RSCH 600 Online_Activity Quantitative Analysis 1. Define the measure of central tendency. What does each measure tell us? 2. From the Gretl sample file, use the data on annual tuition and average...

RSCH 600 Online_Activity Quantitative Analysis 1. Define the measure of central tendency. What does each measure tell us? 2. From the Gretl sample file, use the data on annual tuition and average salary gain for MBAs at the 25 top to work on the following data analysis. (Hint: to access the data, go to Gretl File> Sample File > Ramanathan > data 4.14 Tuition and Salary gain for MBAs) a) At a 0.05 level of significance, is there a difference in average graded by recruiters in being analysts, team players and in having a global view of MBAs? b) Comment on the correlation coefficient for the variables under consideration. c) Which of the factors, according to the dataset, have a significant effect on the salary gain of MBA students at the top 25 universities, explain. (Hint: Multiple regression. Dependent variable ‘salary gain of MBA students at the top 25 universities’ 3. Stationarity From the Gretl sample file, use the data on Corporate profits and sales to work on the following data analysis. (Hint: to access the data, go to Gretl File> Sample File > Ramanathan > data 9.4 Corporate profits and sales). The data depicts the annual corporate profits (after taxes) and sales of the manufacturing sector in the US. a) Explain Stationarity b) Execute a unit root test to check whether variables in the dataset are non-stationary. c) In the case of non-stationarity based on the unit root test, then detrend the variable which is not stationary using the differencing approach. d) In the case of non-stationarity based on the unit root test, then detrend the variable which is not stationary using exponential smoothing (see McClave, Benson, Sincich: Time SeriesFile ppt lecture under Week 9) e) Using the dataset, plot histograms of sales and profits for all the years and describe how the profits and sales evolve. Variance_ Example (Gretl Sample Data) Bartlett and Levene tests for homogeneity of variance across groups. From the Gretl sample file, use the data on aNIST data for variance tests to work on the following data analysis. (Hint: to access the data, go to Gretl File> Sample File > Gretl > NIST data for variance tests) (Sample data from NIST http://www.itl.nist.gov/div898/handbook/eda/section3/eda3581.htm ).

rsch-600onlinactivity-afmip1ns.pdf

Mar 13, 2021

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