1. (Excel simulation). Some requirements use Excel Data Analysis Toolpak. First, please complete the simulation setup, then answer the questions.

1) Simulation setup:

Column Name	Generation guideline
Randomizer	use =NORM.INV(RAND(), 25, 12) formula to generate 250 random numbers.
Temperature	Use the random number generator. N = 250, normal distribution with = 120 and = 35
Temperature^2	Temperature^2
Hardness	Randomizer + 2 Temperature 0.006 Temperature^2

2.Use Temperature and Hardness columns to plot a scatter plot.

3) Use Regression tool in Data Analysis Toolpak to estimate the coefficients. (Hint: Your Input Y should be the Hardness column, Input X should be both Temperature and Temperatre^2 columns. Do not include Randomizer. Copy and paste the Summary Output table below as a picture.

4) Run the regression analysis again. But this time regress only Temperature column against the hardness. Do not include Randomizer and Temperature^2. Copy and paste the Summary Output table below as a picture.

5) "R square tells how well the estimated model fits the sample data. Compare the model outcome from step 3) and step 4). Which model fits the data better?

6) Compare the coefficient estimates (from the best model you chose in step 5) with the data generation process used in step 1. Does your model seem agree with how the data is generated?