Correct question
Sale Price :160 | 180 | 200 | 220 | 240 | 260 | 280
New home : 126 | 103 | 82 | 75 | 82 | 40 | 20
A.) state the linear regression function that estimates the number of new homes available at a specific price.
B.) state the correlation Coefficient of the data, and explain what it means in the context of the problem
Answer:
Y = -0.79X + 249.86
R = -0.9543
Step-by-step explanation:
Sale Price :160 | 180 | 200 | 220 | 240 | 260 | 280
New home : 126 | 103 | 82 | 75 | 82 | 40 | 20
Calculate the Linear regression equation :
Using the linear regression calculator :
The linear regression equation is :
Y = -0.79X + 249.86
The correlation Coefficient 'R' measures the strength of statistical relationship between the relative movement of two variables. The The value of R is -0.9543 in the question above.
This is a strong negative correlation, which means that high sales price of homes scores correlates with low number of new homes scores (and vice versa). Homes with high sales price have fewer number of new homes.
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Step-by-step explanation:
Rohan11
Step-by-step explanation:
You multiply 3 by 9 which is 27
Answer with step-by-step explanation:
Let us find the perfect cubes between 1 to 100.
We know that, 1
3
=1,2
3
=8,3
3
=27,4
3
=64 and the rest numbers i.e. 4,5,6,.... have their cubes greater than 100.
So, only these four numbers have their cubes between 1 to 100.
Thus, there are 4 perfect cubes from 1 to 100.
Now, let's find the cubes between −100 to 0
We know, 0
3
=0,(−1)
3
=−1,(−2)
3
=−8,(−3)
3
=−27,(−4)
3
=−64 and the rest numbers have their cubes less than −100
So, only these 5 numbers have their cubes between −100 to 0 and 4 perfect cubes are there from 1 to 100.
Thus, there are 9 perfect cubes from −100 to 100.
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