|
|
Absolute deviation, 绝对离差
) w3 D8 f+ q5 h B1 aAbsolute number, 绝对数4 |6 e7 p4 z* F: }0 T- a6 \; J
Absolute residuals, 绝对残差% O! P. l6 w8 e) ^
Acceleration array, 加速度立体阵: G, A; I: }7 l. B) v
Acceleration in an arbitrary direction, 任意方向上的加速度9 E _% i! l$ Y* w
Acceleration normal, 法向加速度
* u$ A. v$ c1 }! h# l( DAcceleration space dimension, 加速度空间的维数
2 K# V" b, N. _0 J6 ~$ P/ QAcceleration tangential, 切向加速度
" R8 m/ w. R6 K) KAcceleration vector, 加速度向量
r' z2 _+ Q3 G/ P5 j& yAcceptable hypothesis, 可接受假设
- s& }1 \7 u+ m' |Accumulation, 累积
# z, d' r* l a6 S3 {Accuracy, 准确度
I8 z/ H6 G& O- f M/ AActual frequency, 实际频数
/ k2 L7 u) K! xAdaptive estimator, 自适应估计量. u2 _! @5 l5 d# M8 R" a
Addition, 相加
+ Q' U# o, f# Z& ~5 N& \8 c: K: HAddition theorem, 加法定理; C+ m" a7 G8 L1 O. ` u: W
Additivity, 可加性
% V" L8 H; k' c% s+ cAdjusted rate, 调整率
- R0 N8 X# d6 g7 V: A! ?) PAdjusted value, 校正值
) w. m7 Q- x/ xAdmissible error, 容许误差
: B H* ]( G" n% t8 EAggregation, 聚集性
* e0 z- J5 ^4 v* _) LAlternative hypothesis, 备择假设
6 g s; ?" i8 [( l& P; eAmong groups, 组间, E& P2 M6 Q% H& T. _' q$ J
Amounts, 总量5 `7 A8 \+ [; k
Analysis of correlation, 相关分析
' E3 `& L) i" R' F( vAnalysis of covariance, 协方差分析
" Y" h0 L1 J g, A4 iAnalysis of regression, 回归分析
0 y) V% j5 p9 x* W$ SAnalysis of time series, 时间序列分析
. k$ z6 K6 d/ P) n; FAnalysis of variance, 方差分析7 V$ E9 [6 B! F- p; o$ S/ Q$ a1 O
Angular transformation, 角转换4 ~# ?! [! `4 d2 m) V4 H
ANOVA (analysis of variance), 方差分析- D o% s8 ]8 x3 G$ x6 u; U1 g6 }
ANOVA Models, 方差分析模型5 }: d- Q; g- @5 J
Arcing, 弧/弧旋+ `9 h8 w0 K& Z1 b1 j- p8 W; }+ R
Arcsine transformation, 反正弦变换" E; P$ Z" c ~( j9 \$ l
Area under the curve, 曲线面积
2 U* A6 B; S+ |$ ^- c# p. sAREG , 评估从一个时间点到下一个时间点回归相关时的误差
0 r3 }" }2 ~4 s" w, OARIMA, 季节和非季节性单变量模型的极大似然估计 # r4 I+ c1 A, d* C
Arithmetic grid paper, 算术格纸
8 `* H. o: ~: b. {& z, [Arithmetic mean, 算术平均数
6 W1 t2 Q: I! X; z7 U, iArrhenius relation, 艾恩尼斯关系
d* x: A5 H& ~- s" }Assessing fit, 拟合的评估
# p L5 Y; W% C* H7 S m2 A \Associative laws, 结合律
2 Q t0 N& l; x, z" HAsymmetric distribution, 非对称分布
, Z+ g6 X1 D) a, D! o* i0 r2 t, HAsymptotic bias, 渐近偏倚7 r X/ r! [9 \8 k
Asymptotic efficiency, 渐近效率
8 p2 {; _4 L* }) iAsymptotic variance, 渐近方差
2 }3 v! _9 G: bAttributable risk, 归因危险度
0 p' F% [9 d0 ]- wAttribute data, 属性资料
- B; v7 T) p% g- LAttribution, 属性
2 I$ Z' L8 D" n! J1 M% s& xAutocorrelation, 自相关! z2 `- g, v8 x- S: E7 `& r
Autocorrelation of residuals, 残差的自相关
9 K( m% n1 e& W: P& Y& yAverage, 平均数& g6 c. Y! }2 Z3 a2 s& [
Average confidence interval length, 平均置信区间长度
1 f' i5 y$ T$ ^* B. Q/ ^Average growth rate, 平均增长率! _/ c( {2 Q$ I7 L
Bar chart, 条形图
) h9 |: g5 w9 n7 x ^- D* ABar graph, 条形图8 D* g/ D- G0 E' n
Base period, 基期% F( ^1 a% k0 G9 i# T- n! T
Bayes' theorem , Bayes定理3 S9 I9 x1 e4 W. ^1 t
Bell-shaped curve, 钟形曲线
$ [/ N# @5 | l* n5 zBernoulli distribution, 伯努力分布( |* m- K$ y# z" ?9 \/ o) q8 N
Best-trim estimator, 最好切尾估计量8 s% l" G/ `0 I! q1 \
Bias, 偏性; m( M2 d* I8 D2 j3 F4 M
Binary logistic regression, 二元逻辑斯蒂回归. v, A; l" w$ a3 x. _
Binomial distribution, 二项分布
, _0 t# `- l7 d J/ kBisquare, 双平方* k9 g* ~$ `( C# I7 D
Bivariate Correlate, 二变量相关1 f% g1 m* E# m( B Q! n2 S
Bivariate normal distribution, 双变量正态分布
; p. b% O' {7 c/ KBivariate normal population, 双变量正态总体
9 ?$ k, x+ ~1 o) QBiweight interval, 双权区间! |+ K0 c& R: K3 v7 M8 i5 d
Biweight M-estimator, 双权M估计量9 n/ d9 @$ y1 ~' i. @
Block, 区组/配伍组2 w! P' I+ a) D" a5 t9 U& Q
BMDP(Biomedical computer programs), BMDP统计软件包9 h# R: ] [! g3 q: K
Boxplots, 箱线图/箱尾图" P. C$ Z- M; f: e% ]& y0 U
Breakdown bound, 崩溃界/崩溃点
8 F9 A3 a" A2 d5 d- k" v9 o5 bCanonical correlation, 典型相关
% }, q& Q, _+ TCaption, 纵标目2 Q! L. o1 S5 h0 H: `/ a7 i
Case-control study, 病例对照研究
* h3 S5 Y/ h9 U3 @, e/ qCategorical variable, 分类变量" i: w* @: F; m5 K2 k! j( {' g$ j& q) G
Catenary, 悬链线
# [6 k# i8 o" u( O+ J7 @4 M) HCauchy distribution, 柯西分布
~) Q0 y+ y# ?; l: B; y9 qCause-and-effect relationship, 因果关系
2 M3 y8 d/ L1 c5 U8 FCell, 单元& t4 l3 k: L& \& h9 ]
Censoring, 终检7 t; `3 ^9 [& N+ H6 N# G
Center of symmetry, 对称中心
' K0 k2 o" w! W0 y# D8 F1 x. FCentering and scaling, 中心化和定标
# y1 ]: P1 J6 U- xCentral tendency, 集中趋势( \1 z2 U( S, {, i; F( |3 }' \! X
Central value, 中心值# G4 L8 }. _! x: K- g! E
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
2 l. _, ?3 \! A- sChance, 机遇
# c# {# X k$ T: iChance error, 随机误差
+ J+ j' m' ~( I& \2 g/ aChance variable, 随机变量
1 u5 L: b) P+ e7 }Characteristic equation, 特征方程3 C& \' S) h9 G! H a
Characteristic root, 特征根
# a8 p% U! ^+ t& n3 n0 b3 xCharacteristic vector, 特征向量. h" D! j# e7 N" @) s
Chebshev criterion of fit, 拟合的切比雪夫准则! l; U* m5 z5 W; i8 F2 I [
Chernoff faces, 切尔诺夫脸谱图+ B4 Z% h+ u+ F; P+ _) b, a
Chi-square test, 卡方检验/χ2检验
$ k, ~, n- w7 u4 M9 S* c$ q$ U0 @+ HCholeskey decomposition, 乔洛斯基分解
: n9 k" ?2 c6 K; o9 kCircle chart, 圆图 : I ~1 y! p" S# f
Class interval, 组距
8 y$ R( M9 [! U) qClass mid-value, 组中值
! Z" k7 v+ R3 z$ d" k& Y; xClass upper limit, 组上限
2 |! p b1 G9 M' n) @8 F6 BClassified variable, 分类变量
, k8 W. a( i! J mCluster analysis, 聚类分析. V8 G% e* ?9 L
Cluster sampling, 整群抽样
/ j. d- `7 r% a+ L4 k, I# ?9 g/ }Code, 代码
0 l; q" {: A! j. Y" j- NCoded data, 编码数据$ L& m% g* o/ Z3 D( p
Coding, 编码* g! j" V6 J$ a
Coefficient of contingency, 列联系数
6 y. G6 O- z9 {( [: \; C8 nCoefficient of determination, 决定系数
- M4 s4 S6 d( HCoefficient of multiple correlation, 多重相关系数 Z3 J' { K v, S! Q( u, O: }
Coefficient of partial correlation, 偏相关系数) a/ G3 I) z X9 a( D+ v. u
Coefficient of production-moment correlation, 积差相关系数
~) Y$ z. Z/ N9 m! UCoefficient of rank correlation, 等级相关系数8 Z5 J) G9 f& ^
Coefficient of regression, 回归系数- m2 Q8 \: r2 Q# x. y- ]" T
Coefficient of skewness, 偏度系数/ A- Q0 I( j; R V/ N
Coefficient of variation, 变异系数3 m/ I( J; O- r. A8 R
Cohort study, 队列研究
- l" E+ k" ?9 i0 d$ dColumn, 列
2 T7 E1 ?6 h9 K* V6 V! d, F* ZColumn effect, 列效应: m* r7 A: G- C! q) w Q
Column factor, 列因素
) e+ t5 W2 D3 a) bCombination pool, 合并4 Z6 b6 ?+ Q+ ]9 |4 O4 k
Combinative table, 组合表
8 I$ N* n$ w1 \' ^ g, Z& pCommon factor, 共性因子; F' k- a3 g3 z m
Common regression coefficient, 公共回归系数! S, M* y# E$ @2 M) ^
Common value, 共同值
( \5 d) x" F( B$ m# mCommon variance, 公共方差
[ o( ]1 }! _* s8 uCommon variation, 公共变异
9 j- n1 l( D# f6 P( H* d( cCommunality variance, 共性方差
! G' r6 ]! T1 j* h2 bComparability, 可比性+ m! h0 l1 D: v% C) _6 x/ z- S$ w
Comparison of bathes, 批比较
4 n. y a; K' Y* P% ~/ VComparison value, 比较值4 N/ [7 d4 h* d2 P" M* `
Compartment model, 分部模型2 ]* T2 w! `9 | z" P. ^2 L. z
Compassion, 伸缩
2 X" j& Q- c7 Y, T6 OComplement of an event, 补事件
1 h# t2 c4 [$ pComplete association, 完全正相关
) i1 X. o. |# n& f! ^$ QComplete dissociation, 完全不相关- r4 Q1 L4 ]- O" Y; O
Complete statistics, 完备统计量+ @ U1 F4 ]1 `% f; Y/ g
Completely randomized design, 完全随机化设计
( c7 n( D+ |( i, V3 N0 [- \5 _8 wComposite event, 联合事件1 I4 D* q0 \# |+ ]
Composite events, 复合事件
, R& F% ]6 P, a4 i: g' g \Concavity, 凹性
. b7 a* i' L$ q% p3 ?Conditional expectation, 条件期望
/ v, C& O }) \4 k3 z3 D+ WConditional likelihood, 条件似然
* H" R( J$ Z# I, ~9 i" rConditional probability, 条件概率
/ w( p* X' R4 e7 AConditionally linear, 依条件线性
4 E2 _1 R/ i9 p4 o: }9 JConfidence interval, 置信区间
! P E2 J5 B# }/ G) r- ^, zConfidence limit, 置信限9 W' U0 x* ^' r) j8 R
Confidence lower limit, 置信下限& r" i& ? w8 p7 N: T- i
Confidence upper limit, 置信上限# U1 S7 X* F0 H5 h; N) T* c
Confirmatory Factor Analysis , 验证性因子分析9 ?. D6 D& O0 ^
Confirmatory research, 证实性实验研究0 n- @9 `& A/ T1 [( \4 ]# X0 C
Confounding factor, 混杂因素 x; p# {+ H! ?* V6 ?5 }
Conjoint, 联合分析: T" y5 V9 f. l* V. b7 {* T4 J
Consistency, 相合性$ [! |# n; h. m) E6 }) ~
Consistency check, 一致性检验5 z7 \' {# C% d
Consistent asymptotically normal estimate, 相合渐近正态估计
1 N# s: V' }* N# I2 LConsistent estimate, 相合估计
5 b' q o8 z8 aConstrained nonlinear regression, 受约束非线性回归
. P; {) L/ V+ G! YConstraint, 约束
l' n. a. o# [0 g) AContaminated distribution, 污染分布
. h( T1 n% e2 b, l! U2 i4 ~4 t! CContaminated Gausssian, 污染高斯分布- b8 k! K- A- M: ~& |
Contaminated normal distribution, 污染正态分布2 z1 Q" E9 |' c9 Y" T8 }
Contamination, 污染/ m ~/ p2 D' f, U& x: b
Contamination model, 污染模型
5 G8 H. X A6 f% I c+ Q% hContingency table, 列联表& D' f q; M$ t2 F$ h6 }$ ^7 `( h* Z
Contour, 边界线
; C1 l# y1 \2 a( ^3 v9 D. mContribution rate, 贡献率
( H* D, l) c# R- s+ U* H/ tControl, 对照
' r: n0 ~2 J5 L9 _2 ]+ CControlled experiments, 对照实验
4 Q$ b# Y% Y0 K! [Conventional depth, 常规深度
/ z) T7 k% Z- g' q5 fConvolution, 卷积
* K% W. i' Q% X5 T9 s6 p2 NCorrected factor, 校正因子" K2 r* Q* t# o$ N- a2 Z* t
Corrected mean, 校正均值
! f; Q# X7 s8 Q5 P4 l" A" |Correction coefficient, 校正系数
+ H* n* A# C! x/ j. w$ QCorrectness, 正确性
; B. i$ Y. N' H GCorrelation coefficient, 相关系数
! }9 E2 I% K6 B4 rCorrelation index, 相关指数
* ~; e9 L3 [ K- C* J7 o' C0 RCorrespondence, 对应
- X5 ~' v* u8 X# ?2 l, y' mCounting, 计数
% t2 e1 U! E# b* yCounts, 计数/频数! q0 }4 L4 M, Q* O' Y) n
Covariance, 协方差2 K0 T7 f1 W. k8 d- i- w$ u
Covariant, 共变
) h( W( K( P' N$ x8 j4 R' YCox Regression, Cox回归
. j) w4 @6 e7 sCriteria for fitting, 拟合准则' O! k+ ~# G; |$ s+ Y0 N
Criteria of least squares, 最小二乘准则7 a' E+ H3 T7 A5 R) [; c" z4 e
Critical ratio, 临界比
9 }0 e9 h# s5 C% k1 ~ \Critical region, 拒绝域4 K, T* [0 x J. y/ v/ ^6 n! D$ c
Critical value, 临界值6 s8 z* @! A/ ?& r0 i9 T
Cross-over design, 交叉设计
5 d$ W: }; e0 DCross-section analysis, 横断面分析
% @. W7 R# o' N2 t! A+ w, K& t6 ^Cross-section survey, 横断面调查1 o) R& ]' j+ v3 m7 E
Crosstabs , 交叉表
' `# n$ S1 _! z* p1 `, kCross-tabulation table, 复合表4 D- b1 U9 H8 f; k6 v
Cube root, 立方根
# W2 Z) M5 u$ c( S# h0 MCumulative distribution function, 分布函数
6 R9 s6 V$ _' Y6 d% j0 yCumulative probability, 累计概率; w" I8 C2 [2 v2 b: J. E- m7 S
Curvature, 曲率/弯曲
. u) t; {" F& a8 | x% S# XCurvature, 曲率
- F5 ?, g& q7 D4 C; {Curve fit , 曲线拟和
I/ G& }) u% S7 V" ]& YCurve fitting, 曲线拟合, L3 A6 Z- U+ a7 A4 e
Curvilinear regression, 曲线回归
; o5 N/ U2 U* a* y% }. u" n! d( QCurvilinear relation, 曲线关系
E+ N- f3 P0 t$ e3 ICut-and-try method, 尝试法
- |2 }- h9 q. \; Q0 P5 sCycle, 周期+ |1 X' r" X8 P% ^
Cyclist, 周期性
- B2 u# x0 F2 H" A4 ^& Q* z6 ~0 oD test, D检验
8 F1 R/ c7 z+ c) kData acquisition, 资料收集+ q. K- ?' I% s4 L' u( C2 e+ b
Data bank, 数据库7 @: l: j* }) ]5 V
Data capacity, 数据容量
; I/ S2 X1 [( Q0 _( Q' E6 CData deficiencies, 数据缺乏' ]' {( ], M {! J
Data handling, 数据处理3 F4 x' O: D# m# x
Data manipulation, 数据处理
$ }1 i4 }! t0 rData processing, 数据处理
4 q% [& T+ r' d2 n/ AData reduction, 数据缩减
1 g( Y5 b$ p& u% W3 Y( u+ Q' _Data set, 数据集
* A2 }) o# r+ n+ vData sources, 数据来源
+ o" s- E. q& h. wData transformation, 数据变换$ L# P) c) i2 a* Q9 `; o
Data validity, 数据有效性
6 s- i1 F, H6 z# A/ ?0 S3 fData-in, 数据输入% ~. N, Q& e) [' O+ G( E
Data-out, 数据输出
2 K0 k1 d6 u1 {Dead time, 停滞期
4 G3 L# [2 n2 ]! @/ o' n( BDegree of freedom, 自由度% d m$ Y' f) a- N
Degree of precision, 精密度
9 O! s7 ]8 D& ]0 H! ?5 ~; IDegree of reliability, 可靠性程度7 a! ~0 d. \1 F, M& w( [
Degression, 递减
7 O1 h# _/ o5 qDensity function, 密度函数7 }- T1 J1 M V. |* L6 \% v; q
Density of data points, 数据点的密度
# T$ U- Y! V* \7 B% ADependent variable, 应变量/依变量/因变量
# j6 t. z ]( M- d9 nDependent variable, 因变量
& A( z$ t& z; }1 _; n s- H, hDepth, 深度
7 N- Y, j1 C; L9 O1 `Derivative matrix, 导数矩阵
' |- W% A/ H* `Derivative-free methods, 无导数方法
# I9 `7 M8 y' j# c( [Design, 设计
* A! L/ A5 _9 g4 f6 RDeterminacy, 确定性2 v1 O' p% x' L; E, K: C# Q
Determinant, 行列式
" f3 _% W" o7 y3 KDeterminant, 决定因素
1 B' q8 w, D$ [; b4 G' R# vDeviation, 离差' M& @3 J* |9 ^9 M0 X" d
Deviation from average, 离均差: M% b! }! Q+ x% N' j0 I5 {7 w8 R3 J
Diagnostic plot, 诊断图+ l, R' i s/ N( Y0 m) m+ K' E5 L
Dichotomous variable, 二分变量
% d- M% N% I$ c5 R: A5 ^Differential equation, 微分方程4 F) z& Y* u4 y5 `1 t
Direct standardization, 直接标准化法
" G X, y b4 w2 H! ]0 O, x% zDiscrete variable, 离散型变量
5 H3 N5 B' `. |) F, ]) i% Q* B( oDISCRIMINANT, 判断 " b. I& @% T0 U7 e6 ], C
Discriminant analysis, 判别分析
/ c( g) @8 ^, h6 n9 G XDiscriminant coefficient, 判别系数- K/ D6 a5 `4 Q" ?
Discriminant function, 判别值
7 q4 o9 t9 u! P3 Z7 VDispersion, 散布/分散度
; @- E1 d$ h5 Y& N$ ?Disproportional, 不成比例的 A2 N! w) u2 s6 R* D, M
Disproportionate sub-class numbers, 不成比例次级组含量
4 j( e' L& Z' |7 h6 y5 |Distribution free, 分布无关性/免分布" A' e5 P7 @+ f! y6 R
Distribution shape, 分布形状) y6 I$ L' D6 |# c/ Z
Distribution-free method, 任意分布法
/ S" b3 u2 |9 lDistributive laws, 分配律
! [! }& R8 c) F* X3 W0 B* _5 @Disturbance, 随机扰动项
6 A: h3 d% H! H) ?) m" O h! r# XDose response curve, 剂量反应曲线+ a) o% [1 e) }
Double blind method, 双盲法
$ |1 C( F, P' S* k3 y; DDouble blind trial, 双盲试验
`8 B' L: \9 D/ s$ b& R6 ~. ^7 [Double exponential distribution, 双指数分布
- l; D: ?: Z+ EDouble logarithmic, 双对数
& P t5 ]: I5 Z/ G& d/ M, {' b% pDownward rank, 降秩
# |6 i- _9 J% ^) cDual-space plot, 对偶空间图) j- X1 O# g, ^- @$ c( D
DUD, 无导数方法
3 V; [$ x8 l1 A( j; u9 EDuncan's new multiple range method, 新复极差法/Duncan新法/ {) q' X) q2 k
Effect, 实验效应1 h9 k2 T& R% E# x+ G! a
Eigenvalue, 特征值9 C* y5 {( \( u+ R. F1 I# Z
Eigenvector, 特征向量% J3 s1 F1 o) A; }; j
Ellipse, 椭圆" ^9 N) H! y$ b' T- i' t7 f. A
Empirical distribution, 经验分布: G9 q# y, t; K$ V& H
Empirical probability, 经验概率单位, u1 d% w/ L8 t! r
Enumeration data, 计数资料8 o Y5 K8 q2 Y T0 s
Equal sun-class number, 相等次级组含量) y9 r0 U. v' p5 Y$ i
Equally likely, 等可能. E: M9 M1 d+ U" s. L8 v2 v* }0 H/ x3 K
Equivariance, 同变性
9 R& x5 H$ F# S5 f- v+ WError, 误差/错误
/ y, h* T) t" d% x, LError of estimate, 估计误差% c% A; n0 W7 t \6 @+ F0 X
Error type I, 第一类错误: |! \* g7 F5 r' @
Error type II, 第二类错误
. k1 A' P+ j. G3 sEstimand, 被估量1 C5 r* t- j8 O/ V. o
Estimated error mean squares, 估计误差均方1 d, r" [$ d4 l: y H: E
Estimated error sum of squares, 估计误差平方和
' Q T+ r+ Y9 V: }0 aEuclidean distance, 欧式距离
# p1 J% |. c2 ~2 ~8 H1 h8 NEvent, 事件
8 V- `3 O/ A0 x+ U2 ?Event, 事件
6 `% ]$ ^9 g6 Z3 Z# \& @Exceptional data point, 异常数据点& y5 b) H8 C3 x
Expectation plane, 期望平面6 @6 `. Q8 i" m( v1 J& @" s
Expectation surface, 期望曲面
: t! ~% J) H" l" |7 Z5 mExpected values, 期望值
& \1 f# Q/ [7 z/ o( V! uExperiment, 实验* D) \: {! T* R2 ?
Experimental sampling, 试验抽样4 h2 Q+ ]9 @, V. {4 z
Experimental unit, 试验单位3 S4 _- {/ F: e+ F: x
Explanatory variable, 说明变量9 N6 P) h7 E" `0 |" L: P2 H8 F
Exploratory data analysis, 探索性数据分析
$ {" y: G# l6 h/ M4 u" VExplore Summarize, 探索-摘要
! |5 B; O# O: L& kExponential curve, 指数曲线5 n1 M, g; d+ c; B0 e" F+ l5 E* u
Exponential growth, 指数式增长
; j& @" a/ s" I( a0 gEXSMOOTH, 指数平滑方法 $ _( s0 P. }+ Q# @
Extended fit, 扩充拟合
) C* |, p; s: W" E, yExtra parameter, 附加参数; P. t+ I( H" Z+ _
Extrapolation, 外推法7 Q x1 q' Z# d/ r0 L
Extreme observation, 末端观测值
8 t. A4 L* ]3 |# W) \3 n$ GExtremes, 极端值/极值 m+ d7 P3 |1 O+ o/ B
F distribution, F分布
4 J3 R, u- e5 T4 N% u9 q( VF test, F检验
- @5 Q9 t/ s7 p5 f& WFactor, 因素/因子1 S N$ D( b- X W
Factor analysis, 因子分析
- k' D$ y# q9 Q* D7 N$ EFactor Analysis, 因子分析
, u4 K# b' b: WFactor score, 因子得分 6 i `2 D; C$ e R" s+ `
Factorial, 阶乘
" B& A' S) {) ^# @' V8 PFactorial design, 析因试验设计$ X/ w0 {. f; S* e* _; p
False negative, 假阴性9 ^3 u7 ^- W/ {& f
False negative error, 假阴性错误" g4 k4 ]! H ~8 C% }& \5 j4 |
Family of distributions, 分布族
6 J# a$ ~2 _9 ZFamily of estimators, 估计量族& R1 L1 ?4 H% [& ~) h: O' S
Fanning, 扇面
; V( ~3 u; l7 sFatality rate, 病死率- x. [9 `6 z" Y
Field investigation, 现场调查% L/ [% @1 q; [
Field survey, 现场调查
j1 Q1 _5 T. CFinite population, 有限总体
: G9 `4 L% W9 k5 u- cFinite-sample, 有限样本
" w# }: D7 W8 W0 }2 D; yFirst derivative, 一阶导数
; @ V7 ?. h4 d7 \* L- i/ V# uFirst principal component, 第一主成分
) h, B$ M Q" T2 B& aFirst quartile, 第一四分位数
4 ?% t- K; e# j2 yFisher information, 费雪信息量" N- o9 x1 y9 g0 `8 C
Fitted value, 拟合值3 R5 K( y1 |8 ?: B# ^
Fitting a curve, 曲线拟合3 w9 c3 ]8 |9 P8 o' ?
Fixed base, 定基* k) x( w1 r1 R0 f% d1 M( U
Fluctuation, 随机起伏
" O4 C* v! F/ CForecast, 预测1 z- q$ Y/ O7 @0 `$ R
Four fold table, 四格表8 r0 o5 n: b0 e
Fourth, 四分点
: K0 K9 U6 h2 Z3 I6 J9 d& pFraction blow, 左侧比率
4 p* p% R5 j: Y1 K( M* UFractional error, 相对误差
~6 m3 z, h3 {$ o8 m- ?2 zFrequency, 频率
4 D3 p/ M9 l/ |- @Frequency polygon, 频数多边图
. O6 p4 u5 U/ f+ n2 gFrontier point, 界限点
; z3 }/ }) \* A4 F3 L* z7 HFunction relationship, 泛函关系
' ]$ g8 o- M& w$ ~4 JGamma distribution, 伽玛分布; D# Q# X8 j) `; q+ p
Gauss increment, 高斯增量
1 M- c$ B& U8 a' T" VGaussian distribution, 高斯分布/正态分布3 y2 w) X: h: m% z J
Gauss-Newton increment, 高斯-牛顿增量" P/ B. J. W& @$ L9 s2 s: s
General census, 全面普查
0 r& `1 x( X) _# B' {, {! o% IGENLOG (Generalized liner models), 广义线性模型 ! V4 h( D7 W1 Z# y+ i: Q
Geometric mean, 几何平均数
% R: V5 s9 V! J$ j3 h: {Gini's mean difference, 基尼均差0 [) w* I9 X/ |+ G' ?+ c) R
GLM (General liner models), 一般线性模型
$ N: v: _. o$ _, ^Goodness of fit, 拟和优度/配合度* {) h P3 R4 a4 s9 I k& S# J0 O2 e
Gradient of determinant, 行列式的梯度2 `9 S6 B3 X; |' g- U
Graeco-Latin square, 希腊拉丁方
0 \- E1 C5 J! T! Z6 h5 RGrand mean, 总均值
6 H. W% S* }4 k2 [0 JGross errors, 重大错误
B: [9 ^) f) I8 w9 gGross-error sensitivity, 大错敏感度7 l2 j/ s7 p8 M
Group averages, 分组平均" a# E- Y. A7 F
Grouped data, 分组资料0 L% E7 S6 r: x) S
Guessed mean, 假定平均数/ o, Z* K- i9 `( m: v* J4 z3 _
Half-life, 半衰期7 t" X2 J+ l; b K3 I. Z3 A
Hampel M-estimators, 汉佩尔M估计量4 ]; G! ~5 F. e4 ^4 A0 ]7 J
Happenstance, 偶然事件
6 E! c9 T$ p) f7 ^$ IHarmonic mean, 调和均数7 u1 V' q# H3 A2 [0 f
Hazard function, 风险均数
) P% u _$ Z \/ @, CHazard rate, 风险率
/ c9 H2 n& e- J; K, HHeading, 标目 ; x4 p. x! z/ S0 s! k! ]
Heavy-tailed distribution, 重尾分布
- M2 p* N. C9 B9 a, `" C# I' wHessian array, 海森立体阵' B1 z# z( u0 d9 \/ `8 f
Heterogeneity, 不同质
a3 D, v: V+ w+ D- {9 x3 uHeterogeneity of variance, 方差不齐 + c" U. e* b9 `5 R
Hierarchical classification, 组内分组
; Y7 {9 T' c3 Z+ ]1 Y% EHierarchical clustering method, 系统聚类法
9 w& d5 \- f9 g6 f7 c7 jHigh-leverage point, 高杠杆率点- _6 i7 T" [7 i/ x2 l2 W, s
HILOGLINEAR, 多维列联表的层次对数线性模型: G3 O! i1 s2 c; k3 z# f
Hinge, 折叶点1 Q1 B5 n7 c' C0 D1 q4 l
Histogram, 直方图
# ?: f! k8 `, h# X" ZHistorical cohort study, 历史性队列研究 ) ~9 }) D- }( ^6 t0 L# Z
Holes, 空洞
?3 a( H P l% LHOMALS, 多重响应分析
7 V( i$ _; A7 C3 N" s/ u9 G8 GHomogeneity of variance, 方差齐性
6 Z( U; l6 U# O" @Homogeneity test, 齐性检验+ A" O: U# I$ t5 f' \; K) q: p
Huber M-estimators, 休伯M估计量( D( o8 c& B8 n: W* j; F7 l/ `2 ]7 T
Hyperbola, 双曲线
1 p1 x, \) ]6 f7 l) \5 i7 xHypothesis testing, 假设检验
9 F4 r5 T7 c, r. xHypothetical universe, 假设总体
[( v. F6 t* A$ s9 @Impossible event, 不可能事件
+ I% ~6 Z; `4 n7 RIndependence, 独立性
5 q# k$ U3 O: t; J, \6 qIndependent variable, 自变量" q7 v; ]% }- Q; z0 L, n/ s: L6 ?
Index, 指标/指数
/ z7 t, L+ D& l8 c8 x1 Z/ b/ sIndirect standardization, 间接标准化法
+ B% T# w+ R9 H" H V2 W1 [Individual, 个体
0 d1 Z, G, }- n1 F. YInference band, 推断带$ o6 W; [6 S4 F' N
Infinite population, 无限总体
; J+ E" k" Q7 P1 m* S G" v2 C) {Infinitely great, 无穷大
2 v( V/ f/ @6 {Infinitely small, 无穷小) I" c; c& K& G I
Influence curve, 影响曲线1 r' r' j5 y7 ]( _; U$ y
Information capacity, 信息容量
0 {9 p# K* M: m0 sInitial condition, 初始条件
3 v) _ w" P: [: H* a* `Initial estimate, 初始估计值
- Q( W5 B5 g8 L+ R7 ]. W2 VInitial level, 最初水平
$ X& J2 T' r3 i gInteraction, 交互作用
/ E0 A7 f3 H y' B% qInteraction terms, 交互作用项2 M; g! z) P" v i7 E; X4 `
Intercept, 截距' W; @ Y2 z- w3 J
Interpolation, 内插法
6 ~: q0 z) A7 V ~" Y1 v: x0 ?" h1 kInterquartile range, 四分位距) z, j- K. ]4 b5 L
Interval estimation, 区间估计
9 x+ W+ D9 Q, yIntervals of equal probability, 等概率区间
( F. \" N3 U, W8 t/ mIntrinsic curvature, 固有曲率' C" H% n7 e Q; @5 d; g Q
Invariance, 不变性+ }1 T+ m1 \3 w$ [+ g
Inverse matrix, 逆矩阵' f" R/ }0 u8 v( L' d Z" T
Inverse probability, 逆概率. I: n; H+ Z( p5 E8 C8 A
Inverse sine transformation, 反正弦变换
! z/ N5 K U) {. {5 _Iteration, 迭代
3 d% b( j0 I! r, o0 |& OJacobian determinant, 雅可比行列式8 k% a4 d( T) v! P' m5 k+ @8 ]2 t2 }( V
Joint distribution function, 分布函数
S+ _. @% X9 Q5 }Joint probability, 联合概率
$ H1 s- L, s) I! ~* C8 P+ rJoint probability distribution, 联合概率分布+ W# {* l* K$ k6 z2 t
K means method, 逐步聚类法
, s/ i n/ r8 y8 P3 H* P) d* DKaplan-Meier, 评估事件的时间长度
! h, u2 I1 \3 bKaplan-Merier chart, Kaplan-Merier图
2 g& O" A! T% b& J7 G" wKendall's rank correlation, Kendall等级相关
+ c/ _( U1 | o8 g: HKinetic, 动力学4 V1 `0 y8 n, U, K8 z
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
3 g7 A" m* ~3 n0 D, qKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
! G3 b+ e! e- X5 T5 ~Kurtosis, 峰度
; _2 E' m+ U0 |+ v6 ULack of fit, 失拟
: {" Y8 `% V$ `( m9 \. d2 g8 pLadder of powers, 幂阶梯
& [8 ~2 L5 w: |* i- e- p* eLag, 滞后# a% h; |0 [7 q& b
Large sample, 大样本5 G \" k; {" d3 \- q7 D% }
Large sample test, 大样本检验$ q, v: |. l+ F. D! d
Latin square, 拉丁方
+ b8 A9 q: |( c: _Latin square design, 拉丁方设计
4 ?" W6 g2 ~* ?) D3 C7 n; rLeakage, 泄漏: d' w5 f8 S g* k
Least favorable configuration, 最不利构形
+ y# m% ^& Z* a* a8 PLeast favorable distribution, 最不利分布
H* O% i/ t! M1 _Least significant difference, 最小显著差法
% g0 {, }7 w; U5 OLeast square method, 最小二乘法
% y \2 h3 E0 `4 _3 t3 LLeast-absolute-residuals estimates, 最小绝对残差估计* U/ ?' L. ^3 P
Least-absolute-residuals fit, 最小绝对残差拟合 Z$ z, u& |- T. F( I B
Least-absolute-residuals line, 最小绝对残差线: v$ i' g8 b0 N/ f) s
Legend, 图例
! ^6 x# y+ ?$ r. D8 @) B RL-estimator, L估计量1 Z0 i5 ]1 S% U& ~4 W" ~
L-estimator of location, 位置L估计量# {3 Z+ v) F: Q+ o2 m
L-estimator of scale, 尺度L估计量* h$ k/ g6 t: [ y) v
Level, 水平7 [2 [' }! z$ ^7 ?
Life expectance, 预期期望寿命& h9 Q4 E7 J, b; ?. U
Life table, 寿命表5 R; O% {' Z2 Q& R0 T1 }
Life table method, 生命表法/ q( G# y4 l- V% M8 G2 q# x9 S
Light-tailed distribution, 轻尾分布
0 T2 Y8 g, z3 z* i7 Z: w, Z$ e+ |Likelihood function, 似然函数% U$ {" S" l0 q6 I! I) z& B# [
Likelihood ratio, 似然比& s: ~% Z: F- g7 \. A" o7 G ]9 B3 P
line graph, 线图' L! t! G" i: Z3 j h
Linear correlation, 直线相关' U, V4 E5 P6 `4 D5 P9 N- l
Linear equation, 线性方程
! U! d1 k4 N7 |" s# W' b- S2 W1 [Linear programming, 线性规划
+ k" x: w# |8 N4 RLinear regression, 直线回归: {: r1 F% A ^- R9 z; m
Linear Regression, 线性回归
( j. o6 V" A5 \+ hLinear trend, 线性趋势0 ^ ^* k a) E/ E
Loading, 载荷 ' O5 s- P3 F$ w- d+ A0 J
Location and scale equivariance, 位置尺度同变性$ F$ m" r( _: q x; ?2 I3 }! k2 x! y
Location equivariance, 位置同变性
, A9 ~: a; K7 V& D- TLocation invariance, 位置不变性8 c2 u/ }2 L4 Q. Z# E
Location scale family, 位置尺度族
$ R* J, s4 q! n6 |/ a+ aLog rank test, 时序检验
* a! I# g, T/ N$ i% ]" PLogarithmic curve, 对数曲线! v% i0 L% ^; g a/ d( q8 W! R
Logarithmic normal distribution, 对数正态分布! l$ g ~2 i# b- G) x5 W
Logarithmic scale, 对数尺度
6 Z+ Y0 j1 N9 p4 b1 j8 NLogarithmic transformation, 对数变换0 z' S* L5 a0 W8 \
Logic check, 逻辑检查
' k/ L6 G2 F4 h5 B/ s( yLogistic distribution, 逻辑斯特分布+ W- o$ I3 \2 b2 D: P+ |+ P* V _$ w8 x
Logit transformation, Logit转换
0 j+ C; {5 h: TLOGLINEAR, 多维列联表通用模型
/ }3 e+ `! H" mLognormal distribution, 对数正态分布
9 }( u* v. t4 e2 A/ b. T7 F4 ELost function, 损失函数( Y; c9 W1 E+ l( a! q& ?
Low correlation, 低度相关
6 s6 R2 `' e/ ~& D' w C& r. I1 cLower limit, 下限
, X# F L) S! D, C$ JLowest-attained variance, 最小可达方差
- g& h# R& N5 V& |LSD, 最小显著差法的简称9 j) M& U: P- [4 l% |0 d/ `
Lurking variable, 潜在变量9 J, _- _- P( N. V- L
Main effect, 主效应
& d, {( H# W2 d9 z! T# r9 pMajor heading, 主辞标目
+ f( D: {+ P+ c- o* _5 YMarginal density function, 边缘密度函数
}/ l6 N4 K! iMarginal probability, 边缘概率- t& A( S6 w/ B* o% ?6 D" X
Marginal probability distribution, 边缘概率分布' E, n, ?# B- I! y: D
Matched data, 配对资料
0 A! V$ {6 r" d/ ~# {! MMatched distribution, 匹配过分布4 [. ?4 S N$ w% D
Matching of distribution, 分布的匹配1 u8 D- r3 ]- k; r; P
Matching of transformation, 变换的匹配# x; R' P* V; n" l3 k
Mathematical expectation, 数学期望% y; o! d- z" R! k, ]$ E
Mathematical model, 数学模型
* X; C* u |+ C& ]; g- {Maximum L-estimator, 极大极小L 估计量
4 i. U4 k7 _# ~$ U. ~! BMaximum likelihood method, 最大似然法% a+ [( g8 Q+ \% u- ]5 t
Mean, 均数$ M3 i% L5 q6 y0 u3 y; D* z/ S
Mean squares between groups, 组间均方/ U: }8 N+ r0 u1 A
Mean squares within group, 组内均方
$ I9 {2 t+ ]" S; j b! w1 n' NMeans (Compare means), 均值-均值比较2 z& P+ |/ c8 g* n
Median, 中位数
3 }) W: g5 y' v/ wMedian effective dose, 半数效量
! a d2 ?6 a( _ L$ RMedian lethal dose, 半数致死量) a6 s. t3 c2 x7 s1 K) s6 D
Median polish, 中位数平滑! v9 v! G* X7 [1 x% ^$ x! K) Q
Median test, 中位数检验/ F+ K7 B& }9 Z- f/ l M2 k
Minimal sufficient statistic, 最小充分统计量
6 o" T7 h Q6 X* W( ]Minimum distance estimation, 最小距离估计8 z0 ?& Y( p1 A/ X; n
Minimum effective dose, 最小有效量
: K9 f2 g5 M1 Q0 RMinimum lethal dose, 最小致死量0 t6 Z( ]0 M4 h' ^: Y6 e9 F
Minimum variance estimator, 最小方差估计量
" e5 {0 O" X5 \- z+ dMINITAB, 统计软件包
* ~: e* g8 \; ]( ?, fMinor heading, 宾词标目$ v) U# A; L4 N: f3 s0 h( _
Missing data, 缺失值9 G8 w3 o) k& A2 n/ R- [
Model specification, 模型的确定
7 }; r, y/ H' M! m9 |+ ^Modeling Statistics , 模型统计. J4 _0 H% h' p& n/ N
Models for outliers, 离群值模型
- r/ I. h1 q# fModifying the model, 模型的修正
3 m& |5 \" x: W# Q5 _2 w* mModulus of continuity, 连续性模
, G/ G. a7 {' F% Q& xMorbidity, 发病率
; H, r' g; H3 N- ?' ]% f5 r* |Most favorable configuration, 最有利构形" a0 l4 f7 e: T( ~ E0 r
Multidimensional Scaling (ASCAL), 多维尺度/多维标度, h# c& F1 B) }# A" o. s V3 Q
Multinomial Logistic Regression , 多项逻辑斯蒂回归
\' [$ t6 F2 o# O* z, ~Multiple comparison, 多重比较
' {1 [1 e2 I% M, g h, ^Multiple correlation , 复相关
: ]! i/ v) ?. f0 l2 SMultiple covariance, 多元协方差
; K; u3 t" Y3 M# ~3 p0 @4 ~- [& PMultiple linear regression, 多元线性回归1 j& E. w6 z$ d' k
Multiple response , 多重选项( |, L0 T& N& Z* A4 s2 O
Multiple solutions, 多解+ {. P# x5 [& p2 p* ?8 [
Multiplication theorem, 乘法定理$ n7 X. E9 v! {2 i5 E% o
Multiresponse, 多元响应
7 A+ E- B0 X8 f' b% _( nMulti-stage sampling, 多阶段抽样$ a& \1 n5 _( v' |. ^8 ^
Multivariate T distribution, 多元T分布7 l3 W- O3 [( p0 l4 ~! f/ W5 N( Q7 [
Mutual exclusive, 互不相容9 t( ~) `* s& |6 ]9 E) u
Mutual independence, 互相独立
- ^. j5 g0 q. SNatural boundary, 自然边界! X. u- Z* X9 S, n3 F
Natural dead, 自然死亡
" H9 f. b" ]. G6 }) m: hNatural zero, 自然零
9 B* D2 H: }% l; UNegative correlation, 负相关 x6 a+ [! A: l5 I T+ q- ^6 t
Negative linear correlation, 负线性相关! s) } v9 w" y0 V! [0 x
Negatively skewed, 负偏
3 ]" X3 O/ J* P3 [Newman-Keuls method, q检验
+ B6 ?2 p/ B3 m) VNK method, q检验
' G* A" y Q' A8 k# D+ [1 k* Y d# R- ZNo statistical significance, 无统计意义9 X! [% v' N. l) p: ?) f
Nominal variable, 名义变量
9 _! n" w9 i p; G* W, |/ DNonconstancy of variability, 变异的非定常性
. f+ `8 E j( A* V3 W+ y& ANonlinear regression, 非线性相关
0 F5 H% [/ w2 z XNonparametric statistics, 非参数统计" p, ~3 l( w1 [2 X; r
Nonparametric test, 非参数检验
. V0 h @! j1 L7 O7 y1 \Nonparametric tests, 非参数检验
% b7 g' I3 _ V: C6 a+ A( N% pNormal deviate, 正态离差
1 Q* D6 m) A E. O( [; ZNormal distribution, 正态分布+ G6 V5 K* H; O
Normal equation, 正规方程组
`& c' v! U3 @Normal ranges, 正常范围
+ X0 c* a5 [4 f& _Normal value, 正常值4 X/ Q4 h" t& c
Nuisance parameter, 多余参数/讨厌参数) T, b; Q& I6 \6 w) n
Null hypothesis, 无效假设
. U7 D5 a( \6 D5 q) t+ vNumerical variable, 数值变量* \3 F) ?1 C; A1 W
Objective function, 目标函数# N9 M9 o5 ^; J5 L: t
Observation unit, 观察单位; V p' n- |( v& d+ |; z
Observed value, 观察值$ z8 g$ a4 H& j' a0 l3 p
One sided test, 单侧检验
3 T, R+ C8 P' ZOne-way analysis of variance, 单因素方差分析. x7 Q$ ~3 }, |5 k$ |/ D* [9 V0 Z
Oneway ANOVA , 单因素方差分析- U1 R8 W5 z9 X9 D2 x8 A& e; @5 H
Open sequential trial, 开放型序贯设计
& K0 Z. O5 _. t9 bOptrim, 优切尾
( P1 b% a$ G; Q4 YOptrim efficiency, 优切尾效率
1 ?6 W( a" \1 W7 [Order statistics, 顺序统计量
' m$ {" Z( x: q7 Z1 cOrdered categories, 有序分类
8 L! h. }7 S: I4 ]) ]% ^0 jOrdinal logistic regression , 序数逻辑斯蒂回归. X( V4 Z. K1 i) P! ~' V. N
Ordinal variable, 有序变量
# S. M) @$ l3 Z3 bOrthogonal basis, 正交基
- r) x6 Z+ {6 Y# i5 j- p1 m, V: o* FOrthogonal design, 正交试验设计% v8 i0 }# _& _( p
Orthogonality conditions, 正交条件0 q% @" K0 x; }' D
ORTHOPLAN, 正交设计 $ k. r; r5 m. K3 b
Outlier cutoffs, 离群值截断点. r+ ^7 a" G# j8 y, v
Outliers, 极端值; }$ X& x: R) } A# G) p
OVERALS , 多组变量的非线性正规相关 % U) T' H( C2 C# h3 d
Overshoot, 迭代过度
7 A9 K6 h1 ~, vPaired design, 配对设计 `3 l& I8 J9 k$ F
Paired sample, 配对样本
- Q8 u- B' R# {$ j, l+ V" j, }Pairwise slopes, 成对斜率
6 B/ ~0 d+ _) RParabola, 抛物线4 t+ D# M0 g% [, ^+ ^; }3 y& n
Parallel tests, 平行试验
0 o7 m6 ?( ~+ `; }- D3 A/ k6 G7 KParameter, 参数
. V3 ^6 H1 X* z9 P) KParametric statistics, 参数统计! G" G2 \2 Q- F2 p* N# j
Parametric test, 参数检验' q6 v( B$ I( W; g7 i. N* P
Partial correlation, 偏相关
" q* a6 K8 e, J% g* x" ^) ]$ b0 GPartial regression, 偏回归
* c/ Q& p1 [6 h/ c! e( D* y0 t' zPartial sorting, 偏排序
, m% Q- d5 T) {$ X* rPartials residuals, 偏残差
" L9 q+ u5 M. T+ W0 B: u6 v1 h6 `Pattern, 模式. k/ q, K: [( ]4 R. {" V
Pearson curves, 皮尔逊曲线3 G; ~+ I1 f- n! Q( \
Peeling, 退层* d5 r+ E( f2 H# m7 M
Percent bar graph, 百分条形图2 s" ~5 u" J6 a$ U. t1 x, g
Percentage, 百分比
7 w* y* }( U+ t$ i6 M% yPercentile, 百分位数) _5 |- t& y. @+ ^2 p7 F
Percentile curves, 百分位曲线
" B" M6 j2 X3 [$ CPeriodicity, 周期性. `& x5 \* T5 `8 p5 F
Permutation, 排列
) S- S0 m2 L }& M7 NP-estimator, P估计量) t. l3 H* ~: R, Q/ @, V
Pie graph, 饼图) [0 n( t& H! p
Pitman estimator, 皮特曼估计量
5 B1 m2 ?/ o& p. |5 q$ z# p8 |Pivot, 枢轴量- M- k3 X. g& `
Planar, 平坦 K& e4 J1 N0 X, J
Planar assumption, 平面的假设. f$ A. y9 X6 G4 S
PLANCARDS, 生成试验的计划卡
+ v9 Y1 ~) p1 PPoint estimation, 点估计3 @2 x: r% H7 Z2 U/ o
Poisson distribution, 泊松分布
3 }( y9 Z1 }( U4 K* C" `Polishing, 平滑
7 w3 q& G: i' U( E1 f a$ CPolled standard deviation, 合并标准差
{ h) ~, e: ^* d- NPolled variance, 合并方差9 {% I( C* N0 m2 ~, t3 ]1 s
Polygon, 多边图2 V+ B6 E9 C; }3 i6 ]! j" y
Polynomial, 多项式. \' R* c5 B3 T, d
Polynomial curve, 多项式曲线
# p% j& z% a" T4 h1 h# H2 @Population, 总体+ d" \( w8 _ D8 x Z+ P
Population attributable risk, 人群归因危险度, S" l1 F6 P, @" o8 [' G0 D
Positive correlation, 正相关# H7 @$ p6 U2 A1 ], o
Positively skewed, 正偏
, |3 b" y8 ^# ^Posterior distribution, 后验分布! n& J" M, H' B2 z
Power of a test, 检验效能% n* }/ q+ a- S9 i5 e
Precision, 精密度7 W- i/ C( {4 K7 d- u1 @1 r
Predicted value, 预测值% ^5 P. v0 c! f
Preliminary analysis, 预备性分析9 x9 X6 C: c! p" M t( W
Principal component analysis, 主成分分析
$ ~. s; d5 S* i3 q$ qPrior distribution, 先验分布
0 t* u6 R. t! ?" K% [0 dPrior probability, 先验概率/ U7 ~% n1 Z1 x$ H, R5 |' v% k
Probabilistic model, 概率模型
' \1 e4 D, {- s# Q7 e# @. T K, v7 d9 W7 @probability, 概率
- j* f' E' J }/ L) ]" |7 HProbability density, 概率密度
* x' N6 F) N* HProduct moment, 乘积矩/协方差
# Y" r5 |6 m3 y9 c v' DProfile trace, 截面迹图
0 ]% x% q) h$ _$ W9 k% AProportion, 比/构成比& h( K: n# P$ t q
Proportion allocation in stratified random sampling, 按比例分层随机抽样
2 P; v4 o3 `" f8 `/ _* K! _Proportionate, 成比例$ T- y' a3 s5 p6 m" Y( _# X" z
Proportionate sub-class numbers, 成比例次级组含量: Q/ k( v+ B& t j, S3 \! q
Prospective study, 前瞻性调查0 J5 ?9 q0 o! D6 f' F
Proximities, 亲近性 - O. M1 o" w2 P1 s
Pseudo F test, 近似F检验4 i9 Z6 W' w! _; i
Pseudo model, 近似模型9 |8 r, t5 n1 b5 N/ J* w* Y
Pseudosigma, 伪标准差2 z$ u/ C0 Y/ L4 L: D/ y
Purposive sampling, 有目的抽样( f! {3 K* r( B1 T- S( C: u4 @, a) B
QR decomposition, QR分解
8 B/ [6 ?9 X2 z1 n. b# uQuadratic approximation, 二次近似
, ]& l) K. ~% n9 n8 O8 ^2 Z6 dQualitative classification, 属性分类
; e; } b: c% B0 G; j/ _Qualitative method, 定性方法
o% {, d% H8 T6 @: u; t4 K5 fQuantile-quantile plot, 分位数-分位数图/Q-Q图
6 f+ d4 I8 b4 W+ uQuantitative analysis, 定量分析# C8 @5 Q) f+ U
Quartile, 四分位数, M' c9 T+ {. Q2 r! M7 ]! ~, l0 y8 Z
Quick Cluster, 快速聚类
1 |' j, P' S5 aRadix sort, 基数排序
. j2 r. v4 n, [( e( Q# _4 J3 R- }Random allocation, 随机化分组
5 B# ]& l( j6 u8 XRandom blocks design, 随机区组设计& K9 j# T* y+ ~0 ^+ x8 P
Random event, 随机事件1 V3 \; W/ A* t( z% T2 H: D
Randomization, 随机化" a0 { @$ A) U0 j# g
Range, 极差/全距
: B/ G7 [% m9 H) o1 P3 u6 H9 IRank correlation, 等级相关
8 |$ I$ \6 |9 ~' o0 a8 uRank sum test, 秩和检验. {* \# Y* c) }" t" g) S
Rank test, 秩检验+ d: Y( K( b7 {5 ~
Ranked data, 等级资料
0 b5 L$ \: x* Q0 CRate, 比率
+ H3 W7 s7 F" z; f" c1 E! R5 M7 l# K( TRatio, 比例2 V f; O* }# |- u1 C
Raw data, 原始资料% O# D& e ?: V
Raw residual, 原始残差, l& V' x1 r4 I9 x, Y7 f
Rayleigh's test, 雷氏检验1 M1 V. N8 p! K
Rayleigh's Z, 雷氏Z值 5 @% [$ g3 F {7 L
Reciprocal, 倒数
7 R3 k/ @4 l! a7 e( E8 DReciprocal transformation, 倒数变换& ]; n1 R/ [: }1 `
Recording, 记录6 e7 g! ?) _2 T- q' I
Redescending estimators, 回降估计量
' D6 e+ W! H: B# w; GReducing dimensions, 降维
3 ^6 m8 {* g0 h2 g& rRe-expression, 重新表达
8 a0 L P0 |- RReference set, 标准组2 J0 J1 H0 [' i1 C, s
Region of acceptance, 接受域
4 L1 V' [6 n; ^" cRegression coefficient, 回归系数
, o# H* x, e1 v0 E) qRegression sum of square, 回归平方和
3 b$ A d, l4 ^Rejection point, 拒绝点! `$ s O+ [! E& w* R) _+ u" G Q
Relative dispersion, 相对离散度
7 h, k% W, e3 i, _Relative number, 相对数
7 R) O* I) C" `2 JReliability, 可靠性
2 ^4 ^- Q4 o4 i9 {Reparametrization, 重新设置参数
) S; M Q! M" _& [! A6 oReplication, 重复" y4 G9 U2 x" K; [9 U9 _6 n/ F
Report Summaries, 报告摘要
/ G- b& X. u5 | q( v2 t, j, \Residual sum of square, 剩余平方和% T' W# K7 [8 [/ B2 A
Resistance, 耐抗性
/ |+ q3 x5 V" p m2 V3 u; XResistant line, 耐抗线/ ]1 N+ Z* |; J9 v( O4 D, P T
Resistant technique, 耐抗技术! n( `) S& ~4 }3 @( G. X+ `
R-estimator of location, 位置R估计量
5 w/ ~6 G0 y, k% qR-estimator of scale, 尺度R估计量& }( z4 v. v% j7 f) x: `. d
Retrospective study, 回顾性调查4 o0 P" c8 ~# w
Ridge trace, 岭迹
- D! ? A8 ]- Q/ k8 G8 |% jRidit analysis, Ridit分析
t5 N0 a$ r7 }0 X/ Z0 ?Rotation, 旋转) t4 P9 c$ H7 U: y
Rounding, 舍入
& D2 R1 h+ f& [7 l+ jRow, 行
& n& C; u1 J' }+ X% \Row effects, 行效应
, I6 R8 \# J' a L" A' dRow factor, 行因素
) [5 l$ k( z- B/ b7 L4 BRXC table, RXC表
3 H" S1 e& }: R5 sSample, 样本2 _2 W) G' }1 n; M
Sample regression coefficient, 样本回归系数
5 |4 n7 B/ i7 D9 L+ C" ESample size, 样本量1 L8 n8 K" P* f' Z8 G% K
Sample standard deviation, 样本标准差
- m/ k: j$ j2 aSampling error, 抽样误差# b! \' L/ Q, Q8 ?2 v0 I5 ~
SAS(Statistical analysis system ), SAS统计软件包8 A9 f/ v; `4 i' S F0 R
Scale, 尺度/量表
3 j% ?4 ^8 L8 E! J8 p8 e9 `8 w. [Scatter diagram, 散点图
: q( @7 P" x. s0 C0 y. ESchematic plot, 示意图/简图% T" L0 K K$ ]) m, k7 A
Score test, 计分检验
0 C' Y; c" q' J1 {Screening, 筛检% ~; P8 R1 }# O. y/ f# a* [
SEASON, 季节分析
) m/ w7 I! u$ x3 [" RSecond derivative, 二阶导数
! r5 Z$ F' I4 N4 V6 }! aSecond principal component, 第二主成分( x7 L5 w- Y8 D- x- K# E$ H, a8 q
SEM (Structural equation modeling), 结构化方程模型
9 e$ h' d6 n$ wSemi-logarithmic graph, 半对数图
: \ }0 Q/ H/ v N- Y" aSemi-logarithmic paper, 半对数格纸
& r5 d; w* R* z) |Sensitivity curve, 敏感度曲线
& }* l+ o1 N5 ^* s. y9 _5 V, _3 L) rSequential analysis, 贯序分析
) p: b0 R' ?: m3 t! LSequential data set, 顺序数据集& w W; T- q) i: u4 \2 a, V4 P
Sequential design, 贯序设计2 h$ X9 |+ G/ ]1 [0 `" Y7 O6 r3 b5 I! z
Sequential method, 贯序法
0 |3 n( j2 a/ Y9 e2 _Sequential test, 贯序检验法 @$ R+ @3 F& X) y1 W- ? R
Serial tests, 系列试验0 T% I/ q- D7 A. p
Short-cut method, 简捷法 ! [* M. a1 i% K; u5 L/ r. S5 [
Sigmoid curve, S形曲线3 x" U, A8 \8 W% Q4 ^) A
Sign function, 正负号函数$ G4 I4 i5 `2 ^! X) P' A1 S) }
Sign test, 符号检验
: w9 \& G+ K Y- |Signed rank, 符号秩
4 J$ A, I z% T8 p$ s" S+ z2 o aSignificance test, 显著性检验
* I. j* B4 M: \9 U1 tSignificant figure, 有效数字4 E6 I C% e- M2 _
Simple cluster sampling, 简单整群抽样
9 }& y T& B$ pSimple correlation, 简单相关, }8 [# \* n# e/ ^6 @8 c
Simple random sampling, 简单随机抽样
" \' n! F" j5 A+ g) ^# Z( _Simple regression, 简单回归9 H0 Z ?, ]* N* D2 @5 W5 ?. ~
simple table, 简单表8 x% L0 J! D% d% a/ l. L# O
Sine estimator, 正弦估计量- ~3 m8 T$ D$ O2 @) l
Single-valued estimate, 单值估计& Q3 i5 W q, s/ a2 x" B
Singular matrix, 奇异矩阵
5 W. T* k( q4 V7 ?3 w sSkewed distribution, 偏斜分布) B) h' E* Q8 \7 X6 D# f
Skewness, 偏度8 j. L8 J3 B2 w, V6 N' u1 J
Slash distribution, 斜线分布7 Q# x( a5 p- T1 a, r! z4 X) K4 H
Slope, 斜率
, E/ e9 ]% C# vSmirnov test, 斯米尔诺夫检验' Y6 K0 y; |: z( z( T, h
Source of variation, 变异来源* m. u& W7 F; u' M( T J$ e
Spearman rank correlation, 斯皮尔曼等级相关
/ C" d2 w! g" ~* S w" i; Q4 aSpecific factor, 特殊因子
% P- r6 p0 Z. F) J9 hSpecific factor variance, 特殊因子方差
6 M, L% q0 `& r8 D8 `% A% pSpectra , 频谱- c3 Y) \; p, A; q
Spherical distribution, 球型正态分布
# G; P6 I5 p/ |. vSpread, 展布
6 l7 V* q3 b0 c, mSPSS(Statistical package for the social science), SPSS统计软件包9 z" J% @- c g% h6 ^4 P
Spurious correlation, 假性相关, c' t& T; E4 n% n! C
Square root transformation, 平方根变换
7 `9 a. g5 z0 A' e1 RStabilizing variance, 稳定方差
2 d5 c7 I# v& `1 ?" pStandard deviation, 标准差
" z n1 ?# |6 I" R$ XStandard error, 标准误8 j- w4 f! u9 ~3 D9 @# W, L
Standard error of difference, 差别的标准误
; ]' M. V3 L/ s; U2 }( o0 SStandard error of estimate, 标准估计误差
w2 ^% s2 G* aStandard error of rate, 率的标准误
$ D" y! m4 H, k" U! Q& a) TStandard normal distribution, 标准正态分布
; b3 `4 e. q# `9 \. l* SStandardization, 标准化
! e( g: j; i* P# j4 JStarting value, 起始值3 n$ R" A0 h) {' l, ^" x
Statistic, 统计量
9 L( \0 h0 L$ `$ d& yStatistical control, 统计控制
7 w0 \4 W1 ]0 h1 NStatistical graph, 统计图. }7 {# g0 U: a4 d
Statistical inference, 统计推断
4 |# o7 L5 Y0 x- MStatistical table, 统计表: h) p1 K. j8 s& X5 n7 K
Steepest descent, 最速下降法5 l [4 Q: h/ H! d6 R0 Q
Stem and leaf display, 茎叶图
! P9 U+ ]7 h( k6 CStep factor, 步长因子
( S0 F9 ~7 p1 Y. b/ r: JStepwise regression, 逐步回归
' S: N) n. Z6 R1 b! d; uStorage, 存
2 ?; C( G( g XStrata, 层(复数)& |" |! z" Q. o. D; }$ S
Stratified sampling, 分层抽样
0 B& l3 A" x' T% f P# UStratified sampling, 分层抽样' n& K; z. Y( R- D- R& O
Strength, 强度
- _3 S% W3 B7 S, xStringency, 严密性
$ E, Z. a8 `# u% I: u& m5 {$ }Structural relationship, 结构关系
: g# q: f" J" ^: I/ yStudentized residual, 学生化残差/t化残差3 w2 c; U$ w* R3 p9 r' ~/ e
Sub-class numbers, 次级组含量
) F; C& W V' X& NSubdividing, 分割
4 Q4 | U$ w+ z5 ^1 Y) n% [Sufficient statistic, 充分统计量2 X3 L! X* c3 U' D2 T5 Q0 ^
Sum of products, 积和: l, j9 |; K5 s5 W6 t6 e
Sum of squares, 离差平方和; E! n3 y2 N& N2 }3 i; t1 {: ^ h
Sum of squares about regression, 回归平方和
$ {% K3 H6 O0 l$ N3 K3 bSum of squares between groups, 组间平方和6 V8 {; R$ H: M2 X1 n% b
Sum of squares of partial regression, 偏回归平方和/ S- G( g* |# H1 L3 D$ {$ N
Sure event, 必然事件
7 ^9 y0 k+ L$ |7 Y% f: }) cSurvey, 调查( Z; y0 p' c8 Y$ |( ]0 a
Survival, 生存分析
' L5 E# q, h( g; [Survival rate, 生存率
8 _/ R% |5 Q9 u0 i6 NSuspended root gram, 悬吊根图
- x" }/ f: ]+ T8 g* H: D7 A2 KSymmetry, 对称
9 V, ~0 d& L0 v9 U' FSystematic error, 系统误差+ m/ U3 _, M8 k# Y H4 O
Systematic sampling, 系统抽样4 U: P% A4 x2 q% S( c. i
Tags, 标签
6 l% x+ Y" e- I/ X/ g5 ITail area, 尾部面积& V! o% Z, w1 M% N
Tail length, 尾长. ^' R, l8 A( G) M, z, `: O
Tail weight, 尾重
* t' N, w7 M* o9 S) X; p6 sTangent line, 切线
+ J8 w* T9 |- A' n F' oTarget distribution, 目标分布0 q1 J* u+ D- g& i9 o9 u
Taylor series, 泰勒级数
$ ]6 r8 }7 b! m2 n6 p9 c: `5 eTendency of dispersion, 离散趋势
7 X! ?0 C' H! STesting of hypotheses, 假设检验
& z2 j/ _, w" H! ?" `Theoretical frequency, 理论频数; ?5 @! e4 T# L/ P8 ~" _3 s
Time series, 时间序列* j1 L, r$ t, A6 A* T) n. [' e6 W8 c
Tolerance interval, 容忍区间
' f% |/ ? L( M7 \Tolerance lower limit, 容忍下限( c" R: q4 h2 u+ a
Tolerance upper limit, 容忍上限. t% T5 n: P- d2 ^
Torsion, 扰率
" j* |& X- r& u4 \3 j; v1 B- _Total sum of square, 总平方和2 @; H; M5 v+ z8 J
Total variation, 总变异
! Y' P% j) s4 M: |9 @& y4 MTransformation, 转换
r: N% P- P! R( nTreatment, 处理$ `) y- P0 F: q6 x" z) T0 h, {
Trend, 趋势' i3 C8 G9 M4 ~
Trend of percentage, 百分比趋势
8 _" v6 [% E7 ?' _$ `" \$ R& gTrial, 试验
, {* }2 S( k8 w8 [2 v6 y; w5 {Trial and error method, 试错法' T; z# o$ C9 Q
Tuning constant, 细调常数
; M) W1 f; C ~% HTwo sided test, 双向检验
" n/ j9 M2 Y8 d7 a- s0 ^' oTwo-stage least squares, 二阶最小平方
3 {2 w- m) q z/ `1 B+ rTwo-stage sampling, 二阶段抽样
& m. G. o8 [: u4 w, d$ ]Two-tailed test, 双侧检验
6 w0 `: B( s' g* a+ nTwo-way analysis of variance, 双因素方差分析: r6 X; q2 s1 I3 x& Y+ T
Two-way table, 双向表
: ?2 T& M( ~, \8 G% m- EType I error, 一类错误/α错误" O2 Z+ y$ W1 X+ y/ A
Type II error, 二类错误/β错误" v% d6 D m, c; k4 |( z
UMVU, 方差一致最小无偏估计简称
* R6 Z# `- K2 k* X2 V( xUnbiased estimate, 无偏估计
; M, ~- T4 q: Z6 \Unconstrained nonlinear regression , 无约束非线性回归
+ @( V; B* L+ l& {Unequal subclass number, 不等次级组含量9 m9 j" f& g! R- ]/ a
Ungrouped data, 不分组资料
8 s. ? v+ [* Q* L6 f- ^Uniform coordinate, 均匀坐标
. e. `3 g8 _ |5 Y) {$ UUniform distribution, 均匀分布
7 B. b- |/ X( Z- @& e8 E$ J1 V/ G. OUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
* V% s9 }( M0 a% I5 mUnit, 单元8 w8 P4 U3 x5 V6 W
Unordered categories, 无序分类+ V! P9 W( I2 a5 K( s& @
Upper limit, 上限
, _0 G/ ^( T) x! U& \! W( TUpward rank, 升秩
. s# g4 p. e7 u: u& v1 ]Vague concept, 模糊概念
; l. k2 e# E# _7 [% CValidity, 有效性. S; p. D7 e5 D7 m3 a3 }6 X
VARCOMP (Variance component estimation), 方差元素估计
& `+ H ~0 k8 E1 o( V: e7 }* hVariability, 变异性
4 m& p! m! u' H0 n8 b% A, EVariable, 变量
Y, C5 _6 p% t; U) dVariance, 方差
: O/ K+ x9 E; j4 f6 p: EVariation, 变异
" b1 ^0 `( \" c! j9 z# V8 NVarimax orthogonal rotation, 方差最大正交旋转* `% B$ w' E8 ~) Y8 c. y
Volume of distribution, 容积
" P& m+ V4 b+ n1 C% _# |: bW test, W检验
% f3 q0 [: b: t- n' g' m' GWeibull distribution, 威布尔分布
) t8 Y; ] l* m0 c$ OWeight, 权数
1 ?2 U$ A' a' S3 LWeighted Chi-square test, 加权卡方检验/Cochran检验
* ]! v# n! v8 gWeighted linear regression method, 加权直线回归% A0 L* Q5 T- Y8 p) R5 _0 i
Weighted mean, 加权平均数
% H) z/ q! v; _ C7 Q* ~Weighted mean square, 加权平均方差7 E$ o3 L' n4 C" X8 @
Weighted sum of square, 加权平方和
# P, v9 I) l/ V5 I, |Weighting coefficient, 权重系数; C* {" e* k. m8 a- V- I
Weighting method, 加权法 1 d$ P8 }5 ?8 O2 F* W
W-estimation, W估计量% n6 C! r' [9 {+ F5 X& N% V# `
W-estimation of location, 位置W估计量3 l0 o1 A. e: u7 `: }
Width, 宽度
& p# ]) P$ c6 N1 b! y2 @Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
- Y9 P( {) q7 [Wild point, 野点/狂点& L* Y1 H2 `8 c1 d; g
Wild value, 野值/狂值
* s; ~/ i* ?: K9 a. RWinsorized mean, 缩尾均值1 n( C+ s3 B% F- _
Withdraw, 失访
2 r7 Y! b- u/ I: M# _5 DYouden's index, 尤登指数9 y0 A9 V( _4 h( p: C0 x e Q. K# I
Z test, Z检验
; V/ b/ c& R4 q X1 Q6 z/ b+ d/ r& |Zero correlation, 零相关. x" f9 J9 x% D- g& j- h6 ^6 w
Z-transformation, Z变换 |
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