|
|
Absolute deviation, 绝对离差
% a- n9 V7 d" @- n& q( f9 Q( ~Absolute number, 绝对数
5 ]0 j1 O; B$ w7 m: P4 b3 k+ IAbsolute residuals, 绝对残差6 E+ R! ^# n( P! W! r
Acceleration array, 加速度立体阵* h( c/ x8 L* \) A# }: ?2 J
Acceleration in an arbitrary direction, 任意方向上的加速度
8 B; c' G' E4 Z- TAcceleration normal, 法向加速度
# D9 V2 Q, w' C9 f) n5 P0 XAcceleration space dimension, 加速度空间的维数, w8 H, Q& F7 j6 ^4 {% D3 X) N5 `
Acceleration tangential, 切向加速度
$ n' W' \' C. e- E3 |Acceleration vector, 加速度向量% T4 w+ N) W o& w
Acceptable hypothesis, 可接受假设
( U/ W, |$ o0 K2 Z5 {( P! pAccumulation, 累积( T5 G A! U* G! |& b1 h
Accuracy, 准确度2 A; R8 e3 u- ]# ?0 ~( y: x5 ] |) q
Actual frequency, 实际频数* i+ Y4 `2 i* o" o4 ?- O
Adaptive estimator, 自适应估计量+ S( A% S/ [5 R" X; j
Addition, 相加
3 U1 H- d$ v; Y6 u7 IAddition theorem, 加法定理! E% ]# N0 E. u) x$ O9 f( [
Additivity, 可加性
T8 u! v# u9 Z4 K* y: BAdjusted rate, 调整率
, J0 d/ ~3 m/ |+ `# rAdjusted value, 校正值$ x$ I3 n5 V) u3 a% }
Admissible error, 容许误差2 Y* j& A" [' ~5 G2 g7 z# p2 e# G
Aggregation, 聚集性, d$ y* w' h# y% s) J* t! h: `7 V- a- _8 `
Alternative hypothesis, 备择假设8 M5 Q9 u# F% \# q
Among groups, 组间, Q- S- e1 W0 l5 @+ M3 }/ w
Amounts, 总量
9 G+ {* G9 S( sAnalysis of correlation, 相关分析- P3 B& y9 Y) g3 t
Analysis of covariance, 协方差分析+ `% p6 @; Z3 A* Y8 j/ |5 T
Analysis of regression, 回归分析" p7 H. I% ^% M3 d
Analysis of time series, 时间序列分析
' n- B7 r8 N. M) vAnalysis of variance, 方差分析
- q: z& Q( X! P3 ]Angular transformation, 角转换
0 W" c$ {1 N& J5 U, Q% T( SANOVA （analysis of variance）, 方差分析- v5 r+ q2 J8 s: S3 y( M* M* g
ANOVA Models, 方差分析模型) `: u, L7 N; w- {. u
Arcing, 弧/弧旋' H7 I0 L6 g# s% O: Y+ n
Arcsine transformation, 反正弦变换5 T# p! o+ l2 q" r/ e. M
Area under the curve, 曲线面积
1 S0 d$ i. c( T) j. WAREG , 评估从一个时间点到下一个时间点回归相关时的误差 - r m5 F! w' Z& ~
ARIMA, 季节和非季节性单变量模型的极大似然估计 $ f$ w9 l% {; F! L
Arithmetic grid paper, 算术格纸
+ L3 E5 t$ B) `7 o! W$ ~Arithmetic mean, 算术平均数5 _$ m3 L0 R2 k3 r1 _! c* D
Arrhenius relation, 艾恩尼斯关系! @/ y2 d0 P, ~) o2 \
Assessing fit, 拟合的评估: r' y* ]( [9 R$ K: ?& T5 M" j$ a7 r- O
Associative laws, 结合律; n3 M. J( m0 X+ [0 a. l2 @
Asymmetric distribution, 非对称分布 E, E$ ^' S" P- y+ J4 o( z/ z
Asymptotic bias, 渐近偏倚( W4 |5 |1 g4 t. D: n* v
Asymptotic efficiency, 渐近效率# x' Q- m3 z; i- J- Z" C) n; u2 I
Asymptotic variance, 渐近方差, o% M; ^! F! A& }: {: ~
Attributable risk, 归因危险度
5 g, ?) h. Z& r6 Q& kAttribute data, 属性资料
3 k1 D% C! p7 m1 h& }: H# ]Attribution, 属性; g! P+ t7 m( t$ I# p, f
Autocorrelation, 自相关5 K( _# K2 u* O/ I
Autocorrelation of residuals, 残差的自相关6 G9 o$ ]3 S, L/ b5 O1 [1 e/ y9 U
Average, 平均数2 g0 m- v8 |1 @+ @
Average confidence interval length, 平均置信区间长度/ x1 p6 Z! L. D# `0 g) e7 F7 ^
Average growth rate, 平均增长率; u1 e& _: o5 d4 \
Bar chart, 条形图5 f E. `, I( X$ b6 D w
Bar graph, 条形图 i$ r7 A& e I$ b. u
Base period, 基期
! |- r! Y6 F, U! LBayes' theorem , Bayes定理0 L; \2 Q: }) p6 X; v2 n7 o. c
Bell-shaped curve, 钟形曲线* u' n0 \* ^ N" Q
Bernoulli distribution, 伯努力分布
$ L1 A, k, g" oBest-trim estimator, 最好切尾估计量3 O4 K- `9 `( x; [* y
Bias, 偏性6 w2 @/ @0 E9 P* i5 V$ T- {
Binary logistic regression, 二元逻辑斯蒂回归 i* |4 k9 F7 e* q' G1 {" v& V
Binomial distribution, 二项分布
2 j9 W4 z- f+ D- I' G1 H* A( JBisquare, 双平方
9 k1 w0 z7 B- \: ]Bivariate Correlate, 二变量相关4 k; B% S' r' g' I- m
Bivariate normal distribution, 双变量正态分布
" [/ F$ ]9 B' C: B8 {3 FBivariate normal population, 双变量正态总体
% B( h0 _' b: m; p9 IBiweight interval, 双权区间
% o# Z! x1 b* [Biweight M-estimator, 双权M估计量& a/ c/ a$ u5 g# t
Block, 区组/配伍组! c9 k$ L& d! g2 E4 V
BMDP(Biomedical computer programs), BMDP统计软件包# |* d& b: r$ J4 f4 j( I! f
Boxplots, 箱线图/箱尾图3 S! {5 h0 b' K2 Y' l9 g7 j9 `
Breakdown bound, 崩溃界/崩溃点
4 g. N5 B% M0 m2 ^ gCanonical correlation, 典型相关
+ {) g% {: y5 Z6 JCaption, 纵标目
1 f& Y( Y( ]5 o0 C" n: { f) cCase-control study, 病例对照研究4 v3 Z! |5 \ c% J
Categorical variable, 分类变量& {2 h: ?- @$ T5 N
Catenary, 悬链线$ g* i4 D; g$ W" x
Cauchy distribution, 柯西分布7 M# N; U! X: e& g, D8 _
Cause-and-effect relationship, 因果关系
3 Z, m4 W+ ~* s& `Cell, 单元6 j; h- L. p4 m; X
Censoring, 终检
) P9 a3 \/ y4 ^4 f Q; k+ fCenter of symmetry, 对称中心
! n5 p% f' s6 i0 m4 i6 C7 V+ a0 ZCentering and scaling, 中心化和定标9 T8 w' ?$ L5 p0 `6 q+ c( n
Central tendency, 集中趋势. q1 }3 @: O. X! [5 x$ n
Central value, 中心值
4 L( n6 l1 e% t% K; @' ^$ |8 [CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测& ^0 Z1 O; q1 V. f' ~+ k1 a
Chance, 机遇
; ]( P. {$ f5 y* C* {& i5 ?' {Chance error, 随机误差
0 v2 R- ^- r8 m$ k2 Q" RChance variable, 随机变量( o, }/ G8 z/ Z6 O$ M% v$ }
Characteristic equation, 特征方程
$ D$ {! k- U' dCharacteristic root, 特征根
- O# i. m a- h% X0 R9 l1 B. PCharacteristic vector, 特征向量4 Y6 n4 X7 B2 L- _
Chebshev criterion of fit, 拟合的切比雪夫准则- z+ x P$ h) a) R* f
Chernoff faces, 切尔诺夫脸谱图; P0 Z4 o, w# a& J; S
Chi-square test, 卡方检验/χ2检验' W0 |+ y% C1 h! i$ t7 Y
Choleskey decomposition, 乔洛斯基分解. Y' F: p! V: L, y/ ?/ Y- v( ]
Circle chart, 圆图
; `& `5 F+ Q/ z5 H. w3 J4 A, ZClass interval, 组距+ _) M1 W; J- o- N" K
Class mid-value, 组中值6 ?) d, i* X l- G, x8 a
Class upper limit, 组上限
9 h0 N) Z( b# sClassified variable, 分类变量
1 k+ Z+ C* N& |8 [8 E7 NCluster analysis, 聚类分析 x! c4 M7 ?6 h- h
Cluster sampling, 整群抽样
; L) \2 z @' I3 FCode, 代码
/ q- P K( \" m" r+ z+ p: X. |Coded data, 编码数据
: ?. {" H3 I. F4 J6 UCoding, 编码
$ ^3 `: W: n: z; D* ~0 ^, QCoefficient of contingency, 列联系数, A0 V+ G3 C' j+ |% g" R- j
Coefficient of determination, 决定系数
! |: K- x" b* \+ [- SCoefficient of multiple correlation, 多重相关系数
+ W+ x6 U) K5 Y/ V3 F# hCoefficient of partial correlation, 偏相关系数
8 U# I; I0 X* r4 ~. RCoefficient of production-moment correlation, 积差相关系数
7 s$ p7 P' A/ Z0 Q) b8 }8 i6 W* S3 tCoefficient of rank correlation, 等级相关系数$ c. n" v9 a$ K$ m5 S* p
Coefficient of regression, 回归系数
' q* u( H" ], J3 Q! ICoefficient of skewness, 偏度系数
( S% Q8 p5 {# a# W# }/ QCoefficient of variation, 变异系数
' x: O3 C: N* n* BCohort study, 队列研究
" q; s7 K, {5 z- m/ L0 |& l+ }Column, 列
9 f* {/ f2 a$ @Column effect, 列效应
: K6 x. i" X5 Q) o) e2 rColumn factor, 列因素" p* f0 A0 [4 `( X6 p2 A
Combination pool, 合并
* S6 j# K5 p* ^3 hCombinative table, 组合表
! }- X3 N% o- CCommon factor, 共性因子
! o5 L. P) n& X5 o% h7 N) @* RCommon regression coefficient, 公共回归系数, `% k7 R6 d& r
Common value, 共同值
# L0 _( |1 \5 R3 [& j" SCommon variance, 公共方差% J, W4 s) N% T+ A L7 E- f
Common variation, 公共变异1 S* D( |4 B( T: }* }9 M6 s
Communality variance, 共性方差0 e# v$ a2 p; H" U4 d1 W
Comparability, 可比性
7 q) p6 U2 }1 w# YComparison of bathes, 批比较
8 {, R2 d2 x$ [# T( S4 i% c! V# oComparison value, 比较值$ r2 Q3 M% U, g5 G1 T# s3 h5 t' {
Compartment model, 分部模型
9 S! J3 M4 B9 V" gCompassion, 伸缩
. v4 |* G/ L& i3 HComplement of an event, 补事件
$ S: h# R$ _( _Complete association, 完全正相关) i9 S' L9 m# `5 }2 X8 ` b$ W7 T
Complete dissociation, 完全不相关
+ L$ |* u6 v0 I P2 M. ]Complete statistics, 完备统计量5 l& C! B$ F% |
Completely randomized design, 完全随机化设计
( p, a8 y7 s/ |3 E8 M+ aComposite event, 联合事件
. J! k/ b; i' q- PComposite events, 复合事件: L2 ?$ w" c' H& z- i% m
Concavity, 凹性- L1 }' i6 |$ n: z% u
Conditional expectation, 条件期望
+ k- Q: F+ e+ ^2 O- zConditional likelihood, 条件似然
, r" z3 r2 C) \Conditional probability, 条件概率
$ ~2 _: G& D9 e. Z( Z3 g$ j7 [Conditionally linear, 依条件线性; J! k% Q+ V& D$ R
Confidence interval, 置信区间
9 v& @% D: M/ g; n0 nConfidence limit, 置信限5 s4 s& D6 m2 {
Confidence lower limit, 置信下限
+ n3 D6 B4 B; Z4 W: _9 Q$ aConfidence upper limit, 置信上限, q& r* s0 C, ~6 U* H }
Confirmatory Factor Analysis , 验证性因子分析
3 V2 B6 |! H2 `6 M/ ^ H4 k3 h* c* DConfirmatory research, 证实性实验研究; X( ~- I" u6 [0 b
Confounding factor, 混杂因素
' ~3 @, q" \4 X9 A' l0 OConjoint, 联合分析
8 H& D1 e% }! j- l) x6 L) R+ zConsistency, 相合性3 N0 c: N5 x3 }! x9 @
Consistency check, 一致性检验) _7 ~6 j4 D4 g4 w2 k
Consistent asymptotically normal estimate, 相合渐近正态估计$ j3 E& h/ n8 A- r( M: B' ?
Consistent estimate, 相合估计
) Y* W% |: V! J- ~$ aConstrained nonlinear regression, 受约束非线性回归* [" D D8 O# T/ `8 a
Constraint, 约束# Y% ?, i3 [' O' C
Contaminated distribution, 污染分布' d$ ~) Y% i3 ^
Contaminated Gausssian, 污染高斯分布4 l i" `5 l0 a- s, z5 ?1 W# n3 O
Contaminated normal distribution, 污染正态分布
6 v# }% B7 y6 K: [: T" i* B0 Q- {Contamination, 污染" t5 c) m1 f# Y6 K$ T0 J
Contamination model, 污染模型- S' G* r, \' e. L
Contingency table, 列联表5 l8 w9 d# ]# Q7 \
Contour, 边界线 O& Z1 }) U: B& i
Contribution rate, 贡献率" f3 j& s, t" Q, A3 a: a
Control, 对照
: q6 Q: V' Z* d# lControlled experiments, 对照实验$ A1 o# L- k; r- N9 |6 |
Conventional depth, 常规深度
. P' D1 B4 g1 IConvolution, 卷积- f- q0 {* x" t! b/ m" r# ?& k
Corrected factor, 校正因子
( Z3 n# D9 v, m' G% {' fCorrected mean, 校正均值
2 e" _4 R! W( z* q$ mCorrection coefficient, 校正系数% h: x2 p$ Y6 M- K z* X; w
Correctness, 正确性5 s6 n2 |( \ Z" |# y& n
Correlation coefficient, 相关系数
9 Z2 n! |$ y7 Z. PCorrelation index, 相关指数
4 w7 V; l* Z) O" HCorrespondence, 对应
* k9 v3 J$ b# bCounting, 计数9 A- q3 |5 Z: d9 J9 K) w
Counts, 计数/频数4 A1 ~4 L) `; o/ O; h
Covariance, 协方差
& [. b+ S7 R5 HCovariant, 共变
+ c2 s y8 l6 E; j8 {Cox Regression, Cox回归( x6 u) D$ l; ^9 V0 K6 @9 D
Criteria for fitting, 拟合准则4 q4 e+ I, S% H) E4 x
Criteria of least squares, 最小二乘准则 L3 U m0 p. g, V% R
Critical ratio, 临界比
3 u/ y' s* t% c# _Critical region, 拒绝域0 k5 u0 u& l% i6 j# e
Critical value, 临界值8 T% t6 K3 _( ^% o$ f" S/ Y* q
Cross-over design, 交叉设计
0 [4 r9 n, ?. V1 D% WCross-section analysis, 横断面分析
- H$ f, _( k$ n! f( w6 eCross-section survey, 横断面调查
- |* y" ^9 ?( y1 j# OCrosstabs , 交叉表
& e/ f8 J' l6 ]+ i$ }Cross-tabulation table, 复合表* A6 D) K$ k0 F
Cube root, 立方根
) t* f# M; k7 r5 p( i! o+ ^/ _: [Cumulative distribution function, 分布函数4 A% p) P9 u2 m. r' [5 {8 r% B
Cumulative probability, 累计概率
% K$ }8 ?- \. T6 u$ VCurvature, 曲率/弯曲7 l+ k b F; a6 p* s5 K+ M. K M
Curvature, 曲率! P2 x& y# z; H- ~
Curve fit , 曲线拟和
7 R' U7 s' p) J8 j7 I$ ?0 D. dCurve fitting, 曲线拟合
7 T7 o y; \) F8 uCurvilinear regression, 曲线回归9 {% a. W- A2 ~4 j7 S k
Curvilinear relation, 曲线关系0 t; S( `$ Z1 \2 |: `# p
Cut-and-try method, 尝试法
6 W2 L$ l% d4 Y# ?' B* _Cycle, 周期1 A# `( l" P$ s0 ^. L0 D/ S
Cyclist, 周期性& P# V$ h) m" ]" C! [0 @5 s$ Y. N( K
D test, D检验
7 n. G! d6 N. Y0 c8 GData acquisition, 资料收集& c. a& D' A2 K% {, k
Data bank, 数据库* i. I7 d' S; v5 |
Data capacity, 数据容量
$ [, q3 y, J' u- ZData deficiencies, 数据缺乏
( K0 p- k/ r; G) }1 t- rData handling, 数据处理
( p7 `, X6 D* n* M, r& Y: iData manipulation, 数据处理
8 f' l2 Q- I; vData processing, 数据处理# C9 B1 y3 [) m5 m! R) e" m
Data reduction, 数据缩减% N- u: L1 M5 C; W P( \; v0 T* L
Data set, 数据集
$ X, p6 D* O* N$ M% c, IData sources, 数据来源- o; @1 m3 o) }! V# d5 Z* V* h
Data transformation, 数据变换
+ H9 Q" u& b' m3 S$ mData validity, 数据有效性
# L5 h2 [4 B$ F4 [6 q* R/ xData-in, 数据输入8 a8 d" _' ^* e, _) H/ Z1 Q$ g2 E! Z9 h
Data-out, 数据输出
3 W; N# y4 D* TDead time, 停滞期
* P6 X0 N0 b: R; Y) t0 ~Degree of freedom, 自由度
# x4 `# `4 ?5 J, H* W1 K q0 R1 }Degree of precision, 精密度" r: @! p+ n/ d ]/ L( t# w
Degree of reliability, 可靠性程度$ c# ~1 H# j2 x1 |8 L
Degression, 递减9 m* p% i% L/ g3 v( x. S% E
Density function, 密度函数8 R5 w. t. t4 u! u! O: H
Density of data points, 数据点的密度1 A8 t4 H9 }% _- _! f4 Q$ a
Dependent variable, 应变量/依变量/因变量, |; W2 h3 z) [' E# z1 v) X/ c& y
Dependent variable, 因变量
9 W! y- E# Q/ ~! `- E/ `Depth, 深度0 B6 S$ Q2 c* ~7 l. ^
Derivative matrix, 导数矩阵
+ Q9 A" X0 f& ODerivative-free methods, 无导数方法
! |& z% S9 ?) B7 RDesign, 设计, ~, G( X% t8 U9 w
Determinacy, 确定性 F+ {3 [% [( h8 Q
Determinant, 行列式; t f( P7 I* i! b
Determinant, 决定因素
1 K2 y: J: \0 U# q& yDeviation, 离差' j: J& \6 |, F- K" l* y* g/ S
Deviation from average, 离均差
7 c, Y3 Y( J" XDiagnostic plot, 诊断图: t. [) K! z, U3 S( S
Dichotomous variable, 二分变量
( E5 P* W, R% |: J7 z& CDifferential equation, 微分方程' Z. A8 H% ?' B
Direct standardization, 直接标准化法3 q. J" [. R# |6 V
Discrete variable, 离散型变量% k3 `, q. h- M, t5 G3 V
DISCRIMINANT, 判断
X0 E; E) F6 P' [Discriminant analysis, 判别分析2 h9 ~2 f T) A, e, C" z6 k
Discriminant coefficient, 判别系数
6 ` ^: b, G$ o+ j/ ?5 ]. fDiscriminant function, 判别值! G: ]. e% Z) F% H
Dispersion, 散布/分散度
* X4 ?* a$ g$ O, kDisproportional, 不成比例的
$ d+ O% G4 k; h4 R% I7 q8 {Disproportionate sub-class numbers, 不成比例次级组含量$ ?4 l) Q- ]5 i, r4 o" ~
Distribution free, 分布无关性/免分布
, M" \8 C/ M+ e7 n* qDistribution shape, 分布形状
! t4 j( |0 F$ T5 u! TDistribution-free method, 任意分布法
: P6 q' ~" k; [; pDistributive laws, 分配律8 m6 Q/ r/ R- A1 E6 F1 S
Disturbance, 随机扰动项+ {; D% z4 t9 g9 m8 w7 b _( u( E
Dose response curve, 剂量反应曲线# B3 [! u' @: e2 B' j8 ?
Double blind method, 双盲法" L3 t3 ^) f3 C l, k: M0 n
Double blind trial, 双盲试验
. M- ^8 @8 m1 c+ F" u: Y( N* @Double exponential distribution, 双指数分布" M9 S! a/ D7 A2 `# Z
Double logarithmic, 双对数1 y- T. C/ _, |% g B/ G4 s1 u2 J6 J
Downward rank, 降秩
- N6 D' c' x* {. l( X T1 b5 F: GDual-space plot, 对偶空间图& z/ }( p! w: p
DUD, 无导数方法0 p0 ~% P: w) g" J' K3 U
Duncan's new multiple range method, 新复极差法/Duncan新法
9 }3 t* C* \- B6 T ~Effect, 实验效应. s2 X/ }, _; J/ U. G, l2 H" P
Eigenvalue, 特征值
2 D4 w/ f4 L4 s2 x' g% |Eigenvector, 特征向量5 Y, `( P# z5 H) ] A8 U
Ellipse, 椭圆+ L: R3 c2 {* s- D. }/ I* R
Empirical distribution, 经验分布+ U1 k5 F' t0 J3 P4 h
Empirical probability, 经验概率单位
7 i: E# \7 s" I4 R4 o8 |' z) m2 ZEnumeration data, 计数资料: c1 M% }; {0 J% ]
Equal sun-class number, 相等次级组含量7 E6 [; b2 S3 ? {7 E# i- z
Equally likely, 等可能0 G) ^, ]8 y/ g+ U
Equivariance, 同变性
: [4 C! y: T+ J4 {, KError, 误差/错误
4 x- q# {1 }+ {5 ]% [; D0 rError of estimate, 估计误差7 o! @" l) _" M ~4 P |
Error type I, 第一类错误/ f. t( X$ J* X) Z1 I6 y" {
Error type II, 第二类错误
1 Z" m* h* x" I# B! Z1 D, Z8 CEstimand, 被估量; z6 Q" g% z+ I g1 ~
Estimated error mean squares, 估计误差均方* C+ f3 ^6 V5 |7 L" a; O
Estimated error sum of squares, 估计误差平方和! r$ a; q% r& }
Euclidean distance, 欧式距离
$ O# P5 T. ? c8 vEvent, 事件
2 C' p, _: G) J/ }( `9 ?0 b- V6 OEvent, 事件; V* d0 p0 E8 O+ s U: r7 F! z4 Z
Exceptional data point, 异常数据点. T* w/ m7 P. \
Expectation plane, 期望平面
- s. K2 p5 }, k% Z6 YExpectation surface, 期望曲面9 [9 z# \( H/ e( z. w0 n
Expected values, 期望值
- u5 E! Q/ G5 ZExperiment, 实验
) l. k- S. j- ]: O8 a8 B7 CExperimental sampling, 试验抽样
* N8 R6 z+ c: \( B8 yExperimental unit, 试验单位. c) g |( z9 W" c
Explanatory variable, 说明变量
) ^& }( `4 e+ z) VExploratory data analysis, 探索性数据分析1 O P$ M6 o# K1 [
Explore Summarize, 探索-摘要( v( W% ~1 [9 i$ C- b8 a( y
Exponential curve, 指数曲线
6 e1 B6 C9 O+ S& x0 MExponential growth, 指数式增长8 g/ i6 {$ v% c, _# e, f1 }
EXSMOOTH, 指数平滑方法 / p$ G( s# T6 F* ~0 n' W% ?5 e* q) {! o
Extended fit, 扩充拟合7 E% H# v# L5 ]7 \! Q1 J
Extra parameter, 附加参数
* P3 R- Y. q/ x2 @/ AExtrapolation, 外推法
* Y" _& O5 Z6 m; V+ Y6 yExtreme observation, 末端观测值2 E+ I1 j, u6 W* d' [) e( s
Extremes, 极端值/极值" X% D8 a' ^4 @% r
F distribution, F分布
2 v9 K' K$ u5 {) O& BF test, F检验
' a/ n; e6 E5 s, X0 |6 N6 O+ QFactor, 因素/因子
+ `; X. t: E+ g8 a5 |# dFactor analysis, 因子分析
/ F5 x2 ~+ r U8 a1 S5 c( QFactor Analysis, 因子分析
. Q" o. h# h' b9 Y+ FFactor score, 因子得分 3 [5 H" P# D- b! b, C6 \! Y N
Factorial, 阶乘
+ |8 z5 Y- n# JFactorial design, 析因试验设计
" k3 p0 ?5 L& Z+ ZFalse negative, 假阴性$ g: M" \! m8 P! D: D( O
False negative error, 假阴性错误& [- g1 o( Q, [1 i6 b+ Q
Family of distributions, 分布族% c4 @0 c+ l! t6 K! M
Family of estimators, 估计量族
6 Z1 E5 ]' b+ Z" B( k, _Fanning, 扇面6 M% Q8 J9 \0 U( A0 E3 T( Q3 h, H7 B
Fatality rate, 病死率' A: N0 a) L# |3 E. I
Field investigation, 现场调查
5 E1 s7 N& S* Q' h( EField survey, 现场调查
n' {+ I1 q( |7 o3 ?Finite population, 有限总体/ {8 {" d+ r1 B' n
Finite-sample, 有限样本
- v6 f# A1 @! jFirst derivative, 一阶导数
) [7 }; K, T4 r! hFirst principal component, 第一主成分6 P8 ~7 ]& Q3 H$ [) }0 | Y4 S
First quartile, 第一四分位数 x7 _/ R' K; o- j0 V) V5 F
Fisher information, 费雪信息量: \# O: T! s' b. x$ q+ R
Fitted value, 拟合值% y$ x4 p; w i0 z7 v) V
Fitting a curve, 曲线拟合' V0 `# z$ t8 x: X H
Fixed base, 定基
6 g. F- t- f- R+ EFluctuation, 随机起伏
- V1 e" D. I2 K4 a! \3 bForecast, 预测
8 c" d! D6 a3 }' s1 SFour fold table, 四格表
+ O5 g7 ?( f* ], R; _( J! ^2 cFourth, 四分点
+ R8 l4 ^- p8 a3 [/ zFraction blow, 左侧比率$ a# S0 ?, T% ?( Y" K) U) j% Q
Fractional error, 相对误差1 I& w) k7 r {/ F: i
Frequency, 频率
f5 o5 |6 B- _' @7 n: bFrequency polygon, 频数多边图7 N/ I& H, `4 X4 d
Frontier point, 界限点# M/ Z0 @+ B" C+ Q4 ?
Function relationship, 泛函关系
0 O1 f2 F' o4 |- ZGamma distribution, 伽玛分布
6 o' b5 R6 h; W9 c# |Gauss increment, 高斯增量
( j. F) a# P2 KGaussian distribution, 高斯分布/正态分布
( y* E0 S9 Q" ZGauss-Newton increment, 高斯-牛顿增量
& x, O. g# Q. @* q, M- hGeneral census, 全面普查
$ Q7 e2 p& o! D# kGENLOG (Generalized liner models), 广义线性模型
4 J+ V4 s# u) b$ K" rGeometric mean, 几何平均数: f N) A) V& n& v
Gini's mean difference, 基尼均差8 I) j6 ^" l8 u- A7 L
GLM (General liner models), 一般线性模型
; l8 n6 M9 Q' N- Y) Z0 O4 _7 ^- NGoodness of fit, 拟和优度/配合度
/ Z6 e3 G/ X5 ^% @" JGradient of determinant, 行列式的梯度% Y) \4 u' w: ]0 i. \9 a2 s
Graeco-Latin square, 希腊拉丁方4 E, ~* O1 y3 `* I% S2 s4 M: ?
Grand mean, 总均值: P2 Y% b$ x$ M, n
Gross errors, 重大错误
' u7 u' t3 h7 {/ m% @( D! gGross-error sensitivity, 大错敏感度0 i3 ]* |! ~' \, C* b5 q
Group averages, 分组平均5 ]4 v3 }0 A$ M6 u. x, D
Grouped data, 分组资料# X7 o" J9 h, y- u6 T4 `$ s* k
Guessed mean, 假定平均数
, B& F A$ o/ s( qHalf-life, 半衰期
" N5 W9 x; w' K l, v5 f- ~Hampel M-estimators, 汉佩尔M估计量
( i( t) }, Z- P& |5 xHappenstance, 偶然事件- `; G, y# L6 [1 O L \. D" K1 ^4 R
Harmonic mean, 调和均数
2 x, F% Y( Z; J% g6 MHazard function, 风险均数% A) U+ @& e( T ?
Hazard rate, 风险率
9 V# d# b' K- P8 |( @6 k. UHeading, 标目 # X' x: ]4 L1 x
Heavy-tailed distribution, 重尾分布
$ a' ^/ B* o% t2 ~6 Q7 f2 IHessian array, 海森立体阵: P! f! l+ x# @
Heterogeneity, 不同质
% }6 B+ ~( B+ i; _# ?Heterogeneity of variance, 方差不齐 . U. L: F$ b. T$ |6 e$ i2 t1 n" Y) F
Hierarchical classification, 组内分组+ y& {! G0 ~) }# j$ d8 \3 A5 v/ _
Hierarchical clustering method, 系统聚类法
4 M& ^7 m9 Y+ A Z( WHigh-leverage point, 高杠杆率点
5 E5 \1 T4 }, b8 z x# i$ rHILOGLINEAR, 多维列联表的层次对数线性模型
6 R5 Q; x2 m5 U) g! gHinge, 折叶点
6 h( K7 G0 o1 k; |% t/ |Histogram, 直方图- [- U0 v9 ^5 v6 m. c" y* K0 A6 O
Historical cohort study, 历史性队列研究
2 ]. e& w; }& d0 l% [/ U J8 ]7 t6 bHoles, 空洞
6 r& ]4 g: _3 Z5 i8 \" ^7 o z. jHOMALS, 多重响应分析) h5 a$ z7 w2 U+ P1 _8 N
Homogeneity of variance, 方差齐性9 |: b2 w5 ?% T3 O# P! }
Homogeneity test, 齐性检验5 U7 K: R3 @1 ]& I+ A+ u) l
Huber M-estimators, 休伯M估计量9 h! Z- @, p3 i
Hyperbola, 双曲线
" t3 N R8 ~) H8 k% Q, l4 GHypothesis testing, 假设检验
$ P$ M# p7 `- O# O* Y3 F, e* U9 ZHypothetical universe, 假设总体+ Q+ R/ ]' e* K+ p
Impossible event, 不可能事件
2 m; L8 \3 }' ?8 O: _# g# r& cIndependence, 独立性8 c9 H0 U( H: L f* m
Independent variable, 自变量
. W: t8 L7 Q# ?Index, 指标/指数
2 j* `# g$ W/ D' D: a; n4 W+ `Indirect standardization, 间接标准化法 y% @; @2 A/ T1 q
Individual, 个体& l O* B, L3 d4 J$ x/ u( ~" B5 `
Inference band, 推断带) ?* K, R* F3 ]1 S$ H8 F: L1 V3 p
Infinite population, 无限总体; c7 i4 \. Q3 M4 ~! E
Infinitely great, 无穷大; o0 ^# J' Y" |8 O: m" Z
Infinitely small, 无穷小
, ], b3 w5 I8 E/ k0 i P& i3 mInfluence curve, 影响曲线
) B6 {) ^% P+ }+ t* ]0 B% NInformation capacity, 信息容量) e; U* i( E, _9 h' O* k" }
Initial condition, 初始条件% k. O' z. Y. B! e$ Z& I
Initial estimate, 初始估计值; N. h; R7 y. L
Initial level, 最初水平
6 c9 O e- r$ n! \" ~Interaction, 交互作用
/ g( S" R$ G$ @& c- Z6 T. @Interaction terms, 交互作用项
7 d, P H% l6 H7 K) J- MIntercept, 截距- A3 J) n+ q% P* `# m4 V, x
Interpolation, 内插法: C* N6 k; \/ ]6 L" |& l+ x
Interquartile range, 四分位距
' Y* ]" _+ e' }9 r1 x! sInterval estimation, 区间估计
8 Z7 F: n; N/ u- A( kIntervals of equal probability, 等概率区间
9 `/ ] ?% g$ Y' h/ G/ fIntrinsic curvature, 固有曲率
- }* _# N& M- U/ x1 KInvariance, 不变性- n# [) p1 [8 G3 D
Inverse matrix, 逆矩阵- m( Q& T9 Q2 O2 u8 d' Y* C( ?
Inverse probability, 逆概率4 F- ~; P0 O/ X5 A; O* m
Inverse sine transformation, 反正弦变换* E, _, J, e1 K1 j2 f, O
Iteration, 迭代
6 _& n( h! F: @4 hJacobian determinant, 雅可比行列式
( \7 k i/ _! K& M& XJoint distribution function, 分布函数. U5 P. p0 J9 I% `; J6 K
Joint probability, 联合概率8 O ~9 r1 R4 C
Joint probability distribution, 联合概率分布
) h/ z* _8 ^% X; lK means method, 逐步聚类法
/ b3 g$ \1 i$ |! z( |9 S9 SKaplan-Meier, 评估事件的时间长度
2 W- U! s( v6 N1 e& \( ]Kaplan-Merier chart, Kaplan-Merier图4 I: Z& v, \; f. t( Q4 z8 w1 _
Kendall's rank correlation, Kendall等级相关
2 i. D0 s$ @- R3 K" aKinetic, 动力学$ H |: q z$ C0 _; q
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验3 t- r7 V4 l4 ~. M h
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验- G5 O% B9 W8 l' \; V9 @: \
Kurtosis, 峰度7 I" `; F [, p5 E/ b! A% h
Lack of fit, 失拟
! J+ w- K9 _) [1 K2 s3 CLadder of powers, 幂阶梯
' x1 A9 b3 S5 J- z! F, G9 }Lag, 滞后3 b* Q- y) ^6 t* N! V. M$ E5 M8 V
Large sample, 大样本& _ m* ~. \8 [! f# f) X. m
Large sample test, 大样本检验/ e0 K8 F/ x1 J" }) F- n
Latin square, 拉丁方. Q& e' j5 h5 [) w3 J
Latin square design, 拉丁方设计% e% \0 X8 H. s" P
Leakage, 泄漏
5 J8 r& P( B/ A7 ?/ a1 rLeast favorable configuration, 最不利构形
- M2 c1 C, F) o9 S2 |( ^* y- CLeast favorable distribution, 最不利分布: x5 @4 J9 J y, M
Least significant difference, 最小显著差法
: i: ~" Q+ y! X/ V9 O5 h; rLeast square method, 最小二乘法3 Y0 z9 d. }. i( C
Least-absolute-residuals estimates, 最小绝对残差估计
. e; s0 c9 z0 Q- g6 R. dLeast-absolute-residuals fit, 最小绝对残差拟合
3 K+ Z, P3 X8 J6 I. }% z1 SLeast-absolute-residuals line, 最小绝对残差线1 V) q4 \9 R- t( K, f* ~5 B9 B
Legend, 图例- a: L, q; x1 w6 V8 j8 F& p
L-estimator, L估计量
) W* L1 A% j" A' XL-estimator of location, 位置L估计量
; a7 V5 l5 t( S, d* l% YL-estimator of scale, 尺度L估计量
" m; F4 A# \% tLevel, 水平
' c1 K6 k2 D( A! @* VLife expectance, 预期期望寿命8 V7 H# U$ O5 W R
Life table, 寿命表
( g! k. Q D- x) C" L$ k- P% S; kLife table method, 生命表法
" z& a }' O5 `) f) bLight-tailed distribution, 轻尾分布7 P& }- l2 B0 b U* f4 d+ ?
Likelihood function, 似然函数
0 y \) ?8 Q- [! oLikelihood ratio, 似然比
8 r ^& s' a" l9 n& m% s1 oline graph, 线图
0 u, B9 q& ^( S6 V" SLinear correlation, 直线相关0 W* W* j+ F% @& K5 s! e7 A* D0 k
Linear equation, 线性方程
7 i& @0 B6 ~/ f2 q# hLinear programming, 线性规划1 e/ _6 y+ z! ^ U0 O$ F1 V
Linear regression, 直线回归+ z* E, R! }0 g2 C" r! s* ^; d
Linear Regression, 线性回归$ Q* U9 u. D2 G. _& m8 l, c
Linear trend, 线性趋势
# l# L- t/ J. V% O% \% ~9 VLoading, 载荷
/ P8 L4 V6 G9 }& w' D" H9 F" yLocation and scale equivariance, 位置尺度同变性0 `& R# ~* }1 n# ]. s5 t/ D% Y M
Location equivariance, 位置同变性1 S! J; M! c- x
Location invariance, 位置不变性# c2 Y2 c/ [5 S5 |+ e! `. i, Y e
Location scale family, 位置尺度族* c4 ^+ N, o1 i* r6 }% T
Log rank test, 时序检验 + @) z ?% b1 P
Logarithmic curve, 对数曲线
: a/ ?* [( B5 w/ qLogarithmic normal distribution, 对数正态分布" b$ c' ?% y: e$ v) P
Logarithmic scale, 对数尺度" A0 j2 a5 t! s g4 `
Logarithmic transformation, 对数变换4 Z2 b4 _8 C6 U; T# m& C
Logic check, 逻辑检查, Y* o/ N7 j3 x! |) }* M. Y
Logistic distribution, 逻辑斯特分布
7 C' e' c+ ? q/ Q5 f! _4 R& ILogit transformation, Logit转换% V, V2 f' ? b# d
LOGLINEAR, 多维列联表通用模型 / o6 J+ Z s. |% Y m
Lognormal distribution, 对数正态分布( z8 U. u) I, J
Lost function, 损失函数
8 t* T* v% a* x$ ^Low correlation, 低度相关
. V& ^7 Q' J8 s7 a) _+ hLower limit, 下限
O" z3 Q. s% D3 q' f/ k! T' m( R- VLowest-attained variance, 最小可达方差
& X1 |8 H& K- ]( u5 [+ @LSD, 最小显著差法的简称% \1 o/ x5 _9 e' S
Lurking variable, 潜在变量% n3 D% W' P: V2 l) a1 F6 F; ?* Z! q
Main effect, 主效应6 c0 a/ S& k: n) o
Major heading, 主辞标目
: e+ R. I: f5 t5 C2 TMarginal density function, 边缘密度函数 n9 e& y+ s: l2 q
Marginal probability, 边缘概率7 n2 ^9 }* D! b" }$ W
Marginal probability distribution, 边缘概率分布6 [5 M( y) c; R
Matched data, 配对资料* G6 G, A+ x/ @. x: Z
Matched distribution, 匹配过分布
+ q( O& R4 k( h8 D1 G6 EMatching of distribution, 分布的匹配
/ s# m6 H! [0 |6 e6 A/ u+ LMatching of transformation, 变换的匹配0 f% M5 }+ y% U; t3 j2 ~5 _5 M
Mathematical expectation, 数学期望. k1 K" R& V/ `1 X2 n' ~6 _
Mathematical model, 数学模型" I0 z) _1 l7 X V3 u
Maximum L-estimator, 极大极小L 估计量
& c" F/ n& p/ H, tMaximum likelihood method, 最大似然法5 H7 y0 E% F! G% y
Mean, 均数( o+ i6 K- i4 C) I- ?1 ~, [1 t/ P( Y
Mean squares between groups, 组间均方 c2 J2 |/ Y6 z6 a7 h
Mean squares within group, 组内均方. h6 J% I3 _! Q+ F# t2 a4 @
Means (Compare means), 均值-均值比较* M' C5 Z( I: k5 B& z
Median, 中位数9 d9 q" {0 J# K$ D2 k
Median effective dose, 半数效量2 G# G9 `+ {, `
Median lethal dose, 半数致死量 o' z+ g( W- ?
Median polish, 中位数平滑- r0 L( F$ I8 M; ?5 j
Median test, 中位数检验2 f+ k4 J* n. `& p, b B+ r
Minimal sufficient statistic, 最小充分统计量+ |* Y. t0 u7 a( q: E9 j6 Y2 C i
Minimum distance estimation, 最小距离估计
& K9 {1 |- H/ y- NMinimum effective dose, 最小有效量2 I; E6 E3 r- {" J1 F$ h
Minimum lethal dose, 最小致死量, b. W5 K# M% N8 M
Minimum variance estimator, 最小方差估计量
6 n+ p6 J" S, z" N1 DMINITAB, 统计软件包% ~4 B7 ~* x2 g; O4 L
Minor heading, 宾词标目. O% f$ {5 B( T4 u9 i
Missing data, 缺失值
% M7 s: u; c5 Q# Y) K( t0 BModel specification, 模型的确定
4 Q6 O. k7 N* X8 D6 @4 \Modeling Statistics , 模型统计
6 X% S ~/ z2 v6 ^2 J1 ]# L% @# mModels for outliers, 离群值模型1 f% }' C4 w) n5 y1 \) j: X
Modifying the model, 模型的修正( o9 \8 g7 _8 u4 R: I$ l
Modulus of continuity, 连续性模
% S3 D5 p8 Q) zMorbidity, 发病率 : ]7 ]7 V% d/ G) V$ f/ _$ \
Most favorable configuration, 最有利构形
* X# ~: N; c5 i5 mMultidimensional Scaling (ASCAL), 多维尺度/多维标度' R. W- j! d: J1 L
Multinomial Logistic Regression , 多项逻辑斯蒂回归
. ]: z: C# D* F: X: jMultiple comparison, 多重比较% ]+ N/ E; s0 q
Multiple correlation , 复相关 X- V* |# P' s
Multiple covariance, 多元协方差: N9 U. x7 ^% `' u P6 r+ ^
Multiple linear regression, 多元线性回归- |+ R" q* l& h
Multiple response , 多重选项
- W4 T! q0 U2 U9 rMultiple solutions, 多解
& u+ n( x8 U; J$ I6 i% a* ?Multiplication theorem, 乘法定理
, @. [$ u g( a& f# N& a% ZMultiresponse, 多元响应
4 E4 C4 B$ t3 x. I1 Q/ n& v' rMulti-stage sampling, 多阶段抽样
6 T$ P& S" R; W3 }, P8 tMultivariate T distribution, 多元T分布
$ U& ~* j0 |% v' ~& p3 I# LMutual exclusive, 互不相容
6 e5 ?% e" F, Z* QMutual independence, 互相独立
4 h$ I6 g& {! F8 N4 n* nNatural boundary, 自然边界
9 Z2 B9 `, E& b. `& ~Natural dead, 自然死亡
1 o u8 p2 L; r2 H6 oNatural zero, 自然零8 K) t0 ?5 H: F# A9 d5 m1 y/ L
Negative correlation, 负相关" m! g- A& b# L: S2 K0 _9 S
Negative linear correlation, 负线性相关
# D/ D1 g! V% H5 Q; k* hNegatively skewed, 负偏2 b( f3 q4 s6 F
Newman-Keuls method, q检验
5 t- r4 u' _ ?) f; |0 FNK method, q检验5 Q7 {8 E7 X6 s! o. X4 ]: q
No statistical significance, 无统计意义" ]& S8 s* o/ {0 ?4 s) d
Nominal variable, 名义变量
7 K& X x4 S+ s$ H! kNonconstancy of variability, 变异的非定常性
2 Q8 n2 U0 G( |$ m$ G" i* PNonlinear regression, 非线性相关3 J! c* W2 [; \* ]- D0 S4 d# n
Nonparametric statistics, 非参数统计
8 i+ U" R: H* q. XNonparametric test, 非参数检验4 X6 M. [3 z% h( N9 i/ ^
Nonparametric tests, 非参数检验: i% o5 R, J+ C: E& i
Normal deviate, 正态离差7 a' q% y. B* A% V& y6 G- @
Normal distribution, 正态分布" j0 z3 f' S9 }* |. V
Normal equation, 正规方程组1 `$ u& j$ P) D: Y$ z' c
Normal ranges, 正常范围, Q2 P5 m( X0 v& k* }% r4 z; C
Normal value, 正常值# x+ ~, V7 y8 G
Nuisance parameter, 多余参数/讨厌参数
" A# p* ]$ f* L; C% m- j& BNull hypothesis, 无效假设 + `: G8 w. a9 _% i. [) o: n* S( k
Numerical variable, 数值变量6 |, B, `# W/ |6 x* G
Objective function, 目标函数$ y v1 p3 |9 [) t
Observation unit, 观察单位% W6 Q. k% j" t
Observed value, 观察值
8 o' r& [1 _: t9 P0 b# q8 zOne sided test, 单侧检验2 d8 G1 C5 g8 Q5 H, Z; u
One-way analysis of variance, 单因素方差分析& G: x" G" T7 x0 F4 O# i$ a1 g9 N
Oneway ANOVA , 单因素方差分析
/ ^+ \ z: \* E- oOpen sequential trial, 开放型序贯设计
. r2 H9 l+ w4 E" W& GOptrim, 优切尾: G6 W) X/ _5 }4 d; Y
Optrim efficiency, 优切尾效率
$ z: [- p9 |, l2 o# `Order statistics, 顺序统计量
" G9 `; ]) [4 F2 C8 x- S' {, ]Ordered categories, 有序分类. C4 j! d& D% B" v. ^
Ordinal logistic regression , 序数逻辑斯蒂回归' f% ~& ?) x( G3 y/ U: l) `
Ordinal variable, 有序变量
; ]; P' z4 \3 m' x4 d1 xOrthogonal basis, 正交基4 n7 J z" C7 g% f: l1 ~/ Y
Orthogonal design, 正交试验设计" C8 l3 N0 T( G& p5 B3 o( p
Orthogonality conditions, 正交条件
* G3 \/ ], Z5 a; p# e, VORTHOPLAN, 正交设计 , ~; s1 F! W4 c% |" y
Outlier cutoffs, 离群值截断点
0 S$ R. U# Y$ @* _6 EOutliers, 极端值/ u9 e) k( u+ T: Y
OVERALS , 多组变量的非线性正规相关 ) A$ o- N( ~& [
Overshoot, 迭代过度: a$ v2 [9 g! A6 S
Paired design, 配对设计7 \8 L0 D& z+ M4 a3 \2 [
Paired sample, 配对样本& _( c) O- X6 y0 H4 A
Pairwise slopes, 成对斜率
1 j& g+ a( A# D4 b' w% W. r! UParabola, 抛物线& F4 f6 {0 q: R1 Z
Parallel tests, 平行试验+ [2 D0 t1 n5 B) ^1 S
Parameter, 参数
p% a Z" F1 J+ `& D' VParametric statistics, 参数统计! M1 e" l2 x1 b% Z0 `# S, n
Parametric test, 参数检验9 t2 d& q: O' n0 v
Partial correlation, 偏相关- o+ `2 I% }9 z l% N
Partial regression, 偏回归8 `4 v" |8 p1 o8 X4 J
Partial sorting, 偏排序$ |% t$ d$ ~4 N3 @3 \0 v
Partials residuals, 偏残差
' K, Z5 e( ?" ~ p1 A$ e; ]Pattern, 模式& L$ T Z7 {+ _9 Z
Pearson curves, 皮尔逊曲线% z7 G' a" ]3 N* h
Peeling, 退层
6 V6 O2 |1 Y0 B* Q' {: s" _4 ]4 mPercent bar graph, 百分条形图
! \8 X: x. V+ |5 p0 U7 I! J5 QPercentage, 百分比
' v: o6 D9 G2 n* B- [$ E. ePercentile, 百分位数2 s5 C# z1 l, C5 {# f0 p
Percentile curves, 百分位曲线& Y; U9 \8 T+ x. x& d, i+ t
Periodicity, 周期性& V, Q) x4 T3 p
Permutation, 排列; g- W0 D8 M+ b: T* T8 N. y
P-estimator, P估计量4 l7 T7 r) l3 g. M6 A5 N1 ^7 @
Pie graph, 饼图
1 I6 J( f) b ]3 k aPitman estimator, 皮特曼估计量
3 K1 h) h! Z' O' ?- CPivot, 枢轴量
- K* `) W3 d5 J# u; ^, ~$ m# w( ?Planar, 平坦
- ?# q: k9 F4 l( X# dPlanar assumption, 平面的假设
6 |: [8 ]; I( |: e: s, aPLANCARDS, 生成试验的计划卡
/ E, D! J s1 Y' zPoint estimation, 点估计
. e4 p! A: L/ M" I; U( ZPoisson distribution, 泊松分布6 d5 M8 H2 N; `4 y. a; r
Polishing, 平滑. _/ n1 ]2 K# v2 I; d2 z6 C
Polled standard deviation, 合并标准差
8 q3 [# A- i9 S# Z- o BPolled variance, 合并方差% E9 Q4 Z T( R# a% @3 ]$ d- q
Polygon, 多边图
+ E& N0 B! a$ M; B6 j0 I; KPolynomial, 多项式2 P, h3 l; l6 F2 M# h5 s8 s
Polynomial curve, 多项式曲线6 C. @) `9 E. M: S: j
Population, 总体
" T& F$ B. B S2 ~Population attributable risk, 人群归因危险度: b1 z, T" @; I- e9 @6 f* r
Positive correlation, 正相关: C! a" U4 i: t3 T$ T8 h
Positively skewed, 正偏5 e* J6 N6 [/ P9 |2 r6 y& N
Posterior distribution, 后验分布# P# ^+ c. z2 w& ?
Power of a test, 检验效能
9 J5 i5 b4 V; \& ]7 s& T" b' |3 vPrecision, 精密度+ U' E3 |2 A3 z; H+ S# @6 u# }
Predicted value, 预测值4 F3 C1 l1 y1 T) n; w4 n
Preliminary analysis, 预备性分析: g0 b* @# c5 `/ E5 P
Principal component analysis, 主成分分析
' Z6 V; H% g( b& gPrior distribution, 先验分布. m) f0 U" l7 n }% r
Prior probability, 先验概率
6 K9 Q4 ^3 H# ~# Z7 t7 tProbabilistic model, 概率模型2 t, D8 |4 m* n) r$ Q9 z
probability, 概率3 d; B- {4 l; n* K, T& ]! f: L
Probability density, 概率密度
. ]$ W* \- \+ I; `- i2 KProduct moment, 乘积矩/协方差
! D5 G: `( P7 h' }0 \; SProfile trace, 截面迹图5 `; X$ t d2 Y/ ~& [+ g- o
Proportion, 比/构成比
: q, t$ L* B9 GProportion allocation in stratified random sampling, 按比例分层随机抽样3 S* z2 J1 d: z- x0 G9 ?: ?
Proportionate, 成比例1 W# i5 ?- ?( E3 P$ B# C; K
Proportionate sub-class numbers, 成比例次级组含量
- i1 H! j9 q- \0 ]! y$ WProspective study, 前瞻性调查
$ ^: t5 ^" F# d# V3 ~3 j0 KProximities, 亲近性
& b3 l; g' j+ K1 n9 d4 g+ aPseudo F test, 近似F检验) f1 t6 u6 x6 ^' T
Pseudo model, 近似模型
+ O, m9 A; k6 {Pseudosigma, 伪标准差
- G3 C/ P% Y4 z" E8 `; u* zPurposive sampling, 有目的抽样3 O5 b2 D* F" Q1 V! q
QR decomposition, QR分解
: E" I7 x% i8 R1 Z% m$ TQuadratic approximation, 二次近似- x5 w T1 T$ `
Qualitative classification, 属性分类: i$ v6 n5 o' a
Qualitative method, 定性方法+ u; v7 C: q' L9 i) S2 y
Quantile-quantile plot, 分位数-分位数图/Q-Q图
- G5 D& s, y6 {2 ? f; ^Quantitative analysis, 定量分析
4 J: Z/ s8 j, k4 d. aQuartile, 四分位数
1 R) z& ]0 F' U0 W; MQuick Cluster, 快速聚类
0 i9 j3 b7 g" sRadix sort, 基数排序) L! }7 F4 @9 D _
Random allocation, 随机化分组
4 {- E3 \ I6 W2 Z! [5 C( KRandom blocks design, 随机区组设计; T+ Z. z7 ^5 o
Random event, 随机事件. {8 S" s$ U+ w; d# v
Randomization, 随机化 y( h7 M% \4 k
Range, 极差/全距+ L; _2 G3 L: p) w3 Z4 v5 d' m
Rank correlation, 等级相关
+ C( A$ M, v F: f; ]Rank sum test, 秩和检验7 m/ _# W$ {: u" R# @0 D/ F. u3 i
Rank test, 秩检验
7 q. F+ b4 o# ^+ ^* r1 ZRanked data, 等级资料' u* s; i* Q7 z* V" {
Rate, 比率, Q8 Y+ O8 j3 x6 \
Ratio, 比例6 t n3 o: Q8 A( Y& T* r# H& X
Raw data, 原始资料
% {# l0 X2 @: u7 n* HRaw residual, 原始残差% E5 D7 R- T1 J( Z% X! K
Rayleigh's test, 雷氏检验
[) E8 R8 e, F7 CRayleigh's Z, 雷氏Z值 * ], a0 }0 |9 T4 I
Reciprocal, 倒数
7 U8 _+ B, l5 E/ L( ^Reciprocal transformation, 倒数变换0 o9 Z9 ^$ F: C @
Recording, 记录
4 Z1 L; v$ O+ u5 ^) w# K6 D- }Redescending estimators, 回降估计量% A; \5 ?7 v q
Reducing dimensions, 降维
# L3 a+ O" F1 @) j1 O0 Y% H2 LRe-expression, 重新表达7 z6 R3 O% b( D0 T2 {5 i3 U
Reference set, 标准组 W; E5 o+ K5 h% j% D" y
Region of acceptance, 接受域
- {/ m) W, N9 `) ~% J" u sRegression coefficient, 回归系数4 g) l* D a4 S4 r
Regression sum of square, 回归平方和. l$ W7 [! G, j6 I
Rejection point, 拒绝点
3 Z9 h0 R" i% i! s0 S kRelative dispersion, 相对离散度7 Z' ?$ y$ }% r* A1 ?& Y9 A- `
Relative number, 相对数
! r' E9 H/ f- o, j- UReliability, 可靠性 E% R/ B! J, m" R6 n
Reparametrization, 重新设置参数
# W1 g* u- [- P, q% eReplication, 重复
) K1 r. v- D: {' BReport Summaries, 报告摘要
0 u0 e3 r# F4 ~) L2 dResidual sum of square, 剩余平方和
' w; k- }0 h* n+ I9 c3 Q# wResistance, 耐抗性
) e' K2 Q8 I1 X" cResistant line, 耐抗线
/ a$ P# G, h* XResistant technique, 耐抗技术% H! Y$ k% t. G B) I/ C
R-estimator of location, 位置R估计量$ i0 s1 N! k+ l! t& Q. P
R-estimator of scale, 尺度R估计量# u9 j( \- K8 u3 {7 A5 p |, G
Retrospective study, 回顾性调查
. I3 n% n1 s4 v0 S4 ?Ridge trace, 岭迹
6 ^, ?* l3 g! p$ `. }8 hRidit analysis, Ridit分析; ?# \) S; R: w3 i& I2 J, X
Rotation, 旋转' j3 ~2 a c" U' A+ U
Rounding, 舍入
& i4 X$ Q2 u8 b1 ?2 o bRow, 行
) M& D: i% [' ~! @" o$ t! E5 Y. |Row effects, 行效应8 d9 Z: ^, S0 x: U% M! c4 Y5 U& C
Row factor, 行因素* c! I9 T& S {( |$ _
RXC table, RXC表
1 s/ \6 G0 d! x/ Z+ L+ M+ `3 E- OSample, 样本
( ^0 G* Z( J$ @( r! fSample regression coefficient, 样本回归系数% H ~$ ?4 l& Y3 i2 q4 h) m
Sample size, 样本量5 B! U& G' z# z6 E# S4 C5 Y
Sample standard deviation, 样本标准差, \& f) J4 y, \1 P: {
Sampling error, 抽样误差. I% B; _& A# c9 B
SAS(Statistical analysis system ), SAS统计软件包1 g2 h8 B2 X H/ w0 u
Scale, 尺度/量表
9 E8 n6 U( C$ U/ m3 h* y. y/ CScatter diagram, 散点图
8 D$ |9 C- h4 i( w: ^* Z0 }: uSchematic plot, 示意图/简图* ~+ I$ t3 [6 H' V9 ?# h* j8 F) ~2 T9 B
Score test, 计分检验! I- x7 f' D% r7 }( F0 o( z
Screening, 筛检, ?5 G0 w7 c0 k+ v, L4 v
SEASON, 季节分析
+ n9 O/ b5 b" E* O; ?) MSecond derivative, 二阶导数
" p8 p/ @# {" c% M) QSecond principal component, 第二主成分) N% u/ K! g$ ~& j1 P6 U
SEM (Structural equation modeling), 结构化方程模型
5 m: U: E" Y: D4 nSemi-logarithmic graph, 半对数图1 ]$ A( ]( U+ b3 z/ B: `( }
Semi-logarithmic paper, 半对数格纸
' q ~/ q. r3 |$ ~Sensitivity curve, 敏感度曲线: o# [. ^! `4 O6 B ?+ \
Sequential analysis, 贯序分析
6 E0 e9 d. K& ySequential data set, 顺序数据集
& h3 l7 l" E- u( D# j: GSequential design, 贯序设计/ x$ x: W! i: `4 P- h8 i
Sequential method, 贯序法+ ^" V7 y$ c' N7 E, f
Sequential test, 贯序检验法3 `7 Z z! o" N- |
Serial tests, 系列试验
4 i4 P+ m! _ c VShort-cut method, 简捷法 ; n5 u, S9 N) X4 j* J
Sigmoid curve, S形曲线
) E+ G8 f. @4 W. o; X& K2 k' \Sign function, 正负号函数
& k8 j2 q2 d& h m6 WSign test, 符号检验
; e2 J' n) g. `1 c$ U h& y2 ZSigned rank, 符号秩
5 e" A4 L2 C3 ?/ B# |- CSignificance test, 显著性检验
. b% X( [# l0 j8 p6 g" ySignificant figure, 有效数字
# k! i2 ~8 i! E( ]! j" }% y) QSimple cluster sampling, 简单整群抽样
9 D8 E; ~1 e; ?Simple correlation, 简单相关. F( ^% x4 Z' a o, l
Simple random sampling, 简单随机抽样
1 n5 n2 G+ l4 v3 N1 BSimple regression, 简单回归
# B6 J4 B5 J* a5 z- f" |simple table, 简单表
2 ~0 D5 `- f& t; sSine estimator, 正弦估计量
! I4 m9 \" {- B& hSingle-valued estimate, 单值估计
8 Y! J) h0 W5 L( d6 F/ d* H/ y4 {! e* ySingular matrix, 奇异矩阵) _8 ]4 l& B2 Y/ i
Skewed distribution, 偏斜分布; M) @+ x ?; c) B$ E: N$ c
Skewness, 偏度
X; o( I( r7 R* l6 tSlash distribution, 斜线分布
& h: A# I: D" U2 u- d) H- PSlope, 斜率- \( U1 Y7 {9 L( k2 M6 p: Q; [1 u5 `
Smirnov test, 斯米尔诺夫检验& V# M3 B7 M; r( |# s/ R
Source of variation, 变异来源
3 H1 V/ v i3 \* K: j& Q! p# bSpearman rank correlation, 斯皮尔曼等级相关, t% j# ~. O2 ~$ M
Specific factor, 特殊因子* G% i6 R( B0 C! W @2 T- g
Specific factor variance, 特殊因子方差' }8 I! n+ P& \1 ?2 R( h
Spectra , 频谱
, [- d n) ^6 m" |( b. p1 vSpherical distribution, 球型正态分布
0 G4 N7 a' R; V$ r# e5 L& ]Spread, 展布
# G- x0 ?+ \8 n( {SPSS(Statistical package for the social science), SPSS统计软件包
; ]" @8 h5 i5 S" ?8 W8 G9 b8 zSpurious correlation, 假性相关2 _3 c7 Y+ a; S9 Y, L: S
Square root transformation, 平方根变换+ p! Q5 N- Q) R# K9 |' C
Stabilizing variance, 稳定方差
/ ?. \0 V: P* }Standard deviation, 标准差
7 g5 K# B8 j* NStandard error, 标准误
% G" C* w$ `: DStandard error of difference, 差别的标准误' H9 ]* L6 J9 r! K0 |
Standard error of estimate, 标准估计误差0 [. [( n: ~7 k" Z$ u" f
Standard error of rate, 率的标准误
0 Y8 n! q. _2 p3 LStandard normal distribution, 标准正态分布8 V0 f+ f; n2 W
Standardization, 标准化3 n4 E0 Y m9 h, D
Starting value, 起始值' I5 Q# l8 q9 Y4 _. B: ^$ z8 u* j9 u, i
Statistic, 统计量
! Y; ^; m' n1 G tStatistical control, 统计控制
; ~1 ?2 V8 @3 _8 V$ b+ eStatistical graph, 统计图
# W0 [1 a/ e& [6 Y$ D# \. E/ {Statistical inference, 统计推断
) `7 [8 j+ O% [* @0 F. FStatistical table, 统计表3 {2 {% Y, O5 R) j) n! T6 s
Steepest descent, 最速下降法: `, H" P- U! }4 v' h4 N
Stem and leaf display, 茎叶图
) i4 _1 m, ?: c5 W* NStep factor, 步长因子
) c% B5 N, ]' ?$ m; N6 ^Stepwise regression, 逐步回归
# ~$ \3 B4 v& a2 g' L; [" _# C7 H; \Storage, 存
+ k) \, ]1 \ {1 G EStrata, 层（复数）
+ Q* ]9 O2 g. x8 O! b4 x. IStratified sampling, 分层抽样' ~5 j+ E5 @2 S: R2 m7 m" ?. Z/ T1 l y
Stratified sampling, 分层抽样/ ^/ C" q8 ^. U3 h
Strength, 强度9 A* n& R+ F0 } d% y% r) L' L
Stringency, 严密性
, n6 u6 R! J" I( t) ^/ }Structural relationship, 结构关系# j3 V1 U( a. K2 l, {# ~
Studentized residual, 学生化残差/t化残差, V B6 J$ G( \( E
Sub-class numbers, 次级组含量' X4 C7 m- s5 s# V( e
Subdividing, 分割9 `$ @0 q0 i+ s" R% d# _+ B
Sufficient statistic, 充分统计量
) p: Y, m8 a1 {! ]4 S' |" hSum of products, 积和) z" y; b& Z+ {" H' y, ]2 q
Sum of squares, 离差平方和
. t+ Z" Z2 }: G% S( ySum of squares about regression, 回归平方和
( D/ @& Z6 [( Q) n; _+ g' i, T$ \Sum of squares between groups, 组间平方和
6 L+ s; L* Q! M% ~! Q$ hSum of squares of partial regression, 偏回归平方和1 o1 J! C! A/ H% q. E
Sure event, 必然事件$ a8 ^* Q/ h$ m8 a
Survey, 调查1 x$ u+ G! b/ ^* x7 f5 |8 {/ ?6 ?
Survival, 生存分析
& {, W! }& O! [% ~6 ?; GSurvival rate, 生存率% T; r- I# O1 V$ n- p
Suspended root gram, 悬吊根图, L6 S, w- ~$ P7 ^
Symmetry, 对称4 W- ]1 t8 Z, c7 o1 e
Systematic error, 系统误差+ t& r# s0 \+ b& K8 ?
Systematic sampling, 系统抽样7 i) W. j9 K2 z3 m- A$ c/ h( {
Tags, 标签
5 l% h* L, S# ZTail area, 尾部面积+ G$ B% Q* m" x" u, g3 ?2 `
Tail length, 尾长- A, H# M/ v1 {( i C3 @+ L" H
Tail weight, 尾重8 M9 {2 \1 z# k" A8 s
Tangent line, 切线
8 U. I" F7 k0 j$ T; k. m6 _' @: yTarget distribution, 目标分布
( ]% f2 d) B8 K- M5 _- S: eTaylor series, 泰勒级数, P) u9 t* t5 ~: \
Tendency of dispersion, 离散趋势
0 p5 S5 v9 B% D) ]* Z, ETesting of hypotheses, 假设检验
- `" f9 u* ]4 q9 m7 LTheoretical frequency, 理论频数
4 O) ~2 y1 L8 p# o& w0 H- QTime series, 时间序列
* M6 f9 t `4 Y- W- z! {0 oTolerance interval, 容忍区间
4 h9 B$ B) }4 U7 U7 @! n3 l8 ^0 ?Tolerance lower limit, 容忍下限( j5 c# a" C3 E6 e: f0 K
Tolerance upper limit, 容忍上限0 m$ z4 r7 R) _1 e
Torsion, 扰率4 h6 r9 @- z8 t, S# g$ ?+ Y
Total sum of square, 总平方和/ J8 X0 O. T6 N B5 ]+ a
Total variation, 总变异, x7 @$ j' q+ {" ~8 d5 } r# D8 C& n! {
Transformation, 转换
; [) r. ?9 W, g+ X& b* \Treatment, 处理
4 H F2 n; i r1 ^' vTrend, 趋势: j4 r# Y2 w h4 O+ R
Trend of percentage, 百分比趋势- G! u! h" j% }$ z% E' W& `! q
Trial, 试验0 q9 h- S% e% o d* D
Trial and error method, 试错法6 C1 [ f3 n! z7 A6 Z+ |
Tuning constant, 细调常数 s+ C, V' Z4 e- w$ I+ Z0 [% Z
Two sided test, 双向检验6 M, r4 _& Q6 I/ M( G
Two-stage least squares, 二阶最小平方( X* q" \6 C: c: C0 N) m
Two-stage sampling, 二阶段抽样9 Z$ W5 r! g% j+ X8 _; ?$ n
Two-tailed test, 双侧检验
7 B9 ]$ ]$ d, pTwo-way analysis of variance, 双因素方差分析9 A$ W! U: t1 j0 o- X; O) t& l! b
Two-way table, 双向表% B2 |, K" _7 v; E5 C
Type I error, 一类错误/α错误
$ `$ e; ^7 F7 r/ i" c3 L5 nType II error, 二类错误/β错误 a: J/ Q. B0 k' x1 L
UMVU, 方差一致最小无偏估计简称8 i3 {2 B4 v5 w0 v% T0 V% |7 e
Unbiased estimate, 无偏估计5 j8 ~+ u! C+ ^1 K4 c6 v0 j
Unconstrained nonlinear regression , 无约束非线性回归
3 u2 A3 a# h7 H: n9 x) ?* |) _Unequal subclass number, 不等次级组含量
" r, g: N; B; P- D+ U) A' sUngrouped data, 不分组资料3 I, Q1 v" i) Y. K) U+ @: m" P- D
Uniform coordinate, 均匀坐标; z! q, {7 F1 J1 [- O; y
Uniform distribution, 均匀分布
0 {' _9 V, ^; [Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计. s3 o2 P) S* } w; r/ f/ [
Unit, 单元" @: B& f7 P2 ]7 C! P( R* C" s
Unordered categories, 无序分类/ v7 O/ Y* m! Z- ?) U# `
Upper limit, 上限
2 U' P0 X8 n* n- nUpward rank, 升秩) g( G6 @. O) c+ G
Vague concept, 模糊概念
0 i( ]3 i" b& I9 L8 WValidity, 有效性
' |) Z) y- Q) mVARCOMP (Variance component estimation), 方差元素估计
3 L' e8 N* x# b% L+ e% q- cVariability, 变异性( @: ?) \4 G7 O `1 v# {
Variable, 变量
1 t, b" g" ^( f3 r1 u' J$ rVariance, 方差
# l n. M; ?8 B1 HVariation, 变异, t" V! `" p* z1 e+ h* n3 W. l
Varimax orthogonal rotation, 方差最大正交旋转
+ r8 M" h' }2 e0 f3 ]Volume of distribution, 容积
0 U. c% w7 d5 o s, x( D3 T' {W test, W检验
( |, S7 B j3 q' V6 `: UWeibull distribution, 威布尔分布
7 l; C* V: z, h4 k# _Weight, 权数% m8 V' [+ g0 K) R; X0 A
Weighted Chi-square test, 加权卡方检验/Cochran检验! H) [, B: C2 e3 `% b+ n
Weighted linear regression method, 加权直线回归
; Q8 X$ ]0 P+ DWeighted mean, 加权平均数
/ m6 D0 r& y3 M) E( J/ k6 vWeighted mean square, 加权平均方差
, N* {$ H, y( h- h0 t/ n/ J/ |6 |Weighted sum of square, 加权平方和
* Y3 S5 o# M( E! zWeighting coefficient, 权重系数: X1 Z4 A y, o7 T2 B3 a
Weighting method, 加权法
4 p( M) f% G% LW-estimation, W估计量
# ~6 X/ X. r+ L5 J q; r PW-estimation of location, 位置W估计量5 ~0 P, g- y2 _' N2 b8 t# z0 m
Width, 宽度2 l* T3 n& `# r
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验8 M& i7 \& m) c
Wild point, 野点/狂点
2 e( P* H& b9 d- {3 |6 ?Wild value, 野值/狂值/ p, h9 o7 J9 {2 [# K
Winsorized mean, 缩尾均值7 m/ r" o: q: F& s3 K
Withdraw, 失访 ; {, k% a2 {+ {
Youden's index, 尤登指数$ ^$ G- S; w3 d4 r+ o" y
Z test, Z检验9 f$ s# G5 X2 {5 u1 @: G
Zero correlation, 零相关
, r4 R: I$ G: a4 j$ S- M: b8 J' EZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
