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Introduction to Time Series · LearnSpace
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Introduction to Time Series

Курс от Illinois Tech
Средний≈ 51.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course introduces basic time series analysis and forecasting methods. Topics include stationary processes, ARMA models, modeling and forecasting using ARMA models, nonstationary and seasonal time series models, state-space models, and forecasting techniques. By the end of this course, students will be able to: - Describe important time series models and their applications in various fields. - Formulate real life problems using time series models. - Use statistical software to estimate models from real data and draw conclusions and develop solutions from the estimated models. - Use visual and numerical diagnostics to assess the soundness of their models. - Communicate the statistical analyses of substantial data sets through explanatory text, tables, and graphs. - Combine and adapt different statistical models to analyze larger and more complex data.

Навыки, которые вы освоите

Time Series Analysis and ForecastingR ProgrammingForecastingStatistical ModelingModel EvaluationStatistical Hypothesis TestingPredictive ModelingData AnalysisStatistical ReportingData TransformationStatistical MethodsStatistical AnalysisStatistical VisualizationProbability & StatisticsStatistical SoftwareData PresentationCorrelation AnalysisNumerical AnalysisR (Software)

Программа курса

9 модулей · 127 учебных материалов

01Module 1: Course Introduction and Intuition for Stationarity18 материалов

Course Welcome

Course OverviewВидеоInstructor IntroductionВидеоSyllabusЧтениеMeet and Greet DiscussionОбсуждение

Учитесь у экспертов

Trevor Leslie

Assistant Professor of Applied Mathematics

Introduction to Time Series
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Обучение на Coursera

≈ 51.6 ч

9 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский, Казахский, Венгерский

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Module 1 Introduction

Module 1 IntroductionВидео

Lesson 1: Time Series: What Are Time Series, and How Are They Used?

What Are Time Series?ЧтениеWhat are Time Series, and How are They Used? ВидеоWhat Are Time Series, and How Are They Used QuizЗадание

Lesson 2: Getting started with R

Intro to RЧтениеGetting Started with RВидеоGetting Started with R QuizЗадание

Lesson 3: A Gentle Introduction to Stationarity

StationarityЧтениеA Gentle Introduction to Stationarity - Part 1ВидеоA Gentle Introduction to Stationarity - Part 2ВидеоA Gentle Introduction to Stationarity - Part 3ВидеоA Gentle Introduction to Stationarity QuizЗадание

Module 1 Summative Assessment

Module 1 Summative AssessmentЗадание

Module 1 Summary

Module 1 SummaryЧтение
02Module 2: Basic Analysis of Stationary Processes15 материалов

Module 2 Introduction

Module 2 IntroductionВидео

Lesson 1: Weak and Strong Stationarity

Weak and Strong StationarityЧтениеWeak and Strong Stationarity - Part 1ВидеоWeak and Strong Stationarity - Part 2ВидеоWeak and Strong Stationarity - Part 3ВидеоWeak and Strong Stationarity - Part 4ВидеоWeak and Strong Stationarity QuizЗадание

Lesson 2: Introduction to Linear Processes

Linear ProcessesЧтениеIntroduction to Linear Processes - Part 1ВидеоIntroduction to Linear Processes - Part 2ВидеоIntroduction to Linear Processes - Part 3ВидеоIntroduction to Linear Processes - Part 4ВидеоIntroduction to Linear Processes QuizЗадание

Module 2 Summative Assessment

Module 2 Summative AssessmentЗадание

Module 2 Summary

Module 2 SummaryЧтение
03Module 3: ARMA processes and their Autocorrelation Functions17 материалов

Module 3 Introduction

Module 3 IntroductionВидео

Lesson 1: Understanding ARMA(p,q) processes

Understanding ARMA processesЧтениеUnderstanding ARMA (p, q) Processes - Part 1ВидеоUnderstanding ARMA (p, q) Processes - Part 2ВидеоUnderstanding ARMA (p, q) Processes - Part 3ВидеоUnderstanding ARMA (p, q) Processes - Part 4ВидеоUnderstanding ARMA(p,q) Processes QuizЗадание

Lesson 2: The Partial Autocorrelation Function (PACF)

Computing ACF's Using Difference EquationsЧтениеComputing ACF's of AR (2) Processes Using Difference Equations - Part 1ВидеоComputing ACF's of AR (2) Processes Using Difference Equations - Part 2ВидеоComputing ACF's of AR (2) Processes Using Difference Equations - Part 3ВидеоComputing ACF's of AR (2) Processes Using Difference Equations - Part 4ВидеоComputing ACF's of AR (2) Processes Using Difference Equations - Part 5Видео

Module 3 Summative Assessment

Module 3 Summative AssessmentЗадание

Module 3 Summary

Module 3 SummaryЧтениеInsights from an Industry Leader: Learn More About Our ProgramЧтение
04Module 4: More About the ACF; Best Linear Predictors, Autocorrelation, and Partial Autocorrelation16 материалов

Module 4 Introduction

Module 4 IntroductionВидео

Lesson 1: ACF’s and Difference Equations, continued

ACF's and difference equations, continuedЧтениеACF's and Difference Equations - Part 1ВидеоACF's and Difference Equations - Part 2ВидеоACF's and Difference Equations - Part 3ВидеоACF's and Difference Equations - Part 3 (Cont.)ВидеоACF’s and Difference Equations, continued QuizЗадание

Lesson 2: Best Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation

Best Linear Predictor of a Stationary Process: Principles of Forecasting and the Partial Autocorrelation FunctionЧтениеBest Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 1ВидеоBest Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 2ВидеоBest Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 2 (Cont.)ВидеоBest Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 3ВидеоBest Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation Function - Part 4

Module 4 Summative Assessment

Module 4 Summative AssessmentЗадание

Module 4 Summary

Module 4 SummaryЧтение
05Module 5: Fitting Data to ARMA models17 материалов

Module 5 Introduction

Module 5 IntroductionВидео

Lesson 1: The Sample ACF and Sample PACF

The sample ACF and sample PACFЧтениеThe Sample ACF and Sample PACF - Part 1ВидеоThe Sample ACF and Sample PACF - Part 2ВидеоThe Sample ACF and Sample PACF QuizЗадание

Lesson 2: Preliminary Estimation and the Yule-Walker equations

Preliminary estimation and the Yule-Walker equationsЧтениеPreliminary Estimation and the Yule-Walker Equations - Part 1ВидеоPreliminary Estimation and the Yule-Walker Equations - Part 1 (Cont.)ВидеоPreliminary Estimation and the Yule-Walker equations QuizЗадание

Lesson 3: Maximum likelihood estimation for ARMA processes

Maximum likelihood estimators for ARMA processesЧтениеMaximum Likelihood Estimators for ARMA Processes - Part 1ВидеоMaximum Likelihood Estimators for ARMA Processes - Part 2ВидеоMaximum Likelihood Estimators for ARMA Processes - Part 3ВидеоMaximum Likelihood Estimators for ARMA Processes - Part 4ВидеоMaximum likelihood estimation for ARMA processes QuizЗадание

Module 5 Summative Assessment

Module 5 Summative AssessmentЗадание

Module 5 Summary

Module 5 SummaryЧтение
06Module 6: Diagnostics and Order Selection 13 материалов

Module 6 Introduction

Module 6 IntroductionВидео

Lesson 1: Diagnostics

DiagnosticsЧтениеModel Diagnostics - Part 1ВидеоModel Diagnostics - Part 2ВидеоModel Diagnostics - Part 3ВидеоDiagnostics QuizЗадание

Lesson 2: Order Selection and the AICC

Order SelectionЧтениеOrder Selection and the AICC - Part 1ВидеоOrder Selection and the AICC - Part 2ВидеоOrder Selection and the AICC - Part 3Видео

Module 6 Summative Assessment

Order Selection and the AICC QuizЗаданиеModule 6 Summative AssessmentЗадание

Module 6 Summary

Module 6 SummaryЧтение
07Module 7: Nonstationary processes: ARIMA and SARIMA Models15 материалов

Module 7 Introduction

Module 7 IntroductionВидео

Lesson 1: ARIMA Models

ARIMA ModelsЧтениеARIMA Models - Part 1ВидеоARIMA Models - Part 1 (Cont.)ВидеоARIMA Models - Part 2ВидеоARIMA Models - Part 2 (Cont.)ВидеоARIMA Models - Part 3ВидеоARIMA Models - Part 4ВидеоARIMA Models QuizЗадание

Lesson 2: SARIMA Models

SARIMA ModelsЧтениеSARIMA Models - Part 1ВидеоSARIMA Models - Part 2ВидеоSARIMA Models QuizЗадание

Module 7 Summative Assessment

Module 7 Summative AssessmentЗадание

Module 7 Summary

Module 7 SummaryЧтение
08Module 8: More on Forecasting15 материалов

Module 8 Introduction

Module 8 IntroductionВидео

Lesson 1: Beyond One-Step-Ahead Prediction

Beyond One-Step Ahead PredictionsЧтениеBeyond One-Step-Ahead Prediction - Part 1ВидеоBeyond One-Step-Ahead Prediction - Part 1 (Cont.)ВидеоBeyond One-Step-Ahead Prediction - Part 2ВидеоBeyond One-Step-Ahead Prediction - Part 3ВидеоBeyond One-Step-Ahead Prediction - Part 3 (Cont.)ВидеоBeyond One-Step-Ahead Prediction - Part 4ВидеоBeyond One-Step-Ahead Prediction QuizЗадание

Lesson 2: Exponential Smoothing

Exponential Smoothing ModelsЧтениеExponential Smoothing - Part 1ВидеоExponential Smoothing - Part 2ВидеоExponential Smoothing QuizЗадание

Module 8 Summative Assessment

Module 8 Summative AssessmentЗадание

Module 8 Summary

Module 8 SummaryЧтение
09Summative Course Assessment1 материалов

Summative Course Assessment

Course Summative AssessmentЗадание
Computing ACF's of AR(2) Processes Using Difference Equations QuizЗадание
Видео
Best Linear Predictors, Principles of Forecasting, and the Partial Autocorrelation QuizЗадание