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.
I don't know what I've been told
I think the answer is 50" because if the table is 42" and it needs to hang over 8" then it would have to be 50"
6x-6
Step-by-step explanation:
add both equations together, then multiply that by 2
2*(2x+3+x-6)
Answer:
B) 12,010.9
Step-by-step explanation:
Set up an equation:
Solve:
