Answer:
y=5,902,060*(.957)^t
Step-by-step explanation:
Since the original amount would be decreasing and it's an exponential one, hence the "every year", we can determine that it's an exponential decay equation.
The exponential delay equation is y=A*(1-r)^t. The y is the remaining amount, A is the original amount, r is the rate in decimal form, and t is for years. "1-r" is for decreasing rates and "1+r" is for increasing rates.
First thing we need to do is turn the rate, 4.3%, from a percentage to a decimal. You can do this by moving the decimal two places to the right, which gives you 0.043.
Now plug the numbers into the equation.
y=5,902,060*(1-0.043)^t
Simplify what's inside the parenthesis and get your final equation.
y=5,902,060*(.957)^t
Answer:
First, we are going to find the sum of their age. To do that we are going to add the age of Eli, the age Freda, and the age of Geoff:
The combined age of Eli, Freda, and Geoff is 40, so the denominator of each ratio will be 40.
Next, we are going to multiply the ratio between the age of the person and their combined age by £800:
For Eli:
For Freda:
For Geoff:
We can conclude that Eli will get £180, Freda will get £260, and Geoff will get £360.
Step-by-step explanation:
Answer:
try x equals nine I am sure
Complete question is;
Regarding the violation of multicollinearity, which of the following description is wrong?
a. It changes the intercept of the regression line.
b. It changes the sign of the slope.
c. It changes the slope of the regression line.
d. It changes the value of F-tests.
e. It changes the value of T-tests
Answer:
a. It changes the intercept of the regression line
Step-by-step explanation:
Multicollinearity is a term used in multiple regression analysis to show a high correlation between independent variables of a study.
Since it deals with independent variables correlation, it means it must be found before getting the regression equation.
Now, looking at the options, the one that doesn't relate with multicollinearity is option A because the intercept of the regression line is the value of y that is predicted when x is 0. Meanwhile, multicollinearity from definition above does in no way change the intercept of the regression line because it doesn't predict the y-value when x is zero.
Well one similarity is that since you have to multiply, integer rules still apply and that you can also multiply variables. A difference is that with fractions, you have to make a number into an improper fraction rather than just the regular way which would most likely be the whole number with a decimal.
