|
|
Absolute deviation, 绝对离差 M. f# P5 w. } s# b( O8 a
Absolute number, 绝对数
9 Y+ I- a+ E# _0 U2 j' l: jAbsolute residuals, 绝对残差
& Y, L1 S/ [6 A/ {; h0 BAcceleration array, 加速度立体阵0 O: Q# M- L5 F5 e0 {. u5 d
Acceleration in an arbitrary direction, 任意方向上的加速度
8 m' ]8 [3 T6 vAcceleration normal, 法向加速度5 b7 t- O4 Q1 ?
Acceleration space dimension, 加速度空间的维数0 a+ y1 D+ H( a+ F
Acceleration tangential, 切向加速度$ ]1 @; D- N. A& m2 P. F
Acceleration vector, 加速度向量
; i2 Z8 t$ Y4 q' {7 LAcceptable hypothesis, 可接受假设9 z7 f c! Y7 n$ b
Accumulation, 累积! b" q% O9 _* a( t$ {
Accuracy, 准确度
7 X) m$ z9 T1 n; y: m- l/ [2 pActual frequency, 实际频数6 i! K4 e9 y& M: s3 ^
Adaptive estimator, 自适应估计量7 b% x& P- W. a9 R
Addition, 相加1 e. f8 r- u' U0 }6 [4 b
Addition theorem, 加法定理
6 B! C) w: h/ }* h6 R% ]: p7 g% W6 GAdditivity, 可加性
! d7 B) [- y4 CAdjusted rate, 调整率; Y& m$ b6 I+ V+ F* D# L- w0 C
Adjusted value, 校正值
" \( `% D/ |8 x5 G5 {+ X1 u/ `5 |; DAdmissible error, 容许误差
3 H4 T4 [4 h; W/ S! hAggregation, 聚集性
1 D) u( b6 t6 y) Q4 \# NAlternative hypothesis, 备择假设
8 r7 s2 A% F5 K* \Among groups, 组间! ` K7 @; G! D
Amounts, 总量2 s! J3 B# z8 R- m, k9 g
Analysis of correlation, 相关分析9 I }4 P4 ?0 m4 V& ^4 @( V/ d' L! C
Analysis of covariance, 协方差分析
, U; T# W( a! CAnalysis of regression, 回归分析8 T# v1 P, }# I& P. G) N9 j- f
Analysis of time series, 时间序列分析
7 R+ N3 J6 B X2 cAnalysis of variance, 方差分析4 {; Q6 k! O0 T& v6 s
Angular transformation, 角转换7 c1 n8 L% K( q/ w! ]1 W
ANOVA （analysis of variance）, 方差分析* h* A! \! e! a! z- j! v) L+ o( a
ANOVA Models, 方差分析模型: H% l! f/ `, W4 l4 [' n
Arcing, 弧/弧旋$ C% ]% O& C2 m8 ]% r0 I5 j- j; b% q
Arcsine transformation, 反正弦变换
6 e Y9 {. @8 g, MArea under the curve, 曲线面积
, ]5 L/ Z# M: N' X2 oAREG , 评估从一个时间点到下一个时间点回归相关时的误差 K# m6 E/ Z0 l. ^
ARIMA, 季节和非季节性单变量模型的极大似然估计
9 V, W) ~" o+ ^8 x) xArithmetic grid paper, 算术格纸, c6 s( N+ Q6 x. Q9 o
Arithmetic mean, 算术平均数2 b+ L0 M* L" W. @5 b
Arrhenius relation, 艾恩尼斯关系& x" S8 q7 b0 z) C/ k
Assessing fit, 拟合的评估. _$ h1 A+ F* M
Associative laws, 结合律
" Z3 A7 p2 G7 {* J4 i3 _* AAsymmetric distribution, 非对称分布
6 {5 Z# R% z$ C( b+ I5 ~" vAsymptotic bias, 渐近偏倚5 e: l% S8 r e2 ?" O
Asymptotic efficiency, 渐近效率
- N2 Q: ?/ H/ FAsymptotic variance, 渐近方差
- w, {) [- J, @Attributable risk, 归因危险度# _% a( r( \2 e: j
Attribute data, 属性资料
3 ~0 ^8 E! ]$ _6 H3 N3 Y( }) L6 H) pAttribution, 属性
- R. u2 |8 `- z$ \4 ^Autocorrelation, 自相关3 J/ R4 O! s& Q' b
Autocorrelation of residuals, 残差的自相关
/ ^+ v- J7 s; w. O3 i9 JAverage, 平均数3 n& v) b( Z' O5 i
Average confidence interval length, 平均置信区间长度
* _3 E2 i, _% S0 FAverage growth rate, 平均增长率. S& x3 ?: v4 C8 e/ q# j& Z
Bar chart, 条形图
8 k8 x0 g2 u% w C" DBar graph, 条形图: t( f3 q, M8 n4 T R7 l; z+ I, x
Base period, 基期$ H- @* M, ~- a5 b3 i+ v E
Bayes' theorem , Bayes定理
0 k, {% e% {6 m) }$ W) O2 [/ oBell-shaped curve, 钟形曲线
! o* Q* w6 D* EBernoulli distribution, 伯努力分布& P7 [/ R' h* h
Best-trim estimator, 最好切尾估计量
9 y* T( u! Z& ]9 A3 k% IBias, 偏性, y5 H) E! x% k+ j- ^
Binary logistic regression, 二元逻辑斯蒂回归
5 d8 W7 j: H* E$ X! sBinomial distribution, 二项分布
8 ~+ \# E* s# O$ n& h/ x5 i! @Bisquare, 双平方 G# U+ y8 |* j
Bivariate Correlate, 二变量相关
c& |+ a& f. Q* V6 f+ X% i9 |Bivariate normal distribution, 双变量正态分布! F+ t1 t5 b. a7 n& t$ t# o$ Y
Bivariate normal population, 双变量正态总体% ?. @1 Y3 T6 S% H8 o' V
Biweight interval, 双权区间' j4 ?5 u' y3 u" w7 a! s
Biweight M-estimator, 双权M估计量" }# p4 {" D2 ?3 u! L
Block, 区组/配伍组
8 l+ ^9 Q1 k# B! L: P, a# z$ f8 YBMDP(Biomedical computer programs), BMDP统计软件包
5 g; X1 D2 e/ }. u/ ~' C; D/ L# u& |Boxplots, 箱线图/箱尾图6 d* ?3 W3 X2 }5 }" p8 `. N2 t
Breakdown bound, 崩溃界/崩溃点* r1 j- h9 \$ b! E/ @
Canonical correlation, 典型相关2 R! ]6 p) E% }4 ?% I: m; n* @- \
Caption, 纵标目' L6 x9 h4 y( f! ~
Case-control study, 病例对照研究
% L! ?% P8 o2 M. m sCategorical variable, 分类变量
, |; H& w3 Y# }6 v' SCatenary, 悬链线% X3 Q: W7 H2 [+ L7 h$ E
Cauchy distribution, 柯西分布0 k+ Z- E, r& O9 Y; X3 N/ r1 g
Cause-and-effect relationship, 因果关系9 A' `% ^3 i0 L/ M! H8 J& V+ H& r
Cell, 单元
$ S7 X3 Z9 I8 b. S, WCensoring, 终检
6 I) B# E! }) t, @4 H9 `' ^1 }Center of symmetry, 对称中心3 M6 A$ a4 G$ Z3 d
Centering and scaling, 中心化和定标
+ z+ f3 {! I$ x+ ECentral tendency, 集中趋势
* W" T. }( Z N6 W3 N6 S# ^Central value, 中心值
$ g7 s6 _8 r% iCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测: P* m8 A8 | o) b/ f
Chance, 机遇+ x/ @3 n9 w! k$ c! B6 w3 {1 t
Chance error, 随机误差7 J# I4 j/ T- i. q/ C7 n% B% Y
Chance variable, 随机变量% B% Q6 ~4 I* k% J# o
Characteristic equation, 特征方程
; }6 f% E+ N& g' S: ~3 CCharacteristic root, 特征根4 x- f: |0 P+ ^+ H7 t
Characteristic vector, 特征向量2 ^' Z$ |9 p3 P, z$ u3 |; o' o
Chebshev criterion of fit, 拟合的切比雪夫准则( c4 {/ l4 q: @" k/ o8 u
Chernoff faces, 切尔诺夫脸谱图, J I: V: t2 g
Chi-square test, 卡方检验/χ2检验
2 X# L% Y5 X% H+ [Choleskey decomposition, 乔洛斯基分解
* A. A& ?0 f1 E. k+ NCircle chart, 圆图
, q5 a5 h; t, Q. [# s9 i4 ?Class interval, 组距
3 O, K% |, a$ U/ R) i3 hClass mid-value, 组中值: U9 ?6 @4 j! r4 P+ b
Class upper limit, 组上限& ]4 J; x' U6 _6 Y& `5 t/ j( U$ X
Classified variable, 分类变量
9 h( H$ m$ y( e+ D# X/ FCluster analysis, 聚类分析, Q4 ? l4 Q" q, c+ ~6 h- E# T5 h
Cluster sampling, 整群抽样2 F. m* ^) z2 s5 P2 j# E7 F( M
Code, 代码 [: W+ }% F6 W% B0 x
Coded data, 编码数据2 y, N$ x9 v U3 i
Coding, 编码
# S& D9 J* U5 Y8 a1 W" x) F/ MCoefficient of contingency, 列联系数7 m |8 T9 {9 P! O8 a8 z `
Coefficient of determination, 决定系数
- w1 O! H$ T0 j3 w! q$ g9 oCoefficient of multiple correlation, 多重相关系数
9 i* C8 }' _2 z0 hCoefficient of partial correlation, 偏相关系数! h* x/ `5 ^0 ~) K: h; y4 p
Coefficient of production-moment correlation, 积差相关系数( z B9 u8 Y8 ?# |5 |8 u
Coefficient of rank correlation, 等级相关系数% B. Z* m$ Y" U+ _& X: Q
Coefficient of regression, 回归系数
( ]; ]0 r/ R3 \! j, g0 n) jCoefficient of skewness, 偏度系数
! E* T5 a2 w" m$ c2 \( @Coefficient of variation, 变异系数
1 M6 {9 E! Q7 T# c# L: nCohort study, 队列研究/ M2 l3 Z' e9 d7 g0 J
Column, 列
) i4 d0 q. c3 r% UColumn effect, 列效应: x1 @1 A* h/ y8 j% ^% L" b
Column factor, 列因素6 q4 X( w. A- k& Y
Combination pool, 合并
+ g7 d5 }! o" r& ^Combinative table, 组合表4 |; }% |0 C+ P8 h+ Z- f& `' p
Common factor, 共性因子+ n; @/ r. R- ~5 c% }
Common regression coefficient, 公共回归系数
* u: z- t+ v4 m( HCommon value, 共同值
, }2 Z. Q2 ^) L( L l& ICommon variance, 公共方差
" G# l, {& U. DCommon variation, 公共变异
, C5 n: z* ?% o$ [* e( KCommunality variance, 共性方差
; `$ c+ d. R5 f9 N. W- U6 ~Comparability, 可比性
4 ?' B! z Y1 T& a5 |, IComparison of bathes, 批比较, S0 q0 i O( V% h. m6 k
Comparison value, 比较值
2 f4 H" {0 M, ^# B! S% A% tCompartment model, 分部模型& h$ t3 ?" F. p6 ]1 v
Compassion, 伸缩* O# d4 y* g/ L$ I0 a. X
Complement of an event, 补事件% T9 I/ T4 x) R- _: I7 D
Complete association, 完全正相关% X$ b, S$ i$ Q# b
Complete dissociation, 完全不相关0 H" S& t9 X* N
Complete statistics, 完备统计量
! s8 B% F1 f3 @, {6 F6 M0 t, MCompletely randomized design, 完全随机化设计4 e* J0 L9 {( r% m
Composite event, 联合事件
M( T3 K# U/ R" S0 oComposite events, 复合事件
) R( L& U( ?% R# B! K0 x- lConcavity, 凹性0 B& w$ n! Z$ x {
Conditional expectation, 条件期望! j; N- ~9 a, J4 C( o q7 P
Conditional likelihood, 条件似然
) x5 l4 K# _7 F3 c, H3 mConditional probability, 条件概率 N f# J) z2 o8 }
Conditionally linear, 依条件线性0 C* l9 r- }7 p# c8 [0 d' b
Confidence interval, 置信区间( S% I8 e2 t$ e" n; n5 I
Confidence limit, 置信限0 G, o+ f+ O% @8 L, Y* e9 K
Confidence lower limit, 置信下限
* U; r, P! R, M$ o/ hConfidence upper limit, 置信上限( ?& {( P9 q: f* W, v0 g. |6 `" {- R
Confirmatory Factor Analysis , 验证性因子分析 O2 Y' h0 n) b8 H/ \6 n: ?% n
Confirmatory research, 证实性实验研究
# d; F4 Q8 Y1 eConfounding factor, 混杂因素# ~. [# k/ w, }0 I
Conjoint, 联合分析! X: @1 X6 L+ S% ?1 \# s1 v# i
Consistency, 相合性
) |; X9 I8 ~5 S oConsistency check, 一致性检验7 D r6 ?% A7 _5 b4 k
Consistent asymptotically normal estimate, 相合渐近正态估计% W4 V. f- R9 [2 {. I& d/ |
Consistent estimate, 相合估计
6 l) i% ?& y- @* ^& x# m9 iConstrained nonlinear regression, 受约束非线性回归
! A* z C7 Y i1 R$ fConstraint, 约束
5 ~. t: h/ }* a# E. K* w0 rContaminated distribution, 污染分布! A* e& o4 l5 t/ |, u
Contaminated Gausssian, 污染高斯分布3 Z8 R6 [: g1 j Z
Contaminated normal distribution, 污染正态分布; p2 E( Z' y Y5 h0 C" u
Contamination, 污染1 ?6 E; t4 L# L0 s
Contamination model, 污染模型
/ R0 `9 H4 z1 T, D5 j r7 }* O9 ZContingency table, 列联表
2 E' c$ y }! j8 u6 Y1 WContour, 边界线
9 q% {- s$ U" r! [* a5 O: O1 p) ~8 ~Contribution rate, 贡献率; E3 v7 c$ T0 s* R
Control, 对照) t+ _ \* L7 i% r; g% R' H
Controlled experiments, 对照实验1 u8 F5 J0 Q# D/ ^* R' E4 g
Conventional depth, 常规深度
4 d4 S$ r; r WConvolution, 卷积: U* b, Z/ K& I; o: d( {
Corrected factor, 校正因子 Z" T" f- v( O5 H
Corrected mean, 校正均值
3 L( h5 B. T) ~# D2 S+ \! h* ^: l. QCorrection coefficient, 校正系数
/ C. t$ \ \( C) A( D/ r2 L$ l3 xCorrectness, 正确性, W2 x3 [0 r" h: W" J7 X
Correlation coefficient, 相关系数
2 K3 D. x% P {) t# ^- nCorrelation index, 相关指数. t, Z$ p! ]3 }) G$ o
Correspondence, 对应( M3 ]8 t" Y2 h- [
Counting, 计数
3 \7 d a# G! O" M% k2 V9 l! pCounts, 计数/频数& P; u/ D/ J( {1 Y \
Covariance, 协方差
8 P: f+ H3 N/ I; yCovariant, 共变
: ?$ `7 ]2 f" P- m7 [Cox Regression, Cox回归0 D9 |: l7 A4 U7 l: i9 l
Criteria for fitting, 拟合准则6 d' D' X6 m; T2 D" g. M' {4 g2 o
Criteria of least squares, 最小二乘准则
# E; H$ i3 Q( n qCritical ratio, 临界比1 x; m( F5 a( C5 J
Critical region, 拒绝域
' }# d+ {7 w/ x3 L0 {" T" qCritical value, 临界值: F' y& {0 L( f6 m$ m: x
Cross-over design, 交叉设计
8 S1 s# ~. b$ R6 z- s$ N# _Cross-section analysis, 横断面分析* z# I. K! O. \% s) c* d
Cross-section survey, 横断面调查9 N' i! E* s" d% v1 ]" c; g7 M
Crosstabs , 交叉表
' h0 \0 b1 a7 B: y8 K: t1 ]. [& ~Cross-tabulation table, 复合表
; S: W7 s7 r4 ACube root, 立方根- a3 m0 v; E8 D: U7 }
Cumulative distribution function, 分布函数: w! q% U5 h0 A: k) _
Cumulative probability, 累计概率
; D6 M) m c2 u HCurvature, 曲率/弯曲
9 N5 a- y7 q, DCurvature, 曲率
1 M' z; ^: H# y7 SCurve fit , 曲线拟和
1 k `# P- O9 U5 nCurve fitting, 曲线拟合- \3 s! ?* i% p( h) z
Curvilinear regression, 曲线回归. \; j# V3 X& r/ I
Curvilinear relation, 曲线关系, P9 a9 Z2 p) x; C8 A
Cut-and-try method, 尝试法8 n! d9 m" K. c3 L
Cycle, 周期2 h( Z$ D: S2 v
Cyclist, 周期性
1 r! r9 |$ f) [6 H0 m/ c( j' t0 mD test, D检验
3 i" B4 {) S2 [) \1 h1 q7 E; o1 GData acquisition, 资料收集 _& h+ Q( Y" h, E
Data bank, 数据库# p; i/ h$ o. D4 C1 I ^
Data capacity, 数据容量
- P; a7 [5 S& ^* d1 ]Data deficiencies, 数据缺乏% Q1 v8 E3 k" n' Y, U
Data handling, 数据处理7 q3 L1 p1 j0 e& {- Q
Data manipulation, 数据处理% g8 P, R. X0 B5 t4 D8 U
Data processing, 数据处理# Z, J& q$ O+ l9 A$ `
Data reduction, 数据缩减
6 H! g, G0 K3 ~1 x# U z, l. e8 ~Data set, 数据集
- d! n1 u/ v" g aData sources, 数据来源' K4 }+ `0 p6 @6 X+ I5 |
Data transformation, 数据变换4 ~/ w" Y# ]2 n4 d) F2 Q
Data validity, 数据有效性* f+ Y0 i3 O. m+ H
Data-in, 数据输入3 G" I* ]' q) N* u( Y
Data-out, 数据输出# `9 h2 n" b% E9 i/ u. P
Dead time, 停滞期 d2 v) G3 a: W6 t" A7 j! ^
Degree of freedom, 自由度0 g6 ` M b a' N. q
Degree of precision, 精密度
/ h' u9 J' d3 s8 d5 MDegree of reliability, 可靠性程度' r# E2 i- {& i, l
Degression, 递减6 O. w1 ]+ y U0 {/ ~9 Z* y
Density function, 密度函数
! m& k2 f- N( m) c O# tDensity of data points, 数据点的密度
* n# v$ J8 H, B) V, @% iDependent variable, 应变量/依变量/因变量
2 `/ w( l$ i" T$ F x) VDependent variable, 因变量$ Y% T9 w: N; `2 E
Depth, 深度
1 E5 b9 u2 k6 u: J$ v! SDerivative matrix, 导数矩阵
$ c, u1 G# V! @8 {0 t0 HDerivative-free methods, 无导数方法( z: K" e8 y# b- \' l4 m$ n
Design, 设计$ V3 y/ e4 `* [! a
Determinacy, 确定性. n( B1 R! V z( b1 \- P; H" f
Determinant, 行列式
( Z8 P2 N( U* a; }8 YDeterminant, 决定因素% X+ O: |2 n/ p
Deviation, 离差
! e- E, B3 n J; K5 x# W- Q' k3 F9 x3 UDeviation from average, 离均差; G7 x7 T+ M3 N) ^% y4 L+ v0 O
Diagnostic plot, 诊断图1 g! Q2 d6 u0 f3 ~( f
Dichotomous variable, 二分变量
+ w3 F6 J: A, S( d0 Q5 L$ T( ZDifferential equation, 微分方程
. J* _9 t- w" [Direct standardization, 直接标准化法
0 ~- K5 o3 C" [" G0 p7 c2 W0 ^( S, ODiscrete variable, 离散型变量/ q9 r) f' p$ k5 d8 I
DISCRIMINANT, 判断
/ |, P5 { G- q- VDiscriminant analysis, 判别分析; }0 J+ G) Z0 }
Discriminant coefficient, 判别系数0 x ], O/ t& \& X+ z- s# K1 }5 ~7 h
Discriminant function, 判别值
5 S+ g; C6 {( U: y& \* sDispersion, 散布/分散度
, N' P# R Y& c7 _' H* V& X% b, iDisproportional, 不成比例的
" D" {$ [; u, q0 v1 oDisproportionate sub-class numbers, 不成比例次级组含量
2 A/ A c, C+ s N$ @5 D, [( D. lDistribution free, 分布无关性/免分布
9 D0 M8 B- }# {Distribution shape, 分布形状: I5 C! U$ X" }1 J3 u5 [/ _* \5 W$ g* f
Distribution-free method, 任意分布法* @, i/ @& y& \8 A6 J
Distributive laws, 分配律6 j, A+ b% y8 u
Disturbance, 随机扰动项
. C4 u0 ~+ {, {) H8 ZDose response curve, 剂量反应曲线 Q0 T* O: y4 ~! p$ p
Double blind method, 双盲法* |: @8 p, t" z7 q4 f# q
Double blind trial, 双盲试验- B0 v3 K, R9 @( d& p' q; i) d5 i" \
Double exponential distribution, 双指数分布) W: S' p0 a& B
Double logarithmic, 双对数
% h9 i9 a: K1 b9 p2 y) i8 aDownward rank, 降秩* _3 ~ l( |0 b8 s" Y7 o( |+ U ^
Dual-space plot, 对偶空间图" n7 A) G! E. C8 c( E
DUD, 无导数方法
! d# R/ f* N. e ?Duncan's new multiple range method, 新复极差法/Duncan新法- E/ J" Y( H; H! N& e
Effect, 实验效应
; X h6 k2 x2 i0 d9 XEigenvalue, 特征值
4 B# F1 W+ u1 Z' YEigenvector, 特征向量% F: v7 I `+ g- P# M0 G
Ellipse, 椭圆0 q4 V9 ?4 `( G0 J" J
Empirical distribution, 经验分布+ o' a6 z" C' T$ _7 [: H0 g; `
Empirical probability, 经验概率单位4 {( d. n4 J" @6 |$ d
Enumeration data, 计数资料
U+ J$ D, E3 I# `9 @' w9 U CEqual sun-class number, 相等次级组含量2 @' V$ N. Y7 j5 ^. s; w
Equally likely, 等可能
) c0 c: h+ E- F" B8 J8 NEquivariance, 同变性
3 E& n$ c3 I% A {5 IError, 误差/错误" o. f/ b( k! V6 W& y o
Error of estimate, 估计误差( S1 h- e+ ?2 J$ t3 W: k
Error type I, 第一类错误) M) B( h' W; N& t) Z+ p* G
Error type II, 第二类错误
3 K! s N ^; zEstimand, 被估量
' E# E& ^, p$ D8 q* |Estimated error mean squares, 估计误差均方1 M: u' Z6 f$ F. h7 m$ ^
Estimated error sum of squares, 估计误差平方和. O- p3 y9 N* e8 ~8 E/ o6 d: i6 J" Y" @
Euclidean distance, 欧式距离& W: w6 i6 W2 D9 q( k: ]8 t
Event, 事件
7 H' K+ ^! e% ]/ Z) \, H9 L) sEvent, 事件
& g0 L C3 w5 yExceptional data point, 异常数据点* I0 X* b. G* r' Z6 e# m/ \0 ^
Expectation plane, 期望平面" j0 U' D- {3 d7 K$ `# i: ^
Expectation surface, 期望曲面
( Z# J, \. A: g. W3 W$ HExpected values, 期望值" g8 D% C. V* b
Experiment, 实验; p, e" I R, }4 e' z" e
Experimental sampling, 试验抽样
' q) o8 N- H" R1 Z) bExperimental unit, 试验单位
4 _, d1 K$ Q: ^* \7 S0 BExplanatory variable, 说明变量
8 J/ Y s/ X0 N/ O: N7 \; nExploratory data analysis, 探索性数据分析% S' O* |% A d {: ^
Explore Summarize, 探索-摘要 C/ }- E+ o2 H& g. G6 I3 K' o- i, u
Exponential curve, 指数曲线 k8 m# _0 b$ R9 \+ W" d c; R
Exponential growth, 指数式增长1 d: [5 W4 v, U* I
EXSMOOTH, 指数平滑方法
( m9 N$ q" _5 d2 ^) @3 g1 v1 aExtended fit, 扩充拟合
3 j1 I5 q( j: w+ UExtra parameter, 附加参数( _5 v6 l3 ~, |& p. D7 H f
Extrapolation, 外推法9 l: i6 U) m9 e& u: \7 r$ S o
Extreme observation, 末端观测值: I/ b9 P0 B- x1 h
Extremes, 极端值/极值' J6 r- s9 J% A1 V: a
F distribution, F分布" X0 N7 W5 o, B8 h: C* F' v
F test, F检验
# W0 d% y& u' d0 l; Y. {1 B# xFactor, 因素/因子
7 \8 |' {; o5 N& E4 v3 KFactor analysis, 因子分析' f$ ?- @0 D! _* _
Factor Analysis, 因子分析
$ K" ^$ ]4 V1 K8 Y; A( \ kFactor score, 因子得分 0 I' \* S2 d1 T- j, _9 f
Factorial, 阶乘
0 R' F* s# W& j5 uFactorial design, 析因试验设计
# u7 Y2 d; `; u6 {1 @2 _8 ~False negative, 假阴性! r- X) `% A! r, Z4 Y0 l, o
False negative error, 假阴性错误/ z0 A! ]/ j% e! T6 [
Family of distributions, 分布族
: @# ]0 k8 V# r- T% \5 \Family of estimators, 估计量族0 Q9 f4 W q/ o; n
Fanning, 扇面6 _% w5 s d a, n
Fatality rate, 病死率& ?/ S5 w4 I) T# a N9 z3 L
Field investigation, 现场调查
6 m! ]& H% o8 \9 b# _/ kField survey, 现场调查/ N' g. p6 l9 }( O' J9 v# Z
Finite population, 有限总体& O, h4 M& F x9 S3 ]1 E
Finite-sample, 有限样本
: T# k5 V! f# x& a2 h/ GFirst derivative, 一阶导数' |' f) s2 K4 J3 o2 y0 @
First principal component, 第一主成分
8 q5 n( i- p2 _$ _5 AFirst quartile, 第一四分位数
7 j8 V% {. g/ W; N9 t0 G0 x+ Y5 zFisher information, 费雪信息量
% o) X* K2 Y, h4 W9 lFitted value, 拟合值. I+ V: o% [$ B. |' {! q
Fitting a curve, 曲线拟合
1 }. k0 J! V6 U- W z& a5 Y$ n; bFixed base, 定基" h: A! y1 d! z- h! ?( x* L
Fluctuation, 随机起伏1 S5 U0 D) z5 \# X+ k9 m
Forecast, 预测& P4 O2 i2 B- }' X4 j* h/ S5 i
Four fold table, 四格表1 m! b( a4 ~# H) V/ a6 k
Fourth, 四分点
( B G6 A p6 S7 ?5 u G, L/ nFraction blow, 左侧比率! B8 ^6 R1 G& }: ]
Fractional error, 相对误差
+ ~: Z1 S% V; T8 w4 P; NFrequency, 频率
& q2 k( L. N7 t3 I N7 RFrequency polygon, 频数多边图6 k9 m7 T; T! O+ R' N' {' b
Frontier point, 界限点
* D6 W6 q8 s/ X1 w0 g& zFunction relationship, 泛函关系 `5 J' `, F! d2 W8 A
Gamma distribution, 伽玛分布
* ] \ v8 n6 A% k3 F# HGauss increment, 高斯增量% F8 U" b/ X2 M0 c$ }1 H2 Y2 E" C
Gaussian distribution, 高斯分布/正态分布
1 r# w/ W- }3 q' QGauss-Newton increment, 高斯-牛顿增量
4 F7 n+ R: e9 H& a, E; s# _General census, 全面普查$ J/ a) ^! n/ Y' n9 l
GENLOG (Generalized liner models), 广义线性模型 s! o; B2 @0 f( w, e
Geometric mean, 几何平均数: x9 D7 t( L5 i6 {5 ]1 }* b0 C
Gini's mean difference, 基尼均差1 \4 X3 a, E; D6 O+ ]' t: D. {( p
GLM (General liner models), 一般线性模型
. T% Z- G8 I& S% X9 Y5 @/ u9 R. FGoodness of fit, 拟和优度/配合度, b0 l; }5 l1 _6 M7 P0 I R, d* ]
Gradient of determinant, 行列式的梯度+ H, j/ d3 P$ x* E# e1 z0 {
Graeco-Latin square, 希腊拉丁方
. N+ r" `6 F1 {: K% i# m7 dGrand mean, 总均值
1 j( X; l) P+ O! z* w7 IGross errors, 重大错误
7 D3 m+ U" j& G0 b% p2 i1 `( aGross-error sensitivity, 大错敏感度; T# j% H3 Z8 i4 n) o1 t
Group averages, 分组平均/ X5 {4 x; B1 m2 L
Grouped data, 分组资料
0 S1 {. |5 Z! ]3 x9 u1 Y% BGuessed mean, 假定平均数
0 j6 I4 ~8 J1 b2 C1 J7 ZHalf-life, 半衰期' |5 c! t- S; s4 Q2 Z1 J- f
Hampel M-estimators, 汉佩尔M估计量
, ~" P: u4 D4 H z8 h) m- pHappenstance, 偶然事件
, z5 f, H0 u+ K8 f' THarmonic mean, 调和均数
9 f5 k- a& @& x; P M& R) `. zHazard function, 风险均数* w6 X2 A6 \! \% K
Hazard rate, 风险率
* e4 s% i% `& Z ~Heading, 标目 8 W+ V8 f" X6 p, K5 c4 h
Heavy-tailed distribution, 重尾分布: ~/ f3 R" g- n1 A7 ^/ {( l
Hessian array, 海森立体阵
+ |9 q- k( v, E9 kHeterogeneity, 不同质
! y) |* Y2 Q2 ~/ @0 E5 J- PHeterogeneity of variance, 方差不齐 / m' V7 e- m$ I, W
Hierarchical classification, 组内分组
. z! Y) g6 i- e/ S7 ]Hierarchical clustering method, 系统聚类法! r1 K y1 V8 v
High-leverage point, 高杠杆率点4 a3 D; |) ~" Y% @, {" M
HILOGLINEAR, 多维列联表的层次对数线性模型
2 ]$ L' Z2 Q- M# }$ k& H, _+ AHinge, 折叶点
! Q1 e. }/ M9 ?Histogram, 直方图
+ {# a, z9 \* R0 \Historical cohort study, 历史性队列研究 - s" I8 Q7 t% U
Holes, 空洞
/ u9 K& {# x; _2 q) Q- K5 x( ~HOMALS, 多重响应分析
- O$ P3 t0 K3 JHomogeneity of variance, 方差齐性
. ]0 T8 O% Y* ]Homogeneity test, 齐性检验
3 S6 I& B1 b* ?- Y/ AHuber M-estimators, 休伯M估计量
5 I* E4 K$ \% H9 b( MHyperbola, 双曲线
2 ~2 Y: k0 q/ k( W( vHypothesis testing, 假设检验
; X2 a9 k5 v! N9 f; lHypothetical universe, 假设总体% J# U. ~' v" g6 b
Impossible event, 不可能事件
9 l9 @! L' \' ~# H7 w0 O2 o' \Independence, 独立性
7 n: ^0 [0 o, ]- k( ^* [, `Independent variable, 自变量
- Z P% A& k% GIndex, 指标/指数& _- X, i! g E/ V4 w. T( h$ D
Indirect standardization, 间接标准化法
; p5 }! v* Z! F* r4 YIndividual, 个体
1 X1 a7 J% }3 i/ B% MInference band, 推断带" M) i: R6 X- P7 `* u
Infinite population, 无限总体2 s* |2 H6 t! a
Infinitely great, 无穷大
4 [- W+ q) K, ~5 }" cInfinitely small, 无穷小
9 s: f7 F5 j8 {Influence curve, 影响曲线8 N d$ }( q% N& G7 @6 A
Information capacity, 信息容量
$ I% Z, M, f6 i, S6 oInitial condition, 初始条件1 H. u8 L( ^" j1 h( }! U
Initial estimate, 初始估计值
6 B5 S8 H9 M* E) z; tInitial level, 最初水平% u2 h' u$ [" b& [' x
Interaction, 交互作用
; }% W& A) s2 Q3 o N6 f- LInteraction terms, 交互作用项
$ |% W z( l' RIntercept, 截距9 y: L# P& }' s X7 v% y
Interpolation, 内插法& F2 d+ A3 A c( ?
Interquartile range, 四分位距! c* B% i8 {2 {. K( Q4 g2 B' u- |6 X
Interval estimation, 区间估计
5 d4 h2 n, q* ~8 w" UIntervals of equal probability, 等概率区间# X, k( k D: E
Intrinsic curvature, 固有曲率
3 |; U/ Z; D! @" \$ i% P4 E4 V' V4 UInvariance, 不变性
$ A! Z+ X/ C1 y HInverse matrix, 逆矩阵
/ u$ r) G- [0 ]& V! B5 EInverse probability, 逆概率' A6 z% ]) W% a" l5 U g
Inverse sine transformation, 反正弦变换' L/ e! k5 J; N5 c
Iteration, 迭代
6 Q( m8 E& x6 U+ o* r" AJacobian determinant, 雅可比行列式
: e! h' |2 ` [9 X5 S$ c) ?Joint distribution function, 分布函数
' k7 x9 j% [/ S0 E! w; pJoint probability, 联合概率/ d. [" x7 n" e
Joint probability distribution, 联合概率分布
, \% H! a4 R7 I: Z3 z3 w8 P5 LK means method, 逐步聚类法
# W; f! m: z: E8 U" a8 }) pKaplan-Meier, 评估事件的时间长度 8 B* _) a" ?: u: f, t. S: Z
Kaplan-Merier chart, Kaplan-Merier图
" \) G1 S, R8 M0 @. g6 qKendall's rank correlation, Kendall等级相关' ^' o4 b7 Y H& v0 `& X, ]! f
Kinetic, 动力学4 R: \" A5 d- v# E$ W5 {
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验6 Z* H7 Q+ f9 u7 F3 Z5 x
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
* r" w$ x! K. L9 xKurtosis, 峰度
& V2 J4 l |0 @4 [2 {" ^2 ~Lack of fit, 失拟
/ u6 f: F, H7 ALadder of powers, 幂阶梯
' }9 b+ _4 ]" q4 S$ q, w! DLag, 滞后7 S+ P& ]+ c" [
Large sample, 大样本8 |9 |" F8 p$ r. |& x! U
Large sample test, 大样本检验
. _. X+ ~# X5 R, D9 fLatin square, 拉丁方- E8 h' l& D3 E6 f+ w0 K' g0 X
Latin square design, 拉丁方设计
8 k; I6 e/ t% M/ V$ S# t; ]: JLeakage, 泄漏
V0 H' s+ W" `* c" aLeast favorable configuration, 最不利构形6 b* I( ^4 {: v6 W+ p
Least favorable distribution, 最不利分布 v4 n \3 x- n) V' @+ _
Least significant difference, 最小显著差法
' J* P/ j' e$ c* l" q oLeast square method, 最小二乘法$ E3 F: P, d: Q$ E: q
Least-absolute-residuals estimates, 最小绝对残差估计
" k6 V+ a }- }0 I/ s' ZLeast-absolute-residuals fit, 最小绝对残差拟合5 T+ n% m/ T1 \8 u3 h
Least-absolute-residuals line, 最小绝对残差线+ i, l, f5 P+ I" T$ K
Legend, 图例
. Q1 }4 P U$ z4 KL-estimator, L估计量# f5 p7 y, u! T7 h! w7 i
L-estimator of location, 位置L估计量6 n/ C3 {/ P8 I
L-estimator of scale, 尺度L估计量/ d+ @) a* I& }% k+ h& t% l
Level, 水平7 ~+ K( G2 K% N& f
Life expectance, 预期期望寿命
+ e$ y R6 u* ~1 e: ]Life table, 寿命表
m8 m3 n6 |; j8 B+ G3 ELife table method, 生命表法$ t" W8 k9 p0 d& z; ^* q' m# W
Light-tailed distribution, 轻尾分布1 F9 y6 H7 z- _" n" u* k* s
Likelihood function, 似然函数. ]9 `$ x4 H4 e( k- a! l9 F7 n4 @
Likelihood ratio, 似然比
- l" ]( P, W4 eline graph, 线图
* T+ F! s$ j5 N. f; MLinear correlation, 直线相关
# A" W5 d- M" O% JLinear equation, 线性方程
?) X6 l! q% g- O3 Z8 N/ q9 yLinear programming, 线性规划1 Y; W r/ ?' x7 ~7 ]# ~
Linear regression, 直线回归; U/ s6 q" N* }/ j" ^5 y. R
Linear Regression, 线性回归
. f" t# S8 s: o! n9 lLinear trend, 线性趋势
" r2 {8 e- e; l& n* mLoading, 载荷 , l- T2 D& P: e- H( t, S g3 y# c+ |
Location and scale equivariance, 位置尺度同变性
5 k8 u6 p" y$ i7 X) d$ sLocation equivariance, 位置同变性4 M4 x; m% N+ h% c {. n2 v* H
Location invariance, 位置不变性0 t$ r7 f, p1 v6 u" `- b' P
Location scale family, 位置尺度族" v8 Z$ i/ F+ n+ N1 P
Log rank test, 时序检验
4 D! A- J. Z" |4 A+ x0 VLogarithmic curve, 对数曲线8 K+ D+ _- Q9 V7 ]" w2 I3 U4 }
Logarithmic normal distribution, 对数正态分布6 P- x" u# l; @' J& p7 J& R
Logarithmic scale, 对数尺度$ L" C: h% b% @, u4 t
Logarithmic transformation, 对数变换
- t9 o+ X7 c% J* XLogic check, 逻辑检查( O5 H8 R0 z* z' e; A, `0 P
Logistic distribution, 逻辑斯特分布2 Y5 K7 e/ f& ?
Logit transformation, Logit转换$ V% i# ^$ f/ q6 }
LOGLINEAR, 多维列联表通用模型 & X' b6 f% h: E2 i
Lognormal distribution, 对数正态分布9 a/ ?2 O5 ^. d+ J
Lost function, 损失函数# i6 M( s# b J. w2 [: E3 W
Low correlation, 低度相关/ \( p1 b4 `6 b: Q+ J
Lower limit, 下限
. _4 s& s0 ]* a+ U5 H \Lowest-attained variance, 最小可达方差4 ~! _) X4 I* y- z% L- ?
LSD, 最小显著差法的简称. c$ `1 F u Q- F) Q
Lurking variable, 潜在变量0 s: w! w, ]. {8 H
Main effect, 主效应- J8 {! _' Z* }9 T
Major heading, 主辞标目
0 b1 T) }, z. X! g8 XMarginal density function, 边缘密度函数
- P8 V Q$ e" m2 m! g* VMarginal probability, 边缘概率3 S2 ?1 a- C' x0 s. ?7 m/ _
Marginal probability distribution, 边缘概率分布2 H0 }( c$ C8 a& }: D, a3 |
Matched data, 配对资料2 |+ M5 L1 Z7 s
Matched distribution, 匹配过分布, @' z O# ]0 e1 ]( `- N) e/ \
Matching of distribution, 分布的匹配
( b! Y5 Q0 M- m3 S6 n IMatching of transformation, 变换的匹配; _6 S% N0 O- ~4 b p9 M! N
Mathematical expectation, 数学期望$ N! T) l6 V6 ]" w6 [# I/ U1 D0 b
Mathematical model, 数学模型' s( [+ Z8 ~/ l7 H `. q
Maximum L-estimator, 极大极小L 估计量 ^, }) Y+ N Y! L; E% X; ]
Maximum likelihood method, 最大似然法
) e$ d t$ Q0 u+ ~ X6 JMean, 均数
9 ~9 {/ O7 H2 E5 a- Q1 f0 u0 r/ YMean squares between groups, 组间均方
7 S' X* T1 @( h; i/ b& dMean squares within group, 组内均方9 e& L Y% ^7 ?! a. M6 f" ]! E7 _
Means (Compare means), 均值-均值比较4 b9 s- w; Q) y3 u2 P; X9 S
Median, 中位数
; R5 y" c" y5 g) z" J# Z* V1 QMedian effective dose, 半数效量
& Z' \6 K* @$ N/ WMedian lethal dose, 半数致死量
! p5 f" k5 O% }; B/ hMedian polish, 中位数平滑
; O% M7 V( O1 S/ jMedian test, 中位数检验
1 u3 e4 m( ?( N- }3 F/ {% PMinimal sufficient statistic, 最小充分统计量) u0 }/ ]2 s) E( j, N- I
Minimum distance estimation, 最小距离估计
9 J7 y) m% F3 `+ H7 {' N3 DMinimum effective dose, 最小有效量8 g* ]% [0 W/ o+ S
Minimum lethal dose, 最小致死量
* R# j5 e% K* A, h& ^( gMinimum variance estimator, 最小方差估计量
. a3 y" N8 |0 Q" cMINITAB, 统计软件包
' p+ X$ f3 \6 F% hMinor heading, 宾词标目8 @% F/ h7 m* {1 n. V
Missing data, 缺失值3 L. `9 T3 z' P3 @1 |' D2 v
Model specification, 模型的确定
& q3 N" I7 G/ ]3 q( FModeling Statistics , 模型统计
$ V; o& P' n% F+ O, i6 N5 N3 B' hModels for outliers, 离群值模型
% g# [. i1 M0 L! A3 ^, A( cModifying the model, 模型的修正( T1 [, q! A4 }- o& X8 o4 |8 {
Modulus of continuity, 连续性模
0 d9 C1 z2 r( ?0 W# V. C/ NMorbidity, 发病率 2 Y3 b$ j0 K! X4 U5 V; k5 J
Most favorable configuration, 最有利构形
' @) N, W: m; WMultidimensional Scaling (ASCAL), 多维尺度/多维标度
7 u% Y2 [+ z1 B \+ i5 Q$ }, CMultinomial Logistic Regression , 多项逻辑斯蒂回归
* ^9 w4 A& X& B) Y% z* w9 cMultiple comparison, 多重比较0 X5 a! f- T! k, `* F5 C k# o
Multiple correlation , 复相关. g8 ?* d& ^7 p8 ^
Multiple covariance, 多元协方差
( {- j* @( e l# c1 PMultiple linear regression, 多元线性回归: U8 Q) f$ I% G! c8 A
Multiple response , 多重选项# Q T# x$ e" f0 Y9 p- K
Multiple solutions, 多解5 u7 e2 T! {9 H
Multiplication theorem, 乘法定理
! E5 I' m9 ]6 L+ A9 L. U& y5 p- hMultiresponse, 多元响应0 p! f* [/ G& _
Multi-stage sampling, 多阶段抽样" r7 \' a2 y+ ?) z
Multivariate T distribution, 多元T分布
3 Z, q6 I3 f k/ f# P# \Mutual exclusive, 互不相容
; T% \: t; c5 e5 c5 u, W' B3 aMutual independence, 互相独立* Q! P/ j! N6 f
Natural boundary, 自然边界
, a/ E/ }( `+ Y) E8 [Natural dead, 自然死亡# ], a/ ^. X( u& `
Natural zero, 自然零8 z, }6 N; m6 e3 Z
Negative correlation, 负相关
4 T. z% w, B, B1 W5 ?Negative linear correlation, 负线性相关8 W8 M0 `2 V& f3 E$ b+ z
Negatively skewed, 负偏8 D4 Z* N2 N9 s' U7 X# M4 I
Newman-Keuls method, q检验5 e. K5 F" a& H7 g0 ^3 _
NK method, q检验( l' f% b7 H! t4 E2 {$ q
No statistical significance, 无统计意义
% C7 T/ S; Q$ j" X# A# GNominal variable, 名义变量' j5 l0 ?+ y$ T# P! d) A5 B: j
Nonconstancy of variability, 变异的非定常性% n7 D4 T! @& \% j
Nonlinear regression, 非线性相关
6 v) x4 O0 ^4 f# D2 R1 D) B' LNonparametric statistics, 非参数统计
+ d4 |8 O+ i" ~7 v, HNonparametric test, 非参数检验
# |; m# v! ]" u( o8 v4 ?Nonparametric tests, 非参数检验
/ {5 l" J. F. L, jNormal deviate, 正态离差7 X# }' |1 j3 a4 ~5 h2 _$ `4 B
Normal distribution, 正态分布, r% \, [) v f. o
Normal equation, 正规方程组
8 | {# b" Y2 p& C5 v7 P! pNormal ranges, 正常范围
6 I* c9 T4 N2 M2 J, Q7 iNormal value, 正常值
! [ Q0 R$ R: r/ A+ q$ uNuisance parameter, 多余参数/讨厌参数! a6 W% E2 T, F/ l6 t
Null hypothesis, 无效假设
6 [ w( k8 F8 ^! K" p1 Y" B' vNumerical variable, 数值变量
. p- C* i/ U- p" qObjective function, 目标函数# ? e9 L& Q2 ?# Q) n
Observation unit, 观察单位* Y( ~ Z* ]: n
Observed value, 观察值
# J! R6 c7 z1 t% y& q# ?One sided test, 单侧检验, y/ I( p+ U7 i$ l' v0 t! n
One-way analysis of variance, 单因素方差分析: [4 E ]1 n6 K: h; j
Oneway ANOVA , 单因素方差分析
4 ~& d1 q/ T. K: vOpen sequential trial, 开放型序贯设计, ^5 F! q7 G) P/ R
Optrim, 优切尾
& W7 H: D L, z. _9 {Optrim efficiency, 优切尾效率+ G6 |3 g8 v* W; w$ n
Order statistics, 顺序统计量
- O( `+ ?/ u9 KOrdered categories, 有序分类* h8 V+ w; a8 [. ~
Ordinal logistic regression , 序数逻辑斯蒂回归4 A% y6 W' R1 F8 `% H& Z
Ordinal variable, 有序变量0 K; B2 X) }0 M" U; d( T
Orthogonal basis, 正交基1 P1 }4 I5 c9 _7 l
Orthogonal design, 正交试验设计
' W" m! v6 G% o# N1 t+ }- EOrthogonality conditions, 正交条件
5 P8 d) M8 M8 F o5 L& N. B6 TORTHOPLAN, 正交设计
V8 `$ H& ?- {9 [+ C% }* J- xOutlier cutoffs, 离群值截断点; i! Z) h1 n. n l& D
Outliers, 极端值
. g$ x; j# r1 y# J! OOVERALS , 多组变量的非线性正规相关 * B9 d- g# h" N \
Overshoot, 迭代过度
3 u4 c# e& A3 s; b! W @# a2 p; cPaired design, 配对设计
5 ^/ D, k- G* d) jPaired sample, 配对样本
- @. v B, W7 jPairwise slopes, 成对斜率2 f9 \( W7 r( k8 p6 F
Parabola, 抛物线5 f, F9 g/ R+ J' f$ v
Parallel tests, 平行试验
* ~8 `& I: e. xParameter, 参数
" Z$ R, [0 c$ y \Parametric statistics, 参数统计' C7 W! c$ I. a! s; {+ Z- R _+ Q
Parametric test, 参数检验' u2 a9 O. A4 t3 b* L; `; Q. U
Partial correlation, 偏相关) O: a. Y' ^6 w7 e1 p M
Partial regression, 偏回归
3 v) G- r) K/ A# T& }9 EPartial sorting, 偏排序. Y9 i% n. H5 S" G3 |3 [
Partials residuals, 偏残差
% Q2 v" t+ Z9 ^Pattern, 模式
/ [8 [$ g4 S7 H+ n! B: r0 xPearson curves, 皮尔逊曲线0 `& p1 Q: _2 `% w
Peeling, 退层. O. G( A/ b ]" _1 T( q7 u- f
Percent bar graph, 百分条形图" K' y* ?0 |" r k( ?. C
Percentage, 百分比) \ ` G7 n; f4 P
Percentile, 百分位数
; Z, ?9 S; d" L) X( r1 x& kPercentile curves, 百分位曲线
6 k( n) K, D" I6 u" g' ^Periodicity, 周期性% W" ?7 n1 D4 P% J% H, y5 N
Permutation, 排列
5 e8 |$ {* d3 ]2 z$ }, T `$ G. @P-estimator, P估计量
( W+ b, T2 z' c. |- p2 vPie graph, 饼图
0 i% O. ^2 K4 gPitman estimator, 皮特曼估计量
- f Q7 F* F; P- n) uPivot, 枢轴量7 j( a- f0 W; B
Planar, 平坦
! |8 o @! d% V3 \6 ~7 t. EPlanar assumption, 平面的假设
9 R4 K5 W+ {8 c& O- S2 S v y3 xPLANCARDS, 生成试验的计划卡
9 n1 ?, }5 b( t! z& [7 VPoint estimation, 点估计! I9 \+ U6 d; s4 j( W) I0 e5 Q( [
Poisson distribution, 泊松分布
% U( K/ v9 a; H+ x0 h! OPolishing, 平滑
: ^% U8 W% M4 j$ K7 ~Polled standard deviation, 合并标准差: I6 b' H6 S _3 c, R& B9 e
Polled variance, 合并方差2 R" C% y4 N: g5 d' R0 `
Polygon, 多边图
k5 d' M2 B3 }) v" kPolynomial, 多项式
. G3 \3 y" L& F# ~0 nPolynomial curve, 多项式曲线
4 i! z$ G% V5 @0 o" H. yPopulation, 总体
; G+ u: Y- F+ }- T9 v1 G8 gPopulation attributable risk, 人群归因危险度
% ^+ E+ t$ d1 @/ s8 K8 U$ H- n, fPositive correlation, 正相关
2 c/ F* @6 t5 n9 @7 ]; {Positively skewed, 正偏
( ]1 r% R" L4 c8 o) tPosterior distribution, 后验分布7 ~1 K8 n# c' S% I
Power of a test, 检验效能% p; p' w' E; L8 b, h% n. [8 o
Precision, 精密度
- x% S1 C, H; s( b/ |Predicted value, 预测值& l' t& l3 V* e: K5 T9 R
Preliminary analysis, 预备性分析9 e& K5 v" \7 \% M3 O5 M
Principal component analysis, 主成分分析6 P* V( }, @8 a4 X' X
Prior distribution, 先验分布
9 {! d. G* T4 \$ k6 N8 M6 v. PPrior probability, 先验概率
+ C& f9 ^0 ]5 Q/ T6 {1 qProbabilistic model, 概率模型
# ?5 H! r" Q7 a$ nprobability, 概率
% |& {: A' c3 W, |8 k9 W# kProbability density, 概率密度
3 F( A& d4 F- @' F" H4 eProduct moment, 乘积矩/协方差
2 s! X* s! F$ Z5 m6 G6 `3 y+ kProfile trace, 截面迹图
5 T( {/ I( r/ t/ `9 p+ N5 F& g# L- E& nProportion, 比/构成比; S. u8 W6 E8 S
Proportion allocation in stratified random sampling, 按比例分层随机抽样
5 d* W0 c* _. `- eProportionate, 成比例# f! P. \2 J' C: z1 _9 e; Z3 U( |9 c
Proportionate sub-class numbers, 成比例次级组含量3 V1 G& r9 \, @9 a+ Q( }' g
Prospective study, 前瞻性调查% b0 L5 `5 m V; ~- H7 d
Proximities, 亲近性 % {9 h7 ~4 c( J! s8 l6 M! p
Pseudo F test, 近似F检验- y* |0 x# o- c; d! A4 K" C
Pseudo model, 近似模型
: H, v: s/ U( K' ^2 `- V8 bPseudosigma, 伪标准差
( N* T5 t/ q9 u, ]Purposive sampling, 有目的抽样
; a6 \4 z; a! {; |QR decomposition, QR分解
1 N& p3 a) S4 F {7 `) IQuadratic approximation, 二次近似, d; k& E' K) m
Qualitative classification, 属性分类
; r9 P' a6 u1 {9 f* B7 vQualitative method, 定性方法
0 ?! ^ |! Y4 k2 u0 xQuantile-quantile plot, 分位数-分位数图/Q-Q图/ a, \1 c+ b* s) x7 z' ]$ B
Quantitative analysis, 定量分析 T) B3 n2 F, W- ^8 k6 z
Quartile, 四分位数
3 n' I, c" n9 ? gQuick Cluster, 快速聚类
( ?1 p( E8 k" f1 J# f9 G1 VRadix sort, 基数排序' N$ U5 b7 p% k- t
Random allocation, 随机化分组
% g2 D5 b2 r% I" j4 KRandom blocks design, 随机区组设计
" t: y- V U% h @) v2 C$ v' o$ GRandom event, 随机事件
. m4 W* {5 W5 N3 QRandomization, 随机化
1 G! U; q5 T# ~ g0 u0 z: O# _Range, 极差/全距& x9 b. F1 V& n) A, L) j
Rank correlation, 等级相关
( r& ]9 H z" K7 b- X. R F8 KRank sum test, 秩和检验
; k$ }" S# M4 i p9 T3 KRank test, 秩检验 B3 @6 _/ ~2 s' S9 ?
Ranked data, 等级资料
5 I5 N' \" v/ U( ]' A& M# J9 NRate, 比率
. P4 i% J7 o. i2 j! z- x* G& k. CRatio, 比例
9 S7 S. E) `. g& lRaw data, 原始资料
' N: ^% n* W) v/ Z3 @0 SRaw residual, 原始残差2 z. a$ I. S. M8 P5 U1 C) K
Rayleigh's test, 雷氏检验
1 K2 N, g; l' p: t+ C. F. \Rayleigh's Z, 雷氏Z值 : O8 e" Q7 n; P5 n5 g, ^
Reciprocal, 倒数! E3 z1 h+ D9 g3 i
Reciprocal transformation, 倒数变换$ E6 z+ g/ v" ]3 G' V& q
Recording, 记录2 b* }) G2 u }6 a
Redescending estimators, 回降估计量
; Q6 U& B. n$ v. ?3 I" HReducing dimensions, 降维
: M) D9 o% V4 c6 P+ b5 KRe-expression, 重新表达4 O1 [' _+ `& t2 @' Z
Reference set, 标准组
2 {& w+ ]$ w. B; w1 J5 v: Q1 ~" ARegion of acceptance, 接受域7 J% `& w8 Q$ S; U" b( S+ C
Regression coefficient, 回归系数
0 e/ b3 J6 H& r" M" Y, n! i3 MRegression sum of square, 回归平方和
6 u/ t" V- H1 Y% c" W0 [Rejection point, 拒绝点1 u+ ~2 u/ |/ E& ]5 p1 L/ W7 l
Relative dispersion, 相对离散度
; g% |& z" B$ n/ h4 r! qRelative number, 相对数
9 J! Y% K- W4 w0 A4 _Reliability, 可靠性
% n" Q# r, a% U3 BReparametrization, 重新设置参数0 q# z& R( a2 ]: f/ K5 k8 R
Replication, 重复& X# i( ]8 Z& J8 T3 T9 w u+ W* i. m
Report Summaries, 报告摘要
; _3 {& j' _3 K* T6 {$ w; q0 XResidual sum of square, 剩余平方和
\+ P8 c1 i* ^6 OResistance, 耐抗性
& T, E7 Q: N( K! @, }; ?, G( vResistant line, 耐抗线3 b8 {- u9 ~% p' q* }: g
Resistant technique, 耐抗技术3 f+ b& D$ [, C0 f8 n; B: l
R-estimator of location, 位置R估计量
* o1 a% J! x' YR-estimator of scale, 尺度R估计量
1 b" M0 O8 c$ B6 \2 f- z5 {* z3 KRetrospective study, 回顾性调查5 p% i7 O$ v! P, J! u
Ridge trace, 岭迹- V8 ~# A2 G- v- R% W' H
Ridit analysis, Ridit分析# h1 ]0 I8 Z" Y. r
Rotation, 旋转
2 i( E- E4 O) P) Q. q/ _Rounding, 舍入
' F! a7 F# f2 s9 Y, `+ j- c4 VRow, 行* G: v/ D F* `
Row effects, 行效应. @$ i) H& j9 r+ W: r6 e+ {
Row factor, 行因素
" L: j7 o, q8 j" t0 |$ ]. H vRXC table, RXC表
7 q+ O! V' F1 M; I7 z0 {Sample, 样本
8 O4 \0 [/ K8 d0 [+ D/ XSample regression coefficient, 样本回归系数5 \* ~$ u4 h! C7 n, A
Sample size, 样本量- }' z: ]5 \. n- `/ ^1 W X) U# X
Sample standard deviation, 样本标准差4 \1 ^0 L! n+ f" t B; n
Sampling error, 抽样误差. r/ R5 Q+ m) G# H% J
SAS(Statistical analysis system ), SAS统计软件包
$ @1 B2 u, I, i+ q: Y2 |+ q QScale, 尺度/量表+ ~. z8 D$ s/ \% W5 u0 r' f" }
Scatter diagram, 散点图
5 a1 Z' q& q& xSchematic plot, 示意图/简图3 ?% t- [0 D. H7 f7 w' ]
Score test, 计分检验& y& ]: J# T4 h' O) n
Screening, 筛检
4 Z+ v }4 L+ c9 O$ S0 CSEASON, 季节分析
5 _7 D' a" `1 J; _2 DSecond derivative, 二阶导数
2 y( J- ~& H4 I- e! iSecond principal component, 第二主成分2 P. f/ P) J! f- F$ p
SEM (Structural equation modeling), 结构化方程模型 ; d8 d% V$ R7 ?
Semi-logarithmic graph, 半对数图
% K5 q. v: [6 }7 q( m+ c" }* SSemi-logarithmic paper, 半对数格纸2 Z, E6 t! n# P( k; v" k" n
Sensitivity curve, 敏感度曲线
7 T( p c2 Z+ h: G: J; Z3 fSequential analysis, 贯序分析, O& u# s9 L& }
Sequential data set, 顺序数据集
5 d2 K8 ]/ F nSequential design, 贯序设计. b( }( k0 H. y2 W4 L/ W2 K
Sequential method, 贯序法9 Y* i5 p* u t4 [& k5 j
Sequential test, 贯序检验法
- Y" r7 i& Q; W2 a5 e3 y; [Serial tests, 系列试验
/ E- T% R8 c) X0 @Short-cut method, 简捷法 9 {4 d* p$ M g" y! Q
Sigmoid curve, S形曲线
$ @1 o- D% n! v- V3 j$ m7 a+ PSign function, 正负号函数" I3 n) }1 g# P
Sign test, 符号检验, P; c2 w4 B* N6 q7 K- q
Signed rank, 符号秩+ X4 c# G1 O5 _4 p, s
Significance test, 显著性检验
1 }# o/ f- l1 `' ~+ WSignificant figure, 有效数字
( u4 z3 k! B, q8 [0 z aSimple cluster sampling, 简单整群抽样6 B7 z- D: D9 w% z
Simple correlation, 简单相关9 q' u I7 I& \# T$ r' A
Simple random sampling, 简单随机抽样
2 J7 ]0 J1 B% {( r* eSimple regression, 简单回归
- z7 k- p- l( s8 ^. l" L' o; R- asimple table, 简单表
7 p! L# A( h2 k* Q3 y9 f" CSine estimator, 正弦估计量* x5 l* b/ x7 o2 I; C
Single-valued estimate, 单值估计
8 Y1 C0 h5 y& `$ [" }8 O% {Singular matrix, 奇异矩阵1 w9 |8 g# L' o; R
Skewed distribution, 偏斜分布
9 u) X3 z' T# [* a; U- y/ }Skewness, 偏度7 h- q' Y( A' F& M/ m
Slash distribution, 斜线分布
9 s! v# V3 o& I' O- J) h7 USlope, 斜率
1 z F D" g" t% `Smirnov test, 斯米尔诺夫检验
% K- a. }' S7 R$ kSource of variation, 变异来源; H/ B. I' {$ C, h g) |0 r& M, h
Spearman rank correlation, 斯皮尔曼等级相关
* ]7 N+ G, l& n) J+ `6 S8 ZSpecific factor, 特殊因子
; B; [; ^4 z/ _" e Z5 Y, _# uSpecific factor variance, 特殊因子方差
% @0 g5 H5 h$ VSpectra , 频谱" B7 P$ Y. x% l" d1 |# ?3 g0 v3 F
Spherical distribution, 球型正态分布+ b+ V x& k w* g
Spread, 展布, @% Y2 @) R! ~2 T8 N- s+ U1 X1 |
SPSS(Statistical package for the social science), SPSS统计软件包
# P D/ L8 @. k9 {Spurious correlation, 假性相关; R/ E! X$ g, b( p
Square root transformation, 平方根变换
( K" i0 w# f8 I6 S$ e* SStabilizing variance, 稳定方差
2 s. x5 T! z4 zStandard deviation, 标准差
1 B/ E$ V5 V; a% }( J! d5 ]2 wStandard error, 标准误
2 N: C8 w! f0 Q0 P' JStandard error of difference, 差别的标准误
7 k0 o% c" i$ Z DStandard error of estimate, 标准估计误差; f8 _! e3 _3 N
Standard error of rate, 率的标准误
" K$ A/ w% Q. C4 |' [6 t# HStandard normal distribution, 标准正态分布
" g% ?! V7 N* b3 s% ^Standardization, 标准化( n% v8 R( m# L9 U
Starting value, 起始值
$ O! l9 _$ \% y: g. `; p/ ^2 e5 I' vStatistic, 统计量& F3 w5 F$ Q/ r% H2 }0 \# D, |
Statistical control, 统计控制/ Y: W! \% I$ `; \* v3 `) o6 k5 F* b4 q
Statistical graph, 统计图
3 b9 G* ^* b) b. t' s8 F. JStatistical inference, 统计推断 H* [! t: d# A* ]% C, P
Statistical table, 统计表
' j; l$ k% |7 |. o; s8 ESteepest descent, 最速下降法
( f v7 }3 {# q9 Y5 b( @Stem and leaf display, 茎叶图
3 `# K1 h4 G4 s) h; ~5 H. ^Step factor, 步长因子. A/ |( t* O) Q& j
Stepwise regression, 逐步回归
! n4 t+ I; ]8 P' |% V1 Y' s/ L( PStorage, 存
9 w% y5 g! I% e' wStrata, 层（复数）
; d( i5 g* Z3 e/ i3 W$ d$ ?Stratified sampling, 分层抽样
4 S% }* q0 R1 aStratified sampling, 分层抽样, n& |+ o1 N2 r( O
Strength, 强度
+ m# h/ M! q3 F; |' cStringency, 严密性7 l9 n1 _" D3 c
Structural relationship, 结构关系9 R6 l+ Y7 q% y! z0 {
Studentized residual, 学生化残差/t化残差! c# k& I$ R. ] S
Sub-class numbers, 次级组含量
) |+ _2 j! \1 w$ @& s' ESubdividing, 分割
' v+ R8 T/ K, r1 ?. i& Q& P) `' _Sufficient statistic, 充分统计量
# _! L( u) a0 I& R jSum of products, 积和
B3 `* \5 {' @; qSum of squares, 离差平方和) \! f7 q7 R, n# \( W8 b! d' h
Sum of squares about regression, 回归平方和
& U+ q# ~4 ^( N1 A, TSum of squares between groups, 组间平方和
- Z3 X2 {( q# [1 s) X% [Sum of squares of partial regression, 偏回归平方和
" q& x9 y' d! s& kSure event, 必然事件
4 q; }" ^$ N* _! T1 N7 I$ K4 QSurvey, 调查( M- i% X" Z( V) E! K7 U) ?7 V
Survival, 生存分析& D, M+ J" R* P5 J8 d4 k% y. E+ |
Survival rate, 生存率
# W$ _( l9 u2 L, p$ a4 S7 M+ dSuspended root gram, 悬吊根图: M3 p6 `; ^2 b
Symmetry, 对称" y, o/ U9 j: L+ R
Systematic error, 系统误差
6 r; u9 T9 S! a% n* TSystematic sampling, 系统抽样
- }# z! o' Q' P& N, YTags, 标签
5 w% z- ?/ U& @ [9 j6 V& `3 {Tail area, 尾部面积
/ C8 E- ^/ H r3 m2 `Tail length, 尾长
* N5 o1 V6 x6 O) p O: [1 V4 ?Tail weight, 尾重
3 K* T7 d* s7 X4 b1 | ?Tangent line, 切线6 h# A- z f: T
Target distribution, 目标分布
5 }3 n; q2 k4 h" t6 \, {3 FTaylor series, 泰勒级数) j) N' f6 I4 c7 m
Tendency of dispersion, 离散趋势* z6 a9 o; q( _1 _! [0 c* o( ?
Testing of hypotheses, 假设检验# k; D( }1 j! s5 ^% {1 T* |% s+ J
Theoretical frequency, 理论频数- ? f8 b& d, Y, D; U/ m" w9 i- h
Time series, 时间序列
m, S+ P ?1 t* s8 {8 |- gTolerance interval, 容忍区间
5 q% A0 X7 J1 g5 G" H2 X. [Tolerance lower limit, 容忍下限
9 g6 P3 h8 D/ I( O" ?Tolerance upper limit, 容忍上限) c/ B" o/ `! Q7 E7 J: T4 {" C
Torsion, 扰率$ g% R" E6 m* T- l& ^- S3 \+ ~9 R
Total sum of square, 总平方和
8 B% N/ C5 l% i& h# a8 `2 O! K6 P" bTotal variation, 总变异
s5 D( O: U1 ?3 [ I$ FTransformation, 转换! a/ G# G3 U! k" H
Treatment, 处理
* l- P, L/ a; H' L! ETrend, 趋势. K% n$ j! A3 d" G7 v2 i8 m
Trend of percentage, 百分比趋势
. ?. ]( e& t7 A- k% {Trial, 试验( F% B/ }8 Z3 w4 U
Trial and error method, 试错法& @8 \) b9 n. b$ `
Tuning constant, 细调常数
' J+ j, n6 t. q* o& F4 N \Two sided test, 双向检验
/ I$ c( w' J7 l7 [* D! f9 v6 mTwo-stage least squares, 二阶最小平方
% R9 B- @4 l* t+ ?Two-stage sampling, 二阶段抽样/ p- y9 d& _, @1 S! r* ?
Two-tailed test, 双侧检验5 x! D6 J# E6 Q% z* k/ `2 v
Two-way analysis of variance, 双因素方差分析& d' b" q. S; k4 ]; B, o! f
Two-way table, 双向表
9 H4 L$ _. |, ~Type I error, 一类错误/α错误$ d8 g8 r! Y6 ?
Type II error, 二类错误/β错误4 ]. R+ l. r- @2 H
UMVU, 方差一致最小无偏估计简称
- i' X% b+ ?0 [& uUnbiased estimate, 无偏估计3 D6 b8 |" B T. F1 D7 O7 U
Unconstrained nonlinear regression , 无约束非线性回归
& N, D+ X8 D0 T9 O$ [( g4 `- HUnequal subclass number, 不等次级组含量
6 J6 m2 K9 H) m/ VUngrouped data, 不分组资料, l0 b3 R) a$ R5 u2 p
Uniform coordinate, 均匀坐标: \9 i6 {$ @1 a8 R7 G
Uniform distribution, 均匀分布6 k7 M* M4 A3 K) o. @
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
+ `/ ]* Z. \: K* B7 x6 Z. P Q7 wUnit, 单元
; r& U- k4 q# T& Z5 ^. KUnordered categories, 无序分类& X- v3 ~- P8 A5 `
Upper limit, 上限2 P" z4 Q: e: w+ I
Upward rank, 升秩
7 N( ?/ U4 l: Y# q) S: R; y* }Vague concept, 模糊概念6 O) V( l6 U# g. h& u/ ^6 c# b% o* x
Validity, 有效性
$ o; z$ \; s( o4 ]; W" mVARCOMP (Variance component estimation), 方差元素估计
. a1 s$ a" I L3 w6 V$ qVariability, 变异性
8 R) z& S: J4 j7 u- DVariable, 变量- ^! t! X$ n7 A: D: C* E
Variance, 方差, H" h7 k9 h9 n& D
Variation, 变异0 ]! n7 M, l1 p* T/ c8 y0 j+ i6 s
Varimax orthogonal rotation, 方差最大正交旋转
% w4 S) y' B1 l9 WVolume of distribution, 容积
9 ?/ i0 Z/ `/ Z- |, Z" EW test, W检验* W, `$ @) w! r
Weibull distribution, 威布尔分布' g2 D+ Z0 k8 s: Z9 T% n* Q
Weight, 权数
& \0 N9 }) b/ ?/ c% lWeighted Chi-square test, 加权卡方检验/Cochran检验
9 g6 ^: n) @: X, uWeighted linear regression method, 加权直线回归
e: Z+ }% _9 T; m5 wWeighted mean, 加权平均数
8 K+ _% u; z+ \1 N( @: x' Z- bWeighted mean square, 加权平均方差
, T; i! f; A$ B bWeighted sum of square, 加权平方和" _2 G) T1 B1 k
Weighting coefficient, 权重系数
7 C% h" b X/ o/ BWeighting method, 加权法
; U+ f( d6 a9 I6 _6 B& D2 ^1 eW-estimation, W估计量" q7 P% H3 f/ x ~. l- _+ H
W-estimation of location, 位置W估计量
; P7 |2 Y, F/ q/ i% MWidth, 宽度
1 s8 N/ {3 ], PWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
- L" j" B) p0 z ?. D0 w# ZWild point, 野点/狂点7 j8 {( s$ p" v$ S* ]+ ]
Wild value, 野值/狂值& i, t$ e2 B: ~! U( ^( u* ^3 R
Winsorized mean, 缩尾均值4 C4 o5 w$ ~. [7 ^
Withdraw, 失访
/ E |% i- w' k6 c8 Y* k8 dYouden's index, 尤登指数
@- M/ ?4 N+ K. j% }* x# y/ T7 d+ y# HZ test, Z检验$ B, d# R$ p9 k7 W) {7 v
Zero correlation, 零相关
& o `! T% E7 q. o5 jZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
