In this post, we dive into one of the core statistical concepts used in data science and artificial intelligence—calculating the variance of a continuous frequency distribution. Breaking down the steps If you have data distributed across class intervals with frequencies, the goal is to find the variance. The video explains the columns in the table: […]
Data Science and A.I. – Measures of Dispersion: Variance of Discrete Frequency Distribution In this post from PostNetwork Academy’s Data Science and A.I. Lecture Series, Bindeshwar Singh Kushwaha walks us through the process of calculating the variance of a discrete frequency distribution. This is an essential statistical measure for understanding the spread of data
Exponential Distribution Formula A random variable X is said to follow Exponential distribution if it has the following probability density function the value f(x) is zero when x < 0 otherwise it is equal to f(x). Moment Generating Function The moment generating function (MGF) is a powerful tool in probability theory and statistics used to
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Before understanding Binomial distribution you have to understand Bernoulli trial. What is Bernoulli trial? A Bernoulli trial is a random experiment in which there are two possible outcomes failure and success getting head when tossing a coin is success and getting tail is failure getting 4 is success when rolling a dice and failure when
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Variance and Standard Deviation are both essential concepts in statistics and finance. Let’s explore the differences between them: Variance: Definition: Variance is a numerical value that describes the variability of observations from their arithmetic mean. Calculation: To find the variance, calculate the squared differences between each data point and the mean, then average these squared
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Random variable is a very important concept in probability, statistics, data science and machine learning, one must learn concept of random variable and related concepts. In this post, I have explained random variable and probability mass function that will help you to have basic understanding of random variable and probability mass function. To understand random
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Understand Decision Tree Learning Decision tree learning is a supervised learning algorithm, which can be used for classification as well as regression tasks. Moreover, it mimics the human’s decision making process and very effective in several applications. In this post you will know that how to construct a decision tree learning model using Gini Index.
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Ungrouped data- Ungrouped data refers list of individual observations which are not categorized or summarized. Basically, ungrouped data are collected by statisticians to get insights from data , researchers to prepare a scholarly article or by by organizations preparing report. A simple example of ungrouped data, marks obtained by 25 students in class out out
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