted value, 拟合值9 [) J: i" ~% v
Fitting a curve, 曲线拟合
% {9 b3 F3 _9 e& c$ \$ cFixed base, 定基5 K8 N! S+ @3 @/ A
Fluctuation, 随机起伏
8 P) u! U4 O6 Y# b: E2 g! yForecast, 预测7 N$ }1 I( y& {% |
Four fold table, 四格表
0 j; v! _6 W( NFourth, 四分点) m/ E; Z6 t9 h X* T- G, N
Fraction blow, 左侧比率
( ]/ J3 O) y, ~4 X" k% r- J% oFractional error, 相对误差' k* I7 u* N7 A
Frequency, 频率9 `- |! d! h) d7 x2 ~3 {" h
Frequency polygon, 频数多边图, x# n4 b' D2 }; E$ o2 \9 X2 ^
Frontier point, 界限点! d' d7 H6 z, Y4 X$ I! U0 v
Function relationship, 泛函关系3 \1 M1 _' D; @4 C
Gamma distribution, 伽玛分布
. C" U- Y- x$ p$ `Gauss increment, 高斯增量
& L+ E. p' a0 H/ k) K3 }4 S/ \Gaussian distribution, 高斯分布/正态分布
7 d7 |4 C+ R: @$ r( a0 MGauss-Newton increment, 高斯-牛顿增量
" U, v' e6 i9 d J' i. S4 O RGeneral census, 全面普查
9 X. w# ~( M) x- R y ~$ l: TGENLOG (Generalized liner models), 广义线性模型 ) q0 N6 p* l/ Q
Geometric mean, 几何平均数
, k o! o. r" j* jGini's mean difference, 基尼均差
" T" A' j v5 k0 _& `GLM (General liner models), 一般线性模型 ( }% \# b0 L2 a x
Goodness of fit, 拟和优度/配合度
2 a% i J! v! c, p$ _Gradient of determinant, 行列式的梯度# n/ o' Q+ Z, B
Graeco-Latin square, 希腊拉丁方
2 x7 {5 e" ~1 { L( t+ H1 gGrand mean, 总均值
( h' v; Z( f# r8 \* q& ]Gross errors, 重大错误3 P! O. S; L% [2 j7 f
Gross-error sensitivity, 大错敏感度9 r& t. O: W; o- V
Group averages, 分组平均+ F* s& c% [0 u: q# e! |0 V9 @. `1 b
Grouped data, 分组资料& H. r7 B. ?% D( a" ~
Guessed mean, 假定平均数
( _: H2 v+ v; ^. b% ], h% s |1 r) EHalf-life, 半衰期, G. n' r) ]8 {7 }+ p9 H* a0 Q
Hampel M-estimators, 汉佩尔M估计量6 u E6 x% i6 D2 n
Happenstance, 偶然事件: H2 W) l: t6 G) D: q8 ~- O W7 }
Harmonic mean, 调和均数6 L0 R, I+ O# L# z* e+ f) O
Hazard function, 风险均数
+ q |7 @, e; x/ k9 R' f) WHazard rate, 风险率
: o7 F8 m/ x, Q8 d' GHeading, 标目 ; ]; h4 R5 \4 \' {
Heavy-tailed distribution, 重尾分布
/ T7 i2 L) d$ wHessian array, 海森立体阵
3 O& d; X. O/ n. i( qHeterogeneity, 不同质2 l5 p2 e8 G6 I( Z0 h' u T3 U! {
Heterogeneity of variance, 方差不齐
- ~/ d7 a+ R* ~5 y3 R( e- D6 s7 hHierarchical classification, 组内分组/ R4 f3 F) c) }( O! s0 k* q+ ?# k; E
Hierarchical clustering method, 系统聚类法
: l- ?! \8 r% }! hHigh-leverage point, 高杠杆率点& k3 {' C3 N, M: x' {
HILOGLINEAR, 多维列联表的层次对数线性模型
, s$ t# b! I; EHinge, 折叶点! }$ a! l+ W# D: U- H% n. ~, `& q
Histogram, 直方图. t9 _! [, F5 r$ n
Historical cohort study, 历史性队列研究
. `; C4 l5 _1 O4 @+ t! P+ v o0 lHoles, 空洞" s, M0 Q4 L7 k
HOMALS, 多重响应分析: X3 C- @, P9 F1 g5 E
Homogeneity of variance, 方差齐性
2 D8 t2 c7 a0 T4 {! dHomogeneity test, 齐性检验4 }# Z/ o1 @ G
Huber M-estimators, 休伯M估计量2 X* `- r) n+ @9 f
Hyperbola, 双曲线, z9 f6 d1 }7 k! I1 f& w! l7 Z/ @0 t
Hypothesis testing, 假设检验
- Y% q, m1 \7 Y8 _1 @. g1 T2 L3 PHypothetical universe, 假设总体- q0 X" |& c1 H( E0 J& t
Impossible event, 不可能事件
$ p! p" |/ t% L! C& o0 }- CIndependence, 独立性
7 ^ c ]( w v7 {# c: DIndependent variable, 自变量. Q5 ^# G- T+ n" s n$ ~2 ^
Index, 指标/指数/ y" ?& E- \: w+ M8 U* } _0 b. L
Indirect standardization, 间接标准化法
; W- S7 z% c7 t: F" Q2 yIndividual, 个体
5 C" Y8 C6 `* Z6 |/ uInference band, 推断带
' J- _- B) ?/ hInfinite population, 无限总体 p( C3 i: [0 W6 |8 p2 E
Infinitely great, 无穷大) A3 S& N; T j9 I
Infinitely small, 无穷小
& A+ E+ f/ s9 z! J# M6 @/ e! @Influence curve, 影响曲线. Q+ l6 X; Z4 e4 R; r$ M) e& w
Information capacity, 信息容量
; x* y/ C, D! F, mInitial condition, 初始条件
9 p9 |6 Q9 n. [' \7 N* `# bInitial estimate, 初始估计值* C: X T1 }4 t' p) b6 P
Initial level, 最初水平; X, l) L( G, W% A
Interaction, 交互作用
1 t$ r0 t: h3 KInteraction terms, 交互作用项
6 l* R4 T4 t, p0 h: QIntercept, 截距6 t2 b! l4 i. @
Interpolation, 内插法
$ @9 M$ S# g% n) j7 [7 ?5 MInterquartile range, 四分位距
9 `6 f% z% u$ t6 c2 j& V+ h, B3 zInterval estimation, 区间估计
% u1 F' F/ o4 Q2 s# oIntervals of equal probability, 等概率区间+ U. [" y. P0 y/ f5 r
Intrinsic curvature, 固有曲率
: \, s# A( [9 j/ mInvariance, 不变性
9 S$ \4 H7 M, H1 mInverse matrix, 逆矩阵/ m8 I* c# R5 {2 U4 s* j
Inverse probability, 逆概率
" Q* N" K# ~" hInverse sine transformation, 反正弦变换
- s( W8 I( U/ O: [& L. Z ~, GIteration, 迭代
* Q. k8 T% p/ M2 V$ HJacobian determinant, 雅可比行列式$ D+ ~! T* a" t( b
Joint distribution function, 分布函数 D# ^+ k. x8 X" j- O
Joint probability, 联合概率5 m: @7 p- U- T: @" o" X
Joint probability distribution, 联合概率分布. h$ f3 t( h b: Y3 |" U& V4 w2 d
K means method, 逐步聚类法5 L& g7 ^ l p6 _ b+ h9 T8 K8 |
Kaplan-Meier, 评估事件的时间长度
- h/ r2 a5 m+ v2 j: T& p* f7 OKaplan-Merier chart, Kaplan-Merier图
6 H4 A m" O$ b: s; t( WKendall's rank correlation, Kendall等级相关$ r3 l5 C8 q$ g" K0 Y* h
Kinetic, 动力学, W& q1 S9 c8 s
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验% |0 y o0 O" n b" P
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
3 l% i) ], s0 v& E+ }+ U4 S4 PKurtosis, 峰度* ^1 k E( N! X! o( m, B
Lack of fit, 失拟
3 z( G) w7 @8 T7 g8 V8 eLadder of powers, 幂阶梯
4 [1 v- [; G# NLag, 滞后
! R* C0 C T2 p4 VLarge sample, 大样本
* H! ?6 ^$ T; G! b% u9 P: A: ]+ QLarge sample test, 大样本检验2 z# K3 _5 v w' e
Latin square, 拉丁方
/ _- h# E7 A4 ?) ?$ qLatin square design, 拉丁方设计
. e7 Q1 j& G9 R4 w! ELeakage, 泄漏
! z1 U4 e* x7 _0 j+ d" z) xLeast favorable configuration, 最不利构形
) q: B3 o* q+ p' k! t) v6 N, CLeast favorable distribution, 最不利分布. t4 w! \4 q, P" d1 p
Least significant difference, 最小显著差法
- q& z; d. D& z1 yLeast square method, 最小二乘法2 I) f5 z6 M5 _5 w$ u
Least-absolute-residuals estimates, 最小绝对残差估计
+ f; l) K! _ j5 V$ y5 v/ MLeast-absolute-residuals fit, 最小绝对残差拟合$ z. v. j/ F! u
Least-absolute-residuals line, 最小绝对残差线! A; V8 C& m5 q) K' @
Legend, 图例
2 W/ W P& }1 R. {L-estimator, L估计量
* S7 j1 u/ w+ k \; W' K$ u: V! v# IL-estimator of location, 位置L估计量
1 M) p p* \; x+ }8 GL-estimator of scale, 尺度L估计量7 m% L" \. I5 m6 e
Level, 水平
4 S0 s8 K- ~5 q/ y8 r( s% V% lLife expectance, 预期期望寿命
) p4 o# x( _! l6 _; W- U vLife table, 寿命表
$ w2 k! H/ x6 \1 g3 v1 L- ^Life table method, 生命表法
+ }3 D* a; O. K: Y% vLight-tailed distribution, 轻尾分布
$ {+ K! A; H0 Y; ^* x1 |+ lLikelihood function, 似然函数4 ^) n8 n% F$ h% K6 \4 s4 `
Likelihood ratio, 似然比
( V& K2 `3 ?. wline graph, 线图8 t0 m0 Y5 h) T. o
Linear correlation, 直线相关! t2 S4 N0 T3 v! x0 _" D9 r$ t4 i
Linear equation, 线性方程
& {- d! P3 C4 y& X( p* ELinear programming, 线性规划2 c& b1 ?. c3 a& r$ l
Linear regression, 直线回归
0 F7 G: U6 o3 Q; e8 T# J0 l9 RLinear Regression, 线性回归+ R) T, F: M- C; U) f/ K
Linear trend, 线性趋势
4 E% v9 f5 M1 C8 HLoading, 载荷 . O$ l6 W4 o' v- A* d+ m
Location and scale equivariance, 位置尺度同变性
3 T: x8 D2 h) ~/ y& J) M- H7 S( g) lLocation equivariance, 位置同变性
, k/ g; U2 h' _( B" S, ~; ^! kLocation invariance, 位置不变性
- U3 Y/ H& ]5 \" G. Y2 _7 WLocation scale family, 位置尺度族
& G0 c6 f9 X. M3 j5 L0 I2 v" FLog rank test, 时序检验
$ P1 b: D: @4 i+ Q8 nLogarithmic curve, 对数曲线 L: Z- K4 ~: H L. v
Logarithmic normal distribution, 对数正态分布
) r( j) d$ g; D' XLogarithmic scale, 对数尺度
# b9 Z& q6 }* u7 ~( Y5 ~Logarithmic transformation, 对数变换" T: L) W4 M" w0 r$ `+ F- \ @
Logic check, 逻辑检查5 G+ s; J5 u. ^* M
Logistic distribution, 逻辑斯特分布) U* D! }- [$ c9 U% X" C$ }2 i( e
Logit transformation, Logit转换: }1 n9 v. d! R! }, W# i7 g. A
LOGLINEAR, 多维列联表通用模型 ' {: V# @ y: u! n0 @- ^( }/ S
Lognormal distribution, 对数正态分布+ T& s$ j q* ~9 u
Lost function, 损失函数
- h: h7 [: X+ m' M$ [. ALow correlation, 低度相关% v+ O. F6 t9 @% U
Lower limit, 下限
* @% k8 K$ v$ N; m6 T7 j# S4 _Lowest-attained variance, 最小可达方差+ s% e- V" m- k" ]. Y/ U
LSD, 最小显著差法的简称0 C# Y) ^6 B. Y9 g1 ?9 f+ Q! C
Lurking variable, 潜在变量2 q: R% [. r( ~) z) n. H( p
Main effect, 主效应
; D( M3 Y6 F4 F4 C* Y* {Major heading, 主辞标目
" t9 s1 O9 x+ f4 _, C' ZMarginal density function, 边缘密度函数, U8 f% I3 B' T2 s- X
Marginal probability, 边缘概率% ~6 d) e8 h6 y
Marginal probability distribution, 边缘概率分布# Z- \: x2 U, D+ y
Matched data, 配对资料8 ` A" E% P. A5 E% G1 m H; T6 x
Matched distribution, 匹配过分布
- f, {$ r. Z. r0 Z9 XMatching of distribution, 分布的匹配) i" \0 g# E7 W0 i' n# S4 o
Matching of transformation, 变换的匹配, x) A8 _% ?2 O8 c/ ~; B! ]
Mathematical expectation, 数学期望3 j5 P0 f9 m! O+ N( W8 e
Mathematical model, 数学模型
# U7 F. o- s( Q/ W, v4 c6 W3 tMaximum L-estimator, 极大极小L 估计量
0 g; Y) s; A3 ]! |5 v5 n/ a1 b& ~# ^Maximum likelihood method, 最大似然法& Z5 e. z! N. w7 Q- B+ K) g5 R
Mean, 均数
( i" y3 \4 L! y7 ^# Q8 VMean squares between groups, 组间均方
+ b: O& g7 v# e1 {/ k6 \Mean squares within group, 组内均方
% {6 ?& [9 V9 ?( sMeans (Compare means), 均值-均值比较/ B u* ^" ^- R1 R2 j
Median, 中位数+ W' {# C# e# `6 r) M! }+ m9 I
Median effective dose, 半数效量) i+ Y9 z, G& t* L( r4 [, R3 u
Median lethal dose, 半数致死量
4 P4 B; _6 ^( a2 B) dMedian polish, 中位数平滑
- C% r" |7 P+ kMedian test, 中位数检验
7 c; Y) Z0 R$ I, _$ _4 xMinimal sufficient statistic, 最小充分统计量
2 j) e# {; B$ ~2 U* [% eMinimum distance estimation, 最小距离估计2 h) R& h! J w; L1 h
Minimum effective dose, 最小有效量
/ H7 y1 `1 D |0 ?- ^$ DMinimum lethal dose, 最小致死量
, t6 D3 |0 K$ F* k6 S5 R uMinimum variance estimator, 最小方差估计量/ {% o& D1 d1 m5 d; {' C P; d
MINITAB, 统计软件包
' C) R4 y) f b1 l! ^Minor heading, 宾词标目7 i3 R3 G2 c C4 d8 k& |% d- F1 [
Missing data, 缺失值) g+ {. B$ L5 r% W
Model specification, 模型的确定
7 |3 X; A9 d7 h- C0 m( A' z7 sModeling Statistics , 模型统计
1 ~" {$ @ D" [+ d( cModels for outliers, 离群值模型' k5 v; K' q: q& T
Modifying the model, 模型的修正3 \9 p& r7 S( Z7 |4 Q
Modulus of continuity, 连续性模: M5 A4 \; J( b/ q
Morbidity, 发病率
" H. \) C2 M: P, o# G7 h* w! SMost favorable configuration, 最有利构形: ]) |. f, J% S; x3 S8 v7 C
Multidimensional Scaling (ASCAL), 多维尺度/多维标度; h2 N4 Y8 s1 X
Multinomial Logistic Regression , 多项逻辑斯蒂回归2 h, D2 c, \. ?% L G$ l0 @
Multiple comparison, 多重比较
; o% p0 p: V! j9 u: h: b% aMultiple correlation , 复相关5 z; O. I* w; B7 _
Multiple covariance, 多元协方差6 r4 M4 I0 P8 S+ p$ `1 w
Multiple linear regression, 多元线性回归6 b; }) l$ q$ {1 o# N m
Multiple response , 多重选项
7 z) l2 h( j" r+ E! JMultiple solutions, 多解
" L1 m) G$ z- m* C: V, A4 r6 nMultiplication theorem, 乘法定理
* P3 C8 c& g* p3 t3 N% M' D. g3 UMultiresponse, 多元响应
& `7 ~7 R4 o0 K9 r. A' fMulti-stage sampling, 多阶段抽样8 j( B8 K! [; Z. {( r
Multivariate T distribution, 多元T分布. ~; i( ^7 [1 P' Y( e
Mutual exclusive, 互不相容- U' O7 \! T' [
Mutual independence, 互相独立
( _6 ]2 A+ q# I% \4 y8 gNatural boundary, 自然边界
* s5 h i" C6 l' A6 MNatural dead, 自然死亡
( U( I$ A4 O0 W3 LNatural zero, 自然零9 l7 z0 a# R8 m* Y Z9 D
Negative correlation, 负相关; h8 H! [# P! x* }( |" L- U
Negative linear correlation, 负线性相关
' Z: ], @" m5 q4 W# ~" p0 MNegatively skewed, 负偏7 q. g d( A1 y# p* ^" j" `2 s) W
Newman-Keuls method, q检验
+ S& p- S J7 |/ UNK method, q检验
2 X4 O8 f7 p+ xNo statistical significance, 无统计意义
; w. T7 \( B7 Q4 ~9 Z/ ?" K, {Nominal variable, 名义变量
, m5 [* B4 k& q& i, BNonconstancy of variability, 变异的非定常性3 ~4 g; p4 l) Z0 t5 j) i' Q2 z
Nonlinear regression, 非线性相关4 T) {) W& {* ~2 R, h4 c1 e+ D
Nonparametric statistics, 非参数统计
8 x% k: x% |- P& b( |, uNonparametric test, 非参数检验
0 S( R; ^' _" u+ mNonparametric tests, 非参数检验; E* Y( }, @" ~; G4 q0 p2 t7 r; p
Normal deviate, 正态离差: J, _) G/ j$ p- \- s
Normal distribution, 正态分布
2 @3 @+ r* Y: S6 c' t( V$ g/ jNormal equation, 正规方程组2 a( |9 K% ^' x8 a& w% S& r8 j9 [
Normal ranges, 正常范围* F0 \1 Z0 x" ]5 _" \0 z% G
Normal value, 正常值
) V3 p2 `- a/ K; ?( nNuisance parameter, 多余参数/讨厌参数
% e. t6 W+ R3 n7 {8 Z) }Null hypothesis, 无效假设 4 J; m. @$ R9 o, o6 k1 @' d
Numerical variable, 数值变量
) `$ ]2 \9 ~- b' g4 |. u: oObjective function, 目标函数
. S, K% s3 h, t6 I' n+ [5 MObservation unit, 观察单位
b9 @* d* d3 D$ V% cObserved value, 观察值
; x6 k; f: ~8 X; H8 r* [( u0 UOne sided test, 单侧检验) a: ?1 b5 O H. R
One-way analysis of variance, 单因素方差分析
; F, ?3 \9 \0 S4 E: d/ XOneway ANOVA , 单因素方差分析
1 U$ ?3 X/ Y: Z' V' pOpen sequential trial, 开放型序贯设计- S' _0 v1 `/ O7 t1 q/ s1 C' W5 a: k
Optrim, 优切尾
7 h" q" n0 n: k; ZOptrim efficiency, 优切尾效率* l# R/ k, J$ I b2 |
Order statistics, 顺序统计量5 | V9 t6 F! E+ q8 i+ c3 I; Y
Ordered categories, 有序分类: [4 a7 |5 t% b1 s4 i7 ]- {
Ordinal logistic regression , 序数逻辑斯蒂回归' G$ P! K) S4 k
Ordinal variable, 有序变量
& f0 z+ S( t% F- l& r6 bOrthogonal basis, 正交基9 `1 W# J2 |) V; p
Orthogonal design, 正交试验设计
, e# u2 N! B0 Q1 R4 o5 t [Orthogonality conditions, 正交条件) |2 c; @: P# Z
ORTHOPLAN, 正交设计 ; x/ Z( t7 p8 w, \6 P+ d- k8 D
Outlier cutoffs, 离群值截断点
+ [: ^# {1 b0 i# m) D6 qOutliers, 极端值1 n" a3 a" x6 D7 n/ ?* U6 j8 y
OVERALS , 多组变量的非线性正规相关
0 a" j! S8 O5 YOvershoot, 迭代过度* _8 l8 p9 u* z9 `; W0 a9 k
Paired design, 配对设计
* M a6 d0 [. d) jPaired sample, 配对样本' l( p3 p% H+ i$ q1 {
Pairwise slopes, 成对斜率# C W0 A, m7 }' q o
Parabola, 抛物线6 n2 I; o/ x( S; z" Y
Parallel tests, 平行试验
$ ?4 v% ~) X6 LParameter, 参数
0 I4 |5 r& H b1 p4 n& ZParametric statistics, 参数统计
. \& R- \8 z9 h; M. \! JParametric test, 参数检验
" ~0 J0 }% N7 G) a4 HPartial correlation, 偏相关 C2 R' x; i# K4 K8 K, `8 L( h
Partial regression, 偏回归' Y+ F. c+ X: K: e* p
Partial sorting, 偏排序
% n( B9 z- f! q- Z3 \, _; ZPartials residuals, 偏残差
% r* Z3 g5 ?# j8 x+ o" \& O8 bPattern, 模式7 G' Z1 Q: I( x# j8 S
Pearson curves, 皮尔逊曲线$ @4 x+ z1 Q6 U. ^- {
Peeling, 退层
+ B3 M( F; R3 m/ g1 \' MPercent bar graph, 百分条形图2 I7 v( A1 s4 b; {: v
Percentage, 百分比, o1 b9 A8 E! T: w
Percentile, 百分位数
# _3 [8 V, V; o! pPercentile curves, 百分位曲线
, W; w; z0 r* |. `Periodicity, 周期性, F* N- v% l3 I) I( f+ b# g3 h
Permutation, 排列" R! ~* t! K3 Q, [% L
P-estimator, P估计量 |5 _: q% g! ]8 V: G! H8 w8 S
Pie graph, 饼图
6 K2 H$ s2 P6 k5 T5 {, I" R3 U) LPitman estimator, 皮特曼估计量
( l6 n; T4 J. j- A9 g* LPivot, 枢轴量
; h. I8 b2 K, m& K2 zPlanar, 平坦) I7 F# Z5 q2 Y& x
Planar assumption, 平面的假设
1 ]( G* B5 v4 LPLANCARDS, 生成试验的计划卡1 V! g- x9 R6 t+ U
Point estimation, 点估计 ]) W. _1 J& D8 H7 w" `
Poisson distribution, 泊松分布
; p; s' t' e8 E+ U/ \* ]Polishing, 平滑 c9 R9 w5 v$ m2 T
Polled standard deviation, 合并标准差
3 M+ J8 M: c1 q; b3 E8 dPolled variance, 合并方差; U5 Y) N0 H' Q0 o
Polygon, 多边图" z7 l9 B- q% s
Polynomial, 多项式: D* Y% a6 k4 t5 _
Polynomial curve, 多项式曲线
& R9 C) e; ?0 a$ R& uPopulation, 总体( _, w+ Y5 `) ]: a' J# z
Population attributable risk, 人群归因危险度! [6 a# a( @$ v) F f" r' P
Positive correlation, 正相关
5 I. y0 }% O0 f; | m7 |. J- ?Positively skewed, 正偏
2 p, S3 e" c j; e# G$ kPosterior distribution, 后验分布9 W1 W& Q; r2 v) t5 D1 d
Power of a test, 检验效能
+ `) a. _" s5 zPrecision, 精密度! |( A# r" g0 D; s0 x0 v3 q# n
Predicted value, 预测值+ o( j% y' a# Y* _! Z
Preliminary analysis, 预备性分析
; D8 R: Z4 L1 o3 \' SPrincipal component analysis, 主成分分析
- C3 Y" P% I2 y3 |6 aPrior distribution, 先验分布3 E; v4 S, R5 {# [2 c
Prior probability, 先验概率/ V i% y( U( h% L j* W
Probabilistic model, 概率模型) ^1 Y& m3 J: V- b# [6 S
probability, 概率
8 z: E- r) T0 l; \, s& z! RProbability density, 概率密度% h) O2 N2 D0 j9 d8 W) I" [
Product moment, 乘积矩/协方差& g' l# ~% k5 [( e) `# L
Profile trace, 截面迹图
% a, y4 Y' i t9 v0 Y8 MProportion, 比/构成比
. u& j% D0 ?( xProportion allocation in stratified random sampling, 按比例分层随机抽样
2 k6 C+ ]3 B& ` {2 ^$ hProportionate, 成比例
' [, n& T; N0 @' _- N AProportionate sub-class numbers, 成比例次级组含量
5 T0 g- N! c) z% H% L0 K S( EProspective study, 前瞻性调查
6 ?* J4 M- i5 l8 P( u$ OProximities, 亲近性 9 Q" U( n c3 h* I, Y
Pseudo F test, 近似F检验
4 o0 R- R$ H% RPseudo model, 近似模型, p' A, @% [% Q5 {
Pseudosigma, 伪标准差
9 S( n7 d- b/ HPurposive sampling, 有目的抽样$ t% v7 M& a7 {: H) o4 V
QR decomposition, QR分解6 b3 g( ]4 `+ s+ P- r) r
Quadratic approximation, 二次近似; i, n6 u( B% U" ^7 Q% P' I5 _8 ]
Qualitative classification, 属性分类' w/ E& _% v1 ]' P
Qualitative method, 定性方法9 T2 k$ n& ^; H# v, }
Quantile-quantile plot, 分位数-分位数图/Q-Q图
$ k/ E0 ^3 L7 h! f, AQuantitative analysis, 定量分析; p. T4 _& |# P" V
Quartile, 四分位数
9 a2 {3 i$ m j5 |Quick Cluster, 快速聚类
4 x- w4 Z0 z( V* r% g! k* a8 mRadix sort, 基数排序
' J% X. y2 [6 d2 _( S* ?4 x# `Random allocation, 随机化分组! Y9 O/ B% }8 c
Random blocks design, 随机区组设计
0 z6 t/ W5 k& i2 D% p7 sRandom event, 随机事件
9 ]% G! ]0 p3 C' Q% A, QRandomization, 随机化4 i. Q* _( K5 Q( S+ G
Range, 极差/全距
3 m% {. ?, a# b1 hRank correlation, 等级相关
8 {9 w; g; |+ yRank sum test, 秩和检验" Y. R! T7 X: A
Rank test, 秩检验* q4 O1 a, |% f6 q) X
Ranked data, 等级资料
' [: A) i- [ ~: p( lRate, 比率& r4 q3 n7 ~# d; T/ B
Ratio, 比例( ^/ \( p; v, |) p: B- k! V
Raw data, 原始资料8 O* b+ \, k3 a/ ~! L
Raw residual, 原始残差- H9 |! @9 z) h6 Q0 R
Rayleigh's test, 雷氏检验& T$ y5 ]% r4 N! ~% S) }
Rayleigh's Z, 雷氏Z值 $ }4 R: ]& k" h0 E
Reciprocal, 倒数
& w, I1 \& W6 D8 @- I1 ^Reciprocal transformation, 倒数变换2 j. a7 M' g P8 L0 n# ?
Recording, 记录
! m: B0 y, L( G' b' K* URedescending estimators, 回降估计量
& U0 S$ I% z9 U+ EReducing dimensions, 降维 ]" B r7 e+ \ A6 ]
Re-expression, 重新表达
, ~% h! v, P U- z8 z7 a* ]9 L+ _1 |Reference set, 标准组
, o2 n6 h9 T, |! p v# KRegion of acceptance, 接受域4 A/ ^: F: `, W. E% w5 ]$ W5 S/ s
Regression coefficient, 回归系数0 m6 Q# o' K9 g5 m. x# V1 s! \
Regression sum of square, 回归平方和4 \, h: v) S6 e: D- n/ t
Rejection point, 拒绝点0 p8 q6 S( ^2 r5 u
Relative dispersion, 相对离散度/ i4 x( ^1 K! D3 W9 b; k+ L7 }
Relative number, 相对数
- q" L0 @7 m1 [$ c" X- w- h$ }; I, ?Reliability, 可靠性
# i0 l$ H$ h: j! J% F( h% F! \Reparametrization, 重新设置参数
' k& E a3 C8 V3 uReplication, 重复. \" B0 N/ f$ ?# y7 s5 E# F" ?
Report Summaries, 报告摘要
' h/ J+ A. u& G' P5 J5 X) iResidual sum of square, 剩余平方和4 q1 l1 X9 Y& B1 v# j2 f% `2 [) q
Resistance, 耐抗性& a/ ]: d% _# U" P0 h) e3 s
Resistant line, 耐抗线
* p/ e" H3 @/ JResistant technique, 耐抗技术
6 U5 [1 _1 j3 ]" e2 jR-estimator of location, 位置R估计量
& n8 |: Z9 i& S$ w- y r* zR-estimator of scale, 尺度R估计量 ]" Z3 P" z e
Retrospective study, 回顾性调查
; C1 j% O3 F o9 @Ridge trace, 岭迹8 y" M. ]+ W9 @/ a @
Ridit analysis, Ridit分析7 L2 h) Q. A4 F/ I" F+ O7 { o0 a
Rotation, 旋转# y" N! O7 g* D
Rounding, 舍入3 Y* K' X8 [8 \$ t' c) g
Row, 行
1 q; u/ Q5 K& {. n- CRow effects, 行效应( i/ O: b [* P& B( v
Row factor, 行因素6 Y6 Y- M1 @" X. y! S3 K, {
RXC table, RXC表6 W G0 A4 M+ n) t T, E
Sample, 样本2 ^3 C @; R( B% {
Sample regression coefficient, 样本回归系数
" X$ v, A. K+ `Sample size, 样本量7 S0 r6 ?! ]6 C. q5 {% |2 V$ d
Sample standard deviation, 样本标准差0 Q9 q$ y+ }5 v9 d# m
Sampling error, 抽样误差, p: ^' m' A" p7 k# [# D& }6 T8 N& a
SAS(Statistical analysis system ), SAS统计软件包' w6 y( H& G$ n D4 g
Scale, 尺度/量表4 w/ @8 I$ q* g+ |8 {: L
Scatter diagram, 散点图/ |' b' R' y. h4 r5 i5 f# S( Z
Schematic plot, 示意图/简图
5 I8 n: W; z9 \' N9 H% m9 l5 f. OScore test, 计分检验) T* N W+ e y0 C0 a- C
Screening, 筛检
8 o' H; h% e' ?& aSEASON, 季节分析 , W7 e, G6 e) ]3 i& r Y
Second derivative, 二阶导数3 Y; ]8 N- ^4 e+ n2 q1 d$ R1 |
Second principal component, 第二主成分+ e7 T+ ~7 K4 T' V$ W. U0 P2 {. a
SEM (Structural equation modeling), 结构化方程模型
& d# O0 F6 o! K( i/ JSemi-logarithmic graph, 半对数图
1 W9 v+ D7 v- O' ASemi-logarithmic paper, 半对数格纸8 g- T2 _! \8 v% F
Sensitivity curve, 敏感度曲线; |8 Z& t Q( d5 @- c: W' U* h, O7 N
Sequential analysis, 贯序分析, |2 Y2 {; D8 V- u% j
Sequential data set, 顺序数据集4 d4 F" F$ ?5 Y
Sequential design, 贯序设计6 N# F8 d% I9 T4 @
Sequential method, 贯序法! J3 g% w3 G6 g
Sequential test, 贯序检验法) `/ @ D5 s/ g" K' A, Z
Serial tests, 系列试验
/ o. y: U7 P8 ]Short-cut method, 简捷法
5 i% r" E( _) @4 C) j+ CSigmoid curve, S形曲线) }; e' j) o8 Q8 j$ E3 K) p
Sign function, 正负号函数
' ~, Y: ~/ g. L# z& F1 _Sign test, 符号检验
, }. K- X% p7 aSigned rank, 符号秩* s7 s' Z p0 r; }2 {
Significance test, 显著性检验1 C' L+ V7 R S
Significant figure, 有效数字/ m& A: `. A7 o( T# T* I$ l6 `
Simple cluster sampling, 简单整群抽样% h' @2 b% M( W7 A4 Z9 w, _
Simple correlation, 简单相关' m2 {' k# O$ o7 K3 C
Simple random sampling, 简单随机抽样
9 D. _4 T# [ D# X7 s0 A( _ nSimple regression, 简单回归
6 U. Q/ |' R7 t; E. @. o- n* {8 Tsimple table, 简单表
" n# j/ g* T5 PSine estimator, 正弦估计量$ R9 V( C! u9 s' m) J$ P4 n
Single-valued estimate, 单值估计
& _* w1 P3 _5 f; t8 K: y, FSingular matrix, 奇异矩阵
; `0 Z. K& H' V7 ASkewed distribution, 偏斜分布) |& b1 A% V: K
Skewness, 偏度
7 s6 S+ Z2 |1 S! m- t6 M$ KSlash distribution, 斜线分布/ U! w" K; A5 J3 i, M
Slope, 斜率- K7 E- L2 ]4 z1 f4 E7 y
Smirnov test, 斯米尔诺夫检验" b6 N4 O7 c: C' \/ }
Source of variation, 变异来源; P1 V% @ u k7 I" h
Spearman rank correlation, 斯皮尔曼等级相关
+ V, ~* L" i' q T9 _, F1 i/ JSpecific factor, 特殊因子8 G n" o# M z. E- d( H
Specific factor variance, 特殊因子方差+ I1 m6 }2 |$ Y+ U3 S
Spectra , 频谱
( f; _2 Y6 y, ASpherical distribution, 球型正态分布: x% } B0 r* J7 W! |# c* ^
Spread, 展布
5 w! G8 ~9 T2 O2 T9 KSPSS(Statistical package for the social science), SPSS统计软件包
1 @: Z0 f- a: w; k+ E& o) GSpurious correlation, 假性相关
/ v( ~% _9 k7 A: @ W7 g) BSquare root transformation, 平方根变换4 e! \8 \' e8 {4 s+ D
Stabilizing variance, 稳定方差5 J/ ^8 m1 z2 @
Standard deviation, 标准差- x; X) T) ~" D3 }& ^
Standard error, 标准误0 X! G, K% S7 @) F# m, p
Standard error of difference, 差别的标准误
3 e1 I: z: R7 u; n8 y9 X( n& WStandard error of estimate, 标准估计误差1 j1 o- {3 Y1 W7 m1 b
Standard error of rate, 率的标准误/ }/ j1 D) ]$ D' [# K3 O8 E
Standard normal distribution, 标准正态分布) O( b. ^8 t* [+ h' `5 n t0 V
Standardization, 标准化4 r, p8 V# q1 S, i. Y7 \
Starting value, 起始值6 \0 T9 C1 M- M" J) `
Statistic, 统计量5 s* f1 _ k% d; h/ L- F" S
Statistical control, 统计控制6 c+ Q; } _. R1 ?6 g
Statistical graph, 统计图. ^; v4 K0 `9 i- w& C- c. m
Statistical inference, 统计推断
7 }- j$ ^( \; qStatistical table, 统计表! w- D( s# y/ ?2 t' H
Steepest descent, 最速下降法
3 H3 P D, w; C2 H4 S6 WStem and leaf display, 茎叶图
# L: ]) k! e/ u5 [7 y- n2 Z* SStep factor, 步长因子, d. H6 i" \: I& v1 B
Stepwise regression, 逐步回归
4 A8 H* u4 h) s0 H2 c7 n3 f& H1 |Storage, 存: ]) R) l2 }: ]6 g7 @/ P" O) {+ Z
Strata, 层（复数）
q) {7 Z+ c3 n: J, @Stratified sampling, 分层抽样! x" R# W+ X" z" z6 y8 s/ \" x" r
Stratified sampling, 分层抽样
2 K8 I5 Y" r7 l) IStrength, 强度- |. e5 n4 B6 x) z( L0 U; N! \
Stringency, 严密性
. \% l$ \ b- dStructural relationship, 结构关系
# T0 l: g: ?7 I, xStudentized residual, 学生化残差/t化残差
& w9 ~" Y8 F9 E* B: c2 G$ xSub-class numbers, 次级组含量$ j9 D: D' l2 A
Subdividing, 分割9 t1 z) l. V. p% v8 u$ v
Sufficient statistic, 充分统计量
& q2 r, k6 J3 }+ ^0 YSum of products, 积和7 j9 D( z h6 ^/ m k
Sum of squares, 离差平方和
( x/ `* {- L# P0 N8 H, oSum of squares about regression, 回归平方和
; C3 o8 A H. }. SSum of squares between groups, 组间平方和5 w6 F0 k% R8 O7 |
Sum of squares of partial regression, 偏回归平方和
h: X! z5 p% \% S( hSure event, 必然事件
& h: ]: O$ J4 q; d6 U: KSurvey, 调查6 P( V$ v0 V* K0 J: U
Survival, 生存分析
& ]- c8 B: V3 U) c, n% USurvival rate, 生存率. p& t( e8 Q7 X' |+ C
Suspended root gram, 悬吊根图
6 s6 N& a/ q! rSymmetry, 对称
) s5 P4 C8 i1 H7 e" c. \! ?1 ?Systematic error, 系统误差 b; x+ j0 M1 |3 M# B) a w/ C
Systematic sampling, 系统抽样7 O% i, L, V* d+ L" z
Tags, 标签
: D' s( G8 ~2 q' V* \: V4 {Tail area, 尾部面积
, u0 v' @0 D$ x! V3 h9 B) |Tail length, 尾长
! B7 V* i, m( {1 U, l4 ^Tail weight, 尾重
3 R& Q, c# f. s- zTangent line, 切线
- Z" ?* {( U7 n9 Q' l( G: rTarget distribution, 目标分布 c. D1 m w2 X) {" M
Taylor series, 泰勒级数
`1 A) g: ?1 I& L3 [! q: t3 QTendency of dispersion, 离散趋势6 `6 \1 _/ G2 }5 v2 J0 S: J
Testing of hypotheses, 假设检验
0 S: \0 A1 w8 d6 f* e9 _4 v CTheoretical frequency, 理论频数
+ o- q8 v" u ^+ v3 W RTime series, 时间序列
) q* R+ i: L! @Tolerance interval, 容忍区间
& F1 w% e Y/ E+ {9 s; WTolerance lower limit, 容忍下限4 }$ m* A# c2 _! W' c8 D0 q, O
Tolerance upper limit, 容忍上限' s( u- Q# U" i8 m
Torsion, 扰率
$ f) _- X# ]0 |Total sum of square, 总平方和5 j0 y) a. Y$ F" S
Total variation, 总变异+ F( }2 B# J) }
Transformation, 转换+ u$ m3 h5 ]* o3 y6 S! c
Treatment, 处理
. I! w% H+ t \Trend, 趋势
+ G- u4 l! N* A$ w' w1 }$ KTrend of percentage, 百分比趋势
" v* y% J6 f1 g3 W8 gTrial, 试验
( R/ [/ r2 G! i7 z+ E {. hTrial and error method, 试错法
, T r0 D) v; C% B: w6 f' {0 aTuning constant, 细调常数
/ C' D' J5 u/ V j8 T# |" zTwo sided test, 双向检验2 \; h0 ?" m2 _6 J4 b/ Y
Two-stage least squares, 二阶最小平方
0 W* l8 ~! v3 q- _/ M5 p2 ETwo-stage sampling, 二阶段抽样; c+ o" G+ w5 W u
Two-tailed test, 双侧检验
$ w* h+ C3 x& n( i4 X# \Two-way analysis of variance, 双因素方差分析 g3 Z2 A N$ n, L+ I2 M5 Q# S" m, q
Two-way table, 双向表
$ H& T4 J+ c4 e# eType I error, 一类错误/α错误- F9 _% _% u4 K i& t, m
Type II error, 二类错误/β错误4 `; } ~, [# @. \
UMVU, 方差一致最小无偏估计简称1 ^' o" r0 }3 O& D9 S' ^: ~# R
Unbiased estimate, 无偏估计
; r5 K7 }/ ?5 P" ~Unconstrained nonlinear regression , 无约束非线性回归+ Z, M4 R& c& } o# @
Unequal subclass number, 不等次级组含量) A/ g$ U: E, p' V$ O$ ]
Ungrouped data, 不分组资料
2 _+ M& o& D4 S ?" J# EUniform coordinate, 均匀坐标# q/ n& @6 X: Q4 z. [
Uniform distribution, 均匀分布% O7 g' W# i8 ?0 V* ^
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计0 b' b8 M2 f% y9 ]2 m& M
Unit, 单元
, g& i% A+ q2 j6 u, HUnordered categories, 无序分类( j8 @0 A( V$ ]3 K5 k- W) o0 f) W( A
Upper limit, 上限$ S' t. L* H7 N% n0 o5 U
Upward rank, 升秩8 |& s' E+ R' n5 {5 b
Vague concept, 模糊概念
& C2 U9 j: s0 ?, ~( O4 z) l. }Validity, 有效性4 h) G; p6 z( V
VARCOMP (Variance component estimation), 方差元素估计
0 e* j& I, F0 {+ Q% _2 d c rVariability, 变异性
3 z& \0 w8 w4 \( Z) RVariable, 变量+ L0 Y, B! I7 u
Variance, 方差+ M! K4 S v% Q* n1 p) X
Variation, 变异
6 b2 {; g$ Q) S# ]' N! bVarimax orthogonal rotation, 方差最大正交旋转5 ]) O4 d/ ^$ }* c! L1 }
Volume of distribution, 容积9 i4 c; m' u" q/ k
W test, W检验
, u" T3 g" J l* Z, F0 VWeibull distribution, 威布尔分布! ?, N* U0 I# F: [+ I! p
Weight, 权数* l/ n# P- [+ W- Z9 z7 _
Weighted Chi-square test, 加权卡方检验/Cochran检验 I" U. G' H8 f7 ~% ^6 C
Weighted linear regression method, 加权直线回归) L6 a- P8 }6 v
Weighted mean, 加权平均数
8 A; I: q! D3 c* r$ tWeighted mean square, 加权平均方差7 u7 C7 z- Z: f; ~: ` J
Weighted sum of square, 加权平方和( T; N! \4 J2 _( E$ @
Weighting coefficient, 权重系数
3 Z% w1 u; F/ k {' fWeighting method, 加权法 3 O( S2 U; |6 c
W-estimation, W估计量& k% n; i3 L4 x- l2 V- K5 c% ^
W-estimation of location, 位置W估计量9 J; }5 z. I1 `
Width, 宽度9 M4 w/ ^% b7 s
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验+ a; |( \$ `' W
Wild point, 野点/狂点& [$ C9 z8 M0 S$ [
Wild value, 野值/狂值4 p: m8 z' C/ P' u, t
Winsorized mean, 缩尾均值% j& u% h+ n9 _; e4 {
Withdraw, 失访 ' Z( E3 v' Z8 f5 E. ^- x
Youden's index, 尤登指数! H0 n; b" E6 U4 e R f
Z test, Z检验
% V G6 s- e. r7 ?0 j" P UZero correlation, 零相关
* T& D0 |: c5 f; J. GZ-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
