|
|
Absolute deviation, 绝对离差$ |6 j r7 n/ _% q# i6 {! y$ t
Absolute number, 绝对数+ |3 t1 `# G) v) L% B0 n- M
Absolute residuals, 绝对残差
; T) H+ `, }; r6 R4 z Z" p8 b, SAcceleration array, 加速度立体阵8 ~2 a9 K, Y% h
Acceleration in an arbitrary direction, 任意方向上的加速度
\; Y) } o# k6 h9 O% o( E: dAcceleration normal, 法向加速度# p! \9 r( e+ f& Z( M- B
Acceleration space dimension, 加速度空间的维数
. J0 I9 n9 x. `7 \8 YAcceleration tangential, 切向加速度
3 ]! [& y0 B+ E& v) FAcceleration vector, 加速度向量4 Y2 g* y; W6 ^9 a
Acceptable hypothesis, 可接受假设
e7 o# Y' s" u4 B1 s: cAccumulation, 累积# E' S4 s. R1 D, q' z1 T
Accuracy, 准确度1 Q- q0 _1 T4 ]+ r
Actual frequency, 实际频数. t3 t: {2 K7 d1 K1 K3 w: {9 ^
Adaptive estimator, 自适应估计量# R8 k$ V' _7 U! N) M
Addition, 相加
. G( r; u0 @- `# K3 N" cAddition theorem, 加法定理
7 {3 L2 r/ ~% e9 G. r5 c' MAdditivity, 可加性
! z. ~1 B+ J! l1 T/ H2 JAdjusted rate, 调整率" p' [% G0 W, E8 {/ O
Adjusted value, 校正值
1 g9 D. p9 J0 {' j CAdmissible error, 容许误差
, g* x6 A, n$ v" _/ F% G, `Aggregation, 聚集性
9 u0 t r6 a9 H. G+ O9 QAlternative hypothesis, 备择假设! O) c3 n& d/ G4 F8 `
Among groups, 组间
& a* _% J Q2 |# BAmounts, 总量
# q' Y* N& u. o1 T0 u" w; R2 }Analysis of correlation, 相关分析
8 p1 q( ]: z! I3 c: B3 G8 j) VAnalysis of covariance, 协方差分析
; X3 v7 f2 N! u! l, tAnalysis of regression, 回归分析
2 v C8 A2 k0 G5 Y. S( x! SAnalysis of time series, 时间序列分析
" J/ ?- Y% F$ R+ MAnalysis of variance, 方差分析* r$ u) j! V/ c B: [
Angular transformation, 角转换& r' W& u; `' l0 z$ g3 j' w+ Z; J
ANOVA （analysis of variance）, 方差分析
! {& F& @) B4 z" X0 E! iANOVA Models, 方差分析模型
) P m: {' U/ A) n1 QArcing, 弧/弧旋) e g' @+ X6 m: c9 @
Arcsine transformation, 反正弦变换
# k/ Y$ f9 n7 ?9 e& vArea under the curve, 曲线面积% e& v/ q7 }2 B9 O/ a9 `1 _
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
% {: J1 F/ {9 ~ARIMA, 季节和非季节性单变量模型的极大似然估计 ! M% y! s- U# X
Arithmetic grid paper, 算术格纸. G, N) r+ R( R6 G3 W
Arithmetic mean, 算术平均数! H( f+ {: J5 ~: R" D) R# H
Arrhenius relation, 艾恩尼斯关系
, T( j, J+ J& A2 Y6 J1 CAssessing fit, 拟合的评估
v! }" ^; |' C$ s C0 f) cAssociative laws, 结合律
- C, G; M+ m% q6 c5 p/ t% N+ GAsymmetric distribution, 非对称分布; p3 T# J/ n/ H8 v# q4 E0 g
Asymptotic bias, 渐近偏倚 X% D8 [4 p0 [/ X+ z9 O
Asymptotic efficiency, 渐近效率
& G, A0 u* q/ UAsymptotic variance, 渐近方差+ O' m* r$ u6 q2 {. B
Attributable risk, 归因危险度+ A+ U) a2 @* ]) W, L+ Y( ^
Attribute data, 属性资料# Y1 j$ D+ ?0 E5 K. }
Attribution, 属性) ]2 R$ ?) a+ n% J, G
Autocorrelation, 自相关
7 L1 {! o; L6 K h' \* R! m: D8 vAutocorrelation of residuals, 残差的自相关6 A- R1 n1 t7 ?) _6 u1 w4 S( H
Average, 平均数
; e6 a2 h0 q& Y( z! z) VAverage confidence interval length, 平均置信区间长度
7 M8 T) H, Z7 ZAverage growth rate, 平均增长率2 l- O# k7 G+ Q8 v/ w# \
Bar chart, 条形图
- x1 }0 ^- B9 C! }6 vBar graph, 条形图
7 g2 P% ^' x6 g4 s3 a* s# N jBase period, 基期+ |( I1 {8 A3 z
Bayes' theorem , Bayes定理# T p h+ G2 K% F, e1 j
Bell-shaped curve, 钟形曲线
1 ] c( K4 v _8 _6 uBernoulli distribution, 伯努力分布$ M$ q8 K% Z# S( ~1 ~. n& p3 ?
Best-trim estimator, 最好切尾估计量. ?4 j0 H H1 n) b5 T; ^" {' M
Bias, 偏性: I0 ]+ b8 X; @- W- z
Binary logistic regression, 二元逻辑斯蒂回归/ P0 i. F7 a6 t! c% I% X# {
Binomial distribution, 二项分布' i r6 Z( ]# w5 k1 M1 i* J
Bisquare, 双平方. z8 w; f- F1 `: a: r$ K
Bivariate Correlate, 二变量相关: x* Y0 t# x) P
Bivariate normal distribution, 双变量正态分布: f' j D- i* h6 ~. m
Bivariate normal population, 双变量正态总体
. x/ {2 y1 m) A, v7 {; vBiweight interval, 双权区间
q4 w, X# @5 z7 P% V# BBiweight M-estimator, 双权M估计量
4 Q( i, J+ x4 W9 iBlock, 区组/配伍组' {% [/ t( B, H5 d6 W
BMDP(Biomedical computer programs), BMDP统计软件包
0 ~6 V9 J: q4 J6 qBoxplots, 箱线图/箱尾图
" w9 B `( y- TBreakdown bound, 崩溃界/崩溃点
2 b$ \, D) q0 f: b4 B1 |Canonical correlation, 典型相关
# e6 w8 Q' z1 [: s6 q' ?Caption, 纵标目
& C! @8 @, I& S2 u9 _Case-control study, 病例对照研究 y1 m0 z+ Z1 ]
Categorical variable, 分类变量
4 j+ M1 r9 J9 s' \$ yCatenary, 悬链线: I# [% P0 `6 S5 C3 c5 S( c! Z7 v
Cauchy distribution, 柯西分布
' X i. Q! g' t7 [1 P: o+ G5 ICause-and-effect relationship, 因果关系6 s+ X% M' A4 ~
Cell, 单元( [3 _% v2 q8 h- P$ I$ S8 M
Censoring, 终检
3 i5 N4 T6 o+ U: d# e; hCenter of symmetry, 对称中心+ n; m. a" t4 z+ A3 ^& @: |
Centering and scaling, 中心化和定标0 `1 r/ G, S; a4 p& B8 j' s
Central tendency, 集中趋势
T' z: _2 r% _" JCentral value, 中心值' y+ t8 K. E. W a- j _) D
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
: C* p1 {- r; K5 R+ yChance, 机遇+ c x" P( u. I5 p9 Q F
Chance error, 随机误差; f$ Q" ~6 v9 ]; H# @: i! \
Chance variable, 随机变量
' j. ` v2 j! iCharacteristic equation, 特征方程
' y) a) B# _# R0 E6 O" \( y0 H+ kCharacteristic root, 特征根
2 h9 s, c4 W* p$ X$ K: L0 pCharacteristic vector, 特征向量# G- V% N ]8 ?, @* O6 {9 s
Chebshev criterion of fit, 拟合的切比雪夫准则
' {9 n$ J m0 y8 pChernoff faces, 切尔诺夫脸谱图# E9 i7 c7 z- q. y" ~8 h8 \
Chi-square test, 卡方检验/χ2检验. Z& E& X+ ]9 j/ p. m
Choleskey decomposition, 乔洛斯基分解
0 L& R1 t {: Z4 U& GCircle chart, 圆图 * t" y3 e4 h* G5 S5 R
Class interval, 组距# {# n9 K S* t. U; Y" y
Class mid-value, 组中值! E2 S: \5 H+ Z: |. z
Class upper limit, 组上限. V( U0 z2 N; o+ m$ S5 c1 |, K
Classified variable, 分类变量
/ E0 D9 m* {1 \7 U4 n1 D7 C9 LCluster analysis, 聚类分析
" t- Y+ J4 z/ X+ wCluster sampling, 整群抽样8 d; I+ X5 g' X0 \8 s
Code, 代码
* P/ p2 x6 U$ s% A- g1 C% o: nCoded data, 编码数据) s) E" c0 l: t$ K* I1 G9 m: t! D- c0 N$ P
Coding, 编码: a) D" q- y1 R" K+ F& x
Coefficient of contingency, 列联系数
- M& ?; q0 M! f R, {, DCoefficient of determination, 决定系数
- v$ \* }) A% i: r1 \Coefficient of multiple correlation, 多重相关系数8 B* d1 s7 b/ q& A# n/ @1 G
Coefficient of partial correlation, 偏相关系数
n4 U1 q: b, `0 LCoefficient of production-moment correlation, 积差相关系数
! B9 ]% H2 {/ F( s: j5 Q* bCoefficient of rank correlation, 等级相关系数
* Y( ]5 @% o* x+ j1 p# lCoefficient of regression, 回归系数
' v& B1 E0 N$ n! c4 z8 w7 ACoefficient of skewness, 偏度系数
9 v9 X: h4 x& Y: R& U- OCoefficient of variation, 变异系数 H i( C* z/ H. o
Cohort study, 队列研究
7 ~# X; w5 s& @* r1 [Column, 列
- W2 n* P, T$ _, X- N1 z+ d5 d: MColumn effect, 列效应
6 e# S2 U0 ^3 Y: ~+ QColumn factor, 列因素4 U' j* Z6 B2 C, S4 }4 x0 I% j
Combination pool, 合并
2 B! }$ S6 q. ~9 g! J3 n1 C, ^Combinative table, 组合表+ p0 }6 Y) C" x& Z/ P& ~% H; U
Common factor, 共性因子2 {, [: e& ]* L: |7 P
Common regression coefficient, 公共回归系数* R) m! J% g! A7 y$ n2 i
Common value, 共同值' Y1 A& p" p8 I+ r
Common variance, 公共方差/ i, q4 q6 x/ y, m5 Y
Common variation, 公共变异. b$ J% g( k; \" L
Communality variance, 共性方差( K' F9 \- t, Z3 l* n# u
Comparability, 可比性5 Y; y5 q2 v( @. V9 K1 O6 w) U
Comparison of bathes, 批比较
# n5 W% c% x/ G# T. D7 _7 \Comparison value, 比较值% P' U: m6 e: d' b; ]& Y$ G! @
Compartment model, 分部模型2 a( H5 F, O- A( A) r- |
Compassion, 伸缩
: F3 u3 p- V; u8 kComplement of an event, 补事件2 B8 _# l% D0 q% e5 c
Complete association, 完全正相关; a- }. }3 k1 F# p% h' F
Complete dissociation, 完全不相关
`3 @! u/ y9 G1 l" q: Z) `Complete statistics, 完备统计量
& x: S# l9 S+ qCompletely randomized design, 完全随机化设计
4 x6 l) p# r1 Q& E9 q- IComposite event, 联合事件
. Q X3 |7 ]' G2 _* oComposite events, 复合事件
2 e- {! D- a" U4 |2 \Concavity, 凹性5 |: x3 S' [* W0 S! P( v; P$ e
Conditional expectation, 条件期望5 m1 K/ X$ L0 q4 I$ g
Conditional likelihood, 条件似然8 B5 K& R4 w1 ? H4 F
Conditional probability, 条件概率
1 {) \( @* s& V8 M6 l+ c/ D9 ^Conditionally linear, 依条件线性0 I/ z; ]; D |) G- ?( T3 R5 N
Confidence interval, 置信区间& [3 \7 U0 q$ D! P6 W4 i( ]$ ?
Confidence limit, 置信限6 B; V! E0 I2 N0 A% R3 D0 q- [
Confidence lower limit, 置信下限
. N0 ?$ b4 Z5 Z# CConfidence upper limit, 置信上限
: `# @! |4 R! L# q" ?4 L4 U NConfirmatory Factor Analysis , 验证性因子分析3 x% J# A! U. C8 @# R E
Confirmatory research, 证实性实验研究' Z# J, Z8 x8 X O
Confounding factor, 混杂因素
/ S# E7 d3 }8 l( j, ^% u EConjoint, 联合分析' `2 R0 z! f& d9 h2 r
Consistency, 相合性
! v2 ~8 ]' o+ R4 EConsistency check, 一致性检验
$ Z8 m$ |- `. l9 T& X2 ZConsistent asymptotically normal estimate, 相合渐近正态估计: b0 c! ]/ g! a0 L. T
Consistent estimate, 相合估计
& a4 @: f h$ p( i& S/ G+ cConstrained nonlinear regression, 受约束非线性回归
# Y2 R+ D) H- J0 x6 c% O1 `, `Constraint, 约束! T- V- Y4 {( E1 o+ g- {
Contaminated distribution, 污染分布( G7 w3 Q5 ~5 t# z* x7 L8 H
Contaminated Gausssian, 污染高斯分布
& m5 R* {- D# Y" Q5 t7 uContaminated normal distribution, 污染正态分布
7 p+ d# \' g! p. N+ E: C( Q k3 IContamination, 污染9 X# f' {' K+ h. q4 ^1 W, C. e
Contamination model, 污染模型$ b- s1 C9 W2 c3 b$ d
Contingency table, 列联表
; ~6 U! k) d7 t2 @+ lContour, 边界线
. z2 j- N/ Q. F# k9 bContribution rate, 贡献率; Z. Q- t* F$ n. n( r
Control, 对照
]& h) ~- |4 j, m- P# O$ g( ^/ BControlled experiments, 对照实验 r6 C I% \3 m8 V y1 t
Conventional depth, 常规深度7 M0 I' g0 w- b
Convolution, 卷积$ q4 z3 F' ^3 m& U
Corrected factor, 校正因子
6 Q% ^2 C# z9 q- _- V7 d+ O$ GCorrected mean, 校正均值9 N& r2 ?& o, O; Q
Correction coefficient, 校正系数7 q/ A$ s; t" R Q
Correctness, 正确性
; d Y) i3 _5 s v7 V6 Q1 JCorrelation coefficient, 相关系数7 S6 G3 g) e" ]" T5 ^
Correlation index, 相关指数
: l( k! j' u2 QCorrespondence, 对应4 c h+ }9 W% M( W; q+ {
Counting, 计数
# ?3 L8 b2 c2 X' C) l" D& CCounts, 计数/频数
5 X9 e: w k3 \7 ^# Z3 b( kCovariance, 协方差
1 S5 ?2 M: K' ^% XCovariant, 共变 ) w' @" r& Z$ s) F
Cox Regression, Cox回归
+ w6 }0 ~8 X F+ Y" L' |3 ECriteria for fitting, 拟合准则
9 d4 V1 e: |3 u d5 k! vCriteria of least squares, 最小二乘准则
, g; b" R3 r! [4 H; Z {8 ]6 {Critical ratio, 临界比
- |: C/ }; D% S6 CCritical region, 拒绝域
5 H; F6 n) y% \( T' D. P+ b9 E1 QCritical value, 临界值
" y; H B4 k& \' B8 r# ~6 g7 `3 y# zCross-over design, 交叉设计( `: N, T2 v" u
Cross-section analysis, 横断面分析
! J; S( K5 s( |3 h0 s2 }Cross-section survey, 横断面调查
7 l5 t- q# U! _5 vCrosstabs , 交叉表
9 A) E/ p1 d; f n" V) \- F- {0 UCross-tabulation table, 复合表
5 I0 x' R! h* F6 N z* Y7 D& V( _; |Cube root, 立方根# y2 i! s# K+ \6 q/ s
Cumulative distribution function, 分布函数2 i! w! t% \8 w8 X
Cumulative probability, 累计概率. e8 {& U7 l- h
Curvature, 曲率/弯曲
" Z6 e7 l! F* P4 O" `( mCurvature, 曲率
( n. a' h7 Y' r& \Curve fit , 曲线拟和
" q" T% e5 R% L/ E. PCurve fitting, 曲线拟合1 L0 C1 j9 {' R. y, [9 y7 G1 ~
Curvilinear regression, 曲线回归
( K6 z* e* ]& sCurvilinear relation, 曲线关系' q% G8 x9 o( r% V3 U
Cut-and-try method, 尝试法
! U' ~ P2 T3 |% Y& I- A) y+ cCycle, 周期
, }: k1 y2 g, F; P+ }Cyclist, 周期性
& G$ n! V+ V- RD test, D检验' |7 l2 U3 ^* F7 `' v
Data acquisition, 资料收集
3 [5 N8 _8 L; p5 W% @Data bank, 数据库
7 {: L n" O* M! E+ T0 [' X( h) FData capacity, 数据容量, n. t- k/ W6 J2 }
Data deficiencies, 数据缺乏% J& i, L* V7 S8 L: V; X
Data handling, 数据处理
' T3 m. m: p" Y6 i* o! C! [Data manipulation, 数据处理
( P* Q0 T! d8 y% G) dData processing, 数据处理$ |6 B9 D9 b: S- Z: O
Data reduction, 数据缩减4 L; O0 e% J$ @; J+ i
Data set, 数据集
* d: w7 A' g; M/ @% l+ IData sources, 数据来源# s8 w1 O; y; l0 N6 o( j" }
Data transformation, 数据变换: s) }& B& r1 }) b7 x4 }" W9 @9 `2 Z
Data validity, 数据有效性" _2 H) w- r& F. G! E. o# r! _# b0 a
Data-in, 数据输入
1 A3 b6 y( I u- p7 K# M8 O; xData-out, 数据输出
* U; \) L4 Z" l- L. Y# G& ODead time, 停滞期: g8 Q) J& u; x( j, n0 N1 R- N
Degree of freedom, 自由度
: t2 I1 c' G* A: b8 SDegree of precision, 精密度& j5 [* N+ V( w3 b' ]$ [& m/ V
Degree of reliability, 可靠性程度
8 U& V9 R% Z% B1 y; d- ]4 sDegression, 递减
+ y8 ]$ S% g8 b0 B, X/ x; i4 }/ A2 `Density function, 密度函数% B" L1 C% [( r
Density of data points, 数据点的密度
+ l1 P ]; \/ j/ {Dependent variable, 应变量/依变量/因变量2 [! |# s5 [% m5 D
Dependent variable, 因变量& b& o+ [- `/ P+ K" }) W3 g$ y
Depth, 深度
. }' k8 D3 s$ wDerivative matrix, 导数矩阵
a3 W: O* M- [' j) I$ l: pDerivative-free methods, 无导数方法 i4 k# S) m3 t$ q; C) y
Design, 设计
0 g$ k" w8 d% T2 F9 v8 [Determinacy, 确定性7 A1 d! n& O; y1 W" Z- s
Determinant, 行列式
- S/ L8 z% o# t' rDeterminant, 决定因素 ~0 F+ `3 S1 q [9 p
Deviation, 离差 h; C- Q: h7 E- @4 r1 f3 C
Deviation from average, 离均差) c+ K; c P& c9 L( P- I: J5 m
Diagnostic plot, 诊断图
* ^5 f0 U2 q+ h. E0 `, \, @% EDichotomous variable, 二分变量5 l/ C1 w: s; g1 y- u
Differential equation, 微分方程0 f7 k; I5 L1 E0 E' g5 ]0 S
Direct standardization, 直接标准化法" p: q) ^0 v( B+ `# l! V% b) \
Discrete variable, 离散型变量
0 ~4 i' ~( Q/ B( K8 T$ nDISCRIMINANT, 判断
8 |" M c; w2 |1 cDiscriminant analysis, 判别分析
3 T8 @' J2 N# RDiscriminant coefficient, 判别系数
9 j2 W; C9 m, c3 A TDiscriminant function, 判别值: Y' x/ d) F+ {, V0 D
Dispersion, 散布/分散度
, J3 D D6 L4 l( u. W; BDisproportional, 不成比例的
& f5 H# p6 \+ vDisproportionate sub-class numbers, 不成比例次级组含量6 l, g. y& \# K# ?/ B) m3 \
Distribution free, 分布无关性/免分布
" W, L$ R! W- T4 wDistribution shape, 分布形状: L2 u: H; c/ t" K: l) Z( n4 B$ P, v
Distribution-free method, 任意分布法
+ m' r8 A) h) yDistributive laws, 分配律
" M8 W3 u9 Q W. d0 |7 g5 u7 ~. J! QDisturbance, 随机扰动项
8 _/ F7 \5 O' p( h* A3 ODose response curve, 剂量反应曲线
. J# u; T' {: H; q0 L: v& @4 s& r' bDouble blind method, 双盲法& v/ C7 n7 i$ `+ L
Double blind trial, 双盲试验
. E; J: V# i, R* J) YDouble exponential distribution, 双指数分布% C, t% N) \0 |
Double logarithmic, 双对数- U' r5 }7 Z- {$ E$ I% v
Downward rank, 降秩
# {2 s% m) T/ Q( k8 X0 zDual-space plot, 对偶空间图
& W3 m' |( _8 e5 @DUD, 无导数方法; o, ^; T4 U' t
Duncan's new multiple range method, 新复极差法/Duncan新法' o/ i$ K, f' p3 ~# G$ `* S
Effect, 实验效应/ E$ f8 ?! C& C" H( R
Eigenvalue, 特征值
& s) J# Z! ]; f2 n. u2 V6 wEigenvector, 特征向量2 E( W' K0 B- I
Ellipse, 椭圆
% i( Q! V9 A& xEmpirical distribution, 经验分布" R% `8 V7 W5 S& X' d
Empirical probability, 经验概率单位
% O C! p% A; z& kEnumeration data, 计数资料
- f3 g8 X; x' l" ?8 }Equal sun-class number, 相等次级组含量
! c/ ^+ ?# W% \7 MEqually likely, 等可能
) R3 }; u" J" K4 ]+ T) w$ HEquivariance, 同变性
) z" {" J0 I6 `2 r1 ]3 rError, 误差/错误
! o" Y( \6 O) K/ wError of estimate, 估计误差
# h- u) m Q* V( A4 Q5 RError type I, 第一类错误
6 d# a; `% Y% `2 ^, UError type II, 第二类错误
' t l7 U& _2 n6 {+ V$ R& y% E9 ^Estimand, 被估量9 ]" @9 ]$ p# b7 N
Estimated error mean squares, 估计误差均方
1 A! i" |0 E! `5 ?6 O+ mEstimated error sum of squares, 估计误差平方和
$ Z q0 n- V% E$ V. VEuclidean distance, 欧式距离
( t, ~+ e8 W0 d: zEvent, 事件1 R7 y# d6 G* c. {, w
Event, 事件7 R* [8 M3 K. y" A+ v
Exceptional data point, 异常数据点
$ b1 I8 J: b" AExpectation plane, 期望平面
3 V8 t% [ A1 Z4 n# ~8 EExpectation surface, 期望曲面 x# h9 q! e Z2 ?5 v7 y5 N: F
Expected values, 期望值
# B2 q# F) i5 O1 a0 s* WExperiment, 实验9 s; U1 I! }8 e( c
Experimental sampling, 试验抽样; A% k" K3 _) \7 N* i8 _& x
Experimental unit, 试验单位
$ f: F/ x' h' z7 q, Q2 \$ hExplanatory variable, 说明变量* T! t! j; A' Q4 M. |. g: y }* g* O
Exploratory data analysis, 探索性数据分析
/ T! s2 Q; n( ]& ^& A# {2 \- wExplore Summarize, 探索-摘要; H% a7 X, W9 t$ L- r( s
Exponential curve, 指数曲线1 M0 I1 _5 T6 A( y3 B
Exponential growth, 指数式增长
) \5 R6 U9 i7 l7 U. D! QEXSMOOTH, 指数平滑方法
( P; m# a4 M, d+ b/ e2 f0 a1 l nExtended fit, 扩充拟合
) } K4 W4 N* _' X+ oExtra parameter, 附加参数0 J4 h" f5 V7 D F) }
Extrapolation, 外推法! S+ d* }# N8 n2 l7 c2 j
Extreme observation, 末端观测值
; V6 B3 m/ | d9 WExtremes, 极端值/极值
1 U; {" f' U8 ]% h/ FF distribution, F分布
( K' {4 r1 _6 C8 \* @; gF test, F检验
; Y7 }" O7 B5 CFactor, 因素/因子
1 H/ R' b3 r& \1 H) \; MFactor analysis, 因子分析+ }% V/ |1 H) ^( i% l3 J
Factor Analysis, 因子分析 w9 e$ ~) |1 u* E y) Q+ V
Factor score, 因子得分 ; `$ ~ Q) m( ?; ~, z* q c. x
Factorial, 阶乘
9 E; v9 H! w! pFactorial design, 析因试验设计
8 Y- |# g% I; PFalse negative, 假阴性. V; \2 g5 b: A* {
False negative error, 假阴性错误* }4 c6 Z6 j. M* d( g1 n
Family of distributions, 分布族$ z2 p- |& W7 Q i q5 _, \0 @! I- I* Y
Family of estimators, 估计量族
: |8 ~- b5 _; P0 MFanning, 扇面
6 n5 W! [) x @* H' v) sFatality rate, 病死率
8 B- W' ]/ @! B* y A0 \3 x- sField investigation, 现场调查
! A0 ?2 ]1 y: c3 q( h& yField survey, 现场调查2 y! G$ @8 x1 o, l" z% _4 C7 S2 E
Finite population, 有限总体& q+ _9 m$ Y% D* G; k; S/ d
Finite-sample, 有限样本' y6 Q1 }5 m8 c& Y2 x0 \' B+ W- K) a
First derivative, 一阶导数
' ]' m( }, d3 w. v: ^First principal component, 第一主成分9 @. B' \! B5 g9 |; a
First quartile, 第一四分位数
* H* L$ Y) T+ z! ?# e; ^Fisher information, 费雪信息量" o; K3 [: x& |, M4 ^# l; G
Fitted value, 拟合值9 i D+ @3 S. u, j$ M5 J
Fitting a curve, 曲线拟合; [0 j* P: M% v. Y' T: i% Y
Fixed base, 定基
, u; z" X& g/ |- [4 P; [8 WFluctuation, 随机起伏# d. ], _+ C; @& [
Forecast, 预测7 e3 u8 [9 G% \- J/ R
Four fold table, 四格表$ W% y \7 i6 @5 G; p `- Z# h
Fourth, 四分点! b! S' t' G" J; \
Fraction blow, 左侧比率
( S+ k+ o" F3 o" N) [' `' M% QFractional error, 相对误差( G0 R, V+ q0 L% i8 @
Frequency, 频率
& I8 ]" a; T. NFrequency polygon, 频数多边图9 b4 J; Z* u, a
Frontier point, 界限点
: F0 T* b; j3 o% ]Function relationship, 泛函关系8 a- s; f5 ], C2 m% {9 |
Gamma distribution, 伽玛分布
. S: [ e2 L h0 k& QGauss increment, 高斯增量
/ X' E4 m5 {5 u( O) Y: d% W9 GGaussian distribution, 高斯分布/正态分布
6 g9 |- B& H0 P6 {* T& d0 IGauss-Newton increment, 高斯-牛顿增量
?% i9 @% p& i8 e( H% t. ~# fGeneral census, 全面普查
) ~, E( C" r. t. R& w2 B/ o j5 [GENLOG (Generalized liner models), 广义线性模型 % \( b4 ]5 F1 X
Geometric mean, 几何平均数) \: ~3 I( Q" ^" h+ I
Gini's mean difference, 基尼均差" t' p1 u( v5 A7 n* n! J* |) k
GLM (General liner models), 一般线性模型 ( E5 S% _7 K: u3 M3 f: s$ W. ?
Goodness of fit, 拟和优度/配合度- |) k/ g% w" {
Gradient of determinant, 行列式的梯度
/ }8 E$ O2 {( k/ e0 T2 h. t7 {5 ZGraeco-Latin square, 希腊拉丁方/ e" [) n# {# W, C5 M
Grand mean, 总均值1 b* @2 D, u) Y
Gross errors, 重大错误" F; A, U, X: T2 I! o$ ?7 N/ T
Gross-error sensitivity, 大错敏感度
M4 X/ O+ `) s% }% l- AGroup averages, 分组平均" _% g8 f+ i2 l: T# S* [
Grouped data, 分组资料
, X4 j. z2 T; V# M! r& xGuessed mean, 假定平均数
* `1 J% P# w3 l- v$ j! T) [Half-life, 半衰期
. Q8 B* h- B/ ]Hampel M-estimators, 汉佩尔M估计量
+ |6 S( V! k( K# o: O3 k4 ]! ~( |- jHappenstance, 偶然事件
( p) T6 C1 D6 l6 AHarmonic mean, 调和均数
6 X/ Q- s9 [8 C7 wHazard function, 风险均数) o+ f* X' j" U! k T0 [
Hazard rate, 风险率# ~% q% L) K, x8 J
Heading, 标目 4 _" W5 }; a6 [ d$ g! E1 C: ~
Heavy-tailed distribution, 重尾分布
. t w$ ] w8 m' gHessian array, 海森立体阵$ i/ j1 d+ Q2 L, d
Heterogeneity, 不同质
1 f5 q4 F% v8 L" P; @3 XHeterogeneity of variance, 方差不齐 ! y) v+ q" [# a9 z/ r
Hierarchical classification, 组内分组
. P/ k, h; U$ F4 _Hierarchical clustering method, 系统聚类法5 |6 T, e4 P6 Q* K7 c' ]0 |
High-leverage point, 高杠杆率点
8 ^- v* s+ E/ ]0 Q$ WHILOGLINEAR, 多维列联表的层次对数线性模型6 ^! c! `7 f3 [4 R1 w1 x/ ?" G: |) e
Hinge, 折叶点
/ C2 y8 {( H3 Z6 \Histogram, 直方图
' L1 ?0 u! b" m9 h" O- D0 \Historical cohort study, 历史性队列研究 " P" G8 F! h3 N; u
Holes, 空洞1 n8 w2 M% e3 ]* Z3 |: _0 F& f- o
HOMALS, 多重响应分析
/ a! s9 {* ~1 [- w- ^9 h+ f& UHomogeneity of variance, 方差齐性# @, I. K9 Q9 r: {( A4 [7 c) P* g
Homogeneity test, 齐性检验( M2 j( N6 Y' E4 e5 t
Huber M-estimators, 休伯M估计量
( v7 @- z! K0 {4 O8 l- y7 X9 J! h& P0 lHyperbola, 双曲线0 f/ V4 L( g) U! F
Hypothesis testing, 假设检验
8 u9 R) D: S* s2 P' t+ W) DHypothetical universe, 假设总体
" U. b" I9 T7 WImpossible event, 不可能事件* ^) ~) K5 M9 B& {, K6 m
Independence, 独立性
4 U% i$ |! w8 n9 h: sIndependent variable, 自变量7 T- e1 [* ^; }) x0 i
Index, 指标/指数8 |: V5 M$ W8 R1 D1 L5 D7 w
Indirect standardization, 间接标准化法
% X. }, \: t1 P/ ^# q1 q3 _0 xIndividual, 个体
' o, _! Q$ T5 \4 i9 \Inference band, 推断带
) }. f- B' e7 q* KInfinite population, 无限总体
9 e$ G9 ]. W5 N+ U5 `Infinitely great, 无穷大4 \: }+ G7 W4 n( Z5 D I1 ?
Infinitely small, 无穷小
" t, m1 T, [7 I5 r& D& Y# oInfluence curve, 影响曲线
% o7 N: B- L* i8 F, a" E# z. y; ?Information capacity, 信息容量
0 r* S: N& J* ~/ c) EInitial condition, 初始条件; d, S- ]1 ]. f8 z3 V
Initial estimate, 初始估计值
5 ~) F' k' E4 n4 O4 ~0 s; Y. rInitial level, 最初水平7 l% t' _' ?4 }
Interaction, 交互作用
; e( E* p X$ h" h/ g; UInteraction terms, 交互作用项
# a! q& _8 r$ w. ~4 _# mIntercept, 截距/ j+ L3 f( t' i3 h& f X
Interpolation, 内插法
& H# Q- c7 D0 ~6 s0 @0 Q+ e- M4 vInterquartile range, 四分位距
; p: g6 I$ a# h& \3 IInterval estimation, 区间估计
4 W. Q9 ^4 r% T7 n4 i. WIntervals of equal probability, 等概率区间
! M3 U1 S, I4 L+ ?; i- bIntrinsic curvature, 固有曲率
. W& z' O* X/ L* Y* M4 NInvariance, 不变性
2 S7 @( V0 V9 E$ L. `Inverse matrix, 逆矩阵
% ^% t8 d5 P# @) G: E3 gInverse probability, 逆概率" ]/ z3 P& m2 \( @+ s
Inverse sine transformation, 反正弦变换" T) N, c# r# S3 R- K1 C
Iteration, 迭代
9 E6 {9 ^# }( {) e# k2 g+ RJacobian determinant, 雅可比行列式
% n- q9 _' f2 {' h8 C6 F1 zJoint distribution function, 分布函数3 Y( H4 M& ^- x* K' L
Joint probability, 联合概率
3 L; D$ j% H: ]6 T2 \) ZJoint probability distribution, 联合概率分布
7 g+ h' I, V$ S" N1 ]) EK means method, 逐步聚类法
: ?# o4 \$ x& t' aKaplan-Meier, 评估事件的时间长度
! M; P' A+ W" ~! i5 l; D6 oKaplan-Merier chart, Kaplan-Merier图
`' h4 @9 \" n3 jKendall's rank correlation, Kendall等级相关
5 B5 `% M z& v7 N) X' BKinetic, 动力学
: a. N+ }# T) m$ BKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验( U1 l$ X) j. H$ w/ v
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
; R- d6 l( M2 m7 ]! }Kurtosis, 峰度
% n+ V3 E' h9 s0 @" J( lLack of fit, 失拟9 D1 j2 r7 a/ v
Ladder of powers, 幂阶梯
; Z s* X: V3 q+ O3 p( bLag, 滞后
2 P% O5 s4 ] d/ fLarge sample, 大样本
$ e0 C3 e( @. ?" m; sLarge sample test, 大样本检验
# [( i0 U7 C$ l7 I! BLatin square, 拉丁方+ H: o* g1 D8 e2 D
Latin square design, 拉丁方设计
: L. O6 P; y# V# I7 Y1 F# PLeakage, 泄漏
- i! T, r; \9 x9 z9 s7 ~' L7 ?Least favorable configuration, 最不利构形
" O- l- H/ d3 P0 Y0 n" ILeast favorable distribution, 最不利分布
5 ^, L4 @+ }# P' c$ c! x) wLeast significant difference, 最小显著差法
2 f$ A. Y3 S# A m8 W; xLeast square method, 最小二乘法
* P& Z, J2 @, O. N+ J2 H0 bLeast-absolute-residuals estimates, 最小绝对残差估计; K/ R: Y, U0 p1 H' Y) {! _& p
Least-absolute-residuals fit, 最小绝对残差拟合
. S8 o r" |0 ILeast-absolute-residuals line, 最小绝对残差线4 N9 g# X! g) h8 G# D1 t( y9 o
Legend, 图例& E- l+ m9 y, X. j1 N- k: k+ ]
L-estimator, L估计量, k3 v' G( d! B$ _
L-estimator of location, 位置L估计量- z* a$ \8 t* i3 p z G. M( w
L-estimator of scale, 尺度L估计量8 _2 I0 y$ o G. L& U8 f9 v$ I" S
Level, 水平1 ]2 R: \. M5 T ^) H w5 q% j
Life expectance, 预期期望寿命
9 c( K' k8 y4 S. M2 T' f" X2 w2 BLife table, 寿命表) M o, N* h0 V* e: ]0 X/ E8 w1 d
Life table method, 生命表法
+ A$ \" z4 q, |0 [, y( R6 zLight-tailed distribution, 轻尾分布
# j8 c4 R4 a/ \: p3 KLikelihood function, 似然函数' e& V5 \- i# D1 ~% I
Likelihood ratio, 似然比
1 k. n0 t! ?0 J! X5 C; ]6 Uline graph, 线图
) c. i: [+ d- o1 c# uLinear correlation, 直线相关; v& t& H( h% |
Linear equation, 线性方程2 ]# @! x& _' U! X; g
Linear programming, 线性规划! A' R: K2 g4 M6 }* O/ H
Linear regression, 直线回归& [- S3 C' H0 J* G
Linear Regression, 线性回归
# y1 r+ {- C# M: ^- u% y, cLinear trend, 线性趋势2 E( a/ Q7 B2 s
Loading, 载荷 $ A: S5 M1 @% y7 o
Location and scale equivariance, 位置尺度同变性7 Z$ ]2 E* n7 G! e# V* F9 X) r
Location equivariance, 位置同变性
3 x+ o- @& `4 A# J' ~# M: s9 B* c) uLocation invariance, 位置不变性% N; r- @% J6 [4 @- G5 I. i" s, I
Location scale family, 位置尺度族
) L0 c# {9 {3 n: {Log rank test, 时序检验 & @0 f, ?2 B1 Q, k/ |/ P D, F q
Logarithmic curve, 对数曲线
' q, x1 K9 V" |, z" eLogarithmic normal distribution, 对数正态分布
' L* c1 Y9 ^8 h! H; B7 J( QLogarithmic scale, 对数尺度
6 Z3 A: P1 P1 u* l: P& |) mLogarithmic transformation, 对数变换: C1 B+ o. f4 `7 I6 d# H
Logic check, 逻辑检查
5 t5 n c0 {) {9 ALogistic distribution, 逻辑斯特分布
+ x+ Q, x2 x1 x3 kLogit transformation, Logit转换3 A% L2 t) ]5 \
LOGLINEAR, 多维列联表通用模型
3 U B* `3 S6 j# i9 h \0 [! ALognormal distribution, 对数正态分布+ s1 s( B; T3 E/ Y. y
Lost function, 损失函数
8 c5 \( f( X; j, X% R0 `Low correlation, 低度相关
0 s( C& K) g0 I5 _5 ~Lower limit, 下限0 o6 s, _# g1 J
Lowest-attained variance, 最小可达方差
. o" {6 s1 R$ v5 f) h# CLSD, 最小显著差法的简称
* k! h& u: S' Y. u+ J: U# u. J9 |Lurking variable, 潜在变量
1 N, i/ W" ~- B4 jMain effect, 主效应" `; G) I8 y; y' w5 x* ^
Major heading, 主辞标目
- E; S$ e( {; t( k2 m% gMarginal density function, 边缘密度函数
* Q1 `( S% S8 sMarginal probability, 边缘概率
8 X# T# R. g) J, CMarginal probability distribution, 边缘概率分布% N7 U) Y& x) O/ Q7 i) K
Matched data, 配对资料. a! ?$ e. T. b8 Y4 m: C3 X& t
Matched distribution, 匹配过分布, W) n. ]; p0 d
Matching of distribution, 分布的匹配/ B7 f1 W8 ^! n i5 z6 n% B
Matching of transformation, 变换的匹配4 u4 {5 s6 r" U
Mathematical expectation, 数学期望7 \) o" Q' ]0 v7 }' [- q# i# ]0 E
Mathematical model, 数学模型
! d: h7 l$ H; L6 I% d+ E- H* L5 _Maximum L-estimator, 极大极小L 估计量
9 a) ]: ~) n! q3 I& QMaximum likelihood method, 最大似然法
5 `5 T2 G/ M8 w4 \6 rMean, 均数* a8 K; N: H6 f7 y! p5 m: G2 h- M; d. e1 C
Mean squares between groups, 组间均方" g/ U8 c# T' O: g9 n
Mean squares within group, 组内均方! X9 t" q" a1 p4 N" v8 g
Means (Compare means), 均值-均值比较
( r- ~9 u& I# r/ U. g1 y4 |Median, 中位数, ] _1 O3 c2 \4 G1 l$ c7 R
Median effective dose, 半数效量( A& O: ]. v8 j4 R/ P
Median lethal dose, 半数致死量
5 Z$ Y, b* Y& p3 N: Q0 R3 e3 n: {- [. @$ {Median polish, 中位数平滑+ m! N; \7 L, m w. ~; d
Median test, 中位数检验
4 |4 B" S5 Y, Z) S6 R8 PMinimal sufficient statistic, 最小充分统计量6 \& T+ F& U0 g; e# Y& r
Minimum distance estimation, 最小距离估计, h# M/ K* t7 P( ?( x4 G, t
Minimum effective dose, 最小有效量 r) }$ Z- O& B2 _
Minimum lethal dose, 最小致死量% O$ K5 S" V3 w" `
Minimum variance estimator, 最小方差估计量* j0 ^- A: j$ ^( f# _
MINITAB, 统计软件包/ }* q. o# C* [5 H" p7 r+ K
Minor heading, 宾词标目0 G: j9 @( ` o: w7 w9 U/ S% e
Missing data, 缺失值8 g9 B% s5 G2 y; R
Model specification, 模型的确定, V5 G- R( G3 l* j5 D" q7 ]5 f. Y
Modeling Statistics , 模型统计; ?$ [5 r+ K5 |/ K/ F2 m |
Models for outliers, 离群值模型
9 v5 H% y- Q3 I, r1 h: @Modifying the model, 模型的修正6 N$ _" O- a* }8 Y) o3 t
Modulus of continuity, 连续性模
! C# k! M; {4 w3 X }8 h: UMorbidity, 发病率 * l4 n& E* N% ~, o
Most favorable configuration, 最有利构形
& I5 u- L/ R2 b2 p e/ X6 xMultidimensional Scaling (ASCAL), 多维尺度/多维标度4 h8 _5 S! I2 W7 _& G2 g2 u3 N( t5 L
Multinomial Logistic Regression , 多项逻辑斯蒂回归
: Z, [/ y, G, s- nMultiple comparison, 多重比较
. B6 s% i- l9 c- L GMultiple correlation , 复相关
. V6 B) K r: i: {0 v" ^& j- oMultiple covariance, 多元协方差2 `% Y. I, P2 G% G
Multiple linear regression, 多元线性回归5 @' D* E$ v [2 J/ ~* M
Multiple response , 多重选项
; Q) v7 h8 W5 G) ?0 N& i" g) Q, FMultiple solutions, 多解6 p, W3 }1 U/ w: G: n6 c
Multiplication theorem, 乘法定理3 L1 A& G7 k: \# p- }9 Y
Multiresponse, 多元响应
# b" c( h. i; rMulti-stage sampling, 多阶段抽样3 K, M7 ^0 E$ Z: R+ p
Multivariate T distribution, 多元T分布
2 N, Q' X4 L6 ^Mutual exclusive, 互不相容! r) s/ K2 _' t+ T
Mutual independence, 互相独立 K6 _5 k) e. @ U) ~, r# s) J
Natural boundary, 自然边界1 C) V0 Z/ d! N6 ~1 h% g4 Q# A5 Z
Natural dead, 自然死亡
0 ^% K0 F" I2 N4 pNatural zero, 自然零
* l! j! K6 E, f5 M NNegative correlation, 负相关2 o" Z- l) _) v) A o- Y- \3 Z( _
Negative linear correlation, 负线性相关
/ c s* Y5 g, T; l: vNegatively skewed, 负偏( S; S! l+ Z9 @1 O7 Q5 f
Newman-Keuls method, q检验
2 }$ N6 C) R5 Y$ S1 GNK method, q检验
; e- k D& o" y4 LNo statistical significance, 无统计意义
; r5 J0 k1 C$ ~; N: ?Nominal variable, 名义变量( W$ D- N$ q% @' m
Nonconstancy of variability, 变异的非定常性/ j; P c% d4 R t
Nonlinear regression, 非线性相关
* J6 w: E6 W2 k! W) uNonparametric statistics, 非参数统计3 w3 e4 \3 O$ W+ M) m6 n' ^ U
Nonparametric test, 非参数检验4 x# @5 T- c+ h. D
Nonparametric tests, 非参数检验, r) J1 K6 _9 K* Z3 n3 Q
Normal deviate, 正态离差7 K/ I; B. B: r/ Y
Normal distribution, 正态分布
' x e1 Z" h, GNormal equation, 正规方程组$ V* a& O3 Z1 W' _$ S4 G7 w m& I
Normal ranges, 正常范围
# B3 @' l" j: lNormal value, 正常值7 W* [, ]3 T) a2 m+ ]0 d
Nuisance parameter, 多余参数/讨厌参数6 y* ^! {4 E. b1 a% P1 M/ L
Null hypothesis, 无效假设
$ w- X; y1 B' U% nNumerical variable, 数值变量) \% u; [, z# ]; H: t
Objective function, 目标函数
4 ~7 n4 c& m; Q# Z' ]& n LObservation unit, 观察单位6 k7 K1 i! @. M6 c# I8 b" `
Observed value, 观察值
) n5 E+ R; }3 e6 N" m7 x; tOne sided test, 单侧检验9 l3 v. y. Y+ k4 J& b& ~* e
One-way analysis of variance, 单因素方差分析" Q9 l6 G1 ^! B! k
Oneway ANOVA , 单因素方差分析) w( T4 G6 B2 z* c) D# W
Open sequential trial, 开放型序贯设计# l6 |% Q' ]. a0 P* F& t
Optrim, 优切尾
2 o0 T) t) O7 u8 ` i. @8 a, p% TOptrim efficiency, 优切尾效率* R) i# k$ O" M# q1 @
Order statistics, 顺序统计量
- N- r$ Q5 L" Y4 { {8 fOrdered categories, 有序分类
* A! g: ]( K) ]6 Q2 j" \Ordinal logistic regression , 序数逻辑斯蒂回归
1 j5 A" j h7 }Ordinal variable, 有序变量
5 [4 w, t; o% C; V1 VOrthogonal basis, 正交基 u: a1 j! a6 R- Z$ _" x
Orthogonal design, 正交试验设计, @5 u1 n L* b+ f! c$ i
Orthogonality conditions, 正交条件0 |. k% c/ ]% J6 j. D# U* _, H8 H
ORTHOPLAN, 正交设计 2 @5 n! m2 j! N2 h
Outlier cutoffs, 离群值截断点: f9 S/ l/ v3 ?3 P7 F5 h5 X$ W5 m: q
Outliers, 极端值
: P4 @: ~$ c5 c, Y* @, {8 pOVERALS , 多组变量的非线性正规相关 6 `; l5 p7 f, S9 t% Y: }; p" A, m
Overshoot, 迭代过度5 p3 T# H: U$ O, Y6 R5 W/ O% T
Paired design, 配对设计
5 Z: ?8 Q q- J3 JPaired sample, 配对样本: i; g0 C0 E5 ^
Pairwise slopes, 成对斜率
. W! o& W) a) W! B4 K2 q" S0 Y* s7 DParabola, 抛物线
( Z9 `3 e: d- G: oParallel tests, 平行试验
. H" k' ^& P8 Y6 L0 ^* X* TParameter, 参数
2 z: u* Y1 i; gParametric statistics, 参数统计9 R* u: d' k0 T3 _1 u1 U
Parametric test, 参数检验
& q3 f% U J3 ]) p" F; hPartial correlation, 偏相关3 A* _4 a& D d* n9 G" a
Partial regression, 偏回归
3 `7 v; I' K: E0 O) g( d* EPartial sorting, 偏排序
, E! K3 T6 ^0 cPartials residuals, 偏残差
. ] R, t3 ?& f: m5 f6 XPattern, 模式
, s/ s) E# P$ K% o1 hPearson curves, 皮尔逊曲线' E; q6 f+ Z2 F( ]8 M
Peeling, 退层
% B ^9 b* j4 KPercent bar graph, 百分条形图3 x. e6 p A- G3 z
Percentage, 百分比
4 o3 y; c. M7 v4 FPercentile, 百分位数
" N% S: q( N+ yPercentile curves, 百分位曲线
8 }+ U9 @# P" j! ~0 r# I, b9 i1 dPeriodicity, 周期性
& h6 W* ]. G, WPermutation, 排列7 i& Q0 |& \5 m" _; @5 P; l
P-estimator, P估计量6 |! n; ^3 C) }- s6 v- P5 S6 ?" o
Pie graph, 饼图# Y) i4 Y1 |+ Q$ j, e8 c. k% S1 B
Pitman estimator, 皮特曼估计量
5 Y3 ~! r7 B/ m& a2 W) u$ n+ n* ~2 YPivot, 枢轴量
& Z4 R; v. \0 I @ _7 O! a9 EPlanar, 平坦( u. `7 N$ h5 x
Planar assumption, 平面的假设& a0 ?! c- k5 U
PLANCARDS, 生成试验的计划卡6 e$ t9 I4 v) i- ^4 g1 ^( D$ Q
Point estimation, 点估计. I! k2 s6 T- t; u3 a8 Y% F4 m
Poisson distribution, 泊松分布
* `! Q2 {# }" APolishing, 平滑
- Z5 W- j5 M, NPolled standard deviation, 合并标准差, e+ z" [! t+ w3 G* k) ^9 a
Polled variance, 合并方差
& G# q$ L* N# K6 o+ ]Polygon, 多边图
# G# [1 P" m8 xPolynomial, 多项式
( v4 h5 n. X8 | [Polynomial curve, 多项式曲线
8 q" C! G6 `$ @$ w2 zPopulation, 总体& f( J* O6 e7 o3 n
Population attributable risk, 人群归因危险度2 T: ^ p' M5 h- {! A' ^! z( W
Positive correlation, 正相关
7 E a! o1 P% [1 s- K% X, }Positively skewed, 正偏
( a/ s5 J6 X& ~2 M2 v# pPosterior distribution, 后验分布
2 R* k& [* p/ E ~Power of a test, 检验效能
% x* [5 @. \, }( rPrecision, 精密度) j! X! k/ `+ [5 [* B% o
Predicted value, 预测值
; x* N/ \8 c; o0 k0 \Preliminary analysis, 预备性分析
( ~. z: v) T1 x% g; T+ EPrincipal component analysis, 主成分分析
# Q0 {+ B* p# a0 D! s Y5 K! B; GPrior distribution, 先验分布
& l, k1 ?$ R0 s! {: E8 TPrior probability, 先验概率- ?3 ~! c% X! q/ l
Probabilistic model, 概率模型7 @" X7 h5 S$ p) I: X
probability, 概率2 Y. a( q: \. k6 ^8 z
Probability density, 概率密度' y! o5 d# X& O# y
Product moment, 乘积矩/协方差
8 x8 f& i6 `( q4 T9 b$ xProfile trace, 截面迹图/ q2 z, j/ y* M0 [: a/ l' P2 N
Proportion, 比/构成比" v0 k; Q2 ]7 P X( s* `
Proportion allocation in stratified random sampling, 按比例分层随机抽样
8 T+ c2 P Q4 ]# [Proportionate, 成比例; w n+ Y. s. X% L; }
Proportionate sub-class numbers, 成比例次级组含量
* w( j; d' G, U7 _! b9 c; Q) ], BProspective study, 前瞻性调查% z, t/ Z0 I- \! S8 q
Proximities, 亲近性 * X9 S( r/ Q9 b6 O2 Z, X
Pseudo F test, 近似F检验* f! k, O9 o& z+ J
Pseudo model, 近似模型
# F& s5 H' h8 N) L& mPseudosigma, 伪标准差
# j7 j# T( M* C4 aPurposive sampling, 有目的抽样
( v# T c2 N+ R. E+ `2 y! x1 b( XQR decomposition, QR分解
( C3 ?# g( e2 }9 e) p/ YQuadratic approximation, 二次近似2 G+ `9 {7 g1 f0 e# H5 z* h! y
Qualitative classification, 属性分类* E! D+ ^, z3 e0 I! m% c3 \; M
Qualitative method, 定性方法
) ^8 | ]- R$ j5 e* T% CQuantile-quantile plot, 分位数-分位数图/Q-Q图2 K; j r' B6 Y& D" l
Quantitative analysis, 定量分析
9 b7 w* T v) mQuartile, 四分位数
9 g6 k3 w+ h' |4 L2 IQuick Cluster, 快速聚类
; f6 p( |/ y) a7 g$ z4 PRadix sort, 基数排序
4 V* S: A3 a6 m$ U$ D- J+ K) DRandom allocation, 随机化分组
9 G c$ D+ f/ `5 v+ Q) k( H, i7 gRandom blocks design, 随机区组设计( i9 G2 M9 h5 |( T* Q
Random event, 随机事件
$ O3 L, ^7 U) |Randomization, 随机化
5 E$ f( o* j8 _% |Range, 极差/全距
; g- d! h j* h& w: {& v) P! SRank correlation, 等级相关
8 \! X+ ^7 R m0 `9 F5 uRank sum test, 秩和检验
% |- [ ^! n. `& @: u7 bRank test, 秩检验2 I( V7 D& Y9 Y t+ G0 j% F; b
Ranked data, 等级资料
0 W) U9 M' o. h! ~' p rRate, 比率0 @& ]- Z G/ q! M# x2 @& }% K% S
Ratio, 比例
& n& u6 d: t' J0 m( @$ GRaw data, 原始资料; b- X$ J O8 q
Raw residual, 原始残差
8 w7 b7 x1 g6 x2 `8 y7 O/ HRayleigh's test, 雷氏检验 t7 _, E, F* \; e' P
Rayleigh's Z, 雷氏Z值 - |1 t5 \+ W4 }" I; O1 y
Reciprocal, 倒数1 g' N- ~! R+ l( i0 W& I6 g, A3 e
Reciprocal transformation, 倒数变换
% l7 H( b0 d) vRecording, 记录
5 c s# F6 J3 Z" _7 a& fRedescending estimators, 回降估计量
- R) s, z- K7 S3 w: i8 J) KReducing dimensions, 降维
) }9 @# s8 I* ]5 ^. QRe-expression, 重新表达8 O8 A! J3 O. {5 M! p
Reference set, 标准组8 m4 L- h3 I0 ^3 U# U
Region of acceptance, 接受域5 [, _7 U* Q3 G% l- I
Regression coefficient, 回归系数
: v$ V9 r* o# V) H+ y, ?Regression sum of square, 回归平方和
% K( A* \$ `3 {6 h3 xRejection point, 拒绝点
/ t+ N, P# R, F! A* V t$ gRelative dispersion, 相对离散度
" z0 K8 a& ?1 ~+ k4 z LRelative number, 相对数* g- v4 a7 ^/ D3 D# H0 q
Reliability, 可靠性
" O1 A/ X0 a5 H0 ] zReparametrization, 重新设置参数
2 E7 J6 L7 X4 a( WReplication, 重复
( O) G/ w x2 G2 m, s3 V$ r) Q- tReport Summaries, 报告摘要/ A1 H1 ?% P- P; v$ U6 L0 w
Residual sum of square, 剩余平方和
* P3 h0 P- a# K7 ~1 h7 ~. VResistance, 耐抗性5 H4 {0 p$ d F O
Resistant line, 耐抗线
3 D. v r1 f. A; mResistant technique, 耐抗技术 N( Z8 ^# z: b7 U K5 \% M3 M
R-estimator of location, 位置R估计量
$ j/ d/ {0 `0 g! h" k' nR-estimator of scale, 尺度R估计量8 x8 ^; a S- Y6 [% n( }
Retrospective study, 回顾性调查$ `8 d/ W, b0 `$ ^( k9 F* l) W( ]2 G
Ridge trace, 岭迹
! e, I7 [, z. ]+ MRidit analysis, Ridit分析
! g: u* o$ n& uRotation, 旋转' W' D O1 c, C. s2 u5 \
Rounding, 舍入1 n7 @9 M/ m, W( `
Row, 行: F$ L: g) {! R! A
Row effects, 行效应- P8 R' z" E- B; @
Row factor, 行因素: ~$ V; G% F+ o. A; i, ]
RXC table, RXC表
2 L, e. Q7 b- d' sSample, 样本
$ u; ^5 p3 E# B/ h+ [ XSample regression coefficient, 样本回归系数
' ]8 w0 V, c( Y) V4 `* MSample size, 样本量' }6 C7 Y6 F+ g7 }2 G( T3 V
Sample standard deviation, 样本标准差
. M0 o: t; E" ~: F! H2 @Sampling error, 抽样误差
* ]) X& V6 J( X1 L5 D- a9 x; L8 `SAS(Statistical analysis system ), SAS统计软件包 E) Q( X ]& O4 m( A
Scale, 尺度/量表
4 n( Y" j8 N1 G1 L" e2 GScatter diagram, 散点图! K) k9 y6 [2 U' t# i
Schematic plot, 示意图/简图7 }1 ~6 b9 r6 `
Score test, 计分检验% w p! i8 l$ _; {4 \
Screening, 筛检
0 M$ u& G9 h5 \SEASON, 季节分析 ( y0 L. l7 X0 ], q) W6 y
Second derivative, 二阶导数
# u7 M: J( e8 F; s0 qSecond principal component, 第二主成分
7 C6 `" _# j, n2 GSEM (Structural equation modeling), 结构化方程模型 ' g% Z/ S: t6 V
Semi-logarithmic graph, 半对数图
7 a. I- `4 k: P; d( j% n% k/ ~Semi-logarithmic paper, 半对数格纸
{9 x6 s) B/ ^5 BSensitivity curve, 敏感度曲线0 ?3 I& S" b* P6 z T) }
Sequential analysis, 贯序分析
! s1 k. k5 |5 n2 KSequential data set, 顺序数据集
. f% v, z+ h, [! BSequential design, 贯序设计
9 Y& D3 w% M! o1 PSequential method, 贯序法- x' j# l0 S% u* _
Sequential test, 贯序检验法, Q0 |# Z8 h* {- R1 B
Serial tests, 系列试验8 Z) o! u, R$ Y8 c* ~/ y$ b3 ~+ A
Short-cut method, 简捷法 - O0 A4 v- E( I: l! M3 m$ C
Sigmoid curve, S形曲线# `/ j y1 o( z; @7 \( @
Sign function, 正负号函数2 V4 k; g4 S3 ~- F
Sign test, 符号检验. L* K" n/ `% E) `2 f* q
Signed rank, 符号秩
/ F( d6 c0 y" t" ?# l: J3 FSignificance test, 显著性检验
. f& S* ]/ O1 a. {$ `Significant figure, 有效数字# F- W9 n9 ^# S; ?7 V: X, m7 V
Simple cluster sampling, 简单整群抽样6 {- Y( z& ~0 {6 U5 l: \# J
Simple correlation, 简单相关& M, s7 w" P2 c* W7 T/ r
Simple random sampling, 简单随机抽样' @- ], ^% y& e) r3 t- G5 a, b
Simple regression, 简单回归7 p* a& N! U2 L1 X& _# j2 B
simple table, 简单表$ @5 ?! ]# D* x9 C3 T4 J$ x, y
Sine estimator, 正弦估计量
5 ] @( h$ \' e+ R( h- I% y. LSingle-valued estimate, 单值估计
; s! X; P, y8 HSingular matrix, 奇异矩阵4 A- a* }7 x8 T# H
Skewed distribution, 偏斜分布4 d, H8 O9 n5 ?
Skewness, 偏度( T! x: m) c* ]& s
Slash distribution, 斜线分布
7 u- c$ t3 b6 |1 z; d, x( \* gSlope, 斜率
# ^7 f" { K! X; N0 k- N/ TSmirnov test, 斯米尔诺夫检验
7 Y3 S0 A2 [+ ]9 hSource of variation, 变异来源 U. k: V4 ~. w V [# n; q
Spearman rank correlation, 斯皮尔曼等级相关; o; q7 [ N0 ~( `2 g+ e
Specific factor, 特殊因子
5 X" Z$ h: Q2 e1 t- T/ [Specific factor variance, 特殊因子方差
) z2 |% e& x* `' y# wSpectra , 频谱5 x, `6 w! q; c4 Y. K
Spherical distribution, 球型正态分布
) N: {3 }4 {) a2 t& NSpread, 展布2 h/ D' Y+ ^% [( m) Q, Q
SPSS(Statistical package for the social science), SPSS统计软件包$ W# C) S8 d- l% h. C% r! p
Spurious correlation, 假性相关
) c2 B( w7 m {, Y NSquare root transformation, 平方根变换
1 D: @( T7 t- U! CStabilizing variance, 稳定方差$ x7 i6 i/ c$ }( K
Standard deviation, 标准差
- X& M9 h6 H, ^/ Y/ VStandard error, 标准误9 {9 Y( A( u' Q0 F* p1 N$ G
Standard error of difference, 差别的标准误
" G6 O0 B& S4 XStandard error of estimate, 标准估计误差
$ b8 ?& ?, }8 {4 ?8 i5 lStandard error of rate, 率的标准误7 c! E) p+ I' Q# s
Standard normal distribution, 标准正态分布
$ J1 k% O3 y* y J! ?7 F, nStandardization, 标准化
5 |9 _6 |3 r8 E& XStarting value, 起始值
0 H6 P$ x( m+ S+ pStatistic, 统计量/ U- @8 ]/ u. I; ^% z- b( `
Statistical control, 统计控制
! Y& G* v, B3 l0 c0 ?! ^/ G1 QStatistical graph, 统计图
" H7 L! g1 q* g7 v& [3 bStatistical inference, 统计推断7 d5 o- R1 o- \3 ]) T0 ?" R
Statistical table, 统计表
9 n9 a# o0 B+ s2 ?1 ISteepest descent, 最速下降法+ Q- j! r6 B* o' i% ?* j( t9 E/ S! m1 w
Stem and leaf display, 茎叶图
* X/ A( I3 m( r" WStep factor, 步长因子% \( x8 f' J5 _& V/ H
Stepwise regression, 逐步回归
8 `3 [: S# D0 }* ]/ B6 m4 F! C6 Y& gStorage, 存! a+ M6 ~$ H# \/ P% G
Strata, 层（复数）* @8 v: z' m: o8 G/ f
Stratified sampling, 分层抽样
' s" E" Q& m6 Y, }Stratified sampling, 分层抽样, M0 E5 ~* b; Y$ O( M& F! ? h, A+ e
Strength, 强度
4 s [+ p0 H1 m- v$ XStringency, 严密性
1 U# f, h* i5 I, LStructural relationship, 结构关系
6 K) d$ H$ i) r5 t" }Studentized residual, 学生化残差/t化残差
! j% O- S5 E6 W; Q8 iSub-class numbers, 次级组含量
" @6 R* m- F3 [2 _ q* _" lSubdividing, 分割2 ]. [: T, L2 O2 A3 F9 |
Sufficient statistic, 充分统计量
! z3 f+ L* l* D1 PSum of products, 积和
. s+ V* N! h/ n/ h" J2 vSum of squares, 离差平方和 h( R4 y5 q6 y' Z
Sum of squares about regression, 回归平方和
0 ]+ r5 l2 A) k6 l) NSum of squares between groups, 组间平方和
6 z$ ^" y* V0 `6 m3 W2 |Sum of squares of partial regression, 偏回归平方和0 L- g( r& Z# K( _' g8 l, v
Sure event, 必然事件0 p1 E# e5 m# C, p' i2 F
Survey, 调查
# x& ^% k; q9 USurvival, 生存分析 {2 D( L8 B* P% q/ Q5 I
Survival rate, 生存率
: K* i7 L. L [" D f u- s; b2 |( ~Suspended root gram, 悬吊根图
1 z5 ^% c2 o7 O' J) MSymmetry, 对称; h2 _+ A5 y7 _
Systematic error, 系统误差
3 \5 F! m7 v* \8 gSystematic sampling, 系统抽样$ \& s$ _: T7 o f* S* j6 G
Tags, 标签& B" a. v- `0 p/ i3 G) R
Tail area, 尾部面积' j5 {. I" ~* W+ ~& |9 l
Tail length, 尾长: \# ]- O( n3 v! ~# T
Tail weight, 尾重9 ~5 u! c4 V0 M9 y3 R8 I
Tangent line, 切线. F" R* H/ n, N) \. m! e5 }
Target distribution, 目标分布
* a1 t- p, ?( rTaylor series, 泰勒级数
+ c. j3 ?$ B2 fTendency of dispersion, 离散趋势9 ^( s0 ?, {0 z9 ~
Testing of hypotheses, 假设检验
! O8 c+ z1 R9 g- W+ j+ {3 p: bTheoretical frequency, 理论频数 n/ o/ C7 {* a& E& c' A/ D: T$ k+ r
Time series, 时间序列
4 r/ F" Q- e9 z B! t; }Tolerance interval, 容忍区间" h' S3 t, z+ h* ]9 a8 @
Tolerance lower limit, 容忍下限 m4 }/ c7 a" |* C. a- {
Tolerance upper limit, 容忍上限9 ~8 h# o- B6 @0 @ `3 V: g# `# |
Torsion, 扰率3 I" ?) y. V1 z# L; h
Total sum of square, 总平方和; }- U. ~) H% Q! D5 G" E
Total variation, 总变异
) g z) w, L X% U. e) g. h8 rTransformation, 转换
% u' X' ]/ ]$ z6 {. tTreatment, 处理
' O2 r) x- f" y7 _- LTrend, 趋势7 Y: T0 e' t4 z
Trend of percentage, 百分比趋势8 {( ~# m7 j4 ?' }, X4 y
Trial, 试验 I+ S$ S3 P2 s/ x1 E" ?
Trial and error method, 试错法
" l, e1 x6 h/ C3 Z1 U. [Tuning constant, 细调常数
- A- c. q t0 } z4 p7 D- Y' r7 DTwo sided test, 双向检验3 Y- E9 Q- X, c
Two-stage least squares, 二阶最小平方
; o" U* I/ T7 s/ M; p T6 aTwo-stage sampling, 二阶段抽样
3 E3 M0 i5 Y5 R7 Z- b' B: fTwo-tailed test, 双侧检验' Z# d0 J( a) I+ N* { f" W9 Q+ O) H
Two-way analysis of variance, 双因素方差分析1 d2 f5 `' O9 ^- Q* f/ P
Two-way table, 双向表
- X' _' B; K5 K4 r. xType I error, 一类错误/α错误9 q* O# Q% d8 m1 M
Type II error, 二类错误/β错误6 B& }0 p7 M. B3 X7 H: _# q
UMVU, 方差一致最小无偏估计简称- G; J, [, V" p
Unbiased estimate, 无偏估计: d) O: b% I; ]% B
Unconstrained nonlinear regression , 无约束非线性回归, o* `# a1 m* J8 B0 [
Unequal subclass number, 不等次级组含量
3 z: e9 e! s0 m$ k7 o$ ]Ungrouped data, 不分组资料
2 ~* x7 i$ ]' c: uUniform coordinate, 均匀坐标/ }2 ]6 p% ?& b7 r" p1 e
Uniform distribution, 均匀分布/ N& U* [+ o8 t; O0 _, H! g+ v! `7 B
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计7 o# j& e! \; a
Unit, 单元
9 p" }! o; Q/ w0 M, }Unordered categories, 无序分类: ~- B& F0 q" S S `
Upper limit, 上限; w+ W# B# u z7 F9 m* ? ~, d0 W' @
Upward rank, 升秩6 Z9 k6 X H0 S4 v" K4 {- E9 K
Vague concept, 模糊概念* p% D: a& u6 h8 i1 ~) f( a
Validity, 有效性
- ^0 x: l1 R2 Z' Y) l- Z4 O* QVARCOMP (Variance component estimation), 方差元素估计
+ G- }% p! d+ z9 B7 yVariability, 变异性1 E$ [1 q# s8 a4 z4 R
Variable, 变量! l' V5 }6 H) I/ c( R1 p
Variance, 方差
" E5 `) J$ X+ V+ p1 ?! l$ XVariation, 变异
. [, o* m+ ~: hVarimax orthogonal rotation, 方差最大正交旋转
" U7 A, q* t' {+ RVolume of distribution, 容积
0 C2 k9 n, g% R- @. ?7 uW test, W检验
/ @/ O" b- E9 I1 N3 r& d! cWeibull distribution, 威布尔分布
( V7 T, U) H) w9 GWeight, 权数$ _* r% n+ g% i$ ]5 I8 S6 S/ \1 L
Weighted Chi-square test, 加权卡方检验/Cochran检验+ T3 H2 c" p; J7 K1 d( I. t3 y+ r, z
Weighted linear regression method, 加权直线回归
7 ?+ Q- U% o% ~% HWeighted mean, 加权平均数
3 c9 Q6 j3 y' ^, z1 AWeighted mean square, 加权平均方差- Q$ C1 b4 L: B; h" F9 A
Weighted sum of square, 加权平方和
E/ L5 W& B% @- OWeighting coefficient, 权重系数# C H9 w4 }- n0 M
Weighting method, 加权法 n$ L( h: `$ Z' ]. I
W-estimation, W估计量
& r, a& T3 a( [' x7 ]* p! Y* mW-estimation of location, 位置W估计量5 w$ x3 Y5 F5 Q1 _2 z( a) b
Width, 宽度
T8 F# h' e4 e+ o7 B6 V4 _Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
+ _) h1 N: C. ^& u# J, E: i y& XWild point, 野点/狂点3 v j: F( j) H" p
Wild value, 野值/狂值
* ], W7 s/ M& _& qWinsorized mean, 缩尾均值
& r$ I% j8 T; j% ]/ LWithdraw, 失访
6 D0 C8 O0 t# p0 T1 S' L( P5 }5 NYouden's index, 尤登指数
3 _4 o i8 _3 K/ YZ test, Z检验
* H4 j8 g5 Y- Q! ]! u# p4 {Zero correlation, 零相关
2 Z: w7 Y# Y( s: S$ v: yZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
