Regression Analysis: Modeling Exponential Growth & Business Decisions

This report delves into the application of regression analysis in business, focusing on understanding the relationships between variables and modeling exponential growth. It discusses the straight-line relationship between business variables and different types of models, including predictive, descriptive, and decision-based models, for assessing exponential growth. The concept of correlation and its role in exponential growth are explained, along with the utility of multiple regression in business decision-making, especially in accommodating tangent factors. Furthermore, the report highlights the role of MS Excel tools, such as Pivot Tables, Descriptive Analysis, Trend Curves, and time-based functions, in performing essential functions for business analytics and modeling, emphasizing their ability to connect small databases with big data machinery.

1. Straight Line Relationship between the Variables of the Business
We can divide the business-related data into various types of variables and draw different
scatter plots to understand the relationships between the variables. This process is also known
as regression analysis, for example, let's assume that per Square feet area of a house is one
variable and distance of the house from a particular point is another variable. This equation
clearly gives us a picture that once we increase the number of square feet in the area of the
house its cost will increase. When we put these values in a scatter plots and put some dots
between X-axis and Y-axis, the connecting line between these points will be a straight line
and we can say that effecive cost of the house is directly proportional to its area (Lee, 2012).
2. Modeling of the exponential growth
Predictive Model, Descriptive Model, and Decision-based models are the three types of
model to check the exponential growth. In the predictive model, we compare a sample unit
under ideal or test conditions with a real unit. The difference between the two units can be
further calculated for the creation of scenarios. In a descriptive model, we break down the
customers and variables from a given a sample onto the next level. Here we make groups of a
similar type of customers and study their behaviors on certain fields to predict probable
behavior from their side. Decision-based models are models that can be used for the purpose
of the maximization, minimization or optimization of certain resources or functions based
upon the findings of many Descriptive and predictive models. These models can give us a
point where the business can reach to the level of the exponential growth based on the
correlation of the factors (Solomon, 2016)
3. Co-relation and exponential growth
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The concept of co-relation explains the dependence of two variables with each other.
It can be described under three categories, positive correlation, negative correlation or
no correlation. Exponential growth is the state of positive correlation where after
passing a certain interval of time or any other variable, the growth in the number
becomes rapid and shoots up to an enormous level (Weisberg, 2013).
4. Multiple Regression and its utility in Business decision making
In a straight line regression model we figure out the relationship between two variables,
multiple regression can be termed as the sum of many straight line regressions working
under the same model. For instance, in the case of the tourism industry, factors like
availability of the flight seats, accommodation facility can be treated as constant factors,
however, the weather can become another crucial factor (Solomon, 2016). In a multiple
regression based calculation, we can accommodate certain tangent factors and derive an
outcome based on them. Multiple regressions identify independent and dependent
variables and calculate the total variable and define the predictive power of any
calculation model with the help of "explained variables."
5. Role of MS-Excel
With the help of MS Excel tools, we can independently perform certain functions that
are essential in business analytics. Pivot Tables and Descriptive Analysis tools can
help us in connecting with the bigger picture, Trend Curves, Graphs supporting
multiple regression process and projecting exponential scenarios is another feature.
Time-based functions can be calculated. We can also connect many small Excel
databases with big data machinery with the help of the functions like OFFSET and
INDIRECT. "Inquire" and "add-in" are some other tools that can perform functions
related to business modeling (Winston, 2014).
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Bibliography
Lee, A. (2012). Linear Regression Analysis. New York: Wiley.
Solomon, L. (2016). Design a Better Business: New Tools, Skills, and Mindset for Strategy
and Innovation. New York: Wiley.
Weisberg, S. (2013). Applied Linear Regression. New York: Wiley.
Winston, W. (2014). Microsoft Excel 2013 Data Analysis and Business Modeling. London:
Pearson.
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