The phrase “Simple Linear Regression” is utilized to represent the circumstances

Question

The phrase “Simple Linear Regression” is utilized to represent the circumstances where any one independent variable is utilized to anticipate the value of any dependent variable. (Simple Linear Regression (SLR), n.d.) Organizational Problem 1: Organization is required to compute the reasonable price for its products. Organizational Problem 2: There are some flaws in the management of the organization, how it will influence the performance of the organization. The initial problem is associated to the “simple linear regression” because the complete expenditure (direct and indirect) of the organization on product manufacturing can be helpful in deciding the affordable price for the product of the organization. (Hamel, n.d.) However, the second problem of the organization cannot be considered as associated to the simple linear regression because the management is not the single aspect to decide the performance and progress of the organization. There are some other aspects or variable to decide the organizational progress and performance such as employee satisfaction, market competition, economic level of the nation in which organization is surviving, and number of other facets. (Hamel, n.d.) The simple linear regression is capable to address anyone circumstance, but not other because of number and kind of variables engaged in the circumstances at any time. For instance: if the entire variable of any circumstance are independent, then simple linear regression model cannot be utilized in such circumstance. (Simple Linear Regression (SLR), n.d.)

MY QUESTION IS:

When so in regards to setting up your simple regression analysis would you use the products and list them what would be your independent variable, obviously you could use the price as the dependent variable and correlate but how would you categorize products? Also for the second problem after you looked into the problem more and did some research you could find those problem areas and use those as your dependent variables. After you find and label your variables?

Explanation / Answer

For the first problem, we need to predict the price of different products based on one independent variable. What we can do is to use the total cost of manufacturing that product (direct and indirect cost) and on the basis of that price the products. Say, we have USD 50 sent on manufacturing product A and USD 60 on product B. We can add a profit margin, say 10% of cost and add that to the price of the product. So our equation would be => Price (A) = Cost (A) + 0.1* Cost (A).

For the Second problem, we will have multiple variables or factors affecting the organization, so we will use linear regression with multi variable. We will have the variables like GDP growth rate, employee satisfaction rating, revenue generated that month, growth trend of the company, etc. Here revenue generated that month can be used as out dependent variable and rest and independent variables.

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