Think of a problem dealing with two possibly related variables (Y and X) that you may be interested in. Share your problem and discuss why a regression analysis could be appropriate for this problem. Specifically, what statistical questions are you asking? Why would you want to predict the value of Y? What if you wanted to predict a value of Y that’s beyond the highest value of X (for example if X is time and you want to forecast Y in the future)?

Explained below.

Step-by-step explanation:

Consider the variables height and weight.

It is usually seen that taller people are heavier than shorter people.

So a regression analysis can be used to specify this belief.

The statistical questions that are being asked here are:

The variable Y is considered as the dependent variable and the variable Y is considered as the independent variable.  And the main purpose of the regression analysis is to predict the value of Y when the value of X is given.

The linear regression model can be used to predict the past and future value of the dependent variables provided that the independent variables for those times are provided.

plants store their excess carbohydrate in the form of starch so that it could be used as energy source later on. the excess carbohydrate is converted into starch in the plastid i.e. chloroplast & this process occurs in the presence of sunlight. it is an insoluble polymer of glucose which gets stored in cell organelles named as amyloplasts. in some plants, starch is also stored in roots and embryos.