Standard Error of Mean | Learn with Partha

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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)

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Standard Error of Mean

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