To predict the closing prices of the S&P 500 index using historical data. This dataset contains 4 millions of rows with data from 1962 to the current year 2024.

Analyzing global inflation trends using time series modeling techniques. The dataset, sourced from World Data Bank, spans the years 2000 to 2024 and contains a wide range of macroeconomic indicators, such as GDP, population, and various economic monitors

Using machine learning techniques like Random Forest and XGBoost, we’ll create models that can predict the chances of a crisis based on these economic signals.

In this project I was working with two datasets Disney and General Electric data. I needed to analyze both datasets price of the stock to decide whether to invest in one of the two assets or both. while using the hypothesis test and the intercept is equal to zero. Testing the hypothesis that the beta coefficient is equal to one. Testing the joint hypothesis that the intercept is equal to zero and that the beta coefficient is equal to one. Performing diagnostic testing.

this is a South African map to Pretoria Union Building

This is the Rmarkdown document for Reproducible project