Plastic properties refer to the behaviors and characteristics that define how plastic materials respond under various conditions. Key properties include malleability, allowing plastics to be molded into different shapes; durability, which makes them resistant to impact and wear; lightweight nature, facilitating ease in handling and transport; and chemical resistance, enabling their use in various environments without degrading. However, these same properties can contribute to environmental challenges, such as pollution and difficulty in degradation. Innovations in biodegradable plastics and recycling methods are being developed to address these issues. Understanding plastic properties is crucial for both maximizing their advantageous uses in society and mitigating their environmental impact.

Adding stickers to resin is a creative way to personalize your crafts. First, ensure your sticker is waterproof or coat it with a sealing spray to prevent ink from running. Begin by pouring a thin layer of resin into your mold and allow it to partially cure. Place your sticker on the semi-cured resin surface. To prevent air bubbles, carefully press down on the sticker starting from the center and moving outward. Once in place, pour another layer of resin over the sticker, making sure it's completely covered. Allow it to fully cure as per the resin's instructions. This method secures the sticker in place, making it a permanent part of your resin art piece, offering a three-dimensional look that's both professional and personalized.

Measures of dispersion are statistical tools used to describe the spread or variability within a set of data, providing insight into how much the data points diverge from the central value. The primary measures include Range, which is the difference between the maximum and minimum values; Interquartile Range (IQR), focusing on the middle 50% of data, thus eliminating extreme values; Variance, indicating the average squared deviation from the mean; and Standard Deviation, a widely used measure that quantifies the average distance of data points from the mean. These metrics are critical in fields ranging from finance to social science, as they help understand the stability, consistency, and predictability of datasets. Selecting the appropriate measure of dispersion depends on the data type, distribution, and the focus of analysis.