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Matching21:CHALLENGE - Solutions25:CHALLENGE - Solutions.mp4eed6:lengthi14941446e4:pathl23:10 Section 8 - Matching21:Common Support Region25:Common Support Region.mp4eed6:lengthi5747269e4:pathl23:10 Section 8 - Matching20:Matching - Game Plan24:Matching - Game Plan.mp4eed6:lengthi8762855e4:pathl23:10 Section 8 - Matching8:Matching12:Matching.mp4eed6:lengthi5662739e4:pathl23:10 Section 8 - Matching27:My Experience with Matching31:My Experience with Matching.mp4eed6:lengthi24363567e4:pathl23:10 Section 8 - Matching24:Python - Chi-square Loop28:Python - Chi-square Loop.mp4eed6:lengthi40645346e4:pathl23:10 Section 8 - Matching24:Python - Chi-square Test28:Python - Chi-square Test.mp4eed6:lengthi30237338e4:pathl23:10 Section 8 - Matching39:Python - Cleaning and Preparing Dataset43:Python - Cleaning and Preparing Dataset.mp4eed6:lengthi9533894e4:pathl23:10 Section 8 - Matching44:Python - Common Support Region Visualization48:Python - Common Support Region Visualization.mp4eed6:lengthi20985749e4:pathl23:10 Section 8 - 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Preparing for Common Support Region.mp4eed6:lengthi90332502e4:pathl23:10 Section 8 - Matching37:Python - Race Variable Transformation41:Python - Race Variable Transformation.mp4eed6:lengthi30877532e4:pathl23:10 Section 8 - Matching49:Python - Robustness Check - Removing 1 confounder53:Python - Robustness Check - Removing 1 confounder.mp4eed6:lengthi60162524e4:pathl23:10 Section 8 - Matching48:Python - Robustness Check - Repeated experiments52:Python - Robustness Check - Repeated experiments.mp4eed6:lengthi24996505e4:pathl23:10 Section 8 - Matching20:Python - T-Test Loop24:Python - T-Test Loop.mp4eed6:lengthi27496133e4:pathl23:10 Section 8 - Matching15:Python - T-Test19:Python - T-Test.mp4eed6:lengthi4868879e4:pathl23:10 Section 8 - Matching17:Robustness Checks21:Robustness Checks.mp4eed6:lengthi5533489e4:pathl23:10 Section 8 - Matching27:The Curse of Dimensionality31:The Curse of Dimensionality.mp4eed6:lengthi5464448e4:pathl23:10 Section 8 - Matching16:Unconfoundedness20:Unconfoundedness.mp4eed6:lengthi213471e4:pathl23:11 PART C_ SEGMENTATION48:What is Segmentation and why is it important.pdfeed6:lengthi1636094e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis39:CASE STUDY - Online Shopping (Briefing)43:CASE STUDY - Online Shopping (Briefing).mp4eed6:lengthi11464235e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis24:CHALLENGE - Introduction28:CHALLENGE - Introduction.mp4eed6:lengthi40252585e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis21:CHALLENGE - Solutions25:CHALLENGE - Solutions.mp4eed6:lengthi9000859e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis30:Python - Applying RFM Function34:Python - Applying RFM Function.mp4eed6:lengthi14962649e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis32:Python - Creating Sales Variable36:Python - Creating Sales Variable.mp4eed6:lengthi22601246e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis35:Python - Customer Level Aggregation39:Python - Customer Level Aggregation.mp4eed6:lengthi12049219e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis22:Python - Date Variable26:Python - Date Variable.mp4eed6:lengthi10199577e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis32:Python - Directory and Libraries36:Python - Directory and Libraries.mp4eed6:lengthi22237304e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis21:Python - Loading Data25:Python - Loading Data.mp4eed6:lengthi5460835e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis26:Python - Monetary Variable30:Python - Monetary Variable.mp4eed6:lengthi24145828e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis18:Python - Quartiles22:Python - Quartiles.mp4eed6:lengthi11930367e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis21:Python - RFM Function25:Python - RFM Function.mp4eed6:lengthi6878491e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis18:Python - RFM Score22:Python - RFM Score.mp4eed6:lengthi15651523e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis24:Python - Results Summary28:Python - Results Summary.mp4eed6:lengthi12705057e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis29:Python - Tidying up Dataframe33:Python - Tidying up Dataframe.mp4eed6:lengthi2445455e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis15:RFM - Game Plan19:RFM - Game Plan.mp4eed6:lengthi8442108e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis9:RFM Model13:RFM Model.mp4eed6:lengthi4996598e4:pathl58:12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis24:Value Based Segmentation28:Value Based Segmentation.mp4eed6:lengthi6124094e4:pathl32:13 Section 10 - Gaussian Mixture11:AIC and BIC15:AIC and BIC.mp4eed6:lengthi2770247e4:pathl32:13 Section 10 - Gaussian Mixture39:CASE STUDY - Credit Cards #1 (Briefing)43:CASE STUDY - Credit Cards #1 (Briefing).mp4eed6:lengthi38636305e4:pathl32:13 Section 10 - Gaussian Mixture24:CHALLENGE - Introduction28:CHALLENGE - Introduction.mp4eed6:lengthi226925621e4:pathl32:13 Section 10 - Gaussian Mixture21:CHALLENGE - Solutions25:CHALLENGE - Solutions.mp4eed6:lengthi4873883e4:pathl32:13 Section 10 - Gaussian Mixture10:Clustering14:Clustering.mp4eed6:lengthi2890868e4:pathl32:13 Section 10 - Gaussian Mixture28:Gaussian Mixture - Game Plan32:Gaussian Mixture - Game Plan.mp4eed6:lengthi8375997e4:pathl32:13 Section 10 - Gaussian Mixture22:Gaussian Mixture Model26:Gaussian Mixture Model.mp4eed6:lengthi7573429e4:pathl32:13 Section 10 - Gaussian Mixture31:My Experience with Segmentation35:My Experience with Segmentation.mp4eed6:lengthi13475578e4:pathl32:13 Section 10 - Gaussian Mixture42:Python - Cluster Prediction and Assignment46:Python - Cluster Prediction and Assignment.mp4eed6:lengthi15537159e4:pathl32:13 Section 10 - Gaussian Mixture27:Python - Directory and Data31:Python - Directory and Data.mp4eed6:lengthi9569983e4:pathl32:13 Section 10 - Gaussian Mixture31:Python - Gaussian Mixture Model35:Python - Gaussian Mixture Model.mp4eed6:lengthi109031995e4:pathl32:13 Section 10 - Gaussian Mixture23:Python - Interpretation27:Python - Interpretation.mp4eed6:lengthi21408749e4:pathl32:13 Section 10 - Gaussian Mixture18:Python - Load Data22:Python - Load Data.mp4eed6:lengthi30704279e4:pathl32:13 Section 10 - Gaussian Mixture35:Python - Optimal Number of Clusters39:Python - Optimal Number of Clusters.mp4eed6:lengthi14880256e4:pathl32:13 Section 10 - Gaussian Mixture38:Python - Transform Character variables42:Python - Transform Character variables.mp4eed6:lengthi190563e4:pathl31:14 PART D_ PREDICTIVE ANALYTICS60:What are Predictive Analytics and why are they important.pdfeed6:lengthi1242054e4:pathl29:15 Section 11 - Random Forest39:CASE STUDY - Credit Cards #2 (Briefing)43:CASE STUDY - Credit Cards #2 (Briefing).mp4eed6:lengthi35748230e4:pathl29:15 Section 11 - Random Forest24:CHALLENGE - Introduction28:CHALLENGE - Introduction.mp4eed6:lengthi57124307e4:pathl29:15 Section 11 - Random Forest30:CHALLENGE - Solutions (Part 1)34:CHALLENGE - Solutions (Part 1).mp4eed6:lengthi51368670e4:pathl29:15 Section 11 - Random Forest30:CHALLENGE - Solutions (Part 2)34:CHALLENGE - Solutions (Part 2).mp4eed6:lengthi4557303e4:pathl29:15 Section 11 - Random Forest35:Ensemble Learning and Random Forest39:Ensemble Learning and Random Forest.mp4eed6:lengthi9506566e4:pathl29:15 Section 11 - Random Forest23:How Decision Trees Work27:How Decision Trees Work.mp4eed6:lengthi6223614e4:pathl29:15 Section 11 - Random Forest16:Parameter Tuning20:Parameter Tuning.mp4eed6:lengthi26152403e4:pathl29:15 Section 11 - Random Forest43:Python - Classification Report and F1 score47:Python - Classification Report and F1 score.mp4eed6:lengthi10320229e4:pathl29:15 Section 11 - Random Forest32:Python - Directory and Libraries36:Python - Directory and Libraries.mp4eed6:lengthi20462665e4:pathl29:15 Section 11 - Random Forest27:Python - Feature Importance31:Python - Feature Importance.mp4eed6:lengthi15869769e4:pathl29:15 Section 11 - Random Forest24:Python - Isolate X and Y28:Python - Isolate X and Y.mp4eed6:lengthi19392902e4:pathl29:15 Section 11 - Random Forest21:Python - Loading Data25:Python - Loading Data.mp4eed6:lengthi16467543e4:pathl29:15 Section 11 - Random Forest23:Python - Parameter Grid27:Python - Parameter Grid.mp4eed6:lengthi45878134e4:pathl29:15 Section 11 - Random Forest25:Python - Parameter Tuning29:Python - Parameter Tuning.mp4eed6:lengthi5110337e4:pathl29:15 Section 11 - Random Forest20:Python - Predictions24:Python - Predictions.mp4eed6:lengthi12303199e4:pathl29:15 Section 11 - Random Forest28:Python - Random Forest Model32:Python - Random Forest Model.mp4eed6:lengthi21925739e4:pathl29:15 Section 11 - Random Forest27:Python - Summary Statistics31:Python - Summary Statistics.mp4eed6:lengthi28771874e4:pathl29:15 Section 11 - Random Forest30:Python - Training and Test Set34:Python - Training and Test Set.mp4eed6:lengthi10417359e4:pathl29:15 Section 11 - Random Forest50:Python - Transform Object into Numerical Variables54:Python - Transform Object into Numerical Variables.mp4eed6:lengthi3093656e4:pathl29:15 Section 11 - Random Forest25:Random Forest - Game Plan29:Random Forest - Game Plan.mp4eed6:lengthi3953333e4:pathl29:15 Section 11 - Random Forest20:Random Forest Quirks24:Random Forest Quirks.mp4eed6:lengthi6369428e4:pathl32:16 Section 12 - Facebook Prophet53:Additive vs [TutFlix.ORG]. Multiplicative Seasonality43:Additive vs. Multiplicative Seasonality.mp4eed6:lengthi2539259e4:pathl32:16 Section 12 - Facebook Prophet47:CASE STUDY - Wikipedia (Briefing) [TutFlix.ORG]37:CASE STUDY - Wikipedia (Briefing).mp4eed6:lengthi20968751e4:pathl32:16 Section 12 - Facebook Prophet38:CHALLENGE - Introduction [TutFlix.ORG]28:CHALLENGE - Introduction.mp4eed6:lengthi59428498e4:pathl32:16 Section 12 - Facebook Prophet44:CHALLENGE - Solutions (Part 1) [TutFlix.ORG]34:CHALLENGE - Solutions (Part 1).mp4eed6:lengthi97099251e4:pathl32:16 Section 12 - Facebook Prophet44:CHALLENGE - Solutions (Part 2) [TutFlix.ORG]34:CHALLENGE - Solutions (Part 2).mp4eed6:lengthi66829622e4:pathl32:16 Section 12 - Facebook Prophet44:CHALLENGE - Solutions (Part 3) [TutFlix.ORG]34:CHALLENGE - Solutions (Part 3).mp4eed6:lengthi2853819e4:pathl32:16 Section 12 - Facebook Prophet30:Cross-validation [TutFlix.ORG]20:Cross-validation.mp4eed6:lengthi5157438e4:pathl32:16 Section 12 - Facebook Prophet30:Dynamic Holidays [TutFlix.ORG]20:Dynamic Holidays.mp4eed6:lengthi3394398e4:pathl32:16 Section 12 - Facebook Prophet42:Facebook Prophet - Game Plan [TutFlix.ORG]32:Facebook Prophet - Game Plan.mp4eed6:lengthi37547161e4:pathl32:16 Section 12 - Facebook Prophet36:Facebook Prophet Model [TutFlix.ORG]26:Facebook Prophet Model.mp4eed6:lengthi5494361e4:pathl32:16 Section 12 - Facebook Prophet41:Facebook Prophet Parameters [TutFlix.ORG]31:Facebook Prophet Parameters.mp4eed6:lengthi7886749e4:pathl32:16 Section 12 - Facebook Prophet30:Facebook Prophet [TutFlix.ORG]20:Facebook Prophet.mp4eed6:lengthi9477547e4:pathl32:16 Section 12 - Facebook Prophet33:Forecasting at Uber [TutFlix.ORG]23:Forecasting at Uber.mp4eed6:lengthi3406983e4:pathl32:16 Section 12 - Facebook Prophet32:Parameters to tune [TutFlix.ORG]22:Parameters to tune.mp4eed6:lengthi20483444e4:pathl32:16 Section 12 - Facebook Prophet42:Python - Accuracy Assessment [TutFlix.ORG]32:Python - Accuracy Assessment.mp4eed6:lengthi15229887e4:pathl32:16 Section 12 - Facebook Prophet35:Python - Black Friday [TutFlix.ORG]25:Python - Black Friday.mp4eed6:lengthi15746516e4:pathl32:16 Section 12 - Facebook Prophet63:Python - Combining Events and Preparing Dataframe [TutFlix.ORG]53:Python - Combining Events and Preparing Dataframe.mp4eed6:lengthi51108928e4:pathl32:16 Section 12 - Facebook Prophet39:Python - Cross-validation [TutFlix.ORG]29:Python - Cross-validation.mp4eed6:lengthi14124390e4:pathl32:16 Section 12 - Facebook Prophet46:Python - Directory and Libraries [TutFlix.ORG]36:Python - Directory and Libraries.mp4eed6:lengthi23995731e4:pathl32:16 Section 12 - Facebook Prophet38:Python - Easter Holidays [TutFlix.ORG]28:Python - Easter Holidays.mp4eed6:lengthi22329809e4:pathl32:16 Section 12 - Facebook Prophet34:Python - Forecasting [TutFlix.ORG]24:Python - Forecasting.mp4eed6:lengthi34023689e4:pathl32:16 Section 12 - Facebook Prophet39:Python - Future Dataframe [TutFlix.ORG]29:Python - Future Dataframe.mp4eed6:lengthi11761033e4:pathl32:16 Section 12 - Facebook Prophet35:Python - Loading Data [TutFlix.ORG]25:Python - Loading Data.mp4eed6:lengthi23758437e4:pathl32:16 Section 12 - Facebook Prophet37:Python - Parameter Grid [TutFlix.ORG]27:Python - Parameter Grid.mp4eed6:lengthi49388489e4:pathl32:16 Section 12 - Facebook Prophet39:Python - Parameter Tuning [TutFlix.ORG]29:Python - Parameter Tuning.mp4eed6:lengthi8140382e4:pathl32:16 Section 12 - Facebook Prophet45:Python - Regressor Coefficients [TutFlix.ORG]35:Python - Regressor Coefficients.mp4eed6:lengthi9572818e4:pathl32:16 Section 12 - Facebook Prophet41:Python - Renaming Variables [TutFlix.ORG]31:Python - Renaming Variables.mp4eed6:lengthi11436007e4:pathl32:16 Section 12 - Facebook Prophet44:Python - Training and Test Set [TutFlix.ORG]34:Python - Training and Test Set.mp4eed6:lengthi18366596e4:pathl32:16 Section 12 - Facebook Prophet49:Python - Transforming Date Variable [TutFlix.ORG]39:Python - Transforming Date Variable.mp4eed6:lengthi32135028e4:pathl32:16 Section 12 - Facebook Prophet36:Python - Visualization [TutFlix.ORG]26:Python - Visualization.mp4eed6:lengthi7179338e4:pathl32:16 Section 12 - Facebook Prophet36:Structural Time Series [TutFlix.ORG]26:Structural Time Series.mp4eed6:lengthi4867835e4:pathl32:16 Section 12 - Facebook Prophet35:Training and Test Set [TutFlix.ORG]25:Training and Test Set.mp4eed6:lengthi93300826e4:pathl24:17 Where To Go From Here10:Thank You!14:Thank You!.mp4eed6:lengthi173666e4:pathl20:2 PART A_ STATISTICS50:What are Statistics and why are they important.pdfeed6:lengthi7274619e4:pathl30:3 Section 2 - Basic Statistics15:Arithmetic Mean19:Arithmetic Mean.mp4eed6:lengthi2792249e4:pathl30:3 Section 2 - Basic Statistics28:Basic Statistics - Game Plan32:Basic Statistics - Game Plan.mp4eed6:lengthi1481222e4:pathl30:3 Section 2 - Basic Statistics33:CASE STUDY - Moneyball (Briefing)37:CASE STUDY - Moneyball (Briefing).mp4eed6:lengthi7913853e4:pathl30:3 Section 2 - Basic Statistics22:CASE STUDY - Moneyball26:CASE STUDY - Moneyball.mp4eed6:lengthi16713910e4:pathl30:3 Section 2 - Basic Statistics11:Correlation15:Correlation.mp4eed6:lengthi15742734e4:pathl30:3 Section 2 - Basic Statistics31:EXERCISE - Python - Correlation35:EXERCISE - Python - Correlation.mp4eed6:lengthi12216937e4:pathl30:3 Section 2 - Basic Statistics24:EXERCISE - Python - Mean28:EXERCISE - Python - Mean.mp4eed6:lengthi13304214e4:pathl30:3 Section 2 - Basic Statistics26:EXERCISE - Python - Median30:EXERCISE - Python - Median.mp4eed6:lengthi12480596e4:pathl30:3 Section 2 - Basic Statistics24:EXERCISE - Python - Mode28:EXERCISE - Python - Mode.mp4eed6:lengthi4379996e4:pathl30:3 Section 2 - Basic Statistics38:EXERCISE - Python - Standard Deviation42:EXERCISE - Python - Standard Deviation.mp4eed6:lengthi4891323e4:pathl30:3 Section 2 - Basic Statistics15:Median and Mode19:Median and Mode.mp4eed6:lengthi37967556e4:pathl30:3 Section 2 - Basic Statistics20:Python - Correlation24:Python - Correlation.mp4eed6:lengthi41824359e4:pathl30:3 Section 2 - Basic Statistics38:Python - Directory, Libraries and Data42:Python - Directory, Libraries and Data.mp4eed6:lengthi40774555e4:pathl30:3 Section 2 - Basic Statistics13:Python - Mean17:Python - Mean.mp4eed6:lengthi18264121e4:pathl30:3 Section 2 - Basic Statistics15:Python - Median19:Python - Median.mp4eed6:lengthi16325784e4:pathl30:3 Section 2 - Basic Statistics13:Python - Mode17:Python - Mode.mp4eed6:lengthi19489792e4:pathl30:3 Section 2 - Basic Statistics27:Python - Standard Deviation31:Python - Standard Deviation.mp4eed6:lengthi4460861e4:pathl30:3 Section 2 - Basic Statistics18:Standard Deviation22:Standard Deviation.mp4eed6:lengthi2397679e4:pathl37:4 Section 3 - Intermediary Statistics47:CASE STUDY - Remote Work Predictions (Briefing)51:CASE STUDY - Remote Work Predictions (Briefing).mp4eed6:lengthi5629642e4:pathl37:4 Section 3 - Intermediary Statistics36:CASE STUDY - Wine Quality (Briefing)40:CASE STUDY - Wine Quality (Briefing).mp4eed6:lengthi6227763e4:pathl37:4 Section 3 - Intermediary Statistics15:Chi-square test19:Chi-square test.mp4eed6:lengthi37837826e4:pathl37:4 Section 3 - Intermediary Statistics19:Confidence Interval23:Confidence Interval.mp4eed6:lengthi18378182e4:pathl37:4 Section 3 - Intermediary Statistics30:EXERCISE - Python - Chi-square34:EXERCISE - Python - Chi-square.mp4eed6:lengthi14633688e4:pathl37:4 Section 3 - Intermediary Statistics39:EXERCISE - Python - Confidence Interval43:EXERCISE - Python - Confidence Interval.mp4eed6:lengthi28291411e4:pathl37:4 Section 3 - Intermediary Statistics39:EXERCISE - Python - Normal Distribution43:EXERCISE - Python - Normal Distribution.mp4eed6:lengthi10672151e4:pathl37:4 Section 3 - Intermediary Statistics33:EXERCISE - Python - Shapiro-Wilks37:EXERCISE - Python - Shapiro-Wilks.mp4eed6:lengthi11074283e4:pathl37:4 Section 3 - Intermediary Statistics34:EXERCISE - Python - Standard Error38:EXERCISE - Python - Standard Error.mp4eed6:lengthi23958720e4:pathl37:4 Section 3 - Intermediary Statistics26:EXERCISE - Python - T-test30:EXERCISE - Python - T-test.mp4eed6:lengthi2036305e4:pathl37:4 Section 3 - Intermediary Statistics35:Intermediary Statistics - Game Plan39:Intermediary Statistics - Game Plan.mp4eed6:lengthi7502883e4:pathl37:4 Section 3 - Intermediary Statistics19:Normal Distribution23:Normal Distribution.mp4eed6:lengthi15185858e4:pathl37:4 Section 3 - Intermediary Statistics7:P-Value11:P-Value.mp4eed6:lengthi11077039e4:pathl37:4 Section 3 - Intermediary Statistics25:Powerposing and p-hacking29:Powerposing and p-hacking.mp4eed6:lengthi49360952e4:pathl37:4 Section 3 - Intermediary Statistics24:Python - Chi-square test28:Python - Chi-square test.mp4eed6:lengthi42431772e4:pathl37:4 Section 3 - Intermediary Statistics28:Python - Confidence Interval32:Python - Confidence Interval.mp4eed6:lengthi38638292e4:pathl37:4 Section 3 - Intermediary Statistics42:Python - Normal Distribution Visualization46:Python - Normal Distribution Visualization.mp4eed6:lengthi21273869e4:pathl37:4 Section 3 - Intermediary Statistics42:Python - Preparing Script and Loading Data46:Python - Preparing Script and Loading Data.mp4eed6:lengthi43860860e4:pathl37:4 Section 3 - Intermediary Statistics27:Python - Shapiro-Wilks Test31:Python - Shapiro-Wilks Test.mp4eed6:lengthi27144730e4:pathl37:4 Section 3 - Intermediary Statistics23:Python - Standard Error27:Python - Standard Error.mp4eed6:lengthi59546256e4:pathl37:4 Section 3 - Intermediary Statistics15:Python - T-test19:Python - T-test.mp4eed6:lengthi4801270e4:pathl37:4 Section 3 - Intermediary Statistics18:Shapiro-Wilks Test22:Shapiro-Wilks Test.mp4eed6:lengthi6155206e4:pathl37:4 Section 3 - Intermediary Statistics26:Standard Error of the Mean30:Standard Error of the Mean.mp4eed6:lengthi5553947e4:pathl37:4 Section 3 - Intermediary Statistics6:T-test10:T-test.mp4eed6:lengthi6080555e4:pathl37:4 Section 3 - Intermediary Statistics7:Z-Score11:Z-Score.mp4eed6:lengthi2910665e4:pathl31:5 Section 4 - Linear Regression32:CASE STUDY - Diamonds (Briefing)36:CASE STUDY - Diamonds (Briefing).mp4eed6:lengthi7767761e4:pathl31:5 Section 4 - Linear Regression19:Dummy Variable Trap23:Dummy Variable Trap.mp4eed6:lengthi26519067e4:pathl31:5 Section 4 - Linear Regression37:EXERCISE - Python - Linear Regression41:EXERCISE - Python - Linear Regression.mp4eed6:lengthi3128297e4:pathl31:5 Section 4 - Linear Regression29:Linear Regression - Game Plan33:Linear Regression - Game Plan.mp4eed6:lengthi35926298e4:pathl31:5 Section 4 - 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Google Causal Impact (Econometrics and Causal Inference)30:Python - Bitcoin Price loading34:Python - Bitcoin Price loading.mp4eed6:lengthi18735988e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)20:Python - Correlation24:Python - Correlation.mp4eed6:lengthi9011894e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)23:Python - Defining Dates27:Python - Defining Dates.mp4eed6:lengthi9397168e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)35:Python - Google Causal Impact Setup39:Python - Google Causal Impact Setup.mp4eed6:lengthi40189309e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)29:Python - Google Causal Impact33:Python - Google Causal Impact.mp4eed6:lengthi35874997e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)23:Python - Impact Results27:Python - Impact Results.mp4eed6:lengthi12457818e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)43:Python - Installing and Importing Libraries47:Python - Installing and Importing Libraries.mp4eed6:lengthi21573902e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)28:Python - Load Control Groups32:Python - Load Control Groups.mp4eed6:lengthi48190529e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)28:Python - Preparing DataFrame32:Python - Preparing DataFrame.mp4eed6:lengthi16391320e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)41:Python - Preparing for Correlation Matrix45:Python - Preparing for Correlation Matrix.mp4eed6:lengthi48664273e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)21:Python - Stationarity25:Python - Stationarity.mp4eed6:lengthi3055158e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)16:Time Series Data20:Time Series Data.mp4eed6:lengthi11705815e4:pathl70:9 Section 7 - Google Causal Impact (Econometrics and Causal Inference)37:Why Econometrics and Causal Inference41:Why Econometrics and Causal Inference.mp4eee4:name88:[FreeCoursesOnline.Me] ZeroToMastery - 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