Python

The Python language has established itself as one of the pillars of modern computer development, appreciated for its simplicity, readability and versatility.
Whether for data analysis, web development, artificial intelligence or task automation, Python offers a wide range of applications.
In this section, you’ll find articles exploring the many uses of Python, from tutorials for beginners to in-depth analyses for experienced developers.
We also highlight examples where Python is cited as part of wider discussions on emerging technologies and software development trends.

predictive analytics

Unleashing business growth through predictive analytics: a data-driven approach

A recent study, published in the International Journal of Frontiers in Engineering and Technology Research by Oloruntosin Tolulope Joel and Vincent Ugochukwu Oguanobi, explores how businesses can harness the power of predictive analytics to improve profitability and identify new opportunities for expansion.

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Essential statistical tools

The essential tools of statistical analysis: A guide to modern data interpretation

At a time when data is at the heart of decision-making in many sectors, the importance of statistical analysis tools has never been greater.
Whether to assess market trends, improve business operations or advance scientific research, understanding and applying statistical techniques helps to make sense of complex data sets.
But what are the essential tools of statistical analysis today?
This article explores some of the most important tools and software on which statisticians and data analysts rely.

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Bass Model Forecasting

Bass Model Forecast

The Bass diffusion model predicts the timing of new product purchases by assuming that the probability of purchase depends on the number of previous buyers.
It uses coefficients for innovative and imitative behavior to predict the adoption of consumer durables, among other products.
Innovation coefficient
(p): Represents the influence of external factors on product adoption.
Imitation coefficient
(q) : Represents the influence of previous adopters on potential adopters.
Total potential market (m): The total number of potential adopters of the product.

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Response function

Model and Response Function

Introduction In marketing, models are essential tools for understanding, predicting and optimizing the impact of marketing actions on business results. A fundamental element of these models is the response function, which describes the relationship between marketing efforts and the results obtained. What is a response function? A response function in marketing is a mathematical representation

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