|
|
Absolute deviation, 绝对离差4 I' v' k$ R3 y3 [ K; N# x
Absolute number, 绝对数
% ?' F7 B. _' F" M/ u& GAbsolute residuals, 绝对残差0 [ ?: m- L, I$ ]
Acceleration array, 加速度立体阵
! t* g1 H0 N4 f1 jAcceleration in an arbitrary direction, 任意方向上的加速度- H0 h! l7 y" ]; v
Acceleration normal, 法向加速度. W% R7 g. g) ~; j, r
Acceleration space dimension, 加速度空间的维数4 y& O; _' q$ O
Acceleration tangential, 切向加速度% e4 N7 y! n6 B$ d
Acceleration vector, 加速度向量
N+ c0 R& |1 L" V& R1 f2 TAcceptable hypothesis, 可接受假设, u. u$ h0 e1 t2 ~8 _8 G
Accumulation, 累积
2 K* e( n- i g$ n; F( O9 JAccuracy, 准确度- V( w$ T3 e7 x1 H' b- u
Actual frequency, 实际频数
7 l9 o7 G3 H# G4 g- N2 X$ mAdaptive estimator, 自适应估计量5 T) F8 n( u' [" P- z3 J
Addition, 相加
, \4 [5 r' s) M% F+ vAddition theorem, 加法定理
, J0 Z6 `# _2 h3 H5 uAdditivity, 可加性
5 T0 o( l8 P$ n" rAdjusted rate, 调整率
' E& l9 I( X' {Adjusted value, 校正值) q! {' ?, @$ ^1 V: h
Admissible error, 容许误差
" o4 M' h. A. L& Y- t0 @Aggregation, 聚集性
7 q1 b4 |0 t* l- ~Alternative hypothesis, 备择假设; _2 |! D6 @3 \
Among groups, 组间6 g0 w+ M# { A% M: B2 G3 n# [0 n
Amounts, 总量0 r1 h8 M9 N0 `/ t. `
Analysis of correlation, 相关分析
1 X! }1 |- e( R% d, C1 ZAnalysis of covariance, 协方差分析
! i+ J# }7 n: e jAnalysis of regression, 回归分析
* v, O) K& P& g6 QAnalysis of time series, 时间序列分析5 B: ?) G3 Z* R$ ~6 {' x1 T
Analysis of variance, 方差分析
% [# o4 m# o$ PAngular transformation, 角转换& _ v6 C) i6 z; l3 O- ~7 g- [' m
ANOVA (analysis of variance), 方差分析
, l. x- t1 P3 LANOVA Models, 方差分析模型
. i% D4 w+ a; ]2 |1 i$ P4 F AArcing, 弧/弧旋7 ~- s0 N% t+ e" r8 N$ F
Arcsine transformation, 反正弦变换5 T; Z) _ N3 V" A5 d
Area under the curve, 曲线面积
% N4 Z V; J3 ~5 l4 Y! HAREG , 评估从一个时间点到下一个时间点回归相关时的误差 9 n0 w6 f( I" P
ARIMA, 季节和非季节性单变量模型的极大似然估计
$ d' Q; w3 g1 F' aArithmetic grid paper, 算术格纸& c4 c2 [4 @8 Q5 p0 [ ?: c( _. Z
Arithmetic mean, 算术平均数3 T( w' s n6 s. q2 T$ k! w5 o& H2 [7 b
Arrhenius relation, 艾恩尼斯关系
* k* x1 M8 C8 T7 I# l0 b0 Z" [; `Assessing fit, 拟合的评估
$ Y! j3 j/ t- k* ^" D+ eAssociative laws, 结合律
& m& k2 \/ b, L; EAsymmetric distribution, 非对称分布5 \/ t' a' z; o; y* ?9 [: j
Asymptotic bias, 渐近偏倚1 o- B* x% M$ ~$ U; W# d; j; ?
Asymptotic efficiency, 渐近效率
3 N2 U% G( l' `9 P6 j! d! ?Asymptotic variance, 渐近方差
/ k% \, u! H+ g; W* XAttributable risk, 归因危险度
2 ]9 J V+ V+ H+ ~Attribute data, 属性资料+ o9 F2 e8 D3 J' c7 c( E. s! [
Attribution, 属性3 w7 H( z4 C; D! x5 W- s
Autocorrelation, 自相关
1 Y+ X" X3 l' t, P2 m) d3 u2 ?* [Autocorrelation of residuals, 残差的自相关. _" g4 P6 E" v
Average, 平均数
4 U; \/ D+ q. r7 \" a$ v& @% bAverage confidence interval length, 平均置信区间长度, r- ]9 G* O' n% j/ ?& [
Average growth rate, 平均增长率
. C$ j. w+ n0 Z! |Bar chart, 条形图
1 y& X% o/ K. q% E+ ^% o$ c+ MBar graph, 条形图9 C7 T5 ~3 G1 q9 U
Base period, 基期
, u* Y2 ~8 E( J0 i. D( [. `( dBayes' theorem , Bayes定理
/ e/ F2 \) f6 {# M/ B0 NBell-shaped curve, 钟形曲线, D1 r4 o% i: {* p! g- Z L D: {/ S
Bernoulli distribution, 伯努力分布% r; T, Q) G% H- l4 A1 Y
Best-trim estimator, 最好切尾估计量
/ W$ S# z1 v" h9 I# z! m& L6 x6 ABias, 偏性
, v+ ^6 [4 r" B% {4 |$ `& WBinary logistic regression, 二元逻辑斯蒂回归
" }+ T+ n6 e* g/ N* xBinomial distribution, 二项分布
- {: Z9 _ r. K- r4 \1 {. M" cBisquare, 双平方( ~% g+ l. q7 \/ m% Q" m) w
Bivariate Correlate, 二变量相关
* u: E; m3 K; E z1 \7 x/ wBivariate normal distribution, 双变量正态分布- U& C2 n4 p- t
Bivariate normal population, 双变量正态总体
U# o+ ]: C" `: GBiweight interval, 双权区间# H# c4 O2 h- ]* P3 |
Biweight M-estimator, 双权M估计量
, R; x7 r: w$ F& NBlock, 区组/配伍组
8 H3 l8 D0 ]' w! Q) Y. kBMDP(Biomedical computer programs), BMDP统计软件包
' C2 S) n7 n1 I: n9 XBoxplots, 箱线图/箱尾图
, X b7 T# L5 `! `/ [0 f* X/ GBreakdown bound, 崩溃界/崩溃点' X* ?0 s9 u1 t
Canonical correlation, 典型相关
; m7 z% M1 I3 T' _: eCaption, 纵标目9 `8 R4 D4 c- U5 I
Case-control study, 病例对照研究2 g) f1 _/ D* k2 P: L: A. ]
Categorical variable, 分类变量$ x" s6 l9 a/ G2 J$ H( Z8 F
Catenary, 悬链线1 T( ~3 v: Z2 W$ m% r. M
Cauchy distribution, 柯西分布
: Z1 R, X+ y1 I: ICause-and-effect relationship, 因果关系8 `8 L: M, @# P2 @! U8 S. T
Cell, 单元
" d5 \# B; d# ?Censoring, 终检
- x3 b& n4 B2 }2 |* vCenter of symmetry, 对称中心
+ p2 U) j+ D; g: C9 c& r' wCentering and scaling, 中心化和定标/ e; n5 P p4 }6 \" x; Y* i$ y
Central tendency, 集中趋势
: z& k' ~2 ]4 b$ S" E5 oCentral value, 中心值' K/ m( Y% d& N
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测9 s3 e. q' {. H, Z! A& A
Chance, 机遇
, Z6 b% I+ t/ Y0 sChance error, 随机误差
" M" Y3 s+ C( J4 T6 m2 p/ D% MChance variable, 随机变量# X& g6 p+ }. k$ N( w+ g
Characteristic equation, 特征方程; L" `/ X% O2 ]7 R
Characteristic root, 特征根0 d, N# N4 \+ \* |$ z: I E
Characteristic vector, 特征向量9 B: R9 G9 w$ R5 ~
Chebshev criterion of fit, 拟合的切比雪夫准则
! B* h1 S" w* NChernoff faces, 切尔诺夫脸谱图
. B, | S! s5 i; TChi-square test, 卡方检验/χ2检验
( {1 O1 T1 E: D6 l0 t/ nCholeskey decomposition, 乔洛斯基分解3 Z; A3 M7 w6 e) t$ ?8 d5 A
Circle chart, 圆图
0 w3 W1 N C8 _& T7 ~# Z6 cClass interval, 组距* n. C' P8 h: B2 K* W
Class mid-value, 组中值
8 I" f8 q" S" J2 U: a( IClass upper limit, 组上限' K7 T( K j% a i* ]9 b
Classified variable, 分类变量
) R/ l4 C+ B$ [: l: V6 K. GCluster analysis, 聚类分析: V3 F9 ~3 b+ y! T) t1 \9 R
Cluster sampling, 整群抽样8 Z7 T5 O& _8 h% y- X
Code, 代码
/ z) V8 G" m' [7 u% TCoded data, 编码数据
- o2 v: g6 e0 y% T' h( W: K! R7 h& |Coding, 编码# k n; |: u+ R, F2 y
Coefficient of contingency, 列联系数0 `& T$ R8 `6 \: J( p& w8 ]4 B$ m
Coefficient of determination, 决定系数
Z% B8 z. l- z; B6 Y% c x" o8 nCoefficient of multiple correlation, 多重相关系数
4 K; n2 x" ^* I3 H* y: U. E% VCoefficient of partial correlation, 偏相关系数) u2 y' b4 h' `; q
Coefficient of production-moment correlation, 积差相关系数
5 b: k p0 c2 W" B8 u& g2 PCoefficient of rank correlation, 等级相关系数+ z' A" l: X* ?$ V# V
Coefficient of regression, 回归系数
- d' T% R w v: N1 i3 d1 h/ uCoefficient of skewness, 偏度系数
, J/ \" O/ L7 r5 jCoefficient of variation, 变异系数8 \; [1 U( R( M/ i* d
Cohort study, 队列研究
* K- ?+ w7 {% Y |* q# v+ ^. I6 bColumn, 列
% M; `0 r3 f2 e! O5 E4 mColumn effect, 列效应
/ N$ R) J( h; X9 X' lColumn factor, 列因素
: V# m; K" K% nCombination pool, 合并
8 S; E+ @7 M4 C: P4 e! B; PCombinative table, 组合表
! e) i7 I0 @( A$ v! F# ACommon factor, 共性因子
. X+ y+ l/ i+ JCommon regression coefficient, 公共回归系数
; P* w- h1 z; [/ U7 X/ oCommon value, 共同值
) p8 p1 o; q* r3 d' M- vCommon variance, 公共方差
6 z0 t3 e) P' Q% o1 \Common variation, 公共变异
& [. G8 A# I1 ECommunality variance, 共性方差0 ]& d9 Z* N# c+ x1 l
Comparability, 可比性
: W. j7 Z7 e1 H |3 V4 rComparison of bathes, 批比较- B; ?; E1 ?2 ]. v2 q, `5 [8 j
Comparison value, 比较值
1 o2 l. p: m' T: R7 D! Q) k iCompartment model, 分部模型
6 I6 W0 X/ B. u' \0 o4 ~. c; k& ^Compassion, 伸缩
, K, S4 K9 H! p9 A$ B7 A9 UComplement of an event, 补事件
( l" \7 t6 j8 q+ h4 v8 lComplete association, 完全正相关
1 q% O9 M, d# e! u. I' t' oComplete dissociation, 完全不相关0 N! z* ?8 k! `* a8 k+ |$ p5 |
Complete statistics, 完备统计量
$ n5 B' t, v% }1 n1 PCompletely randomized design, 完全随机化设计
9 [5 {/ ?6 V: J. p' p3 q+ b4 vComposite event, 联合事件9 H% {# l6 ]" `2 m+ [
Composite events, 复合事件' f4 L6 e, |3 _ l; |/ T& h
Concavity, 凹性
7 B/ t7 M0 h+ I& D& J+ m4 B0 nConditional expectation, 条件期望
( @/ g* z" T7 O+ N7 Q( ]. a6 ?" OConditional likelihood, 条件似然
% x& j# _7 A; q8 w$ `7 QConditional probability, 条件概率' f. T) }$ V( e/ U; T
Conditionally linear, 依条件线性
^1 {2 J5 ~9 Z" \# o& ^+ K$ w1 O/ CConfidence interval, 置信区间1 ~; ~! v3 O! q
Confidence limit, 置信限. X2 s$ W# r8 f7 F4 }8 C A3 x
Confidence lower limit, 置信下限
7 c2 `/ M9 B' z% `! j$ Z6 D* V7 rConfidence upper limit, 置信上限( Z4 m0 m: T) T3 C$ U/ F1 d
Confirmatory Factor Analysis , 验证性因子分析$ v! q9 q4 u! ^$ ^% c
Confirmatory research, 证实性实验研究) E5 {9 O1 n% w Q9 ^( K: J) Y" A' _
Confounding factor, 混杂因素: c) g* {. Z6 m; @( v4 h
Conjoint, 联合分析) c( N. A/ @* _# X2 e4 q
Consistency, 相合性7 d3 n# A+ M, F4 j- ?3 G
Consistency check, 一致性检验( u7 K0 i3 ~( X& h
Consistent asymptotically normal estimate, 相合渐近正态估计
\$ v/ Z$ H* T9 ~' A: \Consistent estimate, 相合估计
- e0 l& h$ z+ D- HConstrained nonlinear regression, 受约束非线性回归* |. ?6 T z8 w8 x w6 x
Constraint, 约束
8 q( V0 j9 k* _- l- g6 D% HContaminated distribution, 污染分布
7 X3 i# l% _# {9 F% d9 @Contaminated Gausssian, 污染高斯分布
' [5 i' O" l, F, t- h3 ~2 XContaminated normal distribution, 污染正态分布
( r, Y5 h( X0 Q! L. V5 m" iContamination, 污染# [, f! }0 k, n. C5 A
Contamination model, 污染模型 b: u) U( V- l: u
Contingency table, 列联表
; @$ P# ]8 D0 d% HContour, 边界线
# R7 F! w5 }' l5 UContribution rate, 贡献率
/ z! U- Y: [# i. ?7 i( [Control, 对照
0 i8 f1 ~( x- q2 oControlled experiments, 对照实验
' z* n8 {- \5 K2 u* c! @$ h5 ^Conventional depth, 常规深度
3 F6 g4 v4 s% W" V4 z8 kConvolution, 卷积
- B t+ l* O# ?) e' @Corrected factor, 校正因子
$ E; z" F1 c9 oCorrected mean, 校正均值
' R* j" [, f+ n# [3 C' qCorrection coefficient, 校正系数8 I- E) `& [5 m3 z; ?
Correctness, 正确性
7 f2 b$ v9 F4 Z C! x Z8 @' LCorrelation coefficient, 相关系数
# c1 H5 E3 P& J9 J2 ?7 i& l5 q9 KCorrelation index, 相关指数
. y( C5 h4 O! E* b1 |Correspondence, 对应
' Y0 h# M$ H: \ JCounting, 计数
7 M# Z! k: L3 W, O# c6 I% o8 UCounts, 计数/频数
- c' O7 g6 m$ ~* w7 ~* ^Covariance, 协方差
2 I7 I) g4 j7 M. p# J4 ?8 u( L. vCovariant, 共变 ; q& P/ F5 ^+ g1 g" J7 {6 D+ }
Cox Regression, Cox回归
5 E' T* Q8 L( i, bCriteria for fitting, 拟合准则
7 K0 Y3 h) Q- d7 w8 i# C0 h7 hCriteria of least squares, 最小二乘准则$ w5 ^; m) c/ \) r2 }
Critical ratio, 临界比
! y- {5 g# S9 SCritical region, 拒绝域9 ^1 L9 O* G3 m' z& A
Critical value, 临界值
1 m. v( `+ q* V9 OCross-over design, 交叉设计! H; ] f/ ?1 B* l# [ W
Cross-section analysis, 横断面分析3 N4 ?" P+ z& L+ ]* n S" F
Cross-section survey, 横断面调查
[; B; \ s) F9 I8 }" g- d) xCrosstabs , 交叉表
" u! ~) U- V: C/ d j. ~! RCross-tabulation table, 复合表
6 A, N' R' p3 i5 c; L0 {Cube root, 立方根
; E2 G0 j2 ~' V( ?+ c7 e+ F, ]Cumulative distribution function, 分布函数1 H/ A7 j* o. G: h) @
Cumulative probability, 累计概率5 |4 M- N7 Y% j8 L) Z
Curvature, 曲率/弯曲
3 ~" ]- r$ x5 J Q8 fCurvature, 曲率/ n6 V& N5 ` d! s7 f
Curve fit , 曲线拟和
6 B! k; M- a: I8 FCurve fitting, 曲线拟合
0 @% B1 t. X& P1 K- X/ H) I3 oCurvilinear regression, 曲线回归! A( U( c% @- k/ u' ^/ ?
Curvilinear relation, 曲线关系& l9 \3 g( W0 W) {! `1 [/ H
Cut-and-try method, 尝试法3 F3 R8 u9 c6 [6 R% N
Cycle, 周期6 y$ j' m2 a4 {, U$ ]0 M$ ~
Cyclist, 周期性- _2 k, w9 _# d6 ]5 L8 A2 i
D test, D检验6 \) e3 {9 C- E: ^
Data acquisition, 资料收集/ Q. H, j' K3 i* f: K# H
Data bank, 数据库. n$ I4 I- N2 s Z6 y5 k3 {/ j5 O
Data capacity, 数据容量
" d. ]" T# N9 Q# P/ ?; I/ TData deficiencies, 数据缺乏
5 T9 a, a( P6 R4 s$ uData handling, 数据处理& t/ j2 h! S c$ _# w$ r
Data manipulation, 数据处理4 y L" i- f, o! Z
Data processing, 数据处理( c9 z, I+ S3 N7 x! J% |
Data reduction, 数据缩减) C n5 g$ Z) o# H, B% g: C e
Data set, 数据集
' R+ D1 b, V$ W7 kData sources, 数据来源
$ M, j& A' T0 `" D) ]* O, gData transformation, 数据变换+ L6 D: ~$ s) a5 ?& _* Q9 h0 Y
Data validity, 数据有效性
X4 v8 A- z) n, |+ XData-in, 数据输入
7 d; v6 X0 P: A) ] z4 SData-out, 数据输出 W( S% K- i8 f5 _& X
Dead time, 停滞期
" o* H! v+ y- o8 C9 z( u4 q5 RDegree of freedom, 自由度, K6 X$ A3 u( x! F
Degree of precision, 精密度
; l6 a- q+ g# y! b3 U+ b( IDegree of reliability, 可靠性程度8 d. j4 H6 k/ k$ B" {' {
Degression, 递减
' p4 g: w& l0 D( \Density function, 密度函数! d" g' q- l- n6 Y9 h$ \, M( x
Density of data points, 数据点的密度
, F: x5 \; i4 h6 A @ kDependent variable, 应变量/依变量/因变量
3 `2 i9 w# V z" d4 B% _/ e' m" NDependent variable, 因变量
+ q+ L$ X1 z$ V! _5 K NDepth, 深度
2 p) A( s% C# ?3 p, zDerivative matrix, 导数矩阵
2 L0 U; s a P: D9 ]7 Z# d0 r# m% fDerivative-free methods, 无导数方法
2 p# k9 ^; B& W$ F/ ]Design, 设计
$ w. [+ f7 u; x: n$ w0 ^Determinacy, 确定性
8 _! {7 k2 m% t5 s/ n. oDeterminant, 行列式. h9 J* H. w* l
Determinant, 决定因素
5 G0 T' p' \' q. W D7 bDeviation, 离差9 P5 c5 `: W' E" d, g3 S. R
Deviation from average, 离均差. v6 o* O, `- ~0 H0 v' R2 `* o' R
Diagnostic plot, 诊断图
# @# O3 S$ j" S3 C8 L1 B9 i5 MDichotomous variable, 二分变量
M- y; D# p# z' v0 {, ~7 Q1 C4 HDifferential equation, 微分方程; R7 l- }3 e$ z8 \3 B- ?* O' W
Direct standardization, 直接标准化法
0 A; s5 J4 U: B& _1 yDiscrete variable, 离散型变量' R8 Z4 G4 v: W5 i- y
DISCRIMINANT, 判断
0 H9 U3 I9 ?6 d9 b$ EDiscriminant analysis, 判别分析
! h8 c& U2 h% j7 f* g( Z; QDiscriminant coefficient, 判别系数9 b7 v& R4 J1 s6 z
Discriminant function, 判别值
8 i% B: X5 \% s) LDispersion, 散布/分散度4 G2 f+ z; j2 v! Q$ C8 L5 l
Disproportional, 不成比例的. t+ i5 j) U1 { c
Disproportionate sub-class numbers, 不成比例次级组含量. y+ m+ j5 f) O
Distribution free, 分布无关性/免分布
* A" F9 a9 j# r8 Y! Q, R9 lDistribution shape, 分布形状
) R/ ]0 E; b! {- O% [5 FDistribution-free method, 任意分布法
& ?# ^: W, f, F, BDistributive laws, 分配律
) ^4 x, B: K8 XDisturbance, 随机扰动项
' n6 i$ x6 N) RDose response curve, 剂量反应曲线& ]( A7 b* A# q9 }- Y) Y9 ~& l
Double blind method, 双盲法
$ q; l. _" F- ~. X% FDouble blind trial, 双盲试验& ]# v, a. |/ B
Double exponential distribution, 双指数分布0 X. o5 i% a. O: y& r+ ?4 a
Double logarithmic, 双对数- J7 J* M% Y) E" t+ g
Downward rank, 降秩& Z0 }, `- s6 |! ^
Dual-space plot, 对偶空间图+ N6 H( h! r0 ]
DUD, 无导数方法
7 U, [6 ^- K1 ]( Z3 |Duncan's new multiple range method, 新复极差法/Duncan新法
( T' U( |7 d" vEffect, 实验效应
( |) |" C2 q5 M' a+ r, d5 o- oEigenvalue, 特征值
7 L/ K& W# E" a- k$ \/ \" W3 @+ SEigenvector, 特征向量
9 z8 k8 H# C# kEllipse, 椭圆* B/ M1 E, l% q) g5 C9 v
Empirical distribution, 经验分布
; U. r* j) Q& ^: V2 jEmpirical probability, 经验概率单位
t) N6 x4 H9 S* ^! _" lEnumeration data, 计数资料
5 y& U H t* AEqual sun-class number, 相等次级组含量$ R) d( } Y- H0 {' i
Equally likely, 等可能6 F( F8 m; h/ N# {9 ^
Equivariance, 同变性
! v5 O* s) g" n. T8 VError, 误差/错误
% {3 K4 Q- ~$ |( z8 b0 cError of estimate, 估计误差/ b% A: v% T' E9 d F( [
Error type I, 第一类错误( ?; |( n# a5 F: Q/ [8 b# @/ q
Error type II, 第二类错误: E& C8 ]/ d6 I( }' k& I* x2 x# [. Z
Estimand, 被估量
; c3 H5 a( u" k) B9 n* E. ~7 l3 QEstimated error mean squares, 估计误差均方
' |" d6 A1 r6 U& DEstimated error sum of squares, 估计误差平方和9 i( k! z5 h& H6 U
Euclidean distance, 欧式距离. r+ t/ F! n) j, [$ {4 ?5 i
Event, 事件1 T1 I9 F6 N; n( P! S: z
Event, 事件- a4 ?6 l& P* s U+ _$ p
Exceptional data point, 异常数据点
$ R, ?% `$ Z9 ~% r- X9 z; y aExpectation plane, 期望平面* P7 H+ Q+ t( B3 S- c' p4 p3 V, O% g
Expectation surface, 期望曲面+ \7 k0 E3 j# z0 M* G. i/ D
Expected values, 期望值6 x# w) C. v) ]% S% ~9 w: Y
Experiment, 实验( Q# f, \: {& f1 V
Experimental sampling, 试验抽样
3 y" X, e5 g, j8 F v+ P' bExperimental unit, 试验单位7 d! D8 b8 r( }9 e X
Explanatory variable, 说明变量
" n5 _7 K' O1 D7 W0 z# xExploratory data analysis, 探索性数据分析
0 v s9 L/ m9 y5 F3 HExplore Summarize, 探索-摘要! A, A. `- K* q x0 R
Exponential curve, 指数曲线5 f# H/ L2 F$ j2 A/ k
Exponential growth, 指数式增长
1 a4 |* m. X4 |. P1 C' S" yEXSMOOTH, 指数平滑方法 3 r0 d+ P& e) b! q/ V
Extended fit, 扩充拟合
1 d7 m4 u7 s% W% ]. QExtra parameter, 附加参数
" a: S# n) s% g1 m1 dExtrapolation, 外推法4 F4 d- |* j" a; a
Extreme observation, 末端观测值
5 C+ T& W( `- c5 g' d1 nExtremes, 极端值/极值: M1 ^3 |5 }/ Q2 n4 C% u
F distribution, F分布
2 O* W4 `8 D n6 {) C8 d. qF test, F检验- I* K1 }. p1 M `5 o5 X
Factor, 因素/因子& _2 X. u. B0 v- d( w- |& X# P
Factor analysis, 因子分析; G6 x( L$ N9 k5 X
Factor Analysis, 因子分析7 L- [: b) s) M7 @
Factor score, 因子得分
$ X- y3 M4 A6 N/ P6 j( {! s- UFactorial, 阶乘9 \# ^: g3 U5 H% X. ~8 L3 J; ]
Factorial design, 析因试验设计5 d& V* K, Q5 U0 {+ z% ?7 `
False negative, 假阴性
9 p3 C J9 s3 A5 m: `- DFalse negative error, 假阴性错误
" r0 u) ~8 b \1 u" e d% N( M! iFamily of distributions, 分布族' a" \# e' [- B# q# z
Family of estimators, 估计量族
) q7 V9 s/ Q: hFanning, 扇面- a# G, I8 N& \7 c4 ]
Fatality rate, 病死率
8 \3 x q$ e& F& S* RField investigation, 现场调查
; f J1 C5 U! S) V i ?3 ]Field survey, 现场调查
9 c4 g! w- M7 B# f: A3 \ D0 D. Q% _Finite population, 有限总体
+ S2 N" J( ^2 zFinite-sample, 有限样本9 d4 D- {- z4 `& r- c# i8 ~
First derivative, 一阶导数
3 P1 ]7 ?$ x) lFirst principal component, 第一主成分
% ?0 `* z3 z2 n5 l- E- j6 MFirst quartile, 第一四分位数; `9 z5 I. t( ^# C
Fisher information, 费雪信息量1 {8 ]0 w! f3 q- ^) L3 X
Fitted value, 拟合值
2 E" L1 }# I4 ]9 ^Fitting a curve, 曲线拟合
' C4 X. @1 E: j1 M0 l# `Fixed base, 定基- Z2 G% x. Y: q9 C# @* y
Fluctuation, 随机起伏+ v/ f! {6 S9 |/ \- W$ W2 d
Forecast, 预测
7 [* G3 V" e, J4 \" pFour fold table, 四格表9 l3 p: w& {# K$ V/ Q0 i; c
Fourth, 四分点5 X- w& t; _0 E/ f" E
Fraction blow, 左侧比率
) i4 v3 X6 T: N0 s+ O; c. u6 b2 QFractional error, 相对误差, L& Q9 j! a5 B2 ~. @
Frequency, 频率5 ]8 a% Y/ [6 {- x: Z- F
Frequency polygon, 频数多边图1 i [, Q; L) L( `& Z+ N% f
Frontier point, 界限点
# X5 _1 L# g2 ^Function relationship, 泛函关系' l6 p1 Q$ R! a' V
Gamma distribution, 伽玛分布
' C2 `" I, s0 [; r5 Y* a. rGauss increment, 高斯增量
. M9 g& T/ `2 n" @( xGaussian distribution, 高斯分布/正态分布. j! i) b% _/ d% C( y8 |! G x9 T
Gauss-Newton increment, 高斯-牛顿增量4 }0 S# @) v' D6 K! v w
General census, 全面普查
P" f* K0 O+ ^ qGENLOG (Generalized liner models), 广义线性模型
+ V, n- N- B ^8 sGeometric mean, 几何平均数4 o2 B' t* n; |0 p5 O, n
Gini's mean difference, 基尼均差
8 n2 ^2 s6 J& Y# r; Q2 f7 `# l/ jGLM (General liner models), 一般线性模型
7 a: }( i! j+ N$ }Goodness of fit, 拟和优度/配合度
6 d t9 j" O/ N# q1 I: kGradient of determinant, 行列式的梯度
9 @! J" }- l, D# D8 k1 q' }Graeco-Latin square, 希腊拉丁方
+ `8 j) Z: b* h4 i; E6 w1 _. iGrand mean, 总均值
2 A% w& U: g6 G3 LGross errors, 重大错误
. B2 A4 m$ D. zGross-error sensitivity, 大错敏感度6 H# o- l& M- Y1 f2 ]
Group averages, 分组平均& D2 B7 w; e+ R3 A* F
Grouped data, 分组资料, x) z) u+ ^/ Y" I% L8 a5 p
Guessed mean, 假定平均数$ f% a$ U* p$ V
Half-life, 半衰期/ Q% s* a' T: h1 M/ ~! d& J
Hampel M-estimators, 汉佩尔M估计量
; M5 U1 K. Y. a; D; R+ c8 LHappenstance, 偶然事件
5 q5 x r7 |2 F3 DHarmonic mean, 调和均数) r `' G6 m+ i* G% {8 `1 Z7 V
Hazard function, 风险均数5 U3 @; V, A9 e- l, j
Hazard rate, 风险率1 I4 a* Y& u) \+ W. Q Z$ X% v
Heading, 标目
3 W. S$ k9 f. T8 h& tHeavy-tailed distribution, 重尾分布' L( E8 p6 Y8 y/ H9 }9 I
Hessian array, 海森立体阵
+ c* |/ g5 Z2 Y# k) w4 vHeterogeneity, 不同质& v# s. U; g0 W9 ]- k- Q; X5 X
Heterogeneity of variance, 方差不齐
5 {( }' K' h3 I3 e1 NHierarchical classification, 组内分组, b; s7 P) M$ e a5 {- U3 ^' u
Hierarchical clustering method, 系统聚类法
! b' Z1 |2 e2 F1 [High-leverage point, 高杠杆率点. D4 F/ s" j5 ~' c- S$ ]" F2 R
HILOGLINEAR, 多维列联表的层次对数线性模型
% v) c$ T8 m1 o3 \% x9 @Hinge, 折叶点
7 B+ @1 ]- }: w: m& Z8 O; {Histogram, 直方图
" A+ r; d9 ^" y! W: DHistorical cohort study, 历史性队列研究 & [# q4 t) r w5 L
Holes, 空洞* z, l# z5 @! S, V- }8 a
HOMALS, 多重响应分析1 s/ q, s5 r; ?$ E
Homogeneity of variance, 方差齐性
, p) Y( K- A. d& F, t) P5 h0 |Homogeneity test, 齐性检验
: f0 K# |5 {3 Y2 A' M) w+ L) VHuber M-estimators, 休伯M估计量( J) G# J" ~ X7 N9 f
Hyperbola, 双曲线
& K. v* ~4 Q8 @8 THypothesis testing, 假设检验' S& d* N% }1 D/ f7 l
Hypothetical universe, 假设总体2 g, M9 f6 d8 t
Impossible event, 不可能事件" R5 C' d1 N8 p8 U; r& d Y6 k% ~0 v& L
Independence, 独立性
2 R6 A* v) w5 _- gIndependent variable, 自变量
* C6 D' T* a8 P, e2 U! {Index, 指标/指数
; z. Z. Z' i% o+ |Indirect standardization, 间接标准化法
3 |" @) q' Z: S g) qIndividual, 个体
( e) A8 i4 X3 a9 n1 ^( w- E5 CInference band, 推断带 u1 c: i% I6 y! r- ^, n0 _5 c( I
Infinite population, 无限总体
9 b. S/ k7 ]! c) Z) P" mInfinitely great, 无穷大
0 E" W. n5 d" R9 YInfinitely small, 无穷小( x# J" q; _3 A D/ v8 L$ Y9 h
Influence curve, 影响曲线) C& x. s4 X( P2 e
Information capacity, 信息容量- y9 j: @& s. r4 j2 n& _1 H
Initial condition, 初始条件
3 d8 B1 a4 |$ j+ s4 E0 HInitial estimate, 初始估计值
9 ~8 ]7 K! y' U* }; RInitial level, 最初水平
! H) ^1 @* a1 h. X$ d: ]/ T' [Interaction, 交互作用8 u+ T4 Z* W5 n, ^: i
Interaction terms, 交互作用项
9 g8 k: T8 U" q, @8 D, KIntercept, 截距( y) r3 p2 b+ \ O
Interpolation, 内插法1 V# x/ Z2 Q( ~) D* v8 v$ Y, ]" C
Interquartile range, 四分位距
$ j. o1 a# Z# PInterval estimation, 区间估计& a! c) `! E2 Y a
Intervals of equal probability, 等概率区间. c, ?9 l6 L- F" x3 `
Intrinsic curvature, 固有曲率
6 w" A. Y* T8 o. a3 z) NInvariance, 不变性' T" P+ D% F. |( x, V( c' Z
Inverse matrix, 逆矩阵! [# m5 f7 k' A) v" C* z) ]: a8 D1 [" K
Inverse probability, 逆概率
. r: B3 S5 v( ZInverse sine transformation, 反正弦变换$ `* u. v9 ^4 O q" u8 }+ V
Iteration, 迭代
0 }# R% q: U, I8 A5 E1 @Jacobian determinant, 雅可比行列式
- I3 d. ?* z3 A+ C7 V& J# CJoint distribution function, 分布函数$ X9 d" X/ a9 _- U! A
Joint probability, 联合概率
. Z' d: ]9 K. G3 XJoint probability distribution, 联合概率分布) R G1 T* E' q ?; D) i, Z
K means method, 逐步聚类法
0 y6 e3 m2 }9 c$ M; {2 ?* L5 MKaplan-Meier, 评估事件的时间长度
8 b/ s: y7 }7 \# S" D; JKaplan-Merier chart, Kaplan-Merier图/ k* }: L1 `3 G1 M% f
Kendall's rank correlation, Kendall等级相关
' m$ n% t# a' C6 F2 l& xKinetic, 动力学
3 E$ \& q3 q) P d, O# `/ ]Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验8 R. M5 F M9 I2 G
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
R* S( d4 T* F6 I. |Kurtosis, 峰度
! Q3 \+ e, e& a% A/ gLack of fit, 失拟2 F6 k3 D: v9 @5 D4 S
Ladder of powers, 幂阶梯. X' w7 L$ H. v
Lag, 滞后2 k `8 G$ u, ~& [
Large sample, 大样本6 o0 \& N8 `3 M* T, L
Large sample test, 大样本检验
+ d4 v' x/ [8 G" S7 y/ LLatin square, 拉丁方
1 O5 P6 b3 C' X) a- b8 h4 ~9 w+ h( WLatin square design, 拉丁方设计
) {" f* A! Z# B7 K% s- ?Leakage, 泄漏" {: W( N0 e* a0 D6 [, ^
Least favorable configuration, 最不利构形
' E+ j# M* ?& YLeast favorable distribution, 最不利分布
* ?' H2 T: U8 f4 s" @) i fLeast significant difference, 最小显著差法
* a! s* x6 T Y! W" P& aLeast square method, 最小二乘法
2 G4 j: Z. M* N0 @4 d$ v. X/ ^Least-absolute-residuals estimates, 最小绝对残差估计& T s( o: \; M; E) ?2 Q. a4 n0 H7 R9 j
Least-absolute-residuals fit, 最小绝对残差拟合 c+ h& C. p' a. B0 R
Least-absolute-residuals line, 最小绝对残差线
6 w1 w, I7 c% r# c- s7 ELegend, 图例6 [0 b1 p. o* l/ c# \
L-estimator, L估计量. U1 j8 C) a1 @/ ?& P) A5 x$ F' ^0 q
L-estimator of location, 位置L估计量
/ U% l- J% d1 K) J4 T, S+ q# w7 qL-estimator of scale, 尺度L估计量7 b- P! ]& u a6 n
Level, 水平, ^7 R, A5 i/ E
Life expectance, 预期期望寿命+ T9 ?& p7 _8 K
Life table, 寿命表
. X% {& ~ C# P8 B6 B4 p8 a. wLife table method, 生命表法
2 ?) ?0 ?- E( Q3 |6 JLight-tailed distribution, 轻尾分布
: E/ ^6 E; P3 e( |; m0 W7 tLikelihood function, 似然函数! C7 a/ c, D' e; ? |, Z
Likelihood ratio, 似然比$ }0 L+ s' n( c
line graph, 线图" T1 B' Y) X3 Z
Linear correlation, 直线相关
& \6 O8 y9 b4 C+ B$ C/ CLinear equation, 线性方程8 c0 x7 |, V5 t! F- o9 ]: o* l3 a
Linear programming, 线性规划3 w5 Q+ s' A; I+ T" Q: `1 K
Linear regression, 直线回归' U% L* R1 w6 J) R9 x" s. n0 X' H
Linear Regression, 线性回归
" K5 G' s6 [- H7 N' CLinear trend, 线性趋势: W$ U1 R- Z; r5 c" L2 u i
Loading, 载荷
: l( H5 ~" G, v" g% VLocation and scale equivariance, 位置尺度同变性
% V# }$ @( a1 m: NLocation equivariance, 位置同变性1 E9 E( }9 t, p- I+ k
Location invariance, 位置不变性
, x9 _: R; w1 I; Q! [Location scale family, 位置尺度族
; ?9 K6 a) W/ ~) C! i% X" A+ }! e6 LLog rank test, 时序检验 ! k% ^1 t/ o) U- E/ P
Logarithmic curve, 对数曲线
2 `% T; ^3 }2 m6 K' BLogarithmic normal distribution, 对数正态分布7 s: d0 M! f# g$ q) h9 m
Logarithmic scale, 对数尺度2 ]9 E+ O! S" Z7 @8 J4 a! }/ E' y
Logarithmic transformation, 对数变换0 W' y# u9 R0 U) R! ], I8 M
Logic check, 逻辑检查
& @% v; S% `) ~, j# o+ sLogistic distribution, 逻辑斯特分布/ ~; P$ Q. p; ~6 O
Logit transformation, Logit转换! J; r; X2 M& A5 A0 L) H
LOGLINEAR, 多维列联表通用模型 9 A }, U2 ?) S; y, a( l( |
Lognormal distribution, 对数正态分布0 d; s, R$ b$ C
Lost function, 损失函数
4 P0 `( S2 o6 V/ Y/ O. PLow correlation, 低度相关9 X7 b$ ~1 f; k" M
Lower limit, 下限
; o! d! g0 \$ O4 G: L, f$ x: R0 K% qLowest-attained variance, 最小可达方差
; g, P/ z: f5 V& c6 k# ]LSD, 最小显著差法的简称/ }, O' t/ V! d
Lurking variable, 潜在变量$ c+ g6 X1 p) E- @
Main effect, 主效应
" u$ R- [& o0 |Major heading, 主辞标目
* \9 \) F% N, f& gMarginal density function, 边缘密度函数, \1 ]1 @6 K) x2 N9 [
Marginal probability, 边缘概率+ x$ f$ ^: {( j6 R {
Marginal probability distribution, 边缘概率分布 L* C7 g+ H9 v
Matched data, 配对资料
4 N/ [0 M" Z# E7 X3 |Matched distribution, 匹配过分布
/ `: s. b% a: @Matching of distribution, 分布的匹配
5 @, c/ y/ u' p1 gMatching of transformation, 变换的匹配
X: J- K- b/ w' E: T7 ~Mathematical expectation, 数学期望% r& h$ }# y$ o8 J
Mathematical model, 数学模型1 S5 I! |/ }5 w: l/ n8 n
Maximum L-estimator, 极大极小L 估计量8 @, C/ j1 D# c
Maximum likelihood method, 最大似然法
5 q v; B. H1 H# KMean, 均数
2 K' b4 @' J$ \9 m+ fMean squares between groups, 组间均方0 K+ c X- ?% }# U
Mean squares within group, 组内均方
6 t6 P" f8 Z, e9 ]' Y6 CMeans (Compare means), 均值-均值比较
, l: b$ L" T6 M JMedian, 中位数9 t; _- o k# G1 M" E* n, ^
Median effective dose, 半数效量
2 R8 U; y, H: q$ B6 } _0 d$ oMedian lethal dose, 半数致死量
/ n; I4 y# G9 k2 i6 zMedian polish, 中位数平滑
0 K) x$ P2 s1 Y$ q+ b& YMedian test, 中位数检验
: |4 P" i z2 R( K8 I5 e2 X. bMinimal sufficient statistic, 最小充分统计量& f% G/ m5 t1 j5 c9 R/ `
Minimum distance estimation, 最小距离估计6 D( A S$ p4 e2 m# W7 w, d! Q
Minimum effective dose, 最小有效量9 J; ]) t2 _% f+ ~
Minimum lethal dose, 最小致死量8 p: g. r( g' R+ S# P0 k
Minimum variance estimator, 最小方差估计量
. A) k9 O+ |& ?' q) MMINITAB, 统计软件包
7 s* f( y+ {8 _3 \) s* ~# R# G5 ]Minor heading, 宾词标目6 W* c% S3 ~4 y; p" E% W
Missing data, 缺失值4 I2 u1 N% _. g+ U& \8 F6 m" \
Model specification, 模型的确定8 H0 n0 x4 a. P, R% h5 ?) L
Modeling Statistics , 模型统计
# f$ y5 L$ m3 _* M( ]8 oModels for outliers, 离群值模型
" {; D6 A' s# h& c1 L2 Q BModifying the model, 模型的修正4 Z5 n) H& }. D; A% F+ L/ c
Modulus of continuity, 连续性模
: n* Z5 G+ |8 s6 A6 GMorbidity, 发病率 $ S" r' C9 r9 G; e" [; c
Most favorable configuration, 最有利构形
6 j& p% D, p' I0 O0 _3 gMultidimensional Scaling (ASCAL), 多维尺度/多维标度
3 B! {% l' m J% }& [" GMultinomial Logistic Regression , 多项逻辑斯蒂回归
5 X3 o( \( Y x! _: H5 S- DMultiple comparison, 多重比较- Z8 p! A; U8 u) k
Multiple correlation , 复相关
- s! Q, p- K: D3 l. X D' PMultiple covariance, 多元协方差
4 q; _) [! A: z+ ~8 P- }Multiple linear regression, 多元线性回归& s* A6 I- v* b& J p+ u: c
Multiple response , 多重选项6 o8 ~; V/ M) Q* ~8 e! A
Multiple solutions, 多解/ _% Z& I8 ^; D+ _& L
Multiplication theorem, 乘法定理
/ e( k! H. g" ]3 LMultiresponse, 多元响应6 ?. [1 P% C! i! J5 A, ?
Multi-stage sampling, 多阶段抽样3 h6 q5 B' n# {6 z2 J9 u0 e4 Q
Multivariate T distribution, 多元T分布
; ]& {/ |6 k) s; l' x) D: w vMutual exclusive, 互不相容
- X5 I9 s/ Z: t5 [Mutual independence, 互相独立) n6 k b. _$ J" u
Natural boundary, 自然边界
; S6 S& N {; E7 t: | qNatural dead, 自然死亡
2 G/ u' R/ E( |7 b0 I/ T' }Natural zero, 自然零. K3 K2 i7 S ^0 ~% W3 }# w
Negative correlation, 负相关
0 q E( K/ c2 D( ^5 ~Negative linear correlation, 负线性相关
: q8 R' `) H7 W9 ?8 [+ zNegatively skewed, 负偏$ \( r5 `( @% Q6 G8 ~! J" b) P
Newman-Keuls method, q检验
* M/ |# P4 _6 uNK method, q检验
, c8 E* P. P+ S' K2 bNo statistical significance, 无统计意义1 b! G! s0 g0 A' E1 F7 {) Q" ?' x" D0 l7 H
Nominal variable, 名义变量( E% C8 W" K" a2 J- c
Nonconstancy of variability, 变异的非定常性* k, l9 {$ u: T, q. _4 T) K, a" f
Nonlinear regression, 非线性相关$ ? d ~* A% j( v* Z6 b
Nonparametric statistics, 非参数统计
7 e* ]/ }) h* s, J- iNonparametric test, 非参数检验
% x( [% p2 a* j% _6 Y) R7 M( z3 JNonparametric tests, 非参数检验 Z) b: Y- C$ }6 A
Normal deviate, 正态离差
9 f7 ?0 B! f: n' V8 K8 jNormal distribution, 正态分布0 i* s% m8 _& V& q; H. W+ V
Normal equation, 正规方程组
|! E: p- K- }. n& j; M. s& j: J& YNormal ranges, 正常范围
2 s2 O& x1 S+ @Normal value, 正常值, B Q r: A( X$ e& L6 A. P
Nuisance parameter, 多余参数/讨厌参数
w# i' O& X, K" V" nNull hypothesis, 无效假设 9 q. R. X/ H9 Y: i$ Z) B$ p/ K
Numerical variable, 数值变量+ R. {2 w$ S* D
Objective function, 目标函数
9 e$ z8 a s( N3 j, QObservation unit, 观察单位
: C' Z3 C1 y3 r! k! q# TObserved value, 观察值
9 s$ L I6 R% \One sided test, 单侧检验
! Q3 P- u( E. \One-way analysis of variance, 单因素方差分析
" g" e7 {8 v, p9 P& WOneway ANOVA , 单因素方差分析
9 [4 G6 D" @% i; nOpen sequential trial, 开放型序贯设计
$ ~9 b6 c2 U; X, _. IOptrim, 优切尾& b" ?4 ]$ v& D0 w. h" F9 ~$ w
Optrim efficiency, 优切尾效率
7 X0 z- h2 E; W' L JOrder statistics, 顺序统计量8 [0 Q' @2 L& |3 n" m
Ordered categories, 有序分类2 E! ^. H4 O8 q6 @+ m, M
Ordinal logistic regression , 序数逻辑斯蒂回归' w& K s" U3 U3 y8 g/ z+ j
Ordinal variable, 有序变量 t2 m- ?* B' q4 ]" y+ M& `
Orthogonal basis, 正交基
* }+ T5 l1 L0 w: P! COrthogonal design, 正交试验设计
9 g' z+ C6 A: \1 m0 t+ l3 fOrthogonality conditions, 正交条件8 R1 M+ d. Y' K; z1 b- Z' K
ORTHOPLAN, 正交设计 + E2 Y$ r, Z; ~
Outlier cutoffs, 离群值截断点
1 p/ @1 c8 f3 a+ g6 E$ S5 n2 \; TOutliers, 极端值
; p, H5 ?* D7 H. Z1 w1 V0 GOVERALS , 多组变量的非线性正规相关
1 f' H: V# G# d* tOvershoot, 迭代过度' `5 q2 ~4 y8 W5 z( G* J$ e
Paired design, 配对设计" o. q6 u3 z, I6 B" j+ ?7 [; Q
Paired sample, 配对样本
: z" P+ N% U* W n+ [9 T9 SPairwise slopes, 成对斜率9 R- Y5 h; k( d+ |
Parabola, 抛物线9 W4 j: @% @# X' k7 m2 I
Parallel tests, 平行试验2 Q$ h5 K x1 I" ]# o v
Parameter, 参数
( ~4 w, i2 o+ C% a) v: BParametric statistics, 参数统计+ }4 d1 N) W# {3 f& _" C; O, U
Parametric test, 参数检验' v" Z) E! s4 R
Partial correlation, 偏相关
8 S" f. N, D; G2 z" _Partial regression, 偏回归
/ ^9 K7 X. ^* |* [Partial sorting, 偏排序, f. }8 |5 _3 D u! s; |' r
Partials residuals, 偏残差
( M0 x( K- m( ?% Z; ePattern, 模式5 T3 [) f6 ?9 ~, n! x; w5 R
Pearson curves, 皮尔逊曲线5 A' a. i* o8 E1 S1 A( I
Peeling, 退层, U, A' }7 X2 f4 x# j
Percent bar graph, 百分条形图
# l/ n- q' v7 g) K" q0 L# u) v xPercentage, 百分比
- j6 d) u8 G& T7 y, JPercentile, 百分位数
& Q( [# K' l; K3 {3 O! mPercentile curves, 百分位曲线
/ G4 H8 r! f7 e) K2 l+ J$ ~Periodicity, 周期性7 o( u3 M. g% x# W7 T/ Y- S2 T
Permutation, 排列1 R/ @+ l4 X2 G. R- E( [
P-estimator, P估计量
6 x& u! g# P* RPie graph, 饼图9 D# q3 w% U) z* Y3 f
Pitman estimator, 皮特曼估计量
0 L( H! ? k. C1 [# n, J5 cPivot, 枢轴量6 n0 s Y# _( Z4 i1 Y8 P
Planar, 平坦# R% W+ S7 L/ d9 s& F) x
Planar assumption, 平面的假设
9 V8 l8 k# T. B2 ?* A; e% NPLANCARDS, 生成试验的计划卡
1 e0 Y/ o! u2 XPoint estimation, 点估计
( I- i) r1 M8 y) l8 B0 j# J$ n" HPoisson distribution, 泊松分布# e" _4 U& B2 N
Polishing, 平滑$ d4 e8 o4 @$ h5 @
Polled standard deviation, 合并标准差
; u3 c7 v @, D b8 ~' zPolled variance, 合并方差
* s+ o* T- Y% O8 L' l% ~, BPolygon, 多边图 i. t! a2 C% K# i, e. C
Polynomial, 多项式) v7 {& s" D3 g6 s& U
Polynomial curve, 多项式曲线( w. [" d0 R( _
Population, 总体4 @, ^3 R4 g" X
Population attributable risk, 人群归因危险度
; D) G" G. N- b. |& @' RPositive correlation, 正相关
7 z( b% a" V$ v' o8 LPositively skewed, 正偏; A8 ~ Z8 g* J8 i7 A
Posterior distribution, 后验分布1 C! ^7 w- S1 \
Power of a test, 检验效能/ {8 v' [( |3 P
Precision, 精密度4 O+ D7 I0 a+ M2 k7 Z0 J" x
Predicted value, 预测值
9 K+ s, Q8 K( D2 G$ YPreliminary analysis, 预备性分析 x l n8 W! O' s7 m9 i
Principal component analysis, 主成分分析9 D8 T, _. q- m" B& X
Prior distribution, 先验分布
" i+ Z# b N* f5 }Prior probability, 先验概率
! v3 m2 u+ |8 `% }7 }, v, KProbabilistic model, 概率模型; f- T$ @3 p# m$ I$ b5 y
probability, 概率
& d, u0 f. @" Z3 iProbability density, 概率密度
: p! p# N& g! U# wProduct moment, 乘积矩/协方差
3 k1 N; {' d: q- M0 d* MProfile trace, 截面迹图6 i7 O, l9 n' }" l+ b, E, z
Proportion, 比/构成比6 P* o% v8 I- H: c
Proportion allocation in stratified random sampling, 按比例分层随机抽样
2 u$ Y6 [, ]8 o: K# qProportionate, 成比例
$ W0 S# _. e: h4 l$ ]Proportionate sub-class numbers, 成比例次级组含量3 a6 }& f3 u4 W% E0 E# E
Prospective study, 前瞻性调查5 a: r$ O8 Q3 i: ?. J
Proximities, 亲近性
6 z; _6 M' b$ x8 IPseudo F test, 近似F检验 F4 h! G7 I7 `1 h7 H: d$ K
Pseudo model, 近似模型, z* T# ?( |: P6 X/ |7 b
Pseudosigma, 伪标准差9 C: e/ L, r" f; b6 T, ]
Purposive sampling, 有目的抽样
" M/ `# K" g5 V. B1 g; K! rQR decomposition, QR分解9 r+ J+ I/ p2 Z3 h0 g$ h
Quadratic approximation, 二次近似/ x- C0 P9 @, m+ E& c9 Q+ X4 q
Qualitative classification, 属性分类# F% D( t. D+ B$ j( K9 a
Qualitative method, 定性方法2 S8 r7 N# H ~5 Q0 O% b
Quantile-quantile plot, 分位数-分位数图/Q-Q图
! `0 |: s- y0 C- c) ?% q8 eQuantitative analysis, 定量分析
& D+ T) [) t- ?, c n/ SQuartile, 四分位数1 z) ]2 _( y1 d$ B( z; N% S6 b
Quick Cluster, 快速聚类1 @, L! D8 y+ R7 ~; h, c
Radix sort, 基数排序6 e5 h! q+ M# E% S
Random allocation, 随机化分组
) k# T* L7 {2 y# f; ?! H3 I" mRandom blocks design, 随机区组设计3 q) C' b- ^8 n+ o
Random event, 随机事件
, h3 `) K) r: d5 A- {# }7 k1 PRandomization, 随机化
9 [/ ]9 p3 S3 L$ H" bRange, 极差/全距( Q) y6 v& h, P
Rank correlation, 等级相关
: K: c: ^% w6 F7 o+ B. G8 n5 b" ORank sum test, 秩和检验
- l: }* j5 J: P) XRank test, 秩检验 O( M' K7 d8 P% f; P0 o
Ranked data, 等级资料
+ }8 z& L) T+ U# M; R0 |Rate, 比率
' m+ ]+ I+ \# ?; N- k- ~( r! iRatio, 比例
3 |# ~/ X% _; F6 S5 GRaw data, 原始资料
( {, f3 a5 V- I$ b4 P3 s; nRaw residual, 原始残差
j6 d+ R- U- C: L; S: ]; C: ARayleigh's test, 雷氏检验; x- ^ Z9 d9 G5 S7 d8 m
Rayleigh's Z, 雷氏Z值
' r5 D, ?/ B" ]) iReciprocal, 倒数7 U/ l9 a. a$ X0 t2 m
Reciprocal transformation, 倒数变换' B, U" h3 ~* o0 g
Recording, 记录
0 m- V; l5 [1 }3 a6 ?Redescending estimators, 回降估计量; r1 N. U$ |4 h. J- y& }5 V+ [
Reducing dimensions, 降维3 V2 _! y7 x: F7 I
Re-expression, 重新表达
/ c* \. D: |/ ]2 \5 DReference set, 标准组, M$ ]! @$ Z1 o- V E- q
Region of acceptance, 接受域
. n8 C3 C+ ?+ H; H/ Z( [' P$ j' ?Regression coefficient, 回归系数
* o" p# Q$ z- ? k) iRegression sum of square, 回归平方和: {/ e7 o3 c; Y# o2 V/ Z
Rejection point, 拒绝点; Q3 @0 b1 ?7 m9 \: t4 ~
Relative dispersion, 相对离散度
e) ^+ s' C7 |" D; j" fRelative number, 相对数
) M- J) a7 i0 Q& KReliability, 可靠性
3 `; h4 m/ E0 v: Z2 t$ qReparametrization, 重新设置参数- \9 Y U: ]/ T
Replication, 重复
( K' C% @. V0 C! LReport Summaries, 报告摘要$ Z. x4 L T. o
Residual sum of square, 剩余平方和
5 v, s; m5 l: G& A2 S1 XResistance, 耐抗性
/ H1 m! [7 b8 u9 |: I9 ]Resistant line, 耐抗线
( O N4 f U; t+ _0 N3 f8 D9 OResistant technique, 耐抗技术
, G+ J K6 ]# c2 t- OR-estimator of location, 位置R估计量
- p+ r8 G( E; k: k( i5 yR-estimator of scale, 尺度R估计量
/ A$ ~! v) N6 S% \, Z5 v# ZRetrospective study, 回顾性调查; S% X; P6 h1 h6 B9 L
Ridge trace, 岭迹
: ^' @# }8 X- h& gRidit analysis, Ridit分析
+ [3 Z3 J+ N& DRotation, 旋转. q3 i. J n6 P! R9 S3 V: w5 C
Rounding, 舍入
* E/ R- G( \6 V6 _" kRow, 行
5 q1 k0 W( @+ u! P: RRow effects, 行效应# [2 w& ^. F. V: M% o& |% k) Q
Row factor, 行因素
' l# c! K0 {6 }* O1 X0 rRXC table, RXC表8 D9 K* O3 W) a' `0 R# o7 A
Sample, 样本
; `% u3 T0 f s/ K! Y% }3 V& a \Sample regression coefficient, 样本回归系数, d: S5 b4 L9 O2 l
Sample size, 样本量( c# y- M, j A" L
Sample standard deviation, 样本标准差! }& N+ h3 I# e0 f7 w
Sampling error, 抽样误差% A5 C- |( w' D+ V! b
SAS(Statistical analysis system ), SAS统计软件包
# B( k: C, C; |5 d) M) G, y+ mScale, 尺度/量表) o8 b n2 l" Z; d" T
Scatter diagram, 散点图
7 h+ g" g: x& e+ g( xSchematic plot, 示意图/简图
6 k9 S2 T% o, x' l/ }6 H: TScore test, 计分检验/ w$ {! K' K, i% ~
Screening, 筛检
/ C! e/ B# V6 @5 @, c1 eSEASON, 季节分析
2 i/ z) W( a0 q5 D/ S& GSecond derivative, 二阶导数
# ]. T$ L D$ `! t. I6 x+ TSecond principal component, 第二主成分% k3 v/ {. [) W- y7 r8 [
SEM (Structural equation modeling), 结构化方程模型
/ s$ z% E% ?6 |7 I! m9 d2 ySemi-logarithmic graph, 半对数图" J& J8 V) R8 u- ?
Semi-logarithmic paper, 半对数格纸
' h# T) w8 }( D$ Y; I! ySensitivity curve, 敏感度曲线( H( f. K2 o9 q
Sequential analysis, 贯序分析+ T# Y2 I6 v% X$ E$ f' o
Sequential data set, 顺序数据集
4 F* h0 r/ ~/ lSequential design, 贯序设计 V1 s$ c4 b" t2 N) k: q& s
Sequential method, 贯序法
1 i! P T2 G1 N* m6 PSequential test, 贯序检验法% u1 T* x; I3 O1 x7 K6 ^2 i/ X( e
Serial tests, 系列试验. K& [1 n$ T. m# [1 E
Short-cut method, 简捷法 / t% o1 l7 O( v, F. z7 R) _
Sigmoid curve, S形曲线
% M3 r- Z( K! W8 c5 I5 L+ rSign function, 正负号函数
$ ~! a) p* @) H q1 K# O$ iSign test, 符号检验
- `3 u: g; C4 [- b6 J5 PSigned rank, 符号秩
1 s! D6 m3 m F# a5 kSignificance test, 显著性检验
# R [# }1 J$ x' ]8 TSignificant figure, 有效数字& s( c4 x( }% k; b' u
Simple cluster sampling, 简单整群抽样
) D6 [2 T$ e, \2 J! xSimple correlation, 简单相关9 X4 J9 n) s$ W5 z% j
Simple random sampling, 简单随机抽样9 l& z$ I( n2 ^6 H7 f3 M/ O) r
Simple regression, 简单回归5 O7 \1 V C; p/ G
simple table, 简单表
$ Y6 C2 v' l, W3 ^Sine estimator, 正弦估计量5 G* ~' ?9 T2 s% i: G# O
Single-valued estimate, 单值估计8 N0 B7 O" X0 s8 V. r
Singular matrix, 奇异矩阵
O7 F3 Y" j: r; T V" g3 G% ySkewed distribution, 偏斜分布
( N5 ^- E, ? N4 ISkewness, 偏度
; H/ j* G1 d- g# ESlash distribution, 斜线分布
' D* r: h4 }+ D& Z1 v2 g( hSlope, 斜率
$ @4 Y/ i; J8 fSmirnov test, 斯米尔诺夫检验
0 k+ \' f2 u! ^5 l, u, P: ?Source of variation, 变异来源) t3 u/ ~6 d# _" x( P8 q0 k
Spearman rank correlation, 斯皮尔曼等级相关1 J+ H0 K# E: _1 b- R& r
Specific factor, 特殊因子$ I" C' R+ X& l0 w
Specific factor variance, 特殊因子方差
1 x) y) S9 z& ?, K$ l, mSpectra , 频谱
?7 ]. {: m; L; z' TSpherical distribution, 球型正态分布
4 q9 V1 S. A8 mSpread, 展布
* W! i3 J! y6 _4 r9 t/ lSPSS(Statistical package for the social science), SPSS统计软件包$ H9 X. _! X% a2 {
Spurious correlation, 假性相关
$ U3 T) }7 d5 |8 O# K P( DSquare root transformation, 平方根变换% O7 `8 |! o7 O; J, f3 I8 c. I
Stabilizing variance, 稳定方差
( v5 e) n1 |4 l/ `: u& v: Q! {Standard deviation, 标准差
3 \* g5 J! [ D# F5 e0 RStandard error, 标准误
$ y. u- i) G/ [6 _% i* J" P7 ZStandard error of difference, 差别的标准误
) }6 }* M2 G; l; z1 |# ^+ k8 SStandard error of estimate, 标准估计误差8 G! R7 o) b' O4 Y- k) S
Standard error of rate, 率的标准误- P* n! y! w) Q' J+ q
Standard normal distribution, 标准正态分布
m0 b6 ^! O! o8 M- FStandardization, 标准化* K5 w. n' [1 \$ o2 `" i- h m8 g+ o
Starting value, 起始值6 `4 f" B8 l$ K$ k9 y
Statistic, 统计量
2 s4 M, b! F& L3 p( ?) QStatistical control, 统计控制) r! F9 I) h- o; a
Statistical graph, 统计图9 s7 h. u$ P: ?" }
Statistical inference, 统计推断0 y9 g$ m. T0 @3 s; x
Statistical table, 统计表
/ \' r" A- h7 {8 A$ B/ zSteepest descent, 最速下降法
2 M, j4 c% u$ { N! aStem and leaf display, 茎叶图1 d! b- I5 c- i
Step factor, 步长因子% Y- [# J% ^' d! A, U: a
Stepwise regression, 逐步回归8 L2 \6 Q! y6 e
Storage, 存
7 h1 X* U- S+ XStrata, 层(复数)
4 O* u6 e& J _' a% `& vStratified sampling, 分层抽样
7 E4 C4 S0 U* P5 M7 |; S wStratified sampling, 分层抽样
. L* a, w+ L) C& Z$ f& HStrength, 强度
3 {+ y! M, U! u4 N3 W0 d8 GStringency, 严密性6 b9 T) D, x: T& v6 T7 R
Structural relationship, 结构关系
1 C/ F1 L, |# r" GStudentized residual, 学生化残差/t化残差1 i: E4 K; n. q2 N. J; Z6 [
Sub-class numbers, 次级组含量3 a, n( v/ |0 p1 Z1 q4 S% O F
Subdividing, 分割 ^& C: y8 e+ O4 O# T/ W+ O4 z! ~/ Z
Sufficient statistic, 充分统计量
J3 q0 B+ z6 L& ]* ^Sum of products, 积和
3 I/ T) C- D# s# h$ b4 ?Sum of squares, 离差平方和, ^% }3 |! V# O5 F" R' R
Sum of squares about regression, 回归平方和
& m8 {! h% D% n oSum of squares between groups, 组间平方和+ m# q# e5 F# p8 k
Sum of squares of partial regression, 偏回归平方和
0 g* J4 Q8 L3 F+ E' x% k) ySure event, 必然事件/ c' a9 n6 {+ I& i% U) k
Survey, 调查1 O/ }% i a2 T6 e
Survival, 生存分析+ n" ~+ ?) K& @" r) o3 G. l( i# t
Survival rate, 生存率
) z' f$ O, A5 w3 S0 @* WSuspended root gram, 悬吊根图/ w5 j" a6 y) b, M3 h
Symmetry, 对称' s& U1 V! U1 q- u5 d# m6 c: R/ c
Systematic error, 系统误差1 k# O8 `- q0 ^
Systematic sampling, 系统抽样
( |- ]: Q4 U& ^+ E+ GTags, 标签
5 w5 `. |6 C6 j' x8 E9 VTail area, 尾部面积
* n' H v. R+ S, p# [Tail length, 尾长
( ?$ V, g! F! _- \: ^Tail weight, 尾重. q) f+ p+ J" [) x+ v5 b
Tangent line, 切线
5 K1 w% V* N* G, |) ]Target distribution, 目标分布: g# ]( x# ]- ?4 e+ k; f
Taylor series, 泰勒级数
4 t/ C$ _3 u" M# f0 _8 }6 K$ o0 ?Tendency of dispersion, 离散趋势: x2 }) Z5 Y! e: x- d; h- ]& Q @
Testing of hypotheses, 假设检验9 M, G9 L. f0 b5 ~7 @. P
Theoretical frequency, 理论频数
9 m, S9 D/ {0 o VTime series, 时间序列
1 @* |' e. [4 ITolerance interval, 容忍区间! C) B3 R5 e# |( l! [
Tolerance lower limit, 容忍下限 Z1 r6 U* C/ g! z+ B) [0 p/ e" n
Tolerance upper limit, 容忍上限
8 L! i' |" P# X5 X8 u, c" kTorsion, 扰率
: g9 P9 N A, e& K1 _+ jTotal sum of square, 总平方和* v, q! a7 G" C6 W
Total variation, 总变异
; u6 h( }* I+ T% l: ]3 ^% QTransformation, 转换5 z7 ~- A; R) X5 Y
Treatment, 处理0 g; [ Q* C4 {$ t _: e
Trend, 趋势" V" [3 Y- H! v$ u/ \ p* d
Trend of percentage, 百分比趋势5 [! Z# ]3 I! [+ X& e- V
Trial, 试验) c" ?7 R+ s9 {7 P4 i
Trial and error method, 试错法" r3 D. |. g8 F
Tuning constant, 细调常数) V+ n3 r9 @: j8 Y, ^) d- a
Two sided test, 双向检验
, l% W i- C% T# fTwo-stage least squares, 二阶最小平方3 f: E- K9 ?* O
Two-stage sampling, 二阶段抽样
/ k9 o3 t; ~/ YTwo-tailed test, 双侧检验# q k* Z$ B7 {3 J
Two-way analysis of variance, 双因素方差分析
& t; {; J& @2 g6 cTwo-way table, 双向表
2 f3 I& ~& u; sType I error, 一类错误/α错误+ p& B7 \" I$ u; Y
Type II error, 二类错误/β错误4 }2 P" ~9 o$ Z; M! g& S
UMVU, 方差一致最小无偏估计简称$ K4 D3 b. E1 a! a5 W1 N
Unbiased estimate, 无偏估计
! m6 }+ j, L: B8 V ZUnconstrained nonlinear regression , 无约束非线性回归. c0 r% j" B( w2 z, K' S# W
Unequal subclass number, 不等次级组含量; @2 D/ t2 R0 P! d+ }
Ungrouped data, 不分组资料' [5 @" e! y' g- Z
Uniform coordinate, 均匀坐标
: Y1 o" K, B7 [ u8 K7 ]9 S+ xUniform distribution, 均匀分布
' t8 X k# r$ h! N( {% IUniformly minimum variance unbiased estimate, 方差一致最小无偏估计4 H0 \; g3 |/ R- W& }* [
Unit, 单元! u2 E( W7 L+ K, C: E% n
Unordered categories, 无序分类5 P' r5 T( ], s+ @# i" k
Upper limit, 上限! E: M j' f% i2 g) V
Upward rank, 升秩! c' k1 ^: w! X* [& i; i
Vague concept, 模糊概念
1 s) R1 \# R- t h% C) |7 m; ]Validity, 有效性3 Q) l @6 C$ r0 d' Y
VARCOMP (Variance component estimation), 方差元素估计
- ?* Q7 ^& O$ N, L$ V. q2 M3 HVariability, 变异性
3 g% \8 n) y/ N( {, }# dVariable, 变量( g* i- d% s/ u9 p. L! y& [1 `2 X" s8 Y; B
Variance, 方差
1 @' R% I' ^" z8 X1 Z6 b4 k& k0 p, ?Variation, 变异$ X" @5 c1 }3 C! _5 Z) `
Varimax orthogonal rotation, 方差最大正交旋转
4 {( [% F5 Z& D$ c wVolume of distribution, 容积
' I7 t1 b0 C0 ]) P$ R( ]W test, W检验! L0 |( z7 r* Y6 d3 Y! I% t) ~
Weibull distribution, 威布尔分布
! n# f' f z0 @Weight, 权数
& [/ a. a- O. B) X6 q/ F1 [Weighted Chi-square test, 加权卡方检验/Cochran检验6 P- w1 E+ O' Q/ I, u8 B
Weighted linear regression method, 加权直线回归
6 s" t' D% w; ` C xWeighted mean, 加权平均数4 ]+ H- c9 S0 w
Weighted mean square, 加权平均方差
3 C( O* c- q, Z3 H |3 d, o7 \Weighted sum of square, 加权平方和 Z) U2 \. q2 S) f$ s
Weighting coefficient, 权重系数
/ q2 j* A$ Y* T( J9 ^9 Y/ @, hWeighting method, 加权法 + f {* v. _! Z" ?- C
W-estimation, W估计量+ q1 m" u1 ]8 o. c: X4 t. x3 I9 z# `
W-estimation of location, 位置W估计量
. s" D& M7 v n8 c5 [- I' j/ `Width, 宽度2 a! D% }! r$ d
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验9 w X+ u, j& @/ [
Wild point, 野点/狂点2 D, R. L" ^9 b% O0 @
Wild value, 野值/狂值
0 ]! D- |) x7 PWinsorized mean, 缩尾均值: s, D, U3 e5 H& b
Withdraw, 失访 : z! A( ~& h; s k# ]2 D
Youden's index, 尤登指数% Q" F3 K( E0 B7 j/ b
Z test, Z检验
1 F# U/ K g: S- c d: WZero correlation, 零相关
) ?7 X# E% ?( y0 Z7 q, j9 fZ-transformation, Z变换 |
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