Nish Tahir

Bayes Theorem is a fundamental concept in statistics and probability theory. It provides a way to update the probability of a hypothesis based on new evidence or information. It's particularly useful in situations where have some knowledge about the efficacy of a test or the prevalence of a

The conditional probability of an event is the probability of an event occuring given that another event has occured. The It is denoted as \(P(B|A)\) and is read as "the probability of B given A". That is the probability of event B occuring knowing that event

A Taylor polynomial is generally used when approximating functions. They are especially useful when the true or exact form of the function is complex or difficult to work with. By expressing a function as a Taylor series, it's possible to simplify calculations and gain insights into its behavior,

Probability, in the realm of statistics, is a measure of the likelihood that a specific event will occur. It provides us with a way to quantify uncertainty. We see and characterize this in our everyday lives. For example, when we say that there is a 70% chance of rain, or

Measures of central tendencies like the Mean, Median and Mode summarize the data into a single value. However, they also lose a lot of information. For example if I tell you that the average salary of a given sample of workers $100,000, you might think that most workers make

Central tendency measures are valuable statistical values that shed light on the "typical" or central value around which data tend to cluster. Let's delve into the three primary measures of central tendency: the Mean, Median, and Mode. Mean The Mean, also known as the average, is

A Frequency Distribution is a common way to understand a trend in a dataset. It's a tabular representation of the number of times a value appears in a dataset. If we denote values in a dataset as \(x_1, x_2, \ldots, x_n\), their corresponding frequencies can