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Discussion on analyze phase

3. Hypothesis test on Attribute data

Hello and welcome back to the third session on the analyse phase. Here we will talk about hypothesis tests for hormone attribution. Generally, attributed data is considered a nonnormal type of data, but there are different hypothesis tests required to analyse its results. So be aware of the one-sample proportion and two-sample proportion tests, how to calculate the statistic value for this test, and also how to use tables for critical value calculation. These tests perform well on many tables, but the main focus is given to the contingency test because the contingency test is used when you have more than two proportions in your example, like in an ANOVA test.

So what is the purpose of this contingency test, how to perform it on metadata software, and how to calculate the statistic value manually and the critical value with the help of a contingency table? So be aware of these concepts and try to solve one example that is provided in the ICCP manual. Go through that example and try to solve it on your own; that will improve your understanding. As you can see, questions are asked at the green belt level rather than on a manual calculation. You need to have an idea of how to calculate the statistic value of each hypothesis test manually and interpret the result on the basis of that. So in this way, we cover our discussion on the attribute data hypothesis test. Thank you.

4. Sum up Analyze phase

Welcome back. Now, we already covered our discussion in the analysis phase. So from the exam point of view, once again you go to the ICGB manual, read the analysis phase from that manual, and then practise the 50 questions on the analysis phase. You then analyse yourself to determine whether your preparation for the analysed phase is complete or not. Remember that during the analysis phase, you must have a thorough understanding of the use of z tables, t tables, contingency tables, and the F table. because your exam includes a reference document This is from the ISS, and this document carrying all the information related to these tables means there are chances that the question asked on these tables will indicate that you need to calculate the critical value for your hypothesis test and then interpret the result. This type of question is also asked in your exam.

So what you have to do is first perform the hypothesis test on minuteapp software, then manually calculate the statistic value, and then also calculate that statistic value with the help of these tables showing the critical value. You need to calculate and then compare these values and interpret your result, whether your null hypothesis is rejected or you fail to reject your null hypothesis. So prepare in such a way for this analysis phase because hypothesis testing requires manual calculation and Minitab software interpretation also. So you need to understand both of these concepts. So in this way, we will complete our discussion on analysis. Thank you.

Discussion on improve phase

1. Correlation and regression analysis

Welcome back to the first improvement session. Here we will talk about correlation and regression analysis. So basically, the improved phase consists of topics like correlation analysis, multiple linear regression, linear regression analysis, nonlinear regression analysis, residential analysis, and box-off's transformation.

So at the improved phase, we have to interpret the relationship between two variables, input and output. And then we need to identify whether the relationship is strong or not and also predict its mathematical equation with the help of correlation and regression. So the questions asked about correlation analysis are generally based on the interpretation of a scatter plot, although sometimes theoretical questions are asked. Suppose the scatter plot is given to you, and from that you need to identify whether the correlation coefficient is positive or negative and predict whether the relation is strong or weak—or another way of providing data to you.

You need to calculate that coefficient manually and then predict, with the help of the coefficient range, whether the relation is strong or with the help of coefficient range. To answer these types of questions, you must first understand the approach to correlation coefficient analysis, how to calculate the coefficient manually, what the coefficient's range is, how to interpret the scatter plot, and what the limitations of coefficient analysis are. Then we talk about the regression analysis. So in the case of regression analysis, general questions are asked about the interpretation of the graphs, similar to the correlation analysis. So here you have a clear understanding of the approach to regression analysis, which steps you should follow to perform regression analysis, what are the outcomes of regression analysis, how to interpret the result that we get after the regression analysis, and what are the advantages of regression analysis or the correlation? What exactly is multicoloreality?

What does it mean by the "variance inflation factor"? So you have a proper understanding of these concepts to solve the questions on regression analysis, and if it is possible, then at least perform regression and correlation analysis on many types of software. So that will help you understand the interpretation of graphs visually. Then we talk about the non-linear regression analysis. So now you have a solid understanding of the fundamentals, such as nonlinear regression analysis equations and when we need nonlinear regression analysis, as well as why nonlinear regression analysis is preferred over multiple linear regression analysis and what the benefits and drawbacks are. So you have a clear understanding of these concepts. So in this way, you have to prepare for this correlation and regression analysis section.

2. Residual analysis and Box-Cox Transformation

Welcome back to the second session on improving phases. Here we will talk about resident analysis and Boston's transformation. Generally, residential analyses are performed after the regulatory analysis to validate the assumptions of equality, normality, and independence between the two variables.

By validating this assumption, you need to make a final decision about your regression analysis during your project. So to prepare for this section, you need to understand the meaning of "residual." How should this residual analysis be performed on a minute app, how should the results be interpreted, and what are the various assumptions involved in residual analysis? What steps should you take if any of the assumptions fail during the analysis? So it goes through all these concepts. And in the case of Transformation C, this is the most important tool of your Csima project. Because, as you know, most of the time you require normal data for your analysis, But there are some situations in which you will get nonnormal data. So at that time, this tool is used to convert that nonnormal data into normal, and then you can analyse that data for your project's purposes. So this tool plays an important role during a Six Sigma project to transform the non-normal data into normality.

So, go through the concepts like what "transform power" means, what it ranges for, how to transform this data on the Minute App, and what are the different "transformation rules," which are the different types of functions that are used to transform data, and what are their advantages and disadvantages? Go over all of these concepts, and when we talk about the design of excellence, this topic is basically completely covered in your black belt body of knowledge. But I recommend a "green belt" level. Even if you have a basic idea about the design of Excel and what its purpose is, how to perform it, and what different terminologies are included, what are the types of design approximate, and what is the meaning of manifest and interaction effect? Go through all these basic concepts. So in this way, you need to prepare for this section. Thank you.

3. Sum up improve phase

Hey, welcome back. Now we are ready to continue our discussion on improvements. I hope you will understand it very well. Now you have to go through the ICCB manual, read the Improve phase from that manual, and understand all the concepts. and then perform the correlation and regression analysis on many types of software. Interpret those results so that it will improve your understanding of the graphical analysis that is required for correlation and regression. Once your progression is done, then I can come back to the course and practise the 50 questions provided in this course on improving proficiency. By practising this question, you will get an idea of the types of questions that are generally asked. So in this way, you have to prepare for this section. So we've completed our discussion of this section, and we'll move on to the control phase in the next session. Thanks.

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