|
|
Absolute deviation, 绝对离差
; R3 t: Z$ B4 U: a6 tAbsolute number, 绝对数, `1 C1 [3 B7 y" {8 z3 s5 u* M" F
Absolute residuals, 绝对残差! C% y7 q4 I6 X8 X' P
Acceleration array, 加速度立体阵" t' O& d# g, a q; w- s' m
Acceleration in an arbitrary direction, 任意方向上的加速度* Q- }4 r+ \* I% n
Acceleration normal, 法向加速度
7 a- q- ]' h6 T& _' i% E3 ^Acceleration space dimension, 加速度空间的维数
$ a1 f1 {8 t- u& X5 x% F* L% FAcceleration tangential, 切向加速度
+ \9 h7 g# T6 Z6 q6 KAcceleration vector, 加速度向量0 e* j% C! c6 w1 P* n3 O" W
Acceptable hypothesis, 可接受假设
( A- d4 S- d3 E) Y; b# N5 O: bAccumulation, 累积
1 j' o- t% B4 @/ F$ N0 ]Accuracy, 准确度4 ` T, {* W: |( D& i
Actual frequency, 实际频数
( V/ }- i$ W* ~) ^% g sAdaptive estimator, 自适应估计量( o5 C7 g4 H+ N0 s5 |$ k
Addition, 相加 [' e' c/ A# z7 K8 C. Q3 H' y
Addition theorem, 加法定理
$ p" h- N" c0 @! ~( ~Additivity, 可加性1 b/ ^5 f, J- y+ t
Adjusted rate, 调整率; u* u: t) l. O4 K4 g: t
Adjusted value, 校正值
* t& E8 ]% i, q4 x6 _0 ?$ v, yAdmissible error, 容许误差# g1 l1 P+ e/ x# e d% C I
Aggregation, 聚集性9 `8 l( m, v( [1 |" U$ w
Alternative hypothesis, 备择假设
8 G# [" e. U/ ~" D$ P, i. JAmong groups, 组间; j( w. n7 ?% I% s! \0 ]
Amounts, 总量
3 Z1 ^! f- F/ c9 V4 M9 qAnalysis of correlation, 相关分析
- c& a( V2 [5 mAnalysis of covariance, 协方差分析
1 n* L7 y& i" U8 d8 PAnalysis of regression, 回归分析 U+ V$ {+ h& x3 j
Analysis of time series, 时间序列分析
" { E P) |# Y6 p' `Analysis of variance, 方差分析$ L/ y3 }( O; X& `) b5 l
Angular transformation, 角转换4 K. \5 R! j; M4 P8 J0 l/ V
ANOVA （analysis of variance）, 方差分析
' Z" ~* \* u" w, y8 GANOVA Models, 方差分析模型
. I! V# P4 [& _! l" [( s# i, R0 X1 JArcing, 弧/弧旋
8 c+ R4 K, v" F; L7 z5 YArcsine transformation, 反正弦变换
: g0 R7 q# Y% g' u" x' m% zArea under the curve, 曲线面积, I. F) }, d! D+ r
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
5 J7 ]2 j% L0 ~/ v/ l/ O; e* ~ARIMA, 季节和非季节性单变量模型的极大似然估计 " u+ @) y0 W& n! O) r/ M6 A- [" H
Arithmetic grid paper, 算术格纸# g1 `! F( q0 T4 B$ I: c, |
Arithmetic mean, 算术平均数
1 Y% \8 Y \3 D# }( VArrhenius relation, 艾恩尼斯关系
9 d# ]' i8 s; a8 u$ HAssessing fit, 拟合的评估
$ a# M2 f0 W9 T) z( \! X" FAssociative laws, 结合律
- N- j+ @! n- L+ j S5 zAsymmetric distribution, 非对称分布4 [5 m0 u/ {# j5 p4 D5 a% R/ _, |
Asymptotic bias, 渐近偏倚
$ s" }3 P6 m) y1 ~' N; K* R- [Asymptotic efficiency, 渐近效率- R1 b( ?* w" T T" t, d
Asymptotic variance, 渐近方差! h9 X& m) y3 v3 @$ B& {4 O
Attributable risk, 归因危险度
/ z: H9 q3 ^9 S) I* zAttribute data, 属性资料/ ?- O3 A5 B. n8 `; z
Attribution, 属性: r' |7 e0 h" D# A" ^1 w% g+ N
Autocorrelation, 自相关
7 P; ~3 C9 F: @, _$ tAutocorrelation of residuals, 残差的自相关
7 Y) G1 E5 e9 i) B# nAverage, 平均数- U! I! y1 h$ w, n- Y1 z& E j' t* \
Average confidence interval length, 平均置信区间长度
5 o4 p/ f; m8 `% @Average growth rate, 平均增长率
7 }' o Z9 y3 M# L* RBar chart, 条形图
0 n" e3 N" p2 U6 ~" ?Bar graph, 条形图
3 ]1 L. a3 ^9 f; L' pBase period, 基期( O! m$ E/ m" n5 j! q
Bayes' theorem , Bayes定理2 S4 j3 _& U. Q! |' `9 C
Bell-shaped curve, 钟形曲线3 ?+ j: v* A5 p
Bernoulli distribution, 伯努力分布9 U# }4 ?% y) M" u' H+ X( s" J
Best-trim estimator, 最好切尾估计量
8 @0 S N5 e+ C' z6 X$ s7 Y) eBias, 偏性/ w9 W$ H& N" z
Binary logistic regression, 二元逻辑斯蒂回归/ u# W% g1 L) V" c O! d0 B
Binomial distribution, 二项分布0 z+ t: e! t. U! o2 h
Bisquare, 双平方
* }: u4 {, ?4 W* C* HBivariate Correlate, 二变量相关
- _0 O4 `0 G; J# m. X. q$ rBivariate normal distribution, 双变量正态分布, N& u& w1 ]% R, [
Bivariate normal population, 双变量正态总体
: i/ ]" e! H3 D* ?7 P {( }Biweight interval, 双权区间3 ^$ x9 k- [! {
Biweight M-estimator, 双权M估计量
5 j- X/ Q" S* K' ]2 O, d2 hBlock, 区组/配伍组. V0 G8 e, b ]8 P, k9 y H c$ a
BMDP(Biomedical computer programs), BMDP统计软件包- P: m, Q4 @' Q$ v6 s
Boxplots, 箱线图/箱尾图
, d P( j" P* G! K3 e7 \, t9 T0 l/ wBreakdown bound, 崩溃界/崩溃点
1 ]5 }" X. `% U" R( j8 NCanonical correlation, 典型相关
* V$ \$ Q, G7 ~Caption, 纵标目
# k6 d6 W; y. GCase-control study, 病例对照研究
4 S) M! v& z9 ~' o& ~Categorical variable, 分类变量
" D/ \6 D9 l( z8 c MCatenary, 悬链线
; w! p0 [% T8 A3 R/ s( d2 O! lCauchy distribution, 柯西分布
' p2 p8 S+ z/ F* D0 r7 _* ?Cause-and-effect relationship, 因果关系, ]9 O, z( @, @ ?+ |. K. q4 K
Cell, 单元
5 b" G/ J: E4 q' E" `( S" ~Censoring, 终检
$ Y ~$ i/ b# G; YCenter of symmetry, 对称中心
) S& V/ S0 ?, h2 U& q- BCentering and scaling, 中心化和定标 n7 W7 N4 a* m7 |7 o# Y3 t
Central tendency, 集中趋势. n7 Z$ n$ ^; y0 A
Central value, 中心值% b8 z9 {& _* r J
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
# Y m9 [* k1 m: G' IChance, 机遇
- @1 G0 S* J1 _ S$ r. qChance error, 随机误差
/ n2 `1 E7 ]4 n8 g9 D! O7 T4 mChance variable, 随机变量
, W+ M [2 I" U0 j6 ^" D- ^5 pCharacteristic equation, 特征方程0 r) D$ J& ^$ j- O3 w$ x
Characteristic root, 特征根
4 M+ f3 r) q: J# R' RCharacteristic vector, 特征向量
& H- R* N- O" ?' OChebshev criterion of fit, 拟合的切比雪夫准则, ]4 b& U/ W2 X
Chernoff faces, 切尔诺夫脸谱图
$ N, P* R" y0 ~9 j: c, LChi-square test, 卡方检验/χ2检验( }/ |' x1 h3 ^4 y2 U* G0 P3 o
Choleskey decomposition, 乔洛斯基分解
+ \6 G; [; v( {! h9 VCircle chart, 圆图 6 a- U7 g& a) p5 }
Class interval, 组距& w3 Y/ I9 ~1 t- V0 ~4 w( h; C
Class mid-value, 组中值* B# Z% [" @* p
Class upper limit, 组上限6 v f. T* J) _ l: W
Classified variable, 分类变量
$ a8 M. u; |$ u+ O8 _* PCluster analysis, 聚类分析2 L5 F) R+ H& q* ?" E' a
Cluster sampling, 整群抽样
) ^7 q3 x8 w5 FCode, 代码
0 O2 c7 {$ v( yCoded data, 编码数据 B' R% `. d u& I" Q: c8 |
Coding, 编码
* x2 J9 T r$ }' h/ aCoefficient of contingency, 列联系数' |+ `+ B9 [- o% O
Coefficient of determination, 决定系数" T2 ~5 o2 H* J) O8 l" s8 a4 J0 ~) U3 S
Coefficient of multiple correlation, 多重相关系数 R/ x D" Q3 \ X" W7 }
Coefficient of partial correlation, 偏相关系数
4 Z9 e# `7 }7 \5 n( nCoefficient of production-moment correlation, 积差相关系数/ G9 w7 Q* q5 F" M- w& V1 Y
Coefficient of rank correlation, 等级相关系数+ J4 e/ A, o9 T. |( {, X/ d; I
Coefficient of regression, 回归系数
+ }2 ]( @* b- C8 y1 x. s2 [9 ECoefficient of skewness, 偏度系数
4 q, t- [& t7 Q& u. \2 GCoefficient of variation, 变异系数
) ]3 X6 `; \4 G% ^( a9 mCohort study, 队列研究3 e+ [! V) W/ [( D* N9 R$ e$ d6 a
Column, 列
3 j) `! c1 I, N. zColumn effect, 列效应
1 A9 U. V; Y+ S1 Q e! F* B4 BColumn factor, 列因素
( T9 s& J* r: A4 D5 M) g% BCombination pool, 合并% k" e# U) J* T7 p6 j" {
Combinative table, 组合表6 f8 T2 s2 G; B( W
Common factor, 共性因子
: Q, V4 ?0 o1 D! Q8 N( \Common regression coefficient, 公共回归系数
6 ?( |+ v5 c0 ?; n5 e! j: _1 [* LCommon value, 共同值8 ` h# e( b t# \1 Y* M
Common variance, 公共方差
# g& D& E0 V0 YCommon variation, 公共变异9 s+ e& J j0 Y( @
Communality variance, 共性方差6 c: t# G: `4 h3 j7 U! |
Comparability, 可比性7 }% w6 x$ t& h6 S: a2 s3 e6 V
Comparison of bathes, 批比较
7 n6 A \5 ]/ ?3 X; CComparison value, 比较值
% ^. k1 L- i. d7 f. g" LCompartment model, 分部模型% x. H% Q/ E7 S
Compassion, 伸缩
, D# C* {9 Y: b7 aComplement of an event, 补事件
% K5 q, w7 r5 [8 WComplete association, 完全正相关( c) u+ w0 F% \( g
Complete dissociation, 完全不相关
5 |, Q* r3 H" ^Complete statistics, 完备统计量7 s5 o, u2 N2 u9 E. f6 r
Completely randomized design, 完全随机化设计! M) d, x: S- K3 V# y
Composite event, 联合事件
8 \: Q+ {( _- x) [. \Composite events, 复合事件
% M$ S* u1 l+ y7 vConcavity, 凹性
5 I) q4 u" P+ j7 O* i( o4 dConditional expectation, 条件期望- A! E3 M" ?, D& x) o' `1 u
Conditional likelihood, 条件似然! W2 G+ j0 T' c2 E0 [
Conditional probability, 条件概率
5 [2 q5 K- i4 t7 `Conditionally linear, 依条件线性 Q1 b5 ~4 i" t2 h
Confidence interval, 置信区间5 S9 u/ P0 z4 Q& ^' r! G
Confidence limit, 置信限/ \% D% a1 o1 {5 Y. a6 D# j
Confidence lower limit, 置信下限* ?6 P* t& L8 X J
Confidence upper limit, 置信上限
$ n; V A6 q0 g4 xConfirmatory Factor Analysis , 验证性因子分析
$ [- a% e7 x# |. u" Y: `' SConfirmatory research, 证实性实验研究
5 t& [9 Z4 F; h- u/ xConfounding factor, 混杂因素
\& d& W$ {/ e' J9 z/ c. kConjoint, 联合分析% p) Y4 ^% i3 J
Consistency, 相合性: M' S. F7 F1 Y1 ~; H: V
Consistency check, 一致性检验
& U- ]8 W: A1 I" d) JConsistent asymptotically normal estimate, 相合渐近正态估计, e, K2 j$ I# O0 p: D+ [7 ?
Consistent estimate, 相合估计
+ ]1 R3 C" X1 i8 h1 N; V% CConstrained nonlinear regression, 受约束非线性回归
" L& @, |) q6 f) t& EConstraint, 约束( K, Y( e: J& D. r
Contaminated distribution, 污染分布
( a" B. T6 v! ?7 }( y5 H$ ZContaminated Gausssian, 污染高斯分布2 N" o, m& _ A1 `, g' `# B3 M$ B# t: N
Contaminated normal distribution, 污染正态分布
2 O4 ?2 P& o/ G/ zContamination, 污染* q2 X! l$ p4 v. H% @
Contamination model, 污染模型
9 c: U4 X' K' m+ J; {( I9 IContingency table, 列联表
/ v# H6 E: Q+ \) d, ~8 O7 X% NContour, 边界线7 a- `9 Y8 v. k4 G; r7 X, Q1 ]4 D
Contribution rate, 贡献率) S7 M' C( I4 }7 Z Q! n% [' d% ~
Control, 对照' t8 ^3 d7 d) s/ n" j2 V \
Controlled experiments, 对照实验6 d* d- W i# ] h1 f% \
Conventional depth, 常规深度
& N9 q2 L/ m4 ]8 W7 P0 V9 {Convolution, 卷积
7 P9 H2 X f2 ?. T# |Corrected factor, 校正因子( s9 i4 l1 L. T0 Q" {9 ?; c
Corrected mean, 校正均值
4 t( q1 c- A% y" P- i) \Correction coefficient, 校正系数
. e; ~$ O, g$ F b, t4 TCorrectness, 正确性
, Q6 E/ B& r; c4 f* E+ `, \Correlation coefficient, 相关系数: Q0 S1 J( u) @' F. E/ \% ?
Correlation index, 相关指数$ [: J" b* Z/ O4 l# Y
Correspondence, 对应
' i) U; B8 q/ h/ ~% T* K0 PCounting, 计数
* R% R9 b8 A; g# M \: bCounts, 计数/频数
" [ a* a# a3 X1 c' m, K+ S) E' iCovariance, 协方差
5 g- R' D8 `4 p% g, `0 hCovariant, 共变
$ I4 K+ s& `! y @5 oCox Regression, Cox回归$ I8 ~, O& [6 r! t! d/ c
Criteria for fitting, 拟合准则+ N# e6 n3 _) H$ V: _% ~
Criteria of least squares, 最小二乘准则1 a; a @& R- _+ t# |3 s& M
Critical ratio, 临界比% v% v9 e5 Q. {" z
Critical region, 拒绝域" N- Y0 o8 f7 S- t1 d2 e
Critical value, 临界值
) o# ~$ q; ?: m* hCross-over design, 交叉设计+ j& m; r# n- C
Cross-section analysis, 横断面分析
/ X p8 p( L6 o/ Z0 uCross-section survey, 横断面调查
/ K; Y6 Q+ L3 t+ T* ]! P" _) KCrosstabs , 交叉表 & {. V+ K. k7 P1 t
Cross-tabulation table, 复合表9 O9 S% S/ N0 p! X
Cube root, 立方根8 s& l' @1 }6 B' ~- ^
Cumulative distribution function, 分布函数
+ m& B) W7 [6 R0 v$ @9 ICumulative probability, 累计概率- x0 d! A( y1 E% V3 @
Curvature, 曲率/弯曲
+ B# g4 s: w, k! O& ~& wCurvature, 曲率$ m* X9 m6 Q& j% w3 r7 f
Curve fit , 曲线拟和
* u1 X7 A. a& mCurve fitting, 曲线拟合
& y4 C g; E# X* G6 vCurvilinear regression, 曲线回归2 b: K; {; v0 B5 J+ C& F
Curvilinear relation, 曲线关系
# m. ]% m' |( t. XCut-and-try method, 尝试法
; ?) n' L! v. Z0 `2 t# rCycle, 周期
6 ]: x* y0 S& r; t1 u/ H/ wCyclist, 周期性8 Y1 J' u; b: K; x( v6 {
D test, D检验
, c3 ^) \* b1 V% _0 C2 mData acquisition, 资料收集- p7 P5 f6 c" U9 Z( f
Data bank, 数据库
3 u5 M( N9 F4 K hData capacity, 数据容量
/ B9 r7 k9 k2 w" `; b' t5 w1 AData deficiencies, 数据缺乏
f2 L/ w2 d' t7 z: o; J& TData handling, 数据处理3 e5 N& F! P2 ~. m0 u
Data manipulation, 数据处理( n) k* e8 G2 X' f( w6 c% Y# J
Data processing, 数据处理, @& t) @4 f9 J# }* ?9 S" m
Data reduction, 数据缩减
" a* s; V* M& w0 dData set, 数据集2 e! B" d# Y; v( D
Data sources, 数据来源
8 j% C( S0 W2 z# c \* S4 B- z2 m# JData transformation, 数据变换
+ }+ b7 \: H: _7 KData validity, 数据有效性( w# R4 P$ J2 B! L) \% ?
Data-in, 数据输入
0 j; S/ k; J. j" k7 x2 gData-out, 数据输出
9 D8 }3 B# @& Z, ]: ^+ hDead time, 停滞期
" _! p+ T$ S4 \* X. b( U* v SDegree of freedom, 自由度) G7 q/ y3 i" H4 y
Degree of precision, 精密度
0 b, |- i4 g4 P w9 F2 i- [- C4 Y" bDegree of reliability, 可靠性程度3 e" \: j: R' ^
Degression, 递减
- v4 A6 \) {" K" V1 C oDensity function, 密度函数, L( H v V' @
Density of data points, 数据点的密度7 l0 I! Z0 k, [! }( t5 P `
Dependent variable, 应变量/依变量/因变量: E6 F8 [4 C5 K( `# w3 c
Dependent variable, 因变量
0 I* {2 |; E: T2 ]' n8 vDepth, 深度
M6 i* F2 ?) d+ Q, FDerivative matrix, 导数矩阵
. \3 H' ~% ^% zDerivative-free methods, 无导数方法
; }4 ?. C& {8 t& FDesign, 设计2 b# i! T1 K' e. F6 ]
Determinacy, 确定性% y- d: ^# P1 Z* S: E+ U& b/ v/ [
Determinant, 行列式
P- P. ^$ G) o2 L6 jDeterminant, 决定因素
9 L$ z) @, Z' \/ x6 FDeviation, 离差+ C0 G. P. }" N# l4 s6 `
Deviation from average, 离均差; N6 {1 p7 F) d- T. ]$ y
Diagnostic plot, 诊断图6 [& w# C: `/ F5 W& S
Dichotomous variable, 二分变量5 T, N+ _7 w9 r; n! I
Differential equation, 微分方程) X3 p/ O2 D8 ] v
Direct standardization, 直接标准化法! c: r% G+ `4 ?0 W; E9 @' N
Discrete variable, 离散型变量7 j* x' A' c- e
DISCRIMINANT, 判断 ! X2 {3 h6 E, c; ]
Discriminant analysis, 判别分析1 \% I' u t1 {- r
Discriminant coefficient, 判别系数
" [1 C8 `# w/ z! E2 H6 @Discriminant function, 判别值
. [+ d- a- s4 `7 Z8 K p+ W% BDispersion, 散布/分散度
5 v5 d) A6 Z J3 M; j7 v/ N0 cDisproportional, 不成比例的7 O* ]7 H" Q! t
Disproportionate sub-class numbers, 不成比例次级组含量 F" i' F, @) z7 W) s/ ?
Distribution free, 分布无关性/免分布
2 _ [$ F: G8 j ]' `$ DDistribution shape, 分布形状
0 [& \; i' `' S. gDistribution-free method, 任意分布法4 ?+ {# t7 V. h+ Y2 F% C, |
Distributive laws, 分配律
) P" y# z; v/ H' K4 C0 TDisturbance, 随机扰动项3 \" w7 p2 t& m- F4 D3 d" d
Dose response curve, 剂量反应曲线
, g- v2 R& @: F! M- v P8 Q( ^* dDouble blind method, 双盲法
+ }. D" |0 V0 R6 oDouble blind trial, 双盲试验
3 v& g; ~1 y) R6 ]* J$ iDouble exponential distribution, 双指数分布
' V/ D* J0 f* K2 N# W# C. PDouble logarithmic, 双对数% A7 I z Q% Q% M$ O7 K; @
Downward rank, 降秩) d) w( M3 b! U$ `! c. S
Dual-space plot, 对偶空间图
: a( V& p, @- E' N( w& }& @DUD, 无导数方法3 E% {2 _( R& d6 c0 f# D9 N
Duncan's new multiple range method, 新复极差法/Duncan新法' g3 u5 d$ j# o4 F
Effect, 实验效应$ G% H2 j: [) E5 X' P: |
Eigenvalue, 特征值
$ I+ f( H1 Q8 I, L6 u4 ~, |' [Eigenvector, 特征向量
9 G F! f- U8 j3 N/ OEllipse, 椭圆
C. B4 m# I$ k1 l( f7 E! y( tEmpirical distribution, 经验分布2 I0 \, u. I: i: F% k; @9 f
Empirical probability, 经验概率单位
9 L/ ^; m/ C5 zEnumeration data, 计数资料
. _- @0 w' j1 o; mEqual sun-class number, 相等次级组含量
3 ?7 G5 r, \: YEqually likely, 等可能
5 G f9 O/ [, K) \: ~( CEquivariance, 同变性" F0 K# `# w" x3 ^ G' V
Error, 误差/错误
0 O* j2 c) ~! i3 L3 l% pError of estimate, 估计误差
' s+ f O9 K) y" V8 MError type I, 第一类错误
1 l: ?/ g1 W7 J, u, hError type II, 第二类错误9 e+ V% O4 J( y7 G! n/ z9 R
Estimand, 被估量
' q }) O5 q, h( G2 P/ bEstimated error mean squares, 估计误差均方0 R& @% N1 }+ x) K% A
Estimated error sum of squares, 估计误差平方和
% D3 L1 i& \2 f4 A" g( AEuclidean distance, 欧式距离
3 V, t$ L) H% x0 zEvent, 事件
, b4 D4 @$ X8 u! r' r7 mEvent, 事件5 j+ h4 Y% ~ `
Exceptional data point, 异常数据点
% o) ^8 X1 `4 V4 @: HExpectation plane, 期望平面
* `, P! A+ Q3 O' h3 J! O2 P$ Q9 tExpectation surface, 期望曲面
0 c! W: B+ w3 I" IExpected values, 期望值( q" K6 X6 {3 S: e5 a1 ^
Experiment, 实验. k# r3 L6 ~, s% V
Experimental sampling, 试验抽样( Q2 ~5 r2 P( @5 ]/ S
Experimental unit, 试验单位+ Z; \/ R! @1 |- _
Explanatory variable, 说明变量7 ~1 l8 u( A( A
Exploratory data analysis, 探索性数据分析9 d- t+ I5 P+ @! ^+ O |; j3 m
Explore Summarize, 探索-摘要3 Y1 v) D9 A- F/ L5 P& S
Exponential curve, 指数曲线
+ \" q% J, g2 o; [Exponential growth, 指数式增长
, ]3 l* R! m7 D1 e! P' JEXSMOOTH, 指数平滑方法 & V5 Z3 Q- s, N7 @; J! P
Extended fit, 扩充拟合
0 H0 D+ E- U; W% h$ o; p3 z' EExtra parameter, 附加参数, ]+ t3 u0 s4 N* {0 i! u# D6 J5 J+ S$ M
Extrapolation, 外推法5 c; N- |4 M! j3 z) E
Extreme observation, 末端观测值
1 B+ q8 I8 O2 l. mExtremes, 极端值/极值
1 r8 a' g( z6 {+ RF distribution, F分布
: {/ N) D T8 n8 g( _F test, F检验
- X& F3 a) h. b4 `* GFactor, 因素/因子# h8 J' x l( F2 p# I, P# e
Factor analysis, 因子分析$ ~' e" }' I+ u- ]3 ?
Factor Analysis, 因子分析
; u' D) |5 N6 @, i7 `* e Q: WFactor score, 因子得分 & Q" D i% v- n1 E
Factorial, 阶乘
8 p5 Y8 \4 c; y6 R# v& UFactorial design, 析因试验设计
2 A2 c( t. t8 ]& P( W1 xFalse negative, 假阴性, v% J1 {4 C; p- p. z
False negative error, 假阴性错误
) ~1 {' s' H# i- eFamily of distributions, 分布族
1 c! p: ~9 z8 m. e7 E: A8 n) SFamily of estimators, 估计量族
& F. S% } a7 k/ G* ~6 T b9 PFanning, 扇面
$ `, b5 O& j I. g7 L3 k5 [5 ~Fatality rate, 病死率+ M& O: y7 P7 X' K3 m7 ^! W
Field investigation, 现场调查
4 C1 U* |# D1 a5 k a& q2 T0 J$ @Field survey, 现场调查& b$ l5 P0 y: ~* b
Finite population, 有限总体+ l+ N0 q6 V3 f' m5 s
Finite-sample, 有限样本
9 e1 a4 S; q4 aFirst derivative, 一阶导数
9 ]; \0 }$ u4 j+ b' O5 ~First principal component, 第一主成分
$ h( z6 j7 X( F. B7 n3 e3 N) DFirst quartile, 第一四分位数6 ] L0 {0 B q" X: L
Fisher information, 费雪信息量7 w' X2 Y3 G" o
Fitted value, 拟合值
: a- p+ }$ U; R7 H2 _Fitting a curve, 曲线拟合4 P( b7 D2 [1 O( m7 I* f, ~& k: a
Fixed base, 定基) [( L9 f! H: }
Fluctuation, 随机起伏5 v- \, t$ O9 N
Forecast, 预测
4 h9 @$ ?# x4 m b0 zFour fold table, 四格表
- E! X/ b& A4 c4 X2 qFourth, 四分点' t5 \$ g8 ^8 g0 }0 m% J
Fraction blow, 左侧比率, |+ Q( }5 W+ ?5 l# K; v. L/ s
Fractional error, 相对误差0 Z6 _# Q9 Y* ^! b1 G2 T- q
Frequency, 频率' L* N0 o8 q& O8 r% ^7 _' O. D
Frequency polygon, 频数多边图
1 o8 f0 z! L. `# pFrontier point, 界限点
6 X) i; n# @# I$ f; GFunction relationship, 泛函关系0 Y' K" A i6 b% F+ H
Gamma distribution, 伽玛分布
/ ^5 T E- x& v* N- g2 l$ c- v0 v2 ~Gauss increment, 高斯增量 ~# A1 v8 y: }8 |
Gaussian distribution, 高斯分布/正态分布3 g8 z8 P* }! S% ~$ x
Gauss-Newton increment, 高斯-牛顿增量* `8 W, `9 X' m# W% b7 f$ w0 u
General census, 全面普查
& y1 @# p8 ~ g/ IGENLOG (Generalized liner models), 广义线性模型
; `6 u- C$ y( k3 h2 v" mGeometric mean, 几何平均数+ ~8 z' X. X9 b5 |
Gini's mean difference, 基尼均差0 ^/ Z s( E) ^% d% ]
GLM (General liner models), 一般线性模型
, K9 j" l( |, @8 @Goodness of fit, 拟和优度/配合度* z' E: L3 q& g h. q
Gradient of determinant, 行列式的梯度 O& Y' w" F5 v+ { z( u
Graeco-Latin square, 希腊拉丁方
& s6 }% P; g: y& _6 }" r# p! Z$ iGrand mean, 总均值: K9 O; w2 I( p3 l* h! Y
Gross errors, 重大错误
2 M, L" j7 G) YGross-error sensitivity, 大错敏感度
6 m) _0 _7 F0 C( ]+ {( qGroup averages, 分组平均
/ R& j2 R2 N$ ~6 j+ R; L' @& ~/ z/ }8 HGrouped data, 分组资料, o; Z6 b) v- M, O1 W i
Guessed mean, 假定平均数8 ]0 W7 r3 ]# F+ w4 o' W
Half-life, 半衰期. ^, M5 l$ R% N: u: A3 G
Hampel M-estimators, 汉佩尔M估计量- c b9 T( X" W# e2 s: ]
Happenstance, 偶然事件* a: [. Z) @* s( S
Harmonic mean, 调和均数
0 I2 B5 t2 S9 ~& K9 a* I5 lHazard function, 风险均数( ?, d2 W5 A- [7 g6 ?2 Z
Hazard rate, 风险率8 o& Q0 o( o6 {
Heading, 标目 8 ^5 e8 A" @8 [/ z0 D8 V% x N
Heavy-tailed distribution, 重尾分布
G2 J4 o8 v: v9 PHessian array, 海森立体阵" z7 D% e X" Y2 @; n
Heterogeneity, 不同质5 \6 [- R( i. c. S$ o1 P4 V
Heterogeneity of variance, 方差不齐 ! X8 E7 N6 m5 F: @6 C. M; m3 P- x4 I
Hierarchical classification, 组内分组7 C+ S, D3 s! d
Hierarchical clustering method, 系统聚类法3 ]. e4 f1 O) @$ S8 q" l: O0 x. @
High-leverage point, 高杠杆率点( `8 Z) @2 D- e3 L4 q. [) l
HILOGLINEAR, 多维列联表的层次对数线性模型, G1 K! N2 y: e( a
Hinge, 折叶点
. u/ P* F3 n) }+ `% L# Q U3 aHistogram, 直方图
% _5 {- F+ f3 J' O2 aHistorical cohort study, 历史性队列研究 2 d! K" ?2 ?( U4 m
Holes, 空洞
( U" Y9 E( v1 @+ y/ MHOMALS, 多重响应分析: v8 T1 |" A- V7 {! x: H
Homogeneity of variance, 方差齐性/ I) K% M _- {, u. T( s1 @) k
Homogeneity test, 齐性检验
2 k- P) d9 \' t" ]$ d0 e$ qHuber M-estimators, 休伯M估计量
" w: F/ P: e, C& ~9 C* S$ KHyperbola, 双曲线- p, l) ~. _ [+ H
Hypothesis testing, 假设检验+ ~4 n' a1 b' x5 E
Hypothetical universe, 假设总体
* y5 p" i0 z# b1 S+ `; UImpossible event, 不可能事件/ }* j1 k- E. s7 _/ }2 j0 N1 h
Independence, 独立性) d- @& m( e/ d
Independent variable, 自变量
. z# c0 {$ L" e/ w0 R I; w* iIndex, 指标/指数
6 u; a9 M% v$ z& B8 r1 ^Indirect standardization, 间接标准化法5 P/ y) D2 x2 w- _: x# v4 O- N
Individual, 个体 O9 ^. l: I# {: L3 N, X: e
Inference band, 推断带
4 U* I: y' V% ]2 ]Infinite population, 无限总体
; l1 L* n; N6 ~) s" E9 \/ Y& GInfinitely great, 无穷大
" ^9 i2 u9 u# q: oInfinitely small, 无穷小" E' q9 S3 |- l) k
Influence curve, 影响曲线
# L$ e$ @6 h" Q6 S9 q: B _% LInformation capacity, 信息容量, ]! Q) ]/ r8 D
Initial condition, 初始条件
; R6 {3 r# z2 S9 SInitial estimate, 初始估计值( _/ o& Q, V( _/ G' R
Initial level, 最初水平" H& ~+ D! S$ h
Interaction, 交互作用
9 `4 Z# q% B9 u0 E* {Interaction terms, 交互作用项
& @0 G- F6 V2 v7 k! TIntercept, 截距
+ v! H( G5 F6 W! n6 U6 c) zInterpolation, 内插法
2 r, ]. a" S% V( P2 N/ WInterquartile range, 四分位距( r& W4 r; _# }, M" q4 J
Interval estimation, 区间估计. @# A: u: L0 ?6 B) v! B- F
Intervals of equal probability, 等概率区间, w) {! ~& l# u6 {
Intrinsic curvature, 固有曲率$ u: X* p6 P' J/ C/ n# ?! x( w
Invariance, 不变性) Z& f1 Z/ g6 O# ?
Inverse matrix, 逆矩阵
) @0 o+ k0 d Y/ z! `3 r" ^( yInverse probability, 逆概率
* B- M0 Y. E0 Z6 n$ F# |Inverse sine transformation, 反正弦变换' j$ u9 {2 m8 k* ^
Iteration, 迭代
; k7 T, L" n$ K5 D. [Jacobian determinant, 雅可比行列式8 n8 Z% ^ w; T( t' B
Joint distribution function, 分布函数
1 i6 Q' t: I3 U6 iJoint probability, 联合概率6 y* Z3 i, G/ f
Joint probability distribution, 联合概率分布( q! r# a$ |* f! D7 H8 F+ A7 U
K means method, 逐步聚类法
8 B3 C/ t/ L8 I6 h4 N) n% _# PKaplan-Meier, 评估事件的时间长度 ( [* F0 T2 v6 s# N% r
Kaplan-Merier chart, Kaplan-Merier图
$ a6 F/ O; c! `: k" ?6 vKendall's rank correlation, Kendall等级相关
4 d! C, P2 b! _ M% hKinetic, 动力学
: [( ~6 \/ f/ O- a# \Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
3 z' o# Y" B: a9 `Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验! m& V" B9 f& W9 w8 F3 U) _
Kurtosis, 峰度8 z( K& k# l- M( m3 U; |& ]" W
Lack of fit, 失拟# v7 A! Y3 q$ [( L7 Y9 ~% `4 g
Ladder of powers, 幂阶梯
- j2 I8 y6 o0 L0 R3 }& ~ ]Lag, 滞后
' t. ?3 t' E' B2 G4 F6 q. v0 ULarge sample, 大样本9 D" K) @" M: h/ v% }# b6 B2 z& j: ^
Large sample test, 大样本检验
2 }- i. W) v1 h5 D9 ^Latin square, 拉丁方
/ X8 {3 W: h% v7 v4 \8 ~Latin square design, 拉丁方设计3 ]$ G# j! ~ i1 W
Leakage, 泄漏
! v9 o, g+ E" k6 x& Y& i$ H6 [Least favorable configuration, 最不利构形- `! ~" Q* N8 `/ ^7 r
Least favorable distribution, 最不利分布& j3 ]0 F/ n i: ]/ T# A W/ h
Least significant difference, 最小显著差法% h7 r/ v& G& Y6 n) a! B7 G) E5 F- f
Least square method, 最小二乘法
+ w# k% @1 m6 E1 Q# h& WLeast-absolute-residuals estimates, 最小绝对残差估计
1 F9 f1 P& x" @0 I- QLeast-absolute-residuals fit, 最小绝对残差拟合
6 T4 z; u, t0 l* V; `1 @+ q- d7 oLeast-absolute-residuals line, 最小绝对残差线5 |& f4 p* x8 p) M. D
Legend, 图例2 f2 @% v6 k5 L
L-estimator, L估计量
2 {" p* C5 \# XL-estimator of location, 位置L估计量" ?" }. T' r8 n! I
L-estimator of scale, 尺度L估计量7 U6 o9 I' d3 g7 X6 X
Level, 水平
0 a5 @" T1 R* l" P# kLife expectance, 预期期望寿命
$ S8 n/ @5 y5 lLife table, 寿命表& t& ~0 [# S; O z$ }: D9 e
Life table method, 生命表法) \: J6 \ l" k# m- U d5 N5 v. d/ f
Light-tailed distribution, 轻尾分布9 Z2 c t2 z7 B+ I4 }* ~
Likelihood function, 似然函数% x3 N. [8 A4 a( ]; L* k9 B. D2 Z
Likelihood ratio, 似然比
, H i8 a W' C! \* k6 Kline graph, 线图
. X6 D$ L2 Z5 o5 CLinear correlation, 直线相关
1 E4 I3 ]5 {7 {2 |0 q# a/ oLinear equation, 线性方程. V) d m. L2 L5 u6 t5 K
Linear programming, 线性规划
6 z% ^, V, \# H: o' k9 T4 eLinear regression, 直线回归
- I9 I3 I9 r1 _' L, }Linear Regression, 线性回归
0 U+ p2 E0 f* |% MLinear trend, 线性趋势; T3 D7 M$ ~$ L* p9 Q4 U6 q# G& X
Loading, 载荷
* b4 k$ c# o; r O1 v9 tLocation and scale equivariance, 位置尺度同变性
, G# N* F# G# `- W; \# G- aLocation equivariance, 位置同变性
5 [. g: F! W4 x/ Z+ GLocation invariance, 位置不变性+ p* n7 V" W3 O
Location scale family, 位置尺度族
0 s( _" M4 y3 V; s: MLog rank test, 时序检验
5 n5 \ R$ s. \1 f- M* FLogarithmic curve, 对数曲线& d7 M; F) x# V& v( {) x' L
Logarithmic normal distribution, 对数正态分布 x1 ^3 M% a5 D( y
Logarithmic scale, 对数尺度) E9 h9 _* }! t+ R+ D
Logarithmic transformation, 对数变换
( J' D; [* x- l% l) r2 GLogic check, 逻辑检查
& U5 [: d% e# j+ o$ i" j" e TLogistic distribution, 逻辑斯特分布
: i6 v; y; h$ X# @9 b6 ?& ]Logit transformation, Logit转换# V5 b. A( _- ~
LOGLINEAR, 多维列联表通用模型
& G( v" S& X2 H+ OLognormal distribution, 对数正态分布7 r7 k T R, S
Lost function, 损失函数
# C; u/ I: |! [: KLow correlation, 低度相关4 l) D% D0 Q4 L6 l6 I
Lower limit, 下限
5 W7 H; q: K) m/ b: e/ Z3 QLowest-attained variance, 最小可达方差
' A4 O7 c+ G* v3 Q: x8 j% fLSD, 最小显著差法的简称
3 ]# q. p6 j* Q* o7 sLurking variable, 潜在变量0 e/ t: n2 r. e% q* B/ s
Main effect, 主效应
; E( X+ K t" W: y9 D% ^" T4 ]3 RMajor heading, 主辞标目
; W- e9 a* @1 k1 l/ x% d) z; ]Marginal density function, 边缘密度函数
7 g5 W$ `) z2 Z) `Marginal probability, 边缘概率
" _9 G* G. U: J6 H5 f) k: ZMarginal probability distribution, 边缘概率分布
- C/ D9 H1 z4 T6 e; dMatched data, 配对资料
" ^% A+ a; l- WMatched distribution, 匹配过分布
$ G, a& Y+ R9 d" }4 u, `5 cMatching of distribution, 分布的匹配
) e& r) v5 i* O; MMatching of transformation, 变换的匹配
: j2 X& V3 Q5 p& EMathematical expectation, 数学期望; D% e$ [9 V) [, \% R n
Mathematical model, 数学模型
3 E5 v" g7 }1 _1 `Maximum L-estimator, 极大极小L 估计量6 T$ c0 P; U* i) u: x) N
Maximum likelihood method, 最大似然法
8 ?3 o, |2 z$ vMean, 均数7 S/ S3 Y( S3 e
Mean squares between groups, 组间均方, \$ S5 [6 K0 ^3 k: U) F
Mean squares within group, 组内均方, {# c9 d, ?6 l0 H! T: f
Means (Compare means), 均值-均值比较
9 g' Z$ C+ _" a: W" `Median, 中位数" k2 J1 x$ m1 T `
Median effective dose, 半数效量( @8 ^1 z* m. q& ^) H; l9 C# F
Median lethal dose, 半数致死量
4 _/ z# E9 e, q2 r" k" CMedian polish, 中位数平滑+ x$ t# _" H( q9 {5 m' @0 W
Median test, 中位数检验5 X! c' R' \8 I! B
Minimal sufficient statistic, 最小充分统计量
& z1 G7 S& _2 uMinimum distance estimation, 最小距离估计5 X; w$ F$ p5 e
Minimum effective dose, 最小有效量/ h: R/ Z$ V) m5 g- y1 u
Minimum lethal dose, 最小致死量
. {% T: R" O& |) q; A: }Minimum variance estimator, 最小方差估计量6 Z; J* E$ f: D/ `+ ?# u1 ?
MINITAB, 统计软件包# n2 Y, m; O# X3 g
Minor heading, 宾词标目: }, Y+ N" ?- E* p1 P
Missing data, 缺失值
' N4 E8 Q$ U+ U- `Model specification, 模型的确定* Q) v7 y" }& M; s9 }* f
Modeling Statistics , 模型统计/ L8 u5 o8 p0 x l# @
Models for outliers, 离群值模型
$ j7 g0 x$ D& m' \* A r) ~* [4 lModifying the model, 模型的修正' B( f: c3 V8 Y& C
Modulus of continuity, 连续性模8 `3 }. q5 A0 V# q# O* U$ s) R$ g, l
Morbidity, 发病率
1 _( P% `" e7 f, pMost favorable configuration, 最有利构形
( u% f, L; \0 ^# i- s! [Multidimensional Scaling (ASCAL), 多维尺度/多维标度
; d( W# n8 Y4 O9 l- P9 `Multinomial Logistic Regression , 多项逻辑斯蒂回归0 M, K0 G2 u1 [+ w; c- C1 C
Multiple comparison, 多重比较
; Z; }$ q# u8 Q9 }, k/ SMultiple correlation , 复相关% W0 j7 e5 u" B+ A
Multiple covariance, 多元协方差8 _0 q+ ]7 G6 [- t+ J4 l' C% ?6 B3 D
Multiple linear regression, 多元线性回归& v8 t" e: l3 W( A* ]
Multiple response , 多重选项; H! v: U- r3 _, `4 p, Q
Multiple solutions, 多解: h6 I3 i5 M+ X+ V! Q: q+ E7 j; a; N
Multiplication theorem, 乘法定理
( X& J$ g+ _! E: h2 u3 T, h) HMultiresponse, 多元响应
1 g% G% M" x1 S5 QMulti-stage sampling, 多阶段抽样$ ]+ L0 v0 g$ ^$ q# l
Multivariate T distribution, 多元T分布! `) n# w( x, f
Mutual exclusive, 互不相容
, e9 b) B* V$ c4 ZMutual independence, 互相独立
$ j: l* A& x" G: jNatural boundary, 自然边界
2 r; [* ?1 F6 }Natural dead, 自然死亡
9 I; Q# l$ \. E; SNatural zero, 自然零' c8 @. p" }/ c8 t" h. ?9 G
Negative correlation, 负相关
7 c) m- f9 F5 FNegative linear correlation, 负线性相关; n. W$ k$ k" k! }7 ~2 G" u
Negatively skewed, 负偏
: o# H& F# o! W1 z! e1 O$ FNewman-Keuls method, q检验2 Y" [6 \8 e- ?! e
NK method, q检验
( L' K+ ^ [: F+ [4 ?+ N9 ?No statistical significance, 无统计意义' b& u! t7 x9 E6 d3 N3 w |
Nominal variable, 名义变量
& F6 B+ V: E+ V( }0 S2 |# @Nonconstancy of variability, 变异的非定常性
6 x8 `* p& W% i- INonlinear regression, 非线性相关
0 w9 j2 e8 Q+ ]Nonparametric statistics, 非参数统计; E8 @( k3 {0 k) v1 x7 m1 M
Nonparametric test, 非参数检验2 [% @, h% a$ c9 P5 \% E/ R: d
Nonparametric tests, 非参数检验
& y* ], @# l0 a8 P1 o% ?+ {Normal deviate, 正态离差
7 }( p+ V+ O3 ~- F, MNormal distribution, 正态分布/ G1 f) v7 ^9 u& t- w8 M a) Y
Normal equation, 正规方程组
0 c; t7 T- \6 C' n" T; h9 i: l/ rNormal ranges, 正常范围
8 T' Q* ]: [7 k3 F0 hNormal value, 正常值
2 F" R k5 s f! p7 z/ g8 gNuisance parameter, 多余参数/讨厌参数* d$ K3 {3 o0 Z1 t. w! D8 {' Y3 {! m
Null hypothesis, 无效假设 + k4 c; N, t# g$ M
Numerical variable, 数值变量
4 G* D; W8 g+ [" gObjective function, 目标函数* Y! d, T% E: Q5 G
Observation unit, 观察单位
$ p+ m2 C+ ]& u; C# XObserved value, 观察值0 ^$ d: d( X+ D' ]# U. v& J1 s
One sided test, 单侧检验$ k# \ o+ E/ Z- ?$ X
One-way analysis of variance, 单因素方差分析. ?' N8 q$ ~1 |$ v
Oneway ANOVA , 单因素方差分析7 m4 j# Y4 L! C6 |+ J
Open sequential trial, 开放型序贯设计
+ i- [* }1 `# r, b* e; Q. ]) hOptrim, 优切尾 U1 y2 p$ g9 W& F4 f: I
Optrim efficiency, 优切尾效率$ r8 h6 n! k3 v/ V) H
Order statistics, 顺序统计量* y: n# `4 S! E# M; B
Ordered categories, 有序分类
/ g1 C7 ~$ }+ D" bOrdinal logistic regression , 序数逻辑斯蒂回归4 P9 J3 z, J3 c# p$ d4 w! ?
Ordinal variable, 有序变量
. i3 Q- \% h9 r" l' tOrthogonal basis, 正交基
. ^3 ]$ W; e# S6 e8 l' gOrthogonal design, 正交试验设计
, t4 V; f. S- |* N/ u8 F0 B0 c uOrthogonality conditions, 正交条件+ V- C6 e0 c* I" {7 J/ Y4 \
ORTHOPLAN, 正交设计 : J& N/ T- D& s% x" V( N4 i
Outlier cutoffs, 离群值截断点% x8 F+ y4 {1 I' }, t
Outliers, 极端值
0 P; e! J1 S, W# `0 X: U% oOVERALS , 多组变量的非线性正规相关 ) S: d& S7 k" ~! s9 A
Overshoot, 迭代过度$ ^% M2 x8 L+ ?$ ^+ l! x
Paired design, 配对设计
9 e4 A5 n l+ R6 Q6 b/ l& e1 \Paired sample, 配对样本
0 r! L- s- z& ?8 }3 DPairwise slopes, 成对斜率1 ]$ G) d; t# q: ]2 ?
Parabola, 抛物线! @+ a1 b: n7 _( M
Parallel tests, 平行试验2 Z, f" J3 }8 `8 y. o% o
Parameter, 参数! p8 V7 [, Q1 g B
Parametric statistics, 参数统计$ o4 d$ c3 }5 ~5 H; ~/ {
Parametric test, 参数检验( R- f5 R8 @! @6 w! }7 {
Partial correlation, 偏相关
# T( o1 B! V; Z, x1 ~# b& @Partial regression, 偏回归7 {* i: f( f1 g3 z) T3 u1 L: k/ \. k3 @& r
Partial sorting, 偏排序2 q" |' e$ p* b7 c
Partials residuals, 偏残差
" }- `# Z( u( O8 x/ L, F: O# bPattern, 模式& a6 |0 ~, R+ Q9 d0 R
Pearson curves, 皮尔逊曲线7 W, g5 M4 W. _9 u; a+ f
Peeling, 退层9 `* @- _; v4 K E1 y* m) m: S: {
Percent bar graph, 百分条形图
7 Q* @8 L* D$ B0 iPercentage, 百分比
) A% o6 ^, p- _) p8 F. k$ ?, wPercentile, 百分位数0 L( s5 y1 L+ \) Z
Percentile curves, 百分位曲线 _& P) y! L* `& L, Y5 i3 Q
Periodicity, 周期性- N. Y$ C% L& p w m) ]2 i, i
Permutation, 排列
1 d$ L \ a: @; {- j; [P-estimator, P估计量8 s- u7 o* h ]' W
Pie graph, 饼图: U# S7 X+ A$ ?% R) p! ]6 O r
Pitman estimator, 皮特曼估计量
+ p2 R7 g N, s7 A( jPivot, 枢轴量
& x- b: h8 G6 e; LPlanar, 平坦& f6 [3 m! E- h4 s" B/ g
Planar assumption, 平面的假设1 |* k5 V) t0 C" ~; W! j" N1 h
PLANCARDS, 生成试验的计划卡$ ?! o* u. [7 U6 D! \
Point estimation, 点估计
8 N4 `! v$ o3 k2 a+ b3 X) P RPoisson distribution, 泊松分布
2 A v9 y7 w2 W! s1 ^Polishing, 平滑
6 R* B8 e2 U" G4 a! `8 EPolled standard deviation, 合并标准差) y& _ Y7 |! }; w6 z$ \
Polled variance, 合并方差4 d: q# y7 Z% x# v/ \9 n3 V
Polygon, 多边图
* P. J1 `; R5 q. |Polynomial, 多项式2 k& t& @3 Z$ J, ?" ~, G6 M" X
Polynomial curve, 多项式曲线
7 `8 z. E H" h& t1 V& E5 a- SPopulation, 总体
% J" N& p4 B0 W2 D1 s5 G {- KPopulation attributable risk, 人群归因危险度9 J$ h4 F7 H3 u
Positive correlation, 正相关
- l) N( ~7 }( M+ [( R6 yPositively skewed, 正偏0 }1 V; i1 h5 s3 g. [
Posterior distribution, 后验分布
$ B3 X- i9 B: d. ePower of a test, 检验效能
/ v7 l( ~3 e3 p9 }; L1 `Precision, 精密度
; S6 M1 J$ X- \8 B+ o; GPredicted value, 预测值
: \3 I; m0 V- Z7 @Preliminary analysis, 预备性分析
9 J- ] c9 L$ j% kPrincipal component analysis, 主成分分析
4 }! n. Y( |0 ~Prior distribution, 先验分布' @* q" g& l/ W; ^& E0 y* r
Prior probability, 先验概率
2 g$ |. A. e+ ?* I' lProbabilistic model, 概率模型: [, l0 w0 d* p: i1 b
probability, 概率; T. E. V! V" I. |. O& i
Probability density, 概率密度
2 y& c7 p# y9 |+ G& x- MProduct moment, 乘积矩/协方差
; g" {. {/ e! gProfile trace, 截面迹图
- t. {* x; ?: TProportion, 比/构成比& ~* l+ l& L5 O$ q
Proportion allocation in stratified random sampling, 按比例分层随机抽样
3 M0 Y4 J7 f5 G- B4 _4 QProportionate, 成比例
$ p6 a; }. B" W& I$ X PProportionate sub-class numbers, 成比例次级组含量
4 N* g3 Q+ g6 s1 PProspective study, 前瞻性调查+ t, G0 _( Z8 C1 T" d
Proximities, 亲近性 , ~6 _ W' R! _1 q1 U5 l
Pseudo F test, 近似F检验
6 N1 ~7 N- ?. KPseudo model, 近似模型
# r% H1 ~7 k3 X6 B) L7 ~! zPseudosigma, 伪标准差
& z: p n- X, Y' V+ x) R! j2 {Purposive sampling, 有目的抽样
- m% Z. z9 D$ \% n& W# MQR decomposition, QR分解3 Z A7 m! x+ V9 P+ \; i9 |
Quadratic approximation, 二次近似9 p/ n! o. x% y! ? O
Qualitative classification, 属性分类( [7 L! P/ [# v0 G, o& ~
Qualitative method, 定性方法
) w& N6 o3 l3 I: A" [" jQuantile-quantile plot, 分位数-分位数图/Q-Q图2 I& c( B( i* W1 ^% g$ H
Quantitative analysis, 定量分析0 l. }) R7 R' s" k$ T
Quartile, 四分位数( V" b9 `$ ^6 h' @7 w
Quick Cluster, 快速聚类: a% t$ k2 f% o% s+ Z1 ~
Radix sort, 基数排序0 L. @1 i; d3 h4 R3 y% W
Random allocation, 随机化分组# K$ A, }$ O9 X$ F5 ~5 F4 N
Random blocks design, 随机区组设计
& J+ f, e" \: e* k- QRandom event, 随机事件
& ~! F: A5 A; ~" A9 Y5 w8 Q4 KRandomization, 随机化
2 c% A" E$ w fRange, 极差/全距/ [7 V$ O& z$ K$ ?! x" g( z* K
Rank correlation, 等级相关
$ c p1 u9 ?3 Z" V" ERank sum test, 秩和检验4 [- t: z* `; ~& h$ ^2 M
Rank test, 秩检验
9 ~4 j+ x- B7 a. T- \Ranked data, 等级资料: [ Z J& J3 [" Z4 M, m! W' R, `
Rate, 比率 r& W. m. l2 m0 G0 b4 |
Ratio, 比例6 ^$ m1 x5 Z4 H* R0 s& _. w! H: S0 H
Raw data, 原始资料
8 A9 {& c3 ~$ h! ] [# _/ b; E: QRaw residual, 原始残差) S8 Z) I& C3 p4 Q7 t) O8 A
Rayleigh's test, 雷氏检验( i- J% K$ w1 {; ?3 a
Rayleigh's Z, 雷氏Z值
5 f/ L$ k, A& b- k6 YReciprocal, 倒数9 S0 y7 P; B _0 e+ J8 @ ? J
Reciprocal transformation, 倒数变换
) p8 e) l; Y' _' J: @Recording, 记录
1 k) M8 e# O9 l( ~Redescending estimators, 回降估计量
' O6 ]9 l' A0 w/ U+ U8 H8 H9 MReducing dimensions, 降维# T1 A' q3 h0 g0 j. Q- K
Re-expression, 重新表达
' O- O- x6 n/ k( ?+ | I/ cReference set, 标准组
8 u" ]2 c8 i* ?) qRegion of acceptance, 接受域: G3 Q5 Y1 a* h5 }/ F" G
Regression coefficient, 回归系数! A% o$ K7 X, e1 e
Regression sum of square, 回归平方和# E- B5 Y, _" {( l" C
Rejection point, 拒绝点2 ]1 I, _! s7 t' F" M6 C, k- |
Relative dispersion, 相对离散度
7 X4 U$ l7 v5 e4 `$ C8 @! Q- xRelative number, 相对数
' l5 p& \; G0 C/ R5 aReliability, 可靠性4 H; K5 C5 T/ \% y# {
Reparametrization, 重新设置参数
2 Y3 K F2 }% O4 pReplication, 重复 ~" d4 `2 |8 p; `5 O" s3 C ^; w
Report Summaries, 报告摘要
& F( N+ m% q$ o* I3 Y) [Residual sum of square, 剩余平方和7 N4 [* o! z& ]. m( ?
Resistance, 耐抗性
* R1 f) M8 y8 } bResistant line, 耐抗线. j, ]9 H3 t1 q, |
Resistant technique, 耐抗技术1 p/ N" u+ H6 b0 k4 W/ t
R-estimator of location, 位置R估计量3 C5 N$ [3 P& F
R-estimator of scale, 尺度R估计量
/ c8 G! Y `* `( Q* V) I0 }- i; t# FRetrospective study, 回顾性调查
0 E, m* q. ~2 W# \4 m+ I& nRidge trace, 岭迹
# x- n2 Q A9 V) mRidit analysis, Ridit分析* B, X+ d' \ p2 S$ U
Rotation, 旋转/ N; |3 Q6 h- i6 e2 A% ?7 k* p
Rounding, 舍入
: |: ~: k: x5 {: ]; e/ }Row, 行
" U, ^8 H! e4 l! O7 y5 d" bRow effects, 行效应9 _- a$ I9 I. w6 Z$ R. y2 ~. s- ~
Row factor, 行因素# E, G/ q+ k6 f8 O8 c! U
RXC table, RXC表7 G; Q+ N z; Y/ ^" N1 c; N/ ^
Sample, 样本
" @* {* F: u8 ~" Q' _1 gSample regression coefficient, 样本回归系数. d: c1 b o" R6 E; ^1 X& B' [
Sample size, 样本量# i R& }* Z* f' T* Q) u
Sample standard deviation, 样本标准差7 p5 I4 s7 r$ O! E" ^5 v# g
Sampling error, 抽样误差+ |, V) L5 M* d- U( o9 {" L
SAS(Statistical analysis system ), SAS统计软件包
9 f# w' r* `2 o1 }2 |Scale, 尺度/量表" Q) r g& [9 Y, E B* e
Scatter diagram, 散点图8 X; X/ A, A$ D- ]& T
Schematic plot, 示意图/简图# {7 y, o6 [+ ~, i. m
Score test, 计分检验
, V$ T7 f9 d1 R7 VScreening, 筛检/ d4 a* i c% k' O _
SEASON, 季节分析
! M6 ^3 W, c* `6 HSecond derivative, 二阶导数
/ m# ?: O/ ^+ }/ dSecond principal component, 第二主成分
# A* w7 C9 Y% c4 u- {- X QSEM (Structural equation modeling), 结构化方程模型 8 t% Q0 s) P/ T) ^& ~
Semi-logarithmic graph, 半对数图; g* W% e- h0 [
Semi-logarithmic paper, 半对数格纸9 f" }4 z6 L/ Z' `( `
Sensitivity curve, 敏感度曲线
5 j3 I& d ]4 A$ gSequential analysis, 贯序分析
, q) c! e) d2 {7 C9 QSequential data set, 顺序数据集3 U% F2 |" D4 t+ F
Sequential design, 贯序设计
: ?$ {( r" T3 [7 S1 [: OSequential method, 贯序法( V( H8 c4 A- A: g. H$ I8 ?
Sequential test, 贯序检验法5 o/ y6 C# Z9 o$ l9 w
Serial tests, 系列试验; l7 ?& C" W& ]: n0 _) Q( J% t
Short-cut method, 简捷法 % K) k8 K" W' q' G
Sigmoid curve, S形曲线, V3 m3 c# ]0 u! p* j! a8 ^$ h! c! u
Sign function, 正负号函数
5 ? q* G; W s5 XSign test, 符号检验. P2 k2 Y7 ?, h$ R$ w, P. `
Signed rank, 符号秩$ {6 T) _+ d( |* V$ _6 X1 u8 e
Significance test, 显著性检验0 z/ A% g$ x, S% X$ @; ]- @ Q
Significant figure, 有效数字+ \4 V7 `) k2 n% F* p! \) ?
Simple cluster sampling, 简单整群抽样
- _/ Y- m8 h- p _% BSimple correlation, 简单相关! r* T5 X/ B9 p0 v
Simple random sampling, 简单随机抽样 ]! t3 Y/ ~( O
Simple regression, 简单回归/ Z( o! I. J: M |
simple table, 简单表
9 h+ G; K$ A8 ?4 q4 V b7 j) |1 tSine estimator, 正弦估计量- ?' `2 V& t1 K0 Z
Single-valued estimate, 单值估计
; T. v+ l& b- i3 R# H' {0 \% KSingular matrix, 奇异矩阵/ c# k% g/ x$ n, m* R
Skewed distribution, 偏斜分布0 z8 q- K$ o3 j
Skewness, 偏度
9 f# s& S' c: ^! xSlash distribution, 斜线分布! z6 d0 ~, q. {5 n/ ~7 _
Slope, 斜率3 K7 \& o! T2 P& q
Smirnov test, 斯米尔诺夫检验
( r* {+ E3 N, ]" c/ z- C+ r! Z' {/ L4 d3 RSource of variation, 变异来源
' @8 Z8 k, c, w7 U0 \- g9 e, j+ X1 gSpearman rank correlation, 斯皮尔曼等级相关
( h3 _7 e$ e2 \9 F* x' a) CSpecific factor, 特殊因子& ]% N n; w5 a& E& r4 b
Specific factor variance, 特殊因子方差% \ d4 Z2 T# O4 \
Spectra , 频谱
2 u& J+ ~7 b; i& p+ G/ X' `Spherical distribution, 球型正态分布3 b: v. \: r5 d- D5 {; |3 W( p: V$ `
Spread, 展布" U+ D) e1 a% u
SPSS(Statistical package for the social science), SPSS统计软件包7 }8 C) T% e' a# f8 h3 _
Spurious correlation, 假性相关
9 u- O3 F J2 |$ q& U$ Z2 ySquare root transformation, 平方根变换# r) `. F! V3 `' ~* o8 g
Stabilizing variance, 稳定方差
" k, M. l0 K) ?/ \1 Q; a0 bStandard deviation, 标准差
/ ?% N: ^+ K8 qStandard error, 标准误
s" G2 k! _3 \. q8 T$ VStandard error of difference, 差别的标准误
) D) L A& X8 F* {; g8 S$ ZStandard error of estimate, 标准估计误差( ]! E. k) Y( A" C. o* F; S
Standard error of rate, 率的标准误
; _9 D: W4 A; V' [$ NStandard normal distribution, 标准正态分布5 q( A, A I7 P: H
Standardization, 标准化
* x; Z7 b9 e& RStarting value, 起始值
6 g1 ]7 E ^# R. I0 t' w" u( }Statistic, 统计量1 Z$ j, f" J- A, O
Statistical control, 统计控制8 g+ H2 r' W2 Q" [( W
Statistical graph, 统计图* e/ N; q+ q" Y
Statistical inference, 统计推断
0 y7 g- ]/ `3 ?: oStatistical table, 统计表& r0 v, j7 e5 L3 Y
Steepest descent, 最速下降法9 [4 k) i9 c8 z, \ H- G% ?9 C2 v
Stem and leaf display, 茎叶图
" K3 v/ l9 Q: F4 @- K* N: G# lStep factor, 步长因子
* b! I5 D* t& S0 c& VStepwise regression, 逐步回归
, k8 F; @3 q% C4 `& D" JStorage, 存6 c4 J; P2 j9 t I) D0 U2 q) G
Strata, 层（复数）" }2 x4 [- u+ b b
Stratified sampling, 分层抽样" m% k1 E: y4 z- q* a; G
Stratified sampling, 分层抽样
* C8 Z/ z1 g7 `+ GStrength, 强度
1 {; U' [0 ?% w& s" A* W' ^Stringency, 严密性
- L3 R) b, K7 [9 O" uStructural relationship, 结构关系 j: q+ l$ _2 d4 o
Studentized residual, 学生化残差/t化残差
3 o+ P" N, d# {3 X: U8 t/ A2 RSub-class numbers, 次级组含量) Y- K- C6 [8 Y
Subdividing, 分割
7 v# g+ I) F- t- E! X6 ^Sufficient statistic, 充分统计量. n& v: i/ ?; U& N' U# R
Sum of products, 积和
F+ \+ t8 ]. k2 w* NSum of squares, 离差平方和
4 Y; u% o( `5 XSum of squares about regression, 回归平方和" ]- j8 n" a; \( V
Sum of squares between groups, 组间平方和
* C5 e8 q) U6 r, l) aSum of squares of partial regression, 偏回归平方和
( \! s4 J" s% VSure event, 必然事件
0 o: {4 g/ ^# R: X6 R. z0 |Survey, 调查% {! j" \2 c5 x3 d: e
Survival, 生存分析
/ U7 v0 {/ D- y+ f2 z# q. DSurvival rate, 生存率
5 z1 c) G0 e8 L0 G3 f! MSuspended root gram, 悬吊根图
t+ M0 C, \) e F+ x3 {9 F. ~Symmetry, 对称
; s+ W/ ^8 Y1 ?5 ^+ O0 Q; b. \7 O1 _Systematic error, 系统误差5 H" j$ D O9 g5 h% A0 J. w
Systematic sampling, 系统抽样' u7 n- s' l2 ^( w6 k( K
Tags, 标签+ Q. }+ a( ]7 S3 P/ c* d
Tail area, 尾部面积
# J& n$ q7 j3 [ s9 W" n) h" bTail length, 尾长) L4 a/ W1 i3 E9 Q
Tail weight, 尾重5 h9 }9 N- V t9 f& L4 l- E
Tangent line, 切线
! w, V3 R8 x2 v: ]7 N3 q# M. gTarget distribution, 目标分布0 F: ~5 G+ I2 M+ Q
Taylor series, 泰勒级数" [! w5 w3 i5 _' F8 [2 ?' _6 h( P
Tendency of dispersion, 离散趋势) k% r) A4 h2 U6 D6 K7 r, q
Testing of hypotheses, 假设检验
8 Y4 k) P' C. D; ITheoretical frequency, 理论频数: q! V: S% L H% A) P
Time series, 时间序列
# U* m4 H; Z3 b! [7 _: h+ ^Tolerance interval, 容忍区间
" S, H/ h/ }5 XTolerance lower limit, 容忍下限0 R u/ {# }$ w' C! a5 e9 E
Tolerance upper limit, 容忍上限
3 W$ N0 K. w ~. Z* sTorsion, 扰率
- a* x' `$ Z6 jTotal sum of square, 总平方和
8 z/ e- o5 g! `- h, mTotal variation, 总变异
+ C5 C+ _) t4 @* \9 `- UTransformation, 转换
' ^7 C" Q, Z4 Z4 ^0 z' rTreatment, 处理. h$ T- K5 N* @0 y/ X J
Trend, 趋势' o9 P; v5 M `9 a- I: L
Trend of percentage, 百分比趋势: u9 u) r8 }- t2 O) _+ G8 ~, b: t7 W
Trial, 试验
7 i5 w5 m* ^2 p; H: L \. QTrial and error method, 试错法
' F% D# d0 Q5 |% @; z8 w- {3 \Tuning constant, 细调常数3 H7 I+ S0 Q) E* G, k T9 G
Two sided test, 双向检验" O- E5 c' s" G& k& a3 H
Two-stage least squares, 二阶最小平方% s) B. L- m' p9 o) O! _3 S
Two-stage sampling, 二阶段抽样% _* y5 v3 ?! j/ P
Two-tailed test, 双侧检验
m* O( I( E2 D6 |4 V( hTwo-way analysis of variance, 双因素方差分析
, g( o4 l) C( S8 }! O& k7 CTwo-way table, 双向表+ u. }5 ^( t& A" r7 p
Type I error, 一类错误/α错误7 V4 x O M% u, W& C
Type II error, 二类错误/β错误
* u9 H" a" M1 n- Q; I) h3 _/ o! S3 IUMVU, 方差一致最小无偏估计简称
1 s ?/ \, l# X1 }; v8 K0 _Unbiased estimate, 无偏估计% ] W( I) r+ |* X8 T
Unconstrained nonlinear regression , 无约束非线性回归
" L; U" L) C9 ?$ VUnequal subclass number, 不等次级组含量
" `* W7 T* q8 F# i9 pUngrouped data, 不分组资料* r0 o# W% G( e8 q1 b$ g
Uniform coordinate, 均匀坐标- T4 n7 ~3 X0 u% U3 L
Uniform distribution, 均匀分布1 _. m" h" s+ k- V V2 { y
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计/ }" m: N1 v% u# i
Unit, 单元
. G3 H* y; {# f9 \" cUnordered categories, 无序分类
7 I p ]; b1 c5 fUpper limit, 上限1 v: `( v& [$ u4 e4 F5 Y1 F
Upward rank, 升秩% n5 Q! g& q( @) u$ @. y
Vague concept, 模糊概念9 c, y+ E. D) U5 {" r6 V$ v
Validity, 有效性8 z; W- U7 n5 a5 k! J; P
VARCOMP (Variance component estimation), 方差元素估计3 h d& T+ o/ w( w- d( B: z9 s
Variability, 变异性9 l5 F& S$ Y4 A/ Z! s
Variable, 变量
, h* R/ d8 X# t6 r' F5 r" E* j* zVariance, 方差
( J+ |; i9 m2 t8 R/ r; U. wVariation, 变异
8 ^* o; f2 ?: Z6 EVarimax orthogonal rotation, 方差最大正交旋转
' r$ q# q" }" Z! h( oVolume of distribution, 容积
+ N- I4 ?/ v- s9 Y7 mW test, W检验
I5 }' j1 S2 KWeibull distribution, 威布尔分布
. r& W9 O6 |& R0 N1 _Weight, 权数. K: s* g! B. N2 \) a. h5 w
Weighted Chi-square test, 加权卡方检验/Cochran检验
6 Q0 i$ t/ Q! c* D$ A A: qWeighted linear regression method, 加权直线回归) P! r5 U8 d. d' t# g" R/ _% U
Weighted mean, 加权平均数
/ L) b# v g! V9 [( m' D' eWeighted mean square, 加权平均方差; c' }- @. d- C" U
Weighted sum of square, 加权平方和
/ t6 X( k, [. R& J/ C; RWeighting coefficient, 权重系数$ L7 K9 k; o$ c0 J& f) O
Weighting method, 加权法
9 G! @! I3 n7 dW-estimation, W估计量* U5 R6 {! o8 S3 k# F% X0 z
W-estimation of location, 位置W估计量' J- B' U. G2 A- t; E; J5 D
Width, 宽度& n/ P: U6 n4 Y( b0 G
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验& N9 Y4 f9 x4 i* {7 v6 P! Q. U
Wild point, 野点/狂点
# z5 n$ f! w# W( |: G" Y$ R3 gWild value, 野值/狂值4 F6 B8 K" s5 b
Winsorized mean, 缩尾均值8 E' G* n; u9 `( u [; ?0 I
Withdraw, 失访
* G4 P; u* B' e7 Y, y( w. u5 Q/ aYouden's index, 尤登指数
2 `) _7 `5 y* m0 U& `. m# I; mZ test, Z检验 _3 l) b% r; n& W0 Z& I# }1 @- o
Zero correlation, 零相关
+ s- x; K( J0 Z/ t1 A2 J* FZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
