Answer: none of the above
Step-by-step explanation: when performing an hypothesis test and we want to make conclusion by comparing the p-value with the level of significance α
When p is greater than α, we reject the null hypothesis because it simply implies that we have a larger chance to commit a type 1 error ( α is the probability of committing a type 1 error an error where we reject the null hypothesis instead of accepting it ) which means we reject the null hypothesis.
When p is lesser than level of significance α, it means that we have a lesser chance of committing a type 1 error, which means we accept the null hypothesis.
Answer:
Whats the question?
Step-by-step explanation:
Answer: the anwser is 5 trust me
Step-by-step explanation:
Answer: strong positive correlafion between data plan size 'x' and number of text messages sent 'y'
Step-by-step explanation:
'R' in statistics is used to denote correlation Coefficient. The correlation Coefficient is a value which ranges between -1 to +1. It tells us the level of relationship or correlation which exists between the relative movement of two variables, in this case the relationship between data plan size and the number of text messages sent in the US. R value of 0 depicts that no relationship exists between the two variables, R value closer the R value is to +1 and - 1 depicts the strength of positive and negative correlation of the two variables respectively.
A R value of +0.97 in the context above, depicts a strong positive correlation between data plan size and number of text messages sent in the US. That is large data size usually corresponds to large number of text messages and vice versa.
