SigmaXL - 统计和图形分析软件
· 图文步骤展示:如何在Windows上激 活SigmaXL?
SigmaXL从一开始就被设计为一种经济高效、功能强但易于使用的工具,使用户能够测量、分析、改进和控制他们的服务、交易和制造流程。作为已经熟悉的Microsoft Excel的插件,SigmaXL很适合精益Six Sigma培训或在大学课程中使用。SigmaXL将使您能够在DMAIC序列的任一阶段有效的分析您的数据,并生成您需要的答案,无论您身处哪个行业。
作为具有成本效益且功能强的软件解决方案,各级用户都可以使用已经熟悉的MS Excel软件快速学习关键的图形和统计Sigma工具。
SigmaXL可容纳超过100万行数据,并与Windows PC和Mac计算机上的MX Excel兼容。包括额外的Sigma和精益模板、DMAIC菜单项和控制图选择工具,以简化SPC图表的选择。
SigmaXL功能
数据处理:
-
按类别、编号、日期或随机进行子集
-
转移数据
-
跨行堆叠子群
-
堆叠和取消堆叠列
-
标准化数据
-
转换为离散数据
-
随机数生成器
-
数据准备
-
Box-Cox转换
模板和计算器:
-
DMAIC和DFSS模板
-
Lean Templates
-
图形模板
-
概率运行计算器
-
统计模板
-
测量系统分析(MSA)模板
-
过程Sigma级别—离散和连续
-
过程能力和置信区间
-
公差区间计算器。
-
DOE模板
-
Taguchi DOE模板
-
控制图模板
图形工具:
-
基本和高等(多个)Pareto图
-
EZ-Pivot/Pivot图表。轻松的创建透视图和图表
-
基本柱状图
-
多个直方图和描述性统计(包括平均值和StDev.的置信区间,以及Anderson-Darling正常性测试)
-
多个柱状图和加工能力(Pp, Ppk, Cpm, ppm, %)
-
多重膨胀图、多重X膨胀图、点阵图
-
运行图(带有非参数运行测试,允许你测试聚类、混合物、缺乏随机性、趋势和振荡)
-
叠加运行图
-
多重正态概率图(带有95%的置信区间,便于解释正态性/非正态性)
-
多变量图
-
散点图(带线性回归和可选的95%置信区间和预测区间)
-
散点图矩阵
-
均值分析(ANOM)图
统计工具:
-
当结果显著时,P值变成红色(P值<α)
-
描述性统计,包括Anderson-Darling Normality test、偏度和峰度,以及P值
-
描述性统计选项
-
1 Sample t-test和置信区间
-
Paired t-test, 2 Sample t-test
-
2 Sample comparison tests
-
单向方差分析和均值矩阵
-
单样本、双样本、配对T检验和单程方差分析的自动假设检查
-
双向方差分析(平衡的和不平衡的)
-
等方差检验(Bartlett、Levene和Welch的方差分析)
-
相关矩阵(Pearson和Spearman's Rank Correlation)
-
多重线性回归
-
高等多元回归
-
多重响应优化
-
二元和序数逻辑回归
-
卡方检验(堆积列数据和二维表数据)
-
非参数检验
-
非参数检验—Exact
-
功率和样本量计算器
-
功率和样本量图。快速创建一个显示功率、样本量和差异之间关系的图表
测量系统分析:
-
创建量具的R&R(交叉)工作表
-
分析测量仪的R&R(交叉)
-
属性MSA(二进制、顺序、名义)
制程能力:
-
多重直方图和过程能力
-
个人/分组的能力组合报告
-
分布式拟合报告
-
非正态数据(个人)的能力组合报告
实验设计:
-
生成2-Level Factorial和Plackett-Burman筛选设计
-
基本DOE模板
-
主效应和交互作用图
-
等高线和3D曲面图
-
响应曲面设计
-
分析2-Level Factorial和Plackett-Burman筛选设计
控制图:
-
控制图选择工具
-
个体,个体与移动范围
-
X-Bar&R, X-Bar&S
-
I-MR-R, I-MR-S (之间/之内)
-
P, NP, C, U
-
P'和U'(Laney)处理过度分散
-
控制图包括对特殊原因的测试报告。特殊原因也会在控制图数据点上标明。设置默认值以应用全部的测试1-8
-
过程能力报告(Pp、Ppk、Cp、Cpk)可用于I、I-MR、X-bar&R、X-bar&S图表
-
将数据添加到现有的图表中,方便操作者使用
-
通过用户定义的窗口大小滚动浏览图表
-
高等控制限值选项。子组开始和结束;历史组(例如分割控制限值以展示改进前后的情况)
-
排除用于计算控制限度的数据点
-
在数据点上添加注释,以确定可分配的原因
-
±1,2 Sigma区线
-
非正常数据的控制图(个体)
可靠性/Weibull分析:
-
Weibull分析
自相关数据的时间序列预测和控制图:
-
自相关(ACF/PACF)图
-
交叉相关(CCF)图
-
频谱密度图
-
季节性趋势分解图
-
季节性相互作用图
-
指数平滑预测
-
指数平滑-多重季节性分解(MSD)预测
-
指数平滑控制图
-
指数平滑多季节分解(MSD)控制图
-
ARIMA预测
-
带有预测器的ARIMA预测
-
自回归移动平均模型 - 多重季节性分解(MSD)预测
-
自回归模型控制图
-
带预测器的ARIMA控制图
-
ARIMA多季节性分解(MSD)控制图
-
实用程序:差值数据
-
实用程序:滞后数据
-
实用程序:内插缺失值
SigmaXL PC系统要求:
Minimum System Requirements:
计算机和处理器:500 megahertz (MHz)处理器或更高
内存:1GB或更大的内存
显示器:1024×768或更高分辨率的显示器
操作系统:Microsoft Windows 8或更高版本的操作系统
Microsoft Excel版本:Excel 2013或更高版本,带有新的服务包或Microsoft 365
浏览器:SigmaXL帮助需要一个可用的浏览器
连接性:SigmaXL帮助和互联网激活需要互联网连接(也可使用离线激活)
SigmaXL Mac系统要求:
Minimum System Requirements:
计算机和处理器:500 megahertz (MHz)处理器或更高
内存:1GB或更大的内存
硬盘:1GB的可用硬盘空间
显示器:1024×768或更高分辨率的显示器
操作系统:Sierra和更高版本
Microsoft Excel版本:Excel 2019或更高版本,或Excel for Office 365
浏览器:SigmaXL帮助需要一个可用的浏览器
连接性:SigmaXL帮助和激活需要互联网连接
【英文介绍】
SigmaXL - Powerful Statistical and Graphical Analysis
SigmaXL was designed from the ground up to be a cost-effective, powerful, but easy to use tool that enables users to measure, analyze, improve and control their service, transactional, and manufacturing processes. As an add-in to the already familiar Microsoft Excel, SigmaXL is ideal for Lean Six Sigma training or use in a college statistics course.
SigmaXL features
Data Manipulation:
-
Subset by Category, Number, Date or Random
-
Transpose Data
-
Stack Subgroups Across Rows
-
Stack and Unstack Columns
-
Standardize Data
-
Convert to Discrete
-
Random Number Generator
-
Data Preparation
-
Box-Cox Transformation
Templates&Calculators:
-
DMAIC&DFSS Templates
-
Lean Templates
-
Graphical Templates
-
Probability Distribution Calculators
-
Statistical Templates
-
Measurement System Analysis (MSA) Templates
-
Process Sigma Level - Discrete and Continuous
-
Process Capability&Confidence Intervals
-
Tolerance Interval Calculator (Normal Exact)
-
DOE Templates
-
Taguchi DOE Templates
-
Control Chart Templates
Graphical Tools:
-
Basic and Advanced (Multiple) Pareto Charts
-
EZ-Pivot/Pivot Charts: Easily create Pivot Tables and Charts
-
Basic Histogram
-
Multiple Histograms and Descriptive Statistics (includes Confidence Interval for Mean and StDev., and Anderson-Darling Normality Test)
-
Multiple Histograms and Process Capability (Pp, Ppk, Cpm, ppm, %)
-
Multiple Boxplots, Multiple X Boxplots, Dotplots
-
Run Charts (with Nonparametric Runs Test allowing you to test for Clustering, Mixtures, Lack of Randomness, Trends and Oscillation)
-
Overlay Run Chart
-
Multiple Normal Probability Plots (with 95% confidence intervals to ease interpretation of normality/non-normality)
-
Multi-Vari Charts
-
Scatter Plots (with linear regression and optional 95% confidence intervals and prediction intervals)
-
Scatter Plot Matrix
-
Analysis of Means (ANOM) Charts
Statistical Tools:
-
P-Values turn red when results are significant (P-Value < alpha)
-
Descriptive Statistics including Anderson-Darling Normality test, Skewness and Kurtosis with P-Values
-
Descriptive Statistics Options
-
One-Way ANOVA and Means Matrix
-
Automatic Assumptions Check for One Sample, Two-Sample, Paired T-tests and One-Way ANOVA
-
Two-Way ANOVA (Balanced and Unbalanced)
-
Multiple Linear Regression
-
1 Sample t-test and Confidence Intervals
-
Paired t-test, 2 Sample t-test
-
2 Sample comparison tests
-
Equal Variance Tests (Bartlett, Levene and Welch's ANOVA)
-
Correlation Matrix (Pearson and Spearman's Rank Correlation)
-
Advanced Multiple Regression
-
Multiple Response Optimization
-
Binary and Ordinal Logistic Regression
-
Chi-Square Test (Stacked Column data and Two-Way Table data)
-
Nonparametric Tests
-
Nonparametric Tests - Exact
-
Power and Sample Size Calculators
-
Power and Sample Size Chart. Quickly create a graph showing the relationship between Power, Sample Size and Difference
Measurement System Analysis:
-
Create Gage R&R (Crossed) Worksheet
-
Analyze Gage R&R (Crossed)
-
Attribute MSA (Binary, Ordinal, Nominal)
Process Capability:
-
Multiple Histograms and Process Capability
-
Capability Combination Report for Individuals/Subgroups
-
Distribution Fitting Report
-
Capability Combination Report for Nonnormal Data (Individuals)
Design of Experiments:
-
Generate 2-Level Factorial and Plackett-Burman Screening Designs
-
Basic DOE Templates
-
Main Effects&Interaction Plots
-
Contour&3D Surface Plots
-
Response Surface Designs
-
Analyze 2-Level Factorial and Plackett-Burman Screening Designs
Control Charts:
-
Control Chart Selection Tool
-
Individuals, Individuals&Moving Range
-
X-Bar&R, X-Bar&S
-
I-MR-R, I-MR-S (Between/Within)
-
P, NP, C, U
-
P' and U' (Laney) to handle overdispersion
-
Control charts include a report on tests for special causes. Special causes are also labeled on the control chart data point. Set defaults to apply any or all of Tests 1-8
-
Process Capability report (Pp, Ppk, Cp, Cpk) is available for I, I-MR, X-Bar & R, X-bar&S charts
-
Add data to existing charts for operator ease of use
-
Scroll through charts with user defined window size
-
Advanced Control Limit options: Subgroup Start and End; Historical Groups (e.g. split control limits to demonstrate before and after improvement)
-
Exclude data points for control limit calculation
-
Add comment to data point for assignable cause
-
± 1, 2 Sigma Zone Lines
-
Control charts for Nonnormal data (Individuals)
Reliability/Weibull Analysis:
-
Weibull Analysis
Time Series Forecasting and Control Charts for Autocorrelated Data:
-
Autocorrelation (ACF/PACF) Plots
-
Cross Correlation (CCF) Plots
-
Spectral Density Plot
-
Seasonal Trend Decomposition Plots
-
Seasonal Interaction Plots
-
Exponential Smoothing Forecast
-
Exponential Smoothing – Multiple Seasonal Decomposition (MSD) Forecast
-
Exponential Smoothing Control Chart
-
Exponential Smoothing Multiple Seasonal Decomposition (MSD) Control Chart
-
ARIMA Forecast
-
ARIMA Forecast with Predictors
-
ARIMA – Multiple Seasonal Decomposition (MSD) Forecast
-
ARIMA Control Chart
-
ARIMA Control Chart with Predictors
-
ARIMA Multiple Seasonal Decomposition (MSD) Control Chart
-
Utilities – Difference Data
-
Utilities – Lag Data
-
Utilities – Interpolate Missing Values
- 2024-12-25
- 2024-12-24
- 2024-12-20
- 2024-12-19
- 2024-12-18
- 2024-12-17
- 2024-12-26
- 2024-12-23
- 2024-12-20
- 2024-12-20
- 2024-12-19
- 2024-12-19