|
|
Absolute deviation, 绝对离差
* e# s [7 ` Q' T [: y2 \; a7 TAbsolute number, 绝对数8 Z2 k7 }; O! O
Absolute residuals, 绝对残差
/ v' L3 ~$ e' V5 W& e: c$ sAcceleration array, 加速度立体阵
/ _- Y L" S6 LAcceleration in an arbitrary direction, 任意方向上的加速度) U; e! }( c' J# _! L$ b) t F
Acceleration normal, 法向加速度8 q& R9 {2 V7 o9 e% i2 i
Acceleration space dimension, 加速度空间的维数) w: \/ Z7 d# f4 l5 X5 w
Acceleration tangential, 切向加速度3 w& x* |) Y" P' J. V ]6 Y, i7 \
Acceleration vector, 加速度向量 Z4 w/ B% B7 I: p- U9 c
Acceptable hypothesis, 可接受假设" D9 k. S" z; p0 _7 ]; [7 e
Accumulation, 累积
E9 w% O% d) ^- _1 D. q+ QAccuracy, 准确度
3 n1 [' Z" D* G" x% @Actual frequency, 实际频数
1 e3 }! U7 v. f q& aAdaptive estimator, 自适应估计量
' i6 \( w- V: |; Q3 dAddition, 相加5 y# f9 O! g& k6 u: V
Addition theorem, 加法定理
* J0 A6 F3 { N4 n/ WAdditivity, 可加性
# ?/ h2 d& r% `0 \4 z$ f4 b' }7 AAdjusted rate, 调整率5 V. u0 e. |6 N) P2 o
Adjusted value, 校正值* M* M3 ~# |( e
Admissible error, 容许误差/ S7 o3 N0 t# K. u, |# d! s
Aggregation, 聚集性0 t$ \6 b1 Y! K& S2 C* E7 C
Alternative hypothesis, 备择假设/ }, F& i1 W. T2 {( k
Among groups, 组间
* H8 x( @# W* |- FAmounts, 总量7 r, H+ G0 j& D$ ~8 Z% f
Analysis of correlation, 相关分析
* q' n1 L5 T3 C& o% LAnalysis of covariance, 协方差分析0 C$ a" t5 h9 ]1 `" z q
Analysis of regression, 回归分析
" O$ N: F$ n) q# W; t! | Z4 LAnalysis of time series, 时间序列分析
' y8 o% k. A" U3 J, CAnalysis of variance, 方差分析
/ w8 j% P6 k+ G7 V7 Z9 L6 M& O; Q; \Angular transformation, 角转换 z. z S; {) j
ANOVA (analysis of variance), 方差分析
( @% Q O- H% O mANOVA Models, 方差分析模型
( G. O; V( R. Q0 z4 f3 z& ZArcing, 弧/弧旋* r8 T5 F) x! c- h9 w0 x
Arcsine transformation, 反正弦变换8 ?. _9 V" O$ f) x- ]
Area under the curve, 曲线面积1 e( u! [3 k3 f$ `% G& f
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 . _9 A' j; |. h, }
ARIMA, 季节和非季节性单变量模型的极大似然估计 , z$ Z; {$ u# h6 m2 G5 I
Arithmetic grid paper, 算术格纸
" y- w5 f# P1 C/ Q7 R: W5 J7 ], JArithmetic mean, 算术平均数
& Z( G& w8 \( z% P: `; ~Arrhenius relation, 艾恩尼斯关系
2 f I* l* j* zAssessing fit, 拟合的评估- w0 @2 L$ p" r) w, b* I) T( ]) r
Associative laws, 结合律
+ K& }8 X8 `2 i& b6 tAsymmetric distribution, 非对称分布
/ f4 X# D1 U4 u4 W8 z; R$ R' JAsymptotic bias, 渐近偏倚0 z& f# i i$ B' l0 ~8 {2 J0 V
Asymptotic efficiency, 渐近效率
5 y9 a6 c( G, B" O# DAsymptotic variance, 渐近方差% a& B* B$ p: {, j
Attributable risk, 归因危险度
0 ?& C- r# A; E7 g6 k- `. F. [Attribute data, 属性资料
& p% O0 \0 x' z( ]* GAttribution, 属性) _2 r$ z/ M6 u9 }7 _
Autocorrelation, 自相关
1 m" x7 A0 t; L0 b$ }: RAutocorrelation of residuals, 残差的自相关# D( O$ B0 n9 d, U# _9 m
Average, 平均数6 D* y" M- `# v1 s: A, p1 O
Average confidence interval length, 平均置信区间长度. v9 K' l. R$ u# i
Average growth rate, 平均增长率0 k. B5 A, W" W0 Q: a9 ^
Bar chart, 条形图1 `- F/ w5 @2 |1 U! q `
Bar graph, 条形图8 v$ @1 r2 s! G: h- @/ t9 y& K5 p
Base period, 基期
0 W6 x1 t" [3 Y4 ~* q' Y$ M V( V8 }Bayes' theorem , Bayes定理- m* [) S1 W2 d( f. X% I
Bell-shaped curve, 钟形曲线
0 T4 c) u3 f% x( b$ z# x0 RBernoulli distribution, 伯努力分布
& x/ B# d0 A5 b/ H0 QBest-trim estimator, 最好切尾估计量
" {4 f. ~$ m+ H0 I. z* nBias, 偏性
& K+ | n4 i# Y6 DBinary logistic regression, 二元逻辑斯蒂回归2 X. @1 u \( \
Binomial distribution, 二项分布0 \8 d T- ?8 W; n5 K+ g
Bisquare, 双平方 L4 o6 Y+ n! U: K
Bivariate Correlate, 二变量相关- q! a( U. l! _( G1 H# r
Bivariate normal distribution, 双变量正态分布
+ G7 X+ V" W$ U, r) F0 O: i! W2 ~Bivariate normal population, 双变量正态总体' F* m( N% b8 C* \7 K0 ^
Biweight interval, 双权区间
8 U: H( ~6 H0 u2 a$ E7 q2 I; UBiweight M-estimator, 双权M估计量# x0 Q" o" r. b0 d* w& ^
Block, 区组/配伍组
' t" b2 I1 h/ Y0 X& T" o dBMDP(Biomedical computer programs), BMDP统计软件包% m o, x! [9 [& P
Boxplots, 箱线图/箱尾图2 n4 _( N0 }& S& P. z
Breakdown bound, 崩溃界/崩溃点
3 J5 W5 D, V" d3 K- ~Canonical correlation, 典型相关
9 g2 K3 _ X \+ {4 BCaption, 纵标目4 M; b# a$ F G8 ?: \5 x
Case-control study, 病例对照研究* d) i- Z/ O! Q& ~6 M& l
Categorical variable, 分类变量! C" z3 ^3 G! R4 ^4 s
Catenary, 悬链线
! Y4 M, ?- O# y W# N+ E- eCauchy distribution, 柯西分布6 ~, b% l1 `1 F( x
Cause-and-effect relationship, 因果关系
8 `, B: Z& j' a4 e/ x2 [) s" ^8 |Cell, 单元
& W# E7 y' j5 D. E' XCensoring, 终检
# K8 k+ h- z0 _$ ] WCenter of symmetry, 对称中心$ S/ L ]8 e7 h: x4 C+ f
Centering and scaling, 中心化和定标
' ^' E- v) O, z' X% n7 MCentral tendency, 集中趋势
4 e$ V1 i2 e! H: fCentral value, 中心值
. g+ q* h ]$ J+ B( yCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测3 F6 v: `' k. N) }0 O! s; J; T: P
Chance, 机遇7 T8 ^5 w% ]9 E9 ~
Chance error, 随机误差
. H" H* q9 m2 w, PChance variable, 随机变量
* |! t- @( u" S' X TCharacteristic equation, 特征方程0 M+ [. M6 q7 [( Q
Characteristic root, 特征根
7 f3 F! ^5 q) h% c# ?! ?% nCharacteristic vector, 特征向量! S( k6 D- H6 `- G4 j J+ O
Chebshev criterion of fit, 拟合的切比雪夫准则
; {- r; @4 o! RChernoff faces, 切尔诺夫脸谱图
: Z, b! _, @! K4 FChi-square test, 卡方检验/χ2检验
2 A5 ?% R$ e6 BCholeskey decomposition, 乔洛斯基分解- B8 {$ S( |, y
Circle chart, 圆图
6 d( t; a8 S( L! L9 A$ k1 G$ RClass interval, 组距
1 P5 `$ @. x; }0 a- G2 o- S1 oClass mid-value, 组中值6 s+ d) b* k% `4 G9 x; @
Class upper limit, 组上限: d4 b! R4 b n% }! S
Classified variable, 分类变量8 q1 A1 r! `: ?# Z
Cluster analysis, 聚类分析8 p J7 E8 S/ c- h- u
Cluster sampling, 整群抽样
; y" S. a* Z8 b. ?6 ]6 c( sCode, 代码
& w% C% `# e( S6 sCoded data, 编码数据
! U# Y: S' _8 h9 D4 s- |* \' D1 R! x4 ZCoding, 编码
M0 p+ M4 r! s8 k! r0 z/ vCoefficient of contingency, 列联系数: P1 i$ m, O' `* `$ S0 y# [
Coefficient of determination, 决定系数1 Z, N1 o7 I3 e3 b1 L
Coefficient of multiple correlation, 多重相关系数- D8 f& e) X8 Y* G, @+ r' T ]
Coefficient of partial correlation, 偏相关系数
6 P* d- P. G% ?0 DCoefficient of production-moment correlation, 积差相关系数
" q5 U5 z9 I' B8 j# Y: l! k' DCoefficient of rank correlation, 等级相关系数2 d0 ^5 r9 w! t+ ?; ]+ k
Coefficient of regression, 回归系数
9 y2 c5 E: ~+ kCoefficient of skewness, 偏度系数
9 n/ E5 m8 V( HCoefficient of variation, 变异系数
; u8 ^! A& D9 m7 j. t, i7 v1 R* ECohort study, 队列研究
( ^0 c4 m+ T2 H6 S* z9 iColumn, 列
3 i) a7 H4 Z& Z! i! g8 z1 uColumn effect, 列效应
2 u/ p% q/ G' m% f! yColumn factor, 列因素
- r5 h+ a$ w0 X$ }! b0 }Combination pool, 合并
- M0 s* b/ m) F2 d4 F, ZCombinative table, 组合表. r7 G8 f# p! Z* j" o; Y8 A
Common factor, 共性因子9 I( y6 ?! }2 b# [) D: [
Common regression coefficient, 公共回归系数
& M6 T/ w" c c5 y9 f i. J" zCommon value, 共同值3 V& A# P: y( T s3 X, K
Common variance, 公共方差- @/ x" [/ u" J# k# E4 N
Common variation, 公共变异
V* G. V1 B$ c& a6 u4 i, _; DCommunality variance, 共性方差
! I8 s/ }7 _4 @" L$ ^, p" F9 z) EComparability, 可比性* C8 |- D" t$ m0 |! l, B
Comparison of bathes, 批比较
% b# L; \6 H0 r/ _Comparison value, 比较值- H! d. P+ Z7 c: ^( ^$ ~
Compartment model, 分部模型0 I. x( j: s( q f
Compassion, 伸缩0 W& x' N3 w3 a/ Q
Complement of an event, 补事件
8 z9 Q; U5 C/ s. N1 O+ R, f" WComplete association, 完全正相关4 ^. Y4 n h" Y5 a }2 D
Complete dissociation, 完全不相关
+ s1 v/ O. G# X. a, h% z% |Complete statistics, 完备统计量/ g+ ?7 x2 E5 Y0 o* K% |6 b- x
Completely randomized design, 完全随机化设计5 u; C! w2 ^8 }* B9 z
Composite event, 联合事件
' t1 y& P1 Y" |/ A8 [Composite events, 复合事件& Y' Y. Q4 S, o. e* F" l: T
Concavity, 凹性
4 ~6 |7 K% c1 q5 y _Conditional expectation, 条件期望0 W) P+ r: U `! c5 k, K
Conditional likelihood, 条件似然; I. i5 `/ W I0 E! x' h& a
Conditional probability, 条件概率
) l6 k* c) L) I$ i" M! ?$ ZConditionally linear, 依条件线性
9 l. ~# W* Z# AConfidence interval, 置信区间. T* _. `: s7 L! d {
Confidence limit, 置信限( Z! I) x8 B: {' v a% S! Q
Confidence lower limit, 置信下限3 H: q& p9 N7 O8 C& j
Confidence upper limit, 置信上限
3 l6 r6 B6 t: Y; r; r5 ZConfirmatory Factor Analysis , 验证性因子分析& R I0 l9 H( a+ e
Confirmatory research, 证实性实验研究, m% o; p3 T5 w4 J1 o
Confounding factor, 混杂因素
9 S/ G( p; c; C; m% |+ O3 z! RConjoint, 联合分析; A& S1 R2 I+ `* y. ?4 K* \
Consistency, 相合性! t5 s0 W! l1 R+ k, Y$ S6 ~
Consistency check, 一致性检验4 E4 i8 x/ `4 U' G
Consistent asymptotically normal estimate, 相合渐近正态估计* B6 _5 b3 y* R. ^% n6 v
Consistent estimate, 相合估计
0 C& i1 n/ k) c2 T6 x/ N4 s- lConstrained nonlinear regression, 受约束非线性回归' j9 W/ M7 Y: m8 S9 t2 C
Constraint, 约束
2 m' e- x2 K* h$ H* F4 W: D6 `7 bContaminated distribution, 污染分布* K/ H( h* N% h* E
Contaminated Gausssian, 污染高斯分布
4 f0 F& C9 d& e* A! u4 [( pContaminated normal distribution, 污染正态分布
0 F6 r. ?' E. J7 M+ u _; K( m, a" tContamination, 污染& O8 o1 o% N) _4 |2 Q! {% ?
Contamination model, 污染模型
! e. B+ A4 d# R& U8 g2 _Contingency table, 列联表
% F" M6 M5 F- d& c! MContour, 边界线3 o9 U& I" D9 {
Contribution rate, 贡献率
' Y& O1 r. w0 OControl, 对照
- {- | r) [0 I% _8 UControlled experiments, 对照实验, O4 s$ }7 h8 h$ E- ?
Conventional depth, 常规深度
( f# ^2 A4 @8 j$ C9 ]7 u3 }Convolution, 卷积
( R3 p$ d$ F# J' p2 s7 {* u& L7 J6 M5 g" bCorrected factor, 校正因子( S% h5 h% p& q: w
Corrected mean, 校正均值
0 x. T `6 g: q4 ]% wCorrection coefficient, 校正系数
# D/ O* C7 g5 C, g3 x uCorrectness, 正确性+ M( l* v! {4 @ X" ?
Correlation coefficient, 相关系数
% |' g; O7 l1 }Correlation index, 相关指数
; Y T6 M. j3 O1 \" uCorrespondence, 对应: w" V1 u0 T& v4 H+ Y. d# g
Counting, 计数
" u- \$ ]5 I/ _& Y9 K& {Counts, 计数/频数0 o3 b @0 E) v2 }# J( f
Covariance, 协方差 q+ i* q" E6 X) t/ I" X9 s# u
Covariant, 共变 b+ S1 [; W/ P
Cox Regression, Cox回归( k I* ]6 _) @! X g0 @( X8 y5 J
Criteria for fitting, 拟合准则2 |( e! L1 b. w9 t( e
Criteria of least squares, 最小二乘准则/ u' e. q6 }$ I# C; }% m
Critical ratio, 临界比
3 ?7 T' f, C$ W1 }* {$ K9 U# xCritical region, 拒绝域
! y/ `9 l: b5 MCritical value, 临界值
h5 W6 E/ Z5 F, vCross-over design, 交叉设计 |/ R0 D; I( }* N
Cross-section analysis, 横断面分析( ]" F6 k2 I2 N- {0 o& C7 r
Cross-section survey, 横断面调查4 d% s& {; j) m
Crosstabs , 交叉表
# h3 o$ y3 E& [ U9 _3 CCross-tabulation table, 复合表
0 t4 |4 Z% j7 K C; S6 YCube root, 立方根( t* D. o: l+ F8 t, L7 Z1 L# U
Cumulative distribution function, 分布函数+ N% H- W: s5 P' {! v3 s0 k
Cumulative probability, 累计概率: T6 s- G5 `1 e* G( K
Curvature, 曲率/弯曲
/ V! o9 G4 O$ X7 b2 N h# ]& CCurvature, 曲率
$ Z/ g9 b. j" `Curve fit , 曲线拟和 ' n& W# \' s8 S3 N+ Z, X/ D
Curve fitting, 曲线拟合
( r3 x+ I" N( M) `8 B3 i: yCurvilinear regression, 曲线回归0 o e7 F F( T3 B9 q) \
Curvilinear relation, 曲线关系
% q. C( @9 z0 ^% ECut-and-try method, 尝试法
8 _5 u/ l g3 y9 y% H# e2 d; E, @Cycle, 周期
% Y# P9 u7 ]$ ~ _. j5 T, V7 ?* GCyclist, 周期性
* S5 d! w- _8 i0 K/ I2 l( JD test, D检验
# b2 i4 k" z# g6 E6 TData acquisition, 资料收集
+ u. C# ?1 `& tData bank, 数据库" B* y& R- e& l' ]/ N F
Data capacity, 数据容量0 N: K! W" i+ D8 ]% M
Data deficiencies, 数据缺乏
( G9 C9 r! F& RData handling, 数据处理
, Z* C& a5 l! n+ ?: M6 SData manipulation, 数据处理
( v ]* m; n) `: }. O, p7 {+ OData processing, 数据处理0 P6 y( H* I2 G
Data reduction, 数据缩减
: A7 U o+ P1 Q& G7 S" d' [ JData set, 数据集9 M( ]- g3 b# a4 r3 s; m9 O
Data sources, 数据来源# z% V# y1 j. F8 `
Data transformation, 数据变换# k8 I8 j, r0 V# P6 ~$ a1 e( C, d
Data validity, 数据有效性; s. U7 l1 y8 z- ~+ r b
Data-in, 数据输入 C$ q$ D) I+ a! U. k1 j
Data-out, 数据输出- o" P1 n, @* ]2 f+ z
Dead time, 停滞期
% k9 m% F6 C# }1 G, @2 A0 e. W" YDegree of freedom, 自由度
/ t1 b9 Y, g5 d* d5 CDegree of precision, 精密度3 c. o2 _( o! ^, I& Q
Degree of reliability, 可靠性程度0 ^- E2 X& W2 K) ~
Degression, 递减
/ y1 x5 ~4 T M1 l$ cDensity function, 密度函数
. j" S7 M& [; U( dDensity of data points, 数据点的密度 w, r/ y6 ^& E( }4 g3 A
Dependent variable, 应变量/依变量/因变量# W/ T; k" |0 B& f
Dependent variable, 因变量' C& ?3 y2 B6 O& G7 C# K4 ^5 ?, O
Depth, 深度# M0 `% \3 w6 d2 d
Derivative matrix, 导数矩阵& E/ t( T( y: P, ?. ^
Derivative-free methods, 无导数方法 j! ^9 b: _: `" A; g. r* _1 C+ m& t% ?
Design, 设计. t6 `6 L$ f2 R& C. [5 ]+ X7 B3 r6 G s
Determinacy, 确定性2 U( x% d' X" F! q0 ?) Y$ U" C) o
Determinant, 行列式
$ i) v( E0 C- ~5 {$ M" TDeterminant, 决定因素
2 Z2 M& a( {2 c2 a. TDeviation, 离差
2 v" S/ Q; x) ~3 ^- S# _( T" EDeviation from average, 离均差
; V( r. U+ y; g" j4 I6 F. y$ l" VDiagnostic plot, 诊断图
. }9 e l0 g9 e& D8 m! kDichotomous variable, 二分变量
/ h c+ X* e& c* cDifferential equation, 微分方程1 ^' x" r, \. ^# Q0 k- @0 x
Direct standardization, 直接标准化法. o% h) K, |/ g& f/ w/ q
Discrete variable, 离散型变量+ X. i7 W- U3 k3 g8 [/ W6 V: D
DISCRIMINANT, 判断 & D9 U* j) @ Y) T9 b$ p
Discriminant analysis, 判别分析# H9 R9 Z9 t# k
Discriminant coefficient, 判别系数$ `! o9 j3 e( S( i, Q& R; c: A2 g" L
Discriminant function, 判别值
$ J9 F6 s+ d4 j# x: A* |" \Dispersion, 散布/分散度
! o u G0 l+ ?( h, F" f7 v3 aDisproportional, 不成比例的
; V: z' Z1 s2 h D! q+ YDisproportionate sub-class numbers, 不成比例次级组含量
2 Z. l8 r$ z+ w/ ~Distribution free, 分布无关性/免分布$ K2 R* O5 g- k9 Z+ ?$ f
Distribution shape, 分布形状
& S, o# {( E2 o2 U+ {Distribution-free method, 任意分布法
" d/ Y7 t; c8 l( N6 ODistributive laws, 分配律
" { f* w* j% }* r6 I* u; k. t [Disturbance, 随机扰动项2 X7 t3 \" p. }0 i* A2 g
Dose response curve, 剂量反应曲线
C9 z2 a- {7 s+ M4 |Double blind method, 双盲法: h- R$ F7 `7 L' z; ~8 K
Double blind trial, 双盲试验: L- t G; P# e5 W) ^# d3 z
Double exponential distribution, 双指数分布- ^( S' U. L- A
Double logarithmic, 双对数
9 \8 ^! V- m, l/ K4 _: \( \! PDownward rank, 降秩( F5 L! R4 }; c0 r2 p% I3 U
Dual-space plot, 对偶空间图
) q8 I* a" i, y1 E8 a1 q. X% \DUD, 无导数方法
; i( w$ C$ O; H6 z5 mDuncan's new multiple range method, 新复极差法/Duncan新法
) p! e3 c, z; `. i; G2 tEffect, 实验效应' N B' ~/ @7 R4 {( B) N
Eigenvalue, 特征值
/ K; }, Q1 x7 N) e2 U! ?9 q8 CEigenvector, 特征向量3 ~, \+ d! z, Z' d. A! ~7 Z3 |
Ellipse, 椭圆. {+ g& [: W1 G$ K
Empirical distribution, 经验分布9 Y& J) J6 M/ i6 B/ g. Y( K
Empirical probability, 经验概率单位
6 w9 _6 x+ }2 S/ TEnumeration data, 计数资料
2 ?0 E+ Z4 A' R$ aEqual sun-class number, 相等次级组含量3 j# z3 H" R) A$ T
Equally likely, 等可能2 q1 z+ J: E3 c, _
Equivariance, 同变性/ E' X( r- G( w6 M! f* d: i% A( P
Error, 误差/错误0 a' M* y/ m8 }6 y; E
Error of estimate, 估计误差
2 u2 }, e% a9 Q4 i, l. oError type I, 第一类错误/ \% Z' c' I/ W$ P Y$ u# K( b
Error type II, 第二类错误
0 F* |% P5 W9 X* p" f; I* oEstimand, 被估量# p0 v" }( ~8 L* L3 C# ?' _: [) ]
Estimated error mean squares, 估计误差均方
# z& M3 W q5 V/ o5 N' F* HEstimated error sum of squares, 估计误差平方和
8 e3 X' i6 a$ l* J' KEuclidean distance, 欧式距离1 A3 m* J" w* K
Event, 事件' e$ ~2 \. T+ e$ V+ l/ _: j$ U4 v
Event, 事件 d, G" t7 k# Q. m' u: c [
Exceptional data point, 异常数据点) n) ?! M0 X0 \! t" n) d* K* _
Expectation plane, 期望平面 {) {: B9 Y- f
Expectation surface, 期望曲面8 Z5 g! E& ]4 @- A! o% a2 R
Expected values, 期望值
; Y; l) ?& h: L: c- u# EExperiment, 实验
$ Z& O: @: H3 xExperimental sampling, 试验抽样, O+ Z* L4 K5 `8 h; F/ l4 E: r( N
Experimental unit, 试验单位7 I) }9 l, e" C5 L0 T: g5 Z/ F8 w- ?
Explanatory variable, 说明变量
, R; C% L/ u q4 T& [" aExploratory data analysis, 探索性数据分析
+ I& V. p' m' U: l) e* h3 ^Explore Summarize, 探索-摘要
) i3 ^7 G# j( ]Exponential curve, 指数曲线
c5 p9 P4 t' n- w: UExponential growth, 指数式增长& c! Q, T, p2 j8 F0 t
EXSMOOTH, 指数平滑方法
3 Z6 @( @0 I6 ~ zExtended fit, 扩充拟合+ f! t; e/ C1 k& O( W8 u
Extra parameter, 附加参数: M/ Y1 r# Z7 m! n4 q$ k
Extrapolation, 外推法$ {$ B4 c% R$ O8 ?8 X5 l- J
Extreme observation, 末端观测值# O* u: w+ h' U& [( n( o
Extremes, 极端值/极值 F# O" r& d4 h. D% Q) W- Z2 Q% d2 V
F distribution, F分布. Q/ C4 K# O5 L: B5 s
F test, F检验
' w8 h- O& u2 V# w$ `+ k9 Z2 N1 U8 FFactor, 因素/因子& j9 J2 y. Q& e, X8 D) N
Factor analysis, 因子分析& V' \" l6 C T; z
Factor Analysis, 因子分析
6 C: r: T" x0 R% A2 z$ uFactor score, 因子得分
. o L$ r/ H# J$ k$ m3 \* _7 mFactorial, 阶乘" N6 P b1 [! n
Factorial design, 析因试验设计
( B0 a! R/ i) e3 U5 `, l; E6 JFalse negative, 假阴性+ R0 @7 Y/ x* M4 K
False negative error, 假阴性错误# j: \7 {) D9 M+ ^9 A+ R! N5 A
Family of distributions, 分布族
. M& m* d; j. VFamily of estimators, 估计量族
& p, \8 d7 z5 J2 KFanning, 扇面$ y- R1 T! S0 m3 ^* b* E
Fatality rate, 病死率
, q, L9 A. M+ k( ]# b) a, NField investigation, 现场调查) H- X" p5 T! e
Field survey, 现场调查
7 f' x" p8 H& r# nFinite population, 有限总体2 a" L- f4 W+ K1 k: P! @2 R" H
Finite-sample, 有限样本
/ [; e. c* x2 W+ h" f$ Q3 `5 [First derivative, 一阶导数4 w2 T1 o: k1 K9 W4 h
First principal component, 第一主成分: j) `! f2 a n) [6 K( k5 \7 }) R- U
First quartile, 第一四分位数
( b( [. z3 ?5 {Fisher information, 费雪信息量' `, i' X/ q5 z8 w. B3 ^. z
Fitted value, 拟合值$ ?. }. J4 P1 y! X5 r
Fitting a curve, 曲线拟合) O9 |) ~2 z' t) K
Fixed base, 定基9 P3 u8 S2 l+ ?) @7 S
Fluctuation, 随机起伏# G c1 Q& W! P9 {' v9 U
Forecast, 预测+ {/ D! v9 T! _4 p; R+ [
Four fold table, 四格表
4 v# o6 L8 N1 y* AFourth, 四分点( r4 J P, F6 v8 x9 s# v
Fraction blow, 左侧比率( g" F4 H: Y% n6 S+ i2 I
Fractional error, 相对误差9 \0 B: p* r; G7 J" L$ Z5 q
Frequency, 频率
5 U" v: l+ K9 Q- i: d- rFrequency polygon, 频数多边图4 V0 Q+ u. F- Z
Frontier point, 界限点& d1 k. E) | }9 I. n
Function relationship, 泛函关系: x: _ X* E: r0 W% t
Gamma distribution, 伽玛分布& U0 p8 q4 _) w& f
Gauss increment, 高斯增量
) @ x/ _) t5 ^1 nGaussian distribution, 高斯分布/正态分布
9 X5 X, S1 f2 G! C) t2 {! W4 SGauss-Newton increment, 高斯-牛顿增量
. X3 L" C5 l6 N8 ]General census, 全面普查
( W! }6 Y2 t. {; |) q, EGENLOG (Generalized liner models), 广义线性模型
+ u% l* x* `/ j. V4 CGeometric mean, 几何平均数
4 c2 i Y# P1 I# r( hGini's mean difference, 基尼均差) E, V0 L( K t: `' m) U
GLM (General liner models), 一般线性模型 ( X/ E8 n! L. X$ w
Goodness of fit, 拟和优度/配合度
% u4 R, j. v% {5 E1 n) ~! x7 XGradient of determinant, 行列式的梯度, [5 l" N1 ~; q, d& t9 c
Graeco-Latin square, 希腊拉丁方0 p: s# f( E7 r1 P6 X" p9 \% w7 t
Grand mean, 总均值
; i7 a" ^+ c5 \! ~ Z! MGross errors, 重大错误$ Z8 C# h9 U3 U4 e9 O
Gross-error sensitivity, 大错敏感度0 U& ^/ k# R1 a% }: i2 ?
Group averages, 分组平均
% Y$ H; [+ I$ \+ e& H' R: MGrouped data, 分组资料
" j) s" t0 D& M4 |9 _Guessed mean, 假定平均数
# B( ^- M+ `0 f- P( x4 B9 z5 c* I; n3 ZHalf-life, 半衰期 D s% P/ H4 R, Q$ R. E
Hampel M-estimators, 汉佩尔M估计量8 M$ ]" L) t# L: T7 k( s
Happenstance, 偶然事件
2 U5 |8 t3 _, h4 {. p W, v5 ^Harmonic mean, 调和均数
) y7 m0 J/ y3 x$ KHazard function, 风险均数
8 d& R# U# \ Z$ @/ pHazard rate, 风险率' V! @! Z$ C2 q& d' ^
Heading, 标目 $ |% e0 A: {# P) g/ d$ r+ w/ ]4 d
Heavy-tailed distribution, 重尾分布
0 S( W% H( Q( ~" g3 KHessian array, 海森立体阵0 k/ C. {& V5 U* E: z
Heterogeneity, 不同质7 w1 ?/ P0 }4 G$ t/ S! {4 Q
Heterogeneity of variance, 方差不齐 * C/ S( O, s. j
Hierarchical classification, 组内分组: Q! d3 L; G3 Y" V
Hierarchical clustering method, 系统聚类法
- h0 T' K' L$ L: S% S7 DHigh-leverage point, 高杠杆率点$ P$ M; N V# A$ u0 o# b# y
HILOGLINEAR, 多维列联表的层次对数线性模型5 W/ D+ d# `9 R) L9 y
Hinge, 折叶点9 s! s6 D" W: U8 v3 x% b
Histogram, 直方图: f% Y- J0 E* [( o% }
Historical cohort study, 历史性队列研究 1 l# D) W( y' `- f% e" f' u3 d+ d
Holes, 空洞6 D1 w2 X% Z: y
HOMALS, 多重响应分析( I, I% A+ J" H- X
Homogeneity of variance, 方差齐性
& l* N4 V$ I6 {! i, g4 \Homogeneity test, 齐性检验
) x: s3 o. Y7 d1 Z- ]* ZHuber M-estimators, 休伯M估计量
4 L5 P Y* n- I8 sHyperbola, 双曲线
; @; m, \) z: C% ? O% H* h; [0 HHypothesis testing, 假设检验0 I9 ?; j+ t- H/ \$ k; {$ n% R
Hypothetical universe, 假设总体
, r ?7 H9 s; J; kImpossible event, 不可能事件
8 \* n3 s% S' A2 O/ h0 x* @Independence, 独立性
; W w* H# a6 J r$ k1 o1 v) [Independent variable, 自变量
# t V; D/ b$ d+ Z# _Index, 指标/指数
8 [% M o' K$ K' R' SIndirect standardization, 间接标准化法
9 |8 `; a; i2 @. ]$ G" {% LIndividual, 个体, c3 H) C7 I2 T4 M& a
Inference band, 推断带& k+ Q2 j7 h6 x' C9 H
Infinite population, 无限总体
6 z% w8 z' R! |( s, f$ ]Infinitely great, 无穷大
$ C1 M. O$ Z3 T6 F1 D' n3 c9 wInfinitely small, 无穷小8 _3 J, d1 I1 S- o' X! G4 r1 q5 f
Influence curve, 影响曲线
' U( V! @6 B# _Information capacity, 信息容量7 ^1 l& m( k( U7 | j5 D
Initial condition, 初始条件
1 {/ x, \ p& c* s7 i. N$ EInitial estimate, 初始估计值
% ^& |) ~) C& }Initial level, 最初水平$ |4 A+ u _% Q! C' _
Interaction, 交互作用8 D* u7 I! ^ E" s4 P! H
Interaction terms, 交互作用项
/ A; L3 }1 d ~& W3 {1 ^6 U. v& a. i. AIntercept, 截距( z& k. [, D$ Y7 i
Interpolation, 内插法/ r* t: @# O& R/ `
Interquartile range, 四分位距
( m) o2 Y- n# @* n; ], f) x7 [Interval estimation, 区间估计) {( g9 O; D4 K. j. R6 i
Intervals of equal probability, 等概率区间
4 U, o0 K; p! }: HIntrinsic curvature, 固有曲率
" E- n& H: ^) hInvariance, 不变性 _; Z+ P1 H8 g0 u" Y6 g
Inverse matrix, 逆矩阵
' M" ]* Z4 D3 c: o8 E' i0 kInverse probability, 逆概率
' |6 m1 h4 h" x: kInverse sine transformation, 反正弦变换9 e$ [9 k$ n6 S) `6 S2 x& N, p) d
Iteration, 迭代 ' V9 m# R. e$ ~$ n: T
Jacobian determinant, 雅可比行列式
( [: G4 y1 E" Q' M$ W {Joint distribution function, 分布函数
8 x# [6 M1 I/ H; x/ { C/ C1 UJoint probability, 联合概率. e' b0 h; \ n( D
Joint probability distribution, 联合概率分布% [! G ]2 N5 P' X8 C: Y# q
K means method, 逐步聚类法
( x& r& s" Q7 f; MKaplan-Meier, 评估事件的时间长度 0 C( g4 U) @9 |
Kaplan-Merier chart, Kaplan-Merier图4 C1 q) E& m6 l# Z
Kendall's rank correlation, Kendall等级相关
) F6 _8 a& z$ F7 h* i" s8 CKinetic, 动力学
4 m5 O- [, ~: y' _& l1 u. @Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验$ M, @ ?) c! B) a
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
. D0 ?* Y; K5 MKurtosis, 峰度
; f6 _2 w9 O8 v* W- V0 hLack of fit, 失拟# ]; U- l4 h, R! f
Ladder of powers, 幂阶梯
. ^: y% i8 A% q3 LLag, 滞后
: ?6 L8 c2 ^" O$ q! b( k( LLarge sample, 大样本 f! y' I; r' { k3 K
Large sample test, 大样本检验
+ `6 d( A( ]; m; d, z8 @0 N% ?4 PLatin square, 拉丁方
1 V/ ^+ N( [8 ?1 ELatin square design, 拉丁方设计4 t; F3 K* b1 U$ S5 [5 M; n
Leakage, 泄漏
* O# G0 Y) Z/ ^% [6 TLeast favorable configuration, 最不利构形
) A! T7 |6 F% FLeast favorable distribution, 最不利分布7 s. Q" {* n9 e6 }1 v b
Least significant difference, 最小显著差法
$ a* a% f6 a* b* ]Least square method, 最小二乘法
4 o2 w2 Y7 ?9 ^# x4 E$ G) MLeast-absolute-residuals estimates, 最小绝对残差估计
- m+ t. X! M; ^' }2 _Least-absolute-residuals fit, 最小绝对残差拟合
) ~: u ]0 k9 e$ a% q, e+ gLeast-absolute-residuals line, 最小绝对残差线( k! l% Q# A( c+ [0 z0 W% ^: q& ~
Legend, 图例, ]; W# g( X2 G) j
L-estimator, L估计量
# I" s2 q7 s) n" hL-estimator of location, 位置L估计量' a" {) F6 ]( b( T6 K% X4 x0 f/ P
L-estimator of scale, 尺度L估计量! N" n) T/ c% }' r. g
Level, 水平& x0 ]% g" p4 ^9 m$ M" ~1 s
Life expectance, 预期期望寿命
3 F# p/ i+ R4 \" MLife table, 寿命表
) J0 g4 j$ [6 F( s# P6 _: I! DLife table method, 生命表法
) l2 ]- k% I: `- F$ ALight-tailed distribution, 轻尾分布
6 q3 [6 ^ x1 |9 {) t, bLikelihood function, 似然函数
) H3 s% j; H# I" @Likelihood ratio, 似然比
& w: P+ u7 M0 B* o" uline graph, 线图
+ ~( H$ v9 F: ]Linear correlation, 直线相关
/ x. O+ i, K% Q7 I& ^; GLinear equation, 线性方程/ {# ]5 Z7 i( y; U+ S' u
Linear programming, 线性规划! K- Q' s u- R, p
Linear regression, 直线回归9 l; I8 s' C7 V0 x* i
Linear Regression, 线性回归: F: h% ?0 J8 i* Y! j- S1 z; {: E
Linear trend, 线性趋势6 @1 }2 I' e' D0 m* i
Loading, 载荷
) y0 @/ ]' U0 \1 U( q O* f9 O# ~' WLocation and scale equivariance, 位置尺度同变性
5 H3 e3 K0 ]& b% U; h2 Y! E: ALocation equivariance, 位置同变性
7 Y) ?# T5 g2 @5 H8 w% j. sLocation invariance, 位置不变性
- f5 Y- g5 e1 k& q9 X( {$ w+ Y/ i, }Location scale family, 位置尺度族
, Y1 `: \( I4 Y' N; \% W0 @! pLog rank test, 时序检验
) N1 Y5 f& g( uLogarithmic curve, 对数曲线
8 L* c2 E5 z% p8 z4 A# p7 Y6 U/ A" JLogarithmic normal distribution, 对数正态分布
: X* d0 `% a8 t/ l7 M/ i/ VLogarithmic scale, 对数尺度. h r* D9 j1 A5 f8 ?
Logarithmic transformation, 对数变换6 ]- E# V" @7 Q+ B$ E- j
Logic check, 逻辑检查( f' l, k6 L$ ]' j
Logistic distribution, 逻辑斯特分布' u% u5 k9 z7 x
Logit transformation, Logit转换# l& b3 Z# z7 \ `$ k/ t \
LOGLINEAR, 多维列联表通用模型
" w2 N' o2 ^7 y$ _Lognormal distribution, 对数正态分布+ t, Q& J, o7 Y8 m* @0 Y# e2 V
Lost function, 损失函数: R9 s: p3 o- v( P9 o. a0 g. V
Low correlation, 低度相关) }$ G# _" Q% U) m+ ~
Lower limit, 下限$ B0 A9 ^$ L5 ^% e9 W+ D- w
Lowest-attained variance, 最小可达方差
- z- t: |$ X% v3 K5 |% CLSD, 最小显著差法的简称
8 R4 m- x; t- _1 NLurking variable, 潜在变量1 [: m4 T) t7 x
Main effect, 主效应* k! H' y- {' X1 i. Y( J1 |6 g4 S
Major heading, 主辞标目
6 {2 r1 x! {, BMarginal density function, 边缘密度函数
0 F2 M$ F" Y& ]6 [% IMarginal probability, 边缘概率
/ @" p( x# w# t7 zMarginal probability distribution, 边缘概率分布1 Y8 x* r U# ~6 F3 a0 \* v' t3 X/ ^
Matched data, 配对资料
7 ^$ h8 @+ a. B# VMatched distribution, 匹配过分布+ A5 J" e0 x! r+ |
Matching of distribution, 分布的匹配, v* C' H1 y9 `. T# u
Matching of transformation, 变换的匹配
0 D( Z ^% E1 _# r& o% ^: xMathematical expectation, 数学期望
* G2 q. t) b) F b' Z( dMathematical model, 数学模型( z. b! c( z' Y. _- W2 h* d6 x
Maximum L-estimator, 极大极小L 估计量9 A$ F }% A$ l" G. a5 L
Maximum likelihood method, 最大似然法
3 N/ C/ F& w; t. O- NMean, 均数# @" D! y& [1 l' U& U
Mean squares between groups, 组间均方
9 t/ b* j( E( `/ `8 p, B4 i7 [Mean squares within group, 组内均方- w5 D5 X$ X& n( y% {9 u) W9 V
Means (Compare means), 均值-均值比较
8 O7 u9 X* X8 q/ h' u+ }Median, 中位数" ^& |6 D' N ^% H$ O5 O4 i
Median effective dose, 半数效量
! m" f3 ?' s9 EMedian lethal dose, 半数致死量- a9 d; G& Q3 L: M0 e9 g* R
Median polish, 中位数平滑
- R. Q5 X& B3 [: }: EMedian test, 中位数检验% l$ w! n4 Y+ a; d0 {+ Y3 X
Minimal sufficient statistic, 最小充分统计量
: n( R: I, z; c$ Z- YMinimum distance estimation, 最小距离估计% a9 o" P% r K( G8 c3 r
Minimum effective dose, 最小有效量
6 H+ F0 ?# o0 W# e) h9 q+ W# ?Minimum lethal dose, 最小致死量; i( u- z5 W5 M3 d
Minimum variance estimator, 最小方差估计量, M% b4 t3 _/ C9 `
MINITAB, 统计软件包
l$ L7 n$ r0 x$ M. F1 H' O3 iMinor heading, 宾词标目# t1 O4 w- w. i# B
Missing data, 缺失值4 m7 f" T* q7 D4 f4 c, a
Model specification, 模型的确定7 F7 b: h' ~! y# P9 ~+ Z: y" e% E
Modeling Statistics , 模型统计. \0 b/ i2 d, |7 \
Models for outliers, 离群值模型
0 {" z2 e* q8 l; m" bModifying the model, 模型的修正
. {2 H; G/ I. w2 pModulus of continuity, 连续性模
. p# O y# C4 [/ q MMorbidity, 发病率
& v7 D+ T; s9 Q7 l* EMost favorable configuration, 最有利构形5 u2 F7 x# | `+ W4 l: u
Multidimensional Scaling (ASCAL), 多维尺度/多维标度' [3 L$ g8 P, v# y* \# o
Multinomial Logistic Regression , 多项逻辑斯蒂回归
2 U l: X, i1 ? ?, x* S2 ]; iMultiple comparison, 多重比较
# ^+ w+ i Q$ ^1 s2 ^# y2 n6 RMultiple correlation , 复相关. {- y e- k; L) |0 n
Multiple covariance, 多元协方差 \ \1 v0 B, |: w& R& A6 N
Multiple linear regression, 多元线性回归
, D! A! z \, t8 `0 ?. ?Multiple response , 多重选项! [$ w+ c. a2 v3 B2 X. `
Multiple solutions, 多解
* S0 b s, b/ GMultiplication theorem, 乘法定理# O$ i0 B5 n3 B
Multiresponse, 多元响应3 _6 E+ s( g! s/ a
Multi-stage sampling, 多阶段抽样- j* j' R3 X' F6 d4 \9 r
Multivariate T distribution, 多元T分布) W+ C& K7 |: _8 m, g" q1 O
Mutual exclusive, 互不相容' F! L5 y1 d: s2 v$ Y4 K
Mutual independence, 互相独立" w, B7 e, j/ b4 R# C
Natural boundary, 自然边界
6 u# M( j. q7 F z" E# |9 W$ ANatural dead, 自然死亡
8 v% [5 e8 b+ z( r6 \6 {Natural zero, 自然零
9 D9 z5 {3 V v+ LNegative correlation, 负相关
) e1 N& t/ ^6 S/ t0 vNegative linear correlation, 负线性相关. E% {8 C/ M8 ~: B) w/ j7 k
Negatively skewed, 负偏
. b$ q& e: h; _) fNewman-Keuls method, q检验% [/ o7 k7 H7 z
NK method, q检验
! G5 e: i3 }. {7 k* T: Y0 W! [No statistical significance, 无统计意义$ E2 M% s0 H* S1 Y3 k+ a6 v
Nominal variable, 名义变量
5 m/ p! X' J" x0 [Nonconstancy of variability, 变异的非定常性
7 Q: z* m, ~; r8 m1 o% _; uNonlinear regression, 非线性相关
" H8 |! q9 Z4 s4 D0 {Nonparametric statistics, 非参数统计
& X' L+ T3 E4 \; k# J& c; iNonparametric test, 非参数检验" T0 V1 T' J% J* O+ x/ V8 h9 i
Nonparametric tests, 非参数检验5 T1 X4 S8 l0 J/ k
Normal deviate, 正态离差( } t/ \7 w* d. c" s# [
Normal distribution, 正态分布. Y* M2 T! a9 G+ X& o! s
Normal equation, 正规方程组: y* n4 N8 ?0 r2 o: Y
Normal ranges, 正常范围2 Z8 B) q3 d) ^6 W
Normal value, 正常值
' L% N% r5 T# A- ]) `7 u9 cNuisance parameter, 多余参数/讨厌参数0 I# p2 I7 I* r- ^1 L+ R. l/ |
Null hypothesis, 无效假设
- T) @! G0 p/ _Numerical variable, 数值变量
/ a8 q2 E3 [) c" RObjective function, 目标函数
% H1 h( z# g1 E( l) g& vObservation unit, 观察单位
) i! y$ u- {7 I% L1 tObserved value, 观察值$ i1 \* ?2 q$ f' y
One sided test, 单侧检验
. U, Y5 d! z5 x5 x) n+ yOne-way analysis of variance, 单因素方差分析
* z0 ^1 A; e' JOneway ANOVA , 单因素方差分析
) L, g0 ?- o7 ?& y3 | S v6 iOpen sequential trial, 开放型序贯设计. y/ M, w, A6 P7 p, {0 f$ b
Optrim, 优切尾
4 @4 i6 a" W# Y9 m! h. COptrim efficiency, 优切尾效率# V, V& d9 k, P7 y# M
Order statistics, 顺序统计量
4 P& R+ j: A! q( vOrdered categories, 有序分类
( F1 t$ I1 v+ U ~' wOrdinal logistic regression , 序数逻辑斯蒂回归
5 V: o, Y/ t% J3 A) O0 a3 v6 uOrdinal variable, 有序变量2 w" G/ d( b7 O1 m/ r
Orthogonal basis, 正交基5 P* E& D$ z2 u' o7 H: u% ^
Orthogonal design, 正交试验设计7 J2 Z7 b0 r& [+ V
Orthogonality conditions, 正交条件 O$ ?+ i' g0 s# `. b ?$ S) }3 C
ORTHOPLAN, 正交设计
! d" |- c/ H; D1 R& [: i0 OOutlier cutoffs, 离群值截断点
@% N* c0 T2 N7 ?) iOutliers, 极端值
1 m( v' Y" A$ r. W* L1 ROVERALS , 多组变量的非线性正规相关
5 Q+ [3 P3 H. F8 n% I( mOvershoot, 迭代过度
. e" H$ z/ N: _. {6 I" rPaired design, 配对设计
/ [+ }' F; b/ yPaired sample, 配对样本
8 O$ j' k4 |; M5 S0 W1 C# fPairwise slopes, 成对斜率
6 Q$ T9 ^/ H" g) [( ~& [Parabola, 抛物线6 b4 T( m( `, X& {( P
Parallel tests, 平行试验! [, |8 R& G8 o0 v% Y
Parameter, 参数
) _* ?& y3 S, U" t. d8 e2 CParametric statistics, 参数统计8 O9 }( L! h1 j# p# L" Y9 _
Parametric test, 参数检验
7 \& s6 ~' ^/ U+ f( } e m9 G9 WPartial correlation, 偏相关6 T& ]( U* N& _( J7 d
Partial regression, 偏回归
( I' n. f- a7 o8 o" y9 x2 @+ lPartial sorting, 偏排序
J* f( L9 O5 c/ ~Partials residuals, 偏残差
3 @1 `! ]; R" l! _/ {4 P* UPattern, 模式
) }. s) C) @$ R/ f' M; X; QPearson curves, 皮尔逊曲线( X/ m9 }* O# r" U
Peeling, 退层: ^9 d- G) e; T1 {7 y6 X
Percent bar graph, 百分条形图& D: |! y5 K+ k3 i+ O4 d
Percentage, 百分比* e. a7 d. O5 T5 {' {* s
Percentile, 百分位数
! G. X g# D3 h7 I9 _( a# B. vPercentile curves, 百分位曲线
. z$ A& E0 |. L. rPeriodicity, 周期性$ r; q: `/ t; h8 m2 W: i
Permutation, 排列
6 c8 e4 e( I# z7 CP-estimator, P估计量' j5 F' Z) P- i( a' n' [
Pie graph, 饼图- {( t- e4 ?( ] `- o: E3 T
Pitman estimator, 皮特曼估计量3 ^ ?0 q/ }0 d" C
Pivot, 枢轴量$ w2 l4 @. P) P6 s: O
Planar, 平坦6 t. r5 M* T9 U) u1 H/ ]# U
Planar assumption, 平面的假设
: A% t3 d; s" J# b% W4 I# [& _PLANCARDS, 生成试验的计划卡
- T. w& v1 s) ~; ?Point estimation, 点估计# i2 t% w S9 s
Poisson distribution, 泊松分布
3 N: A7 s& e* I' q0 U; YPolishing, 平滑" m6 L5 d4 [* J1 [8 y
Polled standard deviation, 合并标准差
8 d8 {7 Q- [4 N9 ePolled variance, 合并方差( ]; ~" n* Q' l E
Polygon, 多边图$ B+ L8 V8 m1 t ]+ j
Polynomial, 多项式. P7 j8 h# J8 b! V$ p) T
Polynomial curve, 多项式曲线
( m9 e4 E/ ^7 GPopulation, 总体
. _5 ?5 E* o! o) i$ l9 G2 d- wPopulation attributable risk, 人群归因危险度
! {* U6 I5 O7 R) RPositive correlation, 正相关' g4 M, [7 N8 y! P* s8 r+ S
Positively skewed, 正偏% G" p2 [* K3 D$ P p9 e
Posterior distribution, 后验分布
, m3 ^9 t2 P1 J# i# c6 O% sPower of a test, 检验效能: g: b2 h: k% y2 M/ k
Precision, 精密度- M, j) ?' `$ }" c
Predicted value, 预测值+ G: N7 F; D: x; Z- h' V
Preliminary analysis, 预备性分析2 ]8 K: D; ^5 c! a
Principal component analysis, 主成分分析
% q' r, W& d& t7 K% q& vPrior distribution, 先验分布' V* s; M% d% R# r
Prior probability, 先验概率
) u# D" B$ s6 f) M6 Z/ u! B) ?Probabilistic model, 概率模型
: S5 H: C/ V2 y, a) _probability, 概率: H% w2 H! a. Z+ B8 d
Probability density, 概率密度
) u4 @$ h+ l) ]- @" GProduct moment, 乘积矩/协方差+ i/ ?; Y+ g- G- I
Profile trace, 截面迹图
8 V( `+ u/ o& W$ T6 g$ x% B4 EProportion, 比/构成比
- [# C3 s8 [3 m3 z. XProportion allocation in stratified random sampling, 按比例分层随机抽样
% L, ^: D; p! j9 G% PProportionate, 成比例
' w; x; v1 n& K9 ` _5 bProportionate sub-class numbers, 成比例次级组含量 \# j3 S6 n2 Z' c- A1 k6 j4 b
Prospective study, 前瞻性调查1 O; e7 _/ m, R/ W
Proximities, 亲近性
! ?# y0 i9 T0 U+ l' {$ Z) RPseudo F test, 近似F检验
. k, y3 I( n7 f: f! u+ ~9 J$ b4 mPseudo model, 近似模型1 n/ |" t) X# m7 e$ \1 P6 Z
Pseudosigma, 伪标准差
( O: }* k( O: |2 v# K2 @Purposive sampling, 有目的抽样
J9 C) N# R% y1 F2 | DQR decomposition, QR分解
- \. G0 S; z- r4 D7 { C2 Z4 q1 dQuadratic approximation, 二次近似" _7 J3 |! S! I4 x6 ^, L
Qualitative classification, 属性分类
; w* A: T' m& ?3 F* MQualitative method, 定性方法
% o8 d/ E1 B8 p6 i( \) _Quantile-quantile plot, 分位数-分位数图/Q-Q图/ P+ Z: a$ H# D4 R; y: Y! g
Quantitative analysis, 定量分析4 Q- X! A7 @! i
Quartile, 四分位数# S% g! d# i7 L' G2 o; P! C4 K Z
Quick Cluster, 快速聚类 z j3 \" T9 J8 h
Radix sort, 基数排序
3 o; A% a4 e% `/ S& L1 `Random allocation, 随机化分组7 K% B/ K2 P( V: ^! V7 b3 `
Random blocks design, 随机区组设计8 u9 k& B2 T" y) h& u
Random event, 随机事件
9 [9 a$ _' {& [$ x9 uRandomization, 随机化
8 p# ]: p. U. f! U- P! ^5 lRange, 极差/全距
0 R; o( N4 y4 w4 e1 SRank correlation, 等级相关
0 V& B9 Y( n: [( fRank sum test, 秩和检验
3 Q' t6 j$ D9 x4 k& g4 ]+ M) [Rank test, 秩检验
/ Q* F- O, [! R) a w+ q( oRanked data, 等级资料
- J8 G0 o4 `/ K9 o& T" _9 CRate, 比率9 J4 u; g" @: s9 i5 ^
Ratio, 比例$ R1 n; y5 T9 ~+ s4 a" `. ]' z% {
Raw data, 原始资料
2 j6 [( [% t2 C8 L5 ]Raw residual, 原始残差
" U- A+ ~4 N" A8 M& e0 n+ w7 SRayleigh's test, 雷氏检验
: a c' A% H. m* j/ l$ {/ CRayleigh's Z, 雷氏Z值
: r- q+ Z4 R H9 M4 pReciprocal, 倒数4 g9 N4 k% h }" i& w$ F
Reciprocal transformation, 倒数变换
8 \: F& }2 J8 F" J NRecording, 记录% t. `9 b8 [( P
Redescending estimators, 回降估计量$ D/ u' x8 w% {2 z
Reducing dimensions, 降维; u; p2 g4 J, h2 ~ [! B0 E
Re-expression, 重新表达' R0 a# M, ]) j3 H
Reference set, 标准组6 B5 ?( Q V( a* N
Region of acceptance, 接受域! g* q/ y+ @7 `2 t9 ^$ E- {
Regression coefficient, 回归系数
5 Q6 ]9 U1 V: |% e% M5 rRegression sum of square, 回归平方和
& Y, N: f x, A" b, t% _& ARejection point, 拒绝点
5 A, @4 o( w) t$ f5 NRelative dispersion, 相对离散度
, _+ t. ^* K- d; H; }# DRelative number, 相对数, [& r: u& u z
Reliability, 可靠性. q, x1 z4 ^# G4 B7 f
Reparametrization, 重新设置参数$ a* S1 c* n+ v
Replication, 重复8 |6 w% g: m4 R6 q5 b1 @
Report Summaries, 报告摘要
0 J0 W0 V) [* t8 s w8 ]Residual sum of square, 剩余平方和# I& Y( z0 T9 h3 j) U
Resistance, 耐抗性7 K; ?, A; `0 p* ? Q
Resistant line, 耐抗线* z. V" T8 |1 S
Resistant technique, 耐抗技术
8 l: A$ a/ s' |/ Y% F3 Q1 D( N$ @, MR-estimator of location, 位置R估计量
8 y) V2 |% Q |R-estimator of scale, 尺度R估计量
) y# q9 Q- ~3 F5 s8 d4 @& zRetrospective study, 回顾性调查
& a* h, J4 Q7 l5 v PRidge trace, 岭迹9 f1 g. U7 V* y$ n8 ?
Ridit analysis, Ridit分析
3 I8 b/ K2 _) t: l6 f, SRotation, 旋转
3 j4 |5 `. I- K. D% R; ^" GRounding, 舍入
4 V" h9 q. S3 |; [4 yRow, 行 ~0 T0 I7 O1 E& Y- a' \
Row effects, 行效应& o% h( M! m7 p
Row factor, 行因素
& b6 R# o% _0 Q9 j7 ERXC table, RXC表$ u+ i7 _8 Q# S- V' t
Sample, 样本; s3 X0 N6 W! x6 Q, b+ y- H$ M
Sample regression coefficient, 样本回归系数( r4 P( Q6 T- @1 Y* \; K4 X4 H1 Y
Sample size, 样本量
: Z5 _" `) h1 j( [2 g# rSample standard deviation, 样本标准差0 C [' Y' Y1 v1 `- H8 E B# {5 h
Sampling error, 抽样误差: h; \8 Q4 p! m2 @
SAS(Statistical analysis system ), SAS统计软件包0 r% u- P; P* v9 b# O! C
Scale, 尺度/量表: l: c$ b/ n2 f# C0 N
Scatter diagram, 散点图* [/ g, E) I! B$ K
Schematic plot, 示意图/简图
, D4 S1 j" X% Q9 ^Score test, 计分检验
2 R6 {. X4 |% @3 OScreening, 筛检" t+ m3 G+ f) f4 F" w
SEASON, 季节分析 * ~0 w/ g4 G$ ^2 c) f2 ]5 U! r
Second derivative, 二阶导数
' b1 Z* w- ^5 Q' ^8 W9 l! W3 Q/ tSecond principal component, 第二主成分
$ Y7 v7 v5 x+ G! W2 U; r0 \SEM (Structural equation modeling), 结构化方程模型 ; p/ r8 ]7 I2 g; P9 r( ~
Semi-logarithmic graph, 半对数图
6 `, P% H- ]1 f$ O* t1 y4 ZSemi-logarithmic paper, 半对数格纸
1 D k8 P* W! |- z; ?) \Sensitivity curve, 敏感度曲线+ T& A+ f; S/ t8 z( E5 E
Sequential analysis, 贯序分析' T* B4 ~) F; c
Sequential data set, 顺序数据集+ L- P. T! @1 A* D- d
Sequential design, 贯序设计7 q4 C- L+ P5 y
Sequential method, 贯序法
- Y+ j( T3 J' a- D! Y1 fSequential test, 贯序检验法
$ L7 l: B6 Y8 S' sSerial tests, 系列试验( A# s/ J, Y* ^
Short-cut method, 简捷法 # h$ C- N! T+ e5 ^; M
Sigmoid curve, S形曲线6 d) |* r$ d2 K( f% \) |& n3 y
Sign function, 正负号函数
# Y2 k T: A3 c) rSign test, 符号检验; N% l% o: \' c) U1 f
Signed rank, 符号秩
# {- K; x7 P2 q8 A- E9 QSignificance test, 显著性检验
( |# K, u3 T" A/ a2 [) S; T) h$ tSignificant figure, 有效数字
* R; i- y, [, _- ]7 RSimple cluster sampling, 简单整群抽样
2 E% A2 K: H! a- xSimple correlation, 简单相关
6 F- ~" q) ^6 t- CSimple random sampling, 简单随机抽样3 _3 f5 P4 ]; y2 h7 b
Simple regression, 简单回归. c2 T/ Q+ j! H. C
simple table, 简单表
" |: j* K0 g8 Y2 P5 WSine estimator, 正弦估计量
8 s+ M/ P0 C) F* J: I3 WSingle-valued estimate, 单值估计
. Z+ m3 D1 ]( P. YSingular matrix, 奇异矩阵+ _: j: E$ z' w3 z. ~* p
Skewed distribution, 偏斜分布
+ ]' G& }0 ~; \: ^2 A6 u- jSkewness, 偏度
: p9 W) N. }# l& t0 k' _, F5 OSlash distribution, 斜线分布
% l# b' d J/ w/ Z) YSlope, 斜率2 s% X+ \7 }$ P9 [) G, c. K d
Smirnov test, 斯米尔诺夫检验
! d2 Z6 U- d. lSource of variation, 变异来源
5 _7 k# X2 @+ n' M8 ?- cSpearman rank correlation, 斯皮尔曼等级相关7 y9 F! T5 |8 R* |/ }! L
Specific factor, 特殊因子
6 E1 [. R. O' ]. kSpecific factor variance, 特殊因子方差
8 h: q9 Z" P" M3 `Spectra , 频谱8 y9 E, F" z, F* ?
Spherical distribution, 球型正态分布" B) i) e1 D; M% c4 t7 l
Spread, 展布
# ?" W ^( \4 h4 v% ~8 ?& jSPSS(Statistical package for the social science), SPSS统计软件包) {: g. b" N7 p& z
Spurious correlation, 假性相关9 P( Z* r" G2 c+ y2 ]
Square root transformation, 平方根变换( j/ A; j; `" S5 x6 a1 |5 J+ s
Stabilizing variance, 稳定方差
6 t) J# E2 @2 G& J1 b0 x) x9 kStandard deviation, 标准差4 t& n4 l% x: O
Standard error, 标准误
. i- b7 a( ^$ g: ~- hStandard error of difference, 差别的标准误
" B% X% H+ u o- x; @Standard error of estimate, 标准估计误差
. f% S A3 [% ]Standard error of rate, 率的标准误
. y7 A/ d( `, B. |2 Y6 kStandard normal distribution, 标准正态分布
5 x& ?8 B9 _+ H& u- yStandardization, 标准化/ J( M* w0 j' q1 u2 J6 p: Y
Starting value, 起始值
- @; }; A# c# b' U' _Statistic, 统计量
$ u9 o0 s. N- L- y5 c3 o E2 v2 WStatistical control, 统计控制
: Z2 P' q$ z7 Q; N% w: i' a8 ^Statistical graph, 统计图
& _4 \* m& Y6 F' yStatistical inference, 统计推断
4 F m& Q6 C3 Z" ZStatistical table, 统计表6 m; A. J( x) N" l$ A( r, i7 n" B2 z3 Q
Steepest descent, 最速下降法7 w( ]/ L9 h' j0 a7 w
Stem and leaf display, 茎叶图1 F) U* ^* h& b; S6 v4 ~0 u
Step factor, 步长因子
5 L# E8 @4 t6 P9 _1 D9 O& g1 `9 W( dStepwise regression, 逐步回归
6 G3 K* k/ R! fStorage, 存
. d2 o! Z/ R U, i9 z AStrata, 层(复数)
& L; H, \$ R* H# V- PStratified sampling, 分层抽样6 r" h5 D% d6 d( X4 l/ p8 `
Stratified sampling, 分层抽样& `) r- t2 n% k2 a% m" o
Strength, 强度
( u- }. J7 n- e# fStringency, 严密性
& J( l" @/ A+ @- d W% D$ JStructural relationship, 结构关系
! k. s' C3 s% U* U/ QStudentized residual, 学生化残差/t化残差
5 D7 E0 l+ w% m& k( a" YSub-class numbers, 次级组含量
7 I1 a: U9 c* u6 hSubdividing, 分割* m! D, |. M" U6 X2 S5 U5 ~- T% Y4 L& c
Sufficient statistic, 充分统计量; z G% A1 E% n
Sum of products, 积和
7 ~# i' n) a% I7 \( `, kSum of squares, 离差平方和
; h. W2 i6 \5 H1 G# F$ r2 N5 qSum of squares about regression, 回归平方和! }; o$ {- J( ~5 K: F
Sum of squares between groups, 组间平方和
4 X" ~* G" h w ySum of squares of partial regression, 偏回归平方和
5 K5 t$ ~0 R) i. P, U% I, Q( PSure event, 必然事件
8 z$ p8 H# E/ g4 i% ASurvey, 调查0 |: `0 I) Y8 R/ O
Survival, 生存分析+ u6 g% A+ _/ ^
Survival rate, 生存率
- ]' O; z6 k! z" |6 {* j7 USuspended root gram, 悬吊根图
2 r5 |6 L9 c8 ]Symmetry, 对称
; K, m: p) G1 gSystematic error, 系统误差
! b% c4 n' h. j' J* z* i0 }Systematic sampling, 系统抽样9 O- h h9 t0 k# Z* W
Tags, 标签
& N* C( ?) \6 ~Tail area, 尾部面积8 l _) Y+ o. x. i3 c+ |; _' @4 `* G
Tail length, 尾长. _4 K2 R9 B, [) Z8 Q. L
Tail weight, 尾重: W/ D* {+ ]9 n
Tangent line, 切线
+ C4 |& D& D4 r g; x0 h( `Target distribution, 目标分布- F4 s# X3 A; N+ F. Q2 j
Taylor series, 泰勒级数5 E+ T$ _ P9 {
Tendency of dispersion, 离散趋势
' @3 C6 s1 n+ j' x% }7 TTesting of hypotheses, 假设检验. Z) |" ~# n6 g) C
Theoretical frequency, 理论频数
' V* f7 T/ o6 p4 a! P* e' ]8 \Time series, 时间序列
7 B z* }2 p5 K1 r# R/ o7 Y6 \Tolerance interval, 容忍区间; ?4 m" K) a$ V. o' l) f7 D- Y8 K% F7 V
Tolerance lower limit, 容忍下限 N7 | R) t: r8 i; L1 l0 f" }& G
Tolerance upper limit, 容忍上限6 T& n; G* ^& |0 j* _
Torsion, 扰率
. @# `( g; x! ?& @Total sum of square, 总平方和
5 ~ r0 J+ `) Z1 j% _6 zTotal variation, 总变异; x9 ^: h* K- m( J) n
Transformation, 转换# H. i# m# L; @. s: Q& S& Y
Treatment, 处理9 I7 y6 S7 K2 n% ]( y3 S
Trend, 趋势3 U7 c8 }3 O# y7 }# S
Trend of percentage, 百分比趋势
( A9 {, E0 v0 J) P( U' ]# {Trial, 试验# N5 `- t& K! y5 G4 `
Trial and error method, 试错法( a6 `/ K6 [$ b: U: L1 K x+ J/ u
Tuning constant, 细调常数
+ x8 W, |7 a& D+ W7 J3 @/ k2 n0 yTwo sided test, 双向检验
3 v: }- w. e9 d& z8 [9 D" H$ GTwo-stage least squares, 二阶最小平方7 @: c" w* w" ^
Two-stage sampling, 二阶段抽样
4 j; s" f1 x" h4 GTwo-tailed test, 双侧检验6 F8 b# M# z/ Y1 @3 n
Two-way analysis of variance, 双因素方差分析3 z7 o5 |+ ^! q+ Z
Two-way table, 双向表
% _' W, V |. a7 C; i7 |( \Type I error, 一类错误/α错误
9 x/ s0 p' y, m) f! T1 q+ NType II error, 二类错误/β错误
) T' E6 A$ R; xUMVU, 方差一致最小无偏估计简称
' S3 ~& V6 S- ?Unbiased estimate, 无偏估计
5 l. O* t# B1 y1 F* e" n- sUnconstrained nonlinear regression , 无约束非线性回归
2 Z" w v( D0 }Unequal subclass number, 不等次级组含量
* E) r& `! E( L! @8 _3 FUngrouped data, 不分组资料
7 j; a% y* x# v% d5 b8 `3 qUniform coordinate, 均匀坐标
4 L+ [# V' n" k H! fUniform distribution, 均匀分布1 z4 a& }6 Q* o0 l, J+ t0 k
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计/ I$ ~5 L5 x8 ^
Unit, 单元
' W/ T9 @( {8 f# @4 X9 P! RUnordered categories, 无序分类4 j) n! R/ j2 u2 d: K& I3 u- b
Upper limit, 上限+ e( _6 E. x1 e- c7 l6 \7 N+ Q3 n; N
Upward rank, 升秩# Z! X1 ?/ l! n
Vague concept, 模糊概念/ z! \6 N5 Q# n
Validity, 有效性+ m; ^4 |1 c9 e2 w6 W* M. x6 t1 c
VARCOMP (Variance component estimation), 方差元素估计
6 e+ N+ R, ~- o0 D1 `% [Variability, 变异性
; N+ v" o$ B* G' o1 _Variable, 变量
, }+ T: w3 a- ?* \$ H qVariance, 方差
9 Z! q% d& \; e& [. ?) xVariation, 变异
/ N# B5 |, J7 t( {4 eVarimax orthogonal rotation, 方差最大正交旋转
; ~/ }2 q5 ^0 H I$ a+ o9 }) cVolume of distribution, 容积) o# W3 ~* r+ @( X8 n- i
W test, W检验
' d8 T/ ?5 C2 E7 jWeibull distribution, 威布尔分布
8 M0 O0 K5 D9 ]( ^, K+ q; xWeight, 权数
$ y; D5 S8 M6 z4 gWeighted Chi-square test, 加权卡方检验/Cochran检验) L. t" M3 Y8 D' }# _* J& ?) b
Weighted linear regression method, 加权直线回归
4 Z4 {& I" v UWeighted mean, 加权平均数; D( W: i2 k" I0 y3 }1 M; `
Weighted mean square, 加权平均方差- y0 f! ? @" m% y8 e% {
Weighted sum of square, 加权平方和
5 t$ p) q8 z2 M3 XWeighting coefficient, 权重系数7 s: F% r+ j" Y8 j w$ B
Weighting method, 加权法 . i R7 b' j8 o3 `
W-estimation, W估计量
5 @+ n9 g5 f% c3 T2 LW-estimation of location, 位置W估计量
/ D) O% f9 e' TWidth, 宽度" ^# \" H$ S9 a+ j) z, {
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验& a# ?: [8 O: f5 Y2 K+ g& b
Wild point, 野点/狂点
7 o8 ~- H; v" Q+ iWild value, 野值/狂值
/ `+ W B; ^! V, ]6 RWinsorized mean, 缩尾均值
$ _ ]" J9 e; [Withdraw, 失访
" x2 x) S. w+ N! Z3 A) a" gYouden's index, 尤登指数
% a- D/ B" l* O- J. Z' `Z test, Z检验
- y+ c/ R$ H7 K& m& QZero correlation, 零相关
! s, a2 E, Q6 Z+ hZ-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看,没有账号?注册会员
x
|