Understanding and Applying Linear Regression

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Understanding and Applying Linear Regression files 4-understanding-applying-linear-regression-m4-exercise-files __MACOSX
  • ._module_4.R (1.1 KB)
  • module_4.R (2.6 KB)
    • 5-understanding-applying-linear-regression-m5-exercise-files __MACOSX
    • ._module_5_code.py (1.1 KB)
    • module_5_code.py (2.7 KB)
      • 8-understanding-applying-linear-regression-m8-exercise-files __MACOSX
      • ._module_8.R (1.2 KB)
      • module_8.R (5.2 KB)
        • 9-understanding-applying-linear-regression-m9-exercise-files __MACOSX
        • ._module_9_code.py (1.2 KB)
        • module_9_code.py (3.3 KB)
          • 1-understanding-applying-linear-regression-m1-slides.pdf (1.1 MB)
          • 2-understanding-applying-linear-regression-m2-slides.pdf (1,009.1 KB)
          • 3-understanding-applying-linear-regression-m3-slides.pdf (527.1 KB)
          • 4-understanding-applying-linear-regression-m4-slides.pdf (264.5 KB)
          • 5-understanding-applying-linear-regression-m5-slides.pdf (360.0 KB)
          • 6-understanding-applying-linear-regression-m6-slides.pdf (640.4 KB)
          • 7-understanding-applying-linear-regression-m7-slides.pdf (1.0 MB)
          • 8-understanding-applying-linear-regression-m8-slides.pdf (851.8 KB)
          • 9-understanding-applying-linear-regression-m9-slides.pdf (230.5 KB)
            • 01 - Course Overview - Course Overview.mp4 (4.4 MB)
            • 02 - Modeling Relationships Between Variables Using Regression - Connecting the Dots Using Linear Regression.mp4 (9.0 MB)
            • 03 - Modeling Relationships Between Variables Using Regression - Reasons for Using Regression.mp4 (10.9 MB)
            • 04 - Modeling Relationships Between Variables Using Regression - Versatility of Regression.mp4 (3.4 MB)
            • 05 - Modeling Relationships Between Variables Using Regression - Regression as Machine Learning.mp4 (7.7 MB)
            • 06 - Modeling Relationships Between Variables Using Regression - Mean and Variance.mp4 (4.5 MB)
            • 07 - Modeling Relationships Between Variables Using Regression - Probability Distributions and the Bell Curve.mp4 (9.3 MB)
            • 08 - Understanding Simple Regression Models - Setting up the Regression Problem.mp4 (6.2 MB)
            • 09 - Understanding Simple Regression Models - The Best Fit Line.mp4 (5.5 MB)
            • 10 - Understanding Simple Regression Models - A Quick Taste of Regression in Excel.mp4 (11.0 MB)
            • 11 - Understanding Simple Regression Models - Solving the Regression Problem.mp4 (6.5 MB)
            • 12 - Understanding Simple Regression Models - Residuals and the Regression Assumptions.mp4 (7.6 MB)
            • 13 - Understanding Simple Regression Models - Explaining Variance Using Simple Regression.mp4 (6.3 MB)
            • 14 - Understanding Simple Regression Models - R-squared as Variance Explained.mp4 (8.2 MB)
            • 15 - Understanding Simple Regression Models - Prediction Using Simple Regression.mp4 (8.8 MB)
            • 16 - Implementing Simple Regression Models in Excel - Applying Simple Regression.mp4 (9.9 MB)
            • 17 - Implementing Simple Regression Models in Excel - Violations of Regression Assumptions.mp4 (15.7 MB)
            • 18 - Implementing Simple Regression Models in Excel - Fast Prototyping in Excel.mp4 (22.9 MB)
            • 19 - Implementing Simple Regression Models in Excel - Slope, Intercept, and Prediction.mp4 (24.0 MB)
            • 20 - Implementing Simple Regression Models in Excel - Poorly Specified Regression Models.mp4 (17.4 MB)
            • 21 - Implementing Simple Regression Models in R - R for Regression.mp4 (7.7 MB)
            • 22 - Implementing Simple Regression Models in R - Data Frames in R.mp4 (12.2 MB)
            • 23 - Implementing Simple Regression Models in R - Regressing Returns, Not Prices.mp4 (15.9 MB)
            • 24 - Implementing Simple Regression Models in R - Prediction with Regression in R.mp4 (11.4 MB)
            • 25 - Implementing Simple Regression Models in Python - When Python Is the Right Tool for Regression.mp4 (6.2 MB)
            • 26 - Implementing Simple Regression Models in Python - Using Pandas and NumPy.mp4 (10.9 MB)
            • 27 - Implementing Simple Regression Models in Python - Linear Regression as Machine Learning.mp4 (11.2 MB)
            • 28 - Understanding Multiple Regression Models - Introducing Multiple Regression.mp4 (11.2 MB)
            • 29 - Understanding Multiple Regression Models - Risks in Multiple Regression.mp4 (8.3 MB)
            • 30 - Understanding Multiple Regression Models - Detecting Multicollinearity.mp4 (9.2 MB)
            • 31 - Understanding Multiple Regression Models - Multicollinearity - Prevention and Cure.mp4 (8.7 MB)
            • 32 - Understanding Multiple Regression Models - Benefits of Multiple Regression.mp4 (5.7 MB)
            • 33 - Understanding Multiple Regression Models - Interpreting the Results of a Regression Analysis.mp4 (7.7 MB)
            • 34 - Understanding Multiple Regression Models - Categorical Variables.mp4 (10.7 MB)
            • 35 - Implementing Multiple Regression Models in Excel - Introducing Linest in Excel.mp4 (8.9 MB)
            • 36 - Implementing Multiple Regression Models in Excel - Standard Errors.mp4 (12.2 MB)
            • 37 - Implementing Multiple Regression Models in Excel - T-statistics and P-values.mp4 (6.9 MB)
            • 38 - Implementing Multiple Regression Models in Excel - The F-statistic.mp4 (8.3 MB)
            • 39 - Implementing Multiple Regression Models in Excel - Multiple Regression with Linest.mp4 (17.2 MB)
            • 40 - Implementing Multiple Regression Models in Excel - Categorical Variables in Excel.mp4 (21.7 MB)
            • 41 - Implementing Multiple Regression Models in R - Multiple Regression in R.mp4 (18.8 MB)
            • 42 - Implementing Multiple Regression Models in R - Categorical Variables Without an Intercept in R.mp4 (17.3 MB)
            • 43 - Implementing Multiple Regression Models in Python - Multiple Regression in Two Different Ways.mp4 (16.8 MB)
            • 44 - Implementing Multiple Regression Models in Python - Categorical Variables.mp4 (16.7 MB)

Description

Understanding and Applying Linear Regression



Details:



Understanding and Applying Linear Regression
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 4 Hours 12M | 484 MB
Genre: eLearning | Language: English


Linear regression is a powerful tool, applicable in many common situations in business and data analysis. This course will cover both the theory and implementation of linear regression in Excel, Python, and R.

Linear regression is a key technique used in forecasting and in quantifying cause-effect relationships. In this course, , you will learn how to identify patterns in data and test those relationships for statistical soundness. You will also learn simple regression and multiple regression. Finally, you'll explore the use of categorical variables. When you're finished with this course, you will have a strong applied knowledge of regression in Excel, R, and Python that will help with factor analysis, logistic regression, and other powerful techniques.

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Understanding and Applying Linear Regression

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487 MB
seeders:3
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Understanding and Applying Linear Regression

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