This is the music-related blog for Jonathan (Scooter) Clark, also known in the electronica world as DJ Bolivia, a producer and DJ from Atlantic Canada. I listen to (and produce) a lot of folk, indie, rock, and hip hop music too!
I also run a company (Replant.ca Environmental) through which you can sponsor the planting of trees to build forest reserves and community forests, which are protected from commercial logging. Please visit: www.replant.ca/environmental
Here's another one of my tracks for you to check out. Spring is coming (and with it my seasonal tree planting work) and I feel like I've gotten a lot of work done in the past three months. I finished a number of projects that have been on my to-do list for between 7-12 years, and I've gotten a bit of minor reno and painting work done at my house. I also finished the last of my [major] website redesigns four days ago, which means that all twenty of the sites that I oversee are up to modern standards, finally.
I want to feature another track of mine this morning. It's called, "Confidence Interval." I'll have a download link below.
Here's a link to the track on SoundCloud. You can also click on the down-arrow in the top right to download the mp3 directly from SoundCloud:
For the last few posts about my tracks, I've come up with some silly little stories. Today, I'm going to do something different. A confidence interval is a term used in statistical mathematics. I came up with the title while I was working on a stats project. I'm going to try to explain what it means:
Confidence Interval:
Understanding the Basics: A confidence interval gives us a range of values which is likely to include the true value of something we're trying to estimate. For instance, if I'm out on a silviculture survey project, and I'm studying the average height of a crop trees in a plantation that we planted seven years ago, I may not want to measure every single tree (let's assume that it's a large block, with hundreds of thousands of trees). Instead, my best approach will be to measure a sample of trees then use those measurements to estimate the average height for all the trees. The confidence interval, in this case, is like saying: "Based on my sample, I'm fairly certain that the true average height of all the trees is 'somewhere in this range,' and should be between this minimum and this maximum height."
Sampling and Variability: The concept of a confidence interval hinges on the idea of sampling. Since it may be impossible to examine every single member of a population, I select a limited sample. However, if I were to take several separate samples, each sample would probably exhibit slightly different results due to natural variability. If I take a different piles of seedlings from an unbundled split box each time, one handful might have more or fewer seedlings than another. Similarly, in my previous crop tree example, one sample might have slightly taller or shorter trees on average. The confidence interval accounts for this variability, offering a range that is likely to encompass the true average.
Confidence Level: The "confidence" in confidence interval refers to the level of certainty or assurance I have that the interval includes the true value. It's typically expressed as a percentage (like 95%). The confidence level tells me how sure I can be that the range I have calculated includes the true average. If I say that I'm 95% confident, it means that if I were to take a hundred different samples and calculate one hundred confidence intervals (one for each sample), I should expect about ninety-five of those intervals to accurately contain the true average height of the trees.
Interpreting a Confidence Interval: It's important to understand what a confidence interval does and doesn't tell me. It provides a range that's likely to include the true value based on my sample data, but it doesn't guarantee that the true value lies within my range every time. Also, the interval itself can be wide or narrow, depending on the sample size and variability of the data. A wide interval might tell me that I need to collect more data to make a precise estimate, or it might just reflect high variability in the data itself.
Practical Implications: In practice, confidence intervals are used across various fields of study to help make management decisions. For instance, I'll use an example relating to public health. A confidence interval can help determine whether a new treatment is effectively improving patient outcomes compared to an old treatment. If the confidence interval for the difference in effectiveness between treatments does not include zero (which would indicate that there's a possibility that the new treatment isn't doing anything), then it suggests the treatment works. Thus, confidence intervals provide a useful way to assess the reliability of estimates and to make informed decisions based on data.
Ok, there's your academic lesson for the day.
I also put up a version of this track on YouTube. The visuals accompanying the track were done by an AI, although the music is my own of course. These AI visuals are very rudimentary. But thanks to OpenAI's Sora, my future music videos may look a LOT more professional:
To check out and/or download any of my other tracks, visit:
