Some studies of the relationship between car color and frequency of accidents have found that red cars are more likely to be in
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Let the year represents x axis and consumption represents y axis.
Since 2010 is the initial year, x=0
and 2013 is third year , so x=3
Co-ordinates are (0,8.938)(3,10.480)
Exponential formula is
Putting the value of x in the above formula from 1st coordinate,
As = 1
this gives a= 8.938
Now using the 2nd coordinate
putting the value of a in it we have
taking cube roots on both sides we get
b= 1.05448
Now putting the values of a and b in the exponential formula-
In the year 2028, x=28
so,
y= 39.474
Hence oil consumption per day in 2028 will be 39.474 million barrels.
Answer:
Step-by-step explanation:
Hello!
Given the variables:
X₁: Median Age
X₂: Median Income
b) Considering it from a logical point of view, income changes with age, for example, the more experienced the worker is you would think he would get a better paying job than a younger worker who is just starting. Then the dependent variable will be the median income and the independent variable will be the median age.
a) and c)
To see if there is a linear regression between the median income and median age you have to conduct a hypothesis test for the slope. If the slope is equal to zero, there is no linear regression between the two variables, if it is different to zero, there is a regression between the two of them:
H₀: β=0
H₁: β≠0
α: 0.05
The estimated regression equation for this regression ^Yi= 20.01 + 0.50X
The standard deviation for the slope is Sb= 0.11
And the p-value for the test is 0.0022
The p-value is less than the level of significance I choose, so the decision is to reject the null hypothesis. You can conclude that there is a linear regression between these two variables.
The correlation coefficient between the median income and the median age is r= 0.87 ⇒ This means you could expect a positive and strong linear correlation between the two variables.
d)
The slope represents how much the variable Y is modified whenever the variable X increases one unit.
In this example: Is the modification of the population mean of the median income, when the median age increases one year.
