Darya Sinusoid

Darya’s love for reading started with fantasy novels (The LOTR trilogy is still her all-time-favorite). Growing up, however, she found herself transitioning to non-fiction, psychological, and self-help books. She has a degree in Psychology and a deep passion for the subject. She likes reading research-informed books that distill the workings of the human brain/mind/consciousness and thinking of ways to apply the insights to her own life. Some of her favorites include Thinking, Fast and Slow, How We Decide, and The Wisdom of the Enneagram.

Calculating Investment Risk Using Probability

How do you calculate investment risk? What do you need to know to calculate the expected payoff of a financial investment? Investors often use probability to assess risk when making financial decisions. This is typically done with a statistic called an “expected value.” To calculate the expected value of a financial investment, you need to know the probability of each possible outcome and its respective payoff. Here’s how to use the expected value statistic for calculating investment risk.

Normal Distribution: Explained With Examples

What is the normal distribution in statistics? How do measures of central tendency relate to the normal distribution? The normal distribution is a foundational concept in statistics. When data is normally distributed, it means that most values cluster around the center. Therefore, the mean, median, and mode are exactly the same in a normally distributed data set. Keep reading for the theory of normal distribution, explained in simple terms.

Mean and Mode: Which Should You Use?

What is the difference between mean and mode? Which of the two is a more accurate measure? Both the mean and the mode are measures of central tendency. For non-skewed distributions, the mean is more accurate because it takes into account every value in the data set. For skewed data, the median is better because it isn’t influenced by outliers. Keep reading to learn about the difference between mean vs. mode and when to use which.

Sleep and the Brain: Why You Shouldn’t Skimp on Your Zzzs

What happens in your brain when you sleep? Conversely, what happens in your brain when you don’t sleep? Chronic inadequate sleep leads to a higher risk of many health issues, including dementia and cognitive decline. Extensive research on the effects of sleep shows that sleep is more than just the body’s chance to relax: It’s a vital phase of neural activity and regeneration. Here’s a look at sleep and the brain.

Does Meat Make You Fat? Scientists Can’t Agree

Does meat make you fat? How does eating meat contribute to weight gain? When it comes to meat’s fattening potential, there seems to be a division of opinion, even amongst scientists. Some say that meat (especially, lean meat such as chicken breast) is great for weight loss because it contains no carbs. Others say that eating meat is associated with weight gain. Here’s what Dr. Jason Fung says on the matter.

Charles Wheelan: Naked Statistics (Overview)

What is Charles Wheelan’s Naked Statistics about? What statistics does Wheelan explore in the book? Naked Statistics puts the math behind statistics into digestible terms and explains statistics concepts with relatable, relevant, and even humorous examples. Readers also benefit from additional socio-political insight from the book, as Wheelan uses real-world anecdotes to explore how statistics can inform collective decision-making. Below is a brief overview of the key themes and concepts from Wheelan’s Naked Statistics.

What Does “Statistically Significant” Mean?

What is significance in statistics? What does “statistically significant” mean? In statistics, significance refers to the degree of confidence or certainty in the results of a statistical analysis being attributable to a specific cause. When results are said to be “statistically significant,” the observed relationship between variables is unlikely to be due to chance. Keep reading to learn about the concept of statistical significance, explained in simple terms.

The Importance of Reliability in Data Collection

Why is reliability important in data collection? What are the main challenges inherent in collecting reliable data? As we use statistical data to inform our lives and society, we need them to be both accurate and precise. Therefore, collecting quality data is the true challenge and art of producing reliable, constructive statistics. Keep reading to learn about the importance of reliability in data collection.

The Fat Storage Hormone: How Insulin Functions

What is the main function of the hormone insulin? What happens when your insulin stops functioning properly? Insulin is a hormone, a molecule that transmits “messages” within your body. Its function is to deliver glucose to cells to use for energy and take the excess glucose to the liver. Learn about the role of insulin in the body and what happens when it stops working as intended.

The Central Limit Theorem: Statistics Applied

What is the central limit theorem in statistics? What can the central limit theorem tell us about the distribution of the sample mean? The central limit theorem states that the mean of a representative sample will be close to the mean of the larger population. Therefore, we can confidently make inferences about a population from a sample or about a sample from a population, and we can compare samples to each other. Let’s explore each of these general applications of inferential statistics with an example.