1. Dr. Anna N. Elsa is developing an intervention to help her anxious patients Let It Go. She randomly assigns 33 anxious individuals to three conditions: therapy alone (treatment A), the control...

I don't need the R code for the questions.


1. Dr. Anna N. Elsa is developing an intervention to help her anxious patients Let It Go. She randomly assigns 33 anxious individuals to three conditions: therapy alone (treatment A), the control group), therapy + meditation (treatment B), or therapy + meditation + yoga (treatment C). After completion of the treatment, she measures the participants’ level of anxiety. The data, HDFS881_ anxiety.xlsx, is on D2L. Run the appropriate analysis and write a brief results section. Be sure to include appropriate descriptive statistics and an examination of assumptions. 2. Dr. Autumn O. Beal is examining what impacts the efficiency of various cars. She collects data on horsepower, weight of the car, and the car’s acceleration, in addition to the cars’ efficiency as measured in miles per gallon. The data, HDFS881_cars.xlsx, is on D2L. Run the appropriate analysis and write a brief results section. Assume your readers know very little about cars, and would therefore not understand the units of any of the variables in the dataset. Be sure to include appropriate graphs and an examination of assumptions. [This is real data of cars from the 70s and early 80s. Take a moment to admire how much more efficient cars are today; the average mpg is now about 26 mpg even with the rise of SUVs and pickup trucks.] 3. You all know the idea, right: the red shirt is the character that is going to die. If you aren’t familiar, check out https://en.wikipedia.org/wiki/Redshirt_(stock_character). There is real data on this (it is not more dangerous to wear a red shirt), but I made up different data. The data, HDFS881_shirts. Run the appropriate analysis and write a brief results section. Be sure to include the appropriate table and an examination of assumptions.