In this assessment, we focus on the cornerstone of quantitative research: the variable. One of the many things that makes the health care field so fascinating (and challenging) is the variation we find from one human to the next. Age, gender, eye color, heart rate, ethnicity, emotional response, and food preferences are some of the differences we find in our communities around the globe. In the language of statistics, each of these characteristics is called a variable. Some characteristics, like gender, have little variation, while other characteristics, like age, can have a much larger amount of variation.
Throughout this course, you will see that variables have special names based on their functional roles in the experiment. For example, when a variable is associated with the intervention (such as treatment, where we design the experiment to allow for only two options: practicing yoga versus not), it is referred to as an independent variable.
And when a variable is associated with an outcome in the experiment (for example, stress—which we decide, arbitrarily, will have only three possible levels: high, medium, and low) that is used to measure the direct consequences of the experimental treatment, we refer to this as a dependent variable.
The sneaky thing about statistics is that depending on the circumstances, the independent variable is often referred to in other terms, such as the controlled, explanatory, or predictor variable. If you consider this briefly, the names make sense because you are controlling who gets which treatment, where the treatment really is the key factor in explaining (or predicting) any outcome. The dependent variable may also be referred to as response, outcome, output, or experimental variable. In this course, we will try to be fairly consistent, using the terms independent and dependent.
Overview
The baseline demographic table plays an important role in reporting study results. It summarizes key characteristics of participants numerically (such as age, gender, and ethnicity) at the beginning of a study, before any intervention takes place. Baseline demographic tables are often among the first tables found in the results section of capstone papers, dissertations, and peer-reviewed publications as well. For this assessment, you will create a baseline demographic table and narrative summary using the linked Resources.
Demonstration of Proficiency
By successfully completing this assessment you will address the following scoring guide criteria, which align to the indicated course competencies.
- Competency 1: Describe underlying concepts and reasoning related to the collection and evaluation of quantitative data in health care research.
- Write a summary narrative about statistical results.
- Competency 2: Apply appropriate statistical methods using common software tools in the collection and evaluation of health care data.
- Perform descriptive statistics for selected variables in a data set.
- Create a demographic table populated with descriptive data for specific treatment groups.
- Use appropriate statistics for a given data measurement level.
- Competency 3: Interpret the results and practical significance of statistical health care data analyses.
- Explain the clinical significance of a demographic table.
- Competency 5: Address assignment purpose in a well-organized text, incorporating appropriate evidence and tone in grammatically sound sentences.
- Articulate meaning relevant to the main topic, scope, and purpose of the prompt.
- Apply APA formatting to in-text citations and references.
