What is Least Square and Residual Analysis in Data Science?

Least Square Method: The Least Square method is a form of regression analysis that calculates a linear combination of independent variables (X) to minimize the sum squared residuals (S). Residual Analysis: Residual analysis is a statistical technique for finding patterns in data, which can be used to identify outliers and other important features.

What are some examples of applying these methods in data science projects?

There are many ways in which AI can be used to help data science projects: Generating insights: AI can be used to generate insights that might not have been reached by human scientists. Automating tasks: Data science projects often require a lot of repetitive work and the use of AI tools can automate this process. Generating data sets: Data science projects often require a lot of data and the use of AI tools can generate these data sets at scale. Data augmentation: Data science projects often require additional information about the dataset, such as demographics, geographies, etc.,

Course Content

Understanding of Data Science

7m 33s

How to use LearnVern

3m 20s

Introduction to Data Measurement in Data Science

10m 6s

Types of Variables in Data Science

2m 26s

Levels of Data Measurement in Data Science

10m 25s

Data Measurement Quiz

Charts and Graphs in Data Science

4m 2s

Frequency Distribution in Data Science

5m 46s

Bar Graphs and Pie Charts in Data Science

9m 1s

Summarizing Quantitative Data in Data Science

7m 25s

Cummulative Distribution in Data science

8m 4s

Histogram and Scatter Plot in Data Science

7m 42s

Cross Tabulation in Data Science

6m 13s

Charts and Graphs Quiz

Measures of Central Tendency and Variability in Data Science

6m 51s

Mean and Percentiles in Data Science

5m 32s

Quartiles in Data Science

2m 38s

Measures of Variability in Data Science

4m 56s

Variance and Standard Deviation in Data Science

7m 30s

Application of Standard Deviation in Data Science

5m 40s

Z-score and Co-efficient of Variation in Data Science

5m 23s

Measures of Central Tendency Quiz

Measures of Central Tendency for Grouped Data in Data Science

3m 59s

Standard Deviation and Variance for Grouped Data in Data Science

11m 21s

Skewness in Data Science

5m 25s

Kurtosis in Data Science

3m 48s

Box and Whisker Plots in Data Science

3m 45s

Measures of Shapes Quiz

Hypothesis Testing in Data Science

6m 33s

Statistical Hypothesis in Data Science

6m 30s

Errors in Statistical Hypothesis in Data Science

5m 45s

Statistical Inference for Single Population in Data Science

7m 11s

Testing Example in Data Science

5m 27s

Statistical Inference with Two Population in Data Science

8m 33s

R Programming in Data Science

5m 5s

Data Types in R in Data Science

3m 51s

Understanding R Console and R Studio in Data Science

7m 14s

Analysis of Variance and Annova in Data Science

3m 55s

Assumption and Variation in One-Way ANOVA in Data Science

7m 50s

Two way ANOVA in Data Science

7m 48s

Summary of ANOVA in Data Science

3m 11s

ANOVA Quiz

ANOVA example in Data Science

10m 50s

One way ANOVA Example in Data Science

4m 7s

Two way ANOVA Example in Data Science

9m 24s

Understanding Datamining in Data Science

7m 33s

Introduction to Simple Linear Regression and Correlation in Data Science

7m 28s