econ project

ECON 301 (DATA ANALYSIS) ASSIGNMENT 6 – CREATING AN SPSS DATASET BY MERGING EXTERNAL DATA

File saved as: G:\PD - 2019-05-28\I-Docs\Academic\SDSU\Economics\Econ 301 (Data Analysis)\Mini Projects\Econ 301 - Mini Project 06 - Merging Data in SPSS.doc

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Assignment Objective: Generate Summary Statistics and Inferential Statistics in SPSS. Data Source: GSS2018.sav Assignment Deadline: Tuesday, March 24, 2020 Data Source(s):

 S&P500.csv  VIX–OHLC.csv

Assignment Objective: The objectives of this assignment are as follows:

1. Demonstrate how to import two .csv files into SPSS. 2. Merge two relatively large datasets into one SPSS dataset. 3. Re-enforce the knowledge gained in the previous assignments in SPSS generating

summary statistics. 4. Create variables in SPSS using the compute menus. 5. Re-enforce the knowledge gained in a previous assignments in SPSS generating

regression output. 6. Test for the presence of

A. Multicollinearity in SPSS using the VIF test. B. Autocorrelation in SPSS using the Durbin–Watson test. C. Heteroscedasticity in SPSS using Cook’s Distance statistic.

7. Save output files created in SPSS in other file formats such as .htm for non–SPSS users. Assignment Notes: Please remember to generate SPSS syntax on all aspects of the assignment, and to use the syntax you have generated to create output. (As shown in class, SPSS syntax will appear in the output file that you will print out.) Method of Submission/Deliverables: To be determined but in electronic format. Will involve submitting SPSS Output including the syntax generated. (I DO NOT NEED THE MERGED SPSS DATASET YOU CREATED.) You can save the portions of your output file imbedded into a Word document, or you can save your file in html format.

ECON 301 (DATA ANALYSIS) ASSIGNMENT 6 – CREATING AN SPSS DATASET BY MERGING EXTERNAL DATA

File saved as: G:\PD - 2019-05-28\I-Docs\Academic\SDSU\Economics\Econ 301 (Data Analysis)\Mini Projects\Econ 301 - Mini Project 06 - Merging Data in SPSS.doc

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Assignment Specifics Part 1 – Getting Started

1. Download S&P500.csv from Datasets folder on course’s BlackBoard page 2. Download VIX–OHLC.csv from Datasets folder on course’s BlackBoard page 3. Launch SPSS to import both .csv files (individually) into SPSS. 4. Remember to generate SPSS syntax, and to adjust features of the import wizard as you

import both files. 5. All variables imported in the combined dataset (except date) should be scale variables.

Part II – Performing the Assignment

6. Using either SPSS code or pull downs menus merge both datasets into one dataset on the date variable in both datasets.

7. Using either SPSS code or pull downs menus compute two new variables. A. Range (The difference between the daily high and low price on the S&P 500.) B. Open_Close (The difference between the opening and closing trade of the day on the S&P 500.)

8. Generate summary statistics A. mean B. median C. standard deviation D. standard error of the mean E. skewness F. kurtosis for all variables in the merged dataset except for date. (Note: Since the data in the dataset is a time series, some of the summary statistics generated may not be very meaningful.)

9. Run a simple regression with Volume as the dependent variable, and Range as the independent variable.

10. Run a multiple regression with Volume as the dependent variable, with Range and Open_Close as independent variables.

11. Run a multiple regression with Volume as the dependent variable, and all the other variables (except for date) as independent variables.

12. In the multiple regression models, test for: A. Mulitcollinearity (a situation in which one predictor variable in a multiple regression model is highly linearly related to one or more of the other predictor variables in our model.) by requesting collinearity diagnostics. B. Autocorrelation (a condition often present in time series data where the value of one observation of a variable is highly influenced by the value of that same variable in a previous period.) by requesting a Durbin–Watson test in SPSS.

13. For this project do not worry about the interpretation of these diagnostics.