Transcripts
1. Welcome!: Hi and welcome everybody. My name is voluntarily champ. And I build a 12 years career around advanced data analytics team and project management in three multinational companies. I'm a certified lean Six Sigma green belt as I lead the project with early savings of over $200 thousand. And it is my pleasure to welcome you today to this lean Six Sigma yellow belt training series. In this course, we will explore Lean Six Sigma Yellow Belt measure tools like data collection plans, basic statistics, measurement system analysis, and many under measure tools. I am so excited to have you here. This knowledge has completely transformed my career and I'm looking forward to sharing this with you. I am confident that this actionable information, the demos and the tools that we will bid together will have a significant positive impact on your professional life. So without further ado, let's get started.
2. Calculate with confidence the Mean, Median, and Mode: In this demo, I will share with you how to calculate six basic statistics measures. So that should be able also to retrieve these measures. And being able to calculate these measures, your self is also very important because in the body of knowledge, the, this part has an apply status. So it's not only about the awareness that you understand how these measures work, but as well being able to calculate them. So we are in all go to Excel. And I'll show you here does three tabs. But first of all, it's important that you also download this XML file. And you will find that in the resource section that comes with this lesson, just click on download and open and enable the file and to be able to follow along. To follow along, you'll understand more and then you will be also capable of calculating these measures faster than if you just watch the demo. Now this file has three tabs. We're worksheets you if you want to call them this way. The first one is D example, and we will go through the measure step by step using this data set. The second one is an assignment tab. And at the end of this video, I will give an assignment for you to calculate all the six measures. And then in the third tab, you have the basic statistics measures, their definition and the result considering the dataset from A123. So this is a great reference for you to have a place where you can go. If you're not sure about the definition or how to calculate a specific measure. Let's go back to the example and we have here a data set that is very simple, just three points. I selected a specially in this way, so that is easy for you to follow and understand. These numbers could be anything from number of defects in awake from and let's say minutes spent in operating one step of the process and specific days on a daily basis and so on. Alright, let's now see how do we calculate two. We start with the mean. So minis D, actually the average. And if you just select the numbers, you will see that the total is 12. And there are three observations. So we have an average of four. And the average, as you know, is the sum of the observation divided by the count of the observations. So here we can also write and calculate that in a formula. So in Excel we have the average formula type, start typing branch, and then hit tab for the exile to auto-fill and then finalize your formula. Click Enter, and you can see that the mean is now for moving on to the median. And the median is the central value of a set of observation that are arranged in ascending or descending order. So the first thing that you want to check and do is to see if the observations are sorted. So in our case they are in an ascending order. But if not, you just go and sort them. First. You want to find that point that basically splitting the dataset into two different sets, the upper and the lower set. And now cases three, because here this is the value and above three I just have one value and below three I have another value. So one value here. And what very hears this is the value that splits the data set in half. Alright, so if we just consider more values like ten or 14, the dataset will be split here by eight because we will have two values, a first subset and also to values in the second subset. Now, the thing to understand is working when you have an uneven number of observations, or in our case it was three. Now in this example, they are five. But when you have uneven case, let's put your 20 for example. Now, the median will calculate, will be splitting basically this into 22 or 33. Right? So to exactly the same number of observation in that the two subsets. In this case, the median will be calculated as the average between these two middle values. So in our case it will be nine. Let me showcased that very simple. We have also the formula and we select our internal hit enter. As you can see, the median is nine. But if I remove one of my values, the median is eight. Moving on to the Lord and the mode is the most frequent value in a dataset. As you can observe, in our data set, we actually don't have a value that is repeating. So if we use exome formula mode and we select our dataset, finalize the formula, the reasonable value that is repeating, So we get an error. However, if we change and let's assume that this is ten. Now, you see that the value that is most repeating in our dataset is ten. If we had eight repeating three times, compared to ten repeating two times than the mode would be eight.
3. Calculate with confidence the Range, Variance, and Standard Deviation: Moving on now to the range. And the range is basically the difference between the highest and the lowest value in our dataset. In our case, the highest value is ten and the lowest value is one. Form the mode for the range. We don't have a formula, but just pretty simple. The highest minus d, lowest sign our cases nine. You can also calculate using max from this range, minus min, the minimum of this range. Lastly, we will cover variants and standard variation. Now these are a bit more complex terms, but there will take it step-by-step. I will also show you, besides the step-by-step approach, couple of formulas that you can use to simplify the process. But first of all, let's create simpler dataset with three points and let's say 23. So that would be 56. No seven. Alright, and now the way we can calculate the range is to do a step-by-step calculation. And we have the formula in the definition tab. So we want to subtract from the value. So here the observation i is the first observation, so it is the first value in our case is two. We want to subtract the average, make the square of that division, and then summarize all these observation minus average squared. All right? And then we will do next step, what we will do a division, and then we will be done. Okay, so the first thing is we want to calculate the observation value minus the average. So in our case, the average is four and the observation would be 237. So it is basically the first one minus the average, which is four. I will just put four in this case, you know, Squared. And here we have basically one because f3 minus four minus one squared is one. Okay? And here we have seven minus four, which is 33 squared is nine. Okay? So now when we calculate the sum, the sum is 14. So we calculated this upper part, some of observation minus average squared. Okay, so that is for teen. Now it's very important that you are able to do this step-by-step. But also if you have Excel, you can use this formula to calculate this sum, which is dev S q, d returns the sum of squares of the deviation of data points from their sample mean. Sounds complicated, but once you use it, you just select your data points. And you're done. In a second. You'll see it's 14, so it's an alignment while we have here. Alright, there is a one small step for the hard part now is done. There is one more step to get the variance. And this is the step where you divide these 14 that you've got here, the sum by the total number of observations minus one. So we have three observation, three values minus one is two. Okay? So we go back and we have, the variance is seven, okay? And the standard deviation is the root square of that seven of that variance. So pretty easy once you calculate the variance to also calculate the standard deviation. Or you can use the square SQRT formula and square of this cell. So to sixty four, fifty seven, fifty one. And this is how you do it step-by-step on the thing. This is important that you have the knowledge, oh, and being able with a calculator to get to this value. But let me show you a trick and let me show you a formula that enables you to obtain this value in a second if you are working with Exxon and, and for that you just start typing stdev and selective on this old one. Still available. Select your interval, closed bracket. It enter. And as you can see, we obtain the exactly same number for the standard deviation in just one step. Alright, and now let's test your knowledge with the assignment. So you have here the dataset and calculate the mean, median mode, range, variance, and standard deviation, either using the step-by-step NOT told that your observation or using the formulas that are also available here in the definition part, the last tab. Okay, so free, free to download this file, go to assignment. And when you feel stuck or you need some more information, go to definition and get the information from there. Okay, good luck.
4. Learn the Data Collection Plans: And this lecture we will cover data collection plans. We will specifically look at the definition of a data collection plan. Data sources, methods to collect data, and also frequency of data collection. First of all, what do you think it's a data collection plan? A data collection plan is a detailed document. It describes the exact steps as well as the sequence that needs to be followed in gathering the data for the given Six-Sigma project. This document is important because the people that designed the data gathering plan could be not the same people that will actually be collecting the data. And document ensures that one on the Six Sigma project team has the same understanding of what, when and how the data will be collected. Data sources and data sources are also referred as the where part, where might not indicate the physical location as much as it refers to the location within the process. Let's have a look at the data collection plan that I share here. This is the plan for a Certified Green Belt Lean Six Sigma project. And first-day test servers is in the is the IT system used to collect data. The second data source is actually a physical measurement of the time spent in operating the process. The method of gathering or collecting data is presented in this plan in the last column. It is also referred as the how part of the data collection plan. As you can see, it has a double role. Firstly, it specifies in which tools data points will be collected and stored. For example, excellent spreadsheet. Secondly, it gives a clear indication on which Six Sigma quality tools will be used to analyze this data further. Finally, the frequency of data collection. The data points need to be collected over a period of time. That data collection plan tells exactly at what frequency do data needs to be gathered. This is a part of experiment design and must be agreed by the data collection team without the slightest changes. A great insight that I can give you on the frequency of data collection is the following. A more frequent collection, for example, daily or weekly compared to a monthly one. We'll enable for a project that finishes faster. On the opposite side, the monthly data collection can slow down. The project has burned a waiting times to collect sufficient data points both before and after the processing one phase. So if possible, more frequent is better than less frequent.
5. Master the difference between Qualitative and Quantitative data: In this lecture, we will cover two types of data and the differences between them. What is the qualitative data and what is quantitative data that look at some examples and distinctions. To qualitative data is information that cannot hope, can not be expressed as a number. On the other side, quantitative data is information that can be quantified, that can be numerical. Qualitative data is descriptive data, for example, color or gender passed or failed, good or bad, the category names and so on. Quantitative data is numerical data is the height, weight, age, the number of defects, the distance, the total time spend in operating a process or a step inside of a process. The temperature, monumental costs and savings, and so on. Qualitative data is collected through participants observations, and most Pacific is collected using the five sentences. While quantitative data is collected through measurement instruments, for example, rulers, thermometers and so on. Let's now go back to the data collection plan that I showed in the previous lesson from the greenbelt Lean Six Sigma project. The question is here, is this data that was collected for the project is qualitative or quantitative. So first of all, where do you look in this plan? You will look at the first column. And the, what, what we collected. The first measure collector was overcompensation and up this amount paid wrongly due to a specific route calls. Now, this homolog, basically as money, has a financial impact. And the second measurement was taken on the time spent in operation. So this is basically our minutes and seconds and so on. So is this data, both of them are actually, are this data qualitative or quantitative? I hope your answer was quantitative, as you can see here. This is data that can be quantified. This is numerical data like money or time. Alright, hopefully now that distinction is clear. Let's move on and cover an under measure topic.
6. Data Collection Techniques: In this lesson, we will cover data collection techniques and in particular, surveys, interviews, check sheets, and checklists. A survey is research method used for collecting data from a predefined group or respondent to gain information and insights into various topics of interests. Fundamentally, a survey zone method of gathering information from a sample of people. Traditionally we the intention of generalizing the results to a larger population. Surveys provide a critical source of data and insights for nearly everyone engaged in the information economy, from businesses and the media to government and academics. There are four mod of survey data collection that are commonly used. Face to face surveys, telephone surveys, self-administered paper and pencil surveys, and self-administer computer surveys, or typically they are online. Online survey software has been the most popular way of conducting survey research for over a decade now. And because getting faster insights is imperative to business success, more and more companies are migrating to digital solutions. I will share reducing the next lesson, a step-by-step process to create a free online survey using Google forums. Interviews. An interview is structured conversation when one participants asks questions and the other provides answers. Interviews are often used in qualitative research in which firms try to understand how consumer think. Consumer research firms sometimes use computer assisted telephone interviewing to randomly dial phone numbers to conduct highly structured telephone interviews with scripted questions and responses entered directly into the computer. Check sheets. Another technique in collecting data is represented by the check sheets. A check sheet is structured pre-birth form for collecting and analyzing data. This also generic data collection and analysis tool that can be adapted for a wide variety of purposes. When to use a check sheet. When data can be observed and collected repeatedly by the same person or at the same location. When collecting data on the frequency or patterns of events, problem's defects and effect colocation defect causes are similar issues when collecting data from a production process. This is a topic that we covered in more detail in the Seven Quality Tools, part one lecture, checklists. A checklist is a data collection technique that involves listing a set of required actions or steps in a process and a status box where they can be marked as not started in progress and completed.
7. Create a free Online Survey using Google Forms (step-by-step): And this lecture I want to show you how to create a free online survey using Google Forms. And this is important because this topic and the value of knowledge is treated as an applied topic compared to many others which are just understand and awareness. So the purpose would be for you to only to have the awareness about surveys, but also to apply the knowledge and be able to create one. To get started and just open your browser. And you wanna reach the Google Forms page. And you can do that by either using this link here shared, but sometimes the link with change. So it's not certain that this mistake is same in the features and the way I do it at your IGES Google Google Forms. And then I'm able to open this page with me log n, so you need to have an account to do that. And as you can see here, you have a couple of templates that you can use for your survey. You have also a bland template that we will use in the moment and the reason forms that were created. And let's start by clicking this plus. And this will open a form. So you have here two tabs, questions and responses. And in this tab questions you will be working on the formula, will be designing group, putting a title. And let's imagine that we want to sort of end users so that we can collect some insights about how they use Microsoft Excel. Now we change the name. Let's say working with Microsoft Excel, you can also put out a description. But let's go to the questions and now here we just type your question, survey question. What is your biggest a pain point in working with Excel? I'm addressing here an open question. And I did that on purpose to show you that we have a couple of options here on the right. And the multiple choice is not the one that will work for this question. So the users need to be able to enter a response, a short response. So we can select a short answer. On our case. Then you have here the plus for a couple of options you have that plus two crew. And the question, import, change tile, description, images, video, and section. So you want to add that question. And let's say this would be a multiple choice. Or do you plan to learn in Microsoft Excel? Okay, so we have here now the Options and you'll fill in the options. For example, formulas. Click here to add the second option. And you see the field is already transformed us adults option to charts. You can also learn VBA and so on. So once you're ready, you don't need to save it because it's auto save. While you need to do is to send it. So the way it works, click on sand. And there is an important button on tops of Juana used those email adress further on. You enable this option, collect email addresses. So now if I just exit, you see that there is an order, not question, but another field to be filled in, which is mentoring and the users are required to provide this information in order to submit the survey. So let's go again sand. And you can use for sure email or link. And here just put the distribution, your distribution list. You have the subject already and very important that you personalize a bit this message and give more details and also state how long for them will be to fill in the survey and so on. So there are a couple of best practices also, if there is a benefit for them, you can mention that will help with the response rate. The other cool thing is this option to include the forming an email. And this option makes it even simpler for them because they don't need to go to a site, fill this out and can already do that in the email and submit. All right, this is how you create an online survey using Google Forms. Currently is free, sample and fast.
8. Congratulations! Thank you.: All right, congratulations on completing this course. For free to re-watch some of the lessons for better results. I'm confident that this knowledge will help you tremendously in your career. If you liked this course, then feel free to continue your Lean Six Sigma training with my next material on this topic. Thanks so much for watching, and I'll see you in the next class.