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 speed for which Brian iron the shirts is given by:
Rewriting we have:
Then, for each minute, we have the amount of ironed shirt is:
Answer:
At this rate, Brian plans 10/162 of his shirt.
Answer:
5300
Explination:
3 × (10 × 10) + 5 × (10 ×10 × 10) = 5300
oder of operation, this is the order you do an equation.
Brakets first ( )
Exponets 'power of'
Devision ÷
M multiplication ✖
A addition ➕
S subtraction ➖
Answer:
cant help you i dont one suck
I know the answer but let me just make sure that it is correct
