Answer:
(a) <em>Linear regression</em> is used to estimate dependent variable which is continuous by using a independent variable set. <em>Logistic regression</em> we predict the dependent variable which is categorical using a set of independent variables.
(b) Finding the relationship between the Number of doors in the house vs the number of openings. Suppose that the number of door is a dependent variable X and the number of openings is an independent variable Y.
Step-by-step explanation:
(a) Linear regression is used to estimate dependent variable which is continuous by using a independent variable set .whereas In the logistic regression we predict the dependent variable which is categorical using a set of independent variables. Linear regression is regression problem solving method while logistic regression is having use for solving the classification problem.
(b) Example: Finding the relationship between the Number of doors in the house vs the number of openings. Suppose that the number of door is a dependent variable X and the number of openings is an independent variable Y.
If I am to predict that increasing or reducing the X will have an effect on the input variable X or by how much we will make a regression to find the variance that define the relationship or strong relationship status between them. I will run the regression on any computing software and check the stats result to measure the relationship and plots.
The equation used for this problem is
F = P(1+i)ⁿ
where
F is the future worth
P is the present worth
i is the effective interest rate
n is the number of years
Substituting the values,
F = <span>$8,000(1 + 0.03)</span>⁴
F = $9,004.07
Thus, after 4 years, Aaron will have $9,004.07.
Rearrange them to slope-intercept form
y = 7x + 2
y = -(1/7) x + 8
product of their slopes is 7 * -1/7 = -1 so they are perpendicular
Answer:
59
Step-by-step explanation:
3^3=27
2x27=54
27+54+5=59
Answer:
Step-by-step explanation:
5.9 I had this your welcome
