The rate of change will be positive and a point in the graph will be (1,250);
the function then would be y = 250x;
after 1 year she will owe USD 5,250;
she will have to make 33 payments.
How to form equation using slope and one point?
y - y1 = m(x - x1) is the equation of a straight line's point slope form, where m is the line's slope and (x1, y1) is the point through which the provided line passes.
Using slope-point equation, the equation for the payment can be taken as:
y-250 = [(500-250)/(2-1)]*(x-1)
y - 250 = 250*(x-1)
y = 250 + 250x - 250 = 250x;
Putting x = 12, for a year the amount paid is USD 3,000.
Amount she owes = USD (8250-3000) = USD 5,250;
Total amount to be paid (in USD) = 8250
Amount paid per month (in USD) = 250
Thus, number of payments required = 8250/250 = 33
Thus, the rate of change will be positive and a point in the graph will be (1,250); the function then would be y = 250x; after 1 year she will owe USD 5,250; she will have to make 33 payments.
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Answer:
b
Step-by-step explanation:
The variability of the proportion of blemishes for Mary's sample will be greater than the variability of Pat's.
Answer:
Kindly check explanation
Step-by-step explanation:
Given the data showing the relationship between GPA and hours of study :
From the regression model given :
Regression equation is:
y = 0.141x + 1.096
Also, the regression Coefficient, R = 0.957
a) Describe how the line of best fit and the correlation coefficient can be used to determine the correlation between the two variables on your graph.
From the regression equation, we can infer if the relationship or correlation between the two variables is positive or negative from the value of the slope, a positive slope Value means a positive relationship while a negative slope value means a negative relationship.
The Correlation Coefficient, R also gives the strength of relationship, with values close to - 1 or 1 depicting a strong relationship while positive and negative R values also depictava positive or negative relationship.
Here there is a strong positive relationship between GPA and Hours.
Correlation does not imply causation. Correlation only shows the type of relationship between variables and it does not mean that high GPA values are causes by long hours of study and vice versa.