This course was created with the
course builder. Create your online course today.
Start now
Create your course
with
Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Making Numerical Predictions for Time Series Data - Part 1/3
Welcome to the Course
Introduction (4:28)
Course Contents (3:23)
Introduction to Time Series Data
A look into Time Series Data (8:12)
Moving Averages Method
Using Descriptive Statistics to Predict Values (13:24)
Predicting using Moving Averages (17:15)
Centered Moving Averages (9:54)
Weighted Moving Averages (12:11)
Calculating Standard Deviation for Prediction made using Moving Averages (4:52)
Predicting for Seasonal Data (7:39)
Linear Regression
Calculating Correlations (12:03)
Linear Regression (10:30)
Linear Regression Demonstration (17:03)
Linear Regression using LINEST() (12:45)
Predicting with TREND() (5:16)
Linear Regression using Data Analysis Toolkit (13:21)
Multi Variate Linear Regression (10:39)
Exponential Regression
Exponential Regression with Linear Model (15:57)
Optimising Exponential Regression using Solver (9:41)
Exponential Regression using LOGEST() (7:08)
Multi-Variate Exponential Regression (14:13)
Power Regression
Power Regression (10:58)
Multi-Variate Power Regression (8:27)
Logarithmic Regression
Logarithmic Regression (12:23)
Non-Linear Regression
Quadratic Regression (4:30)
Polynomial Regression (4:22)
Selecting a Model
Selecting a Model through Experimentation (40:59)
Guidelines for Selecting a Model (5:54)
Bonus Videos
Outliers (12:43)
Degrees of Freedom (4:38)
Normal Distribution (14:46)
Standard Error of Mean (11:15)
Confidence Interval (16:21)
Course Closing
Project Work (3:19)
Next Steps (2:27)
About Me (7:32)
Calculating Correlations
Complete and Continue
Discussion
0
comments
Load more
0 comments