I'm confused with both of these questions. can someone help me out? thank you

I have a jar of jelly beans on my desk, and would like to guess how many jelly beans are in the jar. Which of the following approaches would qualify as an ensemble method? Measure the dimensions of the jar, calculate the jar's volume, and divide that by an estimate of the volume per jelly bean. Build a regression model that uses the dimensions of the jar as independent variables to predict the number of jelly beans. Identify a cluster that I believe is 5% of the jelly beans, count them, and multiply the result by 20. Ask 30 different people to guess how many jelly beans are in the jar, and take the average of the 30 guesses. The daily number of customers at our store has a mean of 175 and a standard deviation of 25 . We built a linear regression model to predict the number of customers for any given day based on several other variables. In the Bxcel regression output, the value of "Significance F " is 0.00042. Which of the following can we conclude is true: All of the independent variables are significant. The standard error associated with our predictions is 25. Using this regression model gives better predictions than predicting 175 every day. R Square is greater than 0.5