Different types of research questions can be answered by different types of research designs, which in turn need to be matched to a specific statistical test(s). DESIGN: Discursive paper. METHODS: This paper discusses the issues relating to the selection of the most appropriate statistical test ...
Example: Statistical hypotheses to test a correlation Null hypothesis: Parental income and GPA have no relationship with each other in college students. Alternative hypothesis: Parental income and GPA are positively correlated in college students. Planning your research design A research design is your ...
Independent T-test The independent t-test is also called the two-sample t-test. It is a statistical test that determines whether there is a statistically significant difference between the means in two unrelated groups. For example, comparing cancer patients and pregnant women in a population. ...
The gut microbiome is closely associated with health status, and any microbiota dysbiosis could considerably impact the host’s health. In addition, many active consortium projects have generated many reference datasets available for large-scale retrospe
In order to test for statistical significance, perform these steps: Decide on analpha level. An alpha level is the error rate you are willing to work with (usually 5% or less). Conduct your research. For example, conduct a poll or collect data from an experiment. ...
of direction, you'll want to use a two-tailed test. This is often the default choice in research when you want to ensure that your analysis captures any significant findings, whether they go in the expected direction or not. Here are examples of hypotheses suited for a two-tailed test: ...
decisions are sometimes made that result in analyses that are somewhat arbitrary or that lose statistical efficiency. For example, safety assessments can be too quick to rely on the proportion of patients in each treatment group at each clinic visit who have a lab measurement above two or three...
Through my research, I discovered that statistical significance helps you avoid acting on what could be a coincidence. It asks a crucial question: ‘If we repeated this test 100 times, how likely is it that we’d see this same difference in results?' If the answer is ‘very likely,’ th...
In addition, such algorithms should detect repeatable patterns, and it would be important to demonstrate that accurate predictions could be obtained in a sample of cases that was not used for the predictive modeling itself (a “holdout” or “test” sample). The most effective predictive ...
In contrast, our test statistics, which was directly used to test the differential network structure, performed much faster than DINGO (Supplementary Fig S2). In particular, our method is still feasible even number of genes p = 8000. Real data analysis Lung cancer is the leading cause of...