1 What is science?

Last modified on 17. January 2026 at 20:18:41

“Reality is negotiable.” — Tim Ferriss

The first chapter of this book is already the hardest. I started writing this chapter very early on, perhaps even before any of the others. Yet it took the longest to finish. The question is simple: What is science? The more I researched, the more complicated the answer became. Or the other way around. I followed the advice of Wolfgang Pauli. Pauli defined the scientific method as “taking up a subject repeatedly. Thinking about it. Setting it aside. Gathering new empirical material. And continuing this process for years if necessary. In this way, the conscious mind stimulates the unconscious mind. If anything, this is the only way to achieve results.” Therefore, I tried to read and find answers to the question of what science might be. Perhaps science is, at its core, something personal. However, science also has objective aspects that I want to present here. Ultimately, decide for yourself what science truly is.

Figure 1.1: Visualization of the demarcation line of science. This line divides science from non-science through experimentation and the principle of falsification. The purity of science fields is taken from xkcd comic #435 (https://xkcd.com/435). According to this definition, natural science, including physics, chemistry, and biology, is separated from formal science, including mathematics. Formal science must be clearly distinguished from other intuition-based and subjective non-science, such as pseudoscience or anti-science. The humanities are indisputably different but are also considered non-science in this schematic.

1.1 What is not science?

Mathematics and psychoanalysis have no experiments.

Mathematics and logic are more like scientific tools to do science.

1.2 What is the opposite of science?

As I found out, there is no direct opposite of science. Which is interesting. Because sometimes you can define something by knowing what the think is not. Is mathematics the language of nature?

Cargo cult science

conspiracy theories¹ and²

1.3 Why do science?

1.4 How to do science?

“As a scientist, you are a professional writer,” Joshua Schimel said.³

Pauli defined the scientific method as “taking up a subject repeatedly. Thinking about it. Setting it aside. Gathering new empirical material. And continuing this process for years if necessary. In this way, the conscious mind stimulates the unconscious mind. If anything, this is the only way to achieve results.”⁴. This is more or less about taking a chair and sitting in the middle of the room and getting bored as long as possible. Doing so sparks creativity.

“Many scientific topics can only be solved once all aspects have been explicitly formulated. The mind is not sufficiently prepared for this, as it can only ever focus on small sections at a time. Systematic thinking is only possible when writing, i.e. recording the results of one’s thinking and relating them to other aspects.” — Otto Kruse⁵

1.5 What is statistics?

A toolbox of mathematical models to do science.

In this book we will use Fisherian statistics, which is inductive logic reasoning. Or in other words the logic of inductive inference.

Fisher switched from a mathematical deductive reasoning to a inductive reasoning in science. This is remarkable for me, because he changed the way he does science.

Statistics by Fisher and quantum mechanics have in common that both do inductive probabilistic reasoning. Scientific models are deductive

Statistical models are inductive

Figure 1.2: The difference between the two logical pathways: On the left is the inductive logic, which is a bottom-up approach that goes from specific to general. First, we observe and collect data, then we look for patterns in the data. Then, we draw a general conclusion about the pattern. After observing something a few times, we conclude that it is probably a rule. On the right is the deductive logic, a top-down approach from general to specific. We have a general theory and conduct an experiment to test it. Then, we draw a conclusion. From a more common perspective, the two logical pathways have things in common but differ in their train of thought.

$m = 0.03kg$ and $d = 2m$ and $g = 9.81 m/s^2$

Table 1.1: test

Trails	Height [m]	Potential energy [J]	Time [s]	Velocity [m/s]
1	$0.1$	$0.029$	$1.58$	$1.27$
2	$0.2$	$0.059$	$0.95$	$2.11$
3	$0.3$	$0.088$	$0.85$	$2.36$
4	$0.4$	$0.118$	$0.65$	$3.09$
5	$0.5$	$0.147$	$0.72$	$2.78$

R Code [show / hide]

m <- 0.03
d <- 2
t_func <- \(h) d/sqrt(2*9.81*h)

newton_tbl <- tibble(h = c(0.1, 0.2, 0.3, 0.4, 0.5),
       t = t_func(h) + rnorm(5, 0, 0.1),
       v = d/t,
       E = m * 9.81 * h) 

nls(E ~ 0 + b0 * I(v^b1), data = newton_tbl, 
           start = c(b0 = 0.1, b1 = 1))

Nonlinear regression model
  model: E ~ 0 + b0 * I(v^b1)
   data: newton_tbl
     b0      b1 
0.02048 1.68984 
 residual sum-of-squares: 0.0016

Number of iterations to convergence: 7 
Achieved convergence tolerance: 2.835e-06

R Code [show / hide]

newton_tbl

# A tibble: 5 × 4
      h     t     v      E
  <dbl> <dbl> <dbl>  <dbl>
1   0.1 1.58   1.27 0.0294
2   0.2 0.947  2.11 0.0589
3   0.3 0.847  2.36 0.0883
4   0.4 0.648  3.09 0.118 
5   0.5 0.720  2.78 0.147

R Code [show / hide]

newton_tbl |> 
  ggplot(aes(v, E)) +
  geom_point() +
  geom_function(fun = \(x) 0.5 * 0.03 * x^2) +
  geom_function(fun = \(x) 0 + 0.021 * x^(1.69), color = "red")

1.6 What is a good explanation?

1.7 Age of enlightment

1.8 General background

“Any sufficiently advanced technology is indistinguishable from magic.” — Arthur C. Clarke’s Third Law⁶

Full quote

“Reality is negotiable. Outside of science and law, all rules can be bent or broken, and it doesn’t require being unethical.” — Tim Ferriss

Idea of hypotheses

Science is guessing and falsification

⁷ What is this thing called Science?

⁸ What is science

⁹ What is science?

¹⁰ Models Demystified: A Practical Guide from Linear Regression to Deep Learning

¹¹ Statistical Thinking for the 21st Century

¹² The beginning of infinity: Explanations that transform the world

David Deutsch > Quotes

1.9 Theoretical background

1.10 R packages used

1.11 Data

1.12 Alternatives

Further tutorials and R packages on XXX

1.13 Glossary

term: what does it mean.

1.14 The meaning of “Models of Reality” in this chapter.

itemize with max. 5-6 words

1.15 Summary

References

[1]

Douglas KM, Sutton RM. What are conspiracy theories? A definitional approach to their correlates, consequences, and communication. Annual review of psychology. 2023;74(1):271-298.

[2]

Grimes DR. On the viability of conspiratorial beliefs. PloS one. 2016;11(1):e0147905.

[3]

Schimel J. Writing Science: How to Write Papers That Get Cited and Proposals That Get Funded. OUP USA; 2012.

[4]

Fischer EP. Die Stunde Der Physiker: Einstein, Bohr, Heisenberg Und Das Innerste Der Welt. CH Beck; 2022.

[5]

Kruse O. Keine angst vor dem leeren blatt. Ohne Schreibblockaden durchs Studium. 2007;12:112.

[6]

Clarke AC. Clarke’s third law on UFO’s. Science. 1968;159(3812):255-255.

[7]

Chalmers AF. What Is This Thing Called Science? Hackett Publishing; 2013.

[8]

Feynman R. What is science. Published online 1966.

[9]

Campbell NR. What is science? Published online 1952.

[10]

Clark M, Berry S. Models Demystified: A Practical Guide from Linear Regression to Deep Learning. CRC Press; 2025.

[11]

Cox D, Efron B. Statistical thinking for 21st century scientists. Science advances. 2017;3(6):e1700768.

[12]

Deutsch D. The Beginning of Infinity: Explanations That Transform the World. penguin uK; 2011.

```{r echo = FALSE, warning = FALSE, message = FALSE} source("init.R") source("images/part_0/part_0_science.R") ``` # What is science? {#sec-what-is-science} *Last modified on `r format(fs::file_info("chapter-01-what-is-science.qmd")$modification_time, '%d. %B %Y at %H:%M:%S')`* > *"Reality is negotiable." --- Tim Ferriss* The first chapter of this book is already the hardest. I started writing this chapter very early on, perhaps even before any of the others. Yet it took the longest to finish. The question is simple: What is science? The more I researched, the more complicated the answer became. Or the other way around. I followed the advice of Wolfgang Pauli. Pauli defined the scientific method as "taking up a subject repeatedly. Thinking about it. Setting it aside. Gathering new empirical material. And continuing this process for years if necessary. In this way, the conscious mind stimulates the unconscious mind. If anything, this is the only way to achieve results." Therefore, I tried to read and find answers to the question of what science might be. Perhaps science is, at its core, something personal. However, science also has objective aspects that I want to present here. Ultimately, decide for yourself what science truly is. ```{r} #| message: false #| echo: false #| warning: false #| fig-align: center #| fig-height: 5 #| fig-width: 10 #| fig-cap: "Visualization of the demarcation line of science. This line divides science from non-science through experimentation and the principle of falsification. The purity of science fields is taken from xkcd comic #435 ([https://xkcd.com/435](https://xkcd.com/435/)). According to this definition, natural science, including physics, chemistry, and biology, is separated from formal science, including mathematics. Formal science must be clearly distinguished from other intuition-based and subjective non-science, such as pseudoscience or anti-science. The humanities are indisputably different but are also considered non-science in this schematic." #| label: fig-sience-non-science p_science_overview ``` ## What is not science? Mathematics and psychoanalysis have no experiments. Mathematics and logic are more like scientific tools to do science. ## What is the opposite of science? As I found out, there is no direct opposite of science. Which is interesting. Because sometimes you can define something by knowing what the think is not. Is mathematics the language of nature? Cargo cult science conspiracy theories @douglas2023conspiracy and @grimes2016viability ## Why do science? ## How to do science? "As a scientist, you are a professional writer," Joshua Schimel said. @schimel2012writing Pauli defined the scientific method as "taking up a subject repeatedly. Thinking about it. Setting it aside. Gathering new empirical material. And continuing this process for years if necessary. In this way, the conscious mind stimulates the unconscious mind. If anything, this is the only way to achieve results." @fischer2022stunde. This is more or less about taking a chair and sitting in the middle of the room and getting bored as long as possible. Doing so sparks creativity. > *"Many scientific topics can only be solved once all aspects have been explicitly formulated. The mind is not sufficiently prepared for this, as it can only ever focus on small sections at a time. Systematic thinking is only possible when writing, i.e. recording the results of one's thinking and relating them to other aspects." --- Otto Kruse @kruse2007keine* ## What is statistics? A toolbox of mathematical models to do science. In this book we will use Fisherian statistics, which is inductive logic reasoning. Or in other words the logic of inductive inference. Fisher switched from a mathematical deductive reasoning to a inductive reasoning in science. This is remarkable for me, because he changed the way he does science. Statistics by Fisher and quantum mechanics have in common that both do inductive probabilistic reasoning. Scientific models are deductive Statistical models are inductive ```{r} #| message: false #| echo: false #| warning: false #| fig-align: center #| fig-height: 4.5 #| fig-width: 10 #| fig-cap: "The difference between the two logical pathways: On the left is the inductive logic, which is a bottom-up approach that goes from specific to general. First, we observe and collect data, then we look for patterns in the data. Then, we draw a general conclusion about the pattern. After observing something a few times, we conclude that it is probably a rule. On the right is the deductive logic, a top-down approach from general to specific. We have a general theory and conduct an experiment to test it. Then, we draw a conclusion. From a more common perspective, the two logical pathways have things in common but differ in their train of thought." #| label: fig-sience-inductive p_sience_inductive ``` ```{r} #| message: false #| echo: false #| warning: false #| fig-align: center #| fig-height: 4.5 #| fig-width: 4.5 #| fig-cap: "fooo." #| label: fig-statistic-inductive p_statistic_inductive ``` ```{r} #| message: false #| echo: false #| warning: false #| fig-align: center #| fig-height: 3.75 #| fig-width: 5.75 #| fig-cap: "fooo." #| label: fig-newton-example ggplot() + theme_void() + ## theme_minimal() + coord_cartesian(xlim = c(0.5, 10), ylim = c(0, 6.5)) + scale_x_continuous(breaks = seq(-10, 10, 1)) + scale_y_continuous(breaks = seq(-10, 10, 1)) + annotate("segment", x = 1.5, xend = 2.5, y = 0.5, yend = 0.5, size = 12, color = "gray25", lineend = "round") + annotate("segment", x = 2, xend = 2, y = 0.5, yend = 3, size = 15, color = "gray25") + annotate("segment", x = 2, xend = 2, y = 3, yend = 4.5, size = 10, color = "gray45") + annotate("segment", x = 1.5, xend = 2.5, y = 4.5, yend = 4.5, size = 5, color = "gray25", lineend = "round") + annotate("segment", x = 2, xend = 10, y = 5, yend = 0.1, size = 2.5, color = "#0D0887FF", lineend = "round") + annotate("text", x = 5.5, y = 3.25, label = "d = 0.6m", fontface = 2, size = 7, color = "#0D0887FF", angle = -30) + annotate("segment", x = 2.4, y = 5.3, xend = 3, yend = 4.9, arrow = arrow(length = unit(0.02, "npc"), type = "closed"), size = 1.5, color = "#6A00A8FF") + geom_circle(aes(x0 = 2, y0 = 5.5, r = 0.46), fill = "#6A00A880", size = 1.25) + annotate("text", x = 2, y = 5.5, label = "m", fontface = 2, size = 6, color = "black") + annotate("text", x = 2, y = 6.25, label = "0.03kg", fontface = 2, size = 6, color = "#6A00A8FF") + ## error bars annotate("segment", x = 1, xend = 1, y = 0.1, yend = 5, size = 1, color = "#FCA636FF") + annotate("segment", x = 0.9, xend = 1.1, y = c(0.1, 5), yend = c(0.1, 5), size = 1, color = "#FCA636FF") + annotate("text", x = 0.75, y = 2.45, label = "h", fontface = 2, size = 7, color = "#FCA636FF") + annotate("text", x = 4.5, y = 1.5, label = expression(phantom(x) %up% bold(h) %down% bold(Delta*t)), fontface = 2, size = 8, color = "black") + annotate("text", x = 7.5, y = 4.5, label = expression(bold(v)~"="~frac(bold(d),bold(Delta*t))), fontface = 2, size = 8, color = "black") ``` $m = 0.03kg$ and $d = 2m$ and $g = 9.81 m/s^2$ | Trails | Height \[m\] | Potential energy \[J\] | Time \[s\] | Velocity \[m/s\] | |--------|--------------|------------------------|------------|------------------| | 1 | $0.1$ | $0.029$ | $1.58$ | $1.27$ | | 2 | $0.2$ | $0.059$ | $0.95$ | $2.11$ | | 3 | $0.3$ | $0.088$ | $0.85$ | $2.36$ | | 4 | $0.4$ | $0.118$ | $0.65$ | $3.09$ | | 5 | $0.5$ | $0.147$ | $0.72$ | $2.78$ | : test {#tbl-newton-data} ```{r} m <- 0.03 d <- 2 t_func <- \(h) d/sqrt(2*9.81*h) newton_tbl <- tibble(h = c(0.1, 0.2, 0.3, 0.4, 0.5), t = t_func(h) + rnorm(5, 0, 0.1), v = d/t, E = m * 9.81 * h) nls(E ~ 0 + b0 * I(v^b1), data = newton_tbl, start = c(b0 = 0.1, b1 = 1)) newton_tbl newton_tbl |> ggplot(aes(v, E)) + geom_point() + geom_function(fun = \(x) 0.5 * 0.03 * x^2) + geom_function(fun = \(x) 0 + 0.021 * x^(1.69), color = "red") ``` ## What is a good explanation? ## Age of enlightment ## General background > *"Any sufficiently advanced technology is indistinguishable from magic." --- Arthur C. Clarke's Third Law @clarke1968clarke* Full quote > *"Reality is negotiable. Outside of science and law, all rules can be bent or broken, and it doesn’t require being unethical." --- Tim Ferriss* Idea of hypotheses Science is guessing and falsification @chalmers2013thing [What is this thing called Science?](https://www.pmf.unizg.hr/_download/repository/1._Dodatna_literatura_%28filozofija_znanosti%29%5B3%5D.pdf) @feynman1966science [What is science](https://www-oc.chemie.uni-regensburg.de/diaz/media/docs/feynman_what-is-science_68.pdf) @campbell1952science [What is science?](https://www.whatisscience.info/files/what_is_science_rd1.pdf) @clark2025models [Models Demystified: A Practical Guide from Linear Regression to Deep Learning](https://m-clark.github.io/book-of-models/) @cox2017statistical [Statistical Thinking for the 21st Century](https://statsthinking21.github.io/statsthinking21-core-site/index.html) @deutsch2011beginning [The beginning of infinity: Explanations that transform the world](https://www.academia.edu/download/106176299/rtx120400544p.pdf) [David Deutsch \> Quotes](https://www.goodreads.com/author/quotes/103190.David_Deutsch) ## Theoretical background ## R packages used ## Data ## Alternatives Further tutorials and R packages on XXX ## Glossary term : what does it mean. ## The meaning of "Models of Reality" in this chapter. - itemize with max. 5-6 words ## Summary ## References {.unnumbered}

Trails	Height [m]	Potential energy [J]	Time [s]	Velocity [m/s]
1	\(0.1\)	\(0.029\)	\(1.58\)	\(1.27\)
2	\(0.2\)	\(0.059\)	\(0.95\)	\(2.11\)
3	\(0.3\)	\(0.088\)	\(0.85\)	\(2.36\)
4	\(0.4\)	\(0.118\)	\(0.65\)	\(3.09\)
5	\(0.5\)	\(0.147\)	\(0.72\)	\(2.78\)