|
|
Absolute deviation, 绝对离差
) H' k" Z- r$ X0 j6 `8 v( D+ k0 ^5 |Absolute number, 绝对数8 b6 w7 v/ e9 ^. A8 h
Absolute residuals, 绝对残差
/ a8 H7 ]5 N% v# F# i; e: ~9 \Acceleration array, 加速度立体阵
5 b, e }& \% j# bAcceleration in an arbitrary direction, 任意方向上的加速度
7 B" y4 P. f6 r4 e; [" AAcceleration normal, 法向加速度
2 @4 X. h2 B7 w5 c, c/ j. zAcceleration space dimension, 加速度空间的维数
- d6 e: @. G$ V3 u5 L% H6 y1 TAcceleration tangential, 切向加速度: M6 p5 P% F6 Q
Acceleration vector, 加速度向量( u4 ~, s* k' l% H* t8 _$ S2 _
Acceptable hypothesis, 可接受假设9 U8 [" F1 c# O, I! `) O
Accumulation, 累积& H9 x& w4 c; u; n: V7 H) M! n# Y
Accuracy, 准确度
/ Q2 o a* m7 n( b( a, LActual frequency, 实际频数
# C4 k! Q8 [+ q$ oAdaptive estimator, 自适应估计量
; K. g8 N" }$ DAddition, 相加
6 K% M6 j1 O5 Y/ CAddition theorem, 加法定理8 Q" i4 S. o# L6 R
Additivity, 可加性: y/ j' d8 Q: q) S; B& n# \) k
Adjusted rate, 调整率# e" o& T+ X0 e0 D
Adjusted value, 校正值+ U$ [' q4 L6 K( m
Admissible error, 容许误差
' v. [* E+ \* N! Z+ f# d3 MAggregation, 聚集性
6 u7 @6 `! g7 q1 e$ l8 iAlternative hypothesis, 备择假设
9 y% H/ E' M# ?2 y7 m) }Among groups, 组间. i+ G% S4 f7 A
Amounts, 总量
$ i7 k) @& D8 a2 nAnalysis of correlation, 相关分析8 H' o9 z# a" A
Analysis of covariance, 协方差分析
, T$ o: N( y/ P8 Z$ Q TAnalysis of regression, 回归分析# O/ n1 U& U( ]" d5 w$ M
Analysis of time series, 时间序列分析: F/ @8 B6 h" T% b7 d+ q% g
Analysis of variance, 方差分析; y9 G- p, O( p7 e
Angular transformation, 角转换
$ Y: {( H7 I. N2 c: qANOVA （analysis of variance）, 方差分析- @) r3 X% A$ J- O% v1 X
ANOVA Models, 方差分析模型2 `/ U% }' D( R4 ]( H
Arcing, 弧/弧旋; H. G. r; |& A
Arcsine transformation, 反正弦变换& c* Y4 O0 C& F0 c& U
Area under the curve, 曲线面积
) k/ d G( ~( W! n: @AREG , 评估从一个时间点到下一个时间点回归相关时的误差 + v/ L) d1 Q7 [& o
ARIMA, 季节和非季节性单变量模型的极大似然估计
& x% \0 O4 ]6 q$ e6 O) m4 dArithmetic grid paper, 算术格纸
4 X& o |0 ?: w1 N# j0 iArithmetic mean, 算术平均数0 U4 S' T' P; G$ T
Arrhenius relation, 艾恩尼斯关系
6 k, U4 E2 E: b7 JAssessing fit, 拟合的评估
) K, J3 e2 e# b- t* o9 |% hAssociative laws, 结合律, \' C, C! E8 [8 J
Asymmetric distribution, 非对称分布
$ u" R' C5 i7 c8 k4 x" U6 i s$ _Asymptotic bias, 渐近偏倚
3 \% | V( d8 l! r( _Asymptotic efficiency, 渐近效率
0 c: X2 ]4 n8 d3 b( yAsymptotic variance, 渐近方差
6 x* e) S7 n2 J2 nAttributable risk, 归因危险度
6 H: e# }. @( @& S+ h( ]Attribute data, 属性资料5 x: u4 S. l8 H3 a+ l, [
Attribution, 属性
3 Q" _$ I) y- L* Q3 uAutocorrelation, 自相关
' g2 l3 d, o7 K7 T9 wAutocorrelation of residuals, 残差的自相关" h, Y1 u. N9 d% y; i, X0 x0 u
Average, 平均数
7 C: m/ ]. s7 n ^3 Y: h$ K# gAverage confidence interval length, 平均置信区间长度5 p( ~9 `4 t9 a& T4 h0 D- n
Average growth rate, 平均增长率4 s: s9 x3 q- @3 J! O
Bar chart, 条形图
2 r9 s1 G# j, \Bar graph, 条形图! \' _* [3 v5 c) h1 j# z4 p' C
Base period, 基期8 r% F# t: b! K& H: {
Bayes' theorem , Bayes定理& z- S# W3 Y& }; g7 e y
Bell-shaped curve, 钟形曲线6 [5 c# K; k) c" ?( p
Bernoulli distribution, 伯努力分布
- [! L) M4 z6 k& lBest-trim estimator, 最好切尾估计量
9 _5 J% C; x/ O, MBias, 偏性
& T9 O7 W1 C# ~4 |: }0 yBinary logistic regression, 二元逻辑斯蒂回归. P* d5 w- m. w8 @: g+ c
Binomial distribution, 二项分布
+ ]& Q1 C7 @/ ~5 lBisquare, 双平方5 F! [9 G! L: i6 L" K( P: A9 E+ Q
Bivariate Correlate, 二变量相关
( g! g* A& S& [$ uBivariate normal distribution, 双变量正态分布
/ _* A: N7 i9 qBivariate normal population, 双变量正态总体
% B+ r6 m1 N0 H. K( ]* b" XBiweight interval, 双权区间- t7 K9 p% r* M' D
Biweight M-estimator, 双权M估计量/ _) ]0 \, R, s, b0 I ]2 b1 n
Block, 区组/配伍组4 X7 F: _; F9 ?& Y' | g7 s9 G
BMDP(Biomedical computer programs), BMDP统计软件包) s& N8 X. Q d& e1 q, L0 N
Boxplots, 箱线图/箱尾图
$ {6 C! N, I# s- [8 P5 cBreakdown bound, 崩溃界/崩溃点
5 U1 L% \. ~9 E; d' \! |7 h, O3 L8 cCanonical correlation, 典型相关% S3 @7 @! Z0 J' M0 h
Caption, 纵标目) {& k" F+ G. H7 O& K9 j
Case-control study, 病例对照研究' a7 \+ `' u1 Z. [; Z7 g% w7 I/ c* o
Categorical variable, 分类变量8 t, e( b, g1 ?
Catenary, 悬链线
9 N, i0 \& A0 T- ICauchy distribution, 柯西分布
^7 f' B; C7 X* `1 c) WCause-and-effect relationship, 因果关系* v& H6 g* W' X- t* ^7 g8 ?
Cell, 单元7 h' K) V9 D/ ]- V% D5 T; g
Censoring, 终检
5 U4 S6 m4 I* ?$ l, u3 gCenter of symmetry, 对称中心9 `- x C) ~- U2 C' G f. h( q$ Y6 |
Centering and scaling, 中心化和定标
2 L( t' S: p' [0 D( SCentral tendency, 集中趋势
1 i# U- x9 A' M, FCentral value, 中心值8 p* {/ H( C8 g
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
3 e' E$ z0 M8 ZChance, 机遇 x Z9 x2 e# L0 [8 E/ x* ~; O
Chance error, 随机误差
& G& [" h- S1 Z8 R1 U3 iChance variable, 随机变量
- c* j3 r, C b& yCharacteristic equation, 特征方程
1 z/ Z) D7 r. R2 C" n) e5 j1 hCharacteristic root, 特征根 u5 \; | b: o* S( J$ D
Characteristic vector, 特征向量
5 g% m- O3 X: X6 qChebshev criterion of fit, 拟合的切比雪夫准则
9 j5 w0 s' u F( f& }. N+ ~Chernoff faces, 切尔诺夫脸谱图
5 @. }$ h7 y1 z6 AChi-square test, 卡方检验/χ2检验
! H' r. ^6 P' d3 VCholeskey decomposition, 乔洛斯基分解/ a ?2 _. q4 n3 l3 u4 l e$ y8 I/ f
Circle chart, 圆图
( v# d3 |( \2 Z! J1 S7 uClass interval, 组距! R, H" [4 w, a9 R8 P- D/ R
Class mid-value, 组中值
1 R% r* U+ {* t$ Y% o1 nClass upper limit, 组上限
$ f0 l. F) J0 V: \2 r, K& S$ UClassified variable, 分类变量
1 Z3 u' s2 R" d5 HCluster analysis, 聚类分析: A8 R) [8 Q! \% t% M9 g! a) E
Cluster sampling, 整群抽样' t. k- v) c+ z. m
Code, 代码
% g+ |3 I& V: C5 o$ oCoded data, 编码数据0 {* s+ z/ L0 G: M3 _; Y
Coding, 编码
; M! h! V4 i& x+ D7 ^Coefficient of contingency, 列联系数
3 u0 K! r, I' _Coefficient of determination, 决定系数) N- y0 Y! g9 A8 q% q
Coefficient of multiple correlation, 多重相关系数
* E2 Y( r+ C) I0 b7 i2 wCoefficient of partial correlation, 偏相关系数
/ p( } j( P/ n' M1 P# OCoefficient of production-moment correlation, 积差相关系数
+ m4 L+ e1 W7 W6 ^Coefficient of rank correlation, 等级相关系数
: X ~7 h) O! k% R; t5 e4 ACoefficient of regression, 回归系数3 w+ t' q% S& S* F0 g! l
Coefficient of skewness, 偏度系数
0 A4 a9 u; X q5 i# Z( {5 G7 J2 j9 jCoefficient of variation, 变异系数% e. C7 [& E& [( E6 I
Cohort study, 队列研究
: d$ X( @5 [, o, j2 }" g# {& CColumn, 列# l8 `, `* b3 \$ {0 B
Column effect, 列效应! M2 f! n! P0 Y; u4 z7 G
Column factor, 列因素" U7 j% x9 r" Z- e
Combination pool, 合并7 a% n7 ^# n/ J7 y1 z
Combinative table, 组合表
8 {; |0 ~' r% L3 c& Z" a: dCommon factor, 共性因子
" V2 l7 m2 @: u) w8 Z; ~Common regression coefficient, 公共回归系数
3 b5 i$ k0 @- l5 F: T2 Y/ pCommon value, 共同值
2 h9 {8 p5 D) c0 uCommon variance, 公共方差
N/ `. m1 D( P b$ v2 ZCommon variation, 公共变异
! P `3 F2 i* M6 w! wCommunality variance, 共性方差4 N* i/ A* h# L+ F+ U9 [" r7 c t
Comparability, 可比性* ?8 B7 I7 R6 q5 g4 n# m
Comparison of bathes, 批比较
/ G, l8 g. ^# _4 Z" a c: YComparison value, 比较值
0 c# z$ U$ ~* p. n% |Compartment model, 分部模型: W4 Y! G/ Q4 Q* a% r) [& L
Compassion, 伸缩
6 E5 E' s: [0 A' S+ K& o) }5 ~Complement of an event, 补事件5 `, v& Z9 v* a* l7 W
Complete association, 完全正相关
; K# P; @! P; M( |& ~- v6 KComplete dissociation, 完全不相关
+ q; o2 i# @9 [6 @, k- |, ZComplete statistics, 完备统计量
9 y& B; c3 G3 B6 R3 \Completely randomized design, 完全随机化设计3 d# H$ K7 x/ Y
Composite event, 联合事件8 C$ p r: g6 |) v7 N
Composite events, 复合事件" p' [) W' X5 { X; J
Concavity, 凹性
* T C- x7 W% J7 rConditional expectation, 条件期望
( \6 \- R& j5 |2 P' }Conditional likelihood, 条件似然
2 @9 S, B: c7 E9 YConditional probability, 条件概率( [+ ^% L+ p& m8 i
Conditionally linear, 依条件线性; h% O% H" |) V& P: l5 q d
Confidence interval, 置信区间6 T5 |6 J' G3 O- O4 o7 g8 |
Confidence limit, 置信限9 x2 D8 w- ?: K/ J7 Z# r: L2 S
Confidence lower limit, 置信下限
/ T" t8 W# M4 A5 F5 Q4 hConfidence upper limit, 置信上限9 F2 m* B& L0 X2 _
Confirmatory Factor Analysis , 验证性因子分析
$ E4 L* v' Z& WConfirmatory research, 证实性实验研究
0 F4 {4 y& o- i. ?2 o7 T$ KConfounding factor, 混杂因素5 o' w: k1 S% g6 R' j
Conjoint, 联合分析2 f) @' J0 g+ i. O( r& }6 b
Consistency, 相合性& r4 [/ D o/ G$ E; |$ A; G
Consistency check, 一致性检验
5 x* O* K1 a1 ^( y* i2 Z5 e1 v; IConsistent asymptotically normal estimate, 相合渐近正态估计 z2 K. {( G- D6 h- s0 S: u
Consistent estimate, 相合估计2 M+ N! G. h+ f' T8 |' f7 z
Constrained nonlinear regression, 受约束非线性回归+ S0 p# A: E; m: Y' C5 ^
Constraint, 约束
; ?9 M% C$ P/ ^: wContaminated distribution, 污染分布
4 e/ J6 b, ?% T) G! HContaminated Gausssian, 污染高斯分布
5 V! s |3 m0 l& L! e+ d) g; c7 IContaminated normal distribution, 污染正态分布
6 i/ u6 _$ Y- l, WContamination, 污染
, N4 J+ I; A( |* [Contamination model, 污染模型7 q1 X; z% {% Y" w
Contingency table, 列联表
& O! h" G% c& Q3 eContour, 边界线0 B! Y9 g# w% g1 t1 V" T! o
Contribution rate, 贡献率% N# s' ^7 O9 e- b. x. L
Control, 对照+ a4 H9 o" h, C! p2 q% j* @
Controlled experiments, 对照实验0 R/ v0 B o( T4 f7 C E
Conventional depth, 常规深度
5 B' g+ _# ~6 u3 P, \ E XConvolution, 卷积* N0 w. G: E5 Q4 C2 }1 A
Corrected factor, 校正因子 i% n2 V. R0 ]4 ^; u
Corrected mean, 校正均值
- Z: x' ]: H' |( H" O, d' UCorrection coefficient, 校正系数
" n3 w G3 ^. x/ `9 X& z! WCorrectness, 正确性) ~" r9 v1 _1 e: u7 Q4 V( ~: B. e( M5 _
Correlation coefficient, 相关系数4 L. z% u5 v0 G2 V. U$ p4 a4 W. h
Correlation index, 相关指数/ {* c) d1 w- L& Y& o: T
Correspondence, 对应
+ O* S2 C. L* _Counting, 计数 k/ P/ S3 f. l1 [* L
Counts, 计数/频数
_ q0 [0 Y7 b( uCovariance, 协方差
" H% c# I7 \1 F: MCovariant, 共变 , V' p. W; }# {/ o- b
Cox Regression, Cox回归 ~) x6 `5 [ v1 l! { ^4 z
Criteria for fitting, 拟合准则
" k. B- D8 Y5 X, SCriteria of least squares, 最小二乘准则; T; u0 _/ U+ N# ?' m) b0 _& ~- z3 N2 Y
Critical ratio, 临界比
* r( H- K* t9 t4 i- wCritical region, 拒绝域' v; e' \' w$ b7 t& b0 j$ ~
Critical value, 临界值
3 N! F3 C, {. n7 U. vCross-over design, 交叉设计
9 n2 ?+ e. j" N* e+ qCross-section analysis, 横断面分析
x$ ]4 q D- q3 o" K. M/ r. c# ZCross-section survey, 横断面调查. c! I& B: ]$ d: H
Crosstabs , 交叉表 6 Y! E+ M5 d" W! Q8 Z
Cross-tabulation table, 复合表
+ `# J, G% C( r" c9 YCube root, 立方根
! s7 o* e/ d( J' W7 {Cumulative distribution function, 分布函数) o& \; o. D3 i# Q
Cumulative probability, 累计概率& x3 s# J/ ?+ c7 R3 [+ F v
Curvature, 曲率/弯曲# F& o$ t& _* t8 `& g
Curvature, 曲率7 w `, i5 ~( i, J* M4 F
Curve fit , 曲线拟和 ' ^& Z4 Z' |- j+ s# T7 Q2 ^ ^3 |1 E
Curve fitting, 曲线拟合
4 W: W+ O a4 Z( QCurvilinear regression, 曲线回归
2 C0 F( j; _3 s6 K9 V5 R0 FCurvilinear relation, 曲线关系
, T7 X5 `* A. ?! L$ Z% E W* lCut-and-try method, 尝试法 y3 h, ]) n# T5 s* L' S
Cycle, 周期
5 {9 W5 j* f' ]( x% I6 VCyclist, 周期性
+ v+ I" `1 @0 n1 O3 xD test, D检验
5 n' _' n9 X. IData acquisition, 资料收集
' N+ N3 b5 i' K1 c3 N% DData bank, 数据库7 d" P6 Z3 E$ O2 S, }, f
Data capacity, 数据容量
" {8 m9 m* C1 Z2 \6 E. {Data deficiencies, 数据缺乏
; D# L- v) d7 HData handling, 数据处理7 v: V3 v4 Y* l. ]2 E5 U
Data manipulation, 数据处理: C8 n R! r; Y W0 \* Q5 O
Data processing, 数据处理4 m, o; F5 `8 ?3 B% l
Data reduction, 数据缩减
" r8 P* ~1 p4 Y+ C, T, }2 ~$ s9 rData set, 数据集
1 i# `3 F7 w: D( SData sources, 数据来源2 J) r W' m0 M8 T5 A! c
Data transformation, 数据变换; G" H% Z H1 f
Data validity, 数据有效性
+ u9 q1 B$ O' S h- r xData-in, 数据输入1 Z9 l; C) S4 c, E8 } S$ D8 Q! T0 }; o
Data-out, 数据输出
* P0 ^, v, ~7 S1 W, r! H6 y* ? EDead time, 停滞期
6 q$ j5 q4 ?; h h$ wDegree of freedom, 自由度
# r3 T0 O' j3 I% G$ [3 l/ fDegree of precision, 精密度7 e3 q2 B# i5 y
Degree of reliability, 可靠性程度- U! _* C5 o" }% Y& c( b6 h
Degression, 递减
+ n7 x6 H. u5 jDensity function, 密度函数9 g/ [' F: e9 Q2 e9 A
Density of data points, 数据点的密度# e. ~" D1 w! |+ N% _+ c
Dependent variable, 应变量/依变量/因变量; T6 k- l0 m) K+ @5 f
Dependent variable, 因变量: Z" d3 @6 V- x) ~3 {% A4 H; {
Depth, 深度; `" |4 F! E9 k( U% D! o" `
Derivative matrix, 导数矩阵/ ~# G- f! ~! l3 e# t- O1 ]
Derivative-free methods, 无导数方法: H1 _$ X( K% P8 {+ `
Design, 设计
1 R: L' S, D- V* pDeterminacy, 确定性
{5 W; d! l, f/ T0 Y* G4 l9 ODeterminant, 行列式
! O) b$ f" Q. T6 }8 z7 wDeterminant, 决定因素
9 ?( y7 M4 L4 h% N' jDeviation, 离差
3 g6 P* f' ~4 G" T3 F2 g! VDeviation from average, 离均差
. c/ q5 z) Y7 L" S+ Y) p3 [& ]4 _Diagnostic plot, 诊断图8 G) P1 n+ C* {
Dichotomous variable, 二分变量
# h h( Q, R9 a' W+ dDifferential equation, 微分方程
) e' v1 C5 o3 e4 E2 N0 m. nDirect standardization, 直接标准化法
: t& d9 ] z6 T6 U% A8 Z8 P; oDiscrete variable, 离散型变量
' S" t2 l/ r& c' ZDISCRIMINANT, 判断 % J+ R. C* h6 w- `. c. f
Discriminant analysis, 判别分析/ a9 s" T7 R" ?3 n7 h/ q
Discriminant coefficient, 判别系数! Q; Y" p7 D. r3 g# A% w
Discriminant function, 判别值
$ Z- V! u6 `* d* Z& A6 \7 \Dispersion, 散布/分散度
: \7 X0 M; M/ D1 E8 K7 O; G- w5 ZDisproportional, 不成比例的
: f" K0 Y8 V0 W4 O- \* R! ^Disproportionate sub-class numbers, 不成比例次级组含量
4 ~7 X) z' Z; x/ |Distribution free, 分布无关性/免分布
& Y7 ]6 B8 v6 z( j! _4 m t8 B) vDistribution shape, 分布形状: a( L) ?" C+ B, y `
Distribution-free method, 任意分布法5 j4 p8 n* m3 j3 ]# {5 \
Distributive laws, 分配律
: k# I2 p, S+ O: g9 Z8 J: a2 f/ aDisturbance, 随机扰动项+ ^+ f4 ~5 `- k+ b
Dose response curve, 剂量反应曲线
4 ]$ ?, N" o. P- Y/ tDouble blind method, 双盲法; ]4 e' E" a, U- s% u" x
Double blind trial, 双盲试验5 g$ q8 ~' v! J( H
Double exponential distribution, 双指数分布# u1 C1 p. Y+ E6 v' D# ^
Double logarithmic, 双对数, r8 _* |2 z7 ~
Downward rank, 降秩
" I5 [/ `( y+ M [Dual-space plot, 对偶空间图
, C; k- d8 y' c, f0 EDUD, 无导数方法- Q2 b, S5 e! G. `
Duncan's new multiple range method, 新复极差法/Duncan新法. l, m5 X2 f. e1 r3 v0 {
Effect, 实验效应$ \( l2 K) @9 c
Eigenvalue, 特征值, F6 H" \4 K D3 c6 P
Eigenvector, 特征向量
! B$ y5 U1 `* P+ C. K6 tEllipse, 椭圆
5 T& P# Z$ S0 F* }( j0 I" lEmpirical distribution, 经验分布' O! c* q' j+ m6 }: a: z
Empirical probability, 经验概率单位9 m# k9 W/ N' a* u4 S% r, ~
Enumeration data, 计数资料 h* G0 T( E! y; Z! t z
Equal sun-class number, 相等次级组含量& _5 s: R4 N0 M7 b
Equally likely, 等可能
2 X" I% [3 P5 _9 W Z8 B1 f3 TEquivariance, 同变性
W- f& C4 z: w1 f$ W, m. c6 YError, 误差/错误, E$ A% w# j ~- H
Error of estimate, 估计误差
- d8 t+ T7 Q4 Q# m3 L9 E/ qError type I, 第一类错误
8 c3 f' P1 R/ ~# ?2 J# VError type II, 第二类错误3 l0 j8 Z8 z* a9 z
Estimand, 被估量. o6 V' T# i$ E h: L: o) Z4 V
Estimated error mean squares, 估计误差均方
% ~' X* W4 F4 ?3 }1 t/ NEstimated error sum of squares, 估计误差平方和+ i; X) m- ~2 O% j/ i" ~
Euclidean distance, 欧式距离5 H) U+ u# {4 U
Event, 事件5 r* a% n6 Q# f2 s* L0 P
Event, 事件
& I- b9 E1 g, Z5 [: xExceptional data point, 异常数据点4 T! d$ ^( v% s k& p9 {9 W
Expectation plane, 期望平面
. B; S+ P/ ^3 Y' Z% \" R3 B9 E' oExpectation surface, 期望曲面
- _. O. x* g6 K( f' J$ iExpected values, 期望值0 e4 R% }& \3 U! ~ Z5 y9 i! E6 y8 \
Experiment, 实验
% Q! O1 t& B6 Y2 }, U( v( K; W- _Experimental sampling, 试验抽样9 ~5 ?& R- c2 x; c: I" ?, L* N
Experimental unit, 试验单位% F/ {5 k" g& s y# ^+ ]; o
Explanatory variable, 说明变量7 D( G o- n; [1 h. D, W+ l
Exploratory data analysis, 探索性数据分析/ I; {) J+ W Z9 F4 ?/ b! g* u* U
Explore Summarize, 探索-摘要
/ f7 P) n$ V) p% ^Exponential curve, 指数曲线4 U1 P+ S% S4 T/ r
Exponential growth, 指数式增长9 L1 E0 ~- G U) u
EXSMOOTH, 指数平滑方法
0 y/ y2 t# j$ _' ~4 T# D: a+ e4 {Extended fit, 扩充拟合0 O, y2 X% x! Z
Extra parameter, 附加参数1 I$ h8 h5 O0 `) U
Extrapolation, 外推法- _. ~& `# ^9 A# m& Z; p" E) [
Extreme observation, 末端观测值
/ l6 y% B2 A. k* ~ C9 ^Extremes, 极端值/极值
! g; ~6 ~5 T6 Z1 QF distribution, F分布$ j# A) @4 n& }" C" k! o) ]
F test, F检验- h! ]2 a g0 I; g2 d4 n
Factor, 因素/因子
' u, a2 E+ j: c& KFactor analysis, 因子分析
0 ?& N+ ~) @- b) j% C' ~Factor Analysis, 因子分析
, Y1 L0 `5 r4 Q0 E5 cFactor score, 因子得分 4 L" w2 ]; K2 v# F, i
Factorial, 阶乘( ~$ y* ~: T' L& z3 z
Factorial design, 析因试验设计: G) c% I7 [' D( X* K
False negative, 假阴性' J- u8 ^' e3 Q& r
False negative error, 假阴性错误
5 I o8 ]- \6 x e6 kFamily of distributions, 分布族# k& M! ^3 m6 u' K7 N+ }' a5 O
Family of estimators, 估计量族) Z0 G R, C9 }% J0 P: ~4 e/ f
Fanning, 扇面
0 [# M. z! [' p* jFatality rate, 病死率3 h4 _/ e. r7 }7 g: b" f
Field investigation, 现场调查- r- z6 V, p8 q$ W$ P A
Field survey, 现场调查
3 W$ L) h$ A6 t4 D {: k+ Z# PFinite population, 有限总体% e* K, x7 ^3 O7 Z6 J# r
Finite-sample, 有限样本. c% L( t/ M. j2 |2 k
First derivative, 一阶导数( T9 y4 b' e7 {! E/ b" e; X# I5 V
First principal component, 第一主成分
# ^& X# [- I+ O$ g7 ^3 U4 TFirst quartile, 第一四分位数
6 M" j* S3 l# A/ e& m: m5 }5 g, vFisher information, 费雪信息量, f* H7 \6 x6 s
Fitted value, 拟合值
' F; X8 n/ c% [# k6 z( h- uFitting a curve, 曲线拟合
2 E' H0 ?: V+ y3 Z: b3 hFixed base, 定基
& ?. I9 N% ~6 z2 s- k0 E* oFluctuation, 随机起伏
$ r# P6 g& e6 T2 s$ G2 l3 Z xForecast, 预测
3 k& H6 e$ {7 F2 C4 K" w0 N% lFour fold table, 四格表2 Z5 b2 A) I& \; o) X M
Fourth, 四分点
p' _8 O6 W! X- mFraction blow, 左侧比率
5 i+ Y9 X! O, AFractional error, 相对误差' r1 }' Q' Q- u6 k4 i0 L$ o k
Frequency, 频率( x# ~. F# v3 Z6 F" p( j
Frequency polygon, 频数多边图" E* K; ~0 n; o, R8 M* o2 Z: F5 ]( J
Frontier point, 界限点
; z0 [: K9 {/ a) B8 p) xFunction relationship, 泛函关系
" H! k: ~( b3 {+ I5 iGamma distribution, 伽玛分布
1 y' Z: E* _, t, ^Gauss increment, 高斯增量* e- O+ Q6 b& m6 C
Gaussian distribution, 高斯分布/正态分布
5 o, [0 m. w% ^# I. D9 dGauss-Newton increment, 高斯-牛顿增量5 K8 Z9 J2 u5 H; |
General census, 全面普查5 v# M' H$ L* F' ?0 s
GENLOG (Generalized liner models), 广义线性模型 $ r# f2 @: B3 E) b$ b, F" K& U, b
Geometric mean, 几何平均数( o T0 Q% \( g! ~. N$ \
Gini's mean difference, 基尼均差
* e& q8 f) B8 ?' Z% ^1 ~GLM (General liner models), 一般线性模型 $ X+ `8 y D" E2 D# B# T
Goodness of fit, 拟和优度/配合度
# F9 U b' q$ ZGradient of determinant, 行列式的梯度
- e3 m! G" ?" g1 s5 h) YGraeco-Latin square, 希腊拉丁方
+ Q+ V; z X$ f9 ~, h$ ]' tGrand mean, 总均值6 @. \1 O9 t( I- W7 Y" ^( k3 H
Gross errors, 重大错误% F) U: O0 e9 k* R0 ~1 g, x
Gross-error sensitivity, 大错敏感度% W6 ]0 i. {! E. b
Group averages, 分组平均! ?: `7 p# F# k' m
Grouped data, 分组资料5 Q/ `) n; C3 T; l+ h
Guessed mean, 假定平均数! W6 L9 o9 e# W$ J7 N
Half-life, 半衰期
! F V0 L) M/ q; MHampel M-estimators, 汉佩尔M估计量" R* [( V/ x5 Y0 i1 S7 T @' V
Happenstance, 偶然事件% A" H4 H' w3 g, B' G
Harmonic mean, 调和均数0 @- P+ s* l8 q# f. m, V
Hazard function, 风险均数4 b4 s! |. {( o
Hazard rate, 风险率
9 \; A$ \3 e1 c# |# y" a9 CHeading, 标目 , B1 Q9 q; f* `% q
Heavy-tailed distribution, 重尾分布: k7 I6 v: H. ?* }1 `% _
Hessian array, 海森立体阵
, S( W3 p. r4 w: A4 [5 g, N3 @Heterogeneity, 不同质
0 g9 v9 |" L/ L. F" R! t$ zHeterogeneity of variance, 方差不齐 * |5 I; T6 T8 x
Hierarchical classification, 组内分组
, k6 C# b3 q. _" a+ m" xHierarchical clustering method, 系统聚类法
& F$ y+ E$ v: B9 @0 g H. vHigh-leverage point, 高杠杆率点/ p7 `6 a% S7 H2 F5 F) `4 {% H% |
HILOGLINEAR, 多维列联表的层次对数线性模型
5 L( s; X$ Y0 l0 _, sHinge, 折叶点
# i% M5 C |+ d: c( r1 F( a7 R" C7 P& kHistogram, 直方图& J. E% d' B- F* B1 {/ q& s
Historical cohort study, 历史性队列研究
3 O- ~1 Z* h" V1 X6 HHoles, 空洞, w4 ?$ ^7 H/ W5 N/ J
HOMALS, 多重响应分析
* _, V$ N' X, y: ?Homogeneity of variance, 方差齐性
7 l, `: ?" i) s- H4 QHomogeneity test, 齐性检验
" c9 }6 P7 L' j0 NHuber M-estimators, 休伯M估计量
. M) i9 [4 l, t& L' [Hyperbola, 双曲线1 V& h. Q, l3 e( i0 ~
Hypothesis testing, 假设检验. G+ D+ u- z0 q
Hypothetical universe, 假设总体
' Y4 _: D- i5 A& e1 L5 {0 q% kImpossible event, 不可能事件; O, e4 d1 Z: q; x8 z: p
Independence, 独立性
9 U& l! p3 p4 z: t. WIndependent variable, 自变量* P$ \' {) D4 Y c
Index, 指标/指数7 z6 q" V( _* P/ P* w3 {! p
Indirect standardization, 间接标准化法5 C7 o* X* h; B, p( p G# y) E
Individual, 个体
/ m: w: z" r+ x/ WInference band, 推断带4 d S5 a" A5 Q& A- \9 h
Infinite population, 无限总体
' n; p* @2 A9 p; Y0 DInfinitely great, 无穷大8 |3 O, A$ F. Z0 j% J8 t
Infinitely small, 无穷小
! ?2 d; \9 ] r& a% [ E1 ]8 tInfluence curve, 影响曲线 V+ i+ u% R' J) d
Information capacity, 信息容量2 T& e, A$ [! O/ e3 N7 B p+ g
Initial condition, 初始条件+ D7 X# ~, z/ W$ D: a9 Q4 z
Initial estimate, 初始估计值
! [. B% }/ _) w# ]) j! hInitial level, 最初水平
2 w) b) P5 L# PInteraction, 交互作用) I0 H7 K8 h* K; W
Interaction terms, 交互作用项% j+ j& ?0 [' \; e' X. W! u
Intercept, 截距7 U4 i$ n: _: {) G8 ]
Interpolation, 内插法0 C3 i1 M* |- w8 x5 }, g3 |
Interquartile range, 四分位距' _0 A P6 Q; p
Interval estimation, 区间估计) d! ]# Y3 u( v0 x/ ?7 {. u
Intervals of equal probability, 等概率区间
4 Z' G' x. \- HIntrinsic curvature, 固有曲率
" K* }9 d3 `& E; k5 _Invariance, 不变性
9 J6 [* P5 @, R3 `* n2 y* G! Y# cInverse matrix, 逆矩阵
! F+ O+ u5 e xInverse probability, 逆概率
: K' G8 \. o4 f7 d3 Z; VInverse sine transformation, 反正弦变换
, z' p! U* j$ G: m) {Iteration, 迭代
/ m9 z0 c+ b$ W$ T& d2 C/ sJacobian determinant, 雅可比行列式
0 u) U. W) \! `0 u2 |! W4 ]Joint distribution function, 分布函数
. z7 e" W( z) x1 [7 UJoint probability, 联合概率
$ J# S+ _4 S0 C" X7 }8 a- \Joint probability distribution, 联合概率分布+ x0 D) @2 W6 M, w$ {- c7 E+ `, D
K means method, 逐步聚类法/ Y2 z0 e( ?5 a, b9 O
Kaplan-Meier, 评估事件的时间长度 " L S* q$ }/ F9 ]
Kaplan-Merier chart, Kaplan-Merier图
" A7 L5 ]7 ?0 i* c OKendall's rank correlation, Kendall等级相关
: E5 u3 ~" O( w. rKinetic, 动力学2 D6 z( V) e5 W' i, g+ A4 T
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验7 n- y( N0 g: f/ U
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验0 i( N5 O1 i e' |) m" y8 ?/ `
Kurtosis, 峰度
p+ ~# |$ p3 m; gLack of fit, 失拟: ?/ ]$ D" a t: l1 o% d! l
Ladder of powers, 幂阶梯9 `) v6 p$ I8 M. J
Lag, 滞后
) ?/ E9 r( E; @9 a2 U6 r7 m8 GLarge sample, 大样本; F3 @; }/ V0 y5 a' v
Large sample test, 大样本检验' ]: Q& d5 E) Q. q0 Q
Latin square, 拉丁方! D2 f( b4 N) _5 K% @+ \5 f4 R
Latin square design, 拉丁方设计* _, {& v8 X1 B6 k& E6 [3 K8 @
Leakage, 泄漏) b m5 W8 g. f7 N7 Z9 V
Least favorable configuration, 最不利构形( j; ^0 I! L: R8 {
Least favorable distribution, 最不利分布4 @0 }, C7 n9 T. T
Least significant difference, 最小显著差法
0 @) k2 ~, V! l# TLeast square method, 最小二乘法# |9 n3 A7 R( ^" Y, K
Least-absolute-residuals estimates, 最小绝对残差估计
& B1 B; m3 h* u0 O; @Least-absolute-residuals fit, 最小绝对残差拟合
$ e5 b2 z+ e& e/ u) j5 s* FLeast-absolute-residuals line, 最小绝对残差线- c0 x' Z& n! Y3 k5 [$ _. [
Legend, 图例+ C9 t% q4 k5 F' R
L-estimator, L估计量
6 R0 `8 o: x! y, c9 d" C' O8 \6 z4 l; mL-estimator of location, 位置L估计量- o, M5 W% Y% r5 t4 S5 @
L-estimator of scale, 尺度L估计量
3 J+ W6 H- z8 A6 z9 s* MLevel, 水平
* k0 a& M R( i! ELife expectance, 预期期望寿命
c/ g' q5 R% r8 E# q* ?; L3 g5 KLife table, 寿命表' R' } I: B6 M; r- X
Life table method, 生命表法2 \5 S( m/ N: W7 x3 i" L/ y' d
Light-tailed distribution, 轻尾分布
+ r; a) j& {" V% G. oLikelihood function, 似然函数
( _2 T+ X* W/ Z" q: A d( cLikelihood ratio, 似然比
! a$ G3 ~, U, r* d( |1 |- Yline graph, 线图
( y8 |- n( `' {+ Q7 fLinear correlation, 直线相关: Z, R3 B. b% k. n7 D, z5 u) ~
Linear equation, 线性方程1 |1 A& D; f5 f4 } |) L) L
Linear programming, 线性规划
4 V1 A) _; `! b& jLinear regression, 直线回归- } H8 x2 p& J& C
Linear Regression, 线性回归/ w* i5 w! M! @
Linear trend, 线性趋势. l8 |; n; Z. U4 ^ {5 p
Loading, 载荷
6 n2 @ b2 Z `& Y7 Y3 ?9 }Location and scale equivariance, 位置尺度同变性! Q d1 m) |5 Q9 G c9 }& F/ E5 e2 j1 m
Location equivariance, 位置同变性
8 |" u, Y% V& X: F. }( DLocation invariance, 位置不变性
5 \, j% O& J6 G( i) Z; yLocation scale family, 位置尺度族# V2 `; A# V8 S: s
Log rank test, 时序检验
/ b$ S; v/ N- E6 X$ s5 SLogarithmic curve, 对数曲线/ P0 h* o# q/ F
Logarithmic normal distribution, 对数正态分布
5 ?) T: W5 } o+ xLogarithmic scale, 对数尺度- ?! {/ I, n r2 m1 k* b4 W: a$ _9 ]
Logarithmic transformation, 对数变换
9 X% z4 o1 L+ O% C4 D" [4 XLogic check, 逻辑检查
9 i+ _6 I. n8 t% M0 N; ULogistic distribution, 逻辑斯特分布0 N: x! h3 @& V. W! X' A9 x f
Logit transformation, Logit转换6 Z- Z4 g4 W& R4 `9 F0 I8 ?
LOGLINEAR, 多维列联表通用模型 4 |; @6 _" D2 U# ?/ I& u+ M3 x
Lognormal distribution, 对数正态分布
. C' V2 Z$ J& y& J/ C+ ^Lost function, 损失函数& k8 x3 E/ Q; e+ A0 i$ M% k1 X
Low correlation, 低度相关0 M( ~0 h2 o t H
Lower limit, 下限3 m9 |( ]. _* O4 g! i
Lowest-attained variance, 最小可达方差" r! n* J9 r9 I# Z
LSD, 最小显著差法的简称
8 ]+ c3 `' R3 D# G# C3 CLurking variable, 潜在变量 h; |1 w0 n9 \6 v% U' }
Main effect, 主效应
7 V9 X. Z# F+ X+ n# k( z0 NMajor heading, 主辞标目7 G6 U3 w' _3 N
Marginal density function, 边缘密度函数) s; T1 K( t; g: [+ m) N. A6 Z
Marginal probability, 边缘概率# T/ a1 i2 y5 I: T. o& P. O' {
Marginal probability distribution, 边缘概率分布+ B8 l: Z7 p/ \% G, p2 j
Matched data, 配对资料
9 i' ]' m* l6 c& _. D9 ?7 V" d2 YMatched distribution, 匹配过分布
1 D% r1 y/ k$ q8 j+ b9 _3 p$ `Matching of distribution, 分布的匹配7 V, o& C2 \0 ^# v/ e
Matching of transformation, 变换的匹配
2 H6 `( [# e( b" X- I7 {Mathematical expectation, 数学期望
\! A! J9 q% AMathematical model, 数学模型6 Q' F9 c% h+ I. s F* B% J
Maximum L-estimator, 极大极小L 估计量, D6 c! E2 r& ^- k3 A
Maximum likelihood method, 最大似然法
% w5 f; P6 t6 ~3 V9 |Mean, 均数
+ U: M' R6 B* S/ n4 f* j) a. rMean squares between groups, 组间均方
9 D7 D( _6 ]7 ~ u8 t9 p" cMean squares within group, 组内均方
4 o( R9 a; S! EMeans (Compare means), 均值-均值比较5 B2 [+ B6 a( v8 } U: a* k
Median, 中位数
r' V1 N: f& m: ~/ q" t3 k+ _1 GMedian effective dose, 半数效量/ W' P- B8 \. ?" x
Median lethal dose, 半数致死量0 |; F* l5 T0 F) x" u0 m
Median polish, 中位数平滑
! {9 M# T6 i% wMedian test, 中位数检验: H. J6 ? y$ r6 Z$ O' a7 Y
Minimal sufficient statistic, 最小充分统计量
" `0 N+ A& e$ S: z% R* r, bMinimum distance estimation, 最小距离估计
: O& i7 t6 Z" e; V6 TMinimum effective dose, 最小有效量
* M D7 }. p; M/ T9 ^, u$ }Minimum lethal dose, 最小致死量
- i B9 n8 Z/ X! }9 s" }Minimum variance estimator, 最小方差估计量+ W. E, ~9 C. M, t3 F% _6 s# M
MINITAB, 统计软件包
# {2 C, N1 c J+ @8 i! f t! F3 K0 H% oMinor heading, 宾词标目
7 R3 P& E, {, CMissing data, 缺失值
- K5 n* w# i ~7 f, i0 `# SModel specification, 模型的确定
6 c& Q3 E" V+ ~8 |) `Modeling Statistics , 模型统计% N* z4 L$ d" ~4 G* A( n9 t0 x( r0 ~
Models for outliers, 离群值模型
. n$ f% x" [/ D& d: OModifying the model, 模型的修正" ]! N6 C: N7 j$ _0 `5 Z7 A8 \
Modulus of continuity, 连续性模
8 u: o( \, b1 ^7 TMorbidity, 发病率 3 N8 D: | r7 d! `
Most favorable configuration, 最有利构形
2 J0 x' @6 u; {$ F3 J! W; F- r5 dMultidimensional Scaling (ASCAL), 多维尺度/多维标度
; z* \( j; s5 }* IMultinomial Logistic Regression , 多项逻辑斯蒂回归
/ U5 G( F$ u( Y' Y9 G- ?Multiple comparison, 多重比较8 f; `8 v/ ]. x: t* f7 f
Multiple correlation , 复相关2 Q5 n u* k) w- Y: H) d: N
Multiple covariance, 多元协方差, V- L! Y) U9 n! n2 {( X
Multiple linear regression, 多元线性回归
: L$ e4 v6 M$ R$ H% ]$ L& FMultiple response , 多重选项0 ~5 O7 G. _( v1 H) ]5 r
Multiple solutions, 多解% ]8 s7 T W( x8 [, x2 C
Multiplication theorem, 乘法定理9 I3 v* I: E) b
Multiresponse, 多元响应4 ]" U" s% B$ L2 u
Multi-stage sampling, 多阶段抽样
5 m# R' Q. r/ K0 z6 y+ dMultivariate T distribution, 多元T分布1 T7 j" E9 A6 e4 f
Mutual exclusive, 互不相容) u' H8 H5 P# P5 X/ G/ A1 e& F
Mutual independence, 互相独立- ? h1 A, g: B0 W) \: z
Natural boundary, 自然边界
3 ^) ?6 }2 s! b+ N6 QNatural dead, 自然死亡
3 G. w3 K Q8 U1 Y) F5 G! yNatural zero, 自然零
. U7 {4 n' c: B1 z( c sNegative correlation, 负相关, i- O7 e( x( G; a
Negative linear correlation, 负线性相关
: B+ n- J- G2 `Negatively skewed, 负偏
( u" f/ f9 l! p* l* R4 O( s) TNewman-Keuls method, q检验9 [ J4 [8 N) K4 H
NK method, q检验
9 m C6 s p$ r' V/ WNo statistical significance, 无统计意义
$ r) d" u0 n# U2 sNominal variable, 名义变量
; o4 I+ N, ?4 T; E5 A9 ]" ]( KNonconstancy of variability, 变异的非定常性
$ E5 V0 p: _" _5 p' b; n' L( w9 iNonlinear regression, 非线性相关3 a+ w2 T o' w8 Z9 u3 o+ w1 f
Nonparametric statistics, 非参数统计
- W0 z6 A3 E: X5 V& dNonparametric test, 非参数检验
' c0 {" _; D/ W% M2 Z' R0 |; g4 a% t- KNonparametric tests, 非参数检验: D% ^0 B4 p) ?: B8 l
Normal deviate, 正态离差
1 \( I0 O: ?. M# F3 `Normal distribution, 正态分布5 Y8 [6 O2 Y0 V7 M6 V$ R" [ E
Normal equation, 正规方程组
) m: j1 z+ ?7 l# e* a; uNormal ranges, 正常范围& q- Z4 M) J+ X! k, t* F
Normal value, 正常值9 L9 _; b& B% v" f% |
Nuisance parameter, 多余参数/讨厌参数
J3 e( `8 V2 u2 B$ i, WNull hypothesis, 无效假设 1 \- e; y. O4 Z7 K3 K3 a9 I
Numerical variable, 数值变量 m, l" X H9 g+ z4 o L
Objective function, 目标函数, k# X) j( `2 E! v7 }3 W
Observation unit, 观察单位
/ s0 ^$ b" {# g# yObserved value, 观察值
8 ]) k% C$ O! w/ }! UOne sided test, 单侧检验3 U! G# l9 z8 V! W( m
One-way analysis of variance, 单因素方差分析
7 p/ P) I5 T) _7 KOneway ANOVA , 单因素方差分析
3 M) F+ c1 J0 A! }4 A$ B( zOpen sequential trial, 开放型序贯设计% ?/ D: T" N) s! i; |( k# X) s" p
Optrim, 优切尾
) _6 s7 N% u* _" r7 X- [7 e# _Optrim efficiency, 优切尾效率
) g+ a, o( k: ]/ o3 A YOrder statistics, 顺序统计量; M) y3 W5 v. j6 y9 V: Q) {; t: T# O
Ordered categories, 有序分类& w8 V! C4 Y# `' B
Ordinal logistic regression , 序数逻辑斯蒂回归 q. d$ h5 f- e' a) k! }. U: D
Ordinal variable, 有序变量
- c" a3 z K- f- q- i2 Y% hOrthogonal basis, 正交基
+ A5 o- F' i3 [- B4 V# d9 d- b UOrthogonal design, 正交试验设计4 X! M+ m; B( u. |
Orthogonality conditions, 正交条件2 m6 G6 Y6 _) Y( r. |% A$ l6 ~" {9 G5 Z# U
ORTHOPLAN, 正交设计
5 D( }9 ^6 g JOutlier cutoffs, 离群值截断点2 a# r+ h7 x8 \& v1 v( z8 P
Outliers, 极端值
& D6 p7 _) o* n" a5 |OVERALS , 多组变量的非线性正规相关 : h+ W" E2 a, D9 ~! e( A! I- U+ e( \
Overshoot, 迭代过度9 C p, u* ?, W# k# ]3 |. Q
Paired design, 配对设计
& b/ |% M7 b% N2 q1 {4 JPaired sample, 配对样本
) X; ~$ E5 v5 R2 [. }Pairwise slopes, 成对斜率0 Q4 T* }4 Z/ s m
Parabola, 抛物线- _+ q+ I( `0 P% @0 `
Parallel tests, 平行试验9 h& X* F6 t7 M* W& u
Parameter, 参数5 n" P a6 ~; s+ s4 A; J* f( B9 h
Parametric statistics, 参数统计
6 @! v0 O/ @7 g% hParametric test, 参数检验& e9 n( F% l! A7 k! A d
Partial correlation, 偏相关0 m4 ~- D; U* j; o( m: A" b9 Y
Partial regression, 偏回归
: E& v+ l/ m' ^+ fPartial sorting, 偏排序
5 M) _; g+ I" d \7 @. J# H" uPartials residuals, 偏残差
$ j% q. t. {' T+ G( I3 x1 g0 K3 sPattern, 模式
8 o* z! v' l8 ^" q N, qPearson curves, 皮尔逊曲线
9 x1 c% c' W5 f3 h* w2 I: ?Peeling, 退层5 Y& z ~+ v7 M0 H/ m
Percent bar graph, 百分条形图
0 w' V+ T o' BPercentage, 百分比
U" L, T9 m( ZPercentile, 百分位数
" f9 \6 n3 @( O7 v% T1 @4 tPercentile curves, 百分位曲线
' l5 Y3 s6 z* r: m# A* v- j6 N! }Periodicity, 周期性! n; n9 I' ?; u5 \1 `
Permutation, 排列
( [8 r3 y) w( {* G3 x2 H& i. qP-estimator, P估计量6 y! G# U# |$ H* w
Pie graph, 饼图2 c2 b* P: b7 J- |2 n9 G8 i
Pitman estimator, 皮特曼估计量
4 c5 h1 [. C, c# D# z- u" uPivot, 枢轴量& y) T4 [: F9 B
Planar, 平坦# t- R6 k8 X( J: o5 ]0 e6 P( B
Planar assumption, 平面的假设. l1 M. r9 v) o. ?% s3 t% b
PLANCARDS, 生成试验的计划卡( Z4 F$ ^. S( p4 b+ J2 ]3 w
Point estimation, 点估计. i* x+ q [5 Q( H( o+ j3 X
Poisson distribution, 泊松分布4 w, Z: @0 H# H5 n |
Polishing, 平滑6 m$ o+ _8 |7 h9 J- v
Polled standard deviation, 合并标准差
/ Q6 ~% V0 d# V( ^( }Polled variance, 合并方差
2 H% o6 D. j- DPolygon, 多边图
+ }% t. d. k& w: X* c7 RPolynomial, 多项式
7 h: P9 J+ h6 X* y' A, L, a2 MPolynomial curve, 多项式曲线% ~' P7 s1 r( C- n# h8 y
Population, 总体
" k; Y9 { i( {8 fPopulation attributable risk, 人群归因危险度% }* c1 x, ^. i- T
Positive correlation, 正相关7 Z1 m, [# h( j& w
Positively skewed, 正偏- w5 s" b) z S! F4 T, ^3 H
Posterior distribution, 后验分布4 {! J( M8 H. c" ]5 P
Power of a test, 检验效能3 k# m' M5 R9 I- E S7 z! k7 C
Precision, 精密度1 a/ z; y* L: W8 k
Predicted value, 预测值9 M( ~& A) H' k; m4 D% D
Preliminary analysis, 预备性分析- U( r5 }1 \; W& F/ o
Principal component analysis, 主成分分析
4 q. X2 u. j/ G2 ]5 tPrior distribution, 先验分布( m/ {. f; l$ `! q/ b9 k: r
Prior probability, 先验概率
* y+ Q" O+ e4 \7 n/ o8 U0 C! hProbabilistic model, 概率模型
* A4 N# t8 m; _3 I% k5 r$ ]% g# D2 qprobability, 概率
* M; l" C8 y8 DProbability density, 概率密度
6 F) |# ~( t2 W- T8 ZProduct moment, 乘积矩/协方差2 D: L2 O+ ~* g
Profile trace, 截面迹图% f5 I. N) E3 ]1 u+ M h
Proportion, 比/构成比
0 O+ I- B, F" X2 fProportion allocation in stratified random sampling, 按比例分层随机抽样
# v' i4 [, P8 ?1 Q0 {. b0 F& @! XProportionate, 成比例
% H" ~: |6 ~ m% K6 K+ B5 c' sProportionate sub-class numbers, 成比例次级组含量
+ a8 a' |( ^( cProspective study, 前瞻性调查
) u' I5 Y L0 W7 q* ~3 b6 oProximities, 亲近性 - W. z8 ^! u6 C, d1 a: K+ i7 ?
Pseudo F test, 近似F检验
# N( j. }& F$ D4 Q. cPseudo model, 近似模型
+ N2 ~1 K9 C+ x8 e9 r( Z+ _Pseudosigma, 伪标准差5 L" q- q! M; U5 H; C: z3 z
Purposive sampling, 有目的抽样: g" u" n1 T7 F1 w: U$ k
QR decomposition, QR分解' a9 s. [. |4 z* J8 u
Quadratic approximation, 二次近似
) x# ?" f' x# J! W6 SQualitative classification, 属性分类3 n$ S! E9 U; c" c% }4 y8 `2 j
Qualitative method, 定性方法
8 \% g" Q" `9 U" c, a5 ZQuantile-quantile plot, 分位数-分位数图/Q-Q图0 f6 u+ S) T7 W$ N# C
Quantitative analysis, 定量分析
: p2 ]3 B# Y- p7 n) s& \+ YQuartile, 四分位数
% ~( r3 l R$ T7 L$ {- XQuick Cluster, 快速聚类
( I+ z' @) ? }Radix sort, 基数排序
0 v5 f3 a3 A$ tRandom allocation, 随机化分组! `" T+ B9 A. a/ G6 H3 F6 _
Random blocks design, 随机区组设计
! s! z6 @% H! v3 [2 o1 FRandom event, 随机事件7 X& b4 N M& g2 _
Randomization, 随机化
& j: K9 C8 t( G. a( nRange, 极差/全距# B8 A: @& o$ k, ] D
Rank correlation, 等级相关) J+ a* K5 }+ y
Rank sum test, 秩和检验
! b; G! h7 F. g; \Rank test, 秩检验
" v" l4 E& D S1 B- ZRanked data, 等级资料
8 j. ^! ^! B/ fRate, 比率. I% G7 s0 }3 `" Z
Ratio, 比例
' B2 Z3 w" w3 LRaw data, 原始资料/ [9 y% d; \6 T" X$ s3 N) m3 l% s
Raw residual, 原始残差
8 G2 m; d& a2 `, y" D! |- ARayleigh's test, 雷氏检验
6 K$ L ?/ G, m7 _" {Rayleigh's Z, 雷氏Z值
9 U6 i2 W( M( l; q" A& e; kReciprocal, 倒数# T% @/ a5 |- x! L- L! V
Reciprocal transformation, 倒数变换
5 C1 u3 g5 C% w/ o5 L4 eRecording, 记录
8 q3 q5 e0 ]: K: d# w% B( ?8 BRedescending estimators, 回降估计量. Q* i& \, n6 Z9 E' N( L
Reducing dimensions, 降维
3 _' q, M& c% y, i6 ?) d+ g7 GRe-expression, 重新表达
/ [0 E& q6 Q F) Z" Z# aReference set, 标准组
2 H4 M6 C0 s5 |1 GRegion of acceptance, 接受域) C/ t/ }' p+ c/ X' x5 Q: @ G
Regression coefficient, 回归系数& M* j2 G! R3 m8 d7 U( Y( r
Regression sum of square, 回归平方和& g+ T0 n* e# W. Q' z8 s# b
Rejection point, 拒绝点
, L% w9 M, N) N, }. g FRelative dispersion, 相对离散度4 O' t8 l6 |! \0 _5 S% G0 ]
Relative number, 相对数" U4 @1 n$ n2 a# K$ y
Reliability, 可靠性
0 R: M8 m9 V$ o8 u4 \Reparametrization, 重新设置参数' h/ |3 s+ h6 M) [1 e, m
Replication, 重复
, s6 Q( g. C% u- a: [/ P4 FReport Summaries, 报告摘要
& }" m; M; G9 A1 a2 ]* P4 MResidual sum of square, 剩余平方和
1 n- |- S1 ?# [; G2 `' y5 }# tResistance, 耐抗性' a U: D7 H% p7 `7 d$ }, A
Resistant line, 耐抗线% u* a% _7 W" E9 l3 c
Resistant technique, 耐抗技术! a6 ^' X' O3 U# n6 u
R-estimator of location, 位置R估计量
( R0 v U+ n" [8 N; C9 l+ e" P7 XR-estimator of scale, 尺度R估计量- F( l, J* ~+ j) Q3 c
Retrospective study, 回顾性调查: E) y* g3 W: n3 n1 ~1 [& {
Ridge trace, 岭迹8 J4 ?+ U8 {0 C0 ?. W3 M4 y
Ridit analysis, Ridit分析/ ^. T2 Q( b9 |, u! }' w5 ?( t
Rotation, 旋转& k$ R* e0 [+ G0 ~- E! {! l
Rounding, 舍入+ D0 J: N! A+ f- r: s
Row, 行
0 B S% _0 R8 n" x7 A' bRow effects, 行效应4 u s3 U! i3 z, S. G* |3 v; X5 G
Row factor, 行因素) M5 y" [& u- V
RXC table, RXC表4 v" i$ P: D2 g! O
Sample, 样本
& R9 H% ^6 t: e. \# ySample regression coefficient, 样本回归系数9 e: G b+ d4 M" a
Sample size, 样本量
# i7 K8 x: G: c' Q' g4 N* S. i: \Sample standard deviation, 样本标准差* B2 C! ?" ]. t. i
Sampling error, 抽样误差
k0 \; \6 f9 w( ]" @ }% U; Z5 y0 n' mSAS(Statistical analysis system ), SAS统计软件包
" v: `/ x' O! q4 u/ ^( N N9 ZScale, 尺度/量表
4 j$ l5 |, q: Q$ O7 c) k( T) rScatter diagram, 散点图
, E1 N" Y+ G7 R+ P, ZSchematic plot, 示意图/简图7 p+ j2 w4 Y* J2 _
Score test, 计分检验
) V, Q% q8 O4 mScreening, 筛检$ @. _- {! U: C) e& w- {3 g; q
SEASON, 季节分析
3 l: g" H1 a$ I% x$ g; OSecond derivative, 二阶导数$ p8 b G" r2 k- g3 k
Second principal component, 第二主成分1 ]+ f& t& o6 N5 a2 ]
SEM (Structural equation modeling), 结构化方程模型 + L! }- }& f4 u9 \! H% V- L
Semi-logarithmic graph, 半对数图8 I; C: I- c+ x" D; V+ _! ^
Semi-logarithmic paper, 半对数格纸
$ J, _* T! ^; ASensitivity curve, 敏感度曲线, n% b5 e/ H- y: l. x2 ^- y
Sequential analysis, 贯序分析& I5 T4 o* M9 H4 ~5 y
Sequential data set, 顺序数据集, x. b$ f1 P; W! @. L: Z1 Y6 L" \
Sequential design, 贯序设计
. y2 i6 {! b1 W/ pSequential method, 贯序法0 g0 h$ p* E6 K. j8 i4 w( h( {, x! Q' Q9 {
Sequential test, 贯序检验法
& T' t4 y5 |% d: {# FSerial tests, 系列试验6 H6 f @! P& R
Short-cut method, 简捷法
+ u8 i+ F. K' A* tSigmoid curve, S形曲线
. c5 m6 \+ e4 J7 B; t& ZSign function, 正负号函数1 ?, y _' u; ^7 N: u( ]
Sign test, 符号检验
) p+ s+ X4 n. h) P k GSigned rank, 符号秩. \1 c1 n1 A8 c2 O
Significance test, 显著性检验
* E7 w( C. A+ s) ^- ISignificant figure, 有效数字2 N0 Z P( x. v4 @) T/ D
Simple cluster sampling, 简单整群抽样
2 m* N! \! V/ i5 B# Y& J; K" g% Q# FSimple correlation, 简单相关4 Q l; r: y9 F8 f3 A1 c. v# Q
Simple random sampling, 简单随机抽样
! C$ m1 N6 @# Z7 z1 Z5 ESimple regression, 简单回归* q1 ?' e, K2 ?+ t8 n0 m3 Y3 _
simple table, 简单表/ X; W1 X1 t# b- M) x, E
Sine estimator, 正弦估计量9 T2 z$ g$ D5 }& @: W: }
Single-valued estimate, 单值估计1 {" ? a) [7 t) H+ ?
Singular matrix, 奇异矩阵
. x7 o' D5 P. h0 OSkewed distribution, 偏斜分布) V" G( i7 t) x$ J) k
Skewness, 偏度 J% ` M/ ?- C4 K0 |5 T) C) a
Slash distribution, 斜线分布6 B! k: I8 A6 l- ?) j, t
Slope, 斜率
. c' r( s7 w8 M. F/ pSmirnov test, 斯米尔诺夫检验
4 V t4 M/ r7 O& k/ `9 P4 RSource of variation, 变异来源+ i# `7 G" T1 C5 l. V2 @7 b
Spearman rank correlation, 斯皮尔曼等级相关7 W9 l/ S- L) x3 w D% f- w
Specific factor, 特殊因子
" h0 B$ ?- P) j! i/ c( FSpecific factor variance, 特殊因子方差
: |: } ]2 W% bSpectra , 频谱- }! U% \; Y# X: _5 [/ I
Spherical distribution, 球型正态分布
' o# F* u! }/ `- z4 [7 t2 DSpread, 展布
# ~. {7 }6 ?3 @9 F( U3 D3 ~SPSS(Statistical package for the social science), SPSS统计软件包; M. J% F% C) X) x% K
Spurious correlation, 假性相关
+ c- [7 ?( E, v( SSquare root transformation, 平方根变换
( J; _' l: @) Q) u& YStabilizing variance, 稳定方差
7 ]) Y" X4 u5 P7 @$ Y# lStandard deviation, 标准差
. g/ ]5 g5 `& F% F. p [+ M; R" Q2 aStandard error, 标准误
+ @& [' \4 p( o( M' Y- jStandard error of difference, 差别的标准误 X. b) J+ o% ]1 q, S' k
Standard error of estimate, 标准估计误差
5 n: s+ \' Y& VStandard error of rate, 率的标准误
5 W( p! a' `0 A5 ~1 ` H' m- t) P l* EStandard normal distribution, 标准正态分布" K/ W# a. B0 \1 z6 o9 o
Standardization, 标准化
" E6 a' z m; p1 RStarting value, 起始值' B5 h: t8 i; t ]2 P$ R( l- ^
Statistic, 统计量: u0 E" T/ a/ [* p7 _
Statistical control, 统计控制
4 Q7 |6 y6 f2 P$ W5 f$ _; lStatistical graph, 统计图% K) C* G# H5 y$ k' ]
Statistical inference, 统计推断$ n5 v: s9 v$ S% \1 N, ~7 V
Statistical table, 统计表7 D$ ]+ }$ q: O% [. C6 P" r
Steepest descent, 最速下降法
W& U! h9 [% B9 D7 wStem and leaf display, 茎叶图
, r" G2 e/ Y1 [Step factor, 步长因子
) D/ S% u2 w5 B) [2 TStepwise regression, 逐步回归
& _. q6 u& m) R' v* c0 T3 R- TStorage, 存: P7 M8 p6 G! p$ {6 t+ |$ a$ I
Strata, 层（复数）3 S" f$ x* ?3 n; T7 f5 \
Stratified sampling, 分层抽样1 ~% N; w* L- o* H1 h" q& ?
Stratified sampling, 分层抽样: P9 u4 l& N( z C& {; V
Strength, 强度
c" Z K" r; `3 v+ H+ ]! ^( eStringency, 严密性) B& G, i2 c5 P
Structural relationship, 结构关系
0 ^6 a4 U. b5 b8 x0 C& fStudentized residual, 学生化残差/t化残差
/ \ I( K2 p& |( P. [Sub-class numbers, 次级组含量: m1 M1 a& A& g* L3 {# H
Subdividing, 分割
6 C3 o1 P1 T; P( x2 O& M7 ^Sufficient statistic, 充分统计量
2 p4 m: l+ B2 X. @1 o) TSum of products, 积和6 T; @0 e7 R8 Q$ ^* y7 L' B
Sum of squares, 离差平方和
- W! f7 B: {1 R) d dSum of squares about regression, 回归平方和& w7 @& W7 o2 a x: f a
Sum of squares between groups, 组间平方和% d# W+ P$ p$ P, r9 ~6 ?* n1 Q
Sum of squares of partial regression, 偏回归平方和+ s) d1 I, N% v# u
Sure event, 必然事件
/ ?- {# r7 |( K. o! v+ g- a, x$ xSurvey, 调查- s9 Z4 ?, C% q6 F
Survival, 生存分析2 _" e, C& w4 K- |
Survival rate, 生存率 a3 ]2 q: d" E; L4 E
Suspended root gram, 悬吊根图9 I5 o$ Z V* @1 P! ]* h
Symmetry, 对称, B! ~0 `+ A3 \8 Y/ k
Systematic error, 系统误差
$ p$ K$ a# |9 j2 D: x; `. ^1 QSystematic sampling, 系统抽样
4 t- c# q: n5 V& p( |Tags, 标签6 k' O$ [+ q0 `- j* j; A
Tail area, 尾部面积
. h0 Y5 R& M% @/ Z! T* |# W) z$ |Tail length, 尾长
& ^: ~" B2 A- P( U1 A$ S! KTail weight, 尾重
% [; x% L: L. T! \) D1 K/ nTangent line, 切线
! P# P/ J+ P6 \& N" s7 ^Target distribution, 目标分布
% l9 V% I6 Z$ ^7 Y. ~; N9 c/ MTaylor series, 泰勒级数
7 `- z- V, a2 O0 u- ^" ]Tendency of dispersion, 离散趋势+ b" c! L0 F9 ?4 w1 f* N
Testing of hypotheses, 假设检验% H% \' z `; A
Theoretical frequency, 理论频数# L( k/ y1 Y% ~: w
Time series, 时间序列
, O! O- e; E4 N7 g: d' wTolerance interval, 容忍区间
9 e; p- T, S: ?& N; r9 N! z$ NTolerance lower limit, 容忍下限
4 p$ f# r0 P; d+ zTolerance upper limit, 容忍上限, h" t9 o1 \9 z5 N. ~
Torsion, 扰率2 _, A5 y. `, z1 I R5 L$ M
Total sum of square, 总平方和7 ?' F( j V; C% W1 T
Total variation, 总变异
2 y% b( N$ M0 V/ E. j4 B: o* \Transformation, 转换) W' j4 `: u) a O- E
Treatment, 处理; P9 `1 O; f0 E$ T
Trend, 趋势
% w" @/ \& p) [Trend of percentage, 百分比趋势' x+ d& \3 o) t/ U
Trial, 试验0 }& F# W, m! l7 z
Trial and error method, 试错法
1 j5 q5 B) u: MTuning constant, 细调常数5 J$ L5 Y" ]# N1 ~7 D
Two sided test, 双向检验
: P H- X0 a3 o" V% i: dTwo-stage least squares, 二阶最小平方& a4 a# O# B1 r5 J5 s7 u
Two-stage sampling, 二阶段抽样
0 y( B, z8 w" K5 ?* j. ]* Q: R- STwo-tailed test, 双侧检验
0 y0 E/ F0 b7 Y+ K+ gTwo-way analysis of variance, 双因素方差分析/ K0 b% }% L/ t: V/ x
Two-way table, 双向表
_+ j: T4 k6 d5 z' p# dType I error, 一类错误/α错误
) M! y0 j2 R0 N' J% Y- B5 aType II error, 二类错误/β错误
B% {* P$ O) [. bUMVU, 方差一致最小无偏估计简称
1 @) a( u! J8 h i0 N2 Q/ UUnbiased estimate, 无偏估计9 P0 Q- n0 S5 _: U) ^
Unconstrained nonlinear regression , 无约束非线性回归
$ Z) A- I: r1 _/ kUnequal subclass number, 不等次级组含量
9 |" U% K! M) C$ mUngrouped data, 不分组资料
A' K$ s- j' t8 P6 |# |Uniform coordinate, 均匀坐标
# F8 s8 ]% k4 D! }! XUniform distribution, 均匀分布
; V7 M- W2 u2 ?/ R) _) mUniformly minimum variance unbiased estimate, 方差一致最小无偏估计) v/ x- b: X! u) |4 C4 g$ q6 Q4 e& N! V
Unit, 单元! ?% ?- w; z# ]3 ?3 R8 Y( K
Unordered categories, 无序分类
& @2 w, G" K5 sUpper limit, 上限' M% L, j- B3 d4 s6 x
Upward rank, 升秩
) X9 Z N1 U2 Z2 q$ ^8 \& b5 dVague concept, 模糊概念
7 W6 v4 x! h0 |+ _, WValidity, 有效性
" v2 W# S5 z9 x3 T/ H! L' v2 d' \VARCOMP (Variance component estimation), 方差元素估计2 A. z+ m: Q3 A8 Z7 | j
Variability, 变异性& l+ e9 f a9 r# y4 G
Variable, 变量
; X1 x; b& X* wVariance, 方差) o" x7 @ v6 p! k& D9 n) }0 S" g0 T
Variation, 变异
9 J) z* S# c B) p8 ]Varimax orthogonal rotation, 方差最大正交旋转) q$ N& g9 t) P! R
Volume of distribution, 容积' {" o3 b2 @8 j3 ?5 H
W test, W检验
`4 [( C2 a3 @. MWeibull distribution, 威布尔分布 x$ r% f# T8 b
Weight, 权数/ Y8 T3 ? g# P6 b. b
Weighted Chi-square test, 加权卡方检验/Cochran检验
' g+ \5 h7 c& |) \( y. P. bWeighted linear regression method, 加权直线回归
! x4 S+ N0 a# {$ x$ J/ q' d ]! rWeighted mean, 加权平均数
, b P @; y6 v- D- Q$ |$ hWeighted mean square, 加权平均方差
+ B& m; h9 ^) z! J7 WWeighted sum of square, 加权平方和; j3 R/ h ]7 t& t/ F j( Q
Weighting coefficient, 权重系数- Z$ O5 `8 y/ e% G
Weighting method, 加权法
7 ~& c$ n4 P1 u1 v, I2 T- TW-estimation, W估计量
( m1 v6 I5 q2 X; T d# D' NW-estimation of location, 位置W估计量
. m5 v: w- ~2 m1 L/ Q2 lWidth, 宽度: Y6 V* z: W- q' n3 g
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
$ H$ {0 I/ `3 d2 HWild point, 野点/狂点
, a' i! S0 y0 fWild value, 野值/狂值
/ c* [9 \/ F* Y& T: bWinsorized mean, 缩尾均值( g/ T% D/ f* W( J, I3 R7 O, o
Withdraw, 失访
$ D( ], \0 W. YYouden's index, 尤登指数
2 N- s4 k7 V C4 B3 n( OZ test, Z检验
5 k! V* ?( [1 d( Z2 dZero correlation, 零相关
( W$ h! c1 s! B0 {7 v% s" m% HZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
