Least Squares and RMSE

1. a. Look at the "HSDropoutRate" data set in R.

2. b. (You may want to extract the Rate and Year vectors for future use)

• What is the length/dimension of each vector?

• This should be a single number since each vector is the same length.

What is the output variable for the HSDropoutRate data set?

• Rate

• Months

• x

• y

Tags

CCSS.HSS.ID.B.6

Which is a valid command to fit this data in R?

• project(Rate ~ Year)

• project(Rate ~ Year + 1, data=HSDropoutRate)

• project(Rate ~ m*Year + b, data=HSDropoutRate

Tags

CCSS.HSA.SSE.A.1

CCSS.HSF.BF.A.1

CCSS.HSF.LE.A.1

CCSS.HSF.LE.A.2

After fitting this data with project(), either with the matrix method or the formula method, what is the value of the intercept? Round your answer to three decimal places

Tags

CCSS.HSS.ID.C.7

What would the model predict the dropout rate to be in the year 1976? Round your answer to one decimal place.

Tags

CCSS.HSS.IC.B.4

CCSS.HSS.ID.C.7

CCSS.HSS.MD.A.2

If the actual dropout rate was 14.2 in 1978 and the model predicts a dropout rate of 14.1, what is the component value of the residual vector for the year 1978? Round your answer to one decimal place.

Answer explanation

Residual = Actual data minus prediction

14.2-14.1 = 0.1

Calculate the whole residual vector, and calculate the RMSE. What is the RMSE? Round your answer to three decimal places.

Tags

CCSS.HSS.ID.B.6

Repeat that whole process, from start to finish, with the dataset "WorldPopulation." What is the RMSE of your model? Round your answer to three decimal places.

Tags

CCSS.HSS.IC.A.2