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Lynda - Excel Data Analysis Forecasting

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视频 2017-3-26 07:00 2024-6-25 03:05 124 808.66 MB 54
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文件列表
  1. 00 Introduction/0001 Welcome.mp44.26MB
  2. 00 Introduction/0002 Who is this course for.mp42.75MB
  3. 00 Introduction/0003 What you should know before watching this course.mp43.15MB
  4. 00 Introduction/0004 Using the exercise files.mp43.37MB
  5. 00 Introduction/0005 Using the challenges.mp42.49MB
  6. 01 Visually Displaying Your Time-Series Data/0101 What is time-series data.mp45.6MB
  7. 01 Visually Displaying Your Time-Series Data/0102 Plotting a time series.mp47.83MB
  8. 01 Visually Displaying Your Time-Series Data/0103 Understanding level in a time series.mp411.15MB
  9. 01 Visually Displaying Your Time-Series Data/0104 Understanding trend in a time series.mp46.6MB
  10. 01 Visually Displaying Your Time-Series Data/0105 Understanding seasonality in a time series.mp412.01MB
  11. 01 Visually Displaying Your Time-Series Data/0106 Understanding noise in a time series.mp47.39MB
  12. 01 Visually Displaying Your Time-Series Data/0107 Creating a moving average chart.mp414.27MB
  13. 01 Visually Displaying Your Time-Series Data/0108 Challenge Analyze time-series data for airline miles.mp41.4MB
  14. 01 Visually Displaying Your Time-Series Data/0109 Solution Analyze time-series data for airline miles.mp46.4MB
  15. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0201 Exploring why some forecasts are better than others.mp420.97MB
  16. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0202 Computing the mean absolute deviation (MAD).mp418.17MB
  17. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0203 Computing the mean absolute percentage error (MAPE).mp425.7MB
  18. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0204 Calculating the sum of squared errors (SSE).mp412.46MB
  19. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0205 Computing forecast bias.mp415.85MB
  20. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0206 Advanced forecast bias Determining significance.mp417.83MB
  21. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0207 Challenge Compute MAD, MAPE, and SSE for an NFL game.mp41.72MB
  22. 02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0208 Solution Compute MAD, MAPE, and SSE for an NFL game.mp412.29MB
  23. 03 Using a Trendline for Forecasting/0301 Fitting a linear trend curve.mp414.07MB
  24. 03 Using a Trendline for Forecasting/0302 Interpreting the trendline.mp48.72MB
  25. 03 Using a Trendline for Forecasting/0303 Interpreting the R-squared value.mp422.05MB
  26. 03 Using a Trendline for Forecasting/0304 Computing standard error of the regression and outliers.mp429.92MB
  27. 03 Using a Trendline for Forecasting/0305 Exploring autocorrelation.mp431.92MB
  28. 03 Using a Trendline for Forecasting/0306 Challenge Create a trendline to analyze R squared and outliers.mp41.64MB
  29. 03 Using a Trendline for Forecasting/0307 Solution Create a trendline to analyze R squared and outliers.mp413.73MB
  30. 04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0401 When does a linear trend fail.mp425.37MB
  31. 04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0402 Creating an exponential trend curve.mp426.34MB
  32. 04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0403 Computing compound annual growth rate (CAGR).mp413.03MB
  33. 04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0404 Challenge Fit an exponential growth curve, estimate CAGR, and forecast revenue.mp41.75MB
  34. 04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0405 Solution Fit an exponential growth curve, estimate CAGR, and forecast revenue.mp46.3MB
  35. 05 Seasonality and the Ratio-to-Moving-Average Method/0501 What is a seasonal index.mp420.94MB
  36. 05 Seasonality and the Ratio-to-Moving-Average Method/0502 Introducing the ratio-to-moving-average method.mp48.11MB
  37. 05 Seasonality and the Ratio-to-Moving-Average Method/0503 Computing the centered moving average.mp419.15MB
  38. 05 Seasonality and the Ratio-to-Moving-Average Method/0504 Calculating seasonal indices.mp420.19MB
  39. 05 Seasonality and the Ratio-to-Moving-Average Method/0505 Estimating a series trend.mp49.7MB
  40. 05 Seasonality and the Ratio-to-Moving-Average Method/0506 Forecasting sales.mp423.49MB
  41. 05 Seasonality and the Ratio-to-Moving-Average Method/0507 Forecasting if the series trend is changing.mp414.65MB
  42. 05 Seasonality and the Ratio-to-Moving-Average Method/0508 Challenge Predicting future quarterly sales.mp41.58MB
  43. 05 Seasonality and the Ratio-to-Moving-Average Method/0509 Solution Predicting future quarterly sales.mp47.75MB
  44. 06 Forecasting with Multiple Regressions/0601 What is multiple regression.mp428.46MB
  45. 06 Forecasting with Multiple Regressions/0602 Preparing data for multiple regression.mp442.04MB
  46. 06 Forecasting with Multiple Regressions/0603 Running a multiple linear regression.mp411.78MB
  47. 06 Forecasting with Multiple Regressions/0604 Finding the multiple-regression equation and testing for significance.mp442.79MB
  48. 06 Forecasting with Multiple Regressions/0605 How good is the fit of the trendline.mp426.31MB
  49. 06 Forecasting with Multiple Regressions/0606 Making forecasts from a multiple-regression equation.mp420.74MB
  50. 06 Forecasting with Multiple Regressions/0607 Validating a multiple-regression equation using the TREND function.mp444.01MB
  51. 06 Forecasting with Multiple Regressions/0608 Interpreting regression coefficients.mp420.51MB
  52. 06 Forecasting with Multiple Regressions/0609 Challenge Regression analysis of Amazon.com revenue.mp43.11MB
  53. 06 Forecasting with Multiple Regressions/0610 Solution Regression analysis of Amazon.com revenue.mp422.55MB
  54. 07 Conclusion/0701 Next steps.mp412.28MB
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