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My Data Analysis Site
United Kingdom
Приєднався 15 лют 2018
Essential R Skills: Part 5
In this short video, I demonstrate how you can easily re-run your code and also how you can easily output your results in a convenient format; specifically, HTML, pdf, or Word document.
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Відео
Essential R Skills: Part 4
Переглядів 162 місяці тому
IN this video I cover the essential skills and methods needed to perform regression analysis on time series data.
Essential R Skills: Part 3
Переглядів 242 місяці тому
In this video. I show how to perform some standard regression analysis on cross-section data.
Essential R Skills: Part 2
Переглядів 262 місяці тому
In this second video (of 2) I show how to subset and filter your data set. And I look at some simple ways to identify and exclude cases with missing values.
Essential R Skills: Part 1
Переглядів 472 місяці тому
In this first video (of 2), I show how to carry out some basic analysis of cross section data containing categorical and numeric variables. I show how to create and chart frequency distributions and cross tabulations. And also how to perform a simple chi-square test.
Data Analysis with Python: 11. Regression Part 4
Переглядів 525 місяців тому
In this second video on regression analysis of time series data, I look at how to carry out an F test of a linear restriction manually. I also show how to create a multi-graph chart using a nice feature of matplotlib.
Data Analysis with Python: 10. Regression Part 3
Переглядів 395 місяців тому
In this first video (of 2), I show how to carry out regression analysis of time series data using, again, the excellent statsmodels package. I show how to estimate a regression equation which includes lagged and differenced variables, plus how to draw some standard charts useful for diagnostics. I also look at how to perform a Breush-Godfrey test for autocorrelation.
Data Analysis with Python: 9. Regression Part 2
Переглядів 495 місяців тому
In this second video (of 2), I look at how to carry out typical specification and diagnostic tests on a cross-section regression, in particular testing for heteroscedasticity with the Breusch-Pagan test. I also show how to estimate an equation using Weighted Least Squares.
Data Analysis with Python: 8. Regression Part 1
Переглядів 715 місяців тому
In this first video (of 2), I show how to carry out regression analysis of cross section data using the excellent statsmodels package. I cover the two methods available for estimating a regression equation, plus how to draw some standard charts useful for diagnostics .
Data Analysis with Python: 7. Time Series Data Basic Analysis 2
Переглядів 305 місяців тому
In this video (the second of two), I cover how to apply functions to the data such as the mean; how to create a scatter graph; and how to use the transform function to create an index number series, lag the data, and calculate the growth rate.
Data Analysis with Python: 6. Time Series Data Basic Analysis 1
Переглядів 806 місяців тому
In this video (the first of two), I show how to do some basic analysis of time series data. I cover how to import the data correctly by, if necessary, creating a suitable time index variable; how to subset the data; how to create line graphs of various types; and how to save a chart to disk as a pdf file.
Data Analysis with Python: 5. Cross Section Data Basic Analysis Part 2
Переглядів 676 місяців тому
In this video (the second of two), I continue looking at how to carry out some basic descriptive analysis of cross section data containing categorical and numeric variables. I show how to create cross tabulations with the crosstab and pivot_table functions (as an alternative to using group_by). I also show how to carry out a simple Chi-square test of independence.
Data Analysis with Python: 4. Cross Section Data Basic Analysis Part 1
Переглядів 1166 місяців тому
In this video (the first of two), I cover how to carry out some basic descriptive analysis of cross section data containing categorical and numeric variables. I show how create and chart a frequency distribution of a categorical variable, and a histogram of a numeric variable. I then show how to create and chart a simple cross-tabulation (or pivot table) of two categorical variables.
Data Analysis with Python: 3. Basic skills Part 2
Переглядів 336 місяців тому
In this video, I look at how to select columns (variables) and rows (cases), and how to filter data with the query function to focus on a specific subset of your data. I also show how to creat a simple frequency distribution of a categorical variable, and how to plot that distribution with a basic bar chart.
Data Analysis with Python: 2. Basic skills Part 1
Переглядів 586 місяців тому
In this video I cover how to import the required packages, import a data set, and how to clean the data set by removing missing values,
Data Analysis with Python: 1. Getting Started
Переглядів 976 місяців тому
Data Analysis with Python: 1. Getting Started
Using Logs to Chart Time Series Data
Переглядів 2,3 тис.3 роки тому
Using Logs to Chart Time Series Data
Multiple Regression Analysis with Excel: Part 2
Переглядів 5433 роки тому
Multiple Regression Analysis with Excel: Part 2
Multiple Regression Analysis with Excel: Part 1
Переглядів 1,3 тис.3 роки тому
Multiple Regression Analysis with Excel: Part 1
21. Using RMarkdown to create Documents
Переглядів 3004 роки тому
21. Using RMarkdown to create Documents
Thank you very much
super useful! thanks so much
Bravo 👏, great video . Thanks a lot sir for sharing your knowledge 😊
very useful!!!!!!!!!!!!!!!!!!!! Love you
Hey, loved the video and was super helpful for understanding my thesis! I would like to ask though, why did you calculate the ln of q,k,l if there is no logarithm in the equation?
Btfl lecture. I like it ❤
Very nice presentation
Nice presentation.
very clear and logical explanation! Thank you
Thanks for the guidance, appreciated.
Can you plz provide the data for this exercise?? Thnx!!
such a great guider about the data analysis , like it 😍
Thank you very much sir 😊
Very insightful and well structured video but ones you applied the differentials and the afc showed some of the data being unstationary ...you suggested an ARIMA mode of (3,1,0)...whats the bases of that suggestion
A big thanks to you!
turn up your audio...WE CANT HEAR YOU!
thank you sir it was very useful 👍
Such a well articulated and to the point video . Really deserves more views . Thanks
Sir, If I am doing double exponential smoothing 5 period moving average with a software program--after 5 period exponential moving average is calculated say (X) does computer do second calculation with data X and (X-t1) (X-t2) (X-t3) (X-t4)- - - - forgive me,I went to college 50 years ago..(X-t1) is exponential moving average one period prior & so on.Thank you.
Crackin' presentation. I got a lot out of that, thank you!
Very clear and educative presentation.
life saver
Been looking for how to do it manually everywhere. Finally found a video.
Lecture is very important for forecasting. Everything is here.
Nice lecture sir. Thanks but i have a doubt and wishes to share with you. Can you please share your email id to share the problem in ARIMA modelling, I face.
Great video, thank you.
Thank You So much Sir ❤️ from Bharat 🙏😊
Simple explanation.thanks
Excellent, and to the point.
where does splitting data into train and test sets fit into this ? I thought we only select the model with lowest Aicc or BIC based on how the training set performs on the test set?
I don't think that approach is appropriate with time series data because the observations are not independent and you can't simply extract some of the data into different sets or you would destroy the integrity of the data.
Please adjust your speaker. Your voice is not heard properly
this video is useful to me🤗🤗🤗☺ thank you😇
How do I make SPSS accept triennial intervals (Like 1989, 1992, 1995) in the 'define date and time' options?
in this example there is no MA since the q=0, what if we have MA, for instance if the q = 1? where should we put that MA lag into the equation from this example?
Why u didn't take the average of values as it is moving average??? R u sure u r teaching a right method in right way??
4:24 divide CMA by 8 why shouldn't it be 4????
I agree, I believe if he is taking the moving average to find the level he should be dividing by 4 not 8, however, it appears that he made 2 steps summaion. 1- He summed 4 periods, then he sumed 2 of 4s which I didn't really understand why
Please help me about time series expert modeler
Nice video sir
What is the difference between deseasonalizing a value in a multiplicative and additive model?
if you could speak bit clearly, i had to play like 5 times the same thing to understand.
Thanks! This is very useful when you want to convert an ARIMA model into an Excel Formula.
Please can I have the excel data to practice in SPSS
Can you provide the excel sheet? I would highly appreciate it.
why in other videos when finding the quartiles they are using the function "=quartile" when you are using "=quartile.exc". thank you!
QUARTILE is an old function just kept for backward compatibility reasons. See explanation here: support.microsoft.com/en-us/office/quartile-function-93cf8f62-60cd-4fdb-8a92-8451041e1a2a
Speaker volume is too low. He is murmuring only in his mouth.
Deserve subscription 👏
sir how to estimate constant, lag 1, lag 2 and lag 3 manually
Great. What if we have moving average term as well, can help with equation for that as well?
hi, sir. Thanks for the video. May I ask what will the process if the series is I(2). is it will be y t -y t-1 - yt-2 for independent variable, and apply the same logic for dependent variables? My second question is that is there any examples for MA(1) or MA(2) manual forecasting?
Hi. 1. Yes, you apply the same idea because the parameters are with respect to the stationary time series and with some algebra you will get the forecasted value for the original non-stationary time series. 2. You first fit the AR(p) model. Calculate the residuals and use it as the proxy of your errors. Now you have 2 options, to use your series of your residuals as proxy to the errors or calculate the variance of the residuals and simulate the errors from Normal distribution with mean 0 and the calculated variance. Either way you will obtain the series of errors and applying the same idea as in the video will allow you to forecast ARIMA(p,d,q) manually. All the best!
very clear but unnecessarily long. wish we could have a more simplified process