Sheila would like to sell her 2017 Honda Civic, and she needs to know what price to ask for it in order to write an ad.The car is in fair condition, and Sheila expects to get an average price for it.The question she must answer is "What is an expected selling price for a 2017 Honda Civic?"

A one-day inspection of the classified section of her local newspaper turned up only two ads for 2017 Honda Civics, and the two prices listed varied a great deal.Sheila's statistician husband convinced her that, in order to model accurately the selling behavior for Civics, she should define two variables - age and price - and collect several pairs of values from want ads by individuals.We used the following definitions: X = age of the car in years (current year minus year of manufacture), and Y = the advertised asking price.

For this project, you must collect your own data from classified ads (KBB values are not allowed).Collect ads which match the brand/make of the car that you pick as closely as possible (but a range of different years, of course).Try to find at least two ads for each year and then summarize them using the average of the advertised prices as the y coordinate.Try, as much as is reasonably possible, to select an equal number of ads from both the older side and the younger side of the year you're targeting.(If you are unable to do this, then that might be a source of error that you'd want to discuss in your write-up later on.)Do not use any ads that would obviously be special outliers, such as cars that have very rare and expensive features or "classic" models that don't fit the usual deterioration).

You may substitute a different make, model, and year of car for this problem (for example, 2017 Mustang); the rest of the instructions and questions will remain the same.One caution: don't pick a model year that's so extreme that you're unable to find data on either side of it!For example, this model year's Corvette wouldn't work.)When collecting data, make sure the same ad is not used twice because this would introduce bias into your data.

Tasks

1.Collect a sample of at least n = 20 pieces of bivariate (two variables) data - for example, the ordered pair (6, 9600) would represent a car that's six years old and sells for $9600.

a.Make a chart of your data.

b.Calculate the descriptive statistics for each of the two sets of data: the five-number summary, mean and standard deviation.

c.Analyze the measures of center and spread of the two sets of data.