Time Series Analysis and Forecasting with MS Excel

Focused View

EDUCBA Bridging the Gap

2:43:19

32 View

1. Introduction

1. Introduction to Project.mp4

03:31

2. Forecasting with Excel.mp4

03:00

2. Scenario

1. 21st Century in Low Emission Scenario.mp4

06:53

2. 21st Century in Low Emission Scenario Continue.mp4

04:37

3. 21st Century in Medium Emission Scenario.mp4

05:00

4. 21st Century in Medium Emission Scenario Continue.mp4

03:30

5. 21st Century in High Emission Scenario.mp4

04:03

6. 21st Century in High Emission Scenario Continue.mp4

03:51

3. Weighted Average

1. Calculating Annual Minimum Temperature Average LES.mp4

00:46

2. Weighted Average Maximum Temperature LES.mp4

04:11

3. Weighted Average Minimum Temperature.mp4

02:54

4. Weighted Average Temperature 2A and 2B.mp4

02:38

5. Weighted Average Max Temperature MES.mp4

05:06

6. Weighted Average Minimum Temperature HES.mp4

05:20

7. Weighted Average Max Temperature HES.mp4

05:01

4. Exponential Moving Average Analysis

1. Exponential Average Minimum Temperature Best Scenario.mp4

06:36

2. Exponential Average Maximum Temperature Best Scenario Continue.mp4

05:12

3. Exponential Average Minimum Temperature Normal Scenario.mp4

04:17

4. Exponential Average Maximum Temperature Normal Scenario Continue.mp4

04:40

5. Exponential Average Minimum Temperature Worst Scenario.mp4

05:21

6. Exponential Average Maximum Temperature Worst Scenario Continue.mp4

05:50

5. Regression

1. Correlated MES Min and Max Temperature.mp4

13:00

2. Correlated HES Min and Max Temperature.mp4

12:49

3. Simple Regression LES and HES Max Temperature.mp4

10:36

4. Simple Regression MES and Max Temperature.mp4

10:53

5. Simple Regression HES and Max Temperature.mp4

09:58

6. Multiple Regression Range Prediction.mp4

13:46

Description

Learn about a comprehensive framework of Time Series Analysis and Forecasting with MS Excel

What You'll Learn?

Learn Weighted Average, Exponential Moving Average Analysis and Regression
Simple Forecasting Methods, Simple and Multiple Regression
Time Series Decomposition and Exponential Smoothing
Methods of Forecasting and Steps in Forecasting

Who is this for?

Students, Quantitative and Econometrics Modellers, Financial markets professionals

What You Need to Know?

Prior knowledge of Mathematics and statistics

More details

Description
Time series analysis is a statistical method to analyse the past data within a given duration of time to forecast the future. It comprises of ordered sequence of data at equally spaced interval. To understand the time series data & the analysis let us consider an example. Consider an example of Airline Passenger data. It has the count of passenger over a period of time.
Ample of time series data is being generated from a variety of fields. And hence the study time series analysis holds a lot of applications. Let us try to understand the importance of time series analysis in different areas.
Field of Economics: Budget studies, census Analysis, etc.
Field of Finance: Widely used in the field of finance such as to understand the stock market fluctuations, yield management, understand the market volatility, etc.
Social ScientistÃ : Birth rates or death rates over a period of time and can come with the schemes in their interest.
Healthcare: An epidemiologist might be interested in knowing the number of people infected over the past years. Like in the current situation the researchers might be interested in knowing the people affected by the coronavirus over a period of time. Blood pressure traced over a period of time can be used in evaluating a drug.
Environmental Science: Environmental time series data can help us explain the rise in temperature over the past few years. Plot shows the temperature data over a period of time
Time series data collected over different points in time breach the assumption of the conventional statistical model as correlation exists between the adjacent data points. This characteristic of the time series data breaches is one of the major assumptions that the adjacent data points are independent and identically distributed. This gives rise to the need of a systematic approach to study the time series data which can help us answer the statistical and mathematical questions that come into the picture due to the time correlation that exists.
Time series analysis holds a wide range of applications is it statistics, economics, geography, bioinformatics, neuroscience. The common link between all of them is to come up with a sophisticated technique that can be used to model data over a given period of time where the neighboring information is dependent.
In time series, Time is the independent variable and the goal is forecasting.
Who this course is for:
Students, Quantitative and Econometrics Modellers, Financial markets professionals

User Reviews

Rating

average 0

Total votes0

Focused display

EDUCBA is a leading global provider of skill based education addressing the needs of 1,000,000+ members across 70+ Countries. Our unique step-by-step, online learning model along with amazing 5000+ courses and 500+ Learning Paths prepared by top-notch professionals from the Industry help participants achieve their goals successfully. All our training programs are Job oriented skill based programs demanded by the Industry. At EDUCBA, it is a matter of pride for us to make job oriented hands-on courses available to anyone, any time and anywhere. Therefore we ensure that you can enroll 24 hours a day, seven days a week, 365 days a year. Learn at a time and place, and pace that is of your choice. Plan your study to suit your convenience and schedule.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.