Answer:
I'll setup the problem and leave the computation to you
Step-by-step explanation:
The equation to calculate fixed payments
P= payments
r = interest rate for the period (which is a quarter )
PV = present value (or the amount borrowed)
n = number of periods
r = .25/4 (4 months = quarter of a year)
n = 4*10
PV = R450550.00
if you have questions, put them in the comment
Answer:
$1683.50
Step-by-step explanation:
You are expected to know that a "mill" is one thousandth of a dollar. In this context, it is the amount of tax on one dollar of assessed valuation. So, the tax amount is found by multiplying the valuation by 18.5/1000:
tax = 0.0185 · $91,000 = $1683.50
Answer:
$79.63
Step-by-step explanation:
You can figure this by estimating. 16% is a little less than 20%, which is 1/5. $497.69 is almost $500. So, 1/5 of that is almost $100, and a little less than that is about $80. The closest answer choice is $79.63.
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If you want to figure it exactly, you can do the multiplication ...
16% of $497.69 = 0.16 × $497.69 = $79.6304 ≈ $79.63
Answer:
Step-by-step explanation:
You need to assume that the slope between the dependent Varian and the numerical independent variable is zero.
In regression analysis, to find the effect of one independent variable on the dependent variable, there has to be no interference from the other independent variables whether they be categorical (dummy) or numerical independent variables.
A dummy variable is one which takes on the value of 0 or 1, to represent the absence or presence (respectively) of a given category which is expected to influence the dependent variable.
When a dummy independent variable is included in a regression model, to know the effect of that dummy or category (e.g. day =1, night =0) on the dependent variable, the influence of the numerical independent variable has to be removed temporarily.
In a regression equation,
Y=a+bX+cK
Y is the dependent variable
a is the intercept on the vertical axis on the graph
b is the slope between the dependent variable Y and the independent numerical variable X
c is the slope between the dependent variable Y and the dummy variable K