As a DNP, it is important to know the type of statistics utilized in the study under investigation. Prepare a question-guided with the following questions:
What is the difference between descriptive and inferential statistics?
What is the purpose of a descriptive analysis of the study population?
How do you compare descriptive and inferential statistics? Include a Venn Diagram in the summary where an explanation of the differences and similarities between descriptive and inferential statistics is shown.
Sample Answer
Descriptive vs. Inferential Statistics
Descriptive statistics summarize and describe the main features of a dataset. They provide simple summaries about the sample and the measures. Descriptive statistics include things like the mean, median, mode, standard deviation, and frequency. They are used to describe what the data shows without making any conclusions or inferences about a larger population.
Inferential statistics use data from a sample to make predictions, generalizations, or inferences about a larger population. This type of statistics allows you to draw conclusions beyond the immediate data. Examples include t-tests, ANOVA, and regression analysis. They are used to test hypotheses and determine if a relationship between variables exists in a larger population.
Purpose of a Descriptive Analysis
The purpose of a descriptive analysis is to summarize and organize the characteristics of a study population. This initial step in data analysis helps to understand the fundamental features of the data before any deeper, more complex analyses are performed. It provides a clear picture of the sample's demographics and other relevant variables. For example, a descriptive analysis might show the average age, gender distribution, and frequency of a specific health condition within the study group. This information is crucial for understanding the context of the study and for providing a foundation for the inferential analysis.
Comparison and Summary
| Descriptive Statistics | Inferential Statistics |
| Purpose | To describe, show, or summarize the data. | To make inferences, predictions, or generalizations about a larger population. |
| Data Type | Utilizes data from the entire population or sample. | Uses data from a sample to make conclusions about a population. |
| Key Questions | "What is?" or "What does the data show?" | "What can we conclude?" or "What does this mean for the population?" |
| Examples | Mean, median, mode, frequency distribution, standard deviation. | T-test, ANOVA, chi-square, regression analysis. |
Export to SheetsThe key difference is their function: descriptive statistics simply describe a dataset, while inferential statistics infer conclusions about a population based on a sample. They are not mutually exclusive; most research studies use both. Descriptive statistics are typically used first to get a feel for the data, followed by inferential statistics to test a hypothesis.
Descriptive Statistics Only: Measures of central tendency (mean, median), measures of variability (standard deviation), and frequency distributions. They are used for data summarization.