Mahmood

How did the idea for the book originate, especially considering its connection to Jashn-e-Talat, the concert you organized? An early picture of singer Talat Mahmood The idea for the book originated from a personal experience. Growing up, I knew Talat Mahmood as my grand uncle and had interactions with him as a family member. It wasn’t until much later in my journalism career, around 15 years in, that the concept took shape. Despite having friends in Bollywood reporting, and legends like Lata didi, I never…

Statistics in R SeriesPhoto by Aaron Burden on UnsplashIntroductionReal world data, oftentimes, contains extreme values that can lead to skewed distribution. Skewed data is not suitable for many statistical analysis. The presence of one single outlier can drastically change the overall statistics of a distribution. Therefore, these extreme values need to be handled carefully. If there is no justification for these outliers, the general guideline is to get rid of those. In this article, we will go through the effect of…

Statistics in R SeriesPhoto by Vladimir Fedotov on UnsplashIntroductionWe have covered logistic regression models for both binary and ordinal data and also demonstrated how to implement the model in R. Moreover the prediction analysis using the R libraries was also discussed in earlier articles. We have seen the impact of single as well as multiple predictors on the response variable and quantified it. Binary and ordinal response variables were taken to show how to deal with different types of data. In this article, we…

Statistics in R SeriesPhoto by Jen Theodore on UnsplashIntroductionWe have covered various types of logistic regression in the past several articles. The goal of all these models is to predict future data points as well as intermediate data points as accurately as possible. In this article, we will go through how this prediction analysis can be done in R for simple and multiple logistic regression using both binary and ordinal data.DatasetThe Adult Data Set that is available in the UCI Machine Learning Repository will be…

Turn your ramblings into masterpieces, on demandImage generated by the author using Midjourney on General Commercial Terms.Recent advances in Generative AI have led to the launch of a whole host of services such as DALL-E 2, Midjourney and Stability AI that have the potential to drastically change the way we approach content creation.In this post I show you how to build and serve your very own, high performance, text-to-image service over an API. Based on Stable Diffusion via HuggingFace, using Vertex AI Workbench and…

Leer en español.Rajesh Randev, a man from Vancouver, Canada, was rushing to pick up his kids from school, so he got in his Tesla Model 3 and started to drive over. However, after a good long while, Randev figured out that the car he was driving wasn’t his Model 3. As it turns out, he had stolen someone else’s Model 3 without realizing it, and to make matters worse, Tesla’s app had allowed him to open the car and take off as if nothing was wrong. The incident occurred on March 7, according to Global News. Randev confused…

Statistics in R SeriesPhoto by Edge2Edge Media on UnsplashIntroductionWell, if you have covered my previous articles about “Statistics in R Series”, you may have a good understanding of logistic regression implementation in R and also a fundamental understanding of the different types of logistic regression models. We have come a long way in the regression world and have covered binary, proportional odd (PO), generalized as well as partial proportional odd (PPO) models. In this article, I am going to discuss multinomial…

Statistics in R SeriesPhoto by Joshua Sortino on UnsplashIntroductionWe have previously executed a generalized ordinal logistic regression model where the effect of explanatory variables was allowed to vary across different levels of the response variable. When we find out that some of the predictor variables violating the proportional odd assumption, we can allow the effect of only those variables to vary across different levels of outcomes. This type of model is called the partial proportional odd (PPO) model.Background…

Statistics in R SeriesPhoto by Antoine Dautry on UnsplashIntroductionWe have gone through several logistic regression models which are capable of performing both simple and multiple regression analysis for both binary and ordinal response variable. The outcomes of these logistic regression models are typically the coefficients of all the predictor variables. One of the fundamental assumptions that we made is the proportional odd assumption. Under this assumption, we assume that the coefficients of the predictor variables…

Statistics in R SeriesPhoto by NordWood Themes on UnsplashIntroductionIn simple logistic regression, we have only one predictor variable whereas in multiple logistic regression, there are more than one predictors. The response variable can be binary as well as ordered. For example, the response variable can be just a choice between two categories like city or village, healthy or sick, employed or jobless, educated or illiterate. The response variable can also be ordinal where there can be specific levels from low to high…