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.
Unable to provide a definitive answer due to lack of diagram.
Answer: 1/4
Step-by-step explanation:
Multiples of 6:
Multiples of 6 are numbers obtained when 6 is multiplied by an integer. Such as
(6*1) = 6, (6*2)=12, (6*3) = 18..... and so on.
Probability is calculated by finding the ratio of the required outcome and total possible outcomes.
Probability = required outcome / Total possible outcomes
P(multiple of 6) = number of multiples of 6 / total number of possible outcomes
If number of 6 multiples = 5 and
Total number of faces in the spinner = 20
Then :
P(multiple of 6) = 5/20 = 1/4
Y=Mx +c
M gradient so count how many squares per one line
C = y intercept (7.5) here it looks
Just sub in those
Answer:
11/35
Step-by-step explanation:
First, you would have to make a common denominator. To do this, multiply these 2 denominator, 5 and 7. You should get 35. Then, you would have to make the numerator equal to the denominator. In this case, multiply 3 to 7 and 2 to 5. Now you have 21/35 and 10/35. Now subtract 21 from 10, and simplify if needed. I hope this helps!
Answer:
i don't sorry thanks for the points though
Step-by-step explanation: