Mohammed Looti - PSYCHOLOGICAL STATISTICS

What is Balanced Accuracy? (Definition & Example)

Understanding Classification Metrics and the Challenge of Imbalance When building a classification model, evaluating its effectiveness requires robust metrics that accurately reflect its true performance. Many introductory machine learning projects rely solely on Overall accuracy, which measures the total proportion of correct predictions made across all classes. However, this standard measure becomes misleading when the […]

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Create a Candlestick Chart Using Matplotlib in Python

A candlestick chart is a fundamental tool in financial analysis, providing a visual representation of price action for securities, derivatives, or currencies over a specified period. These charts are essential for technical traders as they display four crucial data points: the open, close, high, and low prices. Unlike simple line charts, candlesticks convey market sentiment

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Change the Position of a Legend in Matplotlib

One of the most critical elements in creating effective data visualization is ensuring that all graphical components are clearly labeled and do not obscure the underlying data. In the Matplotlib library, managing the position of the plot Legend is essential for producing professional and readable figures. To precisely control the location of a legend within

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Calculate Balanced Accuracy in Python Using sklearn

Understanding model performance is critical in machine learning, and while standard accuracy is often the first metric considered, it can be misleading, especially when dealing with complex datasets. This is where Balanced accuracy steps in, providing a robust and reliable measure for assessing the quality of a classification model. Balanced accuracy is particularly useful because

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Calculate Matthews Correlation Coefficient in Python

The Matthews correlation coefficient (MCC) (1/5) is an essential performance metric used to evaluate the quality of a classification model (1/5). Unlike simpler metrics like accuracy or F1 score, MCC is considered one of the most reliable measures for binary classification tasks, especially when dealing with skewed class distributions. Understanding the Matthews Correlation Coefficient (MCC)

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Count Duplicates in Excel (With Examples)

In the realm of data management and analysis, identifying and quantifying duplicate values is a critical step for maintaining data integrity. Whether you are cleaning raw input, performing statistical analysis, or preparing lists for a database, knowing how many times specific entries reappear is essential. Fortunately, Excel offers several robust functions to efficiently count duplicate

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Create a Candlestick Chart in Excel (Step-by-Step)

A candlestick chart is a powerful and popular type of financial visualization used extensively by traders and analysts worldwide. It provides a visual representation of the price movements of securities—such as stocks, currencies, or commodities—over specific time frames. Unlike simple line charts, candlestick charts convey four crucial pieces of information for each period: the open,

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Create a Candlestick Chart in Google Sheets (Step-by-Step)

A Candlestick chart is one of the most fundamental and informative types of financial chart visualizations used by investors and analysts worldwide. It provides a detailed graphical representation of price movements for securities—such as stocks, currencies, or commodities—over a specific period. Mastering the creation of these charts is essential for anyone engaged in serious financial

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Inference vs. Prediction: What’s the Difference?

In the vast field of statistics and data science, data is typically leveraged to achieve one of two primary objectives: generating insights or forecasting future outcomes. While both goals utilize similar mathematical tools, their underlying purposes, model requirements, and evaluation metrics are fundamentally different. These two core activities are known as statistical inference and prediction.

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Combine Two Vectors in R (With Examples)

In the R programming language, the ability to manipulate and combine fundamental data structures is essential for data preparation and analysis. Combining two or more vectors is a common task, but the method you choose depends entirely on the desired resulting structure. Do you require a single, longer vector, or a two-dimensional object like a

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Author name: Mohammed looti