Add one to the other side and y=1/2
Step-by-step explanation:
The measures of variability is blank, the number that best summarizes the data is blank, and the number that best describes how the data varies is blank
Please send the box plot, I can solve it then but there is not enough info right here. Sorry!
Answer:
In math :The objective function is a mathematical term that describes how different variables contribute to a certain value that is being sought to be optimized.
In science: Scientific objectivity is a characteristic of scientific claims, methods and results. It expresses the idea that the claims, methods and results of science are not, or should not be influenced by particular perspectives, value commitments, community bias or personal interests, to name a few relevant factors.
In ela: Being the object or goal of one's efforts or actions. not influenced by personal feelings, interpretations, or prejudice; based on facts; unbiased: an objective opinion. ... being the object of perception or thought; belonging to the object of thought rather than to the thinking subject (opposed to subjective).
Step-by-step explanation:
Answer:
Step-by-step explanation:
Pictured two triangles with two angles and non-included side being congruent.
It doesn't make the triangles congruent as it doesn't match any congruence postulates.
So not enough info in this case.
Answer: C. The data do not provide sufficient evidence to reject H0; thus, we cannot conclude that the mean point spread fo home games is higher than that of away games.
Step-by-step explanation: In Hypothesis Testing using p-value, after stating the null an alternative hypothesis, you have to compare p-value with level of significance, also known as α. If p-value is less than α, reject null hypothesis and accept alternative. If p-value is bigger, we would fail to reject null hypothesis and not accept the alternative.
In the above testing, P-value is 0.4351. Level of significance is, generally, 0.05. Comparing them, p-value is bigger than α. What it means is there is not enough evidence to support null hypothesis and, consequently, we can't conclude the difference in mean point spread of home games is higher than of the away games.