The Inevitability of Improbability

[nwrickert (Neil Rickert)]

@Edgar_Tamarian

Good, saying this you made Evolutionary theory untestable, unfalsifiable.

From the way that I look at science, all scientific theories are untestable and unfalsifiable.

We use a theory to make predictions. Strictly speaking:

• theory plus data leads to predictions about future data.

It’s the predictions that are testable and falsifiable.

We judge a theory on the basis for its usefulness in making good predictions.

[Edgar_Tamarian]

@Timothy_Horton

Evolution is both testable and falsifiable. It can be tested by taking the data from the fossil and genetic records and making a best fit phylogenetic tree for each. Compare the two phylogenies. If there is strong agreement the theory is supported. If there is wild discordance the current theory is falsified.

Apart from fact that there are many inconsistencies in that tree, there is another model which well explains the data.

Ewert W (2018) The dependency graph of life. BIO-Complexity 2018 (3):1-27

[Timothy_Horton]

@Edgar_Tamarian

Apart from fact that there are many inconsistencies in that tree, there is another model which well explains the data.

Attempt to move the goal posts after your silly claim was refuted noted.

[T_aquaticus]

@Edgar_Tamarian

Good, saying this you made Evolutionary theory untestable, unfalsifiable. Since there are always unobserved/unknown possibilities

Here are 29+ examples of tests and potential falsifications for the theory of evolution:

29+ Evidences for Macroevolution: The Scientific Case for Common Descent

[T_aquaticus]

@Mung

Events are treated as if they have already occurred.

The odds of John Smith winning the lottery are 1 in 100 million before the drawing. If John Smith wins, then the odds of John Smith winning are 1 in 1. That’s the difference.

[T_aquaticus]

@Edgar_Tamarian

Apart from fact that there are many inconsistencies in that tree, there is another model which well explains the data.

Ewert W (2018) The dependency graph of life. BIO-Complexity 2018 (3):1-27

While we applaud Ewert’s attempt to address the data, his model still falls well short, even according to Ewert himself. You can find a discussion here:

Winston Ewert: The Dependency Graph of Life

An interesting and signficant article was published at the Discovery Institute, by @Winston_Ewert : The Dependency Graph of Life, DOI: 10.5048/BIO-C.2018.3. [NOTE: This thread has special rules; read and follow them or there will be consequences] This article is being drummed up by a past interlocutor of @vjtorley and myself (@Cornelius_Hunter) here on this forum thread: It has always been known that the common descent model fails, both from a long list of particular examples, as well as in systematic studies. But what might a better model be? Winston Ewert’s new paper (http://bio-complexity.org/ojs/index.php/main/article/view/BIO-C.2018.3 11) presents a dependency graph model, inspired by computer science. The paper uses model selection methods, and shows that the dependency graph model is a far superior model compared to common descent. New Paper Demonstrates Superiority of Design Model - Scientific Evidence - The BioLogos Forum I thought it would be worth discussing this in …

[Edgar_Tamarian]

@T_aquaticus

The odds of John Smith winning the lottery are 1 in 100 million before the drawing. If John Smith wins, then the odds of John Smith winning are 1 in 1. That’s the difference.

Probability of throwing a 6 with one dice is 1/6, after first throwing you get 6, so now probability is no more 1/6 but 1?

[T_aquaticus]

@Edgar_Tamarian

Probability of throwing a 6 with one dice is 1/6, after first throwing you get 6, so now probability is no more 1/6 but 1?

Yes. Once an event occurs the probability of that event occurring is 1, because it happened.

[Edgar_Tamarian]

i see lack of mathematicians in this website

[Mung]

@T_aquaticus

The odds of John Smith winning the lottery are 1 in 100 million before the drawing. If John Smith wins, then the odds of John Smith winning are 1 in 1. That’s the difference.

The odds of John Smith having won the lottery are not 1 in 100 million before the drawing. The probability is 0.0. Since the probabilty of him having won the lottery before the drawing is 0.0 he cannot possibly win the lottery.

[T_aquaticus]

@Edgar_Tamarian

i see lack of mathematicians in this website

So do I.

For example, you gave me a universal upper bound that I cracked with 3 decks of cards. That’s not very good math.

[T_aquaticus]

@Mung

The odds of John Smith having won the lottery are not 1 in 100 million before the drawing.

Could you explain this?

[Mung]

@T_aquaticus

Once an event occurs the probability of that event occurring is 1, because it happened.

If you toss a coin but don’t yet know the outcome which event is it that has a probability of 1? The coin has already been tossed. The outcome is certain. To which event will you assign the probability “1”?

[T_aquaticus]

@Mung

If you toss a coin but don’t yet know the outcome which event is it that has a probability of 1? The coin has already been tossed. The outcome is certain. To which event will you assign the probability “1”?

Please stop changing the analogy. Address the one that has already been given.

“We could also use the lottery to help illustrate the inevitability of improbability. In our example, the chances of winning the lottery is 1 in 100 million. There are exactly 100 million tickets sold in each drawing, and every drawing has a single winner.”

What are the odds that John Smith will win PRIOR TO THE DRAWING???

[Mung]

@T_aquaticus

Could you explain this?

There are two possibilities, not 100 million possibilities. John Smith has either won the lottery or John Smith has not won the lottery. The probability that John Smith has won a lottery that has not taken place is 0.

[T_aquaticus]

@Mung

There are two possibilities, not 100 million possibilities. John Smith has either won the lottery or John Smith has not won the lottery. The probability that John Smith has won a lottery that has not taken place is 0.

There are 100 million possibilities: the 100 million ticket holders.

You seem to be trying really hard to avoid the obvious.

[Mung]

@T_aquaticus

What are the odds that John Smith will win PRIOR TO THE DRAWING???

What are the odds that John Smith will win after the drawing has taken place?

[T_aquaticus]

@Mung

What are the odds that John Smith will win after the drawing has taken place?

PRIOR TO THE DRAWING!!!

Didn’t you read the post?

[nwrickert (Neil Rickert)]

@Edgar_Tamarian

Probability of throwing a 6 with one dice is 1/6, after first throwing you get 6, so now probability is no more 1/6 but 1?

That depends on whether you are asking about the probability for future tosses, or the probability for the toss that was just done (and came up 6).

[Edgar_Tamarian]

@nwrickert

That depends on whether you are asking about the probability for future tosses, or the probability for the toss that was just done (and came up 6).

does not matter, the probability is the same before and after, the fact it came up is because of chance 1/6, not 1, the fact we say there is 1/6 of time chance it will be 6, so, 1/6 chance is realized, it does not automatically become 1,