Prediction Case Instructions: Data Analytics Read the Airbus case and use the Excel data file (both are in a zip file on Canvas in the Assignments section). You must develop and test a prediction...

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Prediction Case Instructions: Data Analytics Read the Airbus case and use the Excel data file (both are in a zip file on Canvas in the Assignments section). You must develop and test a prediction model on how the market will react to the disruption announcement of the A380. Your submission should consist of a .zip file that contains (1) an Excel file with your prediction model and (2) an executive summary in either Microsoft Word or PDF. Your Excel file should consist of a single well-formatted worksheet that includes (1) the regression table, (2) the prediction for each observation in the data based on a cutpoint of 0.50 (i.e., classify each observation as either “0” for smaller than 10% drop or “1” at least 10% drop), (3) the outcome (TP, FN, FP, TN), (4) the confusion matrix based on all of the observations, and (5) the calculations for Accuracy, Sensitivity, Specificity, Negative Predictive Value, Positive Predictive Value, and Prevalence using the confusion matrix. Your executive summary should include a copy and paste image of the regression table and a copy and paste of the confusion matrix. A well-formatted worksheet has: 1. A well-labeled worksheet tab. 2. Intuitive variable names, table structure, and labeling (reference in-class exercise) 3. Tables that are reasonably spaced from each other. 4. Data that does not bleed into adjacent cells. 5. A reasonable number of significant digits for each field. For instance, R-squared should be 2 or 3 digits, p-values should be 2 digits, coefficients and confidence intervals should be 2 or 3 digits or enough to show the first couple of non-zero digits (so instead of “0.00”, display “0.0023” if the coefficient rounds to 0 at two significant digits), etc. These examples are not all inclusive. Show the amount of detail necessary for a reader to interpret the data, but without unnecessary precision. Your executive summary should be clear, relevant, insightful, and concise. It should be around 1000 – 1500 words long. This is approximately 2-4 pages (excluding any tables) using 12-point font and 1-inch margins. This length is a guideline... you may go over or under as needed, provided that you address all the points in the case effectively. Your executive summary should address the following: 1. A succinct outline of the business question that Radek wants to answer and why it is important. 2. A brief summary of your prediction model and what variables you included. You do not need to justify why the variables are included in the prediction model. 3. A brief description of a confusion matrix, using language that a non-technical, but business savvy person (i.e. Radek) could understand and appreciate. 4. A table that provides the values for each metric below and the formula. This table should be accompanied by a 1-sentence description of each metric, using language that a non-technical, but business savvy person (i.e. Radek) could understand and appreciate. 1. Accuracy, 2. Sensitivity, 3. Specificity, 4. Negative Predictive Value, 5. Positive Predictive Value, 6. Prevalence 5. A brief description of how your prediction model works when generating the prediction for EADS. This should include the following: 1. The formula for the probability estimate from the regression model 2. A table summarizing the EADS values for each variable in the regression model 3. The calculated probability for EADS 4. The classification of EADS as either “0” (smaller than 10% drop) or “1” (at least 10% drop) 6. Clear recommendations for a course of action based on your prediction model, and highlighting the appropriate two metric(s) from point 4 that address two ways to measure the likelihood that your prediction is correct. 7. A description of how the analysis could be improved and what is needed to realize that improvement Your assignment will be graded along the following dimensions: 1. Did you address the requirements above 2. Is your writing clear and concise 3. Are your insights interesting and important 4. Is your presentation of the findings logical and effective 5. Did you make appropriate use of facts to substantiate your recommendations 6. Is your write-up suitable for an executive audience Prediction Case Instructions: Data Analytics Read the Airbus case and use the Excel data file (both are in a zip file on Canvas in the Assignments section). You must develop and test a prediction model on how the market will react to the disruption announcement of the A380. Your submission should consist of a .zip file that contains (1) an Excel file with your prediction model and (2) an executive summary in either Microsoft Word or PDF. Your Excel file should consist of a single well-formatted worksheet that includes (1) the regression table, (2) the prediction for each observation in the data based on a cutpoint of 0.50 (i.e., classify each observation as either “0” for smaller than 10% drop or “1” at least 10% drop), (3) the outcome (TP, FN, FP, TN), (4) the confusion matrix based on all of the observations, and (5) the calculations for Accuracy, Sensitivity, Specificity, Negative Predictive Value, Positive Predictive Value, and Prevalence using the confusion matrix. Your executive summary should include a copy and paste image of the regression table and a copy and paste of the confusion matrix. A well-formatted worksheet has: 1. A well-labeled worksheet tab. 2. Intuitive variable names, table structure, and labeling (reference in-class exercise) 3. Tables that are reasonably spaced from each other. 4. Data that does not bleed into adjacent cells. 5. A reasonable number of significant digits for each field. For instance, R-squared should be 2 or 3 digits, p-values should be 2 digits, coefficients and confidence intervals should be 2 or 3 digits or enough to show the first couple of non-zero digits (so instead of “0.00”, display “0.0023” if the coefficient rounds to 0 at two significant digits), etc. These examples are not all inclusive. Show the amount of detail necessary for a reader to interpret the data, but without unnecessary precision. Your executive summary should be clear, relevant, insightful, and concise. It should be around 1000 – 1500 words long. This is approximately 2-4 pages (excluding any tables) using 12-point font and 1-inch margins. This length is a guideline... you may go over or under as needed, provided that you address all the points in the case effectively. Your executive summary should address the following: 1. A succinct outline of the business question that Radek wants to answer and why it is important. 2. A brief summary of your prediction model and what variables you included. You do not need to justify why the variables are included in the prediction model. 3. A brief description of a confusion matrix, using language that a non-technical, but business savvy person (i.e. Radek) could understand and appreciate. 4. A table that provides the values for each metric below and the formula. This table should be accompanied by a 1-sentence description of each metric, using language that a non-technical, but business savvy person (i.e. Radek) could understand and appreciate. 1. Accuracy, 2. Sensitivity, 3. Specificity, 4. Negative Predictive Value, 5. Positive Predictive Value, 6. Prevalence 5. A brief description of how your prediction model works when generating the prediction for EADS. This should include the following: 1. The formula for the probability estimate from the regression model 2. A table summarizing the EADS values for each variable in the regression model 3. The calculated probability for EADS 4. The classification of EADS as either “0” (smaller than 10% drop) or “1” (at least 10% drop) 6. Clear recommendations for a course of action based on your prediction model, and highlighting the appropriate two metric(s) from point 4 that address two ways to measure the likelihood that your prediction is correct. 7. A description of how the analysis could be improved and what is needed to realize that improvement Your assignment will be graded along the following dimensions: 1. Did you address the requirements above 2. Is your writing clear and concise 3. Are your insights interesting and important 4. Is your presentation of the findings logical and effective 5. Did you make appropriate use of facts to substantiate your recommendations 6. Is your write-up suitable for an executive audience
Answered 1 days AfterApr 02, 2021

Answer To: Prediction Case Instructions: Data Analytics Read the Airbus case and use the Excel data file (both...

Vicky answered on Apr 04 2021
153 Votes
Regression Table
    OLS Regression Results
    ==============================================================================
    Dep. Variable: Sell_Threshold R-squared: 0.278
    Model:
OLS Adj. R-squared: 0.276
    Method: Least Squares F-statistic: 148.1
    Date: Sun, 04 Apr 2021 Prob (F-statistic): 2.54e-263
    Time: 00:57:30 Log-Likelihood: -1967.4
    No. Observations: 3862 AIC: 3957.
    Df Residuals: 3851 BIC: 4026.
    Df Model: 10
    Covariance Type: nonrobust
    =============================================================================================
     coef std err t P>|t| [0.025 0.975]
    ---------------------------------------------------------------------------------------------
    Intercept 0.2203 0.011 19.341 0.000 0.198 0.243
    Common_Shares_Outstanding -7.963e-05 4.86e-05 -1.640 0.101 -0.000 1.56e-05
    Disruption 0.3823 0.015 24.968 0.000 0.352 0.412
    Earnings_Surprise -0.2095 0.042 -4.946 0.000 -0.293 -0.126
    Long_Term_Debt -1.304e-05 8.45e-06 -1.544 0.123 -2.96e-05 3.52e-06
    Prior_Disruption 0.2574 0.023 11.417 0.000 0.213 0.302
    Property_Plant_Equipment 4.653e-07 3.26e-06 0.143 0.886 -5.92e-06 6.85e-06
    Share_Price -0.0022 0.000 -5.774 0.000 -0.003 -0.001
    Total_Assets -9.596e-07 5.04e-06 -0.190 0.849 -1.08e-05 8.93e-06
    Total_Common_Equity 3.615e-06 5.89e-06 0.614 0.539 -7.93e-06 1.52e-05
    Total_Liabilities 1.449e-06 4.92e-06 0.295 0.768 -8.19e-06 1.11e-05
    ==============================================================================
    Omnibus: 178.321 Durbin-Watson: 1.733
    Prob(Omnibus): 0.000 Jarque-Bera (JB): 195.754
    Skew: 0.535 Prob(JB): 3.11e-43
    Kurtosis: 2.734 Cond. No. ...
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