Data Science Course > Regression Analysis and Correlation

Residual Analysis of Model Part 3 in Data Science

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The observed responses are subtracted from the projected responses to yield residuals, which are estimates of experimental error. After all of the unknown model parameters have been determined from the experimental data, the anticipated response is calculated using the chosen model.

The 'delta' between the actual target value and the fitted value is the residual in machine learning. In regression issues, residual is a significant notion. It is the foundation of all regression metrics, including mean squared error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE).

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  2. How to use LearnVern
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  1. Introduction to Data Measurement in Data Science
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  2. Types of Variables in Data Science
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  3. Levels of Data Measurement in Data Science
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  1. Charts and Graphs in Data Science
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  2. Frequency Distribution in Data Science
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  3. Bar Graphs and Pie Charts in Data Science
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  4. Summarizing Quantitative Data in Data Science
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  5. Cummulative Distribution in Data science
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  6. Histogram and Scatter Plot in Data Science
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  7. Cross Tabulation in Data Science
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  1. Measures of Central Tendency and Variability in Data Science
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  2. Mean and Percentiles in Data Science
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  3. Quartiles in Data Science
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  4. Measures of Variability in Data Science
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  5. Variance and Standard Deviation in Data Science
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  6. Application of Standard Deviation in Data Science
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  7. Z-score and Co-efficient of Variation in Data Science
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  2. Kurtosis in Data Science
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  3. Errors in Statistical Hypothesis in Data Science
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  5. Testing Example in Data Science
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  6. Statistical Inference with Two Population in Data Science
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  7. Residual Analysis of Model Part 2 in Data Science
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  8. Residual Analysis of Model Part 3 in Data Science
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  5. Example of K Means Clustering in Data Science
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  1. Theoretical Concepts of Dashboard
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  2. Creating Pivots and Preparing Charts
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  3. Slicers in Dashboard
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  4. Preparing Final Dashboard
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  5. Presenting Dashboard
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