explain the correlation between Darwin's theory and Malthus' idea
He proposed a theory that attempts to explain why and the fact of evolution works.It is, so far, the best and most accurate theory that adequately explains why evolution happens.
natural selection and common descent
Charles Darwin! ummm it's kinda obvious! Durr
Charles Darwin formulated the notion of natural selection to explain the existence of patterns of radiative adaptation in nature, and to explain the seemingly common origin of diverse lifeforms.
He explained them in terms of descent with modification, common descent and natural selection.
please answer
The mechanism of heredity. His explanation, some sort of blending, was not supportable by the evidence and completely wrong We now know that heritable traits are particulate in nature.
Explain the partial and multiple correlation
Yes, Darwin's theory of evolution by natural selection continues to be a fundamental principle in the field of biology and is widely accepted by the scientific community. It is used to explain the diversity of species and their adaptations to different environments.
Evolution only deals with the changes within populations of organisms. All other sciences, including Astronomy and Cosmology, are mostly unconcerned with the theory. Otherwise, the theory was, and is, completely sound.
"If y tends to increase as x increases, then the data have a positive correlation. If y tends to decrease as x increases, then the data have a negative correlation. If the points show no correlation, then the data have approximately no correlation."
Through the evolutionary biology which attempts to explain events and processes that have already taken place.
No. The correlation between two variables implies that one of them can be predictor of the other. That is, one variable helps to forecast the other and it is not causality.
Explain. I have never seen the term selection used.
Possibly
No, correlation alone cannot prove causation. While a correlation between two variables indicates that they may be related, it does not demonstrate that one variable causes the other. Other factors, such as confounding variables or coincidence, can also explain the observed correlation. Establishing causation typically requires further evidence, such as experimental data or longitudinal studies.
Correlation analysis can be misused to explain a cause and effect relationship by misinterpreting data to assume that because something happened when a condition was present, it must have caused it, or vice versa. This isn't necessarily so, and those events and conditions may be unrelated.