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How to Write a Proof in a paper

Reviewers are not required to read supplementary materials, but many do. Therefore, making your proof easy to read is important. General Guidelines: Example: Theorem 1: Let and be real numbers. If , then . The… 

Example of using derivatives to find optimal drug dosage

Dosage Optimization: Pharmacologists use derivatives to find the optimal drug dosage that maximizes therapeutic effects while minimizing side effects. The concentration of the drug in the bloodstream is modeled as a function of time, and… 

Example of using derivatives to optimize the material cost

Optimization of Material Usage: Engineers use derivatives to minimize the cost of materials while maintaining structural integrity. For example, determining the optimal dimensions of a container to minimize surface area for a given volume. Example:… 

Combining datasets to increase sample size

Detailed information can be found in Combining datasets to improve model fitting or its presentation slide. Summary: The key points of the paper titled “Combining Datasets to Improve Model Fitting” are as follows: Problem and… 

Calculus can hurt

Supplementary contents for section “Calculus can hurt” in the KSML app: Limit: Derivatives Integral

Expectation Maximization (EM) & implementation

Expectation Maximization (EM) is an iterative algorithm used for finding maximum likelihood estimates of parameters in statistical models, particularly when the model involves latent variables (variables that are not directly observed). The algorithm is commonly… 

A comic guide to denoising noisy data

Handling noisy data is a crucial step in data preprocessing and analysis. In general, here are some common approaches to manage noisy data: 1. Data Cleaning 2. Data Transformation 3. Statistical Techniques 4. Machine Learning… 

A comical guide to Missing Not At Random (MNAR)

Recall that Missing Not At Random (MNAR) is a type of missing data mechanism where the probability of missingness is related to the unobserved data itself. Here are some more examples of MNAR: In each… 

What’s Missing at Random (MAR)?

Missing at Random (MAR) is a statistical term indicating that the likelihood of data being missing is related to some of the observed data but not to the missing data itself. This means that the… 

Tips & Tricks for research newbies

Coding and managing projects Using AI to better code, debug and manage projects How to export an R dataframe to LaTeX Paper writing: Analyze experiment results faster with ChatGPT How to write in Latex faster… 

Check Plagiarism by grammarly

Plagiarism is the act of using someone else’s work, ideas, words, or intellectual property without proper acknowledgment or permission, and presenting it as your own. Even reusing your own previously published work or parts of… 

Using AI to better code, debug and manage projects

1. Code Completion and Suggestions AI-powered code completion tools can predict and suggest the next lines of code based on the context of your current coding. Examples include: Copilot: Uses OpenAI’s Codex to provide code… 

The success rates of Cupid’s arrows

I advised a master’s student to use the binomial probability formula to determine the likelihood of attracting the affection of 15 girls, with Cupid’s success rate at 0.7. The analysis shows that the highest probability of success occurs when 10 girls reciprocate love, with a probability of 0.33.

Grazing the maze of probability

Supplementary materials for section Grazing the maze of probability & A random variable mood in the KSML app: Basic rules of probability: Mutually exclusive events Conditional probability for medical testing in a forestThe conditional probability… 

Tricks for remembering elementary matrix operations

Connecting matrices to systems of linear equations can indeed help in better understanding and remembering the properties of matrices. By visualizing how matrix operations correspond to operations on systems of equations, abstract matrix properties become… 

Bayes theorem in finance of a magical forest

Here, we denote by the event NOT . Example 1: Magical Investment Returns In the magical forest, gnomes invest in enchanted acorns, which sometimes turn into golden trees. A gnome named Glim invests in an… 

Conditional probability

Here, we denote by the event NOT . Example 1: Squirrel Flu Testing In a forest, a group of squirrels is concerned about a new illness called “Squirrel Flu.” It’s more dangerous than the ordinary… 

Tricks for remembering integral rules

Understanding the relationship between derivatives and antiderivatives can significantly help in remembering and applying the rules for finding antiderivatives (also known as integrals). Here’s how this relationship aids in comprehension and recall: 1. Fundamental Theorem… 

Permutation

A permutation refers to the arrangement of objects in a specific order. The order of arrangement is important in permutation. A permutation let us know how many different ways a set or number of things… 

Examples of Exponential distribution

The exponential distribution is commonly used to model the time between events in a Poisson process. It is defined by a single parameter, , which is the rate parameter. The probability density function (PDF) of… 

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