Data Science Course > Regression Analysis and Correlation

Introduction to Simple Linear Regression and Correlation in Data Science

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A correlation analysis determines the strength and direction of a linear relationship between two variables, whereas a simple linear regression analysis calculates parameters in a linear equation that may be used to forecast the values of one variable based on the values of the other. Correlation.

Only one independent variable is present in simple linear regression, and the model must identify a linear relationship between it and the dependent variable. Multiple Linear Regression, on the other hand, uses more than one independent variable to find a relationship.

To model the relationship between two continuous variables, simple linear regression is utilised. The goal is frequently to anticipate the value of an output variable (or responder) based on the value of an input variable (or predictor).

In a nutshell, linear regression is a useful supervised machine learning approach for modelling linear connections between two variables. Simple linear regression is a nice place to start when looking at our data and considering how to develop more complex models.

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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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  2. Statistical Hypothesis in Data Science
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  3. Errors in Statistical Hypothesis in Data Science
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  4. Statistical Inference for Single Population 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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  1. R Programming in Data Science
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  6. One way ANOVA Example in Data Science
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  7. Two way ANOVA Example in Data Science
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  1. Understanding Datamining in Data Science
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  1. Introduction to Simple Linear Regression and Correlation in Data Science
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  2. Least Square and Residual Analysis in Data Science
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  4. Hypothesis and Co-Efficient of Determination 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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