Ep. #620: How to Think About Science

Hello, and welcome to another episode of Muscle For Life. I’m Mike Matthews. Thank you for joining me today. And this episode is special because it is one of the chapters of my newest book, newest audio book in this case, but it’s also available in digital and hard copy formats as well. It is called Fitness Science Explained, and you can get it right now at fitnesssciencebook.com.

And this book is a crash course in reading, understanding and applying scientific research. And it teaches you in very simple terms what most people will never know about how to use science to optimize your. Fitness and lifestyle. Fitness. Science explained covers all of the big moving parts, including the basics of the scientific method, the differences between randomized trials and observational studies.

The power of the placebo effect, the importance of sample sizes, the anatomy of statistical analysis, and much. You’ll also learn in the book how to get access to full text studies without spending a fortune and the most popular journals out there for exercise, nutrition and supplementation. And you will get a scientist formulated cheat sheet that will help you quickly and accurately estimate the quality of research that you want to review.

In my opinion, the cheat. Alone is worth the cost of the book. It is very practical. So whether you want to discover and use evidence-based methods for building muscle or losing fat faster, or maybe reducing your risk of disease or dysfunction, or just maximizing some other aspect of your body, mind, or life, this book will show you the way.

Also to celebrate to this joyous occasion, I am giving away $1,500 in. Gift cards and all you have to do for a chance to win is head over to fitness science book.com by a copy of the book, any format, and then forward your receipt email to [email protected]. And that’s it. You are entered in the giveaway.

You gotta act fast though, because winter is coming now because winners will be chosen this Friday, September 4th. Oh, and you can also increase your chances of winning by. Extra copies of the book, again, any formats. So specifically if you buy three copies, you’re gonna get five giveaway entries. So that is a plus 400% chance to win.

If you buy five copies, you’re gonna get eight giveaway entries, and that is a plus 700% chance to win. And if you buy 10 copies, you’re gonna get 15 giveaway entries, which is a plus 1400% chance to. And you are going to get an autographed copy of the book. So for instance, if you buy the paperback ebook and audiobook, that is three copies, five entries to win.

And if you were to buy three paperbacks as well as the ebook and audiobook, that’s five. So you get eight entries to win and so forth. Anyway, to get your copy or copies of fitness science explained, just head over to fitness science book.com now. All right, let’s get to the. Chapter two, How to think about science.

Nothing has such power to broaden the mind as the ability to investigate systematically and truly. All that comes under thy observation in life. Marcus a really is one of the biggest steps you can take toward both protecting yourself from bad science and benefiting from good science is learning how the scientific method works.

You know what it is in a general sense, the pursuit of knowledge, but you probably aren’t familiar with the exact steps that have to be taken to get that knowledge. Once you understand the primary components of the scientific method, you can appraise science backed claims for yourself and come to your own conclusions.

Let’s start at the top. What is science? Science is simply a way to think about a problem or set of observ. We observe something in the world, then we think that’s interesting. I wonder why that happens. Next, we come up with ideas as to why it happens and then test them. If our ideas fail the tests, then we test new ideas until something passes, at which point we can confidently say that the passing ideas may explain our original observ.

Basically, the scientific process goes like this one, we have a problem or set of observations that needs an explanation. Two, we formulate a hypothesis, a proposed explanation for our problem or set of observations. Three, we test the hypothesis using data. Four, if the data doesn’t support our hypothe, Then we change our hypothesis and test the new one.

Five. If the data supports our hypothesis, we continue to test it using a variety of observations, more data collection and multiple experiments. Six, If a set of related hypotheses is consistently and repeatedly upheld over a variety of observations and experiments, we call it a. Much of science revolves around Step number three, the process of hypothesis testing.

Scientific studies are the primary ways in which scientists engage in hypothesis testing, which contrary to popular belief, doesn’t aim to prove whether something is true. But simply most likely to be true. You can rarely prove something to be absolutely and universally true, but you can engage in a process of narrowing down what is most likely true by showing what isn’t true, and that’s science’s primary goal.

Hypothesis testing may sound abstract, but you actually do it every day. Imagine a situation where your TV isn’t working. This is step number one in the above process. You have a problem, you can’t watch Game of Thrones. You then formulate a hypothesis as to why the TV isn’t working. Step number two, in this case, you hypothesize that it might be because it’s not plugged in.

You then engage in step number three and test your hypothesis with data. In this case, you check behind the TV to see if it’s plugged in. If it isn’t plugged in, this can be considered support for your hypothe. To further test the hypothesis, you plug the TV in and try to turn it on. If it turns on, then you have arrived at the proper conclusion as to why the TV wasn’t working.

If the TV still doesn’t turn on, even if it’s plugged in, however, then you’ve ruled out the plug as the problem. In essence, you falsified your hypothesis that the problem was due to the plug. You now have to change your hypothesis. Step number four, to explain why the TV isn’t working. Now, you think that maybe it’s because the batteries in the remote are dead.

This is your new hypothesis, and to test it, you press buttons on the remote and observe that the light on the remote doesn’t illuminate when you click the button. This supports your hypothesis, so you go grab new batteries to put in the remote. In this way. You continue to go through steps two to four, learning what isn’t true until you narrow down the correct reason as to why your TV isn’t working.

When testing hypotheses, falsification is more important than support because as mentioned earlier, you rarely can prove something to be unequivocally true. Rather you arrive at the most likely explanation by showing what isn’t. Falsification of hypotheses is a crucial part of discovering what’s true and what’s not, and that’s why it’s at the heart of how science works in real life Scenarios can be far more complicated, but the basic approach is the same.

Scientific research begins with a hypothesis and a set of predictions from that hypothesis. Which are things that should be true. If our hypothesis is true, these predictions are then tested by doing experiments and gathering data. If our predictions are shown to be false, then we need to modify our hypothesis or trash it for a new one.

If it pans out, then we know that our hypothesis may indeed be true, and if it continues to pan out in further research, we’ve created a valid theory. So let’s say you had a hypothesis that Mike Matthews was bat. Hey, you never know from this hypothesis, you would formulate a set of predictions that should be true.

If Mike and Batman were the same person, these predictions would include one. Mike and Batman won’t be in the exact same place at the exact same time. Two. Mike will consistently be missing when Batman appears and vice versa. Three. Batman will most frequently turn up in areas of close proximity to where Mike.

Four Mike’s and Batman’s voices should have similarities. Five. Mike and Batman should be of similar height. Six. DNA testing should produce a match. Failure of these predictions would indicate that Mike and Batman are not the same individual, but we may never be able to know for sure Science works in this exact fashion.

We have a hypothesis X is true. We then develop a set of predictions from that Hypothe. If X is true, then A, B, and C must be true. We then test our predictions with scientific studies. In other words, we do studies to see if A, B, and C are true. If they aren’t, then X is not true. Here’s a real life example of hypothesis testing in the fitness world.

One popular hypothesis among some people is that carbohydrates make you fat through the actions of the hormone insulin. We know that eating carbs raises insulin levels, so when you eat a high carb diet, your insulin levels are generally higher. We also know that insulin inhibits the breakdown of fat for energy and stimulates fat storage, so we can hypothesize that the high insulin levels produced by a high carb diet will make fat loss more.

1. The next step is developing a set of predictions from this hypothesis, Things that should be true if carbs and insulin actually make you fat. Some of these predictions could include one, obese people should show less fat released from their fat tissue since they have higher insulin levels. Two high insulin levels should predict future weight gain.

Three. Fat loss should increase when we switch from a high carb diet to a low carb diet while keeping protein and calorie intake the same. There are many other predictions that could be developed from this hypothesis, but let’s just focus on these three, which have already been tested and experiments and shown to be.

In one study, obese people show increased fat release from their fat tissue in another high. Insulin levels did not predict future weight gain, and yet another fat loss was the same or slightly less when people switched to a low carb diet compared to a high carb diet with similar protein in calorie intake.

Given the failure of these predictions, we can confidently say that the hypothesis that carbs make you fat via insulin is false. As scientists repeatedly develop hypotheses and test their predictions using research, the hypotheses that aren’t true get thrown out, and the hypotheses that are most likely to be true are kept.

Rather the evidence to support a hypothesis accumulates over. And the more high quality evidence that exists to support it, the more true the hypothesis becomes. As mentioned earlier, when a hypothesis or set of hypotheses is supported by a large body of high quality evidence that has withstood rigorous scrutiny through repeated testing, we call it a theory given that science is based on the accumulation of evidence, its conclusions are always.

In other words, there is no such thing as 100% certainty in science, which is why you can’t absolutely prove anything. Instead, there’s a degree of certainty, and that degree is based on how much evidence there is to support a scientific concept. Some conclusions in science may be regarded with a high level of certainty due to the vast amount of supporting data and evidence, and others may be highly uncertain due to the lack of high quality.

You can imagine scientific research as a form of betting in some areas of science. The data and conclusions are so strong that you would be willing to bet your life savings on it. In other areas, the data is so lacking that perhaps you might only be willing to bet $100 on it or not even that. The importance of accumulated evidence is why reproducibility is i. For a hypothesis to be true, the experiments that support it should be reproducible by scientists other than those who created it by repeating their experiments and observing the same results. This is also why considering the weight of the evidence is critical when coming to conclusions and why science tends to move slowly over time.

I hope you are enjoying this episode, which is one of the chapters of my newest book, Fitness Science Explained, which is live right now at Fitness Science. Dot com. Now, this book is a crash course in reading, understanding and applying Scientific Research, and it teaches you in simple terms what most people will never know about how to use science to optimize your health, fitness, and lifestyle.

So whether you want to discover and use evidence-based methods for building muscle or losing fat faster, or maybe reducing your risk of disease or dysfunction, or just maximizing. Some other aspect of your body, mind, or life. This book will show you the way. Get your copy [email protected] and forge your email receipt to [email protected] and you’ll be entered to win a Legion gift card.

I am giving away $1,500 in legion gift cards to celebrate this joyous occasion. Again, that URL is fitness science book dot. An example of how conclusions rest on the strength of the evidence is the relationship between blood lipids and heart disease. While some pop science book authors have tried to question the relationship between blood levels of low density, lip bulb, proteins, ldl, and heart disease, the fact is that this relationship is very strong and is supported among multiple lines of evidence, and the evidence is also very strong that decreasing your LDL levels decreases your risk of atheros.

Thus, the evidence is overwhelming that elevated LDL causes heart disease. It’s the type of evidence you’d be willing to bet your life savings on. Now, it’s also been suggested that high density lipoproteins, HDL are protective against heart disease. However, the evidence for that isn’t as strong while observational studies support a relat.

Studies that directly change your HDL via drugs haven’t shown any reduction in heart disease risk. Thus, this is the type of evidence that perhaps you might only be willing to risk a hundred dollars on the limitations of science. While science represents our best tool for understanding and explaining the world around us, it isn’t without its limitations.

This is particularly true when it comes to exercise and nutrition. Whose limitations include but aren’t limited to external validity. External validity refers to the ability to extrapolate the results of a study to other situations and other people. For example, equations used to estimate body composition in Caucasians don’t apply to African Americans or Hispanics because the density of fat free mass is different between different ethnicities.

There are many factors that can limit the external validity of a. Some research is performed under highly controlled artificial conditions. Some is only performed on certain populations like individuals with diabetes or other health conditions, and some studies may use protocols that don’t reflect what people do in real life sample size.

Many studies in the field of exercise and nutrition have a very small number of subjects, often only 10 to 20 people per. This can make it difficult to extrapolate findings to thousands of people because small samples can increase the risk of random findings. For example, as mentioned earlier, small studies suggested that antioxidant supplementation could reduce cancer risk.

However, once larger studies came out, it was clear that antioxidants supplementation didn’t reduce cancer risk. Small sample sizes can also make it more difficult to detect small but meaningful changes in certain variable. For example, some studies haven’t shown any differences in muscle size between low and high volume weight training.

However, these studies had a small number of subjects and short term changes in muscle size can be so small that they’re hard to detect. This may explain why an in depth analysis of a number of studies on the topic has suggested that training volume does indeed impact muscle size animal versus human.

Animal studies have an advantage over human studies in that scientists have more control over the environment, activity, and food. This allows scientists to do a better job of isolating the variables they’re studying. However, these studies can be limited in how much you can extrapolate the results to people.

Because animal physiology while similar to humans, isn’t the same. For example, rodents have a much greater capacity to convert carbs to fat, which means that high versus low carb studies in rodents aren’t necessarily applicable to people, lack of control in free living people, and inaccuracy of self-reporting.

Many studies in the realms of exercise and nutrition are done on free living individuals. That is people living outside the controlled environment of a labor. These studies are easier to conduct, but they’re also challenging because scientists are limited in how much they can control for unknown variables that can change the results.

For example, it’s been shown that people are notoriously inaccurate when reporting how much food they eat and how physically active they are, and therefore, studies that rely on self-reported food intake or physical activity may not be. Science is a systematic process for describing the world around us.

Through the process of hypothesis testing and confirmation or falsification, we can eliminate what definitely isn’t true and hone in on what’s most likely to be true. The beauty of science is that it’s self-correcting and is built on a body of evidence that’s accumulated and interpreted over time. It has plenty of limitations, as do individual.

But that doesn’t mean the scientific method or scientific experiments are fundamentally invalid. It just means we have to carefully consider the quantity and quality of evidence on a given matter when determining our level of certainty in our conclusions. Key takeaways. The scientific process goes like this, We have a problem or set of observations that needs an explanation.

We formulate a hypothe. A proposed explanation for our problem or set of observations. We test the hypothesis using data. If the data doesn’t support our hypothesis, then we change our hypothesis and test the new one. If the data supports our hypothesis, we continue to test it using a variety of observations, more data collection, and multiple experiments.

If a set of related hypotheses is consistently and repeatedly upheld over a variety of observations and experiments, we call it a theory when testing hypotheses. Falsification is more important than support because you rarely can prove something to be unequivocally. Rather, you arrive at the most likely explanation by showing what isn’t true.

As scientists repeatedly develop hypotheses and test their predictions using research, the hypotheses that aren’t true get thrown out, and the hypotheses that are most likely to be true are kept. We say most likely to be true because science can never prove anything definitively. The evidence to support a hypothesis accumulates over time, and the more high quality evidence that exists to support it, the more true the hypothesis becomes.

When a hypothesis or a set of hypotheses is supported by a large body of high quality evidence, that has withstood rigorous scrutiny through repeated testing, we call it a theory. While science represents our best tool for understanding and explaining the world around, It isn’t without its limitations.

Four of the most common limitations of exercise and nutrition research are lack of ability to extrapolate the results of a study to other situations and other people. Small sample size, reliance on animal research that can’t be applied to humans, and lack of control over people in free living Environ.

That is it for this episode of Multiple Life. I hope you liked it, and in case you did not hear the intro or the Midroll ad, this was one of the chapters of my newest book, Fitness Science Explained, which is live right [email protected].