It's seppuku.
For those interested in the occult, you have to start at the bottom to understand occultist texts and not be influenced by dogmatism and other active entities trying to invoke messianic tenancies by manipulating your emotion over your logical process.
I'll go ahead and link youtube videos for beginners to review. There are many books, and which one to read depends on what area of study you are unfamiliar with. I have collected many over the years, and their usefulness is only in proximity to the influence of purpose they serve.
Also, it cannot be stressed enough that one has to study the current paradigm of religious theology to be able to comprehend the language that is used in the gnostic fashion.
See, the core root of gnostic thought revolves around a psychology that is not unlike the scientific method. The issues that come from the practices of such require them to be under the guise of being occult in nature, for they deny the power of state run entities over the personal experiences and knowledge of individuals. This has made many gnostics "Gnostic is a broad term at the point to accentuate any mysticism incorporated as a branch from metaphysical thought." an enemy of state run entities and persecuted by major religions.
As you will know if you study the subject, the practice of mysticism has followed the principles of the scientific method when exploring spiritual studies. This means that trial and error limits both practices, for the idea is a philosophical process for finding an idealistic "Truth". This means that both science, and mysticism can be backwards and obsolete. However, mysticism itself is buried due to persecution, and has been outshined by material expansion in the 20th century. This has caused social priorities dismiss the relevance of mysticism.
Gnostic mysticism from all religious practices is caught on both sides by both science and religion, both trying to destroy its existence. However, it is the bridge that unifies both schools of thought.
[h=3]Process[/h] The overall process involves making
conjectures (
hypotheses), deriving predictions from them as logical consequences, and then carrying out experiments based on those predictions to determine whether the original
conjecture was correct.[SUP]
[4][/SUP] There are difficulties in a formulaic statement of method, however. Though the scientific method is often presented as a fixed sequence of steps, they are better considered as general principles.[SUP]
[25][/SUP] Not all steps take place in every scientific inquiry (or to the same degree), and are not always in the same order. As noted by
William Whewell (1794–1866), "invention, sagacity, [and] genius"[SUP]
[26][/SUP] are required at every step.
[h=4]Formulation of a question[/h] The question can refer to the explanation of a specific
observation, as in "Why is the sky blue?", but can also be open-ended, as in "How can I
design a drug to cure this particular disease?" This stage frequently involves looking up and evaluating evidence from previous experiments, personal scientific observations or assertions, and/or the work of other scientists. If the answer is already known, a different question that builds on the previous evidence can be posed. When applying the scientific method to scientific research, determining a good question can be very difficult and affects the final outcome of the investigation.[SUP]
[27][/SUP]
[h=4]Hypothesis[/h] An
hypothesis is a
conjecture, based on knowledge obtained while formulating the question, that may explain the observed behavior of a part of our universe. The hypothesis might be very specific, e.g., Einstein's
equivalence principle or
Francis Crick's "DNA makes RNA makes protein",[SUP]
[28][/SUP] or it might be broad, e.g., unknown species of life dwell in the unexplored depths of the oceans. A
statistical hypothesis is a
conjecture about some
population. For example, the population might be people with a particular disease. The conjecture might be that a new drug will cure the disease in some of those people. Terms commonly associated with statistical hypotheses are
null hypothesis and
alternative hypothesis. A null hypothesis is the conjecture that the statistical hypothesis is false, e.g., that the new drug does nothing and that any cures are due to chance effects. Researchers normally want to show that the null hypothesis is false. The alternative hypothesis is the desired outcome, e.g., that the drug does better than chance. A final point: a scientific hypothesis must be
falsifiable, meaning that one can identify a possible outcome of an experiment that conflicts with predictions deduced from the hypothesis; otherwise, it cannot be meaningfully tested.
[h=4]Prediction[/h] This step involves determining the logical consequences of the hypothesis. One or more predictions are then selected for further testing. The more unlikely that a prediction would be correct simply by coincidence, then the more convincing it would be if the prediction were fulfilled; evidence is also stronger if the answer to the prediction is not already known, due to the effects of
hindsight bias (see also
postdiction). Ideally, the prediction must also distinguish the hypothesis from likely alternatives; if two hypotheses make the same prediction, observing the prediction to be correct is not evidence for either one over the other. (These statements about the relative strength of evidence can be mathematically derived using
Bayes' Theorem).[SUP]
[29][/SUP]
[h=4]Testing[/h] This is an investigation of whether the real world behaves as predicted by the hypothesis. Scientists (and other people) test hypotheses by conducting
experiments. The purpose of an experiment is to determine whether
observations of the real world agree with or conflict with the predictions derived from an hypothesis. If they agree, confidence in the hypothesis increases; otherwise, it decreases. Agreement does not assure that the hypothesis is true; future experiments may reveal problems.
Karl Popper advised scientists to try to falsify hypotheses, i.e., to search for and test those experiments that seem most doubtful. Large numbers of successful confirmations are not convincing if they arise from experiments that avoid risk.[SUP]
[30][/SUP] Experiments should be designed to minimize possible errors, especially through the use of appropriate
scientific controls. For example, tests of medical treatments are commonly run as
double-blind tests. Test personnel, who might unwittingly reveal to test subjects which samples are the desired test drugs and which are
placebos, are kept ignorant of which are which. Such hints can bias the responses of the test subjects. Furthermore, failure of an experiment does not necessarily mean the hypothesis is false. Experiments always depend on several hypotheses, e.g., that the test equipment is working properly, and a failure may be a failure of one of the auxiliary hypotheses. (See the
Duhem-Quine thesis.) Experiments can be conducted in a college lab, on a kitchen table, at CERN's
Large Hadron Collider, at the bottom of an ocean, on Mars (using one of the working
rovers), and so on. Astronomers do experiments, searching for planets around distant stars. Finally, most individual experiments address highly specific topics for reasons of practicality. As a result, evidence about broader topics is usually accumulated gradually.
[h=4]Analysis[/h] This involves determining what the results of the experiment show and deciding on the next actions to take. The predictions of the hypothesis are compared to those of the null hypothesis, to determine which is better able to explain the data. In cases where an experiment is repeated many times, a
statistical analysis such as a
chi-squared test may be required. If the evidence has falsified the hypothesis, a new hypothesis is required; if the experiment supports the hypothesis but the evidence is not strong enough for high confidence, other predictions from the hypothesis must be tested. Once a hypothesis is strongly supported by evidence, a new question can be asked to provide further insight on the same topic. Evidence from other scientists and experience are frequently incorporated at any stage in the process. Depending on the complexity of the experiment, many iterations may be required to gather sufficient evidence to answer a question with confidence, or to build up many answers to highly specific questions in order to answer a single broader question.
Alchemical study throughout ancient times was the root of all scientific thought and process of the modern era. It as-well follows the trial-and-error format, as well as the process of doubt over variable.
To not become confused by modern lexicons and definitions, I will propose a few statements to clarify the framework.
1. Language and mathematics are tied together through unknown processes, and are in fact two systems that clarify a set of rules to validate information.
2. Alchemical thought, as well as ancient thought structures, did not separate the spiritual and material realms, and saw one as an extension of the other.
3. Validation of all statements made from both schools of thought must be maintained, for natural systems degrade falsehood over time. Ignorance is the leash that the powerful use to pull the masses to their will.
The information that is out there is impossible to format on a short-term basis. So, if anyone is interested in certain topics, I will be happily available to pitch in my experiences.
