Statistics and Data Analytics, B.A.

California Baptist University

Program Summary – Bachelor of Arts in Statistics and Data Analytics (B.A. in Statistics and Data Analytics)

The Bachelor of Arts in Statistics and Data Analytics program equips students with the knowledge and skills to analyze and interpret complex datasets in a variety of contexts. This interdisciplinary program blends statistical theory with practical data analysis techniques, preparing students for careers in sectors like business, healthcare, technology, and government. The program focuses on data collection, data visualization, predictive modeling, and statistical inference, offering students hands-on experience with modern tools and software used in the field of data analytics.

Key Program Features:

• Statistical Analysis – Students learn the fundamentals of statistical theory, probability, and statistical inference.
• Data Collection and Management – Techniques for gathering, cleaning, and managing large datasets to ensure quality and accuracy.
• Predictive Analytics – The use of statistical models and machine learning algorithms to predict trends, behaviors, and outcomes.
• Data Visualization – Emphasis on representing complex data in clear and meaningful ways through graphs, charts, and interactive tools.
• Programming and Software Tools – Training in statistical programming languages (e.g., R, Python, SQL) and data analysis tools (e.g., Excel, Tableau, SPSS).
• Hands-on Projects – Opportunities to apply learning in real-world scenarios through internships, research projects, and case studies.

Key Areas of Study:

1. Introduction to Statistics – Basic principles of probability, descriptive statistics, hypothesis testing, and inferential statistics.
2. Data Analysis and Programming – Learning how to use programming languages like R and Python for data manipulation and analysis.
3. Data Visualization Techniques – Methods and tools for creating clear, impactful visual representations of data.
4. Advanced Statistical Methods – Topics such as regression analysis, time-series analysis, and multivariate analysis to handle more complex datasets.
5. Machine Learning and Predictive Modeling – Introduction to machine learning algorithms and their applications in predictive analytics.
6. Big Data and Data Mining – Techniques for handling and analyzing large-scale datasets, extracting valuable insights through data mining.
7. Applied Data Analytics – Real-world applications of statistics and data analytics in fields such as business, healthcare, and economics.
8. Ethics in Data Analytics – Understanding the ethical challenges of data collection, usage, and interpretation, including privacy issues and biases.

Career Opportunities:

Graduates of the B.A. in Statistics and Data Analytics program can pursue careers in various industries that require data-driven decision-making, such as:

• Data Analyst – Analyzing datasets to uncover trends, patterns, and insights to inform business or policy decisions.
• Business Analyst – Using data to guide business strategies, improve efficiency, and optimize decision-making.
• Data Scientist – Applying advanced analytical techniques and machine learning algorithms to solve complex problems and predict future trends.
• Market Research Analyst – Collecting and analyzing data on market trends, consumer behavior, and competition to assist in business strategy.
• Healthcare Data Analyst – Analyzing patient data to improve healthcare delivery, predict outcomes, and optimize operations.
• Financial Analyst – Using data to assess financial trends, forecast markets, and provide recommendations for investments.
• Government or Public Policy Analyst – Analyzing data to guide policy decisions, evaluate programs, and improve public services.