|
|
Absolute deviation, 绝对离差# C& C; _6 F x
Absolute number, 绝对数
4 f7 }6 \% \* N7 q* J zAbsolute residuals, 绝对残差
& Z$ _, }" t0 _2 j8 P0 j1 PAcceleration array, 加速度立体阵
4 I3 ?% z7 m- LAcceleration in an arbitrary direction, 任意方向上的加速度
% ^# [4 s* J* ^ V, `Acceleration normal, 法向加速度
6 y3 b6 d5 m7 Z9 c& F. c P; VAcceleration space dimension, 加速度空间的维数
! p/ b0 {9 h7 F0 C7 j, pAcceleration tangential, 切向加速度* S1 X" t9 T6 |1 Q! i
Acceleration vector, 加速度向量1 S) F+ P8 [& E Q! u# i
Acceptable hypothesis, 可接受假设' `/ g" j: g6 x2 L3 g( J( p
Accumulation, 累积, ^+ w5 _( p6 ^2 a7 O8 H% y. d3 K
Accuracy, 准确度1 ?4 ^# b4 ^6 t9 Z+ y; O
Actual frequency, 实际频数, \- V. T8 U! x3 ]4 A( J
Adaptive estimator, 自适应估计量
$ G- E" }0 A4 }- }Addition, 相加
8 D5 R& ^1 U$ I0 }1 w- CAddition theorem, 加法定理/ T+ D" E& r# _
Additivity, 可加性$ ^/ L/ `' t6 n& j" ^6 D0 j- b
Adjusted rate, 调整率
1 ?3 i9 A9 {; @" Y# @( p; [# kAdjusted value, 校正值
: [, P% p# a9 T: }9 E0 PAdmissible error, 容许误差
5 ?# X1 T0 n' C3 O# t' nAggregation, 聚集性2 R% p" V- O7 a, c; c
Alternative hypothesis, 备择假设
9 l1 {8 u+ R3 ]( pAmong groups, 组间6 f* u4 d( Q- D+ \
Amounts, 总量
7 a+ m, m! C$ V8 \Analysis of correlation, 相关分析
& I- }3 a3 [6 rAnalysis of covariance, 协方差分析: R+ G7 G9 a$ a2 y4 Z) Y& }- D
Analysis of regression, 回归分析) u& m/ y5 \+ e5 U$ K9 G
Analysis of time series, 时间序列分析
# W+ g0 e' F) [ @+ S# n* |Analysis of variance, 方差分析
7 X, N2 |( \) G5 J; f+ a* \/ VAngular transformation, 角转换, L8 L9 ~% y3 ~8 w5 \: e0 m
ANOVA （analysis of variance）, 方差分析
: V; {- u- O \- ^( a, Q$ OANOVA Models, 方差分析模型
$ R' `1 P" G! f$ g. w# a' OArcing, 弧/弧旋0 G; ?* T( ^+ \# S+ a
Arcsine transformation, 反正弦变换
) T% |1 I5 I) c# Q% W0 WArea under the curve, 曲线面积6 F$ t- q, u) D1 y/ L9 f5 ~/ O
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 6 D/ i- u' B3 J
ARIMA, 季节和非季节性单变量模型的极大似然估计
$ N/ X8 f* x5 z; d4 W* bArithmetic grid paper, 算术格纸6 p, A1 M5 Q! ~- P# v1 @
Arithmetic mean, 算术平均数 Z5 c. d7 g& |2 [
Arrhenius relation, 艾恩尼斯关系
% T8 s+ z# K0 HAssessing fit, 拟合的评估# \( Z2 J& f4 J% C( A" ^
Associative laws, 结合律4 m( U d: L! r' `' K
Asymmetric distribution, 非对称分布, S: k! q0 M* y2 S# i* B
Asymptotic bias, 渐近偏倚
! a5 T" K6 X8 ?* f" {Asymptotic efficiency, 渐近效率
& n3 s8 d$ t" P) S. {. z* ]Asymptotic variance, 渐近方差+ ?) N- p6 b/ F P R, _
Attributable risk, 归因危险度- X# ?6 ~* G+ A3 E, `; c( `2 P
Attribute data, 属性资料
, l. a, x) P4 {3 ^7 \' R& @! H7 c) PAttribution, 属性
/ G' h& _& y& yAutocorrelation, 自相关) \/ u, O2 q5 m5 b# R
Autocorrelation of residuals, 残差的自相关
" {) U+ a4 u3 ~8 ~Average, 平均数4 u1 S$ W% N0 p+ _ q
Average confidence interval length, 平均置信区间长度
/ H ]4 F+ i# w3 h- b; z6 c7 x0 iAverage growth rate, 平均增长率
. a" C ?1 ^, Y5 `Bar chart, 条形图$ _: r$ Z* s, l6 r+ @$ s% s
Bar graph, 条形图' {! _ ]( \# |% H1 b
Base period, 基期
J" V( ^7 n# M \9 }Bayes' theorem , Bayes定理3 z6 ^7 A3 S: d& ?4 B' S/ G+ f" D
Bell-shaped curve, 钟形曲线
1 g+ e6 _7 }1 V2 lBernoulli distribution, 伯努力分布3 R9 W+ C. [. M3 Z
Best-trim estimator, 最好切尾估计量3 }+ `3 q" H1 ]* C; }8 Z6 }8 j% t
Bias, 偏性6 }& Y; [4 P/ q+ s
Binary logistic regression, 二元逻辑斯蒂回归6 ?2 I/ O9 g) g& v
Binomial distribution, 二项分布
0 K% v. z# {7 M2 |$ K8 Q( b/ TBisquare, 双平方( `7 r) a" h5 T& F0 p
Bivariate Correlate, 二变量相关3 \6 M/ O! J* |# C
Bivariate normal distribution, 双变量正态分布# g1 @4 U$ p" D0 \* t
Bivariate normal population, 双变量正态总体: F8 U# ?) d: B" D/ m* U# J
Biweight interval, 双权区间, v, K" Y3 |3 }& }3 r0 ]
Biweight M-estimator, 双权M估计量
5 o2 S X+ y7 t- ?Block, 区组/配伍组
* V; v) z& A0 m+ QBMDP(Biomedical computer programs), BMDP统计软件包: t+ g+ b' ~" P z9 [
Boxplots, 箱线图/箱尾图6 P' W% x& T6 q: |, p0 ^: l
Breakdown bound, 崩溃界/崩溃点7 o. ?( B, x1 S, i3 v+ Q8 C6 \" m P1 ~
Canonical correlation, 典型相关" {8 `8 r& Q' H: |
Caption, 纵标目: c5 a& g7 u# P: p5 A
Case-control study, 病例对照研究
/ Y' w6 i5 \* C- V, n3 s* lCategorical variable, 分类变量2 s. P5 \) J m: @: O
Catenary, 悬链线$ b: ?* s% Z4 Y' C4 _! N
Cauchy distribution, 柯西分布- n4 A1 ?5 Q2 e2 _
Cause-and-effect relationship, 因果关系' C8 `* {$ |( [3 c$ L
Cell, 单元
$ d! Y& ^; B3 Z$ |% wCensoring, 终检
6 K8 H, m2 q! w1 RCenter of symmetry, 对称中心
, j; ^- w2 C3 ]" S0 \Centering and scaling, 中心化和定标6 F: Q W9 L4 T9 p! M
Central tendency, 集中趋势5 E$ P* F1 \: Q1 B# v. K) i
Central value, 中心值
& h4 h% m2 Y$ {CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测# f7 A0 R1 v: T8 O+ V/ |0 Y
Chance, 机遇; W& d/ f; K8 {
Chance error, 随机误差( Y6 ^ l5 x( n* T+ ]' u; g, c
Chance variable, 随机变量
% a0 ]' s# A7 z9 m1 TCharacteristic equation, 特征方程
! ]" h4 v2 j0 D4 ^3 F/ SCharacteristic root, 特征根. V" i0 Z- Y9 t$ z5 P, p4 V7 m
Characteristic vector, 特征向量
. Q+ v# D J2 AChebshev criterion of fit, 拟合的切比雪夫准则7 ]4 S# Z, Q y5 [
Chernoff faces, 切尔诺夫脸谱图) M* F0 }) ~/ y, H4 {
Chi-square test, 卡方检验/χ2检验* E8 I& T8 z7 f# @
Choleskey decomposition, 乔洛斯基分解) s! N, j I. z) u) |) |( I5 p+ A* A
Circle chart, 圆图 : J5 s4 Q6 Z$ f C# ^6 G2 u
Class interval, 组距
# N# b# m* S+ z# D) w8 T4 T2 SClass mid-value, 组中值$ Z; P8 f( X; E- W
Class upper limit, 组上限
( r9 P% r9 H, D0 yClassified variable, 分类变量6 ]6 \2 e% b" ?
Cluster analysis, 聚类分析
2 y# g" s, L% b% ?( T6 NCluster sampling, 整群抽样8 D2 _. O; T$ f2 i
Code, 代码
2 c' _- b1 U9 LCoded data, 编码数据
6 Y; C$ M$ \" r% SCoding, 编码3 ?$ U. r' u' Q8 B% I5 Y- v
Coefficient of contingency, 列联系数
" h8 Q! F# z' c* Q7 _4 Q' qCoefficient of determination, 决定系数
2 N. b: i1 ]7 ]& k& gCoefficient of multiple correlation, 多重相关系数
( Z$ F* A9 j! B, I7 bCoefficient of partial correlation, 偏相关系数
: w/ C) L) E/ a* sCoefficient of production-moment correlation, 积差相关系数
. ?) L* N2 H9 g- _. E! K4 yCoefficient of rank correlation, 等级相关系数! N% z: I+ H4 D
Coefficient of regression, 回归系数0 ?3 E5 G: v5 r0 a6 R" S
Coefficient of skewness, 偏度系数
7 r0 ~; |: \# N, dCoefficient of variation, 变异系数 W- c. A: ?( K2 m- l7 X
Cohort study, 队列研究8 o% e8 ]& Y3 p& I5 u; R7 m* l
Column, 列
5 H& j9 A5 k& z: |8 \Column effect, 列效应( W/ n( k% K! s3 [- J) S+ ~7 E. F4 z
Column factor, 列因素9 l: |* F3 Q' m) S1 T' f* E0 ]
Combination pool, 合并
/ M, D# @" [% X2 M& pCombinative table, 组合表: ]) M& ]( y. h
Common factor, 共性因子, {3 U, n6 O/ _8 F9 B f
Common regression coefficient, 公共回归系数2 j) N) u( S7 ?. q9 p6 q
Common value, 共同值9 R0 Y: ~/ d$ `$ N5 _( A. Q
Common variance, 公共方差
i( ]0 L2 I/ u) A R! }# H- ~3 sCommon variation, 公共变异& E1 L4 u+ a2 _: I+ @. d% |: \
Communality variance, 共性方差
# T( N, g# w% Z2 O5 yComparability, 可比性
+ N4 H6 r( T9 u+ T$ QComparison of bathes, 批比较
* a: ?$ _8 E7 [, `8 V% cComparison value, 比较值: h7 p" \' F6 L8 e4 z' C9 v
Compartment model, 分部模型
6 g2 S! y, a1 U; p9 }. N3 a! LCompassion, 伸缩
, n8 C4 k/ K; o9 P) yComplement of an event, 补事件( m/ A9 d( `; c' l* q, G$ `. t; V
Complete association, 完全正相关
! C0 j' f s* h! q3 dComplete dissociation, 完全不相关
* S4 f, R/ ^7 x1 BComplete statistics, 完备统计量: k% n9 d8 x; A8 P: f
Completely randomized design, 完全随机化设计
* q0 g( g; b" {3 f- y2 b3 NComposite event, 联合事件# K) D1 @& j' j6 u" [
Composite events, 复合事件
# H0 V; E r" U, M2 Q, R7 }4 g* E# x3 tConcavity, 凹性
/ Q( {* s+ b, Z$ N8 `. N: [* sConditional expectation, 条件期望
/ P0 `7 U0 n) I. c% H4 w2 ?Conditional likelihood, 条件似然3 F) s- |7 b/ E$ i5 P
Conditional probability, 条件概率
- U0 Z, @9 U# b- f: MConditionally linear, 依条件线性
1 |5 J9 }* x. k7 H2 M9 y- P$ ]; UConfidence interval, 置信区间! Q3 {6 R" o$ B. E
Confidence limit, 置信限3 [% x* _3 i" |# u
Confidence lower limit, 置信下限8 X, s5 t( `3 `+ V0 M
Confidence upper limit, 置信上限
3 v& \# `; D7 OConfirmatory Factor Analysis , 验证性因子分析% Y; A/ g$ R2 |$ M0 E' @
Confirmatory research, 证实性实验研究
) {: V9 X! w+ w; {Confounding factor, 混杂因素
2 o. e; O8 W$ Y; GConjoint, 联合分析# J9 b8 {% w; r
Consistency, 相合性, r% i5 B# n7 ~2 [0 c# Z) [1 G5 C. W
Consistency check, 一致性检验$ v/ T% g+ ^$ J9 k- c8 m( r( @2 f( {
Consistent asymptotically normal estimate, 相合渐近正态估计6 Q- K! t5 N4 [7 }. y
Consistent estimate, 相合估计7 {, l8 k! R8 ?3 Z- j, Z+ Z
Constrained nonlinear regression, 受约束非线性回归
$ G0 S* m$ O/ b4 c6 C/ DConstraint, 约束
7 O6 w/ ^, e UContaminated distribution, 污染分布# G# l% t0 K4 k9 i
Contaminated Gausssian, 污染高斯分布1 Q, A& [/ L. J* D5 K
Contaminated normal distribution, 污染正态分布; D5 s& }7 c, P1 ?! c* b4 g
Contamination, 污染
# {8 x: n3 H2 o7 ], U5 e: {Contamination model, 污染模型
" K/ w! {6 R4 y9 W1 e- \6 h- m4 s nContingency table, 列联表
0 p0 {: \- y( }3 G: L9 O. d$ JContour, 边界线
7 D0 v, [2 P: C- Y+ t: AContribution rate, 贡献率( f' [' d& r. G2 [8 r8 a; ?, I6 d
Control, 对照
* l' }! c( J, E8 u4 B$ TControlled experiments, 对照实验4 d! ] a& `6 V2 @6 F
Conventional depth, 常规深度2 ]$ i8 e) u+ R7 x3 e
Convolution, 卷积: O, I1 ?) l, N" k* m8 R
Corrected factor, 校正因子- l7 h. x: S$ L/ m, {4 M8 }! D* M
Corrected mean, 校正均值& l- v( V9 ^! m6 c5 n
Correction coefficient, 校正系数3 u8 |$ ]: A+ H) {' R: N
Correctness, 正确性
9 Z! ^& O, Z5 k0 n5 C' [Correlation coefficient, 相关系数& A6 F9 b0 P& D5 _6 g5 r
Correlation index, 相关指数
" h+ h: n0 {$ V0 j0 v& d# rCorrespondence, 对应
1 }6 v2 y+ U; D6 Q. M6 Z; oCounting, 计数
1 }; n; ]% T* }Counts, 计数/频数% l4 z1 { F" S
Covariance, 协方差+ I% h" B( F" f, ? ~3 {, t
Covariant, 共变
E# S& v% S+ d+ k7 YCox Regression, Cox回归
: H8 T" x% W4 w+ T/ T# k$ nCriteria for fitting, 拟合准则$ e( t( p; ?9 R* ^& [6 a' c
Criteria of least squares, 最小二乘准则
. u) `+ X* Z" Q4 ~7 m- h4 {* j6 m5 t$ kCritical ratio, 临界比
$ L/ y$ z$ C: _; m6 \4 bCritical region, 拒绝域 E9 Q Z- T7 s8 y9 X% ~- r3 _
Critical value, 临界值; K T O; j& _) @5 R
Cross-over design, 交叉设计
* m. U8 T' C" F. XCross-section analysis, 横断面分析
2 N; n7 `8 u; x- }! `( R! X- `Cross-section survey, 横断面调查
; p/ K1 W5 X7 O4 rCrosstabs , 交叉表 + b" Y* W y6 v- J& s# C
Cross-tabulation table, 复合表
( ?$ h3 o1 e+ E% t: e" \8 ^Cube root, 立方根9 `7 ]" p# D- K9 P. D1 \" y
Cumulative distribution function, 分布函数
7 k: @0 r( X2 i) ?! wCumulative probability, 累计概率4 ]! U9 s; `( q: s8 n
Curvature, 曲率/弯曲9 \7 ^" ]! U0 \; C
Curvature, 曲率( S& a" o0 A" n* S0 L
Curve fit , 曲线拟和 # ?' F+ X1 I, m* m2 Z# x8 T% A
Curve fitting, 曲线拟合
% f& J$ b2 A( pCurvilinear regression, 曲线回归9 W3 s4 x9 F' E2 {6 }2 L6 }
Curvilinear relation, 曲线关系$ x7 J$ Q- B4 D5 A5 _ n
Cut-and-try method, 尝试法0 x! ]$ t. t; }0 p: V9 h0 _3 D
Cycle, 周期* x" s- ^- d, ]
Cyclist, 周期性
- C% C& D# h1 UD test, D检验
2 `; u; G9 L% V1 v& U2 HData acquisition, 资料收集
5 E5 x* [8 y. Z5 Q2 N+ E7 x/ bData bank, 数据库1 r" w% o$ y+ ^9 s3 p) j
Data capacity, 数据容量; M2 Y# ?% [) Z5 Y
Data deficiencies, 数据缺乏! d+ y- l9 x3 t# z
Data handling, 数据处理
! A8 z/ f# C6 I% O) HData manipulation, 数据处理
& q8 }( q+ u" j1 a1 M S5 g" A ~1 }' c, FData processing, 数据处理0 w2 G1 O/ Y2 k- u/ ]- r
Data reduction, 数据缩减6 M8 m2 T J! b) ^* W+ C/ O
Data set, 数据集
/ K- @& A2 ]6 j' Y M6 M9 E( L3 }; A- _Data sources, 数据来源& z4 \9 s6 x2 Z b
Data transformation, 数据变换! z, N3 C2 K, @- Z0 g( \
Data validity, 数据有效性7 A- S$ u' S; ?$ N# w+ m
Data-in, 数据输入. S. o( u" Y: ?: S3 t
Data-out, 数据输出
8 ^- m* N* L1 \$ BDead time, 停滞期8 x; i! w7 A% M/ C( F
Degree of freedom, 自由度
7 c! Z5 A( h% ` C) m4 i8 X3 }3 nDegree of precision, 精密度
1 T& W0 d7 x$ J& P4 WDegree of reliability, 可靠性程度. H$ }% [/ H+ V0 Z% n! u8 R
Degression, 递减
, w7 P! B# y; k5 K/ ZDensity function, 密度函数
8 J/ [$ E9 Q, X8 g& a' ]Density of data points, 数据点的密度) R; b( \/ Q( A9 }+ t$ C
Dependent variable, 应变量/依变量/因变量
f( S6 Q( B4 @# A7 oDependent variable, 因变量, J* F/ B. n6 E; P2 S9 H
Depth, 深度
& a7 [0 h2 h* i. ^: w( t$ HDerivative matrix, 导数矩阵0 \' v/ r3 C0 f5 W
Derivative-free methods, 无导数方法8 q2 E) B: X( ?
Design, 设计
- C* E9 P, L: p7 S* xDeterminacy, 确定性7 X1 W& O3 v0 [' p, R/ M' d+ q$ a) V
Determinant, 行列式2 P1 w& q$ F( q% F2 u+ [. G: f. F3 V
Determinant, 决定因素
$ b+ P- T0 U: U/ d" K, {) g) G6 \Deviation, 离差
5 I- ]& D$ u r9 [/ gDeviation from average, 离均差* C: {$ N1 h) x: u
Diagnostic plot, 诊断图
' X, O* R" R. Z2 ?, E) yDichotomous variable, 二分变量+ ~* d! }$ |; X) |( [
Differential equation, 微分方程
' }/ Z( Q/ p Z {Direct standardization, 直接标准化法
7 ~ B/ r! h9 z; ?9 {: O' x9 }Discrete variable, 离散型变量; ` U# M# ^9 ]+ r9 x
DISCRIMINANT, 判断 0 ]% D6 n1 `. v( a) d9 h6 y1 A. `
Discriminant analysis, 判别分析
9 C$ `, P9 h7 C: xDiscriminant coefficient, 判别系数
$ ?. |/ x; x; Y" x, VDiscriminant function, 判别值( ~& f1 J2 b: J: V9 r+ o
Dispersion, 散布/分散度
7 G8 H9 c% A5 X* T- p6 s' `Disproportional, 不成比例的
+ n3 v0 \6 @+ QDisproportionate sub-class numbers, 不成比例次级组含量
8 i$ Z% z, L& n4 s$ G" }Distribution free, 分布无关性/免分布# ^' a# N# `, T6 x# m! `+ y3 B- `
Distribution shape, 分布形状4 {' O9 _& M& ^) U5 m
Distribution-free method, 任意分布法
9 E- B' o* a% q. R( I. P& eDistributive laws, 分配律
; F8 X% o8 u% X6 i2 Q% LDisturbance, 随机扰动项 A6 N8 ~# m3 u: W$ v a
Dose response curve, 剂量反应曲线, R8 Q* K+ H: a
Double blind method, 双盲法
8 d# i5 A- z/ SDouble blind trial, 双盲试验
& O) u9 W" R. `9 q6 R: SDouble exponential distribution, 双指数分布. D3 t0 _, F$ ]7 s# _- {: D
Double logarithmic, 双对数1 ?( H; j# Q5 x8 K$ W1 S& O) ^. t
Downward rank, 降秩2 p7 c v( B' K: K3 @
Dual-space plot, 对偶空间图3 V; s7 y' A/ P8 w: S. ?: b" s
DUD, 无导数方法/ _: b. ^8 ]3 W
Duncan's new multiple range method, 新复极差法/Duncan新法
$ G# m3 [, {; w% lEffect, 实验效应
$ M" V# r( g; _Eigenvalue, 特征值1 \1 \3 b4 U9 {: I4 G9 ^5 r9 E! d: a
Eigenvector, 特征向量
5 `: N( v; O, m& e" \& {Ellipse, 椭圆 x6 }' @" O! b {
Empirical distribution, 经验分布1 z- T' m" i; r2 `4 u8 o* Y [4 ~
Empirical probability, 经验概率单位
% T1 K2 a0 {5 S5 x9 T& u- pEnumeration data, 计数资料: Q" D- Y6 J) G2 S4 ]
Equal sun-class number, 相等次级组含量
0 L7 f7 N5 K8 r( f" V; ?& F$ ?! PEqually likely, 等可能0 g0 I8 [! L1 g7 F" P1 Z+ w$ N
Equivariance, 同变性, n8 C" m/ e% K0 A+ `1 @, `
Error, 误差/错误- C3 t* g; J- X4 [- w
Error of estimate, 估计误差: U. m* c% b3 c: b1 V! T
Error type I, 第一类错误+ b: D* P/ u/ i8 d( {0 n. b
Error type II, 第二类错误
2 i* y8 r/ L4 F( H" KEstimand, 被估量5 |! N$ c& l: @$ l% A
Estimated error mean squares, 估计误差均方8 u' w* f% E3 W0 o; y% a W; S/ g4 a
Estimated error sum of squares, 估计误差平方和7 O" @& Q4 O( A) {/ _
Euclidean distance, 欧式距离1 L9 R; O! C- S) u$ m: Q
Event, 事件& k2 M; Q1 e4 V- F0 o" I
Event, 事件, d- Q- l7 s8 A! h0 J( s* l
Exceptional data point, 异常数据点
$ T( ?9 ?/ {+ J6 R1 }9 g) I8 e+ A, hExpectation plane, 期望平面8 A* L5 _4 G2 M: l+ U# W
Expectation surface, 期望曲面1 ]0 X! T0 q. `, u& g
Expected values, 期望值
+ Z) x5 _4 ?0 {9 T7 ~' fExperiment, 实验; b- Z; `& N" Z a) a. T
Experimental sampling, 试验抽样. }6 _7 b0 e, g6 c
Experimental unit, 试验单位
* F) Z* E% [" q3 r ^8 d" LExplanatory variable, 说明变量* I6 n; _- ?1 b
Exploratory data analysis, 探索性数据分析
; r8 F g6 s8 G* N2 { J! kExplore Summarize, 探索-摘要 b. W e, C& _2 Q" b2 ]
Exponential curve, 指数曲线' B2 d% u S: z1 F P7 e
Exponential growth, 指数式增长2 k3 c' j, c) l6 g
EXSMOOTH, 指数平滑方法
3 j9 Q* H M; |. gExtended fit, 扩充拟合4 P$ E' s5 T* C; c! ?) f0 J
Extra parameter, 附加参数2 a0 ~5 C( N2 ~, o
Extrapolation, 外推法
7 n, U& W2 Q6 m5 tExtreme observation, 末端观测值
U( N% |1 m% _3 I h" kExtremes, 极端值/极值- z0 Q" `' z3 z$ u6 z# b
F distribution, F分布
& F/ G8 c) ?0 HF test, F检验
1 o& n2 T7 i" K& tFactor, 因素/因子0 S1 @/ k8 a A* q
Factor analysis, 因子分析
# W/ c8 R; N G$ \% Y2 wFactor Analysis, 因子分析) q' V! j1 h. I) x7 z
Factor score, 因子得分
) t- ?. r6 M/ u9 a! I NFactorial, 阶乘* M- \+ y9 g9 n5 N* R
Factorial design, 析因试验设计, r. n1 Y" V0 C; P4 ^: s
False negative, 假阴性- H1 W( b7 o+ x3 V/ c
False negative error, 假阴性错误
# K4 r- v! z' T. G3 TFamily of distributions, 分布族4 ^& s' a" G+ j
Family of estimators, 估计量族
8 P4 s% r0 |& m2 x& x0 GFanning, 扇面
: I6 \" g X9 r6 J; UFatality rate, 病死率
9 e1 u2 b; {- b% f5 Y: x4 AField investigation, 现场调查
M$ d/ H3 J h/ m& @Field survey, 现场调查 l& C) J: G2 o
Finite population, 有限总体
; I2 R3 S6 ]' a4 fFinite-sample, 有限样本
7 F+ |" T5 i* N: EFirst derivative, 一阶导数8 }3 P1 U$ v" y, C! `
First principal component, 第一主成分: }$ t, n) u. }: m4 e5 F
First quartile, 第一四分位数
$ \4 p3 d0 R. F; e0 qFisher information, 费雪信息量: a4 y9 |2 J4 O* B! [3 u5 U3 N: L+ ?
Fitted value, 拟合值
& c. `% W7 A" d2 E1 _5 yFitting a curve, 曲线拟合; h* R2 a. o4 w$ n
Fixed base, 定基
/ m. w: F6 K! B( G# yFluctuation, 随机起伏! a/ Y5 o) }/ O) X# I% A
Forecast, 预测5 z* R% n" i4 f i( D5 [* Y% K9 C
Four fold table, 四格表, V$ c+ g* @2 @! Z
Fourth, 四分点; j7 Z2 F) S5 F4 n6 ~# z
Fraction blow, 左侧比率" x6 E3 i) J# R6 d
Fractional error, 相对误差9 f; J! J- G( S' ^2 }1 H
Frequency, 频率. Y% W& D2 Q9 `" f' n" `; l
Frequency polygon, 频数多边图
! t# d" y4 Y9 q2 b1 F: PFrontier point, 界限点
( K3 w m0 ^9 a& Q6 N# h& eFunction relationship, 泛函关系3 V$ L1 | x4 ^7 w# q9 \/ B
Gamma distribution, 伽玛分布6 S% H# U; l1 Z- h, J% m* F
Gauss increment, 高斯增量
0 q! D. D/ H+ BGaussian distribution, 高斯分布/正态分布3 q- t$ `8 e9 `8 ?
Gauss-Newton increment, 高斯-牛顿增量
. C( k" w6 ?( J; [! p- O4 o. BGeneral census, 全面普查% Y* s6 e! V1 Y3 r* U
GENLOG (Generalized liner models), 广义线性模型
6 ], |- f7 u- m, t K" u, ?Geometric mean, 几何平均数
9 ~% S. k, H S+ L. d1 cGini's mean difference, 基尼均差) t/ Z3 c* t6 O k7 O, i
GLM (General liner models), 一般线性模型
9 S4 ]6 `! C$ ^* A' V6 PGoodness of fit, 拟和优度/配合度; P5 N- V# A. N7 P+ b- G6 b6 y# i
Gradient of determinant, 行列式的梯度
7 r/ m" n0 Y+ }8 j& U- YGraeco-Latin square, 希腊拉丁方+ D% Q, `( x- d& g- Q5 U; ~" P
Grand mean, 总均值( z5 V) r% A2 a. z# J0 H
Gross errors, 重大错误
7 A* ]; e9 z3 p3 i+ VGross-error sensitivity, 大错敏感度
& c }& y8 W, C. W8 UGroup averages, 分组平均, e) t9 e( K! l+ ^5 @# Q- \: \
Grouped data, 分组资料
5 ]( o' p1 r* I. M6 M6 E" oGuessed mean, 假定平均数0 B3 M& a6 m' ]1 }# y- p
Half-life, 半衰期
1 B* N6 y$ s) U: z/ vHampel M-estimators, 汉佩尔M估计量
& {) d) O J/ Z7 R$ E XHappenstance, 偶然事件, j8 u% `! ?8 M; |; e" v
Harmonic mean, 调和均数, E% L9 y! D' F+ @. t
Hazard function, 风险均数
2 _3 Y3 m) g# cHazard rate, 风险率0 f3 N1 S x4 O
Heading, 标目
& r: k' V! m7 t8 {* M3 S, c4 F) hHeavy-tailed distribution, 重尾分布* c" Q/ {7 v& f% F9 D, X- f, L, V
Hessian array, 海森立体阵; l8 g+ x; r0 _, J4 k$ K
Heterogeneity, 不同质
7 B5 j5 ]; W9 Z# V+ NHeterogeneity of variance, 方差不齐
( F7 C+ @' S* k- f; U9 X, t7 ZHierarchical classification, 组内分组
( @; R+ F4 c1 M) ]9 Y, Q( i* yHierarchical clustering method, 系统聚类法
& |$ L# A( l; r* G9 O0 M2 ]2 yHigh-leverage point, 高杠杆率点
- \" A @) w; L! R* V" G; ]HILOGLINEAR, 多维列联表的层次对数线性模型! U/ K9 K$ B" Q$ @
Hinge, 折叶点5 i7 V U' \1 x
Histogram, 直方图
' R3 Y4 h4 W2 X& I" k, \Historical cohort study, 历史性队列研究 , g* n9 P$ t/ Y4 {$ W4 D' b c8 m, F
Holes, 空洞
+ H9 y( L7 d/ x+ |HOMALS, 多重响应分析/ O2 B: i0 g3 Y$ C( D9 _5 X
Homogeneity of variance, 方差齐性
! p; n+ [- A OHomogeneity test, 齐性检验9 R7 \6 I; I1 `; l' `3 D, ^; S6 p
Huber M-estimators, 休伯M估计量
2 s) B. {7 _- e$ O8 f6 n& VHyperbola, 双曲线" Q, n# }9 O6 v3 W7 u, F
Hypothesis testing, 假设检验
: a: Q- i/ C: X! kHypothetical universe, 假设总体- n- n+ d+ g* i: w- k) _2 F0 R7 l6 G
Impossible event, 不可能事件! q% x, Z$ Y' A7 c( O' b8 s
Independence, 独立性
+ D9 V0 e" h/ Z& J* w+ PIndependent variable, 自变量- A& I/ n' G# P. d( i
Index, 指标/指数
$ i6 L L- C: z0 {7 n( `Indirect standardization, 间接标准化法# X2 g: i/ R1 t2 R
Individual, 个体
f; Q% J0 F5 t( q3 ?# `8 `# a4 GInference band, 推断带
8 v; l" M4 @9 L3 f! r7 vInfinite population, 无限总体
' P6 G7 v) ~8 r8 m9 Q; ^Infinitely great, 无穷大+ _' F) V- Z8 \/ F# g+ G4 x; `
Infinitely small, 无穷小! B' r& c, \) z, _! x
Influence curve, 影响曲线
8 z8 Z' J0 ~% R6 P3 P: jInformation capacity, 信息容量4 T! u. T) e+ C9 f
Initial condition, 初始条件
( ?) B, q' a0 p7 }7 A' n. q$ nInitial estimate, 初始估计值
& }1 Q8 Z" m# HInitial level, 最初水平
9 @* K. E/ H8 H# o7 F2 kInteraction, 交互作用- R0 ?8 l, j, U# W
Interaction terms, 交互作用项
1 ~8 ], G% ^8 G2 X8 ~Intercept, 截距5 Q9 j0 C( X0 a: A8 @
Interpolation, 内插法
1 w" w' ]- c* r$ {# Q8 hInterquartile range, 四分位距
5 c' l" I3 R1 S; n3 }2 w0 mInterval estimation, 区间估计. w1 A8 z5 |! Y- z: T
Intervals of equal probability, 等概率区间6 @) Y$ z l5 x
Intrinsic curvature, 固有曲率. {4 ?# M( {7 O% P& s
Invariance, 不变性& W* S8 s2 y& Y5 q S1 A' H8 S
Inverse matrix, 逆矩阵9 [/ ]9 a! y' A+ ^' h" x
Inverse probability, 逆概率) w; E7 Z- b9 \# f( B& g
Inverse sine transformation, 反正弦变换
! X4 v1 O3 j4 ~* V) rIteration, 迭代
5 A3 t1 |0 R: H1 x; NJacobian determinant, 雅可比行列式 j1 V1 i, F1 ]6 {
Joint distribution function, 分布函数. U7 m4 u: Z/ m$ x
Joint probability, 联合概率& n' d7 n& }$ R& Q: S% E8 X
Joint probability distribution, 联合概率分布8 w4 A) @" S" N0 J+ {6 r* d
K means method, 逐步聚类法) U+ J9 Z5 `- Q/ V# X* v
Kaplan-Meier, 评估事件的时间长度 / y6 ?* f, g: ?" h8 K9 o& [
Kaplan-Merier chart, Kaplan-Merier图
% z! ^7 I" q5 H3 DKendall's rank correlation, Kendall等级相关
, e" X" p3 o4 X* j/ w; F( `& eKinetic, 动力学
5 ?. N& f+ Q' E9 z) J' iKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验% h# P1 o8 f) L: B/ g5 @3 E
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验8 O, i6 _5 J1 K4 n3 W8 n, l
Kurtosis, 峰度
; y3 J- G: s9 wLack of fit, 失拟
: m' S" ^" V% L1 @4 K/ u+ P. g# eLadder of powers, 幂阶梯9 c/ O( \, n. k5 h" G% o
Lag, 滞后
# \; u1 l0 [/ X2 a( X! ELarge sample, 大样本$ A5 \* \* V v
Large sample test, 大样本检验
" ^0 P( i" E2 D% m/ {; @) hLatin square, 拉丁方
) e6 s2 i) k, a _4 eLatin square design, 拉丁方设计
: W5 V8 J) i9 m/ K' Q: OLeakage, 泄漏$ v7 o9 Q5 v7 ]
Least favorable configuration, 最不利构形
% @2 W8 M" a9 k; ULeast favorable distribution, 最不利分布
1 s9 x0 K( {4 w" q" e, yLeast significant difference, 最小显著差法
' s }7 Z- Y* R, k+ Z) {* u2 ZLeast square method, 最小二乘法
: K7 g# R+ d# p9 N3 _1 \Least-absolute-residuals estimates, 最小绝对残差估计
' u- D, {( k4 pLeast-absolute-residuals fit, 最小绝对残差拟合% \* } X" N" r% x. _
Least-absolute-residuals line, 最小绝对残差线
2 v$ c" L* l5 c( v( gLegend, 图例
! L0 J- p, A( V: U9 nL-estimator, L估计量
/ V; y" z! w6 T8 fL-estimator of location, 位置L估计量
. }; y+ s' N" F% j5 GL-estimator of scale, 尺度L估计量
4 e2 p/ c9 `' N' ~Level, 水平& {6 f/ y2 K' i. ~# A
Life expectance, 预期期望寿命' w8 ?6 P- q2 @3 ^( J5 r. `
Life table, 寿命表$ H4 v! T& t5 R7 a$ f# w
Life table method, 生命表法: k" @! W! V' w2 s# f
Light-tailed distribution, 轻尾分布8 k7 k6 I+ T3 @+ R
Likelihood function, 似然函数
3 X* t! m, `" m/ H" VLikelihood ratio, 似然比 E; ?" Z9 {' v! H$ g, J( G
line graph, 线图
# Z% W& `- \; _ JLinear correlation, 直线相关. ]5 n5 ?7 j9 b4 x4 Q
Linear equation, 线性方程0 e/ \8 L' L; _
Linear programming, 线性规划* l! c; Q& X7 k+ G2 ], ^' p
Linear regression, 直线回归
) v$ o4 V; ^: x9 e' v" P9 O$ _Linear Regression, 线性回归* M x- p; t9 w+ o% [2 u
Linear trend, 线性趋势. L; `( r$ r, U; x0 S5 a6 J% Q
Loading, 载荷 * u0 p) }% f: ?2 @+ C5 ?9 X
Location and scale equivariance, 位置尺度同变性) w. S: l" O+ Z! N
Location equivariance, 位置同变性
3 [6 R: [1 ^. M, ?$ pLocation invariance, 位置不变性
, e2 z0 W! x3 ~/ a' FLocation scale family, 位置尺度族
7 [0 G/ Z. s0 oLog rank test, 时序检验 - s1 F2 P/ S0 x
Logarithmic curve, 对数曲线
" U$ _, O. y3 x. `/ xLogarithmic normal distribution, 对数正态分布8 l1 s [' F! i, l) L2 F& p
Logarithmic scale, 对数尺度
6 K$ j# L& E$ j( c# ?' D& iLogarithmic transformation, 对数变换1 r n1 X0 @4 e1 {/ J
Logic check, 逻辑检查
. }: M& U% e3 w# X$ V: `8 Y) K! }Logistic distribution, 逻辑斯特分布 J& E" c L1 w
Logit transformation, Logit转换- D% t: O( M9 [& A" U
LOGLINEAR, 多维列联表通用模型
2 ]! j" E: q4 Y9 j/ [Lognormal distribution, 对数正态分布8 x C* R; ~8 Z0 s
Lost function, 损失函数
- H# v2 e! b9 R) k; H- PLow correlation, 低度相关6 ~1 H, P7 A2 I& Q6 q" p
Lower limit, 下限: k0 ~0 G# l; R
Lowest-attained variance, 最小可达方差
* B7 V+ u6 `* } k# u% ZLSD, 最小显著差法的简称
4 f3 j" P8 D5 V- [: d3 H( ELurking variable, 潜在变量3 Z$ `$ H! c' |
Main effect, 主效应3 f$ ?7 W: g# @( v- |+ a/ ]
Major heading, 主辞标目
% l4 q A0 E2 r! _& j: RMarginal density function, 边缘密度函数
" v" w8 m1 ~( A4 D1 s! GMarginal probability, 边缘概率
0 I" k6 ?+ T7 o) T' e# `Marginal probability distribution, 边缘概率分布/ z5 d; I c2 K" r1 U% g
Matched data, 配对资料
( [1 [) ^5 G- M9 ]Matched distribution, 匹配过分布$ T3 ?) P3 o. j8 h3 w" r; y2 Q4 ]
Matching of distribution, 分布的匹配) ?, T! k- R K$ ?
Matching of transformation, 变换的匹配
# {9 H1 Z5 T" UMathematical expectation, 数学期望
3 {! v$ K3 T3 F3 R+ l3 L0 m9 ]Mathematical model, 数学模型) B0 W/ k) ~4 o3 G3 d# ^ p
Maximum L-estimator, 极大极小L 估计量
$ v) c* F* Q. d% ?$ I9 Z* N" \Maximum likelihood method, 最大似然法/ \4 b8 p8 G7 D: W4 {
Mean, 均数
0 E0 U1 ~: _* J+ D* B3 UMean squares between groups, 组间均方
$ ~2 s5 _- C( f- D/ O! G; Q( X8 TMean squares within group, 组内均方
1 i5 v: ~, m) j$ h/ y- ^Means (Compare means), 均值-均值比较2 z3 e5 b& Q+ I
Median, 中位数
& z. Q+ {$ {. uMedian effective dose, 半数效量1 e( `+ v2 J& ^) Y( h2 z
Median lethal dose, 半数致死量7 e" O+ \# P h' M( m
Median polish, 中位数平滑( M) M, x7 {$ A; C" }
Median test, 中位数检验
. R' M6 F: r7 T; Y2 hMinimal sufficient statistic, 最小充分统计量
. m5 @& H8 C% j3 g k5 R- zMinimum distance estimation, 最小距离估计1 p. ^% O- ?) C$ U
Minimum effective dose, 最小有效量
' V5 H8 Y- O, a4 i X- c! VMinimum lethal dose, 最小致死量* E. ^! T5 D/ N
Minimum variance estimator, 最小方差估计量4 t: v, ? L$ e" w, s x
MINITAB, 统计软件包
8 z" y( H+ o/ E) ~1 _7 eMinor heading, 宾词标目
( X* I- j/ s& V# c) ]& f4 ZMissing data, 缺失值
& m% a8 I% f( \) n1 ^3 yModel specification, 模型的确定
( n2 q. t7 [0 z+ ?2 W$ O" r( K/ lModeling Statistics , 模型统计
, F- k" X2 @ D4 |! E/ e8 T! h |Models for outliers, 离群值模型' b0 g3 c- [5 _0 h# @
Modifying the model, 模型的修正- s, h$ q' \& n5 Y9 N/ Z
Modulus of continuity, 连续性模# j/ i J( E! \7 l6 F
Morbidity, 发病率
& |' N% |: q V' m# ?4 g5 v3 @# }Most favorable configuration, 最有利构形
3 R" _& {$ B* {1 OMultidimensional Scaling (ASCAL), 多维尺度/多维标度
2 Y- ~4 _& q' d3 z' EMultinomial Logistic Regression , 多项逻辑斯蒂回归$ \1 @8 o6 e( h/ ~7 Y! \- ]
Multiple comparison, 多重比较$ @3 I2 K1 ~/ [0 P% x
Multiple correlation , 复相关
: C# R) Z, ] k" h* }: Z! ?7 pMultiple covariance, 多元协方差9 ^+ _$ J6 l. z. s
Multiple linear regression, 多元线性回归
! L! z2 V$ Y+ {0 m3 f% HMultiple response , 多重选项
8 k& @0 k" C% Q: R jMultiple solutions, 多解" o i/ k2 s M: J$ k( I- o5 i: G: U5 `+ {
Multiplication theorem, 乘法定理$ ]8 E! i/ _2 @; S' C" H
Multiresponse, 多元响应
& R8 D+ V$ E- S2 U2 eMulti-stage sampling, 多阶段抽样; {3 y, [8 h! M- ?+ v; j6 n
Multivariate T distribution, 多元T分布
: h& _# ~# q3 }, A& X5 Y6 CMutual exclusive, 互不相容" |5 U/ X+ f3 s9 i' q# p& [& ?4 G
Mutual independence, 互相独立; d3 _8 P* Q2 D+ a: u. T9 N
Natural boundary, 自然边界
$ D! f$ e+ \( ? O% t: b4 A6 O" s5 ONatural dead, 自然死亡* ^$ Q' k* s# y' X- K2 V; k3 E
Natural zero, 自然零
% M2 |+ f/ i \* nNegative correlation, 负相关
. f! F% m' w, X$ N' WNegative linear correlation, 负线性相关7 U0 X( C/ N& f# b, @: T* {
Negatively skewed, 负偏0 H+ B( {/ }- t7 g, ^$ z
Newman-Keuls method, q检验" u& [) U5 G) L* [+ k) Z
NK method, q检验# R: U/ g* q# z& {
No statistical significance, 无统计意义
% n. T5 d3 J( F% f1 r! [' e5 CNominal variable, 名义变量
J, L. w, Z# U `3 B) vNonconstancy of variability, 变异的非定常性1 G& i/ _3 a+ h6 p1 h4 ?
Nonlinear regression, 非线性相关: G1 A$ }0 n; C- f, a
Nonparametric statistics, 非参数统计
+ e: [5 d; R* g& J/ cNonparametric test, 非参数检验% O' W! b& P& u; }. n; ] S
Nonparametric tests, 非参数检验5 Q2 \( ^) [ }( P& K5 p8 _
Normal deviate, 正态离差
5 I' B9 `3 G; _Normal distribution, 正态分布8 Q5 B- V u' Y! P
Normal equation, 正规方程组
' Y5 \& M- @7 u" t. dNormal ranges, 正常范围, U# r# [- o9 s, s* g
Normal value, 正常值" ~( J# Q x5 D$ M: y3 K
Nuisance parameter, 多余参数/讨厌参数
3 `7 Y$ }/ ? R3 f: WNull hypothesis, 无效假设 : }; H i0 b9 Q* ?+ p6 N1 A: m. F
Numerical variable, 数值变量* P; w/ h& X) Y1 o, y/ q
Objective function, 目标函数) c+ x4 x) B% H& Q+ @% v5 j! x
Observation unit, 观察单位
9 ]; C) @8 b! t: Q1 ]* {9 N2 fObserved value, 观察值
$ s5 e3 A6 s _! C# u9 E' T9 oOne sided test, 单侧检验
& B/ @ I1 ^- |3 S' m/ sOne-way analysis of variance, 单因素方差分析) e# u5 u7 a9 y- }* {% X; y$ u5 v
Oneway ANOVA , 单因素方差分析
, X. [% g8 F0 o/ n8 S/ B x" oOpen sequential trial, 开放型序贯设计3 b8 K7 D& Q! W2 X6 A7 {% R& t' `
Optrim, 优切尾( |/ t/ f p9 D& s
Optrim efficiency, 优切尾效率
! b: n0 |( m1 m: X7 lOrder statistics, 顺序统计量
' Y( q2 C% m" H8 ^5 }Ordered categories, 有序分类! Q! d* a) _2 L9 F+ z1 p
Ordinal logistic regression , 序数逻辑斯蒂回归
, }7 M" E, C; \7 f4 qOrdinal variable, 有序变量
- u1 M& S- U. \# \* y+ y! yOrthogonal basis, 正交基* t4 \1 c& K" \& e: x) s: t+ r
Orthogonal design, 正交试验设计# u/ ?) A% K F
Orthogonality conditions, 正交条件
4 s' ]" p# C; b" \# Z) [7 _5 P; x/ OORTHOPLAN, 正交设计 - w: i# G5 u1 f7 Z! t% ^/ s
Outlier cutoffs, 离群值截断点
5 C7 v# d+ l4 H( M9 ]' o8 O1 |4 AOutliers, 极端值' p( c( B H5 x. L& y
OVERALS , 多组变量的非线性正规相关
" v7 O, R8 s/ ^/ p! dOvershoot, 迭代过度8 _1 T9 T8 I$ ^' _9 \$ P6 F. I B
Paired design, 配对设计
4 ]/ S0 {& p, Z& o: z* ~9 W/ x: tPaired sample, 配对样本6 i2 P" z: p, H/ S. l) i: m
Pairwise slopes, 成对斜率" D6 D+ `5 O9 ]( o+ I+ y6 ?
Parabola, 抛物线
: x# I( [3 X& v; E" H6 w; CParallel tests, 平行试验1 j0 _% P. T3 r$ q
Parameter, 参数
0 A% N+ N4 U: _: D$ O9 X1 ]+ q* q( MParametric statistics, 参数统计# L. o2 [! b* e$ `( d g
Parametric test, 参数检验% Y3 ~. ]7 J# \* i1 J( z" B
Partial correlation, 偏相关
( M/ Y4 S. N8 x' PPartial regression, 偏回归3 ^5 W: V% Q. h2 Q0 ]7 d
Partial sorting, 偏排序
4 x$ g+ Z8 A2 P% q! w& YPartials residuals, 偏残差
! @- `8 q( F7 |" HPattern, 模式
" k8 H: J S" D3 VPearson curves, 皮尔逊曲线
, A% [0 {; c+ }/ z0 PPeeling, 退层$ q% R# R) d7 _/ p
Percent bar graph, 百分条形图8 k* k9 Y- g1 n# |3 l; j+ w
Percentage, 百分比
6 h% _- t0 I2 W. N5 zPercentile, 百分位数
% q+ x3 O: r" e3 e5 R# |+ [Percentile curves, 百分位曲线
9 R9 Y6 F0 e. x5 A5 j' JPeriodicity, 周期性! J# K) A4 x$ Z* c8 F, e
Permutation, 排列
9 s9 F J0 D8 z6 c6 h$ mP-estimator, P估计量/ x+ G; ]0 H2 ]) m
Pie graph, 饼图
3 l4 t/ a f6 Y% Q" G$ Q2 X( iPitman estimator, 皮特曼估计量. n/ K B0 V* i5 M/ z% |- u
Pivot, 枢轴量
7 U% R% J% e' v/ BPlanar, 平坦
; a& A6 A& b+ x* [! g3 gPlanar assumption, 平面的假设
9 M4 K+ z9 X3 o% iPLANCARDS, 生成试验的计划卡
: x4 }7 ^4 O( |; ^Point estimation, 点估计8 F/ p, N* Z9 w. P) r
Poisson distribution, 泊松分布7 }# _# s v" s6 M
Polishing, 平滑
& U/ w. G/ r& t+ xPolled standard deviation, 合并标准差
$ g6 M9 m/ Y1 I$ I; a$ x+ ~; WPolled variance, 合并方差8 E4 O- Z9 Y+ N% u) g+ K6 ?6 b
Polygon, 多边图
& T1 x0 Q1 \8 n* E) L& \3 HPolynomial, 多项式
; `: ?1 N2 e; j4 v; Q8 _Polynomial curve, 多项式曲线$ N/ o" P- t/ Z& C, o% K# T! f ]
Population, 总体
& [6 Y- p) O* W0 ]3 w! D0 N' ?Population attributable risk, 人群归因危险度7 Q4 M8 M% Q% W# x8 n4 V) A
Positive correlation, 正相关
! g: m1 l/ h- j% [Positively skewed, 正偏: E1 q% N, w" g, o( r8 y
Posterior distribution, 后验分布
, h1 {1 s; _0 F# w! P# CPower of a test, 检验效能
/ V6 t- ]/ k$ ^& y6 {4 KPrecision, 精密度
, U6 s' w+ h0 W8 v+ ?7 w! aPredicted value, 预测值! e( Y1 {/ ^. Z; n; M
Preliminary analysis, 预备性分析8 K+ u( {' z2 R- c1 a m
Principal component analysis, 主成分分析
0 v( O# f( {4 jPrior distribution, 先验分布8 G5 K" T6 R. f8 O/ U3 J
Prior probability, 先验概率7 _7 E. V+ F4 n
Probabilistic model, 概率模型1 Y/ p) _2 b5 b: t4 j
probability, 概率( Q+ j! b- ~5 j2 f
Probability density, 概率密度6 f- C: f* u" M( O- e: K# t; c
Product moment, 乘积矩/协方差
& j& m: J& ~3 n: l2 X" cProfile trace, 截面迹图
+ k& f4 F/ a/ h7 r) M1 [2 b. w" }Proportion, 比/构成比
5 c" b3 {2 Y( B$ R$ g& qProportion allocation in stratified random sampling, 按比例分层随机抽样. b, F1 |/ [0 b
Proportionate, 成比例' t4 ~ l! _6 j) g
Proportionate sub-class numbers, 成比例次级组含量
1 q" U/ w# z' A+ I0 J1 yProspective study, 前瞻性调查$ |4 U( N/ L+ j: j `0 o
Proximities, 亲近性 9 p9 q6 U' c: m) T6 Z
Pseudo F test, 近似F检验1 h& ?# y& e1 s+ Y" b
Pseudo model, 近似模型" |( I* X3 G* q
Pseudosigma, 伪标准差" w+ D( _+ h. }7 F
Purposive sampling, 有目的抽样6 Y# P8 j) ]- |/ C' U( K! C2 h
QR decomposition, QR分解
) w, N; i4 w. O1 I' IQuadratic approximation, 二次近似( y ~5 X. O+ P/ y1 a2 t3 i' r
Qualitative classification, 属性分类1 ^2 k8 [: O9 @
Qualitative method, 定性方法( Y% D/ c' I8 i9 _0 `/ I: x3 a
Quantile-quantile plot, 分位数-分位数图/Q-Q图! U$ q( v" @1 U% Y3 y; T# A1 Q
Quantitative analysis, 定量分析+ J& U" ~, l" v) c1 f: e9 g
Quartile, 四分位数
* `0 w: @7 Z+ |0 B. Z) YQuick Cluster, 快速聚类
: ^. |( }2 `4 [+ y1 Q5 xRadix sort, 基数排序( o" T3 \- L5 w
Random allocation, 随机化分组
/ B0 q- I+ `9 D& f( \Random blocks design, 随机区组设计. V1 i, _6 r& |
Random event, 随机事件
- s* u; Q: m, E5 W9 JRandomization, 随机化% X6 K9 A4 M* T9 S7 @
Range, 极差/全距, {; C) _; i8 y+ _
Rank correlation, 等级相关' m% o! n/ y! x1 ]7 t
Rank sum test, 秩和检验1 S4 J, q6 }- t4 W( Q7 p; }
Rank test, 秩检验1 H( T$ ^' b0 O1 F6 @4 k* Y- m
Ranked data, 等级资料1 C( Y+ T4 d4 O' L* M4 a: g
Rate, 比率& s3 [4 y/ q7 |# M6 o! C
Ratio, 比例
& {# w# d* a% n3 Y# A& nRaw data, 原始资料
" a' f, a9 O" H5 N8 j* c8 W3 I" URaw residual, 原始残差
0 I' f; A1 x9 q" _2 p& tRayleigh's test, 雷氏检验
/ w/ F! {6 s$ J$ oRayleigh's Z, 雷氏Z值
$ Z/ b# r7 v: iReciprocal, 倒数
8 K* C8 S/ P) q4 p4 p" x3 Z' uReciprocal transformation, 倒数变换" u6 J8 }% A& g
Recording, 记录' |9 Z: R" f& p# A3 {& S( p7 l
Redescending estimators, 回降估计量9 ^' t% B+ S% h+ o6 |0 M/ E
Reducing dimensions, 降维
( R* q, j& } V; K3 s. x4 TRe-expression, 重新表达
* w1 H7 p0 l$ n: ZReference set, 标准组2 O4 d4 B' ]$ G
Region of acceptance, 接受域
1 [5 ~7 V" z$ A3 \Regression coefficient, 回归系数4 y, D7 C8 c/ Q1 s. ~: a
Regression sum of square, 回归平方和0 f/ E# q9 d, b& k, r* H5 q, A
Rejection point, 拒绝点- G. x: B7 c# S; A# `
Relative dispersion, 相对离散度
! [9 y9 o5 h% q7 r- IRelative number, 相对数
( w) Z2 W+ ]# E! b: NReliability, 可靠性
6 X, k: f# w L. o# OReparametrization, 重新设置参数1 i3 C9 I5 b$ r: B0 J ]! g( H
Replication, 重复# S- x( X3 Y7 r9 i* ]
Report Summaries, 报告摘要
& r- o7 D- ^! Y: R. r+ ]0 }Residual sum of square, 剩余平方和/ a9 @; I0 @! o$ v* u
Resistance, 耐抗性
3 A; v5 [: {' gResistant line, 耐抗线
' n/ i4 f3 y1 V; Z( r+ b+ K. @+ jResistant technique, 耐抗技术
7 H+ r5 Q6 C( m( b( w0 G7 CR-estimator of location, 位置R估计量6 _9 g4 x: ?, G/ w: a7 `
R-estimator of scale, 尺度R估计量
, x$ @" k1 }! ?3 a0 oRetrospective study, 回顾性调查' |# T" P- q. H: `& B/ S# W' r
Ridge trace, 岭迹
; [4 Q" ~ \2 R2 T" y% D# LRidit analysis, Ridit分析' z' j6 P- E Y) ]: I9 B, c
Rotation, 旋转
9 H; E7 L- n' J) wRounding, 舍入
: h8 a+ r$ ~7 ^; w1 T5 LRow, 行
3 O& `2 L8 [$ r0 nRow effects, 行效应
/ y2 }/ M2 q0 g$ `3 e, u r4 e4 ]6 CRow factor, 行因素
) X- M! c5 d+ o; A: zRXC table, RXC表" s* s) m( \, e Q
Sample, 样本
0 ]/ q; @6 a' sSample regression coefficient, 样本回归系数
$ U, V7 F; q d7 X, wSample size, 样本量& C( a: i0 d* g6 j. c) [4 A! b- |
Sample standard deviation, 样本标准差 B$ ]& L1 d; _$ j, E, l; f" v
Sampling error, 抽样误差! e, {3 W2 [3 ^0 R8 }" `
SAS(Statistical analysis system ), SAS统计软件包3 ~- ?9 k* X. @( ]& _+ ~7 k! R
Scale, 尺度/量表
2 q, j9 X, r* b1 s( T; d# _Scatter diagram, 散点图
- |% @5 ~" z! C) N7 l9 @Schematic plot, 示意图/简图, V1 X9 S. V8 G
Score test, 计分检验
7 ]6 a7 J: |" i9 _Screening, 筛检; R2 T* M# y1 R& Z7 g
SEASON, 季节分析 # B3 i8 A- K6 Y1 {* y' \# B: o1 ~
Second derivative, 二阶导数
& k5 ]9 j, z$ @" F1 X$ ESecond principal component, 第二主成分
% _5 e u+ O9 [0 I4 s5 U, W; BSEM (Structural equation modeling), 结构化方程模型 ! R: l$ c- Y; o4 z F% o( h
Semi-logarithmic graph, 半对数图! A! Z, @7 m! {$ m, H6 ~" `% _
Semi-logarithmic paper, 半对数格纸( C) t0 L1 t! T' u1 C0 f3 D
Sensitivity curve, 敏感度曲线
* h: t" O- s( U1 YSequential analysis, 贯序分析
% r. y$ G2 J% ?3 m) ~Sequential data set, 顺序数据集. A; U' X. H- m% s
Sequential design, 贯序设计
3 `' u- [- ^% fSequential method, 贯序法
7 i+ }; J: b, M: d% JSequential test, 贯序检验法6 ?. p1 X" z! C6 \
Serial tests, 系列试验
1 x C! f8 P& e% o0 pShort-cut method, 简捷法 5 e6 C$ p4 J/ e* w0 H+ K
Sigmoid curve, S形曲线/ R" t9 D/ @$ t5 O5 Q
Sign function, 正负号函数
: A, h6 P5 |+ h4 r1 S" W7 sSign test, 符号检验9 F) k3 N3 o- q
Signed rank, 符号秩( C3 V6 m) x2 x
Significance test, 显著性检验
" O9 e& H# E% O- g2 R$ |Significant figure, 有效数字
5 Y0 \$ {* n$ P( w% G) Z, dSimple cluster sampling, 简单整群抽样9 N4 f( K$ _" ~" S
Simple correlation, 简单相关
; s" ~$ N4 f5 p8 Q. L, g; mSimple random sampling, 简单随机抽样
! g7 s6 W9 S; @! M$ GSimple regression, 简单回归 a7 E$ G J4 o' p* Y
simple table, 简单表5 d j3 r/ o4 {3 ?. x4 w5 I+ m
Sine estimator, 正弦估计量$ D; x3 @2 G! c) C9 X+ s5 A2 f
Single-valued estimate, 单值估计9 f) b n* E( Z
Singular matrix, 奇异矩阵' @, x) {# B* G+ |9 i3 F7 g7 r7 ^
Skewed distribution, 偏斜分布) t9 _9 _* \! Z+ c8 H: |; m3 ~
Skewness, 偏度& f: \- i* p) M9 B4 X7 J: W
Slash distribution, 斜线分布
4 S M, y( j$ J ~& HSlope, 斜率( C" K9 P0 |: A
Smirnov test, 斯米尔诺夫检验: l, z, j9 }$ s4 @! Z1 y' j" U1 B3 u
Source of variation, 变异来源) G) i4 X9 q2 x2 B
Spearman rank correlation, 斯皮尔曼等级相关
3 v& A; R- G t( OSpecific factor, 特殊因子8 [% o. n; g2 ]# i7 V% F
Specific factor variance, 特殊因子方差
' T/ X: Y* U$ @2 A0 DSpectra , 频谱
0 u* _4 m: ?- z# M. V; F5 a+ kSpherical distribution, 球型正态分布
: Q% w# S' ^ b2 V" ~2 `$ t7 JSpread, 展布( \+ a' S0 W) O$ Z$ y
SPSS(Statistical package for the social science), SPSS统计软件包6 w6 I- a4 a2 F v. |5 O7 t
Spurious correlation, 假性相关
) K- a, T! U) H$ I. S$ L4 g- fSquare root transformation, 平方根变换
, y; L- }9 r/ O& UStabilizing variance, 稳定方差2 P! w8 E T8 R
Standard deviation, 标准差: T' U$ A% J4 o1 X/ \: L8 k7 B4 O) O
Standard error, 标准误
9 ]7 s0 O, `1 S3 r" p( p/ m1 XStandard error of difference, 差别的标准误
6 }( q4 f: T3 X5 C; u2 HStandard error of estimate, 标准估计误差$ u8 K8 I* v- s: |7 {! i8 n- d" U
Standard error of rate, 率的标准误. F- ~+ D5 \ P! ^
Standard normal distribution, 标准正态分布
6 I9 M( e }6 C0 G' W; v# o% B. e9 MStandardization, 标准化; O5 b' F" t$ _6 y: Y
Starting value, 起始值; E- y) A) c& H/ [9 m( I# e" b H6 w/ C
Statistic, 统计量
. Z3 x; G% L/ B- Y) z5 qStatistical control, 统计控制% Y% Q5 P& M$ L$ |2 m" \# h5 N) I; Z
Statistical graph, 统计图
- k$ e/ z9 j9 f4 l/ {9 K2 ?; N B: c# xStatistical inference, 统计推断; I* {5 u& o7 B& w2 Z4 j9 L y
Statistical table, 统计表& K7 C2 U+ r8 s. p( I& I I+ C
Steepest descent, 最速下降法# z: u: a$ t Z% S* E- b
Stem and leaf display, 茎叶图' M$ z" m* \2 s7 h9 k% ?5 W
Step factor, 步长因子/ E2 h% T0 a0 u7 n. z$ l8 F5 X
Stepwise regression, 逐步回归& p5 G. J' @9 {1 e( K& N6 I0 a: t) u
Storage, 存0 s8 V' M/ J- P9 K" \/ R
Strata, 层（复数）/ m& d6 a b9 @' |
Stratified sampling, 分层抽样8 h9 u7 J7 u% d0 o D% F$ q5 I! Q
Stratified sampling, 分层抽样* t+ k* {& V# [# p( d! Q
Strength, 强度
, u! F; n: k; e$ |6 fStringency, 严密性; g. W% R5 o( }1 l" x
Structural relationship, 结构关系! a( n3 ~% d3 D3 _+ n4 t5 q3 P
Studentized residual, 学生化残差/t化残差
3 |! J1 _2 c3 e- J% l; ?) tSub-class numbers, 次级组含量! d9 n; n' n3 X4 g) G) }0 R f
Subdividing, 分割
: Y5 k; t5 A4 ~2 a& |* M2 _Sufficient statistic, 充分统计量" e! R, q$ m! N/ c. f% [
Sum of products, 积和 G0 u: b$ t7 `' ]$ y3 H5 X
Sum of squares, 离差平方和# t: H+ h7 Q+ F/ q2 _
Sum of squares about regression, 回归平方和5 A4 t2 ?: u2 V+ z0 m( @; \5 B
Sum of squares between groups, 组间平方和8 j* ~1 H' Q* Q6 M
Sum of squares of partial regression, 偏回归平方和: ^& L& @: _4 z. t1 S
Sure event, 必然事件/ a0 D7 K8 k; r( u) T
Survey, 调查
8 D2 A3 {' {. ]4 ^; l6 E* o# \* aSurvival, 生存分析
7 M1 F. J" H. g0 \Survival rate, 生存率( [) U3 n) h6 }1 v2 } F8 `, L# J- k8 J
Suspended root gram, 悬吊根图
8 B" Q/ ?2 X X" A0 O0 G VSymmetry, 对称7 }3 @" n u2 S0 u
Systematic error, 系统误差4 ?- g# c% H1 t+ h* [% n& H
Systematic sampling, 系统抽样
' `8 y) o8 r& R" |$ N) C' L/ YTags, 标签4 _! X) P, O- C) o
Tail area, 尾部面积2 U7 \/ d- ~' R& T
Tail length, 尾长: c5 B T' X9 `6 R1 J
Tail weight, 尾重* [: F. y G, [( j. W' U# \& [2 [
Tangent line, 切线8 _( Y$ f; I6 e5 S
Target distribution, 目标分布
9 R0 n8 J) m1 V; kTaylor series, 泰勒级数& s2 g' M& j2 `' }$ P
Tendency of dispersion, 离散趋势
/ D! {& v! I$ Y" d+ ]Testing of hypotheses, 假设检验. C" R% X% x7 M8 n+ ^- {3 U
Theoretical frequency, 理论频数
5 {1 o6 ?' [. Z4 ]Time series, 时间序列
5 Y1 g: `3 A$ y8 oTolerance interval, 容忍区间4 U) a% v$ a4 h9 s0 x3 W" ^
Tolerance lower limit, 容忍下限' r' B3 i2 S+ ]$ ^0 K/ I! f
Tolerance upper limit, 容忍上限
; Z2 f2 G6 @7 I) |) jTorsion, 扰率7 A) a: ^$ o$ d1 ?+ f; @6 o
Total sum of square, 总平方和* M8 \* o3 C+ c$ E% g' x+ [
Total variation, 总变异+ l _! F& Q4 o* n c* }
Transformation, 转换! b e2 `& ]2 W. K/ L
Treatment, 处理: m+ D6 ^* B2 h4 _/ X/ I4 b
Trend, 趋势& e+ H& ?( Z' @9 N0 C
Trend of percentage, 百分比趋势4 u+ i; q& @ J" e$ N8 S
Trial, 试验4 ^( a. O4 ^1 J5 K0 ~7 I8 w
Trial and error method, 试错法
% ]9 T3 {, C# N, e" aTuning constant, 细调常数
9 G( e/ U2 i1 mTwo sided test, 双向检验
. a$ p! B$ ]5 Y% U% M" V0 K: ~% g- ~$ qTwo-stage least squares, 二阶最小平方
" s! P' e* J& y; wTwo-stage sampling, 二阶段抽样
! ]5 h$ ~4 L0 j" F1 l+ YTwo-tailed test, 双侧检验5 o( o6 [5 ?0 }( ?7 k; B
Two-way analysis of variance, 双因素方差分析3 I6 t- x/ U1 c( D0 L
Two-way table, 双向表
7 V- y7 P( ?3 K6 T3 V$ o1 Z2 eType I error, 一类错误/α错误
4 _3 j, B0 ?0 R% k( IType II error, 二类错误/β错误% d2 F) ?6 Z& }4 y
UMVU, 方差一致最小无偏估计简称5 z, Z0 V ^* b$ G) h0 L+ R
Unbiased estimate, 无偏估计
3 {; F7 S4 V6 T- C2 `2 BUnconstrained nonlinear regression , 无约束非线性回归
4 h* s7 t/ h6 h* kUnequal subclass number, 不等次级组含量2 k# D ]1 `: P, l$ r, u' V; s; B0 i
Ungrouped data, 不分组资料) H. G7 v @" A* `
Uniform coordinate, 均匀坐标
X: ~& U6 U5 `5 b8 ?' d' hUniform distribution, 均匀分布
+ i# I2 D0 K% F. H- t$ M+ CUniformly minimum variance unbiased estimate, 方差一致最小无偏估计" U' l/ _8 \3 Y% }" e
Unit, 单元! U5 p8 j( t$ q6 R- |7 q
Unordered categories, 无序分类: H5 c1 d/ e$ [8 G
Upper limit, 上限
" k: ~7 T! l t: HUpward rank, 升秩
( S$ A1 x6 D$ `% M! R1 ?2 kVague concept, 模糊概念
5 B/ |( r( @4 K- jValidity, 有效性
/ F, ]6 t; C2 E5 u: w; X8 g! TVARCOMP (Variance component estimation), 方差元素估计
9 _$ q( |) _9 Y6 hVariability, 变异性
) r6 q8 Q& p1 R1 f+ q8 dVariable, 变量& f D& u+ N% E" K; I
Variance, 方差
/ d5 }9 [$ m, p: \Variation, 变异 E i6 q% J- ^7 y8 N$ }/ t
Varimax orthogonal rotation, 方差最大正交旋转
. p5 F" R- v: I* pVolume of distribution, 容积
" b6 m' N" _) T& t4 _5 M; z$ MW test, W检验
5 T$ \ z1 R1 a# S8 r2 rWeibull distribution, 威布尔分布 r( P) i1 l. g2 I% }
Weight, 权数+ Z, G! u! K; U" F |8 P. f, t! p
Weighted Chi-square test, 加权卡方检验/Cochran检验
$ q. j; W! U1 s; p" j& ]. s, MWeighted linear regression method, 加权直线回归
$ x3 x3 T0 {2 v) }$ _* U# [* XWeighted mean, 加权平均数 D3 K8 X q. h+ c9 ?4 Z; Z/ ]/ A' H& Q
Weighted mean square, 加权平均方差
/ d' y0 o) m0 U, L: L; R$ ?Weighted sum of square, 加权平方和) M; R4 m( v4 X2 J$ v5 f* s* s
Weighting coefficient, 权重系数
% V' x' L( M* m- x& O' T; TWeighting method, 加权法
: Q7 L" A8 f4 h6 `; s. CW-estimation, W估计量
# G. x/ o& v3 d- A7 w( o3 j1 A2 U1 Y' IW-estimation of location, 位置W估计量* q! K: S+ d; }2 y/ ]8 _) C
Width, 宽度- k+ G' A# w/ v
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验8 a# L2 L/ {+ V$ S) w# ]/ U
Wild point, 野点/狂点# T2 l* }+ D1 @+ x1 H
Wild value, 野值/狂值; K0 e$ r! Y' e; N, n
Winsorized mean, 缩尾均值: W0 o, E- A8 C
Withdraw, 失访 % z) b; I+ X1 q! J& ^
Youden's index, 尤登指数. [- g9 [: @- Z3 X0 j9 l
Z test, Z检验
5 v8 z7 @, b, `4 dZero correlation, 零相关- S1 l5 q! f0 w$ m) ^" p2 W
Z-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
