Undergraduate Programs
Purdue's Department of Statistics is Indiana's major center for statistical teaching and research. It has the state's largest and oldest doctoral program in statistics and offers a broader range of statistics courses than any other institution in the state. The faculty is recognized as one of the nation's strongest in studies by the National Research Council.
As one of America's leading technical universities, Purdue offers strong programs in many areas that apply statistics. Numerous computational facilities make statistical software easily accessible on a variety of hardware platforms. First courses in statistics generally include laboratory sessions, and all applied statistics courses use and provide instruction in statistical software. The department has its own computing systems for research, and these are used in some advanced classes.
The Statistics Major consists of two options, one in Applied Statistics and one in Mathematical Statistics. The Statistics Major with Mathematical Statistics Option usually leads to a double major in Mathematics and Statistics. The interdisciplinary major in Actuarial Science is jointly administered by the Department of Statistics and the Department of Mathematics. Most Actuarial Science majors have a double major through the Statistics Major with Applied Statistics option.
Students planning to major in Statistics, Actuarial Science, or Mathematics take the same first-year academic program. It is therefore easy to choose among these majors and joint majors after a year at Purdue.
The Statistics Minor is also an option for students majoring in another discipline.
If you haven't made up your mind about a statistics major, please feel free to contact us.
Course Descriptions
Freshman Orientation Seminar
- Demonstrate the ability to communicate with peers & speakers in classroom.
- Demonstrate the ability to locate and use academic success resources.
- Demonstrate understanding of time management and study skills.
- Demonstrate knowledge in the utilization of Purdue degree planning tools.
- Demonstrate understanding of the academic requirements and career paths.
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Statistics And Society
- Distinguish between and qualify methods of data collection.
- Interpret graphs and statistical analyses.
- Express and calculate the likelihood of events.
- Create a narrative from statistical analysis.
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Introduction To Actuarial Science
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Topics In Statistics For Undergraduates
- Discover data science and professional development opportunities to prepare for a career.
- Design efficient search strategies to acquire new data science skills.
- Devise the most appropriate data science strategy to answer a research question.
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Introduction To Probability Models
- Understand basic terminology, set theory, and counting rules related to probability.
- Identify various discrete and continuous probability models/distributions and apply them to answer probability questions.
- Understand the Normal distribution and how to use the Standard Normal Table.
- Understand basic terms, graphs, and symbols and be able to interpret statistics in the media.
- Have a foundation in statistical methodology including the basics of hypothesis testing.
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Introduction To Data Science
- Use Python, R, and selected tools to scrape, clean, process, and visualize data.
- Apply data management techniques to prepare, parse, manipulate, and store data.
- Use statistical methods to summarize data and identify relationships.
- Explain how to formulate new hypotheses and draw accurate conclusions from data.
- Apply statistics and computational analysis to make predictions based on data.
- Apply basic computer science concepts such as modularity, abstraction, and encapsulation to data analysis problems.
- Effectively communicate the outcome of data analysis using descriptive statistics and visualizations.
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Problems Solving In Probability
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Topics In Statistics For Undergraduates
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Cooperative Experience I
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication and teamwork.
- Increase understanding of the profession and practice, basic industry principles, and principles and practice of ethical responsibility in professional work.
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Cooperative Experience II
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication and teamwork.
- Increase understanding of the profession and practice, basic industry principles, and principles and practice of ethical responsibility in professional work.
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Elementary Statistical Methods
- Students will be introduced to statistical methods and be able to apply them to multiple fields of study.
- Students will be able to understand, interpret standard statistical techniques, analyze data for one variable and for several variables, calculate and use confidence intervals and significance test for means and proportions, understand the design of samples and experiments, perform and understand basic probability calculations, perform simple and multiple regression procedures, and understand correlation.
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Elementary Statistical Methods
- Students will be introduced to statistical methods and be able to apply them to multiple fields of study.
- Students will be able to understand, interpret standard statistical techniques, analyze data for one variable and for several variables, calculate and use confidence intervals and significance test for means and proportions, understand the design of samples and experiments, perform and understand basic probability calculations, perform simple and multiple regression procedures, and understand correlation.
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Probability And Statistics For Business
- Understand basic terminology, set theory, and counting rules related to probability.
- Identify selected discrete and continuous probability models/distributions and apply them to answer probability questions.
- Understand, interpret standard statistical techniques/methods, analyze data, calculate and use confidence intervals and hypothesis tests for means and proportions, understand the design of samples and experiments.
- Understand basic terms, graphs, and symbols and be able to interpret statistics in the media.
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Introductory Probability
- Determine appropriate methods for determining probabilities and conditional probabilities.
- Use of distribution functions involving mass functions and cumulative distribution functions.
- Use of specific distribution functions for both discrete and continuous random variables including means and variances.
- Use of distribution functions involving more than one variable.
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Introduction To Statistics
- Understand basic terms, graphs, and symbols and be able to interpret statistics in the media.
- Understand and be able to explain statistical processes and be able to fully interpret statistical results.
- Understand why and how statistical investigations are conducted and the "big ideas" that underlie statistical investigations.
- Be able to use a statistical package (R or SAS) to analyze data and interpret result.
- Big Ideas in Statistics: variability, distributions, and models; causation vs correlation; practical significance vs statistical significance, etc.
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Introduction To Statistics
- Understand basic terms, graphs, and symbols and be able to interpret statistics in the media.
- Understand and be able to explain statistical processes and be able to fully interpret statistical results.
- Understand why and how statistical investigations are conducted and the "big ideas" that underlie statistical investigations.
- Be able to use a statistical package (R or SAS) to analyze data and interpret result.
- Big Ideas in Statistics: variability, distributions, and models; causation vs correlation; practical significance vs statistical significance, etc.
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Statistics For Data Science
- Utilize simulations to generate data (statistical simulations).
- Explain sampling distributions, their properties, and methods for resampling (Statistical Reasoning).
- Explain foundational concepts such as confidence intervals, hypothesis testing, correlations, etc.
- Assess statistical problems, and justify and apply statistical methods used to solve the problem (Statistical Thinking).
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Professional Practice Co-Op I
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication, and teamwork.
- Increase understanding of the profession and practice, basic professional principles, and principles and practice of ethical responsibility in professional work.
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Professional Practice Co-Op II
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication, and teamwork.
- Increase understanding of the profession and practice, basic professional principles, and principles and practice of ethical responsibility in professional work.
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Professional Practice Co-Op III
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication, and teamwork.
- Increase understanding of the profession and practice, basic professional principles, and principles and practice of ethical responsibility in professional work.
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Topics In Statistics For Undergraduates
- Acquire new data science skills.
- Devise the most appropriate data science strategy in order to answer a research question.
- Apply data science techniques in order to answer a research question about a big data set.
- Apply techniques for documenting, testing, sharing and creating a repository for code.
- Apply the best workflow practices in data science.
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Cooperative Experience III
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication and teamwork.
- Increase understanding of the profession and practice, basic industry principles, and principles and practice of ethical responsibility in professional work.
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Extensive Cooperative Experience IV
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication and teamwork.
- Increase understanding of the profession and practice, basic industry principles, and principles and practice of ethical responsibility in professional work.
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Extensive Cooperative Experience V
- Apply knowledge to identifying and solving problems in the professional context.
- Advance skills related to professional preparation, critical thinking, problem solving, communication and teamwork.
- Increase understanding of the profession and practice, basic industry principles, and principles and practice of ethical responsibility in professional work.
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Probability
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Statistical Theory
- Understand and able to use inference for standard parametric families of distributions; properties of estimators; Bayes and maximum likelihood estimation; sufficient statistics; properties of test of hypotheses; distribution theory for common statistics based on normal distributions.
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Introduction To Time Series
- Manage time series data; extract subset of time series data.
- Visualize time series data.
- Understand trend and correlation.
- Model time series data.
- Forecast of time series data.
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Fundamental Long Term Actuarial Mathematics
- Understand and use decrement models in conjunction with interest rate models to evaluate insurance, annuities, and investments.
- Apply models to calculate actuarial values, gross and net premiums, and benefit and expense reserves.
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Introduction To Arbitrage-Free Pricing Of Financial Derivatives
- Use arbitrage-free option pricing in the binomial market model and the Black-Scholes model.
- Adapt the binomial setting to computing exotic and path-dependent option prices, including the determination of optimal exercise.
- Follow marking-to-market strategies for approximate discrete delta hedging.
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Statistics For Risk Modeling I
- Understand the basics of several important analytic methods, including the following: Linear regression models; Generalized linear models; Principle components analysis; Decision trees; Cluster analysis.
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Advanced Long Term Actuarial Mathematics
- Understand key concepts concerning multiple state mortality/morbidity and joint life mortality models for insurance and annuity contracts.
- Understand key concepts concerning estimation and construction of multiple state and joint life models for insurance and annuity contracts.
- Perform calculations on the present value random variables associated with benefits and expenses for any of the models in the first learning objective.
- Analyze emerging surplus, and to set premiums and reserves, using profit testing.
- Understand how retirement benefits are accrued, valued, and funded.
- Understand various types of equity-linked life insurance guarantees, options that are embedded in life insurance and annuity contracts and be able to price, reserve and hedge the risk inherent in these options.
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Fundamental Short Term Actuarial Mathematics
- Calculate moments, percentiles, and generating functions.
- Describe how changes in the parameters affect the distribution.
- Recognize classes of distributions, including extreme value distributions, and their relationships.
- Create new distributions by multiplication by a constraint, raising to a power, exponentiation, and mixing.
- Identify the applications to which each distribution may apply and explain why.
- Apply the distribution to an application, given the parameters.
- Compare two distributions based on various characteristics of their tails, including moments, ratios of moments, limiting tail behavior, hazard rate function, and mean excess function.
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Topics In Statistics For Undergraduates
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Mathematical Statistics
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