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.
What are the plans?
( Sorry if not answering real question.)
Answer:
0.185%
Step-by-step explanation:
ms.T goals = 13000 steps per day
<u>24</u><u>/</u><u>13000</u><u>×</u><u>100</u>
<u>2400</u>
<u>13000</u>
<u>=</u><u>24</u><u>/</u><u>130</u>
<u>=</u><u> </u><u>0.185</u><u>%</u>
-√121
10 1/11
10.13
10.2 repeating
The answer is C because you would move the decimal 7 places to the right to get 15,000,000.