Simple Linear Reggression Model using Mt cars dataset

Dataset

This dataset was created by Rui Romanini

Released under CC0: Public Domain

Contents

The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973--74 models). The following is a description of the variables:

• mpg: Miles/(US) gallon
• cyl: Number of cylinders
• disp: Displacement (cu.in.)
• hp: Gross horsepower
• drat: Rear axle ratio
• wt: Weight (1000 lbs)
• qsec: 1/4 mile time
• vs: Engine (0 = V-shaped, 1 = straight)
• am: Transmission (0 = automatic, 1 = manual)
• gear: Number of forward gears

Dataset Title: Motor Trend Car Road Tests (mtcars) Description: The data was extracted from the 1974 Motor Trend US magazine and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973–74 models). It is a classic, foundational dataset used extensively in statistics and data science for learning exploratory data analysis, regression modeling, and hypothesis testing.

This dataset is a staple in the R programming language (?mtcars) and is now provided here in a clean CSV format for easy access in Python, Excel, and other data analysis environments.

Acknowledgements: This dataset was originally compiled and made available by the journal Motor Trend in 1974. It has been bundled with the R statistical programming language for decades, serving as an invaluable resource for learners and practitioners alike.

Data Dictionary: Each row represents a different car model. The columns (variables) are as follows:

Column Name Data Type Description model object (String) The name and model of the car. mpg float Miles/(US) gallon. A measure of fuel efficiency. cyl integer Number of cylinders (4, 6, 8). disp float Displacement (cubic inches). Engine size. hp integer Gross horsepower. Engine power. drat float Rear axle ratio. Affects torque and fuel economy. wt float Weight (1000 lbs). Vehicle mass. qsec float 1/4 mile time (seconds). A measure of acceleration. vs binary Engine shape (0 = V-shaped, 1 = Straight). am binary Transmission (0 = Automatic, 1 = Manual). gear integer Number of forward gears (3, 4, 5). carb integer Number of carburetors (1, 2, 3, 4, 6, 8). Key Questions & Potential Use Cases: This dataset is perfect for exploring relationships between a car's specifications and its performance. Some classic analysis questions include:

Fuel Efficiency: What factors are most predictive of a car's miles per gallon (mpg)? Is it engine size (disp), weight (wt), or horsepower (hp)?

Performance: How does transmission type (am) affect acceleration (qsec) and fuel economy (mpg)? Do manual cars perform better?

Classification: Can we accurately predict the number of cylinders (cyl) or the type of engine (vs) based on other car features?

Clustering: Are there natural groupings of cars (e.g., performance cars, economy cars) based on their specifications?

Inspiration: This is one of the most famous datasets in statistics. You can find thousands of examples, tutorials, and analyses using it online. It's an excellent starting point for:

Practicing multiple linear regression and correlation analysis.

Building your first EDA (Exploratory Data Analysis) notebook.

Learning about feature engineering and model interpretation.

Comparing statistical results from R and Python (e.g., statsmodels vs scikit-learn).

File Details: mtcars-parquet.csv: The main dataset file in CSV format.

Number of instances (rows): 32

Number of attributes (columns): 12

Missing Values? No, this is a complete dataset.

Data was extracted from R by typing mtcars on R console

a simulated datasset for benchmarking. Visit https://dataone.org/datasets/sha256%3A495f8ed2e870aae3ffa2ac21191917d0edb56ef4c6618944c7d48a6a50ff1ee9 for complete metadata about this dataset.

Dataset

This dataset was created by kailpraraj

Released under CC0: Public Domain

Contents

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Released under CC0: Public Domain

Contents

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This dataset was created by MANOJS

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This dataset was created by port4siro

Contents

Dataset

This dataset was created by Masoumeh Akhavan

Released under CC0: Public Domain

Contents

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Dataset

This dataset was created by Harika

Released under CC0: Public Domain

Contents

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How to successfully connect a dataset to its code project on short notice, is needing more time to solve. Useability of this college owned dataset uploaded is not something I as a student are intending, when or if other users in Kaggle network or beyond choose to navigate and explore at this time. This upload and code attempt has been created to solve a 'dead kernel' experience due vm timing in a different coding platform. AC2975422 1-12-2025.

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