|
|
Absolute deviation, 绝对离差
' _9 C/ q) G1 D4 f' i9 W d8 O* |Absolute number, 绝对数
( o% A) r2 w/ n0 j% X7 [1 d( QAbsolute residuals, 绝对残差: Y/ F7 j3 ?8 p& I$ u$ ]/ r7 B7 ]" Q, U
Acceleration array, 加速度立体阵
1 i+ Y1 s7 C: S: zAcceleration in an arbitrary direction, 任意方向上的加速度! ^' o, o* N! y# o. b# f u
Acceleration normal, 法向加速度
r! E8 [/ Z; m2 o7 @! M5 y5 ]Acceleration space dimension, 加速度空间的维数
5 v" K! C; M' P. O8 f! v$ ]& |* i. u+ jAcceleration tangential, 切向加速度4 i! G8 ^# n8 p3 U+ U: D& r/ k N
Acceleration vector, 加速度向量
@6 O, o, m9 @3 \' C cAcceptable hypothesis, 可接受假设
0 E8 x6 @. t$ p: X+ `+ WAccumulation, 累积8 H' d8 V- _! B4 C3 X1 d, e
Accuracy, 准确度0 M* v. y2 R, G0 l- Q
Actual frequency, 实际频数, D1 \& U# c+ P
Adaptive estimator, 自适应估计量
+ b% b# O. W1 o/ w: B0 ^( WAddition, 相加
0 R4 J2 q- s5 y' a! vAddition theorem, 加法定理: ?' Z- ]7 j# F4 t7 X
Additivity, 可加性( |+ o0 S; T- ] ]7 g; X: S m% |
Adjusted rate, 调整率
3 w- b0 A% J& ZAdjusted value, 校正值
' W& {0 t# E' u0 t) Z& @Admissible error, 容许误差4 P4 O4 @6 s. V8 X+ W2 Y; s/ V( q ?+ p
Aggregation, 聚集性2 f6 |# |! A! u' p, Y* Z
Alternative hypothesis, 备择假设
* Q6 [# y+ x0 ?4 BAmong groups, 组间" e- t9 ]* N& {8 n% A
Amounts, 总量5 V! L4 T. t# k3 i3 l4 ?
Analysis of correlation, 相关分析
, t8 T/ ]$ f9 {- c, N" Y% d5 v% VAnalysis of covariance, 协方差分析
, ]$ x% w: v, f6 ] }5 VAnalysis of regression, 回归分析' L9 G! F" T: Y* s% O2 e
Analysis of time series, 时间序列分析3 Q! r$ E1 E8 D
Analysis of variance, 方差分析% e) h7 E2 {) Z
Angular transformation, 角转换
8 B; p' O* {+ m5 s, H( W' i8 sANOVA （analysis of variance）, 方差分析# L; Z3 h% _3 d& S
ANOVA Models, 方差分析模型% U1 L. p4 O- T* Z6 Q( ?0 d$ l9 v
Arcing, 弧/弧旋
$ \7 Y$ m- x! A- o7 f: oArcsine transformation, 反正弦变换. |+ u3 ?: |( y' J; D- l$ V
Area under the curve, 曲线面积
; ?0 z0 y& e3 q% c9 n5 R# SAREG , 评估从一个时间点到下一个时间点回归相关时的误差
B+ n [# q9 L Q7 zARIMA, 季节和非季节性单变量模型的极大似然估计
! A3 L- ^/ U2 ]Arithmetic grid paper, 算术格纸/ e$ ?9 n9 ]! G
Arithmetic mean, 算术平均数
: o: F) m, |/ p( w4 N3 uArrhenius relation, 艾恩尼斯关系# N+ Q2 `* R) O1 [( X) ^0 e& a
Assessing fit, 拟合的评估; N; |5 [; z ?3 H
Associative laws, 结合律
5 v) U. K# F( q( ~7 VAsymmetric distribution, 非对称分布
: B5 _; N# Z6 K0 G. P8 }4 qAsymptotic bias, 渐近偏倚7 w0 h2 a- D& b8 a h$ Z. }" O/ m
Asymptotic efficiency, 渐近效率
* M4 i5 \" u. G3 k7 r) O) ?: wAsymptotic variance, 渐近方差; q% l% s' ?& J
Attributable risk, 归因危险度
& I, `4 U7 n$ V8 u' U+ {Attribute data, 属性资料
0 {1 }% [$ d- ~; S* g. ] V. O OAttribution, 属性
0 e' J% |1 {0 D3 M/ dAutocorrelation, 自相关
9 `* K, r1 s: \4 f! eAutocorrelation of residuals, 残差的自相关, x3 i# q- ~2 u# `' H3 O
Average, 平均数4 Q) D( \4 z; q6 O/ Y
Average confidence interval length, 平均置信区间长度
+ Z$ L q3 v% e. B0 WAverage growth rate, 平均增长率+ v7 o0 L$ f; T$ z# O$ _
Bar chart, 条形图6 }+ y7 N2 {! s% Y+ {8 |: p& F
Bar graph, 条形图
8 T2 J/ ]6 o" C, o, F% ^7 j2 [Base period, 基期( t9 G% f9 M4 [: p( \# x
Bayes' theorem , Bayes定理
% y3 y3 n+ b# `Bell-shaped curve, 钟形曲线
$ V# n3 {7 p( y, i& Q5 mBernoulli distribution, 伯努力分布( X% H y0 F! i- C" T
Best-trim estimator, 最好切尾估计量6 Z& V! v! ^7 x2 X1 v
Bias, 偏性
# r5 Q3 I4 Q, W8 k6 A8 EBinary logistic regression, 二元逻辑斯蒂回归
8 p7 e+ l/ T2 T6 `4 g9 iBinomial distribution, 二项分布- D2 `( E! n5 Q( F" X. N
Bisquare, 双平方
E; K! x9 D9 IBivariate Correlate, 二变量相关
1 g2 O5 e4 b; q8 n3 {Bivariate normal distribution, 双变量正态分布4 S2 ^! f6 h/ |" w
Bivariate normal population, 双变量正态总体3 U3 I: b' W" ^) d. _7 r# U0 Y
Biweight interval, 双权区间
! ?& n' g+ I# d& _2 n4 d# DBiweight M-estimator, 双权M估计量
+ p' z/ {# G7 Z$ J. _" e* K! TBlock, 区组/配伍组9 `5 Y: s! t5 G8 \, M9 w
BMDP(Biomedical computer programs), BMDP统计软件包( q4 A: ~! v1 t. ~7 _
Boxplots, 箱线图/箱尾图* |( r: V6 L; v3 O/ l
Breakdown bound, 崩溃界/崩溃点# X4 ^1 }+ ]* L5 t. o
Canonical correlation, 典型相关, r6 L1 p8 i! C. v7 t! I! J
Caption, 纵标目( W5 C' I4 J4 v0 r" L9 j
Case-control study, 病例对照研究
/ x; K$ E/ U1 e' D5 r& R0 SCategorical variable, 分类变量
t/ b# [2 v6 v5 V+ y8 xCatenary, 悬链线
( Z1 A9 v$ N4 F/ HCauchy distribution, 柯西分布
8 B' V5 d8 I) Q+ XCause-and-effect relationship, 因果关系
# ~7 c" X, V- Q `Cell, 单元/ v, I5 P' P! H6 j4 W
Censoring, 终检
* b3 {% I* c. `& _* \Center of symmetry, 对称中心# a7 |( l5 U) n# T+ k1 h" D/ w1 u1 G
Centering and scaling, 中心化和定标
) ?2 w: X0 `( h$ K8 m HCentral tendency, 集中趋势
; @2 [% X1 W: \Central value, 中心值
; g6 }. Q3 i/ l6 PCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 S4 Z1 K: E% n( v# u7 U
Chance, 机遇
7 D& F, }5 [0 N* H3 I0 B# OChance error, 随机误差
% n s) Y: i+ ], \% l0 qChance variable, 随机变量
8 c1 F0 q1 H! ~) \. N, ]3 R9 A+ T8 wCharacteristic equation, 特征方程 V7 h% m. ~6 C* \9 M& R
Characteristic root, 特征根4 E M" e! F8 l& a o9 p
Characteristic vector, 特征向量
, r, \0 f2 s) t" @/ D0 C% ?Chebshev criterion of fit, 拟合的切比雪夫准则 {! H# z0 n/ u O
Chernoff faces, 切尔诺夫脸谱图
# a' w2 |1 d A0 rChi-square test, 卡方检验/χ2检验
$ v. Z, S" E6 W7 D) Q" Y! ECholeskey decomposition, 乔洛斯基分解
* h& }( J) M7 A$ rCircle chart, 圆图
* c7 O$ o1 o0 z- d7 nClass interval, 组距4 W* r' m0 g2 a p* y: ~: J
Class mid-value, 组中值
4 c) h2 P' m( |0 X. R( n* fClass upper limit, 组上限& ^4 n" X3 g+ t4 h& a% R5 J- Y9 E) W
Classified variable, 分类变量
, E; T: d {, @9 KCluster analysis, 聚类分析: l( @# _: V* t3 ~3 J
Cluster sampling, 整群抽样/ s) I$ D/ x" r
Code, 代码( s3 L: w" I7 v ^
Coded data, 编码数据
! M. u4 k; R: |0 lCoding, 编码
- U# F" L4 U3 ]/ | A$ Y' pCoefficient of contingency, 列联系数
" G( p+ j- X& n4 a- l8 [7 d0 H8 j" t* }Coefficient of determination, 决定系数9 D5 ?0 B2 M8 O+ F- k
Coefficient of multiple correlation, 多重相关系数
/ [ F$ ~) c$ s- ^& BCoefficient of partial correlation, 偏相关系数 U+ G) g: X$ s4 f7 @. @+ J8 Y
Coefficient of production-moment correlation, 积差相关系数( y8 F* g8 l7 {8 D8 G0 D
Coefficient of rank correlation, 等级相关系数
6 s$ M+ f) t# J; P3 D3 dCoefficient of regression, 回归系数 v- X# b4 @& C$ u
Coefficient of skewness, 偏度系数- ~: U* W' J9 l1 {; v9 O
Coefficient of variation, 变异系数( ^& z2 M, }2 f; T8 |
Cohort study, 队列研究
! W E9 U4 o8 U5 \Column, 列
3 i+ K$ u6 w, Q8 Y; nColumn effect, 列效应2 [# ?0 \7 ]# f1 p* z
Column factor, 列因素0 p2 i7 l- ]5 o4 H
Combination pool, 合并3 `9 x0 V. ]: F
Combinative table, 组合表# M; ]0 m$ h5 \/ q$ C$ k' n' M
Common factor, 共性因子
) }8 o6 V# R7 \- mCommon regression coefficient, 公共回归系数4 \/ e) f1 Z1 L2 l% E2 k, E! G
Common value, 共同值
( S! f) S! P( b9 l9 wCommon variance, 公共方差! X, ~) P ]" `: z
Common variation, 公共变异
2 P! [/ i$ o# X( ]6 g& A1 [: Y3 @Communality variance, 共性方差
1 h5 Y0 i5 m& L6 x" S: D, ? `. ]Comparability, 可比性2 a3 P! n/ B6 Q
Comparison of bathes, 批比较 d G* K: X W, `
Comparison value, 比较值* N0 p( r) d; X5 N T3 l
Compartment model, 分部模型& y P) z/ x& x, d6 b% k: _
Compassion, 伸缩
8 x6 e/ o8 z5 h! T7 A% GComplement of an event, 补事件
: ?, N: _7 i# `8 AComplete association, 完全正相关
5 R' F% I! ]6 q4 w+ o7 kComplete dissociation, 完全不相关" `$ y4 t9 U( y H3 Y
Complete statistics, 完备统计量, {! y+ ~5 E) J, d7 B: K
Completely randomized design, 完全随机化设计
8 \; k! O1 {) v- d0 C8 x1 A1 eComposite event, 联合事件- ?# G; X5 Z. U9 V! H2 i
Composite events, 复合事件% o/ ~/ n; F* ^
Concavity, 凹性
r3 Y9 L: W K: p( K- |2 w- U/ ^Conditional expectation, 条件期望
9 m+ f2 S& s' G0 ` q+ u" rConditional likelihood, 条件似然6 b9 T6 S A- g8 ~% [
Conditional probability, 条件概率
. `5 ?% V4 B4 B1 _Conditionally linear, 依条件线性* |7 i8 I% t! u$ \
Confidence interval, 置信区间& z! c+ q# }; n- R- u
Confidence limit, 置信限
8 n0 H$ V" {( g; S: b" X0 q5 `Confidence lower limit, 置信下限
' H) x- a* h: K1 t# N+ \9 ^Confidence upper limit, 置信上限
( I; C! t- ^+ nConfirmatory Factor Analysis , 验证性因子分析 f7 w& P. ? D" q" Y7 [
Confirmatory research, 证实性实验研究
# L" e: D4 e0 e/ |8 r1 `Confounding factor, 混杂因素
+ M1 Z( h d2 lConjoint, 联合分析" j+ e( C- J* ~6 I) u
Consistency, 相合性
# ]$ F p# J2 V0 ZConsistency check, 一致性检验
( S! S' i3 f% E* rConsistent asymptotically normal estimate, 相合渐近正态估计) {% y" ^5 d3 @/ `$ I' [6 \# o
Consistent estimate, 相合估计
: p9 Y" L* j9 gConstrained nonlinear regression, 受约束非线性回归5 I* ^* u& e0 c) y3 i6 e$ v
Constraint, 约束 B, J( `9 C; J/ e; \4 ]4 R9 a
Contaminated distribution, 污染分布! V: C7 j. @( u. V3 [, ^
Contaminated Gausssian, 污染高斯分布
6 M# o- n6 N+ e7 k2 OContaminated normal distribution, 污染正态分布& {( a0 Y& y3 v- m0 D
Contamination, 污染
9 P$ E+ ?$ \7 uContamination model, 污染模型9 L% a" H/ j7 K* \$ D# ]/ k
Contingency table, 列联表+ z a3 z% I. q3 \# Y
Contour, 边界线
+ v/ F% {6 D% }. l. O& TContribution rate, 贡献率
& }& a+ V1 ?0 f- z6 j, Q; E* ]9 T6 qControl, 对照
* o* g$ b8 e# ^1 ]3 H |' l9 xControlled experiments, 对照实验5 P& Y9 g* Q$ c" P' W3 M& G4 U
Conventional depth, 常规深度9 i6 a) A# J; V: \& O! V
Convolution, 卷积) @- ?3 h: t! Q
Corrected factor, 校正因子
7 Q; ~8 d' m9 @ aCorrected mean, 校正均值; V) x2 `5 d6 }/ U/ X
Correction coefficient, 校正系数
& M( |) t! n0 O6 D2 wCorrectness, 正确性
# a# k, t6 ?- o) b3 pCorrelation coefficient, 相关系数! b9 t+ ?$ s4 h% } d$ X( E" I
Correlation index, 相关指数* s/ y1 N# Q9 m# ?
Correspondence, 对应5 `$ o$ G/ p) e
Counting, 计数
a$ Q$ B% l* yCounts, 计数/频数& f" |! n d4 b) }1 T, Y
Covariance, 协方差
2 ~8 ]6 M* t6 {+ J( I, PCovariant, 共变
$ y# ]9 s6 s( n9 v; |; U6 F UCox Regression, Cox回归2 Z/ F2 m6 d- p6 r z) v' S7 M
Criteria for fitting, 拟合准则
5 |& H7 E2 [ PCriteria of least squares, 最小二乘准则8 g. l: |6 {+ ]
Critical ratio, 临界比( Q: ]* N! V1 @$ `% i4 ]7 |: G$ F
Critical region, 拒绝域
% ?; H* q. e, H3 |6 YCritical value, 临界值$ t7 P: J! t" ?+ B0 B5 I7 i: w7 O
Cross-over design, 交叉设计
B! g. p( U( Q8 S- J6 A, |Cross-section analysis, 横断面分析6 p4 M; X0 f( h0 L7 N
Cross-section survey, 横断面调查
* n1 x% z1 e, F. O! z N9 V& s7 rCrosstabs , 交叉表
. t, [" ]% m1 n6 ~5 l/ y! W: bCross-tabulation table, 复合表
, N( D1 [; r) `5 R4 h# z& oCube root, 立方根8 j+ Y6 j$ C# P- R- ]+ J
Cumulative distribution function, 分布函数; W! A; p! H l
Cumulative probability, 累计概率
+ d( |( e. A9 W3 y) V5 iCurvature, 曲率/弯曲
1 n# s8 b6 }9 A" P/ P* SCurvature, 曲率0 c" A* [8 q& k
Curve fit , 曲线拟和 0 W, W! v- q; J Q b$ B
Curve fitting, 曲线拟合, i" d; \7 T. r3 F$ P
Curvilinear regression, 曲线回归
1 s$ [, V- g1 U4 q3 c, V+ oCurvilinear relation, 曲线关系
* R$ Q% K! t* P; O3 F' P5 ]Cut-and-try method, 尝试法
) ~. R1 x* r- w/ N; `* dCycle, 周期 [$ C' u" l1 T6 K# f: P
Cyclist, 周期性
: @ v* M0 ]/ U! ^1 v0 m5 e! |D test, D检验4 c+ D& w( c, h; I4 G$ A0 e6 f3 \# J
Data acquisition, 资料收集. K' P6 {( X. G1 Y3 M9 l9 ^6 ~
Data bank, 数据库$ a) h, V! h$ L( x
Data capacity, 数据容量
8 c7 q$ n4 q, L% O0 fData deficiencies, 数据缺乏7 }% a9 t5 v- h# y. R5 t* t
Data handling, 数据处理) R$ R6 p+ d% @/ A( n/ @9 A8 W. V' p/ v
Data manipulation, 数据处理4 W) e8 h4 k5 E. V% R4 N- _! V
Data processing, 数据处理
$ U3 m( e7 } [" ^, rData reduction, 数据缩减' i3 w: F+ o% d2 g+ p8 T
Data set, 数据集( l5 p1 O; j5 H1 y! W: G
Data sources, 数据来源
7 L( o4 r5 t9 Y) g4 oData transformation, 数据变换1 H, m' t. P; I3 z/ d
Data validity, 数据有效性/ l8 M6 Y, O) ~6 u7 r0 a% H4 g
Data-in, 数据输入
4 n3 x3 ~% `8 \* f2 t; Q6 ]4 ZData-out, 数据输出
' m8 Q+ J( ]- R% q' \Dead time, 停滞期
; n/ i P. y' s& U' rDegree of freedom, 自由度, P0 Q0 e- ~+ v1 N5 C9 b7 @# [& M2 {
Degree of precision, 精密度
' R& ]& o4 C" h L Z, s EDegree of reliability, 可靠性程度6 ]" Q; t* V9 Q5 m
Degression, 递减
2 T. {) o3 I( Z# NDensity function, 密度函数8 l; A" b1 W5 x6 b
Density of data points, 数据点的密度
2 ?' x0 ^ I8 \5 YDependent variable, 应变量/依变量/因变量9 r/ [$ m' y9 {% c2 \, O- t
Dependent variable, 因变量* Z4 [8 W, Z8 b# B! Y6 F
Depth, 深度 H" u" P: }' Y7 p: F4 N
Derivative matrix, 导数矩阵
4 s# {- q2 X, a3 O& x9 Y0 Q3 v$ cDerivative-free methods, 无导数方法
7 Q4 Q- a0 i# l5 W0 g. B- uDesign, 设计
( _$ i0 @; N1 lDeterminacy, 确定性* @' f5 Z4 l4 \! y- x
Determinant, 行列式: T, A/ I- w6 O& S; _
Determinant, 决定因素
- C3 E4 L x C, B6 ZDeviation, 离差' z% i( a, d+ ]4 }- f% Y
Deviation from average, 离均差1 Z% g* w5 Z6 H3 c! i
Diagnostic plot, 诊断图
$ v0 Y6 G4 Q) h# X9 b5 @6 yDichotomous variable, 二分变量
; |# d. L R: D A" HDifferential equation, 微分方程
' s! I! {" }5 Q% ~6 M9 m% `Direct standardization, 直接标准化法. B: R2 _$ w1 T/ ]7 o
Discrete variable, 离散型变量" k$ Z8 C" b; K) j; m9 _ w4 R6 Q4 W
DISCRIMINANT, 判断
1 H; g5 _( Z7 t) Q0 mDiscriminant analysis, 判别分析
6 G4 M+ r# V0 `$ k5 uDiscriminant coefficient, 判别系数$ X# f9 b/ o" H# F: m- U
Discriminant function, 判别值
5 T, m J; `/ Q. P$ \Dispersion, 散布/分散度
$ y+ E( x5 K5 g/ D4 u2 {+ J* nDisproportional, 不成比例的
8 X- o& n9 L7 ?Disproportionate sub-class numbers, 不成比例次级组含量. ]' ^; C$ D; ? z
Distribution free, 分布无关性/免分布$ Q2 L. {! d& l/ U, z: Q$ M* Z: H8 a. ~
Distribution shape, 分布形状# k T$ e; ^ K) h
Distribution-free method, 任意分布法
- D. m% U! F# H8 ?Distributive laws, 分配律
7 z% A4 K; ^6 d# o3 j. pDisturbance, 随机扰动项1 z6 B5 I2 u6 T. G2 j3 e
Dose response curve, 剂量反应曲线) {/ B0 U7 E( c4 P# m b9 U
Double blind method, 双盲法
8 v7 n( w' q+ Z$ Y- sDouble blind trial, 双盲试验
! P# A8 \1 R3 s( O$ |3 RDouble exponential distribution, 双指数分布
2 B; v7 W3 V6 fDouble logarithmic, 双对数2 H; g2 h# I) ^: t$ ^% v N
Downward rank, 降秩
8 _5 y" \) {: O/ j$ pDual-space plot, 对偶空间图; g* x1 Y' w; G2 b( p; n
DUD, 无导数方法
9 P3 p, I; Y. c" `' c* v! A5 wDuncan's new multiple range method, 新复极差法/Duncan新法; m) F3 ]. P& w, `8 x8 J
Effect, 实验效应. |2 @6 @6 o) e
Eigenvalue, 特征值9 Z+ v( v& n" x6 b) b# ^
Eigenvector, 特征向量( e: w2 N1 S( g, T7 u6 Z7 b
Ellipse, 椭圆" f3 b3 D" C2 B$ c- m+ W
Empirical distribution, 经验分布
: A& z! S; r8 N% zEmpirical probability, 经验概率单位
) d' }$ z; C$ O- |+ \7 `# t bEnumeration data, 计数资料
; w1 K( E- |1 V) ^4 t1 i! iEqual sun-class number, 相等次级组含量
. k, _1 x* C+ d! {Equally likely, 等可能
& T Q& V" N( {* vEquivariance, 同变性' v- G" V5 M1 ~- k; x
Error, 误差/错误
' y. W2 {2 z, b e* d, y3 X$ nError of estimate, 估计误差' F$ Q7 x! G5 ~& s8 {
Error type I, 第一类错误
9 |: [* m' k7 p: GError type II, 第二类错误6 {% k. N% b# o7 m% c0 O& Z
Estimand, 被估量. z7 X/ g/ T) K" i9 ]9 |6 Q
Estimated error mean squares, 估计误差均方
: z/ z8 [ C% ^( q8 b) l" ~3 zEstimated error sum of squares, 估计误差平方和* f! X% D# w) ?( _: N2 B' n0 z; e) Q
Euclidean distance, 欧式距离
* q6 U2 R Z3 p; B7 _# W4 R5 lEvent, 事件
+ P. W, `2 j k. V9 u# WEvent, 事件. ^+ e8 P, H% A3 {8 w$ s
Exceptional data point, 异常数据点
3 F7 `# l0 M- \8 O& QExpectation plane, 期望平面' N- O- P7 B: S, d! @. K
Expectation surface, 期望曲面+ i! k8 I+ _& |2 S5 b V6 H& P
Expected values, 期望值
Y5 O5 h" F Z T3 kExperiment, 实验; ~7 h1 H1 {" a, j: e4 q% T, H
Experimental sampling, 试验抽样) J+ q# h' C# t" P7 Z( ?. e% q# U2 _
Experimental unit, 试验单位% {& M m* ?# T( E% c- T s, T. G. Y
Explanatory variable, 说明变量/ C8 }" U' R3 s4 @# _
Exploratory data analysis, 探索性数据分析1 c& `( w- i/ D+ Y
Explore Summarize, 探索-摘要/ Z) B; s5 `! t# F7 c5 U
Exponential curve, 指数曲线5 D) q" Y/ p* D' \$ A
Exponential growth, 指数式增长9 c; C( G l/ G
EXSMOOTH, 指数平滑方法 + Z0 S5 x5 z$ M; `
Extended fit, 扩充拟合$ n6 v9 Q6 \' S+ J: z# _! e5 S
Extra parameter, 附加参数
4 G* p: ?. X$ FExtrapolation, 外推法
( v) G0 o* L! B% A2 iExtreme observation, 末端观测值
: h) P, R8 t9 w( @; X1 BExtremes, 极端值/极值
* M, x! g3 K: Q; EF distribution, F分布* Y) I! X! W, }3 w
F test, F检验6 q _% P2 V/ u. l4 ^+ G
Factor, 因素/因子
- C- T# k$ l& I( {" _/ C0 H2 e* LFactor analysis, 因子分析
+ u# z5 }% Q0 b* S8 z# q+ ?/ SFactor Analysis, 因子分析, G! Z4 H5 o% p4 }4 p
Factor score, 因子得分
9 r) Y$ P! Q1 p) AFactorial, 阶乘! t0 F/ \& i; E0 j( X& S1 V. I
Factorial design, 析因试验设计/ O$ A6 |2 \5 d# J8 g: L7 a
False negative, 假阴性 T5 I/ U, P7 f8 P6 |$ c; s
False negative error, 假阴性错误6 C- d) M( {7 }! C4 H
Family of distributions, 分布族3 G V3 w4 Q {! B/ R
Family of estimators, 估计量族
% ?. N2 ^! ^" i3 n7 `4 UFanning, 扇面
: G ~/ \7 ~% A& M9 c1 ^, w3 ~Fatality rate, 病死率
3 |5 s! `3 z6 E8 QField investigation, 现场调查. ~ Z( `1 |8 m& i6 r$ Z% f
Field survey, 现场调查
- |2 g3 T) j2 T# ?Finite population, 有限总体
& J& v- I( \ h/ I( @Finite-sample, 有限样本! ^' C* e& K) R
First derivative, 一阶导数
' B' m. Y* G6 J; Q* bFirst principal component, 第一主成分
9 k. z! ^8 S. s1 ~" ^+ X0 s0 pFirst quartile, 第一四分位数4 M2 @: B: a; ?5 Y1 h9 V
Fisher information, 费雪信息量
- ?" ?- m2 d; p0 E+ F4 }$ t% H% tFitted value, 拟合值0 n4 X. M% J1 z5 s% w9 J: S
Fitting a curve, 曲线拟合6 J# [) _' V5 K* ]! P5 \! h0 f$ @
Fixed base, 定基9 f1 j" q+ B( r5 a
Fluctuation, 随机起伏% U& C' i/ f* h3 _* z- W9 u
Forecast, 预测
' G: t O6 T! y2 H9 ZFour fold table, 四格表
3 u+ v6 U" u* N. kFourth, 四分点
& o' |5 S& ] \3 D' TFraction blow, 左侧比率2 q/ N( O+ ?0 }% K* m
Fractional error, 相对误差
, A7 n2 a( C+ uFrequency, 频率/ v+ Z4 v9 n$ e/ G6 C5 y
Frequency polygon, 频数多边图% Q* a. G1 W& I: H# n
Frontier point, 界限点& W% F/ t' ^- ^) F0 J" X
Function relationship, 泛函关系
8 ^; x( d ]0 l: P) M1 QGamma distribution, 伽玛分布- z$ T5 p6 D$ t
Gauss increment, 高斯增量% q. J; \- h# R) L7 f
Gaussian distribution, 高斯分布/正态分布: n j& E. o' @* _( u1 j G
Gauss-Newton increment, 高斯-牛顿增量# o& u" I" v3 s4 e( R# `
General census, 全面普查
4 W$ J7 J+ d" F' w+ zGENLOG (Generalized liner models), 广义线性模型 ; E4 w& @6 B7 A% D& Y7 Y @
Geometric mean, 几何平均数$ F# D* B7 E8 Y
Gini's mean difference, 基尼均差/ t2 X" K9 n: y5 w, w# e) @; Y( z9 N
GLM (General liner models), 一般线性模型
; d% i& j$ L7 X3 o0 BGoodness of fit, 拟和优度/配合度
, s9 {& I, n2 k7 s0 X8 x4 wGradient of determinant, 行列式的梯度
* C8 l+ q- m. v. d1 lGraeco-Latin square, 希腊拉丁方
9 \: _5 K! p W2 z7 M3 {Grand mean, 总均值
* z+ L: B: E s! [' QGross errors, 重大错误
! R4 i) k) m {2 hGross-error sensitivity, 大错敏感度4 n* ~& x' D! z# |8 Y, ?' U: ?
Group averages, 分组平均& \( G& I& ?2 S$ |& N4 I
Grouped data, 分组资料
8 @$ S+ H! v3 y4 `# kGuessed mean, 假定平均数5 v/ H. V& s0 k8 K) n
Half-life, 半衰期
. x3 g m7 u/ A1 AHampel M-estimators, 汉佩尔M估计量
4 }9 m7 x; [( i4 |6 o& ]! K/ u9 I8 A+ HHappenstance, 偶然事件/ S7 L/ Z; j! C7 ^1 j
Harmonic mean, 调和均数
# V/ H' r! V2 `) P; ]Hazard function, 风险均数( q8 T$ Q7 @8 i( D
Hazard rate, 风险率$ F3 |# j) X* k" v6 t- F. ]2 S
Heading, 标目
6 u) C5 c4 j5 Z. y2 d0 s1 vHeavy-tailed distribution, 重尾分布
( a, n7 A3 J" Q; \- z7 ?Hessian array, 海森立体阵) |. G; p* y" o, w& x8 l5 b( o
Heterogeneity, 不同质& e( g. _3 @6 i, `
Heterogeneity of variance, 方差不齐 8 w; O) h; M* d
Hierarchical classification, 组内分组$ L5 b) G8 c. V8 c4 r! w
Hierarchical clustering method, 系统聚类法
- h a7 P9 M6 A1 R5 O& bHigh-leverage point, 高杠杆率点" p7 |( `/ [3 s* R$ W6 H
HILOGLINEAR, 多维列联表的层次对数线性模型
, b8 R' @7 S' fHinge, 折叶点
1 o0 b, h& t7 f) |. X' | w' t# IHistogram, 直方图5 ^% G) z, b) ?: T9 J% l# C6 ^
Historical cohort study, 历史性队列研究 2 T3 T5 e8 N' b* ]" b! i
Holes, 空洞
9 k& h/ |2 @- q. s T6 j6 @HOMALS, 多重响应分析
6 j5 s7 \! T9 JHomogeneity of variance, 方差齐性
" K) B; c7 R6 _3 K8 y2 NHomogeneity test, 齐性检验
$ Y. e6 R+ S( u# s( r. f- c( EHuber M-estimators, 休伯M估计量; d+ J3 [+ Q) \8 G [" ]
Hyperbola, 双曲线+ O# ]1 J6 K3 _: _$ y% v
Hypothesis testing, 假设检验
/ u) T: f+ M }% O% \Hypothetical universe, 假设总体
5 p/ |! ~* A& M9 S; T- l' C% [7 RImpossible event, 不可能事件
5 \& r0 P2 W4 g1 @* a) x0 gIndependence, 独立性3 g6 I; ] K* D" n) [
Independent variable, 自变量
" j. v( s9 g2 d$ B6 _/ l$ i- nIndex, 指标/指数6 y! ]0 q9 ^7 k4 f
Indirect standardization, 间接标准化法' T5 r# S: R0 l5 u
Individual, 个体- l* e8 n# z+ i( {/ P
Inference band, 推断带
% _; f; T, o$ j z) }Infinite population, 无限总体+ Z( m0 G. X) H. K! h" O- g" y+ n
Infinitely great, 无穷大# ~8 z: _% B I/ Q1 q
Infinitely small, 无穷小; ]: f: V- ~/ p1 O; z4 ?2 y6 b
Influence curve, 影响曲线
0 f5 t. N% p) rInformation capacity, 信息容量' g- g; J3 D4 T4 V2 a
Initial condition, 初始条件
, C8 I- q7 r5 q! n$ QInitial estimate, 初始估计值
, V2 Y8 R' S' M2 V' @1 `Initial level, 最初水平/ d: @# d$ u9 I C" h$ p7 R
Interaction, 交互作用
" ]; s) W1 u# U1 _- P( O6 BInteraction terms, 交互作用项
P9 p! Z/ f( O, i7 b8 [3 BIntercept, 截距/ M' ?% k- z. S) \* Y6 C6 ~. Y
Interpolation, 内插法% I& k7 J: B9 ]0 V( X
Interquartile range, 四分位距* N& J/ s* U4 s# D6 s- H1 F
Interval estimation, 区间估计
) U% I5 U1 o6 ], x W, W0 T* QIntervals of equal probability, 等概率区间
( f5 T+ X0 H4 nIntrinsic curvature, 固有曲率
# F& L% o3 d" W" T1 qInvariance, 不变性6 L' o1 W9 n2 L: }
Inverse matrix, 逆矩阵
# |) A" O. `$ e2 i1 B. \Inverse probability, 逆概率2 [) R4 P4 K0 ?4 B
Inverse sine transformation, 反正弦变换! J* g! X4 p8 P# R3 {/ r
Iteration, 迭代 2 u H* D$ }3 [ w! j: c/ F9 {
Jacobian determinant, 雅可比行列式# ?5 X6 r& u2 X* V ]
Joint distribution function, 分布函数
! F5 O4 P7 C1 UJoint probability, 联合概率
% ^0 r) N- q) B, |Joint probability distribution, 联合概率分布
! ]- ?6 d2 Z0 z5 `3 W2 W, u" ^2 dK means method, 逐步聚类法
5 r0 m+ q! E5 M& OKaplan-Meier, 评估事件的时间长度 9 O7 E% a. L% Q9 s' q
Kaplan-Merier chart, Kaplan-Merier图$ O3 f$ i$ e, i0 }3 m
Kendall's rank correlation, Kendall等级相关
7 |8 y5 T/ H1 f) d8 S' dKinetic, 动力学
+ {/ ]8 E3 p" l4 aKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验 Z9 \$ {+ p) ~* F. w. a
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
: p3 h* M! j8 ?Kurtosis, 峰度
' ?# J8 O9 i4 l6 fLack of fit, 失拟( \3 w# v" ~% g" R2 J
Ladder of powers, 幂阶梯
6 x( y; k0 K |, ^5 k& r) dLag, 滞后2 i. g4 d' _$ {2 K$ z* Q
Large sample, 大样本
, c. [1 V( b1 O _0 f& gLarge sample test, 大样本检验- v6 d1 n) Y( X) X
Latin square, 拉丁方/ n, _, L0 \. C4 x# [7 T) K7 |& V7 u
Latin square design, 拉丁方设计9 i" Z7 {& a' N( q. j
Leakage, 泄漏
. n, j' _1 f! y s0 @" T O! @: Q# sLeast favorable configuration, 最不利构形
/ a4 L6 c& }8 I# {/ BLeast favorable distribution, 最不利分布
8 w: m& C2 ?( C$ U( B vLeast significant difference, 最小显著差法
- W$ B n6 S8 g1 G# z7 VLeast square method, 最小二乘法
( _2 P6 D. p- e! R: R3 _Least-absolute-residuals estimates, 最小绝对残差估计
9 N. H- A) b- qLeast-absolute-residuals fit, 最小绝对残差拟合' h5 ?1 a" a* h0 p
Least-absolute-residuals line, 最小绝对残差线
# ]; v5 ^3 k( o1 ~! g7 WLegend, 图例8 t! `- q) _ M& x) U; C0 b
L-estimator, L估计量
- h0 u+ T2 t% \ X% CL-estimator of location, 位置L估计量
) N% w% Q. a8 @% RL-estimator of scale, 尺度L估计量
# a/ p% _, \1 L( t+ l! f' RLevel, 水平
. a0 m }3 F& k; w1 s: y9 `Life expectance, 预期期望寿命
; P4 c- ?8 P* |/ s- jLife table, 寿命表' Y! C2 f- N0 v* T) e- q
Life table method, 生命表法
- I0 _7 C% B VLight-tailed distribution, 轻尾分布
0 S- o5 A, P/ W, S- Y. PLikelihood function, 似然函数
3 D5 n B) l/ Q2 [Likelihood ratio, 似然比! k9 }0 O, [. Z( s: k/ g
line graph, 线图/ F9 T. ?1 \: i3 c) K
Linear correlation, 直线相关
1 X& C+ }; m+ H5 R' FLinear equation, 线性方程
; D M0 [' R4 \0 U- ?' e# BLinear programming, 线性规划" I2 e V: x1 P7 B" q
Linear regression, 直线回归
) O* b' _% C0 G5 o0 {Linear Regression, 线性回归3 y7 c& S/ `2 W& y9 \0 t# \# x
Linear trend, 线性趋势8 }# m$ G8 D& ^, P
Loading, 载荷 7 E) V0 t3 y; e, ?
Location and scale equivariance, 位置尺度同变性+ w' z* u1 J$ e" g
Location equivariance, 位置同变性- }2 n- d+ `" w& {4 z' F0 h6 q
Location invariance, 位置不变性
7 Y& R w8 n A& ?: ^& dLocation scale family, 位置尺度族3 R9 C. [3 s4 t+ p
Log rank test, 时序检验
5 @0 J+ W V7 m3 n1 a* lLogarithmic curve, 对数曲线- z9 i/ \, Z" X/ v
Logarithmic normal distribution, 对数正态分布5 [& k3 L$ S$ ~5 S& b
Logarithmic scale, 对数尺度+ N* n* w( b% d+ E/ \0 w( c \
Logarithmic transformation, 对数变换+ D1 C6 k: P( k. Z2 W7 d
Logic check, 逻辑检查
" G: Y+ S* Z' E, T) s0 hLogistic distribution, 逻辑斯特分布& B3 Z- W; \+ p' t0 _
Logit transformation, Logit转换4 |# S2 e& K" h
LOGLINEAR, 多维列联表通用模型
7 k2 r! K$ A# {$ wLognormal distribution, 对数正态分布9 O% q) f8 L8 ^
Lost function, 损失函数7 p. v! _+ F2 y; m$ n3 Z' J
Low correlation, 低度相关 S5 T" ?/ J" V: @# ]" E& n. `3 ]+ T& B
Lower limit, 下限$ d8 I4 U2 m3 A* e: c
Lowest-attained variance, 最小可达方差3 | I" W; q# e( ^: @
LSD, 最小显著差法的简称
. c* d* n0 o. C) ^6 _Lurking variable, 潜在变量
H8 x9 {3 k6 B- MMain effect, 主效应3 h7 J3 t9 A! x8 z
Major heading, 主辞标目
1 W5 p+ F! y9 P/ A6 A* ?$ i* m4 VMarginal density function, 边缘密度函数
/ i! J2 Y! e( a) a9 GMarginal probability, 边缘概率
/ l0 _. `( ^ o& c" ?Marginal probability distribution, 边缘概率分布
- G( ]3 L" x+ AMatched data, 配对资料
1 @' K+ g( g" C S ?) PMatched distribution, 匹配过分布( {3 ~% x/ [: U* \7 P
Matching of distribution, 分布的匹配! r; ^0 T! T6 {$ \; d
Matching of transformation, 变换的匹配
: g+ Y. W1 u) |/ @) S8 w. B. aMathematical expectation, 数学期望
7 G( J6 o1 R4 A$ ?' AMathematical model, 数学模型
3 W! R# f9 u$ G8 V. gMaximum L-estimator, 极大极小L 估计量
: x- }( y9 a4 f3 ~8 L4 c$ uMaximum likelihood method, 最大似然法1 O$ t9 R+ d* a p* m4 `4 m
Mean, 均数
* F$ J+ p, u; ~% I* [+ sMean squares between groups, 组间均方2 p; F0 D' J- r: O8 C
Mean squares within group, 组内均方
, }: X0 F- l9 ?; [& c1 g F# ?) oMeans (Compare means), 均值-均值比较2 ~7 _! g- J$ ]& ^1 m( C; x P
Median, 中位数
! P- B ~7 x; J' c- {8 SMedian effective dose, 半数效量' ?! E' N% G& O R Y
Median lethal dose, 半数致死量+ [) z$ K* @# v. J2 ?: D# B
Median polish, 中位数平滑
8 T' g, e6 v' t/ I: F+ x# _7 PMedian test, 中位数检验
* Q( M; ~0 o6 y9 l5 {( IMinimal sufficient statistic, 最小充分统计量1 J d/ O5 m" u- ?* h2 i
Minimum distance estimation, 最小距离估计8 ^: w& u9 Y3 f. z$ S& Y
Minimum effective dose, 最小有效量
& U5 X" a3 p: `Minimum lethal dose, 最小致死量
) O& P* a+ ~0 e- x, ?( q) i/ G. pMinimum variance estimator, 最小方差估计量
2 h0 N6 z- l5 p" y* I4 X: c4 AMINITAB, 统计软件包4 Z7 e' I* l" _, z: X; _8 n
Minor heading, 宾词标目1 Y4 I1 w2 ^- v6 F' {5 k3 r
Missing data, 缺失值
1 w, f- x9 N9 `" D1 ZModel specification, 模型的确定
- c# d, {0 G" o4 V% q: VModeling Statistics , 模型统计
$ Y6 L: R& `, _$ H% O: B6 {Models for outliers, 离群值模型
; j8 X- M K( S; T4 c! |7 E9 v ^Modifying the model, 模型的修正2 Z l4 S6 k! D7 o# k
Modulus of continuity, 连续性模2 T8 Y) M& E& E2 t9 i9 C* x
Morbidity, 发病率 * Q) X. ]/ { [' e2 Z% d
Most favorable configuration, 最有利构形
" g k. _; F) QMultidimensional Scaling (ASCAL), 多维尺度/多维标度
- Y( y- f' Y X* b; }Multinomial Logistic Regression , 多项逻辑斯蒂回归
, _2 |# ~* G* KMultiple comparison, 多重比较$ P7 ~4 q8 j$ D @% _) K
Multiple correlation , 复相关
/ c* j7 ^/ G0 R2 R# q& S2 vMultiple covariance, 多元协方差# |0 u" q7 i0 l# y4 M' S$ v: |
Multiple linear regression, 多元线性回归
, e9 Z6 v# c( ?7 c' r% ~0 R4 NMultiple response , 多重选项
( ^; L& J, `- q1 p. aMultiple solutions, 多解& g! u( d( j" e' T/ r+ x l5 B
Multiplication theorem, 乘法定理
' ^2 o: l+ U9 U7 } M! A" BMultiresponse, 多元响应
+ s7 t& w9 \1 A; s5 F, NMulti-stage sampling, 多阶段抽样
) X' }* {8 W! T* ZMultivariate T distribution, 多元T分布
. @4 v6 k& X, p9 Z8 d* jMutual exclusive, 互不相容
$ e; e6 v1 X2 B2 s8 V/ ^Mutual independence, 互相独立& V5 R7 U! K) d
Natural boundary, 自然边界
4 _6 p) A, o! }+ f2 ~, GNatural dead, 自然死亡
+ z) _1 h7 ]/ B5 t1 u, ZNatural zero, 自然零
/ Y" b- ^/ M. K, p4 B/ P& k6 YNegative correlation, 负相关
' D" @: }" ?0 p% q1 G9 x; \. ^1 z2 WNegative linear correlation, 负线性相关( Y# r6 T2 h0 V; q! i6 f
Negatively skewed, 负偏: u9 J ]2 P A: v# m0 x. R
Newman-Keuls method, q检验
2 r& t! C# ~* Z& r% gNK method, q检验3 Z9 y4 M, x5 t9 T% L
No statistical significance, 无统计意义
' G4 P" G2 f2 N3 @4 wNominal variable, 名义变量
* W" D+ F0 B$ ~- k1 [1 P/ YNonconstancy of variability, 变异的非定常性8 K! |7 N& k; U$ |; S. A
Nonlinear regression, 非线性相关
' r: g; p9 _( c0 F, w, w/ a. O) \Nonparametric statistics, 非参数统计. i" i: O: J6 R; ]" D! a: W
Nonparametric test, 非参数检验, z4 h, j m, l a* X
Nonparametric tests, 非参数检验8 V% f5 u* H6 v0 U o0 `
Normal deviate, 正态离差
& f Y/ Q& H# t! l3 c/ rNormal distribution, 正态分布
1 K$ b$ Q2 B- ` h- w* d6 cNormal equation, 正规方程组
4 |% w" F' x V- D5 mNormal ranges, 正常范围) w o, H( W1 Z Y6 u5 n
Normal value, 正常值
$ J4 [! e6 ] E1 U6 VNuisance parameter, 多余参数/讨厌参数
0 E$ b8 m" B; N- HNull hypothesis, 无效假设 : k6 Y, v; F0 C3 ?$ S: s
Numerical variable, 数值变量
) c) \6 F! ?7 N- g4 p9 \Objective function, 目标函数
) O( q0 @) p. x; @# dObservation unit, 观察单位
" `+ S# U# i# E3 c% AObserved value, 观察值0 A. N' P3 @/ {% q9 _2 K. c
One sided test, 单侧检验
$ F1 c9 `; |& W2 F. L3 S' o1 @+ aOne-way analysis of variance, 单因素方差分析" L" ^* @- ?. K' f5 p
Oneway ANOVA , 单因素方差分析
* Y2 `$ z4 H7 ]6 Z3 qOpen sequential trial, 开放型序贯设计
- v7 ?8 g7 o9 W7 [$ ]' kOptrim, 优切尾6 [8 b C7 B W3 w
Optrim efficiency, 优切尾效率
, \5 r! s/ ^% ?+ J d3 zOrder statistics, 顺序统计量
, O8 y$ L+ c0 dOrdered categories, 有序分类# l, b6 @& R# [- J& x
Ordinal logistic regression , 序数逻辑斯蒂回归9 r3 L3 A3 x( O4 X5 X* H+ T
Ordinal variable, 有序变量9 H5 O8 p4 y) F. e
Orthogonal basis, 正交基
% g, J2 Z( p) B" _7 H8 \Orthogonal design, 正交试验设计
$ T* i. ] }" P0 S/ wOrthogonality conditions, 正交条件4 ^9 `' ^7 @% {/ j- _" H2 Z
ORTHOPLAN, 正交设计
9 B' J6 y' \* D- K& ROutlier cutoffs, 离群值截断点1 O6 s, M" f3 K$ j0 ~+ P
Outliers, 极端值5 R6 L) _( a! ]5 N
OVERALS , 多组变量的非线性正规相关 & ~8 I9 j* c- @) [; N. B
Overshoot, 迭代过度
1 ]" Z. ]# `* [1 k9 q0 uPaired design, 配对设计
/ K0 o7 z5 |- |, |+ w* a3 j. EPaired sample, 配对样本
8 I5 m. F4 m7 y$ l0 TPairwise slopes, 成对斜率) `; Y9 w* F, e
Parabola, 抛物线3 S' E# b, n; L5 P# k
Parallel tests, 平行试验0 s4 |/ b! l( d6 X
Parameter, 参数
2 \2 |. ^$ G u, S( \: T+ TParametric statistics, 参数统计( M, s1 B& p, {# Z) |1 P9 _7 t/ I
Parametric test, 参数检验* A8 w0 [% U' Q; [& ^
Partial correlation, 偏相关. F m% _. x$ q
Partial regression, 偏回归
0 v8 F! H& V5 j, M; F; `Partial sorting, 偏排序
, Z% K3 k# S' p5 C9 {Partials residuals, 偏残差4 Y4 y9 z3 _$ P. L4 C
Pattern, 模式* g+ {1 R8 [% |% L" r1 f
Pearson curves, 皮尔逊曲线, {% N# V; \! Q8 L
Peeling, 退层$ ~, Q0 ~3 l/ c1 ~& Y: i
Percent bar graph, 百分条形图, a* E0 \# D4 Z* r% b$ e9 R
Percentage, 百分比8 ]! t1 J! i3 M; h; q5 q3 u" l
Percentile, 百分位数
6 O1 u+ y8 X8 HPercentile curves, 百分位曲线
5 U" c: S8 _7 g' Q3 K qPeriodicity, 周期性% k( c5 L; e) b6 O
Permutation, 排列9 k' z& ]. l+ ], ^3 W5 M) j
P-estimator, P估计量8 J$ m; J2 M' m7 R% v1 ]. V; B" s
Pie graph, 饼图$ I& ~7 h( D2 |, D5 P2 O! N
Pitman estimator, 皮特曼估计量; h4 P) g2 D E$ d
Pivot, 枢轴量 f. j4 ~, p( g
Planar, 平坦
+ A# M; ]4 I$ xPlanar assumption, 平面的假设) q; T/ m# _" p9 t) y v; }
PLANCARDS, 生成试验的计划卡
+ w9 A' q; s8 _ k4 zPoint estimation, 点估计5 j: d8 J# k9 [) R2 z* N* O% m
Poisson distribution, 泊松分布& Z+ p: F) c5 r P! [
Polishing, 平滑 \7 a1 ?% _' p, J* d9 u3 Z$ H
Polled standard deviation, 合并标准差& }' x! @: q# o' B7 i' X. Q- @' V
Polled variance, 合并方差* m& ^: ^$ U& Q( i4 e, }9 x
Polygon, 多边图2 I4 z! |* s5 k7 h3 f$ H
Polynomial, 多项式
1 [$ a/ {, Y# n. d9 N& p, l& _! K( \Polynomial curve, 多项式曲线
. [1 R! |1 w0 iPopulation, 总体+ M6 G: f) a/ |4 P, J4 g! _
Population attributable risk, 人群归因危险度
( ]0 V3 M% X) ?* n+ C% i7 f8 fPositive correlation, 正相关
+ m7 K# u3 D; M. @ b) Y/ U( NPositively skewed, 正偏8 U+ M& L. O0 \4 R% G
Posterior distribution, 后验分布2 Y }( o0 i% D- V& p+ t' q9 y
Power of a test, 检验效能
1 V; i- @9 G. r3 y5 Q, D* }9 aPrecision, 精密度
* ^. [$ V4 [7 w. RPredicted value, 预测值
- ?: S0 X2 B. j; u+ Y( FPreliminary analysis, 预备性分析
c3 n0 R+ p$ ~+ ^4 B" J% sPrincipal component analysis, 主成分分析. _0 h, R7 b$ z6 {: D, P& Z1 D* w6 ]
Prior distribution, 先验分布% K; Y" Q' h' B
Prior probability, 先验概率$ s2 I: |1 }% o8 S- t! V# ]
Probabilistic model, 概率模型
6 a, F* g6 A) d8 V! kprobability, 概率8 V" c5 q1 }" m) w. N* R$ A
Probability density, 概率密度
0 D) `' [( d! J' _Product moment, 乘积矩/协方差
; C; q! m0 y! m$ m9 xProfile trace, 截面迹图 |& v. v) G. c) Z) ~: _+ A$ V
Proportion, 比/构成比 ]) C H* I- W2 ?! u
Proportion allocation in stratified random sampling, 按比例分层随机抽样6 V$ u" p% \1 j0 K, O/ m- B, g
Proportionate, 成比例6 Z+ B2 w3 u' \ \2 z
Proportionate sub-class numbers, 成比例次级组含量2 E, p) h! @% j, g7 z5 T# o
Prospective study, 前瞻性调查9 ~/ M6 k0 m G, A; {
Proximities, 亲近性 & X" C2 Y8 S6 j: ^* T1 z
Pseudo F test, 近似F检验3 ?$ {4 c' F# O4 M* I4 E3 G- e
Pseudo model, 近似模型% J/ u% m- T% Q+ q# Q; C1 ]8 F# _
Pseudosigma, 伪标准差
) [* @! p* [& S8 b* t( U* H5 kPurposive sampling, 有目的抽样
9 o! [- p' x$ G( |( ^QR decomposition, QR分解4 D& F* o" i; F6 [0 _& @
Quadratic approximation, 二次近似
" p T3 d# B$ o, Z' s( O5 A$ sQualitative classification, 属性分类
+ t4 s) Z7 O, ?$ }# VQualitative method, 定性方法8 r( u! B [( S4 @' L
Quantile-quantile plot, 分位数-分位数图/Q-Q图- f5 m2 G+ M7 f9 B/ @8 ^
Quantitative analysis, 定量分析
( s0 v) L% f6 K, m* [5 q( PQuartile, 四分位数4 @" T- |) U; {2 @; |4 U5 z* b P
Quick Cluster, 快速聚类. h( L$ i, e r+ L" J1 O7 L
Radix sort, 基数排序& A; o. ^4 T: b
Random allocation, 随机化分组" g3 e$ _1 e1 n% ^
Random blocks design, 随机区组设计
6 |( a* T; I# y2 |" }( R6 q( M# G1 S2 CRandom event, 随机事件2 C+ \" e5 L! M9 [! h b
Randomization, 随机化
( u4 R3 Z, P- _/ gRange, 极差/全距
- u( U* R# U9 A1 W6 O2 MRank correlation, 等级相关
0 |) ?- z- P% i8 E* [Rank sum test, 秩和检验
$ x+ @5 M7 _; }& e7 i3 jRank test, 秩检验
8 N" j) M/ C0 @! \$ fRanked data, 等级资料
5 H4 \$ T/ N5 @8 d2 K0 BRate, 比率
# q# R/ y- C f/ N- x( [Ratio, 比例
% y& x+ ^' I* j9 a! ^3 ERaw data, 原始资料
1 t1 q5 @3 f" } mRaw residual, 原始残差, v( L/ i0 j* q6 R8 Y" w( {
Rayleigh's test, 雷氏检验1 \: K% r# D" R5 B* J% [
Rayleigh's Z, 雷氏Z值
- B/ G1 N; F4 K9 A$ sReciprocal, 倒数
3 P6 m- a E% o( b; ^6 }Reciprocal transformation, 倒数变换" D1 k9 B+ d& Z% u) j! L* p
Recording, 记录
2 b1 h3 c1 h! F1 V5 ^Redescending estimators, 回降估计量
7 A5 P* u$ Z b0 KReducing dimensions, 降维4 q% ]& n) m. `7 r
Re-expression, 重新表达# o$ s5 t0 T m" J: x8 |' \
Reference set, 标准组' ?. e k$ `, b% H+ ~
Region of acceptance, 接受域. |! @+ {8 H" A- u% v
Regression coefficient, 回归系数. A2 e- ]; F0 W" d/ K
Regression sum of square, 回归平方和
2 i$ z6 C0 L! ]& Y: O3 JRejection point, 拒绝点
. B0 D ?! n0 O2 j; YRelative dispersion, 相对离散度
% c- ?: |( K `+ b# g$ {Relative number, 相对数
) T) h. I/ ?# v7 f5 G- jReliability, 可靠性9 Z4 f' P3 v9 _: l
Reparametrization, 重新设置参数; e- }5 g3 M: e
Replication, 重复( ` I6 O* B+ ]) U; I5 x) t6 Q
Report Summaries, 报告摘要( \3 s( d9 L- N( c3 g3 a
Residual sum of square, 剩余平方和
, M! C6 f" R1 A3 H% m% O1 tResistance, 耐抗性. Y# s. s5 N. ^) Y' H- p" N
Resistant line, 耐抗线5 e. J! N( W; e* Y
Resistant technique, 耐抗技术
9 I; A5 L7 ~ b4 QR-estimator of location, 位置R估计量5 K1 B+ V2 f! C- \2 M v" L, z
R-estimator of scale, 尺度R估计量# w+ R f- T! m: I+ M9 H
Retrospective study, 回顾性调查
. t `4 g5 |- a) sRidge trace, 岭迹
% w3 X. M5 D+ t5 Y+ U4 T8 HRidit analysis, Ridit分析6 g+ H% Z7 h) {2 a% O( i3 z
Rotation, 旋转3 g0 S! u- X# E+ ~
Rounding, 舍入
! `5 B: ?! Z+ r+ g( WRow, 行) l. ~& V/ X# S9 i3 m! S2 J
Row effects, 行效应, L! H, D, l0 S. z5 p8 H
Row factor, 行因素
! ~: S( c4 s7 J( E: p7 qRXC table, RXC表
) N2 J$ F0 o9 b3 w& Y; }Sample, 样本9 ?; u: {( F. c4 ?& m, T! f! w
Sample regression coefficient, 样本回归系数
3 e1 _1 Z( r u5 y+ rSample size, 样本量7 ^4 x0 U* C3 \# s* f
Sample standard deviation, 样本标准差
' t/ G5 h( c3 l3 C4 t5 h; FSampling error, 抽样误差
* }5 @6 X' U0 ?, i! ?SAS(Statistical analysis system ), SAS统计软件包
8 r- {/ |6 }3 ]6 y2 \Scale, 尺度/量表% ^* [, Z/ [" S; O0 j
Scatter diagram, 散点图
7 H) @3 C: i% `# W4 g1 ^Schematic plot, 示意图/简图4 w0 g; o2 Q$ G0 i1 t
Score test, 计分检验# K( o/ a# K0 R1 I7 k
Screening, 筛检
3 }- e7 y8 W0 {/ B- H/ KSEASON, 季节分析
- g0 l4 C# V) i2 OSecond derivative, 二阶导数2 m+ k1 x- v/ p: n0 ]
Second principal component, 第二主成分
! M! ~8 \ a& RSEM (Structural equation modeling), 结构化方程模型
& u4 z {; U! v$ cSemi-logarithmic graph, 半对数图# e* h0 d% n3 A+ R) R; a4 W; ]
Semi-logarithmic paper, 半对数格纸
$ }; q- A! r' h. f/ U' o# [Sensitivity curve, 敏感度曲线
. N& S4 G2 f3 K7 \3 X" Z! q. CSequential analysis, 贯序分析
, `5 ^8 ^8 _6 E; h3 u" }( sSequential data set, 顺序数据集
* {7 U4 j7 m* g" `4 u9 Z e7 N) {Sequential design, 贯序设计' |+ F. \: ?" z6 W6 s2 B; n5 @
Sequential method, 贯序法
4 a, S* z2 s4 z* D% u1 JSequential test, 贯序检验法 Y* b- M- G: h7 ]9 m2 u0 u
Serial tests, 系列试验+ Q( m% t1 E) i" O, W
Short-cut method, 简捷法
+ \+ ?: ~2 a2 N+ e5 ESigmoid curve, S形曲线
. v7 e% H! T7 S4 G4 X9 O7 HSign function, 正负号函数
2 y; |+ a0 r1 m' `9 OSign test, 符号检验
" {1 ~& y1 d+ [! vSigned rank, 符号秩! s& N% @( H# A8 l1 t4 |3 y' b
Significance test, 显著性检验
& Q4 [! R4 p: y' _. ~Significant figure, 有效数字
" V: {& P w3 R7 L2 a+ ?" x2 F8 JSimple cluster sampling, 简单整群抽样) y$ j4 P- |$ J" G
Simple correlation, 简单相关
9 _ x7 H) t( T% DSimple random sampling, 简单随机抽样 e+ l @- a6 Z
Simple regression, 简单回归 ], r$ W. {* O% L1 |9 ?4 s
simple table, 简单表
3 u" V7 C, _% e2 gSine estimator, 正弦估计量
3 {, N1 g3 G& @' ]# T# MSingle-valued estimate, 单值估计/ h9 o6 d1 C7 o" K9 l1 t
Singular matrix, 奇异矩阵
1 P% m& E' _2 K' E2 Q: s0 h" _8 FSkewed distribution, 偏斜分布
! V% ~4 Q1 J i! ?Skewness, 偏度8 ~3 H, R4 p' n$ Z$ I" @# z1 i w; X6 d/ A
Slash distribution, 斜线分布/ ~ o, Z* g6 }" v& h& K% c" {
Slope, 斜率
0 r( c% q! d$ q/ `1 nSmirnov test, 斯米尔诺夫检验
3 V4 u4 O% E2 r6 T4 L) ZSource of variation, 变异来源
' ~& r1 y5 Z0 U3 F7 FSpearman rank correlation, 斯皮尔曼等级相关9 j2 U6 y% T d1 W1 _ D M- d6 S
Specific factor, 特殊因子
+ w$ h" y& G/ vSpecific factor variance, 特殊因子方差0 u/ s6 D* T: D8 n
Spectra , 频谱
3 m5 `: p2 N- z0 g: z! e/ B; L6 }3 QSpherical distribution, 球型正态分布' ?& [. F' ]6 {
Spread, 展布
9 s1 d* l% P# HSPSS(Statistical package for the social science), SPSS统计软件包
; ]0 t5 }) M, `. c2 C6 H QSpurious correlation, 假性相关
! h" j# B0 \! A' mSquare root transformation, 平方根变换
+ t3 D E1 f0 q: C4 t2 `Stabilizing variance, 稳定方差 x& K0 T% P7 \, l9 a
Standard deviation, 标准差
; K; X$ t: v& {6 F+ UStandard error, 标准误
6 `, a M" Q( O8 I g w- dStandard error of difference, 差别的标准误' p' L, d6 a2 P' K# f
Standard error of estimate, 标准估计误差
" }6 y0 u$ V6 W2 \Standard error of rate, 率的标准误+ O, V& R% F, k3 f4 h: y! G
Standard normal distribution, 标准正态分布/ e3 ]/ m, y; z! M9 I9 {8 a! C! v
Standardization, 标准化4 }0 _% @2 c( o, `: q9 ]
Starting value, 起始值
" Q. u" ?( \/ LStatistic, 统计量
. }* f* P) w! i) V8 bStatistical control, 统计控制% Q* T1 O R t, B4 Z& X/ K) ~
Statistical graph, 统计图6 z& m& E9 U6 D) r
Statistical inference, 统计推断* m7 f0 ?- @4 x) {; v# z4 N& |
Statistical table, 统计表
- F8 z& G% B& Q' w2 p0 t( h2 r* x, j- J6 M, kSteepest descent, 最速下降法
* M$ M8 V* P( R. MStem and leaf display, 茎叶图
) v% y) a- a/ K8 v' Z) fStep factor, 步长因子
" L( e" i* o* aStepwise regression, 逐步回归
e7 e2 C: W" S- ? V/ }& EStorage, 存2 f0 D/ p# x& ]3 X/ w8 M& _
Strata, 层（复数）, e* Q; c6 }) Y9 [ U
Stratified sampling, 分层抽样1 t2 W( W) F" O5 n" T3 l" R
Stratified sampling, 分层抽样
+ _ h. x3 P8 ]% ?! q" }2 xStrength, 强度
" m* w$ y% F C7 cStringency, 严密性
5 [+ N. O% l; c! w; ZStructural relationship, 结构关系
5 L% v2 X6 E0 J$ X7 KStudentized residual, 学生化残差/t化残差
: y0 o+ r5 ^6 W" L3 RSub-class numbers, 次级组含量3 j; K' d% F5 O9 P/ N: B% t) N+ W
Subdividing, 分割
% e, ~9 N' g/ C' k" x9 O6 _; JSufficient statistic, 充分统计量0 n6 a* d4 c. p: l
Sum of products, 积和) X. s4 ^% R8 t. K
Sum of squares, 离差平方和2 v1 J; U r+ y% f! B) `
Sum of squares about regression, 回归平方和
3 m6 ?: w9 j( T2 B: E+ o R2 lSum of squares between groups, 组间平方和" m- I4 L' }! {; ~* i5 d( h
Sum of squares of partial regression, 偏回归平方和# L% e) Z! ^( R4 R! I9 r
Sure event, 必然事件 S) m# v. s0 s' `6 h+ m
Survey, 调查
. m' G( [/ }# d/ Q" V0 X9 mSurvival, 生存分析3 R& w7 N! H) `8 g- E/ f/ W1 P, i
Survival rate, 生存率
* T# ]7 f5 h6 c! ]% O, s( } BSuspended root gram, 悬吊根图
! [; ~ q" S% y+ X& NSymmetry, 对称/ d' S- j6 Q3 J5 z$ d+ R" ?* G$ q. q9 D
Systematic error, 系统误差$ |, X* J2 e5 C0 m
Systematic sampling, 系统抽样
+ H5 U$ Q' S$ L/ ]) {3 z% JTags, 标签4 x6 ~) x( V9 J3 l
Tail area, 尾部面积
0 o9 B; V& C1 c; xTail length, 尾长
1 N# X6 @/ p+ v; pTail weight, 尾重
9 ^0 O( J( a/ V! ^& B) B' Y* t5 XTangent line, 切线
( V+ p+ x; ?& l9 fTarget distribution, 目标分布( k9 J- e5 H! O! Z- g
Taylor series, 泰勒级数2 K* m; U/ |* P! r7 j
Tendency of dispersion, 离散趋势
' q4 m# s+ W% }1 N$ QTesting of hypotheses, 假设检验
1 r1 {4 q& P! oTheoretical frequency, 理论频数5 i8 c+ W5 g$ P3 u9 B7 J( G8 a$ U/ L
Time series, 时间序列- Z' k6 ]/ |, q0 |7 `
Tolerance interval, 容忍区间# y+ q2 }8 p1 K/ N" e
Tolerance lower limit, 容忍下限( n3 [7 V0 n6 D1 ]$ l x
Tolerance upper limit, 容忍上限6 }6 \. o* W: L" x+ ~ U
Torsion, 扰率
, [+ U/ b3 h* dTotal sum of square, 总平方和
+ D M8 p8 J" c, V. A) ^5 wTotal variation, 总变异" J- N. z6 j: ?6 m9 [" j
Transformation, 转换
" |5 b' g# R) A. x2 q% W2 V+ |Treatment, 处理
# W5 K1 T# ?7 V5 ATrend, 趋势
& b E- Z# q5 c* w- gTrend of percentage, 百分比趋势
0 V0 J5 G4 I, r- H% t- s( z" B+ v9 y# gTrial, 试验6 x1 P8 |/ x/ `" _6 ]
Trial and error method, 试错法
% } p3 T' [; w k7 y) ^- n4 T% [5 c% qTuning constant, 细调常数" X% o0 Y7 @3 N$ k& F5 a+ r
Two sided test, 双向检验6 B7 i, r+ j M3 D* g; Y4 I q
Two-stage least squares, 二阶最小平方' X* Q" K6 i4 b7 h
Two-stage sampling, 二阶段抽样 o" d/ i! u6 V4 Z# [
Two-tailed test, 双侧检验4 w( x3 K7 p9 Z2 O# \/ w
Two-way analysis of variance, 双因素方差分析
1 q* e* Z G+ D3 N4 y# xTwo-way table, 双向表7 v5 m- l3 m' A* u) y
Type I error, 一类错误/α错误/ U5 K4 i t: L! b' l2 d5 f8 W* y
Type II error, 二类错误/β错误- D' U. R% Z+ M7 X0 W* F
UMVU, 方差一致最小无偏估计简称+ ~2 j8 d8 ]6 d5 a! @
Unbiased estimate, 无偏估计. E7 t: F. ?( }% D; {
Unconstrained nonlinear regression , 无约束非线性回归
Y+ r0 x" @+ l! V/ }" E( @Unequal subclass number, 不等次级组含量
+ M9 `2 S$ G, bUngrouped data, 不分组资料) r$ R q9 N: P+ b J# k
Uniform coordinate, 均匀坐标
" [# {8 s5 D7 ]/ h9 {' kUniform distribution, 均匀分布9 a0 U! ~& ?' [8 [! @
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
& P {, D( v$ W+ gUnit, 单元% o' V* Z2 y8 W5 Q% h7 j& p- q
Unordered categories, 无序分类) {! q* R( m+ M- l
Upper limit, 上限* a A% v7 F; a4 [% X
Upward rank, 升秩) N4 c+ l9 p% M2 {; P
Vague concept, 模糊概念* N* L" K: ^4 B. P; C% T7 d
Validity, 有效性0 F O! Z* ]7 [) d2 Z
VARCOMP (Variance component estimation), 方差元素估计
( H; o( F8 r" KVariability, 变异性
k E9 R* P- n4 }Variable, 变量
- q& k6 h- Q3 {' m U7 w7 LVariance, 方差
& u' T8 e- o0 b( O* i: EVariation, 变异
+ O# d/ s9 E, fVarimax orthogonal rotation, 方差最大正交旋转! b4 X; W3 D4 R$ H% N& S+ Z
Volume of distribution, 容积2 f+ g, d y* `: n; u
W test, W检验" v) n5 J/ e+ ]0 B/ a N
Weibull distribution, 威布尔分布. J" i+ _* [6 z; j- e3 `1 O D
Weight, 权数; P2 s7 h) M, y; _9 [ s, ^
Weighted Chi-square test, 加权卡方检验/Cochran检验
" } W! c' E- |& `- k# ^0 U, ?Weighted linear regression method, 加权直线回归
' B/ H3 m- `% lWeighted mean, 加权平均数
$ N& X9 r) `* P6 \+ D4 W5 B7 ^Weighted mean square, 加权平均方差
6 d. U, h3 c) k5 G! R* m$ @& jWeighted sum of square, 加权平方和9 M* d* d T: F- o9 S
Weighting coefficient, 权重系数& @# U2 K$ F+ I5 q q! Z+ f! f, \
Weighting method, 加权法
; _0 Y/ c/ }* v/ n/ CW-estimation, W估计量
; I& _( Z, S' S0 h+ gW-estimation of location, 位置W估计量# X5 `6 g0 }( L7 m, F+ O
Width, 宽度* y; L# |$ u# u6 L( c
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验/ T% @5 M; j. C; \
Wild point, 野点/狂点
$ i5 m. O+ I O, M' oWild value, 野值/狂值$ _& K0 f5 H. ?& g: `
Winsorized mean, 缩尾均值
6 c: t' d* `: k6 t/ ^Withdraw, 失访
5 w. M( ?; g Q7 l! nYouden's index, 尤登指数5 e! w) l7 ]/ v3 x5 R
Z test, Z检验
$ k! z- o" x. x% u$ [5 O: a2 V, F" nZero correlation, 零相关- n! G2 P% u/ n M: j( \3 \( u
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
