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Principles of Data Science

Group Project

Principles of Data ScienceGroup Project

Group Project

Project A: Confidence Intervals

Conduct a survey of students in your class or at your school to collect data on the number of hours worked per week by one or two predefined sociodemographic characteristics, such as gender, age, geographic neighborhood of residence, first-generation college student, etc. As a group, create 90% confidence intervals for the average number of hours worked for each category of students. Compare the confidence intervals and come to any relevant conclusions for the average number of hours worked by each category of students.

Project B: Hypothesis Testing

As a group, develop a hypothesis for the proportion of white cars in your city. To collect sample data, go to your school parking lot or a nearby parking lot of some kind and determine the sample proportion of white cars. Then, use this data to conduct a hypothesis test for your original hypothesis.

Project C: Correlation and Regression Analysis

For each student, collect data on shoe length and person’s height. Create a scatterplot of this (x,y)(x,y) data and calculate the correlation coefficient. Test the correlation coefficient for significance. If the correlation is significant, develop a linear regression model to predict a person’s height based on shoe length.

As a second assignment on the same subject, students should research a certain model car, such as Honda Accord or Toyota Camry. Search websites for used car prices for the selected model and record (x,y)(x,y) data where xx is the age of the car and yy is the price of the car. Create a scatterplot of this (x,y)(x,y) data and calculate the correlation coefficient. Test the correlation coefficient for significance. If the correlation is significant, develop a linear regression model to predict a car’s price based on age of the vehicle.

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