|
|
Absolute deviation, 绝对离差
! Z. E) G/ V8 ^Absolute number, 绝对数
3 C% x8 x0 O5 H3 FAbsolute residuals, 绝对残差4 G- l$ j. F* l" T
Acceleration array, 加速度立体阵
* u6 t) V2 Q* }, }+ S k. Z$ U" @8 YAcceleration in an arbitrary direction, 任意方向上的加速度
9 D) i. I7 ?+ j8 f1 P) a* V8 V6 SAcceleration normal, 法向加速度
2 B! u: O9 L" t$ G0 Y* bAcceleration space dimension, 加速度空间的维数+ X# g, M! v* l l7 \1 }5 \1 [/ E
Acceleration tangential, 切向加速度
# }* R( P ~+ m# @5 W7 @3 ?Acceleration vector, 加速度向量9 m' X) B- @0 v2 ?( K
Acceptable hypothesis, 可接受假设
7 s* x7 Y4 f8 K; g0 eAccumulation, 累积
- F) H1 d1 {( r2 aAccuracy, 准确度
' ~+ f3 v) A7 D( U0 m+ OActual frequency, 实际频数5 B5 P2 s5 I0 r# A2 p$ r
Adaptive estimator, 自适应估计量" w5 w$ l- [- V2 m4 @3 a
Addition, 相加2 W0 O) {0 F! D5 e( i5 u8 F' g$ G
Addition theorem, 加法定理
- W3 C1 i# X6 d: NAdditivity, 可加性& [1 q) T. O. g3 t, i# j8 u. [: h
Adjusted rate, 调整率6 [+ { \( ]2 g+ i1 }4 ]
Adjusted value, 校正值1 l+ W- u( R0 r" U4 r% F! R2 ?4 e
Admissible error, 容许误差) |: C5 d5 c! ]
Aggregation, 聚集性, G/ k" n* v' e+ R; n
Alternative hypothesis, 备择假设
3 m- }- M) U) l+ o oAmong groups, 组间- s+ L7 |6 [9 L/ Y
Amounts, 总量2 d0 V/ y. v! `9 V6 T
Analysis of correlation, 相关分析
3 m2 A* I$ L f: ?; c/ V, g- eAnalysis of covariance, 协方差分析' w# f2 m% s9 A# b: y% E( u+ p/ M
Analysis of regression, 回归分析( r- e1 _1 L8 ~( `
Analysis of time series, 时间序列分析# F. E" t3 ], @1 x8 K' U6 K5 o
Analysis of variance, 方差分析
- ]5 M9 @. L0 B, o% Q+ HAngular transformation, 角转换
* N& r1 U$ H. h1 d6 K) Y& I, RANOVA （analysis of variance）, 方差分析
" `+ z& P8 c5 h% d& @ANOVA Models, 方差分析模型
2 f6 H; j$ {$ L/ OArcing, 弧/弧旋2 z2 l6 z6 G# m1 J- d
Arcsine transformation, 反正弦变换" q( f4 @3 _8 w+ O, _1 G6 g
Area under the curve, 曲线面积$ U5 @" L9 _/ A# f5 ~% t3 G
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 % R- S" O' _' S# g- D$ S! j1 u- v
ARIMA, 季节和非季节性单变量模型的极大似然估计 * _( B. }: ]" o! _
Arithmetic grid paper, 算术格纸8 x0 _; x' [0 J5 L, `- V
Arithmetic mean, 算术平均数1 M+ m( l" `4 u
Arrhenius relation, 艾恩尼斯关系+ P8 L3 f' V: i: z8 A1 d0 g
Assessing fit, 拟合的评估) t# M/ s/ I5 P
Associative laws, 结合律
9 s7 S3 R: z( `Asymmetric distribution, 非对称分布
8 f. t* I+ f1 PAsymptotic bias, 渐近偏倚) v1 D3 n2 ?, ]/ S- N [
Asymptotic efficiency, 渐近效率
) u9 ]# {, k P ^! T- wAsymptotic variance, 渐近方差
, U; x# [& ?7 l5 r3 XAttributable risk, 归因危险度
* I- @* X) ^+ y7 }# eAttribute data, 属性资料4 B) m" U1 P/ F. x ^
Attribution, 属性
# X7 K3 A" [4 y! T6 x" aAutocorrelation, 自相关. q! y& x' o7 A4 {
Autocorrelation of residuals, 残差的自相关" o$ i. @; Q. J9 `. ]+ ~4 @4 @
Average, 平均数
. @9 v" V+ g u% D6 ]Average confidence interval length, 平均置信区间长度
8 `* p- z+ F) kAverage growth rate, 平均增长率8 |. a, f5 P" o9 x& { n
Bar chart, 条形图% M! A' d4 j4 Y) J+ r4 J
Bar graph, 条形图
7 z$ ] K: I( v+ ABase period, 基期
( w$ r) l- @9 P3 d2 X: kBayes' theorem , Bayes定理
5 S2 v8 O7 ` T% [* G# b( L% |* yBell-shaped curve, 钟形曲线
+ ?% u9 [4 h3 y) V6 l7 X: oBernoulli distribution, 伯努力分布
: t! t* [& f& K% [: u" ABest-trim estimator, 最好切尾估计量) Q% w8 f+ s! C8 v/ `
Bias, 偏性1 w# V( c& J2 [- \
Binary logistic regression, 二元逻辑斯蒂回归
1 E1 w3 |2 L7 k, s' L9 R/ O# QBinomial distribution, 二项分布
. }7 D: N6 K( aBisquare, 双平方4 B3 I: ^. [( A% N: a
Bivariate Correlate, 二变量相关
1 N4 E& w) @3 z1 q' RBivariate normal distribution, 双变量正态分布
- Q' D) Q- S8 jBivariate normal population, 双变量正态总体
' {) O; W& n% e# R! wBiweight interval, 双权区间9 L( z6 n/ u6 |- K. P; a
Biweight M-estimator, 双权M估计量" L$ u+ ]+ ?5 w
Block, 区组/配伍组
* g4 B: G1 C( [( qBMDP(Biomedical computer programs), BMDP统计软件包
! H% Z# | S) @6 tBoxplots, 箱线图/箱尾图
[! L5 T' E( U7 VBreakdown bound, 崩溃界/崩溃点. x6 q( V5 j$ S8 o* c" L
Canonical correlation, 典型相关
- N4 ^8 W0 v6 ICaption, 纵标目
+ P+ ]8 ~, Z3 ]; p7 ICase-control study, 病例对照研究
1 K: j6 t2 L7 d4 G$ E/ GCategorical variable, 分类变量2 E+ X4 Q& }8 I" h4 n/ h
Catenary, 悬链线
, K% z) T- F4 A- f" xCauchy distribution, 柯西分布( ?+ V7 [7 A& a) }0 K F
Cause-and-effect relationship, 因果关系* ~, S" P/ n @. Q; \4 a
Cell, 单元
3 g2 d7 ^$ v, p5 c, nCensoring, 终检6 e" [3 I. x- G/ p: G6 [
Center of symmetry, 对称中心" }9 j7 M8 C0 z" m, ^
Centering and scaling, 中心化和定标
3 o _& ?4 `- Q/ N" I1 iCentral tendency, 集中趋势
" a: H3 l( R% W. X& ^' A3 N' ICentral value, 中心值, a8 @ D4 }8 `9 F3 `2 H( b/ b d
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
o# q+ a+ [& v' [+ PChance, 机遇
" ]% R5 E; B+ g2 R) EChance error, 随机误差
; Z2 q( [+ o9 z1 [4 Z; y4 ?; R# |2 JChance variable, 随机变量
& z+ g& C" ~; x) E8 F+ pCharacteristic equation, 特征方程
1 j, X3 `- g8 l- P( L7 UCharacteristic root, 特征根
; |9 E5 Z+ P# [; TCharacteristic vector, 特征向量 a1 r0 a2 Y' [4 ^# I
Chebshev criterion of fit, 拟合的切比雪夫准则
0 w% a: \( K- O- P0 z {Chernoff faces, 切尔诺夫脸谱图5 I3 d8 m4 V3 g' t7 M9 v' m
Chi-square test, 卡方检验/χ2检验- r9 T( a& Q5 \7 Z, [, U3 v
Choleskey decomposition, 乔洛斯基分解
, b& s8 z+ u) `5 B! V- Y2 QCircle chart, 圆图
+ Q1 u* D3 v, X. o% JClass interval, 组距
: j) [, d- n, b) PClass mid-value, 组中值2 P# ], \* |" l1 o0 B* A' r
Class upper limit, 组上限' @9 v2 e+ ^2 U' K" L$ g
Classified variable, 分类变量: ~( y. s# ?) V! }7 E
Cluster analysis, 聚类分析
2 n- N2 v- p; L, Y2 X, Q# F# e, Q, MCluster sampling, 整群抽样
+ d# j4 M( v F! k0 b- \Code, 代码 ~" f* w% \! U; o0 m! [" b
Coded data, 编码数据) v. w" z& }2 B }% d5 m" ~2 T* C# A
Coding, 编码9 q+ R3 q7 e3 Z) W9 _: V) ?& W6 e
Coefficient of contingency, 列联系数
4 k, J5 b j7 w6 B" k& UCoefficient of determination, 决定系数% ~ i% d: d3 A# @
Coefficient of multiple correlation, 多重相关系数
1 O9 X1 p8 y' Z$ I/ XCoefficient of partial correlation, 偏相关系数0 S; c6 y3 c5 ], Q
Coefficient of production-moment correlation, 积差相关系数, r$ X K1 l4 j& r
Coefficient of rank correlation, 等级相关系数
+ ]- G$ Y4 c$ {: Y. w+ s7 GCoefficient of regression, 回归系数$ E8 \# A/ p0 m" y
Coefficient of skewness, 偏度系数8 Z7 v$ s" B3 i: C5 F# z
Coefficient of variation, 变异系数7 `0 W9 d" ^* w# K( W2 C8 b! F7 G- h
Cohort study, 队列研究
9 Y( W" v* g. B/ N( E3 `Column, 列% h0 k1 B+ g" s6 |
Column effect, 列效应7 g+ T' q9 }2 ?* d
Column factor, 列因素3 n% v6 K; @: A) |' p
Combination pool, 合并) c$ U( I( I- c; a# O
Combinative table, 组合表
4 f2 f4 [0 a6 n% n) wCommon factor, 共性因子
: b g5 e' \6 z& n7 j& j# z1 O1 O* ?# oCommon regression coefficient, 公共回归系数
7 O# x d* @" j: [$ f F0 NCommon value, 共同值& i- ]+ J( y! T1 \
Common variance, 公共方差
0 @7 X' Y6 L6 R4 Y- W1 G& b z$ mCommon variation, 公共变异
8 R) Z" [; N' h# T+ h8 R. MCommunality variance, 共性方差2 k3 n4 @7 {+ o$ f1 ]- I; T, N. N, ~# i
Comparability, 可比性
. _7 K: D2 V$ t( D Z% w# tComparison of bathes, 批比较$ I4 H j' O: j8 u5 l6 |6 ?* y
Comparison value, 比较值+ X u7 [7 S1 A( |0 [0 U2 S
Compartment model, 分部模型
4 r1 o" y: U }& ^, m1 k2 q PCompassion, 伸缩$ [5 H0 m3 V0 P, R, ?9 T) I
Complement of an event, 补事件5 i' j4 Z- p% ?' M, {
Complete association, 完全正相关
1 U$ d* f6 c6 r0 F: V. `; }Complete dissociation, 完全不相关
3 ^) z, |4 J' |0 s" O: z/ bComplete statistics, 完备统计量* U( r/ ]- p/ n4 i
Completely randomized design, 完全随机化设计
+ H9 T$ C4 l- b! jComposite event, 联合事件
- A" U( U+ e/ j' f% ~ q. `) }! L- x0 qComposite events, 复合事件$ m) z" M$ ?$ c# {' b" C7 `
Concavity, 凹性
/ b% Z7 X( c. G( _" t# C) ?/ KConditional expectation, 条件期望+ f7 K2 E8 D+ i* y4 Q. J
Conditional likelihood, 条件似然
' N( j! S: v! q% ^) cConditional probability, 条件概率; f, o9 `8 a) V1 l v
Conditionally linear, 依条件线性
]: }4 n! O1 r: H/ k2 lConfidence interval, 置信区间
: T6 f: ` G2 H3 W' d g& LConfidence limit, 置信限
C3 o) y$ _ c1 M4 T9 V! A) zConfidence lower limit, 置信下限
^3 }; [6 i0 k" C! E: ^Confidence upper limit, 置信上限, ?. _, O) t/ Y. s% D* B7 |1 T
Confirmatory Factor Analysis , 验证性因子分析4 B% W0 L/ z6 f- e& N7 t
Confirmatory research, 证实性实验研究
% O7 N+ u4 n# ]5 ]Confounding factor, 混杂因素
8 O6 ^: ?' h. s ?+ G0 jConjoint, 联合分析
0 S9 k2 l$ q( s4 Y: \, b# sConsistency, 相合性
7 Y* _% x [- l9 T( @6 WConsistency check, 一致性检验$ O: B# ]* g4 q
Consistent asymptotically normal estimate, 相合渐近正态估计4 O+ Y" H4 M2 f$ H% U+ Z; v& l
Consistent estimate, 相合估计2 b9 X/ m9 I+ n+ Y
Constrained nonlinear regression, 受约束非线性回归( C* B- O" H) r3 C
Constraint, 约束' j& L& g8 U, h1 V/ R
Contaminated distribution, 污染分布6 F4 i' `/ Q* A6 l- ?
Contaminated Gausssian, 污染高斯分布
& S1 S4 w* o$ o( A+ HContaminated normal distribution, 污染正态分布+ v: Z9 G( ?; ^
Contamination, 污染# d2 @5 L! C2 ]8 o& z5 W$ x
Contamination model, 污染模型
: H% g; \6 u7 N. v. e) D: X: D8 PContingency table, 列联表
/ V0 \" C3 A3 ?& }0 {* FContour, 边界线% b5 _$ t, F' y, z3 ~4 r) {
Contribution rate, 贡献率/ v$ j9 R" h6 M1 U( x" v' k
Control, 对照
3 \4 B2 `0 ~ a0 |5 uControlled experiments, 对照实验
. ^4 u' [! V2 n% T' w) YConventional depth, 常规深度
6 B3 d( r+ b ~Convolution, 卷积& A3 \7 ^/ f! D( V1 N( n8 }, _# d0 b) n/ C
Corrected factor, 校正因子
/ J7 S% W- L- c& n/ M* U4 jCorrected mean, 校正均值
8 V7 H+ A8 y1 ~$ r: c! }% zCorrection coefficient, 校正系数$ a/ x1 v4 V# U4 l' g. l' f2 ^
Correctness, 正确性
3 o$ p) s9 S& mCorrelation coefficient, 相关系数4 f; V+ _ O' J b* {- n5 Y! L5 M
Correlation index, 相关指数: V6 W: {- Z, Q8 I$ T% s& U5 U- y
Correspondence, 对应
6 O1 [* c# {" U' C3 uCounting, 计数9 E# s- e! C% j8 Q/ B3 n. }
Counts, 计数/频数
9 b; b& S# D# l% b3 K3 j) J2 n8 F/ dCovariance, 协方差
. R+ z; z9 W/ }6 O) @3 Q+ SCovariant, 共变
, J8 Q; n- a+ K" a: j3 v0 |Cox Regression, Cox回归' d8 Q2 N/ e/ V8 I$ v4 |
Criteria for fitting, 拟合准则0 y/ U' L7 S# B7 T4 x
Criteria of least squares, 最小二乘准则
7 i2 @- j" E/ Y) FCritical ratio, 临界比
5 i, J0 n3 w' Y) f `Critical region, 拒绝域
/ _' x8 \) q. y. wCritical value, 临界值
+ t% G/ K7 ], }7 U: p0 A4 D1 a& YCross-over design, 交叉设计
; b' O- `. }4 y6 m" VCross-section analysis, 横断面分析" G; D% l. k' T
Cross-section survey, 横断面调查' ]* O* l, m% r) E
Crosstabs , 交叉表
& M. K, E6 r7 l: W# N- @Cross-tabulation table, 复合表! ^! t0 ?' R8 K! ]" W
Cube root, 立方根0 q0 C$ r3 K% Z
Cumulative distribution function, 分布函数
" N; z. u" @2 b2 \5 s5 w, {& |; LCumulative probability, 累计概率
R+ }' A2 {% I8 U; C/ YCurvature, 曲率/弯曲
% ~; S0 u# [8 o9 P+ _Curvature, 曲率! f4 u# R& t: ?- b
Curve fit , 曲线拟和
$ A2 e' B5 ]( m# S# {: aCurve fitting, 曲线拟合/ x( A3 y3 C @' t% R
Curvilinear regression, 曲线回归
$ t% k! q2 ^7 f3 u- lCurvilinear relation, 曲线关系1 e0 X0 F9 }6 p2 m h+ [0 v; ]2 I
Cut-and-try method, 尝试法. |" {0 t/ d& w+ Y& `! b3 X
Cycle, 周期 V7 ~% ~$ h1 f+ f7 V2 b/ v4 p2 E
Cyclist, 周期性6 l& ]. k1 Q+ O( h P6 U
D test, D检验
' x) g4 E; t1 l, `) OData acquisition, 资料收集4 ?. ?. e9 h" y* z9 G8 p! I
Data bank, 数据库
1 n- _: q$ h+ p# |3 |Data capacity, 数据容量2 x7 M0 X6 U5 q1 l
Data deficiencies, 数据缺乏5 V9 ^1 _( T+ m1 m: w
Data handling, 数据处理; i) D! J! x, ~" O( m3 {) j
Data manipulation, 数据处理, c. {3 p* b" z: n* |( l8 S
Data processing, 数据处理' ]: h" w3 n* F" p; ^: h1 u
Data reduction, 数据缩减; e4 _& T3 m" b
Data set, 数据集
9 n8 Q) C7 V# k8 X0 N) sData sources, 数据来源
% U& c" d" c% k/ c4 g/ R: e9 hData transformation, 数据变换; p; _' D9 V# N2 z4 j
Data validity, 数据有效性: B1 R0 J/ P/ Y" y9 u' t, a
Data-in, 数据输入
: x3 U9 d. w; n M# e1 cData-out, 数据输出
2 Q7 k5 G" ^" h0 E! b( xDead time, 停滞期
8 e7 L7 Y) O6 w4 n4 iDegree of freedom, 自由度
7 z }1 _. }9 z7 TDegree of precision, 精密度
# j7 F- U, H0 ~' r% VDegree of reliability, 可靠性程度. I3 o4 S5 i/ A+ P0 \* f
Degression, 递减5 l N3 r- j+ L0 Q7 s8 ^
Density function, 密度函数5 {9 a# t+ E* C6 m
Density of data points, 数据点的密度, v# ?8 `8 }) t
Dependent variable, 应变量/依变量/因变量" v0 F" b& o3 Z, w( e
Dependent variable, 因变量
) V/ {7 i% d5 M8 w) G! ~Depth, 深度
! k" R2 F, E" y5 h% vDerivative matrix, 导数矩阵8 i% A8 I3 j& X& e' }- B7 A
Derivative-free methods, 无导数方法2 F3 e- z# \9 s
Design, 设计
4 K8 o& u0 r; v: j% D' E: x1 t- FDeterminacy, 确定性
8 C3 H+ C2 n; g; O& U6 SDeterminant, 行列式
" I5 V5 g" c; N: [4 DDeterminant, 决定因素
9 b. g) E! P0 v3 V4 I* EDeviation, 离差+ Z+ p$ [5 ~; p$ Q- C' W
Deviation from average, 离均差
8 t3 d3 O9 i1 T* E1 P; [. v+ wDiagnostic plot, 诊断图
8 n: M# n: m6 ]) u- B$ NDichotomous variable, 二分变量. }0 ?( B5 y2 s1 T. `* z
Differential equation, 微分方程
6 G5 t/ n+ h$ y! S8 G, EDirect standardization, 直接标准化法3 j- [1 i& H% o. E) O4 T% m6 x
Discrete variable, 离散型变量5 Z+ ]1 d! h: d6 y! }' e' O' Q' o
DISCRIMINANT, 判断
+ |. x2 q0 w/ f; B) ] w6 uDiscriminant analysis, 判别分析
/ d3 w% m, S3 s2 c6 C" ~7 sDiscriminant coefficient, 判别系数
+ @1 R! s. x( s; L3 tDiscriminant function, 判别值; t6 _: ?# D3 I9 d6 c5 M0 q- j5 h
Dispersion, 散布/分散度
" L& u0 s! ~% C( |" ^Disproportional, 不成比例的6 k6 V3 l. z* i4 R9 O7 t
Disproportionate sub-class numbers, 不成比例次级组含量3 ]; m; Z: X" k4 _
Distribution free, 分布无关性/免分布
' { B7 z) e d( G) d2 wDistribution shape, 分布形状, E+ X p/ Q7 d8 q4 \$ r; }
Distribution-free method, 任意分布法
, F0 x. V( a) {9 h, k; i5 D8 Z% \Distributive laws, 分配律
; ?1 L+ x, ]* ~4 R" c9 iDisturbance, 随机扰动项) c4 d6 T/ C2 R) \2 h
Dose response curve, 剂量反应曲线: y1 V% S. @$ F) e
Double blind method, 双盲法+ m" G6 F$ _6 N7 K
Double blind trial, 双盲试验: O* l9 b% `' e# @: i. y- E
Double exponential distribution, 双指数分布
# A' L7 ]' x) W, YDouble logarithmic, 双对数5 d! n3 ^3 s# {9 O' H+ a8 N H; |* V
Downward rank, 降秩
3 t/ A y& G/ `% P$ D: mDual-space plot, 对偶空间图: S7 Z' N' Q* p* |( |4 g, w& I
DUD, 无导数方法, m( O; r5 h+ o* @
Duncan's new multiple range method, 新复极差法/Duncan新法( H7 _6 U: g/ n+ m' @* l, k
Effect, 实验效应
) p0 z7 W/ K) e8 e( b1 m1 s \$ aEigenvalue, 特征值2 c% a# M: O4 d# v5 Y3 C
Eigenvector, 特征向量2 A: D5 F4 B) [8 ?* Q
Ellipse, 椭圆9 q+ V8 O5 j+ x5 S7 n. k% N
Empirical distribution, 经验分布7 ]* x- L6 x0 D
Empirical probability, 经验概率单位
2 n+ j! @" g0 G- R( xEnumeration data, 计数资料- I% G( k5 x: r1 U
Equal sun-class number, 相等次级组含量, C/ g! b5 _# o& l y
Equally likely, 等可能
# [. y& L2 R$ |7 @5 HEquivariance, 同变性6 s @1 ]3 V9 R+ E& m
Error, 误差/错误
+ y- h5 ?; V6 o4 y& S2 q4 E7 mError of estimate, 估计误差( e5 R1 R/ F0 ]" T8 S- Q! Z
Error type I, 第一类错误
! G# G) @* P' h+ D7 bError type II, 第二类错误
/ ~1 l$ N5 g5 iEstimand, 被估量' c0 i% _" B6 t5 O4 N" E3 E$ T
Estimated error mean squares, 估计误差均方
* v# ?$ i. L% U4 QEstimated error sum of squares, 估计误差平方和
' i1 A S1 o; U n7 d, y8 K$ WEuclidean distance, 欧式距离& Z7 ?& I+ T6 B+ D
Event, 事件1 @) d! c' r1 s: V
Event, 事件
# F$ t8 w- |9 z, n+ B* oExceptional data point, 异常数据点
1 b$ }* d" _4 ]9 R( s9 h0 M4 P# n* e! JExpectation plane, 期望平面
: ]- k! [+ {" j% Y; v" pExpectation surface, 期望曲面
- j) ~/ p' G/ P% _- d8 f. vExpected values, 期望值
+ f9 M2 k4 r! R9 S1 @8 y3 p0 ]" ZExperiment, 实验4 Z; @ R% o5 f, ~8 l( O
Experimental sampling, 试验抽样
9 u2 X# O& V7 K/ KExperimental unit, 试验单位
2 k& ]5 c4 B0 ]# y, i s; W9 U6 ^Explanatory variable, 说明变量
9 `/ j4 V8 a; x* P! MExploratory data analysis, 探索性数据分析' ?# p( l( i$ s! q6 t2 c
Explore Summarize, 探索-摘要, d- o( r, h y( R; q. Q4 l9 T( [
Exponential curve, 指数曲线
6 i; Y! R5 s# ]0 pExponential growth, 指数式增长1 H! r& v9 w) c" d! V" n' |
EXSMOOTH, 指数平滑方法
8 C' j; N- E6 v% C- p/ U: V7 L ?Extended fit, 扩充拟合$ z5 e% o" y) ]0 m n3 X
Extra parameter, 附加参数. ]& s& Z' g! a8 g8 h
Extrapolation, 外推法+ ?# i% Y9 P1 \* i% ~
Extreme observation, 末端观测值/ a0 w# i5 f7 y
Extremes, 极端值/极值9 ^+ V$ p* v' z4 u' h: I h6 x, k% r
F distribution, F分布( ?$ }& X; a2 M% r4 L- h$ [
F test, F检验
$ ~6 \' g: p+ g9 _Factor, 因素/因子
6 ?+ l% ]7 r: CFactor analysis, 因子分析
8 d) U% b2 M7 ?/ c2 Q5 s; D5 |Factor Analysis, 因子分析: V5 w, I) t0 Q. T) b
Factor score, 因子得分 0 |) v. l' y# y# j( o
Factorial, 阶乘 w4 r$ F) a6 `/ H3 {, V
Factorial design, 析因试验设计! |3 Q& R+ H J0 X/ D0 m4 d H
False negative, 假阴性
# \0 B+ Q, B2 U2 VFalse negative error, 假阴性错误
" I' P0 w' Z$ {; I/ ]/ z: DFamily of distributions, 分布族3 ?% |0 L; a) L
Family of estimators, 估计量族
, V/ M! d( `- ZFanning, 扇面
- U5 d& f( ^) x |% F/ k3 z7 E) ]Fatality rate, 病死率
$ j% c3 }9 Z$ VField investigation, 现场调查" _ u+ O9 M% m; K' T& w, C
Field survey, 现场调查
6 J4 }& ~. D! l$ cFinite population, 有限总体2 U+ c* M: j8 I
Finite-sample, 有限样本& r3 ` i% P# H$ {" z; u6 V
First derivative, 一阶导数# i. \- \2 T, u2 Z
First principal component, 第一主成分+ a, ]6 f1 o; V# ~
First quartile, 第一四分位数$ G0 q1 N9 K, D+ r8 E* n
Fisher information, 费雪信息量6 j" h. W1 e* i* |+ Z
Fitted value, 拟合值
" ^2 {, o: u5 l4 G) @, T7 eFitting a curve, 曲线拟合
. R. T% c0 y) g$ n4 MFixed base, 定基7 ~2 Y# f4 w/ ]9 ~" i* L. [
Fluctuation, 随机起伏' n. O: u" b) @( H7 C
Forecast, 预测
( K0 ~2 L& Y) ZFour fold table, 四格表# M$ l' |$ E/ `, \" n4 y
Fourth, 四分点
( S! `" }- }7 Y" pFraction blow, 左侧比率
( ]0 O/ [' Z7 ^9 u5 bFractional error, 相对误差! b2 m! {0 t( o* K- B2 ?0 S; Q
Frequency, 频率: R# `6 i5 W6 j* V
Frequency polygon, 频数多边图
$ x9 Z# R% Q9 m8 [0 AFrontier point, 界限点. W! ?9 k. C+ _+ J3 h% m
Function relationship, 泛函关系. Q0 M4 h3 A6 |2 p- Y9 k
Gamma distribution, 伽玛分布
- ^# s$ v( i# a: ]Gauss increment, 高斯增量
% }& d, ~$ Y# d* c% G2 x2 _Gaussian distribution, 高斯分布/正态分布# `. [1 X. G- A Q
Gauss-Newton increment, 高斯-牛顿增量
; e' e' k$ ^' B3 s* nGeneral census, 全面普查3 W! P/ O' z9 }8 ]2 D
GENLOG (Generalized liner models), 广义线性模型
1 m* X4 X1 E6 D0 D. C0 wGeometric mean, 几何平均数; T7 n. d. f" W3 Y
Gini's mean difference, 基尼均差. B- U; y3 `+ Z9 W* x! M4 K2 N
GLM (General liner models), 一般线性模型 ; p, J% _9 ?6 e9 b! `
Goodness of fit, 拟和优度/配合度7 a" P; W* `: n: Q
Gradient of determinant, 行列式的梯度, s# r6 c9 k* k9 [
Graeco-Latin square, 希腊拉丁方
8 t4 l' ~4 l( {! I }Grand mean, 总均值
0 W5 ~' V: N" ]' q9 vGross errors, 重大错误1 k& z* F2 w( v2 t$ ^% g
Gross-error sensitivity, 大错敏感度' }: ^0 E7 N+ \# s! H
Group averages, 分组平均
( v1 A. b: f/ g: g% W5 ^Grouped data, 分组资料
& Q9 s$ I+ s; r% G8 t1 F3 i: X8 IGuessed mean, 假定平均数
# M# A) p- q r: L/ Z0 NHalf-life, 半衰期/ j+ M- Q y; I, k" V+ T
Hampel M-estimators, 汉佩尔M估计量
# W9 a+ G" H* ~+ j) g. nHappenstance, 偶然事件
2 ^% R: {8 Y. | j) X% Y9 |. _Harmonic mean, 调和均数
& t% D+ _; S$ H* THazard function, 风险均数 O3 ]: s: ]$ R' K! }- B1 p6 Y
Hazard rate, 风险率
" z; d& t$ m* _2 \1 qHeading, 标目 5 v. [0 i8 ] B3 E+ @
Heavy-tailed distribution, 重尾分布
% J, J7 l) Q9 c3 |8 iHessian array, 海森立体阵5 ?! x0 m F8 {4 B$ h& g9 b" X. V
Heterogeneity, 不同质3 z/ B& d7 V# V8 S5 d6 E! ]$ ~+ T2 A
Heterogeneity of variance, 方差不齐
6 ^5 q, U4 y5 lHierarchical classification, 组内分组1 U7 j; p. n m9 o
Hierarchical clustering method, 系统聚类法
8 {; p# F7 n2 t# y/ J; G' PHigh-leverage point, 高杠杆率点9 o5 c: b8 F) P' I8 d+ H& y
HILOGLINEAR, 多维列联表的层次对数线性模型: o& j* X% L u" h
Hinge, 折叶点1 |8 Z& W3 x: I8 ] c, Y6 F! n* a4 y: J
Histogram, 直方图) X4 `& p" u) h3 x! d
Historical cohort study, 历史性队列研究
8 M& }* p/ {$ G- [5 v5 {Holes, 空洞
% _2 d) C) W% O7 j9 {2 Y2 Q; `HOMALS, 多重响应分析9 X, a# t" k$ I
Homogeneity of variance, 方差齐性! |# y' S4 U3 p( d& z) D/ P
Homogeneity test, 齐性检验
- C/ }# _0 p* }0 P7 aHuber M-estimators, 休伯M估计量4 A. F7 G6 \# O8 P
Hyperbola, 双曲线1 i$ L, f* U4 v9 x9 W, v
Hypothesis testing, 假设检验
- c& a! o7 z& S' j5 f( t9 SHypothetical universe, 假设总体 d, k {: d6 |0 r' B. `3 z) B& C
Impossible event, 不可能事件
2 S8 w: [8 j7 \. R9 bIndependence, 独立性/ [/ z0 \0 q2 b, N
Independent variable, 自变量
/ d* v e$ [ W- [% y: Y% R0 R( R9 dIndex, 指标/指数- U2 G: ]# Z: J2 @
Indirect standardization, 间接标准化法, e7 v' l0 ]6 ?7 e9 r/ ^4 B \
Individual, 个体0 q& b8 L- e4 I
Inference band, 推断带
6 x+ H# [( t# A8 FInfinite population, 无限总体, d" B% V' [* n' m2 l+ q
Infinitely great, 无穷大+ G U3 s* V: O/ B |2 w
Infinitely small, 无穷小
7 c% V3 D7 W, f- Q( Z, XInfluence curve, 影响曲线
7 T4 L {) N+ X% }) q6 u' w- JInformation capacity, 信息容量+ P* i' v% Y! c$ ? G
Initial condition, 初始条件
+ `6 T5 i" R" N4 J5 KInitial estimate, 初始估计值
[, h% v6 K* I7 z4 lInitial level, 最初水平& g: x. r+ t) H4 k' e; w
Interaction, 交互作用
; a; N2 I$ y; p+ e# o pInteraction terms, 交互作用项
/ X# f0 {# S( {3 WIntercept, 截距
2 ]+ F0 S, J. A! z! Z( NInterpolation, 内插法5 c+ U( z3 i" G: O0 p! F& l
Interquartile range, 四分位距4 D& J1 E+ Y+ Z" g
Interval estimation, 区间估计) R: y5 j" b8 @( o& r9 R
Intervals of equal probability, 等概率区间
& j3 o* M" t" W+ Y( m8 rIntrinsic curvature, 固有曲率
) p# x) [" ]7 U, WInvariance, 不变性9 e" K! K4 d5 O! U5 ^* U
Inverse matrix, 逆矩阵1 o: d p4 A9 l# f! Z
Inverse probability, 逆概率
- c" ^+ m3 e: o" \Inverse sine transformation, 反正弦变换
8 i( S2 _8 c Z3 R' ~Iteration, 迭代 - p$ y/ d- E; w/ n# d7 H. y! s/ x
Jacobian determinant, 雅可比行列式, Z Q1 D# @0 F) `7 ]4 a
Joint distribution function, 分布函数/ N" Z7 N+ d: F9 {$ @0 v
Joint probability, 联合概率. k9 m: b9 ?+ N8 `1 d: j6 s( x; [) o4 }
Joint probability distribution, 联合概率分布7 |) i p7 b! E
K means method, 逐步聚类法8 @+ g9 I1 P+ D3 F: T' S5 Y
Kaplan-Meier, 评估事件的时间长度
Q' Z' J6 a; H X" VKaplan-Merier chart, Kaplan-Merier图
6 C5 k) Z; `% J# h9 bKendall's rank correlation, Kendall等级相关
! L/ G, Z. V; w2 sKinetic, 动力学# R/ `- I+ ?% _" [6 [! }1 p
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
8 }2 Z: ~9 W( i7 v( y$ ?/ U% GKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验# |( U2 e% E8 p" @* V
Kurtosis, 峰度: R* M$ L# q$ x" K {
Lack of fit, 失拟8 a; l1 K( j* X4 M) ~4 ]
Ladder of powers, 幂阶梯
+ ?: o! A7 o! | Z) D; dLag, 滞后5 @; m9 j- E8 M+ v4 }3 N
Large sample, 大样本
; | n/ Y0 W+ q& z$ n8 TLarge sample test, 大样本检验3 E& ^# }$ N4 s) W3 a
Latin square, 拉丁方% Y5 ~! s/ Q8 ?" h- r
Latin square design, 拉丁方设计8 U5 m- }5 {( ]0 r, c3 D# }; E
Leakage, 泄漏5 Z8 m, v1 ]; t6 W! e8 A
Least favorable configuration, 最不利构形0 y$ o! B( K1 I# E/ o
Least favorable distribution, 最不利分布
, z4 s0 r+ p! u5 r$ w& _Least significant difference, 最小显著差法
- D5 {2 R) S0 FLeast square method, 最小二乘法
% R+ M5 B$ v5 s5 Y, {' \3 N5 h6 fLeast-absolute-residuals estimates, 最小绝对残差估计
" w7 i3 M A5 I Q* A& [Least-absolute-residuals fit, 最小绝对残差拟合
0 y D) @& R+ s) c% E8 [Least-absolute-residuals line, 最小绝对残差线
% Q' m+ M) ?8 WLegend, 图例5 x ]' Y' {' }% L4 P
L-estimator, L估计量
5 c$ Y1 g# a6 g: S7 s# wL-estimator of location, 位置L估计量1 N- Z) C8 q3 U ]/ H
L-estimator of scale, 尺度L估计量
3 Y" v1 j3 x4 c+ C* T+ h$ p6 ?Level, 水平
9 ~" s7 m- `# u P# F% y$ uLife expectance, 预期期望寿命. k. u( ~1 a4 f- O
Life table, 寿命表
' T/ w% P: N0 Z- g) ?0 q, pLife table method, 生命表法. m: g4 A$ I+ `( x
Light-tailed distribution, 轻尾分布
+ e* r0 e+ z, SLikelihood function, 似然函数
& z* v; d1 S9 ~Likelihood ratio, 似然比" Y3 s( w" F1 i
line graph, 线图
3 |6 D3 j7 Q- ^- O5 t) yLinear correlation, 直线相关- h0 N5 x( f5 Q: [/ j
Linear equation, 线性方程8 g- c* V @; Q. i& O' z
Linear programming, 线性规划
$ `1 u X% R# E* FLinear regression, 直线回归* S% h3 S. d1 z* ^5 i
Linear Regression, 线性回归
5 i( p2 a7 ?* w' z+ Y4 vLinear trend, 线性趋势$ Z2 C% N# n+ t/ c& v
Loading, 载荷 |$ ?# o" @) _6 J, ~ Y
Location and scale equivariance, 位置尺度同变性
& O# h7 p& P2 {" WLocation equivariance, 位置同变性& p% V) Q; L1 J, B y1 i
Location invariance, 位置不变性# ~8 N! W0 x6 w1 N0 @- T( _
Location scale family, 位置尺度族# y3 M% F7 `3 a3 \. b7 M& x
Log rank test, 时序检验
8 E/ q# x/ O, I6 z3 d6 H5 HLogarithmic curve, 对数曲线
4 H. {3 M! ]' u& iLogarithmic normal distribution, 对数正态分布/ b# u. [5 N) x* q
Logarithmic scale, 对数尺度) N& L: [6 S$ T6 c; P
Logarithmic transformation, 对数变换
3 l+ K- S3 d* NLogic check, 逻辑检查
8 U- s8 A/ h2 Y$ z/ hLogistic distribution, 逻辑斯特分布
- Z& B* A% |3 W; m z3 cLogit transformation, Logit转换
# X( M6 a! F- q5 d2 ~' RLOGLINEAR, 多维列联表通用模型
9 ]$ f3 ~1 ]: `# k$ rLognormal distribution, 对数正态分布
. U9 ]" p( T' Z. X. ?7 z! u6 ULost function, 损失函数
$ ? R, y& t9 x, P# HLow correlation, 低度相关" t/ j% E4 e* n7 G, Z
Lower limit, 下限- m- q' Y# L; Y/ z, i- f( V5 e0 q0 l
Lowest-attained variance, 最小可达方差
. |+ L1 x" I6 w1 E$ yLSD, 最小显著差法的简称- V9 e. X4 E/ l/ |: V5 P3 y; @
Lurking variable, 潜在变量
2 l6 a; `/ e2 k* ]5 G. } `0 gMain effect, 主效应
. o o& \1 y: |+ _9 _Major heading, 主辞标目
$ x! M* M* |* f1 N, zMarginal density function, 边缘密度函数! F5 R8 W1 _; M s
Marginal probability, 边缘概率
* m7 C C0 w2 r) uMarginal probability distribution, 边缘概率分布/ u/ [, y ]9 u+ v8 m& x
Matched data, 配对资料
* S+ M( Z9 s, s; N) x4 PMatched distribution, 匹配过分布8 u _/ j7 s7 R1 Q4 Q0 A
Matching of distribution, 分布的匹配, N4 r$ Q5 W; ^
Matching of transformation, 变换的匹配3 R* D/ k7 g3 W2 c% g3 l. g" \
Mathematical expectation, 数学期望
: {" i) n S) m7 ^, j, V) ?Mathematical model, 数学模型
, ~; D8 n4 a8 P$ QMaximum L-estimator, 极大极小L 估计量2 ^- ~. o' o3 L! a
Maximum likelihood method, 最大似然法. A1 m. g. ?! Z4 S
Mean, 均数$ n+ P: x* U b
Mean squares between groups, 组间均方
$ ~0 S1 O3 ^ q" `Mean squares within group, 组内均方
5 C$ x( L8 e9 ~0 P' gMeans (Compare means), 均值-均值比较* ? B# Y* D$ K5 u; ~
Median, 中位数* }/ K O; i" {0 F. G8 ^9 F# [( L
Median effective dose, 半数效量
A2 a g0 c% [+ hMedian lethal dose, 半数致死量3 R' }6 X0 ~4 F3 \- \' A& m4 ]
Median polish, 中位数平滑
9 U. v3 [+ l6 J- X: [Median test, 中位数检验
0 R. n+ d/ c! Q& S: u5 l3 {Minimal sufficient statistic, 最小充分统计量
$ \1 Z7 H; B: ]Minimum distance estimation, 最小距离估计
0 U8 v( D! U& }! d, KMinimum effective dose, 最小有效量6 s% f8 y/ e& U" w( F6 C7 g
Minimum lethal dose, 最小致死量/ {1 t" d" B" O
Minimum variance estimator, 最小方差估计量: C* T: @4 A* @1 f8 e% l ]
MINITAB, 统计软件包/ N: Z+ d8 G0 j' b7 Y2 x+ D( F+ D
Minor heading, 宾词标目
) d% z- I3 f& _# i' S: yMissing data, 缺失值( K5 W5 L3 ?- m
Model specification, 模型的确定 h* w1 k6 B2 Y1 ^, H+ N% z
Modeling Statistics , 模型统计
4 _( i7 X! ~& N4 [# qModels for outliers, 离群值模型" h: ^: p* A/ A( d# v' E* j% K
Modifying the model, 模型的修正4 R7 ^5 _, A `1 g
Modulus of continuity, 连续性模
. L- Z+ Z/ g2 c5 J0 o3 M0 YMorbidity, 发病率 % Q4 Z4 E; X2 y8 p
Most favorable configuration, 最有利构形
6 ^- L3 g+ W( ^, t% yMultidimensional Scaling (ASCAL), 多维尺度/多维标度
* o# E- v; S, h2 M6 R. rMultinomial Logistic Regression , 多项逻辑斯蒂回归
, |7 j+ P, w/ X0 n/ RMultiple comparison, 多重比较
2 A% p2 u3 t( [/ xMultiple correlation , 复相关8 E3 x$ G: N1 b5 E5 S
Multiple covariance, 多元协方差, @ t8 C" o% |7 @9 G' F' o
Multiple linear regression, 多元线性回归
7 z& F( Y$ ^0 F! q$ {# Y& o3 w8 N. B# A VMultiple response , 多重选项' Y0 Z5 Q) u# p4 z
Multiple solutions, 多解# @' @' ~( j5 Y. Y& D
Multiplication theorem, 乘法定理
/ s9 p, G1 j& GMultiresponse, 多元响应( Y" t0 `6 k" I
Multi-stage sampling, 多阶段抽样
7 D4 n$ N4 W1 f+ y/ j8 m$ C; u( `+ gMultivariate T distribution, 多元T分布' I: Y) S. ?7 ?$ ?& F% t) M* H0 p
Mutual exclusive, 互不相容
' X( V( a2 ~0 U2 PMutual independence, 互相独立7 v8 p! l; ^5 e8 X( |
Natural boundary, 自然边界* C. p+ W- m6 q5 p4 U
Natural dead, 自然死亡, a0 ]8 k/ K t7 |. ]3 E
Natural zero, 自然零! m4 ~1 c; Q1 a/ R$ y
Negative correlation, 负相关
) p5 F- A5 x3 ^, [* ]1 n. xNegative linear correlation, 负线性相关
! L+ N' v5 m t4 _. T n. ONegatively skewed, 负偏* M# f, `7 X9 i( j/ \
Newman-Keuls method, q检验* l2 P: c r6 Z: Q4 ^
NK method, q检验
. Y. M0 t' G: e- GNo statistical significance, 无统计意义2 C, B3 x" i3 p# z. z3 O
Nominal variable, 名义变量
2 u1 f, H$ t! ^Nonconstancy of variability, 变异的非定常性
& a0 D6 t) |2 }. h: e' iNonlinear regression, 非线性相关 D- P( J$ x6 B) t: O
Nonparametric statistics, 非参数统计
9 b ?7 S! C/ J) w- u: ONonparametric test, 非参数检验% F7 W% Z; ^/ q4 d6 V1 o$ R J
Nonparametric tests, 非参数检验! b5 w+ C/ l: n9 L
Normal deviate, 正态离差1 f* o3 I! h1 [
Normal distribution, 正态分布
D J% a# g- w5 V R* ~7 R* g1 ^Normal equation, 正规方程组
: `$ M! ^9 m* f' l; k7 JNormal ranges, 正常范围! @- T0 Y- U1 z' H5 ~
Normal value, 正常值
, x& Z6 D5 J* H4 t ~" g' rNuisance parameter, 多余参数/讨厌参数
B; k$ j# n: p* @7 }5 y: bNull hypothesis, 无效假设 T8 z# L3 c, O$ a8 d9 R! P }
Numerical variable, 数值变量& N$ d4 f# y# l/ F1 [
Objective function, 目标函数
: Q* @$ l* |: m: r! } e# s+ E/ P8 @Observation unit, 观察单位
3 L+ O, L$ i g) v3 HObserved value, 观察值
; J4 U8 A( \5 _' j0 H8 h7 M# [6 iOne sided test, 单侧检验
8 i% [3 T' P0 d FOne-way analysis of variance, 单因素方差分析
! {7 T$ W# p1 ZOneway ANOVA , 单因素方差分析: T" Y- T; T9 p/ I" c: T
Open sequential trial, 开放型序贯设计
+ E6 h- U3 f! A: \+ UOptrim, 优切尾
2 E: P4 @4 a U5 b+ QOptrim efficiency, 优切尾效率0 d. Z# t% a0 k; t
Order statistics, 顺序统计量
8 X: `) b Z8 L l* `/ FOrdered categories, 有序分类" X$ N% X7 R- U. n% i" {
Ordinal logistic regression , 序数逻辑斯蒂回归
- L6 D5 Y0 B/ n, Z, }Ordinal variable, 有序变量* P$ ~& u* O; q3 j( L) B) e
Orthogonal basis, 正交基. C/ F# y+ L' s
Orthogonal design, 正交试验设计
6 g; }" d+ l' X: p+ t$ l. sOrthogonality conditions, 正交条件2 k/ @/ O7 [0 L
ORTHOPLAN, 正交设计
/ i& I3 u4 }7 h; K* MOutlier cutoffs, 离群值截断点5 r" Q" l' G' \" z2 d5 w9 L& C! }1 j
Outliers, 极端值
2 ~" B% N( T, _2 N( xOVERALS , 多组变量的非线性正规相关
/ Q8 z O. f" U! qOvershoot, 迭代过度1 s3 w. }6 k- c8 J( t5 \( C
Paired design, 配对设计1 H5 h W0 A5 @! Y6 |0 v( v0 Y" \
Paired sample, 配对样本$ o5 Y! ~' x/ e- [
Pairwise slopes, 成对斜率$ t7 N" l; Z5 R6 w
Parabola, 抛物线4 q$ T2 g! I6 ] [0 b
Parallel tests, 平行试验
6 h1 C" h0 u: {4 Q6 \6 pParameter, 参数
& @% P% x3 e5 R+ \8 R" W0 ?, ]Parametric statistics, 参数统计
% ^. g4 y0 d) s* wParametric test, 参数检验
) D3 w8 p: N' s* _Partial correlation, 偏相关# [: O- I3 `+ U& ]7 w# {& t1 |
Partial regression, 偏回归
4 o4 d: D& x1 p/ B2 T* MPartial sorting, 偏排序
: M+ n6 I/ d/ YPartials residuals, 偏残差+ K& Q0 c& ~0 T; `1 b9 R) T" E
Pattern, 模式
" M: b8 A7 S [) a) S5 i0 g9 [Pearson curves, 皮尔逊曲线
% Z) h- o, d, Q2 l) [$ ~Peeling, 退层8 E3 \( X N3 v9 G
Percent bar graph, 百分条形图
2 _ m5 K- `, {9 ` _1 qPercentage, 百分比6 p" l4 ] Q+ {; l4 g- n: z
Percentile, 百分位数& j+ x: d3 r y5 k7 G) M- A
Percentile curves, 百分位曲线
, e$ _) J7 C$ n7 p3 l6 j+ S; QPeriodicity, 周期性
0 B( E) J- A0 w: {Permutation, 排列
0 A; V9 |: Z U! r9 K) fP-estimator, P估计量
& ~- W7 D1 D$ w9 g- a" kPie graph, 饼图
/ }& Z1 Q+ f" PPitman estimator, 皮特曼估计量
$ w7 n7 r0 X- y7 e$ ^! a2 dPivot, 枢轴量, w& j3 C6 d1 ^1 E; j
Planar, 平坦
3 X+ }. a! m# c9 ?9 UPlanar assumption, 平面的假设
4 k( k% { S" S! D: UPLANCARDS, 生成试验的计划卡. r3 n, J# F3 }& O2 } F9 ]
Point estimation, 点估计
: N! E' q$ g/ z2 t( v" \4 ~2 gPoisson distribution, 泊松分布3 W( ^1 b: V" q2 E
Polishing, 平滑
0 Z8 c* g8 y- k3 v3 WPolled standard deviation, 合并标准差
0 X& G# ?) F# s8 ePolled variance, 合并方差
+ A$ J% H& k& ~: Q2 EPolygon, 多边图) [# Z) M- s# N4 F! N
Polynomial, 多项式- W# \) l3 M" T& s5 u
Polynomial curve, 多项式曲线& A& J- ?) A# o# [7 [& }. f
Population, 总体
! X3 [' n& E8 q2 B- l* {2 R4 ~Population attributable risk, 人群归因危险度
l& ~+ |6 J$ J! ]% Z* a% E7 JPositive correlation, 正相关
) L* c/ H. c- [5 WPositively skewed, 正偏' k: ^& b2 `: ~/ v$ q0 m
Posterior distribution, 后验分布% L. T) r2 L; Y
Power of a test, 检验效能2 v- `9 l: \5 u5 ^$ U% Q' X% `" R
Precision, 精密度
5 o" I: ], k7 _0 f! RPredicted value, 预测值5 J1 y& N" b9 t9 A" G# `+ t
Preliminary analysis, 预备性分析! F" @: G/ H) L2 o4 I* D' \
Principal component analysis, 主成分分析, f+ g$ Q( R2 M/ o
Prior distribution, 先验分布5 H! |5 W5 c; \( F( n2 I
Prior probability, 先验概率
( N' Q! [1 \, O7 l# K" oProbabilistic model, 概率模型+ k3 T p: i4 F; n% X) ~# `
probability, 概率
+ |* J! ~8 @# L& E3 q5 IProbability density, 概率密度# S& o0 L2 i4 p5 s( h) n7 N& d; ?
Product moment, 乘积矩/协方差
6 L! B, ]/ K, f! I9 S# kProfile trace, 截面迹图: u9 n; y, y6 I) @* b4 g7 W
Proportion, 比/构成比
4 F8 B n! l8 M1 X! q) } k7 yProportion allocation in stratified random sampling, 按比例分层随机抽样
( T8 C& Q7 S1 I( DProportionate, 成比例1 W8 i0 l2 Z' ~- n) m% j
Proportionate sub-class numbers, 成比例次级组含量! t6 H# n) i3 h/ l( n! d
Prospective study, 前瞻性调查: R8 P9 ~( m6 \( a/ \3 w- I
Proximities, 亲近性 # l7 z& W0 u3 C. f; ]* k" b
Pseudo F test, 近似F检验3 |' C. O( f5 \% {2 v$ e4 H
Pseudo model, 近似模型
( n" I3 T1 Q4 A! v# `1 m6 aPseudosigma, 伪标准差/ _# V* P0 B# n. M
Purposive sampling, 有目的抽样2 O- W( o7 b, a- c
QR decomposition, QR分解
) p! e1 j( w6 ?* L4 `* @& ~, s% lQuadratic approximation, 二次近似# L( C. J9 _0 D5 o; S4 `* u, c
Qualitative classification, 属性分类
: f$ K- I8 f1 D0 [1 _- wQualitative method, 定性方法
" x; K+ _' T8 E7 ZQuantile-quantile plot, 分位数-分位数图/Q-Q图
2 D. @+ ^' i3 uQuantitative analysis, 定量分析
( ^2 p& B( {0 |Quartile, 四分位数
. }7 t! @3 u V0 _3 w: _Quick Cluster, 快速聚类
7 J$ q2 I l- q' eRadix sort, 基数排序" \+ ~4 t4 k! J+ x# c; ?( g9 g9 w
Random allocation, 随机化分组
' A' ]# C$ R* yRandom blocks design, 随机区组设计
4 Z) A; N- y) e6 GRandom event, 随机事件
! w7 Q% P7 p# @) hRandomization, 随机化1 M' c- w: a+ S; |/ B' G% a, h' T
Range, 极差/全距
# D- c, a$ m# U9 _/ ORank correlation, 等级相关
0 \& O5 H* B) r% Y4 X1 J2 kRank sum test, 秩和检验. G0 i: U7 P- Q. i+ v
Rank test, 秩检验
( T1 ]+ m0 w, m/ V) n0 }- t0 HRanked data, 等级资料- Y5 |$ L2 l- Q
Rate, 比率' D1 P$ U! M3 M" Z; ]6 j0 A5 L. K
Ratio, 比例5 G. g" o* C6 D4 c
Raw data, 原始资料# X/ m3 {2 g$ |+ l
Raw residual, 原始残差# ^: ^5 q) Y- J8 u4 h6 L
Rayleigh's test, 雷氏检验5 D9 B7 {9 [- P
Rayleigh's Z, 雷氏Z值
% `' a2 X% |: J& ^, V0 DReciprocal, 倒数
x) x3 x2 g7 N& ^& H) W" \- cReciprocal transformation, 倒数变换
) L) Y+ R- {9 ]% S V* NRecording, 记录2 W! ?5 k2 l2 I: T' V0 C" U$ e. o, d' g
Redescending estimators, 回降估计量3 K6 D. t' n% H$ f* e
Reducing dimensions, 降维
5 C8 P d7 R6 _/ u9 kRe-expression, 重新表达9 h+ {" Y X9 t, h& z
Reference set, 标准组4 D* U: G. s4 |( `# @" K+ F
Region of acceptance, 接受域
5 g: _7 \; V* H; @& XRegression coefficient, 回归系数: |7 t2 F! U0 j5 e1 T0 ~' n4 {
Regression sum of square, 回归平方和
9 v& _: G: A4 A( Y. [; \Rejection point, 拒绝点& o' T% N& H" ]+ z5 Q- q
Relative dispersion, 相对离散度
- x/ ^: U: }# d$ F0 HRelative number, 相对数
3 b# ~5 U# g% M0 O& XReliability, 可靠性
# @# B' l( Z |+ e3 v# pReparametrization, 重新设置参数
; D0 L& X' n5 `Replication, 重复
# F. e3 _# b& H. X5 p8 Y+ X. ~/ QReport Summaries, 报告摘要
- Z3 M0 t7 o. i( Q* u! T* Z4 mResidual sum of square, 剩余平方和: q) I9 o) K2 m
Resistance, 耐抗性
}2 g* X. W& e, H F: z5 E( O* {Resistant line, 耐抗线
* m* Q& b4 u& AResistant technique, 耐抗技术
n# W7 |7 t5 b, F9 o5 K; O) ]" HR-estimator of location, 位置R估计量
4 `' z: @: F; f0 XR-estimator of scale, 尺度R估计量
. Y3 o% m2 d. ?! M; F" uRetrospective study, 回顾性调查2 b$ t0 H2 p P' r: O/ f4 m
Ridge trace, 岭迹
" C7 C G1 ]" V* i* ERidit analysis, Ridit分析& W+ H" U/ Y, J
Rotation, 旋转
& U. m# R) K! lRounding, 舍入: }, L$ F$ R: ^$ [0 \
Row, 行
, l! l3 L+ a! M( Z+ L! o! N# lRow effects, 行效应5 }- Q9 j. R( `0 Y
Row factor, 行因素, \( j& T* J* D+ s" ]9 B
RXC table, RXC表
1 [ L8 \0 W" G) XSample, 样本# i1 X0 l7 p" S
Sample regression coefficient, 样本回归系数
8 ?- r1 c: D* e! b2 FSample size, 样本量 e+ F) Y8 l2 X0 l
Sample standard deviation, 样本标准差
3 i$ a) j8 ?8 F8 \Sampling error, 抽样误差$ r" l/ x* m5 f' E8 Y: H) Q( ~
SAS(Statistical analysis system ), SAS统计软件包
) d* [; ^5 l' l$ FScale, 尺度/量表; K% W0 T/ f* ^0 k
Scatter diagram, 散点图2 F E" y4 n5 X4 P
Schematic plot, 示意图/简图
0 J5 p, ~; f/ NScore test, 计分检验9 g1 S# X; `( [5 h+ o
Screening, 筛检
8 d0 i) i, K. l" H: iSEASON, 季节分析
* n; ~/ d, y) T' A# d# [Second derivative, 二阶导数5 M a% S# R: P; ?
Second principal component, 第二主成分) x1 c1 _& g/ Z% n% s$ D. n* ^4 Y
SEM (Structural equation modeling), 结构化方程模型 4 h5 X7 p- F5 u: K6 y& P: h
Semi-logarithmic graph, 半对数图+ @: W/ K U* Z. @$ s6 K
Semi-logarithmic paper, 半对数格纸, Q9 v6 }# u5 N) b7 w8 u
Sensitivity curve, 敏感度曲线5 N4 e! |5 n! M$ h2 G
Sequential analysis, 贯序分析
" t/ Z9 |1 ^4 }- d& OSequential data set, 顺序数据集
! ^& s$ t% X( F" z M3 d" `% sSequential design, 贯序设计4 `6 X0 e: [/ t, a- p# ]
Sequential method, 贯序法
5 v2 K$ O, e* W1 ?$ X* t7 SSequential test, 贯序检验法
3 Y2 G, ^$ b4 W7 z4 }% a7 pSerial tests, 系列试验
& @' h7 h# R; U( [Short-cut method, 简捷法
- i( G1 N$ J- U: ]; {: }6 BSigmoid curve, S形曲线
$ [6 a( h$ [+ D0 P# x- z0 jSign function, 正负号函数
# _; X: T9 w( t% u% A jSign test, 符号检验
( @+ I8 x9 g$ i3 z) cSigned rank, 符号秩
! C- P( x, E) t6 X+ GSignificance test, 显著性检验: z* P" c5 c$ L! j: d( ^# J) @4 T6 ^
Significant figure, 有效数字
0 L) S5 u; d, U: F4 ASimple cluster sampling, 简单整群抽样
6 o4 s9 P; i* {# e2 TSimple correlation, 简单相关
! W! e! d8 ?$ _- v. ?Simple random sampling, 简单随机抽样/ o) {$ b) X+ F/ r. f
Simple regression, 简单回归0 Z- P, t: V- t; V' R; G* i& a: T1 k
simple table, 简单表% F8 T5 F# ?. ^' {0 R& u) N ^% h
Sine estimator, 正弦估计量
$ Y8 h3 K1 {2 R. m: f& U" S- gSingle-valued estimate, 单值估计7 F) L, q: Y8 n; s. `
Singular matrix, 奇异矩阵
: R D: V* x1 h% E6 u$ NSkewed distribution, 偏斜分布
3 ?% P0 T+ ]; _Skewness, 偏度
; O7 m) P# {, d eSlash distribution, 斜线分布& Y5 u& U3 W3 k: C5 D( L
Slope, 斜率; Y6 S4 v3 Y6 z; Z5 n
Smirnov test, 斯米尔诺夫检验) ? ]0 F8 m7 ^
Source of variation, 变异来源( r: Q5 `2 Q2 c/ S4 N0 c3 X
Spearman rank correlation, 斯皮尔曼等级相关! V2 P3 A7 m' d4 K
Specific factor, 特殊因子7 n! [& j1 j4 }" @- c3 ?
Specific factor variance, 特殊因子方差* L+ `, O1 J( G# p) Q6 I
Spectra , 频谱
* Z4 m- |; ~9 W6 j' E/ H: _Spherical distribution, 球型正态分布
* q/ s) q) ^) [# U5 d+ nSpread, 展布& _: j" \& W) f3 t: U+ i! e
SPSS(Statistical package for the social science), SPSS统计软件包, O" g1 _+ Y2 I* j
Spurious correlation, 假性相关
- ]$ y% O' ~- s2 w% }) _Square root transformation, 平方根变换
% I: T) N: `" {4 X9 RStabilizing variance, 稳定方差/ V8 Q: w' f0 X; u" a9 b0 L
Standard deviation, 标准差
_9 j, a* i+ q8 |+ HStandard error, 标准误1 c+ S& u- l+ a \+ v9 h
Standard error of difference, 差别的标准误7 b2 @! ^6 k, q$ W" q
Standard error of estimate, 标准估计误差
+ u1 ]2 E# ^. u/ s- ^Standard error of rate, 率的标准误# w$ p% b4 E- x8 N
Standard normal distribution, 标准正态分布" E; A) {6 u) p% ~ V9 I
Standardization, 标准化
0 |- |& g0 v( s" J, P- u* hStarting value, 起始值6 k: O$ J- } _9 K3 `" }. b) }5 Y
Statistic, 统计量4 v3 V$ o" S% ^
Statistical control, 统计控制) [7 z5 U, N9 g1 c& x
Statistical graph, 统计图& S; R2 i& a% x- k
Statistical inference, 统计推断& {+ ^+ Z$ b9 X& w$ S
Statistical table, 统计表5 ?* y' ]: P; @4 {. h3 t# `: ~4 c4 o) W
Steepest descent, 最速下降法
) j6 x/ v- d5 |' YStem and leaf display, 茎叶图/ Y9 h* q. y1 V* o& b4 C6 A+ j, ?1 h
Step factor, 步长因子
: W2 ?1 d" F& PStepwise regression, 逐步回归
) }' o9 @7 o5 s2 U% \/ UStorage, 存
; q3 X [6 C: ]: L4 }- Y3 ]Strata, 层（复数）
- i& l" }9 d- q, s# G6 M! UStratified sampling, 分层抽样! D: D) W3 J3 m# t: K4 r
Stratified sampling, 分层抽样
7 }* P9 B, H2 K, f- L TStrength, 强度
$ r5 P5 T0 T: ?# o3 I) H! i' lStringency, 严密性
% z. K: h7 s5 E$ t3 }+ wStructural relationship, 结构关系: y. |2 B6 j; H
Studentized residual, 学生化残差/t化残差 ]6 N, e0 o+ j5 ?9 _$ }. _
Sub-class numbers, 次级组含量
$ y& n; _, a+ h, a4 wSubdividing, 分割
: e; D- f, o$ z9 W4 F% k. s6 QSufficient statistic, 充分统计量) V8 @" `/ A, |4 P
Sum of products, 积和
6 R( N8 W1 q6 Z1 `3 |: F1 w* aSum of squares, 离差平方和
) D; ]. z* H# O/ N2 l/ tSum of squares about regression, 回归平方和+ h7 U: e" C- {, ?+ l* b: _
Sum of squares between groups, 组间平方和
* i9 _0 b! n# U: N9 h m: BSum of squares of partial regression, 偏回归平方和# j( u+ v% M$ a, n! t& J
Sure event, 必然事件* F% U' G% ?, Y! W- u
Survey, 调查
9 ^$ Q" L) H# Y1 a: |Survival, 生存分析% \; \# v, |9 J3 s& d
Survival rate, 生存率5 W7 F p5 Q3 n/ h# [+ H
Suspended root gram, 悬吊根图
1 M* n) S* [; Y$ {9 USymmetry, 对称3 P* g- \# M- Z0 L) A- \# V
Systematic error, 系统误差' G! ^1 }. j! S% ~6 L' A
Systematic sampling, 系统抽样) V S4 L" E6 p' _' v
Tags, 标签5 R* x( g+ E5 w% t; }( {
Tail area, 尾部面积5 p/ b7 B5 K! v: y
Tail length, 尾长
" L7 C0 R# b& m5 W1 N- zTail weight, 尾重8 Z+ Z+ }3 `2 \) \5 R& {0 B/ `) N! W8 h
Tangent line, 切线
- L/ D/ D% k7 @5 ~- w5 w' ~1 VTarget distribution, 目标分布
- A6 j1 J _$ w+ |# ITaylor series, 泰勒级数. _/ P# I: k& l& L% c0 |
Tendency of dispersion, 离散趋势
% P$ w: h3 U2 a ^+ Z* Y( NTesting of hypotheses, 假设检验
0 f" x9 H3 `0 D, @" UTheoretical frequency, 理论频数
0 D2 X9 _3 W! }8 o4 ^* W+ @, `! yTime series, 时间序列
- l+ S+ q: y6 HTolerance interval, 容忍区间' [% T5 v, L4 W* J% r7 i
Tolerance lower limit, 容忍下限
; a( I& S6 E/ Z/ }5 `Tolerance upper limit, 容忍上限# f) b. s) B; L! d8 M
Torsion, 扰率+ T' [' Z3 T9 X, Y/ }1 y
Total sum of square, 总平方和
4 i/ @7 W5 j) q/ P4 ^* ETotal variation, 总变异% X* Z8 c/ |; `1 i( V
Transformation, 转换5 D+ V2 m7 s7 z" }( u8 _
Treatment, 处理; k, i7 \( q/ V+ B/ P/ ^$ a
Trend, 趋势
6 } }6 i8 c) w3 ITrend of percentage, 百分比趋势
5 ?- U0 E! {& g6 g+ @2 G8 ~Trial, 试验7 g: b% i3 B# e8 A
Trial and error method, 试错法
9 M2 b( W5 e- k! _Tuning constant, 细调常数' |8 ~* q e9 H) R! u9 }
Two sided test, 双向检验
2 I; s4 a5 P% O( h' Z. ^# bTwo-stage least squares, 二阶最小平方7 E, K2 T& i) a
Two-stage sampling, 二阶段抽样
, c Y0 f1 W; A; }( ^) ~Two-tailed test, 双侧检验
5 _* g- v% L5 S+ l2 eTwo-way analysis of variance, 双因素方差分析2 E) _: t7 A+ Q
Two-way table, 双向表
5 P9 u( J% v H+ z' fType I error, 一类错误/α错误
* U8 G% W7 V$ g! G$ ~) ~4 KType II error, 二类错误/β错误
5 x$ A( y1 n+ ?( p/ d* v0 lUMVU, 方差一致最小无偏估计简称
; e' M% u2 f, ?& \; YUnbiased estimate, 无偏估计2 v) _6 w. F! V* Q
Unconstrained nonlinear regression , 无约束非线性回归% t% j/ X# c- k5 {+ X1 h. i; O# g
Unequal subclass number, 不等次级组含量
8 m, R* d6 O4 l, C' GUngrouped data, 不分组资料
7 X7 H/ k0 b4 O4 B: |, w: {Uniform coordinate, 均匀坐标# N5 W6 r/ n: a5 ?6 |# R1 q3 u
Uniform distribution, 均匀分布* q5 x$ ^+ Z- i/ _" ^
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
' W- z' W. O9 W; g" jUnit, 单元0 t4 H4 M' ]) e- o
Unordered categories, 无序分类. U4 h, e$ h" j b, h
Upper limit, 上限: q; R' z3 U+ K! i
Upward rank, 升秩
" J) `1 [, G; g+ EVague concept, 模糊概念3 x# x$ V D H U7 D. I
Validity, 有效性0 q1 `- e& ^/ H/ D
VARCOMP (Variance component estimation), 方差元素估计
8 L+ k0 J* `- g m, n; eVariability, 变异性3 m. t% U9 K7 `# F2 s' f6 T6 k
Variable, 变量
E7 w7 _; q& Y/ b9 p" u+ PVariance, 方差
: k6 Y* b. h% L# q2 G' ~Variation, 变异- B) {- ~2 ^, r! s
Varimax orthogonal rotation, 方差最大正交旋转
) B+ H0 z- {' @6 X) G0 J! r3 @. |Volume of distribution, 容积/ `6 O1 \6 v, o4 N& J
W test, W检验; Y7 y- d6 P7 S) A* B, S) A( [
Weibull distribution, 威布尔分布
+ h& N2 c# [# DWeight, 权数
9 X" W4 L% A" D6 PWeighted Chi-square test, 加权卡方检验/Cochran检验: n0 a5 w* k( E
Weighted linear regression method, 加权直线回归5 ~1 k7 L: o$ t
Weighted mean, 加权平均数/ _2 S7 E: {! d! j
Weighted mean square, 加权平均方差
. Z" X6 y9 |4 ~2 J0 rWeighted sum of square, 加权平方和$ R, k8 u) _) {$ ?# f! m4 k
Weighting coefficient, 权重系数2 Q3 S1 ?+ i1 [3 Q- L8 r4 h6 h
Weighting method, 加权法
: }2 M+ S- J5 k; v e: i) JW-estimation, W估计量8 k# P3 ]' S1 t
W-estimation of location, 位置W估计量. X0 N9 s! r) C1 B! @
Width, 宽度2 M% N- v* M, A
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
9 U' g( H' m4 N T- q9 N! SWild point, 野点/狂点
. J/ z* b _4 v2 Q) {) oWild value, 野值/狂值
. S/ H, O0 l8 w. h( Q' T) EWinsorized mean, 缩尾均值
1 O) O; y% K* C/ H( rWithdraw, 失访 1 J- N& @1 P- Z8 ?! z
Youden's index, 尤登指数
H: Y' y9 e4 u" Q& ZZ test, Z检验1 Y" r+ t X1 F; k8 H; Y8 X9 ?
Zero correlation, 零相关
5 X! M$ g; k. c) tZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
