How To
Logistic Regression with SigmaXL
What is Logistic Regression? Logistic regression is a statistical method to predict the probability of an event occurring by fitting the data to a logistic curve using logistic function. The regression analysis used for predicting the outcome of a categorical dependent variable, based on one or more predictor variables. The logistic function used to model…
Read MoreFull Factorial DOE with SigmaXL
What is a Full Factorial DOE? In a full factorial experiment, all of the possible combinations of factors and levels are created and tested. For example, for two-level design (i.e.each factor has two levels) with k factors, there are 2k possible scenarios or treatments. Two factors, each with two levels, we have 22 = 4 treatments…
Read MoreAttribute MSA with SigmaXL
Use SigmaXL to Implement an Attribute MSA Data File: “Attribute MSA” tab in “Sample Data.xlsx” (an example in the AIAG MSA Reference Manual, 3rd Edition). Step 1: Reorganize the original data into four new columns (i.e., Appraiser, Assessed Result, Part, and Reference). Select the entire range of the original data (“Part”, “Reference”, “Appraiser A”, “Appraiser…
Read MoreChi Square Tests with SigmaXL
Chi Square (Contingency Tables) We have looked at hypothesis tests to analyze the proportion of one population vs. a specified value, and the proportions of two populations, but what do we do if we want to analyze more than two populations? A chi-square test is a hypothesis test in which the sampling distribution of the…
Read MoreBox Cox Transformation with SigmaXL
Box Cox Transformation [unordered_list style=”star”] Data transforms are usually applied so that the data appear to more closely meet assumptions of a statistical inference model to be applied or to improve the interpret-ability or appearance of graphs. Power transformation is a class of transformation functions that raise the response to some power. For example, a…
Read MoreMultiple Linear Regression
What is Multiple Linear Regression? Multiple linear regression is a statistical technique to model the relationship between one dependent variable and two or more independent variables by fitting the data set into a linear equation. The difference between simple linear regression and multiple linear regression: [unordered_list style=”star”] Simple linear regression only has one predictor. Multiple…
Read MoreCorrelation Coefficient with SigmaXL
Pearson’s Correlation Coefficient Pearson’s correlation coefficient is also called Pearson’s r or coefficient of correlation and Pearson’s product moment correlation coefficient (r), where r is a statistic measuring the linear relationship between two variables. What is Correlation? Correlation is a statistical technique that describes whether and how strongly two or more variables are related. Correlation…
Read MoreSimple Linear Regression
What is Simple Linear Regression? Simple linear regression is a statistical technique to fit a straight line through the data points. It models the quantitative relationship between two variables. It is simple because only one predictor variable is involved. It describes how one variable changes according to the change of another variable. Both variables need…
Read MoreMedian Test with SigmaXL
What is Mood’s Median Test? Mood’s median test is a statistical test to compare the medians of two or more populations. [unordered_list style=”star”] Null Hypothesis (H0): η1 = … = ηk Alternative Hypothesis (Ha): At least one of the medians is different from the others [/unordered_list] The symbol k is the number of groups of…
Read MoreKruskal Wallis with SigmaXL
Kruskal–Wallis One-Way Analysis of Variance The Kruskal Wallis one-way analysis of variance is a statistical hypothesis test to compare the medians among more than two groups. [unordered_list style=”star”] Null Hypothesis (H0): η1 = η2 = … = ηk Alternative Hypothesis (Ha): at least one of the medians is different from others. Where: ηi is the…
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