# ### Data Science Simplified Part 9: Interactions and Limitations of Regression Models

In the last few blog posts of this series discussed regression models at length. Fernando has built a multivariate regression model. The model takes the following shape:

price = -55089.98 + 87.34 engineSize +…
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### Data Science Simplified Part 8: Qualitative Variables in Regression Models

The last few blog posts of this series discussed regression models. Fernando has selected the best model. He has built a multivariate regression model. The model takes the following shape:

price = -55089.98 + 87.34 engineSize + 60.93…

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### Data Science Simplified Part 7: Log-Log Regression Models

In the last few blog posts of this series, we discussed simple linear regression model. We discussed multivariate regression model and methods for selecting the right model.

Fernando has now created a better model.…

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### Data Science Simplified Part 5: Multivariate Regression Models

In the last article of this series, we discussed the story of Fernando. A data scientist who wants to buy a car. He uses Simple Linear Regression model to estimate the price of the car.… Continue

Added by Pradeep Menon on August 6, 2017 at 5:30am — 1 Comment

### Data Science Simplified Part 4: Simple Linear Regression Models

In the previous posts of this series, we discussed the concepts of statistical learning and hypothesis testing. In this article, we dive into linear regression models.

Before we dive in, let us recall some important aspects of statistical learning.

Independent and Dependent…

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### Data Science Simplified Part 3: Hypothesis Testing

Edward Teller, the famous Hungarian-American physicist, once quoted:

“A fact is a simple statement that everyone believes. It is innocent, unless found guilty. A hypothesis is a novel suggestion that no one wants to believe. It is guilty, until…
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