Question

Find solutions to your homework Question An experiment was conducted looking at the likelihood to get covid when you are not vaccinated, vaccinated once, or double va Show transcribed data An experiment was conducted looking at the likelihood to get covid when you are not vaccinated, vaccinated once, or double vaccinated (note, all participants would be subjected to the same amount of virus). Abisays This in a great cxam questiont

Q1. What is the independent variable in this experiment ?
Q2. What is the dependent variable in this experiment?
Q3. What is a plausible H 0 ​ for this experiment ?
Q4. What kind of graph would be the best option for his type of data? Explain your Q5. On the graph below, identify three errors that the person made while creating this Shutterstock graph below.

Answer 1

In a scientific experiment on COVID-19 vaccination, the independent variable is vaccination status and the dependent variable is the likelihood of contracting COVID. A plausible null hypothesis would be that vaccination status has no effect on the likelihood of getting COVID. The best graph to use for this data is a bar graph.

Step-by-step explanation:

An experiment in science is a procedure carried out to support, refute, or validate a hypothesis. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated.

Independent and Dependent Variables

In the context of the provided research experiment, the independent variable is the vaccination status (not vaccinated, vaccinated once, or double vaccinated), which is the factor that is being changed by the researchers to observe effects. The dependent variable is the likelihood to get COVID, which is the result that is being measured in relation to the changes in the independent variable. To interpret the relationship between the two, we could ask: How does the vaccination status affect the likelihood of contracting COVID?

A plausible null hypothesis (H0) for this experiment would be that the vaccination status (not vaccinated, vaccinated once, or double vaccinated) has no effect on the likelihood of contracting COVID. This is because the null hypothesis typically assumes that there is no effect or relationship between the independent and dependent variables.

The best type of graph to represent this type of data would likely be a bar graph because it can clearly compare categorical data (different levels of vaccination) against a numerical measure (incidence of COVID).