S-Z
Sample, 样本
0 p- k) c; j' L4 \ x. w6 p7 DSample regression coefficient, 样本回归系数& E! V' P1 z& b" L- @9 C- G: C
Sample size, 样本量8 X: E( p$ V7 c) P
Sample standard deviation, 样本标准差
: j" H8 a3 ]9 sSampling error, 抽样误差
# r& S! Q4 W- j- z* t, MSAS(Statistical analysis system ), SAS统计软件包2 I X* J/ t% m2 Y4 H
Scale, 尺度/量表7 D% U5 E0 y3 r. p8 }6 k6 E$ e7 }
Scatter diagram, 散点图
& v4 N; i0 K( V X7 i, o/ J. V) QSchematic plot, 示意图/简图/ H( k1 Y8 Q6 M) x6 l
Score test, 计分检验
9 k) p9 Q8 u. Q. D% DScreening, 筛检
9 O% ]( ~7 Y; q3 p/ d* gSEASON, 季节分析 : z8 K" A8 G1 C+ R7 D
Second derivative, 二阶导数
- ?9 `5 p8 n! z$ A b/ R! ^, ESecond principal component, 第二主成分3 h+ I2 m# B' c; l: k
SEM (Structural equation modeling), 结构化方程模型 $ C: m/ B8 l+ w9 s* R
Semi-logarithmic graph, 半对数图( F0 q J4 ]& w5 L( i& Q
Semi-logarithmic paper, 半对数格纸
! S3 \1 b% o2 l3 I( l$ V, ~( XSensitivity curve, 敏感度曲线
& I4 E& F2 s) h" F! `Sequential analysis, 贯序分析$ m7 f$ h1 H4 ^ b, H, U
Sequential data set, 顺序数据集
+ }/ Z8 k4 Q6 _' G' ~5 l, uSequential design, 贯序设计
( K% Q4 T7 s: H4 G1 E( A+ Q9 FSequential method, 贯序法& }: k' s8 c" P1 ~8 F
Sequential test, 贯序检验法2 H' C/ n; X0 Z
Serial tests, 系列试验
5 c3 N# r! W9 [; `5 l9 u4 ?+ \Short-cut method, 简捷法 9 S% z7 a; { e; @
Sigmoid curve, S形曲线
6 s, ]: ]1 g: @6 GSign function, 正负号函数
; f* f8 y6 e M: z8 B! \Sign test, 符号检验
: R; X; m/ S }4 `; H8 MSigned rank, 符号秩* f/ {+ |8 ^0 B; V- K! K
Significance test, 显著性检验
9 N" R7 W8 M$ B. _# ?& ?" jSignificant figure, 有效数字
]0 A! }- t& I2 OSimple cluster sampling, 简单整群抽样
% ^' j) }0 R: x rSimple correlation, 简单相关* s; H* a; }/ l, f
Simple random sampling, 简单随机抽样2 W4 V+ P& K' F! A7 T9 \
Simple regression, 简单回归) M; b3 u6 c' O- O1 t3 y) ^
simple table, 简单表- R4 {. O7 K0 A5 J/ V
Sine estimator, 正弦估计量* I$ I% i+ F, }4 e. o+ y
Single-valued estimate, 单值估计1 o% E$ b6 C4 b% b, P+ w
Singular matrix, 奇异矩阵6 K) }5 N1 D6 j; M: u% P' D
Skewed distribution, 偏斜分布
& C' W" W n( A7 K7 Y! r5 R# ]Skewness, 偏度& b! \/ ]" M. A2 E% Z# [; `. ~
Slash distribution, 斜线分布7 }& k# T9 }9 v! i8 k! {
Slope, 斜率& w1 ^0 V( u3 E) r* w6 y0 g
Smirnov test, 斯米尔诺夫检验
6 r$ i4 A2 _ C$ n. k7 \3 W0 eSource of variation, 变异来源
( {- r; p. \' @0 p; [Spearman rank correlation, 斯皮尔曼等级相关
, w) Q7 |1 W/ R1 p# S* n! mSpecific factor, 特殊因子
& C, f: b) d# [3 X7 s; G2 PSpecific factor variance, 特殊因子方差
3 A7 q% \) ]* x& M$ ?Spectra , 频谱
3 N& k0 Z1 L/ B7 S( C% GSpherical distribution, 球型正态分布
! e( _# G: r u9 fSpread, 展布' w0 H' z7 X' s
SPSS(Statistical package for the social science), SPSS统计软件包4 q9 x. N1 {: R' M- ^
Spurious correlation, 假性相关# \2 j# V/ d. E' r6 H
Square root transformation, 平方根变换: W. n% R$ p" k
Stabilizing variance, 稳定方差1 Z% Y; t$ S6 ^& p. M) |
Standard deviation, 标准差( T2 [: i' l% v$ e/ `
Standard error, 标准误- V' D8 _" b) g' I3 m' y
Standard error of difference, 差别的标准误: c- k) k2 l7 E" s' I% M
Standard error of estimate, 标准估计误差! b& _7 _8 _6 M' Q
Standard error of rate, 率的标准误
6 P( b& B8 H4 R6 }; YStandard normal distribution, 标准正态分布$ h2 r, E4 b: E
Standardization, 标准化1 a& ^& P; m& k* ]; b
Starting value, 起始值
. ^7 N, P( ^* b2 q; w2 J0 iStatistic, 统计量
" k3 [3 \" I' ~0 tStatistical control, 统计控制- x. h: M2 O4 K
Statistical graph, 统计图
( f9 Q; ]! Y- DStatistical inference, 统计推断# k, a& _/ X! `% ]
Statistical table, 统计表
7 f3 x+ R1 x& }6 d1 w7 ]. tSteepest descent, 最速下降法: X+ Y$ l2 u8 z# K) M' n& F2 O
Stem and leaf display, 茎叶图" A8 W4 A9 E% W# H' H- G
Step factor, 步长因子* h+ {1 E. U, `- d- c" b
Stepwise regression, 逐步回归
" {7 N, ]- K" x( u/ u8 b/ cStorage, 存
! J9 F: c+ D4 \" y2 ~Strata, 层(复数)! [4 g. m9 J1 A1 _( O" Q2 k
Stratified sampling, 分层抽样
8 e+ _" y; N2 |1 F! V* f( ZStratified sampling, 分层抽样
8 T: Q" o9 q& _' L5 y* J# wStrength, 强度
6 u6 @7 Z5 @. BStringency, 严密性
I3 { h) j- UStructural relationship, 结构关系
. c% Z5 ~! W$ s- i) k. l' `9 J7 [* UStudentized residual, 学生化残差/t化残差
C4 P- O" d" ]) D0 fSub-class numbers, 次级组含量, T1 ^ U# r1 C$ K) E. \) g
Subdividing, 分割
5 y8 i, J1 a# c& D. s/ K& ^( tSufficient statistic, 充分统计量# t# _8 t f8 G7 M# S
Sum of products, 积和# E7 d" s/ o; X! s6 e5 s( [( F6 H
Sum of squares, 离差平方和
3 V( ]* y4 s$ P' O$ v& p+ ~Sum of squares about regression, 回归平方和
: s9 l4 m6 ~: Z7 ?6 R" }- P" ^1 t/ wSum of squares between groups, 组间平方和
- a% F9 I5 D: a8 iSum of squares of partial regression, 偏回归平方和
0 h3 z' L: K7 ^& ^; b) f9 a. xSure event, 必然事件
3 _0 O# E+ V/ s* Y1 ^, jSurvey, 调查
, s9 I& R# y% \2 R) o+ zSurvival, 生存分析: E4 K4 p {/ T! A b! m
Survival rate, 生存率
7 j, L. \: ?# i, S9 rSuspended root gram, 悬吊根图
, G) X3 O. s9 z5 m) |6 q/ c( O* nSymmetry, 对称
) L: ]$ l! a& W, _; [7 z( ASystematic error, 系统误差6 ?3 Z7 Z$ C% j( }" c* I' f
Systematic sampling, 系统抽样
s: J+ A- `3 H: C, k& l! g3 ETags, 标签6 D, M7 o: n% Q" t, Z8 ~
Tail area, 尾部面积; {, |0 f5 I4 ]
Tail length, 尾长
( v: p* g2 I; Q6 v6 n. qTail weight, 尾重
; F7 Y: A& t( I8 D0 D3 BTangent line, 切线
# [4 [- ~0 w3 @Target distribution, 目标分布9 O$ f p* K- e7 e- R% M6 C8 _" W t
Taylor series, 泰勒级数! f6 q) x3 ~5 d' h3 {6 S
Tendency of dispersion, 离散趋势
1 _3 I, K- Q4 ~6 oTesting of hypotheses, 假设检验' h+ v, Y( @+ o4 c" L0 |5 w- X
Theoretical frequency, 理论频数( Y0 X6 o0 H# i$ L% W. s
Time series, 时间序列
' V' D! i, t5 n- E2 o* `Tolerance interval, 容忍区间: A5 A$ t. L$ M
Tolerance lower limit, 容忍下限% v* @ |+ K9 L d/ Z
Tolerance upper limit, 容忍上限) j/ j D' G# g+ D, \: c
Torsion, 扰率0 G9 e; I, \6 C$ y. \, ^
Total sum of square, 总平方和4 w9 `+ I1 L: u$ e' \% V- E% \
Total variation, 总变异4 d: Q) C: E: d1 M+ n
Transformation, 转换5 i h( P8 l }6 ?3 W! L
Treatment, 处理
, e6 E) u2 ]# UTrend, 趋势3 N* x; x6 t( J7 p, ]% ^
Trend of percentage, 百分比趋势
- Z( [/ ^/ v, y+ u) VTrial, 试验0 ^2 T: |8 H0 e M9 [
Trial and error method, 试错法! q9 O9 T' E9 U$ _
Tuning constant, 细调常数% M% L+ U; L" s1 b( y* M9 z
Two sided test, 双向检验
! c$ d+ P) ?4 ]1 C0 n: x' _" ATwo-stage least squares, 二阶最小平方* }3 e. D0 d+ S( G
Two-stage sampling, 二阶段抽样
7 @: q7 c" }, _, ^% bTwo-tailed test, 双侧检验" u) I+ I" V' |3 V$ h0 M
Two-way analysis of variance, 双因素方差分析" F9 Q; A, B- \) ?
Two-way table, 双向表4 O, N f: h; i8 _
Type I error, 一类错误/α错误
& n, ]: K; [$ A) V# L9 Y. EType II error, 二类错误/β错误# J& C( o+ K% M& i
UMVU, 方差一致最小无偏估计简称: _ D, n+ }/ W
Unbiased estimate, 无偏估计4 ^( S0 l0 \8 |; }/ M# J# b& s% v( V
Unconstrained nonlinear regression , 无约束非线性回归& r" M) {& K% t5 `
Unequal subclass number, 不等次级组含量/ A! P/ D+ g5 z/ p$ C5 ^
Ungrouped data, 不分组资料$ R+ S$ R+ E2 N9 l5 ^/ ^1 u! Z
Uniform coordinate, 均匀坐标1 P2 j& y1 J$ g6 N \# V W
Uniform distribution, 均匀分布( }" X& n5 x$ }' F6 ~2 u
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计: l; K* D" g+ }1 l8 B0 p# q
Unit, 单元3 Q4 F& v8 {: Z7 ]. H, U& C& g( O$ M/ n
Unordered categories, 无序分类
/ ?5 ?& {& b7 N. mUpper limit, 上限
$ a; d( e% |9 b7 _' L3 kUpward rank, 升秩
7 F7 S% p" r" o# M7 Q9 x9 HVague concept, 模糊概念
3 s ^9 T* g9 k4 C, _) uValidity, 有效性
% Y$ {2 W8 o1 k3 X, D9 U$ R, z/ D( x8 ~VARCOMP (Variance component estimation), 方差元素估计
, ]1 r0 V, Z( W5 b9 z) fVariability, 变异性6 x/ e1 g5 |( ?4 `% }5 Z# y" u0 E
Variable, 变量
1 f2 K+ i6 R/ d6 F# O! |Variance, 方差
+ X* y+ x6 r1 X( Y$ i4 O) cVariation, 变异9 U3 F, R4 a3 G8 w
Varimax orthogonal rotation, 方差最大正交旋转7 d0 `, Y/ {6 r4 S
Volume of distribution, 容积5 @3 f! Z$ |; ?- h) X1 y
W test, W检验
4 z" e6 x5 d u6 `! K; I6 L) AWeibull distribution, 威布尔分布" p1 L1 ^$ l, d5 g
Weight, 权数
& v: k- E+ e; o9 |' QWeighted Chi-square test, 加权卡方检验/Cochran检验/ b4 T7 Z9 S0 J& _0 g3 G4 x& x
Weighted linear regression method, 加权直线回归
. W B& F* v7 p- ~& {Weighted mean, 加权平均数5 B! z4 ^; |/ k9 e3 q
Weighted mean square, 加权平均方差2 a2 ]' j1 \( }
Weighted sum of square, 加权平方和
, L1 C$ P% k4 t7 @; Z. {/ FWeighting coefficient, 权重系数6 ^$ c }( \2 s ]5 [+ }: V6 i" S
Weighting method, 加权法
) m0 I- |% U1 k) [; \W-estimation, W估计量: c* O+ M/ y$ Y0 g
W-estimation of location, 位置W估计量
& r0 g6 b4 ]2 d9 x7 Y/ wWidth, 宽度
1 `' f4 V9 W! l7 M& l+ y" `Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
% w# A' g: H$ Q- s9 E2 S9 iWild point, 野点/狂点3 k/ y# d9 V* E
Wild value, 野值/狂值
* R U. _9 V6 @; ^Winsorized mean, 缩尾均值
8 H; |6 w9 s5 SWithdraw, 失访
9 a0 L* ^1 H: pYouden's index, 尤登指数
" P; o6 N4 _5 C8 V- K# P% _9 T2 uZ test, Z检验
- V3 s; T( F( B7 u! ]( Y7 ]- KZero correlation, 零相关: |! W- O* F2 N) s/ a l
Z-transformation, Z变换
M-R
Main effect, 主效应) S4 m; Q; P ^# @7 Y
Major heading, 主辞标目7 {" x! ?0 E/ m3 g9 v% s
Marginal density function, 边缘密度函数6 D* R* L* D8 A2 @% K, F, W5 W
Marginal probability, 边缘概率
* L7 q) e u6 {! y: \( |. kMarginal probability distribution, 边缘概率分布5 X/ O) g( w- Z! N' W; U. p& ^! g
Matched data, 配对资料7 r% s/ \2 e; q0 S* K& e
Matched distribution, 匹配过分布
# \* a, W% v8 M. w5 c1 qMatching of distribution, 分布的匹配
6 _* _; P* B! g* j; T6 C# }Matching of transformation, 变换的匹配
( ~( _) D2 O) X1 y9 ?Mathematical expectation, 数学期望
% Q# x B* {1 h: tMathematical model, 数学模型
0 ~; e+ |0 Z: p, r' R! E" r8 oMaximum L-estimator, 极大极小L 估计量
2 ]; j2 ^$ N" c, ~1 j- l$ R! CMaximum likelihood method, 最大似然法6 n$ `- Y8 a! k/ V
Mean, 均数
: ~- i+ {, t2 `5 u6 S% ], JMean squares between groups, 组间均方5 r: _# h! @7 O, q) y
Mean squares within group, 组内均方$ J0 s. e H L* [
Means (Compare means), 均值-均值比较
9 D, K; a8 l! L2 h& }, {Median, 中位数 t: X/ @9 x6 @: W+ b" Z8 t
Median effective dose, 半数效量
2 n7 j' B8 Y( a* L/ KMedian lethal dose, 半数致死量! B/ {3 T8 |0 L' n5 E5 }/ q. x1 J" n
Median polish, 中位数平滑6 W( i( e" a' Z* i5 H @
Median test, 中位数检验
; z9 ~1 M2 h+ e# J( C Y$ mMinimal sufficient statistic, 最小充分统计量% q$ m/ } A* E4 [" \7 w
Minimum distance estimation, 最小距离估计, ~( n- F" d' Q: K5 R$ l6 s
Minimum effective dose, 最小有效量# P4 k4 u, ?# o* g4 a: x( t
Minimum lethal dose, 最小致死量
+ X8 i" g# e$ y tMinimum variance estimator, 最小方差估计量
- D% J* L7 u" |5 `4 A1 H9 T- j2 {MINITAB, 统计软件包: H7 N9 p W3 E
Minor heading, 宾词标目- |: R6 O+ c. T: {8 o) ~4 [# @3 e
Missing data, 缺失值 ( p h0 E; U6 o7 T
Model specification, 模型的确定
, s* c( X/ g1 d* L1 RModeling Statistics , 模型统计
) k/ c( }# I8 r9 Y/ h" r' K7 mModels for outliers, 离群值模型
$ [% s0 r/ z0 j9 U4 kModifying the model, 模型的修正
; o* `) g) C$ ?2 q( lModulus of continuity, 连续性模
8 S0 e; q2 ~# e+ DMorbidity, 发病率 1 r& V3 X8 Q! c) a
Most favorable configuration, 最有利构形5 \5 e# a" C) O2 R/ {
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
, w1 c# v" d( r2 J7 MMultinomial Logistic Regression , 多项逻辑斯蒂回归
6 p* S v* {, Q$ m) ~) b/ XMultiple comparison, 多重比较& ?' q# n- ~ u' ?7 m: ~6 A3 H/ n% G
Multiple correlation , 复相关
! W' v5 j* X5 iMultiple covariance, 多元协方差
$ A! ?$ j+ T/ P+ tMultiple linear regression, 多元线性回归& `8 O" M7 d9 @6 e( b, f
Multiple response , 多重选项0 Y' L) r( o5 {1 z1 i8 K
Multiple solutions, 多解
. J3 u0 x4 f( IMultiplication theorem, 乘法定理
/ N3 F$ \$ c5 Q* ~2 E( ~' [Multiresponse, 多元响应
$ v% V, u7 I8 ]$ {) X( DMulti-stage sampling, 多阶段抽样7 R" Q8 t* ~* B$ G
Multivariate T distribution, 多元T分布" a- h: v O2 `
Mutual exclusive, 互不相容# e* q1 @: W0 g6 ^
Mutual independence, 互相独立
# M9 U% H/ I7 R. P2 p9 ZNatural boundary, 自然边界) K' @/ H" @% W5 o5 u5 {
Natural dead, 自然死亡
- e" a, N9 }) p: F- TNatural zero, 自然零1 e1 x9 ~& f3 |
Negative correlation, 负相关
* N, _) c3 a; SNegative linear correlation, 负线性相关
( T& l6 R! K+ ^& H) _Negatively skewed, 负偏2 m `% R$ ^; t2 k1 f" L
Newman-Keuls method, q检验
; s: z( Q4 r1 J/ R9 D) e/ x: \4 iNK method, q检验
; `" z! z. |& z3 vNo statistical significance, 无统计意义( f, Q. |' z9 m- X+ L8 b
Nominal variable, 名义变量! f. b$ A: |) n
Nonconstancy of variability, 变异的非定常性
; k9 {: y" f# u# k# `4 W; YNonlinear regression, 非线性相关( q- o8 M I) s: @
Nonparametric statistics, 非参数统计
* Q, r* R( Y5 TNonparametric test, 非参数检验8 ] o- H9 n2 R1 a
Nonparametric tests, 非参数检验
; S& B4 e% Y6 L5 r( @Normal deviate, 正态离差
, e# x5 F+ C& o$ I5 M$ B# n& p0 wNormal distribution, 正态分布7 M% i& B8 i- S4 I
Normal equation, 正规方程组 M& G, V3 c$ q
Normal ranges, 正常范围
1 H& @6 ?/ i2 z1 I- J7 x. F& BNormal value, 正常值& q" x0 M( z* F, A% H
Nuisance parameter, 多余参数/讨厌参数
3 u9 y2 D9 \, s) _7 x$ zNull hypothesis, 无效假设
3 @6 K+ \8 P; r% y1 _% Y4 {Numerical variable, 数值变量4 R8 \3 a4 N9 n" I
Objective function, 目标函数. r- H2 k+ o9 b0 V& k1 }
Observation unit, 观察单位
6 C5 l% e" F/ r8 j, @( [Observed value, 观察值
" K' b+ z) G; j1 eOne sided test, 单侧检验 Z. V) X# Z3 ^% @7 j
One-way analysis of variance, 单因素方差分析, l& m8 X% ~4 J* `; [6 q
Oneway ANOVA , 单因素方差分析
1 c9 W$ Z9 `# A# BOpen sequential trial, 开放型序贯设计5 q, j6 A. w% @3 T$ J, r/ d
Optrim, 优切尾0 o1 f% m k! A W1 \( z2 |0 o/ [
Optrim efficiency, 优切尾效率- |$ v6 B6 i% E8 W6 s- R
Order statistics, 顺序统计量+ S% c- N( o% q9 q* M$ ]* {- U
Ordered categories, 有序分类
3 W9 ]2 n- ?* ^Ordinal logistic regression , 序数逻辑斯蒂回归: v2 }! b2 [' b5 P {8 j9 @; y
Ordinal variable, 有序变量7 z$ o. U# c- J }( \% F
Orthogonal basis, 正交基! C5 Z3 ^7 O3 M. D
Orthogonal design, 正交试验设计
/ J& P C! o3 u. O) Z0 MOrthogonality conditions, 正交条件
; X0 J7 r" i) G' u9 \ORTHOPLAN, 正交设计
, m! v% W" J8 g8 } z" gOutlier cutoffs, 离群值截断点
# U1 J% K' l3 kOutliers, 极端值
# T3 E3 K( ^: e6 H0 F! TOVERALS , 多组变量的非线性正规相关
, a! A" k: U5 E6 C' t& v6 YOvershoot, 迭代过度
, r V D% }6 {( \3 gPaired design, 配对设计
$ J n4 R/ K& H) z: d# x# LPaired sample, 配对样本
/ N- h( i3 g8 W. t8 QPairwise slopes, 成对斜率% Y+ A1 P6 Q* |) A4 @$ h
Parabola, 抛物线4 r5 V$ A- \! p/ y% u1 F0 q& S
Parallel tests, 平行试验, {( [5 ^( R X4 z: \ [/ l7 Y5 V
Parameter, 参数5 f' l# N: e5 R! C, P- v
Parametric statistics, 参数统计
4 B1 \$ B# |. Q; p5 HParametric test, 参数检验
& W% J! u1 I, x. u/ T4 g/ v* g- w. lPartial correlation, 偏相关
( t; D- h& W& B1 [Partial regression, 偏回归 M9 Y! \5 u2 a7 h- h
Partial sorting, 偏排序% C( W! t% D, }( Z& |
Partials residuals, 偏残差+ {! N0 f2 D* }) Z' G* _+ {3 |
Pattern, 模式/ A k5 l4 u; w' X7 A
Pearson curves, 皮尔逊曲线
8 `9 @9 W; u7 V. x6 I1 P* `Peeling, 退层 ^7 b3 m, [6 O2 V% Z+ D
Percent bar graph, 百分条形图 u4 {% z# S/ V& W. K9 v' `* [9 @
Percentage, 百分比. @4 Z+ }7 i: A
Percentile, 百分位数2 l0 g3 Y' f4 b* J* ~, i, I
Percentile curves, 百分位曲线* _# ?# y$ t$ n( T% P
Periodicity, 周期性# R7 f4 n7 u/ T4 x5 w
Permutation, 排列
9 I4 q6 [: ^+ T7 B7 `& hP-estimator, P估计量 y) x4 x | w! D
Pie graph, 饼图, K, W5 s/ v& U1 }0 p
Pitman estimator, 皮特曼估计量
" O/ {9 n V7 X( O/ U( KPivot, 枢轴量
1 R6 S) f/ f% G/ }+ @Planar, 平坦
+ \0 W( w3 D8 B1 j5 I4 tPlanar assumption, 平面的假设5 M$ f& }" m( t4 Z6 ~# x
PLANCARDS, 生成试验的计划卡* d/ q7 J7 T: J& Q' _+ w2 y
Point estimation, 点估计 o, V& j, ]1 m- ?: c
Poisson distribution, 泊松分布
: G4 m3 ?0 v1 ?: mPolishing, 平滑3 M2 U0 u. Z g* ?/ P: z
Polled standard deviation, 合并标准差6 x) c5 c% Z0 z
Polled variance, 合并方差
5 J% m0 A8 d! Z- I2 VPolygon, 多边图
" ~5 R! d! }/ Y7 q* g: ?Polynomial, 多项式
- C) F6 C3 B5 Y0 Z i6 k9 OPolynomial curve, 多项式曲线& d% s( F" b ?) G
Population, 总体* Y* {; I* P/ a9 r
Population attributable risk, 人群归因危险度! |9 v. w. q% s3 E
Positive correlation, 正相关
. V1 n6 Q4 o/ m8 q! y) s. BPositively skewed, 正偏
2 u* X" I: W3 S C* BPosterior distribution, 后验分布
, O M3 |8 d6 y, ?Power of a test, 检验效能6 P% |! j9 z1 R5 ] t5 t n
Precision, 精密度! y6 o6 @% \; {, l# k- ]
Predicted value, 预测值
e# Q9 X2 u% b* NPreliminary analysis, 预备性分析
. v C- |% i9 C. V9 y, {% JPrincipal component analysis, 主成分分析
( g% n5 n1 ~: u" M6 i' VPrior distribution, 先验分布/ F. u( S. L; T) o8 w2 J
Prior probability, 先验概率
: r; o" O9 j2 V. HProbabilistic model, 概率模型
. s* n$ x2 t# f" j; L2 c- E( Pprobability, 概率
# a1 G$ @& n- k, L. DProbability density, 概率密度
' ^, l, ^9 u, EProduct moment, 乘积矩/协方差: ^1 y4 i* p, e0 l$ y; U( n1 G
Profile trace, 截面迹图
5 ` G$ N3 b$ W+ l! T4 FProportion, 比/构成比
! x X0 S8 W% P0 n( m2 R# A' \8 _Proportion allocation in stratified random sampling, 按比例分层随机抽样
; S& y3 t9 }" n& yProportionate, 成比例6 Z3 f d5 B# x
Proportionate sub-class numbers, 成比例次级组含量
3 W' k" \& B% D. b4 ~ z- i2 aProspective study, 前瞻性调查# A& u& s3 E0 N% e
Proximities, 亲近性
- @; k( ?! J4 }" iPseudo F test, 近似F检验* A! O) @- x* Q9 f* ~0 ^: l" `
Pseudo model, 近似模型
3 O) w' L+ E, n1 b0 HPseudosigma, 伪标准差
/ Q: H3 n9 p% R. j4 n7 fPurposive sampling, 有目的抽样8 D5 ]& [% r( V$ V
QR decomposition, QR分解
- R8 t/ D! W& Q: h4 ^: N3 zQuadratic approximation, 二次近似
- d: H' L) S* E* d; hQualitative classification, 属性分类" r2 X9 H3 _- I4 c+ g* s. [
Qualitative method, 定性方法. x0 T# n3 ]; E8 E
Quantile-quantile plot, 分位数-分位数图/Q-Q图
" ~ M$ _+ o' RQuantitative analysis, 定量分析
$ g+ v) ?) D( L# E- l& [6 F/ r8 LQuartile, 四分位数# s1 D0 m- h5 s, ^9 P; Y
Quick Cluster, 快速聚类2 n+ h$ j/ d( S7 W
Radix sort, 基数排序4 F) X$ M8 ^# e5 x1 F. x, D3 v
Random allocation, 随机化分组6 o* A* Y. o/ S0 B- @3 W8 ?0 M
Random blocks design, 随机区组设计
# Y2 L/ N( X/ v$ `3 VRandom event, 随机事件
5 Q3 C6 k5 R: \- c9 i6 Q/ SRandomization, 随机化( r' k( A0 a( U% o! ?% Y
Range, 极差/全距
" f& d, P; z* G! {4 xRank correlation, 等级相关. a% Q2 S8 D: r+ h L/ y
Rank sum test, 秩和检验8 K/ h7 _8 d/ F" d/ O% b
Rank test, 秩检验
* z; E* x i8 Y7 B+ fRanked data, 等级资料. T/ t( S8 V! @$ n* G# r7 Q; d
Rate, 比率+ L {6 b; g+ j8 C7 c
Ratio, 比例
4 j; j: x: Q9 k* t9 n0 NRaw data, 原始资料. ]! E4 _6 Y3 {! Q0 H( x. B
Raw residual, 原始残差* d. Y' u# B% o6 Q; I+ g9 f
Rayleigh's test, 雷氏检验- h/ B W/ P1 S& x
Rayleigh's Z, 雷氏Z值 & ~9 f/ C5 C, h
Reciprocal, 倒数
' D# X+ p0 C+ N! j( eReciprocal transformation, 倒数变换5 d" V$ A( M; P0 I, V; \
Recording, 记录. P3 n0 ~4 U2 T+ ?! C
Redescending estimators, 回降估计量. G; G$ j/ n& f, T0 i+ I
Reducing dimensions, 降维6 { ^$ M( F$ k# q/ ?
Re-expression, 重新表达
3 I# N( v% w+ rReference set, 标准组: V2 i2 D/ _/ z! O; C2 F
Region of acceptance, 接受域
. e! m/ ^8 o9 F2 d3 }Regression coefficient, 回归系数
, t/ i( K) Z, }" `1 cRegression sum of square, 回归平方和 % l9 d2 {* w% U+ M- w8 i& N9 y# @" X
Rejection point, 拒绝点
5 a" D1 ^% O& [7 \7 H/ d# cRelative dispersion, 相对离散度
# G6 o3 |/ \& e! b. x2 e2 _& s% pRelative number, 相对数
. _! `! D! E& v! ` y, Y3 x/ @Reliability, 可靠性
" D0 b3 `, X7 p: E9 l4 p) ?Reparametrization, 重新设置参数* i7 c8 ?+ }. L/ j) p2 U
Replication, 重复
4 N$ m" f4 F: {" |6 pReport Summaries, 报告摘要
, c0 K& W# t: P4 CResidual sum of square, 剩余平方和# N. o j' b9 `5 m
Resistance, 耐抗性
" B* o1 H- X- m a! Q0 e/ j. Q; w* FResistant line, 耐抗线
8 `' v" P3 O5 S, o8 l$ a/ aResistant technique, 耐抗技术( p) P* e# F* J0 s4 V* Q5 P1 ]; y
R-estimator of location, 位置R估计量; l: f6 k( r& {$ Q
R-estimator of scale, 尺度R估计量6 @, ^6 ^* x: k3 ~; V$ J
Retrospective study, 回顾性调查 q/ A5 G1 }% K7 i
Ridge trace, 岭迹7 i6 Q9 X/ \5 b! I+ B& G J/ W
Ridit analysis, Ridit分析
8 i, P7 l$ G, _# C0 V4 bRotation, 旋转1 d* H- c+ w7 [1 L1 Z+ R
Rounding, 舍入( b' b: M6 p& u% o
Row, 行; L# ?5 G- ~1 x0 S, ~
Row effects, 行效应# M3 y ]$ E0 C" Z8 r' B
Row factor, 行因素" A! m: C8 r1 W! f+ Q* z+ a6 r
RXC table, RXC表
E-L
Effect, 实验效应: j+ ?* b1 G- {6 W$ \( S
Eigenvalue, 特征值1 e" h8 w; S. q2 m9 N
Eigenvector, 特征向量) D" H) V7 v. w
Ellipse, 椭圆
: ?2 {7 R4 a7 P3 k) ^% O3 UEmpirical distribution, 经验分布
8 K4 U4 r- m9 rEmpirical probability, 经验概率单位
7 b q* E/ r3 ]7 ?9 fEnumeration data, 计数资料 D. J8 E& A1 v" z5 O
Equal sun-class number, 相等次级组含量 ! F4 u' N6 W2 C# Z8 ~) e
Equally likely, 等可能& Z0 z, {# y5 h+ s/ b/ P
Equivariance, 同变性 O* h) p; @3 a J
Error, 误差/错误; j0 l8 [% N f' _2 m. _
Error of estimate, 估计误差 w* D' Y1 `0 l/ Z, S E( h
Error type I, 第一类错误. U1 `8 Q; s% i+ ~, g* p
Error type II, 第二类错误
# L# u2 u/ E/ p1 J. S9 g( i( IEstimand, 被估量
# e4 C8 n( k: {9 ~Estimated error mean squares, 估计误差均方
* l1 K" x! t* b6 C" w/ e; T# H: lEstimated error sum of squares, 估计误差平方和4 H% y- Y$ t; q1 b- ], f5 V: @
Euclidean distance, 欧式距离
+ r' G9 |0 J3 y. y2 y/ a# hEvent, 事件+ R7 t& w' I' \+ g* @; `$ t g
Event, 事件
! S& f3 o0 P& P9 H dExceptional data point, 异常数据点
. J& V( Q$ x4 X/ X" Z2 NExpectation plane, 期望平面6 D+ X. Q$ E; b' b; @
Expectation surface, 期望曲面
7 X k2 h, w- T& n OExpected values, 期望值
4 H% Z ^; @/ a, n8 CExperiment, 实验" ^5 {$ j6 A" ^# E4 R/ w3 W
Experimental sampling, 试验抽样( x6 g% G" p! o7 ?+ ?+ P
Experimental unit, 试验单位
( G& x! O) V% }! C& B) f3 X. gExplanatory variable, 说明变量0 |+ b! j p. E
Exploratory data analysis, 探索性数据分析/ D0 }8 H8 \# F& Y z" N( A
Explore Summarize, 探索-摘要
) o$ \& A4 G0 S; v8 G0 _Exponential curve, 指数曲线
5 w# I6 J7 [6 y# JExponential growth, 指数式增长
4 N. w: _3 x$ H' y) B' ~) BEXSMOOTH, 指数平滑方法
5 q) y* ~+ o2 u, {' V) oExtended fit, 扩充拟合: L- d2 Y7 ? _* ]9 |! v& A
Extra parameter, 附加参数, x$ m6 k7 I- ~$ g& t* x
Extrapolation, 外推法
$ a( Q7 Y, R- {( F* J4 KExtreme observation, 末端观测值
) Q q% `+ F% C+ _2 d) AExtremes, 极端值/极值
- }5 u4 J0 D6 R9 G% f2 N6 g- P: sF distribution, F分布0 k9 N0 r& {. {# W! Y
F test, F检验( X6 R/ K" a- R5 R+ m
Factor, 因素/因子
. ~( M h9 m6 g! aFactor analysis, 因子分析
! [* K/ g4 O3 r7 T" a$ D( ~Factor Analysis, 因子分析! Z1 h5 g. b1 h6 U2 N4 n+ E
Factor score, 因子得分
+ y& `; V, R, P/ TFactorial, 阶乘
9 r5 F _( v% G/ M) j* X% iFactorial design, 析因试验设计
' x3 l4 _& Y7 K5 N- O/ ]9 X3 hFalse negative, 假阴性
) h0 o* ^$ P2 Z7 @* N" x5 t. vFalse negative error, 假阴性错误
5 I" c" r) @: O% l' ~Family of distributions, 分布族
' e1 b( t" }- R' y6 hFamily of estimators, 估计量族! Z0 ], ^4 y; ^: O
Fanning, 扇面
s# U% I9 D+ V" U. JFatality rate, 病死率
+ U; B) ~. T8 m3 N$ AField investigation, 现场调查
8 [8 ~' I0 a5 M( k+ s9 Z/ q# E" K) [Field survey, 现场调查* p( |' x6 g6 z: S0 C
Finite population, 有限总体
4 Y0 d3 q+ {2 T, z# E7 WFinite-sample, 有限样本
! f G# W/ l1 H- c: O( A9 D' XFirst derivative, 一阶导数 ' e& x/ B9 W5 V S# q I
First principal component, 第一主成分
; C: C8 a/ I, {2 ^4 T8 a& D' \First quartile, 第一四分位数
6 t2 u0 W2 f w$ S* I: B4 XFisher information, 费雪信息量# n2 R8 I6 h3 G; r" _8 }
Fitted value, 拟合值
8 r* l. a+ ~# D9 r% XFitting a curve, 曲线拟合
- ?7 v+ T6 ~( U9 O0 `0 uFixed base, 定基
' h& t9 {+ n2 G; L! A; E9 TFluctuation, 随机起伏
1 m! K. p1 \# R5 ?, b) QForecast, 预测+ Q* V! b) K$ g: D; B
Four fold table, 四格表
, d$ s) Q5 G( j. dFourth, 四分点
7 Y5 V2 y2 T6 u! i! x9 bFraction blow, 左侧比率; r6 B, }: H) P1 ^
Fractional error, 相对误差
* \; v/ h3 V$ g9 JFrequency, 频率
: t6 M' O H% ?: q5 b- ZFrequency polygon, 频数多边图
- W$ d7 y6 A( {6 @2 c! cFrontier point, 界限点& e9 R* N4 n$ m( h# ^- a4 c
Function relationship, 泛函关系
; {( N) p! }& i0 U, @/ TGamma distribution, 伽玛分布
# W* K5 v* E- h6 k; u7 p+ F6 p3 wGauss increment, 高斯增量
: A& c, u4 A2 X! i5 a5 p+ S: BGaussian distribution, 高斯分布/正态分布' |) k* b- c( ]3 O3 d& n7 z+ e
Gauss-Newton increment, 高斯-牛顿增量
/ U1 y& q. H* `! _1 [# UGeneral census, 全面普查7 N+ H$ |7 g1 m/ R3 B. [. a
GENLOG (Generalized liner models), 广义线性模型
- I# M* i2 _3 LGeometric mean, 几何平均数
, z4 ?! ^" s }2 ^2 ^Gini's mean difference, 基尼均差
, Y2 n5 X4 X; W5 t6 n; g* JGLM (General liner models), 通用线性模型
: c" b/ i( s4 v7 W: |; _! NGoodness of fit, 拟和优度/配合度
) j5 @- @, W- X9 LGradient of determinant, 行列式的梯度; _+ g8 |' q0 x' {. D5 B: _3 `
Graeco-Latin square, 希腊拉丁方
% [& y3 ?* ~1 R* NGrand mean, 总均值8 T) i f1 ?: k
Gross errors, 重大错误$ R* [# T' H0 `0 W' `; @/ P' @
Gross-error sensitivity, 大错敏感度
1 p0 S% s5 P2 a6 s* q) rGroup averages, 分组平均
1 @. g$ ?: x- K/ ~Grouped data, 分组资料
( p5 v+ q7 h, v0 x+ qGuessed mean, 假定平均数: o" Q3 v) l: ?/ y: T
Half-life, 半衰期
: ?5 Q( o7 Z+ l' sHampel M-estimators, 汉佩尔M估计量
0 f9 k( O1 L4 F! F3 A1 f" J. NHappenstance, 偶然事件+ q( ]0 U7 ~ L* G. `& L j1 W& s
Harmonic mean, 调和均数
* c0 [- p5 d0 n- cHazard function, 风险均数
/ z6 M6 C, P6 MHazard rate, 风险率1 h4 V2 B9 |* q" X8 g6 M0 N o9 ^
Heading, 标目 / i9 n' c; {) k% H
Heavy-tailed distribution, 重尾分布
( Z) Z8 x3 E2 a7 P) c# @+ ]( bHessian array, 海森立体阵2 ^+ L4 k I! C
Heterogeneity, 不同质
' U6 G9 Q) u& e0 P0 VHeterogeneity of variance, 方差不齐
8 j# V: U( ?* h& f/ ~9 aHierarchical classification, 组内分组8 S3 }" m5 s+ Y( E! B7 [# z6 u: [
Hierarchical clustering method, 系统聚类法
) C' u: V4 }' V1 CHigh-leverage point, 高杠杆率点
2 y$ k+ ?3 m: n7 y5 BHILOGLINEAR, 多维列联表的层次对数线性模型3 E$ r! H( Z9 z/ c
Hinge, 折叶点
+ @% k8 X3 ~. E7 OHistogram, 直方图
: G: M9 a; u2 A1 z* s7 `2 d; _Historical cohort study, 历史性队列研究
+ f& ^- r; A1 a" V% D/ v2 }Holes, 空洞$ r& v$ _& C) O9 D/ h
HOMALS, 多重响应分析
* ~3 S) E. f* ^8 o% ] f8 cHomogeneity of variance, 方差齐性
1 Y! z+ i% C jHomogeneity test, 齐性检验
: v V2 [. P" v; W( wHuber M-estimators, 休伯M估计量
! F8 C H+ L$ E) X- ?" k4 B4 I4 k( OHyperbola, 双曲线
8 F* D! C; L" n' e1 z/ ZHypothesis testing, 假设检验
+ X b7 s% ]+ hHypothetical universe, 假设总体2 o' l6 L: F) E+ r; s+ G2 a/ ^- P
Impossible event, 不可能事件- J7 {8 S4 p: x: ^! }3 `
Independence, 独立性4 s. _+ B. |# {4 y% w
Independent variable, 自变量9 F7 D' h) _0 m/ v, c+ M
Index, 指标/指数
; j# g1 s4 m$ k: U, v( aIndirect standardization, 间接标准化法
7 D" ~% f- F/ B+ hIndividual, 个体
9 P5 R, Y' [( c& bInference band, 推断带
x8 ]' \. P) m* NInfinite population, 无限总体
% D7 S4 E7 ^5 I. O6 D% P$ B9 ?+ X! [Infinitely great, 无穷大
* {/ \0 \5 X! `' i+ V# A, YInfinitely small, 无穷小& O$ ]1 Q- Y( q4 p1 F
Influence curve, 影响曲线
# l( J- e2 y# J4 {' A- k/ KInformation capacity, 信息容量
! T2 i) N( X8 bInitial condition, 初始条件
4 }' M# h3 ^ n2 H6 g, L& ^Initial estimate, 初始估计值) F, H# h% I, B# A1 ?
Initial level, 最初水平% p8 N7 Q! Y) c, Z' v
Interaction, 交互作用2 p0 a( \: _+ I9 O2 j) _
Interaction terms, 交互作用项
! I% b8 O/ u* t4 i# i2 V3 t+ HIntercept, 截距
* b5 P; c8 B' B+ |0 H/ hInterpolation, 内插法
5 t" ^/ o5 s+ u; oInterquartile range, 四分位距6 Q$ _# V# v$ g, x
Interval estimation, 区间估计% C( G' ]9 y: ~; b+ D4 b l1 [
Intervals of equal probability, 等概率区间7 M9 q# q( A# Z# [/ O# x
Intrinsic curvature, 固有曲率
# |: D* {( F6 G$ _7 zInvariance, 不变性! ?1 t% L: c) @3 S3 V7 o5 O
Inverse matrix, 逆矩阵8 N$ |' q6 T. w& ~+ d9 X
Inverse probability, 逆概率6 j( ]. ^3 `/ `- V9 S
Inverse sine transformation, 反正弦变换. E6 A2 W/ s8 v& E* C6 M
Iteration, 迭代 - N+ ]: X m9 V8 L: j W) d
Jacobian determinant, 雅可比行列式
, |) g/ u. \9 ZJoint distribution function, 分布函数. a) s% I( `4 @+ [
Joint probability, 联合概率
K% \$ E5 p, b$ ]: ZJoint probability distribution, 联合概率分布
4 A, d& X$ u& x' A3 O7 ZK means method, 逐步聚类法
* y2 j, h( }9 l! i2 ~Kaplan-Meier, 评估事件的时间长度
1 t# V9 Y2 l0 ?$ N5 PKaplan-Merier chart, Kaplan-Merier图
8 s9 R- X+ L( Q i6 y0 i- uKendall's rank correlation, Kendall等级相关) n1 R* r5 w$ m7 \$ {" |
Kinetic, 动力学. ?: g$ k$ v. R% x
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验, r1 K9 D1 n K H
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验: f: X4 V) h3 ?2 r: m0 g3 h7 J
Kurtosis, 峰度* E; \- Z; ]2 X6 _/ v5 P6 r
Lack of fit, 失拟" U8 B' q9 J) u! |5 I
Ladder of powers, 幂阶梯% p! V% I7 m/ J0 t: r
Lag, 滞后
1 G" ?! p% E6 i+ p c, E0 kLarge sample, 大样本
* a5 c% V& s# E- M0 GLarge sample test, 大样本检验( A& ~* ~& L: Y; N
Latin square, 拉丁方
) j+ W) y, k. l- i% n% L, g% ILatin square design, 拉丁方设计1 g) h5 ]7 B1 J
Leakage, 泄漏
$ ^8 f( w, Y1 I" y; ^Least favorable configuration, 最不利构形
4 U7 d$ `+ L# ?9 r/ OLeast favorable distribution, 最不利分布) o9 I* {1 z" {0 _
Least significant difference, 最小显著差法6 S" G8 T+ T$ ~. h
Least square method, 最小二乘法* j" C- s, p% ]& C: O/ a# M( J
Least-absolute-residuals estimates, 最小绝对残差估计5 O& F/ j/ J, p; v6 h& `
Least-absolute-residuals fit, 最小绝对残差拟合
& z( G5 x% f- E8 j; A+ rLeast-absolute-residuals line, 最小绝对残差线' I! l t R! X% \# d' V
Legend, 图例; W2 a% f o; L# x& }$ O6 u
L-estimator, L估计量
6 m1 B3 m7 a- o0 L$ r7 a) D+ [L-estimator of location, 位置L估计量
8 i" i8 z' ^* _" z3 UL-estimator of scale, 尺度L估计量
& g2 j4 f8 J& B5 T r. nLevel, 水平
7 D' ~. [2 d P3 H6 L) W+ NLife expectance, 预期期望寿命 z2 `' j. H1 A6 d
Life table, 寿命表- _* ~: G. ]- h+ q% G, u1 }
Life table method, 生命表法
! O( `, J& O& |% a. G5 iLight-tailed distribution, 轻尾分布1 [$ H7 V( \; }/ A4 r0 Z% H
Likelihood function, 似然函数
3 ~8 u& g# y( ^$ X6 ?: \1 N! K* FLikelihood ratio, 似然比
' b [ k/ \ |! z. y2 L7 Cline graph, 线图' o7 E; A/ K+ ]1 ~' j1 ^* q
Linear correlation, 直线相关
; j3 H! x" q5 K3 v1 D' NLinear equation, 线性方程5 |* f, s, c, n
Linear programming, 线性规划
- |0 n- H: U5 Q7 v( G4 r+ iLinear regression, 直线回归
+ d2 b% K0 Z( \" N" ^1 w9 iLinear Regression, 线性回归
+ `0 c" b. h. |% Z7 b; Z0 ?5 W: wLinear trend, 线性趋势4 B6 ?0 O: l/ s/ M
Loading, 载荷 - L( p+ q) b$ I4 r# {
Location and scale equivariance, 位置尺度同变性7 b- g/ Q9 X% |9 Z
Location equivariance, 位置同变性
+ C& `9 M/ u/ X0 u7 gLocation invariance, 位置不变性
* p( w) G* w$ Y4 z& ]Location scale family, 位置尺度族
8 l. L3 k6 f! H' [0 sLog rank test, 时序检验 9 {: s' n# b, I7 p
Logarithmic curve, 对数曲线4 N, C; @% o! x& N2 q. f$ l0 |+ }, t
Logarithmic normal distribution, 对数正态分布7 y# F* j' e5 K. |
Logarithmic scale, 对数尺度
; _& ~+ g$ P g' Y$ VLogarithmic transformation, 对数变换
D/ a0 E$ b! t$ O' mLogic check, 逻辑检查" _" B- P& D( i# @
Logistic distribution, 逻辑斯特分布
# g" e8 m# F( P$ O: ~: d$ ULogit transformation, Logit转换6 \% z: H; K! |/ p8 j+ w8 q& `
LOGLINEAR, 多维列联表通用模型 ( z) V" r+ ~- q3 a
Lognormal distribution, 对数正态分布% N, \( R& _- \: u9 p( J( }
Lost function, 损失函数
- A! G6 B3 K' _, U/ n- H0 U3 Z: pLow correlation, 低度相关4 Z7 V' Z' b2 B* y; f: m# {0 X. S" H
Lower limit, 下限
" ^3 `% b( c6 i" c% T. _Lowest-attained variance, 最小可达方差
2 o/ f- K' v/ z3 L# N- `LSD, 最小显著差法的简称
, l2 M- s) w% U( QLurking variable, 潜在变量
A-D
Absolute deviation, 绝对离差$ \- Q- G2 j; I P5 n
Absolute number, 绝对数! j; h# n+ O1 a1 |
Absolute residuals, 绝对残差, M& W8 H2 h' A' a
Acceleration array, 加速度立体阵
" m$ V7 u9 f5 X& tAcceleration in an arbitrary direction, 任意方向上的加速度
* r+ C- V1 u/ b0 C! r. vAcceleration normal, 法向加速度
3 j) I5 j# w+ B/ aAcceleration space dimension, 加速度空间的维数6 k8 B* W1 P3 @# r) I8 t
Acceleration tangential, 切向加速度6 u& p) w4 w2 u) P, w' h
Acceleration vector, 加速度向量
) {1 l8 f# f2 f DAcceptable hypothesis, 可接受假设4 @) a2 F% U( r6 [" M. E
Accumulation, 累积4 r8 m. G5 S+ }$ b+ n
Accuracy, 准确度
( r9 g5 _4 U: p/ t! S1 _8 vActual frequency, 实际频数
4 I. n5 b/ U5 q' n, l jAdaptive estimator, 自适应估计量
& k6 J: {+ e; c6 a! j- d8 rAddition, 相加+ _/ y% [3 j1 s& A, |2 y
Addition theorem, 加法定理- I3 l% ?4 l, q* w1 b- b2 Z
Additivity, 可加性
) ^+ }* P4 y+ H/ Z" ^Adjusted rate, 调整率
7 A. p4 y7 g- K+ B0 I3 I* I6 Y* p! x( RAdjusted value, 校正值
1 z# K) e: K6 L# h* M/ aAdmissible error, 容许误差* o- @1 J! f* I# U; `& h
Aggregation, 聚集性* s) _- R$ b! e! l, W# D* Z- N6 R
Alternative hypothesis, 备择假设
# b& E$ g" |* \; BAmong groups, 组间* [0 H: t% g% r" R4 o
Amounts, 总量
3 S" W7 K$ }8 P6 }. {Analysis of correlation, 相关分析
9 b5 Z, ]0 L2 WAnalysis of covariance, 协方差分析: {" p( G2 f [" } U/ N6 O
Analysis of regression, 回归分析2 [9 Y3 H* d$ T7 A5 N) D
Analysis of time series, 时间序列分析
, |: i+ Z- K6 W9 D$ i Y. k7 hAnalysis of variance, 方差分析
6 Y1 p1 y/ D/ i5 XAngular transformation, 角转换
7 U0 a( Y4 P0 O/ ?ANOVA (analysis of variance), 方差分析6 g3 x# \3 b8 o; s9 I4 V
ANOVA Models, 方差分析模型" A1 q3 i, h) P% C- L L
Arcing, 弧/弧旋
; R w! t. c: d8 j" h5 Y, OArcsine transformation, 反正弦变换5 J5 s* M0 c$ i8 Z4 T
Area under the curve, 曲线面积
3 f2 x8 j5 c7 G. P# a6 ?* BAREG , 评估从一个时间点到下一个时间点回归相关时的误差
% b! J- H& h8 k/ I5 [% R1 HARIMA, 季节和非季节性单变量模型的极大似然估计
, O2 J/ q$ Q/ W! j% BArithmetic grid paper, 算术格纸
7 m6 M# S( L( N/ G8 ` ]0 pArithmetic mean, 算术平均数
! }( n. A5 l" EArrhenius relation, 艾恩尼斯关系0 `$ M x2 Q+ D V2 C
Assessing fit, 拟合的评估- X% s# {4 |! R# c
Associative laws, 结合律1 i, P$ u7 m' y+ O. g! i
Asymmetric distribution, 非对称分布
4 R4 A6 J: r; C! ?* C+ ?Asymptotic bias, 渐近偏倚8 w% ?) t; x" F/ |
Asymptotic efficiency, 渐近效率
8 q6 ?; h4 ^* k5 |, gAsymptotic variance, 渐近方差
6 {! K! R3 D# ^0 ^Attributable risk, 归因危险度
& ^: |2 D- Z$ eAttribute data, 属性资料& Q- x0 G6 e5 a
Attribution, 属性
: R- Y! Y2 s3 c4 z3 cAutocorrelation, 自相关7 c2 ]+ ^ P; m; w, A% B M0 P9 d5 c
Autocorrelation of residuals, 残差的自相关1 V, o: S( v* l2 b) t
Average, 平均数
) |$ Q7 n# |0 L! q8 a7 F# dAverage confidence interval length, 平均置信区间长度* b) z+ g; g$ ~4 x( P# t
Average growth rate, 平均增长率) a X0 X0 V4 u
Bar chart, 条形图
6 B& p. n/ G8 M8 f8 V; [) P8 ` ] zBar graph, 条形图
& b/ p$ z! j& v2 t' Q) h$ [$ gBase period, 基期
! ^* E* h6 _! x( Q& R) Z' S1 ^3 [) }Bayes' theorem , Bayes定理3 e, H3 o4 c( A1 A! w: S+ H! J3 ]
Bell-shaped curve, 钟形曲线
, x; ~/ `2 z* ^- w' mBernoulli distribution, 伯努力分布& c ^5 \6 O4 P4 j9 C: h& G4 R+ ^
Best-trim estimator, 最好切尾估计量
' g1 L+ G! y6 t" _0 |9 e, q& ^Bias, 偏性
- u; v* h6 j* p$ LBinary logistic regression, 二元逻辑斯蒂回归: M: b- d8 `! N' G
Binomial distribution, 二项分布
% A" o3 N, Q* }5 qBisquare, 双平方2 h* ~4 D) t! S9 Z1 V% b
Bivariate Correlate, 二变量相关
5 m4 e/ j" w xBivariate normal distribution, 双变量正态分布
1 P" W2 g( S3 K, f" y7 e2 r( T+ \Bivariate normal population, 双变量正态总体 C7 c% z& e: M/ } m& l0 {5 F' ^
Biweight interval, 双权区间
' v4 z3 I3 I% O3 K4 k' w! }" k ?Biweight M-estimator, 双权M估计量, q; f) G( t! [8 d9 `. p6 G) [
Block, 区组/配伍组5 \8 \/ |; h+ q7 |1 w. f% K9 C
BMDP(Biomedical computer programs), BMDP统计软件包
- m/ d$ o3 m' A& D5 N: w& lBoxplots, 箱线图/箱尾图6 _ A* I4 O m7 }% D: _2 u: \
Breakdown bound, 崩溃界/崩溃点
, J. Q& I, y9 e% h) h5 j8 v. QCanonical correlation, 典型相关
/ E% w8 t; u7 P$ g& s) `Caption, 纵标目2 ]2 ~2 L9 p$ k+ x
Case-control study, 病例对照研究
) o! c3 O2 |+ W6 M) E, _Categorical variable, 分类变量8 W/ B7 c0 Y8 w0 z4 w/ G2 H" z
Catenary, 悬链线4 p+ I& L7 @1 L8 Y& v
Cauchy distribution, 柯西分布
) @0 [4 U9 j, RCause-and-effect relationship, 因果关系
- t0 S4 A; D J+ H7 Y" g' k4 E3 oCell, 单元
* x2 r' Z" d; I: jCensoring, 终检
& Q) Z6 C {! z- W* n. mCenter of symmetry, 对称中心
9 b' \( j% Z5 @# kCentering and scaling, 中心化和定标" |& K3 e" @* m B. u5 i+ e
Central tendency, 集中趋势7 g& }6 ?7 D- n: w$ n
Central value, 中心值8 j6 A# k4 K/ H; Q. o
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
7 i4 ~' W$ ]4 L2 y# j1 b/ q5 `Chance, 机遇2 r% d7 s- L' n; Q5 |# E
Chance error, 随机误差' P \% V6 q8 w" p2 t
Chance variable, 随机变量
: ?5 Y3 j+ ]+ O6 R& DCharacteristic equation, 特征方程
/ Y5 C; I6 @ r n4 uCharacteristic root, 特征根% P% i3 W1 t. m! q$ H
Characteristic vector, 特征向量6 |# b. L! B( N8 C5 {
Chebshev criterion of fit, 拟合的切比雪夫准则1 g& S; D! k* J9 W7 n
Chernoff faces, 切尔诺夫脸谱图
6 J3 Y; o9 b2 t, Y" gChi-square test, 卡方检验/χ2检验
# P, P4 g9 X- \7 K8 x: D* ?Choleskey decomposition, 乔洛斯基分解0 A Q O3 {: P* m' A( j$ k
Circle chart, 圆图 5 Q: }. }" I0 [! r; t& i0 r4 F+ j
Class interval, 组距
: f3 }3 j) w8 l" _& sClass mid-value, 组中值
* P, P/ J& A0 M2 YClass upper limit, 组上限: [ Z4 ^$ L4 e: ~6 `7 p, ~
Classified variable, 分类变量5 J. }* B1 E% |$ Z" J$ H3 ?# m
Cluster analysis, 聚类分析
. D& y# [8 w0 r+ PCluster sampling, 整群抽样7 i6 E4 t. x# o- @: u$ @
Code, 代码
. d" y1 L/ y+ z/ d+ pCoded data, 编码数据
- k0 a0 e; }8 V# `1 JCoding, 编码# @, L% L9 \) L* e. {! n6 u. l
Coefficient of contingency, 列联系数: O- n5 k+ P" N) a! I
Coefficient of determination, 决定系数
: [ l# \7 f x+ S! u" e, MCoefficient of multiple correlation, 多重相关系数# q, R- e5 o& Y- l8 y3 ^- W& T
Coefficient of partial correlation, 偏相关系数+ `1 s0 i1 J) D* Q, ~
Coefficient of production-moment correlation, 积差相关系数
' u2 I$ O! z3 M' YCoefficient of rank correlation, 等级相关系数. v* C, } u, i
Coefficient of regression, 回归系数
! \ ]1 H2 j: S2 A; dCoefficient of skewness, 偏度系数
# p* `$ J5 r* }4 oCoefficient of variation, 变异系数
5 q( a' F, m5 n; j) B; G3 L6 cCohort study, 队列研究
* i U$ p- S. o$ T! J3 K( yColumn, 列
) I) R& z" @, h9 T) NColumn effect, 列效应
$ L4 J* P+ ~3 d8 v$ i4 x" }' {Column factor, 列因素
. Y* |+ t4 l( ACombination pool, 合并7 h" L! s+ Z" A/ H
Combinative table, 组合表$ G% o% k$ Q+ Q- P
Common factor, 共性因子
! u* I c* P# _5 FCommon regression coefficient, 公共回归系数' b C* Q* P% u4 x
Common value, 共同值
8 D/ J. j F. ]& l! Q$ GCommon variance, 公共方差2 W; H& c" o. B' {; [
Common variation, 公共变异
( t% v$ C7 y m) J1 {Communality variance, 共性方差& d7 [7 _( ^$ ~% W
Comparability, 可比性' A# h) \' R, r7 O- S
Comparison of bathes, 批比较
4 }+ b; G* C* d+ R: jComparison value, 比较值
6 p0 a; p' U. R) s9 Z+ k; [9 W$ |Compartment model, 分部模型4 U1 t+ P# Q9 E) b+ `
Compassion, 伸缩9 d& e+ ~) S2 K, R/ p0 F @
Complement of an event, 补事件
" \7 q( W$ _0 n2 ^; `1 q0 a/ n: aComplete association, 完全正相关$ s- q% z' f$ A: s5 ~/ {
Complete dissociation, 完全不相关
/ H9 r) X5 w( p# @Complete statistics, 完备统计量
' D% \9 f7 E( @+ h/ S. F; dCompletely randomized design, 完全随机化设计' y! x2 I l& @; K
Composite event, 联合事件
6 W( e' \8 C3 x6 k$ Q. tComposite events, 复合事件
5 H/ j) a: s7 q; B$ f3 r% aConcavity, 凹性
' D( C" V$ x; U3 W6 JConditional expectation, 条件期望
' l8 j) r1 r2 H, ?# Z: v! y4 RConditional likelihood, 条件似然, B; k; n: e( k: C+ n3 l! l& t
Conditional probability, 条件概率
# E0 z8 J6 t" Q% Y" y# MConditionally linear, 依条件线性* J: q* r$ |& e: e( B1 N4 t
Confidence interval, 置信区间
# ^( \* t1 ]8 F! H* R; wConfidence limit, 置信限! \# j" N8 N! \6 H
Confidence lower limit, 置信下限9 b7 i1 ]3 b7 `; |
Confidence upper limit, 置信上限8 w) B6 N( ]1 j5 ?( u4 [
Confirmatory Factor Analysis , 验证性因子分析
+ q. m( V7 O7 N) {Confirmatory research, 证实性实验研究
# @! E4 l; Z4 bConfounding factor, 混杂因素7 a& M8 `$ l; g* d# T9 ^
Conjoint, 联合分析6 `, _1 X5 I6 j( S
Consistency, 相合性2 c( e5 I4 Y' m- ^
Consistency check, 一致性检验
0 B- g0 _( ?* L# G u/ @Consistent asymptotically normal estimate, 相合渐近正态估计
N; u* d$ k8 u( e+ [$ @Consistent estimate, 相合估计, x9 U9 }% b7 j- u: ?. T/ Y
Constrained nonlinear regression, 受约束非线性回归1 i# g! A; f* y
Constraint, 约束
- U& b- t: T. W6 f0 }, B' }5 jContaminated distribution, 污染分布
& T! T8 _3 E) m6 DContaminated Gausssian, 污染高斯分布' o3 t3 K; l, B. R
Contaminated normal distribution, 污染正态分布" s4 O1 g2 o7 V) [- B& z! J: {- n
Contamination, 污染
# _. D6 E0 k- i# m3 F4 vContamination model, 污染模型$ Q6 T0 A5 I2 b% N. s4 a4 U5 x" n
Contingency table, 列联表
8 _* ]7 Y E$ k8 e% i1 Z5 ZContour, 边界线( @; Q9 `3 r: Y0 T" [; Y6 H
Contribution rate, 贡献率
8 \' ^, }# o" l; |" ?$ x# pControl, 对照
- l- ?$ g. ?0 V% m6 \. `' B+ [Controlled experiments, 对照实验
- g/ ]% f* q$ F6 |+ uConventional depth, 常规深度
9 D: o, ^" h% BConvolution, 卷积* Y( U( R: f: u: V) v- L
Corrected factor, 校正因子# L3 D( [) d$ Z
Corrected mean, 校正均值
6 X% P2 D# P! T; Z3 y. L# cCorrection coefficient, 校正系数
7 ~! O+ t4 Y, h5 D& y0 R% fCorrectness, 正确性 $ p& K2 ] E4 i3 ?( S* d. _' D
Correlation coefficient, 相关系数
) d. O2 L) k7 P: E: |& XCorrelation index, 相关指数2 h }0 e7 O0 H6 o; w- o1 K( \
Correspondence, 对应: ^3 C4 ^5 x _" t
Counting, 计数
1 V: p6 o+ L1 |Counts, 计数/频数' o+ P$ A2 n) a4 o; ~$ ]) W
Covariance, 协方差
1 K" ]. r% w2 S2 M/ C2 CCovariant, 共变 + t& N" r7 W/ B1 K9 ?9 v! d/ @
Cox Regression, Cox回归: I) A; u. _8 g; x2 d
Criteria for fitting, 拟合准则2 K- B: z( x8 \+ y. F- G: M2 n
Criteria of least squares, 最小二乘准则, ?. g- I$ v" P3 f. b: L$ s6 c# j
Critical ratio, 临界比( G1 k0 ^; M: P2 o
Critical region, 拒绝域# @0 i+ o) A8 f" h9 P1 X. i
Critical value, 临界值: _% s' ^* r1 Z4 e$ A, o
Cross-over design, 交叉设计( D% t2 l" y" m, V) O
Cross-section analysis, 横断面分析5 M, D0 k# R+ E1 ~# T7 m
Cross-section survey, 横断面调查
* [. U4 N# ^' r$ G% n; B9 vCrosstabs , 交叉表
/ l: [+ y: j5 R3 g; iCross-tabulation table, 复合表/ ]( j1 M" B4 X' N$ \) ^
Cube root, 立方根
: d& T/ f) l E* m( }Cumulative distribution function, 分布函数
6 j5 F8 w; B: Q3 U9 J# w% x! `Cumulative probability, 累计概率
) y+ F" x8 `+ f7 FCurvature, 曲率/弯曲
5 W" V+ }! d+ h8 kCurvature, 曲率
% U' [' b2 _8 b0 N. h" iCurve fit , 曲线拟和
1 M* A \2 K( zCurve fitting, 曲线拟合
& t/ y# {! {5 b6 p4 T# i! QCurvilinear regression, 曲线回归
, {8 g% u" |% u1 J+ B1 q! O! K( \Curvilinear relation, 曲线关系
/ U- b- l; u4 [" sCut-and-try method, 尝试法1 ^% {8 T2 g1 ^
Cycle, 周期) c) S: m8 M) ^. _+ V. ?
Cyclist, 周期性* S7 A! v* Q+ B, x2 M2 ?# v
D test, D检验$ K \* ^% a; g7 y o; t
Data acquisition, 资料收集; K( w) A: ]9 K4 O8 h9 T9 S3 C
Data bank, 数据库- a' A+ g1 M7 X4 u8 e9 X- @/ b3 k, O
Data capacity, 数据容量
C; v1 q- \5 e/ `0 ^* x3 M, ~. WData deficiencies, 数据缺乏( V' \( I: X& X e& ^0 V9 S+ y) o, f
Data handling, 数据处理, v% a. j$ D4 C6 A
Data manipulation, 数据处理/ i) M( q$ |! l! e# U, X
Data processing, 数据处理9 Z5 G- h3 b6 Q; z
Data reduction, 数据缩减- m) L0 K3 x6 L1 T8 D" M! L* |( S
Data set, 数据集
% X; \; r5 C7 W4 pData sources, 数据来源: z6 t& M5 O) w0 k4 B0 O
Data transformation, 数据变换 X/ Q% m! F2 U: [& ?) T
Data validity, 数据有效性
3 C& F# S2 R. L) sData-in, 数据输入
% m, U$ A, \* Z, m" RData-out, 数据输出9 g8 p5 r) _8 e8 H
Dead time, 停滞期
1 v! |, x; N2 G/ w; KDegree of freedom, 自由度( Y, g/ t( b6 R8 Z$ [: n
Degree of precision, 精密度 E) X7 ?+ ^( a3 A) W1 n/ w
Degree of reliability, 可靠性程度
/ Z4 e% ^( ]6 [2 h2 g9 r* QDegression, 递减
8 c( _% w$ Q e3 E- t6 c2 s' ZDensity function, 密度函数
% y' z5 r1 [' q6 l% SDensity of data points, 数据点的密度! U5 |3 t V4 h/ C
Dependent variable, 应变量/依变量/因变量 + @. ~: d F3 L& `: z
Dependent variable, 因变量2 A2 y Z8 K1 R! o o
Depth, 深度/ f5 |6 h1 n V
Derivative matrix, 导数矩阵
5 |8 a6 X3 E; {/ d1 G' XDerivative-free methods, 无导数方法* o7 D7 {; I/ j3 x5 O) Z+ O
Design, 设计, q/ P5 r4 a" P- ]
Determinacy, 确定性
% ?+ x* I1 o h5 b6 [Determinant, 行列式
6 n& @' N3 K( S4 D! E( WDeterminant, 决定因素
6 x: ^ b; B& l$ H+ ]Deviation, 离差' j* @. n) u# g
Deviation from average, 离均差6 ~& @) M4 F4 E1 c' U
Diagnostic plot, 诊断图5 L1 D8 g* n" x1 G% @
Dichotomous variable, 二分变量
# [% k i. u# G, B% vDifferential equation, 微分方程
# R; s/ I5 K. Y1 m7 [, ^- r- ODirect standardization, 直接标准化法
, v) o* o, I/ q! v( N& O0 HDiscrete variable, 离散型变量
# ]% C6 O' s9 O: gDISCRIMINANT, 判断 ' x) S; B+ M( y: W
Discriminant analysis, 判别分析
2 N( a) Z+ Z" [+ [# ?& uDiscriminant coefficient, 判别系数
5 K& D* S9 R/ p& ADiscriminant function, 判别值
l) `/ m& S' B7 QDispersion, 散布/分散度
# d9 R1 l; n8 W8 SDisproportional, 不成比例的4 j$ u7 D$ X. M0 z: U3 [
Disproportionate sub-class numbers, 不成比例次级组含量
- X' m4 T8 ^; E4 N8 x6 ` _1 eDistribution free, 分布无关性/免分布
& \1 O( Q% ]% D, ?$ D ?- a! q: fDistribution shape, 分布形状/ l3 E9 e' @- L6 ~$ h
Distribution-free method, 任意分布法6 `* K s$ a: B7 {% t0 @6 _5 _ Z- y C
Distributive laws, 分配律% u, {. L( o$ t- g; z. ~, ?/ t
Disturbance, 随机扰动项; c: t' i# j( g. A5 |, v! t
Dose response curve, 剂量反应曲线
& ?( `0 t# P" ?( pDouble blind method, 双盲法% {' f& [8 {7 L- }
Double blind trial, 双盲试验
1 R' [1 m- b5 O# _( QDouble exponential distribution, 双指数分布) l/ i6 H d: B. u/ \
Double logarithmic, 双对数1 d+ ?' R& {" S! c
Downward rank, 降秩& V7 c7 w$ u' I# M' T: @7 s6 p! w/ I
Dual-space plot, 对偶空间图
" @/ y( P+ U# k1 }2 t; a9 R; mDUD, 无导数方法
, V; M/ U& c( N' O2 E3 sDuncan's new multiple range method, 新复极差法/Duncan新法