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.
Answer:
The answer is $21
Step-by-step explanation:
.25×28=7
28-7=21
Answer:
1 over 2 is the slope :)
Step-by-step explanation:
629g < box + cereal < 633g
629g - 5g = 624g
633g - 5g = 628g
Answer: a. 624 < x < 628
Answer:
<h2>N(c, b)</h2>
Step-by-step explanation:
If N is midpoint between Q and R, then use the formula of a midpoint:
We have the points Q(0, 2b) and R(2c, 0). Substitute: