Hypothesis testing is a statistical method used to determine whether there is a significant difference between two or more groups. It is not a type of descriptive statistic, which is used to summarize and describe data.

Inferential statistics are used to make inferences about a population based on a sample. They allow researchers to test hypotheses and determine whether there is a significant difference between two or more groups.

A parametric test is a statistical test that assumes that the data is normally distributed. The t-test is a parametric test that is used to compare the means of two groups.

A Type I error occurs when a researcher rejects the null hypothesis when it is actually true. A Type II error occurs when a researcher accepts the null hypothesis when it is actually false.

A power analysis is used to determine the sample size needed for a study in order to achieve a desired level of statistical power. Statistical power is the probability of rejecting the null hypothesis when it is actually false.

Qualitative research methods are used to collect and analyze non-numerical data. Interviews are a type of qualitative research method in which researchers ask participants open-ended questions and record their responses.

Mixed methods research studies collect and analyze both quantitative and qualitative data. The purpose of a mixed methods study is to triangulate the findings of the two types of data, which can provide a more comprehensive understanding of the research problem.

Data visualization techniques are used to represent data in a visual format. Bar charts, pie charts, histograms, and scatterplots are all examples of data visualization techniques.

The purpose of a research report is to communicate the findings of a research study to readers. Research reports should be written in a clear and concise style and should be free of bias.

Research ethics are the principles that guide the conduct of research. Honesty, objectivity, and confidentiality are all examples of research ethics.