Dark Mode
Breed Intelligence Comparison Dataset
Data Science and Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset offers an exploration of dog intelligence, specifically comparing it based on breed size. It is derived from research conducted by Stanley Coren, a professor of canine psychology at the University of British Columbia. While his initial analysis in 1994 faced some debate, his work has since achieved wide acceptance. The dataset provides unique insights into canine cognition and breed dimensions.
Columns
- Breed: The specific breed of the dogs considered in the experiment. This column has 150 unique and valid values, with no missing data.
- height_low_inches: The lower limit of the dog's height, measured in inches. All 150 entries are valid, with a mean height of 17.7 inches.
- height_high_inches: The upper limit of the dog's height, measured in inches. All 150 entries are valid, with a mean height of 20.7 inches.
- weight_low_lbs: The lower limit of the dog's weight, measured in pounds. All 150 entries are valid, with a mean weight of 42.4 lbs.
- weight_high_lbs: The upper limit of the dog's weight, measured in pounds. All 150 entries are valid, with a mean weight of 57 lbs.
- reps_lower: The lower limit of the number of repetitions a dog needed to understand new commands. There are 136 valid entries, with 14 (9%) missing values, and a mean of 25.6 repetitions.
- reps_upper: The upper limit of the number of repetitions a dog needed to understand new commands. There are 136 valid entries, with 14 (9%) missing values, and a mean of 41.5 repetitions.
Distribution
The dataset is available in a tabular format, typically as a CSV file (e.g., "Dog Intelligence.csv"), and is approximately 5.31 kB in size. It comprises 7 columns and includes data for 150 unique dog breeds. Most columns contain 150 valid entries, while the 'reps_lower' and 'reps_upper' columns have 136 valid entries each, indicating a small number of missing values for these specific attributes.
Usage
This dataset is ideal for analysing patterns in canine behaviour related to physical characteristics, exploring potential correlations between dog breed size and learning capabilities, and for educational applications in canine psychology or animal behaviour studies.
Coverage
The data is based on research by Stanley Coren, a professor at the University of British Columbia, with his foundational work first published in 1994. The dataset covers 150 distinct dog breeds, focusing on their physical dimensions and learning aptitudes. There are no specific geographic or precise time range details for the data collection itself beyond the reference to the original research.
License
CC0: Public Domain
Who Can Use It
- Researchers and Academics: To conduct studies on canine cognition, breed-specific traits, and the interplay between physical attributes and intelligence.
- Dog Breeders and Trainers: To gain insights into breed-specific learning curves and enhance training strategies.
- Data Scientists and Analysts: For practice in data analysis, classification tasks, and working with animal-related datasets.
- Pet Enthusiasts: To learn more about the intelligence rankings and characteristics of various dog breeds.
Dataset Name Suggestions
- Canine Intelligence by Breed Dimensions
- Dog Breed Learning and Size Data
- Stanley Coren's Dog Cognition Metrics
- Breed Intelligence Comparison Dataset
- Dog Command Repetition Data
Attributes
Original Data Source: Breed Intelligence Comparison Dataset
QUALITY