|
|
Absolute deviation, 绝对离差
, {5 K: o' B2 Q* n' SAbsolute number, 绝对数6 \+ z. R5 |& W
Absolute residuals, 绝对残差
# M! `0 N3 O+ b) x/ H) l7 I. SAcceleration array, 加速度立体阵
+ B, c% d: Y% G* L2 W; |3 E& ~Acceleration in an arbitrary direction, 任意方向上的加速度
) g3 u& S6 U; [$ F8 Z) RAcceleration normal, 法向加速度
' u4 i) H% H0 q/ S0 U2 B1 [& [Acceleration space dimension, 加速度空间的维数
, f4 D& g- g* ]( R b. z; T, q) cAcceleration tangential, 切向加速度$ @9 f9 P5 J, Y2 f v2 S5 F9 X9 f
Acceleration vector, 加速度向量2 g. C; d7 m u1 J) o9 a
Acceptable hypothesis, 可接受假设
1 l3 g3 L, i) B* W1 VAccumulation, 累积
\; m! z$ a' h+ bAccuracy, 准确度
# u) U" S# E' `; KActual frequency, 实际频数/ N1 r5 b: t; c, D$ O9 ~
Adaptive estimator, 自适应估计量1 n+ O: ]' q" @! i5 {5 j. a
Addition, 相加
* O! [: X, |& e% c+ i% ?Addition theorem, 加法定理
% Z% u X6 E6 \+ Q* h8 }Additivity, 可加性
4 ^% J) b4 i8 y: ^Adjusted rate, 调整率% F6 _5 }) X8 ]4 R+ U, [/ t
Adjusted value, 校正值& W6 F0 Y' c9 T) ?8 k" p
Admissible error, 容许误差' e' F. b) R" U- U% \
Aggregation, 聚集性
( H3 d5 E8 n# K" O& j! FAlternative hypothesis, 备择假设
4 \. i0 H( `3 z" ^0 }* v8 i- b- I4 QAmong groups, 组间
; R( n+ |) d: c% mAmounts, 总量0 v( b }% p9 O2 @! y7 _
Analysis of correlation, 相关分析, l% S$ q. d" N! q$ `
Analysis of covariance, 协方差分析6 H! ^2 A0 |2 q, r
Analysis of regression, 回归分析
; U- o) F+ r1 l) Z4 R7 u% sAnalysis of time series, 时间序列分析! c/ q( q) f9 z' g' r
Analysis of variance, 方差分析
+ T( Z8 Z% w) w7 T/ kAngular transformation, 角转换5 s/ i. F% y! a
ANOVA （analysis of variance）, 方差分析
& X& Z. G8 S0 D; zANOVA Models, 方差分析模型
- r8 c: e! u* A/ o7 b# c+ FArcing, 弧/弧旋
% p a0 I# t0 g! `8 \! I7 }0 y# dArcsine transformation, 反正弦变换# V3 S# p; u" f2 |2 U
Area under the curve, 曲线面积
`# O' x, s% c7 b) s8 J) IAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ; a$ `) K" r6 _9 |6 w3 D
ARIMA, 季节和非季节性单变量模型的极大似然估计
5 z0 J) [$ g4 EArithmetic grid paper, 算术格纸$ o! d+ C+ }& x- A1 _. F5 n- @4 A
Arithmetic mean, 算术平均数
3 X# Z! {6 }; s( o7 rArrhenius relation, 艾恩尼斯关系4 ~% X O+ t- N+ R7 R0 ? u0 h
Assessing fit, 拟合的评估
3 N! C0 A1 |# F1 R: P ^) S" iAssociative laws, 结合律$ x) j( F( O' x
Asymmetric distribution, 非对称分布
" n+ O: F6 f% [( i$ ]) C9 QAsymptotic bias, 渐近偏倚
; V9 w0 r( I- D3 \! q( U- t7 E: rAsymptotic efficiency, 渐近效率
: B( D5 r& }, h! K9 K% n6 _Asymptotic variance, 渐近方差
. j" k1 ]& ?6 DAttributable risk, 归因危险度
; E* Q9 q9 O! u. ]2 N xAttribute data, 属性资料! A" ]( A+ o& i0 P( Z7 p# N
Attribution, 属性
- a. u/ B1 w5 P+ v, m+ Q5 `9 J& NAutocorrelation, 自相关
d$ d/ a$ u) u/ v6 ]& dAutocorrelation of residuals, 残差的自相关
D5 ?, j% D" Z& O1 WAverage, 平均数
* Y% L6 G+ L# jAverage confidence interval length, 平均置信区间长度9 ^& a. [) G/ T: g( n- Q) u! v
Average growth rate, 平均增长率* u, D$ e f' y1 o
Bar chart, 条形图0 T @9 e! `2 X, D. _
Bar graph, 条形图% G; Z% e X2 E
Base period, 基期
?& w2 G* N, |) z' HBayes' theorem , Bayes定理( n5 [) z. }2 w3 D( B% U
Bell-shaped curve, 钟形曲线9 s' C8 y1 U C7 m4 `# Y
Bernoulli distribution, 伯努力分布
3 d' c9 F% B7 p1 q, \9 }- WBest-trim estimator, 最好切尾估计量
! |8 n1 b3 |8 y0 v2 H. JBias, 偏性: L1 X! q' z- l! e- ?5 T
Binary logistic regression, 二元逻辑斯蒂回归
; L$ H& V$ ? _; l8 PBinomial distribution, 二项分布+ A1 T: n) c4 J: G: p
Bisquare, 双平方9 h9 x% B B3 v& l9 T% w
Bivariate Correlate, 二变量相关
' ~( i5 ~( I$ l3 I* s' w5 `# t+ PBivariate normal distribution, 双变量正态分布( w% h% w0 A9 x7 @" z
Bivariate normal population, 双变量正态总体
$ n7 _ Y- K r g% t6 e' M, EBiweight interval, 双权区间
9 e! z b% [: c9 ^5 eBiweight M-estimator, 双权M估计量% e# Z( c5 J4 m% B* n4 p0 S
Block, 区组/配伍组
7 H8 t4 t, L- j* B( @) X {BMDP(Biomedical computer programs), BMDP统计软件包- n+ @) O/ R9 ]
Boxplots, 箱线图/箱尾图' \* _& n1 `5 x3 \/ Q
Breakdown bound, 崩溃界/崩溃点9 ]% |3 _* e5 G# S# E# Y) P
Canonical correlation, 典型相关
+ {' a4 D Z5 T- x1 lCaption, 纵标目- b3 _: m& g, `0 o+ {# i
Case-control study, 病例对照研究. P7 Z' }: |8 @% p/ q
Categorical variable, 分类变量 w# z. C* W* s7 c# L
Catenary, 悬链线/ V. s* Y) _$ Z* b- Z1 ]) A
Cauchy distribution, 柯西分布
9 D$ a% p1 j& f# lCause-and-effect relationship, 因果关系
3 H* h" l- T1 w; T W4 D" r2 DCell, 单元0 |; X* O; |' X
Censoring, 终检) x1 v8 i) t* K* R8 w9 p; s
Center of symmetry, 对称中心; @6 h: g1 Z4 G. C4 B2 T3 Y1 u
Centering and scaling, 中心化和定标
# U3 S; m8 J( jCentral tendency, 集中趋势
# \: i' ?1 N2 y. ^7 PCentral value, 中心值1 P# j4 I/ H% h& a2 Y) r
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测, I# H' ?) ?* T0 y$ \4 D6 `' c
Chance, 机遇) K, n; @. R8 r( K+ L+ x) b7 O
Chance error, 随机误差6 D# O+ k* l, _4 s0 V: u1 K, q' L
Chance variable, 随机变量0 @2 i& l! a3 n) `$ }
Characteristic equation, 特征方程; u# _, i0 O; _. n# D* A
Characteristic root, 特征根8 E3 K' n9 ]+ L }2 ~
Characteristic vector, 特征向量
# a9 o' c1 j3 c0 X) KChebshev criterion of fit, 拟合的切比雪夫准则
" }0 H; x. P1 i0 ^6 \& vChernoff faces, 切尔诺夫脸谱图. {+ p4 r. w5 {0 D8 E
Chi-square test, 卡方检验/χ2检验( o- S( L1 E2 l+ G
Choleskey decomposition, 乔洛斯基分解; ~, C! \7 O- X* K$ g
Circle chart, 圆图
% P) U# g: O# o9 X+ o! `Class interval, 组距
; j `0 R* W$ ]6 i; [4 Q8 yClass mid-value, 组中值+ E; l d; y- V, E
Class upper limit, 组上限+ r* g* s' a' ^2 s0 K! r# o6 ?. w
Classified variable, 分类变量
" @) j R- c8 x3 Q7 ~3 Q3 ^Cluster analysis, 聚类分析
# n! A! y. S3 S! [1 ]Cluster sampling, 整群抽样. x/ @( p: n! f8 {: u8 D8 h
Code, 代码
, O" N1 e" i! j% F8 ~Coded data, 编码数据
3 T; S, b- |5 k! W9 s5 cCoding, 编码
5 a- i. D+ F/ q4 W# p8 O: }! ^3 jCoefficient of contingency, 列联系数
) i0 L2 Q7 g3 j8 A0 @' aCoefficient of determination, 决定系数9 L- a# `/ d6 g4 V0 i6 c3 }: M
Coefficient of multiple correlation, 多重相关系数
( ^+ H6 F; D9 ~) Z- G& LCoefficient of partial correlation, 偏相关系数
& T1 @" s& e1 `1 M* rCoefficient of production-moment correlation, 积差相关系数1 M6 W* @- P- u0 _6 @
Coefficient of rank correlation, 等级相关系数2 m) d$ ^. z/ {1 ?2 s X \
Coefficient of regression, 回归系数; A6 @4 ~5 ?( a4 O9 Q6 _; W# u
Coefficient of skewness, 偏度系数
P: F( F/ {: S1 S! h5 bCoefficient of variation, 变异系数4 K8 e2 N) n$ T+ N& n
Cohort study, 队列研究3 a6 c$ `; ^: O7 N. m" J# `2 T7 w* J2 o
Column, 列6 T+ F g: W) v* I
Column effect, 列效应
K: F2 @9 L5 n, I( wColumn factor, 列因素
8 F# g9 G7 K0 j( R# D5 L% U! _/ VCombination pool, 合并8 t2 Z: @2 j9 o. x: I
Combinative table, 组合表6 x6 c k$ O. m% B. }9 T. |
Common factor, 共性因子9 P2 C' }( A- ?" i" a0 V
Common regression coefficient, 公共回归系数5 v2 P7 S1 V& m1 b0 N
Common value, 共同值+ V$ s$ H+ g5 v& b
Common variance, 公共方差0 ~! R/ X. c! W
Common variation, 公共变异! a# P; u* l+ y" L
Communality variance, 共性方差9 s+ A0 Y1 E, b4 M
Comparability, 可比性. r, N$ T* ?; F1 s# D3 \; N; n
Comparison of bathes, 批比较% P+ g8 l! s/ W, A# u
Comparison value, 比较值5 z* \' B8 E8 W# E$ R7 V
Compartment model, 分部模型* h8 @8 E+ I2 D/ z" |
Compassion, 伸缩
, c! e+ `* ^7 @Complement of an event, 补事件
& O( J# z. O5 e. lComplete association, 完全正相关1 x. S. y/ U! n W* d% X$ `! j
Complete dissociation, 完全不相关5 n s% D- ?% K% r+ f8 T
Complete statistics, 完备统计量
, D; Z5 n2 T$ h: D% Q* `Completely randomized design, 完全随机化设计6 f; L1 m+ Q) y' @0 V' f- K4 T$ I
Composite event, 联合事件
], W* l* z3 h$ g% dComposite events, 复合事件
O w: c/ @* }, F* ~5 V$ c, eConcavity, 凹性) t& Q' `* `4 K9 Q, v+ A a
Conditional expectation, 条件期望0 D. u9 t8 T$ I
Conditional likelihood, 条件似然0 U: P; Q* I! U1 c
Conditional probability, 条件概率
H4 S5 u3 Z- _: mConditionally linear, 依条件线性
9 s0 w# m* z& H, JConfidence interval, 置信区间
& r' a& ?2 a' l0 G) EConfidence limit, 置信限
2 t- h- Q4 ^1 r% ~- [! |Confidence lower limit, 置信下限! u6 V e$ \; }# Y
Confidence upper limit, 置信上限
6 E+ l/ L. @1 uConfirmatory Factor Analysis , 验证性因子分析
9 P/ d" ^/ g' K1 H7 YConfirmatory research, 证实性实验研究
- Q( N1 O$ [" AConfounding factor, 混杂因素4 U( p; P: @, `9 w* u- O
Conjoint, 联合分析
9 M/ |1 I9 t. D, e% ?/ XConsistency, 相合性
# ^( P- D# \3 B6 K) @Consistency check, 一致性检验! K0 \) J% N/ R" M7 E( P" b h
Consistent asymptotically normal estimate, 相合渐近正态估计
6 U: k; P' Z! p4 w( a6 iConsistent estimate, 相合估计
9 K& r# c O4 L1 N( h0 MConstrained nonlinear regression, 受约束非线性回归
9 U/ |! H& [) t# ~" H5 p' U3 D) VConstraint, 约束
7 c3 T% F Y. [- l DContaminated distribution, 污染分布
' k! g- ?+ T) t- z) M9 \Contaminated Gausssian, 污染高斯分布; _1 O3 o3 T, X- ` y
Contaminated normal distribution, 污染正态分布
& x! t2 o2 J" r; K2 PContamination, 污染
2 g* v+ P4 |' sContamination model, 污染模型
! T/ L- w( K$ U- WContingency table, 列联表# G: ^( c5 C0 w+ H7 W
Contour, 边界线, V, T7 w w, a* x) m3 A" T9 V, J/ V
Contribution rate, 贡献率
: ?! r. i: I0 A9 ^- {0 B7 kControl, 对照
4 w6 g& ~8 v$ e. a1 Y5 _( f, WControlled experiments, 对照实验
7 W8 f3 w7 S& G/ ^Conventional depth, 常规深度
# a e) H# j6 F, DConvolution, 卷积
6 d% ~. W2 E# M' J5 D% }Corrected factor, 校正因子/ S/ D: s; X9 Q. I* T
Corrected mean, 校正均值
2 R; Q: x2 Y8 _) h$ R! ZCorrection coefficient, 校正系数
$ \5 B2 `& J' NCorrectness, 正确性
) F* g/ `; H5 V2 p9 ]* h$ pCorrelation coefficient, 相关系数/ y2 ?3 Y$ [0 o) X/ j/ x5 o& Y; _8 k
Correlation index, 相关指数( G! J- b* q& Z" y# c& @6 Z" x
Correspondence, 对应+ G- t" G$ A9 [
Counting, 计数
% v& L* e* t+ ]% {+ b( W& e1 sCounts, 计数/频数
q% ]4 Z6 O& ~- p9 s$ kCovariance, 协方差2 D7 v0 |" [( L- n
Covariant, 共变 4 P6 ]. p7 ~2 X2 T, b& ]2 z4 Q# j
Cox Regression, Cox回归
3 h. _: }# d3 b6 J7 W, ]8 ?" c$ Q0 ICriteria for fitting, 拟合准则
c8 y$ s. g2 z6 HCriteria of least squares, 最小二乘准则/ A+ o/ i9 b+ o4 e- R H/ c
Critical ratio, 临界比
! x2 L8 m+ A0 e# M- E# t1 |Critical region, 拒绝域. E8 B4 ~" t6 o* z$ ]3 \
Critical value, 临界值7 u, R7 |1 z3 g1 }/ @
Cross-over design, 交叉设计2 T3 r- y: r5 Y# k6 i
Cross-section analysis, 横断面分析3 ~. b3 A8 Z D3 @
Cross-section survey, 横断面调查
D; v; z- ?1 L o3 xCrosstabs , 交叉表
0 |6 G1 z' t7 ?( G1 [) BCross-tabulation table, 复合表8 T3 p$ `3 A5 K7 A- o8 e5 u" P
Cube root, 立方根
5 W9 ^; h! J4 w- }) Q9 Q7 |Cumulative distribution function, 分布函数
# ?6 b5 S% P4 w$ @6 E8 kCumulative probability, 累计概率9 b7 Y! u5 Y9 p; ^# m# `
Curvature, 曲率/弯曲
* @3 o) h: X7 A" i- bCurvature, 曲率" ~: c* S4 P$ M$ E- w; K1 c* z
Curve fit , 曲线拟和 " @+ i# c$ [0 G1 @ e' H p. |
Curve fitting, 曲线拟合5 y( T0 N9 ~, O: l) \
Curvilinear regression, 曲线回归2 T. F3 w' Q. L, A
Curvilinear relation, 曲线关系
/ D4 m. I+ U: r, L/ ]Cut-and-try method, 尝试法4 y/ P: j f |: Z
Cycle, 周期1 j+ c; u. n4 c" T3 Z% j8 ~
Cyclist, 周期性
: ?' `9 m3 W/ R7 e$ pD test, D检验8 o8 N& \% W; C. B8 }9 |: }) ~
Data acquisition, 资料收集7 |8 n6 Y" r5 F( N" _9 t! \# S% A( G
Data bank, 数据库7 s. t1 r/ g/ Z3 L+ S0 g
Data capacity, 数据容量
5 \8 S( g1 Y& \% a; p: wData deficiencies, 数据缺乏
5 Y. _3 g" a9 u7 d1 UData handling, 数据处理
& i* F+ z( a3 O4 o' `) A6 RData manipulation, 数据处理
7 Z: F8 ~5 \4 Y' WData processing, 数据处理1 @+ z" v4 b, p; `8 w4 t
Data reduction, 数据缩减
1 @' _, z, F* Y O) ZData set, 数据集
- C2 c' S' ]9 E T2 Z1 HData sources, 数据来源2 {- d& f' y3 Q" p I% ?6 V* I
Data transformation, 数据变换; k# M+ `2 I& B- p- |
Data validity, 数据有效性1 P! T7 J; R5 h, x- u. i5 l; O1 T
Data-in, 数据输入# M9 r7 A/ E3 u1 \3 e5 A
Data-out, 数据输出9 X, J) h+ [; ?0 i4 r
Dead time, 停滞期
: f$ m7 S# x* M- A* u( s% XDegree of freedom, 自由度
6 z& Q$ d: Q0 e$ b* dDegree of precision, 精密度$ E4 | t1 Z8 |/ ]/ a3 e/ K$ W
Degree of reliability, 可靠性程度
/ d! S$ W2 P- cDegression, 递减3 `- I7 l, n9 s6 X0 w
Density function, 密度函数
4 r4 i) S0 j6 P v' ~ b% N' hDensity of data points, 数据点的密度* N" y- P2 }. V6 I& x. C1 ]4 K% t2 s
Dependent variable, 应变量/依变量/因变量
6 B" f, v* ?' U6 E# {8 eDependent variable, 因变量
7 M+ |& m+ B) T1 B& YDepth, 深度
/ [! }! u) C: F; o; oDerivative matrix, 导数矩阵 r. s! q6 h% n5 g/ _$ v/ L
Derivative-free methods, 无导数方法
7 z; B0 C y3 [" I: W* pDesign, 设计5 x) ]' k3 [# e* i7 Q- T" x
Determinacy, 确定性& K& Y- n4 P7 A7 g ]
Determinant, 行列式2 j9 K/ w3 K) ?" Q c: @
Determinant, 决定因素4 M7 c) P* u% c, k- D7 K2 Z
Deviation, 离差1 c+ T* h2 S+ u* x
Deviation from average, 离均差
+ o" [& K5 i% D: j/ nDiagnostic plot, 诊断图5 z- m4 p3 j, Y7 {1 o- E% v
Dichotomous variable, 二分变量4 v1 |8 S/ z) d* ~
Differential equation, 微分方程) `4 l6 X5 q+ |7 |. B' ?
Direct standardization, 直接标准化法
1 C+ H% a0 u* ?0 Y6 ]' x- nDiscrete variable, 离散型变量8 g8 J+ k7 ~4 k, i" |
DISCRIMINANT, 判断 & j4 \8 N+ v/ L7 B8 C* d5 {- w
Discriminant analysis, 判别分析
4 |* N, I# ~. ^) r; R" Y$ dDiscriminant coefficient, 判别系数
5 l$ O- f, h S) BDiscriminant function, 判别值
$ H7 x/ r# n/ N6 Y" N/ T9 ODispersion, 散布/分散度
2 K2 N. ~- k ^. Y. v0 Q/ l3 \7 EDisproportional, 不成比例的/ T A. t9 Q: K7 {. [9 v
Disproportionate sub-class numbers, 不成比例次级组含量
$ G9 t8 l5 K/ e7 ODistribution free, 分布无关性/免分布
5 d1 _1 Y0 s& N. eDistribution shape, 分布形状
8 q% x5 p; ^4 tDistribution-free method, 任意分布法
) g: D: V$ {- E; X3 lDistributive laws, 分配律! ^; q9 z o( R! m! a8 h5 u
Disturbance, 随机扰动项
# G& V# |* j) l# [Dose response curve, 剂量反应曲线, ]- x% D- n0 n2 e
Double blind method, 双盲法: y6 w2 L. O* e2 m" q5 ?6 T# r9 k
Double blind trial, 双盲试验9 ~! S" q( b, x/ S7 I5 A7 O
Double exponential distribution, 双指数分布( f# z% e; s4 [4 H6 z2 m: _9 {/ ^
Double logarithmic, 双对数: L \1 T- J- L' i' m1 D9 x6 n
Downward rank, 降秩' b ^5 W" B* B
Dual-space plot, 对偶空间图- k) \3 o+ W5 u0 n# e& w
DUD, 无导数方法
+ s* T+ ~% A* d0 ~/ n: hDuncan's new multiple range method, 新复极差法/Duncan新法
5 P) |) b& _# S9 b; p8 `* J' W- ZEffect, 实验效应
5 d# Y3 v A0 ~, o# OEigenvalue, 特征值( @; y8 e* W7 P# P
Eigenvector, 特征向量; m5 |1 X& E, e9 B3 q4 N
Ellipse, 椭圆
+ K9 G* v: M# w3 iEmpirical distribution, 经验分布; ]6 \# i$ V- t% f1 c
Empirical probability, 经验概率单位' n% H4 r2 |% }/ Z
Enumeration data, 计数资料9 h2 g) B1 A7 A& p2 r3 g9 y, C; e: h
Equal sun-class number, 相等次级组含量
4 Y5 }( x" ~9 w7 DEqually likely, 等可能
9 r! W/ @ g7 I' N4 A; Y5 \Equivariance, 同变性/ c/ r1 C# G& e7 w0 @: p# n# g% g
Error, 误差/错误
! p* F& e. g" v; U1 I) KError of estimate, 估计误差
. W! a- s* f* c" X6 |Error type I, 第一类错误1 [; S7 |0 r2 j* ^! R( f
Error type II, 第二类错误
! m( Y" y4 X/ s' DEstimand, 被估量
8 f+ a' U% }, xEstimated error mean squares, 估计误差均方
: ~; T& |0 B! B% GEstimated error sum of squares, 估计误差平方和
. m# q, I7 b* TEuclidean distance, 欧式距离
. s; I( o/ p3 `6 ]2 m* r: zEvent, 事件0 Q% d: a1 Q4 \3 ]7 n2 h6 m
Event, 事件1 _* ]- B% H* a+ E3 ^) ?: o: R
Exceptional data point, 异常数据点
' m9 }' m: `0 ~0 m) iExpectation plane, 期望平面" d" S6 @1 j# W: p% _
Expectation surface, 期望曲面( g/ ?/ s7 ^+ I/ O# r
Expected values, 期望值# K& o! F E( V3 G+ J) z) I7 A/ l
Experiment, 实验- Q; q2 y5 X8 P# v5 W# A9 L
Experimental sampling, 试验抽样% \2 Z8 @$ X2 C R2 A* R
Experimental unit, 试验单位3 B; m% @+ A8 y U# M. O% k' T0 \0 e
Explanatory variable, 说明变量( k" Q* U+ S; V. U
Exploratory data analysis, 探索性数据分析
7 h3 ~4 g2 e8 U0 o8 zExplore Summarize, 探索-摘要
( h# c, K3 ], h; f4 |! X0 w9 MExponential curve, 指数曲线/ n% @2 N9 D8 W; F$ {8 w0 C
Exponential growth, 指数式增长% y. R1 f, t. }6 T" s8 `; h
EXSMOOTH, 指数平滑方法
% c* W- V+ Y" M5 VExtended fit, 扩充拟合
$ ~ l* T6 `0 ]0 YExtra parameter, 附加参数
( {0 V. ^8 S2 n2 P8 c1 R1 NExtrapolation, 外推法1 v3 j, }: @; D2 q! \" M
Extreme observation, 末端观测值# T. h* a' g: Y) s
Extremes, 极端值/极值2 Y' |# G6 ^! @. [& g: A
F distribution, F分布
8 ]0 f) o4 S0 s5 F5 S* W/ \F test, F检验
; D* E. w7 h4 x- S/ Q% Q TFactor, 因素/因子5 R7 W$ p# A; _: M" ^" T& k' o
Factor analysis, 因子分析) J6 `, E6 I, |( _: F
Factor Analysis, 因子分析
/ J9 y8 S/ N& O+ V3 N% H0 Z$ XFactor score, 因子得分 R" b1 O/ h3 _0 ]' d& J1 g; R
Factorial, 阶乘
( _3 D& s! G7 T; h. |# r6 m- wFactorial design, 析因试验设计5 t( _' Z8 U; o% D. Y4 t
False negative, 假阴性
+ r, V) I$ }: G' V/ i4 F& @" I1 @, sFalse negative error, 假阴性错误, J( e- E) Y& U! I+ I8 A
Family of distributions, 分布族. ]% g! v% m8 G% g4 M0 O, l
Family of estimators, 估计量族
/ ^. A# {5 ~+ \: iFanning, 扇面1 H! z0 L: A q
Fatality rate, 病死率
- `4 m1 p# [6 D+ ^! Q: h9 m1 pField investigation, 现场调查- }* A( k6 ]& A7 e. m. t
Field survey, 现场调查
% L, g# o3 f' Z# I4 ?1 CFinite population, 有限总体
s/ m$ l) `2 y, O pFinite-sample, 有限样本
, K& m/ w9 {% N# }First derivative, 一阶导数
0 N( l/ ]' G: e' N# wFirst principal component, 第一主成分
- n1 i. v- H* C0 XFirst quartile, 第一四分位数
& R, M# z4 t& c# U- ^: MFisher information, 费雪信息量8 @( e/ @ i5 ~4 G" U
Fitted value, 拟合值 [5 j9 x3 d9 y- {7 F
Fitting a curve, 曲线拟合
3 O% C; X" C1 k0 I6 U w7 S( w3 K7 DFixed base, 定基
1 O8 D, z7 J* X9 vFluctuation, 随机起伏( A, }$ X/ F$ _# X
Forecast, 预测' h9 s2 M: b" J
Four fold table, 四格表
4 f/ i. ]7 b" ~6 o& w3 w/ ~. a1 G5 KFourth, 四分点$ a) F' B9 c! n+ L y( h, H
Fraction blow, 左侧比率
' A* v' a5 c2 n5 \Fractional error, 相对误差, q, ?& F, c4 l6 ^& H
Frequency, 频率
' R+ O' R8 r& K( B, H/ D. {2 sFrequency polygon, 频数多边图
- k* U$ C4 X; M, a; a. ~! xFrontier point, 界限点: W- ]/ o" H% _7 i0 j+ v
Function relationship, 泛函关系
, V6 x5 I2 X( u9 {# C- Z9 bGamma distribution, 伽玛分布# t- D4 u7 Z. w$ W2 ~, |8 p
Gauss increment, 高斯增量
/ p* P; _1 O" n7 W$ _Gaussian distribution, 高斯分布/正态分布; J' T& f" _3 p2 c x
Gauss-Newton increment, 高斯-牛顿增量& y6 L2 a% K. C
General census, 全面普查; q* E* `) A8 k: ^; J2 ~, Q7 ?7 F
GENLOG (Generalized liner models), 广义线性模型
) `8 ~0 l8 v# D9 c5 h$ [$ }Geometric mean, 几何平均数
. \& I& ~; X9 zGini's mean difference, 基尼均差
4 t% o. P. P+ ?6 e. C5 GGLM (General liner models), 一般线性模型 H" ~: q, g" L8 g3 d4 y
Goodness of fit, 拟和优度/配合度
& n& U3 m! Q' `! sGradient of determinant, 行列式的梯度0 C2 ]7 w) A* g: [+ I7 V' F
Graeco-Latin square, 希腊拉丁方& y% N5 B2 w- A
Grand mean, 总均值
- q g- R5 T- Q/ jGross errors, 重大错误
: M! M7 S1 G% f5 e' ?) F& L) ]* V3 CGross-error sensitivity, 大错敏感度
- ?( u$ |+ G7 ^) `5 K7 A' M; sGroup averages, 分组平均/ ~( @2 b% b% p( o* D; V9 R0 x
Grouped data, 分组资料6 ~/ p0 A; t& X ~
Guessed mean, 假定平均数
5 O0 Z; X$ M! Y( w6 f3 KHalf-life, 半衰期% r2 U- U# g7 W8 U4 h1 G% |
Hampel M-estimators, 汉佩尔M估计量
2 t' n# [0 E0 q$ G8 Y, X* YHappenstance, 偶然事件, o4 X5 ~( D6 v' F% m1 L
Harmonic mean, 调和均数
4 a) J$ N' F1 J5 C. \Hazard function, 风险均数
$ C9 B" n. @6 I% E+ L3 @+ D, {Hazard rate, 风险率
5 L2 i3 Z& D0 K0 VHeading, 标目
" D- f" T* n% q& Z3 tHeavy-tailed distribution, 重尾分布
7 V. U0 R3 @+ M5 T! Y: G ^1 iHessian array, 海森立体阵
, w) G) F: M# s5 h# ~$ G2 NHeterogeneity, 不同质. A0 _7 ~2 f2 x6 h# o3 h
Heterogeneity of variance, 方差不齐 - b6 F- H: [: u3 T' k' V
Hierarchical classification, 组内分组1 p f# G0 k2 f- N, K9 \6 V L
Hierarchical clustering method, 系统聚类法7 i" N4 m- n$ z0 s5 S1 |
High-leverage point, 高杠杆率点8 b0 L D6 e: l& a. C! I1 C; R
HILOGLINEAR, 多维列联表的层次对数线性模型* B* ] C( _# h9 _( k X1 t
Hinge, 折叶点
/ e: V% I9 ]5 B8 z- hHistogram, 直方图
+ d0 P* Q4 C& k/ J/ T! S: aHistorical cohort study, 历史性队列研究
! G6 ]7 g$ J, {: Z$ P$ _- eHoles, 空洞- K0 \- t( P3 ? ?1 [3 v9 n0 d, y. S
HOMALS, 多重响应分析) {. K. Z2 @: G A
Homogeneity of variance, 方差齐性
& L* {( P D1 [Homogeneity test, 齐性检验% L7 f# u) S V
Huber M-estimators, 休伯M估计量+ d6 Y8 w8 H0 q8 h2 y
Hyperbola, 双曲线- Z8 S& w. ~% v# L/ X* z
Hypothesis testing, 假设检验/ H1 a) E0 J* j
Hypothetical universe, 假设总体
$ B; h- w) \+ C( X! V8 c, OImpossible event, 不可能事件3 s. u$ [/ Z/ M3 n# X ^
Independence, 独立性
+ u$ C% e! b0 eIndependent variable, 自变量+ L# r# [; t! }: F e0 H
Index, 指标/指数
: E4 F8 X- u& T S3 y) }* ~; D- BIndirect standardization, 间接标准化法
6 c" D. {( I7 q& q. GIndividual, 个体% R1 ]! p a, w1 Y
Inference band, 推断带
: [- k* J8 f$ m2 m1 \! LInfinite population, 无限总体- P8 z: y* r) ]1 a' x
Infinitely great, 无穷大% k% l: }7 F7 l, x2 v' g
Infinitely small, 无穷小
?/ P) W' G8 _1 H p, a" Y% cInfluence curve, 影响曲线
/ [* T: P' f) H; K0 ZInformation capacity, 信息容量
7 J0 x/ }, D6 B. XInitial condition, 初始条件9 y$ ]1 E% A4 n. S
Initial estimate, 初始估计值: F' `2 l1 f* z( Y. \# m
Initial level, 最初水平
0 U1 Y/ N+ F: G$ F9 u) WInteraction, 交互作用" V* `' B) ~+ _9 i- n2 R* C: _! h+ D
Interaction terms, 交互作用项: ?4 R& ]# Q5 z. L5 T/ w: Z& ?
Intercept, 截距8 H7 T3 H, a F j& A& E5 G! M8 L. s
Interpolation, 内插法
* y8 q9 {9 I! N A% EInterquartile range, 四分位距
U8 V6 s; }1 k* j& [Interval estimation, 区间估计
, _# ^# }& y# u. M1 \& O2 NIntervals of equal probability, 等概率区间
/ S% z# U$ W' }: T7 aIntrinsic curvature, 固有曲率, {, w, \* k. G" H, Y" d
Invariance, 不变性
$ [: m& k5 o2 q( A* FInverse matrix, 逆矩阵5 M3 \4 d6 T i. q+ U# |, v
Inverse probability, 逆概率
7 H- a6 |0 Q* \# j" y& Z) L, V# a, XInverse sine transformation, 反正弦变换
( a6 {& a- | ^" A" rIteration, 迭代 9 B. C9 a4 d4 F+ C- C- w3 J) x
Jacobian determinant, 雅可比行列式! C( K: K* K& |. {# K7 m; X
Joint distribution function, 分布函数; ~/ j a; N, Z5 k/ j: F7 o8 j
Joint probability, 联合概率3 a: K( O2 M6 u. \: b- y
Joint probability distribution, 联合概率分布9 \5 r% `3 R. r( L' F
K means method, 逐步聚类法# O1 Y0 w- c1 Q( w) \
Kaplan-Meier, 评估事件的时间长度 0 Y; n& @3 Z+ t9 t6 ^% _. I
Kaplan-Merier chart, Kaplan-Merier图: K, T0 }5 ?6 e
Kendall's rank correlation, Kendall等级相关# \/ y: f$ ?1 S1 x# V, Z w
Kinetic, 动力学' N1 H) ^4 b3 d( m6 i/ b
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
2 b2 }7 n/ Y o0 I$ I1 q% HKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验2 N4 z) ]$ }$ z) m
Kurtosis, 峰度
" _& {( s8 R; @8 V$ A+ V+ KLack of fit, 失拟
" h2 | m2 s1 `: \/ L! HLadder of powers, 幂阶梯
/ R9 s% q6 z; ?' N5 p$ f: S( j* ^5 n( xLag, 滞后
; Q' Q0 q) r6 X* K6 s- CLarge sample, 大样本4 E7 i. K' l& z3 W3 U
Large sample test, 大样本检验
' A. h7 j8 k) k1 |' {Latin square, 拉丁方5 F1 d2 T @' F& c, _7 x# D
Latin square design, 拉丁方设计
) b5 w3 l9 L) ]+ @. MLeakage, 泄漏9 O3 f* v9 t- |) I2 q# Q
Least favorable configuration, 最不利构形
3 a& x5 y4 F2 L3 n8 ILeast favorable distribution, 最不利分布
4 ?0 t7 v3 Z7 W$ ^. y, @Least significant difference, 最小显著差法
1 L7 X% h4 h7 l, c9 fLeast square method, 最小二乘法& B! Y+ P6 z2 `9 t. P- `
Least-absolute-residuals estimates, 最小绝对残差估计
6 R' S! ^: [) p6 |- x" xLeast-absolute-residuals fit, 最小绝对残差拟合
8 F' a1 Y: }. F6 \# d9 x7 ?Least-absolute-residuals line, 最小绝对残差线
* ?& l) C8 h; ~. }6 `Legend, 图例
3 C( n! c! t5 z$ DL-estimator, L估计量5 k+ ?9 G6 F3 g; m$ e% k, `
L-estimator of location, 位置L估计量 ]4 V' C% x& R5 V) z, m, @
L-estimator of scale, 尺度L估计量% u; \3 R) `& h+ y
Level, 水平" ^: s2 F2 V& ]8 |2 k+ L' i
Life expectance, 预期期望寿命
# W+ v7 c0 S nLife table, 寿命表
8 c2 a0 y2 U" e+ r: k0 o! YLife table method, 生命表法0 G% o* R% m- t9 d
Light-tailed distribution, 轻尾分布* s5 A# d+ X3 @. p3 M
Likelihood function, 似然函数
+ n9 K8 t/ K1 mLikelihood ratio, 似然比: U" v9 j5 Z s- `
line graph, 线图3 t1 ?0 G* e3 e: k7 O2 L
Linear correlation, 直线相关
' ?7 d P! J0 O" `* O( j" b# T# fLinear equation, 线性方程2 e% G. K1 @. [
Linear programming, 线性规划. h( g) n! x" U5 J; ]5 \3 d
Linear regression, 直线回归
' W0 I- i1 L5 z4 Q( Y, e; X1 h( uLinear Regression, 线性回归
/ W: J: S" }4 B% ^1 pLinear trend, 线性趋势
- }% ]1 ^- @- O T0 V5 cLoading, 载荷
5 M: D$ K$ x' q) R" }" }' Y6 Y$ v/ s0 F2 mLocation and scale equivariance, 位置尺度同变性
- M- v. d* g3 W4 R8 y1 y sLocation equivariance, 位置同变性4 U$ N$ J! i" ?0 w/ t3 q, O0 C, _ t
Location invariance, 位置不变性
7 i: B' o0 H9 @2 i0 U; J) qLocation scale family, 位置尺度族
* d; z9 Z6 Q& [" |Log rank test, 时序检验
6 H% z; R. j( ]' x XLogarithmic curve, 对数曲线
$ O o( K5 d) J( ULogarithmic normal distribution, 对数正态分布- c0 E* {$ _& X
Logarithmic scale, 对数尺度
/ Z$ o* l5 G+ [2 ~( }5 T3 OLogarithmic transformation, 对数变换) w9 p6 _- S. Z" G! D
Logic check, 逻辑检查9 B) u% p0 a5 S8 g* ]
Logistic distribution, 逻辑斯特分布! s" r( N8 \1 V# q" h! c1 Q
Logit transformation, Logit转换0 ]7 k4 o2 R9 c, X$ w7 g4 n( M
LOGLINEAR, 多维列联表通用模型
c6 w0 z. ]4 T8 ~' i6 k( ULognormal distribution, 对数正态分布
6 z ]9 E( Y! j n& N4 q& uLost function, 损失函数4 y" C$ H6 m6 H& }% e; ]6 _
Low correlation, 低度相关, @* a+ U/ ]( k- X/ P# D
Lower limit, 下限
0 ^, K. B" V4 m! r5 H, rLowest-attained variance, 最小可达方差" V& L8 g A! E# T
LSD, 最小显著差法的简称. H+ T4 p+ s* a, m5 J& P I, D9 |: L
Lurking variable, 潜在变量' f: K& y% @8 l0 _4 o: M
Main effect, 主效应
/ W# o/ C' J" d- N+ \' l+ o H% yMajor heading, 主辞标目# k4 q* V$ G h& J
Marginal density function, 边缘密度函数+ L: i/ U6 o7 e8 t- Z Q: Q
Marginal probability, 边缘概率
: z8 t) Y* [. B; N# _& ]1 fMarginal probability distribution, 边缘概率分布4 @8 ]3 G2 A e6 p, b
Matched data, 配对资料
3 ~; l2 x6 Y! ]6 L* y: a# L( bMatched distribution, 匹配过分布! q1 P4 I B& u9 W( `% B& [1 f
Matching of distribution, 分布的匹配6 Y" F& V) X% c( ?) i& Z+ F R
Matching of transformation, 变换的匹配& m. G: `& o% m/ c8 M. F+ _
Mathematical expectation, 数学期望
7 J7 }3 b( O0 X2 SMathematical model, 数学模型
+ m* M I# a& i, Z& ?' P5 d pMaximum L-estimator, 极大极小L 估计量
5 k) R" L, m W2 Z& W! X7 Z7 I# _Maximum likelihood method, 最大似然法
6 i5 c) @1 R! h7 Z6 @0 eMean, 均数& S! b3 [: z! o; w
Mean squares between groups, 组间均方
3 t3 ?1 L) c0 u" W1 D6 {) wMean squares within group, 组内均方
3 I8 f4 O" H/ r, ^Means (Compare means), 均值-均值比较
( M8 W) ]+ G8 a8 U( }Median, 中位数
2 C7 J' I9 `+ ~: A( BMedian effective dose, 半数效量$ F* U1 X) n# O# z0 H
Median lethal dose, 半数致死量
& Q a8 B. b% R& y2 TMedian polish, 中位数平滑
@9 f8 `+ X# g) gMedian test, 中位数检验4 i8 e j+ m( r% l4 _! J7 i$ \
Minimal sufficient statistic, 最小充分统计量
. U0 q" p" k2 r' t2 A) FMinimum distance estimation, 最小距离估计) Q0 |1 G, l" d1 `; Y" G
Minimum effective dose, 最小有效量; P9 r2 v! n, }: |
Minimum lethal dose, 最小致死量
9 G8 k7 m. ?! ^8 kMinimum variance estimator, 最小方差估计量8 @$ ?! E, z7 w) K0 M8 a' g
MINITAB, 统计软件包# a5 }# ~* P1 Y. j: F
Minor heading, 宾词标目
- K# s& y/ L8 v9 `3 EMissing data, 缺失值6 V+ L0 S/ @, Y, t, A3 y
Model specification, 模型的确定' F% Q. B* M8 U, m/ G& d, Z
Modeling Statistics , 模型统计
! [: }! o; N1 v& U3 {Models for outliers, 离群值模型! E. p$ C& I+ N0 j
Modifying the model, 模型的修正$ q! y0 g7 _; r) z5 y
Modulus of continuity, 连续性模; T& ^0 O [( v+ P' e; q9 l
Morbidity, 发病率
* I* ?) g, ^2 K3 aMost favorable configuration, 最有利构形
0 u/ T7 N- }+ k% Y. G& mMultidimensional Scaling (ASCAL), 多维尺度/多维标度
( [; y; _+ ~( lMultinomial Logistic Regression , 多项逻辑斯蒂回归
2 x9 i# L' u$ s" ]; n. g2 UMultiple comparison, 多重比较
7 Z: R+ E2 A5 [; k, G8 j3 q7 J. QMultiple correlation , 复相关
7 Q! ?9 G" }/ G: T( y" i+ L: HMultiple covariance, 多元协方差4 G' E0 b) d. }: T/ x3 O; h& ^
Multiple linear regression, 多元线性回归
; U$ C# j. \# \( dMultiple response , 多重选项. {3 z: @9 y3 `8 F
Multiple solutions, 多解
/ r' |) _& D; cMultiplication theorem, 乘法定理& B, @% ?- F$ o
Multiresponse, 多元响应
/ E7 @+ s6 ?1 o- n( M$ Z- |1 UMulti-stage sampling, 多阶段抽样
3 s- _8 W2 z0 ]3 M9 z% u& m4 XMultivariate T distribution, 多元T分布% [3 l3 c, Y, w, M6 h: D
Mutual exclusive, 互不相容 w X: E1 ^% V+ U4 p% f
Mutual independence, 互相独立
5 }- Z1 w J, Q" kNatural boundary, 自然边界9 m2 o& B/ \& W. j
Natural dead, 自然死亡
: K I7 i# ?* h4 G9 q1 ]6 h9 dNatural zero, 自然零
$ @2 ?$ z! m) m! I$ q @Negative correlation, 负相关
# v9 L- p' K% p6 jNegative linear correlation, 负线性相关
; L$ h$ D- a8 ], d& Z" mNegatively skewed, 负偏
' b- u- I9 M4 l$ c/ i2 nNewman-Keuls method, q检验- J9 I7 V" \0 C, W$ f
NK method, q检验
2 J5 u+ \/ h k; r9 u7 X3 ^! g3 e$ n+ INo statistical significance, 无统计意义
: A+ L% D5 q! Y% X' z, |/ O2 i+ KNominal variable, 名义变量
. c) P2 R% F, V3 N* a7 _1 C/ dNonconstancy of variability, 变异的非定常性* I) C/ A# B! s, C- v
Nonlinear regression, 非线性相关+ o( w2 D3 q2 Q0 B \
Nonparametric statistics, 非参数统计
: S6 X5 |% W2 ~ ^' qNonparametric test, 非参数检验
/ |" O$ K# O2 C. ?6 QNonparametric tests, 非参数检验9 t+ f( S6 Z5 e' _( L6 O5 Q
Normal deviate, 正态离差9 Q% T* n" ~8 s3 t
Normal distribution, 正态分布
" i- @& ~+ s0 w: i- }5 t# vNormal equation, 正规方程组1 e$ Q. T5 I3 }' k/ B
Normal ranges, 正常范围8 `3 q6 @- W1 ^5 C# n6 w: H/ |' P
Normal value, 正常值( Z& N, i( s! i3 ~
Nuisance parameter, 多余参数/讨厌参数
5 y, s6 Y8 \3 ?2 KNull hypothesis, 无效假设 " v- U8 R3 l: N
Numerical variable, 数值变量9 Z$ |# P( C4 l# E, w
Objective function, 目标函数3 r; {0 q+ m; ^3 G9 s' M' I( N0 l3 g
Observation unit, 观察单位
! P" v& t2 ~% {- R9 ZObserved value, 观察值6 ~! ^! ]' X1 G2 k- k( v
One sided test, 单侧检验% i! h0 \/ t( J3 h J: ^/ M6 O6 T
One-way analysis of variance, 单因素方差分析% _0 D1 L# K% m: Y6 F3 w2 c
Oneway ANOVA , 单因素方差分析
* i: x) j' o" {1 n. |Open sequential trial, 开放型序贯设计
" R, P4 |% L' sOptrim, 优切尾; P' ^. Y. r' e: l3 H- P$ v0 R
Optrim efficiency, 优切尾效率; s) `/ F: S4 T/ ~
Order statistics, 顺序统计量
# o' j! E! l5 C- ^Ordered categories, 有序分类
6 l+ q9 a8 b: dOrdinal logistic regression , 序数逻辑斯蒂回归
4 {3 K' q4 A5 n1 WOrdinal variable, 有序变量7 i& o$ J' F) k) ~' Z
Orthogonal basis, 正交基
6 ~' N$ Q: ]7 X7 ~0 M8 zOrthogonal design, 正交试验设计
6 t5 M4 A& e/ `7 n) N( \/ JOrthogonality conditions, 正交条件/ c# W7 A+ U v
ORTHOPLAN, 正交设计 & ^+ [# W/ y, L2 y5 E! J
Outlier cutoffs, 离群值截断点( J$ _1 Z) b" D( h
Outliers, 极端值4 I: Q- B+ c7 ]8 j) Z
OVERALS , 多组变量的非线性正规相关
) w2 g: G) V7 ^Overshoot, 迭代过度
/ O: m' _, g/ a0 `' x5 @1 S) d( tPaired design, 配对设计
8 u5 k2 |* G" A# n$ U- }Paired sample, 配对样本
0 J! B6 s- S3 n' Y0 {Pairwise slopes, 成对斜率' n; h: V8 G& V' D2 {, N" O
Parabola, 抛物线
9 U6 k! Y8 q# S2 RParallel tests, 平行试验4 a' n& M W3 |: K+ h: ^* ~
Parameter, 参数+ w/ e7 T+ ^: n; O$ m+ N2 v
Parametric statistics, 参数统计) m; |5 x+ o+ K1 | W
Parametric test, 参数检验6 q" s/ j. x4 {1 |
Partial correlation, 偏相关6 k* x- v1 q$ s* _ E- m$ R
Partial regression, 偏回归
: s- |' U) j$ q! t/ @7 e; |Partial sorting, 偏排序3 T7 @- {- I7 f( `/ R
Partials residuals, 偏残差
# z, I$ ~8 r r# u! D3 V) b, DPattern, 模式
. L4 d% f4 j( A: e8 T8 }% nPearson curves, 皮尔逊曲线
8 t3 x7 S0 ~& T, SPeeling, 退层1 `$ r5 U9 x5 t! W/ P( `
Percent bar graph, 百分条形图# I: {# I' ? e6 M
Percentage, 百分比
; g5 U/ `% W$ B2 iPercentile, 百分位数
0 m& H) L8 A1 z, D! a1 wPercentile curves, 百分位曲线
1 i6 |$ B" K5 q! U$ l. |6 e% FPeriodicity, 周期性3 U, X/ `" p- }0 V2 I L8 H! W
Permutation, 排列
* ^9 ]8 n+ {6 Z0 GP-estimator, P估计量
/ h* E3 P% Y: M& m! ?$ _Pie graph, 饼图0 F/ Z2 l# l7 P1 T5 [
Pitman estimator, 皮特曼估计量
+ H9 f6 r% r7 j7 Z b" VPivot, 枢轴量
7 @# [) z* J. c' L4 QPlanar, 平坦 z" ^4 V& X2 b
Planar assumption, 平面的假设+ L! \1 { y1 `6 k3 ?
PLANCARDS, 生成试验的计划卡9 W" H) _+ W5 E8 z/ U" K4 z. a
Point estimation, 点估计( a9 `6 v6 W. G o/ ^
Poisson distribution, 泊松分布
# |8 _ _& B4 _Polishing, 平滑
( a* d" `- `; |( i' p% D9 bPolled standard deviation, 合并标准差: T( P8 m' e/ h& \* b
Polled variance, 合并方差4 [4 H7 S1 e8 i3 @5 Q. i5 U+ N; \6 t0 |
Polygon, 多边图+ J6 {( Q; g$ _0 r! Q
Polynomial, 多项式* x$ A' C2 ?% m% b Z) h
Polynomial curve, 多项式曲线
: N; k% ?2 X7 K, TPopulation, 总体# e+ {8 N8 P0 N. G6 U- G
Population attributable risk, 人群归因危险度
* V2 O, Z$ w" `7 G5 wPositive correlation, 正相关9 ^. [2 s# C1 v
Positively skewed, 正偏
6 Y+ G' l: C& a0 B. F. n/ b6 }- b& s) qPosterior distribution, 后验分布
! W+ u$ K5 y) D2 UPower of a test, 检验效能' W/ k7 C# W! \) W) j
Precision, 精密度
; F/ V; J7 Z Y6 S3 ?- ], V3 BPredicted value, 预测值
' h" c- S; S V% `$ h7 iPreliminary analysis, 预备性分析
2 p* p1 C& m; ^. I1 f: Q7 X- C5 G; APrincipal component analysis, 主成分分析: m# m5 B* r8 Z
Prior distribution, 先验分布. U$ N' M, |" \
Prior probability, 先验概率( N" [5 B, I" c9 Y& p( V0 R
Probabilistic model, 概率模型$ e0 c( J/ R/ X. c9 O3 m5 Z
probability, 概率& u5 {- {: L; \! ~+ M: S* I* c
Probability density, 概率密度: a H4 I$ S1 x Z+ s. [
Product moment, 乘积矩/协方差
$ h+ Y6 d- p$ C2 A' Y% aProfile trace, 截面迹图
& U. i4 j- l/ o( I2 R' ZProportion, 比/构成比- t7 a8 n+ _8 v o
Proportion allocation in stratified random sampling, 按比例分层随机抽样# U' T- J- K& T3 J* v, K2 W
Proportionate, 成比例
2 h+ B T0 T+ G2 _9 v4 f& [ TProportionate sub-class numbers, 成比例次级组含量
4 A- u/ v0 k6 w& v0 m8 @Prospective study, 前瞻性调查3 }( R w* l, y7 _0 ~
Proximities, 亲近性
0 h' J+ b" q6 iPseudo F test, 近似F检验" d4 L* k/ c4 V, F8 v1 H' |9 X0 X
Pseudo model, 近似模型
; M: }1 K/ W, a& I0 b1 NPseudosigma, 伪标准差
. O7 k; f c0 \# S- q& dPurposive sampling, 有目的抽样
0 a1 \: u, G+ `- b* RQR decomposition, QR分解% ~' R5 Y) x3 G& m( t
Quadratic approximation, 二次近似
8 Q6 P0 v+ B4 i( ^Qualitative classification, 属性分类. n1 a% C7 Y' Q0 Q5 Z
Qualitative method, 定性方法
5 e. S+ F2 `6 d; EQuantile-quantile plot, 分位数-分位数图/Q-Q图. _6 F# v H2 t$ u k; l% W
Quantitative analysis, 定量分析
) \+ r# w( V X5 }+ A5 SQuartile, 四分位数
$ |7 Y5 F* l0 y" B" V) a- OQuick Cluster, 快速聚类0 ~+ c* n) ]0 v0 H9 q+ B
Radix sort, 基数排序
. u t; V5 O( {* YRandom allocation, 随机化分组
: a* K0 j+ U$ a l4 K( ?Random blocks design, 随机区组设计
5 ~7 W" y) e* N' S7 URandom event, 随机事件
9 G$ ?7 r0 {+ K( p7 K5 _Randomization, 随机化 g( i+ R" N6 m5 k! L; g( Z" e) `
Range, 极差/全距. g& K' B% {% r' z" g
Rank correlation, 等级相关
, @/ q/ H" C. p8 r& MRank sum test, 秩和检验6 d3 A4 `' ~$ z0 s% m; p* L& x' z5 |
Rank test, 秩检验
# P! C3 R8 s2 [! e. wRanked data, 等级资料
' Z. T6 M0 ~" |# }) B$ a# _Rate, 比率6 Y* D$ c! W0 r9 A
Ratio, 比例. L* r" \5 [- m2 M) C L8 Y
Raw data, 原始资料# k8 k; | M( k
Raw residual, 原始残差
% q, P! Y; G$ E0 D, b; W3 nRayleigh's test, 雷氏检验0 L9 O" x, k2 b; S( ~
Rayleigh's Z, 雷氏Z值 7 j9 x2 U! t0 |: Z) ^ G! }
Reciprocal, 倒数& g! s8 i& J' M7 |# o- F
Reciprocal transformation, 倒数变换
! M/ {" v' C0 L/ ^) { nRecording, 记录
' C# L y' r; vRedescending estimators, 回降估计量
, z2 z1 Y; T$ w3 J# qReducing dimensions, 降维
& E& z: s8 c' I9 p$ iRe-expression, 重新表达
$ b+ w4 H5 N5 Y c4 PReference set, 标准组 A" S8 G& O4 p2 G
Region of acceptance, 接受域
+ u+ t# t. n' z& z9 s; q" zRegression coefficient, 回归系数# E4 ~( N6 y. b8 r9 f( R
Regression sum of square, 回归平方和
. p7 J7 k2 r5 g/ s8 @5 lRejection point, 拒绝点0 V9 G. D, p" T7 y: S7 F) p
Relative dispersion, 相对离散度
& Q, [" [& D9 X# @( t' bRelative number, 相对数
2 @& o" i- a* M2 D, eReliability, 可靠性
8 `6 z6 |7 L' w9 _. [( YReparametrization, 重新设置参数% q: X9 f4 m5 @: g5 G8 u" g
Replication, 重复
$ s4 j, X2 w* E( w* NReport Summaries, 报告摘要& n8 S: V( V' [% ~
Residual sum of square, 剩余平方和
) j5 ^ m/ L4 Q$ s0 j9 E" q2 ]: J KResistance, 耐抗性# H; T+ C* l) w7 C% E
Resistant line, 耐抗线9 x2 n" d$ V4 p4 ^; H% K
Resistant technique, 耐抗技术' t( j+ f% P) Y0 I( h( `! I" b
R-estimator of location, 位置R估计量
J7 H1 y: C) G1 Q" |% bR-estimator of scale, 尺度R估计量
% R( y, d3 X# v& wRetrospective study, 回顾性调查3 H. P$ ~, q b& P+ x: p; |9 }
Ridge trace, 岭迹
: u: H, ]* v1 ]! e+ tRidit analysis, Ridit分析* ?. B4 F7 D2 c6 }" |" n
Rotation, 旋转0 V4 @- @; X9 T' `, v2 f; e
Rounding, 舍入
7 o6 i- a8 u: k8 v( n, s7 gRow, 行
& N6 k; p5 F+ Q& F- _, R1 I: tRow effects, 行效应, `7 g/ y/ @% z" S
Row factor, 行因素1 u/ `' x( @3 C6 f
RXC table, RXC表6 q- c: U9 K* A' W1 U
Sample, 样本
% T5 x [6 C% cSample regression coefficient, 样本回归系数4 ^0 k9 x* m: j0 T& e2 J1 _
Sample size, 样本量
1 G$ \3 i. `! p! } |2 I8 MSample standard deviation, 样本标准差$ f) n- k9 ]% |4 m9 v8 E* V" z
Sampling error, 抽样误差
j. C# [# V1 u1 d& y0 ]" e; e6 \SAS(Statistical analysis system ), SAS统计软件包
# e% E' T! V0 y' R; d1 ?Scale, 尺度/量表# B0 \" a/ t3 H2 S( L0 C
Scatter diagram, 散点图% r# F" f! N* W8 t& c1 S5 B+ u
Schematic plot, 示意图/简图
' f/ ]1 d. V YScore test, 计分检验
& q; |8 J7 e q" w1 e: qScreening, 筛检
! c9 Q+ H- R* G" oSEASON, 季节分析
) o. U/ Z4 `: ]+ ], ZSecond derivative, 二阶导数& x2 Q$ ^! H0 N5 U" G
Second principal component, 第二主成分
7 u: C" O8 t# `+ _1 Q0 ESEM (Structural equation modeling), 结构化方程模型
$ L, q- m, A; \& |* h4 t6 b0 bSemi-logarithmic graph, 半对数图7 A& p5 L5 G' u/ }2 q: D8 o
Semi-logarithmic paper, 半对数格纸
d* e* `! E, o0 ~& _Sensitivity curve, 敏感度曲线% h9 j4 c( I# x. J; j. k$ p8 r
Sequential analysis, 贯序分析1 j9 y* C5 Y8 L$ g# {9 Z% ?
Sequential data set, 顺序数据集9 Z. \5 ~* d$ `! S
Sequential design, 贯序设计
, q) g6 N* Z" M5 H( m; o. DSequential method, 贯序法 w# Y4 g% a$ Y8 \2 D- u
Sequential test, 贯序检验法
5 A; {( F3 s2 c- j2 _1 n" XSerial tests, 系列试验# h8 }7 z! ~$ a
Short-cut method, 简捷法 4 M( z+ N! u- H; \4 X0 P. c
Sigmoid curve, S形曲线% M. m! H, w8 M9 S; D5 ~
Sign function, 正负号函数- }1 @- S v+ k4 ~
Sign test, 符号检验
- R7 H& Z& O. R% g) y: aSigned rank, 符号秩
- i& ~$ }+ s% jSignificance test, 显著性检验8 e D" l' Y7 M+ ]0 @
Significant figure, 有效数字& Z- H/ P( v" l! b$ z) ^6 \
Simple cluster sampling, 简单整群抽样
* h8 E2 q2 f2 c. OSimple correlation, 简单相关
- \" _2 y: j8 }5 s. Y" H& h5 C' dSimple random sampling, 简单随机抽样7 O+ |: Z; V1 G2 }6 F. ~
Simple regression, 简单回归
) E3 _! ?+ |* k: }) P* _simple table, 简单表/ g1 ?$ a+ a) F& p: `
Sine estimator, 正弦估计量' r1 F: Q3 D0 O }& v/ ?+ g9 v* G' e
Single-valued estimate, 单值估计2 ]( y& M# k3 K9 J% G( U" d. y
Singular matrix, 奇异矩阵: N; l3 c0 ~7 a" i2 Q
Skewed distribution, 偏斜分布
$ D5 X- R' X, U( MSkewness, 偏度& h- s3 w% }# {+ c0 }
Slash distribution, 斜线分布
5 b0 g2 F3 }# y6 c. @. `Slope, 斜率
' ^, W: f0 Q. O/ o, fSmirnov test, 斯米尔诺夫检验
`( ]5 R3 `" R* RSource of variation, 变异来源; v& Y; F4 ?8 ^* e; |
Spearman rank correlation, 斯皮尔曼等级相关4 e6 M: [. ^" ~8 ?; q& W z
Specific factor, 特殊因子
4 Y1 w# Q- E1 q. TSpecific factor variance, 特殊因子方差
7 n; F$ R' K s( A& mSpectra , 频谱
6 j$ Q1 S; G4 l v- g: Z0 M+ SSpherical distribution, 球型正态分布- M: A3 D+ g$ I1 ^
Spread, 展布
& c9 k$ ?. [; O$ k, VSPSS(Statistical package for the social science), SPSS统计软件包; K! D8 p/ @5 Q2 T ?' C
Spurious correlation, 假性相关$ H2 p* _% v3 ~! T. _
Square root transformation, 平方根变换
# m V+ x* w! f1 R9 cStabilizing variance, 稳定方差- { G% R6 l- ]& \
Standard deviation, 标准差
4 r' `% a- _7 e* G- GStandard error, 标准误
2 I! ?) o/ {( h6 r" H9 E Y/ E! ]Standard error of difference, 差别的标准误8 c" A3 ~' V, _
Standard error of estimate, 标准估计误差
* F/ L: B& X; bStandard error of rate, 率的标准误! W9 k) s' s8 b; C a3 C
Standard normal distribution, 标准正态分布. Q3 ~! _4 ~0 _6 O* X2 _
Standardization, 标准化& P% b, F8 K/ I
Starting value, 起始值& O" u; p Y3 `2 h8 Q7 ]$ y
Statistic, 统计量
7 _( e* {4 |+ i% Q& b, I4 PStatistical control, 统计控制: v, x) [( Y: \
Statistical graph, 统计图( w, C; s4 N" S0 o: _" m' m, Q8 Y
Statistical inference, 统计推断
0 r' o% g% \- n0 @0 }# {% BStatistical table, 统计表8 C( y8 `2 ~# Q6 B& x
Steepest descent, 最速下降法; |1 g; |6 U! a6 w
Stem and leaf display, 茎叶图
; t, ?# n/ g8 |8 h% uStep factor, 步长因子
* O7 _2 x. {* k# v% ~Stepwise regression, 逐步回归/ r' y! ]7 a- ~5 f& A
Storage, 存
" d0 q5 _' T6 O& MStrata, 层（复数）
6 W. Y) V3 S" [6 C/ ~- N, D2 W; KStratified sampling, 分层抽样+ a. p+ \- e* M5 x" x+ }; d
Stratified sampling, 分层抽样2 v+ }; v! v6 H7 \: K& [
Strength, 强度. G: R) F# b' O# }+ B
Stringency, 严密性8 y# J0 R5 f+ J Z- \
Structural relationship, 结构关系
, v3 Y( H: H9 S! C: VStudentized residual, 学生化残差/t化残差
# k- J4 I! A% Z' K9 HSub-class numbers, 次级组含量
0 J( c0 f) X* L0 m9 [Subdividing, 分割
9 W! y! X \, B8 x( sSufficient statistic, 充分统计量
9 D8 w8 @* z, Q* v1 J4 ~Sum of products, 积和* r, G2 J" C& d4 D7 j& b
Sum of squares, 离差平方和/ F* O, v% E, P# I
Sum of squares about regression, 回归平方和: e( J+ U$ x! z
Sum of squares between groups, 组间平方和
9 r0 i M/ D5 O* y1 H: KSum of squares of partial regression, 偏回归平方和
" u9 `$ ]1 G. R. p* `$ \0 d4 ISure event, 必然事件
N5 u. B: K+ W& L5 [1 f) OSurvey, 调查 n4 r5 O/ r, |
Survival, 生存分析
! X) J9 f7 s+ [4 KSurvival rate, 生存率
$ r! | r* T* Q3 T6 |% t6 K5 V: DSuspended root gram, 悬吊根图" [+ Y/ F- ?1 B4 h
Symmetry, 对称" `8 B1 d0 B. Y" R9 ~: R
Systematic error, 系统误差
5 A; H" K$ C/ o6 `% {" aSystematic sampling, 系统抽样
* K5 m$ h' x7 Y, I+ Y, I4 F& v; zTags, 标签
2 t* D$ k3 }* }Tail area, 尾部面积3 D' g7 q8 }8 ]. f2 V$ L: S, j% m
Tail length, 尾长& f' h- ?/ L5 ]. A6 e5 U
Tail weight, 尾重
: L, `4 X6 l' Z7 E1 ETangent line, 切线( S: t! }3 a: N I
Target distribution, 目标分布
: R. X' ^" z9 e+ b/ B& q, TTaylor series, 泰勒级数. S0 U. m* r* ?# j1 c4 A9 X0 Y
Tendency of dispersion, 离散趋势
0 j% p5 P& u7 |' Q6 V/ U+ JTesting of hypotheses, 假设检验6 }) T0 n+ X! e1 T; u; R
Theoretical frequency, 理论频数
1 j7 T# e- j7 j. b; ETime series, 时间序列 C- I! |, |# f) r- e
Tolerance interval, 容忍区间5 } g l3 ^; e0 c
Tolerance lower limit, 容忍下限
* `. J5 x2 [. m9 W# D% \Tolerance upper limit, 容忍上限6 j! v9 W1 c- ^9 p) [7 \
Torsion, 扰率
' h/ S& e5 d/ W( t! pTotal sum of square, 总平方和: Y/ \4 X B+ k6 B1 m8 F4 W( h! j
Total variation, 总变异
8 ]! L! W; E. L8 f7 Z% yTransformation, 转换9 |% {$ f5 R3 w% Q( e' Y6 ?( }" z
Treatment, 处理) N; a! |( B8 y3 X p9 f8 o& b
Trend, 趋势
! b0 I" i! r' d, \1 f5 p6 M) F1 uTrend of percentage, 百分比趋势
4 V# c! H. x4 l1 uTrial, 试验5 D& S) R# [& j+ a" ^
Trial and error method, 试错法
7 U) V& ]3 \) J+ |Tuning constant, 细调常数$ O- _9 Y4 d( g4 ]7 o. m3 t; H
Two sided test, 双向检验$ C, y1 k4 I& k; r+ [( O H+ o& X
Two-stage least squares, 二阶最小平方
9 K" B* `3 x- ]Two-stage sampling, 二阶段抽样& t9 P) T6 s3 P0 o. |1 d6 B( W
Two-tailed test, 双侧检验0 i& G6 x# D* P
Two-way analysis of variance, 双因素方差分析- X& q4 f( T1 m" `/ k- F
Two-way table, 双向表0 g9 M& N7 R% z7 T
Type I error, 一类错误/α错误
) f# A" h1 d9 S9 qType II error, 二类错误/β错误
( {; C, t1 E: s! a2 HUMVU, 方差一致最小无偏估计简称
# {2 K5 r) O& \$ y6 o! z$ kUnbiased estimate, 无偏估计7 a8 h2 q5 c, `( Z" |
Unconstrained nonlinear regression , 无约束非线性回归
, {0 s3 O* Y) nUnequal subclass number, 不等次级组含量
; }, {9 d' _7 o8 q+ p \$ F4 p/ JUngrouped data, 不分组资料+ b* U9 L! [5 L$ b" d
Uniform coordinate, 均匀坐标
# Y; r/ i( q2 \( zUniform distribution, 均匀分布
- K4 A" u& E# e4 SUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( g" H# i$ _2 E; e& c1 ^2 OUnit, 单元
9 F/ l: X+ ~3 Q7 _7 oUnordered categories, 无序分类
: _3 w( L" j/ s5 ]4 R9 F+ ]3 j, M- xUpper limit, 上限
$ c3 t- _) A- ~: y* `6 G; m/ q1 lUpward rank, 升秩
, n# Q; M3 Z- j% i K0 RVague concept, 模糊概念
; f' h5 o4 v7 \+ `( ZValidity, 有效性7 t; }% k" N' `; a6 c$ b
VARCOMP (Variance component estimation), 方差元素估计
, ^6 O5 h/ G& K/ m4 ]% TVariability, 变异性
+ ^/ r" z+ }3 B5 P: V, E4 WVariable, 变量! @( Z" Z/ s. m) R. D4 a
Variance, 方差
7 V L! }4 Q. ]2 m# n+ V9 M* y- `Variation, 变异" k3 ]. ?3 \& }8 o0 i
Varimax orthogonal rotation, 方差最大正交旋转1 l8 U& W4 h$ Z7 L8 x5 a* T/ G
Volume of distribution, 容积) f# n7 ^4 u$ L5 b
W test, W检验 z; t* n1 |% A$ T! z% D
Weibull distribution, 威布尔分布
- i/ F/ e$ u! i9 d- E9 N& DWeight, 权数- S( `1 |; ~9 s3 p! A
Weighted Chi-square test, 加权卡方检验/Cochran检验# Z2 {) y* [0 _: m7 b9 i9 q
Weighted linear regression method, 加权直线回归5 c1 ]) N5 W6 @ r* W8 n, t
Weighted mean, 加权平均数' [( N" v, g8 `& N, o
Weighted mean square, 加权平均方差
4 S6 B, j9 v: I4 d, h# Y; V, lWeighted sum of square, 加权平方和4 u- I- p7 A4 D. T$ Q
Weighting coefficient, 权重系数; [' h# I! A; @( B+ p
Weighting method, 加权法
5 O: Y! o- ?8 c; m# ]& T; C/ SW-estimation, W估计量6 G+ L1 L. |: N, x
W-estimation of location, 位置W估计量5 B% U9 Y- a$ _
Width, 宽度7 n& v. }+ D" ^1 A; e+ ~
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验- W( ~) e# D6 N T+ F3 n( t6 W
Wild point, 野点/狂点7 l; F( ]( y L% J
Wild value, 野值/狂值
; ?( X5 w" n k; D6 C9 G- [' JWinsorized mean, 缩尾均值
6 S* K1 l: v. C' d7 q/ S; `6 vWithdraw, 失访 1 c* _4 K$ u6 Y7 `
Youden's index, 尤登指数; c3 `% ]2 ~* Z+ k
Z test, Z检验 y9 v5 U0 I7 s2 t1 U$ z1 ^
Zero correlation, 零相关# i- I' B2 L3 O% w) w
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
