Question

Using the Discussion Board Rubric located below as a guide, develop a well thought-out response about one of the topics listed below, by briefly writing a short essay which may include but must not be limited to definitions, application, and need to understand/use. Include the necessary citations to support any assertions you make. pick one. Correlation Analysis, Linear Regression Analysis, or Hypothesis testing with regression analysis

Answer 1

Linear Regression

Linear Regression Analysis is a statistical approach or technique used to predict the unknown dependant variable value using the known independent variable. It is nothing but a predictive analysis. In Artificial Intelligence ,

A Dependant variable is the variable to be predicted as the outcome variable

An Independent variable is the variable which has relationship to the dependant variable otherwise called as input variable in a regression equation . The equation is

   Y = a + bX

where Y is the Dependant variable and X is the Independent variable. a is the Y intercept and b is the slope of the line.

a is the value of the of Y when the value of X is zero. slope b is the change in the Y for a unit of increase in X

Application of Linear regression

Linear Regression is applied in Machine Learning (ML) applications . Machine Learning belongs to Artificial Intelligence(AI) which automatically learn and predict the output. Machine learning predict the output Y based on the input X using supervised learning which in turn uses linear regression. Supervised learning have input independent variables X and output Dependant variables so that it can apply Linear regression algorithms to learn the mapping function from input to output.

Linear Regression algorithms are used by supervised learning to predict the prices of a property or buildings belonging to real estate , or find the rating of food items manufactured by companies where the rating will be output variable Y based on input variables X.

In the below data , rating marked yellow is the target variable Y which is the dependant variable while columns marked in red are independent X variables which are attributes of cereals vary for every manufacturer.

By applying linear regression algorithms we can predict the rating (Y) and visualize the model fitting using matplotlib library in python language as below

Use

Linear Regression used to estimate real values such as cost of houses or real estate buildings , sales of consumer products based on continuous variables otherwise called as independent variables, It finds its usage in

• Marketing and sales where one can analyse the user preference and recommend the products based on user preferences
• Health care where to analyse and predict the patient health status based on inputs
• Financial services to take business decisions
• Real Estate where on can predict the price based on the various parameters such as location , crime rate, cost of living, medical facilities, education and shopping facilities available in the location