statistics project ideas

statistics project ideas

Exploring Innovative and Impactful Statistics Project Ideas

1. Introduction to Statistics Project Ideas

In order to uncover what are the innovative, interesting or impactful statistics project ideas, ask a question or a problem related to any topic. Then, get others to critically think about the same thing by answering statistics to a specific and well-defined research question. Keep in mind and choose a topic/project that you have, or will have, a passion for. Because this is because pursued projects only offer valuable work inside and outside of lecture learning. Also, it is useful to play with the selection of data sets you have chosen and identify a data set with which one is comfortable and with which the address can be well framed. Learn new techniques, both those covered in class and not covered, because a good statistician’s toolkit is constantly expanding. Hone communication skills through this experience and present the findings effectively to both statisticians and non-statisticians. The skills you obtain by working through the project are valuable and will have enduring value.

If you look around, you might notice that you’re surrounded by a lot of data that seems to be of no real value. But, in actuality, this data is of immense value because it can give attention-grabbing insights. If you’re interested in statistics, this could be a major line of reasoning for deciding to learn it. This article includes innovative and impactful statistics project ideas that will not only get you in ideal projects for your Master or Bachelor course, but also can blow your mind. After receiving inspiration, break with tradition and create your own statistics project to discover the answer to what interests you in the spit of the enormous data. Each idea may seem a little bit clichéd, but it’s an okay reservoir of statistics project ideas.

2. Practical Applications of Statistics Projects

While recognizing that having students motivated to learn fits into a general perspective that may explain much schooling outcomes, some of the specifics of how to create a strong incentive are linked to offering students an opportunity to do something that they are both capable of doing and interested in doing. My approach is to have my students work in teams to carry out a data analysis project dealing with a real problem that involves strong aspects of statistical thinking.

What I would like to do is provide a little more detail in terms of how I use a team-based project for instruction in my research methods and data analysis classes at Seattle University. You will note that the faculty member and students describe how well these projects work in introductory statistics classes. There are lots of different ways to motivate students to engage in serious projects on interesting problems. My students have designed and conducted a national survey project in sampling theory, explored the use of the internet for educational purposes, data on pollution and its effects, data on the operation of ride-sharing services, and aspects of local government including the Seattle city council and the Seattle mayor’s office.

1.1. Research methodology, data analysis, design of experiments.

3. Advanced Statistical Techniques for Project Development

In addition, hierarchical models, time series, and analysis of variance for designs with unbalanced sample sizes and/or unequal variances are possible topics. The dissertation “Exploring Hierarchical Models with Comparison to Nonhierarchical Models” by Jennifer A. Manlove provides an in-depth treatment of hierarchical models. “Hierarchical Modeling: Modeling the Specific and Global Patterns” with Donald Rubin is a very comprehensive introduction to hierarchical modeling. “Data Analysis Plan: Statistical Models with Hierarchical Data” provides information about data analysis methods for researchers who are looking for information about data analysis topics and the results of complex or large data analyses.

There are many advanced statistical techniques, and a good place to start is the Encyclopedia of Statistical Sciences. Specifically, the over 600-page introductory chapter on exploratory data analysis and its companion techniques is especially relevant to a range of potential research projects, with chi-squared tests of independence also described in StatsMethods. This chapter contains 25 tutorials consisting of many worked examples and explanations of subfields of statistics such as computer-based data processing and other advanced statistical topics. Other advanced statistics that could support chemical engineering projects are Principal Components Analysis, Cluster Analysis, Regression, and general non-linear models, etc.

4. Case Studies of Successful Statistics Projects

The Burn and Learn Army, a student-led NGO, created a website that enables users to crowdsource the transcription of handwritten weather data on thousands of Royal Navy ships in the 18th and 19th century. The transcribed data will be used to improve the modern understanding of climate change and galvanize the public’s support for action to combat it. Over 4,000 people have volunteered to help with the project and extensive schools outreach activities are planned for 2021. The project is notable in that the students showed real-world initiative in using the skills learned in the classroom. This project is also notable for its balanced mix of scientific, community engagement, and administrative and project skills.

In the “No Evidence on Evidence-Based” study, students from 88 teams were tasked with systematically reviewing and synthesizing data from 39 studies that aimed to measure the effectiveness of programs targeting vulnerable youth. This project is exemplary in showing the operational value of crowdworking in statistics, as the ultimate goal of the project is to provide useful summaries to policy makers. Further, the students in the top four teams were co-authors on a paper reporting the results in the top health economics journal. The data show that the reviews produced by the students are of equivalent quality to those produced by experienced experts.

Real-world statistics projects have been extremely successful and have delivered measurable impact beyond the classroom. This section of the paper provides a survey of some of these successful projects.

5. Conclusion and Future Directions

We share our philosophy on the relationship between statistics and data as well as project development to involve statistics students in multidisciplinary fields and in real-world problems. We find that utilizing the real-world problems in introductory statistics projects is beneficial for engaging students who have no background in statistics in the course through a variety of learning tasks and longitudinal analysis. Our approach motivates students to learn and utilize scientific methods to make thoughtful decisions and communicate the results to the public. Along with our commitment to sharing our specialized teaching efforts with statistics teachers, we designed our data project collection using web-based resources.

In this paper, we focus on providing information on innovative and impactful data projects for high school students using public data. We discuss a list of project topics, which can be utilized to introduce advanced statistics topics such as multiple linear regression, time series analysis, and data communication techniques. We summarize the projects using a list of data-driven tasks and provide examples of the projects to demonstrate the benefits of data literacy for statistics education. All our suggested topics focus on real-world problems and were derived from everyday life and domain knowledge.