Jesus wants to start saving for college. His parents started an account for him that currently holds $325. Jesus adds $50 each m
onth. Label the y-intercept, the slope, and your axes
1 answer:
Answer:
y-intercept, c = 325
Slope, m = 50
The x-axis represents the number of months and y-axis represents the total amount in saving accounts.
Step-by-step explanation:
We are given the following in the question:
A saving account currently holds $325. Jesus adds $50 each month.
Let x be the number of months and y be the total money n the saving account.
Then, we can use a linear function to represent the money in the account.
Comparing to general linear function,
where m is the slope and tells the rate of change and c is the y-intercept that is the value when x is zero.
Comparing we get:
m = 50
c = 325
y-intercept = c = 325
Slope, m = 50
The x-axis represents the number of months and y-axis represents the total amount in saving accounts.
The attached image shows a graph for the same.
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Now that we know the distance between Paul and Jose, the only thing left is add that distance to the distance from Paul and the base of the tree:
We can conclude that Jose is 33.9m from the base of the tree.
We know that Paul is 19m from the base of the tree and its elevation angle to the top of the tree is 59°. We also know that the elevation angle of Jose and the top of the tree is 43°, but we don't know the distance between Paul of Jose, so lets label that distance as
Now we can build a right triangle between Paul and the tree and another one between Jose and the tree as shown in the figure. Lets use cosine to find h in Paul's trianlge:
Now we can use the law of sines to find the distance
Now that we know the distance between Paul and Jose, the only thing left is add that distance to the distance from Paul and the base of the tree:
We can conclude that Jose is 33.9m from the base of the tree.
Answer:
d. can be equal to the value of the coefficient of determination (r2).
True on the special case when r =1 we have that
Step-by-step explanation:
We need to remember that the correlation coefficient is a measure to analyze the goodness of fit for a model and is given by:
The determination coefficient is given by
Let's analyze one by one the possible options:
a. can never be equal to the value of the coefficient of determination (r2).
False if r = 1 then
b. is always larger than the value of the coefficient of determination (r2).
False not always if r= 1 we have that and we don't satisfy the condition
c. is always smaller than the value of the coefficient of determination (r2).
False again if r =1 then we have and we don't satisfy the condition
d. can be equal to the value of the coefficient of determination (r2).
True on the special case when r =1 we have that