The CSTEP program has implemented “The Proyecto Access CSTEP Research Initiative (PACRI)” that is an intensive two semester research training activity with the objective to enhance research skills of minority/underrepresented students pursuing careers in STEM and license professions.
Students will be paired with a faculty mentor, attend research workshops, and field trips, and present their research topics at the CSTEP Statewide Conference and other research conferences and events.
Science and the Scientific Method
We cannot escape from the significance of science. A student scientist is someone who is being formally educated about science and how to practise science, as well as developing scientific skills and attributes such as teamwork, communication, and personal and professional responsibility. Learn about what science is and how it works, and how science graduates are able to change society for the better.
"In scientific research, we conduct statistical analyses to help us determine whether datasets are different from each other. When statistical analysis determines that datasets are different, we refer to the datasets as ‘statistically different’, or the difference as ‘statistically significant’ or that there is ‘a significant difference’. When statistical analysis reveals that datasets are not different, we say that there is ‘no significant difference’ between groups."
Examining and Understanding Your Data
"It is important to distinguish the types of variables with which you are working, because the type of data influences the kinds of analysis and the presentations that are most appropriate."
You will increase the chance of engaging and informing your audience by communicating the findings of your research visually, through figures and tables. Presenting data in figures and tables, rather than in text alone, will help the audience grasp difficult concepts and observe patterns. You will learn how to create column and line graphs with correct axis titles, error bars, and significance symbols using Microsoft Excel and Word software. You will also learn how to create scientific tables.
Basic Concepts and Design Considerations
Upon obtaining data from a hypothesis-based study, scientists often have the understandable desire to immediately test any underlying hypothesis they may have. In practice, this is not the best way to start. The first step should be a careful evaluation of the raw data, including one or more graphs and/or plots and a number of useful summaries. Such a step can help you to understand the main patterns, catch errors, and, with experience, provide some indication of whether there might be some difficulties with the assumptions that will underlie the statistical tests you perform.
Statistical Inference — Comparing Two Groups
When developing a “formal” hypothesis tests for comparing two samples: first, focus on some key design issues, then develop procedures appropriate for quantitative variables followed by a discussion of comparisons for categorical variables.
ANOVA — Comparing More than Two Groups with Quantitative Data
Quite often, biologists wish to compare more than two groups. Using our example on thistle density from previous chapters, a biologist might be curious about whether thistle densities are the same (or not) for three or more treatment groups: e.g. burned, unburned, and mowed prairie plots. Here we develop statistical inference techniques for comparing three or more groups with quantitative data using normal theory. These methods are often described as ANOVA methods where ANOVA is short for ANalysis Of VAriance.
Further Analysis with Categorical Data
A chi-square (Χ2) test of independence is a nonparametric hypothesis test. You can use it to test whether two categorical variables are related to each other.
Choosing the Right Statistical Test | Types & Examples
Statistical tests are used in hypothesis testing. They can be used to:
Statistical tests assume a null hypothesis of no relationship or no difference between groups. Then they determine whether the observed data fall outside of the range of values predicted by the null hypothesis.
The Beginner's Guide to Statistical Analysis | 5 Steps & Examples
Statistical analysis means investigating trends, patterns, and relationships using quantitative data. It is an important research tool used by scientists, governments, businesses, and other organizations.
To draw valid conclusions, statistical analysis requires careful planning from the very start of the research process. You need to specify your hypotheses and make decisions about your research design, sample size, and sampling procedure.
After collecting data from your sample, you can organize and summarize the data using descriptive statistics. Then, you can use inferential statistics to formally test hypotheses and make estimates about the population. Finally, you can interpret and generalize your findings.
This article is a practical introduction to statistical analysis for students and researchers. We’ll walk you through the steps using two research examples. The first investigates a potential cause-and-effect relationship, while the second investigates a potential correlation between variables.
Scientific Literature and References
An essential skill for all scientists to master is the ability to access relevant and reliable scientific information from a variety of sources. You will need access to scientific literature for a variety of reasons:
•designing an experiment
•writing an article or essay
•designing a poster.
All these tasks involved sourcing reliable, authoritative literature, and you’ll need to know how to reference it.
This chapter will provide student scientists with assistance in navigating the many avenues for locating scientific literature and referencing it, including using the reference management software EndNote.
"It is becoming harder and harder to keep on top of all new findings in a topic area and – more importantly – to work out how they all fit together to determine our current understanding of a topic. This is where literature reviews come in. This chapter will explain what a literature review is and outline the stages involved in writing one. We also provide practical tips on how to communicate the results of a review of current literature on a topic in the format of a literature review."
Writing for Your Health Sciences Audiences
When you begin a writing assignment in a Health Sciences course, you want to ask yourself some questions first:
Who is your audience? Another health professional? The general community? A government official? What kind of tone is most appropriate based on your audience?