Before and after heart rate was measured from a group of participants after taking an experimental COVID19 vaccine. Which of the following conclusions is correct for the test results below. > t.test(hrdata$afterVaccine, hrdata$beforeVaccine, paired=TRUE) Paired t-test data: hrdata$afterVaccine and hrdata$beforeVaccine t = 1.4038, df = 9, p-value = 0.1939 %3D alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -2.568014 10.968014 sample estimates: mean of the differences 4.2 Hint* the first line of code should tell you the type of test you are dealing with. There is a significant difference in Heart Rate data between before and After observations. There is No difference in Heart Rate data between Before and After observations. The confidence intervals indicate that there is a difference between Before and After observations.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Trending now
This is a popular solution!
Step by step
Solved in 3 steps