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种子名称： Lynda - Excel Data Analysis Forecasting
文件类型： 视频
文件数目： 54个文件
文件大小： 808.66 MB
收录时间： 2017-3-26 07:00
已经下载： 3次
资源热度： 145
最近下载： 2024-11-4 11:51

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Lynda - Excel Data Analysis Forecasting.torrent

00 Introduction/0001 Welcome.mp44.26MB

00 Introduction/0002 Who is this course for.mp42.75MB

00 Introduction/0003 What you should know before watching this course.mp43.15MB

00 Introduction/0004 Using the exercise files.mp43.37MB

00 Introduction/0005 Using the challenges.mp42.49MB

01 Visually Displaying Your Time-Series Data/0101 What is time-series data.mp45.6MB

01 Visually Displaying Your Time-Series Data/0102 Plotting a time series.mp47.83MB

01 Visually Displaying Your Time-Series Data/0103 Understanding level in a time series.mp411.15MB

01 Visually Displaying Your Time-Series Data/0104 Understanding trend in a time series.mp46.6MB

01 Visually Displaying Your Time-Series Data/0105 Understanding seasonality in a time series.mp412.01MB

01 Visually Displaying Your Time-Series Data/0106 Understanding noise in a time series.mp47.39MB

01 Visually Displaying Your Time-Series Data/0107 Creating a moving average chart.mp414.27MB

01 Visually Displaying Your Time-Series Data/0108 Challenge Analyze time-series data for airline miles.mp41.4MB

01 Visually Displaying Your Time-Series Data/0109 Solution Analyze time-series data for airline miles.mp46.4MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0201 Exploring why some forecasts are better than others.mp420.97MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0202 Computing the mean absolute deviation (MAD).mp418.17MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0203 Computing the mean absolute percentage error (MAPE).mp425.7MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0204 Calculating the sum of squared errors (SSE).mp412.46MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0205 Computing forecast bias.mp415.85MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0206 Advanced forecast bias Determining significance.mp417.83MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0207 Challenge Compute MAD, MAPE, and SSE for an NFL game.mp41.72MB

02 How Good Are Your Forecasts Errors, Accuracy, and Bias/0208 Solution Compute MAD, MAPE, and SSE for an NFL game.mp412.29MB

03 Using a Trendline for Forecasting/0301 Fitting a linear trend curve.mp414.07MB

03 Using a Trendline for Forecasting/0302 Interpreting the trendline.mp48.72MB

03 Using a Trendline for Forecasting/0303 Interpreting the R-squared value.mp422.05MB

03 Using a Trendline for Forecasting/0304 Computing standard error of the regression and outliers.mp429.92MB

03 Using a Trendline for Forecasting/0305 Exploring autocorrelation.mp431.92MB

03 Using a Trendline for Forecasting/0306 Challenge Create a trendline to analyze R squared and outliers.mp41.64MB

03 Using a Trendline for Forecasting/0307 Solution Create a trendline to analyze R squared and outliers.mp413.73MB

04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0401 When does a linear trend fail.mp425.37MB

04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0402 Creating an exponential trend curve.mp426.34MB

04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0403 Computing compound annual growth rate (CAGR).mp413.03MB

04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0404 Challenge Fit an exponential growth curve, estimate CAGR, and forecast revenue.mp41.75MB

04 Modeling Exponential Growth and Compound Annual Growth Rate (CAGR)/0405 Solution Fit an exponential growth curve, estimate CAGR, and forecast revenue.mp46.3MB

05 Seasonality and the Ratio-to-Moving-Average Method/0501 What is a seasonal index.mp420.94MB

05 Seasonality and the Ratio-to-Moving-Average Method/0502 Introducing the ratio-to-moving-average method.mp48.11MB

05 Seasonality and the Ratio-to-Moving-Average Method/0503 Computing the centered moving average.mp419.15MB

05 Seasonality and the Ratio-to-Moving-Average Method/0504 Calculating seasonal indices.mp420.19MB

05 Seasonality and the Ratio-to-Moving-Average Method/0505 Estimating a series trend.mp49.7MB

05 Seasonality and the Ratio-to-Moving-Average Method/0506 Forecasting sales.mp423.49MB

05 Seasonality and the Ratio-to-Moving-Average Method/0507 Forecasting if the series trend is changing.mp414.65MB

05 Seasonality and the Ratio-to-Moving-Average Method/0508 Challenge Predicting future quarterly sales.mp41.58MB

05 Seasonality and the Ratio-to-Moving-Average Method/0509 Solution Predicting future quarterly sales.mp47.75MB

06 Forecasting with Multiple Regressions/0601 What is multiple regression.mp428.46MB

06 Forecasting with Multiple Regressions/0602 Preparing data for multiple regression.mp442.04MB

06 Forecasting with Multiple Regressions/0603 Running a multiple linear regression.mp411.78MB

06 Forecasting with Multiple Regressions/0604 Finding the multiple-regression equation and testing for significance.mp442.79MB

06 Forecasting with Multiple Regressions/0605 How good is the fit of the trendline.mp426.31MB

06 Forecasting with Multiple Regressions/0606 Making forecasts from a multiple-regression equation.mp420.74MB

06 Forecasting with Multiple Regressions/0607 Validating a multiple-regression equation using the TREND function.mp444.01MB

06 Forecasting with Multiple Regressions/0608 Interpreting regression coefficients.mp420.51MB

06 Forecasting with Multiple Regressions/0609 Challenge Regression analysis of Amazon.com revenue.mp43.11MB

06 Forecasting with Multiple Regressions/0610 Solution Regression analysis of Amazon.com revenue.mp422.55MB

07 Conclusion/0701 Next steps.mp412.28MB