|
|
Absolute deviation, 绝对离差! d% E2 y t2 P& r
Absolute number, 绝对数: Z/ m3 r+ N. [/ y! g5 j+ I
Absolute residuals, 绝对残差
) s3 [' [1 Y! j2 HAcceleration array, 加速度立体阵
, _( I. x! D2 ^5 E& ZAcceleration in an arbitrary direction, 任意方向上的加速度; _: B7 G) K4 k. w
Acceleration normal, 法向加速度+ E* k7 y* B8 k! z1 ?' a [
Acceleration space dimension, 加速度空间的维数# a- t5 m1 d& m" P, @
Acceleration tangential, 切向加速度0 h8 C# b& ~, M6 N( g5 A/ i
Acceleration vector, 加速度向量7 }# W- B; @+ @( P
Acceptable hypothesis, 可接受假设
" p/ {: j- ]# s* Y8 f9 c* g# E3 R/ fAccumulation, 累积
, y* y0 u; t& H+ s* u. QAccuracy, 准确度 K2 e* y. `* F5 [! T# P6 S2 R
Actual frequency, 实际频数2 j. s y( A; d0 U! J w# x3 z) ` N
Adaptive estimator, 自适应估计量
* ]! [1 a W9 r- \Addition, 相加
, V% y- L% D+ l2 c& C# `Addition theorem, 加法定理
6 W* z6 G. ?' ~. v& kAdditivity, 可加性! Q% X" N+ s2 i
Adjusted rate, 调整率
: i$ k. h4 M9 p$ s; N. wAdjusted value, 校正值! W$ ~7 V ^9 a# N$ G: u
Admissible error, 容许误差2 y+ x- Q1 A/ P( V1 F v0 G
Aggregation, 聚集性
" c* i! U$ V, l; u- z0 i+ Y: HAlternative hypothesis, 备择假设
* v6 B5 J* @9 j0 P% w/ c) AAmong groups, 组间
4 E1 @1 Z9 S& `: i" qAmounts, 总量) Z. T- H# x3 g
Analysis of correlation, 相关分析$ t) u; X: r& L. ]1 g1 O; w H
Analysis of covariance, 协方差分析7 K% p6 G; J4 R8 g/ f4 i
Analysis of regression, 回归分析
1 ~5 T b' m# \5 A5 N2 b4 h' R) _Analysis of time series, 时间序列分析$ @2 p1 g+ q: m d( s
Analysis of variance, 方差分析
; W$ w6 z5 y4 W7 @Angular transformation, 角转换; X% |0 q; Q# G+ w
ANOVA （analysis of variance）, 方差分析, P3 ]7 ~6 j3 y' u! D
ANOVA Models, 方差分析模型
; G6 g3 R1 B" T5 ~; y' H9 ZArcing, 弧/弧旋3 B; J- `4 X+ o: j: a
Arcsine transformation, 反正弦变换" S0 J5 |% n& Z4 |/ H5 d
Area under the curve, 曲线面积& k( R5 v- ?) m# g6 P4 x
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
8 m) P+ \; Q$ ^0 g& e2 DARIMA, 季节和非季节性单变量模型的极大似然估计 7 F4 P! y3 z' D- a
Arithmetic grid paper, 算术格纸 f6 L% b3 k8 V$ s) o0 y7 J% v
Arithmetic mean, 算术平均数
1 Q. S* s, m( l8 zArrhenius relation, 艾恩尼斯关系! O% z1 ~7 a/ _0 f
Assessing fit, 拟合的评估5 H4 ^" L2 I. \+ }/ U
Associative laws, 结合律. N4 q9 D$ P. S4 q* E K5 n: h& h
Asymmetric distribution, 非对称分布
# _- w1 x4 C0 `$ ]/ h" y4 l" q" n" xAsymptotic bias, 渐近偏倚- M1 Y" z$ e' x3 I* W8 f9 Q
Asymptotic efficiency, 渐近效率9 v0 ?( y2 d* G( O
Asymptotic variance, 渐近方差
1 L( n! t& q. m8 |( \6 ^Attributable risk, 归因危险度' J- U% i6 y' I& A+ w3 P
Attribute data, 属性资料
: b6 L4 p6 M/ Y [5 @" ^0 T7 u3 QAttribution, 属性: t) l& k8 _3 k+ | T: [* n
Autocorrelation, 自相关
% ]0 R R9 V& J: m0 iAutocorrelation of residuals, 残差的自相关
4 r" O8 J k, I! Y2 I" cAverage, 平均数: k4 k8 i/ s0 f# Q/ G: \
Average confidence interval length, 平均置信区间长度! Y$ J$ K' U- O
Average growth rate, 平均增长率% U' h. \# l1 m) O
Bar chart, 条形图
& w; @! h- w1 p4 I- m0 H. gBar graph, 条形图* w$ F. L* V6 ~4 L& }) f
Base period, 基期
# b; e( j; d/ Z5 F% n8 wBayes' theorem , Bayes定理+ R' `$ Z* Z8 [( E A; q) @
Bell-shaped curve, 钟形曲线. }- p# _$ a& k
Bernoulli distribution, 伯努力分布: R' i7 D* W9 a( @% H1 d) x. T
Best-trim estimator, 最好切尾估计量6 l9 X6 V% X1 R
Bias, 偏性( l& U# Q6 S; c
Binary logistic regression, 二元逻辑斯蒂回归% T8 x) }9 @. d/ j |/ U
Binomial distribution, 二项分布' n) k$ [; c1 Y: H# o$ A
Bisquare, 双平方3 h+ `; b; ~; J
Bivariate Correlate, 二变量相关( T7 `5 [+ V; w6 F2 s: e# d
Bivariate normal distribution, 双变量正态分布+ V. @- x, u6 A0 F3 W* K: a
Bivariate normal population, 双变量正态总体6 u; |7 L0 g% _" r' v a
Biweight interval, 双权区间3 K' \6 |( |) P3 K( Z" v! }
Biweight M-estimator, 双权M估计量9 R3 E) B! ?5 W# u4 P! U
Block, 区组/配伍组+ D" w# F7 `6 K* l) r: J
BMDP(Biomedical computer programs), BMDP统计软件包# H; t& a9 ]& [& a2 \: ]
Boxplots, 箱线图/箱尾图
0 v2 s0 D& p9 g4 ZBreakdown bound, 崩溃界/崩溃点% @+ g0 |; p2 c: N1 b
Canonical correlation, 典型相关1 F* i, J2 Y3 x; [
Caption, 纵标目6 ~4 a1 @, F' j5 f4 d
Case-control study, 病例对照研究1 d( f5 d- J( t
Categorical variable, 分类变量( k* r8 M* l% g9 X0 u' R: K
Catenary, 悬链线
% q) l! l& Z7 m$ a; ?: c7 NCauchy distribution, 柯西分布' t6 L3 k. t8 ~( e: h
Cause-and-effect relationship, 因果关系- f. Z+ O' y" j2 z T
Cell, 单元4 L* d' m/ @1 z- M0 }' H5 E
Censoring, 终检
8 I, w- w. j/ v* Y7 |Center of symmetry, 对称中心: a3 g6 @3 K$ w! \5 A
Centering and scaling, 中心化和定标
; l1 d# z9 C% F1 d: ^0 `Central tendency, 集中趋势. X. N4 T/ [/ j+ g
Central value, 中心值# q8 C( E/ j/ N- U3 j, s
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测5 e" [# e" r' @! ~% R
Chance, 机遇5 `/ V( y P' K0 c1 t9 j# L
Chance error, 随机误差- z, y0 Z2 N7 i
Chance variable, 随机变量; z8 m0 u0 v2 s4 X
Characteristic equation, 特征方程! H* R% z" A8 [2 ]
Characteristic root, 特征根) T" e7 s4 c8 R: d: m; J% y
Characteristic vector, 特征向量% x) d2 h2 u1 |8 i2 Q. j
Chebshev criterion of fit, 拟合的切比雪夫准则
7 K' X, l. [5 _! Y S0 dChernoff faces, 切尔诺夫脸谱图- F5 y' n$ V7 S& I ]& d
Chi-square test, 卡方检验/χ2检验
5 y% E6 b# W, o2 b6 B/ Q5 sCholeskey decomposition, 乔洛斯基分解0 ^9 N* x& Y+ a, Z' p0 D5 H5 `
Circle chart, 圆图
8 C$ B% s) `/ X% m* H! XClass interval, 组距& f6 l0 D$ P1 `. L4 {$ B: U! Y
Class mid-value, 组中值
7 g2 m/ `6 z; v* VClass upper limit, 组上限$ v- b8 M; o8 L' s1 M. u
Classified variable, 分类变量" X2 v9 f( m' `7 Q1 u
Cluster analysis, 聚类分析
1 [: Q$ M, d+ w1 x& WCluster sampling, 整群抽样
1 x8 j6 [9 a# D; O7 fCode, 代码
( A ^, i7 q! R0 @Coded data, 编码数据
# h2 r5 j# ~- Y3 `3 F! Y& I( xCoding, 编码& \* J8 G9 f5 B
Coefficient of contingency, 列联系数# z5 F, y7 @" Y6 k, q* \. m! }# q7 d
Coefficient of determination, 决定系数. d' Y4 a' i3 D6 A1 {& {/ A; O
Coefficient of multiple correlation, 多重相关系数
! B& B( O: S! N2 m8 M$ Z1 ?Coefficient of partial correlation, 偏相关系数2 s2 h8 ]- o; O9 t9 i1 B5 n' y
Coefficient of production-moment correlation, 积差相关系数- k8 z4 [9 {. R4 L: W* U! ~" y* R
Coefficient of rank correlation, 等级相关系数
# }& W3 w! N; U0 J+ FCoefficient of regression, 回归系数8 c& H7 a. d3 U+ |6 E2 |3 D
Coefficient of skewness, 偏度系数/ h: q5 x1 J" x1 `$ }# `% ?6 Z$ H
Coefficient of variation, 变异系数
( |& T* d, D2 D7 } w( e' }Cohort study, 队列研究/ w1 {! Y6 S" v" k
Column, 列
+ E# j7 R6 \4 S" s' _Column effect, 列效应0 D% w1 x2 l1 D( ~
Column factor, 列因素) g4 c$ G! S; R* y* g/ I0 ^; ~2 \0 k
Combination pool, 合并" }( z$ B; P) X4 h6 x" _1 b. f6 I
Combinative table, 组合表/ F7 T* k( `# h
Common factor, 共性因子
5 m, G/ p- U+ B) jCommon regression coefficient, 公共回归系数
6 j* B( D' x2 ~+ z% tCommon value, 共同值# I( s3 G, c- H! c. \; R6 O
Common variance, 公共方差6 |9 p w( ?/ [' e, i8 E
Common variation, 公共变异
) J. ^" X8 c4 BCommunality variance, 共性方差
7 X* p0 |' g8 K# H0 L6 K# `Comparability, 可比性
9 h/ w+ Y# Q: u- o5 N0 jComparison of bathes, 批比较
5 h1 F. l8 b" B9 c# a3 v& UComparison value, 比较值
j% W1 S* W: t1 m% U) ?Compartment model, 分部模型: ]5 ~) X+ ^2 i0 S* i P1 Y6 j( K
Compassion, 伸缩& B" m; e2 @& |5 D$ u
Complement of an event, 补事件" f% |; q9 Y- U1 l, q: |: V
Complete association, 完全正相关
; L, @- t/ {' X- `) i# q5 ?! FComplete dissociation, 完全不相关' h4 l {/ D9 f# p" q+ r, k
Complete statistics, 完备统计量. U4 D. b, w! h$ W2 q2 I' b
Completely randomized design, 完全随机化设计. Z& o+ I9 {; R4 k; |
Composite event, 联合事件
9 G/ f. @ S$ r3 EComposite events, 复合事件
. f. S7 ^+ g/ ~) `* h5 nConcavity, 凹性. |' h0 R; ]$ {) u
Conditional expectation, 条件期望
8 S: p8 G# q$ o& X/ d+ U0 Z. JConditional likelihood, 条件似然
1 [, e6 c9 `; nConditional probability, 条件概率
+ j5 Y1 a4 `3 `4 e& `Conditionally linear, 依条件线性
+ y; L* a5 \0 ^. {9 lConfidence interval, 置信区间
o9 Y" A: W5 G1 V( ~9 XConfidence limit, 置信限$ e; b4 d0 X) c
Confidence lower limit, 置信下限
, d+ U; c# V" K7 K% F: vConfidence upper limit, 置信上限1 w1 s8 x) D0 h
Confirmatory Factor Analysis , 验证性因子分析
. q! ^# p+ k, e0 P; Y7 E2 f1 C2 uConfirmatory research, 证实性实验研究
# D9 l% z) h% C1 ]9 K* HConfounding factor, 混杂因素 T( s. G/ G3 N4 v4 j. h, ^) @
Conjoint, 联合分析8 u. B* j6 P \' v' D; ~& j
Consistency, 相合性* F* R0 n. ^( \, Q
Consistency check, 一致性检验
! ]+ W* B7 \1 A4 o7 W3 VConsistent asymptotically normal estimate, 相合渐近正态估计
$ m5 J* h' d6 [- B9 K. f' fConsistent estimate, 相合估计% {; g5 J, I* A1 s
Constrained nonlinear regression, 受约束非线性回归+ |+ Q9 K2 p, }* J
Constraint, 约束% ]3 R! a% f1 \4 _# f; N1 {8 }
Contaminated distribution, 污染分布: l3 U2 \% c$ ~/ F/ u R
Contaminated Gausssian, 污染高斯分布
* V+ c0 k8 r3 w! H4 T( _9 _$ M; IContaminated normal distribution, 污染正态分布
D2 f! T. S9 i: Z7 UContamination, 污染4 L& h. h& x" t5 X0 @
Contamination model, 污染模型0 u! F& s. M6 G2 e# W( K/ W
Contingency table, 列联表
% D* ?+ _) r5 R1 r1 wContour, 边界线8 B4 M0 n' [! y }" h
Contribution rate, 贡献率
& @! z6 _) C% V: _$ d5 N3 o# EControl, 对照# b% ^+ W1 v4 |. s+ k8 M
Controlled experiments, 对照实验
: h5 I! B' O' |Conventional depth, 常规深度4 c% V( t4 \ P! o: T& X1 a( p" @- W
Convolution, 卷积
0 A# o3 \. q" v2 _Corrected factor, 校正因子0 F O- }. f/ g$ _5 P6 Z; H% N
Corrected mean, 校正均值* _; R+ X: i' ^( f0 f( P: O! d
Correction coefficient, 校正系数
' D4 Z4 c+ ^0 VCorrectness, 正确性- G9 x; p" V1 w e# [4 J, n
Correlation coefficient, 相关系数
/ T Z: M- z* \5 H0 X- hCorrelation index, 相关指数 a( y) B- L$ s
Correspondence, 对应
# E% F' O/ u# \- B1 }& b8 PCounting, 计数8 j% X3 T, F4 S( }" A2 F: U0 M$ l5 [
Counts, 计数/频数
$ a! v: K* Z5 f% F h9 jCovariance, 协方差
2 s- L0 i, e& h3 N3 b, S1 y& d) JCovariant, 共变
" N. @& ]+ P0 K8 Q0 k cCox Regression, Cox回归
( q5 S0 x J1 U' v6 u- MCriteria for fitting, 拟合准则6 o0 A9 ]8 V9 s$ S4 {
Criteria of least squares, 最小二乘准则: P6 l0 a n1 m2 P* s* V2 V
Critical ratio, 临界比7 T" G4 e8 q1 {8 @
Critical region, 拒绝域
* M/ [% `$ v( N6 XCritical value, 临界值
c/ `: W- [+ \+ a; oCross-over design, 交叉设计9 w8 C# M6 C& E* r
Cross-section analysis, 横断面分析
2 U* }& y- `7 [% [Cross-section survey, 横断面调查
* Z2 y5 j9 m! w, z1 e3 o4 wCrosstabs , 交叉表 ( ]/ r- l3 U' ^7 i# k0 f5 d
Cross-tabulation table, 复合表; h* B3 c) E" W6 [
Cube root, 立方根
8 w9 c% k# s" o6 `1 M3 t5 lCumulative distribution function, 分布函数
S6 o$ b* x9 `# ~" S4 c. vCumulative probability, 累计概率
- d2 M+ N2 p/ l! t& s' Q g9 ?6 XCurvature, 曲率/弯曲
) m/ D4 l2 A/ z" |2 ^6 u1 E; V6 DCurvature, 曲率
7 D3 \1 `! Q8 E4 O6 ?% DCurve fit , 曲线拟和 5 k6 I: U+ K# N7 J; I# ?. s
Curve fitting, 曲线拟合
5 m$ O, T4 q2 g5 ]) sCurvilinear regression, 曲线回归$ Q$ w5 e( H8 z# j* u
Curvilinear relation, 曲线关系5 z& u ~8 T% V1 D$ G; i; C$ @
Cut-and-try method, 尝试法! c: U: A. K: z
Cycle, 周期7 G. j2 |+ v% [3 p8 m
Cyclist, 周期性
8 l8 D4 j/ W' H, pD test, D检验2 [+ ~& j) l" X: m: c9 ]
Data acquisition, 资料收集
2 @2 |( s' G, H! Y* l2 bData bank, 数据库
* R$ n* R8 U4 ]7 aData capacity, 数据容量' F( O4 j' ^& k2 \6 w2 c
Data deficiencies, 数据缺乏
$ j: f) {1 o5 \8 v6 m: VData handling, 数据处理$ ]2 F* g& T# U3 J+ ^& p' V. [
Data manipulation, 数据处理
+ ]0 _! K2 R7 c- d1 ~2 cData processing, 数据处理
' Z) z5 O) w7 [Data reduction, 数据缩减
8 I8 H/ H; x0 Y% R6 T: v1 gData set, 数据集
) e3 |0 H2 z- R- {. S7 g0 B3 y7 h HData sources, 数据来源1 k5 T: _2 }! B. _: I4 B- T
Data transformation, 数据变换
5 D4 P! ]' [* i" u- S e# c1 M* A5 o& jData validity, 数据有效性
: n0 t- X4 K0 {& ~& j' `) f tData-in, 数据输入
o- d6 _+ `4 l$ n! q! @Data-out, 数据输出5 Z0 B3 {# G, I7 ?& P0 g, d9 ]
Dead time, 停滞期
, W: x1 a5 O1 Y$ t# NDegree of freedom, 自由度9 W* }6 _% L$ T) V/ J* T
Degree of precision, 精密度' i% c& i: S \/ T' D; }
Degree of reliability, 可靠性程度
( C, O7 s, W( TDegression, 递减
2 ~! y; r$ Z% h# Q; bDensity function, 密度函数
7 k2 J z+ B+ Q8 u8 C. TDensity of data points, 数据点的密度/ ]3 t) k* A& |- {: ?: @6 @
Dependent variable, 应变量/依变量/因变量
& n1 Z4 l& {5 U" F& [Dependent variable, 因变量, \3 p5 m" A: ~, y% H9 F
Depth, 深度
& b3 S: V3 }4 s( C! M1 }; N" ]" IDerivative matrix, 导数矩阵: h i [7 W: u8 S+ ^: j
Derivative-free methods, 无导数方法
, ?. v5 Q( z2 R# O$ g7 I3 u3 A) BDesign, 设计2 {% n2 @6 b& ]4 i
Determinacy, 确定性
6 N* a0 ^5 v4 [$ P: _) IDeterminant, 行列式5 K: f r" y6 i
Determinant, 决定因素
# {/ j& d( A- d+ ~8 P2 {9 }& iDeviation, 离差2 y% L, w1 L: W& ~) v
Deviation from average, 离均差+ ?% x' I7 j8 l# D' J8 e J; R4 \* K
Diagnostic plot, 诊断图, W5 X( ~+ [: i9 Q7 l6 Z2 {
Dichotomous variable, 二分变量2 O# i# g' v, U z) {( C: R7 B1 t5 i
Differential equation, 微分方程
/ p* n# D: ?- J7 B g6 {Direct standardization, 直接标准化法4 p! L6 N. }% H& t4 A9 @1 w+ d
Discrete variable, 离散型变量4 R& o5 C3 I& q
DISCRIMINANT, 判断 l5 G& e8 K% K6 W f
Discriminant analysis, 判别分析& T+ C$ E2 T1 `2 [) g
Discriminant coefficient, 判别系数
. l( B- I5 g6 w: U5 `Discriminant function, 判别值
4 ~+ q/ }. @3 {/ E6 eDispersion, 散布/分散度( c3 \- r# f7 X
Disproportional, 不成比例的# A& f0 \4 ^4 s9 P) Z9 C
Disproportionate sub-class numbers, 不成比例次级组含量" p8 c# z/ j9 }% N
Distribution free, 分布无关性/免分布
, } Z, X. g M: O( WDistribution shape, 分布形状( b2 t0 o' L" t: j0 T; ~
Distribution-free method, 任意分布法
+ w, \) B- o( t4 ]0 HDistributive laws, 分配律' I% J6 ?/ v- s! @* S: d
Disturbance, 随机扰动项" D5 G8 o" h3 M3 l. o
Dose response curve, 剂量反应曲线
2 v8 u% v. @0 o! w1 b, t) c3 k- s1 uDouble blind method, 双盲法
, b) I, m" F, F' iDouble blind trial, 双盲试验
; `/ H7 v, Y J; X4 h+ DDouble exponential distribution, 双指数分布
1 V0 Q: Z5 g! [, n8 S1 ?: ^1 \8 jDouble logarithmic, 双对数 t* Y$ R- U0 p
Downward rank, 降秩( V3 g1 m) k# i( w+ X6 _$ N
Dual-space plot, 对偶空间图) z' W8 ^* O5 ~$ D3 m. m0 ]
DUD, 无导数方法7 d3 I& C4 F3 d z1 H0 q
Duncan's new multiple range method, 新复极差法/Duncan新法! C6 O" | j2 [3 B0 s& s9 ]! m+ n9 `
Effect, 实验效应
: o7 V) w5 p7 y, WEigenvalue, 特征值5 s3 Q1 J: `! h
Eigenvector, 特征向量
8 O3 n7 R8 L A0 N1 x/ Q, z3 @Ellipse, 椭圆
" Z0 N7 p/ Y9 l4 z$ m& qEmpirical distribution, 经验分布; F! q9 T& r5 b" d# M) W- m0 @
Empirical probability, 经验概率单位
% L8 |2 C" w! p+ M6 DEnumeration data, 计数资料8 i4 ^& x* r, i0 I$ j8 [" x1 b
Equal sun-class number, 相等次级组含量
6 V* c8 ?7 o* J1 zEqually likely, 等可能4 X, l3 V; Y6 P. E7 K' a8 t& p" a
Equivariance, 同变性
& j0 |; k' k0 m: Y. u/ H8 z6 o/ }Error, 误差/错误0 l4 ?8 N( G+ W. @6 w
Error of estimate, 估计误差
& v o/ [0 _' E, S+ M6 hError type I, 第一类错误
6 {; U' G; M0 ] m. T7 iError type II, 第二类错误
' w) Y3 ?. f* l0 n$ k2 T2 eEstimand, 被估量) r7 T$ B3 Z8 m% B4 w$ l
Estimated error mean squares, 估计误差均方
3 ?/ |( k- ~5 m, qEstimated error sum of squares, 估计误差平方和
! ?. D, {. j j' ?Euclidean distance, 欧式距离
, e; \; @0 `- I2 b/ r" }; vEvent, 事件
" D+ x- I5 P5 R z; u5 GEvent, 事件! | c* k' H+ ~ v ]! n( A
Exceptional data point, 异常数据点1 q; a: ?6 I0 b1 h, j1 h
Expectation plane, 期望平面 M" ^- I# I/ i8 R" B+ v# j; m
Expectation surface, 期望曲面2 C4 V _" b) D; v& i
Expected values, 期望值
/ a: e/ |' B! H' m' OExperiment, 实验
( G% e9 G r1 Q9 W, D; b( hExperimental sampling, 试验抽样
, P4 _ q& Y; Y& I0 T1 A; BExperimental unit, 试验单位
! c. N( G& u5 X& E, M& [+ sExplanatory variable, 说明变量
# p$ c( A. O+ F5 W2 ^Exploratory data analysis, 探索性数据分析" s2 _% y7 f" ~( A4 b+ s0 Q: W, e
Explore Summarize, 探索-摘要0 U- }! U% ^" N
Exponential curve, 指数曲线% h( o2 `3 q9 G5 z
Exponential growth, 指数式增长8 x" d" R9 U/ U
EXSMOOTH, 指数平滑方法 ( X. B& w9 L1 i' ]5 o
Extended fit, 扩充拟合$ O: |* c+ m* u2 D) q) `
Extra parameter, 附加参数
2 {9 n/ v( l7 ^& V, q1 _. OExtrapolation, 外推法+ q" @, h" c; F% p8 e, d
Extreme observation, 末端观测值
% N+ p( f7 u; Q- \2 `6 g- XExtremes, 极端值/极值" P6 J" y+ u& R3 V6 K1 a) A
F distribution, F分布
' ] @& I0 { j+ LF test, F检验
" q1 Y# P7 l+ }5 f1 bFactor, 因素/因子
, S+ \2 R5 Y% B: X3 E$ i7 s. pFactor analysis, 因子分析0 d- e( Y9 H- h2 {2 L& s/ k
Factor Analysis, 因子分析, }1 g3 Y3 Z- P8 `4 Q% f
Factor score, 因子得分 ' h3 c- }% F/ v% ~7 ]% B; \) a+ T
Factorial, 阶乘( r7 w2 E& u. J$ S" Q9 f
Factorial design, 析因试验设计( o& X1 B4 R; ~! v$ n* A
False negative, 假阴性) l" J$ l. m! `
False negative error, 假阴性错误! X' k0 h6 T d* V% _7 q1 U
Family of distributions, 分布族! A" E/ Z9 E/ [! H- X7 z6 A) e
Family of estimators, 估计量族
) G; g- A% f2 d/ u) oFanning, 扇面
6 [% z% X. l' r5 z; e/ p, E. _4 \& UFatality rate, 病死率! {7 h6 H; Q* o8 L4 D6 B
Field investigation, 现场调查
2 i* q9 ^+ [' i% s) j. e: m. pField survey, 现场调查
d" q1 Q: U8 s5 |Finite population, 有限总体" W. K# G- h. m7 q c
Finite-sample, 有限样本
6 q4 K+ O+ X7 k) F( l$ b& tFirst derivative, 一阶导数
$ f# o# F! o1 s% R: UFirst principal component, 第一主成分
0 Y8 O0 D, z1 Q& P: CFirst quartile, 第一四分位数7 A2 n0 `, n$ Z" d8 c$ }3 f4 w
Fisher information, 费雪信息量7 n% e* c7 u, P
Fitted value, 拟合值7 }$ y9 M# M* R# d: m- g
Fitting a curve, 曲线拟合
# T& ~( z+ t4 K& m8 j. A% S- P0 PFixed base, 定基
3 u. U, Z" q% n2 R2 J- ZFluctuation, 随机起伏1 z+ c: A. {+ K( `. Z
Forecast, 预测
( g0 E( V" G/ b7 [5 yFour fold table, 四格表. f& B) @8 ~' L
Fourth, 四分点
/ Z% g/ |8 |, c7 \# iFraction blow, 左侧比率4 ~* N* D% _5 t9 T, [
Fractional error, 相对误差
5 A+ I1 S* [4 [/ v9 |Frequency, 频率
0 s/ K* `% _' g% A4 uFrequency polygon, 频数多边图+ E) Q0 f& I9 w. V _( \& y a W
Frontier point, 界限点
, G) O7 j0 h( q, e! `6 iFunction relationship, 泛函关系
! l* u0 P- P3 f1 ]; p7 bGamma distribution, 伽玛分布
8 y( X% n2 P& W4 y) ]( P' K) VGauss increment, 高斯增量7 Y# y: j M1 Z) Z; s; Z% A" F
Gaussian distribution, 高斯分布/正态分布" }0 `2 m0 O' v% ^% ~$ o8 g
Gauss-Newton increment, 高斯-牛顿增量# ^+ I" T7 t4 b+ ~5 O
General census, 全面普查" U* O! Y% e' ?. s2 |9 K
GENLOG (Generalized liner models), 广义线性模型 8 F. P3 r: o% G
Geometric mean, 几何平均数: ^/ _2 j* ]% R# ?7 t
Gini's mean difference, 基尼均差; b" z0 X- r; ?4 Z% T4 c
GLM (General liner models), 一般线性模型
, }" |1 u* }- G2 B. c! W# hGoodness of fit, 拟和优度/配合度
6 c/ j1 O2 Y; D. TGradient of determinant, 行列式的梯度
. _/ y# r9 u; w1 e' M, p( yGraeco-Latin square, 希腊拉丁方
% f$ C4 z( J2 HGrand mean, 总均值 A6 O) \. U; k6 @
Gross errors, 重大错误 c' G2 W# C) s
Gross-error sensitivity, 大错敏感度
4 ~. |, X, N4 r: i& BGroup averages, 分组平均
4 T, O7 T _; z! _/ \1 PGrouped data, 分组资料2 U) x1 e) w2 U" k
Guessed mean, 假定平均数
2 s; a" Z# ^7 I: c2 C& V5 jHalf-life, 半衰期( {% F8 V P+ i9 z ~
Hampel M-estimators, 汉佩尔M估计量3 A) k# z; ^' K' g0 A8 z& o
Happenstance, 偶然事件7 i$ o# N! k8 d2 q4 e" Y8 k- V
Harmonic mean, 调和均数
, _ \& m. N+ F5 kHazard function, 风险均数
2 c0 M0 p* C& q2 p8 v+ PHazard rate, 风险率
! ]4 \1 q! i6 b( K0 ]. e; \Heading, 标目 % ?6 |& j5 I4 ]7 [$ I
Heavy-tailed distribution, 重尾分布, _" h9 l3 [( `6 ]: l8 S5 N
Hessian array, 海森立体阵
5 y3 G, T8 H; ]# K+ V% ~5 N9 @7 lHeterogeneity, 不同质. Y! [0 Z* X3 T% l7 Z- Z7 K6 Y$ o5 D. M* r
Heterogeneity of variance, 方差不齐
4 }: ^! ~# \6 g4 P4 eHierarchical classification, 组内分组) [6 y% v) a8 q1 [. N c; c
Hierarchical clustering method, 系统聚类法% r% y6 N5 B# N a
High-leverage point, 高杠杆率点; \( A9 o$ c5 R9 H/ ~% s
HILOGLINEAR, 多维列联表的层次对数线性模型
; x. A; K, `- B, W* \9 vHinge, 折叶点
9 H* V: A$ s4 F7 Y( J% UHistogram, 直方图& n% z% s1 i5 F; ?
Historical cohort study, 历史性队列研究
) R8 q* E* r6 b+ ~( JHoles, 空洞
+ }4 Y1 b( e% e8 {+ ]HOMALS, 多重响应分析% a- ]0 ], j% u$ m; i& a
Homogeneity of variance, 方差齐性" m2 @; w* a0 P1 ]! e- f
Homogeneity test, 齐性检验
3 q# Q, u& ?6 g6 U- ]9 v2 |1 a& y+ uHuber M-estimators, 休伯M估计量
# q# f: W+ h- E4 oHyperbola, 双曲线
: f0 j9 ?9 o- }" k) IHypothesis testing, 假设检验. y- c' |4 H/ P- t; [# ?, J
Hypothetical universe, 假设总体
4 h9 Z" P. R |- n `& k2 y' BImpossible event, 不可能事件+ N# N0 r, b3 `/ }
Independence, 独立性5 D5 o0 M, ?, T3 w/ q6 \! @ v$ k
Independent variable, 自变量, m, H- g. M# g% }* }
Index, 指标/指数( g0 u5 |. f% D7 w7 B& g4 {
Indirect standardization, 间接标准化法
4 U. D) i4 C8 Q% M7 hIndividual, 个体
9 V; }! U0 n# u8 P& @! m0 N# xInference band, 推断带
# J# z- h; T" @6 R7 V8 LInfinite population, 无限总体8 e- Z$ d+ j, j" u# L
Infinitely great, 无穷大4 A: z" b& D U9 i( e* Q6 r
Infinitely small, 无穷小5 y9 x+ e% f' T* F! T& Z4 U3 \4 ^
Influence curve, 影响曲线3 O% f" U7 i" Q3 d$ D( [* I- K" V
Information capacity, 信息容量! K+ T) _ N$ V4 g" a8 }
Initial condition, 初始条件
1 r* b8 C+ ]- ^8 s6 \Initial estimate, 初始估计值
. V1 o# K/ T5 S2 P; p; R& O- |Initial level, 最初水平
; p* U% L# X9 G+ j9 kInteraction, 交互作用4 N3 z i% b$ V7 [$ i, y1 W8 j
Interaction terms, 交互作用项
; G. j% Z! k# H6 h+ ZIntercept, 截距: g2 \ Y3 ?7 G# U: C
Interpolation, 内插法
* |7 J6 o( l. q0 ], A1 \8 hInterquartile range, 四分位距+ T0 N# a/ K0 b$ |! n
Interval estimation, 区间估计
$ u" p* M4 U) I; i( p. KIntervals of equal probability, 等概率区间. t2 H/ d. N1 k/ r& F E
Intrinsic curvature, 固有曲率
5 w: \2 V/ `* `, j) FInvariance, 不变性/ i2 E p8 y; k! n
Inverse matrix, 逆矩阵
+ P! q7 u% f iInverse probability, 逆概率
6 A0 Q; {( N9 o! _; n0 PInverse sine transformation, 反正弦变换8 _/ D6 z2 F8 P$ x' q3 N7 I# |0 ?2 h
Iteration, 迭代
H7 t; w3 K' O! ]Jacobian determinant, 雅可比行列式2 Q. G1 |$ P* c1 z' h
Joint distribution function, 分布函数: N) r5 J) r. }, O- k* `
Joint probability, 联合概率, c R0 @ L- w: l+ [! ] X0 b
Joint probability distribution, 联合概率分布
% B# @6 C+ G2 yK means method, 逐步聚类法- G. d9 F/ W: t, s- e
Kaplan-Meier, 评估事件的时间长度
1 I) ^( |% o, Q1 p. t7 \Kaplan-Merier chart, Kaplan-Merier图9 F! h* ^: G7 [: f% d( g
Kendall's rank correlation, Kendall等级相关- w: N* Z7 M0 `* ?, b
Kinetic, 动力学; y/ z4 ]! \0 t1 m4 K3 P5 _
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验: X3 l% {" w; i: r a6 l, |
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 O5 J8 e4 |8 f8 i: Z- E/ m- ], |3 ~
Kurtosis, 峰度: R. N' J/ h( J2 F4 t0 v7 B
Lack of fit, 失拟
' z% ~" |& t( E/ U3 x; WLadder of powers, 幂阶梯6 h1 t% o# n A
Lag, 滞后
7 {9 ~* H1 S% I& }8 SLarge sample, 大样本
: c- ?' b5 S5 [4 E% Y, H7 |Large sample test, 大样本检验
5 R% i$ C" z# v2 R5 h) vLatin square, 拉丁方
1 }, @+ [/ E0 x& o6 `$ RLatin square design, 拉丁方设计! Q3 h. L5 G& q3 n- Y9 [# Z
Leakage, 泄漏
y, d! F3 ~) m# MLeast favorable configuration, 最不利构形
+ D4 Y% c. f. O8 ^+ j% U" A9 dLeast favorable distribution, 最不利分布
0 t2 Q& \2 u- C6 N1 x) HLeast significant difference, 最小显著差法
1 h& }. }1 C9 aLeast square method, 最小二乘法
: q/ _, b# b2 Q. A" l5 zLeast-absolute-residuals estimates, 最小绝对残差估计' I' p+ ~- k. g2 I0 |/ N0 n
Least-absolute-residuals fit, 最小绝对残差拟合
, | O7 @- D7 h) `6 jLeast-absolute-residuals line, 最小绝对残差线9 Z; J( d6 Z4 y
Legend, 图例
& q- c2 m. h5 n$ sL-estimator, L估计量
& O! l2 Q; c6 A' R& \' K% G6 sL-estimator of location, 位置L估计量
" @' D* c8 E0 o9 f9 dL-estimator of scale, 尺度L估计量
/ p7 y2 I4 i3 [9 Q+ K& C2 \; oLevel, 水平% S* U/ r0 O: G7 S% O
Life expectance, 预期期望寿命" U6 h7 V: b, \: j; j" z
Life table, 寿命表
% d! n' D1 O5 M9 T. z* HLife table method, 生命表法5 k! O" F( z4 s J
Light-tailed distribution, 轻尾分布/ A2 R" e S: K- I! U$ f4 m
Likelihood function, 似然函数
$ O! S4 f/ J: N4 L( {Likelihood ratio, 似然比
( b. S$ z6 y9 {# W( M& f) a7 yline graph, 线图
9 U( K& U8 p! S x1 i& }* F3 pLinear correlation, 直线相关
1 }9 g1 c* e7 r. LLinear equation, 线性方程
% v0 B: W+ e Z: g$ S& I4 cLinear programming, 线性规划
: `5 ]$ K/ Q( c3 s) jLinear regression, 直线回归- a3 I! m5 S" m+ B+ L
Linear Regression, 线性回归
- I; `. r) Y; P" A5 \! V8 d4 KLinear trend, 线性趋势2 m+ T% F/ f6 n* B" Q8 h! l- B/ D
Loading, 载荷
4 V. O5 z1 {; \" ~ B# [! YLocation and scale equivariance, 位置尺度同变性
6 [4 J- B9 S) \( N0 R4 [! |' dLocation equivariance, 位置同变性' R5 Y, e8 q/ i X' u3 K# V. |/ c2 u
Location invariance, 位置不变性
R* }0 Z9 ^: h9 Y2 z$ }% k: ]Location scale family, 位置尺度族
. r" H8 R8 x1 X/ Q1 T$ PLog rank test, 时序检验
+ v/ \- I: U$ G7 J) oLogarithmic curve, 对数曲线# A: d$ f' r: z$ ~& d" m
Logarithmic normal distribution, 对数正态分布
+ x+ D* W1 w5 ~" g W( rLogarithmic scale, 对数尺度3 U' z9 X+ g' z0 d @) V& F
Logarithmic transformation, 对数变换# A( i" w% q0 }$ e( e4 r8 j
Logic check, 逻辑检查4 i1 O0 l! g4 r) E& P
Logistic distribution, 逻辑斯特分布4 W8 R7 ?0 [8 }& Z1 @
Logit transformation, Logit转换6 R) E' @, R4 i v& q3 K2 m7 N
LOGLINEAR, 多维列联表通用模型 0 q: c6 ~" R( {5 G2 G$ B1 ?
Lognormal distribution, 对数正态分布: x: j$ l4 W+ P, f+ o+ L, @7 F
Lost function, 损失函数
8 o% `; Y# `: {1 |! iLow correlation, 低度相关
4 t) t: n3 [6 U: q ^Lower limit, 下限
" e/ V- c1 ~6 q& u( n' p! t9 o5 FLowest-attained variance, 最小可达方差, h( x2 j8 ]. a; @/ s) C# l) u
LSD, 最小显著差法的简称
7 F' Z; p ]; G; ]7 \, R* VLurking variable, 潜在变量
- `5 y" K( x0 @9 v4 ]. ?Main effect, 主效应3 k1 p2 n: z! q6 ?
Major heading, 主辞标目/ M* ?/ `2 i0 n) j
Marginal density function, 边缘密度函数
2 s( w q' G" V1 B7 lMarginal probability, 边缘概率+ |& J8 E; b, _3 i
Marginal probability distribution, 边缘概率分布
! r* u, T+ j* D9 T1 v9 K2 vMatched data, 配对资料( `0 ~6 q8 y1 r- v
Matched distribution, 匹配过分布4 O& M% \% D4 r {
Matching of distribution, 分布的匹配) U) i( O# g4 r2 C; R+ b
Matching of transformation, 变换的匹配3 q' c& C+ `1 E1 Z
Mathematical expectation, 数学期望
m) r( i7 j3 {" nMathematical model, 数学模型/ ^/ H/ C2 U) {+ m3 o ]
Maximum L-estimator, 极大极小L 估计量( O' N4 ?2 ~" X. e6 y0 c
Maximum likelihood method, 最大似然法5 i% e# m2 |1 ^
Mean, 均数
# N- b( _, U1 o& j9 A. A3 d& v" kMean squares between groups, 组间均方% C( K% n& {0 f+ k1 u% L0 i O
Mean squares within group, 组内均方
' S5 t/ I% Q$ f7 eMeans (Compare means), 均值-均值比较
# \ `1 w6 u: mMedian, 中位数
( p. Y9 x6 F* v! s2 z8 F( BMedian effective dose, 半数效量9 b! Z2 U b$ }4 Q3 p
Median lethal dose, 半数致死量: z; E- C8 }3 P3 W, L
Median polish, 中位数平滑# f$ u$ m( D/ o# L( C. n
Median test, 中位数检验
5 x: i& ?& b2 W6 [6 MMinimal sufficient statistic, 最小充分统计量
% N0 N" P( z& D4 D7 H! hMinimum distance estimation, 最小距离估计
& }, x5 `/ u6 n" f# }Minimum effective dose, 最小有效量: @! O) @% F8 I( y. I) \9 O9 s& B
Minimum lethal dose, 最小致死量$ t6 |9 Q/ d1 i+ @" C$ F
Minimum variance estimator, 最小方差估计量
/ N i8 L" g: r* {1 Z; d9 z" V4 uMINITAB, 统计软件包
& r* Q; |' C; C& LMinor heading, 宾词标目0 i9 t6 g4 ]# Q8 @ ~
Missing data, 缺失值
% w, j( H' p$ k4 r4 s9 D1 e2 A% UModel specification, 模型的确定
/ c# ?. Y4 C, v5 r% C4 QModeling Statistics , 模型统计& G T. o+ W6 I/ f! R
Models for outliers, 离群值模型: v* ?2 P0 k9 i; x) v1 g
Modifying the model, 模型的修正# H! x- p V1 E- m
Modulus of continuity, 连续性模
% T5 N% q3 Q7 D& ], `/ d, HMorbidity, 发病率
6 ?- M; q1 V' b# a6 q# zMost favorable configuration, 最有利构形
% i- @8 V9 d8 o4 M$ [. YMultidimensional Scaling (ASCAL), 多维尺度/多维标度/ [1 C% ]" e& n& u
Multinomial Logistic Regression , 多项逻辑斯蒂回归3 N6 b4 ]. s. x$ D, f
Multiple comparison, 多重比较5 c- v* S* P7 m7 l
Multiple correlation , 复相关; K& C* n: q( B! j
Multiple covariance, 多元协方差
- c2 x( E G9 ^Multiple linear regression, 多元线性回归
) B' ~7 d" @/ \( u2 D" w9 GMultiple response , 多重选项" L0 a6 o* I2 _
Multiple solutions, 多解6 w3 n3 M+ U" Z$ h3 [' U8 N
Multiplication theorem, 乘法定理
7 z- X. b: h4 T# [2 l- jMultiresponse, 多元响应
5 ^) o H }9 k& ~( y# A- WMulti-stage sampling, 多阶段抽样
/ `1 X( u% F: xMultivariate T distribution, 多元T分布4 E, W+ } }4 W9 u' L
Mutual exclusive, 互不相容
6 ~$ H- n* g$ I7 c! KMutual independence, 互相独立
0 t- t4 |# D- N" g' p6 q- B( pNatural boundary, 自然边界$ {4 x" t$ c( s4 e/ z& t
Natural dead, 自然死亡
4 U% Z& E1 Y7 ]: b- a5 GNatural zero, 自然零) I- l5 H: E% X q/ e: e
Negative correlation, 负相关
. n* i; i3 u! ?Negative linear correlation, 负线性相关
; c: u7 K2 u. [Negatively skewed, 负偏
/ i I3 Q% C9 M7 g7 kNewman-Keuls method, q检验9 z2 o. F1 m u% g) o) m
NK method, q检验
" ?- f, m, S" f4 R; uNo statistical significance, 无统计意义
4 n0 V9 r. m# A4 V/ lNominal variable, 名义变量
! d# Z3 p6 s( j3 ]/ sNonconstancy of variability, 变异的非定常性. |9 L! k: R4 P* F9 s
Nonlinear regression, 非线性相关
" h4 Q- @+ ~; T6 G6 J3 GNonparametric statistics, 非参数统计5 Q- I2 j/ M7 A/ Q6 T
Nonparametric test, 非参数检验
' Q2 p7 o, d* E: T5 k; ~/ D! ENonparametric tests, 非参数检验+ Y# F7 ~, f) f5 Q# K D/ j: @
Normal deviate, 正态离差: C& D$ f- P2 v) E+ U1 z
Normal distribution, 正态分布$ [' J% n9 S. I' P
Normal equation, 正规方程组
& |8 x( b) S! _) \Normal ranges, 正常范围 [$ I! h" @# A% c% b
Normal value, 正常值
! j8 f- m# K8 b8 HNuisance parameter, 多余参数/讨厌参数
0 r, D% T4 g q3 g& n" JNull hypothesis, 无效假设 - n9 B, b& i5 @# N
Numerical variable, 数值变量
8 l) R" p6 F6 }9 pObjective function, 目标函数( W9 Q- D0 l1 o4 {# {+ e0 |
Observation unit, 观察单位( B/ Z- {% s# j1 H0 F
Observed value, 观察值& m& Q. P3 s. N: l0 S
One sided test, 单侧检验: M! X: @ U/ {( f
One-way analysis of variance, 单因素方差分析
8 {( L1 g+ K# J5 l4 oOneway ANOVA , 单因素方差分析; w2 C' j6 U0 ], M
Open sequential trial, 开放型序贯设计
4 u' j$ E! V# uOptrim, 优切尾' M/ Q! t9 K1 F/ {# z8 d
Optrim efficiency, 优切尾效率( q* x" A3 ?% W& _, F/ K% S
Order statistics, 顺序统计量
0 l7 ]8 H) q# }# YOrdered categories, 有序分类* s- ^! X/ |2 c; {
Ordinal logistic regression , 序数逻辑斯蒂回归; |+ c0 c. g" H+ e
Ordinal variable, 有序变量
' V- i; Q. b5 B/ BOrthogonal basis, 正交基 d# J a! Y; J* `1 {
Orthogonal design, 正交试验设计. F3 T: r6 a' G/ M: U. z
Orthogonality conditions, 正交条件5 C/ L" V- c: K$ ^8 f$ Y/ ]3 S {+ y7 E
ORTHOPLAN, 正交设计
" M5 ]& A" W' r+ ]2 l7 xOutlier cutoffs, 离群值截断点
# d Z* q7 V/ j% l5 B+ `Outliers, 极端值) P0 y. h4 v/ [8 m+ S# Q. `* a
OVERALS , 多组变量的非线性正规相关 w5 \% A8 b3 @1 ^3 W% y' f4 C3 {
Overshoot, 迭代过度. c j L8 }6 {* f' t+ ~" S
Paired design, 配对设计
$ n/ u5 _. J4 o6 vPaired sample, 配对样本9 S O0 k# i2 i9 x* A
Pairwise slopes, 成对斜率; | n1 Q; V& ?4 J6 Y
Parabola, 抛物线 \/ o6 g! [; U. [: }5 I5 N
Parallel tests, 平行试验3 A% l4 M7 S, c0 `: G$ C
Parameter, 参数
( o" M+ d! j$ z5 l0 {0 wParametric statistics, 参数统计
; _( O3 R6 x: ?! Z2 u6 K9 LParametric test, 参数检验
( [: n# o- G& Q B0 L3 X7 fPartial correlation, 偏相关
# F( @+ p; i! ^Partial regression, 偏回归
1 u8 _7 N" N0 `* S3 {9 MPartial sorting, 偏排序
. O5 j6 _0 q; M7 n* I% uPartials residuals, 偏残差( i: u! f4 x7 l7 q; c! H
Pattern, 模式- r/ ]) w* C9 `0 {! [9 |) J: \9 V
Pearson curves, 皮尔逊曲线
9 b1 V3 |9 Y2 I+ D8 p0 S- M8 d! MPeeling, 退层+ B. x3 l* T: t- H* H
Percent bar graph, 百分条形图1 ~# h% I" S/ f0 f" D5 @( L' E) N
Percentage, 百分比
* @- e: @, v- B# p9 b# OPercentile, 百分位数
; p' j1 L6 E4 J6 y. Z' ], z1 ]+ vPercentile curves, 百分位曲线
+ s: m0 d+ J, U k0 E! d8 tPeriodicity, 周期性
7 q9 J9 m1 T3 {/ | SPermutation, 排列
" y) [8 R, e I) E2 ?/ q/ FP-estimator, P估计量, t9 Y W/ }- a! Y- [7 Q2 i% A2 n% f
Pie graph, 饼图. m8 }# U# B/ ?4 ? l( L
Pitman estimator, 皮特曼估计量
5 }/ G# `0 _0 tPivot, 枢轴量) U3 Z% s- {+ B
Planar, 平坦, x, _; F4 V! `/ @
Planar assumption, 平面的假设5 s; [4 y6 `$ m$ |
PLANCARDS, 生成试验的计划卡
2 z/ O0 ^" l' M( @# TPoint estimation, 点估计3 F& T, U. ~/ `! J8 u, c- Y8 F
Poisson distribution, 泊松分布* i R/ P _# g5 A9 ^# X6 Q2 k" J
Polishing, 平滑: d1 K- n, i' D! R) O
Polled standard deviation, 合并标准差' g, S U& E/ b# d$ b; k6 g
Polled variance, 合并方差
: c2 v( S! _4 e! S) QPolygon, 多边图
! q( w9 C& s3 F3 lPolynomial, 多项式 B( g. {$ R% F0 Z7 F6 O
Polynomial curve, 多项式曲线$ G" s" i6 t: c0 t" p9 i
Population, 总体5 ?2 H) ?* t+ Q# U4 c
Population attributable risk, 人群归因危险度2 }* y" g) a) Y: G; k- f8 N
Positive correlation, 正相关
' g/ u( j4 C7 _Positively skewed, 正偏
& _* `" N | ?) r4 A: WPosterior distribution, 后验分布
: H; o( J8 v4 A5 Y4 q3 i4 }Power of a test, 检验效能
' S" c- a# S8 K' O; T3 _: OPrecision, 精密度2 Z' n, \8 C/ \( ~+ A
Predicted value, 预测值
3 q) r: h6 R* F+ \" ?: qPreliminary analysis, 预备性分析5 n8 T3 H! G- [. w+ M* o" l1 H1 }
Principal component analysis, 主成分分析
9 X8 s$ f/ j0 W5 @9 R0 ?, [; N0 y. fPrior distribution, 先验分布
$ d$ g% I$ {9 u1 D XPrior probability, 先验概率
+ W9 o) z. U5 D. SProbabilistic model, 概率模型
; D. \& W3 j, p$ g1 p' uprobability, 概率
; ?9 A8 j0 t7 M% s# W5 E2 H! YProbability density, 概率密度, L; ~: Z2 k7 H- v/ l3 f- Y
Product moment, 乘积矩/协方差& B0 Q' }- T" `5 T5 m$ S: f9 g
Profile trace, 截面迹图0 ^. C7 d5 R7 [1 J2 R
Proportion, 比/构成比9 s7 i' g. @/ q& E0 s
Proportion allocation in stratified random sampling, 按比例分层随机抽样
' Q$ P! F' g5 s0 NProportionate, 成比例
7 U- D0 I. [* E7 L6 r$ x( c( YProportionate sub-class numbers, 成比例次级组含量4 W/ j8 B: T: a6 g$ _
Prospective study, 前瞻性调查: X9 Q7 _' j" w6 k7 }8 j( }: {
Proximities, 亲近性
% Q) n+ E7 _ g* p4 \3 ePseudo F test, 近似F检验, i0 U% b$ {) Q1 b) V( [) G
Pseudo model, 近似模型$ M7 W1 S0 p6 S6 j
Pseudosigma, 伪标准差
5 [" a$ J; {1 P, t2 ^( I$ \% qPurposive sampling, 有目的抽样
7 b. x: {6 x# X$ w( s7 MQR decomposition, QR分解$ ]2 g$ g* ]+ Q( X, G& p/ A
Quadratic approximation, 二次近似2 ^3 n. c/ @3 u2 O$ X" g
Qualitative classification, 属性分类
4 ~) a3 e; n) I3 p. v; |Qualitative method, 定性方法
. a3 b+ c+ z @. j' T; o/ cQuantile-quantile plot, 分位数-分位数图/Q-Q图
- X; n4 R) \9 h6 k" t; L- WQuantitative analysis, 定量分析
6 H5 j9 }& x7 ]! }Quartile, 四分位数- J% Q6 [4 y/ p% t% s C% n- A
Quick Cluster, 快速聚类4 `0 X* m. G1 W. @, k3 O6 s
Radix sort, 基数排序
% x% b% r% d# O' Q: B* P0 O+ J9 LRandom allocation, 随机化分组
; z5 P" g! M% SRandom blocks design, 随机区组设计. W; u: D9 ~5 z+ f0 `
Random event, 随机事件
+ r) M; [4 g. y: [$ W ]. NRandomization, 随机化
- |) B* z. v2 X- K" N' hRange, 极差/全距6 l9 l+ O: O- F& m' d( w
Rank correlation, 等级相关
8 K+ L; g/ D8 G' FRank sum test, 秩和检验- h% q8 i$ S1 \/ l) z9 X
Rank test, 秩检验5 s( I. G5 o/ j+ f
Ranked data, 等级资料
+ |1 t, g* I# cRate, 比率+ I Z/ D% L, ]2 m4 l1 W- |4 }7 E
Ratio, 比例
) i& x! r& @( g+ y; |Raw data, 原始资料 d/ s! s+ B+ p7 E
Raw residual, 原始残差
2 k# w7 r1 q. B$ V) c' aRayleigh's test, 雷氏检验
# R+ ~% y/ {, c M; \* d9 LRayleigh's Z, 雷氏Z值 ) H+ }% m0 d8 f5 @3 O' J
Reciprocal, 倒数
1 g2 |* ]- b# d& T& v$ H, ]Reciprocal transformation, 倒数变换3 h. o, l, l4 h/ E
Recording, 记录
- M) m, f( H6 H" M8 ^/ u/ `4 MRedescending estimators, 回降估计量
! |; W! c/ M/ f$ l$ ?- A& L/ UReducing dimensions, 降维
: R3 T; g! r7 U) Y6 U" BRe-expression, 重新表达
2 D+ q1 W L& H/ W% v {" n! ~) V8 pReference set, 标准组
/ R2 G- q& u% K URegion of acceptance, 接受域
( B, C. K$ c: N9 d+ FRegression coefficient, 回归系数
( K. S7 x4 \, `& E# sRegression sum of square, 回归平方和8 W3 B$ e2 w: p
Rejection point, 拒绝点
( Y* w- ~5 G0 @4 j$ [Relative dispersion, 相对离散度
6 t$ O3 f1 U; ?Relative number, 相对数
u6 u$ ?& X# t$ H, fReliability, 可靠性
1 ?$ r/ m7 Q6 I2 n! rReparametrization, 重新设置参数$ y' F) F* G/ M) ~( F: ^
Replication, 重复
+ _. A$ E/ D& hReport Summaries, 报告摘要8 a! @2 V7 w8 o Z, F
Residual sum of square, 剩余平方和0 }* C. _* S& E; X5 B3 B
Resistance, 耐抗性
3 C9 S7 g. x+ i0 |, {Resistant line, 耐抗线
( m+ R' f( ?8 pResistant technique, 耐抗技术8 ?. R3 N" q3 [
R-estimator of location, 位置R估计量. e# \# `* D0 J
R-estimator of scale, 尺度R估计量! F. F( n1 h3 f: {
Retrospective study, 回顾性调查; I, l5 F9 W$ j2 N( z
Ridge trace, 岭迹
7 [ A/ M) U1 L* q3 [' cRidit analysis, Ridit分析
7 V) |. s. f# M: m( f) K( rRotation, 旋转
1 }$ T' A5 ]9 t6 l7 Z4 nRounding, 舍入
4 q7 s \$ A6 D& m8 }6 y0 v" z1 kRow, 行0 R7 d& q* G9 k
Row effects, 行效应5 x: ]6 u( |, O* h, I0 I \- U
Row factor, 行因素
$ ?1 q _9 Y+ i9 x' z+ URXC table, RXC表
2 ~* Q' M$ Q7 K; T6 c% F( V1 mSample, 样本
: W- c Y' S+ ?Sample regression coefficient, 样本回归系数
" m: M# E9 K: A8 D0 PSample size, 样本量/ g: O) L6 h7 e
Sample standard deviation, 样本标准差$ s8 k2 D; } f% p% H' Q
Sampling error, 抽样误差
2 j( f$ M7 D: q% Y) G* u$ ^3 O3 i# W8 bSAS(Statistical analysis system ), SAS统计软件包5 q' N! q4 T9 i8 _% ~" M( h4 \+ v0 ^
Scale, 尺度/量表
/ b3 V. [/ z/ P6 J! P8 t9 L# ?Scatter diagram, 散点图+ ?) Y: Z$ w6 L+ Z( \: }; y9 \1 ?
Schematic plot, 示意图/简图. S, L7 K3 n+ L0 J, m$ z
Score test, 计分检验
. z* S) r/ A+ j' ]% r8 V% B6 p: [Screening, 筛检& d9 @* w4 x2 f+ g. a0 v5 e: k
SEASON, 季节分析
7 D* M! O9 ?1 Z4 q3 k! [' {Second derivative, 二阶导数
5 z q2 d2 P2 Y# NSecond principal component, 第二主成分
* }8 Z* e2 }' i8 K: }/ i& J8 ?SEM (Structural equation modeling), 结构化方程模型 ! b: F6 P# ^, G- ^
Semi-logarithmic graph, 半对数图
) P) n3 O) U, |/ `, t" mSemi-logarithmic paper, 半对数格纸
9 @* g% E( K: n, X( E5 w; q$ k. dSensitivity curve, 敏感度曲线: w$ _& f9 e f$ e! `. J" J! {
Sequential analysis, 贯序分析, x0 I4 z! n; f8 d9 z$ S1 W
Sequential data set, 顺序数据集/ W) o; \+ j' T2 D: I
Sequential design, 贯序设计+ |# U: F8 e$ W6 Y+ L& p8 ^. W& x
Sequential method, 贯序法
6 t" x) Z$ R1 o1 a2 i S S# z1 tSequential test, 贯序检验法( R9 M8 ]4 C& S' O3 _: C$ B
Serial tests, 系列试验8 C2 Z0 f M9 R1 A
Short-cut method, 简捷法 8 a1 ^& b$ q. n% X# ^; @
Sigmoid curve, S形曲线
5 T9 s" B& x& j; p8 o( rSign function, 正负号函数
3 y- Z+ Z K. [ MSign test, 符号检验$ {' M: |4 _/ ]1 {& W
Signed rank, 符号秩
! A/ w G& s" }2 \" TSignificance test, 显著性检验/ h, `8 n1 \+ T1 z" u# }
Significant figure, 有效数字
. M$ a" B, V k1 X5 A- QSimple cluster sampling, 简单整群抽样4 E0 {6 e6 i S0 o; b$ u: H
Simple correlation, 简单相关6 d) k5 f7 m' X* b( L+ n) c
Simple random sampling, 简单随机抽样# }) {1 ~4 O0 m: x0 ?
Simple regression, 简单回归
. ^- \) O; c, a# }simple table, 简单表
( V! z4 t1 ?1 G& `: DSine estimator, 正弦估计量
' q" l6 C7 r% M% sSingle-valued estimate, 单值估计
5 N1 @+ m. Z* PSingular matrix, 奇异矩阵9 c, y6 h% H( V0 h% @
Skewed distribution, 偏斜分布/ g& e- a$ h2 E& e- I
Skewness, 偏度
+ h: F/ k5 L0 V. I6 D: MSlash distribution, 斜线分布
2 F1 z$ b' r* l4 eSlope, 斜率
8 X3 y1 Z5 I! O: a8 G) b! tSmirnov test, 斯米尔诺夫检验& A* [ R& [$ ~6 t$ U1 U
Source of variation, 变异来源
6 B' a7 v% y" H# o3 a& M( qSpearman rank correlation, 斯皮尔曼等级相关) e8 P" p# Q7 p; u5 l" c$ z
Specific factor, 特殊因子/ m0 k; l5 w `" b, X8 Y
Specific factor variance, 特殊因子方差
( E) Z1 ~( O! _Spectra , 频谱
' x D+ t o9 i. i4 NSpherical distribution, 球型正态分布
0 J& N# G7 p9 U8 N3 a1 bSpread, 展布
6 ]: f( v# u& h- y/ k! \SPSS(Statistical package for the social science), SPSS统计软件包( l- ]( Q0 K9 Z" V$ s3 z& E- J" c
Spurious correlation, 假性相关# o$ D7 x+ W$ H9 m, k# j
Square root transformation, 平方根变换# O* Q3 o/ E2 f6 x& a( S
Stabilizing variance, 稳定方差
9 P9 R) Q1 Q, K% z6 z; e# }Standard deviation, 标准差3 Y" o' J1 M+ m* q- y- t! G8 M
Standard error, 标准误: s# H( u6 N" X) o8 @4 x6 V. _
Standard error of difference, 差别的标准误& W: W& [$ v* A+ [
Standard error of estimate, 标准估计误差4 C, F- h& y$ N
Standard error of rate, 率的标准误
c' }! B/ D* S1 P. g$ C- FStandard normal distribution, 标准正态分布
3 f3 n4 E E( [0 UStandardization, 标准化8 ]( Z8 y4 d$ W
Starting value, 起始值4 E+ Y3 i' a/ V& W
Statistic, 统计量
0 I& K/ s( x; F+ Q7 tStatistical control, 统计控制
4 D. G- W6 P: EStatistical graph, 统计图$ ^) w) I# y( L' ?
Statistical inference, 统计推断/ v I1 R( B: ~/ s- H4 E( k8 q
Statistical table, 统计表% L" {4 x% |, F+ l3 L+ h7 _
Steepest descent, 最速下降法) q& ^5 {; T* X" d$ r
Stem and leaf display, 茎叶图
9 `5 D* h6 A- ?8 b9 EStep factor, 步长因子
# L2 d" z# M; \! p7 m wStepwise regression, 逐步回归
9 K; n2 u7 S$ S7 [; y; wStorage, 存* z+ ]7 J2 P$ d* @5 v
Strata, 层（复数）
8 T+ j; N* T7 h7 ]+ F* |' V) M! ]Stratified sampling, 分层抽样4 Q$ ? y# `* \+ }# Y# `4 Y: U
Stratified sampling, 分层抽样
+ a# D/ N4 V8 UStrength, 强度
7 f/ g2 y/ ^1 m: {' vStringency, 严密性
$ y0 B: @# a ^ x, mStructural relationship, 结构关系, v: D3 i+ @8 j/ Q: U
Studentized residual, 学生化残差/t化残差+ W$ v0 r8 v5 g
Sub-class numbers, 次级组含量6 [( I, R0 {- \4 q* p5 G
Subdividing, 分割
5 M) Q [7 Q, s; N/ vSufficient statistic, 充分统计量" n& M% A6 S p" w" Y7 r' w
Sum of products, 积和
9 x6 k0 f8 O5 O+ v1 A- {* fSum of squares, 离差平方和' E! g+ c. m2 b
Sum of squares about regression, 回归平方和5 O; A' B+ J1 \! T
Sum of squares between groups, 组间平方和! K; l+ t2 A$ X5 M
Sum of squares of partial regression, 偏回归平方和# ~& `+ t0 T) b$ h
Sure event, 必然事件
9 O8 N! e& v. DSurvey, 调查
, r. ^4 \ }" ]' [* }Survival, 生存分析
7 |2 [2 p1 H/ vSurvival rate, 生存率4 Q& F: e& b! {" L# u6 S9 C
Suspended root gram, 悬吊根图
3 r3 j% q$ k, jSymmetry, 对称
4 Q; n) K6 W3 j6 {Systematic error, 系统误差
! t% q1 N' p2 zSystematic sampling, 系统抽样
- {8 Y4 Y: ]: CTags, 标签* P9 ~$ m! q# P+ l8 Z; B
Tail area, 尾部面积
* b% R. O% @- ^, _$ K* zTail length, 尾长
) m/ @# Y* G l7 B& }! [4 |Tail weight, 尾重
: ]/ ]; ~5 x1 k; h7 lTangent line, 切线1 y$ {$ x) ?4 \$ u- y
Target distribution, 目标分布
, A( e( {: |0 h$ k; q, kTaylor series, 泰勒级数
! x3 h+ `( H- \- \. VTendency of dispersion, 离散趋势5 P% m5 q+ G5 V9 q5 s' r$ {# l
Testing of hypotheses, 假设检验
0 S+ H( j% A) V7 u7 yTheoretical frequency, 理论频数
% o! | [9 P& |Time series, 时间序列9 ^* G5 P1 ]5 W; O- X7 u
Tolerance interval, 容忍区间3 ~' n5 l* z9 M2 u; Z/ [% |- \
Tolerance lower limit, 容忍下限# X+ Q$ @2 H/ r6 a! E
Tolerance upper limit, 容忍上限
, J3 s6 ^8 Z$ A7 w4 P- {Torsion, 扰率( A. a G e" T4 Y( @
Total sum of square, 总平方和+ h/ q9 u# q+ }+ I
Total variation, 总变异
+ U- W. i8 @2 |% C0 yTransformation, 转换; r0 E* C. `. Z: l/ ~* B
Treatment, 处理; l4 B0 O0 u- p0 g6 r* k
Trend, 趋势& ]: K) I1 y; \; w, |
Trend of percentage, 百分比趋势+ ] c& J1 B4 e# M' G
Trial, 试验 H) g$ @- b, x' e
Trial and error method, 试错法2 `5 I8 o) F/ I- u4 u- v5 N
Tuning constant, 细调常数. @" i' J8 g9 P2 N* g
Two sided test, 双向检验/ e, P. W2 f4 h: v- \ u9 X" z
Two-stage least squares, 二阶最小平方
6 [+ h0 V: r6 A% }5 n: m8 P' VTwo-stage sampling, 二阶段抽样3 S3 w' B( J9 {8 g/ A, v! N% P
Two-tailed test, 双侧检验
, d* p, N" m' j% b6 tTwo-way analysis of variance, 双因素方差分析1 h7 w) f; P4 z& {5 ]/ \
Two-way table, 双向表
4 a& u4 @9 |9 N9 {2 C pType I error, 一类错误/α错误
3 X) p1 D, u- C7 SType II error, 二类错误/β错误 F, N& f: s. z* G3 e/ K7 w9 `
UMVU, 方差一致最小无偏估计简称2 t o7 E& a; H9 _
Unbiased estimate, 无偏估计0 {/ I" Q" B x* T/ i
Unconstrained nonlinear regression , 无约束非线性回归
2 L0 t# ]: m/ _0 ~8 ]/ TUnequal subclass number, 不等次级组含量5 x/ G% b( d# j- N" g7 r4 n
Ungrouped data, 不分组资料
# x( ^9 q/ U% s$ ?5 uUniform coordinate, 均匀坐标
) V* k m7 G9 S' J5 tUniform distribution, 均匀分布
+ s! I( q+ m! W2 s# h2 JUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
+ \& y7 {+ ^7 N/ c8 ]Unit, 单元
7 G1 u$ o. d/ x- v& P$ ~Unordered categories, 无序分类
0 N/ x4 W2 \5 S& b0 y+ xUpper limit, 上限
3 Z# n% z! ]8 L' ^6 EUpward rank, 升秩
2 w L9 P; r* H* [ qVague concept, 模糊概念+ S3 P. \( S* p' h9 u
Validity, 有效性
- F! d7 v- L! d& b0 [: @8 b B9 kVARCOMP (Variance component estimation), 方差元素估计" o8 t# G% |6 N4 u2 u
Variability, 变异性
" A% B, J/ u) v9 FVariable, 变量
W# T* h' n: \. B# ]6 {: K! _* _Variance, 方差
: u4 ]) y7 P3 QVariation, 变异( b X2 x# E% {9 U
Varimax orthogonal rotation, 方差最大正交旋转
# c( L5 o1 r) e) IVolume of distribution, 容积
9 y9 W- i. |" ?! P& YW test, W检验- Q& K" | k6 H: h2 e& s3 e+ O, ~
Weibull distribution, 威布尔分布
8 B) g0 ]% P7 ~- s/ U5 ]: k7 fWeight, 权数5 h9 w2 k0 g! Q/ Q5 Z+ B
Weighted Chi-square test, 加权卡方检验/Cochran检验
h$ G& P8 {5 k% H1 F& u/ M9 f2 dWeighted linear regression method, 加权直线回归; I- }7 w) F8 e2 \4 W
Weighted mean, 加权平均数" u8 ~& Q1 Q5 T' X6 u
Weighted mean square, 加权平均方差
8 O" V3 g$ L, _9 D A5 }Weighted sum of square, 加权平方和
H2 f. x; q' a! ~3 [Weighting coefficient, 权重系数
5 g) ^0 w( m7 ?9 ?, S0 `Weighting method, 加权法
y7 [9 b7 T$ X# t5 _W-estimation, W估计量, a; h% P& q+ I. T4 y# Q
W-estimation of location, 位置W估计量! w& l. I0 [; W7 |0 K5 K
Width, 宽度
; j3 i x" ~* y6 y2 P* ~! ?Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
- s$ L# Q5 v& rWild point, 野点/狂点: s" f: ?7 y2 |& y6 z
Wild value, 野值/狂值6 p3 J B- v% s5 t7 ?
Winsorized mean, 缩尾均值5 b. C* g* g W1 a7 F( O! M w6 D
Withdraw, 失访 8 N& d' H6 U5 x" T- g9 C
Youden's index, 尤登指数& y5 q$ g$ y5 v1 @; h
Z test, Z检验5 L' K7 `- h2 A B s" e$ Q8 r# o
Zero correlation, 零相关/ S/ |' d" K1 m0 e
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
