|
|
Absolute deviation, 绝对离差" o9 Q, d9 [5 \) L9 [3 x' ~
Absolute number, 绝对数
$ p+ r8 }) U/ O6 Z/ y; |Absolute residuals, 绝对残差
2 \1 ` }3 a* F/ `Acceleration array, 加速度立体阵5 T, F% r. }# n. X) h8 Q% n
Acceleration in an arbitrary direction, 任意方向上的加速度. f: p0 v, V; [" G E% x! ?0 l0 e2 a
Acceleration normal, 法向加速度* \* q0 O! a1 _. H% S- h8 R8 o
Acceleration space dimension, 加速度空间的维数# @ F6 ^$ K; P
Acceleration tangential, 切向加速度( S4 M. F1 I8 r9 n/ x
Acceleration vector, 加速度向量
4 m1 M, _ l( @+ @' `1 sAcceptable hypothesis, 可接受假设
. ?$ [+ P: s ]7 B) `5 fAccumulation, 累积9 S9 @. R* {: ] y* e
Accuracy, 准确度
. M; T# E! r- o; U$ XActual frequency, 实际频数; R( u9 |( O2 m& Q: A) {/ k2 a
Adaptive estimator, 自适应估计量" t; P2 k8 p( g W3 Y8 `7 O
Addition, 相加
! W+ z- u0 X7 }# }7 y) p' y7 NAddition theorem, 加法定理8 S# ?* c4 `2 p
Additivity, 可加性2 w1 u; t) S- G; L8 ~! s3 V
Adjusted rate, 调整率4 G1 B3 r) y$ ?) Z& U1 @# c1 y' r
Adjusted value, 校正值
" B% W+ L( Q# m0 U7 d! V% jAdmissible error, 容许误差/ X$ [7 u" }5 W
Aggregation, 聚集性# R! ~% T" A$ A' K) [2 c$ u
Alternative hypothesis, 备择假设! f7 w9 G% h0 W+ w2 D9 S' H
Among groups, 组间
) y/ ~& e7 J6 LAmounts, 总量
0 k8 p9 w5 ~. v, y7 P9 `Analysis of correlation, 相关分析) F5 r0 R9 }: A
Analysis of covariance, 协方差分析
- Q: @# t0 D. Z' k+ P* w4 [Analysis of regression, 回归分析: \- _% H* l3 a# t
Analysis of time series, 时间序列分析( ^5 l( `4 {9 d3 h
Analysis of variance, 方差分析
( J) s' b- \" F: |Angular transformation, 角转换" ]& \% g" B% E
ANOVA （analysis of variance）, 方差分析- ~( ?4 m- R. K/ r
ANOVA Models, 方差分析模型. e7 }3 b1 ^, R1 H% ~
Arcing, 弧/弧旋; ~" L6 E) A) l) v9 a. t5 c6 V
Arcsine transformation, 反正弦变换3 ^( ^/ m/ F( I" ?" V$ H
Area under the curve, 曲线面积0 o9 w. @2 ]9 D2 U( g3 F9 t' W
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
' m1 u) s+ H# U/ O8 P3 l0 ]5 J# @# RARIMA, 季节和非季节性单变量模型的极大似然估计 1 z' {+ N% ]1 X$ ?3 w, ?+ N* D
Arithmetic grid paper, 算术格纸
+ a6 v* l; O1 p6 HArithmetic mean, 算术平均数& c7 E) s7 {* e9 b) p
Arrhenius relation, 艾恩尼斯关系; m! c$ b$ ]" F+ E& ?
Assessing fit, 拟合的评估: w; r4 j8 J4 ^3 [; o
Associative laws, 结合律# f, E0 J; |0 Y6 H) }. ]
Asymmetric distribution, 非对称分布
, Q& S6 |' u$ OAsymptotic bias, 渐近偏倚
. ^& e0 k% [; V; C9 yAsymptotic efficiency, 渐近效率- s5 M+ J, H$ t
Asymptotic variance, 渐近方差/ m: x" X7 c; _4 Q* H; b" T
Attributable risk, 归因危险度# _7 U% _% n6 S( o! ]% N/ Z D
Attribute data, 属性资料
: J% V4 @7 S; T2 s& {5 s3 QAttribution, 属性
- a0 K7 ^, q+ T, xAutocorrelation, 自相关
) m2 ~' r9 |: d: P' WAutocorrelation of residuals, 残差的自相关* d$ W. d! y9 b6 O. N
Average, 平均数
. R/ g- S/ R l7 {4 M) a1 i% GAverage confidence interval length, 平均置信区间长度
$ ?3 {9 ?: e! CAverage growth rate, 平均增长率
" T9 ]5 g$ n$ Q8 d5 Q5 ZBar chart, 条形图
3 G9 a- b C- H) UBar graph, 条形图
; ^' t$ `& R8 u( R5 @Base period, 基期1 m* }4 z/ U9 f" L6 r4 K* @( a
Bayes' theorem , Bayes定理, f/ X! J+ i6 ?# J
Bell-shaped curve, 钟形曲线
+ n1 |+ ?. `. z `9 {4 ABernoulli distribution, 伯努力分布
1 A1 X4 [8 K. B2 D$ b& v+ vBest-trim estimator, 最好切尾估计量
o7 m, ~: D# J5 Q! \Bias, 偏性
( w4 Z2 T2 H/ c2 G. ~Binary logistic regression, 二元逻辑斯蒂回归% ~3 C6 i) _% e6 H8 P7 J
Binomial distribution, 二项分布) w( j, V' V7 ~+ }7 S
Bisquare, 双平方
) \- r9 c" u; \Bivariate Correlate, 二变量相关
! y- z6 s6 ?- [9 ~, A7 j# OBivariate normal distribution, 双变量正态分布" v! R& L& Z: r- }
Bivariate normal population, 双变量正态总体& N, r( G" t/ H% w5 {: n
Biweight interval, 双权区间$ T1 M/ g+ Y& J9 e) s, N0 o4 ~
Biweight M-estimator, 双权M估计量
* F3 @( `1 C* A6 z& z9 dBlock, 区组/配伍组
+ Z& {2 f$ a) A8 w1 @BMDP(Biomedical computer programs), BMDP统计软件包3 x$ U$ I4 e! o! _" b( v
Boxplots, 箱线图/箱尾图" p& a4 x1 u4 j/ e) H
Breakdown bound, 崩溃界/崩溃点
' \5 H' C+ t7 ]" D! GCanonical correlation, 典型相关; Q9 @6 m* ]$ l$ @
Caption, 纵标目
1 p) ^3 w+ z2 @Case-control study, 病例对照研究 P4 W, S9 a& l% W
Categorical variable, 分类变量
2 ]2 p) }2 l% ?% Q( H$ ^Catenary, 悬链线; v6 z; n; l/ q, O% ]
Cauchy distribution, 柯西分布
7 c, f7 n( m* ]$ T6 {( c$ D' mCause-and-effect relationship, 因果关系
( a5 D- l6 L* W, A) a, kCell, 单元
8 C; [) \" ^! D/ Y5 N' D- GCensoring, 终检8 P( q; L$ Z8 n; n$ C u# D
Center of symmetry, 对称中心
- {8 q& M5 S* k+ d% s# }/ ~+ ^7 n( tCentering and scaling, 中心化和定标
+ G7 c0 r' s7 {9 }Central tendency, 集中趋势9 W8 o4 l( I7 ]
Central value, 中心值
2 A1 X+ w) E4 P$ ~- d+ C6 `CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
& L' v4 m6 {* a2 T9 {: A0 kChance, 机遇
, B! h2 O2 e1 T5 e! s8 W4 NChance error, 随机误差: w- }, P: Q% k& D# R/ ~' K# C/ |6 y
Chance variable, 随机变量
" z! y* s9 a& D# _! aCharacteristic equation, 特征方程
* t! r! w3 ^5 qCharacteristic root, 特征根
& ?* O- Q+ Y3 V4 `9 f+ ICharacteristic vector, 特征向量% c% x3 T7 X, X$ ? B
Chebshev criterion of fit, 拟合的切比雪夫准则, N0 o$ [" O6 o$ n' }/ \
Chernoff faces, 切尔诺夫脸谱图
- q0 v; O; j3 h2 G& N- R, Z/ l& fChi-square test, 卡方检验/χ2检验* S3 y/ z( M7 S. U
Choleskey decomposition, 乔洛斯基分解
3 @: h3 Q( u8 LCircle chart, 圆图 " B/ v# U' W1 `) T9 Z
Class interval, 组距
* E$ n& Z" p& z& zClass mid-value, 组中值
# n1 `4 C$ }8 s. D. M- H) `7 rClass upper limit, 组上限 h- X, |) Q3 }( g
Classified variable, 分类变量
* c2 O* t4 D! P! s9 DCluster analysis, 聚类分析% j: I0 M" R! g! y' P
Cluster sampling, 整群抽样
6 G7 D" z6 p' R0 h0 a8 Y% wCode, 代码) l, F0 x' z- [; \
Coded data, 编码数据
7 [- I2 J4 m8 j; J0 @Coding, 编码
$ b& |" i: x& o5 t& r/ ]& nCoefficient of contingency, 列联系数, [/ ~/ J2 ~ h3 K6 ~* X# o N' E4 G" }
Coefficient of determination, 决定系数
) y5 V2 S0 q8 WCoefficient of multiple correlation, 多重相关系数
E% q: D# {0 o8 C. p: qCoefficient of partial correlation, 偏相关系数% ]! q) T4 x r. G
Coefficient of production-moment correlation, 积差相关系数$ f M3 O8 a$ l3 z. ~
Coefficient of rank correlation, 等级相关系数
! h9 L, W' P- ?& aCoefficient of regression, 回归系数. B4 G9 C5 O d. q9 e. V
Coefficient of skewness, 偏度系数
: r9 }) V+ h- j2 Z6 CCoefficient of variation, 变异系数
- o/ Y: K [ c. JCohort study, 队列研究
4 R9 o- l* l% x& V5 sColumn, 列
( L, r0 a% }5 u6 m/ u& }0 tColumn effect, 列效应
4 q- |1 N7 ~0 w- X+ P5 T, E0 pColumn factor, 列因素6 f2 F b6 X( P! c$ ]
Combination pool, 合并2 Y+ } R5 W" b. G) C- G; E
Combinative table, 组合表
* n" d! K3 o4 P7 K! x p% C. Q, ]# TCommon factor, 共性因子
' I Z6 P( L9 TCommon regression coefficient, 公共回归系数
5 v- m: [- @% X$ y zCommon value, 共同值
" \% Z! Y, j2 o- _/ {Common variance, 公共方差' T. y" |( n& [0 m7 u6 l- _
Common variation, 公共变异
V. W% X V) ?' o# \Communality variance, 共性方差
6 k& [* f% T3 O1 a* [( Z+ kComparability, 可比性
% m! ^* P- w! x( P: P. RComparison of bathes, 批比较
9 h! ~. {* q8 ]* y2 L) GComparison value, 比较值
4 T7 Z' ]' g+ _Compartment model, 分部模型; c& K6 V/ W: ~7 W2 _6 e: Y, M
Compassion, 伸缩
3 D4 M2 t+ @/ l4 TComplement of an event, 补事件! x1 x7 F8 @5 P4 h0 t
Complete association, 完全正相关" x6 c) R. \2 n5 C( V
Complete dissociation, 完全不相关
' ]$ F) M: d! D I1 ^Complete statistics, 完备统计量
* ^2 o' m2 M1 E1 N0 Z: oCompletely randomized design, 完全随机化设计
# ~6 c3 R8 O( ]& Q6 FComposite event, 联合事件- ~% J5 ^6 y* O5 U: V: E
Composite events, 复合事件) W) R, f' r" Z ?% e' G5 F
Concavity, 凹性
. _% K5 _8 v4 s' L L+ ~) BConditional expectation, 条件期望& Z3 f& Q+ {3 t' T; ]% V
Conditional likelihood, 条件似然& J4 R- }! {% g, Q* R
Conditional probability, 条件概率) R3 B3 t2 J% T9 }0 ?' v6 n M+ U
Conditionally linear, 依条件线性/ T7 R X& R' X5 R& C
Confidence interval, 置信区间6 Z5 @9 {9 b0 f
Confidence limit, 置信限
0 }$ _9 A6 S7 q6 b# Y& T6 r" fConfidence lower limit, 置信下限' A, n& _' Y( F/ ~1 p- {
Confidence upper limit, 置信上限) H! E" U S2 Y0 m) Q' `) B6 u+ P
Confirmatory Factor Analysis , 验证性因子分析
' u6 X0 ?$ t* f U9 ~& FConfirmatory research, 证实性实验研究" U* x* ~0 S" x( X1 `; ]
Confounding factor, 混杂因素
( b9 C, [3 F( N* j' o S. @- `1 sConjoint, 联合分析
+ F9 U7 k: G9 x4 v, d* W1 QConsistency, 相合性
) l- T. |. ], u' W! o7 nConsistency check, 一致性检验
5 c/ r3 h4 ?+ q/ `* e1 p/ [3 Q! KConsistent asymptotically normal estimate, 相合渐近正态估计5 `- y1 v2 I9 g" a( d R
Consistent estimate, 相合估计
+ |7 s- d+ n9 \3 ?" kConstrained nonlinear regression, 受约束非线性回归4 U! w+ `$ G$ ~3 t2 [- {8 V9 t
Constraint, 约束/ C0 a4 C" k+ m4 r% a) Z" M
Contaminated distribution, 污染分布
# W4 v1 ^" n% _/ v, S5 N0 hContaminated Gausssian, 污染高斯分布2 ^2 ~1 _& X8 c- f
Contaminated normal distribution, 污染正态分布5 ~6 F( b; v7 ^' T% _) v
Contamination, 污染
7 I) c+ U" U" T5 iContamination model, 污染模型4 j' d* @, w8 j4 R) K7 x4 H0 d" A
Contingency table, 列联表1 y/ E% p4 m; \- Y
Contour, 边界线5 z5 `2 t; ^' L; p8 b) Q: X
Contribution rate, 贡献率; O% O( o& ?# ?, I2 c" R
Control, 对照6 F1 b' T9 |. t8 G l
Controlled experiments, 对照实验
+ @- v% l7 X z, d1 NConventional depth, 常规深度
" b2 v% [* @7 u* T, ]$ wConvolution, 卷积1 e& @# `# f4 |5 s/ A+ G
Corrected factor, 校正因子8 _7 n& H3 a7 r! J8 [$ C
Corrected mean, 校正均值0 B8 j. k6 Z! J( T, k
Correction coefficient, 校正系数. ?/ h: N- r* P: h
Correctness, 正确性6 S5 H b A+ H7 A: g, R& |: Y
Correlation coefficient, 相关系数+ h' R5 D a7 F- I& D0 J
Correlation index, 相关指数- ?( ~9 e+ e" N1 @
Correspondence, 对应
5 W; A3 ~: N" M, B( \" {Counting, 计数9 m9 K2 c0 ?1 f3 Z% j
Counts, 计数/频数) N6 U& e2 G. X4 t" |3 c
Covariance, 协方差) p, k9 a: Q# k
Covariant, 共变 n+ i+ y( K6 S( l
Cox Regression, Cox回归" N. [( F N4 i' d( x0 e' G7 Q
Criteria for fitting, 拟合准则$ D- }7 j6 O% I. L) z% q# e
Criteria of least squares, 最小二乘准则
$ q6 X$ i6 I+ n. eCritical ratio, 临界比
( N! `/ @; e, v7 U% J. I: M, B' ^ k0 c3 {Critical region, 拒绝域& l) H$ K* x# e/ \+ J
Critical value, 临界值* `$ _2 u" J$ R7 S9 }3 w
Cross-over design, 交叉设计
- k& e! Y2 f' B1 T: wCross-section analysis, 横断面分析4 |: y6 ^+ @% k( |8 u1 I% }* I
Cross-section survey, 横断面调查
. r1 x* F6 l. T* f0 M3 NCrosstabs , 交叉表 # ]6 u' N8 P3 D9 ~3 r
Cross-tabulation table, 复合表) ^4 Q9 u+ g- r& [$ C
Cube root, 立方根' Q4 E' d% P% i* R* K& m/ w/ d
Cumulative distribution function, 分布函数) y( m4 t$ ?* F& f* E3 ?
Cumulative probability, 累计概率
8 k& V7 B: [; S5 g7 Q* MCurvature, 曲率/弯曲" u; J/ G0 I. E0 E Y
Curvature, 曲率
8 D6 B2 y, v3 o U8 _* b2 LCurve fit , 曲线拟和 : a6 C4 W4 M# L0 D* U. e
Curve fitting, 曲线拟合 V) |7 p4 t; U# \- ]+ U: \% I
Curvilinear regression, 曲线回归7 R; Q$ H; K! Z* C V% k9 r
Curvilinear relation, 曲线关系
- o9 @) G8 Z% C8 g$ \5 o; C; Y, NCut-and-try method, 尝试法 g; @ n( X+ V3 p; `5 z
Cycle, 周期$ w0 T6 j6 v% n: Y1 u- s
Cyclist, 周期性' o9 ?& {) u: q) i" Z7 h7 d0 B
D test, D检验
4 l8 x4 g% i2 A# mData acquisition, 资料收集6 n3 X) n- Z' p
Data bank, 数据库& \; u2 S! _$ v5 x& a& ]/ O2 s
Data capacity, 数据容量
7 y2 \; ~ ~2 X! G. uData deficiencies, 数据缺乏
' [) I" o2 d* |7 c X+ `Data handling, 数据处理
7 C1 T. d) n6 K* I3 s, b. `! GData manipulation, 数据处理
$ y4 j$ o8 G' q( E7 A e, aData processing, 数据处理
6 x4 O5 o$ Z6 i7 v" l& B) j/ RData reduction, 数据缩减6 S) e% s9 Z3 e# h* [2 \
Data set, 数据集
/ @. L+ @4 S, C. _Data sources, 数据来源/ U+ L' `: Q$ Y* F h5 c
Data transformation, 数据变换
, G; v, K& f% q! H3 w% aData validity, 数据有效性
C# W5 }0 j; w& KData-in, 数据输入
& _: S4 T) N5 p& s |0 JData-out, 数据输出
2 w6 N+ H& z J, X: @, ^; yDead time, 停滞期+ X- r! o! Q0 G8 W9 _4 x8 l
Degree of freedom, 自由度
3 D& H( M: r, P( z$ n5 O, J+ F3 JDegree of precision, 精密度$ g) [( _1 R; b/ X, V0 p+ a
Degree of reliability, 可靠性程度& ]3 i6 _ H2 m v6 x
Degression, 递减
' ^* _& Y, l# _* K9 m) I/ l9 |Density function, 密度函数
' T3 I( y* l" } pDensity of data points, 数据点的密度6 Y* e5 j+ q* ^8 C- {% D5 H
Dependent variable, 应变量/依变量/因变量, K# ~/ C+ A- \8 p7 \( `4 j! r
Dependent variable, 因变量$ X& N9 g& F! t8 X6 }& o
Depth, 深度2 t6 K" U9 t$ b% @8 m8 q7 z
Derivative matrix, 导数矩阵
% R. `( Z' \' o0 _1 O6 g0 a* VDerivative-free methods, 无导数方法, ^7 F8 `4 m) Q1 E
Design, 设计5 p7 [( N$ c- z) | L( L
Determinacy, 确定性
' i9 N3 t+ Y1 g8 _Determinant, 行列式
$ x4 w- P% L# ?& {( t$ u0 xDeterminant, 决定因素
6 p8 u7 x" ?6 q: j' V9 A2 wDeviation, 离差- |" l: s; S% t: s
Deviation from average, 离均差
1 b* E: ~ V, z* jDiagnostic plot, 诊断图0 i4 |' b& _5 P) [$ e9 X; u) [
Dichotomous variable, 二分变量
$ S F9 r( F8 `' O8 LDifferential equation, 微分方程. ]4 @' B5 l4 c. U; S* g
Direct standardization, 直接标准化法- F. f1 V5 L# g2 G
Discrete variable, 离散型变量
/ x Q& v# f; R+ \DISCRIMINANT, 判断 . E' s+ w; }6 X
Discriminant analysis, 判别分析
: Z0 q g" [. Y* G/ j# ^Discriminant coefficient, 判别系数
, U1 P5 F1 z# F0 S: A. SDiscriminant function, 判别值
! i; t% L5 M0 Y/ w0 P0 Z7 SDispersion, 散布/分散度- f6 `$ f, p; q3 p' `) E+ ~
Disproportional, 不成比例的; L, g% i$ ~4 ]4 H5 L8 S1 d
Disproportionate sub-class numbers, 不成比例次级组含量$ }; S& g+ r: H+ l4 I+ @
Distribution free, 分布无关性/免分布
9 P8 t$ Q, A' J) wDistribution shape, 分布形状
) ^* m( X3 S j5 v4 {Distribution-free method, 任意分布法5 a( B8 _1 j# F7 g' u7 }
Distributive laws, 分配律3 J9 d1 `9 r* M& _. ]1 Y3 }' E
Disturbance, 随机扰动项: Z s Z/ [4 f: u6 Y* \2 P% ?0 W9 N
Dose response curve, 剂量反应曲线
7 F) G8 p( m! B; ]Double blind method, 双盲法
, N+ Z: Q1 q+ Z6 K+ kDouble blind trial, 双盲试验
/ Q0 j9 U' f9 M/ KDouble exponential distribution, 双指数分布
( Q- x! H# m; L* m0 H! ~# y# gDouble logarithmic, 双对数
* `7 E' _# {/ h8 dDownward rank, 降秩0 b, i+ X. `; [4 r
Dual-space plot, 对偶空间图- e# |5 y2 E& i% }& m: M
DUD, 无导数方法6 e2 [) J/ E# P% Q$ f# T% E3 R( h
Duncan's new multiple range method, 新复极差法/Duncan新法
. N; {" i! }" R- k; ~Effect, 实验效应( C; V3 ^$ l3 ]" l4 D9 K' P' H8 S
Eigenvalue, 特征值
$ T6 F" H) n( {4 k, REigenvector, 特征向量- R- x D3 F, h$ ^3 L% E. u6 M
Ellipse, 椭圆- y. @; V8 P6 @: N) P& v$ l
Empirical distribution, 经验分布& B/ @3 f, ~. W5 f5 M1 E2 o+ D
Empirical probability, 经验概率单位
* X7 t V7 S1 Q J8 \, {Enumeration data, 计数资料
1 B$ I7 G' P3 bEqual sun-class number, 相等次级组含量: U8 ~* X7 j9 I2 s
Equally likely, 等可能
& I; f9 t5 F- l- R' IEquivariance, 同变性
8 {- U, z* Y$ Q& o# _! D( rError, 误差/错误
# | j2 M# Y- B4 F8 t" R8 hError of estimate, 估计误差
/ e& M. e, H5 T' `. H) D; oError type I, 第一类错误
- _! J3 [. g0 m- wError type II, 第二类错误
5 {! ?7 g+ B: e, LEstimand, 被估量/ L" ~' W- l9 J
Estimated error mean squares, 估计误差均方1 t1 @- @( E. Z4 ]3 B, _7 B
Estimated error sum of squares, 估计误差平方和
7 S( p4 _' V, E) |5 `( p! gEuclidean distance, 欧式距离8 v9 }- U1 `! Z8 Z! ]# O; ^
Event, 事件) P' U0 b1 N u
Event, 事件
6 c" E9 F( V- M2 G/ o* \Exceptional data point, 异常数据点
' J$ a' O/ i4 `Expectation plane, 期望平面) o2 h9 A# }$ [( m! O% r
Expectation surface, 期望曲面) q$ F! G' a7 v& I) D- W0 g
Expected values, 期望值6 X- X* a( O9 Q7 b/ \' E+ A
Experiment, 实验
* {2 [: p {/ \Experimental sampling, 试验抽样6 {' N2 q$ d) b# v8 ?- S: v
Experimental unit, 试验单位
p5 p" W/ B( [- _: t/ ~5 pExplanatory variable, 说明变量
$ q8 H' [: I5 B8 H# eExploratory data analysis, 探索性数据分析# e/ }5 ~. E; A$ `8 g
Explore Summarize, 探索-摘要
& |/ _+ D6 \+ k+ B) ~8 G6 gExponential curve, 指数曲线
# G: F0 G: x$ g9 ]0 ~7 ^Exponential growth, 指数式增长
5 U0 a* N) ?# b' W* yEXSMOOTH, 指数平滑方法 3 C( U+ }& S- e, Z! I4 j( J7 F) H. t
Extended fit, 扩充拟合
2 u% j9 s% o7 Z3 Y+ jExtra parameter, 附加参数) ] ^+ ?& G& C+ X! S N# T8 w
Extrapolation, 外推法
% b5 {: H2 x- g! O n; [! X$ WExtreme observation, 末端观测值
; ^4 ?' b- |) ?) {, ^Extremes, 极端值/极值8 V3 w9 j( t" d
F distribution, F分布, Y' F1 W- q1 ^ C, q3 u
F test, F检验/ P) K* d; @ s3 |
Factor, 因素/因子4 T3 r% t2 V, M4 ~
Factor analysis, 因子分析) e+ b1 q6 N0 Z
Factor Analysis, 因子分析
8 B4 w# K& i$ R5 NFactor score, 因子得分 7 k; S7 Q6 d# B$ Z
Factorial, 阶乘
* c* a* |& t/ H( M3 h6 R- IFactorial design, 析因试验设计
& i. E7 x2 @7 J/ r/ RFalse negative, 假阴性
$ F8 w4 a3 a) [, UFalse negative error, 假阴性错误4 J! k' Q% Z8 ^" b* G% q2 S0 g
Family of distributions, 分布族1 }( A6 b! Q8 D
Family of estimators, 估计量族9 Z1 t1 O* r1 }
Fanning, 扇面6 ~6 H6 ~& X, p0 f3 h" T& p
Fatality rate, 病死率+ |6 F, V3 X- K3 n
Field investigation, 现场调查5 \0 ?3 A U% k* m
Field survey, 现场调查2 @$ H4 E; C2 G! t& f9 d: w" [
Finite population, 有限总体" V, t6 \" }8 @4 L7 p* G
Finite-sample, 有限样本4 a4 \% P* S0 y' U8 J1 d& S
First derivative, 一阶导数
( [7 E# S6 Q7 Y% vFirst principal component, 第一主成分9 M w9 g- L. p3 y
First quartile, 第一四分位数
`) q+ ^ g& k- i- pFisher information, 费雪信息量! X$ u9 }; U- M5 X8 `, P, F0 S
Fitted value, 拟合值
/ o4 ?0 x/ k0 H* qFitting a curve, 曲线拟合; g; c2 e8 J2 ]# y' e
Fixed base, 定基
9 A# ?8 A: u+ HFluctuation, 随机起伏
& ]# Q7 T& J2 J! Q2 YForecast, 预测
# H6 x: y) u, H- j. @- _8 I. [Four fold table, 四格表
7 e% e3 l( \9 G+ y QFourth, 四分点+ s( B) g7 D/ U& d( r$ D
Fraction blow, 左侧比率& b* ^0 K, X6 m r, a3 R: S
Fractional error, 相对误差- z: K/ F6 j: x- M6 A
Frequency, 频率
, S; v' _, {- p3 b1 q3 E2 {: yFrequency polygon, 频数多边图
/ P7 Z, u& A' xFrontier point, 界限点; a) ^; R$ u( e+ y6 s
Function relationship, 泛函关系& A5 A4 ]6 x: C8 Q, }9 _- @
Gamma distribution, 伽玛分布( m$ c+ A9 M0 R$ p
Gauss increment, 高斯增量
+ J+ _+ L1 A; HGaussian distribution, 高斯分布/正态分布# P4 Z4 ]1 t9 o2 V1 f: n9 _- b
Gauss-Newton increment, 高斯-牛顿增量
5 `' g7 L$ Y9 t* n8 O% l- @2 M! SGeneral census, 全面普查" E% L5 ^; u: O2 E0 R# W
GENLOG (Generalized liner models), 广义线性模型
2 d5 f6 v6 x! tGeometric mean, 几何平均数
6 f8 x$ g: |. wGini's mean difference, 基尼均差- @! V) F& F7 V0 o3 x
GLM (General liner models), 一般线性模型 - ~3 s1 s% k3 J- H. P8 a) d2 f
Goodness of fit, 拟和优度/配合度
3 [$ D( J: ~. i2 KGradient of determinant, 行列式的梯度3 ]$ N# r- u( ^5 n; D1 Y Y' P" k4 J
Graeco-Latin square, 希腊拉丁方. i5 H$ V* w3 H( ?* ]# u" `
Grand mean, 总均值% t5 f" A9 w$ S
Gross errors, 重大错误6 W; k) j) C! h% n
Gross-error sensitivity, 大错敏感度0 b* K$ i: }+ A, ~/ j
Group averages, 分组平均
$ R# U. o3 H' F, R7 m7 ?0 NGrouped data, 分组资料
3 n+ G6 M) @" L0 l7 \Guessed mean, 假定平均数
; g. H3 c* f8 r. R9 [Half-life, 半衰期
L- V8 d0 c# P- |, |# d1 K7 _ }% tHampel M-estimators, 汉佩尔M估计量
8 ^6 W/ g% E X3 SHappenstance, 偶然事件
, d1 _; R* B3 c7 e- YHarmonic mean, 调和均数
7 O; C$ v0 N8 h0 `+ d: @Hazard function, 风险均数
& x3 ~$ Z5 `9 n# }) U8 _Hazard rate, 风险率! K" T/ M; A, m
Heading, 标目
5 R! d3 ] G. }Heavy-tailed distribution, 重尾分布
( f& j3 R7 u+ X0 [7 \Hessian array, 海森立体阵! k3 j$ T0 j% Y1 ^- P
Heterogeneity, 不同质- z$ \8 L& r' q
Heterogeneity of variance, 方差不齐 1 b9 m, V( [% n+ r1 D8 C
Hierarchical classification, 组内分组& R: b: ~7 l2 ?8 m4 g( a
Hierarchical clustering method, 系统聚类法( h7 T& z/ s1 O6 Y9 Z
High-leverage point, 高杠杆率点8 Z+ K: G2 Z: P5 N
HILOGLINEAR, 多维列联表的层次对数线性模型
) D# [( Q: o; H+ L8 z; _* v# eHinge, 折叶点
* x$ K% n: Q9 X: C: N9 N9 O' BHistogram, 直方图7 f; |: E/ y5 I! d2 R
Historical cohort study, 历史性队列研究
2 q/ K" |2 r# bHoles, 空洞% d. J, }5 E( P$ v
HOMALS, 多重响应分析
/ G0 E0 y- [( bHomogeneity of variance, 方差齐性
: M1 E# B5 w, r8 }; u' q1 DHomogeneity test, 齐性检验. ~+ J& q$ A1 y$ a+ g% w7 V
Huber M-estimators, 休伯M估计量5 Z" J' B0 l% Q) A5 s" @- g
Hyperbola, 双曲线
* K* U1 O' r8 I5 S- O7 y: WHypothesis testing, 假设检验
/ _* Y7 D' p, k+ ~Hypothetical universe, 假设总体4 }( ~1 k7 T$ I% g4 X& i3 L
Impossible event, 不可能事件
M3 \: ]( z2 V. z0 _7 [2 g- BIndependence, 独立性
- O3 F9 M% L5 j- C6 {Independent variable, 自变量! ^& i5 u9 r0 |0 k
Index, 指标/指数
4 c9 t% r$ Q+ G9 x ], |0 {Indirect standardization, 间接标准化法0 r! K; N4 @! ]6 {
Individual, 个体3 U+ G1 A( @4 h' {2 j
Inference band, 推断带
( `# P- @5 y) M) Z' LInfinite population, 无限总体& D! h' s9 _3 C7 D; w# |& M# i
Infinitely great, 无穷大
5 {, J5 w$ t# b2 ^8 _Infinitely small, 无穷小
. B4 h/ P M! u4 V1 d. n+ \2 `Influence curve, 影响曲线( o, ~3 ~) c Y, Y. \9 m) z& l P
Information capacity, 信息容量( ~0 } Y; j8 ?. `
Initial condition, 初始条件
: V2 _7 ?/ c! }2 JInitial estimate, 初始估计值
1 b; v# p, l0 _- u5 \Initial level, 最初水平
! s1 s8 I! R* C3 S: t- T5 A/ a7 mInteraction, 交互作用4 `. r E( B( y0 q6 d
Interaction terms, 交互作用项0 ~( N Z/ R& c4 u/ _% n
Intercept, 截距1 T; M0 M6 i9 B/ B+ U) W
Interpolation, 内插法- O- F f. w- g0 V8 h0 {
Interquartile range, 四分位距 }+ Q. [: z. W& c
Interval estimation, 区间估计
( }/ D* E: N3 g, X/ s9 e9 m; K5 qIntervals of equal probability, 等概率区间
- J5 p: a' i3 rIntrinsic curvature, 固有曲率+ a/ f) }* t( h; Q" Z; _+ h6 [
Invariance, 不变性6 R X4 X+ U2 b2 a& ^" e+ J
Inverse matrix, 逆矩阵
& y/ S; P* Z: ] e; OInverse probability, 逆概率1 D2 f& e) U$ [# o5 q$ T
Inverse sine transformation, 反正弦变换2 I6 i) {) _5 C8 T4 S5 v
Iteration, 迭代
( w6 C, P5 G- Y' @$ J; [Jacobian determinant, 雅可比行列式+ R8 y# A: k0 J& _
Joint distribution function, 分布函数# |, a E; ]' E3 |* ~: c2 w
Joint probability, 联合概率; o2 D7 d: k5 X6 h* T3 E
Joint probability distribution, 联合概率分布
- f% Z4 p* y9 {" Q" h. dK means method, 逐步聚类法
( g' ~* J" r$ f0 }Kaplan-Meier, 评估事件的时间长度
" Q0 S1 w1 r! h" |+ |Kaplan-Merier chart, Kaplan-Merier图
4 e" f' |9 J% ]5 CKendall's rank correlation, Kendall等级相关
- c9 D' p; s$ s/ V- V* y! jKinetic, 动力学
5 O- L9 `# B" ^1 d$ S1 I8 u9 m2 `6 d, U% EKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验. e5 p+ k5 a3 I: e& I0 f3 p
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验4 V# ~0 B" ?( I$ D+ Q* H4 a
Kurtosis, 峰度# v2 _* f% ^2 c% T
Lack of fit, 失拟
* L3 i* R; ^5 |6 H3 A3 _Ladder of powers, 幂阶梯
- `. `/ `+ x' R# W. [Lag, 滞后
7 v$ Z3 }$ r. w/ C5 a* NLarge sample, 大样本
# i( D# S0 ~ D% G, g6 L0 HLarge sample test, 大样本检验7 q. A; {6 B% f# M4 k n
Latin square, 拉丁方
* l2 j2 W) M0 }1 W4 w+ \; fLatin square design, 拉丁方设计
3 Z8 W! o" ?3 a6 D, N: TLeakage, 泄漏
6 _' W9 h" a) }* u4 ]Least favorable configuration, 最不利构形# G' j; c. D i3 t7 e3 ?
Least favorable distribution, 最不利分布
5 H# ?$ F+ A& f) j4 z2 kLeast significant difference, 最小显著差法
! e3 H% V, C( p1 s2 gLeast square method, 最小二乘法
& x2 a$ I, f% U TLeast-absolute-residuals estimates, 最小绝对残差估计$ v. v. o) D1 l) b0 F& e& ~6 u
Least-absolute-residuals fit, 最小绝对残差拟合
3 T! y/ H: H% ?8 m0 q5 |3 hLeast-absolute-residuals line, 最小绝对残差线+ l \3 N% O$ f# Y& j
Legend, 图例7 u) z P+ H+ L7 N& k* e% j) ^
L-estimator, L估计量. ?+ u; @6 J9 H. o
L-estimator of location, 位置L估计量3 U/ }- K& N& k9 I
L-estimator of scale, 尺度L估计量
. V$ t( z% u* x {6 E0 FLevel, 水平
; K5 n0 f0 q8 o" z9 f( p+ ?Life expectance, 预期期望寿命% u* N2 g( [/ p2 s4 t$ S
Life table, 寿命表
- Q8 [1 W+ ?& x9 {! PLife table method, 生命表法" U8 \6 ?: l* K
Light-tailed distribution, 轻尾分布
1 ]& X; y) B& b+ ?: |6 g: q& JLikelihood function, 似然函数# D$ e3 U$ a' ^8 d6 E6 q3 c4 R( }
Likelihood ratio, 似然比
- C& p K5 b' p6 p: ? hline graph, 线图 U& \7 |& G% m I- N% _
Linear correlation, 直线相关0 Y+ G2 H8 I: O- s' I. J
Linear equation, 线性方程; f6 J" y% W+ s7 U
Linear programming, 线性规划, Y- ^" f: w+ b$ V- ^! i$ G
Linear regression, 直线回归# Z1 n# {4 ?, b- H" f* x
Linear Regression, 线性回归+ c0 D4 \% I9 |' I7 M$ |7 J
Linear trend, 线性趋势; J1 n. ^7 u) e* H
Loading, 载荷 , G! n* h& y" c3 T, w
Location and scale equivariance, 位置尺度同变性$ h, J# `1 M4 j4 }8 X
Location equivariance, 位置同变性
- ?0 U" T' Q; p& a T9 xLocation invariance, 位置不变性
$ D- c2 G9 Z% L, r" B, I7 @Location scale family, 位置尺度族" n3 a% R2 F, K z3 u: n
Log rank test, 时序检验 3 c+ {6 r" d( b* ~2 y7 P1 [
Logarithmic curve, 对数曲线( s' l2 @4 h( r( s# e
Logarithmic normal distribution, 对数正态分布
+ _/ r9 Y5 _3 G- E. h+ d4 G* ZLogarithmic scale, 对数尺度
3 O3 c4 S: d' i) b1 P) ?Logarithmic transformation, 对数变换9 d! V+ | V/ W. f" u- s2 [+ r
Logic check, 逻辑检查
5 \. C$ [$ I- ^4 B+ `- gLogistic distribution, 逻辑斯特分布
; M k* l' ~( G9 TLogit transformation, Logit转换6 d0 T5 f3 O2 M, ~- n3 a- S' M2 u
LOGLINEAR, 多维列联表通用模型 1 s$ G- D2 H8 k8 x& x- D- f5 z
Lognormal distribution, 对数正态分布
^' W, A' S6 j8 T# `* m+ MLost function, 损失函数
0 \' h7 A# o4 }& g9 PLow correlation, 低度相关
5 U$ ^' M5 |* v/ f1 ]Lower limit, 下限* ?5 X4 P$ h- Z2 B
Lowest-attained variance, 最小可达方差
* Y9 I! n* U+ |5 uLSD, 最小显著差法的简称
7 ?2 |, o/ d& x1 g2 W/ ~1 q+ T4 J8 bLurking variable, 潜在变量
8 m: S& y2 h9 i3 |7 H8 eMain effect, 主效应. U+ Z( L6 O: l* N% C' f& H5 S
Major heading, 主辞标目3 A2 ^: w2 z' H
Marginal density function, 边缘密度函数
i0 B2 H' j; c/ OMarginal probability, 边缘概率
! M9 R b; c. LMarginal probability distribution, 边缘概率分布
- R! K0 x2 G3 s4 WMatched data, 配对资料
- q" B0 Y$ ^7 ~8 r E1 K5 j1 V0 ~4 yMatched distribution, 匹配过分布7 ]/ { P, R1 z$ Y; U$ @2 p+ d
Matching of distribution, 分布的匹配
8 d5 |; G7 x2 zMatching of transformation, 变换的匹配
& q9 q, R4 K, f/ p2 y) w6 V( AMathematical expectation, 数学期望( D$ N( O5 L i! m R- |% x
Mathematical model, 数学模型
! s- o& v& ], {3 A" x0 y8 HMaximum L-estimator, 极大极小L 估计量7 ~$ Y" n" c. p9 D" |, L
Maximum likelihood method, 最大似然法4 }7 y- _; Y3 _" p. Z2 q
Mean, 均数
; ]7 ~' @5 ^! q" tMean squares between groups, 组间均方# H4 @; n/ A- g5 s/ H, ^
Mean squares within group, 组内均方0 a; y( x: n& u% [
Means (Compare means), 均值-均值比较: F$ N5 ~ n- k
Median, 中位数
/ ]3 n" i% H2 M) \# U( `/ L _Median effective dose, 半数效量' I* p5 z5 z9 Q9 |8 x, H
Median lethal dose, 半数致死量7 n3 [( \, T7 J/ n6 E! M, N$ r3 W
Median polish, 中位数平滑
, Z- j1 N" F, {% \( b3 O1 r- a$ ^Median test, 中位数检验$ j/ [9 J ?' T* z, f5 E
Minimal sufficient statistic, 最小充分统计量% A$ R# {. b5 ~6 {
Minimum distance estimation, 最小距离估计
) w0 r( O' D' D$ L" V! ~- CMinimum effective dose, 最小有效量, `. e, {) V6 L+ X" B8 v. F
Minimum lethal dose, 最小致死量8 V/ H5 _6 B- F& Y+ Z% X4 O; X' c
Minimum variance estimator, 最小方差估计量8 |" W: }2 H# j$ }. R6 q( s, r
MINITAB, 统计软件包, c( n& E- ~( U* p# c/ H
Minor heading, 宾词标目
9 J7 c5 G+ b0 r& eMissing data, 缺失值. C- ?) M" B8 k* O2 P
Model specification, 模型的确定; K! o% U9 c! e1 f
Modeling Statistics , 模型统计/ s( o- T: `6 B: U
Models for outliers, 离群值模型
, C0 w4 G9 _% u2 T3 W4 K, tModifying the model, 模型的修正* \+ M6 B+ M+ `. [
Modulus of continuity, 连续性模
# v/ B; ^" o6 S5 ~Morbidity, 发病率 ; T* d0 ~1 l4 G' Z6 g
Most favorable configuration, 最有利构形9 q$ D$ |& k' n2 x2 n, w
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
' v* E. G+ w$ o1 n c6 u' K KMultinomial Logistic Regression , 多项逻辑斯蒂回归$ ?4 C9 a' S* F; I. p
Multiple comparison, 多重比较% g! j9 M5 C& q" w4 u
Multiple correlation , 复相关" w! T* ]8 e2 D' S
Multiple covariance, 多元协方差 W8 T6 k0 u8 P d& b
Multiple linear regression, 多元线性回归$ a& @% W) t+ b( ^% e( J, y& X; l
Multiple response , 多重选项1 X: e* L0 C3 z. z. c6 D8 V
Multiple solutions, 多解
9 v: L! q4 _! p. F! i, C) r& _Multiplication theorem, 乘法定理
. j$ }' `2 x. I6 sMultiresponse, 多元响应
3 d3 B- K. R: F6 I5 PMulti-stage sampling, 多阶段抽样
9 k5 d2 ~' ]3 L; _. E/ GMultivariate T distribution, 多元T分布! u5 B4 V. b0 p. X! O4 t- F
Mutual exclusive, 互不相容) r. _+ s- Y# z) R# p
Mutual independence, 互相独立 c+ D7 w( d, G
Natural boundary, 自然边界
; k# h& K( o# @# |' \1 vNatural dead, 自然死亡( A, J/ y/ r3 V: d, u7 g8 H. T
Natural zero, 自然零: p8 V1 u6 p& k
Negative correlation, 负相关9 `+ p; r1 Y: h
Negative linear correlation, 负线性相关
. \1 n1 g n5 l& N/ }$ b6 o2 ] cNegatively skewed, 负偏
' v# D: R6 K( j& P% I) O' D+ J$ CNewman-Keuls method, q检验
/ }8 X) i0 \7 {( U" \" {. CNK method, q检验
, X( r& M8 b! E' j, R9 mNo statistical significance, 无统计意义7 X& y% c7 \7 ~ {5 y! Y
Nominal variable, 名义变量4 W. A; d7 C! o/ z, T- B
Nonconstancy of variability, 变异的非定常性
N5 V4 n4 M" |) {1 cNonlinear regression, 非线性相关4 t5 s+ _" z. Q. P) y" j
Nonparametric statistics, 非参数统计& e) A9 c8 P. B' V$ S$ y3 ?
Nonparametric test, 非参数检验
$ b2 \9 Z9 p" `. B- v9 HNonparametric tests, 非参数检验! I8 x( V3 t/ z4 w
Normal deviate, 正态离差5 |" A; x8 |- Q% E7 P, S6 ]: K
Normal distribution, 正态分布+ d/ S5 V, n& {
Normal equation, 正规方程组
+ k5 a5 A2 p4 _" ~Normal ranges, 正常范围. H0 x4 `$ j0 n6 y! x0 F8 J5 O7 N7 F
Normal value, 正常值
1 M: |* }/ o7 ^9 }Nuisance parameter, 多余参数/讨厌参数% T* g6 a4 |* U" D9 [/ |9 d
Null hypothesis, 无效假设
- E) p# u# {" O! tNumerical variable, 数值变量! [" P1 d$ C! J! u% Z" H2 @( h* A8 N/ y
Objective function, 目标函数
, c& P; G9 j$ w# }8 jObservation unit, 观察单位+ [3 V0 ^5 V+ z
Observed value, 观察值
3 D- ?+ ?( }2 J' L0 ~One sided test, 单侧检验' l8 ~1 Q' z) J2 `
One-way analysis of variance, 单因素方差分析6 J: u9 P7 @2 n7 w" Y: Y
Oneway ANOVA , 单因素方差分析
- _" z; k9 t3 _6 bOpen sequential trial, 开放型序贯设计
; _# M' S7 a; E/ _1 ]Optrim, 优切尾! i) V8 b% X8 S0 X
Optrim efficiency, 优切尾效率
9 }' D$ v2 u& i* W- J5 f/ h& kOrder statistics, 顺序统计量
7 N$ G1 d, ~) d: t+ eOrdered categories, 有序分类8 w& I, x: ~- [2 r% N* N0 ?8 D
Ordinal logistic regression , 序数逻辑斯蒂回归
- }. i7 g6 K( a; F6 e6 x9 ~Ordinal variable, 有序变量; ~. H, R/ k; T
Orthogonal basis, 正交基
% \: v( Y3 P5 A; z8 K, y6 yOrthogonal design, 正交试验设计; Y" J1 G% P; `( K; A4 j1 w+ Q" o
Orthogonality conditions, 正交条件
" h6 C- [( b% l. z" c, h) S; kORTHOPLAN, 正交设计
" Q6 o8 S; z" b6 {( d4 H0 W* S wOutlier cutoffs, 离群值截断点
8 e6 U- B3 m0 T- w- V) \Outliers, 极端值
& O5 _+ @' _+ Q' FOVERALS , 多组变量的非线性正规相关
; W2 T* @) x u+ XOvershoot, 迭代过度4 w% v7 Q' y) K. i W7 d4 w% i
Paired design, 配对设计
. i: H z5 q7 s! Q* }Paired sample, 配对样本
4 O/ X$ y* N* yPairwise slopes, 成对斜率/ @; R) A" T" T1 D3 [
Parabola, 抛物线
2 W; e: h* a7 N6 x" IParallel tests, 平行试验+ F4 o5 ]( y+ S+ o8 p' O/ u
Parameter, 参数+ U6 F- J8 w3 K4 D& d0 s7 P* y
Parametric statistics, 参数统计
6 T3 j u) ]$ j2 P! p# p" X2 ~Parametric test, 参数检验+ F$ ] `$ R# X; z# o
Partial correlation, 偏相关) X6 F, P0 a+ Q, A$ v0 q; G- c
Partial regression, 偏回归
2 f7 J- b o0 P* ?Partial sorting, 偏排序4 Q3 s3 E2 J5 i2 r9 G/ L: v
Partials residuals, 偏残差5 E4 n7 x/ P5 r5 ~$ K/ j* u5 _
Pattern, 模式6 q$ a1 _% S( n7 b2 b
Pearson curves, 皮尔逊曲线
+ K+ d: ?+ }* O) E( oPeeling, 退层
6 d5 w* ?& S$ p( o& jPercent bar graph, 百分条形图' Q9 u6 E! T/ ]" g/ q& L C
Percentage, 百分比3 @0 n6 I0 D5 r; l8 U
Percentile, 百分位数( a* n0 u* X$ \! R3 B, n2 g' C
Percentile curves, 百分位曲线8 V4 E3 N% {% T/ u) T
Periodicity, 周期性
6 U( z F5 {! L y. O0 G: e% C# X+ XPermutation, 排列
; P& R3 P( h$ E1 l0 u) oP-estimator, P估计量
* E% R1 {! f4 H; h l& DPie graph, 饼图
; O J0 j4 t7 C- I2 q! _4 XPitman estimator, 皮特曼估计量
3 Y( ~5 L5 d6 d5 l2 Z W0 aPivot, 枢轴量
( t0 q0 i# { _6 x5 H6 ]( z2 yPlanar, 平坦
. B" p8 u/ w+ G% mPlanar assumption, 平面的假设
" D" L9 t5 {0 {; O6 w2 F. b( hPLANCARDS, 生成试验的计划卡* @. G; [, B3 r/ A4 P
Point estimation, 点估计
/ L- a- P H) c8 i0 O% }( l8 l* nPoisson distribution, 泊松分布4 ?1 Y3 U4 {. u( b1 J
Polishing, 平滑" @, ^8 P+ u8 @* G" D5 p5 t
Polled standard deviation, 合并标准差, D( W# k. |8 a
Polled variance, 合并方差
) c& _- J. R9 f# i1 |& R5 w* ]Polygon, 多边图& }9 S' m, j. o$ n: m9 i; T
Polynomial, 多项式
1 g! g$ f* p% fPolynomial curve, 多项式曲线" ?$ d! o- n, N5 v- e# m* c
Population, 总体
, f% Y. @+ F! I1 G8 \8 \Population attributable risk, 人群归因危险度! c6 K: c% h2 ]' e# ?7 G
Positive correlation, 正相关- U5 N$ _) C6 d5 J
Positively skewed, 正偏
. ]8 b( K3 P8 o N3 m# e; GPosterior distribution, 后验分布
, y7 b7 p$ G% _: @8 QPower of a test, 检验效能# p K6 w- h B% C$ u _' {
Precision, 精密度: H0 ] p5 w5 \9 h" s; F+ G$ A
Predicted value, 预测值
+ g# ], e# g3 ^, ePreliminary analysis, 预备性分析/ a9 ]! O- s5 j$ g% }( k6 X
Principal component analysis, 主成分分析
, I% ~& P& \, ]1 u6 KPrior distribution, 先验分布
0 v! [& U5 H: \5 k- h. X! e5 vPrior probability, 先验概率
: B6 T, D& N" |" p0 a* w/ TProbabilistic model, 概率模型
1 C; s4 N5 X% n8 j/ b! cprobability, 概率/ D4 ?# |; N' _5 A& [+ Q% }$ J" k
Probability density, 概率密度' h# ~3 u2 i; M& L2 s
Product moment, 乘积矩/协方差
4 y- c( q- S7 Z5 i: kProfile trace, 截面迹图! Y9 m- `4 E. A# S) Z4 H2 e
Proportion, 比/构成比
6 k+ n, i$ V" N% u/ X. X0 `Proportion allocation in stratified random sampling, 按比例分层随机抽样
8 c% [) S+ t& gProportionate, 成比例
3 q4 `. Z& _1 t/ Y; kProportionate sub-class numbers, 成比例次级组含量
2 W5 f' u( I/ B& u6 p# F1 @+ C4 PProspective study, 前瞻性调查
& I4 L" |; L' M2 C8 [% OProximities, 亲近性 + G# q- f. `, K ^9 q% Y
Pseudo F test, 近似F检验
( Y- Z7 w4 K( J/ b5 p1 j+ ZPseudo model, 近似模型
; n g _1 g. a1 uPseudosigma, 伪标准差+ V+ F# r: a: b$ z3 L
Purposive sampling, 有目的抽样2 f6 n" k' `, Z# W3 F
QR decomposition, QR分解
: N. _. X5 f5 w2 HQuadratic approximation, 二次近似* ? {0 H/ {! @$ E; s
Qualitative classification, 属性分类 P# a. x+ {( Z5 T; v5 C0 |
Qualitative method, 定性方法: S: D7 d# p; E* K! \/ u. Q
Quantile-quantile plot, 分位数-分位数图/Q-Q图2 ~5 {- m5 H' d
Quantitative analysis, 定量分析
; j, Z5 s7 s3 s. i p& V' ^Quartile, 四分位数
3 ?, A$ y* w( |Quick Cluster, 快速聚类" I6 P+ z$ T* Z) f( ?
Radix sort, 基数排序
0 y' g2 ^8 A( V; rRandom allocation, 随机化分组
4 R9 e7 K5 q2 I, IRandom blocks design, 随机区组设计
5 q" R* q- w& b) d8 v DRandom event, 随机事件
- l* d# g; y1 t& ~1 t( QRandomization, 随机化
G0 d1 C( L; F4 S2 HRange, 极差/全距
' C6 M/ s( W% j; m: T7 P" k# |Rank correlation, 等级相关
2 b3 `+ ?0 w+ U( r- b- V0 IRank sum test, 秩和检验
6 s" |; E6 ~9 i: H8 V1 k5 _Rank test, 秩检验" o! l* c' C( h
Ranked data, 等级资料4 J% m1 {! A* F' q- d
Rate, 比率1 C! B$ f' L) v8 }* N
Ratio, 比例6 L2 H, a5 M" M3 h: M2 s
Raw data, 原始资料
- P h$ n, D9 e, T- |9 HRaw residual, 原始残差4 N& E3 u: ]1 v2 p# |( I/ g$ g
Rayleigh's test, 雷氏检验
/ y7 r' j2 I* x9 KRayleigh's Z, 雷氏Z值 ) o3 c3 d4 X( R, S" N. M& j' D
Reciprocal, 倒数0 U- X1 c7 j7 g% S7 x
Reciprocal transformation, 倒数变换; p+ b, I$ P* k ]* B$ m
Recording, 记录- ]( e7 `2 x: P, b( \3 w
Redescending estimators, 回降估计量
- F$ ]$ S7 \0 V" AReducing dimensions, 降维
8 u. C. [" @5 e, O6 g) WRe-expression, 重新表达( p6 \3 ~' _) C. {& E; h
Reference set, 标准组
, @* C3 Z5 o/ RRegion of acceptance, 接受域
/ S) j% b2 Q5 i; X: G8 URegression coefficient, 回归系数
4 Q; b+ X) C; e C' DRegression sum of square, 回归平方和
: K& l- o$ s" {/ i% q4 Y) URejection point, 拒绝点3 a' C7 O' Y# c4 P1 V0 I4 A% K; V
Relative dispersion, 相对离散度
! k z* l% P7 ~8 iRelative number, 相对数( F9 z& v5 J* k* R# o( _
Reliability, 可靠性
- v% z4 @: O% a- E" Q) z/ J, X4 Y RReparametrization, 重新设置参数
. u. {% [$ x0 M4 ]) sReplication, 重复
/ ]3 T$ a, k! }7 H- ~3 Y VReport Summaries, 报告摘要
* v4 @- C5 w3 o. ]0 k0 |3 KResidual sum of square, 剩余平方和9 \8 [2 P& Q0 b. X( v8 S3 t
Resistance, 耐抗性- z5 z! D# A" U* H
Resistant line, 耐抗线
7 q/ G1 L1 L0 Z4 F- [% A. iResistant technique, 耐抗技术3 E( d1 E% @. b0 Z9 o$ N
R-estimator of location, 位置R估计量7 t3 ?" x. g0 \) Q( O0 K; k! c
R-estimator of scale, 尺度R估计量; i/ P; }, Y9 F$ E3 m9 t
Retrospective study, 回顾性调查
) i" ~. H# d; R3 E/ k" oRidge trace, 岭迹
' o9 H" h0 l% h) {$ H2 N) {Ridit analysis, Ridit分析; L& D P# n1 k
Rotation, 旋转2 Q: S2 S, G7 F, M& [- Y
Rounding, 舍入
, Y! m- ^* n7 S- Z) ^1 ]0 JRow, 行9 s* r! l3 |' Y. [
Row effects, 行效应
" P; L+ d5 i; i; F {' G# X6 iRow factor, 行因素
) S( D2 G% K) C$ t& HRXC table, RXC表' x+ q5 o& V$ v/ |8 p
Sample, 样本
1 ?. G1 J8 k H) P3 A4 vSample regression coefficient, 样本回归系数9 Q5 s) z# C/ e
Sample size, 样本量$ `" g9 o( G6 i+ U: m
Sample standard deviation, 样本标准差+ B1 {6 ~/ a$ z$ _
Sampling error, 抽样误差8 O8 q N; s* |
SAS(Statistical analysis system ), SAS统计软件包
0 h3 R B) T( ^; x8 WScale, 尺度/量表
+ p5 |7 D3 r9 q4 z7 fScatter diagram, 散点图
5 `; X5 \$ g( Q8 @' I/ WSchematic plot, 示意图/简图4 E" I5 Y1 b2 o6 B/ h N0 R! j
Score test, 计分检验6 z( q1 _, N7 q! j" C
Screening, 筛检
9 C6 @9 B# g$ M/ ]; n* I) `SEASON, 季节分析
8 H0 x1 D/ ~2 Y: }Second derivative, 二阶导数0 i1 w# J& [1 i+ p6 m. h# H
Second principal component, 第二主成分0 k% J# {. N0 Y2 y- p* U
SEM (Structural equation modeling), 结构化方程模型
$ T& U; `) Q! ^8 E# G& ^7 o1 d3 u% wSemi-logarithmic graph, 半对数图: E) J+ d4 m+ W, `
Semi-logarithmic paper, 半对数格纸7 A& a8 A& t ?1 S4 ?3 y' i! v3 O
Sensitivity curve, 敏感度曲线
4 w4 N- _& K" D9 o. Y% G- W1 cSequential analysis, 贯序分析
5 h" E9 p( T9 D' @: ^Sequential data set, 顺序数据集
3 s3 Y a6 Z4 GSequential design, 贯序设计* [) e; L2 h: ^, z/ P2 ~
Sequential method, 贯序法
8 d3 ]7 \3 \; h& @" ^8 @Sequential test, 贯序检验法% O" W5 z O: I' B8 n
Serial tests, 系列试验
$ \* l2 W. P/ C! V6 O! iShort-cut method, 简捷法
5 ?$ P: \% g3 x0 w' q9 YSigmoid curve, S形曲线
5 [5 a* G; E7 e+ S$ PSign function, 正负号函数& a- f9 H/ V) G! c6 y* A
Sign test, 符号检验% B$ ]" ^6 n; b" E1 t F7 X3 F
Signed rank, 符号秩. N9 ?8 I! M6 a$ |: O+ P
Significance test, 显著性检验: V* I5 a9 n4 P7 j' o
Significant figure, 有效数字5 r4 v# n5 b: M0 \" I d3 G, A
Simple cluster sampling, 简单整群抽样
5 k7 U4 e# `- c( ?Simple correlation, 简单相关
) W. d) k. b7 V/ }& dSimple random sampling, 简单随机抽样( X7 s% Q, s. ?1 Q3 }
Simple regression, 简单回归
5 a6 x: L O' I& i: ~- fsimple table, 简单表
! y3 ?5 o! C/ E# R/ _6 MSine estimator, 正弦估计量: J" H+ b7 z0 [% R5 ~5 f
Single-valued estimate, 单值估计
" u ?6 j) p, N7 U* w: KSingular matrix, 奇异矩阵0 ~4 E. S9 P& }" E0 E. x
Skewed distribution, 偏斜分布
4 n& D$ j+ e6 K( DSkewness, 偏度
3 v# i! N8 Q7 T& PSlash distribution, 斜线分布; d y2 @; x3 I5 E: W% ]2 E6 h2 Y# y
Slope, 斜率
' ?# F2 a: H d o u7 sSmirnov test, 斯米尔诺夫检验8 n; @3 y, {' x* G+ e) Z e
Source of variation, 变异来源
' V) }2 v0 |) s- O+ w* O3 w) ]6 i; s" J+ ~Spearman rank correlation, 斯皮尔曼等级相关( U3 |9 X. U3 d: x6 C4 K2 T7 p) \
Specific factor, 特殊因子
. U$ y5 \0 E3 }$ V7 }6 m8 wSpecific factor variance, 特殊因子方差
7 V& f }6 d, t% K' \7 h wSpectra , 频谱
- F: l; {0 v. g( v* kSpherical distribution, 球型正态分布
; k) W' r! f; [3 wSpread, 展布
7 A4 `/ A+ a! W6 l- {! t# [. j' \SPSS(Statistical package for the social science), SPSS统计软件包4 o9 D1 J5 w9 S
Spurious correlation, 假性相关
8 h, G8 C) y4 pSquare root transformation, 平方根变换) ?; [$ u/ i8 g, Y k5 z9 C. {4 [
Stabilizing variance, 稳定方差
+ d9 N& G$ q& J% O2 z5 u4 U/ ?Standard deviation, 标准差; G/ L9 o, d: ?, f/ k5 b: C+ x2 R
Standard error, 标准误
, R& Y% p* p% d8 M9 J7 w3 \1 tStandard error of difference, 差别的标准误% ]. ]% b2 j1 N
Standard error of estimate, 标准估计误差. f4 `$ B; q2 I
Standard error of rate, 率的标准误) Z7 f( Y- c- I2 t
Standard normal distribution, 标准正态分布4 S6 Y- D+ R5 h- d9 U! i
Standardization, 标准化( U7 G0 m3 o; v
Starting value, 起始值
+ Q2 r$ ?6 I9 e' dStatistic, 统计量
5 D: w" | q. w6 s" cStatistical control, 统计控制
# V0 [; j I- I7 iStatistical graph, 统计图. h; G. C- G& ]! Y6 Z+ X7 H
Statistical inference, 统计推断& Q/ v# M) x% y! o, `, ?- u5 w1 K
Statistical table, 统计表4 n' \" B& w7 [8 t- e+ b- R' c
Steepest descent, 最速下降法
3 F: F7 i4 t& b0 V) s$ hStem and leaf display, 茎叶图+ a" ]1 Y o' d* z# e% ^
Step factor, 步长因子
0 W+ j5 L1 q1 bStepwise regression, 逐步回归
: E2 I o' P" Y# {: x# ?+ B6 H A8 oStorage, 存
a' |5 R0 N7 S$ G s9 [Strata, 层（复数）" y9 d/ Q, D$ e3 M
Stratified sampling, 分层抽样
, A. n. b/ I# K _( j' vStratified sampling, 分层抽样, M6 S+ V6 T. Z- r0 z
Strength, 强度6 Q: ^3 R( a% G
Stringency, 严密性
8 y. m& ^# O) I" f$ d9 j/ t1 m" ]Structural relationship, 结构关系6 P @9 I2 y! K- C
Studentized residual, 学生化残差/t化残差
1 I) d+ T! I9 \3 G% V% wSub-class numbers, 次级组含量1 \7 c U) O5 Z5 J. u4 d
Subdividing, 分割$ f- u3 M7 [; ~
Sufficient statistic, 充分统计量
+ ?# b8 o0 t& V3 p' h! I9 iSum of products, 积和
4 J- @; d! A- g- R& TSum of squares, 离差平方和/ G' ?# O* K& u. H
Sum of squares about regression, 回归平方和; T# C9 B- U- W) K: p5 M
Sum of squares between groups, 组间平方和
; G5 R- a5 l& \1 w' MSum of squares of partial regression, 偏回归平方和# l* [( ]7 r9 ]. y4 i) H& T4 X
Sure event, 必然事件
; R8 F1 i) v; f+ w; P* a3 g3 ZSurvey, 调查" I/ k9 m. h& p/ [1 E1 V! P; y
Survival, 生存分析
' B8 ?2 {- L: t1 ]( ISurvival rate, 生存率
! i$ T8 S8 o- a% PSuspended root gram, 悬吊根图1 m, j2 J, o, _- S
Symmetry, 对称
) }4 d w: A- P# i k! @3 fSystematic error, 系统误差 Q1 S: o) F' e0 ]3 @3 o. y& }
Systematic sampling, 系统抽样; E; t1 ^- M# \/ s$ f" z& {6 w
Tags, 标签! X0 Z" k; U& w2 ?3 @
Tail area, 尾部面积) \+ D l; |* I5 J0 ^
Tail length, 尾长
& w. M9 c9 B) R) `- t% I6 m9 \4 PTail weight, 尾重
2 e7 A* J+ b( K, ^, p* t& Z" iTangent line, 切线' t+ a6 \! n( ^! R" ~' [( K8 q: p
Target distribution, 目标分布
- R. K' |( k) J+ A8 E u$ V5 ITaylor series, 泰勒级数' P5 L4 Z1 I9 }" m7 Q2 }; X1 @4 R0 r
Tendency of dispersion, 离散趋势$ n3 V- v* C, v0 N( a& N+ X
Testing of hypotheses, 假设检验
( t+ q' q: ?: H5 pTheoretical frequency, 理论频数
1 ]( @- B5 c j# M }4 lTime series, 时间序列
7 D- Y4 s \7 Q- fTolerance interval, 容忍区间
8 F, [3 R. e' c0 z5 |Tolerance lower limit, 容忍下限7 X6 d- W8 q) ]2 ?& Q# W2 ]
Tolerance upper limit, 容忍上限! R6 O8 w4 W, k, m8 [
Torsion, 扰率
. Q0 H; J! [/ fTotal sum of square, 总平方和
4 {0 O* D; `& W* sTotal variation, 总变异
1 a5 |' g2 i# NTransformation, 转换
( a. P7 Y8 y2 t3 l' ?) mTreatment, 处理/ N, i" k4 m2 I
Trend, 趋势
- \$ F o9 ^6 g$ T1 a4 ^4 @Trend of percentage, 百分比趋势$ x/ y/ t3 m0 {% M" f
Trial, 试验
: q7 y' Q2 k% V* S( ` q: t& u* _Trial and error method, 试错法3 h5 H4 f& y5 V
Tuning constant, 细调常数9 ?7 p _, j; a; o. ~; H9 d
Two sided test, 双向检验$ Q, c* U" _: x+ R
Two-stage least squares, 二阶最小平方
4 g+ _6 J& L, L8 r# s) d5 t+ |Two-stage sampling, 二阶段抽样
; j2 k9 i' Q2 A+ vTwo-tailed test, 双侧检验
: j4 I6 Y$ x& ETwo-way analysis of variance, 双因素方差分析
- ]* ]7 y) e% e: gTwo-way table, 双向表
, K1 D5 o2 w0 \5 RType I error, 一类错误/α错误
& n) Y) S3 V3 a* H3 y% \9 |. [( T* OType II error, 二类错误/β错误! g. ]2 |6 l0 C- o5 \
UMVU, 方差一致最小无偏估计简称
/ z' C |. ?" N4 EUnbiased estimate, 无偏估计
$ }! E" X7 y% n! n4 fUnconstrained nonlinear regression , 无约束非线性回归0 b" I: K A, c- x" Z
Unequal subclass number, 不等次级组含量9 Z( T$ P& z2 R0 O( R0 p
Ungrouped data, 不分组资料
4 D; |" Q6 E# v! L* W3 [# IUniform coordinate, 均匀坐标* {5 s x& D) R( ^
Uniform distribution, 均匀分布
9 k* x( `, i. y5 ?& B3 T4 [# [Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计( \$ n7 Q4 P# I+ W
Unit, 单元
) t; q' |. H0 ]7 f& eUnordered categories, 无序分类1 x7 I# C' |2 q# w
Upper limit, 上限, J: a4 W, G2 S7 K# v
Upward rank, 升秩
4 K3 v9 Z w/ l; ~. X$ VVague concept, 模糊概念9 X1 N5 C$ t' c! \1 H3 i
Validity, 有效性
C T _1 F* c5 sVARCOMP (Variance component estimation), 方差元素估计
; g2 e* i( b8 M) {Variability, 变异性' b$ X$ A' }; M3 `% D2 U6 i
Variable, 变量! P, k3 _8 c0 R5 B; N
Variance, 方差
; i6 ~' V" m$ A2 T4 F% u8 N0 h& aVariation, 变异
/ e, g" n& A. nVarimax orthogonal rotation, 方差最大正交旋转
$ g8 k: v* b: y, c9 t5 R* LVolume of distribution, 容积! d4 o1 C) @; x3 D6 M: q2 D
W test, W检验7 G! d- ]8 u& F1 |: z
Weibull distribution, 威布尔分布
/ g( N! p, e2 O' F2 @ cWeight, 权数. {( l( u, S$ a+ U- H
Weighted Chi-square test, 加权卡方检验/Cochran检验3 `, C& n3 i2 L. A
Weighted linear regression method, 加权直线回归
3 f( U" [( Q; {# y- j* ~% |Weighted mean, 加权平均数
, T" M" i# z/ d! R& o( M! Q/ @Weighted mean square, 加权平均方差
: H9 c2 Y7 G9 y/ Z6 hWeighted sum of square, 加权平方和
6 ~4 C5 G6 i4 P/ P, e$ x' RWeighting coefficient, 权重系数
1 D& H7 b) ?: T OWeighting method, 加权法
# ~: R; u4 a8 r8 fW-estimation, W估计量# R% q) Z" N/ ~% G' V
W-estimation of location, 位置W估计量/ w, v* E8 Z9 ]: R# S$ @4 ]
Width, 宽度9 y% i+ ]$ s- q5 j
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验- M0 J% l7 q% f' U# f' t
Wild point, 野点/狂点
' D& P6 ^' F) `Wild value, 野值/狂值8 |* |8 ^* [. ]8 T7 n F
Winsorized mean, 缩尾均值; W" |# M" f1 }4 ~: Z$ d# Z
Withdraw, 失访
7 m% I- u0 O* O0 F6 `! U4 ?Youden's index, 尤登指数
; c7 M( ~" s, A! x9 _1 S0 b+ wZ test, Z检验6 Y0 ]& j: H! g, N6 v7 f8 R; h! f( r
Zero correlation, 零相关, V* _& d1 J7 P( |' Z
Z-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
