Yes examine history and you discover that astrologers have been wrong as much as they have been right (an ininformed guess is as good as an astrologers prediction).
The hypothesis is supported by evidence from the record, indicating a strong correlation between the variables being studied. The data collected aligns with the predictions made by the hypothesis, providing empirical support for its validity. Further analysis and testing may be necessary to confirm the hypothesis and establish its significance.
In terms of inventions, the telescope would have made it possible to do this.
babskit
An observation can also be made using instruments such as microscopes, telescopes, or sensors to gather data. Additionally, observations can be made through experiments, surveys, interviews, or simulations to study various phenomena or events. Furthermore, observations can be made through indirect methods, like analyzing patterns or trends in data or using mathematical models to make predictions.
Its strength was that it could predict the positions of the planets with pretty good accuracy. Its weakness was that by 1600 the techniques of measuring planets' positions had advanced to the point where discrepancies were noticed in the predictions made with the geocentric model.
Yes street signs are a good thing.I have read thousands predictions made by different astrologers but only a handful turned out to be true.
Considering in test-scoring "reliability" refers to the consistency of the test scores, and "validity" refers to the accuracy of the interpretations made from those scores, then reliability is possible without validity, although validity is not possible without reliability.
Because sometimes the predictions might not give accurate advice/response or it wouldn't be possible. The Predictions might've not made sense or it may have been unclear.
A scientist can prove a theory by conducting experiments, collecting data, and analyzing results to see if they consistently support the predictions made by the theory. The more evidence that aligns with the theory's predictions, the stronger the support for the theory. Additionally, peer review and replication of results by other scientists help confirm the validity of a theory.
In general terms, "validity" denotes "something acceptable within context". Thus, in an ordinary, everyday context, an example of "validity" would be a statement made which turns out to be true. Here, one would say that the statement made has "validity". By contrast, in a legal context, a statement made by a witness in a court case might be considered to lack "validity" because of certain legal strictures that prevent the witness' perspective from being considered by a jury. Many other examples could be provided, given the many different applications of "validity" that are possible.
Scientific hypotheses are most often tested by conducting experiments, collecting data, and analyzing results. This process involves comparing the outcomes of experiments with the predictions made by the hypothesis to determine its validity.
Throughout history, popes have made notable predictions such as the prophecies of St. Malachy, who predicted the future popes of the Catholic Church, and the predictions of Pope John XXIII about the Second Vatican Council. Additionally, some popes have made predictions about the end times and the future of the Church.
The validity of a scientific theory is typically tested through experimentation and observation. Scientists conduct tests and gather data to either support or refute the predictions made by the theory. Consistent and replicable results contribute to the validation of a scientific theory.
The astrologers mapped the stars and made observations of their movements. This aided astronomers because it gave them a framework to make further observations. The constellations developed by astrologers are still used today, even in scientific papers.In the related source link below, you can find a fuller history of astrology.
70% of the time no.
my left testes
To calculate accuracy in a statistical model, you compare the number of correct predictions made by the model to the total number of predictions. This is typically done by dividing the number of correct predictions by the total number of predictions and multiplying by 100 to get a percentage. The higher the accuracy percentage, the better the model is at making correct predictions.