|
|
Absolute deviation, 绝对离差: D8 {0 }) j4 X
Absolute number, 绝对数* ~6 T O/ D( z9 m
Absolute residuals, 绝对残差* N5 P9 s4 o) n* P: G4 \
Acceleration array, 加速度立体阵: i& E) S, r, C5 {; U
Acceleration in an arbitrary direction, 任意方向上的加速度
/ Q3 N5 n+ q* J0 P0 d- RAcceleration normal, 法向加速度
! O' x4 \1 U& |Acceleration space dimension, 加速度空间的维数1 B" T& s: N: y
Acceleration tangential, 切向加速度 t% l/ X d K" t2 }) b: l& G
Acceleration vector, 加速度向量
. F5 S! X E. Q7 J' S4 r2 s; C/ g7 [$ Y0 DAcceptable hypothesis, 可接受假设, l0 V7 F5 Z7 v" q2 l0 x" d0 E
Accumulation, 累积* H% x, K1 f0 i: q( J; H; Z& K
Accuracy, 准确度" Z0 m( L* g0 F ~$ w9 Z# E+ O
Actual frequency, 实际频数
; L. K3 b; ` i* O2 ~9 u+ {8 CAdaptive estimator, 自适应估计量: L+ i: [6 h/ r5 j d$ U
Addition, 相加) G) h T: `: w& @# U( Q5 p
Addition theorem, 加法定理2 s! K7 j) C' Y/ y# s9 K
Additivity, 可加性) a9 n" f6 N; C% n! N4 u" Y% y! s
Adjusted rate, 调整率! w0 s2 J1 ?$ y
Adjusted value, 校正值0 Y& T) O. K% L0 ?2 z3 f- s
Admissible error, 容许误差
1 b3 c' h. Z) _7 z. @2 T. U8 YAggregation, 聚集性3 e: o# j/ n( \* S
Alternative hypothesis, 备择假设/ F. i5 G; N- R2 d$ s$ R! ^; M
Among groups, 组间, S0 ?2 D% F- L0 D( e9 z
Amounts, 总量
3 j3 ^9 |( W; d0 ], h* a YAnalysis of correlation, 相关分析6 t$ r: D* c1 K, Q6 b1 T# a# Z
Analysis of covariance, 协方差分析; V2 }( D9 | B6 e
Analysis of regression, 回归分析
* G7 K) ~! H; p4 Y8 F% MAnalysis of time series, 时间序列分析8 x* {4 b7 R$ x/ m6 `
Analysis of variance, 方差分析# y6 ^5 n5 ^# e L
Angular transformation, 角转换3 R( `, O5 Z. d0 N& e1 B
ANOVA （analysis of variance）, 方差分析
, z. t! M& u- FANOVA Models, 方差分析模型, P# p8 ?$ H0 L5 v
Arcing, 弧/弧旋
2 Z: V3 T- X" r$ w7 a+ EArcsine transformation, 反正弦变换, [* I+ P9 u* X3 M; ?0 p
Area under the curve, 曲线面积
4 ~; v* u, L% s0 J8 c" K2 m1 dAREG , 评估从一个时间点到下一个时间点回归相关时的误差
K) o. e2 l' X( VARIMA, 季节和非季节性单变量模型的极大似然估计 & y. W1 T8 b) N
Arithmetic grid paper, 算术格纸
- W6 X: z, r0 J2 nArithmetic mean, 算术平均数 E9 F$ X; P: K( r4 J! R) _# c( F& I+ Z
Arrhenius relation, 艾恩尼斯关系* Y! @5 F1 w; f7 q& H% c/ t
Assessing fit, 拟合的评估$ V' b5 o' s2 }& D$ S
Associative laws, 结合律. ^$ E: w8 v& J$ G8 f
Asymmetric distribution, 非对称分布
, l; F& w% _, \' R3 U2 ^Asymptotic bias, 渐近偏倚
" l; ~2 e3 @7 G3 U$ c- W, QAsymptotic efficiency, 渐近效率' H$ ~; z2 M4 b. y
Asymptotic variance, 渐近方差
5 }( ?- @2 o6 N+ Q9 T# J: |) NAttributable risk, 归因危险度- S) }9 S5 q, S
Attribute data, 属性资料
* d Q5 Q- m; LAttribution, 属性
! R+ w" V3 T, u7 z3 mAutocorrelation, 自相关
. v3 y* q" r/ j* s4 tAutocorrelation of residuals, 残差的自相关2 C3 q$ g" p' K" X& k3 Z9 H
Average, 平均数
; |6 }! o, d! X+ h" k" ^Average confidence interval length, 平均置信区间长度
/ a" b% z5 d* q! ^' JAverage growth rate, 平均增长率
/ L1 A) ^- B* g* ?! j5 r& ]Bar chart, 条形图
. r) E. F/ N2 W+ mBar graph, 条形图
, q/ ~! A; n. X' H* s: SBase period, 基期( @# X* s$ c. P$ Q% N
Bayes' theorem , Bayes定理4 ?8 M# E6 Q4 w
Bell-shaped curve, 钟形曲线' u: d4 i2 [: E8 `- b3 f4 g2 F
Bernoulli distribution, 伯努力分布5 ~8 F: U$ f4 D0 D4 b; Q
Best-trim estimator, 最好切尾估计量' t L* M0 d/ h
Bias, 偏性
* u; | ~" _ R% _7 u/ \; pBinary logistic regression, 二元逻辑斯蒂回归( K3 t# ^8 g. H& y
Binomial distribution, 二项分布
3 M! q/ ]* z- k; R$ Q6 e5 ?1 M0 aBisquare, 双平方
1 f$ B' m; k9 H/ N) {Bivariate Correlate, 二变量相关' U: k& U9 u4 v [0 z! w
Bivariate normal distribution, 双变量正态分布
7 g4 M7 c7 @9 h1 IBivariate normal population, 双变量正态总体: t: X& f1 P- g* q* _" Y
Biweight interval, 双权区间
+ B5 {6 H7 J/ R* |. Q/ oBiweight M-estimator, 双权M估计量0 M5 S9 A9 ~; t2 H$ s8 r
Block, 区组/配伍组
" i; s# i7 e M- H1 v- BBMDP(Biomedical computer programs), BMDP统计软件包
7 t8 o4 @ | M# h0 ?1 u* ABoxplots, 箱线图/箱尾图, E: y! P2 u/ h4 k, D0 Q! r1 J
Breakdown bound, 崩溃界/崩溃点
6 w: ~1 V, u$ M0 LCanonical correlation, 典型相关
: q) N9 Y8 [8 a) T% {# k D! yCaption, 纵标目
, h3 Z. q2 Q. b! }Case-control study, 病例对照研究
3 t3 g# o1 s, |1 [/ C9 W4 a1 d" BCategorical variable, 分类变量/ `" I% f! c* q% {* X+ e
Catenary, 悬链线
% O! F! z R L2 {3 ACauchy distribution, 柯西分布6 E) h; P; {) f# A
Cause-and-effect relationship, 因果关系
; _/ c S/ K" aCell, 单元
3 y7 I- n2 A3 Z d6 o {* gCensoring, 终检
7 N8 w& q# [9 d) r" @Center of symmetry, 对称中心
2 n1 [ z4 Y: l! c1 J2 ZCentering and scaling, 中心化和定标& Y$ k5 m6 W+ u9 G4 Y1 G
Central tendency, 集中趋势8 ^/ i$ ]% M! m7 Q
Central value, 中心值* |$ H8 o7 L* c7 A. @3 [2 A
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测% M- u2 U' ?$ u4 \' _) y
Chance, 机遇: N! p: P- a% x1 l
Chance error, 随机误差
. }: {, B! y- aChance variable, 随机变量
) r6 Y( n; M' y; i0 v3 CCharacteristic equation, 特征方程" ^; R& D$ U t
Characteristic root, 特征根
5 ]' _5 E& h+ V: D( `: ^8 Q! Q( VCharacteristic vector, 特征向量
) j8 @1 I8 o, T0 \Chebshev criterion of fit, 拟合的切比雪夫准则6 a, L3 s3 G6 L) k0 ]6 R$ P+ h( x
Chernoff faces, 切尔诺夫脸谱图 z0 A0 y/ z3 ]$ T' E$ f; q/ B
Chi-square test, 卡方检验/χ2检验0 C$ [. M7 R5 ]3 w2 v5 S4 A
Choleskey decomposition, 乔洛斯基分解. m" \9 h* Y% `2 `! ?
Circle chart, 圆图 ( c5 x8 {: K5 J) D/ k4 [2 r
Class interval, 组距
2 W/ E5 n2 j4 v( B% LClass mid-value, 组中值: y3 a, y5 k! y2 Z
Class upper limit, 组上限
0 J/ N# Z5 p+ O$ NClassified variable, 分类变量
* D* E) B2 D" S( I K2 m6 h3 KCluster analysis, 聚类分析/ R, j: d! R. `6 o# h0 [
Cluster sampling, 整群抽样( \1 |# l$ M5 P% \: N3 h# A
Code, 代码
" X, V! |- E( w+ a3 ]% QCoded data, 编码数据" P$ J- D1 X$ E
Coding, 编码( r1 f5 v) k: I( |. \
Coefficient of contingency, 列联系数% @9 V! a6 A! D. S) j
Coefficient of determination, 决定系数' { @$ A1 q# W% y# w
Coefficient of multiple correlation, 多重相关系数$ l6 w6 f! |9 E- s- Y& k
Coefficient of partial correlation, 偏相关系数2 C/ d8 c% P2 c; H1 O# z
Coefficient of production-moment correlation, 积差相关系数
2 K- o/ m3 L6 c5 M$ a* K1 pCoefficient of rank correlation, 等级相关系数- Z& t) y) U9 }) c9 G h, `
Coefficient of regression, 回归系数
+ ~: @! D& k7 oCoefficient of skewness, 偏度系数) p6 o2 u1 |( g4 k0 T/ t& S
Coefficient of variation, 变异系数0 g6 P" @: p9 l6 W U/ m6 P
Cohort study, 队列研究; q$ Y+ `2 W5 d2 M+ ?5 j$ _5 [
Column, 列
. B( V) R; s1 h4 ^, S) \; O1 jColumn effect, 列效应
. E: N3 [ I& Y2 n. l! MColumn factor, 列因素
: k8 e; O& j7 {Combination pool, 合并3 H2 w1 W) N, n H1 g" }2 ?
Combinative table, 组合表- r( R( o4 C7 o; p
Common factor, 共性因子
, L o5 m4 C% ?Common regression coefficient, 公共回归系数
/ V1 \/ w6 t. {7 H4 x, R' B* k# s$ _Common value, 共同值: l" o2 u) v! _9 L0 c h9 L' D
Common variance, 公共方差
0 j) \. m+ ^' |+ n+ gCommon variation, 公共变异4 J0 N( ]; D( Q g7 f
Communality variance, 共性方差
0 I6 y( H& G- f' N5 |1 \Comparability, 可比性
. O; ?9 ]! a! E3 u6 sComparison of bathes, 批比较8 A, y# U; j* r0 K# r6 |
Comparison value, 比较值
' E2 _" f. M( K- r" dCompartment model, 分部模型, v' i7 b9 W+ Q2 P- j
Compassion, 伸缩- p; r1 H. r; ?3 c) [
Complement of an event, 补事件
9 O; b& L! I7 @- G8 U# Z2 ~Complete association, 完全正相关
1 H: H" Y0 U* VComplete dissociation, 完全不相关
" W+ W/ W' x2 D1 h* H O6 p% `8 `Complete statistics, 完备统计量
6 J$ w0 }' z' Q+ S UCompletely randomized design, 完全随机化设计
; ^9 H9 g9 P5 e; _" ?4 jComposite event, 联合事件
8 n9 B2 m( U9 zComposite events, 复合事件- j; C$ a- N2 s0 C* \
Concavity, 凹性
0 J4 R% ]6 ~' W& K- a( M( Y) y$ CConditional expectation, 条件期望
* {* J) F6 X7 f* x& Z/ jConditional likelihood, 条件似然
5 z9 v& d9 }$ V. G& GConditional probability, 条件概率! ^3 p3 F5 A R7 o, @
Conditionally linear, 依条件线性+ i4 M- V) H+ B3 \; Z
Confidence interval, 置信区间
+ B6 a O& B# E5 b& oConfidence limit, 置信限
8 t2 j, y6 P3 D8 u) x! nConfidence lower limit, 置信下限0 V' {% P5 E: x8 B( \/ f
Confidence upper limit, 置信上限8 C8 p& T3 U9 r) x# q
Confirmatory Factor Analysis , 验证性因子分析
" ~1 j' I. S( P& _, B$ ZConfirmatory research, 证实性实验研究& h" f, _) t; p* O& ~
Confounding factor, 混杂因素! o! L5 ?8 ^/ q- D& M5 w* P
Conjoint, 联合分析
( w: O- U# K6 D9 X* U; uConsistency, 相合性
, A: Q5 z$ ?# O/ e9 O; B6 i; S$ QConsistency check, 一致性检验. {( F. h: K9 I# r6 r8 p
Consistent asymptotically normal estimate, 相合渐近正态估计6 v( z+ K: @( y/ g) E; P' s% N
Consistent estimate, 相合估计+ b2 ^6 L0 e; Q4 A7 W
Constrained nonlinear regression, 受约束非线性回归6 u' s+ W8 Q* k7 Q
Constraint, 约束) m+ k4 f( P7 K2 S' s9 w
Contaminated distribution, 污染分布
- g5 F* F5 \/ h9 m! n5 S+ T* O) lContaminated Gausssian, 污染高斯分布1 R% a! Y) l2 k% u* k
Contaminated normal distribution, 污染正态分布
+ W5 R! {2 {: H! }8 A1 eContamination, 污染
; p( @) t+ `) M. _7 |8 O( LContamination model, 污染模型
# h) f z& `' `& w' uContingency table, 列联表
1 l- u1 `7 A# `; j |& cContour, 边界线
" F* m5 I: h) w! WContribution rate, 贡献率- v0 n7 S, g6 N- X: y, E
Control, 对照
$ K: u! v, r6 G1 A/ @( ZControlled experiments, 对照实验
; Z: j2 [/ u# x8 e& X6 C3 y! wConventional depth, 常规深度) X+ I; H; O5 G0 ^0 O" y' \4 Q
Convolution, 卷积& g5 \8 b4 W5 y. w R
Corrected factor, 校正因子3 i- X2 L* U" S9 ?! r
Corrected mean, 校正均值, ]" J2 Y( R" \" r- T1 W0 G
Correction coefficient, 校正系数- W/ a8 X- Q2 l4 S' c8 g& B
Correctness, 正确性
% @+ J& k8 L1 m# j2 Y( t: mCorrelation coefficient, 相关系数1 W) K3 M4 C/ i U. I& e% c$ I
Correlation index, 相关指数
- F3 D% |) b5 w1 m9 VCorrespondence, 对应' M) W9 g2 ]+ I; c
Counting, 计数, _( q5 ?! ~' x3 u& v) [# C
Counts, 计数/频数0 S* Y# F5 H2 b, T- x/ z
Covariance, 协方差
0 [! r, b( e( S8 L$ QCovariant, 共变 7 G4 k# V2 D; t2 F) t( N9 |2 o
Cox Regression, Cox回归
' h3 _2 E2 f5 oCriteria for fitting, 拟合准则: E' W& B" H% `& R+ J' t2 J5 J
Criteria of least squares, 最小二乘准则
7 Z& s6 X' ~+ r1 u1 R% XCritical ratio, 临界比8 ?* B, h+ t6 a- T
Critical region, 拒绝域
( a( s8 b* r/ {, j+ k7 fCritical value, 临界值: q2 }+ x2 c1 L5 N3 J a
Cross-over design, 交叉设计
' l4 y7 S F9 g) D- I: d7 d' mCross-section analysis, 横断面分析# w8 ]- N& J# p+ F8 w I g
Cross-section survey, 横断面调查
/ `' R- d3 x# n8 H1 xCrosstabs , 交叉表
u/ _" ^* o3 P- W) R* NCross-tabulation table, 复合表
- Z4 Z- V$ P9 @) x! ICube root, 立方根. W) {5 b) K$ F; n
Cumulative distribution function, 分布函数) \ N( g" @# [
Cumulative probability, 累计概率9 G9 s% u! }- S0 T% _3 q$ t. r1 _
Curvature, 曲率/弯曲
" R& r: b3 G$ n8 g6 S, @Curvature, 曲率0 m4 G: R1 k! r' O6 {
Curve fit , 曲线拟和
$ N- o5 ^' U, }1 {+ } ?$ f% W! b4 rCurve fitting, 曲线拟合 P9 M$ T9 ]& E3 c. i, q0 q8 b
Curvilinear regression, 曲线回归
" Y E; q" w3 I, V& G: L* p- xCurvilinear relation, 曲线关系
2 }8 y) O8 [* YCut-and-try method, 尝试法
E0 `( K: _8 ? M- x5 O2 RCycle, 周期6 j0 M/ C/ E3 x* W0 b, y4 I
Cyclist, 周期性
* f; x3 Y+ g/ ~2 w6 SD test, D检验/ s) p% ~0 }- E) {7 v/ o8 F
Data acquisition, 资料收集
7 Q/ [" [- P2 g: o- m$ ZData bank, 数据库' g" O2 ?* j# e6 E
Data capacity, 数据容量
. c; N, ^' M( U1 ~Data deficiencies, 数据缺乏
4 Y: ^ @. k! [8 ~* @$ C& ?* x1 `Data handling, 数据处理1 M U( s/ a' f1 ?( b1 b4 C( @
Data manipulation, 数据处理
1 u* t1 P4 m# W; h% qData processing, 数据处理
, D2 |, f: u0 L: x: ]Data reduction, 数据缩减( m$ k6 K6 e5 i3 D
Data set, 数据集
7 w$ l4 ]8 G2 f. [1 `Data sources, 数据来源
+ a) y. k9 ?# |6 [Data transformation, 数据变换
8 D( Z; f, C, d3 E$ X- N6 x" BData validity, 数据有效性, r- V j6 l8 D2 t
Data-in, 数据输入
6 q& N; }+ S0 Q! i6 FData-out, 数据输出
( v' y! h4 f1 c2 B# xDead time, 停滞期" H$ O1 c) u2 }- ~& S; N
Degree of freedom, 自由度
( b7 g4 S) Z& X7 t" qDegree of precision, 精密度
; `# p& j( D# O# V" k/ Y$ y2 f+ J' SDegree of reliability, 可靠性程度
7 @) J6 F( y! KDegression, 递减
2 X) g4 A6 k) X) ADensity function, 密度函数& F3 z: J" Q" \# a5 g! P- U3 K- v
Density of data points, 数据点的密度
" ~2 @3 k6 A% }+ QDependent variable, 应变量/依变量/因变量4 k2 \- r( D5 O8 S
Dependent variable, 因变量2 x; |8 @* j4 P9 m
Depth, 深度
; B$ O `+ \- _$ e- V. XDerivative matrix, 导数矩阵
$ S' J- X# U; RDerivative-free methods, 无导数方法
- a, n. e9 X7 i1 yDesign, 设计
1 B7 |1 s& o4 t. H `Determinacy, 确定性
' s0 I& M" S: m" w8 ^$ i# M' SDeterminant, 行列式4 z: l. _' m+ D X
Determinant, 决定因素
6 T7 f( N. `" x, LDeviation, 离差
# m ]) j) ]. F& B, V+ ^9 p/ c/ y VDeviation from average, 离均差: e8 g, H! k1 L+ C
Diagnostic plot, 诊断图
) L$ b) `0 [4 \7 |5 W$ VDichotomous variable, 二分变量) R; x+ s6 z* Q
Differential equation, 微分方程
4 t9 z, d T6 ]: g4 ]Direct standardization, 直接标准化法
8 A$ ?2 Z8 k3 w' ]! X4 h9 F. tDiscrete variable, 离散型变量5 N+ y+ F/ b" f! h$ [5 L
DISCRIMINANT, 判断 3 A# O( O: N; w
Discriminant analysis, 判别分析% S7 Z! q8 z) R3 C4 h$ D
Discriminant coefficient, 判别系数3 g$ v ?+ N& ]
Discriminant function, 判别值
3 E6 x! i( d5 F- K! r: uDispersion, 散布/分散度
, v# {4 O5 i3 g* t& uDisproportional, 不成比例的
! ]# `4 Q- w% N' v* e- }" PDisproportionate sub-class numbers, 不成比例次级组含量9 A- B. E6 o7 x3 k% h* z
Distribution free, 分布无关性/免分布
6 {2 h& T. ~; GDistribution shape, 分布形状5 G: o& c7 _- W/ Y' W
Distribution-free method, 任意分布法
( g2 G' h0 B9 c9 v/ MDistributive laws, 分配律
2 T: @0 G- X7 Y* @) H- N9 E$ Q3 u" qDisturbance, 随机扰动项
* n, n/ q4 L' S6 A' r6 ]- JDose response curve, 剂量反应曲线
# B5 P) ~: J& |) K4 iDouble blind method, 双盲法8 p6 f p# p% B" w6 S
Double blind trial, 双盲试验
* h" [8 L2 z* K' A3 \) _. H6 M& [Double exponential distribution, 双指数分布- o/ M" c1 _. [* A6 v+ Z* _
Double logarithmic, 双对数+ ]/ R/ `& i0 t, {4 _. n
Downward rank, 降秩7 m3 p' c. r% j7 P1 r
Dual-space plot, 对偶空间图+ n8 e, k( h4 ^
DUD, 无导数方法
. l* b" E9 ?7 {% JDuncan's new multiple range method, 新复极差法/Duncan新法- K$ Z3 o* o" W1 n
Effect, 实验效应0 Y7 p/ G& E( ~+ }+ n# N
Eigenvalue, 特征值
, Z8 F5 |! k3 x6 @Eigenvector, 特征向量
! ?: l6 }5 f) zEllipse, 椭圆
7 I$ Q+ c0 ]7 J5 S. k CEmpirical distribution, 经验分布
2 s0 n2 b! k9 t" e. xEmpirical probability, 经验概率单位: `/ _6 f5 N$ [: R: p. S4 q
Enumeration data, 计数资料4 c' ^& Q$ H2 h' v; S9 q
Equal sun-class number, 相等次级组含量8 V& U) {: J1 f, O. y, Q/ \4 s) q
Equally likely, 等可能. E/ a- ]' k0 J$ D5 r3 u4 d2 p
Equivariance, 同变性! | t1 Q5 l9 R+ ]4 ^
Error, 误差/错误+ \2 I/ }; w/ ~" @7 O \& Q4 Q
Error of estimate, 估计误差
% |& F7 i% \5 F$ v( c& K, J9 iError type I, 第一类错误& B Q4 S- q9 I: e2 p
Error type II, 第二类错误6 C& [' M/ g- @, D% ^
Estimand, 被估量2 ]* a/ f. ^+ k' {" K; Y" x R
Estimated error mean squares, 估计误差均方
3 G1 B2 y! M& uEstimated error sum of squares, 估计误差平方和$ `) K5 V3 x2 \6 C9 R8 Q1 i9 e9 {7 s
Euclidean distance, 欧式距离
1 j& G* P: J3 X3 e' q/ D. oEvent, 事件3 j* |9 W, {, R3 p- N& p) G
Event, 事件
" v5 _8 c+ x: yExceptional data point, 异常数据点( o# a: M/ z' Z. i1 S* ^: Z
Expectation plane, 期望平面
0 Q8 b) x0 Q5 \% F" jExpectation surface, 期望曲面3 Q6 x, W2 Q _* l
Expected values, 期望值
3 _6 n( a* s! \3 E# w6 L" yExperiment, 实验9 [) n+ b; i7 G, c" ]& T
Experimental sampling, 试验抽样
( l" {+ f+ h+ w/ K/ wExperimental unit, 试验单位
( c( g8 k2 c! |7 W( \& v7 Y# xExplanatory variable, 说明变量' ^5 d5 j) p0 _8 c6 H
Exploratory data analysis, 探索性数据分析0 X2 Z& U' U; h u. ~( S: G: r1 l; {9 w
Explore Summarize, 探索-摘要
2 h) ^5 p8 ]5 a: Z! z- j4 C, RExponential curve, 指数曲线# B0 @7 R( x; w% r/ u3 P
Exponential growth, 指数式增长- U" q0 k1 z1 s8 b
EXSMOOTH, 指数平滑方法 7 _1 i3 @) R% Z0 x1 j- n+ G# A: [
Extended fit, 扩充拟合
/ P- i# b2 M! u _9 hExtra parameter, 附加参数4 O# U+ l* J. P4 j) y& G9 h
Extrapolation, 外推法6 g8 p4 ?& U4 h4 {& ]4 s% U
Extreme observation, 末端观测值: K4 |$ A& w6 h4 k3 }1 q7 Q
Extremes, 极端值/极值9 {% T/ D% [* B4 [+ \8 i
F distribution, F分布4 j0 Q8 G6 N$ H. [
F test, F检验
5 I' h4 J2 E+ s9 @Factor, 因素/因子# r5 d* z3 W: H+ K/ i3 `
Factor analysis, 因子分析
0 T7 l' p, p, v; o$ KFactor Analysis, 因子分析
7 r, t, p. b, `- N, y8 w2 v3 PFactor score, 因子得分 & ?- r- g, y' H+ @( z
Factorial, 阶乘
2 U3 R2 {, R, ~; k0 g: H) Y$ R7 TFactorial design, 析因试验设计
4 L* k/ Q+ C" M) xFalse negative, 假阴性0 }1 U% N0 h0 w+ z5 `7 m9 }! X! Q/ s
False negative error, 假阴性错误
# Y. T. }4 ^( m) n. Z) L5 \Family of distributions, 分布族
2 P7 x( k* Z, _2 l* m& k, G" x0 ?: w6 wFamily of estimators, 估计量族
- {6 Y/ {& g- c' K( w/ gFanning, 扇面( }7 K- X9 a" m, ^
Fatality rate, 病死率* l4 d3 k* _9 X* T) U1 D6 N0 C, j
Field investigation, 现场调查8 L/ X+ v# Y5 ^. o- j7 c! i
Field survey, 现场调查
) ^/ H: r& e# q1 Z$ P/ W% rFinite population, 有限总体
! a1 H2 l, N1 m6 H% iFinite-sample, 有限样本3 ?. v: ~( Z3 ~0 `
First derivative, 一阶导数" t' N% M$ G: f
First principal component, 第一主成分
# S$ Y* i/ n% F$ L1 k% eFirst quartile, 第一四分位数9 S. p- |+ x3 m( d( d
Fisher information, 费雪信息量+ @6 T# h# I7 r! U- E
Fitted value, 拟合值
& E9 S" ~4 f( l2 `% F3 ZFitting a curve, 曲线拟合* q; q g. u$ }2 A7 e# m
Fixed base, 定基
" x; \8 `' o6 S7 T; b3 |4 [: uFluctuation, 随机起伏" b% f% c" t- x' a4 y0 v
Forecast, 预测; F) _" M# N: F$ B
Four fold table, 四格表7 s% I' j* Y8 }2 ]
Fourth, 四分点& J9 h. {( W/ S8 f5 b5 y5 y& r& y1 ?
Fraction blow, 左侧比率
) x% a- i- X/ W7 L$ YFractional error, 相对误差
5 D \6 K7 [" a' H" ]' f8 U' dFrequency, 频率! _ p) A" Q* E
Frequency polygon, 频数多边图# q1 i2 r* L% B% I# D) Y* Q
Frontier point, 界限点
?4 s( r! Z1 c7 Y. pFunction relationship, 泛函关系% X2 ?! p: X# M1 O% j0 l1 Y
Gamma distribution, 伽玛分布
4 ?' r8 Y9 ^! NGauss increment, 高斯增量
7 N' m* Q1 P) O9 G) AGaussian distribution, 高斯分布/正态分布. ?- k. |5 V' T* b+ k [
Gauss-Newton increment, 高斯-牛顿增量
. ~& n$ F/ W5 l, hGeneral census, 全面普查
* q, b( a4 a8 x8 R% vGENLOG (Generalized liner models), 广义线性模型 ( X" A+ T! S. {5 i$ {$ k8 V& u8 o
Geometric mean, 几何平均数 l" y9 r; r o' F/ ^
Gini's mean difference, 基尼均差* A8 {$ s9 n/ H! E! S$ n& j- m7 f
GLM (General liner models), 一般线性模型 % k |2 Q* o1 }- N
Goodness of fit, 拟和优度/配合度, x& y2 X* C7 [; p
Gradient of determinant, 行列式的梯度8 a/ T- E H. s
Graeco-Latin square, 希腊拉丁方
, [' A3 H- X& ]' P2 }! b: X+ v9 dGrand mean, 总均值
4 {7 r0 h6 f& e" ^! b: u5 H( {: {Gross errors, 重大错误, K* i9 m6 ]: j x. |/ r: D& h# u
Gross-error sensitivity, 大错敏感度1 V) h% j" N/ V u2 D6 v) q
Group averages, 分组平均" j" M" K* {8 R! A/ m* g* q
Grouped data, 分组资料4 E: u5 N0 t1 |( ` d5 \2 i7 }
Guessed mean, 假定平均数5 _6 Y3 i( N0 @0 I
Half-life, 半衰期
& ~( F) h1 {4 f. h$ Z; s' R+ MHampel M-estimators, 汉佩尔M估计量0 u% [& M |- q0 G1 ]
Happenstance, 偶然事件
+ { b2 ?/ f% T6 a9 A$ QHarmonic mean, 调和均数2 R$ [5 S) K$ R( }& a* C
Hazard function, 风险均数
) B/ I( o2 N2 Y- a# V. w/ UHazard rate, 风险率/ F* @, C: m( K0 u) m
Heading, 标目 " W* f3 X, z% O6 u
Heavy-tailed distribution, 重尾分布
. a" B# `* g' H; l6 H' l6 fHessian array, 海森立体阵/ d2 J1 q. m Z' F) A1 F
Heterogeneity, 不同质
1 q$ n! l) C. s B; [$ {3 J' MHeterogeneity of variance, 方差不齐
8 a5 |% z: }' \/ _ K* tHierarchical classification, 组内分组/ `8 h! J0 _# b% V
Hierarchical clustering method, 系统聚类法0 c4 S& ]- b' _! f& E3 ?6 K6 s, Q2 U
High-leverage point, 高杠杆率点, Z& Z% O7 i, [8 |: ^& d) X
HILOGLINEAR, 多维列联表的层次对数线性模型
2 x7 Z( D- e" Y; ~) a, U t; \Hinge, 折叶点: O! D! t+ I* W- V4 z
Histogram, 直方图8 s, _# d! o$ V2 h
Historical cohort study, 历史性队列研究
# ?4 y) X C' C- xHoles, 空洞) {2 b/ R& F4 f* n
HOMALS, 多重响应分析
o( t! y! J7 m) b& _6 _Homogeneity of variance, 方差齐性
0 ]( U- o" d: ~6 F" kHomogeneity test, 齐性检验6 \* @& r, b) T8 L6 D G
Huber M-estimators, 休伯M估计量
3 m+ i V2 V: l& w2 w' ?7 S* KHyperbola, 双曲线 t( Z3 K' P9 D, h2 J- y0 ^# H
Hypothesis testing, 假设检验7 ]& ~9 j: T f2 {
Hypothetical universe, 假设总体
+ ?1 E. X1 i# F1 {Impossible event, 不可能事件
, {7 s0 r, u8 Q3 y; BIndependence, 独立性
4 C5 t2 S6 J5 S2 Y7 lIndependent variable, 自变量/ ]4 j, W* T" L: e# h6 h4 w
Index, 指标/指数
# _6 j: q" t7 Z6 f! J1 X. SIndirect standardization, 间接标准化法6 W H8 E/ A3 [' ^- f x+ c
Individual, 个体
! b5 h5 L( k! y P/ qInference band, 推断带
# X6 X. z5 y9 D' JInfinite population, 无限总体
2 v, A" e q8 J# t5 m3 wInfinitely great, 无穷大
- v# A) q2 ]0 X9 S2 x& I- YInfinitely small, 无穷小
! R+ @8 t1 ]. X$ cInfluence curve, 影响曲线& s( e: m K' }2 N4 @! @% p
Information capacity, 信息容量
0 a1 f/ y3 |/ P6 YInitial condition, 初始条件
; y0 {9 W0 D* ]' c% J* E' rInitial estimate, 初始估计值
7 J0 c7 g' G* V, {Initial level, 最初水平
6 z. a; K$ O- s! M7 `Interaction, 交互作用
# m5 n" x8 A3 v3 s: T+ y, `0 NInteraction terms, 交互作用项4 s% m7 M+ V+ Y4 r3 |( j
Intercept, 截距
& F0 T8 w( ], E0 G6 a4 mInterpolation, 内插法- l$ A6 N5 F m2 ]$ b
Interquartile range, 四分位距$ e5 d4 h4 U5 E6 s
Interval estimation, 区间估计
V+ u/ U8 n% A& n0 aIntervals of equal probability, 等概率区间 y1 [% `3 j$ E1 ~$ D- O5 B' ^
Intrinsic curvature, 固有曲率
, w7 { q2 M! b+ fInvariance, 不变性! K5 F5 D/ \( o4 q% i, \: L
Inverse matrix, 逆矩阵
# N- d( @* c! e; YInverse probability, 逆概率
# n+ H- f$ R3 G0 R0 ]6 l: FInverse sine transformation, 反正弦变换) z4 J$ N- v1 L: I& e. k
Iteration, 迭代 * I; P# V9 Y S6 e8 A6 o5 a
Jacobian determinant, 雅可比行列式
& W$ ^' U! A/ M1 }( s F( x* tJoint distribution function, 分布函数% v9 I! I+ h) F. F( ?( M+ H
Joint probability, 联合概率
. }/ z3 x) w* h; h: K TJoint probability distribution, 联合概率分布( C: H" F- k5 d( D3 d; F
K means method, 逐步聚类法
! _ I) v6 Z4 n8 Q' _Kaplan-Meier, 评估事件的时间长度
! [/ d. w2 I A5 E5 h' x5 FKaplan-Merier chart, Kaplan-Merier图3 y- d) O' K1 [9 J; ]- B
Kendall's rank correlation, Kendall等级相关
0 _ f: N4 f" d7 B2 L: wKinetic, 动力学2 K% f" Q6 |2 u: c
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验 @/ S) D( A9 L! L0 o E/ \
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
5 Q) i8 P6 p' KKurtosis, 峰度
" Z6 a0 u; h5 A2 j- L2 CLack of fit, 失拟3 c5 F5 c0 L- A, \" W6 I* U. E
Ladder of powers, 幂阶梯
+ `- z/ U2 V8 D7 L3 H' n8 u3 V1 vLag, 滞后
9 Z1 ]! o6 x e/ ~& PLarge sample, 大样本( O: Z% J! ^; s! S/ R/ k
Large sample test, 大样本检验1 a5 \& Y2 I) _ M
Latin square, 拉丁方3 S. r$ T* Z G! n* [6 q
Latin square design, 拉丁方设计0 V/ C1 c* D3 w
Leakage, 泄漏7 S& b" o+ h/ } N$ ~6 F# I: A9 P
Least favorable configuration, 最不利构形+ {: k, \. Q+ w: \0 B8 `& W P; `# ^
Least favorable distribution, 最不利分布 ^! O% [) R; F) l3 D7 d9 G/ w* p
Least significant difference, 最小显著差法% {# m/ g8 m' V/ b# @& a. V; ]
Least square method, 最小二乘法
+ P- {# N. |- j. ]* R }Least-absolute-residuals estimates, 最小绝对残差估计2 H' G L. |! h0 q9 U
Least-absolute-residuals fit, 最小绝对残差拟合/ M: D8 Y* h1 r8 g% u
Least-absolute-residuals line, 最小绝对残差线* T+ O. C* D- j' ~% U) z
Legend, 图例
+ A8 P3 R6 r9 [2 p; TL-estimator, L估计量
, Q& H* @7 c. S3 WL-estimator of location, 位置L估计量% y6 @; `# L3 `: g
L-estimator of scale, 尺度L估计量
( K4 \4 L& a2 T5 RLevel, 水平
1 g: }1 i9 I, Y! C0 d3 fLife expectance, 预期期望寿命/ |% R$ ` h d) P
Life table, 寿命表" [+ J7 s$ a, K. T. N; Y) i" }
Life table method, 生命表法2 \0 e' P r& v# e( [: r
Light-tailed distribution, 轻尾分布
; Z+ [3 B* |+ L) j$ dLikelihood function, 似然函数
0 x. k$ N6 @- L( k: W( SLikelihood ratio, 似然比* [ f. k+ R; p5 J. h
line graph, 线图: n6 d3 v4 k2 o$ r" ?4 |4 z- o
Linear correlation, 直线相关
) O3 K" q# G9 J! c( V9 CLinear equation, 线性方程
' [5 H' q# z7 J/ |& FLinear programming, 线性规划5 A/ T$ ^+ U N. O. U
Linear regression, 直线回归
: T+ d+ G6 j" ?. O+ q0 B: e- Q# GLinear Regression, 线性回归
6 ]2 b# J* w2 s9 q" ALinear trend, 线性趋势$ Y' d. S6 |3 E+ S
Loading, 载荷
( M; a. ]& o" | p7 q ?Location and scale equivariance, 位置尺度同变性
+ x3 ?3 l! y# A' O+ Y2 @# ]7 T% qLocation equivariance, 位置同变性
$ S& D; m, T6 G; kLocation invariance, 位置不变性
% e! B+ E6 F9 k+ @+ u8 `Location scale family, 位置尺度族( h; w& d, o# j5 ~
Log rank test, 时序检验 - v* l: f; a) h: H3 c
Logarithmic curve, 对数曲线5 v" L6 e: |% b- \
Logarithmic normal distribution, 对数正态分布! t5 a+ J6 {+ }. m' r9 i
Logarithmic scale, 对数尺度
0 i$ q0 d: {, p, F* @Logarithmic transformation, 对数变换0 a' ^$ u! u) r w( S
Logic check, 逻辑检查% C' A- v; l( o# ^& z
Logistic distribution, 逻辑斯特分布
1 }+ `4 k+ }# RLogit transformation, Logit转换2 a7 k4 A6 Y0 V9 ^& w6 R2 w9 g
LOGLINEAR, 多维列联表通用模型 1 T; L: H/ P/ }8 C- I0 w
Lognormal distribution, 对数正态分布
2 x. |+ D+ w, S9 O; B" QLost function, 损失函数
+ f# u/ C4 d& C, wLow correlation, 低度相关
; f" A! T$ V9 c) y5 q% kLower limit, 下限' b. m# ~9 Y& B, Y3 a+ `
Lowest-attained variance, 最小可达方差) X+ G) {0 c2 W
LSD, 最小显著差法的简称
5 w5 ]! s1 ^" z! b4 |5 @% e' [/ RLurking variable, 潜在变量3 @8 y) r1 {/ w U* p6 a4 `
Main effect, 主效应6 Y a! Y# L+ a0 B8 i5 V5 i0 f
Major heading, 主辞标目" Q) i2 m8 V- m. u
Marginal density function, 边缘密度函数1 }3 b- y6 y H* K- K4 m
Marginal probability, 边缘概率, l3 f3 j& ^. c- Q9 F3 b% _
Marginal probability distribution, 边缘概率分布
$ X( ~( c, {. C- D, Z* jMatched data, 配对资料: B g/ ?( f' b: Q/ I. ]
Matched distribution, 匹配过分布7 F: h1 F9 e: ^8 m( X8 [0 F& E/ _
Matching of distribution, 分布的匹配) m" d! V" `! w1 |3 Q/ F/ ?
Matching of transformation, 变换的匹配
9 y; @$ s/ X1 C' y$ o" S$ VMathematical expectation, 数学期望
( l6 v6 p, t, kMathematical model, 数学模型
% X7 @& W9 s8 n7 ~6 WMaximum L-estimator, 极大极小L 估计量! l4 X& z/ I+ T) N1 C! S. X
Maximum likelihood method, 最大似然法! M, \5 Q% K( q3 N3 j5 G5 R: U' a+ f
Mean, 均数. c6 b( }' n- p/ }% ^- j
Mean squares between groups, 组间均方
0 ? e* w2 Q( q, G, x; ZMean squares within group, 组内均方5 y/ @2 m# Z; p G' U
Means (Compare means), 均值-均值比较. Z D/ M" i2 Y& E5 B( J' l6 o
Median, 中位数
% ^/ K# C+ }6 ^( ^. MMedian effective dose, 半数效量( V9 N/ ?( ~2 b o* q
Median lethal dose, 半数致死量
+ S" n# n6 ^ t( S1 t5 iMedian polish, 中位数平滑, ~. ^' t# H5 j/ s' a* [
Median test, 中位数检验
* o/ ?9 z' R: v8 M& k2 |Minimal sufficient statistic, 最小充分统计量
; o4 k; D) Y6 ]) X& K5 rMinimum distance estimation, 最小距离估计- S' I1 t5 r& l" M; _" c
Minimum effective dose, 最小有效量2 U8 P7 x w3 V5 E. y% x( H6 p% v
Minimum lethal dose, 最小致死量
1 t+ D, ^ D7 J( dMinimum variance estimator, 最小方差估计量
6 f" e, @" p. z$ k8 k: D( Y2 z& `MINITAB, 统计软件包3 w& {! H, Z f. ~! f3 W' y
Minor heading, 宾词标目4 G2 i' @. h( Q" I% y v
Missing data, 缺失值/ a9 N& T5 z n( I; n$ h# c
Model specification, 模型的确定* k6 l+ ?1 s2 @+ U5 f( m+ B
Modeling Statistics , 模型统计8 q# M F8 D- ?' ]
Models for outliers, 离群值模型8 \$ A- ]) Y: @* P. ~/ N& M% |! |
Modifying the model, 模型的修正2 {0 E$ ^( a0 Y- S2 l2 Q. O3 j; w$ h$ j
Modulus of continuity, 连续性模: X2 s' \ b1 W5 n; A9 \9 r" c
Morbidity, 发病率
0 K: m; O9 f8 r* JMost favorable configuration, 最有利构形/ O; B- R( G! j; w6 N! ^1 o) b3 l$ k" p
Multidimensional Scaling (ASCAL), 多维尺度/多维标度3 |+ z6 [$ f0 D& W: d- E, O
Multinomial Logistic Regression , 多项逻辑斯蒂回归9 r7 {8 M% H/ a+ t
Multiple comparison, 多重比较
7 u; s( z0 j) l8 x6 ?Multiple correlation , 复相关
( j, i- l, U8 |9 iMultiple covariance, 多元协方差/ S( V, n2 E O5 e
Multiple linear regression, 多元线性回归
% m9 t8 I/ q4 xMultiple response , 多重选项
( M; p3 T2 L4 H. `$ lMultiple solutions, 多解
: o* T1 J# a YMultiplication theorem, 乘法定理
$ J' E2 n+ ]6 I1 nMultiresponse, 多元响应
5 z, R) h' U; jMulti-stage sampling, 多阶段抽样
( P" b, t4 k- P4 G3 AMultivariate T distribution, 多元T分布3 T, f( b' n J, g% F+ i6 c" |
Mutual exclusive, 互不相容
" Y6 `( o$ p0 j4 k/ j% PMutual independence, 互相独立$ E4 F' W+ t! y! o |1 P/ M6 D" p
Natural boundary, 自然边界
2 u5 J* P' ^+ w, W% e {7 nNatural dead, 自然死亡1 i$ C/ o \/ A
Natural zero, 自然零
4 H# [$ ?" ]/ t1 T; S- {Negative correlation, 负相关: I! k+ m8 z; X5 X$ B, ^8 T
Negative linear correlation, 负线性相关, `, L# w L5 I" c3 j
Negatively skewed, 负偏
* X' Z# g+ I; ]- ENewman-Keuls method, q检验8 n! k7 c2 w- x# t
NK method, q检验8 A/ B. ^% i+ q& J
No statistical significance, 无统计意义
- D; M/ W* N2 X# YNominal variable, 名义变量6 k; e# p; |4 w9 h h
Nonconstancy of variability, 变异的非定常性
( f5 a& n) [# s% m @- u% O C2 gNonlinear regression, 非线性相关4 [& o. j1 w6 Q) k3 D* U1 B
Nonparametric statistics, 非参数统计( P' b5 g% Z. B+ |. O6 e1 H
Nonparametric test, 非参数检验
2 {3 E% g& `& X( sNonparametric tests, 非参数检验
( Y1 y9 I9 e5 R' v( D% K/ e/ c! ?Normal deviate, 正态离差5 T/ ~% w' t7 W" y* p4 V2 ^
Normal distribution, 正态分布
0 [2 c9 Q$ N0 L0 [) [' N' _4 `4 cNormal equation, 正规方程组
1 }% |7 |2 l9 F5 ^* oNormal ranges, 正常范围
) C! {, o2 d0 Y# F0 i# |Normal value, 正常值* P: [1 ]& H4 u( E2 D. X3 `. w" X s
Nuisance parameter, 多余参数/讨厌参数" e' p6 b( A6 Z% j/ J1 v' D9 I1 x
Null hypothesis, 无效假设 6 m, q5 W3 a) I$ }
Numerical variable, 数值变量% Q3 T, z+ B) f' X3 t
Objective function, 目标函数' ?" n- n0 Q* m) M. F! M4 w
Observation unit, 观察单位: k+ Q% }, ^; N; U- B% G$ @
Observed value, 观察值
1 B D$ L* X6 C5 g! ]One sided test, 单侧检验$ |# O* L- t+ C* K7 ~! H3 O
One-way analysis of variance, 单因素方差分析
4 m9 q) M2 I; p, jOneway ANOVA , 单因素方差分析
" Z0 D2 }* g' z( SOpen sequential trial, 开放型序贯设计
) ?4 R. M5 \" ~Optrim, 优切尾
0 I' v% M" t4 gOptrim efficiency, 优切尾效率
$ H) o1 y( T0 iOrder statistics, 顺序统计量7 q, ]' Z# x. i& H9 c+ s
Ordered categories, 有序分类
% ^$ s1 N$ p# P* V# X! Z0 ?( {- wOrdinal logistic regression , 序数逻辑斯蒂回归
+ m3 K; H+ r7 [% K/ D7 ZOrdinal variable, 有序变量2 Z: s, |, C& X6 x3 w* i3 j4 {
Orthogonal basis, 正交基
1 v+ k9 J5 t- A$ A ZOrthogonal design, 正交试验设计
7 [" r3 V; z6 J) J: y) f4 {$ s9 ~Orthogonality conditions, 正交条件, W, p! @, h7 R# p g4 x
ORTHOPLAN, 正交设计
- D% O9 X( s; P4 ZOutlier cutoffs, 离群值截断点* V6 e8 u! I3 y' ~6 n0 o1 h
Outliers, 极端值9 ?0 p( X( D, M6 A: V) }- Y
OVERALS , 多组变量的非线性正规相关 6 R2 E9 _0 k- k; n) F' k$ \
Overshoot, 迭代过度- x5 P( M2 O: z2 V
Paired design, 配对设计
5 V l [3 e3 {$ f( b8 N$ NPaired sample, 配对样本
* r& P+ V ]. PPairwise slopes, 成对斜率
+ Q y% K5 D6 a5 g" { @Parabola, 抛物线
! j* F6 N( |8 n; U7 eParallel tests, 平行试验
8 s- g3 J+ }! ^4 mParameter, 参数) ?3 k1 U& Y# ?0 ]
Parametric statistics, 参数统计
% x' k3 S5 L2 XParametric test, 参数检验4 c) E: ~. @, I/ X; m3 f% G
Partial correlation, 偏相关
' e9 w" C2 |6 [6 MPartial regression, 偏回归+ P) D: j0 x( R' [; ]
Partial sorting, 偏排序* e- K: k9 a# @3 O- V0 H
Partials residuals, 偏残差+ ` H' Z% ?' ^) W7 M
Pattern, 模式% D/ c4 I9 x. i% Z- D# B: i' n: T
Pearson curves, 皮尔逊曲线
( _7 x) C/ ^$ I* u3 \ TPeeling, 退层5 ^, e) J. j6 s; K. Q- @
Percent bar graph, 百分条形图) q# f0 o' c1 x/ n: k u9 p" k
Percentage, 百分比
0 A9 z, l J4 _% b) gPercentile, 百分位数
) u$ d& ~' o. t! {+ L" WPercentile curves, 百分位曲线
; y+ m! q% ^7 L q, s5 D# P) z' BPeriodicity, 周期性! i6 i5 P: T4 h5 s0 o
Permutation, 排列
. K; e) h$ n5 L# ~, ]4 vP-estimator, P估计量4 N- E, B0 F* V' ]
Pie graph, 饼图; ?8 W. c. a2 K, S
Pitman estimator, 皮特曼估计量
- c" ~; x$ g" z1 E( X7 }! k( ?Pivot, 枢轴量! e- J; R- }0 z3 Y5 u) f
Planar, 平坦
* Y/ `' i3 R; o* u* I iPlanar assumption, 平面的假设
- }8 w" [4 a9 z* k1 {; aPLANCARDS, 生成试验的计划卡
5 t2 x, W0 N! c- ]Point estimation, 点估计+ }* W, G8 z3 d& J
Poisson distribution, 泊松分布
1 Q8 \8 S% V& {0 F, u( wPolishing, 平滑
! u0 l1 B& ^3 f6 p4 e% J8 UPolled standard deviation, 合并标准差" D7 Y5 Z& X) l1 Y& V
Polled variance, 合并方差
$ I& O) n5 V) c% F1 dPolygon, 多边图
# `9 _% F. o0 \# ?) cPolynomial, 多项式+ r8 m7 a2 N1 x5 F+ F) t
Polynomial curve, 多项式曲线
$ |2 U4 {9 r, t; A0 T) u2 x: R7 wPopulation, 总体% O5 [3 ~+ B# w2 h c, c3 Y7 Y
Population attributable risk, 人群归因危险度! }7 U$ l" J, {6 `/ e$ _
Positive correlation, 正相关) \: }4 I1 d2 h1 `5 ?8 e
Positively skewed, 正偏
& y& q6 Z! E) t( J" [Posterior distribution, 后验分布6 ]% z, _ s6 _ ]
Power of a test, 检验效能3 \' k6 j, t9 i# ^$ f
Precision, 精密度1 H, \( ~# O! \" y/ {" I
Predicted value, 预测值
- P. f0 e. ]8 T& QPreliminary analysis, 预备性分析
% Q% m4 t' p7 V; y0 mPrincipal component analysis, 主成分分析
; b. m% C5 j; X7 B+ [- W) ]( [2 bPrior distribution, 先验分布
# b1 w/ L- H! _ K- ZPrior probability, 先验概率
8 A% N: w6 d+ H# t. B7 ^& S/ fProbabilistic model, 概率模型+ B( n" X& i, H( T; U0 G2 W) R
probability, 概率% A2 y7 u9 v$ S7 c
Probability density, 概率密度
" }! w, }# g* w2 _8 M! ^$ X4 pProduct moment, 乘积矩/协方差; l- G( T: E8 Q8 c# K# K
Profile trace, 截面迹图" t& G% R) |2 u8 c
Proportion, 比/构成比; P7 y3 r0 Q# _/ A
Proportion allocation in stratified random sampling, 按比例分层随机抽样9 }1 z& u# N7 v9 n0 {
Proportionate, 成比例
8 [7 m r0 J. ~* ~: Z. V, w, VProportionate sub-class numbers, 成比例次级组含量
# A0 E1 S" [# \: p2 zProspective study, 前瞻性调查
5 X! @* ]2 m. S W1 PProximities, 亲近性 7 U/ _- @" h @4 h
Pseudo F test, 近似F检验
; A. l, q+ f" G, S7 u. SPseudo model, 近似模型
1 _( }7 G. D* e5 F. gPseudosigma, 伪标准差
+ y7 u9 H8 F2 W6 o0 g7 y5 kPurposive sampling, 有目的抽样1 n4 A) c+ T; Y g, P/ U2 D$ n# w
QR decomposition, QR分解
2 {8 }% K. }8 I" t2 p% C! qQuadratic approximation, 二次近似5 G* E' X+ F7 X* k5 q: M8 q9 O( l
Qualitative classification, 属性分类0 ^7 @/ j& r# {9 Y* @
Qualitative method, 定性方法. b% Q/ \# y9 }7 W0 v7 N) g5 f
Quantile-quantile plot, 分位数-分位数图/Q-Q图; M) M; n3 t! f. d9 l6 w: d
Quantitative analysis, 定量分析
/ ?% N& F/ r9 U6 ZQuartile, 四分位数0 q4 {* X2 N' s; f$ b% P3 z" E
Quick Cluster, 快速聚类! O& [& w4 ~5 p" {# L' E/ w5 Y* P
Radix sort, 基数排序8 ~ b' l: h W8 ~) y: `; P% M
Random allocation, 随机化分组
e! v9 o9 s8 xRandom blocks design, 随机区组设计
+ s' h5 a& c5 r, e$ p. @ |% l2 q" XRandom event, 随机事件
' Q- R: D) Y: M* Q! p; CRandomization, 随机化
! |! u& ?+ O# e3 T$ X* kRange, 极差/全距
z, L2 ^/ }! k% U* U/ mRank correlation, 等级相关
1 [1 t, v, a% U3 A2 eRank sum test, 秩和检验
8 a% k% S1 R4 v' F5 g CRank test, 秩检验' h9 n& H' L2 _
Ranked data, 等级资料
& y& Z% W. m- u- iRate, 比率# t! H/ O4 {8 S5 u ^: b6 D$ K: g
Ratio, 比例
/ D. F5 K" |! h* \6 ^5 XRaw data, 原始资料
2 D3 F1 C, J5 F, f$ w9 |) {/ u$ A5 jRaw residual, 原始残差
2 W, {: b9 a# i% ]+ IRayleigh's test, 雷氏检验, s' Z. l9 ~' Z+ y# R+ c& Y
Rayleigh's Z, 雷氏Z值
y/ ?+ d1 t$ Y: N Y: \# J2 IReciprocal, 倒数; i0 |4 e7 ], n
Reciprocal transformation, 倒数变换
$ S+ j" ^7 b7 m9 y; jRecording, 记录# w m4 f4 K6 E& o' `
Redescending estimators, 回降估计量( z! Z8 R( X0 X( R' O
Reducing dimensions, 降维; }( J% j5 x/ H
Re-expression, 重新表达
; T& L- i ]# B1 ]# mReference set, 标准组* J# V/ C/ z( I) T/ M7 M b! i
Region of acceptance, 接受域! ?7 J/ K! L3 |" m
Regression coefficient, 回归系数
a, v# X0 }0 @5 m- g2 `! lRegression sum of square, 回归平方和% X& M8 q' Z! }, w b3 o% a) _
Rejection point, 拒绝点* q8 ~& K& m$ H# ]: k
Relative dispersion, 相对离散度
9 Y, {$ A+ F, _2 J( E+ X' BRelative number, 相对数
@! D# ^& W' t1 ^3 w, |/ @8 ?& ]5 p$ qReliability, 可靠性
; ]# m- f: B5 k, EReparametrization, 重新设置参数) o; ?. t+ C- k, ~( g7 }( }* h
Replication, 重复
$ N" j6 V" E) _: G$ A+ a& g5 z/ MReport Summaries, 报告摘要
2 w' C- z5 W- W4 J- {2 tResidual sum of square, 剩余平方和
' w: U/ ]7 H% I9 M6 BResistance, 耐抗性& t! S$ a& {6 j4 Y
Resistant line, 耐抗线" @( O3 _* h0 | \# c, G7 U0 T
Resistant technique, 耐抗技术6 O1 c; w" t/ a$ z% I
R-estimator of location, 位置R估计量- c: w" X/ I# q4 H; ~7 k
R-estimator of scale, 尺度R估计量) s( m; }+ o6 ^
Retrospective study, 回顾性调查
' N% z- ~$ J8 m+ v3 u6 L) A3 PRidge trace, 岭迹; X* `2 U8 }* z, P8 r6 t2 s$ j8 a- N* S
Ridit analysis, Ridit分析
1 h6 o# Q$ @5 Z& ARotation, 旋转% t; \+ l8 k1 E) x7 A6 X
Rounding, 舍入* u' `! ^! e3 _7 a" R/ C
Row, 行. I% t% D. l3 T# @- y/ P+ a
Row effects, 行效应
: O" z7 J$ [5 m5 l+ Z6 sRow factor, 行因素
' s! V& x0 ^- c9 p. rRXC table, RXC表
# }, J7 c- n7 o( w4 MSample, 样本
. ^0 F9 E& W4 cSample regression coefficient, 样本回归系数: E$ A0 \1 B0 N9 q0 V( `
Sample size, 样本量3 f2 a, ?4 }: |, {% w
Sample standard deviation, 样本标准差
0 u( c8 L1 K) h9 a3 OSampling error, 抽样误差
3 N- o. o0 t) n) n, FSAS(Statistical analysis system ), SAS统计软件包
/ H8 _) G5 F+ b3 D) aScale, 尺度/量表 W/ s) N0 B: U( @3 r
Scatter diagram, 散点图
/ S2 p) v5 L& B) zSchematic plot, 示意图/简图$ U/ Q q( W! D9 z, j2 S; x' t
Score test, 计分检验) v$ ?0 h4 v: H6 R
Screening, 筛检- `9 X+ h v9 {; g
SEASON, 季节分析
1 C, f* B$ p6 m6 a0 G, r5 XSecond derivative, 二阶导数
2 d2 \. l L/ t' t w `) b* V3 YSecond principal component, 第二主成分% S3 R! x$ L9 D2 @" {3 d) I9 L/ H" f
SEM (Structural equation modeling), 结构化方程模型 ) R: d( G" f+ M8 V+ H7 {
Semi-logarithmic graph, 半对数图
# D( c! e, @1 s# W" nSemi-logarithmic paper, 半对数格纸5 n( f! m! d) P% h1 l4 K7 x" ^
Sensitivity curve, 敏感度曲线
# Y1 d8 G5 e/ ~- LSequential analysis, 贯序分析
% H5 n/ b5 Y* r1 u3 BSequential data set, 顺序数据集
3 m+ c0 @* O0 _Sequential design, 贯序设计' t8 h5 A2 x1 h4 g. W$ N/ q/ p
Sequential method, 贯序法
% L& p- r% L9 ]( n9 t. b/ pSequential test, 贯序检验法
2 z, [2 R; I; tSerial tests, 系列试验0 K. c' W: y- V$ B! y' Q5 g3 J
Short-cut method, 简捷法
5 W/ \. ^% I$ G" Q1 L, e! L+ S6 M9 n, _Sigmoid curve, S形曲线
5 D9 Z2 b0 d7 m, N7 P8 Q# ESign function, 正负号函数
& ]3 j, W' ?, a5 u2 K( b) NSign test, 符号检验1 `' G$ J8 B% l2 m6 u' h+ n& G4 a
Signed rank, 符号秩$ R* ]4 H- z& m
Significance test, 显著性检验) p9 F! ]- L3 N" K
Significant figure, 有效数字- q, [& v K v3 F0 i! ~: C9 h; }
Simple cluster sampling, 简单整群抽样3 ^) O/ S$ T n. R/ Q" N
Simple correlation, 简单相关
8 n$ D# A9 E2 X! S. q2 TSimple random sampling, 简单随机抽样
9 e) l1 \0 ^" h' k) R- {2 ~: |6 XSimple regression, 简单回归
[6 S" T" p" ?2 z1 Csimple table, 简单表
3 Z7 Y, F4 y. n4 _5 jSine estimator, 正弦估计量- ]& _0 b- w9 O& \. u2 c& O- N
Single-valued estimate, 单值估计
1 U! ~; h. T1 y* USingular matrix, 奇异矩阵
2 [8 T V% F! N- g" [' I" rSkewed distribution, 偏斜分布# Y/ `2 d1 x# \1 A9 y* c
Skewness, 偏度
. k" E4 Y; d$ D7 ^! ~- qSlash distribution, 斜线分布
0 I8 Q, M, ^( L6 Z9 [Slope, 斜率
8 p( N6 U* s, c7 k4 V" \Smirnov test, 斯米尔诺夫检验) w1 r% ? f+ w& `" X5 q+ Z
Source of variation, 变异来源
$ T; w6 y, ^( D. A oSpearman rank correlation, 斯皮尔曼等级相关
/ o4 q& m% c0 [# c( c* zSpecific factor, 特殊因子6 G! c x) q+ d& j5 D! W# y
Specific factor variance, 特殊因子方差
7 u' o9 y7 c2 A$ t9 d, sSpectra , 频谱' K. I/ M; V) X: @ u% ]% S
Spherical distribution, 球型正态分布. o/ p4 z4 w; g! r% q
Spread, 展布$ p; t* W+ C2 D9 q4 W% j( P: e
SPSS(Statistical package for the social science), SPSS统计软件包
; u9 l# Y! W, D2 U. GSpurious correlation, 假性相关" a; u( u4 ^# k& L, C; u/ ?4 X5 n, X
Square root transformation, 平方根变换
2 C1 k, {" x+ p3 n, oStabilizing variance, 稳定方差* y' u3 o+ b( T5 D
Standard deviation, 标准差
5 L4 x# v3 q; P( w# ~0 bStandard error, 标准误
/ O1 |( W% z4 e: B4 w; Y; [Standard error of difference, 差别的标准误4 F4 P# i# N# P" o# A
Standard error of estimate, 标准估计误差
; I. U8 @) J, k$ }. [/ NStandard error of rate, 率的标准误: Y4 v2 ~2 d7 a+ `, v1 f- |4 B
Standard normal distribution, 标准正态分布
# O6 ?9 V! V/ u. ]- W: R: q. K2 eStandardization, 标准化
4 \2 f" a( q+ g4 \! f+ uStarting value, 起始值
1 x) R/ }# u' w8 B0 ]# C" kStatistic, 统计量
, R0 J0 x0 q/ A/ U0 RStatistical control, 统计控制
( M8 H: t" a# g0 p- _. m9 a, kStatistical graph, 统计图
; ]& S7 r4 Q2 AStatistical inference, 统计推断
6 j8 C2 m3 x! \: U! k" t1 @6 l: uStatistical table, 统计表# E9 X, S+ g7 }& v+ k
Steepest descent, 最速下降法( G0 U' S, }7 _1 j- _1 e k9 }
Stem and leaf display, 茎叶图
' S2 z* N- T% V& ~7 |% B5 i+ ?" @Step factor, 步长因子
( ^3 U- j+ b2 B1 jStepwise regression, 逐步回归1 \. R% b, p' v$ m! @9 d; i
Storage, 存
% ~( {3 r p6 h: j+ N( H0 rStrata, 层（复数）; ]5 [: O( N' Y" @* W, r& u+ _/ V3 D
Stratified sampling, 分层抽样
4 ^' [3 F* H0 b( l& k! w2 A/ RStratified sampling, 分层抽样+ n K N' M* {/ ^6 t
Strength, 强度 `! B2 o3 |. p. X+ {6 V# ~& P
Stringency, 严密性/ z8 B3 S, F, t: o/ T c+ S7 K) Z$ l! d
Structural relationship, 结构关系
1 d) w( f E& R% E4 ~* jStudentized residual, 学生化残差/t化残差
& q, v" A4 ^# _* E/ [0 u4 }Sub-class numbers, 次级组含量+ [ n: I; b1 n# S
Subdividing, 分割
$ G& C6 E& @1 v( I" q3 d8 OSufficient statistic, 充分统计量
2 f0 H3 l; F1 Y3 ^Sum of products, 积和4 D$ \( ?7 A2 [6 m! k$ s
Sum of squares, 离差平方和
( G9 u2 z9 ?& qSum of squares about regression, 回归平方和* j5 G) Z$ J2 w5 _
Sum of squares between groups, 组间平方和
$ g# L( S0 Q+ A( W+ QSum of squares of partial regression, 偏回归平方和
. C7 k" F! b2 \$ Z8 T$ zSure event, 必然事件0 J- k8 F# V: O$ D( c i, U
Survey, 调查7 o- N0 ~9 H4 `2 A& |4 O
Survival, 生存分析
9 l9 C. n8 e" r- P/ n- ASurvival rate, 生存率5 ~" t# A9 V7 n3 j+ b/ C b
Suspended root gram, 悬吊根图$ ?5 f; r1 c2 N8 @7 I1 k
Symmetry, 对称7 d3 J$ p% i" |$ a& }5 ]4 Y
Systematic error, 系统误差
5 N- N1 v" Q, z" A& CSystematic sampling, 系统抽样- U \2 Q* u) |4 ^
Tags, 标签( [ ~. Z4 ` F8 t4 G, y) Z+ ~
Tail area, 尾部面积
9 w8 s5 ?$ c. tTail length, 尾长; e, @; [' u% h8 x% J
Tail weight, 尾重, Q' {( ~$ Z2 m* o6 y+ }$ h4 U% [
Tangent line, 切线& ?7 d6 z# M% L
Target distribution, 目标分布
& s& M3 e$ F! x( ^9 ~# o% nTaylor series, 泰勒级数
2 X! \6 X+ y; q5 oTendency of dispersion, 离散趋势
& j8 Q; |, |, J: u, s1 C( VTesting of hypotheses, 假设检验1 q8 @. h% I3 L6 o3 n) d" y* T
Theoretical frequency, 理论频数& [$ ]7 x, y4 M5 L# K9 Q
Time series, 时间序列
* Q2 u' Z7 b6 a7 dTolerance interval, 容忍区间; O: n; G- i4 y! P
Tolerance lower limit, 容忍下限
; k( `0 ^* a9 S+ cTolerance upper limit, 容忍上限; h9 s$ ?* N& j/ n5 D
Torsion, 扰率( s7 t: R$ d o: |8 c- `
Total sum of square, 总平方和# C/ h; d S6 h- e! q
Total variation, 总变异; Q0 \) s7 r! b0 T P! n! g7 k9 D5 g
Transformation, 转换
& S) _) c: m+ l" L6 b( nTreatment, 处理- k E2 C3 O& \* N
Trend, 趋势) U6 m ]& \! P3 z4 N" t0 k! H! q
Trend of percentage, 百分比趋势$ R6 a& ^3 O1 M) k% H- _9 _- |
Trial, 试验
4 G( L4 R& k6 G& B dTrial and error method, 试错法% ~& p! X( o _; W
Tuning constant, 细调常数7 @1 h. Q) M9 M8 D) V; V
Two sided test, 双向检验- e2 b3 N" t2 z7 T1 T$ p- x
Two-stage least squares, 二阶最小平方+ T$ Z) _; F# m6 f
Two-stage sampling, 二阶段抽样2 l/ w) r0 z- J. p
Two-tailed test, 双侧检验3 o a: u L5 Q! n' R
Two-way analysis of variance, 双因素方差分析5 x) J7 ^0 G' D# |& v7 ?( c
Two-way table, 双向表
, d: P3 Y' z; M" g8 G0 x. QType I error, 一类错误/α错误+ Z7 D4 g! s% q9 z
Type II error, 二类错误/β错误! A* v9 {! F7 ]# t% H) m1 R4 v
UMVU, 方差一致最小无偏估计简称4 ~% v7 W" Z! E m* e: h/ K
Unbiased estimate, 无偏估计
. k/ T) ? |4 K! P( H! i! l& FUnconstrained nonlinear regression , 无约束非线性回归2 k% ~! P8 E: @! x, _- J
Unequal subclass number, 不等次级组含量
; B* J* F% _4 `: k$ W. g; DUngrouped data, 不分组资料4 e5 R$ e6 A% u' j! Y0 _
Uniform coordinate, 均匀坐标
3 k0 v" q0 c9 U c1 G: AUniform distribution, 均匀分布
! \) ~4 K, j6 g, A$ |( U a' DUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
& r x* l9 b0 iUnit, 单元
0 \3 c6 g# k; b: y, YUnordered categories, 无序分类' V1 J3 y# a, O: ]/ T8 H
Upper limit, 上限7 H2 [( Z; ]1 x7 }3 a" _% s: ^" I
Upward rank, 升秩
/ K+ n* }. k }# G% RVague concept, 模糊概念
, r: K, L4 c; f. F4 aValidity, 有效性1 e+ @/ ]5 E2 u
VARCOMP (Variance component estimation), 方差元素估计
0 n9 K- |0 R( @6 C; F v, q" Q! OVariability, 变异性" o- r! z: \3 O+ l0 ]
Variable, 变量
7 i- g+ L8 B, Y. @7 IVariance, 方差+ g, z. _( m7 O3 y9 O8 D8 e
Variation, 变异
$ f. o2 J( M0 A5 S! Y# xVarimax orthogonal rotation, 方差最大正交旋转
q+ u, q2 d& L5 D. d$ ~Volume of distribution, 容积
9 J* P4 ?# e" [W test, W检验
* q; }8 \% d- V# O/ k0 tWeibull distribution, 威布尔分布" o2 T, W$ j, `" D; G
Weight, 权数. N& |1 B( V* }. L' p
Weighted Chi-square test, 加权卡方检验/Cochran检验& R! Y* t1 p) B& f8 I
Weighted linear regression method, 加权直线回归9 K* V+ ^, I- y0 ~2 Y0 F5 I
Weighted mean, 加权平均数
, }4 T& J9 x, ?. r" q/ E" Y* `, XWeighted mean square, 加权平均方差
- U/ O, Q; {7 ZWeighted sum of square, 加权平方和6 ]" u, Q( _5 G6 @
Weighting coefficient, 权重系数7 v4 F$ ]/ \2 d6 j' m2 M- L* g
Weighting method, 加权法
, i4 N, b) d& FW-estimation, W估计量
; f( ~$ s M" U& i9 E) I& t- U7 dW-estimation of location, 位置W估计量
% g7 V) |8 Z2 t0 cWidth, 宽度
" A3 W8 x9 T( h- a3 f; YWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
& _" j6 b+ z! ?. L6 @' j' AWild point, 野点/狂点
. h+ H% N; O" r$ YWild value, 野值/狂值% ?- w1 m, _& J( D7 F4 Z
Winsorized mean, 缩尾均值0 L, L9 i, l* q: A7 U2 |; N* B- }1 J
Withdraw, 失访 + B) d9 q4 X6 [' k1 v' O
Youden's index, 尤登指数1 D; ?! C7 j8 j9 o4 | _" w
Z test, Z检验
- t+ z- N& Y+ g1 T. f: D3 DZero correlation, 零相关
! L' ^% {- K- yZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
