|
|
Absolute deviation, 绝对离差
6 x- Q% v& q" V* n1 zAbsolute number, 绝对数
2 T$ W; j u3 M4 {' D' N0 g9 E- EAbsolute residuals, 绝对残差
( J3 \) v: R! s# p$ h( B: KAcceleration array, 加速度立体阵
- U/ q$ c) D P4 Y& l0 O# F! `Acceleration in an arbitrary direction, 任意方向上的加速度
0 p9 O* g! _! P9 FAcceleration normal, 法向加速度. V' P5 Q( g1 t1 ^8 B" K5 H
Acceleration space dimension, 加速度空间的维数
, X0 `7 N& e d+ W8 P4 n0 _Acceleration tangential, 切向加速度- D0 P3 v" i7 @$ O- \# l) x6 n
Acceleration vector, 加速度向量( H. I. q. p1 l. X8 }9 [
Acceptable hypothesis, 可接受假设! e* w' v* B \7 ^# ~9 `; r5 @: k
Accumulation, 累积
6 p, X2 G- [ C9 R% B4 E1 zAccuracy, 准确度1 n3 ]1 b# B9 t! P7 i, K# N9 p1 f
Actual frequency, 实际频数
$ ?5 @3 R2 L9 f# N" XAdaptive estimator, 自适应估计量. u6 t$ T% }' E% _6 u& B% O4 J& e
Addition, 相加; C- p% e7 r9 p: t; }/ A9 {( r
Addition theorem, 加法定理! w: o7 Y7 E8 H3 `" z5 b
Additivity, 可加性3 S- X: C! \( V9 p6 q5 C
Adjusted rate, 调整率
5 L9 F* {6 ~. _5 d6 [# F9 h% fAdjusted value, 校正值
6 H- [8 L z. i9 g7 C2 r" z) |+ HAdmissible error, 容许误差7 d! n1 f0 G# d# o( m' }/ N
Aggregation, 聚集性$ p+ z! o! b: G! R4 ?; ?
Alternative hypothesis, 备择假设7 I2 e2 n0 M# d6 g
Among groups, 组间
1 _8 v5 ^ b9 S7 [5 lAmounts, 总量6 W: S4 k5 n' W0 T5 e
Analysis of correlation, 相关分析
8 D; ~1 \2 b# ?' K1 C! eAnalysis of covariance, 协方差分析9 I) ]' ~2 G) R' J# M) q$ f- s
Analysis of regression, 回归分析& k" X1 b4 K1 M( a9 G/ k# z( w
Analysis of time series, 时间序列分析+ W/ C. X- d0 F! N) }
Analysis of variance, 方差分析
; a) Q- h- u5 b* v8 O# v3 V6 uAngular transformation, 角转换1 t4 |. D: A/ |* L
ANOVA （analysis of variance）, 方差分析
2 [ r. N' ~( W, v) O$ S- qANOVA Models, 方差分析模型
" ~* X1 ^: v4 W. x$ E5 u: HArcing, 弧/弧旋
6 {( n3 k5 E: ?. o& AArcsine transformation, 反正弦变换
* T; O0 J# O, a. R( `Area under the curve, 曲线面积1 r# q- x4 O6 o: _0 H
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 - E" s/ n1 S( h4 x1 i# }# Y7 @
ARIMA, 季节和非季节性单变量模型的极大似然估计 ) s# \6 J& j& ^8 U% j
Arithmetic grid paper, 算术格纸
h# E r! e5 ^. H E, eArithmetic mean, 算术平均数; [$ f# r1 @; {; b( V: {' j
Arrhenius relation, 艾恩尼斯关系
# M% f. B+ L; Q/ z. H$ f4 nAssessing fit, 拟合的评估. E8 ]" c" H4 g. R3 Q8 S0 d9 B
Associative laws, 结合律! u/ w# C% f; L
Asymmetric distribution, 非对称分布
% R8 d' o$ B( e# V2 H% Q9 P" M- U- mAsymptotic bias, 渐近偏倚
' w1 J4 E- G( K0 Z0 `; hAsymptotic efficiency, 渐近效率/ C4 `& H% a6 ?! Z
Asymptotic variance, 渐近方差: o+ R: c9 ]# \/ g+ N( P
Attributable risk, 归因危险度
5 c0 p5 ~1 i- Z, x' IAttribute data, 属性资料. J( m. G; k2 Q9 L
Attribution, 属性
Q' m) }: g$ j; k: rAutocorrelation, 自相关
$ w; Z/ { b! K- {Autocorrelation of residuals, 残差的自相关$ b# b2 [" y+ I. z
Average, 平均数, A9 ]( n& t+ j: Q; @. ^* G
Average confidence interval length, 平均置信区间长度; ?3 b# w$ t" x3 _
Average growth rate, 平均增长率
4 C6 \% d& n1 p% F, G( TBar chart, 条形图0 ~' e2 Y M h+ C
Bar graph, 条形图# D1 i9 y. ^+ Y
Base period, 基期, L3 X4 [& e- I" Q
Bayes' theorem , Bayes定理
& P& M! e. t" @" E! G8 E- p/ zBell-shaped curve, 钟形曲线! n( R4 R& t+ f8 X3 f) M
Bernoulli distribution, 伯努力分布3 p/ T. i2 m8 {! X, e
Best-trim estimator, 最好切尾估计量
4 F3 ^( T2 B7 s; z' p$ rBias, 偏性
3 b- T f# I) p& }Binary logistic regression, 二元逻辑斯蒂回归
% N3 O) Z5 H F0 f! u& e& L9 VBinomial distribution, 二项分布. u/ M' _3 P( C0 Y- [ E" Y# N+ S( A
Bisquare, 双平方
% I* y: L% }9 ?Bivariate Correlate, 二变量相关; I: N" y5 M. n2 h/ w) F! `
Bivariate normal distribution, 双变量正态分布* u3 \6 d2 r, B/ @+ B% C- P
Bivariate normal population, 双变量正态总体
4 N8 r$ O- N0 oBiweight interval, 双权区间
# y, }# H8 d' {6 j) _Biweight M-estimator, 双权M估计量
9 f( w4 R% x7 c" SBlock, 区组/配伍组" g2 P7 e: Z g2 ]& a" P1 Q; V# f f/ ^
BMDP(Biomedical computer programs), BMDP统计软件包4 o) N0 e* G+ k! {) A9 K
Boxplots, 箱线图/箱尾图
[$ B/ _ a- T9 s ^, H' LBreakdown bound, 崩溃界/崩溃点& K$ g* N% A4 t
Canonical correlation, 典型相关
( w9 Z5 Y) q8 A6 M8 h9 MCaption, 纵标目5 l/ V* M, {2 ]% Q H; O& V/ N# s
Case-control study, 病例对照研究
5 ^9 w( f4 f% ?( V; H) ECategorical variable, 分类变量
( u) \( B4 C4 h! r7 zCatenary, 悬链线
5 k, D4 u% j& v# O/ s7 l; B- eCauchy distribution, 柯西分布6 U. n' J W4 ]. y# d4 u
Cause-and-effect relationship, 因果关系$ M# \6 G' A& B, v4 }% h
Cell, 单元) k+ j/ H/ D' r+ x) \9 F
Censoring, 终检8 K5 X3 b* l% k8 [7 a' [4 p
Center of symmetry, 对称中心
! V2 n; p* q! \7 f5 VCentering and scaling, 中心化和定标
! U" r' H& {! X# o, V4 BCentral tendency, 集中趋势
; D' B, L8 Z* i3 o+ C8 jCentral value, 中心值* k5 A$ }# m1 f2 z, X
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
: D0 `. s- R4 `6 t; s# j" @Chance, 机遇
5 c4 M9 X8 M K3 l/ s( qChance error, 随机误差1 `, q& I9 n/ R7 h+ l, R+ ?% D
Chance variable, 随机变量
8 ]6 @, T- E2 g* zCharacteristic equation, 特征方程
: S6 U8 _9 l8 G& g. {* iCharacteristic root, 特征根
" ~! O5 Q" R/ ^/ GCharacteristic vector, 特征向量
$ ?$ B+ \, ]: |9 e$ X3 U4 l- M- qChebshev criterion of fit, 拟合的切比雪夫准则. S) X' A3 B) B, D( h- a+ U
Chernoff faces, 切尔诺夫脸谱图; @4 P5 j$ @- f* m2 {0 L
Chi-square test, 卡方检验/χ2检验
; S4 T* `: q2 `/ u: B9 aCholeskey decomposition, 乔洛斯基分解+ z0 o" ?+ {5 D
Circle chart, 圆图
6 v# {# N( x" G6 n9 p% |6 O2 vClass interval, 组距" t7 m4 Q- r F, e/ n9 N% @
Class mid-value, 组中值
; L. x$ S- }9 p$ A4 OClass upper limit, 组上限
0 G7 @: s5 C2 \Classified variable, 分类变量
4 }: V4 F7 T `& _ G7 ?7 DCluster analysis, 聚类分析; Z; [3 Q& t p, H6 F" R k
Cluster sampling, 整群抽样5 a9 ]8 j" n# Q. o& o5 {$ K
Code, 代码* L+ {3 N% x% {! g+ a9 Q
Coded data, 编码数据
$ R% W- u* i$ \5 h7 [% E: t; MCoding, 编码
4 T3 r1 I/ ^ _3 q3 @Coefficient of contingency, 列联系数. h5 l0 s* G$ v! I$ o
Coefficient of determination, 决定系数7 T4 A. g1 j8 J6 h
Coefficient of multiple correlation, 多重相关系数
7 C& h/ Z6 H5 C: CCoefficient of partial correlation, 偏相关系数
7 g- m( Y* a) x% R. c; z0 u) V) ZCoefficient of production-moment correlation, 积差相关系数
' x* o- c+ S3 [+ \Coefficient of rank correlation, 等级相关系数' `0 [6 O' m& G8 Q: B- z
Coefficient of regression, 回归系数
6 n5 D6 p7 G* J- m, YCoefficient of skewness, 偏度系数7 X' T2 a! @- [; T" A) j
Coefficient of variation, 变异系数8 o* k+ v. `6 f" L
Cohort study, 队列研究
3 b% E% H, I: O2 P7 lColumn, 列
+ [% l* p: W5 i$ r' W+ }/ \6 @Column effect, 列效应8 ?- S8 V5 O% I( O* y' Z
Column factor, 列因素4 T- L+ g; A, y" x) Y' v
Combination pool, 合并+ c/ m* n$ y$ x" U9 J
Combinative table, 组合表
1 H$ U- G" l: f$ c1 h7 C6 V; s- U8 mCommon factor, 共性因子
p* `& F2 V, M) b) ?Common regression coefficient, 公共回归系数- x9 m, b3 {" F! `5 V
Common value, 共同值
# e, E' F8 w8 V2 I# y9 @' O3 G- T8 mCommon variance, 公共方差# I3 _9 c+ b7 s/ ^2 Z3 i0 t" k
Common variation, 公共变异7 O0 I1 I4 Z2 p6 q. M
Communality variance, 共性方差% |8 V2 w5 V; o6 U# d
Comparability, 可比性$ a4 p; N* D! f. N5 I; @
Comparison of bathes, 批比较! ~) ?' R' p% N k: y! U8 N% m/ ?
Comparison value, 比较值3 S1 G. ~- ^' n/ D* b. R
Compartment model, 分部模型* j; w, a$ A1 l) t. V6 x# F, ]& V
Compassion, 伸缩/ Q( j$ D ]/ g7 i+ [- y
Complement of an event, 补事件' T: ]7 e! p! j: S& Y4 h+ r
Complete association, 完全正相关, `8 _+ \+ P" j2 I, O/ A
Complete dissociation, 完全不相关8 G9 u6 n9 k) j5 p J
Complete statistics, 完备统计量. }9 S, D' V) e, s% [
Completely randomized design, 完全随机化设计 \6 ^/ f# ]/ y0 S( X! q# Z" a! Q- s6 _
Composite event, 联合事件
+ y! ^3 f1 L" `( I9 a9 Y% nComposite events, 复合事件
. r1 X) b# g' I+ v* @& t& o LConcavity, 凹性
- ]6 D8 @$ ]. _1 f, @; q0 c* l, @Conditional expectation, 条件期望
5 Q x$ \4 u& `* E2 N5 X- I% AConditional likelihood, 条件似然
+ k ]# Z4 h: V& t# n% aConditional probability, 条件概率
% t3 A5 v& A) PConditionally linear, 依条件线性; t1 l9 b- F8 ~1 M$ {
Confidence interval, 置信区间% }8 {, a$ S" N2 N* b
Confidence limit, 置信限; K* w y) t& `
Confidence lower limit, 置信下限' A2 E' T# U0 l: g, T0 Q5 p3 C
Confidence upper limit, 置信上限
; ~( ?/ p0 F0 p* wConfirmatory Factor Analysis , 验证性因子分析1 @- ]( o$ A8 }+ M' f! {. X6 X5 V% q
Confirmatory research, 证实性实验研究
1 C: n1 t& Y+ G/ I8 p" H' V+ q0 qConfounding factor, 混杂因素
$ u- a( g+ \) C+ Z, Z/ S' W7 wConjoint, 联合分析
; O- v X% i- [9 x& C" UConsistency, 相合性
' G, g" R6 U. e$ C l6 [2 I UConsistency check, 一致性检验& C. r' \$ ^( z! P
Consistent asymptotically normal estimate, 相合渐近正态估计
6 j* B/ V7 u! fConsistent estimate, 相合估计7 c3 y+ i* p f+ @0 a7 R& t* {
Constrained nonlinear regression, 受约束非线性回归- ?+ k% n7 W: C: h
Constraint, 约束+ k, f5 e# K: x/ s) h8 L3 p
Contaminated distribution, 污染分布
. i$ [6 ~. N0 p/ k JContaminated Gausssian, 污染高斯分布" F4 z# l7 V' {
Contaminated normal distribution, 污染正态分布. h, h# X3 I7 x8 W. G J4 j
Contamination, 污染! J3 P& e! w4 I3 y" w! k* n
Contamination model, 污染模型, D7 S- _6 D/ T6 T+ ~' J' ^7 q
Contingency table, 列联表8 m0 _* k" _, s+ J3 s% o' K
Contour, 边界线
2 S# {* {3 }! r: N c$ C6 Z' DContribution rate, 贡献率
) W6 L* d2 |5 GControl, 对照9 |: W& C7 A6 h& ^- L1 l
Controlled experiments, 对照实验! e4 Q9 R$ m2 E; L6 ~, b9 E. [
Conventional depth, 常规深度9 c3 z2 E, G7 Y9 X3 [9 k
Convolution, 卷积
! p3 s' }9 l+ s9 d. yCorrected factor, 校正因子5 c/ z; V4 S8 h
Corrected mean, 校正均值& K3 o- d9 N' m( b3 r+ l- w
Correction coefficient, 校正系数
) O8 ~- Y7 Q' e- BCorrectness, 正确性
$ c- x- R* D3 t0 c3 E" k2 ]/ X- d- u; rCorrelation coefficient, 相关系数$ x' N1 @, O h; u4 E' c/ D
Correlation index, 相关指数! Z! b! _& d1 o. t8 d, ~
Correspondence, 对应
& e7 P9 J# j; F' B# x/ TCounting, 计数
. l' s: z/ r. l' X5 f T" TCounts, 计数/频数) P9 g# V' z0 |* A, ]
Covariance, 协方差
- v2 O2 e+ A0 e: S% ?8 yCovariant, 共变 $ i3 V+ V5 m) N: i1 i
Cox Regression, Cox回归
/ r7 D6 [9 w8 f# M8 eCriteria for fitting, 拟合准则. L+ P1 f& }5 N# ?$ H$ e
Criteria of least squares, 最小二乘准则
! `7 ?7 K: Q; e7 G. {1 \; T- @: mCritical ratio, 临界比
6 M" e' h% Y0 \) qCritical region, 拒绝域
$ o% x7 F1 A0 \6 p; sCritical value, 临界值
2 Z. w! d) d+ l, YCross-over design, 交叉设计& a0 U: s! z2 p
Cross-section analysis, 横断面分析0 d' x! B4 z9 g% X/ M m
Cross-section survey, 横断面调查" V! R2 A) j1 w+ l" r: V
Crosstabs , 交叉表 ! k0 w; T8 P- q) W* |$ |
Cross-tabulation table, 复合表
) u8 i7 ~7 K) \& f9 ?8 bCube root, 立方根
\1 r" C8 x! U- D& e1 F, bCumulative distribution function, 分布函数
1 n$ j; K; |% g) l1 g8 d* q* MCumulative probability, 累计概率
4 f' w( ]# E0 Z: t4 W- B. ~Curvature, 曲率/弯曲
% Q6 ~# ?% ~: F4 }2 [0 rCurvature, 曲率
; V! m$ s( x) N) o6 T! WCurve fit , 曲线拟和
& @# ~& h2 V2 g9 T6 F T G/ d0 SCurve fitting, 曲线拟合; }+ L3 x4 c1 l* K) A# G
Curvilinear regression, 曲线回归; R4 {6 J2 t* Y9 h: m( }
Curvilinear relation, 曲线关系6 O3 e* D9 S6 b+ Z' V
Cut-and-try method, 尝试法0 y: ^8 u8 Q4 U' p0 R* O
Cycle, 周期
- M. \+ V( ~' A$ u2 |! OCyclist, 周期性
6 E: U- W" N; W- wD test, D检验
9 I! K" D: s: C0 |Data acquisition, 资料收集
. `% {* o( x0 x8 VData bank, 数据库
0 X& f5 d7 w! g3 z8 I! s& b4 t) kData capacity, 数据容量 { F7 ?+ Q! @9 T1 ?
Data deficiencies, 数据缺乏
$ H- Z6 q ~. G! s! C' qData handling, 数据处理
. A* l# S. H6 t! i; [" }/ c7 O0 pData manipulation, 数据处理
$ Z c% g5 |& A# ?Data processing, 数据处理
6 @& m3 `9 `; `6 a x9 ^; X( tData reduction, 数据缩减
2 c* R2 l: Q3 ~& \Data set, 数据集
9 O: g' }# q9 N7 ~9 Y2 |Data sources, 数据来源
! U3 |: E9 E% E0 }( i9 WData transformation, 数据变换" g$ a( ^9 t- s: W
Data validity, 数据有效性9 U( l6 [/ G6 v0 E0 Z! K" {, d
Data-in, 数据输入$ ]8 m% X8 ~: p5 b+ U
Data-out, 数据输出3 d5 Y' D( J+ M/ D
Dead time, 停滞期
! ?* I" `# G. H' y+ t$ }- y% CDegree of freedom, 自由度# p( O! N7 \& x* Y/ P
Degree of precision, 精密度% z! A! }+ w- k% N# O
Degree of reliability, 可靠性程度) y8 h7 U. Z- f# M
Degression, 递减, l; N( N& |8 `$ L# F
Density function, 密度函数8 n. I0 k1 N/ O& P7 g
Density of data points, 数据点的密度9 d3 _- U0 S) H+ B0 U0 o
Dependent variable, 应变量/依变量/因变量
# D3 Q- m( _ @) ?* `Dependent variable, 因变量8 b* D7 D2 k w* X3 p! d
Depth, 深度. l8 ~0 a v9 g6 O; L4 l
Derivative matrix, 导数矩阵7 O7 o; _; A: X
Derivative-free methods, 无导数方法! D5 s- W3 a) ]
Design, 设计3 U7 y. z/ r0 v( C, S6 M
Determinacy, 确定性
# O3 y( k& Q$ R ^' t- ?Determinant, 行列式* {# H9 M& E6 [' g( ]" m
Determinant, 决定因素: c" O: R+ Q7 b% ?
Deviation, 离差& {# {+ O- y0 q% u- d
Deviation from average, 离均差7 w' ?' {8 l9 y5 ]* F/ B( b
Diagnostic plot, 诊断图0 q7 k4 M. f0 D! x! X
Dichotomous variable, 二分变量. A `9 @) h4 t# A) Q
Differential equation, 微分方程$ j' V$ Q3 b! E+ @ K5 L
Direct standardization, 直接标准化法
$ u% z9 w7 k+ C+ e$ o9 cDiscrete variable, 离散型变量
) U/ U4 I5 H2 b; Z2 n2 pDISCRIMINANT, 判断
4 @8 G! |$ f z: S1 _+ ^Discriminant analysis, 判别分析3 z$ |( f0 R+ @8 @0 V
Discriminant coefficient, 判别系数
: m& Z9 D! Y6 Q- G$ t# g& K1 HDiscriminant function, 判别值
9 C6 r, M/ d0 S4 ^# [. s' S5 j* gDispersion, 散布/分散度
1 |; f, `: D/ b# \* g3 k% S5 KDisproportional, 不成比例的% Q+ z$ m4 M+ T9 Y. R! O9 f# Z
Disproportionate sub-class numbers, 不成比例次级组含量
% Q: r4 o4 a, J( uDistribution free, 分布无关性/免分布
# }/ O* ^* }7 V# @& ~- x- d/ r5 ~Distribution shape, 分布形状
8 c; x/ L; I3 ^, [Distribution-free method, 任意分布法: ~% i- V5 a" _! Z1 r- c4 ?
Distributive laws, 分配律. m# G4 m% J3 O9 T8 u
Disturbance, 随机扰动项: s) Y) N& [* Y& v$ k
Dose response curve, 剂量反应曲线
: P4 ~( o" D" a8 j* _6 kDouble blind method, 双盲法+ \. _# z0 p5 e
Double blind trial, 双盲试验
0 h4 t6 T( E8 [5 tDouble exponential distribution, 双指数分布- p0 W2 I. {" s' ^5 ^
Double logarithmic, 双对数
; I. P0 P: Y% }4 d4 h7 ADownward rank, 降秩
% |' v' t+ X1 E& l" G* Y" oDual-space plot, 对偶空间图" b& S2 N" }4 r) ^, u
DUD, 无导数方法
' f* r+ x- p2 N5 ^+ q# _: a2 K b7 IDuncan's new multiple range method, 新复极差法/Duncan新法* D* Z9 k) l) f1 p
Effect, 实验效应1 L: r6 W7 [; @6 R4 T" v
Eigenvalue, 特征值
: Z1 _ f+ A5 f; K5 s. y9 X1 JEigenvector, 特征向量9 E) U5 s2 i4 s# V( q) Z
Ellipse, 椭圆' L7 c: _4 e4 o J: l7 q& U6 b9 ]/ x! p
Empirical distribution, 经验分布
5 Q, y. \2 ]! e- vEmpirical probability, 经验概率单位
# H; D7 P1 p' \& V7 j: |, C8 HEnumeration data, 计数资料. ?$ b6 o% F* }* Q$ h% I2 Y' B
Equal sun-class number, 相等次级组含量
' p( F5 H9 B% g N4 ]# u; ]- [Equally likely, 等可能/ Q0 P) u# k% M+ K. [% j/ C
Equivariance, 同变性! X- r3 E( X1 e8 s; A- U
Error, 误差/错误 w2 v4 R" R/ Z. Z `8 }7 c1 z! b
Error of estimate, 估计误差
% Y3 Z. l: Q1 K9 MError type I, 第一类错误
1 e5 v, v0 c( k" `4 T6 q: f/ MError type II, 第二类错误
) A, {$ u: g; |% |4 VEstimand, 被估量
" I: \( Q' ~8 X8 c8 h$ b- _Estimated error mean squares, 估计误差均方
2 p2 g; K/ Q7 G8 ~# g, W. Z/ PEstimated error sum of squares, 估计误差平方和
7 K3 W: j4 E8 I' b, U% FEuclidean distance, 欧式距离( q7 h& r* @6 {5 r0 F0 F
Event, 事件, K8 E7 i/ x2 r
Event, 事件& U7 X# Z" B& j4 r" X
Exceptional data point, 异常数据点) R8 H, m2 g5 X, `8 l) x/ L
Expectation plane, 期望平面+ k. j4 |3 l* q( c0 l8 _
Expectation surface, 期望曲面7 u# J+ |1 [6 e6 `" P
Expected values, 期望值
4 C* j* D& d, h6 e7 v1 @, ~Experiment, 实验4 K- p. d2 X- m9 E- F) g
Experimental sampling, 试验抽样. \. @( t" H% ~; {% o: j, V
Experimental unit, 试验单位
6 J1 m/ o4 }: T& c9 z) GExplanatory variable, 说明变量
7 ^8 N$ K* q2 |* [% V/ qExploratory data analysis, 探索性数据分析
) f* S' F* s6 N/ c3 |Explore Summarize, 探索-摘要
/ [7 `9 s4 H; M* y6 K O7 W( Z' ZExponential curve, 指数曲线
) y4 A& }7 H+ \- j5 f2 B' MExponential growth, 指数式增长
4 o9 Y) m6 [/ ?' B) W8 XEXSMOOTH, 指数平滑方法
- {% O8 P* S {$ IExtended fit, 扩充拟合
! R* W& m$ w( ?1 g) EExtra parameter, 附加参数
x5 h" J5 N! H+ `( l3 m/ TExtrapolation, 外推法/ `3 j3 ]% f7 I5 ?" Z# t& n# A
Extreme observation, 末端观测值5 O* y4 j* F: @% P8 Q
Extremes, 极端值/极值
5 {6 ^. E @2 {7 h( F/ n/ X4 m5 bF distribution, F分布* k. g E* F: m6 F. i
F test, F检验( g8 P p: T" Z. b U! _) e
Factor, 因素/因子
9 O. t$ o6 j! G$ MFactor analysis, 因子分析
6 ?3 ^8 `. t: z$ \" B$ P% rFactor Analysis, 因子分析) g3 m* N! |/ a: k
Factor score, 因子得分
+ t z) ]7 ~5 W v# [Factorial, 阶乘
: F# ?1 F: M! d; S. |Factorial design, 析因试验设计5 e( t6 F* l- J1 ?( [, |
False negative, 假阴性# p1 c+ M3 z1 V* Q) D
False negative error, 假阴性错误
' p b6 x ^5 n: gFamily of distributions, 分布族
% c9 i: f7 }5 q9 f8 e/ u$ h% ^. WFamily of estimators, 估计量族* d8 O6 A) i& M* D
Fanning, 扇面
7 I! j8 i* h% _' s9 [+ Q" vFatality rate, 病死率
3 }1 D; c* b. o. I2 N% e* `+ }Field investigation, 现场调查; {6 Q/ J0 E: p8 _" a
Field survey, 现场调查$ N, P X. J4 B& z" f
Finite population, 有限总体4 V; }6 t1 s" Y+ c" ~3 r) y
Finite-sample, 有限样本
$ ^3 T9 f4 t0 U( V1 h+ N/ E7 bFirst derivative, 一阶导数
. G: I: U# v8 Y3 XFirst principal component, 第一主成分7 P3 j& |7 g2 r6 t( _. m) V& \; R
First quartile, 第一四分位数
/ Y5 g( X5 q1 h. i: t2 _Fisher information, 费雪信息量
3 a' ^8 j' [7 L @& x {6 \Fitted value, 拟合值
8 s+ c Z; h2 O" P. ZFitting a curve, 曲线拟合
6 t% ?; r# o8 R$ l- s) r* r" @Fixed base, 定基
' h* c( r( l1 C; P* W2 iFluctuation, 随机起伏. G/ h+ Q1 G7 a" N/ {
Forecast, 预测
2 F' r' d& W* b& Q7 `+ l$ V, tFour fold table, 四格表1 m- A4 b, t* L1 i6 {
Fourth, 四分点
9 P Y2 R3 d/ U/ X6 hFraction blow, 左侧比率
' B& x0 O" W, U2 |* wFractional error, 相对误差
% c2 z& ?8 h% @) J$ `+ v, z; J- AFrequency, 频率
9 I$ A: \! K! K4 o6 K( ^Frequency polygon, 频数多边图
/ D+ w6 z4 S; XFrontier point, 界限点
' o# u0 x T6 G2 c2 Z0 cFunction relationship, 泛函关系: w: x2 q( C) Y5 i0 j7 [' `
Gamma distribution, 伽玛分布
5 h( N/ Y& G& wGauss increment, 高斯增量
_- L4 x1 a: W& {Gaussian distribution, 高斯分布/正态分布
: V6 u) l. g0 m# p( CGauss-Newton increment, 高斯-牛顿增量
( t5 {. o& @" V4 OGeneral census, 全面普查7 S, u7 y F5 r) H/ w% s l) T
GENLOG (Generalized liner models), 广义线性模型 1 ^7 m; _8 n* R/ G0 L! O$ a
Geometric mean, 几何平均数
0 O( ]% j( F9 K; j, E( [) VGini's mean difference, 基尼均差: E& |% T' K, q7 C. @& G6 ^
GLM (General liner models), 一般线性模型
7 j" p, A$ ^, O6 v& z% v, ]. yGoodness of fit, 拟和优度/配合度1 b0 @' L3 ^7 K
Gradient of determinant, 行列式的梯度. f1 `4 I: m5 H
Graeco-Latin square, 希腊拉丁方
* o# |8 T% V; X, u! c. O# sGrand mean, 总均值
% Q0 s/ x( ~ VGross errors, 重大错误- _) u1 d8 W$ H; D% r
Gross-error sensitivity, 大错敏感度% q0 G7 p3 u; Q+ l' m) R/ j9 z& o
Group averages, 分组平均, t5 \3 B. k; \* V; J2 v2 t" }% V
Grouped data, 分组资料+ i6 k* |8 [% k" b- j, a8 F
Guessed mean, 假定平均数6 f/ k1 C- ~6 G+ i
Half-life, 半衰期2 r q( F$ k d+ N: L' O
Hampel M-estimators, 汉佩尔M估计量
8 w$ G* V2 B# ]3 WHappenstance, 偶然事件) y% o3 d& B2 |0 r! n
Harmonic mean, 调和均数
, d7 I9 j: X/ I2 B7 u/ EHazard function, 风险均数% ^! r) X0 L- m- Z4 B/ E
Hazard rate, 风险率
0 m' b9 ]) T. H1 Z# D1 j; q- W9 lHeading, 标目 9 |( O9 Z7 S7 ?' j$ Y4 h; I
Heavy-tailed distribution, 重尾分布2 Z# {. F2 j% Y, ?, T5 Z: W
Hessian array, 海森立体阵( r& c) ]& E Z6 T8 {0 A
Heterogeneity, 不同质, X" z, o( X" Z+ c! ^
Heterogeneity of variance, 方差不齐
1 i8 E6 T* H0 iHierarchical classification, 组内分组. \+ D+ Y: ^* k
Hierarchical clustering method, 系统聚类法
5 D8 S6 C8 U, VHigh-leverage point, 高杠杆率点
5 A/ z N8 B* d/ `7 H5 z" h* QHILOGLINEAR, 多维列联表的层次对数线性模型
2 u9 u5 ^- r$ r$ V) ZHinge, 折叶点9 L* S/ ^' V, \! t& L* S" o
Histogram, 直方图+ {0 H; m; V/ N6 i! M
Historical cohort study, 历史性队列研究
: G/ M5 V! w- X. fHoles, 空洞
B' E4 k0 K( o2 J; w* J% ~ [HOMALS, 多重响应分析
8 V. A' W, e: H3 Z( @Homogeneity of variance, 方差齐性
7 ^( w- N7 }$ LHomogeneity test, 齐性检验. R8 e' y5 e8 k
Huber M-estimators, 休伯M估计量& N! Q9 R+ h# O/ h: `8 K0 A+ x9 G
Hyperbola, 双曲线
: f3 J; S9 }# }7 iHypothesis testing, 假设检验. Q% r( f# u; d+ G4 |$ t0 d' F
Hypothetical universe, 假设总体
: r5 r& s/ C( m* vImpossible event, 不可能事件
- _4 z7 f8 a" @7 u1 p2 Y% `Independence, 独立性, j! A! w' a$ H; S* W* ^. S
Independent variable, 自变量7 r: d! v5 m. I5 a* |% @
Index, 指标/指数
# \' ^6 I, G7 ~0 ]2 a1 ~Indirect standardization, 间接标准化法$ z7 e2 t( Q% J) S0 q c3 U9 |
Individual, 个体
+ `, A1 r; X' j3 X1 w7 D1 |/ x! }0 v5 X" mInference band, 推断带5 k0 h5 H* m; x4 ^( u" E2 m
Infinite population, 无限总体+ L& R# s) n2 K" F8 Q+ t
Infinitely great, 无穷大
1 @9 A5 }2 G( A# P. {Infinitely small, 无穷小
3 R; {1 b1 L2 n S& o1 _Influence curve, 影响曲线) K5 o7 [/ t& w& A$ o
Information capacity, 信息容量( s8 G$ _- Z) H u7 \2 b5 I1 t1 B
Initial condition, 初始条件0 K+ t$ c0 K! O* G9 c
Initial estimate, 初始估计值8 j% g+ d& L" Z# k( v
Initial level, 最初水平" i0 s. R1 g T, x
Interaction, 交互作用
' L+ s* H' ^( L9 zInteraction terms, 交互作用项% S9 I* ?' Z$ {3 i5 c9 z6 q H
Intercept, 截距: G& D) x. F' Z* w
Interpolation, 内插法
; L* `; j5 T, ^Interquartile range, 四分位距8 r& t7 x/ Q7 S
Interval estimation, 区间估计
3 A* u3 S8 S( ~9 V1 ]0 \Intervals of equal probability, 等概率区间# s; \# k: t* U) K8 Z( K
Intrinsic curvature, 固有曲率- v0 I& R# d9 S# f# k! D$ g
Invariance, 不变性( O* |$ s* U1 g8 \$ m6 ~$ V# t
Inverse matrix, 逆矩阵7 `5 |+ o% J; D2 r
Inverse probability, 逆概率) B9 y8 Z9 \; J% U
Inverse sine transformation, 反正弦变换3 K# S; N) T- M) w! v; }# u- A
Iteration, 迭代 + l7 d3 U2 Z+ ?* E/ g5 h9 x
Jacobian determinant, 雅可比行列式
: n9 B: f+ o, PJoint distribution function, 分布函数
, ^' I" S! g- W/ |/ }/ `% KJoint probability, 联合概率4 \0 g' s: a* X: N% n4 A6 \9 A) l9 M
Joint probability distribution, 联合概率分布- F5 a; b$ _% S5 s `
K means method, 逐步聚类法4 B* J8 T+ [6 n3 E& `# z" M e0 L
Kaplan-Meier, 评估事件的时间长度
( r, F! T7 i; [# Y9 y6 FKaplan-Merier chart, Kaplan-Merier图
* D; E. t/ q' E8 M7 {9 d$ E/ P# [Kendall's rank correlation, Kendall等级相关7 W/ S, ^( {4 ]" W6 [
Kinetic, 动力学, z. A( X) N# k- g! M9 S2 M$ F
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验; [8 D: m! j% F3 K
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验. s0 Q3 y- s+ r8 E& Q
Kurtosis, 峰度5 q5 E6 [) {+ J0 {. n9 G, F
Lack of fit, 失拟
* h# J: v/ ]- B& DLadder of powers, 幂阶梯4 }# J3 `$ {5 n1 b" T. a
Lag, 滞后
6 q4 M* B) @5 a- FLarge sample, 大样本
" }3 b+ b# e1 J2 ?Large sample test, 大样本检验
' C% t/ L2 |# E) nLatin square, 拉丁方
" ]. f6 U+ ]! P3 q8 E) A2 XLatin square design, 拉丁方设计
) W( ~( P) \) E( y3 fLeakage, 泄漏0 g3 e) J0 x/ E
Least favorable configuration, 最不利构形 F' m6 W- B- X$ E2 i2 L
Least favorable distribution, 最不利分布0 z7 g0 T3 A) S4 x
Least significant difference, 最小显著差法
- {" \' d, E: \ c) ?+ i# rLeast square method, 最小二乘法2 J* I8 C4 x9 t6 ~2 N
Least-absolute-residuals estimates, 最小绝对残差估计
1 X) v( \1 e, K1 kLeast-absolute-residuals fit, 最小绝对残差拟合9 `$ D" s' v; |6 ~, ^6 \/ d
Least-absolute-residuals line, 最小绝对残差线: `1 E$ A# _, s/ a3 C
Legend, 图例
3 s/ }+ H& n; aL-estimator, L估计量
, [. R, H F+ HL-estimator of location, 位置L估计量
& [2 ~5 V8 {6 Y: jL-estimator of scale, 尺度L估计量
& k4 O; r7 W8 _/ `% M; YLevel, 水平- S" C `: p! ?) T! v, ~' d3 P. X
Life expectance, 预期期望寿命
1 S, T. d4 u" ~$ b/ vLife table, 寿命表' @, P8 _0 ?+ B3 B- H" D! f; t
Life table method, 生命表法
" _/ g2 z9 b7 \0 j0 K: d. gLight-tailed distribution, 轻尾分布1 W9 C* N- b2 N3 `6 [1 G O" R' T
Likelihood function, 似然函数. g) B4 z: ^4 s; s
Likelihood ratio, 似然比# r/ N) a6 E% u; T$ @9 h
line graph, 线图% Q! s5 R. {7 S/ E; V
Linear correlation, 直线相关# s2 S6 n) w# ?3 y7 k( H1 s; ?
Linear equation, 线性方程+ l% V& }, T6 [" ]8 D
Linear programming, 线性规划1 K* o! |/ s9 w
Linear regression, 直线回归
( K/ ~# M1 t# I- Z" i; ^Linear Regression, 线性回归3 @3 ~% ]: A9 w" z7 q. }
Linear trend, 线性趋势
% s$ @ v9 c5 }3 u6 MLoading, 载荷
1 u9 O7 A' E+ zLocation and scale equivariance, 位置尺度同变性8 o/ N% I! l* N+ x! |6 w2 f
Location equivariance, 位置同变性
: g* q+ \; w1 U( RLocation invariance, 位置不变性+ ?, k1 O8 |2 B+ Y
Location scale family, 位置尺度族& L! [. c( _/ V* L( y) k( i% x
Log rank test, 时序检验 + J6 B6 T# x( V" x9 W9 I* w
Logarithmic curve, 对数曲线5 R" c( o* X4 w0 @% B$ z- W
Logarithmic normal distribution, 对数正态分布
6 N% h$ n7 E: K yLogarithmic scale, 对数尺度
% f: x3 N ?; u9 H0 WLogarithmic transformation, 对数变换
* h2 ~5 r$ R/ JLogic check, 逻辑检查) s' K- v6 R. o9 B
Logistic distribution, 逻辑斯特分布
$ ?0 K! _+ R" }Logit transformation, Logit转换7 y% C( ?1 G! a& U0 R
LOGLINEAR, 多维列联表通用模型
( ^+ r/ e2 {: e) H% l" D' MLognormal distribution, 对数正态分布
" ]6 ` ]0 {' E' jLost function, 损失函数
! w+ ^, j: u8 ?0 \1 P; j$ M2 ?0 cLow correlation, 低度相关2 m; X9 K# F" ]- b9 W$ Q+ Z/ z0 P
Lower limit, 下限2 ?6 }' i+ ~/ _8 Y& l
Lowest-attained variance, 最小可达方差
" H* @. t5 L- L. b0 _% iLSD, 最小显著差法的简称0 p% S/ [3 E( l% A+ F+ O$ h
Lurking variable, 潜在变量7 _ `0 }/ q4 Y1 I- `
Main effect, 主效应
: c+ ^; b& h5 l$ W) MMajor heading, 主辞标目3 K _; V8 }( o" G3 ]
Marginal density function, 边缘密度函数0 f" f9 u+ g+ ~0 y8 O) p R7 J
Marginal probability, 边缘概率
9 \' u/ q* s! d4 hMarginal probability distribution, 边缘概率分布# l/ s* M# o. X$ J) w: Z5 J& O
Matched data, 配对资料0 l6 D6 Q2 J. T$ H& ^! s
Matched distribution, 匹配过分布9 j% x' X9 `$ |) ]% \+ H, S& \
Matching of distribution, 分布的匹配
, i3 `1 U4 V$ ?8 f; jMatching of transformation, 变换的匹配
3 L' n# B* n: A5 e$ M1 X- iMathematical expectation, 数学期望4 M b0 B4 r. o7 w( C- K
Mathematical model, 数学模型
* A5 ~' @- b( z6 [' GMaximum L-estimator, 极大极小L 估计量- E/ w( o: |1 b% `% _
Maximum likelihood method, 最大似然法
# X# h r" B2 i) u5 K- NMean, 均数
' f" X! U. r3 K! O0 {Mean squares between groups, 组间均方5 a6 O B5 e# j' P" v6 i# i. k5 o
Mean squares within group, 组内均方
5 ~& G- Q0 e! G/ n+ j9 OMeans (Compare means), 均值-均值比较. {6 P! O D! F2 H. V
Median, 中位数; z' g! A q/ O) D: e* J2 ?
Median effective dose, 半数效量$ _0 m* o/ Z" ]3 O K' \; \* x
Median lethal dose, 半数致死量
) ?7 W8 b/ k) M! W. _Median polish, 中位数平滑5 D* }1 t; n6 o: w5 n
Median test, 中位数检验, J3 @# `; ~ C, b
Minimal sufficient statistic, 最小充分统计量2 E0 }+ h6 _+ C: s3 {
Minimum distance estimation, 最小距离估计
; d8 b/ X: q& S% g ]Minimum effective dose, 最小有效量
; g) I; Q) ]7 d" A7 `4 a9 S! s' t% p+ vMinimum lethal dose, 最小致死量$ k; ^' g9 i) F# {# B* y
Minimum variance estimator, 最小方差估计量# ~$ w# |5 K+ ~7 E
MINITAB, 统计软件包- b% a+ [6 Q$ \" F2 o6 a
Minor heading, 宾词标目1 N1 A4 I5 P+ f# Q
Missing data, 缺失值
1 e) I! `$ O iModel specification, 模型的确定
+ Y. P4 T9 Y8 w O# D+ h7 @* SModeling Statistics , 模型统计( R8 B- q: A0 Y7 A% z' r% C( ~
Models for outliers, 离群值模型
+ ~/ ]0 G6 ~# l( eModifying the model, 模型的修正/ f# J& A j" l/ I' |4 q
Modulus of continuity, 连续性模
) m) B: M# M; t% c" h. WMorbidity, 发病率 4 O. r5 y' N5 v4 k4 Y3 u/ U
Most favorable configuration, 最有利构形: m+ |+ `) ~ a0 o# q
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
4 E5 W: k* w: [/ g7 X zMultinomial Logistic Regression , 多项逻辑斯蒂回归! i3 J2 r# }, {$ S: E
Multiple comparison, 多重比较1 ^ a+ V$ u) o' R& V
Multiple correlation , 复相关
$ F" ?* L8 N; D& AMultiple covariance, 多元协方差, h5 S$ w8 |( p; ^
Multiple linear regression, 多元线性回归: B4 {: W" W) K" `" O8 Q+ l) T7 q9 A
Multiple response , 多重选项; a0 V* y) u2 T7 x, _2 c' v
Multiple solutions, 多解
' ~8 V' ~+ V. p; {( x9 d: RMultiplication theorem, 乘法定理
) M" r* Z+ u5 {/ Z) L" yMultiresponse, 多元响应: P" ?5 {! e# H2 C
Multi-stage sampling, 多阶段抽样4 I( p: }0 G+ { X
Multivariate T distribution, 多元T分布; f; |3 v! E! c
Mutual exclusive, 互不相容
" P, p3 G6 B4 ~2 b) e" x! bMutual independence, 互相独立
/ |% V+ c+ ~; T; ~/ w. U2 s7 INatural boundary, 自然边界# v3 m/ H- m) ]
Natural dead, 自然死亡5 h m! Q" v$ I8 `5 a
Natural zero, 自然零, c( P" w' W+ P7 y
Negative correlation, 负相关, V F. N$ p2 p5 K1 u& q) T
Negative linear correlation, 负线性相关
: ~9 o8 o2 o* Q; Q, V( e) v% PNegatively skewed, 负偏
1 B0 {( p4 w5 ]" D7 J" U( DNewman-Keuls method, q检验
; L0 I* C! C' C5 jNK method, q检验
* J0 z/ y/ k0 \4 p4 x8 s* V3 _No statistical significance, 无统计意义( E7 y \2 [9 L
Nominal variable, 名义变量! w6 Z+ A, g: q6 r0 o7 v$ u4 A, e
Nonconstancy of variability, 变异的非定常性. |6 ]) R" T: ~1 n- H* _6 E0 H
Nonlinear regression, 非线性相关: A6 M1 ]) N: m6 P, N
Nonparametric statistics, 非参数统计8 e) Z- d9 ]+ D+ R8 W
Nonparametric test, 非参数检验8 j; F9 r- ]( L1 G0 X
Nonparametric tests, 非参数检验' ]- w0 W- c( x+ F0 |( z3 T
Normal deviate, 正态离差
5 n) r2 d3 r/ g" A9 zNormal distribution, 正态分布
3 W% m5 s( g* W' M7 s, i0 ]Normal equation, 正规方程组2 M" ~. I7 E& B: F' K
Normal ranges, 正常范围
% e) E b3 t3 W9 ]8 gNormal value, 正常值# A4 B5 Z! B2 Y5 c8 `
Nuisance parameter, 多余参数/讨厌参数* v) T o( M1 E7 |+ S
Null hypothesis, 无效假设
/ `+ ]. D1 W; D6 p# d. `" L) C6 H/ eNumerical variable, 数值变量
, b% w3 j6 T. sObjective function, 目标函数& [9 m5 [6 s, g6 A& K3 q2 g
Observation unit, 观察单位/ e$ y2 ?5 U4 W* ~ n
Observed value, 观察值
. g7 |" J, H1 z0 A3 \# {One sided test, 单侧检验7 h5 j+ G, r9 W7 Z2 S+ a# d- i
One-way analysis of variance, 单因素方差分析$ @& ~; }+ G9 ~: m% W" u, ~* J$ z
Oneway ANOVA , 单因素方差分析
7 \) w. V$ ~) z# y% s" W3 OOpen sequential trial, 开放型序贯设计
1 ^1 q" N) ~% B- D+ N& HOptrim, 优切尾3 C4 R/ M) f! F, w/ L5 i* O9 {
Optrim efficiency, 优切尾效率
, g* S1 o0 T9 C; {Order statistics, 顺序统计量
- }0 K& L; R) n8 R% m- @+ q! WOrdered categories, 有序分类
. S- z' {+ w, K Y) }4 q+ b! i: bOrdinal logistic regression , 序数逻辑斯蒂回归$ V0 _& |. I! Y
Ordinal variable, 有序变量) _; C a) w5 C1 C8 G, B
Orthogonal basis, 正交基
8 y6 F+ N- w5 Y) {5 \" D; z' POrthogonal design, 正交试验设计
" r5 Q, n' m, r7 rOrthogonality conditions, 正交条件
) y' d/ L7 T6 Q9 N! p5 ^! lORTHOPLAN, 正交设计
9 i. y4 L- G/ X7 k" |% p: _5 d; cOutlier cutoffs, 离群值截断点$ `$ A" R, Y1 ^$ V+ [2 v
Outliers, 极端值1 G: D% r8 g9 p
OVERALS , 多组变量的非线性正规相关
# p! K2 W! m/ n! a5 k& F9 tOvershoot, 迭代过度+ B5 s, r" }& ^2 [ w# V$ U" Z1 |
Paired design, 配对设计
, Q* B: ^ S: T9 dPaired sample, 配对样本
9 h: r1 S* Y# w W/ RPairwise slopes, 成对斜率
4 j# F9 ]5 i. m7 pParabola, 抛物线) R7 M6 R, \4 [# J3 G* ^
Parallel tests, 平行试验
$ h- W, e3 q4 D- S/ G/ m- CParameter, 参数8 @2 H. H2 C( D/ t0 t
Parametric statistics, 参数统计6 ?; O4 w! w6 ~$ Y0 \9 w
Parametric test, 参数检验
* p+ Y* I5 B2 i b wPartial correlation, 偏相关
2 \# n. t2 ~7 T4 @) R7 Q7 cPartial regression, 偏回归
6 H) `9 L1 u7 G7 H: n/ EPartial sorting, 偏排序3 e- Z7 ]- J0 J/ n% {
Partials residuals, 偏残差
' t, X( l) e7 z/ P7 ?* u6 d" WPattern, 模式
9 l. Q: Q/ g% R4 c- UPearson curves, 皮尔逊曲线
- Y! p, ^/ N. O5 p/ n$ jPeeling, 退层4 h& a1 }9 V# q4 }2 g+ i
Percent bar graph, 百分条形图- i. E! z* j. Z2 y
Percentage, 百分比
6 M0 c, z! E1 o5 ], yPercentile, 百分位数
- p: Z& Q9 K% fPercentile curves, 百分位曲线
* K4 N* H0 Q8 T8 y2 b: v* G4 uPeriodicity, 周期性5 |3 ^4 W( n; x2 K& c$ f" n$ _
Permutation, 排列
$ `5 m- H* q. x5 N* ~5 A1 b7 YP-estimator, P估计量0 f, K& k8 z* a& S7 ~
Pie graph, 饼图
+ p! V3 b7 e- f7 a1 Y' VPitman estimator, 皮特曼估计量
7 Y( V# u0 S+ _* A+ tPivot, 枢轴量
: [; b- K2 w8 z' M4 k& `Planar, 平坦: D+ K& W3 U2 B' |; Y
Planar assumption, 平面的假设
( o4 H( H% R6 k( TPLANCARDS, 生成试验的计划卡
7 L* Q' B% F6 ~$ l. xPoint estimation, 点估计. K9 n1 {5 e9 U ?- f
Poisson distribution, 泊松分布
$ j. I) t$ Y. U2 @, o a5 aPolishing, 平滑
1 O8 U2 E3 h3 \' @6 [/ qPolled standard deviation, 合并标准差
4 x% s! @8 J( j0 O8 n/ GPolled variance, 合并方差
3 t& K! R# r' i8 o9 r5 B8 K& wPolygon, 多边图
! ]# w& b/ D0 ~+ W8 iPolynomial, 多项式. B( E% X; d( |* l4 p6 H& ]
Polynomial curve, 多项式曲线, k% c6 i$ `6 L) U4 W- D: a2 b
Population, 总体) t; s2 E- K( n' B! G
Population attributable risk, 人群归因危险度; K7 z+ L# s7 B2 a, m
Positive correlation, 正相关4 p6 t( q5 Z H" a3 L
Positively skewed, 正偏
) Z5 o* ~+ Z1 l% A, SPosterior distribution, 后验分布
% v( Z$ u2 _( a2 s- ~% ~9 d- FPower of a test, 检验效能
n9 A( g; N5 v" Q# t' u3 Y$ WPrecision, 精密度) |/ X, ^( X3 r6 k3 i! f3 z- d
Predicted value, 预测值, G' U# q0 c2 p3 m) i/ T8 I
Preliminary analysis, 预备性分析
. g: R) [2 j( q8 n9 Q7 KPrincipal component analysis, 主成分分析0 x2 J" G S: ~: ^+ M8 k
Prior distribution, 先验分布
. @; S# K! ?2 ~7 o) YPrior probability, 先验概率; G* y4 R$ |5 K$ ~7 q! O0 S' [
Probabilistic model, 概率模型2 `( K! x* ?3 s1 m0 T) K. J& W; u5 o8 T
probability, 概率
X9 M' u: h4 }4 ]% E8 yProbability density, 概率密度
' c5 v6 T1 Q% u$ y3 ?( CProduct moment, 乘积矩/协方差
- J3 p( f! E3 ~9 E$ d7 n0 E( d1 ~Profile trace, 截面迹图7 W1 O, Y" q* e2 |7 o. P5 e( [
Proportion, 比/构成比
1 V5 s2 _# O9 |% N+ ~1 G" b# nProportion allocation in stratified random sampling, 按比例分层随机抽样1 J' i" h$ v* M' H
Proportionate, 成比例
* T2 t0 d! K/ A2 y1 AProportionate sub-class numbers, 成比例次级组含量
7 o! q; ?5 W$ _1 uProspective study, 前瞻性调查
9 C z: W4 }( g' sProximities, 亲近性 4 b3 K: `# Z! [6 W" B$ `3 a* e; u2 Q
Pseudo F test, 近似F检验
& j! G8 o+ f9 ~ dPseudo model, 近似模型
m; H7 S" i- lPseudosigma, 伪标准差
. |8 H) J, P6 ePurposive sampling, 有目的抽样! g$ S5 P o" o* @- j' M5 W
QR decomposition, QR分解& D7 v- c) F3 b6 J3 b" M
Quadratic approximation, 二次近似
* o$ O% G, X* C* H, @! f) zQualitative classification, 属性分类( ~0 G0 R4 Y; S
Qualitative method, 定性方法8 n% N2 L0 h' \3 p9 C! o, K
Quantile-quantile plot, 分位数-分位数图/Q-Q图! _1 B4 ?! y( D' W6 c. W
Quantitative analysis, 定量分析/ o% ?' |, [( H- E0 ^ o! z
Quartile, 四分位数
$ Q5 a- q& }4 b% o5 BQuick Cluster, 快速聚类/ w) Q1 Z1 h6 m/ Z1 c- G% H- Q
Radix sort, 基数排序+ j, j, h+ w' F" H0 t
Random allocation, 随机化分组, w5 n6 U: l# t7 @' @2 k4 n/ L& o
Random blocks design, 随机区组设计
# O% ~; t) c! {, ], URandom event, 随机事件
! x( A3 ~# n, m8 b5 f( hRandomization, 随机化
! R2 y; L5 |/ u3 S" a7 s* RRange, 极差/全距' B u p& z& Y
Rank correlation, 等级相关
$ f! t) F7 ?* t- B U$ s: aRank sum test, 秩和检验
& g8 Z' {( D! d/ NRank test, 秩检验4 s; i5 M0 P0 g! O9 G
Ranked data, 等级资料: I/ c& C b" h
Rate, 比率1 j; y' w5 _! o
Ratio, 比例' Z( C; `: k7 D( r
Raw data, 原始资料/ ?1 x- w4 n ^1 P" c
Raw residual, 原始残差
0 K: f# J4 X! O% m. L8 r& b% qRayleigh's test, 雷氏检验0 q7 |% M4 ] ~4 G" E( @. C
Rayleigh's Z, 雷氏Z值 ; H9 d8 i1 w" s; X8 H
Reciprocal, 倒数2 R3 J! F x2 f. y
Reciprocal transformation, 倒数变换
7 Z* D/ V" k' V; jRecording, 记录" y% \1 ]/ n: ~# x M1 S
Redescending estimators, 回降估计量- K) r9 S% _& s! i) F8 j3 X3 J7 m
Reducing dimensions, 降维( W! f8 c9 \0 y) p+ M; ?' [' y
Re-expression, 重新表达+ ]' m4 j3 Z, K
Reference set, 标准组
9 @ _7 P: m7 A5 r0 xRegion of acceptance, 接受域
# _: M7 k! x9 @5 BRegression coefficient, 回归系数
( x, [' j) g+ \$ F5 {/ A# G/ gRegression sum of square, 回归平方和2 u! s1 ?1 p& _; R$ P4 }0 Y5 d p
Rejection point, 拒绝点. L( g& G. n( W4 k
Relative dispersion, 相对离散度
8 R2 W5 K$ V r; a# Z6 \Relative number, 相对数
; W0 b- q7 j' G3 O7 @7 \Reliability, 可靠性
' v. g$ F, v9 z6 ]. {Reparametrization, 重新设置参数# x! c& ?( {7 l* U2 V# t
Replication, 重复7 h9 }7 I2 m6 z- b2 {3 i3 I
Report Summaries, 报告摘要
2 X4 M/ d+ ?! GResidual sum of square, 剩余平方和
; F! [4 ]- J6 r9 F k ?Resistance, 耐抗性* F! j/ _6 q' U* h
Resistant line, 耐抗线* O/ b' K; r4 r
Resistant technique, 耐抗技术( N* ~" j: I# R2 a3 R0 j
R-estimator of location, 位置R估计量
( c+ \8 w( z# ?R-estimator of scale, 尺度R估计量
. c$ a" V$ K/ @& LRetrospective study, 回顾性调查
+ P/ P* c+ e' c8 T0 m! A0 uRidge trace, 岭迹
2 V' X* ~, @) j$ ]* H- o6 eRidit analysis, Ridit分析
) p- W7 [$ `+ r0 n! `% R) WRotation, 旋转% x6 w0 g0 E' y. t) I
Rounding, 舍入
' i }+ b& u; V: B0 n. ^Row, 行* k, F$ u* S- @1 Z4 U
Row effects, 行效应0 K/ d, W; s% L1 Q
Row factor, 行因素7 p' a5 f3 O2 A/ u9 v' O
RXC table, RXC表
, [, D9 G% M9 z/ _# F8 {. c4 TSample, 样本
! O5 [$ c+ @) n8 U/ j uSample regression coefficient, 样本回归系数
% ]7 s. a7 s# ]- ]. h( c7 e7 sSample size, 样本量1 m8 Q3 R" f# }! _- c5 O3 \+ v8 G
Sample standard deviation, 样本标准差
, J" R$ w' m, ^/ S) b* k9 R: WSampling error, 抽样误差
0 [9 ^6 F2 v/ @SAS(Statistical analysis system ), SAS统计软件包# O D+ I) Z8 o5 e
Scale, 尺度/量表
% C0 x& j3 f, i( g4 o/ M; vScatter diagram, 散点图
9 }9 U# t$ m HSchematic plot, 示意图/简图
. K( y( L# W# L8 E* ] DScore test, 计分检验) }& |# c5 U0 `3 g9 _8 S |" ^: Y
Screening, 筛检' V Y" d6 z9 a, E! u! {6 k6 @: F. H; H
SEASON, 季节分析
" [# Q& G9 K9 B- I# Z" ^3 pSecond derivative, 二阶导数
9 I+ w; p. U, Y8 h* ^5 |Second principal component, 第二主成分
! T2 E/ r# ]8 ^ }) wSEM (Structural equation modeling), 结构化方程模型 : Y& ^( S6 s5 j; q0 O( P5 M
Semi-logarithmic graph, 半对数图
9 T0 G7 ^9 t0 R* T3 H4 ZSemi-logarithmic paper, 半对数格纸; m/ C. Y4 i# D7 S9 [
Sensitivity curve, 敏感度曲线
' N8 \2 h D3 B3 F- V5 G* j7 Z1 gSequential analysis, 贯序分析! D4 X* D: w6 m# ]0 h
Sequential data set, 顺序数据集3 T* U3 h+ p3 n2 T
Sequential design, 贯序设计1 k5 u& h% |7 I' n5 j" C
Sequential method, 贯序法1 {' L* ^' w( n* A! M; M
Sequential test, 贯序检验法( U i1 e/ U4 V0 g. Z' W
Serial tests, 系列试验8 j9 H" N) |5 H* c; K5 ~- F" |
Short-cut method, 简捷法
8 b7 U2 j' i# F) NSigmoid curve, S形曲线
( o% \* [7 z! w$ r% k* p S2 USign function, 正负号函数7 D+ ~3 c, E$ H2 h
Sign test, 符号检验7 A2 n% S! m9 Z; I
Signed rank, 符号秩+ N! B" d6 n: v# s( A) g! Q
Significance test, 显著性检验9 p I: ?" G1 ~( X% Q# p `) N; v
Significant figure, 有效数字
7 r& q' _& v% _( H) ^) S# v7 Z% |; O% bSimple cluster sampling, 简单整群抽样3 C9 m0 O1 M% N; D8 M M
Simple correlation, 简单相关
* k( l+ I& q! N! d, P9 P2 @! ]Simple random sampling, 简单随机抽样, o+ x0 `' D U7 {$ C
Simple regression, 简单回归
% M# R" |$ b o; G* v$ asimple table, 简单表$ \0 ?% p3 M) a! k9 I8 [
Sine estimator, 正弦估计量
7 h) w& Z' {- |/ y L/ [2 NSingle-valued estimate, 单值估计
: Z& u3 w/ D$ S* z2 ] WSingular matrix, 奇异矩阵
% @/ i1 o% ]0 E8 W+ G! N, s% q3 PSkewed distribution, 偏斜分布
" v3 W8 d; n$ i# @, r5 [' Z9 C0 |9 `2 O( \Skewness, 偏度
0 e2 @6 F) [0 n- T: ^Slash distribution, 斜线分布
' _6 x( r* | ?0 h0 Z! @Slope, 斜率! m; F. _' f0 ]6 |
Smirnov test, 斯米尔诺夫检验/ X* K+ ^& ]: L4 o8 v0 q
Source of variation, 变异来源
! K, t) c4 }& Z+ Q5 ASpearman rank correlation, 斯皮尔曼等级相关3 q2 W& P# q& j- I8 J
Specific factor, 特殊因子9 A2 U( u9 ?; Q7 ^* a+ `0 \
Specific factor variance, 特殊因子方差
, t+ X$ `6 ?1 s+ }, W+ E FSpectra , 频谱/ d- K3 p( W& e6 n% i
Spherical distribution, 球型正态分布- N" b' f% \6 l7 x, h0 L: ~/ E
Spread, 展布
: [% K2 u4 S! i% }, H* [9 D4 o* \1 h, ASPSS(Statistical package for the social science), SPSS统计软件包7 @" p1 G3 m3 B9 @1 V2 D( ]
Spurious correlation, 假性相关/ T& ~, N4 J2 H' E" w l i2 e
Square root transformation, 平方根变换
4 J4 W# z; r8 v: Y3 w" {$ X1 m% }Stabilizing variance, 稳定方差
# d% _1 }% k9 _' i% ?% Q% ]Standard deviation, 标准差' P, a3 g7 }9 s" \4 b
Standard error, 标准误4 C, y( c+ }$ o7 P* j0 C
Standard error of difference, 差别的标准误
, ~( p) }1 o1 OStandard error of estimate, 标准估计误差. }4 |: ?! J3 _4 ~& y
Standard error of rate, 率的标准误# A7 w8 a! m7 u$ M
Standard normal distribution, 标准正态分布4 _4 |& q x' W$ I1 v" y
Standardization, 标准化
. _3 i4 @$ l% _' c: p0 E# T$ _8 E! tStarting value, 起始值
( G- z# X* }* z. V# N7 I3 LStatistic, 统计量2 _3 g7 ~. k/ C# \3 {
Statistical control, 统计控制
& V$ Y6 [6 E" s# \Statistical graph, 统计图
, t! t1 g$ \- ^1 k6 }! l5 YStatistical inference, 统计推断( [7 {& O, x1 p) E/ z% D' q `& L
Statistical table, 统计表3 R, G, `! C8 ]
Steepest descent, 最速下降法
/ P$ r% A, h" G9 _7 J) GStem and leaf display, 茎叶图
) D" K* S% Q, n9 M" l, E EStep factor, 步长因子
& u% k. X$ ]6 K% P7 ^Stepwise regression, 逐步回归
# C) v" o* e" D: H( q% j& k* JStorage, 存5 w) h7 L4 |# ?8 X
Strata, 层（复数）6 E. {4 k7 ]& g
Stratified sampling, 分层抽样
1 K, P/ ~5 |; M$ Q; Z( YStratified sampling, 分层抽样; {4 i- T+ s E& k0 O
Strength, 强度/ A2 ]3 Z5 L& h1 n+ e' M
Stringency, 严密性- J+ |7 y2 x1 q; `
Structural relationship, 结构关系
. o! X* c( q3 d, w: z1 Y$ Z8 WStudentized residual, 学生化残差/t化残差4 n9 B& H v3 p) J
Sub-class numbers, 次级组含量 P& f8 \ V+ ?
Subdividing, 分割 o- }3 B' p1 H# g6 w# N6 A
Sufficient statistic, 充分统计量
7 M- c; ~* }% T2 JSum of products, 积和
; ^5 p5 q$ h. l8 v. }' O' A3 |' X1 dSum of squares, 离差平方和. ~8 k( R0 A9 t0 b) S
Sum of squares about regression, 回归平方和9 ^; p$ @6 Z4 g+ h2 \
Sum of squares between groups, 组间平方和
% \5 S$ `1 T8 W$ W: R, pSum of squares of partial regression, 偏回归平方和
; i. c6 U! k( z6 T: R6 x& @Sure event, 必然事件
5 f& \+ p; G' G* s @; W+ u7 |Survey, 调查
N. x' e( }+ n$ c2 J- ?) r$ xSurvival, 生存分析' q' t/ J& \" j9 [' ~: k$ u
Survival rate, 生存率# x% G5 Y4 V2 w [
Suspended root gram, 悬吊根图1 C9 C# K6 i4 ^
Symmetry, 对称
' F: v4 d2 G; p+ r; S1 @. ~Systematic error, 系统误差6 e! M. ~: J( M
Systematic sampling, 系统抽样$ C0 p A1 t. ^5 I/ H
Tags, 标签1 t5 l3 j/ n/ U
Tail area, 尾部面积& k5 O' U2 n8 q$ J
Tail length, 尾长
/ I% O/ P! v# G) M# ATail weight, 尾重7 h9 g8 k4 Y' b' B; e$ l
Tangent line, 切线+ d ^6 a# E3 Z/ Q6 z4 @
Target distribution, 目标分布
) v5 S: g& z& STaylor series, 泰勒级数
. Z) |# @5 ~* M1 C4 oTendency of dispersion, 离散趋势
2 t) E! a% w3 J- VTesting of hypotheses, 假设检验
/ ?6 \* r* w: u! [5 G7 j4 f% |' JTheoretical frequency, 理论频数
0 p! ~$ a: ?* A! P; `6 f- u- |Time series, 时间序列' f" S! ^, W: Y
Tolerance interval, 容忍区间
2 g* C5 A( F R, Z. }2 u- X7 ITolerance lower limit, 容忍下限
& C! l, F' d2 M" u" C* {( iTolerance upper limit, 容忍上限
" l* g1 |) f9 fTorsion, 扰率
6 g4 ?& B# E# a$ ~. C, ^Total sum of square, 总平方和+ O5 `6 ~% g8 y1 h0 G$ e) R
Total variation, 总变异
2 |' v4 d5 }. F) a) WTransformation, 转换
$ l# Y6 ^; R o3 i6 u+ DTreatment, 处理* e+ @8 i# ]! L2 Y
Trend, 趋势5 X2 j! f+ H0 L; y- ^9 S
Trend of percentage, 百分比趋势
6 L& G% ?: m; ^$ Y1 _$ T( Y: mTrial, 试验3 z2 w6 ^+ W: V' Z+ Q
Trial and error method, 试错法
) W; k {7 [ a2 {1 _" m+ o* r" N! aTuning constant, 细调常数2 f7 o6 U% a" y5 s4 s& j7 L) m
Two sided test, 双向检验8 G( D" M N4 o- r. {; Z! r8 v
Two-stage least squares, 二阶最小平方, f7 u5 |9 n1 G6 I3 ]
Two-stage sampling, 二阶段抽样
. f& Y; b- u* Y) q+ y; A; cTwo-tailed test, 双侧检验% [4 g7 j$ _1 r, k
Two-way analysis of variance, 双因素方差分析
4 J) w: x6 N9 w7 ~! r% t: c$ OTwo-way table, 双向表3 P! V _" ? x- A/ w
Type I error, 一类错误/α错误1 D l# o8 T; J) E: P
Type II error, 二类错误/β错误/ i0 y H I+ V) n. M
UMVU, 方差一致最小无偏估计简称: f# u) v, Y9 r/ p- X1 Z
Unbiased estimate, 无偏估计
! E. i1 A1 l n, M4 \# R; tUnconstrained nonlinear regression , 无约束非线性回归
# _; z; [, S5 w8 [' fUnequal subclass number, 不等次级组含量9 E {# x' x. Z" g; ?( V5 @; c+ d/ H
Ungrouped data, 不分组资料* }+ y% P; ]3 D5 V- B1 I, U
Uniform coordinate, 均匀坐标
! _+ n- _! a3 L4 OUniform distribution, 均匀分布
4 k8 L, A4 a) K5 {2 f/ Q9 iUniformly minimum variance unbiased estimate, 方差一致最小无偏估计* f9 ^8 ~% p0 p/ C* C/ ?9 S6 A
Unit, 单元
8 M. h7 B0 H3 n, Z: PUnordered categories, 无序分类
+ ^6 i% {9 q" q9 VUpper limit, 上限$ Q- ^5 f- E/ G
Upward rank, 升秩
7 N- y8 f l4 h7 nVague concept, 模糊概念
/ W' {7 g8 N, T! H( o" L: VValidity, 有效性5 Q" n: P- j* z6 d
VARCOMP (Variance component estimation), 方差元素估计( [, V6 ^- h: H& R) @0 H
Variability, 变异性$ j3 m2 N. v/ Z1 O s9 j: V! }0 p9 q5 o
Variable, 变量( @! i; i5 f B) l0 Y
Variance, 方差
/ ?* c8 R0 t i% t' `Variation, 变异
8 b! c5 q; G5 \; G: `Varimax orthogonal rotation, 方差最大正交旋转. }4 w: A e' \; u! y
Volume of distribution, 容积
5 Z# W- O p/ v3 p+ ?) M' X2 P+ lW test, W检验
& `% S. x4 n3 s7 wWeibull distribution, 威布尔分布
" X9 i( r' i4 UWeight, 权数
* S' |. b; {8 c1 X" Y0 aWeighted Chi-square test, 加权卡方检验/Cochran检验7 @2 M: q# K, @4 z2 Y/ [; I
Weighted linear regression method, 加权直线回归9 C3 L& S2 @5 L
Weighted mean, 加权平均数
# f1 z! a; {/ Y1 q) E3 i; tWeighted mean square, 加权平均方差+ K& W' h/ V F6 t! j. E
Weighted sum of square, 加权平方和
9 ^# O4 O) U/ U8 H- nWeighting coefficient, 权重系数
4 q: }- B# o$ f: CWeighting method, 加权法
, q0 ^! v! U/ U8 C% xW-estimation, W估计量
9 Y* X6 M7 F* P: T$ cW-estimation of location, 位置W估计量2 q5 s/ b# \1 X9 m8 X
Width, 宽度$ O9 G7 k4 s$ x7 T2 I9 c8 b8 \
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验. t' F% F+ \; q9 L& e6 O, m: r
Wild point, 野点/狂点
1 K7 ~$ o9 p* q7 G. g3 f' ?Wild value, 野值/狂值
+ B; y* ], E7 {Winsorized mean, 缩尾均值3 v% T+ t, m, ^* D
Withdraw, 失访
" I& q! B s) `; B$ w8 V+ V& TYouden's index, 尤登指数6 X, U+ c, j6 D
Z test, Z检验
5 R. x7 j9 f% {Zero correlation, 零相关
& R0 O; D4 l! Z# }& |Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
