Part I:  Objective:  Use the Gretl program to analyze the relationship between Y (weight) and X (height) from the data described in Example 1.4 (contained in the htwt1.csv file) on pp. 18-20.   A.    Programming:  Click here for programming directions. Note:  this data is cross-sectional data, i.e., it's measured across individuals at a point of time. B.   Assignment: i.   Generate descriptive statistics (means, standard deviations, minimums and maximums) for the Y and X variables and briefly discuss.  How is each variable measured specifically? ii.   Generate a scatterplot of Y and X and discuss what it shows. iii.  Write a regression model (equation) that describes the likely relationship between Y and X.  Which is the dependent variable?  the independent variable?  Why so?  Discuss what the equation posits. iv.  Estimate your regression model and also generate predicted Y values and residuals. v.   Specifically, what do the observed Y, fitted (predicted) Y, and residual columns tell you?  How are they computed? vi.   Interpret the estimated coefficients. Part II:  Objective:  Use the Gretl program to analyze the relationship between PRICE and SQFT from the data described in Example 1.5 (contained in the house1.csv file) on pp. 20-23.   A.    Programming:  Click here for programming directions.  Note:  this data is cross-sectional data, i.e., it's measured across houses at a point of time. B.   Assignment: i.   Generate descriptive statistics (means, standard deviations, minimums and maximums) for the PRICE and SQFT variables and briefly discuss.  How is each variable measured specifically? ii.   Generate a scatterplot of  PRICE and SQFT and discuss what it shows. iii.  Write a regression model (equation) that describes the likely relationship between PRICE and SQFT.  Which is the dependent variable?  the independent variable?  Why so?  Discuss what the equation posits. iv.  Estimate your regression model and also generate predicted Y values and residuals. v.   Specifically, what do the observed Y, fitted (predicted) Y, and residual columns tell you?  How are they computed? vi.   Interpret the estimated coefficients.