Answer:
Depth below sea level is the independent quantity,
Water pressure is the dependent quantity
Step-by-step explanation:
An independent quantity is a variable that can be changed in an experiment. While, dependent quantity results from the independent quantity or we can say, that depends upon the independent quantity.
Here,
The water pressure increases 0.44 pounds per square inch (0.44 psi) with each increase of one foot in depth below sea level,
So, for measuring the water pressure we took depth below sea level as a variable,
⇒ Depth below sea level is the independent quantity,
While, with increasing depth by 1 foot the pressure is also increase by 0.44 pounds per square inches ⇒ pressure depends upon the depth
⇒ Water pressure is the dependent quantity.
Answer:
A
Step-by-step explanation:
A real interest rate is an interest rate that has been adjusted to remove the effects of inflation to reflect the real cost of funds to the borrower and the real yield to the lender or to an investor. A nominal interest rate refers to the interest rate before taking inflation into account.
15$ I believe, as we can disregard the two original books (they have been payed for) leaving her to buy 1 book and having seven dollars, however if she needs $8 more you simply need to add 8+7.
About 13,992
Hope that helps have a good day and can I get brainlist
Answer:
E IS THE CORRECT ANSWER
The R-squared is 0.64 and it means that the dependent value explains 64% of the independent value in the simple regression analysis
Step-by-step explanation:
R-Squared value is a very important indicator in a regression analysis.
What does it measure?
It measures how close to the line of best fit are the data points. How good the fitted line is can be indicated by the value of the r-squared.
The maximum value it can take is 1 and at this value, there is a direct and complete relationship between the independent variable x and the dependent variable y. The value 1 represents an 100% relationship between both parties.
The r-squared has a value of between 0 and 100%. The closer to 100, the better the model while the closer to 100, the more faulty the model is. In fact, a value of 0 indicates no relationship at all between the dependent and the independent variable.
With an R-squared value of 0.64, the regression model works above average to explain that the dependent variable explains 64% of the independent value in the simple regression analysis.
