Approaches in analyzing

1. Approaches in Analyzing
Alternatives
Rara Mercado

3. Small businesses can’t afford to make decisions
on a whim without researching and justifying
those actions. According to research conducted
by the U.S. Small Business Administration in
2018, the average profit margin for a small
business in North America is roughly 7% per
year.

5. Regression Analysis
● Estimate relationship
between variables.
● Predict the value of one
variable(dependent) on the
basis of other variables
(independent)
● useful in assessing the
strength of the relationship
between variables.
Ex. relationship between size
of the house to it’s selling
price.

6. Where:
● Y= the dependent variable of the regression equation
● M= slope of the regression equation
● x=dependent variable of the regression equation
● B= constant of the equation

7. Let us try and understand regression analysis with the help of another example. Let us try to find out what is
the relation between the height of the students of a class and the GPA grade of those students. Someone
actually does a regression equation to validate whether what he thinks of the relationship between two
variables is also validated by the regression equation.

8. The regression for this example will be
● y = MX + b
● y= 2.65*.0034+0
● y= 0.009198

9. Differential Analysis
-incremental Analysis
-involves analyzing the different costs and benefits that
would arise from alternative solutions to a particular
problem.
-Examine only the changes in revenues, cash and profits that
result from a business decision instead of creating income
statement for each

10. It is used to make the following types of decisions
- Make or buy product
- Keep or drop product
- Keep or drop customers
- Accept or reject special customer orders.

11. Linear Programming
-a simple technique where we depict complex relationships through linear
functions and then find the optimum points. The important word in the
previous sentence is depicted. The real relationships might be much more
complex – but we can simplify them to linear relationships.

12. Common terminologies used in Linear Programming
● Decision Variables: The decision variables are the variables that will decide my output.
They represent my ultimate solution. To solve any problem, we first need to identify the
decision variables.
● Objective Function: It is defined as the objective of making decisions. I
● Constraints: The constraints are the restrictions or limitations on the decision variables.
They usually limit the value of the decision variables.
● Non-negativity restriction: For all linear programs, the decision variables should always
take non-negative values. This means the values for decision variables should be greater
than or equal to 0.

15. Cost benefit Analysis
It is a comparison between the costs and benefits associated with a
business action. A cost-benefit analysis will give you a better
insight into whether or not an action is worth the investment in the
short and long term through evidence-based evaluations.