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ClassicQuants
India
Приєднався 4 лип 2021
The idea behind this channel is to help the students, professionals, and industry experts to learn the concepts of operations management, operation research, and management science in the most lucid and easy-to-understand manner. We will strive to incorporate all the concepts/ frameworks that are/ can be used to improve operations in the workplaces (irrespective of industry and domain). Management education, all over the world has become too expensive and not all can afford the same. Our goal is to provide these training modules/ standalone videos to those who want to optimize their workplace but are not yet lucky enough to get a degree from a management education institute. Needless to say, the students in masters and bachelors of management education will be the prime beneficiaries though. By learning these concepts, the viewers will be able to apply them readily. The instructor will also be associated with the subscriber in improving the content and help them apply the concepts.
6. Probability & Distributions - Part 2 I #poisson_distribution | #business #statistics
Probability & Distributions - Part 2 I #poisson_distribution | #business #statistics #management #statistics #probability
In this video, I have explained the theory and underlying story behind Poisson distribution, its PMF and CDF, and then explained the calculations using a spreadsheet. I have also compared Binomial and Poisson distribution and shown, with calculations, when and how we can use binomial distribution to compute Poisson probabilities.
Other playlists in this channel:
Optimization using Excel (ua-cam.com/play/PLmP64hoCcu5GQhUTuv6Cgr5QE083DY2wQ.html)
Business Forecasting (ua-cam.com/play/PLmP64hoCcu5GxPm6vbgQ5hlz3vvyhnHFL.html)
Simulation (ua-cam.com/play/PLmP64hoCcu5F79Ik2z197n2T7vzR4hD9y.html)
In this video, I have explained the theory and underlying story behind Poisson distribution, its PMF and CDF, and then explained the calculations using a spreadsheet. I have also compared Binomial and Poisson distribution and shown, with calculations, when and how we can use binomial distribution to compute Poisson probabilities.
Other playlists in this channel:
Optimization using Excel (ua-cam.com/play/PLmP64hoCcu5GQhUTuv6Cgr5QE083DY2wQ.html)
Business Forecasting (ua-cam.com/play/PLmP64hoCcu5GxPm6vbgQ5hlz3vvyhnHFL.html)
Simulation (ua-cam.com/play/PLmP64hoCcu5F79Ik2z197n2T7vzR4hD9y.html)
Переглядів: 29
Відео
5. Probability & Distributions - Part 1 I #binomial_distribution | #business #statistics
Переглядів 496 місяців тому
Probability & Distributions - Part 1 I #binomial_distribution | #business #statistics #management #statistics #probability In this video, I have started defining fundamentals of probability very briefly from where I moved quickly to distributions. I have defined and explained the and continuous distributions and shifted by attention to discrete distribution - more specifically the binomial dist...
4. Descriptive Statistics - Part 3 I Business Statistics | #statistics #management #business
Переглядів 187 місяців тому
Descriptive Statistics - Part 3 I Business Statistics | #statistics #management #business In this video, I have covered descriptive statistics percentile, quartile, box plots, scatter diagram, and time series plots. At the end, I have presented the tools and charts in descriptive statistics to be used under various contexts/ questions to be answered. Link for the data used: www.google.com/url?s...
3. Descriptive Statistics - Part 2 I Business Statistics | #statistics #management #business
Переглядів 337 місяців тому
Descriptive Statistics - Part 2 I Business Statistics | #statistics #management #business In this video, I have covered descriptive statistics report reading, histogram, and dot plot using Minitab 19. Link for the data used: www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwih6cqkwauFAxXr9zgGHSAEDocQFnoECBUQAQ&url=http://jse.amstat.org/v19n1/cafedata.xls&usg=AOvVa...
2. Descriptive Statistics - Part 1 I Business Statistics | #statistics #management #business
Переглядів 267 місяців тому
Descriptive Statistics - Part 1 I Business Statistics | #statistics #management #business In this video, I have introduced the basic concepts of descriptive statistics. This is the foundational knowledge required for computing descriptive statistics using Excel or Minitab at a later stage. The concepts discussed are as follows: Population Sample Parameters Statistic Central tendency Dispersion ...
1. Introduction I Business Statistics | #analytics #statistics #management #business #msexcel
Переглядів 1267 місяців тому
Introduction I Business Statistics | #analytics #statistics #management #business #msexcel This is a brand new lecture series where I have started to explain the concepts and applications of business statistics. This is the first video which is just an introduction video. In this video, I have discussed the plan to move forward. In the last two slides, I have tried to explain what does a statis...
5. Triangular and Exponential Distributions | Simulation using Excel #simulation #msexcel #analytics
Переглядів 1008 місяців тому
Simulating Triangular and Exponential Distributions | Simulation using Excel #msexcel #analytics This is the fifth and final video of the 'Simulation' video series. Here, we have shown the process of developing inverse functions for Exponential and Triangular distribution for no direct inverse function is given with Ecel's native functionality. For Exponential distribution, we have shown two me...
4. Simulating Discrete Distributions | Simulation using Excel #simulation #msexcel #analytics
Переглядів 1218 місяців тому
Simulating Discrete Distributions | Simulation using Excel #simulation #msexcel #analytics This is the fourth video of the 'Simulation' video series. Here, we have shown the process of building a simulation model when the underlying distribution is Discrete in nature. In a discrete distribution, specific number of outcomes have specific probability and no other outcome is possible except for th...
3. Profit Model using Data Table | Simulation using Excel #simulation #msexcel #analytics #business
Переглядів 1409 місяців тому
Profit Model using Data Table | Simulation using Excel #simulation #msexcel #analytics #business This is the third video of the 'Simulation' video series. Here, we have again developed the basic profit model as we did in the second video of this series - the only difference being, we used the data table functionality of Excel to develop the model. We have explained the benefits of using data ta...
2. Simulating the Profit Model | Simulation using MS Excel #simulation #msexcel #analytics #business
Переглядів 1569 місяців тому
Simulating the Profit Model | Simulation using MS Excel #simulation #msexcel #analytics #business This is the second video of the 'Simulation' video series. Here, we have developed the most basic simulation model using the total profit equation that we elaborated on in the previous video. The total profit equation is written as TP = (s - v)*Q - F where s, v, Q, and F are selling price, unit var...
1. Introduction to Simulation | Simulation using MS Excel #simulation #msexcel #analytics #business
Переглядів 28510 місяців тому
Introduction to Simulation | Simulation using MS Excel #simulation #msexcel #analytics #business This is the first video of the 'Simulation' video series. Here, we have introduced the idea of computer simulation - the reason and the advantages of it. A simulation imitates the operation of real-world processes or systems with the use of models. The model represents the key behaviors and characte...
Forecasting Promo | Business forecasting #demand #forecast #qualitative #quantitative
Переглядів 3,2 тис.Рік тому
#demand #forecast #qualitative #quantitative This is the promo video for the Business Forecasting series The previous module: Optimization using Excel: ua-cam.com/play/PLmP64hoCcu5GQhUTuv6Cgr5QE083DY2wQ.html HBR Article "Six Rules for Effective Forecasting" by Paul Saffo: hbr.org/2007/07/six-rules-for-effective-forecasting What is qualitative and quantitative forecasting? Quantitative forecasti...
9. Dividend Discount Model (DDM) | Security Analysis for Investments #finance #investing #valuation
Переглядів 113Рік тому
Dividend Discount Model (DDM) | Security Analysis for Investments #finance #investing #valuation #fdff #dcf In this video, we'll be discussing the security analysis for an investment with a DDM (Dividend Discount Model). We'll go over the different factors that need to be taken into account when undertaking a security analysis, as well as the important financial ratios that need to be evaluated...
8. Free Cash Flow to Firm (FCFF) | Security Analysis for Investments #finance #fdff #dcf #valuation
Переглядів 130Рік тому
Free Cash Flow to Firm (FCFF) | Security Analysis for Investments #finance #fdff #dcf #valuation Free Cash Flow to Equity (FCFE)|Security Analysis for Investments #finance #accounting #tatasteel #fcfe #dcf #wacc #discountedcashflow #investing In this video, we'll be discussing the security analysis for an investment with a FCFF (Free Cash Flow to Firm). We'll go over the different factors that ...
7. Free Cash Flow to Equity (FCFE) - PART-2 | Security Analysis for Investments #finance #tatasteel
Переглядів 175Рік тому
Free Cash Flow to Equity (FCFE)|Security Analysis for Investments #finance #accounting #tatasteel #fcfe #dcf #wacc #discountedcashflow #investing In this video, we'll be discussing the security analysis for an investment with a FCFE (Free Cash Flow to Equity). We'll go over the different factors that need to be taken into account when undertaking a security analysis, as well as the important fi...
6. Free Cash Flow to Equity (FCFE) - PART-1|Security Analysis for Investments #finance #tatasteel
Переглядів 289Рік тому
6. Free Cash Flow to Equity (FCFE) - PART-1|Security Analysis for Investments #finance #tatasteel
5. Calculate WACC for Tata Steel | Security Analysis for Investments #finance #valuation #wacc
Переглядів 2,2 тис.Рік тому
5. Calculate WACC for Tata Steel | Security Analysis for Investments #finance #valuation #wacc
4. Weighted Average Cost of Capital (WACC) | Security Analysis for Investment
Переглядів 160Рік тому
4. Weighted Average Cost of Capital (WACC) | Security Analysis for Investment
3. How to Calculate Cost of Equity using CAPM | Security Analysis for Investments
Переглядів 371Рік тому
3. How to Calculate Cost of Equity using CAPM | Security Analysis for Investments
2. What is β? - An Overview of Market Risk and Firm-Specific Risk | Security Analysis for Investment
Переглядів 196Рік тому
2. What is β? - An Overview of Market Risk and Firm-Specific Risk | Security Analysis for Investment
1. Introduction to Valuation | Security Analysis for Investments | Basic finance; Personal Finance
Переглядів 255Рік тому
1. Introduction to Valuation | Security Analysis for Investments | Basic finance; Personal Finance
META LAYOFFS: 11,000 People Officially Fired, Pushed Out the Door
Переглядів 133Рік тому
META LAYOFFS: 11,000 People Officially Fired, Pushed Out the Door
17. Box-Jenkins Method (ARIMA) - PART-3 | Business Forecasting
Переглядів 6042 роки тому
17. Box-Jenkins Method (ARIMA) - PART-3 | Business Forecasting
16. Box-Jenkins Method (ARIMA) - PART-2 | Business Forecasting
Переглядів 9262 роки тому
16. Box-Jenkins Method (ARIMA) - PART-2 | Business Forecasting
15. Box-Jenkins Method (ARIMA) - PART-1 | Business Forecasting
Переглядів 3,4 тис.2 роки тому
15. Box-Jenkins Method (ARIMA) - PART-1 | Business Forecasting
14. Multiple Regression for Time Series| Business Forecasting #forecast #quantitative #data #demand
Переглядів 3122 роки тому
14. Multiple Regression for Time Series| Business Forecasting #forecast #quantitative #data #demand
13. Time Series Decomposition - PART 2| Business Forecasting #forecast #quantitative #data #demand
Переглядів 3062 роки тому
13. Time Series Decomposition - PART 2| Business Forecasting #forecast #quantitative #data #demand
12. Time Series Decomposition - PART 1| Business Forecasting #forecast #quantitative #data #demand
Переглядів 5822 роки тому
12. Time Series Decomposition - PART 1| Business Forecasting #forecast #quantitative #data #demand
11. Multiple Linear Regression Analysis| Business Forecasting #forecast #quantitative #data #demand
Переглядів 2482 роки тому
11. Multiple Linear Regression Analysis| Business Forecasting #forecast #quantitative #data #demand
10. Use these 5 methods in Excel for Linear Regression | Business Forecasting | #data #quantitative
Переглядів 8782 роки тому
10. Use these 5 methods in Excel for Linear Regression | Business Forecasting | #data #quantitative
Thanks
Thank you for the clear explanation. Well appreciated 😊
Hello i need the excel file you are working with
Sir please
Great Videos. Please keep it coming
Music in background is toomuch disturbing in such a serious subject
Excellent lecture!
Thankyou so much sir❤❤
Thanks you
Great, thank you.
Great content. Keep it coming please. These
Thanks for the video. These videos are top notch. Please do a series on ' ANNOVA'
I’m learning. Thank you.
sir these video are goldmine for me. I am a second year MBA student from Great Lakes Chennai and I am greatly benefitted from your videos. Just got to know that you are yourself an XLRI alum. Will share your channel with my batchmates, they will also be benefitted and hopefully you will gain some reach
Thank u sir plz tell me d book
It's from my own notes and understanding. Don't know which book covers this exactly as per the video
Chris Brooks book
How does one formulate this for 4 weeks and track inventory?
It will be formulated using a transportation production planning method. If you want a video, please let me know.
why i still get 0?
why i still get 0?
Check you model thoroughly. You will catch some mistakes definitely.
Thank you sir!
You are welcome!
Awesome Video
Just saved me tonight! Thanks!
Can you kindly post a video of the safety stock calculation when the demand pattern doesn’t follow the normal distribution
You need to plot the distribution for the lead time demand and see where is the 95% line (suppose the service level is 95%). The left side of the curve to that line will be the safety stock. An easier method is to use normal approximation. For example, if the distribution is Possion with a mean λ, then use an approximate normal distribution of mean=λ and std dev=√λ. Then use this normal distribution to find safety stock.
Thank you! I used this video to create my own chart in my Discrete math course. You explained it in way a that was easy to follow along 💕💕💕
Glad it was helpful!
Sir if the company not paying any dividend how to calculate RR ? RR will be 100% ? WAITING FO UR REPLY SIR,
Yes, it will be 100% or 1 because every portion of the profit is retained by the company.
Sir one more doubt, In the final stage of intrinsic calculation we have to devide Firm value with no of outstanding shares or no of issued shares ? And also is there any other term for principal repayment (source cash flow statement) Can we take finance cost paid, Short/long term borrowings These two comes under principal repayment
I always use Outstanding shares to divide
Thanks sir
All the best
My dear doctor, why did you put in all constraints less than or equal to 3? I did not understand this point
The MTZ constraint is Ui - uj + N*Xij <= N - 1. N equals 4, therefore the constraint has to be less then or equal to 3
Actually I didn't explain how the MTZ constraint works. My focus was not that, I focused only on implementation of the constraint Ui - Uj + N*Xij <= N - 1 where N=4 because we had 4 nodes here. So, the RHS becomes 4-1=3.
@@classicquants778 yes, i know, that was what i meant to say
@@classicquants778can you kindly explain what’s is this MTZ constraints, how it works and where should we use this
Excellent Sir
Thanks
ClassicQuants SIr chad🔥
ClassicQuant Bhai Chad
ClassicQuants Bhai OP
Quants bhai, ek hi toh dil hai kitni baar jitoge 🔥🔥
Sir ,pls also explain bass diffusion model of forecasting
The Output variance seems very large??
Does not matter. It is just an example problem. The data used is fictitious. Only the methodology is important.
Thanks
very honestly made very good video Sir
Thanks for watching
it was really clear and understandable explanation thank you so much!
Glad it was helpful!
Hello, I need some help in Optimization case study, Can you help?
Well Explained. Thank you
You are welcome!
thank you, can you please provide the excel sheet for this problem please?
I had not saved the file when I made the video. Will try to find it, if found will post.
Use the following link to get the file: docs.google.com/spreadsheets/d/1kWTEa-x3vxGNVZ6ocV_I_nqvvRzg9rYJ/edit?usp=sharing&ouid=107418194511757054983&rtpof=true&sd=true
Hey there, this is a great tutorial. May I ask if I want to to limit the solver to just solve 3 cities instead of 4, how can I do that?
Just delete one row to readjust the worksheet
@@schakraborty336699 Cool, do you know how can I choose which cities I want to optimize? For example I want 1,3,4 not 1,2,3?
Thank you.
Very Well explained
Keep watching
Please start making videos again
Will do. But nobody watches. It takes too much effort to make these videos. After that the subscription growth and watch time are really demotivating.
he is a very kind hearted man. currently i m freshers n improving my skills. i m personally helped by this channel. i just want to salute him. may god bless u.
Hello. Thank you for putting up your shortest path solution. I am trying to do something similar-but-more complex, and am having trouble, and I was wondering if you could give me some guidance. What I want to in Excel with shortest paths is: 1) layout a large m-by-n matrix of nodes, with distances in meters between them. I'll use pseudo-chess-board nomenclature with one axis being A-Z and one axis being numbered 1-n (calling nodes "A1", "C3", "F7", etc) 2) have the ability to request multiple shortest paths from (say) B3->F8, G2->A14, F2->R23, etc 3) partially congest a route based on previous paths. For example, if a route is found it may be tagged as 25% congested between two nodes. Another route may add to this. Eventually the route would be congested, and an alternative shortest path would have to be found. 4) ideally I'd like to make it iteratively optimise, but I realise that may be impossible to do in Excel, so the above congestion may have be sequentially built in Do you know of any examples where such a thing has been done? Thank you in advance, Adam
can you have the goal function being evaluated by a macro?
Too good🎉
Thanks a lot!!
Thank you so much for making such a complex concept so easy.
Thanks for the appreciation.
I would suggest you include comments on the "non-negative" checkbox. I think we typically take that "constraint" for granted, but of course that's not always the case. I might also suggest you explain the "INT", "BIN", and "DIF"" selections for constraint types. Really an excellent discussion. Looking forward to the rest of the video series. Thank you.
Using the SUMPRODUCT function to setup the constraints is a great idea. Really saves time.Thanks.
You're welcome!
This is a beautiful and well thought-out way to arrange your Excel spreadsheet for a classic optimization problem. Very helpful. The way you set up the Constraints for easy entry in Solver is quite clever.
Glad it was helpful!
Please, could you show how to solve the MILP problem? Thanks a lot
If you post the problem, I will try to make a video
I'm referring to the video example, transportation problem
@@giulianopierucci2903 But the video example is a simple application of a transportation problem which does not require MILP formulation. It is just an LP. MILP will be needed if other types of costs (e.g., fixed costs) are involved in the problem.
@@classicquants778 Sir please make a video about this drive.google.com/file/d/1QLdiRT3rzqgYntI6sJy5SOmhFCqUaTWf/view?usp=sharing , it is very good because it will connect between Transportation and Transshipment model. NOTE: Please use Excel, not Lingo. Thank you.
Can you include the plant operation cost for the same problem and post a video for solving by MILP
Hello. Please help me with this problem. Consider a set of city districts 𝐼. There is a candidate for building a medical emergency service station in every city district. The cost of building an ambulance station is given by the parameter 𝑓𝑖 and the total budget for building stations throughout the city is 50 million. Furthermore, if a station is built in city district 2, it must not be station built in city district 6. Determine in which city districts to build ambulance stations so that the maximum travel time is minimized. What is the optimal maximum travel time? The cost of building stations in the city district 𝑖 ∈ 𝐼, 𝑓𝑖 are: [32,20,25,30,40,29] The city districts and the driving distances between them are interpreted in the following graph: ( [[ 0, 4, 12, 27, 25, 58], [ 4, 0, 24, 16, 29, 38], [12, 24, 0, 31, 14, 30], [27, 16, 31, 0, 21, 8], [25, 29, 14, 21, 0, 11], [58, 38, 30, 8, 11, 0]]) The right answer is to build stations in districts 2 and 4, and optimal travel time is 24. But how can I solve it with excel or with Python, please, help me.