In statistics, a confidence interval is a range of values that is likely to contain a population parameter with a certain level of confidence. This level of confidence is typically expressed as a percentage and is often set at 95% or 99%. Confidence intervals are commonly used in statistical inference…

A matched filter is a signal processing technique that is widely used in a variety of applications to detect signals in noisy data. It works by designing a filter that is matched to the shape of the signal that is being transmitted or received. …

“Alone we can do so little; together we can do so much.” — Helen Keller In machine learning, bias and variance tradeoff is one of the key concerns for every practitioner while dealing with any algorithm. To tackle this tradeoff they can take advantage of some Ensemble Learning based techniques…

In our real world, we often search for a parameter or statistic of a specific population such as mean or standard deviation. But it is quite difficult to estimate these statistics from the population. In this case, we can collect some random data or samples from the population and can…

In my last two articles, we have looked at discrete probability distribution where data consists of distinct numeric values and we can specify the exact values of probability of each of the data. But in real life, maximum problems don’t involve this type of discrete data. In the case of…

In the previous chapter of discrete probability distribution, we have learned about discrete random variables, discrete probability distribution, and its expected value and variance. Discrete Probability Distribution : Part 1 | by Dhrubjun | Nerd For Tech | Sep, 2021 | Medium In this chapter, we will discuss different discrete…

What are discrete random variables and discrete probability distribution? In probability and statistics, a random variable is a quantitative variable whose value depends on the outcomes of a random phenomenon. For example, let us toss a coin 3 times and let X represents the number of tails that appear in that 3 tosses. Then X can take any one…

Why do we need measures of variability? The three main measures of central tendency or the three ‘M’s of statistics: the mean, the median, and the mode describe a single value that tries to describe a given data set by identifying the central position or typical value within the data…

Whenever we come across a machine learning problem or a Kaggle competition, we often get confused thinking about which machine learning algorithm/model we should use or which algorithm/model will give the best result. We need to verify the stability of our machine learning model so that after deploying it gives…