Bitcoin Price Prediction: Data Analysis Using Regression Model

This report examines the potential to forecast Bitcoin prices using market capitalization and volume data. The study uses historical data from January 24th, 2019, to March 23rd, 2019, to build a predictive model. The core of the analysis involves multiple regression analysis, a technique selected due to its suitability for prediction problems involving multiple variables. The report addresses a real-world business situation by aiming to provide insights into Bitcoin price movements, which can inform investment decisions. The data, sourced from coinmarketcap.com, includes price, volume, and market capitalization, and the analysis seeks to determine the relationships between these factors and Bitcoin's price. The goal is to create a model capable of predicting Bitcoin prices at any given time, offering valuable information for investors and analysts. The report references Bolin's work on regression-based approaches to data analysis, providing a methodological foundation for the study.

Data Driven Decision Making Template
Student name:
ID number:
Date:
PROMPT RESPONSE
B.
Describe a real-world
business situation that
could be addressed by
collecting and analyzing a
set of data.
The emergence of numerous cryptocurrencies has attracted
individual and company investors. Bitcoin is one of the most
famous and valuable Cryptocurrency. Investors and business
analysist are trying to determine the best investment
decisions that can result into high returns. Determining the
expected price change (rise or fall) is a major factor in
Cryptocurrency investment. The change in prices can be
predicted/forecasted using the historical data. The other
factor that can be determined is the relationship between
price and other factors such as volume and market cap.
B1.
Summarize one question or
decision relevant to the
real-world business situation
you will answer by
collecting and analyzing a
set of data.
The research question that we will seek to answer is: Can we
forecast the price of Bitcoin using the market capitalization
and volume?
B2.
Explain why the situation or
question would benefit from
a data analysis.
The prediction of the price of Bitcoin would benefit from data
analysis because it will be possible to develop a model for
determining the expected prices of Bitcoin at any given time.
B3.
Identify data you will need
to collect that is relevant to
the situation or question.
Note: A sample size of 30
or more is suggested to
provide a statistically
reliable finding.
The data that we will need for the study is the historical data
of Bitcoin Cryptocurrency. The data on price, volume and
market capitalization. The data that will be used will include
two months data: Jan 24th 2019, to March 23rd 2019.
B4.
Describe the data gathering
methodology you will use to
collect data.
The data that is a secondary data. The data is publicly
available on the money Market cap website
https://coinmarketcap.com/.

B5.
Identify the appropriate
data analysis technique you
will use to analyze this data
(e.g., linear programming,
crossover analysis, t-test,
regression).
The analysis technique that will be used is the multiple
Regression Analysis. A multiple regression analysis will be
used to build a model that can be used to determine the
price of a Bitcoin at any given point.
B5a.
Explain why the data
analysis technique you
chose is an appropriate
technique to analyze the
data collected.
Multiple regression analysis is appropriate in this case
because the problem at hand is a prediction problem.
Furthermore, the data set contains more than one variable
and hence a multiple regression analysis is appropriate
(Bolin, 2014).
C.
Sources Used (if applicable) References
Bolin, J. H. (2014). Introduction to Mediation, Moderation, and
Conditional Process Analysis: A Regression-Based
Approach. Journal of Educational Measurement, 51(3),
2-10.