Answer:
im pretty sure its the second one i might be wrong tho
Explanation:
Answer: Consistency and Accuracy
Explanation:
Consistency tends to prove how reliable a test can be while to know it's validity we check how accurate it it is.
Regression is problematic for classical statistical tests that assume independently distributed errors.
Regression is a statistical technique that relates a dependent variable to one or more independent (explanatory) variables. A regression model can indicate whether an observed change in the dependent variable is associated with changes in one or more of the explanatory variables.
Regression comes from "regress", which comes from the Latin word "regresses" – (to return to something). In this sense, regression is a technique that allows us to move from chaotic and difficult-to-interpret data to a clearer and more meaningful model.
Regression analysis predicts a continuous dependent variable from a set of variables. Used when the independent variable. If your dependent variable is dichotomous, you should use logistic regression.
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The answer is D! hope it helped
Answer:
This statement is CORRECT: <u>One can keep adding premises to inductive arguments to make them go from strong to weak, then back to strong again, etc.</u>
Explanation:
The inductive reasoning is based on how the the premises are built, in order for them to lead us to a conclusion. This is why building the right premises can lead to a week or strong argument.
The process of builing a inductive argument is based on specific observations or statements into more general aspects. Although strong premises can lead to strong arguments, they do not garantee the conclusion would be true.
In logic, inductive argument it is not classify as valid or invalid, it is strong or weak according to the premises. The premises can be testable for instance, or they can come from observation.